This paper aims to achieve a high-quality exposure level quantification of whole-body average-specific absorption rates (WBA-SARs) for small animals in a medium-size reverberation chamber (RC). A two-step method, which incorporates the finite-difference time-domain (FDTD) numerical solutions with electric field measurements in an RC-type exposure system, has been used as an evaluation method to determine the whole-body exposure level in small animals. However, there is little data that quantitatively demonstrate the validity and accuracy of this method in an RC up to now. In order to clarify the validity of the two-step method, we compare the physical quantities in terms of electric field strength and WBA-SARs by using a direct numerical assessment method known as the method of moments (MoM) with ten homogenous gel phantoms placed in an RC with 2GHz exposure. The comparison results show that the relative errors between the two-step method and the MoM approach are approximately below 10%, which reveals the validity and usefulness of the two-step technique. Finally, we perform a dosimetric analysis of the WBA-SARs for anatomical mouse models with the two-step method and determine the input power related to our developed RC-exposure system to achieve a target exposure level in small animals.

This paper proposes a noise reduction method for impact noise with damped oscillation caused by clinking a glass, hitting a bottle, and so on. The proposed method is based on the zero phase (ZP) signal defined as the IDFT of the spectral amplitude. When the target noise can be modeled as the sum of the impact part and the damped oscillation part, the proposed method can reduce them individually. First, the proposed method estimates the damped oscillation spectra and subtracts them from the observed spectra. Then, the impact part is reduced by replacing several samples of the ZP observed signal. Simulation results show that the proposed method improved 10dB of SNR of real impact noise.

A novel method for calibrating the probes used in standard measurement systems to evaluate SAR (specific absorption rate) of the radio equipment operating at frequencies over 3GHz is proposed. As for the proposed method, the electric-field distribution produced by a waveguide aperture installed in a liquid container is used to calibrate the SAR probe. The field distribution is shown to be the same as that given by a conventional calibration method by analytically deriving a closed-form expression for the field produced by the waveguide aperture with the help of the paraxial approximation. Comparing the approximated and measured distributions reveals that the closed-form expression is valid for the electric-field distribution near the central axis of the aperture. The calibration factor for a commercial SAR probe is evaluated by the proposed method and agrees well with that provided by the manufacturer of the probe.

This paper presents a spatial fading emulator for evaluating handset MIMO antennas in a cluster environment. The proposed emulator is based on Clarke's model and has the ability to control RF signals directly in spatial domain to generate an accurate radio propagation channel model, which includes both uniform and non-uniform angular power spectra (APS) in the horizontal plane. Characteristics of a propagation channel such as fading correlations, eigenvalues and MIMO channel capacities of handset antennas located in the vicinity of the emulator's ring can be evaluated. The measured results show that the fading emulator with 31 antenna probes is sufficient to evaluate fading correlation and MIMO channel capacity of handset antenna in the case of a narrow APS with the standard deviation of more than 20 degrees.

The applicability of at-speed scan-based logic built-in self-test (BIST) is being severely challenged by excessive capture power that may cause erroneous test responses even for good circuits. Different from conventional low-power BIST, this paper is the first to explicitly focus on achieving capture power safety with a novel and practical scheme, called capture-power-safe logic BIST (CPS-LBIST). The basic idea is to identify all possibly-erroneous test responses caused by excessive capture power and use the well-known approach of masking (bit-masking, slice-masking,vector-masking) to block them from reaching the multiple-input signature register(MISR). Experiments with large benchmark circuits and a large industrial circuit demonstrate that CPS-LBIST can achieve capture power safety with negligible impact on test quality and circuit overhead.

Visual quality evaluation is crucially important for various video and image processing systems. Traditionally, subjective image quality assessment (IQA) given by the judgments of people can be perfectly consistent with human visual system (HVS). However, subjective IQA metrics are cumbersome and easily affected by experimental environment. These problems further limits its applications of evaluating massive pictures. Therefore, objective IQA metrics are desired which can be incorporated into machines and automatically evaluate image quality. Effective objective IQA methods should predict accurate quality in accord with the subjective evaluation. Motivated by observations that HVS is highly adapted to extract irregularity information of textures in a scene, we introduce multifractal formalism into an image quality assessment scheme in this paper. Based on multifractal analysis, statistical complexity features of nature images are extracted robustly. Then a novel framework for image quality assessment is further proposed by quantifying the discrepancies between multifractal spectrums of images. A total of 982 images are used to validate the proposed algorithm, including five type of distortions: JPEG2000 compression, JPEG compression, white noise, Gaussian blur, and Fast Fading. Experimental results demonstrate that the proposed metric is highly effective for evaluating perceived image quality and it outperforms many state-of-the-art methods.

We propose a new algorithm to suppress both stationary background noise and nonstationary directional interference noise in a speech enhancement system that employs the generalized sidelobe canceller. Our approach builds on advances in generalized sidelobe canceller design involving the transfer function ratio. Our system is composed of three stages. The first stage estimates the transfer function ratio on the acoustic path, from the nonstationary directional interference noise source to the microphones, and the powers of the stationary background noise components. Secondly, the estimated powers of the stationary background noise components are used to execute spectral subtraction with respect to input signals. Finally, the estimated transfer function ratio is used for speech enhancement on the primary channel, and an adaptive filter reduces the residual correlated noise components of the signal. These algorithmic improvements give consistently better performance than the transfer function generalized sidelobe canceller when input signal-to-noise ratio is 10 dB or lower.

Survivability is an essential requirement of the networked information systems analogous to the dependability. The definition of survivability proposed by Knight in [16] provides a rigorous way to define the concept. However, the Knight's specification does not provide a behavior model of the system as well as a verification framework for determining the survivability of a system satisfying a given specification. This paper proposes a complete formal framework for specifying and verifying the concept of system survivability on the basis of Knight's research. A computable probabilistic model is proposed to specify the functions and services of a networked information system. A quantified survivability specification is proposed to indicate the requirement of the survivability. A probabilistic refinement relation is defined to determine the survivability of the system. The framework is then demonstrated with three case studies: the restaurant system (RES), the Warship Command and Control system (LWC) and the Command-and-Control (C2) system.

In this paper, a new database suitable for HMM-based automatic Filipino speech recognition is described for the purpose of training a domain-independent, large-vocabulary continuous speech recognition system. Although it is known that high-performance speech recognition systems depend on a superior speech database used in the training stage, due to the lack of such an appropriate database, previous reports on Filipino speech recognition had to contend with serious data sparsity issues. In this paper we alleviate such sparsity through appropriate data analysis that makes the evaluation results more reliable. The best system is identified through its low word-error rate to a cross-validation set containing almost three hours of unknown speech data. Language-dependent problems are discussed, and their impact on accuracy was analyzed. The approach is currently data driven, however it serves as a competent baseline model for succeeding future developments.

A major challenge for speech emotion recognition is that when the training and deployment conditions do not use the same speech corpus, the recognition rates will obviously drop. Transfer learning, which has successfully addressed the cross-domain classification or recognition problem, is presented for cross-corpus speech emotion recognition. First, by using the maximum mean discrepancy embedding (MMDE) optimization and dimension reduction algorithms, two close low-dimensional feature spaces are obtained for source and target speech corpora, respectively. Then, a classifier function is trained using the learned low-dimensional features in the labeled source corpus, and directly applied to the unlabeled target corpus for emotion label recognition. Experimental results demonstrate that the transfer learning method can significantly outperform the traditional automatic recognition technique for cross-corpus speech emotion recognition.

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).

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.

The data rate of VLSI interconnections has been increasing according to the demand for high-speed operation of semiconductors such as CPUs. To realize high performance VLSI systems, high-speed data communication has become an important factor. However, at high-speed data rates, it is difficult to achieve accurate communication without bit errors because of inter-symbol interference (ISI). This paper presents high-speed data communication techniques for VLSI systems using Tomlinson-Harashima Precoding (THP). Since THP can eliminate the ISI with limiting average and peak power of transmitter signaling, THP is suitable for implementing advanced low-voltage VLSI systems. In this paper, 4-PAM (Pulse amplitude modulation) with THP has been employed to achieve high-speed data communication in VLSI systems. Simulation results show that THP can remove the ISI without increasing peak and average power of a transmitter. Moreover, simulation results clarify that multiple-valued data communication is very effective to reduce implementation costs for realizing high-speed serial links.

We propose a speaker adaptation method based on the probabilistic principal component analysis (PPCA) of acoustic models. We define a training matrix which is represented in a two-way array and decompose the training models by PPCA to construct bases. In the two-way array representation, each training model is represented as a matrix and the columns of each training matrix are treated as training vectors. We formulate the adaptation equation in the maximum a posteriori (MAP) framework using the bases and the prior.

We compared two audio output devices for augmented audio reality applications. In these applications, we plan to use speech annotations on top of the actual ambient environment. Thus, it becomes essential that these audio output devices are able to deliver intelligible speech annotation along with transparent delivery of the environmental auditory scene. Two candidate devices were compared. The first output was the bone-conduction headphone, which can deliver speech signals by vibrating the skull, while normal hearing is left intact for surrounding noise since these headphones leave the ear canals open. The other is the binaural microphone/earphone combo, which is in a form factor similar to a regular earphone, but integrates a small microphone at the ear canal entry. The input from these microphones can be fed back to the earphones along with the annotation speech. We also compared these devices to normal hearing (i.e., without headphones or earphones) for reference. We compared the speech intelligibility when competing babble noise is simultaneously given from the surrounding environment. It was found that the binaural combo can generally deliver speech signals at comparable or higher intelligibility than the bone-conduction headphones. However, with the binaural combo, we found that the ear canal transfer characteristics were altered significantly by shutting the ear canals closed with the earphones. Accordingly, if we employed a compensation filter to account for this transfer function deviation, the resultant speech intelligibility was found to be significantly higher. However, both of these devices were found to be acceptable as audio output devices for augmented audio reality applications since both are able to deliver speech signals at high intelligibility even when a significant amount of competing noise is present. In fact, both of these speech output methods were able to deliver speech signals at higher intelligibility than natural speech, especially when the SNR was low.

We present the adaptation of the acoustic models of hidden Markov models (HMMs) to the target speaker and noise environment using bilinear models. Acoustic models trained from various speakers and noise conditions are decomposed to build the bases that capture the interaction between the two factors. The model for the target speaker and noise is represented as a product of bases and two weight vectors. In experiments using the AURORA4 corpus, the bilinear model outperforms the linear model.

A smoothing method for minimum phone error linear regression (MPELR) is proposed in this paper. We show that the objective function for minimum phone error (MPE) can be combined with a prior mean distribution. When the prior mean distribution is based on maximum likelihood (ML) estimates, the proposed method is the same as the previous smoothing technique for MPELR. Instead of ML estimates, maximum a posteriori (MAP) parameter estimate is used to define the mode of prior mean distribution to improve the performance of MPELR. Experiments on a large vocabulary speech recognition task show that the proposed method can obtain 8.4% relative reduction in word error rate when the amount of data is limited, while retaining the same asymptotic performance as conventional MPELR. When compared with discriminative maximum a posteriori linear regression (DMAPLR), the proposed method shows improvement except for the case of limited adaptation data for supervised adaptation.

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.

Smart city services are implemented using various data collected from houses and infrastructure within a city. As the volume and variety of the smart city data becomes huge, individual services have suffered from expensive computation effort and large processing time. In order to reduce the effort and time, this paper proposes a concept of Materialized View as a Service (MVaaS). Using the MVaaS, every application can easily and dynamically construct its own materialized view, in which the raw data is converted and stored in a convenient format with appropriate granularity. Thus, once the view is constructed, the application can quickly access necessary data. In this paper, we design a framework of MVaaS specifically for large-scale house log, managed in a smart-city data platform. In the framework, each application first specifies how the raw data should be filtered, grouped and aggregated. For a given data specification, MVaaS dynamically constructs a MapReduce batch program that converts the raw data into a desired view. The batch is then executed on Hadoop, and the resultant view is stored in HBase. We present case studies using house log in a real home network system. We also conduct an experimental evaluation to compare the response time between cases with and without MVaaS.

This paper proposes a new spectrum sharing scheme which uses one-sided collaboration. In the proposed system, the transmitter of the secondary system relays the primary signal and overlays its own data on the retransmitted primary signal. The results of the theoretical analysis show that the proposed scheme with regenerative relay allows the secondary system to communicate at the same speed as the primary system that disregards the presence of the secondary system.