• Journal of Practical Engineering Education
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• v.7 no.1
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• pp.77-80
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• 2015

Vocational training efficiency and participation was intended to try to find a reliable demand survey methods to find ways that can be maximized. The exact demand investigation may be the most important factor that can improve the quality of training. Furthermore, the training is due to inaccurate demand as research shows the result of ineffective training because of low participation. Four methods of demand survey are used in the form of large mail, telephone, electronic and face-to-face. This paper describes the demand survey that has been carried out through the training of human resources in the training business that suits description local industry human resource development (HRD) consortium of Mokpo University country, proposed a method of effective demand survey.

• Educational Technology International
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• v.6 no.1
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• pp.139-154
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• 2005

There were misgivings that the teachers in charge might not have enough understanding of the true purpose of teaching "Information". To learn about the general attitude of those teachers, the research group of private schools in Osaka began a project, 'The Public Presentation Caravan', in which teachers who had already started using information tools opened their class to teachers from other schools and exchanged ideas. It may be deduced that the combination of the two forums for exchanging opinions, one is held on the internet and the other face to face, is important. Teachers' community exists on the point where these two environments meet. Through this project, we might suggest creating a new mode of teachers' community using a network will be indispensable for the new teachers training.

• Journal of the Korea Safety Management & Science
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• v.18 no.3
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• pp.91-97
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• 2016

Currently many geriatric hospitals have been built in Korea because younger people don't want to care their parents and have been decreasing for labor. However, the increasing geriatric hospitals make the increasing fire safety accidents. Therefore, this study is conducted by survey and face-to-face talk for analyzing fire safety problem of twelve among 15 geriatric hospitals in the north of Chung-Buk area. The result of this study is that infection and fall accident are higher than others and fire safety implement rate of safety rule followed by CEO is 71%. Monthly safety training rate is 49% and initial fire safety training not conducted is 33%. Yearly outside fire safety training rate is 97% but workers who know how to use fire evacuation facility are 61%. Furthermore, safety instruction rate of fire safety manager is much higher than supervisor's safety instruction. The cause of accident is facility (33%). In conclusion, the institution and rule improvement need for decreasing infection and falling, increasing implement level of fire safety rule and fire safety training, participation rate of supervisor for fire safety, quality of fire safety training, and investment of fire safety facility.

• Journal of KIISE:Software and Applications
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• v.31 no.1
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• pp.54-60
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• 2004

Face recognition is one of the problems to be solved by appearance based matching technique. However, the appearance of face image is very sensitive to variation in illumination. One of the easiest ways for better performance is to collect more training samples acquired under variable lightings but it is not practical in real world. ]:n object recognition, it is desirable to focus on feature extraction or normalization technique rather than focus on classifier. This paper presents a simple approach to normalization of faces subject to directional illumination. This is one of the significant issues that cause error in the face recognition process. The proposed method, ICR(illumination Compensation based on Multiple Linear Regression), is to find the plane that best fits the intensity distribution of the face image using the multiple linear regression, then use this plane to normalize the face image. The advantages of our method are simple and practical. The planar approximation of a face image is mathematically defined by the simple linear model. We provide experimental results to demonstrate the performance of the proposed ICR method on public face databases and our database. The experimental results show a significant improvement of the recognition accuracy.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2021.06a
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• pp.105-108
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• 2021

Generative adversarial networks (GANs) have reached a great result at creating the synthesis image, especially in the face generation task. Unlike other deep learning tasks, the input of GANs is usually the random vector sampled by a probability distribution, which leads to unstable training and unpredictable output. One way to solve those problems is to employ the label condition in both the generator and discriminator. CelebA and FFHQ are the two most famous datasets for face image generation. While CelebA contains attribute annotations for more than 200,000 images, FFHQ does not have attribute annotations. Thus, in this work, we introduce a method to learn the attributes from CelebA then predict both soft and hard labels for FFHQ. The evaluated result from our model achieves 0.7611 points of the metric is the area under the receiver operating characteristic curve.

• Journal of Korea Multimedia Society
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• v.21 no.4
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• pp.471-477
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• 2018

As an important key technology using on electronic devices, face recognition has become one of the hottest technology recently. The traditional BP Neural network has a strong ability of self-learning, adaptive and powerful non-linear mapping but it also has disadvantages such as slow convergence speed, easy to be traversed in the training process and easy to fall into local minimum points. So we come up with an algorithm based on BP neural network but also combined with the PCA algorithm and other methods such as the elastic gradient descent method which can improve the original network to try to improve the whole recognition efficiency and has the advantages of both PCA algorithm and BP neural network.

• Fashion & Textile Research Journal
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• v.13 no.3
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• pp.398-408
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• 2011

This study shows that the self-satisfaction individually is rising and social life is attracted effective and successful in image making field by structuring the facial image improvement program through experimental study in order to improve unbalance of women's face. Experiment is conducted by electing 3 samples for 12 weeks and analyzing the measurement and visual analysis, infrared thermography, and evaluation of experts in order to check the facial unbalance. Subject 1 had the effect at approximately in 4 weeks with the severely distorted chin line and mouth appendage. The facial outline became softer to turn entire image to be softer and more feminine. Subject 2 had the severe distortion of location and size of eyes and nose. But the skin was getting better at first, followed by eyes getting clearer with the location changed in left and right. Subject 3 had the twisted nose and lower chin, but after two weeks, the eye area and skin were better and the width of left and right chin was similarly changed. On the basis of the above research result, the program to effectively improve the image was structured and presented with the resolution of facial unbalance. Program is consist of the training of breathing method, face washing method, facial muscle exercise.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.31-33
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• 2009

Face detection using AdaBoost algorithm is capable of processing images rapidly while having high detection rates. It seemed to be the fastest and the most robust and it is still today. Many improvements or extensions of this method have been proposed. However, previous approaches only deal with upright faces. They suffer from limited discriminant capability for rotated faces as these methods apply the same features for both upright and rotated faces. To solve this problem, it is necessary that we rotate input images or make independently trained detectors. However, this can be slow and can require a lot of training data, since each classifier requires the computation of many different image features. This paper proposes a robust algorithm for finding rotated faces within an image. It reduces the computational and sample complexity, by finding common features that can be shared across the classes. And it will be able to apply with multi-class object detection.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.460-463
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• 1999

We present an efficient face recognition method that is robust to illumination changes. We named the proposed method as SKKUfaces. We first compute eigenfaces from training images and then apply fisher discriminant analysis using the obtained eigenfaces that exclude eigenfaces correponding to first few largest eigenvalues. This way, SKKUfaces can achieve the maximum class separability without considering eigenfaces that are responsible for illumination changes, facial expressions and eyewear. In addition, we have developed a method that efficiently computes beween-scatter and within-scatter matrices in terms of memory space and computation time. We have tested the performance of SKKUfaces on the YALE and the SKKU face databases. Initial Experimental results show that SKKUfaces performs greatly better over Fisherfaces on the input images of large variations in lighting and eyewear.

• Journal of Information Technology Services
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• v.20 no.5
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• pp.147-158
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• 2021

The digital transformation and COVID-19 are also causing major changes in teaching-learning methods. The biggest change is the spread of remote training and the emergence of various innovative learning platforms. Distance education has been criticized for not meeting technology trends and field demands..However, the problem of distance education is being solved through a system that supports various interactions and collaborations and supports customized learning paths. The researcher conducted a case study on domestic and foreign learning platforms that provide non-face-to-face ICT education. Based on the case study results, the researcher presented the functional characteristics of a learning platform that effectively supports non-face-to-face learning. In common, these sites faithfully supported the basic functions of the information system. In addition to learning progress check and learning guidance, some innovative learning platforms were providing differentiated functions in practice support, performance management, mentoring, learning data analysis, curation provision, and CDP support. Most learning platforms supported one-way, superficial interaction. If the platform effectively supports a variety of learning experiences and provides an integrated learning experience thanks to the development of IT technology, user satisfaction with the learning platform, intention to continue learning, and achievement will increase.