Electrical and Computer Engineering Commons^™

Optocoupler Integration Of Ltcc-Based Gate Driver In A Sic Power Module, Michael Oghenekome Otobo

Graduate Theses and Dissertations

The growing demand for electrical energy in today’s industrialized economy has driven the need for innovative approaches to meet diverse application requirements. Notably, advancements have been made in the field of power electronic systems, as reliable power electronic converters are essential for managing multiple power sources and loads. However, the development of these systems poses challenges related to power device switching speed, system weight and size, and power losses. The integration of a gate driver into a SiC power module offers a solution to many of these challenges, thereby driving the advancement of electrical power density expansion. An LTCC-based gate …

A Scalable, Cost-Oriented Approach For Computing Charge Plans For Electric Bus Fleets, Daniel T. Mortensen

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Recent attention for reduced carbon emissions has pushed transit authorities to adopt battery electric buses (BEBs). One challenge experienced by BEB users is extended charge times, which create logistical challenges and may force BEBs to charge when energy is more expensive. Furthermore, BEB charging leads to high power demands, which can significantly increase monthly power costs and may push electrical infrastructure beyond its present capacity, requiring expensive upgrades. This work presents a novel method for minimizing the monthly cost of BEB charging while meeting bus route constraints. This method extends previous work by incorporating a more novel cost model, effects …

Development Of The Digital Signal Processing For The Space Weather Probes Version 2 Sensor Using The Matlab/Simulink Environment, Benjamin J. Lewis

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Space Weather Probes (SWP) is an instrument that provides measurements of the plasma environment of the ionosphere. SWP was flown on the Scintillation Prediction Observation Task (SPORT) mission, a joint mission between the United States of America and Brazil. This thesis will develop the digital signal processing (DSP) hardware design for the Space Weather Probes version 2 (SWP2). The data from these instruments will be used to determine the density and temperature of the local plasma, as well as the electric field in the local plasma. This thesis presents the design and testing of the DSP designs for all of …

Mission Planning Techniques For Cooperative Leo Spacecraft Constellations, Skylar A. Cox

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

This research develops a mission planning approach that allows different systems to cooperate in accomplishing a single mission goal. Using the techniques described allows satellites to cooperate in efficiently maneuvering, or collecting images of Earth and transmitting the collected data to users on the ground. The individual resources onboard each satellite, like fuel, memory capacity and pointing agility, are used in a manner that ensures the goals and objectives of the mission are realized in a feasible way. A mission plan can be generated for each satellite within the cooperating group that collectively optimize the mission objectives from a global …

Developing Firmware For Space Weather Probes 2 Using Hdl Coder, Nicholas L. Wallace

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

GPS and wireless communications are affected by interference from the ionosphere. Space weather affects plasma in the ionosphere, causing communication disruptions and reliability issues. To better understand how space weather affects the ionosphere, instruments are flown in space to collect data about the electrical characteristics of plasma in the ionosphere. Space systems require a lot of time and effort to develop and test. This thesis explores how a high level tool can be used to simplify the process and some obstacles that still exist with developing some space systems. To do this, the firmware architecture of a new version of …

Evalattai: A Holistic Approach To Evaluating Attribution Maps In Robust And Non-Robust Models, Ian E. Nielsen, Ravi Ramachandran, Nidhal Carla Bouaynaya, Hassan M. Fathallah-Shaykh, Ghulam Rasool

Henry M. Rowan College of Engineering Departmental Research

Eyes are one of the main critical organs of the body that provide our brain with the most information about the surrounding environment. Disturbance in the activity of this informational organ, resulting from different ocular diseases, could affect the quality of life, so finding appropriate methods for treating ocular disease has attracted lots of attention. This is especially due to the ineffectiveness of the conventional therapeutic method to deliver drugs into the interior parts of the eye, and the also presence of barriers such as tear film, blood-ocular, and blood-retina barriers. Recently, some novel techniques, such as different types of …

Study Of Radiation Effects In Gan-Based Devices, Han Gao

Electrical Engineering Theses and Dissertations

Radiation tolerance of wide-bandgap Gallium Nitride (GaN) high-electron-mobility transistors (HEMT) has been studied, including X-ray-induced TID effects, heavy-ion-induced single event effects, and neutron-induced single event effects. Threshold voltage shift is observed in X-ray irradiation experiments, which recovers over time, indicating no permanent damage formed inside the device. Heavy-ion radiation effects in GaN HEMTs have been studied as a function of bias voltage, ion LET, radiation flux, and total fluence. A statistically significant amount of heavy-ion-induced gate dielectric degradation was observed, which consisted of hard breakdown and soft breakdown. Specific critical injection level experiments were designed and carried out to explore …

A Special Issue: Electric Machinery And Transformers, Huseyin R. Hiziroglu

Electrical & Computer Engineering Publications

As the demand for electrical energy increases worldwide, engineers and scientists have been investigating new electrical systems and materials to meet this demand economically, having large-scale planning and employing environmentally friendly energy production and energy-efficient systems for consumption to minimize adverse environmental effects. New applications such as renewable energy production, e-mobility, and aerospace technology can be considered within the scope of this perspective. Thus, it is a necessity to establish new paradigms in the design, construction, and selection of new materials and drive systems for electric machines and transformers, where such stringent requirements, as high power density, low weight, compact …

Empowering 5g Mmwave: Leveraging Kml Placemarks For Enhanced Rf Design And Deployment Efficiency, Gustavo A. Fernandez

School of Mathematical & Statistical Sciences Faculty Publications

This publication explores the significance of Keyhole Markup Language (KML) in telecommunications, particularly in the context of 5G mmWave RF design and planning. With the advent of 5G mmWave technology, the demand for seamless and efficient network deployments has never been greater. The deployment of small cells and repeaters for 5G mmWave necessitates utmost precision in location accuracy and rapid information exchange during site surveys and evaluations. The challenges of mmWave frequencies, including their limited range and susceptibility to attenuation, intensify the complexity and criticality of this process. Network operators must ensure that the chosen location is devoid of obstacles …

Deep Learning For Multi-Structured Javanese Gamelan Note Generator, Arik Kurniawati, Eko Mulyanto Yuniarno, Yoyon Kusnendar Suprapto

Knowledge Engineering and Data Science

Javanese gamelan, a traditional Indonesian musical style, has several song structures called gendhing. Gendhing (songs) are written in conventional notation and require gamelan musicians to recognize patterns in the structure of each song. Usually, previous research on gendhing focuses on artistic and ethnomusicological perspectives, but this study is to explore the correlation between gendhing as traditional music in Indonesia and deep learning technology that replaces the task of gamelan composers. This research proposes CNN-LSTM to generate notation of ricikan struktural instruments as an accompaniment to Javanese gamelan music compositions based on balungan notation, rhythm, song structure, and gatra …

Recent Progress Of Bifunctional Electrocatalysts For Oxygen Electrodes In Unitized Regenerative Fuel Cells, Tian-Long Zheng, Ming-Yu Ou, Song Xu, Xin-Biao Mao, Shi-Yi Wang, Qing-Gang He

Journal of Electrochemistry

Unitized regenerative fuel cells (URFCs), which oxidize hydrogen to water to generate electrical power under thefuel cells (FCs) mode and electrolyze water to hydrogen under the water electrolysis (WE) mode for recycling, areknown as clean and sustainable energy conversion devices. In contrast to the hydrogen oxidation reaction (HOR) andhydrogen evolution reaction (HER) on the hydrogen electrode side, the sluggish kinetics of oxygen reduction reaction(ORR) and oxygen evolution reaction (OER) on the oxygen electrode side requires highly efficient bifunctional oxygencatalysts. Conventional precious metal oxygen catalysts combine Pt and IrO₂ with excellent ORR and OER activities toachieve bifunctional electrocatalysis performance, but …

Band Alignments Of Metal/Oxides-Water Interfaces Using Ab Initio Molecular Dynamics, Yong-Bin Zhuang, Jun Cheng

Journal of Electrochemistry

Band alignments of electrode-water interfaces are of crucial importance for understanding electrochemical interfaces. In the scenario of electrocatalysis, applied potentials are equivalent to the Fermi levels of metals in the electrochemical cells; in the scenario of photo(electro)catalysis, semiconducting oxides under illumination have chemical reactivities toward redox reactions if the redox potentials of the reactions straddle the conduction band minimums (CBMs) or valence band maximums (VBMs) of the oxides. Computational band alignments allow us to obtain the Fermi level of metals, as well as the CBM and VBM of semiconducting oxides with respect to reference electrodes. In this tutorial, we describe …

Machine Learning-Based Drone And Aerial Threat Detection For Increased Turret Gunner Survivability, Nikolas Koutsoubis

Theses and Dissertations

The introduction of aerial drones on the modern battlefield has transformed combat operations, posing a significant threat to ground-based military operations. Detecting drones in safety scenarios is crucial. However, modern machine learning (ML)-based object detectors struggle to detect small objects like drones. This thesis presents three main contributions: (a) data and algorithmic modifications to improve small object detection in YOLO to aid in drone detection, (b) the development of a benchmark drone detection dataset called DyViR, and (c) the implementation of explainable artificial intelligence (XAI) to ensure transparent and trustworthy decision-making. To boost the performance of small object detection, we …

Design Of Asic Based Electrical Impedance Tomography Microendoscopic System For Prostate Cancer Surgical Marginal Assessment, Mohsen Shahghasemi

Dartmouth College Ph.D Dissertations

Prostate cancer is the second most common cancer in the United States. It is typically treated by surgically excising the cancerous section of the prostate. Because there is not always a visible distinction between the healthy and cancerous sections, surgery often leaves some cancerous tissue behind. This is referred to as a positive surgical margin and it requires adjuvant treatment with adverse side effects. Electrical impedance tomography (EIT) is a low-cost low-form-factor method that can be used to assess surgical marginal intraoperatively to ensure that no cancerous tissue is left behind. EIT-based surgical margin assessment works on the principle that …

Designing Intelligent Energy Efficient Scheduling Algorithm To Support Massive Iot Communication In Lora Networks, Jui Mhatre

Master of Science in Computer Science Theses

We are about to enter a new world with sixth sense ability – “Network as a sensor -6G”. The driving force behind digital sensing abilities is IoT. Due to their capacity to work in high frequency, 6G devices have voracious energy demand. Hence there is a growing need to work on green solutions to support the underlying 6G network by making it more energy efficient. Low cost, low energy, and long-range communication capability make LoRa the most adopted and promising network for IoT devices. Since LoRaWAN uses ALOHA for multi-access of channels, collision management is an important task. Moreover, in …

Using Machine Learning To Assist Auditory Processing Evaluation, Hasitha Wimalarathna, Sangamanatha Veeranna, Minh Vu Duong, Chris Allan Prof, Sumit K. Agrawal, Prudence Allen, Jagath Samarabandu, Hanif M. Ladak

Electrical and Computer Engineering Publications

Introduction: Approximately 0.2–5% of school-age children complain of listening difficulties in the absence of hearing loss. These children are often referred to an audiologist for an auditory processing disorder (APD) assessment. Adequate experience and training is necessary to arrive at an accurate diagnosis due to the heterogeneity of the disorder.

Objectives: The main goal of the study was to determine if machine learning (ML) can be used to analyze data from the APD clinical test battery to accurately categorize children with suspected APD into clinical sub-groups, similar to expert labels.

Methods: The study retrospectively collected data from 134 children referred …

Adaptive Gps Antenna Array Beam Nulling Effectiveness Under Varying Antenna Element Positioning, Aadesh Neel

Electrical and Computer Engineering ETDs

Global Positioning System (GPS) is an essential part of modern life but is susceptible to same frequency jamming. GPS jamming can add excessive noise to a received low power signal and have the capability to change or completely distort information being sent through the GPS signal. Adaptive antenna arrays have long since been a solution to mitigating GPS jamming via beamnulling algorithms. However, there is little research on the effectiveness of these beamnulling algorithms under varying element positioning. In this work, an adaptive antenna array, consisting of Right-Hand Circularly Polarized (RHCP) nearly square GPS antenna elements, was constructed and tested …

A Machine Learning Approach For The Early Detection Of Bronchopulmonary Dysplasia (Bpd) In Preterm Infants Using Inter Hypoxemia Intervals, Ratri Mukherjee

Electrical Engineering Theses

Preterm birth is a significant global public health concern, affecting millions of babies yearly. Despite advancements in medical care that have improved the survival rates of preterm infants, preterm birth remains a leading cause of neonatal morbidity and mortality worldwide. It has both short-term and long-term health consequences that can profoundly impact the child's growth and development, as well as their family and society.

One of the challenges preterm infants face is their underdeveloped immune system, which makes them more vulnerable to infections and other health problems. Their delicate condition requires specialized care, often provided in a Neonatal Intensive Care …

Flux-Quanta Injection For Nonreciprocal Current Control In A Two-Dimensional Noncentrosymmetric Superconducting Structure, Serafim Teknowijoyo, Sara Chahid, Armen Gulian

Mathematics, Physics, and Computer Science Faculty Articles and Research

We designed and experimentally demonstrated a four-terminal superconducting device, a “quadristor,” that can function as a nonlatching (reversible) superconducting switch from the diode regime to the resistive state by application of a control current much smaller than the main transport current. The device uses a vortex-based superconducting-diode mechanism that is switched back and forth via the injection of flux quanta through auxiliary current leads. Our finding opens a new research area in the field of superconducting electronics.

A Natural Organic Artificial Synaptic Device Made From A Honey And Carbon Nanotube Admixture For Neuromorphic Computing, Md Mehedi Hasan Tanim, Zoe Templin, Kaleb Hood, Jun Jiao, Feng Zhao

Electrical and Computer Engineering Faculty Research & Creative Works

Artificial synaptic devices are the essential hardware component in emerging neuromorphic computing systems by mimicking biological synapse and brain functions. When made from natural organic materials such as protein and carbohydrate, they have potential to improve sustainability and reduce electronic waste by enabling environmentally friendly disposal. In this paper, a new natural organic memristor based artificial synaptic device is reported with the memristive film processed by a honey and carbon nanotube (CNT) admixture, that is, honey-CNT memristor. Optical microscopy, scanning electron microscopy, and micro-Raman spectroscopy are employed to analyze the morphology and chemical structure of the honey-CNT film. The device …

Ki-Cook: Clustering Multimodal Cooking Representations Through Knowledge-Infused Learning, Revathy Venkataramanan, Swati Padhee, Saini Rohan Rao, Ronak Kaoshik, Anirudh Sundara Rajan, Amit Sheth

Publications

Cross-modal recipe retrieval has gained prominence due to its ability to retrieve a text representation given an image representation and vice versa. Clustering these recipe representations based on similarity is essential to retrieve relevant information about unknown food images. Existing studies cluster similar recipe representations in the latent space based on class names. Due to inter-class similarity and intraclass variation, associating a recipe with a class name does not provide sufficient knowledge about recipes to determine similarity. However, recipe title, ingredients, and cooking actions provide detailed knowledge about recipes and are a better determinant of similar recipes. In this study, …

A Unified Switched Nonlinear Dynamic Model Of An Electric Vehicle For Performance Evaluation, Dibyendu Khan, Kuntal Mandal, Anjan Kumar Ray, Abdelali El Aroudi

Department of Electrical and Computer Engineering: Faculty Publications

The advanced modeling and estimation of overall system dynamics play a vital role in electric vehicles (EVs), as the selection of components in the powertrain and prediction of performance are the key market qualifiers. The state-space averaged model and small-signal transfer function model are useful for assessing long-term behavior in system-level analysis and for designing the controller parameters, respectively. Both models take less computation time but ignore the high-frequency switching dynamics. Therefore, these two models could be impractical for the development and testing of EV prototypes. On the other hand, the multi-domain model in available simulation tools gives in-depth information …

Nasa Weather Data Based Neural Network Grid Connected Pv System Maximum Power Point Tracking, Oluwatobiloba Mausi Johnson

Theses and Dissertations

Research and development for alternative energy sources that are cleaner, renewable, and have little to no environmental impact have been pushed by the ongoing rise in energy demand, the possibility of a decline in the use of conventional petroleum fuels, and concerns about environmental degradation. Electricity from photovoltaic (PV) systems is significantly better regarded among these alternative sources as a renewable energy source such as wind power, bioenergy, tidal energy, and hydroelectric with a wide application range because it is clean, accessible, and abundant with little to no environmental effect. However, solar energy usage is significantly impacted by the landscape, …

Is There A “Nationwide System” In Field Of Science And Technology In Japan?—Survey Of Semiconductor Technology, Huimin Li, Rongping Mu, Yue Hao

Bulletin of Chinese Academy of Sciences (Chinese Version)

Different scholars interpret the connotations and characteristics of the “Nationwide System” in quite different ways and fail to reach a consensus about whether some measures that Japan implements to tackle key problems are attributed to a “Nationwide System”. On this basis, the work started with the connotations and characteristics of the “Nationwide System” in the field of science and technology, conducted a case study of measures taken by Japan to tackle key technical problems in the semiconductor technology, and analyzed whether these measures embody relevant characteristics of the “Nationwide System” from an empirical perspective, so as to demonstrate whether there …

An Ai-Based Intervention For Improving Undergraduate Stem Learning, Mohammad Rashedul Hasan, Bilal Khan

Department of Electrical and Computer Engineering: Faculty Publications

We present results from a small-scale randomized controlled trial that evaluates the impact of just-in-time interventions on the academic outcomes of N = 65 undergraduate students in a STEM course. Intervention messaging content was based on machine learning forecasting models of data collected from 537 students in the same course over the preceding 3 years. Trial results show that the intervention produced a statistically significant increase in the proportion of students that achieved a passing grade. The outcomes point to the potential and promise of just-in-time interventions for STEM learning and the need for larger fully-powered randomized controlled trials.

An Enhanced Adaptive Learning System Based On Microservice Architecture, Abdelsalam Helmy Ibrahim, Mohamed Eliemy, Aliaa Abdelhalim Youssif

Future Computing and Informatics Journal

This study aims to enhance Adaptive Learning Systems (ALS) in Petroleum Sector in Egypt by using the Microservice Architecture and measure the impact of enhancing ALS by participating ALS users through a statistical study and questionnaire directed to them if they accept to apply the Cloud Computing Service “Microservices” to enhance the ALS performance, quality and cost value or not. The study also aims to confirm that there is a statistically significant relationship between ALS and Cloud Computing Service “Microservices” and prove the impact of enhancing the ALS by using Microservices in the cloud in Adaptive Learning in the Egyptian …

Visual Question Answering: A Survey, Gehad Assem El-Naggar

Future Computing and Informatics Journal

Visual Question Answering (VQA) has been an emerging field in computer vision and natural language processing that aims to enable machines to understand the content of images and answer natural language questions about them. Recently, there has been increasing interest in integrating Semantic Web technologies into VQA systems to enhance their performance and scalability. In this context, knowledge graphs, which represent structured knowledge in the form of entities and their relationships, have shown great potential in providing rich semantic information for VQA. This paper provides an abstract overview of the state-of-the-art research on VQA using Semantic Web technologies, including knowledge …

Systematic Characterization Of Power Side Channel Attacks For Residual And Added Vulnerabilities, Aurelien Tchoupou Mozipo

Dissertations and Theses

Power Side Channel Attacks have continued to be a major threat to cryptographic devices. Hence, it will be useful for designers of cryptographic systems to systematically identify which type of power Side Channel Attacks their designs remain vulnerable to after implementation. It’s also useful to determine which additional vulnerabilities they have exposed their devices to, after the implementation of a countermeasure or a feature. The goal of this research is to develop a characterization of power side channel attacks on different encryption algorithms' implementations to create metrics and methods to evaluate their residual vulnerabilities and added vulnerabilities. This research studies …

Field Studies Of Perc And Al-Bsf Pv Module Performance Loss Using Power And I-V Timeseries, Alan J. Curran, Xuanji Yu, Jiqi Liu, Laura S. Bruckman, Roger H. French

Faculty Scholarship

We have studied the degradation of both full-sized modules and minimodules with PERC and Al-BSF cell variations in fields while considering packaging strategies. We demonstrate the implementations of data-driven tools to analyze large numbers of modules and volumes of timeseries data to obtain the performance loss and degradation pathways. This data analysis pipeline enables quantitative comparison and ranking of module variations, as well as mapping and deeper understanding of degradation mechanisms. The best performing module is a half-cell PERC, which shows a performance loss rate (PLR) of −0.27 ± 0.12% per annum (%/a) after initial losses have stabilized. Minimodule studies …

Ecg Recordings As Predictors Of Very Early Autism Likelihood: A Machine Learning Approach, Deepa Tilwani, Jessica Bradshaw, Amit Sheth, Christian O'Reilly

Publications

In recent years, there has been a rise in the prevalence of autism spectrum disorder (ASD). The diagnosis of ASD requires behavioral observation and standardized testing completed by highly trained experts. Early intervention for ASD can begin as early as 1–2 years of age, but ASD diagnoses are not typically made until ages 2–5 years, thus delaying the start of intervention. There is an urgent need for non-invasive biomarkers to detect ASD in infancy. While previous research using physiological recordings has focused on brain-based biomarkers of ASD, this study investigated the potential of electrocardiogram (ECG) recordings as an ASD biomarker …