Engineering Commons^™

Biom 2720: Experimental Design And Analysis For Biomedical Engineering (Syllabus), Stephen Strain

Biomedical Engineering Syllabi Archive

Course Description: Application of probability, statistics, error analysis, uncertainty in design and performance of biomedical engineering experimentation; discussion and evaluation of common experimental designs for medical device development.

Biom 3110: Medical Physiology (Syllabus), Bradford D. Pendley

Biomedical Engineering Syllabi Archive

Course Description: Basic principles of human physiology and how these are applied in medicine and biomedical engineering problem and devices; physiological principles using appropriate mathematical and engineering models to construct an understanding of how the body works as an integrated system.

Biom 2720: Experimental Design And Analysis For Biomedical Engineering (Syllabus), Stephen Strain

Biomedical Engineering Syllabi Archive

Course Description: Application of probability, statistics, error analysis, uncertainty in design and performance of biomedical engineering experimentation; discussion and evaluation of common experimental designs for medical device development.

Biom/Biol 4110: The Science Of Medicine (Syllabus), Bradford D. Pendley

Biomedical Engineering Syllabi Archive

Course Description: Integration of fundamental principles from physics, chemistry, biology and mathematics, and applications of these principles to solve problems in medicine.

Engr 1010: Engineering Problem Solving (Syllabus), Stephen Strain

Biomedical Engineering Syllabi Archive

Course Description: Introduction to the methods of engineering problem solving. Application of mathematical concepts to solve engineering problems.

Biom 3110(Honors): Medical Physiology (Syllabus), Bradford D. Pendley

Biomedical Engineering Syllabi Archive

Course Description: Basic principles of human physiology and how these are applied in medicine and biomedical engineering problem and devices; physiological principles using appropriate mathematical and engineering models to construct an understanding of how the body works as an integrated system.

Biom 4906: Tissue Engineering (Syllabus), Gary L. Bowlin

Biomedical Engineering Syllabi Archive

Course Description: To study the design, development, and implantation of tissue engineered components. Analysis of the basis for cell growth and differentiation, control of tissue development (in vivo & in vitro), models for tissue engineering, and transplantation of engineered cells and tissues. The emphasis of these analyses will be focused on the cardiovascular system (blood vessels and cardiac prostheses), musculoskeletal system (Bone, cartilage, and tendons), and skin.

Biom 4801/6801: Introduction To Medical Imaging (Syllabus), Aaryani Sajja

Biomedical Engineering Syllabi Archive

Course Description: This course will introduce fundamentals of the four most-important clinical medical imaging modalities: X-ray, Radionuclide, Ultrasound, and MRI. The primary focus is on the physical principles, instrumentation methods, imaging algorithms, and clinical applications of each imaging modality.

Engr 1009: Preparation For Engineering Problem Solving (Syllabus), Stephen Strain

Biomedical Engineering Syllabi Archive

Course Description: Applications of algebra and trigonometry to engineering problems. Accelerated preparation for an engineering or technology major.

Patient-Specific Cardiovascular Superelastic Niti Stents Produced By Laser Powder Bed Fusion, Valentina Finazzi, Francesca Berti, Roger J. Guillory Ii, Lorenza Petrini, Barbara Previtali, Ali Gökhan Demir

Michigan Tech Publications, Part 1

To date, there is a general lack of customizability within the selection of endovascular devices for catheter-based vascular interventions. Laser powder bed fusion (LPBF) has been flexibly exploited to produce customized implants using conventional biomedical alloys for orthopedic and dental applications. Applying LPBF for cardiovascular applications, patient-specific stents can be produced with small struts (approximately 100-300 µm), variable geometries, and clinically used metals capable of superelastic behaviour at body temperature (eg. equiatomic nickel-titanium alloys, NiTi). Additionally, the growing availability and use of patient-specific 3D models provides a unique opportunity to outline the necessary manufacturing process that would be required for …

Hardware In The Loop Implementation And Simulations Of A Wave Energy Converter Using Typhoon Hil And Speedgoat, Pranav Nair

Dissertations, Master's Theses and Master's Reports

Several studies have indicated that electricity production is the prime source of greenhouse emissions, more than flying and driving combined. Hence, over the past few decades, there has been a significant rise in the need for clean energy to achieve the targets in emissions reduction. It has been observed that the share of renewable energy sources in the percentage of total electricity production is rising, but, according to climate experts, the transition needs to speed up. Hence, it is significant to study and develop underutilized renewable energy sources.

One of these underutilized renewable energy sources is wave energy. It has …

An Antimicrobial Polydopamine Surface Coating To Reduce Biofouling On Telemetry Tags Used In Marine Conservation Practices, Ariana Smies

Dissertations, Master's Theses and Master's Reports

Satellite telemetry tags are used to track the migration patterns of large cetaceans. These tags penetrate the dermis and remain embedded in the underlying blubber tissue. As the dermis of cetaceans is host to a diverse microbiome, and it is impossible to clean the skin before implanting the devices, the potential for infection is increased when the tags penetrate through the skin. H₂O₂ is a potential antimicrobial agent that, in addition to showing broad-spectrum efficacy against gram-negative and gram-positive bacteria, can promote wound healing outcomes by promoting proliferative factors and peptides that protect against oxidative stress. However, …

Process Development, Physical, And Electrical Characterization Of Langmuir Blodgett Trough Deposited Polyaniline, Mehdi Malekrah

Dissertations, Master's Theses and Master's Reports

Conductive polymers have recently attracted a lot of attention in advanced technologies because of their unique characteristics. Among the conductive polymers, polyaniline (PANi) has been studied widely because of its environmental stability, simple processing, inexpensive source monomer, and, most importantly, its controllable wide conductivity range due to the doping (protonation) process. These characteristics of PANi make it a strong candidate for applications in numerous areas such as biosensors, transparent display, photovoltaic devices, batteries, and, more recently, flexible electronics. Even with the many studies that have been conducted in this field, however, future advances are still needed to optimize the processability, …

Molecular Modeling Of High-Performance Polymers, Sagar Umesh Patil

Dissertations, Master's Theses and Master's Reports

High-performance polymers are extensively used in the aerospace and aeronautics industries due to their low density, high specific strength, and high specific stiffness. These properties along with better infiltration with reinforcements [carbon nanotubes (CNTs), glass, etc.] capability make them an excellent candidate to fabricate Polymer Matrix Composites (PMCs) tailored for specific applications. The applications range from products used daily to deep space exploration. These materials are subjected to varying temperatures and pressures during fabrication and in service. Therefore, the evolution of their intrinsic properties needs to be studied and their ability to sustain extreme environmental conditions in outer space needs …

Calorimetric Measurements Of Lunar Regolith Simulant And Water. An Experimental Study Correlating Weight Percent Water And Temperature Change Through Periods Of Phase Change., George B. Johnson

Dissertations, Master's Theses and Master's Reports

Permanently Shaded Regions (PSRs) are cold traps located around the lunar south pole that have been confirmed to contain possible interesting quantities or volatiles such as H2O, CO2, SO2, CH4, and others. [1] The identification of these volatiles on the lunar surface was a critical step in the development of NASA’s strategic goals for scientific discoveries, sustained space travel and exploration, and re-establishing a human presence on the moon. These volatiles are vital to the future of operating in and exploring space. The LCROSS impact revealed the existence of these resources in PSRs but more information is needed about the …

Measuring The Physicochemical Properties Of Viral Vectors To Enhance Gene Therapy Production, Oluwatoyin Areo

Dissertations, Master's Theses and Master's Reports

Gene therapy is a therapeutic intervention designed to correct single gene disorders. AAV has been identified as a suitable vector for delivering therapeutic genes. However, the use of AAV has been hampered by manufacturing challenges inclusive of low virus recovery, and the presence of AAV without the gene of interest (empty capsids). To solve these problems, we characterized the charge and hydrophobicity of AAV, and surrogate viruses using chemical force microscopy (CFM). CFM uses a modified atomic force microscope (AFM) probe to measure the adhesion force between a virus particle and a functional chemistry.The virus particles to be measured are …

A Coupled Viscoplastic-Damage Constitutive Model For Semicrystalline Polymers, Jeffrey Wiersma

Dissertations, Master's Theses and Master's Reports

The ease of processing, recyclability, and ideal cost to weight ratio makes the semi-crystalline polymers attractive in the aerospace, automotive, and defense industries. Use of semicrystalline polymers for engineering design requires a thorough understanding of their response to mechanical deformation, rate of loading, temperature, and failure mechanisms. However, there lacks a generally agreed upon constitutive model to capture the large deformation elastic-viscoplastic response of semicrystalline polymers while incorporating the strain-rate dependence and damage behavior. To address this aspect, the objective of this dissertation is to develop an elastic-viscoplastic constitutive model to predict the rate dependent, large deformation response of semicrystalline …

Green Infrastructure In Parking Lot Retrofits, Delaney Sall, Julie Wildschut

Student Papers and Reports

The built environment poses significant risks to surrounding ecosystems. Impervious surfaces like roofs, roads, and parking lots do not allow rainwater to gradually filter into the soil. Instead, runoff often flows directly into storm drains and waterways —causing flooding, erosion and pollution.

One way to mitigate these negative impacts is the installation of Green Infrastructure (GI), a variety of practices designed to infiltrate runoff into the soil, filter out pollutants, and provide habitat for native species.

Because of the way urban areas developed, most commercial parking lots lack GI. If a property owner wants to use their space to …

Cold-Formed Steel Strength Predictions For Torsion, Yu Xia, Robert S. Glauz, Benjamin W. Schafer, Michael Seek, Hannah B. Blum

Engineering Technology Faculty Publications

Locally slender open cross-section members are susceptible to significant twisting and high warping torsion stresses. Torsion considerations are complicated by whether it is derived as a first-order effect from loading or a second-order effect from instability. Previous direct torsion experiments on lipped channels have shown significant inelastic reserve in limited cases. The current design for combined bending and torsion interaction has some limitations, including only considering the first yield in torsion and ignoring the cross-section slenderness in torsion. A parametric study is conducted to predict the torsion capacity in locally slender cross-sections. Shell finite element models of lipped Cee and …

Efficient Removal Of Lead Ions From Aqueous Media Using Sustainable Sources On Marine Algae, Hannah Namkoong, Erik Biehler, Gon Namkoong, Tarek M. Abdel-Fattah

Electrical & Computer Engineering Faculty Publications

The goal of this project is to explore a new method to efficiently remove Pb(II) ions from water by processing Undaria pinnatifida into immobilized beads using sodium alginate and calcium chloride. The resulting biosorbent was characterized by Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy coupled with energy-dispersive X-ray spectroscopy (SEM-EDS). Using immobilized U. pinnatifida, we investigated the effect of various factors on Pb(II) ion removal efficiency such as temperature, pH, ionic strength, time, and underlying biosorption mechanisms. For Pb(II) ion biosorption studies, Pb(II) ion biosorption data were obtained and analyzed using Langmuir and Freundlich adsorption models. It …

Real-Time Cavity Fault Prediction In Cebaf Using Deep Learning, Md. M. Rahman, K. Iftekharuddin, A. Carptenter, T. Mcguckin, C. Tennant, L. Vidyaratne, Sandra Biedron (Ed.), Evgenya Simakov (Ed.), Stephen Milton (Ed.), Petr M. Anisimov (Ed.), Volker R.W. Schaa (Ed.)

Electrical & Computer Engineering Faculty Publications

Data-driven prediction of future faults is a major research area for many industrial applications. In this work, we present a new procedure of real-time fault prediction for superconducting radio-frequency (SRF) cavities at the Continuous Electron Beam Accelerator Facility (CEBAF) using deep learning. CEBAF has been afflicted by frequent downtime caused by SRF cavity faults. We perform fault prediction using pre-fault RF signals from C100-type cryomodules. Using the pre-fault signal information, the new algorithm predicts the type of cavity fault before the actual onset. The early prediction may enable potential mitigation strategies to prevent the fault. In our work, we apply …

A Formal Power Series Approach To Multiplicative Dynamic And Static Output Feedback, Venkatesh Subbarao Guggilam

Electrical & Computer Engineering Faculty Publications

The goal of the paper is two-fold. The first of which is to derive an explicit formula to compute the generating series of a closed-loop system when a plant, given in a Chen-Fliess series description is in multiplicative output feedback connection with another system given in Chen-Fliess series description. In addition, the multiplicative dynamic output feedback connection has a natural interpretation as a transformation group acting on the plant. The second of the two-part goal of this paper is same as the first part albeit when the Chen-Fliess series in the feedback is replaced by a memoryless map, so called …

Qu-Brats: Miccai Brats 2020 Challenge On Quantifying Uncertainty In Brain Tumor Segmentation - Analysis Of Ranking Scores And Benchmarking Results, Raghav Mehta, Angelos Filos, Ujjwal Baid, Chiharu Sako, Richard Mckinley, Michael Rebsamen, Katrin Dätwyler, Raphael Meier, Piotr Radojewski, Gowtham Krishnan Murugesan, Sahil Nalawade, Chandan Ganesh, Ben Wagner, Fang F. Yu, Baowei Fei, Ananth J. Madhuranthakam, Joseph A. Maldjian, Laura Daza, Catalina Gómez, Pablo Arbeláez, Chengliang Dai, Shuo Wang, Hadrien Reynaud, Yuan-Han Mo, Elsa Angelini, Yike Guo, Wenjia Bai, Subhashis Banerjee, Lin-Min Pei, Murat Ak, Sarahi Rosas-González, Ilyess Zemmoura, Clovis Tauber, Minh H. Vu, Tufve Nyholm, Tommy Löfstedt, Laura Mora Ballestar, Veronica Vilaplana, Hugh Mchugh, Gonzalo Maso Talou, Alan Wang, Jay Patel, Ken Chang, Katharina Hoebel, Mishka Gidwani, Nishanth Arun, Sharut Gupta, Mehak Aggarwal, Praveer Singh, Elizabeth R. Gerstner, Jayashree Kalpathy-Cramer, Nicholas Boutry, Alexis Huard, Lasitha Vidyaratne, Md. Monibor Rahman, Khan M. Iftekharuddin, Joseph Chazalon, Elodie Puybareau, Guillaume Tochon, Jun Ma, Mariano Cabezas, Xavier Llado, Arnau Oliver, Liliana Valencia, Sergi Valverde, Mehdi Amian, Mohammadreza Soltaninejad, Andriy Myronenko, Ali Hatamizadeh, Xue Feng, Quan Dou, Nicholas Tustison, Craig Meyer, Nisarg A. Shah, Sanjay Talbar, Marc-André Weber, Abhishek Mahajan, Andras Jakab, Roland Wiest, Hassan M. Fathallah-Shaykh, Arash Nazeri, Mikhail Milchenko1, Daniel Marcus, Aikaterini Kotrotsou, Rivka Colen, John Freymann, Justin Kirby, Christos Davatzikos, Bjoern Menze, Spyridon Bakas, Yarin Gal, Tal Arbel

Electrical & Computer Engineering Faculty Publications

Deep learning (DL) models have provided the state-of-the-art performance in a wide variety of medical imaging benchmarking challenges, including the Brain Tumor Segmentation (BraTS) challenges. However, the task of focal pathology multi-compartment segmentation (e.g., tumor and lesion sub-regions) is particularly challenging, and potential errors hinder the translation of DL models into clinical workflows. Quantifying the reliability of DL model predictions in the form of uncertainties, could enable clinical review of the most uncertain regions, thereby building trust and paving the way towards clinical translation. Recently, a number of uncertainty estimation methods have been introduced for DL medical image segmentation tasks. …

Field Emission Migration In Cebaf Srf Cavities Using Deep Learning, K. Ahammed, J. Li, A. Carpenter, R. Suleiman, C. Tennant, L. Vidyaratne

Electrical & Computer Engineering Faculty Publications

The Continuous Electron Beam Accelerator Facility (CEBAF) operates hundreds of superconducting radio frequency (SRF) cavities in its two main linear accelerators. Field emission can occur when the cavities are set to high operating RF gradients and is an ongoing operational challenge. This is especially true in newer, higher gradient SRF cavities. Field emission results in damage to accelerator hardware, generates high levels of neutron and gamma radiation, and has deleterious effects on CEBAF operations. So, field emission reduction is imperative for the reliable, high gradient operation of CEBAF that is required by experimenters. Here we explore the use of deep …

Optimized Cancer Detection On Various Magnified Histopathological Colon Imagesbased On Dwt Features And Fcm Clustering, Tina Babu, Tripty Singh, Deepa Gupta, Shahin Hameed

Turkish Journal of Electrical Engineering and Computer Sciences

Due to the morphological characteristics and other biological aspects in histopathological images, the computerized diagnosis of colon cancer in histopathology images has gained popularity. The images acquired using the histopathology microscope may differ for greater visibility by magnifications. This causes a change in morphological traits leading to intra and inter-observer variability. An automatic colon cancer diagnosis system for various magnification is therefore crucial. This work proposes a magnification independent segmentation approach based on the connected component area and double density dual tree DWT (discrete wavelet transform) coefficients are derived from the segmented region. The derived features are reduced further shortened …

Cnn Based Sensor Fusion Method For Real-Time Autonomous Robotics Systems, Berat Yildiz, Aki̇f Durdu, Ahmet Kayabaşi, Mehmet Duramaz

Turkish Journal of Electrical Engineering and Computer Sciences

Autonomous robotic systems (ARS) serve in many areas of daily life. The sensors have critical importance for these systems. The sensor data obtained from the environment should be as accurate and reliable as possible and correctly interpreted by the autonomous robot. Since sensors have advantages and disadvantages over each other they should be used together to reduce errors. In this study, Convolutional Neural Network (CNN) based sensor fusion was applied to ARS to contribute the autonomous driving. In a real-time application, a camera and LIDAR sensor were tested with these networks. The novelty of this work is that the uniquely …

Fft Enabled Ecc For Wsn Nodes Without Hardware Multiplier Support, Utku Gülen, Selçuk Baktir

Turkish Journal of Electrical Engineering and Computer Sciences

ECC is a popular cryptographic algorithm for key distribution in wireless sensor networks where power efficiency is desirable. A power efficient implementation of ECC without using hardware multiplier support was proposed earlier for wireless sensor nodes. The proposed implementation utilized the number theoretic transform to carry operands to the frequency domain, and conducted Montgomery multiplication, in addition to other finite field operations, in that domain. With this work, we perform in the frequency domain only polynomial multiplication and use the fast Fourier transform to carry operands between the time and frequency domains. Our ECC implementation over $GF((2^{13}-1)^{13})$ on the MSP430 …

Using Vertical Areas In Finite Set Model Predictive Control Of A Three-Level Inverter Aimed At Computation Reduction, Alireza Jaafari, Alireza Davari, Cristian Garcia, Jose Rodriguez

Turkish Journal of Electrical Engineering and Computer Sciences

In power electronics applications, finite set model predictive control (FS-MPC) has proven to be a viable strategy. However, due to the high processing power required, using this technology in multilevel converters is difficult. This strategy, which is based on predicting the behavior of the system for all conceivable states, has an issue with a numerous of possible switching states. A recent and useful strategy for dealing with the problem is the limiting of calculations based on triangle regions. Despite its success, this method has several limitations, including the computation required to locate the right triangle and the boundary modes. In …

Application Of Long Short-Term Memory (Lstm) Neural Network Based On Deeplearning For Electricity Energy Consumption Forecasting, Mehmet Bi̇lgi̇li̇, Ni̇yazi̇ Arslan, Ali̇i̇hsan Şekerteki̇n, Abdulkadi̇r Yaşar

Turkish Journal of Electrical Engineering and Computer Sciences

Electricity is the most substantial energy form that significantly affects the development of modern life, work efficiency, quality of life, production, and competitiveness of the society in the ever-growing global world. In this respect, forecasting accurate electricity energy consumption (EEC) is fairly essential for any country?s energy consumption planning and management regarding its growth. In this study, four time-series methods; long short-term memory (LSTM) neural network, adaptive neuro-fuzzy inference system (ANFIS) with subtractive clustering (SC), ANFIS with fuzzy cmeans (FCM), and ANFIS with grid partition (GP) were implemented for the short-term one-day ahead EEC prediction. Root mean square error (RMSE), …

Deep Learning-Aided Automated Personal Data Discovery And Profiling, Apdullah Yayik, Vedat Aybar, Hasan Hüseyi̇n Apik, Sevcan İçöz, Beki̇r Bakar, Tunga Güngör

Turkish Journal of Electrical Engineering and Computer Sciences

In Turkey, Turkish Personal Data Protection Rule (PDPR) No. 6698, in force since 2016, provides protection to citizens for the legal existence of their personal data. Although the law provides excellent guidance, companies currently face challenges in complying with its regulations in terms of storing, sharing, or monitoring personal data. Since any specially designed software with wide industrial usage is not on the market, almost all of the companies have no other choice but to take expensive and error-prone operations manually to ensure their compliance. In this paper, we present an automated solution to facilitate and accelerate PDPR compliance. In …