Engineering Commons^™

A Integrated Approach Of Deep Learning And Augmented Reality For Pneumonia Detection In Chest X-Ray Images, Jeevarathinam Senthilkumar

Open Access Theses & Dissertations

Pneumonia is a viral or fungal illness that spreads to the lungs of the human body, causing fluid to accumulate in the lungs' air sacs. Millions of people are affected by this disease each year. One of the most common radiological diagnostics for diagnosing and screening this kind of sickness is a chest X-ray. The most commonly available radiological test for diagnosing and screening this kind of illness is a chest X-ray. An inaccurate diagnosis, especially over-diagnosis and under-diagnosis, is a common issue in the medical sector. As another issue, human-assisted diagnosis has limitations like the availability of an expert, …

How The Pavement's Lifetime Depends On The Stress Level: An Explanation Of The Empirical Formula, Edgar Daniel Rodriguez Velasquez, Vladik Kreinovich, Olga Kosheleva, Hoang Phuong Nguyen

Departmental Technical Reports (CS)

We show that natural invariance ideas explain the empirical dependence on the pavement's lifetime on the stress level.

Non-Invasive In-Vitro Glucose Monitoring Using Optical Sensor And Machine Learning Techniques For Diabetes Applications, Maryamsadat Shokrekhodaei

Open Access Theses & Dissertations

Diabetes is a major public health challenge affecting more than 451 million people. Physiological and experimental factors influence the accuracy of non-invasive glucose monitoring, and these need to be addressed before replacing the finger prick method with a non-invasive glucose measurement technique. Also, the suitable employment of machine learning techniques on experimental data can significantly improve the accuracy of glucose predictions.

This work includes the design, development, testing and data analysis of an optical based sensor for glucose measurements. The feasibility of non-invasive measurement of glucose within aqueous solutions that assimilate the composition of human blood plasma is investigated. The …

Fast Magnetic Resonance Image Reconstruction With Deep Learning Using An Efficientnet Encoder, Tahsin Rahman

Open Access Theses & Dissertations

This thesis aims to develop an efficient, deep network based method for Magnetic Resonance Imaging (MRI) acceleration through undersampled MR image reconstruction. Deep Neural Networks, particularly Deep Convolutional Networks, have been demonstrated to be highly effective in a wide variety of computer vision tasks, including MRI reconstruction. However, modern highly efficient encoder structures, such as the EfficientNet can potentially reduce reconstruction times further while improving reconstruction quality. To that end, we have developed a multi-channel U-Net MRI reconstruction network which uses an EfficientNet encoder and a custom asymmetric. The network was trained and tested using 5x undersampled multi-channel brain MR …

Hardware For Quantized Mixed-Precision Deep Neural Networks, Andres Rios

Open Access Theses & Dissertations

Recently, there has been a push to perform deep learning (DL) computations on the edge rather than the cloud due to latency, network connectivity, energy consumption, and privacy issues. However, state-of-the-art deep neural networks (DNNs) require vast amounts of computational power, data, and energyâ??resources that are limited on edge devices. This limitation has brought the need to design domain-specific architectures (DSAs) that implement DL-specific hardware optimizations. Traditionally DNNs have run on 32-bit floating-point numbers; however, a body of research has shown that DNNs are surprisingly robust and do not require all 32 bits. Instead, using quantization, networks can run on …

Digital Twin Technology Applications For Transportation Infrastructure - A Survey-Based Study, Hector Cruz

Open Access Theses & Dissertations

In the past couple of decades, various industries have taken advantage of emerging advanced technologies, such as digital twin (DT), to find more effective solutions in their respective areas. In the transportation infrastructure sector, the concept and implementation of DT technologies are slowly gaining traction but lagging behind other major industries. To better understand the limitations, opportunities and challenges for the adoption of DT in this sector, a survey questionnaire was distributed to collect information from industry professionals involved in transportation infrastructure projects. The purpose of this study is to understand how DT technology is being perceived by the industry. …

Low-Complexity Zonotopes Can Enhance Uncertainty Quantification (Uq), Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

In many practical situations, the only information that we know about the measurement error is the upper bound D on its absolute value. In this case, once we know the measurement result X, the only information that we have about the actual value x of the corresponding quantity is that this value belongs to the interval [X − D, X + D]. How can we estimate the accuracy of the result of data processing under this interval uncertainty? In general, computing this accuracy is NP-hard, but in the usual case when measurement errors are relatively small, we can linearize the …