• Title/Summary/Keyword: Quadratic Regression Model

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실험계획법을 이용한 전자부품 위치정렬장치 최적 운영조건 사례연구 (A Study on Optimal Operation Conditions for an Electronic Device Alignment System by Using Design of Experiments)

  • 이동헌;이미림;배석주
    • 품질경영학회지
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    • 제43권3호
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    • pp.453-466
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    • 2015
  • Purpose: The purpose of this study is to design a systematic method to estimate optimal operation conditions of design variables for an electronic device alignment system. Method: The 2-level factorial design and the central composite design are used in order to plan experiments. Based on the experiment results, a regression model is established to find optimal conditions for the design variables. Results: 3 of 5 design variables are selected as major factors that affect the alignment system significantly. The optimized condition for each variable is estimated by using a sequential experiment plan and a quadratic regression model. Conclusion: The method designed in this study provides an efficient and systematic plan to select the optimized operation condition for the design variables. The method is expected to improve inspection accuracy of the system and reduce the development cost and period.

Generalized methods of moments in marginal models for longitudinal data with time-dependent covariates

  • Cho, Gyo-Young;Dashnyam, Oyunchimeg
    • Journal of the Korean Data and Information Science Society
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    • 제24권4호
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    • pp.877-883
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    • 2013
  • The quadratic inference functions (QIF) method proposed by Qu et al. (2000) and the generalized method of moments (GMM) for marginal regression analysis of longitudinal data with time-dependent covariates proposed by Lai and Small (2007) both are the methods based on generalized method of moment (GMM) introduced by Hansen (1982) and both use generalized estimating equations (GEE). Lai and Small (2007) divided time-dependent covariates into three types such as: Type I, Type II and Type III. In this paper, we compared these methods in the case of Type II and Type III in which full covariates conditional mean assumption (FCCM) is violated and interested in whether they can improve the results of GEE with independence working correlation. We show that in the marginal regression model with Type II time-dependent covariates, GMM Type II of Lai and Small (2007) provides more ecient result than QIF and for the Type III time-dependent covariates, QIF with independence working correlation and GMM Type III methods provide the same results. Our simulation study showed the same results.

Epidemiological application of the cycle threshold value of RT-PCR for estimating infection period in cases of SARS-CoV-2

  • Soonjong Bae;Jong-Myon Bae
    • Journal of Medicine and Life Science
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    • 제20권3호
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    • pp.107-114
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    • 2023
  • Epidemiological control of coronavirus disease 2019 (COVID-19) is needed to estimate the infection period of confirmed cases and identify potential cases. The present study, targeting confirmed cases for which the time of COVID-19 symptom onset was disclosed, aimed to investigate the relationship between intervals (day) from symptom onset to testing the cycle threshold (CT) values of real-time reverse transcription-polymerase chain reaction. Of the COVID-19 confirmed cases, those for which the date of suspected symptom onset in the epidemiological investigation was specifically disclosed were included in this study. Interval was defined as the number of days from symptom onset (as disclosed by the patient) to specimen collection for testing. A locally weighted regression smoothing (LOWESS) curve was applied, with intervals as explanatory variables and CT values (CTR for RdRp gene and CTE for E gene) as outcome variables. After finding its non-linear relationship, a polynomial regression model was applied to estimate the 95% confidence interval values of CTR and CTE by interval. The application of LOWESS in 331 patients identified a U-shaped curve relationship between the CTR and CTE values according to the number of interval days, and both CTR and CTE satisfied the quadratic model for interval days. Active application of these results to epidemiological investigations would minimize the chance of failing to identify individuals who are in contact with COVID-19 confirmed cases, thereby reducing the potential transmission of the virus to local communities.

건구온파를 오인한 장기최대전력수요예측에 관한 연구 (Long-Term Maximum Power Demand Forecasting in Consideration of Dry Bulb Temperature)

  • 고희석;정재길
    • 대한전기학회논문지
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    • 제34권10호
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    • pp.389-398
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    • 1985
  • Recently maximum power demand of our country has become to be under the great in fluence of electric cooling and air conditioning demand which are sensitive to weather conditions. This paper presents the technique and algorithm to forecast the long-term maximum power demand considering the characteristics of electric power and weather variable. By introducing a weather load model for forecasting long-term maximum power demand with the recent statistic data of power demand, annual maximum power demand is separated into two parts such as the base load component, affected little by weather, and the weather sensitive load component by means of multi-regression analysis method. And we derive the growth trend regression equations of above two components and their individual coefficients, the maximum power demand of each forecasting year can be forecasted with the sum of above two components. In this case we use the coincident dry bulb temperature as the weather variable at the occurence of one-day maximum power demand. As the growth trend regression equation we choose an exponential trend curve for the base load component, and real quadratic curve for the weather sensitive load component. The validity of the forecasting technique and algorithm proposed in this paper is proved by the case study for the present Korean power system.

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소변 중 메트암페타민, 암페타민 및 대마 대사체 LC-MS/MS 정량분석에서 검량선 작성을 위한 R을 활용한 회귀모델 선택 (Regression model for the preparation of calibration curve in the quantitative LC-MS/MS analysis of urinary methamphetamine, amphetamine and 11-nor-Δ9-tetrahydrocannabinol-9-carboxylic acid using R)

  • 김진영;신동원
    • 분석과학
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    • 제34권6호
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    • pp.241-250
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    • 2021
  • 검량선 작성은 기기분석을 통해 생체시료에서 분석물질의 농도를 측정하는 정량분석법 개발과 측정값의 정확도 향상에 있어서 필수적인 요소이다. 본 연구에서는 R 기반 통계분석기법을 이용하여 개별 분석물질 정량에 적합한 가중계수와 회귀모델 선정하기 위한 단계별 선택 기준을 적용하여 분석 프로그램을 설정하였다. 국내에서 남용빈도가 가장 높은 필로폰과 대마 복용여부 확인을 위해 액체크로마토그래피-질량분석법(LC-MS/MS)이 적용되었으며, 분석물질로 마약의 복용 여부를 확인에 일반적으로 사용되는 대상 마약의 모체와 대사체를 소변 시료에서 분석하였다. 검량선 작성에 있어서 가중계수 적용여부는 원본데이터의 이분산성 검정을 통해 확인하였고, 가중계수가 필요하다고 판단된 경우 분산분석을 통해 적정 가중계수를 선정하였다. 다음으로 편분산분석을 이용하여 회귀모델에 적합한 차수를 결정하였다. 분석물질인 메트암페타민, 암페타민, 대마 대사체에 대해 R 기반 프로그램에 적용한 결과, 단계별 결과 및 최종 모델식을 직관적으로 이해하기 쉽고 신속하게 얻을 수 있었다. 이러한 결과는 문서 파일로 저장이 가능하여 보관의 편의성을 제고하였으며, 본 연구를 통해 제작된 R 기반 프로그램을 활용하여 검량선 작성을 필요로 하는 다양한 약물분석 분야에 확대 적용할 수 있을 것으로 판단된다.

제한급전하는 오프그리드의 독립형 마이크로그리드 최적 설계 및 경제성 평가를 위한 일부하곡선 추정 방안에 관한 연구 (A Study on the Estimation Method of Daily Load Curve for the Optimization Design and Economic Evaluation of Stand-alone Microgrids Based on HOMER Simulation in Off-Grid Limiting the Supply of Electricity)

  • 남용현;윤석민;김정훈;황성욱
    • 전기학회논문지
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    • 제68권1호
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    • pp.27-35
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    • 2019
  • There is a growing interest in various microgrid solutions that supply electricity 24 hours a day to off-grid areas where are not connected with the main grid, and Korea has many positive effects by constructing overseas microgrids as a country operating the emission trading scheme. Since it is not clear how to obtain load curves that is one of the inputs of the HOMER used to design a microgrid optimization plan, or it is necessary to examine whether electricity is supplied to the peak load level of the areas where have not received the electricity benefits from the viewpoint of the demand management, a methodology should be developed to know the load composition ratio and the shape of the daily load curve. In this paper, the relative coefficient and average load information for each load group obtained from the survey are used besides peak load and total average load. A mathematical model is proposed to derive the load composition ratio in the form of a Quadratic Programming and the load forecasting is performed using simple linear regression with future indicators. The effectiveness of the proposed method is confirmed for the Philippine island region supported by Korea Energy Agency and the Asian Development Bank.

확률론적 베이지언 모델링에 의한 케이블 교량의 복합열화 리스크 평가 및 예측시스템 (The Risk Assessment and Prediction for the Mixed Deterioration in Cable Bridges Using a Stochastic Bayesian Modeling)

  • 조태준;이정배;김성수
    • 한국구조물진단유지관리공학회 논문집
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    • 제16권5호
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    • pp.29-39
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    • 2012
  • 상관관계가 높은 복합열화의 완벽한 개별예측모델의 개발은 매우 어려운 문제로, 본 논문에서는 현수교 시스템의 미래열화와 유지 예산을 예측하기 위하여, 10년간의 유지 데이터가 주어진 매개변수(파손지표와 사용성)의 사후 확률 밀도함수를 찾기 위해 베이지언 추론을 적용하였다. 마르코프 연쇄 몬테카를로법을 이용하여 매개변수의 사후 분포를 조사하였다. 감소한 사용성의 모의위험예측은 사전분포와 연간유지 업무에서 업데이트한 데이터의 가능성에 따라 작성한 사후 분포이다. 기존의 선형 예측 모델과 비교하면, 제안된 2차 모델은 교량부품의 사용성, 위험요소, 그리고 유지 예산의 측정 데이터에 대하여 매우 개선된 수렴성과 근접성을 제공한다. 따라서 제안된 2차 추계학적 회귀 모델을 기반으로 복잡한 사회간접설비의 미래 성능과 유지관리예산을 예측하고 제어할 수 있는 기회를 제공할 것으로 기대한다.

Optimizing the composition of the medium for the viable cells of Bifidobacterium animalis subsp. lactis JNU306 using response surface methodology

  • Dang, Thi Duyen;Yong, Cheng Chung;Rheem, Sungsue;Oh, Sejong
    • Journal of Animal Science and Technology
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    • 제63권3호
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    • pp.603-613
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    • 2021
  • This research improved the growth potential of Bifidobacterium animalis subsp lactis strain JNU306, a commercial medium that is appropriate for large-scale production, in yeast extract, soy peptone, glucose, L-cysteine, and ferrous sulfate. Response surface methodology (RSM) was used to optimize the components of this medium, using a central composite design and subsequent analyses. A second-order polynomial regression model, which was fitted to the data at first, significantly lacked fitness. Thus, through further analyses, the model with linear and quadratic terms plus two-way, three-way, and four-way interactions was selected as the final model. Through this model, the optimized medium composition was found as 2.8791% yeast extract, 2.8030% peptone soy, 0.6196% glucose, 0.2823% L-cysteine, and 0.0055% ferrous sulfate, w/v. This optimized medium ensured that the maximum biomass was no lower than the biomass from the commonly used blood-liver (BL) medium. The application of RSM improved the biomass production of this strain in a more cost-effective way by creating an optimum medium. This result shows that B. animalis subsp lactis JNU306 may be used as a commercial starter culture in manufacturing probiotics, including dairy products.

루틴, 퀘르세틴, 식이섬유 혼합물 설계를 이용한 전분소화 지연 효과의 최적화에 대한 융합 연구 (Convergence Study on the Optimization for Suppression of Starch Hydrolysis using Rutin, Quercetin and Dietary Fiber Mixture Design)

  • 오임경;배인영
    • 한국융합학회논문지
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    • 제11권5호
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    • pp.35-41
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    • 2020
  • 본 연구는 루틴, 퀘르세틴, 식이섬유가 전분 소화율에 미치는 영향을 통계적 혼합물 설계방법을 이용하여 확인하고자 하였다. 세 가지 성분들은 모두 농도가 증가함에 따라 전분소화 지연 효과가 나타났으며, 그 중에서도 퀘르세틴과 식이섬유가 함께 섞였을 때 가장 높은 지연 효과를 보였다. 이 혼합물 설계는 simplex-centroid 실험설계법을 이용하였고, 최적 모델은 quadratic 모델에서 나타났다. 이때 얻어진 회귀방정식을 통하여 유의한 상승효과를 확인할 수 있었다. 최적화 통계 방법을 사용하여 혼합비를 분석한 결과 퀘르세틴과 식이섬유가 72: 28 비율에서 전분 소화 지연 효과가 최대로 나타나는 것을 확인하였다. 전분소화에 대한 영향을 3차원 표면 도표로 시각화하여 나타내었으며, 이 결과로 퀘르세틴과 식이섬유의 상호작용으로 인하여 전분 소화를 15% 이상 지연시키는 것을 확인할 수 있었다.

실험계획법과 유한요소해석에 의한 디스크 브레이크의 열변형 최적설계 (Optimal Design for the Thermal Deformation of Disk Brake by Using Design of Experiments and Finite Element Analysis)

  • 이태희;이광기;정상진
    • 대한기계학회논문집A
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    • 제25권12호
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    • pp.1960-1965
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    • 2001
  • In the practical design, it is important to extract the design space information of a complex system in order to optimize the design because the design contains huge amount of design conflicts in general. In this research FEA (finite element analysis) has been successfully implemented and integrated with a statistical approach such as DOE (design of experiments) based RSM (response surface model) to optimize the thermal deformation of an automotive disk brake. The DOE is used for exploring the engineer's design space and for building the RSM in order to facilitate the effective solution of multi-objective optimization problems. The RSM is utilized as an efficient means to rapidly model the trade-off among many conflicting goals existed in the FEA applications. To reduce the computational burden associated with the FEA, the second-order regression models are generated to derive the objective functions and constraints. In this approach, the multiple objective functions and constraints represented by RSM are solved using the sequential quadratic programming to archive the optimal design of disk brake.