The roadside network system for ITS services uses microcells in its access infrastructure. For the roadside network that provides the uninterrupted communication using microcells such as DSRC, an effective communication control scheme must be established so as to manage the communication passes to vehicles in the network. One of the fundamental requirements for the communication control scheme for the roadside network is to assure fault-tolerance, which means in this system that the communication control mechanism needs to be managed even in part of the base stations in the network might be in fault. On the other hand, for the communication control in the roadside network using microcells, issues to be solved are the handover mechanism for taking over connection information to provide uninterrupted communication environment, which causes the degradation of the end-to-end throughput. In order to solve those problems, the authors developed a communication control scheme. We implemented the scheme as the specific 'ADS algorism' to control the communication zone dynamically, which works effectively on the Autonomous Decentralized System (ADS) communication platform. Furthermore, we also developed the specific ADS algorism to assure fault-tolerance for the communication zone control, which can reconfigure the communication zone in case the BSs in the roadside network are in fault and can keep the operations by the reconfigured communication zone. We evaluated the ADS algorism for the communication zone control by computer simulation. The results show the effectiveness of the ADS algorism for the dynamic communication zone control mechanism and for the fault-tolerant mechanism for communication zone reconfiguration on fault.

One of the most challenging tasks in computer graphics and cyberworlds is the realistic animation of the behavior of virtual agents emulating human beings and evolving within virtual 3D worlds. In a previous paper, the authors presented a new, sophisticated behavioral system that allows the agents to take intelligent decisions by themselves. A central issue of this process is the adequate choice of appropriate mechanisms for goal selection. This is actually the aim of the present contribution. In this paper a new scheme for goal selection is described. According to it, the goal's priority is calculated as a combination of different agent's internal states (given by mathematical functions also described in this paper) and external factors (which will determine the goal's feasibility). The architecture of the goal selection module as well as its simulation flow are also analyzed in this paper. Finally, the excellent performance of this new scheme is enlightened by means of a simple yet illustrative example.

A new interacting multiple model (IMM) algorithm using intelligent input estimation (IIE) is proposed for maneuvering target tracking. In the proposed method, the acceleration level for each sub-model is determined by IIE-the estimation of the unknown target acceleration by a fuzzy system using the relation between the residuals of the maneuvering filter and the non-maneuvering filter. The genetic algorithm (GA) is utilized to optimize a fuzzy system for a sub-model within a fixed range of target acceleration. Then, multiple models are represented as the acceleration levels estimated by these fuzzy systems, which are optimized for different ranges of target acceleration. In computer simulation for an incoming anti-ship missile, it is shown that the proposed method has better tracking performance compared with the adaptive interacting multiple model (AIMM) algorithm.

This paper presents two new intelligent methods to linearize the Multi-Carrier Power Amplifiers (MCPA). One of the them is based on the Neuro-Fuzzy controller while the other uses two small neural networks as a polar predistorter. Neuro-Fuzzy controllers are not model based, and hence, have ability to control the nonlinear systems with undetermined parameters. Both methods are adaptive, low complex, and can be implemented in base-band part of the communication systems. The performance of the linearizers is obtained via simulation. The simulation is performed for three different scenarios; namely, a multi-carrier amplifier for GSM with four channels, a CDMA amplifier and a multi-carrier amplifier with two tones. The simulation results show that Neuro-Fuzzy Controller (NFC) and Neural Network Polar Predistorter (NNPP) have higher efficiencies so that reduce IMD3 by more than 42 and 32 dB, respectively. The practical implementation aspects of these methods are also discussed in this paper.

The traffic congestion problem in urban areas is worsening since traditional traffic signal control systems cannot provide] efficient traffic regulation. Therefore, dynamic traffic signal control in Intelligent Transportation System (ITS) recently has received increasing attention. This study devised a multi-agent architecture, the Adaptive and Cooperative Traffic light Agent Model (ACTAM), for a decentralized traffic signal control system. The proposed architecture comprises a data storage and communication layer, a traffic regulation factor processing layer, and a decision-making layer. This study focused on utilizing the cooperation of multi-agents and the prediction mechanism of our architecture, the Forecast Module, to forecast future traffic volume in each individual intersection. The Forecast Module is designed to forecast traffic volume in an intersection via multi-agent cooperation by exchanging traffic volume information for adjacent intersections, since vehicles passing through nearby intersections were believed to significantly influence the traffic volume of specific intersections. The proposed architecture can achieve dynamic traffic signal control. Thus, total delay time of the traffic network under ACTAM can be reduced by 37% compared to the conventional fixed sequence traffic signal control strategy. Consequently, traffic congestion in urban areas can be alleviated by adopting ACTAM.

This paper presents a VLSI design methodology for the MAC-level DWT/IDWT processor based on a novel limited-resource scheduling algorithm. The r-split Fully-specified Signal Flow Graph (FSFG) of limited-resource FIR filtering has been developed for the scheduling of the MAC-level DWT/IDWT signal processing. Given a set of architecture constraints and DWT parameters, the scheduling algorithm can generate four scheduling matrices that drive the data path to perform the DWT computation. Because the memory for the inter-octave is considered with the register of FIR filter, the memory size is less than the traditional architecture. Besides, based on the limited-resource scheduling algorithm, an automated DWT processor synthesizer has been developed and generates constrained DWT processors in the form of silicon intelligent property (SIP). The DWT SIP can be embedded into a SOC or mapped to program codes for commercial off-the-shelf (COTS) DSP processors with programmable devices. As a result, it has been successfully proven that a variety of DWT SIPs can be efficiently realized by tuning the parameters and applied for signal processing applications.

We describe a new inconsistent case which is susceptible to occur while producing consistent answer set using prioritized default logic. We define new semantics for prioritized default logic in order to solve this problem. There is a sign difference between General and Extended logic programs. Extended logic programs are formulated using classical negation, For this reason, an inconsistent answer set can sometimes be produced. For the most part, default reasoning semantics successfully resolved this problem, but a conflict could still arise in one particular case. The purpose of this paper is to present this eventuality, and revise the semantics of default logic in order to give an answer to this problem.

A new approach for ultra-low-power LSIs based on quantum devices is presented and its present status and critical issues are discussed with a brief background review on the semiconductor nanotechnology. It is a hexagonal binary decision diagram (BDD) quantum logic circuit approach suitable for realization of ultra-low-power logic/memory circuits to be used in new applications such as intelligent quantum (IQ) chips embedded in the ubiquitous network environment. The basic concept of the approach, circuit examples showing its feasibility, growth of high density nanostructure networks by molecular beam epitaxy (MBE) for future LSI implementation, and the key processing issues including the device isolation issue are addressed.

This paper outlines and analyses major P2P technologies currently being actively studied at various research organisations or already in use in both business and personal environments. Various technical features of P2P as well as its history and market trends are shown. P2P principles focussing on discovery and network-organisational mechanisms of major P2P systems such as JXTA, SIONet, Freenet, and Chord are first summarised. Also, other technical issues related to delivery, network control, security, digital rights management, and distributed computing are described. Then, P2P technologies to promote next-generation community networks with autonomous and intelligent characteristics are addressed. Based on these, P2P applications are analysed and some examples are shown. Studies of P2P traffic measurement, which is difficult by using traditional evaluation methods, are taken up to consider total network design in the P2P era.

In order to achieve a transponder antenna for intersection collision avoidance systems in Intelligent Transport Systems, a lens horn antenna that generates a cosecant squared beam is developed. This paper clarifies the method for designing the antenna to achieve accurate radiation pattern synthesis. A H-plane sectral horn is selected. The ray tracing method is employed in the design of the lens shape. The aperture of the horn is determined to be seven wavelengths based on a comparison of calculated radiation patterns and the desired cosecant squared beam shape. Accurate electrical performance, such as radiation patterns and electrical fields in the horn, is calculated using Finite Difference Time Domain software. Electrical field disturbances caused by reflected waves at the lens surfaces expanded widely inside the small horn. As a result, sidelobe levels of the radiation patterns are increased. In order to eliminate these disturbances, matching layers are attached to the shaped lens surface. Then, electrical field distributions in the horn are recovered and disturbances disappear. Measured radiation patterns become almost the same as that designed using the ray tracing method. The results show that application of the ray tracing method to radiation pattern synthesis of a small lens horn antenna is effective. We clarify the electrical field disturbances caused by reflections at the lens surfaces and show that eliminating the reflection at the lens surface by attaching matching layers is very important to achieving radiation pattern synthesis.

Although production systems are widely used in artificial intelligence (AI) applications, they are seen to have certain disadvantages in terms of their need for special purpose assistance software to build and execute their knowledge-bases (KB), and in the fact that they will not run on any operating system (platform dependency). Furthermore, for AI applications such as learning assistance systems, there is a strong requirement for a self-adaptive function enabling a flexible change in the service contents provided, according to the user. Against such a background, a Java based production system (JPS) featuring no requirement for special purpose assistance software and no platform dependency, is proposed. Furthermore, a new self-adaptive Java production system (A-JPS) is proposed to realize the "user adaptation" requirement mentioned above. Its key characteristic is the combination of JPS with a Causal-network (CN) for obtaining a "user profile". In addition, the execution time of the JPS was studied using several benchmark problems with the aim of comparing the effectiveness of different matching algorithms in their recognize-act cycles as well as comparing their performance to that of traditional procedural programs for different problem types. Moreover, the effectiveness of the user adaptation function of the A-JPS was studied for the case of a CN with a general DAG structure, using the experimental KB of a learning assistance system.

In 1960, the famous computer pioneer J.C.R. Licklider described a vision for human-computer interaction that he called "man-computer symbiosis. " Licklider predicted the development of computer software that would allow people "to think in interaction with a computer in the same way that you think with a colleague whose competence supplements your own. " More than 40 years later, one rarely encounters any computer application that comes close to capturing Licklider's notion of human-like communication and collaboration. We echo Licklider by arguing that true symbiotic interaction requires at least the following three elements: a complementary and effective division of labor between human and machine; an explicit representation in the computer of the user's abilities, intentions, and beliefs; and the utilization of nonverbal communication modalities. We illustrate this argument with various research prototypes currently under development at Mitsubishi Electric Research Laboratories (USA).

In this paper, we propose a new content delivery platform on the ITS (Intelligent Transport Systems) road-vehicle communication system on the basis of ROF (Radio over Fiber). The platform is strongly motivated by the ROF communication system capabilities of (1) broadband access, (2) integrated multiple service transmission interface, and (3) simultaneous use of a single and downsized vehicle terminal shared among multiple services based on a multi-mode software radio system. Content is delivered on per reservation basis, as is carefully envisaged as a primary service which is subjected to immaturity of early ITS road-vehicle communication systems, and is provided in limited service areas such as parking on main highways. After the reservation, requested content is stored in a cache connected to a ROF local station via optical fiber. At the designated time, the content is delivered from the cache to a target terminal by way of the ROF local station at high-speed. It can also be done by moving the content from the cache to another cache depending on the target terminal location in a flexible and reliable manner, even if the target terminal could not reach the place at the time designated in the reservation. Such flexibility and reliability are required for consequent practical application, and are provided using information given in the reservations. We implement a preliminary system to evaluate the proposed platform from the viewpoints of (1) processing time from logging into the system for a reservation to delivering content to the target terminal and (2) amount of control traffic required for the delivery. The results show that the proposed platform in which content is delivered from a cache connected with a ROF local station distributed geographically is effective. We also evaluate content delivery throughput using the system connected with an actual ROF local station, and show that the effective throughput is 40 Mbps and the proposed platform is a promising ITS service platform. The paper concludes by discussing future study toward realizing a more promising and practical system.

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.

It is expected that per-user customized services are widely used in next generation Personal Communication Network. To provide personalized services for each call, per-user service profiles are frequently referenced, so efficient service profile management is essentially required. To provide service profile based services, typically two schemes can be employed: One is Intelligent Network based Central scheme and the other is IMT-2000 based full replication scheme, we refer to as Follow-Me Replication Unconditional (FMRU). Since the Central scheme only depends on the service call rate and the FMRU is merely dependent on the movement rate, it is apparent that the FMRU scheme outperforms the Central scheme if the call-to-mobility ratio (CMR) is large, and vice versa. In this paper, we propose a new service profile replication schemes, Adaptive Follow-Me Replication Conditional (AFMRC) that determine replication automatically according to the user's varying CMR in real-time. We compared the performance of the AFMRC with the previous non-adaptive Follow-Me Replication Conditional (FMRC) scheme. Performance results indicate that as the CMR of a user changes, AFMRC adapts well compared to the existing schemes.

Intelligent paging uses the sequential paging technique with additional user information in order to reduce the paging delay cost and the paging load cost. Our proposed paging scheme uses distribution density information of users as required additional user information. This letter addresses an optimal paging sequence and introduces formulas to calculate the paging costs. These formulas are necessary to evaluate the performance of location management. The paging delay cost and the paging load cost for the proposed paging scheme and two other paging schemes are calculated and numerical analyses for these paging schemes are performed. Results show how the paging delay cost and the paging load cost vary as either the paging request arrival rates or the number of cells in an LA increases. The proposed paging scheme is more efficient in view of both the paging delay cost and the paging load cost.

The present paper addresses the design of manufacturing systems. A resource planning and task allocation problem is proposed, and a multi-agent system for this problem is discussed. In the multi-agent system, an agent exists for each resource and for each operation. The proposed multi-agent system improves the quality of resulting plans by the learning of these agents.

This paper describes a rhythm pattern accuracy diagnosis system based on the rhythm pattern matching algorithm and a diagnosis feedback method by employing the SVM technique. A beat rhythm pattern is recorded by a PC and analyzed with an algorithm including cluster-analysis-based pattern matching. Rhythm performance is represented by a performance feature vector, which features note length deviation, note length instability, and tempo instability. The performance feature vector is effective for objectively evaluating the accuracy of rhythm patterns objectively. In addition, this system has the music experts' knowledge base, which is calculated from the performance feature vectors associated with the experts' subjective evaluation by listening to the performance. The system generates both an objective measuring report, and experts' comments for learners. Reproductivity of experts' comments is statistically indicated to be excellent for eight rhythm patterns, two tempo levels, and eight users. Reliability of experts' comments are also described considering the threshold of the decision function of SVM. Subjective evaluation of the system is carried out by fifteen users by a questionnaire using the SD method. As a result of factor analysis for the sixteen questions, four factors named "Audio-visual representation," "User-friendliness," "Reliability," and "Window representation," are extracted. Users' four factor scores indicate that the system is reliable and easy to use.

This paper presents a fuzzy control-based intelligent medium access controller (FiMAC), which optimizes random access control between heterogeneous traffic aiming at more efficient voice/data integrated services in dynamic reservation TDMA-based broadband radio access networks. In order to achieve the design objective, viz. a differentiated quality-of-service (QoS) guarantee for individual service plus maximal system resource utilization, the FiMAC intelligently and independently controls the random access parameters such as the lengths of random access regions dedicated to respective service traffic and the corresponding permission probabilities, frame-by-frame basis. In addition, we have adopted a mobile-assisted random access mechanism where the voice terminal readjusts a global permission probability from the FiMAC, to handle the 'fair access' issue resulting from distributed queueing problems inherent in the access network. Our extensive simulation results indicate that the FiMAC is well coordinated with a mobile-assisted mechanism such that significant improvements are achieved in terms of voice capacity, delay, and fairness over most of the existing MAC schemes for the integrated services.

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 that switch strategies depending on system conditions to achieve better performance than can be realized by agents that use the same strategies under all system conditions. For the real-time job scheduling problem, the paper presents a basic CDA architecture and the results of an extensive empirical evaluation of its performance relative to other rule-based schemes based on several common indices for real-time dispatch.