• The Journal of Korean Association of Computer Education
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• v.13 no.2
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• pp.25-34
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• 2010

The Internet has brought us a new paradigm called WEB 2.0 which inherently represents the openness, participation, sharing, and cooperation. The WEB 2.0 has rendered people to actively participate in the creation of information and to dynamically interact with others to build mutual knowledge-bases, introducing a whole new web environment. One of the most representative techniques demonstrating the value of the WEB 2.0 is the WIKI which is essentially based on the 'Collective Intelligence' and the 'Wisdom of Crowds'. So far, the WIKI has drawn lots of attention for its potential as an educational tool. In this research, we explored the educational potential of the WIKI by investigating various programs and web-based tools offering WIKI services, and then, analyzing the usage model and characteristics of its users. Based on the analysis, we developed a WIKI-based instructional model and also proposed concrete lesson plans adopting this model. Besides, we introduced preliminary methodologies on the active use of the WIKI in the Edunet and the Cyber Home Learning System as well.

• The KIPS Transactions:PartA
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• v.9A no.4
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• pp.603-614
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• 2002

Delivery efficiency of e-learning media can be influenced by authoring processes. Generally, a moving picture recorded by video camera can be delivered to student by multimedia streaming service, using media server technology. A e-learning media authored by lecture authoring tool is played in a student application by download-based delivery system. Recently, some animation know-how are applied to author e-learning media by hand-operation. In this paper, we suggest a client-based streaming service for the e-leaning media consists of media files and integration data The lecture of e-learning media nay be divided into some time-based small blocks. Each blocks can be located distributed site. The student system gather those blocks by download-scheduling. This is a valid method for QoS guarantee streaming services. In addition to our study, lecturers can author composite e-learning media includes media files and dynamic web pages simply, The distributed e-learning media files of our study is managed by multi-author and updated rapidly.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.12
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• pp.507-514
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• 2018

This study utilized latent growth curve modeling to investigate the trajectories of adolescent life satisfaction changes in middle and high school students. The effects of self-esteem, career identity, school learning activity, gender, and household earnings on life satisfaction changes were examined. Data was obtained from the Korea Child Youth Panel Survey (KYCPS), a longitudinal study following students for 7 years. Year 3-6 data was utilized. Results found that the life satisfaction trajectory resulted as a quadratic model in which individual differences were significant. Second, school learning activity used as a time variant variable had a positive significant effect on life satisfaction each year. Third, gender and self-esteem as time invariant variables had significant effects on initial levels while self-esteem had effects on the slope and quadratic change. Further implications and research issues are discussed.

• Journal of Internet Computing and Services
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• v.23 no.1
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• pp.87-93
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• 2022

Since 99% of PCs operating in the defense domain use the Windows operating system, detection and response of Window-based malware is very important to keep the defense cyberspace safe. This paper proposes a model capable of detecting malware in a Windows PE (Portable Executable) format. The detection model was designed with an emphasis on rapid update of the training model to efficiently cope with rapidly increasing malware rather than the detection accuracy. Therefore, in order to improve the training speed, the detection model was designed based on a Bidirectional LSTM (Long Short Term Memory) network that can detect malware with minimal sequence data without complicated pre-processing. The experiment was conducted using the EMBER2018 dataset, As a result of training the model with feature sets consisting of three type of sequence data(Byte-Entropy Histogram, Byte Histogram, and String Distribution), accuracy of 90.79% was achieved. Meanwhile, it was confirmed that the training time was shortened to 1/4 compared to the existing detection model, enabling rapid update of the detection model to respond to new types of malware on the surge.

• KNOM Review
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• v.24 no.2
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• pp.24-34
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• 2021

Service providers using edge computing provide a high level of service. As a result, devices store important information in inner storage and have become a target of the latest cyberattacks, which are more difficult to detect. Although experts use a security system such as intrusion detection systems, the existing intrusion systems have low detection accuracy. Therefore, in this paper, we proposed a machine learning model for more accurate intrusion detections of devices in edge computing. The proposed model is a hybrid model that combines a stacked sparse autoencoder (SSAE) and a convolutional neural network (CNN) to extract important feature vectors from the input data using sparsity constraints. To find the optimal model, we compared and analyzed the performance as adjusting the sparsity coefficient of SSAE. As a result, the model showed the highest accuracy as a 96.9% using the sparsity constraints. Therefore, the model showed the highest performance when model trains only important features.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.5
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• pp.165-170
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• 2023

With the recent rise of blockchain technology, cryptocurrency platforms using it are increasing, and currency transactions are being actively conducted. However, crimes that abuse the characteristics of cryptocurrency are also increasing, which is a problem. In particular, phishing scams account for more than a majority of Ethereum cybercrime and are considered a major security threat. Therefore, effective phishing scams detection methods are urgently needed. However, it is difficult to provide sufficient data for supervised learning due to the problem of data imbalance caused by the lack of phishing addresses labeled in the Ethereum participating account address. To address this, this paper proposes a phishing scams detection method that uses both Trans2vec, an effective graph embedding techique considering Ethereum transaction networks, and semi-supervised learning model Tri-training to make the most of not only labeled data but also unlabeled data.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.801-807
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• 2024

Linear motion robots are devices that perform functions such as transferring parts or positioning devices, and require high precision. In companies that develop linear robot application systems, human workers are in charge of quality control and fault diagnosis of linear robots, and the result and accuracy of a fault diagnosis varies depending on the skill level of the person in charge. Recently, there have been many attempts to utilize artificial intelligence to diagnose faults in industrial devices. In this paper, we present a system that automatically diagnoses linear rail and ball screw misalignment of a linear robot using transfer learning. In industrial systems, it is difficult to obtain a lot of learning data, and this causes a data imbalance problem. In this case, a transfer learning model configured by retraining an established model is widely used. The information obtained by using an acceleration sensor and torque sensor was used, and its usefulness was evaluated for each case. After converting the signal obtained from the sensor into a spectrogram image, the type of abnormality was diagnosed using an image recognition artificial intelligence classifier. It is expected that the proposed method can be used not only for linear robots but also for diagnosing other industrial robots.

• The KIPS Transactions:PartA
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• v.18A no.4
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• pp.129-134
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• 2011

E-learning in Korea supports different educational needs of diverse learners. E-learning became one of the major source of educational services for schools, higher education, lifelong learning, and for special education. Many e-learning contents offered by cyber universities use HTML, CSS, and Flash, and these are known to have limitations on accessibilities. People with disabilities or aged have problems accessing such contents. The purpose of this study is to evaluate accessibility of Flash e-learning contents offered by 9 cyber universities. AccChecker is used to assess accessibility of the contents. The result shows many errors and warning with Text Equivalents, Keyboard Navigation, Properties, Depth of Tree, and Structures that restrict access. In order to improve the quality and expansion of quality e-learning contents, we need aggressive measures to obtain accessibility of contents, and these should be designed at the planning phase rather than adjusted during the development stage. Furthermore, it is vital to train instructional designers, developers and the CEOs to realize the importance of accessibility and learn appropriate skills to increase accessibilities of e-learning contents.

• The Journal of the Korea Contents Association
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• v.16 no.3
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• pp.694-711
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• 2016

National Competency Standards (NCS) is a good resource for curriculum development and operations corresponding to the industrial damand. Recently, four-year colleges and universities are committed to a restructuring of the industry demand-driven training courses in order to strengthen competitiveness. However, NCS is focused to train the technical personnel in vocational training institutions(ex. College, Polytechnic University). Accordingly, NCS applications of four-year colleges and universities are hard to find. In this study, we propose a new model for NCS-based curriculum development and operations. Also, NCS was utilized to complement the existing curriculum. This paper includes the following contents; 1) NCS-based curriculum development process, 2) NCS-based course development and operation, 3) learner satisfaction analysis. Finally, this study provide practical implications to four-year colleges and universities to consider NCS application.

• Journal of Platform Technology
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• v.9 no.3
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• pp.70-77
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• 2021

The purpose of Serious games in immersive Metaverse platform to provide users both fun and intriguing learning experiences. We proposes a serious game for self-trainable fire evacuation drill with collaboration among avatars synchronized with multiple trainees and optionally with real-time supervising placed at different remote physical locations. The proposed system architecture is composed of wearable motion sensors and a Head Mounted Display to synchronize each user's intended motions to her/his avatar activities in a cyberspace in Metaverse environment. The proposed system provides immersive as well as inexpensive environments for easy-to-use user interface for cyber experience-based fire evacuation training system. The proposed configuration of the user-avatar interface, the collaborative learning environment, and the evaluation system on the VR serious game are expected to be applied to other serious games. The game was implemented only for the predefined fire scenario for buildings, but the platform can extend its configuration for various disaster situations that may happen to the public.