• 제목/요약/키워드: Auto-Management

검색결과 473건 처리시간 0.026초

주유소의 가격결정전략 (The Pricing Behavior of Korean Gas Stations)

  • 조영진;이지훈;윤충한
    • 대한안전경영과학회지
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    • 제17권3호
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    • pp.331-341
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    • 2015
  • Gasoline prices vary across Korea. Some gas stations charge higher prices, while others charge lower prices. In this paper, we try to find: why gasoline prices differ markedly across regions. We empirically estimate the determinants of gas prices by incorporating supply side factors as well as demand side factors into the empirical model. Empirical results show that both location-specific factors and store-specific factors affect gas prices. Concentration of competing stores, store brands, ownership of gas stations, and self-service availability influence gas prices. In addition, the availability of other customer services such as convenience stores, car wash, and auto repairs affects gas prices.

판재 최적절단 시스템에 관한 연구 (Investigation of Optimization Nesting Systems on a Board)

  • 이장규;이선곤;조대희;김봉각
    • 대한안전경영과학회:학술대회논문집
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    • 대한안전경영과학회 2008년도 추계학술대회
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    • pp.649-658
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    • 2008
  • This paper investigates the optimal nesting system for a board. A hybrid method is used to search the optimal solution for rectangular nesting problem. This method is composed of heuristic approach algorithm. An engineer's experience of board nesting in which a loss occurred to sheet because of various individual error and diffidence. So, item layout at resource sheet were evaluated in engineering algorithm logic in which specially designed was installed. The nesting system consists of Lisp and Visual Basic. The system was controlled by AutoCAD so as to best item batch path test.

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GARCH 모형을 활용한 비트코인에 대한 체계적 위험분석 (Systematic Risk Analysis on Bitcoin Using GARCH Model)

  • 이중만
    • Journal of Information Technology Applications and Management
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    • 제25권4호
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    • pp.157-169
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    • 2018
  • The purpose of this study was to examine the volatility of bitcoin, diagnose if bitcoin are a systematic risk asset, and evaluate their effectiveness by estimating market beta representing systematic risk using GARCH (Generalized Auto Regressive Conditional Heteroskedastieity) model. First, the empirical results showed that the market beta of Bitcoin using the OLS model was estimated at 0.7745. Second, using GARCH (1, 2) model, the market beta of Bitcoin was estimated to be significant, and the effects of ARCH and GARCH were found to be significant over time, resulting in conditional volatility. Third, the estimated market beta of the GARCH (1, 2), AR (1)-GARCH (1), and MA (1)-GARCH (1, 2) models were also less than 1 at 0.8819, 0.8835, and 0.8775 respectively, showing that there is no systematic risk. Finally, in terms of efficiency, GARCH model was more efficient because the standard error of a market beta was less than that of the OLS model. Among the GARCH models, the MA (1)-GARCH (1, 2) model considering non-simultaneous transactions was estimated to be the most appropriate model.

PREDICTION OF FAULT TREND IN A LNG PLANT USING WAVELET TRANSFORM AND ARIMA MODEL

  • Yeonjong Ju;Changyoon Kim;Hyoungkwan Kim
    • 국제학술발표논문집
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    • The 3th International Conference on Construction Engineering and Project Management
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    • pp.388-392
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    • 2009
  • Operation of LNG (Liquefied Natural Gas) plants requires an effective maintenance strategy. To this end, the long-term and short-term trend of faults, such as mechanical and electrical troubles, should be identified so as to take proactive approach for ensuring the smooth and productive operation. However, it is not an easy task to predict the fault trend in LNG plants. Many variables and unexpected conditions make it quite difficult for the facility manager to be well prepared for future faulty conditions. This paper presents a model to predict the fault trend in a LNG plant. ARIMA (Auto-Regressive Integrated Moving Average) model is combined with Wavelet Transform to enhance the prediction capability of the proposed model. Test results show the potential of the proposed model for the preventive maintenance strategy.

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딥러닝 기반 80대·90대 노령자 대상 폐암 진단 후 사망률 예측에 관한 연구 (A Study on the Prediction of Mortality Rate after Lung Cancer Diagnosis for the Elderly in their 80s and 90s Based on Deep Learning)

  • 변경근;이덕규;신용태
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2022년도 춘계학술발표대회
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    • pp.452-455
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    • 2022
  • 4차 산업혁명의 확산으로 의학계에서도 딥러닝 기술을 이용한 질병의 치료결과 예측 연구가 활발하다. 이와 관련, 일부 연구에서 국소적인 환자 데이터의 활용으로 인해 도출된 연구 결과의 일반화가 어려웠으며 예측률 제고를 위해 특정 딥러닝 알고리즘을 중심으로 한 실험이 추진되어 다양한 알고리즘별 예측률의 비교·분석 결과를 제시하는 연구도 미흡하였다. 이에, 건강보험심사평가원의 대규모 진료 정보와 다종의 알고리즘을 제공하는 AutoML을 이용, 사망률이 높은 80대·90대 노령자 대상 폐암 진단 후 84개월간의 사망률을 예측하는 Decision Tree 등 5개 알고리즘별 모델을 생성하고 이를 활용, 사망률의 예측 성능을 비교하고 사망률에 영향을 미치는 요인에 대한 분석 결과를 도출하였다.

Determining the Impact of Information Technology (IT) on Achieving competitive advantages in Third party logistics Companies (3PL): ISACO and SAIPALogistics

  • Javanmard, Habibollah;Ahmadi, Kourosh
    • 융합경영연구
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    • 제3권1호
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    • pp.1-22
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    • 2015
  • High growth and increasing traffic and transport finished vehicles, a significant impact on how organize the flow of parts to auto makers an dagencies have As a result, the automakers to improve its position as a highly responsive, with minimal costs, the out sourcing of their logistics processes. This paperis the result of field research to determine the effectiveness of the logistics industry in Iran and focuses on information technology deals the transport vehicle and parts sales deals, indicators used in the model include: IT focuses, IT Valence, IT Competency, IT Managerial Commitment, IT Resource Commitment and competitive advantage identified. Data collected by questionnaires from managers and experts have been towing companies ISACO and SAIPA trailer hypotheses using structural equation methods and software has been analyzed Amos, Results show, focusing on information technology now has significant impacts on logistics and transport. As a result the impact of, IT valence, IT competency and IT Managerial Commitment analytics to gain competitive advantage was not approved, but the rest of the factors were confirmed.

도시고속도로 돌발상황 감지 알고리즘 개발에 관한 연구 및 평가 (Study and Evaluation of an Incident Detection Algorithm for Urban Freeways)

  • 서정호;임성만;김영찬
    • 한국ITS학회 논문지
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    • 제3권1호
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    • pp.53-65
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    • 2004
  • 도로에서 발생하는 비반복적이며 예측불가능한 일련의 사건을 돌발상황(incident)이라고 하며 이러한 돌발상황이 발생하게 되면 교통류의 정상 흐름이 와해되고 이로써 도로의 용량감소를 일으키며 교통혼잡과 대기오염 등 막대한 사회$\cdot$경제적 손실을 초래한다. 돌발상황으로 인한 피해를 최소화하고자 국내외 각종 교통관리센터에서는 자동 돌발감지 알고리즘에 의한 자동감지 방법을 사용하고 있다. 그러나 현재 운영중인 돌발상황 감지 알고리즘들은 어느 정도의 감지율은 확보하고 있으나 오경보율이 높아 대체적인 성능은 낮은 것으로 판단된다. 유출입램프 수요과다로 인해 도로용량이 다른 구간에 비해 현저히 떨어지는 병목(bottleneck)구간의 경우, 돌발상황이 빈번하게 발생함에도 불구하고 진출입차량으로 인한 대기행렬과 차로변경등의 유사 돌발상황이 발생하여 자동 돌발상황 감지가 더욱 어려운 실정이다. 본 연구에서는 진출입영향권내에서 발생하는 돌발상황을 정확히 감지하기 위해 돌발상황시 혼잡상황 구분을 통한 자동감지 알고리즘을 바탕으로 램프구간의 혼잡 감지시 인접한 본선의 차로를 돌발상황 판단모듈에서 제외함으로써 모형의 성능을 향상시킬 수 있음을 살펴보았다.

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BIM 기반 LID 시설 물량 자동 검토 모듈 개발 (Development of BIM based LID Facilities Supply Auto-checking Module)

  • 최준우;정종석;임석화;최정주;김신;현경학
    • 환경영향평가
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    • 제26권3호
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    • pp.195-206
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    • 2017
  • 최근 도시물순환 회복을 위한 저영향개발(LID) 기법 적용에 대한 관심이 증가함에 따라, LID 계획 설계 및 시공, 유지관리 등에 활용할 수 있는 건축정보모델(BIM)에 대한 관심이 증가하고 있다. 이에 따라 본 논문에서는 LID 기법의 계획 및 설계공정 단계에서 BIM의 적용가능성과 활용방안을 검토하고자 2D기반의 설계도서를 통해 산출된 LID 시설물의 물량과 BIM 모델링에서 산출된 LID 시설물의 물량을 자동으로 비교하는 모듈을 개발하여 2D기반 산출물량과 비교검토하였다. BIM 기반 LID 시설물량 자동검토 모듈을 개발하기 위해서 연구대상지를 선정하고, BIM 모델링을 통해 물량산출표를 추출하였다. 추출된 물량산출표를 2D 기반의 물량산출표와 비교하기 위한 알고리듬을 작성하고, 작성된 알고리듬을 프로그램화해 산출된 물량의 비교 검토를 실시하였다. 대상지에 적용된 LID 시설물의 모델링을 완료하고, LID 시설물량 자동검토 모듈을 이용해 2D 기반 설계도서의 물량산출표와 BIM기반 물량산출표의 비교 검토를 실시하여, 좀 더 정확한 물량산출을 진행하였다. 또한 산출된 결과 중 재료의 물량 오차율이 ${\pm}30%$를 벗어나는 시설물들의 오차발생 원인을 분석하여 LID 시설물량 자동검토 모듈의 정확도를 검토하였다. LID 시설물량 자동검토 모듈을 통해, 설계도서를 기반으로 한 물량 산출과정에서 발생할 수 있는 오류들을 조기에 발견하고 수정할 수 있을 것으로 보이며, BIM 기반 LID 시설물 종합 관리 시스템 구축의 기반을 마련할 수 있을 것으로 판단된다.

오차항과 러닝 기법을 활용한 예측진단 시스템 개선 방안 연구 (A Study on the Prediction Diagnosis System Improvement by Error Terms and Learning Methodologies Application)

  • 김명준;박영호;김태규;정재석
    • 품질경영학회지
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    • 제47권4호
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    • pp.783-793
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    • 2019
  • Purpose: The purpose of this study is to apply the machine and deep learning methodology on error terms which are continuously auto-generated on the sensors with specific time period and prove the improvement effects of power generator prediction diagnosis system by comparing detection ability. Methods: The SVM(Support Vector Machine) and MLP(Multi Layer Perception) learning procedures were applied for predicting the target values and sequentially producing the error terms for confirming the detection improvement effects of suggested application. For checking the effectiveness of suggested procedures, several detection methodologies such as Cusum and EWMA were used for the comparison. Results: The statistical analysis result shows that without noticing the sequential trivial changes on current diagnosis system, suggested approach based on the error term diagnosis is sensing the changes in the very early stages. Conclusion: Using pattern of error terms as a diagnosis tool for the safety control process with SVM and MLP learning procedure, unusual symptoms could be detected earlier than current prediction system. By combining the suggested error term management methodology with current process seems to be meaningful for sustainable safety condition by early detecting the symptoms.

M2M Device최적화 설계와 4M 생산자원 정보통합 (Optimizing the Design of M2M Device and Methodology for Integrating 4M Manufacturing Resources)

  • 윤재영;김한규;이성근;허영숙;차석근
    • 한국정밀공학회지
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    • 제29권4호
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    • pp.380-385
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    • 2012
  • This paper contains the optimized M2M technology, and the information of production resource of 4M, which understanding the roles and functions of M2M Device, and the explanation of its effectiveness, and the information of optimized M2M Device in IT convergence point of view. In addition, this content also points out the optimized M2M Device, analyzes and collects various type of management information which emphasizes the need for a common platform's were Middleware, and Auto-Configuration, WebLine Monitoring, WebService through the functionality of an integrated management information supports the productions by digitizing the information with standardized data for management efficiency.