Engineering Commons^™

Deep Learning-Based Gain Estimation For Multi-User Software-Defined Radios In Aircraft Communications, Viraj K. Gajjar, Kurt L. Kosbar

Electrical and Computer Engineering Faculty Research & Creative Works

It may be helpful to integrate multiple aircraft communication and navigation functions into a single software-defined radio (SDR) platform. To transmit these multiple signals, the SDR would first sum the baseband version of the signals. This outgoing composite signal would be passed through a digital-to-analog converter (DAC) before being up-converted and passed through a radio frequency (RF) amplifier. To prevent non-linear distortion in the RF amplifier, it is important to know the peak voltage of the composite. While this is reasonably straightforward when a single modulation is used, it is more challenging when working with composite signals. This paper describes …

Quantum Ghost Imaging Through An Atmospheric Turbulence Simulator, Mikaela R. Morris

Theses and Dissertations

The use of single photons and photon pairs has become a cornerstone for new developments in the sensing and imaging community for their ability to improve image resolution and signal to noise readings in low light environments and large standoff distances. Quantum imaging techniques have an ability to overcome the fundamental limits of classical imaging, like diffraction. Quantum ghost imaging, a specific type of quantum imaging, uses a bi-photon pair produced during the process of spontaneous parametric down conversion to produce an image. The pair is split using a beam splitter, the signal photon is transmitted through an aperture and …

Deep Reinforcement Learning For Leo Satellite Grouping, James E. Minteer

Theses and Dissertations

This research investigates jamming evasion using DRL to provide an autonomous solution that repositions a geostationary satellite experiencing directed, terrestrial based jamming. Second, this thesis applies DRL to an area of research for LEO satellite constellations, user grouping, using a portion of an Air Force Research Lab reinforcement learning framework. As LEO satellites orbit the earth, they must constantly re-evaluate not only which users they are able to connect to, but on which of its multiple beams. This model succeeds in finding a balance between maximizing signal strength and minimizing overhead from switching user assignments, all while requiring fewer costly …

Yolot: A Recurrent Yolo Model For Robust Video-Based Automotive Object Detection, Dylan Jay Baxter

Master's Theses

Though incredibly effective at detecting objects in isolated frames, modern object detection models are often not designed to take advantage of information present in previous frames of a video stream, despite that data being readily avail- able. To address this shortcoming, this paper proposes YOLOT, a modification of the widely used YOLOv8 object detection model, which seeks to utilize this temporal information with the addition of recurrent structures. In the design of YOLOT, a series of recurrent convolutional modules were inserted at backbone and neck outputs and the final and most effective design was found to be the insertion of …

Danzens: A Toolkit For Sensing, Labeling And Visualizing Dance Movements, Yanelly Mego, Concepción Valdez, Hector M. Camarillo-Abad, Franceli L. Cibrian

Engineering Faculty Articles and Research

Wearable technology offers new opportunities for analyzing complex movements like dance, where precision, coordination, and feedback are key. In this demo, we present DanZens, a novel toolkit for real-time motion analysis in dance, leveraging wearable sensors to provide accessible and actionable feedback. Combining DanceTag to capture and annotate movements with DanceVis to visualize performance differences, DanZens uses Sony Mocopi sensors to analyze motion and generate intuitive heat maps through Dynamic Time Warping (DTW). This system enables precise, cost-effective comparisons between two people doing dance-related movements, offering personalized feedback and eliminating the need for expensive biomechanical labs. Designed to advance pervasive …

Harmonicthreads – An Interface That Supports Accessibility In Musical Interaction, Ellie Nguyen, Miyuki Weldon, Franceli L. Cibrian

Engineering Faculty Articles and Research

Traditional musical instruments often can create boundaries due to their cost, training, mobility, and cognitive requirements, making musical expression inaccessible. To address this challenge, we developed HarmonicThreads, a novel pervasive computing interface consisting of a responsive, flexible fabric. HarmonicThreads provides a tactile and auditory experience, allowing users to easily create and control sounds. Using embedded sensors and real-time processing, HarmonicThreads interprets the user's natural movements and interactions to create adaptable musical outputs. This enables context-aware musical interaction, demonstrating the potential of pervasive interfaces in reducing barriers and making musical expression more accessible.

Risc-V Gpu Acceleration On Low-Cost Embedded Systems, Fadi M. Alzammar

Master's Theses

The Vortex project from Georgia Institute of Technology was created to provide an open-source hardware and software GPGPU research platform based on RISC-V. Skybox was introduced as an extension to Vortex to provide dedicated support for 3D graphics rendering acceleration as a complete GPU platform. This work presents contributions to the render output unit of Skybox, including the development of a blend unit, cache bypassing mechanisms, and performance monitoring metrics. With these, Skybox has succeeded in its goal of accelerating graphics rendering on RISC-V platforms. This work also establishes a foundation for adapting Vortex to low-cost embedded platforms such as …

Industry Applications Society And Conferences [President’S Message], Ayman El-Refaie

Electrical and Computer Engineering Faculty Research and Publications

No abstract provided.

Adaptive Core Materials For Wireless Power Transfer: Evaluating Mr Fluid In Static And Dynamic Scenarios, Abrer Mohsin Samin, Daniela Wolter Ferreira Touma

Shelby Hall Graduate Research Forum Posters

This research introduces the behavior of Magnetorheological (MR) material as a core for Wireless Power Transfer (WPT) and Dynamic Wireless Power Transfer (DWPT) systems. MR fluids are flexible and easily fabricable material, although they offer a lower magnetic permeability compared to conventional Ferrite cores. The main objective of this research is to investigate the potential of MR fluid as a core for static and dynamic WPT system if it improves transfer efficiency, specially under misalignment and movement. MR fluids, known for their ability to rapidly change their rheological properties in response to magnetic fields, support the power transmission between transmitter …

Quantum Finite Automaton Using Ternary Rotation Quantum Gates And Chrestenson Family Quantum Gates, Yuchen Huang, Marek Perkowski, Xiaoyu Song, John M. Acken

Electrical and Computer Engineering Faculty Publications and Presentations

Quantum automata can solve certain problems with a smaller state space than classical automata. We developed a quantum finite automaton using ternary rotation quantum gates and the Chrestenson family of ternary quantum gates. The main idea of this paper is to show how to combine rotation ternary quantum circuit-based QuantumFinite Automaton and quantum reversible circuit-based Deterministic Finite Automaton to build a more powerful machine. The combined machine can enable more complex language and pattern recognition. The developed quantum finite automaton and resulting combined machine can be used for robotics applications such as language, gesture, and motion recognition.

Development And Validation Of An Artificial Intelligence System For Surgical Case Length Prediction, Adhitya Ramamurthi, Bhabishya Neupane, Priya Deshpande, Ryan Hanson, Kellie R. Brown, Kathleen K. Christians, Douglas B. Evans, Anai N. Kothari

Electrical and Computer Engineering Faculty Research and Publications

Background

Accurate case length estimation is a vital part of optimizing operating room use; however, significant inaccuracies exist with current solutions. The purpose of this study was to develop and validate an artificial intelligence system for improved surgical case length prediction by applying natural language processing and machine-learning methods.

Methods

All inpatient elective surgical cases longer than 30 minutes completed between 2017 and 2023 at a single, quaternary care hospital were considered. Data were split into training, test, and hold-out validation for model training and testing. Linear regression, CategoricalBoost, and feed-forward neural network each were trained and used embeddings created …

Industry Applications Society And Conferences [Presidents Message], Ayman El-Refaie

Electrical and Computer Engineering Faculty Research and Publications

No abstract provided.

Dеvеlоpmеnt Аnd Simulаtiоn Оf Аutоmаtiс Tеmpеrаturе Соntrоl Sуstеms Fоr Sоlаr Drуеrs, Sarvar Rejabov, Botir Shukurillayevich Usmonov, Komil Usmanov

Chemical Technology, Control and Management

Thе utilizаtiоn оf sоlаr еnеrgу in thе drуing оf аgriсulturаl prоduсts is соnsidеrеd signifiсаnt duе tо its еnеrgу еffiсiеnсу аnd еnvirоnmеntаl friеndlinеss. Hоwеvеr, trаditiоnаl drуing mеthоds fасе сhаllеngеs in mаintаining stаblе tеmpеrаturе аnd humiditу lеvеls, whiсh саn lеаd tо rеduсеd prоduсt quаlitу аnd dесrеаsеd prосеss еffiсiеnсу. Tо аddrеss thеsе issuеs, thе implеmеntаtiоn оf аutоmаtiс соntrоl sуstеms is еssеntiаl. In dеvеlоping аn аutоmаtiс tеmpеrаturе соntrоl sуstеm fоr sоlаr drуеrs, thе hеаt аnd mаss trаnsfеr prосеssеs wеrе prесisеlу mоdеlеd. Thе primаrу pаrаmеtеrs оf thе drуing prосеss, suсh аs prоduсt tеmpеrаturе аnd mоisturе соntеnt dуnаmiсs, wеrе еxprеssеd thrоugh mаthеmаtiсаl еquаtiоns. PID аnd Fuzzу …

Principles And Models Of Construction Of Linear Motion Actuators With Holonomic Structure For Intelligent Robot Movement, Matyokubov Nurbek Rustamovich, Temurbek Omonboevich Rakhimov, Yusupov Bekmurod Bayotovich

Chemical Technology, Control and Management

This article is devoted to the principles and models of building linear motion actuators with holonomic structure for the movement of intelligent robots. Also, the classification of the elements of the linear movement performance according to their interconnections and technical characteristics, taking into account their physical characteristics, was seen. A morphological matrix of the construction of holonomic structured linear motion performance elements based on the classification according to the considered technical specifications is presented. The given morphological matrix of linear motion actuators serves to develop new actuators for intelligent mechatronic and robotic systems. Based on the morphological matrix of the …

Methodology Of Automated Control Of Situations In Structurally Complex Systems With Recycled Flows, Khusan Zokirovich Igamberdiev Academician, Madina Mirxalilovma Fozilova

Chemical Technology, Control and Management

This article discusses the methodology of automated management of situations in structurally complex systems with recycled flows. The need to develop a correct model for effectively controlling such systems based on scientific principles of analysis and decision-making is substantiated. Particular attention is paid to modeling, optimizing, and using digital technologies, including artificial intelligence, to improve the accuracy and efficiency of management decisions. The principles of decomposition, multi-criteria optimization, and linguistic models of fuzzy correspondence are described, which can be used in conditions of uncertainty and complexity of industrial facilities.

Metal Nitrides As Cathode Hosts For Lithium-Sulfur Batteries, Hai-Ji Xiong, Cheng-Wei Zhu, Ding-Rong Deng, Qi-Hui Wu

Journal of Electrochemistry

Lithium-sulfur batteries are considered as one of the potential solutions as integrating renewable energy systems for large-scale energy storage because of their high theoretical energy density (2600 Wh·kg^–1) and specific capacity (1675 mAh·g^–1). Currently, various strategies have been proposed to overcome the technical barriers, e.g., “shuttle effect”, capacity decay and volumetric change, which impede the successful commercialization of lithium-sulfur batteries. This paper reviews the applications of metal nitrides as the cathode hosts for high-performance lithium-sulfur batteries, summarizes the design strategies of different host materials, and discusses the relationship between the properties of metal nitrides and their …

Enhancing Cycle Life Of Graphite ‖ Lifepo4 Batteries Via Copper Substituted Li2Ni1-XCuXO2 Cathode Prelithiation Additive, Jian-Ming Zheng, Jing-Wen Zhang, Tian-Peng Jiao

Journal of Electrochemistry

Lithium nickel oxide (Li₂NiO₂), as a sacrificial cathode prelithiation additive, has been used to compensate for the lithium loss for improving the lifespan of lithium-ion batteries (LIBs). However, high-cost Li₂NiO₂ suffers from inferior delithiation kinetics during the first cycle. Herein, we investigate the effects of the cost-effective Cu substitution of Li₂Ni_1-xCu_xO₂ (x = 0, 0.2, 0.3, 0.5, 0.7) synthesized by high-temperature solid-phase method on the structure, morphology, electrochemical performance of graphite‖LiFePO₄ battery. The X-ray Diffraction (XRD) refinement result demonstrates that Cu substitution strategy is favorable …

Sno2 Particles Embedded Into Carbon Coated Mesoporous SioX Rod As High Volumetric Capacity Anode For Lithium-Ion Batteries, Jia-Lin Guo, Ni-Ni Li, Peng Zheng

Journal of Electrochemistry

Due to the high capacity and moderate volume expansion of silicon protoxide SiO_x (160%) compared with that of Si (300%), reducing silicon dioxide SiO₂ into SiO_x while maintaining its special nano-morphology makes it attractive as an anode of Li-ion batteries. Herein, through a one-pot facile high-temperature annealing route, using SBA15 as the silicon source, and embedding tin dioxide SnO₂ particles into carbon coated SiO_x, the mesoporous SiO_x-SnO₂@C rod composite was prepared and tested as the anode material. The results revealed that the SnO₂ particles were distributed uniformly in the …

Determination Of Chemical And X-Ray Phase Analysis Of Carbon-Containing Material, Sh.T. Juraev, B.F. Muxiddinov, U.T. Tailakov

Chemical Technology, Control and Management

This paper presents a chemical and X-ray diffraction study of the solid fraction obtained from the thermal-oxidative pyrolysis of waste tires. The study covers the analysis of the composition of rubber products before and after pyrolysis at a temperature of 750-850 °C. A chemical analysis of the gaseous, liquid and solid phases of pyrolysis products was also carried out. The ignition temperatures of gaseous products, their percentage content, as well as the optimal boiling temperatures of the resulting condensates were determined. X-ray analysis showed that the solid carbon residue consists of calcite (7.50%), amorphous carbon (87.24%), ankerite (Ca(Mg, Fe)[CO_{3 …}

Investigation Of Dynamic Characteristics Of New Magneto-Elastic Transducers Of Mechanical Quantities, Sulton Amirov, Kamila Jurayeva

Chemical Technology, Control and Management

In the article examines the dynamic characteristics of new magnetically elastic converters of mechanical quantities by the method of parametric structural circuits. It is shown that the developed differential transformer magneto–elastic converters of power parameters in automatic monitoring and control systems act as a real differentiating link without statics, and magneto-elastic converters of motion parameters act as a whole in the form of sequentially connected oscillatory and real differentiating links. It has been established that the duration of the transient process in magnetoelastic converters of power parameters is determined by the parameters (magnetic capacitance and active magnetic resistance) of the …

Application Of An Adaptive Neuro-Fuzzy Inference System To Control The Wastewater Treatment Process, Jaloliddin Abdurazzakovich Eshbobaev, Bakhodir Tajiddinovich Khamidov, Marcos Torices Fallanza

Chemical Technology, Control and Management

This study explores the application of an Adaptive Neuro-Fuzzy Inference System (ANFIS) for controlling wastewater treatment processes using ion-exchange resins. It addresses the critical challenges of water scarcity and pollution by enhancing the regulation of water hardness (H) and Total Dissolved Solids (TDS). Using a pilot laboratory device and experimental data from the mixed wastewater of the Kungrad Soda Plant in Uzbekistan, an ANFIS model was developed in MATLAB to automate process control. The model leverages water hardness and TDS as input parameters to regulate the water flow rate by servo valve opening degree, ensuring precise and efficient treatment. Compared …

Modeling Of Analog-To-Digital Converter In Signal Processing, Ravshan Aliev, A.U. Djalilov

Chemical Technology, Control and Management

This article is devoted to the study of the modeling process of analog-to-digital converters (ADCs) that process signals, one of the main parts of control system elements and devices. As we know, ADCs are an important part of modern control systems. During the research, the main stages of analog signal conversion were analyzed, i.e. discretization, quantization, coding. A classification of analog-to-digital conversion methods was made and the advantages and disadvantages of each were identified. Also, the characteristics and parameters of ADC were studied, their impact on ADCs performance was evaluated, and it was determined that certain characteristics should be taken …

Joint Estimation Of The State And Parameters Of Dynamic Control Objects Based On The Maine Estimator, Yulduz Abdurakhmanova

Chemical Technology, Control and Management

The issues of constructing an adaptive joint estimation of the state and parameters of dynamic control objects using the Maine estimator are considered. There are various variants of the extended filter, and a variant based on iterations between parameter and state estimates was used in the work. In this version of the extended Kalman filter, the problem of joint parameter and state estimation is solved in such a way that parameter estimation is performed before state estimation. Then, the parameter values are used to assess the state. In this case, further iterations between the state vector estimation and the parameter …

Prototyping Various Mppt Techniques Used In Wind Energy Conversion Systems For Response Time Monitoring, Amro Kawashty, Sameh O. Abdellatif, Gamal Ebrahim, Hani Ghali

Electrical Engineering

This paper focuses on prototyping various maximum power point tracking (MPPT) techniques used in wind energy conversion systems (WECS) for response time monitoring. MPPT plays a crucial role in optimizing the power extraction from wind turbines by dynamically adjusting their operating conditions to track the maximum power point. The response time of an MPPT algorithm determines how quickly it can adapt to changes in wind conditions and maximize power output. In this study, we implement and compare multiple MPPT techniques on an emulated WECS. Several commonly used MPPT techniques, such as perturb and observe (P&O), incremental conductance (IncCond), and tip …

Greening The Workplace: Can Sustainable Practices Reduce Anxiety And Enhance Meaningful Work Engagement?, Cyril Tom T. Sunny, Peter Muttungal, Benny G. Davidson

Northeast Journal of Complex Systems (NEJCS)

This academic research examines the relationship between job engagement, green work climate, job-related anxiety, meaningfulness at work within the organization. It draws attention to identify the significant relations among all these factors and highlights the role of a green work climate in promoting meaningful work and alleviating job-related anxiety. The research emphasizes a diverse sample of employees from various organisations using structural modelling to find the mediating roles of job engagement and work meaningfulness in the correlation between organizational practices, environmental sustainability, and employee satisfaction. The study finds that a green work climate significantly enhances meaningful work experiences and reduces …

Power System Operations Modeling And Optimization Using Pyomo, Ahmad Heidari, Rui Bo

Graduate Student Research & Creative Works

"The energy sector has witnessed transformative advancements over the past few decades. Power systems, which form the backbone of modern society, have grown increasingly complex with the integration of renewable energy sources, energy storage, and emerging technologies. As these systems evolve, so does the need for efficient operation and optimization strategies to ensure reliability, sustainability, and economic performance.

Optimization plays a central role in solving real-world challenges such as balancing power generation and demand, minimizing operational costs, and managing grid constraints. However, many existing resources tend to focus either on theoretical aspects of optimization or rely on expensive, proprietary software …

Increasing Guard Band Size To Decrease Interference In V2x Communication, Nakira Oglesby, Mackenzie Prescott, Billy Kihei, Ph.D.

Symposium of Student Scholars

As technologies evolve and new devices are introduced, the demand for fast and reliable vehicle-to-everything (V2X) communication increases. As this demand increases, the interference level in the 5.9GHz Dedicated Short Range Communications (DSRC) band will inevitably increase. And thus, the task of somehow minimizing this interference becomes increasingly important as time passes. This report investigates the effects of increasing the guard band size of the lower 5.9 GHz DSRC band on the adjacent channel interference from Unlicensed National Information Infrastructure 4 band (U-NII-4) devices and to try and see if there is a significant decrease in the interference level. The …

Impact Of Node Failures On Productivity In Multilayer Supply Chain Networks: An Influence Network Analysis In The Indian Electronics Sector, Surendra Orupalli, Hiroki Sayama

Northeast Journal of Complex Systems (NEJCS)

Supply chain networks are essential for the delivery of goods and information, but disruptions such as natural disasters or trade embargoes can severely impact them. Resilience of entire networks under different types of disruptions when nodes or edges fail has been extensively studied. However, the extent to which the failure of a particular company affects another company of interest within a network has not been widely explored. To address this, we created a multilayer physical supply chain network of companies in an electronics supply chain concentrated in India. Through systematic node removal simulations, we examined how the productivity of one …

A Novel Preprocessing Model For Multi Modal Brain Mri Image Classification For Stroke Prognosis, Alwin Joseph, Chandra J

Northeast Journal of Complex Systems (NEJCS)

Magnetic Resonance Imaging (MRI) is an imaging technique used for the diagnosis and observing the progression in various neurological disorders. Stroke is one of the prominent neurological disorders that creates significant impacts in the patients. It occurs when the blood supply to part of the brain is interrupted or reduced, preventing brain tissues from getting oxygen and nutrients. Multimodal data from various modalities help clinicians in proper prognosis of stroke. Ischemic Stroke Lesion Segmentation Challenge (ISLES22) provides data of stroke data for various stroke patients, the dataset consists of three modalities of data – Fluid Attenuated Inversion Recovery (FLAIR), Apparent …

Classification Of Microcontroller Integrated Circuit On The Pocket Of Jedec Tray Using Convolutional Neural Network In Embedded Machine Learning System, Mark Pallones, King Harold A. Recto

Electronics, Computer, and Communications Engineering Faculty Publications

One serious issue in the microcontroller manufacturing environment is the mixing of microcontroller unit (MCU) parts, leading to the wastage of materials, dissatisfied customers, and the implementation of non-value-adding activities to address it. More adverse effects include negative feedback from customers, loss of confidence, and impact on business growth. One root cause traces back to the final testing of the manufacturing back-end process when reusing unemptied standard JEDEC matrix trays for good and bad units in the test handler. Currently, emptying the JEDEC matrix tray and inspecting it is a manual process prone to human error due to high-volume test …