This paper presents and discusses the first attempts to design a DNA computer, basically from the pionnering work of Len Adleman (Hamiltonian path problem with lab experiments) and then of Richard Lipton (SAT problem, Boolean formulae). Though DNA computers perform individual operations slowly, they use the same massive parallelism that is found in nature, in every living cell. Molecular computers are still in their infancy, they have raised enthusiasm and expectations. But also, active research is now trying to cope with two main types of obstructions: physical (difficulties to deal with large scale systems and coping with errors) and logical (versatility and efficiency to accomodate a wide variety of computational problems).

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In this paper we propose a fuzzy artificial Intelligent system with a learning function, which is called "FAIS" short for. This system has functions which acquire new fuzzy knowledge from experiences under an unknown situation and solve some problems by deducing anew state through fuzzy inference. The purpose of constructing this system "FAIS" is also to make a system that can solve many kinds of problems in various fields. As an example, the FAIS is applied to a pregnant prognosis for some cases of infertility, and then the usefulness of the FAIS is discussed from the simulation results.

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We have devised computer supporting system for diagnosis of surgical site infection using fuzzy logic. Nevertheless, Surgical site infections have various kinds of subjects, the degree of inflammatory reaction, amounts of antibiotic agents post-operatively used, etc. We reconstructed fuzzy logic supplementing several informations of surgical infections.

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To investigate antihypertensive effect of two calcium antagonists : 1) long-acting nifedipine 40mg, and 2) manidipine 20mg, I assessed ambulatory blood pressure monitoring (ABPM) by fuzzy measurements. I selected four measuring items : 1) mean BP, 2) hyperbaric area (HBA), 3) maximum BP, and 4) minimum BP. Each item was graded on a scale of one hundred points by using fuzzy model. Finally, I made comprehensive assessment of ABPM by fuzzy measurement. The score obtained by the system was consistent with subjective clinical assessment of ABPM. Long-acting nifedipine and manidipine had similar antihypertensive scores on both systolic and diastolic BP.

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Diagnosis with medical imaging such as CT scan contains fuzziness because of subjective assessment of the findings by examiner. We have developed a computer diagnostic supporting system using fuzzy inference, which allows objective assessment of cervical lymph nodes metastasis in head and neck cancer. The diagnostic accuracy of this system for 52 cases was above 90%, and there was not a false-negative case. This diagnostic supporting system appears to be beneficial for diagnosis of cervical lymph node metastasis by CT scan. The purpose of this study is to evaluate for the diagnostic accuracy of this diagnostic supporting system for 67 cases in addition to 15 cases, and possibility in this system in clinical medicine.

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In the presurgical work-up of orthognathic surgery, a resultant profile is predicted on a lateral cephalogram. Several hard to soft tissue ratios or linear regression formulas are available to predict a change of soft tissue landmark. But the change in nasolabial region is unpredictable with linear formulas. Because the change is a nonlinear result of the interaction of some factors, including elasticity of the nasal cartilage, tissue thickness and tonicity, and the bony movement. The aim of this paper is to demonstrate a prediction system employing the fuzzy inference.Materials were 40 lateral cephalograms taken before and six months after surgery of twentybimaxillary orthognathic surgery cases. The change of point "Pronasale" was tested for fuzzy prediction system. The system showed high correlation between actual and predicted values and coefficient was 0.94. Errors ranged from -0.6mm to 0.5mm with standard error 0.35. Therefore, the fuzzy prediction system is available for a clinical use.

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The authors have developed the computer assisted system for ultrasonography using fuzzy reasoning. The system was constructed to differentiate the metastatic lymph node from inflammatory ones. To construct the system, we set up three fuzzy production rules according to the diagnostic criteria. Furthermore, in order to simulate the experienced clinician's consideration, we refered the method of analytic hierarchy process (AHP). Consequently, the diagnostic accuracy was improved and usefulness of the AHP was suggested.

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It could be more practical to represent the human relations using a fuzzy graph rather than a crisp form such as a hard cluster. According to the data obtained from several questionnairs, we could measure the connectivity degrees among members and construct its fuzzy graph. Using the fuzzy clusterings and orderings, we have developed its analysis method. Here, we would not only discuss our analysis method of fuzzy sociogram, but also illustrate its practical effectiveness with the case study.

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Nippon Medical School had Special Lectures on Fuzzy Theory for 1st, grade students. The lecture Course was composed of five lectures, titles of which were (1) The Outline of Fuzzy Theory (2) The Fuzzy Logic (3) The Application to Industry (4) The Application to Medicine (5) The Application to Humane Science The main object of this Conres was to make new medical students touch and feel The Fuzzy Thooy, (The New Current of Thought). They were interested in it and many of them attended to the Course, which ended successfully.

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This paper describes a human interface for behavior design of biorobots. This interface is connected to a software architecture which we have developed for generating robot's behaviors. This architecure, which we call Consciousness Architecure, is designed based on a model of the human and animal's develpment of consciousness and behavior. While our human inteface shows the robot's subjetive world including the robot's perceptions on the computer screen, a user can input virtual obejcts through the screen to the robot by a mouse to help to design robot's behaviors. This interface tool will enhance users' design capbilities and save time to make real objects because the interface enables users to treat the robot's subjectivity as an objetivity to the users.

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Understanding complex many-body systems such as living lives is a very difficult, and therefore chalengable problem. Here we overlook various approaches from microscopic or from macroscopic point of views. We focus our attention to the recent idea, so-called living machine. The idea is first devide the lives to parts, and consider them as molecular machines, then understand them from physical rules. We show this view point is actual and fruitfull.

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This paper proposes a new type of neuron model considering the background on chemical particles transmission in synoptic region, and on the recent scientific knowledge that the several kinds of transmission particles (about 25 kinds) have been discovered, (really, more than 100 kinds of particles are estimated to exist). The model has the following three major functions as an simplified atialogy of real neuron activity in the synoptic region : 1) symbolized particles, each of which has identical mass as an analogy of chemical particle are defined, and also generation mechanism of the particles are defined related with the output spike sequence from the simulated axon. 2) Reaction for those of the simulated symbolized particles is defined by the analogic mechanism of deposition toward basement and accumulation on the basement in the defined vessel. 3) The accumulated symbolized particles cause strong effect on the generation of simulated post synaptic potential 4) The statistical information included in the accumulated particles is introduced besides the neurons output spikes. The information will be used for something like state information of certain systems.

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This study is proposal of a model, comprising of fuzzy processing units in a general purpose computer. The fundamental ideas of constuction are imitative of the structues of the central nervous system of animal somata. Parts of the input processing are correspondent to the sensoy segments of the spinal cords or to the pimay nucleus of the sensoy organs, parts of the output processing to the functional unit columns of the forebrain cortices, and the associating parts to the intercalating nuclei as the fuzzy sets respectively. The proposed method consists of the multidimensional processing associatited with the emotinal center. This system may open a way to the word computer processing.

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This paper presents a emotion model that generate artificial emotion based on experiences. The experience database included in this model enable to ganerate more human emotion than conventional models.

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In the feild of information science, studies on feeling generation processes have made little progress. We initiate the idea of a "mental attitude" to simulate one's feeling generation with computers naturally. In addition, we introduce an "event", which indicates to what degree an external incident affects his feeling, to represent the changes of his feelings.

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Psychosocial information from the first visit to the outpatients clinicand the relation to the doctor shopping were considered. Severe somatic symptom and the patient's character deviation are significantly high in the doctor shoppers. These psychosocial information included in the first visit to the outpatients clinic is very important for understanding the patient's consulting behavior and for constructing the good doctor patient relationship.

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How to express KANSEI words ? We propose a methodology for constructing image-code which can express KANSEI words using vector data. An object is described by the image-codes defined on the several attributes, such as emotional attributes, (introduced from R. Plutchik Theory). We introduce the emotional image-code at first, and explain how to make image-code from a defined relationship between each objects in a category. Lastly, we briefly explain a mapping function of each spaces.

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This paper gives an overview to Human Media Technology as a trend of Kansei information processing. This study takes a human-centered approach to the next generation information technologies for the national and global information infrastructure in the twenty first century.

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This study aims to clarify the applicability of neural network to represent hypertension model. From medical database, 599 cases were randomly chosen to the learning group. Input variables used in this study were sex, age, smoking and drinking habits, body mass index, systolic and diastolic blood pressure, total cholesterol, triglyceride, fasten plasma glucose and uric acid. These input variables were used directly and also used after transforming to the fuzzy memberships. For quantitative evaluation of risk factors, the output ratio (risk/standard) derived from neural network, odds ratio based on logistic regression, coefficient based on the covariance structure analysis are compared. The neural network was also able to represent the risk factors associated to the occurrences of hypertension.

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We try to make the line drawing system, which consists of the feature detection part and the drawing part. In the feature detection part, the edge features are detected by using neural network. In the drawing part, the primitive patterns are displayed by the information of the detected features. We analyze the detected features so as to develop the mechanism of the drawing part.

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Fractal dimension images were generated by a pixel-by-pixel method. The fractal dimension at the target pixel was estimated as Hausdorff dimension (D) which is defined as n (r)=D (1/r) using the surrounding NxN unit cell, where r varies 1 to N-1 and n (r) is the number of unit voxel r covering the three dimensional surface of the unit cell N.We apply this method for the glucose metabolic rate and the oxygen metabolic images of the brain in 5 patients with Alzheimer disease and in 2 normal cases. Mean fractal dimension of the cerebral functional images increased and the fitting error decreased as N increased. In a patient with typical Alzheimer disease, low glucose metabolic rate regions with higher or lower fractal dimension were observed.

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A fuzzy regression model illustrates the possibility of a considered system so that all given data are included in fuzzy intervals obtained by the model. So the fuzzy regression model is easily warped and bended by data with large error, when the error data are mixed in the possibilistic data. Especially the marginal data have the influence on configurating the shape of the model. Hyperelliptic function is employed to select marginal data by means of recognizing data positions by adjusting its parameters. The fuzzy robust regression model is proposed in this paper so that the data with large error can be removed out of the marginal data using distance. As an application of the fuzzy robust regression model, the relation between economy in Asian region and environmental problem is analyzed. This application shows the meaning and effectiveness of the fuzzy robust regression model.

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This paper proposes a device that translates handicapped person's movements into direct movements of the computer's cursor. It replaces the desktop mouse or even the keyboard for people who can't use them. In order that the camera can be settled freely, the automatic coordinate transformation by the neurofuzzy adaptive modeling using Gram-Schmidt Orthogonalization Process is employed. A color trucker system for the measurement of the positions of hand or head is used. The neurofuzzy modeling improves the difficulty of tuning of mouse cursor sensitivity.

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Diagnostic methods in Oriental Medicine consist of inspection, ausculation and olfaction, interrogation, palation. In this study, we had attempted to investigate the diagnosic standard of the tongue inspection using a fuzzy theory. It suggested that a fuzzy theory was useful for setting up a diagnotstic weight on the diagnotstic standard of the tongue inspection.

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Recently, fuzzy theory is applied to many fields such as an engineering, a medical, and an agriculture and so on. We apply the fuzzy theory to the needle and moxa cure. The decision rules for these remedies are described by fuzzy liguistic language. In this application, the combinations of assist, no cure, and/or pour are selected by fuzzy rules and patients' information (measurement values by a neurometer).

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The fundamental remedy on Oriental Medicine is generally based on the qualitatively or practically systematized principle constructed by the theory for Yin and Yang, Gogyo (Five Elements)theor}f and Hosha Theory. This paper proposes a mathematical model introducing these qualitative theories into the linear system based on derivative equation.

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A study of panoramic and three-dimensional microstructures using a scanning electron microscope (SEM) and a transmission electron microscope (TEM) is described. SEM studies have revealed aggregative alveoli and dental microwear on the flat, convex and concave surfaces. Using SEM by a freeze-drying method panoramic views of various cells and fibers of cerebellum are observed. Using TEM the transverse sections of human skeletal muscle show two concentric circles of two kinds of filaments, the broad and dark A bands, and the light I bands with the Z lines, are alternatively observed. In the longitudinal sections these two bands are observed in straight lines.

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This paper presents a method of membership function acquisition in consequent clause in fuzzy diagnostic systems for two-group differentiation. In fuzzy diagnostic system, the expert knowledge is represented by fuzzy if-then rules. However, the membership function acquisition in the fuzzy if-then rule is time consuming owing to less information about the weight of each clinical diagnostic rule. This method calculates the relative positions and widths of membership functions in consequent clause using the possibility of fuzzy events and the information content of fuzzy sets in antecedent clauses. Furthermore, the membership functions are detected by optimization using learning data. To evaluate the performance of our method, we have applied it on Fisher's iris data. As a result, the accuracy is from 96% to 100%.

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This paper introduces an algorithm of membership function acquisition in consequent clause in fuzzy diagnostic systems for multi-group differentiation. In this algorithm, the relative positions and widths of membership functions in consequent clause are obtained by calculation of the possibility of fuzzy events and the information content of fuzzy sets in antecedent clauses. Moreover, the membership functions are detected by optimization using learning data. To evaluate the performance of this algorithm, we have applied it on Fisher's iris data. As a result, the accuracy is more than 98%.

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Direct responding DATA base to human thinking has not been contrived. Because it is extremely difficult for a computer to guess a thought of a parson. While for a human, the correct spelling is sometime difficult to input to computer, however, if slant fitting theory in imagined matrix was applied, computer became possible to defuzzify a fuzzy word to a correct or a few resembled words. A line or a sentence search in the DATA base using fuzzy search targeting theory made the computer more a like human and increased the quality of computer DATA base. This looked as if computer imaged scientific definite descriptions like a human by input words.

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This paper discusses the properties of so-called "singleton-type fuzzy reasoning method" whose fuzzy rules have a singleton rather than a fuzzy set in the consequent part. Among the singleton-type fuzzy reasoning methods are "simplified fuzzy reasoning method" whose consequent part consists of a real number, which is the most widely used in fuzzy control and neuro-fuzzy techniques ; "fuzzy singleton-type reasoning method" whose consequent part is a fuzzy singleton (that is, a real number with a weight) ; and "fuzzy reasoning method with compatibility functions" in which compatibility functions are attached to the consequent part.

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