Chung Yuan Christian University

About: Chung Yuan Christian University is a education organization based out in Taoyuan City, Taiwan. It is known for research contribution in the topics: Membrane & Fuzzy logic. The organization has 9819 authors who have published 11623 publications receiving 213139 citations. The organization is also known as: Tiong-gôan-tāi-ha̍k & CYCU.

The new design of an infrared-controlled human-computer interface for the disabled

Abstract: This paper reports on the development of an eyeglass-type infrared (IR)-controlled computer interface for the disabled. This system may serve to assist those who suffer from spinal cord injuries or other handicaps to operate a computer. This system is comprised of three major components: 1) an infrared transmitting module, 2) an infrared receiving/signal-processing module, and 3) a main controller, the Intel-8951 microprocessor. The infrared transmitting module utilizes tongue-touch circuitry which is converted to an infrared beam and a low power laser (<0.1 mW) beam. The infrared receiving/signal-processing module, receives the infrared beam and fine tunes the unstable infrared beam into standard pulses which are used as control signals. The main controller is responsible for detecting the input signals from the infrared receiving/signal-processing module and verifying these signals with the mapping table in its memory. After the signal is verified, it is released to control the keys of the computer keyboard and mouse interface. This design concept was mainly based on the idea that the use of an infrared remote module fastened to the eyeglasses could allow the convenient control of the input motion on the keys of a computer keyboard and mouse which are all modified with infrared receiving/signal-processing modules. The system is designed for individuals with spinal cord injuries and disabled in which the subjects' movement are severely restricted. The infrared transmitting module can be easily mounted on eyeglasses or artificial limbs.

Optimality test for generalized FCM and its application to parameter selection

Abstract: In cluster analysis, the fuzzy c-means (FCM) clustering algorithm is the best known and most widely used method. It was proven to converge to either a local minimum or saddle points by Bezdek et al. Wei and Mendel produced efficient optimality tests for FCM fixed points. Recently, a weighting exponent selection for FCM was proposed by Yu et al. Inspired by these results, we unify several alternative FCM algorithms into one model, called the generalized fuzzy c-means (GFCM). This GFCM model presents a wide variation of FCM algorithms and can easily lead to new and interesting clustering algorithms. Moreover, we construct a general optimality test for GFCM fixed points. This is applied to theoretically choose the parameters in the GFCM model. The experimental results demonstrate the precision of the theoretical analysis.

Particle swarm optimization for bi-level pricing problems in supply chains

Abstract: With rapid technological innovation and strong competition in hi-tech industries such as computer and communication organizations, the upstream component price and the downstream product cost usually decline significantly with time. As a result, an effective pricing supply chain model is very important. This paper first establishes two bi-level pricing models for pricing problems with the buyer and the vendor in a supply chain designated as the leader and the follower, respectively. A particle swarm optimization (PSO) based algorithm is developed to solve problems defined by these bi-level pricing models. Experiments illustrate that this PSO based algorithm can achieve a profit increase for buyers or vendors if they are treated as the leaders under some situations, compared with the existing methods.