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91	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
92	Determinants of Health Care Use Among Rural, Low-Income Mothers and Children: A Simultaneous Systems Approach to Negative Binomial Regression Modeling Valluri, Swetha 01 January 2011 (has links) (PDF) The determinants of health care use among rural, low-income mothers and their children were assessed using a multi-state, longitudinal data set, Rural Families Speak. The results indicate that rural mothers’ decisions regarding health care utilization for themselves and for their child can be best modeled using a simultaneous systems approach to negative binomial regression. Mothers’ visits to a health care provider increased with higher self-assessed depression scores, increased number of child’s doctor visits, greater numbers of total children in the household, greater numbers of chronic conditions, need for prenatal or post-partum care, development of a new medical condition, and having health insurance (Medicaid/equivalent and HMO/private). Child’s visits to a health care provider, on the other hand, increased with greater numbers of chronic conditions, development of a new medical condition, and increased mothers’ visits to a doctor. Child’s utilization of pediatric health care services decreased with higher levels of maternal depression, greater numbers of total children in the household, if the mother had HMO/private health care coverage, if the mother was pregnant, and if the mother was Latina/African American. Mother’s use of health care services decreased with her age, increased number of child’s chronic conditions, income as a percent of the federal poverty line, and if child had HMO/private health care insurance. The study expands the econometric techniques available for assessing maternal and pediatric health care use and the results contribute to an understanding of how rural, low-income mothers choose the level of health care services use for themselves and for their child. Additionally, the results would assist in formulating policies to reorient the type of health care services provided to this vulnerable population. Rural mothers maternal health care utilization pediatric health care utilization simultaneous systems negative binomial regression Rural Families Speak Applied Statistics Categorical Data Analysis Econometrics Health Economics Health Policy Other Mental and Social Health Other Public Health Other Statistics and Probability Programming Languages and Compilers Statistical Methodology Statistical Theory
93	Accessible Real-time Eye-Gaze Tracking For Neurocognitive Health Assessments, A Multimodal Web-based Approach Tisdale, Daniel C 01 June 2024 (has links) (PDF) We introduce a novel integration of real-time, predictive eye-gaze tracking models into a multimodal dialogue system tailored for remote health assessments. This system is designed to be highly accessible requiring only a conventional webcam for video input along with minimal cursor interaction and utilizes engaging gaze-based tasks that can be performed directly in a web browser. We have crafted dynamic subsystems that capture high-quality data efficiently and maintain quality through instances of user attrition and incomplete calls. Additionally, these subsystems are designed with the foresight to allow for future re-analysis using improved predictive models, as well as enable the creation and training of new eye-gaze tracking datasets. As we explored gaze patterns for various user-performed tasks, we developed generalizable eye-gaze metrics that capture and reflect the distinct gaze trends among different cohorts. And through testing various feature extraction and classification methods, we have found promising results that have enabled us to effectively classify individuals with Mild Neurocognitive Disorder (MiNCD) / Mild Cognitive Impairment (MCI) in a crowdsourced pilot study (N = 35) with an average accuracy of 0.94 (f1 = 0.83). Although just the beginning, this work represents the first step towards establishing predictive eye-gaze tracking as an accessible and important modality for healthcare applications moving forward, with the potential to significantly impact remote screening and monitoring of neurocognitive health. Eye-Gaze Tracking Remote Health Assessments Multimodal Health Classification Mild Cognitive Impairment Mild Neurocognitive Disorder Artificial Intelligence and Robotics Behavior and Behavior Mechanisms Categorical Data Analysis Clinical Trials Cognition and Perception Cognitive Psychology Cognitive Science Data Science Design of Experiments and Sample Surveys Experimental Analysis of Behavior Investigative Techniques Mental Disorders Psychological Phenomena and Processes Software Engineering Systems Architecture Telemedicine Vision Science Vital and Health Statistics
94	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
95	Software Internationalization: A Framework Validated Against Industry Requirements for Computer Science and Software Engineering Programs Vũ, John Huân 01 March 2010 (has links) View John Huân Vũ's thesis presentation at http://youtu.be/y3bzNmkTr-c. In 2001, the ACM and IEEE Computing Curriculum stated that it was necessary to address "the need to develop implementation models that are international in scope and could be practiced in universities around the world." With increasing connectivity through the internet, the move towards a global economy and growing use of technology places software internationalization as a more important concern for developers. However, there has been a "clear shortage in terms of numbers of trained persons applying for entry-level positions" in this area. Eric Brechner, Director of Microsoft Development Training, suggested five new courses to add to the computer science curriculum due to the growing "gap between what college graduates in any field are taught and what they need to know to work in industry." He concludes that "globalization and accessibility should be part of any course of introductory programming," stating: A course on globalization and accessibility is long overdue on college campuses. It is embarrassing to take graduates from a college with a diverse student population and have to teach them how to write software for a diverse set of customers. This should be part of introductory software development. Anything less is insulting to students, their family, and the peoples of the world. There is very little research into how the subject of software internationalization should be taught to meet the major requirements of the industry. The research question of the thesis is thus, "Is there a framework for software internationalization that has been validated against industry requirements?" The answer is no. The framework "would promote communication between academia and industry ... that could serve as a common reference point in discussions." Since no such framework for software internationalization currently exists, one will be developed here. The contribution of this thesis includes a provisional framework to prepare graduates to internationalize software and a validation of the framework against industry requirements. The requirement of this framework is to provide a portable and standardized set of requirements for computer science and software engineering programs to teach future graduates. Software Internationalization Software Localization Software Globalization Computer Science Education Software Engineering Education Industry Survey Industry Questionnaire Industry Case Study Statistics Hypothesis Testing Applied Statistics Categorical Data Analysis Clinical Trials Curriculum and Instruction Design of Experiments and Sample Surveys Educational Psychology Graphics and Human Computer Interfaces International and Comparative Education Other Applied Mathematics Other Computer Sciences Other Education Other Mathematics Other Physical Sciences and Mathematics Other Statistics and Probability Software Engineering Statistical Methodology Statistical Models Statistics and Probability

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