• Journal of the Korea Safety Management & Science
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• v.25 no.4
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• pp.15-23
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• 2023

This study analyzed effective capacity building education plans for public institution management supervisors. A survey was conducted on 635 management supervisors of public institutions (99 institutions) subject to the safety management rating system to understand the characteristics of educational participants and the impact of educational satisfaction on professionalism improvement after capacity building education. As a result of statistical analysis, the professional improvement according to the affiliation of educational participants was higher in the workplace and construction site divisions than in the research facility division, and the professional improvement according to the working period was higher for more than 15 years than for less than 5 years and less than 15 years. In addition, the quality of education had a significant positive (+) effect on the degree of professional improvement. This study can be used as basic data for further research related to capacity building education for public institution management supervisors

• Nuclear Engineering and Technology
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• v.56 no.1
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• pp.222-232
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• 2024

New modular factory-built methodologies implemented in the construction and industrial plant industries may bring down costs for modular reactors. A factory-built environment brings about benefits such as; improved equipment, tools, quality, shift patterns, training, continuous improvement learning, environmental control, standardisation, parallel working, the use of commercial off shelf equipment and much of the commissioning can be completed before leaving the factory. All these benefits combine to reduce build schedules, increase certainty, reduce risk and make financing easier and cheaper.Currently, the construction and industrial chemical plant industries have implemented successful modular design and construction techniques. Therefore, the objectives of this paper are to understand and analyse the state of the art research in these industries through a systematic literature review. The research can then be assessed and applied to modular reactors.The literature review highlighted analysis methods that may prove to be useful. These include; modularisation decision tools, stakeholder analysis, schedule, supply chain, logistics, module design tools and construction site planning. Applicable research was highlighted for further work exploration for designers to assess, develop and efficiently design their modular reactors.

• Journal of the Korean Society of Physical Medicine
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• v.19 no.1
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• pp.119-129
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• 2024

PURPOSE: The purpose of this study was to examine the effectiveness of a low-intensity combined exercise program on daily physical fitness parameters such as balance, flexibility, muscle strength, and fear of falling of elderly women in the community. METHODS: This study assigned 30 elderly women randomly into two groups: The control and experimental groups. The control group (n = 15) underwent routine gait. The experimental group (n = 15) underwent the low-intensity combined exercise. The exercise program in this study comprising combined exercise, including balance, flexibility, muscle strength training, and the exercise program using props was conducted twice a week for 8 weeks. RESULTS: The average age of the control and experimental groups was 77.27 years and 78.33 years, respectively. There were significant differences in static balance (t = -4.167, p < .001), dynamic balance (t = 2.463, p < .001), (t = -3.870, p < .001), (t = -2.262, p < .001), (t = -5.732, p < .001), (t = -6.573, p < .001), and fear of falling (t = -5.129, p < .001). CONCLUSION: The results show that low-intensity combined exercise is an effective intervention that improves physical health fear of falling in older women. The combined exercise program was found to be more effective in terms of physical function and fall-related psychological function compared to the control group that only walked.

• International journal of advanced smart convergence
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• v.13 no.1
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• pp.212-220
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• 2024

When a typhoon or natural disaster occurs, a significant number of orchard fruits fall. This has a great impact on the income of farmers. In this paper, we introduce an AI-based method to enhance low-quality raw images. Specifically, we focus on apple images, which are being used as AI training data. In this paper, we utilize both a basic program and an artificial intelligence model to conduct a general image process that determines the number of apples in an apple tree image. Our objective is to evaluate high and low performance based on the close proximity of the result to the actual number. The artificial intelligence models utilized in this study include the Convolutional Neural Network (CNN), VGG16, and RandomForest models, as well as a model utilizing traditional image processing techniques. The study found that 49 red apple fruits out of a total of 87 were identified in the apple tree image, resulting in a 62% hit rate after the general image process. The VGG16 model identified 61, corresponding to 88%, while the RandomForest model identified 32, corresponding to 83%. The CNN model identified 54, resulting in a 95% confirmation rate. Therefore, we aim to select an artificial intelligence model with outstanding performance and use a real-time object separation method employing artificial function and image processing techniques to identify orchard fruits. This application can notably enhance the income and convenience of orchard farmers.

• Journal of Korean Critical Care Nursing
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• v.17 no.2
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• pp.55-70
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• 2024

Purpose : The demand for skilled critical care nurses and the significant impact of the practice-readiness gap underscore the need for educational programs bridging nursing education and clinical practice. This would ensure safe, high-quality patient care and a stable workforce. This study aimed to explore the educational needs of critical care nurses to develop an essential nursing education program for nursing students, addressing the practice-readiness gap they may encounter as new nurses. Methods : The study espoused a qualitative approach by utilizing focus group interviews conducted in South Korea in April and May 2022. A total of 11 nurses participated in the study. Data were collected from three focus groups, each consisting of three to four nurses from intensive care units. Focus group interviews were conducted using a semi-structured questionnaire. Content analysis was performed on the interview data using thematic analysis. Ethical approval for the study was obtained from the institutional review board. Results : Nursing education programs in intensive care units should prioritize fundamental nursing competencies such as basic nursing and physical examinations. Participants' critical care nursing education needs were categorized into four main themes: holistic nursing competency, advancement of practical education, skilled communication, and systematic critical care nursing education. Conclusion : The study's findings provide valuable insights and guidelines for developing critical and intensive care nursing education programs tailored for nursing students.

• Journal of Information Processing Systems
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• v.20 no.4
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• pp.491-500
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• 2024

In hopes of resolving the issue of poor quality of information input for teaching spoken English online, the study creates an English teaching assistance model based on a recognition algorithm named dynamic time warping (DTW) and relies on automated voice recognition technology. In hopes of improving the algorithm's efficiency, the study modifies the speech signal's time-domain properties during the pre-processing stage and enhances the algorithm's performance in terms of computational effort and storage space. Finally, a simulation experiment is employed to evaluate the model application's efficacy. The study's revised DTW model, which achieves recognition rates of above 95% for all phonetic symbols and tops the list for cloudy consonant recognition with rates of 98.5%, 98.8%, and 98.7% throughout the three tests, respectively, is demonstrated by the study's findings. The enhanced model for DTW voice recognition also presents higher efficiency and requires less time for training and testing. The DTW model's KS value, which is the highest among the models analyzed in the KS value analysis, is 0.63. Among the comparative models, the model also presents the lowest curve position for both test functions. This shows that the upgraded DTW model features superior voice recognition capabilities, which could significantly improve online English education and lead to better teaching outcomes.

• Journal of Korean Academy of Nursing
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• v.54 no.3
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• pp.300-310
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• 2024

Purpose: Medical support staff nurses have traditionally performed various supportive tasks for physicians, often extending beyond standard nursing roles. Despite these long-standing practices, there is a notable lack of official recognition and legal protection for these expanded responsibilities, leading to increasing legal concerns. Therefore, there is a need for proposing a rational solution to address these issues. Methods: The number of medical support staff nurses is rising, particularly as they fill gaps left by the 2024 resident physician strike. The study focuses on identifying potential challenges arising from this shift and developing strategic improvements to address these challenges effectively. Results: This study proposed legally expanding the scope of nursing duties and creating a robust system for training and certifying nurses to handle these responsibilities effectively, by integrating these roles within the advanced practice nurse (APN) framework. Conclusion: Integrating these roles within the framework of APN can offer a sustainable and legally sound solution to the ongoing healthcare crisis, ensuring patient safety and safeguarding healthcare workers' legal rights.

• Annual Conference of KIPS
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• 2024.10a
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• pp.760-763
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• 2024

Detecting vulnerabilities in source code is essential for maintaining software security, but traditional methods like static and dynamic analysis often struggle with the complexity of modern software systems. Large Language Models (LLMs), such as GPT-4, have emerged as promising tools due to their ability to learn programming language patterns from extensive datasets. However, their application in vulnerability detection faces significant hurdles. This paper explores the key challenges limiting the effectiveness of LLMs in this domain, including limited understanding of code context, scarcity of high-quality training data, accuracy and reliability issues, constrained context windows, and lack of interpretability. We analyze how these factors impede the models' ability to detect complex vulnerabilities and discuss their implications for security-critical applications. To address these challenges, we propose several directions for improvement: developing specialized and diverse datasets, integrating LLMs with traditional static analysis tools, enhancing model architectures for better code comprehension, fostering collaboration between AI systems and human experts, and improving the interpretability of model outputs. By pursuing these strategies, we aim to enhance the capabilities of LLMs in vulnerability detection, contributing to the development of more secure and robust software systems.

• Journal of Acupuncture Research
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• v.41
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• pp.209-215
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• 2024

Background: The increasing importance of developing good clinical skills in medical education underscores the value of an objective structured clinical examination (OSCE). Additionally, ultrasound devices and studies have been frequently used by Korean medical doctors. However, education and use of ultrasound in the current curriculum in Korea are insufficient; therefore, we developed an OSCE for shoulder joint ultrasonography for clinical practice students at Korean medical universities. Methods: We reviewed previous studies and shoulder ultrasound guidelines to create a checklist for an OSCE. A satisfaction questionnaire survey was also developed by collecting and analyzing existing survey data on medical education satisfaction to address quality and problems of OSCE. Results: The checklist consisted of six items: ultrasound preparation, biceps tendon detection, subscapularis detection, supraspinatus detection, infraspinatus and teres minor detection, and finishing. The satisfaction survey consisted of four items: topic appropriateness and difficulty assessment, content assessment, self-assessment, and comment on the OSCE. Conclusion: We developed an ultrasound OSCE checklist for the rotator cuff. The OSCE should be revised based on the satisfaction survey data and expert opinions in the future. Our study data can be useful for practical training at Korean medical universities.

• Culinary science and hospitality research
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• v.17 no.1
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• pp.26-43
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• 2011

This study aims to give insight into better understanding how service quality influences customers' attitude and behavior in terms of loyalty as well as how its effects vary by the types of restaurants (family restaurants or fast food restaurants). The results of the study are summarized as follows. First, perceived service quality, which consists of food, service, menu and atmosphere, made a significant impact on customer satisfaction for food, menu, atmosphere, and service, respectively. Second, the study examined how perceived service quality affected future expectations, and found only food turned out to be a significant factor. Third, customer satisfaction affected future satisfaction and customer loyalty, and it had a greater impact on attitudinal loyalty than behavioral loyalty. Fourth, future satisfaction affects customer loyalty, and it had a greater impact on attitudinal loyalty than behavioral loyalty. Fifth, the study examined how service quality, customer satisfaction and future expectation affected attitudinal loyalty and behavioral loyalty differently by different types of the food service industry (family restaurants or fast food restaurants) and found out there were some differences in the effects of customer satisfaction on behavioral loyalty and the future expectations and attitudinal loyalty on behavioral loyalty. The marketing implication is that service providers should be one step ahead in understanding the service quality perceived by customers (food, service, menu, and atmosphere). In addition, they should understand that establishing long-tenn relationships with customers by providing high quality service bas a direct impact on their business performance. Furthermore, management in family restaurants and fast food restaurants should include the improvement of service quality in their employee training programs.