• Journal of Information Display
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• v.8 no.3
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• pp.29-33
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• 2007

The temporal dark image sticking phenomena are examined and compared for the two different electrode structures such as the face-to-face and coplanar sustain electrode structure. To compare the temporal dark image sticking phenomena for both structures, the differences in the infrared emission profile, luminance, and perceived luminance of the image sticking cells and the non image sticking cells were measured. It is observed that the temporal dark image sticking is mitigated for the face-to-face structure. The mitigation of the temporal dark image sticking for the face-to-face structure is due to the slight increase in the panel temperature induced by the ITO-less electrode structure.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.5
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• pp.33-40
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• 2004

In this paper, we constructs face database by using wavelet comparison, and compare face recognition rate by using principle component analysis (Principal Component Analysis : PCA) algorithm. General face recognition method constructs database, and do face recognition by using normalized size. Proposed method changes image of normalized size (92${\times}$112) to 1 step, 2 step, 3 steps to wavelet compression and construct database. Input image did compression by wavelet and a face recognition experiment by PCA algorithm. As well as method that is proposed through an experiment reduces existing face image's information, the processing speed improved. Also, original image of proposed method showed recognition rate about 99.05%, 1 step 99.05%, 2 step 98.93%, 3 steps 98.54%, and showed that is possible to do face recognition constructing face database of large quantity.

• 한국HCI학회:학술대회논문집
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• 2008.02c
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• pp.172-177
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• 2008

Biometrics is essential for person identification because of its uniqueness from each individuals. Face recognition technology has advantage over other biometrics because of its convenience and non-intrusive characteristics. In this paper, we will present a overview of face recognition technology including face detection, feature extraction, and face recognition system. For face detection, we will describe template based method and face component based approach. PCA and LDA approach will be discussed for feature extraction, and nearest neighbor classifiers -will be covered for matching. Large database and the standardized performance evaluation methodology is essential in order to support state-of-the-art face recognition system. Also, 3D based face recognition technology is the key solution for the pose, lighting and expression variations in many applications.

• 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 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.

• 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.

• Journal of Korea Multimedia Society
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• v.24 no.1
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• pp.125-133
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• 2021

Due to Covid-19, the un-contact culture has affected society as a whole, and the methods of education conducted offline has been greatly affected. In the private education of preparing for university entrance, the public official examinations and certification acquisition, the method of online education has been shown to have positive effects. While private class and school class which have offered in off-line to cope with rapid changes caused various problems such as decline in quality for education. Due to the characteristic of design class, practical training is important. As interactive feedback between students and educators is more important than one-way of delivering knowledge while class is conducted in online, educators have a challenge when they prepare for class. This study handles the methods of online education for the purpose of practical education methods in university nowadays, Especially, the non-face-to-face education methods for game animation production. Based on this study, I propose an effective educational method with non-face-to-face class that allows students to be satisfied and increases their knowledge, beyond face-to-face class.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.319-331
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• 2022

The latest global COVID-19 pandemic has made the use of facial masks an important aspect of our lives. People are advised to cover their faces in public spaces to discourage illness from spreading. Using these face masks posed a significant concern about the exactness of the face identification method used to search and unlock telephones at the school/office. Many companies have already built the requisite data in-house to incorporate such a scheme, using face recognition as an authentication. Unfortunately, veiled faces hinder the detection and acknowledgment of these facial identity schemes and seek to invalidate the internal data collection. Biometric systems that use the face as authentication cause problems with detection or recognition (face or persons). In this research, a novel model has been developed to detect and recognize faces and persons for authentication using scale invariant features (SIFT) for the whole segmented face with an efficient local binary texture features (DLBP) in region of eyes in the masked face. The Fuzzy C means is utilized to segment the image. These mixed features are trained significantly in a convolution neural network (CNN) model. The main advantage of this model is that can detect and recognizing faces by assigning weights to the selected features aimed to grant or provoke permissions with high accuracy.

• Educational Technology International
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• v.8 no.2
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• pp.53-71
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• 2007

This study identified the effectiveness of e-learning by comparing learning outcome in conventional face-to-face lecture with the selected e-learning methods. Two e-learning contents (animation based and video based) were developed based on the rapid prototyping model and loaded onto the learning management system (LMS), which is http://www.enaged.co.kr. Fifty-four Korean agricultural high school students were randomly assigned into three groups (face-to-face lecture, animation based e-learning, and video based e-learning group). The students of the e-learning group logged on the LMS in school computer lab and completed each e-learning. All students were required to take a pretest and posttest before and after learning under the direction of the subject teacher. A one-way analysis of covariance was administered to verify whether there was any difference between face-to-face lecture and e-learning in terms of students' learning outcomes after controlling the covariate variable, pretest score. According to the results, no differences between animation based and video based e-learning as well as between face-to-face learning and e-learning were identified. Findings suggest that the use of well designed e-learning could be worthy even in agricultural education, which stresses hands-on experience and lab activities if e-learning was used appropriately in combination with conventional learning. Further research is also suggested, focusing on a preference of e-learning content type and its relationship with learning outcome.