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The Little Diagram That Could: Geometric Properties And Statistical Applications Of Persistence Diagrams In Topological Data Analysis, Eugene Kler

McKelvey School of Engineering Graduate Student Theses & Dissertations

Topological Data Analysis (TDA) is a collection of techniques for data analysis that leverages topological invariants of spaces formed from data points. These methods excel at extracting useful information from noisy or sparse data, making them attractive to many mathematicians, statisticians, and scientists. In this thesis, we explore TDA on three fronts: algebraic foundations, statistical applications, and metric properties. Throughout, the central object of study is the Persistence Diagram (PD), a summary of the changes in homology that occur as one builds simplicial complexes from the data by increasing a parameter.

Game Changing Education: Empowering High School Stem Teachers To Teach Engineering Using Games, Leslie Brown

All Graduate Theses and Dissertations, Fall 2023 to Present

In response to the Next Generation Science Standards (NGSS) released in 2013, there was a nationwide push for K-12 schools to include engineering concepts in science classrooms. However, there is an overall lack of teacher preparedness and training towards engineering topics as shown by common engineering misconceptions. To improve this issue, I initiated a qualitative study to describe the strategies and attitudes of high school science, technology, engineering, and mathematics (STEM) teachers that have implemented game-based, engineering activities into their classroom. Game-based learning is an instructional framework that utilizes game-like elements in a classroom and was used in this study …

Cross-Dataset Fairness Evaluation Of Transformer-Based Sentiment Models, Sara Zuiran

Theses and Dissertations

With the growing exploration of Natural Language Processing (NLP) systems in decision-making environments, it is essential to evaluate technical and ethical aspects of the dataset and the NLP model to improve fairness. To assess fairness, the thesis examines demographic imbalances in sentiment classification models by evaluating transformer-based models fine-tuned on the Stanford Sentiment Treebank version 2 dataset (SST-2) against the demographically annotated Comprehensive Assessment of Language Model dataset (CALM). This work identifies performance disparities in sentiment prediction across demographic groups by examining sensitive attributes such as gender and race. The study evaluates both the RoBERTa and MentalBERT transformer models using …

Developing Predictive Mathematical Model For Optimizing Coating Weight Variation In Galvalume Production: A Case Study Of A Metal Industry, Victoria Mahabi

Tanzania Journal of Engineering and Technology (TJET)

Variations in coating weight for galvanized steel sheets can result in notable differences between batches. Such variations may cause various issues, such as diminished corrosion resistance, lower mechanical strength, and visual defects, which can ultimately drive-up costs, lead to customer dissatisfaction, and pose safety risks. Even with attempts to manage elements like air knife pressure and line speed, coating weight inconsistencies remain challenging. The research focuses on developing a predictive mathematical model designed to optimize variations in coating weight during Galvalume production. The critical parameters influencing coating weight variation were identified and analysed using a systematic literature review, primary data …

A Comprehensive Analysis Of Recognition Of Hand Gestures Using Machine Learning, Shivani Shivani, Satinder Bal Gupta

Makara Journal of Technology

Hand gestures are a natural means of conveying information and thus, there is an increasing interest in utilizing gestures for communication with computers. This study focuses on systematically reviewing different machine learning algorithms while assessing their working mechanisms and accuracy. Articles were analyzed for comparing the performance of K-Nearest Neighbors (KNN), Random Forest (RF), Support Vector Machines (SVM), Naive Bayes (NB), Convolutional Neural Networks (CNN), and Recurrent Neural Networks (RNN). In accordance with input data, intricacy of gestures, processing resources, and real-time demands, the study shows that each technique has distinct advantages and disadvantages. RNN showed the best accuracy of …

Microwave Ore Pre-Treatment Review And Process Flowsheet Conceptualization, Baker F. Giyani

Tanzania Journal of Engineering and Technology (TJET)

The global demand for mineral commodities has increased dramatically over the years, and this is largely due to several factors, including technological advancements, industrialization, and a rise in population. Further, the demand keeps increasing because the ore being mined is becoming more complex, and the feed grade is declining over the years, prompting the need for innovative technologies to treat such ores more efficiently. Microwave ore pre-treatment is one of the potential technologies that can be employed to improve process performance. This is possible because ores are composed of both good-microwave heaters and poor microwave heaters, which creates thermal stresses …

Research Of The Dynamic Characteristics Of A Time-Pulse Ultrasonic Sensor, Aliev Ravshan, A.U. Djalilov

Chemical Technology, Control and Management

This article investigates the dynamic characteristics of a time-pulsed ultrasonic sensor used to measure water flow in open channels. The operating principle of the sensor, its response time in various hydrodynamic conditions, speed, and factors affecting measurement accuracy are analyzed. In the process of research, the improved ultrasonic sensor was tested and its effectiveness in measuring water flow in real time was evaluated. The results obtained showed that the sensor adapts to the velocity, temperature and turbulence level of the water flow. Based on the results of the research, the possibilities of working of time-impulse ultrasound sensors in open channels …

Security In Biometric Access Control Systems Based On Fingerprints, Elmurad Jamuradovich Qilichev, Baxodir Saydullaevich Achilov, Ismoil Ergash OʻGʻLi Isroilov, Mirshod Mirkomil O'G'Li Ahmadov

Chemical Technology, Control and Management

This article analyzes biometric access control systems using fingerprints. The article considers the advantages of using biometric technologies, including solutions aimed at ensuring security, protecting users' personal data, and increasing the efficiency of systems. A detailed explanation of the principles of operation of fingerprint biometric systems, their underlying algorithms, and technological advances is provided. Problems that arise when assessing the level of security, ease of use, and technological and social aspects of biometric access systems and methods for combating them are also covered. At the end of the article, opinions are expressed about the future of fingerprint-based biometric systems and …

Artificial Intelligence Applications For Grid-Connected Solar Inverters, Utkirjon Ubaydullaev, Sarvinoz Mirzaeva, Hasan Mustafoev

Chemical Technology, Control and Management

The increasing global demand for renewable energy has highlighted the importance of grid-connected solar inverters in ensuring efficient and stable power conversion. However, challenges such as fluctuations in solar energy generation, grid disturbances, and power quality issues necessitate advanced control strategies. The integration of artificial intelligence (AI) into solar inverters presents a transformative solution, enhancing performance, adaptability, and reliability in real-world applications.

This review explores the role of AI techniques, including machine learning (ML), deep learning (DL), fuzzy logic, and reinforcement learning (RL), in optimizing key inverter functionalities such as maximum power point tracking (MPPT), fault detection, power quality enhancement, …

Static Characteristics Of An Electromagnetic Three-Phase Reactive Power Sensor For Converting Asymmetric Currents, Timur Urunbayevich Kurbaniyazov

Chemical Technology, Control and Management

This article discusses the processes in the elements and structures of three-phase electromagnetic current sensors used in measuring and controlling three-phase asymmetric reactive power in power supply systems, research models of quantities and parameters, physical mechanisms, and mathematical formulas based on graphical models.

Algorithms For Feature Extraction And Optimisation Of Object Recognition Operator, Hudayberdiev Xakkulmirzayevich Mirzaakbar, Bobomurod Mamitjonovich Tojiboev, Feruza Komiljonovna Samadova

Chemical Technology, Control and Management

This paper deals with the development and analysis of feature extraction and optimisation algorithms for object recognition operators. Different algorithms are used to improve the efficiency of recognition operators in the automatic analysis of remote sensing images. The information model of objects and methods for selecting, extracting and optimising their features have been studied. The issue of extracting important features of objects using spectral, textural and statistical features and constructing optimal operators based on them has also been studied. Effective approaches based on the theory of convex hulls and multidimensional analysis methods have been proposed, taking into account the mutual …

Application Of Quantum Algorithms In Optimization Of Cognitive Decision-Making Systems, Noilakhon Yakubova

Chemical Technology, Control and Management

The article analyzes the potential of quantum algorithms for optimizing cognitive decision-making systems in production processes in the energy sector. Compared with traditional algorithms, quantum algorithms allow high-speed processing of large amounts of variable data in real time and solving multiparameter problems based on an integrated approach. The study considers uncertainties and issues of increasing efficiency in the processes of production and distribution of electricity using a cognitive model. The integration of quantum algorithms into this model allows developing optimal strategies for using resources in production. A heating boiler was taken as a control object, and taking into account its …

Algorithms For Fast Fire Risk Prediction And Real-Time Data Processing, Mirzoyan Mirzaaxmedovich Kamilov, Tolaniddin Ramziddinovich Nurmukhamedov, Oybek Zokirovich Koraboshev, Bakhodir Saydullayevich Achilov

Chemical Technology, Control and Management

Ensuring fire safety in facilities with high fire risk is one of the pressing problems of modern society. Nowadays, there is a great need for accurate and effective prediction systems for fire prevention and rapid response. Since traditional methods do not provide the ability to quickly analyze and predict in real time, the development of algorithms and modern approaches using modern technologies is of great importance. This article analyzes fire risk prediction algorithms, their principles of operation and effectiveness, and considers methods for assessing and predicting fire risk using Artificial Intelligence (AI), Machine Learning (ML), and Big Data technologies. The …

Detection Of Http Flood Attacks Based On Machine Learning Algorithms, Norbek Karimov, Furkat Rakhmatov, Oybek Xolmuminov

Chemical Technology, Control and Management

This paper analyzes the effectiveness of Random Forest and SVM models for detecting HTTP Flood attacks. Experimental results demonstrate that both models achieve high accuracy. Evaluation was conducted using Precision, Recall, and F1 Score metrics. Additionally, key features of network traffic were extracted through correlation analysis to enable real-time application of the models in attack detection. The findings provide important insights into detecting DDoS attacks using machine learning and improving model performance.

Towards Human Modeling For Human-Robot Collaboration And Digital Twins In Industrial Environments: Research Status, Prospects, And Challenges, Guoyi Xia, Zied Gharairi, Thorsten Wuest, Karl Hribernik, Aaron Heuermann, Furui Liu, Hui Liu, Klaus-Dieter Thoben

Faculty Publications

Human-Robot Collaboration (HRC) and Digital Twins (DT) have significantly advanced industrial development and digital transformation. Human representations and models are essential in Industry 5.0, where human-centric is one of the key features. Despite the growing interest in human models for HRC and DT, a comprehensive overview of these models and enabling technologies currently needs to be provided. This paper aims to present the research status, prospects, applications, and challenges of human modeling for HRC and DT in industrial environments. This paper adopts a Systematic Literature Review (SLR) approach. Moreover, a framework is proposed to systematize human modeling aspects, the technologies …

Enhanced And Interpretable Prediction Of Multiple Cancer Types Using A Stacking Ensemble Approach With Shap Analysis, Shahid Mohammad Ganie, Pijush Kanti Dutta Pramanik, Zhongming Zhao

Faculty, Staff and Student Publications

Background: Cancer is a leading cause of death worldwide, and its early detection is crucial for improving patient outcomes. This study aimed to develop and evaluate ensemble learning models, specifically stacking, for the accurate prediction of lung, breast, and cervical cancers using lifestyle and clinical data.

Methods: 12 base learners were trained on datasets for lung, breast, and cervical cancer. Stacking ensemble models were then developed using these base learners. The models were evaluated for accuracy, precision, recall, F1-score, AUC-ROC, MCC, and kappa. An explainable AI technique, SHAP, was used to interpret model predictions.

Results: The stacking …

Quantifying Treatment Response To A Macrophage-Targeted Therapy In Combination With Immune Checkpoint Inhibitors After Exposure To Conventional Chemotherapy, Shelby N. Bess, Gaven K. Smart, Timothy J. Muldoon

Biomedical Engineering Faculty Publications and Presentations

Background: Conventional chemotherapeutic agents, such as 5-fluorouracil (5-FU), can exert anti-tumor effects through immunogenic cell death (ICD) induction. Researchers have found hallmarks that quantify ICD (such as the translocation of HMGB1 and calreticulin). Although chemotherapeutic agents can induce ICD, they increase the expression of immune checkpoints, limiting their effectiveness. Studies have emphasized the importance of investigating the heterogeneous responses of cells co-localized in a solid tumor (macrophages, tumor cells, etc.) to ICD induction. However, these studies were performed in vivo, which limits the collection of information on cell-cell interactions due to model complexity.

Methods: In this study, we used a …

Interference Management For Next-Generation Dynamic Spectrum Sharing, Jie Wang

McKelvey School of Engineering Graduate Student Theses & Dissertations

The exponential growth of wireless devices and bandwidth-intensive applications has intensified the demand for efficient spectrum utilization, exposing the limitations of traditional static spectrum allocation schemes. Next-generation spectrum sharing has emerged as a transformative solution to enhance spectrum efficiency by enabling multiple wireless systems to coexist opportunistically in the same frequency band and geographic area. However, such dynamism introduces significant challenges, particularly in interference management, which is critical to enabling reliable coexistence, ensuring access priority, and building mutual trust across diverse applications. This thesis advances interference management by developing advanced techniques for interference prediction, monitoring, and control in dynamic spectrum …

Quantum Machine And Deep Learning For Medical Image Classification: A Systematic Review Of Trends, Methodologies, And Future Directions, Eman A. Radhi, Mohammed Y. Kamil, Mazin Abed Mohammed

Iraqi Journal for Computer Science and Mathematics

Quantum Learning (QL) has emerged as a promising approach to medical image classification, leveraging the principles of quantum mechanics to improve the performance and efficiency of machine learning algorithms. This systematic review provides a comprehensive critical assessment of the current status of QL techniques developed for medical image classification, with a specific focus on trends, methodologies, and future directions in this rapidly evolving field. A thorough literature search was conducted across five major databases, resulting in a total of 28 relevant studies published between 2018 and 2024. The studies were analyzed and classified based on the type of quantum algorithm, …

Liberated Arabic Handwritten Text Recognition Using Convolutional Recurrent Neural Networks, Ahmad Abdulqadir Alrababah, Mohammed Khalid Aljahdali, Abdulrahim Abdulhamid Al Jahdali, Mohammed Saleh Alghanmi, Israa Ibraheem Al_Barazanchi

Iraqi Journal for Computer Science and Mathematics

Arabic script is exhibited in a cursive style, which is a departure from the norm in many common languages, and the shapes of letters are contingent on their positions within words. The form of the first letter is influenced by the subsequent letter, middle letters are shaped by both preceding and succeeding letters, and the shape of the final letter is determined by the preceding letter. Additionally, certain letters are found to have strikingly similar shapes, making Arabic text recognition a formidable challenge in computer vision. The challenge of detecting and recognizing Arabic handwritten text is addressed in this paper …

Characteristics Of Dynamic Mode Ⅱ Fracture Of Frozen Saturated Sandstones Under Varying Low Temperatures And Loading Rates, Zhao Tao, Cui Zhao, Jia Hailiang, Yang Guangyu

Coal Geology & Exploration

Background Investigating the mode Ⅱ fracture of frozen saturated sandstones under dynamic disturbances, including changes in their critical stress intensity factor (SIF; i.e., fracture toughness) and energy dissipation mechanisms, is crucial for the safe excavation of frozen wellbores through drilling and blasting in coal mines. Methods Using a split Hopkinson pressure bar (SHPB), this study conducted experiments on the dynamic mode Ⅱ fracture of a sandstone specimen using the short core in compression (SCC) method (also referred to as dynamic SCC experiments) under varying temperatures and loading rates. Accordingly, this study analyzed the SIF versus time curves of the frozen …

Capturing Interfacial Phase Change And Flow Physics During Vertical Downflow Condensation, Thanh Hoang Phan, Cho Ning Huang, Chirag R. Kharangate

Faculty Scholarship

Two-phase configurations can address the urgent demand for effective heat dissipation solutions in Naval power and energy systems. A better understanding of thermal transport processes in phase-change flows is critical for developing novel two-phase design tools for naval scientists and engineers. This study investigates interfacial phase change and flow dynamics during condensation flow through numerical simulations. An enhanced phase change model, incorporating a mass transfer intensity coefficient dependent on condensation film thickness, is implemented for vertical downflow condensation. A two-dimensional homogeneous two-phase Reynolds-Averaged Navier-Stokes model, coupled with the Shear-Stress Transport k-ω turbulence model, is employed. The developed solver is thoroughly …

A Study Of The Parameters Involved In Nir Sintering Of Silver Microparticle-Based, Pad-Printed Features, Jonah Clement Brooks

Theses and Dissertations

This study explores the effectiveness of pad printing and near-infrared (NIR) sintering for producing conductive silver microparticle traces. A new pad printer was set up, and silver inks with varying concentrations of silver particles (17.5 %v/v, 20 %v/v, and 25 %v/v) were manufactured, printed, and sintered. The study identified sintering time and silver concentration as the most influential parameters affecting resistivity, with the best result of 8.73 × 10⁻⁷ Ω·m achieved using 25 %v/v ink sintered for 3 seconds at full power. Although resistivity continued to decrease at this maximum sintering duration, further optimization of parameters, including NIR bulb distance …

Small-Scale Production Of Bespoke Accelerated Aging Plutonium Alloy, K. S. Holliday, A. M. Parkes, Devin Rappleye, D. J. Roberts, K. J. Kondrat, S. A. Simpson, A. J. Swift, U. Mehta, R. M. Kissinger, D. L. Rosas, L. S. Ripplinger, E. R. Tardiff, S. L. Harris, S. Perkins, C. Hawkins, N. J. Gibbs, R. J. P. Driscoll, A. T. Sidambe, R. A. Cole, T. T. Roehling, J R. Jeffries

Faculty Publications

This study demonstrates the 100 g scale manufacture of a plutonium alloy that ages at an accelerated rate. The resulting alloy ages six times faster than typical weapons-grade plutonium due to the addition of ²³⁸Pu. As a major innovation, the process involved using a partial direct oxide reduction technique. This method was achieved by developing a new, complex geometry stirrer using additive manufacturing to reduce the ²³⁸Pu oxide and efficiently incorporate it into weapons-grade plutonium metal. The material was then purified by molten salt extraction and electrorefining before being alloyed with gallium. The alloy was then cold-rolled and …

Mechanism Of Property Enhancement Of Cu−Ti Alloys Via Microalloying With Cr And Mg Elements, Huan Wei, Hong Wei, Hua-Yun Du, Qian Wang, Cai-Zhi Zhou, Ying-Hui Weu, Li-Feng Hou

Faculty Publications

The effect of adding Cr and Mg on the microstructure and properties of Cu−Ti alloys was examined. Cu−Ti−Cr−Mg alloys were fabricated using vacuum induction melting. The microstructure and phase composition of Cu−Ti−Cr−Mg alloys in different aging states were characterized. Additionally, the hardness and electrical conductivity of the materials were investigated. Results show that the precipitation pattern in Cu−Ti−Cr−Mg alloys resembled that of binary Cu−Ti alloys, with Cr and Ti forming the intermetallic compound of Cr2Ti during casting. The introduction of Cr and Mg increased the hardness of the alloy. Increasing the Mg content in the Cu−Ti−Cr−Mg alloy led to grain …

Assessing The Impact Of Internal Flow Dynamics On Detection Region Concentrations Of Low-Cost Optical Particle Counters, Livingstone Quarshie

Theses and Dissertations

Particulate matter (PM) poses significant risks to human health and the environment, making accurate measurement essential for exposure assessment and regulatory decisions. While traditional reference methods provide reliable data, they are often bulky, expensive, and difficult to maintain. Optical Particle Counters (OPCs) offer a cost-effective alternative, commonly used in clean rooms, residential spaces, and personal exposure monitoring. These devices rely on light scattering to measure PM concentrations. However, low cost OPCs face challenges related to calibration and measurement accuracy, requiring careful performance evaluation. This study used computational fluid dynamics (CFD) tools, CONVERGE Studio and ANSYS Fluent, to simulate a simplified …

In-Situ Void Formation During Liquid Composite Molding For Preformed Warp, Weft, And Alternating Orientation Rtm Samples, Tanner Cal Garrett

Theses and Dissertations

Carbon fiber reinforced parts are utilized by the transportation industry due to being strong yet lightweight. The highest quality parts are made using carbon fiber (CF) pre-impregnated with resin processed in an autoclave to reduce void content. The autoclave process is expensive and takes up a large amount of space, so liquid composite molding (LCM) is a less expensive alternative. The parts produced using LCM can be manufactured to rival the mechanical performance of parts made with pre-preg in an autoclave, but concerns remain over voids. Most research pertaining to void formation has been done ex-situ by either micro-CT or …

Surface-Texture Fabrication Of Zirconia-Toughened Alumina Using Focused Ion-Beam Machining, Kameron M. Woodruff

Theses and Dissertations

Focused ion-beam machining (FIBM), a precise form of micro-machining, was tested for feasibility in the manufacturing of microscopic dimples in zirconia-toughened alumina (ZTA), a wear resistant ceramic used in artificial joint replacements. The interaction between the ion-beam and the ceramic was characterized in terms of material removal rate (MRR), surface roughness, and notable irregularities (e.g. pitting, steps at vertical faces). These characteristics were used to design and machine patterns of microscopic dimples for tribological testing. The dimple size and pattern area were limited due to a slow MRR and high cost of milling. No significant difference in the coefficient of …

Investigation Of Temperature Control's Effects In Additive Friction Stir Deposition Of Al 7050-T7451, Jason Noah Glenn

Theses and Dissertations

Additive Friction Stir Deposition (AFSD) is a friction stir based process that includes the addition of material extruding through a bore in the center of the rotating tool. The deformation of the material from the tool rotation and high pressures result in fully dense depositions printed at very high rates with forged like mechanical properties. While deposition properties of varying alloys have been increasingly published, little work has been done investigating control of the process and as with all additive processes, consistency and predictability are of significant concern before implementation can occur. One common control method implemented in Friction Stir …

Scalable Cyber-Physical Testbed For Cybersecurity Evaluation Of Synchrophasors In Power Systems, Shuvangkar Chandra Das, Tuyen Vu, Hebert L. Ginn Iii

Faculty Publications

This paper presents a synchrophasor-based real-time cyber-physical power system testbed with a novel security evaluation tool, pySynphasor, that can emulate different real attack scenarios on the phasor measurement unit (PMU). The testbed focuses on real-time cyber-security emulation using different components, including a real-time digital simulator, virtual machines (VM), a communication network emulator, and a packet manipulation tool. The script-based VM deployment and software-defined network emulation facilitate a highly scalable cyber-physical testbed, which enables emulations of a real power system under different attack scenarios such as address resolution protocol (ARP) poisoning attack, man-in-the-middle (MITM) attack, false data injection attack (FDIA), and …