Input/Output (I/O) automata and the Temporal Logic of Actions (TLA) are two well-known techniques for the specification and verification of concurrent systems. Over the past few years, they have been extended to the so-called dynamic I/O automata and, respectively, Mobile TLA (MTLA) in order to be more appropriate for mobile agent systems. Dynamic I/O automata is just a mathematical model, whereas MTLA is a logic with a formally defined language. In this paper, therefore, we investigate how MTLA could be used as a formal language for the specification of dynamic I/O automata. We do this by writing an MTLA specification of a travel agent system which has been specified semi-formally in the literature on that model. In this specification, we deal with always existing agents as well as with an initially unknown number of dynamically created agents, with mobile and non-mobile agents, with I/O-automata-style communication, and with the changing communication capabilities of mobile agents. We have previously written a TLA specification of this system. This paper shows that an MTLA specification of such a system can be more elegant and faithful to the dynamic I/O automata definition because the agent existence and location can be expressed directly by using agent and location names instead of special variables as in TLA. It also shows how the reuse of names for dynamically created and destroyed agents within the dynamic I/O automata framework can be specified in MTLA.

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Frequent Itemsets(FI) mining is a popular and important first step in analyzing datasets across a broad range of applications. There are two main problems with the traditional approach for finding frequent itemsets. Firstly, it may often derive an undesirably huge set of frequent itemsets and association rules. Secondly, it is vulnerable to noise. There are two approaches which have been proposed to address these problems individually. The first problem is addressed by the approach Frequent Closed Itemsets(FCI), FCI removes all the redundant information from the result and makes sure there is no information loss. The second problem is addressed by the approach Approximate Frequent Itemsets(AFI), AFI could identify and fix the noises in the datasets. Each of these two concepts has its own limitations, however, the authors find that if FCI and AFI are put together, they could help each other to overcome the limitations and amplify the advantages. The new integrated approach is termed Noise-tolerant Frequent Closed Itemset(NFCI). The results of the experiments demonstrate the advantages of the new approach: (1) It is noise tolerant. (2) The number of itemsets generated would be dramatically reduced with almost no information loss except for the noise and the infrequent patterns. (3) Hence, it is both time and space efficient. (4) No redundant information is in the result.

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In the recent high-density and low-power VLSIs, the occurrence of soft errors has become a significant problem. Recently, soft errors frequently occur on not only memory system but also logic circuits. Based on this standpoint, some constructions of soft-error-tolerant FFs were proposed. A conventional FF consists of some master and slave latches and C-elements. In the FF, soft error pulses occurring on combinational parts of logic circuits are corrected as long as the width of the pulses is narrow, that is within a specified width. However, error pulses with wide width are neither detected nor corrected in the FF. This paper presents a construction of soft-error-tolerant FFs by modifying the conventional soft-error-tolerant FF. The proposed FFs have the capability to detect error pulses having wide width as well as the capability to correct those having narrow width. The proposed FFs are also capable of detecting hard errors. The evaluation shows the soft-error-tolerant capability, AC characteristics, area overhead and power consumption of the FFs.

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In this study we introduce AdjScales, a method for scaling similar adjectives by their strength. It combines existing Web-based computational linguistic techniques in order to automatically differentiate between similar adjectives that describe the same property by strength. Though this kind of information is rarely present in most of the lexical resources and dictionaries, it may be useful for language learners that try to distinguish between similar words. Additionally, learners might gain from a simple visualization of these differences using unidimensional scales. The method is evaluated by comparison with annotation on a subset of adjectives from WordNet by four native English speakers. It is also compared against two non-native speakers of English. The collected annotation is an interesting resource in its own right. This work is a first step toward automatic differentiation of meaning between similar words for language learners. AdjScales can be useful for lexical resource enhancement.

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In this paper, we present a forecasting method for the view of Mt. Fuji as an application of Earth observation data (EOD) obtained by satellites. We defined the Mt. Fuji viewing index (FVI) that characterises how well the mountain looks on a given day, based on photo data produced by a fixed-point observation. A long-term predictor of FVI, ranging from 0 to 30 days, was constructed through support vector machine regression on climate and earth observation data. It was found that the aerosol mass concentration (AMC) improves prediction performance, and such performance is particularly significant in the long-term range.

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In this paper, a novel illumination invariant face recognition algorithm is proposed for face recognition. This algorithm is composed of two phases. In the first phase, we reduce the effect of illumination changes using a nonlinear mapping of image intensities. Then, we modify the distribution of the coefficients of wavelet transform in certain sub-bands. In this step, the recognition performance is more important than image quality. In the second phase, we used the unitary factor of polar decomposition of enhanced image as a feature vector. In the recognition phase, the correlation-based nearest neighbor rule is applied for the matching. We have performed some experiments on several databases and have evaluated the proposed method in different aspects. Experimental results in recognition show that this approach provides a suitable representation for overcoming illumination effects.

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In this letter we give a lower bound on the worst-case time complexity of Dijkstra's three-state mutual exclusion algorithm by specifying a concrete behavior of the algorithm. We also show that our result is more accurate than the known best bound.

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This paper presents a fuzzy-based path selection method for improving the security level, in which each cluster chooses paths based on the detection power of false data and energy efficiency.

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In this paper, we study d-primitive words and D(1)-concatenated words. First we show that neither D(1), the set of all d-primitive words, nor D(1)D(1), the set of all D(1)-concatenated words, is regular. Next we show that for u, v, w ∈ Σ⁺ with |u|=|w|, uvw ∈ D(1) if and only if uv⁺w ⊆ D(1). It is also shown that every d-primitive word, with the length of two or more, is D(1)-concatenated.

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Weighted graph matching is computationally challenging due to the combinatorial nature of the set of permutations. In this paper, a new relaxation approach to weighted graph matching is proposed, by which a new matching algorithm, named alternate iteration algorithm, is designed. It is proved that the algorithm proposed is locally convergent. Experiments are presented to show the effectiveness of the proposed algorithm.

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In this paper, we propose a new feature selection algorithm for multi-class classification. The proposed algorithm is based on Gaussian mixture models (GMMs) of the features, and it uses the distance between the two least separable classes as a metric for feature selection. The proposed system was tested with a support vector machine (SVM) for multi-class classification of music. Results show that the proposed feature selection scheme is superior to conventional schemes.

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This paper introduces an intermediate virtual representation, called ideal fisheye image, which obeys the ideal simple projection without camera distortion. By using a look-up-table from the ideal fisheye image to the input fisheye image with distortion, a view-direction-free perspective display can be generated fast in comparison with the method of solving a set of nonlinear equations of camera distortion parameters.

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Coding complexity is a crucial parameter in rate control scheme. Traditional measures for coding complexity are based on statistic and estimation. This way may cause the imprecise coding complexity and finally bring inaccurate output bit rate more or less. To resolve this problem, we propose a hypothetical virtual coding complexity to imitate the real coding complexity. Based on the proposed coding complexity measure, a novel rate control algorithm is proposed either. Experimental results and analysis show that the proposed mearsure for coding complexity is effective, and our scheme outperforms the JVT-W042 solution by providing more accurate QP prediction, reducing frame skipping, and improving visual quality.

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In this letter, we present an automatic approach of objective singing performance evaluation for untrained singers by relating acoustic measurements to perceptual ratings of singing voice quality. Several acoustic parameters and their combination features are investigated to find objective correspondences of the perceptual evaluation criteria. Experimental results show relative strong correlation between perceptual ratings and the combined features and the reliability of the proposed evaluation system is tested to be comparable to human judges.

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