Arc discharge at 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 holder temperature on the bridge and arc-duration, opening-waveforms at slowly separating silver-tin dioxide contact with different holder temperature are measured and discussed experimentally in this paper. Firstly, as opening-waveforms, the contact voltage, the contact current and the movement of moving contact related to the gap length are measured simultaneously. Secondly, the relationship between temperature of the holder and duration of the arc was quantified experimentally. It was revealed that as the initial temperature of the holder becomes higher, arc-duration becomes slightly longer. More importantly, the holder temperature dependencies of percentage of each-phase (metallic and gaseous-phases) are different with different closed-current.

This paper proposes the synchronization control method for two different unified chaotic systems with unknown mismatched parameters using sum of squares method. Previously, feedback-linearizing and stabilization terms were used in the controller for the synchronization problem. However, they used just a constant matrix as a stabilization control gain, whose performance is shown to be valid only for a linear model. Thus, we propose the novel control method for the synchronization of the two different unified chaotic systems with unknown mismatched parameters via sum of squares method. We design the stabilization control input which is of the polynomial form by sum of squares method and also the adaptive law for the estimation of the unknown mismatched parameter between the master and slave systems. Since we can use the polynomial control input which is dependent on the system states as the stabilization controller, the proposed method can have better performance than the previous methods. Numerical simulations for both uni-directional and bi-directional chaotic systems show the validity and advantage of the proposed method.

Chip multiprocessors (CMPs) improve performance by simultaneously executing multiple threads using integrated multiple cores. However, since these cores commonly share one cache, inter-thread cache conflicts often limit the performance improvement by multi-threading. This paper focuses on two causes of inter-thread cache conflicts. In shared caches of CMPs, cached data fetched by one thread are frequently evicted by another thread. Such an eviction, called inter-thread kickout (ITKO), is one of the major causes of inter-thread cache conflicts. The other cause is capacity shortage that occurs when one cache is shared by threads demanding large cache capacities. If the total capacity demanded by the threads exceeds the actual cache capacity, the threads compete to use the limited cache capacity, resulting in capacity shortage. To address inter-thread cache conflicts, we must take into account both ITKOs and capacity shortage. Therefore, this paper proposes a capacity-aware thread scheduling method combined with cache partitioning. In the proposed method, inter-thread cache conflicts due to ITKOs and capacity shortage are decreased by cache partitioning and thread scheduling, respectively. The proposed scheduling method estimates the capacity demand of each thread with an estimation method used in the cache partitioning mechanism. Based on the estimation used for cache partitioning, the thread scheduler decides thread combinations sharing one cache so as to avoid capacity shortage. Evaluation results suggest that the proposed method can improve overall performance by up to 8.1%, and the performance of individual threads by up to 12%. The results also show that both cache partitioning and thread scheduling are indispensable to avoid both ITKOs and capacity shortage simultaneously. Accordingly, the proposed method can significantly reduce the inter-thread cache conflicts and hence improve performance.

In the image classification applications, the test sample with multiple man-handcrafted descriptions can be sparsely represented by a few training subjects. Our paper is motivated by the success of multi-task joint sparse representation (MTJSR), and considers that the different modalities of features not only have the constraint of joint sparsity across different tasks, but also have the constraint of local manifold structure across different features. We introduce the constraint of local manifold structure into the MTJSR framework, and propose the Locality-constrained multi-task joint sparse representation method (LC-MTJSR). During the optimization of the formulated objective, the stochastic gradient descent method is used to guarantee fast convergence rate, which is essential for large-scale image categorization. Experiments on several challenging object classification datasets show that our proposed algorithm is better than the MTJSR, and is competitive with the state-of-the-art multiple kernel learning methods.

This paper introduces a radio frequency identification (RFID) tag for urination detection. The proposed tag is embedded into paper diapers in order to detect the patient's urination immediately. For this tag, we designed an RFID tag antenna at 950MHz, which matches the impedance of the associated integrated circuit (IC) chip. In addition, we calculate the antenna characteristics and measure the reflection coefficient (S11) and radiation pattern of the antenna. The results show that this system can be used to detect urination.

Regular on-site testing is an elementary means to obtain real-time data and state of Electromagnetic Compatibility (EMC) of electronics systems. Nowadays, there is a lot of measured EMC data while the application of the data is insufficient. So we put forward the concept of EMC model synthesis. To carry out EMC data mining with measured electromagnetic data, we can build or modify models and synthesize variation rules of electromagnetic parameters of equipment and EMC performance of systems and platforms, then realize the information synthesis and state prediction. The concept of EMC reliability is brought forward together with the definition and description of parameters such as invalidation rate and EMC lifetime. We studied the application of statistical algorithms and Artificial Neural Network (ANN) in model synthesis. Operating flows and simulation results as well as measured data are presented. Relative research can support special measurement, active management and predictive maintenance and replenishment in the area of EMC.

In this letter, we propose a partial impedance-matching method using a two-strip resonator for noncontact Passive Intermodulation (PIM) measurements using a coaxial tube. It is shown that the strip closer to the inner tube of the coaxial tube is dominant in the observed PIM characteristics while both strips are excited equally. The ideal efficiency of power to each strip is 50%, which is a significant improvement in comparison with conventional methods.

Natural language (NL) requirements are usually human-centric and therefore error-prone and inaccurate. In order to improve the 3Cs of natural language requirements, namely Consistency, Correctness and Completeness, in this paper we propose a systematic pattern matching approach supporting both NL requirements modeling and inconsistency, incorrectness and incompleteness analysis among requirements. We first use business process modeling language to model NL requirements and then develop a formal language — Workflow Patterns-based Process Language (WPPL) — to formalize NL requirements. We leverage workflow patterns to perform two-level 3Cs checking on the formal representation based on a coherent set of checking rules. Our approach is illustrated through a real world financial service example — Global Equity Trading System (GETS).

A method to estimate sound source orientation in a reverberant room using a microphone array is proposed. We extend the conventional modeling of a room transfer function based on the image method in order to take into account the directivity of a sound source. With this extension, a transfer function between a sound source and a listener (or a microphone) is described by the superposition of transfer functions from each image source to the listener multiplied by the source directivity; thus, the sound source orientation can be estimated by analyzing how the image sources are distributed (power distribution of image sources) from observed signals. We applied eigenvalue analysis to the spatial correlation matrix of the microphone array observation to obtain the power distribution of image sources. Bsed on the assumption that the spatial correlation matrix for each set of source position and orientation is known a priori, the variation of the eigenspace can be modeled. By comparing the eigenspace of observed signals and that of pre-learned models, we estimated the sound source orientation. Through experiments using seven microphones, the sound source orientation was estimated with high accuracy by increasing the reverberation time of a room.

Orthogonal arrays have important applications in statistics and computer science, as well as in coding theory. In this letter, a new construction method of symmetric orthogonal arrays of strength t is proposed, which is a concatenation of two orthogonal partitions according to a latin square. As far as we know, this is a new construction of symmetric orthogonal arrays of strength t, where t is a given integer. Based on the different latin squares, we also study the enumeration problem of orthogonal partitions, and a lower bound on the count of orthogonal partitions is derived.

Design equations for satisfying off-nominal operating conditions of the class E amplifier with a nonlinear shunt capacitance for a grading coefficient of 0.5 and the duty cycle D=0.5 are derived. By exploiting the off-nominal class E operation, various amplifier parameters such as input voltage, operating frequency, output power, and load resistance can be set as design specifications. As a result of the analysis in this paper, the following extension of the usability of the class E amplifier was achieved. With rising up the dc supply voltage, the shunt capacitance which achieves the off-nominal operation can be increased. This means that a transistor with higher output capacitance can be used for ZVS operation. This also means that maximum operating frequency which achieves ZVS can be increased. An example of a design procedure of the class E amplifier is given. The theoretical results were verified with an experiment.

This paper proposes T-CROM (Time-delayed Collaborative ROuting and MAC) protocol, that allows collaboration between network and MAC layers in order to extend the lifetime of MANETs in a resources-limited environment. T-CROM increases the probability of preventing energy-poor nodes from joining routes by using a time delay function that is inversely proportional to the residual battery capacity of intermediate nodes, making a delay in the route request (RREQ) packets transmission. The route along which the first-arrived RREQ packet traveled has the smallest time delay, and thus the destination node identifies the route with the maximum residual battery capacity. This protocol leads to a high probability of avoiding energy-poor nodes and promotes energy-rich nodes to join routes in the route establishment phase. In addition, T-CROM controls the congestion between neighbors and reduces the energy dissipation by providing an energy-efficient backoff time by considering both the residual battery capacity of the host itself and the total number of neighbor nodes. The energy-rich node with few neighbors has a short backoff time, and the energy-poor node with many neighbors gets assigned a large backoff time. Thus, T-CROM controls the channel access priority of each node in order to prohibit the energy-poor nodes from contending with the energy-rich nodes. T-CROM fairly distributes the energy consumption of each node, and thus extends the network lifetime collaboratively. Simulation results show that T-CROM reduces the number of total collisions, extends the network lifetime, decreases the energy consumption, and increases the packet delivery ratio, compared with AOMDV with IEEE 802.11 DCF and BLAM, a battery-aware energy efficient MAC protocol.

Information security has been seriously threatened by the differential power analysis (DPA). Delay-based dual-rail precharge logic (DDPL) is an effective solution to resist these attacks. However, conventional DDPL convertors have some shortcomings. In this paper, we propose improved convertor pairs based on dynamic logic and a sense amplifier (SA). Compared with the reference CMOS-to-DDPL convertor, our scheme could save 69% power consumption. As to the comparison of DDPL-to-CMOS convertor, the speed and power performances could be improved by 39% and 54%, respectively.

This paper presents a novel data compression method for testing integrated circuits within the framework of pattern run-length coding. The test set is firstly divided into 2n-length patterns where n is a natural number. Then the compatibility of each pattern, which can be an external type, or an internal type, is analyzed. At last, the codeword of each pattern is generated according to its analysis result. Experimental results for large ISCAS89 benchmarks show that the proposed method can obtain a higher compression ratio than existing ones.

This paper proposes an enhancement to a previously reported adaptive peak-to-average power ratio (PAPR) reduction method based on clipping and filtering (CF) for eigenmode multiple-input multiple-output (MIMO) — orthogonal frequency division multiplexing (OFDM) signals. We enhance the method to accommodate the case with adaptive modulation and channel coding (AMC). Since the PAPR reduction process degrades the signal-to-interference and noise power ratio (SINR), the AMC should take into account this degradation before PAPR reduction to select accurately the modulation scheme and coding rate (MCS) for each spatial stream. We use the lookup table-based prediction of SINR after PAPR reduction, in which the interference caused by the PAPR reduction is obtained as a function of the stream index, frequency block index, clipping threshold for PAPR reduction, and input backoff (IBO) of the power amplifier. Simulation results show that the proposed PAPR reduction method increases the average throughput compared to the conventional CF method for a given adjacent channel leakage power ratio (ACLR) when we assume practical AMC.

We propose a low-overhead fault-secure parallel prefix adder. We duplicate carry bits for checking purposes. Only one half of normal carry bits are compared with the corresponding redundant carry bits, and the hardware overhead of the adder is low. For concurrent error detection, we also predict the parity of the result. The adder uses parity-based error detection and it has high compatibility with systems that have parity-based error detection. We can implement various fault-secure parallel prefix adders such as Sklansky adder, Brent-Kung adder, Han-Carlson adder, and Kogge-Stone adder. The area overhead of the proposed adder is about 15% lower than that of a previously proposed adder that compares all the carry bits.

Hyperthermia is one of the modalities for cancer treatment, utilizing the difference of thermal sensitivity between tumor and normal tissue. Interstitial microwave hyperthermia is one of the heating schemes and it is applied to a localized tumor. In the treatments, heating pattern control around antennas are important, especially for the treatment in and around critical organs. This paper introduces a coaxial-dipole antenna, which is one of the thin microwave antennas and can generate a controllable heating pattern. Moreover, generations of an arbitrary shape heating patterns by an array applicator composed of four coaxial-dipole antennas are described.

Based on sample-pair refinement and local optimization, this paper proposes a high-accuracy and quick matting algorithm. First, in order to gather foreground/background samples effectively, we shoot rays in hybrid (gradient and uniform) directions. This strategy utilizes the prior knowledge to adjust the directions for effective searching. Second, we refine sample-pairs of pixels by taking into account neighbors'. Both high confidence sample-pairs and usable foreground/background components are utilized and thus more accurate and smoother matting results are achieved. Third, to reduce the computational cost of sample-pair selection in coarse matting, this paper proposes an adaptive sample clustering approach. Most redundant samples are eliminated adaptively, where the computational cost decreases significantly. Finally, we convert fine matting into a de-noising problem, which is optimized by minimizing the observation and state errors iteratively and locally. This leads to less space and time complexity compared with global optimization. Experiments demonstrate that we outperform other state-of-the-art methods in local matting both on accuracy and efficiency.

The Log-structured File System (LFS) transforms random writes to a huge sequential one to provide superior write performance on storage devices. However, LFS inherently suffers from overhead incurred by cleaning segments. Specifically, when file system utilization is high and the system is busy, write performance of LFS degenerates significantly due to high cleaning cost. Also, in the newer flash memory based SSD storage devices, cleaning leads to reduced SSD lifetime as it incurs more writes. In this paper, we propose an enhancement to the original LFS to alleviate the performance degeneration due to cleaning when the system is busy. The new scheme, which we call Slack Space Recycling (SSR), allows LFS to delay on-demand cleaning during busy hours such that cleaning may be done when the load is much lighter. Specifically, it writes modified data directly to invalid areas (slack space) of used segments instead of cleaning on-demand, pushing back cleaning for later. SSR also has the added benefit of increasing the lifetime of the now popular SSD storage devices. We implement the new SSR-LFS file system in Linux and perform a large set of experiments. The results of these experiments show that the SSR scheme significantly improves performance of LFS for a wide range of storage utilization settings and that the lifetime of SSDs is extended considerably.

In this paper, we propose a hybrid fuzzy geometric active contour method, which embeds the spatial fuzzy clustering into the evolution of geometric active contour. In every iteration, the evolving curve works as a spatial constraint on the fuzzy clustering, and the clustering result is utilized to construct the fuzzy region force. On one hand, the fuzzy region force provides a powerful capability to avoid the leakages at weak boundaries and enhances the robustness to various noises. On the other hand, the local information obtained from the gradient feature map contributes to locating the object boundaries accurately and improves the performance on the images with heterogeneous foreground or background. Experimental results on synthetic and real images have shown that our model can precisely extract object boundaries and perform better than the existing representative hybrid active contour approaches.