• 산업기술연구
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• 제24권A호
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• pp.185-194
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• 2004

To evaluate seismic performance of reinforced concrete piers two procedures for capacity spectrum method are presented. The capacity spectrum procedures include the reduction factor-ductility-period($R_{\mu}-{\mu}-T$)relationship in order to construct the inelastic demand spectra from the elastic demand spectra. Application of the procedures are illustrated by example analysis. Maximum displacements estimated by the procedures are compared to those by inelastic time history analysis for several artificial earthquakes. The results show that the maximum displacements estimated by the procedures are, on overall, smaller than those by the inelastic time history analysis.

• Earthquakes and Structures
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• 제15권2호
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• pp.203-214
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• 2018

Deflection control in tall buildings is a challenging issue. Connecting of the towers is an interesting idea for architects as well as structural engineers. In this paper, two reinforced concrete core-wall towers are connected by a truss bridge with buckling restrained braces. The buildings are 40 and 60-story. The effect of the location of the bridge is investigated. Response spectrum analysis of the linear models is used to obtain the design demands and the systems are designed according to the reliable codes. Then, nonlinear time history analysis at maximum considered earthquake is performed to assess the seismic responses of the systems subjected to far-field and near-field record sets. Fiber elements are used for the reinforced concrete walls. On average, the inter-story drift ratio demand will be minimized when the bridge is approximately located at a height equal to 0.825 times the total height of the building. Besides, because of whipping effects, maximum roof acceleration demand is approximately two times the peak ground acceleration. Plasticity extends near the base and also in major areas of the walls subjected to the seismic loads.

• 대한전기학회논문지
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• 제45권4호
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• pp.511-516
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• 1996

In this paper, weekly maximum power demand forecasting method in consideration of temperature estimation using a time series model was presented. The method removing weekly, seasonal variations on the load and irregularities variation due to unknown factor was presented. The forecasting model that represent the relations between load and temperature which get a numeral expected temperature based on the past 30 years(1961~1990) temperature was constructed. Effect of holiday was removed by using a weekday change ratio, and irregularities variation was removed by using an autoregressive model. The results of load forecasting show the ability of the method in forecasting with good accuracy without suffering from the effect of seasons and holidays. Percentage error load forecasting of all seasons except summer was obtained below 2 percentage. (author). refs., figs., tabs.

• 한국조명전기설비학회지:조명전기설비
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• 제6권1호
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• pp.29-39
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• 1992

In this paper, the basic idea of optimum electric system design by means of the forecasting of maximum demand is presented, and the load characteristics and practical operating conditions are based on the technical data. After reconstruction of th model plant by use of above method, power supply reliability, future extention, initial cost, and running cost saving effects are analyzed. As a result, it is verified that the systems wherein the power is supply to each load frm main transformer whose capacity is calculated by forecasting are economic rather than the systems wherein the power is supply to each electric feeders from each corresponding transformer.

• Communications for Statistical Applications and Methods
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• 제16권1호
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• pp.127-135
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• 2009

한국의 경제규모가 꾸준히 커감에 따라 가정, 건물, 공장 등에서 필요로 하는 전력량이 지속적으로 증가하고 있다. 전력공급의 안정화를 위해서는 최대전력량보다 전력공급능력이 높아야 한다. 월별 최대전력량을 잘 설명할 수 있는 통계모형을 찾기 위해 Winters 모형, 분해 시계열모형, ARMA 모형, 설명 변수를 통해 추세성분과 계절성분을 교정한 모형을 살펴보았다. 모형의 예측력 비교 기준으로 모형적합으로부터 구한 RMSE와 MAPE가 사용되었다. 여름철 최대전력량을 예측하기 위해 평균기온과 열대야 일수를 설명 변수로 갖는 시계열 모형이 가장 우수하였다. 아울러 외부요인을 갖는 극단분포 모형을 이용한 분석을 시도하였다.

• 한국컴퓨터정보학회논문지
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• 제21권1호
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• pp.59-64
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• 2016

This paper suggests heuristic algorithm with O(mn) polynomial time complexity using Excel for partially survivable networks optimization problem of cellular telecommunication systems with m cells and n hubs. This problem only can be get the solution using linear programming or LINGO software package. The proposed algorithm connects the cell to hubs in ring network with minimum cost as the connection diversity of each cell. If the traffic of ring network (T) is T>2K for ring capacity (K), we adjust the maximum cost hub to MTSO that has a ascending order of (D/DC)/${\Delta}^+$ cell with each cell traffic demand (D) and ${\Delta}^+$=(MTSO cost-maximum cost hub) than we get the $T{\leq}2K$. Finally, we adjust MTSO to the removed maximum cost hub for the cell with 2K-$T{\geq}$(D/DC) and $_{max}{\Delta}^-$. While we using like this simple method, the proposed algorithm can be get the same optimal solution for experimental data as linear programing and LINGO software package.

• Steel and Composite Structures
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• 제38권6호
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• pp.671-690
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• 2021

Seismic responses of RC core wall with two outriggers are investigated in this study. In the models analyzed here, one of the outriggers is fixed at the top of the building and the second is placed at different levels along the height of the system. Each of the systems resulting from the placement of the outrigger at different locations is designed according to the prescriptive codes. The location of the outrigger changes along the height. Linear design of all the structures is accomplished by using prescriptive codes. Buckling restrained braces (BRBs) are used in the outriggers and forward directivity near fault and far fault earthquake record sets are used at maximum considered earthquake (MCE) level. Results from nonlinear time history analysis demonstrate that BRB outriggers can change the seismic responses like force distribution and deformation demand of the RC core-walls over the height and lead to the new plastic hinge arrangement over the core-wall height. Plasticity extension in the RC core wall occurs at the base as well as adjacent to the outrigger levels. Considering the maximum inter-story drift ratio (IDR) demand as an engineering parameter, the best location for the second outrigger is at 0.75H, in which the maximum IDR at the region upper the second outrigger level is approximately equal to the corresponding value in the lower region.

• 산업경영시스템학회지
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• 제43권4호
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• pp.93-106
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• 2020

This research explores how imported automobile companies can develop their strategies to improve the outcome of their recalls. For this, the researchers analyzed patterns of recall demand, classified recall types based on the demand patterns and examined response strategies, considering plans on how to procure parts and induce customers to visit workshops, recall execution capacity and costs. As a result, recalls are classified into four types: U-type, reverse U-type, L- type and reverse L-type. Also, as determinants of the types, the following factors are further categorized into four types and 12 sub-types of recalls: the height of maximum demand, which indicates the volatility of recall demand; the number of peaks, which are the patterns of demand variations; and the tail length of the demand curve, which indicates the speed of recalls. The classification resulted in the following: L-type, or customer-driven recall, is the most common type of recalls, taking up 25 out of the total 36 cases, followed by five U-type, four reverse L-type, and two reverse U-type cases. Prior studies show that the types of recalls are determined by factors influencing recall execution rates: severity, the number of cars to be recalled, recall execution rate, government policies, time since model launch, and recall costs, etc. As a component demand forecast model for automobile recalls, this study estimated the ARIMA model. ARIMA models were shown in three models: ARIMA (1,0,0), ARIMA (0,0,1) and ARIMA (0,0,0). These all three ARIMA models appear to be significant for all recall patterns, indicating that the ARIMA model is very valid as a predictive model for car recall patterns. Based on the classification of recall types, we drew some strategic implications for recall response according to types of recalls. The conclusion section of this research suggests the implications for several aspects: how to improve the recall outcome (execution rate), customer satisfaction, brand image, recall costs, and response to the regulatory authority.

• 전자공학회논문지
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• 제50권2호
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• pp.35-46
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• 2013

모바일 네트워크 사용량이 급증함에 따라 트래픽 수요 문제를 해결하기 위한 많은 연구가 이뤄지고 있다. 특히 네트워크 환경 측정 분야는 정확한 분석을 통해 네트워크상에 발생되는 문제들의 원인을 찾아냄으로써 트래픽 수요 문제를 해결할 수 있는 기반을 제공한다. 특히 최근 스마트폰의 수요가 늘어남에 따라 모바일 플랫폼 특성이 네트워크에 미치는 영향을 고려한 측정시스템이 필요하다. 이에 본 논문에서는 모바일 플랫폼을 위한 네트워크 환경 측정 시스템을 설계하였다. 설계된 시스템은 클라이언트를 통하여 얻은 패킷의 정보를 통하여 패킷 전송간의 지연시간과 throughput을 실시간으로 계산한다. 그리고 측정시 클라이언트인 모바일 단말기에 요구되는 계산량을 줄임으로써 모바일 단말기에 걸리는 부하를 최소화하였다. 설계한 시스템을 통하여 네트워크 자원을 최대로 사용하였을 시 Wi-Fi 망이 3G 망보다 짧은 전송지연시간, 높은 최대 throughput, 낮은 손실률을 가지고, Android가 iOS보다 짧은 전송지연시간과 높은 최대 throughput을 가지며, UDP가 TCP보다 긴 전송지연시간, 높은 최대 throughput을 가진다는 것을 확인하였다.

• 한국ITS학회 논문지
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• 제11권3호
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• pp.81-91
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• 2012

최근 기후변화에 따른 위기감으로 인해 세계 각국은 화석연료의 자동차를 전기자동차로 대체하기 위한 노력을 기울이고 있다. 정부는 2020년까지 소형차의 10% 이상을 전기자동차 보급 목표로 설정하였고 '주택건설 기준 등에 관한 규정'을 개정하여 전기자동차 충전설비를 공동주택의 부대설비에 포함시키는 등 충전 인프라 구축에도 노력하고 있다. 공동주택에서 전기자동차의 충전 인프라 및 주차 공간 등의 확보는 전기자동차 보급에 있어 핵심이 되지만, 이들에 대한 합리적 용량 산정 등에 필요한 전기자동차의 수요예측 연구는 미미한 상태이다. 이를 위해 본 연구는 수도권의 공동주택 거주자(분양과 임대 구분)를 대상으로, 통계자료의 시계열분석과 선호도 결과를 이용하여 전기자동차 수요를 예측하였다. 그 결과 2020년 공동주택 거주자의 전기자동차 비율은 임대아파트의 경우 6～21%, 분양아파트는 21～39% 수준이며, 이들의 사용을 지원할 최대전력량은 1,000가구 1일 기준으로 임대아파트 4,200kwh, 분양아파트 7,800kwh로 예측되었다.