• 한국재난정보학회 논문집
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• 제5권2호
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• pp.76-85
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• 2009

SWE(Sensor Web Enablement) is the standard platform of OGC for the sensor data service. SWE is only focusing in the data transmission protocols, but supporting the semantic decision. Sensor data service is the decision service of the status whether is on normal or not. In this study, we study the semantic decision model of the sensor data. It can support the context-aware service based on the decision information.

• International Journal of Naval Architecture and Ocean Engineering
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• 제3권4호
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• pp.233-241
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• 2011

The article describes actions and strategies to obtain higher productivity on maritime automobile terminals. The main focus is on elaboration of efficient and effective organizational structure to model and implement short-term, mid-term and long-term strategies. In addition, with an empiric approach we combined the analyses of current findings in important scientific papers and our acknowledgments in practical research of north Adriatic maritime automobile terminals. The main goal is to propose actions towards increasing system's productivity. Based on our research of the north Adriatic maritime automobile terminals and with Lambert's model an in-deep analysis of limiting factors, user's expectations and possibilities for productivity increase has been performed. Moreover, with our acknowledgments a three-level decision-support model is presented. With an adequate model implementation it is possible to efficiently develop and implement different strategies of productivity measurement and productivity increase, especially in the fields of internal transport productivity, entrance/exit truck gates operations and wagon manipulations. According to our observation a significant increase might be achieved in all three fields.

• 한국정보시스템학회지:정보시스템연구
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• 제8권2호
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• pp.91-110
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• 1999

Recently, searching agent systems to help purchase of products between business and customer have been actively studied in Electronic Commerce(EC). However, the most of comparative searching agent systems are only provided customers with searching results by the keyword-based search, and is not support the efficient decision models to be selected products considering the customer's requirements. This paper proposes the decision agent system applied decision model as well as searching functions based on the keyword-input to be selected useful products in EC. The proposed decision agent system is consist of the user interface, provider interface, decision model. Especially, as the example of the decision model, this paper is designed and implemented the prototype of decision agent system which is normalized the searching data and value of customer's preference weight as to each attribute, and orderly provided customers with computed results. This agent system is also carried out sensitive analysis according to the reflection ratio of the each attribute.

• 정보관리연구
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• 제33권4호
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• pp.107-128
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• 2002

이 연구는 R&D 투자에 대한 신속한 의사결정을 지원하고 R&D의 경제적 성과를 극대화시키기 위하여 R&D 기획 초기부터 기술의 경제적 수익에 대한 개념을 도입하고, 개발 완료된 R&D 기술의 상용화에 이르기까지 의사결정에 필요한 정보를 제공하는 시스템에 관한 것이다. 이 연구는 R&D 의사결정의 주요 경로를 파악하고, 단계별로 소요되는 정보에 대한 분석과 지식정보의 지원을 위하여 KISTI 과학기술 데이터 베이스 및 다른 공개용 정보원과의 원활한 연계 및 기술가치평가 정보 지원으로 구성되어 있다. 특히, 경제적 성과를 추정하기 위한 기술가치평가 정보 지원은 단계별 근거가 되는 지식정보를 지원하는 KISTI 기술가치평가 모델을 접목함으로써 좀더 객관적인 추정과 의사결정을 지원하도록 하였다.

• Smart Structures and Systems
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• 제26권4호
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• pp.533-544
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• 2020

Effective bridge maintenance reduces bridge operation costs and extends its service life. The possibility of storing bridge life-cycle data in a 3D parametric model of the bridge through Bridge Information Modeling (BrIM) provides new opportunities to enhance current practices of bridge maintenance management. This study develops a Decision Support System (DSS), namely BrDSS, which employs BrIM and an efficient optimization model for bridge maintenance planning. The BrIM model in BrDSS extracts basic data of elements required for the optimization process and visualizes the inspection data and the optimization results to the user to help in decision makings. In the optimization module of the DSS, the specifically formulated Genetic Algorithm (GA) eliminates the chances of producing infeasible solutions for faster convergence. The practicality of the presented DSS was explored by utilizing the DSS in the maintenance planning of a bridge under operation in the southwest of Iran.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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• pp.64-67
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• 2004

Change detection using aerial and satellite images is one of the important research topics in photogrammetry and image interpretation. It is of particular importance especially in the fields of military, political and administrative affairs. When there is a need to detect changes in multi-temporal images, the most efficient methods for change detection and thresholds of change/no change area need to be chosen. Also, the images obtained from the various methods need to be analyzed. To do so, we need a system that can support our decision making process. Therefore, in this paper, we propose the Decision Support System for Change Detection. This system is composed of Data Base, Model Base and Graphic User Interface(GUI). Data base is a compilation of previous change detection results, and Model Base comprise of numerous operations. The data can be input and have the results of change detection analyzed by using GUI. In this paper, we will explain the entire operation of the system and demonstrate the level of its effectiveness.

• International Journal of Computer Science & Network Security
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• 제22권11호
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• pp.184-188
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• 2022

The article considers the improved method and model of automated air situation assessment using a decision support system based on fuzzy networks of target installations. The advanced method of automated assessment of the air situation using the decision support system is based on the methodology of reflexive control of the first rank. With this approach, the process of assessing the air situation in the framework of the formulated task can be reduced to determining the purpose, probabilistic nature of actions and capabilities of the air target. The use of a homogeneous functional network for the formal presentation of air situation assessment processes will formally describe the process of determining classes of events during air situation assessment and the process of determining quantitative and qualitative characteristics of recognized air situation situations. To formalize the patterns of manifestation of the values of quantitative and symbolic information, it is proposed to use the mathematical apparatus of fuzzy sets.

• 한국군사과학기술학회지
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• 제27권1호
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• pp.80-93
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• 2024

This study attempted to analyze the factors that influence the participation of beneficiary companies in the government's defense industry promotion support project. To this end, experimental data were analyzed by constructing a prediction model consisting of highly important variables in beneficiary company decisions among various company information using the decision tree model, one of the data mining techniques. In addition, various rules were derived to determine the beneficiary companies of the government's support project using the analysis results expressed as decision trees. Three policy measures were presented based on the important rules that repeatedly appear in different predictive models to increase the effect of the government's industrial development. Using the analysis methods presented in this study and the determinants of the beneficiary companies of the government support project will help create a sustainable future defense industry growth environment.

• Journal of Korea Artificial Intelligence Association
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• 제1권1호
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• pp.1-6
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• 2023

This study developed models using decision forest, support vector machine, and logistic regression methods to predict and prevent suicidal ideation among Korean adolescents. The study sample consisted of 51,407 individuals after removing missing data from the raw data of the 18th (2022) Youth Health Behavior Survey conducted by the Korea Centers for Disease Control and Prevention. Analysis was performed using the MS Azure program with Two-Class Decision Forest, Two-Class Support Vector Machine, and Two-Class Logistic Regression. The results of the study showed that the decision forest model achieved an accuracy of 84.8% and an F1-score of 36.7%. The support vector machine model achieved an accuracy of 86.3% and an F1-score of 24.5%. The logistic regression model achieved an accuracy of 87.2% and an F1-score of 40.1%. Applying the logistic regression model with SMOTE to address data imbalance resulted in an accuracy of 81.7% and an F1-score of 57.7%. Although the accuracy slightly decreased, the recall, precision, and F1-score improved, demonstrating excellent performance. These findings have significant implications for the development of prediction models for suicidal ideation among Korean adolescents and can contribute to the prevention and improvement of youth suicide.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2001년도 The Pacific Aisan Confrence On Intelligent Systems 2001
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• pp.224-229
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• 2001

When a semiconductor package is assembled, various materials such as die attach adhesive, lead frame, EMC (Epoxy Molding Compound), and gold wire are used. For better preconditioning performance, the combination between the packaging materials by studying the compatibility of their properties as well as superior packaging material selection is important. But it is not an easy task to find proper packaging material sets, since a variety of factors like package design, substrate design, substrate size, substrate treatment, die size, die thickness, die passivation, and customer requirements should be considered. This research applies case-based reasoning(CBR) technique to solve this problem, utilizing prior cases that have been experienced. Our particular interests lie in building decision support model to aid the selection of proper die attach adhesive. The preliminary results show that this approach is promising.