• 제목/요약/키워드: Long-term scenarios

검색결과 233건 처리시간 0.029초

물리치료사 인력의 수급전망과 정책방향 (A Prospect for Supply and Demand of Physical Therapists in Korea Through 2030)

  • 오영호
    • 대한통합의학회지
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    • 제6권4호
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    • pp.149-169
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    • 2018
  • Purpose : This study was to develop a strategy for modeling future workforce projections to serve as a basis for analyzing annual supply of and demand for physical therapists across the South Korea into 2030. Methods : In-and-out movement model was used to project the supply of physical therapists. The demand was projected according to the demand-based method which consists of four-stages such as estimation of the utilization rate of the base year, forecasting of health care utilization of the target years, forecasting of the requirements of clinical physical therapists and non-clinical physical therapists based on the projected physical therapists. Results : Based on the current productivity standards, there will be oversupply of 39,007 to 40,875 physical therapists under the demand scenario of average rate in 2030, undersupply of 44,663 to 49,885 under the demand scenario of logistic model, oversupply of 16,378 to 19,100 under the demand scenario of logarithm, and oversupply of 18,185 to 20,839 under the demand scenario of auto-regressive moving average (ARIMA) model in 2030. Conclusion : The result of this projection suggests that the direction and degree of supply of and demand for physical therapists varied depending on physical therapists productivity and utilization growth scenarios. However, the need for introduction of a professional physical therapist system and the need to provide long-term care rehabilitation services are actively being discussed in entering the aging society. If community rehabilitation programs for rehabilitation of disabled people and the elderly are activated, the demand of physical therapists will increase, especially for elderly people. Therefore, healthcare policy should focus on establishing rehabilitation service infrastructure suitable for an aging society, providing high-quality physical therapy services, and effective utilization of physical therapists.

Future water quality analysis of the Anseongcheon River basin, Korea under climate change

  • Kim, Deokwhan;Kim, Jungwook;Joo, Hongjun;Han, Daegun;Kim, Hung Soo
    • Membrane and Water Treatment
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    • 제10권1호
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    • pp.1-11
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    • 2019
  • The Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) predicted that recent extreme hydrological events would affect water quality and aggravate various forms of water pollution. To analyze changes in water quality due to future climate change, input data (precipitation, average temperature, relative humidity, average wind speed and sunlight) were established using the Representative Concentration Pathways (RCP) 8.5 climate change scenario suggested by the AR5 and calculated the future runoff for each target period (Reference:1989-2015; I: 2016-2040; II: 2041-2070; and III: 2071-2099) using the semi-distributed land use-based runoff processes (SLURP) model. Meteorological factors that affect water quality (precipitation, temperature and runoff) were inputted into the multiple linear regression analysis (MLRA) and artificial neural network (ANN) models to analyze water quality data, dissolved oxygen (DO), biological oxygen demand (BOD), chemical oxygen demand (COD), suspended solids (SS), total nitrogen (T-N) and total phosphorus (T-P). Future water quality prediction of the Anseongcheon River basin shows that DO at Gongdo station in the river will drop by 35% in autumn by the end of the $21^{st}$ century and that BOD, COD and SS will increase by 36%, 20% and 42%, respectively. Analysis revealed that the oxygen demand at Dongyeongyo station will decrease by 17% in summer and BOD, COD and SS will increase by 30%, 12% and 17%, respectively. This study suggests that there is a need to continuously monitor the water quality of the Anseongcheon River basin for long-term management. A more reliable prediction of future water quality will be achieved if various social scenarios and climate data are taken into consideration.

암반 대수층에서 개방형 지열 시스템의 개발 및 적용 (Development of a Groundwater Source Heat Pump in a Fractured Rock Aquifer)

  • 심병완;김성균;최한나;이수형;하규철;김용철
    • 신재생에너지
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    • 제17권3호
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    • pp.32-41
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    • 2021
  • A groundwater source heat pump (GWHP) was developed in this study by adapting a borehole heat exchanger with closed-loop and open-loop systems in a new building. In the pilot test building, the air-conditioning on the second floor was designed to employ a closed-loop system and that on the third floor had an open-loop system. The GWHP design is based on the feasibility of groundwater resources at the installation site. For the hydrogeological survey of the study site, pumping and injection tests were conducted, and the feasibility of GWHP installation was evaluated based on the air-conditioning load demand of the building. The site was found to be satisfactory for the design capacity of the thermal load and water quality. In addition, the effect of groundwater movement on the performance of the closed-loop system was tested under three different operational scenarios of groundwater pumping. The performance of the system was sustainable with groundwater flow but declined without appropriate groundwater flow. From long-term observations of the operation, the aquifer temperature change was less than 2℃ at the observation well and 5℃ at the injection well with respect to the initial groundwater temperature. This pilot study is expected to be of guidance for developing GWHPs at fractured rock aquifers.

A Systems Engineering Approach for Predicting NPP Response under Steam Generator Tube Rupture Conditions using Machine Learning

  • Tran Canh Hai, Nguyen;Aya, Diab
    • 시스템엔지니어링학술지
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    • 제18권2호
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    • pp.94-107
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    • 2022
  • Accidents prevention and mitigation is the highest priority of nuclear power plant (NPP) operation, particularly in the aftermath of the Fukushima Daiichi accident, which has reignited public anxieties and skepticism regarding nuclear energy usage. To deal with accident scenarios more effectively, operators must have ample and precise information about key safety parameters as well as their future trajectories. This work investigates the potential of machine learning in forecasting NPP response in real-time to provide an additional validation method and help reduce human error, especially in accident situations where operators are under a lot of stress. First, a base-case SGTR simulation is carried out by the best-estimate code RELAP5/MOD3.4 to confirm the validity of the model against results reported in the APR1400 Design Control Document (DCD). Then, uncertainty quantification is performed by coupling RELAP5/MOD3.4 and the statistical tool DAKOTA to generate a large enough dataset for the construction and training of neural-based machine learning (ML) models, namely LSTM, GRU, and hybrid CNN-LSTM. Finally, the accuracy and reliability of these models in forecasting system response are tested by their performance on fresh data. To facilitate and oversee the process of developing the ML models, a Systems Engineering (SE) methodology is used to ensure that the work is consistently in line with the originating mission statement and that the findings obtained at each subsequent phase are valid.

Understanding the Current State of Deep Learning Application to Water-related Disaster Management in Developing Countries

  • Yusuff, Kareem Kola;Shiksa, Bastola;Park, Kidoo;Jung, Younghun
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2022년도 학술발표회
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    • pp.145-145
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    • 2022
  • Availability of abundant water resources data in developing countries is a great concern that has hindered the adoption of deep learning techniques (DL) for disaster prevention and mitigation. On the contrary, over the last two decades, a sizeable amount of DL publication in disaster management emanated from developed countries with efficient data management systems. To understand the current state of DL adoption for solving water-related disaster management in developing countries, an extensive bibliometric review coupled with a theory-based analysis of related research documents is conducted from 2003 - 2022 using Web of Science, Scopus, VOSviewer software and PRISMA model. Results show that four major disasters - pluvial / fluvial flooding, land subsidence, drought and snow avalanche are the most prevalent. Also, recurrent flash floods and landslides caused by irregular rainfall pattern, abundant freshwater and mountainous terrains made India the only developing country with an impressive DL adoption rate of 50% publication count, thereby setting the pace for other developing countries. Further analysis indicates that economically-disadvantaged countries will experience a delay in DL implementation based on their Human Development Index (HDI) because DL implementation is capital-intensive. COVID-19 among other factors is identified as a driver of DL. Although, the Long Short Term Model (LSTM) model is the most frequently used, but optimal model performance is not limited to a certain model. Each DL model performs based on defined modelling objectives. Furthermore, effect of input data size shows no clear relationship with model performance while final model deployment in solving disaster problems in real-life scenarios is lacking. Therefore, data augmentation and transfer learning are recommended to solve data management problems. Intensive research, training, innovation, deployment using cheap web-based servers, APIs and nature-based solutions are encouraged to enhance disaster preparedness.

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해양기상부표의 센서 데이터 품질 향상을 위한 프레임워크 개발 (Development of a Framework for Improvement of Sensor Data Quality from Weather Buoys)

  • 이주용;이재영;이지우;신상문;장준혁;한준희
    • 산업경영시스템학회지
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    • 제46권3호
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    • pp.186-197
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    • 2023
  • In this study, we focus on the improvement of data quality transmitted from a weather buoy that guides a route of ships. The buoy has an Internet-of-Thing (IoT) including sensors to collect meteorological data and the buoy's status, and it also has a wireless communication device to send them to the central database in a ground control center and ships nearby. The time interval of data collected by the sensor is irregular, and fault data is often detected. Therefore, this study provides a framework to improve data quality using machine learning models. The normal data pattern is trained by machine learning models, and the trained models detect the fault data from the collected data set of the sensor and adjust them. For determining fault data, interquartile range (IQR) removes the value outside the outlier, and an NGBoost algorithm removes the data above the upper bound and below the lower bound. The removed data is interpolated using NGBoost or long-short term memory (LSTM) algorithm. The performance of the suggested process is evaluated by actual weather buoy data from Korea to improve the quality of 'AIR_TEMPERATURE' data by using other data from the same buoy. The performance of our proposed framework has been validated through computational experiments based on real-world data, confirming its suitability for practical applications in real-world scenarios.

Network Anomaly Traffic Detection Using WGAN-CNN-BiLSTM in Big Data Cloud-Edge Collaborative Computing Environment

  • Yue Wang
    • Journal of Information Processing Systems
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    • 제20권3호
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    • pp.375-390
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    • 2024
  • Edge computing architecture has effectively alleviated the computing pressure on cloud platforms, reduced network bandwidth consumption, and improved the quality of service for user experience; however, it has also introduced new security issues. Existing anomaly detection methods in big data scenarios with cloud-edge computing collaboration face several challenges, such as sample imbalance, difficulty in dealing with complex network traffic attacks, and difficulty in effectively training large-scale data or overly complex deep-learning network models. A lightweight deep-learning model was proposed to address these challenges. First, normalization on the user side was used to preprocess the traffic data. On the edge side, a trained Wasserstein generative adversarial network (WGAN) was used to supplement the data samples, which effectively alleviates the imbalance issue of a few types of samples while occupying a small amount of edge-computing resources. Finally, a trained lightweight deep learning network model is deployed on the edge side, and the preprocessed and expanded local data are used to fine-tune the trained model. This ensures that the data of each edge node are more consistent with the local characteristics, effectively improving the system's detection ability. In the designed lightweight deep learning network model, two sets of convolutional pooling layers of convolutional neural networks (CNN) were used to extract spatial features. The bidirectional long short-term memory network (BiLSTM) was used to collect time sequence features, and the weight of traffic features was adjusted through the attention mechanism, improving the model's ability to identify abnormal traffic features. The proposed model was experimentally demonstrated using the NSL-KDD, UNSW-NB15, and CIC-ISD2018 datasets. The accuracies of the proposed model on the three datasets were as high as 0.974, 0.925, and 0.953, respectively, showing superior accuracy to other comparative models. The proposed lightweight deep learning network model has good application prospects for anomaly traffic detection in cloud-edge collaborative computing architectures.

유한요소기법을 이용한 복합재 풍력 블레이드 구조해석 (Structural Analysis of Composite Wind Blade Using Finite Element Technique)

  • 김운성;박경렬;강성민;최용석;정경은;이수민;이경준
    • Tribology and Lubricants
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    • 제40권4호
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    • pp.133-138
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    • 2024
  • This study evaluates the structural safety of wind turbine blades, analyzes the behavior of composite laminate structures with and without defects, and assesses surface erosion wear. The NREL 5 MW standard is applied to assign accurate composite material properties to each blade section. Modeling and analysis of the wind turbine blades reveal stable behavior under individual load conditions (gravity, motor speed, wind speed), with the web bearing most of the load. Surface erosion wear analysis in which microparticle impacts are simulated on the blade coating shows a maximum stress and maximum displacement of 14 MPa and 0.02 mm, respectively, indicating good initial durability, but suggest potential long-term performance issues due to cumulative effects. The study examines defect effects on composite laminate structures to compare the stress distribution, strain, and stiffness characteristics between normal and cracked states. Although normal conditions exhibit stable behavior, crack defects lead to fiber breakage, high-stress concentration in the vulnerable resin layer, and decreased rigidity. This demonstrates that local defects can compromise the safety of the entire structure. The study utilizes finite element analysis to simulate various load scenarios and defect conditions. Results show that even minor defects can significantly alter stress distributions and potentially lead to catastrophic failure if left unaddressed. These findings provide valuable insights for wind turbine blade safety evaluations, surface protection strategies, and composite structure health management. The methodology and results can inform the design improvements, maintenance strategies, and defect detection techniques of the wind energy industry.

중국군의 해양작전능력과 한국군의 과제 (PRC Maritime Operational Capability and the Task for the ROK Military)

  • 김민석
    • Strategy21
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    • 통권33호
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    • pp.65-112
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    • 2014
  • Recent trends show that the PRC has stepped aside its "army-centered approach" and placed greater emphasis on its Navy and Air Force for a wider range of operations, thereby reducing its ground force and harnessing its economic power and military technology into naval development. A quantitative growth of the PLA Navy itself is no surprise as this is not a recent phenomenon. Now is the time to pay closer attention to the level of PRC naval force's performance and the extent of its warfighting capacity in the maritime domain. It is also worth asking what China can do with its widening naval power foundation. In short, it is time to delve into several possible scenarios I which the PRC poses a real threat. With this in mind, in Section Two the paper seeks to observe the construction progress of PRC's naval power and its future prospects up to the year 2020, and categorize time frame according to its major force improvement trends. By analyzing qualitative improvements made over time, such as the scale of investment and the number of ships compared to increase in displacement (tonnage), this paper attempts to identify salient features in the construction of naval power. Chapter Three sets out performance evaluation on each type of PRC naval ships as well as capabilities of the Navy, Air Force, the Second Artillery (i.e., strategic missile forces) and satellites that could support maritime warfare. Finall, the concluding chapter estimates the PRC's maritime warfighting capability as anticipated in respective conflict scenarios, and considers its impact on the Korean Peninsula and proposes the directions ROK should steer in response. First of all, since the 1980s the PRC navy has undergone transitions as the focus of its military strategic outlook shifted from ground warfare to maritime warfare, and within 30 years of its effort to construct naval power while greatly reducing the size of its ground forces, the PRC has succeeded in building its naval power next to the U.S.'s in the world in terms of number, with acquisition of an aircraft carrier, Chinese-version of the Aegis, submarines and so on. The PRC also enjoys great potentials to qualitatively develop its forces such as indigenous aircraft carriers, next-generation strategic submarines, next-generation destroyers and so forth, which is possible because the PRC has accumulated its independent production capabilities in the process of its 30-year-long efforts. Secondly, one could argue that ROK still has its chances of coping with the PRC in naval power since, despite its continuous efforts, many estimate that the PRC naval force is roughly ten or more years behind that of superpowers such as the U.S., on areas including radar detection capability, EW capability, C4I and data-link systems, doctrines on force employment as well as tactics, and such gap cannot be easily overcome. The most probable scenarios involving the PRC in sea areas surrounding the Korean Peninsula are: first, upon the outbreak of war in the peninsula, the PRC may pursue military intervention through sea, thereby undermining efforts of the ROK-U.S. combined operations; second, ROK-PRC or PRC-Japan conflicts over maritime jurisdiction or ownership over the Senkaku/Diaoyu islands could inflict damage to ROK territorial sovereignty or economic gains. The PRC would likely attempt to resolve the conflict employing blitzkrieg tactics before U.S. forces arrive on the scene, while at the same time delaying and denying access of the incoming U.S. forces. If this proves unattainable, the PRC could take a course of action adopting "long-term attrition warfare," thus weakening its enemy's sustainability. All in all, thiss paper makes three proposals on how the ROK should respond. First, modern warfare as well as the emergent future warfare demonstrates that the center stage of battle is no longer the domestic territory, but rather further away into the sea and space. In this respect, the ROKN should take advantage of the distinct feature of battle space on the peninsula, which is surrounded by the seas, and obtain capabilities to intercept more than 50 percent of the enemy's ballistic missiles, including those of North Korea. In tandem with this capacity, employment of a large scale of UAV/F Carrier for Kill Chain operations should enhance effectiveness. This is because conditions are more favorable to defend from sea, on matters concerning accuracy rates against enemy targets, minimized threat of friendly damage, and cost effectiveness. Second, to maintain readiness for a North Korean crisis where timely deployment of US forces is not possible, the ROKN ought to obtain capabilities to hold the enemy attack at bay while deterring PRC naval intervention. It is also argued that ROKN should strengthen its power so as to protect national interests in the seas surrounding the peninsula without support from the USN, should ROK-PRC or ROK-Japan conflict arise concerning maritime jurisprudence. Third, the ROK should fortify infrastructures for independent construction of naval power and expand its R&D efforts, and for this purpose, the ROK should make the most of the advantages stemming from the ROK-U.S. alliance inducing active support from the United States. The rationale behind this argument is that while it is strategically effective to rely on alliance or jump on the bandwagon, the ultimate goal is always to acquire an independent response capability as much as possible.

국가산림자원조사와 장기생태연구 자료를 활용한 산림경관모형의 모수화 및 적용성 평가 (Parameterization and Application of a Forest Landscape Model by Using National Forest Inventory and Long Term Ecological Research Data)

  • 조원희;임원택;김은숙;임종환;고동욱
    • 한국농림기상학회지
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    • 제22권3호
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    • pp.215-231
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    • 2020
  • 산림경관모형은 산림생태계의 복잡한 구조와 다양한 기능의 동적특성을 연구하는데 적합한 모형으로 평가받는다. 산림경관모형은 경관생태학을 기반으로 제작되었으며, 그 특성상 넓은 시공간적 규모를 다루기 때문에 새로운 지역에 적용하는데 환경특성, 수종특성 등에 대한 모수화와 검증에 어려움이 있다. 이에 이 연구에서는 산림경관모형 LANDIS-II Biomass succession 익스텐션에 대한 국내 적용성을 평가하기 위해 계방산 일대를 대상으로 1) 공간정보 입력자료 제작 및 수종특성 모수화, 2) 모형의 보정, 3) 모형의 적용 및 검증방안을 제시하였다. 모형에 적용한 총 14수종은 국가산림조사(National Forest Inventory; NFI), 장기생태조사자료, 아고산대조사자료 기반의 수종별 중요도를 기반으로 선정하였으며, 공간정보 입력자료는 30m 해상도의 수치표고모형을 기반으로 제작한 생태역 지도와 NFI와 장기생태조사자료 기반의 초기 식생형 지도 등을 제작하였다. 수종별 생장모수(ANPPmax, Maxbiomass)는 한국, 중국, 일본 등 동아시아 지역의 생리실험 문헌자료를 종합하여 선정한 수종별 생리특성 모수(FolN, SLWmax, Halfsat, 생장온도, 내음성 등)를 PnET-II 모형에 적용하여 추정하였다. 모형의 보정과 검증은 모형과 조사자료의 수종별 지상부생물량을 비교하여 산출한 결정계수(R2)와 최소 제곱근 오차(RMSE)를 통해 실시하였으며, 검증결과 0.98의 R2와 8.9의 RMSE의 준수한 결과를 나타냈다. 따라서, 이 연구를 기반으로 한반도의 산림경관 변화를 모사할 수 있을 것으로 판단되며 산림관리, 산불, 풍해, 병충해, 기후변화 등 외적요인에 따른 산림경관 변화에 대한 연구가 수행될 수 있을 것으로 기대된다.