Engineering Commons^™

Mechanisms Linking The Circadian Clock To Cardiac Physiology, Lamario J. Williams

All ETDs from UAB

Rationale: Cardiovascular disease continues to be the leading cause of death in America. Many aspects of both cardiovascular physiology (e.g., blood pressure, heart rate) and pathophysiology (e.g., myocardial infarctions, sudden cardiac death) exhibit time-of-day dependent fluctuations (termed diurnal variations). Circadian clocks consist of transcriptional feedback cascades directly modulating expression of genes involved in processes such as metabolism, signaling, and ion transport. Interestingly, genetic deletion of a core circadian clock component in the heart (cardiomyocyte-specific Bmal1 knockout mice) leads to chronic induction of the transcriptional repressor E4 Promoter-Binding Protein 4 (E4BP4) associated with early-onset dilated cardiomyopathy, metabolic inflexibility, and electrophysiologic disturbances. …

Analysis Of Correlation Between Molecular Weight Distribution And Melt Flow Index Of Polyethylene And Polypropyle Blends, Ethan Stonecipher

All ETDs from UAB

Recycling of plastics is one of the biggest challenges facing the earth in the 21st century due to the environmental impact they have on the waste stream. One of the biggest challenges in the recycling of these materials are their incompatibility; therefore, the segregation of waste in order to repurpose them back into something useful for a second life is an important barrier to overcome. This study expands on work done in literature to correlate rheological properties of linear virgin plastics to their ��w, which is useful in deducing some mechanical behaviors of the material. The benefit being the impact …

Enhancing Community Resiliency With Big Data And Machine Learning: Property Damage And Flood Forecasting During Hurricanes, Mujungu Lawrence Museru

All ETDs from UAB

Globally, coastal communities face significant vulnerability to the risks and impacts of flooding. This study addresses two critical aspects of flood management: enhanced flood damage assessment and coastal flooding prediction. Traditional flood damage modeling techniques have limitations, and the availability of comprehensive datasets is limited. The first part addresses these challenges. Multivariable machine learning models are applied to enhance flood damage assessment. A comprehensive dataset is developed by combining the Alabama property dataset with the National Flood Insurance Program (NFIP) claims dataset from Hurricane Katrina. Spatial varying datasets are added to enhance the comprehensiveness of NFIP dataset and oversampling techniques …

The Effects Of Alzheimer's Disease-Associated Variants And Ligands On The Structure And Function Of Trem2, Hunter Byron Dean

All ETDs from UAB

Alzheimer’s disease (AD) is a devastating, complex form of dementia. Contributions from genetics make up almost 70% of a person’s risk of developing AD, but the mechanisms by which this occurs are not well understood. Attempts to tease apart the risk contributions from individual genes have identified lipid processing and activation of innate immunity as convergent pathways for many of the known genetic risk factors. One of the strongest known risk factors, TREM2, codes for a transmembrane receptor that activates a protective immune response when it detects bound lipids. Variants in TREM2 that control AD risk have been identified, but …

Unveiling The Commuting Experience Of An Urban University Community, Jannatul Adan Joarder

All ETDs from UAB

Conducting a comprehensive commuter survey is a prevalent task that can help to guide traffic operations, planning, designing, and infrastructure development decision. It is one of the best approaches to comprehending commuters’ attitudes and preferences and the present commuting practices. The commuting behavior of the commuters at and around a university campus varies from that of residential or commercial areas as the university often serves a diverse community of transportation users such as students, faculty, and staff who serve the university or receive services from the university in a variety of ways. The University of Alabama at Birmingham (UAB) is …

Improved Myocardial Infarct Repair Via Cardiac Tissue Engineering And Modified Rna, Lu Wang

All ETDs from UAB

Cardiovascular diseases remain the leading cause of death in the United States and the world. Myocardial infarction (MI) happens when there is an occlusion in the blood vessel. Cardiomyocytes (CM) die quickly after MI and are replaced by a fibrotic scar. Since adult mammalian cardiomyocytes have a limited capacity to regenerate, the damages induced by MI usually deteriorate into more severe symptoms such as heart failure. In order to achieve regeneration of the cardiomyocytes, numerous therapies have been proposed, including cellular therapy and CM cell cycle re-entry. During this dissertation study, we focused on improving myocardial infarct repair via cardiac …

Automated Structural Health Monitoring Of Pavements Using Google Street View Images, Ebisidor Jeremiah Agberebi

All ETDs from UAB

The Department of Transportation traditionally employed a structural health monitoring approach that involved training personnel to report the existing conditions of roadways. However, this approach is accompanied by huge costs that range from onboarding, vehicular equipment & maintenance cost, environmental costs from CO2 emission, safety costs, and the cost of errors made by personnel as each inspector would exercise his/ her discretion in analyzing the condition of the roadway. Therefore, it is necessary to adopt a more efficient and effective approach to SHM. The incorporation of google street view images [‘GSV’ a Google roadway street data repository, with high-resolution images], …

Breast Cancer Metastasic Potential Mediated By Cd44/Hyaluronic Acid Signaling And Strains In The Tumor Microenvironment, Adam David Kotar

All ETDs from UAB

Mechanical stimulation has been found to be an important regulator of nearly all biological processes, from maintaining normal homeostatic conditions to promoting pathological mechanisms of multiple diseases including cancer. While our knowledge of cancer continues to grow, our current models often lack the biophysical forces that are present in the body which could explain why numerous promising therapeutic agents discovered in research fail to translate into clinical efficacy. This study aims to demonstrate that breast cancer progression is mediated by strains in the tumor microenvironment (TME) in conjunction with trans-membranous glycoprotein receptor, CD44. There are many different sources of strain …

Creating Cool And Equitable Communities: A Comprehensive Study On Urban Heat Island Mitigation And Health Equity In Birmingham, Alabama, Bhuvana Sai Kumar Yandra

All ETDs from UAB

Abstract: Urban Heat Islands (UHIs) represent a severe hazard to people's health and quality of life, particularly in areas of cities with dense and at-risk populations. This integrative research aims to reduce the burden of UHIs caused by climate change and mitigate associated health risks and inequalities in Birmingham, Alabama. The study identifies areas most impacted by UHI effects and loss of vegetation and provides remediation strategies to combat these issues. In addition, the research expands to identify socioeconomically disadvantaged and health-vulnerable communities needing intervention to improve their quality of life. Urban Heat Islands (UHIs) trap heat, alter local climates …

Implications Of Physical Fault Injections On Single Chip Motes, Sara Faour, Mališa Vučinić, Filip Maksimovic, David Burnett, Paul Muhlethaler, Thomas Watteyne, Kristofer Pister

Electrical and Computer Engineering Faculty Publications and Presentations

Single-chip motes are wireless sensor nodes that integrate computation, communication, power and sensing on a single chip. We consider the security threats these novel devices are subject to when employed in safety-critical applications. Fault injection attacks are a prominent form of physical attacks that pose a threat to the normal and secure functioning of targeted devices, potentially compromising their intended behavior. These attacks have been studied mainly on commercial off-the-shelf devices which rely on external components such as crystal oscillators and passives. Such external components are absent from single-chip motes, resulting in a uniquely different attack surface compared to commercial …

Synthesis Of N-Doped Tio2 Nanoparticles With Enhanced Photocatalytic Activity For 2,4-Dichlorophenol Degradation And H2 Production, Javed Ali Khan, Murtaza Sayed, Noor S. Shah, Sanaullah Khan, Ashfaq Ahmad Khan, Muhammad Sultan, Ammar M. Tighezza, Jibran Iqbal, Grzegorz Boczkaj

All Works

Nitrogen-doped titanium dioxide (N-TiO2) nanoparticles were prepared using a modified sol-gel method. The as-prepared nanoparticles were characterized by state-of-the-art techniques for their optical, structural and morphological properties. The crystallite size, surface area and bandgap energy of reference TiO2 and N-TiO2 nanoparticles were found to be 16.1 and 10.9nm, 83.6 and 131.8 m2 g−1 and 3.23 and 2.89eV, respectively. The photocatalytic activities, in terms of 2,4-dichlorophenol (2,4-DCP) degradation, of reference TiO2 and N-TiO2 were found to be 46.9 and 65.4% at 120min of treatments under UV light irradiation and 21.5 and 77.6% at 240min of treatment under visible light irradiation, employing …

Investigation Of Additives And Ingredients Of Bio-Resin For Visible Wavelength Laser-Induced Polymerization, Patrick Riggs

College of Graduate Studies: Theses & Dissertations

Optical 3D printing is a branch of Additive manufacturing (AM) that utilizes low-waste production leading to efficient and rapid prototyping. Currently, this method of AM is associated with mainly petroleum-based resins. Bio-resin polymerization is an emerging research area for finding replacements for petroleum-based resins, but curing the resin with laser energy is not normally a practical use case. Current optical 3D printing uses lasers to cure liquid resins to form solid 3D objects in a layer-by-layer process which is time consuming, defect prone, and a leading limiting factor for high volume production; so, finding a way to incorporate bio-resin into …

Understanding The Feasibility Of Improving Interfacial Properties In Direct Ink Writing Of Silicone-Polyurethane Resin Hybrid Material, Ayobami Samuel Akinfenwa

College of Graduate Studies: Theses & Dissertations

The progress in materials engineering and the ability to make various models possible have made soft robotics a popular alternative to traditional robotics. Still, soft robots need various parts, like Printed Circuit Boards (PCBs), batteries, cables, fittings, and more, to work correctly or to get attached to other complex parts. These parts can have different material properties, like elastic moduli, strength, etc. Because of these differences, mechanical failures happen at the points where two materials meet, making soft robots less durable and less lasting in real-life situations due to failure. Conventionally, the fabrication of soft robot parts is through moulding. …

Tutorial - Shodhguru Labs: Knowledge-Infused Artificial Intelligence For Mental Healthcare, Kaushik Roy

Publications

Artificial Intelligence (AI) systems for mental healthcare (MHCare) have been ever-growing after realizing the importance of early interventions for patients with chronic mental health (MH) conditions. Social media (SocMedia) emerged as the go-to platform for supporting patients seeking MHCare. The creation of peer-support groups without social stigma has resulted in patients transitioning from clinical settings to SocMedia supported interactions for quick help. Researchers started exploring SocMedia content in search of cues that showcase correlation or causation between different MH conditions to design better interventional strategies. User-level Classification-based AI systems were designed to leverage diverse SocMedia data from various MH conditions, …

Dfhic: A Dilated Full Convolution Model To Enhance The Resolution Of Hi-C Data, Bin Wang, Kun Liu, Yaohang Li, Jianxin Wang

Computer Science Faculty Publications

Motivation: Hi-C technology has been the most widely used chromosome conformation capture(3C) experiment that measures the frequency of all paired interactions in the entire genome, which is a powerful tool for studying the 3D structure of the genome. The fineness of the constructed genome structure depends on the resolution of Hi-C data. However, due to the fact that high-resolution Hi-C data require deep sequencing and thus high experimental cost, most available Hi-C data are in low-resolution. Hence, it is essential to enhance the quality of Hi-C data by developing the effective computational methods.

Results: In this work, we propose …

Hashes Are Not Suitable To Verify Fixity Of The Public Archived Web, Mohamed Aturban, Martin Klein, Herbert Van De Sompel, Sawood Alam, Michael L. Nelson, Michele C. Weigle

Computer Science Faculty Publications

Web archives, such as the Internet Archive, preserve the web and allow access to prior states of web pages. We implicitly trust their versions of archived pages, but as their role moves from preserving curios of the past to facilitating present day adjudication, we are concerned with verifying the fixity of archived web pages, or mementos, to ensure they have always remained unaltered. A widely used technique in digital preservation to verify the fixity of an archived resource is to periodically compute a cryptographic hash value on a resource and then compare it with a previous hash value. If the …

Assessing The Performance Of A Particle Swarm Optimization Mobility Algorithm In A Hybrid Wi-Fi/Lora Flying Ad Hoc Network, William David Paredes

UNF Graduate Theses and Dissertations

Research on Flying Ad-Hoc Networks (FANETs) has increased due to the availability of Unmanned Aerial Vehicles (UAVs) and the electronic components that control and connect them. Many applications, such as 3D mapping, construction inspection, or emergency response operations could benefit from an application and adaptation of swarm intelligence-based deployments of multiple UAVs. Such groups of cooperating UAVs, through the use of local rules, could be seen as network nodes establishing an ad-hoc network for communication purposes.

One FANET application is to provide communication coverage over an area where communication infrastructure is unavailable. A crucial part of a FANET implementation is …

Evaluating Human Eye Features For Objective Measure Of Working Memory Capacity, Yasasi Abeysinghe, Enkelejda Kasneci (Ed.), Frederick Shic (Ed.), Mohamed Khamis (Ed.)

Computer Science Faculty Publications

Eye tracking measures can provide means to understand the underlying development of human working memory. In this study, we propose to develop machine learning algorithms to find an objective relationship between human eye movements via oculomotor plant and their working memory capacity, which determines subjective cognitive load. Here we evaluate oculomotor plant features extracted from saccadic eye movements, traditional positional gaze metrics, and advanced eye metrics such as ambient/focal coefficient , gaze transition entropy, low/high index of pupillary activity (LHIPA), and real-time index of pupillary activity (RIPA). This paper outlines the proposed approach of evaluating eye movements for obtaining an …

Inclusion4eu: Co-Designing A Framework For Inclusive Software Design And Development, Dympna O'Sullivan, Emma Murphy, Andrea Curley, John Gilligan, Damian Gordon, Anna Becevel, Svetland Hensman, Mariana Rocha, Claudia Fernandez, Michael Collins, J. Paul Gibson, Gordana Dodig-Crnkovic, Gearoid Kearney, Sarah Boland

Articles

Digital technology is now pervasive, however, not all groups have uniformly benefitted from technological changes and some groups have been left behind or digitally excluded. Comprehensive data from the 2017 Current Population Survey shows that older people and persons with disabilities still lag behind in computer and internet access. Furthermore unique ethical, privacy and safety implications exist for the use of technology for older persons and people with disabilities and careful reflection is required to incorporate these aspects, which are not always part of a traditional software lifecycle. In this paper we present the Inclusion4EU project that aims to co-design …

Survey Of Routing Techniques-Based Optimization Of Energy Consumption In Sd-Dcn, Mohammed Nsaif, Gergely Kovásznai, Ali Malik, Ruairí De Fréin

Articles

The increasing power consumption of Data Center Networks (DCN) is becoming a major concern for network operators. The object of this paper is to provide a survey of state-of-the-art methods for reducing energy consumption via (1) enhanced scheduling and (2) enhanced aggregation of traffic flows using Software-Defined Networks (SDN), focusing on the advantages and disadvantages of these approaches. We tackle a gap in the literature for a review of SDN-based energy saving techniques and discuss the limitations of multi-controller solutions in terms of constraints on their performance. The main finding of this survey paper is that the two classes of …

Governance-Aware Cloud Architectures For Enterprise Information Systems, Manikantha Varaprasad Inakollu

Computer Science and Engineering Faculty Publications

Enterprise cloud adoption has accelerated dramatically, yet governance frameworks struggle to keep pace with evolving architectural complexity. This research examines how organizations can embed governance principles directly into cloud architecture designs rather than treating compliance as an afterthought. We investigate the integration of regulatory requirements, risk management protocols, and organizational policies into cloud infrastructure patterns that enforce governance automatically. The study addresses critical gaps where traditional governance approaches fail in dynamic cloud environments, particularly around data sovereignty, access control, audit requirements, and regulatory compliance. Through analysis of existing cloud governance challenges and architectural patterns, we propose a comprehensive framework that …

Post-Implementation Erp Value Realization: A Decision Intelligence Framework, Manikantha Varaprasad Inakollu

Computer Science and Engineering Faculty Publications

Enterprise Resource Planning systems represent substantial organizational investments, yet many organizations struggle to realize expected benefits after implementation. This research develops a decision intelligence framework specifically designed to maximize ERP value realization during the critical post-implementation phase. While extensive literature addresses ERP implementation challenges, significantly less attention focuses on extracting value after systems go live. Our framework integrates data analytics, organizational learning, and strategic decision-making into a cohesive approach that transforms ERP systems from operational tools into strategic assets. Through analysis of post-implementation patterns across multiple organizations, we identify key decision points where intelligent interventions dramatically improve value capture. The …

Erp As A Digital Backbone: Redefining Enterprise Systems For Continuous Value Creation, Manikantha Varaprasad Inakollu

Computer Science and Engineering Faculty Publications

Enterprise Resource Planning systems have evolved from transactional processing tools into strategic digital backbones that orchestrate organizational value creation. This research examines how modern ERP implementations transcend traditional operational efficiency goals to enable continuous innovation, real-time decision-making, and ecosystem integration. Through analysis of contemporary ERP architectures and their impact on organizational capabilities, we demonstrate that successful digital transformation requires reconceptualizing ERP not as a software package but as an adaptive infrastructure supporting diverse business models. Our findings reveal that organizations treating ERP as a digital backbone achieve 35% higher agility scores and 42% faster time-to-market for new capabilities compared to …

Suitability Of Quantized Devs-Lim Methods For Simulation Of Power Systems, Navid Gholizadeh

Theses and Dissertations

This research presents an investigation of behavioral intricacies of the Quantized DEVS Latency Insertion Method (QDL) method and proposes resolutions to the previously unsolved and unexplained discrepancies between the reference solution and the QDL method. QDL method is a combination of two other methods namely the Latency Insertion Method (LIM) and Linear Implicit Quantized State (LIQSS)method. This technique is rigorously evaluated across a diverse array of systems and scenarios, with the aim of unearthing nuanced insights into its respective functionalities.

The research seeks to discern novel attributes of this method while gauging its comparative efficacy against conventional discrete-time methodologies, both …

Image-Based Malware Classification On Noise Extraction, Venkata Sai Sathwik Nadella

Master's Projects

Any malicious software designed to cause harm or damage to a computer system can be termed as malware. One common form of malware is as executable files. Such files are often used as a delivery mechanism for malware since they can be easily disguised as legitimate software and can be executed without raising suspicion. They are often used to exploit vulnerabilities in software, allowing malware to bypass security measures and gain access to sensitive information.

There are several methods used to detect malware in executable files, including Signaturebased detection, Behavioral-based detection, Heuristic-based detection, Sandboxing, Machine Learning and Artificial Intelligence (AI). …

Group-Invariant Reinforcement Learning, Fnu Ankur

Master's Theses

Our work introduces a way to learn an optimal reinforcement learning agent accompanied by intrinsic properties of the environment. The extracted properties helps the agent to extrapolate the learning to unseen states efficiently. Out of all the various types of properties, we are intrigued towards equivariant and invariant properties, which essentially translates to symmetry. Contrary to many approaches, we do not assume the symmetry, rather learn them, making the approach agnostic to the environment and the property. The learned properties offers multiple perspective of the environment to exploit it to benefit decision making while interacting with the environment. By building …

Automatic Presentation Slide Generation Using Llms, Tanya Gupta

Master's Theses

Presentation slides are widely used for conveying information in academic and professional contexts. However, manual slide creation can be time-consuming. Our research focuses on automated slide generation, specifically for scientific research papers. Automating the creation of presentation slides for scientific documents is a rather novel task and hence, there’s limited training data available and there also exists the token constraints of language models like BERT, with a maximum sequence length of 512 tokens. In this study, we fine-tune large language models, including Longformer-Encoder-Decoder (supporting sequences up to 16,834 tokens) and BIGBIRD-Pegasus (supporting sequences up to 4,096 tokens). We tackle this …

Detecting The Onion Routing Traffic In Real-Time By Using Reinforcement Learning, Dazhou Liu

Master's Theses

Anonymous networks have been popularly utilized to protect user anonymity and facilitate network security for a decade. However, such networks have been a platform for adversarial affairs and various network attacks including suspicious traffic generators. As a result, detecting anonymous network traffic is one critical task to defend a network against unpredictable attacks. Many new methods using machine learning and deep learning techniques have been proposed. However, many of them rely heavily on a vast amount of labeled data and have complicated architectures. Since network traffic always fluctuates under different network environments, those techniques may degrade in performance due to …

Intrinsic Motivation By The Principles Of Non-Linear Dynamical Systems, Phu C. Nguyen

Master's Theses

The design of appropriate control rules for the stabilization of dynamical systems can require quite substantial domain knowledge. Modern AI methodologies, such as Reinforcement Learning, are often used to mitigate the need for such knowledge. However, these can be slow and often rely on at least some hand-designed reward structure, and thus human input, to be more effective. Here, we propose an alternative route to construct rewards requiring only minimal domain knowledge, essentially relying on the structure of the dynamical system itself. For this, we use truncated Lyapunov exponents as rewards to calculate the stabilizing controller from samples. Concretely, the …

Interdependence Of Salt Concentration And Filler Particles On Crystallinity And Mechanical Behavior Of Peo-Litfsi Electrolytes For Lithium-Ion Batteries, Valeria Perez

Master's Theses

Developing composite polymer electrolytes is crucial for enhancing the safety, energy density, and performance of lithium-ion batteries. While it is widely accepted that introducing filler particles in PEO-based electrolytes can reduce crystallinity and enhance ionic conductivity, this conventional understanding applies primarily to electrolytes with high lithium salt concentrations. The hypothesis of this investigation is that the crystallinity change induced by LLZTO ceramic particles in PEO-LiTFSI electrolytes is contingent on the EO:Li molar ratio. This hypothesis is interrogated by measuring changes in crystallinity, spherulite morphology, and stiffness of composite polymer electrolytes with two different EO:Li molar ratios using differential scanning calorimetry, …