In this paper we consider a parallel and distributed computation of genetic algorithms on loosely-coupled multiprocessor systems. Loosely-coupled ones are more suitable for massively parallel processing and also more easily VLSI implementation than tightly-coupled ones. However, communication overhead on parallel processing is more serious for loosely-coupled ones. We propose in this paper a parallel and distributed execution method of genetic algorithm on loosely-coupled multiprocessor systems of fixed network topologies in which each processor element carries out genetic operations on its own chromosome set and communicates with only the neighbors in order to save communication overhead. We evaluate the proposed method on the multiprocessor systems with ring, torus, and hypercube topologies for benchmark problem instances. From the results, we find that the ring topology is more suitable for the proposed parallel and distributed execution since variety of chromosomes in the ring is kept much more than that in the others. Moreover, we also propose a new network topology called cone which is a hierarchical connection of ring topologies. We show its effectiveness by experimental evaluation.

Unfolding originally introduced by McMillan is gaining ground as a partial-order based method for the verification of concurrent systems without state space explosion. However, it can be exposed to redundancy which may increase its size exponentially. So far, there have been trials to reduce such redundancy resulting from conflicts by improving McMillan's cut-off criterion. In this paper, we show that concurrency is also another cause of redundancy in unfolding, and present an algorithm to reduce such redundancy in live, bounded and reversible Petri nets which is independent of any cut-off algorithm.

By treating each different output pattern as a state, we propose a low power architecture for pipelined circuits using bipartition. It is possible that the output of a pipelined circuit transit mainly among some of different states. If some few states dominate most of the time, we could partition the combinational portion of a pipelined circuit into two blocks: one that contains the few states with high activity is small and the other that contains the remainder with low activity is big. The original pipelined circuit is bipartitioned into two individual pipelined circuits. An additional combination logic block is introduced to control which of the two partitioned blocks to work. Power reduction is based on the observation that most time the small block is at work and the big one is at idle. In order to minimize the power consumption of this architecture, we present an algorithm that can improve the efficiency of this additional control block. Experiments with MCNC benchmarks show high percentage of power saving by using our new architecture for low power pipelined circuit design.

In this work, a new algorithm for tracking the directions-of-arrival (DOA's) of moving targets by introducing a linear approximation is proposed. The targets are assumed to move with constant angular velocities within a short time and emitting continuously narrow-band signals that impinge on an array of sensors. Therefore the trajectories of targets can be approximated by linear functions of time, which consist of the DOA's and the angular velocities, within the short time. In the condition that the number of targets is known and the outputs vector of the sensors including the additive white complex Gaussian noises is observed continuously, a cost function which consists of the squared residual error vectors is defined. The estimation of the DOA's and the angular velocities of targets is performed by minimizing this cost function. By estimating both the DOA's and the angular velocities at the same time, the proposed algorithm is able to improve the tracking performance for rapidly moving targets. In computer simulations, the performance of the proposed algorithm is compared with the ESPRIT method, which is one of the typical subspace methods with super resolution.

Many Ziv-Lempel algorithms have a similar property, that is, slow encoding and fast decoding. This paper proposes a simple improved Ziv-Lempel algorithm to encode a large amount of data quickly as well as compactly by using multiple-processor system.

We introduce a subclass of context-free languages, called pure context-free (PCF) languages, which is generated by context-free grammars with only one type of symbol (i. e. , terminals and nonterminals are not distinguished), and consider the problem of identifying paralleled even monogenic pure context-free (pem-PCF) languages, PCF languages with restricted and enhanced features, from positive data only. In this paper we show that the ploblem of identifying the class of pem-PCF languages is reduced to the ploblem of identifying the class of monogenic PCF (mono-PCF), by decomposing each string of pem-PCF languages. Then, with its result, we show that the class of pem-PCF languages is polynomial time identifiable in the limit from positive data. Further, we refer to properties of its identification algorithm.

We propose a robust detection scheme by employing an order statistic filter as a preprocessor of the input signal. For ease of design, the variance of the order statistic filtered output is modeled by proposing an approximate upper bound. The detector is analytically designed using a fixed sample size (FSS) test scheme. The performance of the proposed detector is compared to that of other robust detectors in terms of the sample size required for given false alarm and miss detection probabilities. Finally, analytical results are verified by computer simulation.

The characteristics of circular polarization from a slot with a parasitic dipole are investigated analytically. It is derived that its phase is linearly dependent upon the angle of the dipole and is independent of that of slot. This interesting behavior is also confirmed by experiments.

An image recognition system using NEURO4, a programmable parallel processor, is described. Optical flow is the velocity field that an observer detects on a two-dimensional image and gives useful information, such as edges, about moving objects. The processing time for detecting optical flow on the NEURO4 system was analyzed. Owing to the parallel computation scheme, the processing time on the NEURO4 system is proportional to the square root of the size of images, while conventional sequential computers need time in proportion to the size. This analysis was verified by experiments using the NEURO4 system. When the size of an image is 84 84, the NEURO4 system can detect optical flow in less than 10 seconds. In this case the NEURO4 system is 23 times faster than a workstation, Sparc Station 20 (SS20). The larger the size of images becomes, the faster the NEURO4 system can detect optical flow than conventional sequential computers like SS20. Furthermore, the paralleling effect increases in proportion to the number of connected NEURO4 chips by a ring expansion scheme. Therefore, the NEURO4 system is useful for developing moving image recognition algorithms which require a large amount of processing time.

Widely tunable coherent terahertz (THz)-wave generation was successfully demonstrated based on the laser light scattering from the lowest A1-symmetry polariton mode by using a Q-switched Nd:YAG laser pumping. This method exhibits multiple advantages like wide tunability (frequency: 0. 9-2. 2 THz), coherency and compactness of its system. In this paper, the general performances of this THz-wave generator, as well as the recent development of the system and its application are reported. Measurements of tunability, coherency, power, polarization, radiation angle, and divergence are shown. The cryogenic cooling of the crystal was performed in addition, and a more than one hundred times higher THz-wave output was observed. A spectroscopic application of our wave source is demonstrated by measuring the water vapor absorption.

In this paper we newly define a generalized edge-ranking of a graph G as follows: for a positive integer c, a c-edge-ranking of G is a labeling (ranking) of the edges of G with integers such that, for any label i, deletion of all edges with labels >i leaves connected components, each having at most c edges with label i. The problem of finding an optimal c-edge-ranking of G, that is, a c-edge-ranking using the minimum number of ranks, has applications in scheduling the manufacture of complex multi-part products; it is equivalent to finding a c-edge-separator tree of G having the minimum height. We present an algorithm to find an optimal c-edge-ranking of a given tree T for any positive integer c in time O(n2log Δ), where n is the number of vertices in T and Δ is the maximum vertex-degree of T. Our algorithm is faster than the best algorithm known for the case c=1.

An ultra-broadband optical parametric amplification can be attained by a noncollinear phase-matching. The group-velocity matching of the signal and idler reduces the signal-pulse width to 14-fs in an optical parametric amplifier based on a β-BaB2O4 crystal pumped by a second harmonics of a Ti: sapphire regenerative amplifier. This simple novel method shows the potential light source of a tunable sub-10-fs pulse in a visible region.

In this paper, we propose an algorithm of classification by feature partitioning (CFP) which learns concepts in the batch mode. The proposed algorithm achieved almost the same predictive accuracies as the best results of a CFP algorithm presented by Guvenir and Sirin. However, our algorithm is not affected by parameters and the order of examples.

This paper proposes a method of constructing single-electron logic subsystems on the basis of the binary decision diagram (BDD). Sample subsystems, an adder and a comparator, are designed by combining single-electron BDD devices. It is demonstrated by computer simulation that the designed subsystems successfully produce, through pipelined processing, an output data flow in response to the input data flow. The operation error caused by thermal agitation is estimated. An output interface for converting single-electron transport into binary-voltage signals is also designed.

We describe an algorithm for efficiently compositing partial images generated during parallel volume rendering on a distributed memory parallel computer. In this object space partitioning algorithm, each PE is assigned to several subvolumes where each subvolume has a corresponding local frame buffer. After volume rendering is performed independently for each subvolume, the partial images stored in the local frame buffers are combined to generate a complete image. During this compositing process, the communication of partial image data between the PEs is kept minimal by assigning PEs to subvolumes in an interleaved manner. This assignment makes possible a reduction in communication in the axis direction in which there is the most communication. Experimental results indicate that a 9% to 35% reduction in the total rendering time can be attained with no additional data structures and no memory overhead.

The Non-stop Service-Enhanceable Software (NOSES) platform was developed as part of our overall plan to establish a communications software platform that can be customized for use by various communications systems, such as STM, ATM and IN. The developed NOSES techniques are call-recovery restart, system file update, and on-line partial file modification, so called "Plug-in"; they were achieved by using dynamic program modification. A system-file update inevitably affects calls in service, despite efforts to save in-service calls by copying the call data from the old file to the new one. We therefore developed a different approach: Plug-in modification. This paper evaluates the applicability of the plug-in mechanism of the NOSES platform. Plug-in is a dynamic partial-file modification technique that does not affect calls in service in a communication switching system. In order to apply plug-in program modification widely, the static and dynamic properties of the modified software must be considered. Therefore, an applicability judgement matrix is introduced. The evaluated applicability of plug-in based on case studies and field data was about 60% for service feature additions and modifications. Thus, plug-in is effective for file maintenance of switching systems from the viewpoint of quick provisioning of new service features and bug fixes.

Parallelism on heterogeneous machines brings cost effectiveness, but also raises a new set of complex and challenging problems. This paper addresses the problem of estimating the minimum time taken to execute a program on a fine-grained parallel machine composed of different types of processors. In an earlier publication, we took the first step in this direction by presenting a graph-construction method which partitions a given program into several homogeneous parts and incorporates timing constraints due to heterogeneous parallelism into each part. In this paper, to make the method easier to be applied in a scheduling framework and to demonstrate its practical utility, we present an efficient implementation method and compare the results of its use to the optimal schedule lengths obtained by enumerating all possible solutions. Experimental results for several different machine models indicate that this method can be effectively used to estimate a program's minimum execution time.

In this paper, we present an analytic model to study the reliability of some important disk array organizations that have been proposed by others in the literature. These organizations are based on the combination of two options for the data layout, regular RAID-5 and block designs, and three alternatives for sparing, hot sparing, distributed sparing and parity sparing. Uncorrectable bit errors have big effects on reliability but are ignored in traditional reliability analysis of disk arrays. We consider both disk failures and uncorrectable bit errors in the model. The reliability of disk arrays is measured in terms of MTTDL (Mean Time To Data Loss). A unified formula of MTTDL has been derived for these disk array organizations. The MTTDLs of these disk array organizations are also compared using the analytic model. By numerical experiments, we show that the data losses caused by uncorrectable bit errors may dominate the data losses of disk array systems though only the data losses caused by disk failures are traditionally considered. The consideration of uncorrectable bit errors provides a more realistic look at the reliability of the disk array systems.

We consider the situation that plural degraded images are obtained. When no prior knowledge about original images are known, these images are individually restored by an optimum restoration filter, for example, by Wiener Filter or by Projection Filter. If correlations between original images are obtained, some restoration filters based on Wiener Filter or Projection Filter are proposed. In this paper, we deal with the case that some pixels or some parts of original images overlap, and propose a restoration method using a formulae for overlapping. The method is based on Partial Projection Filter. Moreover, we confirm an efficacy of the proposed method by numerical examples.

A family of nonce-based authentication and key distribution protocols based on the trusted third-party model are proposed which are not only efficient on the view points of computation and communication, but also secure against on-line and off-line password guessing attacks. A new concept of implicit or indirect challenge-response authentication which can be used to combine the processes of identify authentication and data integrity assurance during key distribution and to make the entire protocol be more concise and efficient is introduced in this paper. In the proposed family of protocols, specific protocol can be chosen such that the secure session key to be distributed is selected by specific participant in the protocol. Detailed security analyses of every protocols are given.