Wen-Tsai Sung

Interactive web‐based training tool for CAD in a virtual environment

Innovative products and reduced time‐to‐market are essential for competitiveness in the modern market. Consequently, it is very important for industry to apply new information technologies and training tools to support product development, production planning, and other product processes. Virtual reality is one of these enabling technologies. This investigation proposes a novel approach to enhance CAD training and design in a web‐based environment such as a Web browser or VR browser. Previous investigations successfully developed a CAD curriculum analysis and design, and also proposed the use of virtual reality modeling to improve training techniques. For this reason, this study designs a simple interactive web‐based training tool for CAD in a virtual environment, along with an integrated graphics real‐time system. Using OpenGL, the proposed system can run on different operating systems, such as Windows 2000, Windows 98, Windows 95, Windows NT, Linux and Macintosh. Owing to the increasing need for design and training CAD in network environments, drawing real‐time complex curves and surfaces in a network browser is an emerging technological trend.

Web-based search system of pattern recognition for the pattern of industrial component by an innovative technology

The real-time system uses a recurrent neural network (RNN) with associative memory for training and recognition. This study attempts to use associative memory to apply pattern recognition (PR) technology to the real-time pattern recognition of engineering components in a web-based recognition system with a client-server network structure. Remote engineers can draw the shape of the engineering components using the browser, and the recognition system then searches the component database via the Internet. Component patterns are stored in the database system considered here. Moreover, the data fields of each component pattern contain the properties and specifications of that pattern, except in the case of engineering components. The database system approach significantly improves recognition system capacity. The recognition system examined here employs parallel computing, which increases system recognition rate. The recognition system used in this work is all Internet based client-server network structure. The final phase of the system recognition applies database matching technology to processing recognition, and can solve the problem of spurious states. The system considered here is implemented on the Yang-Fen Automation Electrical Engineering Company as a case study. The experiment is continued for 4 months, and engineers are also used to operating the web-based pattern recognition system. Therefore, the cooperative plan described above is analyzed and discussed here. Finally, these papers propose the tradition methods compare with the innovative methods.

Development of intelligent virtual reality web-based robotics for manufacturing applications

This paper describes several methods for using the Virtual Reality Modeling Language (VRML) as the visualization integration technology for manufacturing simulation systems. One of our goals was to develop an integration methodology based on the Web-Based Manufacturing translators to produce reusable VRML assembly components and Simulation. Virtual Reality (VR) can be handled as improved animation operated by a simulation system. Manufacturing basically comprises some basic classes of engineering tasks, these tasks could benefit from the application of VR through the high-fidelity visualizations, providing model and situation representation in the 3D space, and the power of interactive handling of large data sets in real-time or near real-time. The underlying principles of VR via VRML are described and applications in design and manufacturing tasks are illustrated by assembly planning and intelligent robotic examples. The final, we propose Robotic-Simulator software design and a framework for the Web-Based Manufacturing Simulation.

Web-based search system of pattern recognition for the pattern of industrial components by an innovate technology

This work utilizes the pattern recognition (PR) technologies by Client-Server network structure into a web-based recognizing system. The system uses a recurrent neural network (RNN) with associative memory to perform the action of training and recognition. Client-end engineer is able to draw directly the shape of engineering components by the browser, and the recognition system will proceed with search for the component database of company by the structure of Internet. In this paper, these component patterns are stored in the database system. Their properties and specifications are also attached to the data field of each component pattern except the pattern of engineering component. These Component patterns with the approach of database system will be able to improve the capacity of recognition system effectively. In our approach, the recognition system adopts parallel computing, and it will raise the recognition rate of system. Our recognition system is a client-server network structure by Internet. The last phase joins the technology of database matching in process of the recognition, and it will solve the problem of spurious state. In this paper, our study will be carried out in the Yang-Fen Automation Electrical Engineering Company. Therefore, the cooperative plan of above context will be analyzed and discussed in this paper.

Developing a Web-based pattern recognition system for the pattern search of components database by a parallel computing

The research investigates the use of pattern recognition (PR) technologies with associative memory for real-time pattern recognition of engineering components by a parallel computing system. Component patterns are stored in the database system. Their properties and specifications are also attached to the data field of each component pattern except the pattern of engineering component. A distant engineer is able to draw directly the shape of engineering components via the browser, and the recognition system will search for the component database of the company via the Internet. Component patterns with the matching approach of database system will be able to improve the capacity of the recognition system effectively. The recognition system makes use of parallel computing, and it raises the recognition rate of the system. The recognition system is a client-server network structure using the Internet. The system uses a recurrent neural network (RNN) with associative memory to perform training and recognition. The system is being implemented in the Automation Electrical Engineering Company.

Accelerate the calculation of NURBS curves and surfaces based on parallel architecture

The aim of the paper is to propose a three-dimensional graphics chip with parallel architecture, in accordance with the chip of the NURBS algorithm was structured. This architecture presents a regular and easily scalable structure, suitable for VLSI implementation, which can be efficiently exploited for the computing process. This architecture can apply to a peripheral device of a computer and a user can use it for fitting curves and surfaces, convert NURBS curves to Bezier and so on, which have 16 bit precision. In this paper, we first describe the framework of the whole system. Secondly, we introduce the hardware of FPGA and explain the principle. Next, we will also illustrate NURBS, and test and verify using Visual C++ and OpenGL. The performance of the proposed architecture is improved by the use of carry save arithmetic which permits the reduction of the system time cycle.

Web-based distributed pattern recognition system

This study attempts to apply the principle of neural networks and pattern recognition (PR) technologies to real-time recognition by client-server network structure into a web-based recognizing system. In this paper, we recommend a Web-Based PR technology, which is improved recurrent neural network (RNN) from possessing feedback and non-linear activation function with its input, be taken out threshold. The purpose of this article is. to construct a Client-Server network structure for PR system with associative memory. The Server-end is built a databases management system for storage sample patterns. In proceed with training, the user can real-time assign any pattern, which is a record in the Server-end databases. In deal with retrieve task, we propose a novel PR method via databases matching, it can efficient solve spurious states problem from RNN in the WBPR system. On the other hand, taking advantage of Database Matching is to overcome the capacity restrictions on RNN. In order to clarify and corroborate the above Web-Based PR technology, thus a simulation experiment will be presented and their algorithms are also discussed.

Using the RNN to develop a Web-based pattern recognition system for pattern search of component database

This study attempts to apply pattern recognition (PR) technologies with associative memory to real-time pattern recognition of engineering components using a client-server network structure in a Web-based recognition system. A remote engineer is able to draw directly the shape of engineering components using the browser, and the recognition system will search for the component database of a company using the Internet. Component patterns are stored in the database system. Their properties and specifications are also attached to the data field of each component pattern except that of engineering components. In our approach, the recognition system adopts parallel computing, and will raise the recognition rate. Our recognition system is a client-server network structure using the Internet. The system uses a recurrent neural network (RNN) with associative memory to perform training and recognition. The last phase utilizes the technology of database matching and solves the problem of spurious state. Our system will be used at the Yang-Fen Automation Electrical Engineering Company.

Using a Real-Time Web-Based Pattern Recognition System to Search for Component Patterns Database

Faraway engineers are able to sketch direct the shape of engineering components by the browser, and the recognition system will proceed with search for the component database of company by the Internet. In this paper, component patterns are stored in the database system. Component patterns with the approach of database system will be able to improve the capacity of recognition system effectively. In our approach, the recognition system adopts distributed compute, and it will raise the recognition rate of system. The system uses a recurrent neural network (RNN) with associative memory to perform the action of training and recognition. The final phase joins the technology of database match in process of the recognition except distributed compute, and it will solve the problem of spurious state. In this paper, our system will be carried out in the Yang-Fen Automation Electrical Engineering Company. The plan of experiment has gone through four months, and their engineers are also used to take advantage of the way of Web-Based pattern recognition.

Study on the Computer Network and Virtual Reality Technology for e-Learning ----Baed on WebDeGrator System

The purpose of this research is to apply the network and virtual reality (VR) technologies to computer-aided geometry design (CAGO) curriculum by integrating network, CAD and VR into an e-learning environment. Through wireless technologies, it is expected that the computer graphics (CG) course can be transit to anywhere. VR technologies provide a novel method to enhance user visualization of complex three-dimensional graphics and environments. We have developed an e-learning system to simulate and adjust computer graphics through various complex curves and surfaces algorithms, it be named WebDeGrator, which is an e-learning system for CAD design and application, such as fitting and adapting NURBS curve and surface, fundament mathematics of tools, robot model in VR, visualization for bioinformatics… etc. It’s related to educationa1 and VR technologies will be presented and discussed herein.