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Journal articles on the topic 'Stepwise multiple linear regression'

Author: Grafiati

Published: 4 June 2021

Last updated: 16 February 2022

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1

Ray, Supratim, Chandana Sengupta, and Kunal Roy. "QSAR modeling for lipid peroxidation inhibition potential of flavonoids using topological and structural parameters." Open Chemistry 6, no. 2 (2008): 267–76. http://dx.doi.org/10.2478/s11532-008-0014-7.

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AbstractIn the present study, Quantitative Structure-Activity Relationship (QSAR) modeling has been carried out for lipid peroxidation (LPO)-inhibition potential of a set of 27 flavonoids, using structural and topological parameters. For the development of models, three methods were used: (1) stepwise regression, (2) factor analysis followed by multiple linear regressions (FA-MLR) and (3) partial least squares (PLS) analysis. The best equation was obtained from stepwise regression analysis (Q2 = 0.626) considering the leave-oneout prediction statistics.

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Simmons, R. W., and P. Pongsakul. "Preliminary Stepwise Multiple Linear Regression Method to Predict Cadmium and Zinc Uptake in Soybean." Communications in Soil Science and Plant Analysis 35, no. 13-14 (2005): 1815–28. http://dx.doi.org/10.1081/lcss-200026798.

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3

Nouman, Shakeel. "Multiple and stepwise regression of reproduction efficiency on linear type traits in Sahiwal cows." International Journal of Livestock Production 4, no. 1 (2013): 14–17. http://dx.doi.org/10.5897/ijlp12.029.

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Oliveira, Cinthia Pereira de, Rinaldo Luiz Caraciolo Ferreira, José Antônio Aleixo da Silva, et al. "Modeling and Spatialization of Biomass and Carbon Stock Using LiDAR Metrics in Tropical Dry Forest, Brazil." Forests 12, no. 4 (2021): 473. http://dx.doi.org/10.3390/f12040473.

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In recent years, with the growing environmental concern regarding climate change, there has been a search for efficient alternatives in indirect methods for the quantification of biomass and forest carbon stock. In this article, we seek to obtain pioneering results of biomass and carbon estimates from forest inventory data and LiDAR technology in a dry tropical forest in Brazil. We use forest inventory data in two areas together with data from the LiDAR flyby, generating estimates of local biomass and carbon levels obtained from local species. We approach three types of models for data analysi

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Park, ManKi, HyeRan Yoon, KyoungHo Kim, and JungHwan Cho. "Quantitative analysis by diffuse reflectance infrared Fourier transform and linear stepwise multiple regression analysis I —Simultaneous quantitation of ethenzamide, isopropylantipyrine, caffeine, and allylisopropylacetylurea in tablet by DRIFT and linear stepwise multiple regression analysis—." Archives of Pharmacal Research 11, no. 2 (1988): 99–113. http://dx.doi.org/10.1007/bf02857712.

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6

Liu, Yingxia, Gerard B. M. Heuvelink, Zhanguo Bai, et al. "Analysis of spatio-temporal variation of crop yield in China using stepwise multiple linear regression." Field Crops Research 264 (May 2021): 108098. http://dx.doi.org/10.1016/j.fcr.2021.108098.

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Hanif, Aswar. "Menggunakan Stepwise Linear Regression Untuk Menentukan Faktor Yang Mempengaruhi Produktivitas Tenaga Kerja." Jurnal Informatika 5, no. 1 (2018): 73–80. http://dx.doi.org/10.31311/ji.v5i1.2701.

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Abstrak Semakin lama masa kerja, semakin banyak pengalaman yang dimiliki seseorang atas pekerjaannya. Seorang yang memiliki tingkat kehadiran yang tinggi, dianggap sebagai pekerja yang baik. Kedua faktor ini membentuk asumsi bahwa masa kerja dan tingkat kehadiran, secara positif atau negatif, mempengaruhi produktivitas pekerja. Dikarenakan besarnya pengaruh produktivitas pekerja terhadap kesehatan sebuah perusahaan, kegiatan menganalisis produktivitas tenaga kerja perusahaan, seharusnya tidak didasarkan pada asumsi-asumsi, meskipun asumsi tersebut bisa diterima. Menggunakan Regresi Linie

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Ghasemi, Jahan B., Parvin Zohrabi, and Habibollah Khajehsharifi. "Quantitative structure–activity relationship study of nonpeptide antagonists of CXCR2 using stepwise multiple linear regression analysis." Monatshefte für Chemie - Chemical Monthly 141, no. 1 (2009): 111–18. http://dx.doi.org/10.1007/s00706-009-0225-4.

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Zhan, Xinhua, Xiao Liang, Guohua Xu, and Lixiang Zhou. "Influence of plant root morphology and tissue composition on phenanthrene uptake: Stepwise multiple linear regression analysis." Environmental Pollution 179 (August 2013): 294–300. http://dx.doi.org/10.1016/j.envpol.2013.04.033.

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10

Zhou, Yiqian, Rehman Qureshi, and Ahmet Sacan. "Data simulation and regulatory network reconstruction from time-series microarray data using stepwise multiple linear regression." Network Modeling Analysis in Health Informatics and Bioinformatics 1, no. 1-2 (2012): 3–17. http://dx.doi.org/10.1007/s13721-012-0008-4.

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11

Ding, J., U. Haberlandt, and J. Dietrich. "Estimation of the instantaneous peak flow from maximum daily flow: a comparison of three methods." Hydrology Research 46, no. 5 (2014): 671–88. http://dx.doi.org/10.2166/nh.2014.085.

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Three different methods are compared to estimate the instantaneous peak flow (IPF) from the corresponding maximum daily flow (MDF), as the daily data are more often available at gauges of interest and often with longer recording periods. In the first approach, simple linear regression is applied to calculate IPF from MDF values using probability weighted moments and quantile values. In the second method, the use of stepwise multiple linear regression analysis allows to identify the most important catchment descriptors of the study basin. The resulting equation can be applied to transfer MDF in

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12

Roy, Banibrata, Kyle Perry, Ira Ripstein, and Barry Cohen. "Predictive value of grade point average (GPA), Medical College Admission Test (MCAT), internal examinations (Block) and National Board of Medical Examiners (NBME) scores on Medical Council of Canada qualifying examination part I (MCCQE-1) scores." Canadian Medical Education Journal 7, no. 1 (2016): e47-e56. http://dx.doi.org/10.36834/cmej.36616.

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Background: To determine whether the pre-medical Grade Point Average (GPA), Medical College Admission Test (MCAT), Internal examinations (Block) and National Board of Medical Examiners (NBME) scores are correlated with and predict the Medical Council of Canada Qualifying Examination Part I (MCCQE-1) scores.Methods: Data from 392 admitted students in the graduating classes of 2010-2013 at University of Manitoba (UofM), College of Medicine was considered. Pearson’s correlation to assess the strength of the relationship, multiple linear regression to estimate MCCQE-1 score and stepwise linear reg

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13

Sapkota, Kamal Raj. "Study on QSPR Method for Theoretical Calculation of Boiling Point of Some organic Compounds." Himalayan Physics 3 (January 1, 2013): 93–95. http://dx.doi.org/10.3126/hj.v3i0.7316.

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Quantitative structure-property relationship (QSPR) models based on molecular descriptors derived from molecular structures have been developed for the prediction of boiling point using a set of 25 organic compounds. The molecular descriptors used to represent molecular structure include topological indices and constitutional descriptors. Forward stepwise regression was used to construct the QSPR models. Multiple linear regressions is utilized to construct the linear prediction model. The prediction result agrees well with the experimental value of these properties.The Himalayan PhysicsVol. 3,

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14

Ray, Supratim, Chandana Sengupta, and Kunal Roy. "QSAR modeling of antiradical and antioxidant activities of flavonoids using electrotopological state (E-State) atom parameters." Open Chemistry 5, no. 4 (2007): 1094–113. http://dx.doi.org/10.2478/s11532-007-0047-3.

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AbstractIn the present paper QSAR modeling using electrotopological state atom (E-state) parameters has been attempted to determine the antiradical and the antioxidant activities of flavonoids in two model systems reported by Burda et al. (2001). The antiradical property of a methanolic solution of 1, 1-diphenyl-2-picrylhydrazyl (DPPH) and the antioxidant activity of flavonoids in a β-carotenelinoleic acid were the two model systems studied. Different statistical tools used in this communication are stepwise regression analysis, multiple linear regressions with factor analysis as the preproces

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15

Kokaly, R. "Spectroscopic Determination of Leaf Biochemistry Using Band-Depth Analysis of Absorption Features and Stepwise Multiple Linear Regression." Remote Sensing of Environment 67, no. 3 (1999): 267–87. http://dx.doi.org/10.1016/s0034-4257(98)00084-4.

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Grossman, Y. L., S. L. Ustin, S. Jacquemoud, E. W. Sanderson, G. Schmuck, and J. Verdebout. "Critique of stepwise multiple linear regression for the extraction of leaf biochemistry information from leaf reflectance data." Remote Sensing of Environment 56, no. 3 (1996): 182–93. http://dx.doi.org/10.1016/0034-4257(95)00235-9.

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Boulet, Sebastien, Elsa Boudot, and Nicolas Houel. "Relationships between each part of the spinal curves and upright posture using Multiple stepwise linear regression analysis." Journal of Biomechanics 49, no. 7 (2016): 1149–55. http://dx.doi.org/10.1016/j.jbiomech.2016.02.054.

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18

Huang, Linsheng, Hansu Zhang, Wenjuan Ding, Wenjiang Huang, Tingguang Hu, and Jinling Zhao. "Monitoring of Wheat Scab Using the Specific Spectral Index from ASD Hyperspectral Dataset." Journal of Spectroscopy 2019 (November 11, 2019): 1–9. http://dx.doi.org/10.1155/2019/9153195.

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It is highly important to accurately monitor wheat scab and provide technical guidance for the crop pests and diseases. In this study, relevant analysis was performed among spectral reflectance, first-derivate data, and the disease severity data through ASD hyperspectral data. Two sensitive spectral wavelength ranges of 450–488 nm and 500–540 nm were selected. Then, a new wheat scab index (WSI) consisting of the two bands was proposed. The inversion models of the scab severities were comparatively built by unitary linear regression and multiple stepwise regression techniques. The results showe

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19

Quartezani, Waylson Zancanella, Julião Soares de Souza Lima, Talita Aparecida Pletsch, et al. "Multiple linear and spatial regressions to estimate the influence of Latosol properties on black pepper productivity." June 2019, no. 13(06) 2019 (June 20, 2019): 857–62. http://dx.doi.org/10.21475/ajcs.19.13.06.p1424.

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There is little knowledge available on the best techniques for transferring spatial information such as stochastic interpolation and multivariate analyses for black pepper. This study applies multiple linear and spatial regression to estimate black pepper productivity based on physical and chemical properties of the soil. A multiple linear regression including all properties of a Latosol was performed and followed by variance analysis to verify the validity of the model. The adjusted variograms and data interpolation by kriging allowed the use of spatial multiple regression with the properties

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Li, Mingjun, and Junxing Wang. "An Empirical Comparison of Multiple Linear Regression and Artificial Neural Network for Concrete Dam Deformation Modelling." Mathematical Problems in Engineering 2019 (April 17, 2019): 1–13. http://dx.doi.org/10.1155/2019/7620948.

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Deformation predicting models are essential for evaluating the health status of concrete dams. Nevertheless, the application of the conventional multiple linear regression model has been limited due to the particular structure, random loading, and strong nonlinear deformation of concrete dams. Conversely, the artificial neural network (ANN) model shows good adaptability to complex and highly nonlinear behaviors. This paper aims to evaluate the specific performance of the multiple linear regression (MLR) and artificial neural network (ANN) model in characterizing concrete dam deformation under

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Guimarães, Bruno V. C., Sérgio L. R. Donato, Ignacio Aspiazú, Alcinei M. Azevedo, and Abner J. de Carvalho. "Regression models for productivity prediction in cactus pear cv. Gigante." Revista Brasileira de Engenharia Agrícola e Ambiental 24, no. 11 (2020): 721–27. http://dx.doi.org/10.1590/1807-1929/agriambi.v24n11p721-727.

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ABSTRACT The understanding of plant behavior and its reflexes on yield is essential for rural planning; thus, the biomathematical models are promising in the yield prediction of cactus pear cv. Gigante. This study aimed to adjust, through simple and multiple regression analysis, models for predicting the yield of cactus pear cv. Gigante. The study, using homogeneous treatments, was developed at the Instituto Federal Baiano, Campus of Guanambi, Bahia, Brazil. Data were collected in an area consisting of 384 basic units (plants), in which the yield, defined as a dependent variable, and the predi

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Machado, M. V., A. M. G. Tommaselli, V. M. Tachibana, R. P. Martins-Neto, and M. B. Campos. "EVALUATION OF MULTIPLE LINEAR REGRESSION MODEL TO OBTAIN DBH OF TREES USING DATA FROM A LIGHTWEIGHT LASER SCANNING SYSTEM ON-BOARD A UAV." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W13 (June 4, 2019): 449–54. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w13-449-2019.

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<p><strong>Abstract.</strong> Vegetation mapping requires information about trees and underlying vegetation to ensure proper management of the urban and forest environments. This information can be obtained using remote sensors. For instance, lightweight systems composed of Unmanned Aerial Vehicles (UAVs) as a platform, low-cost laser units and the recent miniaturized navigation sensors (positioning and orientation) have become a very feasible and flexible alternative. Low-cost UAV-ALS systems usually provide centimetric accuracy in altimetry, according to flight data configu

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Minshew, Hudson, John Selker, Delbert Hemphill, and Richard P. Dick. "NLEAP Computer Model and Multiple Linear Regression Prediction of Nitrate Leaching in Vegetable Systems." HortTechnology 12, no. 2 (2002): 250–56. http://dx.doi.org/10.21273/horttech.12.2.250.

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Predicting leaching of residual soil nitrate-nitrogen (NO3-N) in wet climates is important for reducing risks of groundwater contamination and conserving soil N. The goal of this research was to determine the potential to use easily measurable or readily available soilclimatic-plant data that could be put into simple computer models and used to predict NO3 leaching under various management systems. Two computer programs were compared for their potential to predict monthly NO3-N leaching losses in western Oregon vegetable systems with or without cover crops. The models were a statistical multip

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Zhang, Tao, Shanshan Zhang, Lan Chen, et al. "UHPLC–MS/MS-Based Nontargeted Metabolomics Analysis Reveals Biomarkers Related to the Freshness of Chilled Chicken." Foods 9, no. 9 (2020): 1326. http://dx.doi.org/10.3390/foods9091326.

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To identify metabolic biomarkers related to the freshness of chilled chicken, ultra-high-performance liquid chromatography–mass spectrometry (UHPLC–MS/MS) was used to obtain profiles of the metabolites present in chilled chicken stored for different lengths of time. Random forest regression analysis and stepwise multiple linear regression were used to identify key metabolic biomarkers related to the freshness of chilled chicken. A total of 265 differential metabolites were identified during storage of chilled chicken. Of these various metabolites, 37 were selected as potential biomarkers by ra

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Arthur, Yarhands, Samuel Asiedu-Addo, and Charles Assuah. "Teacher-Student Variables as Predictor of Students' Interest in Mathematics: The Use of Stepwise Multiple Linear Regression Analysis." Asian Research Journal of Mathematics 4, no. 3 (2017): 1–11. http://dx.doi.org/10.9734/arjom/2017/33544.

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Zhang, Yanyan, Haile Ma, Bei Wang, Wenjuan Qu, Asif Wali, and Cunshan Zhou. "Relationships between the structure of wheat gluten and ACE inhibitory activity of hydrolysate: stepwise multiple linear regression analysis." Journal of the Science of Food and Agriculture 96, no. 10 (2015): 3313–20. http://dx.doi.org/10.1002/jsfa.7509.

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Zare, Sanaz, Seyed Rashid Fallah Shamsi, and Seyed Ali Abtahi. "Weakly-coupled geo-statistical mapping of soil salinity to Stepwise Multiple Linear Regression of MODIS spectral image products." Journal of African Earth Sciences 152 (April 2019): 101–14. http://dx.doi.org/10.1016/j.jafrearsci.2019.01.008.

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Ahmadi, Shahin, Roohallah Khani, and Maryam Moghaddas. "Prediction of anti-cancer activity of 1,8-naphthyridin derivatives by using of genetic algorithm-stepwise multiple linear regression." MEDICAL SCIENCES JOURNAL 28, no. 3 (2018): 181–94. http://dx.doi.org/10.29252/iau.28.3.181.

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Barbosa, Lucas, Caio Sousa, Marcelo Sales, et al. "Celebrating 40 Years of Ironman: How the Champions Perform." International Journal of Environmental Research and Public Health 16, no. 6 (2019): 1019. http://dx.doi.org/10.3390/ijerph16061019.

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We aimed to determine which discipline had the greater performance improvements in the history of Ironman triathlon in Hawaii and also which discipline had the greater influence in overall race time. Data from 1983 to 2018 of the top three women and men of each year who competed in the Ironman World Championship were included. In addition to exploratory data analyses, linear regressions between split times and years of achievement were performed. Further, a stepwise multiple linear regression was applied using total race time as the dependent variable and split times as the independent variabl

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Jia, Renfu, Shibiao Fang, Wenrong Tu, and Zhilin Sun. "Driven Factors Analysis of China’s Irrigation Water Use Efficiency by Stepwise Regression and Principal Component Analysis." Discrete Dynamics in Nature and Society 2016 (2016): 1–12. http://dx.doi.org/10.1155/2016/8957530.

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This paper introduces an integrated approach to find out the major factors influencing efficiency of irrigation water use in China. It combines multiple stepwise regression (MSR) and principal component analysis (PCA) to obtain more realistic results. In real world case studies, classical linear regression model often involves too many explanatory variables and the linear correlation issue among variables cannot be eliminated. Linearly correlated variables will cause the invalidity of the factor analysis results. To overcome this issue and reduce the number of the variables, PCA technique has

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CORDELL, HEATHER J., JOHN A. TODD, and G. MARK LATHROP. "Mapping multiple linked quantitative trait loci in non-obese diabetic mice using a stepwise regression strategy." Genetical Research 71, no. 1 (1998): 51–64. http://dx.doi.org/10.1017/s0016672398003152.

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A simple regression strategy for mapping multiple linked quantitative trait loci (QTLs) in inbred populations is proposed and applied to data from a non-obese diabetic (NOD) mouse backcross. The method involves adding and deleting markers from a linear model in a stepwise manner, allowing the association with a particular marker to be examined once associations with other (in particular neighbouring) markers have been taken into account. This approach has the advantage of using programs available in standard statistical packages while still allowing adequate separation of possible multiple lin

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Pandiyan, Vigneashwara, Wahyu Caesarendra, Adam Glowacz, and Tegoeh Tjahjowidodo. "Modelling of Material Removal in Abrasive Belt Grinding Process: A Regression Approach." Symmetry 12, no. 1 (2020): 99. http://dx.doi.org/10.3390/sym12010099.

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This article explores the effects of parameters such as cutting speed, force, polymer wheel hardness, feed, and grit size in the abrasive belt grinding process to model material removal. The process has high uncertainty during the interaction between the abrasives and the underneath surface, therefore the theoretical material removal models developed in belt grinding involve assumptions. A conclusive material removal model can be developed in such a dynamic process involving multiple parameters using statistical regression techniques. Six different regression modelling methodologies, namely mu

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Latt, Zaw Zaw, and Hartmut Wittenberg. "Improving Flood Forecasting in a Developing Country: A Comparative Study of Stepwise Multiple Linear Regression and Artificial Neural Network." Water Resources Management 28, no. 8 (2014): 2109–28. http://dx.doi.org/10.1007/s11269-014-0600-8.

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SILVA, KETSON BRUNO DA, RAFAEL OLIVEIRA BATISTA, FRANCISCO DE OLIVEIRA MESQUITA, DANIELA DA COSTA LEITE COELHO, and WESLEY DE OLIVEIRA SANTOS. "EMPIRICAL MODELS FOR PERFORMANCE OF DRIPPERS APPLYING CASHEW NUT PROCESSING WASTEWATER." Revista Caatinga 29, no. 2 (2016): 405–14. http://dx.doi.org/10.1590/1983-21252016v29n217rc.

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ABSTRACT: The objective of this work was to develop empirical models for hydraulic performance of drippers operating with cashew nut processing wastewater depending on operating time, operating pressure and effluent quality. The experiment consisted of two factors, types of drippers (D1=1.65 L h-1, D2=2.00 L h-1 and D3=4.00 L h-1), and operating pressures (70, 140, 210 and 280 kPa), with three replications. The flow variation coefficient (FVC), distribution uniformity coefficient (DUC) and the physicochemical and biological characteristics of the effluent were evaluated every 20 hours until co

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FATEMI, MOHAMMAD H., and PARISA IZADIAN. "IN SILICO PREDICTION OF MELTING POINTS OF IONIC LIQUIDS BY USING MULTILAYER PERCEPTRON NEURAL NETWORKS." Journal of Theoretical and Computational Chemistry 11, no. 01 (2012): 127–41. http://dx.doi.org/10.1142/s0219633612500083.

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Quantitative structure–property relationship (QSPR) was used to predict melting points of 62 ionic liquids (ILs), which include ammonium, pyrrolidiniu, imidazolium, pyridiniu, piperidiniu, phosphonium ionic liquid salts. The structures of ionic liquids were optimized by Hyperchem software and MOPAC program, and stepwise multiple linear regression method was applied to select the relevant structural descriptors. The predicting models correlating selected descriptors and melting points were set up using multiple linear regressions (MLR) and multilayer perceptron neural network (MLP NN), separate

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Tang, Min, Song-Hao Wang, Hui-Lin Li, et al. "Mental health status and quality of life in elderly patients with coronary heart disease." PeerJ 9 (February 17, 2021): e10903. http://dx.doi.org/10.7717/peerj.10903.

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Background Coronary heart disease (CHD) is the leading cause of morbidity and mortality among elderly individuals. Patients with CHD are at high risk for mental health disorders, and psychological issues may affect the quality of life (QoL) of these patients. Nevertheless, there is little evidence regarding the psychological issues and QoL of patients with CHD among the elderly population. This study aimed to investigate the relationship between comorbidities and mental status as well as QoL among elderly patients with CHD. Methods Overall, 216 patients were included in this cross-sectional, o

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Kol, N. A., A. F. Chul'dum, M. G. Rostovtsev, and Yu A. Kalush. "Linear Regression Models Used for the Description of Long-Term Epizootic Process in Tuvinian Natural Plague Focus (Karginsk Mezofocus)." Problems of Particularly Dangerous Infections, no. 1(111) (February 20, 2012): 43–47. http://dx.doi.org/10.21055/0370-1069-2012-1(111)-43-47.

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The results of modeling showed the dependence of epizootic activity in Tuvinian natural plague focus on climatic conditions (average monthly amount of precipitations in the current year and the preceding four years and temperatures in the current and the preceding three years). The multiple linear regression models were used to predict the activity of zoonosis development within a year. The models obtained by means of stepwise regression were most approximated to the natural zoonotic process. The amount of precipitations in winter months and temperature in spring and summer were of the greates

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BOURQUE, GUILLAUME, and DAVID SANKOFF. "IMPROVING GENE NETWORK INFERENCE BY COMPARING EXPRESSION TIME-SERIES ACROSS SPECIES, DEVELOPMENTAL STAGES OR TISSUES." Journal of Bioinformatics and Computational Biology 02, no. 04 (2004): 765–83. http://dx.doi.org/10.1142/s0219720004000892.

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We present a method for gene network inference and revision based on time-series data. Gene networks are modeled using linear differential equations and a generalized stepwise multiple linear regression procedure is used to recover the interaction coefficients. Our system is designed for the recovery of gene interactions concurrently in many gene regulatory networks related by a tree or a more general graph. We show how this comparative framework can facilitate the recovery of the networks and improve the quality of the solutions inferred.

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Lian, Peng Fei, Jun Xu, Bo Yi, Lu Tang, and Yong Gan Zhao. "PM 2.5 Concentration Research Based on Multiple Models." Advanced Materials Research 926-930 (May 2014): 4280–83. http://dx.doi.org/10.4028/www.scientific.net/amr.926-930.4280.

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Along with containing more and more PM2.5, the atmosphere is getting more and more harmful to the human’s health.Therefore, the reseach in PM2.5 characteristics and governance method is extremly significant.In this thesis, the stepwise regression,that is used to analysis the relevance between the PM2.5 concentration and the total concentration of the five other elements of the AQI(Air Quality Index) are introduced firstly.Then the 3-dmensional concentration distribution model in regard to the 10 atmospheric monitoring points of Wuhan is simulated by Matlab, which can reflected the PM2.5 concen

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Et al., Rungroje Songsraboon. "Healthcare Service Quality Model of Private Hospitals in Bangkok, Thailand." Psychology and Education Journal 58, no. 1 (2021): 3854–58. http://dx.doi.org/10.17762/pae.v58i1.1419.

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The objectives of this article are (1) to explore the perceived factors of service quality affecting the decision to use services in private hospitals, (2) to analyze the relationship of service quality models and the decision to use services in private hospitals, and (3) to develop service quality models that influence the decision to use services in private hospitals. The sample group was 400 patients who were admitted to private hospitals listed on the Stock Exchange of Thailand, by the convenience sampling method. The statistics used in this research were descriptive statistics, percentage

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Singh, Ganpat, Arun Goel, and Mahender Choudhary. "Analysis of domestic water demand variables of a residential colony in Ajmer, Rajasthan (India)." Journal of Water, Sanitation and Hygiene for Development 7, no. 4 (2017): 568–75. http://dx.doi.org/10.2166/washdev.2017.020.

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Abstract In this paper, significant variables of domestic urban water demand required for the purpose of estimation of urban water supply in five planned colonies of the City of Ajmer, Rajasthan, India, are identified. The data for these 16 variables are entered in the multiple linear regression (MLR) (stepwise) models in SPSS software, and domestic water demand models are developed. Based on these models, the six most significant variables, namely temperature (T), rainfall (RF), family size (FS), family income (FI), number of bathrooms (NB), and age of house (AH), are identified. The data of

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Fakorede, M. A. B., and B. O. Opeke. "Weather Factors Affecting the Response of Maize to Planting Dates in a Tropical Rainforest Location." Experimental Agriculture 21, no. 1 (1985): 31–40. http://dx.doi.org/10.1017/s0014479700012229.

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SUMMARYSimple linear correlations, stepwise multiple regressions and path-coefficient analyses were used to determine the relation between grain yield of maize (Zea mays L.) and weather factors in a three year study involving several planting dates within each year. Maximum and minimum relative humidity, which demonstrated negative relationships with yield, were the most reliable factors, both directly and indirectly, for predicting yield. Temperature (including accumulated heat units), sunshine hours and total and effective rainfall generally showed negligible direct effects on yield. Potenti

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Alnsour, Muhammed S., Sawsan A. Alshaer, and Abdelhalim Al-Zubi. "Restaurants Facebook Advertising and Consumers Purchase Intention." WSEAS TRANSACTIONS ON BUSINESS AND ECONOMICS 18 (July 13, 2021): 1113–20. http://dx.doi.org/10.37394/23207.2021.18.105.

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Purpose: This main aim of this study is to find out the effects of Facebook ads on Jordanian consumers’ purchase intentions in the restaurant industry. Design/methodology/approach: The design of this research takes a descriptive quantitative approach; a sample of 202 participants answered an online questionnaire, the collected data were analysed by Standardized Multiple Linear Regression and Stepwise Multiple Linear Regression. Findings: The study concluded that restaurants’ Facebook advertising dimensions (Informativeness, Entertainment, Perceived Relevance, Incentive) affect Jordanian consum

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Niu, Guifen, Jian Li, Huaiguo Wang, Yuan Ren, and Jie Bai. "Associations of A-FABP with Anthropometric and Metabolic Indices and Inflammatory Cytokines in Obese Patients with Newly Diagnosed Type 2 Diabetes." BioMed Research International 2016 (2016): 1–6. http://dx.doi.org/10.1155/2016/9382092.

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The study aimed to evaluate the relationship between anthropometric and metabolic indices, inflammatory cytokines, and adipocyte fatty acid-binding protein (A-FABP) in obese patients with newly diagnosed type 2 diabetes. The study included 48 nonobese subjects with newly diagnosed type 2 diabetes, 42 obese subjects with newly diagnosed type 2 diabetes, 30 simple obese subjects, and 30 matched normal subjects. Serum A-FABP was assessed by enzyme-linked immunosorbent assay. Pearson’s correlations and multiple linear regression stepwise analysis were used to analyze correlations of A-FABP with an

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Lebeau, B., and W. E. Hammers. "Estimation of tobacco blend compositions using closed-loop stripping analysis and stepwise multiple linear regression and partial least-squares techniques." Journal of Chromatography A 596, no. 2 (1992): 285–89. http://dx.doi.org/10.1016/0021-9673(92)85019-p.

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Cyr, Kenneth A. "Geophysical Variables and Behavior: XXVIII. Group Health-Care-Seeking Behavior and Meteorological Variables." Perceptual and Motor Skills 60, no. 3 (1985): 863–66. http://dx.doi.org/10.2466/pms.1985.60.3.863.

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Outpatient visits to a “subtropical” military medical clinic (group health-care-seeking behavior) were correlated to weather variables via stepwise linear regression. Despite several significant sets of correlations, quantitative ( r, r2, multiple R, multiple Ra and xχ) and qualitative (matrix) analyses did not support the existence of lag/causal relationships between weather and behavior. The largest amount of variance ( r2) attributable to an individual weather variable was 3% for lowest (minimum) daily mean wind speed per month. No regression accommodated more than 36% of variance. Thus, 64

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Gonzalez-Sanchez, Alberto, Juan Frausto-Solis, and Waldo Ojeda-Bustamante. "Attribute Selection Impact on Linear and Nonlinear Regression Models for Crop Yield Prediction." Scientific World Journal 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/509429.

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Efficient cropping requires yield estimation for each involved crop, where data-driven models are commonly applied. In recent years, some data-driven modeling technique comparisons have been made, looking for the best model to yield prediction. However, attributes are usually selected based on expertise assessment or in dimensionality reduction algorithms. A fairer comparison should include the best subset of features for each regression technique; an evaluation including several crops is preferred. This paper evaluates the most common data-driven modeling techniques applied to yield predictio

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Avval, Zhila, Eslam Pourbashir, Mohammad Ganjali, and Parviz Norouzi. "Application of genetic algorithm - multiple linear regressions to predict the activity of RSK inhibitors." Journal of the Serbian Chemical Society 80, no. 2 (2015): 187–96. http://dx.doi.org/10.2298/jsc140523064a.

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This paper deals with developing a linear quantitative structure-activity relationship (QSAR) model for predicting the RSK inhibition activity of some new compounds. A dataset consisting of 62 pyrazino [1,2-?] indole, diazepino [1,2-?] indole, and imidazole derivatives with known inhibitory activities was used. Multiple linear regressions (MLR) technique combined with the stepwise (SW) and the genetic algorithm (GA) methods as variable selection tools was employed. For more checking stability, robustness and predictability of the proposed models, internal and external validation techniques wer

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Stelzl, Anika, Michael Pointl, and Daniela Fuchs-Hanusch. "Estimating Future Peak Water Demand with a Regression Model Considering Climate Indices." Water 13, no. 14 (2021): 1912. http://dx.doi.org/10.3390/w13141912.

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Although Austria is a water-rich country, impacts of climate change on water supply are already noticeable. Some regions were affected by water scarcity in recent years. Due to climate change, an increase in peak water demand is expected in the future. Therefore, water demand prediction models that include climate indices are of interest. In this paper, we present a general multiple linear regression (GMLR) model that can be applied to selected study sites. We compared the performance of the GMLR model with different modeling approaches, i.e., stepwise multiple linear regression, support vecto

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Евстегнеева, V. Evstegneeva, Честнова, Tatyana Chestnova, Смольянинова, and O. Smolyaninova. "Regression analysis forecasting pririrodno focal infections." Journal of New Medical Technologies. eJournal 9, no. 4 (2015): 0. http://dx.doi.org/10.12737/17086.

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Regression analysis - a set of statistical methods for processing of experimental data to a condition of stochastic dependence study of the value of non-random or random variables to define this relationship. Statement of the problem of regression analysis is formulated as follows. There is a set of observational results. Requires a quantitative relationship between the index and factors. In this paper, we try to establish a quantitative relationship between the incidence of natural - focal infections and biotic and abiotic factors of the environment. By biotic fa

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