• Journal of Radiation Protection and Research
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• v.38 no.1
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• pp.10-21
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• 2013

Action Learning is a teaching-learning method to solve a problem through which members in a team discuss the problem and a facilitator supports the members in the team. The Action Learning makes learners develop human-relationship skills, which are connected to the value of social capital in the modern society. The purpose of this study is to clarify the relationship between action learning and social capital with 17 participants who joined in a nuclear education course opened in the Korea Atomic Energy Research Institute. The result showed that the action learning positively influenced the social capital among members in the team. Consequently, it is easily recognized that action learning is one of positive teaching-learning methods to achieve educational purposes of a organization and should be more developed in the future.

• Education of Primary School Mathematics
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• v.20 no.2
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• pp.143-151
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• 2017

An increasing number of students are giving up on learning mathematics at all grade levels, including elementary school. The study in this paper considers seven non-cognitive student characteristics to identify which are strongly correlated with giving up on mathematics at the elementary school level. Data were collected with a survey on the non-cognitive domain of mathematics learning that was developed by the Korea Foundation for the Advancement of Science and Creativity in 2015. The data were collected from 3,636 elementary school students in Korea, and we analyzed the data using the statistical computing program R. Of the seven components, efficacy and interest have a strong correlation with students' tendency to profess that they have given up trying to learn mathematics. The findings of the study shed light on which non-cognitive domain areas mathematics teachers need to pay more attention to in order to make their teaching effective. This study further investigated the correlation between responses to each of the 24 survey items and students' claim that they have given up on mathematics. Using the 8 items with the highest correlations, we have developed a shorter, 8-item version of the survey, which will be useful for similar future studies.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.6
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• pp.715-721
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• 2012

A threat evaluation is the technique which decides order of priority about tracks engaging with enemy by recognizing battlefield situation and making it efficient decision making. That is, in battle situation of multiple target it makes expeditious decision making and then aims at minimizing asset's damage and maximizing attack to targets. Threat value computation used in threat evaluation is calculated by sensor data which generated in battle space. Because Battle situation is unpredictable and there are various possibilities generating potential events, the damage or loss of data can make confuse decision making. Therefore, in this paper we suggest that substantial threat value calculation using learning bayesian network which makes it adapt to the varying battle situation to gain reliable results under given incomplete data and then verify this system's performance.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.6
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• pp.1123-1130
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• 2020

This study aims to classify the severity in car crashes using five classification learning models. The dataset used in this study contains 21,013 vehicle crashes, obtained from Korea Expressway Corporation, between the year of 2015-2017 and the LightGBM(Light Gradient Boosting Model) performed well with the highest accuracy. LightGBM, the number of involved vehicles, type of accident, incident location, incident lane type, types of accidents, types of vehicles involved in accidents were shown as priority factors. Based on the results of this model, the establishment of a management strategy for response of highway traffic accident should be presented through a consistent prediction process of accident severity level. This study identifies applicability of Machine Learning Models for Predicting of the Severity of Car Traffic Accidents on a Highway and suggests that various machine learning techniques based on big data that can be used in the future.

• Journal of vocational education research
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• v.37 no.3
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• pp.85-111
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• 2018

The purpose of this study is to derive the competence of nursing teacher in Specialized vocational high school. The knowledge, skills, and attitudes required for the nursing teachers were verified and the competency groups and sub-competencies were verified and priorities were suggested. To do this, 23 nursing teachers who were currently working in the Specialized vocational high school were selected as expert panels and the study was conducted using Delphi and Layered Analysis(AHP) technique. The results of this study were as follows. First, the competency group of the nursing teacher in Specialized vocational high school showed teaching and learning methods & techniques, student guidance, curriculum development and operation, school management support, industry-academy cooperation, self-development and professionalism improvement. The total number was 6. Second, the sub-competency is composed of knowledge and skills related to the curriculum, planning and preparation of instruction, instruction operation, guidance of experiment and practice, instruction evaluation, development and utilization of teaching and learning medium, instruction environment, guidance on student education activities outside the curriculum, career guidance, life guidance, class management, guidance of technology and qualification, development of school curriculum, organization and operation of school curriculum, planning and operation of field practice, work planning, school management support, teacher evaluation and personnel management support, leaning support(practice place and equipment), establishment and operation of industry-academia cooperation, strengthening community cooperation, public relations in the school(department), field research for improvement of educational activities, participation in conferences and training, exploration of new knowledge and technology, The total number was 26. The most important of the relative importance was the curriculum development and operation. The subordinate competencies that have a high priority in each competency group were guidance of experiment and practice, guidance of technology and qualification, planning and operation of field practice, leaning support(practice place and equipment), management and work planning, establishment and operation of industry-academia cooperation, exploration of new knowledge and technology. The competency system derived from this study will be applied to the training and evaluation of nursing teachers in the future and can be used as basic data for related research.

• Journal of Engineering Education Research
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• v.13 no.1
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• pp.23-37
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• 2010

The purpose of this study is to explore applicability of teaching-learning methods for creative problem solving which was designed to improve students' creative thinking and problem solving competencies. Methodology is literature review and focus group interview. The students who attended the elective course 'creative women and science' was participated during 15 weeks. Through this teaching-learning methods, students were fully aware of learning methods for creative problem solving, sought for problems, clarified problems, found solutions through discussions, and continuously examined ideas by receiving feedbacks. They could deduce creative new solutions to solve encountered problems regarding team dynamics and apply it in real situation. As the results of applying teaching-learning methods for creative problem solving to a course in University, it had the advantages of enhancing students' competencies in analyzing problems and applying derived solutions in actual field.

• Journal of Satellite, Information and Communications
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• v.10 no.4
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• pp.113-116
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• 2015

The electric utility has the responsibility of reducing the impact of peaks on electricity demand and related costs. Therefore, they have introduced Direct Load Control System (DLCS) to automate the external control of shedding customer load that it controls. The existing DLCS have been operated only depend on On/Off signal from the electric utility. That kind of DLCS operating has been successfully used until now. But since the number of customer load participating in the DLC program are keep increasing, On/Off signal control from the electric utility is no longer meets the needs of many different kind of customers. Therefore, In this paper, the author suggest the design of direct load control system using weather sensors to meet the diversity of different customer needs.

• Proceedings of the Korea Contents Association Conference
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• 2008.05a
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• pp.343-347
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• 2008

There are two kind of system in hotel for evaluating management. the first is infra system, for example Front management system - reservation system, C/I, C/O system, POS system , web system, call center management -, Back office system, interface system, and so on which manage direct control for hotel, and next is strategic system, for example BSC , CS . which is supporting hotel management. The purpose of this study was to find using the Balanced Scorecard to evaluate hotel management perfomance. Management performance is based on productivity, quality, time, effect, and responsiveness. Hotel economic value is not equal visual asset which is measured financial value. It is include hotel brand, image, customers who have good loyalty, employees who give customers special service, and systems which was affected by internal process. In conclusion, innovation, growth, internal system process, empioyee and customer have effect hotel performance. Therefore hotel has to know non-financial performance which has positively relate to financial performance.

• Journal of Digital Convergence
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• v.10 no.6
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• pp.141-152
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• 2012

This study is a comparatively analyzes innovation tools for developing appropriate business models according to the types of convergence. Firstly, it examines previous studies on the type of convergence, business models, and innovation tools. Based on the understanding of each topic through literature search, it introduces Convergence-Business-Innovation Tools Cube (CBI Cube) model with the concept of developing innovative business models by applying innovation tools under the condition of convergence. In order to quantify (concretize) the concept, we have compared the relative priority of innovation tools for developing business models to find component factors of CBI Cube model through the survey of an expert group by adopting DelPhi method and AHP method. From the result of this study, we expect to be able to make an easier approach to the development of innovative products, services and market as it allo ws to develop business models of value innovation beyond just benchmarking or simple imitation of existing business models.

• Korean Chemical Engineering Research
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• v.61 no.4
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• pp.542-549
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• 2023

Since the growing interest in surrogate modeling, there has been continuous research aimed at simulating nonlinear chemical processes using data-driven machine learning. However, the opaque nature of machine learning models, which limits their interpretability, poses a challenge for their practical application in industry. Therefore, this study aims to analyze chemical processes using Explainable Artificial Intelligence (XAI), a concept that improves interpretability while ensuring model accuracy. While conventional sensitivity analysis of chemical processes has been limited to calculating and ranking the sensitivity indices of variables, we propose a methodology that utilizes XAI to not only perform global and local sensitivity analysis, but also examine the interactions among variables to gain physical insights from the data. For the ammonia synthesis process, which is the target process of the case study, we set the temperature of the preheater leading to the first reactor and the split ratio of the cold shot to the three reactors as process variables. By integrating Matlab and Aspen Plus, we obtained data on ammonia production and the maximum temperatures of the three reactors while systematically varying the process variables. We then trained tree-based models and performed sensitivity analysis using the SHAP technique, one of the XAI methods, on the most accurate model. The global sensitivity analysis showed that the preheater temperature had the greatest effect, and the local sensitivity analysis provided insights for defining the ranges of process variables to improve productivity and prevent overheating. By constructing alternative models for chemical processes and using XAI for sensitivity analysis, this work contributes to providing both quantitative and qualitative feedback for process optimization.