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Using A Neural Network To Remove Noise From Images, Anvar Asatilloyevich Ravshanov
Using A Neural Network To Remove Noise From Images, Anvar Asatilloyevich Ravshanov
Chemical Technology, Control and Management
This article proposes modern approaches to the problem of noise reduction in images using neural networks and also analyses the possibilities of noise reduction using neural networks. The convolutional neural network model and the Mediana, Sobel filter were considered for image denoising. The quality improvement of the trained neural network and the comparison with classical noise reduction methods have been carried out.
Advancing Influence In Social Networks Based On Game Theory, Adedamola Adesokan
Advancing Influence In Social Networks Based On Game Theory, Adedamola Adesokan
Electrical and Computer Engineering ETDs
Online Social Networks (OSNs) have become part of our everyday life, as a means of interacting with people, sharing content, attending events, etc. Influencers are professional OSN users, who have a large loyal audience and use the OSNs to market various goods or services based on brand partnerships. In this thesis, we introduce a novel mechanism to enable OSN users to become influencers by strategically deciding their activity within the OSN. Initially, the concepts of social coordinates and social communities are proposed. Then, a non-cooperative game is introduced to enable the users to make optimal decisions regarding their activity in …
Matrix Processing With Photonic Analog Computing, James Michael Garofolo
Matrix Processing With Photonic Analog Computing, James Michael Garofolo
Theses and Dissertations
In the digital age, a wide variety of engineering problems have been solved, to a great deal of success, by digital computing techniques. The flexibility of software and relatively low cost of digital computing hardware make it an ideal starting point for solving a majority of tasks, and the numerical stability of software solutions make it highly appealing as the major workhorse for computational tasks. Despite this, many problems are actually suboptimally solved by digital methods, leading to systems with high latency, low throughput, power hungry parallel processing units and an excess of memory for discretizing sensor inputs. Computational photonic …
Surface Structures And Properties Of High-Voltage Licoo2: Reviews And Prospects, Jian-Jun Fang, Yu-Hao Du, Zi-Jian Li, Wen-Guang Fan, Heng-Yu Ren, Hao-Cong Yi, Qing-He Zhao, Feng Pan
Surface Structures And Properties Of High-Voltage Licoo2: Reviews And Prospects, Jian-Jun Fang, Yu-Hao Du, Zi-Jian Li, Wen-Guang Fan, Heng-Yu Ren, Hao-Cong Yi, Qing-He Zhao, Feng Pan
Journal of Electrochemistry
Nowadays, the development of high-voltage LiCoO2 (lithium cobalt oxide, LCO) cathodes has attracted the widespread attention from both the academic and industry fields. Among the multiple concerns, researches on the surface issues would provide the most effective performance optimization pathway for the synthesis of high-voltage LCO. In this work, the issues of high-voltage LCO, including the phase transitions and crack formation, the oxygen redox related issues and side reactions, as well as the surface structure degradation, have been systematically reviewed. Then, we further clarify the surface modulations, and the interplay between the surface modulation and electrolyte tuning. Finally, we …
Molybdenum Disulfide And Carbon Nanotubes Composite Electrode For Electrochemical Conversion Of Salinity Gradient Energy, Jia-Jun Li, Wei-Bin Zhang, Xin-Yu Liu, Jing-Lei Yang, Yi Yin, Ze-Qin Yang, Xue-Jing Ma
Molybdenum Disulfide And Carbon Nanotubes Composite Electrode For Electrochemical Conversion Of Salinity Gradient Energy, Jia-Jun Li, Wei-Bin Zhang, Xin-Yu Liu, Jing-Lei Yang, Yi Yin, Ze-Qin Yang, Xue-Jing Ma
Journal of Electrochemistry
The ocean accounts for 97% of the total water resources on earth, covering over 70% of the map's surface area. With the continuous consumption of non-renewable energy sources such as fossil fuels and the rapid development of renewable energy, humans are increasingly paying attention to the utilization of ocean resources. Ocean energy includes tidal energy, wave energy, temperature difference energy, and salinity gradient energy. Salinity gradient energy is the energy generated by the interaction of seawater and fresh water, which is the ocean energy existing in the form of chemical energy. This energy is mostly generated in estuaries. The osmotic …
In Situ Diffuse Reflectance Spectroelectrochemistry Of Cathode Materials In Lithium-Ion Batteries, Lu-Lu Chen, Hao-Ran Li, Wei-Yi Liu, Wei Wang
In Situ Diffuse Reflectance Spectroelectrochemistry Of Cathode Materials In Lithium-Ion Batteries, Lu-Lu Chen, Hao-Ran Li, Wei-Yi Liu, Wei Wang
Journal of Electrochemistry
Developing in situ spectroelectrochemistry methods, which can provide detailed information about species transformation during electrochemical reactions, is very important for studying electrode reaction mechanisms and improving battery performance. Studying real-time changes in the surface of electrode materials during normal operation can be an effective way to assess and optimize the practical performance of electrode materials, thus, in situ and in operando characterization techniques are particularly important. However, batteries are hard to be studied by in situ characterization measurements due to their hermetically sealed shells, and there is still much room for battery characterizations. In this work, a specially designed battery …
Deep Learning Framework For Graph-Based Molecular Drug Discovery, Daniel Manu
Deep Learning Framework For Graph-Based Molecular Drug Discovery, Daniel Manu
Electrical and Computer Engineering ETDs
This dissertation proposes the GraphGANFed framework, which combines Graph Convolutional Networks (GCN), Generative Adversarial Networks (GAN), and Federated Learning (FL) to generate novel molecules while preserving data privacy. FL allows learning from distributed clients without sharing local datasets, GCN extracts molecular structural properties, and GAN generates new molecules retaining the learned properties. Extensive simulations on three benchmark datasets show GraphGANFed's effectiveness, producing molecules with high novelty (≈ 100) and diversity (> 0.9). Results indicate a trade-off among evaluation metrics, and the right dropout ratio avoids mode collapse. Additionally, Conditional GraphGANFed (cGraphGANFed) incorporates a critic network from Reinforcement Learning (RL) to …
Creative Insights Into Motion: Enhancing Human Activity Understanding With 3d Data Visualization And Annotation, Isaac Browen, Hector M. Camarillo-Abad, Franceli L. Cibrian, Trudi Di Qi
Creative Insights Into Motion: Enhancing Human Activity Understanding With 3d Data Visualization And Annotation, Isaac Browen, Hector M. Camarillo-Abad, Franceli L. Cibrian, Trudi Di Qi
Engineering Faculty Articles and Research
This paper presents a novel 3D system for human motion analysis - Motion Data Visualization and Annotation (MoViAn). Designed to provide a comprehensive visual representation of 3D human motion data, MoViAn incorporates detailed visualization of gaze direction, hand movements, and object interactions, alongside an interactive interface for efficient data annotation. A user study involving eight participants indicates that MoViAn enables users to thoroughly explore and annotate human motion data, with System Usability Scale (SUS) results demonstrating a satisfactory usability level. The contribution of this paper lies in the development of an interactive and usable data analytics tool aimed at deepening …
Board 125: Work In Progress: Faculty Experiences And Learning Through Oral-Assessment Implementation In Engineering Courses, Minju Kim, Carolyn L. Sandoval, Josephine Relaford-Doyle, Torus Washington Ii, Saharnaz Baghdadchi, Nathan Delson, Marko Lubarda, Alex M. Phan, Curt Schurgers, Huihui Qi
Board 125: Work In Progress: Faculty Experiences And Learning Through Oral-Assessment Implementation In Engineering Courses, Minju Kim, Carolyn L. Sandoval, Josephine Relaford-Doyle, Torus Washington Ii, Saharnaz Baghdadchi, Nathan Delson, Marko Lubarda, Alex M. Phan, Curt Schurgers, Huihui Qi
Psychology Faculty Articles and Research
This WIP qualitative research paper explores faculty experiences with implementing oral exams in high-enrollment undergraduate engineering courses at a research university. With a primary goal to improve conceptual mastery, as well as a desire to ensure academic integrity in the sudden move to remote instruction at the height of the pandemic, a group of faculty in Mechanical and Aerospace Engineering and Electrical and Computer Engineering departments implemented oral assessments in their own engineering courses across several quarters. They formed a research group with educational developers in a teaching and learning center on campus, and investigated the impact of oral assessments …
Plc Multi-Robot Integration Via Ethernet For Human Operated Quality Sampling, Jeevan S. Devagiri, Paniz Khanmohammadi Hazaveh, Nathir Rawashdeh, Sai Revanth Reddy Dudipala, Pratik Mohan Desmuhk, Aditya Prasad Karmarkar
Plc Multi-Robot Integration Via Ethernet For Human Operated Quality Sampling, Jeevan S. Devagiri, Paniz Khanmohammadi Hazaveh, Nathir Rawashdeh, Sai Revanth Reddy Dudipala, Pratik Mohan Desmuhk, Aditya Prasad Karmarkar
Michigan Tech Publications
In automation, quality control inspection is a critical requirement to ensure product standards. The goal of this work is to insure product quality without interrupting the production line flow. The multi-robot system presented, connects a programmable logic controller (PLC), as the main controller, to a conveyor belt and two FANUC industrial robotic arms via EtherNet/IP. Human interaction is implemented to pick a work piece from the moving conveyor and return it with a quality label. This label is used by the PLC to execute the correct robot action; either to return the inspected part to the conveyor or discard it …
Model-Based Systems Engineering For Engineering Education Systems Simulation, Pallavi Singh
Model-Based Systems Engineering For Engineering Education Systems Simulation, Pallavi Singh
USF Tampa Graduate Theses and Dissertations
As the engineering education system continuously evolves to meet the demands of modern industry and society, there is a need for a methodology that would manage and resolve the complexities inherent in engineering educational systems. Model-based Systems Engineering (MBSE) is a structured approach to system design that utilizes models across all stages of the system's life cycle and supports requirements management, design, analysis, verification, and validation processes. While MBSE has been applied successfully in industries like defense, aerospace, and automotive, its application in engineering educational systems remains unexplored. This dissertation develops a dynamic model of the university-level engineering education system …
Estimation Of Vehicle Traffic Parameters Using An Optical Distance Sensor For Use In Smart City Road Infrastructure, Rafał Burdzik, Ireneusz Celiński, Minvydas Ragulskis, Vinayak Ranjan, Jonas Matijošius
Estimation Of Vehicle Traffic Parameters Using An Optical Distance Sensor For Use In Smart City Road Infrastructure, Rafał Burdzik, Ireneusz Celiński, Minvydas Ragulskis, Vinayak Ranjan, Jonas Matijošius
Henry M. Rowan College of Engineering Departmental Research
In recent decades, the dynamics of road vehicle traffic have significantly evolved, compelling traffic engineers to develop innovative traffic monitoring solutions, especially for dense road networks. Traditional methods for measuring traffic volume along road sections may no longer suffice for modern traffic control systems. This is particularly true for induction loops, a widely used method since the last century. In contrast, measuring techniques using microwaves or visible light offer better accuracy but are often hindered by the high cost of sensors. This paper presents new techniques for measuring traffic flow and other parameters that adapt to changing traffic dynamics using …
Large-Scale Research Infrastructure Empowers High-Quality Development Of Private Enterprises: Current Situation, Challenges, And Policy Recommendations, Lingling Zhang, Fuqiang Wang, Mingze Zhang, Zexia Li
Large-Scale Research Infrastructure Empowers High-Quality Development Of Private Enterprises: Current Situation, Challenges, And Policy Recommendations, Lingling Zhang, Fuqiang Wang, Mingze Zhang, Zexia Li
Bulletin of Chinese Academy of Sciences (Chinese Version)
Private enterprises have become an important source of innovation in China’s economic development. Large-scale research infrastructure, as a crucial strategic support and innovation element for breaking through key technologies, provides a platform for the innovative development of private enterprises. At present, some large-scale research infrastructures in China, such as the China Spallation Neutron Source and the Shanghai Synchrotron Radiation Facility, have begun actively exploring mechanisms to serve private enterprises. These efforts have helped a number of private companies overcome critical technological bottlenecks and achieve original innovations. Nevertheless, in the current process of opening up large-scale research infrastructures to private enterprises …
Advancing Adversarial Audio: Human-In-The-Loop Black-Box Attacks, Rui Duan
Advancing Adversarial Audio: Human-In-The-Loop Black-Box Attacks, Rui Duan
USF Tampa Graduate Theses and Dissertations
Adversarial audio attacks pose significant security challenges to real-world audio applications. Attackers may manipulate speech to impersonate a speaker, gaining access to smart devices like Amazon Echo. In audio applications, there are two key areas: music and speech. In music, most attackers create a small noise-like perturbation on the original signal to evade copyright detection. However, this method degrades music's perceived quality for human listeners. In the speech, creating an adversarial example often requires many queries to the target model, a process too cumbersome for practical use in real-world scenarios, like interacting with smart devices numerous times.
In this dissertation, …
A Country-Level Primary-Final-Useful (Cl-Pfu) Energy And Exergy Database: Overview Of Its Construction And 1971–2020 World-Level Efficiency Results, Paul E. Brockway, Matthew Kuperus Heun, Zeke Marshall, Emmanuel Aramendia, Paul Steenwyk, Thomas Relph, Michelle Widjanarko, Jeonghoo (James) Kim, Anjana Sainju, Julian Irtube
A Country-Level Primary-Final-Useful (Cl-Pfu) Energy And Exergy Database: Overview Of Its Construction And 1971–2020 World-Level Efficiency Results, Paul E. Brockway, Matthew Kuperus Heun, Zeke Marshall, Emmanuel Aramendia, Paul Steenwyk, Thomas Relph, Michelle Widjanarko, Jeonghoo (James) Kim, Anjana Sainju, Julian Irtube
University Faculty Publications and Creative Works
Societal exergy analysis examines the flows of energy and exergy through societies, from primary (e.g. oil) to final (e.g. gasoline) to useful (e.g. propulsion) energy stages. By extending the study of energy to the useful stage, new insights into the under-represented role of energy in economic growth have been made. However, currently (a) country coverage is patchy and incomplete, (b) available data are based on varying methods and assumptions including efficiencies based on economic rather than engineering data, and (c) datasets are constructed using piecemeal computational approaches. To address these gaps, we construct a country-level primary-final-useful (CL-PFU) energy and exergy …
Investigating The Impact Of Inverter-Based Resources On Power Grid Dynamics, Ratik Mittal
Investigating The Impact Of Inverter-Based Resources On Power Grid Dynamics, Ratik Mittal
USF Tampa Graduate Theses and Dissertations
This dissertation explores the stability challenges posed by integrating Inverter-Based Resources (IBR) into power grids, particularly focusing on two major scenarios: IBRs connected to weak grid interconnections and their performance in series-compensated networks. With the increasing dependency on renewable energy sources, ensuring the stability of these grids is crucial. A multilayered investigative approach is employed, utilizing Electromagnetic Transient Simulations that model grid systems interfaced with IBRs. These simulations are pivotal as they emulate real-world stability issues and provide a foundational understanding of grid interactions. In this dissertation two major types of IBR control are modeled and analyzed: Grid Following Control …
Evaluation Of Reduced Graphene Oxide For Advanced Thermal Management In Microwave Electronics Packaging, Utkarsh Misra
Evaluation Of Reduced Graphene Oxide For Advanced Thermal Management In Microwave Electronics Packaging, Utkarsh Misra
USF Tampa Graduate Theses and Dissertations
The continuous push towards making electronic devices smaller and denser, largely driven by the demand for higher power capabilities, has led to a critical need for innovative and comprehensive methods for managing the heat these devices generate. Traditional cooling solutions for electronics often rely on methods such as copper-based layers or channels to distribute and dispel heat. However, these conventional methods and materials are becoming increasingly insufficient, especially for Radio Frequency (RF) and millimeter-wave electronics. These components are becoming ever more compact while requiring more power, thus presenting unique challenges for thermal management in their packaging.
In this thesis we …
Federated Learning Based Autoencoder Ensemble System For Malware Detection On Internet Of Things Devices, Steven Edward Arroyo
Federated Learning Based Autoencoder Ensemble System For Malware Detection On Internet Of Things Devices, Steven Edward Arroyo
Theses and Dissertations
New technologies are being introduced at a rate faster than ever before and smaller in size. Due to the size of these devices, security is often difficult to implement. The existing solution is a firewall-segmented “IoT Network” that only limits the effect of these infected devices on other parts of the network. We propose a lightweight unsupervised hybrid-cloud ensemble anomaly detection system for malware detection. We perform transfer learning using a generalized model trained on multiple IoT device sources to learn network traffic on new devices with minimal computational resources. We further extend our proposed system to utilize federated learning …
Transforming Orthopedic Surgery: Autonomous Image-Guided Techniques For Femur Fracture Robotic Surgery, Marzieh Sadat Saeedi-Hosseiny
Transforming Orthopedic Surgery: Autonomous Image-Guided Techniques For Femur Fracture Robotic Surgery, Marzieh Sadat Saeedi-Hosseiny
Theses and Dissertations
Long-bone fractures, particularly femur fractures, are prevalent and necessitate surgical intervention due to traumatic forces. Manual reduction procedures pose challenges, including excessive traction forces and reliance on limited X-ray imaging, resulting in malalignment-related complications and repeated surgeries. Current methods for femur fracture reduction are prone to inaccuracies, prolonged surgical times, and postoperative complications. This research introduces image-guided methods to automate a surgical robotic system, Robossis, to enhance femur alignment accuracy, reduce procedure times, and improve patient outcomes. To address these challenges, a marker-based approach utilizing a few X-ray images is developed to detect the spatial relative position of the femur …
Modeling And Optimization Of Time Delay Unit Network Architectures For Reducing Complexity Of Ultra- Wideband Phased Antenna Arrays, Daniel A. Ramirez
Modeling And Optimization Of Time Delay Unit Network Architectures For Reducing Complexity Of Ultra- Wideband Phased Antenna Arrays, Daniel A. Ramirez
USF Tampa Graduate Theses and Dissertations
This dissertation presents a systematic technique for modeling and optimization of the hierarchical time delay unit (TDU) architectures of ultra-wideband (UWB) phased antenna arrays (PAAs). The first major contribution of this dissertation is the optimization of a linear PAA by casting the problem in the standard form of integer linear programming (ILP) optimization with an objective function that targets minimizing the total number of TDUs within the RF feed network fanout while maintaining phase error and manufacturability constraints. This optimization can significantly reduce the cost, power, and complexity of UWB PAAs in contrast to prior methods that iteratively converge on …
Performance Analysis Of Underground-To-Aboveground Communication In Agricultural Iot Networks, Irfana Ilyas Manzil
Performance Analysis Of Underground-To-Aboveground Communication In Agricultural Iot Networks, Irfana Ilyas Manzil
Thesis/ Dissertation Defenses
This thesis investigates the potential of LoRa, a low-power, wide-area networking technology, for establishing reliable communication between underground sensors and aboveground infrastructure. We comprehensively analyze LoRa's performance in both single-hop and multi-hop configurations, considering the impact of diverse environmental factors such as soil composition, moisture content, underground transmission distance, and path loss on signal propagation. We delve into the crucial role of the spreading factor (SF) within the LoRa communication system, analyzing its influence on network performance. Furthermore, we develop a comprehensive mathematical model for bit error rate (BER) under various channel conditions, including additive white Gaussian noise (AWGN) and …
Back To The Future: A Case For The Resurgence Of Approximation Theory For Enabling Data Driven “Intelligence”, Michael Dominic Ciocco
Back To The Future: A Case For The Resurgence Of Approximation Theory For Enabling Data Driven “Intelligence”, Michael Dominic Ciocco
Theses and Dissertations
Artificial Intelligence (AI) has exploded into mainstream consciousness with commercial investments exceeding $90 billion in the last year alone. Inasmuch as consumer-facing applications such ChatGPT offer astounding access to algorithms that were hitherto restricted to academic research labs, public focus of attention on AI has created an avalanche of misinformation. The nexus of investor-driven hype, “surprising” inaccuracies in the answers provided by AI models – now anthropomorphically labeled as “hallucinations”, and impending legislation by well-meaning and concerned governments has resulted in a crisis of confidence in the science of AI. The primary driver for AI’s recent growth is the convergence …
Single-Molecule Orientation Imaging Reveals The Nano-Architecture Of Amyloid Fibrils Undergoing Growth And Decay, Brian Sun, Tianben Ding, Weiyan Zhou, Tara S. Porter, Matthew D. Lew
Single-Molecule Orientation Imaging Reveals The Nano-Architecture Of Amyloid Fibrils Undergoing Growth And Decay, Brian Sun, Tianben Ding, Weiyan Zhou, Tara S. Porter, Matthew D. Lew
Electrical & Systems Engineering Publications and Presentations
Amyloid-beta (Aβ42) aggregates are characteristic Alzheimer’s disease signatures, but probing how their nanoscale architectures influence their growth and decay remains challenging using current technologies. Here, we apply time-lapse single-molecule orientation-localization microscopy (SMOLM) to measure the orientations and rotational “wobble” of Nile blue (NB) molecules transiently binding to Aβ42 fibrils. We correlate fibril architectures measured by SMOLM with their growth and decay over the course of 5 to 20 min visualized by single-molecule localization microscopy (SMLM). We discover that stable Aβ42 fibrils tend to be well-ordered and signified by well-aligned NB orientations and small wobble. SMOLM also shows that increasing order …
Modeling A Hydropower Plant Powerhouse Based On Hebgen Dam, James Savella, Paul De La Cruz
Modeling A Hydropower Plant Powerhouse Based On Hebgen Dam, James Savella, Paul De La Cruz
Electrical Engineering
The United States Department of Energy (DOE) Water Power Technologies Office (WPTO) invited California Polytechnic State University (Cal Poly) to participate in the 2024 Hydropower Collegiate Competition (HCC) to research and design ways to convert non-powered dams (NPDs) to hydropower plants to contribute to a clean energy future. The Cal Poly HCC Electrical Engineering team used information gathered for the competition to create a simulated hydropower plant model of Hebgen Dam, in Montana, using a salient pole synchronous generator and a PID governor for an Electrical Engineering Senior Project. The simulated hydropower plant model allows a user to control the …
Design And Analysis Of A New Buck-Boost Converter With A Low-Side Switch, Abdullah Awidah
Design And Analysis Of A New Buck-Boost Converter With A Low-Side Switch, Abdullah Awidah
Master's Theses
This work explores the design, simulation, construction, and analysis of a novel Non-isolated DC-DC Buck-Boost converter which has the advantage of incorporating a low-side switch compared to the traditional buck-boost which requires a high-side switch. This allows the use of a low-side driver which further simplifies the design and operation of the converter. The proposed Buck-Boost converter was constructed to provide -24 V output from an input range of 12V-18V with 15V nominal input at 10W maximum output power utilizing 500kHz switching frequency. Findings from simulations and hardware tests verify that the converter effectively provides the desired -24 V output …
Enhancing Direction Finding Accuracy In Perturbed Digital Arrays Via Rf Ranging-Based Self Calibration, Ariel Freiman
Enhancing Direction Finding Accuracy In Perturbed Digital Arrays Via Rf Ranging-Based Self Calibration, Ariel Freiman
Master's Theses
Direction finding with radio-frequency (RF) waves have numerous applications in radio navigation, wireless localization, emergency aid, and air traffic control, among others. Direction-finding using digital arrays outperforms traditional analog techniques but requires precise knowledge of the location of the array elements to obtain accurate results. Array perturbations can lead to algorithm failures and false detection, compromising direction-finding capabilities.
This research proposes implementing a Matched Filter - Least Square (MF-LS) algorithm for Two-Way Ranging (TWR) to enhance direction-finding accuracy in arrays with perturbed element locations. The MF-LS algorithm leverages the properties of matched filters to accurately determine element positions by measuring …
An Analysis Of Indoor Air Quality At Cal Poly For Sensor Design, Isabella M. Santi
An Analysis Of Indoor Air Quality At Cal Poly For Sensor Design, Isabella M. Santi
Master's Theses
Prior research has shown that indoor air quality (IAQ) impacts cognitive performance. At Cal Poly, many older buildings are unable to maintain appropriate IAQ because of their outdated ventilation systems and the increasing number of students in the rooms. This work analyzes the IAQ of different buildings at Cal Poly, with a focus on Building 20. Carbon dioxide, temperature, and relative humidity inside classrooms are collected using an integrated circuit sensor and a microcontroller. A total of 38 hours of data was collected, with 22 of those hours in Building 20 specifically. We find that unlike temperature and relative humidity, …
A Hybrid Computer To Solve The Selective Harmonic Minimization Problem In Single-Phase Inverters, Dillon Nguyen
A Hybrid Computer To Solve The Selective Harmonic Minimization Problem In Single-Phase Inverters, Dillon Nguyen
Master's Theses
Power electronics possess forms of non-ideality due to the nonlinearity present in physical switches. These switches are driven with pulse width modulation (PWM), which properly down-converts or up-converts based on converter topology. When these switches turn on or off, they introduce the main proponent of efficiency loss: harmonics. This becomes a nonlinear optimization problem with many converters. The solution proposed in this thesis is an analog/digital hybrid computer that utilizes the speed of analog computation and the accuracy of digital computing together. A Plexim RT Box provides the programmability needed for algorithms, while the analog circuit provides low-power, high-speed computation …
Optimal False Data Injection (Fdi) In Simulated Cooperative Adaptive Cruise Control (Cacc) Systems, Lovro Dukic
Optimal False Data Injection (Fdi) In Simulated Cooperative Adaptive Cruise Control (Cacc) Systems, Lovro Dukic
Master's Theses
In the rapidly advancing field of autonomous vehicles, ensuring the security and reliability of self-driving systems is crucial. Autonomous vehicle systems, such as cooperative adaptive cruise control (CACC), must undergo significant research and testing before their integration into commercial intelligent transportation systems. CACC considers multiple vehicles in close proximity as a single entity, or platoon, with each vehicle equipped with a controller that uses sensor-based measurements and vehicle-to-vehicle (V2V) communication to control inter-vehicle spacing. While this system offers numerous potential benefits for traffic safety and efficiency, it is also susceptible to False Data Injection (FDI) attacks, which can cause the …
Harmonic Flow Modeling And Analysis Of A Green Hybrid Ac/Dc Seaport Power System, Krishan Kaushal Ram, Taufik, Helen Yu, Siddharth Vyas
Harmonic Flow Modeling And Analysis Of A Green Hybrid Ac/Dc Seaport Power System, Krishan Kaushal Ram, Taufik, Helen Yu, Siddharth Vyas
Master's Theses
This thesis aims to design and develop a model for a proposed Green Seaport power system and perform harmonic analysis. The model was developed using MATLAB Simulink and tests were performed by dividing the system into several Battery Energy Storage System (BESS) operating modes such as simultaneous charging and discharging, simultaneous charging, and simultaneous discharging. For each mode, BESS state of charge and other factors such as solar irradiance for the PV system, load levels and power factor were varied to observe the impact on system’s voltage Total Harmonic Distortion (THD) level and current Total Demand Distortion (TDD). 62 separate …