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Marquette University

Master's Theses (2009 -)

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Full-Text Articles in Physical Sciences and Mathematics

Global Challenges In Accessing Mental Health Services And Addressing The Impact Of Alzheimer's Disease And Depression, Padmapriya Velupillai Meikandan Apr 2024

Global Challenges In Accessing Mental Health Services And Addressing The Impact Of Alzheimer's Disease And Depression, Padmapriya Velupillai Meikandan

Master's Theses (2009 -)

This research project focuses on developing a quantum sensing system that can detect biomarkers associated with health disorders, like Alzheimer’s and depression. Our goal is to create a sensitive and highly selective quantum sensing device using a diamond nitrogen vacancy (NV) center. To train and test our quantum machine learning algorithms we will preprocess data from the available Human Connectome Project dataset. This dataset forms the basis of our quantum-based methods. The core of our project revolves around developing quantum machine learning algorithms that utilize techniques such as Support Vector Machines and neural networks to diagnose health disorders using data …

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Integrating Drone And Satellite Imaging With Machine Learning For Green Stormwater Infrastructure Condition Assessments, Matthew Dupasquier Apr 2024

Integrating Drone And Satellite Imaging With Machine Learning For Green Stormwater Infrastructure Condition Assessments, Matthew Dupasquier

Master's Theses (2009 -)

Green Stormwater Infrastructure (GSI) has been increasingly utilized to improve urban stormwater management strategies. However, the performance and utility of GSI decrease over time if the infrastructure is not properly maintained. In recent history, the intrinsic operations and maintenance costs associated with the complex networks of new infrastructure have placed a burden on municipalities, ultimately prohibiting many from reaching the full extent of their stormwater management goals. One way for cities to achieve cost savings is through automated monitoring that can quickly assess the condition of GSI assets; however, existing cost-effective technologies are limited. Drones and satellites may be able …

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Advanced Machine Learning Approaches For Predicting Mental Health Disorders Following Long Covid Diagnosis, Manoj Purohit Apr 2024

Advanced Machine Learning Approaches For Predicting Mental Health Disorders Following Long Covid Diagnosis, Manoj Purohit

Master's Theses (2009 -)

After the global spread of COVID-19, the enduring effects of Long COVID and its health implications have emerged as a significant global issue, affecting people worldwide. The lingering symptoms post a COVID-19 infection can significantly affect individuals who had previously contracted the virus, exerting considerable influence over their mental well-being. Prolonged recuperation associated with Long COVID has been connected with the emergence of symptoms such as depression and anxiety, all of which can have adverse effects on emotional health. This project delves into an in-depth analysis of healthcare data pertaining to Long COVID from the Froedtert Health (FH) Medical System …

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Exploring Post-Quantum Cryptographic Schemes For Tls In 5g Nb-Iot: Feasibility And Recommendations, Kadir Sabanci Apr 2023

Exploring Post-Quantum Cryptographic Schemes For Tls In 5g Nb-Iot: Feasibility And Recommendations, Kadir Sabanci

Master's Theses (2009 -)

Narrowband Internet of Things (NB-IoT) is a wireless communication technology that enables a wide range of applications, from smart cities to industrial automation. As a part of the 5G extension, NB-IoT promises to connect billions of devices with low-power and low-cost requirements. However, with the advent of quantum computers, the incoming NB-IoT era is already under threat due to conventional cryptographic algorithms that might be adapted to secure devices in NB-IoT being susceptible to be broken soon. In this context, we investigate the feasibility of using post-quantum key exchange and signature algorithms for securing NB-IoT applications. We develop a realistic …

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Using Object Detection To Navigate A Game Playfield, Peter Kearnan Hyde-Smith Apr 2023

Using Object Detection To Navigate A Game Playfield, Peter Kearnan Hyde-Smith

Master's Theses (2009 -)

Perhaps the crown jewel of AI is the self-navigating agent. To take many sources of data as input and use it to traverse complex and varied areas while mitigating risk and damage to the vehicle that is being controlled, visual object detection is a key part of the overall suite of this technology. While much efforts are being put towards real-world applications, for example self-driving cars, healthcare related issues and automated manufacturing, we apply object detection in a different way; the automation of movement across a video game play field. We take the TensorFlow Object Detection API and use it …

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Enots Wolley Variations And Related Sequences, Nathan Myles Nichols Apr 2023

Enots Wolley Variations And Related Sequences, Nathan Myles Nichols

Master's Theses (2009 -)

The Enots Wolley sequence is a lexicographically earliest sequence (LES) that is closely related to the Yellowstone sequence. It is an open conjecture by N. J. Sloane that every number with at least two distinct prime factors appears as a term of the Enots Wolley sequence. In this thesis, this conjecture is proved for a variation of the Enots Wolley sequence that operates on the binary representation of a positive integer rather than the prime factorization. The methods used are then applied to prove some new properties of the prime factorization Enots Wolley sequence.

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Transcriptional Profile Of Cohesin Complex Mutations In The Background Of Npm1 And Runx1-Runx1t1 Aml, Jacob Tiegs Oct 2022

Transcriptional Profile Of Cohesin Complex Mutations In The Background Of Npm1 And Runx1-Runx1t1 Aml, Jacob Tiegs

Master's Theses (2009 -)

Acute Myeloid Leukemia is a cancer of the blood, characterized by a heterogenous mixture of disease causing mutations. Mutations of the cohesin complex is a group of such mutations and occur alongside several other driving mutations in the development of Acute Myeloid Leukemia. This thesis specifically focuses on cohesin complex mutations in the context of concurrence with NPM1 mutation and the Core Binding Factor (CBF) mutation RUNX1-RUNX1T1 in three distinct components. The first two components involved Differential Expression Analysis (DEA) to identify significantly differentiated genes in each model, followed by Gene Set Enrichment Analysis (GSEA) to identify Gene Ontology (GO) …

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The Role Of Self-Tutorial In Introductory Physics Student Performance On Test Of Understanding Of Vectors, Katherine Finegan Jul 2022

The Role Of Self-Tutorial In Introductory Physics Student Performance On Test Of Understanding Of Vectors, Katherine Finegan

Master's Theses (2009 -)

A single-interaction self-guided lesson was designed to teach basic vector concepts to introductory physics students. The self-guided lesson was tested for efficacy by comparing pre-test and post-test subscores on a Test of Understanding of Vectors (TUV) and comparing subscore differences to students in the same physics courses who had not taken the self-guided lesson. Analysis showed no significant differences in subscore differences between students taking the self-guided lesson and those in comparable control groups, indicating that more robust interventions are needed and/or further work must be done on the self-guided lesson to improve student vector understanding.

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Properties And Behavior Of Tricarbonyl Manganese Scorpionate Complexes, Billy Shone Jul 2022

Properties And Behavior Of Tricarbonyl Manganese Scorpionate Complexes, Billy Shone

Master's Theses (2009 -)

Manganese tricarbonyl complexes have widely been studied for their ability to release carbon monoxide (CO) in the presence of light for potential applications in cancer therapy and in catalysis. Most studies focus on the kinetics and quantity of CO release and the overall impact on cell death. Far fewer studies identify the manganese intermediates and final products after decarbonylation. Identification of such products would be critical to improving reactivity and understanding potential (undesirable) side effects in future applications employing these CO releasing molecules (CORMs). Recently, nitrogen confused C-scorpionate ligands were introduced by the Gardinier group where a pyrazolyl ring is …

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Synthesis And Characterization Of Enantioenriched Deuterated And Fluorinated Small Molecules, Mitchell D. Mills Apr 2022

Synthesis And Characterization Of Enantioenriched Deuterated And Fluorinated Small Molecules, Mitchell D. Mills

Master's Theses (2009 -)

The development of novel deuterated and fluorinated bioisosteres has significantly impacted the pharmaceutical and agricultural industry and created a growing demand for new synthetic methodology. Both deuterated and fluorinated small molecules exist at the forefront of drug discovery due to their unique ability to attenuate the pharmacokinetic properties of new and currently existing drugs. Selective, high-throughput methods for deuteration and fluorination are scarce in the literature, especially methods that introduce D or F atoms asymmetrically. Benzylic CH bonds are oftentimes key sites for enzymatic manipulation in metabolic processes, alteration of CH bonds to CD or CF bonds at the benzylic …

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Crowdsourced Archiving Of The January 6th Us Capitol Insurrection: An R/Datahoarders Case Study, Edward Miezio Chapman Oct 2021

Crowdsourced Archiving Of The January 6th Us Capitol Insurrection: An R/Datahoarders Case Study, Edward Miezio Chapman

Master's Theses (2009 -)

The crowdsourced archiving that occurred in the wake of the January 6th US Capitol insurrection exemplifies the potential for agile, collaborative evidence gathering during a crisis situation. This paper studies the r/DataHoarders subcommunity of Reddit and the collective and spontaneous archiving project that users initiated. Users were drawn to the thread out of a desire to contribute to law enforcement efforts, enact punitive justice upon the rioters, engage in public discourse, and preserve information for posterity. They did this by gathering and preserving social media evidence that may have otherwise been lost. I discovered that this constituted a crowdsourced archive …

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Statistical Modeling Of Daily Confirmed Covid-19 Cases And Deaths In Europe And United States, Zerui Zhang Jul 2021

Statistical Modeling Of Daily Confirmed Covid-19 Cases And Deaths In Europe And United States, Zerui Zhang

Master's Theses (2009 -)

A novel coronavirus disease was first discovered in Wuhan, China, in December 2019. This new coronavirus named COVID-19 has rapidly spread and become a global threat affecting almost all the countries in the world. Therefore, it is important to know the trend of coronavirus disease to mitigate its effects. A good prediction model is crucial for the health care system to understand the trend of the COVID-19. This study aims to construct a good prediction model. Firstly, we detect change points of the time series data of daily confirmed cases and deaths of COVID-19 in the United States and Europe, …

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Efficient Service For Next Generation Network Slicing Architecture And Mobile Traffic Analysis Using Machine Learning Technique, Billian Khan Tapan Jul 2021

Efficient Service For Next Generation Network Slicing Architecture And Mobile Traffic Analysis Using Machine Learning Technique, Billian Khan Tapan

Master's Theses (2009 -)

The tremendous growth of mobile devices, IOT devices, applications and many other services have placed high demand on mobile and wireless network infrastructures. Much research and development of 5G mobile networks have found the way to support the huge volume of traffic, extracting of fine-gained analytics and agile management of mobile network elements, so that it can maximize the user experience. It is very challenging to accomplish the tasks as mobile networks increase the complexity, due to increases in the high volume of data penetration, devices, and applications. One of the solutions, advance machine learning techniques, can help to mitigate …

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Copper-Catalyzed Transfer Hydrogenation, Deuteration, And Selective Transfer Hydrodeuteration Of Aryl Alkynes, Kiera Behlow Jul 2021

Copper-Catalyzed Transfer Hydrogenation, Deuteration, And Selective Transfer Hydrodeuteration Of Aryl Alkynes, Kiera Behlow

Master's Theses (2009 -)

Transfer hydrogenation utilizes a non-H2 source of hydrogen to reduce double and triple bonds, utilizing transition metal catalysts in addition to some organocatalysts. The use of earth-abundant first row transition metals with ligands that fine tune the reactivity of the catalyst allows for the selective reduction of unsaturated functionalities by utilizing cheap and ubiquitous hydrogen sources such as water and various alcohols. This precludes the need for highly flammable H2 gas, which is often used with heterogeneous catalysts that offer limited selectivity and functional group tolerability. Catalysts optimized for the transfer hydrogenation of the desired functionality can be implemented to …

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Predicting Daily Confirmed Cases In Midwestern Central States In U.S. By Using Aima And Lstm, Yi Zheng Jul 2021

Predicting Daily Confirmed Cases In Midwestern Central States In U.S. By Using Aima And Lstm, Yi Zheng

Master's Theses (2009 -)

Covid-19 is an epidemic disease caused by SARS-Cov-2 virus, which is a type of coronavirus. This virus is highly contiguous, and the confirmed cases of this disease have increased rapidly in a short period. After one month of the first reported case, the World Health Organization (WHO) claims that the Covid-19 will become an international public health emergency. The main purpose of this thesis is to predict the daily confirmed cases of Covid-19 in the midwestern central states in the U.S, by using Autoregression Integrated Moving Average (ARIMA) model and Long Short-Term Memory network (LSTM), which is a type of …

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Using Grids As Password Entry Devices, Karol Lejmbach Apr 2021

Using Grids As Password Entry Devices, Karol Lejmbach

Master's Theses (2009 -)

The classic text-based password has been around for a very long time. A lot of security research has been conducted on it. A set of best practices has been available for many years stressing the use of longer and more complex passwords. The issue with this approach is that humans have a hard time recalling long complex sequences of characters. Worse, the more complex the string of characters the more prone it is to being written down which is the most detrimental security threat. The goal of this paper is to introduce and provide an introductory analysis of a grid-based …

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Hydrogen-Bonded Clusters: A Study Of The Elusive Anisole-Ammonia And Anisole-Water 1:1 Complexes, John Lawrence Loman Apr 2021

Hydrogen-Bonded Clusters: A Study Of The Elusive Anisole-Ammonia And Anisole-Water 1:1 Complexes, John Lawrence Loman

Master's Theses (2009 -)

The hydrogen bond is one of the most important and versatile interactions found in most subsets of chemistry and biology. This interaction is responsible for reactions and characteristic properties of the systems in thereof. This interaction is just one of several available non-covalent interactions that can occur and over the past several decades of molecular spectroscopy studies, the definition of the hydrogen bond has become broader compared to the “classic” definition. To accurately study the hydrogen-bonding in these systems can be quite challenging due to the size and complexity of the molecules involved, as well as the other interactions that …

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Synthesis Of Composites From Cellulose, Chitosan, And Ciprofloxacin Hci Encapsulated In Sporopollenin Capsules, Mark Mitmoen Apr 2021

Synthesis Of Composites From Cellulose, Chitosan, And Ciprofloxacin Hci Encapsulated In Sporopollenin Capsules, Mark Mitmoen

Master's Theses (2009 -)

In order to be effective dressings for the treatment of infected wounds in the battlefield, it is essential that composite materials made from the biopolymers Cellulose and Chitosan contain broad-spectrum antibiotic drugs. These drugs must first be encapsulated into microcapsules in order to protect them from the manufacturing process, ensuring that they remain in a usable form in the final product. Here we demonstrate the successful encapsulation of Ciprofloxacin HCl into Sporopollenin Exine Capsules (SEC) to produce Cipro@SEC, followed by incorporation of Cipro@SEC into a polymer composite consisting of a mixture of Cellulose and Chitosan dissolved in 1-butylmethylimidazolium chloride, an …

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Auto-Grading Oct Images Diagnostic Tool For Retinal Disease Classification, Shiyu Tian Apr 2021

Auto-Grading Oct Images Diagnostic Tool For Retinal Disease Classification, Shiyu Tian

Master's Theses (2009 -)

Retinal eye disease is the most common reason for visual deterioration. Long-term management and follow-up are critical to detect the changes in symptoms. Optical Coherence Tomography (OCT) is a non-invasive diagnostic tool for diagnosing and managing various retinal eye diseases. With the increasing desire for OCT image, the clinicians are suffered from the burden of time on diagnoses and treatment. This thesis proposes an auto-grading diagnostic tool to divide the OCT image for retinal disease classification. In the tool, the classification model implements convolutional neural networks (CNNs), and the model training is based on denoised OCT images. The tool can …

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Biochemical Analysis Of Dual T-Loop Rna Motifs That Perform Shape Recognition Of The Trna Elbow, John Aparicio Aguirre Apr 2021

Biochemical Analysis Of Dual T-Loop Rna Motifs That Perform Shape Recognition Of The Trna Elbow, John Aparicio Aguirre

Master's Theses (2009 -)

T-loops are highly abundant, structurally conserved five nucleotide motifs that facilitate long range intra- and intermolecular interactions and function to stabilize the tertiary fold of RNA. Interlocked or dual T-loop motifs provide additional thermodynamic stability and perform long-range docking of other RNA molecules. Dual T-loop RNA structures are present within the multi-turnover ribonuclease P-based ribozyme, the ribosome, and the bacterial tRNA-sensing riboswitch genetic element. In all three systems, a dual T-loop structure recognizes TYC/D-loop region of tRNA. Interestingly, sequence conservation at specific positions in the T-loops suggest a conserved interlocked RNA architecture. While X-ray crystallography provides insight into the putative …

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Analyzing Adverse Events From Publicly Available Web Sources, Alexander Salamun Oct 2020

Analyzing Adverse Events From Publicly Available Web Sources, Alexander Salamun

Master's Theses (2009 -)

Data mining for drug-reaction associations is a major topic in the pharmaceutical industry. Historically the focus has been on using privately owned and maintained datasets consisting of information that has been transformed via the FDA Adverse Event Reporting System (FAERS) and privatized reporting systems that house the data from clinical trials. Our focus will be on building a pipeline that demonstrates an open source solution for building a drug’s safety profile from data collection through signal detection. In contrast this pipeline primarily uses the openFDA and social media data available through Reddit with all analysis being done in the R …

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Towards Developing A Mobile-Based Care For Children With Asd Using Remote Experience Sampling Method (Mcare), Dipranjan Das Oct 2020

Towards Developing A Mobile-Based Care For Children With Asd Using Remote Experience Sampling Method (Mcare), Dipranjan Das

Master's Theses (2009 -)

Autism Spectrum Disorder (ASD) is the most prevalent among all of the neurodevelopmental disorders, which have increased 20-30 times in the last 50 years. A child with ASD requires regular monitoring, care, and support. But, the existing social-cultural-financial constraints and the scarcity of mental health care practitioners have deprived the families raising children with ASD in low-and middle-income countries (LMICs) like Bangladesh. However, the recent overwhelming adoption (~80%) of mobile phones has created an opportunity to improve the existing practice of care using affordable mobile applications. mCARE, a mobile-based care system, has been developed to reduce the gap between families …

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Synthesis And Evaluation Of Small Molecule Inhibitors Of Pyruvate Carboxylase, Daniel John Burkett Jul 2020

Synthesis And Evaluation Of Small Molecule Inhibitors Of Pyruvate Carboxylase, Daniel John Burkett

Master's Theses (2009 -)

Through structure-based drug design (SBDD), a series of small molecules have been synthesized and evaluated for inhibitory activity against the pyruvate carboxylase (PC) enzyme via two biological assays. The -hydroxycinnamic acid scaffold was identified as the most privileged scaffold for inhibition of PC. Analogues of phenylpyruvic acid were generated and evaluated, leading to the discovery of inhibitors with single digit micromolar (M) IC50 values. The most potent inhibitors identified were evaluated for inhibitory activity against other metalloproteins, and 2-hydroxy-3-(quinolone-2-yl)propenoic acid did not significantly inhibit human carbonic anhydrase II, matrix metalloproteinase-2, malate dehydrogenase, or lactate dehydrogenase. The small molecules presented in …

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Application Of Siem/Ueba/Soar/Soc (Cyber Suss) Concepts On Mscs 6560 Computer Lab, Kunal Singh Jul 2020

Application Of Siem/Ueba/Soar/Soc (Cyber Suss) Concepts On Mscs 6560 Computer Lab, Kunal Singh

Master's Theses (2009 -)

Increased Cyber-attacks on the IT infrastructure is a grave concern for organizations. Cyber defense and cyber threat remediation have become topmost priority of organizations. This thesis explains the core concepts of SIEM, UEBA, SOAR and SOC (SUSS) and explains the details of an experimental solution to which was applied MSCS 6560 lab computers for real time cyber threat detection and remediations. To test and validate SUSS concepts, these technologies were successfully applied to a small lab environment in the MSCS infrastructure for the graduate class on the Principle of Service Management and System Administration. Lab machines in this class were …

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Using Machine Learning Tools To Predict The Severity Of Osteoarthritis Based On Knee X-Ray Data, Yaorong Xiao Apr 2020

Using Machine Learning Tools To Predict The Severity Of Osteoarthritis Based On Knee X-Ray Data, Yaorong Xiao

Master's Theses (2009 -)

Knee osteoarthritis(OA) is a very general joint disease that disturb many people especially people over 60. The severity of pain caused by knee OA is the most important portent to disable. Until now, the bad impact of osteoarthritis on health care and public health systems is still increasing.In this paper, we will build a machine learning model to detect the edge of the knee based on the X-ray image and predict the severity of OA. We use a clustering algorithm and machine learning tools to predict the severity of OA in knee X-ray images. The data is coming from …

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A Parallel Algorithm And Implementation To Compute Spatial Autocorrelation (Hotspot) Using Matlab, Mingjun Li Apr 2020

A Parallel Algorithm And Implementation To Compute Spatial Autocorrelation (Hotspot) Using Matlab, Mingjun Li

Master's Theses (2009 -)

Being a spatial autocorrelation visualization tool in recent years, hotspot is often used in various fields, such as disease analysis, crime analysis, and weather conditions analysis and prediction in a certain area. Most of the research in hot spot analysis is in applying the concept to a variety of fields and to gain insights on the statistical significance prevalent in the clustering of data. Only a few of them discussed the efficiency and optimization of the algorithm. Commonly, these kinds of analyses would be based upon a huge dataset about space and time, and the conventional algorithm would take too …

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Alarm Forecasting In Natural Gas Pipelines, Colin Quinn Apr 2020

Alarm Forecasting In Natural Gas Pipelines, Colin Quinn

Master's Theses (2009 -)

This thesis examines alarm forecasting methods for a natural gas production pipeline to assure the efficient transportation of high-quality natural gas. Natural gas production companies use pipelines to transport natural gas from the extraction well to a distribution point. Forecasting natural gas pipeline pressure alarms helps control room operators maintain a functioning pipeline and avoid costly down time. As gas enters the pipeline and travels to the distribution point, it is expected that the gas meets certain specifications set in place by either state law or the customer receiving the gas. If the gas meets these standards and is accepted …

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A Critical Study Of Geospatial Algorithm Use In Crime Analysis And Predictive Policing, Katy Weathington Apr 2020

A Critical Study Of Geospatial Algorithm Use In Crime Analysis And Predictive Policing, Katy Weathington

Master's Theses (2009 -)

We examine in detail two geospatial analysis algorithms commonly used in predictive policing. The k-means clustering algorithm is used to partition input data into k clusters, while Kernel Density Estimation algorithms convert geospatial data into a 2-dimensional probability distribution function. Both algorithms serve unique roles in predictive policing, helping to inform the allocation of limited police resources. Through critical analysis of the k-means algorithm, we found that parameter choice can greatly impact how crime in a city is clustered, which therefor impacts how mental models of crime in the city are developed. Interviews with crime analysts who regularly used k-means …

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An Educational Operating System Supporting Computer Security, Patrick Joseph Mcgee Apr 2020

An Educational Operating System Supporting Computer Security, Patrick Joseph Mcgee

Master's Theses (2009 -)

It is uncommon to teach computer security concepts using an embedded operating system. Few educational operating systems are implemented in systems courses, and a small subset of them are used to teach hardware-related security elements such as system calls. This work explores relevant approaches to teaching low-level security concepts, including difficulties associated with building a hands-on learning environment. This work also presents additions to the Embedded Xinu kernel that support system calls and memory protection on a Raspberry Pi 3 B+. Provided sample assignments are intended to help give students a solid understanding of intricate hardware details. Results from an …

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Photophysical Properties And Excited State Dynamics Of Porous Organic Materials, Korlan Duisenova Apr 2020

Photophysical Properties And Excited State Dynamics Of Porous Organic Materials, Korlan Duisenova

Master's Theses (2009 -)

Charge transfer complexes are charge separated states that are formed at donor - acceptor interfaces and play significant role in charge photogeneration. One of the main criteria for efficient charge transfer is suppression of charge recombination process. Previous experiments show that one of the most effective ways to inhibit recombination is an introduction of bridge molecules between donor and acceptor or increase the number of electron donating and withdrawing groups. These solutions are inspired by photosynthetic reaction centers where charge transfer occurs over long distances. Covalent Organic Frameworks (COFs) are advanced porous crystalline materials that can be constructed of multiple …

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