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Articles 31 - 60 of 714
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Beyond Anomaly Detection: Classifying Attacker Automation Level From Ssh Honeypot Behavioral Signatures, Ashley Alt
Beyond Anomaly Detection: Classifying Attacker Automation Level From Ssh Honeypot Behavioral Signatures, Ashley Alt
Theses
The proliferation of AI-assisted offensive tools has introduced a new category of cyber attacker that combines the speed of automation with the adaptive reasoning previously associated only with skilled human operators. Despite the richness of behavioral data captured by SSH honeypots, existing analyses treat interaction logs primarily as evidence of malicious activity rather than as a dataset capable of distinguishing between attacker types. This thesis investigates whether human-driven, traditionally automated, and AI-assisted attackers produce distinguishable behavioral signatures within SSH honeypot interactions, and whether machine learning techniques can reliably classify attacker behavior from session-level features. A controlled experimental architecture was developed …
Prediction Of Methane Gas By Using Hyperspectral Imageries And Remote Sensing Techniques, Aysha Ali Alhajeri
Prediction Of Methane Gas By Using Hyperspectral Imageries And Remote Sensing Techniques, Aysha Ali Alhajeri
Theses
Greenhouse gases is important for sustaining life on earth as well as in mitigating climate change. Methane (CH4) is considered as one of the most important critical gases for the global climate change and have significant influences on our life. Accordingly, the prediction of this greenhouse gas emissions is very important for avoiding the climate change effects and to maintain environmental sustainability. The objective of this study is to explore the potential applications for remote sensing to predict methane levels in the Earth’s atmosphere with a combination of local ground data and data from hyperspectral satellite imagery. By using hyperspectral …
Inflection Points In Academic Career Trajectories: Statistical Modeling And Interactive Visualization, Aicha Malouche
Inflection Points In Academic Career Trajectories: Statistical Modeling And Interactive Visualization, Aicha Malouche
Theses
This thesis examines the temporal structure of academic career trajectories, with a particular focus on identifying non-linear patterns of research productivity and moments of maximum acceleration in scientific impact. Situated within the broader context of bibliometric evaluation, the study responds to long-standing limitations of aggregate and linear career models that obscure heterogeneity across disciplines and national research systems. Drawing on theories of cumulative advantage, life-cycle productivity, and structural stratification, the research seeks to clarify how and when elite researchers experience peak growth in impact over the course of their careers. The study is guided by four research questions: (1) when …
Multipath Exploitation For Radar Sensing In An Urban Environment Using The Music Algorithm For Jammer Mitigation, Daniel De Zutter
Multipath Exploitation For Radar Sensing In An Urban Environment Using The Music Algorithm For Jammer Mitigation, Daniel De Zutter
Theses
With the increased push for spectrum sharing techniques, the technological world surrounding radar has been constantly pushing to find new methodologies. From being able to integrate with a communication system to mitigating the effects of other users on a system, the research community is pushing forward. We look to tackle the problem of mitigating a jammer using a multipath MUltiple SIgnal Classification (MUSIC) based approach. We take multiple steps to implement this and generate a framework for future work. We first take a look at understanding the current state of the art research surrounding DFRC, multipath exploitation, MUSIC algorithms, RIS …
Urban Effects On Cloud Formation, Boundary Layer Circulation, And Rainfall Over Miami, Aaron A. Serre
Urban Effects On Cloud Formation, Boundary Layer Circulation, And Rainfall Over Miami, Aaron A. Serre
Theses
The sensitivity of cloud and precipitation formation is expected to be enhanced over urban areas due to persistent sea-breeze forcing. This study combines surface observations, satellite data, and numerical modeling to investigate the impacts of urbanization in the Miami Metropolitan Region (MMR) on surface meteorology, cloud formation, and precipitation. Satellite observations reveal urban expansion of approximately 348 km², along the western boundary of the MMR. These areas also exhibit statistically significant increases in land surface and air temperatures. Geostationary satellite data show enhanced morning cloud formation over the MMR, while increasing rainfall and interannual variability in cloudiness are observed along …
Leveraging Ai, Iot, And Predictive Analytics For Crisis Management And Urban Resilience In Dubai, Suhail Bin Kalli
Leveraging Ai, Iot, And Predictive Analytics For Crisis Management And Urban Resilience In Dubai, Suhail Bin Kalli
Theses
The thesis will discuss how smart technologies could be incorporated in the crisis management structures of Dubai to make the city more resilient. As Dubai grows more urbanized, it experiences increased problems with managing its crisis especially in the high population density places, traffic congestion, utility disruption, and extreme weather. This paper discusses how artificial intelligence (AI), the Internet of Things (IoT), and predictive analytics can be used to ameliorate the response to emergencies, manage the allocation of resources, and enhance the coordination between different agencies. The crisis management systems at Dubai are still ineffective despite the level of technologies …
Characterization Of Krypton Ion Sputtering Of Spacecraft Materials Using Electric Propulsion, Ethan Cummins
Characterization Of Krypton Ion Sputtering Of Spacecraft Materials Using Electric Propulsion, Ethan Cummins
Theses
In the field of electric propulsion (EP), xenon is the most commonly used gas for ionization. However, krypton has been identified as a potential substitute due to its high specific impulse and low cost compared to xenon. Therefore, there is a desire to understand the effects of using krypton. In EP, sputtering of spacecraft materials downstream of the ion engines have proven to be an issue during long duration missions. This research observes how krypton ions sputter a variety of spacecraft materials (anodized aluminum, glass, BN ceramic, and Kapton). The experiments in this study subject materials to different sputtering variables …
Understanding Computer-Mediated Human Experience In Digital-Physical Hybrid Space, Jiangnan Xu
Understanding Computer-Mediated Human Experience In Digital-Physical Hybrid Space, Jiangnan Xu
Theses
With the rapid development of mobile and immersive technologies, the boundary between the digital and real world is increasingly blurred, giving rise to hybrid spaces. Hybrid spaces have permeated daily life and reshaped spatial meaning-making and social interaction. Despite their growing prevalence, empirical understanding of human experiences in hybrid spaces remains limited. If left unexamined, hybrid spaces risk becoming technology-centered rather than human-centered environments that overlook socio-cultural dimensions, potentially leading to harmful consequences for individuals and society. To investigate human experience in hybrid spaces, this thesis comprises five studies and uses gameful systems as research probes. Prior literature identifies collaboration …
Planning For Power: The Role Of Architecture & Urban Form In Local Energy Generation In Dense Built-Up Areas, Chris Shing Wai Leung
Planning For Power: The Role Of Architecture & Urban Form In Local Energy Generation In Dense Built-Up Areas, Chris Shing Wai Leung
Theses
This thesis explores how the urban form/building design, and a well-thought-out City Master Plan can significantly affect wind patterns and enhance on-site energy generation in dense urban areas. It will examine strategies such as modifying building heights, adjusting separations between structures, shaping urban landforms, and varying the roughness of the urban fabric to optimize wind energy generation. Additionally, the research will focus on the strategic placement of community power harvesting devices. The study of the urban forms and fabric with the impact of wind patterns is simulated by fluid mechanics with Computational Fluid Dynamics (CFD) software. The goal of this …
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 …
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.
Rubbing Away Respect: How Repeated Touch Alters The Meaning Of Women’S Statues, Olivea Kittrell
Rubbing Away Respect: How Repeated Touch Alters The Meaning Of Women’S Statues, Olivea Kittrell
Theses
This thesis examines how repeated public interactions with statues of women, particularly the ritualized rubbing of their breasts, alter both the material surfaces and symbolic meanings of statues. We will focus on three bronze sculptures: the Molly Malone statue in Dublin, the Juliet statue in Verona, and the Bust of Dalida in Paris. Through these, we will investigate how statues created with commemorative intent become sites of sexualized behavior based on gender. The problem this thesis addresses is the lack of scholarly analysis on how gendered public interaction physically and symbolically transforms statues of women. While some scholarship covers either …
Identity And Representation In Contemporary Art: An Inclusive 400/500-Level Art History Seminar Course, Laura E. Franz
Identity And Representation In Contemporary Art: An Inclusive 400/500-Level Art History Seminar Course, Laura E. Franz
Theses
This project is an upper-level art history seminar addressing identity and representation – specifically related to race, ethnicity, gender, and sexuality – in contemporary art. Primarily a discussion-based course, the course is focused on inclusivity and is highly structured, with weekly low-stakes assignments that provide students with ample opportunities to practice engaging with academic texts. Designed for students with varying levels of academic skills, it is built around current non-academic articles that students select via an online survey. Students then “unpack” the “big ideas” in each of the four chosen non-academic articles via a cluster of academic readings and videos …
Make Ready: Productive Disruption And Interstitial Sites Of Graphic Design Practice, Peter Maybury
Make Ready: Productive Disruption And Interstitial Sites Of Graphic Design Practice, Peter Maybury
Theses
This thesis draws on five publications produced between 2010–22: My 2020 film installation Landfall; a series of four museum and gallery-published books made with artist Gerard Byrne (2010–18); Gall, my practice enquiry with Tom dePaor which encompasses film, writing, books, sculpture, curation, and gallery works; releases and live performances by my band Thread Pulls during the period 2010–12; and my exhibition, conference talk, and book Make Ready (2015), the structure of which is taken as ‘armature’ for the writing of the thesis. Through these wide-ranging pursuits, this thesis articulates a non-normative role for the graphic designer. It identifies my operative …
Comprehensive Drought Analysis: Machine Learning-Based Meterological Drought Forecasting And Pca-Driven Agricultural Drought Monitoring., Bishal Poudel
Theses
Drought is a long-term natural disaster that affects many aspects of human life from health, water supply to ecosystems and agriculture. Drought’s occurrence and intensity has increased in recent years because of global warming, which urges for proper and accurate monitoring and forecasting of drought. For better understanding of droughts, this study uses two approaches. In first part, the study uses the historical temperature and precipitation data from period of 1960 to 2021 as input features for three different machine learning models – Artificial Neural Network (ANN), Support Vector Machine (SVM) and Random Forest (RF). The research focuses on calculating …
Flood Susceptibility Assessment Through Gis Integrated Analytical Hierarchy Process And Machine Learning Models, Sujan Shrestha
Flood Susceptibility Assessment Through Gis Integrated Analytical Hierarchy Process And Machine Learning Models, Sujan Shrestha
Theses
Flooding is among the most destructive natural disasters globally, and it inflicts severe damage on both natural environments and human-made structures. The frequency of floods has been increasing due to unplanned urbanization, climate change, and changes in land use. Flood susceptibility maps help identify at-risk areas, supporting informed decisions in disaster preparedness, risk management, and mitigation. This study aims to generate a flood susceptibility map for two regions: Davidson County of Tennessee using an integrated geographic information system (GIS) and analytical hierarchical process (AHP), and the Briar Creek watershed of Mecklenburg County, North Carolina using an integrated GIS and machine …
Leveraging Ai In Traffic Monitoring For Improved Accident Prediction In Uae, Mahra Alattar
Leveraging Ai In Traffic Monitoring For Improved Accident Prediction In Uae, Mahra Alattar
Theses
This paper investigates how Machine Learning (ML) models can be used in traffic surveillance and predict accidents in the United Arab Emirates (UAE). In spite of large infrastructure developments and stringent traffic laws, traffic accidents continue to be a major problem with an increase in fatalities and injuries. There is a gap in effective detection and responses since traditional monitoring and forecasting techniques are unable to capture the intricate, nonlinear, and time-dependent character of traffic patterns. This thesis fills that void by utilizing sophisticated the potential use of Artificial Neural Network (ANN), Recurrent Neural Network (RNN), Deep Neural Network (DNN), …
Enhancing Airport Operations With Ai For A Seamless Passenger Experience, Rashed Alsubousi
Enhancing Airport Operations With Ai For A Seamless Passenger Experience, Rashed Alsubousi
Theses
The paper is research exploring the importance of Artificial Intelligence (AI) and Data Analytics to optimize airport operations and the passenger experience in the environment of the expanding air traffic in the world and the smart city movement. With increasing tasks that airports currently experience, congestion, flight delays, mishandling of baggage, and limited capacity, nowadays AI-based technologies integration is crucial to the operational efficiency, sustainability, and customer satisfaction. This study discusses the use of predictive analytics, machine learning, and clustering models to enhance passenger flows, resource allocation, and performance in general at airports. The research is based on the working …
Data-Driven Crime Prediction: Toward Smarter Reduction Strategies, Zayed Almarri
Data-Driven Crime Prediction: Toward Smarter Reduction Strategies, Zayed Almarri
Theses
This study explores how machine learning and weather data can be used for the prediction of crime more accurately in the city of Seattle. Predictive policing is a method in law enforcement that uses data and computer algorithms to forecast the locations that crimes are likely to happen. Although many studies focused on using past crime data alone, this research also includes weather conditions like temperature, rainfall, and humidity, which may influence when and where crimes occur. Several machine learning models, including Random Forest (RF) and Support Vector Machines (SVM), were used to classify areas of the city into high-risk …
Predicting Violent Crime Hotspots, Mohammad Alhammadi
Predicting Violent Crime Hotspots, Mohammad Alhammadi
Theses
This thesis presents a systematic literature review and an empirical demonstration focused on predicting violent-crime hotspots. Drawing on 50 studies published between 2010 and 2025, the review synthesises methodological developments across hotspot mapping, spatio-temporal modelling, risk terrain analysis, and machine-learning approaches. The review highlights a clear evolution from retrospective density maps to more dynamic, data-driven techniques, while also identifying persistent challenges related to data bias, temporal granularity, environmental context, fairness, and operational implementation. To complement the review, the thesis applies kernel density estimation (KDE) and three ensemble machine-learning models—Random Forest, Gradient Boosting, and XGBoost—to 769,680 geocoded violent-crime incidents recorded in …
Integrating Climate And Geospatial Features Into Machine Learning Models, Abdulaziz Ahmed Aljaziri
Integrating Climate And Geospatial Features Into Machine Learning Models, Abdulaziz Ahmed Aljaziri
Theses
This thesis addresses a significant gap in real estate valuation models by investigating the economic impact of localized climate conditions and granular geospatial amenities. An abstract summarizes the following: - The main themes, ideas or areas of theory being investigated: This research investigates the integration of localized climate conditions and granular geospatial amenities into machine learning (ML) frameworks for residential real estate valuation. - The background and context of the research: In dynamic urban markets like Dubai, traditional valuation models often rely on broad location labels and structural attributes, overlooking the tangible economic impact of environmental comfort and micro-climates in …
Optimizing Delivery Time Predictions Using Machine Learning: A Data-Driven Approach To Last-Mile Logistics, Mohamed Burqaiba
Optimizing Delivery Time Predictions Using Machine Learning: A Data-Driven Approach To Last-Mile Logistics, Mohamed Burqaiba
Theses
This paper addresses how machine learning can be utilized to improve the prediction of delivery times during the last mile, specifically in Dubai urban logistics issues whereby the traffic congestion and weather circumstances usually contribute to unpredictable delivery times. The main goal was to evolve machine learning models that can predict properly delivery time depending on several parameters, i.e., speed of traffic, weather, length of delivery, and geography. The reason why three machine learning models were chosen [Random Forest, Gradient Boosting, and XGBoost] in this analysis is that they have the opportunity to work with non-linear relationships in the data. …
A Machine Learning Framework For Forecasting Passenger Flow At Dubai International Airport, Khalifa Alfalasi
A Machine Learning Framework For Forecasting Passenger Flow At Dubai International Airport, Khalifa Alfalasi
Theses
The fast growth of global air travel made the accurate prediction of passenger flow a challenge for airport operations. Traditional forecasting models, like regression and SARIMA, have been useful in stable conditions but usually do not show the non-linear and dynamic changes driven by weather, infrastructure, and behaviour of passengers. Therefore, recent studies showed the potential of machine learning and big data to improve the accuracy of forecasting. However, most of the work is still limited to specific airports, datasets, or operations. This study develops a machine learning–based predictive framework for short-interval passenger throughput at Dubai International Airport. Using available …
The Simulation Of Hyperspectral Observations By The Upcoming Spacecraft "Arab Satellite 813", With The Radiative Transfer Model Sciatran, Sara Maher Alhasan
The Simulation Of Hyperspectral Observations By The Upcoming Spacecraft "Arab Satellite 813", With The Radiative Transfer Model Sciatran, Sara Maher Alhasan
Theses
The Arab Satellite 813, which is scheduled to be launched in 2025/2026 by the UAE Space Agency, is set to increase earth observation and monitor the climate across the middle East and North Africa (MENA) region. This study uses the SCIATRAN radiative transfer model which was originally developed for the Envisat mission to simulate the hyperspectral observation specifically tailored for the satellite's payload. Using calibrations that were used by the previous research in their SCIATRAN V4.6 study and adjusting parameters like the Leaf Area Index (LAI), a simulation which agreed robustly with the benchmarks set by the previous research was …
Making Math Accessible: Addressing Language Challenges In 3rd Grade English Medium Math Classrooms, Salha Mohamad
Making Math Accessible: Addressing Language Challenges In 3rd Grade English Medium Math Classrooms, Salha Mohamad
Theses
The research article, Making Math Accessible: Addressing Language Difficulties in 3rd Grade English Medium Math Classrooms, addresses the issue of how the teachers in UAE elementary schools assist a student who is to study mathematics in English rather than Arabic. In the School X, Grades 1 and 2 applied mathematics and science using the Ministry of Education (MOE) Arabic-medium curriculum. Since Grade 3, however, the school has used the American curriculum, so students are expected to study these subjects in English. This change brings major barriers in understanding basic mathematical terms, word problems, and instructions. The research applies …
Design That Builds Communitites: An Evaluation Method For Analyzing, Assessing, And Improving The Way We Plan And Design The Places Around Us, Devine Karas-Gonzalez
Design That Builds Communitites: An Evaluation Method For Analyzing, Assessing, And Improving The Way We Plan And Design The Places Around Us, Devine Karas-Gonzalez
Theses
The places around us shape and impact on the way we interact and live within our communities. As such, it is important to place greater emphasis on designing spaces which are meant to better respond to the needs and functions of a place. With an architectural design process this will result in the use of design strategies which will inform much of the design. In this research, multiple design strategies (Smart Growth, Placemaking, Place Value, and Street Experiments) are evaluated and compared using four regionally similar cities to analyze and assess how the different strategies impact the design process by …
Multiplex Leiden Optimized Dynamic Network Microsegmentation And Flow Validation For Software Defined Networks, Rashed Husni Rashed Alnuman
Multiplex Leiden Optimized Dynamic Network Microsegmentation And Flow Validation For Software Defined Networks, Rashed Husni Rashed Alnuman
Theses
Modern digital infrastructure is fundamentally built upon robust networks, which underpin seamless communication, data exchange, and the operation of critical systems. These networks facilitate everything from internet access and real-time patient vital sign transfers in healthcare to the management and control of industrial processes. As demands on networks have surged, their complexity and functionality have evolved significantly, continuously adapting to diverse sectoral needs. However, this rapid evolution has also amplified security challenges. The escalating scale and intricacy of contemporary networks have exposed vulnerabilities that traditional perimeter-based security models are often insufficient to counter. Static defenses prove inadequate in dynamic environments …
Haunted Echoes, Stuti Kasat
Haunted Echoes, Stuti Kasat
Theses
Haunted Echoes explores the narrative and emotional possibilities of interactive digital fiction by creating a room-based haunted experience. By placing the users within a haunted manor the project encourages emotional discovery through narrative exploration. As a room-based exploratory experience, users get to navigate a dollhouse-style 3D interface, interacting with objects to reveal layered micro-stories and uncover the manor’s haunted past. The experience turns spatial exploration into emotional discovery, drawing inspiration from immersive theater, point-and-click adventures, and environmental storytelling in video games. The thesis examines the intersection and overlap of interactive storytelling, visual communication, and emotional immersion, integrating 3D modeling (Blender/Cinema …
Product, Process, And Behavior Influences On Value Retention Processes: Toward A Circular Economy In Consumer Electronics, Kyle Parnell
Product, Process, And Behavior Influences On Value Retention Processes: Toward A Circular Economy In Consumer Electronics, Kyle Parnell
Theses
Consumer electronic products (CEP) manufacturing and retail contribute markedly to global industrial activity; worldwide estimates suggest revenue growth from $1 trillion in 2020 to $1.5 trillion by 2026. Consequently, the production, distribution, use, and end-of-life (EOL) disposition of these products are responsible for considerable social and environmental impacts, including 35 million metric tonnes of waste to landfill per year, 793 million metric tonnes (MMT)—and growing—of carbon dioxide-equivalent (CO2e) greenhouse gas (GHG) emissions per year, and innumerable adverse effects on human health and development. Driving these impacts are the inherent characteristics of CEPs themselves, which increasingly require critical materials in design, …