• Journal of the Korea Society for Simulation
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• v.8 no.2
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• pp.13-28
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• 1999

The main purpose of this paper is to design and implement forest fire information system (FOFIS) for effective prevention of forest fire using GIS, database, 3-D graphics, and simulation techniques. In contrast to conventional fire information systems that are mostly based on the 2-D graphics and analytic modeling approaches, we have proposed the cell-based modeling approaches, i.e., spatial, data, and simulation modeling approaches. The cell-based spatial modeling is proposed by eliminating the cliff effect of the typical elevation model so that it can provide realistic 3-D graphics of the forest fire. The cell-based data modeling of geography, meteorology, and forestry information is also proposed. The cell-based dynamic modeling for forecasting of the fire diffusion is developed using the variable structure modeling techniques. Several simulation tests of FOFIS performed on a sample forest area of Chungdo, Kyungsangbukdo will demonstrate our approaches.

• International Journal of Computer Science & Network Security
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• v.23 no.6
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• pp.1-12
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• 2023

With the rapid increase of user generated data on digital platforms, the task of categorizing and classifying theses huge data has become difficult. Topic modeling is an unsupervised machine learning technique that can be used to get a summary from a large collection of documents. Topic modeling has been widely used in English content, yet the application of topic modeling in Arabic language is limited. Therefore, the aim of this paper is to provide a systematic review of the application of topic modeling algorithms in Arabic content. Using a well-known and trusted databases including ScienceDirect, IEEE Xplore, Springer Link, and Google Scholar. Considering the publication date from 2012 to 2022, we got 60 papers. After refining the papers based on predefined criteria, we resulted in 32 papers. Our result show that unfortunately the application of topic modeling techniques in Arabic content is limited.

• Korean Journal of Computational Design and Engineering
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• v.2 no.4
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• pp.222-236
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• 1997

Conventional solid or surface modeling systems cannot represent both the complete solid model and the abstract model in a unified framework. Recently, non-manifold modeling systems are proposed to solve this problem. This paper describes FlexDesigner, an open kernel system for modeling non-manifold models. It summarizes the data structure for non-manifold models, system design methodology, system modularization, and the typical characteristics of each module in the system. A data structure based on partial-topological elements is adopted to represent the relationship among topological elements. It is efficient in the usage of memory and has topological completeness compared with other published data structures. It can handle many non-manifold situations such as isolate vertices, dangling edges, dangling faces, a mixed dimensional model, and a cellular model. FlexDesigner is modularized hierarchically and designed by the object-oriented methodology for reusability. FlexDesigner is developed using the C++ and OpenGL on both SGI workstation and IBM PC.

• The Journal of Society for e-Business Studies
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• v.1 no.1
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• pp.141-157
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• 1996

Data sharing is a major challenge to implement CALS. STEP is the international standard for the product model data exchange among heterogeneous systems and plays a key role in CALS. Advances in computer networks are rapidly changing the product development processes. The network oriented modeling system premises to integrate design activities across the enterprise. To achieve goals of CALS 3-dimensional concurrent modeling that complies international standard is required since integrity and common perception of product data can be assured. This paper presents 3-dimensional concurrent geometric modeling on high speed network using STEP and methodologies.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.23 no.9
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• pp.1129-1138
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• 1999

This paper presents a systematic two-zone modeling for reliable performance prediction of centrifugal compressors. In order to improve the predictive capability, a modified jet slip factor is developed and new corrections for the wake flow deviation and mass fraction are suggested based on the comprehensive experimental data of the three Eckardt impellers. The proposed two-zone modeling is tested against nine sets of measured data of centrifugal compressors. The results are also compared with those obtained by the mean streamline analysis. It was found that the predictions by the present two-zone modeling agree fairly well with experimental data for a variety of centrifugal compressors over the wide operating conditions.

• Transactions of the Korean Society of Automotive Engineers
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• v.8 no.3
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• pp.190-197
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• 2000

A graphic vehicle modeling pre-processing program and a visualization post-processing program have been developed for AutoDyn7, which is a special program for vehicle dynamics. The Rapid-App for GUI(Graphic User Interface) builder and the Open Inventor for 3D graphic library have been employed to develop these programs in Silicon Graphics workstation. A Graphic User Interface program integrates vehicle modeling pre-processor, AutoDyn7 analysis processor, and visualization post-processor. In vehicle modeling pre-processor, vehicle hard point data for a suspension model are automatically converted into multibody vehicle system data. An interactive graphics capabilities provides suspension modeling aides to verify user input data interactively. In visualization post-processor, vehicle virtual test simulation results are animated with virtual testing environments.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.6
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• pp.616-628
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• 2000

In this paper, we present the modeling of the ozone prediction system using Neuro-Fuzzy approaches. The mechanism of ozone concentration is highly complex, nonlinear, and nonstationary, the modeling of ozone prediction system has many problems and the results of prediction is not a good performance so far. The Dynamic Polynomial Neural Network(DPNN) which employs a typical algorithm of GMDH(Group Method of Data Handling) is a useful method for data analysis, identification of nonlinear complex system, and prediction of a dynamical system. The structure of the final model is compact and the computation speed to produce an output is faster than other modeling methods. In addition to DPNN, this paper also includes a Fuzzy Logic Method for modeling of ozone prediction system. The results of each modeling method and the performance of ozone prediction are presented. The proposed method shows that the prediction to the ozone concentration based upon Neuro-Fuzzy approaches gives us a good performance for ozone prediction in high and low ozone concentration with the ability of superior data approximation and self organization.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.4
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• pp.58-66
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• 1998

In many situations, it is very important to identify a certain unkown system, it from its input-output data. For this purpose, several system modeling algorithms have been suggested heretofore, and studies regarding the fuzzy modeling based on its nonlinearity get underway as well. Generatlly, fuzzy models have the capability of dividing input space into several subspaces, compared to linear ones. But hitherto subggested fuzzy modeling algorithms do not take into consideration the correlations between components of sample input data and address them independently of each other, which results in ineffective partition of input space. Therefore, to solve this problem, this letter proposes a new fuzzy modeling algorithm which partitions the input space more efficiently that conventional methods by taking into consideration correlations between components of sample data. As a way to use correlation and divide the input space, the method of principal component is ued. Finally, the results of computer simulation are given to demonstrate the validity of this algorithm.

• The KIPS Transactions:PartD
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• v.10D no.7
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• pp.1115-1126
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• 2003

In this paper, we propose modeling method for video data that represents structural and semantic contents of video data efficiently. Also, a browsing method that helps users easily understand and play the contents of video data is presented. The proposed modeling scheme consists of three layers such as raw data layer, content layer and key frame layer The content layer represents logical hierarchy and semantic contents of video data. We implement two kinds of browsers for playing video data and providing video contents. The playing browser plays video data and Presents the information of currently playing shot. The content browser allows users to browse raw data, structural information and semantic contents of video data.

• Journal of Information Technology Services
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• v.15 no.3
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• pp.71-95
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• 2016

In recent years, text mining has been used to extract meaningful insights from the large volume of unstructured text data sets of various domains. As one of the most representative text mining applications, topic modeling has been widely used to extract main topics in the form of a set of keywords extracted from a large collection of documents. In general, topic modeling is performed according to the weighted frequency of words in a document corpus. However, general topic modeling cannot discover the relation between documents if the documents share only a few terms, although the documents are in fact strongly related from a particular perspective. For instance, a document about "sexual offense" and another document about "silver industry for aged persons" might not be classified into the same topic because they may not share many key terms. However, these two documents can be strongly related from the R&D perspective because some technologies, such as "RF Tag," "CCTV," and "Heart Rate Sensor," are core components of both "sexual offense" and "silver industry." Thus, in this study, we attempted to discover the differences between the results of general topic modeling and R&D perspective topic modeling. Furthermore, we package social issues from the R&D perspective and present a prototype system, which provides a package of news articles for each R&D issue. Finally, we analyze the quality of R&D perspective topic modeling and provide the results of inter- and intra-topic analysis.