Web Service Business Process Execution Language (BPEL) has become the de facto standard for developing instant service-oriented workflow applications in open environment. The correctness and reliability of BPEL processes have gained increasing concerns. However, the unique features (e.g., dead path elimination (DPE) semantics, parallelism, etc.) of BPEL language have raised enormous problems to it, especially in path feasibility analysis of BPEL processes. Path feasibility analysis of BPEL processes is the basis of BPEL testing, for it relates to the test case generation. Since BPEL processes support both parallelism and DPE semantics, existing techniques can't be directly applied to its path feasibility analysis. To address this problem, we present a novel technique to analyze the path feasibility for BPEL processes. First, to tackle unique features mentioned above, we transform a BPEL process into an intermediary model — BPEL control flow graph, which is proposed to abstract the execution flow of BPEL processes. Second, based on this abstraction, we symbolically encode every path of BPEL processes as some Satisfiability formulas. Finally, we solve these formulas with the help of Satisfiability Modulo Theory (SMT) solvers and the feasible paths of BPEL processes are obtained. We illustrate the applicability and feasibility of our technique through a case study.

Software peer review is regarded as one of the most important approaches to preserving software quality. Due to the distributed collaborations in Open Source Software (OSS) development, the review techniques and processes conducted in OSS environment differ from the traditional review method that based on formal face-to-face meetings. Unlike other related works, this study investigates peer review processes of OSS projects from the social perspective: communication and interaction in peer review by using social network analysis (SNA). Moreover, the relationship between peer review contributors and their activities is studied. We propose an approach to evaluating contributors' activeness and social relationship using SNA named Peer Review Social Network (PeRSoN). We evaluate our approach by empirical case study, 326,286 review comments and 1,745 contributors from three representative industrial OSS projects have been extracted and analyzed. The results indicate that the social network structure influences the realistic activeness of contributors significantly. Based on the results, we suggest our approach can support project leaders in assigning review tasks, appointing reviewers and other activities to improve current software processes.

This paper proposes an algorithm that solves the node-to-set disjoint paths problem in an n-Möbius cube in polynomial-order time of n. It also gives a proof of correctness of the algorithm as well as estimating the time complexity, O(n4), and the maximum path length, 2n-1. A computer experiment is conducted for n=1,2,...,31 to measure the average performance of the algorithm. The results show that the average time complexity is gradually approaching to O(n3) and that the maximum path lengths cannot be attained easily over the range of n in the experiment.

Cost aggregation is one of the most important steps in local stereo matching, while it is difficult to fulfill both accuracy and speed. In this letter, a novel cost aggregation, consisting of guidance image, fast aggregation function and simplified scan-line optimization, is developed. Experiments demonstrate that the proposed algorithm has competitive performance compared with the state-of-art aggregation methods on 32 Middlebury stereo datasets in both accuracy and speed.

We consider a problem of the choice of price plans offered by a telecommunications company: a “pay-as-you-go” plan and a “flat-rate” plan. This problem is formulated as an online optimization problem extending the ski-rental problem, and analyzed using the competitive ratio. We give a lemma for easily calculating the competitive ratio. Based on the lemma, we derive a family of optimal strategies for a realistic class of instances.

The power grid defines one of the most important technological networks of our times and has been widely studied as a kind of complex network. It has been developed for more than one century and becomes an extremely huge and seemingly robust system. But it becomes extremely fragile as well because some unexpected minimal failures may lead to sudden and massive blackouts. Many works have been carried out to investigate the structural vulnerability of power grids from the topological point of view based on the complex network theory. This Letter focuses on the structural vulnerability of the power grid under the effect of selective node removal. We propose a new kind of node centrality called overall information centrality (OIC) to guide the node removal attack. We test the effectiveness of our centrality in guiding the node removal based on several IEEE power grids. Simulation results show that, compared with other node centralities such as degree centrality (DC), betweenness centrality (BC) and closeness centrality (CC), our OIC is more effective to guide the node removal and can destroy the power grid in less steps.

In this paper, we study the power allocation problem in a relay assisted multi-band underlay cognitive radio network. Such a network allows unlicensed users (secondary users) to access the spectrum bands under a transmission power constraint. Due to the concave increasing property of logarithm function, it is not always wise for secondary users to expend all the transmission power in one band if their aim is to maximize achievable data rate. In particular, we study a scenario where two secondary users and a half-duplexing relay exist with two available bands. The two users choose different bands for direct data transmission and use the other band for relay transmission. By properly allocating the power on two bands, each user may be able to increase its total achievable data rate while satisfying the power constraint. We formulate the power allocation problem as a non-cooperative game and investigate its Nash equilibria. We prove the power allocation game is a supermodular game and that Nash equilibria exist. We further find the best response function of users and propose a best response update algorithm to solve the corresponding dynamic game. Numerical results show the overall performance in terms of achievable rates is improved through our proposed transmission scheme and power allocation algorithm. Our proposed algorithm also shows satisfactory performance in terms of convergence speed.

The usage of peer-to-peer (P2P) networks that provide sharing of real-time environmental data by internet users is becoming more and more popular. As a result, it's necessary to identify the problems during P2P communication and to develop proper solutions. One of the major problems of P2P communication is that it's not possible to reach the clients behind devices that create private networks like network address translation (NAT) and firewalls from the public network. Among the solutions proposed for this problem, Interactive Connectivity Establishment (ICE) and Real Time Media Flow Protocol (RTMFP) are the methods most preferred in the literature. These methods seem more attractive than other NAT traversal mechanisms since they are independent from internet infrastructure and are also appropriate for dynamic structures. However, they do have some disadvantages. In this study, a new state-based end-to-end communication technique (SBN) for NAT traversal was designed and realized. The performance of the designed method was evaluated against three criteria, connectivity check delay, connection packet count and bandwidth, and compared with the ICE method. The results revealed that the suggested SBN method proved an average of 78% success in connectivity check delay, 69% in the number of packets used and 66% in the consumption of bandwidth over the ICE method.

We developed an electrically driven near-infrared broadband light source based on self-assembled InAs quantum dots (QDs). By combining emissions from four InAs QD ensembles with controlled emission center wavelengths, electro-luminescence (EL) with a Gaussian-like spectral shape and approximately 85-nm bandwidth was obtained. The peak wavelength of the EL was blue-shifted from approximately 1230 to 1200 nm with increased injection current density (J). This was due to the state-filling effect: sequential filling of the discrete QD electron/hole states by supplied carriers from lower (ground state; GS) to higher (excited state; ES) energy states. The EL intensities of the ES and GS emissions exhibited different J dependence, also because of the state-filling effect. The point-spread function (PSF) deduced from the Fourier-transformed EL spectrum exhibited a peak without apparent side lobes. The half width at half maximum of the PSF was 6.5 µm, which corresponds to the estimated axial resolution of the optical coherence tomography (OCT) image obtained with this light source. These results demonstrate the effectiveness of the QD-based device for realizing noise-reduced high-resolution OCT.

In this study, we propose a simple, yet general and powerful framework of integrating multiple global and local features by Product Sparse Coding (PSC) for image retrieval. In our framework, multiple global and local features are extracted from images and then are transformed to Trimmed-Root (TR)-features. After that, the features are encoded into compact codes by PSC. Finally, a two-stage ranking strategy is proposed for indexing in retrieval. We make three major contributions in this study. First, we propose TR representation of multiple image features and show that the TR representation offers better performance than the original features. Second, the integrated features by PSC is very compact and effective with lower complexity than by the standard sparse coding. Finally, the two-stage ranking strategy can balance the efficiency and memory usage in storage. Experiments demonstrate that our compact image representation is superior to the state-of-the-art alternatives for large-scale image retrieval.

This paper proposes a moving source localization method that combines TDOA, FDOA and doppler rate measurements. First, the observation equations are linearized by introducing nuisance variables and an initial solution of all the variables is acquired using the weighted least squares method. Then, the Taylor expression and gradient method is applied to eliminate the correlation between the elements in the initial solution and obtain the final estimation of the source position and velocity. The proposed method achieves CRLB derived using TDOA, FDOA and doppler rate and is much more accurate than the conventional TDOA/FDOA based method. In addition, it can avoid the rank-deficiency problem and is more robust than the conventional method. Simulations are conducted to examine the algorithm's performance and compare it with conventional TDOA/FDOA based method.

In this paper we present a novel treatment of cellular automata (CA) from an algebraic point of view. CA on monoids associated with Σ-algebras are introduced. Then an extension of Hedlund's theorem which connects CA associated with Σ-algebras and continuous functions between prodiscrete topological spaces on the set of configurations are discussed.

In this study, we propose a method for measuring a photoplethysmograph using a complementary metal-oxide-semiconductor image sensor (CMOS) or smartphone camera for the adaptation of a mobile health (m-health) services. The proposed algorithm consists of six procedures. Before measuring the photoplethysmograph, the human fingertip must make contact with the smartphone camera lens and turn on the camera light. The first procedure converts the red-green-blue (RGB) to a gray image from a camera image, Then, region of interest (ROI) must be detected from the obtained image. The third procedure calculates the baseline level to reduce direct current (DC) offset effect, before extracting the photoplethysmograph from the camera image. The baseline is filtered, and the last step oversamples the resulting baseline filtered data using cubic spline interpolation. The proposed algorithm has been tested on six people using CMOS image sensors of several smartphones, which can effectively acquire a PPG signal in any situation. We believe that the proposed algorithm could easily be adapted into any m-health system that used a CMOS image sensor.

We numerically and experimentally demonstrate for the first time a novel all-optical quantization technique using dense spectral slicing with a specially designed arrayed waveguide grating for orthogonal frequency division multiplexed signals. By using a mode-locked laser diode with low jitter, the quantization technique can be achieved a high-speed and low-jitter operation. Both numerical and experimental results confirm the feasibility of 10 GSample/s, completely linear 3-bit step quantization for photonic analog to digital conversion. This optical quantization technique will be beneficial for ultra-high-speed optical communication using digital signal processing.

Recently, notable improvements in voice activity detection (VAD) problem have been achieved by adopting several machine learning techniques. Among them, the deep neural network (DNN) which learns the mapping between the noisy speech features and the corresponding voice activity status with its deep hidden structure has been one of the most popular techniques. In this letter, we propose a novel approach which enhances the robustness of DNN in mismatched noise conditions with multi-task learning (MTL) framework. In the proposed algorithm, a feature enhancement task for speech features is jointly trained with the conventional VAD task. The experimental results show that the DNN with the proposed framework outperforms the conventional DNN-based VAD algorithm.

Nowadays, with the development of online social networks (OSN), a mass of online social information has been generated in OSN, which has triggered research on social recommendation. Collaborative filtering, as one of the most popular techniques in social recommendation, faces several challenges, such as data sparsity, cold-start users and prediction quality. The motivation of our work is to deal with the above challenges by effectively combining collaborative filtering technology with social information. The trust relationship has been identified as a useful means of using social information to improve the quality of recommendation. In this paper, we propose a trust-based recommendation approach which uses GlobalTrust (GT) to represent the trust value among users as neighboring nodes. A matrix factorization based on singular value decomposition is used to get a trust network built on the GT value. The recommendation results are obtained through a modified random walk algorithm called GlobalTrustWalker. Through experiments on a real-world sparser dataset, we demonstrate that the proposed approach can better utilize users' social trust information and improve the recommendation accuracy on cold-start users.

To overcome the privacy limitations of conventional PKI (Public Key Infrastructure) systems, combinatorial certificate schemes assign each certificate to multiple users so that users can perform anonymous authentication. From a certificate pool of N certificates, each user is given n certificates. If a misbehaving user revokes a certificate, all the other users who share the revoked certificate will also not be able to use it. When an honest user shares a certificate with a misbehaving user and the certificate is revoked by the misbehaving user, the certificate of the honest user is said to be covered. To date, only the analysis for the worst scenario has been conducted; the probability that all n certificates of an honest user are covered when m misbehaving users revoke their certificates is known. The subject of this article is the following question: how many certificates (among n certificates) of an honest user are covered on average when m misbehaving users revoke their certificates? We present the first average-case analysis of the cover probability in combinatorial certificate schemes.

This paper presents a novel MEMD interval thresholding denoising, where relevant modes are selected by the similarity measure between the probability density functions of the input and that of each mode. Simulation and measured EEG data processing results show that the proposed scheme achieves better performance than other traditional denoisings.

It is known that in the selected mapping (SLM) scheme for orthogonal frequency division multiplexing (OFDM), correlation (CORR) metric outperforms the peak-to-average power ratio (PAPR) metric in terms of bit error rate (BER) performance. It is also well known that four times oversampling is used for estimating the PAPR performance of continuous OFDM signal. In this paper, the oversampling effect of OFDM signal is analyzed when CORR metric is used for the SLM scheme in the presence of nonlinear high power amplifier. An analysis based on the correlation coefficients of the oversampled OFDM signals shows that CORR metric of two times oversampling in the SLM scheme is good enough to achieve the same BER performance as four times and 16 times oversampling cases. Simulation results confirm that for the SLM scheme using CORR metric, the BER performance for two times oversampling case is almost the same as that for four and 16 times oversampling cases.

Aiming to solve the input/output (I/O) bottleneck concerning next-generation interconnections, 5×5-millimeters-squared silicon-photonics-based chip-scale optical transmitters/receivers (TXs/RXs) — called “optical I/O cores” — were developed. In addition to having a compact footprint, by employing low-power-consumption integrated circuits (ICs), as well as providing multimode-fiber (MMF) transmission in the O band and a user-friendly interface, the developed optical I/O cores allow common ease of use with applications such as multi-chip modules (MCMs) and active optical cables (AOCs). The power consumption of their hybrid-integrated ICs is 5mW/Gbps. Their high-density user-friendly optical interface has a spot-size-converter (SSC) function and permits the physical contact against the outer waveguides. As a result, they provide large enough misalignment tolerance to allow use of passive alignment and visual alignment. In a performance test, they demonstrated 25-Gbps/ch error-free operation over 300-m MMF.