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Traditional centralized clustering clusters a data set stored in a single site, but it cannot satisfy the clustering requirements when data is distributed, while distributed clustering can satisfy this need, for it extracts classification mode from distributed data. This paper surveyed and analyzed distributed clustering algorithms. Firstly, it classified existing distributed clustering algorithms. Then, it compared basic ideas, advantages and disadvantages of each class of these algorithms. Finally, it used two data sets--Iris and Wine to compare several distributed clustering algorithms with two metrics: clustering accuracy and clustering time. [ABSTRACT FROM AUTHOR]

DaaS is a kind of cloud service which can provide the database services for others based on cloud infrastructure. It can effectively solve the difficulty of storage and management for massive data of individuals and enterprises. However, privacy leaks greatly hinder the development of DaaS. How to enhance the privacy protection of the existing DaaS becomes an urgent problem needed to be solved. Adopting the literature analysis method, this paper firstly summarized service architecture of DaaS and its privacy leaks mode. Then comprehensively analyzed the present researches on data confidentiality, query privacy preserving and query result validation, privacy preserving during data integrity validation of DaaS. From the analysis, it can be inferred that existing privacy preserving methods exist varying degrees of impairment in the aspects of efficiency of data update and query of DaaS and its practical applications. How to design more efficient algorithms for data confidential and the data queries with privacy preserving and query results validation are still the future research focus. Finally, it gave the he future research directions of in the privacy preserving in DaaS. [ABSTRACT FROM AUTHOR]

Aimed to the locomotion imitation problem of following human being on humand robot, this paper compared the method based on locomotion analytic equation to that one based on similarity human locomotion for designing the motion tracks of humanoid robot, which illustrated the basic structure of similarity locomotion system, the image capture and dealing, similarity feature dealing, locomotion constraint and optimization. It also described the research developments, including locomotion capturing and dealing, calculation of joints, locomotion simplified model and retargeting, key pose dealing and evaluation of similarity degree, space pose calculation of joint, dynamics march. Finally it showed the forecast and drew the conclusion. [ABSTRACT FROM AUTHOR]

This paper presented and discussed all the typical approaches based on MRF. First it provided a general framework of MRF in image segmentation and new progress for MRF modeling in recent years, and then emphatically presented the major image segmentation algorithms based on MRF, including graph cut algorithm, normalized cut algorithm, belief propagation algorithm, etc. Finally, it pointed out the future work for these segmentation algorithms. [ABSTRACT FROM AUTHOR]

This paper introduced studies of domestic and foreign researchers in Landweber iterative method for inverse problems. It overviewed the fundamental theory and conclusion of Landweber iterative method for inverse problems and introduced the application in some areas, especially in image restoration. It put forward briefly some research directions of Landweber iterate method in the future. [ABSTRACT FROM AUTHOR]

Aimed at the serious problem of phenomenon that there are so many out-of-vocabulary words and translation disorder in Uyghur-Chinese machine translation, and combined the features of Uyghur and the maximum entropy classification algorithm, this paper presented a max entropy reordering model in Uyghur-Chinese machine translation based on tackiness fuzzy rules. The model was based on max entropy classification algorithm, and created the constraints of tackiness fuzzy rules for Uyghur in the word level, then extracted better effective reordering rules from training corpus to guide the translation decoding procedure. The experiments show that compared with the current reordering methods, such as MSD (mono, swap, discontinuous) and so on, this reordering method is better retained the tackiness feature of Uyghur, and the quality of the translation is also improved. [ABSTRACT FROM AUTHOR]

Traditional recommendation algorithms overemphasize recommendation accuracy and homogenization phenomenon of recommendation lists is prominent. In view of this problem, this paper proposed a new recommendation selection algorithm called DivEnhance. First, it gave definition of recommender lists' diversity and utility, and then constructed a constrained integer programming model to solve the problem, through a parameter adjustment, it could realize the flexible control of diversity and accuracy. Experiment results demonstrate that the proposed algorithm can enhance the diversity of recommendation lists at the cost of a certain accuracy reduction. Specially, it outperformed other recommendation algorithms in recommending some novel items. [ABSTRACT FROM AUTHOR]

Based on the analysis of the factors that affect retweet behavior, this paper proposed a predict SVM algorithm with five features: user influence, user activity, interest similarity, the importance of micro-blog content and users closeness. Furthermore, it proposed the predict algorithm of retweet scale on the basis of SVM, also, gave a method to evaluate the predict accuracy. The experiment with Sina micro-blog data shows a good result that the predict accuracy is up to 86.63%. [ABSTRACT FROM AUTHOR]

In hot topics found on micro-blog, because the text of micro-blog is short and less words, and the terms are not standard, so the traditional hot topic detection method can not find hot topics effectively. In order to solve this problem, this paper presented a method of hot topics found based on speed growth. Firstly, it divided the pretreated micro-blogs on the basis of the equal number of window, and added up the term frequency in each window, and expressed as feature trajectory of binary group sequence. Secondly, it calculated the growth slope of every adjacent two windows to find the words with growth speed. Thirdly, it calculated the growth speed of the word's relevant users and the growth speed of the word's relevant micro-blogs to ensure the word was hot subject or not. Finally, it found hot topics through the hot subject clustering. The experimental proves the feasibility of the algorithm, results show that the method improves the efficiency of the detection to a certain extent, and reduces the undetected rate and false detection rate, it can effectively discover hot topics on micro-blog in time. [ABSTRACT FROM AUTHOR]

To overcome the data sparsity of traditional collaborative filtering algorithm which can cause inaccuracy during finding the nearest-neighbors, the paper came up with a new method combining conditional probability with traditional collaborative algorithm whose neighbors was not always k. The algorithm' core was that the last data matrix was calculated by two-step filling. The first step, it accepted the users whose similarity and the number of both- rated items met the standard as the target user's neighbors and then calculated the value and filled the unrated- items. The second step would fill the left unrated- items relying on the data matrix filled by the first step. Experimental results show that this algorithm can find reliable neighbors, alleviate the data sparsity and achieve better prediction accuracy obviously. [ABSTRACT FROM AUTHOR]

The correlation among different labels plays an important role in classification problems, and recent studies have taken into account label correlation during multi-label learning. The label information is marked into the attribute space through the classifier chains and provides useful information for the other labels during the classification process. The classification results are indeterminate and instable because of the random classifier order in the classifier chain. Besides, it may cause to propagate the error label information. This paper fully considered the local distribution of instance labels, and proposed a locally ordinal classifier chain algorithm. Experimental results show that, the new algorithm outperforms the other commonly used multi-label algorithms most of the time. [ABSTRACT FROM AUTHOR]

This paper proposed an Apriori frequent itemset mining based on bittable and inverted index (A-FIMBII). A-FIM-BII built the index from the collection of items to the transaction, and used priori nature to reduce the generation of candidate sets, calculating the support counts of two items through the bit operations. It compared to Apriori, ECLAT in four datasets. The experiment results show that A-FIMBII has a higher efficiency. [ABSTRACT FROM AUTHOR]

Because the topics changed rapidly which network users discussed, it was difficult to pre-construct the training corpus to meet a variety of situations. To solve the problem above, this paper proposed a method to analyze the orientation in the opinion leaders identification, then established an opinion leader identification model which was based on the influence diffusion probability model (IDPM) and introducing the effective coefficient considering the orientation of the replied comments. The experiments show that the proposed method is effective, the average precisions of the top 50 numbers increased by 10.97% and 5. 45% respectively. [ABSTRACT FROM AUTHOR]

Some recommendation methods based on social network have been raised. These approaches incorporate social network into the CF algorithms and users' preferences can be influenced by the favors of their friends. These social approaches require the knowledge of similarities among friends. There are two popular similarity functions: vector space similarity (VSS) and Pearson correlation coefficient (PCC). However, both friends similarity functions are based on the item-sets they rated in common. In most cases, these functions are impractical, i. e. if two friends do not share the same items in common, the similarity between them will be zeros. To solve this problem, this paper proposed a new social similarity (NSS) function based on the matrix factorization technique. It conducted experiment on a large dataset: Epinions, which was a widely-used dataset with social information. The experiment results illustrate that this approach outperforms the baseline models and achieves a better performance than social-based method, and can solve the problem of new users. [ABSTRACT FROM AUTHOR]

With more and more B2C companies start to provide free delivery service to attract the customers, how to design the free-shipping rule to maximize the retailers' profit and market share has become a new problem facing the online retailers. This paper decomposed the problem into a two-stage model: customer's behavior model and retailer's profit model. First, it built the customer's behavior model to get the optimal purchasing decisions of consumers under a given free shipping threshold and product price. And then it maximized the retailer's profit model which was established on the result of the customer's behavior function to determine the optimal free shipping policy of retailer. Through algorithm design and numerical study, it found that the retailer's profits would jump when free shipping threshold was set at the boundary of product price combination value. [ABSTRACT FROM AUTHOR]

City is a large dissipative system with the self-organizing model. Economy and traffic are the most important subsystems. As the engines of urban system, they both have a clear dynamic evolution process. The process of interactive evolution promotes the development of cities. Under the conditions of the urban self-organizing model, this paper added the government intervention as hetero-organization factors. At the same time, this article introduced how to construct the economy and traffic mutual evolution model by presupposing the stable development of the system. Through the MATLAB software programming to realize the evolutionary process simulation under the balanced power, transport power and economic power, explored the evolution of the interaction between two mechanisms that played an important role in understanding the processes of urban development under the different conditions and forecasting the future trends of urban development. [ABSTRACT FROM AUTHOR]

Cascading failure of the logistics network caused by emergency can have great effect on the security operation of the network. For this reason, this paper built a cascading failure model based on the local information of logistics nodes, for studying and analyzing the effect on the logistics network. The simulation results indicate that: it can resist largely damage caused by cascade failure with less load capacity setting. The more important the node is, the more destructive to logistics network if it failed. The greater the average degree of logistics network, the stronger ability to resist the cascading failure. Lastly, the research has academic guidance significance to enhance the efficient to emergency program and control efficiency in the logistics network. [ABSTRACT FROM AUTHOR]

This paper presented a wolf colony search algorithm based on the leader's strategy, which was based on the characteristics of the wolves prey behavior. The algorithm ideas from the following process. Wolves' individuals competed with each other. So, the strongest wolf was selected as the leader of the wolves, the wolves hunted prey under the leadership of the leader, so that they could be more effective to capture prey. Ultimately wolves could find the global optimum solution by constantly search and capture prey under the leadership of the leader wolf. In order to prove the algorithm's validity, it used test standard functions to make comparison with other algorithms. The results show that the algorithm has better performance in aspects of convergence speed and accuracy, and it is difficult to trap-in local minimum. [ABSTRACT FROM AUTHOR]

Aiming at solving the uncertain multi-objective linear programming (MOLP) with the coefficients under the ellipsoidal disturbance in objective functions and constrain conditions, this paper proposed a robust MOLP problem under the ellipsoidal disturbance. Based on the assumption that all objective functions needed to acquire the robust solutions, it proposed the theorem and proof. Therefore, converted the original uncertain MOLP to the deterministic MOLP constrained with second-order cone. Then, it designed the mixed strategy algorithm, in which the overall process was multi-objective genetic algorithm and calculated the local optimization by SOCP software Sedumi, to obtain the robust solution set. A numerical example demonstrates the effectiveness of the algorithm. [ABSTRACT FROM AUTHOR]

This paper presented an immune particle swarm algorithm for solving generalized Nash equilibrium problem. First it reformulated the generalized Nash equilibrium problem as the nonlinear equations problem by the nonlinear complementarity problem. Then it designed an immune particle swarm algorithm by involving the immune memory function and the antibody concentration inhibition mechanism into the original swarm algorithm. Finally the computer simulation results demonstrate that the proposed algorithm is effective and it not only keeps the variety of the original swarm, but also improves the abilities of seeking the global optimization result and the evolution speed of convergence. [ABSTRACT FROM AUTHOR]

In order to overcome the problems of low convergence precision and easily relapsing into local extremum in basic fruit fly optimization algorithm (FOA), this paper presented an adaptive mutation fruit fly optimization algorithm (FOAAM). During the evolution, in the condition of basic FOA's trapping in local extremum judging from the population's fitness variance and the current optimal, first, it generated M current optimal replicates. Then, it disturbed replicates by a certain probability P Gauss mutation operator. Finally, it optimized mutated replicates again to jump out of local extremum and continue to optimize. Experimental results show that the new algorithm has the advantages of better global searching ability, speeder convergence and more precise convergence. [ABSTRACT FROM AUTHOR]

In dynamic grid environment, workflow scheduling problem with multi-QoS (quality of service) constraints is the key to decide the task execution success and efficiency. The existing grid workflow scheduling algorithm was difficult to meet the different needs of practical application, and the algorithm was lack of optimization, it was difficult to provide a variety of strategy, so this paper introduced an improved chaos-genetic algorithm based on the deadline and budget QoS constraints. In order to avoid algorithm appear convergence stagnation, it used the chaos mechanism to combine with genetic algorithms and dynamically adjusted the probability of mutation. Then it put forward the concept of linear combination of time and budget, so that the objective function was transformed into a fitness function. Finally the results of applying chaos-genetic scheduling algorithm show greater performances on both balanced and unbalanced workflows. [ABSTRACT FROM AUTHOR]

This paper defined the interference in the resource-constrained project scheduling problem (RCPSP) and established the corresponding resource-constrained project scheduling models and chaotic particle swarm algorithms for solving interference of several questions. Simulation of the project network disruption, task disruption and resources disruption from the RCPSP has been done to verify the validity of the algorithms and models. And it shows the way for the decision makers how to adjust the original optimal scheduling scheme timely after the disruption events happened. [ABSTRACT FROM AUTHOR]

In order to improve the scalability of collaborative filtering algorithm, this paper provided an algorithm of GPU based parallel collaborative filtering. GPU used single instruction multiple data (SIMD), and was proper for calculating weak logic and large amount data, which was exactly the features of collaborative filtering. It designed the whole procedure of the GPU based parallel collaborative filtering and implemented it using CUDA. The experimental results show the algorithm is very efficient to process the large-scale datasets with good accuracy. [ABSTRACT FROM AUTHOR]

In the analysis of existing methods of Petri net modeling and FPGA implementation of the models, this paper firstly discussed the Petri net modeling of parallel computing. This method included decomposing the parallel computing task into multiple parallel processing units, and modeling the system by using IOPT net. Then it proposed the double layer structure, which contained monitoring layer and of algorithm layer, in order to map the Petri net model to FPGA implementation. This implementation method was an effective solution to the problem that transitions of Petri nets model could only represent the simple addition and subtraction operations. A matrix multiplication application shows that the above methods are correct and generic. Finally, it gave further research directions. [ABSTRACT FROM AUTHOR]

The fast Fourier transform (FFT) method is an algorithm than most commonly used in practical applications, but the traditional FFT method to measure the flicker caused by multiple modulation is not accurate enough relative to the method recommended by International Electrical Commit (IEC). In order to accurately measure the flicker, this paper proposed an improved fast FFT method. Using the single-frequency modulation wave and double-frequency one for flicker detection input signal, it compared each processing step between the FFT-based method and the IEC method, found out the error of the FFT-based method, and then proposed correction method. The simulation results show that the flicker estimating results by the modified FFT-based method are consistent with the IEC method, and meet the requirements of IEC standard. The correction method is also applied to flicker estimation containing three-frequency modulation wave. [ABSTRACT FROM AUTHOR]

In D-S evidence theory, conflict coefficient cannot well depict the conflict between evidence, and counterintuitive results generate in the combination of highly conflicting evidence. Aiming at this question, this paper proposed a new combination approach from the aspect of clustering analysis. Firstly, it built up cosine similarity space, in which cosine between evidence vectors was used to measure the similarity degree, and then classified the evidence by way of conflict evidence detection coefficient. Moreover, it introduced conflict proportion coefficient to decide the modified method--local modification or full modification according to its similarity. Finally, it input the modified evidence to D-S combination formula. Application examples prove that this approach can differentiate conflict evidence, processes good stability, classification precision and convergence speed, so it is suitable for the combination of similarity evidence and conflict evidence. [ABSTRACT FROM AUTHOR]

Text e-mail data represented by vector space model (VSM) are high dimensionality. This situation is not conducive to construct e-mail filtering model. Therefore, dimensionality reduction need be performed. MNMF could simultaneously achieve dimensionality reduction and e-mail classification, and graph regularized NMF could keep the geometrical structure of the data space. Based on the above two improved NMF models, this paper put forward GMNMF algorithm, and designed an iterative solution algorithm. Using GMNMF algorithm and other related algorithm do Chinese spam filtering experiments. The experimental results show that the model of the proposed algorithm is superior to models of other good algorithms. [ABSTRACT FROM AUTHOR]

This paper presented a reliable guaranteed cost control for the control of the system output probability density functions (PDF) with which existed non-reliable controller using numerical solution optimization. It was noted that the performance index of the guaranteed cost was guaranteed to be more than a certain upper bound using the control algorithm. It gave a sufficient condition for the existence of reliable guaranteed cost algorithm using linear matrix inequality (LMI). Furthermore, it derived the optimal reliable guaranteed cost algorithm using a convex optimization algorithm. An illustrative example demonstrates that the system output probability density functions follows the given probability density functions and the well robustness and stability is obtain. [ABSTRACT FROM AUTHOR]

The traditional ATPG generating test pattern data by single faults model leads to huge test pattern quantities. Aiming for this problem, this paper proposed a dynamic compaction of multiple target test patterns based on SAT and demonstrated how the multiple target test generation problems could be formulated as a SAT problem. This method integrated robust SAT algorithm into the classical dynamic compaction flow. Classical dynamic compaction flow pruned a large number of faults which were easy to detect with only a few test patterns, and then the SAT solver to get the one synchronous solution in multiple target faulty and additional constraint. Finally, it obtained the high faulty coverage test pattern data and the maximum faulty list for one synchronous test. Experimental results on same large industrial circuits show that generated data of multiple target test generation compared with them of classical dynamic compression is able to reduce data count as much as 70%. [ABSTRACT FROM AUTHOR]

It is frequent to search a lot of useless states and actions which can result in redundant calculations in solving planning problems over a non-deterministic state-transition system in non-determinate plan field. Getting state accessibility relation for the nondeterministic state-transition system can avoid useless searching, reduce redundant calculations and create a guided information for the nondeterministic state-transition system. Based on acyclic reachability relation, this paper defined the calculation rules of matrix multiplication, classification of circular reachability relation and two-reachability relation. It aslo presented the method to get circular reachability relation and designed an algorithm for this. The example proves the validity and correctness of the algorithm. If the non-determinate plan has the information of state accessibility, it can delete useless states and actions to reduce the size of the problem and improve solution efficiency of solving planning problem. [ABSTRACT FROM AUTHOR]

Aiming at the premature convergence problem in traditional intelligent optimization algorithm, this paper proposed a fuzzy artificial bees colony algorithm, it based on the principles of fuzzy processing and bees colony behavior. It introduced fuzzy inputs and fuzzy outputs into the algorithm to maintain dynamic updates of the nectar access probability. According to effective adjustment on nectar access probability during the different stages of algorithm calculation, the algorithm avoided local optima. Simulation tests of traveling salesman problem and comparisons with other algorithms show the performance of proposed algorithm. The computational results prove the algorithm is feasible and effective. [ABSTRACT FROM AUTHOR]

Aiming at the semantic network graph matching problem's particularity, this paper proposed a new matching algorithm based on the state backtracking search method, which called EBGM. This method took use of the semantic network's directional, converting the graph matching problem into a path search planning and used the depth-first algorithm to form a search step set. And at the same time this paper created index for the all edges of the target graph to accelerate the process of forming edge mapping table, finally made connect of the edge mapping table to get the result set. Experiment results on the real dataset show that the algorithm has higher efficiency. [ABSTRACT FROM AUTHOR]

In order to improve the convergence rate of distributed consensus algorithms, this paper proposed a discrete-time high-order distributed consensus algorithm. The new high-order algorithm utilized the previous state values of two-hop adjacency nodes to accelerate the convergence rate based on single-hop communication. The convergence performance and convergence rate of the discrete-time high-order distributed consensus algorithm were analyzed under undirected networks, meanwhile, it analyzed the discrete-time high-order distributed consensus algorithm with communication time-delay. It provided the simulation results to verify these analytical results, the results show that an average consensus can be reached under a certain condition, the convergence rate of the high-order algorithm is superior to those consensus algorithms, but the time-delay is smaller than the other algorithms utilizing the information of two-hop adjacency nodes. [ABSTRACT FROM AUTHOR]

This paper designed and implemented a system for modeling GPS location history data and anomalous detection. This system could analyze and visualize the distribution of stopovers, movement sequences of moving objects, and the importance of the stopovers. By calculating and visualizing the movement sequences consistency, this system could discover common movement sequences and uncommon movement behaviors. It conducted experiments on the data collected from bar-headed geese captured in the Qinghai Lake region and discover three common movement sequences and three anomalous behaviors respectively which indicate the correctness of our system. [ABSTRACT FROM AUTHOR]

At present there are many problems in the development of the Internet of things. These coding systems are not uniform, not compatible with each other, and limited to certain areas so unable to be applied in a multi-industry, cross-platform and large-scale way. In order to solve this problem, this paper put forward a new coding ideas and systems, which applied the unified method of coding to mark various items. This coding system abstracted a carrier items which provided the displacement. It looked on product of all the fields as the combination of the two in different way. With the application of the unified coding method on the physical objects and carrier items, it completed the coding of the products, both at the production and circulation stages. And With the application of the unified coding method, based on cloud computing the analysis service system dynamically updates the information of product's owners and state to meet the need of IoT for the real-time monitoring and intelligent management. [ABSTRACT FROM AUTHOR]

According to the coordinated control problem of urban region transportation, this paper presented a traffic cloud computing platform, in which considered the relationship between different control nodes, to allocate control strategy for getting more reasonable the signal timing for different intersections in urban transportation, the growing Internet of things provided reference recommendations on the development strategy for transportation managements based on the characteristics of dynamic change of execution status among different control nodes and the random mutations in running of cloud computing platform. The experimental result shows that the proposed coorderate control cloud strategy is not only increase the traffic efficiency, but also reduce significantly the running energy consumption of cloud computing platform. [ABSTRACT FROM AUTHOR]

In real-time city-traffic monitoring, due to the difficulty in collecting delay time at intersections and the complexity of the computational model of the intersection traffic, it is very difficult to judge the city-traffic accurately. In order to solve the problem, this paper proposed a real-time traffic discrimination method based on simplified network model. In this method, various intersections were abstracted to a node respectively and the delay time at an intersection was added to the travel time of the road connected to it. Then in real-time traffic monitoring, it calculated the traffic state of ordinary roads, roundabouts and overpasses to achieve real-time monitoring of the traffic. Finally, it gave a simulation experiment of real-time city-traffic monitoring to prove its validity. [ABSTRACT FROM AUTHOR]

For the problem of little regarding of the constituent elements associated with each other for the dynamic evolution of the software architecture, it considered the composition of the software architecture from the associated point, described software architecture and its dynamic evolution with incidence matrix and incidence cardinality, this paper proposed a dynamic evolution method of the software architecture based on the incidence matrix, and designed the corresponding implemented algorithm, finally, through case analysis and experimental, verified the effectiveness of the method. This method can be effectively achieve traceability and controllability of the dynamic evolution of software architecture. [ABSTRACT FROM AUTHOR]

The comprehensive evaluation of software usability process is necessary factors to develop credible software products. First, this paper constructed the software usability process comprehensive evaluation model by software life-cycle model and software usability measurement model. It used this model to guide and regulate the software usability development process. In that case it could be guaranteed to produce a high usability product. Secondly, it used the fuzzy analytic hierarchy process (FAHP) to measure and evaluate this model. Finally through an example shows that this method can effectively apply in the software development process, and early to ensure the usability of software in the development process. And this method indicates the direction of developing high usability software. [ABSTRACT FROM AUTHOR]

This paper introduced the basic SNM and analyzed its deficiency, and put forward a amelioration method of SNM. To avoid missing comparison and reduce excrescent comparison, adopting changing flexible window method, which changed the size of window dynamically. Solved the problem of subjectivity and inaccurate with fixed field weight offer by man-made by using dynamic adjusting ranking method, and according the record similarity to adjust the rank of field. And it transferred the ranking of field to weight by rank-based weights method. The experiments on the data from the information system show the effectiveness and advantage of the proposed method. At the same time, these two methods are the same with other approximately duplicate records examine methods which based on sorted-merge, advancing the efficiency and accuracy. [ABSTRACT FROM AUTHOR]

Computer interlocking software is the highest safety integrity level software, so it is essential to test it before putting it into use. In order to get interlocking software test cases, combined with UML models with sufficient testing information, this paper proposed a method of test case generation based on UML sequence diagram. By proposing generating algorithm of directed graph SG, transferred sequence diagram into SG and traversed SG based on specific coverage criteria and by using depth-first algorithm. It generated the input, respected output, constraint and scenario context and these four constituted the test case. Finally, route setting example proves the feasibility and correctness of this method. [ABSTRACT FROM AUTHOR]

To satisfy the application demands of modeling for complex semantics of data model, and to overcome the drawbacks of the existing modeling methods of data model based on category theory both in theoretical research and engineering practice, this paper made a sketch data model. The model described formally the consistency transformation of database states by category theory independent of particular database modeling languages in the framework of model category, which extended the expressive and process functions of traditional ER model. Based on the support of sketch for graphical modeling specification, it also provided an algorithm of translating ER model to sketch data model. Besides, it compared and analyzed the advantages of sketch data model and the algorithm through experiments so as to provide a convenient and efficient formal theory framework for categorical method of data model. [ABSTRACT FROM AUTHOR]

The prediction accuracy of most current software defect prediction models is not very high. To solve the problem, this paper investigated a software defect prediction model with the least absolute shrinkage and select operator (LASSO) and the support vector machine (SVM). At first, it reduced the dimension of the original data sets and extracted the data which was irrelevant with software defect prediction by taking advantage of the feature selection capability of LASSO. Then it found the correlated optimal weights of the SVM by making use of the parameter preference capability of cross validation. At last,it finished software defect prediction by utilizing the non-linear computing power of SVM. The simulation experiment indicated that proposed method owe a higher prediction precision than the traditional ones and predicted faster. [ABSTRACT FROM AUTHOR]

Temporal logic of actions is a logic which combines the temporal logic and the logic of actions, describing and validating the concurrent systems with this logic. TLA can express the system and the corresponding properties by adding actions and behaviors, it's harder to understanding the complexity systems' specification with the TLA formula. As same as the state transition graph, predicate behavior graph will be used to describe the concurrent systems. First, this paper introduced the grammar and semantics of temporal logic of actions and how to description the specification of concurrent systems with predicate behavior graphs, then proven the correctness of this describing method. [ABSTRACT FROM AUTHOR]

This paper put forward a cooperating method for key derivation based on the idea of combination of radio interface and core network. It produced the radio child-keys according to the security algorithm list provided by plain radio message and obtained parent-key, and decided the right key by comparing the plain context and the decrypted context. It proves that the correct rate of key derivation is more than 90% in the case that the symbol error rate (SER) is less than 10-3 according to the analysis of feasibility. Therefore it has practical application values. [ABSTRACT FROM AUTHOR]

In order to guarantee the security of cloud computing, based on the analysis of cloud computing security requirements and elliptic curve cryptosystems, this paper proposed a covert mapping combined public key management scheme that was suitable for the distributed cloud computing. It made detailed description of the process of key management, such as key initialization, key distribution, key agreement, key update and key revocation. The analysis results show that the scheme can solve the problem of large scale keys storage and management correctly and efficiently, has high scalability, can resist collusion attack and ensure the security services provided by cloud computing. [ABSTRACT FROM AUTHOR]

Aiming at solving the problems of attack graphs that the complicated relationships between nodes, the existing of cyclic attack paths and reflecting merely the static risk when evaluating the network security, this paper put forward the concept of Bayesian-attack graphs which simplified attack graphs and avoided the appearing of the cyclic paths by an optimized algorithm, combining attack graphs and Bayesian theory. By importing attack evidence and CVSS, this paper proposed a new method against to the vulnerability which could dynamically evaluate the whole and partial network security based on Bayesian-attack graphs. Experimental results in the real network show its veracity and validity, and the method can dynamically reflect the changes of the network security situation comparing to traditional assessment methods. [ABSTRACT FROM AUTHOR]

Internal network brings convenience for corporate office, but increasing threats are also brought into enterprises. Insider threat causes great harm to enterprises, and is difficult to detect, so it is urgently to be solved. This paper put forward a predictive model of insider threat based on Bayesian network attack graphs. It considered the behaviors in attacking process as research objects, and considered the resources and operation sequence as nodes, established Bayesian network attack graphs. It described the different attack paths and attack state in the process of attacking by Bayesian network attack graphs, and used Bayesian network inference algorithm to calculate the risk probability of insider threat. In Bayesian network attack graphs, the concepts of meta-operation, atomic attack and intrusion evidence were defined, and node variable, its value and conditional probability distribution were quantified. Based on the improved likelihood weighted algorithm, the calculation of Bayesian network parameters is easier, and the prediction of insider threat is more accurate. Ultimately, by simulation experiment, it is proved that the modeling speed is fast, the process of calculation is simple, the result is exact, and it is valid and applicative in predicting insider threat. [ABSTRACT FROM AUTHOR]

This paper introduced the definition and the properties of Chebyshev polynomial. According to the deterministic public-key cryptosystem of Chebyshev polynomial, found that it couldn't resist chosen cipher-text attacks. Combining with the security model against chosen cipher-text attacks, this paper proposed the probabilistic public-key cryptosystem of Chebyshev polynomial. The analysis show that the proposed cryptosystem is correct. Through the result of the reduction proof, the proposed cryptosystem can resist the adaptive chosen cipher-text attacks and has the IND-CCA2 security. [ABSTRACT FROM AUTHOR]