• Journal of Korea Society of Digital Industry and Information Management
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• v.18 no.1
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• pp.65-77
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• 2022

The purpose of this study is to develop a competency strengthen program with the aim of training designers who respond to changing national policies in the era of artificial intelligence. To this end, this study was conducted through a total of five steps. First, through literature research and analysis of prior research and literature related to the role of training designers and HRD managers was investigated and analyzed, and based on related prior research, theoretical and academic grounds for training designer competency modeling were prepared. In the second stage, a draft training program was developed to strengthen the competency of training designers based on the needs analysis of stakeholders and advice from education experts. In the third stage, a pilot program was conducted based on the draft training program. In step 4, the effectiveness verification was confuted and the deficiencies of the training program were derived from the pilot program. Finally, the final draft of the training program for strengthening the competency of training designers in the era of artificial intelligence was developed. The final training program consisted of 10 modules and was designed to run for three days. The details of specific training program are presented in the article.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.6
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• pp.1317-1328
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• 2009

As a study on how the Neurofeedback training effects on young children's brain function and intelligence, first, this paper aims to verity the effect Neurofeedback training brings to the function of young children's brain. Second, through K-WPPSI IQ test, analyses how Neurofeedback training influences on the development of young children's intelligence. The subjects of this study were the 60 five-year children attenging J kindergarten in Cheon-an, experimnet treatment was performed according to Neurofeedback training guidance from Aprile 21 to December 12, 2008. It analyzes the states of brain waves before and after the Neurofeedback training, and performed the statistical analysis through t-test, using SPSS for Window(V.13.0) package. As a result of analysis, it was shown that firstly Neurofeedback training was very effective on the d!evelopment of infan's brain intelligence, since the quotient to evaluate the entire brain function appeared to have a meaningful influence. Secondly, it was proved that Neurofeedback training had much influence on the object assembly-area, the maze-area, and picture completion-area, and that it had the same influence on the performance intelligence quotient too. So, such results as these one make us realize that Neurofeedback training is a very effective method to the development of performance intelligence quotient. Thirdly, they indicate that Neurofeedback training hasn't a meaningful influence on verbal intelligence quotient, since it affects only on the similarities area among verbal intelligence quotient, the total evaluative quotient.

• Journal of East-West Nursing Research
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• v.19 no.1
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• pp.15-22
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• 2013

Purpose: The purpose of this study is to identify the effects of the interpersonal relationship training program based on emotional intelligence on interpersonal relationship, emotional intelligence, and self-esteem of nursing students. Methods: The study adopted a quasi-experimental study with a nonequivalent control group pre-post test. Total participants were 89 nursing students of S and K Universities. They were divided into the control (39 students) and experimental group (50 students). Participants went through the emotional intelligence program 100min which consisted of 100 minutes per session, once a week for total of 8 session from March 3th to April 21th, 2011. The contents were composed with interpersonal relationship training program to promote positive formation of emotional intelligence, interpersonal relationship, and self-esteem. All data were analyzed by SPSS 18.0 program. Results: The experimental group showed a significant increase of emotional intelligence (t=-3.17, p=.002) and interpersonal relationship (t=-3.07, p=.003). Conclusion: The interpersonal relationship training program based on emotional intelligence was effective in improving emotional intelligence and interpersonal relationship.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.577-582
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• 2020

The performance of a teacher has an important role in the success of education in general. This study aims to determine the factors that affect the decline in teacher performance in one of the junior secondary schools in Indonesia. Based on the literature review, four exogenous variables were identified, namely, training, utilization of information technology, intellectual intelligence, and emotional intelligence. This study uses primary data, collected from a questionnaire distributed to respondents. The questionnaire items are measured using a Likert scale. The sample in this study were all teachers at MTS Darul Falah Sirahan, totaling 32 people. The analysis technique used in testing the hypothesis of this study is multiple regression analysis. Statistical product and service solutions are used as analysis tools. The results of this study indicate that only the variable 'utilization of information technology' has a positive and significant effect. However, the variables 'training,' 'intellectual intelligence,' and 'emotional intelligence' did not have a significant effect. This finding contradicts the literature in general. Therefore, this study recommends improving training methods, both those carried out internally by schools and by related agencies, and schools still need to optimize guidance and potential for teacher's intelligence in improving performance.

• The Journal of Korea Robotics Society
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• v.14 no.2
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• pp.122-130
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• 2019

Collecting a rich but meaningful training data plays a key role in machine learning and deep learning researches for a self-driving vehicle. This paper introduces a detailed overview of existing open-source simulators which could be used for training self-driving vehicles. After reviewing the simulators, we propose a new effective approach to make a synthetic autonomous vehicle simulation platform suitable for learning and training artificial intelligence algorithms. Specially, we develop a synthetic simulator with various realistic situations and weather conditions which make the autonomous shuttle to learn more realistic situations and handle some unexpected events. The virtual environment is the mimics of the activity of a genuine shuttle vehicle on a physical world. Instead of doing the whole experiment of training in the real physical world, scenarios in 3D virtual worlds are made to calculate the parameters and training the model. From the simulator, the user can obtain data for the various situation and utilize it for the training purpose. Flexible options are available to choose sensors, monitor the output and implement any autonomous driving algorithm. Finally, we verify the effectiveness of the developed simulator by implementing an end-to-end CNN algorithm for training a self-driving shuttle.

• Environmental Engineering Research
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• v.14 no.2
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• pp.102-110
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• 2009

Application of artificial intelligence (AI) approaches in eco-environmental modeling has gradually increased for the last decade. Comprehensive understanding and evaluation on the applicability of this approach to eco-environmental modeling are needed. In this study, we reviewed the previous studies that used AI-techniques in eco-environmental modeling. Decision Tree (DT) and Artificial Neural Network (ANN) were found to be major AI algorithms preferred by researchers in ecological and environmental modeling areas. When the effect of the size of training data on model prediction accuracy was explored using the data from the previous studies, the prediction accuracy and the size of training data showed nonlinear correlation, which was best-described by hyperbolic saturation function among the tested nonlinear functions including power and logarithmic functions. The hyperbolic saturation equations were proposed to be used as a guideline for optimizing the size of training data set, which is critically important in designing the field experiments required for training AI-based eco-environmental modeling.

• Asia Marketing Journal
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• v.19 no.3
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• pp.75-98
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• 2017

Our study is trying to investigate the perceived training effectiveness by applying the theory of planned behavior (TPB) and Technological Acceptance Model (TAM) and intend to examine the effects of individual differences on perceived training effectiveness and performance of individuals. The main purpose is to evaluate the perceived training effectiveness, and role of individual differences in terms of learning. The results of this study supported all the hypothesis that participants with higher level of creative self-efficacy, intrinsic motivation, creativity and emotional intelligence (EI) will have greater inclinations to learn. Results showed that perceive training effectiveness is positively related to training transfer and training transfer increase the performance of individuals. Study results significantly agree with the theory of planned behavior (TPB) which was applied to measure the perceived training effectiveness and suggest trainee's perception of usefulness, ease and benefits enhance learning dimensions of participants that make any program effective. The study has highlighted a number of issues that influence the perceived training effectiveness.

• Korean Journal of Applied Biomechanics
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• v.32 no.3
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• pp.69-79
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• 2022

Objective: The purpose of this study is to analyze trends related to sports and artificial intelligence (AI) to understand the trends and how they change according to time, and to establish methods to apply AI in sports. Both macro and micro perspectives related to sports utilization of AI were analyzed. Method: In this study, after analyzing and discussing various information related to the use of artificial intelligence in the sports through a search of academic journals, papers, books, and websites published recently at nationally and internationally, the application plan of artificial intelligence in the sports field was presented. Results: 1) Motion analysis technology using artificial intelligence is effective in sports where posture is important, and if it provides systematic feedback and training methods, it can help improve performance. 2) The introduction of a sports referee judgment system using artificial intelligence is expected to improve performance by restoring factual judgment and objective fairness in sports games. 3) Artificial intelligence will provide coaching staff and players with a variety of information to help improve performance through systematic coaching and improving feedback and enhanced training methods. 4) It is judged that artificial intelligence-related to sports ethics, sports ICT, sports marketing, sports prediction, etc. We think that based on the current AI research trends will have a positive impact on all sports-related areas, helping to revitalize sports. Conclusion: Motion analysis technology using artificial intelligence, sports referee judgment system, coaching using artificial intelligence, and artificial intelligence are judged to have a positive effect on all sports-related areas and help revitalize sports.

• Journal of Practical Engineering Education
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• v.12 no.2
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• pp.339-351
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• 2020

In response to changes in Fourth Industrial Revolution in recent years, the field of education has focused on development of the human resources in the areas of artificial intelligence (AI: Artificial Intelligence) and industrial robot. Due to particular interest in these areas, the importance of developing integrated human resources equipped with artificial intelligence technology is emphasized in higher education and vocational competence development. In regards to rapid changing environment, this study created a program "Fostering personalized AI integrated human resource" and established an operational model correspond to latest personalized education trend. The established operational model was conducted twice using Delphi survey with experts in AI and innovative education in order to verify the suitability of program's basic structure, training process, and the sub-components of the operational strategy. The final training model was applied to the online vocational training platform (STEP) and a plan was proposed to establish a personalized training model to foster an AI integrated competent individual.

• Electronics and Telecommunications Trends
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• v.38 no.6
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• pp.84-94
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• 2023

Open source has many advantages and is widely used in various fields. However, legal disputes regarding copyright and licensing of datasets and learning models have recently arisen in artificial intelligence developments. We examine how datasets affect artificial intelligence learning and services from the perspective of copyrighting and licensing when datasets are used for training models. The licensing conditions of datasets can lead to copyright infringement and license violation, thus determining the scope of disclosure and commercialization of the trained model. In addition, we examine related legal issues.