• ETRI Journal
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• 제35권6호
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• pp.1058-1067
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• 2013

An approach for game bot detection in massively multiplayer online role-playing games (MMORPGs) based on the analysis of game playing behavior is proposed. Since MMORPGs are large-scale games, users can play in various ways. This variety in playing behavior makes it hard to detect game bots based on play behaviors. To cope with this problem, the proposed approach observes game playing behaviors of users and groups them by their behavioral similarities. Then, it develops a local bot detection model for each player group. Since the locally optimized models can more accurately detect game bots within each player group, the combination of those models brings about overall improvement. Behavioral features are selected and developed to accurately detect game bots with the low resolution data, considering common aspects of MMORPG playing. Through the experiment with the real data from a game currently in service, it is shown that the proposed local model approach yields more accurate results.

• 한국정보교육학회:학술대회논문집
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• 한국정보교육학회 2021년도 학술논문집
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• pp.175-179
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• 2021

언플러그드 활동은 프로그래밍 프로그램 이외의 학습 도구를 통하여 컴퓨터 과학에 대하여 학습하는 활동들이다. 기존의 언플러그드 활동은 절차적인 사고 과정에 초점을 맞추고, 놀이를 통해 사고 과정을 지도하는 것에 초점을 두어, 최근 주목되는 머신 러닝에서 중요한 비중을 차지하는 비지도 학습에 대한 연구는 부족한 실정이다. 본 연구에서는 초등학생들에게 익숙한 영상 매체를 사용하여 데이터를 분석하는 비지도 학습을 위한 언플러그드 수업을 설계하고, 수업을 실시한 후에 비버챌린지를 활용하여 수업의 효과성에 대한 결과를 분석하였다. 사전 검사와 사후 검사의 점수를 분석한 결과 학생들의 computational thinking 과 문제 해결력이 향상되었음을 확인할 수 있었다.

• Journal of Information Processing Systems
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• 제15권4호
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• pp.833-852
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• 2019

In real time applications, due to their effective cost and small size, wireless networks play an important role in receiving particular data and transmitting it to a base station for analysis, a process that can be easily deployed. Due to various internal and external factors, networks can change dynamically, which impacts the localisation of nodes, delays, routing mechanisms, geographical coverage, cross-layer design, the quality of links, fault detection, and quality of service, among others. Conventional methods were programmed, for static networks which made it difficult for networks to respond dynamically. Here, machine learning strategies can be applied for dynamic networks effecting self-learning and developing tools to react quickly and efficiently, with less human intervention and reprogramming. In this paper, we present a wireless networks survey based on different machine learning algorithms and network lifetime parameters, and include the advantages and drawbacks of such a system. Furthermore, we present learning algorithms and techniques for congestion, synchronisation, energy harvesting, and for scheduling mobile sinks. Finally, we present a statistical evaluation of the survey, the motive for choosing specific techniques to deal with wireless network problems, and a brief discussion on the challenges inherent in this area of research.

• Nuclear Engineering and Technology
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• 제52권7호
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• pp.1436-1442
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• 2020

Nuclear infrastructure systems play an important role in national security. The functions and missions of nuclear infrastructure systems are vital to government, businesses, society and citizen's lives. It is crucial to design nuclear infrastructure for scalability, reliability and robustness. To do this, we can use machine learning, which is a state of the art technology used in various fields ranging from voice recognition, Internet of Things (IoT) device management and autonomous vehicles. In this paper, we propose to design and develop a machine learning algorithm to perform predictive maintenance of nuclear infrastructure. Support vector machine and logistic regression algorithms will be used to perform the prediction. These machine learning techniques have been used to explore and compare rare events that could occur in nuclear infrastructure. As per our literature review, support vector machines provide better performance metrics. In this paper, we have performed parameter optimization for both algorithms mentioned. Existing research has been done in conditions with a great volume of data, but this paper presents a novel approach to correlate nuclear infrastructure data samples where the density of probability is very low. This paper also identifies the respective motivations and distinguishes between benefits and drawbacks of the selected machine learning algorithms.

• 한국엔터테인먼트산업학회논문지
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• 제13권7호
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• pp.409-417
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• 2019

최근 영어 조기교육의 중요성이 증대되면서 미취학 아동들을 위한 많은 교육기관들에서 영어교육이 점차 활성화되고 있다. 특히 역할연기(Role-play)는 미취학 아동들의 언어에 대한 관심을 증진시키고 자연스럽게 영어권 문화를 접할 수 있어 아동들의 영어학습에서 효과적인 것으로 알려져 있다. 이에 따라 본 논문에서는 미취학 아동들을 대상으로 영어교육을 위한 역할연기에서 UCC의 효과적인 활용방법을 알아보도록 하였다. 먼저 연구를 위해 미취학 아동들에 대하여 사전, 사후 검사를 위한 설문을 진행하였다. 그리고 이를 SPSS로 분석하여 아동들의 UCC에 대한 이해, 영어에 대한 흥미, 역할연기에 대한 흥미, 연기에 대한 관심 등 알아보았다. 분석 결과, 대부분의 아동들은 UCC를 잘 알고 있었으며 시청이나 제작에 관한 흥미도 강함을 알 수 있었다. 제작된 콘텐츠 시청과 교사의 피드백을 통해 더 발전된 영어와 연기를 보이고 싶어 하였다. 따라서 미취학 아동의 영어교육에서도 교사의 통제하에 역할연기를 통해 UCC를 제작하고 활용하는 것으로써 언어와 연기의 발전을 보일 수 있으며 유튜브 등을 통해 콘텐츠를 배포함으로써 이에 대한 흥미를 더욱 높일 수 있을 것으로 사료된다. 이러한 연구의 결과는 어린이집이나 유치원에서 역할연기를 통한 영어 교육을 계획할 때 효과적으로 활용될 수 있을 것으로 기대한다.

• 지역사회간호학회지
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• 제27권1호
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• pp.9-20
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• 2016

Purpose: The purpose of this study was to survey the current status of mental health education and need for mental health education enhancing protective factors in the elementary schools. Methods: We surveyed 10 school health teachers and 328 fifth- and sixth-grade students using 19- and 20-item questionnaires, respectively. Results: All of the teachers and 65.2% of the students replied that they were either teaching or being taught mental health in school. Topics covered suicide, depression, school violence, and Internet addiction. All of the teachers and 84.1% of the students expressed the need for mental health education enhancing protective factors in school. Both groups replied that two sessions are enough. The teachers preferred role play and discussion as teaching methods, and audiovisual materials and computer as instructional media. The students preferred lecture and role play as teaching methods, and audiovisual materials and smartphone as instructional media. Both groups ranked self-esteem, parent-child relationship, peer relationship, and emotional regulation as the most important topics to be covered in the education. Conclusion: There is a high demand for mental health education enhancing protective factors. Therefore, it is recommended to develop educational programs enhancing protective factors by enabling formal and informal learning using smartphone.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권6호
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• pp.1462-1477
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• 2024

With the evolving complexity of connected vehicle features, the volume and diversity of data generated during driving continue to escalate. Enabling data sharing among interconnected vehicles holds promise for improving users' driving experiences and alleviating traffic congestion. Yet, the unintentional disclosure of users' private information through data sharing poses a risk, potentially compromising the interests of vehicle users and, in certain cases, endangering driving safety. Federated learning (FL) is a newly emerged distributed machine learning paradigm, which is expected to play a prominent role for privacy-preserving learning in autonomous vehicles. While FL holds significant potential to enhance the architecture of the Internet of Vehicles (IoV), the dynamic mobility of vehicles poses a considerable challenge to integrating FL with vehicular networks. In this paper, a novel clustered FL framework is proposed which is efficient for reducing communication and protecting data privacy. By assessing the similarity among feature vectors, vehicles are categorized into distinct clusters. An optimal vehicle is elected as the cluster head, which enhances the efficiency of personalized data processing and model training while reducing communication overhead. Simultaneously, the Local Differential Privacy (LDP) mechanism is incorporated during local training to safeguard vehicle privacy. The simulation results obtained from the 20newsgroups dataset and the MNIST dataset validate the effectiveness of the proposed scheme, indicating that the proposed scheme can ensure data privacy effectively while reducing communication overhead.

• 유통과학연구
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• 제14권5호
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• pp.5-16
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• 2016

Purpose - This study was to empirically validate the mediating roles of psychological ownership and learning goal orientation in the relationships of managerial coaching behaviors and organizational citizenship behaviors/creative behaviors of employees. Research design, data, and methodology - A total of 270 employees in the Korean distribution industry were surveyed on-line, and the results were analyzed using confirmatory factor analysis and structural equational modeling. Results - The study confirmed prior research results that managerial coaching behaviors were related positively to employees' psychological ownership and learning goal orientation, both of which were associated positively with their organizational citizenship behaviors and creative behaviors respectively. It revealed the complete mediating effect of psychological ownership between managerial coaching and organizational citizenship behaviors and that of learning goal orientation between managerial coaching and creative behaviors. Conclusions - Psychological ownership was found to play an important role in the relationship between managerial coaching behaviors and organizational citizenship behaviors. It gives some practical implication regarding the higher turn-over intention rate of the distribution industry, in that promoting psychological ownership through managerial coaching behaviors could reduce the turn-over intention rate.

• 실천공학교육논문지
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• 제15권1호
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• pp.223-232
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• 2023

일학습병행은 산업현장과 학교 교육의 미스매치를 해소하고 능력중심 사회를 구현하기 위한 핵심적인 정책으로 추진되어 2022년 12월 기준으로 16,664개 기업이 훈련에 참여하였다. 학습기업은 현장훈련을 실시하는 교육훈련 공급기관으로써 매우 중요한 역할을 수행하고 있다. 본 연구에서는 일학습병행에 참여하고 있는 학습기업의 평가를 위해 해당기업을 담당하고 있는 전문가들의 인지구조 분석을 통해 기업현장 교육훈련의 질을 결정하는 중요 요인을 도출하고 학습기업의 평가지표를 제시하여 일학습병행의 질적 내실화를 도모하는 기초 자료로 활용될 것이다.

• Journal of Audiology & Otology
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• 제23권3호
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• pp.121-128
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• 2019

Background and Objectives: There is a scant evidence on the use of simulations in audiology (especially in Malaysia) for case-history taking, although this technique is widely used for training medical and nursing students. Feedback is one of the important components in simulations training; however, it is unknown if feedback by instructors could influence the simulated patient (SP) training outcome for case-history taking among audiology students. Aim of the present study is to determine whether the SP training with feedback in addition to the standard role-play and seminar training is an effective learning tool for audiology case-history taking. Subjects and Methods: Twenty-six second-year undergraduate audiology students participated. A cross-over study design was used. All students initially attended two hours of seminar and role-play sessions. They were then divided into three types of training, 1) SP training (Group A), 2) SP with feedback (Group B), and 3) a non-additional training group (Group C). After two training sessions, the students changed their types of training to, 1) Group A and C: SP training with feedback, and 2) Group B: non-additional training. All the groups were assessed at three points: 1) pre-test, 2) intermediate, and 3) post-test. The normalized median score differences between and within the respective groups were analysed using non-parametric tests at 95% confidence intervals. Results: Groups with additional SP trainings (with and without feedback) showed a significantly higher normalized gain score than no training group (p<0.05). Conclusions: The SP training (with/without feedback) is a beneficial learning tool for history taking to students in audiology major.