• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.3
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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.

• Journal of The Korean Society of Agricultural Engineers
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• v.66 no.4
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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.

• Journal of Intelligence and Information Systems
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• v.14 no.2
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• pp.83-102
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• 2008

Ubiquitous computing requires timely supply of contextual information in order to upgrade decision quality. In this sense, this study is aimed at proposing a multi-dynamic decision support system for highly ill-structured problems. Especially, it is very important for decision makers in the ubiquitous computing to coordinate conflicts among local goals and global goal harmoniously. The proposed Multi-Dynamic Decision Support System (MDDSS) is basically composed of both central structure and distributed structure, in which central structure supports multi objects decision making and distributed structure supports individual decision making. Its hybrid architecture consists of decision processor, multi-agent controller and intelligent knowledge management processor. Decision processor provides decision support using contexts which come from individual agents. Multi-agent controller coordinates tension among multi agents to resolve conflicts among them. Meanwhile, intelligent knowledge management processor manages knowledge to support decision making such as rules, knowledge, cases and so on. To prove the validity of the proposed MDDSS, we applied it to an u-fulfillment problem system in which many kinds of decision makers exist trying to satisfy their own objectives, and timely adjustment of action strategy is required. Therefore, the u-fulfillment problem is a highly ill-structured problem. We proved its effectiveness with the aid of multi-agent simulation comprising 60 customers and 10 vehicles under three experimental modes.

• Journal of Korean Society for Quality Management
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• v.34 no.3
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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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• v.1 no.1
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• pp.63-72
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• 1993

The purpose of this research is to determine how the present use of Geographic Information Systems (GISs) can be improved for ill-structured problems in planning and design, While information-oriented GIS technology has proven useful for routine and administrative problems, it is not yet capable of providing information and knowledge interactively within a problem solving process that can be characterized as "ill-structured." This suggests that GIS technology must be embedded wi thin a large problem solving process for ill-structured problems. The hypothesis of this research is that implementation of conceptualization-oriented Spatial Decision Support Systems(SDSSs) will significantly improve the use of GIS technology for ill-structured problems.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.11a
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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.

• Journal of KIBIM
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• v.6 no.3
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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.

• Proceedings of the Korea Water Resources Association Conference
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• 1993.07a
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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.

• Solar Energy
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• v.10 no.1
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• pp.63-79
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• 1990

It has been recognized that a policy for supplying solar house and hot water production systems utilizing solar energy needs to be driven to save civilian comsuming energy or to develop alternative energy. However, the economic feasibility study of solar energy systems must be carried out before their practical use. The purpose of this study is to furnish information for supplying policy and enlightening users with the economic feasibility study of solar house and hot water production systems. Decision support systems are established to carry out economic analysis on solar systems more accurately. Therefore, computer simulation is carried out to analyze the performance of solar systems and also economic feasibility study by trial and error method is carried out. Fuel cost and additional cost for solar systems are estimated employing present worth concept and economic analysis has been conducted using the break-even point analysis method and life-cycle cost analysis method.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.4
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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.