A loosened connector between interconnected electric devices causes an increase in electromagnetic radiation when the devices operate in high-frequency bands. To develop a high-frequency circuit equivalent to a connector with contact failure, we previously investigated the parasitic elements caused by failure at the contact boundary. From the results of that study, the inductance and resistance at a connection contact boundary are increased by the loosening of a connector. Furthermore, the increase in inductance is the dominant factor in increasing the intensity of the electromagnetic radiation. In this paper, to suppress electromagnetic radiation resulting from a loose contact, we formulate the contact performance requirement needed to maintain a good contact condition when a small loosening has occurred at the interconnection. To this end, we investigate the mechanism of increase in the inductance by loosening the connector.

Break arcs are rotated by the radial magnetic field formed by a magnet embedded in the pipe-shaped cathode. The arcs are generated in switching a DC42 V resistive circuit. The closed contact current varies from 5 A to 21 A. The curvature of the anode surface is varied to study the dependence of the arc length and the positions of the break arcs in the contact gap. The following results are obtained: (i) as current decreases, there is more difference in arc duration among different curvatures; (ii) as current decreases, the arc duration decreases with decrease of the radius of curvature; (iii) in each contact curvature, the anode spots region is located nearer to the center axis than the cathode spots region; (iv) the arc length just before arc extinction is independent of the curvature of the contacts.

This paper proposes the test case prioritization in regression testing. The large size of a test suite to be executed in regression testing often causes large amount of testing cost. It is important to reduce the size of test cases according to prioritized test sequence. In this paper, we apply the Markov chain Monte Carlo random testing (MCMC-RT) scheme, which is a promising approach to effectively generate test cases in the framework of random testing. To apply MCMC-RT to the test case prioritization, we consider the coverage-based distance and develop the algorithm of the MCMC-RT test case prioritization using the coverage-based distance. Furthermore, the MCMC-RT test case prioritization technique is consistently comparable to coverage-based adaptive random testing (ART) prioritization techniques and involves much less time cost.

High-speed IP address lookup with fast prefix update is essential for designing wire-speed packet forwarding routers. The developments of optical fiber and 100 Gbps interface technologies have placed IP address lookup as the major bottleneck of high performance networks. In this paper, we propose a novel structure named Compressed Multi-way Prefix Tree (CMPT) based on B+ tree to perform dynamic and scalable high-speed IP address lookup. Our contributions are to design a practical structure for high-speed IP address lookup suitable for both IPv4 and IPv6 addresses, and to develop efficient algorithms for dynamic prefix insertion and deletion. By investigating the relationships among routing prefixes, we arrange independent prefixes as the search indexes on internal nodes of CMPT, and by leveraging a nested prefix compression technique, we encode all the routing prefixes on the leaf nodes. For any IP address, the longest prefix matching can be made at leaf nodes without backtracking. For a forwarding table with u independent prefixes, CMPT requires O(logmu) search time and O(mlogmu) dynamic insert and delete time. Performance evaluations using real life IPv4 forwarding tables show promising gains in lookup and dynamic update speeds compared with the existing B-tree structures.

In this paper, we propose a hardware solution for overcoming the problem of high computational demands in a nearest neighbor (NN) based multi-prototype learning system. The multiple prototypes are obtained by a high-speed K-means clustering algorithm utilizing a concept of software-hardware cooperation that takes advantage of the flexibility of the software and the efficiency of the hardware. The one nearest neighbor (1-NN) classifier is used to recognize an object by searching for the nearest Euclidean distance among the prototypes. The major deficiency in conventional implementations for both K-means and 1-NN is the high computational demand of the nearest neighbor searching. This deficiency is resolved by an FPGA-implemented coprocessor that is a VLSI circuit for searching the nearest Euclidean distance. The coprocessor requires 12.9% logic elements and 58% block memory bits of an Altera Stratix III E110 FPGA device. The hardware communicates with the software by a PCI Express (4) local-bus-compatible interface. We benchmark our learning system against the popular case of handwritten digit recognition in which abundant previous works for comparison are available. In the case of the MNIST database, we could attain the most efficient accuracy rate of 97.91% with 930 prototypes, the learning speed of 1.310-4 s/sample and the classification speed of 3.9410-8 s/character.

A facial components based facial expression recognition algorithm with sparse representation classifier is proposed. Sparse representation classifier is based on sparse representation and computed by L1-norm minimization problem on facial components. The features of “important” training samples are selected to represent test sample. Furthermore, fuzzy integral is utilized to fuse individual classifiers for facial components. Experiments for frontal views and partially occluded facial images show that this method is efficient and robust to partial occlusion on facial images.

In most software development environments, time, computing and human resources needed to perform the testing of a component is strictly limited. In order to deal with such situations, this paper proposes a method of creating the best possible test suite (covering the maximum number of 3-tuples) within a fixed number of test cases.

Accurate estimation of Software Code Size is important for developing cost-efficient embedded systems. The Code Size affects the amount of system resources needed, like ROM and RAM memory, and processing capacity. In our previous work, we have estimated the Code Size based on CFP (COSMIC Function Points) within 15% accuracy, with the purpose of deciding how much ROM memory to fit into products with high cost pressure. Our manual CFP measurement process would require 2.5 man years to estimate the ROM size required in a typical car. In this paper, we want to investigate how the manual effort involved in estimation of Code Size can be minimized. We define a UML Profile capturing all information needed for estimation of Code Size, and develop a tool for automated estimation of Code Size based on CFP. A case study will show how UML models save manual effort in a realistic case.

Channel estimation using data-dependent superimposed training (DDST) is developed to doubly selective channels of Orthogonal Frequency Division Multiplexing (OFDM) systems; it consumes no extra bandwidth. An Inter-carrier interference (ICI) Self-cancelation method based on DDST scheme, IS-DDST, is designed which mitigates the interference from adjacent subcarriers to estimation. Moreover, a dual-iteration detection method is proposed to mitigate the ICI for IS-DDST scheme. Theoretical analysis and simulations show that the proposed scheme can achieve better Mean Square Error (MSE) and Bit Error Ratio (BER) performance than the existing DDST based scheme.

A novel watermarked MDC system based on the SFQ algorithm and the sub-sampling method is proposed in this paper. Sub-sampling algorithm is applied onto the transformed image to introduce some redundancy between different channels. Secret information is embedded into the preprocessed sub-images. Good performance of the new system to defense the noise and the compression attacks is shown in the experimental results.

In this correspondence, we devise a new method for constructing a ternary column sequence set of length 3m+1-1 form ternary sequences of period 3m-1 with ideal autocorrelation, and the ternary LCZ sequence set of period 3n-1 is constructed by using the column sequence set when (m+1)|n. In addition, the method is popularized to the p-ary LCZ sequence. The resultant LCZ sequence sets in this paper are optimal with respect to the Tang-Fan-Matsufuji bound.

Internet behavior is becoming more complex due to ever-changing networking technologies and applications. Thus, understanding and controlling the complex behavior of the Internet are important for designing future networks. One of the complex behaviors of the Internet is traffic dynamics. Previous studies revealed that flow control in the transport layer affects the traffic dynamics of the Internet. However, it is not clear how the topological structure impacts traffic dynamics. In this paper, we investigate packet delay dynamics and traffic fluctuation in ISP router-level topologies where the degree distribution exhibits a power-law nature, and the nodes interact via end-to-end feedback control functionality. We show the packet delay dynamics of the BA topologies generated by the Barabasi-Albert (BA) model and the ISP router-level topologies. Simulation results show that the end-to-end delay distributions exhibit a heavy tail in the TCP model. Moreover, the number of links with highly fluctuating queue length increases dramatically compared to that in the stop-and-wait model. Even in this case, the high-modularity structures of the ISP topologies reduce the number of highly fluctuating links compared with the BA topologies.

In this paper, an improved B-picture coding algorithm based on the symmetric bi-directional motion estimation (ME) is proposed. In addition to the block match error between blocks in the forward and backward reference frames, the proposed method exploits the previously-reconstructed template regions in the current and reference frames for bi-directional ME. The side match error between the predicted target block and its template is also employed in order to alleviate block discontinuities. To efficiently perform ME, an initial motion vector (MV) is adaptively derived by exploiting temporal correlations. Experimental results show that the number of generated bits is reduced by up to 9.31% when the proposed algorithm is employed as a new macroblock (MB) coding mode for the H.264/AVC standard.

The non-homogeneous Poisson process (NHPP) has been applied successfully to model nonstationary counting phenomena for a large class of problems. In software reliability engineering, the NHPP-based software reliability models (SRMs) are of a very important class. Since NHPP is characterized by its rate (intensity) function, which is known as the software failure rate of NHPP-based SRM, it is of great interest to estimate accurately the rate function from observed software failure data. In the existing work the same authors introduced a Haar-wavelet-based technique for this problem and found that the Haar wavelet transform provided a very powerful performance in estimating software failure rate. In this paper, we consider the application potentiality of a Daubechies wavelet estimator in the estimation of software failure rate, given the software failure time data. We give practical solutions by overcoming technical difficulties in applying the Daubechies wavelet estimator to the real software failure time data.

Recently, Lee et al. [Y. Lee, E. Kim, S. Seok, and M. Jung, A smartcard-based user authentication scheme to ensure the PFS in multi-server environments, IEICE Transactions on Communications, vol.E95-B, no.2, pp.619–622, 2012] proposed a smartcard-based user authentication scheme for multi-server environments. They claimed that their scheme could withstand various attacks and provide the perfect forward secrecy (PFS). However, in this letter, we will point out that their scheme is vulnerable to three kinds of attacks and cannot provide the PFS.

A Superconcentrator is a directed acyclic graph with specific properties. The existence of linear-sized supercentrator has been proved in [4]. Since then, the size has been decreased significantly. The best known size is 28N which is proved by U. Schöning in [8]. Our work follows their construction and proves a smaller size superconcentrator.

Considerable effort has been devoted to minimizing XPath queries under the assumption that the minimal query is faster than the original query. However, little attention has been paid to the validity of the assumption. In this paper, we provide a detailed analysis on the effectiveness of XPath query minimization and present an extensive experimental evaluation on the effectiveness using six publicly available XQuery engines. To the best of our knowledge, this is the first work done towards this objective. Experiments on real and synthetic data sets show that although the assumption is valid for some cases, the performance of the minimal query is often lower than or almost equal to that of the original query.

We consider wireless secure communications between a source and a destination aided by a multi-antenna relay, in the presence of an eavesdropper. In particular, two cooperation schemes of the relay are explored: cooperative relaying (CR) and cooperative jamming (CJ). We first investigate the transmit weight optimization of CR and CJ, for both cases with and without the eavesdropper's channel state information (ECSI). Then, for the case with ECSI, we derive the conditions under which CR achieves a higher secrecy rate than CJ; for the case without ECSI, we compare the secrecy rates of CR and CJ in high transmit power regimes. Building on this, we propose a novel hybrid scheme in which the relay utilizes both CR and CJ, and study the power allocation of the relay between CR and CJ for maximizing the secrecy rate under individual power constraints. Further, we study the case with imperfect channel state information (CSI) for both CR and CJ. At last, extensive numerical results are provided.

An exponential regression-based model with stochastic intensity is developed to describe the software reliability growth phenomena, where the software testing metrics depend on the intensity process. For such a generalized modeling framework, the common maximum likelihood method cannot be applied any more to the parameter estimation. In this paper, we propose to use the pseudo maximum likelihood method for the parameter estimation and to seek not only the model parameters but also the software reliability measures approximately. It is shown in numerical experiments with real software fault data that the resulting software reliability models based on four parametric approximations provide the better goodness-of-fit performance than the common non-homogeneous Poisson process models without testing metric information.