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The purpose of this paper is to develop a new wheel control scheme for wheeled vehicle with passive linkage mechanism which realizes high step‐overcoming performance.

Developing wheeled vehicle realizes omni‐directional motion on flat floor using special wheels and passes over non‐flat ground using the passive suspension mechanism. The vehicle changes its body shape and wheel control references according to ground condition when it runs over the rough terrain.

Utilizing the proposed wheel control scheme, the slip ratio and the disturbance ratio of the wheel reduce when the vehicle passes over the step and its step‐overcoming performance is improved.

The paper's key idea is modification of its kinematic model referring to the body configuration dynamically and using this model for wheel control of the vehicle. The controller adjusts the wheel control references when the vehicle passes over the rough terrain changing the body shape and reduces the slippage and the rotation error of wheels.

The purpose of this paper is to present classification schemes for the crystallization state of proteins utilizing image processing.

Two classification schemes shown here are combined sequentially.

The correct ratio of experimental result using the method presented here is approximately 70 per cent.

The paper is a contribution to automated evaluation crystal growth, combining two classifiers based on specific visual feature, sequentially.

The aim is to develop a force assistance system for standing‐up which prevents the decreasing of physical strength of the patient by using their remaining physical strength.

The system realizes the standing up motion using the support bar with two degrees of freedom and the bed system which can move up and down. For using the remaining physical strength, our system uses the motion pattern which is based on the typical standing up motion by nursing specialist as control reference.

The assistance system realizes the natural standing up motion by nursing specialist and it is effective to assist the aged person to stand up without reducing their muscular strength.

The first idea is distributed system which controls the support bar and the bed system with coordination among them. The second idea is the combination of force and position control.

The purpose of this paper is to propose a state discrimination for crystallization samples (droplets), the purpose of which is to discriminate between diffractable extracts (crystal) and other objects.

The line feature from the image of the protein droplet was extracted and the state discriminated using a classifier based on line features. A support vector machine is used as the classifier.

In order to verify the performance of the proposed method, the growth state was discriminated experimentally using the images taken by TERA, an automated crystallization system. The correction ratio was determined to exceed 80 percent.

Contribution to automated evaluation process of the growth state of protein crystallization samples.

The purpose of this paper is to describe the development of a contactless and batteryless loading sensor system that can measure the internal loading of an object structure through several covering materials for structural health monitoring.

The paper proposed an architecture by which two radio frequency identification (RFID) tags are used in the system. It has been difficult to realize sensing by RFID because of the low power supply. To solve the power supply problem, a method using functional distribution of RFID tags of two kinds of RFID for communication and power supply was proposed. One RFID tag is specialized as a power supply for communication of strain loading information through A/D conversion. Another is specialized to supply power for driving the strain gauges bridge circuit.

By using developed system, the measurement of the structural internal loading with 20.0 mm depth was possible through covering materials such as concrete, but also plaster board, flexible boards, silicate calcium board, blockboard, and polystyrene with a resolution performance from 10 × 10⁻⁶ to 40 × 10⁻⁶.

A sensor system was developed using passive RFID, which enables measurement of load‐deformation information inside a structural object. Moreover, the inexpensive wireless, batteryless devices used in this system require little maintenance, and applications for the user interface are also included in the developed system for uniform management of structural health monitoring. The developed system was evaluated in an actual situation using not only concrete but also other materials as covering materials on a structural object.

The purpose of this paper is to propose an automatic interpolation method for binarized confocal laser scanning microscopy (CLSM) images of a premotor neuron in the silkworm moth.

Partial deficiencies occur in binary images through the form extraction process because of noises in a CLSM image series. The proposed method selects several points from a binarized image series and connects these points with a Bezier curve based on premotor neuron characteristics in order to interpolate partial deficiencies.

To verify the availability of the proposed method, a three‐dimensional form of a premotor neuron of a silkworm moth was extracted. The results of each branch's relation of connection and of the interpolated neuron thickness show that the proposed method realizes to interpolate partial deficiencies and to extract three‐dimensional form of the premotor neuron.

The proposed method contributes to realize efficient premotor extraction process using image‐processing techniques. The extracted result by proposed method can be utilized for the form comparison among many data of the premotor neurons quickly. Moreover, it also contributes to provide the parameters of an accurate neuron model for realizing computer simulation of electrical of the neurons.

The proposed method extracts not only a topological form but also a premotor neuron's thickness by interpolating partial deficiencies based on specific characteristics of the neuron. Thickness values of the neuron are an important factor for a simulating accurate electrical response of the neuronal circuit.