This paper explores the optimum apportionment of letter presentation time in a visual-audio display from the viewpoint of multimodal interface and carries out a comparison with that in a visual or an audio display. The optimum apportionment of the presentation time of eight randomly-selected Roman letters sequentially presented visually in the same position on the screen and through a headset acoustically was determined for four young males by using the time-continuous model of short-term memory. These apportionments are thought to allow for the easiest retention in short-term memory. The average optimum apportionment, was also obtained. This apportionment has shown the same tendency as that in a visual or an audio display. but minimum presentation time has been slightly shorter than in the audio display. The number of recalled letters in the case of presentation under the optimum apportionment is greater for all subjects than the maximum value of the number of recalled letters, on condition that the presentation time of each letter is made equal. Moreover, there is a significant difference between the former and the letter. Accordingly, the effectiveness of the method employed here has been confirmed in the visual-audio display as well. Furthermore, in the visual-audio display, the number of recalled letters under the optimum apportionment was greater than that in the visual or the audio display for all subjects.

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Fuzzy set cloning (FSC) was performed to detect cDNAs that react to gene expression regulator molecules such ascorbic acid (VC) and hydrocortisone. Our target was proteoglycan involved in tissue construction as a component of extracellular matrices. While proteoglycan is not usually produced in hematopoietic cells, MT1 and MT2 cell-derived cell lines of adult T-cell leukemia cells (ATL cells) expressed 100 k dalton (kDa) proteglycan. We performed FSC using a partially purified anti-100 kDa protein antibody as the fuzzy set antibody (FSAb), sequenced the obtained clones, and defuzzified them as new clones using computer queries of the GenBank and EMBL databases. A second defuzzification was performed by analyzing mRNA levels by reverse transcription (RT)-PCR analysis between peripheral lymphocytes and MT1 cells after induction of gene expression by ascorbic acid and hydrocortisone. We were able to obtain functional new cDNAs that exist specifically in ATL cells but not in normal peripheral lymphocytes. Moreover, we were able to define the promoter functions as inducible by VC, hydrocortisone or as none-responsive genes.

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Surgical fluid replacement is a critical issue in medicine as the fluid volume excess or deficit can both complicate the patient's condition. Currently, the administration of fluid volume is carried our primarily based on the experience and expertise of the anaesthetist as there is no analytical method available to estimate the patient's fluid level. The development of an adaptive fuzzy decision support system (DSS) to assist the anaesthetist in estimating the required fluid infusion rate for a particular patient is developed. The DSS employs a multi-rule base (MRB) learning scheme. The design and development of DSS are introduced and its performance is demonstrated. The results obtained so far are encouraging.

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Traditional Chinese medicine has a systematized methodology of medical treatment based on subjective information from the five senses. We proposed here, a diagnostic system of tongue inspection using the fuzzy theory and applied this system to healthy volunteers based on traditional Chinese medicine. Our findings suggested that this diagnostic system is useful for tongue inspection of traditional Chinese medicine.

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Recently the digital dental imaging system (DDIS) has been developed and its use has spread widely. Although it has several advantages, the image quality is not better than that of conventional dental radiographs. Particularly, the density distributions of DDIS images are often insufficient and inadequate. Therefore, the authors considered the density optimization of DDIS images. For this aim, we applied a fuzzy c-means clustering algorithm because the pattern of DDIS images has an extensive variety. Using our method, the denstity distribution of most DDIS images can be improved appropriately. In addition, this method provides a dose reduction for the patients. Consequently, 38.3% of the absorbed dose was decreased.

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This paper introduces basic concept of an emotional dialogue system and shows how to construct the system by simulation. We discuss a dialogue between two simulated persons who know only emotilnal words. At first, we show image code dictionary of mixed emotions which are regarded as emotions in usual life, introduced by R. Plutchik [4]. Secondly, we also show how to design an emotional dialogue system based on the theory for Subjective Observation Model (SOM) [1], which have high applicability to several kinds of fields [2][3]. We explain the outline of the theory. Finally, we show several attractive dialogues by computer simulation.

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We have designed and built a fuzzy logic wheelchair controller which minimizes the effect of Multiple Sclerosis hand tremors. The aim of our project has been to give people with Multiple Sclerosis better control of an electric wheelchair by removing tremors from the joystick signal. The system intercepts the signal from the joystick and then passes it through the fuzzy logic controller. The fuzzy logic rules identify and eliminate erratic or unusual movements, employing a history mechanism to determine what "unusual" is. The fuzzy logic then outputs asignal wihch most closely represents the intent of the user. This paper reports on the experiments conducted with our prototype wheelchair, using test volunteers with MS, as well as on the design of a new fuzzy logic controller. Also, we give a brief overview of the variety of recorded tremors. We show that those who have the most severe MS tremors benefit from the system, and are able to control the wheelchair safely.

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The theoretical foundations of simple genetic algorithm (SGA) are the Schema Theorem and the Building Block Hypothesis. Although SGA does well in many applications as an optimization method, still it does not guarantee the convergence of a global optimum in GA-hard problems and deceptive problems. Therefore as an alternative scheme, there is a growing interest in a co-evolutionary system, where two populations constantly interact and cooperate each other. In this paper we propose a schema co-evolutionary algorithm (SCEA) and show why the SCEA works better than SGA in terms of an extended schema theorem. The experimetnal analyses show the schema co-evolutionary algorithm works well in GA-hard problems such as deceptive functions.

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This article considers modeling and control of a special type of pneumatic actuator, called Artificial Pneumatic Muscle (APM). The APM is able to exhibits many of the properties found in real biological muscles. Contrary to its simple design, the control of APM is very complex due to its nonlinearity, compressibility of air, time varying properties and difficulties in modeling. In order to overcome this problem, adaptive control law based on APM fuzzy dynamic model is proposed here. The optimal architecture of the fuzzy model is determined by using an APM approximate analytical model, whilst the structure and parameters of the low order fuzzy systems are determined through fuzzy clustering of measured deta. The proposed control law is verified by computer simulation.

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We present a new method for modelling ordered datasets using Baldwin's mass assignment. This method generates a simplified memory-based fuzzy belief updating model. The predicted class fuzzy set naturally describes the current state of belief and the previous class fuzzy set defines how previous beliefs colour future beliefs. The model is implementaed using Fril evidential logic rules. Results are given in application to particle classification and facial feature detection. The models generated using this method are concise linguistically clear glass box models.

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Recently, the identification of chaotic phenomenon is required in research of dynamic system such as biological process and human body. By selecting the chaotic pattern that is the most similar to the output pattern, we can identify the dynamic system. The processing of 2-dimensional line figure can be applied to the choatic pattern matching, by dealing with the 2-dimesional projection of choatic attractor. The line figure is analyzed by the cross correlation function of the two complex valued functions which show the each line figure. In this paper, the analysis of 2-dimensional line figure an the method of applying to the analysis of chaotic phenomenon are described.

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