• The Journal of Sustainable Design and Educational Environment Research
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• v.15 no.2
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• pp.1-12
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• 2016

This study was conducted to extract the student-centered experiential safety education activities in order to establish safety-experience-education-facilities based on "School safety education 7 standards" announced by the Ministry of Education in 2015. For this purpose, we established the concept of safety-experience-education-facilities, and conducted surveys twice targeting experts of each 7 fields based on the learned results of 758 sessions through "School safety education 7 standards". First, through the surveys, it was organized by 150 sessions out of 758 education class that extracted from safety-education-program sessions on experts, conducted a second expert survey for the validation of selected educational programs in Delphi format, the result of 5 sessions of the program is deleted, and 145 sessions was surveyed to be maintained. It was ascertained that 145 sessions of education program, 21 sessions of life safety area, 22 sessions of traffic safety area, 18 sessions of violence and personal safety area, 5 sessions of drugs and cyber addiction area, 36 sessions of disaster safety area, 10 sessions of occupation safety area, 33 sessions of first-aid area, is the experiential safety education activities that have to be applied to the safety-experience-education-facilities.

• Journal of the Korea Convergence Society
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• v.6 no.6
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• pp.293-299
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• 2015

MOOC (Massive Open Online Course) is an online course aimed at limited participation and open access via the web. There is even the prospect that MOOC may break down the existing university system and open a new horizon of education. However, MOOC is going differently from the first prospect that it would threat the existing higher education institutions. So this study wishes to provide a starting point of discussion that we can produce and utilize MOOC to fit our situation of higher education by revealing the inherent problems of MOOC. MOOC is a basically online education, so that it cannot help inheriting the essential weakness of the existing one: the interaction, supervision and evaluation. The newly added concept 'massive' raises the problem of class size which is the most sensitive part in the field of education. The concept 'open' reverses a customized education because MOOC is a kind of video clips of a lecture for unspecific massive learners. As a conclusion, we predicts that MOOC will be positioned as a higher education service for very prominent learners in self-led learning ability and people who cannot access even traditional online higher education institutions. Also MOOC is highly likely to be used as a means of Flipped Learning in universities. Therefore, considering these points in the future, we need to develop MOOC to suit these targets.

• Journal of Digital Contents Society
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• v.13 no.3
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• pp.393-399
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• 2012

New and creative skills must be developed, and adapted into a lesson, to motivate learners to acquire a second language easily and enjoyment, Multimedia tools which are of interest to learners, such as; smart phones, computers, and notebooks with wireless internet compatability, will provide learners opportunities to study, and do their work practically anywhere and anytime. Recently, podcasts, which are a type of digital media, consisting of a series of audio episodes or video files, subscribed to and downloaded through web syndication, or streamed online to a computer or mobile device, are used to facilitate ESL (English as a Second Language) learning. Development of a variety of teaching methods, using multimedia tools, is needed. There are advantages and disadvantages to using a variety of multimedia tools. The current research aims to study its characteristics and application, in order to maximize their effective use, in English education. The current study suggests a ubiquitous learning environment using multimedia content tools, internet media, video teleconferencing, cyber-learning, and one-to-one videos used in conjunction with, or as a digital textbook for the English lesson. This study also investigates future educational changes, using state-of-the-art equipment for the self-learning experience, and will present a new direction in English education, through a variety of instructional devices and a marginalized class system model.

• Journal of Digital Contents Society
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• v.4 no.2
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• pp.167-179
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• 2003

It has been widely researched in many studies what is the most effective way to learn English as a second language. It has been generally accepted that the most effective teaching method is to make students interested in learning of English. Teaching method has to be modified with the change of the times according to the demand of the students. The purpose of this study is to reveal that language teaming method through internet could be more effective than that of the existing teaching one by offline loaming. For this purpose some subject students were divided by two groups of the experimental and of the controlled. From the result of the study it could be derived that teaching method, by means of cyber lecture, make a great effect not only on the attitude but on the achievement of the students when they are in the class of English as a second language. This paper also shows what could be the typical model for the teaching method by internet based on the experiment. This kind of way of teaching is supported by the questionnaire which has much more positive response from the students who were in the member of experimental group. Finally such a experiment would be described based on the Web-oriented teaching method with the respect of education of digital contents.

• Journal of Internet Computing and Services
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• v.22 no.2
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• pp.29-39
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• 2021

As damages to individuals, private sectors, and businesses increase due to newly occurring cyber attacks, the underlying network security problem has emerged as a major problem in computer systems. Therefore, NIDS using machine learning and deep learning is being studied to improve the limitations that occur in the existing Network Intrusion Detection System. In this study, a deep learning-based NIDS model study is conducted using the Convolution Neural Network (CNN) algorithm. For the image classification-based CNN algorithm learning, a discrete algorithm for continuity variables was added in the preprocessing stage used previously, and the predicted variables were expressed in a linear relationship and converted into easy-to-interpret data. Finally, the network packet processed through the above process is mapped to a square matrix structure and converted into a pixel image. For the performance evaluation of the proposed model, NSL-KDD, a representative network packet data, was used, and accuracy, precision, recall, and f1-score were used as performance indicators. As a result of the experiment, the proposed model showed the highest performance with an accuracy of 85%, and the harmonic mean (F1-Score) of the R2L class with a small number of training samples was 71%, showing very good performance compared to other models.

• Journal of the Korea Society of Computer and Information
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• v.26 no.6
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• pp.73-80
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• 2021

In this paper, we propose a packet processing method capable of handling large-capacity traffic over 20Gbps using multi-core and huge page memory approaches. As ICT technology advances, the global average monthly traffic is expected to reach 396 exabytes by 2022. With the increase in network traffic, cyber threats are also increasing, increasing the importance of traffic analysis. Traffic analyzed as an existing high-cost foreign product simply stores statistical data and visually shows it. Network administrators introduce and analyze many traffic analysis systems to analyze traffic in various sections, but they cannot check the aggregated traffic of the entire network. In addition, since most of the existing equipment is of the 10Gbps class, it cannot handle the increasing traffic every year at a fast speed. In this paper, as a method of processing large-capacity traffic over 20Gbps, the process of processing raw packets without copying from single-core and basic SMA memory approaches to high-performance packet reception, packet detection, and statistics using multi-core and NUMA memory approaches suggest When using the proposed method, it was confirmed that more than 50% of the traffic was processed compared to the existing equipment.

• 한국노년학
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• v.40 no.1
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• pp.1-21
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• 2020

The purpose of this study is to examine that basic pension entitlement affects the subjective well-being(SWB) of the elderly. For controlling unobserved heterogeneity, we used fixed effects model for longitudinal data. The data used for this study is KLoSA from 2006 to 2016. The research results are as follows. SWB of non-basic pensioners was higher than for basic pension beneficiaries. Second, when the demographic variables were controlled, SWB of the basic pension recipients was higher then that of non-beneficiaries. Third, the factors affecting SWB were economic satisfaction, marital status, family financial support, employment status, subjective health status, daily life restrictions, gender, and age. Fourth, the effect of basic pension on SWB was positive at the lowest income quartile. The results of this study shows that the basic pension system has a positive effect on the SWB of elderly despite the low benefit level. Therefore, it is necessary to expand the basic pension system to solve poverty problems and improve the quality of life for the aged. Also, various aspects of social support for the low-income vulnerable elderly are needed. Lastly, It was suggested that the benefit level of the basic pension should be raised to have a substantial effect on the low-income class, which is a key policy subject.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.3
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• pp.1100-1118
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• 2021

In a wide range of ML applications, the training data contains privacy-sensitive information that should be kept secure. Training the ML systems by privacy-sensitive data makes the ML model inherent to the data. As the structure of the model has been fine-tuned by training data, the model can be abused for accessing the data by the estimation in a reverse process called model inversion attack (MIA). Although, MIA has been applied to shallow neural network models of recognizers in literature and its threat in privacy violation has been approved, in the case of a deep learning (DL) model, its efficiency was under question. It was due to the complexity of a DL model structure, big number of DL model parameters, the huge size of training data, big number of registered users to a DL model and thereof big number of class labels. This research work first analyses the possibility of MIA on a deep learning model of a recognition system, namely a face recognizer. Second, despite the conventional MIA under the white box scenario of having partial access to the users' non-sensitive information in addition to the model structure, the MIA is implemented on a deep face recognition system by just having the model structure and parameters but not any user information. In this aspect, it is under a semi-white box scenario or in other words a gray-box scenario. The experimental results in targeting five registered users of a CNN-based face recognition system approve the possibility of regeneration of users' face images even for a deep model by MIA under a gray box scenario. Although, for some images the evaluation recognition score is low and the generated images are not easily recognizable, but for some other images the score is high and facial features of the targeted identities are observable. The objective and subjective evaluations demonstrate that privacy cyber-attack by MIA on a deep recognition system not only is feasible but also is a serious threat with increasing alert state in the future as there is considerable potential for integration more advanced ML techniques to MIA.