Ag and Pd electrical contact pairs are separated at constant separating speeds (5, 10 and 20 mm/s) in a DC 42 V/8.4 A resistive circuit. The motion of the breaking arc is observed with a high-speed video camera. For Ag contacts, the motion of the breaking arc becomes stable at a certain critical gap at separating speeds of 10 mm/s and 20 mm/s, and the breaking arc moves extensively at the separating speed of 5 mm/s. For Pd contacts, the breaking arc moves extensively regardless of the separating speed. These results are attributed to the following causes. For Ag contacts, the difference in the motion of arc spots at each separating speed is changed by the difference in the total energy input to the contacts. For Pd contacts, the temperature of the contact surfaces is kept high because of the lower thermal conductivity of Pd than Ag.

This paper deals with the random number generation problem under the framework of a separate coding system for correlated memoryless sources posed and investigated by Slepian and Wolf. Two correlated data sequences with length n are separately encoded to nR1, nR2 bit messages at each location and those are sent to the information processing center where the encoder wish to generate an approximation of the sequence of independent uniformly distributed random variables with length nR3 from two received random messages. The admissible rate region is defined by the set of all the triples (R1,R2,R3) for which the approximation error goes to zero as n tends to infinity. In this paper we examine the asymptotic behavior of the approximation error inside and outside the admissible rate region. We derive an explicit lower bound of the optimal exponent for the approximation error to vanish and show that it can be attained by the universal codes. Furthermore, we derive an explicit lower bound of the optimal exponent for the approximation error to tend to 2 as n goes to infinity outside the admissible rate region.

Repacking is an efficient scheme for bandwidth packing problem (BPP) in centralized networks (CNs), where a central unit allocates bandwidth to the rounding terminals. In this paper, we study its performance by proposing a new formulation of the BPP in the CN, and introducing repacking scheme into next fit algorithm in terms of the online constraint. For the realistic applications, the effect of call demand distribution is also exploited by means of simulation. The results show that the repacking efficiency is significant (e.g. the minimal improvement about 13% over uniform distribution), especially in the scenarios where the small call demands dominate the network.

This paper examines a system which is inspected at equally spaced points in time. We express the observed states of the system as a discrete time Markov chain with an absorbing state. It is assumed that the true state is certainly identified through inspection. After each inspection, one of three actions can be taken: Operation, repair, or replacement. We assume that the result of repair is uncertain. If repair is taken, we decide whether to inspect the system or not. When inspection is performed after completion of repair, we select an optimal action. After replacement, the system becomes new. We study the optimal maintenance policy which minimizes the expected total discounted cost for unbounded horizon. It is shown that, under reasonable conditions on the system's deterioration and repair laws and the cost structures, a control limit policy is optimal. We derive several valid properties for finding the optimal maintenance policy numerically. Furthermore, numerical analysis is conducted to show our theoretical results could hold under weaker conditions.

In this paper, we propose an integral-type T-S fuzzy control scheme to deal with the regulation problem of buck converters without current sensors. This current sensorless control of converters provides the output voltage to achieve zero steady-state error and is with high robust performance. The stability of the overall closed-loop system is rigorously analyzed by using Lyapunov's method. Based on an appropriate assumption, the separation principle can still succeed in the control problems. Hence, the controller and observer gains can be separately obtained by solving LMIs via Matlab's toolbox. The observer-based controller is realized with Simulink and digital signal processors (DSPs). The simulation and experimental results verify the feasibility of the proposed schemes and show the satisfactory performance for the power converters.

Intelligent scissors is an interactive image segmentation algorithm which allows a user to select piece-wise globally optimal contour segment corresponding to a desired object boundary. However, the intelligent scissors is too sensitive to a noise and texture patterns in an image since it utilizes the gradient information concerning the pixel intensities. This paper describes a new intelligent scissors based on the concept of the separability in order to improve the object boundary extraction performance. The effectiveness of the proposed method has been confirmed by some experiments for actual images acquired by an ordinary digital camera.

Arranging n points as uniformly as possible is a frequently occurring problem. It is equivalent to packing n equal and non-overlapping circles in a unit square. In this paper we generalize this problem in such a way that points are inserted one by one with uniformity preserved at every instance. Our criterion for uniformity is to minimize the gap ratio (which is the maximum gap over the minimum gap) at every point insertion. We present a linear time algorithm for finding an optimal n-point sequence with the maximum gap ratio bounded by in the 1-dimensional case. We describe how hard the same problem is for a point set in the plane and propose a local search heuristics for finding a good solution.

This paper deals with graph colouring games, an example of pseudo-telepathy, in which two players can convince a verifier that a graph G is c-colourable where c is less than the chromatic number of the graph. They win the game if they convince the verifier. It is known that the players cannot win if they share only classical information, but they can win in some cases by sharing entanglement. The smallest known graph where the players win in the quantum setting, but not in the classical setting, was found by Galliard, Tapp and Wolf and has 32,768 vertices. It is a connected component of the Hadamard graph GN with N=c=16. Their protocol applies only to Hadamard graphs where N is a power of 2. We propose a protocol that applies to all Hadamard graphs. Combined with a result of Frankl, this shows that the players can win on any induced subgraph of G12 having 1609 vertices, with c=12. Moreover combined with a result of Godsil and Newman, our result shows that all Hadamard graphs GN (N ≥ 12) and c=N yield pseudo-telepathy games.

A time domain (TD) speech enhancement technique to improve SNR in noise-contaminated speech is proposed. Additional supplementary scheme is applied to estimate the degree of noise of noisy speech. This is estimated from a function, which is previously prepared as the function of the parameter of the degree of noise. The function is obtained by least square (LS) method using the given degree of noise and the estimated parameter of the degree of noise. This parameter is obtained from the autocorrelation function (ACF) on frame-by-frame basis. This estimator almost accurately estimates the degree of noise and it is useful to reduce noise. The proposed method is based on two-stage processing. In the first stage, subtraction in time domain (STD), which is equivalent to ordinary spectral subtraction (SS), is carried out. In the result, the noise is reduced to a certain level. Further reduction of noise and by-product noise residual is carried out in the second stage, where blind source separation (BSS) technique is applied in time domain. Because the method is a single-channel speech enhancement, the other signal is generated by taking the noise characteristics into consideration in order to apply BSS. The generated signal plays a very important role in BSS. This paper presents an adaptive algorithm for separating sources in convolutive mixtures modeled by finite impulse response (FIR) filters. The coefficients of the FIR filter are estimated from the decorrelation of two mixtures. Here we are recovering only one signal of interest, in particular the voice of primary speaker free from interfering noises. In the experiment, the different levels of noise are added to the clean speech signal and the improvement of SNR at each stage is investigated. The noise types considered initially in this study consist of the synthesized white and color noise with SNR set from 0 to 30 dB. The proposed method is also tested with other real-world noises. The results show that the satisfactory SNR improvement is attained in the two-stage processing.

In this study, we propose a robust approach for blind source separation (BSS) by using radial basis function networks (RBFNs) and higher-order statistics (HOS). The RBFN is employed to estimate the inverse of a hypothetical complicated mixing procedure. It transforms the observed signals into high-dimensional space, in which one can simply separate the transformed signals by using a cost function. Recently, Tan et al. proposed a nonlinear BSS method, in which higher-order moments between source signals and observations are matched in the cost function. However, it has a strict restriction that it requires the higher-order statistics of sources to be known. We propose a cost function that consists of higher-order cumulants and the second-order moment of signals to remove the constraint. The proposed approach has the capacity of not only recovering the complicated mixed signals, but also reducing noise from observed signals. Simulation results demonstrate the validity of the proposed approach. Moreover, a result of application to X-ray image separation also shows its practical applicability.

The Hilbert transformation together with empirical mode decomposition (EMD) produces Hilbert spectrum (HS) which is a fine-resolution time-frequency representation of any nonlinear and non-stationary signal. The EMD decomposes the mixture signal into some oscillatory components each one is called intrinsic mode function (IMF). Some modification of the conventional EMD is proposed here. The instantaneous frequency of every real valued IMF component is computed with Hilbert transformation. The HS is constructed by arranging the instantaneous frequency spectra of IMF components. The HS of the mixture signal is decomposed into subspaces corresponding to the component sources. The decomposition is performed by applying independent component analysis (ICA) and Kulback-Leibler divergence based K-means clustering on the selected number of bases derived from HS of the mixture. The time domain source signals are assembled by applying some post processing on the subspaces. We have produced experimental results using the proposed separation technique.

This paper introduces the hardware platform of the structured light processing based on depth imaging to perform a 3D modeling of cluttered workspace for home service robots. We have discovered that the degradation of precision and robustness comes mainly from the overlapping of multiple codes in the signal received at a camera pixel. Considering the criticality of separating the overlapped codes to precision and robustness, we proposed a novel signal separation code, referred to here as "Hierarchically Orthogonal Code (HOC)," for depth imaging. The proposed HOC algorithm was implemented by using hardware platform which applies the Xilinx XC2V6000 FPGA to perform a real time 3D modeling and the invisible IR (Infrared) pattern lights to eliminate any inconveniences for the home environment. The experimental results have shown that the proposed HOC algorithm significantly enhances the robustness and precision in depth imaging, compared to the best known conventional approaches. Furthermore, after we processed the HOC algorithm implemented on our hardware platform, the results showed that it required 34 ms of time to generate one 3D image. This processing time is about 24 times faster than the same implementation of HOC algorithm using software, and the real-time processing is realized.

In 2000, Sandirigama, Shimizu, and Noda proposed a simple password authentication scheme, SAS. However, SAS was later found to be flawed. Recently, Chen, Lee, Horng proposed two SAS-like schemes, which were claimed to be more secure than similar schemes. Herein, we show that both their schemes are still vulnerable to denial-of-service attacks. Additionally, Chen-Lee-Horng's second scheme is not easily reparable.

We report on the design and experimental results of a fix-tuned Superconductor-Insulator-Superconductor (SIS) mixer for Atacama Large Millimeter/submillimeter Array (ALMA) band 8 (385-500 GHz) receivers. Nb-based SIS junctions of a current density of 10 kA/cm2 and one micrometer size (fabricated with a two-step lift-off process) are employed to accomplish the ALMA receiver specification, which requires wide frequency coverage as well as low noise temperature. A parallel-connected twin-junction (PCTJ) is designed to resonate at the band center to tune out the junction geometric capacitance. A waveguide-microstrip probe is optimized to have nearly frequency-independent impedance at the probe's feed point, thereby making it easy to match the low-impedance PCTJ over a wide frequency band. The RF embedding impedance is retrieved by fitting the measured pumped I-V curves to confirm good matching between PCTJ and signal source. We demonstrate here a minimum double-sideband receiver noise temperature of 3 times of quantum limits for an intermediate-frequency range of 4-8 GHz. The mixers were measured in band 8 cartridge with a sideband separation scheme. Single-sideband receiver noise below ALMA specification was achieved over the whole band.

We propose utilizing subband-based blind source separation (BSS) for convolutive mixtures of speech. This is motivated by the drawback of frequency-domain BSS, i.e., when a long frame with a fixed long frame-shift is used to cover reverberation, the number of samples in each frequency decreases and the separation performance is degraded. In subband BSS, (1) by using a moderate number of subbands, a sufficient number of samples can be held in each subband, and (2) by using FIR filters in each subband, we can manage long reverberation. We confirm that subband BSS achieves better performance than frequency-domain BSS. Moreover, subband BSS allows us to select a separation method suited to each subband. Using this advantage, we propose efficient separation procedures that consider the frequency characteristics of room reverberation and speech signals (3) by using longer unmixing filters in low frequency bands and (4) by adopting an overlap-blockshift in BSS's batch adaptation in low frequency bands. Consequently, frequency-dependent subband processing is successfully realized with the proposed subband BSS.

We propose a new two-stage blind separation and deconvolution strategy for multiple-input multiple-output (MIMO)-FIR systems driven by colored sound sources, in which single-input multiple-output (SIMO)-model-based ICA (SIMO-ICA) and blind multichannel inverse filtering are combined. SIMO-ICA can separate the mixed signals, not into monaural source signals but into SIMO-model-based signals from independent sources as they are at the microphones. After the separation by the SIMO-ICA, a blind deconvolution technique for the SIMO model can be applied even when each source signal is temporally correlated and the mixing system has a nonminimum phase property. The simulation results reveal that the proposed algorithm can successfully achieve separation and deconvolution of a convolutive mixture of speech, and outperforms a number of conventional ICA-based BSD methods.

The effect of intermediate frequency magnetic fields or, very-low-frequency magnetic fields (VLFMF) on living biological cells was investigated using a highly sensitive mutagenesis assay method. A bacterial gene expression system for mutation repair (umu system) was used for the sensitive evaluation of damage in DNA molecules. Salmonella typhimurium TA1535 (pSK1002) were exposed to VLFMF (20 kHz and 600 µT) in a specially designed magnetic field loading chamber. The experiment results showed the possibility of applying the umu assay for sensitive and effective evaluation of damage in DNA molecules. No effects from exposure to 20 kHz and 600 µT magnetic fields in terms of damage in DNA molecules were observed.

In this paper, we address the blind separation problem of binaural mixed signals, and we propose a novel blind separation method, in which a self-generator for initial filters of Single-Input-Multiple-Output-model-based independent component analysis (SIMO-ICA) is implemented. The original SIMO-ICA which has been proposed by the authors can separate mixed signals, not into monaural source signals but into SIMO-model-based signals from independent sources as they are at the microphones. Although this attractive feature of SIMO-ICA is beneficial to the binaural sound separation, the current SIMO-ICA has a serious drawback in its high sensitivity to the initial settings of the separation filter. In the proposed method, the self-generator for the initial filter functions as the preprocessor of SIMO-ICA, and thus it can provide a valid initial filter for SIMO-ICA. The self-generator is still a blind process because it mainly consists of a frequency-domain ICA (FDICA) part and the direction of arrival estimation part which is driven by the separated outputs of the FDICA. To evaluate its effectiveness, binaural sound separation experiments are carried out under a reverberant condition. The experimental results reveal that the separation performance of the proposed method is superior to those of conventional methods.

This paper presents a study on the blind separation of a convoluted mixture of speech signals using Frequency Domain Independent Component Analysis (FDICA) algorithm based on the negentropy maximization of Time Frequency Series of Speech (TFSS). The comparative studies on the negentropy approximation of TFSS using generalized Higher Order Statistics (HOS) of different nonquadratic, nonlinear functions are presented. A new nonlinear function based on the statistical modeling of TFSS by exponential power functions has also been proposed. The estimation of standard error and bias, obtained using the sequential delete-one jackknifing method, in the approximation of negentropy of TFSS by different nonlinear functions along with their signal separation performance indicate the superlative power of the exponential-power-based nonlinear function. The proposed nonlinear function has been found to speed-up convergence with slight improvement in the separation quality under reverberant conditions.

This paper focuses on the underdetermined blind source separation (BSS) of three speech signals mixed in a real environment from measurements provided by two sensors. To date, solutions to the underdetermined BSS problem have mainly been based on the assumption that the speech signals are sufficiently sparse. They involve designing binary masks that extract signals at time-frequency points where only one signal was assumed to exist. The major issue encountered in previous work relates to the occurrence of distortion, which affects a separated signal with loud musical noise. To overcome this problem, we propose combining sparseness with the use of an estimated mixing matrix. First, we use a geometrical approach to detect when only one source is active and to perform a preliminary separation with a time-frequency mask. This information is then used to estimate the mixing matrix, which allows us to improve our separation. Experimental results show that this combination of time-frequency mask and mixing matrix estimation provides separated signals of better quality (less distortion, less musical noise) than those extracted without using the estimated mixing matrix in reverberant conditions where the reverberant time (TR) was 130 ms and 200 ms. Furthermore, informal listening tests clearly show that musical noise is deeply lowered by the proposed method comparatively to the classical approaches.