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.

The minimized assumption generation has been recognized as an important improvement of the assume-guarantee verification method in order to generate minimal assumptions. The generated minimal assumptions can be used to recheck the whole component-based software at a lower computational cost. The method is not only fitted to component-based software but also has a potential to solve the state space explosion problem in model checking. However, the computational cost for generating the minimal assumption is very high so the method is difficult to be applied in practice. This paper presents an optimization as a continuous work of the minimized assumption generation method in order to reduce the complexity of the method. The key idea of this method is to find a smaller assumption in a sub-tree of the search tree containing the candidate assumptions using the depth-limited search strategy. With this approach, the improved method can generate assumptions with a lower computational cost and consumption memory than the minimized method. The generated assumptions are also effective for rechecking the systems at much lower computational cost in the context of software evolution. An implemented tool supporting the improved method and experimental results are also presented and discussed.

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.

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%.

A model-based mutation testing (MBMT) approach enables to perform negative testing where test cases are generated using mutant models containing intentional faults. This paper introduces an alternative MBMT framework using pushdown automata (PDA) that relate to context-free (type-2) languages. There are two key ideas in this study. One is to gain stronger representational power to capture the features whose behavior depends on previous states of software under test (SUT). The other is to make use of a relatively small test set and concentrate on suspicious parts of the SUT by using MBMT approach. Thus, the proposed framework includes (1) a novel usage of PDA for modeling SUT, (2) novel mutation operators for generating PDA mutants, (3) a novel coverage criterion, and an algorithm to generate negative test cases from mutant PDA. A case study validates the approach, and discusses its characteristics and limitations.

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.

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.

3 dB bandwidth enhancement of single mode semiconductor lasers is confirmed numerically and experimentally when they are operated by intensity modulated signal light injection. 3 dB bandwidth is enlarged to 2.5 times of resonant frequency. The numerical analysis of rate equations predicts that the bandwidth enhancement is accomplished by the modal gain control of semiconductor lasers with injected intensity modulated signal light through non-linear gain coefficient term.

In this paper, a contactless measurement technique of passive intermodulation (PIM) using a coaxial tube excited with standing waves is proposed. The principle of the proposed method is described using a two-port network model with the lumped resistances representing the losses of a specimen and test equipment. To show its validity, a test using nickel wires producing high PIM is carried out, and its PIM-dependency on DUT-position in the coaxial tube is simulated using the FDTD method. The simulated result shows a good agreement to the experiment. Through the examination, it is found that the power consumption by the PIM source in a specimen is essential in PIM production, and sensitive PIM detection does not require good matching condition. Finally, the relation between PIM-source size and generated PIM level is also examined. The result shows that at least 18 dB-PIM reduction is obtained by PIM source size in a half-wavelength conductive wire.

Experiments were carried out at several voltages to clarify the influence of the voltage on various characteristics, i.e. arc duration, contact resistance, arc energy, and the change in electrode mass. The voltage was varied from DC100 V to 160 V, the load current was fixed at 5 A constant, and the electromagnetic contactor was operated continuously up to 100,000 times. The experiments were carried out under the three operation modes which are classified by the arc discharge. As a result, the relation between the operation mode and contact resistance was clarified. When only a make arc was generated, the contact resistance was smallest. In addition, the contact resistance was not affected by the source voltage.

In this letter, we propose a Cooperation-aware topology control scheme with Opportunistic Interference Cancellation (COIC) to improve network capacity in wireless ad hoc networks by jointly considering both upper layer network capacity and physical layer cooperative communications with interference cancellation. We show that the benefits brought by cooperative communications are opportunistic and rely on network structures and channel conditions. Such opportunistic advantages have significant impacts on network capacity, and our proposed COIC can effectively capture these opportunities to substantially improve network capacity.

This paper presents a method of measuring the traffic of IP multicast streaming, such as IPTV, by using IPFIX and PSAMP. The IP multicast streaming service has recently become one of the popular network services, but no IP multicast operation method has been established yet. In particular, traffic measurement of IP multicast streaming encounters two challenges: as monitoring a multicast path tree and QoS measurement. There is no method to monitor them continuously in large-scale networks. Hence, we explore measurement structure suitable for large-scale networks, and then using IPFIX and PSAMP, we propose an efficient a network-level quality measurement method for IPTV and a method to extract multicast path tree data. In addition, we demonstrate the feasibility of the measurement method by evaluating a prototype system.

In a shared medium communication system, mobile users contend for channel access according to a given set of rules to avoid collisions and achieve efficient use of the medium. If one or more users do not comply with the agree rules either due to selfish or malicious behaviours, they will cause some impacts on the system performance, especially to the well-behaved users. In this paper, we consider the problem of user misbehaviours on the performance of a wireless infrastructure-based network using reservation-based MAC protocols. Key misbehaving strategies possible in such a network are identified and explained. To quantify the impact of these misbehaviours upon the network performance, three different misbehaving scenarios are developed to allow a systematic investigation of each misbehaving strategy. For each scenario, we have derived mathematical formulations for evaluating and analyzing the key performance metrics, i.e., probabilities of success of well-behaved and misbehaved users and the fairness index. Numerical results show that the presence of misbehaviours can cause different levels of damage depending on the misbehavior strategy used. The combined multi-token and increasing permission probability strategies where the misbehaved user selfishly accesses the channel more times and with higher probabilities than allowed is shown to cause the most severe impairment of performance and fairness.

For real-time services, such as VoIP and videoconferencing supplied through a multi-domain MPLS network, it is vital to guarantee end-to-end QoS of the inter-domain paths. Thus, it is important to allocate an appropriate QoS class to the inter-domain paths in each transit domain. Because each domain has its own policy for QoS class allocation, each domain must then allocate an appropriate QoS class adaptively based on the estimation of the QoS class allocation policies adopted in other domains. This paper proposes an adaptive method for acquiring a QoS class allocation policy through the use of reinforcement learning. This method learns the appropriate policy through experience in the actual QoS class allocation process. Thus, the method can adapt to a complex environment where the arrival of inter-domain path requests does not follow a simple Poisson process and where the various QoS class allocation policies are adopted in other domains. The proposed method updates the allocation policy whenever a QoS class is actually allocated to an inter-domain path. Moreover, some of the allocation policies often utilized in the real operational environment can be updated and refined more frequently. For these reasons, the proposed method is designed to adapt rapidly to variances in the surrounding environment. Simulation results verify that the proposed method can quickly adapt to variations in the arrival process of inter-domain path requests and the QoS class allocation policies in other domains.

A price-based spectrum investment and pricing scheme in cooperative cognitive radio networks is presented to use wireless resource more efficiently in technical and economic aspects. We analyze the impact of cooperative communications and the relationship between spectrum hole cost and leasing cost in the optimal decision of SAP.

In this paper, the optimal control problem of a probabilistic Boolean network (PBN), which is one of the significant models in gene regulatory networks, is discussed. In the existing methods of optimal control for PBNs, it is necessary to compute state transition diagrams with 2n nodes for a given PBN with n states. To avoid this computation, a polynomial optimization approach is proposed. In the proposed method, a PBN is transformed into a polynomial system, and the optimal control problem is reduced to a polynomial optimization problem. Since state transition diagrams are not computed, the proposed method is convenient for users.

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.

Heterogeneous resources such as configurable logic blocks (CLBs), multiplier blocks (MULs) and RAM blocks (RAMs) where millions of logic gates are included have been added to field programmable gate arrays (FPGAs). The fixed-outline floorplanning used by the existing methods always has a big penalty item in the objective function to ensure all the modules are placed in the specified chip region, which maybe greatly degrade the wirelength. This paper presents a three-phase floorplanning method for heterogeneous FPGAs. First, a non-slicing free-outline floorplanning method is used to optimize the wirelength, however, in this phase, the satisfaction of resource requirements from functional modules might fail. Second, a min-cost-max-flow algorithm is used to tune the assignment of CLBs to functional modules, and assign contiguous regions to each module so that all the functional modules satisfy CLB requirements. Finally, the MULs and RAMs are allocated to modules by a network flow model. CLBs hold the maximum quantity among all the resources. Therefore, making a high utilization of them means an enhancement of the FPGA densities. The proposed method can improve the utilization of CLBs, hence, much larger circuits could be mapped to the same FPGA chip. The results show that about 7–85% wirelength reduction is obtained, and CLB utilization is improved by about 25%.