• The Journal of the Korea Contents Association
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• v.15 no.5
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• pp.365-374
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• 2015

The present study set out to explore the factors affecting rights advocacy for clients. The sample consisted of 251 adult learners who were in the classes of social welfare in S cyber university. Analysis revealed that students' rights advocacy level was 4.19(high) and the respondents showed higher level of class/case advocacy than policy advocacy. The group which had higher human rights sensitivity and had experience of human rights education showed higher level of rights advocacy. Regression analysis revealed that the experiences of human rights education in university curriculum were found to have a significant explanatory power in rights advocacy. These findings highlight that in the education of social worker as a human rights professionals it would be necessary to enhance the human rights and rights advocacy contents. It was suggested that multidisciplinary teaching method including direct experience and participation would be necessary to effective human rights education.

• Journal of the Society of Disaster Information
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• v.15 no.4
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• pp.531-539
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• 2019

Purpose: The purpose of this study is to present the commodity classification method of domestic rack-type warehouse for sprinkler system design. Method: On-site surveys and classification criteria of the NFPA, FMDS, EN and Japan were analysed and ISO 12949 test were carried out with proposed each classification commodity. Result: Based on a heat of combustion, a classification method for extra high, high, medium and low are proposed. Conclusion: Sprinkler design criteria to secure the maximum extinguishing strength for each class of commodity need to be applied.

• Journal of Intelligence and Information Systems
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• v.12 no.4
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• pp.109-126
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• 2006

An effective customer classification has been essential for the successful customer relationship management. The typical customer rating is carried out by the proportionally allocating the customers into classes in terms of their life time values. However, since this method does not accurately reflect the homogeneity within a class along with the heterogeneity between classes, there would be many problems incurred due to the misclassification. This paper suggests a new method of rating customer using Holistic profit technique, and validates the new method using the customer data provided by an insurance company. Holistic profit is one of the methods used for deciding the cutoff score in screening the loan application. By rating customers using the proposed techniques, insurance companies could effectively perform customer relationship management and diverse marketing activities.

• Journal of the Society of Disaster Information
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• v.17 no.2
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• pp.226-235
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• 2021

Purpose: The risk assessment for earthquakes was conducted in accordance with the current design standard (KBC2016) for the Coalescer facility, which is a major facility of energy storage facilities. Method: The risk assessment for earthquakes was conducted in accordance with the current design standard (KBC2016) for the Coalescer facility, which is a major facility of energy storage facilities. Result: In this study, by statically loading earthquake loads and evaluating the level of collapse prevention of special-class structures, facility managers can easily recognize and evaluate the risk level, and this analysis result can be applied to future facility risk management. Earthquake analysis was performed so that. Conclusion: As a result of analyzing the Coalescer facility according to the current design standard KBC2016, the stress ratio of the main supporting members was found to be up to 4.7%. Therefore, the members supporting Coalescer were interpreted as being safe against earthquakes with a reproducibility period of 2400 years that may occur in Korea.

• Journal of The Korean Association of Information Education
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• v.23 no.2
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• pp.141-148
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• 2019

We proposed a curriculum that can learn the principle of blockchain by using the gamification which can bring up the interest and concentration of the students by connecting the contents of the class with the game. The proposed method is to educate the blockchain in a game format and to solve the problem that can be easily accessed in everyday life by applying the blockchain. By strengthening the thinking ability of computing, By growing information processing capacity, communication capacity, and community capacity, students can naturally enhance their education capacity. It is expected that the blockchain curriculum using the proposed gamification can be used to improve the information curriculum.

• Journal of the Korea Convergence Society
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• v.11 no.12
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• pp.105-112
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• 2020

This study categorized the developments of advanced online education in Korea, which have achieved rapid growth for past 20 years, and analyzed the characteristics of each stage. Starting from the introduction stage, which focused on video content and basic LMS, it went through a growth stage in which the transition from lifelong to advanced education institute, and the first online graduate program accreditation were achieved. In the maturity stage, the expansion of online graduate programs led to the spread of online real-time classes and seminars, and the introduction and proliferation of smart-phone also paved the way for smart learning. However, as the non-face-to-face teaching method was suddenly implemented as a whole due to the COVID-19 pandemic, online education has rapidly developed and also faced various problems to improve the quality of education. By analyzing and reviewing the trend, this study discussed the problems facing the current revolutionary period and what needs to be solved for future development.

• The Southeast Asian review
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• v.28 no.4
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• pp.223-252
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• 2018

The purpose of this paper is to substantially analyse the patterns of complements considering the aspects of not only syntax but also morphology since the concept of complement has been used as a term to analyse the components of a sentence. However, it cannot be denied that there seemed to be limitations due to the partial explanation or different explanations of the same sentence. Thus, this paper aims at dealing with the close relation between sentential components and suffixes to examine the sentence patterns; subject, predicate, object, complement, and adjunct focusing on the terms of complement which has been seen problematic due to incomplete explanations and different interpretations of the same sentence. Finally, this paper synthesises various opinions of many scholars and integrates them to get explicit and practical patterns of complement of a sentence based on not only syntax but also morphology through close relation between sentential components and morphological suffixes.

• International Journal of Computer Science & Network Security
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• v.21 no.12
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• pp.137-142
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• 2021

Distance learning universities provide online course content. The main methods of providing class contents are on-demand and live-streaming. This means that students are not restricted by time or space. The advantage is that students can take the course anytime and anywhere. Therefore, unlike commuting students, there is no commuting time to the campus, and there is no natural process required to take classes. However, despite this convenient situation, the attendance rate and graduation rate of distance learning universities tend to be lower than that of commuting universities. Although the course environment is not the only factor, students cannot obtain a bachelor's degree unless they fulfill the graduation requirements. In both commuter and distance learning universities, taking classes is an important factor in earning credits. There are fewer time and space constraints for distance learning students than for commuting students. It is also easy for distance learning students to take classes at their own timing. There should be more ease of learning than for students who commute to school with restrictions. However, it is easier to take a course at a commuter university that conducts face-to-face classes. I thought that the reason for this was that commuting to school was a part of the process of taking classes for commuting students. Commuting to school was thought to increase the willingness and motivation to take classes. Therefore, I thought that the inconvenient constraints might encourage students to take the course. In this research, I focused on the act of commuting to school by students. These situations are also applied to the distance learning environment. The students have physical time constraints. To achieve this goal, I will implement a course restriction method that aims to promote the willingness and attitude of students. Therefore, in this paper, I have implemented a virtual school system called "virtual go to school (VG2S)" that reflects the actual route to school.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.2
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• pp.201-211
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• 2022

According to the recent change in the cybersecurity paradigm, research on anomaly detection methods using machine learning and deep learning techniques, which are AI implementation technologies, is increasing. In this study, a comparative study on data preprocessing techniques that can improve the anomaly detection performance of a GRU (Gated Recurrent Unit) neural network-based intrusion detection model using NGIDS-DS (Next Generation IDS Dataset), an open dataset, was conducted. In addition, in order to solve the class imbalance problem according to the ratio of normal data and attack data, the detection performance according to the oversampling ratio was compared and analyzed using the oversampling technique applied with DCGAN (Deep Convolutional Generative Adversarial Networks). As a result of the experiment, the method preprocessed using the Doc2Vec algorithm for system call feature and process execution path feature showed good performance, and in the case of oversampling performance, when DCGAN was used, improved detection performance was shown.

• Journal of the Korea Society of Computer and Information
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• v.29 no.3
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• pp.11-20
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• 2024

Among the generative models in Artificial Intelligence (AI), especially Generative Adversarial Network (GAN) has been successful in various applications such as image processing, density estimation, and style transfer. While the GAN models including Conditional GAN (CGAN), CycleGAN, BigGAN, have been extended and improved, researchers face challenges in real-world applications in specific domains such as disaster simulation, healthcare, and urban planning due to data scarcity and unstable learning causing Image distortion. This paper proposes a new progressive learning methodology called Progressive Step Training (PST) based on the Auxiliary Classifier GAN (ACGAN) that discriminates class labels, leveraging the progressive learning approach of the Progressive Growing of GAN (PGGAN). The PST model achieves 70.82% faster stabilization, 51.3% lower standard deviation, stable convergence of loss values in the later high resolution stages, and a 94.6% faster loss reduction compared to conventional methods.