Engineering Commons^™

A Data-Driven Multi-Regime Approach For Predicting Real-Time Energy Consumption Of Industrial Machines., Abdulgani Kahraman

Electronic Theses and Dissertations

This thesis focuses on methods for improving energy consumption prediction performance in complex industrial machines. Working with real-world industrial machines brings several challenges, including data access, algorithmic bias, data privacy, and the interpretation of machine learning algorithms. To effectively manage energy consumption in the industrial sector, it is essential to develop a framework that enhances prediction performance, reduces energy costs, and mitigates air pollution in heavy industrial machine operations. This study aims to assist managers in making informed decisions and driving the transition towards green manufacturing. The energy consumption of industrial machinery is substantial, and the recent increase in CO2 …

Super P-Sulfur Cathodes For Quasi-Solid-State Lithium-Sulfur-Batteries., Milinda Bharatha Kalutara Koralalage

Electronic Theses and Dissertations

Lithium-Sulfur (Li-S) batteries have become a promising candidate to meet the current energy storage demand, with its natural abundance of materials, high theoretical capacity of 1672 mAhg-1, high energy density of 2600 Whkg-1, low cost and lower environmental impact. Sulfide based solid state electrolytes (SSEs) have received greater attention due to their higher ionic conductivity, compatible interface with sulfur-based cathodes, and lower grain boundary resistance. However, the interface between SSEs and cathodes has become a challenge in all solid-state Li-S batteries due to the rigidity of the participating surfaces. A hybrid electrolyte containing SSE coupled with a small amount of …

Modeling, Simulation And Control Of Microrobots For The Microfactory., Zhong Yang

Electronic Theses and Dissertations

Future assembly technologies will involve higher levels of automation in order to satisfy increased microscale or nanoscale precision requirements. Traditionally, assembly using a top-down robotic approach has been well-studied and applied to the microelectronics and MEMS industries, but less so in nanotechnology. With the boom of nanotechnology since the 1990s, newly designed products with new materials, coatings, and nanoparticles are gradually entering everyone’s lives, while the industry has grown into a billion-dollar volume worldwide. Traditionally, nanotechnology products are assembled using bottom-up methods, such as self-assembly, rather than top-down robotic assembly. This is due to considerations of volume handling of large …

The Study Of Corrosion On Additive-Manufactured Metals., Braydan Daniels

Electronic Theses and Dissertations

The purpose of this study was to investigate and compare the corrosion mechanisms between wrought and additive-manufactured (3D-printed) copper and stainless steel. The experimental procedure consisted of measuring the open circuit potential, electrochemical impedance spectroscopy, linear sweep voltammetry, Tafel analysis, surface topology, and scanning electron microscopy for each metal within salt water, tap water, sulfuric acid, and synthetic body fluid (excluding copper in synthetic body fluid).

Overall, printed stainless steel was more corrosion-resistant than wrought stainless steel in tap water and synthetic body fluid based on OCP, LSV, and surface topology results. Additionally, printed copper was more corrosion-resistant than wrought …

The Role Of Generative Adversarial Networks In Bioimage Analysis And Computational Diagnostics., Ahmed Naglah

Electronic Theses and Dissertations

Computational technologies can contribute to the modeling and simulation of the biological environments and activities towards achieving better interpretations, analysis, and understanding. With the emergence of digital pathology, we can observe an increasing demand for more innovative, effective, and efficient computational models. Under the umbrella of artificial intelligence, deep learning mimics the brain’s way in learn complex relationships through data and experiences. In the field of bioimage analysis, models usually comprise discriminative approaches such as classification and segmentation tasks. In this thesis, we study how we can use generative AI models to improve bioimage analysis tasks using Generative Adversarial Networks …

Role Of Deep Learning Techniques In Non-Invasive Diagnosis Of Human Diseases., Hisham Abouelseoud Elsayem Abdeltawab

Electronic Theses and Dissertations

Machine learning, a sub-discipline in the domain of artificial intelligence, concentrates on algorithms able to learn and/or adapt their structure (e.g., parameters) based on a set of observed data. The adaptation is performed by optimizing over a cost function. Machine learning obtained a great attention in the biomedical community because it offers a promise for improving sensitivity and/or specificity of detection and diagnosis of diseases. It also can increase objectivity of the decision making, decrease the time and effort on health care professionals during the process of disease detection and diagnosis. The potential impact of machine learning is greater than …

Computer Aided Diagnosis System For Breast Cancer Using Deep Learning., Asma Baccouche

Electronic Theses and Dissertations

The recent rise of big data technology surrounding the electronic systems and developed toolkits gave birth to new promises for Artificial Intelligence (AI). With the continuous use of data-centric systems and machines in our lives, such as social media, surveys, emails, reports, etc., there is no doubt that data has gained the center of attention by scientists and motivated them to provide more decision-making and operational support systems across multiple domains. With the recent breakthroughs in artificial intelligence, the use of machine learning and deep learning models have achieved remarkable advances in computer vision, ecommerce, cybersecurity, and healthcare. Particularly, numerous …

Structural, Charge Transport, Gas Sensing, Magnetic, Pseudocapacitive, And Electrocatalytic Properties Of Perovskite Oxides., Surendra Bahadur Karki

Electronic Theses and Dissertations

Perovskites are functional materials with the general formula ABO₃ (A = alkali, alkaline earth or lanthanoid cations and B = transition metal or main group cations). These materials are marked by a variety of crystal structures and interesting properties such as colossal magnetoresistance, ferroelectricity, multiferroicity, superconductivity, pseudocapacitance, gas sensing, charge transport, and electrocatalytic properties. The formula of perovskite can be written as AA’BB’O₆, when there is ordering between two cations over A and B-sites. Such compounds are called double perovskite oxides. Some amount of oxygen could be lost from crystal structure without decomposition of the phase. Such …

Surface-Functionalized Chemiresistive Films That Exploit H-Bonding, Cation-Pi, And Metal-Halide Interactions., Prasadanie Karunarathna Adhihetty

Electronic Theses and Dissertations

The development of gas sensors for detection of volatile organic compounds (VOCs) has been of interest in the sensing field for decades. To date, the use of metal nanoparticle-based chemiresistors for trace VOC detection, particularly gold nanoparticle-based sensors, is of great interest due to their high chemical stability, ease of synthesis, unique optical properties, large surface to volume ratio, and high level of conductivity. Much effort has been devoted towards gold monolayer protected clusters (Au MPCs) as chemiresistors to detect harmful VOCs. The present thesis documents the results of our efforts to exploit the advantages of functionalized Au MPCs chemiresistors …

Nucleate Boiling Under Different Gravity Values: Numerical Simulations & Data-Driven Techniques., Sandipan Banerjee

Electronic Theses and Dissertations

Nucleate boiling is important in nuclear applications and cooling applications under earth gravity conditions. Under reduced gravity or microgravity environment, it is significant too, especially in space exploration applications. Although multiple studies have been performed on nucleate boiling, the effect of gravity on nucleate boiling is not well understood. This dissertation primarily deals with numerical simulations of nucleate boiling using an adaptive Moment-of-Fluid (MoF) method for a single vapor bubble (water vapor or Perfluoro-n-hexane) in saturated liquid for different gravity levels. Results concerning the growth rate of the bubble, specifically the departure diameter and departure time have been provided. The …

Synthesis, Crystal Structure And Ionic Conductivity Of Ruddlesden-Popper Oxide Materials: Effects Of Ionic Radii And Defects On Lithium-Ionic Conductivity., Selorm Joy Fanah

Electronic Theses and Dissertations

Layered perovskite oxides of the Ruddlesden-Popper (RP) type structure can be good lithium-ion conductors for solid electrolyte applications in all-solid-state batteries, due to the large gap separating octahedral layers which can be useful pathways for Li-ion conduction. However, little work has been done on their lithium-ion transport properties in these materials despite their interesting structural properties. This work highlights the synthesis and study of the ionic conductivities in a series of n = 2 and 3 Ruddlesden-Popper oxides, as part of an ongoing investigation in search of alternative solid electrolyte materials. Several different strategies were employed for the enhancement of …

Towards Long Term Colloid Suspension In A Vertically Rotated System., Md Mahmudur Rahman

Electronic Theses and Dissertations

Within a colloidal suspension gravity may compromise the observation of governing physical interactions, especially those that are weak and/or take significant time to develop. Conducting the experiment in a long-term microgravity environment is a viable option to negate gravitational effects, though significant resources are required to do so. While it may not be possible to simulate long-term microgravity terrestrially, particles can resist quick sedimentation in a confined suspension system rotating vertically with appropriate rotation speed. The goal of the investigation is to demonstrate the existence of long-term particle suspension regime for a certain colloidal suspension while characterizing colloidal behavior due …

Develop A Multi-Functional Green Pervious Concrete (Mgpc) Pavement With Polycyclic Aromatic Hydrocarbons (Pahs) Removal Function., Hong Shang

Electronic Theses and Dissertations

Stormwater runoff induced Polycyclic Aromatic Hydrocarbons (PAHs) contaminant increasingly imperils the groundwater quality and the sustainable development of human society due to the potential carcinogenic risks. Pavement can be considered as the first line of defense for contaminant removal of the stormwater runoff. New construction materials with stormwater runoff quantity and quality control are in urgent demand for updating the existing pavement system. An innovative material called Multi-functional Green Pervious Concrete (MGPC) was developed in the department of Civil and Environmental Engineering at University of Louisville. This material uses organoclay as the amendment to enhance the PAHs removal capacity of …

Signal Fingerprinting And Machine Learning Framework For Uav Detection And Identification., Olusiji Oloruntobi Medaiyese

Electronic Theses and Dissertations

Advancement in technology has led to creative and innovative inventions. One such invention includes unmanned aerial vehicles (UAVs). UAVs (also known as drones) are now an intrinsic part of our society because their application is becoming ubiquitous in every industry ranging from transportation and logistics to environmental monitoring among others. With the numerous benign applications of UAVs, their emergence has added a new dimension to privacy and security issues. There are little or no strict regulations on the people that can purchase or own a UAV. For this reason, nefarious actors can take advantage of these aircraft to intrude into …

High-Density Parking For Autonomous Vehicles., Parag J. Siddique

Electronic Theses and Dissertations

In a common parking lot, much of the space is devoted to lanes. Lanes must not be blocked for one simple reason: a blocked car might need to leave before the car that blocks it. However, the advent of autonomous vehicles gives us an opportunity to overcome this constraint, and to achieve a higher storage capacity of cars. Taking advantage of self-parking and intelligent communication systems of autonomous vehicles, we propose puzzle-based parking, a high-density design for a parking lot. We introduce a novel method of vehicle parking, which leads to maximum parking density. We then propose a heuristic method …

Multilateration Index., Chip Lynch

Electronic Theses and Dissertations

We present an alternative method for pre-processing and storing point data, particularly for Geospatial points, by storing multilateration distances to fixed points rather than coordinates such as Latitude and Longitude. We explore the use of this data to improve query performance for some distance related queries such as nearest neighbor and query-within-radius (i.e. “find all points in a set P within distance d of query point q”). Further, we discuss the problem of “Network Adequacy” common to medical and communications businesses, to analyze questions such as “are at least 90% of patients living within 50 miles of a covered emergency …

Image Analysis Of Charged Bimodal Colloidal Systems In Microgravity., Adam J. Cecil

Electronic Theses and Dissertations

Colloids are suspensions of two or more phases and have been topics of research for advanced, tunable materials for decades. Stabilization of colloids is typically attributed to thermodynamic mechanisms; however, recent studies have identified transport or entropic mechanisms that can potentially stabilize a thermodynamically unstable colloidal system. In this study, suspensions of silsesquioxane microparticles and zirconia nanoparticles were dispersed in a nitric acid solution and allowed to aggregate for 8-12 days in microgravity aboard the International Space Station. The suspensions were subsequently imaged periodically at 2.5x magnification. Due to the inadequacy of existing image analysis programs, the python package “Colloidspy” …

Formally Designing And Implementing Cyber Security Mechanisms In Industrial Control Networks., Mehdi Sabraoui

Electronic Theses and Dissertations

This dissertation describes progress in the state-of-the-art for developing and deploying formally verified cyber security devices in industrial control networks. It begins by detailing the unique struggles that are faced in industrial control networks and why concepts and technologies developed for securing traditional networks might not be appropriate. It uses these unique struggles and examples of contemporary cyber-attacks targeting control systems to argue that progress in securing control systems is best met with formal verification of systems, their specifications, and their security properties. This dissertation then presents a development process and identifies two technologies, TLA+ and seL4, that can be …

Lithium Molybdate-Sulfur Battery., Ruchira Ravinath Dharmasena

Electronic Theses and Dissertations

Rechargeable energy storage systems play a vital role in today’s automobile industry with the emergence of electric vehicles (EVs). In order to meet the targets set by the department of energy (DOE), there is an immediate need of new battery chemistries with higher energy density than the current Li- ion technology. Lithium–sulfur (Li–S) batteries have attracted enormous attention in the energy-storage, due to their high specific energy density of 2600 Wh kg^-1 and operational voltage of 2.0 V. Despite the promising electrochemical characteristics, Li-S batteries suffer from serious technical challenges such as dissolution of polysulfides Li₂S_{x …}

An Explainable Sequence-Based Deep Learning Predictor With Applications To Song Recommendation And Text Classification., Khalil Damak

Electronic Theses and Dissertations

Streaming applications are now the predominant tools for listening to music. What makes the success of such software is the availability of songs and especially their ability to provide users with relevant personalized recommendations. State of the art music recommender systems mainly rely on either Matrix factorization-based collaborative filtering approaches or deep learning architectures. Deep learning models usually use metadata for content-based filtering or predict the next user interaction (listening to a song) using a memory-based deep learning structure that learns from temporal sequences of user actions. Despite advances in deep learning models for song recommendation systems, none has taken …

A Transfer Learning Approach For Sentiment Classification., Omar Abdelwahab

Electronic Theses and Dissertations

The idea of developing machine learning systems or Artificial Intelligence agents that would learn from different tasks and be able to accumulate that knowledge with time so that it functions successfully on a new task that it has not seen before is an idea and a research area that is still being explored. In this work, we will lay out an algorithm that allows a machine learning system or an AI agent to learn from k different domains then uses some or no data from the new task for the system to perform strongly on that new task. In order …

Evaluation Of Drug-Loaded Gold Nanoparticle Cytotoxicity As A Function Of Tumor Tissue Heterogeneity., Hunter Allan Miller

Electronic Theses and Dissertations

The inherent heterogeneity of tumor tissue presents a major challenge to nanoparticle-medicated drug delivery. This heterogeneity spans from the molecular to the cellular (cell types) and to the tissue (vasculature, extra-cellular matrix) scales. Here we employ computational modeling to evaluate therapeutic response as a function of vascular-induced tumor tissue heterogeneity. Using data with three-layered gold nanoparticles loaded with cisplatin, nanotherapy is simulated with different levels of tissue heterogeneity, and the treatment response is measured in terms of tumor regression. The results show that tumor vascular density non-trivially influences the nanoparticle uptake and washout, and the associated tissue response. The drug …

High Dynamic Range Optical Devices And Applications., Elijah Robert Jensen

Electronic Theses and Dissertations

Much of what we know about fundamental physical law and the universe derives from observations and measurements using optical methods. The passive use of the electromagnetic spectrum can be the best way of studying physical phenomenon in general with minimal disturbance of the system in the process. While for many applications ambient visible light is sufficient, light outside of the visible range may convey more information. The signals of interest are also often a small fraction of the background, and their changes occur on time scales so quickly that they are visually imperceptible. This thesis reports techniques and technologies developed …

Longitudinal Tracking Of Physiological State With Electromyographic Signals., Robert Warren Stallard

Electronic Theses and Dissertations

Electrophysiological measurements have been used in recent history to classify instantaneous physiological configurations, e.g., hand gestures. This work investigates the feasibility of working with changes in physiological configurations over time (i.e., longitudinally) using a variety of algorithms from the machine learning domain. We demonstrate a high degree of classification accuracy for a binary classification problem derived from electromyography measurements before and after a 35-day bedrest. The problem difficulty is increased with a more dynamic experiment testing for changes in astronaut sensorimotor performance by taking electromyography and force plate measurements before, during, and after a jump from a small platform. A …

Network Science Algorithms For Mobile Networks., Heba Mohamed Elgazzar

Electronic Theses and Dissertations

Network Science is one of the important and emerging fields in computer science and engineering that focuses on the study and analysis of different types of networks. The goal of this dissertation is to design and develop network science algorithms that can be used to study and analyze mobile networks. This can provide essential information and knowledge that can help mobile networks service providers to enhance the quality of the mobile services. We focus in this dissertation on the design and analysis of different network science techniques that can be used to analyze the dynamics of mobile networks. These techniques …

Multi Self-Adapting Particle Swarm Optimization Algorithm (Msapso)., Gerhard Koch

Electronic Theses and Dissertations

The performance and stability of the Particle Swarm Optimization algorithm depends on parameters that are typically tuned manually or adapted based on knowledge from empirical parameter studies. Such parameter selection is ineffectual when faced with a broad range of problem types, which often hinders the adoption of PSO to real world problems. This dissertation develops a dynamic self-optimization approach for the respective parameters (inertia weight, social and cognition). The effects of self-adaption for the optimal balance between superior performance (convergence) and the robustness (divergence) of the algorithm with regard to both simple and complex benchmark functions is investigated. This work …

A Framework For Clustering And Adaptive Topic Tracking On Evolving Text And Social Media Data Streams., Gopi Chand Nutakki

Electronic Theses and Dissertations

Recent advances and widespread usage of online web services and social media platforms, coupled with ubiquitous low cost devices, mobile technologies, and increasing capacity of lower cost storage, has led to a proliferation of Big data, ranging from, news, e-commerce clickstreams, and online business transactions to continuous event logs and social media expressions. These large amounts of online data, often referred to as data streams, because they get generated at extremely high throughputs or velocity, can make conventional and classical data analytics methodologies obsolete. For these reasons, the issues of management and analysis of data streams have been researched extensively …

Artificial Olfactory System For Multi-Component Analysis Of Gas Mixtures., Alexander Aleksandrovich Larin

Electronic Theses and Dissertations

Gas analysis is an important part of our world and gas sensing technology is becoming more essential for various aspects of our life. A novel approach for gas mixture analysis by using portable gas chromatography in combination with an array of highly integrated and selective metal oxide (MOX) sensors has been studied. We developed a system with small size (7 x 13 x 16 inches), low power consumption (~10 W) and absence of special carrier gases designed for portable field analysis (assuming apriori calibration). Low ppb and even sub-ppb level of detection for some VOCs was achieved during the analysis …

Dynamic Adversarial Mining - Effectively Applying Machine Learning In Adversarial Non-Stationary Environments., Tegjyot Singh Sethi

Electronic Theses and Dissertations

While understanding of machine learning and data mining is still in its budding stages, the engineering applications of the same has found immense acceptance and success. Cybersecurity applications such as intrusion detection systems, spam filtering, and CAPTCHA authentication, have all begun adopting machine learning as a viable technique to deal with large scale adversarial activity. However, the naive usage of machine learning in an adversarial setting is prone to reverse engineering and evasion attacks, as most of these techniques were designed primarily for a static setting. The security domain is a dynamic landscape, with an ongoing never ending arms race …

A Data Science Pipeline For Educational Data : A Case Study Using Learning Catalytics In The Active Learning Classroom., Asuman Cagla Acun Sener

Electronic Theses and Dissertations

This thesis presents an applied data science methodology on a set of University of Louisville, Speed School of Engineering student data. We used data mining and classic statistical techniques to help educational researchers quickly see the data trends and peculiarities. Our data includes scores and information about two Engineering Fundamental Class. The format of these classes is called an inverted classroom model or flipped class. The purpose of this study is to analyze the data in order to uncover potentially hidden information, tell interesting stories about the data, examine student learning behavior and learning performance in an active learning environment, …