• 제목/요약/키워드: Adoption Prediction

검색결과 49건 처리시간 0.028초

Prediction of Pervaporation Performance Using Solubility Parameter Calculation

  • John R. Dorgan;Nam, Sang-Yong
    • Korean Membrane Journal
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    • 제5권1호
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    • pp.36-42
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    • 2003
  • A Prediction of pervaporation performance was studied by solubility parameter calculation approach for the benzene/cyclohexane mixture system using rubbery blend membrane with various solubility parameters. The solubility parameter of the rubbery blend membranes were controlled with different blend ratio of the poly(acrylonitrile-co-butadiene), poly(styrene-co-butadiene) and poly(vinyl chloride). Screening of blend formulations was accomplished by simple swelling tests. When the content of NBR is increased, the swelling of both benzene and cyclohexane are decreased. However, the ratio of benzene swelling to swelling by cyclohexane (the swelling selectivity) increases. The same is true for blends in which the PVC content is increased. Adoption of a solubility parameter calculation provides an a priori methodology for seeking the best blend formulation.

건설현장의 공사사전정보를 활용한 사망재해 예측 모델 개발 (Development of Prediction Models for Fatal Accidents using Proactive Information in Construction Sites)

  • 최승주;김진현;정기효
    • 한국안전학회지
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    • 제36권3호
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    • pp.31-39
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    • 2021
  • In Korea, more than half of work-related fatalities have occurred on construction sites. To reduce such occupational accidents, safety inspection by government agencies is essential in construction sites that present a high risk of serious accidents. To address this issue, this study developed risk prediction models of serious accidents in construction sites using five machine learning methods: support vector machine, random forest, XGBoost, LightGBM, and AutoML. To this end, 15 proactive information (e.g., number of stories and period of construction) that are usually available prior to construction were considered and two over-sampling techniques (SMOTE and ADASYN) were used to address the problem of class-imbalanced data. The results showed that all machine learning methods achieved 0.876~0.941 in the F1-score with the adoption of over-sampling techniques. LightGBM with ADASYN yielded the best prediction performance in both the F1-score (0.941) and the area under the ROC curve (0.941). The prediction models revealed four major features: number of stories, period of construction, excavation depth, and height. The prediction models developed in this study can be useful both for government agencies in prioritizing construction sites for safety inspection and for construction companies in establishing pre-construction preventive measures.

Enhancement of the Virtual Metrology Performance for Plasma-assisted Processes by Using Plasma Information (PI) Parameters

  • Park, Seolhye;Lee, Juyoung;Jeong, Sangmin;Jang, Yunchang;Ryu, Sangwon;Roh, Hyun-Joon;Kim, Gon-Ho
    • 한국진공학회:학술대회논문집
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    • 한국진공학회 2015년도 제49회 하계 정기학술대회 초록집
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    • pp.132-132
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    • 2015
  • Virtual metrology (VM) model based on plasma information (PI) parameter for C4F8 plasma-assisted oxide etching processes is developed to predict and monitor the process results such as an etching rate with improved performance. To apply fault detection and classification (FDC) or advanced process control (APC) models on to the real mass production lines efficiently, high performance VM model is certainly required and principal component regression (PCR) is preferred technique for VM modeling despite this method requires many number of data set to obtain statistically guaranteed accuracy. In this study, as an effective method to include the 'good information' representing parameter into the VM model, PI parameters are introduced and applied for the etch rate prediction. By the adoption of PI parameters of b-, q-factors and surface passivation parameters as PCs into the PCR based VM model, information about the reactions in the plasma volume, surface, and sheath regions can be efficiently included into the VM model; thus, the performance of VM is secured even for insufficient data set provided cases. For mass production data of 350 wafers, developed PI based VM (PI-VM) model was satisfied required prediction accuracy of industry in C4F8 plasma-assisted oxide etching process.

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CFD를 이용한 승용차 에어컨 덕트의 최적설계 (Optimum Design of an Automotive A/C Duct using by CFD)

  • 김태훈;정수진
    • 한국분무공학회지
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    • 제1권3호
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    • pp.37-50
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    • 1996
  • Computational fluid dynamics was used to optimize an A/C duct. Three dimensional flow analysis in an automotive A/C duct was performed computationally using various turbulence models and compared numerical predictions such as outlet flow split, surface pressure distribution along the duct to experimental data. Additionally, we studied the effect of location variation of 2nd branch on exit flow ratio and could find optimal location of 2nd branch. The design of an A/C duct was modeled and calculated to enhance the airflow distribution in each outlet using the STAR-CD computational fluid dynamics software. In results, modified $k-\varepsilon$ turbulence model allows a successful prediction of static pressure distribution particulary at around strong curvature but little improvement flow split. In the future, adoption of CFD to design an A/C duct with modified $k-\varepsilon$ model will bring benefits of producing more accurate prediction, and also give designers more detail information much more than now.

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HVAC 덕트내의 3차원 난류유동에 관한 수치해석적 연구 (Numerical Analysis of Three Dimensional Turbulent Flow in a HVAC Duct)

  • 정수진;류수열;김태훈
    • 한국자동차공학회논문집
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    • 제4권4호
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    • pp.118-129
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    • 1996
  • In this study, three dimensional flow analysis in a HVAC duct was performed computationally using various turbulence models and compared numerical predictions such as outlet flow split, surface pressure distribution along the duct to experimental data. It's well known that accuracy of computational predictions of flow heavily dependent on turbulent models and discritization method. Therefore, in this work, to assess the ability of turbulent models to predict characteristics of duct flow, three kinds of models, namely standard $k-\varepsilon$, RNG $k-\varepsilon$ and modified $k-\varepsilon$, containing parameter for the effect of streamline curvature were employed and validated one another by comparing with experimental data. In results, modified $k-\varepsilon$ turbulence model allows a successful prediction of static pressure distribution particulary at around strong curvature but little improvement flow split. In the futrue, adoption of CFD to design HVAC duct with modified $k-\varepsilon$ model will bring benefits of producing more accurate prediction, and also give designers more detail information much more than now.

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월 PMP 개념의 적용에 관한 연구 (A Study of Adoption on the Concept of Monthly Probable Maximum Precipitation)

  • 최한규;김남원;최용묵;윤희섭
    • 산업기술연구
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    • 제21권B호
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    • pp.241-248
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    • 2001
  • Normally at a flood season the operation of the dam depends on a short range weather forecast that makes many difficulties of the management at a dry season. It is needed to study the pattern of the long period rainfall. The concept of PMP(Probable Maximum Precipitation) was used for designing dam. From the concept, this study is applied the concept of monthly probable maximum precipitation for operating dam. It can be possible to let us know the appropriateness of a limiting water level at a rainy season. For the operation of dam at a dry season this study can predict roughly the flood season's pattern of precipitation by month or period, therfore the prediction of precipitation can rise efficient operation of a dam.

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데이터 마이닝을 이용한 생산공정 데이터 분석 시나리오 (Scenarios for Manufacturing Process Data Analysis using Data Mining)

  • 이형욱;배성민
    • 융복합기술연구소 논문집
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    • 제3권1호
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    • pp.41-44
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    • 2013
  • Process and manufacturing data are numerously accumulated to the enterprise database in industries but little of those data are utilized. Data mining can support a decision to manager in process from the data. However, it is not easy to field managers because a proper adoption of various schemes is very difficult. In this paper, six scenarios are conducted using data mining schemes for the various situations of field claims such as yield problem, trend analysis and prediction of yield according to changes of operating conditions, etc. Scenarios, like templates, of various analysis situations are helpful to users.

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고압환경에서 동축 스월 분사기 분무 특성에 대한 수치적 해석 (Numerical Analysis for Characteristics of Coaxial Swirl Injector in High-Pressure Environment)

  • 문윤완;설우석;김동준;윤영빈
    • 한국추진공학회:학술대회논문집
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    • 한국추진공학회 2007년도 제29회 추계학술대회논문집
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    • pp.131-134
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    • 2007
  • 본 연구에서는 상압환경에 적용되었던 액막 분열 모델을 고압환경에 적용하였다. 실험에서 주위압이 고압으로 진행할수록 액막의 분열길이는 짧아지는데 개발된 액막 분열 모델은 이러한 경향을 잘 예측하는 것으로 나타났으며 분무 형상도 정성적으로 실험결과와 일치하는 것으로 나타났다.

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주철근 겹침이음을 갖는 철근콘크리트 교각의 비탄성 거동 및 연성능력에 관한 해석적 연구 (Analytical Study on Inelastic Behavior and Ductility Capacity of Reinforced Concrete Bridge Columns with Lap Splices)

  • 김태훈;김운학;신현목;정영수
    • 한국콘크리트학회:학술대회논문집
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    • 한국콘크리트학회 2003년도 봄 학술발표회 논문집
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    • pp.931-936
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    • 2003
  • Lap splices were located in the plastic hinge region of most bridge piers that were constructed before the adoption of the seismic design provision of Korea Highway Design Specification on 1992. Lap splicing is also permitted if hoops or spiral reinforcement are provided over the lap length in the current seismic design provision. But sudden brittle failure of lap splices may occur under inelastic cyclic loading. The purpose of this study is the analytical prediction of nonlinear hysteretic behavior and ductility capacity of reinforced concrete bridge piers with lap splices under cyclic loading. For this purpose, a nonlinear analysis program, RCAHEST(Reinforced Concrete Analysis in Higher Evaluation System Technology) is used. Lap spliced bar element is developed to predict behaviors of lap spliced bar. Maximum bar stress and slip of lap spliced bar is considered.

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재무제표 주석의 텍스트 분석 통한 재무 비율 예측 향상 연구 (Financial Footnote Analysis for Financial Ratio Predictions based on Text-Mining Techniques)

  • 최형규;이상용
    • 지식경영연구
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    • 제21권2호
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    • pp.177-196
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    • 2020
  • Since the adoption of K-IFRS(Korean International Financial Reporting Standards), the amount of financial footnotes has been increased. However, due to the stereotypical phrase and the lack of conciseness, deriving the core information from footnotes is not really easy yet. To propose a solution for this problem, this study tried financial footnote analysis for financial ratio predictions based on text-mining techniques. Using the financial statements data from 2013 to 2018, we tried to predict the earning per share (EPS) of the following quarter. We found that measured prediction errors were significantly reduced when text-mined footnotes data were jointly used. We believe this result came from the fact that discretionary financial figures, which were hardly predicted with quantitative financial data, were more correlated with footnotes texts.