Simultaneous wavelength conversion utilizing four-wave mixing in optically-pumped GaN/AlN intersubband optical amplifiers has been investigated by means of a finite-difference time-domain (FDTD) model. The conversion efficiencies at a pump power of +7-+10 dBm were predicted to be -9-+6 dB depending on the frequency detuning (0.3-10.9 THz). The difference in efficiency among 18 channels of WDM signals with 100-GHz spacing was within about 3 dB.

This paper proposes the use of the ratio of wavelet extrema numbers taken from the horizontal and vertical counts respectively as a texture feature, which is called aspect ratio of extrema number (AREN). We formulate the classification problem upon natural and synthesized texture images as an optimization problem and develop a coevolving approach to select both scalar wavelet and multiwavelet feature spaces of greater discriminatory power. Sequential searches and genetic algorithms (GAs) are comparatively investigated. The experiments using wavelet packet decompositions with the innovative packet-tree selection scheme ascertain that the classification accuracy of coevolutionary genetic algorithms (CGAs) is acceptable enough.

Bit-errors in a subband of a wavelet-based video frame during network transmission affect not only lower-level subbands within the same frame but also the subsequent frames. This is because the video frame is wavelet-transformed image with multi-levels and referenced from later frames. In this paper, we propose a new motion estimation scheme for wavelet-based video called Intra-frame Motion Estimation (IME), in which each subband except the LL subband refers to the 1-level-lower subband in the same orientation within the same frame. This scheme protects video quality by confining the effects of the bit-errors of all subbands, except the LL subband, within a frame. We evaluated the performance of our proposed scheme in a simulated wireless network environment. As a result of tests, it was shown that the proposed IME algorithm performs better than MRME, a motion-compensated video coding scheme for wavelet video, in a heavy motion video sequence, while IME outperforms MRME at a high bit-rate in small motion video sequence.

We developed a new millimeter-wave plastic chip size package (CSP) to operate up to 100 GHz by using a thin-film substrate. It has a flip-chip distributed amplifier with inverted microstrip lines and the amplifier has a bandwidth of beyond 110 GHz. The transmission line on the substrate consists of grounded coplanar waveguides that yield low insertion loss and high isolation characteristics in coupled lines even in mold resin in comparison with conventional microstrip lines. The CSP amplifier achieved a gain of 7.8 dB, a 3-dB bandwidth of 97 GHz, and operated up to 100 GHz. To the best of our knowledge, this value is the highest operating frequency reported to date for a distributed amplifier sealed in a plastic CSP. We also investigated the transmission characteristics of lead-free solder bumps through experiments by assemblying CSPs on printed circuit boards and modeling them so that we could design the packages accurately.

This paper proposes several novel hierarchical interconnection networks based on the (3, 3)-graphs, namely folded (3, 3)-networks, root-folded (3, 3)-networks, recursively expanded (3, 3)-networks, and flooded (3, 3)-networks. Just as the hypercubes, CCC, Peterson-based networks, and Heawood-based networks, these hierarchical networks have the following nice properties: regular topology, high scalability, and small diameters. Due to these important properties, these hierarchical networks seem to have the potential as alternatives for the future interconnection structures of multicomputer systems, especially massively parallel processors (MPPs). Furthermore, this paper will present the routing and broadcasting algorithms for these proposed networks to demonstrate that these algorithms are as elegant as the algorithms for hypercubes, CCC, and Petersen- or Heawood-based networks.

This paper proposes an efficient query evaluation scheme for a mediator system intended to integrate heterogeneous computing environment in terms of operating systems, database management systems, and other software. Most of mediator systems transform a global query into a set of sub-queries based on their target remote servers. Each sub-query is evaluated by the query modification method to evaluate a global query. However, it is possible to reduce the evaluation cost of a global query when the results of frequently requested sub-queries are materialized in a mediator. In a mediator, its integrating schema can be incrementally modified and the evaluation frequency of a global query can also be continuously varied. In order to select the optimized set of materialized sub-queries with respect to their current evaluation frequencies, the proposed method applies a decay factor for modeling the recent access behavior of each sub-query. In other words, the latest access of a sub-query gets the highest attention in the selection process of materialized sub-queries. As a result, it is possible to adjust the optimized set of materialized sub-queries adaptively according to the recent changes in the evaluation frequencies of sub-queries. Since finding the optimum solution of this problem is NP-hard, it takes too long to be used in practice when the number of sub-queries is large. Consequently, given the size of mediator storage, the rank-based selection algorithm proposed in this paper finds the set of materialized sub-queries which minimizes the total evaluation cost of global queries in linear search complexity.

A flexible and robust rate-distortion optimization algorithm is presented to select macroblock coding mode for H.264/AVC transmission over wireless channels subject to burst errors. A two-state Markov model is used to describe the burst errors on the packet level. With the feedback information from the receiver and the estimation of the channel errors, the algorithm analyzes the distortion of the reconstructed macroblock at the decoder due to the channel errors and spatial and temporal error propagation. The optimal coding mode is chosen for each macroblock in rate-distortion (R-D)-based framework. Experimental results using the H.264/AVC test model show a significant performance of resilience to the burst errors.

Techniques for automatic program recognition, at the algorithmic level, could be of high interest for the area of Software Maintenance, in particular for knowledge based reengineering, because the selection of suitable restructuring strategies is mainly driven by algorithmic features of the code. In this paper an automated hierarchical concept parsing recognition technique, and a formalism for the specification of algorithmic concepts, is presented. Based on this technique, the design and development of ALCOR, a production rule based system for automatic recognition of algorithmic concepts within programs, aimed at support of knowledge based reengineering for high performance, is presented.

Scientific computations for diffusion equations and ANNs (Artificial Neural Networks) are data intensive tasks accompanied by heavy memory access; on the other hand, their computational complexities are relatively low. Thus, this type of tasks naturally maps onto SIMD (Single Instruction Multiple Data stream) parallel processing with distributed memory. This paper proposes a high performance acceleration processor of which architecture is optimized for scientific computing using diffusion equations and ANNs. The proposed architecture includes a customized instruction set and specific hardware resources which consist of a control unit (CU), 16 processing units (PUs), and a non-linear function unit (NFU) on chip. They are effectively connected with dedicated ring and global bus structure. Each PU is equipped with an address modifier (AM) and 16-bit 1.5 k-word local memory (LM). The proposed processor can be easily expanded by multi-chip expansion mode to accommodate to a large scale parallel computation. The prototype chip is implemented with FPGA. The total gate count is about 1 million with 530, 432-bit embedded memory cells and it operates at 15 MHz. The functionality and performance of the proposed processor is verified with simulation of oil reservoir problem using diffusion equations and character recognition application using ANNs. The execution times of two applications are compared with software realizations on 1.7 GHz Pentium IV personal computer. Though the proposed processor architecture and the instruction set are optimized for diffusion equations and ANNs, it provides flexibility to program for many other scientific computation algorithms.

Fault-tolerance is an essential feature of the distributed systems where the possibility of a failure increases with the growth of the system. In spite of extensive researches over two decades, fault-tolerance systems have not succeeded in practical use. It is due to the high overhead and the unhandiness of the previous fault-tolerance systems. In this paper, we propose MPICH-GF, a user-transparent checkpointing system for grid-enabled MPICH. Our objectives are to fill the gap between the theory and the practice of fault-tolerance systems, and to provide a checkpointing-recovery system for grids. To build a fault-tolerant MPICH version, we have designed task migration, dynamic process management, and atomic message transfer. MPICH-GF requires no modification of application source codes, and it affects the MPICH communication characteristics as less as possible. The features of MPICH-GF are that it supports the direct message transfer mode and that all of the implementation has been done at the lower layer, that is, the abstract device level. We have evaluated MPICH-GF using NPB applications on Globus middleware.

A new excitation enhancement technique based on a harmonic model is proposed in this paper to improve the speech quality of low-bit-rate speech coders. This technique is employed only in the decoding process of speech coders and improves high-frequency components of excitation. We develop the procedure of harmonic model parameters estimation and harmonic generation and apply the technique to a current state-of-art low bit rate speech coder. Experiments on spectrum reading and spectrum distortion measurement show that the proposed excitation enhancement technique improves speech quality.

We have developed a novel basic technology for terahertz (THz) imaging, which allows detection and identification of chemicals by introducing the component spatial pattern analysis. The spatial distributions of the chemicals were obtained from terahertz multispectral transillumination images, using absorption spectra previously measured with a widely tunable THz-wave parametric oscillator. We have also separated the component spatial patterns of frequency-dependent absorptions in chemicals and frequency-independent components such as plastic, paper and measurement noise in THz spectroscopic images. Further we have applied this technique to the detection and identification of illicit drugs concealed in envelopes.

In 1987, Ito, Saito and Nishizeki proposed a secret sharing scheme realizing general access structures, called the multiple assignment secret sharing scheme (MASSS). In this paper, we propose new MASSS's which are perfect secret sharing schemes and include Shamir's (k,n)-threshold schemes as a special case. Furthermore, the proposed schemes are more efficient than the original MASSS from the viewpoint of the number of shares distributed to each participant.

In this paper, the optimal assignment problem which assigns cells in PCS (Personal Communication Service) to switches on ATM (Asynchronous Transfer Mode) network is investigated. The cost considered in this paper has two components: one is the cost of handoff that involves two switches, and the other is the cost of cabling. This problem assumes that each cell in PCS can be assigned to two switches in ATM network. This problem is modelled as dual-homing cell assignment problem, which is a complex integral linear programming (ILP) problem. Since finding an optimal solution of this problem is NP-hard, a hybrid method which combines several heuristics and a stochastic search method (based on a simulated annealing(SA) approach) is proposed to solve this problem. The solution method consists of three phases: Primary Assignment Decision Phase (PADP), Secondary Assignment Decision Phase (SADP) and Refinement Phase (RP). The PADP and SADP are used to find good initial assignment, then domain-dependent heuristics are encoded into perturbations of SA in Refinement Phase to improve the result. Simulation results show that the proposed hybrid method is robust for this problem.

This paper presents a prototype of a distributed 3D rendering system in a hierarchical Grid environment. 3D rendering with massive data sets is a computationally intensive task. In order to make full use of computational resources on Grids, a hierarchical system architecture is designed to run over multiple clusters. This architecture involves both sort-first and sort-last parallel rendering algorithms to achieve excellent scalability, rendering performance and load balance.

A face recognition system based on the hard-limited eigenfunctions derived from the Karhunen-Loeve transform is proposed. The key of this approach is to change the inner product of the face image and the selected eigenvectors from floating point arithmetic to integer arithmetic. A database with 1000 facial images corresponding to 100 subjects is collected for system evaluation. It is demonstrated that 92% correct classification rate and 6-fold computational time saving can be achieved by the use of the first 150 hard-limited features.

This paper presents a local learning framework in which the local classifiers can be pre-learned and the support size of each classifier can be selected to minimize the error bound. The proposed algorithm is compared with the conventional support vector machine (SVM). Experimental results show that our scheme using the user-defined parameters C and σ is more accurate and less sensitive than the conventional SVM.

In this letter we suggest sets of features to classify genres of web documents. Web documents are different from textual documents in that they contain URL and HTML tags within the pages. We introduce the features specific to web documents, which are extracted from URL and HTML tags. Experimental results enable us to evaluate their characteristics and performances. On the basis of the experimental results, we implement a user interface of a web search engine that presents documents grouped by genres.

We have developed Multi-modal Neural Networks (MNN) to improve the accuracy of symbolic sequence pattern classification. The basic structure of the MNN is composed of several sub-classifiers using neural networks and a decision unit. Two types of the MNN are proposed: a primary MNN and a twofold MNN. In the primary MNN, the sub-classifier is composed of a conventional three-layer neural network. The decision unit uses the majority decision to produce the final decisions from the outputs of the sub-classifiers. In the twofold MNN, the sub-classifier is composed of the primary MNN for partial classification. The decision unit uses a three-layer neural network to produce the final decisions. In the latter type of the MNN, since the structure of the primary MNN is folded into the sub-classifier, the basic structure of the MNN is used twice, which is the reason why we call the method twofold MNN. The MNN is validated with two benchmark tests: EPR (English Pronunciation Reasoning) and prediction of protein secondary structure. The reasoning accuracy of EPR is improved from 85.4% by using a three-layer neural network to 87.7% by using the primary MNN. In the prediction of protein secondary structure, the average accuracy is improved from 69.1% of a three-layer neural network to 74.6% by the primary MNN and 75.6% by the twofold MNN. The prediction test is based on a database of 126 non-homologous protein sequences.

The configuration and operation of an all-optical 3R-regenerator for high-speed data transmission are described. An all-optical 3R-regenerator using a fiber-based optical switch is proposed and successfully demonstrated in a 160 Gbit/s 3R-regenerating transmission experiment.