Computer Engineering Commons^™

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

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

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

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

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

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

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

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

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

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 …

Smart Robot Design And Implementation To Assist Pedestrian Road Crossing, Hovannes Kulhandjian

Mineta Transportation Institute

This research focuses on designing and developing a smart robot to assist pedestrians with road crossings. Pedestrian safety is a major concern, as highlighted by the high annual rates of fatalities and injuries. In 2020, the United States recorded 6,516 pedestrian fatalities and approximately 55,000 injuries, with children under 16 being especially vulnerable. This project aims to address this need by offering an innovative solution that prioritizes real-time detection and intelligent decision-making at intersections. Unlike existing studies that rely on traffic light infrastructure, our approach accurately identifies both vehicles and pedestrians at intersections, creating a comprehensive safety system. Our strategy …

A Study On Privacy Over Security And Privacy Enhancing Networks, Everett Lee Conway

Master's Theses

With rapid developments in communication technologies and awareness of security and privacy risks online, Security and Privacy Enhancing Networks (SPENs) have become increasingly popular. Especially during the COVID-19 pandemic, workplaces encouraged employees to take additional security measures, such as VPNs. In this work, we conduct a comprehensive study on website fingerprinting attacks. A comprehensive system model and threat model based on two types of SPENs (Virtual Private Networks and Tor Networks) are presented. Moreover, we demonstrate a website fingerprinting attack by ethically collecting website fetch data and analyzing the collected data using five different machine learning classification models including k …

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

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 …

Autonomous Apple Harvester Robot, Jack Ryan Cline, Tyus Green, Devon Woolston

Electrical Engineering

As agricultural demands rise and manual labor costs increase, there has become a dire need to automate apple harvesting. However, the precision and speed necessary for cost-efficient apple harvesting pose a significant challenge for robotic automation. To maintain cost-effective production, a harvester must be able to operate fast enough and long enough to compete with human labor. It must also be able to navigate and traverse apple orchards autonomously and pick apples without damaging the fruit or tree. This project presents an apple harvesting robot that uses a Mask R-CNN vision system with an RGB-D camera to detect the location …

Anomaly Detection In Heterogeneous Iot Systems: Leveraging Symbolic Encoding Of Performance Metrics For Anomaly Classification, Maanav Patel

Master's Theses

Anomaly detection in Internet of Things (IoT) systems has become an increasingly popular field of research as the number of IoT devices proliferate year over year. Recent research often relies on machine learning algorithms to classify sensor readings directly. However, this approach leads to solutions being non-portable and unable to be applied to varying IoT platform infrastructure, as they are trained with sensor data specific to one configuration. Moreover, sensors generate varying amounts of non-standard data which complicates model training and limits generalization. This research focuses on addressing these problems in three ways a) the creation of an IoT Testbed …

A Federation Of Sentries: Secure And Efficient Trusted Hardware Element Communication, Blake A. Ward

Master's Theses

Previous work introduced TrustGuard, a design for a containment architecture that allows only the result of the correct execution of approved software to be outputted. A containment architecture prevents results from malicious hardware or software from being communicated externally. At the core of TrustGuard is a trusted, pluggable device that sits on the path between an untrusted processor and the outside world. This device, called the Sentry, is responsible for validating the correctness of all communication before it leaves the system. This thesis seeks to leverage the correctness guarantees that the Sentry provides to enable efficient secure communication between two …

Sequential Memory Generation For Cognitive Models, Eben Miles Sherwood

Master's Theses

Understanding the process of memory formation in neural systems is of great interest in the field of neuroscience. Valiant’s Neuroidal Model poses a plausible theory for how memories are created within a computational context. Previously, the algorithm JOIN has been used to show how the brain could perform conjunctive and disjunctive coding to store memories. A limitation of JOIN is that it does not consider the coding of temporal information in a meaningful manner. We propose SeqMem, a similar algorithmic primitive that is designed to encode a series of items within a random graph model. We investigate the feasibility of …

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 …

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 …

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

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 …

The Journey To Desensitization: A Mobile App For Oral Immunotherapy Patients, Madeleine Waldie

Computer Science and Engineering Senior Theses

Millions of individuals in the United States confront the daily challenges of food allergies, with the threat of potentially life-threatening reactions ever-present. Oral Immunotherapy (OIT) emerges as a beacon of hope in this landscape, gradually desensitizing patients to their allergens. This groundbreaking treatment, contrasting avoidance strategies, promises a life with fewer restrictions. However, it is a journey fraught with complexities, requiring rigorous adherence to protocols, emotional fortitude, and frequent medical supervision for patients. This thesis centers on the creation of an iPhone application tailored to OIT patients, leveraging Apple’s privacy and security features. The app integrates seamlessly with the Apple …

Network Slicing And Noma Enabled Mobile Edge Computing For Next-Generation Networks, Mohammad Arif Hossain

Dissertations

The advent of next-generation wireless networks ushers in a new era of potential, harnessing cutting-edge technologies like mobile edge computing (MEC), non-orthogonal multiple access (NOMA), and network slicing as pivotal drivers of transformation. Within this landscape, an innovative approach is proposed by introducing a NOMA-enabled network slicing technique within MEC networks. This approach aims to achieve multiple objectives: meeting stringent quality of service requirements, minimizing service latency, and enhancing spectral efficiency. By seamlessly integrating NOMA with network slicing in edge computing environments, significant reductions in overall latency are achieved, alongside ensuring optimal resource allocation for NOMA users. To address these …

Integrating Laser Charging And Drones For Secure Edge Computing, Weiqi Liu

Dissertations

Drone-mounted base stations (DBSs) have emerged as a promising solution to enhance the flexibility and coverage of wireless networks, potentially revolutionizing communication systems. This dissertation explores the integration of DBSs into 5G and beyond networks, focusing on methodologies to optimize their deployment and performance. A laser charging-enabled DBS framework is proposed to extend flight time and enhance network coverage. By leveraging laser charging technology, the DBS can receive continuous energy transmission from a ground-based charging station while providing communication services to users. The framework is formulated as an optimization problem to jointly maximize flight time and communication data rate, while …

The Next Strike: Pioneering Forward-Thinking Attack Techniques With Rowhammer In Dram Technologies, Nakul Kochar

Theses

In the realm of DRAM technologies this study investigates RowHammer vulnerabilities in DDR4 DRAM memory across various manufacturers, employing advanced multi-sided fault injection techniques to impose attack strategies directly on physical memory rows. Our novel approach, diverging from traditional victim-focused methods, involves strategically allocating virtual memory rows to their physical counterparts for more potent attacks. These attacks, exploiting the inherent weaknesses in DRAM design, are capable of inducing bit flips in a controlled manner to undermine system integrity. We employed a strategy that compromised system integrity through a nuanced approach of targeting rows situated at a distance of two rows …

Expanding The Horizon: Blockchain Technology Beyond The Bounds Of Cryptocurrency, Hassan Azhar

SMU Data Science Review

Blockchain technology has extended beyond its initial role as the infrastructure for cryptocurrencies to transform various industries with its decentralized and transparent ledger system. This paper examines the broad spectrum of blockchain applications beyond cryptocurrency. It explores its potential to innovate and drive change across finance, supply chain management, healthcare, real estate, and voting systems. We review recent literature, detail specific use cases, and discuss blockchain's challenges and opportunities, aiming to provide a comprehensive overview of its transformative impact. Integrating emerging technologies, scalability, regulatory considerations, and energy consumption are critical challenges to its adoption. Our findings underscore the need for …

Protectnic - Smartnic Ransomware Detection, Arnav Choudhury, Eason Liu, Anson Xu

Computer Science and Engineering Senior Theses

Ransomware, a form of malware that restricts access to data until a ransom is paid, accounts for 20% of all cyber crimes. Although companies and organizations often require their personnel to take training for awareness of such bad actors, social engineering is constantly evolving and ransomware slips through the cracks every year. In this paper, we suggest a system that would help detect ransomware using a Smart Network Interface Card (SmartNIC) which runs machine learning algorithms to detect ransomware before it enters the system. This relieves computers in the network of the burden of detecting malware, freeing CPU capacity to …

Design Of Multi-Objective Optimization Algorithms For Vlsi Floor Planning, Srinivasan B

Theses and Dissertations

VLSI floorplanning is a key design step that determines the optimal placement of circuit modules to minimize chip area, wire length, and heat generation. Existing swarm intelligence–based metaheuristics improve area and wire length but often ignore thermal effects.

To address this, the Multi-Objective Firefly Optimization–based Floorplanning (MOFO-FP) technique is introduced, using a Heat-Aware Firefly Optimization (HAFO) algorithm that minimizes heat, space, and wire length under fixed outline constraints. Each firefly represents a floorplan, with brightness indicating solution quality; dimmer fireflies move toward brighter ones to find optimal placements.

A second method, the Hybridized Multicriteria Ant Colony and …