Open Access. Powered by Scholars. Published by Universities.®

Engineering Commons™

Open Access. Powered by Scholars. Published by Universities.®

Electrical and Computer Engineering

Institution
Keyword
Publication Year
Publication
Publication Type
File Type

Articles 3721 - 3750 of 36788

Full-Text Articles in Engineering

Deep Feature Extraction, Dimensionality Reduction, And Classification Of Medical Images Using Combined Deep Learning Architectures, Autoencoder, And Multiple Machine Learning Models, Ahmet Hi̇dayet Ki̇raz, Fatime Oumar Djibrillah, Mehmet Emi̇n Yüksel Oct 2023

Deep Feature Extraction, Dimensionality Reduction, And Classification Of Medical Images Using Combined Deep Learning Architectures, Autoencoder, And Multiple Machine Learning Models, Ahmet Hi̇dayet Ki̇raz, Fatime Oumar Djibrillah, Mehmet Emi̇n Yüksel

Turkish Journal of Electrical Engineering and Computer Sciences

Accurate analysis and classification of medical images are essential factors in clinical decision-making and patient care. A novel comparative approach for medical image classification is proposed in this study. This new approach involves several steps: deep feature extraction, which extracts the informative features from medical images; concatenation, which concatenates the extracted deep features to form a robust feature vector; dimensionality reduction with autoencoder, which reduces the dimensionality of the feature vector by transforming it into a different feature space with a lower dimension; and finally, these features obtained from all these steps were fed into multiple machine learning classifiers (SVM, …

Go to article

Feature Distillation From Vision-Language Model For Semisupervised Action Classification, Asli Çeli̇k, Ayhan Küçükmani̇sa, Oğuzhan Urhan Oct 2023

Feature Distillation From Vision-Language Model For Semisupervised Action Classification, Asli Çeli̇k, Ayhan Küçükmani̇sa, Oğuzhan Urhan

Turkish Journal of Electrical Engineering and Computer Sciences

The training of supervised machine learning approaches is critically dependent on annotating large-scale datasets. Semisupervised learning approaches aim to achieve compatible performance with supervised methods using relatively less annotation without sacrificing good generalization capacity. In line with this objective, ways of leveraging unlabeled data have been the subject of intense research. However, semisupervised video action recognition has received relatively less attention compared to image domain implementations. Existing semisupervised video action recognition methods trained from scratch rely heavily on augmentation techniques, complex architectures, and/or the use of other modalities while distillation-based methods use models that have only been trained for 2D …

Go to article

Cccd: Corner Detection And Curve Reconstruction For Improved 3d Surface Reconstruction From 2d Medical Images, Mriganka Sarmah, Arambam Neelima Oct 2023

Cccd: Corner Detection And Curve Reconstruction For Improved 3d Surface Reconstruction From 2d Medical Images, Mriganka Sarmah, Arambam Neelima

Turkish Journal of Electrical Engineering and Computer Sciences

The conventional approach to creating 3D surfaces from 2D medical images is the marching cube algorithm, but it often results in rough surfaces. On the other hand, B-spline curves and nonuniform rational B-splines (NURBSs) offer a smoother alternative for 3D surface reconstruction. However, NURBSs use control points (CTPs) to define the object shape and corners play an important role in defining the boundary shape as well. Thus, in order to fill the research gap in applying corner detection (CD) methods to generate the most favorable CTPs, in this paper corner points are identified to predict organ shape. However, CTPs must …

Go to article

Focal Modulation Network For Lung Segmentation In Chest X-Ray Images, Şaban Öztürk, Tolga Çukur Oct 2023

Focal Modulation Network For Lung Segmentation In Chest X-Ray Images, Şaban Öztürk, Tolga Çukur

Turkish Journal of Electrical Engineering and Computer Sciences

Segmentation of lung regions is of key importance for the automatic analysis of Chest X-Ray (CXR) images, which have a vital role in the detection of various pulmonary diseases. Precise identification of lung regions is the basic prerequisite for disease diagnosis and treatment planning. However, achieving precise lung segmentation poses significant challenges due to factors such as variations in anatomical shape and size, the presence of strong edges at the rib cage and clavicle, and overlapping anatomical structures resulting from diverse diseases. Although commonly considered as the de-facto standard in medical image segmentation, the convolutional UNet architecture and its variants …

Go to article

Infrared Imaging Segmentation Employing An Explainable Deep Neural Network, Xinfei Liao, Dan Wang, Zairan Li, Nilanjan Dey, Rs Simon, Fuqian Shi Oct 2023

Infrared Imaging Segmentation Employing An Explainable Deep Neural Network, Xinfei Liao, Dan Wang, Zairan Li, Nilanjan Dey, Rs Simon, Fuqian Shi

Turkish Journal of Electrical Engineering and Computer Sciences

Explainable AI (XAI) improved by a deep neural network (DNN) of a residual neural network (ResNet) and long short-term memory networks (LSTMs), termed XAIRL, is proposed for segmenting foot infrared imaging datasets. First, an infrared sensor imaging dataset is acquired by a foot infrared sensor imaging device and preprocessed. The infrared sensor image features are then defined and extracted with XAIRL being applied to segment the dataset. This paper compares and discusses our results with XAIRL. Evaluation indices are applied to perform various measurements for foot infrared image segmentation including accuracy, precision, recall, F1 score, intersection over union (IoU), Dice …

Go to article

Nitrogen Radiofrequency Plasma Treatment Of Graphene, Antoine Bident, Nathalie Caillault, Florence Delange, Christine Labrugere, Guillaume Aubert, Cyril Aymonier, Etienne Durand, Alain Demourgues, Yongfeng Lu, Jean-François Silvain Oct 2023

Nitrogen Radiofrequency Plasma Treatment Of Graphene, Antoine Bident, Nathalie Caillault, Florence Delange, Christine Labrugere, Guillaume Aubert, Cyril Aymonier, Etienne Durand, Alain Demourgues, Yongfeng Lu, Jean-François Silvain

Department of Electrical and Computer Engineering: Faculty Publications

The incorporation of nitrogen (N) atoms into a graphitic network such as graphene (Gr) remains a major challenge. However, even if the insertion mechanisms are not yet fully understood, it is certain that the modification of the electrical properties of Gr is possible according to the configuration adopted. Several simulations work, notably using DFT, have shown that the incorporation of N in Gr can induce an increase in the electrical conductivity and N acts as an electron donor; this increase is linked to the amount of N, the sp2/sp3 carbon configuration, and the nature of C-N bonding. …

Go to article

Self-Dual Systems For Backscattering Cancellation, Nasim Mohammadi Estrakhri Oct 2023

Self-Dual Systems For Backscattering Cancellation, Nasim Mohammadi Estrakhri

Engineering Faculty Articles and Research

Using carefully arranged electric and magnetic components, we have recently demonstrated that backscattering from otherwise arbitrarily shaped two- and three-dimensional structures can be fully eliminated. Here, first we investigate the possibility of creating self-dual microwave absorbers that may provide advantages compared to typical commercial magnetoelectric absorbers. Next, we demonstrate that the self-duality condition is not limited to homogenous structures and may be extended to effective material properties, opening the door to realistic implementation of these structures at microwave and optical frequencies.

Go to article

Enabling Intelligent Network Management Through Multi-Agent Systems: An Implementation Of Autonomous Network System, Petro Mushidi Tshakwanda Oct 2023

Enabling Intelligent Network Management Through Multi-Agent Systems: An Implementation Of Autonomous Network System, Petro Mushidi Tshakwanda

Electrical and Computer Engineering ETDs

This Ph.D. dissertation presents a pioneering Multi-Agent System (MAS) approach for intelligent network management, particularly suited for next-generation networks like 5G and 6G. The thesis is segmented into four critical parts. Firstly, it contrasts the benefits of agent-based design over traditional micro-service architectures. Secondly, it elaborates on the implementation of network service agents in Python Agent Development Environment (PADE), employing machine learning and deep learning algorithms for performance evaluation. Thirdly, a new scalable approach, Scalable and Efficient DevOps (SE-DO), is introduced to optimize agent performance in resource-constrained settings. Fourthly, the dissertation delves into Quality of Service (QoS) and Radio Resource …

Go to article

Precision Spraying Using Variable Time Delays And Vision-Based Velocity Estimation, Paolo Rommel Sanchez, Hong Zhang Oct 2023

Precision Spraying Using Variable Time Delays And Vision-Based Velocity Estimation, Paolo Rommel Sanchez, Hong Zhang

Henry M. Rowan College of Engineering Departmental Research

Traditionally, precision farm equipment often relies on real-time kinematics and global positioning systems (RTK-GPS) for accurate position and velocity estimates. This approach proved effective and widely adopted in developed regions where RTK-GPS satellite and base station availability and visibility are not limited. However, RTK-GPS signal can be limited in farm areas due to topographic and economic constraints. Thus, this study developed a precision sprayer that estimated the travel velocity locally by tracking the relative motion of plants using a deep-learning-based machine vision system. Sprayer valves were then controlled by variable time delay (VTD) queuing and dynamic filtering. The proposed velocity …

Go to article

Overview Of Hil Co-Simulation For Very Large Distribution Systems And Power Electronic Converters With A Dc Fast Charging Ev Benchmark Study On An Ieee Test Feeder, Rosemary E. Alden, Donovin D. Lewis, Dan M. Ionel Oct 2023

Overview Of Hil Co-Simulation For Very Large Distribution Systems And Power Electronic Converters With A Dc Fast Charging Ev Benchmark Study On An Ieee Test Feeder, Rosemary E. Alden, Donovin D. Lewis, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

Current development towards implementation of the future smart grid includes advanced controller and power hardware-in-the-loop (CHIL/PHIL) testing of new technology. The impact of new loads, distributed energy resources (DER) equipment, and controls spans two fields, both electric distribution power systems modeling, typically completed in the phasor domain, and electromagnetic transient (EMT) analysis across the frequency domain. The co-simulation of distribution power systems and power electronic converter controls is a growing field of research for improved design using real-time HIL capability. Within this paper, over fifty references are reviewed to summarize the current state of HIL technology, specifically with co-simulation in …

Go to article

The Role Of Feedback Within Scrum For Engineering Department Operations, Massood Towhidnejad, Omar Ochoa, James J. Pembridge, Radu Babiceanu Oct 2023

The Role Of Feedback Within Scrum For Engineering Department Operations, Massood Towhidnejad, Omar Ochoa, James J. Pembridge, Radu Babiceanu

Posters

The Scrum framework is built on the principles of inspection and adaptation. Feedback drives the inspection process, and the team adapts based on that feedback to optimize its performance and outcomes. Within engineering departments, Scrum requires departments to examine how and when feedback is obtained to ensure that the department is remaining agile. This poster illustrates the role of feedback within two Scrum teams, one focused on student success and the other focused on faculty rewards and incentives. The two cases emphasize the need for continuous introspection at team and department levels.

Go to article

Distribution System Optimal Operation Of Smart Homes With Battery And Equivalent Hvac Energy Storage For Virtual Power Plant Controls, Steven B. Poore, Rosemary E. Alden, Evan S. Jones, Dan M. Ionel Oct 2023

Distribution System Optimal Operation Of Smart Homes With Battery And Equivalent Hvac Energy Storage For Virtual Power Plant Controls, Steven B. Poore, Rosemary E. Alden, Evan S. Jones, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

Battery energy storage systems (BESS) that can be utilized for demand response (DR) and load shifting are limited in adoption by high capital cost. Large residential loads such as electric water heaters (EWH) and heating, ventilation and air-conditioning (HVAC) may be controlled using distributed energy resource management systems (DERMS) to perform functions like batteries, such as reducing cost and decreasing energy storage capacity requirements when implemented at the aggregate level. Increasing levels of renewable generation further incentivizes shifting loads in time through controls and energy storage to reduce curtailment and carbon footprint. This paper proposes techniques for the optimization and …

Go to article

On The Prediction Of The Mechanical Properties Of Limestone Calcined Clay Cement: A Random Forest Approach Tailored To Cement Chemistry, Taihao Han, Bryan K. Aylas-Paredes, Jie Huang, Ashutosh Goel, Narayanan Neithalath, Aditya Kumar Oct 2023

On The Prediction Of The Mechanical Properties Of Limestone Calcined Clay Cement: A Random Forest Approach Tailored To Cement Chemistry, Taihao Han, Bryan K. Aylas-Paredes, Jie Huang, Ashutosh Goel, Narayanan Neithalath, Aditya Kumar

Materials Science and Engineering Faculty Research & Creative Works

Limestone calcined clay cement (LC3) is a sustainable alternative to ordinary Portland cement, capable of reducing the binder's carbon footprint by 40% while satisfying all key performance metrics. The inherent compositional heterogeneity in select components of LC3, combined with their convoluted chemical interactions, poses challenges to conventional analytical models when predicting mechanical properties. Although some studies have employed machine learning (ML) to predict the mechanical properties of LC3, many have overlooked the pivotal role of feature selection. Proper feature selection not only refines and simplifies the structure of ML models but also enhances these models' prediction performance and interpretability. This …

Go to article

Computationally Efficient Design, Diagnosis, And Test Of Analog Integrated Circuit Analysis, Nisharg Shah Oct 2023

Computationally Efficient Design, Diagnosis, And Test Of Analog Integrated Circuit Analysis, Nisharg Shah

Computer Science and Engineering Theses and Dissertations

With the modern trend in chip functionalities and chip size, considerable advancement
has been made in EDA (Electronic Design Automation). EDA algorithms have become
irreplaceable in the semiconductor industry. We use adjoint sensitivity analysis and transient
simulations to render runtimes affordable and responses accurate.
This dissertation presents various advantages of adjoint sensitivity analysis to improve
the design cycle, provide better testing, and make more efficient the diagnosis of analog
circuits. Our motivation for all our applications has been to greatly reduce the computational
resources required while still providing the required result for design diagnosis and test.

Go to article

Hardware-In-The-Loop Reaction Wheel Testbed With Camera Vision, Abigail Romero, Harvey Perkins, Stephen Kwok-Choon Oct 2023

Hardware-In-The-Loop Reaction Wheel Testbed With Camera Vision, Abigail Romero, Harvey Perkins, Stephen Kwok-Choon

College of Engineering Summer Undergraduate Research Program

Reaction wheels are widely used in aerospace systems as a method of attitude control. This research was focused on the design, development, and testing of a hardware-in-the-loop reaction wheel testbed that can be used for research and teaching applications related to satellite navigation and control. This project successfully utilized commercial off-the-shelf components to develop a reaction wheel capable of controlling the orientation of a freely rotating platform, as well as tracking objects using computer vision.

Go to article

Spoken Language Processing And Modeling For Aviation Communications, Aaron Van De Brook Oct 2023

Spoken Language Processing And Modeling For Aviation Communications, Aaron Van De Brook

Doctoral Dissertations and Master's Theses

With recent advances in machine learning and deep learning technologies and the creation of larger aviation-specific corpora, applying natural language processing technologies, especially those based on transformer neural networks, to aviation communications is becoming increasingly feasible. Previous work has focused on machine learning applications to natural language processing, such as N-grams and word lattices. This thesis experiments with a process for pretraining transformer-based language models on aviation English corpora and compare the effectiveness and performance of language models transfer learned from pretrained checkpoints and those trained from their base weight initializations (trained from scratch). The results suggest that transformer language …

Go to article

Modeling And Compensating Of Noise In Time-Of-Flight Sensors, Bryan Rodriguez Oct 2023

Modeling And Compensating Of Noise In Time-Of-Flight Sensors, Bryan Rodriguez

Electrical Engineering Theses and Dissertations

Three-dimensional (3D) sensors provide the ability to perform contactless measurements of objects and distances that are within their field of view. Unlike traditional two-dimensional (2D) cameras, which only provide RGB data about objects within a scene, 3D sensors are able to directly provide depth information for objects within a scene. Of these 3D sensing technologies, Time-of-Flight (ToF) sensors are becoming more compact which allows them to be more easily integrated with other devices and to find use in more applications. ToF sensors also provide several benefits over other 3D sensing technologies that increase the types of applications where ToF sensors …

Go to article

Simulation-Based Optimization Of A Dc Microgrid: With Machine-Learning-Based Models And Hybrid Meta-Heuristic Algorithms, Tyler Van Deese Oct 2023

Simulation-Based Optimization Of A Dc Microgrid: With Machine-Learning-Based Models And Hybrid Meta-Heuristic Algorithms, Tyler Van Deese

Theses and Dissertations

The field of economic dispatch (ED) focuses on optimizing power flow in a power system to minimize costs. It has the potential to significantly enhance system effectiveness, and efficiency, and reduce operating costs. Various techniques have been employed to tackle this problem, each with its own strengths and weaknesses. One promising approach is simulation-based optimization (SBO), which allows for accurate modeling of system interactions and improved representation of expected results. However, SBO requires running numerous simulations to identify an optimal solution, and there is a possibility of not achieving the global optimum. This work aims to address these challenges using …

Go to article

Conservative Estimation Of Inertial Sensor Errors Using Allan Variance Data, Kyle A. Lethander, Clark N. Taylor Oct 2023

Conservative Estimation Of Inertial Sensor Errors Using Allan Variance Data, Kyle A. Lethander, Clark N. Taylor

Faculty Publications

To understand the error sources present in inertial sensors, both the white (time-invariant) and correlated noise sources must be properly characterized. To understand both sources, the standard approach (IEEE standards 647-2006, 952-2020) is to compute the Allan variance of the noise and then use human-based interpretation of linear trends to estimate the separate noise sources present in a sensor. Recent work has sought to overcome the graphical nature and visual-inspection basis of this approach leading to more accurate noise estimates. However, when using noise characterization in a filter, it is important that the noise estimates be not only accurate but …

Go to article

Robustness Of Convolutional Neural Networks: Analysis And Applications, Xin Zhang Oct 2023

Robustness Of Convolutional Neural Networks: Analysis And Applications, Xin Zhang

Theses and Dissertations

Convolutional neural networks (CNNs) have gained increasing popularity and versatility in recent decades, finding applications in diverse domains including image recognition, natural language processing, recommendation systems, as well as safety-critical areas like autonomous driving, medical diagnostics, and military fields. However, the widespread use of CNNs in safety-critical applications has also given rise to concerns regarding their robustness. The low robustness of CNNs may lead to erroneous predictions and even significant losses of human life and property, especially when dealing with corner cases or boundary cases in real-world problem-solving. Most existing methods for evaluating CNNs still heavily rely on their accuracy …

Go to article

Creating An Automatic Lowering Function For Quarter-Scale Tractor Pulling Sled, Sam Wilkins Oct 2023

Creating An Automatic Lowering Function For Quarter-Scale Tractor Pulling Sled, Sam Wilkins

Honors Program: Senior Projects (Public)

As the agricultural industry works to continuously integrate innovative technology and improve production efficiency, improved on-board data acquisition and transmission will be necessary for all agricultural machines. To make this a reality, the utilization of controller area network (CAN) technology will be crucial. Therefore, it is important for all agricultural engineers to have foundational knowledge of CAN bus systems and the standards that govern their use in industry. The UNL quarter-scale tractor team regularly utilizes CAN buses on their tractors and testing equipment. One such testing machine is the team’s pulling sled, which uses CAN messages to transport important information …

Go to article

Robust Deep Learning Models For Multi-Label Image Classification In Limited And Free Annotation Scenarios, Rabab Ezzeldin Rabie Abdelfattah Oct 2023

Robust Deep Learning Models For Multi-Label Image Classification In Limited And Free Annotation Scenarios, Rabab Ezzeldin Rabie Abdelfattah

Theses and Dissertations

This proposal introduces various methods for tackling the challenge of multi-label image classification in different scenarios, including partial labels and free-annotation settings. Multi-label image classification is typically formulated as a partial-label learning problem because it can be expensive to annotate all labels in every training image. Existing partial-label learning approaches typically focus on annotating each training image with only a subset of its labels, including a special case of annotating only one positive label per image. To further alleviate the annotation burden and improve classifier performance, this proposal introduces a new partial-label setting where only a subset of training images …

Go to article

Novel Approach To In-Situ Mocvd Oxide/Dielectric Deposition For Iii-Nitride-Based Heterojunction Field Effect Transistors, Samiul Hasan Oct 2023

Novel Approach To In-Situ Mocvd Oxide/Dielectric Deposition For Iii-Nitride-Based Heterojunction Field Effect Transistors, Samiul Hasan

Theses and Dissertations

III-Nitride-based compound semiconductors have unique properties such as high bandgap and high breakdown field, which make them attractive for a variety of applications, including high-power and high-frequency electronics and optoelectronics. The most common types of III-Nitride-based field effect transistors (FETs) are aluminum gallium nitride (AlGaN)/gallium nitride (GaN) based, which suffer from some inherent problems such as virtual gate effect, current collapse, gate leakage, etc. The solution to this problem can be the inclusion of a dielectric passivation layer under the gate. However, the addition of the dielectric layer impacts one of the most critical device-controlling parameters, “threshold voltage”, which suffers …

Go to article

Probabilistic Cable Aging Diagnosis And Prognosis With Reflectometry And Capacitance Methods, Xuan Wang Oct 2023

Probabilistic Cable Aging Diagnosis And Prognosis With Reflectometry And Capacitance Methods, Xuan Wang

Theses and Dissertations

Safe and reliable operation of power plants and power transmission are critical to economy and society. Cables in power generation and transmission are subject to various thermal, chemical, and mechanical stresses, which generally lead to aging and degradation of cable insulation. It is reported that some cables with a projected lifetime of 40 years need to be replaced in 10-15 years. Poorly maintained aged cables can adversely affect power delivery and lead to catastrophic events, such as blackout, fires, and loss of lives. The current research on cable is mainly focused on the detection and localization of hard faults, which …

Go to article

Design And Fabrication Of High-Resolution Epitaxial 4h-Sic Metal Insulator Semiconductor Detectors, Omerfaruk Karadavut Oct 2023

Design And Fabrication Of High-Resolution Epitaxial 4h-Sic Metal Insulator Semiconductor Detectors, Omerfaruk Karadavut

Theses and Dissertations

In the last two decades, significant strides have been made in the epitaxial film growth of 4H-silicon carbide (4H-SiC), establishing it as a premier wide bandgap material for radiation detection application under harsh environments. This is primarily attributed to its unique combination of physical properties such as high thermal conductivity, wide bandgap, robust breakdown field, and radiation hardness. Metal/4H-SiC epitaxial layer Schottky barrier diodes (SBDs) have emerged as reliable radiation detectors for harsh environments. However, the utilization of thicker epitaxial layer devices encounters challenges due to the minimum achievable doping concentration in 4H-SiC epitaxial layers, necessitating higher bias voltages for …

Go to article

Circularly-Shifted Chirps For Triple Functionality: Communications, Radar, And Computation, Safi Shams Muhtasimul Hoque Oct 2023

Circularly-Shifted Chirps For Triple Functionality: Communications, Radar, And Computation, Safi Shams Muhtasimul Hoque

Theses and Dissertations

This dissertation presents circularly-shifted chirps (CSCs), synthesized within orthogonal frequency domain multiplexing (OFDM) framework, as a novel solution for integrating radar, communication, and computation functionalities to a wireless network. Firstly, {index modulation (IM)} with circularly-shifted chirps (CSCs) (CSC-IM) for dual-function radar and communication (DFRC) system is discussed. The proposed scheme encodes the information bits with the CSC indices and the phase-shift keying (PSK) symbols. It allows the receiver to exploit the frequency selectivity naturally in fading channels by combining IM and wideband CSCs. It also leverages the fact that a CSC is a constant-envelope signal to achieve a controllable peak-to-mean …

Go to article

Study Of All-Group-Iv Sigesn Mid-Ir Lasers With Dual Wavelength Emission, Grey Abernathy, Solomon Ojo, Abdulla Said, Joshua M. Grant, Yiyin Zhou, Hryhorii Stanchu, Wei Du, Baohua Li, Shui-Qing Yu Oct 2023

Study Of All-Group-Iv Sigesn Mid-Ir Lasers With Dual Wavelength Emission, Grey Abernathy, Solomon Ojo, Abdulla Said, Joshua M. Grant, Yiyin Zhou, Hryhorii Stanchu, Wei Du, Baohua Li, Shui-Qing Yu

Electrical Engineering Faculty Publications and Presentations

Direct band gap GeSn alloys have recently emerged as promising lasing source materials for monolithic integration on Si substrate. In this work, optically pumped mid-infrared GeSn lasers were studied with the observation of dual-wavelength lasing at 2187 nm and 2460 nm. Two simultaneous lasing regions include a GeSn buffer layer (bulk) and a SiGeSn/GeSn multiple quantum well structure that were grown seamlessly using a chemical vapor deposition reactor. The onset of dual lasing occurs at 420 kW/cm2. The wider bandgap SiGeSn partitioning barrier enables the independent operation of two gain regions. While the better performance device in terms …

Go to article

Fabrication Of Smooth Sac305 Thin Films Via Magnetron Sputtering And Evaluations Of Microstructure, Creep, And Electrical Resistivity, Manish Ojha Oct 2023

Fabrication Of Smooth Sac305 Thin Films Via Magnetron Sputtering And Evaluations Of Microstructure, Creep, And Electrical Resistivity, Manish Ojha

Mechanical & Aerospace Engineering Theses & Dissertations

SAC305 (96.5%Sn-3%Ag-0.5%Cu) is the leading alternative to the traditional Sn-Pb solder eutectic alloy owing to its low melting temperature, better compatibility with other components, and excellent mechanical/structural properties. In the realm of modern electronics, where devices are increasingly miniaturized, the design and characterization of thin solder joints become paramount. The orientation and size of the grains within the solder can influence its ability to withstand mechanical stresses. However, research on SAC thin films remains sparse, and these films present unique challenges and characteristics compared to their bulk counterparts, influenced by factors like interfaces, stresses, thickness, microstructure, and the nature of …

Go to article

Optics Studies For Multipass Energy Recovery At Cebaf: Er@Cebaf, Isurumali Neththikumara Oct 2023

Optics Studies For Multipass Energy Recovery At Cebaf: Er@Cebaf, Isurumali Neththikumara

Physics Theses & Dissertations

Energy recovery linacs (ERLs), focus on recycling the kinetic energy of electron beam for the purpose of accelerating a newly injected beam within the same accelerating structure. The rising developments in the super conducting radio frequency technology, ERL technology has achieved several noteworthy milestones over the past few decades. In year 2003, Jefferson Lab has successfully demonstrated a single pass energy recovery at the CEBAF accelerator. Furthermore, they conducted successful experiments with IR-FEL demo and upgrades, as well as the UV FEL driver. This multi-pass, multi-GeV range energy recovery demonstration proposed to be carried out at CEBAF accelerator at Jefferson …

Go to article

Framework For Implementing Advanced Radar Plotting Aid Capability For Small Maritime Vessels, Jason Stark Harris Oct 2023

Framework For Implementing Advanced Radar Plotting Aid Capability For Small Maritime Vessels, Jason Stark Harris

Electrical & Computer Engineering Theses & Dissertations

Every year in the United States many people are killed or injured when maritime vessels collide with other vessels or fixed objects. According to the United States Coast Guard, the top contributing factors to these collisions are operator inattention, operator inexperience and an improper lookout. Larger commercial vessels are required to have RADAR systems which support Automatic RADAR Plotting Aid (ARPA) which can automatically detect collisions and alert an operator to change course. These systems can be very expensive which put them out of reach of the average recreational boater. It is however possible to implement a low cost ARPA …

Go to article

First Prev Next Last