• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.10a
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• pp.303-311
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• 1999

The amount of financial information in today's sophisticated large data bases is huge and makes comparisons between company performance difficult or at least very time consuming. The purpose of this paper is to investigate whether neural networks in the form of self-organizing maps can be used to manage the complexity in large data bases. This paper structures and analyzes accounting numbers in a large data base over several time periods. By using self-organizing maps, we overcome the problems associated with finding the appropriate underlying distribution and the functional form of the underlying data in the structuring task that is often encountered, for example, when using cluster analysis. The method chosen also offers a way of visualizing the results. The data base in this study consists of annual reports of more than 80 Korean companies with data from the year 1998.

• IE interfaces
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• v.13 no.1
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• pp.60-64
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• 2000

Faced with increasing competitive pressures to reduce time-to-market, many business organizations have recognized that shortening the design cycle by taking full advantage of their intellectual property is inevitable in maintaining their market share. This paper describes a knowledge management system for machine tool design. Product structuring, change management, and complex design knowledge management are possible through the developed system. The system can speed up the design process by making necessary data instantly available as it is needed and keeping track of all the relevant design information and knowledge including individual decisions, design intentions, documents, and drawings.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.7
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• pp.814-820
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• 1999

We propose a target identification algorithm for visual tracking. Target identification is realized by finding out corresponding line segments to the hypothesized model segments of the target. The key idea is the combination of the Mahalanobis distance with the geometrical relationship between model segments and extracted line segments.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.17 no.32
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• pp.81-94
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• 1994

The objective of this case study is to describe ins and outs of a production and information management system developed for footwear industry (based on MRP system). First, basic structure of the total system, configuration of sub-system modules, specification and configuration of software/hardware used in this system are presented. Second, design of the total system flow, configuration of code system, file description used in this system are explained. Third, function of software modules and principal algorithms and basic data structuring technigues are discussed. Finally, inplementation plan and output reports are presented.

• 한국지형공간정보학회:학술대회논문집
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• 2003.09a
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• pp.135-138
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• 2003

최근 국내외에서 3D GIS 및 VideoGIS분야의 연구가 시작되고 있다. 동영상을 기반으로 하는 VideoGIS는 기존의 2D 및 2.5D GIS보다 더 현실감있고 생동감있는 정보의 제공이 가능할 것으로 기대된다. 그러나 동영상의 경우, 그 양이 방대할 뿐 아니라, 본질적으로 순차적인 특징을 가지고 있어 자료 사용(브라우징 및 검색)에 있어 사용자가 필요한 정보에 접근하기 위해서는 반복적인 검색기능을 수행해야 하는 문제점이 있다. 동영상 자료의 접근성 개선 및 VideoGIS의 기초 자료로 활용하기 위해 본 논문에서는 동영상 자료구조화에 관한 연구를 수행하였다.

• Journal of the Korean Operations Research and Management Science Society
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• v.26 no.3
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• pp.1-20
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• 2001

The amount of financial information in sophisticated large data bases is huge and makes interfirm performance comparisons very difficult or at least very time consuming. The purpose of this paper is to investigate whether neural networks in the form of self-organizing maps (SOM) can be successfully employed to manage the complexity for competitive financial benchmarking. SOM is known to be very effective to visualize results by projecting multi-dimensional financial data into two-dimensional output space. Using the SOM, we overcome the problems of finding an appropriate underlying distribution and the functional form of data when structuring and analyzing a large data base, and show an efficient procedure of competitive financial benchmarking through clustering firms on two-dimensional visual space according to their respective financial competitiveness. For the empirical purpose, we analyze the data base of annual reports of 100 Korean listed companies over the years 1998, 1999, and 2000.

• The Journal of Korean Association of Computer Education
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• v.21 no.3
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• pp.11-20
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• 2018

One major change in the 2015 revised national curriculum is that computational thinking ability is becoming an essential competency for students. Computational thinking is divided into abstraction, automation, and creative convergence in the curriculum for secondary schools' Information subject. And, the curriculum contains problem solving and programming area. Among the components of computational thinking, data representation emphasizes the ability to structure data and information for problem solving of learners. Pre-service teachers of Information subject at secondary schools also learn how to structure information through diagramming. There are differences in the ability to structure diagrams among students, but the studies on learning methods that help students develop their structuring abilities have rarely been performed. The purpose of this paper is to analyze the differences of abstract thinking disposition and gender perspective among college students. As a result, female students had more concrete thinking disposition than male students. Also, there were gender differences according to the characteristics of diagrams. Differences in abstract thinking disposition also made a difference in structuring diagrams. It is useful for achieving the education purpose of improving computational thinking ability by finding out the differences in thinking tendency between males and females and finding the education method that can complement them.

• The Transactions of the Korea Information Processing Society
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• v.5 no.11
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• pp.2797-2808
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• 1998

Multimedia scenario database system is a read-only multimedia-on-demand system which transfers scenarios representing the display ordering of multimedia objects. A scenario is a graph of multimedia objects and it contains spatial, temporal and contextual information of multimedia data. By structuring multimedia objects as a scenario, it is possible to enforce their display order based on their context. Furthermore, it can provide multiple display paths as well as the sharing of objects between different scenarios. As a result, the multimedia scenario database system can perform the pre-scheduling of multimedia objects, which makes it possible to reorder the transmission order of objects in a scenario. Consequently, the overall system resource such as data buffer and network bandwidth can be highly utilized. In this paper, we discuss the requirements of structuring a scenario to design a scenario database that stores and manages multimedia scenario. Furthermore, we devise and analyze several scheduling policies based on the reordering mechanism for the objects in a scenario.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.7
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• pp.1277-1282
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• 2016

The term "Big Data" has been defined to encapsulate a broad spectrum of data sources and data formats. It is often described to be unstructured data due to its properties of variety in data formats. Even though the traditional methods of structuring data in rows and columns have been reinvented into column families, key-value or completely replaced with JSON documents in document-based databases, the fact still remains that data have to be reshaped to conform to certain structure in order to persistently store the data on disc. ETL processes are key in restructuring data. However, ETL processes incur additional processing overhead and also require that data sources are maintained in predefined formats. Consequently, data in certain formats are completely ignored because designing ETL processes to cater for all possible data formats is almost impossible. Potentially, these unconsidered data sources can provide useful insights when incorporated into big data analytics. In this project, using big data solution, Apache Spark, we tapped into other sources of data stored in their raw formats such as various text files, compressed files etc and incorporated the data with persistently stored enterprise data in MongoDB for overall data analytics using MongoDB Aggregation Framework and MapReduce. This significantly differs from the traditional ETL systems in the sense that it is compactible regardless of the data formats at source.

• Journal of the Korea Society of Computer and Information
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• v.21 no.9
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• pp.85-90
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• 2016

In this paper, we study the domain-independent sensor data structuring method and the derivations about ' Filter Criteria' expansion factors of heterogeneous domain systems. For this purpose, we propose a 5W1H based information search and retrieval method without knowledges about the target domains. And we also suggest a resource management model that can support expanding search of information. By the suggested method, the oneM2M standard able to implement the use-cases like 'data exchanging between the heterogeneous domains'.