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Articles 1 - 10 of 10
Full-Text Articles in Categorical Data Analysis
A Deep Bilstm Machine Learning Method For Flight Delay Prediction Classification, Desmond B. Bisandu, Irene Moulitsas
A Deep Bilstm Machine Learning Method For Flight Delay Prediction Classification, Desmond B. Bisandu, Irene Moulitsas
Journal of Aviation/Aerospace Education & Research
This paper proposes a classification approach for flight delays using Bidirectional Long Short-Term Memory (BiLSTM) and Long Short-Term Memory (LSTM) models. Flight delays are a major issue in the airline industry, causing inconvenience to passengers and financial losses to airlines. The BiLSTM and LSTM models, powerful deep learning techniques, have shown promising results in a classification task. In this study, we collected a dataset from the United States (US) Bureau of Transportation Statistics (BTS) of flight on-time performance information and used it to train and test the BiLSTM and LSTM models. We set three criteria for selecting highly important features …
Cov-Inception: Covid-19 Detection Tool Using Chest X-Ray, Aswini Thota, Ololade Awodipe, Rashmi Patel
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 …
Using The R Library Rpanel For Gui-Based Simulations In Introductory Statistics Courses, Ryan M. Allison
Using The R Library Rpanel For Gui-Based Simulations In Introductory Statistics Courses, Ryan M. Allison
Statistics
As a student, I noticed that the statistical package R (http://www.r-project.org) would have several benefits of its usage in the classroom. One benefit to the package is its free and open-source nature. This would be a great benefit for instructors and students alike since it would be of no cost to use, unlike other statistical packages. Due to this, students could continue using the program after their statistical courses and into their professional careers. It would be good to expose students while they are in school to a tool that professionals use in industry. R also has powerful …
An Administrative View Of Model Uncertainty In Public Health, Clark D. Carrington
An Administrative View Of Model Uncertainty In Public Health, Clark D. Carrington
RISK: Health, Safety & Environment (1990-2002)
Dr. Carrington reviews several ways to deal with model uncertainty, including those failing to acknowledge any use of models. He then evaluates six such methods with regard to, e.g., transparency and cost of execution.
Datascan - April 30, 1991, Nova University
Datascan - March 11, 1991, Nova University
Datascan - February 18, 1991, Nova University
Datascan - December 9, 1990, Nova University
Datascan - November 2, 1990, Nova University
Datascan - October 19, 1990, Nova University