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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
Accuracy-Constrained Efficiency Optimization and GPU Profiling of CNN Inference for Detecting Drainage Crossing Locations
Article describes how the accurate and efficient determination of hydrologic connectivity has garnered significant attention from both academic and industrial sectors due to its critical implications for environment management. To address these challenges, the focus of the author's study is on detecting drainage crossings through the application of advanced convolutional neural networks.
Date:
November 12, 2023
Creator:
Zhang, Yicheng; Pandey, Dhroov; Wu, Di; Kundu, Turja; Li, Ruopu & Shu, Tong
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
agroString: Visibility and Provenance through a Private Blockchain Platform for Agricultural Dispense towards Consumers
Article discusses the large quantities of farm and meat products that rot and are wasted if correct actions are not taken leading to serious health concerns if consumed. Because there is no proper system for tracking and communicating the status of goods to consumers, a right which according to the authors should be a given, they propose a method of increased communication using Corda private blockchain.
Date:
October 27, 2022
Creator:
Vangipuram, Sukrutha L. T.; Mohanty, Saraju P.; Kougianos, Elias & Ray, Chittaranjan
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
Artificial Intelligence for Colonoscopy: Past, Present, and Future
Article summarizing the past and present development of colonoscopy video analysis methods, focusing on two categories of artificial intelligence (AI) technologies used in clinical trials, (1) analysis and feedback for improving colonoscopy quality and (2) detection of abnormalities.
Date:
August 2021
Creator:
Tavanapong, Wallapak; Oh, JungHwan; Riegler, Michael; Khaleel, Mohammed I.; Mitta, Bhuvan & de Groen, Piet C.
Object Type:
Article
System:
The UNT Digital Library
Autoencoder Composite Scoring to Evaluate Prosthetic Performance in Individuals with Lower Limb Amputation
Authors of the article created an overall assessment metric using a deep learning autoencoder to directly compare clinical outcomes in a comparison of lower limb amputees using two different prosthetic devices—a mechanical knee and a microprocessor-controlled knee. The proposed methods were used on data collected from ten participants with a dysvascular transfemoral amputation recruited for a prosthetics research study.
Date:
October 18, 2022
Creator:
Tabashum, Thasina; Xiao, Ting; Jayaraman, Chandrasekaran; Mummidisetty, Chaithanya K.; Jayaraman, Arun & Albert, Mark
Object Type:
Article
System:
The UNT Digital Library
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
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
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
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
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
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
COVID-19 Vaccination-Related Sentiments Analysis: A Case Study Using Worldwide Twitter Dataset
Article is a study analyzing the global perceptions and perspectives towards COVID-19 vaccination using a worldwide Twitter dataset, natural language processing, and machine learning.
Date:
December 20, 2021
Creator:
Reshi, Aijaz Ahmad; Rustam, Furqan; Aljedaani, Wajdi; Shafi, Shabana; Alhossan, Abdulaziz; Alrabiah, Ziyad et al.
Object Type:
Article
System:
The UNT Digital Library
Crinet: A computational tool to infer genome-wide competing endogenous RNA (ceRNA) interactions
This article develops a computational tool named Crinet to infer genome-wide ceRNA networks addressing critical drawbacks. Crinet-inferred ceRNA groups that were consistently involved in the immune system related processes could be important assets in the light of the studies confirming the relation between immunotherapy and cancer. The source code of Crinet is in R and available at https://github.com/bozdaglab/crinet.
Date:
May 13, 2021
Creator:
Kesimoglu, Ziynet Nesibe & Bozdag, Serdar
Object Type:
Article
System:
The UNT Digital Library
Deep learning for peptide identification from metaproteomics datasets
This article explores a proposed deep-learning-based algorithm called DeepFilter for improving peptide identifications from a collection of tandem mass spectra. The authors find that DeepFilter is believed to generalize properly to new, previously unseen peptide-spectrum-matches and can be readily applied in peptide identification from metaproteomics data.
Date:
July 8, 2021
Creator:
Feng, Shichao; Sterzenbach, Ryan & Guo, Xuan
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
Design and Assessment of a Task-Driven Introductory Data Science Course Taught Concurrently in Multiple Languages: Python, R, and MATLAB
This article is from the 26th ACM Conference on Innovation and Technology in Computer Science Education and discusses the design, effectiveness, and curricular impacts of an introductory data science course focused on practical programming skills and allowing students to concurrently complete the course in Python, R, or MATLAB. Students indicated a preference for the multi-language course design and the course became the recommended first programming course for a newly developed and approved undergraduate data science majors.
Date:
June 26, 2021
Creator:
Xiao, Ting; Greenberg, Ronald I. & Albert, Mark
Object Type:
Article
System:
The UNT Digital Library
Detecting Covid-19 chaos driven phishing/malicious URL attacks by a fuzzy logic and data mining based intelligence system
Article analyses the impact of Covid-19 on various cyber-security related aspects.
Date:
June 7, 2022
Creator:
Zahra, Syed Rameem; Chishti, Mohammad Ahsan; Baba, Asif Iqbal & Wu, Fan
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; Jiménez-Zafra, Salud María; Morante, Roser; Martín-Valdivia, María Teresa & Ureña-López, L. Alfonso
Object Type:
Article
System:
The UNT Digital Library
Detection of DDoS Attack in Software-Defined Networking Environment and Its Protocol-wise Analysis using Machine Learning
Article describes how distributed-denial-of-service (DDoS) attacks can cause a great menace to numerous organizations and their stakeholders. The authors assert that the objective of this research work is to take into account a DDoS afflicted SDN specific dataset and detect the malicious traffic by using various machine learning algorithms namely., K-Nearest Neighbours, Logistic Regression, Multilayer Perceptron, Iterative Dichotomiser 3, and Stochastic Gradient Descent.
Date:
January 10, 2022
Creator:
Prasad, Ashwani; Prasad, Sanjana; Arockiasamy, Karmel; P, Karthika & Yuan, Xiaohui
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
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
Electroencephalogram Signals for Detecting Confused Students in Online Education Platforms with Probability-Based Features
Article discusses how despite the advantages of online education, it lacks face-to-face settings, which makes it very difficult to analyze the students’ level of interaction, understanding, and confusion. This study proposes a novel engineering approach that uses probability-based features (PBF) for increasing the efficacy of machine learning models.
Date:
September 9, 2022
Creator:
Daghriri, Talal; Rustam, Furqan; Aljedaani, Wajdi; Bashiri, Abdullateef H. & Ashraf, Imran
Object Type:
Article
System:
The UNT Digital Library