• Proceedings of the Korea Information Processing Society Conference
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• 2014.04a
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• pp.781-784
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• 2014

Face recognition under controlled settings, such as limited viewpoint and illumination change, can achieve good performance nowadays. However, real world application for face recognition is still challenging. In this paper, we use Affine SIFT to detect affine invariant local descriptors for face recognition under large viewpoint change. Affine SIFT is an extension of SIFT algorithm. SIFT algorithm is scale and rotation invariant, which is powerful for small viewpoint changes in face recognition, but it fails when large viewpoint change exists. In our scheme, Affine SIFT is used for both gallery face and probe face, which generates a series of different viewpoints using affine transformation. Therefore, Affine SIFT allows viewpoint difference between gallery face and probe face. Experiment results show our framework achieves better recognition accuracy than SIFT algorithm on FERET database.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.6
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• pp.1129-1135
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• 2007

Human face detection technique plays an important role in computer vision area. It has lots of applications such as face recognition, video surveillance, human computer interface, face image database management, and querying image databases. In this paper, a fast face detection approach using Principal Component Analysis (PCA) and Support Vector Machines (SVM) is proposed based on the previous study on face detection technique. In the proposed detection system, firstly it filter the face potential area using statistical feature which is generated by analyzing the local histogram distribution the detection process is speeded up by eliminating most of the non-face area in this step. In the next step, PCA feature vectors are generated, and then detect whether there are faces present in the test image using SVM classifier. Finally, store the detection results and output the results on the test image. The test images in this paper are from CMU face database. The face and non-face samples are selected from the MIT data set. The experimental results indicate the proposed method has good performance for face detection.

• 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.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2003.05a
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• pp.225-229
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• 2003

When hot strip is trimmed in the side trimming process at the entry side of tandem cold rolling mill, due to bad quality of trimming face and burr, product quality(saw ear)becomes so bad that it causes drop of yield and claim from customers. Therefore, it was examined that applying ultrasonic vibration is an effective method to improve quality of strip trimming face and decrease burr magnitude by decreasing shear force acting between strip trimming face and knife in side trimming process of cold rolling.

• Journal of Information Technology Services
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• v.20 no.5
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• pp.1-9
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• 2021

Since the first confirmed case in January 2020, Coronavirus disease 2019(COVID-19) has brought many changes to our society, and Korea is no exception. Some changes are direct and immediate such as restrictions on overseas travel and social distancing, but the others are indirect and slowly adapted such as lifestyle changes impacting industries and businesses. IT service sector is tremendously influenced by COVID-19. IT service is used extensively in response to COVID-19 taking advantage of its non-face-to-face characteristics. In that sense, the industry is positively affected and in some sense invigorated, giving birth to new kind of services. This special issue focuses on introducing how the IT services are affected, what kind of transformations are undergoing, and how these are expedited after COVID-19. This special issue expands and extends the case research section by collecting new IT service case studies concerning these topics. After competitive review process, 11 studies are selected for this special issue which deals with four different but closely related aspects: (1) evolutions of private IT services, (2) transformations in public IT services, (3) impacts in the hospitality and tourism industry, and (4) changes of people's behavior along with COVID-19. The first set reports on the evolution of private IT services that have created terms such as foodtech and edutech as we enter a rapid non-face-to-face situation. The second set consists of studies dealing with the evolution of public IT services. Evolution and rapid response to non-face-to-face appear to be no exception in the public sector. The third includes studies of hospitality and tourism which is most strongly affected by COVID-19. The last set deals with the behavioral changes of users such as technostress in telecommuting. Lessons learned through best practices and key problems identified in these studies may help us to actively respond to the coming waves of changes incurred by COVID-19 in our society as well as in the IT service industry.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.24 no.6
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• pp.519-524
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• 2011

ABLB (alternate binaural loudness balance) test is one of the medical assessments to diagnose detailed lesion of sensory-neural hearing loss based on a recruitment phenomenon. However, current ABLB audiometry 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, this face-to-face model leads to expensive audiometrist's labor cost and lengthy wait when there exist many subjects. As a solution, this paper suggests an ABLB audiometry system supporting one-to-many model in which model an audiometrist enables to assess several subjects concurrently. By providing such capabilities as real-time transfer of assessment result, video monitoring of subject and video chat, this solution can provide same effect as face-to-face model but overcome weakness of the existing face-to-face model.

• Journal of the Korea Convergence Society
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• v.12 no.1
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• pp.219-223
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• 2021

This study aims to present a non-face-to-face teaching methodology for the theory and practical lessons of design majors, especially for the arts and sports field. It was conducted to improve the existing teaching models after the non-face-to-face online lectures which began with COVID-19. Various existing smart learning methods such as online classes, interactive classes, and flip learning were reviewed, and a method to efficiently manage practical skills by supplementing the shortcomings of each study was suggested. 4 stages of teaching development - setting a teaching method, teaching progress, evaluation, and follow-up management-were designated and applied to the class of design majors. The result showed that it is effective in terms of teaching method and progress; however, the limitations of non-face-to-face classes were found in the stages of evaluation and follow-up management. Therefore, it is expected that further research on evaluation and follow-up management, such as specific practical instruction methods is required to improve completion.

• Journal of the Korean Society of Radiology
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• v.14 no.7
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• pp.923-930
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• 2020

The COVID-19 crisis inevitably led to full-scale non-face-to-face education in 2020. The researchers selected five universities out of 48 universities in radiology and radiology departments nationwide (1.2 in 2019 and 1.2 in 2020) to examine the results of face-to-face training and non-face-to-face mock tests conducted by senior students in radiology departments and radiology departments of the national health department (12 in 2019 and 1.2 in 2020) in preparation for the license test. It turned out to be. Comparing the results of face-to-face and non-face-to-face training (two in 2019 and two in 2020), statistics were analyzed by nonparametric tests, and the results showed that there were differences in theory (Z=-2.023, p<0.05, application (Z=-2.023), p<0.05), practical skills (Z=-1.753, and p<0.05). As a result of the mock test, non-face-to-face education results in poor grades compared to face-to-face education, it is believed that lectures should be taught differently or various educational methods that can communicate with students should be combined.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.2
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• pp.11-20
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• 2010

In this paper we propose a face detection system which consists of a method of face candidate extraction using skin color and a method of face verification using the feature of facial structure. Firstly, the proposed extraction method of face candidate uses the image segmentation and merging algorithm in the regions of skin color and the neighboring regions of skin color. These two algorithms make it possible to select the face candidates from the variety of faces in the image with complicated backgrounds. Secondly, by using the partial face classifier, the proposed face validation method verifies the feature of face structure and then classifies face and non-face. This classifier uses face images only in the learning process and does not consider non-face images in order to use less number of training images. In the experimental, the proposed method of face candidate extraction can find more 9.55% faces on average as face candidates than other methods. Also in the experiment of face and non-face classification, the proposed face validation method obtains the face classification rate on the average 4.97% higher than other face/non-face classifiers when the non-face classification rate is about 99%.

• The KIPS Transactions:PartB
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• v.9B no.4
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• pp.491-500
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• 2002

In this paper, we propose a real-time face detection and recognition system by using skin color informations, geometrical feature vectors of face, and facial angle informations from color face image. The proposed algorithm improved face region extraction efficiency by using skin color informations on the HSI color coordinate and face edge information. And also, it improved face recognition efficiency by using geometrical feature vectors of face and facial angles from the extracted face region image. In the experiment, the proposed algorithm shows more improved recognition efficiency as well as face region extraction efficiency than conventional methods.