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Classifying Abdominal Fat Distribution Patterns by Using Body Measurement Data
This article aims to explore new categorization that characterizes the distribution clusters of visceral and subcutaneous adipose tissues (VAT and SAT) measured by magnetic resonance imaging (MRI), to analyze the relationship between the VAT-SAT distribution patterns and the novel body shape descriptors (BSDs), and to develop a classifier to predict the fat distribution clusters using the BSDs.
Date:
February 19, 2021
Creator:
Sun, Jingjing; Xu, Bugao; Lee, Jane & Freeland-Graves, Jeanne H.
System:
The UNT Digital Library
Deriving Theorems in Implicational Linear Logic, Declaratively
This article aims to generate all theorems of a given size in the implicational fragment of propositional intuitionistic linear logic. It was presented at the 36th International Conference on Logic Programming (ICLP).
Date:
September 19, 2020
Creator:
Tarau, Paul & de Paiva, Valeria
System:
The UNT Digital Library
Blood cancer prediction using leukemia microarray gene data and hybrid logistic vector trees model
Article is a study proposing an approach for blood cancer disease prediction using the supervised machine learning approach to perform blood cancer prediction with high accuracy using microarray gene data.
Date:
January 19, 2022
Creator:
Rupapara, Vaibhav; Rustam, Furqan; Aljedaani, Wajdi; Shahzad, Hina Fatima; Lee, Ernesto & Ashraf, Imran
System:
The UNT Digital Library
FlexiChain 3.0: Distributed Ledger Technology-Based Intelligent Transportation for Vehicular Digital Asset Exchange in Smart Cities
Article describes how, due to the enormous amounts of data being generated between users, Intelligent Transportation Systems (ITS) are complex Cyber-Physical Systems that necessitate a reliable and safe infrastructure. In this work, the authors explore Distributed Ledger Technology (DLT) and collect data about consensus algorithms and their applicability to be used in the IoV as the backbone of ITS.
Date:
April 19, 2023
Creator:
Alkhodair, Ahmad; Mohanty, Saraju P. & Kougianos, Elias
System:
The UNT Digital Library
Predicting psoriasis using routine laboratory tests with random forest
Article describes how psoriasis is a chronic inflammatory skin disease that affects approximately 125 million people worldwide. The goal of the authors' study is to derive a powerful predictive model for psoriasis disease based on only routine hospital tests.
Date:
October 19, 2021
Creator:
Zhou, Jing; Li, Yuzhen & Guo, Xuan
System:
The UNT Digital Library