Abstract:This paper proposes an event temporal logic (ETL) because there has been no suitable temporal logic that can directly describe the properties of event graph (EG) models. ETL takes events as its atomic propositions and has the abilities to describe the event canceling edge, the passing parameter values between events, time constraints and the priorities of coinstantaneous events, which can facilitate the description of properties for EGs. A model checking method for EG and ETL on the basis of theory of automata is also proposed in this paper to check whether properties hold for models, according to the accepted language is an empty set or not. The experimental results show ETL is powerful enough to describe EG models, and the model checking method for EG and ETL is effective.

Abstract:The Shannon expansion in symbolic computation tree logic is generalized. In a n-valued Łukasiewicz logic system, Łn, the expansion of n-valued McNaughton functions which are induced by logical formulae is studied. The quasi disjunctive normal form and quasi conjunctive normal form of m-ary n-valued McNaughton functions, and the counting problems of m-ary n-valued McNaughton functions are given. In n-valued Łukasiewicz logic system Łn, the construction of formulae and counting problems of their logic equivalence class are provided.

Abstract:Combining user interests with visited web page contents to perform contextual advertising enhances the user experience and adds more ad clicks, increasing revenue. The key issue is to improve the prediction accuracy of click rates for advertisements. The crucial challenges of the advertisement recommendation algorithm are the scalability on large number of users and web page contents, and the low prediction accuracy resulting from data sparsity. When data is large and sparse, the accuracy and efficiency of the traditional recommendation algorithms is poor. This paper proposes a factor model called AdRec. Based on the Unified Probability Matrix Factorization (UPMF), the model addresses the data sparsity problem by combining features of users, advertisements and web page contents to predict the click rate with higher accuracy. In addition, the computational complexity of our algorithm is linear with respect to the number of observed data, and scalable to very large datasets.

Abstract:Under the background of a computer wargame system, a trajectory clustering algorithm named CTECW (clustering trajectories of entities in computer wargames) is proposed. The algorithm is composed of three parts: trajectory pretreatment, trajectory segments clustering, and visual presentation. Trajectory pretreatment transforms original trajectories into simplified ones which are ulteriorly processed into linear segments. In the second part, the concept of density function derived from DENCLUE is introduced and trajectory segments are clustered based on similarity measure under the framework of DBSCAN. The visual presentation exhibits clusters of trajectory segments with martial meanings to trainees, which embodies practical values of CTECW. Both theoretical analysis and experimental results indicate that CTECW could acquire approximate clusters more efficiently compared with TRACLUS and requires no input parameters.

Abstract:Many-Objective optimization is a difficulty for classical multi-objective evolutionary algorithm and has gained great attention during the past few years. In this paper, a dominance relation named bipolar preferences dominance is proposed for addressing many-objective problem. The proposed dominance relation considers the decision maker's positive preference and negative preference simultaneously and creates a strict dominance relation among the non-dominated solutions, which has ability to reduce the proportion of non-dominated solutions in population and lead the race to the Pareto optimal area, which is close to the positive preference and far away from negative preference. To demonstrate its effectiveness, the proposed approach was integrated into NSGA-Ⅱ to be a new algorithm denoted by 2p-NSGA-Ⅱ and tested on a benchmark of two to fifteen-objective test problems. Good results were obtained. The proposed dominance relation was also compared to g-dominance and r-dominance which was the most recently proposed dominance relation, the results of comparative experiment showed 2p-NSGA-Ⅱ was superior to g-NSGA-Ⅱ and r-NSGA-Ⅱ on a whole, no matter the accuracy of obtained solutions or the efficiency of algorithm.

Abstract:Many classical clustering algorithms like Average-link, K-means, K-medoids, Clara, Clarans and so on are all based on a single cluster-center and are only apt to discover convex-structured clusters. Other methods, e.g., CURE and DBSCAN, use more than one point to represent a cluster and can find some well-separated clusters of arbitrary shape. However, they only consider the original scale of the input data; thus, they cannot depart over-lapped or noisy clusters. To this end, this paper is used to propose a multilevel core-set based agglomerative clustering algorithm (MulCA). The idea of MulCA is that the clustering structure is described by multi-level core set. Clustering process is achieved through procedure which the top of the core set automatically becomes the underlying data set. In addition, through the introduction of random sampling based ε-core set (RBC), MulCA algorithm is applied to large-scale data sets. A large number of numerical experiments fully verify the algorithm MulCA.

Abstract:This paper propos a periodic intermittently connected-based data delivery in opportunistic networks (PICD). By effectively utilizing periodic intermittent connectivity between any two nodes, PICD can improve data delivery: First, for a certain node, based on its periodic intermittently-connected paths to the sink and its data delay tolerance, PICD establishes the delay probability model by means of random dynamic programming. Next, PICD will calculate the node's periodic delay probability distribution matrix by the function space iteration. Next, according to the node's distribution matrix, the current data delivery probability can be calculated by specifying period and tolerable delay, and this will become the key-player of the next-hop choosing. In short, the probability forwarding mechanism is delay-relevant and can increase data delivery probability within a tolerable amount of delay. Simulation shows that compared with existing algorithms, which only take advantage of single-hop delivery probability, PICD is better at data delivery and can also lower delay.

Abstract:Resource deployment is an effective means to improve search performance and can also be used to enhance the availability of resource replicas in unstructured P2P networks. Most of the current studies focus on the quantitative analysis of various types of resource replicas and distributed deployment strategies. During the resource deployment process each node selects resource replica exclusively for deployment; however, the process lacks a consideration for deployment behavior interactions among participating nodes. In a P2P network, each node keeps in touch with several other neighbors and are aware of local information, so each node can be assumed to be bounded rational. This paper designs the performance-related payoff function through analyzing the relation between search performance and resource deployment behaviors of nodes, and then models the resource deployment as an evolutionary game. In terms of the description of game evolution, the study can effectively analyze the interactions among nodes and the expected search performance. The simulation results indicate that the proposed resource deployment evolutionary model achieves higher success rate and approximate optimal average hop counts while maintaining a relatively low redundancy.

Abstract:Abuse of anonymous communication systems has introduced new challenges into network administration. The effective identification of anonymous communication traffic is a prerequisite to prevent such abuse; thus, this is fundamentally important for both theoretical researches and practical applications. Existing researches mainly focus on the confirmation of anonymous communication relationship and cannot be used to identify and block anonymous communication traffic. To solve this problem, the operation mechanism is deeply analyzed and traffic characteristics are summarized for the widely used Tor anonymous communication system. On this basis, a TLS fingerprint-based and packet-size distributions based methods are proposed to identify Tor anonymous communication traffic, respectively. The advantages, disadvantages and applicability of these two methods are analyzed and discussed in detail, and are validated by CAIDA dataset and online deployment. Experimental results prove that both methods are effective in identifying Tor anonymous communication traffic.

Abstract:In a wireless sensor network (WSN), the battery is not only limited to, but is also the storage memory. To reduce the requirement of a capacity of the memory in data transmissions, a visual node based progressive data transmission protocol is proposed. First, the concept of a virtual node is introduced. Next the relationships among the virtual nodes are constructed aiming at making full use of sensory data dependence. Second, based on those relationships, a virtual nodes scheduling algorithm is proposed. In a certain data transmission round, the number of cluster members that are scheduled to transmit data is determined accordingly to the memory size of its corresponding cluster-head. The cluster-head collects the data and encodes them jointly, and the progressive memory efficient data transmission is formed. Theoretical analysis and experiment results show that this proposed method can further save energy consumption and has minimal delay compared to DIMENSIONS. More importantly, it is memory-efficient.

Abstract:By considering the frequent migration characteristic of mobile terminal and the existing delegation based RBAC, the delegation based cross-domain access control model in cloud computing of the mobile terminal is presented. This delegation model can solve the problems of the frequent migration. It makes the management node of each domain maintain a dynamic routing table to locate the node. Also, a synthetic method to obtain synthetic mapping role is proposed. By combining the quantified-role method, the delegated node obtains the final mapping role of this cross-domain requirement. This can effectively solve the problem of permission hidden ascension in the mapping. The requirement frequency threshold will avoid the risk which is caused by the malicious node's excessive operation. Analysis shows that the model has better security.

Abstract:In centralized routing, routing tables are computed by a control platform, but routers do not make decisions anymore. It is necessary to build backup paths for each router so that packets can be forwarded after failure. Existing protecting routing schemes cannot work well in low-connectivity topology. To solve this problem, a method for building centralized protection routing is proposed in this paper. In this method, packets can be pushed back to the upstream nodes and sent by the backup paths of upstream nodes if current node has no valid paths after failure. The problem of building optimal protection routing for a given topology is proved to be NP-hard and a heuristic algorithm is proposed. The algorithm is verified in various topologies and the experimental results show that it is better than existing schemes.

Abstract:Although high-speed multi-plane switching networks have removed their internal conflict problem, a routing control algorithm is necessary for realizing conflict-free routing. Otherwise, the conflict phenomenon cannot be totally avoided. This is because the routing plane may be chosen inappropriately by the incoming packet at the input stage. Therefore, a control algorithm based on the idea of conflict links set is presented in this paper. This algorithm controls the allocation of packets among routing planes in the multi-log₂N switching networks, and hence, the conflict-free routing is totally guaranteed. Moreover, it is not only applicable for the RNB and SNB, but also suitable for unicast and multicast. On the other hand, inner link conflicts are removed in multi-log₂N networks. The switching efficiency is improved, but no performance analysis models can be used to analyze the switching performance of Multi-log₂N switching networks. So an analysis model based on embedded Markov chain is proposed in this paper, and is adopted to analyze the queue management and the relevant performance measures in detail, such as the mean waiting time, queue length and the probability of packets loss. All these conclusions are capable of providing well theoretical support for the design of the optical switching architecture based on multi-log₂N switching networks.

Abstract:In order to automatically parse message formats of unknown application-layer protocols, this paper proposes an approach to optimally segment the message formats without a priori knowledge. A hidden semi-Markov model (HSMM) is established for the segmentation and its parameters are estimated from a set of message sequences collected from application sessions. By using the estimated HSMM in the maximum most likely segmentation, a message can be optimally divided into segments and keywords that provide semantic information about the segments can be extracted. This approach does not require the training set to be absolutely pure. The noise mixed in the training set can be filtered out based on its likelihood fitting to the HSMM. The experiments conducted in this paper show that the approach is suited to both text and binary protocols. The application-layer signatures constructed from the extracted keywords are highly accurate in identifying the protocols. The noise mixed in the training set can be efficiently detected and automatically filtered out.

Abstract:To avoid complicated pairing operation and improve performance, Liu, et al. proposed a pairing-free certificateless signcryption scheme, and claims that their scheme is provably secure in a strengthened security model. Unfortunately, by giving concrete attacks, the sutdy indicates that Liu's et al. certificateless signcryption scheme is not secure in this strengthened security model. To solve the problem, an efficient countermeasure is also proposed.

Abstract:Influenced by factors like facial features, accessories, facial outer contours are extracted by the traditional geometric active contour models and conatin depressions and result in fragmentation, etc. To address these problems, according to the characteristics of human face image, the study proposes a hybrid energy based geometric active contour model via combining the energies of contour outer tension force and skin color with the global energy. First an outwards tension force, computed by neighborhoods of contour points, is added to the contour. This force makes the curve insusceptible to the facial features and accessories, but move towards to the facial outer contour. As skin color is the major feature of a human face. Skin color energy is integrated to ensure a more robust algorithm. Finally, an improved skin tone detection model is proposed based on the single Gaussian function. It could generate initial position that are close to the real facial contour, laying a good foundation for contour evolution. The proposed method gives essentially accurate face segmentations on two public face databases. Take the manually segmentations as the ground truth, the proposed method compares favorably to both traditional global and local energy algorithms. Next a more challenging set containing 100 faces of life photos with variances in pose is introduced with illumination and backgrounds. Segmentation results have validated that the proposed method could extract outer facial contour steadily and accurately under such variances.

Abstract:This paper proposed a maximum intensity projection method to enhance the depth and shape perception of the internal maximum intensity features, without a sophisticated or time-consuming transfer function specification. On the basis of a traditional maximum intensity projection, the study first searched for the boundary sample with a similar intensity value and the optimal normal in front of the maximum intensity feature. Through by comparing the intensity and gradient norm. Next, the local illumination coefficients were updated according to the depth of boundary structures, the consequential depth-based shading results largely enhanced the depth, and the shape perception of internal feasible structures. A two-threshold region growing scheme was designed to perform and further highlight the features of interest. The seed was selected by users interactively on the rendered image, and the growing process depended on the intensity values and 3D spatial distances of the boundary samples with optimal normal. The comparison results showed that the proposed method provided more depth cues and shape information of the maximum intensity features than traditional methods and had practical applications in medical and engineering fields.

Abstract:Triangular surface reconstruction out-of-point clouds suffer from noisy, non-uniform distributed data, and complicated topology structure. Thus, an improved growing neural gas approach is proposed. A point cloud projection on local grid is employed to direct node insertion; therefore, to adaptively control neuron growing rate, the geometric and topologic transforms are sychronized. Redundant links are removed through non-manifold edge detection, that guarantees a topologically validate mesh. The network keeps updating triangular grid and then fills holes in a post phase by the extended neighborhood connection mechanism. After all those steps come to a convergent end, there is a gap free and an Euler characteristic correct mesh was obtained. Case studies invalidate the noise robustness and complex topology adaptability. The algorithm cand further adjust mesh size to point cloud distribution. Plus is that reconstructed mesh approximates the surface in high accuracy, and it characterizes uniform equilateral edge share.