The purpose of this study is to research the thoughts transmitted from five senses experience and to communicate from this computer supported collaborative work. The research structure is based on a virtual production as the research subject. We will analyze the visual production examples that are able to provide new thinking for designers who engage in material related industries - which comes in the form of “the visual telling of stories” and focus on “user-centered design” forms. Virtual product designs are not just to show the material of production, but to draw closer to people's demands physiologically and psychologically through interactive designs so as to achieve cognition between people and their environment of the computer supported collaborative work. We are also able to regard it as a kind of material, and an activity of story expression, allowing the interactive design's spirit, product material, and experience ideas to be transmitted to the target tribal group in a design communication and image performance method. It is a far more confident and innovative attempt, and meanwhile, able to achieve entertainment, joy, and other such fundamental interactive transmissions. Therefore, this study takes “user-centered design” thinking as a basis to establish a set of virtual designs with interactive experience material and to assist designers to examine the five sensual feelings of interactive demands in order to initiate a new value in the design industry.

Struck-string instruments such as pianos usually have groups of strings that terminate at some common bridges. Because of the strong coupling phenomenon, the produced tones can exhibit highly complex modulation patterns, and synthesizing such complex tones turns out to be quite complicated. It is also difficult to determine the synthesis model parameters such that the synthesized tones can match the recorded tones. This paper proposes a multichannel recurrent network based on three previous works: the coupled-string model, the commuted piano synthesis method, and the infinite impulse response (IIR) synthesis method. This work attempts to automatically extract the synthesis parameters by using a neural-network training algorithm without the knowledge of the instruments' physical properties. Encouraging results are shown in the computer simulations

A novel neural network based method for halftoning and inverse halftoning of digital images is presented. We first start from inverse half-toning of images produced from error diffusion methods using an RBF network plus an MLP network. The restored contone images have had good quality already. Then, an SLP neural network is used to refine the halftoning processing and the training process of the inverse half-toning network is also involved. The combined training procedure produces half-tone images and the corresponding continuous tone images at the same time. It is found that these contone images have even better PSNR performance. Furthermore, the resulted half-tone images are visually sharper and clearer, too. The proposed inverse half-toning method is also compared to the well-known LUT method.