Holonic Manufacturing Systems (HMSs), in which decisions are made through cooperation among holons (autonomous and cooperative manufacturing entities), eliminate various bottlenecks that exist in conventional systems to adapt to high-variety low-volume production. This paper describes the architecture of HMSs. Issues regarding incremental development and dynamic reconfiguration of cooperation mechanisms themselves, and mechanisms for ensuring stable and safe behaviors of HMSs are also discussed with reference to several proposals, with a view to applying the HMS architecture to large and complicated applications.

In this paper, we study reliable decentralized supervisory control of discrete event systems with a control architecture where certain controllable events are controlled under the conjunctive fusion rule, and certain others are controlled under the disjunctive fusion rule. We first introduce a notion of reliable co-observability with respect to such a partition of the controllable event set. We then prove that reliable co-observability together with L_m(G)-closure and controllability is a necessary and sufficient condition for the existence of a reliable decentralized supervisor under a given partition. Moreover, we present necessary and sufficient conditions for the existence of a partition of the controllable event set under which a given specification language is reliably co-observable.

The present paper discusses an assembly line balancing problem (ALBP). ALBP discussed up to now does not consider rack spaces where tools or parts are stored. We introduce an extended resource planning and assembly line balancing problem that takes the rack space into account. An exact search method for solving the problem by using a graph structure, and a heuristics for the method are proposed. The proposed method is evaluated by computational experiments.

In this paper, a new grouping method for Group Technology using Self-Organizing Map (SOM) is proposed. The purpose of our study is to divide machines in a factory into any number of cells so that the machines in each cell can process a similar set of parts to increase productivity. A main feature of our method is to specify not only the number of the cells but also the maximum and minimum numbers of machines in a cell. Some experimental results show effectiveness of our proposed algorithm.

Analysis of concurrent systems, such as computer/communication networks and manufacturing systems, usually employs formal discrete event models. The analysis then includes model validation, property verification, and performance evaluation of such models. The DEVS (Discrete Event Systems Specification) formalism is a well-known formal modeling framework which supports specification of discrete event models in a hierarchical, modular manner. While validation and verification using formal models may not resort to discrete event simulation, accurate performance evaluation must employ discrete event simulation of formal models. Since formal models, such as DEVS models, explicitly represent communication semantics between component models, their simulation cost is much higher than using simulation languages with informal models. This paper proposes a method for simulation speedup in performance evaluation of concurrent systems using DEVS models. The method is viewed as a compiled simulation technique which eliminates run-time interpretation of communication paths between component models. The elimination has been done by a behavior-preserved transformation method, called model composition, which is based on the closed under coupling property in DEVS theory. Experimental results show that the simulation speed of transformed DEVS models is about 14 times faster than original ones.

This paper proposes a simulation framework suitable for holonic manufacturing systems, or HMS, based on the concept of distributed self-simulation. HMS is a distributed system that comprises autonomous and cooperative elements called holons, for the flexible and agile manufacturing. The simulation framework proposed here capitalizes on this distributed nature, where each holon functions similar to an independent simulator with self-simulation capabilities to maintain its own clock, handle events, and detect inter-holon state inconsistencies and perform rollback actions. This paper discusses the detailed architecture and design issues of such a simulator and reports on the results of a prototype.

Autonomous distributed manufacturing systems(ADMS) consist of multiple intelligent components with each component acting according to its own judgments. The ADMS objective is to realize more agile and adaptive manufacturing systems. This paper presents the introduction of context-dependent agents (CDAs) in ADMS, and switch strategies depending on system conditions to achieve better performance can be realized by agents that use the same strategies under all system conditions. For the real-time job scheduling problem, the present paper recalls a basic CDA architecture, and presents the results of an extensive empirical evaluation its performance relative to other rule-based schemes based on several common indices for real-time dispatch.

This paper presents a framework for building mobile agent-based components. The framework introduces the notion of agent hierarchy and inter-agent migration and thus allows a group of mobile agents to be dynamically assembled into a single mobile agent. It provides a powerful method of constructing complex, large-scale mobile agent-based applications. To demonstrate how to exploit our framework, we construct an extensible and portable mobile agent system for executing and migrating hierarchical mobile agents. The system itself is also implemented as a collection of mobile agents and can thus dynamically change and adapt its functions through migrating agents that offer the functions. Mobile agent-based applications running on the system can naturally inherit the extensibility and adaptability of the system.

Finding a nonnegative integer solution x for Ax = b (A Z^mn, b Z^m1) in Petri nets is NP-complete. Being NP-complete, even algorithms with theoretically bad worst case and with average complexity can be useful for a special class of problems, hence deserve investigation. Then a Grobner basis approach to integer programming problems was proposed in 1991 and some symbolic computation systems became to have useful tools for ideals, varieties, and algorithms for algebraic geometry. In this letter, Grobner basis approach is applied to three typical problems with respect to state equation in P/T Petri nets. In other words, after Grobner bases are derived by the tool Maple 7, we consider how to derive the T-invariants and particular solutions of the Petri nets by using them in this letter.

The paper develops the transformation rules in order to use the Stochastic Petri Net model to evaluate the performance of various task scheduling algorithms. The transformation rules are applied to DFRN scheduling algorithm to investigate its effectiveness. The performance comparison reveals that the proposed approach provides very accurate evaluation for the scheduling algorithm when the Communication to Computation Ratio value is small.

In speech enhancement with adaptive microphone array, the voice activity detection (VAD) is indispensable for the adaptation control. Even though many VAD methods have been proposed as a pre-processor for speech recognition and compression, they can hardly discriminate nonstationary interferences which frequently exist in real environment. In this research, we propose a novel VAD method with array signal processing in the wavelet domain. In that domain we can integrate the temporal, spectral and spatial information to achieve robust voice activity discriminability for a nonstationary interference arriving from close direction of speech. The signals acquired by microphone array are at first decomposed into appropriate subbands using wavelet packet to extract its temporal and spectral features. Then directionality check and direction estimation on each subbands are executed to do VAD with respect to the spatial information. Computer simulation results for sound data demonstrate that the proposed method keeps its discriminability even for the interference arriving from close direction of speech.

The adaptive cross-spectral (ACS) technique recently introduced by Okuno et al. provides an attractive solution to acoustic echo cancellation (AEC) as it does not require double-talk (DT) detection. In this paper, we first introduce a generalized ACS (GACS) technique where a step-size parameter is used to control the magnitude of the incremental correction applied to the coefficient vector of the adaptive filter. Based on the study of the effects of the step-size on the GACS convergence behaviour, a new variable step-size ACS (VSS-ACS) algorithm is proposed, where the value of the step-size is commanded dynamically by a special finite state machine. Furthermore, the proposed algorithm has a new adaptation scheme to improve the initial convergence rate when the network connection is created. Experimental results show that the new VSS-ACS algorithm outperforms the original ACS in terms of a higher acoustic echo attenuation during DT periods and faster convergence rate.

The purpose of this paper is to propose a novel cluster map based blind RBF equalizer for received signal constellation (RSC) independent channel, which belongs to RSC based blind equalization approach. Without channel estimator, firstly, the desired numbers of unlabeled RBF centers are obtained by an unsupervised clustering algorithm. Then a cluster map generated from the known RBF equalizer structure is used to partition the unlabeled centers into appropriate subsets merely by several simple sorting operations, which corresponds to the weight initialization. Finally, the weight is adjusted iteratively by an unsupervised least mean square (LMS) algorithm. Since the process of the weight initialization using the underlying structure of RBF equalizer is very effective, the proposed blind RBF equalizer can achieve almost identical performance with the optimal RBF equalizer. The validity of the proposed equalizer is also demonstrated by computer simulations.

This paper presents a distinct approach to the robustness stability analysis and design of linear uncertain systems. Based on the extension version of the projection method, the specific stability issue, which ensures the poles within a specific region, can be efficiently analyzed. Furthermore, we derive a simple design scheme for a class of uncertain systems. By the proposed numerical algorithm, some examples are given to demonstrate the validity and effectiveness.

The knowledge of a good enclosure of the range of a function over small interval regions allows us to avoid convergence of optimization algorithms to a non-global point(s). We used interval slopes f[X,x] to check for monotonicity and integrated their derivative forms g[X,x], x X by quadratic and Newton methods to obtain narrow enclosures. In order to include boundary points in the search for the optimum point(s), we expanded the initial box by a small width on each dimension. These procedures resulted in an improvement in the algorithm proposed by Hansen.

This investigation proposes a new multiplication algorithm in the finite field GF(2^m) over the polynomial basis, in which the irreducible x^m +xⁿ + 1 with gcd(m,n) = 1 generates the field GF(2^m). The algorithm involves two steps--the intermediate multiplication and the modulo reduction. In the first step, the intermediate multiplication algorithm permutes a polynomial to construct the full-bit-parallel systolic intermediate multiplier. The circuit is identical of m² cells, each cell is identical of one 2-input AND gate, one 2-input XOR gate, and four 1-bit latches. In the second step, based on the results of the intermediate multiplication in the first step, the modulo reduction circuit is built using regular and simple reduction operations. The latency of the proposed multiplier requires m + k + 1 clock cycles, where k = + 1. Notably, the latency can be very low if n is in the range 1 n . For the computing multiplication in GF(2^m), the novel multiplier exhibits much lower latency than the existing systolic multipliers, and is well suited to VLSI systems due to their regular interconnection pattern, modular structure and fully inherent parallelism.

Recently six conjectures on linear complexities (LC) of some Kronecker sequences of two or three component sequences are proposed by Karkkainen. In, the LC of Kronecker sequences of two component sequences were studied by Uehara and Imamura, their results are true except in the case when e_b 2 or when e_a = e_b = 1. In this paper the LC for Kronecker sequences of two component sequences are determined completely, and it is shown that all the six conjectures are true except in some special cases, which are listed and corrected.

Aging is progressing in our country. Cerebral disease poses a serious problem. Viewing this problem objectively, we can say that support of aging and cerebral disease patients is a useful research theme. To the present, we have done rank evaluation of cerebral disease using synthetic face picture images. This study assesses cognitive ability and expression control ability for intoxication, which is known to impair thinking, cognition, and memory ability. We also examine correspondence of intoxication to cerebral disease. Measurement of cognitive ability corresponds to observation of an internal condition; the measurement of expression control ability corresponds to observation of an external condition. In measurement of cognitive ability, we simulated early stage symptoms of vascular dementia in the second stage of BAC. Also, decreased cognitive ability occurs from the first stage of BAC on face recognition to figure and language. Moreover, face test results show significant difference between decrease in the first stage of BAC and one in the second stage of BAC. These results indicate the possibility of rank evaluation and early stage detection of vascular dementia using a face picture image. From measurement of expression control ability, we obtained the result that we can judge whether a subject has reached second stage of BAC by observing an expression's strength of smile. The second stage of BAC shows symptoms similar to those of vascular dementia. We found the possibility that smile is valid as one externally-observable index for detection of cerebral disease.

Reinforcement Learning (RL) is an efficient learning method for solving problems that learning agents have no knowledge about the environment a priori. Ant Colony System (ACS) provides an indirect communication method among cooperating agents, which is an efficient method for solving combinatorial optimization problems. Based on the cooperating method of the indirect communication in ACS and the update policy of reinforcement values in RL, this paper proposes the Q-ACS multiagent cooperating learning method that can be applied to both Markov Decision Processes (MDPs) and combinatorial optimization problems. The advantage of the Q-ACS method is for the learning agents to share episodes beneficial to the exploitation of the accumulated knowledge and utilize the learned reinforcement values efficiently. Further, taking the visited times into account, this paper proposes the T-ACS multiagent learning method. The merit of the T-ACS method is that the learning agents share better policies beneficial to the exploration during agent's learning processes. Meanwhile, considering the Q-ACS and the T-ACS as homogeneous multiagent learning methods, in the light of indirect media communication among heterogeneous multiagent, this paper presents a heterogeneous multiagent RL method, the D-ACS that composites the learning policy of the Q-ACS and the T-ACS, and takes different updating policies of reinforcement values. The agents in our methods are given a simply cooperating way exchanging information in the form of reinforcement values updated in the common model of all agents. Owning the advantages of exploring the unknown environment actively and exploiting learned knowledge effectively, the proposed methods are able to solve both problems with MDPs and combinatorial optimization problems effectively. The results of experiments on hunter game and traveling salesman problem demonstrate that our methods perform competitively with representative methods on each domain respectively.

Edge linking is a fundamental computer vision task, yet presents difficulties arising from the lack of information in the image. Viewed as a constrained optimization problem, it is NP hard-being isomorphic to the classical Traveling Salesman Problem. This paper proposes a gradient ascent learning algorithm of the elastic net approach for edge linking of images. The learning algorithm has two phases: an elastic net phase, and a gradient ascent phase. The elastic net phase minimizes the path through the edge points. The procedure is equivalent to gradient descent of an energy function, and leads to a local minimum of energy that represents a good solution to the problem. Once the elastic net gets stuck in local minima, the gradient ascent phase attempts to fill up the valley by modifying parameters in a gradient ascent direction of the energy function. Thus, these two phases are repeated until the elastic net gets out of local minima and produces the shortest or better contour through edge points. We test the algorithm on a set of artificial images devised with the aim of demonstrating the sort of features that may occur in real images. For all problems, the systems are shown to be capable of escaping from the elastic net local minima and producing more meaningful contours than the original elastic net.

Parameter-optimized cubic convolution is used to accurately analyze the pitch center, rate and extent of vibrato tones. We interpolate the time-tracing fundamental frequencies of vibrato tones using parametric cubic convolution, and analytically estimate the positions and values of the extrema, which are used to analyze the characteristics of the vibrato. The optimal values of α, the parameter of the interpolation kernel, are also shown as a function of the normalized vibrato rates.

The propagator method (PM) belongs to a class of subspace based methods for direction-of-arrival estimation which only requires linear operations but does not involve any eigendecomposition or singular value decomposition as in common subspace techniques. In this paper, we apply the PM for estimating the frequencies of multiple real sinusoids in noise and a computationally simple as well as high resolution multiple frequency estimation algorithm is developed. The estimation accuracy of the proposed method is contrasted with the conventional MUSIC and Cramer-Rao lower bound under different noise conditions.

In order to stabilize a convey-crane with only cart position measurement, this paper designs an additional dynamics with which the parallel-connected system is feedback passive. Since the crane system can be stabilized with a proportional-derivative (PD) law, the additional system is constructed by using the PD gains, and the closed-loop system exhibits almost same performances with the PD law. With the proposed control law, the transfer function of the additional system has the form of sH(s) with a strictly positive real (SPR) H(s).

Fault-tolerant execution of a mobile agent is an important design issue to build a reliable mobile agent system. Several fault-tolerant schemes for a single agent system have been proposed, however, there has been little research result on the multi-agent system. For the cooperating mobile agents, fault-tolerant schemes should consider the inter-agent dependency as well as the mobility; and try to localize the effect of a failure. In this paper, we investigate properties of inter-agent dependency and agent mobility; and then characterize rollback propagation caused by the dependency and the mobility. We then suggest some schemes to localize rollback propagation.

At EuroCrypt '95, Stadler, Piveteau and Camenish introduced the concept of fair blind signatures to prevent the misuse of blind signature schemes by criminals. Recently, Hwang, Lee and Lai claimed that Stadler et al.'s first fair blind signature scheme cannot meet the untraceability property of the blind signature schemes. However, this letter will demonstrate that Hwang et al.'s claim is incorrect and Stadler et al.'s first scheme still holds the untraceability property.

A good watermark is known to be perceptually invisible, undetectable without key and robust to spatial/temporal data modification. In this paper, we utilize the characteristics of the human visual system (HVS) for watermarking. In HVS, the response of visual cortex decomposes the image spectra into perceptual channels that are octave bands in spatial frequency. Based on the octave-bands division, same numbers of bits of the watermark are inserted into each channel. Experimental results show that the proposed method based on HVS method gives strong robustness to the attacks compared with conventional DCT, wavelet and DFT watermarking methods.