In this letter, we present a general construction of sequence sets with low correlation zone, which is based on finite fields and the balance property of some functions. The construction is more flexible as far as the partition of parameters is concerned. A simple example is also given to interpret the construction.

This paper presents a novel similarity measure that computes similarity scores among scientific research papers. The text of a given paper in online scientific literature is often found to be incomplete in terms of its potential to be compared with others, which likely leads to inaccurate results. Our solution to this problem makes use of both text and link information of a paper in question for similarity scores in that the comparison text of the paper is strengthened by adding that of papers related to it. More accurate similarity scores can be computed by reinforcing the input with the citations of the paper as well as the citations included within the paper. The efficacy of the proposed measure is validated through our extensive performance evaluation study which demonstrates a substantial gain.

Linear Discriminant Analysis (LDA) is one of the most popular dimensionality reduction techniques in existing handwritten Chinese character (HCC) recognition systems. However, when used for unconstrained handwritten Chinese character recognition, the traditional LDA algorithm is prone to two problems, namely, the class separation problem and multimodal sample distributions. To deal with these problems,we propose a new locally linear discriminant analysis (LLDA) method for handwritten Chinese character recognition.Our algorithm operates as follows. (1) Using the clustering algorithm, find clusters for the samples of each class. (2) Find the nearest neighboring clusters from the remaining classes for each cluster of one class. Then, use the corresponding cluster means to compute the between-class scatter matrix in LDA while keeping the within-class scatter matrix unchanged. (3) Finally, apply feature vector normalization to further improve the class separation problem. A series of experiments on both the HCL2000 and CASIA Chinese character handwriting databases show that our method can effectively improve recognition performance, with a reduction in error rate of 28.7% (HCL2000) and 16.7% (CASIA) compared with the traditional LDA method.Our algorithm also outperforms DLA (Discriminative Locality Alignment,one of the representative manifold learning-based dimensionality reduction algorithms proposed recently). Large-set handwritten Chinese character recognition experiments also verified the effectiveness of our proposed approach.

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.

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.

A method for spatio-temporal resolution enhancement of video sequences based on super-resolution reconstruction is proposed. A new observation model is defined for accurate resolution enhancement, which enables subpixel motion in intermediate frames to be obtained. A modified optimization formula for obtaining a high-resolution sequence is also adopted.

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.

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.

We present attacks on the generalized Feistel schemes, where each round function consists of a subkey XOR, S-boxes, and then a linear transformation (i.e. a Substitution-Permutation (SP) round function). Our techniques are based on rebound attacks. We assume that the S-boxes have a good differential property and the linear transformation has an optimal branch number. Under this assumption, we firstly describe known-key distinguishers on the type-1, -2, and -3 generalized Feistel schemes up to 21, 13 and 8 rounds, respectively. Then, we use the distinguishers to make several attacks on hash functions where Merkle-Damgård domain extender is used and the compression function is constructed with Matyas-Meyer-Oseas or Miyaguchi-Preneel hash modes from generalized Feistel schemes. Collision attacks are made for 11 rounds of type-1 Feistel scheme. Near collision attacks are made for 13 rounds of type-1 Feistel scheme and 9 rounds of type-2 Feistel scheme. Half collision attacks are made for 15 rounds of type-1 Feistel scheme, 9 rounds of type-2 Feistel scheme, and 5 rounds of type-3 Feistel scheme.

Nowadays, software development societies have given more precedence to Open Source Software (OSS). There is much research aimed at understanding the OSS society to sustain the OSS product. To lead an OSS project to a successful conclusion, researchers study how developers change source codes called patches in project repositories. In existing studies, we found an argument in the conventional patch acceptance detection procedure. It was so simplified that it omitted important cases from the analysis, and would lead researchers to wrong conclusions. In this research, we propose an algorithm to overcome the problem. To prove out our algorithm, we constructed a framework and conducted two case studies. As a result, we came to a new and interesting understanding of patch activities.

Electromagnetic wave scattering in two open-ended coaxial cables with flanges is presented for adiabatic transmission line applications. Field distributions in the cables are obtained by employing the mode-matching method. A set of simultaneous equations is solved to investigate the transmission and reflection coefficients.

We present a novel transmission rate control method for Wireless Mesh Networks, termed Semi-Fixed Rate Control (SFRC), which incorporates the advantages of Fixed Rate Control (FRC) and Adaptive Rate Control (ARC). SFRC has two periods, which are alternately repeated: an autorate period and a fixed-rate period. A unit of an autorate period and the successive fixed-rate period is termed “rate-control period”. The duration of the rate-control period is set considerably longer than that of the autorate period. In the autorate period, RTS/CTS is used with the lowest transmission rate, transmission rate adjustment is only applied to data frames, and loss of CTS frames is not reflected in the transmission rate adjustment. In the fixed-rate period, the transmission rate that was used most frequently in the preceding autorate period (optimum rate) is fixed, and RTS/CTS is not used. Implementation of SFRC is straightforward as it uses conventional IEEE 802.11 DCF and only minor modification of the wireless LAN driver is required. SFRC, which uses a modified SampleRate, an ARC implementation in the Madwifi, (SampleRate+) in the autorate period, termed SFRC-SampleRate+, was developed. The results of real-world experiments indicate that SFRC-SampleRate+ is superior to SampleRate and SampleRate+, and is closer to FRC, which uses optimum rate on each link, in terms of throughput in wireless mesh network environments.

This letter presents a robust receiver using the generalized sidelobe canceller aided with the high-order derivative constraint technique for multicarrier code-division multiple-access (MC-CDMA) uplink against carrier frequency offset (CFO). Numerical results demonstrate the efficacy of the proposed receiver.

In wireless single-hop networks, IEEE 802.11e Enhanced Distributed Channel Access (EDCA) is the standard for Quality of Service (QoS) control. However, it is necessary for controlling QoS to modify the currently used IEEE 802.11 Distributed Coordination Function (DCF)-compliant terminals as well as Access Points (APs). In addition, it is necessary to modify the parameter of IEEE 802.11e EDCA when the traffic is heavy. This paper proposes a novel scheme to guarantee QoS of high-priority flow with Receiving Opportunity Control in MAC Frame (ROC) employed adaptive flow control in wireless multi-hop network. In the proposed scheme, the edge APs which are directly connected to user terminals estimate the network capacity, and calculate appropriate ACK prevention probability against low-priority flow according to traffic load. Simulation evaluation results show that the proposed scheme guarantees QoS.

Decision tree-based clustering and parameter estimation are essential steps in the training part of an HMM-based speech synthesis system. These two steps are usually performed based on the maximum likelihood (ML) criterion. However, one of the drawbacks of the ML criterion is that it is sensitive to outliers which usually result in quality degradation of the synthesized speech. In this letter, we propose an approach to detect and remove outliers for HMM-based speech synthesis. Experimental results show that the proposed approach can improve the synthetic speech, particularly when the available training speech database is insufficient.

This letter presents a novel opportunistic cooperative positioning approach for orthogonal frequency-division multiple access (OFDMA) systems. The basic idea is to allow idle mobile terminals (MTs) opportunistically estimating the arrival timing of the training sequences for uplink synchronization from active MTs. The major advantage of the proposed approach over state-of-the-arts is that the positioning-related measurements among MTs are performed without the paid of training overhead. Moreover, Cramer-Rao lower bound (CRLB) is utilized to derive the positioning accuracy limit of the proposed approach, and the numerical results show that the proposed approach can improve the accuracy of non-cooperative approaches with the a-priori stochastic knowledge of clock bias among idle MTs.

This paper proposes a novel satellite channel allocation algorithm for a demand assigned multiple access (DAMA) controller. In satellite communication systems, the channels' total bandwidth and total power are limited by the satellite's transponder bandwidth and transmission power (satellite resources). Our algorithm is based on multi-carrier transmission and adaptive modulation methods. It optimizes channel elements such as the number of sub-carriers, modulation level, and forward error correction (FEC) coding rate. As a result, the satellite's transponder bandwidth and transmission power can be simultaneously used to the maximum and the overall system capacity, i.e., total transmission bit rate, will increase. Simulation results show that our algorithm increases the overall system capacity by 1.3 times compared with the conventional fixed modulation algorithm.

We propose a primary traffic based multihop relaying algorithm with cooperative transmission (PTBMR-CT). It enlarges the hop transmission distances to reduce the number of cognitive relays on the route from the cognitive source (CS) to the cognitive destination (CD). In each hop, from the cognitive nodes in a specified area depending on whether the primary source (PS) transmits data to the primary destination (PD), the cognitive node that is farthest away from the cognitive relay that sends data is selected as the other one that receives data. However, when the PS is transmitting data to the PD, from the cognitive nodes in a specified area, another cognitive node is also selected and prepared to be the cognitive relay that receives data of cooperative transmission. Cooperative transmission is performed if the PS is still transmitting data to the PD when the cognitive relay that receives data of the next hop transmission is being searched. Simulation results show that the average number of cognitive relays is reduced by PTBMR-CT compared to conventional primary traffic based farthest neighbor relaying (PTBFNR), and PTBMR-CT outperforms conventional PTBFNR in terms of the average end-to-end reliability, the average end-to-end throughput, the average required transmission power of transmitting data from the CS to the CD, and the average end-to-end transmission latency.

Distributed applications and services have become pervasive in our society due to the widespread use of internet and mobile devices. There are urgent demands to efficiently ensure safety and correctness of such software. A session-type system is a framework to statically check whether communication descriptions conform to certain protocols. They are shown to be effective yet simple enough to fit in harmony with existing programming languages. In the original session type system, the subject reduction property does not hold. This paper establishes a conservative extension of the original session type system with the subject reduction property. Finally, it is also shown that our typing rule properly extends the set of typeable processes.

Cloud data center services, such as video on demand (VoD) and sensor data monitoring, have become popular. The quality of service (QoS) between a client and a cloud data center should be assured by satisfying each service's required bandwidth and delay. Multipath traffic engineering is effective for dispersing traffic flows on a network; therefore, an improved k-shortest paths first (k-SPF) algorithm is applied to these cloud data center services to satisfy their required QoS. k-SPF can create a set of multipaths between a cloud data center and all edge routers, to which client nodes are connected, within one algorithm process. Thus, k-SPF can produce k shortest simple paths between a cloud data center and every access router faster than with conventional Yen's algorithm. By using a parameter in the algorithm, k-SPF can also impartially use links on a network and shorten the average hop-count and number of necessary MPLS labels for multiple paths that comprise a multipath.