A novel high-speed and area-efficient Reed-Solomon decoder is proposed, which employs pipelining architecture of minimized modified Euclid (ME) algorithm. The logic synthesis and simulation results of its VLSI implementation show that it not only can operate at a higher clock frequency, but also consumes fewer hardware resources.

In this letter, we present a blind carrier frequency offset (CFO) estimator by exploiting the subspace-based technique for multicarrier-code division multiple access (MC-CDMA) systems. Relative high accuracy and low-complexity to the CFO estimation can be achieved by rooting a polynomial. Simulation results are provided for illustrating the effectiveness of the proposed blind polynomial rooting estimator.

The size-dependent array problem is a problem with systolic arrays such that the size of systolic arrays limits the size of calculations, which in a do-loop structure controls how many times it is repeated and how deep the nesting loops are. A systolic array cannot deal with larger calculations. For the size-dependent array problem, a spiral systolic array has been studied so far. It has non-adjacent connections between PEs, such as loop paths for sending data back so that data flows over the array independently of its own size. This paper takes an approach to the problem without non-adjacent connections. This paper discusses systolic messy arrays for infinite iterative algorithms so that they are independent from the size of calculations. First a systolic messy array called two-square shape is introduced then the properties of two-square shape are summarized: memory function, cyclic addition, and cyclic multiplication. Finally a way of building systolic messy arrays that calculate infinite iterative algorithms is illustrated with concrete examples such as an arithmetic progression, a geometric progression, N factorial, and Fibonacci numbers.

We present a novel training method for recognizing traffic sign symbols. The symbol images captured by a car-mounted camera suffer from various forms of image degradation. To cope with degradations, similarly degraded images should be used as training data. Our method artificially generates such training data from original templates of traffic sign symbols. Degradation models and a GA-based algorithm that simulates actual captured images are established. The proposed method enables us to obtain training data of all categories without exhaustively collecting them. Experimental results show the effectiveness of the proposed method for traffic sign symbol recognition.

Pole-tip-driven structure, which is composed of a coil wounded at the main pole tip, is favorable for obtaining a sharp and strong head field as a single-pole-type head. Three kinds of pole-tip-driven-type heads with different yoke and coil structures are investigated in terms of magnetomotive force dependence of head field and effect of coil recession. Field calculation by finite-element method (FEM) showed that the three heads exhibited the same field sensitivity in spite of the difference in distribution of coil exciting field and magnetization of the main pole. In a lower range of magnetomotive force the heads showed different dependence of field sensitivity on the coil recession. However, there was not much difference in degradation of sensitivity in a region near the saturation of field. Thus, the importance of reducing coil recession was confirmed as reported earlier.

This paper describes a novel discrimination method of pulmonary nodules based on statistical analysis of thoracic computed tomography (CT) scans. Our previous Computer-Aided Diagnosis (CAD) system can detect pulmonary nodules from CT scans, but, at the same time, yields many false positives. In order to reduce the false positives, the method proposed in the present paper uses a relationship between pulmonary nodules, false positives and image features in CT scans. The trend of variation of the relationships is acquired through statistical analysis of a set of CT scans prepared for training. In testing, by use of the trend, the method predicts the appearances of pulmonary nodules and false positives in a CT scan, and improves the accuracy of the previous CAD system by modifying the system's output based on the prediction. The method is applied to 218 actual thoracic CT scans with 386 actual pulmonary nodules. The receiver operating characteristic (ROC) analysis is used to evaluate the results. The area under the ROC curve (Az) is statistically significantly improved from 0.918 to 0.931.

In statistical pattern recognition, it is important to estimate the distribution of patterns precisely to achieve high recognition accuracy. In general, precise estimation of the parameters of the distribution requires a great number of sample patterns, especially when the feature vector obtained from the pattern is high-dimensional. For some pattern recognition problems, such as face recognition or character recognition, very high-dimensional feature vectors are necessary and there are always not enough sample patterns for estimating the parameters. In this paper, we focus on estimating the distribution of high-dimensional feature vectors with small number of sample patterns. First, we define a function, called simplified quadratic discriminant function (SQDF). SQDF can be estimated with small number of sample patterns and approximates the quadratic discriminant function (QDF). SQDF has fewer parameters and requires less computational time than QDF. The effectiveness of SQDF is confirmed by three types of experiments. Next, as an application of SQDF, we propose an algorithm for estimating the parameters of the normal mixture. The proposed algorithm is applied to face recognition and character recognition problems which require high-dimensional feature vectors.

This paper investigates the prospects and challenges of hierarchical optical path networks. The merits and issues of introducing higher order optical paths are elucidated. State of the art of the key enabling technologies are demonstrated including hierarchical optical cross-connect switch architectures, hierarchical optical path network design algorithms, a newly developed waveband filter, and waveband conversion technologies.

We propose, in this article, the Hierarchical Behavior-Knowledge Space as an extension of Behavior-Knowledge Space. Hierarchical BKS utilizes ranked level individual classifiers, and automatically expands its behavioral knowledge in order to satisfy given reliability requirement. From the statistical view point, its decisions are as optimal as those of original BKS, and the reliability threshold is a lower bound of estimated reliability. Several comparisons with original BKS and unanimous voting are shown with some experiments.

This paper reports an efficient Discrete Cosine Transform (DCT) processing method for images using a massive-parallel memory-embedded SIMD matrix processor. The matrix-processing engine has 2,048 2-bit processing elements, which are connected by a flexible switching network, and supports 2-bit 2,048-way bit-serial and word-parallel operations with a single command. For compatibility with this matrix-processing architecture, the conventional DCT algorithm has been improved in arithmetic order and the vertical/horizontal-space 1 Dimensional (1D)-DCT processing has been further developed. Evaluation results of the matrix-engine-based DCT processing show that the necessary clock cycles per image block can be reduced by 87% in comprison to a conventional DSP architecture. The determined performances in MOPS and MOPS/mm2 are factors 8 and 5.6 better than with a conventional DSP, respectively.

Various trajectories of design, arising from the new methodology of analog network design, are analyzed. Several major criteria suggested for optimal selection of initial approximation to the design process permit the minimization of computer time. The initial approximation point is selected with regard to the previously revealed effect of acceleration of the design process. The concept of separatrix is defined making it possible to determine the optimal position of the initial approximation. The numerical results obtained for passive and active networks prove the possibility of optimal choice of the initial point in design process.

This paper presents the latest trends in Generalized Multi-Protocol Label Switching (GMPLS) standardization within the Internet Engineering Task Force (IETF). GMPLS, a suite of control and management plane protocols, represents an extension of MPLS to cover any connection-oriented technology, such as packet (or MPLS), Time Division Multiplexing (TDM), lambda and fiber. GMPLS allows automated network operations, distributed at the network equipment level, with multi-vendor and multi-layer interoperability. As such, it is expected that GMPLS will enable control and management of the transport network by standardized mechanisms, rather than proprietary management systems and interfaces. In addition, GMPLS offers opportunities to integrate control and management of multiple network layers. The basic suite of GMPLS protocols, namely signaling, routing and link management, has been already standardized, and has been shown to be stable and functional through several years of testing and early deployments. Now carriers are looking at how they can leverage the protocols to realize revenue and activate advanced services. Accordingly, discussion in the IETF has shifted to how to apply GMPLS protocols to support various scenarios and use cases. After briefly reviewing GMPLS basics, this paper presents the latest trends in GMPLS standardization, with a focus on deployment strategies, service aspects, and operation and management.

The specification of a Multi-Agent System (MAS) involves the identification of a large number of entities and their relationships. This is a non-trivial task that requires managing different views of the system. Many problems concerning this issue originate in the presence of contradictory goals and tasks, inconsistencies, and unexpected behaviours. Such troublesome configurations should be detected and prevented during the development process in order to study alternative ways to cope with them. In this paper, we present methods and tools that support the management of contradictions during the analysis and design of MAS. Contradiction management in MAS has to consider both individual (i.e. agent) and social (i.e. organization) aspects, and their dynamics. Such issues have already been considered in social sciences, and more concretely in the Activity Theory, a social framework for the study of interactions in activity systems. Our approach applies knowledge from Activity Theory in MAS, especially its base of contradiction patterns. That requires a formalization of this social theory in order to be applicable in a software engineering context and its adaptation to agent-oriented methodologies. Then, it will be possible to check the occurrence of contradiction patterns in a MAS specification and provide solutions to those situations. This technique has been validated by implementing an assistant for the INGENIAS Development Kit and has been tested with several case studies. This paper shows part of one of these experiments for a web application.

In this paper, we propose a new concurrency control protocol for parallel B-tree structures capable reducing the cost of structure-modification-operation (SMO) compared to the conventional protocols such as ARIES/IM and INC-OPT. We call this protocol the MARK-OPT protocol, since it marks the lowest SMO occurrence point during optimistic latch-coupling operations. The marking reduces middle phases for spreading an X latch and removes needless X latches. In addition, we propose three variations of the MARK-OPT, which focus on tree structure changes from other transactions. Moreover, the proposed protocols are deadlock-free and satisfy the physical consistency requirement for B-trees. These indicate that the proposed protocols are suitable as concurrency control protocols for B-tree structures. To compare the performance of the proposed protocols, the INC-OPT, and the ARIES/IM, we implement these protocols on an autonomous disk system adopting the Fat-Btree structure, a form of parallel B-tree structure. Experimental results in various environments indicate that the proposed protocols always improve system throughput, and 2P-REP-MARK-OPT is the most useful protocol in high update environment. Additionally, to mitigate access skew, data should be migrated between PEs. We also demonstrate that MARK-OPT improves the system throughput under the data migration and reduces the time for data migration to balance load distribution.

Future optical code division multiple access (CDMA) networks should be designed for multirate and fully integrated multimedia services. In the conventional schemes, multilength optical orthogonal codes (OOCs) are designed to support multirate systems, while variable-weight OOCs are designed to support differentiated quality of service (QoS) for multimedia applications. In this paper, a novel class of optical signature codes; multiple-length variable-weight optical orthogonal codes (MLVW-OOC) is proposed for supporting multirate and integrated multimedia services in optical CDMA networks. The proposed MLVW-OOC has features that are easy to construct variable-weight codes and expanded to multiple-length codes. A construction method for designing MLVW-OOCs up to three levels of codes is discussed. The designed MLVW-OOCs can support differentiated requirements on data rates and QoS for several types of services in the networks. A code analysis for obtaining the value of cross-correlation constraints or multiple access interference (MAI) computation for several levels of codes is also suggested. The cross-correlation constraints of the proposed codes are better than the conventional codes such as multilength OOCs. Finally, the bit error probability performance of the two-level MLVW-OOC is evaluated analytically. The results show that the proposed MLVW-OOC can provide differentiated bit error probability performances for several combinations of data rates and QoS.

In this letter, we propose an improved global soft decision for noisy speech enhancement. From an investigation of statistical model-based speech enhancement, it is discovered that a global soft decision has a fundamental drawback at the speech tail regions of speech signals. For that reason, we propose a new solution based on a smoothed likelihood ratio for the global soft decision. Performances of the proposed method are evaluated by subjective tests under various environments and show better results compared with the our previous work.

This proposes a scalable QoS control scheme, called Elephant Flow Control Scheme (EFCS) for high-speed large-capacity networks; it controls congestion and provides appropriate bandwidth to normal users' flows by controlling just the elephant flows. EFCS introduces a sampling packet threshold and drops packets considering flow size. EFCS also adopts a compensation parameter to control elephant flows to an appropriate level. Numerical results show that the sampling threshold increases control accuracy by 20% while reducing the amount of memory needed for packet sampling by 60% amount of memory by packet sampling; the elephant flows are controlled as intended by the compensation parameter. As a result, EFCS provides sufficient bandwidth to normal TCP flows in a scalable manner.

A speech enhancement method is proposed that can be implemented efficiently due to its use of wavelet packet transform. The proposed method uses a modified spectral subtraction with noise estimation by a least-squares line method and with an overweighting gain per subband with nonlinear structure, where the overweighting gain is used for suppressing the residue of musical noise and the subband is used for applying the weighted values according to the change of signals. The enhanced speech by our method has the following properties: 1) the speech intelligibility can be assured reliably; 2) the musical noise can be reduced efficiently. Various assessments confirmed that the performance of the proposed method was better than that of the compared methods in various noise-level conditions. Especially, the proposed method showed good results even at low SNR.

As the amount of recorded TV content is increasing rapidly, people need active and interactive browsing methods. In this paper, we use both text information from closed captions and visual information from video frames to generate links to enable users to easily explore not only the original video content but also augmented information from the Web. This solution especially shows its superiority when the video content cannot be fully represented by closed captions. A prototype system was implemented and some experiments were carried out to prove its effectiveness and efficiency.

This paper proposes probabilistic pruning techniques for a Bayesian video face recognition system. The system selects the most probable face model using model posterior distributions, which can be calculated using a Sequential Monte Carlo (SMC) method. A combination of two new pruning schemes at the resampling stage significantly boosts computational efficiency by comparison with the original online learning algorithm. Experimental results demonstrate that this approach achieves better performance in terms of both processing time and ID error rate than a contrasting approach with a temporal decay scheme.