• Journal of the Korea Society of Computer and Information
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• v.13 no.6
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• pp.301-314
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• 2008

The purpose of this study is to examine the effect of information service quality on user satisfaction and individual performance in Outbound Callcenter. A survey was conducted and data were collected from 330 respondents of 1 company which adopted CMS. Validity and reliability of the research instrument were tested and research hypotheses were examined using PLS Graph 3.0. As a result of data analysis, 6 out of 8 hypotheses were supported. User satisfaction is significantly influenced by information quality factors such as accuracy, currency, and relevancy. 2) Also, User satisfaction is significantly affected by internal service quality factors such as training support and reward system. 3) Individual performance is significantly influenced by user satisfaction. Implications of these findings are discussed for researchers and practitioners.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.2
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• pp.735-744
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• 2014

In this study, emotional intelligence which is defined as knowing yourself and other people's emotions and the ability to use regulation was judged as an important factor for the service quality implementation of aircraft crew members perform to work in special circumstances. And the purpose of this study is how emotional Intelligence affects job satisfaction and organizational loyalty. So we analyze the emotional intelligence of the K domestic airline crew in this study. This study showed that emotional intelligence affect high quality of service to perform the work well and contribute to job satisfaction. And job satisfaction has a positive impact on organizational loyalty also. Therefore, the ability of airlines to improve service quality as well as performing work also for the emotional intelligence to increase satisfaction and loyalty unplug staffs and it will require ongoing sensitivity training.

• The Korean Journal of Health Service Management
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• v.13 no.4
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• pp.215-228
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• 2019

Objectives: The purpose of this study is to figure out that Facilitation education can affect significant improvement in sales staff's understanding of precise pharmacokinetics, benefits, safety, and side effects, etc. and eventually lead to increase in call after taking courses. Methods: Data utilized in this study was collected from 413 sales staffs who completed Facilitation course for 5 months. This study used statistical methodologies, paired t-test, exploratory factor analysis, and logistic regression model in order to identify change in Call and after Facilitation courses. Results: The result shows that there are statistically significant increases in CALL quality after Facilitation courses based on the result of pared t-test. Moreover, Facilitation education is more effective in average time of one-time detail than average number of visits per day and average number of doctors per day from the result of logistic regression. Conclusions: In order for MR in pharmaceutical company to improve CALL quality, the education for precise pharmacokinetics, benefits, safety, and side effects is necessary. In addition, various professional training required for detail, including disease education, Selling Skills education, and literacy education are essential. Therefore, Facilitation education would be desirable choice in terms of pharmaceutical marketing strategy.

• Journal of Information Management
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• v.36 no.3
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• pp.127-165
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• 2005

This study is focused on the quality of the Web databases which has been produced in science. For the quality evaluation of NDSL, PubMed, Scopus, and WoS, 10 evaluating criteria are developed on the basis of literature review. The evaluation results show that NDSL and PubMed are superior in the currentness and cost. Scopus and WoS are superior in the information of citing and the analysis tool. It is needed for purchasing, user training, and library service based on the above evaluation results.

• Journal of the Korea Convergence Society
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• v.9 no.12
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• pp.365-372
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• 2018

This study aimed to investigate the perception on dental hygienists and convergence factors to affect social requirements on their roles so as to utilize them as the fundamental data to assist the common people to understand the occupation and roles of dental hygienists and expand their positive perception further. Upon the multiple regression analysis from 235 final analysis subjects who underwent survey from August 1st to 25th 2017 among 270 adults in Busan and Gyeongnam areas, the awareness level on the dental hygienists was higher as the education level was lower and quality of life was more positive. Requirements were increased more as the education level was lower, quality of life related to oral health was more positive, quality of life was more positive, and awareness level on the roles and knowledge of dental hygienists was increased more. Further programs and promotional plans should be continuously activated to establish the career roles and expand the awareness in every field including dental clinic practices, dental hygiene training, related groups, and so on.

• Phonetics and Speech Sciences
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• v.13 no.3
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• pp.71-78
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• 2021

Most neural-network-based speech synthesis models utilize neural vocoders to convert mel-scaled spectrograms into high-quality, human-like voices. However, neural vocoders combined with mel-scaled spectrogram prediction models demand considerable computer memory and time during the training phase and are subject to slow inference speeds in an environment where GPU is not used. This problem does not arise in linear spectrogram prediction models, as they do not use neural vocoders, but these models suffer from low voice quality. As a solution, this paper proposes a Tacotron 2 and Transformer-based linear spectrogram prediction model that produces high-quality speech and does not use neural vocoders. Experiments suggest that this model can serve as the foundation of a high-quality text-to-speech model with fast inference speed.

• Journal of Korean Society on Water Environment
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• v.27 no.4
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• pp.533-541
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• 2011

Algal blooms have caused problems for drinking water as well as eutrophication. However it is difficult to control algal blooms by current warning manual in rainy season because the algal blooms happen in a few days. The water quality data, which have high correlations with Chlorophyll-a on Daecheongho station, were analyzed and chosen as input data of Artificial Neural Networks (ANN) for training pattern changes. ANN was applied to early forecasting of algal blooms, and ANN was assessed by forecasting errors. Water temperature, pH and Dissolved oxygen were important factors in the cross correlation analysis. Some water quality items like Total phosphorus and Total nitrogen showed similar pattern to the Chlorophyll-a changes with time lag. ANN model (No. 3), which was calibrated by water temperature, pH and DO data, showed lowest error. The combination of 1 day, 3 days, 7 days forecasting makes outputs more stable. When automatic monitoring data were used for algal bloom forecasting in Daecheong reservoir, ANN model must be trained by just input data which have high correlation with Chlorophyll-a concentration. Modular type model, which is combined with the output of each model, can be effectively used for stable forecasting.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.2
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• pp.101-113
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• 2022

The intensification and acceleration of severe competition among companies due to the advancement of the service industry have raised the quality level of services required by consumers, and these circumstances also have a significant impact on the public fields' service provision environment, which has to take into account the rapidly changing technologies along with the special situation of COVID-19. Thus, this study examines the applicability of the educational material based on the framework for public service quality management in accordance with 『ISO18091:2019』 developed by MOIS(the ministry of interior and safety), through a survey after training workers in public institutions. This study also provides some implications and guidelines that should be considered to increase the level of public service quality from the following three perspectives: i) data utilization and verification, ii) broadness of public services, and iii) the size and capability of service provider according to the results of field studies conducted with public sector employees who participated in actual improvement activities.

• Archives of Plastic Surgery
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• v.49 no.5
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• pp.668-675
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• 2022

Background Educational resources on the internet are extensively used to obtainmedical information. YouTube is the most accessed video platform containing information to enhance the learning experience of medical professionals. This study systematically analyzed the educational value of microsurgery-related videos on this platform. Methods A systematic review was conducted on YouTube from April 18 to May 18, 2020, using the following terms: "microsurgery," "microsurgical," "microsurgical anastomosis," "free flap," and "free tissue transfer." The search was limited to the first 100 videos, and two independent reviewers screened for eligible entries and analyzed their educational value using validated scales, including a modified version of the DISCERN score (M-DISCERN), Journal of the American Medical Association (JAMAS) benchmark criteria, and the Global Quality Score (GQS). Evaluation of video popularity was also assessed with the video power index (VPI). Results Of 356 retrieved videos, 75 (21%) were considered eligible. The educational quality of videos was highly variable, and the mean global scores for the M-DISCERN, JAMAS, and GQS for our sample were consistent with medium to low quality. Conclusions A limited number of videos on YouTube for microsurgical education have high-educational quality. The majority scored low on the utilized criteria. Peer-reviewed resources seem to be a more reliable resource. Although the potential of YouTube should not be disregarded, videos should be carefully appraised before being usedas an educational resource.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.9
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• pp.1305-1311
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• 2022

With the recent rapid development of mobile terminals and personal computers and the advent of neural network technology, real-time face swapping using images has become possible. In particular, the cycle generative adversarial network made it possible to replace faces using uncorrelated image data. In this paper, we propose an input data processing scheme that can improve the quality of face swapping with less training data and time. The proposed scheme can improve the image quality while preserving facial structure and expression information by combining facial landmarks extracted through a pre-trained neural network with major information that affects the structure and expression of the face. Using the blind/referenceless image spatial quality evaluator (BRISQUE) score, which is one of the AI-based non-reference quality metrics, we quantitatively analyze the performance of the proposed scheme and compare it to the conventional schemes. According to the numerical results, the proposed scheme obtained BRISQUE scores improved by about 4.6% to 14.6%, compared to the conventional schemes.