• Korean Journal of Veterinary Research
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• v.43 no.4
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• pp.683-688
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• 2003

Caffeine (1,3,7-trimethylxanthine), a central nervous system stimulant, is contained in various foods, beverages and over-the-counter medications. Sulfadimethoxine (SDM) is one of the anti-thyroid agents and induces proliferation of thyroid capsule in two stage thyroid carcinogenesis model using N-bis(2-hydroxypropyl)nitrosamine (DHPN). In this study, we examined the effect of caffeine on fibrous proliferation of thyroid capsule in DHPN and SDM-treated rats. Five-week-old male F344 rats were given a single subcutaneous injection of DHPN (2,800 mg/kg, body weight). Starting one week thereafter, SDM (1,000 ppm in drinking water) with or without caffeine (1,500 ppm in diet) was administered for 12 weeks. All animals were autopsied and histopathological examination of the thyroid glands was performed. Thyroid follicular proliferative changes were induced in all rats treated with DHPN+SDM. In addition, the proliferation of perithyroidal fibrous tissue and pleomorphic thyroid follicular cells within the capsule were observed in DHPN+SDM treated group. Caffeine would not be related to these lesions in this experimental condition. although pentoxifylline, a methyl xanthine derivative, has an anti fibrotic effects.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.8
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• pp.3565-3572
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• 2015

Background: Breast cancer is the most common cancer among women and leading cause of death worldwide, including in Turkey. High perceptions of cancer fatalism are associated with lower rates of participation in screening for breast cancer. This study was conducted to evaluate the effect of breast cancer fatalism and other factors on breast cancer awareness among nursing students in Turkey. Materials and Methods: This cross-sectional descriptive study was conducted at three universities in the Western Black Sea region. The sample was composed of 838 nursing students. Data were collected by Personal Information Form, Powe Fatalism Inventory (PFI) and Champion's Health Belief Model Scale (CHBMS). Results: Breast cancer fatalism perception of the students was at a low level. It was determined that students; seriousness perception was moderate, health motivation, BSE benefits and BSE self-efficacy perceptions were high, and BSE barriers and sensitivity perceptions were low. In addition, it was determined that students awareness of breast cancer was affected by breast cancer fatalism, class level, family history of breast cancer, knowledge on BSE, source of information on BSE, frequency of BSE performing, having breast examination by a healthcare professional within the last year and their health beliefs. Conclusions: In promoting breast cancer early diagnosis behaviour, it is recommended to evaluate fatalism perceptions and health beliefs of the students and to arrange training programs for this purpose.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.22 no.2
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• pp.126-132
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• 2010

An approach to calculating expected damage of breakwater assisted by artificial neural network was developed. Wave height in front of a breakwater was predicted by a trained artificial neural network with inputs of wave height in deep ocean and tidal level. Prediction results by the neural network can be comparable to that by professional numerical model for wave transformation. Using the wave prediction neural network, it was very easy and fast to obtain a number of significant waves at breakwater and finally analysis time for expected damage can be shortened. In addition, the effect of considering tidal level in the calculation of expected damage was revealed by comparing the expected damages with and without tidal variation. Therefore, it was pointed out that tidal variation should be considered to improve prediction accuracy.

• The Journal of the Korea Contents Association
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• v.14 no.9
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• pp.450-462
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• 2014

The main purpose of this study was to explore the causal relationships among transactional leadership, coaches' emotional intelligence, and athlete satisfaction in soccer teams. High school, university, and semi-professional soccer players(N=495) in Korea participated in a survey. Transactional leadership inventory, emotional intelligence test, and athlete satisfaction questionnaire previously developed to investigate was performed to utilize. The data were analyzed by structural equation model of the AMOS 18.0. The results were as follows; transactional leadership have meaningful influence on emotional intelligence and athlete satisfaction, and emotional intelligence have significant influences on athlete satisfaction. The mediating effect of leader's emotional intelligence between transactional leadership and athlete satisfaction was confirmed. Findings of this study can enhance our understanding of the emotional leadership to increase athlete satisfaction in Soccer players.

• Journal of Korean Academy of Nursing
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• v.46 no.6
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• pp.793-803
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• 2016

Purpose: Developmental care has been recognized as a very important component for the development and health promotion of preterm infants. However, research on how to assess developmental nursing competency has not been studied as expected. This study was done to develop and evaluate a new scale to measure nursing competency for developmental support of preterm infants. Methods: Concept analysis was done with using the Hybrid model of Schwartz-Barcott and Kim (2000), from which a preliminary new scale (30 items) was developed. To test the validity and reliability of the new scale being developed, data were collected from 122 NICU nurses at 4 hospitals in 3 cities in the Republic of Korea, from December, 2014 to March, 2015. Results: The final version of the Developmental Support Competency Scale for Nurses (DSCS-N) caring for premature infants was a 4-point Likert type scale, consisting of 19 items, and categorized as 6 factors, explaining 62.5% of the total variance. Each of the factors were named as follows; 'environmental support' (4 items), 'parental support' (3 items), 'interaction' (3 items), 'critical thinking' (3 items), 'professional development' (3 items), and 'partnership' (3 items). The Cronbach's ${\alpha}$ coefficient for the scale was .83 and the reliability of the subscales ranged from .60~.76. Conclusion: The psychometric evaluation of the new scale demonstrated an acceptable validity and reliability. Findings indicate that the DSCS-N can be used as the tool to test the effect of educational programs for nurses and contribute to advance developmental care for preterm infants.

• Convergence Security Journal
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• v.17 no.2
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• pp.153-158
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• 2017

The robot imitates humans and recognizes the external environment and judges the situation. The robot is a machine that operates autonomously. Robots are divided into manufacturing robots and service robots. Service robots are classified as professional service robots and personal service robots. Because of the intensified competition of productivity in manufacturing industries, rising safety issues, low birth rate and aging, the robots industry is emerging. Recently, the robot industry is a complex of advanced technology fields, and it is attracting attention as a new industry where innovation potential and growth potential are promising. IT, BT, and NT related elements are fused and implemented, and the ripple effect is very large. Due to changes in social structure and life patterns, social interest in life extension and health is increasing. There is much interest in the medical field. Now the artificial intelligence (AI) industry is growing rapidly. It is necessary to secure global competitiveness through strengthening cooperation between large and small companies. We must combine R&D investment capability and marketing capability, which are advantages of large corporations, and robotic technology. We need to establish a cooperative model and secure global competitiveness through M&A.

• Journal of Convergence for Information Technology
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• v.9 no.8
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• pp.63-73
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• 2019

The purpose of this study is to examine the effects of nursing work environment and reciprocity on job embeddedness in the small and medium size hospital nurses. The data were collected from questionnaires filled out by 206 nurses. Data collection was performed from March 4 to 22, 2019. The collected data were analyzed by SPSS 25.0 program. As a result of the research, the study model accounted for 66.0% of job embeddedness. The most powerful variable affecting job embeddedness was support system of nurse, among sub - variables of nursing work environment. Therefore, nursing managers should improve the nurse's job embeddedness by creating nursing work environment that supports nurses such as salary improvement, professional development and promotion opportunities. In addition, it suggests that improvement of hospital and nursing organization system is needed to maintain cooperative relationship with nursing team or other health care professionals.

• Journal of Information Technology Services
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• v.17 no.4
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• pp.101-117
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• 2018

Companies are responding appropriately to the rapidly changing business environment and striving to lead those changes. As part of that, we are meeting our strategic goals through IT projects, which increase the number of simultaneous projects and the importance of project portfolio management for successful project execution. It also strives for efficient deployment of human resources that have the greatest impact on project portfolio management. In the early stages of project portfolio management, it is very important to establish a reasonable manpower plan and allocate performance personnel. This problem is a problem that can not be solved by linear programming because it is calculated through the standard deviation of the input ratio of professional manpower considering the uniformity of load allocated to the input development manpower and the importance of each project. In this study, genetic algorithm, one of the heuristic methods, was applied to solve this problem. As the objective function, we used the proper input ratio of projects, the input rate of specialist manpower for important projects, and the equal load of workload by manpower. Constraints were not able to input duplicate manpower, Was used as a condition. We also developed a program for efficient application of genetic algorithms and confirmed the execution results. In addition, the parameters of the genetic algorithm were variously changed and repeated test results were selected through the independent sample t test to select optimal parameters, and the improvement effect of about 31.2% was confirmed.

• Journal of Korean Medicine Rehabilitation
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• v.31 no.4
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• pp.1-11
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• 2021

Objectives Hwanggeumjakyak-tang (HJT) has traditionally been used to treat gastrointestinal inflammatory diseases; however, its protective effects against neuronal inflammation are still undiscovered. Methods We investigated the anti-neuroinflammatory effects of HJT water extract on lipopolysaccharide (LPS)-stimulated BV2 mouse microglia cells. BV2 cells were treated with LPS (1 ㎍/mL) 1 hour prior to the addition of HJT. We measured cell viability using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) assay and nitrite production using the Griess assay. We performed a reverse transcription-polymerase chain reaction assay to measure messenger RNA expression of inflammatory cytokines including interleukin (IL)-1β, IL-6, and tumor necrosis factor (TNF)-α. Western blot analysis was performed to determine protein expression of mitogen-activated protein kinases (MAPKs) and inhibitor of nuclear factor kappa B (NF-κB)α. Results HJT inhibited excessive nitrite release in LPS-stimulated BV2 cells and also significantly inhibited inflammatory cytokines such as IL-1β, IL-6, and TNF-α in LPS-stimulated BV2 cells. Moreover, HJT significantly suppressed LPS-induced MAPK and NF-κB activation and inhibited the elevation of IL-1β, IL-6, and TNF-α in the brain of LPS-injected mice. Conclusions Our study highlights the anti-neuroinflammatory effects of HJT via MAPK and NF-κB deactivation.

• Progress in Medical Physics
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• v.31 no.3
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• pp.111-123
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• 2020

Deep learning (DL) is a subset of machine learning and artificial intelligence that has a deep neural network with a structure similar to the human neural system and has been trained using big data. DL narrows the gap between data acquisition and meaningful interpretation without explicit programming. It has so far outperformed most classification and regression methods and can automatically learn data representations for specific tasks. The application areas of DL in radiation oncology include classification, semantic segmentation, object detection, image translation and generation, and image captioning. This article tries to understand what is the potential role of DL and what can be more achieved by utilizing it in radiation oncology. With the advances in DL, various studies contributing to the development of radiation oncology were investigated comprehensively. In this article, the radiation treatment process was divided into six consecutive stages as follows: patient assessment, simulation, target and organs-at-risk segmentation, treatment planning, quality assurance, and beam delivery in terms of workflow. Studies using DL were classified and organized according to each radiation treatment process. State-of-the-art studies were identified, and the clinical utilities of those researches were examined. The DL model could provide faster and more accurate solutions to problems faced by oncologists. While the effect of a data-driven approach on improving the quality of care for cancer patients is evidently clear, implementing these methods will require cultural changes at both the professional and institutional levels. We believe this paper will serve as a guide for both clinicians and medical physicists on issues that need to be addressed in time.