The goal of dimension reduction is to represent high-dimensional data in a lower-dimensional subspace, while intrinsic properties of the original data are kept as much as possible. An important challenge in unsupervised dimension reduction is the choice of tuning parameters, because no supervised information is available and thus parameter selection tends to be subjective and heuristic. In this paper, we propose an information-theoretic approach to unsupervised dimension reduction that allows objective tuning parameter selection. We employ quadratic mutual information (QMI) as our information measure, which is known to be less sensitive to outliers than ordinary mutual information, and QMI is estimated analytically by a least-squares method in a computationally efficient way. Then, we provide an eigenvector-based efficient implementation for performing unsupervised dimension reduction based on the QMI estimator. The usefulness of the proposed method is demonstrated through experiments.

Much attention has recently been paid to direction of arrival (DOA) estimation using compressed sensing (CS) techniques, which are sparse signal reconstruction methods. In our previous study, we developed a method for estimating the DOAs of multi-band signals that uses CS processing and that is based on the assumption that incident signals have the same complex amplitudes in all the bands. That method has a higher probability of correct estimation than a single-band DOA estimation method using CS. In this paper, we propose novel DOA estimation methods for multi-band signals with frequency characteristics using the Khatri-Rao product. First, we formulate a method that can estimate DOAs of multi-band signals whose phases alone have frequency dependence. Second, we extend the scheme in such a way that we can estimate DOAs of multi-band signals whose amplitudes and phases both depend on frequency. Finally, we evaluate the performance of the proposed methods through computer simulations and reveal the improvement in estimation performance.

Two types of 3D folded dipole antenna with feed line (FDAFL) were reported for a small terminal, which covered WiMAX 2.5/3.5GHz bands and WLAN 2.4GHz band. In this study, folded monopole antenna (FMA) is proposed as a variant of FDAFL. We show the broadband characteristics of FMA and determine the most suitable configuration of FMA array for realizing MIMO system. Also, a multiband variant is created by introducing a parasitic element to FMA. The result is a multiband FMA array with parasitic elements operating at 5GHz band of WiMAX and WLAN as well as WiMAX 2.5/3.5GHz bands and WLAN 2.4GHz band with total antenna efficiency of between 70% to 96% and the envelope correlation coefficient of less than 0.02. Finally, a prototype antenna is implemented, and we confirm the validity of the simulation by comparison to measured results.

This paper focuses on the S-parameter method that is a basic method for measuring the input impedance of balanced-fed antennas. The basic concept of the method is summarized using the two-port network, and it is shown that the method can be enhanced to the unbalanced antennas using a formulation based on incident and reflected waves. The compensation method that eliminates the influence of a measurement jig and the application of the S-parameter method for the measurement of a radiation pattern with reduced unbalanced currents are explained. Further, application of the method for measuring the reflection and coupling coefficients of multiple antennas is introduced. The measured results of the input impedance of a dipole antenna, radiation patterns of a helical antenna on a small housing, and S-parameters of multiple antennas on a small housing are examined, and the measured results obtained with the S-parameter method are verified.

To study the molten bridge phenomenon of contacts at the initial breaking process, an experimental device of molten bridge between slowly opening contacts was developed. The system consists of the contact moving control module, the circuit load and the observation module. The molten bridge of copper contact under two load conditions 9,V/19,A and 9,V/7.3,A were studied. The voltage and current characteristics curves of Cu molten bridge were extracted and the resistance and the instantaneous power of the molten bridge were analyzed. The image of the Cu molten bridge diameter was captured by CCD under 9,V/19,A and the influences of the contact force and the separation speed on the molten bridge length and the crater diameter of the anode were studied. The root profile of the Cu contacts after separation was analyzed by digital microscope. Research results show that the Cu molten bridge length has the same changing trend as the diameter of the anode crater. They both decrease with the increment of the separation speed and the decrement of the contact force.

Earlier attempts to deploy two units of parametric loudspeakers have shown encouraging results in improving the accuracy of spatial audio reproductions. As compared to a pair of conventional loudspeakers, this improvement is mainly a result of being free of crosstalk due to the sharp directivity of the parametric loudspeaker. By replacing the normal parametric loudspeaker with the steerable parametric loudspeaker, a flexible sweet spot can be created that tolerates head movements of the listener. However, spatial aliasing effects of the primary frequency waves are always observed in the steerable parametric loudspeaker. We are motivated to make use of the spatial aliasing effects to create two sound beams from one unit of the steerable parametric loudspeaker. Hence, a reduction of power consumption and physical size can be achieved by cutting down the number of loudspeakers used in an audio system. By introducing a new parameter, namely the relative steering angle, we propose a stereophonic beamsteering method that can control the amplitude difference corresponding to the interaural level difference (ILD) between two sound beams. Currently, this proposed method does not support the reproduction of interaural time differences (ITD).

Local descriptors, Local Binary Pattern (LBP) and Scale Invariant Feature Transform (SIFT) are widely used in various computer applications. They emphasize different aspects of image contents. In this letter, we propose to combine them in sparse coding for categorizing scene images. First, we regularly extract LBP and SIFT features from training images. Then, corresponding to each feature, a visual word codebook is constructed. The obtained LBP and SIFT codebooks are used to create a two-dimensional table, in which each entry corresponds to an LBP visual word and a SIFT visual word. Given an input image, LBP and SIFT features extracted from the same positions of this image are encoded together based on sparse coding. After that, spatial max pooling is adopted to determine the image representation. Obtained image representations are converted into one-dimensional features and classified by utilizing SVM classifiers. Finally, we conduct extensive experiments on datasets of Scene Categories 8 and MIT 67 Indoor Scene to evaluate the proposed method. Obtained results demonstrate that combining features in the proposed manner is effective for scene categorization.

Since electromagnetic (EM) noise resulting from an arc discharge disturbs other electric devices, parameters on electromagnetic compatibility, as well as lifetime and reliability, are important properties for electrical contacts. To clarify the characteristics and the mechanism of the generation of the EM noise, the arc column and voltage fluctuations generated by slowly breaking contacts with external direct current (DC) magnetic field, up to 20,mT, was investigated experimentally using Ag$_{90.7{ m wt%}}$SnO$_{2,9.3{ m wt}%}$ material. Firstly the motion of the arc column is measured by high-speed camera. Secondary, the distribution of the motion of the arc and contact voltage are discussed. It was revealed that the contact voltage fluctuation in the arc duration is related to the arc column motion.

This paper describes a soft-error tolerant and margin-enhanced nMOS-pMOS reversed 6T SRAM cell. The 6T SRAM bitcell comprises pMOS access and driver transistors, and nMOS load transistors. Therefore, the nMOS and pMOS masks are reversed in comparison with those of a conventional bitcell. In scaled process technology, The pMOS transistors present advantages of small random dopant fluctuation, strain-enhanced saturation current, and small soft-error sensitivity. The four-pMOS and two-nMOS structure improves the soft-error rate plus operating margin. We conduct SPICE and neutron-induced soft-error simulations to evaluate the n-p reversed 6T SRAM bitcell in 130-nm to 22-nm processes. At the 22-nm node, a multiple-cell-upset and single-bit-upset SERs are improved by 34% and 51% over a conventional 6T cell. Additionally, the static noise margin and read cell current are 2.04× and 2.81× improved by leveraging the pMOS benefits.

When ultra-high-frequency (UHF) method is applied in partial discharge (PD) detection for GIS, the propagation process and rules of electromagnetic (EM) wave need to be understood clearly for conducting diagnosis and assessment about the real insulation status. The preceding researches are mainly concerning about the radial component of the UHF signal, but the propagation of the signal components in axial and radial directions and that perpendicular to the radial direction of the GIS tank are rarely considered. So in this paper, for a 252,kV GIS with T-shaped structure (TS), the propagation and attenuation of PD-induced EM wave in different circumferential angles and directions are investigated profoundly in time and frequency domain based on Finite Difference Time Domain (FDTD) method. The attenuation rules of the peak to peak value (Vpp) and cumulative energy are concluded. By comparing the results of straight branch and T branch, the influence of T-shaped structure over the propagation of different signal components are summarized. Moreover, the new circumferential and axial location methods proposed in the previous work are verified to be still applicable. This paper discusses the propagation mechanism of UHF signal in T-shaped tank, which provides some referential significance towards the utilization of UHF technique and better implementation of PD detection.

In this paper, we propose a novel approach for multiple-shot people re-identification. Due to high variance in camera view, light illumination, non-rigid deformation of posture and so on, there exists a crucial inter-/intra- variance issue, i.e., the same people may look considerably different, whereas different people may look extremely similar. This issue leads to an intractable, multimodal distribution of people appearance in feature space. To deal with such multimodal properties of data, we solve the re-identification problem under a local distance comparison framework, which significantly alleviates the difficulty induced by varying appearance of each individual. Furthermore, we build an energy-based loss function to measure the similarity between appearance instances, by calculating the distance between corresponding subsets in feature space. This loss function not only favors small distances that indicate high similarity between appearances of the same people, but also penalizes small distances or undesirable overlaps between subsets, which reflect high similarity between appearances of different people. In this way, effective people re-identification can be achieved in a robust manner against the inter-/intra- variance issue. The performance of our approach has been evaluated by applying it to the public benchmark datasets ETHZ and CAVIAR4REID. Experimental results show significant improvements over previous reports.

This paper presents an experimental study that analyzes how conversational agents activate human communication in thought-evoking multi-party dialogues between multi-users and multi-agents. A thought-evoking dialogue is a kind of interaction in which agents act to provoke user thinking, and it has the potential to activate multi-party interactions. This paper focuses on quiz-style multi-party dialogues between two users and two agents as an example of thought-evoking multi-party dialogues. The experimental results revealed that the presence of a peer agent significantly improved user satisfaction and increased the number of user utterances in quiz-style multi-party dialogues. We also found that agents' empathic expressions significantly improved user satisfaction, improved user ratings of the peer agent, and increased the number of user utterances. Our findings should be useful for activating multi-party communications in various applications such as pedagogical agents and community facilitators.

Complex-valued Hopfield associative memory (CHAM) is one of the most promising neural network models to deal with multilevel information. CHAM has an inherent property of rotational invariance. Rotational invariance is a factor that reduces a network's robustness to noise, which is a critical problem. Here, we proposed complex-valued bipartite auto-associative memory (CBAAM) to solve this reduction in noise robustness. CBAAM consists of two layers, a visible complex-valued layer and an invisible real-valued layer. The invisible real-valued layer prevents rotational invariance and the resulting reduction in noise robustness. In addition, CBAAM has high parallelism, unlike CHAM. By computer simulations, we show that CBAAM is superior to CHAM in noise robustness. The noise robustness of CHAM decreased as the resolution factor increased. On the other hand, CBAAM provided high noise robustness independent of the resolution factor.

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.

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.

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 a so called quasi-linear support vector machine (SVM), which is an SVM with a composite quasi-linear kernel. In the quasi-linear SVM model, the nonlinear separation hyperplane is approximated by multiple local linear models with interpolation. Instead of building multiple local SVM models separately, the quasi-linear SVM realizes the multi local linear model approach in the kernel level. That is, it is built exactly in the same way as a single SVM model, by composing a quasi-linear kernel. A guided partitioning method is proposed to obtain the local partitions for the composition of quasi-linear kernel function. Experiment results on artificial data and benchmark datasets show that the proposed method is effective and improves classification performances.

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.

Coalition Structure Generation (CSG) means partitioning agents into exhaustive and disjoint coalitions so that the sum of values of all the coalitions is maximized. Solving this problem could be facilitated by employing some compact representation schemes, such as marginal contribution network (MC-net). In MC-net, the CSG problem is represented by a set of rules where each rule is associated with a real-valued weights, and the goal is to maximize the sum of weights of rules under some constraints. This naturally leads to a combinatorial optimization problem that could be solved with weighted partial MaxSAT (WPM). In general, WPM deals with only positive weights while the weights involved in a CSG problem could be either positive or negative. With this in mind, in this paper, we propose an extension of WPM to handle negative weights and take advantage of the extended WPM to solve the MC-net-based CSG problem. Specifically, we encode the relations between each pair of agents and reform the MC-net as a set of Boolean formulas. Thus, the CSG problem is encoded as an optimization problem for WPM solvers. Furthermore, we apply this agent relation-based WPM with minor revision to solve the extended CSG problem where the value of a coalition is affected by the formation of other coalitions, a coalition known as externality. Experiments demonstrate that, compared to the previous encoding, our proposed method speeds up the process of solving the CSG problem significantly, as it generates fewer number of Boolean variables and clauses that need to be examined by WPM solver.

Electromagnetic field analysis is a time-consuming process, and a method involving the use of an FPGA accelerator is one of the attractive ways to accelerate the analysis; the other method involve the use of CPU and GPU. In this paper, we propose an FPGA accelerator dedicated for a two-dimensional finite-difference time-domain (FDTD) method. This accelerator is based on a two-dimensional single instruction multiple data (SIMD) array architecture. Each processing element (PE) is composed of a six-stage pipeline that is optimized for the FDTD method. Moreover, driving signal generation and impedance termination are also implemented in the hardware. We demonstrate that our accelerator is 11 times faster than existing FPGA accelerators and 9 times faster than parallel computing on the NVIDIA Tesla C2075. As an application of the high-speed FDTD accelerator, the design optimization of a waveguide is shown.