Physical Sciences and Mathematics Commons^™

Cov-Inception: Covid-19 Detection Tool Using Chest X-Ray, Aswini Thota, Ololade Awodipe, Rashmi Patel

SMU Data Science Review

Since the pandemic started, researchers have been trying to find a way to detect COVID-19 which is a cost-effective, fast, and reliable way to keep the economy viable and running. This research details how chest X-ray radiography can be utilized to detect the infection. This can be for implementation in Airports, Schools, and places of business. Currently, Chest imaging is not a first-line test for COVID-19 due to low diagnostic accuracy and confounding with other viral pneumonia. Different pre-trained algorithms were fine-tuned and applied to the images to train the model and the best model obtained was fine-tuned InceptionV3 model …

Critical Media, Information, And Digital Literacy: Increasing Understanding Of Machine Learning Through An Interdisciplinary Undergraduate Course, Barbara R. Burke, Elena Machkasova

Irish Communication Review

Widespread use of Artificial Intelligence in all areas of today’s society creates a unique problem: algorithms used in decision-making are generally not understandable to those without a background in data science. Thus, those who use out-of-the-box Machine Learning (ML) approaches in their work and those affected by these approaches are often not in a position to analyze their outcomes and applicability.

Our paper describes and evaluates our undergraduate course at the University of Minnesota Morris, which fosters understanding of the main ideas behind ML. With Communication, Media & Rhetoric and Computer Science faculty expertise, students from a variety of majors, …

Atmospheric Contrail Detection With A Deep Learning Algorithm, Nasir Siddiqui

Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal

Aircraft contrail emission is widely believed to be a contributing factor to global climate change. We have used machine learning techniques on images containing contrails in hopes of being able to identify those which contain contrails and those that do not. The developed algorithm processes data on contrail characteristics as captured by long-term image records. Images collected by the United States Department of Energy’s Atmospheric Radiation Management user facility(ARM) were used to train a deep convolutional neural network for the purpose of this contrail classification. The neural network model was trained with 1600 images taken by the Total Sky Imager(TSI) …

The Right To Human Intervention: Law, Ethics And Artificial Intelligence, Maria Kanellopoulou - Botti, Fereniki Panagopoulou, Maria Nikita, Anastasia Michailaki

Computer Ethics - Philosophical Enquiry (CEPE) Proceedings

The paper analyses the new right of human intervention in use of information technology, automatization processes and advanced algorithms in individual decision-making activities. Art. 22 of the new General Data Protection Regulation (GDPR) provides that the data subject has the right not to be subject to a fully automated decision on matters of legal importance to her interests, hence the data subject has a right to human intervention in this kind of decisions.

Smart Parking Systems Design And Integration Into Iot, Charles M. Menne

Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal

This paper looks at two smart parking reservation algorithms, and examines the ongoing efforts to connect smart systems of different domains in a city's infrastructure. The reservation algorithms are designed to improve the performance of smart parking systems. The first algorithm considers the distance between parking areas and the number of free parking spaces in determining a parking space. The second algorithm uses distance between parking areas and driver destination, parking price, and the number of unoccupied spaces for each parking area. Neither of these smart parking systems cover how they could fit into a larger scale smart system. As …

Comparison Of Sequence Alignment Algorithms, Tejas Gandhi

Journal of Undergraduate Research at Minnesota State University, Mankato

The fact that biological sequences can be represented as strings belonging to a finite alphabet (A, C, G, and T for DNA) plays an important role in connecting biology to computer science. String representation allows researchers to apply various string comparison techniques available in computer science. As a result, various applications have been developed that facilitate the task of sequence alignment. The problem of finding sequence alignments consists of finding the best match between two biological sequences. A best match can infer an evolutionary relationship and functional similarity. However, there is a lack of research on how reliable and efficient …

Improved Storm Data Processing Through Parallel Computing Approaches, Shauna Smith

Journal of Undergraduate Research at Minnesota State University, Mankato

A previous research study conducted at Michigan Technological University by Dr. Deborah Nykanen and her colleague Dr. Daniel Harris analyzed storm data in order to develop algorithms that will allow coarse resolution rainfall forecasted by weather models to be optimally used in high resolution hydrology models with the goal of improving stream flow predictions and early detection algorithms that can be used to warn communities about potential flash floods. This research was performed by analyzing a series of independent radar images derived from Weather Surveillance Radar-1988 Doppler (WSR-88D) data obtained from Dr. James A. Smith at Princeton University using a …

Verification Of Costless Merge Pairing Heaps, Joshua Vander Hook

Journal of Undergraduate Research at Minnesota State University, Mankato

Most algorithms’ performance is limited by the data structures they use. Internal algorithms then decide the performance of the data structure. This cycle continues until fundamental results, verified by analysis and experiment, prevent further improvement. In this paper I examine one specific example of this. The focus of this work is primarily on a new variant of the pairing heap. I will review the new implementation, compare its theoretical performance, and discuss my original contribution: the first preliminary data on its experimental performance. It is instructive to provide some background information, followed by a formal definition of heaps in 1.1. …

Fast Software Multiplication In F_2[X] For Embedded Processors, Serdar Süer Erdem

Turkish Journal of Electrical Engineering and Computer Sciences

We present a novel method for fast multiplication of polynomials over F_2 which can be implemented efficiently in embedded software. Fast polynomial multiplication methods are needed for the efficient implementation of some cryptographic and coding applications. The proposed method follows a strategy to reduce the memory accesses for input data and intermediate values during computation. This strategy speeds up the binary polynomial multiplication significantly on typical embedded processors with limited memory bandwidth. These multiplications are usually performed by the comb method or the Karatsuba-based methods in embedded software. The proposed method has speed and memory advantages over these methods on …