Annals of Faculty of Computer and Information Sciences, Hosei University
Department of computer science   Next>>
HOME >> No.8 CONTENTS >> Runhe HUANG
Professor
Runhe HUANG
Refereed Publications
  1. Hiroyuki Morohoshi, Runhe Huang, Jianhua Ma and Ying Huang, “A Bridge Linking Ubiquitous Devices and Grid Services,” in IEEE CS Proceedings of the 21st International Conference on Advanced Information Networking and Applications (AINA2007), Canada, May 2007, pp. 747-753.
    Abstract - Grid computing has made rapid strides from their first serving the scientific computing domain to having great impact on the life science area and their use in the daily activities of users from the resource constrained ubiquitous devices such as PDA and mobile phone. To allow ubiquitous devices to use Grid services, there is a necessity to having a platform or middleware, a bridge linking the devices to Grid services. This paper presents such bridge named BtoG (Bridge to Grid). The design idea and system architecture are described, a sample application of skin checking, accessing to a skin-expert service from a mobile phone via the proposed bridge, is explained, and evaluation and comparisons with other related platforms are given in the paper.
  2. Katsuhiro Takata, Masataka Tanaka, Jianhua Ma, Runhe Huang, Bernady O. Apduhan, and Norio Shiratori, “A Wearable System for Outdoor Running Workout State Recognition and Course Provision,” in the Lecture Note in Computers Science on Autonomic and Trusted Computing (ATC2007), Vol. LNCS 4610, Springer, 2007, pp. 385-394.
    Abstract - The objective of this research is to develop a wearable prototype system to assist people doing outdoor running workout safely and effectively. One essential research issue is to correctly recognize a runner's state during a running workout process by analyzing contextual data obtained from sensors and GPS positioning device carried on by the runner. The running workout process is represented as a state transition diagram using the Space-Oriented Model. The state recognition is based on the state correlations with the runner's heartbeat rate and running speed. Our test results show that by utilizing the runner's state correlation, is more precise to recognize a runner’s state as compared to the state judgment which is only based on detecting whether a sensed value exceeds some medical threshold value.

>PAGE TOP