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Social- and Content-Aware Prediction for Video Content Delivery
Article proposes a Social- and Content-aware Video content delivery Prediction method (SCVP) to address the problem of predicting whether a video will be watched by a user for efficient video content delivery in mobile social networks.
Date:
February 10, 2020
Creator:
Fan, Yuqi; Yang, Bing; Hu, Donghui; Yuan, Xiaohui & Xu, Xiong
Object Type:
Article
System:
The UNT Digital Library
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
BAM: A Block-Based Bayesian Method for Detecting Genome-Wide Associations with Multiple Diseases
Article proposes a novel Bayesian method, named BAM, for simultaneously partitioning Single Nucleotide Polymorphisms (SNPs) into Linkage Disequilibrium(LD)-blocks and detecting genome-wide multi-locus epistatic interactions that are associated with multiple diseases. Experimental results on the simulated datasets demonstrate that BAM is powerful and efficient.
Date:
April 16, 2020
Creator:
Guo, Xuan; Wu, Guanying & Xu, Baohua
Object Type:
Article
System:
The UNT Digital Library
Detecting Negation Cues and Scopes in Spanish
Article addresses the processing of negation in Spanish by presenting a machine learning system that processes negation in Spanish and providing a qualitative error analysis aimed at understanding the limitations of the system and showing which negation cues and scopes are straightforward to predict automatically, and which ones are challenging.
Date:
May 2020
Creator:
Blanco, Eduardo; JimĂ©nez-Zafra, Salud MarĂa; Morante, Roser; MartĂn-Valdivia, MarĂa Teresa & Ureña-LĂłpez, L. Alfonso
Object Type:
Article
System:
The UNT Digital Library
An Experiment-Based Review of Low-Light Image Enhancement Methods
Article reviews the current techniques of low-light image enhancement.
Date:
May 6, 2020
Creator:
Yuan, Xiaohui; Wang, Wencheng; Wu, Xiaojin & Guo, Zairui
Object Type:
Article
System:
The UNT Digital Library
Massive MIMO Systems for 5G and beyond Networks—Overview, Recent Trends, Challenges, and Future Research Direction
This article presents a comprehensive overview of the key enabling technologies required for 5G and 6G networks, highlighting the massive MIMO systems. The authors discuss the fundamental challenges related to pilot contamination, channel estimation, precoding, user scheduling, energy efficiency, and signal detection in massive MIMO systems and discuss state-of-the-art mitigation techniques. Recent trends such as terahertz communication, ultra massive MIMO (UM-MIMO), visible light communication (VLC), machine learning, and deep learning for massive MIMO systems are outlined. Finally, future research for massive MIMO systems for 5G and beyond is discussed.
Date:
May 12, 2020
Creator:
Chataut, Robin & Akl, Robert G.
Object Type:
Article
System:
The UNT Digital Library
Mining Potential Effects of HUMIRA in Twitter Posts Through Relational Similarity
Article investigating HUMIRA effects mentioned in Twitter posts using a relational similarity-based method. The authors were able to identify effects previously known as well as potentially unreported, which demonstrates the power of this method and its potential for studying effects of other medications shared by Twitter users.
Date:
June 16, 2020
Creator:
Feng, Shichao; Jiang, Keyuan; Huang, Liyuan; Chen, Tingyu & Bernard, Gordon R.
Object Type:
Article
System:
The UNT Digital Library
Exploring Edge Computing in Multi-Person Mixed Reality for Cooperative Perception
Article and accompanying poster presenting a prototype for the use of Edge with MR devices to provide cooperative perception capability to the MR device.
Date:
June 25, 2020
Creator:
Tang, Sihai; Chen, Bruce (Haidi); Hochstetler, Jacob; Hirsch, Jason & Fu, Song
Object Type:
Article
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
Object Type:
Article
System:
The UNT Digital Library
Accelerometer-Based Automated Counting of Ten Exercises without Exercise-Specific Training or Tuning
Article presents research that creates an automatic repetition counting system that is flexible enough to measure multiple distinct and repeating movements during physical therapy without being trained on the specific motion.
Date:
October 10, 2020
Creator:
Zelman, Samuel; Dow, Michael; Tabashum, Thasina; Xiao, Ting & Albert, Mark
Object Type:
Article
System:
The UNT Digital Library
JS-MA: A Jensen-Shannon Divergence Based Method for Mapping Genome-Wide Associations on Multiple Diseases
Article develops a a simple, fast, and powerful method, named JS-MA, based on Jensen-Shannon divergence and agglomerative hierarchical clustering, to detect the genome-wide multi-locus interactions associated with multiple diseases.
Date:
October 30, 2020
Creator:
Guo, Xuan
Object Type:
Article
System:
The UNT Digital Library
An Analysis of Natural Language Inference Benchmarks through the Lens of Negation
Article presents a new benchmark for natural language inference in which negation plays a critical role and shows that state-of-the-art transformers struggle making inference judgments with the new pairs.
Date:
November 2020
Creator:
Hossain, Md Mosharaf; Dutta, Pranoy; Kao, Tiffany; Wei, Elizabeth; Blanco, Eduardo & Kovatchev, Venelin
Object Type:
Article
System:
The UNT Digital Library
Determining Event Outcomes: The Case of #fail
Article presents research determining event outcomes in social media.
Date:
November 2020
Creator:
Murugan, Srikala; Chinnappa, DhivyaAssociation for Computational Linguistics & Blanco, Eduardo
Object Type:
Article
System:
The UNT Digital Library
Helpful or Hierarchical? Predicting the Communicative Strategies of Chat Participants, and their Impact on Success
Article studies the communication styles present in chat interactions of thousands of aspiring entrepreneurs who discuss and develop business models. The authors find that these styles can be reliably predicted, and that the communication styles can be used to predict a number of indices of business success.
Date:
November 2020
Creator:
Rashid, Farzana; Blanco, Eduardo; Fornaciari, Tommaso; Hovy, Dirk & Vega-Redondo, Fernando
Object Type:
Article
System:
The UNT Digital Library
A Performance Study of Some Approximation Algorithms for Computing a Small Dominating Set in a Graph
Article implements and tests the performances of several approximation algorithms for computing the minimum dominating set of a graph. This article belongs to the Special Issue: Algorithms for Hard Graph Problems.
Date:
December 14, 2020
Creator:
Shahrokhi, Farhad; Li, Jonathan & Potru, Rohan
Object Type:
Article
System:
The UNT Digital Library
Investing Data with Untrusted Parties using HE
Article proposing the use of anonymization techniques coupled with graph algorithms over homomorphically encrypted (HE) graphs as a basis of analysis for this accumulated data. This approach ensures individuals’ privacy and anonymity while preserving the usefulness of the plaintext data. This article was originally presented at the 18th International Conference on Security and Cryptography - SECRYPT.
Date:
2021
Creator:
Dockendorf, Mark; Dantu, Ram; Morozov, Kirill & Bhowmick, Sanjukta
Object Type:
Article
System:
The UNT Digital Library
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.
Object Type:
Article
System:
The UNT Digital Library
On Comparing the Similarity and Dissimilarity Between Two Distinct Vehicular Trajectories
This article studies the problem of comparing the similarity and dissimilarity between two distinct vehicular trajectories by proposing an adjacency-based metric. This approach has a broad application in building truthfulness by comparing the similarity between two vehicles and evaluating the dissimilarity between two distinct paths in hazardous materials transportation.
Date:
February 23, 2021
Creator:
Qingge, Letu; Zhou, Peng; Dai, Lihui; Yang, Qing & Zhu, Binhai
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
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
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
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
Action unit classification for facial expression recognition using active learning and SVM
Article utilizing active learning and support vector machine (SVM) algorithms to classify facial action units (AU) for human facial expression recognition. Experimental results show that the proposed algorithm can effectively suppress correlated noise and achieve higher recognition rates than principal component analysis and a human observer on seven different facial expressions.
Date:
April 4, 2021
Creator:
Yao, Li; Wan, Yan & Xu, Bugao
Object Type:
Article
System:
The UNT Digital Library
Urban land-use analysis using proximate sensing imagery: a survey
This article reviews and summarizes the state-of-the-art methods and publicly available data sets from proximate sensing to support land-use analysis. Discussions highlight the challenges, strategies, and opportunities faced by the existing methods using proximate sensing imagery in urban land-use studies.
Date:
November 30, 2020
Creator:
Qiao, Zhinan & Yuan, Xiaohui
Object Type:
Article
System:
The UNT Digital Library
COS: A new MeSH term embedding incorporating corpus, ontology, and semantic predications
Article studying the problem of incorporating corpus, ontology, and semantic predications to learn the embeddings of MeSH terms. The authors propose a novel framework, Corpus, Ontology, and Semantic predications-based MeSH term embedding (COS), to generate high-quality MeSH term embeddings.
Date:
May 4, 2021
Creator:
Ding, Juncheng & Jin, Wei
Object Type:
Article
System:
The UNT Digital Library