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Articles 961 - 990 of 21692
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Energy Forecasting Inaccuracies And Their Direct Impact On Grid Performance, Rashed Khalid Alboom
Energy Forecasting Inaccuracies And Their Direct Impact On Grid Performance, Rashed Khalid Alboom
Theses
Accurate energy forecasting is critical for the stability, efficiency, and cost-effectiveness of modern power grids, particularly as renewable energy sources like solar and wind become more prominent. The variability of these sources presents challenges for traditional forecasting models, which struggle with non-linearity, external dependencies, and evolving grid conditions. These limitations lead to operational inefficiencies, grid instability, and increased financial risks. This study investigates the effectiveness of traditional statistical models, advanced machine learning techniques, and hybrid forecasting approaches to enhance prediction accuracy and grid performance. Using real-world datasets from Kaggle, including historical energy generation, consumption, pricing, and weather variables, this research …
Customer Flow Prediction At Emirates Id Centers, Humaid Ahmed Saeed Alkhuroosi
Customer Flow Prediction At Emirates Id Centers, Humaid Ahmed Saeed Alkhuroosi
Theses
Emirates ID centers face significant resource management challenges due to fluctuating customer traffic, leading to long wait times, customer dissatisfaction, and inefficient resource use. This thesis explores the application of time series analysis to predict customer traffic at Emirates ID centers, focusing on the Autoregressive Integrated Moving Average (ARIMA) and Long Short-Term Memory (LSTM) models. The primary research question is: “Can historical queue data from the Qmatic system be effectively used to forecast customer traffic at Emirates ID centers?” To answer this question, 800,000 observations of historical ticket issuance data from the Qmatic queue management system were analyzed. The study …
Roads Of Tomorrow: Augmented Reality For Enhanced Road Maintenance, Nasser Humaid Alshamsi
Roads Of Tomorrow: Augmented Reality For Enhanced Road Maintenance, Nasser Humaid Alshamsi
Theses
The rapid deterioration of roads creates major obstacles that affect public security, urban movement capacity, and economic durability. Standardized road maintenance operations depend heavily on human inspections that prove time-consuming while being labour-intensive and subject to human mistakes. Implementing Augmented Reality (AR) with Point Cloud Data represents a smart approach that improves delivery efficiency in road maintenance procedures for modern cities. AR enables real-time visual content and interactive displays through this research, yet Point Cloud Data delivers detailed, precise road inspections through high-definition three-dimensional mapping. These technologies are evaluated for their usability, effectiveness, and adoption barriers in research that advance …
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 …
A Prototype High Power Dc-Dc Converter For Regulating Generator Output Voltage In A Series Hybrid Electric Vehicle, Alex Currie
A Prototype High Power Dc-Dc Converter For Regulating Generator Output Voltage In A Series Hybrid Electric Vehicle, Alex Currie
Theses
As fully electric and hybrid electric vehicles become more commonplace, a strong incentive for innovation in electric powertrain technology has been created. Though the instantaneous power available from an electric motor may appeal to consumers of powersports vehicles, this has been an area with relatively little advancement towards electric architectures. One primary concern of electrifying such a platform is the need for large battery packs that tend not to perform well in the harsh weather conditions often seen in powersports such as snowmobiling. As such, hybrid electric architectures may prove to be a successful middle ground between fossil fuels and …
Uvm Based Verification Of Ee621 Risc Processor Module, Collin Neidel
Uvm Based Verification Of Ee621 Risc Processor Module, Collin Neidel
Theses
In the process of digital design, the majority of efforts are focused on verification. This is because a proper verification environment can help engineers discover bugs that otherwise would have flown under the radar. On the other hand, a poorly designed verification environment could fail to fully confirm the device’s functionality and leave the customer with a buggy mess. For obvious reasons, this should be avoided at all costs, hence the emphasis on functional verification and validation efforts. Throughout time, the complexity of the average design under test (DUT) has increased dramatically, making verification a significant challenge for today’s verification …
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. …
An Analysis Of Dc-Dc Converter Efficiencies, Carley Visser
An Analysis Of Dc-Dc Converter Efficiencies, Carley Visser
Theses
With the increase in technology used in everyday life, the need for DC-DC converters has continued to increase. The efficiency of these converters is an essential parameter as an increase in a few percent can increase battery life by hours. There are several different factors that effect the efficiency of converters ranging from temperature, component selection, quiescent current and more. In this paper, a series of eleven DC-DC converters will be designed and tested in order to observe how the efficiencies and other parameters compare to the values provided in this datasheet. For this investigation two different PCBs were designed, …
Sustainable Retrofits: The Balance Between Energy Efficiency And Embodied Energy, Alexander Narvaez
Sustainable Retrofits: The Balance Between Energy Efficiency And Embodied Energy, Alexander Narvaez
Theses
This thesis looks at how to balance energy efficiency with embodied energy in small commercial retrofits, focusing on restaurant buildings. Rather than tearing down older buildings and starting from scratch—something that wipes out all the embodied energy already invested—retrofitting can improve performance while preserving what's already there. Using EnergyPlus for operational energy modeling and the Athena Impact Estimator for embodied energy analysis, this study compares different retrofit scenarios. These include retrofitting one, two, or all three major assemblies (walls, roofs, and floors) to see how each combination affects total emissions over time. The results show that not all retrofits are …
Investigating The Relationship Between Cellular Senescence And Pulmonary Fibrosis, Crystal Lee
Investigating The Relationship Between Cellular Senescence And Pulmonary Fibrosis, Crystal Lee
Theses
This study investigates the complex relationship between cellular senescence, aging, and pulmonary fibrosis through a comprehensive analysis of bulk RNA-seq data from patients with idiopathic pulmonary fibrosis (IPF), chronic obstructive pulmonary disease (COPD), and scleroderma. Using differential expression (DE) and age-associated differential expression (AADE) analyses, we revealed a paradoxical pattern: senescence-related gene sets were significantly downregulated in disease comparisons but progressively upregulated with aging within these same diseases. Gene set enrichment analysis (GSEA) revealed that gene sets associated with DNA damage/telomere stress and oxidative stress were among the most enriched senescence inducers in fibrotic disease states, while cellular senescence and …
Methionine Matters: Comparative Dynamic Insights Into Viral Inhibition Of Host Rna Export Via Rae1-Nup98, Skye Bixler
Methionine Matters: Comparative Dynamic Insights Into Viral Inhibition Of Host Rna Export Via Rae1-Nup98, Skye Bixler
Theses
Over time, viruses have evolved a myriad of mechanisms to gain an advantage in the virus-host battle, such as inhibiting host mRNA export through RNA Export Factor 1 (Rae1) and Nucleoporin 98 (Nup98). This strategy employed by the Vesicular Stomatitis Virus (VSV) M protein, Kaposi’s Sarcoma-Associated Herpesvirus (KSHV) ORF10, and SARS-CoV-1/2 ORF6 disrupts antiviral production. Despite their evolutionary distance, these viral proteins share a key methionine flanked by acidic residues that competitively bind to the ssRNA binding pocket of Rae1. The VSV mutant, R1, carries an M51R mutation that disrupts viral inhibition and restores host gene export— a pattern observed …
Forecasting Load At Residential, Industrial, And Commercial Stations For Dubai Electricity And Water Authority: A Machine Learning Approach To Managing Generation During Peak And Off-Peak Times Over The Coming Years, Mohammad Anoohi
Theses
In Dubai, with the rapid growth of energy demand, efficient demand side management is necessary to optimize the distribution of electricity, reduce peak loads, and improve grid stability. Traditional DSM strategies are based on historical data and reactive control mechanisms that cannot adapt to evolving consumption patterns. This research uses Machine Learning techniques to enhance DSM in residential, commercial, and industrial sectors by developing predictive models that forecast energy demand based on seasonal variations. The dataset used was from Dubai Electricity and Water Authority (DEWA), covering the consumption patterns across Summer, Winter, Transition from Winter to Summer, and Transition from …
My Two Bodies, Zahra Babaei
My Two Bodies, Zahra Babaei
Theses
My Two Bodies examines the intersection of visibility, memory, and gendered absence through photographic and material strategies. Engaging with censorship and instability of the image, it investigates how realities are shaped by what is seen, obscured, or erased. Referencing the gendered absence of women in Iranian visual culture, the project considers how censorship intensifies rather than eliminates visibility. Drawing from Jacques Derrida’s concept of hauntology, absence is approached not as a void but as an active presence that disrupts the surface of the image. Through processes such as collage, projection, and fabric-based image making, photographs are treated as tactile, mutable …
Reducing Co2 Levels In A Classroom Through The Use Of Biofilters, Jenna Rosser
Reducing Co2 Levels In A Classroom Through The Use Of Biofilters, Jenna Rosser
Theses
We spend 80% of our time indoors and are seeing an increase in indoor pollutants (Sharma et al., 2022). With the push to create more energy efficient buildings, the envelopes are becoming more airtight. As a result, indoor air quality (IAQ) has decreased due to the inability of indoor pollutants to escape from the building as easily through cracks and seams. (Irga et al., 2018; Satish et al., 2012). To date, there is a lot of existing research in regard to the role biofilters play in improving IAQ. Research ranges from having examined specific parts of the plants, soil conditions, …
Beyond Regex – Heuristic-Based Secret Detection, Jesse Burdick-Pless
Beyond Regex – Heuristic-Based Secret Detection, Jesse Burdick-Pless
Theses
Accidental token or credential leakage presents a significant concern within digital environments. Current detection methods of such secrets employ ruleset-based techniques to identify secret information. These methods use pattern recognition within strings (i.e., regex rules) to pinpoint characteristics that resemble various types of secrets. However, regex does not allow for detection of secrets that lack specific patterns, such as passwords. This research addresses the possibility of using heuristics and machine learning to develop a reliable and accurate method for determining if a given string is merely a piece of inconsequential data or a leaked secret requiring timely attention, without the …
Using Generative Ai For Tutoring Data Science, Yusra Khalid
Using Generative Ai For Tutoring Data Science, Yusra Khalid
Theses
A large increase in the use of Generative AI has been observed in the last few years. Data science is also a rapidly growing field with a high demand for skilled professionals. The goal of this thesis is to explore the potential of Generative AI, specifically ChatGPT, in facilitating data science education. The focus is on how ChatGPT can be used as a tutor to help solve practical exercises. The capabilities of Generative AI were explored along with the comparison of a few different models in terms of data science. Exploratory analysis was conducted to compare Generative AI models and …
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 …
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 …
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, …
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 …
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 …
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, …
A Remote Sensing-Based Evaluation Of Road And Electricity Infrastructure Expansion Effects On Development In Sub-Saharan Africa, Tunmise Ibukun Raji
A Remote Sensing-Based Evaluation Of Road And Electricity Infrastructure Expansion Effects On Development In Sub-Saharan Africa, Tunmise Ibukun Raji
Theses
Sub-Saharan African countries consistently rank low on human development indicators despite decades of international aid and domestic investment. To address these challenges, governments across the region are allocating substantial portions of their national budgets to infrastructure expansion, viewing it as a catalyst for accelerated socio-economic development. However, given severely constrained budgets, these nations often face trade-offs between infrastructure development and investment in other important sectors such as healthcare and education. This highlights the need for infrastructure investments to deliver their anticipated benefits. This dissertation examines the relationship between infrastructure development and socio-economic development in Sub-Saharan Africa, with a particular focus …
Dot-Line — Furniture For Inspired Living, Jannet Loumi
Dot-Line — Furniture For Inspired Living, Jannet Loumi
Theses
Design as a functional outlet results from research that revolves around the user experience. It is a fair definition that seems to acknowledge today's standards of designing for the masses, prioritizing market-driven factors that include utility, manufacturability, and market demand. This approach aligns with contemporary design, but does it take ontological design out of the equation? Given that consumer consciousness determines what exists in the market, a design's nonvisual and deeply conceptual aspects may go unnoticed. While market research allows designers to anticipate and shape consumer desires, it is also an opportunity to delve deeper into the user's psyche, not …
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 …
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 …
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 …
Modelling And Optimization Of A Desiccant Cooling System For Industrial Applications In Dubai, Ahmad Ababneh
Modelling And Optimization Of A Desiccant Cooling System For Industrial Applications In Dubai, Ahmad Ababneh
Theses
The study examines the modelling and optimization of solar-assisted desiccant cooling systems (SADCS) specifically designed for industrial applications in Dubai. Four system configurations were evaluated under Dubai's extreme climate using TRNSYS 18 simulation software: classic ventilation, variable percentage recirculation, ventilation with a sensible heat exchanger that utilizes exhaust air to preheat the feed of the auxiliary heating air, and recirculation with a sensible heat exchanger that also utilizes exhaust air for preheating the auxiliary heating air feed. A parametric study comprising 60 simulation cases was performed, examining variations in desiccant wheel effectiveness, airflow rates (3–5 ACH), regeneration temperatures (50–80 °C), …
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 …