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 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.

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.

Discrete-Time fractional Brownian motion (DFBM) and its increment process, called discrete-time fractional Gaussian noise (DFGN), are usually used to describe natural and biomedical phenomena. These two processes are dominated by one parameter, called the Hurst exponent, which needs to be estimated in order to capture the characteristics of physical signals. In the previous work, a variance estimator for estimating the Hurst exponent directly via DFBM was provided, and it didn't consider point selection for linear regression. Since physical signals often appear to be DFGN-type, not DFBM-type, it is imperative to first transform DFGN into DFBM in real applications. In this paper, we show that the variance estimator possesses another form, which can be estimated directly via the autocorrelation functions of DFGN. The above extra procedure of transforming DFGN into DFBM can thus be avoided. On the other hand, the point selection for linear regression is also considered. Experimental results show that 4-point linear regression is almost optimal in most cases. Therefore, our proposed variance estimator is more efficient and accurate than the original one mentioned above. Besides, it is also superior to AR and MA methods in speed and accuracy.

This study proposes an improved per-survivor-processing (PSP) scheme to tackle the phase error issue in the convolutionally coded OFDM systems. The proposed approach takes advantage of the trellis structure of the convolutional codes to compensate the symbol-time-offset (STO) caused phase error in frequency domain. Unlike the traditional PSP scheme which simply estimates the phase error by using a state-based horizontal process, the proposed approach develops an extra state-wise vertical process which selects the most likely phase estimate as the survival phase in each trellis stage and then accordingly align the phase of all states to this survival phase before moving to next trellis stage of the PSP scheme. With the vertical process, the resultant phase estimate is more reliable than that of the conventional PSP scheme and hence improve the accuracy in data decoding. Computer simulations confirm the validity of the proposed approach.

There exists a considerable number of node placement models and algorithms for simulation of wireless multihop networks. However, the topologies created with the existing algorithms do not have properties of real networks. We have developed NPART (Node Placement Algorithm for Realistic Topologies) in order to resolve this fundamental issue in simulation methodology. We compare topologies generated by NPART with open wireless multihop network in Berlin. The NPART generated topologies have almost identical node degree distribution, number of cut-edges and vertices as the real network. Unlike them, topologies generated with the common node placement models have their own characteristics which are considerably different both from NPART and from reality. NPART algorithm has been developed into a tool. We propose a method and present a tool for integration of NPART with various realistic node mobility algorithms and tools, such as Citymob [1] and MOVE [2]. This integrated tool allows easy and time-efficient generation of highly complex, realistic simulation scenarios. We use the tool to evaluate effects of integration between existing open community wireless multi-hop networks and vehicular ad-hoc networks (VANETs). The evaluation shows that despite partial coverage and peculiar topological properties of open networks, they offer high levels of performance and network availability to the mobile end users, virtually identical to performance and availability of planned, dedicatedly deployed networks. Our results indicate that the integration of these networks may bring considerable benefits to all parties involved.

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.

In this letter, an improved statistical simulation model with a new parameter computation method is proposed for Rayleigh fading channels. Compared with the existing simulators, the proposed model yields much higher simulation efficiency, while it can still obtain adequate approximations of the desired statistical properties.

Arc discharge generated by breaking electrical contact is considered as a main source of not only degradation of the electrical property but also an undesired electromagnetic (EM) noise. In order to clarify the effect of heated temperature on the bridge, arc-duration and the fluctuation of voltage, opening-waveforms at slowly separating silver-tin dioxide contact with holder heating are measured and discussed experimentally in this paper. Firstly, opening-waveforms are measured. Secondly, voltage fluctuation of the each arc-phase is discussed to extract the effect of the heated holder. The relationship between temperature of the heated holder and duration and fluctuation of the arc was investigated experimentally. It was revealed that as the initial temperature of the heated holder becomes higher, arc-duration becomes slightly longer. In addition, voltage fluctuation at the gaseous-phase decreases when the holder is heated. Consequently, the heated holder can suppress the voltage fluctuation even if its duration becomes slightly longer.

This paper presents a response time acceleration technique in a high-gain capacitive-feedback frontend amplifier (FA) for high output impedance sensors. Using an auxiliary amplifier as a unity-gain buffer, a sample-and-hold capacitor which is used for band-limiting and sampling the FA output is driven at the beginning of the transient response to make the response faster and then it is re-charged directly by the FA output. A condition and parameters for the response time acceleration using this technique while maintaining the noise level unaffected are discussed. Theoretical analysis and simulation results show that the response time can be less than half of the case without the acceleration technique for the specified settling error of less than 0.5%.

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.

Question and Answering (Q&A) sites are recently gaining popularity on the Web. People using such sites are like a community-anyone can ask, anyone can answer, and everyone can share, since all of the questions and answers are public and searchable immediately. This mechanism can reduce the time and effort to find the most relevant answer. Unfortunately, the users suffer from answer quality problem due to several reasons including limited knowledge about the question domain, bad intentions (e.g. spam, making fun of others), limited time to prepare good answers, etc. In order to identify the credible users to help people find relevant answer, in this paper, we propose a ranking algorithm, InfluenceRank, which is basis of analyzing relationship in terms of users' activities and their mutual trusts. Our experimental studies show that the proposed algorithm significantly outperforms the baseline algorithms.

Tin (Sn) contacts are widely applied to connector contacts. Surfaces of plated tin layer are covered with an oxide film that results in high contact resistance. However, it is possible to obtain low contact resistance by using high contact load. Current downsizing trends often make it difficult to obtain high contact loads. Therefore, it is important to conduct basic studies of the contacts resistance characteristics under low contact load conditions. In this study, relationships between contact resistance and the changes of contact traces were examined. When a platinum (Pt) hemisphere contacted to tin plated flat coupon, it was found that the hemisphere surface sank into the softer tin plated flat surface during loading resulting in a piling up tin crystal grains along the periphery of the contact trace. During this process, sudden decrease in contact resistance was observed. To clarify the phenomenon, morphology changes of contact traces were observed by AFM, SEM and EBSD. FEM analysis was also used to analyze the mechanical stress distribution in the tin plated layer. Due to the peculiar distribution of stress, the crystal grains are separated and push out the contact area. This phenomenon is very different from commonly observed decrease in contact resistance due to elastic and plastic deformation inducing mechanical fracture of the surface oxide film.

In this paper, we propose a successive signal-to-leakage-plus-noise ratio (SLNR) based precoding with geometric mean decomposition (GMD) for the downlink multi-user multiple-input multiple-output (MU-MIMO) systems. The known leakages are canceled at the transmit side, and SLNR is calculated with the unknown leakages. GMD is applied to cancel the known leakages, so the subchannels for each receiver have equal gain. We further improve the proposed precoding scheme by ordering users. Simulation results show that the proposed schemes have a considerable bit error rate (BER) improvement over the original SLNR scheme.

In this paper, the correspondence between the weighted line graph and the Mason signal flow graph (MSFG) has been established, which gives an interpretation of a convolutional network code (CNC) over a cyclic network from a different perspective. Furthermore, by virtue of Mason theorem, we present two new equivalent conditions to evaluate whether the global encoding kernels (GEKs) can be uniquely determined by the given complete set of local encoding kernels (LEKs) in a CNC over a cyclic network. These two new equivalent conditions turn out to be more intuitive. Moreover, we give an alternative simple proof of an existing result.

Non-negative matrix factorization (NMF) is widely used for music transcription because of its efficiency. However, the conventional NMF-based music transcription algorithm often causes harmonic confusion errors or time split-up errors, because the NMF decomposes the time-frequency data according to the activated frequency in its time. To solve these problems, we proposed an NMF with temporal continuity and harmonicity constraints. The temporal continuity constraint prevented the time split-up of the continuous time components, and the harmonicity constraint helped to bind the fundamental with harmonic frequencies by reducing the additional octave errors. The transcription performance of the proposed algorithm was compared with that of the conventional algorithms, which showed that the proposed method helped to reduce additional false errors and increased the overall transcription performance.

Entangled states play crucial roles in quantum information theory and its applied technologies. In various protocols such as quantum teleportation and quantum key distribution, a good entangled state shared by a pair of distant players is indispensable. In this paper, we numerically examine entanglement sharing protocols using quantum LDPC CSS codes. The sum-product decoding method enables us to detect uncorrectable errors, and thus, two protocols, Detection and Resending (DR) protocol and Non-Detection (ND) protocol are considered. In DR protocol, the players abort the protocol and repeat it if they detect the uncorrectable errors, whereas in ND protocol they do not abort the protocol. We show that DR protocol yields smaller error rate than ND protocol. In addition, it is shown that rather high reliability can be achieved by DR protocol with quantum LDPC CSS codes.

It is shown that simple preprocessing on the reference signals in multichannel feedforward ANC system can improve the convergence performance of the adaptive ANC algorithm. A fast and efficient blind preprocessing algorithm in frequency domain is proposed to reduce the computational complexity even that the reference sensors are located far from the noise sources. The permutation problem at different frequency bin is also addressed and solved by an independent vector analysis algorithm. The basic principle and performance comparison are given to verify our conclusion.

We propose linear precoders which jointly minimize the mean-squared error of estimated symbol at the destination node for cooperative multiple-input multiple-output communication systems. Unlike the existing precoders which require high computational complexity to solve the optimization problem on the direct link, the proposed precoder is expressed in a closed-form. Simulation results show that the proposed precoder outperforms the existing precoders in the low SNR region. Moreover, we observe that the proposed iterative algorithm is not sensitive to the initial matrices.

An ad hoc network is a decentralized network that consists of mobile nodes with wireless communication devices without the aid of access points. A Vehicular Ad-hoc NETwork (VANET) is one of the representative applications of the ad hoc network. Epidemic routing has been proposed as a routing protocol based on Store-Carry-Forward mechanism for VANET environment. However, in Epidemic Routing, network resources such as packet buffer of a node are significantly consumed because data packets are spread across the network. Therefore, this paper proposes a new autonomous clustering-based data transfer scheme using positions and moving direction of vehicles for VANETs. The autonomous clustering configures multiple clusters in the network and then only the cluster head that manages the cluster stores data packets. Whenever the cluster meets a new cluster, the cluster head of the cluster decides whether it should forward data packets to the new cluster based on its own position, the destination node's position, and moving direction of the cluster. Finally, this paper presents the simulation results to show the effectiveness of the proposed scheme.