Digital Commons Network^™

Optimization Of The Operational Efficiency Of Transport And Technological Complexes Based On Simulation Modeling, Kamoliddin Juraboevich Rustamov, Gulom Gaffurdjanovich Atabaev

Technical science and innovation

The article presents a comprehensive analytical approach to improving the operational efficiency of transport and technological machines (TTM) based on simulation modeling. The proposed model integrates the economic and reliability characteristics of maintenance (TM) strategies by describing the operation of aggregates, the probability of failures, and transitions between states — operational (W), faulty (F), and restored (R) — as probabilistic processes. Model parameters are identified using statistical data from real operating conditions and adapted to various types of technical systems. Computer simulation experiments are carried out under multiple scenarios of maintenance periodicity, workload intensity, spare parts resource, and repair policy. …

A Novel Electrolyte Pyridine Additive For Enhancing Cycle Life Of Lithium-Ion Batteries, Peng-Cheng Wang, Ding-Chang Li, Jun-Tao Li, Guang-Bo Lu, Shi-Wen Wang

Journal of Electrochemistry

Lithium-ion (Li-ion) battery using a graphite (Gr.) anode and a lithium iron phosphate (LiFePO₄, LFP) cathode (Gr.||LFP) has been widespread in energy storage. To match the warranty period of energy storage systems, the lifespan of this kind of Li-ion battery, not only under room temperature but also under relatively high temperature, is critical. Exploration of functional electrolyte additive provides an efficient approach to address this issue. This study reports the usage of pyridine (Py) as a new electrolyte functional additive for Gr.||LFP. In the first cycle, it was found that Py can be reduced before ethylene carbonate and …

Comprehensive Mechatronic Design Methodology For 6-Dof Stationary Lower Limb Rehabilitation Exoskeleton Robot With Safety-Integrated Control Architecture, Javlonbek Rakhmatillaev Mr., Nodirbek Kimsanboyev Mr., Umidjon Takabaev Mr., Zafar Juraev3 Dr.

Chemical Technology, Control and Management

This paper presents the mechatronic design of a proposed six-degree-of-freedom (6-DOF) stationary lower limb rehabilitation exoskeleton (SLLRE) robot, developed through a comprehensive mechatronic design methodology that includes mechanical design, actuator and sensor selection, and the development of a control structure based on a safety-oriented control approach. The proposed 6-DOF SLLRE mechanical design introduces a comprehensive mechanical structure comprising bilateral hip, knee, and ankle joints, degrees of freedom, joint ranges of motion, human parameters for rehabilitation training, as well as the frames and structural elements of the proposed system. Furthermore, the selection of appropriate sensors, actuators, and control architecture for the …

Design Of A Fuzzy Set-Point Tracking Controller Based On The State-Dependent Control Characteristics Of Fuzzy Logic And Pid For Temperature Control Systems In Electrical Equipment, Rahim Mammadzada

Chemical Technology, Control and Management

This paper presents a Fuzzy-SPT (Fuzzy Set-Point Tracking) controller designed to combine the strengths of FLC (Fuzzy Logic Control) and PID (Proportional-Integral-Derivative) control while mitigating their limitations across varying operating conditions. Inspired by state-dependent reasoning but implemented within a single controller, the method uses internal logic to adapt the control effort across different operating regions. FLC handles rapid changes and nonlinear transients, enabling fast system response without overshoot, while PID-like integral action is activated when the FLC reaches steady state or enters a threshold region near the set point, eliminating residual errors and maintaining stable performance. By applying each behavior …

Performance Assessment Of Operators Under Digital Simulator-Based Training In Automated Industrial Systems, Kamola Abdullaeva

Chemical Technology, Control and Management

This article proposes a comprehensive approach to training process operators, based on computer simulators integrated with digital twins, SCADA/DCS systems, real production data, and artificial intelligence algorithms. This approach is particularly relevant given the increased requirements for safety, productivity, and reliability of industrial facilities, as human factors are often the main cause of accidents (up to 60-80% of cases). The architecture of the simulator complex is designed to accurately emulate steady-state, transient, and pre-emergency operating modes of equipment, which are not achievable under actual production conditions. The experiment compared the training effectiveness of two groups of operators: one that used …

Cache-Conscious Sparse Matrix Dense Matrix Multiplication On Gpus, Haoqiang Guo

LSU Doctoral Dissertations

Over the past decade, high-performance deep learning has evolved into a critical research domain, driven by the demand for efficient models and high inference throughput. Deep learning architectures have shifted from stacked convolutional layers to transformer-based models, while pruning techniques and graph-structured data have established sparse matrix–dense matrix multiplication (SpMM) as a fundamental kernel—particularly in graph neural networks (GNNs). Modern GPUs, with their massive parallelism and high-bandwidth memory, offer immense potential for accelerating these workloads. While SpMM implementations using the compressed sparse row (CSR) format remain common to avoid conversion overhead, preprocessing-based methods have recently demonstrated superior potential. In GNN …

Integration Of Renewable Energy Networks Into Smart Grid Infrastructure: A Matlab/Simulink-Based Simulation Approach, Saturday Noghayin Osaretin

Electrical Engineering Theses

The rising demand for sustainable and resilient energy systems has accelerated the transformation from traditional power grids toward smart grids integrated with renewable energy networks. This thesis explores the integration of solar energy sources into smart grids to replace conventional fossil-fuel-based generation. A simulation model is developed using MATLAB/Simulink to evaluate the operational performance, stability, and adaptability of the proposed smart grid architecture. Key challenges, including intermittency, synchronization, and bidirectional power flows, are identified, and corresponding solutions, such as energy storage systems, are proposed to address these issues. Simulation results demonstrate enhanced grid stability, reduced carbon footprint, and improved power …

Puf-Based Digital Money With Propagation-Of-Provenance And Offline Transfers Between Two Parties, Benjamin Bean, Cyrus Minwalla, Eirini Eleni Tsiropoulou, Jim Plusquellic

Electrical and Computer Engineering ETDs

Building on prior concepts of electronic money (eCash), we introduce a digital currency where a physical unclonable function (PUF) engenders devices with the twin properties of being verifiably enrolled as a member of a legitimate set of eCash devices and possessing of a hardware-based root-of-trust. A hardware-obfuscated secure enclave (HOSE) is proposed as a means of enabling a PUF-based propagation-of-provenance (POP) mechanism, which allows eCash tokens (eCt) to be securely signed and validated by recipients without incurring any third party dependencies at transfer time. The POP scheme establishes a chain of custody starting with token creation, extending through multiple bilateral …

Empowering Wireless Mesh Uav Networks Through Software-Defined Networking, Hieu Quang

Electrical and Computer Engineering ETDs

Unmanned Aerial Vehicles (UAVs) have been widely deployed in applications such as environmental monitoring, disaster response, and surveillance. Effective coordination between UAVs depends on low-latency inter-UAV communication to exchange state information, decisions, and other critical data. UAV networks are inherently dynamic which necessitates a framework capable of handling scenarios such as traffic re-routing, and resilience to communication failures. To address the challenges of managing dynamic UAV networks, this thesis proposes a dual network approach composed of three main components. First, the Better Approach to Mobile Ad-hoc Networking (BATMAN) protocol is used to enable communication among UAVs. Second, the OpenFlow protocol …

Parameter Informed Reinforcement Learning For Vehicle System Identification, Nathan Schaff

Doctoral Dissertations and Master's Theses

Accurate system identification is essential for modeling and controlling vehicle dynamics. This dissertation explores the application of Parameter Informed Reinforcement Learning (PIRL) as a novel approach to system identification (SYSID). PIRL integrates prior system knowledge, such as physical parameters, into reinforcement learning (RL) frameworks to improve estimation accuracy. The study begins with an overview of traditional SYSID methods and then introduces PIRL as a modification of standard RL. The research applies PIRL to short-period aircraft dynamics, demonstrating its effectiveness in both offline and online learning frameworks. The dissertation then further explores PIRL’s utility in an indirect model reference adaptive control …

Development And Validation Of 2nn-Meam Interatomic Potential For Sc And Al-Sc Alloys Thermodynamics Solidification And Intermetallic Ordering, Avik Mahata

Mechanical Engineering Faculty Publications

We present a second-nearest-neighbor Modified Embedded Atom Method (2NN–MEAM) potential for Scandium (Sc) and Aluminum-Scandium (Al–Sc) alloys that unifies cohesive, thermodynamic, and solidification behavior within a single transferable framework. The Sc component accurately reproduces cohesive energy, lattice constants, defect energetics, and the experimental melting point obtained from two-phase coexistence, demonstrating reliable description of both hcp and liquid phases. The Al–Sc binary interaction parameters were fitted using the L1₂–Al₃Sc reference and benchmarked against first-principles and calorimetric data. The potential reproduces the strong negative formation enthalpy of Al₃Sc (–0.45 eV atom⁻¹), correct relative stability …

Engr 204 – Electrical Circuits Project Assignment: Exploring A Key Concept From The Textbook, Liubov Kreminska

Open Educational Resources

This assignment requires students to select a major concept from the ENGR 204 Electrical Circuits textbook and explore it through historical research, conceptual explanation, problem-solving, and real-world application. The project is structured to promote understanding through multiple means of representation, engagement, and expression, following Universal Design for Learning (UDL) principles. Students will describe the history and importance of the chosen concept, explain its main ideas using written or visual aids, solve representative and advanced problems related to the topic, and demonstrate how the concept appears in real-world engineering contexts. The submission must include clearly labeled sections, supporting visuals or simulations, …

Engr 204: 8-Week Op-Amp Major Project Series, Liubov Kreminska

Open Educational Resources

This submission outlines a collection of electronic design projects that can be completed within an 8-week timeframe, progressing from beginner-friendly circuits to advanced real-world applications involving op-amp design. Each project includes a week-by-week plan, required equipment, and key technical challenges. Through these projects, students gradually develop competence in signal processing, circuit stability, noise reduction, calibration, filter design, audio electronics, and bio-signal amplification. The structured timeline ensures systematic learning while allowing hands-on experimentation, troubleshooting, and refinement. The projects serve both as academic exercises and as practical foundations for more advanced electronic system design.

Iphone-Based Image Refocusing, Katie Jeong, Daniel Niu

Electrical and Systems Engineering Capstone Design Projects

In this project, we show that we can change the focus of a picture after we take it by using real optical physics instead of fake software blur. Modern phones try to create “portrait mode” effects, but those results are often not physically correct. Our approach uses multiple photos taken from slightly different positions to figure out the directions that light rays came from in the scene.

To collect the photos, we move an iPhone sideways on a slider in small, precise steps. Since we know exactly how far the phone moved for each picture, we can track how objects …

Measurement-Based Dynamic Load Model Parameterization Via A Stacked Long Short-Term Memory - Deep Neural Network, Zach H. Smith

All Theses

Increases in distributed generation and changes to predominate load types in modern power systems are driving the need for updated or newly developed dynamic load models. Accurate load modeling is necessary for transmission planning and operation, post-mortem analysis, and inter-regional transfer studies. The most widely used dynamic load model is the WECC Composite Load (CMLD). The CMLD model is an aggregation of substation impedance, under voltage and frequency controls, dynamic motor loads, and static loads. Parameterizing dynamic load models, especially composite models with high parameter counts like the CMLD, is can be difficult. This work proposes a measurement-based, machine learning …

Extremum-Seeking Approach For Real-Time Self-Healing Of Position Sensor Offset Error In Non-Salient Pmsms, Ramitha Kalhara Dissanayake Ralalage

Masters Theses

The inherent advantages of permanent magnet synchronous machines (PMSMs), such as high efficiency, has led to their frequent use in industry, including safety-critical applications, such as transportation electrification. The accurate measurement of the rotor position is key to achieving efficient and reliable field-orientation-based torque regulation. With the high reliance on the rotor position measurement, position sensor fault diagnosis and mitigation facilitate a layer of safety. Conventional methods for compensating position sensor offset errors in electric drives typically depend on accurate knowledge of motor parameters. However, these parameters are often subject to variation due to temperature changes, system aging, and other …

Isolated Dc-Dc Converter For An Ev Microgrid, Oscar Yu, William Leiker

Electrical Engineering

This product is a redesign of a DC-DC buck-boost converter which utilizes a new topology, the flyback converter, for use in an electric vehicle (EV) as a microgrid. The main driver behind the redesign is to provide electrical isolation between elements in the microgrid. The EV microgrid consists of the battery, motor, external DC and AC ports, and the power electronics (DC-DC converter and AC-DC inverter) which were designed and built in previous senior projects. Using EV’s as microgrids can help relieve stress from the main power grid caused by charging electric vehicles. Implementing EV’s as a microgrid enables the …

Adaptive Deep Learning In Physical Layer Applications, Ali Owfi

All Dissertations

Traditionally, signal processing models in communication systems have been designed based on solid foundations in statistics and information theory, often assuming linearity and optimizing for simplified models. However, real-world communication systems exhibit numerous imperfections and non-linearities that traditional linear models struggle to capture accurately. Deep Learning (DL)-based approaches, unconstrained by rigid mathematical models, have shown promise in optimizing system performance by accommodating specific hardware configurations and dynamic channel conditions as an alternative to the traditional methods. Despite all the recent research efforts on DL-based methods for physical layer applications, DL models have still not been widely applied to physical layer …

Platforming For Circuit Education, Grady Oliver Schneider

Computer Engineering

The purpose of this project was to provide an alternative for students being introduced to resistive circuits. As a freshman in electrical engineering (transferred to computer engineering), I saw the struggles of other freshman to grasp the conceptual basics of circuits. While there’s lots of guides to circuit education, I think many of them fall short of being both engaging and teaching the intuition behind circuits. A lot of the more advanced concepts in circuits depends on the basic intuition of KCL, KVL, and Ohm’s Law. While there’s several basic techniques (such as voltage divider, current divider, and mesh current …

Position Sensor Offset Fault Calibration In Speed-Regulated Pmsm Drives, Ujala Anuradhi Maha Gamage

Masters Theses

Speed regulation of electro-mechanically actuated systems is common across broad application segments, including industrial and residential sectors. The increasing demand for efficient energy conversion has made permanent magnet synchronous machines (PMSM) a preferred choice in modern applications. Vector controlled PMSMs in speed regulation mode being the dominant form of control, accurate speed and position measurement is crucial. However, a misalignment in the position sensor with respect to the true rotor zero position in speed regulated PMSM drives leads to inefficient energy conversion with the possibility of unstable motor behavior. The considered position sensor offset error fault, under severe fault modes, …

Editable 4d Gaussian Splatting: Scalable And Consistent Video Editing Via Uv-Texture Decomposition, Shuai Lyu

All Theses

Dynamic 3D videos are now widely used in VR, AR, and telepresence, where users often want to change the style or appearance of objects such as clothing over a whole sequence. However, editing such dynamic 3D content is still hard, because appearance, geometry, and motion are tightly coupled, so even a simple color change must stay consistent in all views and at all time steps. Existing editing methods based on 4D Gaussian Splatting often work in a frame-by-frame way, which is slow and makes it difficult to keep temporal and multi-view consistency.

This thesis proposes Editable-4DGS, a representation-centric framework that …

Design And Optimization Of High-Frequency Medium-Voltage Dual Active Bridge Dc/Dc Converter Using Sic Device, Hui Cao

Graduate Theses and Dissertations

High frequency Dual Active Bridge (DAB) converters have become a key enabling technology in medium- and high-power applications such as renewable energy integration, electric vehicle fast charging, and emerging DC power distribution systems. However, when operating at high power and high frequency, DAB converters face critical challenges including limited soft-switching range, uneven semiconductor loss distribution, deadtime-induced resonance, switching-frequency constraints of wide-bandgap (WBG) devices, and transformer DC bias during dynamic transitions. This dissertation addresses these challenges through advancements in modulation strategies and converter architecture. First, an enhanced triple-phase-shift (E-TPS) modulation scheme is proposed to achieve balanced switching and conduction losses across …

Study And Simulation Of Model-Reference Adaptive Control Via The Heffron-Philips Model For Enhanced Power System Stability, Laila Ayman Dallol

Graduate Theses and Dissertations

Improving power transmission and quality has been an area of research interest over the past decades and was improved using renewable energy resources, mainly wind, and solar generation. Renewable energy penetration into power grids aims to replace some traditional synchronous generators, affecting the overall power system with reduced gas emissions that help with climate change and pollution issues. However, renewable generation in power systems ranging from microgrids to national grids is subjected to large disturbances that affect its transient stability, which is measured by its critical clearing time. As increased amounts of renewable generation connected to power systems have resulted …

Volume Status Detection With Integral Pulse Frequency Modulation Model Of Peripheral Venous Pressure, Jeremiah Rhys Wimer

Graduate Theses and Dissertations

This thesis studies the effectiveness of utilizing a modified integral pulse frequency modulation (IPFM) algorithm to synthesize peripheral venous pressure (PVP) waveforms for the detection of several physiological conditions using logistic regression. PVP waveforms are collected from 18 human patients and 4 porcine subjects. Human data are used to train models for determining the hypovolemic status of the patient, while the porcine data are used to train models for determining level of anesthesia and detecting internal hemorrhaging. In the human dataset, the waveforms collected from the 18 patients are classified into two groups according to serum chloride levels: resuscitated (≥100 …

Flood-Level Estimation Using Aerial Imagery, Yisen Zhang

Electrical & Computer Engineering Projects for D. Eng. Degree

Reliable flood-level estimation using aerial UAV (Unmanned aerial vehicle) imagery is essential for effective post-disaster assessment and rapid emergency response. This study utilizes a UAV-based dataset, referred to as the UVA dataset, which integrates multiple public datasets and manually labeled UAV images, together with a multi-stage vehicle-centric framework for flood-depth estimation. The UVA dataset integrates images from multiple public sources, including Unmanned Drone Water Assessment (UDWA), Unmanned Aerial Vehicle Detection and Tracking (UAVDT), Car Parking Lot (CARPK), and additional UAV-view images collected from the internet, followed by manual annotation for water depth, viewing angle, and altitude labels. In the proposed …

Feed Network Design For Passive Beamforming In Hemispherical Phased Arrays, Daniel Flores

Theses and Dissertations

This thesis presents the design, fabrication, and evaluation of a four-element microstrip patch antenna array with a passive 1 to 4 corporate feed network operating at 5 GHz. A single inset-fed patch was developed on Rogers DiClad 880 to ensure accurate tuning and mechanical flexibility, achieving a measured resonance of 5.009 GHz with excellent return loss. The corporate feed network, synthesized using T-junction dividers and quarter-wave transformers, demonstrated strong impedance matching, balanced amplitude distribution, and broadside realized gain near 10 dBi when integrated with the array.

Beam steering was examined through simulation-based phase control, revealing effective scanning up to approximately …

Rapid Prototyping Of Low-Cost Sensor Systems Towards A Platform For Upper Limb Posture Estimation, Russell Rathbun

Electrical Engineering and Computer Science Undergraduate Honors Theses

Physical therapy requires patients to perform repeated actions to achieve meaningful results in rehabilitation. This thesis explores production methods and various sensor systems by utilizing rapid prototyping, inertial measurement units (IMUs), and capacitive sensor arrays (CSAs). CSAs can be made from a wide ar- ray of materials and techniques including 3d printing and laser ablation–to rapidly create CSAs that can be custom fit to enable proximity, force, and touch detection. IMU and CSA systems individually are able to track upper limb movements, ges- tures, and positions. This combination of sensors enables accurate upper limb pos- ture estimation of patients. This …

Reinforcement Learning Based Security Schemes For Distributed Ai Systems, Ashan Chamath Gunawardena

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

Distributed machine learning (DML) is a component of modern intelligent systems, enabling collaborative training across devices such as mobile clients, vehicles, and edge networks. However, the decentralized nature of these systems introduces vulnerabilities, particularly data poisoning attacks that compromise model integrity and degrade performance. Traditional defenses, such as statistical filtering, robust aggregation, and privacy-preserving techniques, often struggle to adapt to overwhelming adversaries or operate under strict privacy and real-time constraints. This dissertation proposes the use of reinforcement learning (RL) and deep reinforcement learning (DRL) based misbehavior detection schemes that dynamically identify poisoning attempts in distributed AI systems, including federated learning, …

A Study On Utilizing Coherently Coupled Orbital Angular Momentum Beams For Maritime Sensing And Communication, Evan Robertson

All Dissertations

A large portion of the world is covered in water which introduces a couple of key challenges in communication and sensing systems. The impact of particulates in the water will limit the ability to successfully transmit information through the water. The study of how the channel impacts specific frequencies and the ability to transmit more information at a single time can limit the impact of this environment in how it degrades an optical communication system. In sensing applications, it is important to detect information related to an object’s motion which will either be towards or away from a system, or …

Lstm Network-Based Scheme For Automatic Characterization Of Power Quality Disturbances, Akram Elmitwally, Mohamed Nader

Mansoura Engineering Journal

Recognition of power quality (PQ) troubles is a critical task in the electrical power industry. Most previous works solve the classification problem using separate feature extraction phase and classification phase. Each phase has its own techniques, and consumes a computation time. This study proposes to utilize the long short-term memory (LSTM) network as a deep learning model to classify the PQ events in one shot. The LSTM network uses its particular processing to classify a PQ event signal directly by reading its time-sequence data. Then, a dedicated post-classification algorithm (PCA) extracts start time, end time, duration, amplitude, and total harmonic …