• Title/Summary/Keyword: Grid Systems

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The Perceived Causal Structure Model on Stress Experienced by Nursing Students during Clinical Practice (간호학생의 임상실습스트레스에 관한 인지적 인과구조모형)

  • Park, Mi-Young
    • The Journal of Korean Academic Society of Nursing Education
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    • v.10 no.1
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    • pp.54-63
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    • 2004
  • The purpose of this study is to identify the factors that influence stress experienced by nursing students and to provide a perceived causal structure model among these variables. The ultimate goal of this study is to develop efficient guidance to clinical nursing education in this population. This study intends to apply perceived causal structure: network analysis method which was developed by Kelly(1983), and has been applied in nursing research. This method is selected to show dynamic relationship of stressor using network method. Data was collected from convenient sample of 186 junior college nursing students who had the clinical practice experience during 10 weeks. Data collection and analysis was conducted in 2 steps from December, 9, 2002 to February, 8, 2003. Step 1.: Data was collected using literature review(10 articles) to identify the causes of stress. Nine causes of stress were extracted. Step 2.: As perceived casual structure network study, data was collected using questionnaires which included 9 extracted cause and stress. The questionnaire contained a 10 X 10 grid table with 10 causes and effects printed. In network analysis, 'Yes' was scored as 1, 'No' was scored as 0, and the mean(maximum 1, minimum 0) was calculated. Construction of the network under inductive eliminative analysis which stopped the construction of the network when the consensual agreement level dropped near 50% was proceeded by adding causes in order of the mean rating level. In this study, construction of the final network was stopped by consensual agreement level of 52% of the total subjects. The results are summarized as follows : Step 1: Investigation of the causes of stress ; The extracted causes of stress from quality data was identified 9 categories ; negative nurse, lack of clinical practice opportunity, ambiguous role, negative patient, lack of nursing knowledge and skill, difficult of personal relations, inefficient clinical practice guidance, gap of theory and practice, lack of support. Step 2 : Construction of the perceived causal structure model ; 1) The most central cause of stress is ambiguous role in the systems of causation. 2) The distal cause of stress is inefficient clinical practice guidance 3) The causes that have a number of outgoing link are negative nurse, ambiguous role. 4) The causes that have a number of incoming link are ambiguous role, gap of theory- practice, lack of clinical practice opportunity, lack of nursing knowledge- skill. 5) There is a mutual relationship between stress and difficult of personal relations, stress and ambiguous role, ambiguous role and negative nurse, ambiguous role and lack of clinical practice opportunity, ambiguous role and lack of nursing knowledge-skill, lack of nursing knowledge-skill and gap of theory- practice. In conclusion, the network suggests that the first centre cause is related on ambiguous role and the second on negative nurse, inefficient clinical practice guidance in the systems of causation

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A Study on the Smart Home Safety Management System Based on NIALM (NIALM 기반의 스마트 홈 안전관리시스템에 관한 연구)

  • Jeong, Han-Sang;Sung, Kyung-Sang;Oh, Hae-Seok
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.18 no.8
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    • pp.55-63
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    • 2017
  • Due to spatial problems and system size,conventional measurement methods used to acquire the information needed for existing electrical energy and management have been limited to new buildings or areas where replacement is possible. This electric load management method is problematic when applying it to energy and safety management of vulnerable areas or existing homes or offices. The problem with installing a measurement module in every branch is that the system is too large. Even if the measurement module is installed, the type of load is not recognized, and efficient management is not performed. In particular, it is very difficult to apply it to traditional markets and backward facilities in Korea. In this paper, we apply NIALM technology and arc detection technology to solve these problems and verify the feasibility of NIALM for normal arc generation. Also, based on the verification results, we propose a new smart home safety management system that can effectively manage electrical safety and that can be applied to conventional market and existing home safety management systems. The proposed system conducts a comparative performance test with an existing safety management system. In addition, it achieves 95% or more load recognition for four loads, which is impossible in 40% of the existing systems, and the arc detection function was confirmed.

A Proposal of the Prediction Method of Decentralized Power on Climatic Change (기후 변화에 따른 분산 전력 예측 방법 제안)

  • Kim, Jeong-Young;Kim, Bo-Min;Bang, Hyun-Jin;Jang, Min-Seok
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2010.05a
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    • pp.942-945
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    • 2010
  • The development of decentralized power has appeared as part of an effort to decrease the energy loss and the cost for electric power facilities through installing small renewable energy generation systems including solar and wind power generation. Recently a new era for decentralized power environment in building is coming in order to handle the climatic and environmental change occurred all over the world. Especially solar and wind power generation systems can be easily set up and are also economically feasible, and thus many industrial companies enter into this business. This paper suggests the overall architecture for the decentralized renewable power system and the prediction method of power on climatic change. The ultimate goal is to help manage the overall power efficiently and thus provide the technological basis for achieving zero-energy house.

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Active Front End Rectifier Control of DC Distribution System Using Neural Network (신경회로망을 적용한 직류배전시스템의 AFE 정류기 제어에 관한 연구)

  • Kim, Seongwan;Jeon, Hyeonmin;Kim, Jongsu
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.27 no.7
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    • pp.1124-1128
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    • 2021
  • As regulations of emissions from ships become more stringent, electric propulsion systems have been increasingly used to solve this problem in vessels ranging from large merchant ships to small and medium-sized ships. Methods for improving the efficiency of the electric propulsion system include the improvement of power sources; the use of a system linked to environmentally friendly power sources, such as batteries, fuel cells, and solar power; and the development of hardware and control methodology for rectifiers, power conversion devices, and propulsion motors. The method using a phase-shifting transformer with diodes has been widely used for rectification. Power semiconductor devices with grid connection to an environmentally friendly power source using DC distribution, a variable speed power source, and the application of small and medium-sized electric propulsion systems have been developed. Accordingly, the demand for active front-end (AFE) rectifiers is increasing. In this study, a method using a neural network rather than a conventional proportional-integral controller was proposed to control the AFE rectifier. Tested controller data were used to design a neural network controller trained through MATLAB/Simulink. The neural network controller was applied to a rectification system designed using PSIM software. The results indicated the effectiveness of improving the waveform and power factor DC output stage according to the load variation. The proposed system can be applied as a rectification system for small and medium-sized environmentally friendly ships.

Estimating Travel Frequency of Public Bikes in Seoul Considering Intermediate Stops (경유지를 고려한 서울시 공공자전거 통행발생량 추정 모형 개발)

  • Jonghan Park;Joonho Ko
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.22 no.3
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    • pp.1-19
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    • 2023
  • Bikes have recently emerged as an alternative to carbon neutrality. To understand the demand for public bikes, we endeavored to estimate travel frequency of public bike by considering the intermediate stops. Using the GPS trajectory data of 'Ttareungyi', a public bike service in Seoul, we identified a stay point and estimated travel frequency reflecting population, land use, and physical characteristics. Application of map matching and a stay point detection algorithm revealed that stay point appeared in about 12.1% of the total trips. Compared to a trip without stay point, the trip with stay point has a longer average travel distance and travel time and a higher occurrence rate during off-peak hours. According to visualization analysis, the stay points are mainly found in parks, leisure facilities, and business facilities. To consider the stay point, the unit of analysis was set as a hexagonal grid rather than the existing rental station base. Travel frequency considering the stay point were analyzed using the Zero-Inflated Negative Binomial (ZINB) model. Results of our analysis revealed that the travel frequency were higher in bike infrastructure where the safety of bike users was secured, such as 'Bikepath' and 'Bike and pedestrian path'. Also, public bikes play a role as first & last mile means of access to public transportation. The measure of travel frequency was also observed to increase in life and employment centers. Considering the results of this analysis, securing safety facilities and space for users should be given priority when planning any additional expansion of bike infrastructure. Moreover, there is a necessity to establish a plan to supply bike infrastructure facilities linked to public transportation, especially the subway.

Using Spatial Data and Crop Growth Modeling to Predict Performance of South Korean Rice Varieties Grown in Western Coastal Plains in North Korea (공간정보와 생육모의에 의한 남한 벼 품종의 북한 서부지대 적응성 예측)

  • 김영호;김희동;한상욱;최재연;구자민;정유란;김재영;윤진일
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.4 no.4
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    • pp.224-236
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    • 2002
  • A long-term growth simulation was performed at 496 land units in the western coastal plains (WCP) of North Korea to test the potential adaptability of each land unit for growing South Korean rice cultivars. The land units for rice cultivation (CZU), each of them represented by a geographically referenced 5 by 5 km grid tell, were identified by analyzing satellite remote sensing data. Surfaces of monthly climatic normals for daily maximum and minimum temperature, precipitation number of rain days and solar radiation were generated at a 1 by 1 km interval by spatial statistical methods using observed data at 51 synoptic weather stations in North and South Korea during 1981-2000. Grid cells felling within a same CZU and, at the same time, corresponding to the satellite data- identified rice growing pixels were extracted and aggregated to make a spatially explicit climatic normals relevant to the rice growing area of the CZU. Daily weather dataset for 30 years was randomly generated from the monthly climatic normals of each CZU. Growth and development parameters of CERES-rice model suitable for 11 major South Korean cultivars were derived from long-term field observations. Eight treatments comprised of 2 transplanting dates $\times$ 2 cropping systems $\times$ 2 irrigation methods were assigned to each cultivar. Each treatment was simulated with the randomly generated 30 years' daily weather data (from planting to physiological maturity) for 496 land units in WCP to simulate the growth and yield responses to the interannual climate variation. The same model was run with the input data from the 3 major crop experiment stations in South Korea to obtain a 30 year normal performance of each cultivar, which was used as a "reference" for comparison. Results were analyzed with respect to spatial and temporal variation in yield and maturity, and used to evaluate the suitability of each land unit for growing a specific South Korean cultivar. The results may be utilized as decision aids for agrotechnology transfer to North Korea, for example, germplasm evaluation, resource allocation and crop calendar preparation.

Comparative Study on the Methodology of Motor Vehicle Emission Calculation by Using Real-Time Traffic Volume in the Kangnam-Gu (자동차 대기오염물질 산정 방법론 설정에 관한 비교 연구 (강남구의 실시간 교통량 자료를 이용하여))

  • 박성규;김신도;이영인
    • Journal of Korean Society of Transportation
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    • v.19 no.4
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    • pp.35-47
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    • 2001
  • Traffic represents one of the largest sources of primary air pollutants in urban area. As a consequence. numerous abatement strategies are being pursued to decrease the ambient concentration of pollutants. A characteristic of most of the these strategies is a requirement for accurate data on both the quantity and spatial distribution of emissions to air in the form of an atmospheric emission inventory database. In the case of traffic pollution, such an inventory must be compiled using activity statistics and emission factors for vehicle types. The majority of inventories are compiled using passive data from either surveys or transportation models and by their very nature tend to be out-of-date by the time they are compiled. The study of current trends are towards integrating urban traffic control systems and assessments of the environmental effects of motor vehicles. In this study, a methodology of motor vehicle emission calculation by using real-time traffic data was studied. A methodology for estimating emissions of CO at a test area in Seoul. Traffic data, which are required on a street-by-street basis, is obtained from induction loops of traffic control system. It was calculated speed-related mass of CO emission from traffic tail pipe of data from traffic system, and parameters are considered, volume, composition, average velocity, link length. And, the result was compared with that of a method of emission calculation by VKT(Vehicle Kilometer Travelled) of vehicles of category.

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Optimum Design of Steel-Deck System for Two-Story Roads (2층도로용 강구조 덱 시스템의 최적설계)

  • Cho, Hyo Nam;Min, Dae Hong;Kim, Hyun Woo
    • Journal of Korean Society of Steel Construction
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    • v.10 no.3 s.36
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    • pp.553-564
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    • 1998
  • Recently, more and more steel-deck structural system for two story roads has been adopted as a solution against traffic congestion in urban area, mainly because of fast construction, reduced self-weight, higher stiffness and efficient erection compared to that of concrete decks. The main objective is to study on the unit-elective optimal type and proportioning of a rational steel-deck system for two story roads using an optimum design program specifically developed for steel-deck systems. The objective function for the optimization is formulated as a minimum cost design problem. The behavior and design constraints are formulated based on the ASD(Allowable Stress Design) criteria of the Korean Bridge Design Code. The optimum design program developed in this study consists of two steps - the first step for the optimization of the steel box or plate girder viaducts, and the second step for the optimum design of the steel-decks with closed or open ribs. A grid model is used as a structural analysis model for the optimization of the main girder system, while the analysis of the deck system is based on the Pelican-Esslinger method. The SQP(Sequential Quadratic Programming) is used as the optimization technique for the constrained optimization problem. By using a set of application examples, the rational type related to the optimized steel-deck system designs is investigated by comparing the cost effectiveness of each type. Based on the results of the investigation it may be concluded that the optimal linear box girder and deck system with closed ribs may be utilized as one of the most rational and economical viaducts in the construction of two-story roads.

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Application of Two-Dimensional Boundary Condition to Three-Dimensional Magnetotelluric Modeling (3차원 MT 탐사 모델링에서 2차원 경계조건의 적용)

  • Han, Nu-Ree;Nam, Myung-Jin;Kim, Hee-Joon;Lee, Tae-Jong;Song, Yoon-Ho;Suh, Jung-Hee
    • Geophysics and Geophysical Exploration
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    • v.11 no.4
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    • pp.318-325
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    • 2008
  • Assigning an exact boundary condition is of great importance in three-dimensional (3D) magnetotelluric (MT) modeling, in which no source is considered in a computing domain. This paper presents a 3D MT modeling algorithm utilizing a Dirichlet condition for a 2D host. To compute boundary values for a model with a 2D host, we need to conduct additional 2D MT modeling. The 2D modeling consists of transverse magnetic and electric modes, which are determined from the relationship between the polarization of plane wave and the strike direction of the 2D structure. Since the 3D MT modeling algorithm solves Maxwell's equations for electric fields using the finite difference method with a staggered grid that defines electric fields along cell edges, electric fields are calculated at the same place in the 2D modeling. The algorithm developed in this study can produce reliable MT responses for a 3D model with a 2D host.

Study of the Construction of a Coastal Disaster Prevention System using Deep Learning (딥러닝을 이용한 연안방재 시스템 구축에 관한 연구)

  • Kim, Yeon-Joong;Kim, Tae-Woo;Yoon, Jong-Sung;Kim, Myong-Kyu
    • Journal of Ocean Engineering and Technology
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    • v.33 no.6
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    • pp.590-596
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    • 2019
  • Numerous deaths and substantial property damage have occurred recently due to frequent disasters of the highest intensity according to the abnormal climate, which is caused by various problems, such as global warming, all over the world. Such large-scale disasters have become an international issue and have made people aware of the disasters so they can implement disaster-prevention measures. Extensive information on disaster prevention actively has been announced publicly to support the natural disaster reduction measures throughout the world. In Japan, diverse developmental studies on disaster prevention systems, which support hazard map development and flood control activity, have been conducted vigorously to estimate external forces according to design frequencies as well as expected maximum frequencies from a variety of areas, such as rivers, coasts, and ports based on broad disaster prevention data obtained from several huge disasters. However, the current reduction measures alone are not sufficiently effective due to the change of the paradigms of the current disasters. Therefore, in order to obtain the synergy effect of reduction measures, a study of the establishment of an integrated system is required to improve the various disaster prevention technologies and the current disaster prevention system. In order to develop a similar typhoon search system and establish a disaster prevention infrastructure, in this study, techniques will be developed that can be used to forecast typhoons before they strike by using artificial intelligence (AI) technology and offer primary disaster prevention information according to the direction of the typhoon. The main function of this model is to predict the most similar typhoon among the existing typhoons by utilizing the major typhoon information, such as course, central pressure, and speed, before the typhoon directly impacts South Korea. This model is equipped with a combination of AI and DNN forecasts of typhoons that change from moment to moment in order to efficiently forecast a current typhoon based on similar typhoons in the past. Thus, the result of a similar typhoon search showed that the quality of prediction was higher with the grid size of one degree rather than two degrees in latitude and longitude.