• Journal of Information Science Theory and Practice
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• v.11 no.2
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• pp.67-81
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• 2023

This paper presents a dynamic development of an ontology-based statistical information system supporting the collection, storage, processing, analysis, and the presentation of statistical knowledge at the national scale. To accomplish this, we propose a data mining technique to dynamically collect data relating to citizens from publicly available data sources; the collected data will then be structured, classified, categorized, and integrated into an ontology. Moreover, an intelligent platform is proposed in order to generate quantitative and qualitative statistical information based on the knowledge stored in the ontology. The main aims of our proposed system are to digitize administrative tasks and to provide reliable statistical information to governmental, economic, and social actors. The authorities will use the ontology-based statistical information system for strategic decision-making as it easily collects, produces, analyzes, and provides both quantitative and qualitative knowledge that will help to improve the administration and management of national political, social, and economic life.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.5
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• pp.141-148
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• 1994

Both the neural network classifier utilizing multi-layer perceptron and the linear tree classifier composed of hierarchically structured linear discriminating functions can form arbitrarily complex decision boundaries in the feature space and have very similar decision making processes. In this paper, a new method for automatically choosing the number of neurons in the hidden layers and for initalzing the connection weights between the layres and its supporting theory are presented by mapping the sequential structure of the linear tree classifier to the parallel structure of the neural networks having one or two hidden layers. Experimental results on the real data obtained from the military ship images show that this method is effective, and that three exists no siginificant difference in the classification acuracy of both classifiers.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2007.02a
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• pp.131-138
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• 2007

Distributed Group Decision Support System (GDSS) is in the stage between exploration and implementation, there is not unified constructing model. As computer software and hardware, network technique develop, especially the development of object-oriented programming, distributed process, and artificial intelligence, this makes it possible the practical and valid implementation of distributed GDSS. With a view of emphasizing and solving process-supporting, this article discusses how to use the key technologies of network, distributed process, artificial intelligence and man-machine mutual interface, to implement more adaptable, more flexible, and more valid GDSS than before.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.485-492
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• 2020

Information on the energy consumption of buildings that can be obtained through conventional methods is limited. Therefore, this study aims to develop a model that can support decision making about building facility management through digital transformation technologies. Through the IoT sensor, the building's energy data and indoor air quality data are collected, and the monitored data is visualized through the ELK Stack and produced as a dashboard. In addition, the target building is photographed with a 360-degree camera and maps using a tool to create a 360-degree tour. Using such digital transformation technologies, users of buildings can obtain various information in real time without visiting buildings directly. This can lead to changes in actions or actions for building management, supporting facility management decisions, and consequently reducing building energy consumption.

• International Commerce and Information Review
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• v.8 no.3
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• pp.3-21
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• 2006

This study aims to explore the developing strategies of knowledge based industry in ChunChon Area. This study suggests several strategies for promoting local development in Chunchon Area as follows ; first, building of local innovation system in chunchon area and convergence and diffusion of knowledge based industries. second, making of industrial environment suitable to developing knowledge based industries. third, the establishment of overall industrial supporting systems. fourth, expansion of industrial infra and prevention of the brain drain. fifth, transformation of industrial complex into innovation clusters. The result of this study will be useful for the chief executives officers to make more rational decision making for industrial developing strategies is related to the Knowledge based Industries. The paper also strives to provoke debate in this area with to encouraging further research on the topic.

• Journal of Information Technology Services
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• v.11 no.1
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• pp.83-92
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• 2012

The development of science and technology oriented knowledge society accelerates the convergence between scientific theory and industrial technology and increases the complexity problem of social and economic sectors. These cause the difficulty of securing the reliability and objectivity of science and technology policy. These also are barriers of balanced evaluation between rational science and technology policy making, management, and policy coordination. In this regard, Advanced countries in science and technology develops policy support system and promotes the program of evidence-based SciSIP(Science of Science and Innovation policy) together. This paper introduces a new approach developing science service of science and technology policy utilizing business intelligence technology in Korea. Also, it proposes the integration method of policy knowledge base and component-based service supporting S&T policy decision-making process and introduces services case studies.

• Journal of Agricultural Extension & Community Development
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• v.11 no.2
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• pp.359-369
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• 2004

The objectives of this study were: a) to classify the rural women's roles according to degree of participation in farming and decision making, b) to find out the needs for support policy considering the role types, and c) to put forward the programs for supporting rural women according to their role types. This study was based on a literature review, empirical analysis, and opinions from a panel of experts and professionals including rural women in Korea. Based on the findings from this study, the following suggestions should be considered for supporting the rural women according to the types of their roles: 1) Government should enhance the support system for rural women in terms of policy and social system. Careful considerations on the status of woman farmers according to their role types should be reflected in the policy and social system. 2) Family cultural reform, farming helper system, reducing the housework burden, supporting educational expenses, and providing more opportunities for closer contact to the community actions and educational programs should be included in the support system. 3) Rural women's participation in various community action and educational programs should be encouraged by providing diverse incentives, appropriate information and educational supports designed to support woman farmers.

• Journal of the Korean Society of Marine Environment & Safety
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• v.10 no.1 s.20
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• pp.23-28
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• 2004

Up until now, the government has propelled various projects to establish and stabilize the Safety Management System(SMS). Now it is time for companies to diagnose and evaluate the safety management system to see if it is being operated in accordance with the situations of the companies. Therefore, this study has proposed to develop a model that can monitor the safety management system and evaluate operational achievements and an implementation supporting module that can operate the safety management system. Additionally, the AHP scheme was reviewed, which is one of the major decision making method." mainly used in Management Science.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.5
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• pp.521-530
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• 2018

This paper proposes "The Agriculture Decision-making System(ADS) based on Deep Learning for improving crop productivity" that collects weather information based on location supporting precision agriculture, predicts current crop condition by using the collected information and real time crop data, and notifies a farmer of the result. The system works as follows. The ICM(Information Collection Module) collects weather information based on location supporting precision agriculture. The DRCM(Deep learning based Risk Calculation Module) predicts whether the C, H, N and moisture content of soil are appropriate to grow specific crops according to current weather. The RNM(Risk Notification Module) notifies a farmer of the prediction result based on the DRCM. The proposed system improves the stability because it reduces the accuracy reduction rate as the amount of data increases and is apply the unsupervised learning to the analysis stage compared to the existing system. As a result, the simulation result shows that the ADS improved the success rate of data analysis by about 6%. And the ADS predicts the current crop growth condition accurately, prevents in advance the crop diseases in various environments, and provides the optimized condition for growing crops.

• Journal of Intelligence and Information Systems
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• v.12 no.4
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• pp.73-90
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• 2006

When a consumer intends to purchase products through Internet stores, many difficulties are met because of limitations of the current search engines and the current web structure, and lack of tools supporting decision-makings. This paper raises an Internet shopping problem and proposes a framework of decision making process to settle it with an intelligent agent based on Semantic Web and Finite Domain Constraint. The agent uses finite domain constraint programming as modeling and solution methods for the decision problem under the Semantic Web environment.