The University Consortium for e-Learning, Shikoku Center” is a parent organization of Cooperative University e-Learning Project for the Shikoku Area. The organization consists of five national universities in Shikoku area of Japan. Kagawa University takes the initiative of this project. The aim of this organization is to improve the educational quality in the five universities using e-Learning technology. To achieve the aim, in this project, we create the unique educational system that can provide courses with distinguished features opened in the respective universities to students. That is why it is anticipated that many students of the aforementioned five universities will take a lot of courses. It might cause heavy access to e-Learning servers. Therefore, the balancing of their loads is needed because e-Learning service must be suitable and available even in tough condition such as heavy and burst access. In this paper, we propose load-balancing strategy for our e-Learning management system. We have monitored and analyzed network environment of our university to design strategy of load balancing for future demand of e-Learning services.

This paper presents development of a Web-based visual simulator with communication support and its application to computer architecture education. The simulator written in Java has equipped visualization and communication support for real education. The former is designed to show how a computer works graphically and helps learners to understand basic computer architecture visually. The latter is realized with a built-in e-mail function. It allows learners to send question e-mails with a snapshot of simulator's execution to instructors. They receive such question e-mails and then redo to verify the execution of learners' simulators. With these supporting equipments, learners and their instructors can share suitable information between their simulators.

A new robotic hand system with high-speed finger motion of 180 [deg] per 0.1 [s] has been developed. With high-speed visual feedback at a rate of 1 [kHz], various dynamic manipulations are achieved. As examples of dynamic manipulation we describe the dynamic active catching tasks for a falling ball and a falling cylinder using a high-speed multifingered hand. We achieved these difficult tasks by utilizing high-speed motion and impact forces actively. Experimental results using active catching strategy based on visual feedback are shown.

In this paper we introduce a newly developed high-speed multi-fingered robotic hand. The hand has 8-joints and 3-fingers. A newly developed small harmonic drive gear and a high-power mini actuator are fitted in each finger link, and a strain gauge sensor is in each joint. The weight of the hand module is only 0.8 kg, but high-speed motion and high-power grasping are possible. The hand can close its joints at 180 deg per 0.1 s, and the fingertips have an output force of about 28 N. The hand system is controlled by a massively parallel vision system. Experimental results are shown in which a falling object was caught by the high-speed hand.

An education tool has been developed to explain internal behavior and structure of computer graphically. It is written in Java Language and designed for students to understand how computer works in the classroom lecture of information science. This paper describes some characteristics of our education tool and improvement of its facilities, especially embedded mail handling module for information exchange between teacher and students.

This paper describes the hardware architecture and the employed algorithm of a parallel processor system for three-dimensional color graphics. The design goal of the system is to generate realistic images of three-dimensional environments on a raster-scan video display in real-time. In order to achieve this goal, the system is constructed as a two-level hierarchical multi-processor system which is particularly suited to incorporate scan-line algorithm for hidden surface elimination. The system consists of several Scan-Line Processors (SLPs), each of which controls several slave PiXel Processors (PXPs). The SLP prepares the specific data structure relevant to each scan line, while the PXP manipulates every pixel data in its own territory. Internal hardware structures of the SLP and the PXP are quite different, being designed for their dedicated tasks.