• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2614-2616
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• 2002

According to the appearance of various virtual websites using multimedia technologies for engineering education, the internet applications in engineering education have drawn much interests. But unidirectional communication, simple text/image based webpages and tedious learning process without motivation etc. have made the lowering of educational efficiency in cyberspace. Thus, to cope with these difficulties this paper presents a web-based educational Flash movies based on ActionScript language for understanding the principles of the computer system architecture. The proposed Flash movies provides the improved learning methods which can enhance the interests of learners. The results of this paper can be widely used to improve the efficiency of cyberlectures in the cyber university. Several sample Flash movies are illustrated to show the validity of the proposed learning method.

• Asia pacific journal of information systems
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• v.12 no.3
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• pp.45-70
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• 2002

This paper examines the role of distance learning self-efficacy, belief in one's capabilities of using a system in the accomplishment of web-based distance learning, in predicting user intention to use and performance of distance learning system. It used self-efficacy theory and technology acceptance model(TAM) to build a model that predicts relationships between antecedents to students' distance learning self-efficacy assessments and their behavioral and attitudinal consequences. The model was tested using LISREL analysis on the sample of 250 students who have worked with the Distance Learning System. The results indicated partial support for the conceptual model. In accordance with TAM, perceived usefulness had strong direct effects on intention to use and performance, while perceived ease of use had both direct and indirect effects on intention to use, but not performance. Distance learning self-efficacy had only direct effect on perceived ease of use to use. Computer experience was found to have a strong positive effect on distance learning self-efficacy, and computer anxiety had a negative effect on distance learning self-efficacy. Implications of these findings are discussed for researchers and practitioners.

• The Journal of Korean Association of Computer Education
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• v.8 no.2
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• pp.33-40
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• 2005

It has been found that the learning method based on conventional CAI(Computer Assisted Instruction) to be inadequate and inefficient as it is designed without considering the individual learning characteristics of the learners. In order to rectify and remedy the problem, the development of an ITS(Intelligent Tutoring System) that is adequately equipped with an artificial intelligence that successfully interprets the individual learning ability characteristics through accumulated individual data is in order. This study attempts to verify the individual acquisition ability and the possible error committed by learners in the process of learning in order to present the elements to be considered for designing a successful student module that enables the effective learning through the 'learner ability grouping' for learning Electronic Calculator Architecture.

• International Journal of Computer Science & Network Security
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• v.23 no.7
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• pp.202-209
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• 2023

Android malware is now on the rise, because of the rising interest in the Android operating system. Machine learning models may be used to classify unknown Android malware utilizing characteristics gathered from the dynamic and static analysis of an Android applications. Anti-virus software simply searches for the signs of the virus instance in a specific programme to detect it while scanning. Anti-virus software that competes with it keeps these in large databases and examines each file for all existing virus and malware signatures. The proposed model aims to provide a machine learning method that depend on the malware detection method for Android inability to detect malware apps and improve phone users' security and privacy. This system tracks numerous permission-based characteristics and events collected from Android apps and analyses them using a classifier model to determine whether the program is good ware or malware. This method used the machine learning techniques KNN-SVM, DBN, and GRU in which help to find the accuracy which gives the different values like KNN gives 87.20 percents accuracy, SVM gives 91.40 accuracy, Naive Bayes gives 85.10 and DBN-GRU Gives 97.90. Furthermore, in this paper, we simply employ standard machine learning techniques; but, in future work, we will attempt to improve those machine learning algorithms in order to develop a better detection algorithm.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.830-833
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• 2002

To solve the internal security problem such as human error and bad faith, the automation of computer system management is significant. For this purpose, we focus attention in the automation of Mail Delivery Service. Today, requirement for reliable mail delivery system becomes larger and larger. However, existing systems are too strict about their configuration. Hence, we propose the method based on Reinforcement Learning (RL) to achieve proper MX record ordering. A measure on validity of the design of system, such as network topology number of servers and so on, is also obtained as side benefit. In order to verify the usability of the presented method, we did on a small model of mail delivery system. As a result, we show that RL is available for determination of the proper MX record ordering. Additionally, we suggest that it is also available for comparing validity of setting of MTA and the network design.

• The Journal of Korean Association of Computer Education
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• v.6 no.2
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• pp.121-135
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• 2003

This paper proposes a web-based adaptive tutoring system based on fuzzy set that provides learning materials and questions dynamically according to students' knowledge state, and gives advices for the learning after an evaluation. For this, we design a courseware knowledge structure systematically and then construct a fuzzy level set on the basis of it considering importance of learning targets, difficulty of learning materials and relation degree between learning targets and learning materials. Using the fuzzy level set, our system offers learning materials and questions to adapt to individual students. Moreover, a result of the test is evaluated with fuzzy linguistic variable. Appling the fuzzy concept to the tutoring system could naturally consider and deal with various and uncertain items of learning environment thus could offer more flexible and effective instruction-learning methods.

• Journal of The Korean Association of Information Education
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• v.5 no.2
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• pp.279-287
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• 2001

In this paper, we have defined and designed the structure of standardized XML content for supplying efficient e-Learning contents. We have also implemented the prototype of XML contents generator to create the educational contents easily. In addition, we have suggested the contents searching method using Case Base Reasoning and Bayesian belief network to supply XML contents suitable to learners request. The existing e-Learning system based on HTML could not customize and standardize, but XML contents can be reused and made an intelligent learning by supplying an adaptive content according to learners level. For evaluating the efficiency of designed XML content, we make the standard XML content for learning JAVA program in e-Learning system as well as discussing about the integrity and expanding the educational content. Finally, we have shown the architecture and effectiveness of the knowledge-based XML contents retrieval manager.

• International Journal of Computer Science & Network Security
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• v.22 no.11
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• pp.115-120
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• 2022

The main purpose of the study is to identify the key aspects of the use of innovative distance learning technologies in the training of biology students. Currently, there is a modernization, the evolution of the education system from a classical university to a virtual one, from lecture material teaching to computer educational programs, from a book library to a computer one, from multi-volume paper encyclopedias to modern search databases. During studies in higher education, distance learning ensures the delivery of information in an interactive mode through the use of information and communication technologies. The main disadvantage of distance learning is the emotional interaction of the teacher with students. It is necessary to increase the level of methodological developments for independent studies of students. The methodology includes a number of theoretical methods. Based on the results of the study, the main elements of the use of innovative distance learning technologies in the training of biology students were identified.

• Journal of the Korea Society of Computer and Information
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• v.11 no.4 s.42
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• pp.127-135
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• 2006

In the existing education using the globe. teaching contents are very simple and the relationship among learning units lacks a little bit because teaching materials are composed individually with the globe. Therefore, in this study, we developed the education glove system based on multimedia that is closely connected with teaching materials and the globe. This system is composed of the globe device and the learning software based on computer control. The globe device rotates itself on its axis as the solar center, and provides more efficient and visual education environment to students through the link between computer and the globe. The learning software provides the multimedia contents such as parallax, climate, culture, and education information about each country, and this software also can simulate the revolution of the earth around the sun. The globe device can be operated in off-line without the computer link. This system was developed by the industry cooperation and was displayed in the principal exhibitions. We have obtained positive results through the exhibitions and will promote the product in the future.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.2
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• pp.165-170
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• 2021

Machine learning has recently been applied to research in most areas. This is because the results of machine learning are not determined, but the learning of input data creates the objective function, which enables the determination of new data. In addition, the increase in accumulated data affects the accuracy of machine learning results. The data collected here is an important factor in machine learning. The proposed system is a convergence system of cloud systems and local fog systems for service delivery. Thus, the cloud system provides machine learning and infrastructure for services, while the fog system is located in the middle of the cloud and the user to collect and refine data. The data for this application shall be based on the Sensitive data generated by smart devices. The machine learning technique applied to this system uses SVM algorithm for classification and RNN algorithm for status recognition.