• International Journal of Contents
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• v.10 no.2
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• pp.18-27
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• 2014

This study examines underlying factors that influence undergraduate students' willingness to enhance communication with their instructor by comparing the frequency of e-mail and face-to-face interaction between students and instructors. Data was collected through a survey of 322 undergraduate journalism students at a large Midwestern university. The findings showed that the more passive students were in expressing their opinion during the class, the less likely they were to send e-mails to their instructor (Coef. = -0.180, p < .01) or to communicate with their instructor face-to-face (Coef. = -0.262, p < .01). The findings also showed that the more students described their personality as "shy," the less likely they were to e-mail their instructor (Coef. = -0.157, p < .05) or communicate with their instructor face-to-face (Coef. = -0.210, p < .01). It is noteworthy that the degrees of both passivity and shyness had a more negative effect on the probability of face-to-face interaction than they did on email interaction. In summary, email usage follows similar broader patterns of social interaction, rather than introducing a different trend in communication. This finding implies that the importance of e-mail should not be exaggerated as a communication tool for reticent students.

• The Research Journal of the Costume Culture
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• v.12 no.5
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• pp.757-768
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• 2004

This study was aimed to provide the fundamental and various measurement data of the head and face for Korean children. Two hundred sixty nine female children, aged nine to twelve years, participated for this study. The 28 regions on the head and face of the subjects were directly measured by the expert experimenters. Factor analysis, cluster analysis, GLM analysis and Tukey HSD test were performed' using these data. Through factor analysis, six factors were extracted upon factor scores and those factors comprised 71.42% for the total variances. Four clusters as their head and face shape were categorized using six factor scores by cluster analysis. Type 1 was characterized by the shorter head & face length and width and the lowest position from forehead to nose. Type 2 had the longer head & face length and width and the highest ear position and the largest mouse width. Type 3 was characterized by the longest and head & face type and the widest head & face girth. Type 4 was characterized by shortest head & face length the lower ear and lips position.

• Knowledge Management Research
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• v.21 no.2
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• pp.119-135
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• 2020

Owing to pandemic (COVID-19), the traditional face-to-face education method has been changed to the non-face-to-face real-time online education methods. Using a real time-based video conference system, synchronous education can be adopted by face-to-face class easily. Specially, it is very important to minimize the difference in learning effects between face-to-face and non-face-to-face in Entrepreneurship education. In this study, in order to derive the factors that affect the satisfaction of learners in synchronous online education, authors collected data from learners taking a synchronous entrepreneurship course. Through previous research, learned the reality of education and the composition of lessons. Spatiotemporal effectiveness, mentor ability, and educational environment influence learning satisfaction. PLS-SEM results revealed that it was confirmed that only spatiotemporal effects affect learner satisfaction. However, the education environment (fluent operation and convenience of function use of real-time based online conference system) effect teaching presence, class structure, and spatiotemporal effects. Through this research, we hope to provide theoretical and practical support for developing effective teacher activities, proper lesson structure, convenient function of the conference system, and learner-centered online learning environment when developing synchronous online classes.

• Journal of Information Technology Services
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• v.6 no.3
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• pp.241-249
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• 2007

This paper describes a real-time face tracking system using effective detector and Kalman filter. In the proposed system, an image is separated into a background and an object using a real-time updated face color for effective face detection. The face features are extracted using the five types of simple Haar-like features. The extracted features are reinterpreted using Principal Component Analysis (PCA), and interpreted principal components are used for Support Vector Machine (SVM) that classifies the faces and non-faces. The moving face is traced with Kalman filter, which uses the static information of the detected faces and the dynamic information of changes between previous and current frames. The proposed system sets up an initial skin color and updates a region of a skin color through a moving skin color in a real time. It is possible to remove a background which has a similar color with a skin through updating a skin color in a real time. Also, as reducing a potential-face region using a skin color, the performance is increased up to 50% when comparing to the case of extracting features from a whole region.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.5
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• pp.205-216
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• 2020

This study seeks to empirically analyze the effects of core self-evaluation and adaptive selling behavior on sales performance for female salespersons engaged in door-to-door sales through the face-to-face channel in the wellness industry. This study seeks to examine the importance of adaptive selling, through, salespeople derive appropriate strategies in response to market changes. For female salespeople who use face-to-face channels, this study empirically investigated the relationship between core self-evaluation and adaptive selling, and effects on sales performance. A 31-item survey was constructed, based on prior research. We selected six door-to-door sales companies in South Korea and conducted one-to-one interviews with female salespeople in the Seoul metropolitan area and analyzed 208 pieces of significant data. Results demonstrated that among the core self-evaluation factors for female salespeople, self-esteem, self-efficacy, and neuroticism had an effect on adaptive selling factors, while locus of control did not. These factors were found to affect sales performance through the mediating role of adaptive selling. Improvements in the adaptive selling capabilities of female salespeople in charge of face-to-face channels positively affected sales performance. Management efforts are required to enhance self-esteem, self-efficacy, or neuroticism. These results suggest that companies should support enhancing individual adaptive selling capabilities of their salespeople.

• Journal of the Korean Society of Clothing and Textiles
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• v.21 no.8
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• pp.1287-1296
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• 1997

The purpose of the study is to make experimental whether three-dimensional body (especially face) has illusion based on theoretical background of form dimensions and color bright among precedent multi-form illusion, using the function of computer simulation. To investigate illusion that factors of clothing design(line, color, material) effect face, as the following is tried to solve giving change to neckline, collar, scarf which is believed to influence near face. How to make experiment as follows watching in order 13 scenes of a pair of with basic design and experiment design. Then the data were subjected to analysis of variance and Duncan's multiple range test. The result of this studying as follows, 1. Face looks larger in complex neckline than simple neckline. The larger collar is the larger face looks. 2. In white jacket, illusion(the lower luminosity of scarf color gets, the brighter face brightness gets) is shown. In black jacket, also illusion(the higher luminosity of scarf color gets, the darker face brightness gets) is shown. 3. In experiment on hardness and softness of face impression according to the material of collar, collar of knit and fur gives us assimilation illusion bring softer impression of face.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.12
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• pp.5464-5484
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• 2016

Few samples face recognition has become a highly challenging task due to the limitation of available labeled samples. As two popular paradigms in face image representation, sparse component analysis is highly robust while parts-based paradigm is particularly flexible. In this paper, we propose a probabilistic generative model to incorporate the strengths of the two paradigms for face representation. This model finds a common spatial partition for given images and simultaneously learns a sparse component analysis model for each part of the partition. The two procedures are built into a probabilistic generative model. Then we derive the score function (i.e. feature mapping) from the generative score space. A similarity measure is defined over the derived score function for few samples face recognition. This model is driven by data and specifically good at representing face images. The derived generative score function and similarity measure encode information hidden in the data distribution. To validate the effectiveness of the proposed method, we perform few samples face recognition on two face datasets. The results show its advantages.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.5
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• pp.9-17
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• 2018

Recently, the increasing interest of biometric systems has led to the creation of many researches of biometrics forgery. In order to solve this forgery problem, this paper proposes a method of determining whether a synthesized face made of artificaial intelligence is real face or fake face. The proposed algorithm consists of two steps. Firstly, we create the fake face images using various GAN (Generative Adversarial Networks) algorithms. After that, deep learning algorithm can classify the real face image and the generated face image. The experimental results shows that the proposed algorithm can detect the fake face image which looks like the real face. Also, we obtained the classification accuracy of 88.7%.

• Proceedings of the Korean Geotechical Society Conference
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• 2010.09b
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• pp.200-211
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• 2010

Tunnel Mapper, which is tunnel face survey system was used to conduct Face Mapping on the face of the tunnel that is under construction. Then, accuracy and utility value on the forecast of discontinuity were verified to verify the field application in order to present the measures for the use of the system for conducting research on the discontinuity. As result of the directivity verification following discontinuity‘s project, forecasted measurement and actually researched measurement error for the Dip direction and Dip angle was less than ${\pm}10$. Accuracy was 82.6% for Dip direction and 90.7% for Dip angle, which are high. Accordingly, face research discontinuity forecasting system's reliability level towards directivity is high. Tunnel Mapper, a tunnel face survey system can be leveraged to replace face's visual survey and to obtain objective information, enabling execution of the survey system that can automate face survey going beyond time and space related limitations.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.359-362
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• 2016

Face is an information unique to each person such as Iris, fingerprints, etc,. Research on face recognition are in progress continuously from the past to the present. Through these research, various face recognition methods have appeared. Among these methods, there are face recognition algorithms using the face data composed in stereo. In this paper, Convolutional Neural Network with Stereo Images as input was used for face recognition. This method showed better performance than the result of stereo face recognition using PCA that is used frequently in face recognition.