• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.2
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• pp.252-258
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• 2007

In this paper, a face recognition algorithm system using Principal Component Analysis (PCA) is proposed. The algorithm recognized a person by comparing characteristics (features) of the face to those of known individuals of Intelligent Control Laboratory (ICONL) face database. Simulations are carried out to investigate the algorithm recognition performance, which classified the face as a face or non-face and then classified it as known or unknown one. Particularly, a Principal Components of Linear Discriminant Analysis (PCA + LDA) face recognition algorithm is also proposed in order to confirm the recognition performances and the adaptability of a proposed PCA for a certain specific system.

• Proceedings of the Korean Geotechical Society Conference
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• 2000.03b
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• pp.457-464
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• 2000

Stereographic method is a general and basic method to analyse sliding failure potential of rock slope. Region of failure analysis using stereographic method extend to curved slope from straight slope in this paper, Curved slope is defined as the multi-face slope with free surface more than two face and has different characteristics from straight single face slope. Individual daylight envelopes of free surfaces are combined into total daylight envelope of multi-face slope. So, sliding envelope of multi-face slope is the daylight envelope except friction cone. Specially, If only single joint set is developed in the slope, single plane sliding(or plane failure) is impossible in the single-face straight slope, but possible in the multi-face slope. In the multi-face slope with only one joint set, single plane sliding occurs when orientation of sliding plane is between two side slope orientation in the sliding envelope.

• Smart Media Journal
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• v.7 no.4
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• pp.61-69
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• 2018

Multi-tracking of general objects and specific faces is an important topic in the field of computer vision applicable to many branches of industry such as biometrics, security, etc. The rapid development of deep neural networks has resulted in a dramatic improvement in face recognition and object detection problems, which helps improve the multiple-face tracking techniques exploiting the tracking-by-detection method. Our proposed method uses face detection trained with a head dataset to resolve the face deformation problem in the tracking process. Further, we use robust face features extracted from the deep face recognition network to match the tracklets with tracking faces using Hungarian matching method. We achieved promising results regarding the usage of deep face features and head detection in a face tracking benchmark.

• Journal of Korea Society of Digital Industry and Information Management
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• v.17 no.3
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• pp.121-132
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• 2021

The purpose of this study is to explore ways to improve the quality of real-time video lectures in a non-face-to-face environment using IPA (Importance-Performance Analysis). Recently, due to the impact of COVID-19 in universities, all remote classes are being implemented, so research is needed to raise learner awareness. Accordingly, factor analysis, mean analysis, correspondence analysis, and IPA analysis were performed based on the data of 632 students who responded from March 21 to June 30, 2021 for learners of K University in Chungbuk. First, overall satisfaction was low compared to importance, and the difference in system perception was the largest. Second, the difference in learner perception of real-time video lectures through the IPA matrix showed that the system error and screen cutoff were the largest. Third, the difficulty of lecture content, task and test feedback, etc. are classified. Accordingly, the satisfaction of real-time video lectures in non-face-to-face environments is low, suggesting that school-level support for quality improvement to improve learner satisfaction in non-face-to-face environments and the role of instructors are needed to improve learners' academic achievement.

• Steel and Composite Structures
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• v.19 no.2
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• pp.485-501
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• 2015

Channels are implemented in composite beams as shear connectors in two arrangements, face to face and back to back. No relevant explanation is found in the design codes to clarify the preference of the mentioned arrangements. Besides, the designers do not have a common opinion on this subject; i.e., some recommend the face to face and others, back to back status. In this research, channel shear connectors in composite beams are studied analytically for both arrangements using ABAQUS software. For this purpose, they have been modeled in simply supported beams in the arrangements of face to face and back to back; their effects on the crack initiation load of concrete slabs were monitored. The stiffness values of composite beams were also compared in the two arrangements using force-displacement curve; the results are relatively the same in both cases. Furthermore, the effects of compressive strength of concrete, channel size, length and spacing of channels as well as steel type of channels on the performance of composite beams have been investigated. According to the results obtained in this research, the face to face status shows better performance in comparison with that of back to back, considering the load of concrete fracturing.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.5
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• pp.1055-1062
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• 2021

As face-to-face education becomes difficult due to the spread of COVID-19, the use of e-learning content and virtual training is increasing. In the case of information security education, practice to learn response techniques is important, so simulation hacking and vulnerability analysis activities have been supported as virtual training for a long time. In order to increase the educational effect, contents should be designed similar to real situation, and learning activities to achieve the learning goals should be designed. In addition, excellent functions and scalability of the system supporting learning activities are required. The researcher developed an LMS evaluation index that supports non-face-to-face education by considering the key elements of non-face-to-face education and training. The developed evaluation index was applied to the information security education platform to verify its practical utility.

• Journal of muscle and joint health
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• v.25 no.3
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• pp.218-229
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• 2018

Purpose: The purpose of this study is to investigate relationships among workplace face to face bullying, cyber bullying, self-esteem, and turnover intention of hospital nurses, and to identify affecting factors for turnover intention through their relationships. Methods: Data were collected from 178 hospital nurses by self-reported questionnaire. The relationship among variables were analyzed with Pearson's coefficient correlation and affecting factors for turnover intention were identified by using multiple linear regression. Results: The mean score of turnover intention was $3.55{\pm}0.94$. Turnover intention was significantly different by age, marriage status, educational background, total experience as a nurse, designation, health status, bullying experience, and bullied experience. Turnover intention had positive relationships with workplace face to face bullying and hospital size, but negative relationships with self-esteem and health status. Workplace face to face bullying, health status and hospital size were identified as influencing factors in turnover intention. Conclusion: It is necessary to nursing community's efforts to decrease face to face bullying in order to lower the turnover intention of nurses. In this regard workplace bullying among nurses should be addressed using a comprehensive strategy that considers both individual and organizational factors. It is also necessary to nurse 's efforts to increase self-esteem.

• The Journal of Korean Academy of Orthopedic Manual Physical Therapy
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• v.27 no.1
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• pp.1-11
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• 2021

Background: The purpose of this study is to identify the elements for the construction of the Korean academy of orthopedic manipulative physical therapy's (KAOMPT's) non-face-to-face lecture system using the Delphi method. Methods: The Delphi method was applied to 50 expert panel members of the Central Committee and the Provincial Branch of the KAOMPT. The Delphi survey was conducted in two rounds, and the first Delphi survey collected opinions on 40 questions on 12 topics. The second Delphi survey was collected into 25 questions on 4 topics. As a result of the survey, the content validity ratio (CVR), consensus and convergence were measured. Referring to the number of expert panels and previous studies were determine a CVR of at least 2.29, a consensus of at least .75 and a convergence of 0 to .5. Result: In the first Delphi result, out of the total 40 items, 20 items with high content validity ratio were found, and 10 items found double agreement. In the second Delphi result, 13 out of the total 25 items had a content validity ratio higher than 2.29, and 5 items found a double agreement. Conclusion: This study derived items on the role of central and municipal councils, lecture support and lecture room construction, non-face regular course and special lecture operation and personnel for the establishment of non-face-to-face lecture system. Based on this content, it is expected that it will help establish a non-face-to-face lecture system in 2021 through a pilot non-face-to-face lecture that will be implemented in the future.

• Journal of Information Technology Services
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• v.10 no.2
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• pp.259-269
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• 2011

The B$\'{e}$k$\'{e}$sy audiometer is used to determine not only hearing threshold but also assumption of recruit phenomenon and cause of disease. However, current B$\'{e}$k$\'{e}$sy audiometer takes an operational model, so called face-to-face model, in which model one audiometrist can assess only one subject at a time. As a result, the face-to-face model leads to high audiometrist's labor cost and long waiting time when there exist many subjects. To improve such weakness, this paper extends PC based B$\'{e}$k$\'{e}$sy audiometer to support client/server model in which model one audiometrist enables to concurrently access several subjects. As providing capabilities such as real-time transfer of assessment result, video monitoring of subject and video chat, the same effect as face-to-face model but overcomes weakness of face-to-face model.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.2C
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• pp.194-199
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• 2009

This paper proposes a face detection algorithm that uses geometrical information on face and hair region. This information that face adjoins hair regions can be the important one for face detection. It is also kept in images with frontal, rotated and lateral face. The face candidates are founded by the analysis of skin regions after detecting the skin and hair color regions in an image. Next, the intersected lesions between face candidates and hair's are created. Finally, the face candidates that include the subsets of these regions turn out to be face. Experimental results showed the high detection rates for frontal and lateral faces as well as faces geometrically distorted.