• Title/Summary/Keyword: 시계확보

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Demand Forecasts Analysis of Electric Vehicles for Apartment in 2020 (2020년 아파트의 전기자동차 수요예측 분석 연구)

  • Byun, Wan-Hee;Lee, Ki-Hong;Lee, Sang-Hyuk;Kee, Ho-Young
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.11 no.3
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    • pp.81-91
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    • 2012
  • The world has been replacing fast fossil fuels vehicles with electric vehicles(EVs) to cope with climate change. The government set a goal which EVs will be substitute at least 10% of the domestic small vehicles with EVs until 2020, and will try to build electric charging infrastructures in apartments with the revision the law of 'the housing construction standards'. In apartments the EVs charging infrastructure and parking space is, essential to accomplish the goal. But the studies on EVs demand are few. In this study, we predicted that the demand for EVs using time-series analysis of statistical data, survey results for apartments residents in the metropolitan area. As a result, the ratio of the EVs appeared to be 6~21% for the total vehicles in a rental apartments for the years 2020, 21~39% in apartments for sales. For the EVs, the maximum power required for 1,000 households in rental apartment is predicted to be about 4200 kwh on a daily basis, while the maximum power in the apartment for sales is predicted to be 7800kwh.

The Impact of Nuclear Power Generation on Wholesale Electricity Market Price (원자력발전이 전력가격에 미치는 영향 분석)

  • Jung, Sukwan;Lim, Nara;Won, DooHwan
    • Environmental and Resource Economics Review
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    • v.24 no.4
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    • pp.629-655
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    • 2015
  • Nuclear power generation is a major power source which accounts for more than 30% of domestic electricity generation. Electricity market needs to secure stability of base load. This study aimed at analyzing relationships between nuclear power generation and wholesale electricity price (SMP: System Marginal Price) in Korea. For this we conducted ARDL(Autoregressive Distributed Lag) approach and Granger causality test. We found that in terms of total effects nuclear power supply had a positive relationship with SMP while nuclear capacity had a negative relationship with SMP. There is a unidirectional Granger causality from nuclear power supply to SMP while the reverse was not. Nuclear power is closely related to SMP and provides useful information for decision making.

Design and Validation of Model Inversion Flight Control Law for Fly By Wire Helicopter (FBW 헬리콥터 모델 역변환 비행제어법칙 설계 및 검증)

  • Kim, Chong-Sup;Cho, In-Je;Lee, Seung-Duck;Lee, Han-Ju
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.40 no.8
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    • pp.678-687
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    • 2012
  • The Fly-By-Wire(FBW) flight control system is essential to improve the stability and flying quality of the helicopter. Advanced aerospace companies, such as Bell-Sikorsky (USA) and NHI (European Consortium), have already applied the FBW flight control system to manufacture V-22 and NH-90 helicopters, respectively. This paper addresses the development of control law design using model inversion method improve the hover and low speed handling qualities of helicopter based on BO-105 model in 'Day' and 'Degraded visual environments(DVEs)' in accordance with ADS-33E-PRF. Design parameters are optimized to satisfy the handling qualities specification using Control Designer's Unified Interface (CONDUIT) commercial control law software. The result of the analysis based on CONDUIT and non-real time simulation in-house software, HETLAS (HElicopter Trim Linearization And Simulation) reveals that the provides an efficient mean to achieve Level 1 handling qualities.

Trend analysis of the number of nurses and evaluation of nursing staffs expansion policy in Korean hospitals (시계열 자료를 이용한 병원 간호 인력의 변화 추이 및 병원 간호사 확보를 위한 정책의 효과 평가)

  • Park, Bo Hyun;Lee, Tae Jin;Park, Hyeung-Keun;Kim, Chul-Woung;Jeong, Baek-Geun;Lee, Sang-Yi
    • Health Policy and Management
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    • v.22 no.3
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    • pp.297-314
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    • 2012
  • Purpose : The purpose of this study was to analyze the trend of the number of nursing staffs and skill mix and to assess the effectiveness of hospital nurse expansion policies in Korea. Methods : The trend of the number of nursing staffs and skill mix were analyzed using time series data, which composed of yearly series data from 1975 to 2009. The impact of hospital nurse expansion policies was estimated by autoregressive integrated moving average(ARIMA) intervention model. Results : The number of general hospital and hospital nurses per 100 beds was decreased in late 1980s and late 1990s due to rapid growth of beds. As a result of the number of nurse aids per 100 beds decreased, skill mix became high in general hospital but nurse ratio among hospital nursing staffs was about 50%. Expansion of new nurse and revised differentiated inpatient fee were only effective in expansion of hospital nursing staffs. But they had no effect in general hospitals. Conclusion : In Korea, a few policies related to expansion of hospital nurses have an effect on increasing the number of hospital nurse. Nevertheless, level of hospital nursing staffs is inferior to that of general hospital.

Fault Detection Performance Analysis of GNSS Integrity RAIM (GNSS 무결성을 위한 RAIM 기법의 고장검출 성능 분석)

  • Kim, Ji Hye;Park, Kwan Dong;Kim, Du Sik
    • Journal of Korean Society for Geospatial Information Science
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    • v.20 no.3
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    • pp.49-56
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    • 2012
  • Performance analysis on RAIM, which is one of the techniques for monitoring integrity to ensure the reliability of GPS, was conducted in this study. RAIM is such a method which allows its user to monitor integrity in the stand-alone mode. Among the existing RAIM procedures, the representative methods including the RCM (Range Comparison Method), LSRM (Least Square Residual Method), Parity approach and WRAIM (Weighted RAIM) were evaluated, and their performance was analyzed. To validate the performance of the implemented algorithms, fault detection was tried on the clock malfunctioning event of PRN 23 occurred on January 1st, 2004. As a result, it was identified that the LSRM and the WRAIM detected all the faults happened in the event. In the case of RCM, all the states of fault were detected except for the error which occurred as a false alarm at one epoch. Furthermore, simulated biases were added for each satellite to analyze the sensitivity of each algorithm. Consequently, when biases of the 9-13 meters range were simulated for the RCM and LSRM algorithm, all the malfunctions were detected. For the WRAIM method, it could detect range biases greater than 15 meters.

Application of Levenberg Marquardt Method for Calibration of Unsteady Friction Model for a Pipeline System (관수로 부정류 마찰항 보정을 위한 Levenberg Marquardt 방법의 적용연구)

  • Park, Jo Eun;Kim, Sang Hyun
    • Journal of Korea Water Resources Association
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    • v.46 no.4
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    • pp.389-400
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    • 2013
  • In this study, a conventional pipeline unsteady friction model has been integrated into Levenberg Marquardt method to calibrate friction coefficient in a pipeline system. The method of characteristics has been employed as the modeling platform for the frequency dependant model of unsteady friction. In order to obtain Hessian and Jacobian matrix for optimization, the direct differentiation of pressure to friction factor was calculated and sensitivities to friction for heads and discharges were formulated for implementation to the integration constant in the characteristic method. Using a hypothetical simple pipeline system, time series of pressure, introduced by a sudden valve closure, were obtained for various Reynolds numbers. Convergency in fiction factors were evaluated both in steady and unsteady friction models. The comparison of calibration performance between the proposed method and genetic algorithm indicates that faster and stabler behaviour of Levenberg Marquardt method than those of evolutionary calibration.

A Study on Estimating Regional Water Demand and Water Management Policy (물 수요함수 추정과 지역 물 관리 정책 연구)

  • Lim, Dongsoon
    • Journal of Digital Convergence
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    • v.16 no.7
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    • pp.1-8
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    • 2018
  • In Korea, water supply capacity and facility investments had been emphasized around the 1980s. The water pricing have gained focuses in water policy since the 1990s. This study analyzes a water demand and estimates the relation of water demand and other socio-economic variable, using econometric models on the city of Busan. Water price and income are two key elements to explain water demand. Modeling approach using translog function provides better results, and water demand responds positively to population and income. Energy and water prices are negative factors in deciding water demand. It is requested that water pricing needs to reflect more production costs. Alternative approaches such as water saving facilities by household and use of digital water information should be emphasized for efficient water management in a local community.

Investigation of Research Trends in the D(Data)·N(Network)·A(A.I) Field Using the Dynamic Topic Model (다이나믹 토픽 모델을 활용한 D(Data)·N(Network)·A(A.I) 중심의 연구동향 분석)

  • Wo, Chang Woo;Lee, Jong Yun
    • Journal of the Korea Convergence Society
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    • v.11 no.9
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    • pp.21-29
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    • 2020
  • The Topic Modeling research, the methodology for deduction keyword within literature, has become active with the explosion of data from digital society transition. The research objective is to investigate research trends in D.N.A.(Data, Network, Artificial Intelligence) field using DTM(Dynamic Topic Model). DTM model was applied to the 1,519 of research projects with SW·A.I technology classifications among ICT(Information and Communication Technology) field projects between 6 years(2015~2020). As a result, technology keyword for D.N.A. field; Big data, Cloud, Artificial Intelligence, extended keyword; Unstructured, Edge Computing, Learning, Recognition was appeared every year, and accordingly that the above technology is being researched inclusively from other projects can be inferred. Finally, it is expected that the result from this paper become useful for future policy·R&D planning and corporation's technology·marketing strategy.

A Bayesian Approach to Storm Water Management Model (SWMM) for the Estimation of Parameters and Their Uncertainty (Bayesian 기법과 연계한 SWMM 매개변수 추정 및 불확실성 분석)

  • Kim, Jang-Gyeong;Ban, U-Sik;Kwon, Hyun-Han
    • Proceedings of the Korea Water Resources Association Conference
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    • 2016.05a
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    • pp.110-110
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    • 2016
  • 도시 유역의 강우-유출 모의에는 지표 투수율 및 하수관거 영향 등 인위적 배수계통의 영향을 고려할 수 있는 도시유출모형이 널리 이용되고 있으며, 모형 검증을 통해 모의 성능을 평가한다. 도시유출모형의 검증은 일반적인 강우-유출 모형과 같이 강우사상별 유량의 관측시계열과 모의시계열의 목적함수가 최소가 되는 최적 매개변수를 탐색하는 과정이다. 도시유출모형의 검증에서 발생하는 문제점은 크게 다음과 같다. 첫째, 대규모 도시 유역의 복잡하고 다양한 하수관거에 대한 최적매개변수를 관거별로 구하는 것은 물리적으로 불가능하다. 따라서 동일 배수분구내 하수관거의 매개변수 값은 동일하다고 가정하거나, 모형 단순화 과정을 통해 매개변수의 물리적 범위 내에서 최적해를 탐색해야 하는 단순화에서 기인한 불확실성이 있다. 둘째, 다양한 매개변수들의 물리적 범위를 고려하기 위해서는 전역최적화기법이 유효하다. 그러나 전역최적화 종류, 목적함수, 모의횟수, 목표성능별 최적 매개변수 결과가 각각 다르므로 추정된 최적 매개변수의 범위에 대한 불확실성이 있다. 이에 본 연구에서는 Bayesian 모형과 EPA SWMM(Storm Water Management Model)을 연계하여 도시유출모형의 매개변수 불확실성을 정량적으로 분석할 수 있는 모형을 제안하고자 한다. 이를 위해 서울 우이천 유역을 대상으로 SWMM 모형을 구축하고, 절단 정규분포(truncated Gaussian distribution)를 사전분포(prior)로 가정하여 매개변수의 물리적 범위를 고려하였다. 최종적으로 결합확률분포로 계산된 각 매개변수간 사후분포를 통해 모의된 유출량의 불확실성을 정량적으로 분석하였다. 본 연구에서 제안된 모형은 대규모 도시 유역의 도시유출모형 구축 시 다양한 매개변수의 물리적 범위를 고려한 최적화와 동시에 내재된 불확실성을 정량적으로 분석할 수 있으므로, 침수예측 및 홍수예경보 등의 문제에서 상당한 신뢰성을 확보할 수 있을 것으로 판단된다.

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Predicting the Future Price of Export Items in Trade Using a Deep Regression Model (딥러닝 기반 무역 수출 가격 예측 모델)

  • Kim, Ji Hun;Lee, Jee Hang
    • KIPS Transactions on Software and Data Engineering
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    • v.11 no.10
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    • pp.427-436
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    • 2022
  • Korea Trade-Investment Promotion Agency (KOTRA) annually publishes the trade data in South Korea under the guidance of the Ministry of Trade, Industry and Energy in South Korea. The trade data usually contains Gross domestic product (GDP), a custom tariff, business score, and the price of export items in previous and this year, with regards to the trading items and the countries. However, it is challenging to figure out the meaningful insight so as to predict the future price on trading items every year due to the significantly large amount of data accumulated over the several years under the limited human/computing resources. Within this context, this paper proposes a multi layer perception that can predict the future price of potential trading items in the next year by training large amounts of past year's data with a low computational and human cost.