• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.112-119
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• 2017

Selecting suppliers in the global supply chain is the very difficult and complicated decision making problem particularly due to the various types of supply risk in addition to the uncertain performance of the potential suppliers. This paper proposes a multi-phase decision making model for supplier selection under supply risks in global supply chains. In the first phase, the model suggests supplier selection solutions suitable to a given condition of decision making using a rule-based expert system. The expert system consists of a knowledge base of supplier selection solutions and an "if-then" rule-based inference engine. The knowledge base contains information about options and their consistency for seven characteristics of 20 supplier selection solutions chosen from articles published in SCIE journals since 2010. In the second phase, the model computes the potential suppliers' general performance indices using a technique for order preference by similarity to ideal solution (TOPSIS) based on their scores obtained by applying the suggested solutions. In the third phase, the model computes their risk indices using a TOPSIS based on their historical and predicted scores obtained by applying a risk evaluation algorithm. The evaluation algorithm deals with seven types of supply risk that significantly affect supplier's performance and eventually influence buyer's production plan. In the fourth phase, the model selects Pareto optimal suppliers based on their general performance and risk indices. An example demonstrates the implementation of the proposed model. The proposed model provides supply chain managers with a practical tool to effectively select best suppliers while considering supply risks as well as the general performance.

• Journal of the Korean Operations Research and Management Science Society
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• v.30 no.1
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• pp.75-94
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• 2005

Research in the decision sciences has continued to develop a variety of mathematical models as well as software tools supporting corporate decision-making. Yet. in spite of their potential usefulness, the models are little used in real-world decision making since the model solution processes are too complex for ordinary users to get accustomed. This paper proposes an intelligent and flexible model-solver integration framework that enables the user to solve decision problems using multiple models and solvers without having precise knowledge of the model-solution processes. Specifically, for intuitive model-solution, the framework enables a decision support system to suggest the compatible solvers of a model autonomously without direct user intervention and to solve the model by matching the model and solver parameters intelligently without any serious conflicts. Thus, the framework would improve the productivity of institutional model solving tasks by relieving the user from the burden of leaning model and solver semantics requiring considerable time and efforts.

• Communications of Mathematical Education
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• v.26 no.2
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• pp.221-249
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• 2012

The purpose of this study is to investigate students decision-making progress through ill-structured problem solving process. For this study, 25 fifth graders in an elementary school were observed by applying ABCDE model (Analyze - Browse - Create - Decision making - Evaluate), and analyzed their decision-making progress analyzing framework which follows 3 steps - making their own decision, discussing/revising with peers, and lastly decision making/solving problem. Upper two groups with better performance in ill-structured problem solving model among 6 groups showed active discussion in group and decision making process with 3 steps (making their own decision, discussing/revising with peers). Even though their decisions are not good-fit to mathematical reasoning result, development and application of ill-structured problems would bring better ability of high level thinking and problem solving to students.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.15 no.6
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• pp.89-96
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• 2001

This paper presents a decision making technique of reasonable $O_2$quantity needed to resolve organic matter via microbe in wastewater treatment. Decision making system of inferring reasonable $O_2$quantity consists of three parts. The first part is to compute reasonable $O_2$quantity with given process data. The second part is to find output features of processed wastewater using process model when $O_2$quantity is changed to a value inferred from decision making system. The third part is to show the results of decision making system. In order to verify performance of proposed decision making system computer simulation was done with process data gathered during 40 days. Simulation result shows that $O_2$quantity can be reduced over 10% under the condition of satisfying the specifications for processed wastewater.

• Journal of Oral Medicine and Pain
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• v.8 no.1
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• pp.5-31
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• 1983

Author studied the changes of experimental bite marks using a special apparatus which was equipped with adults human resin dental model(in accordance with the time elapsed). The experimental bite marks were made in the forearm of 20 healthy men and in the buttock of 10 Durac pigs with various pressure. In making the experimental bite marks, the left forearm was pressed with a load of 70kgs and 130kgs for 3 seconds, and 5 of the 10 pigs were sacrigiced immediately after making the bite marks. Through visual examinations, photographs and rubber base impressions of bite marks, following results were obtained : 1. The durations of measurable indentation of the experimental bite marks in the forearm of living human subject were depended upon the degree of the pressure and the length of the pressure time applied in making the bite marks. 2. As a physiological responds to a physical stimulus of biting, indentation, bruising, edema and subepithelial bleeding were observed in the experimental bite marks in the forearm of living human. And the experimental bite marks in the buttok of pigs which were sacrificed immediately after making the bite showed only indentation and subepithelial bleeding in addition to postmortem changes. 3. The duration of measurable indentation of the experimental bite marks in the buttock of pigs which were sacrificed immediatly after making the bite were much longer than those of the living pigs. 4. All of the measurements of the experimental bite marks were not matched completly with those of the model which was used in making the bite marks.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.203-214
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• 2024

This study seeks to provide implications for domestic-related policies through exploratory analysis research to support AI-based policy decision-making. The following should be considered when establishing an AI-based decision-making model in Korea. First, we need to understand the impact that the use of AI will have on policy and the service sector. The positive and negative impacts of AI use need to be better understood, guided by a public value perspective, and take into account the existence of different levels of governance and interests across public policy and service sectors. Second, reliability is essential for implementing innovative AI systems. In most organizations today, comprehensive AI model frameworks to enable and operationalize trust, accountability, and transparency are often insufficient or absent, with limited access to effective guidance, key practices, or government regulations. Third, the AI system is accountable. The OECD AI Principles set out five value-based principles for responsible management of trustworthy AI: inclusive growth, sustainable development and wellbeing, human-centered values and fairness values and fairness, transparency and explainability, robustness, security and safety, and accountability. Based on this, we need to build an AI-based decision-making system in Korea, and efforts should be made to build a system that can support policies by reflecting this. The limiting factor of this study is that it is an exploratory study of existing research data, and we would like to suggest future research plans by collecting opinions from experts in related fields. The expected effect of this study is analytical research on artificial intelligence-based decision-making systems, which will contribute to policy establishment and research in related fields.

• Journal of Korean Academy of Nursing
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• v.31 no.5
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• pp.846-857
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• 2001

This study was conducted to study on 1) What is nursing students' experience of ethical problems involving nursing practice\ulcorner 2) What is nursing students' experience of using ethical decision-making models\ulcorner Method: In order to answer these two questions, we selected 97 senior baccalaureate nursing students from two Korean universities using a conceptual framework and method of content analysis. Result: From 97 ethical problems emerged five content categories, the largest being ethical problems involving health professionals (69%); the basic nature of the nursing students' experience of ethical problems consisted of conflict, resolution, and rationale; 94% of the students stated that using an ethical decision- making model was helpful. Conclusion: Although additional research is needed, these findings have important implications for nursing ethics education and practice.

• Journal of Biosystems Engineering
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• v.42 no.2
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• pp.98-103
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• 2017

Purpose: Precision agriculture includes determining the right amount of nitrogen for a specific location in the field. This work focused on developing and validating a model using variable rate nitrogen application based on the estimated SPAD value from the ground-based image sensor. Methods: A variable rate N application based on the decision making system was performed using a sensor-based variable rate nitrogen application system. To validate the nitrogen application decision making system based on the SPAD values, the developed N recommendation was compared with another conventional N recommendation. Results: Sensor-based variable rate nitrogen application was performed. The nitrogen deficiency level was measured using the image sensor system. Then, a variable rate application was run using the decision model and real-ti me control. Conclusions: These results would be useful for nitrogen management of corn in the field. The developed nitrogen application decision making system worked well, when considering the SPAD value estimation.

• Journal of Intelligence and Information Systems
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• v.1 no.2
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• pp.1-16
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• 1995

The field of human judgment and decision making provides useful methodologies for examining the human decision making process and substantive results. One of the methodologies is a lens model analysis which can examine valid nonlinearity in the human decision making process. Using the method, valid nonlinearity in human decision behavior can be successfully detected. Two linear(statistical) models of human experts and two nonlinear models of human experts are compared in terms of predictive accuracy (predictive validity). The results indicate that nonlinear models can capture factors(valid nonlinearity) that contribute to the expert's predictive accuracy, but not factors (inconsistency) that detract from their predictive accuracy. Then, it is argued that nonlinear models cab be more accurate than linear models, or as accurate as human experts, especially when human experts employ valid nonlinear strategies in decision making.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.3
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• pp.220-224
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• 2008

This paper presents the polygon-based Q-leaning and Parallel SVM algorithm for object search with multiple robots. We organized an experimental environment with one hundred mobile robots, two hundred obstacles, and ten objects. Then we sent the robots to a hallway, where some obstacles were lying about, to search for a hidden object. In experiment, we used four different control methods: a random search, a fusion model with Distance-based action making (DBAM) and Area-based action making (ABAM) process to determine the next action of the robots, and hexagon-based Q-learning, and dodecagon-based Q-learning and parallel SVM algorithm to enhance the fusion model with Distance-based action making (DBAM) and Area-based action making (ABAM) process. In this paper, the result show that dodecagon-based Q-learning and parallel SVM algorithm is better than the other algorithm to tracking for object.