Abstract: The purpose of this paper was to investigate the system thinking paradigm and current science education in a theoretical view and to discuss its implications with information technology. This is theoretical and philosophical research, and is divided into three parts: firstly, significant trends in science education during the late 20th Century are examined; secondly, the nature of the thinking paradigm are discussed, with a specific focus on system thinking; thirdly, the implications of the system thinking paradigm are discussed in relation to science education. The following results are then presented: 1) scientific literacy has emerged as the major goal of science education in the age of information; 2) the current thinking paradigm is changing from analytics to systemics in that it is concerned with interrelated components and systems as the property of the whole; and 3) in terms of its implications in science education, system thinking can be interpreted as the essential form of scientific literacy.
Abstract: This paper introduces an easy way of authoring and presenting a user’s own story in the form of animation on the World Wide Web. Since visual authoring is difficult and time-consuming, most of the existing online story-making tools support text-based authoring, and a few others allow users the freedom of choosing characters from a given database. Comparatively, we suggest a way of incorporating a user’s own sketches of characters and scenes to build a story without demanding much intervention from the user. We also present an automatic view control method to transform simple sketches into animation on the web.
Abstract: Region-oriented segmentation is a simple relatively robust method for coin recognition. In this paper we present the use of Region-oriented segmentation for Coin Recognition. We use an improved K-Means Clustering Algorithm, which has the advantage to speed up the automatic determining of the optimal number of classes, to group all the gray-levels into several clusters. With the help of this cluster algorithm a label image of original coin image is obtained. In turn, the features such as area, perimeter, compactness and polar distance are extracted from the label image. The coins presented in the image could be recognized by matching the classifiers stored in the database. Several common segmentation approaches are also presented here in comparing to the region-oriented segmentation.
Abstract: Architectural design is one of those areas that have actively employed interactive design tools such as CAD/CAM software. In order to add a realistic view of the design results in the 3D work process, there have been several recent attempts to employ a virtual reality technology that allows architects to explore design in 3D space. However, VR’s weakness is that common interaction tasks, such as navigation and selection, are still not supported conveniently in 3D space. In addition, VR devices are generally unfamiliar to the average person and are too expensive to use. This paper presents a VR framework that makes the design task easily achieved by employing a PDA interface for a VR interaction applied to street-view emotional color design problems.
Abstract: This paper proposes a novel protein structure descriptor (or representation) and its application for structure comparison. Since the functions of protein may come from its structure, the method of measuring structural similarities between two proteins can infer their functional closeness. In this paper, we have developed a novel descriptor (3D edge histogram) to compare the structures of proteins. The 3D edge histogram is a local distribution of bonds between the atoms in a protein. We have designed and implemented a protein structure retrieval system based on the 3D edge histogram to demonstrate that it could be effective in protein structure comparison. In this system, principal component analysis for aligning, voxelization for volume generation, quantization, 3D edge extraction, and comparison of 3D edge histogram are performed. The protein structure retrieval system using the 3D edge histogram shows fast retrieval with relatively precise results. It can be used for pre-screening purposes with a huge database.
Abstract: The ultimate goal of a knowledge-based society is to encourage the individuals to share and disseminate their knowledge spontaneously, so that the circulation of knowledge is accomplished. The structure of knowledge circulation consists of the following loop: preparation of explicit knowledge from implicit knowledge (externalization), sharing of the explicit knowledge, reproduction of implicit knowledge from shared explicit knowledge (internalization) and externalization of reproduced implicit knowledge. In addition, for the purpose of sharing knowledge,
the market place should be established and offer a variety of incentives that induce people to willingly participate in the creation of knowledge. In this paper, we show a successful example of a knowledge community, the Global Network of Korean Scientists and Engineers (KOSEN, www.kosen21.org), focusing on its organization and operation. KOSEN was established in 1999 in order to share
knowledge and information resources of Korean scientists and engineers all over the world. Among 4 knowledge management processes--knowledge creation and acquisition, knowledge organization and storage, knowledge distribution and knowledge utilization--KOSEN supports 3 processes (aside from the utilization of knowledge). Moreover, KOSEN seeks knowledge utilization by encouraging the
formation of small groups within the community.
Abstract: SRT division schemes are presented based on a redundant number operand format aiming high speed operation. The proposed SRT division method based on a redundant binary adder (RBA) and one based on a recoded binary signed digit adder (RBSDA) show a 33% and 50% speed improvement, respectively. The time complexity of the proposed division based on redundant number is O(n); importantly, the redundant number based design is easy to implement due to its structural regularity.
Abstract: Clustering methods have been often used to find biologically relevant groups of genes or conditions based on their expression levels. Since many functionally related genes tend to be coexpressed, by identifying groups of genes with similar expression profiles, the functionalities of unknown genes can be inferred from those of known genes in the same group. In this paper we address a novel clustering approach, called seed-based clustering, where seed genes are first systematically chosen by computational analysis of their expression profiles, and then the clusters
are generated by using the seed genes as initial values for k-means clustering. The seed-based clustering method has strong mathematical foundations and requires only a few matrix computations for seed extraction. As a result, it provides stability of clustering results by eliminating randomness in the selection of initial values for cluster generation. Our empirical results reported here indicate that the entire clustering process can be systematically pursued using seedbased clustering, and that its performance is favorable compared to current approaches.
Abstract: Natural land cover patterns continuously undergo changes, impacted by various natural as well as human-managed factors. The remotely sensed data are commonly utilized to detect land cover change, which is important to understanding long-term landscape dynamics. Generally, a methodology for global change is composed of mapping, quantifying, and monitoring changes in the physical characteristics of land cover. The selected processing and analysis techniques affect the quality of the obtained information. In this research, a change detection/feature extraction system is proposed based on remotely sensed data: preprocessing, change detection and segmentation, resulting in the mapping of the change-detected areas. Here, appropriate methods are studied for each step and in particular, in the segmentation process, a multiresolution framework to reduce computational complexity is investigated for multitemporal images of large size.
Abstract: This paper presents an effective method for segmenting and recognizing license plate characters on a moving vehicle in actual outdoor environment. It is applicable to various camera conditions and installation environment and provides some effective methods to improve the rate of recognition and procedure speed. This paper is concerned not only implementations in laboratory environment but also in outdoor environment like roads, entrances of parking areas and other similar places where license recognition is needed. The digital images used can be obtained from any digital camera. The proposed vehicle license plate character recognition methods are constructed from a feature-based approach. By regulating a character, a unique structural feature for each character can be extracted. The extracted feature is insensible to changes in the outdoor environments. The proposed recognition system has two main processes: 1) to construct the feature information and 2) to segment a character image from any object image of a license plate and identify it. The relative regulations, the similarity and dissimilarity between each character, are used as recognition features.