Engineering Commons^™

Development Of Zr(Iv) Mof-Enabled Nerve Agent Electrochemical Hydrolysis Sensors, Tyler James Marlar

Theses and Dissertations

Nerve agents are acetylcholinesterase inhibitors and among the most toxic chemical warfare agents ever synthesized. Detection of these chemicals is critical for the protection of populations and strategic resources. G-series nerve agents are volatile compounds. V-series nerve agents are persistent phosphonothioate compounds. Persistent nerve agents do not readily volatilize and can contaminate environmental resources for extended periods. While nerve agents are inherently non-electroactive, they can be hydrolyzed to electroactive products compatible with electrochemical sensing. Zr(IV) MOFs are next-generation nanoporous materials, which have been shown to rapidly catalyze nerve agent hydrolysis. In this work, the catalytic processes of MOF-808, a specific …

Enhancing Cyber Resilience: Development, Challenges, And Strategic Insights In Cyber Security Report Websites Using Artificial Inteligence, Pooja Sharma

Harrisburg University Dissertations and Theses

In an era marked by relentless cyber threats, the imperative of robust cyber security measures cannot be overstated. This thesis embarks on an in-depth exploration of the historical trajectory and contemporary relevance of penetration testing methodologies, elucidating their evolution from nascent origins to indispensable tools in the cyber security arsenal. Moreover, it undertakes the ambitious task of conceptualizing and implementing a cyber security report website, meticulously designed to fortify cyber resilience in the face of ever-evolving threats in the digital realm.

The research journey commences with an insightful examination of the historical antecedents of penetration testing, tracing its genesis in …

The Role Of Attention Mechanisms In Enhancing Transparency And Interpretability Of Neural Network Models In Explainable Ai, Bhargav Kotipalli

Harrisburg University Dissertations and Theses

In the rapidly evolving field of artificial intelligence (AI), deep learning models' interpretability

and reliability are severely hindered by their complexity and opacity. Enhancing the

transparency and interpretability of AI systems for humans is the primary objective of the

emerging field of explainable AI (XAI). The attention mechanisms at the heart of XAI's work

are based on human cognitive processes. Neural networks can now dynamically focus on

relevant parts of the input data thanks to these mechanisms, which enhances interpretability

and performance. This report covers in-depth talks of attention mechanisms in neural networks

within XAI, as well as an analysis …

Decoding The Future: Integration Of Artificial Intelligence In Web Development, Dhiraj Choithramani

Harrisburg University Dissertations and Theses

The thesis explores AI's profound impact on web development, particularly in front-end and back-end processes. AI revolutionizes UI prototyping by automating design creation, enhancing both efficiency and aesthetics. It also aids in code review, content generation, and process flow experimentation, streamlining development workflows. Through AI-driven tools like GitHub's Copilot and Wix ADI, developers benefit from coding assistance and innovative design capabilities. Despite some challenges, AI's evolving role promises to reshape web development, offering unprecedented efficiency and user-centric solutions.

Enhancing Mobile App User Experience: A Deep Learning Approach For System Design And Optimization, Deepesh Haryani

Harrisburg University Dissertations and Theses

This paper presents a comprehensive framework for enhancing user experience in mobile applications through the integration of deep learning systems. The proposed system design encompasses various components, including data collection and preprocessing, model development and training, integration with mobile applications, dataset management service, model training service, model serving, hyperparameter optimization, metadata and artifact store, and workflow orchestration. Each component is meticulously designed with a focus on scalability, efficiency, isolation, and critical analysis. Innovative design principles are employed to ensure seamless integration, usability, and automation. Additionally, the paper discusses distributed training service design, advanced optimization techniques, and decision criteria for hyperparameter …

Predictive Ai Applications For Sar Cases In The Us Coast Guard, Joshua Nelson

Cybersecurity Undergraduate Research Showcase

This paper explores the potential integration of predictive analytics AI into the United States Coast Guard's (USCG) Search and Rescue Optimal Planning System (SAROPS) for deep sea and nearshore search and rescue (SAR) operations. It begins by elucidating the concept of predictive analytics AI and its relevance in military applications, particularly in enhancing SAR procedures. The current state of SAROPS and its challenges, including complexity and accuracy issues, are outlined. By integrating predictive analytics AI into SAROPS, the paper argues for streamlined operations, reduced training burdens, and improved accuracy in locating drowning personnel. Drawing on insights from military AI applications …

Proposed Charlotte To Atlanta High-Speed Passenger Rail Line: An Economic, Infrastructural, And Developmental Analysis In The Upstate Of South Carolina, Ian C. Macurda, Kimberly Whitehead

SC Upstate Research Symposium

This research paper is an in-depth analysis of the high-speed passenger rail line proposed between Charlotte, NC and Atlanta, GA and its impact on the economy, infrastructure, and future development of the Upstate of South Carolina. Currently, passenger rail service between Charlotte and Atlanta is offered on Amtrak at late hours throughout the night on its long-distance passenger rail line The Crescent from New York City, NY to New Orleans, LA. The train is often delayed and is operating at a deficit for Amtrak, like most of their long-distance routes. Traffic on Interstate 85 through the Upstate is another issue …

A Biocompatible Hybrid Approach For The Selection Of Gas Drainage Methods In Coal Mines Based On The Best-Worst Method And Analytic Network Process, Amir Jafarpour, Mehdi Najafi, Ali Dabagh

Journal of Sustainable Mining

Methane drainage is one of the main steps in underground coal mining projects. The operation of methane extraction from coal mines/seams is important from the safety, economic, and technical points of view. Selecting the appropriate method for methane drainage is very difficult, and if the method is not chosen correctly, it will lead to environmental problems. The relationship between different influencing factors, parameters, and methods (and how they affect) is significant in choosing the method of gas drainage. In the current study, a hybrid algorithm is presented based on an Analytic Network Process (ANP) and a method based on the …

A Case Study Of The Crashoverride Malware, Its Effects And Possible Countermeasures, Samuel Rector

Cybersecurity Undergraduate Research Showcase

CRASHOVERRIDE is a modular malware tailor-made for electric grid Industrial Control System (ICS) equipment and was deployed by a group named ELECTRUM in a Ukrainian substation. The malware would launch a protocol exploit to flip breakers and would then wipe the system of ICS files. Finally, it would execute a Denial Of Service (DOS) attack on protective relays. In effect, months of damage and thousands out of power. However, due to oversights the malware only caused a brief power outage. Though the implications of the malware are cause for researching and implementing countermeasures against others to come. The CISA recommends …

Seeding Effects Of Submicron Caal-No3 Ldh Particles On The Hydration And Properties Of Portland Cement And Sulfoaluminate Cement Pastes, Sukanta K. Mondal, Monday Uchenna Okoronkwo

Chemical and Biochemical Engineering Faculty Research & Creative Works

Layered Double Hydroxide (LDH) Is Reported To Improve The Durability Of Concretes, Primarily Due To Its Ability To Exchange Anionic Species, Including Chloride, Which Is Implicated In Corrosion-Driven Durability Issues. However, There Is No Comprehensive Study Investigating The Effect Of LDH On The Properties Of Different Cement Systems At Both Early And Mature Ages. In This Study, The Early Age And Mature Age Properties Of Portland Cement (OPC) And Calcium Sulfoaluminate (CSA) Cement Pastes Seeded With Submicron-Sized Calcium Aluminum-NO3 LDH (CaAl-NO3 LDH) Were Investigated. The Effects Of The 1–5%mass Dosage Of LDH On The Hydration Of Both Cement Systems Were …

Immersive Japanese Language Learning Web Application Using Spaced Repetition, Active Recall, And An Artificial Intelligent Conversational Chat Agent Both In Voice And In Text, Marc Butler

MS in Computer Science Project Reports

In the last two decades various human language learning applications, spaced repetition software, online dictionaries, and artificial intelligent chat agents have been developed. However, there is no solution to cohesively combine these technologies into a comprehensive language learning application including skills such as speaking, typing, listening, and reading. Our contribution is to provide an immersive language learning web application to the end user which combines spaced repetition, a study technique used to review information at systematic intervals, and active recall, the process of purposely retrieving information from memory during a review session, with an artificial intelligent conversational chat agent both …

Application Of High-Deflection Strain Gauges To Characterize Spinal-Motion Phenotypes Among Patients With Clbp, Spencer Alan Baker

Theses and Dissertations

Chronic low back pain (CLBP) is a nonspecific and persistent ailment that entails many physiological, psychological, social, and economic consequences for individuals and societies. Although there is a plethora of treatments available to treat CLBP, each treatment has varying efficacy for different patients, and it is currently unknown how to best link patients to their ideal treatment. However, it is known that biopsychosocial influences associated with CLBP affect the way that we move. It has been hypothesized that identifying phenotypes of spinal motion could facilitate an objective and repeatable method of determining the optimal treatment for each patient. The objective …

Time-Dependent Strain-Resistance Relationships In Silicone Nanocomposite Sensors, Alex Mikal Wonnacott

Theses and Dissertations

Flexible high-deflection strain gauges have been demonstrated as cost-effective and accessible sensors for capturing human biomechanical deformations. However, the interpretation of these sensors is notably more complex compared to conventional strain gauges, partially owing to the viscoelastic nature of the strain gauges. On top of the non-linear viscoelastic behavior, dynamic resistance response is even more difficult to capture due to spikes in resistance during strain changes. This research examines the relationships between stress, strain, and resistance in nanocomposite sensors during dynamic strain situations. Under the assumption that both macroscopic stress and resistance are governed by microscopic stress concentrations at the …

High Data Rate Signal Processing Architectures And Compilation Strategies For Scalable, Multi-Gigabit Digital Systems, Daniel Alexander Nybo

Theses and Dissertations

In this study we present a high-performance computing architecture and hardware acceleration strategy for a heterogeneous multi-gigabit computing system. The system architecture integrates a BeeGFS distributed file system, capable of achieving 80 Gbps of sustained write throughput across five nodes, essential for managing the high data volumes generated by a 25 high performance computer (HPC) compute cluster. To ensure operational efficiency and scalability, the tasks performed on the Linux compute cluster consisting of 30 nodes are automated using Ansible, facilitating seamless deployment, management, and updates. We present compilation strategies for a hardware accelerated Polyphase Filter Bank (PFB) channelization routine optimized …

Multiscale Characterization Of Dislocation Development During Cyclic Bending Under Tension In Commercially Pure Titanium, Nathan R. Miller

Theses and Dissertations

Continuous bending under tension (CBT) has been shown to increase room temperature elongation-to-failure (ETF) in various sheet metals past that of simple tension (ST). In commercially pure titanium (CP-Ti) Grade 4, up to 3x extended elongation over ST has been achieved. A greater understanding of deformation mechanisms in CBT would allow for its elongation-enhancing effects to be more fully exploited in HCP and other metals, creating potential for new forming strategies. While most of the extended ETF has been attributed to delayed localization via incremental deformation inherent to the CBT process, together with compressive stabilization and relaxation of mechanical strain …

Human-Machine Communication: Complete Volume. Volume 7 Special Issue: Mediatization

Human-Machine Communication

This is the complete volume of HMC Volume 7. Special Issue on Mediatization

Artificial Sociality, Simone Natale, Iliana Depounti

Human-Machine Communication

This article proposes the notion of Artificial Sociality to describe communicative AI technologies that create the impression of social behavior. Existing tools that activate Artificial Sociality include, among others, Large Language Models (LLMs) such as ChatGPT, voice assistants, virtual influencers, socialbots and companion chatbots such as Replika. The article highlights three key issues that are likely to shape present and future debates about these technologies, as well as design practices and regulation efforts: the modelling of human sociality that foregrounds it, the problem of deception and the issue of control from the part of the users. Ethical, social and cultural …

Mediatization And Human-Machine Communication: Trajectories, Discussions, Perspectives, Andreas Hepp, Göran Bolin, Andrea L. Guzman, Wiebke Loosen

Human-Machine Communication

As research fields, mediatization and Human-Machine Communication (HMC) have distinct historical trajectories. While mediatization research is concerned with the fundamental interrelation between the transformation of media and communications and cultural and societal changes, the much younger field of HMC delves into human meaning-making in interactions with machines. However, the recent wave of “deep mediatization,” characterized by an increasing emphasis on general communicative automation and the rise of communicative AI, highlights a shared interest in technology’s role within human interaction. This introductory article examines the trajectories of both fields, demonstrating how mediatization research “zooms out” from overarching questions of societal and …

Voltage Scaled Low Power Dnn Accelerator Design On Reconfigurable Platform, Rourab Paul, Sreetama Sarkar, Suman Sau, Sanghamitra Roy, Koushik Chakraborty, Amlan Chakrabarti

Electrical and Computer Engineering Faculty Publications

The exponential emergence of Field-Programmable Gate Arrays (FPGAs) has accelerated research on hardware implementation of Deep Neural Networks (DNNs). Among all DNN processors, domain-specific architectures such as Google’s Tensor Processor Unit (TPU) have outperformed conventional GPUs (Graphics Processing Units) and CPUs (Central Processing Units). However, implementing low-power TPUs in reconfigurable hardware remains a challenge in this field. Voltage scaling, a popular approach for energy savings, can be challenging in FPGAs, as it may lead to timing failures if not implemented appropriately. This work presents an ultra-low-power FPGA implementation of a TPU for edge applications. We divide the systolic array of …

Investigating Which Muscles Are Most Responsible For Tremor Through Both Experimental Data And Simulation, Daniel Benjamin Free

Theses and Dissertations

Tremor affects millions of people and many patients desire alternative treatment options to medication or neural surgery. Peripheral suppression techniques are gaining greater use, but are currently applied in a trial-and-error method. To optimize these techniques, the muscles most responsible for an individual patient's tremor need to be identified. In this dissertation, I explored two parallel paths that both could aid in identifying muscles responsible for tremor. The first method utilizies measured data and a technique (coherence) that quantifies the frequency dependent correlation between two signals. Using coherence to identify muscles contributing to tremor requires at least two parts: an …