• Journal of Korea Society of Industrial Information Systems
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• v.12 no.5
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• pp.71-85
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• 2007

In recent years, the need of the education for the Internet ethics is emphasized as the number of offenses committed by juveniles is increasing. So many researches on the methodologies about educating the Internet ethics have been being performed But, those are not competent to make young people inspire the sense of ethics in the cyber-space because they get trained by the cramming system of education with a textbook in their schools. In this paper, we developed a web-based learning model and an learning system including various multimedia materials that induce the learners for ethics to study actively. And then we applied our system to school education for the Internet ethics, and verified the effectiveness of our learning model and system.

• Journal of Internet Computing and Services
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• v.22 no.5
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• pp.27-33
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• 2021

With the broad adoption of the Internet of Things (IoT) in a variety of scenarios and application services, management and orchestration entities require upgrading the traditional architecture and develop intelligent models with ultra-reliable methods. In a heterogeneous network environment, mission-critical IoT applications are significant to consider. With erroneous priorities and high failure rates, catastrophic losses in terms of human lives, great business assets, and privacy leakage will occur in emergent scenarios. In this paper, an efficient resource slicing scheme for optimizing federated learning in software-defined IoT (SDIoT) is proposed. The decentralized support vector regression (SVR) based controllers predict the IoT slices via packet inspection data during peak hour central congestion to achieve a time-sensitive condition. In off-peak hour intervals, a centralized deep neural networks (DNN) model is used within computation-intensive aspects on fine-grained slicing and remodified decentralized controller outputs. With known slice and prioritization, federated learning communications iteratively process through the adjusted resources by virtual network functions forwarding graph (VNFFG) descriptor set up in software-defined networking (SDN) and network functions virtualization (NFV) enabled architecture. To demonstrate the theoretical approach, Mininet emulator was conducted to evaluate between reference and proposed schemes by capturing the key Quality of Service (QoS) performance metrics.

• Journal of The Korean Association of Information Education
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• v.8 no.2
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• pp.167-176
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• 2004

Due to the development of information communication technology, educational environment has undergone much change and various types of teaching and learning methods based on information communication technology has been suggested. Recently, remote education using the internet are also spreading. However, in current classrooms, students are asked to do an teacher-centered assignment, which they are required to collect and report some information using the internet. This method does not help students use the advantages of learning using the internet, which stimulate students-students interaction and teacher-students interaction.Thus, this study focused on the problem-based learning system based on video communication technology. The researcher designed the problem-based learning system based on video communication technology and applied the system to classes at elementary school. The results were analyzed in terms of students-students interaction and teacher-students interaction in the internet. This research found that the problem-based learning system stimulates teacher and students communication and has positive effects on students' attitude and interest in learning. This research proposes that the traditional teacher-centered teaching method can be supplemented with cyber space learning, which has the merit of problem-based learning model.

• The Journal of the Korea Contents Association
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• v.6 no.6
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• pp.64-73
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• 2006

In this paper, I explored the direction of ICT used learning that can improve the access ability of e-learning to activate a neglected class's lifelong education by e-learning. I had a good grasp of a neglected class's actual condition of the access ability of e-learning and presented the direction of basic ICT used learning for the adults that can improve the access ability for the lifelong education by e-learning. According to the result of this research, it was found that the adult learners had a considerable disparity by age group. Therefore, it is desirable that they had to learn ICT used learning with considering the actual condition by age. Teenagers and 20 years of age need to be learned in order of an Internet club, word processor, moving picture and etc. It needs to be teamed for the $30{\sim}40$ age bracket lil order of a chat, an Internet club, searching engines and etc and for the $30{\sim}40$ age bracket in order of a chat, an Internet club and moving picture and etc. And also it needs to induce a neglected class to develope participation abilities for themselves by activating an internet club activity.

• Journal of Internet Computing and Services
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• v.12 no.4
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• pp.135-143
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• 2011

The smartphone allows learners to be involved in learning environments in which students actively study from anywhere and at anytime. Because learners can keep engaged in the environment where they can access to the internet, they can efficiently study in transit using various features and functions of smartphone. Smart learning is a unique learning based on mobility and functions of mobile digital devices including searching and sharing information and using various applications. For the effective use of smartphones in e-learning systems, the contents and learning management systems should be designed to meet effective teaching and learning principles, such as interactivity and collaborations. In smart learning, learning contents for effective learning need to be integrated with typical functions of smartphones and to develop small pieces of learning contents according to learning topics. In the case of learning management systems, it should reflect understanding of learners' environment using a PA agent program and provide personalized learning services.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.2 no.5
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• pp.239-252
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• 2008

To facilitate the processes of e-learning resource description, discovery and reuse, e-learning objects should be appropriately described and classified using standard metadata that need to be published in a registry to reduce duplication of effort and enhance semantic interoperability. This paper describes how standard ebXML registries can be used for semantic grid computing for annotating, storing, discovering and retrieving e-learning object metadata. For semantic annotation of e-learning objects, IEEE Learning Object Metadata (LOM) is adopted as the metadata ontology. In order to support the e-learning metadata ontology in interoperable ebXML registries, a mapping scheme between LOM and ebXML Registry Information Model (RIM) is proposed. The usefulness of sharing e-learning object metadata is demonstrated by prototyping a semantic registry based on the scheme.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.231-238
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• 2023

As the demand for distance education increases, interest in the management of learners' rights is increasing. Blockchain technology is a technology that guarantees the integrity of the learner's learning history, and enables learner-led learning control, data security, and sharing of learning resources. In this paper, we proposed a blockchain technology-based learning management system based on Hyperledger Fabric that can be verified through permission between nodes among blockchain platforms. Learning resources can be shared differentially according to the learning progress. Also the percentage of individual learners that can be managed. As a result of the study, the superiority of the platform in terms of convenience compared to the existing platform was demonstrated. As a result of the performance evaluation for the research in this paper, it was confirmed that the convenience was improved by more than 5%, and the performance was 4-5% superior to the existing platform in terms of learner satisfaction.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.3
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• pp.610-632
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• 2024

Mobile Learning (M-learning) adoption and success in supporting students' learning engagement mainly depend on many factors. Therefore, this study systematically reviews the literature, synthesizes and analyzes the predictors of M-learning adoption, and uses success for students' learning engagement. Literature from 2016 to 2023 in various databases is covered in this study. Based on the review's findings, the factors that influence students' learning engagement when it comes to M-learning usage and adoption, can be divided into technical, pedagogical, and social factors. More specifically, technical factors include mobile devices availability and quality, connectivity to the internet, and user-friendly interfaces, pedagogical factors include effective instructional design, teaching methods, and assessment strategies, and social factors include motivation of students, social interaction and perceived enjoyment - all these factors have a significant impact on the M-learning adoption and use success. The findings of the review also indicated that M-learning has a key role in enhancing the learning engagement of students through different ways, like increasing their motivation, attention, and participation in their process of learning, paving the way for interaction and building relationships opportunities with peers and instructors, which in turn, can lead to strengthening the learning environment. The implications of these findings extend beyond immediate educational contexts, offering vital insights for future educational technology strategies and policy decisions, particularly in addressing global educational challenges and embracing technological advancements in learning.

• Journal of the Korean School Mathematics Society
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• v.4 no.2
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• pp.75-84
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• 2001

The purpose of this research is to promote the academic achievement motivation and improve problem solving ability in Mathematics. In addition I hope to explore a new teaching method and facilitate students interest in mathmatics. If the teachers utilize an Internet Web Page and exchang information, the interaction activities will allow them to collect and analyse a variety of data. As this teaching method assists students motivation to get the effects of self-regulated learning strategies of students using the internet and their academic achievements and learning attitudes can be explored. The information will be gathered after the students participate in classes which were taught through the Edunet Homepage and the Department of Mathematics Homepage of KongJu National University. The Internet pages focused on the "Function" chapter of the first grade text for students attending middle school. The students were divided into two groups, experimental and comparative. Each group is composed of three levels, high, middle, and low. In the post experimental phase, two tests were administered which measured achievement ability and the learning attitude of the students. The results of the tests were then compared and analyzed. The results were as follows: First, the study demonstrated that self-regulated Learning Starategies towards Academic Achievements and Learning Attitudes were more effective than traditional teaching methods. These methods were significantly effective in the middle level and low level groups. The study demonstrated little to no improvement in the high level groups

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.2
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• pp.494-510
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• 2024

Internet users are exposed to sophisticated cyberattacks that intrusion detection systems have difficulty detecting. Therefore, research is increasing on intrusion detection methods that use artificial intelligence technology for detecting novel cyberattacks. Unsupervised learning-based methods are being researched that learn only from normal data and detect abnormal behaviors by finding patterns. This study developed an anomaly-detection method based on unsupervised machines and deep learning for a network intrusion detection system (NIDS). We present a hybrid anomaly detection approach based on unsupervised learning techniques using the autoencoder (AE), Isolation Forest (IF), and Local Outlier Factor (LOF) algorithms. An oversampling approach that increased the detection rate was also examined. A hybrid approach that combined deep learning algorithms and traditional machine learning algorithms was highly effective in setting the thresholds for anomalies without subjective human judgment. It achieved precision and recall rates respectively of 88.2% and 92.8% when combining two AEs, IF, and LOF while using an oversampling approach to learn more unknown normal data improved the detection accuracy. This approach achieved precision and recall rates respectively of 88.2% and 94.6%, further improving the detection accuracy compared with the hybrid method. Therefore, in NIDS the proposed approach provides high reliability for detecting cyberattacks.