• Journal of Digital Convergence
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• v.8 no.2
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• pp.217-228
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• 2010

There are two streams on e-Learning. The first one is to create new value through aligning products included information systems and service. The second one is to utilize the service system and the service process for service systematization. The service system is made up human, technology, value proposition, service network, and shared information. The service process consists of design, development, operation and evaluation phases. In this paper, we design and implement the evaluation management of e-learning service based on the service science. The evaluation management service is sets of evaluation type management, general review management, award management, evaluation sheet management and evaluation result management. Feature of this paper is that we can service with different criteria to learner, guardian and evaluator. The worthy of this paper is that we construct service oriented environment possible to systematize evaluation work easily and provide evaluation results clearly.

• Journal of Information Processing Systems
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• v.8 no.3
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• pp.521-538
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• 2012

As the knowledge society matures, not only distant, but also off-line universities are trying to provide learners with on-line educational contents. Particularly, high effectiveness of mobile devices for e-Learning has been demonstrated by the university sector, which uses distant learning that is based on blended learning. In this paper, we analyzed previous m-Learning scenarios and future technology prospects. Based on the proposed m-Learning scenario, we designed cellular phone-based educational contents and service structure, implemented m-Learning system, and analyzed m-Learning service satisfaction. The design principles of the m-Learning service are 1) to provide learners with m-Learning environment with both cellular phones and desktop computers; 2) to serve announcements, discussion boards, Q&A boards, course materials, and exercises on cellular phones and desktop computers; and 3) to serve learning activities like the reviewing of full lectures, discussions, and writing term papers using desktop computers and cellular phones. The m-Learning service was developed on a cellular phone that supports H.264 codex in 3G communication technology. Some of the functions of the m-Learning design principles are implemented in a 3G cellular phone. The contents of lectures are provided in the forms of video, text, audio, and video with text. One-way educational contents are complemented by exercises (quizzes).

• IEMEK Journal of Embedded Systems and Applications
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• v.8 no.1
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• pp.11-16
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• 2013

With the development and general use of a variety of Android/iOS-based smart phones and smart pads, the existing e-learning contents need to be changed in such a way that they can be carried out on different smart device platforms. This paper shows what changes are needed for that aim, and, in particular, for the compatibility of different platforms by designing and implementing Android/iOS-based smart learning contents in the form of a hybrid app. This paper will hopefully help you consider what elements are required to develop smart-learning contents on a variety of platforms for mobile devices.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.604-607
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• 2003

Most recommendation systems recommend the products or other information satisfying preferences of users on the basis of the users' previous profile information and other information related to product searches and purchase of users visiting web sites. This study aims to apply these application categories to e-mail more necessary to users. The E-Mail System has the strong personality so that there will be some problems even if e-mails are automatically classified by category through the learning on the basis of the personal rules. In consideration with this aspect, we need the semi-automatic system enabling both automatic classification and recommendation method to enhance the satisfaction of users. Accordingly, this paper uses two approaches as the solution against the misclassification that the users consider as the accuracy of classification itself using the dynamic threshold in Bayesian Learning Algorithm and the second one is the methodological approach using the recommendation agent enabling the users to make the final decision.

• Electronics and Telecommunications Trends
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• v.38 no.6
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• pp.95-106
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• 2023

As artificial intelligence has become commonplace in various fields, the transparency of AI in its development and implementation has become an important issue. In safety-critical areas, the eXplainable and/or understandable of artificial intelligence is being actively studied. On the other hand, machine learning have been applied to the intelligence of self-organizing network (SON), but transparency in this application has been neglected, despite the critical decision-makings in the operation of mobile communication systems. We describes concepts of eXplainable machine learning (ML), along with research trends, major issues, and research directions. After summarizing the ML research on SON, research directions are analyzed for explainable ML required in intelligent SON of beyond 5G and 6G communication.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.14-19
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• 1993

In this paper, we proposed an indirect learning and direct adaptive control schemes using neural networks, i.e., composite adaptive neural control, for a class of continuous nonlinear systems. With the indirect learning method, the neural network learns the nonlinear basis of the system inverse dynamics by a modified backpropagation learning rule. The basis spans the local vector space of inverse dynamics with the direct adaptation method when the indirect learning result is within a prescribed error tolerance, as such this method is closely related to the adaptive control methods. Also hash addressing technique, similar to the CMAC functional architecture, is introduced for partitioning network hidden nodes according to the system states, so global neuro control properties can be organized by the local ones. For uniform stability, the sliding mode control is introduced when the neural network has not sufficiently learned the system dynamics. With proper assumptions on the controlled system, global stability and tracking error convergence proof can be given. The performance of the proposed control scheme is demonstrated with the simulation results of a nonlinear system.

• International Journal of Computer Science & Network Security
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• v.23 no.3
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• pp.17-30
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• 2023

The current research aims to reveal the impact of using some participatory e-learning strategies (participatory product - classroom web simulation) in developing cognitive achievement, electronic course design skills, and - skills list - Torrance test of innovative thinking). The tools of innovative thinking among a sample of Information Science students. To achieve the objectives of current research, the researcher designed an educational website to train students to produce electronic courses via the web, according to the two participatory e-learning strategies. The researcher used a set of tools represented in (achievement test research and experimental treatment were applied to a sample of the Faculty of Computer students at Umm Al-Qura University. The results found that both participatory product strategy and web simulation have an imact on developing learning aspects discussed in the research. As for which of the two strategies had a greater impact than the other, it turned out that the web simulation strategy had a greater impact than the participatory product strategy in developing these aspects.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.1-10
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• 2024

In the era of big data, the growth of e-commerce transactions brings forth both opportunities and risks, including the threat of data theft and fraud. To address these challenges, an automated real-time fraud detection system leveraging machine learning was developed. Four algorithms (Decision Tree, Naïve Bayes, XGBoost, and Neural Network) underwent comparison using a dataset from a clothing website that encompassed both legitimate and fraudulent transactions. The dataset exhibited an imbalance, with 9.3% representing fraud and 90.07% legitimate transactions. Performance evaluation metrics, including Recall, Precision, F1 Score, and AUC ROC, were employed to assess the effectiveness of each algorithm. XGBoost emerged as the top-performing model, achieving an impressive accuracy score of 95.85%. The proposed system proves to be a robust defense mechanism against fraudulent activities in e-commerce, thereby enhancing security and instilling trust in online transactions.

• Journal of information and communication convergence engineering
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• v.22 no.1
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• pp.7-13
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• 2024

User preferences and ratings may be anticipated by recommendation systems, which are widely used in social networking, online shopping, healthcare, and even energy efficiency. Constructing trustworthy recommender systems for various applications, requires the analysis and mining of vast quantities of user data, including demographics. This study focuses on holding elections with vague voter and candidate preferences. Collaborative user ratings are used by filtering algorithms to provide suggestions. To avoid information overload, consumers are directed towards items that they are more likely to prefer based on the profile data used by recommender systems. Better interactions between governments, residents, and businesses may result from studies on recommender systems that facilitate the use of e-government services. To broaden people's access to the democratic process, the concept of "e-democracy" applies new media technologies. This study provides a framework for an electronic voting advisory system that uses machine learning.

• The KIPS Transactions:PartA
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• v.18A no.6
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• pp.241-248
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• 2011

Many learning systems are applying Self-Directed Learning to improve learning efficiency. The degree of understanding of the same learning contents can be different even if the learner's level is same. Therefore, it is difficult to represent an effective learning experience because the learning is progressed by the determined difficulty of learning and the learning process even thought the provided content is difficult to understand. In this paper, we augmented SCORM to reconstruct the learning contents which are suitable for the changed level of each learner in real-time. Also, we designed and implemented this augmented SCORM based DCOS(Differential Contents Organization System). In order to provide the suitable contents for each learner, DCOS reorganizes learning contents based on the learner's level, the learner's achievement of learning objectives, and the correlation between learning objects, that is the component of the learning content. Each 30 Each 30 students studied e-learning contents, which are constructed based on the existing System and DCOS respectively. And the average score and system's satisfaction of the students who studied DCOS based e-learning contents was higher.