Saudi Cultural Missions Theses & Dissertations
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Item Restricted VHealth Suite: A Unified, Secure, and Intelligent Patient-Centered Framework for Legacy System Integration in Virtual Hospital Ecosystems(Saudi Digital Library, 2026) Alsalamah, Sara Abdullah; Chang-Tien, LuA virtual hospital (VH) is a distributed, digitally enabled healthcare ecosystem that extends clinical services beyond physical facilities, facilitating patient-centered (PC) care across geographically dispersed settings through interoperable infrastructures, telemedicine platforms, and hub-and-spoke coordination. However, legacy healthcare information systems remain fragmented, disease-centered, and operationally reactive, which limits secure data sharing, knowledge integration, and system-wide capacity awareness. These challenges are further exacerbated by rising demand, workforce constraints, and the need for predictive operational intelligence to enable efficient and scalable care delivery. To address these limitations, this dissertation proposes VHealth Suite, a unified, secure, and intelligent framework designed to modernize legacy healthcare information systems and seamlessly integrate them into VH ecosystems without requiring system replacement. The framework is implemented as a multi-component architecture that integrates secure data exchange, intelligent knowledge extraction, predictive operational intelligence, and human-in-the-loop interaction. First, the secure data exchange component is realized through VHealth-AC, a novel access control (AC) model that enables fine-grained and secure access to PC data across distributed and autonomous healthcare systems. The model employs a five-tier PC information classification scheme and operates as a neutral collaboration security domain, allowing clinicians to securely access patient data across institutional boundaries at the point of care. Second, intelligent PC knowledge extraction is achieved through VHealth-CNN and VHealth-MFusion. VHealth-CNN leverages a double-layer convolutional neural network (CNN) to extract and classify health-related features from biomedical data, achieving prediction accuracies of 91.3%, 93.5%, and 95% for obesity, hypertension, and diabetes, respectively. VHealth-MFusion introduces a hierarchical multimodal deep learning framework that integrates chest X-ray (CXR) images with structured clinical data, achieving 97.2\% overall classification accuracy, improving robustness under class imbalance, and reducing misclassifications among clinically similar conditions. Third, predictive operational intelligence and clinical routing are addressed through VHealth-Routing, an AI-driven framework that combines clinical decision support with capacity-aware optimization. The framework integrates a clinical routing engine, a spatiotemporal prediction engine, and a constrained re-ranking mechanism to align clinical relevance with operational feasibility. It is evaluated using a large-scale real-world dataset from the Seha VH ecosystem in Saudi Arabia, comprising over 15 million records, with a representative subset of 1,006,111 appointments used for experimentation. Results demonstrate strong routing performance, with XGBoost achieving 73.2% Top-1 accuracy and 97.6% Top-3 accuracy, alongside effective demand forecasting and waiting time estimation, supporting improved workload distribution and reduced system inefficiencies. Finally, the human-in-the-loop component is implemented through VHealth-Bot, an AI-driven conversational platform that integrates natural language processing, diagnostic reasoning, and adaptive learning to support clinician–patient interaction. The system enhances real-time symptom assessment, personalized response generation, and collaborative decision-making, while maintaining clinician oversight to ensure safety and preserve clinical expertise. Evaluation results indicate improvements in diagnostic support, workflow efficiency, clinician–patient communication, and patient satisfaction. Overall, VHealth Suite provides a scalable, privacy-preserving, and intelligent architecture that unifies clinical intelligence with operational optimization. The proposed framework enables proactive, data-driven, and PC care delivery in large-scale VH ecosystems, improving clinical outcomes, enhancing operational efficiency, and fostering more responsive healthcare systems.17 0Item Restricted JOINT NONPARAMETRIC TESTS FOR LOCATION AND SCALE DIFFERENCES IN MULTIPLE POPULATIONS(Saudi Digital Library, 2026) Alrefeadi, Fatimah Abdullah; Rhonda, MagelNonparametric statistical methods are widely used when data do not satisfy the assumptions required for parametric procedures, such as normality and homogeneity of variances. While many existing nonparametric tests are designed to detect differences in either location or scale parameters separately, practical applications often require the simultaneous assessment of both. When location and scale vary together, procedures that focus on only one parameter may suffer from reduced power or lead to misleading conclusions. This dissertation develops new combined nonparametric tests for jointly assessing differences in location and scale across multiple populations. The proposed methods are constructed by combining the Kruskal–Wallis test for location with scale components derived from the Moses Kruskal–Wallis and Levene tests. Two groups of test statistics are introduced, each incorporating measures of central tendency based on the mean, median, and trimmed mean, to enhance robustness across symmetric, skewed, and heavy-tailed distributions. The performance of the proposed tests is evaluated through extensive simulation studies under a wide range of distributions and sample size configurations for three and four populations. The results demonstrate that the tests generally maintain nominal Type I error rates and achieve improved power when scale differences or joint location–scale differences are present. Among the proposed methods, Moses-based procedures show superior performance in heavy-tailed distributions, whereas Levene-based procedures exhibit more stable behavior across a broad range of distributional settings. Overall, the proposed tests provide reliable and effective tools for joint nonparametric inference on location and scale in multi-sample problems.11 0Item Restricted FROM ACCEPTANCE TO PRACTICE: A MIXED-METHODS STUDY OF GENERATIVE AI INTEGRATION AMONG SAUDI UNIVERSITY EFL TEACHERS(Saudi Digital Library, 2026) Alderaan, Hadir; Thomas, SalsburyDespite growing interest in artificial intelligence in education, there is still limited research on how EFL teachers in Saudi higher education perceive and use Generative Artificial Intelligence (GAI) in their teaching. Much of the existing literature focuses on student use, with less attention given to teachers’ pedagogical decision-making and the realities of integrating these tools into classroom practice. This gap is particularly significant in contexts where clear institutional guidance is lacking, leaving teachers to navigate issues such as academic integrity, ethical use, and the cultural appropriateness of AI-generated content on their own. This study employs a mixed-methods design to examine how 101 Saudi university EFL instructors engage with GAI tools and how teaching experience relates to their instructional practices. The study is guided by the Technology Acceptance Model (TAM), Technological Pedagogical Content Knowledge (TPACK), and Expectancy–Value Theory (EVT). Data were collected through an online survey and followed by semi-structured interviews with seven purposively selected participants. The findings indicate that teachers generally hold positive attitudes toward GAI; however, their use remains selective and primarily focused on preparatory tasks. Participants reported using GAI for lesson planning, generating example texts, and supporting grammar instruction, while avoiding its use in assessment and direct student-facing tasks due to concerns about academic integrity and student overreliance. Interview data further show that teachers actively negotiate how and when to use GAI, setting boundaries based on pedagogical judgment and contextual constraints. The study also highlights the additional effort teachers invest in reviewing, verifying, and adapting AI-generated content to ensure accuracy and cultural relevance. Rather than reducing workload, GAI often shifts teachers’ effort from content creation to evaluation and modification. Overall, the findings suggest that positive attitudes alone do not lead to meaningful integration, emphasizing the need for clearer institutional support and targeted professional development to enable ethical and contextually appropriate use of GAI in EFL classrooms.6 0Item Restricted ABT-263 Exerts Transient Senolytic Activity Against Therapy-Induced Senescence in NSCLC(Saudi Digital Library, 2026) Alshehri, Muruj Ahmed; Gewirtz, DavidTherapy-induced senescence (TIS) can suppress tumor growth but may also facilitate long-term relapse through a subset of cells capable of regaining proliferative potential, while the senescence-associated secretory phenotype (SASP) can further promote tumor progression. Senolytic agents, such as the BCL-XL/BCL-2 inhibitor ABT-263 (navitoclax), have therefore emerged as a strategy to selectively eliminate senescent tumor cells. In this study, we evaluated the senolytic efficacy of ABT-263 in murine (CMT-167) and human (A549) non–small cell lung cancer (NSCLC) models following clinically relevant radiation regimens: a single high dose (10 Gy) mimicking stereotactic body radiation therapy (SBRT) and a hypofractionated regimen (2.75 Gy × 4). Both radiation regimens induced a senescent phenotype, although senescence was consistently less pronounced following fractionated irradiation. To determine whether enhanced DNA damage could increase senescence depth and senolytic sensitivity, we combined fractionated radiation with the PARP inhibitor Talazoparib. This combination markedly amplified senescence markers and transiently increased sensitivity to ABT-263. In contrast, combining cisplatin with fractionated radiation failed to enhance senescence induction or senolytic sensitivity beyond cisplatin alone. Across all conditions, despite clear evidence of senolytic activity, ABT-263 consistently failed to achieve durable eradication of senescent cells. A substantial population of cells persisted after treatment while retaining senescence markers. Together, these findings indicate that ABT-263 eliminates only a subset of therapy-induced senescent cells, leaving behind a residual senescent population. This highlights the need for improved strategies to achieve more complete and durable targeting of therapy-induced senescence in NSCLC.5 0Item Restricted Gene-Environment Interactions in the Regulation of Obesity and Metabolic Disorders(Saudi Digital Library, 2026) Baabbad, Murad; Pender, Sylvia; Cagampang, FelinoBackground: Obesity and type 2 diabetes arise from gene-environment interactions. Matrix metalloproteinase 28 (MMP28) is an immune-modulating extracellular matrix protease. Previous studies have shown that Mmp28-/- mice reared under specific pathogen-free (SPF) conditions develop obesity, hepatic steatosis, and metabolic dysfunction, including elevated fasting blood glucose. Transferring SPF-housed Mmp28-/- mice to a conventional mouse room (CMR, low-barrier, richer microbial exposure) for 5 weeks partially reversed these metabolic abnormalities. In the present study, we aimed to investigate whether the development of obesity, hepatic steatosis, and metabolic dysfunction can be prevented by raising and maintaining the Mmp28-/- mice in CMR from birth. Methods: Male and female Mmp28-/- and wild-type (WT) C57BL/6J mice were reared in either SPF or CMR facilities on an identical chow diet. Phenotyping at about 30 weeks of age included body weight, food intake, indirect calorimetry for energy expenditure (EE), open field activity, fasting blood glucose and glucose tolerance tests, tail-cuff blood pressure, and liver histology. Hepatic bulk RNA-seq assessed differential gene expression by genotype, housing, and their interaction, followed by gene set enrichment analysis. Results: As previously found, in SPF, Mmp28-/- mice developed increased adiposity, impaired glucose tolerance with elevated fasting glycaemia, reduced EE, and hepatic steatosis versus WT. By contrast, Mmp28-/- mice housed from birth in CMR remained lean, normoglycemic and largely free of fatty liver, with higher EE and activity, resembling WT mice. Blood pressure showed a genotype-environment interaction where Mmp28-/- mice showed higher systolic and diastolic values in CMR than SPF-housed Mmp28-/- mice, whereas WT mice tended to show the opposite trends. Liver transcriptomics revealed genes involved in fatty acid β-oxidation and mitochondrial catabolism were downregulated in SPF-housed Mmp28-/- mice, while genes related to inflammation and lipogenesis were upregulated. These transcriptomic changes are consistent with the observed obesity and metabolic dysfunction in these mice. Housing Mmp28-/- mice in CMR prevented these transcriptomic alterations, resulting in profiles comparable to those of WT mice. Taken together, these findings indicate that housing exerts a dominant effect on the metabolic and transcriptomic phenotypes of Mmp28-/- mice. Conclusions: The metabolic consequences of Mmp28 deletion are strongly influenced by the housing environment. Lifelong CMR exposure prevented obesity, glucose dysregulation and hepatic steatosis observed under SPF conditions. These effects may involve environment-driven immune and metabolic adaptations, with a possible contribution of microbiota-related mechanisms inferred from previous studies, although these were not directly assessed in this study. Overall, these findings highlight the critical role of environmental context in metabolic genetics and support microbiome-targeted or environment-mimetic strategies to mitigate obesity risk in genetically susceptible individuals.6 0Item Restricted The Impact of Digital Governance on the Performance of Municipal Sector Institutions in the Al-Jawf Region Municipality: The Mediating Role of Organizational Immunity(Saudi Digital Library, 2026) Alruwaili, Abdullah Naji; Salih, Ahmad AliThe Impact of Digital Governance on the Performance of Municipal Sector Institutions in the Al-Jawf Region Municipality: The Mediating Role of Organizational Immunity Prepared by: Abdullah Naji Sweilem Alruwaili Supervised by: Professor Dr. Ahmad Ali Salih Abstract المُلـخّـص باللغة الإنجليزية This study aimed to examine the effect of digital governance on the performance of municipal sector institutions affiliated with Al-Jouf Municipality, while testing the mediating role of organizational immunity. The study adopted the descriptive-analytical approach as the most appropriate for its nature and objectives. The study population consisted of all employees working in municipal sector institutions affiliated with Al-Jouf Municipality across senior, middle, and lower administrative levels. A proportionate stratified random sample of 300 employees was selected. Data were collected using a questionnaire as the main research instrument, which was developed based on the theoretical literature and previous studies. Its validity and reliability were verified using face validity and construct validity indicators, Cronbach’s alpha coefficient, composite reliability, and average variance extracted (AVE). Data were analyzed using descriptive and inferential statistical methods, in addition to structural equation modeling using the Partial Least Squares approach (PLS-SEM) through the SmartPLS software to test direct and indirect hypotheses. The descriptive results showed that the level of digital governance implementation in municipal sector institutions affiliated with Al-Jouf Municipality was high. The results also indicated that the level of institutional performance was moderate, while organizational immunity was at a moderate level. Hypothesis testing results revealed a positive and statistically significant effect of digital governance on institutional performance, a positive and statistically significant effect of digital governance on organizational immunity, and a positive and statistically significant effect of organizational immunity on institutional performance. Furthermore, the results confirmed the existence of an indirect effect of digital governance on institutional performance through organizational immunity, which acted as a partial mediating variable with a substantial influence on the relationship. The study recommended strengthening the adoption of digital governance practices in municipal sector institutions by developing digital infrastructure, building human capacities, and activating mechanisms of digital transparency, participation, and accountability. It also emphasized supporting organizational immunity through the adoption of flexible and proactive policies that contribute to improving institutional performance and achieving organizational sustainability in Saudi municipalities. Keywords: digital governance, institutional performance, organizational immunity, municipal sector institutions affiliated with Al-Jouf Municipality1 0Item Restricted Experimental and Numerical Study of Pulsating Water and Nanofluid Flow in Photovoltaic-Thermal Solar Collectors(University of Dayton, 2026) Mushabbab, Abdulwahed; Chiasson, AndrewPhotovoltaic thermal (PVT) systems are designed to generate electricity and useful heat from the same surface, but their performance is often limited by high photovoltaic (PV) cell temperature and weak heat transfer under laminar cooling conditions. Most previous work has used steady water flow and geometric modifications to improve PVT cooling, which can increase complexity and cost. Pulsating flow and nanofluids have shown heat transfer benefits in other applications, but their effect on full-scale flat-plate PVT collectors has not been clearly quantified. This work investigates the influence of controlled pulsating flow on the thermal and electrical performance of a flat-plate water-cooled PVT system under laminar conditions. Two experimental campaigns were carried out using the same indoor solar simulator with an average light intensity (I) between 700 and 800 W/m2. In the first part, water was used as the working fluid and the PVT system was tested under uncooled, continuous (steady)-flow and pulsating-flow operation. Flow rates of 1-4 L/min were examined with pulsation frequencies of 0.25, 0.5, 1 and 2 Hz. System performance was evaluated against uncooled and continuous-flow reference cases. Pulsating operation reduced the PVT surface temperature and increased thermal efficiency compared with continuous flow, while electrical efficiency showed a smaller but consistent improvement. The frequency of 0.5 Hz obtained the best performance, with thermal efficiencies above 50% at higher flow rates and electrical efficiency around 9.8% without a measurable increase in average pressure drop. In the second part of the thesis study, a 0.1 vol.% Al2O3/water nanofluid was used at a fixed flow rate of 4 L/min under continuous and pulsating flow. Frequencies from 0.25 to 2 Hz were tested and supported by a three-dimensional (3D) transient Computational Fluid Dynamics (CFD) model of the PVT channel. Pulsating nanofluid cooling further reduced PVT surface temperature, with the 2 Hz case giving the lowest measured value of about 30 degrees C and a maximum thermal efficiency increase of roughly 22% compared with continuous nanofluid flow. Electrical efficiency gains remained modest, on the order of 1%, which confirms that the main benefit lies in improved thermal recovery. The CFD predictions reproduced the experimental trends closely. Overall, the results show that pulsation frequency can be used as a control parameter to enhance the thermal performance of flat-plate PVT systems while maintaining laminar flow and only small changes in electrical efficiency.2 0Item Restricted تأثير ممارسات إدارة الموارد البشرية المستدامة على الميزة التنافسية: دراسة تطبيقية على العاملين بمستشفى بقعاء العام بمنطقة حائل(Saudi Digital Library, 2025) العتيبي, سعود; مصطفى, منى ساميهدف البحث إلى التعرف على تأثير ممارسات إدارة الموارد البشرية المستدامة على الميزة التنافسية “دراسة تطبيقية على العاملين بمستشفى بقعاء العام بمنطقة حائل”، واعتمد الباحث على أسلوب الاستقصاء في جمع البيانات الخاصة بالبحث، من خلال تصميم وإعداد قائمة استقصاء، وتمثل مجتمع هذا البحث في جميع العاملين بمستشفى بقعاء العام بمنطقة حائل بالمملكة العربية السعودية، والبالغ عددهم (348) مفردة وفقًا لإحصائية الموارد البشرية بمستشفى بقعاء العام لسنة 2023 – 2024م وقد قام الباحث بعمل حصر شامل لمجتمع البحث. وتوصلت نتائج الدراسة إلى وجود علاقة معنوية بين أبعاد ممارسات إدارة الموارد البشرية المستدامة وأبعاد الميزة التنافسية من وجهة نظر عينة البحث، كما أسفرت النتائج عن وجود تأثير معنوي لأبعاد ممارسات إدارة الموارد البشرية المستدامة على أبعاد الميزة التنافسية لدى العاملين في مستشفى بقعاء العام بمنطقة حائل بالمملكة العربية السعودية. وأسفرت النتائج أيضًا عن وجود فروق معنوية بين آراء عينة البحث حول درجة توافر كل من أبعاد إدارة الموارد البشرية المستدامة وأبعاد الميزة التنافسية وفقًا لاختلاف المتغيرات الديموغرافية (العمر، المستوى التعليمي، الخبرة الوظيفية).2 0Item Restricted أثر تفعيل آليات الإدارة الرشيقة في دعم نماذج إدارة المعرفة في القطاع الصحي السعودي(Saudi Digital Library, 2026) الحربي, سلطان; طاهر, شريفالعلاقة بين الإدارة الرشيقة وإدارة المعرفة تُعد من العلاقات التفاعلية التي تتسم بالديناميكية والتأثير المتبادل داخل البيئة التنظيمية. فالإدارة الرشيقة، بما تتضمنه من مبادئ مثل الاستجابة السريعة للتغير، والمرونة، والعمل الجماعي، والتحسين المستمر، تُوفّر بيئة تنظيمية داعمة لتدفق المعرفة وتوظيفها بفاعلية. ومن خلال تفعيل آليات الإدارة الرشيقة – مثل فرق العمل الذاتية، وتكرار الدورات التكيفية، والتغذية الراجعة المستمرة – يتم تعزيز العمليات الأساسية لإدارة المعرفة، والمتمثلة في: توليد المعرفة، وتخزينها، وتشاركها، وتطبيقها.2 0Item Restricted Efficient Intrusion Detection for IoMT: Integrating Machine Learning, Feature Selection, and Fuzzy Logic(Saudi Digital Library, 2026) Balhareth, Ghaida; Ilyas, MohammadThe internet of medical things (IoMT) has transformed healthcare by enabling real-time patient monitoring, remote diagnoses, and effective data exchange among connected medical devices and clinical systems. The increasing reliance on interconnected medical equipment has also intensified cybersecurity risks, as resource-constrained devices and wireless communication channels are vulnerable to attacks such as man-in-the-middle, spoofing, data injection, and ransomware. Intrusion Detection Systems (IDSs) play a critical role in mitigating these threats; however, traditional IDS approaches often struggle with high-dimensional IoMT data, class imbalance, and uncertainty in traffic patterns, which can increase false alarms and reduce reliability in safety-critical environments. This dissertation investigates efficient and deployable IDS designs for IoMT networks by integrating machine learning, feature selection, and fuzzy logic to improve detection reliability while reducing model complexity. First, the dissertation provide an extensive examination of IDS approaches proposed for IoMT, classifying them into machine learning, deep learning, fuzzy logic , and hybrid categories, while analyzing IoMT architectures and security vulnerabilities across layers. Next, it develops an efficient IDS model based on machine learning classifiers combined with feature selection techniques to enhanced detection accuracy and reduce computational cost in edge and gateway settings. Building on this direction, the dissertation proposed a multi-level feature selection pipeline that combines complementary ranking methods and consensus selection to identify consistently informative features, followed by a fuzzy inference system that supports uncertainty-aware intrusion classification using interpretable rule-based reasoning. The suggested IDS systems exhibit robust detection capabilities with reduced false-alarm rates, utilizing small feature sets appropriate for gateway and edge deployment throughout benchmark tests. The dissertation presents a cohesive security system that prioritizes efficiency, interpretability, and practical implementation for the protection of IoMT communications and the safeguarding of sensitive healthcare information. Future works will expand these IDS designs to include other IoMT datasets and real network traffic, while further investigating robustness in the context of concept drift and increasing adversarial strategies, all while maintaining low complexity and transparency.6 0