944 resultados para Non-linear multiple regression


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This study offers an analytical approach in order to provide a determination of the temperature field developed during the DC TIG welding of a thin plate of aluminum. The non-linear characteristics of the phenomenon, such as the dependence of the thermophysical and mechanical properties with temperature were considered in this study. In addition to the conductive heat exchange process, were taken into account the exchange by natural convection and radiation. A transient analysis is performed in order to obtain the temperature field as a function of time. It is also discussed a three-dimensional modeling of the heat source. The results obtained from the analytical model were be compared with the experimental ones and those available in the literature. The analytical results show a good correlation with the experimental ones available in the literature, thus proving the feasibility and efficiency of the analytical method for the simulation of the heat cycle for this welding process.

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This research explores Bayesian updating as a tool for estimating parameters probabilistically by dynamic analysis of data sequences. Two distinct Bayesian updating methodologies are assessed. The first approach focuses on Bayesian updating of failure rates for primary events in fault trees. A Poisson Exponentially Moving Average (PEWMA) model is implemnented to carry out Bayesian updating of failure rates for individual primary events in the fault tree. To provide a basis for testing of the PEWMA model, a fault tree is developed based on the Texas City Refinery incident which occurred in 2005. A qualitative fault tree analysis is then carried out to obtain a logical expression for the top event. A dynamic Fault Tree analysis is carried out by evaluating the top event probability at each Bayesian updating step by Monte Carlo sampling from posterior failure rate distributions. It is demonstrated that PEWMA modeling is advantageous over conventional conjugate Poisson-Gamma updating techniques when failure data is collected over long time spans. The second approach focuses on Bayesian updating of parameters in non-linear forward models. Specifically, the technique is applied to the hydrocarbon material balance equation. In order to test the accuracy of the implemented Bayesian updating models, a synthetic data set is developed using the Eclipse reservoir simulator. Both structured grid and MCMC sampling based solution techniques are implemented and are shown to model the synthetic data set with good accuracy. Furthermore, a graphical analysis shows that the implemented MCMC model displays good convergence properties. A case study demonstrates that Likelihood variance affects the rate at which the posterior assimilates information from the measured data sequence. Error in the measured data significantly affects the accuracy of the posterior parameter distributions. Increasing the likelihood variance mitigates random measurement errors, but casuses the overall variance of the posterior to increase. Bayesian updating is shown to be advantageous over deterministic regression techniques as it allows for incorporation of prior belief and full modeling uncertainty over the parameter ranges. As such, the Bayesian approach to estimation of parameters in the material balance equation shows utility for incorporation into reservoir engineering workflows.

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The known moss flora of Terra Nova National Park, eastern Newfoundland, comp~ises 210 species. Eighty-two percent of the moss species occurring in Terra Nova are widespread or widespread-sporadic in Newfoundland. Other Newfoundland distributional elements present in the Terra Nova moss flora are the northwestern, southern, southeastern, and disjunct elements, but four of the mosses occurring in Terra Nova appear to belong to a previously unrecognized northeastern element of the Newfoundland flora. The majority (70.9%) of Terra Nova's mosses are of boreal affinity and are widely distributed in the North American coniferous forest belt. An additional 10.5 percent of the Terra Nova mosses are cosmopolitan while 9.5 percent are temperate and 4.8 percent are arctic-montane species. The remaining 4.3 percent of the mosses are of montane affinity, and disjunct between eastern and western North America. In Terra Nova, temperate species at their northern limit are concentrated in balsam fir stands, while arctic-montane species are restricted to exposed cliffs, scree slopes, and coastal exposures. Montane species are largely confined to exposed or freshwater habitats. Inability to tolerate high summer temperatures limits the distributions of both arctic-montane and montane species. In Terra Nova, species of differing phytogeographic affinities co-occur on cliffs and scree slopes. The microhabitat relationships of five selected species from such habitats were evaluated by Discriminant Functions Analysis and Multiple Regression Analysis. The five mosses have distinct and different microhabitats on cliffs and scree slopes in Terra Nova, and abundance of all but one is associated with variation in at least one microhabitat variable. Micro-distribution of Grimmia torquata, an arctic-montane species at its southern limit, appears to be deterJ]lined by sensitivity to high summer temperatures. Both southern mosses at their northern limit (Aulacomnium androgynum, Isothecium myosuroides) appear to be limited by water availability and, possibly, by low winter temperatures. The two species whose distributions extend both north and south or the study area (Encalypta procera, Eurhynchium pulchellum) show no clear relationship with microclimate. Dispersal factors have played a significant role in the development of the Terra Nova moss flora. Compared to the most likely colonizing source (i .e. the rest of the island of Newfoundland), species with small diaspores have colonized the study area to a proportionately much greater extent than have species with large diaspores. Hierarchical log-linear analysis indicates that this is so for all affinity groups present in Terra Nova. The apparent dispersal effects emphasize the comparatively recent glaciation of the area, and may also have been enhanced by anthropogenic influences. The restriction of some species to specific habitats, or to narrowly defined microhabitats, appears to strengthen selection for easily dispersed taxa.

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Large scale disasters, such as the one caused by the Typhoon Haiyan, which devastated portions of the Philippines in 2013, or the catastrophic 2010 Haiti earthquake, which caused major damage in Port-au-Prince and other settlements in the region, have massive and lasting effects on populations. Nowadays, disasters can be considered as a consequence of inappropriately managed risk. These risks are the product of hazards and vulnerability, which refers to the extent to which a community can be affected by the impact of a hazard. In this way, developing countries, due to their greater vulnerability, suffer the highest costs when a disaster occurs. Disaster relief is a challenge for politics, economies, and societies worldwide. Humanitarian organizations face multiple decision problems when responding to disasters. In particular, once a disaster strikes, the distribution of humanitarian aid to the population affected is one of the most fundamental operations in what is called humanitarian logistics. This term is defined as the process of planning, implementing and controlling the effcient, cost-effective ow and storage of goods and materials as well as related information, from the point of origin to the point of consumption, for the purpose of meeting the end bene- ciaries' requirements and alleviate the suffering of vulnerable people, [the Humanitarian Logistics Conference, 2004 (Fritz Institute)]. During the last decade there has been an increasing interest in the OR/MS community in studying this topic, pointing out the similarities and differences between humanitarian and business logistics, and developing models suited to handle the special characteristics of these problems. Several authors have pointed out that traditional logistic objectives, such as minimizing operation cost, are not the most relevant goals in humanitarian operations. Other factors, such as the time of operation, or the design of safe and equitable distribution plans, come to the front, and new models and algorithms are needed to cope with these special features. Up to six attributes related to the distribution plan are considered in our multi-criteria approach. Even though there are usually simple ways to measure the cost of an operation, the evaluation of some other attributes such as security or equity is not easy. As a result, several attribute measures are proposed and developed, focusing on different aspects of the solutions. Furthermore, when metaheuristic solution methods are used, considering non linear objective functions does not increase the complexity of the algorithms significantly, and thus more accurate measures can be utilized...

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Background: Internationally, tests of general mental ability are used in the selection of medical students. Examples include the Medical College Admission Test, Undergraduate Medicine and Health Sciences Admission Test and the UK Clinical Aptitude Test. The most widely used measure of their efficacy is predictive validity.A new tool, the Health Professions Admission Test- Ireland (HPAT-Ireland), was introduced in 2009. Traditionally, selection to Irish undergraduate medical schools relied on academic achievement. Since 2009, Irish and EU applicants are selected on a combination of their secondary school academic record (measured predominately by the Leaving Certificate Examination) and HPAT-Ireland score. This is the first study to report on the predictive validity of the HPAT-Ireland for early undergraduate assessments of communication and clinical skills. Method. Students enrolled at two Irish medical schools in 2009 were followed up for two years. Data collected were gender, HPAT-Ireland total and subsection scores; Leaving Certificate Examination plus HPAT-Ireland combined score, Year 1 Objective Structured Clinical Examination (OSCE) scores (Total score, communication and clinical subtest scores), Year 1 Multiple Choice Questions and Year 2 OSCE and subset scores. We report descriptive statistics, Pearson correlation coefficients and Multiple linear regression models. Results: Data were available for 312 students. In Year 1 none of the selection criteria were significantly related to student OSCE performance. The Leaving Certificate Examination and Leaving Certificate plus HPAT-Ireland combined scores correlated with MCQ marks.In Year 2 a series of significant correlations emerged between the HPAT-Ireland and subsections thereof with OSCE Communication Z-scores; OSCE Clinical Z-scores; and Total OSCE Z-scores. However on multiple regression only the relationship between Total OSCE Score and the Total HPAT-Ireland score remained significant; albeit the predictive power was modest. Conclusion: We found that none of our selection criteria strongly predict clinical and communication skills. The HPAT- Ireland appears to measures ability in domains different to those assessed by the Leaving Certificate Examination. While some significant associations did emerge in Year 2 between HPAT Ireland and total OSCE scores further evaluation is required to establish if this pattern continues during the senior years of the medical course.

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Objective. The prevalence of smoking in Aboriginal Canadians is higher than non-Aboriginal Canadians, a behavior that also tends to alter dietary patterns. Compared with the general Canadian population, maternal smoking rates are almost twice as high. The aim of this study was to compare dietary adequacy of Inuvialuit women of childbearing age comparing smokers versus non-smokers. Research methods & procedures. A cross-sectional study, where participants completed a culturally specific quantitative food frequency questionnaire. Non-parametric analysis was used to compare mean nutrient intake, dietary inadequacy and differences in nutrient density among smokers and non-smokers. Multiple logistic regression analyses were performed for key nutrients inadequacy and smoking status. Data was collected from three communities in the Beaufort Delta region of the Northwest Territories, Canada from randomly selected Inuvialuit women of childbearing age (19-44 years). Results: Of 92 participants, 75% reported being smokers. There were no significant differences in age, BMI, marital status, education, number of people in household working and/or number of self employed, and physical activity between smokers and non-smokers. Non-parametric analysis showed no differences in nutrient intake between smokers and non-smokers. Logistic regression however revealed there was a positive association between smoking and inadequacies of vitamin C (OR = 2.91, 95% CI, 1.17-5.25), iron (OR = 3.16, 95% CI, 1.27-5.90), and zinc (OR = 2.78, 95% CI, 1.12-4.94). A high percentage of women (>60%), regardless of smoking status, did not meet the dietary recommendations for fiber, vitamin D, E and potassium. Conclusions: This study provides evidence of inadequate dietary intake among Inuvialuit of childbearing age regardless of smoking behavior.

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Objectives: To explore socioeconomic differences in four cardiovascular disease risk factors (overweight/obesity, smoking, hypertension, height) among manufacturing employees in the Republic of Ireland (ROI). Methods: Cross-sectional analysis of 850 manufacturing employees aged 18–64 years. Education and job position served as socioeconomic indicators. Group-specific differences in prevalence were assessed with the Chi-squared test. Multivariate regression models were explored if education and job position were independent predictors of the CVD risk factors. Cochran–Armitage test for trend was used to assess the presence of a social gradient. Results: A social gradient was found across educational levels for smoking and height. Employees with the highest education were less likely to smoke compared to the least educated employees (OR 0.2, [95% CI 0.1–0.4]; p b 0.001). Lower educational attainment was associated with a reduction in mean height. Non-linear differences were found in both educational level and job position for obesity/overweight. Managers were more than twice as likely to be overweight or obese relative to those employees in the lowest job position (OR 2.4 [95% CI 1.3–4.6]; p = 0.008). Conclusion: Socioeconomic inequalities in height, smoking and overweight/obesity were highlighted within a sub-section of the working population in ROI.

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Background: Academic integrity (AI) has been defined as the commitment to the values of honesty, trust, fairness, respect, and responsibility with courage in all academic endeavours. The senior years of nursing studies provide an intersection for students to transition to professional roles through student clinical practice. It is essential to understand what predicts senior nursing students’ intention to behave with AI so that efforts can be directed to initiatives focused on strengthening their commitment to behaving with AI. Research Questions: To what extent do students differ on Theory of Planned Behaviour (TPB) variables? What predicts intention to behave with academic integrity among senior nursing students in clinical practice across three different Canadian Schools of Nursing? Method: The TPB framework, an elicitation (n=30) and two pilot studies (n=59, n=29) resulted in the development of a 38 question (41-item) self-report survey (Miron Academic Integrity Nursing Survey—MAINS: α>0.70) that was administered to Year 3 and 4 students (N=339). Three predictor variables (attitude, subjective norm, perceived behavioural control) were measured with students’ intention to behave with AI in clinical. Age, sex, year of study, program stream, students’ understanding of AI policies, and locations where students accessed AI information were also measured. Results: Hierarchical multiple regression analyses revealed that background, site, and TPB variables explained 32.6% of the variance in intention to behave with academic integrity. The TPB variables explained 26.8% of the variance in intention after controlling for background and site variables. In the final model, only the TPB predictor variables were statistically significant with Attitude having the highest beta value (beta=0.35, p<0.001), followed by Subjective Norm (beta=0.21, p<0.001) and Perceived Behavioural Control (beta=0.12, p<0.02). Conclusion: Student attitude is the strongest predictor to intention to behave with AI in clinical practice and efforts to positively influence students’ attitudes need to be a focus for schools, curricula, and clinical educators. Opportunities for future research should include replicating the current study with students enrolled in other professional programs and intervention studies that examine the effectiveness of specific endeavours to promote AI in practice.

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Metacognition is the understanding and control of cognitive processes. Students with high levels of metacognition achieve greater academic success. The purpose of this mixed-methods study was to examine elementary teachers’ beliefs about metacognition and integration of metacognitive practices in science. Forty-four teachers were recruited through professional networks to complete a questionnaire containing open-ended questions (n = 44) and Likert-type items (n = 41). Five respondents were selected to complete semi-structured interviews informed by the questionnaire. The selected interview participants had a minimum of three years teaching experience and demonstrated a conceptual understanding of metacognition. Statistical tests (Pearson correlation, t-tests, and multiple regression) on quantitative data and thematic analysis of qualitative data indicated that teachers largely understood metacognition but had some gaps in their understanding. Participants’ reported actions (teaching practices) and beliefs differed according to their years of experience but not gender. Hierarchical multiple regression demonstrated that the first block of gender and experience was not a significant predictor of teachers' metacognitive actions, although experience was a significant predictor by itself. Experience was not a significant predictor once teachers' beliefs were added. The majority of participants indicated that metacognition was indeed appropriate for elementary students. Participants consistently reiterated that students’ metacognition developed with practice, but required explicit instruction. A lack of consensus remained around the domain specificity of metacognition. More specifically, the majority of questionnaire respondents indicated that metacognitive strategies could not be used across subject domains, whereas all interviewees indicated that they used strategies across subjects. Metacognition was integrated frequently into Ontario elementary classrooms; however, metacognition was integrated less frequently in science lessons. Lastly, participants used a variety of techniques to integrate metacognition into their classrooms. Implications for practice include the need for more professional development aimed at integrating metacognition into science lessons at both the Primary and Junior levels. Further, teachers could benefit from additional clarification on the three main components of metacognition and the need to integrate all three to successfully develop students’ metacognition.

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In this work I study the optical properties of helical particles and chiral sculptured thin films, using computational modeling (discrete dipole approximation, Berreman calculus), and experimental techniques (glancing angle deposition, ellipsometry, scatterometry, and non-linear optical measurements). The first part of this work focuses on linear optics, namely light scattering from helical microparticles. I study the influence of structural parameters and orientation on the optical properties of particles: circular dichroism (CD) and optical rotation (OR), and show that as a consequence of random orientation, CD and OR can have the opposite sign, compared to that of the oriented particle, potentially resulting in ambiguity of measurement interpretation. Additionally, particles in random orientation scatter light with circular and elliptical polarization states, which implies that in order to study multiple scattering from randomly oriented chiral particles, the polarization state of light cannot be disregarded. To perform experiments and attempt to produce particles, a newly constructed multi stage thin film coating chamber is calibrated. It enables the simultaneous fabrication of multiple sculptured thin film coatings, each with different structure. With it I successfully produce helical thin film coatings with Ti and TiO_{2}. The second part of this work focuses on non-linear optics, with special emphasis on second-harmonic generation. The scientific literature shows extensive experimental and theoretical work on second harmonic generation from chiral thin films. Such films are expected to always show this non-linear effect, due to their lack of inversion symmetry. However no experimental studies report non-linear response of chiral sculptured thin films. In this work I grow films suitable for a second harmonic generation experiment, and report the first measurements of non-linear response.

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Existential loneliness is a concept that is largely ignored in the psychological research tradition, although from a philosophical perspective it is deeply connected to inherent human longings of connection and meaning. This research investigated the relationship between existential loneliness and two variables that are theoretically closely related to the concepts of connection and meaning, namely mindfulness (connection to oneself and others) and spiritual well-being (connection to a larger whole). This was done in a sample of n = 180 individuals (61.7% female; mean age 41.72, SD = 12.16) of the Dutch population. A multiple regression analysis was conducted. It can be concluded that there is a negative relationship between mindfulness and existential loneliness, as well as between spiritual well-being and existential loneliness. This means that people with a higher level of mindfulness and/or a higher level of spiritual well-being experience a lower level of existential loneliness. At the same time, people with a lower level of mindfulness and/or spiritual well-being experience a lower level of existential loneliness. There are some limitations to this study, for example the use of a non-random sampling method, a limited sample group, a scale that has not been widely tested, and a potential bias towards the higher educated. However, these limitations are inherent to exploratory research and does not diminish the main strength of this thesis, namely that it has provided more insight into an important and prevalent societal phenomenon, that had not been extensively researched previously, that has so far only been addressed in more philosophical instead of scientific debates, and linked almost exclusively to negative concepts, such as terminal illness. This research provides a first understanding of two positive determinants of existential loneliness, which could potentially be used to help make sense of this inherently humane condition, as well as to actively cope with the potential (adverse) effects of it.

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Thirty-six 12-month-old hill hoggets were used in a 2 genotype (18 Scottish Blackface vs. 18 Swaledale×Scottish Blackface)×3 diet (fresh vs. ensiled vs. pelleted ryegrass) factorial design experiment to evaluate the effects of hogget genotype and forage type on enteric methane (CH4) emissions and nitrogen (N) utilisation. The hoggets were offered 3 diets ad libitum with no concentrate supplementation in a single period study with 6 hoggets for each of the 6 genotype×diet combinations (n=6). Fresh ryegrass was harvested daily in the morning. Pelleted ryegrass was sourced from a commercial supplier (Aylescott Driers & Feeds, Burrington, UK) and the ryegrass silage was ensiled with Ecosyl (Lactobacillus plantarum, Volac International Limited, Hertfordshire, UK) as an additive. The hoggets were housed in individual pens for at least 14 d before being transferred to individual respiration chambers for a further 4 d with feed intake, faeces and urine outputs and CH4 emissions measured. There was no significant interaction between genotype and forage type on any parameter evaluated. Sheep offered pelleted grass had greater feed intake (e.g. DM, energy and N) but less energy and nutrient apparent digestibility (e.g. DM, N and neutral detergent fibre (NDF)) than those given fresh grass or grass silage (P<0.001). Feeding pelleted grass, rather than fresh grass or grass silage, reduced enteric CH4 emissions as a proportion of DM intake and gross energy (GE) intake (P<0.01). Sheep offered fresh grass had a significantly lower acid detergent fibre (ADF) apparent digestibility, and CH4 energy output (CH4-E) as a proportion of GE intake than those offered grass silage (P<0.001). There was no significant difference, in CH4 emission rate or N utilisation efficiency when compared between Scottish Blackface and Swaledale × Scottish Blackface. Linear and multiple regression techniques were used to develop relationships between CH4 emissions or N excretion and dietary and animal variables using data from sheep offered fresh ryegrass and grass silage. The equation relating CH4-E (MJ/d) to GE intake (GEI, MJ/d), energy apparent digestibility (DE/GE) and metabolisability (ME/GE) resulted in a high r2 (CH4-E=0.074 GEI+9.2 DE/GE−10.2 ME/GE−0.37, r2=0.93). N intake (NI) was the best predictor for manure N excretion (Manure N=0.66 NI+0.96, r2=0.85). The use of these relationships can potentially improve the precision and decrease the uncertainty in predicting CH4 emissions and N excretion for sheep production systems managed under the current feeding conditions.

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This work presents a computational, called MOMENTS, code developed to be used in process control to determine a characteristic transfer function to industrial units when radiotracer techniques were been applied to study the unit´s performance. The methodology is based on the measuring the residence time distribution function (RTD) and calculate the first and second temporal moments of the tracer data obtained by two scintillators detectors NaI positioned to register a complete tracer movement inside the unit. Non linear regression technique has been used to fit various mathematical models and a statistical test was used to select the best result to the transfer function. Using the code MOMENTS, twelve different models can be used to fit a curve and calculate technical parameters to the unit.

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Thesis (Ph.D.)--University of Washington, 2016-07

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Empirical evidence has demonstrated the benefits of using simulation games in enhancing learning especially in terms of cognitive gains. This is to be expected as the dynamism and non-linearity of simulation games are more cognitively demanding. However, the other effects of simulation games, specifically in terms of learners’ emotions, have not been given much attention and are under-investigated. This study aims to demonstrate that simulation games stimulate positive emotions from learners that help to enhance learning. The study finds that the affect-based constructs of interest, engagement and appreciation are positively correlated to learning. A stepwise multiple regression analysis shows that a model involving interest and engagement are significantly associated with learning. The emotions of learners should be considered in the development of curriculum, and the delivery of learning and teaching as positive emotions enhances learning.