Digital Commons Network^™

Open-Source Forensics Tools Are Great Tools For Critical Used Machines, Erik Herrera

Electronic Theses and Dissertations

Open-Source software exists on everything from operating systems to daily productivity applications. In digital forensics, a very popular tool that is used to learn on and expand is Autopsy. Autopsy is known in the digital world due to its potential and wide usage. It is in many built packages of software inside the open-source world of applications. It is built into premade operating systems that are involved in Digital Forensics and Penetration Testing. Prebuilt OS includes Kali Linux and Computer Aided Investigative Environment (CAINE).

In the application to defend Open-Source software being just as good as closed-source software, I will …

Enabling Iov Communication Through Secure Decentralized Clustering Using Federated Deep Reinforcement Learning, Chandler Scott

Electronic Theses and Dissertations

The Internet of Vehicles (IoV) holds immense potential for revolutionizing transporta- tion systems by facilitating seamless vehicle-to-vehicle and vehicle-to-infrastructure communication. However, challenges such as congestion, pollution, and security per- sist, particularly in rural areas with limited infrastructure. Existing centralized solu- tions are impractical in such environments due to latency and privacy concerns. To address these challenges, we propose a decentralized clustering algorithm enhanced with Federated Deep Reinforcement Learning (FDRL). Our approach enables low- latency communication, competitive packet delivery ratios, and cluster stability while preserving data privacy. Additionally, we introduce a trust-based security framework for IoV environments, integrating a central authority …

Trust, Transparency, And Transport: The Impact Of Privacy Protection On The Acceptance Of Last-Mile Drone Delivery, Jurgen Heinz Famula

Electronic Theses and Dissertations

A common set of problems commercial delivery companies face is finding ways to increase the efficiency and reliability of the “last mile” of a package’s journey, all while reducing operating costs. This need for efficiency has driven many companies to explore using unmanned aerial vehicles (UAVs), or drones, to get packages to their final destination. Although UAVs have great potential to help increase efficiency in commercial package delivery, this comes at a potential cost to the privacy of people who intersect the flight paths of these unmanned vehicles. This thesis explores the effect of a mobile phone application for commercial …

Towards A Pleasurable Food Experience: Influencing People's Liking, Taste Perceptions, And Mediated Emotions Using Augmented Flavor Experiences, Meetha Nesam James Ravindran Santhakumar

Electronic Theses and Dissertations

The multisensory nature of food and beverage flavors plays an integral role in our everyday lives. While eating is primarily for survival, individuals seek pleasure in their eating experiences through diverse means. Prior research has acknowledged that the experience of flavor is inherently multisensory, engaging the five basic senses (taste, smell, sight, touch, and hearing) and integrating additional sensory inputs(temperature, humidity, spatial smell, lighting, and even the visual and tactile characteristics of cutlery). To enhance the pleasure of consuming food and beverages, individuals consider various perceptual and cognitive factors, including the pleasure derived from taste sensations, overall hedonic liking of …

Human Perception Of Modern Light Field Rendered Displays: A Comparison Of A Lightfield And Headtracked Display System And Human Perception Of Animation Degradation Independent Of Render Frame Rate, Tim Bruce

Electronic Theses and Dissertations

This research directly compares natively head tracked spatial displays against actively head tracked ones. The belief is that by suppressing the latency, emulation of object presence can be improved. Modern Virtual Reality (VR) headset systems target 90Hz refresh rates in order to reduce tracking latency, yet with such low latencies, users still report motion sickness. Frame rates in film target 24-30Hz for smooth motion. This disconnect between frame rates for smooth motion and head tracking speed indicates that they may not be related. This thesis addresses these questions of latency and animation speed by building two display systems, a native …

Identification Of Conceptual Neighborhoods And Topological Relations In Z2, Brendan P. Hall

Electronic Theses and Dissertations

Topological relations are an essential element of spatial queries and reasoning about spatial information. The predominant model for topological relations in geographic information systems—the 9-intersection—identifies sixteen different relations between groups of pixels (called raster regions) given a set of conditions restricting the composition of the regions interior and boundary. Several of these relations are dependent on the raster region sizes to be realized. An example, ‘Completely Inside' would require raster regions to be sufficiently different in size for one raster to entirely encompass the other. By developing an iterative computational model, this work generates conceptual neighborhood graphs that outlined …

Detection And Classification Of Diabetic Retinopathy Using Deep Learning Models, Aishat Olatunji

Electronic Theses and Dissertations

Healthcare analytics leverages extensive patient data for data-driven decision-making, enhancing patient care and results. Diabetic Retinopathy (DR), a complication of diabetes, stems from damage to the retina’s blood vessels. It can affect both type 1 and type 2 diabetes patients. Ophthalmologists employ retinal images for accurate DR diagnosis and severity assessment. Early detection is crucial for preserving vision and minimizing risks. In this context, we utilized a Kaggle dataset containing patient retinal images, employing Python’s versatile tools. Our research focuses on DR detection using deep learning techniques. We used a publicly available dataset to apply our proposed neural network and …

Formalization Of A Security Framework Design For A Health Prescription Assistant In An Internet Of Things System, Thomas Rolando Mellema

Electronic Theses and Dissertations

Security system design flaws will create greater risks and repercussions as the systems being secured further integrate into our daily life. One such application example is incorporating the powerful potential of the concept of the Internet of Things (IoT) into software services engineered for improving the practices of monitoring and prescribing effective healthcare to patients. A study was performed in this application area in order to specify a security system design for a Health Prescription Assistant (HPA) that operated with medical IoT (mIoT) devices in a healthcare environment. Although the efficiency of this system was measured, little was presented to …

Using Dynamic Schemas For Query Optimization Over Json Data., Tomas Felipe Llano-Rios

Electronic Theses and Dissertations

Query optimization in document stores has traditionally relied on rule-based approaches, but recent research advocates for a shift towards cost-based optimization. However, this transition is hindered by the fragmented nature of existing approaches, stemming from the early development stage of cost-based query optimization for document databases. A key challenge lies in the absence of a standardized query language and semantics, exacerbated by the diverse and schema-less nature of JSON document collections. To tackle these challenges, the literature has proposed dynamic schemas, primarily utilized at parsing time. However, these schemas lack a formal foundation that describes meaningful semantics for query optimization. …

Multithreaded Applications On The Heterogeneous Research Computing Environment., Sungbo Jung

Electronic Theses and Dissertations

Bioinformatics is a domain that has experienced rapid research growth in recent years, as evidenced by the increasing number of articles in biomedical databases such as PubMed, which adds over a million publications every year. However, this also poses a challenge for researchers who need to find relevant citations for their work. Therefore, developing efficient indexing and searching methods for text data is crucial for Bioinformatics. One key technique for information retrieval is document inversion, which involves creating an inverted index to enable efficient searching through vast collections of text or documents. This Ph.D. research aims to design the research …

An Soa-Based Approach Of Adaptive E-Tutoring Systems, Parth Hetalkumar Mistry

Electronic Theses and Dissertations

The educational technology landscape continually evolves, and e-tutoring systems are pivotal in modern pedagogy. Traditional e-tutoring methods often need help with adaptability and user-friendliness across various devices and platforms. To address these challenges, this research introduces a novel approach that leverages service-oriented architecture (SOA) principles, enhancing scalability and flexibility. The SOA configuration streamlines communication between system components, optimizing question delivery and response evaluation. Additionally, the research contributes adaptive interfaces that intelligently engage users based on their device configurations and preferences, offering facial, vocal, or textual interactions. These interfaces ensure a consistent and tailored learning experience across PCs, laptops, and mobile …

Automatic Construction Of Ontology With Public-Domain Datasets For Personalized Tutoring With Eca, Asim Jamal

Electronic Theses and Dissertations

E-tutoring systems have transformed remote learning and personalized education, offering potent tools for tailored instruction. The core of a personalized tutor lies in its robust ontology and knowledge base, working seamlessly to deliver captivating educational experiences. These two integral components collaborate to empower the tutor to discern learners’ needs, adapt content accordingly, and provide tailored guidance. This study introduces an automated approach for constructing an ontology utilizing publicly accessible datasets, aiming to enhance personalized tutoring through Embodied Conversational Agents (ECA). The objective is to improve the tutoring encounter by delivering bespoke, domain-specific knowledge to learners. The approach harnesses natural language …

City Guarding With Cameras Of Bounded Field Of View, Mohammad Hashemi

Electronic Theses and Dissertations

We study two problems related to the City Guarding and the Art Gallery problems. 1. Given a city with k rectangular buildings, we prove that 3k+1 cameras of 180◦ field of view (half-sphere guards) are always sufficient to guard the free space (the ground, walls, roofs, and the sky). This answers a conjecture of Daescu and Malik (CCCG, 2020). 2. Given k orthogonally convex polygons of total m vertices in the plane, we prove that (m/2)+k+1 cameras of 180◦ field of view are always sufficient to guard the free space (avoiding all the polygons). This answers another conjecture of Daescu …

Xlnet4rec: Modeling User’S Long-Term And Short-Term Interests In E-Commerce Recommender Systems, Namarta Vij

Electronic Theses and Dissertations

In e-commerce, a sequential recommender system is often used to predict the item that the user is likely to select next. This prediction can be used to create a recommender system to assist the user in making selections. However, when the user’s interests evolve over time, it becomes challenging to make such personalized recommendations. A more accurate recommender system thus needs to effectively interpret and adapt to a user’s changing interests by considering user’s long-term and short-term interests. Many attention-based methods focus on a user’s last clicked item to learn short-term interests. However, this approach may not consistently represent the …

Knowledge Informed Fake News Detection Using Large Language Models, Jess Joseph Joseph Benny

Electronic Theses and Dissertations

The spread of false or misleading information as news has been a significant threat to governments, organizations and the economy for a long time. However, it has become more prevalent and influential in recent years due to the growing popularity of social media, which is now the primary source of information for more than half of the world’s population. Detecting fake news used to rely mostly on statistical and linguistic analysis of texts, but with the advancement of AI and computer-assisted writing tools, fake news authors can now deceive statistical models. Therefore, more sophisticated methods that use document representations from …

Adaptive Model Selection In Stock Market Prediction: A Modular And Scalable Big Data Analytics Approach, Mohammadehsan Akhavanpour

Electronic Theses and Dissertations

In today's globalized economy, financial markets are more interconnected than ever, generating vast amounts of data from thousands of sources every second. The need to accurately analyze and interpret this data is crucial for investors, analysts, and researchers alike. Traditional models for market prediction are limited by their ability to adapt to the real-time nature and 'big data' dimensions of these complex financial datasets. To address these challenges, this thesis proposes and implements a novel framework that combines Apache Kafka with a microservices framework. This framework offers a scalable, real-time solution for financial market prediction that effectively manages the 5Vs …

Railroad Condition Monitoring Using Distributed Acoustic Sensing And Deep Learning Techniques, Md Arifur Rahman

Electronic Theses and Dissertations

Proper condition monitoring has been a major issue among railroad administrations since it might cause catastrophic dilemmas that lead to fatalities or damage to the infrastructure. Although various aspects of train safety have been conducted by scholars, in-motion monitoring detection of defect occurrence, cause, and severity is still a big concern. Hence extensive studies are still required to enhance the accuracy of inspection methods for railroad condition monitoring (CM). Distributed acoustic sensing (DAS) has been recognized as a promising method because of its sensing capabilities over long distances and for massive structures. As DAS produces large datasets, algorithms for precise …

Assessing Performance Optimization Strategies In Cloud-Native Environments Through Containerization And Orchestration Analysis, Daniel E. Ukene

Electronic Theses and Dissertations

This thesis comprises three distinct, yet interconnected studies addressing critical aspects of web infrastructure management. We begin by studying containerization via Docker and its impact on web server performance, focusing on Apache and Nginx hosted on virtualized environments. Through meticulous load testing and analysis, we provide insights into the comparative performance of these servers, adding users of this technology know which webservers to leverage when hosting their webservice along alongside the infrastructure to host it on. Next, we expand our focus to examine the performance of caching systems, namely Redis and Memcached, across traditional VMs and Docker containers. By comparing …

Machine Learning Based Three-Limb Core-Type Transformer Core Aspect Ratios Identification, Ananta Bijoy Bhadra

Electronic Theses and Dissertations

Power transformers are considered one of the key elements of electric grids. Transient studies include transformer transient analysis which is required for the continuous power supply. However, to perform the transient analysis, the details of the internal structure of the transformer are required which are unobtainable and considered as confidential information. Therefore, the application of topological-based transformer models is limited although the models can accurately represent the transformers. To address this concern, a novel approach utilizing Machine Learning (ML) to identify the core aspect ratios of the three-limb core-type transformer is introduced. The proposed approach, using only the voltage and …

Reinforcement Learning: Applying Low Discrepancy Action Selection To Deep Deterministic Policy Gradient, Aleksandr Svishchev

Electronic Theses and Dissertations

Reinforcement learning (RL) is a subfield of machine learning concerned with agents learning to behave optimally by interacting with an environment. One of the most important topics in RL is how the agent should explore, that is, how to choose actions in order to rate their impact on long-term reward. For example, a simple baseline strategy might be uniformly random action selection. This thesis investigates the heuristic idea that agents will learn faster if they explore by factoring the environment’s state into their decision and intentionally choose actions which are as different as possible from what they have previously observed. …