Open Access. Powered by Scholars. Published by Universities.®
- Institution
-
- Missouri University of Science and Technology (1607)
- TÜBİTAK (1233)
- California Polytechnic State University, San Luis Obispo (973)
- Air Force Institute of Technology (799)
- New Jersey Institute of Technology (589)
-
- Old Dominion University (502)
- University of Central Florida (443)
- University of Nebraska - Lincoln (408)
- Technological University Dublin (380)
- Portland State University (370)
- Brigham Young University (363)
- University of Kentucky (298)
- University of Arkansas, Fayetteville (271)
- Utah State University (266)
- Clemson University (205)
- Embry-Riddle Aeronautical University (205)
- Purdue University (205)
- Louisiana State University (202)
- University of New Mexico (200)
- Marquette University (195)
- Wright State University (183)
- Michigan Technological University (181)
- University of South Carolina (176)
- Cleveland State University (175)
- Florida Institute of Technology (169)
- University of Nevada, Las Vegas (155)
- University of Texas at El Paso (150)
- Boise State University (147)
- Tashkent State Technical University (131)
- University of Texas at Arlington (125)
- Keyword
-
- Machine learning (233)
- Deep learning (168)
- Department of Electrical Engineering (157)
- Machine Learning (125)
- FPGA (124)
-
- Image processing (121)
- Optimization (114)
- Applied sciences (109)
- #antcenter (107)
- Classification (107)
- Electrical Engineering (101)
- Computer vision (93)
- Signal processing (80)
- Simulation (79)
- Neural networks (76)
- Electrical and Computer Engineering (75)
- Deep Learning (74)
- Daniel Felix Ritchie School of Engineering and Computer Science (73)
- Reliability (70)
- Security (68)
- Power Electronics (66)
- Robotics (66)
- Radar (64)
- Control (63)
- UAV (63)
- Engineering (62)
- Algorithms (59)
- Remote sensing (59)
- Modeling (58)
- Artificial intelligence (56)
- Publication Year
- Publication
-
- Theses and Dissertations (1329)
- Turkish Journal of Electrical Engineering and Computer Sciences (1233)
- Electrical and Computer Engineering Faculty Research & Creative Works (1018)
- Electrical Engineering (601)
- Electronic Theses and Dissertations (593)
-
- Theses (511)
- Masters Theses (406)
- Electrical and Computer Engineering Faculty Publications and Presentations (306)
- Electrical and Computer Engineering Faculty Publications (305)
- Master's Theses (286)
- Electrical & Computer Engineering Theses & Dissertations (257)
- Faculty Publications (235)
- Department of Electrical and Computer Engineering: Faculty Publications (234)
- Dissertations (219)
- Graduate Theses and Dissertations (186)
- Electrical and Computer Engineering ETDs (178)
- Browse all Theses and Dissertations (176)
- Dissertations and Theses (161)
- Articles (157)
- Open Access Theses & Dissertations (150)
- Doctoral Dissertations (149)
- All Graduate Theses and Dissertations, Spring 1920 to Summer 2023 (144)
- Conference papers (144)
- Electrical and Computer Engineering Faculty Research and Publications (142)
- Theses and Dissertations--Electrical and Computer Engineering (131)
- Electrical & Computer Engineering Faculty Publications (122)
- All Theses (118)
- USF Tampa Graduate Theses and Dissertations (117)
- Electrical Engineering and Computer Science Faculty Publications (115)
- LSU Master's Theses (110)
- Publication Type
- File Type
Articles 1561 - 1590 of 14334
Full-Text Articles in Entire DC Network
Project Thetis: A Low-Cost, Low-Profile Inertial Data Logger, Braidan Duffy
Project Thetis: A Low-Cost, Low-Profile Inertial Data Logger, Braidan Duffy
Theses and Dissertations
This thesis details the design, testing, calibration, and verification of a nine degree of freedom inertial measurement data logger for use with floating bodies. The instrument was conceived to address limitations of equipment used in classes within the Ocean Engineering department at Florida Institute of Technology. By meeting with several stakeholders and end users, a series of stakeholder requirements, capabilities, and component-level requirements were de- veloped that informed the design constraints. There were several hardware iterations of the board, culminating in Revision F5 which was extensively tested and proven. The design was inspected after testing concluded to determine which capabilities …
Ism-Band Energy Harvesting Wireless Sensor Node, Fnu Naveed
Ism-Band Energy Harvesting Wireless Sensor Node, Fnu Naveed
Graduate Theses and Dissertations
In recent years, the interest in remote wireless sensor networks has grown significantly, particularly with the rapid advancements in Internet of Things (IoT) technology. These networks find diverse applications, from inventory tracking to environmental monitoring. In remote areas where grid access is unavailable, wireless sensors are commonly powered by batteries, which imposes a constraint on their lifespan. However, with the emergence of wireless energy harvesting technologies, there is a transformative potential in addressing the power challenges faced by these sensors. By harnessing energy from the surrounding environment, such as solar, thermal, vibrational, or RF sources, these sensors can potentially operate …
Characterization Of Highly Doped N-Type And P-Type Silicon Carbide Ohmic Contacts, Tanner Rice
Characterization Of Highly Doped N-Type And P-Type Silicon Carbide Ohmic Contacts, Tanner Rice
Graduate Theses and Dissertations
Silicon Carbide (SiC) is a rather new material that possesses unparalleled properties when compared to Silicon. Due to its larger band gap alongside other thermal properties, SiC can survive in hotter, more radiation intensive environments, whether that be within the crust of the earth or in the reaches of space. As a desirable semiconductor for these applications, CMOS is an especially important device due to its low power consumption. However, creating a good contact between the metal and semiconductor optimally requires two different metals for the n -type and the p-type semiconductor. This greatly increases the processing time, as separate …
Enhanced Privacy-Enabled Face Recognition Using Κ-Identity Optimization, Ryan Karl
Enhanced Privacy-Enabled Face Recognition Using Κ-Identity Optimization, Ryan Karl
Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research
Facial recognition is becoming more and more prevalent in the daily lives of the common person. Law enforcement utilizes facial recognition to find and track suspects. The newest smartphones have the ability to unlock using the user's face. Some door locks utilize facial recognition to allow correct users to enter restricted spaces. The list of applications that use facial recognition will only increase as hardware becomes more cost-effective and more computationally powerful. As this technology becomes more prevalent in our lives, it is important to understand and protect the data provided to these companies. Any data transmitted should be encrypted …
An Investigation Of Match For Lossless Video Compression, Brittany Sullivan-Reicks
An Investigation Of Match For Lossless Video Compression, Brittany Sullivan-Reicks
Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research
A new lossless video compression technique, Match, is investigated. Match uses the similarity between the frames of a video or the slices of medical images to find a prediction for the current pixel. A portion of the previous frame is searched to find a matching context, which is the pixels surrounding the current pixel, within some distance centered on the current location. The best distance to use for each dataset is found experimentally. The matching context refers to the neighborhood of w, nw, n, and ne, where the pixel in the previous frame with the closest matching context becomes the …
Low-Power, Event-Driven System On A Chip For Charge Pulse Processing Applications, Joseph A. Schmitz
Low-Power, Event-Driven System On A Chip For Charge Pulse Processing Applications, Joseph A. Schmitz
Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research
This dissertation presents an electronic architecture and methodology capable of processing charge pulses generated by a range of sensors, including radiation detectors and tactile synthetic skin. These sensors output a charge signal proportional to the input stimulus, which is processed electronically in both the analog and digital domains. The presented work implements this functionality using an event-driven methodology, which greatly reduces power consumption compared to standard implementations. This enables new application areas that require a long operating time or compact physical dimensions, which would not otherwise be possible. The architecture is designed, fabricated, and tested in the aforementioned applications to …
Ai Assisted Workflows For Computational Electromagnetics And Antenna Design, Oameed Noakoasteen
Ai Assisted Workflows For Computational Electromagnetics And Antenna Design, Oameed Noakoasteen
Electrical and Computer Engineering ETDs
These days large volumes of data can be recorded and manipulated with relative ease. If valuable information can be extracted from them, these vast amounts of data can be a rich resource not just for the digital economy but also for scientific discovery and development of technology. When it comes to deriving valuable information from data, Machine Learning (ML) emerges as the key solution. To unlock the potential benefits of ML to science and technology, extensive research is needed to explore what algorithms are suitable and how they can be applied.
To shine light on various ways that ML can …
A Practical Low-Dimensional Feature Vector Generation Method Based On Wavelet Transform For Psychophysiological Signals, Erdem Erkan, Yasemi̇n Erkan
A Practical Low-Dimensional Feature Vector Generation Method Based On Wavelet Transform For Psychophysiological Signals, Erdem Erkan, Yasemi̇n Erkan
Turkish Journal of Electrical Engineering and Computer Sciences
High-dimensional feature vectors entail computational cost and computational complexity. However, a successful classification can be obtained with an optimally sized feature vector consisting of distinctive features. With the widespread use of the internet and mobile devices, the need for systems with low computational costs is increasing day by day. In this study, starting from the idea that each motor imagery is represented as a subject-specific pattern in the brain, we propose a new and practical method that can generate a low-dimensional feature vector based on wavelet transform. The feature vector is obtained from the correlation between each trial and each …
Lsav: Lightweight Source Address Validation In Sdn To Counteract Ip Spoofing-Based Ddos Attacks, Ali̇ Karakoç, Fati̇h Alagöz
Lsav: Lightweight Source Address Validation In Sdn To Counteract Ip Spoofing-Based Ddos Attacks, Ali̇ Karakoç, Fati̇h Alagöz
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, we propose a design to detect and prevent IP spoofing-based distributed denial of service (DDoS) attacks on software-defined networks (SDNs). DDoS attacks are still one of the significant problems for internet service providers (ISPs) and individual users. These attacks can disrupt customer services by targeting the availability of the system, and in some cases, they can completely shut down the target infrastructure. Protecting the system against DDoS attacks is therefore crucial for ensuring the reliability and availability of internet services. To address this problem, we propose a lightweight source address validation (LSAV) framework that leverages the flexibility …
Exploring The Impact Of Training Datasets On Turkish Stance Detection, Muhammed Sai̇d Zengi̇n, Berk Utku Yeni̇sey, Mücahi̇d Kutlu
Exploring The Impact Of Training Datasets On Turkish Stance Detection, Muhammed Sai̇d Zengi̇n, Berk Utku Yeni̇sey, Mücahi̇d Kutlu
Turkish Journal of Electrical Engineering and Computer Sciences
Stance detection has garnered considerable attention from researchers due to its broad range of applications, including fact-checking and social computing. While state-of-the-art stance detection models are usually based on supervised machine learning methods, their effectiveness is heavily reliant on the quality of training data. This problem is more prevalent in stance detection task because the stance of a text is intimately tied to the target under consideration. While numerous datasets exist for stance detection, determining their suitability for a specific target can be challenging. In this work, we focus on Turkish stance detection and explore the impact of training data …
A Comparative Study Of Blind Source Separation Methods, Burak Baysal, Mehmet Önder Efe
A Comparative Study Of Blind Source Separation Methods, Burak Baysal, Mehmet Önder Efe
Turkish Journal of Electrical Engineering and Computer Sciences
Blind source separation is a popular research topic used for decomposing mixed signals, particularly in the field of music. In addition to exploring machine learning-based approaches, this study aims to examine the performance of classical algorithms in separating audio signal sources. The evaluation of different genres is a significant aspect of this study as the performance of the methods may vary across various musical genres and different audio components. This consideration provides a novel perspective and contributes to a comprehensive analysis of the algorithms. Using the MusDB-HQ dataset, we conducted experimental studies comparing classical algorithms, including FastICA, NMF, and DUET, …
New Modified Carrier-Based Level-Shifted Pwm Control For Npc Rectifiers Considered For Implementation In Ev Fast Chargers, Merve Mollahasanoğlu, Hakki Mollahasanoğlu, Hali̇l İbrahi̇m Okumuş
New Modified Carrier-Based Level-Shifted Pwm Control For Npc Rectifiers Considered For Implementation In Ev Fast Chargers, Merve Mollahasanoğlu, Hakki Mollahasanoğlu, Hali̇l İbrahi̇m Okumuş
Turkish Journal of Electrical Engineering and Computer Sciences
In this study, the aim is to evaluate three-phase (3?) AC/DC neutral point-clamped (NPC) power factor corrected (PFC) multilevel converter performance for electric vehicle (EV) fast chargers. Power factor correction for EV fast chargers is very important in terms of efficient power usage and charger compatibility with the grid. Multilevel converters improve charging efficiency, reduce voltage stresses on components, minimize electromagnetic interference, and support high power capabilities. For this reason, multilevel converters with the PFC feature contribute to the reliable and effective operation of the fast-charging infrastructure. Rectifier analysis is tested with extensive simulations using a new modified carrier-based level-shifted …
A Novel Computing Scheme Based On Pattern Matching For Identification Of Nephron Loss And Chronic Kidney Disease Stage, Rehan Ahmad, Basant Mohanty
A Novel Computing Scheme Based On Pattern Matching For Identification Of Nephron Loss And Chronic Kidney Disease Stage, Rehan Ahmad, Basant Mohanty
Turkish Journal of Electrical Engineering and Computer Sciences
Nephrons are the basic filtering units of the kidneys. Progression of chronic kidney disease (CKD) destroys nephrons permanently. Although there are many computing schemes suggested in recent years to identify CKD stages, no computing method has been suggested for identifying the nephron loss within kidney regions during CKD progression. In this paper, a novel pattern matching-based computation scheme is proposed to detect nephron loss in the kidney regions during CKD progression. We consider image registration (IR) with different transforms and a structural similarity index algorithm (SSIM) to match patterns of ultrasound images of kidney regions to identify the nephron loss. …
Fuzzycsampling: A Hybrid Fuzzy C-Means Clustering Sampling Strategy For Imbalanced Datasets, Abdullah Maraş, Çi̇ğdem Erol
Fuzzycsampling: A Hybrid Fuzzy C-Means Clustering Sampling Strategy For Imbalanced Datasets, Abdullah Maraş, Çi̇ğdem Erol
Turkish Journal of Electrical Engineering and Computer Sciences
Classification model with imbalanced datasets is recently one of the most researched areas in machine learning applications since they induce to the emergence of low-performing machine learning models. The imbalanced datasets occur if target variables have an uneven number of examples in a dataset. The most prevalent solutions to imbalanced datasets can be categorized as data preprocessing, ensemble techniques, and cost-sensitive learning. In this article, we propose a new hybrid approach for binary classification, named FuzzyCSampling, which aims to increase model performance by ensembling fuzzy c-means clustering and data sampling solutions. This article compares the proposed approaches' results not only …
Towards A Virtual Reality Visualization Of Hand-Object Interactions To Support Remote Physical Therapy, Trudi Di Qi, Louanne Boyd, Scott Fitzpatrick, Meghna Raswan, Franceli L. Cibrian
Towards A Virtual Reality Visualization Of Hand-Object Interactions To Support Remote Physical Therapy, Trudi Di Qi, Louanne Boyd, Scott Fitzpatrick, Meghna Raswan, Franceli L. Cibrian
Engineering Faculty Articles and Research
Improving object manipulation skills through hand-object interaction exercises is crucial for rehabilitation. Despite limited healthcare resources, physical therapists propose remote exercise routines followed up by remote monitoring. However, remote motor skills assessment remains challenging due to the lack of effective motion visualizations. Therefore, exploring innovative ways of visualization is crucial, and virtual reality (VR) has shown the potential to address this limitation. However, it is unclear how VR visualization can represent understandable hand-object interactions. To address this gap, in this paper, we present VRMoVi, a VR visualization system that incorporates multiple levels of 3D visualization layers to depict movements. In …
Resonance Damping Of Lcl Filters Using Capacitor-Current Proportional-Integral Positive Feedback Method For Grid-Integrated Fuel Cell System, Majid Hosseinpour, Amin Kholousi
Resonance Damping Of Lcl Filters Using Capacitor-Current Proportional-Integral Positive Feedback Method For Grid-Integrated Fuel Cell System, Majid Hosseinpour, Amin Kholousi
Emirates Journal for Engineering Research
Nowadays, the use of grid-integrated inverter proton exchange membrane fuel cell (PEMFC) systems is becoming more prevalent due to their efficiency and favorable environmental effects. Switching the grid-connected inverters causes high-frequency harmonics, which are eliminated using LCL filters. These filters are susceptible to instability when their resonant frequency is affected by changes in network impedance. Active damping methods are used to weaken the resonance of LCL filters. However, the grid-connected inverter is prone to be unstable under grid impedance variations due to the negative equivalent resistance resulting by digital control delays. As a solution to this problem, the capacitor-current proportional-integral …
Multi-Model Digital Twins With Ai Forecasting For Seed To Stand Supply Chain, Rania Sherif Elashmawy
Multi-Model Digital Twins With Ai Forecasting For Seed To Stand Supply Chain, Rania Sherif Elashmawy
USF Tampa Graduate Theses and Dissertations
The present dissertation embodies a multi-faceted investigation aimed at enhancing strawberry production pre-harvest and post-harvest quality through data-driven approaches. It unfolds multi-stages framework.
The first stage presents a complete data collection and its preliminary statistical analysis obtained from the first phase of a large-scale soil study on how to improve strawberry production and achieve sustainable and high-quality harvests through sensor-assisted real-time field monitoring. Six real-time loggers were placed in an operational commercial strawberry farm in Central Florida for the entirety of a harvest season from soil preparation to planting to harvesting. Along with high-resolution soil sensory measurements including water content, …
A Moving Target Architecture As A Side-Channel Countermeasure, Rachel M. Cazzola
A Moving Target Architecture As A Side-Channel Countermeasure, Rachel M. Cazzola
Electrical and Computer Engineering ETDs
We investigate a novel side-channel attack countermeasure called Side-channel Power analysis Resistance for Encryption Algorithms using Dynamic partial reconfiguration (SPREAD). The countermeasure leverages a strategy that is best characterized as a moving target architecture. Modern field-programmable gate array (FPGA) architectures provide support for dynamic partial reconfiguration (DPR), a feature that allows real-time reconfiguration of portions of the programmable logic (PL) while the FPGA continues to carry out computing tasks. Using the Advanced Encryption Standard (AES), the proposed moving target architecture leverages DPR to change the implementation characteristics of the substitution boxes (SBOX) in real time. We present experimental hardware results …
Study Of Si-Gan Photoconductive Switches Operating Modes Using Near-Ir Radiation, Nicolas Eduardo Gonzalez Padilla
Study Of Si-Gan Photoconductive Switches Operating Modes Using Near-Ir Radiation, Nicolas Eduardo Gonzalez Padilla
Electrical and Computer Engineering ETDs
One of the most promising solid-state devices for fast switching and radio frequency generation applications is the photoconductive switch (PCSS). These devices have been thoroughly explored since the late 1980s and exhibit remarkable switching properties in gallium arsenide (GaAs). With recent advances in wide bandgap (WBG) semiconductor manufacturing processes, there has been an increasing interest in using WBG semiconductors to implement PCSS. WBG semiconductors could exhibit the same switching characteristics as GaAs while overcoming their poor power management and short lifetime under pulsed power conditions, making PCSS a reliable option in high-power applications. Gallium Nitride (GaN) has emerged as one …
Design, Optimization, And Hardware Deployment Of A Deep Learning Model For Gps Spoofing Detection Using Gnss Satellite Receiver Protocol Data, Clarizza Morales Chacon
Design, Optimization, And Hardware Deployment Of A Deep Learning Model For Gps Spoofing Detection Using Gnss Satellite Receiver Protocol Data, Clarizza Morales Chacon
Electrical and Computer Engineering ETDs
The contemporary GPS infrastructure plays a vital role in advancing Position, Navigation, and Timing (PNT) applications across various sectors, including transportation, commerce, finance, and aviation. To provide a robust and authenticated infrastructure for users, it is important to develop a methodology for verifying the authenticity of satellite navigation signals, especially in civilian applications using the C/A code. This thesis explores Machine Learning (ML) techniques, focusing on the analysis of Global Navigation Satellite System (GNSS) protocol messages like UBX and NMEA to detect anomalies in receiver and satellite behavior, indicative of potential spoofing. The research demonstrates the deployment of Machine Learning …
The Automated Wheelchair, Jonathan Doksa Kamba Ngoyi
The Automated Wheelchair, Jonathan Doksa Kamba Ngoyi
Honors College Theses
Automation refers to the use of technology to execute tasks through programmed instructions and automated control mechanisms to ensure accurate execution. This minimizes human involvement and encompasses various fields, including business process automation. A notable form of automation is assistive technology, which refers to any device or software that enhances individuals' learning, communication, or overall functionality. This can range from advanced tools like computers to simpler aids like walking sticks. Assistive technology aims to promote inclusivity and participation, particularly among individuals with disabilities, the elderly, and those with non-communicable diseases.
The Automated Airport Wheelchair is a culmination of prior projects …
Comparative Evaluation Of Investigation Methods For Estimating The Load-Dependent State Of Charge And End Of Discharge Of A Multirotor Uav Battery, Hanna Dibbern, Morten Roßberg, Claudia Werner
Comparative Evaluation Of Investigation Methods For Estimating The Load-Dependent State Of Charge And End Of Discharge Of A Multirotor Uav Battery, Hanna Dibbern, Morten Roßberg, Claudia Werner
Journal of Aviation Technology and Engineering
As the scope of multirotor unmanned aerial vehicle (UAV) applications increases, more attention is being paid to UAV energy requirements, which vary depending on the mission profile. To obtain accurate information about the UAV battery during flight, the idea of a digital twin including a battery state estimation model is promising. For battery state estimation, a Kalman filter combination is the preferred approach in the literature. Comparing different Kalman filters, the unscented Kalman filter has a more accurate estimation for nonlinear systems compared to the extended Kalman filter. In the application of UAV flight with load-dependent flight missions, the comparison …
Stereoscopic-Based Mass Properties Estimation For Warhead Fragments, Alessia Nocerino, Katharine Larsen, Riccardo Bevilacqua, Elisabetta L. Jerome
Stereoscopic-Based Mass Properties Estimation For Warhead Fragments, Alessia Nocerino, Katharine Larsen, Riccardo Bevilacqua, Elisabetta L. Jerome
Student Works
FRAGMENTATION characteristics such as spatial distribution, number of fragments, fragment velocity, and fragment mass can be used to characterize the lethality of a fragmenting weapon or any metal cased explosive [1,2]. However, most warhead tests and evaluations are limited to static arena testing, where fragment characteristics must be collected by hand. Recently, stereoscopic imaging techniques have been added to static arena tests. Using this method, position tracks can be collected for each fragment, and then velocity information can be found. This paper proposes a method to estimate the mass and moment of inertia using data collected by a stereoscopic imaging …
Ambient Air Emission Profiles Of Polycyclic Aromatic Hydrocarbons Around A Typical University Power House In Nigeria, Oyetunji Okedere
Ambient Air Emission Profiles Of Polycyclic Aromatic Hydrocarbons Around A Typical University Power House In Nigeria, Oyetunji Okedere
Tanzania Journal of Engineering and Technology (TJET)
The level of electricity generation in Nigeria is presently grossly inadequate. Consequently, the productive sectors of the economy do not presently enjoy an uninterrupted supply of electrical energy from the country’s national grid and the downtime is in most cases too much. Using diesel-fueled electric power generators has become an attractive alternative to meet the shortfall in the energy supply gap. In this study, the levels of polycyclic aromatic hydrocarbons in the vicinity of the diesel-fueled electric power generators operated by Osun State University, Osogbo, Nigeria were investigated with a view to ascertain the priority levels and carcinogenic PAHs. Since …
Employment Of Intelligent Predictive Maintenance On Thermal Power Plant Component Parts Taking Condenser Vacuum As A Case Study, Titus Ajewole
Employment Of Intelligent Predictive Maintenance On Thermal Power Plant Component Parts Taking Condenser Vacuum As A Case Study, Titus Ajewole
Tanzania Journal of Engineering and Technology (TJET)
This work proposes deployment of machine learning in the maintenance of individual constituent parts of steam power plant assemblages. With the condenser vacuum of a steam turbine (in a six-turbine plant assemblage) taken as a case study, information on the past operating parameters of the selected plant component was used to forecast its future working condition. Based on Exponential Gaussian Process of Regression, a model was developed, trained using the diachronic operational data, and employed in determining the future. A quantitative evaluation was employed to provide the distribution of the test values of the data about the lines of regression, …
Novel Systems Engineering Framework Analysis Of Photovoltaic Models And Equations, Peter R. Michael
Novel Systems Engineering Framework Analysis Of Photovoltaic Models And Equations, Peter R. Michael
USF Tampa Graduate Theses and Dissertations
This dissertation analyzes Photovoltaic PV equations and models for silicon based systems from a Systems Engineering framework. Background information includes an introduction, a summary of the state of PV use, a brief history of photovoltaics, and the detailed derivation of equations that enable the finding of the PV parameters contained in the PV models.The novel inquiry, leveraging systems engineering frameworks, includes three areas useful in analyzing PV equations and models. The first is a statistical verification of common simplifications of PV equations at the primary conditions of short circuit, open circuit, and maximum power. Additional analysis shows other simplifications that …
Optimal Inverter-Based Resource Installation To Minimize Technical Energy Losses In Distribution Systems, Felipe B. Dantas, Damasio Fernandes, Washington L.A. Neves, Alana K.X.B. Branco, Flavio Costa
Optimal Inverter-Based Resource Installation To Minimize Technical Energy Losses In Distribution Systems, Felipe B. Dantas, Damasio Fernandes, Washington L.A. Neves, Alana K.X.B. Branco, Flavio Costa
Michigan Tech Publications
This paper proposes an algorithm for the optimal installation of inverter-based resources (IBR) composed of wind energy conversion systems, photovoltaic systems, and battery energy storage systems in distribution systems using genetic algorithm (GA) and the cuckoo search (CS) as optimization techniques. The OpenDSS software is used to calculate the power flow in the distribution system with different penetration levels of IBRs. It is used a standard load shape of the IEEE 123 bus system programmed in OpenDSS and irradiance, temperature, and wind speed curves from Brazil. The proposed algorithm, using a genetic algorithm and cuckoo search, was able to define …
Frequency Stability Constrained Grid Operation With High Penetration Of Renewables, Ningchao Gao
Frequency Stability Constrained Grid Operation With High Penetration Of Renewables, Ningchao Gao
Electronic Theses and Dissertations
Achieving carbon neutrality necessitates a significant integration of renewable energy into power systems. However, the swift implementation of fluctuating renewable energy (VRE) sources such as solar photovoltaics (PV) exacerbates real time power imbalances due to the randomness and uncertainty associated with VRE power generation. Further, the declining reliance on conventional synchronous generators (SGs) for system inertia presents considerable challenges in maintaining frequency stability, especially following disturbances.
Two possible solutions are proposed to address the first issue. Firstly, a speedy real time generation dispatch can be scheduled to allocate generation resources within short time intervals to effectively respond to changes in …
Custom Led Dashboard Integration For The Cal Poly Racing Team, Josue Hernandez
Custom Led Dashboard Integration For The Cal Poly Racing Team, Josue Hernandez
Computer Engineering
The Custom LED Dashboard Integration was made for the Cal Poly Racing Team, specifically the BAJA division. The dashboard was made as a way to combat the current limitations endured from the past methods used to display critical information of the vehicle to the car. The display was made to combat issues of limited quantity of data being able to be displayed to the driver and its small readability was an issue, the display helped combat that by providing a greater quantity of data being able to be sent and displayed on the display and the information being displayed having …
Real-Time Object Tracking With Yolov5 And Recurrent Network On A Hardware Platform, Mohammed Abdulhakeem Alameri
Real-Time Object Tracking With Yolov5 And Recurrent Network On A Hardware Platform, Mohammed Abdulhakeem Alameri
Theses
The advancement of computer vision, particularly in the domain of object tracking, involves the integration of conventional feature-based approaches with contemporary deep learning methodologies. The initial phase of object detection plays a fundamental role in generating prospective objects for further tracking, and its level of success has a direct influence on the overall effectiveness of the tracking process. Many of the methods used to generate candidate objects start with object detection, and then object tracking algorithms are developed to link the object instances together to create the trajectories.
The primary difficulties in object tracking pertain to the establishment of reliable …