• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.45-50
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• 2022

The article substantiates the feasibility of using and actively implementing innovative technologies in the practice of organizing the educational process. The need for the use of telecommunication technologies, which provide constant communication between students and the teacher outside the classroom, has been identified. Particular attention is paid to the latest approaches to the use of various forms of multimedia technologies in student education, which intensify the process of acceptance and assimilation of educational material by foreign students. The advantages of using innovative means of distance education are determined, which thanks to modern electronic educational systems allow students to receive quality higher education. Innovative technologies promote the development of cognitive interest in students, they learn to systematize and summarize the material studied, discuss and debate. In this regard, the reorientation of the system of higher education in Europe towards innovation is becoming the most important tool in ensuring the competitiveness of graduates in the labor market. In addition, the investment attractiveness of a university often depends on the innovative nature of the development of scientific, educational and practical activities of the subjects of the educational process, their inclusion in the national innovation system. The article analyzes that in the universities of the European Union in the training of specialists in the management of basic interactive methods, forms and tools are binary lecture, briefing, webinar, video conference, video lecture, virtual consultation, virtual tutorial, slide lecture, comp. utheric tests. Various classes on slide technology took active forms during the training of management specialists.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.30 no.4
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• pp.117-131
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• 2022

Human rights education is to acquire understanding and knowledge about human rights, to develop values, attitudes and character that respect human rights, to develop the ability to overcome human rights violations and discriminatory acts, and to protect and promote the human rights of others. In order to prevent human rights violations of the transportation vulnerable, such as the disabled, it is necessary to develop specialized human rights education plans for aviation security personnel to practice human rights perspectives. Therefore, in accordance with the 「National Civil Aviation Security Education and Training Guidelines」, specialized human rights education should be included in the initial aviation security education and regular education courses. The point is that there is a need to reexamine the aviation security education program for aviation security personnel based on the essential knowledge and educational contents for aviation security personnel to perform security screening tasks in the aviation security education course. When this happens, various efforts must be made to improve the human rights of the transportation vulnerable, such as the disabled, during the security screening process, so that human rights violations will be significantly reduced. In particular, it is necessary to enhance the ability to detect dangerous terrorist items such as weapons or explosives that can be used for illegal sabotage through practical security screening training. For aviation security and aircraft safety, efforts to improve the quality of aviation security personnel training, such as human rights training, must be continuously made while thoroughly preparing for terrorism in advance.

• Korean Journal of Exercise Nutrition
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• v.16 no.1
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• pp.27-33
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• 2012

This study was conducted to investigate the effect of a 24-week combined exercise training program in older women with hypertension. Women with hypertension who were 70 years and older were randomized into two groups: combined exercise group (CE; n = 15) and a control group (n = 15). The CE group performed a combined exercise training program four times per week for 24 weeks and the control group did not. Five factors, including body composition (percent body fat and skeletal muscle mass), health-related physical fitness, adipocytokines (interleukin-6 [IL-6] and tumor necrosis factor-alpha [TNF-α]), kidney risk factors (glomerular filtration rate [GFR] and cystatin C), and systolic and diastolic blood pressure were measured before and after the program. The findings showed that total muscle mass, health-related physical fitness factors, and GFR increased significantly in the CE group compared to those in the control. Additionally, systolic and diastolic blood pressure and IL-6, TNF-α, and cystatin C levels in the CE group decreased significantly after the intervention. In contrast, total muscle mass decreased significantly and blood pressure remained unchanged in the control group. These results suggest that CE training may positively impact circulating levels of adipocytokines and cystatin C and improve physical fitness levels in elderly women with hypertension. Therefore, CE training helps to prevent renal disease and improve health-related physical fitness, eventually leading to a better quality of life.

• Animal Bioscience
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• v.37 no.4_spc
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• pp.730-741
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• 2024

Pig production is one of the viable enterprises of the livestock sub-sector of agriculture. It contributes significantly to the economy and animal protein supply to enhance food security in Africa and globally. This article explored the present status of pig production in Africa, the challenges, prospects and potentials. The pig population of Africa represents 4.6% of the global pig population. They are widely distributed across Africa except in Northern Africa where pig production is not popular due to religio-cultural reasons. They are mostly reared in rural parts of Africa by smallholder farmers, informing why majority of the pig population in most parts of Africa are indigenous breeds and their crosses. Pig plays important roles in the sustenance of livelihood in the rural communities and have cultural and social significance. The pig production system in Africa is predominantly traditional, but rapidly growing and transforming into the modern system. The annual pork production in Africa has grown from less than a million tonnes in year 2000 to over 2 million tonnes in 2021. Incidence of disease outbreak, especially African swine fever is one of the main constraints affecting pig production in Africa. Others are lack of skills and technical know-how, high ambient temperature, limited access to high-quality breeds, high cost of feed ingredients and veterinary inputs, unfriendly government policies, religious and cultural bias, inadequate processing facilities as well as under-developed value-chain. The projected human population of 2.5 billion in Africa by 2050, increasing urbanization and decreasing farming population are pointers to the need for increased food production. The production systems of pigs in Africa requires developmental research, improvements in housing, feed production and manufacturing, animal health, processing, capacity building and pig friendly policies for improved productivity and facilitation of export.

• Imaging Science in Dentistry
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• v.54 no.3
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• pp.257-263
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• 2024

Purpose: The purpose of this study was to classify mandibular molar furcation involvement (FI) in periapical radiographs using a deep learning algorithm. Materials and Methods: Full mouth series taken at East Carolina University School of Dental Medicine from 2011-2023 were screened. Diagnostic-quality mandibular premolar and molar periapical radiographs with healthy or FI mandibular molars were included. The radiographs were cropped into individual molar images, annotated as "healthy" or "FI," and divided into training, validation, and testing datasets. The images were preprocessed by PyTorch transformations. ResNet-18, a convolutional neural network model, was refined using the PyTorch deep learning framework for the specific imaging classification task. CrossEntropyLoss and the AdamW optimizer were employed for loss function training and optimizing the learning rate, respectively. The images were loaded by PyTorch DataLoader for efficiency. The performance of ResNet-18 algorithm was evaluated with multiple metrics, including training and validation losses, confusion matrix, accuracy, sensitivity, specificity, the receiver operating characteristic (ROC) curve, and the area under the ROC curve. Results: After adequate training, ResNet-18 classified healthy vs. FI molars in the testing set with an accuracy of 96.47%, indicating its suitability for image classification. Conclusion: The deep learning algorithm developed in this study was shown to be promising for classifying mandibular molar FI. It could serve as a valuable supplemental tool for detecting and managing periodontal diseases.

• Culinary science and hospitality research
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• v.22 no.2
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• pp.252-269
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• 2016

This study was conducted to analyze the influence of the service quality of the food court on customer satisfaction, revisit intention in a discount store. Among the 400 surveys, 371 participants were collected and 350 respondents were analyzed for the statistical analysis to verify research purposes. SPSS 21.0 program was used to derive the following: factor analysis, reliability analysis, simple regression, and multiple regression analysis. Results shown that, first, service quality at the discount store can affect the customer's satisfaction. The factors which can affect the customer's satisfaction are type, empathy and credibility but guarantee and reactivity don't affect it. Second, service quality at the discount store can affect a customer's revisiting. The factors which can affect the customer's revisiting are type, guarantee, empathy and credibility but reactivity doesn't affect it. Third, the customer's satisfaction at the discount store can affect the customer's revisit intention. Through this study, food court service quality can affect not only the customers' satisfaction but also consumers' revisit intention. Therefore, the company and the management need to keep researching and developing various menus, customer service training, and hygiene training in order to set the customer at ease along with making a comfortable mood and set up a dine out & meeting system.

• Agricultural and Biosystems Engineering
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• v.4 no.1
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• pp.8-15
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• 2003

In Korea, quality evaluation of dried oak mushrooms are done first by classifying them into more than 10 different categories based on the state of opening of the cap, surface pattern, and colors. And mushrooms of each category are further classified into 3 or 4 groups based on its shape and size, resulting into total 30 to 40 different grades. Quality evaluation and sorting based on the external visual features are usually done manually. Since visual features of mushroom affecting quality grades are distributed over the entire surface of the mushroom, both front (cap) and back (stem and gill) surfaces should be inspected thoroughly. In fact, it is almost impossible for human to inspect every mushroom, especially when they are fed continuously via conveyor. In this paper, considering real time on-line system implementation, image processing algorithms utilizing artificial neural network have been developed for the quality grading of a mushroom. The neural network based image processing utilized the raw gray value image of fed mushrooms captured by the camera without any complex image processing such as feature enhancement and extraction to identify the feeding state and to grade the quality of a mushroom. Developed algorithms were implemented to the prototype on-line grading and sorting system. The prototype was developed to simplify the system requirement and the overall mechanism. The system was composed of automatic devices for mushroom feeding and handling, a set of computer vision system with lighting chamber, one chip microprocessor based controller, and pneumatic actuators. The proposed grading scheme was tested using the prototype. Network training for the feeding state recognition and grading was done using static images. 200 samples (20 grade levels and 10 per each grade) were used for training. 300 samples (20 grade levels and 15 per each grade) were used to validate the trained network. By changing orientation of each sample, 600 data sets were made for the test and the trained network showed around 91 % of the grading accuracy. Though image processing itself required approximately less than 0.3 second depending on a mushroom, because of the actuating device and control response, average 0.6 to 0.7 second was required for grading and sorting of a mushroom resulting into the processing capability of 5,000/hr to 6,000/hr.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.27 no.2
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• pp.71-86
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• 2022

The water quality index (WQI) has been widely used to evaluate marine water quality. The WQI in Korea is categorized into five classes by marine environmental standards. But, the WQI calculation on huge datasets is a very complex and time-consuming process. In this regard, the current study proposed machine learning (ML) based models to predict WQI class by using water quality datasets. Sihwa Lake, one of specially-managed coastal zone, was selected as a modeling site. In this study, adaptive boosting (AdaBoost) and tree-based pipeline optimization (TPOT) algorithms were used to train models and each model performance was evaluated by metrics (accuracy, precision, F1, and Log loss) on classification. Before training, the feature importance and sensitivity analysis were conducted to find out the best input combination for each algorithm. The results proved that the bottom dissolved oxygen (DO_Bot) was the most important variable affecting model performance. Conversely, surface dissolved inorganic nitrogen (DIN_Sur) and dissolved inorganic phosphorus (DIP_Sur) had weaker effects on the prediction of WQI class. In addition, the performance varied over features including stations, seasons, and WQI classes by comparing spatio-temporal and class sensitivities of each best model. In conclusion, the modeling results showed that the TPOT algorithm has better performance rather than the AdaBoost algorithm without considering feature selection. Moreover, the WQI class for unknown water quality datasets could be surely predicted using the TPOT model trained with satisfactory training datasets.

• Korean Journal of Organic Agriculture
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• v.31 no.2
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• pp.135-155
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• 2023

The purpose of this study is to investigate the relationship between the service quality of WPL (Work Place Learning) and the revisit intention through customer satisfaction, targeting users who use the WPL. Data to achieve the purpose of this study were conducted for trainees who had received on-the-job training at 4 selected WPL in Jeollabuk-do. Out of the 210 copies of questionnaires, 170 were picked up, and all of them were used for analysis. As a result of the analysis, First, as a result of analyzing the relationship between service quality and customer satisfaction in WPL, it was discovered that among the service quality components, Responsiveness, Assurance, and Empathy had a substantial influence on customer satisfaction, while Tangibles and Reliability of service quality did not appear to have any significant effect. Second, it was discovered that customer contentment had a considerable influence on revisit intention after evaluating the link between customer satisfaction and revisit intention. It can be shown that the higher the level of client happiness, the greater the likelihood of returning. Third, as a result of analyzing the relationship between service quality and revisit intention of WPL, among service quality factors, Reliability, Responsiveness, and Empathy were found to have a significant effect on revisit intention. As a result of verifying the mediating effect of service quality at WPL on revisit intention through customer satisfaction, responsiveness, assurance, and empathy of service quality were found to be significant in their relationship with revisit intention.

• Quality Improvement in Health Care
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• v.29 no.2
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• pp.47-63
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• 2023

Purpose:This study aims to suggest the future direction for applying service design to improve the quality of healthcare as part of hospital service innovation and present implementation plans in Korea, based on a review of quality improvement activities and the current status of service design applications. Methods: Through a literature review, we examined the status of service design introduction and application in the healthcare field, focusing on cases in the US and Europe. The possibility and limitations of service design in the healthcare field were examined through a comparison of oversea and domestic cases. Results: Recently, service design has begun to be applied to the healthcare field worldwide. Service design shows the possibility of an alternative that alleviates and complements the limitations of existing quality improvement activities. It also offers the possibility of creating new organizational improvement and innovation approaches through integration and convergence with existing quality improvement activities and management innovation. Conclusion: To effectively apply service design to hospitals, it is necessary to integrate internal organizations related to service improvement, combine methods, and objectively measure and evaluate performance. To this end, we propose the operation of a nationwide education and training center for quality improvement and service design led by academic society. Service design will provide an opportunity to change the management innovation and organizational culture of hospitals beyond the scope of the current quality improvement, which deals only with micro-subjects of individual hospitals.