When a large-size car exists on the ETC lane (Electronic Toll Collection System), there is the possibility that the interference on the adjacent lane occurs by the scattering waves from one. In this paper, we propose a new improvement method which the transparent EM wave absorber is placed between the ETC lane and the adjacent one in order to suppress the scattering waves from a large-size car. Therefore, we design the transparent EM wave absorber which consists of the transparent resistive and conductive films. Then, this absorber is produced, and its reflection and transmission coefficients are evaluated. In addition, its transmittance in optics is evaluated. As the results, the reflectivity of this absorber is obtained lower than -20 dB in the oblique incident angle from 0to 30at 5.8 GHz circular polarized wave, abbreviated as CP wave, and also the transmittivity is obtain lower than -27 dB in the oblique incident angle from 0to 70, respectively. On the other hand, the transmittance in optics is obtained higher than 60%. Moreover, we study experimentally on the ETC system with placing this absorber between the ETC lane and the adjacent one. We measured the distribution of receiving power on the adjacent lane, when a water sprinkler existed on the ETC lane. As a result, it is confirmed that the receiving power on the adjacent lane could be realized lower than -70.5 dBm, and then a new improvement method has proven to be very useful in the ETC system.

The diagnosis system of Maglev Train is one of most important parts, which can obtain kinds of status messages of electric and electronic devices in vehicle to ensure the whole train safety. In this paper, diagnosis system structure and diagnosis method are analyzed and discussed in detail. The disadvantages of diagnosis system are described. In virtue of the theory of ADS, some basic ideas of ADS are applied in new diagnosis system. The structure, component parts and diagnosis method of new diagnosis system are proposed, designed and discussed in detail. The analysis results show that new diagnosis not only embodies some ADS' ideas but also better meets the demands of Maglev Train Diagnosis System.

This work deploys Autonomous Decentralized System (ADS) based formulation to cluster of networked visual sensors. The goal is to utilize and integrate the sensing and networking capabilities of the sensors with the systematic and autonomous features of ADS to perform visual surveillance through object detection in the covered areas of interest. In the proposed approach, several cells are distributed through an area of interest called Autonomous Observer Cell. The decentralized subsystems detect and track moving objects present on the scene by looking through a camera embedded in each sensor. These subsystems form a cluster and each cluster sends information to an Autonomous Analysis Cell that determines if an object of interest is present. The Autonomous Observer Cells share a common data field and a cluster-head works as a gateway between the cluster and the Autonomous Analysis Cell.

This paper addresses the parameter estimation problem of an interval-based hybrid dynamical system (interval system). The interval system has a two-layer architecture that comprises a finite state automaton and multiple linear dynamical systems. The automaton controls the activation timing of the dynamical systems based on a stochastic transition model between intervals. Thus, the interval system can generate and analyze complex multivariate sequences that consist of temporal regimes of dynamic primitives. Although the interval system is a powerful model to represent human behaviors such as gestures and facial expressions, the learning process has a paradoxical nature: temporal segmentation of primitives and identification of constituent dynamical systems need to be solved simultaneously. To overcome this problem, we propose a multiphase parameter estimation method that consists of a bottom-up clustering phase of linear dynamical systems and a refinement phase of all the system parameters. Experimental results show the method can organize hidden dynamical systems behind the training data and refine the system parameters successfully.

The conventional decentralized supervisory control architectures for discrete event systems assume that default control of controllable events is static. In this paper, we propose a new decentralized supervisory control architecture using dynamic default control of controllable events. We present necessary and sufficient conditions for the existence of a decentralized supervisor in the proposed architecture. Then, we give an example of a language that is achieved in the proposed architecture, but not in the conventional architectures using static default control.

In our previous work, the hyper H∞ filter is developed for tracking of unknown time-varying systems. Additionally, a fast algorithm, called the fast H∞ filter, of the hyper H∞ filter is derived on condition that the observation matrix has a shifting property. This algorithm has a computational complexity of O(N) where N is the dimension of the state vector. However, there still remains a possibility of deriving alternative forms of the hyper H∞ filter. In this work, a fast J-unitary form of the hyper H∞ filter is derived, providing a new H∞ fast algorithm, called the J-fast H∞ filter. The J-fast H∞ filter possesses a computational complexity of O(N), and the resulting algorithm is very amenable to parallel processing. The validity and performance of the derived algorithm are confirmed by computer simulations.

A supervisor proposed by Ramadge and Wonham controls a discrete event system (DES) so as to satisfy logical control specifications. However a precise description of both the specifications and the DES is needed for the control. This paper proposes a synthesis method of the supervisor for decentralized DESs based on reinforcement learning. In decentralized DESs, several local supervisors exist and control the DES jointly. Costs for disabling and occurrence of events as well as control specifications are considered. By using reinforcement learning, the proposed method is applicable under imprecise specifications and uncertain environment.

A batch process is a discontinuous and concurrent process which is suitable for multi-product, small-sized production. The distinctive feature of a batch process is that various decision making processes, such as scheduling, design, operation, etc. are strongly connected with each other. Interaction among these processes is necessary to dynamically and flexibly cope with a variety of unplanned events. This paper aims at presenting a batch scheduling technique based on Petri net models and showing the possibilities of integration between scheduling and design of batch processes. For this purpose, it first views the behavior of a batch operating system as a discrete event system and presents a Petri net model to be used for scheduling, design and operation. It next formulates batch scheduling problems based on Petri net partial languages, proposes their solution technique and last discusses the integration between scheduling and design of batch systems.

Petri nets are a well-known graphical and modeling tool for concurrent and distributed systems, and there have been many results on the theory, and also on practical applications. In the last decade, various Object-Oriented Petri nets (OO-nets) are proposed. As object orientation was adopted for programming languages, extension to OO-nets inspired from object-oriented programming is a natural flow. This article presents state-of-the-art on OO-nets.

Recently, there are so many researches on Autonomous Distributed Manufacturing Systems (ADMSs), where cooperation among agents is used to solve problems, such as the scheduling problem and the vehicle routing problem. We target ADMSs where an ADMS consists of two sub-systems: a Production System (PS) and an Autonomous Transportation System (ATS). This paper discusses an on-line Tasks Assignment and Routing Problem (TARP) for ATSs under conditions of given production schedule and finite buffer capacity. The TARP results in a constrained version of the Pickup and Delivery Problem with Time Windows (PDPTW), and this paper gives a mathematical formulation of the problem. This paper, also, proposes a cooperative algorithm to obtain suboptimal solutions in which no deadlocks and buffer overflows occur. By computational experiments, we will examine the effectiveness of the proposed algorithm. Computational experiments show that the proposed algorithm is able to obtain efficient and deadlock-free routes even though the buffer capacity is less.

This paper proposes a new detection ordering scheme, which minimizes average error rate of the MIMO system with per antenna rate control. This paper shows an optimal scheme minimizing average error rate expressed by the Q function, and simplifies the optimal scheme by using the minimum equivalent SINR scaled by modulation indices, based on approximated error rate. In spite of reduced complexity, the simplified scheme demonstrates the almost same performance as the optimal scheme. Owing to the diversity of detection ordering, the proposed scheme has over 2 dB higher SNR gain at the BER of 10-3 than the existing ordering schemes in balanced array size systems.

Quality of Service (QoS)-constrained policy has an advantage in that it satisfies QoS requirements requested by users. We propose a Quorum based resource management scheme in Grid and resource reconfiguration algorithm based on temporal execution time estimation for satisfying QoS. We compare and evaluate the processing time and deviation of the resource reconfiguration algorithm using a Heart Hemodynamics analysis.

A rack-mounted DC power-supply system utilizing Li-ion batteries, which have higher energy density than conventional VRLA batteries, was developed. The system was designed to have the management functions of Li-ion batteries, such as overcharge protection, over-discharge protection, and cell-voltage equalization, by taking operational requirements into consideration. The volume and weight of the entire system were decreased to one-fourth and three-fifths, respectively, of the volume and weight of a conventional system, making the proposed system ideal as a high-energy-density backup power supply. The functions, system configuration, and characteristics of this rack-mounted DC power supply system utilizing Li-ion batteries are described.

The next-generation wireless networks will bring users with Software Defined Radio (SDR) terminals seamless mobility and ubiquitous computing through heterogeneous networks. This paper proposes a soft-prioritization based system selection algorithm performed by SDR terminal and investigates the effectiveness of the soft-prioritization based system selection by using a concrete simulation model. To maximize the quality of service (QoS), wireless communication systems are prioritized on the basis of criteria for system selection such as data rate, channel quality and cost, and should be dynamically changed. However, frequent inter-system handovers based on hard-prioritization are undesirable in view of interrupting and dropping, particularly for real-time traffic and managing channel capacities. Wireless communication systems are softly prioritized in the soft-prioritization based system selection algorithm, and therefore inter-system handovers between systems with the same priority aren't initiated. To elucidate the validity of the soft-prioritization based system selection algorithm, a system simulation model consisting of five wireless communication systems is employed. Simulation results confirm that the soft-prioritization system selection algorithm offers higher performance in terms of the number of inter-system handovers and throughput of best effort traffic.

The voltage margin of an embedded DRAM's sense operation has been shrinking with the scaling of process technology. A method to estimate this margin would be a key to optimizing the memory array configuration and the size of the sense transistor. In this paper, the voltage margin of the sense operation is theoretically analyzed. The accuracy of the proposed voltage margin model was confirmed on a 0.13-µm eDRAM test chip, and the results of calculation were generally in agreement with the measured results.

Multi-swing trajectories, which refer to those trajectories which oscillate several cycles and then become unbounded, has been a nuisance in general simulation programs for power system stability study since the corresponding transient stability is very difficult to access accurately. In this letter, two possible models are developed to explain possible scenarios of such multi-swing behaviors. Theoretical investigation has strongly indicated a close relationship between multi-swing instability problems and chaotic behaviors of the power system.

A novel digital redesign methodology based on evolutionary programming (EP) is introduced to find the 'best' digital controller for optimal tracking design of hybrid uncertain multi-input/ multi-output (MIMO) input-delay systems with constraints on states and controls. To deal with these multivariable concurrent specifications and system restrictions, instead of conventional interval methods, the proposed global optimization scheme is able to practically implement optimal digital controller for constrained uncertain hybrid systems with input time delay. Further, an illustrative example is included to demonstrate the efficiency of the proposed method.

Though there are intensive researches on off-line electronic cash (e-cash), the current computer network infrastructure sufficiently accepts on-line e-cash. The on-line means that the payment protocol involves with the bank, and the off-line means no involvement. For customers' privacy, the e-cash system should satisfy unlinkability, i.e., any pair of payments is unlinkable w.r.t. the sameness of the payer. In addition, for the convenience, exact payments, i.e., the payments with arbitrary amounts, should be also able to performed. In an existing off-line system with unlinkable exact payments, the customers need massive computations. On the other hand, an existing on-line system does not satisfy the efficiency and the perfect unlinkability simultaneously. This paper proposes an on-line system, where the efficiency and the perfect unlinkability are achieved simultaneously.

This paper deals with new fuzzy controller for handling systems having large dead time and nonlinearities, via approximations of large rule fuzzy logic controller by simplest fuzzy controller (4 rules). The error between large rule fuzzy controller and simplest fuzzy controller are compensated by proposed compensating factors. These compensating factors are modified to handle large dead time and nonlinear systems. Features of proposed approximations are discussed. The concept of variation of nonlinearity factor of fuzzy controller is also discussed. Various processes from different literatures are utilized to demonstrate the proposed methodology. After doing many simulations it has been found that with proper tuning, overall system handles large dead time and nonlinearity which may be difficult by conventional methods. The processes are also simulated for load disturbances and change of operating point (set point) and it has been found that proposed scheme is robust for long dead times.

This paper introduces a state-of-art on an ultra-wideband (UWB) technology in intelligent transport systems (ITS). To examine the detection performance of a UWB short-range radar for vehicular applications, we developed a 26-GHz band short-range UWB radar system with an embedded compact MMIC-based RF module. In this paper, we briefly comment on the current regulatory environment for UWB radar systems by outlining the structure of an international organization involved in examining the regulatory status of these systems. We then describe the principles of detection and system design for impulse radar, the radar system that we developed, and a MMIC-based RF module as well as the performance of these devices. We measured their performance in a series of laboratory experiments and also measured UWB radar cross sections of an automobile. The results of our experiments suggest that our radar system is capable of detecting targets with a range resolution of around 9 cm.