In this letter the classification of echocardiographic images is studied by making use of some texture features, including the angular second moment, the contrast, the correlation, and the entropy which are obtained from a gray-level cooccurrence matrix. Features of these types are used to classify two sets of echocardiographic images-normal and abnormal (cardiomyopathy) hearts. A minimum distance classifier and evaluation indexes are employed to evaluate the performance of these features. Implementation of our algorithm is performed on a PC-386 personal computer and produces about 87% correct classification for the two sets of echocardiographic images. Our preliminary results suggest that this method of feature-based image analysis has potential use for computer-aided diagnosis of heart diseases.

A noise cancelling sonar-ranging system based on the adaptive filtering technique, which can automatically adapt itself to the changes in environmental noise-field and improve the passive sonar-ranging/goniometric precision, was introduced by this paper. In the meantime, the software and hardware design principle of the system using high speed VLSI (Very Large Scale Integrated) DSP (Digital Signal Processing) chips, and the practical test results were also presented. In comparison with the traditional ranging system, the system not only enhanced obviously the ranging precision but also possessed some more characteristics such as simple structure, rapid operation, large data-storage volume, easy programming, high reliability and so on.

Recent technical advances in WDM (Wavelength Division Multiplexing) technologies suggest that their practical application is imminent. By adopting WDM technologies in the transport network, a bandwidth abundant B-ISDN could be realized cost-effectively. This requires the introduction of WDM technologies, especially into the path layer. This paper explores optical path cross-connect (OPXC) nodes that offer very high levels of expandability because existing traffic demands, which are rather limited, must be efficiently supported while permitting easy step-wise expansion in capacity. This paper highlights modularity with regard to incoming/outgoing links. The OPXC architecture that offers the highest modularity is elaborated, and its transmission characteristics, optical loss and switching power consumption are evaluated. This paper also examines OPXC architecture considering the interface needed to connect electrical path cross-connects. The proposed OPXC architectures provide flexibility and minimum investment to encourage the early introduction of B-ISDN and also supports incremental network growth to match traffic demand. The design of OPXC parameters in terms of transmission performance is shown to ensure the applicability of the proposed OPXC architecture to long-haul optical fiber transmission networks. This is made possible with the low optical component losses offered by the OPXC. The proposed OPXC architectures will, therefore, be applied not only to regional networks, but also to global area networks. Thus they will play a key role in realizing the optical path infrastructure for the future bandwidth abundant B-ISDN.

This paper discusses some problems in Molecular Biology for which learning paradigms are strongly desired. We also present a framework of knowledge discovery by PAC-learning paradigm together with its theory and practice developed in our work for discovery from amino acid sequences.

When communication network planning-design is performed, especially in a short-term case, it is important to utilize existing facilities in the construction of the new network. In this paper, link capacity assignment problem (CA problem) for packet-switched networks is investigated with the consideration of the existing network. To deal with this, per-unit cost of existing link capacity is thought to be less than that of newly installed capacity and a link cost function is modeled by a non-linear, non-differentiable one which is composed of two portions of capacity cost. After formulating the CA problem, two optimum algorithms derived from Lagrange multiplier method are presented and a modified algorithm is used for solving the CA problem in order to reduce the computation time. Some numerical results show that according to the values of link traffic flows, there will be links whose capacities must be set equally to the existing values. Moreover, when link cost difference is introduced in the CA problem, the number of links that the capacities of which have to be changed from existing values is less than that of linear cost function case, i.e., the case without consideration of the cost difference in link capacity.

In coherent optical space communication systems, the phase noise generated from high power laser diodes and the polarization axis mismatch between transmitter and receiver are the serious problem. In this paper, a novel coherent optical space communication system, called optical polarization azimuth modulation (POLAM)/heterodyne detection system is newly proposed, and its system performance is theoretically investigated. It is clarified that the POLAM system can perfectly remove the laser phase noise, is actually insensitive to the polarization axis mismatch, and can provide the remarkable performance improvement compared to a conventional optical frequency modulation system.

A new approximation calculation method, named the Recursive Matrix-calculation (RM) method, is proposed. It uses matrix calculation to determine the number of link disjoint paths under a hop link number constraint, i.e. hop limit. The RM method does not overestimate the number of link disjoint paths. When networks are designed by this method, network reliability is perfectly guaranteed. Moreover, the RM method is based on matrix calculation, so CPU time can be reduced by using super-computers equipped with vector processors. Simulation results confirm that the RM method yields rapid approximations that are conservative. Thus the proposed method is very useful for designing reliable multimedia networks.

Various authors have proposed probabilistic extensions of Valiant's PAC (Probably Approximately Correct) learning model in which the target to be learned is a (conditional) probability distribution. In this paper, we improve upon the best known upper bounds on the sample complexity of the parameter estimation part of the learning problem for distributions and stochastic rules over a finite domain with respect to the Kullback-Leibler divergence (KL-devergence). In particular, we improve the upper bound of order O(1/ε2) due to Abe, Takeuchi, and Warmuth to a bound of order O(1/ε). In obtaining our results, we made use of the properties of a specific estimator (slightly modified maximum likelihood estimator) with respect to the KL-divergence, while previously known upper bounds were obtained using the uniform convergence technique.

Although consistent learning is sufficient for PAC-learning, it has not been found what strategy makes learning more efficient, especially on the sample complexity, i.e., the number of examples required. For the first step towards this problem, classes that have consistent learning algorithms with one-sided error are considered. A combinatorial quantity called maximal particle sets is introduced, and an upper bound of the sample complexity of consistent learning with one-sided error is obtained in terms of maximal particle sets. For the class of n-dimensional axis-parallel rectangles, one of those classes that are consistently learnable with one-sided error, the cardinality of the maximal particle set is estimated and O(d/ε1/ε log 1/δ) upper bound of the learning algorithm for the class is obtained. This bound improves the bounds due to Blumer et al. and meets the lower bound within a constant factor.

Many combinatorial problems can be efficiently solved for partial k-trees (graphs of treewidth bounded by k). The edge-coloring problem is one of the well-known combinatorial problems for which no NC algorithms have been obtained for partial k-trees. This paper gives an optimal and first NC parallel algorithm to find an edge-coloring of any given partial k-tree with bounded degrees using a minimum number of colors. In the paper k is assumed to be bounded.

A number of flexible control mechanisms used in buffer management, congestion control and bandwidth allocation have been proposed to improve the performance of ATM networks by introducing parameters, such as threshold, push-out probability and incremental bandwidth size of a virtual path, which are adjustable by network providers. However, it is difficult to adaptively adjust these parameters, since the traffic in ATM networks is further complicated by accommodating various kinds of services. To overcome the problem, we propose in this paper a control scheme based on the genetic algorithms and the neural estimator. The neural estimator forecasts the future QOS values for each candidate parameter set, and the genetic algorithms select the best one to control the real network. An example of buffer management in an ATM switch is examined in this paper. Simulation results show the effectiveness of the proposed control scheme in adaptively adjusting the parameter set even when the traffic environment and the QOS requirements are dynamically changing.

This paper describes an O(log3n) time O(n/log n) processors parallel algorithm for determining the congruence (exact matching) of two point sets in three-dimensions on a CREW PRAM, where n is the maximum size of the input point sets. Although optimal O(n log n) time sequential algorithms were developed for this problem, no efficient parallel algorithm was known previously. In the algorithm, the original problem is reduced to the two-dimensional congruence problem by computing a three-dimensional point set cps(S) for each input point set S, where cps(S) satisfies the following conditions: 0|cps(S)|12; cps(T(S))T(cps(S)) for all isometric transformations T. The two-dimensional problem can be solved efficiently in parallel using a parallel version of a previously-known sequential algorithm. cps(S) is computed recursively in the following way: the size of a point set is reduced by a constant factor in each recursive step. To reduce the size of a point set, a convex hull is constructed and then it is regarded as a planar graph, so that combinatorial properties of a planar graph are used effectively. A sequential version of the algorithm works in O(n log n) time, so that this paper gives another optimal sequential algorithm. The presented algorithm can be applied for graphs such that each vertex corresponds to a point and each edge corresponds to a line segment connecting its endpoints. Moreover, the algorithm can be modified for computing the canonical form of a point set or a graph.

As a first step to develop a system to analyze or recognize patterns contained in mages, it is important to provide a good base representation that can facilitate efficiently the interpretation of such patterns. Since structural features of basic patterns in document images such as characters or tables are horizontal and vertical stroke components, we propose a new expression of document image based on the MCR expression that can express well such features of text and tabular components of an image.

In this paper, we report a new approach about parsing and searching problem for a given phonetic lattice. The approach is based on the Divide and Conquer (DC) strategy. By dividing the phonetic lattice, we first construct a PD-tree to represent this lattice, then, we parse through this PD-tree to identify the possible sentence which is supposed to be the speech utterance. Next, we propose a new search scheme called Downward Request (DR) search model to decrease the computation costs, and this search model gives us the optimal or N-best solutions. Experiments performed on Chinese speech recognition show us the good results.

The Manchester Dataflow Machine (MDFM) works with tasks of size equal to one single instruction. This fine granularity aims at exploring all parallelism at the instruction level. However, this project decision increases the instruction communication cost, which ends up to jam the interconnection network and reduces the system performance. One way to skirt this problem is to adopt variable size tasks instead of working with such small task size. In this paper, in order to study whether or not the usage of such variable size tasks in the MDFM architecture contributes to the improvement of the performance, some simulations by toy programs take place. In the simulation, variable size tasks are realized by packing the sequential instruction stretches into one task. To manage this packing, the Sequential Block (SB) technique is developed. The simulation of those packed and unpacked programs give an outline of advantages and disadvantages of working with variable size tasks, and how the SB technique should be implemented in the system.

Next generation personal communication systems will provide a range of different services to moving users. In parallel, packet switching is being proposed as a way to statistical multiplexing and hence to better resource exploitation. The co-existence of different services may prove difficult due to the different requirements on quality of service parameters like packet loss, delay, and so on. This requires a careful design of Call Admission Control policies, which are to be quite different from those used in fixed network, due to two phenomena which are typical of mobile systems, namely co-channel interference and handovers. In this paper we address these complex topics, and propose some basic rules for Call Admission Control policies suitable in this context.

Complexity of Boolean functions satisfying the propagation criterion (PC), an extended notion of the perfect nonlinearity, is discussed on several computation models. The following topics are investigated: (i) relationships between the unateness and the degree of the PC, (ii) the inversion complexity of perfectly nonlinear Boolean functions, (iii) the formula size of Boolean functions that satisfy the PC of degree 1, (iv) the area-time-square complexity of VLSI circuits computing perfectly nonlinear Boolean functions, (v) the OBDD size perfectly nonlinear Boolean functions.

This paper surveys low-power circuit techniques for CMOS ULSIs. For many years a power supply voltage of 5 V was employed. During this period power dissipation of CMOS ICs as a whole increased four-fold every three years. It is predicted that by the year 2000 the power dissipation of high-end ICs will exceed the practical limits of ceramic packages, even if the supply voltage can be feasibly reduced. CMOS ULSIs now face a power dissipation crisis. A new philosophy of circuit design is required. The power dissipation can be minimized by reducing: 1) supply voltage, 2) load capacitance, or 3) switching activity. Reducing the supply voltage brings a quadratic improvement in power dissipation. This simple solution, however, comes at a cost in processing speed. We investigate the proposed methods of compensating for the increased delay at low voltage. Reducing the load capacitance is the principal area of interest because it contributes to the improvement of both power dissipation and circuit speed. Pass-transistor logic is attracting attention as it requires fewer transistors and exhibits less stray capacitance than conventional CMOS static cicuits. Variations in its circuit topology as well as a logic synthesis method are presented and studied. A great deal of research effort has been directed towards studying every portion of LSI circuits. The research achievements are categorized in this paper by parameters associated with the source of CMOS power dissipation and power use in a chip.

Optical path technology that employs both WDM/FDM and wavelength routing will play a key role in supporting future high bandwidth transport networks. WP/VWP (Wavelength Path/Virtual Wavelength Path) technologies are very effective in realizing optical path networks. In these networks, since photonic wavelengths are scarce resources, the number of wavelengths required to construct the network must be minimized. However, the wavelength assignment problem, minimizing the number of wavelengths, is an NP-complete problem. Solving this problem heuristically is an important issue for designing large-scale WP/VWP based networks that are also practical. To realize optical path networks, we need to develop path accommodation design algorithms that heuristically solve the wavelength assignment problem. This paper proposes novel path accommodation design algorithms for WP/VWP networks that minimize the number of wavelengths required. We numerically elucidate that the numbers of wavelengths required for active WPs and VWPs are almost equal. When link failure restoration is considered, they are different; more wavelengths are needed with the WP scheme than with the VWP scheme. It is also demonstrated that the proposed algorithms are applicable to a large scale network design.

This paper describes a method for screening psychiatric patients based on a questionnaire consisting of simple yes/no questions regarding to physical, mental conditions and subjective symptoms which is provided at their first visit to the hospital. The analysis of the questionnaire is important to understand patients' background. One hundred filled out questionnaires were utilized for constructing and evaluating a pseude Bayesian classifier which classifies patients into three categories i.e. Schizophrenic, emotional and neurotic disorders with average correct prediction rate of 73.3%. The rate was 16.6% higher than the result given by experienced medical doctors and the method will be a useful mean for automatic screening of the psychiatric patients.