We have fabricated short-gate A1GaN/GaN HEMTs by using electron beam lithography technique. The devices show good pinch-off characteristics, and typical parameters of g_m=195mS/mm, f_T=26GHz, f_max=80GHz, V_S=3.6 × 10⁶cm/s were obtained. We have also conducted photoluminescence and electroluminescence(EL) measurements in order to clarify the carrier transport mechanism. It is found that a single peak in the EL spectrum due to the intraband transition of the channel electrons in the high field region at the drain edge.

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We propose a novel method to discriminate tissue regions in ultrasonic image by using adaptive smoothing filter for speckle suppression, wavelet transform and active surface model. We analyzed three dimensional images of superficial peripheral vein acquired by a high-frequency ultrasonic diagnostic equipment. Diagnosis of superficial peripheral vein is regard as an important matter for diagnosis of functional disease at a blood vessel. We attempt to detect three dimensional structure and shape of superficial peripheral vein by the application of the proposed method.

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The technique of magnetic stimulation has been applied to studies on the human brain and neurological research. The most application or methods of magnetic stimulation is, to stimulate the human brain and obtain the peripheral responses, as EMG signals. In contrast, it was very difficult to obtain the EEG responses from human brain by using magnetic stimulation, because the artifact of its high powered electric fields.
In this study, we have developed the artifact free EEG measurement system by using magnetic stimulation with a technique of delayed measurement. By using this system, we have obtained very interesting results of EEG responses by magnetic stimulation.

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We have so far designed and constructed a facial recognition system based on the optical parallel Joint Transform Correlator combined with a digital computer. In addition to this, we devices a compact prototype PJTC (COPaC) and examined it for a practical use. According to the guideline for identification using biometrics, we carried out the accuracy evaluation by one-to-one collation using 300 facial images. We ascertained its performance to be remarkably precise and thus reliable.
In this paper, we proposed the Real-time individual authentication system in the mobile network, which is based on an optical correlation. It was examined for the influence of the camera resolution, image compression and background removal. Consequently, we confirmed that this system is highly robust against these potential influences. Moreover, we tested this in a wireless LAN environment, and verified its high possibility for a further facial identification use.

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The newly developed monitor watches the fluidized condition of FBC (Fluidized Bed Combustor), referring to acoustic signals which are collected by heating tubes in the beds and passing to tube acceleration sensors outside the fluidized Beds. The monitor can be applied to FBC easily without any observation hole or special probes, and detects the bad-fluidized region, which requires proper operations for preventing from agglomeration.
The monitor adopts the joint time-frequency analysis technique to the acoustic signals as well as considers non-Gaussian properties, on decision making procedure, including skewness and excess of parameter distributions which are the resulting characteristics through the analyses on the time-frequency plain.
The monitor has been applied to a 350MWe FBC for testing, and validated through two year operation.

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Recently, because aging is progressing in our country, cerebral disease is becoming a serious problem. Therefore, viewing this problem objectively, we can say support of aging and dementia patients is a very useful research theme. In this time, we examine the drinking condition as one noticing point in a case of carrying out the rank evaluation of dementia. Because it is generally known the condition like dementia by alcohol, dementia is deeply involved with alcohol.
In this time's experiment, we examined the condition like dementia by alcohol. We carried out the experiment to observe an internal condition (cognitive ability) and an external condition (expression control ability) for the first stage and second stage in drinking level. First, by assessment of cognitive ability, though decline of cognitive ability by drinking occurs whole brain, it is shown to influence to left-brain in first step. Next, by assessment of expression control ability, we showed AU influenced by drinking in expression's output level. By these 2 experiments, we found out the concrete symptom of the condition like dementia by alcohol. In future, we examine the relationship between the condition like dementia by alcohol and dementia, and then we proceed advancing of rank evaluation of dementia.

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Ground clutter of cultivated land was measured using an L-band long-range air-route surveillance radar (ARSR). The observed area was on the Ohsumi peninsula across the big bay of Kagoshima, a distance from the radar site of 23.3km over the sea. Weather conditions were clear and the wind velocity was 3.7 to 18.5m/s. To determine the ground clutter amplitude statistics, we introduced the Akaike Information Criterion (AIC), which is more rigorous fit of the distribution to the data than the least squares method. It was discovered that ground clutter obeys the Weibull, log-Weibull and K-distributions. To suppress such ground clutter, a CFAR circuit normalized by the standard deviation was proposed. It was analytically shown that this circuit is valid for the Weibull distribution. On the other hand, the simulation was carried out for the log-Weibull and K-distributions, since, it is not possible to show analytically that this circuit validates for these distributions.

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In the digital communication systems, the communication channels are often impaired by channel intersymbol interference (ISI) and additive noise. Furthermore, the nonlinear ISI that often arise at high transmission rate affects the channel performance. At the receiver, the linear and nonlinear ISI must be compensated and the noise must be removed to reconstruct the transmitted data symbols. The purpose of this paper is to design a spatial and temporal RBF equalizer with adaptive array antenna, which presents good characteristic on multipath channel. In this system, the received sequence vector separates into signal sequence vectors through each path. As a result, the number of channel states needed in making decision is reduced and the minimum distance between the two classes of channel states may increase. Simulation results show the remarkable improvement in BER performances, comparing with conventional RBF and viterbi equalizers in multipath and nonlinear intersymbol interference environments.

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Nonlinear oscillators are often used to express the biorhythm. This paper proposes an emotional model with oscillators (EMO) to model mood and emotion. Mood is a steady state of feeling, which is maintained comparatively weakly for a long time, and it is represented by the Van der Pol nonlinear oscillator. Emotion is a transient of feeling, which is quickly caused, and it is represented by an overdamping oscillator. The EMO models such interactions between mood and emotions as attraction, and produces complicate and unpredictable changes of feeling. Applying the EMO to a pet robot, we conducted simulation and experiment, and obtained satisfactory results demonstrating the validity of the proposed model EMO.

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In signal processing applications and image processing applications, some problems are difficult to process based on the linear theory. In these problems, nonlinear processing will be more suitable for obtaining better results. On the other hand, neural networks with a nonlinear input-output relation are applied to various problems such as pattern recognition and the estimation of nonlinear systems. This paper presents a method for noise removal for degraded images using neural networks. Furthermore, in order to effectively apply neural networks to noise removal of the images with different features from the teacher images, a method is proposed for using multiple neural networks to extract the features of the images properly. Finally, the results of computer simulation are presented to illustrate the effectiveness of the proposed method.

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This paper proposes a method to generate an output image with good contrast and smooth gradations from plural gray-scaled input images that have different exposures. The proposed method generates an output image with a wide gray-scaled dynamic range and delicate gradations from an accumulated image of plural input images using the genetic algorithm. The chromosome of an individual is represented by the array of genes that have all gray-scales included in the accumulated image. The fitness of each individual is evaluated by the liner differential value that is obtained in the output image. The experimental results show that the output images with delicate and smooth gradations were generated by the proposed method. The qualities of the output images were also evaluated using the method based on the delta-histograms. The output images by the proposed method recorded the good sharpness factors.

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The input-and-output characteristic of ultrasonic motor (USM) has non-linear elements and change with a temperature rise or fluctuation of load-mass. Therefore, it is difficult to accomplish satisfactory control performance by using the conventional PID controller. In this paper, we proposed PID controller combined with neural network (NN-PID controller). In this design method, NN-PID controller's gains consist of con-stant gains of PID controller and variable gains of NN controller. Weights of NN are adjusted by back propagation method so that control error may be minimized. This method need not long learning-hour of NN. The effectiveness of the proposed design method is confirmed by experiments using the existent USM.

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We describe the detection method of shady objects which are unexpectedly mixed in kneaded food material while various kind of processing are made. Also, we propose automatic measurement of total area of the food material. We focus on the light transmittivity because the material has a tendency to diffuse light and produce shadows depending on the mixtures even when the objects are nonmetallic, i.e. plastic, vinyl, wood, and etc.. We devise a milky white hood for illuminating the object so that the shadow becomes clear not only at material center but also at its tip when the mixture exists. The transmitted light is collected by photodiodes and digitized for logical processing. Also, formulation for estimating the total area by signal processing is derived. Experimental results obtained in real time are shown to prove the validity of the detection method for unexpected mixtures, number of piled objects, and total area.

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Recently, there has been growing interest in utilizing dispersed generation systems, which are grouped into micro turbine systems, co-generation systems, etc., as a substitute for fuel oil energy and a technology to prevent a global warming. Since start-up time of dispersed generation systems is short, it is possible to operate systems to supply load power corresponding to a demand. Moreover, PPS (Power Producer and Supplier) can participate in power retail sales company, since deregulation of electric utilities has been started from 2000. However, PPS have to keep instantaneous generating power commissioning rule, to maintain supply and demand balance between customer and supplier. Therefore, in this paper, we examine instantaneous generating power commissioning for dispersed generators that start-up time is short and is possible to operate systems to supply power load corresponding to a demand. We adopt a PI controller as a controller. The system is composed of double control loop in inner loop and in outer loop. In inner loop electric power are controlled and in outer loop electric energy are controlled. The controller parameters are designed with using the pole-placement technique. The effectiveness of the proposed control system is confirmed by simulations.

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Micromanipulation systems using haptic interface are developed to fabricate a micro robot, or process and inspect micro components. These are scaled bilateral tele-operation systems among different structures. These systems are composed of the original 6DOF parallel link manipulator to carry out micromanipulation and haptic interface with force feedback. It aims to make the micromanipulation more effective by realizing the expantion of scale and force of the micro environment to the operators.
In this paper, we propose new micromanipulation systems and evaluate performances. And we analyze proposed systems by doing fundamental experiments from the viewpoints of preciseness and manipulability.

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A non-intrusive load monitoring system has been developed to ascertain each electrical appliance in a household by disaggregating the total load demand. This system does not need to intrude into a house when metering power consumption of each appliance. Therefore, the system has significant cost advantages and is less troublesome to the customers. This paper describes a non-intrusive load monitoring system which is especially useful when the household has inverter-driven appliances that frequently change their operational state. Conventional non-intrusive load monitoring system cannot treat these inverter-driven appliances easily because of their complicated operation. In the developed system, the load consumption of household appliances is identified by a Neural Network, which perceives the pattern of harmonics flowing out of the house. An air conditioner, a refrigerator, an incandescent lamp, a fluorescent lamp and a television set were used as household appliances for experiments of inference tests. From the experimental result, it was verified that the NN could identify the load consumption of an inverter-driven air conditioner from the pattern of harmonics of the total load. For this reason, the non-intrusive load monitoring system for the household which has several appliances including inverter-driven appliances is viewed as reliable.

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This paper presents a Genetic Algorithm and intelligent Monte carlo approach for thermal unit commitment problem. Unit commitment problem is one of most difficult optimization problem in power system. Recently Genetic Algorithm has been successfully applied to unit commitment problem. However, random-operated genetic operator and initial random-generated populations greatly reduced the searching effort. To overcome these difficulties, we introduced new strategy such as new genetic operator, intelligent Monte carlo method and intelligent method for generating initial populations. Intelligent Monte carlo method is operated in feasible area. Using the proposed method, better solution can be obtained in reasonable computation time.

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Information searching and retrieving are two important aspects that most of the Internet users do when they are using the Internet. Unfortunately, many available tools that are being used to search a particular information from the Internet such as a search engine could not give the satisfying results. This is due to the problem such as broken and duplicated links. Also the ranking algorithms that are applied by the search engines are different from one to another. This paper discusses the limitations of current software tools to search in the Internet and proposes a new approach by employing a mobile agent to retrieve the query results in the local search servers. The Mobile Agent Search System (MaSS) has been developed to reduce the time for searching and retrieving information from the Internet. Furthermore, the ranking of query results are evaluated using the Number of Relevant Ordering Score (NROS) method. The main advantage of the MaSS is to reduce the time for searching and retrieving information as it is done in the off-line case compared to the on-line case.

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It is expected that the odor sensors can be applied to the deodorization or the modulation of odors to make comfortable living space. The analysis of the resident's preferences of the various odors is needed for this application. Because, even if the odor sensors can detect the kinds and the concentrations of the odors, the odor preferences are much different according to the various characteristics of the residents. Firstly, the Analytic Hierarchy Process (AHP) is applied to the preference analysis. The weights calculated by the AHP can be considered as degrees of the resident's preferences or dislikes of the odors. Furthermore, a model by using the dynamic judgments in the AHP is proposed to express the olfactory adaptation of the resident. The adaptation-time until the resident adapts to the odors is estimated by the proposed model. Because the time has also much differences among individuals, it is expected that the proposed model is effective in the field of the system control for the odors, which can deodorize or modulate the odors according to the characteristic of each resident. Lastly, the evaluation experiments are carried out by using T&T olfactometer. The results show the usefulness of the proposed model.

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This paper proposes a fuzzy-based unsupervised segmentation of textured color images. Homogeneity decision makes a fusion of texture features and color features with fuzzy-rule theory for similarity measure. Hierarchical segmentation based on the fuzzy homogeneity decision is performed in four steps to obtain rough segmentation. Segmentation experiments are presented to evaluate the effectiveness of the proposed approach.

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In this letter, a system identification method for nonuniform sampling data is proposed. First, nonuniform sampling data is transformed to uniform sampling data whose sampling period is smaller than the original data. Second, a system identification method with missing data estimation is applied to the transformed data, since the transformed data contains a lot of missing data, Finally, the effectiveness of the proposed method is examined though a numerical example.

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