Computational Engineering Commons^™

Neuromorphic Computing Applications In Robotics, Noah Zins

Dissertations, Master's Theses and Master's Reports

Deep learning achieves remarkable success through training using massively labeled datasets. However, the high demands on the datasets impede the feasibility of deep learning in edge computing scenarios and suffer from the data scarcity issue. Rather than relying on labeled data, animals learn by interacting with their surroundings and memorizing the relationships between events and objects. This learning paradigm is referred to as associative learning. The successful implementation of associative learning imitates self-learning schemes analogous to animals which resolve the challenges of deep learning. Current state-of-the-art implementations of associative memory are limited to simulations with small-scale and offline paradigms. Thus, …

Capturing Microstructural Heterogeneity And Predicting Local Transport Phenomena In Pemfc Catalyst Layers: A Comprehensive Network Modeling Approach, Shahriar Alam

Dissertations, Master's Theses and Master's Reports

A unique network architecture that captures the microstructural heterogeneity and predicts the local transport properties of PEMFC catalyst layers is proposed. Separate networks containing numerous cylindrical elements and nodes are generated that represent the solid and pore phase of the catalyst layer. Transport resistances are assigned to the elements while the nodes are volumeless. The networks are interlinked through nodes where local properties are stored. The generated computational grid's macroscopic behaviors (percolation behavior, gas diffusivity, and ion conductivity) will be matched against the experimental data for validation. Diffusion-like transport equations are applied to the networks that provide local water balance, …

Liquid Tab, Nathan Hulet

Williams Honors College, Honors Research Projects

Guitar transcription is a complex task requiring significant time, skill, and musical knowledge to achieve accurate results. Since most music is recorded and processed digitally, it would seem like many tools to digitally analyze and transcribe the audio would be available. However, the problem of automatic transcription presents many more difficulties than are initially evident. There are multiple ways to play a guitar, many diverse styles of playing, and every guitar sounds different. These problems become even more difficult considering the varying qualities of recordings and levels of background noise.

Machine learning has proven itself to be a flexible tool …

Use Of Bioheat Modeling To Characterize And Optimize Implantable Medical Devices And Neuromodulation Technologies, Adantchede Louis Zannou

Dissertations and Theses

Medical device development includes prototyping, benchtop characterization, preclinical studies, and clinical trials. Understanding the limitations and potential adverse effects of medical devices prior to their administration in humans is a crucial first step. Optimizing medical devices is essential to employing technology and improving patients care. Computational modeling is widely adopted as a powerful tool to predict stimulation/recording parameter optimization, rapid electrode/device prototyping, investigating novel mechanism of action, and testing working principles of any medical devices. Many implantable neuromodulation technologies including Spinal Cord Stimulation (SCS), which provide substantial therapeutic benefit for patient population with lower back pain, produces heat via the …

Anomaly Based Intrusion Detection System Through Remote Virtual Machine Introspection, Huseyn Huseynov

Dissertations and Theses

Research on identifying malicious applications is an important direction in information security, especially when it comes to detection of evasive malware such as keyloggers, trojans, rootkits and their derivatives. Inspired by a biological immune system and based on negative selection algorithm approach to detect various types of malwares is proposed in this paper.

By deeply studying Linux kernel, understanding links behind different internal system processes, examining, and experimenting with hundreds of various keyloggers we propose a single Artificial Intelligence based solution as a comprehensive protection against wide range of malwares. Developed Intrusion Detection System (IDS) can be deployed in the …

Energy-Efficient Hmac For Wireless Communications, Cesar Enrique Castellon Escobar

UNF Graduate Theses and Dissertations

This thesis introduces the Farming Lightweight Protocol (FLP) optimized for energy-restricted environments that depend upon secure communication, such as multi-robot information gathering systems within the vision of ``smart'' agriculture. FLP uses a hash-based message authentication code (HMAC) to achieve data integrity. HMAC implementations, resting upon repeated use of the SHA256 hashing operator, impose additional resource requirements and thus also impact system availability. We address this particular integrity/availability trade-off by proposing an energy-saving algorithmic engineering method on the internal SHA256 hashing operator. The energy-efficient hash is designed to maintain the original security benefits yet reduce the negative effects on system availability. …

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 …

Accessibility Of Health Data Representations For Older Adults: Challenges And Opportunities For Design, Peterson Jean, Emma Murphy, Enda Bates

Books/Book Chapters

Health data of consumer off-the-shelf wearable devices is often conveyed to users through visual data representations and analyses. However, this is not always accessible to people with disabilities or older people due to low vision, cognitive impairments or literacy issues. Due to trade-offs between aesthetics predominance or information overload, real-time user feedback may not be conveyed easily from sensor devices through visual cues like graphs and texts. These difficulties may hinder critical data understanding. Additional auditory and tactile feedback can also provide immediate and accessible cues from these wearable devices, but it is necessary to understand existing data representation limitations …

Comparative Analysis Of Fullstack Development Technologies: Frontend, Backend And Database, Qozeem Odeniran

College of Graduate Studies: Theses & Dissertations

Accessing websites with various devices has brought changes in the field of application development. The choice of cross-platform, reusable frameworks is very crucial in this era. This thesis embarks in the evaluation of front-end, back-end, and database technologies to address the status quo. Study-a explores front-end development, focusing on angular.js and react.js. Using these frameworks, comparative web applications were created and evaluated locally. Important insights were obtained through benchmark tests, lighthouse metrics, and architectural evaluations. React.js proves to be a performance leader in spite of the possible influence of a virtual machine, opening the door for additional research. Study b …

Analytical Heat Transfer Modeling Of The Microwave Heating Process: A Focus On Carbon Black, Craig Offutt

Graduate Theses, Dissertations, and Problem Reports (ETD)

Electronic waste (e-waste) has become a significant environmental issue due to the rapid advancement of technology, increasing demand for electronic devices, and shorter lifespan of electronics. One critical step in processing the e-waste involves ball milling as a means of preparing the recycling e-waste for the recovery of critical materials. Ball milling is a technique that involves the mechanical crushing and grinding of electronic waste to reduce its size and improve its reactivity during recovery. Our focused recovery technique is based on a microwave recovery technique of these critical materials from e-waste. The size and distribution of the e-waste with …

Advancing Medical Technology For Motor Impairment Rehabilitation: Tools, Protocols, And Devices, Matthew Yough

Graduate Theses, Dissertations, and Problem Reports (ETD)

Excellent motor control skills are necessary to live a high-quality life. Activities such as walking, getting dressed, and feeding yourself may seem mundane, but injuries to the neuromuscular system can render these tasks difficult or even impossible to accomplish without assistance. Statistics indicate that well over 100 million people are affected by diseases or injuries, such as stroke, Parkinson’s Disease, Multiple Sclerosis, Cerebral Palsy, peripheral nerve injury, spinal cord injury, and amputation, that negatively impact their motor abilities. This wide array of injuries presents a challenge to the medical field as optimal treatment paradigms are often difficult to implement due …

Object Detection And Classification In The Visible And Infrared Spectrums, Domenick D. Poster

Graduate Theses, Dissertations, and Problem Reports (ETD)

The over-arching theme of this dissertation is the development of automated detection and/or classification systems for challenging infrared scenarios. The six works presented herein can be categorized into four problem scenarios. In the first scenario, long-distance detection and classification of vehicles in thermal imagery, a custom convolutional network architecture is proposed for small thermal target detection. For the second scenario, thermal face landmark detection and thermal cross-spectral face verification, a publicly-available visible and thermal face dataset is introduced, along with benchmark results for several landmark detection and face verification algorithms. Furthermore, a novel visible-to-thermal transfer learning algorithm for face landmark …

Face Image And Video Analysis In Biometrics And Health Applications, Na Zhang

Graduate Theses, Dissertations, and Problem Reports (ETD)

Computer Vision (CV) enables computers and systems to derive meaningful information from acquired visual inputs, such as images and videos, and make decisions based on the extracted information. Its goal is to acquire, process, analyze, and understand the information by developing a theoretical and algorithmic model. Biometrics are distinctive and measurable human characteristics used to label or describe individuals by combining computer vision with knowledge of human physiology (e.g., face, iris, fingerprint) and behavior (e.g., gait, gaze, voice). Face is one of the most informative biometric traits. Many studies have investigated the human face from the perspectives of various different …

Optimal Design And Operation Of Integrated Hydrogen Generation And Utilization Plants, Ijiwole Solomon Ijiyinka

Graduate Theses, Dissertations, and Problem Reports (ETD)

There are considerable efforts worldwide for reducing the use of fossil fuel for energy production. While renewable energy sources are being increasingly used, fossil fuel still contribute about 80% of the energy used worldwide. As a result, the level of CO₂ is still increasing fast in the atmosphere currently exceeding about 410 parts per million (ppm). For reducing CO₂ build up in the atmosphere, various approaches are being investigated. For the electric power generation sector, two key approaches are post-combustion CO₂ capture and use of hydrogen as a fuel for power generation. These two solutions can also …

Development Of A Framework To Support Community-Scale Nutrient Recovery For Local Crop Fertilization And Production, Scott A. Lopez

Graduate Theses, Dissertations, and Problem Reports (ETD)

Nutrient and resource recovery (NRR) has become increasingly crucial as regions face deteriorating sanitation infrastructures, limited support, and growing environmental challenges. Implementing region-specific NRR technologies and systems could provide effective circular economy insights into addressing these challenges. Because of the multidisciplinary challenges associated with the design and implementation of NRR strategies, various government and local decision-makers need to collaborate effectively in the decision-making process. Structured decision-making (SDM) methodologies are practical when determining the most appropriate NRR strategy for nutrient-rich waste streams. However, applications of computational SDM limited because of the vast amounts of data that are needed to analyze the …

Digital Platform To Aid Youth Substance Abuse Prevention, Bingxuan Li

Discovery Undergraduate Interdisciplinary Research Internship

Through research and interviews, I discovered that a significant portion of students in Africa become drug addicts and drop out of school. The solution is to prevent youth substance abuse before it happens, so that more students in Africa may continue their education. With the strong motivation of expanding African student involvement in higher education, I participated DURI program to increase higher education rates in the Democratic Republic of the Congo, Africa. The local government is establishing rehabilitation centers to monitor at-risk students and prevent youth substance abuse, but due to extremely limited resources, it is critical to evaluate the …

An Efficient Integrated Circuit Simulator And Time Domain Adjoint Sensitivity Analysis, Jiahua Li

Electrical Engineering Theses and Dissertations

In this paper, we revisit time-domain adjoint sensitivity with a circuit theoretic approach and an efficient solution is clearly stated in terms of device level. Key is the linearization of the energy storage elements (e.g., capacitance and inductance) and nonlinear memoryless elements (e.g., MOS, BJT DC characteristics) at each time step. Due to the finite precision of computation, numerical errors that accumulate across timesteps can arise in nonlinear elements.

Energy Dissipation In A Sand Damper Under Cyclic Loading, Ehab Sabi

Civil and Environmental Engineering Theses and Dissertations

Various seismic and wind engineering designs and retrofit strategies have been in development to meet structures' proper and safe operation during earthquake and wind excitation. One such method is the addition of fluid and particle dampers, such as sand dampers, in an effort to reduce excessive and dangerous displacements of structures. The present study implements the discrete element method (DEM) to assess the performance of a pressurized sand damper (PSD) and characterize the dissipated energy under cyclic loading. The idea of a PSD is to exploit the increase in shearing resistance of sand under external pressure and the associated ability …