SACM - United States of America
Permanent URI for this collectionhttps://drepo.sdl.edu.sa/handle/20.500.14154/9668
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Item Restricted The Red Sea Region and the Belt and Road Initiative of China(New York University, 2024-12) Alomri, Khader; Rama, ShinasiThis thesis looks at the sequential ripple effect of China’s Belt and Road Initiative (BRI) on Red Sea countries, emphasizing Djibouti, Egypt, and Sudan. In line with the above research questions, the study uses qualitative and quantitative data to establish the impact of the BRI on the economy, geopolitics, and socio-political systems. The study incorporates the big picture of the Red Sea's strategic value; the Red Sea is a critical shipping lane between Europe, Asia, and Africa that is vital for commerce and energy. The study places the BRI in this context, looking at how Chinese investments in ports, railways, and free-trade zones are intended to increase interconnectivity and boost economic activity. The study reveals a strong positive impact on GDP growth rates, the volume of trade, and FDI inflow in the analyzed countries. However, these benefits are accompanied by severe problems, including high debt and economic dependence on China. This thesis explores the political consequences of the BRI and how, through its strategic investment and military foothold in the region, it could shift the power dynamics, threaten Western dominance, and stir tensions about security in the region. First, as indicated in the analysis of crucial BRI investment areas, there is an analytical focus on the economic-development aspect of the BRI. In contrast, there is silence about a second more political aspect of BRI. This is because the BRI represents both an economic-development initiative and a geopolitical power play, indicating China’s desire to alter the global trade map and consolidate its position. This thesis analyzes three countries: Djibouti, Egypt, and Sudan. These case studies of the BRI show both the positive outcomes and the negative outcomes for the nations. These case studies underscore the efficiency of debts, the disclosing of policies, and the cooperation within the region to avoid issues detrimental to the achievement of the goal of sustainable development. The last chapter provides policy implications for rebuilding regional stability and suggestions for future work focusing on using the BRI’s economic opportunities and mitigating the BRI’s geopolitics and socio-economic concerns. The findings of this thesis help to enhance knowledge about the BRI’s impact on the Red Sea region and provide valuable recommendations for various actors.31 0Item Restricted A PUF-based Keyless Authentication Paradigm for Secure IoT Systems(University of Louisiana at Lafayette, 2024) Alahmadi, Sara; Bayoumi, MagdyThe Internet of Things (IoT) drives innovation at individual and industrial scales, introducing massive interconnecting devices with varying security requirements. Authenticating these devices has emerged as a critical challenge, especially for constrained devices. In this context, Physically Unclonable Functions (PUFs) have gained popularity as promising hardware security primitives that offer lightweight and efficient solutions. Despite PUFs’ potential, they are susceptible to modeling attacks, leading researchers to explore new design approaches to increase their resiliency. This research addresses these challenges by developing different Arbiter PUF (APUF) solutions applicable to various applications from constrained devices to those requiring high security and post-quantum protection. First, a taxonomy of consumer IoT ( CIoT) and industrial IoT (IIoT) was presented to identify their distinguishing aspects. Addressing IoT security effectively requires considering the specific needs of different types of IoT applications, mainly consumer and industrial IoT. Second, a detailed analysis of APUF-based designs was conducted, measuring each design’s security scalability. This work evaluates the area and security of studied designs and defines an efficiency metric as security gain per area. Therefore, it showcases how the security of each of the studied design approaches scales in terms of area versus security, providing a guideline and insight for developers and for future improvement. Third, obfuscating techniques were introduced to secure APUF against modeling attacks. The methods implement transformation functions to obscure and safeguard the responses from modeling attacks. The first technique incorporates weak PUFs to fortify strong PUFs. The second technique encodes the challenges into constant weight vectors before generating the response. In addition, Dynamic Feedforward PUF was introduced to enhance the original Feedforward PUF. The method has two levels of configuration and incorporates randomness in the response generation process. Finally, a post-quantum PUF-driven authentication and message exchange framework (McPQ-PUF) was developed. This hybrid authentication and secret message exchange scheme utilizes two security primitives: APUF and McEliece, a post-quantum resilient Public Key Encryption (PKE). The McPQ-PUF framework is resilient against modeling and quantum attacks. This dissertation’s contribution should facilitate PUF-based authentication in an IoT environment. It provides secure and efficient solutions that address IoT ecosystems’ diverse security needs.8 0Item Restricted PARETO OPTIMALITY BASED ZONAL ALLOCATION OF DISTRIBUTED ENERGY RESOURCES CONSIDERING TECHNICAL AND ECONOMIC CONSTRAINTS(University Of Missouri - Kansas City, 2024) Alanazi, Waleed; Goli, PreethamDistributed Energy Resources (DERs) play a crucial role in enhancing the resilience of distribution networks during High-Impact Low-Frequency (HILF) events. Optimal al location of DERs is essential to minimize capital costs while improving the operational performance of the distribution network. This paper introduces a Pareto Optimality Based Grey Wolf Optimization (GWO)approach for the strategic placement of DERs across various zones of a distribution network. We formulate a multi-objective optimization problem within the fuzzy domain, aiming to minimize DER installation costs, reduce power losses and enhance the voltage profile of the network. The proposed optimization algorithm is evaluated using the IEEE 123-bus test system through a co-simulation between MATLAB and OpenDSS. The results illustrate that the proposed approach effectively balances cost and power losses while ensuring the voltage profile remains within the NERC standards.39 0Item Embargo Optimized Dynamic Electric Vehicles Charging in Smart Cities(University of Maryland Baltimore County, 2024-11-22) Alaskar, Shorooq Sulaiman; Younis, MohamedRecent technological advances have fueled interest in the development of smart cities where the convenience and health of inhabitants are core objectives. Increased automation and reduced green gas emission are prime means for achieving these objectives. No wonder that there is a major push for the adoption of electrical vehicles. Yet, the deployment of electric vehicles (EVs) is slow-paced. One of the primary obstacles hindering the widespread adoption of EVs is range anxiety, which refers to the fear that an EV will not have sufficient battery charge to reach its destination or a nearby charging station. Additionally, long charging times pose a significant barrier, as recharging an EV battery can take considerably longer compared to refueling a conventional gasoline vehicle, making it less convenient for users. Furthermore, the scarcity of charging infrastructure capable of handling a large number of EVs exacerbates these concerns, deterring potential buyers due to worries about accessibility and convenience. Most of the existing charging techniques require EVs to remain stationary while being charged. Wireless charging has emerged as a viable solution that mitigates such a shortcoming by enabling dynamic EV-to-EV charging. It can also expand the driving range of automobiles if the battery can be continuously charged while the vehicle is in motion, hence extending the traveled distance. EV-to-EV charging provides drivers with greater temporal and spatial flexibility, specifically in densely populated urban regions, while aiding in the reduction of energy consumption. It can also mitigate the burden of the grid during peak loads and optimize power usage during off-peak hours. EV-to-EV charging not only adds convenience to drivers, but it enables a new business model as well, where mobile suppliers may sell their energy to EVs on the road. This dissertation addresses the challenge of the dynamic charging and routing of EVs in smart cities. We first present RIMEC, a Routing for Increased Mobile Energy Charging algorithm that determines an optimized EV travel route for utilizing the Mobile Energy Disseminator (MEDs) in order to maximize the potential energy that can be harvested while minimizing the impact on travel time. Second, we introduce an EV-to-EV charging framework for energy suppliers. The framework opts to maximize the profit, while considering battery degradation and the overhead cost. The optimization is modeled as a time-space network and a dynamic programming-based solution strategy is pursued to optimally pair and route the energy supplier (ES) and requester (ER). Specifically, ES is incentivized to rendezvous ERs at encounter nodes to dispense the requested energy through platooning. The complexity of the problem arises from nonstationary consumers and service supply, which make monitoring and synchronizing the movement of ES and ER spatiotemporally challenging. Third, we tackle the problem of dynamic EV-to-EV charging that aims to maximize the supplier's profitability within a specific timeframe, taking into account overhead costs. Finally, we address the multi-supplier, multi-requester routing problem. We formulate the optimization problem mathematically as a mixed-integer program and develop a local search based-heuristic algorithm. Our objective is to optimize system-level metrics, including profitability and throughput. The simulation results validate the effectiveness of our proposed approach, demonstrating significant improvements in maximizing overall profit while minimizing energy consumption, travel time, and distance for requesters.20 0Item Restricted EXPLORING SIC QUANTUM-DOT NANOCOMPOSITES THROUGH NON-THERMAL PLASMA SYNTHESIS: A CRYOGENIC INVESTIGATION OF PHOTOLUMINESCENCE (PL) AND QUANTUM YIELD (QY)(North Dakota State University, 2024) Alharthi, Naif Saad; Hobbie, ErikBy using non-thermal plasma (NTP) synthesis, we generated 2D silicon carbide (SiC) nanocrystals (NCs) from a liquid precursor tetramethylsilane (Si(CH3)4) (TMS). These NCs have a distinct surface emission. By working in an oxygen-shielded environment, we obtain high photoluminescence quantum yields (QYs) of nearly 70% which present a high efficiency of emission. Microscopy analysis (TEM/AFM) shows that the NCs have a size of about 5-10 nm and a very small thickness of under one nanometer (1 nm). X-ray diffraction (XRD) and high resolution transmission electron microscopy (HRTEM) confirm their crystallinity and thickness. Raman spectra also confirm crystallinity relative to the bulk, indicative of crystalline quasi-2D material and the layered structure of the flakes.FTIR analysis reveals Si-OCxHy groups on the surface of the SiC NCs. These functional groups play a significant role in the light emission of these confined 2D particles. These discoveries collectively provide additional insights about the complex relationship between the surface of the nanocrystal and the quantum confinement that affects how light energy is used in these materials. In a connected manner, SiC QDs-based polymer nanocomposites (PNCs) have been synthesized and investigated for their radiative emission dynamics. These materials have attracted significant interest due to their wide range of potential applications, including new biolabeling and solar-collection technologies. While the nature of photoluminescence (PL) relaxation in 2D layered vitrified colloidal silicon-carbide (SiC) nanocrystals (NCs) is still under investigation, efficient PL from SiC QDs polymer nanocomposites has been achieved. In this study, we investigate the radiative emission dynamics and cryogenic photoluminescence response of a novel two-dimensional silicon carbide nanocrystal-polymer composite synthesized via the off-stoichiometric thiol-ene process. To delve into the details, we used four-functional thiol, three-functional allyl, and a group of dodecyl-covered two-dimensional stacked silicon carbide (SiC) nano crystals (NCs) to make a series of polymer/nanocrystal composites. We looked at how the emission wavelength, quantum yield, and temperature changed, especially the changes in PL dynamics when cooled to cryogenic conditions.5 0Item Restricted RECYCLABLE THERMOPLASTIC ELASTOMERS FROM DYNAMICALLY CROSSLINKED HAIRY NANOPARTICLES (HNPs)(Clark Atlanta University, 2024-12) Alsahli, Sultan; Khan, IshratChain-end furan-functionalized hairy nanoparticles (HNPs) with robust polystyrene (PS) cores and flexible polydimethylsiloxane (PDMS) shells were successfully synthesized through a one-pot high vacuum anionic living polymerization process. The synthesis involved the preparation of the living core by copolymerizing styrene and divinylbenzene, followed by the addition of hexamethylcyclotrisiloxane (D3) as the second monomer to the living polystyrene core. The resulting living polymer was terminated with dimethylchlorosilane, yielding HNPs terminated with Si-H functional end groups (HNP-SiH). Furan-functionalized HNPs were then obtained by hydrosilylation of HNP-SiH with 2-vinylfuran to (HNP-F). In parallel, furan end-functionalized poly(dimethylsiloxane) and poly(styrene) were synthesized using anionic living polymerization. The successful synthesis of these structures was confirmed through 1H NMR and FT-IR spectra. Differential scanning calorimetry revealed two thermal transitions of HNP, indicating the presence of a poly(dimethylsiloxane) soft phase and a poly(styrene) hard phase, classifying the HNP as thermoplastic elastomers. A Diels−Alder chemistry approach was employed as a proof of principle for creating thermoreversible cross-linked networks in the polymer. Furan-functionalized HNP demonstrated the formation of thermoreversible elastomeric networks upon cross-linking with bismaleimide (BMI) via Diels−Alder coupling reactions. Kinetic studies of the forward Diels–Alder reaction between the functionalized polymer and BMI revealed a temperature-dependent increase in reaction rate constants, following second-order kinetics. The activation energy of the cross-linking reactions for furan functionalized HNP, PS, and PDMS with BMI were determined. The resulting retro-Diels−Alder cross-links in the polymer dissociated at elevated temperatures (around 140–154 °C), as confirmed by (DSC). Scanning electron microscopy (SEM) was used to study the morphological changes of furan-functionalized hairy nanoparticles, polystyrene, and PDMS at the un-crosslinked, crosslinked, and decrosslinked stages in reaction with bismaleimide. The analysis provided detailed insight into structure development in such types of materials at each cross-linking stage. The results suggest that furan functionalized HNPs are promising building blocks for preparing thermo-reversible elastomeric networks.4 0Item Restricted EVALUATION OF INUNDATED ASPHALT PAVEMENT USING PERFORMANCE MODELING AND LABORATORY CHARACTERIZATION(University of Florida, 2025) Almutairi, Abdulrahman; Tia, MangFlooding is recognized as one of the most common natural disasters. It interrupts the transportation network and causes major damage to the pavement. It can cause a reduction in pavement life and a rapid decline in structure strength. This study aims to evaluate the performance of inundated flexible pavements by predicting fatigue cracking and rutting and studying the effects of key mixture factors on moisture susceptibility. The impact of lowering the water level through the base and subgrade was evaluated. Two types of bases (A-1-a and A-2-4) and subgrades (A-4 and A-7-5) were evaluated. The soil-water characteristic curve (SWCC) is used to predict the resilience modulus of unsaturated soils, and KENLAYER is implemented to obtain the critical strains. The fatigue crack and rut were predicted using MEPDG distress equations. Laboratory tests were conducted to evaluate the key mixture factors in this study. These key mixture factors were the polymer modification (Polymer-Modified Asphalt and High Polymer), the air void content (4%, 7%, and 10%), the binder content, and the anti-stripping agent (Hydrated Lime and Liquid Anti-strip). The results showed that pavement with a strong base and strong subgrade (SBSG) consistently performed better with lower deflection, reduced strains, low fatigue crack growth, and least rut development. The mixture's indirect tensile strength (ITS) can be influenced by the polymer modification, the air void content, the binder content, and the anti-stripping agent. All the mixtures exhibited excellent moisture resistance, surpassing Florida Department of Transportation's specifications of 80%.25 0Item Restricted Design and Synthesis of Rapid-Release Naloxone Ester Conjugates for Enhanced Antidote Efficacy(University of the Pacific, 2024) Balgoname, Abdulmalek Ahmed; Mamoun, AlhamadshehAbstract By Abdulmalek Ahmed Balgoname University of the Pacific 2024 The opioid crisis remains a major public health challenge, exacerbated by the surge in overdose deaths linked to potent synthetic opioids such as fentanyl. Naloxone, a life-saving opioid antagonist, is pivotal in emergency overdose interventions due to its rapid reversal of opioid effects. However, its short duration of action limits its effectiveness, particularly in situations where timely medical follow-up is unavailable. To address this limitation, our lab has developed an innovative prodrug delivery system for naloxone, aimed at enhancing its pharmacokinetic profile and enabling controlled, sustained release. This dissertation research focuses on the synthesis and in vitro stability evaluation of novel naloxone ester conjugates. The study highlights the influence of ester chemistry, where variations in the steric and electronic properties of the ester moiety significantly impact hydrolysis rates and naloxone release in plasma. Steric hindrance near the ester bond modulates access to hydrolytic enzymes, while electronic effects govern bond polarization, collectively fine-tuning the release profile. These findings underline the potential of tailored ester chemistry to optimize naloxone delivery and address the challenges of opioid overdose management, paving the way for improved patient outcomes.13 0Item Restricted Identity in and out of Time: Narratives of Temporal Displacement in Contemporary Migrant Fiction(The George Washington University, 2024) Alshammari, Raad; Daiya, KavitaThis dissertation explores the role of time in contemporary migrant fiction, investigating the question of how representations of migrant temporality shape fictional narratives of displacement and deepen our understanding of “the age of migration.” Situated at the intersection of temporal turns in both migration studies and literary studies and informed by theories of postcolonial temporality, the dissertation analyzes six different works of postcolonial migrant fiction by major writers of multi-ethnic American and British multicultural literature. The analyzed texts all emphasize the temporal dimensions of migrant mobility, featuring a consciousness of temporal displacement that operates across both thematic and formal dimensions of the narrative. The dissertation seeks to illuminate how these texts negotiate the intricate relationship between displacement and temporality while articulating migrant experiences and identities in contemporary contexts. It argues that time plays a pivotal role in the literary production of meaning around individual and collective migrant identities, functioning across political, cultural, and aesthetic dimensions. Central to the dissertation’s argument is the idea that migrant movement in these works extends beyond a purely spatial journey. It represents a temporal movement that transgresses and redraws the temporal boundaries of both the self and the world as constructed by cultural, national, and global forms of hegemony. By emphasizing this temporalized understanding of mobility, the dissertation underscores a sense of agency and subjectivity that challenges the framing of migrant experiences within geographical narratives of time. It demonstrates how migrant temporalities enable a “cognitive remapping” of a world that is no longer anchored in fixed ideological teleologies but is instead shaped by the global interconnectedness of economies, cultures, and populations. In this context, the dissertation highlights the importance of recognizing the “in-betweenness” of migrant subjectivity as a form of temporal in-betweenness—one that not only captures the nuances of the migrant experience but also reflects the broader condition of global humanity. Here, the dissertation underlines the role of migrant literature as a distinctive space where the de- spatialized, in-between temporality of the migrant subject becomes tangible and representational.7 0Item Restricted Next-Generation Diagnostics: Deep Learning based Approaches for Medical Image Analysis(Florida Institute of Technology, 2024-12) Alsubaie, Mohammed; Li, XianqiHigh-resolution medical imaging plays a pivotal role in accurate diagnostics and effective patient care. However, the extended acquisition times required for detailed imaging often lead to patient discomfort, motion artifacts, and increased scan failures. To address these challenges, advanced deep learning approaches are emerging as transformative tools in medical imaging. In this study, we propose a conditional denoising diffusion model-based framework designed to enhance the resolution and reconstruction quality of medical images, including Magnetic Resonance Imaging (MRI) and Magnetic Resonance Spectroscopic Imaging (MRSI). The framework incorporates a data fidelity term into the reverse sampling process to ensure consistency with physical acquisition models while improving reconstruction accuracy. Furthermore, it leverages a Self-Attention UNet architecture to upsample low-resolution MRSI data, preserving fine-grained details and critical structural information essential for clinical diagnostics. The proposed model demonstrates adaptability across varying undersampling rates and spatial resolutions, as a network trained on acceleration factor 8 generalizes effectively to other acceleration factors. Evaluations on publicly available fastMRI datasets and MRSI data highlight significant improvements over state-of-the-art methods, achieving superior metrics in SSIM, PSNR, and LPIPS while maintaining diagnostic relevance. Notably, the diffusion model excels in preserving intricate structural details, detecting small tumors, and maintaining texture integrity, particularly in glioma imaging for mapping tumor metabolism associated with IDH1 and IDH2 mutations. These findings underscore the potential of deep learning-based diffusion models to revolutionize medical imaging, enabling faster, more accurate scans and improving diagnostic workflows across clinical and research applications.12 0