Abstract:Android phones have a large market share in the world, and the third-party system based on Android-derived is also very popular. As the security issues appear in Android systems frequently, this paper uses Clang to compile Android source code for static analysis. This analysis extracts rules and models from published CVE vulnerabilities, and uses the improved Clang to statically analyze Android source code to detect potentially unsafe code snippets. During the analysis of the Android source code, the Clang static analyzer taints attack surface, and calls the new added STP constrained solver. Then it taints sensitive data through the symbolic execution, and makes taint analysis on the sensitive functions, sensitive operations, sensitive rules, finally reports unsafe code snippets if there are potential security risks. Through experimental analysis, this method can accurately identify unsafe source code snippets that exist in the Android source code with the same type of security risk, and this method can detect five high-risk CVE vulnerabilities in the libstagefright module.

Abstract:With the rapid development and wide application of SAN technology, multi-path technology becomes one of the key technologies to achieve disaster tolerance and high performance. Based on the existing techniques, an improved multi-path storage sub-system is presented. And then improvement is made in four modules, i.e., LUN ownership management, configuration of ALUA, path selection strategy, and I/O forwarding implementation. The test results show that this scheme can be a very good solution to the path failover and load balance problems, greatly enhancing the I/O performance.

Abstract:In the desktop computing environment, files and directories are frequently changed, such as being created, deleted, modified, renamed, moved, and copied, which has higher demands on the real-time updating of desktop index and its efficiency. However,the traditional desktop index updating methods are fully or partially dependent on periodically full scan, which inevitably requires a large-scale index reconstruction and leads to long delay of index generation and high usage of system resources. In order to overcome these drawbacks, this paper puts forward a new desktop index real-time updating method based on a new file system events monitoring, and implements corresponding desktop index real-time updating system. Experimental results show that the proposed index updating method provides lower latency and lower usage of system resources.

Abstract:The text is informal in social networks. One of the common phenomena is that there are a lot of morphs in social networks. People are keen on creating morphs to replace their real targets to avoid censorship and express strong sentiment. In this paper we aim to solve the problem of finding real targets corresponding to their entity morphs. We exploit the temporal and semantic and POS constraints to collect target candidates. Then we propose a method based on joint character-word training to sort the target candidates. Our method does not need any additional annotation corpora. Experimental results demonstrate that our approach achieved some improvement over state-of-the-art method. The results also show that the performance is better when morphs share the same character as targets.

Abstract:As an effective strategy to improve the efficiency for CPU reading and writing, and to fill the speed gap between CPU and the main memory, the cache in CPU makes the best of the locality theory by storing the latest or the most frequently used data. It dominates the performance of a CPU, and the microarchitecture of the cache, however, dominates the cache performance. The modern advanced cache commonly constructed with very complicated structures, contain multiple cache strategies, hardware algorithm and multi-level design, making it expensive to design and verify directly with hardware for time as well as money. Thus, it is far-reaching to simulate the hardware microarchitecture by software modeling. Cache microarchitecture simulator exactly assists the design or the evaluation of an excellent cache. In this article, a highly configurable and extensible cache microarchitecture functional simulator CMFSim is developed on the basis of hardware structure. It implements the common cache strategies and hardware algorithm, which can conveniently simulate the cache microarchitecture for the given configuration and analyze the performance with the specified parameters.

Abstract:In this paper we present BAEG, a system to automatically look for exploitable bugs in the binary program. Every bug reported by BAEG is accompanied by the control flow hijacking exploit. The working exploits ensure robustness that each bug report is security-critical and exploitable. Giving BAEG a vulnerable program and an input crash, the challenges are:1) how to replay crash and get the state of crash; 2) how to automatically generate exploit. For the first challenge, we present a path-guided algorithm, take crash input as symbolic data, and replay crash path. For the second challenge, we summarize the principles of multiple control-flow hijack and establish the corresponding exploit generation model. Besides, BAEG can explore deep code especially for invalid symbolic read and symbolic write, which can help us decide whether there still are exploits at deeper code.

Abstract:In recent years, with the rapid development of Internet technology, cloud computing services begin to widely spread. Large-scale Internet companies, small and medium enterprises have begun to provide their own cloud computing services. The Chinese Academy of Sciences also provides a cloud computing service platform-CAS "science-cloud". Concerned with the actual needs of the "Science Cloud" project of the Chinese Academy of Sciences, this paper designs and implements a spider-based data monitoring system referencing the function and operation mode of the existing commercial cloud monitoring systems. Compared with the commercial cloud monitoring system, this system supports the monitoring of URL (Boolean) type data, adds the monitoring of numeric types and text types, supports better monitoring of the third party services, and realizes service failure alarm and monitoring data Visualization and monitoring data distributed storage.

Abstract:With the economic development in society, people do not only pursue higher material life, but they also pay more attention to their physical health and monitor their own health information. This paper introduces the National Physical Fitness Monitoring System, which is used to monitor the users' personal information, health data and basic motion data, and provide a complete one-stop service solution for health management and chronic disease intervention. The system consists of data statistics and analysis subsystem based on.NET MVC, data synchronization service and data aggregation service based on Windows service and system monitoring program based on Zabbix and so on, and the system can also provide access forms:the Web and the mobile terminal access. The data statistics and analysis subsystem is used to count the user data, and it uses the data mining technology to give the statistical analysis result and the scientific fitness guidance scheme. The data synchronization service is used to prepare data to ensure data integrity and consistency of the system. The data aggregation service aggregates data from the ground station database of provincial data center to the central database, and the data can be exchanged between the central database and the data statistics and analysis subsystem. The system monitoring program monitors the server networking, IIS state, the state of the database as well as the possible errors in the running process of the system, and gives the warning information by message or e-mail. The National Physical Fitness Monitoring System, we designed and developed, provides an effective national physical fitness monitoring and scientific fitness guidance scheme to help users improve their physical condition.

Abstract:As one of the most popular tools for automatic operation and maintenance in cloud platforms, Ansible usually stores a lot of administrator accounts information in a configuration file for batching executions. The configuration file is usually stored in the disk in plain text. However, it is not safe in the cloud because the confidentiality and integrity of configuration of Ansible depend on the security of the underlying software. Therefore, it is crucial to reinforce the security of configuration management mechanism of Ansible. In this paper, we implement a configuration management component for Ansible based on SGX (Software Guard eXtensions) proposed by Intel in recent years, which can manage the configuration information of Ansible in a trusted execution environment (TEE) independently. With this component, the configuration information cannot be read or written from outside and its security doesn't depend on the underlying software. The experiments show that our solution is more reliable, and the extra overhead is also acceptable. It is possible to extend our application to a general component for configuration protection in cloud platforms such as OpenStack.

Abstract:To improve the poor quality of industrialized sea cucumber farming, the system of water quality monitoring, aquatic environment water quality analysis and evaluation, underwater video observation and breeding knowledge popularization were designed and realized. The system has been tested to be accurate in the water quality, and the underwater video observation is real-time and clear, which can meet the actual needs of sea cucumber breeding. The promotion of the system can help aquaculture enterprises to carry out breeding decision-making, and improve their intelligence farming. The use of industrialization and intelligence in the field of aquaculture vertical diffusion and deep integration helps to explore the modern farming model, to enhance the smart technology in the fishery economic development contribution rate.

Abstract:At present, there is an increasing demand for intelligent functions such as machine vision and autonomous path planning in industrial robots. However, adding intelligent function modules in the traditional industrial robot systems requires a lot of source code modification, wasting manpower and cost. An easy-to-extend robot system development platform based on ROS presented in this paper provides developers with the convenience of developing intelligent industrial robotic systems. The platform is divided into server-side and robot-side. The robot-side as a first-level node, communicates with the server-side installed with the ROS. The first-level node of the robot consists of the second-level functional nodes and functional modules. According to this platform, the JPB06 6-DOF industrial robot system has intelligent function modules, such as machine vision, autonomous positioning and voice control, which can meet the needs of industrial robots for intelligent and real-time control.

Abstract:The traditional log analysis technology has low efficiency, simple function, poor scalability in practice in processing the large-scale log. To solve these problems, a large-scale log collection and analysis system based on Docker is designed. There are five layers including data collection, data cache, data forwarding, data storage, data retrieval and display in the system. And the system can take in any type of log files from different data sources, provide reliable data transmission through Kafka message queue, utilize Elasticsearch to realize distributed storage and retrieval of data, and analyze log by means of visualization. Meanwhile, the use of docker container technology can realize rapid deployment and version control of the system. The system has the characteristics of real-time, scalability, easy deployment and so on. The experimental results show that the system is feasible and effective with good practical value.

Abstract:With the development of multimedia technology, and the real-time communication technology, people's requirement for real-time audio and video communication is higher and higher. The WebRTC technology emerges and occupies the market quickly based on its powerful audio and video processing engine, which has a huge impact on multimedia communications industry. WebRTC JSEP provided, however, can only perform simple media link function. It is required to combine with other modules or signaling protocol to do a complete application in the communication of enterprise. This paper focuses on the WebRTC communication with the SIP, and in the iOS terminal it designs and implements a kind of application layer gateway based on WebRTC technology. Finally, the feasibility and practicability of the gateway is verified with experiments.

Abstract:This paper presents a method to transplant Android's graphic system, SurfaceFlinger, to run on desktop Linux distribution's X Window System. SurfaceFlinger running on X can make UI of the Android applications, running as native processes in the desktop Android runtime, show in a window of X. Using Mesa as the OpenGL ES implementation and making Mesa EGL compatible with Android's native window, together with gralloc.drm.so module, the Android UI rendering process and SurfaceFlinger's graphic compositing process can be implemented by using the GPU for hardware acceleration. In addition, using X11's DRI2 extension to coordinate window of SurfaceFlinger with X Server's DDX driver, can avoid graphic buffer coping from GPU's dedicated memory to the system memory. In our experiment, the third-party 3D benchmark software San-Angeles can achieve 60FPS on variety GPUs. Compared with the existing method, the architecture of our method is more concise, efficient, and supportive of hardware acceleration.

Abstract:In accordance with the sender's message, through a series of steps such as information extraction and semantic analysis, the SMS automatic 3D animation generating system can generate a 3D animation and eventually send it back to the sender. The animation light cannot only light the whole scene, but can also foil themes, atmosphere, etc. This paper mainly focuses on automatic generation of light in SMS automatic 3D animation generating system, including qualitative planning and quantitative calculation. The qualitative planning describes themes and templates which are about light by ontology. The rule base is used to combine the subject, templates, scene, and illumination properties by rules. The quantitative calculation is combined with the specific scene, the qualitative planning information into specific data, and then calls the Maya API, and the results of qualitative planning in the Maya scene.

Abstract:Based on messages sent by users, the 3D animation automatic generation system of mobile phone, after a serial process of information extraction, plot planning, would generate a video animation and send it to the receivers. The layout planning is an important part of the automatically generated system, which can place the model to the space on the animation scene. Through the study of layout problems, this paper proposes a hierarchical layout method based on the regional and model layout. It includes qualitative planning and quantitative calculation, using semantic web technology to build hierarchical layout knowledge base, derivation of hierarchical layout qualitative planning scheme based on rule, dynamic calculation of model location. Finally, experimental results show that the hierarchical layout planning is effective and diverse, and it meets the requirements of automatic generation system for layout planning.

Abstract:The traditional Web IM requires both sides to install plug-ins (such as Adobe Flash Player) in the browser, which does not only reduce the user experience, but also increases the developers' tedious work for plug-in development, updating and maintenance. In addition, the traditional Web IM mainly adopts the method of the regular access server (the polling mode) to achieve the interaction between the browser and server, which reduces the real-time performance and increases the consumption of server resources. According to the problems above, this article implements the long connection between the browser and server and data interaction through WebSocket, which improves the real-time performance. Then on the basis of providing WebRTC API, we implement a module which performs the function of audio and video communication and file transfer. Through the MVC three-tier architecture model, we carry on the concrete division and implementation of the module. Finally, the test shows that the design can meet the basic functional requirements of the user.

Abstract:The SSL/TLS protocol is one of the most widely used security protocols in communication security and identity authentication. It plays a very important role in ensuring the security of information system. However, due to the complexity of the SSL/TLS protocol, web sites are prone to security vulnerabilities such as code implementation vulnerabilities, deployment configuration defects and certificate key management problems when implementing and deploying SSL/TLS protocols. This type of security problems often occurs in Web sites, which also causes a lot of network security events, affecting a large number of sites. However, the existing methods to analyze and detect web security cannot satisfy the need. First, there are very few tools in this field, and their targets tend to focus on some certain aspects. In addition, these problems need to be further explored to acquire more detailed analysis and recommendations. In this paper, we design and implement a detection system to test the SSL/TLS protocol deployment of web site based on SSL/TLS. Our system performs vulnerability scanning and analysis mainly from three aspects:protocol basic configuration, cipher suites support, and typical attack test. We use it to scan the top 1 million websites of Alexa, and give detailed statistics and analysis. We found that the unsafe cipher suite 3DES is generally supported and the critical expansion OCSP Stapling support rate is less than 25%. What's more serious is that there are still many sites suffering from HeartBleed attacks and many other serious problems. Finally, the corresponding solutions or suggestions are given for the main problems in the scanning results.

Abstract:A MMORPG (massively multiplayer online role-playing games) is developed based on Unity 3D. The character controller, the mouse-value interactive algorithm, the motion strategy and the AI-interaction are used to enhance the game performance. In order to improve the working efficiency of game, this paper proposes client resource forecast and synchronous reading by using coroutine technology. The strategy that uses coroutine technology in forecast reading of maps can make it possible to have long-time reading running in the spare time of the system. Experimental performance analysis and experimental results both show that the optimization method proposed can effectively reduce the time complexity of the program and enhance the efficiency of game runtime.

Abstract:Microservices refine the granularity of services, and the monitoring of flexible microservices is the core of the microservices management. With the aim of extending the full-link application service monitoring, a flexible microservices monitoring framework is designed and implemented on the existing service management layer to monitor the microservices status and the changing service load. Compared with the existing distributed monitoring architecture, the framework is more flexible, more aware of service changes. The Raft algorithm is used to enhance data consistency and avoid single point failure. The experimental analysis shows that the cost is smaller, and the validity of the framework and the method is verified in the actual project.

Abstract:In order to fully tap and apply the information of textbook reviews on the e-commerce website, we use fine-grained emotional classification algorithm to analyze the user's online comments, based on the sentiment analysis results of product feature level, so as to assist customers and businesses to make reasonable and effective decision. In this article, we first use the crawler tool to collect online comment texts of teaching materials, and carry on some pretreatments such as denoising, segmentation and POS tagging, and then analyze the product features, based on the general emotional dictionary expands domain sentiment dictionary. Finally, based on the syntactic analysis results, combined with the language features of textbook comments, we design an affective tendency analysis algorithm which is suitable for the textbook reviews, and prove the validity of the algorithm through experiments.

Abstract:Most hyper-ellipsoidal clustering(HEC) algorithms use the Mahalanobis distance as a distance metric. It has been proven that HEC, under this condition, cannot be realized since the cost function of partitional clustering is a constant. We demonstrate that HEC with a modified Gaussian kernel metric can be interpreted as a problem of finding condensed ellipsoidal clusters(with respect to the volumes and densities of the clusters) and propose a practical HEC algorithm named K-HEC that is able to efficiently handle clusters that are ellipsoidal in shape and that are of different size and density. We then try to refine the K-HEC algorithm by utilizing ellipsoids defined on the kernel feature space to deal with more complex-shaped clusters. Simulation experiments demonstrate the proposed methods have a significant improvement in the clustering results and performance over K-means algorithm, fuzzy C-means algorithm, GMM-EM algorithm and HEC algorithm based on minimum-volume ellipsoids using Mahalanobis distance.

Abstract:German cache coherence protocol is used in parallel multi-processor systems, and the verification of German protocol has always been a hot spot in international industry and academia. We generate the flow chart of German protocol and describe each step of the flow chart. Besides, we present a method to verify the cache coherence protocol by flow analysis and inductive invariants in this paper. By searching for the relations between the invariants and the flow chart of German protocol, we can further analyze and verify the correctness of German protocol.

Abstract:Huaihe River basin is one of the key areas for the water environment control. Due to its complicated water situation, water pollution is easy to happen. This paper considers the situation of emergent water pollution and how to schedule the ecological water in the dams and reservoirs to control the pollution in the shortest time. Dam scheduling problem is the combinatorial optimization problem, and the efficiency of scheduling is the objective function. The constraints include water storage capacity, concentration of water and dam distance. In this paper, the artificial fish swarm algorithm (AFSA) is applied to water pollution control requirements, which is adopted and satisfied. AFSA has the advantage of fast track change and jumping out of local extremum, and can avoid possible premature problems at initial stage. Experimental results show that the water ecological scheduling method based on AFSA performs accurately and efficiently in dealing with such problems. It can find near optimal solutions within fewer iterations, and the results have better feasibility and referential.

Abstract:In order to improve the recognition rate of vehicle in natural situations, this paper proposes a vehicle logo recognition modal based on a multi-path tree structure convolutional neural networks, which modal with different convolution kernel in the same convolutions, namely T-CNN. Firstly, different layer convolution features are obtained and are joined together as the input of the fully connected layer to get classifiers. Compared with the traditional method, the theoretical analysis and simulation results show that T-CNN can increase the recognition accuracy up to 98.43%.

Abstract:In order to improve the scientificity of power material subdivision and the rationality of demand forecasting, this paper constructs the power material subdivision model based on NPCA-SOFM algorithm with the material demand characteristic as the breakthrough point. Firstly, the non-linear principal component analysis (NPCA) is used to reduce the dimensionality of the index and the loss of information caused by the standardization of indicators. Afterwards, we use the SOFM neural network algorithm to cluster the principal components after dimension reduction. Finally, the validity of the method is verified with an example. The results show that the clustering performance of NPCA-SOFM neural network algorithm is superior to PCA-SOFM and SOFM algorithm alone, and the dimension reduction effect is more obvious, which can provide reference value for intensive management of electric material and enterprise operation decision.

Abstract:The traditional methods of personalized recommendation are faced with the problems of sparse data and cold start. This paper combines the previous research of the project team and introduces the user interest to form the comprehensive similarity, based on the comprehensive consideration of user characteristics and user trust degree. At the same time, this paper uses the social tags which enrich the recommendation data to solve the problem of sparse data in current recommendation system. Firstly, the similarity degree is used to find the similar neighbors of the users and form a tag set by labeling the similar neighbors. Secondly, a tag-based recommendation algorithm is used to generate the final recommendation list. The experimental results show that the proposed algorithm can effectively improve the accuracy of recommendation and the recall rate.

Abstract:With the rapid development of micro-blog, spam detection and filtering is faced with enormous challenges. It is significant to realize realtime and accurate detection of spam, which is important to improve user experience and the sustainable development of micro-blog platform. In this paper, a spam detection method based on multi-features of micro-blog is proposed. The main procedures are:first, the features of user and content are extracted. Second, LDA is applied to extract latent topic features. Finally, the features above are fused and a proper classifier is trained based on SVM. Experimental results show that the precision and F1 get increased while adopting the method proposed in this paper compared to the pervious methods.

Abstract:As the label is marked by the user according to their own understanding and preferences, the expression of the concept is fuzzy and there are a large number of noise tags, resulting in the low efficiency of the traditional label-based recommendation algorithm recommended. casein view of this problem, a tag recommendation algorithm combining the score information entropy is proposed. The algorithm determines the importance of the tag for the user in order to build the user's interest model for the rating of the label. The algorithm can effectively use the score weight and combine the information entropy to enhance the recommendation accuracy, and compared with the previous label-based recommendation algorithm, it can get a satisfactory recommendation effect.

Abstract:The traditional ARIMA time series analysis method is based on the linear technology to predict the time series, while its processing of nonlinear data is not reasonable with poor effect. There are many factors influencing the demand of power supply, and most of the material sequences usually contain both the linear time series and the nonlinear time series. In this paper, based on the ARIMA forecast, the BP neural network is combined with error correction to extract the composite features in the material sequence in order to improve the forecast precision of the electric power materials. The experimental results show that the accuracy of power supply forecasting with error correction can be improved significantly, which can provide important data support for material procurement plan.

Abstract:Aiming at the problem of mileage calculation and statistical error based on vehicle real-time latitude and longitude information in the current application of vehicle networking, this paper presents a method of computing the vehicle mileage under low frequency of signal sampling. Firstly, the trustworthiness of the starting point is verified to eliminate the influence of the starting point drift. Secondly, the continuous large-angle filter, large distance filter, large speed filter, and large acceleration filter are combined to eliminate the noise. On this basis, velocity interpolation and angular interpolation are combined to compensate for the curve. In addition, for the lost data, mileage compensation is made based on the path planning method of electronic map calls, to further improve the accuracy of the algorithm. Experiments show that this algorithm still has high accuracy and efficiency at the lower position signal sampling frequency.

Abstract:Urban road vehicle detection is an important part of modern intelligent transportation system-ITS. According to image sequence time-space relations of continuous change, the underneath shadow feature vehicle detection algorithm is further improved by constructing the time-space model of video image sequence, and is combined with the AdaBoost algorithm, filtering out false candidate region of vehicle. Experimental results demonstrate that the accuracy rate of proposed algorithm is 92.1%, with the false positive being 4.3%, the resolution of image being 1920*1088 and the time of processing being 76ms under the complex urban traffic environment. The algorithm effectively improves the high false detection rate and low effectiveness of AdaBoost and underneath shadow feature detection algorithms, and can meet the accuracy and robustness requirements of vehicle detection in the urban road environment.

Abstract:With the growing population of elderly people, the safety of the elders living alone becomes a rising issue for the society. Falling down is one of the most common and greatest risks and injuries occurring to the elders living at home. There have been many algorithms on elderly falling detection. However, the vast majority of the existing methods, which use foreground extraction to get human body silhouette are implemented on static cameras. It means that we should implement cameras for every independent region in the house to make sure that the elders is visible in the frame, which is impractical. This paper proposes a novel approach for detecting human body falls based on image semantic segmentation and convolutional neural network model(CNN), which can be implemented on portable cameras. First, the fully convolutional network(FCN) is used to segment human pixels in the frame. If the body shape meets the conditions of area ratio, aspect ratio is used to estimate whether it is a falling body or not. Otherwise, a combined CNN classification model is used. Regions of human body are classified in three cases (fall, stand, half-lying) and the results are used to estimate whether there is a falling body in the frame. From the experimental results we achieved, it was concluded that our method has a high recognition rate (91.32%) and low false alarm rate(1.66%).

Abstract:Aiming at counting the grain number per spike in wheat breeding, a novel method based on fractal image segmentation is proposed in this paper. Firstly, a square image window is selected. Then, the fractal dimension of the window is set as eigenvalue of its center pixel. In order to extract the wheat spike, a proper threshold is selected to segment the image according to the pixel eigenvalue. To make the wheat spike perpendicular to the row direction of image, the angle between the wheat spike and the vertical direction of the segmented image is computed through analyzing row data of the image. The image is rotated according to the angle, and an angle-adjusted image is obtained. At last, the grain number can be calculated by column data of the angle-adjusted image. Experiments show this method achieves a higher accuracy and better efficiency than the traditional counting method.

Abstract:A solution of staged simulated annealing is proposed to settle the schedule problem of senior high schools. The difficulty of the problem mainly lies in how to solve lots of conflicts existing in the schedule and how to optimize it. We initialize a schedule with conflicts randomly, and dissimilate the structure of the solution with artificial intervention to make the schedule feasible in the first stage. In the second stage, we try to make the schedule meet general constraints by instructively changing the structure of the schedule. In the third stage, we generate optimized solution through varying the schedule with heuristic dissimilate random field employed. In order to meet the demand for diversified schedule, the actual production environment in the user interface provides the manual adjustment to the schedule. It is found that the improved simulated annealing algorithm has a faster convergence speed, and higher operation efficiency in solving curriculum schedule problem of senior high schools and in the case of less number of iterations, it can also generate a feasible solution.

Abstract:Pulse Coupled Neural Network (PCNN) is a new generation artificial neural network (ANN) based on biological vision. It has wide application prospects in the field of digital image processing and artificial intelligence. In this paper, we propose a method to extract face features by studying PCNN theoretical model and its working characteristics. Firstly, the low frequency feature of face image is extracted by wavelet transform. Then, the simplified PCNN is used to extract the corresponding time series of face image reconstructed by wavelet low-frequency coefficient, which is used as the feature sequence of face recognition. Finally, the face recognition process is completed with time series and Euclidean distance. In this paper, we demonstrate the effectiveness of the method with ORL face database.

Abstract:With the escalating of EAST and the continuous improvement of plasma discharge parameters, the obtained plasma current and energy storage also have been increased. Once such a high-energy plasma disrupts, the harm to the first wall of the experiment device is destructive. This article is to handle the abnormal events occurring during the plasma discharge, and proposes the algorithm which can control plasma current in the abnormal state of the slope down through the code. The abnormal plasma is controlled by the active feedback control method, and the current of the plasma can be sloping down. The effectiveness of this method has been verified by a simulation server with a circular plasma model.

Abstract:This paper designs and implements a cervical spondylosis prevention system based on pressure sensors and the computer camera. This system obtains the body pressure data through a cushion which contains many pressure sensors, and the human face data through a computer camera. We optimize the number and layout of pressure sensors in the cushion, and reduce the computational complexity by image processing by recognizing facial features. By fusing the data from both pressure sensors and camera, this system achieves a more accurate sitting posture recognition, comparting with using pressure sensors and camera separately. The results are further used to estimate the risk level of cervical spondylosis for the users. The system can also guide the users to complete a series of given actions to test their criticality or potential risk of cervical spondylosis. This system is smart, well-designed, and non-invasive, and hence quite applicable to common workplaces.

Abstract:Sql statement tuning is an important aspect of database performance tuning. To achieve the same effects, sql statement has a variety of wording, with different performance for the different wording. Even with only one sql statement, the oracle also has a variety of ways to implement. That is, there are multiple execution plans. The oracle compares the performance of these multiple execution plans, the cost of resources, to select the optimal execution plan. In assessing the performance of each implementation plan, the oracle needs the implementation of sql statement with the environment, that is statistical information to calculate the cost of the number of resources for each implementation plan. Therefore, it is critically important for the oracle to choose the best implementation plan to collect as much as possible accurate statistical information. Among them, the collection of the histogram plays a very important role. The experiment verifies the impact of the histogram for the sql implementation plan, which clears the circumstances under which it needs to collect histograms.

Abstract:Based on the control of the whole production process, to make emissions of SO₂ concentration conform to the standards in the production of sulfuric acid with pyrite, we propose prediction for SO₂ concentration of tail gas with GA-ELM modeling. In the production of sulfuric acid by pyrite, we collect the key parameters with greater influence on the SO₂ concentration of exhaust gas, and use GA-ELM neural network to predict the SO₂ concentration while producing acid with exhaust gas. The method is tested in a factory, and the predicted results are highly identical with actual data. It plays an important guiding role for the adjustment and optimization of process index and exhaust emissions conforming to the standards.

Abstract:The AC motor is simple in structure, easy in manufacture, low in cost, easy to control. It is gradually replacing the DC motor in many cases and becoming the first choice for motor users. However, the speed regulation system of AC motor is very complex. It is difficult to match DC motor. This paper designs an AC motor control system based on the ARM platform which makes use of Vector control and PID algorithm to control the AC motor exactly. The system has three parts:hardware, software, and the interface of the host computer. The hardware circuit includes current acquisition and IGBT circuit. The software part uses C language and KEI MDK software development tools to program. The upper computer uses the LabVIEW software to write the test interface and runs the PID program. Finally we develop a set of motor control for AC motor speed control system.

Abstract:It is the time of "Internet+". This paper develops a mobile electronic newspaper reading system based on HTML5 for readers to read online newspapers, especially with mobiles. This system solves the problem of reader's reading from the traditional PDF file to HTML5 document which has rich reading experience. This article focuses on implementation techniques of this system, such as backstage subsystem, Android client, and how to use JSON technology to realize the information exchange between front and back stages.

Abstract:Nowadays, the run-time performance of server becomes a crucial factor for online games. To solve the problem, this paper proposes a new method, which uses the callback strategy based on templates, to improve the run-time performance of game-server. Based on Visual Studio and C++, the key technology and strategy during the erection of server are researched. In the article, the server is divided into 4 parts:database, account server, network and map. The experimental result shows that the delay in server session reduces obviously by using the callback strategy based on templates. Through this experiment, it is proved that the key technology proposed can be used in VR environments, game development and many other fields and has practical value.

Abstract:Studies in vehicular ad hoc networks using public goods game theory to enhance the cooperation show that the performance of cooperation in those types of network would have been poor in the areas with high vehicle density. In this paper, the result of simulation shows that the certain range of degrees of vehicle will enhance the cooperation in network. Therefore, we propose a grouping game model with the concept of the game degree and game topology to enhance the cooperation in the areas with high vehicle density. This model can change the game topology and reduce the game degree of nodes. The experimental results show that using this model in any high density regions of vehicles can significantly enhance the performance of cooperation in the network.

Abstract:This paper proposes a method to accelerate the virtual router's data plan by VPP. This method separates the virtual router into control plan and data plan, then moves the data plane's transform work to the VPP running in Linux userspace and alters the VPP's route table by listening to the control plan info. In this way, it could eliminate the bottleneck of the traditional virtual route's rate of transform packets which make it possible to replace the network device with standard x86 platform server. It can promote the network function virtualization in some way and make the network resource more flexible and easier to be managed.

Abstract:A mobile video monitoring system based on Node.js is designed by using OpenCV coupling with Web front-end technology in this paper. The system adopts B/S structure. Node.js server is built on windows system for acquisition and transmission of video data and OpenCV built on the same system is used for image processing and encoding. The client is made with Web front-end technology and Hybrid App development model running on the mobile terminal, to provide monitoring function. The test results show that under WiFi environment, the system carries out multi-user and real-time monitoring effectively.

Abstract:The DMA transfer design of PCI Express bus interface is realized by FPGA based on the in-depth understanding of PCI Express protocol and its application technology. This paper mainly introduces three parts of the design:DMA sending module, DMA receiving module and DMA state control module in detail. Finally, it realizes PCI-E driver in one PC based on Linux system, then uses miniBEE as a test platform of BEEcube Company to test the design and give the results.

Abstract:Smart residential areas information portal system contains a large number of sensitive data related to the residential life and property security. In order to ensure the confidentiality of the data, optimized AES encryption algorithm is used to encrypt the data to reduce the encryption time, thereby reducing the communication time delay, which improves the performance of the system a lot. The principle, as well as the flow of encryption and decryption of AES algorithm, is analyzed in the following sections. In order to overcome the problem that the time used in decryption is longer than in encryption, a simplest matrix in the Galois field GF(2^8) is going to be adopted in MixColumn and inverse MixColumn operation to reduce the computation and time consumption in decryption. And then based on this, the steps in encryption and decryption process is merged and optimized in some degree, reducing the storage space, at the same time it can keep the execution efficiency. In the Visual Studio 2010 platform, several optimized AES algorithms are implemented in intelligentHome by adopting C language. It shows that the proposed optimized algorithm has higher efficiency and occupies less storage space.