Computer Sciences Commons^™

Cure Unity, Saisandesh Devireddy

All Capstone Projects

No abstract provided.

Smart Attendance Gui Application, Tushar Uppal

All Capstone Projects

The Smart Attendance GUI Application presents a cutting-edge approach to simplify attendance monitoring in workplaces and educational settings. This innovative solution incorporates face recognition technology to automate attendance, ensuring accuracy and efficiency. In situations where face recognition may not be suitable, the application offers a manual attendance entry option. The user-friendly graphical interface caters to individuals with varying technical proficiency, facilitating easy navigation. Beyond attendance tracking, the application includes features such as student registration, instructor data management, and an alert system to communicate attendance-related information to students. The utilization of this tool streamlines attendance tracking, making the process straightforward and …

Discovering Vulnerabilities And Designing Trustworthy Defenses In Iot Systems And Devices, Bryan Pearson

Electronic Theses and Dissertations, 2020-2023

Internet of Things (IoT) dominates many functions in the modern world, from sensing and reporting temperature, humidity, and air quality, to controlling and automating homes, commercial buildings, and equipment. However, IoT systems have received scrutiny in recent years due to countless security incidents, which can have physical and even deadly consequences. This research provides a comprehensive assessment of the security of IoT systems and devices, including low-cost microcontroller (MCU) based sensors, cloud services, and Building Automation Systems (BAS). We begin by exploring the current landscape of vulnerabilities and defenses in modern IoT applications. We show that many security needs can …

Fundraiser, Christopher Shivers

All Capstone Projects

Using the Fund Raiser, a web tool, event administrators and organizers may raise money from a variety of sources for various events they have listed. Therefore, a fund-raising effort might be used to develop various types of campaigns, gather money, and compile a list of contributors who made contributions in a visible timeline.

Finance plays a crucial part in everything from effectively arranging an event to giving financial relief to those who have been affected by various natural disasters. Therefore, Fund Raiser may serve as a facilitator for effectively generating money for various campaigns and support activities to promote and …

Campus Safety Data Gathering, Classification, And Ranking Based On Clery-Act Reports, Walaa F. Abo Elenin

College of Graduate Studies: Theses & Dissertations

Most existing campus safety rankings are based on criminal incident history with minimal or no consideration of campus security conditions and standard safety measures. Campus safety information published by universities/colleges is usually conceptual/qualitative and not quantitative and are based-on criminal records of these campuses. Thus, no explicit and trusted ranking method for these campuses considers the level of compliance with the standard safety measures. A quantitative safety measure is important to compare different campuses easily and to learn about specific campus safety conditions.

In this thesis, we utilize Clery-Act reports of campuses to automatically analyze their safety conditions and generate …

Application Of Big Data Technology, Text Classification, And Azure Machine Learning For Financial Risk Management Using Data Science Methodology, Oluwaseyi A. Ijogun

College of Graduate Studies: Theses & Dissertations

Data science plays a crucial role in enabling organizations to optimize data-driven opportunities within financial risk management. It involves identifying, assessing, and mitigating risks, ultimately safeguarding investments, reducing uncertainty, ensuring regulatory compliance, enhancing decision-making, and fostering long-term sustainability. This thesis explores three facets of Data Science projects: enhancing customer understanding, fraud prevention, and predictive analysis, with the goal of improving existing tools and enabling more informed decision-making. The first project examined leveraged big data technologies, such as Hadoop and Spark, to enhance financial risk management by accurately predicting loan defaulters and their repayment likelihood. In the second project, we investigated …

A Novel Approach To Detecting And Mitigating Keyloggers, Damilola Osedumbi Elelegwu

College of Graduate Studies: Theses & Dissertations

As the digital world gets increasingly ingrained in our daily lives, cyberattacks—especially those involving malware—are growing more complex and common, which calls for developing innovative safeguards. Keylogger spyware, which combines keylogging and spyware functionalities, is one of the most insidious types of cyberattacks. This malicious software stealthily monitors and records user keystrokes, amassing sensitive data, such as passwords and confidential personal information, which can then be exploited. This research work introduces a novel browser extension designed to thwart keylogger spyware attacks effectively. The extension is underpinned by a cutting-edge algorithm that meticulously analyzes input-related processes, promptly identifying and flagging any …

Material Extrusion-Based Additive Manufacturing: G-Code And Firmware Attacks And Defense Frameworks, Haris Rais

Theses and Dissertations

Additive Manufacturing (AM) refers to a group of manufacturing processes that create physical objects by sequentially depositing thin layers. AM enables highly customized production with minimal material wastage, rapid and inexpensive prototyping, and the production of complex assemblies as single parts in smaller production facilities. These features make AM an essential component of Industry 4.0 or Smart Manufacturing. It is now used to print functional components for aircraft, rocket engines, automobiles, medical implants, and more. However, the increased popularity of AM also raises concerns about cybersecurity. Researchers have demonstrated strength degradation attacks on printed objects by injecting cavities in the …

Inclusive Random Sampling In Graphs And Networks, Yitzchak Novick, Amotz Bar-Noy

Publications and Research

It is often of interest to sample vertices from a graph with a bias towards higher-degree vertices. One well-known method, which we call random neighbor or RN, involves taking a vertex at random and exchanging it for one of its neighbors. Loosely inspired by the friendship paradox, the method is predicated on the fact that the expected degree of the neighbor is greater than or equal to the expected degree of the initial vertex. Another method that is actually perfectly analogous to the friendship paradox is random edge, or RE, where an edge is sampled at random, and then one …

Adaptive Single Low-Light Image Enhancement By Fractional Stretching In Logarithmic Domain, Thaweesak Trongtirakul, Sos S. Agaian, Shiqian Wu

Publications and Research

Low-light image enhancement is a challenging task that aims to improve the visibility and quality of images captured in dark environments. However, existing methods often introduce undesirable artifacts such as color distortion, halo effects, blocking artifacts, and noise amplification. In this paper, we propose a novel method that overcomes these limitations by using the logarithmic domain fractional stretching approach to estimate the reflectance component of the image based on the improved Retinex theory. Moreover, we apply a simple adaptive gamma correction algorithm to the Lab color-space to adjust the brightness and saturation of the image. Our method effectively reduces the …

Optimising A Defence-Aware Threat Modelling Diagram Incorporating A Defence-In-Depth Approach For The Internet-Of-Things, Menaka L. Godakanda

Theses: Doctorates and Masters

Modern technology has proliferated into just about every aspect of life while improving the quality of life. For instance, IoT technology has significantly improved over traditional systems, providing easy life, time-saving, financial saving, and security aspects. However, security weaknesses associated with IoT technology can pose a significant threat to the human factor. For instance, smart doorbells can make household life easier, save time, save money, and provide surveillance security. Nevertheless, the security weaknesses in smart doorbells could be exposed to a criminal and pose a danger to the life and money of the household. In addition, IoT technology is constantly …

Modelling The Relationship Between Personality Traits And Basic Emotions: A Multi-Modal And Affective Computing Approach, Brendan Ryan Donovan

Theses

In the field of Psychology, it has long been assumed that one’s personality traits are linked to one’s emotional states. Yet there is a scarce amount of research that has directly quantified the relationships between basic emotional states and Big Five personality traits. Most empirical research has investigated how attributes of emotional states map to a narrow selection of personality traits (Extraversion and Neuroticism) via a single modality (questionnaires). This narrow focus restricts the field’s understanding of the relationship between emotional states and personality traits.

In this research, the Personality Emotion Mapping (PEM) model was developed to map the relationships …

Achieving High Map-Coverage Through Pattern Constraint Reduction, Yingquan Zhao, Zan Wang, Shuang Liu, Jun Sun, Junjie Chen, Xiang Chen

Research Collection School Of Computing and Information Systems

Testing multi-threaded programs is challenging due to the enormous space of thread interleavings. Recently, a code coverage criterion for multi-threaded programs called MAP-coverage has been proposed and shown to be effective for testing concurrent programs. Existing approaches for achieving high MAP-coverage are based on random testing with simple heuristics, which is ineffective in systematically triggering rare thread interleavings. In this study, we propose a novel approach called pattern constraint reduction (PCR), which employs optimized constraint solving to generate thread interleavings for high MAP-coverage. The idea is to iteratively encode and solve path conditions to generate thread interleavings which are guaranteed …

T-Counter: Trustworthy And Efficient Cpu Resource Measurement Using Sgx In The Cloud, Chuntao Dong, Qingni Shen, Xuhua Ding, Daoqing Yu, Wu Luo, Pengfei Wu, Zhonghai Wu

Research Collection School Of Computing and Information Systems

As cloud services have become popular, and their adoption is growing, consumers are becoming more concerned about the cost of cloud services. Cloud Service Providers (CSPs) generally use a pay-per-use billing scheme in the cloud services model: consumers use resources as they needed and are billed for their resource usage. However, CSPs are untrusted and privileged; they have full control of the entire operating system (OS) and may tamper with bills to cheat consumers. So, how to provide a trusted solution that can keep track of and verify the consumers’ resource usage has been a challenging problem. In this paper, …

Dashboard Design Mining And Recommendation, Yanna Lin, Haotian Li, Aoyu Wu, Yong Wang, Huamin Qu

Research Collection School Of Computing and Information Systems

Dashboards, which comprise multiple views on a single display, help analyze and communicate multiple perspectives of data simultaneously. However, creating effective and elegant dashboards is challenging since it requires careful and logical arrangement and coordination of multiple visualizations. To solve the problem, we propose a data-driven approach for mining design rules from dashboards and automating dashboard organization. Specifically, we focus on two prominent aspects of the organization: , which describes the position, size, and layout of each view in the display space; and, which indicates the interaction between pairwise views. We build a new dataset containing 854 dashboards crawled online, …

Champions For Social Good: How Can We Discover Social Sentiment And Attitude-Driven Patterns In Prosocial Communication?, Raghava Rao Mukkamala, Robert J. Kauffman, Helle Zinner Henriksen

Research Collection School Of Computing and Information Systems

The UN High Commissioner on Refugees (UNHCR) is pursuing a social media strategy to inform people about displaced populations and refugee emergencies. It is actively engaging public figures to increase awareness through its prosocial communications and improve social informedness and support for policy changes in its services. We studied the Twitter communications of UNHCR social media champions and investigated their role as high-profile influencers. In this study, we offer a design science research and data analytics framework and propositions based on the social informedness theory we propose in this paper to assess communication about UNHCR’s mission. Two variables—refugee-emergency and champion …

Identity-Based Edge Computing Anonymous Authentication Protocol, Naixin Kang, Zhenhu Ning, Shiqiang Zhang, Sadaqat Ur Rehman, Muhammad Waqas

Research outputs 2022 to 2026

With the development of sensor technology and wireless communication technology, edge computing has a wider range of applications. The privacy protection of edge computing is of great significance. In the edge computing system, in order to ensure the credibility of the source of terminal data, mobile edge computing (MEC) needs to verify the signature of the terminal node on the data. During the signature process, the computing power of edge devices such as wireless terminals can easily become the bottleneck of system performance. Therefore, it is very necessary to improve efficiency through computational offloading. Therefore, this paper proposes an identity-based …

A Geospatial Analysis Of Crime Hotspots, Campus Safety Measures, And The Campus Community’S Perceived Safety At Murray State University, Rachel Stuckey

Murray State Theses and Dissertations

Murray State University (Murray State) is in far Western Kentucky. Murray State prides itself on being a safe campus for prospective students. In this study spatial analysis was used to analyze the relationship among crime hotspots, campus safety measures, and students’ perception of safety on campus the campus of Murray State. A survey was distributed to students to determine the areas of the campus where students feel safe and unsafe. Geographical Information Systems (GIS) were used to determine the location of crime hotspots over eight years (2014-2022) to measure the spatial relationship between logged crime hotspots and perceived safe and …

Continual Learning-Based Optimal Output Tracking Of Nonlinear Discrete-Time Systems With Constraints: Application To Safe Cargo Transfer, Behzad Farzanegan, S. (Sarangapani) Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This Paper Addresses a Novel Lifelong Learning (LL)-Based Optimal Output Tracking Control of Uncertain Non-Linear Affine Discrete-Time Systems (DT) with State Constraints. First, to Deal with Optimal Tracking and Reduce the Steady State Error, a Novel Augmented System, Including Tracking Error and its Integral Value and Desired Trajectory, is Proposed. to Guarantee Safety, an Asymmetric Barrier Function (BF) is Incorporated into the Utility Function to Keep the Tracking Error in a Safe Region. Then, an Adaptive Neural Network (NN) Observer is Employed to Estimate the State Vector and the Control Input Matrix of the Uncertain Nonlinear System. Next, an NN-Based …

Lifelong Learning-Based Multilayer Neural Network Control Of Nonlinear Continuous-Time Strict-Feedback Systems, Irfan Ahmad Ganie, S. (Sarangapani) Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

In This Paper, We Investigate Lifelong Learning (LL)-Based Tracking Control for Partially Uncertain Strict Feedback Nonlinear Systems with State Constraints, employing a Singular Value Decomposition (SVD) of the Multilayer Neural Networks (MNNs) Activation Function based Weight Tuning Scheme. the Novel SVD-Based Approach Extends the MNN Weight Tuning to (Formula Presented.) Layers. a Unique Online LL Method, based on Tracking Error, is Integrated into the MNN Weight Update Laws to Counteract Catastrophic Forgetting. to Adeptly Address Constraints for Safety Assurances, Taking into Account the Effects Caused by Disturbances, We Utilize a Time-Varying Barrier Lyapunov Function (TBLF) that Ensures a Uniformly Ultimately …

Towards Robust Consensus For Intelligent Decision-Making In Iot Blockchain Networks, Charles Rawlins, S. (Sarangapani) Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

Distributed consensus is the core aspect of blockchain protocol security design. Recent protocols like IOTA have improved concurrency and scalability over Proof-of-work (PoW) with Bitcoin but have core design decisions that are inefficient for limited devices and do not take advantage of previous network experience to reduce calculations. This work proposes the first blockchain consensus protocol based on active machine-learning decisions, called Proof-of-history (PoH). PoH is setup as a distributed reinforcement-learning task for monitoring classification and training of blockchain transactions with an inner deep classifier. Early theoretical analysis and simulations show that PoH is robust to uncoordinated byzantine attacks through …

Continual Reinforcement Learning Formulation For Zero-Sum Game-Based Constrained Optimal Tracking, Behzad Farzanegan, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This study provides a novel reinforcement learning-based optimal tracking control of partially uncertain nonlinear discrete-time (DT) systems with state constraints using zero-sum game (ZSG) formulation. To address optimal tracking, a novel augmented system consisting of tracking error and its integral value, along with an uncertain desired trajectory, is constructed. A barrier function (BF) with a tradeoff factor is incorporated into the cost function to keep the state trajectories to remain within a compact set and to balance safety with optimality. Next, by using the modified value functional, the ZSG formulation is introduced wherein an actor–critic neural network (NN) framework is …

Optimal Tracking Of Nonlinear Discrete-Time Systems Using Zero-Sum Game Formulation And Hybrid Learning, Behzad Farzanegan, S. (Sarangapani) Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents a novel hybrid learning-based optimal tracking method to address zero-sum game problems for partially uncertain nonlinear discrete-time systems. An augmented system and its associated discounted cost function are defined to address optimal tracking. Three multi-layer neural networks (NNs) are utilized to approximate the optimal control and the worst-case disturbance inputs, and the value function. The critic weights are tuned using the hybrid technique, whose weights are updated once at the sampling instants and in an iterative manner over finite times within the sampling instants. The proposed hybrid technique helps accelerate the convergence of the approximated value functional …

Mapping The Focal Points Of Wordpress: A Software And Critical Code Analysis, Bryce Jackson

Electronic Theses and Dissertations, 2020-2023

Programming languages or code can be examined through numerous analytical lenses. This project is a critical analysis of WordPress, a prevalent web content management system, applying four modes of inquiry. The project draws on theoretical perspectives and areas of study in media, software, platforms, code, language, and power structures. The applied research is based on Critical Code Studies, an interdisciplinary field of study that holds the potential as a theoretical lens and methodological toolkit to understand computational code beyond its function. The project begins with a critical code analysis of WordPress, examining its origins and source code and mapping selected …

Identification And Modeling Social Media Influence Pathways: A Characterization Of A Disinformation Campaign Using The Flooding-The-Zone Strategy Via Transfer Entropy, Jasser Jasser

Electronic Theses and Dissertations, 2020-2023

The internet has made it easy for narratives to spread quickly and widely without regard for accuracy or the harm they may cause to society. Unfortunately, this has led to the rise of bad actors who use fake and misleading articles to spread harmful misinformation. These actors flood the information space with low-quality articles in an effort to disrupt opposing narratives, sow confusion, and discourage the pursuit of truth. In societies that prioritize free speech, maintaining control over the information space remains a persistent challenge. Achieving this requires strategic planning to protect the dissemination of information in ways that promote …

Inventions In The Area Of Nanotechnologies And Nanomaterials. Part I, Leonid A. Ivanov, Li Da Xu, Zhanna V. Pisarenko, Svetlana R. Muminova, Nadezda G. Miloradova

Information Technology & Decision Sciences Faculty Publications

Introduction. Advanced technologies inspire people by demonstrating the latest achievements (materials, methods, systems, technologies, devices etc.) that dramatically change the world. This, first of all, concerns nanotechnological inventions designed by scientists, engineers and specialists from different countries. Main part. The article provides an abstract overview of inventions of scientists, engineers and specialists from different countries: Germany, Russia, China, USA et al. The results of the creative activity of scientists, engineers and specialists, including inventions in the field of nanotechnology and nanomaterials allow, when introduced to industry, achieving a significant effect in construction, housing and communal services, and related sectors of …

“Any Means Necessary To Refuse Erasure By Algorithm:” Lillian-Yvonne Bertram’S Travesty Generator, Zach Whalen

Communication & Digital Studies Articles

Lillian-Yvonne Bertram's 2019 book of poetry is titled Travesty Generator in reference to Hugh Kenner and Joseph O'Rourke's Pascal program to “fabricate pseudo-text” by producing text such that each n-length string of characters in the output occurs at the same frequency as in the source text. Whereas for Kenner and O'Rourke, labeling their work a “travesty” is a hyperbolic tease or a literary burlesque, for Bertram, the travesty is the political reality of racism in America. For each of the works Travesty Generator, Bertram uses the generators of computer poetry to critique, resist, and replace narratives of oppression and to …

Pmp: Privacy-Aware Matrix Profile Against Sensitive Pattern Inference, Li Zhang, Jiahao Ding, Yifeng Gao, Jessica Lin

Computer Science Faculty Publications

Recent rapid development of sensor technology has allowed massive fine-grained time series (TS) data to be collected and set the foundation for the development of data-driven services and applications. During the process, data sharing is often involved to allow the third-party modelers to perform specific time series data mining (TSDM) tasks based on the need of data owner. The high resolution of TS brings new challenges in protecting privacy. While meaningful information in high-resolution TS shifts from concrete point values to local shape-based segments, numerous research have found that long shape-based patterns could contain more sensitive information and may potentially …

Prediction Of Kinase-Substrate Associations Using The Functional Landscape Of Kinases And Phosphorylation Sites, Marzieh Ayati, Serhan Yılmaz, Filipa Blasco Tavares Pereira Lopes, Mark R. Chance, Mehmet Koyutürk

Computer Science Faculty Publications

Protein phosphorylation is a key post-translational modification that plays a central role in many cellular processes. With recent advances in biotechnology, thousands of phosphorylated sites can be identified and quantified in a given sample, enabling proteome-wide screening of cellular signaling. However, for most (> 90%) of the phosphorylation sites that are identified in these experiments, the kinase(s) that target these sites are unknown. To broadly utilize available structural, functional, evolutionary, and contextual information in predicting kinase-substrate associations (KSAs), we develop a network-based machine learning framework. Our framework integrates a multitude of data sources to characterize the landscape of functional relationships …

An Experiment On The Effects Of Using Color To Visualize Requirements Analysis Tasks: Supplemental Material, Yesugen Baatartogtokh, Irene Foster, Alicia M. Grubb

Computer Science: Faculty Publications

Supplemental material for the paper: "An Experiment on the Effects of using Color to Visualize Requirements Analysis Tasks".
This paper is a scientific evaluation of the effectiveness and usability of EVO. We conduct an experiment to measure any effect of using colors to represent evidence pairs.