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Abstract—This paper introduces a new method for resistance identification in the HVAC distribution network based on a novel collective intelligence system. The proposed method implements the identification process by solving the basic energy and flow balance functions and exchanging information between neighboring nodes. The identification results are presented and the non-uniqueness problem is investigated. The necessary conditions to secure a unique solution are studied and the potential of using the proposed method for fault diagnosis of the HVAC system is discussed.
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Abstract—With the rapid development of economy and society, all walks of life have put forward higher requirements for the reliability of power supply. In this paper, we summarize the existing three types of no-blackout operation, introduce their working principle, and comprehensively introduce their design scheme, operation process and evaluation index through an application case. At the end, we propose an intelligent live operation system for distribution network based on virtual reality technology. Theoretically, this system can improve the configuration of distribution network equipment adapted to a variety of operating environments and improve the level of automation, intelligence and informatization of operating equipment through the research and development of diversified non-power outage operating equipment.
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Abstract—In addition to the target echo, the signal environment of the secondary surveillance radar (SSR) also includes environmental echo and noise interference, which greatly affect the correct decoding of the response signal. Nowadays, the processing of secondary radar response signals basically uses traditional signal processing methods, and there are few methods for denoising using deep learning neural networks. This paper proposes a secondary radar signal processing method based on the deep residual separable neural network (DRS-Net), which can effectively extract the deep features of the secondary radar signal and predict the original response signal. The core of the network is based on the deep separable convolutional neural network, and the deep residual connection structure can effectively learn the deep features of the signal. We conducted a lot of experiments and verifications using secondary radar response signals with different signal-to-noise ratio noise. The experimental results show that the method has high denoising performance in the normal radar operating environment and can accurately predict secondary radar response signals. When the signal-to-noise ratio is 5dB, the strict accuracy rate can reach 94%. When the signal-to-noise ratio is higher than 10dB, the strict accuracy rate has reached 99.95%.
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Abstract—As of non-intrusive load monitoring (NILM) in demand-side response, the main problem is that there are too many differences in power characteristics refer to the different types of electrical devices. This paper proposes an algorithm that can run on inexpensive and energy-efficient embedded system. A smart meter solution is designed to integrate the embedded system together with the meter in offshore oil platform power system. All the data is processed in the embedded system. It can distinguish the behavior of electrical appliances, providing a data foundation for demand-side response.
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Abstract—Aiming at the basic issues of huge energy consumption and operator costs derived from the wide usage of datacenters, this paper focused on the key technologies based on underutilized energy storage devices (ESDs)deployed inside the datacenters to participate in the regulation of its own power. The research progress and recent results of studies on datacenters using energy storage devices to adjust the power consumption were summarized, by classifying and analyzing the characteristics of different types of energy storage devices. Also, from the perspective of the models and algorithms of smart grid demand response, we also discussed about the approaches used in datacenters for participating the demand response programs in the smart grid leveraging the advantages of ESDs. Finally, the prospects of possible future research directions were discussed.
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Abstract—In this paper, a novel hybrid modular multilevel converter (MMC) with reduced capacitor voltage fluctuation is proposed. Compared with traditional MMC based on flyingcapacitor submodules (FC-SMs), it replaces the top and bottom FC-SMs with the three-level flying-capacitor converter, and inserts a full-bridge submodule in the ac side. The operating principle and capacitor voltage fluctuation suppression method of hybrid MMC are analyzed in detail, which shows that the hybrid MMC can suppress the voltage fluctuation and eliminate the influence of injecting high-frequency components. Moreover, considering the feature of FC-SM, a novel hybrid capacitor voltage control is proposed, which can reduce the number of PI controllers and sorting complexity. Finally, the accuracy of the proposed topology and corresponding control design is confirmed by simulation results.
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Abstract— With rapidly use of energy internet, more and more research focus on microgrid with hybrid renewable energy in recent decades. In this paper, research of virtual synchronous machine (VSM) control strategy of hybrid renewable energy in DC microgrid is put forward. Mode and topology of key devices are given, a virtual governor and a virtual excitation regulator are also designed to make sure that the grid control center can dispatch microgrid with the same way as dispatching synchronous machines. At the end, a simulation model of VSM control strategy of hybrid renewable energy in DC microgrid is created in Simulink platform, the site operation results shown the high performance of the designed VSM control strategy.
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Abstract—In this paper, a hybrid MMC with reduced number of components is proposed. Compared with the traditional MMC and the existing similar MMCs, the proposed hybrid MMC has following advantages. The number of components is fewer. And the voltage ripples of SM capacitors are lower, which can reduce the requirement of capacitance. Therefore, when the voltage stress of components and the number of output voltage level are same, the size, weight and cost of proposed hybrid MMC are reduced. The principle is analyzed. The component count and voltage ripple are compared with other MMCs in detail to visualize its advantages. Phase shift carrier pulse width modulation is used and the controllers of voltage balance is designed. All abovementioned analyses and advantages of proposed hybrid MMC are verified by the results of simulation.
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Abstract—On-line partial discharge detection is an important method for operation status evaluation of high voltage cable. Affected by propagation characteristics of partial discharge and external interference signals, it may be difficult for field testing personnel to determine suspected partial discharge. Taking advantage of the irreversibility of solid insulation defects, this paper proposes to utilize intensive care technique to track suspected partial discharge signals detected by live detection, and observe long-term accumulation of discharge spectrum. Combined with an effective case of partial discharge monitoring for high voltage cable, the application effect of intensive care system is introduced. The intensive care technique is an important supplementary means to diagnose partial discharge in high voltage cable, which can ensure safe and stable operation of high voltage cable.
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Abstract—Competitive team sports are one of the most informative scenarios in the research of team cooperation analysis. However, there is a lack of simple, robust and accurate key event-based methods when evaluating the performance of a soccer team. In this paper, we first built a ball-passing network to facilitate teamwork analysis of a soccer team, with the help of which we then proposed a novel model for quality assessment based on highlight moments to evaluate the performance of the team. Further, we develop a third model to identify the rhythm conversion of offensive/defensive tactics so as to quantify them. Using spatiotemporal tracking data of key events in 38 Premier League games, a comprehensive and systematic analysis is formed on the performance of both the team staff and players of the Everton Football Club. Also, the key factors to the match result are quantitatively explored and modeled.
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Abstract—The temperature field of transformer bushings is one of the important problems to be considered in bushings design. It is of great significance to analyze the temperature field of casing for evaluating the operation state of bushings. In this paper, the heat loss of the bushings has been calculated based on the structure of 1000 kV oil paper capacitor bushings. And a simplified two-dimensional model of the UHV bushings was constructed. After setting reasonable boundary conditions, the temperature field of the two-dimensional model was calculated and analyzed. Finally, the temperature distribution diagram of UHV bushings was calculated by simulation, and the temperature distribution rule and its influencing factors also have been analyzed. The results can provide important references for the design and operation of UHV Transformer Bushings.
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Abstract—Drugs may have multiple drug targets, and the most of targets are composed of different proteins. Therefore, the study of drug-target interaction (DTI) prediction has important meaning in drug repositioning, drug development time shortening and the cost of drug research and development reducing. Most of the existing methods are based on shallow learning model. The prediction accuracy is not high. In this paper, we proposed a deep belief network-based DTI prediction algorithm: we extracted extended connected fingerprint of the drug from the molecular structure. And then, we extracted the structure characteristics of the three peptide of the protein from the amino acid sequence of the protein. At last, we train the deep belief network by the characteristic vector extracted from drugs and proteins. In our proposed method, we fully use of the characteristics in the deep learning network and integrate the empirical feature selection into the deep belief network. Base on the public data set and compared with the state-of-the-art approaches, the experimental results show that our method outperforms the other algorithms in massive data sets.
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Abstract—With the continuous development of society, electrical energy is an important energy source for human life. Therefore, it is of great significance to discuss and study the ways for electric power companies to reduce losses and increase efficiency to promote the development of the power industry, the development of the social economy, and improve the utilization rate of electrical energy. The large amount of data accumulated by electric power companies for a long time provides a data basis for the analysis of corporate loss reduction and efficiency increase. Aiming at the technology of loss reduction and efficiency increase, the power consumption monitoring model and abnormal line loss analysis model in the station area are proposed in this paper based on the data association in the "perception layer" and big data analysis in the "application layer" of Ubiquitous Power Internet of Things to effectively carry out the research of multidimensional design ideas of loss reduction and efficiency increase.
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Abstract—As an important switchgear in the power system, the ring network cabinet is of great importance to the safe and reliable operation of the power system. Among all the faults of the ring network cabinet, the faults caused by the mechanical characteristics account for a large proportion, so the online monitoring of the mechanical characteristics of the ring network cabinet is an important prerequisite to improve the stable operation of the power system. This paper analyzes the hardware and software aspects of the on-line monitoring system of the ring network cabinet's mechanical characteristics. Through the transformation of the operating mechanism structure, the encoder is used to monitor the travel-time of the ring main unit, and the contact travel, contact opening distance, contact over-travel, average opening speed and Characteristic parameters such as average closing speed, opening and closing time, etc .; CAN bus system completes data upload, realizes communication with upper computer, and can realize the function of remote communication. The test shows that the error measured by the online monitoring system designed in this paper is within the allowable range, which can fully meet the requirements of online monitoring and fault early warning of ring network cabinets, and has strong enforceability.
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Abstract—In order to ensure the safe and stable operation of the power supply system, an online fault detection method based on local features of data is proposed for the loop network cabinet data modeling and online monitoring. Using the strategy of local feature extraction based on neighborhood preserving embedding (NPE) algorithm, real-time data features are obtained through multiple measurement variable information and environment variable information of ring network cabinet, and a fault detection model of ring network cabinet based on data features is constructed. The constructed NPE model is applied to the on-line detection of real ring network cabinet, and the original data space is divided into irrelevant feature space and data residual space. According to these two spaces, the monitoring statistics of Hotelling T 2 and the sum of the squared prediction errors (SPE) are constructed respectively, and based on these two monitoring statistics, the online real-time monitoring and fault alarm of ring network cabinet are realized. This method is applied to the fault detection of ring network cabinet, and the test results prove the effectiveness of this method in fault detection of ring network cabinet.
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Abstract—Robot is a hot topic in modern research. To meet the requirements of large power, high energy, large load and high speed, hydraulic driven manipulator is a priority. However, the micro deformation of manipulator under large load cannot be ignored. Therefore, dynamic modeling and control of large load manipulator are studied in this paper. Firstly, the force of large load manipulator is analyzed, and a reasonable mode is selected for the kinematic analysis of the deformation of the large load manipulator. Considering the damping factor, the dynamic model of large load manipulator is constructed by using the Lagrange method. Then, the coupling dynamic system of the manipulator is decomposed into two subsystems by using the small parameter perturbation method, and the complex control of large load manipulator system is carried out by using the inversion sliding mode control and LQR respectively. Finally, the effectiveness of the modeling and the feasibility of the control system are verified by simulation. It is of great significance for the theoretical research and control of hydraulic flexible manipulator.
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Abstract—Because the containers share the operating system kernel of the host, the performance interference, that is, the performance isolation problem will occur between the containers due to the resource competition. This paper defines the I/O isolation of container system from the perspective of SLA of I/O service, analyzes the I/O evaluation index and queue model of container system, collects the change trend of I/O performance index of container system through experiments, analyzes the quantitative relationship between the indexes, and the impact of overloaded container on the overall I/O performance of container system. Based on this analysis, this paper proposes an algorithm and designs a logic model to improve the isolation of I/O performance of the container system by dynamically adjusting the intensity of I/O load of the overload container, and verifies the feasibility of the algorithm through a simple experiment.
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Abstract—The wisdom classroom full of immersion experience could create an excellent sense of learning experience for learners to improve their learning effect, and the level of learning immersion has become one of the indicators to assess students’ learning state. However, the traditional way to evaluate learning immersion is greatly influenced by the subjective factors of individuals. This study proposes a novel method to assess learning immersion based on physiological characteristics: by constructing two learning scenes with different immersion senses: VR video watching (for high immersion) and normal document reading (for low immersion) to induce immersion. During the learning process, the subjects' PPG signals and EEG signals were collected for later preprocessing and extracting. By entering different compositions of feature vectors to train SVM classifier model and comparing their prediction accuracy and training time, the results show that the most suitable feature vectors to assess learning immersion are: pulse rate, the ratio of attention score and relaxation score, high alpha wave of EEG. The precision of the model reaches 88.93%.
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Abstract—In this paper, a planned maintenance cycle model with the lowest maintenance costs is established to ensure the reliability and operating status of medical X-ray diagnostic equipment. The proposed method is obtained based on the reliability analysis and fault characteristics of medical X-ray diagnostic equipment. In view of the feature of medical X-ray diagnostic equipment that was susceptible to environmental changes, we find out the relationship between the change law of the equipment operating state and the condition monitoring feature quantity by using equipment condition monitoring data. A Proportional Hazard Model (PHM) state maintenance decision model based on Weibull proportional risk model is given, and case analyses of the two models are performed separately. The results of the case analyses show that these two models can effectively improve and ensure the reliability and operating status of the equipment, thereby further promoting the current maintenance level of medical X-ray diagnostic equipment.
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Abstract—Based on data management system, the dynamic simulation system of multidimensional reservoirs accomplishes research on reservoir fine description result managements, 3D model visualization and reservoir numerical simulation. In addition, it offers technical support for multidimensional linkage visualization, intelligent management and reservoir dynamic modeling and provides new technologies on the applications of fine reservoir description and technical support for stimulation measures.
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Abstract—Oilfield companies have carried out tremendous research on fine reservoir description and managed a large number of basic data and reservoir model. However, study on further application of dynamic data, static data and reservoir model is still insufficient. Based on the accumulated work, we intend to build the Resource Management System of Multidimensional Reservoir Simulation to realize the further application of reservoir description resources. The resource management system could provide visualization application environment for 3D model, realize process data monitoring and inspection and improve the reliability and application rate of research results. It could realize reservoir research and dynamic prediction based on three-dimensional reservoir model in order to provide basis for designing development plan and optimization measure, enhancing oil recovery, reducing costs and increasing oilfield development efficiency.
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Abstract—A microgrid is defined as a group of interconnected loads and distributed energy resources, that the electrical loads fluctuate with respect to the grid. When focusing on load anomaly in microgrid, different from the traditional centralized grid (macrogrid), a method of microgrid anomaly detection based on the extreme studentized deviate(ESD) test, is proposed as GLAD (grid load anomaly detection). GLAD under the enhanced ESD is adapted to solve this problem properly, using the detect_ts function of PyCuliarity library to carry out anomaly detection simulation experiment in Python software, according to a series of statistical analysis. In the paper, the existing time series and anomaly detection methods are firstly analyzed and summarized, then GLAD are designed to detect the grid load variations. Some conventional anomaly detection methods are also discussed for higher efficiency of GLAD. Moreover, there are still better methods for anomaly detection of microgrid, Finally, GLAD with machine learning modeling is discussed for the future smartgrids of anomaly detection in distributed energy resources.
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Abstract—During nuclear power maintenance, the primary main pipe blocking plate needs to be put into the manhole of steam generator water chamber to complete the blocking plate operation. In view of the limitation of the space condition of the working site in the steam generator, this paper designs a six degree of freedom robot with a hybrid of moving and rotating joints. In order to meet the needs of blocking operation, the joint types and driving system of the robot are designed and calculated. According to the robot configuration, the kinematics model of the robot is established and the forward and inverse kinematics are solved. Matlab is used to simulate the trajectory planning of the manipulator in order to determine the motion state of each axis and provide theoretical support for practical application.
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Abstract—Smoke is an important omen in the early stage of forest fire disaster. However, due to the complexity of outdoor scene, current video-based smoke detection methods are prone to cause false alarms. Aiming on this situation, in order to realize robust real-time forest smoke detection in outdoor scene, a novel method based on deep learning and dynamic background modeling is proposed to suppress false alarm. Firstly, the Single Shot MultiBox Detector (SSD) deep learning network was selected for the preliminary smoke detection. Secondly, taking into account the motion characteristics of the smoke, ViBe dynamic background modeling technology was used to obtain the dynamic region in the video. Thirdly, dynamic region was used to reduce the false alarms of the preliminary smoke detection results. Through massive experiment on various forest real scenes, the accuracy was improved by 30% relative to the method of single SSD, which verified the effectiveness of the method in this paper.
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Abstract—In order to support the stable and efficient operation of power wireless heterogeneous network, the power wireless heterogeneous network management system based on big data technology is proposed. The system includes four modules: heterogeneous data acquisition module, resource management module, monitoring alarm module, and decision support module. An improved big data association rule mining algorithm which named the SG-DLYGApriori algorithm is proposed. Based on the traditional Apriori algorithm, the improved algorithm simplifies the calculation of support and reduces the number of times to read the database by constructing the support calculation support array, and improves the efficiency of data analysis in heterogeneous power networks.
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Abstract—When a ground fault occurs in the distribution network, it will cause a large-scale and long-term power outage on the entire line, which will have a significant impact on the safe and stable operation of the power system. In order to improve the real-time and accuracy of online monitoring of distribution network ground faults, a suitable ground fault monitoring method based on the phase difference detection on transmission lines is proposed. The way we detect the occurrence of ground faults is as follows: we first measure the three-phase voltage, current, and difference of their phase on the transmission line, and then we use the sudden changes of the phase difference between voltage and current as our criterion to determine whether ground faults occur or not. In order to search ground faults rapidly on the entire transmission line, it is necessary to install measurement devices at important nodes. According to the comparison of simulation tests, we find that the ground fault location judgment method based on the phase difference can detect the ground faults accurately, which is of great significance to guarantee the safety of the power supply.
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Abstract—As the main equipment for petroleum and petrochemical raw materials and products storage, storage tanks are widely used in petroleum and petrochemical companies. The safe operation of storage tank is the precondition of normal production. The tank bottom is the highest risk for it is always used under the composite medium, some of them is very corrosive and often causing tank bottom failure. For the tank bottom belongs to the concealed work which always runs under the corrosive composite medium circumstance, and the bottom defect couldn’t find by daily inspection. So, the newly developed acoustic emission detection technology is emerging, which has advantages of online detection and avoiding the expense and risk of opening the tank. But the acoustic emission detection has disadvantages of give qualitative results, which couldn’t give the accurate remaining thickness of the tank bottom, so the magnetic flux leakage detection is developed which can give the quantitative results. These two methods have their own merits and demerits, so the two methods are often used together in the practice. Recently, our institute in accordance with the requirements of the group company safety and environmental protection department to carry out a large number of acoustic emission testing work online in order to avoid the tank perforation, two hundred tanks of DAQING oil field, LIAOHE oil field and other oilfield belong to CNPC were tested by acoustic emission detection technology and forty tanks of these tanks were testified by magnetic flux leakage detection technology when opening the tanks. The results show that the two detection methods can reflect the corrosion of the bottom of the tank well, and can provide decision support for the daily management and maintenance of the tank.
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Abstract—The dangers caused by fires are very great, causing property damage, casualties and environmental damage. Rapid detection of fire hazards and prompt response measures are the best means to reduce the damage caused by fire. The distributed plant fire alarm system can quickly detect the fire and issue an alarm to reduce the damage caused by the fire. The fire alarm system is a control system that integrates signal detection, transmission, processing and control. It mainly completes the basic functions of fire, smoke and temperature module monitoring fire, and studies the multi-point communication of nRF2401 wireless transceiver module to realize the function of transmitting data at multiple points simultaneously. Qt is used to create a back-end system and operation interface to write user and monitoring information to the database.
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Abstract—In recent years, the technology of industrial and agricultural generation driven by information technology is developing vigorously. The design and research of distributed temperature and humidity monitoring system is immeasurable for the impact and promotion of tertiary industry, agriculture and industry. It is the general trend of modern prosperity and future development. It is self-evident that it is of great significance to occupy the supreme prestige and level of international advanced science and technology strategy, especially for the development of economy and the improvement of industrial automation.
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Abstract—The crime is a complex social problem, and it is caused by many factors such as population factors, political factors, economic factors, social factors, cultural factors, and ecological factors. But how and to what extent the factors impact crime, is determined by industry experts according to their experience most of the time. It is probably to bring the risk of subjective experience, and it is difficult to figure out the effect of the objective factors from the quantitative point of view. Another problem is that the feature dimension is too high when choosing multi-factors indicators by experience, and it results in inefficient operation because of insignificant factors doped. This paper is devoted to solving the above two problems, and proposing a bagging method based on the principle of "good and different". Heterogeneous learners are used to construct an integrated learning device to identify the impact of the occurrence factors, then improve the efficiency and accuracy of crime prediction with less dimension of factors. The experimental results show that the EFV_Bagging algorithm proposed in this paper has better generalization ability and stability, and the prediction accuracy on the test sample also has a better performance than other algorithms. In addition, the algorithm does not need a priori knowledge to manually set the selected feature subset dimension, which has obvious advantages in the application field of criminal data analysis and forecasting.
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Abstract—Kiln is the structure and site to fire and produce ceramic. The property of kiln is mainly divided into civil kiln and official kiln. The property of Luochong Kiln, which is located in the western suburb of Fanchang County, has so far been uncertain. We put forward a method of FP-growth mining to identify the property of Luochong Kiln. We discriminate by comparing Luochong Kiln and Kechong Kiln, both belong to the important parts of Fanchang Kiln, to determine whether there is a difference between the frequent items. Through launching Top-k expert questionnaire and analyzing 100 experts’ discriminant results of the frequent items, we conclude that Luochong Kiln is official kiln.
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Abstract—Deep neural networks are vulnerable to the adversarial example. So far, the primary way of generating the adversarial example is comparing the success rates of the adversarial attack. However, the distance between the made example and the original example is also an essential indicator. In this paper, it is demonstrated that the optimization algorithm could reduce the perturbation of adversarial example generated by using the extremum loss function to obtain the perturbation. This paper introduces the OPA optimization algorithm and uses it to find the best advantage on the model decision boundary as the adversarial example. This paper tests four attack methods FGSM, BIM, MI-FGSM and C&W, and measures the perturbation between the original sample and the generats sample by the Euclidean distance. And it is found that the noise of the sample image is significantly reduced by OPA optimization. It should be set in 12-point font size.
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Abstract—The bioinformatics features are collected by pattern recognition technology, and the digital coding and format conversion of the feature data are realized by using the theory of topological group transformation. Authentication and Signature based on Zero Knowledge Proof Technology can be used as the trusted credentials of cloud platform and cannot be forged, thus realizing trusted and secure access.
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Abstract—The main components in the study of multi-agent systems in the field of IoT are intelligent agents and contexts. From the viewpoint of each agent, the primary objective is to choose actions that maximize the agent's future utility. The choice of a correct action depends on a process of complex data collection from context. Using a neuroscience model, we consider the receptive field to slice the context area and to group the appropriate sensors. To permit the phenomenological analysis and consequent cognitive evaluation, we have applied Bellmund and Doeller’s model of hippocampus identifying two types of cells: the map cells and the grid cells. The first linked to the positional aspects and the second to cognitive aspects. This paper describes only the phenomenological layer architecture. From a scientific point of view there is a novel fusion between fluent calculus and neural network ensemble. Such net is used to associate to situations’ fluent the appropriate schema of actions.
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Abstract—In view of the common occurrence of potential accidents in iron and steel industry at present, but only post-accident analysis of production accidents, according to the analysis of production environment, data communication and data traceability requirements of production site, a pre-defined accident information is proposed to alert production site accidents, and the pre-defined accident information can self-improve the accident early warning analysis framework after confirming the architecture, event flow, data acquisition, acousto-optic control and data real-time are studied in depth, which makes the accident early warning analysis architecture modular, visual, scalable, robust and real-time, and effectively prevent or reduce accidents. Through the early warning information of the acousto-optic device, the production site takes timely preventive measures to effectively eliminate and optimize the hidden danger of the accident, realize the early warning of the accident, solve the problem that the accident is only analyzed after the event, which is of great significance to the reduction of the accident rate, the improvement of the production efficiency and the improvement of the intelligent production.
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Abstract—With the development and progress of society, the same new things come into being, but also bring about the emergence of new culture. But it is precisely because of the emergence of new culture that the traditional national culture in China has been impacted, and as the most influential musical instrument culture, it is the first one to bear the brunt. Gradually national music culture began to disappear or become intangible cultural heritage. So, in order to change this situation, we use the most popular dual computer communication and virtual instrument and human-computer interaction technology to protect and inherit the musical instruments carrying the music culture. Through the technology of human-computer interaction and 3D modeling, the virtual musical instrument library is established on the web side, and the transmission equipment integrated with the data transmission module in the dual computer communication is used for data interaction to control the virtual musical instrument for performance. This will take off the hat of national music and culture intangible cultural heritage, and even change the status quo of all traditional cultures under threat of intangible cultural heritage. This paper first describes the research background and the development status of various technologies, and expounds the design ideas, design feasibility and so on.
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Abstract—In recent years, the scale of Internet data grows exponentially with the development of Internet technology. Such huge amount of Internet data is valuable. Web crawler is one of the most popular technology, which is often used to obtain these data. Scrapy is a popular framework of web crawler which is widely used in various Internet information collection systems. This paper optimizes the framework of Scrapy, designs a firmware data acquisition system based on the framework of Scrapy based on the technologies of distributed, anti-crawler, ELK and automatic construction, and crawls the firmware information of various manufacturers on the Internet. The experimental results show that after employing the distributed and prevent anti-crawler technology, the number of target acquisition increases by 10%, and the time is shortened by 70%. The large-scale logs analysis using ELK solves the problem that the log number is too large for analysis, and the crawler can be automatically constructed and crawls through the code automatic construction technology. This method is efficient for the optimization of firmware crawler.
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Abstract—Bridge health monitoring is not only a new technology for traditional bridge detection and structural assessment, but also given the significance of structural monitoring and evaluation, design verification and research and development. The basic data acquisition method is to use the high-precision non-destructive sensing technology in the field to analyze the structural system characteristics including structural response, and achieve the functions of structural monitoring and evaluation, design verification and research and development. However, the sensor faces the challenge of being calibrated as the use time is lengthened during use. It is especially difficult to evaluate the uncertainty in the field calibration process. This paper analyzes the bridge in the construction stage by numerical simulation combined with statistical algorithm analysis, and adopts two methods to reduce the error of numerical simulation. It is fitted with the actual monitoring data, and this method is used to compare and analyze the field monitoring data. It provides theoretical support for the uncertainty assessment of the field calibration process.
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Abstract—According to the current development situation, cloud computing technology will still have great development and progress space in the future, which will also further enhance the overall demand for IPv6 address resources. At the same time, users on this basis will gradually become IPv6 network users, but the previous use of IPv4 and IPv6 cannot be directly interoperable, so it will inevitably narrow its audience. In addition, the limitation of the number of IP addresses themselves and the problem of internal and external network transformation will also reduce the overall computing power of cloud computing platform. Based on this, this paper starts with the analysis of the structure and key technologies of cloud computing platform under the requirements of IPv6, and puts forward corresponding strategies on how to build a new cloud computing platform under IPv6.
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Abstract—The research and development of innovation project analysis system is particularly urgent in the perspective of big data fusion. This paper focuses on the direction and key technologies of system development and design, construction methods, system structure charts, and the technical route and significance of system research and development. In order to establish an analysis system that can provide entrepreneurs with various kinds of information reference and analysis services, we enhance the overall control ability of innovative entrepreneurship projects and enhance the possibility of entrepreneurial success.
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Abstract—With the increasing urban population and vehicles, the urban traffic problem has become increasingly prominent. The traditional traffic management mode has been unable to meet the traffic management needs under the new situation. Traffic management system based on big data includes data acquisition, data transmission, data cleaning and storage, data processing and display and output. It has become an effective tool for urban traffic control in the field of traffic congestion control, chaos control, risk management and law enforcement supervision.
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Abstract—An empirical mode decomposition (EMD) denoising method based on principal component analysis (PCA) is proposed for the denoising of nonlinear and non-stationary signals. Based on the decomposition characteristics of EMD, PCA is used to remove the noise in intrinsic mode function (IMF) decomposed by EMD nonlinear and non-stationary signals. Firstly, detailed information of the first IMF layer is extracted by using the "three rules", and the energy of noise in each IMF layer is estimated. Then the IMF is transformed by PCA and the appropriate number of principal components are selected to be reconstructed according to noise energy in IMF layers so as to remove the noise.
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Abstract—In order to improve the quality of the traditional exam management system test paper generation, joining the genetic algorithm of simulated annealing algorithm is put forward, and study at last on the automatic group volume algorithm update the topic the difficulty coefficient. By analyzing the simulation results, the algorithm can improve the efficiency and quality of the volume.
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Abstract—The system under OpenCV environment was studied to realize the localization and ranging of forest fire sources effectively. The forest fire was identified by using the solar-blind ultraviolet-infrared binocular detector, and a gyroscope measured the azimuth. With the switching function of the binocular sensor, the ranging binocular part of the system can be activated. The equipment that has completed camera calibration and binocular image correction uses the SGBM algorithm to perform binocular matching and obtain a disparity map. Then the three-dimensional transformation of coordinates can be completed to get the ranging result under the OpenCV environment. The system adopts ultraviolet sun-blind imaging monitoring technology to eliminate the interference of sunlight and utilizes SGBM algorithm, which has the advantages of fast processing speed and distinct processing effect. The obtained parallax map provides a reliable basis for binocular ranging; thus, it has a minor error. This system has realized the binocular forest fire source localization and ranging, with advantages of self-sensing, self-identification, self-triggering, so it has a great automatic extent. It has advanced significantly in the forest fire location and range.
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Abstract—In order to solve the problems of tedious workflow and difficult communication in traditional student work, this paper proposes a design scheme of student assistant system based on Spring MVC framework with reference to old version. The system interface is simple and easy to operate and concurrently controlled.
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Abstract—It is considered that Electronic Votes is an alternative of safer systems, which provides greater confidence and transparency to the general public, but the problems exist in the organisms that manage this process. The main objective is to describe the Homomorphic encryption, understand why this algorithm is the basis for different schemes mentioned in the document. There are several implementations of homomorphic properties that generate the possibility to continue analyzing the different encryption schemes and application areas as visualized in electronic voting. We use the deductive methodology, logical analytics, and exploratory research to analyze the description of three schemes that have a Homomorphic base. It is a basis for properly selecting a homomorphic scheme that fits a specific need. It is concluded that the homomorphic schemes presented in this analysis have different uses of algorithms, but they do not leave behind the efficiency that all present, at the same time the reference is made to a distributed architecture that helps to have an additional point when dealing with the information obtained in electoral.
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Abstract—We analyze several alternatives of blind digital signatures, for an electronic electoral system in a distributed architecture environment, in view of the persistence of blind signature problems in electoral processes. The objective is to recognize and propose an alternative of a blind signature scheme to improve privacy, confidentiality for the voter and in this way reduce any type of vulnerability with respect to the information of the same. The deductive method is used to summarize the information of the scientific articles studied. It results in a blind signature prototype based on algorithms to mitigate the vulnerabilities of voter information. It is concluded that, in order to guarantee privacy and confidentiality, several blind signature schemes must be implemented together to obtain the benefits of each of them, thus reducing the risks to which the voter's information is exposed in this process.
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Abstract—Time series outlier detection is an important topic in data mining, having significant applications in reality. Due to the complexity and dynamics of time series, it is quite difficult to detect outlier in time series. Particularly, influenced by outside factors, time series are usually unpredictable, accompanied with concept drift. Recently, recurrent neural network has been used to identify time series outlier, and demonstrated great potential. However, RNN usually uses deterministic state transition structure, which cannot characterize the variability of high-dimensional time series. This paper proposes to incorporate latent variables into RNN, aiming to catch the time series variability as much as possible. In particular, our method combines RNN and variation auto-encoder framework. We evaluate our method with several real datasets, and demonstrate that our method has superior detecting performance.
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Abstract—As it is known to all, more and more traffic pressure lead to traffic jams. Sometimes one-way traffic jams happened in two-way streets. This system is designed to solve this problem. It is a mobile partition piles system, which contains three parts. They are information acquisition module, image processing module and automatic control module. This system can monitor the condition of roads in real time by using machine vision technology. It can also move partition piles according to the traffic condition, which can ease traffic jams. Besides, partition piles will be back to original position when the problem is solved. The hardware and software of control system and mechanical structure has been accomplished. Several tests verified the characteristics of this system, such as distinguish accurately, react rapidly, high intellect, low cost and run stably.
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Abstract—In this paper, we use maize yield and meteorological data during the period of 1980-2015 in the Yilan County, Heilongjiang Province to study the impact of meteorological factors (rainfall, sunshine hours, temperature) on maize yield. Based on the computer simulation, Fisher integral model and Chebyshev orthogonal polynomials are used to analyze the coefficients between meteorological factors (temperature, precipitation and sunshine hours) and the maize yield so as to establish a mathematics model between the two. Through the coefficients between meteorological factors and maize yield during different periods, it is discovered that meteorological factors have a great effect on maize yield. By fitting degree of maize yield meteorological model, the maize yield can be predicted in an accurate way. It provides a theoretical basis for the information management of maize production in Heilongjiang Province based on the computer simulation. It is of great significance in providing scientific guidance for the sustainable development of Heilongjiang’s corn industry.
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Abstract—Two different methods of optimization and least square method are used to solve the reliability model of bearing rollers lifetime in this paper. Two different models of lifetime reliability are obtained. According to the models, two reliability curves are drawn and compared with the experimental data. Then, the lifetime of this bearing rollers is estimated by the models when its reliability is 90% and 50% respectively. The results are compared with experimental data. The conclusion is that the model obtained by least square method is more secure than the model obtained by the optimization method. But the model obtained by least square method is less economical than the model obtained by the optimization method.
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Abstract—Given the available time and the maintenance degree, using the relationship between the maintenance degree and the maintenance time, this paper establishes an algorithm to judge whether the maintenance task can be completed within a certain time, and proposes a method for calculating the amount of equipment maintenance in the available time, which is extremely helpful for the maintenance decision making process especially with the support of computers.
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Abstract—Through making an analysis of the randomicity of the spare parts demand, probability theory and mathematical statistics are applied to establish the support expense minimum model based on equipment availability, confidence values of the equipment readiness rate and support probability of spare parts. The arithmetic of spare parts joint support storage based on expense is presented. Then inventory optimization method of spare parts joint support based on computer simulation is determined. Applicability of the method is given by way of a numerical example. The inventory optimization method based on computer simulation provides a theoretical basis for solving the problems of inventory and expense in other relative areas.
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Abstract—Particle swarm optimization (PSO), as a kind of swarm intelligence algorithm, has the advantages of simple algorithm principle, less programmable parameters and easy programming. Many scholars have applied particle swarm optimization (PSO) to various fields through learning it, and successfully solved linear problems, nonlinear problems, multiobjective optimization and other problems. However, the algorithm also has obvious problems in solving problems, such as slow convergence speed, too early maturity, falling into local optimization in advance, etc., which makes the convergence speed slow, search the optimal value accuracy is not high, and the optimization effect is not ideal. Therefore, many scholars have improved the particle swarm optimization algorithm. Taking into account the improvement ideas proposed by scholars in the early stage and the shortcomings still existing in the improvement, this paper puts forward the idea of improving particle swarm optimization algorithm in the future.
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Abstract—The classroom is the main place for students to attend classes and self-study. Because the school classroom is limited, it often takes more time for students to find a classroom with no classes or few people. Therefore, the real-time statistics of the number of students in the classroom is of great significance for strengthening the school spirit and assisting teachers to understand the classroom situation. And it is meaningful to develop a classroom population statistics system to help students find a suitable self-study room quickly. In order to solve the problem that it is difficult to automatically count the number of students in the classroom and can not be real-time, according to the principle of face detection and referring to the convolution neural network target detection framework, a special single detection architecture and a scale allocation strategy suitable for this framework are proposed. the difficulty of automatic counting of students in the classroom is solved. In this paper, we use a specific data set for verification, achieve advanced detection results, and finally get a statistical accuracy of 97.8%. In classroom surveillance images, individual students are small targets, but the existing R-FCN target detection algorithm based on convolution neural network is difficult to detect small targets. In order to solve this problem, a series of improvements are made on the basis of R-FCN, which greatly improve the ability of R-FCN target detection algorithm to recognize small targets. It is verified on the self-made data set, and the accuracy is up to 89.4%.
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Abstract—In the design and control of robotic sensor system or haptic rendering system, one key technology is to give robotics the ability of feeling compliance like human. An easy way to realize it is quantitatively describing the relationship between stimuli and subjective perceptual results. In this work, we address the problem of mapping the interactive data of compliant objects to the perceptual compliance using perceptual model. Firstly, a perceptual space of compliant objects was built though psychophysical experiments and the N-MDS method. Then effective features were selected to estimate human-perceived differences of compliance based on correlation analyses. Finally, a perceptual model was built based on regression analysis to describe the subjective perception using effective feature parameters. Results show that a one-dimensional embedding space of “hardness” is proper to describe the subjective perception. Features of global stiffness and ratio of force and displacement could fit the perceptual results well in the form of exponential expression.
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Abstract—In driver assistance systems, thermal cameras are often used because they can provide compensation information for other sensors in the case of darkness or glare. For many existing thermal image vehicle detection algorithms, they can get a good detection accuracy in some occasions but the detection speed is relatively slow so they can’t meet the real-time requirements. In order to address this problem, we proposed a real-time thermal image vehicle detection algorithm based on yolov3-tiny. We have made two major improvements to the original yolov3-tiny. The first is to recalculate the anchor box priors by running k-means clustering algorithm on the bounding boxes of training dataset to make the network easier to learn. The second is to deepen the network structure of the original yolov3-tiny, so that it can better extract the characteristics of the vehicle in thermal images, so as to improve the vehicle detection accuracy. Our experimental results show that the mean Average Precision (mAP) of our proposed method is 6% higher than the origin yolov3-tiny while maintaining the detection speed comparable to the original yolov3-tiny.
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Abstract—As a distributed database that maps domain names and IP addresses to each other, DNS enables users to access the Internet more conveniently without having to remember IP addresses that can be directly read by the machine. DNS is the basic framework of the Internet, therefore DNS is also vulnerable to be taken advantage of by adversaries. However, DNS data can also be a tool to detect and retrace attacks. To be specific, some network security problems can be solved by obtaining passive DNS data. This paper discusses the collection and use of passive DNS data, and make a summary of current research.
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Abstract—This paper systematically analyzes the servo position loop and its control object of the shipboard TT & C radar system from the practical engineering application. The selection and parameter design of the position loop regulator are deeply studied. The method flow and computer realization scheme of the parameter design of the servo position loop are proposed, which provides theoretical support and practical feasibility for the design and improvement of the servo position loop of the shipboard TT & C radar system Scheme.
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Abstract—This paper introduces the influence of ship sway on the work of ship borne TT & C radar, compares and analyzes three kinds of ship sway isolation technologies commonly used at present, deduces the calculation method of ship sway isolation degree corresponding to the three technologies, and verifies the superiority of gyro speed feedforward compensation method to isolate ship sway through experiments, so as to realize stable tracking and give full play to the equipment efficiency of ship borne TT & C radar system It provides theoretical support and practical scheme.
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Abstract—The volume of the passenger in airport is an important indicator of the plan and management, so it is necessary to accurately predict the volume. Because the volume of the passenger is complex,linearly and nonlinearly. This paper proposes a forecasting model based on LSSVM to correct ARIMA error. We find the parameters of LSSVM by improving the inertia weights and acceleration coefficients of the standard PSO algorithm. We use the data from the Baiyun international airport to test the model. The simulation results show that the proposed model can improve the accuracy of the prediction.
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Abstract—Battlefield unmanned aerial vehicles (UAVs) usually suffer from complex, flexible and invisible electromagnetic interference, and as a result, they are easy to get out of control from the ground base. To address this problem, the method of the UAV electromagnetic jamming security situation awareness based on semantic analysis is proposed in this paper. The data source of semantic analysis is collected based on the subtle changes of the UAV state parameters during the electromagnetic interference process. Abnormal behavior detection is realized by a tracing comparison method. Subsequently, the fuzzy logic reasoning is adopted to realize the semantic analysis of the link jamming and intrusion situation. Finally, the semantic evaluation of the link situation is developed. Simulation results show that the proposed method can realize the evaluation of the security situation according to the limited and isomerism state parameters, which can, therefore, improve the active defense capacity of battlefield UAVs.
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Abstract—Blockchain technology is bringing new changes to the global financial landscape and immeasurable potential power for economic development in this new era. We believe that the development of blockchain technology has huge prospects, and it is necessary to sort out the current status of blockchain technology. Based on the synthesis of domestic and foreign research, this paper combines the development of blockchain in China in recent years, summarizes the current status of the architecture of blockchain technology, reviews its development and predicts its future development.
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Abstract—To improve the efficiency and accuracy of knowledge access in the oil industry, we propose to build a question-answer system for domain users. The system applies the state-of-the-art natural language processing techniques to analyze the domain knowledge in the form of keywords and their explanations. To this end, we collect over 20,000 keyword entries from reliable resources in the oil domain. The system then uses four different feature extraction techniques, including deep learning models, over these keyword entries to generate features, which are used to compute similarity between any given user question and keyword entries. Eventually, the keyword entries with the highest similarity scores are chosen as the answers and presented to the user. Our empirical evaluation shows that the traditional TF-IDF methods for feature extraction outperforms the other methods in our testing dataset.
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Abstract—Considering the bright future of intelligent driving and automatic driving technology, many researchers pay attention to the significance of traffic signs detection and recognition. In this paper, a fast and accurate traffic signs detection and recognition model was proposed, which uses a detector similar to the fully convolution network and one stage method in semantic segmentation problem to localize the traffic signs in a pre-pixel fashion. Compared with other stateof- the-art object detection networks such as Faster R-CNN [1] and YOLOv3 [2], the semantic segmentation network proposed in this paper does not need predefined anchor, so it completely avoids the complex calculation and super parameter settings related to anchor boxes, which greatly reduces the workload of training and accelerates the model inference procedure.
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Abstract—For Chinese web pages, we use regular expression and Viterbi algorithm to realize Chinese filtering and word segmentation, then use ngram2vec algorithm to get the word vector set of web page and pre train the word vector set of Baidu Encyclopedia. Baidu Encyclopedia word vector set is based on Infomap clustering algorithm to realize word vector Clustering and tagging types, training neural network through training data set and Baidu Encyclopedia corpus to determine the type of unknown web pages through neural network, and achieve the purpose of detecting the semantic information of unknown web pages. This algorithm is has few super parameters and high calculation efficiency. Experiments show that the accuracy of the trained neural network model reaches 96.73%, which can quickly and accurately identify the type of web page.
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Abstract—The paper carries out an in-depth analysis on the sum-rate bounds for a Gaussian partially cognitive radio channel with “mixed” interference, where one transmitter partially feeds another with messages in a non-causal manner. This implies that the cognitive transmitter can acquire the messages of primary users in part. The combination of superposition coding and joint decoding results in the formation of an inner bound. It is shown that, under certain conditions, the sum-rate lower bound obtained from the inner bound is the sum-rate capacity. Furthermore, it turns out that the lower bound lives up to the sum-rate capacity requirements imposed by the Gaussian channel with mixed interference and common messages. By comparing the two mentioned sum-rate capacities in certain mixed interference regimes, it can be fitly judged that the cognitive receiver is able to decode messages from primary users without affecting the sum rate. Finally, numerical results show the gains from unidirectional cooperation, where the cognitive information may be either perfect or incomplete.
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Abstract—Nowadays, portable notebook computers have made mobile offices very common. At the same time, as a piece of common office equipment, printers have not made a breakthrough in portable performance. For those who need to travel frequently, often the printer cannot be found anytime, anywhere. We have designed a new type of intelligent portable printer, which can be easily carried in a bag. Our main contributions include letting the printer enter the mobile office field for the first time, and greatly expanding the functions of traditional printers. In terms of function, it can simultaneously cover a lot of existing technical inventions such as traditional household printers, copiers, Polaroids, clothing pattern printing and dyeing machines, large-scale banner poster printings machines, mobile phone shell printing machines.
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Abstract—Vehicle positioning and classification is an important technology in intelligent transportation and autonomous driving. The system uses SSD algorithm to achieve vehicle classification and positioning, from the picture collection, picture calibration, model training, model detection several aspects of the detailed introduction of vehicle classification process. Pre-labeled can be adopted in image annotation to improve annotation efficiency. The SSD algorithm is a mainstream deep learning-based target detection algorithm in recent years. The algorithm has high detection efficiency and correct rate, and is widely used in classification recognition and target positioning.
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Abstract—Video object detection technology can improve the battlefield object search capability of tank fire control system. However, complex battlefield environment and faster speeds of tank and objects bring great challenge to video object detection. A video object detection method is proposed in this paper for the tank fire control system. Given the rich spatial-temporal information in the video and the large position deviation of the target in the adjacent video frames, a spatial-temporal convolutional feature memory model consisted of spatial-temporal convolution feature alignment mechanism and convolution gated recurrent unit is proposed to transmit and fuse the information of adjacent frames. Moreover, the feature extraction network and the detection sub-network are improved by the deformable convolution networks to increase the detection accuracy of deformed objects. To evaluate the proposed method, a database named TFCS VID including 1396 videos labelled for seven types of typical objects in the battlefield was developed. Compared to several other video object detection methods, the proposed method achieved excellent detection results on TFCS VID and could better meet the actual application requirements of equipment.
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Abstract—Firstly, this article recommends the principle of DLB algorithm, then describes the DSLB algorithm designed for the improvement of DLB algorithm, and proposes a dynamic scheduling load balancing algorithm on account of data center network fat tree topology. This algorithm mainly improves the DLB load balancing algorithm to reduce the possibility of network congestion caused by DLB algorithm in the real data center network environment. According to the available bandwidth of all possible upload paths and send paths, the DSLB algorithm chooses the best transport path for the traffic, so as to better solve the problem of local network congestion caused by DLB algorithm the traffic load balance of the core network provides a better solution. This paper analyzes and compares the performance of DLB and DSLB, and proves that the load balancing effect of DSLB is better.
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Abstract—Tor is currently the most used anonymous browser. Users can communicate anonymously on the Internet through Tor and some criminals can use Tor for illegal and criminal activities. In order to deal with congestion, Tor introduced a bridge mechanism to replace the previous ingress node. Obfs4 is one of the most important bridges used by Tor. It uses an improved elliptic curve encryption algorithm and random padding to hide message information, the antidetection ability is extremely strong. In order to effectively identify Obfs4 traffic, this paper proposes a Obfs4 identification method based on Multiple-feature fusion. Through research on Obfs4 protocol, data packet structure, node publishing strategy, and node distribution, this paper proposes many ways to obtain multiple features, including randomness characteristics, sequential characteristics, handshake packet length characteristics, and communication packet statistics characteristics. In addition, this paper proposes a machine learning algorithm based on a weighted Gaussian kernel function, which can modify the weight of different features to change the degree of influence of different features on the final classification result. Finally, the weight of each feature and the parameters used by the algorithm are determined through experiments. The accuracy of the algorithm is 93.82%, the recall is 99.00%, and the accuracy is 94.34%, which is much better than other algorithms mentioned in this paper. At the same time, this paper proves that there are some loopholes in Obfs4's anonymity mechanism, and its effective fingerprint can be obtained from the information it leaks to carry out attacks.
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Abstract—Tor anonymous communication system's resource publishing is vulnerable to enumeration attacks. Zhao determines users who requested resources are unavailable as suspicious malicious users, and gradually reduce the scope of suspicious users through several stages to reduce the false positive rate. However, it takes several stages to distinguish users. Although this method successfully detects the malicious user, the malicious user has acquired many resources in the previous stages, which reduce the availability of the anonymous communication system. This paper proposes a detection method based on Integer Linear Program to detect malicious users who perform enumeration attacks on resources in the process of resource distribution. First, we need construct a bipartite graph between the unavailable resources and the users who requested for these resources in the anonymous communication system; next we use Integer Linear Program to find the minimum malicious user set. We simulate the resource distribution process through computer program, we perform an experimental analysis of the method in this paper is carried out. Experimental results show that the accuracy of the method in this paper is above 80%, when the unavailable resources in the system account for no more than 50%. It is about 10% higher than Zhao's method.
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Abstract—In this paper, a new kind of composite continuous wave signal modulated by pseudorandom code family is designed aiming at solving the problem of group targets resolution with high dynamic: more quantity, larger speed variation, larger distribution and higher resolution. With a thumbtacked ambiguity, the new composite signal retained the advantage of pseudo code signal with high 2 dimensional resolution of speed and range. Furthermore, a new single demodulation method is proposed for this modulated signal. This method brings the characteristic of multi-resolution for the composite signal. Single demodulation method has been proved to be feasible through the correlation analysis and fuzzy characteristics analysis of sub-signal from the composite signal. Meanwhile, the realization process of signal multiresolution is illustrated by an example. At last, recommendations pertaining to signal selection, number option and usage are put forward for this signal modulated by pseudo-code family and this single demodulation method. The study of this paper is helpful for group targets resolution and is also of great importance to improve complex waveform design and performance.
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Abstract—Traditional imaging algorithms of uniform motion SAR are not suitable for maneuvering imaging. Timedomain algorithm is too computational to be suitable for realtime imaging. Frequency domain algorithm mainly relies on the solution of two-dimensional spectrum. It is usually suitable for SAR imaging in a single motion mode, and its applicability is poor. A maneuvering SAR imaging algorithm based on the separation of azimuthal motion information is proposed. The algorithm breakes through the limitation that the traditional frequency domain imaging algorithm can only be applied to a single motion state. Through simulation, the applicability of the algorithm in the traditional uniform motion, threedimensional uniform motion, three-dimensional uniform acceleration motion and other motion states is verified. The algorithm is simple, stable and applicable.
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Abstract—CO is one of the main air pollution gases. The monitoring of CO concentration is very important for air pollution control. At present, TDLAS has been widely used in air environment monitoring. However, in the measurement process, the baseline fitting error will lead to a large error in CO concentration measurement. Therefore, this paper proposes to adjust the input signal of the signal generator iteratively and modify the baseline nonlinearity to improve the baseline fitting error, so as to effectively reduce the CO concentration measurement error. First of all, by comparing the real baseline with the polynomial fitting baseline of different orders, the polynomial fitting error is 33% ~ 56%, which proves that the non-linearity of baseline will lead to large concentration measurement error. Secondly, by modifying the baseline nonlinearity, polynomial fitting is used to measure the baseline concentration, the error is reduced to 6.2%, and the measurement accuracy is improved obviously. This method improves the polynomial fitting baseline error caused by baseline nonlinearity, improves the accuracy of CO concentration measurement, and provides technical support for CO monitoring in air pollution.
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Abstract—In order to meet the current needs of enterprises and institutions in data center construction, this paper designs and implements the deployment of private cloud platform based on KVM and open stack on the infrastructure layer of private cloud platform. The private cloud platform designed in this paper provides users with virtual resource adaptive services and cloud storage services through cloud middleware. It designs and implements resource monitoring, resource prediction, virtual resource adaptive, user management and cloud storage on the cloud middleware layer, so as to meet the application needs of current enterprises and institutions. Among them, virtual resource adaptation is the core function of private cloud platform. This paper focuses on the design process of virtual resource adaptation module, and gives the implementation method and process of each middleware function module.
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Abstract—This paper optimizes the parallel receiver algorithm, the parallel receiver system applies parallel demodulation algorithm and dynamic signal detection algorithm into modules such as data arrangement, FFT processing, and phase compensation. With the improved algorithm, parallel receiver can realize the accurate decision of the effective signal and demodulate the parallel signal quickly.
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Abstract—A novel EBG structure is proposed. The proposed EBG (denote as DAS-EBG) structure is compact and flexible. The proposed EBG structure consists of a mushroom-type EBG with four symmetrical U-shaped slots etched on it, which is compact and flexible. Due to the change of surface resistance of multiple U-shaped slots, DAS-EBG got a width reduces of 33.75% and height reduces of 20%. By changing the size of the U-shaped slots, the number and size of DAS-EBG surface resonance points can be flexibly changed. The proposed EBG structure can be used in future broadband and multi-frequency applications.
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Abstract—With the rising global ocean temperatures, the habitats of Marine organisms change, which affecting human production practices at the same time. First of all, in order to explore the relationship between global ocean temperature and time, we collected sea surface temperature (SST) data in the north Atlantic region. We establish the BP neural network prediction model based on EMD. The prediction model firstly used EMD to stabilize the water temperature time series, and obtained a group of stable components IMF and a surplus. Then the BP neural network is used to predict each component, and the predicted value is added as the predicted value of the original sequence. To get a forecast for the sea surface temperature of Scotland over the next 50 years. Visualize the past and predicted the data and match the range of suitable temperatures for herring and mackerel to the sea surface temperatures near Scotland. Matching area represents the fish habitat. Observing the movement of the matching area each year, the fish's habitat migration process can be predicted. The second problem is to choose the suitable operating strategy for fishing company. Because the migration of fish is sensitive to the changes in temperature, there will be a risk of secondary transfer if choosing transfer assert. Thus, we suggest to use small fishing vessels.
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Abstract—Aiming at the problem that the current AW3D30 data has a cavity outside 60° north and south latitude, In experiments, different fusion methods, including direct mosaic, inverse distance weighting, inverse distance square weighting, gaussian inverse distance weighting and gaussian inverse distance square weighting methods, were compared using ASTER GDEM v3 and AW3D30 v2.2 data sets in the area around 60°north latitude. The fusion results are compared by longitudinal section and surface error information entropy. The results show that: 1) Among the five methods, the direct mosaic boundary is obvious, the other four methods adopt curve transition, and the transition at the boundary is relatively natural; 2) Further comparison in the four curve edge-connection modes, the two weighting methods using Gaussian function are better at the northern boundary of the transition zone. The mean value of the elevation difference is 1.3 m. The inverse distance weighting and the inverse distance square weighting effect are poor, and the elevation difference is poor. The mean value is 16.0 m; 3) Finally, using the surface error information entropy to compare the two Gaussian methods, the fusion result of Gaussian inverse distance weighting method is better, and the average surface error information entropy is 3.22 bit. Therefore, among the five fusion methods, the Gaussian inverse distance weighting method has the best effect.
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Abstract—This article expounds and demonstrates how to help the Amazon online products gain the favor of the users. It selects the user evaluation text from some Amazon products. It uses the methods of data analysis, coefficient of variation, literature review and questionnaire to select the relevant indicators. Nine factors are chosen as indicators such as average product score, total number of comments and number of helpful comments and so on. The user preference evaluation index system is established, and the weight is determined by swing weight method. Based on the theory and method of grey fuzzy comprehensive evaluation and text emotion analysis, a comprehensive evaluation model is established, and the evaluation results and suggestions are obtained.
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Abstract—Sprinkler irrigating equipment play a necessary role in modern agriculture. Their energy consumption and flexibility of manipulation are quite important to the user for their daily routine. An underactuator configuration of a novel robotic arm which has three bellows as a flexible arm for precision sprinkler irrigation were introduced. Multiple DoFs can be realized by using hydraulic theorem with a manipulating strategy of three solenoid valves and a hydraulic piston motor which provides the driven force. These combinations make multiple DoFs manipulation possible by using just one driven motor, which cuts the energy consumptions and equipment costs.
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Abstract—Electrorheological (ER) valves have advantages of fast response speed and low energy loss. But, under the condition of high shear rates, the ER valves governed by traditional uniform electric field have poor performance and cannot meet the demands of applications with high speed loads. Existing researches show that when parallel components of an electric field were applied to the flow direction of ER fluids, the yield stress of the ER fluid can be greatly improved at high shear rates. Using non-uniform electric fields which can provide parallel components of electric field to the flow of ER fluids may make ER valves a possibility to meet the demands of working at high shear rates. In this paper, an intermittent staggered electrodes configuration was introduced, which can generate a non-uniform electric field with parallel components for ER valves. Distributions of electric fields are simulated and analyzed by COMSOL Multiphysics. An algorithm of the effective electric field strengths for non-uniform electric fields was introduced to evaluate the yield strength of the ER fluid. The ER valves’ performances for applications at high shear rates can be assessed by the average values of effective electric field strengths in the working area of the electric field. The average values of effective electric field strengths varying with structural parameters of the intermittent staggered electrodes were studied. They have a peak value when varying with the increment of electrode widths, and rise up with increments of insulation widths and electrodes dislocation distances. The results provide a reference to the electrodes configuration design of ER valves governed by non-uniform electric field.
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Abstract—The refreshing rate of a multi-lines Braille display using electrorheological (ER) valves matrix plays a very important role to meet the demands of reading experiences of visual impaired people, a lower refreshing rate of Braille dots which is less than the reading rate of visual impaired people will stop them from using the Braille display and let them learn knowledge by listening. The refreshing rate is governed by the rate of flow of an ER valve which was used to be an actuator of the corresponding Braille dot. A mathematical model of the refreshing rate was established to learn the effects of the critical parameters of the ER valve on the rate of flow of the ER valve which is equivalent to the refreshing rate of the Braille display in this paper. The results show that to meet the demand of refreshing rate for visual impaired people, the governed voltages of ER valves should be higher than 1kV. The minimum value of operational governed voltages of an ER valve will decrease when higher tolerances were exploited to the parameters of channel of an ER valve. These results may provide some suggestions to design of an ER valve.
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Abstract—The event recognition is an important foundation in the event extraction task. This paper uses Chinese Emergencies Corpus (CEC) as the raw corpus, and the vector representation of the text is obtained by embedding a pre-trained language model ALBERT(A Lite Bidirectional Encoder Representation from Transformers).Then the BiLSTM-CRF (Bidirectional Long Short Term Memory-Conditional Random Field) model is used to extract the text features and label-dependent features, the model finally outputs the predicted label sequence to realize the boundary and type recognition of the trigger word. The experimental results show that the micro-F1 value of the trigger word recognition on the CEC reaches 76.4%. In comparison with other event recognition methods, our approach achieves more outstanding performance, and have higher training efficiency.
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Abstract—Recently, with the increase of high-rise buildings, as a convenient tool, elevator has become more and more popular. However, the cost of safety monitoring equipment is relatively high in the elevator market, and is not suitable for the promotion of small and medium-sized elevator use. This paper makes use of virtual instrument technology to monitor the operation state of elevator. Labview visual module has a large of specialized controls and function libraries, with cameras. It can monitor and warn the elevator running state efficiently and accurately. In addition, the system is easy to modify, can add some other common elevator conditions, such as calculating the number of passengers, face recognition and so on. The system will be more perfect by increasing functional models.
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Abstract—The blockchain is based on a distributed security network. It has a unique data trust protection mechanism and strong data security protection and tamper protection capabilities. It meets the traditional physical security network's physical decentralized data trust and other network data trust for other information security application technologies. Technical requirements also have natural technological advantages in the application of information security technologies such as the mobile Internet of Things cloud. Therefore, this article starts with several related basic conceptual issues related to blockchain security technology, focusing on research and analysis of its technical advantages in the development of IoT security applications and the widespread application and commercial promotion of blockchain security technology in the future. Refer to decision recommendations.
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Abstract—With the development of information technology in recent years, the combination of web design and computer image processing technology has become a hot research topic. Based on this, this article discusses the application of computer image processing in web design. The technology is summarized, its concept, development, function and its advantages in web design applications are introduced. Then the application of computer image processing in web design is analyzed, including diversified image forms, reasonable distribution of images, image processing techniques, controlling image size and color, etc. Finally, the blind areas and targeted strategies of web design are described from three aspects, which provides theoretical support for increasing the application of computer image processing in web design in the future.
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Abstract—The evaluation of Radar anti-jamming effect is a very complicative problem. Firstly,the paper analyzes the main factors affecting the effect evalution of interference. Secondly, the fuzzy comprehensive evalution model is given by using the viewpoint of fuzzy mathematics. Finally, the effectiveness of fuzzy comprehensive evalution of radar interfernve is verified by simulation, and draw a useful conclusion.
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Abstract—In recent years, pedestrian detection has attracted more attention in many practical applications. In this paper, a novel pedestrian detection method using quaternion histograms of oriented gradients (QHOG) was proposed, which is integrated the advantages of both the quaternionic representation and HOG feature of a color image. Firstly, the quaternionic representation was performed on the color image in the sliding window, and then the histograms of oriented gradients (HOG) feature was extracted over the quaternionic representation map. After that, the QHOG histogram was constructed to represent the sliding window. Two groups of experiments are performed on two popular pedestrian datasets, INRIA dataset and Daimler Chrysler (DC) dataset, respectively. The experimental results show that our proposed QHOG detector performs better than the HOG detector, HOG-LBP detector and MWLD detector.
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Abstract—Drowsy driving contributes more than 20% of road fatalities, especially to countries like America which relies heavily on road transportation. With significant physical injuries to passengers and significant economic losses, it becomes a vital task to detect driver drowsiness and relieve their fatigue. In this research, we developed an integrated facility to help resolve this task, which contains a polymorphic detection model, based on deep learning, and a music recommender system, aiming to release drivers’ fatigue. The detection model contains two parts. The first utilized human keypoints detection model to monitor driver’s expression and detect drowsiness while the other used real time heart rate to detect. To ease the pressure of data collection and make the whole system a integrated product, a wearable device is made by ourselves. Besides these, a novel personalized music recommender system is built up to help adjust the status of driver. With the combination of two detection model, we achieved 96.82% accuracy and built up a finetuned deep learning model.
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Abstract—Existing cleaning robots, such as household circular cleaning robots and road cleaning vehicles, are applied to flat ground. However, whether it is indoor or outdoor, there are a large number of steps or stairs, such as in residential buildings, office buildings and many high-rise buildings. The cleaning of the steps in the stairwell cannot be ignored, but it requires labor and material resources, so a device that can replace manual cleaning is obviously very much needed. The robot can efficiently and stably clean the stair area within the specified range within a set time and any time period. The device is a robot for cleaning stairs and platforms, which can automatically go upstairs and clean the surface of the stairs. The device is equipped with two independent suspension systems at the front and rear to adapt to stairs with different height differences and to complete the movement of going upstairs or steps. The steering wheel controls the forward and backward movement of the four wheels to achieve the movement of the entire machine, and the wheels can be rotated horizontally to move left and right to achieve the entire sweep of all corners of a single staircase.
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Abstract—This project mainly explores an all-terrain vehicle that can assist disaster relief after a disaster, which has good passability and certain demolition ability. This all-terrain vehicle is equipped with a variety of sensors, which can effectively search and locate the location where the victim may be buried, providing useful information for subsequent search and rescue. The terrain vehicle will adopt a triangular track structure to improve its passability; In addition, the machine is equipped with a main demolition device so that it can expand the gap that exists after the disaster and therefore increase the machine's capacity in small gaps; Equipped with a variety of sensors, the terrain vehicle can effectively perform path planning, search for survivors or locate areas where it may be, and return position and vital sign data. With the help of these data, search and rescue team members will conduct a more effective search of possible areas, thereby improving search and rescue efficiency.
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Abstract—Through in-depth research on the principle of the mechanical arm, this project adopts a multi-degree-of-freedom mechanical arm structure designed by the electric system. The system includes a control section and a robot arm section. The control part is to control the movement and grab function of the arm through Arduino. An acceleration sensor is installed on the foot to sense different attitudes of the foot, the movement of the corresponding mechanical arm, and grasping. The bending of the robot arm and the grasping of the fingers are done by the steering gear. The ultimate goal of this research is to control the movement and grip of the robotic arm through the feet, to help people with disabilities to grasp the objects and facilitate their daily affairs.
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Abstract—Aiming at the shortcomings of high communication cost and power consumption in the existing intelligent lighting system, an intelligent lighting system based on low power wireless transceiver chip NRF24L01P is studied. The overall architecture of the system is given and the realization of system functions is introduced. The system adopts NRF24L01P networking technology to realize interconnection and intercommunication between LED lighting devices, which reduces the cost and power consumption of wireless communication; converts Wi-Fi protocol into NRF24L01P communication protocol by designing IoT router, enables user terminal to remotely control and monitor LED The lighting device and the fuzzy PID algorithm are used to improve the stability of the system. The solar temperature difference power supply based on the thermoelectric power generation chip is studied to realize the green environmental protection for the IoT router.
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Abstract—This paper is devoted to the problem on the finite-time stabilization (FS) of stochastic neural networks (SNNs) with time-varying delay (TVD) via impulsive control. By structuring the proper Lyapunov-Krasovskii functional and with the help of average impulsive interval method (AII), some sufficient conditions to ensure the FS of SNNs with TVD are derived in term of LMIs. Compared with the impulsive sequence with uniform distribution, our results are more suitable for the practicalities. Finally, numerical simulations are shown to verify the effectiveness of our results.
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Abstract—The distributed fault-tolerant computer technology of deterministic communication takes the needs of a new generation of IVMS as background in this paper, the system architecture design and software architecture of distributed fault-tolerant computer are studied, and one kind of communication software based on VxWorks653 partition operating system is designed and implemented, moreover, it has been practically applied in engineering, and it can meet the communication needs of big data and high-performance in avionics applications after function and performance verification. This communication protocol software is implemented with layered architecture, which is conducive to cross-platform migration, software reuse, and subsequent hardware upgrades.
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Abstract—In this paper, a miniaturized space-borne broadband beacon antenna of 243MHz/406MHz is designed. Based on the improvement of the structure of the monopole antenna, the working bandwidth is effectively expanded by adopting the parallel feeding method. After the antenna structure is determined, the microwave simulation software XFDTD is used for simulation analysis. The calculation and analysis results show that the standing wave ratio SWR is less than or equal to 2.0 in the 243MHz/406MHz working bandwidth, and the antenna pattern is basically similar to a monopole antenna. Using one antenna can cover 243MHz and 406MHz working frequencies, which can be used for manned spacecraft or return spacecraft beacon antennas. Finally, the antenna is made and tested with a network analyzer to verify the theoretical analysis and simulation results.
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Abstract—Data is most precious resource for the world in the era of big data. Now most of the information and data needed for audit is in electronic form. The technology and resources related to big data will have a far-reaching impact on audit, and inspire auditing institutions to make technological, business and management innovations oriented from big data, and drive the reform of audit management by constructing the audit management and operation platforms.
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Abstract—With the continuous development of computer technology, both hardware and software equipment have undergone upgrading. At the same time, in order to meet the aesthetic needs of the public and the application needs of various industries, the computer is directly used in graphic design, which can give graphic design Bring new changes. Designers have gradually developed from the use of paper and pen as a carrier to use a variety of design software as a carrier to make the designed floor plan more in line with the aesthetic needs of modern people. From the design concept to the presentation of works, continuous innovation can be achieved, thereby expanding the scope of graphic design applications. This article is based on the use of Flash AIR programming and development + Photoshop technology to build a flat visual design platform to meet the needs of customers in the graphic design process. It has the aesthetics of graphic layout, shortens creative design time, improves work efficiency, safe and reliable system, and convenient operation.
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Abstract—Due to the network topology high dynamic changes, the number of ground users and the impact of uneven traffic, the load difference between SDN-based satellite network controllers varies widely, which will cause network performance such as network delay and throughput to drop dramatically. Aiming at the above problems, a multi-controller optimized deployment strategy of satellite network based on SDN was proposed. First, the controller's load state is divided into four types: overload state, high load state, normal state, and idle state; second, when a controller in the network is idle, the switch under its jurisdiction is migrated to the adjacent low load controller and turn off the controller to reduce waste of resources. When the controller is in a high-load state and an overload state, consider both the controller and the switch, and migrate the high-load switch to the adjacent low-load controller. Balance the load between controllers, improve network performance, and improve network performance and network security. Simulation results show that the method has an average throughput improvement of 2.7% and a delay reduction of 3.1% compared with MCDALB and SDCLB methods.
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Abstract—In order to realize the hardware universal design of key matrix, function software custom settings and the number of keys can be expanded in the human-computer interaction scenario. The OLED display technology are studied, and the key matrix based on OLED display technology is designed. According to study the driving principle of OLED display keys, the circuit schematic diagram of LPC1788 controller, realizes the configurability of the software for displaying text and pictures. The key matrix design based on OLED display technology is stable, reliable, clear, versatile, beautiful in appearance, friendly in man-machine interface, and can be widely used in man-machine interaction system for keyboard requirements of vehicle, ship and airborne.
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Abstract—In order to speed up the detection of cybercrime worldwide, a new cross-border cybercrime detection system is designed by introducing the PSE theory and the principle of big data analysis. In the TFTP server, the U-boot network development board and OpenStack crime information detection component are connected to build the hardware running environment of the cross-border network crime detection system. On this basis, through the analysis of the characteristics of detection information, the calculation of cross-border network detection domain and the directional planning of network crime information, the software operating environment of the detection system is built, and the cross-border network crime detection system based on PSE and big data analysis is designed with the basis of hardware implementation. The comparative experimental results show that, compared with the conventional case detection situation, the average detection time of criminal cases is basically maintained between 3-5 days after the application of cross-border cyber crime detection system, and the accuracy of criminal location is maintained at more than 90%.
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Abstract—This article comprehensively uses the theory and technology of visualization technology, pattern recognition technology, human-computer interaction, computer graphics, and graphic design technology to do in-depth research on the principle and implementation method of circuit graphic design based on dynamic modular interactive whiteboard Through the modular design idea and dynamic link library technology, the interface of SMART interactive whiteboard and AutoCAD is studied, and the interactive operation of the two is realized. The combination of the visualization technology, pattern recognition technology and computer automatic processing function of the interactive electronic whiteboard and the practical experience and creative thinking of the engineers will surely further improve the work efficiency and quality of railway line design. Therefore, the related research on the principle and implementation technology of railway line graphic design based on interactive electronic whiteboard is of great significance.
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Abstract—With the rapid development of China's economy, the elevator has become a basic tool in our daily life, and the safety risks brought by the elevator are also increasingly serious. It is necessary to use the technology of big data to mine the existing multi-source Heterogeneous elevator data, so as to find out the various rules of fault. Data collection and preprocessing are the important parts of big data mining and analysis. In this paper, through the research of collection and preprocessing of multi-source heterogeneous elevator data, the quality of inputting data which is needed for the data modeling later on is improved, so as to provide better service for elevator fault prediction.
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Abstract—Compared with the traditional three-phase induction motor, the five phase induction motor has the advantages of low torque ripple amplitude, high ripple frequency, high power density, good fault-tolerant performance. It is widely used in the driving and propulsion fields of electric vehicles, rail transit, ships, etc., and also in some special small power transmission mechanisms with high fault-tolerant performance requirements. In this paper, the main parameters of a small five phase induction motor are calculated based on the magnetic circuit method and the winding function method. At the same time, the number of stator and rotor slots in the small five phase induction motor is calculated and simulated. It is concluded that the stator 40 slots and the rotor 26 slots can be used as the optimization of the small five phase motor.
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Abstract—A multi-scale R-FCN detection algorithm is presented to solve the problem of region-based full convolution network (R-FCN) in multi-scale object detection. Firstly, in order to solve the problem that R-FCN algorithm has limited receptive field and semantic information in single feature map detection, a multi-scale proposal box (proposal) is obtained by using multi-scale feature maps in the main network. At the same time, in order to make the feature maps of different layers have rich semantic information at the same time during the two-stage detection, the feature maps of different layers are fused from top to bottom. Finally, in order to make the two-stage position-sensitive score map also have good multiscale representation ability, a multi-layer shared convolution method is used to generate the position-sensitive score map. The experimental results on PASCAL VOC dataset show that the multiscale R-FCN algorithm in this paper is better than the original R-FCN algorithm in detection accuracy. At the same time, the detection map shows that the algorithm performs better in multi-scale object detection.
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Abstract—Vibration will affect the performance of high-precision equipment, so it is necessary for the research of vibration isolators. This paper takes air spring vibration isolators applied to high-precision chip testing equipment as the research object, and designs a three-wire pendulum mechanism with a ball hinge structure. The ball-hinge structure can reduce the horizontal stiffness of the three-wire pendulum mechanism, thereby improving the isolation performance of the vibration isolator. Then the mathematical model of the three-wire pendulum mechanism is established, and the factors that affect the horizontal stiffness of the three-wire pendulum mechanism when subjected to slight vibration are obtained through theoretical analysis. Finally, ANSYS Workbench is used to carry out the finite element simulation analysis, which verifies the results of the theoretical analysis. Reducing the diameter of the fixed plate of the swing rod can reduce the horizontal stiffness of the swing mechanism. When the diameter of the fixed plate of the swing rod is reduced by 2%, the horizontal rigidity is reduced by 5.86%; Increasing the diameter of the wobble plate can reduce the horizontal stiffness of the pendulum mechanism. When the diameter of the wobble plate is increased by 2%, the horizontal stiffness is reduced by 4.96%; Increasing the distance between the fixed plate of the swing rod and the swing plate can reduce the horizontal stiffness of the swing mechanism. When the distance between the fixed plate of the swing rod and the swing plate is increased by 2%, the horizontal rigidity is reduced by 3.99%. It provides a basis for the subsequent research on vibration isolators using the three-wire pendulum mechanism.
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Abstract—This article aims at the lack of a unified platform support for business processes in the process design of an enterprise, which leads to inefficient information transmission and the multiple versions of a large number of process data documents, which makes it difficult to efficiently manage process data, and process data cannot be effectively accumulated and reused, which cannot form Process knowledge base and other issues. The construction of process knowledge base and structured process list (BOP, Bill Of Processes) based on Teamcenter platform is proposed, and the structured process information is extracted and summarized through the secondary development of Teamcenter, and the work order sheet is output to guide the operation production. It is verified that the system improves the efficiency of enterprise business circulation, process preparation, the reuse rate of process knowledge, reduces a large amount of process data redundancy, and lays a solid foundation for the level of enterprise automation.
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Abstract—To improve the health of pig breeding and reduce the incidence of pig epidemic, this paper studies and analyzes the environment of pig breeding. Pig breeding has the characteristics of closedness and intensiveness, for which a system based on the wireless sensor network for remote monitoring of pig houses has been developed. Aiming at the characteristics that the body temperature of pigs in pig breeding is difficult to be measured quickly and efficiently, thermal infrared imaging technology is used to automatically detect the body temperature of pigs. Finally, with regard to the monitoring and prevention of epidemic situations in pig farms, a method of automatic detection using non-contact ears is proposed as well as a vehicle for automatic inspection and disinfection is developed. The research results show that the wireless sensor network can monitor the environment of the pig house in real-time and regulate the environment to make it more suitable for the growth of pigs. The use of thermal infrared imaging technology realizes the temperature parameters of the characteristic regions of pig ears. The use of non-contact ear automatic detection technology and the vehicle for automatic inspection and disinfection can automatically disinfect the pig house and carry out automatic alarm work for epidemic situations. It is found that the use of automatic detection technology, as well as automatic inspection and disinfection vehicles can monitor the live environment of pigs, and ensure the health of the environment, thereby reducing the incidence of pig epidemics and the cost of pig breeding.
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Abstract—This paper aims at the resource scheduling problem in public environment, in consideration of the real situation of virtual computing environment experiment platform. It introduces the trust mechanism in the experimental platform to ensure the trust issue of resource scheduling problem in public environment; through the gradual in-depth analysis of resource properties and application, this paper realizes the gradual fining match and scheduling between resource and application, so as to enhance the overall performance of the virtual computing environment.
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Abstract—At present, there are some problems in database technology, such as low sharing of data, poor security of data, and frequent data leakage. Data bottlenecks are also a big constraint. In order to satisfy the user's needs to edit, manage and store the data, it is necessary to replicate the data to improve the accessibility of data. This paper expounds the design and implementation of related technologies, and hopes to offer some help to perfect these technologies.
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Abstract—With the constant development of sports scientization, the combination between sports information management and informatization technology is increasingly close. Sports information development will be a future tendency. By analyzing relevant references of domestic and overseas sports fields in information management system application, the author summarized the application status of sports information management system and pointed out some problems and development prospects of information management system application in this field.
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Abstract—with the continuous development of the society, informatization is a social theme of the new century, whose core is the e-government. In this paper, the research and establishment of the sports Enterprise Informatization Evaluation Index System is aiming to make quantitative evaluation of the sports enterprise informatization, calculate the index of information, and analyze the evaluation result qualitatively.
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Abstract—The high risk of the entire coal industry and the characteristics of every coal mine in Jiugu Coal Industry: large water and gas, and complex geological conditions are considered in this paper. With the consideration of Jiugu Coal Industry’s network environment and the superiority’s network requirements of underground video surveillance system, a full needs analysis is conducted from the perspective of information technology and information technology. And security management mechanisms are effectively combined to open up initiatives and new measures of innovative production safety management. The paper created a mine drilling video networking system with good fusion. With the help of information technology, the management level of security risks and management purposes are improved so as to provide a strong technical support for enterprise safety production.
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Abstract—In the real-time acquisition of human body motion physiological parameters, the data will be collected back to the processor, guiding the exercise physiological parameters for adaptive correction. A method of human motion physiological parameter acquisition system is proposed based on embedded design. TMS320VC5409A DSP chip is used as the core processor. The hardware modularization design of the human body motion physiological parameter collector is carried out in embedded ARM. The collector is mainly divided into sensor module, signal processing module, embedded integrated control module and human-computer interaction module. A realistic geometric model of human motion is generated in 3DS Max software. In the forward channel, various signals are converted into electrical signals, and the sensor nodes are arranged under the embedded Linux kernel. The information sampling of human motion physiological parameters is realized, and the man-machine interaction and interface design based on PCI VXI ISA bus interface are carried out, and the embedded integrated design of human body motion physiological parameter collector is realized. The test results show that the designed collector can collect human body motion physiological data, the reliability of the system is high.
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Abstract—With the rapid growth of Chinese economy and constant improvement of internet popularity, Chinese electronic commerce (for short e-commerce) has seen a remarkable performance. From the initial B2B mode to network retailing mode as well as the eye-catching C2B mode, the concern is focused on the status, problem and suggestion on the e-commerce mode, but there is short of corresponding theoretical study among the e-commerce modes. For this reason, the path, theoretical mechanism and future development direction of cross-border e-commerce mode are the emphases in this paper.
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Abstract—In order to improve the intelligence and fidelity of cultural and creative product design, the method of cultural and creative product interaction system based on VR technology is proposed, and the virtual reality(VR) design of cultural creative product is carried out by image processing. the 3D geometric model of the cultural creative product is modeled with Multigen Creator software, the visual simulation of the cultural creative product is carried out, and the polygon modeling of the cultural creative product is carried out. A graphic instance set of cultural and creative products is constructed in Lynx Prime, the VR rendering and 3D modeling of the interactive system of cultural and creative products are realized by using the real-time scene simulation rendering software Vega Prime. The virtual reality visual simulation of cultural and creative products is realized. The software of intelligent management system of cultural and creative products is developed under embedded Linux, and the database model of interactive system of cultural and creative products is constructed according to OpenGL graphics library. The simulation results show that the interactive system of cultural and creative products designed in this paper has a good virtual modeling effect of cultural and creative products. The design of cultural and creative products fidelity is good; the ability of information interaction is strong.
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Abstract—In order to improve the sharing ability of network video data resources under the new media environment, the integration and sharing system optimization design of the network film and television data resources are carried out. In this paper, a new media integration method based on resource load balancing and scheduling is proposed. First, the collection and storage structure of network video data is analyzed, and the feature of network video data information flow is extracted. In order to realize the optimal clustering and scheduling of network film and television data resources, the attributes of network film and television are processed by template matching and data clustering, and then the software development and design of resource integration and sharing system are carried out. The hue database of the resource integration and sharing system adopts MySQL. The background server is built and the interface is designed under the framework of B/S. In the embedded Linux kernel environment, the integration of network video data resources and the software development of sharing system are conducted. The system test results show that the method is used to integrate and share the network video data resources, and the utilization rate of the resources is high. The clustering of network film and television resources data is better, the performance of resource scheduling is improved, and the effect of resource sharing is better.
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Abstract—In the network environment, the multi- dimensional user experience evaluation model is built to meet the personalized needs of multi-dimensional users and improve the network service instructions for multi-dimensional users. A design method of multidimensional user evaluation model is proposed based on principal component analysis and personalized data mining. The semantic ontology feature directivity clustering method is used to mine the personalized demand data of multi-dimensional users, and the association user adaptive tracking method is used to predict the multi- dimensional user experience, and the principal component analysis is carried out according to the prediction structure. The state recognition and data feature analysis of multidimensional user experience data are realized, the feature decomposition model of multi-dimensional user experience data under mobile computing environment is constructed, and the multidimensional user experience evaluation is realized. The simulation results show that, this method has good accuracy and high satisfaction in multi-dimensional user experience evaluation, which has a good application value in improving the network service.
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Abstract—In order to improve the ability of food packaging optimization and selection, combined with big data analysis method, different food best packaging methods are selected, and a large data classification technology for different food packaging methods based on fuzzy directivity classification is proposed. Big data parametric model which reflects the best packaging characteristics of different foods is extracted, and the extracted packaging parameters are matched by adaptive fuzzy matching. Then, the directional clustering method is used to classify and identify big data, which is combined with the food packaging. The shelf life and food characteristics are processed by big data information fusion to realize the best match between food packaging and food characteristics. The retrieval node graph model grouping method is used to classify different food packaging data to optimize the selection of different food packaging methods. The simulation results show that, the method used to select the best packaging methods for different foods has better intelligence, improving the ability of classification and recognition of food packaging, and promoting the intelligent development of food packaging.
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Abstract—In order to improve the ability of pushing and evaluation of achievements of cultural innovation from multiple perspectives, the authors design an experience exchange platform for achievements of cultural innovation from multiple perspectives. A design method of experience exchange platform for achievements of cultural innovation is proposed based on multi-thread bus, which describes the overall design of the system, and establishes an experience exchange platform for achievements of cultural innovation based on Visual DSP++4.5. In the embedded environment, the resource scheduling of the cultural creative products is carried out, and the information collection and visual remote operation of the experience exchange platform of the cultural creative products under the embedded Linux kernel are carried out in combination with the information loading module. The interactive performance of achievements of cultural innovation is improved, and the experience exchange platform of achievements of cultural innovation is designed. The cross-compiling software is used to realize the interactive experience design of achievements of cultural innovation from multiple perspectives. The simulation results show that, this method is used to design the experience exchange platform of achievements of cultural innovation from multiple perspectives. The resources scheduling performance of achievements of cultural innovation is better, the ability of information checking is stronger, and the interactive experience performance of achievements of cultural innovation is better.
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Abstract—In order to improve the control performance and virtual reality of the virtual tourism system, the design of the virtual tourism system with the characteristics of cultural tourism resources is carried out by using the three-dimensional tourism virtual reality technology. A design method of cultural tourism resource characteristic development system is proposed based on 3D virtual reality quantitative tracking fusion technology. The overall structure model of virtual tourism system is constructed, and the function module of virtual tourism system is analyzed. The functional components of the virtual tourism system are divided into tourism resource development module, information transmission module, information fusion module and virtual reality visual simulation module. The virtual reality simulation environment of cultural tourism resources characteristic development is established by Multigen Creator software. According to the object-oriented development of cultural tourism resources, 3D geometric modeling and rendering of virtual tourism system is carried out. The development and design of virtual tourism system software based on MAXStudio SoftImage is realized. The matching ability and man-machine interaction of virtual tourism system are improved by using quantitative fusion and tracking technology. The simulation results show that, the virtual tourism system designed has good human-computer interaction, and the visual simulation of tourism scene is more authentic, which effectively promotes the development of cultural tourism resources.
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Abstract—In order to realize shadow automatic generation in 2D animation production, an automatic shadow generation algorithm based on gray histogram feature segmentation and edge contour feature extraction is proposed, and the image processing model of 2D animation is constructed. The edge contour feature of 2D animation image is extracted, and the gray pixel value fusion and difference feature extraction are carried out in the process of shadow automatic generation by using depth learning algorithm. The shaded area of 2D animation image is calibrated by the regional grid segmentation, and the multi-scale Retinex color feature component of 2D animation image is extracted by using Radon scale transform, and the gray histogram of shadow region of 2D animation image is constructed. The simulation results show that the shadow can be generated automatically by using the algorithm, the shadow expression ability of the image and the quality of the output image are better. The normalized correlation coefficient of shadow region is high, which shows that shadow generation is effective.
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Abstract—In order to improve the ability of 3D virtual reconstruction and recognition of motion behavior features, human motion behavior features are extracted and segmented. A motion behavior feature segmentation algorithm based on intelligent vision analysis is proposed. The motion behavior feature image is collected and analyzed under multimedia vision, and multi-scale Retinex corner selection is carried out for the acquired motion behavior feature image. The method of 3D dynamic tracking recognition is used to analyze the dynamic image of motion behavior feature, and the histogram distribution feature fuzzy learning method is used to realize the 3D dynamic tracking recognition of motion behavior feature. The motion behavior feature segmentation is realized by analyzing the dynamic characteristics of the motion behavior feature combined with the three-dimensional motion manifold feature. The simulation results show that, this method can improve the intelligent judgment and detection ability of the moving image, and the feature expression ability of image segmentation is strong, and the performance of template matching is better.
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Abstract—The process of integration of the army and the people faces two obstacles, the first one is geographically scattered niche markets in which military enterprises have been built, and the second one is unqualified technology and standard, as well as dispersed key technology mastered by small enterprises in different areas. Therefore, based on the Internet era and economics literature, the central government was proposed to build an intranet platform for military enterprises’ products and a collaborative innovation platform for private and military enterprises’ products.
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Abstract—For the rail head wear detection, the feasibility of collecting rail images by CCD camera is analyzed. MATLAB image processing technology is used to establish the calculation model of rail wear measurement. By using the methods of edge detection and image filling, the key problems of rail image positioning are studied. The results show that the rail abrasion image detection system can get the rail abrasion accurately in real time under the condition of non-contact. The method can calculate the rail wear more accurately and provide a reference for the loss prevention of the rail and the development of new detection technology.
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Abstract—In order to solve copyright protection problems of cloud database, watermark can be added with information hiding in network environment. It can take advantage of chaos random public key cryptography to produce different public and private keys, through the controllable factors associated public key to detect the watermark information, which can protect intellectual property rights of cloud database, avoiding leakage of watermark key information.
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Abstract—Co-link analysis is an important method in link analysis. This paper attempts to research the categories of video websites with an alternative method of co-link analysis, called URL co-occurrence analysis. In the research, hierarchical cluster analysis and multidimensional scaling analysis are used to study the competition situation. Results show that the video websites in China can be divided into 4 -layer gradient websites. Overall, some comprehensive websites hold the most share of the market and characteristic websites highlights the market and small websites coexist at the same time.
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Abstract—With the development of virtual reality technology, a variety of virtual models have sprung up, and it has been proved that the application of these virtual models to consumers and real estate enterprises have brought tangible benefits. For real estate companies, VR virtual templates are built cheaply and efficiently. For consumers, virtual model can be based on the real size of the reduction of production, consumers no longer need to be based on the plan effect of three-dimensional modeling. It takes only a few minutes of smart device experience to know the room. At present, the virtual home Improvement system concentrates on Unity3d engine, uses 3Dmax modeling software to do model and interior furniture models, and realizes the virtual decoration system with VS2015 as the script development environment, mostly limited to tour, poor interactivity, and mainly through mouse keyboard to realize interaction. The UE4 engine is more powerful in this paper, as a result, the application of virtual home decoration needs a large number of models, more material, amd large amount of data, and Unity3d for large data applications do not apply UE4 's powerful lighting and physical rendering system so that processing data faster, and picture effect being more perfect.
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Abstract—In order to meet the requirements of information and office automation, a set of meteorological technical equipment management system is developed, which can be used to directly query, modify, add and browse various instruments and equipment data in the warehouse. The establishment of the system has improved the efficiency and reliability of meteorological technology and equipment management.
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Abstract—Cybercrime is growing rampantly around the world, which has caused huge monetary damages in recent years. One of the major difficulties in cybercrime forensic analysis is to identify relevant digital evidence from a large amount of electronic documents. Traditional methods, such as manual inspection and keyword searching, are no longer effective both in terms of time and accuracy. In order to reduce the cost, save time and improve the accuracy of forensic investigation, the paper proposed a predictive coding scheme to study and identify relevant digital evidence. The experimental results show that the predictive coding based on semantic searching is feasible, and more efficient and accurate than the keyword searching.
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Abstract—The concept of (strong) homomorphisms of lattice-valued fuzzy finite automaton is introduced, and related properties are investigated, homomorphism theorem is discussed. Eventually, the notions of admissible relation on A and kernals of strong homomorphisms are introduced, and their related properties are studied.
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Abstract—This paper analyzes the ARP protocol and its operating principle, as well as the current protection method for ARP spoofing attacks to understand their defense and detection features. To study the principle of realization and complexity for these methods, and summarize their proper environment, strength and weakness, based on the WinPcap research, this paper mentioned this Dynamic Trust Model of ARP Real-Time Intrusion Detection based on Extended Subjective Logic(DTMARID-ESL). This model introduces Jøsang’s Subjective logic to detect ARP Intrusion behavior, and extend its subjective logic to solve and detect ARP intrusion’s dynamic trust problems, including basic elements such as base rate and un-certain factors, etc.) and dynamic evaluation from time and space. The simulation results show this model has high accuracy and efficiency.
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Abstract—This paper has firstly introduced big data services and cloud computing model based on different process forms, and analyzed the authentication technology and security services of the existing big data to understand their processing characteristics. Operation principles and complexity of the big data services and cloud computing have also been studied, and summary about their suitable environment and pros and cons have been made. Based on the Cloud Computing, the author has put forward the Model of Big Data Cloud Computing based on Extended Subjective Logic (MBDCC-ESL), which has introduced Jøsang's subjective logic to test the data credibility and expanded it to solve the problem of the trustworthiness of big data in the cloud computing environment. Simulation results show that the model works pretty well.
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Abstract—Needle spacecraft test system development present situation, the through the test of the concept of flexible test system architecture, from the test requirements of manned spacecraft, standardization, extensible architecture of software and hardware as well as means of standardized test resource description, spacecraft oriented product test and measurement solutions are put forward.
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Abstract—This paper focuses on estimating confidence intervals for statistically differences among datasets with semiempirical likelihood. This method is designed dedicatedly for those medical research applications that the exact data distributions are semi-linear and, as well as missing data, or the incomplete data. Our experiments showed that the proposed approach works well on distinguishing the structural differences between, for example, the malign cancer and the benign breast one.
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Abstract—The speed of the vacuum switch opening and closing speed indicates the speed of the vacuum switch opening and closing process as a whole. Its size can directly affect the recovery strength of the medium after the arc and the degree of opening and closing bounce. This paper mainly introduces a method for detecting the opening speed using a linear displacement sensor. This method can successfully detect the opening speed of the vacuum switch, which lays a technical foundation for the study of the mechanical parameters of the vacuum switch.
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Abstract—Intelligent combat simulation needs the scenario of intelligent simulation to support the operation. How to formalize the complex network link relationship between intelligent combat entities and support intelligent combat simulation is a difficult and important research domain. After analyzing the structure composition and the formalized description of the intelligent simulation, the formalized description optimization research is carried out aiming at the four problems existing in the scenario of intelligent combat simulation. This research has been applied in the design and implementation of a simulation system and achieved good results.
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Abstract—A joint 2-D angle estimation algorithm based on TDOA is proposed in this paper for multi-antenna system, which can solve the problem of using it in tracking system, such as limited estimation accuracy and inapplicability of wideband signals. Based on the principle of least squares, this algorithm comprehensively utilizes multiple baseline measurements to perform iterative calculations, which effectively improves the estimation accuracy and does not require ambiguity solving.The CRLB and RMSE expressions of the algorithm are derived. Also the angle measurement performance of the algorithm is discussed. Simulation results verify the correctness and effectiveness of the algorithm. The algorithm takes into account both the estimation accuracy and the algorithm complexity, and the angle estimation accuracy is close to CRLB.
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Abstract—Image noise plays a vital role in digital image processing. However, in some specific application scenarios, random noise has an uncontrollable effect on digital image processing. Besides, a large number of hyper parameters which need to be fine-tuned can lead to inefficient projects. Therefore, we propose a Image Noise Level Classification(INLC) technique for specific application scenarios by comparing image quality assessment(IQA) methods, fitting curves and designing two neural networks. For low-accuracy, we come up with a soft way by setting a tolerance rate to achieve a higher acceptable accuracy. Experiments show that our INLC is more accurate and efficient.
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Abstract—In order to reduce the impact on complex information, a comprehensive knowledge base is of great urgency to be constructed and the knowledge needs to be hosted on the question-answering robot. A new kind of knowledge base -Association Map is constructed, which is based on human'sassociation of entities and associate related entities. And thispaper shows the application of the knowledge base in knowledgeretrieval and reasoning of question-answering robot.
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Abstract—With the information processing technology changing from “computation-intensive” to “data-intensive”, “Memory wall” is becoming a problem which cannot be ignored. Near-data processing (NDP) architecture becomes an effective means to improve the performance of the system and reduce the energy consumption. However, due to the reason that the NDP model has no standard programming mode, it is still difficult to reasonably allocate the place of instruction execution in NDP architecture to improve the computational performance is still a difficult problem. In this paper, we propose a global-sensitive mechanism to intelligently partition NDP instructions by combining instruction characteristics with data locality. The experimental results show that the proposed mechanism can successfully cover the amount of data intensive application, and achieves performance improvement up to x1.4.
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Abstract—We consider a deep reinforcement learning based Spinal code transmission strategy to reduce resource consumption and improve channel utilization while guaranteeing communication quality in long-distance free space optical (FSO) communication. First, a deep Q network is established to model the channel state-action value function, and then the neural network approximation value function is trained so as to determine the number of Spinal code symbols that should be transmitted for effective communication under current channel conditions. The final simulation results show that compared with the basic spinal code transmission mechanism and the adjustment algorithm based on linear filtering, the average throughput of the system using the proposed algorithm is improved by 26% -34%.
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Abstract—To figure out the shortage of traditional fault diagnosis method, the paper carried out fault diagnosis and forecast by detecting abnormal data based on LS-SVM algorithm. SVM has the optimal solution and good generalization ability in small samples and can avoid falling into local minimum. The paper introduced the principle of SVM, made up the model of non-linear least squares support vector regression solve various breakdowns coexist of actual circumstance, then identified and prognosis abnormal data by using high- dimension feature vector space as the input of LSSVM. Examples showed that abnormal data could be detected effectively. The results proved that the model of fault diagnosis and prediction effective and has higher rate of correct judgments.
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Abstract—In this paper, according to the technical requirements of the asynchronous motor drive system for electric vehicle, the motor model of the asynchronous motor in the synchronous rotating coordinate system is derived, and the vector control scheme of the rotor flux indirect orientation is presented, and A set of simulation system based on MATLAB / Simulink and a set of test platform of asynchronous motor for electric vehicle based on TMS320l28335 are developed, and the dynamic and static performances are carried out. Simulation and experimental results show that the scheme can obtain good dynamic and steady state control effect.
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Abstract—In this paper, a class of time-varying descriptor system with uncertain parameters is investigated based on the analysis method of linear matrix inequality. By constructing Lyapunov functions, the problems of robust stabilization for the system are analysed, and sufficient conditions of robust stabilization are obtained. When actuator failure occurs, the robust fault-tolerant control for the system is also discussed, considering the cases where the state vector can be fully observed and cannot be directly observed.
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Abstract—The ultimate purpose of the accumulation of scientific and technological achievements is to form a product industrial chain. The products in the laboratory stage can only be used as technical experience, not bring high profits. Only by assigning the products to the market value can bring company and the country new profit growth points and generate income. In view of the weak sensor core industry in China at present, this paper puts forward the development mode of power sensor industrialization from the perspective of electricity, and forecasts the input-output efficiency ratio of the mode development by using the data envelopment analysis method, and comprehensively evaluates the development trend of power sensor industrialization in recent years. Through the analysis and calculation results of this paper, it has a strong guiding significance for power enterprises in sensor industry planning[1].
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Abstract—The application and reward of electric power scientific technological achievements has been regarded as an important indicator of the year-end assessment of enterprises and departments, which plays an important role in the development of enterprises and personal career. Therefore, enterprises pay special attention to the application, and spend a lot of human and material resources to focus on the work of application and reward every year to the end of the year, with low efficiency and effectiveness. Under this demand, this paper puts forward an efficient way to extract the key content of scientific and technological achievements. Through the series of operations of de duplication, classification, integration and extraction of achievements, the key extraction of the accumulated achievements of the enterprise in the same year can be realized. It can quickly grasp the key direction of the centralized development of the enterprise, package multiple high-quality scientific and technological achievements into prize materials, and highly integrate the advantages.Fully reflect the strength and development of enterprises, there can achieve the best results in the process of award-winning[1].
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Abstract—In view of the development status of the evaluation system of scientific, this paper proposes an algorithm based on the weighted Dijkstra classification path model. It takes the existing scientific and technological achievements as the model input, obtains the classification and division of scientific and technological achievements. According to a variety of criteria, determines the comprehensive index data of the core nodes according to the newly generated data set of scientific and technological achievements, and takes it as the evaluation reference data, performance rating of each scientific and technological achievement. The whole evaluation process is carried out in a standardized, standardized and automated software environment, with high efficiency and accurate data results, which will become a popular method in the evaluation system of scientific and technological achievements[1].
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Abstract—This paper considers a parallel algorithm for Cholesky factorization on account of PBMD. Compared with the traditional data distribution for matrix-vector multiplication computation, the algorithm proposed incurs strictly less communication overhead and improves the load balancing. Experimental results demonstrate that the PBMD based matrix-vector multiplication computation makes the implementation of Cholesky factorization easier and enhances performance effectively.
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Abstract—To improve the objectivity and scientificity of weighting the evaluation index, the grey clustering weighting of expert group based on information entropy is introduced to weight the evaluation index. The actual example on flight training airspace environment safety indicates that the method can weight the evaluation index, and shows good operability and logicality.
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Abstract—In order to improve the safety level for avoidance collision, a wavelet neural network safety evaluation method of airspace environment is proposed for military flight training. In the method, the airspace environment safety evaluation index system is first established for military flight training, and then wavelet neural network is introduced to establish the problem of airspace environment safety evaluation for military flight training. The actual example shows that the proposed method has a good evaluation result for airspace environment safety evaluation.
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Abstract—This paper proposes a new experimental system for the pointing error analysis of Photoelectric detection mechanisms. The system using embedded system technique to implement the Semi-Parametric Model algorithms to analyze the Pointing Errors rapidly and automatically, which can quicken the signal and data analysis procedure and make the control system highly integrated.
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Abstract—The research on the characteristics of vacuum arc plays an important role on development of vacuum circuit breaker. In this study, an improved MHD of supersonic vacuum arc was established. The model took the actually flowing status of supersonic vacuum arc into account. The influence of contactor geometry parameters on the characteristics of supersonic was obtained and analysed in detail. It shown that, both of the contactor radium and gap length have impact on the plasma density, ion temperature, electron temperature, plasma pressure and energy flux density on anode surface. The increase of contactor radius and the decrease of gap length result in the homogeneous distribution of the energy flux density. Thus they benefit the improvement of interruption performance of vacuum circuit breakers.
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Abstract —In this paper, combined with depth information and rich texture information in RGB video sequences, a multi-stream behavior recognition algorithm is proposed. The algorithm uses DenseNet as the main network to obtain color texture information, optical flow information and depth information, and uses them as input to the information flow network. Then use LSTMs for feature fusion and behavior classification. Through experiments, the recognition rate on the UTD-MHAD data set of the public action recognition library is 93.88%, which is significantly better than similar algorithms.
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Abstract—The number of basic software products is excessive. If every kind of platform combination and every index of each combination is tested, there exists the problem of combination explosion, and the test cycle and cost increase rapidly. As a scientific and effective software testing method, combinatorial testing uses fewer test cases to detect the effects of the various factors of the software system and their interactions on the system effectively. It has been proved by practice that it has high error detection ability. In order to meet the test requirements with the minimal test case, this paper presents a test case set reduction method based on ant colony algorithm. Through abstracting each test case as an independent node, constructing virtual ant colony and updating the pheromone, the method is verified by the instance at last. The experimental results prove that the method is feasible and effective.
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Abstract—This paper describes how PaaS secures the containers that host application instances on Linux generally. It provides an overview of container isolation and container networking, describes how PaaS administrators customize container network traffic rules for their deployment, and describes how PaaS secures containers by running application instances in unprivileged containers and by hardening them.
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Abstract—The method of phase synchronization (PS) of chaotic is applied and the difference of electroencephalograms (EEGs) recorded from lie detection (LD) experiment between the truth and the lying responses from the two kinds of subjects is explored. In this study, the LD experiment based on the standard three stimuli protocol was designed to gather information of the twenty subjects’ EEG. Phase Locking Value (PLV) was used as a statistical measure from PS for the aim of few stimulus in LD experiment. Experimental result shows first a specific spatial and temporal disparity in PS that guilty group has a stronger /higher PLV than innocent group. In particular, the result of pattern recognition---high accuracy is up to 88%. It is concluded that functional connectivity network for lie detection can help to collect more insight into the deception process. Therefore, PLV can be considered to be a valid method to identify deception and guide us to understand cognition processing with connectivity network of lie.
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Abstract—The modeling and simulation of transporting elderly posture of a new multifunctional elderly-assistant and walking-assistant robot(EWR) considering the elderly falling angle are investigated in this paper, which introduced by the authors lab to assist the elderly for doing the daily activities Satisfactorily. The elder was modeled as a double inverted pendulum one is the elder head and second is the elder body. The elder muscles are represented by a rotational spring and rotational damper which used to connect the double inverted pendulum. Mass-Spring-Damper system was used for robot modeling. MATLAB simulation is used to analyze the vibration characteristics when an outside disturbance is applied as input for the wholly system. Simulation results prove the stability of the elderly-robot system and show the ability of robot to prevent the elderly from falling.
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Abstract—In recent years, smart grid has gradually become the common development trend of the world's power industry, and its security issues are increasingly valued by researchers. Smart grids have applied technologies such as physical control, data encryption, and authentication to improve their security, but there is still a lack of timely and effective detection methods to prevent the grid from being threatened by malicious intrusions. Aiming at this problem, a model based on machine learning to detect smart grid DoS attacks has been proposed. The model first collects network data, secondly selects features and uses PCA for data dimensionality reduction, and finally uses SVM algorithm for abnormality detection. By testing the SVM, Decision Tree and Naive Bayesian Network classification algorithms on the KDD99 dataset, it is found that the SVM model works best.
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Abstract—In a microgrid-connected system, under the condition of the unbalance of the grid, the output power of the virtual synchronous generator (VSG) will oscillate at twice the grid frequency, and the three-phase output currents will produce the unbalanced fluctuations, which will seriously affect the stable operation and safe of the power system. In this paper, a control strategy of a microgrid-connected system based on VSG is proposed. Firstly, the control command expressions under different control targets are obtained by analyzing the operation of VSG under the unbalanced grid voltages. And then, an improved VSG control structure is designed based on the traditional VSG control structure. Finally, the negative sequence current obtained by the control structure is added to the positive sequence current obtained by the traditional VSG control system to gain the SVPWM (space vector pulse width modulation) control signals, thus implementing the control of the microgrid-connected system. The results obtained show that the strategy can effectively improve the output power quality of the system under the condition of unbalanced grid voltage, and does not depend on the type and cause of the unbalance of the grid voltages, and the voltage source characteristics of VSG are not changed. Furthermore, the control system has fast response speed and both the structure and the instruction current calculation method are simple and efficient.
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Abstract—This paper presents a novel cooperative grasping wheeled wall-climbing robot with the ability to climb concrete, brick walls using tracked-spines arrays located around the track. The robot uses a combination of the crank-link mechanism and gear transmission to control the tracked spines on both sides of the robot to grasp the asperities. The kinematic and dynamic analysis of the crank-link mechanism and the simulation demonstrate that the motion state of the robot is stable in the climbing process. By means of wireless communication, the control information is transmitted to the main controller, which drives the motors to make each mechanism work together. Finally, the prototype is fabricated and several experiments are carried out to verify the climbing performance of the robot.
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Abstract—For given a single input and output controllability or observability linear control system, one can transfer it to a canonical form. In this paper the authors consider an inverse problem of above theory. That is, for given a canonical linear system, we construct a new linear polynomial system which is algebraicly equivalent to the canonical one. Its observability/controllability matrices as well as the associated generalized Bezout matrix are studied. Meanwhile, some analogous expression formulas of the generalized Bezout matrix in terms of the new observability and controllability matrices are obtained.
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Abstract—The GPS signal is interfered unintentionally or manually, which leads to the GPS failure. It will cause the position error reported by the aircraft, making the pilots lose situational awareness. As a result, it will lay a great hidden peril for flight safety. In this study, the GPS signal loss analysis was carried out by using the QAR data to accurately capture loss location and period information of the signal. By displaying the analysis data on the electronic map, keeping consistent with the flight route of the aircraft, and using the longitude and latitude coordinate information of the map, it can effectively improve the efficiency and timeliness of manual patrol signal interference detection and reduce the potential safety hazards of civil aviation flight.
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Abstract—In order to solve the problems of sensor installation and measurement noise, a single-phase LCL photovoltaic grid connected inverter control strategy based on state observer is proposed. Firstly, the Luenberger state observer is designed for the single-phase LCL grid-connected inverter. Then, based on the observed values of the state observer, the double-current loop control structure is designed. The inner loop of capacitor current is used to realize the active damping of LCL filter, and the outer loop of grid-connected current is used to realize the zero-error tracking of gridconnected current. Finally, the effectiveness of the proposed control strategy is verified by simulation and experiment.
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Abstract—Power factor depends on the circuit parameters. Too low power factor will cause a series of problems, so it is important for the development of the national economy to improve the power factor of the power grid. In this paper, the method of improving power factor is designed and verified by Multisim simulation software. It will be great help to understand the method and significance of improving power factor.
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Abstract—This paper introduces the circuit design of voltage-controlled color changing lamp based on Multisim. The circuit mainly comprises the reference signal generating circuit and voltage comparator. With Multisim software simulating and debugging, the simulation results show the circuit function can be achieved.
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Abstract—The number of vehicles has increased dramatically, with the continuous expansion of vehicle production scale. This paper designs and implements a parking lot management system, which solves the problems of parking difficulty and complex vehicle management. Compared with the previous system, the administrator can check the parking space and vehicle information at any time, which greatly reduces the workload. The driver can not only check the parking information of the nearby parking lot, but also book the parking space by selecting key words. At the same time, this paper analyzes the complexity of different path guidance algorithms, considering the different real-time requirements of the map in the parking lot and off-site path guidance, and finally uses Dijkstra algorithm based on heap optimization and Floyd algorithm to realize the parking space navigation, which greatly reduces the time for the driver to find the parking space.
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Abstract—In UWB wireless indoor positioning, due to the influence of the indoor environment, the ranging error is often very large. In order to eliminate the influence of these environmental factors as much as possible and improve the accuracy of indoor wireless location, an indoor positioning optimization algorithm combining genetic algorithm and RBF neural network(GA-RBF) is proposed in this paper. We use genetic algorithm to find the optimal parameters of RBF network, so as to give full play to the advantages of RBF neural network for fast and high precision approximation. A large number of sample data are used to train genetic RBF neural network, the experimental results show that the positioning error of this algorithm is within 10cm, which can achieve a high positioning accuracy in the not line of sight (NLOS) environment. Compared with the traditional RBF neural network algorithm, its optimization performance has been greatly improved.
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Abstract—After uploading the user ID data and ECG data to the cloud platform data center by the use of Intelligent Cloud health detector, this paper describes how to generate the image of user or ECG, in order to meet the display and use of the onstage website and mobile phone APP.
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Abstract—Real-time is an important index of fabric defect detection. The optimal selection of Gabor wavelet is an effective method to solve the problems of data redundancy and low operation of multi-channel Gabor wavelet. In this research, several kinds of Gabor wavelet optimal selection detection algorithms commonly used in fabric defects are summarized. And these algorithm ideas are analyzed. According to the characteristics of fabric defects in actual production, a new optimal Gabor wavelet algorithm, Defect Direction Projection Algorithm(DDPA) is proposed. Last but not least, the operation speed and detection accuracy performance of six optimal selection algorithms are compared. The experimental results show that the proposed algorithm has certain advantages of performance and application.
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Abstract—The emergence of big data technology makes the dissemination of online advertising not only rely on design and media, but firmly combine data, users, platforms, businesses and even industries, so as to promote the continuous update and development of the advertising industry towards the direction of information and technology.This paper constructs an accurate online advertising delivery system based on big data technology, analyzes the core issues of online advertising delivery under the technology of big data, and expounds the connection between media, data, users and platforms, as well as the realization logic of accurate online advertising delivery, so as to provide reference for relevant researches on online advertising delivery.
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Abstract—Most of the traditional remote sensing image change detection adopts the band ratio method and the image difference method. This type of method is simple to operate, and only the image pixel difference value and the band ratio value are used for calculation, and the detection accuracy cannot be guaranteed. Aiming at this problem, this paper proposes a kind of spectral product-based fusion algorithm based on algebraic weighting. The algorithm combines the ratio image and the difference image, and then selects the Ostu algorithm to iteratively calculate the fusion to extract the image change region. The experimental results show that the detection accuracy of this method is better than the traditional change detection method, and it has certain stability and intelligence.
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Abstract—With the shift in storage paradigm, there is anincreasing need for privacy of dataset and also for an encryption scheme that permits computation on encrypted data. Paillier cryptosystem is a good example of such a homomorphic encryption scheme. To improve the efficiency of the Paillier homomorphic encryption scheme in terms of its decryption speed and overall computational cost, we propose an improved decryption process. Specifically, the inclusion of a variable k to reduce the modular multiplicative arithmetic. The variable k is combined with the L function and CRT recombination method, to arrive at a fast and improved decryption process, showing the mathematical correctness of the decryption algorithm. Experimental results validate that our scheme is significantly efficient in its decryption speed.
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Abstract—Since the polar radius of an elliptic ring uniformly charged is not a constant, it is extremely difficult or even impossible for us to obtain the analytical function of the spatial electric field distribution of the elliptic ring uniformly charged. Using the computer simulation and the analytical method we present the spatial distribution of the electric field of a uniformly charged elliptic ring, revealing the characters of the field spatial distribution of a uniformly charged elliptic ring.
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Abstract—In order to solve the shortcomings including the sending and receiving high delay, the high memory utilization and the high CPU(Central Processing Unit) utilization of the traditional airport scene monitoring system data, several kinds of data communication in the airport scene monitoring system are illustrated. Besides, the mechanism of non-blocking communication of airport data based on dynamic thread pool is researched, and the parameters of the data sending and receiving delay time, the memory utilization of and the CPU utilization are analyzed. By comparing some communication methods including single-thread communication, multi-thread communication and dynamic thread pool non-blocking communication, the related theory is verified by programming. By the experiment results, the non-blocking data communication mechanism based on dynamic thread pool can be applied to the data interaction of the related airport systems with less data delay time, lower CPU utilization and lower memory utilization.
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Abstract—Internet of Things (IoT) enables information sharing among massive small and cheap wireless devices. However, the secret key sharing process in massive IoT applications becomes more challenging due to the low latency communication requirements and resource constrained IoT devices. To adress those probelms, we propose a physical layer secret key sharing scheme for MIMO (multiple-input-multipleoutput) IoT applications, which can realize secret key sharing with communication simultaneously. This is because the information of secret key is attached in the combination of the activated/non-activated parallel sub-channels of the legitimate receiver, which is created by SVD (singular value decomposition) of the MIMO channel of the legitimate receiver. Consequently, the legitimate receiver can accurately obtain the shared key and demodulate the communication data with an arbitrary low key BER and BER (bit error rate). The simulation results verified the validity and security of the proposed scheme.
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Abstract—This paper summarizes the research progress of convolution neural networks in the field of target detection in recent years. The development of these convolutional neural networks makes the development of deep learning to a new level. On the basis of consulting data, this paper summarizes the main network structure and working principle of convolutional neural network application in the field of target detection, and focuses on several commonly used convolution neural networks, including AlexNet, VGGNet, GoogLeNet and ResNet, and analyzes their technologies, analyzes their network structure characteristics, and summarizes their respective advantages and disadvantages. And in the last part, it points out the current research situation and the future development direction.
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Abstract—At present, the most natural language processing tasks use common data sets for experiments. However, as the concept of domain knowledge graphs is proposed, domain-based data sets have gradually become a demand. In this article, we collect data from various travel websites and official websites of tourist attractions, and use this to build a question and answer data set. At the same time, we also introduce the current Bert model with outstanding effect in the nlp field, and use this model to conduct experiments in the travelling question and answer data set. The experimental results not only show the feasibility of the constructed tourism data set, but also lay a foundation for the subsequent construction of a knowledge question answering system for tourism knowledge graph.
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Abstract—Compared with traditional databases such as Oracle database, SQL Server database and MySQL database, Dameng database is a domestic database with independent intellectual property rights. Combined with the security management of Dameng database and the requirement of database audit, this paper designs the security configuration baseline of Dameng database. By designing the security configuration baseline of Dameng database, the audit work of Dameng database can be carried out efficiently, and by analyzing the audit results, the security configuration baseline of Dameng database can be improved.
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Abstract—Time series forecasting is a subjective or intuitive expectation of the future events. It can use the collected historical data and mathematical models to measure future things in order to understand the process and results of things in advance. In this paper, a time series forecasting framework based on grey system and sparse linear regression is proposed. In some applications, the number of data samples are very limited, while the number of features can be tremendous. Thus, to prevent overfitting, an appropriate feature selection method is needed to select only most related features and fed them into machine learning algorithms. The grey system is utilized for feature selection in this paper due to its ability to generate and extract useful information from uncertain systems with partially known information. Then sparse linear regression model and artificial neural network are implemented for the purpose of forecasting. The proposed framework was validated using the actual Gross Domestic and agriculture production dataset. The results have shown a very promising prediction accuracy.
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Abstract—Broad learning system is well applied in hyperspectral imaging sensing and analysis with its theoretical simple, fast, and good generalization performance. However, the conventional broad learning system only uses the spectral information of the hyperspectral image when classifying the hyperspectral image, so that it cannot achieve high classification accuracy. To solve this problem, we propose a spatial-spectral composite feature broad learning system classification methods (BLSCF). First, we combine the spectral and spatial features of the hyperspectral image as composite features, Then, the composite feature is combined with broad learning system. BLSCF inherits the advantages of BLS and can be used directly for multi-class tasks. We perform experiments on three hyperspectral images. The experimental results show that the algorithm proposed in this paper can effectively improve the classification accuracy of hyperspectral images and outperforms current state-of-the-art algorithms.
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Abstract—A residual hypothesis test algorithm (RHTA) for hyperbolic localization in mixed LOS-NLOS environments is proposed in this paper. The residual, referred to as the difference between the initial and the improved position estimate presented by CHAN’s algorithm as a well-known estimator for hyperbolic location, is selected as an object of hypothesis test to distinguish line-of sight base stations (LOSBS) from non-line-of-sight base stations (NLOS-BS) without any prior information about NLOS measurements. Then, localization can proceed with only the LOS-BS. The Monte- Carlo experimental results show that RHTA can greatly mitigate the positioning error caused by NLOS, and the root mean square errors (RMSE) of RHTA follows the Cramer-Rao Lower Bound (CRLB) at low noise level.
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Abstract—In view of the problem of “information island” caused by the lack of collaborative management of application software in the current design and manufacturing process of ship shop, this paper puts forward a scheme of building application collaboration of ship shop design and manufacturing on the basis of private cloud platform. All kinds of resources needed in the whole life cycle of ship design and manufacturing are packaged together. Ship design and manufacturing units distributed in different places connect the private cloud platform, utilize the design and manufacturing resources on the cloud, realize business collaboration between design and manufacturing applications, and make the seamless flow of design and manufacturing data through.
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Abstract—We proposed an algorithm for broadband signals which provide minimum variance distortionless Response(MVDR) on data reconstruction. The output of different array elements at the same time is taken as the sampling of the continuous line array based on the sampling theorem, and the data of the time domain is re-sampled. The method is used to estimate the azimuth of the broadband coherent source and a method of obtaining the focus error is proposed to analyze the performance of the MVDR algorithm of the broadband coherent source. We compared the computer simulation of the FFT interpolation method and data reconstruction method of the azimuth estimation. Results show that data reconstruction method for the broadband MVDR algorithm, has better resolution probability and lower RMS error than the FFT interpolation method.
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Abstract—Rough set theory has long been applied to the formulation and induction of rules. Rough set theory approximates a rule through three regions (positive, boundary, and negative region), uses the rule boundary as the limiting condition, and uses the rough set to build a model for decision-making. In this case, the decision cost needs to be considered. Based on this, we will propose an optimized simulated annealing algorithm (OSAA), which is an optimized algorithm for minimizing cost attributes. The algorithm proposes a heuristic method combined with a coarse-grained parallel algorithm to solve the DTRS optimization problem. We combined the optimized simulated annealing algorithm and the adaptive learning method to design an experiment. The experiment compares the running time and decision-making cost, and experiment shows the proposed new method has higher efficiency and lower cost.
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Abstract—Sharing parking is a core content in the sharing economy. However, for electric vehicles (EVs), parking is not only a matter of renting price and parking time, but also a matter of battery charging. Moreover, when there are multiple parking lots, the competition between them should also be considered. In order to solve these problems, this paper proposes a new framework of multiple shared car parking units. This framework considers the charging optimization of EVs in demand side management and electricity market optimization of parking units. The electricity market structure is binary market structure, which is more complex and popular. The numerical study demonstrates that the proposed framework and models can not only optimize the electric costs of the cars but also the costs of the units.
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Abstract—The smart grid is an upgraded power network that integrates advanced metering infrastructure to provide seamless two-way communication between consumers and suppliers. Many researchers have proposed solutions to confidentiality, integrity, and authenticity in uplink transmission, but there are few pieces of literature on the security of downlink multicast communication. In this paper, we first introduce a new cryptographic concept called identity and policy based signcryption (IPSC) scheme. Then we give a concrete IPSC scheme, and prove the proposed scheme is IND-CPA secure under the DBDH assumption and UF-CMIA secure under the ECDL assumption. Finally, we present a secure and efficient smart grid downlink transmission framework by exploiting our IPSC scheme, which can ensure origin non-repudiation, data confidentiality and integrity, and can also provide fine-grained access control on downlink multicast information.
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Abstract—Personal safety is the most important part in power grid safety. Personal safety accidents of power grid happen frequently. Most of personal safety accidents are attributed to violation. This paper aims to prevent violation and designs the intelligent identification method of personnel violation in substations based on deep learning. The substations remote video monitoring system is used to detect and collect personnel behavior in substations. It is transported to image processing identification unit in different channels to do intelligent identification for violation.
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Abstract—Devices and their faults increasingly bring a great difficulty to grid operators. In order to solve troubles caused by equipment fault diagnosis, this paper conducts a research on the intelligent image recognition and diagnosis technology of key external insulation devices based on deep learning.
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Abstract—Distribution transformer noise is one of the main factors affecting residents near substations. Studying the relationship between vibration and sound radiation characteristics of tank wall surfaces of typical distribution transformers is of great significance for corresponding noise and vibration control. In this paper, field measurements are conducted to study the coupling between tank wall vibration of 35kV and 110kV distribution transformers and their corresponding near-field and far-field sound radiation. Results show that, vibration and noise radiation of two typical surfaces of distribution transformer are mainly concentrated between 200 Hz and 500 Hz. Coherence between vibration and sound signals proves the strong coupling between the tank wall vibration and noise radiation of distribution transformers.
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Abstract—With the rapid development of the intelligent power grid, the intelligent identification technology of the substation equipment faults also becomes more important. In this paper, the intelligent identification method of the substation equipment faults based on deep learning is designed. Alex Net and Dense Net of the two-channel network's convolutional neural network is used to conduct the intelligent identification for fever faults of power transformation equipment to do intelligent identification, so as to confirm the fever temperature and position of the equipment. This method helps a lot to overhaul fever faults for the substation equipment.
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Abstract—With the construction of the intelligent substation, it is more important to realize data management power transformation in intelligent substations. In this paper, a data management and decision-making method of the intelligent substation system is designed. Such method manages the system configuration documents (SCD) in the intelligent substation. Through the SCD content change of the online monitoring intelligent substations, an assistant decision-making method is provided.
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Abstract—When we solving the scheduling problem of stacker, the commonly used Genetic Algorithm (GA) requires a large initial population size and the convergence speed is slow when the number of iterations is high. A better solution can be found, and it is easy to fall into the local part. The ICRO algorithm proposed in this paper not only has a good global optimization, but also has a stronger ability to jump out of the local optimum, it can improve the convergence speed of the algorithm, so it can effectively improve the scheduling optimization of inbound and outbound for double-stackers.
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Abstract—To improve the running efficiency of automated warehouse, numerous enter prices adopts the warehouse layout model which uses double-stackers on monorail with two I/O station. For the problem of double-stackers scheduling, the anti-collision principle is taken as the basic principle and the required operating time of two stackers as the evaluation criteria to present a new scheduling model based on mixed command sequence by analyzing the operating modes of double-stackers in different tasks. On this basis, improved Chemical Reaction Optimization (ICRO) is used to optimize the scheduling path of double-stackers. According to the analysis of simulation, the proposed stacker scheduling model could adapt to the warehouse operating condition and avoid the collision. Meanwhile the optimization algorithm could improve the storage efficiency for double-stackers on monorail with two I/O station model.
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Abstract—To discuss the role of Ontology Matching Algorithm in linguistic features, the application fields of Ontology Matching Algorithm are introduced firstly. Then, the major Ontology Systems and typical Ontology Matching Frameworks are discussed so that the concept of Ontology Matching Algorithm is Clear. Thirdly, to further explore the importance of Ontology Matching Algorithm in linguistic, the Ontology Matching Algorithm based on semantic (Omabos) is Analysed. At last, the Ontology Matching Algorithm based on linguistic features (Omablf) is designed and verified. The results show that the presented Algorithm has good effects. However, any kind of Matching Algorithm always has its drawbacks and is difficult to do well in each aspect of matching. Therefore, in practical applications, Matching Systems are usually synthesized by a variety of different types of Matching Algorithms (element level or structure level), to achieve a good matching effect.
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Abstract—Aiming at solving problems of low signal-to-noise ratio (SNR) and difficulty in de-noising of internal leakage signals of hydraulic slide valves, this paper proposes a denoising method based on CEEMDAN-MI-IncrEn-NLM. First, signals are decomposed by CEEMDAN (Complete ensemble empirical mode decomposition with adaptive noise) approach respectively. Noise signals are distinguished from noise-dominant signals by MI(mutual information) method, and the noise signals are eliminated. Then, IncrEn (increment entropy) is used to distinguish noise-dominant signals and internal leakage signals. Finally, NLM (Non-local means) algorithm is used to filter noise of noise-dominant signals and reconstruct internal leakage signals. Results show that the method in severe noise-contaminated environment can effectively improve regular signals’ SNR around 19 dB at maximum, and it can filter out gaussian white noise while reserving valid signals of internal leakage as well.
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Abstract—Under the condition of satisfying the demand of smelter for ore quality, how to optimize the ore benefit in a certain period is a concerned problem. For a batch of ore, a multi constraint integrated greedy optimization algorithm (MICG)is proposed. According to the ore quality requirements, considering the content of each substance in the batch of ore, each ore is automatically allocated to a specific group, thus improving the sales profit of that batch of ore. Experiments show that the algorithm proposed in this paper has more advantages than artificial optimal grouping, and can guide effectively mining companies to mine ore.
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Abstract—In view of the problem that the random selection of LEACH Routing Protocol cluster head in WSN network will lead to the short lifetime of nodes and network, an e-leach protocol based on energy improvement is proposed in this paper, which optimizes the cluster head selection stage by considering both energy and distance factors, and introduces the average value of node residual energy, and the distance between nodes and base station as weight parameters to the threshold in the probability. A new threshold judgment formula is constructed, and the cluster head node is selected according to it, so that the node which is close to the base station, has more residual energy and less energy change is more likely to become the cluster head. The simulation results show that e-leach protocol can prolong the lifetime of network and nodes, and has better performance.
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Abstract—The regulated power supply (the stabilized voltage supply) is an important device that can provide alternating current (AC) or direct current (DC) to various electronic equipment. At present, it can be used in most electronic devices and instruments. We need to use the direct current stabilized power it provided to make the equipment work normally. The AC power grid provides voltage with the effective value of 220V and the frequency of 50Hz. We need to use the regulated power supply to convert the power into stable direct voltage with a specific amplitude, so that the power can be applied to all kinds of appliances in our life. This paper studies the soft start voltage stabilizing circuit based on the integrated circuit LM317 through the simulation software of Multiuse. The whole power circuit is mainly composed of the transformer, the filter circuit, the rectifying circuit and the voltage stabilizing circuit. This kind of power supply has the advantages of small size, good stability and high cost performance. This paper mainly introduces the principle of the regulated power supply and how to realize it, and further analyses the working principle of specific hardware circuits and specific methods to realize their functions. After many times of simulation in the software, it is found that the power supply designed in this paper has flexible adjustability as well as good control effect. Therefore, this kind of power supply can be more widely used in electronic instruments, measuring instruments, other electronic control circuits and other occasions. According to the results, the function and index of this soft started regulated power supply circuit with the load function can meet the requirements of this experiment.
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Abstract—The Navigation System discussed in the paper can recognize ripe fruit automatically for agricultural harvesting machinery by machine vision technology, and then achieve the purpose of autonomous positioning and navigation through autonomous path planning. In order to achieve this process, agricultural machinery positioning and navigation system must have high precision and fast image processing algorithm. Based on this, this paper introduces the extreme learning machine algorithm into the agricultural machinery navigation system, combined with BP neural network algorithm, through the determination of the image coordinates of ripe fruit and fruit tree, to achieve the rapid navigation of agricultural machinery operation. In order to verify the feasibility of the scheme, the computational efficiency and precision of the algorithm are counted. The experimental results show that the picking efficiency has been improved obviously and the picking accuracy has been improved by using the extreme learning machine, which can meet the design requirements of modern agricultural machinery and equipment.
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Abstract—The realization of an intelligent robot and its motion control system requires a combination of various hardware and software modules such as processors, infrared sensors, motion control, and geomagnetic navigation to accurately control the robot's basic movements and walking lines to avoid movement Robot collision or abnormal state. This paper uses the Windows software operating system, Visual C++, etc. to develop and design mobile robot embedded control programs, application processing modules, and multi-task mechanisms to achieve algorithmic tracking and tracking of mobile robot motion paths control.
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Abstract—With the improving of the intelligent driving awareness, object detection as an important part of intelligent driving, has now become a research hotspot in the world. In recent years, convolutional neural network (CNN) has attracted more and more attention in the field of computer vision. CNN has made a series of important breakthroughs in the field of object detection. This paper introduces the object detection method based on deep learning. This paper mainly introduces the detection algorithm based on regional suggestion and regression, and analyzes the advantages and disadvantages of the detection algorithm and detection performance from two aspects of accuracy and speed. Then, the disadvantages of these detection methods in detecting small objects and the difficulties in detecting small objects are analyzed. On this basis, the public data sets and evaluation criteria related to small object detection are introduced.
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Abstract—The development of the Internet and artificial intelligence has brought a lot of convenience to people's production and life. The rise and progress of the transportation industry means that people's travel efficiency has been improved. Public transportation, as one of the means of delivery, bears the task of urban residents' life. Interactive information design gives birth to intelligent urban public transportation and promotes the development of people-oriented information communication industry to meet people's needs. Based on the characteristics of information interaction, this paper intends to explore the interactive information design of intelligent urban public transportation. From a design point of view, automobiles have evolved from a vehicle to a design object containing personal space, public space and social space. In this context, the human-computer interaction design of intelligent vehicles has become the focus of the automotive enterprises and technology companies at home and abroad.
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Abstract—Control technology, automation and intelligent products are constantly updated, which speeds up the process and promotes the rapid development of society. Although the traditional closed robot controller is simple and reliable, it is only suitable for fixed operation tasks and objects, which can not meet the growing demand of modern manufacturing for diversified products, and the production tasks are constantly changing. Compared with centralized control, distributed control system has greater flexibility and robustness. At present, most control strategies adopted by motion control cards in the market are fixed, so it is difficult for users to use them to study other control strategies. On the basis of studying the open robot controller, this paper focuses on the open robot controller based on motion control card and its related technologies, and analyzes the performance of the control system.
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Abstract—Mobile robots have unparalleled advantages over other types of robots. They can be easily integrated into the daily life and working environment of human beings to help human beings accomplish certain tasks. Everyone in the group has independent decisions and behaviors, but the group has extensive altruistic cooperative behaviors. In the complex multi degree of freedom system, the robot needs to use its own multi-sensor information to identify the changes of external environment and its own state, and adjust its own motion actuator. In different task requirements, the shape of distributed control and the strictness of maintaining the distribution are different, so the requirements of environment are different. Based on automation technology, this paper analyzes the tracking control mode of mobile robot servo system, aiming at the characteristics of many degrees of freedom, high real-time and reliability requirements.
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Abstract—With the increasing awareness of the environment and the gradual popularization of electric vehicles, it is considered that different types of electric vehicles in logistics enterprises have different battery maximum capacity, battery charging rate, unit consumption rate of electricity, maximum load capacity, fixed cost and variable cost. In this paper, considering the factors such as mileage, charging time and delivery time of electric vehicles in practical application, the vehicle routing problem with time windows is studied, the corresponding mixed integer programming model is established, and then the branch pricing algorithm is improved to obtain the optimal solution. In the search process, the penalty factor is added to allow the existence of infeasible solutions and reduce the possibility of local optimization. Then, the accuracy of the model and the results of the algorithm are verified by several sets of examples, and it is also proved that the acceleration process proposed in this paper can effectively improve the solution speed of the algorithm. Finally, the influence of the change of vehicle variable cost on the results is analyzed by examples of different scales.
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Abstract—In order to improve the control performance of permanent magnet synchronous motor (PMSM), firstly, this paper analyses the characteristics of traditional PID controller and PID controller based on BP neural network. Aiming at the problems of large overshoot and weak anti-interference, this paper studies a BP-SSO-PID controller based on spider clustering algorithm to optimize the parameters of BP neural network. Then, by establishing the mathematical model of PMSM and compiling the S-function function block, this paper sets up the speed control model of PMSM based on BP-SSOPID algorithm in MATLAB. The results of experiment are compared with traditional PID controller and neural network PID controller’s results. At last, it proves that the new method can effectively improve the overshoot, improve the response of the system and enhance the anti-interference of the PMSM.
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Abstract—In this paper, the representation and reasoning of uncertainty in the field of tactical intention recognition are analyzed and studied. An intelligent command and control decision support process based on deep reinforcement learning and fuzzy multi-entity Bayesian network is proposed. On this basis, a method of tactical intention recognition based on fuzzy multi-entity Bayesian network is also proposed and probability ontology is constructed. The experimental results show that the method proposed in this paper is feasible and provides a new solution for the representation and reasoning of uncertain information in the field of battlefield situation estimation.
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Abstract—The prevention and control of pitaya fruit is very important. In this paper, the pitaya fruit disease and disease spots are separated from the image to determine the type of pitaya fruit. When considering the image segmentation algorithm, we consider the small difference between the foreground and background of the image, and use the two-dimensional OTSU algorithm with the FCM algorithm for the segmentation algorithm. This paper conducts experiments on the sample pictures of the experimental base. The experimental results show that the improved algorithm has better segmentation effect and accuracy than the similar algorithms, and the edge information is preserved well, which has certain experimental value.
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Abstract—In order to solve the problem caused by the nonstationarity of wind speed sequence in wind speed prediction, an improved CEEMD-FOA-LSSVM model is proposed: Firstly, the standard Complementary ensemble empirical mode decomposition (CEEMD) algorithm is improved to decompose the original wind speed sequence and reduce the end effect. Secondly, calculate the permutation entropy value of each modal component after decomposition, and the sub-sequences are recombined and merged according to the permutation entropy value to obtain multiple new sub-sequences, and the improved Fruit Fly Optimization Algorithm (FOA) algorithm can improve the optimization effect and optimize the Least Squares Support Vector Machine(LSSVM) parameters. Finally, the optimized model is used for predicti on for each new sequence, and the predicted values are combined to complete the model prediction. The simulation results prove that the proposed improved model not only effectively solves the above problems but also improves the prediction accuracy.
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Abstract—If the degree of polynomial is properly determined, the trend surface can be fitted in complex terrain. The trend surface can be fine-tuned by filling the depression. Based on the free flow model, the flow direction is determined. The least square method is used to determine the length of water flow. Finally, the confluence analysis is carried out to generate the river network. The experimental results show that the river network extracted from the complex surface is in good agreement with the actual river network based on the trend surface fitting.
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Abstract—With the continuous progress of the information age, e-commerce, the Internet of things and other emerging Internet areas are gradually emerging. Massive amount of structured data auditing becomes a major issue. Log files and other data can be uploaded to the cloud via the Internet to guard against potential threats. Difficulty now is how to realize the data in the field of data audit query online, interactive and impromptu. There are two main methods of data warehouse, respectively is zhang table reduction method and basic data verification method. In the age of big data, data quantity increases gradually, so that the audit speed, design of the data storage and so on will be more or less problematic. If the audit task is not completed in time, it will result in the failure to store the audit data, which will cause losses to enterprises and the government. This paper focuses on the data cube physical model and distributed technical analysis, through the establishment of a set of efficient distributed and online auditing system, so as to make the data fast and efficient auditing.
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Abstract—Agricultural machinery automatic navigation technology has been widely used at home and abroad and it is an important practice of agriculture intelligent operation. This paper conducts research by combining GPS technology. According to the characteristics of agricultural mechanization, the paper studies GPS at home and abroad, machine vision, and inertial navigation unit, such as the laser navigation positioning sensor research. Considering the existing experimental conditions, the author chooses GPS for navigation and positioning sensors.
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Abstract—The rapid development of the Internet has made social network an important information dissemination platform. Although comprehensive research has been conducted on maximizing social network in the past few decades, users are usually modelled invariably as vertices in the graph, due to the lack of personal user data. However, the simple premises and assumptions ignore the differences between users. In this paper, we propose a diffusion model CMMI based on user preferences and diffusion enhancement. To access accurately user preferences, we propose to integrate user and product interactive information into social network. Then, we raise the issue of maximizing social network influence under diffusion model based on user preferences. Finally, we optimize the influence maximization algorithm. We conduct several experiments to prove the effectiveness of the algorithm on them. The experimental results show the superiority of our proposed algorithms.
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Abstract—With the continuous progress of Internet information technology, cloud computing has come into being. In the cloud computing environment, most applications and data are moved to the huge network data centers of cloud service providers. However, when users outsource sensitive data to cloud services, this raises a number of issues related to data security and access control. Focusing on cloud computing environment based on the weight of attribute more agencies encryption problem, this paper puts forward a cloud computing environment based on the weight of attribute more agencies encryption scheme, and by introducing concept of attribute weights, attributes authority according to the attribute importance for attributes assigned different weights. Attribute weights of attributes can be converted to set. This scheme can reflect the importance of attributes, so it has more practical significance, so as to prove the security and correctness of the cloud computing environment.
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Abstract—In the current situation, the case-based translation method is becoming more and more popular. The advantage of using machine translation is that machine translation does not need to analyze a sentence word by word, but to replace it under the same word meaning in the original language database. When there are more cases, the translation results will be more accurate. This paper mainly studies the case-based machine translation method. In order to find more accurate similarity, some similar cases of the system in the retrieval process. This paper first introduces the current situation of case-based machine translation and the practical problems of the system, and studies the relevant principles of the simhash algorithm and the principles of the simhash algorithm, so as to realize the purpose of the simhash algorithm to quickly retrieve similar cases, and carefully handle the details in the process of using the simhash algorithm, which can reduce the number of similar cases to be retrieved. With the time, the larger the corpus size, the more accurate the results can be brought to the retrieval in the detection. If synonyms appear in the similar situation, the similarity of the two words can be calculated by the above method, and the real similarity can be seen more objectively from the results.
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Abstract—In terms of the current international situation, English is still the most widely used language interoperability many countries. Many people use English as a second language, and even some large international companies, who store their important documents in English, so research in the English language is needed, and one of the most significant research is the English text information filtering algorithm. As we all know, text information filtering is a kind of text information processing technology, including information classification, filtering and other technologies which is the link between text information and computer processing and filtering technology, and can be reprocessed according to the information content of the text. In the process of information processing, support vector machines (SVM) can solve many problems in the process. Generally, the problems such as high sparse dimension of text vector, high correlation between information features, and high sparsity among vectors always exist in text information filtering, while SVM can exactly solve the above problems. According to the feature of SVM for text problems, the center set region is established for positive sample clustering when filtering information, and it is difficult to judge the data and continue to use clustering decision when meeting later, so the accuracy of SVM algorithm in information filtering is improved.
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Abstract—This paper designs a new type of antenna based on square and circular terahertz for short-range communication applications. The square and circular shapes in the antenna radiation patch change the path of the current on the antenna surface. The antenna is simulated by HFSS simulation software. The antenna is a dual-band antenna with a bandwidth of 5 GHz at 190 GHz and a bandwidth of 4 GHz at 230 GHz, the gain of the antenna is 4.1 dBi. The antenna has a simple structure and stable performance indicators. It has certain application value for communication systems and wireless transmission systems operating in the terahertz frequency band.
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Abstract—Conductors of transmission lines are long and have high flexibility, which are obviously influenced by wind loads. The non-uniformity of wind pressure of conductors along the transmission line direction is crucial to the wind-resisting design of power transmission tower-line systems. In this paper, through distributing wind pressure sensors on the whole conductor, the wind load information of the whole conductor is monitored simultaneously. The statistical characteristics and value taking laws of the wind pressure non-uniformity of the conductor are investigated for mean and fluctuating wind, respectively. Results show that by adopting the Generalized Extreme Value distribution model, the probability distribution characteristics of non-uniformity coefficients of mean wind pressure of conductor can be reflected well. The value taking of its probability statistical parameters is stable, which meets ergodic properties of steady-state distribution samples. For the non-uniformity characteristics of fluctuating wind, its spatial correlation coefficient is gradually reduced with the distance increasing; when the distance is increased to about 60 m, in most cases, the decay rate of spatial correlation coefficient is reduced obviously and even reaches the steady state. Meanwhile, the probability distribution of turbulence integral scale meets the characteristics of extreme value distribution, with the mean value of 9.521m. More than 90% samples are distributed within 0-40m.
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Abstract—The integrated energy system (IES) has the characteristics of integrating and improving system performance and high reliability. Firstly, the paper analyses the problems existing in the original energy supply architecture and introduces the comprehensive energy supply architecture with deep gradient utilization. At the same time, the technical and economic model of IES is proposed as an index to evaluate the profitability of the system. An objective function of maximum return considering energy supply is proposed. This problem is a mixed integer linear programming (MILP) problem that is optimized to achieve IES operation optimization from an economic perspective. Finally, the method is applied to a numerical example to verify the economic foresight and practical usability of the proposed method.
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Abstract—Recently, the study of underwater electric field has been attracted much attention that have interesting applications in a variety of measurement devices and equipment for marine electric field underwater. After the laboratory measurement of the underwater electric field being completed, a series of offshore verification in the coastal area are required to further verify the performance of test equipment in general. Therefore, the relevant electric field characterization of the coastal area needs to be measured explicitly. In this paper, we carries out a series of environmental observations in a certain coastal sea area of Dalian by using a long baseline observation device and obtains some important conclusions through statistical analysis, which has certain guiding significance for the study of the law of the low-frequency underwater electric field in specific sea area.
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Abstract—Spatial process is one of the basic movement forms of ecological environment, social economy and geographical system. Spatial analysis refers to a series of theories and techniques for analyzing, simulating, predicting and regulating spatial processes. With the support of BIM (building information modelling) technology, it can realize the real-time sharing of information, effectively reducing the shortcomings of traditional construction management process. Thus, the cooperation among different departments and specialties in the process of spatial analysis of geographic information is realized. The information integration of BIM technology mainly reflects the integration of the design process and the integration of design information. There is information when there are differences, and information is a reproduction of differences. Therefore, regional differences will inevitably lead to the generation of geospatial information flow. The powerful function of BIM technology can realize the simulation processing of geographic information analysis. BIM technology has changed the way of information transmission in the life cycle of construction projects, and effectively improved the connection efficiency between design and management. This paper studies the construction method of geographic information spatial analysis system based on BIM technology.
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Abstract—Notebook testing in production stage is a very important link, which is an important guarantee for high quality and high reliability in the process of computer production. Efficient software and hardware testing can ensure the quality of the products, at the same time improve the efficiency of production. At present, there have been many open source test automation tools and automated tools for commercial purposes, but these automated testing tools need manually writing test scripts, which consumes a lot of time on the test script development, increasing the notebook production cycle. Therefore, for the development of the test scripts, a test script converter is designed to automatically convert test scripts. First of all, according to the test requirements for operation, testers use Ranorex, a manual recording, generate XML format file, and then use the script converter converts it to corresponding test scripts in the end. Through the experiment, the script converter can effectively and accurately work out test scripts, which brings convenience for the notebook computer test, improves the quality of the production of notebook and shortens the notebook generation cycle.
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Abstract—The structure of offshore platform is complex and the cost is too high. Once the platform has an accident, it will not only cause environmental pollution, but also bring about a series of problems such as economic losses and casualties, thus causing a bad impact on the society. Therefore, it is necessary to monitor the structure of offshore platform. Due to offshore platform structure has long been the bad service in the Marine environment, and suffered various effects, such as: the wind load, wave load, load current and ice etc., and even in some cases will be subjected to earthquake, typhoon, tsunami, etc and Marine platform itself also will be affected by the environment corrosion, Marine biological adhesion, water erosion, etc., these factors will be suffered damage to the Marine platform. Because the offshore platform has been in such a harsh environment or even the design and use of the platform is not appropriate, the platform structure will suffer damage, which will reduce the self-bearing capacity of the platform, and seriously will lead to platform failure. In this paper, the three-dimensional frame structure is applied to the offshore platform structure, and the damage situation of the offshore platform structure is analyzed, and a series of diagnostic methods are proposed. In this paper, the diagnosis method is mainly verified from three aspects: shear structure, three-dimensional frame structure and finite element model of offshore platform structure. In addition, the damage degree of the platform will be evaluated by modal parameter identification technology under the influence of certain noises.
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Abstract—with the rapid development of China's economy and society, numerical classification has occupied an important position in the economic development. A customercentric, comprehensive operational service model is the future of the business economy. The core idea is to improve the service quality system and thus the management strategy. The business economy not only grasps the customer's psychological consumption situation, but also manages the market according to the customer's actual demand, through taking the corresponding measures to establish a good customer relationship. Only in this way can the market's operating share be increased, thus achieving the goal of improving the enterprise's economic benefit. Data clustering algorithm refers to a research topic in the research field of data mining. In the research field of data mining, the research work of data clustering is mainly to analyze the data in the database and find the appropriate application mode.
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Abstract—In structural deformation measurement, the traditional method of structural deformation measurement is complex and cannot meet the measurement accuracy requirements. Digital photography based on hydrodynamic model makes the application of digital photography technology in variable measurement of structural test possible because of the great improvement of image quality. With the development of hydrodynamics related research and image processing technology, close-range photogrammetry has become a trend, which has revolutionized the operation mode of measurement. Generally, it is only placed at the key points and positions of the test piece, and digital photography can record the test process and test scene. The requirements for the layout of the control points are high, and the accuracy is high, which can effectively reduce the labor intensity. The node can obtain the direction of load flow at that point based on its location information. In the relevant monitoring process, professional measuring instruments can be used based on the fluid dynamics model. Ensure the function of the measuring instrument and check the calibration of the measuring device in advance.
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Abstract—In the process of machining, there are often many factors that affect the final machining quality of workpieces, and machining accuracy is an important index to measure the machining quality of parts. Each influencing factor of product quality is interrelated and interactive, and ultimately determines the output of product quality. In this process, mechanical engineering processing and manufacturing will involve several major links such as product research and development, preparation of mechanical engineering processing and manufacturing process, and mechanical engineering processing and manufacturing. As market demand, products and organizational structure are constantly changing, the processing quality control system is required to be able to respond quickly to various changes. Using the optimization design technology based on finite element analysis, it is very important to optimize the forging process parameters. This paper analyzes the design of quality control system for machining based on finite element technology.
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Abstract—This paper aims at exploring the participants' eye movement characteristics and aesthetic preferences of various decorative pattern of the wardrobe door. It takes 12 kinds of different decorative patterns of the wardrobe door as the research objects, and uses the eye movement recording technique combined with subjective evaluation method as the comprehensive research means for the study. The results show that: (1) According to the analysis of variance (ANOVA), different decorative patterns influence participants' eye movement indexes (fixation duration and number of fixation) and subjective evaluation significantly. (2) Through regression analysis, subjects' eye movement fixation duration and subjective evaluation value could be fitted into linear regression equation y=329.56x-226.47. Further significance test of regression equation shows that F (1, 22) = 137.544, P < 0.001, which indicates that the effect of regression equation overall regression is very obvious. (3) Subjective evaluation value and the number of fixation could be fitted into the equation y=1.1336x-0.5463, and its significance test of the regression equation results is F (1, 22) = 168.91, P < 0.001, so the higher eye movement numerical value, the higher the level of subjective evaluation, and the stronger the degree of preference. (4) The patterns with simple lines, clear graphics and more creative shapes get stronger aesthetic preference. In addition, the decorative elements of a wide stripe in the middle of the door like a belt get strong aesthetic preference.
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Abstract—Under the background of Internet big data era, the amount of data information in all walks of life is increasing day by day. How to filter, mine and manage different kinds of data information has become an important topic of network communication, public service data analysis, privacy protection and other activities. This paper mainly discusses the algorithm of association rules mining based on Apriori algorithm. The association algorithm is used to process the raw data and privacy data of different network data sets, and dig out the multi-level frequent itemsets in the database.
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Abstract—A medical CT image classification model with hybrid BBO (Biogeography Based Optimization) and HS (Harmony Search) algorithm is proposed to improve medical CT image classification accuracy and solve SVM parameter optimization problem in the classifier. Firstly, HS algorithm has strong search capabilities for global solutions, but poor local search abilities. It can be better to search global and local solutions by integrating migration operations of BBO algorithm into HS algorithm. Finally, the medical CT image classification model is established according to the optimal parameter and meanwhile the simulation test is also carried out to verify the performance of the model. The simulation result shows that relative to the comparison model, BBO-HS-SVM can not only improve medical CT image classification accuracy, but also accelerate the classification speed, thus being more suitable for the real-time classification requirements of medical CT images.
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Abstract—In recent years, with the rapid development of civil aviation, the contradiction between flight flow and airspace capacity has become increasingly prominent. In order to balance the contradiction between the supply and demand of airspace resources and reduce flight delays, it is necessary to carry out scientific and reasonable evaluation on the operational capacity of airspace system. As the most basic unit of airspace system, the operating environment of the control sector is increasingly complex, so the accurate evaluation of sector operating capacity becomes one of the preconditions for the fine measurement of airspace operating capacity. In this paper, the background of the research is discussed, the concept of sector capacity assessment, the characteristics of sector operation and the influencing factors of sector capacity are introduced in detail, and a new sector capacity and workload model for air traffic controllers based on least square method is proposed. According to the model, an optimized sector capacity evaluation method is proposed. Finally, an example of sector capacity evaluation is introduced to verify the evaluation model, and suggestions for optimizing sector operation and upgrading sector capacity are given on the basis of analysis and comparison of capacity evaluation results.
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Abstract—The research and construction of the intelligent dispatching technology support platform is the key to and basic content of the whole intelligent dispatching system construction. The realization of the efficient integration and integration of the main distribution network information and the further realization of the application function cooperative operation on this basis is an important part of the establishment of the intelligent dispatching technology support platform. Enterprises and research institutions serving the power grid technology field have made many beneficial researches and explorations on the intelligent dispatching technology support platform. In this paper, a comprehensive evaluation index system of smart grid based on master distribution coordination planning is proposed. The research results have been successfully applied in power supply, and have been vigorously promoted and applied in power Grid Company. The field operation experience shows that the results have effectively improved the business coordination ability and work efficiency of master network dispatching and distribution network dispatching, and achieved good economic and social benefits.
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Abstract—with the rapid development of artificial intelligence technology, as a direction of artificial intelligence research, the research of facial expression recognition has entered a new stage. Facial expression recognition has a wide range of applications in the fields of safe driving, medical treatment, human-computer interaction, etc. This paper studies a facial expression recognition method based on deep learning, which uses OpenCV to complete facial recognition. The facial expression recognition is realized through building and training CNN network by keras.
CS501 Resistance Identification in HVAC Distribution Networks Based on Collective Intelligence SystemLi Li, Zhen Yu, Huai Li- CS502 Research on Operation Method of Intelligent Distribution Network Without Power FailureJianjun Wang, Dailin Jiang, Yikai Wu, Liangren Shi
- CS503 Secondary Radar Signal Processing Based on Deep Residual Separable Neural NetworkXue Du, Kuo Liao, Xiaofeng Shen
- CS505
Research of NILM in Offshore Oil Platform Power SystemQingguang Yu, Zhicheng Jiang, Di Yang, Yuming Liu, Gaoxiang Long, Tingliang Zhang
- CS508
A Survey of Research on Datacenters Using Energy Storage Devices to Participate in Smart Grid Demand ResponseZhao Mengmeng, Wang Xiaoying
- CS510
Hybrid Modular Multilevel Converter with Reduced Capacitor Voltage FluctuationSiqi Li, Bo Zhang, Dongyuan Qiu, Yuan Chen, Runhong Huang, Wanyu Cao, Shukai Xu, Yan Li, Hong Rao, Licheng Li
- CS513
Research of Virtual Synchronous Machine Control Strategy of Hybrid Renewable Energy in MicrogridQingguang Yu, Zhicheng Jiang, Mengchu Zhao, Yuming Liu, Gaoxiang Long, Min Guo
- CS515
Hybrid Modular Multilevel Converter with Reduced Number of ComponentsLi, Hong Rao, Licheng Li
- CS517
Research on Intensive Care Technique for Partial Discharge in High Voltage CableJiaxin Liu, Defu Wei, Zhenwei Zhao, Guanhua Li
- CS518
Performance Analysis of Everton Football Club Based on Tracking DataYikang Wang, Hao Wang, Mingyue Qiu
- CS522
Analysis of Temperature Field for Ultra High Voltage Transformer BushingsZhaoliang Gu, Mengzhao Zhu, Wenbing Zhu, Jiabin Zhou, Qingdong Zhu, Jian Wang
- CS524
High Accuracy Drug-Target Protein Interaction Prediction Method based on DBNWanrong Gu, Guohua Wang, Ziye Zhang, Yijun Mao, Xianfen Xie, Yichen He
- CS526
Multidimensional Design Ideas of Reducing Loss and Increasing Benefit Based on Ubiquitous Power Internet of ThingsWang Jinliang, Liu Chaonan, Qin Jin, Wang Wenbo, Wang Jingfei, Liu Zishan
- CS527
Research on On-line Monitoring Technology of Mechanical Characteristics of Ring Network CabinetGuo Zhiwei, Wang Yu, Xu Zitao, Wang Fuwang
- CS528
Research on Fault Detection for Ring Network CabinetGuo Zhiwei, Wang Yu, Xu Zitao, Wang Fuwang
- CS531
The study of dynamics modeling and composite control for large load robotFuli Zhang, Zhaohui Yuan, Sheng Dong
- CS534
I/O Performance Optimization Analysis of Container on Cloud PlatformCao Jiqing
- CS536
Learning Immersion Assessment Model Based on Multi-dimensional Physiological CharacteristicsBoxin Wan, Junqi Guo
- CS539
Decision-Making Method for Preventive Maintenance of Medical X-Ray EquipmentMingxin Zhao, Haodong Duan, Kai Sun
- CS540
Research on Dynamic Simulation System of Multidimensional ReservoirsRui Huang, Ruihe Wang, Xiaohan Jin, Changhai Yu, Zengfei Wang, Heyu Wu
- CS541
Research on Resource Management System of Multidimensional Reservoir SimulationRuihe Wang, Rui Huang, Changhai Yu, Xiaohan Jin, Changjie Zhao, Musen Zhang
- CS545
GLAD: A Method of Microgrid Anomaly Detection Based on ESD in Smart Power GridQiyu Wei, Rui Ma, Yiqiu Wang, Mingyu Chen, Yanru Sun, Mingjie Liu, Xiaoyong Lin
- CS546
Design and trajectory planning of blocking plate robot in steam generatorPeng Junjie
- CS550
Forest smoke detection based on deep learning and background modelingGuohua Wang, Juncong Li, Yongsen Zheng, Qi Long, Wanrong Gu
- CS551
Power Wireless Heterogeneous Network Management System based on Big Data TechnologyChen Shuiyao, Qiu Lanxin, Shao Weiping, Lu Tao
- CS552
Research on Ground Fault Monitoring Method for High Voltage Line Based on Phase Difference MethodJiang Yijun, Lv Jun, Wang Liqun
- CS553
Intelligent computing methods used in acoustic emission and magnetic flux leakage detection of tank bottomYongtao Zhao, Zhuang Wu, Dong Li, Yuhan Zhang, Guowei Guan
- CS555
Design of Distributed Factory Fire Alarm SystemMingyu Song, Wuxing Li, Xiaomin Zhang, Li Liu, Yanke Ci, Xushan Peng, Yongping Li, Haosong Chen
- CS557
Design of Distributed Plant Temperature and Humidity Monitoring SystemJingda Ying, Xiaomin Zhang, Yibin Pan, Li Liu, Yanke Ci, Xushan Peng, Yongping Li, Haosong Chen
- CS558
A Method of Predicting Crime of Theft Based on Bagging Ensemble Feature SelectionTuo Shi
- CS560
Identification for Property of Luochong Kiln Based on Frequency-treeTiejun Zhu, Yong Wan
- CS561
Reducing Perturbation of Adversarial Examples via Projected Optimization MethodJiaqi Zhou, Kunqing Wang, Wencong Han, Kai Yang, Hongwei Jiang, Quanxin Zhang
- CS563
Trusted Connect Technology of Bioinformatics Authentication Cloud Platform Based on Point Set Topology Transformation TheoryLinge Wang
- CS565
Phenomenological Layer Structure of an Intelligent Agent for IoTFrancesco Rago
- CS566
Design and Application of a Production Accident Early Warning and Analysis SystemQiaoshun Wu, Kun Pi, Qigen Liang, Haibo Peng
- CS567
Research on Virtual Wind Instrument and Performance System Based on Dual Computer CommunicationSheng Hu, Cheng Du, Junweri Song, Chen Tong, Zhigang Yuan
- CS569
Design and Implementation of Firmware Data Acquisition System Based on Scrapy FrameworkXiaowei Han, Likun Zheng
- CS570
Comparative Study on Numerical Simulation and Monitoring Data of Bridge Construction Monitoring PhaseLu Peng, Zhu Luo, Na Miao, Genqiang Jing, Yixu Wang, Jing Zhu
- CS572
Research and Analysis on Key Technologies of Cloud Computing Platform Based on IPv6Lin Lin
- CS573
Research and Development of Innovation and Entrepreneurship Project Analysis System Based on Big DataHaimei Liu
- CS575
Research on Urban Traffic Governance and Optimizing Strategy Based on Big DataBaohua Qi
- CS578
De-noising Method of Joint Empirical Mode Decomposition and Principal Component AnalysisChun Wu, Li Huang, Wenbo Wang
- CS579
Research on Intelligent Volume Algorithm Based on Improved Genetic Annealing AlgorithmTianci Li, Guangbo Lei, Fang Wan, Yating Shu
- CS580
Research on Binocular Forest Fire Source Location and Ranging SystemZhang Yaping, Shao Zhihang
- CS583
The Design of the Assistant System for College StudentsTianci Li, Jinglu Li, Shanshan Yu, Kexin Hu
- CS584
A Homomorphic Encryption Approach in a Voting System in a Distributed ArchitectureSegundo Moisés Toapanta Toapanta, Luis José Chávez Chalén, Javier Gonzalo Ortiz Rojas, Luis Enrique Mafla Gallegos
- CS585
Ensuring the Blind Signature for the Electoral System in a Distributed EnvironmentSegundo Moisés Toapanta Toapanta, Darío Fernando Huilcapi Subia, Milton Andrés Cepeda Aveiga, Luis Enrique Mafla Gallegos
- CS588
A Deep Autoencoder Based Outlier Detection for Time SeriesJin Wang, Fang Miao, Lei You, Wenjie Fan
- CS589
A Design of Mobile Partition Piles System in Urban RoadHang Yuan, Shangshang Nie, Fahai Zhong, Ronghui Luo
- CS591
Computer Simulation of Maize Yield by Fisher Integral Model Based on Meteorological FactorsShanshan Seng, Yongen Zhang, Wen Yu, Shiwei Xu
- CS592
Application of Optimization Method and Least Square Method in Reliability Analysis of Bearing RollerYan Li, Xintao Xia
- CS594
Algorithm of Maintenance Time and Maintenance Amount Based on Maintenance DegreeXiaobo Su, Qi Gao, Weining Ma, Yukun Chen
- CS597
Inventory Optimization Models of Equipment Spare Parts Based on Computer SimulationWang Lihui, Tan Liwei, Liu Shenyang, Liu Yan
- CS599
Application research and improvement of particle swarm optimization algorithmLigang Cai, Yuqing Hou, Yongsheng Zhao, and Jianhua Wang
- CS600
Intelligent Counting System for Classroom Numbers Based on Video SurveillanceMingxi Liu, Xinze Zhang, Yiran Han
- CS602
Perceptual model for compliance in ineraction with compliant objects with rigid surfaceZhiyu Shao, Zhiyong Cao, Cong He, Qiangqiang Ouyang, Juan Wu
- CS603
Vehicle detection in thermal images with an improved yolov3-tinyJing Gong, Jianhui Zhao, Fan Li, He Zhang
- CS605
Application of Passive DNS in Cyber SecurityGuo Xuanzhen, Pan Zulie, Chen Yuanchao
- CS606
Research on the design method of servo position loop parameters of shipborne TT&C radarRu Hailong
- CS607
Research on the method of ship sway isolation for the antenna of shipborne TT&C radarRu Hailong, Yan Zuoyin
- CS609
Short-term Forecast of Passengers Volume at Guangzhou Baiyun International Airport Based on ARIMA-LSSVM-DACPSO ModelYingying Wei, Shuaiying Wei
- CS610
UAV security situation awareness method based on semantic analysisXijun Gao, Hongxia Jia, Zili Chen, Guogang Yuan, Sen Yang
- CS611
New Technology Architecture and Research Hotspot of Blockchain in 2020Bowei Mou, Fuyan Liu
- CS613
Question-Answering using Keyword Entries in the Oil&Gas DomainLin Xia, Wu Boyu, Liu Lixia, Lu Ruidi
- CS614
D-FCOS: Traffic Signs Detection and Recognition Based on Semantic SegmentationFusheng Zhang, Yong Zeng
- CS615
Semantic Information Detection of Webpage Based on Word Vector and InfomapYuqian Wang, Jianyou Lv
- CS618
On the Sum-Rate Capacity of the Gaussian Partially Cognitive Radio Channel with Mixed InterferencePeng Zou, Jiaru Lin
- CS619
Smart Printer: Design of Intelligent Portable Automatic PrinterDong Xie, Yihan Gong, Zhen Zhang
- CS622
Realization of Vehicle Classification System Based on Deep LearningYanhong Yang
- CS623
Video object detection based on the spatial-temporal convolution feature memory modelWenjun Dai, Tianqing Chang, Libin Guo
- CS625
Research on dynamic load balancing of data center network based on openflow technologyHaiyang Chen, Jun Yu, Hengmao Pang, Lin Wang, Mingjie Xu, Zhu Mei, Lin Qian
- CS627
Obfs4 Traffic Identification Based on Multiple-feature FusionDi Liang, Yongzhong He
- CS628
Detection of Sybil Attack on Tor Resource DistributionKunjie Ge, Yongzhong He
- CS631
Analysis of Single Demodulation of Composite Continuous Wave Signal Modulated by Pseudorandom Code FamilyXiaofang Shao, Jianqiang Hou
- CS634
Maneuvering SAR Imaging AlgorithmsJiasen Li, Jianqiang Hou
- CS635
Study on CO concentration measurement of TDLAS based on baseline nonlinear improvementShangwei Hu, Xiaobo Tu, Shuang Chen, Furong Yang
- CS638
Research on private cloud platform for virtual resource adaptationMingjie Xu, Jun Yu, Lin Wang, Haiyang Chen, Zhu Mei, Hengmao Pang, Lin Qian
- CS639
Improved Signal Demodulation and Detection Algorithm for Parallel ReceiverHailiang Feng, Feng Zou, Zhanxin Yang, Yuanjia Gong
- CS641
Flexible and compact EBG structure design for Multi-band applicationsWang Weijiang
- CS642
Living Range Trends and Fishery Policies for Herring and Mackerel in Scotland Based on Computer Modeling and AnalysisHengyi Yang, Mengnan Hou, Aoran Cui, Kexun Cai
- CS644
Comparative Study on the Mosaic Methods of AW3D30 v2.2 and ASTER GDEM v3Pengcheng Guo, Shangmin Zhao, Zhuojian Li
- CS645
Text Sentiment Analysis Based on Amazon Product EvaluationJunjie Zhao, Yuepeng Xin, Yao Tong, Shilu Lu, Silin Li, Chaochao Ru
- CS647
Underactuator configuration and manipulating strategy of a novel flexible arm for precision sprinkler irrigationLi Yang, Zhanyong Wei, Baoping Han, and Yan Yang
- CS650
Simulation of a Non-Uniform Electric Field with a Novel Electrodes Configruation of an Electrorheological Valve for High Shear Rates LoadDou Shilei, Huang Jingyu, Xu Luning, and Han Li
- CS651
Modeling of Refreshing Rate and its Parametric Analysis of a Multi-lines Braille Display using Electrorheological Valves MatrixHuang Jingyu, Dou Shilei, Xu Luning, and Han Li
- CS653
Event Recognition in Chinese Emergencies Corpus Using ALBERT-BiLSTM-CRFWang Bo, Wei Wei, Wu Yang, Wang Xuefeng, Liu Caiwei
- CS654
Virtual Instrument Technology for Elevator Safety Monitoring and Alarm SystemPeng Liao, Junzhen Zhou, and Peiyi Zhu
- CS656
Research on Application of Internet of Things Information Security Using Blockchain TechnologyZhiwei Jin, Zhou Jian
- CS657
Research on Application of Computer Image Processing in Web DesignYi Zheng, Haiqing Li, Aiqun Ren
- CS659
Research on a Radar Interference Assessment MethodSong Yuzhen, Liu Lian
- CS660
Pedestrian detection using quaternion histograms of oriented gradientsGuoyun Lian
- CS661
Integrated Intelligent Drowsiness Detection System Based on Deep LearningJiayi Lin
- CS662
Floor Climbing Cleaning Robot Based on Slide Rail Lifting StructureBeiquan Fan
- CS664
An All-terrain Vehicle for Post-disaster Search and RescueRuichen Li
- CS666
Design and Implementation of a Foot-Controlled Robot Arm SystemXiaohu Mu
- CS667
Research on Intelligent Lighting System of Concentrator Based on NRF24L01PTianze Lan, Yihui Qing, Shuqing Wang
- CS668
Finite-time stabilization of stochastic neural networks with time-varying delay via impulsive controlTao Chen, Shiguo Peng, Zhenhua Zhang
- CS669
Design and Implementation of Distributed Fault-tolerant Computer Communication Software of Deterministic Communication Based on TTEYong Guo, Shuai Lu, Xiaodi Dai, Haijun Duan
- CS670
Design of Space-borne Broadband VHF/UHF Beacon AntennaXinfei Liu, Yuxi Liu, and Yan Qiu
- CS673
Study on the Impact of Big Data Technology on the Audit and its ApplicationZhang Xing, Sun Yuan, Chen Xiongzhi
- CS674
Application of Photoshop Technology Based on Computer Graphic Design SoftwareTianshuang Zhang, Yue Chang
- CS676
SDN-based multi-controller optimization deployment strategy for satellite networkDebin Wei, Ning Wei, Li Yang, Zhixiang Kong
- CS678
Key Matrix Design Based on OLED Display TechnologyFanchang Zeng
- CS679
Design of Cross-border Network Crime Detection System Based on PSE and Big Data AnalysisXingchen Yu
- CS680
Application and Research of Modular Dynamic Graphic Design Technology in PracticeYu Ying, Di Miaosen
- CS682
Research on Collection and Preprocessing of Multi-source Heterogeneous Elevator DataChen Wang, Shuangchang Feng
- CS683
Selection and analysis of slot number of stator and rotor for small five phase squirrel cage induction motorYiyong Xiong, Jinghong Zhao, and Xiaohu Liu
- CS689
Multi-Scale Region-based Fully Convolutional NetworksChengqi Xu, Xuehai Hong, Yuanzhou Yao, Hengheng Shen, Qian Ma, and Hui Jiang
- CS692
Optimization Design and Horizontal Stiffness Analysis of Three-wire Pendulum Mechanism of Air Spring Vibration IsolatorChengyao Liu, Wanguo Li, Shicheng Zheng, Jiaming Chen
- CS694
Method for Realizing Structured Process through Secondary Development of Teamcenter SystemYize Liu, Xianghui Zhan, and Xiaoda Li
- CS695
Application of Wireless Sensor Network in Automatic Detection of Spray Disinfection in Pig Epidemic EnvironmentJuan Zhang
- CS698
Research on Key Technology of Resource Scheduling Based on Trust in Virtual Computing EnvironmentLi Kai, Ni Jiati, An Wenyan, Mier Alimujiang, Shi Haohan
- CS699
Research on Spatial Database Technology Based on ArcsdeLi Kai, Zhou Wenting, Wang Tianjun, He Wei, Shi Haohan
- CS700
The Theoretical Construction and Application System Development Study of Sports Information ManagementDong Jinguo
- CS701
Research on the Evaluation Index System of Sports Enterprise InformationizationDong Jinguo
- CS705
Research and Application of Jiugu Coal Industry Drilling Video Network SystemQi Yunrui
- CS706
Embedded Design of Human Motion Physiological Parameter CollectorZhao Meihuan
- CS708
The Cross-border C2B Development Study Based on the Information Cost TheoryHuo Yuanyuan
- CS709
Design of Cultural Creative Product Interaction System Based on VRChen Zhigang, Zhou Juelu
- CS711
Research on Integration and Sharing System of Network Movie and TV Data Resources under New Media EnvironmentFu Yijun, Li Chengjia
- CS712
Research on Multidimensional User Experience Evaluation Model Based on Principal Component AnalysisSong Xiangbo, Tian Wei
- CS714
Selection of Optimal Packaging Methods for Different Food Based on Big Data AnalysisTian Wei, Song Xiangbo
- CS715
Design of Interactive Experience Platform for Cultural and Creative Products from Multiple PerspectivesWang Tingting, Chen Zhigang
- CS718
Design of Virtual Tourism System Based on Characteristics of Cultural Tourism Resource DevelopmentZhou Juelu, Wang Tingting
- CS719
An Automatic Shadow Generation Algorithm in Two-dimensional Animation ProductionLiu Yimin, Zhong Shiquan
- CS720
Motion Behavior Feature Segmentation Based on Intelligent VisionZhao Meihuan
- CS721
Analysis of Intelligent Manufacturing System Constructed by the Army and the People in Internet EraHuo Guangyao, Zhang Xiang, Xing Lei
- CS724
Detection of the Rail Profile Wear Based on Image ProcessingJie Li, Bowen Ma, Huajun Dong
- CS725
A Watermarking Algorithm for Cloud Database Based on Chaos CryptographyHaiting Cui
- CS727
Hierarchical Cluster and Multidimensional Scaling Analysis of Video Websites Based on URL Co-occurrenceYonghe Lu, Yongshan Chen
- CS729
Design and Implementation of a UE4 Based Virtual Home Improvement Interactive Simulation ApplicationYutian Shi, Mingzhi Cheng, Luyue Zhang, Hao Li, Yatian Xue
- CS730
Design and Implementation of Meteorological Equipment Management SystemJing Chen
- CS736
Forensic Analyses Based on Predictive CodingShuhi Hou, Shanshan Dong, Siuming Yiu, Tetsutaro Uehara
- CS739
Homomorphism of Lattice-valued Fuzzy Finite AutomataHu Zhonggang
- CS740
Dynamic Trust Model of ARP Real-Time Intrusion Detection Based on Extended Subjective LogicMiao Zengliang, Liu Guodong, Wang Hongyan, Wang Yong
- CS742
The Model of Big Data Cloud Computing Based on Extended Subjective LogicWang Hongyan, Wang Yong, Miao Zengliang, Zheng Enyu
- CS744
Research on Flexible Manufacturing Technology of Spacecraft Testing SystemFeng Yang, Liang Ren, Yongcong He
- CS745
Semi-linear Estimation for Differences between Datasets with Missing DataHao Wu, Chen Cheng, Cuicui Li
- CS747
Opening speed detection based on displacement sensorXiaozhao Li, Kun Li, Yang Zhang
- CS749
Research on four problems in the scenario specification of intelligent combat simulationQingjun Qu, Yaqi Wang, Yiping Yao, Shidong Qiao
- CS750
Joint 2-D Angle Estimation using TDOA in Distributed Multi-antenna SystemYandu Liu, Yiwen Jiao, Hong Ma
- CS751
Image Noise Level Classification Technique Based on Image Quality AssessmentLuo Geng, Zhao Zicheng, Long Qian, Lv Chun, Bao Jie
- CS753
Construction and Application of Knowledge BasesYong Ren, Wenyu Zheng, Yan Ren
- CS754
GNP: A Global-Sensitive Mechanism for Near-Data ProcessingXianfeng Li, Juanjuan Zhao
- CS757
Deep Reinforcement Learning Based Spinal Code Transmission Strategy in Long Distance FSO CommunicationJun Ao, Na Li, Chunbo Ma
- CS758
Abnormal Test Data Diagnosis and Prognosis Based on Least Squares Support Vector MachineHan Huilian, Cui Zhaojing
- CS760
Indirect Field Oriented Control Technology for Asynchronous Motor of Electric VehicleWang Qinglong, Yu Changzhou, Yang Shuying
- CS762
Robust Fault-tolerant Control for Time-Varying Descriptor SystemGang Wang, Xuxing Tang, Jun Zhou
- CS765
Research on the industrialization mode development and case evaluation system of major scientific and technological achievements of power sensorHaiyun Yang, Shanzhe Shi, Shilin Li, Yuhui Liu, Yamin Liu
- CS766
Research on key direction extraction technology of electric power achievement awardYamin Liu, Yuhui Liu, Shanzhe Shi, Haiyun Yang, Shilin Li
- CS768
Establishment of path model of electric power scientific and technological achievements based on information collaborative decisionShilin Li, Yuhui Liu, Shanzhe Shi, Haiyun Yang, Yamin Liu
- CS769
Effective Matrix-Vector Multiplication Computations on Account of Physically Based Matrix DistributionZhen Li, Hongmei Xu, Chen Su, Jianyong Dong, Xingang Wang
- CS771
Research on Grey Clustering Weighting of Expert Group Based on Information EntropyQian Wang, Xusheng Gan, Baoan Han, Guozhou Yang
- CS772
Safety Evaluation of Training Airspace Environment Based on Wavelet Neural NetworkHaiqing Huang, Xusheng Gan, Baohua Han, Baoan Han
- CS775
A Fast Pointing Error Analysis System for Photoelectric Detection MechanismsJing Zhou, Huajie Hong, Dapeng Fan
- CS777
Simulation Research on the Characteristics of Supersonic Vacuum ArcShibai Liu, Yuhao Wang, Congjun Xue, Liting Ma, Chuan Xiang
- CS779
Multi-Streams Network for Action RecognitionSu Chang, Zhang Jian
- CS780
Research on Simplified Method of Combination Test Case Set for Basic Software SystemWei Liu, Jing Xiong
- CS781
Research on Container Security of PaaSJing Zhong, Wei Liu
- CS783
Phase synchrony and its application to lie detectionYijun Xiong, Lingyun Gu, Junfeng Gao
- CS785
Vibration Analysis of Transporting Elderly Posture Behavior of Elderly-Assistant and Walking-Assistant Robot Considering Elderly Falling AngleKhaled Kadry Hamza, Xiaodong Zhang, Xiaoqi Mu, Odekhe Randolph Osivue
- CS788
DoS attack detection model of smart grid based on machine learning methodWang Zhe, Cheng Wei, Li Chunlin
- CS790
A Control Strategy of Microgrid-Connected System Based on VSGXiaojing Liu, Renxi Gong
- CS791
Design, simulation and experimentation of a biomimetic wall-climbing robot with tracked spinesJia Shi, Linsen Xu, Jinfu Liu, Gaoxin Cheng, Xingcan Liang, Lei Liu, Shouqi Chen, and Hong Xu
- CS792
Construction of General Linear System and Associated Polynomial Bezout MatrixHuazhang Wu, Bing Li, and Mingda Xin
- CS794
A Methond of Capturing GPS Signal Loss Based on QAR DataYang Jiao, Bin Li, Xiaoyue Zhang
- CS796
Control of Single Phase LCL Photovoltaic Grid-Gonnected Inverter Based on State ObserverLiuwen Qin
- CS798
Improvement of Power Factor and its Multisim SimulationYijun Fan, Miao Zhang, Jihong Li
- CS799
The Circuit Design of Voltage-controlled Color Changing Lamp Based on MultisimYing Chen, Miao Zhang, Jie Hao
- CS800
Research on parking lot management system based on parking space navigation technologyRuixuan Chen, Xingyan Hu, Wei Mu
- CS801
Indoor Positioning Optimization Based on Genetic Algorithm and RBF Neural NetworkHua Guo, Mengqi Li
- CS803
Design and Implementation of ECG Generation Software Based on Primary Medical CareYang Yuanyuan, Shu Minglei
- CS804
Fabric Defect Detection with Optimal Gabor Wavelet Based on RadonLi Yihong, Zhou Xiaoyi
- CS806
Research on network advertisement precise delivery system based on big data technologyLai Jieyu
- CS807
Change Monitoring of Urban Typical Facilities for Remote Sensing Images FusionLi Huafeng, Xu Guibin, Zang Yuwei, Xie Lianke, Bai Xiaochun, Wang Jie
- CS808
Fast Decryption Algorithm for Paillier Homomorphic CryptosystemTaiwo Blessing Ogunseyi, Tang Bo
- CS810
Computer simulation on field spatial distributions generated by an elliptic ring uniformly chargedPing Zhu
- CS811
Research on non-blocking communication of airport data based on dynamic thread poolCunxi Chang, Guoqiang Wang, Wei Shi
- CS812
Secret Sharing Simultaneously in Internet of ThingsJie Tang, Huanhuan Song, Aidong Xu, Yixing Jiang, Hong Wen, Yunan Zhang, Kaiyu Qin
- CS815
Research on Convolutional Neural Network in the Field of Object DetectionBingzhen Li, Wenzhi Jiang, Jiaojiao Gu, Ke Liu, Yangyong Wu
- CS816
Knowledge Extraction Experiment Based on Tourism Knowledge Graph Q & A Data SetXuchao Liang, Han Cao, Weizhen Zhang
- CS818
Research on Audit Model of Dameng Database based on Security Configuration BaselineShenwen Wang, Yonghui Yang, Shukun Liu
- CS819
Grey System Correlation-based Feature Selection for Time Series ForecastingWei Cheng, Shufeng Wei, Fei Cheng
- CS821
Hyperspectral Image Classification Based on Broad Learning System with Composite FeaturePeng Chen
- CS822
Hyperbolic Localization Algorithm in Mixed LOS-NLOS EnvironmentsJianhua Guo, Lu Zhang, Wei Wang, Kai Zhang
- CS823
Research on Design and Manufacturing Collaboration of Ship ShopWang Meng, Bian Dezhi, Hu Changping
- CS826
MVDR algorithm for broadband coherent source signals based on data reconstructionHui Xia
- CS828
Research on Application of Optimal Algorithm Based on Simulated Annealing in Intelligent Decision ModelHui Xia
- CS829
Demand Side Management with Multiple EVs Sharing Parking Units in Electricity MarketJiaxi Kang, Jiejun Chen, Qiang Sun, Miao Zhang, Fangyuan Xu
- CS830
Identity and Policy Based Signcryption Scheme for AMI Downlink TransmissionChangji Wang, Yuan Yuan
- CS831
Research on the Intelligent Identification Method of Personnel Violation in Substations Based on Deep LearningJiacheng Su, Wenle Song, Baoyong Li, Guipeng Wei
- CS833
Research on the Intelligent Image Recognition and Diagnosis Technology of Key External Insulation Devices Based on Deep LearningShaoqi Yin, Yijun Hu, Rui Peng
- CS835
Coupling Characteristics of Noise Radiation and Tank Wall Vibrations of Typical Distribution Transformers Based on Field MeasurementsZhu Yunxiang, Tu Feng, Wang Zhiyong, Hu Jingyu, Shen Chong, Xu Jianfeng, Min Hequn, Cao Meigen
- CS836
Research on the Intelligent Identification Method of the Substation Equipment Faults Based on Deep LearningWenle Song, Xiangyu Liu, Junlei Zhao, Menglin Wang, Yang Liu
- CS837
Research on the Data Management and Decision-Making Method of the Intelligent Substation System Based on SCDWenle Song, Chunxiao Yan, Menglin Wang, Xiaokai Wang, Yang Liu
- CS839
Research on Scheduling Optimization of Inbound and Outbound for Double-StackersJianxiong Qiu
- CS840
Research on Production Scheduling for Coordination Operation of Stackers on MonorailJianxiong Qiu
- CS843
Application of Ontology Matching Algorithm in Linguistic FeaturesYan Zhu
- CS845
Study on De-Noising of Internal Leakage Acoustic Emission Signal in Hydraulic Slide
Valves Based on CEEMDAN-MI-IncrEn-NLMJie Liu, Likun Peng, Fei Song
- CS846
Ore Grouping Multi-Constraint Integration Benefit Greedy Optimization MethodBin Wang
- CS849
Simulation and Analysis of Clustering Routing Protocol Based on Improved LEACHMinglan Yuan
- CS852
A Kind of Soft Started Regulated Power SupplyQinzhu Wang, Huan Li
- CS853
Navigation System Research and Design Based on Intelligent Image Classification
Algorithm of Extreme Learning MachineHua Yu, Lin Yang, Yunfeng Zhou
- CS854
Research on Embedded Intelligent Robot and Its Motion Control SystemYufeng Liang
- CS856
Small Object Detection Based on Deep LearningWei Wei
- CS858
Research on Interactive Information Design for Intelligent Urban Public TransportXingchen Pan, Liqun Gao
- CS860
Research on Open Robot Controller Based on Motion Control Card and Related TechnologiesXin Zhao, Jian Zhang, Shangteng Qi
- CS861
Research on Motion Trajectory Tracking Control Method Based on Mobile Robot Servo SystemZe Liu, Shijun Jin
- CS862
Research on Vehicle Routing Branch Pricing Algorithm for Multi-Model Electric Vehicles
Based on Board TestingGuowei Wang, Dong Cui
- CS865
Research on Speed Control Strategy of Permanent Magnet Synchronous Motor Based on BP-SSO-PID AlgorithmMengqi Lei, Xiaoming Ren, Xun Fu
- CS866
Tactical Intention Recognition Based on Fuzzy Multi-Entity Bayesian NetworkZhen Lei, Peizhi Cui, Yanyan Huang
- CS869
Dragon Fruit Disease Image Segmentation Based on FCM Algorithm and
Two-Dimensional OTSU AlgorithmWen Dong, Yihua Xia, Yongna Liu
- CS870
Short-term Wind Speed Prediction Based on Improved CEEMD-FOA-LSSVMLi Minjie, Gao Guige
- CS873
Study on the River Network Extraction Method from Complex Surface Based on Trend Surface FittingDandan Su
- CS874
Design and Implementation of Distributed Government Audit System Based on Multidimensional Online AnalysisZhenxun Tian
- CS877
Research and Design of Automatic Navigation System for Agricultural Machinery Based on GPSJinqi Zhang, Fachuang Zhou, Changrui Jing, Shuangming Wei, Yao Wu, Changrui Jing
- CS878
Maximizing Social Network Influences Based on User PreferencesShoujian Yu, Yi Li
- CS880
Research and Application of Data Privacy Protection Technology in Cloud Computing Environment Based on Attribute EncryptionWenfeng Zhang, Shiqi Jin
- CS881
Research on the Fast Retrieval Algorithm of English Sentences Based on SimhashJing Ouyang
- CS883
Research on English Text Information Filtering Algorithm Based on SVMJing Ouyang
- CS885
Novel Structure of Terahertz Antenna Based on Square and CircleJiajia Lei, Jianguo Yu, Lan Wang
- CS886
Research on Full-Scale Measurement of Non-Uniformity of Wind Pressure of Power Transmission ConductorHongjie Zhang, Fengli Yang, Shuai Shao, Guo Huang, and Qing Zhu
- CS891
Coupling Integration and Evaluation of Centralized Energy Station and Distributed Energy Cascade Utilization SystemTao Peng, Qifen Li, Yongwen Yang
- CS892
Analysis of Steady-State Underwater Electric Field Characterization in Coastal Sea AreasGuoyi Yang, Zhe Dong, Linan Jia, Sha Liu, Jianye Su, Jialu Sun
- CS894
Construction of Geographic Information Spatial Analysis System Based on BIM TechnologyShuhui Jiang, Qin Zong, and Wanying Qin
- CS904
Script Converter for Automated Testing of LaptopsYongfeng Huang, Mingle Shao, and Baoguo Lou
- CS905
Security Posture Assessment Techniques for Marine InformationJing Zhao, Yong Xiang, Fengkai Liu
- CS908
Research on the analysis of commercial economic data based on hierarchical clustering algorithmYifei Wang
- CS909
Application of Digital Close-range Photogrammetry Based on Hydrodynamic Model in Deformation Measurement of Model TestShuhui Jiang, Wenjin Wang, and Wanying Qin
- CS910
Design and Analysis of Machining Quality Control System Based on Finite Element TechnologyLie Yang
- CS912
User Preference Significance Impact Measurement Based on Eye-Movement Data--Case Study of Decorative Pattern of Wardrobe DoorYuan Yang, Han Wu
- CS915
Application of dynamic association rules in network data miningSong Changxin, Ma ke
- CS918
Medical CT Images Classification Model Based on BBO-HS Algorithm Optimized SVMSun Rui
- CS919
Study on Sector Capacity and Workload Model of Air Traffic Controllers Based on Least Square MethodLiao Chenxi, Wei Zheng
- CS920
Design and Application of Comprehensive Evaluation Index System of Smart Grid Based on Coordination Planning of Main Power DistributionZhu Rui
- CS922
Research on facial expression recognition of robot based on CNN convolution neural networkZhenhua Nie