Object-oriented technology is used for the software of the large range, and its application fields are increasing. Object-oriented technology is also accepted naturally in the field of Internet application. Consequently, developments of new kinds of object-oriented technologies have been performed. Agent technology has been developed based on an object-oriented concept, and may have a great evolution with applying to applications of Internet field. In this paper, authors introduce the latest trend and the example of application of such object-oriented technology and agent technology.

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This paper describes the foundations of Object-oriented and Agent Technologies for younger readers as a guide to understand research papers in this special issue.

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We developed a dynamic pair-program downloading architecture to establish flexible industrial remote operation environments. In the architecture, a pair of programs appears in one remote operation context. One program is downloaded to a plant side and another is downloaded to a remote operator side. Both programs are simultaneously started and communicate each other. The remote-side operator’s commands are executed in the plant side program and the execution results are viewed via the operator-side program. By using this architecture, the remote-side operator is able to select best match programs whenever he or she needs, and dynamically start them. Remote operations such as maintenance, diagnoses, and command executions are more and more needed in these days in industrial automation domains. This architecture provides a solution for flexible computing environments where dynamic operation changes are highly needed. In this paper, we explain our architecture first, and then, report the evaluation results through the experiences of architecture development, prototype application developments, and using the applications in a real remote plant-operation environment

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We propose a fault-tolerant mechanism based on message integrity code (MIC) method for mobile agent authentication under non-secured network environment. We introduce one or more secured nodes (OASIS NODE) and a mobile agent (FT_Agent) having a replica management mechanism. We assume that the candidate agents for authentication are safely stored in an OASIS NODE and a shared secret key is safely distributed to user terminals from the OASIS NODE at the beginning. When the replica agents on user terminals need their authentication, they calculate MIC by using the shared secret key and move themselves having the MIC to the OASIS NODE, which verifies the MIC. The FT_Agents which are also verified by an OASIS NODE are distributed to the each agent and dynamically manage active replicas and passive replicas. By introducing the MIC method and the replica management mechanism, a secured fault-tolerant system suitable for mobile agents under non-secured network environment can be constructed.

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This paper proposes a new cooperative trading system model using marketers’ evaluation functions of their preferences to goods. We introduce a computational market mechanism as a solution to the distribution of goods according to the market model. Every customer would not accept any reduction of evaluation without any merit like price cuts. As a result, suppliers must pay rewards to customers to cooperate with each other. This approach provides us with an on-line estimation of the evaluation functions and rewards. In addition to them, it can deal with time-variable tendency of customers.

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In recent years, improvement in computer performance and development of computer network technology or the distributed information processing technology has a remarkable thing. Moreover, the deregulation is starting and will be spreading in the electric power industry in Japan. Consequently, power suppliers are required to supply low cost power with high quality services to customers. Corresponding to these movements the authors have been proposed SCOPE (System Configuration Of PowEr control system) architecture for distributed EMS/SCADA (Energy Management Systems / Supervisory Control and Data Acquisition) system based on distributed object technology, which offers the flexibility and expandability adapting those movements. In this paper, the authors introduce a prototype of the power system information delivering system, which was developed based on SCOPE architecture. This paper describes the architecture and the evaluation results of this prototype system. The power system information delivering system supplies useful power systems information such as electric power failures to the customers using Internet and distributed object technology. This system is new type of SCADA system which monitors failure of power transmission system and power distribution system with geographic information integrated way.

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Since computerized documents, e.g. XML documents, have been increased, it is desired to find particular information from a huge amount of XML documents. This paper proposes an automatic method for extracting keywords from the valid XML documents. Structured elements of an XML document are defined by DTD. We consider that a certain element of the structure represents importance for the document. First, the importance of an element is determined by the definition in DTD. For example, elements that cannot be omitted and elements that appear only once at the maximum in their parent elements are considered important ones. Second, all elements in the target XML document are scored by the tree structure of elements and contained texts in the document. Third, candidates of the keywords are extracted from elements with the scores. Finally, scores are summed up and candidates ranked higher are selected as keywords of the XML document. The validity of this method is examined.

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We describe a new framework for multiagent systems, framework which contributes to increase the efficiency of development and maintainability with reusable code, and to realize the transition from simulation to hardware smoothly. Multiagent system (MAS) is a kind of the complex system by which an unexpected behavior emerges caused by interaction between each agent. Recently, the system is well known as a novel design technique which realizes acquiring of suitable behavior autonomously in spite of unknown environment. However, since most application is only designed with its independent specification, there are some problems in which the comparative evaluation among the MASs and the reusing of design are hard to realize. Supposing a common framework for MAS is usable, the development efficiency of MAS would be improved greatly. In this paper, first, we point out the need of the framework for MAS. Second, we clarify the problems on designing of the framework. In order to resolve the problems, we apply the design patterns element of object-oriented paradigm which are catalogued by Gamma et al. Third, we design a new framework for MAS, framework which realizes the compatibility among same functional components and the evolutionary programming. Finally, in order to discuss the effectivity of the framework, we design a crowd behavior simulator using the framework, and confirm its high potential for reusable software

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Controlling the progress for software development project has been managed from only developers’ point of view. Especially in implementation phase, the progress reports of coding and testing have been explained by using modules or classes. However, it is not easy for users to understand those specified notions. In object-oriented methods, it is advocated to keep the consistency of the process by using use cases, which are understandable for users and developers. Nevertheless, in the present stage, use cases have not been used enough to improve the communication between developers and users. We propose a new controlling system of progress by using use cases in implementation phase, which doesn’t increase developers’ burdens. This system was accomplished by linking classes and methods in both of implementation phase and analysis phase.

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In recent years, online shopping has been popularized. However, the users can not find efficiently their items at on-line markets. This paper proposes an engine to find items easily at the online market. This engine has the following facilities. First, it presents information in a fixed format. Second, the user can find items by selected keywords. Third, it presents only necessary information by using his/her history. Finally, it has a customize function for each user. Moreover, the system asks the users to down load a page of recommended items. We show the effectives of our proposal with some experiments.

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Genetic Algorithm(GA) is widely known as a general-purpose optimization method, which can provide sub-optimum solutions for various optimization problems by means of modeling genetic evolutionary process of creatures. Several essential difficulties exist in GA, however, with regard to large amount of computation time and proper adjustment of many GA parameters. In order to overcome the difficulties of GA, this paper describes the architecture for a high speed evolutionary computation, which is optimized hierarchic pipelines to take generation models into consideration and can be flexible genetic operations corresponding to a given problems. Simulation results evaluating the proposed architecture show to achieve 193 times speed on average compared with software processing.

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Various surface-cooling apparatus such as the cooling cap, muffler and blankets have been commonly used for the cooling of the brain to provide hypothermic neuro-protection for patients of hypoxic-ischemic encephalopathy. The present paper is aimed at the brain temperature regulation from the viewpoint of automatic system control, in order to help clinicians decide an optimal temperature of the cooling fluid provided for these three types of apparatus. At first, a biothermal model characterized by dynamic ambient temperatures is constructed for adult patient, especially on account of the clinical practice of hypothermia and anesthesia in the brain hypothermia treatment. Secondly, the model is represented by the state equation as a lumped parameter linear dynamic system. The biothermal model is justified from their various responses corresponding to clinical phenomena and treatment. Finally, the optimal regulator is tentatively designed to give clinicians some suggestions on the optimal temperature regulation of the patient’s brain. It suggests the patient’s brain temperature could be optimally controlled to follow-up the temperature process prescribed by the clinicians. This study benefits us a great clinical possibility for the automatic hypothermia treatment.

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A cascaded second order notch filter implemented using an allpass filter, for elimination of multiple sinusoids, has been proposed. Various adaptive algorithms for the adaptive notch filters are used. As the one of them, an adaptive algorithm which has a reduced bias in comparison to the gradient based algorithm has been proposed. It has the problem that the convergence speed deteriorates when the number of the narrow band signal increases. Therefore, a small step size is required. However, the range of the step size for the adaptive notch filters to be stable has not been derived yet. The purpose of this paper is the derivation of it by using the principle of the contraction mapping. Finally, computer simulation results are presented to confirm the convergence characteristics.

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In the analysis-synthesis coding of speech signals, realization of the high quality in the low bit rate coding depends on the extraction of its characteristic parameters in the pre-processing. The precise extraction of the fundamental frequency, one of the parameters of the source information, guarantees the quality in the speech synthesis. But its extraction is difficult because of the influence of the consonant, non-periodicity of vocal cords vibration, wide range of the fundamental frequency, etc..
In this paper, we will propose a new fundamental frequency extraction with the criterion based on its harmonics structure and low bit rate speech coding system using the Wavelet transform.

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This paper proposes a method for extracting lip shape and its location from sequential facial images by using color information. The proposed method has no need of extra information on a position nor a form in advance. It is also carried out without special conditions such as lipstick or lighting. Psychometric quantities of a metric hue angle, a metric hue difference and a rectangular coordinates, which are defined in CIE 1976 L*a*b* color space, are used for the extraction. The method employs fuzzy reasoning in order to consider obscurity in image data such as shade on the face.
The experimental result indicate the effectiveness of the proposed method; 100 percent of facial images data was estimated a lip’s position, and about 94 percent of facial images data was extracted its shape.

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Polyethylene resins (PE), having extremely superior electric characteristics, are widely used as an insulating material of cables for high voltage. However, cables such as PE cables can deteriorate by oxide. Therefore, materials with less oxide deterioration urgently need to be developed. As a valuation of oxide deterioration, some parameters for chemiluminescence are known to have a strong correlation with results of the stability test of high polymer materials. From the chemiluminescence measurement of samples, in which PE with an annex of 0.3 (per hundred resin, phr) vapor grown carbon fiber(VGCF) was treated by heat at 120°C for 72 hours, the luminosity decreased by approximately 1/6 of PE with non-annex. Moreover, in the case of an annex of 5 phr for PE, the luminosity became approximately 1/30 of PE with non-annex, which reveals that PE with an annex of 5 phr has extremely low oxide deterioration. This indicates that an annex of VGCF can decrease the amount of chemiluninescence of PE, which improves resistance against oxidization.

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The Wiener model consists of a linear dynamic block in cascade with a static nonlinearity. And many physical systems can be naturally described by the Wiener systems. The linear subsystem is modeled by the transfer function model, and the non-linear function of the Wiener system is expressed by the artificial neural networks which have the ability to learn complex nonlinear relationships. The parameters of both linear and non-linear subsystems are estimated simultaneously, by optimizing the nonlinear objective function which is the total error of the system and the model.
As the order of linear subsystem and the adequate number of hidden neurons are unknown, they are estimated by the minimum description length criteria. The generalized predictive control is applied to the linear subsystem, and the estimated parameters of linear and non-linear subsystem are used adaptively to the generalized predictive control. The numerical examples demonstrate the validity of both proposed identification method and control design.

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The development of small, light weight, low power navigation system for guidance of both tethered and autonomous Unmanned Underwater Vehicle (UUV) is required in applications such as deep salvage, oil and gas well head and pipe line laying and maintenance, etc. All have stringent position requirements in order to define target locations followings the initial find, minimize search time for return missions, as well as support of autopilot functions. In these applications mainly an accurate Sonar Doppler Velocity Log (DVL) was used for Inertial Navigation System (INS) error corrections. But the settlement of DVL is not affordable to various UUV so that not convenient to low cost and small UUV. In this paper we propose a new algorithm for combining the low cost but highly accurate INS with Water Screw Speed (WSS) of the UUV efficiently. In order to evaluate our algorithm we produced the data acquisition system and after several experimental run, we simulated this algorithm searching the error correlation time and noise variance of these estimations.

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This paper presents a practical control method for the experimental mobile vehicle. By merging the advantages of the neural network, adaptive algorithm and fuzzy control, the adaptive fuzzy control based on neural network is presented. This adaptive fuzzy control system can deal with a large amount of training data by the neural network, from these data produce more reasonable fuzzy rules by the adaptive (clustering) algorithm, at last control the object by the fuzzy control. It is not the simple combination of the three methods, but merging them into one control system. Experiments and some future considerations are also given.

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We have developed a view-based visual tracking system to cope with change of the appearance of the template in 3D environment using affine transformed templates. We have extended the system to stereo vision for hand over action between human and robot. The system estimates 3D pose of a target object while performing 2D tracking of different parts of the object in the stereo images.

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This paper presents a vision and landmark based approach to improve the efficiency of probability grid Markov localization for mobile robots. The proposed approach uses visual landmarks that can be detected by a rotating video camera on the robot. We assume that visual landmark positions in the map are known and that each landmark can be assigned to a certain landmark class. The method uses classes of observed landmarks and their relative arrangement to select regions in the robot posture space where the location probability density function is to be updated. Subsequent computations are performed only in these selected update regions thus the computational workload is significantly reduced. Probabilistic landmark-based localization method, details of the map and robot perception are discussed. A technique to compute the update regions and their parameters for selective computation is introduced. Simulation results are presented to show the effectiveness of the approach.

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This paper proposes an electric field optimization at the joint of power cables using the evolution strategy(ES). The object is to minimize the electric field strength on the inner curved surface of the electrode under the constraint that the electric field strength along the interface between the two different insulators should be below a permissible value. The second order of Riesenfeld spline function is applied for smoothing the inner curved electrode surface. The surface charge method that provides accurate solutions on the boundaries for the multi-layer substances with less number of elements is employed for the calculation of the electric field distributions. ES can easily omit the cases that are out of the constraint condition. Moreover, ES can easily change the search width in the consequence of searching the shape. The searching process of ES was compared with that of the genetic algorithm(GA). As a result, ES reduces the electric field strength on the inner curved electrode compared to GA. In the best case, the electric field strength was reduced to 49.7% that of an initial model.

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In this paper, rainfall is predicted by using a Neural Network(NN) and a Genetic Algorithm(GA). GA selects data needed to predict the rainfall. NN learns and predicts it using attributes selected by GA. The real-coded GA is used to decide data priority, and data really needed for the rainfall forecast are selected based on the priority. In order to show the effectiveness of the proposed rainfall prediction system, computer simulations are performed for real weather data. Finally, the effectiveness of this system is shown with data analysis.

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In this paper, we adopt a genetic-based machine learning (GBML) approach to a realtime scheduling problem in which several products are to be assigned to one of the buffers, and propose a method of generating and selecting rules for assigning each product to a desirable buffer. In applying the GBML, we use the Pitt approach, where the set of rules (rule-set) is represented symbolically as an individual of genetic algorithms, and the fitness of an individual is calculated based on the total cost required for transporting, operating and keeping of whole products. Through some computational experiments, the effectiveness and the possibility of our approach is investigated.

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Graph partitioning is an important problem that has extensive applications in many areas, including VLSI design, scientific computing, data mining, geographical information systems and job scheduling. The graph partitioning problem (GPP) is NP-complete. There are several heuristic algorithms developed finding a reasonably good resolution. The most famous partitioning methods are simulated annealing (SA) and mean field algorithm (MFA) known to produce good partition for a wide class of problems, and they are used quite extensively. However these methods are very expensive in time and very sensitive in parameters tuning methods.
In this paper, a new parameter-free algorithm for GPP has been proposed. The algorithm has been constructed using the S-model learning automata with multi-teacher random environments. As shown in our experiments, the proposed algorithm has some advantages superior to SA, MFA and ParMeTiS.

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Market Oriented Programming (MOP) proposed by Wellman is a decentralized control method using auction machanism inspired by the market economy. It is applied to many problems such as network and computation resource allocation. Conventional MOP models are formulated based on the concept of ‘competitive market’ of economics which assumes that the market consists of sufficiently many and small agents. However, in realistic applications of MOP, number of agents is limited and their interdependency is not negligible. In this paper, MOP for interdependent agents is discussed. An oligopoly market model for MOP is introduced, and adaptation process of interdependent agents and its stability are discussed. Further, it is also demonstrated that selfish learning of adaptation coefficiency by each agent achieves stability of market through computer simulation.

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We studied the optical forces acting on a sphere in order to corroborate the three-dimensional optical trapping by the laser beams from optical fiber ends inserted at an angle. From these investigations, we verified that the stiffness of the produced restoring forces to the equilibrium point depended on the horizontal distance between each optical fiber end, and the strong restoring force could be obtained when the beam waists of the laser beams from lensed optical fiber ends coincided at the beam-crossing point.

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Matching with stereo camera images is a fundamental task to recover 3D. In this paper, we match with vertex points of images by searching the information of the incidence matrixes of the graphs.The stereo segment images are specified to a basis (BI) and a reference image (RI), respectively. First the tree and their order of vertexes of BI are determined by depth-first search. The search is carried out by tracing the degrees order of vertexes of RI corespond to that of BI.

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