Measurement of quality is an important task in the evaluation of agricultural products. The inspection process is normally pursued on visual inspection basis according to the ripeness standards of the crop, and this grading is subject to expert knowledge and interpretation. Therefore, the quality inspection process of fruits needs to be conducted properly to ensure that good quality fruit bunches is selected for production. Moreover, it needs to be considered during the evaluation that human subjective judgments make the fruit grading inexact. Hence, the objectives of this paper are to build a robust fuzzy hierarchical evaluation model that characterizes criteria of oil palm fruits, and to decide the fuzzy weights of these criteria based on a fuzzy regression model. A numerical example is included to illustrate the computational process of the proposed model.

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The parallelization techniques used in the conventional computer technology need the overhead with respect to the synchronization cost. Moreover it is difficult to achieve a high speed- up ratio in general. On the other hand, turning to our brains, although they achieve high-speed information processing using only low-speed neurons, it is hard to imagine such parallelization takes place in our brains. Are there any simple and efficient parallelization techniques? In this paper we discuss about such parallelization technique for state pace search problem. We also prove a basic theorem about this parallelization, and show a simple guideline of using this technique. Although the neural network is inherently a massively parallel algorithm, we can realize the parallelization of neural networks, namely the parallelization of massively parallel, by using the proposed technique.

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Osteoporosis is one of diseases having a condition that causes thin bone. The osteoporosis appears as a condition in which the bones become fragile and brittle. It causes the bedridden problem by the senior citizen's fracture. The osteoporosis is diagnosed by using the transformation level of the bone density and the bone based on the image which is obtained by CR, CT, MRI, etc. However, there are no methods for automatic detection in the visual screening. In this paper, we propose a new CAD (Computer aided diagnosis) method to analyze the osteoporosis by using image processing technique from the CR image. The technique is to extract the spine by using the idea of peripheral distribution, and to measure the shape. Afterwards, we measure the height of the edge in the back, front, and center of the spine, before evaluation. The proposed method adopted for 36 cases which combined normal and abnormal cases, and satisfactory results are obtained.

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Spinal deformity is one of serious diseases, mainly suffered by teenagers during their growth stage. In order to detect the spinal deformity in early stage, orthopedists have traditionally performed a painless examination called a forward bending test or moire topographic image test in mass screening of school. It is, however, inspection base on the forward bending method takes much time, and the moire images and visual examination also require a large amount of moire images because from elementary as well as junior high schools are collected. This causes exhaustion of doctors and therefore leads to misjudgment. Therefore automated scoliosis inspection based on the moire images has long been desired among orthopedists. In this paper, we propose a method for automatic detection of spinal deformity from moire topographic images by using a new asymmetric feature which is obtained difference of left- and right-hand side density features based on scapula area and shape of moire fringes which is obtained by Fourier descriptor. The proposed technique applied 1200 real moire topographic images and satisfactory performance was achieved. Obtained some experimental results are shown along with the discussions.

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Image registration is one of important problems and a fundamental task in computer vision. In the medical image processing fields, image registration and image warping techniques are introduced in order to register the same or different modalities such as CT and MR imaging. Especially, for diagnosing the legions in the head and to make a surgical planning, physicians gain important information from these modalities. In radiotherapy planning, manual registration techniques are performed on MR and CT images of the brain. In general, physicians segment the volumes of interest (VOIs)from each set of slices on the multi modal images manually. However, manual registration of the object area may require several minutes for analysis based on anatomical knowledge. In this paper, we develop a new method for registration of head images with high speed by using an optimization of volume of interest on the local area. The primary objective of this study is to increase accuracy of the registration and for reducing the computational time for the registration from two images of different modalities.

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In this paper, an orthognathic surgery support system, in which features of patients before and after surgery are represented in 2D map using weighted distance-based self-organizing map, is proposed. The proposed system makes it easy to visually observe a change of a profile pre- and post surgery on 2D map, then it is useful for planning of surgery and informed consent.

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Information science has wide applications, and it provides a useful tool for basic medical researches. This paper shows two examples recently developed by our group. One is to search useful probes to directly idetify the higher ranks of bacterias in taxonomy, and the second is to classify the archaea based on the lipid component parts. These two are done in the same way by a novel method, which introduces two indeces, Coincidence Ratio Inside Group (CRIG), and Coincidence Number Outside Group (CNOG). Using these two indeces, the usufulness of the probes are characterized, many hierachical objects are classified in a systematic way. Its application to the 16S rRNA gene of 2206 bacterial species is shown as the first major result.

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In order to remove a bad smell around bedside, evaluation of the flow of the air around the bedside is done from a theoretical side. Simulated calculations are performed for various conditions. The calculation is based on the Navier-Stokes equation. The flow vectors are drawn for seveval models for the comparison between models. The shapes of the nozzule of the inlet are compared, and it is shown that the wide nozzule shape is more effective than the other shapes. A system is newly evaluated, which has a pair of outlet and inlet in their oposite side. It is concluded that the circulation of the flow is much effective, since the air works in both ends. These findings are a guideline which makes it possible to construct a new machine to remove effectively the odor around bedside.

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We proposed new basic theory and methods for quantum computation and neuro-computer based on functional path integral of quantum theory. And then we concretely calculated probability amplitudes for quantum circuit and slit which have interferences and tunnel effects. We give operator expressions of switches and their circuits, and the diagrams of those systems correspond to potentials of Hamiltonian. Finally, we found that AND-circuit is represented by second order of perturbation, and OR-circuit looks upon as two particles scattering system. We showed it is useful to design and to make tests for new quantum system and computers.

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We could generally analyze the inexact information efficiently and investigate the fuzzy relation by applying the fuzzy graph theory. We would extend the fuzzy graph theory, and propose a fuzzy node fuzzy graph. And we transform it to a fuzzy graph by using T-norm family. In this paper, we would discuss about the decision analysis of the optimal fuzzy graph G_<λ0> in the fuzzy graph sequence {G_λ}. By using the fuzzy node fuzzy graph theory and this new T-norm, we could clarify the relational structure of fuzzy information, and by using the decision of an optimal level on a partition tree, we could analyze the clustering relation among nodes. Moreover, we would illustrate its practical effectiveness with the case study concerning sociometry analysis.

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We often use fuzzy graph to analyze inexact information such as sociogram structure ([1]and[2]). Concerning the hierarchical cluster analysis of a fuzzy graph ([3], [4] ,[5] and [11]), the number of clusters may have to be decided in the actual cluster analysis. In other word, we woud like to decide the optimal level with a partition tree. Concerning this problem, the steepest decent method in the multivariate analysis and the evaluation method based on Fuzzy Decision have been designed by us ([^*]). But, the steepest decent method could produce local limited solution problem. In this paper, we improved our methods by use of AIC to show that the new statistical scheme could find a statistically equilibrium optimal level of fuzzy clustering.

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In 2008, the American Presidential election will be held. We tried to estimate who would be the President in terms of the English literary style of the candidates' speeches. In short, we analyzed various speeches of the two Presidential candidates, Barack Obama and John McCain metrically. Comparing them with special characteristic tendencies of successive Presidents' speeches, we tried an estimation. For this study, each characteristic of character- and word-appearance was approximated by an exponential function to educe some peculiar features of each speech. The estimation values were derived from all past Presidents' inaugural addresses using 6 kinds of approximate equations. Judging from the results, we predicted that Obama would be the 44th President as far as English style is concerned.

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In order to realize intelligent agent such as autonomous mobile robots, Reinforcement Learning is one of necessary techniques in behavior control system. However, applying the reinforcement learning to actual sized problem, the "curse of dimensionality" problem in partition of sensory states should be avoided maintaining computational efficiency. Furthermore the robot task is desired to be decomposed automatically in learning process for good performance. We tackle these two issues by applying modular fuzzy model with gating unit to reinforcement learning. The modular fuzzy model extending SIRMs architecture is formulated to apply Q-Learning reinforcement algorithm. The gating unit that is constructed as a neural network model or simple learning parameters is installed to switch the use of the modular model for task decomposition. Through numerical examples, we found that the proposed method has fair convergence property of learning compared with the conventional algorithms.

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Though various contents are provided through the internet recently, it is not easy to collect favorite contents among huge amounts of contents in terms of user's preference. In this paper, we focus on the collaborative filtering algorithm in the recommender system. We propose a modeling approach based on Modular fuzzy model for preference similarity model in collaborative filtering. In our approach, the model is constructed through optimization of MAE (Mean Absolute Error). The model decides the weights of preference similarity from the value of correlation coefficient, the number of items and variance values of evaluation ratings of each person. Through numerical experiments compared with conventional correlation coefficient based approach using Movie Lens data, we discuss validness of the model for collaborative filtering.

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Characteristic behavior of magnetic fluid was investigated for a key technology study of the magnetic targeting drug delivery system, which is the specific delivery of chemotherapeutic agents to a desired location in the body, such as tumor by the control of an external magne tic field. Densi ty images of the fluid were taken by using a X〜ray CT scanner a t the Na tional Hospital Organization Kyushu Medical Center. We scan magnetic fluid under various conditions. The physical interactions between nanoparticles, one of the essential factors to achieve the drug delivery control, were discussed.

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Several guidance robots that safely guide for senior and handicapped persons at hospitals or welfare facilities have been developed. However, in order to guide a visually handicapped parsons safely, it is noted it that the implementation of the specific mechanism that was made to guide them should be required. In this study, we developed 2 kinds of guidance leads that conduct force information between user and the robot bidirectionally for our guidance robot. The characteristics of each guidance lead about usability and safety were evaluated by psychophysiological experiment.

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Recent advances in robotics have produced several kinds guidance robot at the public places. However, the guidance functions of these robots assigned a focus to guiding a healthy person, and the functions were not effective to guide a visually handicapped person. Our long-term objective is to develop a guidance function for the visually handicapped person using force and auditory information. In the present paper, we proposed a dynamic control system of the guidance lead to feed back a force information effectively.

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Although, walking training instruments are widely utilized to the rehabilitation for walking-disabled patients, the most of those has only simple functions and rehabilitation protocol was limited by restriction of those instruments. To improve the efficiency of walking training, our research group had developed an omni-directional walker, which can make a user exercise omni-directional walking movements. Its availability had been proved by clinical study. But, a movement inaccuracy due to disproportion of the frictional resistance for the wheels has been observed. In this paper, we applied a path tracking control for omni directional walker to reduce the movement inaccuracy. And, the efficacy of the control method has been evaluated by computer simulation.

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We continued fundamental researches that nano magnetic fluid(Fe) is used for the drug delivery system (DDS). We observed rat's kidney into which Ag/Fe nano-particle were injected, using SPring-8 synchrotron radiations.

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In optimization process of genetic algorithm application, early convergence often happens through iterations of the generation alternation. In order to avoid such situation, individuals in GA should be sufficiently varied in whole generations (Diversity maintaining). Distributed genetic algorithm (DGA) is a promising approach for the diversity maintaining as well as acceleration of the calculation. This paper presents a study on topology of each group(island) in construction ofDGA based optimization system. We discuss the performance especially resulting from the difference of topologies such as "small-world networks" in DGA, through numerical experiments of traveling salesman problem, in terms of accuracy and diversity of the solutions.

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Risk management of medical accident is important to attain better "fabric administration", "Accident correspondence", and "field management". We performed an investigation for actual medical accidents cases. We classified the medical accidents into four factors by using cluster analysis and regression analysis. As a result, rates of malpractices caused by "Carelessness group" had about 49%, Which has much influence on maintaining for our quality of medical cares. We used analytic hierarchy process (AHP) and, from this result, determined strategy of prevention for "the accidents with various medical apparatus". As a result, most effective correspondence was "enlightenment education" and the next was "emergency measure", and then the third was "detailed research". At First, we advance a suggestion "Emergency measure" and "Detailed research" on "Carelessness group". In addition, we suggestion "educations on improvements of Working environment" with applying same schedule for Working Environmental group. Secondly, we suggestion about "administration counter measure" and "Inexperience research" or "safety control". We got the result that these plans are the most effective counter measures. The AHP analysis counter measure was thought to be useful tools in all in medical scene.

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For the exclusion of bad smell around a bedside, theoretical and experimental researches have been attempted. A simulated calculation of the air streams is solved based on Navier- Stokes equations. Effects of the shape of the mouth of exhaust pipe are investigated for various cases. For each case, the flows of the air around the bed is visualized by flow vectors, and the change in the flow vectors is investigated. On the other hand, as the experimental study, a test machine is set up to investigate the effect of the filter to absorbe the stink. The odor meter is used to detect the strength of the odor, it is found that there are two components in the contaminated air, one is the fast component, which is easyly absorbed by the filter, on the other hand, the slow compornent can not absorbed by the filter. The air can not be smelled after the filter.

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The Japan population decrease since 2005. In particular, the working population has begun to decrease in 1995. In the meantime, the number of AIDS patients and HIV carriers goes on increasing yet in Japan. But in the other advanced nations, they decreased. An effect of HIV is greater on the working population than senior population. In present Japan, influence from HIV carrier / AIDS to give total population is small. However, the reported number increases every year, and it is considered that the influence will grow in the future. We estimate an effect of HIV on Japanese population. In these calculations of the simulated population, the total fertility rate is used 1.29. As a result, HIV carrier decreased from about 2050.

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Depression is often accompanied with various physical symptoms, especially autonomic nervous system's symptoms such as dizziness when standing, palpitation and stiff shoulders. The object of this study is to estimate physiological state in depression objectively by measurement of motor activity and autonomic nervous system's activity using actigraphy. Seven depressed patients at a psychiatric ward in our university hospital who met the DSM-IV criteria for major depressive disorder, and who had a score of seventeen or higher on the 17-item Hamilton rating scale for Depression (Ham-D) before treatment were enrolled in this study. All patients participated this study voluntarily in agreement with its purport and written informed consent was obtained from them. This study was approved by the ethics committee of the University of Occupational and Environmental Health. All the seven patients were females and the mean age was 67.1±7.7years. The R-R interval and motor activity were measured simultaneously by an actigraphy over three days from the date of admission and recovery of depression. The clinical symptoms on each patient were also evaluated by using the Ham-D at the same time. Motor activity was significantly increased after recovery from depression. The HFnorm, which probably reflects the activity of cardiac vagal nerves, showed a trend of increase. On the other hand, LF/HF, which is the ratio of LF to HF and is thought to be a marker of sympathetic nervous activity decreased significantly after recovery from depression. These findings suggest the possibility that the activity of the sympathetic nerves would be higher and the activity of the vagal nerves system would be lower in depressive states. Furthermore the fractal dimension of the R-R interval power spectrum was decreased significantly lower after recovery from depression. It could be supposed that this fractal dimension has a close relationship to the balance of total autonomic nervous system activity. Therefore further study will be needed to elucidate these arguments.

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Brain potentials to abnormal stimuli in medical care. The eye fixation related brain potentials (EFRP) is a unique event related brain potential that is associated with offset of a saccadic eye movement; i.e. onset of an eye fixation. The potential is measurable at eye moving situations. The potential like ERP changes with attention. 13 subjects were asked to search visual stimuli consisting of pictures of three directional stopcocks in a display. The task was to detect irregular directions of the knob of stopcocks. EFRP was measured in the visual searching task to detect targets as irregular positions of a medical device. EEG (Oz, Pz and Cz) and EOG were measured. EEG epochs associated with offset of saccades were averaged to get EFRP. The positive components of 100 ms appeared predominantly at Oz to all stimuli. When the subject detected targets correctly positive components with latency of about 300 ms appeared at Oz, Pz and Cz.

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