Abstract:The research status of access control models for online social networks was analyzed and summarized. The key problems and challenges were also pointed out, and some development trends and future research directions was proposed. Along with the explosive development of online social networks, problems such as data sharing and privacy preservation are gradually grabbing the attention of the public. As information security mechanism, traditional access control models are incompetent to meet the security requirements under the complex circumstances of online social networks. Recent years, research on access control models for online social networks is becoming a hot topic and many new access control models have been proposed based on different perspectives.

Abstract:With the advent of the information age, some criminals always tend to query information from the Internet before they engaged in criminal activity. So the browser they used has become the key to the forensics of judicial authorities. Whether we can extract the effective evidence of crime depends on the forensics method of browser. This article introduces the forensics technology of Firefox and IE browser which are the current mainstream browsers, outlined the browser temporary file structure, such as the IE cache file and the SQLite database log files of the Firefox, proposed information recovery method. It can collect evidence and analyze the user's behavior by extract the information of the deleted log files or cache files.

Abstract:It has been more than 40 years since the "software engineering" concept mentioned at NATO conference in 1969. Recently, software engineering theory has made great progress and gained huge success. For forty years, the theory of software engineering does not change much, continuing the natural logic of four stages which are requirement, design, coding and testing. The projects are finished step by step and in each stage, the demand and the development cooperated closely. In reality, software developments still face many problems, such as the uncertainty of demand and cost's out of control which eventually lead to the failure of the development. Based on the analysis of software development method and the development cost of the software engineering, demand and acceptance stage problems are analyzed. A appropriate technique to realize software visualization and standardization is proposed. The improved demand analysis method can form analysis more specific and control the development costs easier, improving the success rate of software development.

Abstract:Aiming at the problem of the gap between theory and practice that exists in our stock index futures market which causes the disequilibrium between the development demand and actual condition of the market. The present paper proposes a strategy to solve it, namely to construct a system of stock index futures arbitrage and management. The system's design is based on practical survey, and the realized system named SIFAM-System is based on C#. The system implements two calendar spread arbitrage strategies based on models. One is calendar spread arbitrage based on basis trade and the other is calendar spread arbitrage based on arbitrage-free interval. It also implements some management functions that are related to the core function of arbitrage. The system implements model calculation, market monitoring, arbitrage opportunities judgment, and open or close positions by computer-assisted, which achieves the goal of decision-making for investors. It also provides a solution strategy from theory to practice to the development problem that exists in the stock index futures market.

Abstract:An image registration method is proposed. A low altitude remote sensing image mosaicking system is development by using OpenCV library. We use the scale invariant feature transform (SIFT) points as the feature vector for image mosaicking. Local extreme points in scale space of the image are calculated. The SIFT feature points are extracted. The feature points' rough matching is performed based on the vectors Euclidean distance. We use random sample consensus (RANSAC) algorithm to optimize feature points matching. The image transform matrix is accurately estimated. Image fusion of overlap region is realized. The experimental results show that this method can solve the image registration problems which often occur in remote sensing images such as translation, scaling and rotation transform. Good mosaic results are achieved using the proposed method.

Abstract:The traditional electricity data processing methods of a corporation's financial management information system have difficulty as the amount of electricity data is growing rapidly. Hadoop is a large-scale distributed computing framework that has the advantages of high efficient, reliable and scalable. Hadoop is widely used in the massive data processing field. Based on the analysis and research of electricity process and Hadoop, this paper proposed a novel electricity process model which includes a distributed computing platform based on Hadoop and Hive. The experimental results show the platform can effectively solve the performance bottleneck that the electricity processing service is facing and improve the speed and efficiency of electricity process. In addition, the new model can provide high-performance electricity detailed query functions.

Abstract:E-government as the organic combination of electronic information technology and management has become one of the most important areas of modern information technology. The project is based on the needs of the Guangzhou branch of Chinese Academy of Sciences and Guangdong province academy of management information. This project builts the office platform based on the sufficient research firstly. On this basis, it builds the Guangdong Provincial Academy of Sciences Document Management System, to achieve docking with the ARP system. After business system setting up, considering the interactions with the society, it constructs the Guangdong academy of sciences website group of system as the window of foreign contact, which can enhance the social influence of each unit further.

Abstract:Through detailed analysis on the management of university research, combined with the characteristics of scientific research work in higher vocational college, this paper designs and develops a scientific research management information system based on the mixed model of C/S and B/S. On the actual need of scientific research business processes and the staff in higher vocational college, this paper designs the corresponding function modules and operating processes. The application of regular expressions technology is used to extract the information of staff's paper from CNKI directly and it saves the data entry time. The system has been put into operation for two years. The result of use shows that the system makes the scientific research management more standardized and efficiency.

Abstract:According to the requirement of flight monitoring and control of UAV, this paper put forward a design of UAV remote telemetry ground control station software. The UAV remote telemetry ground control station software, which consists of five parts including system debugging, route planning, flight monitoring, video capturing and data replaying. Based on Google Earth COM API secondary development and Visual C++6.0 development environment, it uses modular design concept, serial communication, virtual aviation instrument, and vedio capturing technology to develop.

Abstract:The paper introduces the hardware structure and working process of the embedded microprocessor based on S3C2440 streaming media system. The server will be streaming media data transmitted by RTP/RTCP protocol. The client will decompress and playback of received data real-time. The receive buffer is allocated into the receive buffer, playout buffer and DMA buffer. The sizes of the three buffers are arranged according to the ratio of 1:1:2. To constrain the buffer zone by the average rate, delay jitter and decoding rate and other parameters of thecapacity. In the receiving buffer, two critical points are set. Through the detection of the two critical points, we can assist the data sending rate adjustment of the sending end. Not only can avoid network congestion, but also can improve the quality of streaming media transmission.

Abstract:Power Software has gradually become market-oriented and product-oriented. With the application requirements and market demand on planning management software of power industry, the authors propose a supporting platform for planning management business application, mainly introduce its general design and focus on the thinking of business component library, visual development toolset for custom business, supervision optimizer, and business reference model library. This platform will provide full support for the planning management application, throughout development, running and supervision phases.

Abstract:This paper designs an Android communication system on the basis of studying the related communication research, and the system utilizes the wifi network and point-to-point architecture and messages between client sides are delivered by means of the Socket. In addition to the instant text information transmission, functions of on-line and off-line as well as file transfer are added. The adoption of the multi-threading technology enhances the program's utilization of the system resources. Better operating results are obtained in the test on the Android platform.

Abstract:The object of our work is to fulfil the philosophy that patients are the core of the service and construct a practical, feasible, scientific, objective and fair valuation system so as to improve the service quality of hospital. The methods we use in this paper are based on the military healthy No.1 platform and HIS database and systematically supported by JAVA and Eclipse technology. The system has been being operated for 30 months, during this interval. It has a great performance on the supervisor function which made the patients comprehensive stasfication degree increase 4.35%. This system facilitate the service awareness of medical service pesonel, the improvement of public and social images and the alleviation of gradually increasing contradicts between medical service and patients, which builds a harmonious relationship between hospital and patierntes and has a higher value that needs to be promoted.

Abstract:One problem the present ontology faces is low construction efficiency and low reusability. For this issue, this paper proposed a new modular method for ontology based on transforming the forest into trees. In this method, the domain was decomposed into atomic subfields, each of which was modeled individually and later assembled into a modular ontology according to the inheritance relationships among the concepts and the principles for transforming a forest into trees. We examined this modular method by constructing the ontology on the undergraduate studies level, and proved that this modular method can effectively improve the reusability of the ontology, and thus was an effective approach for constructing ontology in large scale domains.

Abstract:Research on music classification has been processing years, but the performance of each method is not very well. This paper proposes a new method based on entropy and support vector machine for music classification. It uses bank of filters to decompose the music clip into different channels. Then the filters turns it into spectrum through discrete Fourier transform and compute the information entropy and uses support vector machine training and testing on a dataset containing four categories of music. The experiment compares three different kinds of filters, among which the Bark filter achieves an accuracy of 80%. The result shows that the proposed feature vector is better than MFCC.

Abstract:The classification of mice behavior is very important in the study fields of neuroscience, biological science, drug development and so on. In behavioral analysis,according to the short limbs of mice, it is difficult to extract relevant information. Mouse behavior is classified using characteristics of mouse contour. Firstly, mouse contour is extracted from each frame behavior video. Then, the distance of eight directions are calculated which are from contour center to edge and calculate two main components of contour. Using these values to form ten dimensional vectors as feature vector. Finally, calculate the log-covariance distance and classify. Experimental results show that the correct rate of classification is 87.6%.

Abstract:In this paper, a compressed sensing signal reconstruction algorithm that based on Bayesian compression perception theory is proposed. It can be applied to signal compression and transmission as well as reconstruction. The new algorithm inverted the compressed sensing problem into a linear regression problem. Firstly, then deduced an iterative relationship of the resulting vectors gradually, at last got the exact reconstruction of the original signal by iteration. The simulation experiment exploted that the Bayesian compressive sensing algorithm have a good reconstruction effect used in one-dimensional and two-dimensional signal processing and the reconstruction.

Abstract:Previous studies proved that, adding part of speech tag information to the input layer of neural language model, can improve the performance significantly. But part of speech tag need hand-annotated data to train the tag model, which consumes a lot and the extra tagger also makes the model more complicated. To solve the problem, this article propose adding the results of brown clustering, instead of part of speech tag information to the input layer of the recurrent network language model. In the Penn Treebank corpus, the relative improvement over the original recurrent neural network language model reaches 8%~9%.

Abstract:With the explosively increase of social networking, bioinformatics network and other relational datas. It is urgent to improve the processing capability on large scale graphs with billions of vertices. The traditional graph algorithms can no longer meet the rapidly growing demand for the calculate dependence of the memory. To find the Weakly Connected Components of a graph, this paper presented a fast, scalable and iterable coloring algorithm CR and also established the MapReduce model. At last, we give out a contrast experiment between the open-source data mining toolbox XRIME and CR on four sets of communication data, which is provided by the Social Network Analysis Laboratory in Stanford University.

Abstract:With the continuous expansion and consolidation, due to the limited teaching resources, reasonable arrangement of teaching plan has become an increasingly serious problem. Row of class and classroom teaching plan reasonable use has become an important task for the management of. Based on the genetic algorithm and the university course scheduling needs study, from the classroom management, conflict detection and time planning three aspects carries on the thorough analysis, and the corresponding algorithm are described in detail and design. The initial population of genetic algorithm selection, crossover, mutation processes evolve, finally achieved the optimal schedule. Finally, Visual C++ implementation of the course scheduling system, proved the feasibility of the algorithm.

Abstract:In order to accelerate the query speed of embedded database SQLite, we propose an improved index mechanism based on the original B+ tree, which can actually improve the query speed with little influence on the embedded memory resources.

Abstract:Matinez et al has proposed a secure RFID protocol which only relies on the use of Elliptic Curve Cryptography and a zero knowledge based authentication scheme. In this paper, we present that the proposed protocol can't resist desynchronization attack. The attacker only block the last acknowledge message from Back End Server. Then the share key of Tag and Back End Server is different. For this, we propose our revised scheme, and prove that revised scheme can resist desynchronization attack.

Abstract:A method for volume measurement of small coal heap based on combination of SURF feature and binocular vision is presented in this article. Firstly, the principle of binocular vision and stereo matching based on SURF algorithm is briefly introduced. Then, in order to achieve the non-contact volume measurement of coal heap, the 3D reconstruction and volume measurement method of coal heap is given, and the main factors influencing the calculation accuracy and related solution are discussed. Finally, the feasibility and application value of this method used for volume measurement of coal has been proved according to the experimental results.

Abstract:In order to solve premature phenomenon and slow convergence problems in particle swarm algorithm, an improved mean particle swarm algorithm is provided. The algorithm apply to the nonlinear weight. At the same time in each iteration step, the history optimal particle and the global optimal population were averaged and multiplied a nonlinear weight so that it improve the global search capacity and convergence speed. Through four standard function test, The results show that the effectiveness of the proposed algorithm.

Abstract:Three common numerical optimization algorithms are first studied, including conjugate gradient algorithm, quasi-newton algorithm and LM algorithm. The three kinds of algorithms are used to improve BP neural network respectively and the corresponding classification models based on BP neural network are established. Then the models are used in pattern classification of two-dimensional vectors, and their generalization abilities are also tested. The classification results of different classification models based on BP network are compared with each other. Simulation results show that for small or medium scale networks, BP neural network improved by LM algorithm has the most precise classification result, the fastest convergence speed and the best classification ability. The one improved by conjugate gradient algorithm has the biggest error, slowest convergence speed and worst classification ability. While the classification precision, convergence speed and classification ability of quasi-newton algorithm lie between the above two algorithms.

Abstract:In graph-based recommendation, the calculation and storage of resource allocation matrix take up a lot of overhead, in order to improve efficiency of algorithm. Path Integration-Based Multiple Layers Recommendation(PIML) was proposed. In the algorithm, path integration-based shunt strategy was used to dynamically allocate resources, and timestamp and ratings were added to the graph. On the other hand, demographic information and item content information were added to the multiple layers structure, considering a variety of factors, it gave more comprehensive recommendation. Experimental results show that the algorithm improves the accuracy without increasing time cost; and makes recommendation more comprehensive and can give real-time recommendation.

Abstract:An adaptive weighted residuals multi-element collaborative representation classification is proposed in this paper. To address the weak discriminative power of SRC (sparse representation classifier) method, we propose using multiple elements to represent each element and construct multiple collaborative representation for classification. To reflect the different element with different importance and discriminative power, we present adaptive weighted residuals method to linearly combine different element representations for classification. Experimental results demonstrate the effectiveness and better classification accuracy of our proposed method.

Abstract:Clickstream data are the key to analysis the psychological tendency of Internet users. Internet users clustering can be realized by analyzing the clickstream data.This paper presents a similarity calculation method based on vector. Clickstream data can be converted to vector data.Through the calculation of vector clustering, results could be obtained. Algorithm overcomes the drawbacks of the traditional clustering algorithm. It can meet researchers study of web clickstream data about the requirements of personalized clustering more.

Abstract:Recommend system is an effective method for people to get useful knowledge from mass information. It has attracted widespread attention in both academia and industry. Collaborative filtering (CF) is the most popular algorithm in the research of Recommend system. However most of current CF algorithms are static models, which do not take into account of user interest changing. The paper proposed a hybrid recommend method, which capture user's long-term interests with Gaussian probabilistic latent semantic (PLSA) algorithm, at the same time, capture user's short-time interests with rating window. The experimental results obtained on Movielens dataset and Netflix dataset clearly show that the new algorithm is more accurate than traditional user-based algorithm and PLSA algorithm.

Abstract:In this paper, the HDFS distributed file system is conducted in-depth research. In HDFS the way of streaming to read and write large files is very efficient, but the efficiency on reading and writing of the mass of small files is relatively low. According to this problem this paper presents a small files based on relational database consolidation strategy. Firstly creating a user's file for each user, then uploading file's metadata information to relational database and the file is written to the user's file when user uploads small files. Finally user via streaming mode to read small files according to the metadata information. When user reads file which size is smaller than the file block, datanode takes load balancing strategy, the datanode of storing data transfers data directly so as to reduce the pressure of the main server and improve the efficiency of file's transfer. The experimental results show that this scheme solves the shortcoming of HDFS reading and writing small files, improves the HDFS file system of reading and writing performance on massive small files. This scheme can apply to massive small files on cloud storage system, and reduce memory consumption of NameNode to improve the efficiency of file's reading and writing.

Abstract:A rapid pedestrian detection and counting algorithm based on HOG is proposed for getting the pedestrian flow passing the confined space. The time efficiency is increased remarkable by restricting window shrink range and setting ROI. Counting method based on single line is presented for getting tow directions people number. Experiments in three different passageway show that the proposed method don't depend on moving information, besides it has the ability of fast and stable in confined space pedestrian counting.

Abstract:Faced with the broad prospect in research & application of cloud computing, the paper has studied and analyzed architecture and core principle of Hadoop platform, and its existing typical job scheduling algorithm. Furthermore, to resolve the pre-configuration issue of the algorithm, improved algorithm is proposed based on Naive-Bayes classification. According to the simulation test result, the improved algorithm is proven to be with satisfied performance, easy to learn. It may reduce administrator's workload, improve management efficiency, and reduce human error.

Abstract:Bacteria foraging optimization algorithm is a kind of group evolution algorithm inspired from E. coli foraging phenomenon, and it has good global optimization, strong robustness, simple arithmetic, and so on. But it is also easy to premature and slow convergence speed and other shortcomings. According to its shortcomings, it is proposed that an improved bacteria foraging optimization algorithm. The improved algorithm accelerates the convergence speed and avoids the premature in a certain extent. It is applied to on-line self-tuning of PID parameters that the original algorithm and improved algorithm. And through the matlab simulation, it is proved that the superiority of the improved algorithm.

Abstract:As the Web continues to grow, it has become increasingly obvious that information overload, low-efficiency using traditional search engines. In this paper, after researching the index sort algorithm applied in the Lucene.Net and considering the requirement from the end-users, we present an approach to address this issue. The experimental results showed that the proposed approach is practical.

Abstract:The resource allocation algorithm in multi-user multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems has been studied. The user's fairness is ensured in this algorithm, and based on minimum transmitting power to allocate the sub-carriers and the bits in system. The sub-carriers' first allocation is done according to the user's channel gain under the order from worst to best. And then, by comparing their powers to find the most suitable sub-carriers ultimately. Finally, the greedy water-filling algorithm is used to allocate bits for the sub-carrier. Simulation results have shown that the transmitting power can be decreased and the system performance has been improved.

Abstract:Now online reviews have become an important resource for mining users'opinion and refining products. As a foundation of further analysis, features extraction influences the precision of the opinion mining results. This paper proposes a PMI-Bootstrapping algorithm which realizes extracting product features from Chinese online reviews by combining three language rules. First, utilize the language rules to get a candidate feature set. Then, calculate the weighted average PMI for each candidate feature with the seeds in the initial seed set. Add the candidate feature which satisfies the threshold to the seed set. Iterate until the seed set is convergent. Output the seed set as the extraction result. Experimental results show that the algorithm achieved very good precision and recall rate.

Abstract:Computer modeling simulation has been developed as an important means of product development and system testing. Simulation credibility is critical to simulation results, but the procedure of credibility evaluation is usually very cumbersome. Therefore, there is a need for a proper method of simulation credibility evaluation, which can finish the work of system establishment, quantitative evaluation, qualitative evaluation and expert advice collection. This paper introduces the principle and application of DS evidence theory, and improves it for the implementation in evaluation system. With the auxiliary of convex evidence, a methodology of simulation credibility evaluation for complex product based on DS evidence theory is established. Finally, an example is showed to illustrate the concrete application of this method in the evaluation of simulation credibility.

Abstract:This paper presents on breast cancer knowledge mining and network to its effective to explore. Before the application of various data mining method in probability, find out the progression of the disease by using the network. The results are helpful to reasonable treatment to the doctor for the patient. For the high dimension data set and overcome the problems associated with the data, this paper uses principal component to reduce the data dimension and find out the suitable network analysis. Application of BP neural network structure is assessed, performance on the breast cancer data in a hospital in Beijing, the BP neural network is analyzed. The results show that principal component analysis to eliminate the correlation between the input of the network, reducing the input of network, improve the performance of the network as a whole. The good results have been achieved.

Abstract:Trust network is an effective means of resisting malicious fraud and reducing the risk of interactions between users. Most of existing researches focus on trust propagation and aggregation strategies, while pay little attention to the importance of agents. This paper presents a sequential pattern mining algorithm which called T-Seq, in which trust propagation process is regarded as trust sequences. It is effective in important nodes discovery through sequences mining. Experiments showed the effectiveness of T-Seq in sequential pattern mining and important nodes discovery.

Abstract:The singleton pattern is a design pattern used for Web development,the class instantiate the only object inside the class applied the singleton pattern, and provide the object to the whole application through the static methods of the class, play a shared global role. Application of this kind of mode can reduce the application's resource consumption and improve operational efficiency. But it is difficult when competency system task or an instance exists only. Multiple instances model is as an extension of singleton pattern. It can avoid disorderly generating the class body object through generating a finite object instance.It is a very good solution to finish the task unfinished by the only object also. This model can be said to be continuation and expansion of the singleton pattern.

Abstract:The crystal oscillator is a high stability and high precision resonant devices, used widely in various electronic measurement, radio communications, aviation, aerospace and other fields. In this paper, the crystal structure of the peripheral circuit parameters and matching perspective to discuss how to improve the accuracy of the crystal method. Our work gives out a peripheral circuit which can improve the accuracy of the crystal range of parameter through Multisim circuit simulation software. The experiments use the GSP-810 spectrum analyzer for the actual testing and verify the actual crystal oscillator circuit spectrum and the results more visually.

Abstract:In order to analysis the sequence data generated by online experimental system, the first-order Markov chain is introduced. It artificially classifies the experimental data into the learning initiative and fraud, and constructs two Markov chain models. It determines by the larger possibility from which model the test data comes. At the end, it discusses the steady state distribution. Experimental results show that the model based on Markov chain has higher classification accuracy.

Abstract:Aming at low precision and weak robust of the temperature control in the quenching process of round link chain, this paper puts forward a new quenching system for round link chain which is based on expert PID controller. The paper describes the principle and implementation method of expert PID controller, applies the algorithms into the quenching system for round link chain, and compares the effect of the common PID and expert PID controller. The experiment results show that the quenching system for round link chain based on expert pid controller system can achieve good control of round link chain quencher temperature and hold the advantages of fast response and strong robustness.

Abstract:In order to improve the data processing capacity of application software based on embedded operating system μC/OS-Ⅲ. This paper focused on the porting method of mutex, memory allocation and VFS three subsystems by analyzing SQLite's operating system interface, provided the technology of porting SQLite to μC/OS-Ⅲ, and validated the feasibility of the database porting combined with instance.

Abstract:A design of portable electrical instrument verification system interface based on Qt was presented, the design of modules such as window widgets, database, file management and mouse and keyboard responding events were achieved. Besides, the program transplant was completed in the embedded Linux system. According to the verification, the characteristics of the system interface were configuration flexible and friendly. Users can complete the automatic test, data storage, exporting test reports by setting the parameters and testing plans. The design in this work can meet the requirements.

Abstract:Facing malicious attacks from internet, equipment damage and other emergency situations, backup of data and configuration has become an important way to restore system quickly. By several tests proved that it can backup the important information which is in server, switching and routing equipment automatically and manually with Windows's scheduled task, script and the appropriate software. When a disaster occurs, it recover rapidly with minimal consideration.