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Articles 2611 - 2640 of 25650
Full-Text Articles in Engineering
Scdi: Privacy-Preserving Device Identification, Ethan Shenassa, Michael Castillo
Scdi: Privacy-Preserving Device Identification, Ethan Shenassa, Michael Castillo
Computer Science and Engineering Senior Theses
As internet security concerns grow due to the increasing complexity of cyberattacks, heterogeneity of network-connected devices, and popularity of insecure Internet of Things (IoT) devices, network administrators require more intelligent ways of managing and securing their networks. One crucial step in this regard is the ability to identify and classify devices from the edge of networks. However, many recent advances in network security come at the cost of user privacy, as device classification algorithms often require packet payload data, Internet Protocol (IP) addresses, or other sensitive information. This paper proposes the Shenassa-Castillo Device Identifier (SCDI): a software network device identifier …
Deep Learning Based Single Image Super-Resolution, Samuel Smith
Deep Learning Based Single Image Super-Resolution, Samuel Smith
Computer Science and Engineering Senior Theses
Single image super-resolution (SR) involves taking a given low-resolution (LR) image and generating a corresponding high-resolution (HR) image. This is a core task in the computer vision field due to its multitude of applications ranging from helping current-day issues of storage and transfer of data to restoration of low-resolution images. The current strategies, however, struggle to reach the quality needed for their widespread use and are often too resource-intensive for the average consumer. While other lightweight SR techniques exist with different techniques, like Cascading Residual Networks [3], their success comes at the cost of expensive technology inaccessible to most situations. …
Distant Horizon: Exploring Human-Ai Interaction Through Video Games, Gabe Labadie, Dalia Suszko, Max White
Distant Horizon: Exploring Human-Ai Interaction Through Video Games, Gabe Labadie, Dalia Suszko, Max White
Computer Science and Engineering Senior Theses
As the field of Artificial Intelligence (AI) continues to grow and become more and more integrated into our everyday lives, it has begun to raise ethical concerns surrounding authority, autonomy, and responsibility. Researchers and consumers alike have begun to wonder how much trust we are willing to place in a non-human decision maker, especially if an Artificial General Intelligence (AGI) capable of surpassing human cognitive capabilities is ever developed. If we are willing to let an AI write essays for us, are we willing to let it manage a business? A government agency? What about a nuclear reactor?
Our project …
Daily Digest: A News Aggregation Site, Justin Wang, Jack Maguin, George Orloff, Justin Groves
Daily Digest: A News Aggregation Site, Justin Wang, Jack Maguin, George Orloff, Justin Groves
Computer Science and Engineering Senior Theses
A staggering amount of news articles are uploaded every day – approximately 5,000 in the United States alone [1]. That volume of information causes difficulty for many people who try to stay up-to-date with current events. The number of articles and the multitude of sources that they come from can feel overwhelming. In our project, we attempt to tackle this issue. We use web scraping to collect a dataset of news articles and combine it with a Large Language Model (LLM) capable of processing those articles to generate news summaries for the user. The user interacts with the program through …
General Purpose Tuning Data Visualization, Chris Augustine, Francisco Salinas, Aakash Shetty
General Purpose Tuning Data Visualization, Chris Augustine, Francisco Salinas, Aakash Shetty
Computer Science and Engineering Senior Theses
This project centers on the visualization of High-Performance Computing (HPC) data obtained from the GPTune website. GPTune serves as a valuable resource for HPC experiments, providing a wealth of performance data from tuning studies and optimization tasks. Our objective is to develop an advanced data visualization framework tailored to GPTune’s datasets. Utilizing state-of-the-art visualization techniques, we aim to create an interactive platform that allows users to explore, analyze, and derive insights from the diverse tuning experiments conducted on HPC systems. The visualization tool will facilitate the identification of optimal configurations, performance trends, and patterns within GPTune data, empowering researchers and …
Applied Auto-Tuning On Lora Hyperparameters, Darren Inouye, Lucas Lindo, Robin Lee, Edmund Allen
Applied Auto-Tuning On Lora Hyperparameters, Darren Inouye, Lucas Lindo, Robin Lee, Edmund Allen
Computer Science and Engineering Senior Theses
This senior design project explores the application of Bayesian optimization-based auto-tuning techniques on the low-rank adaptation (LoRA) fine-tuning of large language models (LLMs), demonstrating how fine-tuning methods can reduce training times and costs, albeit with a slight trade-off in accuracy. However, little is known about the optimal hyperparameters on LoRA and its variants for those methods. This project addresses this lack of knowledge by analyzing data gathered from auto-tuning LoRA hyperparameters to determine the most optimal parameter configurations for a model’s accuracy and training efficiency.
The team has implemented a pipeline utilizing many different technologies. The main technology driving the …
9-Axis Motion Tracking To Aid Therapeutic Recovery Via Visualization, Analysis And Progress Monitoring, Megan Wiser, Liam A'Hearn, Christopher Tamayo, Liam Kelly
9-Axis Motion Tracking To Aid Therapeutic Recovery Via Visualization, Analysis And Progress Monitoring, Megan Wiser, Liam A'Hearn, Christopher Tamayo, Liam Kelly
Computer Science and Engineering Senior Theses
This paper presents an innovative approach to enhance at-home physical therapy exercises through the development of a wearable motion tracking system. The proposed system utilizes motion tracking bands worn by patients during exercises, specifically focusing on a squat jump for the initial phase of the project. The bands, placed around the ankle and knee, monitor the alignment of the user's motion and transmit data via Bluetooth Low Energy (BLE) to a dedicated webpage. This webpage integrates real-time data analysis, offering immediate feedback to users, enabling them to monitor their form and track progress over time. The collected data is stored …
Hiv3: An Efficient Beehive Monitoring System, Jack Ursillo, Aneal Kuverji, Connor Merhab, Anshuman Sahu
Hiv3: An Efficient Beehive Monitoring System, Jack Ursillo, Aneal Kuverji, Connor Merhab, Anshuman Sahu
Computer Science and Engineering Senior Theses
Beehive monitoring plays a major role in ensuring the health of beehives by checking for overpopulation or underpopulation within a hive. Beehive monitoring provides beekeepers with the opportunity to take action and save the hive before the problem becomes irreversible. Most solutions are too expensive for everyday beekeepers and lack elements of sustainability, making it impractical for small scale beekeepers. In this thesis, we propose a solution to this problem, demonstrating its sustainability and user-friendliness, which enables us to effectively reach a larger consumer market. We support these claims through the use of sustainable systems such as using a solar …
Enhancing Vqgan-Based Model With Connext For Blind Super-Resolution, Lebin Zhou
Enhancing Vqgan-Based Model With Connext For Blind Super-Resolution, Lebin Zhou
Computer Science and Engineering Master's Theses
This thesis presents a novel super-resolution model based on Vector Quantized Generative Adversarial Network (VQGAN) to enhance image resolution. Inspired by recent advancements in the field of image reconstruction, we apply VQGAN to the super-resolution task, leveraging its powerful generative capabilities to produce higher quality high-resolution images.
Building on the VQGAN framework, we propose an improved architecture that incorporates an additional ConvNeXt feature extractor based on Convolutional Neural Networks (CNN) to effectively capture and refine features from low-resolution images. To further enhance model performance, we implemented various strategies to optimize the utilization of the codebook, including capacity optimization, improved initialization, …
Finding The Shortest Path Using Dijkstra’S Algorithm, Orit D. Gruber, Deborah Sturm
Finding The Shortest Path Using Dijkstra’S Algorithm, Orit D. Gruber, Deborah Sturm
Open Educational Resources
This lab experiment explores an algorithm which is used to find the shortest path between two or more locations. After completing the lab, you will be able to answer the following questions in the final lab report:
- What is an Algorithm?
- What is a Graph ?
- What is the purpose and operation of Dijkstra’s Algorithm ?
Ultra Low-Power, High-Performance Presence Detection System, Dante Bajarias, Cristian Medal, Jashan Kaeley
Ultra Low-Power, High-Performance Presence Detection System, Dante Bajarias, Cristian Medal, Jashan Kaeley
Computer Science and Engineering Senior Theses
The proliferation of Internet of Things (IoT) devices emphasizes a greater connection between humans and smart technology. From computer peripherals, personal electronics, and domestic appliances to building access management, healthcare, and security systems, modern applications are generating as much data or more than they are receiving from other sources. Human presence is a type of data that is becoming a compelling requirement for a plethora of today’s applications that must ensure seamless interactions of users with the systems and their associated services. The ultra low-power, high performance presence detection system is an accelerometer-based system capable of person detection, people counting, …
Edge-Connected Microcontroller Security, Divya Syal, Gavin Ryder, Neena Ekanathan
Edge-Connected Microcontroller Security, Divya Syal, Gavin Ryder, Neena Ekanathan
Computer Science and Engineering Senior Theses
With a wide range of applications and the rise of cyber attacks, securing microcontrollers has become imperative; however, ensuring microcontroller performance is also crucial given how interconnected today’s systems are. This project examines the security and performance of next-generation microcontroller units leveraging new security solutions for IoT edge applications. By benchmarking these MCUs against key performance metrics, their viability will be assessed to facilitate the widespread adoption of this latest firmware.
Our research focuses on profiling the power consumption and performance of the new STM32H573 and the integrated Secure Manager, a new technology from ST Microelectronics that allows for privileged …
Autonomous Microgrid System, Xavier Kuehn, Brian Xiong
Autonomous Microgrid System, Xavier Kuehn, Brian Xiong
Computer Science and Engineering Senior Theses
Microgrids have made a revolutionary change in the realm of energy distribution due to the features that they offer, including localized, resilient, and sustainable energy solutions. Operating renewable resources in a microgrid while maintaining generation-load balance and acceptable voltage-frequency limits has been an open research problem. This thesis presents smart python agents for microgrid systems to automate the operations and control of microgrid renewable resources in an effort to provide resilient solutions to the intermittence issues that could potentially arise within the microgrid energy system. The smart agents operate the microgrids by not only integrating the use of renewable energy …
Uhd: Unary Processing For Lightweight And Dynamic Hyperdimensional Computing, Mehran Shoushtari Moghadam, M. Hassan Najafi
Uhd: Unary Processing For Lightweight And Dynamic Hyperdimensional Computing, Mehran Shoushtari Moghadam, M. Hassan Najafi
Faculty Scholarship
Hyperdimensional computing (HDC) is a novel computational paradigm that operates on long-dimensional vectors known as hypervectors. The hypervectors are constructed as long bit-streams and form the basic building blocks of HDC systems. In HDC, hypervectors are generated from scalar values without considering bit significance. HDC is efficient and robust for various data processing applications, especially computer vision tasks. To construct HDC models for vision applications, the current state-of-the-art practice utilizes two parameters for data encoding: pixel intensity and pixel position. However, the intensity and position information embedded in high-dimensional vectors are generally not generated dynamically in the HDC models. Consequently, …
Enhanced Adaptive Image-Codebook Learning For Image Reconstruction, Yutong Ge
Enhanced Adaptive Image-Codebook Learning For Image Reconstruction, Yutong Ge
Computer Science and Engineering Master's Theses
In the field of image reconstruction and super-resolution, using codebooks has shown promising results despite various image degradations. Previous methods either use distinct codebooks for each image category or multiple codebooks per category, with the latter achieving better performance by capturing more nuanced image features. Our research proposes a novel method that employs enhanced sets of codebooks and weight maps tailored to each image category. These weight maps dynamically combine different codebook bases to adapt to various reconstruction tasks, resulting in improved image recognition and robustness. This approach significantly enhances the expressiveness and quality of reconstructed images, making it versatile …
E-Scooter Black Box, Soham Phadke, Suvass Ravala, Joshua Jerome, Raghav Batra, Mubashir Hussain
E-Scooter Black Box, Soham Phadke, Suvass Ravala, Joshua Jerome, Raghav Batra, Mubashir Hussain
Computer Science and Engineering Senior Theses
The burgeoning market for shared e-scooters is significantly hampered by the short lifespan of commercial e-scooters, which currently average just three months due to rough handling by users. To address this challenge, our project aims to extend the lifespan of shared e-scooters through an innovative onboard solution that discourages detrimental riding behaviors.
Our solution integrates a portable sensor hub from STMicroelectronics to capture ride data, which is then processed and sent via a user’s iOS app to a Google Firebase backend. A machine learning model running in the cloud analyzes the data to extract valuable metrics. These metrics are displayed …
Residual Transformer Unet For Medical Image Segmentation, Ruopu He
Residual Transformer Unet For Medical Image Segmentation, Ruopu He
Computer Science and Engineering Master's Theses
With the continuous development of deep learning theory in the field of medical images, information technology-assisted treatment methods represented by medical image segmentation technology can help doctors to quickly determine the shape and location of the lesions and improve the diagnosis efficiency of brain tumors. Based on deep learning technology, this thesis carries out related research work on MRI image segmentation. The main contents are as follows:
To begin with, acquire and prepare the brain tumor (MRI) image segmentation dataset from the official MICCAI Society website. This involves normalizing the images, cropping, and slicing, as well as scaling the data …
Comprehensive Network Redundancy Implementation And Cybersecurity Hardening Project: Ensuring Resilience And Defending Against Dhcp Starvation, Stp Man-In-The-Middle, And Brute Force Attacks, Seth Shaheen
Williams Honors College, Honors Research Projects
I have created a network topology that contains three Cisco routers, three Cisco switches, and three endpoints. The network has been built using the software GNS-3. The endpoints on the topology include one VPC, one Kali Linux VM, and one Ubuntu Server VM. The main purpose of this network topology is to show the skills I have learned during my tenure at The University of Akron. This will be done by hardening this network to ensure that the network is impervious to cyber-attacks. The Kali Linux VM will act as the attacker on the network and conduct three attacks: STP …
Exploring The Impact Of Artificial Intelligence On Project Management Across The Manufacturing, Technology, And Construction Industries, Susie Diaz Ferrera
Exploring The Impact Of Artificial Intelligence On Project Management Across The Manufacturing, Technology, And Construction Industries, Susie Diaz Ferrera
Harrisburg University Dissertations and Theses
This study explores the impact of Artificial Intelligence (AI) on project management across the manufacturing, technology, and construction industries. The research focuses on understanding the benefits, challenges, and long-term implications of AI utilization in these sectors. Key findings indicate that 46% of participants use AI mainly for task automation and enhancing functions like brainstorming and communication, which significantly boosts efficiency and team productivity. Despite these benefits, the research identifies several obstacles, including high initial costs, inadequate training, technical issues, and unclear regulatory guidelines. The study addresses four main questions, revealing that AI not only enhances project management processes but also …
Sustaining Digital Assets Through Mobile Estate Planning, Norliza Katuk, Asvinitha Muniandy, Norazlina Abd. Wahab, Ijaz Ahmad
Sustaining Digital Assets Through Mobile Estate Planning, Norliza Katuk, Asvinitha Muniandy, Norazlina Abd. Wahab, Ijaz Ahmad
An-Najah University Journal for Research - B (Humanities)
Many people own online accounts, with some having financial values like Internet banking, e-wallet and cryptocurrency. In the case of sudden death, their heirs are unaware of the digital assets possessed by the deceased person, which causes the assets to be lost forever, and the heirs might not receive the assets. If an estate plan did not account for digital assets properly, the beneficiaries would not be able to access them. Therefore, this paper addresses this issue by implementing a software development approach in designing a suitable model for sustaining digital assets through smartphones to allow the inheritance of digital …
Waypoint Profiler, Jeff Ke, Ricky Schober, Alexander Collins, Kevin Wang
Waypoint Profiler, Jeff Ke, Ricky Schober, Alexander Collins, Kevin Wang
Computer Science and Engineering Senior Theses
Ocean health monitoring is crucial for maintaining the health of the ocean ecosystem. Currently, divers are deployed to collect data manually, which is both time and resource-consuming. Additionally, this process poses significant dangers to the divers. Therefore, a more efficient method for collecting oceanic data is needed. This thesis describes the design of a novel autonomous marine vehicle, the waypoint profiler. Launched from shore with scientific sensors, it autonomously navigates to ocean locations of interest and dives to measure key ocean health markers. The system integrates subsystems for scientific sensing, health monitoring, structural integrity, communications, and navigation/control, tailored to meet …
Piloted Autonomous Crisis Reconnaissance Robot (Pacrr), Aidan O’Hare, Luca Chierotti, Tyler Costello, Nicholas Kenny
Piloted Autonomous Crisis Reconnaissance Robot (Pacrr), Aidan O’Hare, Luca Chierotti, Tyler Costello, Nicholas Kenny
Computer Science and Engineering Senior Theses
PACRR stands for Piloted/Autonomous Crisis Reconnaissance Robot. The aim of PACRR is to create a low-cost, autonomous-capable quadruped robot for first responder applications such as search and rescue, detecting gas leaks, mapping obstructed areas, and other situations that are dangerous or too confined for humans. The design process for PACRR involved the addition of perception sensors to use with a simultaneous localization and mapping (SLAM) algorithm, alterations to the power delivery system, adjusting the control of the robot, as well as other hardware and software modifications to an open-source 3D-printed design originally developed at Monash University called DINGO.
Nautilus: Deep Sea Dexterity, Quinn Bates, Saunder Salazar, Morgan Watts, Davis Robertson, Sarah Abruzzo, Ian Staff, Nick Aguilar
Nautilus: Deep Sea Dexterity, Quinn Bates, Saunder Salazar, Morgan Watts, Davis Robertson, Sarah Abruzzo, Ian Staff, Nick Aguilar
Computer Science and Engineering Senior Theses
Global warming and climate change are prevalent issues in today's society. As a result, research in the ocean, earth's biggest ecosystem, is imperative in efforts to protect the environment. Santa Clara University's Robotic Systems Lab contributes to this field through work and development on remotely operated vehicles (ROVs). Nautilus was built to support geologists and other researchers, primarily in the Lake Tahoe and Monterey Bay area. Thus far the ROV s sole scientific instrument has been its onboard camera, though partner geologists desire the ability to collect physical samples using a robotic arm attachment at depths up to 100 meters. …
Deep Learning-Based Video Prediction, Mareeta Mathai
Deep Learning-Based Video Prediction, Mareeta Mathai
Engineering Ph.D. Theses
The task of video prediction is to generate unseen future video frames based on the past ones. It is an emerging, yet challenging task due to its inherent uncertainty and complex spatiotemporal dynamics. The ability to predict and anticipate future events from video prediction has applications in various prediction systems like self-driving cars, weather forecasting, traffic flow prediction, video compression etc. Due to the success of deep learning in the computer vision field, several deep learning Artificial Intelligence (AI) architectures such as convolutional neural networks (CNNs), long short-term memory (LSTMs), convolutional LSTMS (ConvLSTMs) and transformers have been explored to improve …
Technocene, Vir Joseph Naidu
Technocene, Vir Joseph Naidu
Masters Theses
Embodied human communication within the Anthropocene. Existing at the intersection of technology, and the body.
The design industry has developed technology that is, paradoxically, isolating. The exposure to a vast audience in the digital sphere has introduced new societal pressures, leading to a disconnection from our immediate surroundings, detached, and donning metaphorical masks. Technocene lives on the fringes of the discipline by blending conceptual thinking with practical application. Through curious, experimental artifacts, it prompts us to shed our masks and embrace vulnerability. Technocene endeavors to reimagine the human experience by acting as a discursive design project. It probes the boundaries …
Drone Swarm Search And Rescue, Rushabh Shah, Christopher Short, Anderson Macmillan, Wyatt Colburn
Drone Swarm Search And Rescue, Rushabh Shah, Christopher Short, Anderson Macmillan, Wyatt Colburn
Electrical Engineering
Drone swarms offer the potential to drastically reduce search times and improve the effectiveness of search and rescue operations. This senior project explores the development of a drone swarm system for search and rescue missions, focusing on two key challenges: (1) precise localization of each drone within the swarm relative to one another and (2) accurate localization of a target beacon relative to the drones. The project utilizes Real Time Kinematic (RTK) processing to enhance the accuracy of drone localization, achieving centimeter-level precision. Target localization is achieved through a triangulation-based approach using Received Signal Strength Indication (RSSI) data from a …
A Comparative Study Of The Npm, Pypi, Maven, And Rubygems Open-Source Communities, Saurav Gupta
A Comparative Study Of The Npm, Pypi, Maven, And Rubygems Open-Source Communities, Saurav Gupta
Master's Theses
Open-source software (OSS) ecosystems, defined as environments composed of package managers and programming languages (e.g., NPM for JavaScript), are essential for software development and foster collaboration and innovation. Although their significance is acknowledged, understanding what makes OSS communities healthy and sustainable requires further exploration. This thesis quantitatively assesses the health of OSS projects and communities within the NPM, PyPI, Maven, and RubyGems ecosystems. We explore five research questions addressing project standards, community responsiveness, contribution distribution, contributor retention, and newcomer integration strategies. Our analysis shows varied documentation practices, insider engagement levels, and contribution patterns. Our findings highlight both strengths and different …
Masonry Column Analysis Through Python, Ali Sherief Saleh
Masonry Column Analysis Through Python, Ali Sherief Saleh
Architectural Engineering
This project serves as a study of Masonry Column Analysis and Design through the lens of the TMS 402 (22) Code: mimicking in-firm tools without using finite-element analysis. Chapter 9 of the TMS 402 (22) code provides the outline of the process taken to analyze these columns.
Investigation compares columns using the Python program to hand-calculations designs as to show additional capability that is lost due to approximation. PM-interaction for the columns is computed by a stress-strain approach. This report expands on the python design and approach to User Interface and inputs that are needed to analyze multiple datatypes with …
Communication Challenges In Underwater Wireless Networks: Mac Protocols And Software Solutions, Dmitrii Dugaev
Communication Challenges In Underwater Wireless Networks: Mac Protocols And Software Solutions, Dmitrii Dugaev
Dissertations, Theses, and Capstone Projects
Underwater wireless networks (UWNs) represent a diverse and intriguing research domain, encompassing a wide array of scientific and industrial applications. This dissertation delves into the communication challenges at the Medium Access Control (MAC) layer within UWNs, stemming from the distinctive signal propagation conditions and the harshness of the deployment environment. The manuscript provides comprehensive coverage of key aspects of UWNs, including potential applications, communication protocols, methodologies employed in such networks, and existing software solutions that facilitate simulation, emulation, and real testbed scenarios for underwater research endeavors. Furthermore, this research introduces innovative software and communication solutions designed to facilitate the seamless …
Poster: Towards Efficient Spatio-Temporal Video Grounding In Pervasive Mobile Devices, Dulanga Kaveesha Weerakoon Mudiyanselage, Vigneshwaran Subbaraju, Joo Hwee Lim, Archan Misra
Poster: Towards Efficient Spatio-Temporal Video Grounding In Pervasive Mobile Devices, Dulanga Kaveesha Weerakoon Mudiyanselage, Vigneshwaran Subbaraju, Joo Hwee Lim, Archan Misra
Research Collection School Of Computing and Information Systems
As the use of pervasive devices expands into complex collaborative tasks such as cognitive assistants and interactive AR/VR companions, they are equipped with a myriad of sensors facilitating natural interactions, such as voice commands. Spatio-Temporal Video Grounding (STVG), the task of identifying the target object in the field-of-view referred to in a language instruction, is a key capability needed for such systems. However, current STVG models tend to be resource-intensive, relying on multiple cross-attentional transformers applied to each video frame. This results in runtime complexity that increases linearly with video length. Furthermore, deploying these models on mobile devices while maintaining …