• The Journal of Korean Institute for Practical Engineering Education
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• v.4 no.2
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• pp.67-74
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• 2012

This study elicits alternatives for improving blended education by comparing the face-to-face education and blended education of VET teacher license program. To produce a basis for the methods of blended education, this study compared the scores of satisfaction and academic performance of face-to-face and of blended education. Also it examined the three factors of learners' characteristics, teaching and learning design, and its environment as they affect the education effect. The results showed that academic performance of face-to-face education is higher than blended and that competition rate of blended education is higher than that of face-to-face. To improve the effect of blended learning, various teaching and learning activities, design of contents that promotes participation and interaction, and development of contents which satisfy the various levels of learning needs were discussed.

• Journal of Korea Multimedia Society
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• v.16 no.11
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• pp.1338-1347
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• 2013

Face recognition is a science of automatically identifying individuals based their unique facial features. In order to avoid overfitting and reduce the computational reduce the computational burden, a new face recognition algorithm using PCA-fisher linear discriminant (PCA-FLD) and fuzzy radial basis function neural network (RBFNN) is proposed in this paper. First, face features are extracted by the principal component analysis (PCA) method. Then, the extracted features are further processed by the Fisher's linear discriminant technique to acquire lower-dimensional discriminant patterns, the processed features will be considered as the input of the fuzzy RBFNN. As a widely applied algorithm in fuzzy RBF neural network, BP learning algorithm has the low rate of convergence, therefore, an improved learning algorithm based on Levenberg-Marquart (L-M) for fuzzy RBF neural network is introduced in this paper, which combined the Gradient Descent algorithm with the Gauss-Newton algorithm. Experimental results on the ORL face database demonstrate that the proposed algorithm has satisfactory performance and high recognition rate.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.7
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• pp.1705-1720
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• 2013

Human face gender recognition requires fast image processing with high accuracy. Existing face gender recognition methods used traditional local features and machine learning methods have shortcomings of low accuracy or slow speed. In this paper, a new framework for face gender recognition to reach fast face gender recognition is proposed, which is based on Local Ternary Pattern (LTP) and Extreme Learning Machine (ELM). LTP is a generalization of Local Binary Pattern (LBP) that is in the presence of monotonic illumination variations on a face image, and has high discriminative power for texture classification. It is also more discriminate and less sensitive to noise in uniform regions. On the other hand, ELM is a new learning algorithm for generalizing single hidden layer feed forward networks without tuning parameters. The main advantages of ELM are the less stringent optimization constraints, faster operations, easy implementation, and usually improved generalization performance. The experimental results on public databases show that, in comparisons with existing algorithms, the proposed method has higher precision and better generalization performance at extremely fast learning speed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.8
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• pp.1136-1141
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• 2022

Researches of face recognition on masked faces have been increasingly important due to the COVID-19 pandemic. To realize a stable and practical recognition performance, large amount of facial image data should be acquired for the purpose of training. However, it is difficult for the researchers to obtain masked face images for each human subject. This paper proposes a novel method to synthesize a face image and a virtual mask pattern. In this method, a pair of masked face image and unmasked face image, that are from a single human subject, is fed into a convolutional autoencoder as training data. This allows learning the geometric relationship between face and mask. In the inference step, for a unseen face image, the learned convolutional autoencoder generates a synthetic face image with a mask pattern. The proposed method is able to rapidly generate realistic masked face images. Also, it could be practical when compared to methods which rely on facial feature point detection.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.4
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• pp.116-128
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• 2011

In this paper, we propose the structure of a high-performance face-detection engine that responds well to facial rotating changes using rotation transformation which minimize the required memory usage compared to the previous face-detection engine. The validity of the proposed structure has been verified through the implementation of FPGA. For high performance face detection, the MCT (Modified Census Transform) method, which is robust against lighting change, was used. The Adaboost learning algorithm was used for creating optimized learning data. And the rotation transformation method was added to maintain effectiveness against face rotating changes. The proposed hardware structure was composed of Color Space Converter, Noise Filter, Memory Controller Interface, Image Rotator, Image Scaler, MCT(Modified Census Transform), Candidate Detector / Confidence Mapper, Position Resizer, Data Grouper, Overlay Processor / Color Overlay Processor. The face detection engine was tested using a Virtex5 LX330 FPGA board, a QVGA grade CMOS camera, and an LCD Display. It was verified that the engine demonstrated excellent performance in diverse real life environments and in a face detection standard database. As a result, a high performance real time face detection engine that can conduct real time processing at speeds of at least 60 frames per second, which is effective against lighting changes and face rotating changes and can detect 32 faces in diverse sizes simultaneously, was developed.

• Journal of Multimedia Information System
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• v.7 no.4
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• pp.239-248
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• 2020

The performance of the facial recognition system is determined by many technical factors. Further, most of the technical factors have been realized or are still in continued research. The recognition rate has a great influence on performance not only by technical factors but also by other factors. However, researchers are trying to improve the recognition rate by focusing only on technical factors. The mechanism of recognizing is to compare a face image obtained by photography to an already stored face image and determine the score of the similarity. However, if the photographed image is damaged by external light, even a system with a good algorithm will fail to recognize it. Therefore, it is important to prevent the disturbance of light entering from the outside, so it should be blocked, but the camera will not work without light. Thus, it is proposed that a method to secure the external light but block the disturbance of light that affects photography. A method of blocking disturbance light is to use a polarization filter. There are three polarization methods: circular polarization, linear polarization, and elliptical polarization. In this paper, an experiment was performed to overcome disturbance of light using only a circularly polarized filter. In addition, a lighting system that reproduces disturbance light was provided for the experiment, and light of varying intensities and angles was installed to affect the face recognition camera. As a result of actual application, it was determined that a very improved recognition performance in various disturbance light environments.

• The Journal of the Korea Contents Association
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• v.16 no.9
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• pp.117-126
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• 2016

This study examined the relative effects of different feedback delivery method (face-to-face vs. e-mail) and reinforcement history on work performance. Participants were asked to work on a simulated mobile phone assembly task. They performed for 30 minutes per session and attended 4 sessions. The dependents variable was the percentage of correctly completed work tasks. Of 100 participants recruited, 50 had a reinforcement history and another 50 had no reinforcement history with the feedback provider in this study. The participants in each group were randomly assigned into two experimental conditions: face-to-face feedback and e-mail feedback. The results showed that for the participants who had reinforcement history, the two feedback delivery methods did not produce a significant difference in the percentage of correctly completed work tasks. However, for those who had no reinforcement history, the two feedback methods did produce a significant difference.

• Journal of Digital Convergence
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• v.12 no.1
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• pp.149-161
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• 2014

According to the economic advancement, the position of service industry in GDP has increased. Development of service industry has solved the employment issue and derived the activation of the internal market. It has contributed to demand creation in health care, education, and culture, enhancing competition of the manufacturing industry and entire economic development. By the development of information communication technologies, improvement of the quality of life from those, and changes in the competitive environment, customers, from businesses and public agencies, or the customer's needs are increasing. In these circumstances, companies are operating non-face-to-face contact call center for the purpose to communicate with customers, handle customer complaints, attract and retain new customers. In this study, to improve the performance of the non-face-to-face contact call center, this study tried to derive the call center's 'Service Process Modeling' and future policy assignment by analyzing the problem from the research of the service and process summary, performance evaluation, call center evaluation and etc.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.4
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• pp.1824-1845
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• 2016

The GMM is a conventional approach which has been recently applied in many face recognition studies. However, the question about how to deal with illumination changes while ensuring high performance is still a challenge, especially with real-world databases. In this paper, we propose a Visual Observation Confidence (VOC) measure for robust face recognition for illumination changes. Our VOC value is a combined confidence value of three measurements: Flatness Measure (FM), Centrality Measure (CM), and Illumination Normality Measure (IM). While FM measures the discrimination ability of one face, IM represents the degree of illumination impact on that face. In addition, we introduce CM as a centrality measure to help FM to reduce some of the errors from unnecessary areas such as the hair, neck or background. The VOC then accompanies the feature vectors in the EM process to estimate the optimal models by modified-GMM training. In the experiments, we introduce a real-world database, called KoFace, besides applying some public databases such as the Yale and the ORL database. The KoFace database is composed of 106 face subjects under diverse illumination effects including shadows and highlights. The results show that our proposed approach gives a higher Face Recognition Rate (FRR) than the GMM baseline for indoor and outdoor datasets in the real-world KoFace database (94% and 85%, respectively) and in ORL, Yale databases (97% and 100% respectively).

• Tribology and Lubricants
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• v.26 no.4
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• pp.230-239
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• 2010

Mechanical face seal installed in boiler feedwater pump prevents leakage of working fluid using thin fluid film between stator and rotor. If the leakage of working fluid exceeds the allowable volume, serious malfunction of boiler feedwater pump will be happen. The thinner fluid film exists between stator and rotor, the less working fluid leaks out. However, if the thickness of fluid film is not enough, the wear of seal face will be increased. And it causes the decrease in life of mechanical face seal. Therefore appropriate design is necessary to maximize the performance and life of mechanical face seal. In this study, numerical analysis using finite volume method was conducted to investigate the static characteristics of wavy mechanical face seals which have 4 different wavy surface profiles on rotor. As a result, opening force, leakage volume of working fluid and friction torque were obtained. For the same minimum film thickness, the static characteristics of mechanical face seal were affected by the wavy surface profile which can change the thickness of working fluid film and pressure distribution.