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Articles 181 - 210 of 6568
Full-Text Articles in Entire DC Network
A Search For Serotyping Candidates In The Streptococcus Sobrinus Genome, Ryan Schwendel
A Search For Serotyping Candidates In The Streptococcus Sobrinus Genome, Ryan Schwendel
Theses
Streptococcus sobrinus (SSO) is a pathogenic microbe native to the human oral microbiome. SSO is historically implicated in carie formation, and may be involved in neurodegenerative disease progression. The study of SSO is challenged by a lack of access to a serotyping assay. This study aims to identify sero-specific candidates from available SSO genomes using sequence alignment and phylogenetic analysis. Three candidate genes were found that may be sero-specific: putative quinol monoxygenase, a hypothetical protein, and elongation factor Tu. To further assess the candidates the original antibodies or a list of proteins involved is required. Alternatively, a new classification system …
Disposal, Yihan Su
Disposal, Yihan Su
Theses
Disposal is a mixed-media animated short film created as a graduate thesis project. The story explores the protagonist’s search for meaning in life and his defiance of a predetermined fate. At the beginning, he is an ordinary, guileless figure without remarkable qualities. In his world, life revolves around constant competition, and one’s worth is measured by their position on a ranking board. Only the top three may pass through the golden gate, a symbol of transcendence. Others must continue the endless cycle of contests, while the lowest seven face incineration in the Disposal. Despite his efforts, the protagonist falls into …
Understanding Crime Through Harm: A Multi-Stage Study Of Rochester, Ny, Hayder Alhafedhi
Understanding Crime Through Harm: A Multi-Stage Study Of Rochester, Ny, Hayder Alhafedhi
Theses
This capstone project develops, critiques, and applies a Crime Harm Index (CHI) for the City of Rochester, New York, as an alternative to traditional crime measures that rely solely on raw counts. Rather than treating all offenses as equal “one crime = one unit,” the project weights crimes by the severity of harm they cause, using New York State sentencing guidelines as the core metric. Across four working papers, the project moves from conceptual foundations and limitations of harm-based metrics, to the construction of a Rochester-specific Crime Harm Index, and finally to a set of spatial regression models that link …
Understanding The Relationship Between Mental Health And Criminal Justice Involvement: Pathways, Disparities, And Improving System Responses, Haley Bly
Theses
This capstone project examines the complex relationship between mental health and involvement in the criminal justice system, emphasizing how pathways, external conditions, structural inequities, and system responses interact to shape long-term outcomes for persons with mental illness (PwMI). While mental illness alone is not a predictor of criminal behavior, the intersection between psychological disorders, social strain, stigma, and systemic failures significantly heightens the risk of criminal justice involvement. Combining four working papers, this capstone examines these relationships across individual, environmental, institutional, and community levels, ultimately arguing that treatment and rehabilitative-centered reforms are essential for improving the experiences of individuals with …
Catherine, Reagan Christie
Catherine, Reagan Christie
Theses
A golden lamb sleeps peacefully in a quiet meadow, showcased in an intricate golden frame. She wakes up and slowly begins to stand, her knobby knees trembling all the way up. She steadies herself, turning toward the viewer, blinking. Catherine looks at her reflection in a grimy sink full of water. The sink drips, reflection dissipating. She looks up into the mirror above the sink in an endless bathroom, tucks a loose curl of hair back into her habit, and exits the bathroom. Catherine makes her way down a long spiral staircase, humming a hymn to herself. In the kitchen, …
The Impact Of Screen Time Patterns On Digital Behaviour And Productivity: A Data Analytics Study Across Age Groups, Maytha Alshamsi
The Impact Of Screen Time Patterns On Digital Behaviour And Productivity: A Data Analytics Study Across Age Groups, Maytha Alshamsi
Theses
The increasing incidence of screen time of all ages has generated a greater interest in the effect of screens on the human psyche. This paper looks at behavioural data of 2, 000 individuals aged 13-64 to investigate the predictability of a composite mental- health score by various modalities of screen-time, lifestyle and psychological charac- teristics. We determine, based on exploratory statistics, multivariate regression and su- pervised machine-learned models, that in as much as the influence of total screen time and social-media consumption has significant relationships with worse mental health, the effects are small when juxtaposed to those of lifestyle and …
Beyond Static Models - A Framework For Evaluating Dynamic Ml Approaches In Heart Failure Risk Prediction, Mohammad Arif Ul Islam
Beyond Static Models - A Framework For Evaluating Dynamic Ml Approaches In Heart Failure Risk Prediction, Mohammad Arif Ul Islam
Theses
Heart failure remains a pressing global health challenge, affecting approximately 64 million people and incurring annual healthcare costs of $108 billion, driven by high readmission rates and delayed interventions. Current risk prediction models predominantly rely on static machine learning approaches, utilizing fixed datasets that fail to adapt to the evolving nature of patient health. This limitation results in outdated risk assessments, hindering timely clinical responses and worsening patient outcomes and resource efficiencies. This research addresses a fundamental methodological gap by developing and validating a chunk-based ensemble framework that enables researchers to evaluate dynamic machine learning potential using readily available static …
An Educational Approach To Mitigating Stormwater Debris Pollution In The Great Lakes Basin, Autumn Potts
An Educational Approach To Mitigating Stormwater Debris Pollution In The Great Lakes Basin, Autumn Potts
Theses
Accumulation of anthropogenic debris (AD) in the environment, especially plastic, is a pervasive issue that impacts human communities and ecosystems worldwide. Since AD pollution at every scale stems from human activities, its mitigation is contingent on analyzing and modifying the scale-dependent drivers of human behavior surrounding this issue. Although the underlying mechanisms driving litter input and accumulation are not well understood, these patterns suggest a need for hyperlocal solutions. Because environmental education (EE) fosters a significant influence on environmental knowledge, attitudes, and behaviors, it can play an important role in the mitigation of debris input and littering behavior. One method …
Social Media's Impact On Female Generation Alpha's Beauty Standards And Consumer Habits, Matisen O'Brien
Social Media's Impact On Female Generation Alpha's Beauty Standards And Consumer Habits, Matisen O'Brien
Theses
This study examines how social media shapes beauty standards and consumer behaviors among female Generation Alpha (ages 7–13). As the first generation fully immersed in digital culture, these young girls face early exposure to influencer marketing, algorithmic promotion, and adult beauty practices, which influence their skincare routines and product preferences. The research highlights the decline of child-centered physical spaces, intensifying their engagement with digital platforms. Using a mixed-methods approach focused on a subgroup of female gymnasts, the study combines quantitative surveys and qualitative analysis to reveal how social media affects identity formation, consumer choices, and related mental health concerns. Results …
A Decision Support System For Global Vaccine Funding: Data-Driven Proposal Scoring, Epidemiological Risk Modeling, And Portfolio Optimization, Ashutosh Kumar
A Decision Support System For Global Vaccine Funding: Data-Driven Proposal Scoring, Epidemiological Risk Modeling, And Portfolio Optimization, Ashutosh Kumar
Theses
Global health financing must continually stretch limited immunization resources across competing priorities, and Gavi, the Vaccine Alliance, plays a central role in this landscape. This work reframes Gavi’s funding decisions as a multi-objective portfolio optimization problem that jointly considers health impact, equity, cost-effectiveness, sustainability, and epidemiological interdependence. To operationalize this approach, this study develops a decision support system grounded in Modern Portfolio Theory, treating each proposal as an asset characterized by expected return and risk. Proposal returns are estimated through a heterogeneous data-fusion pipeline that generates quantitative, multi-objective scores aligned with Gavi’s strategic priorities, while epidemiological risk is quantified using …
Adaptive Design Solutions For Golfers With Arm Impairment, Samuel Hao-Yu Wang
Adaptive Design Solutions For Golfers With Arm Impairment, Samuel Hao-Yu Wang
Theses
Golf is a game of precision, focus, and enjoyment for everyone, regardless of age, physical condition, or experience. However, for many people with disabilities, full participation in the game can be challenging. This project created an inclusive golfing experience for players with physical disabilities by assisting them with specific actions required in golf. The goal was to design solutions that reduce limitations caused by impairments, enabling players to enjoy the game with greater freedom. The United States Disabled Golf Association recognizes 14 sport classes of physical impairments, categorizing competitors by different types and levels of disability. This project focused on …
Unmasking Corruption And Bribery Using Predictive Analytics, Maha Salem
Unmasking Corruption And Bribery Using Predictive Analytics, Maha Salem
Theses
The initiative (Unmasking Corruption and Bribery Using Predictive Analytics) aims to identify employees in government sectors who commit corruption and bribery by addressing issues such as the lack of transparency, fairness, equality, and public trust, as well as weakened loyalty and poor reputation. This project focuses on data analytics and predictive modeling to detect suspicious or high-risk employee behaviors related to corruption and bribery. The main objective is to reduce these unethical activities in government sectors, strengthen integrity, and promote transparency and public trust through predictive capabilities. It also seeks to raise awareness about how serious and harmful these crimes …
The Role Of Technology In Modernizing Prison Management Systems, Essa Anwahi
The Role Of Technology In Modernizing Prison Management Systems, Essa Anwahi
Theses
This thesis examines the role of technology in modernizing prison management systems and improving operational efficiency, security, and decision-making. It explores how digital technologies and data analytics can address challenges in traditional prison management, such as inefficient processes and limited data utilization. The study highlights the potential of technology-driven solutions to enhance system performance and support more effective management practices within correctional facilities.
Optimizing Human Resource Decisions: Predicting Promotions Using Data Analytics, Mohammad Khalid A Mohammad Abdulrahim
Optimizing Human Resource Decisions: Predicting Promotions Using Data Analytics, Mohammad Khalid A Mohammad Abdulrahim
Theses
Proper and objective selection of high potential employees to promote them is a major dilemma in the Human Resources (HR) department, more so in sensitive and hierarchal environments in the public sector where subjectivity is likely to take place. This paper is based on this ubiquitous issue, and it seeks to develop, experiment, and examine a clear and equitable machine learning model that can forecast the possibility of an employee to get a promotion according to organized past HR records. The technique was solid preprocessing, alleviation of extreme class imbalances on the basis of the Synthetic Minority Over-sampling Technique (SMOTE), …
Security Vulnerabilities In Cloud Storage: A Comparative Study Of Google Drive, Dropbox, And Onedrive, Sultan Majid Alshamsi
Security Vulnerabilities In Cloud Storage: A Comparative Study Of Google Drive, Dropbox, And Onedrive, Sultan Majid Alshamsi
Theses
In recent years, use of internet has increased manifold. People have started creating more data, and instead of saving it locally, people have started preferring storing it “online”. Companies are also following the same path to maintain accessibility and availability of their data. Thus, data has become a central part of our lives. People, companies, and institutions rely heavily on cloud storage solutions these days for managing their data. Some of the main cloud storage solution are Google Drive, Dropbox, and OneDrive. These are sophisticated solutions developed by tech giants, and general expectation of the public is that these solutions …
Work And Play In Tandem: A Brief Study Of Familiar Silhouettes In The Contemporary Workplace, Tanisa Bose Samaddar
Work And Play In Tandem: A Brief Study Of Familiar Silhouettes In The Contemporary Workplace, Tanisa Bose Samaddar
Theses
This thesis addresses the limitations posed by conventional office furniture, and its impact on human psychological and physiological well-being. Drawing upon literature that delves into the topics of neuroscience of play, environmental psychology, and emotional sustainability, the thesis seeks to solve these issues through design modifications. It aims to understand how brief, movement-focused breaks can help rejuvenate executive functioning, uplift mood, and encourage bursts of social interaction. A five-stage prototyping process, thumbnail sketches, clay models, 3D modeling, full-scale drawings, and iterative Fusion360 refinements, later Tandem was born. By requiring at least two users to operate its see-saw mode, Tandem counteracts …
A Comparative Analysis Of Machine Learning And Deep Learning Models For Human Activity Recognition Using Wearable Sensor Data, Fares Shaban
A Comparative Analysis Of Machine Learning And Deep Learning Models For Human Activity Recognition Using Wearable Sensor Data, Fares Shaban
Theses
Wearable sensors have become vital for health monitoring, evaluation of sport performance, and recognition of activities of daily life in Human Activity Recognition (HAR). With the combination of machine learning and inertial sensing, new possibilities for the collection of data pertaining to human motion in daily life have emerged. Nevertheless, problems remain to be resolved in the field of modeling in relation to tradeoffs in classification. The focus remains on imaging, signal variability, and sensor noise. This study aims to determine the usefulness of Inertial Measurement Unit (IMU) data for activity recognition and compares classical machine learning methods with a …
Modeling Economic Effects On Climate Change, Ahmed Abdulqader
Modeling Economic Effects On Climate Change, Ahmed Abdulqader
Theses
Climate change represents one of the most critical challenges facing the global economy today. While environmental impacts receive considerable attention, the economic implications are equally significant and require rigorous quantitative analysis. This thesis investigates the relationship between climate change and major economic indicators including GDP growth, inflation, trade balances, and employment across 50 countries from 1990 to 2023. The research employs a comprehensive multi-methodological approach combining panel data econometrics, time-series analysis, and machine learning techniques. Fixed-effects and random-effects panel regression models reveal statistically significant relationships between climate-related disaster frequency and economic performance. Specifically, disaster count demonstrates a positive coefficient of …
A Ux Approach To Improving Patient Experience In Healthcare, Lingxin Sun
A Ux Approach To Improving Patient Experience In Healthcare, Lingxin Sun
Theses
Doc Ease is a UX research and design project that addresses the emotional and functional difficulties patients experience before visiting a doctor. Through user interviews, competitive analysis, and design iteration, this project identified key user pain points such as unclear appointment processes, lack of trust, and pre-visit anxiety. The resulting mobile app offers clear booking tools, visual doctor information, medication reminders, and an emotional wellness module to help patients prepare with confidence. The project contributes to the field of healthcare UX by integrating functional usability with emotional care, proposing a design framework that centers patient experience in both logic and …
Beyond Detection: A Batch-Based Ai Framework For Temporal And Event-Correlated Trend Analysis Of Misinformation On Social Media, Vishnu Tejas Vijayaraghavan
Beyond Detection: A Batch-Based Ai Framework For Temporal And Event-Correlated Trend Analysis Of Misinformation On Social Media, Vishnu Tejas Vijayaraghavan
Theses
The rapid spread of misleading information on social media influences public behaviour and complicates crisis communication. Although transformer models such as BERT accurately detect misinformation at the post level, most studies analyse posts in isolation and overlook howmisinformation fluctuates over time or responds to major events. This study addresses that gap by developing an end-to-end analytical workflow that integrates BERT-based classification with temporal aggregation, topic clustering, anomaly detection, and event alignment. The analysis uses 10,700 COVID-19–related tweets (6,420 training, 2,140 validation, and 2,140 testing). Because timestamps were unavailable, synthetic timestamps were assigned using an evenly spaced date range between 1 …
Hyaluronic Acid Loaded With Aloe Vera-Derived Extracellular Vesicles: A New Bioactive Approach For Fibrotic Scarring, Maria Camila Ceballos Santa
Hyaluronic Acid Loaded With Aloe Vera-Derived Extracellular Vesicles: A New Bioactive Approach For Fibrotic Scarring, Maria Camila Ceballos Santa
Theses
Disruptions in wound healing can result in pathological outcomes ranging from chronic nonhealing wounds to excessive fibrotic scarring. Hypertrophic scars and keloids are hallmarks of this dysregulation, characterized by abnormal collagen deposition, persistent myofibroblast activation, and disorganized extracellular matrix (ECM) remodeling. Chronic inflammation and oxidative stress play central roles by increasing reactive oxygen species (ROS), which damage essential macromolecules and sustain pro-inflammatory signaling, while promoting the transdifferentiation of fibroblasts into myofibroblasts and the excessive production of ECM proteins, such as collagen and α-smooth muscle actin (α-SMA). This fibrotic cascade leads to tissue stiffness, contractility, and disfigurement, affecting the well-being of …
Exploring The Relationship Between Social Media And Anxiety In Deaf Community Students: A Mixed-Methods Approach., Gigi Zheng
Theses
The mental health of Deaf individuals, particularly in relation to social media engagement, is an understudied area amid growing global concerns about anxiety disorders. Deaf individuals face unique challenges, including communication barriers, social isolation, and stigma, all of which can heighten anxiety levels. Although social media offers valuable opportunities for connection and self-expression, it may also amplify stress and feelings of inadequacy when accessibility barriers persist. This mixed-methods study examined anxiety among Deaf college students and explored the cultural validity of two widely used anxiety measures—the State-Trait Anxiety Inventory (STAI) and the Beck Anxiety Inventory (BAI). Quantitative data were collected …
Ecotheology For Kids, Lana Glenn
Ecotheology For Kids, Lana Glenn
Theses
This project includes research into the eco-anxiety of children and how ecotheology may help ease the children’s minds. This project is meant as a sign of hope in the climate crisis; there are so many reasons to look forward to ecological improvements for the Earth. As adults, we should remind children of these reasons to be hopeful for the future. This 24-page book has illustrations with prayers to help calm the readers, while the cover is informational and inviting.
The Vampire In Video Games: Narrative Structures, Game Mechanics, And Cultural Significance, Ricardo Longo Minervino
The Vampire In Video Games: Narrative Structures, Game Mechanics, And Cultural Significance, Ricardo Longo Minervino
Theses
This thesis examines how vampires are represented in video games by analyzing narrative structures, game mechanics, and cultural meaning. Using the existing games of Vampyr, V Rising, Vampire: The Masquerade – Bloodlines, The Sims 4: Vampires, Skyrim: Dawnguard, Baldur’s Gate 3, and Bloodlines 2, the study identifies which design strategies successfully create an engaging and believable vampire experience for the player, as well as determining which development decisions could hurt the experience for players. Using formalism, symbolism, feminist methodology, and player reception theory, this thesis argues that vampire games function best when players confront moral dilemmas, experience consequences for feeding …
Detecting Illicit Bitcoin Transactions On The Dark Web, Abdulla Alsuwaidi
Detecting Illicit Bitcoin Transactions On The Dark Web, Abdulla Alsuwaidi
Theses
Dark web markets use Bitcoin and related cryptocurrencies to transfer and launder proceeds of crime while obscuring the real-world identities of operators. This creates an increasingly challenging environment for regulators and law-enforcement agencies, who must analyse suspi- cious transactions on decentralised, public, pseudonymous blockchains and increasingly dense and noisy Bitcoin transaction graphs. This thesis investigates whether, and how, blockchain analytics and machine learning can help detect illicit transactions on Bitcoin networks. The first part of the thesis is a systematic literature review of recent contributions from academia and industry that examine major solution approaches for identifying illicit flows on public …
Persuasive Pathways In Digital Apologies: The Role Of Persuasion Routes In Engagement With Youtuber Apology Videos, Darrin Majocha
Persuasive Pathways In Digital Apologies: The Role Of Persuasion Routes In Engagement With Youtuber Apology Videos, Darrin Majocha
Theses
This study explores how viewers process YouTube apology videos and how those processing methods relate to their judgments of the creator and their willingness to continue engaging with the channel. Guided by the Elaboration Likelihood Model, a single-session online survey experiment randomly assigned 413 adult participants to watch one of five publicly available apology videos from well-known YouTubers. After viewing, participants reported the extent to which they engaged in central versus peripheral processing, rated the creator's credibility and the apology's sincerity, and indicated their intentions to engage. Central processing was positively associated with engagement intentions, whereas peripheral processing was weakly …
Transgender Adolescents' Healthcare Rights: The Gap Between Gender-Affirming-Care (Gac) Policymakers’ And Healthcare Providers’ Goals, Jayden Galli
Theses
Transgender people have marginalized healthcare experiences that result in decreased health outcomes. For transgender adolescents, gender-affirming-care (GAC) is even more difficult to access and being restricted with increasing frequency. This mixed methods study was conducted to examine transgender healthcare through the gaps between GAC policymakers’ and healthcare providers’ goals. General research has focused on the relationship between GAC and transgender health, GAC policy development, and the discrepancies between GAC policy outcomes and medical professionals’ advice. This leads to the research question about how policymakers and healthcare providers can collaborate to bridge the gap between GAC policies and transgender minors' healthcare …
Physics Meets Data: Merging Physics-Based Methods With Deep Learning To Model Complex Systems, Maryam Toloubidokhti
Physics Meets Data: Merging Physics-Based Methods With Deep Learning To Model Complex Systems, Maryam Toloubidokhti
Theses
Accurate modeling of complex systems is crucial in domains such as healthcare, where personalized diagnosis and treatment planning are essential. Traditional physics-based models provide structured, theoretically grounded insights but are often computationally intensive and constrained by simplified assumptions that limit adaptability to patient-specific conditions. In contrast, data-driven models are computationally efficient and capable of capturing complex patterns, yet they often lack interpretability and fail to incorporate essential physical principles, reducing robustness and generalization. This disconnect between mechanistic understanding and computational practicality presents significant challenges in critical applications such as healthcare, where both physical accuracy and real-time performance are vital. To …
The Impact Of The 2008 Financial Crisis On Crime And Cybercrime In The United States, Rashed Adel Alsuwaidi
The Impact Of The 2008 Financial Crisis On Crime And Cybercrime In The United States, Rashed Adel Alsuwaidi
Theses
This thesis will examine how the traditional crime and cy- were affected by the 2008 financial crisis. United States are also experiencing a rise in crime between 2005 and 2012. Based on the FBI data at the national level. The Internet Crime Complaint Center (IC3), Uniform Crime Reports and important economic indicators. The study, which involves tors, including unemployment, GDP, rates of foreclosures, and mortgage rates, is a combination. correlationbased interpretation supported by exploratory descriptive trend analysis. model-fit checks. The results indicate that contrary to the conventional expectations, violent and property crime also maintained their long-term reduction during the period …
Predicting Employee Attrition With Machine Learning: Data-Driven Strategies For Enhancingworkforce Retention, Ali Almheiri
Predicting Employee Attrition With Machine Learning: Data-Driven Strategies For Enhancingworkforce Retention, Ali Almheiri
Theses
In this research, the dual prediction and prescription model is developed and validated so that this model can not only predict employee turnover risk, but it also proposes the appropriate retention interventions, which apply across industries. On the basis of the IBM HR Analytics Attrition dataset (n=1,470), we preprocessed demography, job and satisfaction variables and trained three machine-learning classifiers, Random Forest, Logistic Regression and XGBoost to predict voluntary turnover. XGBoost model recorded the best discrimination (AUC=0.87), sensitivity (0.76), and specificity (0.81), which signifies strong predictive power. Analysis of feature-importance was conclusive with time, rate of frequent business travel and compensation …