Efficient, Secure Learning And Resource Management For Wireless Networks, Jiahao Xue

USF Tampa Graduate Theses and Dissertations

The rapid advancement of wireless networks has enabled a wide range of applications such as federated learning (FL) and Internet of Things, with supporting technologies like radio frequency identification (RFID). However, resource management and security challenges in wireless networks remain insufficiently addressed for these representative applications. In this dissertation, we first investigate wireless resource management for FL, then study novel attack and defense mechanisms for RFID systems. Finally, we analyze the performance and security of artificial intelligence (AI)-enabled next generation wireless networks.

First, we investigate the client assignment and bandwidth allocation problem for FL in a multi-provider wireless setting. Unlike …

Building Trustworthy Information Systems: A Unified Framework For Comparative Risk Detection, Parisa Momeni

USF Tampa Graduate Theses and Dissertations

Risk detection in large scale information systems increasingly depends on heterogeneous data generatedby both centralized and distributed ecosystems. While centralized systems provide curated and validated reports, distributed environments produce large-scale and real-time observational evidence. Existing computational approaches analyze these ecosystems in isolation, limiting systematic comparison of risk repre-sentations across heterogeneous sources.

This dissertation presents a unified computational framework for comparative risk detection across centralized and distributed information systems. The framework provides a domain independent methodology for transforming heterogeneous risk reporting data into comparable multidimensional representations. To enable interpretable comparison of heterogeneous risk distributions, this work introduces the Geometric Overlap Score …

Urban Resilience To Environmental Displacement: Sustainable Design Strategies In Samarra And Najaf, Ghufran Rassam Hade, Khalid Hammood Mudhahe

AUIQ Technical Engineering Science

This research investigates the critical role of urban resilience as a strategic framework to mitigate climate-induced environmental displacement in hot-arid regions, specifically focusing on the historical Iraqi cities of Samarra and Najaf. As global temperatures rise, these cities face intensifying thermal stress and desertification, acting as primary ``push factors'' for involuntary migration. The objective of this study is to evaluate the efficacy of sustainable urban design and traditional planning morphologies in enhancing the adaptive capacity of these urban centers. The methodology employs a Variable-based Digital Spatial Analysis utilizing Landsat 8 TIRS and Sentinel-2 satellite imagery. Through advanced geospatial processing, original …

Printing Press Renewal, Ashley Mcguire, Margaret Wood Balch, Anna Kaetz, Timothy M. Wick

Libraries Professional Work

The University of Alabama at Birmingham (UAB) Libraries are home to a Chandler & Price printing press, originally built in 1885. Unfortunately, this press was not whole or fully operational when it was acquired by the UAB Libraries in the 1970s. Among its defects, the press lacked the treadle, Pittman arm, and crankshaft to power the press, a functioning rotating ink plate, a chase for holding the type in place, and the pin that keeps the large wheel turning in time with the gears that lead the machine to function. Members from the UAB Libraries Historical Collections and Reference and …

Exploring Gene Regulatory Neural Network Biocomputing Of Bacteria, Adrian Merle Ratwatte

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Artificial Intelligence (AI) has evolved from brain-inspired algorithms into a discipline that increasingly integrates with biological systems. While silicon-based platforms have advanced machine learning, they remain limited in energy efficiency and operation in environments beyond silicon. This motivates biological computing as an alternative, enabling efficient, resource-aware, and reconfigurable computing within living systems. This dissertation addresses these limitations by introducing a bacterial computing framework that models Gene Regulatory Networks (GRNs) as Gene Regulatory Neural Networks (GRNNs). The GRNN mirrors the structure and function of Artificial Neural Networks (ANNs) through gene-gene interactions across trans-omic layers, enabling natural, self-regulating information processing within living …

Magnetic Cellulose Nanocrystal Composites: Synthesis, Properties, Applications, And Opportunities, Mohammad Jahid Hasan, Kishore Chand, Esteban E. Ureña-Benavides, Erick S. Vasquez-Guardado

Chemical and Materials Engineering Faculty Publications

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Magnetic Cellulose Nanocrystal Composites: Synthesis, Properties, Applications, and Opportunities

Ion Irradiation Of Microelectromechanical Resonators, Hengky Chandrahalim, David D. Lynes

AFIT Patents

A method of enhancing an electromechanical coupling coefficient of a microelectromechanical (“MEMS”) device. The method includes applying, to a fully fabricated MEMS device, heavy particle ion radiation to the MEMS device at a fluence of at least 1×10¹⁴ cm.⁻². According to other embodiments of the present invention are directed to a bandpass filter comprising a plurality of MEMS devices fabricated in accordance with the methods provided. The MEMS of the plurality are electronically or mechanically coupled.

Photoluminescent Studies Of Metal-Organic Frameworks For Small Molecule Sensing, Julia T. Dematteo

USF Tampa Graduate Theses and Dissertations

Metal–organic frameworks (MOFs) are highly tunable nanoporous materials with broad applications in gas separation, drug delivery, light harvesting, and chemical sensing. The incorporation of photoactive components into MOFs enables the development of optical sensors capable of detecting a wide range of analytes. Porphyrins and metalloporphyrins are particularly attractive for such applications due to their high molar absorptivity, strong emission quantum yields, and versatile interactions with chemical species.

In this work, two porphyrinic MOFs, PCN-222 and MOF1(Cd), are investigated. Both frameworks utilize tetrakis(4-carboxyphenyl)porphyrin (TCPP) as the organic linker, imparting optical functionality to the materials. Integration of TCPP into the framework induces …

Visionarium, June 2026, Full Issue

International Journal of Emerging and Disruptive Innovation in Education : VISIONARIUM

No abstract provided.

Metacognition As Disciplinary Infrastructure In Ai-Mediated Learning, Tina R. Austin, Jason Gulya, Nick Potkalitsky

International Journal of Emerging and Disruptive Innovation in Education : VISIONARIUM

Metacognition is often presented as a response to generative AI’s disruption of teaching and learning, yet the term has become too generalized to guide practice. In AI-mediated environments, asking students merely to “reflect on your thinking” is insufficient. Because AI tools can redistribute cognitive labor, their educational value depends on how students use them and whether that use supports disciplinary forms of reasoning. This essay argues that metacognition must be understood as disciplinary infrastructure: students cannot effectively monitor their thinking without understanding the epistemological and ontological demands of the field in which they are working. Classrooms therefore become sites where …

Optimizing Human Capital In Ai-Enabled Architectures: A Systems Constraint And Capability Analysis, Jeremy A. Schlegel, Jennifer Daffinee

International Journal of Emerging and Disruptive Innovation in Education : VISIONARIUM

Artificial intelligence (AI) comprises not only models, but full socio-technical systems involving data pipelines, instrumentation, human-machine interfaces, deployment architectures, and organizational processes for design, monitoring, and evaluation. Using a systems-oriented analytical framework, this paper argues that despite accelerating advances in AI capabilities, human capital remains the enduring and dominant system constraint. Human interfaces define throughput limits in areas such as prompt engineering, data-stream curation, adjudication of model outputs, and the orchestration of hybrid automation workflows including robotics, scraping, and digitization. Synthesizing emerging research across human-AI interaction, machine-learning lifecycle management, organizational adoption, and adult learning theory, we present a socio-technical evaluation …

Law Or Flaw: A Double – Blind Study Comparing Student Comprehension Of Real And Ai Generated Legal Case Briefs, Grant Shostak, Nick Wintz, Melissa A. Petkovsek

International Journal of Emerging and Disruptive Innovation in Education : VISIONARIUM

In recent years, the U.S. legal system has seen an increase of legal filings using fictitious court cases or legal propositions generated by artificial intelligence (AI) (Stokel-Walker, 2026). Rules of professional responsibility require that lawyers review filings in which AI was used to ensure their accuracy (Missouri Bar, Office of Legal Ethics Counsel, 2024, Opinion No. 2024‑11) Despite this mandate, filings with fictitious cases and incorrect statements of law are being filed. Besides posing a threat to the parties to an action, such filings may set an unwarranted precedent for future cases. They also tie up court resources searching for …

A Smart Contract Framework For Project Financing In Gold Mining Operations: Implications For Improved Financial Forecasting, Silvia Lydia Priskilla, Mohammed Ali Berawi, Mustika Sari Dr.

Smart City

Gold mining projects are characterized by high capital intensity and significant operational variability, making financial forecasting particularly sensitive to the quality and timing of cash-flow data. In practice, conventional financing systems rely on multi-stage administrative processes that create delays between work completion and payment realization, reducing the reliability of financial records used for investment evaluation.

This study aims to develop a smart contract-based financing framework to improve the accuracy of profitability projections in gold mining projects. A case study approach is employed using operational and financial data from a mining project in Sumatra over the period 2023–2026. The analysis combines …

Label-Flip Attack Detection Via Trust-Weighted Aggregation In Federated Learning For Underground Mine Security, Md Sazedur Rahman, Sanjay Madria, Samuel Frimpong

Computer Science Faculty Research & Creative Works

Underground mining operations are increasingly dependent on autonomous vehicles, robotic drilling systems, and intelligent inspection platforms operating in confined, GPS-denied tunnel environments. These systems rely on distributed perception models to interpret navigation cues, hazard warnings, and environmental signals in real time. While centralized deep learning can enhance model performance, transferring raw operational data across mining sites introduces serious confidentiality and security risks. Federated Learning (FL) offers a privacy-preserving alternative by enabling collaborative model training without sharing local datasets. However, deploying FL in underground mining introduces several critical challenges: (i) Training labels may be modified either maliciously by compromised clients or …

Rf-Derived Viscoelastic Modeling For Blood Clot Occlusion Sensing, Abdulrahman Mohammed Aldosari

Thesis/ Dissertation Defenses

Early and reliable detection of vascular thrombus remains a critical challenge for portable and non-invasive diagnostic systems. This work presents an RF-based sensing methodology for blood clot occlusion sensing through the extraction of viscoelastic clot characteristics derived from microwave reflection coefficient (S₁₁) measurements. A compact single-port coaxial probe is employed to interrogate the vessel–tissue system over a wide frequency range (1–25 GHz), where the measured RF response is used to derive equivalent viscoelastic and electrical model parameters associated with clot formation and progression. Both lumped-element RLC and distributed transmission-line representations are utilized to establish the relationship between the measured dielectric …

Toward Passwordless Document Encryption, Isaac Henry Teuscher

Theses and Dissertations

Document files with sensitive information are used across nearly every industry. In recent years, cyberattacks targeting cloud-based file transfer applications have resulted in millions of sensitive documents being exposed. Although document encryption methods exist, they are often limited in usability, security, or deployability. Password-based encryption, the most widely available option, remains vulnerable to brute-force attacks, unauthorized sharing, and human error. We address these gaps in three phases. First, we present a structured comparative framework adapted from the usability-deployability-security model to evaluate nine document encryption methods across 15 design properties, identifying the benefits and limitations of current approaches. Second, we design …

Decarbonizing Electrical Substations: An Integrative Review Of Green Technologies And Sustainable Practices Across The Infrastructure Life Cycle, Sulthan Syah Ali, Mohammed Ali Berawi, Mustika Sari

Smart City

Decarbonization of electrical infrastructure s becoming increasingly important in efforts to meet climate change mitigation targets, particularly in reducing emissions from substations. However, conventional substations continue to release significant quantities of GHG emissions throughout their life cycle As an example, a typical 500 kV substation emits around 150,000 tCO2e from construction to decommissioning. In addition, the development of green substation concepts remains limited, particularly in Indonesia where standardized approaches are not yet established. In response to the need for more sustainable power infrastructure, this study aims to identify, classify, and review all types of green technologies, practices, and innovations that …

Real-Time Iot-Enabled Dissolved Oxygen Monitoring And Automated Wastewater Recirculation In Constructed Wetlands, Sivasankar Pandiarajan, Vanitha Sankararajan, Devarinti Chandu

Mansoura Engineering Journal

Wastewater treatment is necessary for environmental conservation and combating water pollution. This study demonstrates real-time dissolved oxygen (DO) monitoring in constructed wetland treatment. The system would ensure an adequate supply of oxygen through automated water circulation whenever the level is below 4 mg/L, and shut down when it reaches the normal level. From experiments conducted, it was observed that within three automated circulation processes, it is possible to increase DO concentrations from 0.5 mg/L to 5.0 mg/L. Additionally, Total Dissolved Solids reduced from 1,380 ppm to 920 ppm. pH also stabilized from 8.38 to 7.9. In this system, data is …

Bridging Machine Learning And Climate Futures: A Framework For Explainable, Self-Directed (Agentic) Ai Models In Monitoring, Mitigation, And Governance Of Anthropogenic Climate Impacts, Vijayanandh Rajamanickam, Ketaki Kulkarni, Vishwanadham Mandala, Ozgur Kisi

Mansoura Engineering Journal

Environmental and societal damage due to anthropogenic climate change demands detection and mitigation strategies that are both effective and accountable. Machine Learning (ML) appears to offer a powerful set of tools but remains unexploited in these areas. A key barrier remains its poor ability to draw causal inferences about external systems, an essential requirement for meaningful continued monitoring, acting on, and shaping of the climate. Explainable, self-directed learned models operate by attributing environmental changes and deciding how best to model the resulting dynamics—they offer a natural solution. Recent developments in computational ecology, meteorology, and ML are combined to propose a …

Deep Q Network For Adaptive Pelican Crossing Signal Optimization Balancing Pedestrian Safety And Vehicular Efficiency, Amalia Yasmin Chairunnisa, Andyka Kusuma, Jachrizal R. Sumabrata

Smart City

Static pelican crossing systems often fail to accommodate the stochastic arrival patterns prevalent in high-density transit-oriented development (TOD) zones, creating operational inefficiencies between pedestrian clearance and vehicular flow. At the Cikini Station transit hub in Jakarta, existing fixed signal cycles contribute to pedestrian delays and peak-hour congestion. This study evaluates an adaptive signal control model for mid-block pelican crossings using a Deep Q-Network (DQN) algorithm. To calibrate the simulation, empirical data were extracted from field CCTV footage using the YOLOv8 algorithm, accurately capturing 15-minute peak flow fluctuations and commuter surges. The system is formulated as a Markov Decision Process (MDP) …

Use Of Smart Safety Devices And Artificial Intelligence And Its Impact On Workplace Injury Reduction In High-Risk Industries In Cameroon: A Qualitative Exploration Of Worker And Management Perspectives, John Atabong Zifac

Doctoral Dissertations and Projects

Workplace injury has been a significant concern within high-risk industries in Sub-Saharan Africa, especially Cameroon, with weak worker safety standards, poor infrastructure, lack of compliance with regulatory requirements, and a limited level of digital infrastructure contributing to a high risk of worker injury. While artificial intelligence (AI) supported smart safety technologies have revolutionized the way companies conduct workplace safety management in developed nations, little research exists on the perception of these technologies and practicality among low-resource industrial operators in Sub-Saharan Africa. This qualitative phenomenological study investigated management and employee perceptions regarding the use of AI-based smart safety devices to reduce …

Sam-1: An Assistive Robot For Remote Patient Monitoring, Aana Farhana Ahsan

USF Tampa Graduate Theses and Dissertations

The global aging population has increased the demand for caregiving, while the availability of caregivers has not grown at the same pace. These trends have contributed to disparities in consistent and accessible care for older adults and increased caregiver burden. Geriatric care robots have emerged as a promising solution to support older adults and reduce caregiver burden. Existing systems have been developed for a wide range of applications, including rehabilitation, social support, assistance with activities of daily living, therapy, and caregiver telepresence. This thesis presents the development of SAM-1, an assistive robot designed to support remote monitoring of older adults …

Adaptive Intervention Strategies In Co-Evolving Multiplex Networks: A Reinforcement Learning Approach To Real-Time Misinformation Containment, Anjali Ashokrao Bhadre Dr., Harshvardhan Prabhakar Ghongade Dr.

Northeast Journal of Complex Systems (NEJCS)

The growing transmission of misinformation via social media creates serious challenges to public health, democracy and social cohesion. To date, methods used to contain misinformation rely upon static representations of networks and set rules for interventions. In contrast, this study presents the first Multiplex Adaptive Reinforcement Intervention Network (MARIN), a framework for real-time adaptive intervention in the context of dynamic misinformation transmission using co-evolving multiplex networks and deep reinforcement learning. Unlike past studies that have assumed static network structures, MARIN has the ability to allow for dynamic changes in network topology as a result of both misinformation transmission and intervention …

Tinyvgg-Based Real-Time Degradation Classification For Adverse Driving Scenes Using A Newly Collected Iraqi Driving Dataset, Yousif N. Abbas, Matheel E. Abdulmunim, Nada H. Ali, Ismail A. Mageed

Journal of Soft Computing and Computer Applications

Environmental conditions such as low-light at night, fog scattering, glare artifacts, rain streaks, and rain smear distortions are significant issues of camera-based perception in Autonomous Vehicles (AVs). These degradations alter the statistics of the scene, mask structure, introduce non-uniform noise, and adversely affect downstream vision processes, including detection and tracking. To overcome this shortcoming, this paper presents a lightweight TinyVGG-based degradation classification system that runs in real time. The network extracts discriminative spatial features with hierarchical convolutional encoding and projects them to a lower-dimensional semantic representation with fully connected layers and a multi-class predictor based on SoftMax. In addition, a …

Improving Approach Of Evolutionary Strategies For Clustering Technique Enhancement, Duaa Mahde Saleh, Hasanen S. Abdullah, Ahmad Zamsuri

Journal of Soft Computing and Computer Applications

The existence of the information has been the essential aspect of the whole society. Information is concentrated in all forms to be effectively utilized. Clustering — an unsupervised learning technique. It is based on data similarity that gives rise to issues in collection, challenges and instability in data structure. It proposes an advanced evolutionary method by combining two approaches. Firstly, it adopts the evolutionary approach and integrates the advantages between two methods to design one. Among them are Differential Evolution (DE) and Genetic Algorithm (GA), Evolutionary Strategy (ES) and Genetic Programming (GP), and Evolutionary Programming (EP) and Particle Swarm Optimization …

Comparative Study On Throughput Optimization In Nfv: Traditional Dissemination Techniques Vs. Swarm Intelligence Approaches, Sanaa Salih Alwan, Asia Ali Salman, Wulfrano Arturo Luna Ramírez

Journal of Soft Computing and Computer Applications

Network Functions Virtualization (NFV) modernizes networks by replacing hardware with software, creating a more flexible network architecture and offering flexibility in dynamic network environments. This foundational technology is essential for creating the networks of the future, including the Internet of Things (IoT) and cellular services. NFV does provide flexibility, but it struggles to maintain system throughput during high traffic loads while achieving high resource utilization efficiency and dynamic packet routing. The problem lies in the fact that traditional request distribution mechanisms, such as flooding and gossip, fail to operate efficiently in complex network topologies (scale-free networks), leading to: (a) random …

A Comprehensive Review Of The A* Algorithm: Evolution, Applications, And Future Trends In Path Planning, Saleel H. Abood, Hussein M. H. Al-Khafaji, Mohanned M. H. Al-Khafaji

Journal of Soft Computing and Computer Applications

Despite being a fundamental problem to autonomous robotics and intelligent navigation systems, path planning is still a challenge. The A^* algorithm is often used among search-based techniques for optimal search performance, as it's a tradeoff of computation. The above techniques have been developed for various applications as many versions of A^* Dynamic A^* (D^*), D^* Lite, Hybrid A^*, and Anytime A^* are suggested to deal with dynamic environments, real-time constraints, and kinematic restrictions. This paper comprehensively and structurally reviews the A^* algorithm and its major extensions, encompassing historical development, methodological …

Skin Lesion Classification Using Cnn Model And Augmented Dataset, Mohammed Nawzad Mohammed-Ramzi, Aso M. Aladdin

Journal of Soft Computing and Computer Applications

Skin cancer is a deadly disease. Skin lesion classification is a critical challenge due to its prevalent and deadly nature. Skin lesions are difficult for dermatologists to detect using eye examination, which is time-consuming and variable. A deep learning model of skin lesions classification has been proposed using a Convolutional Neural Network (CNN) trained on the HAM10000 dataset of 10,015 dermatoscopies. To improve resilience and address the dataset's extreme class imbalance, data augmentation techniques such as geometric transformations, brightness/contrast adjustments, blurring, noise addition, histogram equalization, color space alterations, and elastic deformations are used. With a carefully balanced 10% test set, …

Development And Standardization Of Teds Actuator Templates Under Ieee 1451 Framework, Jim Kang

Theses and Dissertations

The IEEE 1451 standard is a family of standards that defines a framework for smart transducers, including both sensors and actuators, to support consistent, interoperable, and cost-effective integration across diverse applications. However, the current IEEE 1451.4 standard templates only define the method for encoding Transducer Electronic Data Sheet (TEDS) information for a broad range of sensor types and applications; they do not address actuator TEDS. Specific types of sensors and actuators are being developed to assess underground environmental conditions in cold regions with widespread permafrost. Evaluating subsurface conditions before construction can help prevent high construction expenses for structures built on …

Modelling And Analysis Of 50 Mwp Solar Pv Integration Into Tanzania’S Transmission Network: A Case Study Of Tagamenda Substation, Iringa Region, Santos Kihwele

Tanzania Journal of Science

While increasing the share of renewable energy in the grid, grid integration studies for the utility solar photovoltaic (PV) plants are vital, given their intermittency and the fact that Tanzania has never had one connected to the grid. This paper presents a 50 MWp grid integration study, including a technical analysis conducted using PSS®E software. The study investigates the grid behaviour during the integration of the 50 MWp solar plant, considering the most suitable technical and economic solutions. The study analysed the load flow under normal conditions, contingency analysis (N-1), short- circuit analysis, and voltage stability assessment. The results show …