This paper summarizes power reduction methods applicable for VLSI bus systems in terms of reduction of signal swing, effective capacitance reduction and reduction of signal transition, which have been studied in authors' research group. In each method the basic concept is reviewed quickly along with some examples of its application. A future perspective is also described in conclusion.

The rapid growth of the Internet impacts ATM networks to be furnished IP handling capability. This paper discusses networking issues for IP and ATM integration. First, it considers function allocation at the boundary of an ATM backbone network and the Internet. As the result, the paper explains the necessity of built-in IP handling capability into an ATM switching system, and summarizes functional requirements for the system architecture. According to the discussion above, the authors propose the system architecture of the IP/ATM integration in the ATM switching system. The implementation of the proposed architecture is evaluated, and the wire-speed IP handling capability in the ATM switch is confirmed.

Low voltage (LV) analog circuit design techniques are addressed in this tutorial. In particular, (i) technology considerations; (ii) transistor model capable to provide performance and power tradeoffs; (iii) low voltage implementation techniques capable to reduce the power supply requirements, such as bulk-driven, floating-gate, and self-cascode MOSFETs; (iv) basic LV building blocks; (v) multi-stage frequency compensation topologies; and (vi) fully-differential and fully-balanced systems.

This paper presents a new data hiding scheme via steganographic image transformation, which is different from conventional data hiding techniques. The transformation is achieved in the frequency domain and the concept of Fourier filtering method is used. An input image is transformed into a fractal image, which can be used in Computer Graphic (CG) applications. One of the main advantages of this scheme is the amount of data to be hidden (embedded) is equal to that of the host signal (generated fractal image) while it is in general limited in the conventional data hiding schemes. Also both the opened fractal image and the hidden original one can be properly used depending on the situation. Unauthorized users will not notice the "secret" original image behind the fractal image, but even if they know that there is a hidden image it will be difficult for them to estimate the original image from the transformed image. Only authorized users who know the proper keys can regenerate the original image. The proposed method is applicable not only as a security tool for multimedia contents on web pages but also as a steganographic secret communication method through fractal images.

Two different examples have been respectively given by Aggarwal and Viswanathan to establish the necessity of (n + 2)/5 edge guards for spiral polygons. However, the former example is incorrect. To show why it is wrong, we give an alternate proof of sufficiency of (n + 2)/5 edge guards for spiral polygons. Our proof is simpler than the sufficiency proof given by Viswanathan.

Fuzzy rule-based edge detection using multiscale edge images is proposed. In this method, the edge image is obtained by fuzzy approximate reasoning from multiscale edge images which are obtained by derivative operators with various window sizes. The effect of utilizing multiscale edge images for edge detection is already known, but how to design the rules for deciding edges from multiscale edge images is not clarified yet. In this paper, the rules are represented in a fuzzy style, since edges are usually defined ambiguously, and the fuzzy rules are designed optimally by a training method. Here, the fuzzy approximate reasoning is expressed as a nonlinear function of the multiscale edge image data, and the nonlinear function is optimized so that the mean square error of the edge detection be the minimum. Computer simulations verify its high performance for actual images.

The Communications Research Laboratory (CRL), the National Astronomical Observatory (NAO), the Institute of Space and Astronoutical Science (ISAS), and the Telecommunication Network Laboratory Group of Nippon Telegraph and Telephone Corporation (NTT) have developed a very-long-baseline-connected-interferometry array, maximum baseline-length was 208 km, using a high-speed asynchronous transfer mode (ATM) network with an AAL1 that corresponds to the constant bit-rate protocol. The very long baseline interferometry (VLBI) observed data is transmitted through a 2.488-Gbps [STM-16/OC-48] ATM network instead of being recorded onto magnetic tape. By combining antennas via a high-speed ATM network, a highly-sensitive virtual (radio) telescope system was realized. The system was composed of two real-time VLBI networks: the Key-Stone-Project (KSP) network of CRL (which is used for measuring crustal deformation in the Tokyo metropolitan area), and the OLIVE (optically linked VLBI experiment) network of NAO and ISAS which is used for astronomy (space-VLBI). These networks operated in cooperation with NTT. In order to realize a virtual telescope, the acquired VLBI data were corrected via the ATM networks and were synthesized using the VLBI technique. The cross-correlation processing and data observation were done simultaneously in this system and radio flares on the weak radio source (HR1099) were detected.

This paper presents a robust and nonblocking group membership protocol for large-scale distributed systems. This protocol uses the causal relation between membership-updating messages (i. e. , those specifying the adding and deleting of members) and allows the messages to be executed in a nonblocking manner. It differs from conventional group membership protocols in the following points: (1) neither global locking nor global synchronization is required; (2) membership-updating messages can be issued without being synchronized with each other, and they can be executed immediately after their arrival. The proposed protocol therefore is highly scalable, and is more tolerant to node and network failures and to network partitions than are the conventional protocols. This paper proves that the proposed protocol works properly as long as messages can eventually be received by their destinations. This paper also discusses some design issues, such as multicast communication of the regular messages, fault tolerance and application to reliable communication protocols (e. g. , TCP/IP).

An increase in high quality of service (QoS) applications such as video conferencing and distribution, and the evolution of the Internet have popularized ATM-LAN use based on the private network node interface (PNNI). Also in public networks, which serve as backbone networks for LANs, ATM technology is being introduced for high-speed and broadband communication. These situations lead to a great demand for economically and seamlessly interconnecting remote ATM-LANs via ATM public networks, which are based on broadband ISDN user part (BISUP). This paper discusses a method of peer group configuration method for such internetworking architecture that can avoid an overload of the PNNI routing processing in each peer group. The paper also proposes a method for seamless interconnection of remote ATM-LANs. In this method, complete PNNI signaling and routing is executed between a local switch (LS) in a public network and each ATM-LAN. It also can reduce the PNNI routing processing load on each public network by emulating PNNI routing and signaling between LSs.

Future high-speed switches and routers will be expected to support a large number of ports at high line rates carrying traffic with diverse statistical properties. Accordingly, scheduling mechanisms will be required to handle Tbit/sec aggregated capacity while providing quality of service (QoS) guarantees. In this paper a novel high-capacity switching scheme for ATM/WDM networks is presented. The proposed architecture is contention-free, scalable, easy to implement and requires no internal "speedup. " Non-uniform destination distribution and bursty cell arrivals are examined when studying the switching performance. Simulation results show that at an aggregated throughput of 1 Tbit/sec, low latency is achieved, yielding a powerful solution for high-performance packet-switch networks.

A nonlinear inverse filter is proposed for restoring signals degraded by a linear system and additive Gaussian noise. The proposed filter consists of combination of a linear high pass filter and an ε-filter, which is modified from the cascaded linear filter. The nonlinear property of the ε-filter is utilized to suppress pre-enhanced additive random noise and to restore sharp edges. It is demonstrated that the filter can be reduced to a multi-layered neural network model, and the optimal design is described by using the back propagation algorithm. The nonlinear function is approximated by a piecewise linear function, which results in simple and robust training algorithm. An application to image restoration is also presented, illustrating the effectiveness over the linear filter, especially when the amplitude of additive noise is small.

We propose a new sampling method for 2D and 3D implicit surfaces. The method is based on a stochastic process defined by the Langevin equation with a Gaussian random-force term. Our Langevin equation describes a stochastic-dynamical particle, which develops in time confined around the sampled implicit surface with small width. Its numerically generated solutions can be easily moved onto the surface strictly with very few iteration of the Newton correction. The method is robust in a sense that an arbitrary number of sample points can be obtained starting from one simple initial condition. It is because (1) the time development of the stochastic-dynamical particle does not terminate even when it reaches the sampled implicit surface, and (2) there is non-zero transition probability from one disconnected component to another. The method works very well for implicit surfaces which are complicated topologically, mathematically, and/or in shape. It also has some advantageous features in rendering 3D implicit surfaces. Many examples of applying our sampling method to real 2D and 3D implicit surfaces are presented.

Low Power design has emerged as a both practically and theoretically attractive theme in modern LSI system design. This paper presents system level power optimization techniques. A brief survey of system level low power design approaches and several examples in detail are described. It reviews some techniques that have been proposed to overcome the power issue and gives guideline for prospective system level solutions.

This paper reviews design aspects of computational discovery systems through the analysis of some successful discovery systems. We first review the concept of viewscope/view on data which provides an interpretation of raw data in a specific domain. Then we relate this concept to the KDD process described by Fayyad et al. (1996) and the developer's role in computational discovery due to Langley (1998). We emphasize that integration of human experts and discovery systems is a crucial problem in designing discovery systems and claim together with the analysis of discovery systems that the concept of viewscope/view gives a way for approaching this problem.

We address the problem of computing various types of expressive tests for decision trees and regression trees. Using expressive tests is promising, because it may improve the prediction accuracy of trees, and it may also provide us some hints on scientific discovery. The drawback is that computing an optimal test could be costly. We present a unified framework to approach this problem, and we revisit the design of efficient algorithms for computing important special cases. We also prove that it is intractable to compute an optimal conjunction or disjunction.

We propose a new probabilistic ID-based non-interactive key sharing scheme that has non-separable secret-key functions and a non-separable common-key function. The proposed scheme uses the calculation over modulo-P, modulo-Q and over integer ring for realizing non-separability. This proposed scheme has a large threshold against linear attack by the collusive entities.

Methods to discover laws are reviewed from among both statistical approach and artificial intelligence approach with more emphasis placed on the latter. Dimensions discussed are variable dependency checking, passive or active data gathering, single or multiple laws discovery, static (equilibrium) or dynamic (transient) behavior, quantitative (numeric) or qualitative or structural law discovery, and use of domain-general knowledge. Some of the representative discovery systems are also briefly discussed in conjunction with the methods used in the above dimensions.

A support system for hepatectomy that allows segmentation of the liver interactively and directly on 3D images was developed. Intuitive 3D images of the liver and its vessels and tumors were drawn with an improved volume-rendering method. Regions supplied with blood by each branch were interactively identified. 3D segments were defined directly on the images using a mouse and excisions were estimated from these interactive inputs.

A multilayer perceptron is usually considered a passive learner that only receives given training data. However, if a multilayer perceptron actively gathers training data that resolve its uncertainty about a problem being learnt, sufficiently accurate classification is attained with fewer training data. Recently, such active learning has been receiving an increasing interest. In this paper, we propose a novel active learning strategy. The strategy attempts to produce only useful training data for multilayer perceptrons to achieve accurate classification, and avoids generating redundant training data. Furthermore, the strategy attempts to avoid generating temporarily useful training data that will become redundant in the future. As a result, the strategy can allow multilayer perceptrons to achieve accurate classification with fewer training data. To demonstrate the performance of the strategy in comparison with other active learning strategies, we also propose an empirical active learning algorithm as an implementation of the strategy, which does not require expensive computations. Experimental results show that the proposed algorithm improves the classification accuracy of a multilayer perceptron with fewer training data than that for a conventional random selection algorithm that constructs a training data set without explicit strategies. Moreover, the algorithm outperforms typical active learning algorithms in the experiments. Those results show that the algorithm can construct an appropriate training data set at lower computational cost, because training data generation is usually costly. Accordingly, the algorithm proves the effectiveness of the strategy through the experiments. We also discuss some drawbacks of the algorithm.

A quantization-based watermarking system for motion pictures is proposed. In particular, methods for improving the image quality of watermarked video, the watermarking data tolerance, and the accuracy of watermark data detection are described. A quantitative evaluation of the reliability of watermarked data, which has not generally been discussed up to now, is also performed.