In this study, we have developed a translation repair method to automatically improve the accuracy of translations. Machine translation (MT) supports multilingual communication; however, it cannot achieve high accuracy. MT creates only one translated sentence; therefore, it is difficult to improve the accuracy of translated sentences. Our method creates multiple translations by adding personal pronouns to the source sentence and by using a word dictionary and a parallel corpus. In addition, it selects an accurate translation from among the multiple translations using the results of a Web search. As a result, the translation repair method improved the accuracy of translated sentences, and its accuracy is greater than that of MT.

Recent studies have focused on developing security systems using micro-Doppler radars to detect human bodies. However, the resolution of these conventional methods is unsuitable for identifying bodies and moreover, most of these conventional methods were designed for a solitary or sufficiently well-spaced targets. This paper proposes a solution to these problems with an image separation method for two closely spaced pedestrian targets. The proposed method first develops an image of the targets using ultra-wide-band (UWB) Doppler imaging radar. Next, the targets in the image are separated using a supervised learning-based separation method trained on a data set extracted using a range profile. We experimentally evaluated the performance of the image separation using some representative supervised separation methods and selected the most appropriate method. Finally, we reject false points caused by target interference based on the separation result. The experiment, assuming two pedestrians with a body separation of 0.44m, shows that our method accurately separates their images using a UWB Doppler radar with a nominal down-range resolution of 0.3m. We describe applications using various target positions, establish the performance, and derive optimal settings for our method.

In this letter, we address monaural source separation based on supervised nonnegative matrix factorization (SNMF) and propose a new penalized SNMF. Conventional SNMF often degrades the separation performance owing to the basis-sharing problem. Our penalized SNMF forces nontarget bases to become different from the target bases, which increases the separated sound quality.

In this paper, a novel White-RGB (WRGB) color filter array-based imaging system for cell phone is presented to reduce noise and reproduce color in low illumination. The core process is based on adaptive diagonal color separation to recover color components from a white signal using diagonal reference blocks and location-based color ratio estimation in the luminance space. The experiments, which are compared with the RGB and state-of-the-art WRGB approaches, show that our imaging system performs well for various spatial frequency images and color restoration in low-light environments.

In this paper, we apply a mutation operation based on a multivariate Cauchy distribution to fast evolutionary programming and analyze its effect in terms of various function optimizations. The conventional fast evolutionary programming in-cooperates the univariate Cauchy mutation in order to overcome the slow convergence rate of the canonical Gaussian mutation. For a mutation of n variables, while the conventional method utilizes n independent random variables from a univariate Cauchy distribution, the proposed method adopts n mutually dependent random variables that satisfy a multivariate Cauchy distribution. The multivariate Cauchy distribution naturally has higher probabilities of generating random variables in inter-variable regions than the univariate Cauchy distribution due to the mutual dependence among variables. This implies that the multivariate Cauchy random variable enhances the search capability especially for a large number of correlated variables, and, as a result, is more appropriate for optimization schemes characterized by interdependence among variables. In this sense, the proposed mutation possesses the advantage of both the univariate Cauchy and Gaussian mutations. The proposed mutation is tested against various types of real-valued function optimizations. We empirically find that the proposed mutation outperformed the conventional Cauchy and Gaussian mutations in the optimization of functions having correlations among variables, whereas the conventional mutations showed better performance in functions of uncorrelated variables.

This letter proposes a noise spectrum estimation algorithm for speech enhancement. The algorithm incorporates the speech presence probability, which is calculated from SNR (signal-to-noise ratio) discrepancy. The discrepancy is measured based on the estimation of the a priori and a posteriori SNR. The proposed algorithm is found to be effective in rapidly switched noise environments. This is confirmed by the experimental results which indicate that the proposed algorithm when integrated in a speech enhancement scheme performs better than conventional noise estimation algorithms.

Television white spaces (TVWS) are locally and/or temporally unused portions of TV bands. After TVWS regulations were passed in the USA, more and more regulators have been considering efficient use of TVWS. Under the condition that the primary user, i.e., terrestrial TV broadcasting system, is not interfered, various secondary users (SUs) may be deployed in TVWS. In Japan, the TVWS regulations started with broadcast-type SUs and small-area broadcasting systems, followed by voice radio. This paper aims to provide useful insights for more efficient utilization of TVWS as one of the options to meet the continuously increasing demand for wireless bandwidth. TVWS availability in Japan is analyzed using graphs and maps. As per the regulations in Japan, for TV broadcasting service, a protection contour is defined to be 51dBµV/m, while the interference contour for SU is defined to be 12.3dBµV/m. We estimate TVWS availability using these two regulation parameters and the minimum separation distances calculated on the basis of the ITU-R P.1546 propagation models. Moreover, we investigate and explain the effect of two important factors on TVWS availability. One is the measures to avoid adjacent channel interference, while the other is whether the SU has client devices with interference ranges beyond the interference area of the master device. Furthermore, possible options to increase available TVWS channels are discussed.

The separation time-overlapping ultrasound signals is necessary to obtain accurate estimate of transit time and material properties. In this letter, a method to determine the optimal transform order of fractional Fourier transform (FRFT) for decomposition of overlapping ultrasonic signals is proposed. The optimal transform order is obtained by minimizing the mean square error (MSE) between the output and the reference signal. Furthermore, windowing in FRFT domain is discussed. Numerical simulation results show the performances of the proposed method in separating signals overlapping in time.

Temporal Decorrelation source SEParation (TDSEP) is a blind separation scheme that utilizes the time structure of the source signals, typically, their periodicities. The advantage of TDSEP over non-Gaussianity based methods is that it can separate Gaussian signals as long as they are periodic. However, its shortcoming is that separation performance (SEP) heavily depends upon the values of the time shift parameters (TSPs). This paper proposes a method to automatically and blindly estimate a set of TSPs that achieves optimal SEP against periodic Gaussian signals. It is also shown that, selecting the same number of TSPs as that of the source signals, is sufficient to obtain optimal SEP, and adding more TSPs does not improve SEP, but only increases the computational complexity. The simulation example showed that the SEP is higher by approximately 20dB, compared with the ordinary method. It is also shown that the proposed method successfully selects just the same number of TSPs as that of incoming signals.

We consider the minimum feedback vertex set problem for some bipartite graphs and degree-constrained graphs. We show that the problem is linear time solvable for bipartite permutation graphs and NP-hard for grid intersection graphs. We also show that the problem is solvable in O(n2log 6n) time for n-vertex graphs with maximum degree at most three.

This paper deals with the problem of underdetermined blind source separation (BSS) where the number of sources is unknown. We propose a BSS approach that simultaneously estimates the number of sources, separates the sources based on the sparseness of speech, estimates the direction of arrival of each source, and performs permutation alignment. We confirmed experimentally that reasonably good separation was obtained with the present method without specifying the number of sources.

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.

In this paper, we propose a new class of two dimensional (2D) M-channel (M-ch) non-separable filter banks (FBs) based on cosine modulated filter banks (CMFBs) via a new diagonally modulation scheme. Until now, many researchers have proposed 2D non-separable CMFBs. Nevertheless, efficient direction-selective CMFBs have not been yet. Thanks to our new modulations with diagonal shifts, proposed CMFBs have several frequency supports including direction-selective ones which cannot be realized by conventional ones. In a simulation, we show design examples of proposed CMFBs and their various directional frequency supports.

High-resolution time of arrival (TOA) estimation techniques have great promise for the high range resolution required in recently developed radar systems. A widely known super-resolution TOA estimation algorithm for such applications, the multiple-signal classification (MUSIC) in the frequency domain, has been proposed, which exploits an orthogonal relationship between signal and noise eigenvectors obtained by the correlation matrix of the observed transfer function. However, this method suffers severely from a degraded resolution when a number of highly correlated interference signals are mixed in the same range gate. As a solution for this problem, this paper proposes a novel TOA estimation algorithm by introducing a maximum likelihood independent component analysis (MLICA) approach, in which multiple complex sinusoidal signals are efficiently separated by the likelihood criteria determined by the probability density function (PDF) of a complex sinusoid. This MLICA schemes can decompose highly correlated interference signals, and the proposed method then incorporates the MLICA into the MUSIC method, to enhance the range resolution in richly interfered situations. The results from numerical simulations and experimental investigation demonstrate that our proposed pre-processing method can enhance TOA estimation resolution compared with that obtained by the original MUSIC, particularly for lower signal-to-noise ratios.

This paper deals with reflection and transmission of a TE plane wave from a one-dimensional random slab with slanted fluctuation by means of the stochastic functional approach. By starting with a generalized representation of the random wavefield from a two-dimensional random slab, and by using a manner for slanted anisotropic fluctuation, the corresponding random wavefield representation and its statistical quantities for one-dimensional cases are newly derived. The first-order incoherent scattering cross section is numerically calculated and illustrated in figures.

Random telegraph noise (RTN) is a phenomenon that is considered to limit the reliability and performance of circuits using advanced devices. The time constants of carrier capture and emission and the associated change in the threshold voltage are important parameters commonly included in various models, but their extraction from time-domain observations has been a difficult task. In this study, we propose a statistical method for simultaneously estimating interrelated parameters: the time constants and magnitude of the threshold voltage shift. Our method is based on a graphical network representation, and the parameters are estimated using the Markov chain Monte Carlo method. Experimental application of the proposed method to synthetic and measured time-domain RTN signals was successful. The proposed method can handle interrelated parameters of multiple traps and thereby contributes to the construction of more accurate RTN models.

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.

Separation-of-Duty (SoD) is a fundamental security principle for prevention of fraud and errors in computer security. It has been studied extensively in traditional access control models. However, the research of SoD policy in the recently proposed usage control (UCON) model has not been well studied. This paper formulates and studies the fundamental problem of static enforcement of static SoD (SSoD) policies in the context of UCONA, a sub-model of UCON only considering authorizations. Firstly, we define a set-based specification of SSoD policies, and the safety checking problem for SSoD in UCONA. Secondly, we study the problem of determining whether an SSoD policy is enforceable. Thirdly, we show that it is intractable (coNP-complete) to direct statically enforce SSoD policies in UCONA, while checking whether a UCONA state satisfies a set of static mutually exclusive attribute (SMEA) constraints is efficient, which provides a justification for using SMEA constraints to enforce SSoD policies. Finally, we introduce a indirect static enforcement for SSoD policies in UCONA. We show how to generate the least restrictive SMEA constraints for enforcing SSoD policies in UCONA, by using the attribute-level SSoD requirement as an intermediate step. The results are fundamental to understanding SSoD policies in UCON.

Recently, the 3-D vertical Floating Gate (FG) type NAND cell arrays with the Sidewall Control Gate (SCG), such as ESCG, DC-SF and S-SCG, are receiving attention to overcome the reliability issues of Charge Trap (CT) type device. Using this novel cell structure, highly reliable flash cell operations were successfully implemented without interference effect on the FG type cell. However, the 3-D vertical FG type cell has large cell size by about 60% for the cylindrical FG structure. In this point of view, we intensively investigate the scalability of the FG width of the 3-D vertical FG NAND cells. In case of the planar FG type NAND cell, the FG height cannot be scaled down due to the necessity of obtaining sufficient coupling ratio and high program speed. In contrast, for the 3-D vertical FG NAND with SCG, the FG is formed cylindrically, which is fully covered with surrounded CG, and very high CG coupling ratio can be achieved. As results, the scaling of FG width of the 3-D vertical FG NAND cell with S-SCG can be successfully demonstrated at 10 nm regime, which is almost the same as the CT layer of recent BE-SONOS NAND.

In this paper, we propose a method for supervised single-channel speech separation through sparse decomposition using periodic signal models. The proposed separation method employs sparse decomposition, which decomposes a signal into a set of periodic signals under a sparsity penalty. In order to achieve separation through sparse decomposition, the decomposed periodic signals have to be assigned to the corresponding sources. For the assignment of the periodic signal, we introduce clustering using a K-means algorithm to group the decomposed periodic signals into as many clusters as the number of speakers. After the clustering, each cluster is assigned to its corresponding speaker using preliminarily learnt codebooks. Through separation experiments, we compare our method with MaxVQ, which performs separation on the frequency spectrum domain. The experimental results in terms of signal-to-distortion ratio show that the proposed sparse decomposition method is comparable to the frequency domain approach and has less computational costs for assignment of speech components.