• Journal of Nutrition and Health
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• v.35 no.8
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• pp.886-895
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• 2002

Introduction and application of virtual education has been rapidly increased in these days. A variation of information communication technology has an effect on education in interconnect with network as internet in the world that exceed the limit of time and regional. Computer and network communication technology through the medium of internet make an entrance cyber education as a new education paradigm. It must be affective on learner who have various educational characteristics and requirements. It begins to appear quality, quantity improvements of knowledge and the development of information technology that web based cyber education. This study was conducted to develop the web based education program and to evaluate the effectiveness of learning satisfaction and accomplishment and to compare the cyber lecture system with the traditional lecture system During the second semester of 2001, this study was investigated 317 registered students in a "Food and Culture" class at Kyungwon University. The data were obtained from pre and post-study with self-administered questionnaire. The evaluation and satisfaction score of students who were registered in cyberclass was negative tendency to compare pre with post-test scores, because of insuffciency of computer-aided lecture system. The major problem was inconvenient in checking system for connecting times in cyberclass which was one of evaluation point in final score. Another problem was frequently disconnection during cyber studying and not to concentrate each time in the cyber lecture because of eye fatigue, boring due to less interesting contents than other newly developed web-site. The students was prefer to mix type of the cyber and traditional lecture type class. The result of final score an each class, the score of cyber class (71.36 $\pm$ 22.44) was significantly lower than other groups (mixed type : 76.66 $\pm$ 19.99, traditional type :79.17 $\pm$ 15.72) (p < 0.05). Cyber class was attempted to present a useful and interesting teaching and learning tool which can be applied successfully in a longer term. The result suggest that various teaching and learning strategies should be developed considering the fact that the student learn alone most in time.t in time.

• Proceedings of the Korea Information Processing Society Conference
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• 2004.05a
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• pp.637-640
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• 2004

e-Learning에 대한 관심이 높아지면서 e-Learning 표준화에 대한 다양한 연구들이 진행되어지고 있으며 ADL에서 주도하는 SCORM이 e-Learning의 실질적인 표준으로 자리잡고 있다. SCORM 메타데이터는 기존자료들에 대한 재사용성을 높이고 컨텐츠의 개발과 관리에 따른 시간과 비용의 감소를 가져온다. 기존의 E-Mail system에 메타데이터 생성기를 추가하여 E-Mail을 통해 전달받은 다양한 컨텐츠들을 재사용과 분류, 검색이 가능한 xml 파일로 바인딩 시키는 system을 제안하였다.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.170-178
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• 2024

Through the growth of the fifth-generation networks and artificial intelligence technologies, new threats and challenges have appeared to wireless communication system, especially in cybersecurity. And IoT networks are gradually attractive stages for introduction of DDoS attacks due to integral frailer security and resource-constrained nature of IoT devices. This paper emphases on detecting DDoS attack in wireless networks by categorizing inward network packets on the transport layer as either "abnormal" or "normal" using the integration of machine learning algorithms knowledge-based system. In this paper, deep learning algorithms and CNN were autonomously trained for mitigating DDoS attacks. This paper lays importance on misuse based DDOS attacks which comprise TCP SYN-Flood and ICMP flood. The researcher uses CICIDS2017 and NSL-KDD dataset in training and testing the algorithms (model) while the experimentation phase. accuracy score is used to measure the classification performance of the four algorithms. the results display that the 99.93 performance is recorded.

• Proceedings of the Korean Society of Computer Information Conference
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• 2018.07a
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• pp.23-24
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• 2018

스마트 팩토리의 핵심 요소 중 하나인 AGV를 운용하기 위해서 스케줄링은 간과할 수 없는 문제이다. 기존의 정적인 휴리스틱 방식은 실시간으로 운용되는 스마트 팩토리에 다소 부적합한 면이 있다. 본 논문에서는 이러한 스케줄링에 관한 문제를 해결하고자 SLAM 기반의 자율주행 AGV를 운용 할 수 있는 3D 가상 환경을 설계하고 해당 환경에서 강화학습을 기반으로 한 스케줄링을 구현해 실시간으로 변화하는 공장에 적합한 동적인 스케줄링을 설계하였다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.41-44
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• 2021

In this paper, we propose a monitoring system that can monitor gas leakage concentrations in real time and forecast the amount of gas leaked after one minute. When gas leaks happen, they typically lead to accidents such as poisoning, explosion, and fire, so a monitoring system is needed to reduce such occurrences. Previous research has mainly been focused on analyzing explosion characteristics based on gas types, or on warning systems that sound an alarm when a gas leak occurs in industrial areas. However, there are no studies on creating systems that utilize specific gas explosion characteristic analysis or empirical urban gas data. This research establishes a deep learning model that predicts the gas explosion risk level over time, based on the gas data collected in real time. In order to determine the relative risk level of a gas leak, the gas risk level was divided into five levels based on the lower explosion limit. The monitoring platform displays the current risk level, the predicted risk level, and the amount of gas leaked. It is expected that the development of this system will become a starting point for a monitoring system that can be deployed in urban areas.

• Journal of the Korea Society of Computer and Information
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• v.19 no.4
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• pp.101-109
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• 2014

This paper aims to design and implement a collaborative learning system based on the augmented reality. The existing augment reality-based learning systems have just focused on interactivity between a system and learners without consideration of cooperability, thereby leading to an ineffective approach to encouraging an learning system to be more supportive and conducive of and to cooperation among learners. The collaborative learning system is a learning method, with which learners achieve a common objective through critical thinking and cooperative teamwork so as to seek solutions to such fulfillment. This requires positive interdependence, proactive interactions, a sense of responsibility shared by individuals as well as the group, and development of teamwork among learners. Educators and systems assume a critical role in helping the collaborative education be effective. An educator is responsible for defining a project at the outset of learning activities, organizing groups for learners, and providing evaluation criteria applied to a group's project activities. Meanwhile, a system shall support interactions to take place while facilitating learning activities. Furthermore, an educator shall provide a system for managing and evaluating activities involving interactions among learners. This paper suggests and embodies a collaborative learning system based on the augmented reality with consideration of the aforementioned collaborative education.

• Journal of The Korean Association of Information Education
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• v.5 no.2
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• pp.216-229
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• 2001

A more interactive teaching-learning system is increasingly necessary in the consumer-oriented environment of distance education. This article would like to suggest a more spontaneous system which is learners at various levels. The suggested system keynotes its efficiency with the introduction of a "mobile agent" concept through which learners are able to network and complete their assignments despite their dispersed environments. This article also suggests some managerial techniques for the systematic management of agent-based learners possessing diverse characteristics. Through this study, we expect more highly effect by offer data adapted to learning goal to learner's ability, get out of uniform web-based teaching-learning.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2399-2413
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• 2021

A recommendation system is an information filter tool, which uses the ratings and reviews of users to generate a personalized recommendation service for users. However, the cold-start problem of users and items is still a major research hotspot on service recommendations. To address this challenge, this paper proposes a high-efficient hybrid recommendation system based on Fuzzy C-Means (FCM) clustering and supervised learning models. The proposed recommendation method includes two aspects: on the one hand, FCM clustering technique has been applied to the item-based collaborative filtering framework to solve the cold start problem; on the other hand, the content information is integrated into the collaborative filtering. The algorithm constructs the user and item membership degree feature vector, and adopts the data representation form of the scoring matrix to the supervised learning algorithm, as well as by combining the subjective membership degree feature vector and the objective membership degree feature vector in a linear combination, the prediction accuracy is significantly improved on the public datasets with different sparsity. The efficiency of the proposed system is illustrated by conducting several experiments on MovieLens dataset.

• Journal of Korea Game Society
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• v.15 no.2
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• pp.95-104
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• 2015

Many games for English vocabulary learning, such as hangman, cross puzzle, matching, etc, have been developed which are of board-type or computer game-type. Most of these computer games are adapting strategy-style game plays so that there is a limit on giving the fun, a nature of games, to learners who do not like games of this style. In this paper, a system for memorizing new English words is proposed which is based on a single-player car racing game targeting youths and adults. In the game, the core of our system, a learner drives a car and obtains game points by colliding with English word texts like game items appearing on the track. The learner keeps on viewing English words being exposed on the track while driving, resulting in memorizing those words according to a learning principle stating viewing is memorization. To our experiment, the effect of memorizing English words by our car racing game is good, and the degree of satisfaction with our system as a English vocabulary learning tool is reasonably high. Also, previous word games are suitable for the memory enforcement of English words but our game can be used for the memorization of new words.

• Journal of the Korea Society of Computer and Information
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• v.23 no.11
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• pp.31-41
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• 2018

Text classification has been studied for a long time in the Natural Language Processing field. In this paper, we propose an article- and paragraph-level genre classification system using Word2Vec-based LSTM, GRU, and CNN models for large-scale English corpora. Both article- and paragraph-level classification performed best in accuracy with LSTM, which was followed by GRU and CNN in accuracy performance. Thus, it is to be confirmed that in evaluating the classification performance of LSTM, GRU, and CNN, the word sequential information for articles is better than the word feature extraction for paragraphs when the pre-trained Word2Vec-based word embeddings are used in both deep learning-based article- and paragraph-level classification tasks.