QoS-based Web service ranking problem is complex due to the diverse characteristic of QoS properties and the trade-off issue between them. A ranking mechanism needs to take into account different ways to effectively handle different types of QoS properties measured by different methods with different units and value types, as well as to unify those various QoS measurements in a fair comparison method. In this paper, we present a novel method for ranking and selecting Web services by introducing an extensible QoS model and a corresponding ranking algorithm. The QoS model takes into account the following considerations: different roles and preferences of users and system brokers in specifying QoS demand, different important levels between required QoS constraints and optional QoS preferences, and different QoS value comparison rules with respect to value types and comparative effects of QoS properties. AHP, a multiple criteria decision making method, is applied as an underlying mechanism for developing a flexible and effective ranking algorithm. The experimental results verify that our proposal produces significant achievement with our extensible QoS model and the new service ranking algorithm.

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Service of Digital Satellite Sound Bloadcasting was started. In this paper, we propose a message delivery method using data line of Digital Satellite Sound Bloadcast having large receivable area and broad band of data casting. And, we conduct verification of the system.

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The La_0.5Sr_0.5CoO₃ was used as a cathode for the first time when the plasma display panel was used on the handheld personal computer. It has favorable sputtering resistance characteristic and stable discharge characteristic in gases. A cathode made from the La_0.5Sr_0.5CoO₃ has unique electrical characteristic in early phase discharge voltage and luminescence characteristics. The discharge voltage and luminance continue to decrease from the starting value. In this report, the discharge and luminescence area shift of the La_0.5Sr_0.5CoO₃ were investigated through an analysis of the DC plasma panel which was made as prototype. It is presumed that the discharge voltage and luminance shift is caused by the discharge and luminance area shift of the cathode surface, and that the current density shift is caused by the surface profile of the cathode particles. In order to find out this mechanism, the spherical form model was applied to the discharge voltage shift, and the discharge voltage and luminance shift process was speculated by means of the measured values and this model.

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Silica glass can be ablated using focused laser plasma soft X-rays. The ablation technique enables us to fabricate trenches with a width as narrow as 50 nm. In the present paper, we have investigated the nano-ablation process. The soft X-ray irradiation cause silica surface broken into almost atomic species. Ionic species have kinetic energies higher than that gained by heating up to the boiling point. We measured ablation depth as a function of soft X-ray fluence. The analysis of the depth revealed that soft X-rays are absorbed in silica surface with a effective aborption depth of 10 nm. The result leads to that the energy densty of the soft X-rays per unit volume at the threshold fluence is comparable to that required for breaking silica glass into atomic species. Futher, the results suggests that ablation occurs before diffusion of absorbed energy into the surroudning region. In addition to the energy absorption, repulssive force between ionic species may cause ablation of silica surface by soft X-ray irradiation. These properties of soft X-ray ablation may achieve nano-ablation of silica glass.

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In this paper, we propose a dispersion compensating square-lattice PCF (SPCF) with high negative dispersion characteristics, low confinement losses and relative dispersion slope closely matching the one of conventional single mode fiber (SMF). The design of six air-hole rings SPCF with dispersion coefficient of about -280∼ -390 ps/(nm·km) and low confinement loss of less than 10^-4 dB/km within a considered wavelength range, is confirmed by numerical simulations. In addition, we discuss the splicing problem, its solution and influence of design parameters within a tolerance of ±1% on the proposed SPCF's transmission properties.

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This paper describes improvement of phase noise characteristics of an Fr oscillator. We have examined the configuration of the Fr oscillator, the loaded Q of which is improved by using matching network, and we have predicted value of the loaded Q. Furthermore, we actually made several configurations of Fr oscillator and measured the SSB phase noise. We show the measured loaded Q of Fr oscillator is corresponding to the calculation results well, and the phase noise characteristics are improved by decreasing characteristic impedance of the frequency selective circuit.

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In this study, an expert knowledge-based automatic sleep stage determination system working on a multi-valued decision making method is developed. Visual inspection by a qualified clinician is adopted to obtain the expert knowledge database. The expert knowledge database consists of probability density functions of parameters for various sleep stages. Sleep stages are determined automatically according to the conditional probability. Totally, four subjects were participated. The automatic sleep stage determination results showed close agreements with the visual inspection on sleep stages of awake, REM (rapid eye movement), light sleep and deep sleep. The constructed expert knowledge database reflects the distributions of characteristic parameters which can be adaptive to variable sleep data in hospitals. The developed automatic determination technique based on expert knowledge of visual inspection can be an assistant tool enabling further inspection of sleep disorder cases for clinical practice.

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In this paper, we propose a novel method for acurate automated discrimination of breast tumors (carcinoma, fibroadenoma, and cyst). We defined 199 features related to diagnositic observations noticed when a doctor judges breast tumors, such as internal echo, shape, and boundary echo. These features included novel features based on a parameter of log-compressed K distribution, which reflect physical characteristics of ultrasonic B-mode imaging. Furthermore, we propose a discrimination method of breast tumors by using an ensemble classifier based on the multi-class AdaBoost algorithm with effective features selection. Verification by analyzing 200 carcinomas, 30 fibroadenomas and 30 cycts showed the usefulness of the newly defined features and the effectiveness of the discrimination by using an ensemble classifier trained by AdaBoost.

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This paper investigates a vision based robot control via a receding horizon control strategy for fixed camera systems, as a stabilizing predictive visual feedback control. Firstly, a 3D dynamic visual feedback system with a fixed camera configuration is reconstructed in order to improve performance of estimation. Next, a stabilizing receding horizon control for the 3D dynamic visual feedback system, a highly nonlinear and relatively fast system, is proposed. The stability of the receding horizon control scheme is guaranteed by using the terminal cost derived from the energy function of the dynamic visual feedback system. Furthermore, simulation and actual nonlinear experimental results are assessed with respect to the stability and the performance.

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We are using a ship handling simulator for sea pilot's training; however, in case of entering a port, it is not enough for a visual image around own ship. The general ship handling simulator does not have the visual image (screen) around own ship. We challenge to clear the effect of a visual system around own ship for entering a port. The training for entering a port is one of important training factor for a sea pilot. This paper describes characteristics of captain's visual observation area and the mental workload for ship handling when entering a port. The visual observation area comes from eye movement and the mental workload comes from heart rate variability (R-R interval), nasal temperature. The results show that the visual system around own ship gives their safe ship handling for entering a port based on eye movement.

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A present massage chair realizes the massage motion and force designed by a professional masseur. However, appropriate massage force to the user cannot be provided by the massage chair in such a method. On the other hand, the professional masseur can realize an appropriate massage force to more than one patient, because, the masseur considers the physical condition of the patient. This paper proposes the method of applying masseur's procedure to the massage chair. Then, the proposed method is composed by estimation of the physical condition of user, decision of massage force based on the physical condition and realization of massage force by the force control. The realizability of the proposed method is verified by the experimental work using the massage chair.

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In the situation in which a robot and a human work together by collaborating with each other, a robot and a human share one working environment, and each interferes in each other. In other ward, it is impossible to avoid the physical contact and the interaction of force between a robot and a human. The boundary of each complex dynamic occupation area changes in the connection movement which is the component of collaborative works at this time. The main restraint condition which relates to the robustness of that connection movement is each physical charactristics, that is, the embodiment. A robot body is variability though the embodiment of a human is almost fixed. Therefore, the safe and the robust connection movement is brought when a robot has the robot body which is well suitable for the embodiment of a human. A purpose for this research is that the colaboration works between the self-reconfiguration robot and a human is realized. To achieve this purpose, a self-reconfiguration algorithm based on some indexes to evaluate a robot body in the macroscopic point of view was examined on a modular robot system of the 2-D lattice structure. In this paper, it investigated effect specially that the object of learning of each individual was limited to the cooperative behavior between the adjoining modules toward the macroscopic evaluation index.

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We developed a system that detects spatial signatures from the defect inspection data of each substrate and thus identifies fault detection in device manufacturing. Leveraging the independent component analysis facilitates an unsupervised simultaneous classification of any defect distribution generated with one or more tool malfunctions. All substrates are classified according to our proposed coefficient of similarity to each defect distribution. A root cause process is identified through a test of independence between the manufacturing tools and their rates of the number of classified substrates on the basis of the classification result and their fabrication history data. The tests of independence use χ² tests in combination with exact tests to decrease the incidence of false positive errors. The root cause tool is identified in terms of the highest rate between the tools in the identified process. Our system functions automatically and requires no experience or technical skill. We present the case where for approximately two days, our system detected a tool malfunction earlier than the conventional monitoring of substrates, and with greater total defect counts per substrate than a control limit; further, we present another case where our system detected a greater number of substrates than the conventional monitoring.

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This paper proposes a scheduled model predictive control method such that input and output constraints are satisfied. In particular, an overshoot constraint as an output constraint is dealt with and an offline technique for finding appropriate feedback gains satisfying the overshoot constraint is presented. Moreover, an online technique for tuning the control input is proposed to improve the output response. The proposed method is applied to a pneumatic servo system, and an experimental result is given to show the effectiveness of the proposed method.

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This paper describes a high-speed and a high-accuracy optical position sensor that detects the positions of plural light spots illuminated by various types of light sources, such as light-emitted diode and laser diode. The applications using these systems usually require the measurement performance to be fast, of high accuracy and capable of simultaneously detecting plural points. Moreover, the applications should have some intelligence function, such as the adaptation of the detection procedure to the environment being measured. Here, we designed a new sensor system using an optical 2-D sensor array, an analog parallel scan circuit and a neural network implemented on a Field Programmable Gate Array (FPGA), which satisfied the abovementioned requirements. The experiment results with the prototype sensor system were as follows: (1) The relative error was at most 1.4%; (2) The sampling frequency was about 20kHz; and (3) The sensor system reduced the influence of background light on the position detection by the neural network.

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This paper proposes the automatic color conversion method for color-defective vision persons about presentation slides. In order to set up this method, first, we defined the color combinations which are difficult to distinguish for color-defective vision persons by using the color confusion locus. Second, the function was derived which realizes the brightness difference values between strings and background. Then the automatic color conversion method was constructed by using above the color combinations and the function. By the experimental results, it turned out that the proposed method has been available for color-defective vision persons.

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We aim to synthesize individual facial image with expression based on muscular contraction parameters. We have proposed a method of calculating the muscular contraction parameters from arbitrary face image without using learning for each individual. As a result, we could generate not only individual facial expression, but also the facial expressions of various persons. In this paper, we propose the muscle-based facial model; the facial muscles define both the linear and the novel sphincter. Additionally, we propose a method of synthesizing individual facial image with expression based on muscular contraction parameters. First, the individual facial model with expression is generated by fitting using the arbitrary face image. Next, the muscular contraction parameters are calculated that correspond to the expression displacement of the input face image. Finally, the facial expression is synthesized by the vertex displacements of a neutral facial model based on calculated muscular contraction parameters. Experimental results reveal that the novel sphincter muscle can synthesize facial expressions of the facial image, which corresponds to the actual face image with arbitrary and mouth or eyes expression.

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Counting of passing persons in passage or corridor is considered important for security or various investigations. This paper proposes a method for automatic counting of moving persons with different moving ways in a horizontal view scene. Every gravitational center of a separated block in a frame for detecting motion is plotted in a plotting space. After that, movements of passing persons are detected by Hough transform without motion tracking. Intercepts and slopes of detected lines by Hough transform represent starting times when persons came into a scene and moving speeds of targets. Moving ways also can be recognized by measuring differences of moving speeds of detected persons. The experimental results showed that reliable detection and counting of passing persons were realized by the proposed method.

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Recently, the keyword image retrieval is widely studied. By using these technologies, we can obtain the images with the corresponding keywords easily. In case of conventional image search systems, we search according to the file names basically. However, filenames which is named are frequently incorrect. To resolve this problem, we propose the automatic keyword addition method for scene images. In this paper, there are two important points. One of them is the image segmentation method using the maximum distance algorithm (MDA). The other is the automatic keyword addition using the color feature of regions. The other is the color feature extraction of regions. In the image segmentation method, we propose the automatic decision method of parameters in the MDA. For this purpose, we investigate the relation between the optimal parameters and features of regions. In the color feature extraction of regions, we propose the genetic algorithm(GA). Moreover, in order to show the effectiveness of the proposed method, we show the simulation examples. According to the results of the simulations, we achieve the keyword addition for scene images.

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In a re-entrant flow shop scheduling problem we proposed some algorithms to get a better TAT (turn around time) with a genetic search method. One is an operation which searches for a solution that shifts the start timing in limited areas of each lot. Another is an operation which searches for a solution that shifts left and chooses the machine which starts fastest. Some algorithms are effective on the benchmark including those proposed by Taji et al. In the first step, it is easiest to choose the probabilistic problem by local search. The second step is to search for the solution that shifts the start timing in limited areas of each lot, makes the Gantt chart, chooses the machine and gets the results. The third step is to search for the solution that again shifts left, makes the Gantt chart, chooses the machine and gets the results. The proposed algorithms are more valid than local search methods by Taji et al, such as swap, move, swap-2 neighborhood and FIFO (first in first out). The first algorithm has produced the best result in an experimental test when interval time was short. The second algorithm produced the best result of all solutions. The results have shown that the proposed algorithms are effective for interval time cut and get better TAT than previous methods.

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This paper proposes an efficient learning method for the layered neural networks based on the selection of training data and input characteristics of an output layer unit. Comparing to recent neutral networks; pulse neural networks, quantum neuro computation, etc, the multilayer neural network is widely used due to its simple structure. When learning objects are complicated, the problems, such as unsuccessful learning or a significant time required in learning, remain unsolved. The aims of this paper are to suggest solutions of these problems and to reduce the total learning time. The total learning time means the total computational time required to learn certain objects including adjusting parameter values and restarting the learning from the beginning. Focusing on the input data during the learning stage, we undertook an experiment to identify the data that makes large errors and interferes with the learning process. Our method devides the learning process into several stages. In general, input characteristics to an output layer unit show oscillation during learning process for complicated problems. Focusing on the oscillatory characteristics, it is determined whether the learning will move on to the next stage or the learning will restart from the beginning. Computational experiments suggest that the proposed method has the capability of higher learning performance and needs less learning time compared with the conventional method.

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A macro-action is a typical series of useful actions that brings high expected rewards to an agent. Murata et al. have proposed an Actor-Critic model which can generate macro-actions automatically based on the information on state values and visiting frequency of states. However, their model has not assumed that generated macro-actions are utilized for leaning different tasks. In this paper, we extend the Murata's model such that generated macro-actions can help an agent learn an optimal policy quickly in multi-task Grid-World (MTGW) maze problems. The proposed model is applied to two MTGW problems, each of which consists of six different maze tasks. From the experimental results, it is concluded that the proposed model could speed up learning if macro-actions are generated in the so-called correlated regions.

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This paper describes a prototype and its experimental evaluation of the chat system that offers cooperation support between discussion space and activity space in collaborative learning. In collaborative learning in the proposed system, students are divided into groups, carry out discussion on a study theme by chats, and create on-line reports in cooperative manner. The proposed cooperation support method aims at improving the level of cooperation among students and the effectiveness of the study by making group members grasp other member's study situation mutually through cooperation support in group member's utterance and report creation. We use Wiki as a tool for collaborative work in this research. Cooperation support displays the Wiki's updating time and contents on the chat system with activity cooperation support that offers a space for remote collaborative learning and allows a student to know about other students' condition. In addition, the number of chat utterances was displayed, and other students' condition is easily grasped.

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This paper considers the effectiveness of service business approach for reducing CO₂ emission. “HDRIVE” is a service business using inverters to reduce energy consumption of motor drive. The business model of this service is changed for finding new opportunities of CO₂ emission reduction by combining various factors such as financial service or long-term service contract. Risk analysis of this business model is very important for giving stable services to users for long term. HDRIVE business model is found to be suitable for this objective. This service can be applied to the industries such as chemical or steel industry effectively, where CO₂ emission is very large, and has the possibility of creating new business considering CDM or trading CO₂ emission right. The effectiveness of this approach is demonstrated through several examples in real business.

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An OTDM access system transmitting 4×10Gb/s signal is proposed. All-optical parallel-serial conversion technique using XAM (Cross-absorption modulation) in an EA modulator (EAM) is applied for MUX/DEMUX of the signals. Transmission experiment is carried out using 11-km SMF installed outside. In the experiment, 10-Gb/s NRZ signal is converted to RZ signal using an EAM and a 40-Gb/s signal is made applying OTDM technique. From the observation of the 40-Gb/s signal waveform, fine 4×10Gb/s-to-40Gb/s parallel/serial conversion is confirmed. Simultaneously, the 40-Gb/s signal and 10-GHz optical pulses after transmitted 11-km SMF are injected to an EAM and 40Gb/s-to-4×10-Gb/s signal conversion is also confirmed.

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In this study, we propose evolutionary computation technique that uses physiological index and subjective evaluation as evaluation value. With this technique, the system provides and presents media contents to a user, and the user listens or watches and evaluates them as same as conventional evolutionary computation. In a same time, user's physiological signal is measured and used as evaluation value. As a concrete system, we construct an evolutionary computation system creating musical piece based on user's heartbeat information and simple subjective evaluation relating to relaxation and favor. Furthermore, an action of the system is fundamentally confirmed with listening experiment.

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