IUCRC Phase I University of North Texas: Center for Electric, Connected and Autonomous Technologies for Mobility (eCAT) (open access)

IUCRC Phase I University of North Texas: Center for Electric, Connected and Autonomous Technologies for Mobility (eCAT)

Data management plan for the grant "IUCRC Phase I University of North Texas: Center for Electric, Connected and Autonomous Technologies for Mobility (eCAT)."
Date: 2023-03-15/2028-02-29
Creator: Fu, Song
Object Type: Text
System: The UNT Digital Library
Computing microRNA-gene interaction networks in pan-cancer using miRDriver (open access)

Computing microRNA-gene interaction networks in pan-cancer using miRDriver

This article is a study where the authors integrated the multi-omics datasets such as copy number aberration, DNA methylation, gene and microRNA expression to identify the signature microRNA-gene associations from frequently aberrated DNA regions across pan-cancer utilizing a LASSO-based regression approach.
Date: March 8, 2022
Creator: Bose, Banabithi; Moravec, Matthew & Bozdag, Serdar
Object Type: Article
System: The UNT Digital Library
REU Site: TaMaLe - Testing and Machine Learning for Context-Driven Systems: Research Experience for Undergraduates (open access)

REU Site: TaMaLe - Testing and Machine Learning for Context-Driven Systems: Research Experience for Undergraduates

Data management plan for the grant, "REU Site: TaMaLe - Testing and Machine Learning for Context-Driven Systems: Research Experience for Undergraduates." TaMaLe (Testing and Machine Learning for Context-Driven Systems), a renewal Research Experience for Undergraduates (REU) Site at University of North Texas, engages 10 undergraduate students for 10 weeks with problems in the context-driven system domain. The students explore research problems to improve the reliability and security of context-driven systems. Context-driven systems, such as mobile apps, face constant streams of input from both users and context changes in their environments. Users interact with apps through touch and speech interfaces. These systems also respond to context events that occur in their environments such as changes to network connection, battery level, screen orientation, and more. The combined explosion of possible user events and context event sequences pose new challenges that require cost effective testing solutions. Students and mentors in this REU program work in small teams to develop and empirically evaluate new software testing techniques for context-driven systems using strategies such as reinforcement learning and combinatorial-based techniques.
Date: 2022-03-01/2025-02-28
Creator: Bryce, Renee & Tunc, Cihan
Object Type: Text
System: The UNT Digital Library
Detection of Parkinson's Disease Through Automated Pupil Tracking of the Post-illumination Pupillary Response (open access)

Detection of Parkinson's Disease Through Automated Pupil Tracking of the Post-illumination Pupillary Response

This article describes a system for pupil size estimation with a user interface to allow rapid adjustment of parameters and extraction of pupil parameters of interest in order to identify Parkinson's disease (PD) as early as possible.
Date: March 25, 2021
Creator: Tabashum, Thasina; Zaffer, Adnaan; Yousefzai, Raman; Colletta, Kalea; Jost, Mary Beth; Park, Youngsook et al.
Object Type: Article
System: The UNT Digital Library
Automatic trend detection: Time-biased document clustering (open access)

Automatic trend detection: Time-biased document clustering

This article presents a novel approach of introducing a weighted temporal feature to bias a topic clustering toward articles in a similar time frame, performed over a set of finance journal abstracts from 1974 to 2020 to demonstrate how time can be emphasized in trend detection. The authors detect trending finance topics that are not identifiable when we use a standard clustering approach with no temporal bias.
Date: March 2, 2021
Creator: Behpour, Sahar; Mohammadi, Mohammadmahdi; Albert, Mark; Alam, Zinat S.; Wang, Lingling & Xiao, Ting
Object Type: Article
System: The UNT Digital Library
Research Experiences for Undergraduates Site: Interdisciplinary Research Experience on Accelerated Deep Learning through A Hardware-Software Collaborative Approach (open access)

Research Experiences for Undergraduates Site: Interdisciplinary Research Experience on Accelerated Deep Learning through A Hardware-Software Collaborative Approach

Data management plan for the grant, "REU Site: Interdisciplinary Research Experience on Accelerated Deep Learning through A Hardware-Software Collaborative Approach." This Research Experiences for Undergraduates (REU) Site Program at the University of North Texas will enhance the knowledge and research skills of a diverse cohort of undergraduate students through empowering, innovative, and interdisciplinary research experiences in developing Deep Learning applications and systems. The program aims to 1) expose undergraduate students to real-world and cutting-edge research focused on accelerated deep learning through combined hardware and software development; 2) encourage more undergraduate students to continue their academic careers and seek graduate degrees in computer science, computer engineering, and related disciplines; 3) develop research skills and improve communication and collaborative skills in undergraduate students.
Date: 2021-03-01/2024-02-29
Creator: Zhao, Hui & Albert, Mark
Object Type: Text
System: The UNT Digital Library
SSOR Preconditioned Gauss-Seidel Detection and Its Hardware Architecture for 5G and beyond Massive MIMO Networks (open access)

SSOR Preconditioned Gauss-Seidel Detection and Its Hardware Architecture for 5G and beyond Massive MIMO Networks

This article proposes a novel preconditioned and accelerated Gauss–Siedel algorithm referred to as Symmetric Successive Overrelaxation Preconditioned Gauss-Seidel (SSORGS) to address the signal detection challenges associated with massive MIMO technology.
Date: March 1, 2021
Creator: Chataut, Robin; Akl, Robert G.; Dey, Utpal Kumar & Robaei, Mohammadreza
Object Type: Article
System: The UNT Digital Library
Hidden Markov model-based activity recognition for toddlers (open access)

Hidden Markov model-based activity recognition for toddlers

Article describes study which sought to evaluate methods for activity recognition for toddlers.
Date: March 5, 2020
Creator: Albert, Mark; Sugianto, Albert; Nickele, Katherine; Zavos, Patricia; Sindu, Pinky; Ali, Munazza et al.
Object Type: Article
System: The UNT Digital Library