Behavioral-Centric Team Evaluation Via Consistent Rewards,
2026
Dartmouth College
Behavioral-Centric Team Evaluation Via Consistent Rewards, Clement Kudakwashe Nyanhongo
Dartmouth College Ph.D Dissertations
Across human domains ranging from sports to business and organizational settings, complex tasks are often solved by teams rather than individuals, leveraging benefits such as interaction, mutual support, complementary skills, cohesion, and task allocation. Evaluating team effectiveness, however, is inherently challenging due to the subjectivity of many existing techniques and the limitations of outcome-driven metrics that primarily focus on performance scores while overlooking the team processes that generated the scores. To address these challenges, this dissertation proposes a behavioral-centric, end-to-end framework for team evaluation grounded in reward functions that model sequential team behavior. Reward functions offer compact and interpretable representations …
Advancement And Characterization Of Next-Generation Solid-State Photon-Counting Image Sensors For Astrophysics Applications,
2026
Thayer School of Engineer at Dartmouth College
Advancement And Characterization Of Next-Generation Solid-State Photon-Counting Image Sensors For Astrophysics Applications, Nicholas R. Shade
Dartmouth College Ph.D Dissertations
Astronomers’ pursuit of detecting light from increasingly faint and distant objects in the expanse of space necessitates continuous improvement in signal-to-noise ratio of camera technology. Recent advancements in solid-state detector technologies have enabled the determination of photon-number, including single photon events, enabling observations at the fundamental limits of physics. These developments are instrumental not only for standard two-dimensional imaging but also for advanced spectroscopy, which increasingly drives future astrophysical applications. This thesis presents an evaluation of three next-generation silicon-based detectors capable of photon-counting with deep-sub-electron input-referred read noise: the electron-multiplying charge-coupled device (EMCCD), the single-photon avalanche diode (SPAD), and the …
Tuning And Performance Of Pid Controlled Low Complexity Systems,
2026
The University of Southern Mississippi
Tuning And Performance Of Pid Controlled Low Complexity Systems, Timothy Evans
Honors Theses
Proportional integral derivative (PID) controllers are used for precise position and orientation control in systems such as autonomous underwater vehicles (AUVs). This project supports the University of Southern Mississippi’s (USM) Robotics Club’s RoboSub AUV effort by developing, troubleshooting, and manually tuning PID controllers to characterize tracking performance and settling time across systems of increasing complexity. Initially, the project hypothesized that tracking performance would be reduced and settling times would increase as system complexity advanced from one degree-of-freedom (DOF) to two DOF. However, prior research was found that suggests that for small disturbances around an equilibrium state, separate PID-controlled DOFs can …
Control And Stability Analysis Of Three-Phase Grid-Connected Inverters In Renewable Energy Systems,
2026
University of Arkansas, Fayetteville
Control And Stability Analysis Of Three-Phase Grid-Connected Inverters In Renewable Energy Systems, Yasser Ayeva
Electrical Engineering and Computer Science Faculty Publications and Presentations
The increase in demand for renewable energy sources such as solar and wind systems has led to widespread use and integration of a three-phase grid connected inverters in electric modern electric power systems. The inverters are essential to convert DC power into AC power and to control the delivered power to the grid. However, the use of the inverters in a renewable energy system has some challenges related to stability and control due to the presence of power electronic interfaces and filter dynamics. This paper analyzes the control and stability of three phase grid connected inverter through an LCL filter. …
A Software-Defined Radio Testbed For Mimo-Ofdm Communications,
2026
University of Nebraska-Lincoln
A Software-Defined Radio Testbed For Mimo-Ofdm Communications, Chaz G. Maschman
Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research
In this thesis, we implement a testbed for multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems via GNU Radio. Specifically, we implement a configurable framework for the construction of MIMO-OFDM software-defined radio (SDR) systems as a GNU Radio module. The GNU Radio MIMO-OFDM module consists of multiple algorithmic blocks necessary for implementation of a MIMO-OFDM system. This includes a library for the generation of orthogonal or pseudo-random pilot sequences, amendments to the Schmidl-Cox protocol for MIMO synchronization, and the creation of click-and-drag GNU Radio blocks implementing the conversion of arbitrary data sent via external programs to MIMO-OFDM frames, the initial …
Microstructural And Thermal Studies Of Niobium On Copper Fabricated By Sputtering And Multicharged Ion Deposition,
2026
Old Dominion University
Microstructural And Thermal Studies Of Niobium On Copper Fabricated By Sputtering And Multicharged Ion Deposition, Md Obidul Islam
Electrical & Computer Engineering Theses & Dissertations
Niobium-coated copper (Nb/Cu) superconducting radiofrequency (SRF) cavities are a promising alternative to bulk niobium cavities for next-generation particle accelerators due to their reduced material cost and superior thermal conductivity of the copper substrate. However, cavity performance is fundamentally limited by the microstructural quality of sputtered Nb films and thermal transport across the Nb/Cu interface. Reduced thermal diffusivity in thin films and high interfacial thermal resistance contribute to localized heating and performance degradation under high RF fields. This dissertation addresses these challenges through a combined experimental and methodological investigation of thermal transport in Nb thin films, focusing on interface engineering using …
Using Ai To Predict Energy Expenditure In Lower Limb Prosthesis Users,
2026
St. Mary's University
Using Ai To Predict Energy Expenditure In Lower Limb Prosthesis Users, Nelly Diaz, Siem Hadish
Posters - 2026
• Computer vision has evolved from simple image classification and object detection to analyzing human motion and biomechanics (1). • CNN’s are usually focused on image classification, but, in this case, we are not asking the model if a person is walking. • Many real-world problems require regression: Predicting a continuous number like energy expenditure of walking is a complex task. • It is essential for Prosthetists to understand energy expenditure of their prosthetic patients (2). • An amputee may use 20-30% more energy to walk. • In this project, we developed an AI model to analyze human motion and …
Assessment Of Thickness-Dependent Recombination Mechanisms And Realistic Performance Limits In Csbi₃I₁₀ Lead-Free Perovskite Solar Cells,
2026
Edith Cowan University
Assessment Of Thickness-Dependent Recombination Mechanisms And Realistic Performance Limits In Csbi₃I₁₀ Lead-Free Perovskite Solar Cells, Samiul Sadek, Ayan Saha, Jegadesan Subbiah, Mohammad Tariqul Islam, Mohammad Junaebur Rashid, Mohammad Aminul Islam, Gufran Umar Alam Shaikh, Wan Zulhafizhazuan Bin Wan Jusoh, Mohammad Nur-E-Alam, Puvaneswaran Chelvanathan, Mohd Adib Ibrahim
Research outputs 2022 to 2026
Lead-free perovskite solar cells (PSCs) offer a promising, environmentally sustainable alternative to their lead-based counterparts, yet their performance is often constrained by charge transport and recombination limitations. This study presents a comprehensive numerical investigation into the thickness-dependent performance of lead-free bismuth-based PSCs employing CsBi₃I₁₀ as the absorber layer. Through systematic variation of the absorber, electron transport layer (ETL), and hole transport layer (HTL) thicknesses within a planar FTO/TiO₂/CsBi₃I₁₀/Spiro-OMeTAD/Ag architecture modeled using SCAPS-1D, an optimal absorber thickness range of 0.5–1.0 µm is identified. Under idealized conditions, a peak power conversion efficiency (PCE) of 21.62% is predicted, primarily to illustrate thickness-dependent trends. …
Comparative Numerical Analysis Of Lead-Free Perovskite Solar Cells Using Scaps-1d,
2026
The University of Texas Rio Grande Valley
Comparative Numerical Analysis Of Lead-Free Perovskite Solar Cells Using Scaps-1d, Md Shazarul Islam, Md Abdul Kuddus Sheikh, Hasina Huq
Electrical and Computer Engineering Faculty Publications
A comprehensive numerical study of lead-free perovskite solar cells was conducted using the SCAPS-1D simulation framework with the device architecture ITO/SnO2/Perovskites/NiOx/Au. The work investigates the replacement of the central Pb cation with Sn, Ge, and Bi, followed by absorber-layer thickness optimization to enhance device performance. The impact of systematic Pb substitution on key photovoltaic parameters was first evaluated. Among the candidates, FASnI3-based devices exhibited the most promising performance, achieving a power conversion efficiency (PCE) of 26.48%, with a short-circuit current density (Jsc) of 19.31 mAcm-2, an open -circuit voltage (Voc) of 1.57 V, and a fill factor (FF) of 87.29%. …
A Comparative Study On Performance Of Iot-Driven Ml-Enabled Forecasting Models For Efficient Air Quality Monitoring,
2026
United Arab Emirates University
A Comparative Study On Performance Of Iot-Driven Ml-Enabled Forecasting Models For Efficient Air Quality Monitoring, Bara Ksiksi
Theses
Air pollution is one of the most critical environmental challenges affecting public health globally, responsible for approximately 4.2 million premature deaths annually according to the World Health Organisation. This thesis presents a comparative study of IoT-driven machine learning forecasting models for air quality monitoring in Abu Dhabi, UAE, introducing a zonal approach combined with satellite-based spatial validation. The primary objective is to evaluate forecasting performance across three distinct activity zones using ground station data from the Environment Agency Abu Dhabi (EAD), and to incorporate a spatial validation component using satellite imagery to assess the consistency of ground-based predictions at a …
Traditional And Machine-Learning Equalization Techniques For Bandwidth-Limited Short-Reach Optical Communication Channels,
2026
United Arab Emirates University
Traditional And Machine-Learning Equalization Techniques For Bandwidth-Limited Short-Reach Optical Communication Channels, Abdullah Khawatmi
Theses
This thesis investigates equalization techniques for bandwidth-limited short-reach optical communication systems, with a focus on Visible Light Communication (VLC) and Step-Index Plastic Optical Fiber (SI-POF) links. Commercial light-emitting diodes and photodiode receivers impose severe bandwidth constraints, inter-symbol interference, and noise sensitivity, which fundamentally limit achievable data rates. The work addresses these impairments through systematic evaluation of traditional digital signal processing–based equalizers and modern machine-learning-based post-equalization methods. The primary aim of this thesis is to enhance the achievable data rate and reliability of commercial short-reach optical links while maintaining practical computational complexity. Specifically, the objectives are to (i) design and experimentally …
Analysis Of A Coaxial Transmission Line Filled With An Orthorhombic Dielectric-Magnetic Medium,
2026
United Arab Emirates University
Analysis Of A Coaxial Transmission Line Filled With An Orthorhombic Dielectric-Magnetic Medium, Fathima Manikunnath Abdul Akbar
Theses
Coaxial transmission lines are fundamental means for Transverse Electromagnetic (TEM) wave propagation in RF, microwave and high-speed electronic systems. The study of transmission lines is often familiar when they are filled with isotropic materials; however modern engineered direction dependent materials reshape field distributions. In this thesis, we consider a coaxial transmission line of an inner radius and outer radius b filled with an orthorhombic dielectric-magnetic material, which is described by two anisotropy parameters αx and αy. The potential and field distributions are studied in relation to the ratio b/a as well as the anisotropy parameters αx and αy. Due to …
Efficient Fpga Implementation Of A 1 Million-Point Fft,
2026
United Arab Emirates University
Efficient Fpga Implementation Of A 1 Million-Point Fft, Jwaher Abdulqader Al Tamimi
Theses
The one-million-point Fast Fourier Transform is implemented using a radix-2 single-path delay feedback pipeline architecture. To minimize the computational overhead, twiddle factors were pre-computed and stored in memory. The design uses a fixed-point representation with two integer bits and seven fractional bits, achieving a measured signal-to-noise ratio of 37.98. Given the substantial memory requirements, a memory partitioning approach was used. It mapped the delay buffers in each stage lookup table memory, block random-access memory, or ultra random-access memory, based on word width and memory depth.
The implementation operates successfully at 100 megahertz on a mid-scale field-programmable gate array. Post-implementation reported …
Breath-Based Detection Of Liver Cancer Biomarkers Using An Swcnt-Fet Nano-Biosensor: Quantumatk,
2026
United Arab Emirates University
Breath-Based Detection Of Liver Cancer Biomarkers Using An Swcnt-Fet Nano-Biosensor: Quantumatk, Mohamed Mohieb Rashdan
Theses
Early detection of liver cancer remains limited by the slow pace and invasiveness of current testing methods. This study proposes a single-walled carbon nanotube field-effect transistor (SWCNT-FET) designed to detect hexanal—a volatile organic compound (VOC) elevated in liver cancer—directly from exhaled breath. The device is modeled in QuantumATK using a semi-empirical Extended Hückel Hamiltonian within the non-equilibrium Green's function (NEGF) framework, emphasizing realistic contact physics by employing metallic SWCNT electrodes instead of conventional metal films. Zigzag channels with (11,0) and (12,0) chiralities are examined to analyze how geometry and contact matching influence charge transport. Simulations include current–voltage (I–V) characteristics and …
An Integrated Tracking Technique For Underwater Navigation Using Acoustic And Imu Measurements,
2026
Edith Cowan University
An Integrated Tracking Technique For Underwater Navigation Using Acoustic And Imu Measurements, Mainul Islam Chowdhury, Quoc Viet Phung, Iftekhar Ahmed, Daryoush Habibi
Research outputs 2022 to 2026
Accurate navigation is essential for underwater vehicles like AUVs, which often operate in deep or remote areas. However, complex ocean dynamics, cumulative inertial-measurement unit (IMU) drift, and diverse noise sources often result in erratic and unreliable position estimates. To overcome these challenges, we proposed a method that combines underwater acoustic signals with onboard motion sensor data to improve the underwater position tracking system. The proposed system uses a long baseline (LBL) acoustic array of surface buoys to capture the Time-difference-of-Arrival (TDoA) of a multi-pulse beacon. We extract arrival times using a superimposed-envelope-spectrum (SES) detector, which exploits the beacon’s periodic structure …
Efficient Energy Management In Networked Microgrids Using Multi-Agent Deep Reinforcement Learning In The Presence Of Uncertainties,
2026
United Arab Emirates University
Efficient Energy Management In Networked Microgrids Using Multi-Agent Deep Reinforcement Learning In The Presence Of Uncertainties, Ayodele Benjamin Chukwuyem
Dissertations
Microgrid technology is essential in facilitating the transition to smart energy grids in developed countries and mitigating energy poverty in developing countries, particularly in areas where grid extensions are not feasible. Recently, the concept of networked microgrids (NMGs) has garnered tremendous attention due to the plausibility of interactions among interconnected microgrids leading to power networks that are more resilient, reliable, and stable. However, because each microgrid has diverse distributed generation resources (renewables and controllable generators) and each microgrid operator (MO) has different objectives, coordinated energy management is required to satisfy local and system-wide goals under conditions with significant uncertainty. Existing …
How Do Social Network Models Compare To All-To-All Models For Forecasting Tuberculosis Epidemics? A Mathematical Modeling Study,
2026
NYU Grossman School of Medicine
How Do Social Network Models Compare To All-To-All Models For Forecasting Tuberculosis Epidemics? A Mathematical Modeling Study, Masabho Peter Milali, Hae-Young Kim, George Corliss, Anna Bershteyn
Electrical and Computer Engineering Faculty Research and Publications
Background. Mathematical models guide tuberculosis (TB) target-setting, yet most assume homogeneous “all-to-all” mixing. We compared projected intervention impacts between an all-to-all compartmental model and a Barabási–Albert (BA) scale‑free social network model under otherwise identical disease assumptions.
Methods. We calibrated transmission parameters so both models produced similar baseline trends, then introduced vaccination (coverage 30–70%; efficacy 80–95%) and treatment (20–50% increases in recovery) after a 400‑day burn‑in. Outcomes were assessed 300 days post‑intervention.
Results. Under 60% coverage, increasing vaccine efficacy from 80% to 95% yielded smaller projected reductions in active TB with the network model than with all‑to‑all mixing. Treatment improvements showed …
Condition Monitoring Of Induction Motor Using Motor Current Signature Analysis,
2026
Department of Electrical and Electronics Engineering,DeltaStatePolytechnic,Otefe-Oghara,DeltaState,Nigeria.
Condition Monitoring Of Induction Motor Using Motor Current Signature Analysis, Francis Ikechukwu Obianke, Joseph Okhaifoh, Benjamin Akinloye
Al-Bahir
Induction machines serve as the cornerstone and driving force of modern manufacturing and production systems. This research aims to monitor and analyse the operating performance of induction motors using motor current signature analysis (MCSA). MCSA is employed to process the current signal of a motor into a frequency spectrum, known as the current signature by applying the Fast Fourier Transform (FFT) algorithm. The underlying principle is that vibration generated in a motor is closely related to the changes of the magnetic field density, and the induced voltage varies with the stator current.
A simulation model replicating the behaviour of an …
AiXGa1−XN (0.7 < X < 1) Schottky Diodes Using Distributed Polarization Doped Layer With A Current Density Of 14 Ka/Cm2,
2026
University of South Carolina
AiXGa1−XN (0.7 < X < 1) Schottky Diodes Using Distributed Polarization Doped Layer With A Current Density Of 14 Ka/Cm2, Tariq Jamil, Abdullah Al Mamun Mazumder, Mafruda Rahman, Muhammad Ali, Grigory Simin, M. Asif Khan
Faculty Publications
High Al-content AlxGa1-xN (0.7 < x < 1) quasi-vertical Schottky barrier diodes (SBDs) with distributed polarization doping were grown on the bulk AlN substrate. They exhibit excellent rectification behavior with a large forward current density (~14 kA/cm2 ) and a high breakdown field of ~8.3 MV/cm. The SBDs also exhibited low ideality factors of (n~1.2) with a high Schottky barrier height (Φ b~ 1.7 eV). Thus, this study demonstrates the feasibility of the distributed polarization doping approach for high current–high voltage devices.
An Interpretable Hybrid Deep And Reinforcement Learning Paradigm For Glioma Prognosis,
2026
SASTRA Deemed to be University
An Interpretable Hybrid Deep And Reinforcement Learning Paradigm For Glioma Prognosis, Renuga Devi M Ms
Theses and Dissertations
Brain tumors are highly aggressive and lethal types of cancer, particularly gliomas. These cancerous growths show complicated pathophysiological behaviours and with poor prognosis despite therapeutic advances. Due to their biological differences and infiltrating growth, as well as overlapping radiological characteristics, they pose great difficulty in diagnosis, grading, and survival prediction. Artificial intelligence technology, which includes machine learning , deep learning, and reinforcement learning has developed into a new paradigm for the automation of brain tumor diagnostics and personalized treatment. The main goal of this study is to create an integrated AI-based framework that can perform brain tumor segmentation, grading and …
