In the era of global aging and the retirement of baby boomers, the response is very intensive and dynamic. As baby boomers actually retire, the terms for middle-aged people have been diversified into middle-aged, midle-elderly, and the new middle, which are also evident in the training process. In line with the timing, the government and academia are also making efforts to advance the development of training courses for middle-aged, along with organizing terms for middle-aged. From this point of view, this study aims to analyze the performance of the three-year training courses (2018-2020) for the new middle at Korea Polytechnics and suggest the direction of development of the new middle training course. As a result of the study, the three-year performance of the Shin middle-aged training course gradually increased, but the completion rate and employment rate gradually decreased, indicating that countermeasures were needed. In addition, campus performance in the metropolitan area was higher than that in the non-capital area, so a plan for this deviation was needed. In addition, the need for the integrated operation of the existing 'middle-aged' and 'the new middle' courses operated by Korea Polytechnics was suggested, and measures to specialize in the new middle-aged were proposed.
Jung keun Ahn;Kwangsoo Cho;Han-jin Jeong;Ji-hun Jeong;Seung-joo Kim
Journal of the Korea Institute of Information Security & Cryptology
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v.33
no.5
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pp.827-846
/
2023
Recently, various information technologies such as network communication and sensors have begun to be integrated into weapon systems that were previously operated in stand-alone. This helps the operators of the weapon system to make quick and accurate decisions, thereby allowing for effective operation of the weapon system. However, as the involvement of the cyber domain in weapon systems increases, it is expected that the potential for damage from cyber attacks will also increase. To develop a secure weapon system, it is necessary to implement built-in security, which helps considering security from the requirement stage of the software development process. The U.S. Department of Defense is implementing the Risk Management Framework Assessment and Authorization (RMF A&A) process, along with the introduction of the concept of cybersecurity, for the evaluation and acquisition of weapon systems. Similarly, South Korea is also continuously making efforts to implement the Korea Risk Management Framework (K-RMF). However, so far, there are no cases where K-RMF has been applied from the development stage, and most of the data and documents related to the U.S. RMF A&A are not disclosed for confidentiality reasons. In this study, we propose the method for inferring the composition of the K-RMF based on systematic threat analysis method and the publicly released documents and data related to RMF. Furthermore, we demonstrate the effectiveness of our inferring method by applying it to the naval battleship system.
The Autonomous ships are equipped with a function to judge and navigate the sea conditions on their own, so the job of the ship officer who operates it changes. The educational curriculum to nurture ship officer with the ability to operate and manage autonomous ships must also be changed. This study aimed to develop the curriculum for training autonomous ship officer by using the Delphi survey method suitable for predicting the uncertain future. Among the current 61 subjects for training ship officer identified in the Delphi survey, 32 subjects with high importance should be maintained in the training for autonomous ship officer, and subjects with low importance should be abolished or integrated into other subjects. These subjects were collectively referred to as 'general courses'. The expert panel of the Delphi survey suggested 42 items as new subjects, with 18 items of 'high', 14 items of 'middle', and 10 items of 'low'. Through in-depth analysis of these items by experts, 27 subjects were adjusted and three courses were proposed : 1)'Basic course(10 courses)' for developing basic capabilities such as basic theories for understanding advanced technology and information applied to autonomous ships, 2)'Job course(10 courses)' for practical competency directly related to autonomous ship operation, 3)'Intensive course(7 subjects)' for fostering land remote operators of autonomous ships. Since the introduction and spread of autonomous ships will progress rapidly, research to develop and supplement autonomous ship pilot training courses should be continued by reflecting the level of autonomous navigation of autonomous ships.
Journal of the Korea Society of Computer and Information
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v.28
no.11
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pp.29-42
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2023
In this paper, we propose a method to enhance the prediction accuracy of solar irradiance for three major South Korean cities: Seoul, Busan, and Incheon. Our method entails the development of five generative models-vanilla GAN, CTGAN, Copula GAN, WGANGP, and TVAE-to generate independent variables that mimic the patterns of existing training data. To mitigate the bias in model training, we derive values for the dependent variables using random forests and deep neural networks, enriching the training datasets. These datasets are integrated with existing data to form comprehensive solar irradiance prediction models. The experimentation revealed that the augmented datasets led to significantly improved model performance compared to those trained solely on the original data. Specifically, CTGAN showed outstanding results due to its sophisticated mechanism for handling the intricacies of multivariate data relationships, ensuring that the generated data are diverse and closely aligned with the real-world variability of solar irradiance. The proposed method is expected to address the issue of data scarcity by augmenting the training data with high-quality synthetic data, thereby contributing to the operation of solar power systems for sustainable development.
Byeonghan Lee;Deok-Gyeong Seong;Young Min Jin;Yeon-Hyeon Hwang;Young-Gwang Kim
Journal of Internet of Things and Convergence
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v.9
no.6
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pp.93-98
/
2023
In paddy rice farming, water management is a critical task. To suppress weed emergence during the early stages of growth, fields are deeply flooded, and after transplantation, the water level is reduced to promote rooting and stimulate stem generation. Later, water is drained to prevent the production of sterile tillers. The adequacy of water supply is influenced by various factors such as field location, irrigation channels, soil conditions, and weather, requiring farmers to frequently check water levels and control the ingress and egress of water. This effort increases if the fields are scattered in remote locations. Automated irrigation systems have been considered to reduce labor and improve productivity. However, the net income from rice production in 2022 was about KRW 320,000/10a on average, making it financially unfeasible to implement high-cost devices or construct new infrastructure. This study focused on developing an IoT-Based irrigation valve that can be easily integrated into existing agricultural infrastructure without additional construction. The research was carried out in three main areas: Firstly, an irrigation valve was designed for quick and easy installation on existing agricultural pipes. Secondly, a power circuit was developed to connect a low-power Cat M1 communication modem with an Arduino Nano board for remote operation. Thirdly, a cloud-based platform was used to set up a server and database environment and create a web interface that users can easily access.
Journal of the Korea Institute of Construction Safety
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v.6
no.1
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pp.19-26
/
2024
In this study, we analyzed the status of safety management in industrial sites and fatal accident statistics to identify problems and suggest directions for increasing the utilization of convergence engineering. Current industrial site safety management is passive, formal, and unsystematic, and at the same time, the delivery of information on site safety management is very insufficient. In addition, domestic occupational safety and health education was not systematic and could not be considered effective as it was repeating past education forms. Recently, ICT technology has been introduced throughout the industry, and this study suggests several directions for the introduction of convergence safety engineering. Keke is the organization and operation of school curriculum in a convergent manner. In addition, we proposed a plan to apply VR content and experiential education so that safety management education can be conducted in a practical and realistic manner. Lastly, it was proposed to provide differentiated education by industry and type of work, taking into account the characteristics of various industrial sites. It is expected that the results of this study will be able to emphasize the need for convergence and integrated safety education for those involved in the field of domestic industrial safety management and education.
The Journal of The Korea Institute of Intelligent Transport Systems
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v.23
no.2
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pp.119-131
/
2024
Understanding accurate traffic performance is crucial for ensuring efficient highway operation and providing a sustainable mobility environment. On the other hand, an immediate and precise estimation of highway traffic performance faces challenges because of infrastructure and technological constraints, data processing complexities, and limitations in using integrated big data. This paper introduces a framework for estimating traffic performance by analyzing real-time data sourced from toll collection systems and dedicated short-range communications used on highways. In particular, this study addresses the data errors arising from segmented information in data, influencing the individual travel trajectories of vehicles and establishing a more reliable Origin-Destination (OD) framework. The study revealed the necessity of trip linkage for accurate estimations when consecutive segments of individual vehicle travel within the OD occur within a 20-minute window. By linking these trip ODs, the daily average highway traffic performance for South Korea was estimated to be248,624 thousand vehicle kilometers per day. This value shows an increase of approximately 458 thousand vehicle kilometers per day compared to the 248,166 thousand vehicle kilometers per day reported in the highway operations manual. This outcome highlights the potential for supplementing previously omitted traffic performance data through the methodology proposed in this study.
This paper is concerned in the theme of the liability for the breach of duty to inform(Haftungszurechnung der $Aufkl{\ddot{a}}rungspflichtverletzung$) and the malpractice of cosmetic surgery. Here, the terms, treatments for healing purposes and purely medical-technical cosmetic operations are well integrated in the category of "medical conduct(medizinische Handlung)" within the meaning of the public and administrative 'Medical Law'. In the judgment of 6. 13. 2013 Az. 2012DA94865 provides the KHGH(Korean Highest Court of Justice) to inform the patient about the prospects and risks of cosmetic surgery(Infrabrow Excision Blepharoplasty) stringent requirements, similar to the judicature of BGH(cf. BGH, Urt. v. 6. 11. 1990, Az.: VI ZR 8/90). Even in the judgment of 5. 12. 2014 Az. 2013GASO865646 the SZLG(Seoul Central Regional Court) recognizes the physician contract for 'cosmetic septoplasty' as a sort of contract for work. The medical treatment(${\ddot{a}}rztliche$ Heilbehandlung) is still regarded as a prototype of the medical activity, therefore in the meaning of the 'Civil Law(KBGB)', its term needs to be used immediately for healing purposes. The cosmetic operation, desired by a patient, differs from the healing treatment by the element of "indication" and the fact that the "healing purpose(Heilzweck)" itself is missing. In comparative context - methodically fully aware that the unreflective term transfer between different laws might contradict their legal purposes - a series of judgments BSG(BSGE 63, 83, BSGE 72, 96, BSGE, 82, 158, BSGE 93, 252 etc.) and some judgments of LSG are reviewed. In addition, also the dogmatic topic for the "legal natur of a medical treatment contract" is to reconsider by comparative introducing BGHZ 63, 306. Now in view of the current state of greater popularity of artificial cosmetic surgery still indeed is the sentences: The doctor is minister naturae, a helper of nature. A doctor promises regularly only the proper treatment of the patient, but the contractual liability for work should not be excluded in medical conditions for cosmetic surgeries altogether. "With cosmetic operations, seeking to eliminate the external deformities, the doctor may miss the medical profession entirely." - A. Laufs, Medical Law, 5th ed. P. 18.
In this study, a combined process of sequential anaerobic-aerobic digestion (SAAD), fluidized-bed bioreactor (FBBR), and ultrafiltration (UF) for the treatment of small scale food waste leachate was developed and evaluated. The SAAD process was tested for performance and stability by subjecting leachate from food waste to a two-phase anaerobic digestion. The main process used FBBR composed of aerators for oxygen supply and fluidization, three 5 ton reaction chambers containing an aerobic mesophilic microorganism immobilized in PE (polyethylene), and a sedimentation chamber. The HRTs (hydraulic retention time) of the combined SAAD-FBBR-UF process were 30, 7, and 1 day, and the operation temperature was set to the optimal one for microbial growth. The pilot process maintained its performance even when the CODcr of input leachate fluctuated largely. During the operation, average CODcr, TKN, TP, and salt of the effluent were 1,207mg/L, 100mg/L, 50 mg/L, and 0.01 %, which corresponded to the removal efficiencies of 99.4%, 98.6%, 89.6%, and 98.5%, respectively. These results show that the developed process is able to manage high concentration leachate from food waste and remove CODcr, TKN, TP, and salt effectively.
Journal of Korean Tunnelling and Underground Space Association
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v.19
no.6
/
pp.915-936
/
2017
In this study, current status of Korean hazard mitigation guideline for tunnel operation is summarized. It shows that requirement for CCTV installation has been gradually stricted and needs for tunnel incident detection system in conjunction with the CCTV in tunnels have been highly increased. Despite of this, it is noticed that mathematical algorithm based incident detection system, which are commonly applied in current tunnel operation, show very low detectable rates by less than 50%. The putative major reasons seem to be (1) very weak intensity of illumination (2) dust in tunnel (3) low installation height of CCTV to about 3.5 m, etc. Therefore, an attempt in this study is made to develop an deep-learning based tunnel incident detection system, which is relatively insensitive to very poor visibility conditions. Its theoretical background is given and validating investigation are undertaken focused on the moving vehicles and person out of vehicle in tunnel, which are the official major objects to be detected. Two scenarios are set up: (1) training and prediction in the same tunnel (2) training in a tunnel and prediction in the other tunnel. From the both cases, targeted object detection in prediction mode are achieved to detectable rate to higher than 80% in case of similar time period between training and prediction but it shows a bit low detectable rate to 40% when the prediction times are far from the training time without further training taking place. However, it is believed that the AI based system would be enhanced in its predictability automatically as further training are followed with accumulated CCTV BigData without any revision or calibration of the incident detection system.
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