We attempted to estimate subjective scores of the Japanese Diagnostic Rhyme Test (DRT), a two-to-one forced selection speech intelligibility test. We used automatic speech recognizers with language models that force one of the words in the word-pair, mimicking the human recognition process of the DRT. Initial testing was done using speaker-independent models, and they showed significantly lower scores than subjective scores. The acoustic models were then adapted to each of the speakers in the corpus, and then adapted to noise at a specified SNR. Three different types of noise were tested: white noise, multi-talker (babble) noise, and pseudo-speech noise. The match between subjective and estimated scores improved significantly with noise-adapted models compared to speaker-independent models and the speaker-adapted models, when the adapted noise level and the tested level match. However, when SNR conditions do not match, the recognition scores degraded especially when tested SNR conditions were higher than the adapted noise level. Accordingly, we adapted the models to mixed levels of noise, i.e., multi-condition training. The adapted models now showed relatively high intelligibility matching subjective intelligibility performance over all levels of noise. The correlation between subjective and estimated intelligibility scores increased to 0.94 with multi-talker noise, 0.93 with white noise, and 0.89 with pseudo-speech noise, while the root mean square error (RMSE) reduced from more than 40 to 13.10, 13.05 and 16.06, respectively.

This paper proposes a feature-based service identification method to improve productivity using a feature relationship; where a feature can express service properties. We define the distance measured between features by considering their selective (node) and relational (edge) attributes and present the service boundary concept. The result of an evaluation of the proposed method shows that it has higher productivity than existing methods.

When P2P systems are used for data sensitive systems, the data availability has become an important issue. The availability-based replication using individual node availability is the most popular method keeping high data availability efficiently. However, since the individual node availability is derived by the individual lifetime information of each node, the availability-based replication may select useless replicas. In this paper, we explore the relative MTTF (Mean Time To Failure)-based incentive scheme for the more efficient availability-based replication. The relative MTTF is used to classify the guaranteed replicas which can get the incentive node availability, and these replicas help reduce the data traffic and the number of replicas without losing the target data availability. Results from trace-driven simulations show that the replication using our relative MTTF-based incentive scheme achieves the same target data availability with 41% less data traffic and 24% less replicas.

The Firing Squad Synchronization Problem (FSSP), one of the most well-known problems related to cellular automata, was originally proposed by Myhill in 1957 and became famous through the work of Moore [1]. The first solution to this problem was given by Minsky and McCarthy [2] and a minimal time solution was given by Goto [3]. A significant amount of research has also dealt with variants of this problem. In this paper, from a theoretical interest, we will extend this problem to number patterns on a seven-segment display. Some of these problems can be generalized as the FSSP for some special trees called segment trees. The FSSP for segment trees can be reduced to a FSSP for a one-dimensional array divided evenly by joint cells that we call segment array. We will give algorithms to solve the FSSPs for this segment array and other number patterns, respectively. Moreover, we will clarify the minimal time to solve these problems and show that there exists no such solution.

Power-aware scheduling problem has been a recent issue in cluster systems not only for operational cost due to electricity cost, but also for system reliability. In this paper, we provide SLA-based scheduling algorithms for bag-of-tasks applications with deadline constraints on power-aware cluster systems. The scheduling objective is to minimize power consumption as long as the system provides the service levels of users. A bag-of-tasks application should finish all the sub-tasks before the deadline as the service level. We provide the power-aware scheduling algorithms for both time-shared and space-shared resource sharing policies. The simulation results show that the proposed algorithms reduce much power consumption compared to static voltage schemes.

This paper proposes approaches to perform HW/SW (Hardware/Software) partition and parallelization of computing-intensive tasks of the H.264 HiP (High Profile) decoding algorithm on an embedded coarse-grained reconfigurable multimedia system, called REMUS (REconfigurable MUltimedia System). Several techniques, such as MB (Macro-Block) based parallelization, unfixed sub-block operation etc., are utilized to speed up the decoding process, satisfying the requirements of real-time and high quality H.264 applications. Tests show that the execution performance of MC (Motion Compensation), deblocking, and IDCT-IQ (Inverse Discrete Cosine Transform-Inverse Quantization) on REMUS is improved by 60%, 73%, 88.5% in the typical case and 60%, 69%, 88.5% in the worst case, respectively compared with that on XPP PACT (a commercial reconfigurable processor). Compared with ASIC solutions, the performance of MC is improved by 70%, 74% in the typical and in the worst case, respectively, while those of Deblocking remain the same. As for IDCT_IQ, the performance is improved by 17% no matter in the typical or worst case. Relying on the proposed techniques, 1080p@30 fps of H.264 HiP@ Level 4 decoding could be achieved on REMUS when utilizing a 200 MHz working frequency.

It is known that wireless ad hoc networks employing omnidirectional communications suffer from poor network throughput due to inefficient spatial reuse. Although the use of directional communications is expected to provide significant improvements in this regard, the lack of efficient mechanisms to deal with deafness and hidden terminal problems makes it difficult to fully explore its benefits. The main contribution of this work is to propose a Medium Access Control (MAC) scheme which aims to lessen the effects of deafness and hidden terminal problems in directional communications without precluding spatial reuse. The simulation results have shown that the proposed directional MAC provides significant throughput improvement over both the IEEE802.11DCF MAC protocol and other prominent directional MAC protocols in both linear and grid topologies.

The performance of the kernel-based learning algorithms, such as SVM, depends heavily on the proper choice of the kernel parameter. It is desirable for the kernel machines to work on the optimal kernel parameter that adapts well to the input data and the learning tasks. In this paper, we present a novel method for selecting Gaussian kernel parameter by maximizing a class separability criterion, which measures the data distribution in the kernel-induced feature space, and is invariant under any non-singular linear transformation. The experimental results show that both the class separability of the data in the kernel-induced feature space and the classification performance of the SVM classifier are improved by using the optimal kernel parameter.

This paper proposes a new hybrid method for machine transliteration. Our method is based on combining a newly proposed two-step conditional random field (CRF) method and the well-known joint source channel model (JSCM). The contributions of this paper are as follows: (1) A two-step CRF model for machine transliteration is proposed. The first CRF segments a character string of an input word into chunks and the second one converts each chunk into a character in the target language. (2) A joint optimization method of the two-step CRF model and a fast decoding algorithm are also proposed. Our experiments show that the joint optimization of the two-step CRF model works as well as or even better than the JSCM, and the fast decoding algorithm significantly decreases the decoding time. (3) A rapid development method based on a weighted finite state transducer (WFST) framework for the JSCM is proposed. (4) The combination of the proposed two-step CRF model and JSCM outperforms the state-of-the-art result in terms of top-1 accuracy.

This paper investigates the communication range and interference range of millimeter-wave wireless personal area networks (WPAN) based on realistic system design. Firstly, the effective communication range of the millimeter-wave networks are calculated based on realistic physical (PHY) layer design and 60 GHz channel obtained from actual measurements. Secondly, an interference model is developed to facilitate the analysis of the impact of interferer-to-victim range on the victim link performance. It is found that system with BPSK modulation is able to support use cases with higher number of portable devices within a 3 m range, while system with 16QAM modulation is more suitable for fixed high speed data streaming devices within a shorter range of 1 m. Also, the interferer-to-victim range that causes no interference in all conditions is found to be approximately 40 m, while a 25 m range causes a typical bit error rate (BER) degradation of 1-digit (e.g. BER = 10-6 to 10-5).

To reduce the manufacturing cost of SoCs with many embedded SRAMs, we propose a scheme to reduce the area per good die for the SoC memory built-in self-test (MBIST). We first propose BIST hardware overhead reduction by application of an encoder-based comparator. For the repair of a faulty SRAM module with 2-D redundancy, we propose spare assignement algorithm. Based on an existing range-cheking-first algorithm (RCFA), we propose assign-all-row-RCFA (A-RCFA) which assign unused spare rows to faulty ones, in order to suppress the degradation of repair rate due to compressed fail location information output from the encoder-based comparator. Then, considering that an SoC has many SRAM modules, we propose a heuristic algorithm based on iterative improvement algorithm (IIA), which determines whether each SRAM should have a spare row or not, in order to minimize area per a good die. Experimental results on practical scale benchmark SoCs with more than 1,000 SRAM modules indicate that encoder-based comparators reduce hardware overhead by about 50% compared to traditional ones, and that combining the IIA-based algorithm for determining redundancy architecture with the encoder-based comparator effectively reduces the area per good die.

It is known that traditional water-filling provides a closed form solution for capacity maximization in frequency-selective channels or fading channels with adaptive modulation. However, the solution is derived from a maximum mutual information argument with a single total power constraint. Motivated by the new technology of coordinated multiple point transmission (CoMP), this paper considers a novel power allocation scheme for a frequency-selective fading channel with multiple coordinated transmission points (CTP) transmission, in which each CTP has a power constraint and an individual channel state information (CSI). In order to maximize the channel's throughput, closed form solutions are obtained by solving a non-convex constrained optimization problem. The solution turns out to take the form of traditional WF and also combined with some regular cooperative feature. Based on the derived solution, we firstly investigate a joint water-filling (Jo-WF) power allocation scheme and a new iterative Jo-WF algorithm. Numerical results are presented to verify the optimality of the derived scheme and to show throughput gains over traditional non-coordinated water-filling (WF) and equal power allocation (EPA). Considering the flexibility of CTP's category, e.g., base station or relay station, it is known that the derived Jo-WF power allocation scheme can be valid for any coordinated networks such as next-generation cellular networks or ad-hoc networks.

This paper describes ultra wideband (UWB) radio propagation measurements and modeling for wireless body area network (WBAN) applications in different environments. Several propagation measurement campaigns and associated modelings were carried out in either a radio anechoic chamber or a specific room type; however, dependence of the radio propagation on surrounding environments was not studied. Multipaths (mainly reflected from floor, ceiling, and walls) highly depend on the environment. To address this problem, radio propagation around the human body was measured in a radio anechoic chamber and four different-sized rooms. Parameters in a conventional loss model derived from the measurements were found to significantly diverge and depend on room volume and line-of-sight (LOS)/non-LOS (NLOS) cases. A modified model considering the impact of room volume has been proposed for the LOS/NLOS cases. Different propagation mechanisms were discussed along with parameter derivation. Probability distributions for the UWB propagation losses were also examined.

In wireless OFDM systems, the system performance is suffered from frequency offset and symbol timing offset due to the Doppler effect. Using the discrete Fourier transform (DFT) and inverse discrete Fourier transform (IDFT) for traditional signal transformation from the time-domain into frequency-domain, and vice versa, the system performance may be severely degraded. To make the OFDM system that can tolerate the above problems, we have considered that the harmonic transform can be applicable to the traditional signal transformation, thereby improving the system performance. In this paper, we combine the good characteristics of harmonic transform and instantaneous frequency to be a novel transformation for wireless OFDM systems. We propose a modified discrete harmonic transform (MDHT) which can be performed adaptively. Our proposed scheme called the modified discrete harmonic transform OFDM (MDHT-OFDM scheme). We derive the equations of the novel discrete harmonic transform which are suitable for wireless OFDM systems and the novel channel estimation cooperated with the novel transformation. The proposed channel estimation is performed in both time-domain and frequency-domain. The performance of a MDHT-OFDM scheme is evaluated by means of a simulation. We compare the performance of a MDHT-OFDM scheme with one of the conventional DFT-OFDM scheme in the term of symbol error rate (SER). MDHT-OFDM scheme can achieve better performance than that of the conventional DFT-OFDM scheme in mitigating the Doppler spread.

Base station (BS) cooperation is a promising technique to suppress co-channel interference for cellular networks. However, practical limitations constrain the scale of cooperation, thus the network is divided into small disjoint BS cooperation groups, namely clusters. A decentralized scheme for BS cluster formation is proposed based on efficient BS negotiations, of which the feedback overhead per user is nearly irrelevant to the network size, and the number of iteration rounds scales very slowly with the network size. Simulations show that our decentralized scheme provides significant sum-rate gain over static clustering and performs almost the same as the existing centralized approach. The proposed scheme is well suited for large-scale cellular networks due to its low overhead and complexity.

We have investigated the bottleneck in web-based MORPG system and proposed a load-distribution method using multiple web servers. This technique uses a dynamic data allocation method, called the moving home. This paper describes the evaluation of our method using 4, 8, 16 web servers. We evaluated it on both the single-server system and multi-server system. And we confirm that the effect of the moving home through the comparison between the multi-server system without the moving home and that with the moving home. Our experimental result shows that the upper bound of the number of avatars in the eight-server system with the moving home becomes 380 by contrast that in the single-server system is 200.

The demand for data/audio streaming/video streaming multicast services in large scale networks has been increasing. Moreover, the improved transmission speed and mobile-device capability in wireless access networks enable people to use such services via their personal mobile devices. Peer-to-peer (P2P) architecture ensures scalability and robustness more easily and more economically than server-client architecture; as the number of nodes in a P2P network increases, the amount of workload per node decreases and lessens the impact of node failure. However, mobile users feel much larger psychological cost due to strict limitations on bandwidth, processing power, memory capacity, and battery life, and they want to minimize their contributions to these services. Therefore, the issue of how we can reduce this psychological cost remains. In this paper, we consider how effective a social networking service is as a platform for mobile P2P multicast. We model users' cooperative behaviors in mobile P2P multicast streaming, and propose a social-network based P2P streaming architecture for mobile networks. We also measured the psychological forwarding cost of real users in mobile P2P multicast streaming through an emulation experiment, and verify that our social-network based mobile P2P multicast streaming improves service quality by reducing the psychological forwarding cost using multi-agent simulation.

We develop a mathematical framework for the extrinsic information transfer (EXIT) analysis to assess the convergence behavior of maximum a posteriori (MAP)-based joint iterative decoding of correlated sources, which are separately encoded and transmitted over noisy channels. Unlike the previous work, our approach focuses on the case side information about the correlation is not perfectly given at the joint decoder but is extracted from decoder output and updated in an iterative manner. The presented framework provides a convenient way to compare between schemes. We show that it allows us to easily and accurately predict joint decoding gain and turbo cliff position.

This paper proposes a medium access control (MAC) mechanism for the recently developed IEEE 802.15.4 standard, a promising candidate to become the physical (PHY) and MAC layer standard for Wireless Sensor Networks (WSNs). The main concern in WSNs is the energy consumption, and this paper presents a mechanism that adapts properly the duty cycle operation according to the traffic conditions. Various traffic adaption mechanisms have been presented for the MAC layer of the IEEE 802.15.4. However these conventional mechanisms only consider the temporal traffic fluctuations. The proposed mechanism outperforms the conventional mechanism when applied to cluster-tree based WSNs, because it considers not only the temporal fluctuations but also the spatial (geographical) fluctuations, which are intrinsic characteristics of traffic in WSNs with the cluster tree topology. Evaluations showed that the proposed mechanism achieves less energy consumption than the conventional traffic adaptation mechanism, with maintaining almost the same transmission performance.

A stacked rectangular microstrip antenna with a shorting plate and a helical pin is proposed as a car antenna for triple band operation in ITS. The proposed antenna operates as a conventional stacked microstrip antenna at the highest frequency band. At the middle and the lowest frequency bands, the antenna radiates at low elevation angles from the helical pin and the shorting plate. In this paper, as an example of triple band antennas in the ITS, an antenna is designed that supports PHS, VICS and ETC. The proposed antennas have the proper radiation pattern for each application and are small in size.