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Articles 2671 - 2700 of 25609

Full-Text Articles in Computer Engineering

Practical Static Binary Instrumentation Attacks Against Binary Stylometry, Justin Lee Carpenter May 2024

Practical Static Binary Instrumentation Attacks Against Binary Stylometry, Justin Lee Carpenter

Masters Theses, 2020-current

Binary stylometry aims to find the features in a binary computer program and use them to identify the developers of the corresponding source code. Despite the noises in the code compilation process from the compiler, assembler, linker, and library functions, two existing studies based on machine learning for binary stylometry have reported high success rates (Alrabaee, Shirani, Wang, Debbabi, and Hanna 2018; Caliskan, Yamaguchi, Dauber, Harang, Rieck, Greenstadt, and Narayanan 2018). In this thesis, we first observe that both existing studies are based on a largely benign security model and assume that the binaries used in testing and prediction are …

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Flexible Strain Gauge Sensors As Real-Time Stretch Receptors For Use In Biomimetic Bpa Muscle Applications, Rochelle Jubert May 2024

Flexible Strain Gauge Sensors As Real-Time Stretch Receptors For Use In Biomimetic Bpa Muscle Applications, Rochelle Jubert

Student Research Symposium

This work presents a novel approach to real-time length sensing for biomimetic Braided Pneumatic Actuators (BPAs) as artificial muscles in soft robotics applications. The use of artificial muscles enables the development of more interesting robotic designs that no longer depend on single rotation joints controlled by motors. Developing robots with these capabilities, however, produces more complexities in control and sensing. Joint encoders, the mainstay of robotic feedback, can no longer be used, so new methods of sensing are needed to get feedback on muscle behavior to implement intelligent controls. To address this need, flexible strain gauge sensors from Portland company, …

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Chiroptical Second-Harmonic Tyndall Scattering From Silicon Nanohelices, Ben J. Olohan, Emilija Petronijevic, Ufuk Kilic, Shawn Wimer, Matthew Hilfiker, Mathias Schubert, Christos Argyropoulos, Eva Schubert, Samuel R. Clowes, G. Dan Pantoş, David L. Andrews, Ventsislav K. Valev May 2024

Chiroptical Second-Harmonic Tyndall Scattering From Silicon Nanohelices, Ben J. Olohan, Emilija Petronijevic, Ufuk Kilic, Shawn Wimer, Matthew Hilfiker, Mathias Schubert, Christos Argyropoulos, Eva Schubert, Samuel R. Clowes, G. Dan Pantoş, David L. Andrews, Ventsislav K. Valev

Department of Electrical and Computer Engineering: Faculty Publications

Chirality is omnipresent in the living world. As biomimetic nanotechnology and self-assembly advance, they too need chirality. Accordingly, there is a pressing need to develop general methods to characterize chiral building blocks at the nanoscale in liquids such as water-the medium of life. Here, we demonstrate the chiroptical second-harmonic Tyndall scattering effect. The effect was observed in Si nanohelices, an example of a high-refractive-index dielectric nanomaterial. For three wavelengths of illumination, we observe a clear difference in the second-harmonic scattered light that depends on the chirality of the nanohelices and the handedness of circularly polarized light. Importantly, we provide a …

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Evaluating The Effect Of Noise On Secure Quantum Networks, Karthick Anbalagan May 2024

Evaluating The Effect Of Noise On Secure Quantum Networks, Karthick Anbalagan

Master's Theses

This thesis focuses on examining the resilience of secure quantum networks to environmental noise. Specifically, we evaluate the effectiveness of two well-known quantum key distribution (QKD) protocols: the Coherent One-Way (COW) protocol and Kak’s Three-Stage protocol (Kak06). The thesis systematically evaluates these protocols in terms of their efficiency, operational feasibility, and resistance to noise, thereby contributing to the progress of secure quantum communications. Using simulations, this study evaluates the protocols in realistic scenarios that include factors such as noise and decoherence. The results illustrate each protocol’s relative benefits and limitations, highlighting the three-stage protocol’s superior security characteristics, resistance to interference, …

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Robustness Of Trajectory Prediction Neural Network Models, Guocheng He May 2024

Robustness Of Trajectory Prediction Neural Network Models, Guocheng He

McKelvey School of Engineering Graduate Student Theses & Dissertations

The application of autonomous vehicles in real life relies on trajectory prediction models based on perception and observation of the surrounding scene. The deep neural network model has been widely proven to provide relatively stable and excellent performance in various scenarios. Many formal approaches are used as verification of the prediction results of DNN models, where Conformal Prediction is one which can provide statistical safety guarantee region for DNN models. However, so far, no research has shown that conformal prediction possesses satisfactory robustness in dealing with purposed adversarial attacks. In this paper, we propose an adversarial attack approach against trajectory …

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Machine Learning For Intrusion Detection Into Unmanned Aerial System 6g Networks, Faisal Alrefaei May 2024

Machine Learning For Intrusion Detection Into Unmanned Aerial System 6g Networks, Faisal Alrefaei

Doctoral Dissertations and Master's Theses

Progress in the development of wireless network technology has played a crucial role in the evolution of societies and provided remarkable services over the past decades. It remotely offers the ability to execute critical missions and effective services that meet the user's needs. This advanced technology integrates cyber and physical layers to form cyber-physical systems (CPS), such as the Unmanned Aerial System (UAS), which consists of an Unmanned Aerial Vehicle (UAV), ground network infrastructure, communication link, etc. Furthermore, it plays a crucial role in connecting objects to create and develop the Internet of Things (IoT) technology. Therefore, the emergence of …

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Improving Ethics Surrounding Collegiate-Level Hacking Education: Recommended Implementation Plan & Affiliation With Peer-Led Initiatives, Shannon Morgan, Dr. Sanjay Goel May 2024

Improving Ethics Surrounding Collegiate-Level Hacking Education: Recommended Implementation Plan & Affiliation With Peer-Led Initiatives, Shannon Morgan, Dr. Sanjay Goel

Military Cyber Affairs

Cybersecurity has become a pertinent concern, as novel technological innovations create opportunities for threat actors to exfiltrate sensitive data. To meet the demand for professionals in the workforce, universities have ramped up their academic offerings to provide a broad range of cyber-related programs (e.g., cybersecurity, informatics, information technology, digital forensics, computer science, & engineering). As the tactics, techniques, and procedures (TTPs) of hackers evolve, the knowledge and skillset required to be an effective cybersecurity professional have escalated accordingly. Therefore, it is critical to train cyber students both technically and theoretically to actively combat cyber criminals and protect the confidentiality, integrity, …

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Using Digital Twins To Protect Biomanufacturing From Cyberattacks, Brenden Fraser-Hevlin, Alec W. Schuler, B. Arda Gozen, Bernard J. Van Wie May 2024

Using Digital Twins To Protect Biomanufacturing From Cyberattacks, Brenden Fraser-Hevlin, Alec W. Schuler, B. Arda Gozen, Bernard J. Van Wie

Military Cyber Affairs

Understanding of the intersection of cyber vulnerabilities and bioprocess regulation is critical with the rise of artificial intelligence and machine learning in manufacturing. We detail a case study in which we model cyberattacks on network-mediated signals from a novel bioreactor, where it is important to control medium feed rates to maintain cell proliferation. We use a digital twin counterpart reactor to compare glucose and oxygen sensor signals from the bioreactor to predictions from a kinetic growth model, allowing discernment of faulty sensors from hacked signals. Our results demonstrate a successful biomanufacturing cyberattack detection system based on fundamental process control principles.

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Characterizing Advanced Persistent Threats Through The Lens Of Cyber Attack Flows, Logan Zeien, Caleb Chang, Ltc Ekzhin Ear, Dr. Shouhuai Xu May 2024

Characterizing Advanced Persistent Threats Through The Lens Of Cyber Attack Flows, Logan Zeien, Caleb Chang, Ltc Ekzhin Ear, Dr. Shouhuai Xu

Military Cyber Affairs

Effective cyber defense must build upon a deep understanding of real-world cyberattacks to guide the design and deployment of appropriate defensive measures against current and future attacks. In this abridged paper (of which the full paper is available online), we present important concepts for understanding Advanced Persistent Threats (APTs), our methodology to characterize APTs through the lens of attack flows, and a detailed case study of APT28 that demonstrates our method’s viability to draw useful insights. This paper makes three technical contributions. First, we propose a novel method of constructing attack flows to describe APTs. This abstraction allows technical audiences, …

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Generative Machine Learning For Cyber Security, James Halvorsen, Dr. Assefaw Gebremedhin May 2024

Generative Machine Learning For Cyber Security, James Halvorsen, Dr. Assefaw Gebremedhin

Military Cyber Affairs

Automated approaches to cyber security based on machine learning will be necessary to combat the next generation of cyber-attacks. Current machine learning tools, however, are difficult to develop and deploy due to issues such as data availability and high false positive rates. Generative models can help solve data-related issues by creating high quality synthetic data for training and testing. Furthermore, some generative architectures are multipurpose, and when used for tasks such as intrusion detection, can outperform existing classifier models. This paper demonstrates how the future of cyber security stands to benefit from continued research on generative models.

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Machine Learning Security For Tactical Operations, Dr. Denaria Fields, Shakiya A. Friend, Andrew Hermansen, Dr. Tugba Erpek, Dr. Yalin E. Sagduyu May 2024

Machine Learning Security For Tactical Operations, Dr. Denaria Fields, Shakiya A. Friend, Andrew Hermansen, Dr. Tugba Erpek, Dr. Yalin E. Sagduyu

Military Cyber Affairs

Deep learning finds rich applications in the tactical domain by learning from diverse data sources and performing difficult tasks to support mission-critical applications. However, deep learning models are susceptible to various attacks and exploits. In this paper, we first discuss application areas of deep learning in the tactical domain. Next, we present adversarial machine learning as an emerging attack vector and discuss the impact of adversarial attacks on the deep learning performance. Finally, we discuss potential defense methods that can be applied against these attacks.

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Securing The Void: Assessing The Dynamic Threat Landscape Of Space, Brianna Bace, Dr. Unal Tatar May 2024

Securing The Void: Assessing The Dynamic Threat Landscape Of Space, Brianna Bace, Dr. Unal Tatar

Military Cyber Affairs

Outer space is a strategic and multifaceted domain that is a crossroads for political, military, and economic interests. From a defense perspective, the U.S. military and intelligence community rely heavily on satellite networks to meet national security objectives and execute military operations and intelligence gathering. This paper examines the evolving threat landscape of the space sector, encompassing natural and man-made perils, emphasizing the rise of cyber threats and the complexity introduced by dual-use technology and commercialization. It also explores the implications for security and resilience, advocating for collaborative efforts among international organizations, governments, and industry to safeguard the space sector.

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Commercial Enablers Of China’S Cyber-Intelligence And Information Operations, Ethan Mansour, Victor Mukora May 2024

Commercial Enablers Of China’S Cyber-Intelligence And Information Operations, Ethan Mansour, Victor Mukora

Military Cyber Affairs

In a globally commercialized information environment, China uses evolving commercial enabler networks to position and project its goals. They do this through cyber, intelligence, and information operations. This paper breaks down the types of commercial enablers and how they are used operationally. It will also address the CCP's strategy to gather and influence foreign and domestic populations throughout cyberspace. Finally, we conclude with recommendations for mitigating the influence of PRC commercial enablers.

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Analysis And Evaluation Of Different Transformer Architectures For The Protein Sequence Representation And The Corresponding Hypothetical Applications, Mary Mao May 2024

Analysis And Evaluation Of Different Transformer Architectures For The Protein Sequence Representation And The Corresponding Hypothetical Applications, Mary Mao

Theses and Dissertations

This project is to investigate and assess several Transformer topologies for the modeling of protein sequences and their corresponding uses. Each major model for the protein sequence representations is inspected with its mathematical theory and analyzed for the different performance of the models with various validation repositories.

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Rgb Root Matriz Color Dance, Danielle E. Gauthier May 2024

Rgb Root Matriz Color Dance, Danielle E. Gauthier

Theses and Dissertations

RGB Root Matriz Color Dance (Color Dance) is an immersive, interactive experience that combines poetic phrases and color filters to create a womb-like environment. Designed by Danielle Gauthier, this artistic piece uses a webcam to respond to users’ movements in real time, allowing them to confront and express their emotions through metaphor and dance. Color Dance creates a unique platform for self-discovery and empowerment by fostering a connection between the body and discomforting emotions.

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Simulating Information And Communication Applications In Employee Interaction Network Models, Matthew Kanter May 2024

Simulating Information And Communication Applications In Employee Interaction Network Models, Matthew Kanter

Departmental Honors & Graduate Capstone Projects

Information and communication technology (ICT) use has been identified throughout its development and evolution with the Internet boom as a net positive tool for most employees and organizations in the working world. Only recently have studies regarding employees’ well-being begun to come to the forefront of research regarding these rapidly evolving technologies, however these are important issues to discuss in the context of work-life boundary management, emotional exhaustion, overwhelming stress levels, and moral disengagement among other employee well-being dimensions. To explore how employees’ well being might be influenced by ICT use, this study conducted a quantitative survey and analyzed a …

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Analyzing Information Cascades Through Machine Learning And Data Analytics, Betul Agirman May 2024

Analyzing Information Cascades Through Machine Learning And Data Analytics, Betul Agirman

Honors Scholar Theses

In today's digital age, social media platforms have become pivotal in influencing public opinion and behavior, with information spreading being both beneficial and detrimental. This rapid spread is typically called an information cascade, and they are important in further understanding social influence, managing misinformation, and even predicting potential trends of public responses. With social media, people are connected so easily to one another like a network, wherein it becomes possible for them to influence each other’s behavior and decisions. Utilizing a dataset from Weibo that spans critical periods of the COVID-19 outbreak, this study integrates machine learning and data analytics …

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Thematic Synthesis: Rethinking Generative Music With Compositional Understanding In Game And Software Development, Jasper Moore Tucker May 2024

Thematic Synthesis: Rethinking Generative Music With Compositional Understanding In Game And Software Development, Jasper Moore Tucker

Dartmouth College Master’s Theses

Generative music, first introduced by composers like Brian Eno and David Cope in the mid-to-late 20th century, has evolved through many stages, with diverse applications across music and technology companies as well as the game industry. However, despite this widespread interest, there remains a notable lack of the foundational understanding of composition and individual expressiveness in current generative systems that was apparent in the work of early composers. This paper advocates for a shift towards prioritizing compositional thought in system design to foster greater diversity and innovation within generative music. To demonstrate this approach, a novel system synthesizing two distinct …

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Star-Based Reachability Analysis Of Binary Neural Networks On Continuous Input, Mykhailo Ivashchenko May 2024

Star-Based Reachability Analysis Of Binary Neural Networks On Continuous Input, Mykhailo Ivashchenko

School of Computing: Dissertations, Theses, and Student Research

Deep Neural Networks (DNNs) have become a popular instrument for solving various real-world problems. DNNs’ sophisticated structure allows them to learn complex representations and features. However, architecture specifics and floating-point number usage result in increased computational operations complexity. For this reason, a more lightweight type of neural networks is widely used when it comes to edge devices, such as microcomputers or microcontrollers – Binary Neural Networks (BNNs). Like other DNNs, BNNs are vulnerable to adversarial attacks; even a small perturbation to the input set may lead to an errant output. Unfortunately, only a few approaches have been proposed for verifying …

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Adaptive Solutions For Improving The Quality Of Mobile User Experiences, Meena V May 2024

Adaptive Solutions For Improving The Quality Of Mobile User Experiences, Meena V

Theses and Dissertations

Nowadays, mobile applications have drawn a lot of attention as they bring computational and storage resources close to consumers globally through high-speed networks. Applications such as the medical microscope, 2D barcode reader, environmental sensor(s), mobile security and authenticator, vehicle remote controller, and IoT-based synchronizer come pre- applications are resource-intensive, as it performs computation(s) by utilizing diverse services like location, app-tracking, networking, camera, calendar, contacts, Bluetooth, etc. for each user activity. Parallel execution of such intense services might utilize the utmost memory and CPU of the mobile device which in turn degrades the overall Quality of Experience (QoE). This ultimately ends …

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Development And Simulation Of A Damage Assessment And Recovery Method For Critical Database Systems, Anthony Pham May 2024

Development And Simulation Of A Damage Assessment And Recovery Method For Critical Database Systems, Anthony Pham

Computer Science and Computer Engineering Undergraduate Honors Theses

With how much the world relies on technology and the critical database infrastructure that supports it, the infrastructures require efficient methods to detect and resolve suspicious database transactions, whether malicious or not. This paper focuses on an algorithm that detects and resolves malicious transactions in a database. The process begins with identifying suspicious transactions based on common patterns. When a transaction is flagged, the algorithm segments groups of suspicious transactions in separate log files, separating them for easy access. Within these segments, any dependent transactions that use data affected by the suspicious transactions will be stored there. After the transaction …

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Side Channel Detection Of Pc Rootkits Using Nonlinear Phase Space, Rebecca Clark May 2024

Side Channel Detection Of Pc Rootkits Using Nonlinear Phase Space, Rebecca Clark

Poster Presentations

Cyberattacks are increasing in size and scope yearly, and the most effective and common means of attack is through malicious software executed on target devices of interest. Malware threats vary widely in terms of behavior and impact and, thus, effective methods of detection are constantly being sought from the academic research community to offset both volume and complexity. Rootkits are malware that represent a highly feared threat because they can change operating system integrity and alter otherwise normally functioning software. Although normal methods of detection that are based on signatures of known malware code are the standard line of defense, …

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Investigating Autonomous Ground Vehicles For Weed Elimination, Abraham Mitchell May 2024

Investigating Autonomous Ground Vehicles For Weed Elimination, Abraham Mitchell

Computer Science and Computer Engineering Undergraduate Honors Theses

The management of weeds in crop fields is a continuous agricultural problem. The use of herbicides is the most common solution, but herbicidal resistance decreases effectiveness, and the use of herbicides has been found to have severe adverse effects on human health and the environment. The use of autonomous drone systems for weed elimination is an emerging solution, but challenges in GPS-based localization and navigation can impact the effectiveness of these systems. The goal of this thesis is to evaluate techniques for minimizing localization errors of drones as they attempt to eliminate weeds. A simulation environment was created to model …

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Enhancing Cybersecurity In Wireless Sensor Networks: Machine Learning, Blockchain And Future Perspectives, Ilemona Solomon Atawodi May 2024

Enhancing Cybersecurity In Wireless Sensor Networks: Machine Learning, Blockchain And Future Perspectives, Ilemona Solomon Atawodi

Dissertations

Security in the Industrial Internet of Things encounters various security issues but the main issues can be broken down into three core issues: Availability, Integrity, and Confidentiality. Security challenges generally tend to be caused by a failure of the system in one of these areas or cause a failure in one of these areas. Therefore researching scalable solutions to these security issues is prudent to explore methods that could be applied to large-scale industrial IIoT with tens to hundreds of devices as well as small-scale systems on a tiny factory floor comprising of just a few devices. In our research, …

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High-Altitude Ballooning And Payload Design, Matthew Smith May 2024

High-Altitude Ballooning And Payload Design, Matthew Smith

Honors College Theses

The Icarus project began in 2017 where a team performs high-altitude balloon (HAB) launches to conduct atmospheric and payload design research. The project involves sending a data-collecting payload containing recording equipment to high altitudes (~100,000 feet). This paper outlines the Icarus project as well as the efforts to design a payload that will remain stable throughout flight while also protecting the equipment housed within the payload shell. SOLIDWORKS computer-aided design (CAD) software was used to design a unique payload system. The payload parts were manufactured with PLA filament using a Prusa MK4 3D printer. The secondary goal of this thesis …

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Building A Wireless Electronic Control Unit For An Electric Vehicle, Hector S. Sosa May 2024

Building A Wireless Electronic Control Unit For An Electric Vehicle, Hector S. Sosa

2024 Spring Honors Capstone Projects - Archive

Modern vehicles have a variety of features such remote start systems, advance drive assist systems, smart suspension systems, and a feature rich infotainment system. With all this technology in the car, there exists a complex network of computers working together in conjunction to deliver the modern driving experience that many people have today. To be competitive in the market, auto manufacturers are tasked to add additional features to vehicles by adding additional or modifying electronic control units (ECUs). In this study, an ECU will be designed for a mock electric vehicle which contains an already established network of ECU’s. The …

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Navigate The World Of Rfid: Diversity, Capabilities, And Constraints Of Readers And Tags, Rachana Pandey May 2024

Navigate The World Of Rfid: Diversity, Capabilities, And Constraints Of Readers And Tags, Rachana Pandey

2024 Spring Honors Capstone Projects - Archive

Radio-Frequency Identification (RFID) technology, a method for storing and retrieving data through electromagnetic transmission to an RFID tag, is revolutionizing inventory and asset management in various sectors, including healthcare. This research explores the applications of RFID in a medical setting. It assesses various RFID readers and tags, focusing on their functional capabilities, ranges, and limitations within a medical environment. Employing a comprehensive approach, the study integrates an extensive literature review, comparative analysis, and empirical data from both experimental simulations and real-world healthcare scenarios. The aim is to identify RFID solutions that optimize surgical equipment management, thereby enhancing both operational efficiency …

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Effectivity Analysis Of Recommendation Algorithm: A Comparative Study Of The Performance Of A Hybrid Model And An Individual Recommendation Algorithm, Saniah Safat May 2024

Effectivity Analysis Of Recommendation Algorithm: A Comparative Study Of The Performance Of A Hybrid Model And An Individual Recommendation Algorithm, Saniah Safat

2024 Spring Honors Capstone Projects - Archive

This study explores the effectiveness of a hybrid recommendation system for e-commerce by integrating content-based, collaborative, and popularity-based models. Traditional individual algorithms have inherent limitations, such as handling new users or items data sparsity and ensuring relevance and diversity in suggestions. The hybrid model seeks to overcome these challenges by leveraging the strengths of all three methods, thus potentially offering more precise, personalized product suggestions. The performance of each model and its integration into a hybrid system are evaluated through logistic regression analysis. Initial results indicate that the hybrid system significantly outperforms the individual models in terms of accuracy and …

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Analysis Of Cnn Performance Utilizing Jpeg Compressed Images Created On An Fpga, Timothy Shaughnessy May 2024

Analysis Of Cnn Performance Utilizing Jpeg Compressed Images Created On An Fpga, Timothy Shaughnessy

All Theses

JPEG (Joint Photographic Experts Group) was formed in 1986 to create a method to reduce image size primarily for ease of transfer on the Internet. Released to the public in 1992, JPEG compression is a form of lossless compression that has been a staple for compressing images. JPEG is the go-to image compressor because it provides high compression ratios while maintaining visual integrity for the human eye. Growing image sizes have made JPEG compression increasingly relevant. It is vital to keep up with growing data sizes for improved image handling performance on an edge device like a Field-Programmable Gate Array …

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Bidding Strategy For A Wind Power Producer In Us Energy And Reserve Markets, Anne Stratman May 2024

Bidding Strategy For A Wind Power Producer In Us Energy And Reserve Markets, Anne Stratman

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Wind power is one of the world's fastest-growing renewable energy resources and has expanded quickly within the US electric grid. Currently, wind power producers (WPPs) may sell energy products in US markets but are not allowed to sell reserve products, due to the uncertain and intermittent nature of wind power. However, as wind’s share of the power supply grows, it may eventually be necessary for WPPs to contribute to system-wide reserves. This paper proposes a stochastic optimization model to determine the optimal offer strategy for a WPP that participates in the day-ahead and real-time energy and spinning reserve markets. The …

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