• International journal of advanced smart convergence
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• v.11 no.4
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• pp.68-80
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• 2022

Since the launch of AI, technology development to implement complete and sophisticated AI functions has continued. In efforts to develop technologies for complete automation, Machine Learning techniques and deep learning techniques are mainly used. These techniques deal with supervised learning, unsupervised learning, and reinforcement learning as internal technical elements, and use the Big-data Analysis method again to set the cornerstone for decision-making. In addition, established decision-making is being improved through subsequent repetition and renewal of decision-making standards. In other words, big data analysis, which enables data classification and recognition/recognition, is important enough to be called a key technical element of AI function. Therefore, big data analysis itself is important and requires sophisticated analysis. In this study, among various tools that can analyze big data, we will use a Python program to find out what variables can affect addiction according to smartphone use in a decision tree environment. We the Python program checks whether data classification by decision tree shows the same performance as other tools, and sees if it can give reliability to decision-making about the addictiveness of smartphone use. Through the results of this study, it can be seen that there is no problem in performing big data analysis using any of the various statistical tools such as Python and R when analyzing big data.

• Journal of Korean Home Economics Education Association
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• v.10 no.1
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• pp.171-183
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• 1998

The purpose of this study were to see the concept of creativity for the application to the home economics subject and to analyze the home economics textbooks required by the 6th curriculum in a viewpoint of the development of creativity. To achieve these purposes, the learning unit of making necessaries of 8 different home economics textbooks for middle school were compared in the point of titles of learning unit, learning objectives, contents of learning unit, study problems, and exercises. The results of this study were as follows : 1) For the learning objectives, most of home economics textbooks were focused on the basic knowledge and basic skills education rather than the creative thinking and creative problem solving. 2) For the contents of the textbooks, all of home economics textbooks were fixed by the materials and making steps for education of basic skills. So, it was found that the creativity of students could not developed. 3) For the study problems, most of home economics textbooks had some posibility of developing the creativity of students, relatively. 4) For the exercises, most of home economics textbooks had limited posibility of developing the creativity of students.

• Journal of Korean Home Economics Education Association
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• v.24 no.3
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• pp.101-122
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• 2012

The purpose of this study is to develop teaching learning process plans with problem-based learning using book-making applying to the "Dressing and Self Expression" unit and evaluate its effect in middle school home economics for first grade. We developed teaching learning process plans with problem-based learning using book-making including 9 teaching materials for teachers and 15 learning materials for students. Further, we conducted and investigated pre- and post-tests in a form of questionnaires in 167 students from a girls' middle school in Pusan. Teaching learning process plans with problem-based learning using book-making showed positive results in body satisfaction, such as reduction in distortion or less dissatisfaction regarding students' body images. Also, they were found to be less affected by sociocultural attitude towards appearance. The estimation of students included the positive contents that the class was interested with various materials and it provided them with a chance to understand their body. Meanwhile, minor comments pointed out lack of time and complained of the amount of assignments. With these results, we found that teaching learning process plans with problem-based learning using book-making was an appropriate model to achieve the purpose of this study and we suggested that this class might be applied to other units of middle school home economics.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2006.10a
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• pp.176-183
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• 2006

A novel intelligent anti-collision decision-making supporting system is addressed in this paper. To obtain precise anti-collision information capability, an innovative neurofuzzy network is proposed and applied. A fuzzy set interpretation is incorporated into the network design to handle imprecise information. A neural network architecture is used to train the parameters of the Fuzzy Inference System (FIS). The learning process is based on a hybrid learning algorithm and off-line training data. The training data are obtained by trial manoeuvre. This neurofuzzy network can be considered to be a self-learning system with the ability to learn new information adaptively without forgetting old knowledge. This supporting system can decrease ship operators' burden to deal with bridge data and help them to make a precise anti-collision decision.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.22 no.3
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• pp.308-317
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• 2015

Purpose: The aim of this study was to examine the effects of case-based learning (CBL) on clinical decision making and nursing performance. Methods: This research was conducted between September, 2011 and January, 2012 as a nonequivalent comparison group design. The participants were 55 third year nursing students who were enrolled in a college of nursing in a university in Korea. The intervention was the CBL procedures which involved role-play practice videoed by camera and watched on the computer by the students. Questionnaires were used before and after the intervention to measure clinical decision-making. Nursing performance tests were done after the intervention. Results: Statistically significant group differences were observed in clinical decision-making. Nursing performance was significantly higher in the CBL group than in the control group. Conclusion: CBL focused on the solving problem process and clinical cases which are based on clinical setting allowing students to develop efficiency in clinical practice and adaptation to the clinical situation.

• Journal of Information Technology Applications and Management
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• v.16 no.3
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• pp.113-124
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• 2009

How can action learning program promote organizational learning performance and especially project based team performance in Web-based small and medium-sized enterprises (SMEs)? This article discusses the association between project based team in action learning program and the performance of Web-based SME to be learning organization. In the case of ALPACO, action learning program that promote employee communication behavior, knowledge sharing, and organizational learning are found to be positively associated with the project based team performance and organizational learning, The results indicate that action learning program in SMEs indeed associated with greater knowledge sharing, learning communication skills and changing organizational culture. Learning organization can be, in turn, positively developed by project based team through action learning program for creating competitive advantage, Also, this study offers further support for the practical perspective on learning organization performance. The evidence from this case study suggests that the project team in action learning program playa significant role in team performance and the development of learning organization of the firm. Therefore, in the future, Web-based SMEs should consider making investments in action learning program that encourage project team's effective management in decision making, knowledge sharing, and organizational learning.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.4
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• pp.406-411
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• 2005

In this paper, we present the area-based Q-learning to search a target object using multiple robot. To search the target in Markovian space, the robots should recognize their surrounding at where they are located and generate some rules to act upon by themselves. Under area-based Q-learning, a robot, first of all, obtains 6-distances from itself to environment by infrared sensor which are hexagonally allocated around itself. Second, it calculates 6-areas with those distances then take an action, i.e., turn and move toward where the widest space will be guaranteed. After the action is taken, the value of Q will be updated by relative formula at the state. We set up an experimental environment with five small mobile robots, obstacles, and a target object, and tried to search for a target object while navigating in a unknown hallway where some obstacles were placed. In the end of this paper, we presents the results of three algorithms - a random search, area-based action making (ABAM), and hexagonal area-based Q-teaming.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.12
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• pp.1657-1664
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• 2018

This paper proposes a decision making scheme for choosing the best move at each state of game in order to implement an artificial intelligence othello game player. The proposed decision making scheme predicts the various possible states of the game when the game has progressed from the current state, evaluates the degree of possibility of winning or losing the game at the states, and searches the best move based on the evaluation. In this paper, we generate learning data by decomposing the records of professional players' real game into states, matching and accumulating winning points to the states, and using the Artificial Neural Network that learned them, we evaluated the value of each predicted state and applied the Minimax search to determine the best move. We implemented an artificial intelligence player of the Othello game by applying the proposed scheme and evaluated the performance of the game player through games with three different artificial intelligence players.

• Journal of Digital Convergence
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• v.19 no.12
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• pp.587-595
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• 2021

This study investigates the relationships among empathy, career decision-making self-efficacy and learning flow of nursing students in non-face-to-face classes caused by a Pandemics. The subjects were 165 nursing students, analyzed the collected data using SPSS WIN 21.0. According to the study, empathy, career decision-making self-efficacy, and learning flow were a significant static correlation. The variables that significantly affect learning flow are major satisfaction and career decision-making self-efficacy, and explanatory ability is 22.7%. Based on this results, it is proposed to prepare a plan to advance major satisfaction and career decision-making self-efficacy in a non-face-to-face classes.

• Journal of the Korean Chemical Society
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• v.65 no.3
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• pp.219-229
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• 2021

In this study, the new electrochemical cell device using Arduino and sensor was developed, and experiments of changes in voltage at the time of serial and parallel connection of electrochemical cells were conducted to verify the effectiveness of the device. In addition, in order to examine the educational effects of the device, student's inquiry activities of measuring voltage of electrochemical cells and making objects using the voltage difference were conducted. As a result, it was confirmed that the electrochemical device using Arduino and sensor could not only perform automatic measurements and visualize data but also have a possibility to seek various educational effects through easy coding and modification of the device. Based on the results of students' performance, it was found that experimental activities using the device impart a positive effect not only on the understanding of scientific concepts, but also on the development of the practical ability to apply scientific knowledges to the real life. Educational implications are discussed in terms of 'learning by making'.