• The Journal of Asian Finance, Economics and Business
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• 제7권5호
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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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권7호
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• pp.2547-2567
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• 2021

It has been widely acknowledged that occlusion impairments adversely distress many face recognition algorithms' performance. Therefore, it is crucial to solving the problem of face image occlusion in face recognition. To solve the image occlusion problem in face recognition, this paper aims to automatically de-occlude the human face majority or discriminative regions to improve face recognition performance. To achieve this, we decompose the generative process into two key stages and employ a separate generative adversarial network (GAN)-based network in both stages. The first stage generates an initial coarse face image without an occlusion mask. The second stage refines the result from the first stage by forcing it closer to real face images or ground truth. To increase the performance and minimize the artifacts in the generated result, a new refine loss (e.g., reconstruction loss, perceptual loss, and adversarial loss) is used to determine all differences between the generated de-occluded face image and ground truth. Furthermore, we build occluded face images and corresponding occlusion-free face images dataset. We trained our model on this new dataset and later tested it on real-world face images. The experiment results (qualitative and quantitative) and the comparative study confirm the robustness and effectiveness of the proposed work in removing challenging occlusion masks with various structures, sizes, shapes, types, and positions.

• 한국학교보건학회지
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• 제35권1호
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• pp.11-21
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• 2022

Purpose: This study investigated the relationship between satisfaction with fundamental nursing skills practicum, confidence in fundamental nursing skills performance and learning flow, and examined factors influencing satisfaction with practicum programs of fundamental nursing skills in face-to-face and online classes for nursing students amid COVID-19. Methods: The subjects of the study were 229 junior nursing students from two colleges of nursing located in D and C city, respectively. The collected data were analyzed with descriptive statistics, independent t-test, ANOVA, Kruskal-Wallis test, Pearson's correlation and hierarchical multiple regression, using SPSS/WINdows 23.0. Results: The subjects' satisfaction with practicum showed a high positive correlation with confidence in performance (r=.55, p<.001) and learning flow (r=.70, p<.001) in face-to-face classes, and their satisfaction with practicum showed a high positive correlation with confidence in performance (r=.56, p<.001) and learning flow (r=.73, p<.001) in online classes. The factors affecting the subjects' satisfaction with practicum were learning flow (β=.51, p<.001) and confidence in performance (β=.30, p<.001) for face-to-face classes, and motivation for application (β=.14, p=.034), learning flow (β=.58 p<.001) and confidence in performance (β=.19, p=.015) for online classes. These factors explained 53% and 60% of the satisfaction with practicum in face-to-face classes (F=23.07, p<.001) and online classes (F=20.66, p<.001), respectively. Conclusion: Learning flow and confidence in performance should be considered when developing learning strategy programs to improve nursing students' satisfaction with fundamental nursing skills practicum in both face-to-face and online classes.

• 정보보호학회논문지
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• 제23권4호
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• pp.737-742
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• 2013

최근 감시시스템은 휴먼인식 기술을 활용하여 스스로 판단하고 대처할 수 있는 지능형으로 발전하고 있다. 기존 얼굴인식 기술은 근거리에서 인식성능이 우수하지만 원거리로 갈수록 인식률이 떨어진다. 본 논문에서는 원거리 휴먼인식을 위해 거리별 얼굴영상을 학습으로 사용한 얼굴인식에서 보간법 및 얼굴인식 알고리즘에 따른 얼굴인식률의 성능을 분석한다. 영상 정규화에는 최근접 이웃, 양선형, 양3차회선, Lanczos3 보간법을 사용하고, 얼굴인식 알고리즘은 PCA와 LDA를 사용한다. 실험결과, 영상 정규화로 양선형 보간법과 얼굴인식 알고리즘으로 LDA를 사용했을 때 우수한 성능을 나타냄을 확인하였다.

• 산업과 과학
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• 제2권1호
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• pp.39-44
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• 2023

본 연구의 목적은 코로나 팬데믹 시기 대학의 온라인 수업과 비대면 혼합수업의 성과와 만족도를 비교하기 위함이다. 연구는 일 대학 간호학과에서 성인간호학 강의를 수강하는 4학년 학생을 대상으로 하였으며 전면 비대면 수업에 참여한 113명과 비대면 혼합수업에 참여한 134명의 학습 성과와 수업 만족도를 비교하였다. 연구결과 비대면 혼합수업의 성과와 만족도가 전면 비대면 수업보다 통계적으로 유의하게 높았다. 코로나 팬데믹 시기를 지나오면서 대학 구성원은 수업의 질을 결정하는 요인은 대면이냐 비대면이냐 형식의 문제라기보다는 가르치는 사람의 성의와 배우는 사람의 열의가 더욱 중요함을 모두 경험했다. 따라서 교육과 학습에 대한 성의와 열의를 기본으로 하여 앞으로의 교육환경 변화에 대비한 새로운 교육방법 개발 운영, 이에 따른 효과연구는 계속되어야 할 것으로 생각된다.

• 정보통신설비학회논문지
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• 제11권1호
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• pp.23-28
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• 2012

In this paper, we proposed and developed a fast and efficient real time face detection and recognition which can be run on embedded system instead of high performance desktop. In the face detection process, we detect a face by finding eye part which is one of the most salient facial features after applying various image processing methods, then in the face recognition, we finally recognize the face by comparing the current face with the prepared face database using a template matching algorithm. Also we optimized the algorithm in our system to be successfully used in the embedded system, and performed the face detection and recognition experiments on the embedded board to verify the performance. The developed method can be applied to automatic door, mobile computing environment and various robot.

• 설비공학논문집
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• 제27권8호
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• pp.395-401
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• 2015

Recently, many research studies have been carried out on the efficiency of light-shelf daylighting systems, especially comparing performance improvements and the limitations of reflective surfaces and their lighting performance. In this study, a crystal face reflective surface is proposed. The objective of the study is to evaluate the lighting performance of a crystal face light-shelf through a performance study. The performance study was carried out in a full scale test-bed in order to calculate the light distribution and energy consumption utilizing the standard indoor illumination as an index. The conclusions of the performance study are as follows. 1) The optimal angle of incidence for daylighting for both the operable flat type light-shelf and the crystal face light-shelf are taken in the natural environment on the dates of the winter and summer solstices, as well as the autumn and spring equinoxes. 2) The application and installation of the crystal face light-shelf can produce a 29.9%~34.3% increase of light distribution within the indoor space. However, the increase of light distribution can also lead to a decrease in the uniformity ratio, a design challenge that should be considered when applying a crystal face light-shelf. 3) It is possible to achieve a 7.98%~13.3% greater reduction in energy consumption when applying a crystal face light-shelf than when applying a flat type light-shelf. The increase in the number of crystal faces should concur with the analysis of the energy reduction. A limitation of the study is that only one predetermined pattern was performance tested for a crystal face light-shelf. In order to carry out further research on crystal face light-shelves, additional performance studies are needed based on alternative patterns and designs.

• 한국IT서비스학회지
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• 제6권2호
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• pp.161-175
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• 2007

Face recognition technology has lately attracted considerable attention because of its non-intrusiveness, usability and applicability. Related companies insist that their commercial products show the recognition rates more than 95% according to their self-testing. But, the rates cannot be admitted as official recognition rates. So, performance evaluation methods and tools are necessary to objectively measure the accuracy and performance of face recognition systems. In this paper, I propose a reference model for biometrics recognition evaluation tools, and implement an evaluation tool for the face recognition system based on the proposed reference model.

• 정보보호학회논문지
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• 제33권2호
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• pp.201-210
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• 2023

딥러닝 기반 얼굴 인증 모델은 높은 성능을 보이며 많은 분야에 이용되지만, 얼굴 이미지를 모델에 입력하는 과정에서 사용자의 얼굴 이미지가 유출될 가능성이 존재한다. 얼굴 이미지의 노출을 최소화하기 위한 방법으로 비식별화 기술이 존재하지만, 얼굴 인증이라는 특수한 상황에서 기존 기술을 적용할 때에는 인증 성능이 감소하는 문제점이있다. 본 논문에서는 원본 얼굴 이미지에 다른 인물의 얼굴 특성을 결합한 뒤, StyleGAN을 통해 비식별화 얼굴이미지를 생성한다. 또한, HopSkipJumpAttack을 활용해 얼굴 인증 모델에 맞춰 특징들의 결합 비율을 최적화하는 방법을 제안한다. 우리는 제안 방법을 통해 생성된 이미지들을 시각화하여 사용자 얼굴의 비식별화 성능을 확인하고, 실험을 통해 얼굴 인증 모델에 대한 인증 성능을 유지할 수 있음을 평가한다. 즉, 제안 방법을 통해 생성된 비식별화 이미지를 사용하여 얼굴 인증을 할 수 있으며, 동시에 얼굴 개인정보 유출을 방지할 수 있다.

• Journal of Multimedia Information System
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• 제6권1호
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• pp.15-22
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• 2019

There are many ways to perform face recognition. The first step of face recognition is the face detection step. If the face is not found in the first step, the face recognition fails. Face detection research has many difficulties because it can be varied according to face size change, left and right rotation and up and down rotation, side face and front face, facial expression, and light condition. In this study, facial features are extracted and the extracted features are geometrically reconstructed in order to improve face recognition rate in extracted face region. Also, it is aimed to adjust face angle using reconstructed facial feature vector, and to improve recognition rate for each face angle. In the recognition attempt using the result after the geometric reconstruction, both the up and down and the left and right facial angles have improved recognition performance.