• Nuclear Engineering and Technology
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• v.49 no.1
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• pp.148-164
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• 2017

The focus on the issues surrounding spent nuclear fuel and lifetime extension of old nuclear power plants continues to grow nowadays. A transparent decision-making process to identify the best suitable nuclear fuel cycle (NFC) is considered to be the key task in the current situation. Through this study, an attempt is made to develop an equilibrium model for the NFC to calculate the material flows based on 1 TWh of electricity production, and to perform integrated multicriteria decision-making method analyses via the analytic hierarchy process technique for order of preference by similarity to ideal solution, preference ranking organization method for enrichment evaluation, and multiattribute utility theory methods. This comparative study is aimed at screening and ranking the three selected NFC options against five aspects: sustainability, environmental friendliness, economics, proliferation resistance, and technical feasibility. The selected fuel cycle options include pressurized water reactor (PWR) once-through cycle, PWR mixed oxide cycle, or pyroprocessing sodium-cooled fast reactor cycle. A sensitivity analysis was performed to prove the robustness of the results and explore the influence of criteria on the obtained ranking. As a result of the comparative analysis, the pyroprocessing sodium-cooled fast reactor cycle is determined to be the most competitive option among the NFC scenarios.

• Journal of the Korea Convergence Society
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• v.12 no.9
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• pp.307-314
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• 2021

This study examined to identify the effect of self-leadership, career decision-making self-efficacy, and critical thinking disposition on career preparation behavior in nursing students. Data were collected from nursing students attending in nursing departments in G and M cities from April to June 2019. The 208 data were analyzed by descriptive statistics, t-test, ANOVA, Pearson's correlation coefficient, and multiple regression analysis. Self-leadership(β=.331, p<.001) and critical thinking disposition(β=.302, p<.001) reported to have effect on career preparation behavior. The study model accounted for 38.7% of career preparation behavior. These results suggest that measures to promote self-leadership and career decision-making self-efficacy should be developed and operated to improve career preparation behavior of nursing students in the nursing education field.

• International Journal of Quality Innovation
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• v.10 no.1
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• pp.37-51
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• 2009

The purpose of TQM (Total Quality Management)-centered organizational culture is to enhance the efficiency of business through the proper allocation and concentration of restricted resources. In order to maximize the corporate profitability through customer satisfaction, what kind of, when and how many resources should be allocated and managed to the preventive TQM activities and corrective TQM activities have become a very important decision making factors at the point of high management. This study aims to identify the causal relationships of quality-centered organizational culture on service quality and customer satisfaction relating to service failure in food service industry. And this study is intended to discover the factors of quality-centered organizational culture which impacts on service recovery justice after service failure happens, and it can be helpful for the top managers to make a decision to how to form corporate structural culture.

• Proceedings of KOSOMES biannual meeting
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• 2018.06a
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• pp.138-138
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• 2018

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.231-252
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• 2021

Artificial intelligence (AI) is a key technology that will change the future the most. It affects the industry as a whole and daily life in various ways. As data availability increases, artificial intelligence finds an optimal solution and infers/predicts through self-learning. Research and investment related to automation that discovers and solves problems on its own are ongoing continuously. Automation of artificial intelligence has benefits such as cost reduction, minimization of human intervention and the difference of human capability. However, there are side effects, such as limiting the artificial intelligence's autonomy and erroneous results due to algorithmic bias. In the labor market, it raises the fear of job replacement. Prior studies on the utilization of artificial intelligence have shown that individuals do not necessarily use the information (or advice) it provides. Algorithm error is more sensitive than human error; so, people avoid algorithms after seeing errors, which is called "algorithm aversion." Recently, artificial intelligence has begun to be understood from the perspective of the augmentation of human intelligence. We have started to be interested in Human-AI collaboration rather than AI alone without human. A study of 1500 companies in various industries found that human-AI collaboration outperformed AI alone. In the medicine area, pathologist-deep learning collaboration dropped the pathologist cancer diagnosis error rate by 85%. Leading AI companies, such as IBM and Microsoft, are starting to adopt the direction of AI as augmented intelligence. Human-AI collaboration is emphasized in the decision-making process, because artificial intelligence is superior in analysis ability based on information. Intuition is a unique human capability so that human-AI collaboration can make optimal decisions. In an environment where change is getting faster and uncertainty increases, the need for artificial intelligence in decision-making will increase. In addition, active discussions are expected on approaches that utilize artificial intelligence for rational decision-making. This study investigates the impact of artificial intelligence on decision-making focuses on human-AI collaboration and the interaction between the decision maker personal traits and advisor type. The advisors were classified into three types: human, artificial intelligence, and human-AI collaboration. We investigated perceived usefulness of advice and the utilization of advice in decision making and whether the decision-maker's personal traits are influencing factors. Three hundred and eleven adult male and female experimenters conducted a task that predicts the age of faces in photos and the results showed that the advisor type does not directly affect the utilization of advice. The decision-maker utilizes it only when they believed advice can improve prediction performance. In the case of human-AI collaboration, decision-makers higher evaluated the perceived usefulness of advice, regardless of the decision maker's personal traits and the advice was more actively utilized. If the type of advisor was artificial intelligence alone, decision-makers who scored high in conscientiousness, high in extroversion, or low in neuroticism, high evaluated the perceived usefulness of the advice so they utilized advice actively. This study has academic significance in that it focuses on human-AI collaboration that the recent growing interest in artificial intelligence roles. It has expanded the relevant research area by considering the role of artificial intelligence as an advisor of decision-making and judgment research, and in aspects of practical significance, suggested views that companies should consider in order to enhance AI capability. To improve the effectiveness of AI-based systems, companies not only must introduce high-performance systems, but also need employees who properly understand digital information presented by AI, and can add non-digital information to make decisions. Moreover, to increase utilization in AI-based systems, task-oriented competencies, such as analytical skills and information technology capabilities, are important. in addition, it is expected that greater performance will be achieved if employee's personal traits are considered.

• Journal of Engineering Education Research
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• v.17 no.5
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• pp.28-32
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• 2014

Engineering Ethics is a fundamental and essential subject and the understanding of ethics is of great importance for students in engineering courses and professional engineers. Most courses would consist of ethical tests, decision making opportunities, case studies, case methods, and group discussion. It is important to consider each case carefully, so we offer a number of hypothetical short stories to students as case methods that they cover in detail. We check the behavior decisions of students as they read the hypothetical short stories. In this study, the short story was about 200 words in length. This paper shows how, with the addition of minor changes to the text, some students changed their behavioral decisions. For example, with the addition of "if you take financial liability for the losses," some thought that they would not want to carry the debt. Other cases showed how some students disliked the majority rule. The paper shows that this arranged hypothetical short story method can often guide student's decision-making process, and can result in decreased undesirable decisions.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.7
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• pp.584-590
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• 2001

An inventory management system of manufacturing industry has a model of different kinds according to the objective and the situation. An inventory management system needs superior system technique in demand forecast, economical efficiency, reliability and application for stable supply of the finished goods, the raw materials and the parts. This paper proposes a demand forecast method based on fuzzy structured neural network, which uses min-operation and trapezoid membership function of fuzzy rules. So we can construct an intelligent inventory management system that make optimized decision-making for forecasting data with expert s opinion in fuzzy environment. The inventory management system uses intelligence agent and it could be adapted to a system environment change in order.

• Spatial Information Research
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• v.21 no.1
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• pp.75-86
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• 2013

The use of planning support systems in urban planning and management provides objective information that is beneficial in the decision-making stage. The existing planning support system, however, lacks in the consideration of ecological properties. In this study, a planning support system development that is capable of reflecting ecological elements was set as the ultimate goal. This system can support planning processes ranging from ecological potential anaylsis to alternatives designing and stimulation. Additionally, factors such as soil, water, climate, biotope, ecological network and recreation can be handled according to their natural potentials. The establishment and visualization of land use planning that addresses ecological characteristics based on the analyzed results are possible. Therefore, this system could operate as a framework to assist planners and decision makers through a computer-based system to provide useful ecological information and to allow effective decision-making by analyzing, displaying and visualizing ecological spatial data.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.4
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• pp.25-37
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• 2009

This Study constructs a dashboard system to synthetically and systematically monitor national R&D information based on data warehouse. Managing the national R&D statistics and trend is important since it provides data for policies and decision making for national R&D. Many agencies related to national R&D information collect the basic R&D statistic data which provides the basis of logical decision making and R&D policies. The data has not well been used. The data has not been consistently collected nor managed. The raw data has not been organized nor processed to meet various demands. The needs has been arisen for a consistent national R&D monitoring system to increase the relevance, accessibility and efficiency of data for various users. This study selects 25 key indicators based on the user requirements and designs data warehouse for supporting the indicators using star schema. The dashboard system is developed in this study provides the infrastructure of monitoring national R&D information and analytic environment of supporting statistical analysis and time-series data analysis.

• Journal of Navigation and Port Research
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• v.35 no.10
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• pp.837-846
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• 2011

Due to its vast range of areas and scopes of port logistics, professional training for port logistics experts has faced a limitation to raise manpower that the nation and companies ask for. This study looks at the current and expected demand and supply of workforce to identify necessary subjects and competitive factors in secondary education for training port logistics experts. Based on previous studies, this study proposes an assessment model by eliciting the priority of subjects in secondary education. and then, provides reasons for decision making.