Digital Commons Network^™

Development Of Proposed Airworthiness Certification Criteria For Interference-Tolerant Radio Altimeter Systems, Matheus B. Furstenberger

Student Works

Radio altimeters provide height-above-ground information to flight deck displays and multiple safety-critical aircraft systems, however legacy certification standards were not developed for high-power terrestrial wireless services operating in adjacent C-Band spectrum. This study addressed the absence of a consolidated airworthiness certification framework for interference-tolerant radio altimeter systems installed on Title 14 Code of Federal Regulations Part 25 transport category airplanes. An archival research synthesis was conducted using publicly available regulations, proposed and final rules, technical standard orders, advisory circulars, airworthiness directives, industry standards, spectrum-management documents, technical studies, and stakeholder comments. Qualitative content analysis and source triangulation were used to identify …

Provocable Forgiveness In Noisy Brand--Consumer Systems:An Agent-Based Study Of Repeated Interaction, Tahere Ahmadiyan, Hamidreza Navidi, Behbod Keshavarzi

Northeast Journal of Complex Systems (NEJCS)

Repeated brand--consumer exchange is often treated as a managerial problem of loyalty, recovery, and trust. It can also be read as a small complex system: many local decisions about cooperation, retaliation, and forgiveness accumulate into market-level selection. This study uses that perspective to examine which relational rules survive when communication is imperfect. Eight canonical Iterated Prisoner's Dilemma strategies are translated into marketing archetypes and evaluated through round-robin tournaments, a six-level noise sweep, proportional-fitness ecological dynamics, and finite-population Moran invasion tests. The tournament leaderboard is calculated without same-strategy self-play, so that reported payoffs reflect inter-archetype competition rather than homogeneous self-coordination. At …

Explainable Machine Learning For Biomedical Diagnostics: Optical Imaging And Eeg Signal Analysis, Fozia Rajbdad

LSU Doctoral Dissertations

The growing convenience of complex biomedical data begins new roads for better disease detection and functional identification via artificial intelligence (AI). Nevertheless, conventional analysis methods often rely on basic metrics that drop sensitive biotic differences, and various AI systems are difficult to infer, limiting their clinical reliability and practical use. There is a growing need for explainable, physiologically relevant computational models that can extract key biomarkers from diverse biomedical data sources. This dissertation addresses this problem by obtaining explainable machine learning and deep learning procedures for studying biomedical signals and optical imaging data.

This dissertation is divided into two parts; …

Efficient Edge Implementation Of Midasnet For Real-Time Depth Estimation In Indoor Robotics, Muhammed Yasi̇n Adiyaman, İsmai̇l Fai̇k Başkaya

Turkish Journal of Electrical Engineering and Computer Sciences

Real-time depth estimation is crucial in many vision-related tasks, including autonomous driving, 3D reconstruction, robotics, and simultaneous localization and mapping. In recent years, many methods have been proposed to solve depth maps from images by utilizing different modality setups like monocular vision, binocular vision, or sensor fusion. However, for real-time deployment on edge devices, complex methods are not suitable due to latency constraints and limited computation capacity. For edge implementation, models should be simple, minimal in size, and hardware-friendly. Considering these factors, we implemented MiDaSNet, which works on the simplest setup of monocular vision and utilizes hardware-friendly convolutional neural network-based …

A Holistic Approach For Workforce Scheduling And Routing, Kerem Can Manalp, Ansel Kaplan Erol, Kutluhan Erol, Cem Evrendi̇lek

Turkish Journal of Electrical Engineering and Computer Sciences

The workforce scheduling and routing problem (WSRP) involves assigning tasks across multiple locations while accounting for varying travel times, service durations, time windows, and skill requirements in a wide range of industries, from healthcare to telecommunications. This paper presents a mixed-integer programming model for the WSRP that balances the trade-off between cost and customer satisfaction using a score-generation function and subsequently evaluates the trade-off between solution quality and computation time for several algorithms on well-known datasets. We demonstrate that our model effectively balances cost, service-level agreement satisfaction, and task priorities while providing high-quality solutions in a timely manner. Observing that …

Cnkg: Harnessing Large Language Models For Cognitive Neuroscience Knowledge Graph Construction, Ali Sarabadani, Kheirollah Rahsepar Fard, Hamid Dalvand

Turkish Journal of Electrical Engineering and Computer Sciences

Textual resources are among the most valuable sources of information in cognitive neuroscience (CN) for understanding and investigating brain activity and cognitive processes. Extracting and constructing knowledge graphs (KGs) from these texts can facilitate medical research by providing deeper insights into neurological diseases and brain function. In recent years, the use of large language models (LLMs) in natural language processing (NLP) has become increasingly widespread, significantly enhancing the extraction of meaningful information from large volumes of text. This study proposes a novel approach for constructing and evaluating a specialized knowledge graph, termed the cognitive neuroscience knowledge graph (CNKG), from scientific …

Erratum To “Sgsc-Kko-Lstm: A Deeplearning Classifier Model For Smart Grid” [Turkish Journal Of Electrical Engineering & Computer Sciences 34 (2) 2026 185-213], Samaniba Imchen, Dushmanta Kumar Das

Turkish Journal of Electrical Engineering and Computer Sciences

The first and second authors were incorrectly ordered in the article PDF due to a typesetting error. To rectify this oversight and ensure the accuracy of the published work, the author order have been corrected as follows: 1. Samaniba Imchen – First Author 2. Dushmanta Kumar Das – Second Author

A link to the original article can be found at: https://doi.org/10.55730/1300-0632.4170

A Revenue-Driven Approach For Enhanced Task Utilization In Vehicular Cloud Computing, Ashish Singh Saluja, Satyabrata Das, Sanjib Kumar Nayak, Sohan Kumar Pande

Turkish Journal of Electrical Engineering and Computer Sciences

Vehicular networks support intelligent transportation through vehicle-to-roadside Units (V2R) and vehicle-to-vehicle (V2V) communication but face challenges from dynamic topologies, limited RSU coverage, and bandwidth scarcity, which impact service delivery and revenue. RDA-ITU addresses these challenges by integrating V2R and V2V paradigms to maximize RSU revenue, enhance service availability, and improve system efficiency. It dynamically allocates services based on real-time network conditions and vehicle mobility, leveraging V2V relays to optimize both RSU-direct and cooperative communication. Through extensive simulations, RDA-ITU significantly outperforms four baselines: RBSM, VVMM-U, VVMM-LW, and VVMM-MA. It achieves 81.1% higher total revenue, 154.8% more completed requests, and 103.6% higher …

Scalefusion: Hierarchical Feature Aggregation For Unified Multiscale Object Detection, Ayşenur Yaylaci, Berru Kaya, Mehmet Kiliçarslan

Turkish Journal of Electrical Engineering and Computer Sciences

Detecting objects across a wide range of scales, particularly small ones, remains a significant challenge in computer vision. Existing methods often improve small object detection at the cost of performance on larger objects or introduce significant computational overhead through external techniques like image slicing. This paper introduces ScaleFusion, a novel, unified, end-to-end object detection architecture designed to provide robust performance across all scales within a single model. The core of our approach is a hierarchical feature aggregation strategy structured like a tree. ScaleFusion processes an image by running a shared backbone network only on fine-grained patches at the lowest level …

Swindeitvit: A Soft Voting Vision Transformer Ensemble For Accurate And Explainable Solar Panel Fault Detection, Mahe Zabin

Turkish Journal of Electrical Engineering and Computer Sciences

Solar panels are becoming very essential in providing sustainable energy but they are usually affected by defects on the surface like dust, snow, bird droppings, physical damages and electrical faults which interfere with their performance. These faults must be identified accurately and in a timely manner to enhance energy efficiency, lower the maintenance cost, and supplement the traditional manual methods of inspection which are labor-intensive, time-consuming and subject to human errors in judgment. The most common methods, such as traditional CNNs and hybrid architectures tend to be less accurate, less explainable and cannot be properly evaluated to be deployed in …

Assessing Computer Vision Based Conflict Detection In Uas Traffic Monitoring Under Secure Communication Constraints, Fadjimata Issoufou Anaroua

Doctoral Dissertations and Master's Theses

The rapid growth of Unmanned Aircraft Systems (UAS) and Advanced Air Mobility (AAM) is creating a new low-altitude airspace ecosystem where drones, air taxis, service suppliers, communication networks, sensors, and ground-based monitoring systems must work together safely. Within this ecosystem, UAS Traffic Management (UTM) is expected to provide a digital framework for coordinating operations beyond traditional air traffic control. However, reliable integration also requires resilient monitoring methods that can detect non-cooperative aircraft, protect communication links, and maintain timely situational awareness under real-world constraints.

This dissertation examines how computer vision can support cooperative monitoring systems such as Remote ID and ADS-B …

Investigation Of Energy Efficiency Of An Autonomous Mobile Photovoltaic-Thermal (Pv/T) System With A Polycarbonate Absorber, Sanjar Kodir Ugli Shoguchkarov, Anvar Rakhmat Ugli Rakhmatov, Rushana Husen Kizi Abdullaeva, Orazbek Maratbay Ugli Temirbaev

Technical science and innovation

This study analyzes the enhancement of energy efficiency in photovoltaic-thermal (PV/T) systems, which enable the simultaneous generation of electrical and thermal energy from solar radiation. The research focus is an autonomous mobile unit based on multi-channel polycarbonate heat collectors with a hydraulic diameter of 8 mm, characterized by their lightweight nature and superior corrosion resistance compared to conventional metal absorbers. Experimental investigations were conducted at the solar testing field of the Physical-Technical Institute of the Academy of Sciences of Uzbekistan under extreme continental climatic conditions to determine the system's stable thermophysical indicators. The results demonstrated that active water cooling using …

Adaptive – Compositional Method For Coordinating Subsystems At Different Levels In Hierarchical Control Systems, Husan Zakirovich Igamberdiyev, Uktam Farxodovich Mamirov Mr, Inomjon Ilxom Ugli Abdukaxxarov Mr

Technical science and innovation

This paper examines the problem of synthesizing algorithms for the composition of subsystems at various levels within complex hierarchical control systems under conditions of uncertainty and resource constraints. It is demonstrated that classical composition algorithms, which rely on the intersection of admissible sets and the use of local optimality criteria, suffer from several significant drawbacks. These include a combinatorial increase in complexity, dependence on the expert selection of parameters, and limited applicability in dynamic environments. To overcome these shortcomings, an adaptive-compositional method is proposed. This method is based on the dynamic recalculation of coordination parameters, the integration of model predictive …

Leader Election System For An Unmanned Ground Vehicle Swarm, Milan Chhetri, Brendan Beas, Paul Levin

Electrical Engineering

This senior project presents the design and implementation of a leader-election system for a leader-follower unmanned ground vehicle (UGV) swarm using embedded control and wireless communication. The objective of the project is to improve the robustness and mission longevity of a multi-agent robotic system by allowing the swarm to dynamically select the most suitable leader during operation. Each UGV is equipped with an ESP32 microcontroller, DWM1000 Ultra-Wideband (UWB) ranging modules, an MPU-6050 inertial measurement unit (IMU), motor drivers, and supporting power electronics to enable communication, sensing, and autonomous control. A battery monitoring subsystem was developed using the ESP32's built-in Analog-to-Digital …

Archimedean Spiral Antenna Array With Klopfenstein And Exponential Tapered Balun Feeds, Leo Joseph Alvelais Iv, Paul Obrecht, Naguib Abdulla, Preston Mavady, Collin Fan

Electrical Engineering

This project presents the design, fabrication, and experimental evaluation of a broadband 3x3 Archimedean spiral antenna array tile for 2.8-3.8 GHz. Each element combines a two-arm spiral on Rogers RO4350B, a printed 50 to 150 Ω tapered balun, and a conductive backplane. Klopfenstein and Exponential feed implementations were modeled in Ansys HFSS, generated and tuned with automated scripting, fabricated, and evaluated with calibrated network and anechoic-chamber measurements. The Klopfenstein-fed hardware met the -10 dB input-reflection criterion across the project band. The exponential array provided a broad matched response but reached approximately -8 dB near 2.95 GHz. Measured center-element patterns retained …

Vision-Based Autonomous Tracking Rover, Alejandro Ahumada, Erick Ayala, Jonathan Chavez

Electrical Engineering

AAC Vision designed and constructed a vision-based autonomous tracking rover capable of exploring an indoor environment, avoiding obstacles, generating a two-dimensional LiDAR map, detecting a standard orange basketball, and approaching the target without manual steering. The rover uses a Raspberry Pi 4, an Intel RealSense D435 RGB-D camera, an RPLIDAR C1, four JGB37-520 Hall-encoder motors, dual H-bridge motor drivers, a 12 V battery, and a custom aluminum chassis measuring approximately 8 in by 12 in and weighing 6.7 lb. The final mission emphasized reliable target discovery rather than travel between predetermined points. The software integrates Python, OpenCV, Ultralytics YOLO, RealSense …

Dc/Dc Converter For A Solar Module, Francine Therese A. Canal, Jesus Cruz, Juan Jose Gonzalez

Electrical Engineering

This project presents the design and implementation of a DC/DC power converter intended for photovoltaic (PV) modules with varying electrical output characteristics. Solar panels experience significant changes in output voltage and power due to variations in sunlight, temperature, and load conditions. To ensure reliable operation across a range of conditions, the proposed converter is capable of both step-up and step-down operation to accommodate solar modules with power ratings from 50 W to 450 W and open-circuit voltages between 10 V and 80 V. The system operates at load currents up to 10 A and provide a user-adjustable output voltage within …

Dc/Dc Converter For A Solar Module, Stella Uribe, Richie Zaragoza, Olivia Grace Tran, Phillip Tyler Rich

Electrical Engineering

This project focuses on the design and validation of a general-purpose DC/DC power converter intended for use with photovoltaic (PV) solar modules operating under variable environmental and loading conditions. Solar panels exhibit significant variation in output voltage, current, and available power due to changes in irradiance, temperature, and operating point, making direct connection to downstream loads impractical. The proposed system addresses this challenge by providing a single, user-adjustable regulated DC output capable of both stepping up and stepping down the solar module voltage. The converter is designed to interface with solar modules rated between 50 W and 400 W, with …

Stationary Bike Power/Efficiency Monitor, Paula J. Diaz, Pilar M. Cook, Danielle Rhind

Electrical Engineering

This project developed a real-time power and efficiency monitoring system for a SportsArt ECO-POWR stationary exercise bicycle. The goal was to measure rider mechanical power and electrical power delivered to the utility grid simultaneously, allowing the overall bike-to-grid efficiency to be calculated and displayed in real time. Rider power was measured using Garmin Rally ANT+ power pedals, while grid power was measured using a Yokogawa WT310E power analyzer. A Raspberry Pi 3 Model B+ synchronized both data sources, calculated efficiency, displayed live performance metrics through a graphical user interface, and logged measurement data to CSV files for later analysis. The …

Autonomous Terrain-Mapping Robot For Search And Rescue, Soumil Joshi, Seann Calub

Electrical Engineering

This report documents the design, modular testing, and challenges faced while developing an autonomous terrain-mapping robot intended to navigate to a destination waypoint and deliver a small payload for search-and-rescue applications. The system combines a LiDAR sensor, an IMU sensor, and a Raspberry Pi 3B as the onboard processor, and an ESP32 microcontroller interfacing with motor drivers over a four-wheel chassis. A companion mobile application was developed to enable remote control and monitoring of the robot over a WiFi hotspot connection. A lithium-ion battery pack supplies power to all onboard components, with power budgets verified against component datasheets. Testing progresses …

Understanding The Structural Drivers Of Useful Exergy Intensity, João Santos, Tiago Domingos, Tânia Sousa, Matthew Kuperus Heun, André Serrenho

University Faculty Publications and Creative Works

Energy-Economy Decomposition Analysis Across 112 Countries 1971-2020

Distinct Regulatory Dna Methylation Signatures Across Multiple Sclerosis, Neuromyelitis Optica, And Neurological Post-Acute Sequelae Of Covid-19, Syed Ilyas Munzir, Daniel B. Hier, Michael D. Carrithers

Electrical and Computer Engineering Faculty Research & Creative Works

Background/Objectives: Our prior epigenome-wide association study (EWAS) on multiple sclerosis (MS) identified myeloid-associated methylation signatures and an association with enhancer regions. Here we compared differential DNA methylation across three central nervous system inflammatory disorders: MS, neuromyelitis optica (NMO), and neurologic post-acute sequelae of COVID-19 (neuro-PASC). Methods: Whole-blood DNA was profiled on Infinium MethylationEPIC arrays. Analyses included EWAS at the CpG level, differentially methylation region (DMR) analysis, and gene regulatory-element enrichment using Locus Overlap Analysis (LOLA). Limma linear models were adjusted for race, EPIC array version, age, sex, disease-modifying treatment class, and blood cell composition. Results: All three diseases were associated …

The Neuropsychological Analysis Of The Effect Of Shame And Traumatic Memories In Paranoia: A Network Analysis, Anwesha Maitra

Clinical Psychology Dissertations

Paranoia is increasingly recognized as a multidimensional psychological phenomenon influenced by trauma-related distress, shame, maladaptive interpersonal experiences, and emotional functioning. Although these factors have been extensively associated with paranoia, their relationships with neurocognitive functioning, social cognition, and global functioning remain less well understood. The present study examined these relationships using traditional statistical analyses, network analysis, and machine-learning approaches in a non-clinical sample of 42 adults.

Participants completed self-report measures assessing trauma-related distress, childhood interpersonal experiences, shame, paranoia, depressive symptoms, fear of negative evaluation, self-esteem, and hostile attribution bias, in addition to a comprehensive neurocognitive battery, an emotion recognition task, and …

Sputtered Transport Layers Enabling Ambient-Air Processed Cspbi3 Perovskite Solar Cells, Shamik Datta, Md Abdul Kuddus Sheikh, Md Shazarul Islam, Mohammed Jasim Uddin, Hasina Huq

Electrical and Computer Engineering Faculty Publications

Perovskite solar cells offer promising efficiency compared to traditional technologies. In this study, NiOx and ZnO were employed as charge transport layers using a magnetron sputtering process within a p-i-n architecture (ITO/NiOx/CsPbI3/ZnO/Au). This approach produced uniform, low-defect interfaces and supports low-temperature, scalable fabrication suitable for flexible substrates. Our investigation, using techniques such as X-Ray Diffraction (XRD), UV-Visible spectroscopy, Scanning Electron Microscopy (SEM), and Atomic Force Microscope (AFM), revealed the formation of uniform layers deposited by the magnetron sputtering process. The photoactive CsPbI3 layer was deposited via a spin coating solution process. UV-Visible spectroscopy revealed strong absorbance in the wavelength range …

Veribrief: A Multi-Agent Retrieval-Augmented Generation System For Policy Decision Support, Imane Bahji

Electrical and Computer Engineering ETDs

VeriBrief is a multi-agent retrieval-augmented generation (RAG) system for evidence-grounded economic policy analysis. The system orchestrates a five-stage LangGraph pipeline, retrieval, research, analysis, synthesis, and critique, to produce cited, structured responses while detecting out-of-scope queries. An empirical evaluation on eight questions drawn from official U.S. macroeconomic releases compared VeriBrief against a single-pass RAG baseline. The multi-agent system achieved 100% refusal precision on unanswerable analytical queries versus 0% for the baseline. Unsupported claims fell substantially on answerable factual questions. A context-propagation defect discovered during evaluation was diagnosed and corrected. Limitations include failure of the evidence gate on policy-counterfactual queries and a …

Development Of Medical Device For Hypovolemic Assessment Using Peripheral Venous Pressure, Connor J. Breshears

Graduate Theses and Dissertations

Accurate assessment of intravascular volume status remains challenging because traditional measurements such as heart rate, blood pressure, physical examination findings, and laboratory values may be subjective, delayed, or insensitive to early volume loss. Peripheral venous pressure (PVP) waveform analysis provides a potential approach for minimally invasive volume-status monitoring because PVP waveforms can be acquired from peripheral venous access and may contain frequency-domain information related to cardiac activity, respiratory modulation, vascular coupling, and intravascular filling. This thesis presents the development and evaluation of a proof-of-concept embedded prototype for PVP waveform acquisition and volume-status classification. The system integrates a Millar MEMS pressure …

Sliding Mode Control In Grid-Tied Inverters: Techniques, Applications, And Future Directions, Taimoor Muzaffar Gondal, Asma Aziz, Daryoush Habibi, Iftekhar Ahmad

Research outputs 2022 to 2026

Sliding mode control (SMC) has emerged as a robust and adaptive strategy for grid-tied inverters. It has unique attributes which make it an appropriate control choice under increasingly complex power systems. However, there are a limited number of review articles which comprehensively explore the true potential of SMC for grid-tied inverter applications. This systematic review has been structured to explore SMC techniques with respect to certain challenges, i.e., stability challenges, unbalanced conditions, low inertia scenarios, and harmonics distortion. The classification of various SMC techniques is presented with respect to their control law and sliding surfaces design. The comparative analysis indicates …

Subspace Decomposition For Spatial Parameter Estimation, Arthur Grik

USF Tampa Graduate Theses and Dissertations

Passive emitter localization is an important capability for wireless sensing, interference detection, and spectrum awareness. Classical timing-based localization methods estimate emitter position from differences in signal arrival time across distributed sensor platforms, but their performance depends on precise receiver synchronization and favorable signal bandwidth characteristics. This thesis investigates subspace-decomposition-based spatial parameter estimation as an alternative approach in which directional information is extracted from coherent antenna-array measurements. This work develops the theoretical foundation and signal-processing framework for angle-of-arrival estimation. Various spatial parameter estimators are presented as supporting array-processing methods before focusing on a well-known subspace-decomposition-based approach called the Multiple SIgnal Classification …

Joint Channel And Phase Noise Estimation For Mmwave Ofdm Systems Using Adaptive Kalman Filtering, Kwame Salum Ibwe

Tanzania Journal of Science

This manuscript presents a joint channel and phase-noise estimation framework for millimeter-wave (mmWave) OFDM systems based on an adaptive extended Kalman filter (EKF). The proposed method formulates a unified state-space model that simultaneously tracks time-varying multipath channels and oscillator phase noise, a critical impairment in 5G NR frequency range 2 (FR2) and emerging 6G transceivers. An innovation-based covariance adaptation mechanism is introduced to enhance estimation accuracy while maintaining computational efficiency. Simulation results demonstrate that the proposed approach achieves up to a 5 dB SNR gain at a target BER of 10⁻³, maintains NMSE below 10⁻³ for linewidths up to 200 …

Distribution And Transport Of Lithium Ions At Interfaces Between Graphite And Carboxymethyl Celluloses, Zi-Jun Huang, Zhen-Ying Zheng, Hua-Wei Cao, Jian Wang, Qing-Feng Zhang, Sheng-Li Chen

Journal of Electrochemistry

Carboxymethyl cellulose (CMC) is a water-processable binder widely used for graphite anodes. However, a microscopic understanding of why the identity of CMC counterions (Li⁺/Na⁺/K⁺) strongly affects electrode performance remains limited. Here, molecular dynamics (MD) simulations are used to track Li⁺ transport accessibility across electrolyte/CMC/graphite three-phase interfaces, comparing pure CMC-Li, CMC-Na, CMC-K, and mixed-counterion CMC binders. We find that CMC-Li sustains a continuous Li⁺ transport pathway from the electrolyte through the binder phase toward graphite. In contrast, in CMC-Na and CMC-K, Na⁺/K⁺ ions preferentially enrich at the graphite/binder interface, forming …