Abstract:RED diagrams represent states of a timed automata in a single and integrated diagram for both the dense-time and the discrete parts of the states. This integration contributes greatly to the considerable efficiency of the model checker RED in verification of timed automata. On the other hand, the state-of-the-art model checkers for probabilistic timed automata (PTAs) still use different representations for the dense-time and the discrete parts of probabilistic states. This paper proposes an elegant way to extend RED diagrams to represent probabilistic states, yet reuses the structures of original RED diagrams and hence preserves their efficiency. It also implements a prototype tool for reachability analysis of PTAs based on the extended RED diagrams, while the PTA benchmarks distributed within the probabilistic model checkers PRISM and Modest are used to evaluate its performance. Experimental results show that our integrated representation of probabilistic state space can indeed help improve the time efficiency and scalability for PTA reachability analysis.

Abstract:StackExchange is one of the most popular Q&A rendezvous, including dozens of Q&A communities. In the paper, based on the Q&A relationships and the geographical information of users, this paper analyzes the knowledge spreading patterns in Q&A communities in StackExchange in USA and statistical characters of networks. It extracts spreading patterns of Q&A communities and obtains knowledge sharing methods of users. We find that, generally, a Q&A community may have several spreading sources. Meanwhile, it establishes a spreading network for each Q&A community and finds that most of these spreading networks share similar statistical characters, indicating that these Q&A communities have similar spreading patterns.

Abstract:After the fact that an adversary obtains an actor's long-term secret key, the adversary may impersonate other actors or obtain secrete information with the key. This kind of attack is called AKC (Actor Key Compromise) attack. Except for key exchange protocols, not much attention has been paid on other types of security protocols in the research of AKC attacks. In this paper, we consider this AKC problem and provide systematic analysis of AKC attacks, its attack patterns and countermeasures. Based on experimental analysis, this paper classifies four AKC attack patterns, and three corresponding protocol models and design principles to protect against AKC attacks. Based on these models and principles, it proposes a heuristic algorithm that transforms a protocol into an AKCS one (that keeps security property under AKC attacks). As case studies, it apply the algorithm on protocols including Email, SET and Kerberos. The results show that these protocols are vulnerable to AKC attacks, but after the transformation by the algorithm, they are no longer vulnerable to such attacks.

Abstract:Blind demodulation is one of the most important technologies to obtain useful information on non cooperative digital communication signals. This article firstly summarizes the blind demodulation of existing digital communication signal. And then it further improves the theory and noise reduction algorithm of nonlinear dynamical system on the basis of our published paper to blind demodulation the random bit stream on carrier frequency modulated by BPSK with negative SNR. The test results show that Bit error rate is 0, using nonlinear dynamical system noise reduction under Eb/N0>7dB and blind demodulation error curve of noise reduction is lower than the error curve of existing non coherent demodulation method under 0 < Eb/N0 < 7dB. Therefore, the blind demodulation of nonlinear dynamical system noise reduction compared with existing non coherent demodulation at least improves the processing capacity of 7 db. Test results show that the research results provide an effective method of blind demodulation for electronic reconnaissance signal processing.

Abstract:Android is the mobile operating system which has the highest market share of 84.2%. Its open access mechanism not only brings more users and developers, but also a lot of security issues. According to the survey by China Internet Network Information Center, only 44.4% of users will view the authorization instructions carefully in the process of downloading and installing an application. Most people have the risk of blind authorization. For software developers, due to the lack of strong supervision and proper permission specifications, application authority abuse in the procedure of Android application development has been widespread, which seriously affected the code and quality specifications. Besides, the user's blind authorization and the software developer's permission application abuse has become the main reason for the users' information leakage. In this paper, based on the existing permission detection scheme, it designs and implements an abuse of authority detection system named PACS. Test results show that 812 applications abuses permission among 1077 applications, which account for about 75.4%. Meanwhile the sampling of test results proves the accuracy and validity of the PACS's results.

Abstract:Phishing is a kind of online fraud that combines social engineering techniques and sophisticated attack vectors to steal the users' sensitive information to achieve the illegal purpose. In order to detect phishing web pages quickly and efficiently, this paper presents a model for depth detection of phishing web pages based on ensemble learning. The model uses page rendering to deal with common page camouflage, extract several sensitive features including URL and domain features, link and reference information, and contents of text messages; and then constructs and trains several base learning models with ensemble learning method using the features above; finally, generates the final result with base models using classification and integration method. Experiments on PhishTank indicate that the detection model this paper proposed has good accuracy and recall rate.

Abstract:Virtualization presents a variety of trends in development, including both hypervisor-based and container-based classes. The former virtualization has the characteristic of well isolated and convenient operation, the latter one is lightweight and supply shortcut. With the rapid development of IT technology and the depth in application, complex applications require both types of virtualization to provide services. This paper proposes a two-stage approach to resource management, the first stage is to resolve physical resources monitoring, statistics, allocation of decision-making and isolation, allows a single physical resource has the ability of multiple virtualization resource abstraction; the second stage schedule for solving the resource needs of users and the underlying physical resources in place in order to achieve the object of increased physical resource utilization. While first stage scheduler also takes into account the difference in heterogeneous physical resources, and introduces a weighted DRF algorithm evaluation of heterogeneous physical effect on application performance. Based on the CloudSuite experiments, on the premise of guaranteed QOS parameters, the system resource utilization of the whole system is effectively promoted 20%.

Abstract:In this paper, based on cloud computing technology, using service oriented architecture (SOA) concept, from the structure, operation and development of SaaS application in three dimensions to build a smart cloud service platform for industrial park, aims to solve the integration of informatization service mode and the cost of park construction wisdom in the industrial process of industrialization and information depth problem. This paper provides a reference model for the industrial park's wisdom.

Abstract:With the development of robot technology and the popularity of hardware, the prospect of robot market is much brighter than in the past. However, there are still many limitations of robots, in particular the weakness of portability, high computing costs and few applications. With the raise of cloud robotics, computing process can be migrated from local robot to cloud, not only improves the computing power and reduces hardware costs of robot, but also allows a more balanced allocation of resources. In this paper, it proposes a service framework for ROS-based cloud robot. This service framework uses open-source robot operating system ROS as the basis for running the robot, enhancing its portability to different hardware and software environments. Meanwhile, it joins the service management system and service analysis module in the cloud, so that robot service can be easily expanded and quickly called. As the experiment part of the paper, it uses a face recognition service module to testing our framework for ROS-based cloud robot.

Abstract:Online examination compared to traditional examination methods has many advantages, such as lower cost, the real-time updates of the examination papers, online examination can offer statistical analysis of examination result in time, it also can generate different examination questions to prevent plagiarism. This paper systematically analyzes the architecture of online examination system and how to optimize system performance, such as front-end optimization based on Ajax, distributed caching mechanism and so on.

Abstract:This paper introduces an Engine Type of Quick Page Construction Service Based on Page Model. This service is ahead in electric power industry. With few codes or not, normal developers can quickly construct business applications with UI and business logic. This paper mainly expounds the principle and composition of Page Model, Page Designer and Runtime Engine in the Page Construction Services. Given the practical results of some supporting projects, it greatly increases the development efficiency and reduces operational costs, and it also has excellent adaptability and scalability.

Abstract:For the demand for informatization and flowing of management of teaching assistants(TA) in the university, the TA management system based on Symfony2 is designed and implemented. This paper introduces the present situation and the improvement direction of the TA management of our university, and then summarizes the functions of the TA management system based on Symfony2, finally focuses on the design and implement of the database, reminding and job evaluation module of the system. At present, the system can run stably for two semesters in our university, which provides the university with a reliable process of TA's work evaluation and saves the cost.

Abstract:EAST's inner structure is very complicated and contains a lot of subsystems which have different functions. The virtual EAST system aims to establish an EAST virtual reality scene in which the user can roam and access to information by interacting with the system. In order to facilitate the development of different systems' need, a variety of formats and types of device model are produced in the preprocessing stages. Besides, related parameter information, diagnostic information and magnetic measurement information are stored in MySQL database. The virtual EAST system's developers use and maintenance the model and data together. Therefore, in order to promote mutual cooperation of developers and avoid a collision from disoperation, it is necessary to establish a system to efficiently use those models and a unified entrance for viewing and managing models and data.

Abstract:In container-based virtualization platforms, detecting anomalies with fixed thresholds is not practical, because many kinds of applications completely shared physical resources. Furthermore, monitoring systems need to consider the tradeoff between the timeliness and overhead by adjusting the monitoring period. To address these issues, this paper proposes an online anomaly detection method based on Principle Component Analysis (PCA), and then adjusts the monitoring period according to the anomaly significance. First, it non-intrusively collects the monitoring data of containers to get a matrix for each container. Then, it uses PCA to present the main direction of each matrix, and calculates the abnomal significance by calculating the cosine similarity between the current direction and the last one. If the significance is out of the defined tolerability threshold, the monitoring system sends an alert message to administrators, and automatically adjusts the monitoring period according to the significance. The experimental results demonstrate that our method can detect typical faults injected in HDFS with the accuracy of 80%, the delay of alerts iswithin 5 seconds, and the monitoring overhead ismuch lower than that with a fixed monitoring period.

Abstract:With the rapid development of mobile networking, a logistics operation mode based on Wechat is constructed in order to present quality transport service, efficient communication, and a pleasant visual experience to the customers. A Wechat ordering platform is hereby designed and implemented. Adaptive web pages are designed at Wechat foreground based on HTML5, CSS3 and JavaScript; background utilizing Struts2 Spring, Hibernate and Ext-JS is constructed, first, through presentation of enterprise talents, events, unique services, the service value of logistics is fully recognized by the customers. Then, with web apps issued, an important platform is established for company's operation, the service system is intensified, and the business process is also standardized. Besides, through interaction, message becomes abundant, and the management and operating cost is reduced.

Abstract:The digital signal processor (Digital Signal Processing, DSP) is widely used in the field of signal processing, digital communication. The majority of modern high-performance DSP use long instruction word architecture, by exploiting instruction-level parallelism to launch multiple instructions at the same clock cycle out for a higher level of calculating performance. The article describes target system characteristics on BWDSP104x, BWDSP104x is designed in the light of high performance computing and processor, uses 16 launch, single instruction stream and multiple data stream architecture.in order to make full use of multi-cluster hardware resources, this paper proposes the back-end optimization about software pipelining based on the open-source compiler named Open64. Including the early stage of cycle options, resource constraints and precedence constraints computing, the classic Module-Scheduling algorithm is used in SWP-Scheduling, module variable expansion is for the conflict of registers using in different iteration. The experimental results show that program has better performance after software pipelining optimization.

Abstract:With the widespread of smart terminals, there appear a lot of applications to satisfy all kinds of needs in users' daily lives. Existing systems of smart terminals manage the background applications through an LRU-based task killing policy. LRU algorithm only considers applications' recent using logs instead of users' application using habits, it'll increase the application restart ratio and also lead to problems like increasing application launch delay, increasing energy consumption and losing state. In this paper, it designs and implements a Bayesian network-based application management policy named BNLP, which analyzs users' application using behavior to predict the probability of launching each application in the near future. Then BNLP will manage the background applications according to these probabilities. Experiment results show that our BNLP model can decrease the restart ratio of LRU by 17.2%, which greatly reduces launch delay, energy consumption and improves user experience.

Abstract:Logic model checking raise unique challenges to the efficiency and scalability of various algorithms. In this paper, it argues that the linear temporal logic model checking algorithm calls for an efficient and common solution. We then introduces a novel parallel on-the-fly model checking algorithm based on subset of states, namely SCPLM. According to the density property of subgraph with active states subset, SCPLM schedules parallel computing tasks dynamically, which has been proven to reduce the synchronization overhead significantly. It implements SCPLM on a lightweight parallel graph processing system, Ligra. A detailed evaluation using benchmarks shows that SCPLM outperforms the existing state-of-art algorithm by up to 1.2~1.3X, yet with much better scalability.

Abstract:With the continuous development of Internet, email has become a more popular forms of communication in people's life, and as well spam has become a major problem in E-mail users. Thus suppressing spam has become a rather urgent task. A minimum risk bayes algorithm based on the traditional bayesian is proposed on the basis of loss factor k, By adjusting the k value, the algorithm can improve the influence of spam false negative result, and reduce the loss of users at its best. At last, The results of the experiment indicates that the minimum risk bayes algorithm can make spam has a better filtering effect.

Abstract:Risk assessment is an important technology to ensure the security of information system. Information system risk assessment is subject to a number of effects and has dynamic and changeable, in order to improve the accuracy of information system risk assessment, this paper puts forward a information system risk assessment model based on hierarchical analysis method and neural network. At first, the current situation of the information system risk are analyzed, and this paper builds the evaluation index system according to the experts, and then the analytic hierarchy process is used to estimate the weights of evaluation indexes, and SVM neural network is used to establish the information system risk assessment model, at last, the reliability of the evaluation results is tested by using the risk data of information system. The results show that the proposed model can reasonably determine the weight of evaluation index, it can describe relationship between risk factors and expected value of information system, obtains ideal assessment results, and so it has certain practical value.

Abstract:Mutation strategy plays a decisive role on the success of the differential evolution algorithm(DE). However, the direction information has not been fully exploited in the design of DE and the balance between the evolution speed and the population diversity cannot be well handled so far. In this paper, it explores a novel direction information which is generated by the selection operation and it's directive effect on the mutation operation. On this basis, it proposes an evolution direction-based mutation strategy "DE/current-to-pbest/1/Gvector" and an improved differential evolution algorithm based on adaptive differential evolution algorithm(JADE) for comparison. We name our algorithm as DVDE and compare it with five state-of-the-art adaptive DE variants(JADE, SaDE, CoDE, jDE, EPSDE), using 12 standard numerical benchmarks taken from the IEEE Congress on Evolutionary Computation 2005. The simulation results indicate that the average performance of the DVDE is better than those of all other competitors, especially for the unimodal functions. The experimental results also illustrate that the using of the evolution direction is helpful to improve the algorithm's convergence speed, maintain the population, and effectively avoid premature convergence problem.

Abstract:With the rapid growth of Internet and Web service technology, the number of Web services having the same function is getting more and more. When constructing service-oriented applications, Quality of Service(QoS) as the non-functional properties of services is attracting more and more attention from users. To recommend high quality services to users, first we need to predict the quality of services. Now there are many research works on Web service QoS prediction, but most of these works focus on the optimization of modeling methods, which ignore the impact of auxiliary features. This paper emphatically analyzes auxiliary features' impact on QoS prediction such as service category and user location. To achieve this goal, in this paper designs and builds up a unified QoS prediction framework based on Factorization Machines, which can incorporate multiple auxiliary features easily and conveniently. Combined with service category and user location, this paper develops a QoS prediction method, which is proved to be advantageous via experiments on real-life data sets.

Abstract:By promoting of our government, more and more electronic business enterprise join the competition of online sales. With the sharp increase in sales, an ever increasing number of sales data is accumulated by the third party enterprise, and these sales data which is too scattered in original classification, it brings some difficulty in sales forecasting, in detail, it would lead to incomplete condition or severe deviation of predicted value. To improve this problem, a prediction model which is based on goods re-classification is constructed in this paper. This model used common sales features of products to extract the product cluster, then it used time series forecasting model to give the predicted value which is decorated by HMM in probability distribution aspect. Through experimental analysis, the final predicted values preferable fit the true values, and this achievement will provide the reference value to enterprise in establishing policies of distribution.

Abstract:VCP can't adjust the congestion window according to the congestion degree because of insufficient feedback information,and shows slow convergence speed with the burst traffic flows.This thesis presents a improved VCP congestion control algorithm named VCP-BE in high bandwidth delay product networks,which uses the end-to-end bandwidth estimation algorithm and two existing ECN bits to improve the accuracy of congestion information feedback, provides more precise congestion control information for the source congestion window adjustment.Simulations show that the improved VCP-BE can adapt to high bandwidth delay networks, has faster fair convergence speed than VCP and MLCP.

Abstract:Social network data is the basis of social network analysis that is why it's important to collect such data. To solve the problem of less collected data and low recall rate in current focused crawlers on social network, this paper proposes a method combining the based built-in search engine and general search engines to crawl topic messages, as well as applys the LDA model to extract the topic keywords from collected data iteratively and adds new topic keywords to the seed. Besides, an efficient expansion strategy based on users survival value is discussed. Our experiment shows that the methods proposed can improve the recall rate with a high precision.

Abstract:Recently, developing interactive perception applications using cloudlet's service always traps in hardship or duplication. To resolve this problem, Bolt service framework is designed and realized for creating interactive perception applications on cloudlet. Bolt is based on ZeroMQ, which is a kind of message queue, and could be divided into three parts: Bolt Client Lib, Bolt Service Lib and Bolt Broker. These make up a "Client-Broker-Service" architecture. Bolt Client Lib and Bolt Service Lib can respectively provide API for clients on mobile device side and cognitive engines on cloudlet side, reducing the difficulty and redundant works dues to the separate developing. The experiments show that Bolt service framework has only a 1ms system overhead and using just 2 socket ports meanwhile compared to applications such as Gabreil.

Abstract:Human detection is a basic functionality for home service robots. For complex family environments where lying person is partially occluded or in cluster, this paper proposes a lying person detection approach integrates 3D point cloud segmentation and local feature matching. Our approach segments the point cloud of each object into several pieces, matches local features of each object piece, and classifies them to detect lying person. Experiments show that our approach can achieve high detection accuracy with average recognition time less than 0.3s. Our approach meets the human detection requirements for service robots and is demonstrated to be practical and reliable, even when parts of human body is occluded.

Abstract:According to the problem that traditional computer intelligent composing objective evaluation is not accurate, the difficulty is too big, this paper on intelligent composition discusses and gives a genetic algorithm intelligent composing model, and puts forward a simplified genetic algorithm based intelligent composing model. For the model from two aspects of algorithm design and realization of the algorithm is discussed, and the program is given out. The experimental results show that the model to improve the local without affecting other parts, has high scalability, the algorithm's time and space complexity is better, proves that this algorithm is feasible and effective.

Abstract:Aiming at the problem of the global frequent extreme weather conditions, it is more important to discover the appearance of the disaster weather. With the rapid development and wide application of data mining technology. In this paper, it uses improved FP-growth algorithm to mining the possible correlation between various meteorological factors, so as to find the weather characteristics and forecast the near future weather condition. The simulation results show that the improved algorithm has a significant improvement in the accuracy of weather forecast.

Abstract:In this research, an approach of three-phase 3D corresponding algorithm based on hybrid feature of Harris and line feature points matching is proposed, in which relative matching, relaxation matching and LMedS matching are implemented respectively. At the mean time there Human-machine interaction processes are added, namely limitation of matching area, adding feature points by hand as well as line matching. Through coordinated transformation between views, 3D data of scene form different views integrated into a uniform reference coordinate frame, which can solve the false matching problem caused by inconsistent or shadowed areas. Experiment demonstrates the efficiency and robustness of this corresponding method, in which the 3D model of the targeted object can be displayed on all views.

Abstract:In order to improve the accuracy of emotion recognition, this paper proposes a novel speech emotion recognition algorithm, and takes speech signal as the research subject. The idea of locality preserving projection (LPP) is integrated into the objective function of PCA. It not only realizes the maximum of the total variance, but also keeps the local neighbor structure. That is beneficial to comprehensive extraction of global and local features, and overcomes the defects that the traditional PCA can only keep the structure in global and can not maintain the structure in local. Experiment results verify the feasibility and effectiveness of the proposed method, and accomplish recognition for five kinds of human emotion (joy, anger, sadness, fear, neutral). Research results provide new methods into emotion recognition, promote the further development of human-computer interaction system.

Abstract:This paper proposes a location algorithm based on dual-GPS vibrator. Firstly this algorithm gets accurate GPS positioning coordinates data, and the resulting coordinate data feedback is sent to the microcontroller. Then through the integration process of the algorithm in the microcontroller, the conclusion gets the position coordinates vibrator. The simple calculation is simple. Experimental results show that the algorithm is efficient operation, accuracy and timeliness to meet the dual requirements.

Abstract:In the application of text-independent speaker recognition, this paper puts forward an improved feature extraction of MFCC parameters to supply the inefficient traditional MFCC. Endpoint detection is added in traditional algorithm to remove silence parts. Gaussian shaped filters are used to replace triangular filter banks to improve the accuracy of speaker identification. Gauss mixed model is for speaker recognition. Experiments show that Gaussian shaped filters gain 9.63% performance improvement while proposed MFCC can significantly improve recognition rate by 11.07%. The result indicates that the new method is an effective feature extraction algorithm.

Abstract:Particle swarm optimization (PSO) was applied in many fields because of its simplicity and fast convergence, but it is easily prone to be premature and get struck in local optima. Combination with the characteristics of Lévy flight, this paper proposes a new variation of PSO with Lévy mutation (LévyPSO), and then analyzed it's convergence and pointed out that the algorithm convergence in probability for the global optima. The experiments is conducted on 8 classic benchmark functions, the results show that the Lévy mutation can use the current knowledge of particles and increase the diversity of population. Thus, the proposed algorithm has better performance because of it can more effectively balance the global search and local search. The parameters settings of the proposed algorithm are discussed in the final.

Abstract:Existing studies on parallel spatial join query mostly focus on algorithm process. Few of them pay enough attentions on implementation and application research. After analyzing existing algorithm process, parallel spatial join algorithms are divided into four phases which are parallel candidate tasks generating, assignment, executing and results collection. Each of them is designed and implemented on a parallel RDBMS cluster which is built on a open-source project named ‘PL/Proxy’. In addition, to implement parallel computation, mixed computation migration method is proposed. Spatial extension function is implemented to support the spatial data sets operation on the cluster. Result of experiments using real data sets shows that, the implemented algorithm gains near linear speedup when data declustering scheme is optimal. Moreover, speedup is also gained while significant data skew caused by data declustering exists. The data declustering scheme is replaceable for improving the algorithm performance. A practicable solution for parallel spatial data sets management is provided in this paper.

Abstract:In order to complete the basic operation in abstract data type of Child-Sibling Tree and then better serves for teaching and daily application, the paper solves a important and complex operation of the lack of depth research in Child-Sibling Tree——searching parents node. By the means of mathematical techniques analysis that the time and space complexity of the algorithm are both O(n). It is known by excavating its potential that the algorithm has good application prospects in the place-name searching system.

Abstract:As GUI applications are dominant in desktop environment, online migration GUI applications can improve user experience. However, the X Window System protocol which is in widespread use today, is very complex and not conducive to the live migration of GUI applications. In addition, if the runtime environments of the two machines are not consistent, it will lead to the migration failure. Therefore the live migration of GUI applications has not been realized so far. In recent years, Wayland emerges as a new graphical interface protocol, in which rendering is left to GUI clients. This brings great convenience for the migration. And today's popular Docker container technology is able to package the Wayland GUI application and its runtime library, which ensures the consistency of the runtime environments. When migration happens, the whole container will be migrated to the target machine so that the GUI application can continue its running status. In this paper, the corresponding processing Wayland protocol module is developed. And on the basis of the CRIU tool, it realizes the reconstruction of Wayland state. The experiments show that our scheme is feasible, and can be extended to most GUI applications with minor modification.

Abstract:Multi-people detection and tracking is a basic function for service robots when they serve people and interact with people. However, there exists a big challenge because of complex environment and occlusion of multiple people. To detect people, a new method based nearest neighbor algorithm combiningleg detection of laser and body detection of Kinect is proposed and it improves the accuracy and completeness of detection. For multi-people tracking, an improved particle filter is proposed to predict the people's position and velocity, which can overcome the problem of heavy computational amount and particle degradation. In the experimental stage, a turtlebot robot with laser and Kinect is used to test the method in a real indoor environment. Results show the method can detect and track people in real time, and the method is robust and accurate.

Abstract:The paper designs and implements a wireless temperature and humidity acquisition system which is based on the Z-Stack protocol stack and ZigBee technology, with CC2530 rf transceiver chip and DHT22 digital temperature and humidity sensor as the core, and in the IAR environment with the method of upper machine software with GUI to display temperature and humidity changes in terminal intuitively. This paper mainly expounds the system structure design, temperature and humidity data acquisition process and graphical interface monitoring implementation. The experimental result shows that the system of temperature and humidity data acquisition is not only real-time and effective, good scalability, and has high reliability and excellent stability.

Abstract:A vertex-labeled semigraph is a semigraph whose n-vertices are labeled by distinct symbols. Various results on enumeration of vertex-labeled semigraphs containing non-adjacent edges and the number of vertex-labeled semigraphs with two adjacent s-edges are obtained. Also the number of vertex-labeled semigraphs from 1 to 8 vertices is calculated.

Abstract:For the demands of real-time processing and application environment, a new animal vision-based vehicle identification algorithm is put forward, and packaged as component used in heterogeneous processing platform. By determining relevance of neighboring pixels, this algorithm eliminates false errors and raises the accuracy of vehicle identification. Meanwhile speediness algorithm adapting contributes to rapid application. Experimental results show that the heterogeneous processing platform reduces development period, improves algorithm utilization, fast updates algorithm and processing.

Abstract:In view of the traditional IT operational service desk event full-text retrieval accuracy is not high and the low utilization rate of a large number of historical events list, this paper puts forward a disposal reference model based on event text vectorization method. Through the establishment of production operations of key library, the event text is represented into a feature vector, and selects the appropriate algorithm for different event text feature vector similarity calculation, eventually finds the historical events or the knowledge base by calculation with the existing high similarity of events, as a reference disposal for operations staff. Applying this method to the enterprise service desk incident disposal process, can help operations staff quickly and accurately to find the similar events in the history of or related to knowledge, to formin matter disposal of reference, to speed up the treatment efficiency, but also further improves the intelligent and automation level of the operational tools.

Abstract:The mobile Internet and health big data is causing big health healthcare management industry disruptive change, the formation of a firm focuses on building levels based on the "Internet+IoT+medical service" technology-based business model to cloud O2O health management system platform. "Zhong Ke Hui Kang" health cloud platform mainly provides health management platform for health institutions and users. This paper discusses in aspects of the platform architecture design and system optimization starting from load balancing, distributed caching, database optimization, socket forwarding server design a good cloud platform to support business development. Experimental results show that the system architecture to meet the one million level of data forwarding and user access, application practice shows the feasibility of the scheme.

Abstract:Aiming at the image of ship target is small and far from the harbor surveillance, the interference of sea noise and other characteristics, a background suppression algorithm based on morphological filtering is proposed. According to the geometric features of the ship, the project first uses the weighted morphological filtering of multi group structure elements to separate the ship target and the sea background, then the adaptive and fast median filter based on neighborhood is used to filter the impulse noise, finally, due to the sea clutter in the frames is discontinuous and the area is lesser, thus the connected domain computing to eliminate the ship's model about morphological feature is also used. The experimental results show that the proposed detection algorithm can effectively suppress the background noise, the sea clutter, and quickly detect the ship target in the actual port video.

Abstract:In view of the loss, information fraud or other issues for old man and children under the background of information era, a security monitor system based on Android platform is designed by using Java language through constructing the Eclipse ADT SDK Android development environment. The system includes monitoring, SMS monitoring, positioning and monitoring and unlock monitoring module, etc. The running results show that the system is concise, stable, reliable.

Abstract:In order to accurately measure the parameters of the signal, a wideband AC and DC signal detection system is proposed, the STC12C5A32S2 microcontroller is used as control chip of the system. First, the signal is collected by the AC and DC and signal measurement circuit is processed and analyzed. Then, the signal will be processed by dividing and automatic gain amplification circuit, the frequency and phase of the signal is measured in the frequency and phase detection circuit. Finally, the amplitude, phase and frequency information of the signal is shown on the LCD. In the experiment, the signal with 0-20KHz frequency at different amplitudes is measured, the experimental results shows that the measurement error can be ignored in the low-frequency signal measurement, and in the high-frequency signal measurement error is less than 1%.

Abstract:Economic active analysis is an important measure to strengthen operation management and improve economic effectiveness for enterprise. This paper is pointed at some questions, which is professional, difficult to use and concentrated to analysis targets. The system of economic active analysis is designed, which is multifunctional, like multidimensional analysis, data cache, data compression, multi-thread and so on. Besides some traditional function of data acquisition, data procession and statistical analysis, it is customization and visualization in the system. It is proved availability of this research, results with this platform coming into service of operation and controlling of enterprise and work efficiency and quality is enhanced.

Abstract:This essay focuses on introducing the study of centralized storage management and control system based on domestic secure operating system, by employing core technologies of sandbox, multi-factors intensifying ID authentication, data storage with centralized encrytion, load balancing, etc. It can realize the functions of secure encryption of users' files, centralized storage of data, Terminal Security Management, peripheral Traffic control management and log comprehensive audit function, through a flexible, secure and efficient centralized storage and management strategy control aiming at special targeted users will be achieved.

Abstract:In the traditional K-means algorithm, the clustering results greatly depend on the random selection of initial cluster centers and the artificial K values. In order to improve the clustering accuracy, this paper proposes to select the initial cluster centers by using the minimum distance and the average clustering degree. The number of clusters is obtained by the hierarchical clustering CURE algorithm as K value, so that the clustering accuracy can be improved. Finally, the improved K-means algorithm is applied to the micro-blog topic discovery. Through the analysis of the experimental results, it is proved that the algorithm can improve the accuracy of clustering results.