Cho, Uiju;Suh, Kwang Sun;Kie, Jeong Hae;Choi, Yeong Jin;Renal Pathology Study Group of Korean Society of Pathologists,
Korean Journal of Transplantation
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v.31
no.4
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pp.170-176
/
2017
We need to establish an informative guideline to increase inter-institutional and inter-observer reproducibility of renal transplant diagnosis, and to improve the diagnostic ability of pathologists in Korea. A first nation-wide survey for renal transplant pathology was conducted by Renal Pathology Study Group of the Korean Society of Pathologists in 2016, to provide the continued excellence in the transplantation pathology laboratory, and to improve the diagnostic ability for the best treatment of transplant patients. This survey revealed the significant variations in scale, work load and biopsy indications for the renal transplant pathology in various institutions in Korea. The Banff classification were used by all institutions for the diagnosis of renal transplant pathology, but different formats were used: most institutions (70%) used the "2013 Banff classification" while the others were using "2007 Banff classification" (20%) or even older formats. In daily diagnostic practice of the renal allografts, difficulties that pathologists encounter were quite diverse due to different environments they work in. Most respondents agreed that standardized diagnostic practice guidelines, regular education on renal transplant pathology and convenient ways of consultation are further needed. We are currently working toward the enhancement of the expertise of renal pathologists and to increase inter-institutional and inter-observer reproducibility by 1) development of a set of virtual slides of renal allograft biopsies for the training, 2) validation and gathering expert's consensus on the core variables of rejection diagnosis by using virtual slides, and 3) continued education by the developed virtual slide atlas.
The fourth industrial revolution is emerging as the talk of the times. The industrial structure is changing greatly from the past, as well as the social scene, changing our daily lives. Especially, the importance of the software sector is growing. For students who have to live in this future society, computational thinking is a key capability. In order to achieve this goal, this study was carried out in the following steps. First, we organized a SW education convergence program based on life-oriented aspects. Second, the configured program was applied to the site to verify the effectiveness of computational thinking. The results of this study show that the experimental group has 32 points better than the pre-test, and the comparative group has about 2 points better. The statistical significance probability was a significant difference of .028. The results of this study may be used as a reference for the training of SW convergence education and future talent in the future.
Background: Legal regulations and fees have been established in Korea to provide visiting oral health care services to individuals with long-term care insurance (LTCI). However, beneficiaries of this service are very limited. Therefore, to improve the Korean system we propose a comparative analysis with the Japanese system. Methods: This study is a descriptive analysis based on secondary data, such as statistics, laws, and service record forms from Korea and Japan. The most recent institutional documents were obtained through a Google search. The variables investigated were financial resources of LTCI, co-payment structure, monthly limit of LTCI benefits, care levels of LTCI, service providers, service costs, contents of service, and the number of cases of service. Results: In both Korea and Japan, LTCI is financed through a combination of taxes and insurance premiums. However, the monthly limit for receiving LTCI services in Japan is about 2.4 times higher than in Korea. Visiting medical and dental treatment is also possible in Japan. Furthermore, nursing staff can provide daily oral health care services according to dental hygienists' instruction unlike Korea. Oral health care services in Korea are focused on oral hygiene and prevention of oral diseases, while Japan additionally provides oral function screening, patient education for oral health management, and training for nursing staff to enhance oral function, eating, and swallowing of the patients. Conclusion: We concluded that the possibility of visiting dental treatment, differences in monthly limit of LTCI benefits, oral function assessment and guidance, as well as collaboration with other healthcare professionals contributed to the difference in the frequency of utilization of visiting oral health care services between Korea and Japan.
Processed meat products play a vital role in our daily dietary intake due to their rich protein content and the inherent convenience they offer. However, they often contain synthetic additives and ingredients that may pose health risks when taken excessively. This review explores strategies to improve meat product quality, focusing on three key approaches: substituting synthetic additives, reducing the ingredients potentially harmful when overconsumed like salt and animal fat, and boosting nutritional value. To replace synthetic additives, natural sources like celery and beet powders, as well as atmospheric cold plasma treatment, have been considered. However, for phosphates, the use of organic alternatives is limited due to the low phosphate content in natural substances. Thus, dietary fiber has been used to replicate phosphate functions by enhancing water retention and emulsion stability in meat products. Reducing the excessive salt and animal fat has garnered attention. Plant polysaccharides interact with water, fat, and proteins, improving gel formation and water retention, and enabling the development of low-salt and low-fat products. Replacing saturated fats with vegetable oils is also an option, but it requires techniques like Pickering emulsion or encapsulation to maintain product quality. These strategies aim to reduce or replace synthetic additives and ingredients that can potentially harm health. Dietary fiber offers numerous health benefits, including gut health improvement, calorie reduction, and blood glucose and lipid level regulation. Natural plant extracts not only enhance oxidative stability but also reduce potential carcinogens as antioxidants. Controlling protein and lipid bioavailability is also considered, especially for specific consumer groups like infants, the elderly, and individuals engaged in physical training with dietary management. Future research should explore the full potential of dietary fiber, encompassing synthetic additive substitution, salt and animal fat reduction, and nutritional enhancement. Additionally, optimal sources and dosages of polysaccharides should be determined, considering their distinct properties in interactions with water, proteins, and fats. This holistic approach holds promise for improving meat product quality with minimal processing.
The development of information and communication technology in the 21st century has increased operational efficiency by providing hyper-connectivity and hyper-intelligence in the control systems of major infrastructure, but is also increasing security vulnerabilities, exposing it to hacking threats. Among them, the electric power system that supplies electric power essential for daily life has become a major target of cyber-attacks as a national critical infrastructure system. Recently, in order to protect these power systems, various security systems have been developed and the stability of the power systems has been maintained through practical cyber battle training. However, as cyber-attacks are combined with advanced ICT technologies such as artificial intelligence and big data, it is not easy to defend cyber-attacks that are becoming more intelligent with existing security systems. In order to defend against such intelligent cyber-attacks, it is necessary to know the types and aspects of intelligent cyber-attacks in advance. In this study, we analyzed the evolution of cyber attacks combined with advanced ICT technology.
International Journal of Computer Science & Network Security
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v.23
no.10
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pp.37-43
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2023
The hospital situation, timing, and patient restrictions have become obstacles to an optimum therapy session. The crowdedness of the hospital might lead to a tight schedule and a shorter period of therapy. This condition might strike a post-stroke patient in a dilemma where they need regular treatment to recover their nervous system. In this work, we propose an in-house and uncomplex serious game system that can be used for physical therapy. The Kinect camera is used to capture the depth image stream of a human skeleton. Afterwards, the user might use their hand gesture to control the game. Voice recognition is deployed to ease them with play. Users must complete the given challenge to obtain a more significant outcome from this therapy system. Subjects will use their upper limb and hands to capture the 3D objects with different speeds and positions. The more substantial challenge, speed, and location will be increased and random. Each delegated entity will raise the scores. Afterwards, the scores will be further evaluated to correlate with therapy progress. Users are delighted with the system and eager to use it as their daily exercise. The experimental studies show a comparison between score and difficulty that represent characteristics of user and game. Users tend to quickly adapt to easy and medium levels, while high level requires better focus and proper synchronization between hand and eye to capture the 3D objects. The statistical analysis with a confidence rate(α:0.05) of the usability test shows that the proposed gaming is accessible, even without specialized training. It is not only for therapy but also for fitness because it can be used for body exercise. The result of the experiment is very satisfying. Most users enjoy and familiarize themselves quickly. The evaluation study demonstrates user satisfaction and perception during testing. Future work of the proposed serious game might involve haptic devices to stimulate their physical sensation.
KSCE Journal of Civil and Environmental Engineering Research
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v.43
no.6
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pp.763-774
/
2023
The water availability in a river is related to the return flow of residential water. However it is still difficult to determine the exact return flow. In this study, the residential water-cycle system is defined as a process consisting of water inflow, water transfer and water outflow. The study area is Hampyeong-gun, Jeollanam-do, and is set as a single inflow to a single outflow through the water-cycle system after classification of complete and incomplete measurement points. The time-series prediction models(ARIMA model and TFM) are established with daily inflow and outflow data for 6 years. Inflow and outflow are predicted by dividing into training and test periods. As a result, both models show the feasibility of short-term prediction by deriving stable residuals and securing statistical significance, implementing the preliminary form of the water-cycle system. As a further study, it is suggested to predict the actual return flow of the target basin and efficient water operation by adding input factors and selecting the optimal model.
Kyung-Jin RYU;Su-Hyung KIM;Kyunghun LEE;Sunghun KIM;Sung-Jae WON;Yoo-Won LEE
Journal of the Korean Society of Fisheries and Ocean Technology
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v.60
no.2
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pp.152-160
/
2024
We analyzed risk factors of coastal gillnet fishers during fishing process and considered work safety measures to reduce safety accidents during fishing using a UWB (ultra wideband) based positioning system. The static position accuracy of the UWB based positioning system was 45 cm. When entering a port, there is a risk of falling overboard. When casting a net, there was a risk of falling overboard due to being hit by fishing gear or guards, or getting caught in a buoy line or sinker line. When hauling a net, there is a risk of getting caught between fishing gear and net hauler, and the risk of musculoskeletal disorders due to repetitive work over a long period of time. Most safety accidents during work on fishing boats are blamed on human errors of the fisher and skipper, but safety accidents occur due to a mixture of mechanical and equipment factors, work and environmental factors, and management factors in addition to human errors. Therefore, the 4E were presented as countermeasures against the 4M, which are causes of safety accidents, and the proposed measures were used to identify risk factors for operation process, comply with work safety rules, and ensure the wearing of personal protective equipments. We need to reduce safety accidents during work by making it part of our daily routine. These research results can be used in the future for optimal placement of fishing gear and fishing nets in other coastal industries where safety accidents occur frequently.
The objective of this study was to conduct research and analysis using Group Focus Interview to survey the between construction site workers and managers implementing for the Severe Accident Punishment Act. Focused on measures to improve safety management effectiveness for the effectiveness of establishing a safety management system. A plan to improve the efficient safety management system was presented to 50 construction industrial managers and workers. In order to ensure the industrial accident prevention policies appropriately, it is necessary to be aware of safety obligations for workers as well as business operators. In addition, despite the existence of a commentary on the Serious Accident Punishment Act, confusion in the field still persists, so in the event of a major accidents, the obligation to take safety and health education is strengthened, and effective case education is proposed by teaching actual accident cases suitable for actual working sites. It is necessary to make all training mandatory, and it is necessary to reconsider awareness through writing a daily safety log, awareness of risk factors, etc., and writing down risk information. Above all, at the construction ordering stage, it is necessary to keep the construction safety, request corrections and supplements for problems issues that arise, and consult between the orderer and the construction company about the problems issues. Rather than having only the construction company correct or supplement the safety management plan, the contents should be shared with supervisors and workers to establish a more practical solution. Results of this study will contribute to improving the effectiveness of the serious accident and construction safety management system.
Korean Journal of Agricultural and Forest Meteorology
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v.25
no.2
/
pp.80-98
/
2023
This study explores the effectiveness of various data preprocessing algorithms for improving subseasonal to seasonal (S2S) climate predictions from six climate forecast models and their Multi-Model Ensemble (MME) using a deep learning-based postprocessing model. A pipeline of data transformation algorithms was constructed to convert raw S2S prediction data into the training data processed with several statistical distribution. A dimensionality reduction algorithm for selecting features through rankings of correlation coefficients between the observed and the input data. The training model in the study was designed with TimeDistributed wrapper applied to all convolutional layers of U-Net: The TimeDistributed wrapper allows a U-Net convolutional layer to be directly applied to 5-dimensional time series data while maintaining the time axis of data, but every input should be at least 3D in U-Net. We found that Robust and Standard transformation algorithms are most suitable for improving S2S predictions. The dimensionality reduction based on feature selections did not significantly improve predictions of daily precipitation for six climate models and even worsened predictions of daily maximum and minimum temperatures. While deep learning-based postprocessing was also improved MME S2S precipitation predictions, it did not have a significant effect on temperature predictions, particularly for the lead time of weeks 1 and 2. Further research is needed to develop an optimal deep learning model for improving S2S temperature predictions by testing various models and parameters.
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