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Full-Text Articles in Engineering

Enhanced Iot-Based Electrocardiogram Monitoring System With Deep Learning, Jian Ni May 2023

Enhanced Iot-Based Electrocardiogram Monitoring System With Deep Learning, Jian Ni

UNLV Theses, Dissertations, Professional Papers, and Capstones

Due to the rapid development of computing and sensing technologies, Internet of Things (IoT)-based cardiac monitoring plays a crucial role in providing patients with cost-efficient solutions for long-term, continuous, and pervasive electrocardiogram (ECG) monitoring outside a hospital setting. In a typical IoT-based ECG monitoring system, ECG signals are picked up by sensors located on the edge, and then uploaded to the remote cloud servers. ECG interpretation is performed for the collected ECGs in the cloud servers and the analysis results can be made instantly available to the patients as well as their healthcare providers.In this dissertation, we first examine the …


Modeling And Analysis Of Subcellular Protein Localization In Hyper-Dimensional Fluorescent Microscopy Images Using Deep Learning Methods, Yang Jiao May 2022

Modeling And Analysis Of Subcellular Protein Localization In Hyper-Dimensional Fluorescent Microscopy Images Using Deep Learning Methods, Yang Jiao

UNLV Theses, Dissertations, Professional Papers, and Capstones

Hyper-dimensional images are informative and become increasingly common in biomedical research. However, the machine learning methods of studying and processing the hyper-dimensional images are underdeveloped. Most of the methods only model the mapping functions between input and output by focusing on the spatial relationship, whereas neglect the temporal and causal relationships. In many cases, the spatial, temporal, and causal relationships are correlated and become a relationship complex. Therefore, only modeling the spatial relationship may result in inaccurate mapping function modeling and lead to undesired output. Despite the importance, there are multiple challenges on modeling the relationship complex, including the model …


Infants' Facial Emotion Recognition, Umme Fatema May 2021

Infants' Facial Emotion Recognition, Umme Fatema

UNLV Theses, Dissertations, Professional Papers, and Capstones

Facial Emotion Recognition (FER) has become a popular computer vision topic and attracted a lot of researchers. However, these researches mostly focus on adult facial emotion. Infants’ facial structure and expression of emotions differ from adults’. That is why our target is to create a model that particularly focuses on infants’ facial emotions. In this work, we classify three types of emotions: positive, negative, and neutral. Two datasets are used in this work. One is an image-based dataset named ‘The City’ that consists of 154 images of infants aged 0-12 months. Another is the Rebel Dataset from the Department of …


A Framework For Vector-Weighted Deep Neural Networks, Carter Chiu May 2020

A Framework For Vector-Weighted Deep Neural Networks, Carter Chiu

UNLV Theses, Dissertations, Professional Papers, and Capstones

The vast majority of advances in deep neural network research operate on the basis of a real-valued weight space. Recent work in alternative spaces have challenged and complemented this idea; for instance, the use of complex- or binary-valued weights have yielded promising and fascinating results. We propose a framework for a novel weight space consisting of vector values which we christen VectorNet. We first develop the theoretical foundations of our proposed approach, including formalizing the requisite theory for forward and backpropagating values in a vector-weighted layer. We also introduce the concept of expansion and aggregation functions for conversion between real …


Cyclist Detection, Tracking, And Trajectory Analysis In Urban Traffic Video Data, Farideh Foroozandeh Shahraki Aug 2017

Cyclist Detection, Tracking, And Trajectory Analysis In Urban Traffic Video Data, Farideh Foroozandeh Shahraki

UNLV Theses, Dissertations, Professional Papers, and Capstones

The major objective of this thesis work is examining computer vision and machine learning detection methods, tracking algorithms and trajectory analysis for cyclists in traffic video data and developing an efficient system for cyclist counting. Due to the growing number of cyclist accidents on urban roads, methods for collecting information on cyclists are of significant importance to the Department of Transportation. The collected information provides insights into solving critical problems related to transportation planning, implementing safety countermeasures, and managing traffic flow efficiently. Intelligent Transportation System (ITS) employs automated tools to collect traffic information from traffic video data. In comparison to …