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A Bulk Driven Transimpedance Cmos Amplifier For Sipm Based Detection, Shahram Hatefi Hesari 2022 University of Tennessee, Knoxville

A Bulk Driven Transimpedance Cmos Amplifier For Sipm Based Detection, Shahram Hatefi Hesari

Masters Theses

The contribution of this work lies in the development of a bulk driven operational
transconducctance amplifier which can be integrated with other analog circuits and
photodetectors in the same chip for compactness, miniaturization and reducing the
power. Silicon photomultipliers, also known as SiPMs, when coupled with scintillator materials are used in many imaging applications including nuclear detection. This thesis discuss the design of a bulk-driven transimpedance amplifier suitable for detectors where the front end is a SiPM. The amplifier was design and fabricated in a standard standard CMOS process and is suitable for integration with CMOS based SiPMs and commercially …


Miniaturized Battery Powered Air Quality Monitoring System, Bryan Chacon 2022 Clemson University

Miniaturized Battery Powered Air Quality Monitoring System, Bryan Chacon

All Theses

In this work, an air quality monitoring system was developed using various sensors that measure specific air quality parameters, including Volatile Organic Compounds, Carbon Dioxide, particulate matter of varying sizes, ambient pressure, humidity, and temperature. This system is based off a Particle micro-controller, Boron LTE CAT-M1 which allows for cellular connectivity for real-time data transmission. It is powered by a 3.7 Volt Li-Po battery and has a miniaturized design which allows for portability. This data is processed through an Internet of Things software provider that allows for the device to be connected and accessed to and from anywhere in the …


Embedding A Grid Of Load Cells Into A Dining Table For Automatic Monitoring And Detection Of Eating Events, Mohammad Mayyan 2022 Clemson University

Embedding A Grid Of Load Cells Into A Dining Table For Automatic Monitoring And Detection Of Eating Events, Mohammad Mayyan

All Dissertations

This dissertation describes a “smart dining table” that can detect and measure consumption events. This work is motivated by the growing problem of obesity, which is a global problem and an epidemic in the United States and Europe. Chapter 1 gives a background on the economic burden of obesity and its comorbidities. For the assessment of obesity, we briefly describe the classic dietary assessment tools and discuss their drawback and the necessity of using more objective, accurate, low-cost, and in-situ automatic dietary assessment tools. We explain in short various technologies used for automatic dietary assessment such as acoustic-, motion-, or …


Design And Operation Of A Microwave Flow Cytometer For Single Cell Detection And Identification, Jeffrey A. Osterberg 2022 Clemson University

Design And Operation Of A Microwave Flow Cytometer For Single Cell Detection And Identification, Jeffrey A. Osterberg

All Dissertations

Microwave dielectric sensing has become a popular technique in biological cell sensing for its potential in online, label-free, and real-time sensing. At microwave frequencies probing signals are sensitive to intracellular properties since they are able to penetrate cell membranes, making microwave flow cytometry a promising technology for label-free biosensing. In this dissertation a microwave flow cytometer is designed and used to measure single biological cells and micro particles. A radio frequency (RF)/microwave interferometer serves as the measurement system for its high sensitivity and tunability and we show that a two-stage interferometer can achieve up to 20 times higher sensitivity than …


Credit Card Fraud Detection Using Machine Learning Techniques, Nermin Samy Elhusseny, shimaa mohamed ouf, Amira M. Idrees AMI 2022 BIS Helwan University

Credit Card Fraud Detection Using Machine Learning Techniques, Nermin Samy Elhusseny, Shimaa Mohamed Ouf, Amira M. Idrees Ami

Future Computing and Informatics Journal

This is a systematic literature review to reflect the previous studies that dealt with credit card fraud detection and highlight the different machine learning techniques to deal with this problem. Credit cards are now widely utilized daily. The globe has just begun to shift toward financial inclusion, with marginalized people being introduced to the financial sector. As a result of the high volume of e-commerce, there has been a significant increase in credit card fraud. One of the most important parts of today's banking sector is fraud detection. Fraud is one of the most serious concerns in terms of monetary …


Bicep Muscle Rep Counter With Semg, Matthew Max Garcia 2022 California Polytechnic State University, San Luis Obispo

Bicep Muscle Rep Counter With Semg, Matthew Max Garcia

Electrical Engineering

The Bicep Muscle Rep Counter with SEMG is a device that was made to develop three repetition thresholds or difficulty levels from a fully-flexed bicep brachii muscle and signal to the user when consequent bicep muscle contractions pass said thresholds or levels. This device can be used when performing a bicep-focused movement or when generally flexing the bicep muscle. Essentially, this device serves to make sure each repetition of a muscle contraction passes a percentage value calculated from the electrical activity outputted from a max contraction.

The device is not designed for and does not produce data for muscle growth, …


Smart Bottle Ble Integration, Joshua M. Rizzolo 2022 California Polytechnic State University, San Luis Obispo

Smart Bottle Ble Integration, Joshua M. Rizzolo

Electrical Engineering

In 1975, four percent of children aged five to nineteen were categorized as overweight or obese. As of 2016, this figure climbed above 18 percent [1]. Researchers at California Polytechnic State University San Luis Obispo (Cal Poly) want to investigate the effect of overeating in early childhood on later childhood obesity. This research requires collecting feeding pattern data on infants, which proves challenging. Parents cannot be relied on to regularly collect clean data due to factors including work schedule, multitasking, and general exhaustion. Thus, we have developed a tool to automatically collect data on feeding frequency and duration, as well …


Neural Network Based Diagnosis Of Breast Cancer Using The Breakhis Dataset, Ross E. Dalke 2022 California Polytechnic State University, San Luis Obispo

Neural Network Based Diagnosis Of Breast Cancer Using The Breakhis Dataset, Ross E. Dalke

Master's Theses

Breast cancer is the most common type of cancer in the world, and it is the second deadliest cancer for females. In the fight against breast cancer, early detection plays a large role in saving people’s lives. In this work, an image classifier is designed to diagnose breast tumors as benign or malignant. The classifier is designed with a neural network and trained on the BreakHis dataset. After creating the initial design, a variety of methods are used to try to improve the performance of the classifier. These methods include preprocessing, increasing the number of training epochs, changing network architecture, …


Improving The Performance And Evaluation Of Computer-Assisted Semen Analysis, Ji-Won Choi 2022 New Jersey Institute of Technology

Improving The Performance And Evaluation Of Computer-Assisted Semen Analysis, Ji-Won Choi

Dissertations

Semen analysis is performed routinely in fertility clinics to analyze the quality of semen and sperm cells of male patients. The analysis is typically performed by trained technicians or by Computer-Assisted Semen Analysis (CASA) systems. Manual semen analysis performed by technicians is subjective, time-consuming, and laborious, and yet most fertility clinics perform semen analysis in this manner. CASA systems, which are designed to perform the same tasks automatically, have a considerable market share, yet many studies still express concerns about their accuracy and consistency. In this dissertation, the focus is on detection, tracking, and classification of sperm cells in semen …


Assessing Structural And Functional Brain Alterations And Work-Related Fatigue In Non-Hyposmic And Hyposmic Covid-19 Survivors, Rakibul Hafiz 2022 New Jersey Institute of Technology

Assessing Structural And Functional Brain Alterations And Work-Related Fatigue In Non-Hyposmic And Hyposmic Covid-19 Survivors, Rakibul Hafiz

Dissertations

In the year 2019, life began to change at the advent of a global pandemic caused by the novel coronavirus. Mask mandates and mass vaccinations have mitigated the effects significantly, yet cases keep rising with new variants, especially, in densely populated countries, like India. Recent neuroimaging evidence shows the virus can attack the central nervous system (CNS). However, exactly which brain regions undergo structural and functional changes remain largely unknown. Many patients experience 'loss of/reduced sense of smell' (i.e., hyposmic) and an alarming number of survivors develop persistent symptoms ('long-COVID') for several months after initial infection. Fatigue is the most …


Closed-Loop Brain-Computer Interfaces For Memory Restoration Using Deep Brain Stimulation, David Xiaoliang Wang 2022 Southern Methodist University

Closed-Loop Brain-Computer Interfaces For Memory Restoration Using Deep Brain Stimulation, David Xiaoliang Wang

Electrical Engineering Theses and Dissertations

The past two decades have witnessed the rapid growth of therapeutic brain-computer interfaces (BCI) targeting a diversity of brain dysfunctions. Among many neurosurgical procedures, deep brain stimulation (DBS) with neuromodulation technique has emerged as a fruitful treatment for neurodegenerative disorders such as epilepsy, Parkinson's disease, post-traumatic amnesia, and Alzheimer's disease, as well as neuropsychiatric disorders such as depression, obsessive-compulsive disorder, and schizophrenia. In parallel to the open-loop neuromodulation strategies for neuromotor disorders, recent investigations have demonstrated the superior performance of closed-loop neuromodulation systems for memory-relevant disorders due to the more sophisticated underlying brain circuitry during cognitive processes. Our efforts are …


Radiomic Features To Predict Overall Survival Time For Patients With Glioblastoma Brain Tumors Based On Machine Learning And Deep Learning Methods, Lina Chato 2022 University of Nevada, Las Vegas

Radiomic Features To Predict Overall Survival Time For Patients With Glioblastoma Brain Tumors Based On Machine Learning And Deep Learning Methods, Lina Chato

UNLV Theses, Dissertations, Professional Papers, and Capstones

Machine Learning (ML) methods including Deep Learning (DL) Methods have been employed in the medical field to improve diagnosis process and patient’s prognosis outcomes. Glioblastoma multiforme is an extremely aggressive Glioma brain tumor that has a poor survival rate. Understanding the behavior of the Glioblastoma brain tumor is still uncertain and some factors are still unrecognized. In fact, the tumor behavior is important to decide a proper treatment plan and to improve a patient’s health. The aim of this dissertation is to develop a Computer-Aided-Diagnosis system (CADiag) based on ML/DL methods to automatically estimate the Overall Survival Time (OST) for …


The Mobility And Cognitive Mechanisms Involved In Altering Gait Speed In Children With Autism Spectrum Disorder, Alyssa Olivas 2022 The University of Texas at El Paso

The Mobility And Cognitive Mechanisms Involved In Altering Gait Speed In Children With Autism Spectrum Disorder, Alyssa Olivas

Open Access Theses & Dissertations

Autism is a socio-behavioral disorder, and diagnoses are conducted through behavioral screening instruments. Recent research suggests motor deficits may be a core symptom of the disorder, as children with autism present with deficits in motor development, locomotor skills, and postural instability. In addition, children with autism often have affected, executive function, attention, and perception cognitive domains. Different gait speeds have been used to examine gait adaptations in other clinical populations. Additionally, individuals with decreased cognitive abilities have demonstrated difficulties in modulating their walking speed. There is limited research on mechanisms children with autism use to alter their gait speed, or …


Insole Fall Prevention Device, Nick M. Hughes, Andrew M. Slaboda 2022 California Polytechnic State University, San Luis Obispo

Insole Fall Prevention Device, Nick M. Hughes, Andrew M. Slaboda

Biomedical Engineering

Falls among the aging population occur every single day, with 1 in every 5 resulting in some injury and 300,000 hospitalized every year with a hip fracture [1]. The most popular and effective way to mitigate these falls is through physical therapist intervention. However, with the increased popularity in telerehab, many patients at risk for falls cannot accurately convey their gait tendencies to their physical therapists from the comfort of their home or while not in direct contact with the PT. A device like an insole, implanted with force sensors, which measures different parts of a patient’s foot, could convey …


Predicting The Progression Of Diabetes Mellitus Using Dynamic Plantar Pressure Parameters, Mathew Sunil Varre 2022 University of Nevada, Las Vegas

Predicting The Progression Of Diabetes Mellitus Using Dynamic Plantar Pressure Parameters, Mathew Sunil Varre

UNLV Theses, Dissertations, Professional Papers, and Capstones

Introduction: Diabetic peripheral neuropathy is one of the common complications of type-2 diabetes mellitus (DM). Changes in the intrinsic plantar tissue coupled with repetitive mechanical loads and loss of sensation may lead to foot related complications (skin break down, ulcerations, and amputations) in persons with neuropathy if left untreated. The purpose of this dissertation was to stratify individuals with pre-diabetes, diabetes with and without neuropathy using dynamic plantar pressure parameters during walking, using machine learning algorithms.Methods: Plantar pressure data was collected from one hundred participants during walking with pressure measuring insoles fixed between the feet and thin socks. Simultaneously high-definition …


The Bracelet: An American Sign Language (Asl) Interpreting Wearable Device, Samuel Aba, Ahmadre Darrisaw, Pei Lin, Thomas Leonard 2022 University of Tennessee, Knoxville

The Bracelet: An American Sign Language (Asl) Interpreting Wearable Device, Samuel Aba, Ahmadre Darrisaw, Pei Lin, Thomas Leonard

Chancellor’s Honors Program Projects

No abstract provided.


Bms 202: Human Anatomy And Physiology Laboratory Oer Curation, Chealsye Bowley 2022 Grand Valley State University

Bms 202: Human Anatomy And Physiology Laboratory Oer Curation, Chealsye Bowley

Curated OER Collections

This OER curation is an annotated bibliography of prospective OER for the GVSU course BMS 202: Human Anatomy and Physiology Laboratory, assembled by request from the instructor.


Automated Segmentation Of The Inner Ear And Round Window In Computed Tomography Scans Using Convolutional Neural Networks, Kyle A. Rioux 2022 The University of Western Ontario

Automated Segmentation Of The Inner Ear And Round Window In Computed Tomography Scans Using Convolutional Neural Networks, Kyle A. Rioux

Electronic Thesis and Dissertation Repository

Computed tomography (CT) scans are acquired prior to cochlear implant (CI) surgery. Three-dimensional segmentations of the inner ear (IE) and round window (RW) based on clinical CTs can improve the CI procedure. Software pipelines are presented here which employ convolutional neural networks to automatically segment the IE and RW. The first pipeline produces high resolution segmentations of the IE and RW in tightly cropped CTs. Mean IE Dice score and RW centroid error were 0.88, 0.57mm and 0.93, 0.18mm in implanted and non-implanted samples, respectively. The second pipeline automatically segments the IE in large field of view CTs of any …


Novel Platforms For Large-Scale Adherent Culture Of Mammalian Cells, Ashkan YekrangSafakar 2022 Louisiana State University and Agricultural and Mechanical College

Novel Platforms For Large-Scale Adherent Culture Of Mammalian Cells, Ashkan Yekrangsafakar

LSU Doctoral Dissertations

With recent advances in biotechnology, there is a strong and urgent need for robust platforms to culture mammalian cells on a large scale to produce biopharmaceuticals. To this end, various bioreactors have been developed over the past decades, but their capacity and efficiency are often limited by insufficient mass transfer rate and excessive shear stress. In this work, multiple novel bioreactors for the large-scale adherent culture of anchorage-dependent cells were developed.

Hollow MicroCarriers (HMC) was developed as an alternative solution for the microcarrier-based culture system in a stirred-tank bioreactor. In the conventional microcarrier technique, cells are exposed to the harmful …


System Design And Control Optimization For Neurorehabilitation Exoskeleton, Rodrigo N. Ramon 2022 Florida International University

System Design And Control Optimization For Neurorehabilitation Exoskeleton, Rodrigo N. Ramon

FIU Electronic Theses and Dissertations

Neurorehabilitation is a comprehensive approach aimed at helping patients regain motor control after a neural injury, including spinal cord injury, stroke, or other ischemic events. Early-stage neurorehabilitation is particularly delicate due to voluntary muscular weakness and lack of motor control, presenting in the form of spasticity. Unfortunately, this period of elevated weakness is when most neural control improvement can be made through a phenomenon called brain plasticity. Early rehabilitation traditionally requires a human therapist due to the adaptive and dynamic interpretation of undesired neuromuscular events. While efforts have been made to develop devices to aid in neurorehabilitation, the considerations that …


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