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MACHINE LEARNING AND SOFTWARE SOLUTIONS FOR DATA QUALITY ASSESSMENT IN CERN’S ATLAS EXPERIMENT
Get PDFThe Large Hadron Collider (LHC) is home to multiple particle physics experiments designed to verify the standard model and push our understanding of the universe to its limits. The ATLAS detector is one of the large general-purpose experiments that make use of the LHC and generates a significant amount of data as part of its regular operations. Prior to physics analysis, this data is cleaned through a data assessment process which involves significant operator resources. With the evolution of the field of machine learning and anomaly detection, there is great opportunity to upgrade the ATLAS Data Quality Monitoring Framework to include automated, machine learning based solutions to reduce operator requirements and improve data quality for physics analysis. This thesis provides an infrastructure, theoretical foundation and a unique machine learning approach to automate this process. It accomplishes this by combining 2 heavily documented algorithms (Autoencoders and DBScan) and organizing the dataset around geometric descriptor features. The results of this work are released as code and software solutions for the benefit of current and future data quality assessment, research, and collaborations in the ATLAS experiment
Racial Discrimination from a Self-Determination Lens
Get PDFDespite significant advances toward equality, racism and discrimination have been a central feature of America’s culture. This inequality has been presented from the history of slavery to the present-day violence against unarmed Black men. Oppression and inequalities have led calls to action from the African American community and activist groups including the Black Lives Matter Movement. Many White individuals are unaware of the existing benefits of their Whiteness and are simultaneously unaware of the significant psychological, emotional, physical, and social consequences for African American individuals. While there are several established theories to address the psychological and social aspects of how individuals exhibit discriminatory thoughts and behaviors, they are often not comprehensive of both individual and social underpinnings. Self Determination Theory proposes that motivations vary not only in social environments or contexts, but also in the source provided within and for the individual. Within the theory, there are two forms of locus of causality including intrinsic and extrinsic which can vary on a continuum of regulations. While racism is manifested in many forms, literature indicates it has moved from an overt, explicit, form to a covert, sublet form. Limited studies have examined overt and covert behaviors on discrimination simultaneously. Likewise, society has shifted in culture to be more intentional with overt acts such as White nationalist “Unite the Right” march rally in Charlottesville, VA as well as deficiency in punishments for hate crimes and the attempt of reversal of civil rights and social justice policies. The purpose of this study is to examine racial discrimination at both covert and overt levels utilizing self-determination theory as the theoretical framework to explore regulatory motivations on a continuum when individuals are exhibiting discriminatory or prosocial behaviors. Latent profile analysis (LPA), a person-centered analysis, rather than a variable level analysis was utilized to categorize individuals into groups based on similar characteristics to examine how different each group of individuals differs on their motivations
Cultures of Assessment in Educator Preparation: A Study of Assessment Leaders
Get PDFThe purpose of this research was to create a Culture of Assessment Instrument (Appendix F) that will allow education program provider (EPP) assessment leaders to measure the assessment culture within their program. General Systems Theory was the theoretical framework as the foundation of this research. Using a modified Delphi panel of assessment leaders, the researcher developed a valid Culture of Assessment Instrument (Appendix F). A key finding is that the instrument accurately reflects the culture of assessment, as evidenced in a pilot study. Leaders can use this instrument to measure the culture of assessment within an EPP undergoing change to determine growth over time. The instrument can also be used as a formative guide for best practices to shape a positive culture of assessment
A Qualitative Study Identifying a School Leadership Model Promoting and Fostering Technology-Enhanced Teaching and Learning
Get PDFTechnology-enhanced teaching and learning (TETL) is the integration of technology into teaching and learning practices to improve the quality of learning outcomes. This is an essential strategy for improving educational quality. School leaders significantly affect the integration of effective TETL in the classroom. The International Society for Technology in Education (ISTE) provides Standards for Leaders that serve as a framework for innovation in education. Situational Leadership Theory contends that one leadership style cannot be applied to all leadership tasks. This study expands upon the current use of SLT to help derive characteristics needed to develop a school leadership model that promotes and fosters effective (TETL) in PK-12 education. This study employed a qualitative, multi-case study to investigate highly effective TETL public school districts in Louisiana. A multi-level approach in research was taken to avoid the risk of ignoring influence within its complex layers. The district and school leaders in these districts were interviewed to explore TETL, leadership, perception, skill, and self-efficacy to uncover characteristics needed to promote and foster TETL. A structured interview approach was taken during this study. This approach increased the ability to compare responses between the various school districts. Results of this study lead the researcher to develop a School-Level Leadership model for effective TETL, which includes the following elements: vision, empowering future leaders, fostering growth, support, student-centered strategies, and curriculum focus. This model also consists of the overlapping partnership between the school-level leader, school TETL team, and district leadership team
UNDERSTANDING THE SHEAR DEFORMATION MECHANISM OF TRANSITION METAL/CERAMIC INTERFACES USING COMPUTATIONAL METHODS
Get PDFThe objective of this research was to investigate the deformation behavior of metal/ceramic interfaces under external loadings in a multi-scale framework including first principles density functional theory (DFT) and molecular dynamics (MD) simulations. The mechanical properties of the metal/ceramic interfaces are dominated by defects on a length scale that first principles computations cannot access. Since the DFT calculations become computationally expensive for such large sized systems, therefore, MD simulations are required to deal with such systems. For MD simulations, second nearest neighbor modified embedded atom method (MEAM) potentials were developed to study metal/ceramic interfaces involving Cr, Ti, Al, and N. The effect of misfit dislocation networks (MDNs) on the stability and shear strength of Cr/TiN was investigated using the newly developed potential. Good agreement with a combination of experimental and DFT results was achieved. The interfacial energy was lowest when the MDN was located in the Cr layer adjacent to the chemical interface, which also had the largest dislocation core width. This was consistent with generalized stacking fault energies, which had lower energy barriers between the first and second Cr layers next to the chemical interface. For all positions of MDNs, shear failure occurred in the ceramic, between the first and the second TiN layers next to the chemical interface. The lowest shear strength was found for the system with the MDN in the first Cr layer with respect to the chemical interface. Only for this particular configuration was there a significant plastic deformation present. The impact of Al doping on the stability and shear strength of Ti/TiN metal/ceramic interface was also investigated. The model was parameterized to the interfacial properties of pure Al, TiAl and AlN binaries as well as TiAlN ternary systems. A Monte Carlo scheme was developed to find the most likely doping configuration of Al atoms in Ti/TiN. The doping was increased up to 25 mol % Al concentration after which the enthalpy of mixing started to increase. There was a drastic increase in the maximum shear stress from about 200 MPa in case of the undoped system to almost 1 GPa for the 25 mol % Al doped Ti/TiN. This study would be particularly useful in materials-based engineering of metal/ceramic interfaces and will have a significant impact on applications of ceramic coating/substrate systems in material engineering
Flood Risk Prediction in Southern Louisiana Using Support Vector Machines
Get PDFFlooding in Southern Louisiana is a growing concern as violent weather becomes more frequent. According to the Environmental Protection Agency (EPA), Louisiana soils have become drier and annual rainfall trends have increased, which may lead to more severe flooding in the coming years. In light of this change in weather trends, flood prediction has become increasingly important for the public’s safety. The focus of this paper is to apply the Support Vector Machine (SVM), a machine learning technique, to classify flood risks based on water gage height, wind speed and direction, and time of the year. In this paper, the methodology of this technique is discussed, and the Support Vector Machine method is applied on the data collected by the National Weather Service (NWS) and the US Army Corps of Engineers using the R language. Finally, this paper will examine the results to discern if this technique is a valid choice for flood risk prediction
