• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권3호
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• pp.775-793
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• 2023

Human decision-making is a complex behavior. A replication of human decision making offers a potential to enhance the capacity of intelligent systems by providing additional user assistance in decision making. By reducing the effort and task complexity on behalf of the user, such replication would improve the overall user experience, and affect the degree of intelligence exhibited by the system. This paper explores individuals' decision-making processes when using recommender systems, and its related outcomes. In this study, human decision-making (HDM) refers to the selection of an item from a given set of options that are shown as recommendations to a user. The goal of our study was to identify IS constructs that contribute towards such decision-making, thereby contributing towards creating a mental model of HDM. This was achieved through recording Electroencephalographic (EEG) readings of subjects while they performed a decision-making activity. Readings from 16 righthanded healthy avid readers reflect that reward, theory of mind, risk, calculation, task intention, emotion, sense of touch, ambiguity and decision making are the primary constructs that users employ while deciding from a given set of recommendations in an online bookstore. In all 10 distinct brain areas were identified. These brain areas that lead to their respective constructs were found to be cingulate gyrus, precentral gyrus, inferior parietal lobule, posterior cingulate, medial frontal gyrus, anterior cingulate, postcentral gyrus, superior frontal gyrus, inferior frontal gyrus, and middle frontal gyrus (also referred to as dorsolateral prefrontal gyrus (DLPFC)). The identified constructs would help in developing a design theory for enhancing user assistance, especially in the context of recommender systems.

• 한국농공학회논문집
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• 제66권4호
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• pp.17-26
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• 2024

This study aimed to design and build a web-based decision support system for wheat cultivation management. The system is designed to collect and measure the weather environment at the growth stage on a daily basis and predict the soil moisture content. Based on this, APSIM, one of the process-based crop models, was used to predict the potential yield of wheat cultivation in real time by making decisions at each stage. The decision-making system for wheat crop management was designed to provide information through a web-based dashboard in consideration of user convenience and to comprehensively evaluate wheat yield potential according to past, present, and future weather conditions. Based on the APSIM model, the system estimates the current yield using past and present weather data and predicts future weather using the past 40 years of weather data to estimate the potential yield at harvest. This system is expected to be developed into a decision support system for farmers to prescribe irrigation and fertilizer in order to increase domestic wheat production and quality by enhancing the yield estimation model by adding influence factors that can contribute to improving wheat yield.

• 지능정보연구
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• 제14권2호
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• pp.83-102
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• 2008

본 연구에서는 무선 네트워크 접속기능을 갖춘 유비쿼터스 컴퓨팅 환경에서의 다중 동적 의사결정지원시스템(Multi-Dynamic Decision Support System in Ubiquitous Computing; UMD-DSS)을 제안한다. 즉 유비쿼터스 컴퓨터환경에서의 의사결정은 다수의 유동 참여자들이 시시각각 변화하는 정보를 기반으로 의사결정자들 개인의 목적과 참여된 집단의 목적을 동시에 만족하는 의사결정을 지원한다. 이를 위해 본 연구에서 제안하는 의사결정지원시스템은 혼합형구조를 이룬다. 개별 의사결정자들의 의사결정을 지원하는 분산형 의사결정지원시스템과 의사결정자가 속한 집단의 목적함수를 최대화를 지원하는 중앙집중형 의사결정 시스템이 혼합된 혼합형 의사결정지원시스템을 제안한다. 혼합형 의사결정지원시스템의 기본 구조는 의사결정에 참여하는 개별에이전트들로부터 인식된 상황정보를 이용한 의사결정프로세스를 관리하는 의사결정프로세서, 다중 에이전트들을 관리하는 다중 에이전트 프로세서 및 의사결정을 위해 필요한 지식을 관리하는 지능적 지식관리 프로세서로 구성된다. 유비쿼터스 컴퓨터 환경에서의 의사결정은 시간과 공간의 제약을 받지 않으며 다중 유동의사결정자의 의사결정을 동시에 할 수 있고, 이러한 의사결정이 의사결정자가 속한 집단의 목적함수를 최대화 할 수 있도록 해야 한다. 이에 적합한 비구조적인 문제인 유풀필먼트(u-Fulfillment)의 특징은 다음과 같다. 의사결정에 참여하는 유동 의사결정자가 다수이며 시시각각으로 변하는 문제에 즉각적인 대응이 요구되고 단기간의 공유된 정보를 활용하여 의미 있는 의사 결정이 요구되는 특징이 있다. 따라서 본 연구에서는 유풀필먼트(u-Fulfillment)를 본 연구의 활용 대상으로 하여 유비쿼터스 다중 동적 의사결정지원시스템을 제안한다.

• 품질경영학회지
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• 제34권3호
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• pp.31-40
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• 2006

Companies had to be more intelligent in order to survive in the rapidly changing environments. We need to make a decision to build the Information System to support the managers in their decision making. That is the reason many companies are tend to have Business Intelligence Systems. But, how can we know the new system would be better than the old system in making us intelligent? The answer is we can do it with the concept of Intelligence Density. In this study, Intelligence Density concept will be introduced, and the way how it can be applied to the information system will be presented. I think Intelligence Density should be studied more to help managers make right decisions for the DSS implementation.

• Spatial Information Research
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• 제1권1호
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• pp.63-72
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• 1993

현재의 GIS가 감당할 수 있는 것은 모든 공간적 문제는 아니다. 그동안 알려진 GIS는 정보를 생산해 내는 정보위주의 GIS일뿐 정보의 다각적 이해와 의사결정과 정에 깊이 관여하지 못하였다. 단순문제(structured problems)들을 해결하기에는 정보위주의 GIS가 적합하지만 계획과 설계와 같은 비단순문제(ill-structured problems)들을 다루기에는 미흡한 단계이며, 이 단계에서 도약하기 위해 개념위주의 SDSS(Spatual Decision Suppert System)로 발전되어야 한다. 이 글에서는 개념위주의 SDSS가 비단순문제 해결을 지원하기 위한 기구로서 소개되며 정보위주 GIS의 미래상으로 비젼(vision)을 제시한다.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2005년도 공동추계학술대회
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• pp.183-192
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• 2005

Recently, community computing has been proposed for group formation and group decision-making. However, legacy community computing systems do not support group need identification for ad hoc group formation, which would be one of key features of ubiquitous decision support systems and services. Hence, this paper aims to provide a multi-agent based methodology to enable nomadic community computing which supports ad hoc need identification and group formation. Focusing on supporting group decision-making of relatively small sized multiple individual in a community, the methodology copes with the following three characteristics: (1) ad hoc group formation, (2) context-aware group need identification, and (3) using mobile devices working in- and out-doors. NAMA-US, an RFID-based prototype system, has been developed to show the feasibility of the idea proposed in this paper.

• 한국BIM학회 논문집
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• 제6권3호
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• pp.24-33
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• 2016

Planning occurs from day-to-day, small-scale decisions to large-scale infrastructure investment decisions. For that reason, various attempts have been made to appropriately assist decision-making process and its optimization. Lately, initiation of a large amount of data, also known as big data has received great attention from diverse disciplines because of versatility and adoptability in its use and possibility to generate new information. Accordingly, implementation of big data and other information management systems, such as geographic information systems (GIS) and building information modeling (BIM) have received enough attention to establish each of its own profession and other associated activities. In this extent, this study illustrates a series of big data implementation cases that can provide a lesson to urban planning domain. In specific, case studies analyze how data was used to extract the most optimized solution and what aspects could be helpful in relation to planning decisions. Also, important notions about GIS and its application in various urban cases are examined.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 1993년도 수공학연구발표회논문집
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• pp.3-26
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• 1993

I have briefly described some of the important advances in hydrosystems and to remark on the important scientific research priorities in hydrological sciences. We have concentrated on data collection systems, real-time control of hydrosystems, global climate change and decision support systems and GIS. In summary, I would like to stress the following points: - the advances in data collection systems, advanced methodologies for interfacion hydrologic, hydraulic, and optimization models through optimal control approaches; and the advances in decision support systems and GIS will allow the interfacing of all these technologies into some sophisticated and much needed tools for operating hydrosystems; - the ability to better understand the hydrologic processes and their relationships to other earth processes is important to understanding and modelling of the hydrologic cycle and its interactions with the ocean-atmosphere system; - and the solution to a better understanding of hydrologic sciences needs to be an international effort such as the GEWEX program briefly discussed above. I would like to thamk each of you for listening to my lecture and to once again thank those responsible for me being here today. Thank you.

• 태양에너지
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• 제10권1호
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• pp.63-79
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• 1990

태양열 주택 및 급탕의 보급 정책은 민수용 에너지의 절감 또는 대체의 의미에서 그 필요성 및 당위성을 인정받고 있으나, 다른 대체에너지와 마찬가지로 태양열 이용시스템의 경제성이 가상 문제가 되고 있는 실정이다. 본 연구에서는 태양열 주택 및 급탕의 경제성을 상세히 분석함으로써 실질적인 보급정책 자료를 제공하며, 실수요자를 위한 계몽근거를 마련하고자 한다. 본 연구에서는 태양열 이용시스템의 경제성을 정확히 수행하기 위한 의사결정지원 시스템(decision support system)을 확립시켰으며, 이에 따른 태양열 이용시스템의 열적성능 해석과 동시에 경제성 분석은 시행오차(trial & error)하에 수행할 수 있도록 각종전산 프로그램을 개발하였다. 태양열 주택 및 급탕의 열적성능 해석은 모의실험을 통하여 기상 조건과의 상관관계를 도출하고 태양열 이용시스템의 추가비용 및 연료가 이용을 현재가 (present worth) 개념으로 적응하여 산출하고, 순익분기 해석법 (break-even point analysis method) 및 수명가 산정법(life-cycle cost analysis method)으로 경제성 분식을 중점적으로 수행하였다.

• 산업경영시스템학회지
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• 제45권4호
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• pp.180-186
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• 2022

Agrophotovoltaic (APV) system is an integrated system producing crops as well as solar energy. Because crop production underneath Photovoltaic (PV) modules requires delicate management of crops, smart farming equipment such as real-time remote monitoring sensors (e.g., soil moisture sensors) and micro-climate monitoring sensors (e.g., thermometers and irradiance sensors) is installed in the APV system. This study aims at introducing a decision support system (DSS) for smart farming in an APV system. The proposed DSS is devised to provide a mobile application service, satellite image processing, real-time data monitoring, and performance estimation. Particularly, the real-time monitoring data is used as an input of the DSS system for performance estimation of an APV system in terms of production yields of crops and monetary benefit so that a data-driven function is implemented in the proposed system. The proposed DSS is validated with field data collected from an actual APV system at the Jeollanamdo Agricultural Research and Extension Services in South Korea. As a result, farmers and engineers enable to efficiently produce solar energy without causing harmful impact on regular crop production underneath PV modules. In addition, the proposed system will contribute to enhancement of the smart farming technology in the field of agriculture.