This paper introduces a novel approach of feature description by integrating the intensity order and textures in different support regions into a compact vector. We first propose the Intensity Order Local Binary Pattern (IO-LBP) operator, which simultaneously encodes the gradient and texture information in the local neighborhood of a pixel. We divide each region of interest into segments according to the order of pixel intensities, build one histogram of IO-LBP patterns for each segment, and then concatenate all histograms to obtain a feature descriptor. Furthermore, multi support regions are adopted to enhance the distinctiveness. The proposed descriptor effectively describes a region at both local and global levels, and thus high performance is expected. Experimental results on the Oxford benchmark and images of cast shadows show that our approach is invariant to common photometric and geometric transformations, such as illumination change and image rotation, and robust to complex lighting effects caused by shadows. It achieves a comparable accuracy to that of state-of-art methods while performs considerably faster.

Wireless patient monitoring is an active research area with the goal of ubiquitous health care services. This study presents a novel means of exploiting the distributed source coding (DSC) in low-complexity compression of ECG signals. We first convert the ECG data compression to an equivalent channel coding problem and exploit a linear channel code for the DSC construction. Performance is further enhanced by the use of a correlation channel that more precisely characterizes the statistical dependencies of ECG signals. Also proposed is a modified BCJR algorithm which performs symbol decoding of binary convolutional codes to better exploit the source's a priori information. Finally, a complete setup system for online ambulatory ECG monitoring via mobile cellular networks is presented. Experiments on the MIT-BIH arrhythmia database and real-time acquired ECG signals demonstrate that the proposed system outperforms other schemes in terms of encoder complexity and coding efficiency.

Maximizing network lifetime and optimizing aggregate system utility are important but usually conflict goals in wireless multi-hop networks. For the trade-off, we present a matrix game-theoretic cross-layer optimization formulation to jointly maximize the diverse objectives in such networks with network coding. To this end, we introduce a cross-layer formulation of general network utility maximization (NUM) that accommodates routing, scheduling, and stream control from different layers in the coded networks. Specifically, for the scheduling problem and then the objective function involved, we develop a matrix game with the strategy sets of the players corresponding to hyperlink and transmission mode, and design multiple payoffs specific to lifetime and system utility, respectively. In particular, with the inherit merit that matrix game can be solved with mathematical programming, our cross-layer programming formulation actually benefits from both game-based and NUM-based approaches at the same time by cooperating the programming model for the matrix game with that for the other layers in a consistent framework. Finally, our numerical experiments quantitatively exemplify the possible performance trad-offs with respect to the two variants developed on the multiple objectives in question while qualitatively exhibiting the differences between the framework and the other related works.

This study analyzes emotions established between people while interacting in face-to-face conversation. By focusing on empathy and antipathy, especially the process by which they are perceived by external observers, this paper aims to elucidate the tendency of their perception and from it develop a computational model that realizes the automatic inference of perceived empathy/antipathy. This paper makes two main contributions. First, an experiment demonstrates that an observer's perception of an interacting pair is affected by the time lags found in their actions and reactions in facial expressions and by whether their expressions are congruent or not. For example, a congruent but delayed reaction is unlikely to be perceived as empathy. Based on our findings, we propose a probabilistic model that relates the perceived empathy/antipathy of external observers to the actions and reactions of conversation participants. An experiment is conducted on ten conversations performed by 16 women in which the perceptions of nine external observers are gathered. The results demonstrate that timing cues are useful in improving the inference performance, especially for perceived antipathy.

Because dielectrics between active layers have low thermal conductivities, there is a demand to reduce the temperature increase in three-dimensional integrated circuits (3D ICs). This paper demonstrates that, in the design of 3D ICs, different layer assignments often lead to different temperature increases. Based on this observation, we are motivated to perform temperature-aware layer assignment. Our work includes two parts. Firstly, an integer linear programming (ILP) approach that guarantees a minimum temperature increase is proposed. Secondly, a polynomial-time heuristic algorithm that reduces the temperature increase is proposed. Compared with the previous work, which does not take the temperature increase into account, the experimental results show that both our ILP approach and our heuristic algorithm produce a significant reduction in the temperature increase with a very small area overhead.

This paper presents our project of designing EdgeWrite text entry methods for Japanese language. We are developing a version of EdgeWrite text entry method for Japanese language: Katakana EdgeWrite. Katakana EdgeWrite specifies the line stroke directions and writing order of the Japanese Katakana character. The ideal corner sequence pattern of EdgeWrite for each Katakana character is designed based on its line stroke directions and writing order.

In this paper, we propose a new matting algorithm using local and nonlocal neighbors. We assume that K nearest neighbors satisfy the color line model that RGB distribution of the neighbors is roughly linear and combine this assumption with the local color line model that RGB distribution of local neighbors is roughly linear. Our assumptions are appropriate for various regions such as those that are smooth, contain holes or have complex color. Experimental results show that the proposed method outperforms previous propagation-based matting methods. Further, it is competitive with sampling-based matting methods that require complex sampling or learning methods.

By exploiting the inherent sparsity of wireless propagation channels, the theory of compressive sensing (CS) provides us with novel technologies to estimate the channel state information (CSI) that require considerably fewer samples than traditional pilot-aided estimation methods. In this paper, we describe the block-sparse structure of the fast time-varying channel and apply the model-based CS (MCS) for channel estimation in orthogonal frequency division multiplexing (OFDM) systems. By exploiting the structured sparsity, the proposed MCS-based method can further compress the channel information, thereby allowing a more efficient and precise estimation of the CSI compared with conventional CS-based approaches. Furthermore, a specific pilot arrangement is tailored for the proposed estimation scheme. This so-called random grouped pilot pattern can not only effectively protect the measurements from the inter-carrier interference (ICI) caused by Doppler spreading but can also enable the measurement matrix to meet the conditions required for MCS with relatively high probability. Simulation results demonstrate that our method has good performance at high Doppler frequencies.

This paper proposes the assignment of resource blocks (RBs) to reduce the peak-to-average power ratio (PAPR) of orthogonal frequency division multiplexing (OFDM) in a multi-user OFDM system. This system ranks the users according to the channel state information (CSI) for RB assignment. In our proposed technique, an RB is assigned to either the first- or second-ranked mobile station (MS) to minimize the PAPR of the OFDM signal. While this process reduces the PAPR, the throughput is also reduced because of the user diversity gain loss. A PAPR-throughput tradeoff is then established. Theoretical analyses and computer simulations confirm that when the number of MSs becomes large, the PAPR-throughput tradeoff is eased because of the minimal effect of the diversity gain loss. Therefore, significant PAPR reduction is achieved with only a slight degradation in the throughput.

Metaheuristic methods have been studied for combinational optimization problems for some time. Recently, a Consultant-Guided Search (CGS) has been proposed as a metaheuristic method for the Traveling Salesperson Problem (TSP). This approach is an algorithm in which a virtual person called a client creates a solution based on consultation with a virtual person called a consultant. In this research, we propose a parallel algorithm which uses the Ant Colony System (ACS) to create a solution with a consultant in a Consultant-Guided Search, and calculate an approximation solution for the TSP. Finally, we execute a computer experiment using the benchmark problems (TSPLIB). Our algorithm provides a solution with less than 2% error rate for problem instances using less than 2000 cities.

The dynamic characteristics of the class E power amplifier with frequency modulation are derived. Such an analysis is essential for designing amplitude and frequency modulated amplifier systems such as an EER scheme. Conventionally, an analytical expression for the frequency response of a frequency modulated class E amplifier has not been derived yet. This omission is rectified here by modeling the circuit with both a low-frequency model and a high-frequency model. Further, a time domain waveform is derived from the frequency domain transfer function for some typical time varying drive signals. The analytical results for the frequency response of a 1-MHz class E amplifier are shown to match PSpice simulations and measured values well.

Graph matching is to find an independent edge set in a graph. It can be used for various purposes such as finding a cover in a graph, chemical structural computations, multi-level graph partitioning and so on. When a graph is too large to be handled by a single machine, we should use multiple machines. In this paper, we use Pregel, a cloud graph processing architecture which is able to process massive scale graph data in scalable and fault-tolerant ways. We propose a parallel maximal matching algorithm described in the Pregel's vertex-centric BSP model. We test our algorithm on an 8 node cluster and the results show that our algorithm can realize high quality matching for a large graph in a short time. Also, our algorithm is linearly scalable with the number of machines.

To implement a wideband bandpass filter with improved skirt-selectivity and out-band characteristics, a new parallel-coupled three-line unit with two short-circuited stubs symmetrically-loaded at the center line is proposed. Unlike most traditional ones, the passband of the proposed parallel-coupled three-line structure is based on the cross-coupling between non-adjacent lines rather than the direct-coupling between adjacent ones, whereas a pair of attenuation poles is found in the stopbands. After revealing its work mechanism, an efficient filter-design-scheme is correspondingly proposed for the presented structure. Firstly, based on a chebyshev-filter synthesis theory, a wideband passband filter consisting of a parallel-coupled two-line and two short-circuited stubs loaded at the input- and output- ports is designed. Furthermore, by putting a properly-designed 3/4-wavelength stepped-impedance resonator (SIR) in between the parallel-coupled two lines, two attenuation poles are then realized at the frequencies very close to the cutoff ones. Accordingly, the roll-off characteristics of the filter are significantly-improved to greater than 100,dB/GHz. Furthermore, two-section open-ended stubs are used to replace the short-circuited ones to realize a pair of extra attenuation poles in stopbands. To validate the proposed techniques, a wideband filter with a bandwidth of 3--5,GHz (Fractional bandwidth (FBW) $= (5,GHz-3,GHz)/4,GHz =50%)$ was designed, simulated, fabricated and measured. The measured responses of the filter agree well with the simulation and theoretical ones, which validates the effectiveness of the newly-proposed three-line unit and the corresponding design scheme.

Recent progress in research on the finite element method (FEM) for optical waveguide design and analysis is reviewed, focusing on the author's works. After briefly reviewing fundamentals of FEM such as a theoretical framework, a conventional nodal element, a newly developed edge element to eliminate nonphysical, spurious solutions, and a perfectly matched layer to avoid undesirable reflections from computational window edges, various FEM techniques for a guided-mode analysis, a beam propagation analysis, and a waveguide discontinuity analysis are described. Some design examples are introduced, including current research activities on multi-core fibers.

Coalition Structure Generation (CSG) is a main research issue in the domain of coalition games. A majority of existing works assume that the value of a coalition is independent of others in the coalition structure. Recently, there has been interest in a more realistic settings, where the value of a coalition is affected by the formation of other coalitions. This effect is known as externality. The focus of this paper is to make use of Maximum Satisfiability (MaxSAT) to solve the CSG problem where externalities may exist. In order to reduce the exponentially growing number of possible solutions in the CSG problem, we follow the previous works by representing the CSG problem as sets of rules in MC-nets (without externalities) and embedded MC-nets (with externalities). Specifically, enlightened by the previous MC-net-based algorithms exploiting the constraints among rule relations to solve the CSG problem, we encode such constraints into weighted partial MaxSAT (WPM) formulas. Experimental results demonstrate that an off-the-shelf MaxSAT solver achieves significant improvements compared to the previous algorithm for the same set of problem instances.

Blur distortion is a common artifact in image communication and affects the perceived sharpness of a digital image. In this paper, we capitalize on the mathematical knowledge of Gaussian convolution and propose a strategy to minimally reblur test images. From the reblur algorithm, synthetic reblur images are created. We propose a new blind blur metric which makes use of the reblur images to produce blur scores. Compared to other no-reference blur assessments, the proposed method has the advantages of fast computation and training-free operation. Experiment results also show that the proposed method can produce blur scores which are highly correlated with human perception of blurriness.

An optoelectronic 32-bit serial-to-parallel converter with a novel conversion scheme and shared-trigger configuration has been developed for the label processing of 100-Gbps (25-Gbps $ imes 4 lambda)$ optical packets. No external optical trigger source is required to operate the converter, as the optical packet itself is used to perform self-triggering. Compared to prior optoelectronic label converters, the new device has a much higher gain even while converting labels at higher data rates, and exhibits tolerance to the voltage swing of received packets. The device response is presented together with the experimental demonstration of serial-to-parallel conversion for 4 different labels at 25 Gbps.

Performance suveyrance of CPML (Convolutional PML) for FDTD (Finite-Difference Time-Domain) method in cylindrical coordinate system was carried out. The CPML was placed perpendicularly to the radial axis and designed to absorb diverging or converging waves. To be able to analyze microstructured optical fibers and disk/ring resonators we introduced finite axial wavenumbers into the FDTD formulation. We investigated the dependence of reflectivity upon CPML's constituteve parameters such as $kappa$ and $sigma$ for various curvature radii and the axial wavenumbers. As a result of evaluation we found that the reflectivity gradually increased togather with the increase of the wavenumber. We also confirmed that the absorption performance was of the similar order for the converging waves and the diverging ones provided that their curvature radii were the same.

In this paper, the function expansion based topology optimization is employed to the automatic optimization of the waveguide dispersion property, and the optimum design of low-dispersion slow-light photonic crystal waveguides is demonstrated. In order to realize low-dispersion and large group index, an objective function to be optimized is expressed by the weighted sum of the objective functions for the desired group index and the low-dispersion property, and weighting coefficients are updated through the optimization process.

In this letter, a new sparse locality preserving projection (SLPP) algorithm is developed and applied to facial expression recognition. In comparison with the original locality preserving projection (LPP) algorithm, the presented SLPP algorithm is able to simultaneously find the intrinsic manifold of facial feature vectors and deal with facial feature selection. This is realized by the use of l1-norm regularization in the LPP objective function, which is directly formulated as a least squares regression pattern. We use two real facial expression databases (JAFFE and Ekman's POFA) to testify the proposed SLPP method and certain experiments show that the proposed SLPP approach respectively gains 77.60% and 82.29% on JAFFE and POFA database.