This paper addresses the modeling and measurement of a small boat. In some fishing tasks, anchorage is not applicable in order to capture shellfishes or fishes efficiently. Currently, many fishermen are manually stabilizing boats simultaneously with the capturing task. We propose a boat modeling method named FAD learning. In this method, the free dynamics acceleration and actuator acceleration of a boat are learned using the online learning of two dynamics learning trees (DLTs), which are developed by us. In order to measure the position, velocity, and acceleration, we developed an image processing method with an underwater camera. In the experiment, the motor babbling of a boat was performed on a water pool. The dynamical data from the boat was learned by DLTs. The effectiveness of the modeling was confirmed through the validation of the velocity that was predicted by DLTs.

Since the entropic concept was introduced in image segmentation by Pun, many entropic methods have been developed in rapid succession. Consequently, the entropic approach has become a major category of segmentation. Abutaleb et al. firstly introduced the two-dimensional entropies, taking the spatial correlation into account. However, their method takes up too much computational time to give better results. In this paper, a new entropic thresholding method is proposed based on the two-dimensional Shannon entropies by using the orientation histogram. Utilizing several images, the new method is compared with Abutaleb's method and the two-dimensional entropic thresholding method proposed by Xiao et al. The experimental results demonstrate the effectiveness of the proposed method in aspects of two-dimensional entropic thresholding.

Antiphasic electromyographic (EMG) activities between biarticular arm muscles are indispensable for smooth performance. In the case of two-joint arm movement in a planar horizontal plane, elbow and shoulder joint movements were achieved by the biceps brachii (BB) and the triceps brachii muscles (TB). To our knowledge, however, no conclusions have been reached concerning the antiphasic EMG activities between biarticular arm muscles during two-joint arm movements in stroke patients and the effects of training in paretic upper limbs. The objective of this study was to investigate whether or not the antiphasic EMG activities with the BB and the TB muscles were restored in stroke patients by repetitive two-joint arm movements. Three stroke patients performed point-to-point movement (PTP) and circle-drawing (Circle) tasks 20 minutes daily for 10 days. The movement velocity and achievement periods increased after training for the same duration. After the training, antiphasic EMG activities between the BB and the TB appeared. The increased movement velocities played a major contribution in increasing the antiphasic EMG activities and improving positional precision. These results suggested that stroke patients could achieve motor performance to move their wrists fast and precisely by practicing a two-joint arm movement, especially, circle drawing.