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11	INFERENCE FOR ONE-SHOT DEVICE TESTING DATA Ling, Man Ho 10 1900 (has links) <p>In this thesis, inferential methods for one-shot device testing data from accelerated life-test are developed. Due to constraints on time and budget, accelerated life-tests are commonly used to induce more failures within a reasonable amount of test-time for obtaining more lifetime information that will be especially useful in reliability analysis. One-shot devices, which can be used only once as they get destroyed immediately after testing, yield observations only on their condition and not on their real lifetimes. So, only binary response data are observed from an one-shot device testing experiment. Since no failure times of units are observed, we use the EM algorithm for determining the maximum likelihood estimates of the model parameters. Also, inference for the reliability at a mission time and the mean lifetime at normal operating conditions are also developed.</p> <p>The thesis proceeds as follows. Chapter 2 considers the exponential distribution with single-stress relationship and develops inferential methods for the model parameters, the reliability and the mean lifetime. The results obtained by the EM algorithm are compared with those obtained from the Bayesian approach. A one-shot device testing data is analyzed by the proposed method and presented as an illustrative example. Next, in Chapter 3, the exponential distribution with multiple-stress relationship is considered and corresponding inferential results are developed. Jackknife technique is described for the bias reduction in the developed estimates. Interval estimation for the reliability and the mean lifetime are also discussed based on observed information matrix, jackknife technique, parametric bootstrap method, and transformation technique. Again, we present an example to illustrate all the inferential methods developed in this chapter. Chapter 4 considers the point and interval estimation for the one-shot device testing data under the Weibull distribution with multiple-stress relationship and illustrates the application of the proposed methods in a study involving the development of tumors in mice with respect to risk factors such as sex, strain of offspring, and dose effects of benzidine dihydrochloride. A Monte Carlo simulation study is also carried out to evaluate the performance of the EM estimates for different levels of reliability and different sample sizes. Chapter 5 describes a general algorithm for the determination of the optimal design of an accelerated life-test plan for one-shot device testing experiment. It is based on the asymptotic variance of the estimated reliability at a specific mission time. A numerical example is presented to illustrate the application of the algorithm. Finally, Chapter 6 presents some concluding remarks and some additional research problems that would be of interest for further study.</p> / Doctor of Philosophy (PhD) One-shot device testing accelerated life-test EM algorithm optimal test plan exponential distribution weibull distribution Biostatistics Design of Experiments and Sample Surveys Statistical Models Survival Analysis Biostatistics
12	Statistical Improvements for Ecological Learning about Spatial Processes Dupont, Gaetan L 20 October 2021 (has links) (PDF) Ecological inquiry is rooted fundamentally in understanding population abundance, both to develop theory and improve conservation outcomes. Despite this importance, estimating abundance is difficult due to the imperfect detection of individuals in a sample population. Further, accounting for space can provide more biologically realistic inference, shifting the focus from abundance to density and encouraging the exploration of spatial processes. To address these challenges, Spatial Capture-Recapture (“SCR”) has emerged as the most prominent method for estimating density reliably. The SCR model is conceptually straightforward: it combines a spatial model of detection with a point process model of the spatial distribution of individuals, using data collected on individuals within a spatially referenced sampling design. These data are often coarse in spatial and temporal resolution, though, motivating research into improving the quality of the data available for analysis. Here I explore two related approaches to improve inference from SCR: sampling design and data integration. Chapter 1 describes the context of this thesis in more detail. Chapter 2 presents a framework to improve sampling design for SCR through the development of an algorithmic optimization approach. Compared to pre-existing recommendations, these optimized designs perform just as well but with far more flexibility to account for available resources and challenging sampling scenarios. Chapter 3 presents one of the first methods of integrating an explicit movement model into the SCR model using telemetry data, which provides information at a much finer spatial scale. The integrated model shows significant improvements over the standard model to achieve a specific inferential objective, in this case: the estimation of landscape connectivity. In Chapter 4, I close by providing two broader conclusions about developing statistical methods for ecological inference. First, simulation-based evaluation is integral to this process, but the circularity of its use can, unfortunately, be understated. Second, and often underappreciated: statistical solutions should be as intuitive as possible to facilitate their adoption by a diverse pool of potential users. These novel approaches to sampling design and data integration represent essential steps in advancing SCR and offer intuitive opportunities to advance ecological learning about spatial processes. Spatial capture-recapture population density spatial sampling optimal design data integration animal movement Applied Statistics Design of Experiments and Sample Surveys Natural Resources and Conservation Population Biology Statistical Models
13	Snap Scholar: The User Experience of Engaging with Academic Research Through a Tappable Stories Medium Burk, Ieva 01 January 2019 (has links) With the shift to learn and consume information through our mobile devices, most academic research is still only presented in long-form text. The Stanford Scholar Initiative has explored the segment of content creation and consumption of academic research through video. However, there has been another popular shift in presenting information from various social media platforms and media outlets in the past few years. Snapchat and Instagram have introduced the concept of tappable “Stories” that have gained popularity in the realm of content consumption. To accelerate the growth of the creation of these research talks, I propose an alternative to video: a tappable Snapchat-like interface. This style is achieved using AMP, Google’s open source project to optimize web experiences on mobile, and particularly the AMP Stories visual medium. My research seeks to explore how the process and quality of consuming the content of academic papers would change if instead of watching videos, users would consume content through Stories on mobile instead. Since this form of content consumption is still largely unresearched in the academic context, I approached this research with a human-centered design process, going through a few iterations to test various prototypes before formulating research questions and designing an experiment. I tested various formats of research consumption through Stories with pilot users, and learned many lessons to iterate from along the way. I created a way to consume research papers in a Stories format, and designed a comparative study to measure the effectiveness of consuming research papers through the Stories medium and the video medium. The results indicate that Stories are a quicker way to consume the same content, and improve the user’s pace of comprehension. Further, the Stories medium provides the user a self-paced method—both temporally and content-wise—to consume technical research topics, and is deemed as a less boring method to do so in comparison to video. While Stories gave the learner a chance to actively participate in consumption by tapping, the video experience is enjoyed because of its reduced effort and addition of an audio component. These findings suggest that the Stories medium may be a promising interface in educational contexts, for distributing scientific content and assisting with active learning. HCI Stories Video User experience Academic papers Snapchat Applied Statistics Artificial Intelligence and Robotics Categorical Data Analysis Design of Experiments and Sample Surveys Graphics and Human Computer Interfaces Other Computer Sciences Probability Software Engineering
14	Niche-Based Modeling of Japanese Stiltgrass (Microstegium vimineum) Using Presence-Only Information Bush, Nathan 23 November 2015 (has links) The Connecticut River watershed is experiencing a rapid invasion of aggressive non-native plant species, which threaten watershed function and structure. Volunteer-based monitoring programs such as the University of Massachusetts’ OutSmart Invasives Species Project, Early Detection Distribution Mapping System (EDDMapS) and the Invasive Plant Atlas of New England (IPANE) have gathered valuable invasive plant data. These programs provide a unique opportunity for researchers to model invasive plant species utilizing citizen-sourced data. This study took advantage of these large data sources to model invasive plant distribution and to determine environmental and biophysical predictors that are most influential in dispersion, and to identify a suitable presence-only model for use by conservation biologists and land managers at varying spatial scales. This research focused on the invasive plant species of high interest - Japanese stiltgrass (Mircostegium vimineum). This was identified as a threat by U.S. Fish and Wildlife Service refuge biologists and refuge managers, but for which no mutli-scale practical and systematic approach for detection, has yet been developed. Environmental and biophysical variables include factors directly affecting species physiology and locality such as annual temperatures, growing degree days, soil pH, available water supply, elevation, closeness to hydrology and roads, and NDVI. Spatial scales selected for this study include New England (regional), the Connecticut River watershed (watershed), and the U.S. Fish and Wildlife, Silvio O. Conte National Fish and Wildlife Refuge, Salmon River Division (local). At each spatial scale, three software programs were implemented: maximum entropy habitat model by means of the MaxEnt software, ecological niche factor analysis (ENFA) using Openmodeller software, and a generalized linear model (GLM) employed in the statistical software R. Results suggest that each modeling algorithm performance varies among spatial scales. The best fit modeling software designated for each scale will be useful for refuge biologists and managers in determining where to allocate resources and what areas are prone to invasion. Utilizing the regional scale results, managers will understand what areas on a broad-scale are at risk of M. vimineum invasion under current climatic variables. The watershed-scale results will be practical for protecting areas designated as most critical for ensuring the persistence of rare and endangered species and their habitats. Furthermore, the local-scale, or fine-scale, analysis will be directly useful for on-the-ground conservation efforts. Managers and biologists can use results to direct resources to areas where M. vimineum is most likely to occur to effectively improve early detection rapid response (EDRR). Japanese stiltgrass modeling GLM ENFA Maxent GIS Biostatistics Design of Experiments and Sample Surveys Natural Resources and Conservation Natural Resources Management and Policy Other Statistics and Probability Probability Statistical Methodology Statistical Models Statistical Theory
15	Statistical Designs for Network A/B Testing Pokhilko, Victoria V 01 January 2019 (has links) A/B testing refers to the statistical procedure of experimental design and analysis to compare two treatments, A and B, applied to different testing subjects. It is widely used by technology companies such as Facebook, LinkedIn, and Netflix, to compare different algorithms, web-designs, and other online products and services. The subjects participating in these online A/B testing experiments are users who are connected in different scales of social networks. Two connected subjects are similar in terms of their social behaviors, education and financial background, and other demographic aspects. Hence, it is only natural to assume that their reactions to online products and services are related to their network adjacency. In this research, we propose to use the conditional autoregressive model (CAR) to present the network structure and include the network effects in the estimation and inference of the treatment effect. The following statistical designs are presented: D-optimal design for network A/B testing, a re-randomization experimental design approach for network A/B testing and covariate-assisted Bayesian sequential design for network A/B testing. The effectiveness of the proposed methods are shown through numerical results with synthetic networks and real social networks. A/B testing Conditional auto-regressive model D-optimal design Mixed integer programming Social network Re-randomization Applied Statistics Design of Experiments and Sample Surveys Statistical Methodology Statistical Models Statistical Theory Statistics and Probability
16	Behavior and Habitat Use of Roseate Terns (Sterna dougallii) Before and After Construction of an Erosion Control Revetment Grinnell, Corey 01 January 2010 (has links) (PDF) An erosion control revetment was constructed at the Falkner Island Unit of the Stewart B. McKinney National Wildlife Refuge, Connecticut during the winter of 2000–2001. At the time, Falkner Island was the fifth largest breeding colony site for the federally endangered Roseate Tern. This study measures and describes some baseline information regarding Roseate Tern nesting, behavior, and habitat use at Falkner Island during the three breeding seasons prior to revetment construction (1998–2000). This baseline information is then compared to similar information from the first breeding season following revetment construction (2001). For Roseate Tern adults, this study examined changes in pre-nesting habitat use, nest site distributions, and pre-nesting behavioral time allocation. Changes in habitat availability and habitat use by Roseate Terns are compared as a result of the revetment construction. Roseate Terns used rocky beach in a greater proportion than other habitats before revetment construction, and used revetment boulders in a greater proportion than all other habitats after revetment construction. Roseate Terns nested more often in artificial sites (nest boxes and tires) than in natural sites in all years of the study. The mean date for the first eggs in each nest did not differ between years. We observed more Roseate Terns prospecting artificial nest sites (n = 66 times) than natural sites (n = 21 times) for three years of this study. Prospecting behavior occurred later in the season in some subcolonies, but this difference did not appear to be related to the construction. For Roseate Tern chicks, this study investigated the use of crevices as hiding places from before (1999–2000) and after (2001) the construction of an erosion control revetment. In all years, Roseate Tern chicks used crevices found under artificial nest sites more frequently than expected by chance when compared to crevices found in other microhabitats. Chicks also used crevices formed in various microhabitat types at different stages of development. The erosion control revetment created crevices that had larger openings, steeper floors, and deeper lengths than those previously used by chicks before construction. In the year after revetment construction, the openings of crevices used by chicks that died were wider than crevices used by chicks that survived. We discuss our findings in the context of the potential consequences that the revetment construction had on Roseate Tern chick survival. Roseate Tern Sterna dougalli revetment habitat use behvaior endangered species Biology Biology Biometry Design of Experiments and Sample Surveys Natural Resources and Conservation Natural Resources Management and Policy Other Life Sciences
17	Nutrition, Childhood Development and Prevalence of Anemia in Ghanaian Children: Analysis of Health Survey Ewusie, Joycelyne E. 04 1900 (has links) <p>Malnutrition and Anemia in children continue to be major public health challenges in most developing countries, particularly in Africa. Malnutrition and Anemia pervade all aspects of their health, growth, cognitive and social development. They lead to irreversible and lifelong effects that prevent children from realising their full potential. This study was designed to examine the prevalence and determinants of malnutrition and anemia in children under 5 years of age in the Ghanaian population. This research is based on data from the Ghana Demographic and Health Survey (GDHS) 2008, obtained from the Ghana Statistical Service (GSS). The survey is an extensive survey conducted using a stratified, two-stage cluster sampling design. The GDHS data contains a wealth of information on health, demographic, as well as socio-economic factors but is underutilised due to the complexity of the survey data. This study therefore stands out as one of the few that use the GDHS to investigate aspects of child health in Ghana. In this study, we perform subgroup analysis by disaggregating the data by age and gender specific subgroups and then by place of residence and region. This was in order to identify sub level estimates as national estimates have a high tendency of concealing true values and deviations from general trends. Also, subgroup analysis is very significant especially for resource allocation so as to minimize the likelihood of missing the target populations. We investigated associations between the three measurements of malnutrition; stunting, underweight and wasting and anemia (assessed by haemoglobin concentration) and the various risk factors using chi-square test to examine bivariate associations and chi-square trend test to examine linear trends in association. We identified the following variables to be significantly associated with all forms of malnutrition and/or anemia: age of child, mother’s education, financial status and place of residence. Other factors that were identified to be associated with some form of malnutrition and/or anemia include duration of breastfeeding, source of drinking water, mother’s occupation and currently breastfeeding. In view of the high rate of malnutrition, approximately 36% (33.6−37.6) and the alarming prevalence of anemia, 78% (76.7 − 80.2) in children in Ghana, particularly among those less than 2 years old, and the grave consequences on their cognitive and behavioral development even in later years, there is an urgent need for effective and efficient public health interventions.</p> / Master of Science (MSc) Malnutrition Stunting Underweight Wasting Anemia Risk factors Children Applied Statistics Biostatistics Design of Experiments and Sample Surveys International Public Health Maternal and Child Health Public Health Education and Promotion Vital and Health Statistics Applied Statistics
18	Combined Computational-Experimental Design of High-Temperature, High-Intensity Permanent Magnetic Alloys with Minimal Addition of Rare-Earth Elements Jha, Rajesh 20 May 2016 (has links) AlNiCo magnets are known for high-temperature stability and superior corrosion resistance and have been widely used for various applications. Reported magnetic energy density ((BH) max) for these magnets is around 10 MGOe. Theoretical calculations show that ((BH) max) of 20 MGOe is achievable which will be helpful in covering the gap between AlNiCo and Rare-Earth Elements (REE) based magnets. An extended family of AlNiCo alloys was studied in this dissertation that consists of eight elements, and hence it is important to determine composition-property relationship between each of the alloying elements and their influence on the bulk properties. In the present research, we proposed a novel approach to efficiently use a set of computational tools based on several concepts of artificial intelligence to address a complex problem of design and optimization of high temperature REE-free magnetic alloys. A multi-dimensional random number generation algorithm was used to generate the initial set of chemical concentrations. These alloys were then examined for phase equilibria and associated magnetic properties as a screening tool to form the initial set of alloy. These alloys were manufactured and tested for desired properties. These properties were fitted with a set of multi-dimensional response surfaces and the most accurate meta-models were chosen for prediction. These properties were simultaneously extremized by utilizing a set of multi-objective optimization algorithm. This provided a set of concentrations of each of the alloying elements for optimized properties. A few of the best predicted Pareto-optimal alloy compositions were then manufactured and tested to evaluate the predicted properties. These alloys were then added to the existing data set and used to improve the accuracy of meta-models. The multi-objective optimizer then used the new meta-models to find a new set of improved Pareto-optimized chemical concentrations. This design cycle was repeated twelve times in this work. Several of these Pareto-optimized alloys outperformed most of the candidate alloys on most of the objectives. Unsupervised learning methods such as Principal Component Analysis (PCA) and Heirarchical Cluster Analysis (HCA) were used to discover various patterns within the dataset. This proves the efficacy of the combined meta-modeling and experimental approach in design optimization of magnetic alloys. AlNiCo magnets Data-driven Materials Science Composition-property relationship Materials Genome Initiative (MGI-ICME) Meta-model (Response Surfaces) Evolutionary (Genetic) Algorithms Multi-objective Optimization Pareto Optimality Principal Component Analysis (PCA) Heirarchichal Clustering Analysis (HCA) Categorical Data Analysis Design of Experiments and Sample Surveys Metallurgy Other Materials Science and Engineering Statistical Methodology Theory and Algorithms
19	THE RELATIONSHIP BETWEEN SELF-DETERMINATION AND CLIENT OUTCOMES AMONG THE HOMELESS Hanna, Samuel M. 01 June 2015 (has links) This paper has attempted to determine if there is a significant relationship between self-determination and client outcomes among the homeless. The study has been based upon the conceptual framework set forth in Self-Determination Theory. The purpose of the study was to explore the relationship between self-determination and client outcomes among the homeless. Using a data collection instrument, based on empirically validated instrumentation, clients from several homeless service providers in the City of San Bernardino were assessed for the level of self-determination and autonomy support they experience within these agencies. Outcome measures included such things as whether the client was going to school, had a job and had a bank account. Overall, the results of the study were inconclusive, though some interesting post hoc observations were made. It was the primary aim of this paper to increase the knowledge base of the local network of homeless service providers and to promote the compassionate, equitable, and dignified treatment of the population they serve. Homelessness Social Work Self Determination Theory Outcomes Survey Chi Square Cognition and Perception Community-Based Learning Community-Based Research Design of Experiments and Sample Surveys Housing Law Legal Studies Mental and Social Health Other Social and Behavioral Sciences Other Statistics and Probability Personality and Social Contexts Place and Environment Privacy Law Probability Property Law and Real Estate Public Health Public Law and Legal Theory Social and Behavioral Sciences Social Psychology Social Welfare Social Work Statistics and Probability Substance Abuse and Addiction Theory and Philosophy
20	The Effects of the Use of Technology In Mathematics Instruction on Student Achievement Myers, Ron Y 30 March 2009 (has links) The purpose of this study was to examine the effects of the use of technology on students’ mathematics achievement, particularly the Florida Comprehensive Assessment Test (FCAT) mathematics results. Eleven schools within the Miami-Dade County Public School System participated in a pilot program on the use of Geometers Sketchpad (GSP). Three of these schools were randomly selected for this study. Each school sent a teacher to a summer in-service training program on how to use GSP to teach geometry. In each school, the GSP class and a traditional geometry class taught by the same teacher were the study participants. Students’ mathematics FCAT results were examined to determine if the GSP produced any effects. Students’ scores were compared based on assignment to the control or experimental group as well as gender and SES. SES measurements were based on whether students qualified for free lunch. The findings of the study revealed a significant difference in the FCAT mathematics scores of students who were taught geometry using GSP compared to those who used the traditional method. No significant differences existed between the FCAT mathematics scores of the students based on SES. Similarly, no significant differences existed between the FCAT scores based on gender. In conclusion, the use of technology (particularly GSP) is likely to boost students’ FCAT mathematics test scores. The findings also show that the use of GSP may be able to close known gender and SES related achievement gaps. The results of this study promote policy changes in the way geometry is taught to 10th grade students in Florida’s public schools. Mathematics Technology Acheivement Gender SES Geometer's Sketchpad (GSP) Geometry Manova Acheivement gap Minority Algebra Algebraic Geometry Analysis Categorical Data Analysis Curriculum and Instruction Demography, Population, and Ecology Design of Experiments and Sample Surveys Disability and Equity in Education Education Educational Psychology Gender and Sexuality Geometry and Topology Inequality and Stratification Mathematics Other Education Other Mathematics Other Physical Sciences and Mathematics Other Sociology Other Statistics and Probability Physical Sciences and Mathematics Probability Race and Ethnicity Science and Mathematics Education Science and Technology Studies Service Learning Social and Behavioral Sciences Social Psychology and Interaction Sociology Statistical Models Statistical Theory Statistics and Probability

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