• International journal of advanced smart convergence
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• 제11권4호
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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.

• 한국가정과교육학회지
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• 제10권1호
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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.

• 한국가정과교육학회지
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• 제24권3호
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• pp.101-122
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• 2012

본 연구는 중학교 1학년 가정과 '옷차림과 자기표현' 단원에 적용할 책만들기를 활용한 문제중심학습 교수 학습 과정안을 개발하고 적용한 후 수업의 효과를 알아보는데 목적을 두었다. 본 연구의 목적을 달성하기 위하여 책만들기를 활용한 문제중심학습 교수 학습 과정안, 학생자료 15개, 교사자료 9개를 개발하여 부산광역시 소재의 여자중학교 학생 167명을 대상으로 적용한 후 결과를 분석하였다. 본 수업이 학생들의 신체이미지에 대한 왜곡이나 불만족을 줄여줘 신체이미지를 긍정적으로 변화시킨 것으로 나타났다. 또한 외모에 대한 사회문화적 태도에 대해서는 사회적 영향을 덜 받는 것으로 바람직하게 변화되었다. 수업에 대한 학생들의 평가는 수업이 재미있고, 특별나고, 학습자료가 다양하며, 나의 신체에 대해 생각하는 계기가 되었다는 등으로 매우 긍정적이었으나 수업시간의 부족과 과제가 많았다고 하였다. 이상의 결과로 본 교수 학습과정안이 연구의 목적을 달성하는 데 적합한 모형임을 알 수 있었다. 앞으로 교수 학습 과정안의 타당성 검토와 수업시간의 확보를 통한 학습활동이 이루어지도록 하는 후속 연구를 통해 더욱 발전된 책만들기를 활용한 문제중심 학습 교수 학습 과정안이 개발되기를 기대한다.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2006년도 Asia Navigation Conference
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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.

• 기본간호학회지
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• 제22권3호
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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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• 제16권3호
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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.

• 한국지능시스템학회논문지
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• 제15권4호
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• pp.406-411
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• 2005

본 논문에서는 다수 로봇의 목표물 탐색을 위한 area-based Q-learning 알고리즘에 대해 논한다. 선험적 정보가 없는 공간내의 목표물을 탐색하기 위해, 로봇들은 주위의 환경을 인식하고 스스로 다음 행동에 대한 결정을 내릴 수 있어야 한다. Area-based Q-learning에서, 먼저 각 로봇은 정육각형을 이루도록 배치된 6개의 적외선 센서를 통해 자신과 주변 환경 사이의 거리를 구한다. 다음으로 이 거리데이터들로부터 6방향의 면적(area)을 계산하여, 보다 넓은 행동반경을 보장해주는 영역으로 이동(action)한다. 이동 후 다시 6방향의 면적을 계산, 이전 상태에서의 이동에 대한 Q-value를 업데이트 한다. 본 논문의 실험에서는 5대의 로봇을 이용하여 선험적 지식이 없고, 장애물이 놓여 있는 공간에서의 목표물 탐색을 시도하였다. 결론에서는 3개의 제어 알고리즘-랜덤 탐색, area-based action making (ABAM), hexagonal area-based Q-learning - 을 이용하여 목표물 탐색을 시도한 결과를 보인다.

• 전기학회논문지
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• 제67권12호
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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.

• 디지털융복합연구
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• 제19권12호
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• pp.587-595
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• 2021

본 연구는 팬데믹으로 인한 비대면 수업환경에서 간호대학생의 공감능력과 진로결정 자기효능감이 학습몰입에 미치는 영향을 파악하고자 시도된 서술적 조사연구이다. 연구 대상자는 간호대학생 165명이며, 2021년 5월 10일부터 6월 30일까지 설문조사하였고, 수집된 자료는 SPSS WIN 21.0을 이용하여 분석하였다. 연구 결과 공감능력과 진로결정 자기효능감, 공감능력과 학습몰입, 진로결정 자기효능감과 학습몰입은 유의한 정적 상관관계가 있었으며, 학습몰입에 유의한 영향을 미치는 변수는 전공만족도와 진로결정 자기효능감으로 설명력은 22.7 %이다. 이상의 결과를 바탕으로 비대면 수업환경에서의 전공만족도와 진로결정 자기효능감 향상을 위한 방안마련이 필요하며 이를 위한 추가적인 연구를 제언한다.

• 대한화학회지
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• 제65권3호
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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'.