Certain irregularities in the utterances of words or phrases often occur in English spoken by Japanese native subject, referred to in this article as Japanese English. Japanese English is linguistically presumed to reflect the phonetic characteristics of Japanese. We consider the prosodic feature patterns as one of the most common causes of irregularities in Japanese English, and that Japanese English would have better prosodic patterns if its particular characteristics were modified. This study investigates prosodic differences between Japanese English and English speakers' English, and shows the quantitative results of a statistical analysis of pitch. The analysis leads to rules that show how to modify Japanese English to have pitch patterns closer to those of English speakers. On the basis of these rules, the pitch patterns of test speech samples of Japanese English are modified, and then re-synthesized. The modified speech is evaluated in a listening experiment by native English subjects. The result of the experiment shows that on average, over three-fold of the English subjects support the proposed modification against original speech. Therefore, the results of the experiments indicate practical verification of validity of the rules. Additionally, the results suggest that irregularities of prominence lie in Japanese English sentences. This can be explained by the prosodic transfer of first language prosodic characteristics on second language prosodic patterns.

In spectrum sensing, if the primary user (PU) signal and the channel noise both follow Gaussian distribution and neither of their probability distribution functions (PDFs) are known, the traditional approaches based on entropy or Likelihood Ratio Test (LRT) etc., become infeasible. To address this problem, we propose a spectrum sensing method that exploits the similarity of PDFs of two time-adjacent detected data sets with cross entropy, while accounting for achieving the detection performance of LRT which is Neyman-Pearson optimal in detecting the primary user. We show that the detection performance of the proposed method asymptotically approximates that of LRT in detecting the PU. The simulation results confirm our analysis.

This paper investigates a new method for fusion of scores generated by multiple classification sub-systems that help to further reduce the classification error rate in Spoken Language Recognition (SLR). In recent studies, a variety of effective classification algorithms have been developed for SLR. Hence, it has been a common practice in the National Institute of Standards and Technology (NIST) Language Recognition Evaluations (LREs) to fuse the results from several classification sub-systems to boost the performance of the SLR systems. In this work, we introduce a discriminative performance measure to optimize the performance of the fusion of 7 language classifiers developed as IIR's submission to the 2009 NIST LRE. We present an Error Corrective Fusion (ECF) method in which we iteratively learn the fusion weights to minimize error rate of the fusion system. Experiments conducted on the 2009 NIST LRE corpus demonstrate a significant improvement compared to individual sub-systems. Comparison study is also conducted to show the effectiveness of the ECF method.

The statistical static timing analysis has been studied intensively in the last decade so as to deal with the process variability, and various techniques to represent distributions of timing information, such as a gate delay, a signal arrival time, and a slack, have been proposed. Among them, the Gaussian mixture model is distinguished from the others in that it can handle various correlations, non-Gaussian distributions, and slew distributions easily. However, the previous algorithm of computing the statistical maximum for Gaussian mixture models, which is one of key operations in the statistical static timing analysis, has a defect such that it produces a distribution similar to Gaussian in a certain case, although the correct distribution is far from Gaussian. In this paper, we propose a new algorithm for statistical maximum (minimum) operation for Gaussian mixture models. It takes the cumulative distribution function curve into consideration so as to compute accurate criticalities (probabilities of timing violation), which is important for detecting delay faults and circuit optimization with the use of statistical approaches. We also show some experimental results to evaluate the performance of the proposed method.

Radio frequency on free-space optical (RoFSO) technology is regarded as a new universal platform for enabling seamless convergence of fiber and FSO communication networks, thus extending broadband connectivity to underserved areas. In this paper, we investigate the performance to characterize the transmission of code division multiple access (CDMA) based wireless signals over RoFSO system using aperture averaging (AA) technique under strong turbulence conditions. An analytical model including a modified carrier-to-noise-plus- interference ratio (CNIR) form and a novel closed-form expression for the bit-error rate (BER) is derived. Unlike earlier work, our model takes into consideration the effect of using the AA technique modeled by the gamma-gamma distribution, the optical noises, the intermodulation distortion term due to the laser diode non-linearity and the multiple interference access. By investigating the impact of AA on our model in the strong turbulence regime, we show that there is a design trade-off between the receiver lens aperture and the number of users to achieve a required CNIR ensuring a substantial scintillation fade reduction. The presented work can be used as baseline for the design and performance evaluation of the RoFSO system's ability to transmit different broadband wireless services signals over turbulent FSO links in real scenarios.

Bayesian methods are often applied for estimating the event rate from a series of event occurrences. However, the Bayesian posterior distribution requires the computation of the marginal likelihood which generally involves an analytically intractable integration. As an event rate is defined in a very high dimensional space, it is computationally demanding to obtain the Bayesian posterior distribution for the rate. We estimate the rate underlying a sequence of event counts by deriving an approximate Bayesian inference algorithm for the time-varying binomial process. This enables us to calculate the posterior distribution analytically. We also provide a method for estimating the prior hyperparameter, which determines the smoothness of the estimated event rate. Moreover, we provide an efficient method to compute the upper and lower bounds of the marginal likelihood, which evaluate the approximation accuracy. Numerical experiments demonstrate the effectiveness of the proposed method in terms of the estimation accuracy.

Thin film glucose biosensors were fabricated with organic/inorganic hybrid films based on glucose oxidase (GOx) and Prussian Blue nano-clusters. The biosensors composed of hybrid films were characterized by the low operating potential and the advantage to interference-free detection. In this research, we employed two kinds of thin films for GOx immobilization: Langmuir-Blodgett (LB) and self-assembled monolayer (SAM). The LB film immobilizes GOx in its inside through the electrostatic force, while the SAM immobilizes GOx with the covalent bond. The sensors with LB film produced a relatively high current signal, while the non-linear behavior and a low stability were recognized. On the other hand, the sensors with SAM presented a good linear relationship and a very stable performance.

We propose a novel saliency detection model based on Bayes' theorem. The model integrates the two parts of Bayes' equation to measure saliency, each part of which was considered separately in the previous models. The proposed model measures saliency by computing local kernel density estimation of features in the center-surround region and global kernel density estimation of features at each pixel across the whole image. Under the proposed model, a saliency detection method is presented that extracts DCT (Discrete Cosine Transform) magnitude of local region around each pixel as the feature. Experiments show that the proposed model not only performs competitively on psychological patterns and better than the current state-of-the-art models on human visual fixation data, but also is robust against signal uncertainty.

In this letter, we propose a novel speech enhancement algorithm based on data-driven residual gain estimation. The entire system consists of two stages. At the first stage, a conventional speech enhancement algorithm enhances the input signal while estimating several signal-to-noise ratio (SNR)-related parameters. The residual gain, which is estimated by a data-driven method, is applied to further enhance the signal at the second stage. A number of experimental results show that the proposed speech enhancement algorithm outperforms the conventional speech enhancement technique based on soft decision and the data-driven approach using SNR grid look-up table.

Object tracking is a major technique in image processing and computer vision. Tracking speed will directly determine the quality of applications. This paper presents a parallel implementation for a recently proposed scale- and rotation-invariant on-line object tracking system. The algorithm is based on NVIDIA's Graphics Processing Units (GPU) using Compute Unified Device Architecture (CUDA), following the model of single instruction multiple threads. Specifically, we analyze the original algorithm and propose the GPU-based parallel design. Emphasis is placed on exploiting the data parallelism and memory usage. In addition, we apply optimization technique to maximize the utilization of NVIDIA's GPU and reduce the data transfer time. Experimental results show that our GPGPU-based method running on a GTX480 graphics card could achieve up to 12X speed-up compared with the efficiency equivalence on an Intel E8400 3.0 GHz CPU, including I/O time.

In this paper, we propose a hybrid test application in partial skewed-load (PSL) scan design. The PSL scan design in which some flip-flops (FFs) are controlled as skewed-load FFs and the others are controlled as broad-side FFs was proposed in [1]. We notice that the PSL scan design potentially has a capability of two test application modes: one is the broad-side test mode, and the other is the hybrid test mode which corresponds to the test application considered in [1]. According to this observation, we present a hybrid test application of the two test modes in the PSL scan design. In addition, we also address a way of skewed-load FF selection based on propagation dominance of FFs in order to take advantage of the hybrid test application. Experimental results for ITC'99 benchmark circuits show that the hybrid test application in the proposed PSL scan design can achieve higher fault coverage than the design based on the skewed-load FF selection [1] does.

Coordinated multi-point processing at multiple base stations can improve coverage, system throughput, and cell-edge throughput for future cellular systems. In this paper, we study the coordinated reception of transmitted signals at multiple MIMO base stations to exploit cooperative diversity. In particular, we propose to employ cooperative multicell automatic repeat request (ARQ) protocol via backhaul links. The attractiveness of this protocol is that processing between coordinated base stations can be made completely transparent to the mobile user, and it improves the mobile user's link reliability and throughput significantly compared to noncooperative ARQ protocol. In our proposed protocol, we consider the scenario where the multicell processing involves one of the following three schemes: decode-and-forward, amplify-and-forward, and compress-and-forward schemes. We derive the average packet error rate and throughput for these cooperative multicell ARQ protocols. Numerical results show that the cooperative multicell ARQ protocols are promising in terms of average packet error rate and throughput. Furthermore, we show that the degree of improvement depends on the type of cooperative multicell ARQ protocol employed and the operating average signal-to-noise ratio of the main and backhaul links.

This paper presents a step-up/step-down DC-DC converter using a digital dither technique to achieve high efficiency and small output voltage ripple for portable electronic devices. The proposed control method minimizes not only the switching loss by operating like a pure buck or boost converter, but also the conduction loss by reducing the average inductor current even when four switches are used. Digital dither control is introduced to implement a buffer region for smooth transition between buck and boost modes. A minimum ripple dither with higher fundamental frequency is adopted to decrease the output voltage ripple. A window delay-line analog to digital converter (ADC) with delay calibration is achieved to digitalize the control voltage. The step-up/step-down DC-DC converter has been designed with a standard 0.5 µm CMOS process. The output voltage is regulated within the input voltage ranged from 2.5 V to 5.5 V, and the output voltage ripple is reduced to less than 25 mV during the mode transition. The peak power efficiency is 96%, and the maximum load current can reach 800 mA.

This paper presents a high-performance dual-issue 32-core SIMD platform for image and video processing. The SIMD cores support 8/16 bits SIMD MAC instructions, and vertical vector access. Eight cores with a 4-ports L2 cache are connected by CIB bus as a cluster. Four clusters are connected by mesh network. This hierarchical network can provide more than 192 GB/s low latency inter-core BW in average. The 4-ports L2 cache architecture is also designed to provide 192 GB/s L2 cache BW. To reduce coherence operation in large-scale SMP, an application specified protocol is proposed. Compared with MOESI, 67.8% of L1 cache energy can be saved in 32 cores case. The whole system including 32 vector cores, 256 KB L2 cache, 64-bit DDRII PHY and two PLL units, occupy 25 mm2 in 65 nm CMOS. It can achieve a peak performance of 375 GMACs and 98 GMACs/W at 1.2 V.

The purpose of this paper is to present the static and dynamic characteristics and a smart design approach for the digital PID control forward type multiple-output dc-dc converter. The central problem of a smart design approach is how to decide the integral coefficient. Since the integral coefficient decision depends on the static characteristics, whatever integral coefficient is selected will not be yield superior dynamic characteristics. Accordingly, it is important to identify the integral coefficient that optimizes static as well as dynamic characteristics. In proposed design approach, it set the upper and lower of input voltage and output current of regulation range. The optimal integral coefficient is decided by the regulation range of the static characteristics and the dynamic characteristics and then the smart design approach is summarized. As a result, the convergence time is improved 50% compared with the conventional designed circuit.

This work addresses the problem of a fast packet retransmission scheme intended for transporting delay-sensitive flows in a Cooperative Diversity (CD) environment. This cooperative fast retransmission scheme exploits the advantages of the CD environment and hybrid Automatic-Repeat-reQuest (ARQ), while allowing retransmission just one time via a cooperating user (i.e., partner) or via both the sender and the partner simultaneously. Complementary link packets are used for the retransmission whose policy can be adjusted on the basis of the qualities of channels among the sender, the partner and the receiver, as well as the application layer protocol data unit size, using the application throughput as the objective. For this scheme, we first derive the application throughput formulas which are then verified via simulations. Next, the CD-based optimized fast retransmission scheme is shown able to achieve better effective throughput (goodput) than other CD-based or non-CD-based ARQ schemes in various Nakagami-m slow-fading environments. As a result, the proposed scheme should be an excellent fast retransmission mechanism for real-time multimedia transport in many CD environments.

In this paper, a distributed cooperative multicell beamforming algorithm is proposed, and a detail analysis and solving method for instantaneous and statistical channel state information (CSI) are presented. Firstly, an improved distributed iterative beamforming algorithm is proposed for the multiple-input single-output interference channel (MISO IC) scenario which chooses virtual signal-to-interference-and-noise (SINR) as decision criterion to initialize and then iteratively solves the constrained optimization problem of maximizing the virtual SINR for a given level of generated interference to other users. Then, the algorithm is generalized to the multicell date sharing scenario with a heuristics power allocation scheme based on a viewpoint of the layered channel. Finally, the performance is illustrated through numerical simulations.

Telecommunications networks have become an important social infrastructure, and their robustness is considered to be a matter of social significance. Conventional network planning methods are generally based on the maximum volume of ordinary traffic and only assume explicitly specified failure scenarios. Therefore, present networks have marginal survivability against multiple failures induced by an extraordinarily high volume of traffic generated during times of natural disasters or popular social events. This paper proposes a telecommunications network planning method based on probabilistic risk assessment. In this method, risk criterion reflecting the degree of risk due to extraordinarily large traffic loads is predefined and estimated using probabilistic risk assessment. The probabilistic risk assessment can efficiently calculate the small but non-negligible probability that a series of multiple failures will occur in the considered network. Detailed procedures for the proposed planning method are explained using a district mobile network in terms of the extraordinarily large traffic volume resulting from earthquakes. As an application example of the proposed method, capacity dimensioning for the local session servers within the district mobile network is executed to reduce the risk criterion most effectively. Moreover, the optimum traffic-rerouting scheme that minimizes the estimated risk criterion is ascertained simultaneously. From the application example, the proposed planning method is verified to realize a telecommunications network with sufficient robustness against the extraordinarily high volume of traffic caused by the earthquakes.

In Long-Term Evolution (LTE)-Advanced, a heterogeneous network in which femtocells and picocells overlay macrocells is being extensively discussed in addition to traditional well-planned macrocell deployment to improve further the system throughput. In heterogeneous network deployment, cell selection as well as inter-cell interference coordination (ICIC) is very important to improve the system and cell-edge throughput. Therefore, this paper investigates three cell selection methods associated with ICIC in heterogeneous networks in the LTE-Advanced downlink: Signal-to-interference plus noise power ratio (SINR)-based cell selection, reference signal received power (RSRP)-based cell selection, and reference signal received quality (RSRQ)-based cell selection. The results of simulations (4 picocells and 25 sets of user equipment are uniformly located within 1 macrocell) that assume a full buffer model show that the downlink cell and cell-edge user throughput levels of RSRP-based cell selection are degraded by approximately 2% and 11% compared to those for SINR-based cell selection under the condition of maximizing the cell-edge user throughput due to the impairment of the interference level. Furthermore, it is shown that the downlink cell-edge user throughput of RSRQ-based cell selection is improved by approximately 5%, although overall cell throughput is degraded by approximately 6% compared to that for SINR-based cell selection under the condition of maximizing the cell-edge user throughput.

Downlink multi-point transmission as a capacity enhancement method for the users at cell edge and the operators is studied in this paper. It is based on the so-called aggregate base station architecture using distributed antennas and cloud computing. Its advantages are analyzed by both its architectural side and simulation. The simulation results show that the capacity may be affected by the number of cell belonging to an aggregate base station and by the parameters related to the operation of it.