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 …

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 …

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, …

Multi-Domain Secure Dds Networks For Aerial And Ground Vehicle Communications, Daniel Pendleton

All Theses

none

4-Channel Spatially Multiplexed Communication System In Single-Core Optical Fibers, Ce Su

Theses and Dissertations

This dissertation delves into exploring and advancing spatial domain / space division multiplexing (SDM) technologies within single-core optical fibers, a frontier in optical fiber communications poised to meet the burgeoning global demand for data transmission. At the heart of this research is the pursuit to significantly enhance the capacity and efficiency of optical fiber communication systems without necessitating additional fiber infrastructure. This work unveils a new paradigm in optical fiber communications characterized by a pioneering 4-channel SDM system through a meticulous process encompassing theoretical modeling, computational simulations, design innovations, and rigorous experimental validations. Theoretical contributions include the development of refined …

Cloud Computing Integration Into Mixed-Reality: Physical To Abstraction, Yassine Chahid, Patrick Slattery

Publications and Research

This research evaluates the progression of cloud computing and mixed-reality technologies, and to identify how these technologies influence advancements in the latter. Both cloud computing and mixed reality have significantly impacted the IT field and the services available to the public and various institutions. Cloud computing provides a valuable way to process information or allocate computational resources on otherwise limited hardware. Augmented or virtual reality hardware would greatly benefit from this by offloading resource-intensive tasks to other machines. The research methodology involves analyzing essential components of both innovations, divided into multiple categories. These components range from physical, hardware-based elements to …

Detection Of Deficiencies And Data Analysis Of Bridge Members With Deep Convolutional Neural Networks, Bennett Jackson

Department of Civil and Environmental Engineering: Dissertations, Theses, and Student Research

Concrete cracks and structural steel corrosion are two of the most common defects in bridges. Quantifying and classifying these defects provide bridge inspectors and engineers with valuable data for assessing deterioration levels. However, the bridge inspection process is typically a subjective, time intensive, and tedious task, as defects can be overlooked or in locations not easily accessible. Previous studies have investigated deep learning-based inspection methods, implementing popular models such as Mask R-CNN and U-Net. The architectures of these models offer certain advantages depending on the required task. This thesis aims to evaluate and compare Mask R-CNN and U-Net regarding their …

Hybrid Method Neighbor Node Discovery In Wireless Sensor Networks: A Framework, Sagar Mekala, Shahu Chatrapati Kaila, Jyothi Rani Matang

Makara Journal of Technology

Wireless devices are now being adapted for diverse purposes, such as healthcare, agriculture, transportation, and tactical operations, which present challenges in network formation owing to high device mobility. Current methods rely on discovery techniques for forming wireless sensor networks (WSNs); however, the existing research has been criticized for its high time complexity and redundant neighbor discovery process. In this study, we provide a hybrid strategy to effectively handle the difficulties of locating neighboring nodes in WSNs. Our method combines several strategies to produce precise and effective neighbor detection. Herein, shared memory–based discovery, a beacon technique, and range and distance overlap …

The Next Threat Landscape: Securing America’S Cyber-Physical Systems, Grayson Thomas

Honors College Theses

The goal of this research is to explore, identify, and enumerate the security threats that exist to industry current industrial controls systems (ICS) and supervisory control and data acquisition systems (SCADA). A scale lab similar to industry standard will be built and developed for research purposes. The Purdue Model for ICS and the Cyber Kill Chain will be referenced as frameworks for attack sequences, and the MITRE ATT&CK framework will be referenced for attack types. Attempts will be made to compromise the various pieces of our built SCADA system via configuration errors, software vulnerabilities, and deployment mistakes common with industrial …

A Design Science Approach To Investigating Decentralized Identity Technology, Janelle Krupicka

Cybersecurity Undergraduate Research Showcase

The internet needs secure forms of identity authentication to function properly, but identity authentication is not a core part of the internet’s architecture. Instead, approaches to identity verification vary, often using centralized stores of identity information that are targets of cyber attacks. Decentralized identity is a secure way to manage identity online that puts users’ identities in their own hands and that has the potential to become a core part of cybersecurity. However, decentralized identity technology is new and continually evolving, which makes implementing this technology in an organizational setting challenging. This paper suggests that, in the future, decentralized identity …

Enhancing Cybersecurity Learning Efficiency: Leveraging Spaced Repetition Systems For Rapid Adaptation, Takudzwanashe Nyabadza

Research Week

No abstract provided.

Secure Cislunar Communication Architecture: Cryptographic Capabilities And Protocols For Lunar Missions, Michael Hamblin, Bilal Abu Bakr

Research Week

The surge in lunar missions intensifies concerns about congestion and communication reliability. This study proposes a secure cislunar architecture for real-time, cross-mission information exchange. We focus on cryptographic protocols and network design for a native IPv6 cislunar transit system.

Through a review of internet and space communication advancements, we emphasize the need for a secure network, exemplified by LunaNet. A robust data transit system with encryption is crucial for a common communication infrastructure. Traditional protocols face latency challenges. We advocate for user-friendly encryption methods to address confidentiality within the CIA Triad. Integrity is maintained through cryptographic message authentication codes. Availability …

Chatting With Online Agent, Guoxi Robert Zhang

Honors Theses

This study investigates trust in AI-generated language fluency. Participants engaged with both human and AI-generated content, varying in fluency. Findings were to favor trust in fluent human and AI interactions over disfluent ones. Understanding fluency's impact can inform AI design and encourage critical thinking when dealing with AI-generated content. By using qualitative analysis of think-aloud reports, we examined strategies that people use to assess texts labeled as human-generated and AI-generated content.

Cyber Attacks Against Industrial Control Systems, Adam Kardorff

LSU Master's Theses

Industrial Control Systems (ICS) are the foundation of our critical infrastructure, and allow for the manufacturing of the products we need. These systems monitor and control power plants, water treatment plants, manufacturing plants, and much more. The security of these systems is crucial to our everyday lives and to the safety of those working with ICS. In this thesis we examined how an attacker can take control of these systems using a power plant simulator in the Applied Cybersecurity Lab at LSU. Running experiments on a live environment can be costly and dangerous, so using a simulated environment is the …

The Impact Of Government Data Open Platform Construction On Promoting The Development Of Digital Government: An Econometric Analysis Based On Psm Model, Taitian Mao, Tang Gan, Jinliang Chen

Journal of Scientific Information Research

[Purpose/significance]Open government data is the direction of the digital development of government, and exploring the impact of the Open Government Data Platform （OGDP） on the development of digital government is of guiding significance in advancing the goal of modernizing the national governance system and governance capacity. [Method/process]Based on the establishment or not of OGDP, this paper uses the propensity score matching method to investigate the causal relationship between OGDP construction and digital government development by using the cross-sectional data of 101 prefecture-level cities across China in 2019 as the research sample for empirical analysis. [Result/conclusion]Overcoming sample selection bias and eliminating …

Objective.Gg: Uniting Scholastic Esports, Douglas Beirne

Posters - 2024

Objective.gg is a startup recruitment platform within the scholastic esports scene that seeks to unite esports prospects with collegiate esports programs in an effective manner. Objective.gg seeks to accomplish its mission by operating an online platform that allows prospects and collegiate coaches to create their own profiles and connect with one another, building a community in the process. This platform will begin with a free tier, but additional features will be offered through a subscription-based model with two additional pricing tiers to choose from. The online platform will be supported by free online and paid in-person tournaments for Objective.gg platform …

Performance Analysis Of Mobile Edge Computing Deployment Models In 5g Networks, Safaa Alali, Abdulkaim Assalem

Jerash for Research and Studies Journal مجلة جرش للبحوث والدراسات

5G networks and Mobile Edge Computing (MEC) are two main pillars of the next technological revolution. The first pillar provides ultra-reliable, high-bandwidth connectivity with ultra-low latency, while the second pillar gives mobile networks cloud computing capabilities at the edge of the network, enabling compute-dense, context-aware services for mobile users. So the next generation of mobile networks will see close integration between computing and communication. Therefore, it was necessary to study the different deployment options for edge hosts in 5G network, to know the effect of those options on the overall performance of the network. In this research, (Omnetpp 6.0) network …

Data-Driven Approaches For Enhancing Power Grid Reliability, Behrouz Sohrabi

Electronic Theses and Dissertations

This thesis explores the transformative potential of data-driven approaches in addressing key operational and reliability issues in power systems. The first part of this thesis addresses a prevalent problem in power distribution networks: the accurate identification of load phases. This study develops a data-driven model leveraging consumption measurements from smart meters and corresponding substation data to reconstruct topology information in low-voltage distribution networks. The proposed model is extensively tested using a dataset with more than 5,000 real load profiles, demonstrating satisfactory performance for large-scale networks. The second part of the thesis pivots to a crucial safety concern: the risk and …

Mmwave Rat Optimization: Mac Layer Initial Access Design And Transport Layer Integration, Suresh Srinivasan

Dissertations and Theses

MmWave Radio Access Technology (RAT) is a promising technology for wireless communication due its large bandwidth and is already being deployed in 5G cellular and emerging WiFi technologies. MmWave systems use highly directional beams with narrow beamwidths to overcome the high path loss associated with their frequency bands. A mmWave radio can be used either in a standalone mode (where all radios use the same technology) or simultaneously with other technologies such as LTE and low frequency WiFi in a communication mode commonly referred to as integrated mode. This thesis proposes two methods to optimize mmWave RAT performance in both …

Fair Fault-Tolerant Approach For Access Point Failures In Networked Control System Greenhouses, Mohammed Ali Yaslam Ba Humaish

Theses and Dissertations

Greenhouse Networked Control Systems (NCS) are popular applications in modern agriculture due to their ability to monitor and control various environmental factors that can affect crop growth and quality. However, designing and operating a greenhouse in the context of NCS could be challenging due to the need for highly available and cost-efficient systems. This thesis presents a design methodology for greenhouse NCS that addresses these challenges, offering a framework to optimize crop productivity, minimize costs, and improve system availability and reliability. It contributes several innovations to the field of greenhouse NCS design. For example, it recommends using the 2.4GHz frequency …

Adaptive Inter-Vehicular Collaboration For Level 5 Autonomous Driving, Sumbal Malik

Dissertations

The evolution of sensor technologies, mobile networks, and artificial intelligence has significantly expanded the horizons of various sectors, notably in autonomous driving. According to the World Health Organization, over 1.3 million people succumb to traffic accidents annually, predominantly due to human negligence. Complex urban environments, characterized by mixed traffic flow involving Human Driven Vehicles and Connected and Autonomous Vehicles, intricate traffic patterns, frequent lane changes, and slow speeds, face escalating challenges related to traffic accidents and congestion. These challenges lead to wasted time, increased fuel consumption, and heightened pollution emission levels. Hence, the development of a safe and robust version …

Tree Localization In A Plantation Using Ultra Wideband Signals, Akshat Verma

The Journal of Purdue Undergraduate Research

No abstract provided.

Securing Edge Computing: A Hierarchical Iot Service Framework, Sajan Poudel, Nishar Miya, Rasib Khan

Posters-at-the-Capitol

Title: Securing Edge Computing: A Hierarchical IoT Service Framework

Authors: Nishar Miya, Sajan Poudel, Faculty Advisor: Rasib Khan, Ph.D.

Department: School of Computing and Analytics, College of Informatics, Northern Kentucky University

Abstract:

Edge computing, a paradigm shift in data processing, faces a critical challenge: ensuring security in a landscape marked by decentralization, distributed nodes, and a myriad of devices. These factors make traditional security measures inadequate, as they cannot effectively address the unique vulnerabilities of edge environments. Our research introduces a hierarchical framework that excels in securing IoT-based edge services against these inherent risks.

Our secure by design approach prioritizes …

Motivations Driving Video Research Podcasts: Impact On Value And Creation Of Research Video Presentations, My Doan, Anh Tran, Na Le

Posters-at-the-Capitol

Abstract

Purpose: The purpose of the study is to better understand the role and impact of video research podcasts in bridging the gap between academia and the general public, especially concerning the challenges of accessibility and comprehension of scholarly research.

Methods: A 10-question survey was administered to evaluate the effectiveness, utility, and acceptance of video recordings in research presentations. The survey also aimed to gather insights into the motivations, challenges, and benefits of using video podcasts for research dissemination. Results were then analyzed using the Unified Theory of Acceptance and Use of Technology (UTAUT) model.

Results: There were 102 respondents …

Digital Phobia: An Inquiry For Mapping The Unseen Dimension Of New Digital Anxiety, The ‘Digiphobia’, Amarjit Kumar Singh ,Library Assistant, Md. Arshad Ali , Professional Assistant, Dr. Pankaj Mathur, Deputy Librarian,

Library Philosophy and Practice (e-journal)

Background: As technology continues to advance, individuals' interactions with digital platforms have become integral to daily life. Amidst this technological evolution, a novel concern emerges—Digital Phobia, hereafter referred to as “Digiphobia.” This phenomenon, although not previously explored in scholarly literature, necessitates an in-depth investigation due to its potential impact on individuals' well-being. Our research employs a two-step methodology to investigate its existence, implications, and manifestations.

Introduction: This research paper introduces and proposes the term "Digiphobia" as a comprehensive conceptualization of anxiety arising from interactions with digital spaces, applications, and environments. The proliferation of digital technologies has led to the emergence …

Alice In Cyberspace 2024, Stanley Mierzwa

Center for Cybersecurity

‘Alice in Cyberspace’ Conference Nurtures Women’s Interest, Representation in Cybersecurity

The Role Of Ai, Big Data And Predictive Analytics In Mitigating Unemployment Insurance Fraud, Siddikur Rahman, Md Abu Sayem, Shariar Emon Alve, Md Shahidul Islam, Muhammad Mahmudul Islam, Arifa Ahmed, Mohammed Kamruzzaman

Finance, Economics, and Data Analytics

The fraudulent claims for Unemployment Insurance (UI) have also risen massively in the United States especially during the onset of COVID-19 pandemic with billions of dollars that were lost. These approaches applied formerly in fraud detection and prevention have been challenged by new and advanced fraud systems. For this reason, AI, Big Data and Predictive Analytics are now crucial for improving fraud mitigation in UI programs. The aim of this research is to understand how far AI, Big Data and Predictive Analytics have been utilized, for how effective they are and the barriers they pose in tackling unemployment insurance fraud …

Ai And Workforce Development: A Comparative Analysis Of Skill Gaps And Training Needs In Emerging Economies, Gursahildeep Singh Sidhu, Md Abu Sayem, Nazifa Taslima, Ahmed Selim Anwar, Fariba Chowdhury, Manataka Rowshon

Finance, Economics, and Data Analytics

AI is developing quickly and offers considerable prospects for economic development; nevertheless, it presents crucial challenges for instance, skills development and its effect on employee's jobs in developing economies. This research will seek to establish the current state of AI related skills deficits and training in these economies to establish how governments and organizations can close the gaps by preparing the workforce for the future AI revolution. In line with the research questions, the following emerges as the research problem: To what extent have emerging market companies embraced AI? What key skills are scarce both in the internal and external …

Internet-Of-Things Privacy In Wifi Networks: Side-Channel Leakage And Mitigations, Mnassar Alyami

Graduate Thesis and Dissertation 2023-2024

WiFi networks are susceptible to statistical traffic analysis attacks. Despite encryption, the metadata of encrypted traffic, such as packet inter-arrival time and size, remains visible. This visibility allows potential eavesdroppers to infer private information in the Internet of Things (IoT) environment. For example, it allows for the identification of sleep monitors and the inference of whether a user is awake or asleep.

WiFi eavesdropping theoretically enables the identification of IoT devices without the need to join the victim's network. This attack scenario is more realistic and much harder to defend against, thus posing a real threat to user privacy. However, …

Streamlining Public Engagement In Transportation Projects Using Text Analytics, Alireza Shamshiri

Civil Engineering Dissertations - Archive

Infrastructure projects impact a broad range of stakeholders, particularly local communities, whose engagement is critical for successful outcomes. Despite the importance of public engagement in these projects, traditional methods of capturing and analyzing public opinion often fail to fully represent the diverse, genuine perspectives involved. This has led to conflicts between community members and project sponsors. On the other hand, despite advancements in text analytics, including natural language processing (NLP) and its subfields such as topic modeling, sentiment analysis, and neural networks, their functionalities and effectiveness in analyzing public opinion in the domain of infrastructure projects have not been fully …