Relevant bibliographies by topics / Regression-later

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Regression-later'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Regression-later"

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Abramson, David H., Cynthia M. Gerardi, Robert M. Ellsworth, Beryl McCormic, David Sussman, and Liebert Turner. "Radiation Regression Patterns in Treated Retinoblastoma: 7 to 21 Years Later." Journal of Pediatric Ophthalmology & Strabismus 28, no. 2 (1991): 108–12. http://dx.doi.org/10.3928/0191-3913-19910301-12.

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Ghosh, U. K., D. Sharma, H. Iliyas, and R. Baveja. "A Simple Regression Model for Estimating Gestational Age in Later Pregnancy by Ultrasonography." Asia-Oceania Journal of Obstetrics and Gynaecology 16, no. 2 (2010): 161–64. http://dx.doi.org/10.1111/j.1447-0756.1990.tb00019.x.

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Xiang, Xiaoling, and Xiafei Wang. "Childhood adversity and major depression in later life: A competing‐risks regression analysis." International Journal of Geriatric Psychiatry 36, no. 1 (2020): 215–23. http://dx.doi.org/10.1002/gps.5417.

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Brotherstone, Susan, and W. G. Hill. "A retrospective evaluation of the weights in the cow genetic index." Animal Science 44, no. 3 (1987): 355–61. http://dx.doi.org/10.1017/s0003356100012289.

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ABSTRACTThe fat plus protein yield of 70 011 records of pedigree British Friesian/Holstein cows was regressed on various components of their dam's Cow Genetic Index (CGI) in order to obtain the regression coefficients for comparison with the index weights currently used in the calculation of the CGI. For the first and later (2 to 5) lactation components of the CGI, the regression coefficients obtained by analysis were consistent with the tabulated index weights, but the coefficients for the sire component tended in some cases to be lower than the table values. The analysis was repeated using only dams that had widely used sires. The partial regression coefficients for the first and later lactation components were again consistent with the tabulated weights, and the coefficient for the sire component lay within one s.d. of the table values. In all cases, a cow's CGI is shown to take full account of her first and later lactation information and her sire's and dam's transmitting abilities.
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Cole, Timothy James. "Can Partial Least Squares Regression Separate the Effects of Body Size and Growth on Later Blood Pressure?" Epidemiology 21, no. 4 (2010): 449–51. http://dx.doi.org/10.1097/ede.0b013e3181d74bf5.

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Tsai, Alan C., Tsui-Lan Chang, and Shu-Hwang Chi. "Frequent consumption of vegetables predicts lower risk of depression in older Taiwanese – results of a prospective population-based study." Public Health Nutrition 15, no. 6 (2011): 1087–92. http://dx.doi.org/10.1017/s1368980011002977.

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AbstractObjectiveThe study evaluated the association between consumption frequencies of the major food categories and the risk of new depression four years later in older Taiwanese.DesignA prospective cohort study with multistage random sampling. Logistic regression analysis evaluated the significance of the longitudinal associations of intake frequencies of the major food categories with future (4 years later) risk of new depression, controlled for possible confounding factors with or without adjustment for cognitive status.SettingPopulation-based free-living elderly.SubjectsMen and women (n 1609) ≥65 years of age.ResultsIn a regression model that controlled for demographic, socio-economic, lifestyle and disease/health-related variables but not cognitive status, both fruits (OR = 0·66, 95 % CI 0·45, 0·98, P = 0·038) and vegetables (OR = 0·38, 95 % CI 0·17, 0·86, P = 0·021) were protective against depressive symptoms 4 years later. However, when the same regression model was also adjusted for cognitive status, only vegetables (OR = 0·40, 95 % CI 0·17, 0·95, P = 0·039) were protective against depressive symptoms. Higher consumption of eggs was close to being significant in both regression models (P = 0·087 and 0·069, respectively). Other food categories including meat/poultry, fish, seafood, dairy, legumes, grains and tea showed no significant associations.ConclusionsResults suggest that although confounding factors cannot be totally ruled out, more frequent consumption of vegetables seems to be protective against depressive symptoms in the elderly. Further studies are needed to elucidate the causal role and the mechanism of the association.
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Walters, Glenn D., and Dorothy L. Espelage. "Bullying Perpetration and Subsequent Delinquency: A Regression-Based Analysis of Early Adolescent Schoolchildren." Journal of Early Adolescence 39, no. 5 (2018): 669–88. http://dx.doi.org/10.1177/0272431618791277.

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The purpose of this study was to determine whether bullying perpetration in early adolescence is capable of predicting delinquency 1 year later. Nine control variables were included in a regression analysis of the bullying–delinquency relationship in 1,001 schoolchildren ([Formula: see text] age = 12.97 years). The nine control variables (age, sex, race, social support, bullying victimization, probullying attitudes, parental knowledge, impulsivity, and peer delinquency), along with bullying perpetration and prior delinquency, were regressed onto delinquency measured 1 year later. Because the majority of participants (63.3%) were missing data on the outcome measure, a full information maximum likelihood (FIML) with auxiliary variables was performed. The results of a preliminary confirmatory factor analysis demonstrated that the bullying and delinquency scales employed in this study were assessing separate constructs. The main analysis revealed that parental knowledge, impulsivity, bullying, and precursor delinquency predicted delinquency one year later.
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Wright, Liam, Jenny A. Head, and Stephen Jivraj. "How robust is the association between youth unemployment and later mental health? An analysis of longitudinal data from English schoolchildren." Occupational and Environmental Medicine 78, no. 8 (2021): 618–20. http://dx.doi.org/10.1136/oemed-2021-107473.

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BackgroundSeveral studies show that youth unemployment is associated with worse mental health later in life. However, existing studies report results for only one model, or a few models, and use regression adjustment to support causal claims. We use two novel methods to address these gaps in the literature.MethodsWe use data from Next Steps, a cohort study of English schoolchildren who entered the labour market in the aftermath of the 2008–2009 global financial crisis, and measure mental health using the 12-item General Health Questionnaire (GHQ-12) at age 25. We use specification curve analysis and a negative control outcome design (a form of placebo test) to test whether associations between youth unemployment and later GHQ-12 scores are sensitive to model specification or are likely to be confounded by unobserved factors.ResultsWe find that the association between unemployment and later GHQ-12 is qualitatively similar across 99.96% of the 120 000 models we run. Statistically significant associations with two placebo outcomes, height and patience, are not present when regression adjustments are made.ConclusionsThere is clear evidence that youth unemployment is related to later mental health, and some evidence that this cannot be easily explained by unobserved confounding.
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Zagar, Robert John, William M. Grove, Kenneth G. Busch, John Russell Hughes, and Jack Arbit. "Looking Forward in Records of Youth Abused as Infants: Risks for Homicidal, Violent, and Delinquent Offenses." Psychological Reports 104, no. 1 (2009): 47–75. http://dx.doi.org/10.2466/pr0.104.1.47-75.

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To study risks for abuse and later homicidal behavior, 192 abused infants ( M age = 3.12 yr., SD = 1.48; 82 girls, 110 boys) and 192 controls were matched on demographics and examined; data discriminating abused and later homicidal cases were analyzed with Shao's bootstrapped logistic regression. Predictors of Abused status were injury, burn, poisoning, fetal substance exposure ( OR = 2.47), later parental or youth court contacts ( OR = 1.86e+12), and parental alcohol abuse (OR = .54; AUC = .99; 95% CI= .96−.99). Youth tracked through records 12 years (to M age = 12.17 yr., SD =1.89) were classified into Abused Later Homicidal (11%, n = 21), Abused Later Violent (14%, n = 27), Abused Later Delinquent (31%, n = 60), Abused Later Nondeliquent ( n = 44), and Control groups ( n = 192). Data were analyzed similarly. When the Abused Later Homicidal was contrasted with the Control group, predictors of homicide were three or more home/school moves ( OR = .78), illnesses ( OR = .90), and later court contacts ( OR= 1.75e+07; AUC=.99; 95% CI=.90−.98). When the Abused Later Homicidal was compared with the Abused Later Nondelinquent group, predictors of homicide were poorer executive function ( OR = 2.29) and later court contacts ( OR = 7.78e+06; AUC=.94; 95% CI= .90−.98).
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Anas, Malik Muhammad, Zhensheng Huang, David Anekeya Alilah, Ambreen Shafqat, and Sajjad Hussain. "Mean Estimators Using Robust Quantile Regression and L-Moments’ Characteristics for Complete and Partial Auxiliary Information." Mathematical Problems in Engineering 2021 (July 31, 2021): 1–8. http://dx.doi.org/10.1155/2021/9242895.

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Ratio type regression estimator is a prevalent and readily implemented heuristic under simple random sampling (SRS) and two-stage sampling for the estimation of population. But this existing method is based on the ordinary least square (OLS) regression coefficient which is not an effective approach in the presence outliers in the data. In this article, we proposed a class of estimators firstly for complete auxiliary information and, later on, for partial auxiliary information for the presence of outliers in the data. To address this problem, initially we presented a distinct class of estimators by introducing the characteristics of L-moments in the existing estimators. Later on, quantile regression estimators are defined as more robust in the presence of outliers. These techniques empowered the proposed estimators to handle the problem of outliers. To prove the better performance of the proposed estimators, numerical studies are carried out using R language. To calculate the mean square error (MSE), hypothetical equations are expressed for adapted and proposed estimators. Percentage Relative Efficiencies (PRE) are compared to justify the proposed estimators.
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Dissertations / Theses on the topic "Regression-later"

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Martin, Ruth A. (Ruth Angela) Carleton University Dissertation Sociology and Anthropology. "The Later life course: a study of the snowbird phenomenon." Ottawa, 1999.

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Ha, Hongjun. "Essays on Computational Problems in Insurance." 2016. http://scholarworks.gsu.edu/rmi_diss/40.

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This dissertation consists of two chapters. The first chapter establishes an algorithm for calculating capital requirements. The calculation of capital requirements for financial institutions usually entails a reevaluation of the company's assets and liabilities at some future point in time for a (large) number of stochastic forecasts of economic and firm-specific variables. The complexity of this nested valuation problem leads many companies to struggle with the implementation. The current chapter proposes and analyzes a novel approach to this computational problem based on least-squares regression and Monte Carlo simulations. Our approach is motivated by a well-known method for pricing non-European derivatives. We study convergence of the algorithm and analyze the resulting estimate for practically important risk measures. Moreover, we address the problem of how to choose the regressors, and show that an optimal choice is given by the left singular functions of the corresponding valuation operator. Our numerical examples demonstrate that the algorithm can produce accurate results at relatively low computational costs, particularly when relying on the optimal basis functions. The second chapter discusses another application of regression-based methods, in the context of pricing variable annuities. Advanced life insurance products with exercise-dependent financial guarantees present challenging problems in view of pricing and risk management. In particular, due to the complexity of the guarantees and since practical valuation frameworks include a variety of stochastic risk factors, conventional methods that are based on the discretization of the underlying (Markov) state space may not be feasible. As a practical alternative, this chapter explores the applicability of Least-Squares Monte Carlo (LSM) methods familiar from American option pricing in this context. Unlike previous literature we consider optionality beyond surrendering the contract, where we focus on popular withdrawal benefits - so-called GMWBs - within Variable Annuities. We introduce different LSM variants, particularly the regression-now and regression-later approaches, and explore their viability and potential pitfalls. We commence our numerical analysis in a basic Black-Scholes framework, where we compare the LSM results to those from a discretization approach. We then extend the model to include various relevant risk factors and compare the results to those from the basic framework.
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Books on the topic "Regression-later"

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Wrightson, Christiana. Choices: How Bad Karma Causes Suffering in a Later Life and How Regression Psychotherapy Helps. Authorhouse, 2003.

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Smith-Hicks, C. L., and S. Naidu. Rett Syndrome. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780199937837.003.0054.

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Rett Syndrome (RTT) is a neurodevelopmental disorder that predominantly affects females but males with RTT have been identified. RTT was first described by an Austrian pediatrician, Andreas Rett. Rett syndrome was mapped to chromosome Xq28 in 1998 and a year later it was determined to be due to mutations in the MeCP2 gene at this locus. Identification of the gene led to the broadening of the clinical phenotype and further characterization into classic and atypical forms of the disease that overlap with Autism spectrum disorders during the period of regression. More than 95% of individuals with classic RTT have mutations in the MeCP2 gene.
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Book chapters on the topic "Regression-later"

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Glasserman, Paul, and Bin Yu. "Simulation for American Options: Regression Now or Regression Later?" In Monte Carlo and Quasi-Monte Carlo Methods 2002. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-642-18743-8_12.

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Frühwirth, Rudolf, and Are Strandlie. "Statistics and Numerical Methods." In Pattern Recognition, Tracking and Vertex Reconstruction in Particle Detectors. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-65771-0_3.

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AbstractThe chapter gives an outline of some statistical and numerical methods that will be applied in later chapters. The first section deals with the minimization of functions. Several gradient-based methods and a popular non-gradient method are discussed. The following section discusses statistical models and the estimation of model parameters. The basics of linear and nonlinear regression models and state space models are presented, including least-squares estimation and the (extended) Kalman filter. The final section gives a brief overview of clustering and different types of clustering algorithms.
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Myck, Michal, Charles Waldegrave, and Lena Dahlberg. "Two Dimensions of Social Exclusion: Economic Deprivation and Dynamics of Loneliness During Later Life in Europe." In International Perspectives on Aging. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-51406-8_24.

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AbstractWe contribute to the discussion on social exclusion interrelationships by examining the relationship between material conditions and loneliness, as one potential marker of connections between the social and economic domain. Our analysis focuses on a sample of individuals aged 50+ in the Survey of Health Ageing and Retirement in Europe (SHARE). In its 5th wave, the survey was extended to include specific items related to economic and social deprivation. We use this extended information on material conditions and examine how it correlates with the level and dynamics of a composite loneliness measure at the time of wave 5 and between wave 5 and 6 of the survey (undertaken in 2013 and 2015, respectively). In order to isolate the effect of material deprivation on loneliness, regression analyses include an extensive set of control variables. The analyses show a strong and significant relationship between material deprivation, and both the level of loneliness and deterioration in the loneliness status.
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Eshel, Gidon. "Regression and Least Squares." In Spatiotemporal Data Analysis. Princeton University Press, 2011. http://dx.doi.org/10.23943/princeton/9780691128917.003.0009.

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This chapter focuses on linear regression, the process of identifying the unique model that best explains a set of observed data among a specified class of general models. Regression thus occupies a uniquely important position at the very interface of modeling and data analysis. Regression arises very often, in various guises, in handling and analyzing data. Since it is one of the most basic, useful, and frequently employed data analysis tools, and since some understanding of regression is needed in later sections, regression will be discussed in some detail. Topics covered include setting up the problem; the linear system Ax = b, least squares, special problems giving rise to linear systems, statistical issues in regression analysis, and multidimensional regression and linear model identification.
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Temin, Peter. "Appendix to Chapter 3." In The Roman Market Economy. Princeton University Press, 2012. http://dx.doi.org/10.23943/princeton/9780691147680.003.0012.

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I employ descriptive regressions of the price of each commodity over time to examine the long-and short-run variation in prices as a whole. The results of estimating equations in the text show that contemporaries could not have predicted future prices; descriptive regressions can tell later observers what actually happened. The first such regression evaluates the long-run trend of prices. It models the relationship between each commodity’s log price and the year, year squared, year cubed, and three dummy variables for different intervals:...
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Kaufman, Claire S., Keith B. Quencer, and John A. Kaufman. "IVC Embryology and Anatomy." In Interventional Radiology, edited by Bradley B. Pua, Anne M. Covey, and David C. Madoff. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190276249.003.0021.

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As the largest venous structure in the body, the inferior vena cava (IVC) acts as a central conduit in many interventional radiology (IR) procedures. It originates from the regression of three paired embryonic veins in the developing embryo. Given the complex embryology of the IVC, it is not surprising that many anomalies occur. The first portion of this chapter provides an overview of the anatomy and embryology of the IVC to frame subsequent discussions later in the chapter on the anomalies and various pathologies that an interventional radiologist may encounter. An in-depth discussion on IVC filtration is also included.
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Papazoglou, Emily. "Development: What You Need to Know." In Don't Wait and See!, edited by Emily Papazoglou. Oxford University Press, 2020. http://dx.doi.org/10.1093/med-psych/9780190081300.003.0001.

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Early and intensive intervention is one of the most powerful tools we have to combat developmental disorders, but developmental issues are frequently identified much later than they should be, often because a “wait and see” approach is recommended during early childhood. The power of early intervention as one of the key tools to support your child’s development will be discussed. Developmental milestones are reviewed along with common patterns of development. Development may occur unevenly across skill areas and spurts in skill building are common, but regression, or loss of skills, is not. The higher risk of developmental issues in boys also will be discussed.
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Hector, Andy. "Introduction." In The New Statistics with R. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780198798170.003.0001.

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This chapter sets out the aims of the book, the approach, what is covered in the book, and what is not. The chapter introduces the R and RStudio software packages. It also summarizes the changes made to the second edition of the book. The book starts by introducing several different variations of the basic linear-model analysis (analysis of variance, linear regression, analysis of covariance, etc.). The later part of the book covers generalized linear models (for data with non-normal distributions). The book ends by combining these two extensions into generalized linear mixed-effects models. To allow a learning-by-doing approach, the R code necessary to perform the basic analysis is embedded in the text along with the key output from R.
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Kraner, Mariah. "Social Media and Voter Participation." In Digital Democracy. IGI Global, 2012. http://dx.doi.org/10.4018/978-1-4666-1740-7.ch079.

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This chapter looks at the political trends associated with using social media sources as a way to enhance participation in national elections. It is hypothesized that participation has declined across groups and through time, regardless of the new uses of social media in political campaigning. The historical significance of voter participation is examined using Alexis De Tocqueville’s and Robert Putnam’s frameworks. The path is paved to examine both the importance of new media in the election process and its drawbacks. A national empirical test is presented that examines the correlation between race categories, genders, and age ranges, with the percentage of voter turnout in each presidential election year from 1964 to 2008. Regression analysis is also conducted to examine the predictive nature of increased time on national voter participation. The correlation and regression results are presented, indicating that, in general, participation has continued to decline among most groups, regardless of the perceived access and connection provided by social media outlets. However, a slight change after 1996 may indicate an effect from social media presence. The data presents a starting point for future evaluation of e-government effects on national voter participation in the election process, providing a benchmark for later empirical tests.
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Kraner, Mariah. "Social Media and Voter Participation." In Public Service, Governance and Web 2.0 Technologies. IGI Global, 2012. http://dx.doi.org/10.4018/978-1-4666-0071-3.ch002.

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This chapter looks at the political trends associated with using social media sources as a way to enhance participation in national elections. It is hypothesized that participation has declined across groups and through time, regardless of the new uses of social media in political campaigning. The historical significance of voter participation is examined using Alexis De Tocqueville’s and Robert Putnam’s frameworks. The path is paved to examine both the importance of new media in the election process and its drawbacks. A national empirical test is presented that examines the correlation between race categories, genders, and age ranges, with the percentage of voter turnout in each presidential election year from 1964 to 2008. Regression analysis is also conducted to examine the predictive nature of increased time on national voter participation. The correlation and regression results are presented, indicating that, in general, participation has continued to decline among most groups, regardless of the perceived access and connection provided by social media outlets. However, a slight change after 1996 may indicate an effect from social media presence. The data presents a starting point for future evaluation of e-government effects on national voter participation in the election process, providing a benchmark for later empirical tests.
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Conference papers on the topic "Regression-later"

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Cai, Weihua, Mihir Sen, K. T. Yang, and Arturo Pacheco-Vega. "Genetic-Programming-Based Symbolic Regression for Heat Transfer Correlations of a Compact Heat Exchanger." In ASME 2005 Summer Heat Transfer Conference collocated with the ASME 2005 Pacific Rim Technical Conference and Exhibition on Integration and Packaging of MEMS, NEMS, and Electronic Systems. ASMEDC, 2005. http://dx.doi.org/10.1115/ht2005-72293.

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We describe a symbolic regression methodology based on genetic programming to find correlations that can be used to estimate the performance of compact heat exchangers. Genetic programming is an evolutionary search technique in which functions represented as parse trees evolve as the search proceeds. An advantage of this approach is that functional forms of the correlation need not be assumed. The algorithm performs symbolic regression by seeking both the functional structure of the correlation and the coefficients therein that enable the closest fit to experimental data. This search is conducted within a functional domain constructed from sets of operators and terminals that are used to build tree-structures representing functions. A penalty function is used to prevent large correlations. The methodology is tested using first artificial data from a one-dimensional function and later a set of published heat exchanger experiments. Comparison with published results from the same data show that symbolic-regression correlations are as good or better. The effect of the penalty parameters on the “best function” is also analyzed.
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Luo, Chen, and Shiliang Sun. "Variational Mixtures of Gaussian Processes for Classification." In Twenty-Sixth International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/642.

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Gaussian Processes (GPs) are powerful tools for machine learning which have been applied to both classification and regression. The mixture models of GPs were later proposed to further improve GPs for data modeling. However, these models are formulated for regression problems. In this work, we propose a new Mixture of Gaussian Processes for Classification (MGPC). Instead of the Gaussian likelihood for regression, MGPC employs the logistic function as likelihood to obtain the class probabilities, which is suitable for classification problems. The posterior distribution of latent variables is approximated through variational inference. The hyperparameters are optimized through the variational EM method and a greedy algorithm. Experiments are performed on multiple real-world datasets which show improvements over five widely used methods on predictive performance. The results also indicate that for classification MGPC is significantly better than the regression model with mixtures of GPs, different from the existing consensus that their single model counterparts are comparable.
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Liang, Yang, and B. F. Feeny. "Parametric Identification of Chaotic Base-Excited Double Pendulum Experiment." In ASME 2004 International Mechanical Engineering Congress and Exposition. ASMEDC, 2004. http://dx.doi.org/10.1115/imece2004-59836.

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An improved parametric identification of chaotic systems was investigated for a double pendulum. From recorded experimental response data, the unstable periodic orbits were extracted and later used in a harmonic balance identification process. By applying digital filtering, digital differentiation and linear regression techniques for optimization, the results were improved. Verification of the related simulation system and linearized system also corroborated the success of the identification algorithm.
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Sun, Shuai, Jun Bi, Montserrat Guillen, and Ana Maria Pérez-Marín. "Regression scores to identify risky drivers from braking pulses." In CARMA 2020 - 3rd International Conference on Advanced Research Methods and Analytics. Universitat Politècnica de València, 2020. http://dx.doi.org/10.4995/carma2020.2020.11514.

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Driving data record information on style and patterns of vehicles that are inmotion. These data are analysed to obtain risk scores that can later beimplemented in insurance pricing schemes. Scores may also be used in on-board sensors to create risk alerts that help drivers to keep up with safetymargins. Regression methods are proposed and a prototype real sample of 253drivers is analysed. Conclusions are drawn on the mean number of brakepulses per day as measured within 30 seconds time-intervals. Linear andlogistic regressions serve to construct a label that classifies drivers. A novelfactor based on the driving range that is defined from geo-localizationimproves the results considerably. Driving range is expressed as measures thediagonal of a rectangle that contains the furthest North-South versus East-West weekly vehicle trajectory. This factor shows that frequent braking activityis negatively related to the square of driving range.
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Jeffries, Brien, J. Wesley Hines, Albert Klein, Thomas Palmé, and Romain Bayère. "Early Detection of Boiler Leakage in a Combined Cycle Power Plant Using an Auto Associative Kernel Regression Model." In ASME Turbo Expo 2013: Turbine Technical Conference and Exposition. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/gt2013-94216.

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This paper presents the results of applying a data-driven condition-based monitoring system for the fault detection of a boiler leakage in a Combined Cycle Power Plant (CCPP). An auto associative kernel regression model is developed using normal process data and tested with faulted data to determine the earliest warning of the boiler leakage. Automatic variable grouping, which uses the linear correlations among the available thirty sensors, is employed to obtain optimal groupings to be used in model development. Several models were developed, optimized and compared. A logic test was used for fault detection and this test produced alarms in the region were the leak was later confirmed to have occurred. Comparison of these results with those of a physics-based analysis also confirmed the accuracy of the models in the early detection of the leakage.
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Li, Pingchuan, Xianguo Tuo, Mingzhe Liu, et al. "Effect of Temperature and Humidity on Measuring Ionization Current Inside Contaminated Pipes." In 2013 21st International Conference on Nuclear Engineering. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/icone21-16048.

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This paper reported the experimental results of ion current under different temperatures and relative humidity using long range alpha detector (LRAD). An approximation relation between the measuring values, temperatures and relative humidity has been obtained using the linear multiple regression method. The experimental results have shown that the measuring values decrease with the increase of temperature and humidity. The influence of humidity on results outweighs that of temperatures. And both temperature and humidity are obviously negative correlated with measured values. Further experiments will be performed to confirm the coupling effects of temperature and humidity and reported later.
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Giraldo, Jorge, Jaime Garci´a, Antonio Bula, Marco Sanjuan, and Adria´n A´vila. "Extended Arrhenius Kinetic Model for the Transesterification Reaction of Biodiesel From Palm Oil and Ethanol." In ASME 2007 International Mechanical Engineering Congress and Exposition. ASMEDC, 2007. http://dx.doi.org/10.1115/imece2007-43512.

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Modeling and understanding reaction kinetics is essential for processes and equipment design. This paper presents a kinetic analysis of the transesterification reaction of palm oil extracted in the Colombian north coast with ethanol to produce biodiesel. The analysis is based in actual lab scale production and it considers a set of three reactions in a batch reactor with dynamic behavior. It was found that the kinetics does not adjust to the common Arrhenius equation model, therefore an extended Arrhenius equation model was proposed. This extended model captures temperature effects better than the standard Arrhenius form. New reaction constants were found using computer-based regression analysis, and the model was later used to simulate a continuous biodiesel production plant.
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Zhou, Xiaoyu, Hongxia Li, and Yi Huang. "Modified Probability Density Evolution Method for the Solution of Multi-Degree-of-Freedom Nonlinear Stochastic Dynamical Systems." In ASME 2017 36th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/omae2017-62382.

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A probability density evolution based exponential polynomial regression (PDEM-EPR) method to calculate the probability density function (PDF) of the high dimensional nonlinear stochastic dynamical systems is presented in this paper. Several typical examples, such as linear oscillator and Duffing oscillator are solved by PDEM-EPR method, and the results fit well with the analytical solutions. An engineering practice problem of ship nonlinear random roll in the beam waves is involved in this paper. The results obtained by PDEM-EPR is compared with those obtained by path integral method. The later results were given by Chai Wei [3]. It shows that PDEM-EPR method has the advantages as following: 1) The multi-degree-of-freedom (MDOF) nonlinear stochastic dynamical problems can be solved by PDEM-EPR method; 2) High efficiency can be obtained by PDEM-EPR method.
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9

Kalina, Ondrej, Lucia Barbierik, and Jozef Benka. "LONGITUDINAL EFFECT OF THE PUNAV PREVENTION PROGRAM ON NORMATIVE BELIEFS AND ALCOHOL USE AMONG UNIVERSITY STUDENTS." In International Psychological Applications Conference and Trends. inScience Press, 2021. http://dx.doi.org/10.36315/2021inpact087.

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"The universal Prevention Program of Substance Use among University Students (PUNAV) is based on the strategy of correcting normative beliefs (NBs) regarding alcohol use. The current research shown that NBs are a significant factor in relation to alcohol consumption. This study has explored whether a change of NBs is associated with a decrease of alcohol use among university students. The data used in this study were collected before the implementation of PUNAV in September 2018 (N=137, Mage = 21.9, 77% women) and 18 months later after the implementation of the program in March 2020 (N=54, 77% women). Participants provided information on alcohol consumption, alcohol dependence, alcohol harmful use and descriptive NBs regarding alcohol consumption. The level of NBs at T2 was subtracted from level of NB at T1 (T1 – T2) to identify changes in NBs over time. Using SPSS 21, a linear regression model which controlled for the level of the outcome variables at T1 and observed changes in NBs were used to predict the outcome variables measured at T2. Alcohol consumption and NBs after PUNAV decreased alcohol consumption but increased the dependence and alcohol harmful consequences. The regression model, which controlled for alcohol use at T1, showed that a significant change in NBs was negatively associated with alcohol consumption at T2. The findings have in general shown that the observed changes in NBs (corrected NBs) were more likely to decrease alcohol consumption among university students."
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Alemela, Panduranga Reddy, Dan Fanaca, Florian Ettner, Christoph Hirsch, Thomas Sattelmayer, and Bruno Schuermans. "Flame Transfer Matrices of a Premixed Flame and a Global Check With Modelling and Experiments." In ASME Turbo Expo 2008: Power for Land, Sea, and Air. ASMEDC, 2008. http://dx.doi.org/10.1115/gt2008-50111.

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In this paper alternative ways to obtain the thermo-acoustical characteristics of perfectly premixed flames given by their flame transfer matrix (FTM) is investigated. In particular a model based data reduction procedure which greatly reduces the experimental effort and therefore enables to provide this flame data for many more operation points than previously possible is proposed and validated. It is shown how the acoustic pressure field measured from two forcing states using the multi microphone method leads to the determination of the direct experimental FTM. The next relatively simpler method shown is the hybrid method which is based on Rankine-Hugoniot relations and the experimental flame transfer function (FTF) from OH*-chemiluminescence measurements for heat release fluctuations. Later to obtain the FTM using a network model based on Rankine-Hugoniot relations and an n-τ-σ FTF model representing the flame by regression analysis of the acoustical measurements is presented. Experimental results for the direct experimental FTM and the hybrid FTM are compared with the model based result. The results indicate very good consistency between the direct, hybrid and model based techniques providing a global check of the methods/tools used for analysing the thermoacoustic mechanisms of flames.
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Reports on the topic "Regression-later"

1

Over, Thomas, Riki Saito, Andrea Veilleux, et al. Estimation of Peak Discharge Quantiles for Selected Annual Exceedance Probabilities in Northeastern Illinois. Illinois Center for Transportation, 2016. http://dx.doi.org/10.36501/0197-9191/16-014.

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This report provides two sets of equations for estimating peak discharge quantiles at annual exceedance probabilities (AEPs) of 0.50, 0.20, 0.10, 0.04, 0.02, 0.01, 0.005, and 0.002 (recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years, respectively) for watersheds in Illinois based on annual maximum peak discharge data from 117 watersheds in and near northeastern Illinois. One set of equations was developed through a temporal analysis with a two-step least squares-quantile regression technique that measures the average effect of changes in the urbanization of the watersheds used in the study. The resulting equations can be used to adjust rural peak discharge quantiles for the effect of urbanization, and in this study the equations also were used to adjust the annual maximum peak discharges from the study watersheds to 2010 urbanization conditions. The other set of equations was developed by a spatial analysis. This analysis used generalized least-squares regression to fit the peak discharge quantiles computed from the urbanization-adjusted annual maximum peak discharges from the study watersheds to drainage-basin characteristics. The peak discharge quantiles were computed by using the Expected Moments Algorithm following the removal of potentially influential low floods defined by a multiple Grubbs-Beck test. To improve the quantile estimates, regional skew coefficients were obtained from a newly developed regional skew model in which the skew increases with the urbanized land use fraction. The skew coefficient values for each streamgage were then computed as the variance-weighted average of at-site and regional skew coefficients. The drainage-basin characteristics used as explanatory variables in the spatial analysis include drainage area, the fraction of developed land, the fraction of land with poorly drained soils or likely water, and the basin slope estimated as the ratio of the basin relief to basin perimeter. This report also provides: (1) examples to illustrate the use of the spatial and urbanization-adjustment equations for estimating peak discharge quantiles at ungaged sites and to improve flood-quantile estimates at and near a gaged site; (2) the urbanization-adjusted annual maximum peak discharges and peak discharge quantile estimates at streamgages from 181 watersheds including the 117 study watersheds and 64 additional watersheds in the study region that were originally considered for use in the study but later deemed to be redundant. The urbanization-adjustment equations, spatial regression equations, and peak discharge quantile estimates developed in this study will be made available in the web-based application StreamStats, which provides automated regression-equation solutions for user-selected stream locations. Figures and tables comparing the observed and urbanization-adjusted peak discharge records by streamgage are provided at http://dx.doi.org/10.3133/sir20165050 for download.
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