Computational Engineering Commons^™

Numerical Study Of Nutrient Mixing In Trabecular Bone In Microgravity, Disuse And Normogravity, Sagar Gharti

Doctoral Dissertations and Master's Theses

Mechanical loading is known to regulate bone remodeling by driving interstitial fluid flow which stimulates cells and drives nutrient transport within the trabecular network. In microgravity, the absence of mechanical stimulation or loading suppresses convective flow processes, causing diffusion-driven nutrient mixing and renewal, and accelerated bone loss. This thesis investigates how oscillation frequency and trabecular bone density jointly control nutrient mixing and wall shear stress within trabecular cavities.

A computational fluid dynamics (CFD) framework is developed in STAR-CCM+ using a soft-cap oscillation model that mimics cyclic compression. Three idealized trabecular morphologies are simulated across different frequencies to represent microgravity or …

A Virtual-Reality-Based Dental Simulator For Endodontics With Automated Formative Feedback, Yousef Salah Abo El Ela

Theses and Dissertations

Advancements in virtual reality (VR) and haptic technology are transforming the landscape of medical and dental education, offering new avenues for safe, immersive, and repeatable training experiences. Within dentistry, endodontics presents unique challenges for preclinical education due to anatomical complexity, limited access to extracted teeth, ethical concerns, and the shortcomings of conventional plastic models. Despite endodontics specific plastic teeth being available, they fall short of replicating the hardness of real extracted teeth, are relatively costly compared to generic plastic teeth, and are ultimately a disposable item which makes them inadequate as a sustainable long-term solution. Extracted teeth do a much …

Mechanical Characterization And Modeling Of Rat Myocardia Under The Influence Of Epirubicin, Abdallah Mahmoud Alkhaiyat

Theses and Dissertations

Cancer remains a predominant health challenge that is responsible for a significant portion of global morbidity and mortality. Epirubicin (EPI), a chemotherapeutic anti-cancer drug, has shown remarkable efficacy in combating various malignancies. However, it is known to have undesirable side effects on the heart, collectively referred to as cardiotoxicity. This research investigates the adverse effects of chemotherapy on cardiac contractility through an in vitro examination of the mechanics of healthy and infarcted animal heart tissues. Electrically stimulated slices of rat ventricular tissue were tested using an isometric force measurement tissue bath. The tissue slices were subjected to uniaxial stretching, allowing …

Microgravity-Induced Alterations In Left Atrial Hemodynamics And Thrombogenic Risk: Insights From Healthy And Atrial Fibrillation Models, Grace M. Hoeppner

Dissertations, Master's Theses and Master's Reports

Background: Microgravity exposure alters cardiovascular loading, yet its impact on left atrial flow dynamics and thrombotic risk remains poorly understood. This study investigates how spaceflight-relevant microgravity-induced changes in cardiac outflow affect left atrial hemodynamics in healthy individuals and patients with atrial fibrillation.

Methods: Patient-specific left atrial models were generated for three healthy individuals and three AF patients. Computational fluid dynamics (CFD) simulations were performed using each patient’s baseline mitral outflow waveform and two modified waveforms representing short- and long-duration post-flight cardiac loading changes derived from echocardiographic observations. Hemodynamic metrics included left atrial velocity, time averaged wall shear stress, oscillatory shear …

Probing Proficiency-Related Neural Representations With Pca And Ica, Onila R. Narayana Mudalige Don

Graduate Student Theses, Dissertations, & Professional Papers

How proficiency-related information is represented in task fMRI depends not only on the data themselves, but on the representational lens used to summarize them. This thesis examines second-language (L2) proficiency as a problem of representational organization rather than as a simple classification exercise. Using task fMRI from adult language learners performing semantic animacy judgments in their native language (L1) and second language (L2), I derive shared low-dimensional network representations with principal component analysis (PCA) and independent component analysis (ICA), then evaluate those representations under matched leakage-controlled decoding pipelines.

Across analyses, the central comparison is between representational frameworks rather than between …

Towards Computational Methods In Medical Data Analysis: From Speech And Text To Imaging, Kristin Qi

Graduate Doctoral Dissertations

Early detection of cognitive decline and efficient medical image analysis remain critical challenges in healthcare. Traditional clinical assessments are infrequent and resource-intensive, while everyday speech data and unlabeled medical images remain largely unexploited. This dissertation develops computational methods integrating machine learning and artificial intelligence across speech, text, and imaging modalities to address challenges in medical data processing. For cognitive monitoring, this work first introduces methods using voice assistant systems to collect longitudinal speech data in home environments, demonstrating that incorporating historical session patterns significantly enhances detection of mild cognitive impairment. Building on this foundation, a framework combining large language model-driven …

Bending Energy Schemes For Discrete-Spring-Network Structural Modelling Of Red Blood Cells, Osayomwanbor Ehi-Egharevba, Mingzhu Chen, Fergal Boyle

Articles

Red blood cells (RBCs) undergo large structural deformation, including bending, when passing through capillaries. They also exhibit a range of complex shapes such as stomatocytes, discocytes and echinocytes that form due to altered blood pH and salt levels, ingested drugs and adenosine triphosphate depletion. Discrete-spring-network structural models of RBCs employ different numerical treatments of the continuum bending energy. This affects bending accuracy and the prediction of accurate RBC shapes. This research compares three representations called bending energy scheme (BES) A, B and C to evaluate their accuracy in shape predictions. BES A, seen throughout the literature, is based on the …

Modeling Synaptic Dysfunction As Neural Contagion: A Graph-Based Sedr Framework For Simulating Signal Spread, Michelle Marfo, Dr. Padmanabhan Seshaiyer, Alonso Ogueda-Oliva

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Fundus Retinal Images And Glaucoma Detection, Lama Alsabban, Malak Alnahdi, Nema Salem

Effat Undergraduate Research Journal

Abstract. Glaucoma is a severe eye disease that has no symptoms and, globally, it is the second cause of blindness. Glaucoma causes structural changes in the retina that make ophthalmologists detecting the disease in early stage and thus provide the suitable treatment. Fundus camera is an imaging technique that provides the fundus image showing the internal structure of retina. Our project provides an automated system for early detection of Glaucoma. The proposed system based MATLAB starts by acquiring the fundus image, followed by preprocessing stage, going through noise removal, enhancement, segmentation, feature extraction and ends up by the classification stage. …

Toward The Application Of Natural Language Processing In Electronic Health Record Analysis For Taxonomy Development, Latoya Mcdonald

All Dissertations

Electronic health records (EHRs) are pivotal resources for nurse practice because they increase the timeliness and reliability of patient information at the point of care and support access by multiple healthcare providers and the individual patients themselves. However, it is widely recognized that data extraction from EHRs is challenging due to the variability in the language used in clinical care notes and the lack of standardized terminology across healthcare systems. The broad objective of this dissertation is to develop taxonomy-based classification models for nursing care by applying feature engineering approaches to EHRs that include nursing care of ostomy patients following …

Direct Numerical Simulation Of Pulsating Flow In Curved Pipes: Insights Into Aortic Dissection In Humans, Gokul Anugrah Gopakumar

Theses and Dissertations--Mechanical and Aerospace Engineering

This dissertation investigates the hemodynamics of pulsating blood flow in curved vessels through direct numerical simulations (DNS), with the overarching aim of uncovering fluid dynamic mechanisms linked to the onset and progression of aortic dissection in humans. The work is structured in two parts: (i) fundamental studies in idealized geometries and (ii) preliminary investigations in patient-specific anatomies. In the first part, curved pipe models representing the aortic arch are used to isolate the effects of pulsation frequency, amplitude ratio, and curvature ratio on transitional and turbulent flow dynamics. The simulations reveal that curvature-driven centrifugal forces shift the peak velocity toward …

Assessing The Impact Of Femur Morphological Variations On Pediatric Hip Joint Biomechanics Using Statistical Shape Modeling, Tamara Chambers

Doctoral Dissertations and Master's Theses

This dissertation aimed to (1) quantify morphological variations in the pediatric hip joint and (2) evaluate the sensitivity of an infant musculoskeletal model (MSM) to these variations, considering hip joint center estimation errors. A shape statistical model (SSM) of decedent infant femurs from the Ortolani collection was created using ShapeWorks, capturing key morphological features, such as variations in the femoral neck-shaft and anteversion angles. Seven synthetic femurs were generated from the SSM to create SSM-informed MSMs, which were systematically evaluated through kinematics and kinetics analyses in OpenSim. Incorporating the SSM led to slight changes in the pediatric MSMs’ kinematics but …

Exploring The Identification Of Autoregression Model By General Least Deviation Method, Mostafa Abotaleb, Tatiana Makarovskikh, Ramadhan, Ali J

Al-Bahir

We are considering a novel method for analyzing time series data that relies on quasi-linear recurrence relations. Unlike neural networks, this approach allows for directly formulating high-quality quasi-linear difference equations that accurately represent the studied process. Techniques for determining the parameters of a single equation have been devised and validated. This work discusses and tests a technique for identifying the parameters of a quasi-linear recurrence equation. This approach is employed to tackle the issue of regression analysis including observable variables that are mutually dependent. It enables the utilization of the Generalized Least Deviations Method (GLDM). This model was utilized in …

Collision Dynamics Of Compound Droplets In Microchannels: A Combined Numerical And Data-Driven Study, S M Abdullah Al Mamun

Dissertations

Understanding and predicting the hydrodynamic interactions of micron-scale droplets is crucial in a wide range of industrial and real-life applications, including microfluidics, pharmaceutics, drug delivery, food science, and enhanced oil recovery. These multi-phase and multi-scale phenomena are further complicated by the presence of core droplets of an immiscible fluid within shell droplets, known as compound droplets. The collisions and interactions of droplets in emulsions are influenced by various physical and geometric parameters, leading to distinct rheological and dynamic responses. This research employs numerical methods for a systematic parametric study of both simple and compound droplet pair collisions under confined shear …

Auxiliary Diagnosis Of Dental Calculus Based On Deep Learning And Image Enhancement By Bitewing Radiographs, Tai Jung Lin, Yen Ting Lin, Yuan Jin Lin, Ai Yun Tseng, Chien Yu Lin, Li Ting Lo, Tsung Yi Chen, Shih Lun Chen, Chiung An Chen, Kuo Chen Li, Patricia Angela R. Abu

Ateneo Laboratory for Intelligent Visual Environments

In the field of dentistry, the presence of dental calculus is a commonly encountered issue. If not addressed promptly, it has the potential to lead to gum inflammation and eventual tooth loss. Bitewing (BW) images play a crucial role by providing a comprehensive visual representation of the tooth structure, allowing dentists to examine hard-to-reach areas with precision during clinical assessments. This visual aid significantly aids in the early detection of calculus, facilitating timely interventions and improving overall outcomes for patients. This study introduces a system designed for the detection of dental calculus in BW images, leveraging the power of YOLOv8 …

An Attention Lstm U-Net Model For Drosophila Melanogaster Heart Tube Segmentation, Xiangping Ouyang

McKelvey School of Engineering Graduate Student Theses & Dissertations

Machine learning is commonly used in biomedical image analysis, as it allows automated image segmentation and identification that minimizes the need for tedious human involvement. Drosophila melanogaster is often used as a cardiac disease model, where optical coherence microscopy (OCM) is used to image and analyze its beating dynamics. As OCM often generates a large volume of images, automated image segmentation is necessary to quantify the heart beating efficiently. Our most recent heart segmentation model, FlyNet 2.0+, is a fully convolutional LSTM U-Net model. However, the performance of the model diminishes in the presence of artifacts, such as image reflection …

Presence Of Atheromatous Plaques And Theirs Effects On The Blood Flow, Belhocine Mostefa Bm, Amrani Hichem Ah, Fedaoui Kamel Dr, Mazouz Hammoudi Mh

Emirates Journal for Engineering Research

The paper utilizes a finite element method to study both the blood flow and atheromatous plaques. Specifically, the COMSOL finite element package is employed to achieve a fluid model. COMSOL is a powerful finite element tool commonly used in various research and industrial domains to study multiphysics problems. The focus of the investigation is on the geometric aspects of the atheromatous plaques. The study considers different forms and arrangements of stenosis, taking into account the irregularities formed by various shapes of the plaques and the resulting flow patterns. The key findings of the research suggest that the pressure and velocity …

Multicellular And Multiscale Models Of Microbes And Host Systems, Elebeoba May

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Digital Twins Of The Living Knee: From Measurements To Model, Thor Erik Andreassen

Electronic Theses and Dissertations

Modern medicine has dramatically improved the lives of many. In orthopaedics, robotic surgery has given clinicians superior accuracy when performing interventions over conventional methods. Nevertheless, while these and many other methods are available to ensure treatments are performed successfully, far fewer methods exist to predict the proper treatment option for a given person. Clinicians are forced to categorize individuals, choosing the best treatment on “average.” However, many individuals differ significantly from the “average” person, for which many of these treatments are designed. Going forward, a method of testing, evaluating, and predicting different treatment options' short- and long-term effects on an …

Automatic Cardiac Mri Image Segmentation And Mesh Generation, Ziyuan Li

McKelvey School of Engineering Graduate Student Theses & Dissertations

Segmenting and reconstructing cardiac anatomical structures from magnetic resonance (MR) images is essential for the quantitative measurement and automatic diagnosis of cardiovascular diseases [1]. However, manual evaluation of the time-series cardiac MRI (CMRI) obtained during routine clinical care are laborious, inefficient, and tends to produce biased and non-reproducible results [2]. This thesis proposes an end-to-end pipeline for automatically segmenting short-axis (SAX) CMRI images and generating high-quality 2D and 3D meshes suitable for finite element analysis. The main advantage of our approach is that it can not only work as a stand-alone pipeline for the automatic CMR image segmentation and mesh …

Nanoscale Modeling Of Membrane Systems Under Mechanical Deformation In Traumatic Brain Injury Using Molecular Dynamics, Anh Thi Ngoc Vo

Theses and Dissertations

Neuronal membrane disruption and mechanoporation are nanoscale damage mechanisms that critically affect brain cell viability during traumatic brain injury (TBI). These nanoscale cellular impairments are elusive in experiments and necessitate in silico approaches such as molecular dynamics (MD) simulations. Implementing MD, this research aims to investigate the effects of different key factors related to membrane deformation and damage, including force field resolutions, lipid compositions, and loading conditions.

To examine the impact of force field resolution, MD deformation simulations were conducted on 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphatidylcholine (POPC) lipid bilayer membranes, using all-atom (AA), united-atom (UA), and coarse-grained Martini (CG-M) force fields. The mechanical responses …

Neurocomputing And Interfacing Digital Tasting System: Research, Design, And Evaluation, Amira J. Zaylaa, Ahmad El Hajj

BAU Journal - Science and Technology

The continuous evolution in computing and interfacing has been extended to develop multi-sensory experiences in many domains such as neurological, auditory, vision, and haptic domains. So far, only a few remarkable system approaches have been approved to be serving the taste sensation digitally. Although taste sensation is linked to the brain, there is a lack of optimal neurocomputing digital taste sensation systems. Our study provides a new neurocomputing method to digitally stimulate the sense of taste by electrical stimulation on the human tongue. We aim to link chemical stimulation and electrical stimulation in order to design an electronic interface for …

Enhancement Of Deep Learning Protein Structure Prediction, Ruoming Shen

Modeling, Simulation and Visualization Student Capstone Conference

Protein modeling is a rapidly expanding field with valuable applications in the pharmaceutical industry. Accurate protein structure prediction facilitates drug design, as extensive knowledge about the atomic structure of a given protein enables scientists to target that protein in the human body. However, protein structure identification in certain types of protein images remains challenging, with medium resolution cryogenic electron microscopy (cryo-EM) protein density maps particularly difficult to analyze. Recent advancements in computational methods, namely deep learning, have improved protein modeling. To maximize its accuracy, a deep learning model requires copious amounts of up-to-date training data.

This project explores DeepSSETracer, a …

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 …

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 …

Mango Surface Color Features Measurement Using Digital Image Processing, Md Towfiqur Rahman, Goutom Kumar, Md Abdul Momin

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Summary

Postharvest processing of agricultural produce is still done the conventional way in Bangladesh. Manual grading of agricultural produce, especially fruits and vegetables, is laborious and costly due to acute shortage of labor during the peak season, as well as difficulty maintaining the product quality. Machine vision system (MVS) applications are widely used nowadays as a non-destructive and cost-effective technology for automatically grading and sorting large volumes of produce in the packing house according to size, shape, color, texture, and surface defects. In this study, a simple MVS was constructed measuring different color features of mango fruit surface as a …

Application Of Deep Learning For Medical Sciences And Epidemiology Data Analysis And Diagnostic Modeling, Somenath Chakraborty

Dissertations

Machine Learning and Artificial Intelligence have made significant progress concurrent with new advancements in hardware and software technologies. Deep learning methods heavily utilize parallel computing and Graphical Processing Units(GPU). It is already used in many applications ranging from image classification, object detection, segmentation, cyber security problems and others. Deep Learning is emerging as a viable choice in dealing with today’s real-time medical problems. We need new methods and technologies in the field of Medical Science and Epidemiology for detecting and diagnosing emerging threats from new viruses such as COVID-19. The use of Artificial Intelligence in these domains is becoming more …

Cardio-Net: A Matlab-Based Software For The Display And Diagnostic Utilization Of Vectorcardiograms, Ali H. Mannaa, Domenico Gatti

Medical Student Research Symposium

Background: The 12-lead technique is the standard in ECG, however alternate cardiography modalities such as vectorcardiography (VCG) exist . While the VCG modality offers unique clinical metrics and certain advantages over ECG, it is hardly utilized due to it being more difficult to obtain than ECG. Here we introduce Cardio-Net, a MATLAB-based software that uses standard 12-lead ECG data to generate and visualize VCGs. Furthermore, we demonstrate the diagnostic potential of VCG by utilizing a recurrent neural network (RNN) to accurately classify vectorcardiograms.

Methods: MATLAB version 2019b and the following toolboxes were used for data processing: Deep learning, …

Representation Learning For Chemical Activity Predictions, Mohamed S. Ayed

Dissertations, Theses, and Capstone Projects

Computational prediction of a phenotypic response upon the chemical perturbation on a biological system plays an important role in drug discovery and many other applications. Chemical fingerprints derived from chemical structures are a widely used feature to build machine learning models. However, the fingerprints ignore the biological context, thus, they suffer from several problems such as the activity cliff and curse of dimensionality. Fundamentally, the chemical modulation of biological activities is a multi-scale process. It is the genome-wide chemical-target interactions that modulate chemical phenotypic responses. Thus, the genome-scale chemical-target interaction profile will more directly correlate with in vitro and in …

Numerical And Scaling Study On Application Of Inkjet Technology To Automotive Coating, Masoud Arabghahestani Dr.

Theses and Dissertations--Mechanical and Aerospace Engineering

A thorough literature review identified lack of precision control over quality of droplets generated by the currently available industrial sprayers and a growing need for higher quality droplets in the coating industry. Particularly, lack of knowledge and understanding in continuous inkjets (CIJ) and drop-on-demand (DOD) technologies is identified as significant. Motivated by these needs, this dissertation is dedicated to computational fluid dynamics (CFD) and scaling studies to improve existing inkjet technologies and develop new designs of efficient coating with single and/or multiple piezoelectric sensors to produce on-demand droplets. This dissertation study aims at developing a new DOD type coating technology, …