Engineering Commons^™

Emerging Technologies For Automation In Environmental Sensing: Review, Shekhar Suman Borah, Aaditya Khanal, Prabha Sundaravadivel

Electrical Engineering Faculty Publications and Presentations

This article explores the impact of automation on environmental sensing, focusing on advanced technologies that revolutionize data collection analysis and monitoring. The International Union of Pure and Applied Chemistry (IUPAC) defines automation as integrating hardware and software components into modern analytical systems. Advancements in electronics, computer science, and robotics drive the evolution of automated sensing systems, overcoming traditional limitations in manual data collection. Environmental sensor networks (ESNs) address challenges in weather constraints and cost considerations, providing high-quality time-series data, although issues in interoperability, calibration, communication, and longevity persist. Unmanned Aerial Systems (UASs), particularly unmanned aerial vehicles (UAVs), play an important …

Plasma Diagnostics For Anode Cathode Plasmas And High Energy Density Physics On A Linear Transformer Driver, Robert Beattie-Rossberg

Electrical and Computer Engineering ETDs

A twelve-brick air insulated linear transformer driver (LTD) was characterized by charging to voltages ranging from 30 to 70 kV and delivering energy to two separate resistive loads. Various plasma diagnostics were built and fielded with an emphasis on the design, implementation and analysis of a Mach Zehnder interferometer, a moiré deflectometer and a spectroscopy system providing information on the temporal evolution of plasma electron density and atomic composition. Rogowski coils, XRD radiation detectors, framing camera images and time integrated DSLR images are used to further understand load conditions where current data, x ray radiation data, velocity data and instability …

Arkansas Tech University Modular Robotics Training System, Andrew L. Hilsdon, Jacob L. Crawford, Luke C. Hartman, Samuel E. Allen, Anthony W. Knudson, Kyle B. Mcmillan

ATU Scholars Symposium

Arkansas Tech University Modular Robotic Training System (ATUM RTS) project aims to combine two existing systems: The Georgia Tech Robotarium and the Micromouse maze-solving competition. The goal of ATUM RTS is to incorporate the challenge and excitement of maze-solving robots with the cloud-based learning system of the Robotarium. We intend to develop an automatic maze table with future remote capabilities to further student learning and engagement. By being able to create custom mazes with ATUM RTS, students will have access to a resource that will allow them to practically apply what they are learning in the classroom. The ATUM RTS …

Ieee Robotics Competition, Emily Webb, Arath Sanchez, Genesis V. Garay, Caleb Bynum, Brandon Bunton

ATU Scholars Symposium

No abstract provided.

Applications Of Supercapacitors In Robotic Systems, Charles Davis, Zachary Giese, Joseph Gober, Samuel Grisham, Avery Mahan

ATU Scholars Symposium

This project explores the utilization of a bespoke supercapacitor system to energize and propel a robot across various challenging courses. The custom supercapacitor setup serves as the primary power source, providing rapid charging capabilities and high energy density. The research investigates the integration of this innovative power solution into the robot's design, aiming to optimize its performance and endurance in competitive environments.

Hybrid Pv-Teg System, Anna-Marie Pesaresi, Paige Woolheater, Chance Eoff, Nicholas Colburn

ATU Scholars Symposium

This research is focused on an innovative approach to improving the efficiency of a well- established renewable energy source. Solar cells are becoming more prominent as the power industry is shifting towards using more clean energy sources. Photovoltaic (PV) solar cells can only absorb a portion of the irradiance spectrum. The portion that is not absorbed raises the temperature of the system. The efficiency of PV cells drastically decreases as the temperature of the module rises and more energy is lost in the form of heat waste. Thermoelectric generator (TEG), when combined with PV cell, thrives off of the PV …

Exploring Various Integration Methods Of Carbon Quantum Dots In Cspbcl3 Perovskite Solar Cells For Enhanced Power Conversion Efficiency, Eman Sawires, Zahraa Ismail, Mona Samir, Ahmed Agour, Fathy Amer, Hassan Nageh, Sameh O. Abdellatif

Electrical Engineering

No abstract provided.

Advancing Brain Tumor Segmentation With Spectral–Spatial Graph Neural Networks, Sina Mohammadi, Mohamed Allali

Engineering Faculty Articles and Research

In the field of brain tumor segmentation, accurately capturing the complexities of tumor sub-regions poses significant challenges. Traditional segmentation methods usually fail to accurately segment tumor subregions. This research introduces a novel solution employing Graph Neural Networks (GNNs), enriched with spectral and spatial insight. In the supervoxel creation phase, we explored methods like VCCS, SLIC, Watershed, Meanshift, and Felzenszwalb–Huttenlocher, evaluating their performance based on homogeneity, moment of inertia, and uniformity in shape and size. After creating supervoxels, we represented 3D MRI images as a graph structure. In this study, we combined Spatial and Spectral GNNs to capture both local and …

Ferroresonance In Three-Phase Electrical Networks, Shavkat Ernstovich Begmatov

Technical science and innovation

Possible modes of ferroresonance in three-phase electric networks and analysis of substitution schemes where ferroresonance voltage increase is observed are considered. The most complete magnetization curve of the transformer core and the analysis of the generalized equivalent substitution scheme are presented, as a result of which more accurate formulas for determining the values of equivalent parameters of the electrical network and voltage transformer in ferroresonance mode are obtained. Factor of ferroresonance voltage increase is introduced, which determines ratio between amplitude values of transformer phase voltage and mains voltage. The method of determination of boundary conditions of steady ferroresonance voltage increase …

Main Prospects Of Natural Gas Purification Technologies From Acidic Compounds, Oybek Yusupdjanovich Aripdjanov, Diyora Zokhid Qizi Khayrullaeva, Jonibek Avazek Ogli Abdumuminov

Technical science and innovation

The article discusses the main prospects for the technology of purifying natural gas from acidic components and the problems of ensuring the purity of oil and gas products in accordance with state standards. An increase in the degree of purification from H₂S, CO₂, elemental sulfur, carbonyl sulfide, ethyl mercaptans (thiols), methyl mercaptan, carbon disulfide, sulfides, disulfides (dithioethers), thiophene, sulfoxides and sulfones is considered. Also, the physicochemical properties of the absorbent for the purification of sulfur compounds (generated during natural gas processing) are studied. Based on the study of various absorbents (ethanolamine (EA), methylethanolamine (MEA), diethanolamine (DEA), …

Modeling The Human Learning Process Using An Industrial Steam Boiler Analogy To Design A Psychophysiological-Based Hypermedia Adaptive Automation System, Liliana María Villavicencio López

USF Tampa Graduate Theses and Dissertations

This dissertation aims to address the existing gap in the integration of various dimensions within the student learning system, encompassing cognitive, emotional, and physical variables. The primary objective is to construct a Personalized Learning Adaptive Automation model using Electroencephalography (EEG) technology.

To provide deeper insight into the intricate nature of the Human Learning Process, this study introduces a novel analogy with an Industrial Steam Boiler. This analogy serves as a distinctive contribution to research in the field.

The research methodology involved the collection of brainwaves data from engineering students while they undertook educational tasks of varying levels of difficulty, categorized …

Techno-Economic Analysis Of Solar Pv Systems Under Various Environmental Conditions, Ramkiran B

Theses and Dissertations

World Energy Council has predicted that the global electricity demand will peak in 2030. The need for renewable energy has grown rapidly due to the rising energy demand in this ever-growing population. Green house gas emissions are predominantly due to the energy generation and consumption of fossil fuels. On the other hand, fossil fuels supply nearly 74% of India's energy demand, making India one of the world's largest coal consumers.

According to World Resource Institute, India ranks fourth in the world in terms of carbon emissions. Investments in renewable energy sources and energy-saving technologies should be part of a solution …

Controlling The Broadband Enhanced Light Chirality With L-Shaped Dielectric Metamaterials, Ufuk Kilic, Matthew Hilfiker, Shawn Wimer, Alexander Ruder, Eva Schubert, Mathias Schubert, Christos Argyropoulos

Department of Electrical and Computer Engineering: Faculty Publications

The inherently weak chiroptical responses of natural materials limit their usage for controlling and enhancing chiral light-matter interactions. Recently, several nanostructures with subwavelength scale dimensions were demonstrated, mainly due to the advent of nanofabrication technologies, as a potential alternative to efficiently enhance chirality. However, the intrinsic lossy nature of metals and the inherent narrowband response of dielectric planar thin films or metasurface structures pose severe limitations toward the practical realization of broadband and tailorable chiral systems. Here, we tackle these problems by designing all-dielectric silicon-based L-shaped optical metamaterials based on tilted nanopillars that exhibit broadband and enhanced chiroptical response in …

1st Person Ev With Electronic Differential, Tessa Biondo

Honors Theses

The First Person EV with Electronic Differential for Vehicle Dynamics Analysis project makes a significant leap forward in the exploration of electric vehicle (EV) stability and performance enhancement. Lead by a team of skilled electrical engineering students under the guidance of WMU’s associate Professor Dr. Sandun Kuruppu, this project aims to improve EV stability by optimizing power and torque distribution between wheels using an electronic differential system. The project encompasses the design and assembly of a 1/7^th scale custom electric vehicle, capable of remote control via a first-person view (FPV) camera and modified USB wheel and pedal assembly. The …

W/V-Band Propagation Modeling, Nolan Rebernick

Electrical and Computer Engineering ETDs

Enhancing the accuracy of atmospheric loss modeling holds the potential to significantly refine estimations of received power, thereby enhancing the overall quality of satellite communication links. This study aims to pioneer and validate an innovative modeling framework to reliably predict atmospheric attenuation along satellite-to-ground propagation paths, particularly focusing on portions of the W-band (81-86 GHz) and V-band (71-76 GHz). By leveraging meteorological data, this approach will encompass various weather scenarios, including clear skies, cloud cover, and diverse forms of precipitation. Utilizing the generated time domain data, the research aims to construct complementary cumulative distribution functions, enabling the analysis of satellite …

A Reputation System For Provably-Robust Decision Making In Iot Blockchain Networks, Charles C. Rawlins, Sarangapani Jagannathan, Venkata Sriram Siddhardh Nadendla

Electrical and Computer Engineering Faculty Research & Creative Works

Blockchain systems have been successful in discerning truthful information from interagent interaction amidst possible attackers or conflicts, which is crucial for the completion of nontrivial tasks in distributed networking. However, the state-of-the-art blockchain protocols are limited to resource-rich applications where reliably connected nodes within the network are equipped with significant computing power to run lottery-based proof-of-work (pow) consensus. The purpose of this work is to address these challenges for implementation in a severely resource-constrained distributed network with internet of things (iot) devices. The contribution of this work is a novel lightweight alternative, called weight-based reputation (wbr) scheme, to classify new …

Quantum Search Algorithms For Constraint Satisfaction And Optimization Problems Using Grover's Search And Quantum Walk Algorithms With Advanced Oracle Design, Abdirahman Sheikh Hassan Alasow

Dissertations and Theses

The field of quantum computing has emerged as a powerful tool for solving and optimizing combinatorial optimization problems. To solve many real-world problems with many variables and possible solutions for constraint satisfaction and optimization problems, the required number of qubits of scalable hardware for quantum computing is the bottleneck in the current generation of quantum computers. In this dissertation, we will demonstrate advanced, scalable building blocks for the quantum search algorithms that have been implemented in Grover's search algorithm and the quantum walk algorithm. The scalable building blocks are used to reduce the required number of qubits in the design. …

Joint Energy And Security Optimization In Underwater Wireless Communication Networks, Kazi Y. Islam, Iftekhar Ahmad, Yue Rong, Daryoush Habibi

Research outputs 2022 to 2026

Underwater wireless communication networks (UWCNs) can support a wide range of applications in the underwater domain, including mining and drilling, coastline monitoring, border surveillance, and submarine/mine detection. Some of these applications are sensitive in nature (e.g., military) and demand stringent security requirements for data communications. In order to prevent malicious attacks (e.g., jamming) in these UWCNs, robust security countermeasures must be implemented. Additionally, sensitive data communications must be protected. However, computationally expensive security protocols, such as encryption, can severely shorten UWCN lifetime, where battery-powered nodes already suffer from scarce energy supplies. In this work, we exploit content caching as a …

Ml/Ai Enabled Intelligent Next Generation Autonomous Network System: Performance Enhancement And Management, Harsh Kumar

Electrical and Computer Engineering ETDs

The smart next generation autonomous system for network performance enhancement and management, specifically suitable for networks like 5G, B5G, 6G, and SDN, is presented in this PhD dissertation powered by ML/AI. The dissertation has been divided into six critical parts. First, it focuses on QoS monitoring and provisioning using intelligent QoS agent design in 6G network. Second, it elaborates on LSTM and SP-LSTM comparative analysis towards network traffic prediction in 6G networks. Third, digging into 6G frontier navigation using SE-DO for intelligent Agent Optimization. Fourth, the dissertation delves into role delegation function as a service to improve reliability and latency …

A Framework For Managing System Resources And Pricing In Multi-Provider Edge Computing Environments, Matthew Paul Salcido

Electrical and Computer Engineering ETDs

Multi-provider multi-user multi-access edge computing provides a recent market driven networking paradigm facilitating the user data offloading process. In this thesis, we introduce the AGORA framework, which employs a sophisticated multi-leader multi-follower Stackelberg game that jointly optimizes the data offloading, computing resource allocation, and computing resource pricing, all facilitated through a non-cooperative game-theoretic approach. In order to support the aforementioned modeling and approach, a novel utility function that quantifies the users satisfaction, factoring in the computing service cost, and an innovative profit function for the MEC providers is introduced, emphasizing the market penetration and the computing service provision costs. Numerical …

Data Driven Enhanced Vsg Control For Microgrids, Sophia A. Strathman, Oroghene Oboreh-Snapps, Jonathan W. Kimball

Undergraduate Research Conference at Missouri S&T

This research explores the fusion of deep reinforcement learning and virtual synchronous generator control in a bid to enhance microgrid operations. Microgrids typically consist of multiple inverter-based distributed generators (IBDGs) connected in parallel to mismatched line impedances. This results in unequal reactive power sharing which negatively impacts the performance of IBDGs in microgrids. To achieve enhanced control, a solution utilizing deep reinforcement learning (DRL) is proposed. DRL agents are trained to control variables in each IBDG using a well-designed reward function capable of achieving the following objectives: 1.) ensure output voltage of each IBDG remains within the designated operating boundary …

Experiential Learning In Rf Circuit Design, Benjamin Cuebas

Undergraduate Research Conference at Missouri S&T

This research project will explore the intricacies of Radio Frequency (RF) circuitry design, demonstrating acquired insights by constructing a discrete RF amplifier with digital input attenuation control. The study will delve into a multitude of RF topics such as serial communication, digital data storage, transmission line theory, impedance matching, network parameters, amplifier classes, and Smith chart analysis. The RF amplifier will be designed to have an approximately 15dB input gain/attenuation digitally controlled by an external microcontroller. The device will operate at 50 MHz, in the VHF frequency range, with an input and output impedance of 50 . A network analyzer …

The Deconstructed 555 Timer And Application Circuits For Interactive Educational Experience, Preston Carroll, Benjamin Cuebas, Justin Fausto, Rohit Dua

Undergraduate Research Conference at Missouri S&T

The Deconstructed 555 Timer and Application Circuits for Interactive Educational Experience offers interactional implementation of three fully discrete 555 Timer example circuits. The research project goal was to gain knowledge of the 555 Timer by deconstructing the device down to the component level. Three independent example application circuits, which showcase the application versatility of the 555 Timer in different modes, include Monostable, Astable, and Bistable circuits. Each mode has a hardware interface that can be used to adjust the operation of the 555 Timer allowing for a full interactive experience. The user can observe the differences in the internal working …

Voltage Scaled Low Power Dnn Accelerator Design On Reconfigurable Platform, Rourab Paul, Sreetama Sarkar, Suman Sau, Sanghamitra Roy, Koushik Chakraborty, Amlan Chakrabarti

Electrical and Computer Engineering Faculty Publications

The exponential emergence of Field-Programmable Gate Arrays (FPGAs) has accelerated research on hardware implementation of Deep Neural Networks (DNNs). Among all DNN processors, domain-specific architectures such as Google’s Tensor Processor Unit (TPU) have outperformed conventional GPUs (Graphics Processing Units) and CPUs (Central Processing Units). However, implementing low-power TPUs in reconfigurable hardware remains a challenge in this field. Voltage scaling, a popular approach for energy savings, can be challenging in FPGAs, as it may lead to timing failures if not implemented appropriately. This work presents an ultra-low-power FPGA implementation of a TPU for edge applications. We divide the systolic array of …

A Scalable Approach To Minimize Charging Costs For Electric Bus Fleets, Daniel Mortensen, Jacob Gunther

Electrical and Computer Engineering Faculty Publications

Incorporating battery electric buses into bus fleets faces three primary challenges: a BEB’s extended refuel time, the cost of charging, both by the consumer and the power provider, and large compute demands for planning methods. When BEBs charge, the additional demands on the grid may exceed hardware limitations, so power providers divide a consumer’s energy needs into separate meters even though doing so is expensive for both power providers and consumers. Prior work has developed a number of strategies for computing charge schedules for bus fleets; however, prior work has not worked to reduce costs by aggregating meters. Additionally, because …

Meso-Scale Seabed Quantification With Geoacoustic Inversion, Tim Sonnemann, Jan Dettmer, Charles W. Holland, Stan E. Dosso

Electrical and Computer Engineering Faculty Publications and Presentations

Abstract Knowledge of sub-seabed geoacoustic properties, for example depth dependent sound speed and porosity, is of importance for a variety of applications. Here, we present a semi-automated geoacoustic inversion method for autonomous underwater vehicle data that objectively adapts model inference to seabed structure. Through parallelized trans-dimensional Bayesian inference, we infer seabed properties along a 12 km survey track on the scale of about 10 cm and 50 m in the vertical and horizontal, respectively. The inferred seabed properties include sound speed, attenuation, density, and porosity as a function of depth from acoustic reflection coefficient data. Parameter uncertainties are quantified, and …

Use Of Mathematical Skills For Technical Condition Assessment Of Power Autotransformers, Dilafruz Rustamjon Qizi Abdullabekova, Nurali Berdiyorovich Pirmatov

Technical science and innovation

In this paper, we review innovative approaches to assess the technical condition of autotransformers using mathematical methods. The main purpose of these methods is to increase the efficiency of diagnostics and prevent possible failures in power systems. The developed mathematical expression is based on complex data analysis, application of statistical methods and machine learning technologies. This makes it possible to achieve more accurate and earlier detection of potential problems. As a result of these innovative approaches, the possibilities for early detection and prevention of faults are significantly increased. This is important for ensuring the smooth operation of power systems and …

Quantitative Assessment And Characterization Of Tool Wear Phenomena In Advanced Manufacturing Processes, Oybek Valijonovich Tuyboyov

Technical science and innovation

This paper explores the quantitative assessment and characterization of tool wear phenomena in advanced manufacturing processes, employing a multifaceted approach encompassing traditional measurements, image processing, machine learning, and predictive modeling. The study emphasizes the intricate dynamics of tool wear and its direct impact on cutting tool performance, addressing challenges in real-time monitoring and optimization of machining operations. Traditional methods like VBmax measurement are juxtaposed with advanced techniques such as the improved conditional generative adversarial net with a high-quality optimization algorithm (CGAN-HQOA), efficient channel attention destruction and construction learning (ECADCL), and shape descriptors based on contour, moments, orientations, and texture. Artificial …

Implementing A Solar Photovoltaic Station In Watering Systems Utilizing Complex Software, Akbarxon Sarvar O'G'Li Uroqov, Faxriddin Jaylovovich Nosirov, G'Olibjon Pardayevich Arzikulov, Zarina Amriddin Qizi Sayfutdinova

Technical science and innovation

This article explores the benefits of transitioning from traditional agricultural irrigation systems to more cost-effective alternatives powered by renewable energy sources. By integrating solar photovoltaic technology into irrigation processes, significant reductions in resource wastage, estimated at 45-50%, are achievable through the implementation of drip irrigation techniques. This results in enhanced agricultural productivity. Moreover, the utilization of solar panels in green zones mitigates surface temperature increases, contributing to a 2-5% boost in electricity production. Currently, irrigation facilities primarily rely on the main energy grid. However, transitioning to renewable energy sources decreases reliance on non-renewable fuels, reduces greenhouse gas emissions, and fosters …

Theory Of Development And Improvement Of The Mathematical Model Of The Methodology Of Public Control In The Management Of Occupational Safety And Industrial Risks, Aliakbar Khamidullaevich Rasulev, Sunnatilla Suleymanovich Suleymanov, Nodira Bakhadirzhanovna Gaibnazarova

Technical science and innovation

The article develops and analyzes a mathematical model based on a logical flowchart of the methodology of public control in the management of occupational safety and industrial risks and probability theory, according to the model, the results of compliance with the requirements of social cooperation on occupational safety lead to a sharp increase in the probability of reliability, management efficiency becomes higher. Analysis of the mathematical model of the developed logical flowchart based on probability theory has shown that when the parties cooperate to monitor the results of compliance with labor protection requirements, they lead to a sharp increase in …