Recent rapid development of high-speed wireless access technologies has created mixed WLAN (Wireless LAN) environments where QoS capable APs coexist with legacy APs. To provide QoS guarantee in this mixed WLAN environment, this paper proposes a new AP selection algorithm. The proposed algorithm assigns an STA (Station) to an AP in the overall WLAN service area. Simulation results show improvement in the VoIP performance in terms of an eMOS (estimated Mean Opinion Score) value and the FTP throughput compared to conventional algorithms.

This paper discusses the infinite horizon static output feedback stochastic Nash games involving state-dependent noise in weakly coupled large-scale systems. In order to construct the strategy, the conditions for the existence of equilibria have been derived from the solutions of the sets of cross-coupled stochastic algebraic Riccati equations (CSAREs). After establishing the asymptotic structure along with the positive semidefiniteness for the solutions of CSAREs, recursive algorithm for solving CSAREs is derived. As a result, it is shown that the proposed algorithm attains the reduced-order computations and the reduction of the CPU time. As another important contribution, the uniqueness of the strategy set is proved for the sufficiently small parameter ε. Finally, in order to demonstrate the efficiency of the proposed algorithm, numerical example is given.

Recently, multimedia services are increasing with the widespread use of various wireless applications such as web browsers, real-time video, and interactive games, which results in traffic asymmetry between the uplink and downlink. Hence, time division duplex (TDD) systems which provide advantages in efficient bandwidth utilization under asymmetric traffic environments have become one of the most important issues in future mobile cellular systems. It is known that two types of intercell interference, referred to as crossed-slot interference, additionally arise in TDD systems; the performances of the uplink and downlink transmissions are degraded by BS-to-BS crossed-slot interference and MS-to-MS crossed-slot interference, respectively. The resulting performance unbalance between the uplink and downlink makes network deployment severely inefficient. Previous works have proposed intelligent time slot allocation algorithms to mitigate the crossed-slot interference problem. However, they require centralized control, which causes large signaling overhead in the network. In this paper, we propose to change the shape of the cellular structure itself. The conventional cellular structure is easily transformed into the proposed cellular structure with distributed receive antennas (DRAs). We set up statistical Markov chain traffic model and analyze the bit error performances of the conventional cellular structure and proposed cellular structure under asymmetric traffic environments. Numerical results show that the uplink and downlink performances of the proposed cellular structure become balanced with the proper number of DRAs and thus the proposed cellular structure is notably cost-effective in network deployment compared to the conventional cellular structure. As a result, extending the conventional cellular structure into the proposed cellular structure with DRAs is a remarkably cost-effective solution to support asymmetric traffic environments in future mobile cellular systems.

Luminescent characteristics of BaGd4Si3O13:Tb phosphor powder including fluorine, which is synthesized at about 1000, have been investigated. This phosphor shows the green emission due to Tb3+ under VUV excitation. By incorporation of F ion based on low-temperature synthesis, the photoluminescence excitation band lying in the wavelength region from 130 to 170 nm increases drastically in comparison to BaGd4Si3O13:Tb phosphor synthesized at 1550. This phosphor is a candidate for a green PDP phosphor for both 147 nm resonance line and 172 nm excimer band of Xe plasma.

In this paper we present our investigation into improving the performance of our computer-assisted language learning (CALL) system through exploiting the acoustic model and features within the speech recognition framework. First, to alleviate channel distortion, speaker-dependent cepstrum mean normalization (CMN) is adopted and the average correlation coefficient (average CC) between machine and expert scores is improved from 78.00% to 84.14%. Second, heteroscedastic linear discriminant analysis (HLDA) is adopted to enhance the discriminability of the acoustic model, which successfully increases the average CC from 84.14% to 84.62%. Additionally, HLDA causes the scoring accuracy to be more stable at various pronunciation proficiency levels, and thus leads to an increase in the speaker correct-rank rate from 85.59% to 90.99%. Finally, we use maximum a posteriori (MAP) estimation to tune the acoustic model to fit strongly accented test speech. As a result, the average CC is improved from 84.62% to 86.57%. These three novel techniques improve the accuracy of evaluating pronunciation quality.

In the present paper, the use of a combination of channel-bonding and multi-channel techniques is proposed to improve the performance of wireless mesh networks (WMNs). It is necessary to increase the network throughput by broadening the bandwidth, and two approaches to effectively utilize the broadened bandwidth can be considered. One is the multi-channel technique, in which multiple separate frequency channels are used simultaneously for information transmission. The other is the channel-bonding technique used in IEEE 802.11n, which joins multiple frequency channels into a single broader channel. The former can reduce the channel traffic to mitigate the effect of packet collision, while the latter can increase the transmission rate. In the present paper, these two approaches are compared and their respective advantages are clarified in terms of the network throughput and delay performance assuming the same total bandwidth and a CSMA protocol. Our numerical and simulation results indicate that under low-traffic conditions, the channel-bonding technique can achieve low delay, while under traffic congestion conditions, the network performance can be improved by using multi-channel technique. Based on this result, the use of a combination of these two techniques is proposed for a WMN, and show that it is better to use a proper channel technique according to the network traffic condition. The findings of the present study also contribute to improving the performance of a multimedia network, which consists of different traffic types of applications.

In this paper, we give some resuts on primitive words, square-free words and disjunctive languages. We show that for a word u ∈Σ+, every element of λ(cp(u)) is d-primitive iff it is square-free, where cp(u) is the set of all cyclic-permutations of u, and λ(cp(u)) is the set of all primitive roots of it. Next we show that pmqn is a primitive word for every n, m ≥1 and primitive words p, q, under the condition that |p| = |q| and (m, n) ≠ (1, 1). We also give a condition of disjunctiveness for a language.

This letter proposes a QoS control method for video streaming service over wireless networks. Based on statistical analysis, the time-varying MAC parameters highly related to channel condition are selected to predict available bitrate. Adaptive bitrate control of scalably-encoded video guarantees continuity in streaming service even if the channel condition changes abruptly.

In this paper, the simplified search designs for the stochastic codebook of algebraic code excited linear prediction (ACELP) for ITU-T G.729D speech coder are proposed. By using two search rounds and limiting the search range, the computational complexity of the proposed approach is only 6.25% of the full search method recommended by G.729D. In addition, the computational complexity of proposed approach is only 59% of the global pulse replacement search method recommended by G.729.1. Simulation results show that the coded speech quality evaluated by using the standard subjective and objective quality measurements is with perceptually negligible degradation.

In 2006, Miranda et al. proposed an anonymity scheme to achieve peers' anonymity in Peer-to-Peer (P2P) reputation systems. In this paper, we show that this scheme can not achieve peers' anonymity in two cases. We also propose an improvement which solves the problem and improves the degree of anonymity.

This letter studies the tracking error in Multi-input Multi-output Feedback Error Learning (MIMO-FEL) system having insufficient excitation. It is shown that the error converges to zero exponentially even if the reference signal lacks the persistently excitation (PE) condition. Furthermore, by making full use of this fast convergence, we estimate the plant parameter while in operation based on frequency response. Simulation results show the effectiveness of the proposed method compared to a conventional approach.

This letter proposes an efficient uplink scheduling algorithm for the voice over Internet protocol (VoIP) service with variable frame-duration according to the voice activity in IEEE 802.16e/m systems. The proposed algorithm dynamically changes the grant-interval to save the uplink bandwidth, and it uses the random access scheme when the voice activity changes from silent-period to talk-spurt. Numerical results show that the proposed algorithm can increase the VoIP capacity by 26 percent compared to the conventional extended real-time polling service (ertPS).

Luby et al. derived evolution of degree distributions in residual graphs for irregular LDPC code ensembles. Evolution of degree distributions in residual graphs is important characteristic which is used for finite-length analysis of the expected block and bit error probability over the binary erasure channel. In this paper, we derive detailed evolution of degree distributions in residual graphs for irregular LDPC code ensembles with joint degree distributions.

We propose an effective voice-based gender identification method using a support vector machine (SVM). The SVM is a binary classification algorithm that classifies two groups by finding the voluntary nonlinear boundary in a feature space and is known to yield high classification performance. In the present work, we compare the identification performance of the SVM with that of a Gaussian mixture model (GMM)-based method using the mel frequency cepstral coefficients (MFCC). A novel approach of incorporating a features fusion scheme based on a combination of the MFCC and the fundamental frequency is proposed with the aim of improving the performance of gender identification. Experimental results demonstrate that the gender identification performance using the SVM is significantly better than that of the GMM-based scheme. Moreover, the performance is substantially improved when the proposed features fusion technique is applied.

Embedded zero-tree image coding in wavelet domain has drawn a lot of attention. Among noteworthy algorithms is the set partitioning in hierarchical trees (SPIHT). Typically, most of images' energy is concentrated in low frequency subbands. For an image with textures, however many middle-high frequency wavelet coefficients are likely to become significant in the early passes of SPIHT; thus the coding results are often insufficient. Middle and high frequency subbands of images may demand further decompositions using adaptive basis functions. As wavelet packet transform offers a great diversity of basis functions, we propose a quad-tree based adaptive wavelet packet transform to construct adaptive wavelet packet trees for zero-tree image coding. Experimental results show that coding performances can be significantly improved especially for fingerprints images.

Using query-by-sketch we propose an application to efficiently create collages with some user interaction. Using rough color strokes that represent the target collage, images are automatically retrieved and segmented to create a seamless collage. The database is indexed using simple geometrical and color features for each region, and histograms that represent these features for each image. The image collection is then queried by means of a simple paint tool. The individual segments retrieved are added to the collage using Poisson image editing or alpha matting. The user is able to modify the default segmentations interactively, as well as the position, scale, and blending options for each object. The resulting collage can then be used as an input query to find other relevant images from the database.

The ηT pairing for supersingular elliptic curves over GF(3m) has been paid attention because of its computational efficiency. Since most computation parts of the ηT pairing are GF(3m) multiplications, it is important to improve the speed of the multiplication when implementing the ηT pairing. In this paper we investigate software implementation of GF(3m) multiplication and propose using irreducible trinomials xm+axk+b over GF(3) such that k is a multiple of w, where w is the bit length of the word of targeted CPU. We call the trinomials "reduction optimal trinomials (ROTs)." ROTs actually exist for several m's and for typical values of w = 16 and 32. We list them for extension degrees m = 97, 167, 193, 239, 317, and 487. These m's are derived from security considerations. Using ROTs, we are able to implement efficient modulo operations (reductions) for GF(3m) multiplication compared with cases in which other types of irreducible trinomials are used (e.g., trinomials with a minimum k for each m). The reason for this is that for cases using ROTs, the number of shift operations on multiple precision data is reduced to less than half compared with cases using other trinomials. Our implementation results show that programs of reduction specialized for ROTs are 20-30% faster on 32-bit CPU and approximately 40% faster on 16-bit CPU compared with programs using irreducible trinomials with general k.

The steady approach of advanced nations toward realization of ubiquitous computing societies has given birth to rapidly growing demands for new-generation distributed computing (DC) applications. Consequently, economic and reliable construction of new-generation DC applications is currently a major issue faced by the software technology research community. What is needed is a new-generation DC software engineering technology which is at least multiple times more effective in constructing new-generation DC applications than the currently practiced technologies are. In particular, this author believes that a new-generation building-block (BB), which is much more advanced than the current-generation DC object that is a small extension of the object model embedded in languages C++, Java, and C#, is needed. Such a BB should enable systematic and economic construction of DC applications that are capable of taking critical actions with 100-microsecond-level or even 10-microsecond-level timing accuracy, fault tolerance, and security enforcement while being easily expandable and taking advantage of all sorts of network connectivity. Some directions considered worth pursuing for finding such BBs are discussed.

Spectral subtraction is commonly used for speech enhancement in a single channel system because of the simplicity of its implementation. However, this algorithm introduces perceptually musical noise while suppressing the background noise. We propose a wavelet-based approach in this paper for suppressing the background noise for speech enhancement in a single channel system. The wavelet packet transform, which emulates the human auditory system, is used to decompose the noisy signal into critical bands. Wavelet thresholding is then temporally adjusted with the noise power by time-adapted noise estimation. The proposed algorithm can efficiently suppress the noise while reducing speech distortion. Experimental results, including several objective measurements, show that the proposed wavelet-based algorithm outperforms spectral subtraction and other wavelet-based denoising approaches for speech enhancement for nonstationary noise environments.

In this paper, we propose a new mask estimation method for the computational auditory scene analysis (CASA) of speech using two microphones. The proposed method is based on a hidden Markov model (HMM) in order to incorporate an observation that the mask information should be correlated over contiguous analysis frames. In other words, HMM is used to estimate the mask information represented as the interaural time difference (ITD) and the interaural level difference (ILD) of two channel signals, and the estimated mask information is finally employed in the separation of desired speech from noisy speech. To show the effectiveness of the proposed mask estimation, we then compare the performance of the proposed method with that of a Gaussian kernel-based estimation method in terms of the performance of speech recognition. As a result, the proposed HMM-based mask estimation method provided an average word error rate reduction of 61.4% when compared with the Gaussian kernel-based mask estimation method.