• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.20 no.1
• /
• pp.96-102
• /
• 2019

This study proposes basic information to make effective environments for social welfare education, revealing the reasons why students choose the social welfare major at Konyang Cyber University. We conducted qualitative research with 41 students in the social welfare department at Konyang Cyber University. The result of this research is as follows. First, most students chose their major to get a certificate that can benefit them in the near future. Second, they chose their major as a way to achieve renown, and to enhance the quality of their lives. Third, they desired to contribute to society through their social work. Finally, individual experiences and family background were also motives. Based on the research, to improve learning outcomes in social welfare education, the necessary learning strategies are as follows. First, goal-oriented learning is necessary for students who want to get the certificate. A practical curriculum needs to contain both practical skills and professional knowledge applicable to the social work field. Second, education for students who choose the major to gain fame, and to develop their lives, requires generation-integrated education to help them review their lives and find their own meaning in life. Third, education for students who choose the major for a practical social contribution has to contain volunteer training that can lead them to be professional volunteers in society. Fourth, education for students who choose the major based on their personal experiences and their family background needs to deal with case management, which discovers the recipients who need help in society and the students who can achieve visible outcomes after all.

• Journal of the Korea Convergence Society
• /
• v.11 no.1
• /
• pp.119-130
• /
• 2020

This study developed an English conversation learning program in immersive virtual reality (VR) environments and compared its effects with non-immersive VR environment using a computer monitor. The effects of the program was assessed using language anxiety and learning achievement. The results indicated that students' language anxiety decreased significantly after learning English conversation in VR environment, but there was no difference between immersive and non-immersive VR. The two VR conditions also produced similar learning outcomes. Future research on immersive VR need to address cyber sickness problems and develop effective learning contents in order to realize its potential for learning.

• KIPS Transactions on Software and Data Engineering
• /
• v.12 no.8
• /
• pp.355-364
• /
• 2023

As advanced cyber threats continue to increase in recent years, it is difficult to detect new types of cyber attacks with existing pattern or signature-based intrusion detection method. Therefore, research on anomaly detection methods using data learning-based artificial intelligence technology is increasing. In addition, supervised learning-based anomaly detection methods are difficult to use in real environments because they require sufficient labeled data for learning. Research on an unsupervised learning-based method that learns from normal data and detects an anomaly by finding a pattern in the data itself has been actively conducted. Therefore, this study aims to extract a latent vector that preserves useful sequence information from sequence log data and develop an anomaly detection learning model using the extracted latent vector. Word2Vec was used to create a dense vector representation corresponding to the characteristics of each sequence, and an unsupervised autoencoder was developed to extract latent vectors from sequence data expressed as dense vectors. The developed autoencoder model is a recurrent neural network GRU (Gated Recurrent Unit) based denoising autoencoder suitable for sequence data, a one-dimensional convolutional neural network-based autoencoder to solve the limited short-term memory problem that GRU can have, and an autoencoder combining GRU and one-dimensional convolution was used. The data used in the experiment is time-series-based NGIDS (Next Generation IDS Dataset) data, and as a result of the experiment, an autoencoder that combines GRU and one-dimensional convolution is better than a model using a GRU-based autoencoder or a one-dimensional convolution-based autoencoder. It was efficient in terms of learning time for extracting useful latent patterns from training data, and showed stable performance with smaller fluctuations in anomaly detection performance.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.8 no.2
• /
• pp.709-722
• /
• 2014

In the $21^{st}$ century, IT reform has led to the development of cyber-infrastructure owing to the outstanding enhancement of computer and network performance. The ripple effect has continued to increase. Accordingly, this study suggests a new computational research environment using mobile devices. In order to simplify the access of supercomputer, Science AppStore, task management and virtualization technologies are developed on mobile devices. User can be able to research by utilizing computational science SW such as compressible flow solver and nano device simulation tool that in installed on supercomputer in mobile environments. Also, this research environment makes it possible to monitor the simulation result and covers 14 university, 33 subjects, and 1,202 individuals.

• Educational Technology International
• /
• v.12 no.2
• /
• pp.117-134
• /
• 2011

Online education is moving forward with more interactive environments due to the availability of new technologies. In addition, many researches have represented that interaction and high motivation are very critical factors in order to improve students' motivation and teaching effectiveness in online learning and education. Therefore, it is very meaningful for students and educators that motivation and effectiveness are observed by positive expectation and interaction satisfaction in their online counseling courses. For this study, two important instruments are used: Modified Short Forms of Instructional Materials Motivation Survey and Student Evaluation of Online Teaching Effectiveness. Results show that high expected students who are satisfied with interaction indicate higher motivation and evaluation on the online teaching effectiveness than low expected students who are not satisfied with interaction.

• International Journal of Computer Science & Network Security
• /
• v.23 no.12
• /
• pp.1-12
• /
• 2023

Ensuring the security of Supervisory Control and Data Acquisition (SCADA) and Industrial Control Systems (ICS) is paramount to safeguarding the reliability and safety of critical infrastructure. This paper addresses the significant threat posed by reconnaissance attacks on SCADA/ICS networks and presents an innovative methodology for enhancing their protection. The proposed approach strategically employs imbalance dataset handling techniques, ensemble methods, and feature engineering to enhance the resilience of SCADA/ICS systems. Experimentation and analysis demonstrate the compelling efficacy of our strategy, as evidenced by excellent model performance characterized by good precision, recall, and a commendably low false negative (FN). The practical utility of our approach is underscored through the evaluation of real-world SCADA/ICS datasets, showcasing superior performance compared to existing methods in a comparative analysis. Moreover, the integration of feature augmentation is revealed to significantly enhance detection capabilities. This research contributes to advancing the security posture of SCADA/ICS environments, addressing a critical imperative in the face of evolving cyber threats.

• Journal of Korean Biological Nursing Science
• /
• v.3 no.2
• /
• pp.63-68
• /
• 2001

Increasing interest in computer-mediated learning technologies has prompted educators to incorporate them into many learning environments ; however, there is still little evaluative evidence to support their effectiveness. This report describes the development and evaluation of a web-based instructional program on basic nursing science for nursing students. Researcher-designed questionnaires were used to assess the characteristics of our students, and to solicit their ratings of the instructional program on ease of use, accuracy of content, clarity of content, interest, and convenience of the program, using 5-point Likert scales. The respondents indicated that the package was easy and convenient to use, with high technical quality, and of a level challenging to some but not all of the students. On-line quizzes were most highly rated. Also it was confirmed that frequent users of electronic bulletin board showed much higher achievement score than that of nonfrequent users. It was also found that the effect of cyber education was dependent on the active participation of the students. These data suggest that the use of web-based instructional program as a distance education strategy can be an effective method for nursing students and nurses.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.12
• /
• pp.6145-6158
• /
• 2019

It is a challenge for the current security industry to respond to a large number of malicious codes distributed indiscriminately as well as intelligent APT attacks. As a result, studies using machine learning algorithms are being conducted as proactive prevention rather than post processing. The k-NN algorithm is widely used because it is intuitive and suitable for handling malicious code as unstructured data. In addition, in the malicious code analysis domain, the k-NN algorithm is easy to classify malicious codes based on previously analyzed malicious codes. For example, it is possible to classify malicious code families or analyze malicious code variants through similarity analysis with existing malicious codes. However, the main disadvantage of the k-NN algorithm is that the search time increases as the learning data increases. We propose a fast k-NN algorithm which improves the computation speed problem while taking the value of the k-NN algorithm. In the test environment, the k-NN algorithm was able to perform with only the comparison of the average of similarity of 19.71 times for 6.25 million malicious codes. Considering the way the algorithm works, Fast k-NN algorithm can also be used to search all data that can be vectorized as well as malware and SSDEEP. In the future, it is expected that if the k-NN approach is needed, and the central node can be effectively selected for clustering of large amount of data in various environments, it will be possible to design a sophisticated machine learning based system.

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

• Phonetics and Speech Sciences
• /
• v.12 no.4
• /
• pp.9-17
• /
• 2020

Changes in the first language (L1) sound system as a result of acquiring a second language (L2) (i.e., phonetic drift) have received considerable attention from a variety of speakers, settings, and environments. Less attention has been given to phonetic drift in adult speakers' L2 learning as their length of residence in America (LOR) increases. This study examines the effects of LOR on voice onset time (VOT) in L1 Korean stops. Three different groups of Korean adult learners of L2 English were compared to assess how malleable their L1 representations are in terms of LOR and whether there is any relationship between L1 change and L2 acquisition. The results showed that the effect of LOR was linguistically unimportant in the production of Korean stops. However, VOT merger as evidence of sound change in Korean stops were robust in the speech production of most of the female speakers across the groups. The results suggest that L2 English may not be the primary cause of L1 sound change. For generalizability, further study is necessary to see whether other acoustic cues show a similar pattern.