• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권6호
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• pp.2709-2729
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• 2016

Representation based classification, kernel method and sparse representation have received much attention in the field of face recognition. In this paper, we proposed an improved kernel principal component analysis method based on sparse representation to improve the accuracy and robustness for face recognition. First, the distances between the test sample and all training samples in kernel space are estimated based on collaborative representation. Second, S training samples with the smallest distances are selected, and Kernel Principal Component Analysis (KPCA) is used to extract the features that are exploited for classification. The proposed method implements the sparse representation under ℓ₂ regularization and performs feature extraction twice to improve the robustness. Also, we investigate the relationship between the accuracy and the sparseness coefficient, the relationship between the accuracy and the dimensionality respectively. The comparative experiments are conducted on the ORL, the GT and the UMIST face database. The experimental results show that the proposed method is more effective and robust than several state-of-the-art methods including Sparse Representation based Classification (SRC), Collaborative Representation based Classification (CRC), KCRC and Two Phase Test samples Sparse Representation (TPTSR).

• 한국컴퓨터정보학회논문지
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• 제23권11호
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• pp.75-84
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• 2018

Social engineering attack means to get information of Social engineering attack means to get information of opponent without technical attack or to induce opponent to provide information directly. In particular, social engineering does not approach opponents through technical attacks, so it is difficult to prevent all attacks with high-tech security equipment. Each company plans employee education and social training as a countermeasure to prevent social engineering. However, it is difficult for a security officer to obtain a practical education(training) effect, and it is also difficult to measure it visually. Therefore, to measure the social engineering threat, we use the results of social engineering training result to calculate the risk by system asset and propose a attack graph based probability. The security officer uses the results of social engineering training to analyze the security threats by asset and suggests a framework for quick security response. Through the framework presented in this paper, we measure the qualitative social engineering threats, collect system asset information, and calculate the asset risk to generate probability based attack graphs. As a result, the security officer can graphically monitor the degree of vulnerability of the asset's authority system, asset information and preferences along with social engineering training results. It aims to make it practical for companies to utilize as a key indicator for establishing a systematic security strategy in the enterprise.

• 컴퓨터교육학회논문지
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• 제20권4호
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• pp.37-46
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• 2017

2018년부터 중학교에서 필수로 실시되는 정보교육의 수준은 정보 컴퓨터 교사의 교과전문성에 의존한다. 본 연구는 중등 교사양성기관이 정보 컴퓨터 교사의 교과전문성을 담보하는 교육과정을 제공하고 있는지 분석하기 위한 목적이 있다. 목적 달성을 위해 첫째, 한국 중등 교사양성기관의 정보 컴퓨터 교사양성을 위한 교육과정 과목을 일본 정보학 분야 고등정보교육과정인 J07-CS의 내용체계를 기반으로 구성된 과목과 비교하였다. 둘째, 교육부에서 제시하는 기본이수과목과 비교하고 셋째, 각 대학의 기본이 수과목 개설 현황도 분석하였다. 연구 결과, 중등 교사양성기관에서 개설되는 정보관련 과목 수는 J07-CS의 과목 수와 비교하여 부족하였다. 비교기준을 기본이수과목으로 한정해도 내용요소가 부족하였고, 교사양성기관별 기본이수과목의 개설 비율도 낮았다. 2018년부터 실시되는 정보교육의 목표를 원활이 달성하기 위해서는 중등 교사양성기관의 교육과정에 대한 개선이 시급하다.

• 경영과학
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• 제14권2호
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• pp.161-184
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• 1997

This research examines the importance of IT training/education, present situation and possible suggestion for the successful training/education. The research method adopts a comparative analytical approach based on questionnaire survey responses from three work groups - managers, employees, and union representatives - drawn from five sample Korean banks. The evidence indicates that all three groups agree that IT improves banking efficiency and reduces job repetitiveness, but their job satisfaction level with IT-based work is surprisingly very low. The main reasons are mainly lack of training/education and poor user manuals. Also the research shows that most respondents would like to get further training/education to more adequately fit them for their jobs. Those from banks which invested in continuing training/education revealed more positive work attitudes and higher job satisfaction.

• 한국멀티미디어학회논문지
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• 제22권1호
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• pp.44-54
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• 2019

Recently, image-based object detection has made great progress with the introduction of Convolutional Neural Network (CNN). Many trials such as Region-based CNN, Fast R-CNN, and Faster R-CNN, have been proposed for achieving better performance in object detection. YOLO has showed the best performance under consideration of both accuracy and computational complexity. However, these data-driven detection methods including YOLO have the fundamental problem is that they can not guarantee the good performance without a large number of training database. In this paper, we propose a data sampling method using CycleGAN to solve this problem, which can convert styles while retaining the characteristics of a given input image. We will generate the insufficient data samples for training more robust object detection without efforts of collecting more database. We make extensive experimental results using the day-time and night-time road images and we validate the proposed method can improve the object detection accuracy of the night-time without training night-time object databases, because we converts the day-time training images into the synthesized night-time images and we train the detection model with the real day-time images and the synthesized night-time images.

• 한국정보시스템학회지:정보시스템연구
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• 제31권1호
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• pp.1-24
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• 2022

Purpose The purpose of this study is to investigate the factors that affect the user satisfaction and continuous use intention of the improved ATCIS in the Korean Army. Design/methodology/approach Based on the various theories in relation to IT continuance, user satisfaction was identified as the main factor with regard to the continuous use intention of the improved ATCIS. In addition, computer self-efficacy, education-training, and system quality were hypothesized as antecedent variables to user satisfaction, and information security stress was set as a moderating variable for these relationships. Findings Survey results show that computer self-efficacy, education and training, and system quality had a positive effect on user satisfaction, and information security stress was found to moderate these relationships. The effects of computer self-efficacy and education-training on user satisfaction were higher in the group with low information security stress. However, the relationship between system quality and user satisfaction was higher in the group with high information security stress. User satisfaction is found to have a positive effect on the continuous use intention even with habit considered as a control variable.

• 한국컴퓨터게임학회논문지
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• 제31권4호
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• pp.111-119
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• 2018

국가기관과 기업은 정비사를 양성을 위한 고등학교부터 대학교, 기업 훈련센터 같은 교육기관을 만들어 숙련된 정비사로 훈련시키려고 많은 노력을 하고 있다. 하지만 교재를 이용한 이론교육과 현장에서 사용하지 않는 장비를 이용한 실습교육으로는 제대로 된 정비교육을 진행하지 못하며 특수장비를 활용한 교육이나 위험한 상황을 가정한 정비의 교육은 매우 위험하여 영상이나 사진으로 교육을 진행하고 있었다. 최근에는 VR과 AR을 접목하여 단순정비에서 특수정비까지 시뮬레이션으로 안전하게 상황을 체험하고 문제를 해결하는 효과적인 교육 시뮬레이션이 연구되고 개발되는 사례가 많이 있다. 본 논문에서는 다누리 VR과 DisTi Engine, Remote AR을 비교분석하고, 유니티 엔진 기반으로 외부에서 전달된 정보를 기반으로 콘텐츠를 디바이스 화면에 최적화하여 출력하는 AR API를 소개하고, VR 디바이스인 HTC Vive의 컨트롤러와 HMD의 정보를 실시간으로 수집하고 수집된 정보를 파일에 저장하는 VR API를 구현한 사례를 소개했다. 본 연구에서 구현한 API를 사용하면 콘텐츠를 제작할 때 도움을 줄 수 있을 것이다.

• International Journal of Computer Science & Network Security
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• 제22권4호
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• pp.387-393
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• 2022

The article reflects short-term perspectives on the use of information and communication technologies in the training of teachers for higher education. Education is characterized by conservatism, so aspects of systematic development of the industry are relevant to this cluster of social activity. Therefore, forecasting the introduction of innovative elements of ICT training is in demand for the educational environment. Forecasting educational trends are most relevant exactly in the issues of training future teachers of higher education because these specialists are actually the first to implement the acquired professional skills in pedagogical activities. The article aims to consider the existing potential of ICT-based learning, its implementation in the coming years, and promising innovative educational elements that may become relevant for the educational space in the future. The tasks of scientific exploration are to show the optimal formats of synergy between traditional and innovative models of learning. Based on already existing experience, extrapolation of conditions of educational process organization with modeling realities of using information and communication technologies in various learning dimensions should be carried out. Educational trends for the next 3 years are a rather tentative forecast because, as demonstrated by the events associated with the COVID-19 pandemic, the socio-cultural space is very changeable. Consequently, the dynamism of the educational environment dictates the need for a value-based awareness of the information society and the practical use of technological advances. Thus, information and communication technologies are a manifestation of innovative educational strategies of today and become an important component along with traditional aspects of educational process organization. Future higher education teachers should develop a training strategy taking into account the expediency of the ICT component.

• 한국컴퓨터정보학회논문지
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• 제25권11호
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• pp.9-16
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• 2020

TA-50 항공기는 공중전에 대비하여 공대공, 공대지 사격 훈련 등 다양한 상황에 대한 모의 훈련을 수행하고 있다. 또한 조종사의 실전 배치 전 훈련용으로도 사용되고 있다. 그러나 TA-50은 스마트 무장 운용 능력을 보유하고 있지 않아 훈련에 제한이 되고 있다. 이에 본 연구에서는 TA-50 항공기에 스마트 무장 중 하나인 합동정밀직격탄(JDAM)의 가상훈련이 가능하도록 구현하고자 하였다. 먼저, TA-50 항공기와 유사한 기종인 FA-50 항공기에 구현된 JDAM 기능을 분석하였다. 또한 FA-50 항공기에 구현된 기능은 소스코드의 직접 활용이 불가능하므로 머신러닝 기법(TensorFlow)을 활용하여 알고리즘을 추출하였다. 본 기능을 구현함으로써 실 무장을 장착하지 않아도 실제와 유사한 훈련이 가능할 것으로 기대된다. 마지막으로 본 연구 결과를 바탕으로 연구의 한계점을 보완하여 실제와 동일하게 구현할 수 있는 방안을 제안하고자 한다.

• Journal of Information Processing Systems
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• 제14권6호
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• pp.1464-1479
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• 2018

In face recognition, sometimes the number of available training samples for single category is insufficient. Therefore, the performances of models trained by convolutional neural network are not ideal. The small sample face recognition algorithm based on novel Siamese network is proposed in this paper, which doesn't need rich samples for training. The algorithm designs and realizes a new Siamese network model, SiameseFacel, which uses pairs of face images as inputs and maps them to target space so that the $L_2$ norm distance in target space can represent the semantic distance in input space. The mapping is represented by the neural network in supervised learning. Moreover, a more lightweight Siamese network model, SiameseFace2, is designed to reduce the network parameters without losing accuracy. We also present a new method to generate training data and expand the number of training samples for single category in AR and labeled faces in the wild (LFW) datasets, which improves the recognition accuracy of the models. Four loss functions are adopted to carry out experiments on AR and LFW datasets. The results show that the contrastive loss function combined with new Siamese network model in this paper can effectively improve the accuracy of face recognition.