Based on the newly established taste avoidance conditioning paradigm, Lymnaea can learn the temporal sequence of sucrose application and subsequent applied high voltage with small current resulting in significant suppression of feeding response to sucrose. The most efficient condition to acquire the long-term memory (LTM) is obtained by 15 paired presentations of a conditional stimulus (CS) and an unconditional stimulus (US). This repetition number for LTM acquisition is different among the taste avoidance conditioning employed as US, such as KCl, mechanical tapping and electrical high voltage, however the behavioral modification is thought to activate the same neuronal circuit via RPeD11 which is the inter neuron to control the whole-body withdrawal response. All of these USs are thought to be recognized as a noxious stimulus sensing at RPeD11.

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The magnetic stimulation is the way of stimulating the nervous and muscle tissue with the electric field induced by the stimulation coil and is widely used in the evaluation of the nervous system and the field of the exercise physiology. The focality and the deep stimulation efficiency of the magnetic stimulation are affected by the coil arrangement and shape of the stimulated object since the induced electric field distribution is varied by them. In this study, we used the 5 layers head model and estimated the induced electric field distribution by calculation. As the result, the induced electric field distribution is mostly affected by the boundary between different tissues which have different conductivities.

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Human computer interaction systems via eye blinks have been reported. A purpose of these systems is communication aid for people with severe physical disabilities, such as amyotrophic lateral sclerosis (ALS) patients. Some of these systems classify user's voluntary (conscious) blinks. If the voluntary blinks can be distinguished in automatic, the usability of the input interface is increased. We have proposed an eye blink extraction method that utilizes split interlaced images of the eye. These split images are odd- and even- field images and are generated from interlaced images. The proposed method yields a time resolution that is double that in the 1080i Hi-Vision format. We refer to this approach as a “frame-splitting method”. We realized a method for automatic eye blink extraction using frame-splitting method. Based on this extraction method, we also proposed a classification method of a blink type which set a threshold in the duration of eye blink. Our classification method requires calibration process before measurement. In this paper, we clarify required minimum number of eye blinks for the calibration. Furthermore, we discuss the performance of blink type classification using this calibration.

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Somatic sensations are thought to be represented by the neural activity in the primary somatosensory cortex (S1), which can then be used for higher brain functions, such as decision-making, and memory. However, it is still unclear how neural activity represents these sensations and contributes to those functions. In a previous study, we showed that the intensity of limb stimulation in awake rodents could be coded by dendritic activity of layer 5 pyramidal neurons in S1⁽¹⁾. This implies that somatosensation of tactile stimuli can also be used as a primary mode of input for higher brain areas. To understand causal relationship between S1 activity and higher brain functions, we developed a new experimental system in which mice discriminated texture in a modified Y-maze. With this maze, mice were successfully trained to discriminate a specific tactile stimulus on the floor of the maze at an area just before the branch point. On the basis of these results, we designed a task in virtual world situations. This system also can present tactile stimulation while mice are running within the maze. Now, we are using this system for electrophysiological and optogenetic experiments, and trying to gain new knowledge in the field of neurobehavioral research.

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Drive-train bench is utilized to test power-train components of a vehicle such that transmission, torque-converter, etc. In order to simulate the torque vibration of engine, it is necessary to control the amplitude and the static value of the shaft torque of drive-train bench. In this paper, we propose a shaft torque vibration control method composed of three controllers. In the low frequency band, we propose a static shaft torque controller of I-PD with 1st order low-pass filter which is robustly stable even in the case of stiffness variation of the power-train component. In the high frequency band, we design a resonance suppression controller by mu-synthesis method. Its controller does not change the characteristics of low-frequency. We combine the static shaft torque controller, the resonance suppression controller and an automatic tuner of vibration amplitude reference.

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In this paper, we propose a new method for identification of linear time-invariant systems and estimation of unknown periodic disturbance. We assume that a disturbance to be considered here is unknown except its period. In this method, by stacking not only the unknown coefficients of a mathematical model but also the unknown disturbance as a parameter vector, we modify the equation error method so as to treat the unknown disturbance in the identification scheme. Particularly, we also explain how the periodicity of the disturbance is utilized. In order to show the validity of this method, we give an illustrative numerical example.

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Our previous studies, eye control input interface using an electro-oculograph (EOG) amplified by AC coupling has been developed. We proposed Eye Gesture input interface using combination of several eye movements. It is unnecessary for Eye Gesture input to restrict head movement in comparison with conventional eye gaze input. However, it is necessary to use start operations before Eye Gesture input. Therefore, Eye Glance input has been proposed. Eye Glance input is to use only combination of contrary directional eye movements so that Eye Glance input does not need to use start operations. However, we could not always succeed in Eye Glance input because algorithm for detection of eye movement from EOG signals was not adapted to slight sift of signal base line. In this study, we proposed new determination algorithm for Eye Glance input interface. In experiments using our improved algorithm, we achieved a direction determination success rate of over 80% for 6 subjects.

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The purpose of this paper is to analyze the correlation relationship between the salt satin environment and the actual damage of electric power distribution equipment caused by existing two typhoons including the 2012 typhoon No.4 (T1204) and the 2011 typhoon No.15 (T1115). The T1204 caused salt stain damage to voltage current transformer (VCT) while the T1115 caused no damage to VCT installed in a same target area. In this paper, the salt stain environment during two typhoons, which includes the maximum wind speed, the accumulated rainfall, and Na⁺ flux, is evaluated by a weather reproduction simulation to discuss the causal relationship between the salt stain environment and the VCT damage. As a result, a damage evaluation model is proposed to evaluate the salt-induced damage risk potential of the VCT for the reasonable restoration activity.

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Localization in wireless ad-hoc networks has been attracting much research attention for several years. Existing localization schemes can be categorized into ranging and range-free approaches. This paper proposes a distributed hybrid solution which integrates Received Signal Strength (RSS) based ranging and Self-Organizing Maps (SOM) based range-free approaches for the purpose of achieving high localization accuracy with low cost and power consumption. Distance information between the nodes is estimated using RSS ranging. Then, both RSS-based distance and nodes' connectivity information are applied to the SOM-based location learning steps. The proposed scheme also uses known information of anchors to detect and avoid obstacles or irregular network shapes and to minimize the location estimation error in anisotropic networks. For RSS-based distance estimation, a thorough empirical analysis of the radio propagation model is presented. This paper evaluates the effects of network topology, anchor placement and utilization, node density, radio irregularity and the number of learning steps over the performance of the proposed scheme. Results show that the proposed scheme achieves better localization performances than several existing schemes in most cases while reducing learning steps and anchor utilization.

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Using Internet communication, new home electronics have functions of monitoring and control from remote. However in many case these electronics work as standalone, and old electronics are not followed. Then, we developed the total remote system include not only new electronics but olds. This systems node is an adapter of electrical power plug that embed relay switch and some sensors, and these nodes communicate with each other on mobile ad hoc network. In this paper, we classify many sensor data for monitoring and configuration of energy saving and so on, using principal component analysis and some clustering methods. In experiment results, some part of classified data suggest simple room situation. In few situations, for example absence and sleeping, were mixed but they can classified using infrared and light sensors information.

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Two power consumption smoothing methods for a water transition and distribution system based on water supply management and demand adjustment are proposed and evaluated by simulations. One is the power smoothing method with the achievable power target calculation. The other is the power smoothing method with a demand adjustment that can achieve a flat demand by effectively using the storage capacity of receiving tanks of heavy consumers. Simulation tests showed that the former method is effective to attain flat power consumption during a time zone with a high water demand and the latter method can achieve almost flat power consumption throughout a day.

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An object's optical reflection properties are due to the microscopic structure of the object's surface. Therefore, optical reflection measurement is important to obtain a realistic representation in computer graphics and in the inspection of industrial parts. In this study, we developed a compact reflectance measurement system without a mechanical drive unit. The system has the advantage of being simple and highly portable compared to the conventional measuring device used for this purpose. We constructed a prototype camera system and carried out several experiments to test it. The experimental results showed that the reflection characteristics will vary depending on the surface roughness of objects, and we could recognize the state of the surface reflection visually.

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In this research, combination of haptic display technology and ultrasonic elasticity imaging technology is attempted. The system can provide living body elasticity information in a three-dimensional space as sense of sight information and sense of force information. To realize the system, Haptic rendering method is proposed, which can consider the effect of 3D distribution of elasticity to reproduce reaction force. Reaction force can touch from arbitrary direction. The sight information is displayed quasi-biological body using OpenGL and NURBS surface. Distortion such as a human body is expressed by NURBS. The system can diagnose from arbitrary direction by improving displacement filter. It was verified by experiments on the accuracy of the displacement filter. It was possible to identify even from any direction as a result.

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An industrial product with high quality is made by the skill of a craftsman. The craftsmen are aging year by year, while few young people succeed to them. A problem is how to succeed to the skill of the craftsmen. This paper focuses on handworks for producing a micro-nipper (a kind of cutoff tools) as a skillful work by the craftsman. We develop a motion capture system based on multiple high-speed cameras which measures the movement of the fingers of hands as well as tool and work, and make a 3D animation of the hand work as a teaching material for young successors.

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In this paper, we propose a control system based on auto-fusion cerebellar perceptron improved model using feedback error learning which imitates the human cerebellum, and it is applied to the consensus problem of a multi-agent system (MAS). It is important to control multiple agents because each of them has own scale and complexity. Therefore, the coordinative control of multi-agent system for each autonomous decision making has been focused. To control MAS, we consider use of feedback error learning related to biological movement control, also, propose an auto fusion mechanism for mitigation of neuronal fluctuation. We call the proposed system an “Auto-Fusion Cerebellar Perceptron improved model-based Control System (AFCPCS)” here. Through the computer simulation for a consensus problem of MAS, we show the effectiveness of the proposed method.

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This letter presents a new multi-point combinatorial optimization method. The method construes the solution space as a hierarchical structure, and relates the structure to two strategies: the search of a local area and the movement to unsearched area. The strategies using a proximate optimality principle based interaction provide a move to a promising and unsearched area. The performance of the method is verified through simulations using benchmark problems.

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＊投稿手引の改正に伴い，2013年10月1日以降に新規に投稿され，その後掲載決定となった論文および資料には，Extended Summaryがありません。

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