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Articles 121 - 150 of 4407
Full-Text Articles in Entire DC Network
The Impact Of Artificial Intelligence On Employee Attrition And Organizational Profitability, Saeed Almehairi
The Impact Of Artificial Intelligence On Employee Attrition And Organizational Profitability, Saeed Almehairi
Theses
Artificial Intelligence (AI) has become a transformative force in the modern workplace, reshap- ing decision-making processes, enhancing operational efficiency, and influencing the dynamics of human resource management. One of the critical areas where AI demonstrates substantial potential is in predicting, managing, and mitigating employee attrition. Employee attrition remains a pressing organizational challenge, incurring substantial costs in recruitment, training, and lost productivity. This research investigates the dual impact of AI on employee attrition and organizational profitability, exploring both the opportunities and the challenges that arise from its integration into human resource and business operations. The study examines how AI-driven predictive analytics …
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 …
Comparative Analysis Of Machine Learning Models For Spam Email Detection, Rashed Almarri
Comparative Analysis Of Machine Learning Models For Spam Email Detection, Rashed Almarri
Theses
The current research examines one of the most effective approaches to spam email detection based on machine learning and natural language processing (NLP). The study is placed in the context of the rising cyber threats and the influx of emails, where the spam/ham data is to be classified correctfully using the combination of the Logistic Regression, NLP (including tokenization, lemmatization, and TF-IDF vectorization). The questions of the research were devoted to the efficiency of such an approach and the interpretation of its results. The data used are obtained by a publicly available Kaggle data set that contains 5,572 labeled email …
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.
Beyond The Mozart Effect: How Musical Experience And Emotional Response Shape Individual Differences In Spatial Reasoning, Connor Watkinson
Beyond The Mozart Effect: How Musical Experience And Emotional Response Shape Individual Differences In Spatial Reasoning, Connor Watkinson
Theses
Research on the Mozart effect (the short-term enhancement of spatial-temporal reasoning after music listening) has yielded inconsistent results, often due to overlooking individual differences and using limited stimuli. This study examined multiple musical conditions (popular lyrical, classical, and white noise control) while considering the moderating roles of musical experience and the mediating influence of emotional responses. Undergraduate participants (N = 162) completed spatial reasoning assessments before and after an eight-minute listening session, alongside measures of musical background, listening habits, mood, and music-evoked emotions.Analyses revealed no overall difference in spatial reasoning improvement between music and white noise conditions. However, substantial individual …
A Comparison Of Fixed And Repetitive Models During Imitation Training In Children With Developmental Delays In A School Setting, Laci Fletcher
A Comparison Of Fixed And Repetitive Models During Imitation Training In Children With Developmental Delays In A School Setting, Laci Fletcher
Theses
Imitation training is commonly recommended in applied behavior analytic literature to address deficits in imitative skills. Few studies have directly compared imitative models to identify the most efficient and effective teaching arrangement to facilitate imitative skills (Deshai & Vollmer, 2019; Halbur et al., 2023). Previous results are inconclusive, and the authors recommended further research comparing the effect of fixed and repetitive models. Therefore, the present study was a replication of Halbur et al. (2023) and addressed limitations suggested by the authors. We examined whether components of imitative models affected the efficiency of the model type and reduced faulty stimulus control …
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 …
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 …
Asymptote, Aybuke Yilmazer
Asymptote, Aybuke Yilmazer
Theses
Asymptote is a short film that is an expression of mankind’s emotional consumption through confusing love with sex. This film is a frame-by-frame hand-drawn animation that combines digital and analog techniques. It was produced between August 2024 and April 2025, and its music was re-produced in August 2025. This paper is a written declaration of the motives and intentions of the director, Aybuke Yilmazer, in making this film, and analyzes the filmmaking process. The text of the thesis is in third person except for the self-evaluation section.
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 …
Rise Of Social Media Hacking: Ai-Based Ip Tracking For Uae Law Enforcement, Mounikha Naarrayen Chakravarthula
Rise Of Social Media Hacking: Ai-Based Ip Tracking For Uae Law Enforcement, Mounikha Naarrayen Chakravarthula
Theses
Social media has evolved into a critical channel for communication, expression, and public influence, but it has also become a prevalent avenue for cybercrime, particularly in digitally advanced nations such as the United Arab Emirates (UAE). The rising complexity of online offences, coupled with anonymisation tools and cross-border digital behaviour, has made the attribution of social-media-based cyber incidents increasingly challenging for law enforcement. In this context, artificial intelligence (AI) offers the potential to strengthen digital investigations by providing intelligent, scalable, and evidence-driven attribution capabilities. This research develops an AI-assisted Internet Protocol (IP) attribution framework tailored specifically for UAE law enforcement …
Predicting Mental Health Risk In Remote Workers: A Machine Learning Approach, Majed Al Mheiri
Predicting Mental Health Risk In Remote Workers: A Machine Learning Approach, Majed Al Mheiri
Theses
This dissertation explores the application of machine learning in mental health risk prediction of remote workers, which is increasingly becoming a significant issue, with the practise of flexible working reshaping organisational practises. It is based on the theoretical framework that has been used previously such as Job Demands Resources model and Stress-Strain model which emphasise the role of workload, support systems and personal resources in determining the well-being of employees. The context of the study indicates the growing rate of remote and hybrid employment, and the associated increase in the number of issues associated with stress and isolation, as well …
Defaking Deepfakes: Designing And Evaluating Ai-Powered Digital Media, Saniat Javid Sohrawardi
Defaking Deepfakes: Designing And Evaluating Ai-Powered Digital Media, Saniat Javid Sohrawardi
Theses
The rapid spread of generative AI has revolutionized media production, creating new challenges for information integrity as convincing deepfakes proliferate. Journalists play a critical role in upholding credible public information, yet existing deepfake detection technologies often overlook their specific workflows and requirements. This dissertation addresses these needs by identifying what journalists require from detection tools and evaluating usability in realistic scenarios through the following works: Journalists' Needs and Tool Design: Through qualitative user studies, we uncover journalists' preferences for tools that provide transparent, explainable evidence and context-aware analysis integrated into news verification routines. These insights drive the design of DeFake, …
An Interpretable Machine Learning Framework For Detecting Phishing Urls Based On Lexical Features, Khalid Alrokhaimi
An Interpretable Machine Learning Framework For Detecting Phishing Urls Based On Lexical Features, Khalid Alrokhaimi
Theses
Phishing attacks represent one of the most significant and persistent threats in the cybersecu- rity landscape, with attackers increasingly using sophisticated URL manipulation techniques to deceive users and steal sensitive information. Traditional detection methods, which rely primarily on blacklists and heuristic rules, struggle to identify zero-day phishing URLs that have not yet been catalogued in security databases. This research addresses this critical gap by developing an interpretable machine learning framework for detecting phishing URLs usingclexical, structural, content-based, and domain metadata features. The study employs a comprehensive dataset of 11,430 labeled URLs (5,715 legitimate and 5,715 phishing) with 87 extracted features, …
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 …
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 …
Potential And Low-Cost Football Talents For Uae Clubs Based On Data-Driven Analysis, Rashid Alqemzi
Potential And Low-Cost Football Talents For Uae Clubs Based On Data-Driven Analysis, Rashid Alqemzi
Theses
The use of data analytics in professional football has changed the way clubs view, value and invest in players. Meanwhile, elite European teams have consistently exploited the data-driven strategies that offer them a competitive edge, but in up-and-coming football markets, such as the UAE Pro League, nepotism has remained strong, with reputation-based and agentdriven recruitment being the transformation choice of even the biggest profile moves. This work explores whether predictive analytics can discover hidden high-quality football talent from ”hotbeds” of talent including Brazil and Argentina, in a way that matches the economic capabilities of clubs in the UAE, given the …
Predicting Athlete Performance Using Machine Learning Models, Mohammad Abdulbasit Mohammad Alabdulla
Predicting Athlete Performance Using Machine Learning Models, Mohammad Abdulbasit Mohammad Alabdulla
Theses
The purpose of this research is to develop and assess multi-modal machine learning for robust performance analysis to predict athletic performance and evaluate injury risk. The study employed Data Analytics approach, where composite features, i.e., Training Stress and Recovery Score,were modelled to characterize training-recovery correlations. It had four different regression models (MLR, RFR, SVR, DNN) and four different classification models (Logistic Regression, RFC, SVM, DNN). DNN exhibited an increased degree of effectiveness in the forecasting Synthetic Performance Score (R2 =0.9998). Notably, the Random Forest Classifier (RFC) turned out to be the most valid predictor of injuries risk (F1-Score 0.7736; AUC-ROC …
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 …
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), …
Deepfake Audio Detection, Rashed Alfalasi
Deepfake Audio Detection, Rashed Alfalasi
Theses
The rise of deepfake audio technology has introduced a serious threat to information credibility, personal security, and media integrity. This thesis investigates the application of machine learning techniques for detecting synthetic audio through the analysis of acoustic features, including Mel-Frequency Cepstral Coefficients (MFCCs), spectral centroid, chroma_stft, and zero-crossing rate. The dataset used in this study was sourced from Kaggle and contains labeled samples of real and fake audio clips. The research aimed to train and evaluate multiple machine learning models—Support Vector Machines (SVM), Random Forest, XGBoost, Logistic Regression, and Neural Networks—to determine the most effective approach for deepfake audio classification. …
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 …
Chatgpt As A Mental Health Ally: A Study On College Students’ Adoption Of Ai For Therapy, Alya Albastaki
Chatgpt As A Mental Health Ally: A Study On College Students’ Adoption Of Ai For Therapy, Alya Albastaki
Theses
This research investigates college students’ use of ChatGPT for mental health support, addressing a population with high unmet mental health needs due to barriers like accessibility and cost. Through a mixed-methods study, which included a survey of 126 students and sentiment analysis of 1,200+ social media posts, the research examined adoption prevalence, gender influences, and perceived benefits and limitations. Survey findings show 40.5% of students use ChatGPT for mental health, especially those with self-reported challenges. Female students reported higher adoption, linked to greater mental health needs and openness to supplementary support. Key benefits included 24/7 access, anonymity, and low cost, …
Echo’S Repertoire: Performing Science Fiction And Trans Care Models, Juniper Blue
Echo’S Repertoire: Performing Science Fiction And Trans Care Models, Juniper Blue
Theses
Echo’s Repertoire is a mixture of a passion piece and a call for more work with performing science fiction. It focuses on interpersonal communication within trans studies and the experiences of transgender individuals and myself. Echo’s Repertoire is also an example of the Lyrical Model proposed by Awkward-Rich as a new model for trans affirming speech. The show is laid out non-linearly and follows along with Echo as he starts to build new relationships with the advice of his spaceship ai, Eep, who is a previous version of himself prior to transformation (transition).
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 …
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 …
Predictive Maintenance For It Equipment Using Machine Learning Models, Rashed Khalid Alshirawi
Predictive Maintenance For It Equipment Using Machine Learning Models, Rashed Khalid Alshirawi
Theses
Predictive maintenance was recently introduced as a paradigm shift in the field of smart manufacturing, and it allows organizations to predict equipment failures and streamline maintenance planning based on the data-driven insights. The present work addresses the concept of the implementation of a decision tree-based predictive maintenance model based on AI4I 2020 Predictive Maintenance Dataset, a simulated environment of an actual industry through sensor data including temperature, torque, rotational velocity, and toolwear. The study uses a quantitative approach that is based on positivism philosophy, which is the focus on objectivity, empirical validation, and statistical testing of the model performance. Synthetic …
Strainx : A Technical Exploration Of Cinema4d'S Native Particle System In An Experimental Title Sequence, Farah Ahmad
Strainx : A Technical Exploration Of Cinema4d'S Native Particle System In An Experimental Title Sequence, Farah Ahmad
Theses
This paper presents a practice-based investigation into the capabilities of Cinema 4D’s native particle system through the creation of an experimental title sequence titled StrainX. The project was conceived as a technical and aesthetic exploration, prioritizing abstraction, form, and motion over narrative content. Through iterative testing and simulation, the study examines how Cinema 4D’s built-in particle, geometry, and material tools can generate visually complex results without relying on third-party plugins, such as X-Particles. All assets, simulations, and textures were developed natively within Cinema 4D, allowing for a unified and efficient workflow. The methodology emphasizes procedural experimentation, simulation caching using Alembic …