In order to verify the correctness of PLC programs by formal methods, the definition of denotational semantics on PLC program language was studied to achieve PLC programs modeling and model checking. Based on the exte...
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In order to verify the correctness of PLC programs by formal methods, the definition of denotational semantics on PLC program language was studied to achieve PLC programs modeling and model checking. Based on the extended λ-calculus definition, the configuration of PLC program architecture, denotational semantics of PLC programs and functions of denotational semantics were defined, which proves the basis of model checking and theorem.
In mathematics, various representations of real numbers have been investigated and all these representations are proved to be mathematically equivalent. Furthermore, it is known that all effective versions of these re...
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When a large-scale distributed interactive simulation system is running on WAN, the sites usually disperse over a wide area in geography, which results in the simulation clock of each site is hardly to be accurately s...
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When a large-scale distributed interactive simulation system is running on WAN, the sites usually disperse over a wide area in geography, which results in the simulation clock of each site is hardly to be accurately synchronized with that of other sites. The asynchronous clocks and large transmission latency on WAN bring on a problem for the large-scale simulations to preserve the real-time causal order delivery of received events at each site. In this article, we analyze the indirect way to compare the values of asynchronous simulation clocks at first, and then propose a novel scheme which can select the reconstructible causal control information for each message so as to ensure the causal ordering of events in real time. Experiments demonstrate that the scheme can weaken the effect of network latency, reduce the overhead of the transmission amount of control information and improve the causal order consistency in asynchronous distributed simulations.
In this paper, a robust watermarking algorithm against geometric distortions and common signal processing is proposed. This algorithm is based on two method to solve the synchronization of the original watermarking im...
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The Common Spatial Patterns (CSP) algorithm is useful for calculating spatial filters for detecting event-related desynchronization (ERD) for use in ERD-based brain-computer interfaces (BCIs). However, basic CSP is a ...
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The Common Spatial Patterns (CSP) algorithm is useful for calculating spatial filters for detecting event-related desynchronization (ERD) for use in ERD-based brain-computer interfaces (BCIs). However, basic CSP is a supervised algorithm suited only to two-class discrimination; it is unable to solve multiclass discrimination problems. This paper proposes a new method named the binary common spatial patterns (BCSP) algorithm to extend the basic CSP method to multi-class recognition. Our method arranges the spatial filters and Fisher classifiers in the form of a binary tree whereby N - 1 spatial filters and N - 1 Fisher classifiers are calculated for N class recognition. This is fewer than must be calculated in other methods (e.g. one-versus-rest, OVR). This makes the overall classification procedure less redundant. Simulation results show that BCSP has better performance than the OVR scheme and outperforms the three best teams in the 2008 BCI-competition.
With the rapid development of the informationtechnology, it is inevitable that the distributed mobile computing will evolve to the pervasive computing gradually whose final goal is fusing the information space compos...
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With the rapid development of the informationtechnology, it is inevitable that the distributed mobile computing will evolve to the pervasive computing gradually whose final goal is fusing the information space composed of computers with the physical space in which the people are working and living in. To achieve this goal, one of the problems is how to continuously monitor/capture and interpret the environment related information efficiently to assure high context awareness. Many attentions have been paid to the research of the context-aware pervasive applications. However, most of them just use the raw context directly or take just some aspects of the Quality of Context (QoC) into account. Therefore, we propose a middleware based context-aware framework that support QoC management in various layers. By this framework we can refinery raw context, discard duplicate and inconsistent context so as to protect and provide QoS-enriched context information of users to context-aware applications and services.
In this paper, a new visual saliency detection method is proposed based on the spatially weighted dissimilarity. We measured the saliency by integrating three elements as follows: the dissimilarities between image pat...
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In this paper, a new visual saliency detection method is proposed based on the spatially weighted dissimilarity. We measured the saliency by integrating three elements as follows: the dissimilarities between image patches, which were evaluated in the reduced dimensional space, the spatial distance between image patches and the central bias. The dissimilarities were inversely weighted based on the corresponding spatial distance. A weighting mechanism, indicating a bias for human fixations to the center of the image, was employed. The principal component analysis (PCA) was the dimension reducing method used in our system. We extracted the principal components (PCs) by sampling the patches from the current image. Our method was compared with four saliency detection approaches using three image datasets. Experimental results show that our method outperforms current state-of-the-art methods on predicting human fixations.
We address the cryptographic topic of proxy re-encryption (PRE), which is a special public-key cryptosystem. A PRE scheme allows a special entity, known as the proxy, to transform a message encrypted with the public...
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We address the cryptographic topic of proxy re-encryption (PRE), which is a special public-key cryptosystem. A PRE scheme allows a special entity, known as the proxy, to transform a message encrypted with the public key of a delegator (say Alice), into a new ciphertext that is protected under the public key of a delegatee (say Bob), and thus the same message can then be recovered with Bob's private key. In this paper, in the identity-based setting, we first investigate the relationship between so called mediated encryption and unidirectional PRE. We provide a general framework which converts any secure identity-based unidirectional PRE scheme into a secure identity-based mediated encryption scheme, and vice versa. Concerning the security for unidirectional PRE schemes, Ateniese et al. previously suggested an important property known as the master secret security, which requires that the coalition of the proxy and Bob cannot expose Alice's private key. In this paper, we extend the notion to the identity-based setting, and present an identity-based unidirectional PRE scheme, which not only is provably secure against the chosen eiphertext attack in the standard model but also achieves the master secret security at the same time.
E-learning provides an unprecedented flexibility and convenience for learners via breaking the limitation of space-time. Most researchers are only concerned about the learner's cognitive and construct a great amou...
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E-learning provides an unprecedented flexibility and convenience for learners via breaking the limitation of space-time. Most researchers are only concerned about the learner's cognitive and construct a great amount of substantive digital learning resources, however they neglect of the learners' affect in current e-learning systems. In this paper, we focus primarily on the negative affect of learners, and propose an emotion compensation mechanism associated with trust and personality traits in traditional recommender technology. First, we analyze the difference between emotion compensation and traditional recommender. Next, the score of trust is calculated with historical behavior, otherwise depend on similarity of personality traits without historical experience. We use trustworthiness to replace similarity as prediction weight in trust filtering process. At last we do experiments with data collected in previous system named emotion-chatting. Compared with results of experiments between traditional recommender and trust-personality recommender, the average of accuracy is improved 4 points in percentage.
Cloud computing' service-oriented characteristics advance a new way of service provisioning called utility based computing. However, toward the practical application of commercialized Cloud, we encounter two chall...
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Cloud computing' service-oriented characteristics advance a new way of service provisioning called utility based computing. However, toward the practical application of commercialized Cloud, we encounter two challenges: i) there is no well-defined job scheduling algorithm for the Cloud that considers the system state in the future, particularly under overloading circumstances; ii) the existing job scheduling algorithms under utility computing paradigm do not take hardware/software failure and recovery in the Cloud into account. In an attempt to address these challenges, we introduce the failure and recovery scenario in the Cloud computing entities and propose a Reinforcement Learning (RL) based algorithm to make job scheduling fault-tolerable while maximizing utilities attained in the long term. We carry out experimental comparison with Resource-constrained Utility Accrual algorithm (RUA), Utility Accrual Packet scheduling algorithm (UPA) and LBESA to demonstrate the feasibility of our proposed approach.
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