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Articles 661 - 690 of 11541
Full-Text Articles in Entire DC Network
Determining Sustainable Urban Renewal: A Case Of Quantifying Sustainability For Adaptive Reuse Within Mumbai’S Textile Mill Sector, Arundhati Rajesh Kawlekar
Determining Sustainable Urban Renewal: A Case Of Quantifying Sustainability For Adaptive Reuse Within Mumbai’S Textile Mill Sector, Arundhati Rajesh Kawlekar
Theses
This study explores adaptive reuse as a sustainable approach to urban development in Mumbai, India, focusing on the revitalization of a heritage textile mill site. It investigates how historical significance and evolving community needs can shape design decisions, while assessing sustainability through Life Cycle Analysis (LCA) and energy efficiency metrics. Mumbai’s defunct textile mills, once central to its industrial growth, now pose challenges to urban vitality. Through a literature review, the paper examines their historical, social, and cultural relevance and the decline of the mill industry. Adaptive reuse emerges as a key strategy to reimagine these structures, offering an environmentally …
Through Legitimate Dissent, The Supreme Court Repairs Itself, Afnaan A. Qureshi
Through Legitimate Dissent, The Supreme Court Repairs Itself, Afnaan A. Qureshi
Theses
The decisions of the Supreme Court of the United States, along with its reasoning, influence the direction and scope of historical events. Through an analysis of landmark dissents from four of the worst Supreme Court decisions, Curtis’ dissent in Dred Scott v. Sandford (1857), Harlan’s dissent in Plessy v. Ferguson (1896), Holmes’ dissent in Abrams v. United States (1919), and Murphy’s dissent in Korematsu v. United States (1944), we can take steps towards catalyzing its self repair by stepping away from digital echo chambers and engaging in legitimate dissent. The four cases marked turning points in the efforts to protect …
A Bert-Resnet Cross-Attention Fusion Network And Modality Utilization Assessment For Multimodal Sentiment Classification, Ronen G. Gold
A Bert-Resnet Cross-Attention Fusion Network And Modality Utilization Assessment For Multimodal Sentiment Classification, Ronen G. Gold
Theses
This study explores the growing field of Multimodal Sentiment Analysis (MSA), focusing on understanding how advanced fusion techniques can improve sentiment prediction in social media contexts. As platforms like X and TikTok continue to expand and facilitate sharing sentiment through digital media, there is an increasing need for neural network architectures that can accurately interpret sentiment across modalities. We implement a model using BERT for textual features and ResNet for visual features. A cross-attention fusion module aligns the modalities for joint representation. We conduct experiments on the MVSA-Single and MVSA-Multiple datasets, which contain over 5,000 and 17,000 labeled text-image pairs. …
Enhancing Influence Estimation In Gradient Boosted Decision Trees Through Hierarchical Analysis, Anurag Choubey
Enhancing Influence Estimation In Gradient Boosted Decision Trees Through Hierarchical Analysis, Anurag Choubey
Theses
This report presents a novel influence function for gradient-boosted decision trees (GBDTs), a widely-used class of predictive models. Influence estimation aims to quantify how individual training samples affect a model’s predictions, offering valuable insights for model debugging, data quality analysis, and in- terpretability. Existing influence functions for GBDTs—such as LeafInfluence, LeafInfluenceSP, and BoostIn—have shown varying degrees of success, with BoostIn currently recognized as the state-of-the-art in terms of estimation quality and computational efficiency. In this work, we propose BoostInLCA, a new influence function that extends BoostIn by incorporating information from non-leaf nodes via the Lowest Common Ancestor (LCA) path, thereby …
Beyond The Badge: Predicting Military Employee Attrition In The Police Force, Alia Abdulla Alhajji
Beyond The Badge: Predicting Military Employee Attrition In The Police Force, Alia Abdulla Alhajji
Theses
This study explores the issue of employee attrition within the military police force, with a focus on predicting which employees are at risk of leaving. Attrition in law enforcement is costly and disruptive, especially in roles that require long training periods and operational readiness. The research specifically targets the internal organizational factors influencing turnover in military police environments and aims to leverage machine learning models to support the early identification of high-risk individuals. Guided by the CRISP-DM framework, the study followed a structured process across six stages: business understanding, data exploration, preparation, modeling, evaluation, and insight generation. A simulated dataset …
Factors Influencing Community Assembly Of The Amphibian Microbiome In Rochester, Ny, Thomas R. Minahan
Factors Influencing Community Assembly Of The Amphibian Microbiome In Rochester, Ny, Thomas R. Minahan
Theses
Amphibians are crucial in wetlands and, by extension, our planet. As predator and prey, amphibians serve as keystone species, vital for the continued equilibrium in their wetland ecosystems. However, the global amphibian population is currently threatened by the spread of a pathogenic fungus known as Batrachochytrium dendrobatidis (Bd). Over the past thirty years, Bd has spread worldwide, threatening hundreds of amphibian species. The environmental factors that influence microbial community assembly in amphibians are key to developing interventions that can protect amphibians from disease. This research examines the abiotic and biotic factors influencing microbial community composition in amphibians of Rochester, New …
Under The Mask: Labeling And Self-Perception In Augmented Reality, Ruiyuan Guo
Under The Mask: Labeling And Self-Perception In Augmented Reality, Ruiyuan Guo
Theses
Under the Mask is a speculative AR experience that critically explores how social labels shape both perception and self-perception in everyday life. The project reimagines augmented reality not as a technological novelty, but as a conceptual mirror—a way to visualize how identity is continuously negotiated in social space. Users interact with two distinct labeling functions: when they assign a tag to themselves, it becomes visible to everyone, symbolizing the ways in which self-identification enters public discourse. In contrast, when users label others, those tags remain private—visible only to the individual user—highlighting how our assumptions primarily influence our own vision, not …
Bodies Unseen: Hysteria’S Stain On Women’S Healthcare, Layla Dehrab
Bodies Unseen: Hysteria’S Stain On Women’S Healthcare, Layla Dehrab
Theses
Bodies Unseen is a 5-minute motion graphics piece accompanied by a 12-page zine that explores the historical and ongoing dismissal of women’s pain within the medical system, rooted in the legacy of hysteria. Through the fictionalized stories of Ada, Rosa, and Mabel-women from different time periods who face misdiagnosis and neglect, the project illustrates the persistent gender bias in healthcare. Drawing from historical records, feminist theory, and contemporary research on medical inequity, this work connects past injustices to modern-day disparities in diagnosis and treatment. The animation and zine work in tandem to educate viewers and encourage dialogue about the systemic …
What’S Coco Eating Today: Using Fragmented Time To Reduce Stress, Yaxuan Wang
What’S Coco Eating Today: Using Fragmented Time To Reduce Stress, Yaxuan Wang
Theses
In modern society, electronic mobile devices have become an integral part of life and entertainment. From a developmental perspective, the abundance of virtual content has brought significant changes in emotional, cognitive, and social aspects. On this background, the rise of the gaming industry has made 'digital games' a common form of entertainment. As games become a normalized part of daily life, the variety of game types has expanded greatly. This led me to consider: through interaction design and using games as a medium, is it possible to reduce users' stress in a short time and provide positive emotional feedback? Based …
Ai Emotional Companion App, Ruyi Liu
Ai Emotional Companion App, Ruyi Liu
Theses
"Lumi" is an AI emotional companion app designed to provide personalized, immersive, and emotionally supportive experiences. The project explores how customizable virtual characters can fulfill the growing emotional and social needs of users through multimodal interaction, intimacy-building systems, and gamified engagement. By combining user interviews, competitive analysis, and iterative prototyping, this thesis investigates how design strategies can strengthen the user’s emotional bond with an AI character. The final product presents a flexible platform where users can create unique AI companions, interact in diverse ways, and develop lasting emotional connections. This work contributes to the field of emotional UX and digital …
Sales Opportunities Lead Qualification In B2b Market, Hajar Hussain Ahli
Sales Opportunities Lead Qualification In B2b Market, Hajar Hussain Ahli
Theses
This thesis addresses the challenge of inefficient lead qualification in the business-to-business (B2B) market by applying machine learning techniques to predict the likelihood of winning a sales opportunity. Using a real-world dataset of over 78,000 records and 17 variables, the study aims to improve how sales teams identify and prioritize high-conversion leads. A thorough data preparation process was conducted, including handling of missing values, outlier detection, and under-sampling to resolve class imbalance between won and lost opportunities. After thorough data cleaning, preprocessing, and under-sampling to address class imbalance, five machine learning models were developed: Logistic Regression, Random Forest, Neural Network, …
Mosaic: Sustainable Housing For A Displaced World, Vaibhav Balasubramanian
Mosaic: Sustainable Housing For A Displaced World, Vaibhav Balasubramanian
Theses
The global refugee crisis demands solutions that go beyond just providing yet another roof over the head. Tents in these camps/settlements are almost always crowded, temporary, poorly made, and often fail to offer any comfort, privacy, or a sense of normalcy in life. This project explores an alternative: modular housing that can be set up quickly and tailored to different needs. These units can be assembled faster, reducing the time refugees spend in unstable and unfavorable conditions significantly. The modular nature of these units allows for customization, adapting to various family sizes. By offering personal space, privacy, stability, and durability, …
Transforming Rural Schools: Adaptive Reuse For Sustained Community And Sustainability, Christine Limbert
Transforming Rural Schools: Adaptive Reuse For Sustained Community And Sustainability, Christine Limbert
Theses
In many small towns, there are little to no places for gathering and community to exist except for an often community central location of their school, even though the schools become a community hub they are not immune to the effects of the outside world, and with a population decline trend, they face the threat of becoming closed from low enrollment and inefficient use. There could, however, potentially be a different solution other than consolidation, partial adaptive reuse. By analyzing input from those who would be affected by the school closure, analyzing previous closure and their effect on the smaller …
Intellimad: A Framework For Secure Machine Learning Models Evaluation And Fine-Tuning In Federated Setting, Dmitrii Korobeinikov
Intellimad: A Framework For Secure Machine Learning Models Evaluation And Fine-Tuning In Federated Setting, Dmitrii Korobeinikov
Theses
In contemporary artificial intelligence (AI) appli- cations, Machine Learning (ML) models are core components enabling AI-driven functionalities, yet selecting and fine-tuning a model and its hyperparameters remains challenging. ML model architecture, as well as key model training parameters, such as the number of training epochs, batch size, and learning rate, are highly dependent on both the dataset modalities and the specific task resolved in a particular application. More sophisticated execution setups may require determination of additional environment-related parameters, such as identifica- tion of computational capabilities required for execution of a particular AI-driven task, or discovery and establishment of desired security-related …
Back To The Basics: Extracellular Protein Interaction Networks Of The Human Infant Immune System, Mavis Amity Irwin
Back To The Basics: Extracellular Protein Interaction Networks Of The Human Infant Immune System, Mavis Amity Irwin
Theses
Datamining without an age filter proves challenging, especially when searching for direct data from human infants. Although online databases provide immune interaction networks, they often lack information about the age of data sources, resulting in categorizations as age-unspecified. This limitation underrepresents the physiology of naïve immune systems in infants, particularly since full-term infant immunity transitions to an adult-like phenotype between 24 and 30 months of age. This study aims to reconstruct an age-specific immune interaction network for full-term infants by integrating literature-based evidence with existing online database content. A list of 60 extracellular protein candidates involved in immune responses was …
Predicting The Probability Of Crime Related Danger In Los Angeles, Joshua Oghenetega Okpako
Predicting The Probability Of Crime Related Danger In Los Angeles, Joshua Oghenetega Okpako
Theses
This thesis examines the use of advanced machine learning to predict crime danger in Los Angeles, where 2023 violent crime rates (503 per 100,000) surpass the national average (363.8 per 100,000). Rooted in theories like social disorganization and victim vulnerability, it addresses the lack of combined victim-centric modeling by focusing on three questions: (1) Do blended ensemble models outperform individual models in predicting crime danger? (2) Can unsupervised learning techniques enhance supervised models’ accuracy through label generation or augmentation? (3) How can we interpret accurate machine learning models' decision-making processes? Using historical crime data from Los Angeles (2020–2025) and various …
Data-Driven Prediction Of Vehicle Residual Value In The Uae Automotive Industry, Meera Al Hashmi
Data-Driven Prediction Of Vehicle Residual Value In The Uae Automotive Industry, Meera Al Hashmi
Theses
In this master’s thesis, machine learning methods are applied to predict the residual value of a vehicle, focusing on the problem of estimating the vehicle’s price after sale. The research addresses some of the most important drivers of depreciation which include market segmentation, country, region-specific details, transmission type, and some numerical values obtained through factor analysis. This is very important to the automotive industry, leasing businesses, and financial institutions. The data was collected from the open-source online marketplace Dubizzle and contains 25 variables and 62,922 cases. The initial data posed notable challenges as there were non-standardized feature values, incomplete data …
Innovating Criminal Justice: Predictive Analytics For Effective Recidivism Management, Dina Ali Haidar
Innovating Criminal Justice: Predictive Analytics For Effective Recidivism Management, Dina Ali Haidar
Theses
Recidivism—the tendency of previously convicted individuals to reoffend—poses significant challenges to criminal justice systems worldwide. In the United States, a study by the Bureau of Justice Statistics revealed that approximately 68% of released prisoners were rearrested within three years, and 83% within nine years (Bureau of Justice Statistics, 2018). These high rates underscore systemic deficiencies in rehabilitation processes and resource allocation. Traditional risk assessment tools often rely on static factors, failing to account for the dynamic and individualized nature of reoffending risks. This limitation highlights the need for innovative, data-driven methodologies to enhance offender management strategies. This study proposes a …
Predicting And Forecasting University Rankings In The Uae Using Machine Learning, Fatma Ibrahim Ahmad
Predicting And Forecasting University Rankings In The Uae Using Machine Learning, Fatma Ibrahim Ahmad
Theses
Higher Education Institutions (HEIs) play a vital role in advancing knowledge economies, and institutional rankings are increasingly used as global benchmarks of academic performance and reputation. In the context of the United Arab Emirates (UAE), enhancing institutional competitiveness in global rankings aligns with national strategies such as UAE Vision 2030 and the Centennial Plan 2071. This research applies machine learning (ML) techniques to develop predictive models that forecast institutional ranking outcomes, enabling data-driven planning and continuous academic improvement. The study utilizes a dataset compiled from the QS World University Rankings (2020–2024), cross- referenced against the institutional listings maintained by the …
Ai-Driven Prediction Of Flight Cancellations: A Machine Learning Approach In Minimizing Airline Disruption, Hind Nasser
Ai-Driven Prediction Of Flight Cancellations: A Machine Learning Approach In Minimizing Airline Disruption, Hind Nasser
Theses
This thesis investigates the use of machine learning to predict flight cancellations, aiming to reduce operational disruption and improve airline decision-making. The research is motivated by the need for more proactive strategies in aviation, where flight cancellations often result in financial losses and customer dissatisfaction. The study is framed within the CRISP-DM methodology and demonstrates how historical flight data can be transformed into actionable insights using structured analytics. The research addresses three core questions: how effectively machine learning can predict cancellations, which evaluation metrics are most suitable in an imbalanced context, and how model outputs can support airline operations. A …
Personalized Nutrition Recommendations For Arab Communities: Transforming Diet And Health Through Machine Learning, Khalfan Aldoobi
Personalized Nutrition Recommendations For Arab Communities: Transforming Diet And Health Through Machine Learning, Khalfan Aldoobi
Theses
A lack of cultural understanding in traditional nutrition approaches prevents proper adherence to healthy dietary patterns among individuals. The Arab population faces unique challenges due to cultural dietary customs and lifestyle changes that have made obesity and diet illnesses major global public health challenges. The rapid shift to high-calorie but undernourished foods and less physical activity has resulted in alarming rate increases of obesity, cardiovascular diseases, and type 2 diabetes. The lack of cultural understanding in traditional nutrition approaches prevents proper adherence to healthy dietary patterns among individuals. This study focuses to fills the existing gap by applying Artificial Intelligence …
Innovative Solutions For Data Accessibility: Utilizing Synthetic Data In Dewa Operations, Saif Khalid Alshahin
Innovative Solutions For Data Accessibility: Utilizing Synthetic Data In Dewa Operations, Saif Khalid Alshahin
Theses
Smart‑meter data are pivotal to modern demand‑side management and predictive maintenance, yet strict confidentiality rules at Dubai Electricity and Water Authority (DEWA) hinder internal access. Synthetic data generated by Generative Adversarial Networks (GANs) offers a promising privacy‑preserving alternative, potentially unlocking analytics without exposing customer information. This study assesses the ability of three GAN variants—vanilla GAN, Tabular GAN (TGAN), and Conditional Tabular GAN (CTGAN)—to replicate real consumption patterns. A publicly available \emph{Smart Meters in London} daily dataset comprising 3.51 million records was utilised. After exploratory data analysis (EDA) and cleansing, identifier (\texttt{LCLid}) and date (\texttt{day}) variables were removed, leaving seven numerical …
Modelling And Load Frequency Control (Lfc) Design Of Microgrid Frame-Worked As Technological Norm To Multi Energy System (Mes), Mekonnen Shewarega Worku
Modelling And Load Frequency Control (Lfc) Design Of Microgrid Frame-Worked As Technological Norm To Multi Energy System (Mes), Mekonnen Shewarega Worku
Theses
In today's world, the trend of using renewable energy sources as an alternative energy source is becoming more and more common due to various driving factors, such as energy scarcity (fossil fuel depletion, etc.) and environmental issues (carbon footprint). This trend is leading to a steady increase in the penetration of renewable energy sources (RESs) through microgrid (MG), which is formed from combination of various distribution energy sources (DERs). The inherent intermittent nature of RESs coupled with abrupt load changes can instigate sustained frequency fluctuations and can keep the frequency deviation out of the allowable range that leads to an …
Towards Vision Intelligence-Based Liver Surgery, Zixin Yang
Towards Vision Intelligence-Based Liver Surgery, Zixin Yang
Theses
Despite advancements in surgical interventions, modern procedures still heavily rely on surgeons' expertise, requiring extensive training while maintaining limited accuracy. Although image guidance systems have been developed, “GPS-like” surgical navigation systems have yet to become standard practice due to their high costs and accuracy limitations. This thesis aims to enhance surgical navigation and mitigate some of its current limitations by leveraging vision intelligence: integrating image processing, modeling, and computer vision to extract rich, underlying information from images. The key to achieving these improvements lies in improving surgical perception, which involves understanding the spatial relationships between the endoscopic camera, surgical instruments, …
Crafting Human-Ai Collaborative Analysis For Usability Evaluations, Emily Kuang
Crafting Human-Ai Collaborative Analysis For Usability Evaluations, Emily Kuang
Theses
In the rapidly evolving domain of human-computer interaction (HCI), ensuring a high-quality user experience (UX), which encompasses all aspects of a user’s interaction with an interface, is critical to the success and adoption of technology. Central to this is the concept of usability: the degree to which an interface can be effectively, efficiently, and satisfactorily used by its intended audience. Usability testing is a key method for uncovering usability problems, relying on structured evaluations involving real users. However, traditional approaches to analyzing usability test recordings—where UX evaluators observe user behavior and verbalizations while taking notes—are labor-intensive and prone to human …
A Review Of Smart Public Transport Systems: Challenges, Technological Innovations, And Future Directions, Ahmed Masam Alfalasi
A Review Of Smart Public Transport Systems: Challenges, Technological Innovations, And Future Directions, Ahmed Masam Alfalasi
Theses
Urbanization has created greater demand for effective and sustainable public transport systems in smart cities. Yet, overcrowding, congestion, and old infrastructure remain the main challenges to the effectiveness of these systems. This literature review discusses the major issues affecting smart public transport, such as reliability issues, environmental sustainability, and improved integration and coordination between modes of transport. Technologies like the Internet of Things (IoT), artificial intelligence (AI), and big data analytics are being applied to enhance public transportation efficiency, alleviate congestion, and improve passenger experience. Qualitative research methods were used, relying on secondary data from academic journals, government reports, and …
Future Unleashed: Reimagining Marketing Strategies With Future Foresight, Afra Sultan Al Suwaidi
Future Unleashed: Reimagining Marketing Strategies With Future Foresight, Afra Sultan Al Suwaidi
Theses
In today’s fast-paced and dynamic business landscape, marketing plays a crucial role in influencing business strategy and decision-making in an organisation. Marketing not only helps organisations identify and anticipate trends, threats, and opportunities, but also enables them to formulate and implement effective strategies to capitalise on these insights and achieve the organisation’s vision and goals. Future Foresight in marketing empowers organisations to stay ahead of the curve and gain a deeper understanding of the target audience and industry landscape. The evolving nature of marketing driven by advancements in technology, particularly artificial intelligence, machine learning, and digital marketing channels, makes it …
Investigating The Performance Variation For Graphene-Based Field-Effect Transistor, Tzu-Jung William Huang
Investigating The Performance Variation For Graphene-Based Field-Effect Transistor, Tzu-Jung William Huang
Theses
As silicon CMOS technology approaches its scaling limits, two-dimensional (2D) materials such as graphene offer promising alternatives due to its atomically thin material property and high carrier mobility. Graphene field-effect transistors (GFETs) are especially suited for high-frequency and RF applications; however, large-scale integration is hindered by substantial device-to-device variability. Primary contributors include inconsistent graphene transfer, contact resistance, poor dielectric interfaces, and underlying substrate topography. This work presents a comparative study of three GFET architectures to address variability: (a) raised Al gate with 15 nm Al2O3, (b) raised Al gate with monolayer hexagonal boron nitride (hBN), and (c) recessed Al gate …
Steering Through Change: How Aging Eyes And Stroke-Induced Vision Loss Affect Driver Control, Arianna P. Giguere
Steering Through Change: How Aging Eyes And Stroke-Induced Vision Loss Affect Driver Control, Arianna P. Giguere
Theses
Imaging system engineers could greatly benefit from understanding how biological systems have evolved to solve difficult imaging problems. In this thesis, we study how the human visual system has evolved to address the complex task of visually-guided steering, particularly as a person ages and experiences a prevalent type of vision loss from stroke called cortical blindness (CB) that results in the loss of one quarter to one half of the visual field. In a series of three studies, we test the hypothesis that the effects of CB on vision and steering extend beyond those that accompany healthy aging, and we …
You! Me! Dancing!, Aaron Ickler
You! Me! Dancing!, Aaron Ickler
Theses
YOU! ME! DANCING! is a 3-piece photo installation consisting of photographs of myself and the Rochester area furry community. YOU! contains 145 medium format slides across two light panels exploring my relation to the masculine aspects of the Furry Fandom through staged studio portraits, intimate looks into furries in their natural habitats, and moments from local meetups. ME! uses large format sheet film layered in acrylic to highlight the change of character of wearing a fursuit, featuring my own custom fursuit. Lastly, DANCING!, is a visually inaccessible 80 image slideshow in which the pace and interval timed start of the …