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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
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
A smartphone-based online system for fall detection with alert notifications and contextual information of real-life falls
This article presents the results of a prospective study investigating a proof-of-concept, smartphone-based, online system for fall detection and notification. Apart from functioning as a practical fall monitoring instrument, this system may serve as a valuable research tool, enable future studies to scale their ability to capture fall-related data, and help researchers and clinicians to investigate real-falls.
Date:
August 10, 2021
Creator:
Harari, Yaar; Shawen, Nicholas; Mummidisetty, Chaithanya K.; Albert, Mark & Kording, Konrad P.
Object Type:
Article
System:
The UNT Digital Library
Event-Driven Deep Learning for Edge Intelligence (EDL-EI)
Article on deep-learning framework for edge intelligence EDL-EI (event-driven deep learning for edge intelligence). To verify the proposed framework, the authors include a case study of air-quality scenarios based for the most polluted cities in South Korea and China.
Date:
September 8, 2021
Creator:
Shah, Sayed Khushal; Tariq, Zeenat; Lee, Jeehwan & Lee, Yugyung
Object Type:
Article
System:
The UNT Digital Library
Identifying Degree and Sources of Non-Determinism in MPI Applications Via Graph Kernels
This article proposes a software framework for identifying the percentage and sources of communication non-determinism.
Date:
May 18, 2021
Creator:
Chapp, Dylan; Tan, Nigel; Bhowmick, Sanjukta & Taufer, Michela
Object Type:
Article
System:
The UNT Digital Library
Evaluating spatial patterns of seasonal ozone exposure and incidence of respiratory emergency room visits in Dallas-Fort Worth
This article examines the relationships between spatial patterns of long-term ozone exposure and respiratory illness within Dallas-Fort Worth to better understand impacts on health outcomes.
Date:
April 13, 2021
Creator:
Northeim, Kari; Marks, Constant & Tiwari, Chetan
Object Type:
Article
System:
The UNT Digital Library
Protein functional module identification method combining topological features and gene expression data
Article conducting an intensive study on the problems of low recognition efficiency and noise in the overlapping structure of protein functional modules, based on topological characteristics of PPI network. Developing a protein function module recognition method ECTG based on Topological Features and Gene expression data for Protein Complex Identification. The experimental results show that the ECTG algorithm can detect protein functional modules better.
Date:
June 8, 2021
Creator:
Zhao, Zihao; Xu, Wenjun; Chen, Aiwen; Han, Yueyue; Xia, Shengrong; Xiang, ChuLei et al.
Object Type:
Article
System:
The UNT Digital Library
Using a microprocessor knee (C-Leg) with appropriate foot transitioned individuals with dysvascular transfemoral amputations to higher performance levels: a longitudinal randomized clinical trial
Article evaluating whether advanced prostheses can provide better safety and performance capabilities to maintain and improve quality of life in individuals who are predominantly designated MFCL level K2. This study used a 13 month longitudinal clinical trial to determine the benefits of using a C-Leg and 1M10 foot in individuals at K2 level with transfemoral amputation due to vascular disease.
Date:
May 25, 2021
Creator:
Jayaraman, Chandrasekaran; Mummidisetty, Chaithanya K.; Albert, Mark; Lipschutz, Robert; Hoppe-Ludwig, Shenan; Mathur, Gayatri et al.
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
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
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
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
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
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
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
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
Measuring the impact of suspending Umrah, a global mass gathering in Saudi Arabia on the COVID‑19 pandemic
This article uses a stratified SEIR epidemic model to evaluate the impact of Umrah, a global Muslim pilgrimage to Mecca, on the spread of the COVID-19 pandemic during the month of Ramadan, the peak of the Umrah season. The analyses provide insights into the effects of global mass gatherings on the progression of the COVID-19 pandemic locally and globally.
Date:
September 6, 2021
Creator:
Alshammari, Sultanah M.; Almutiry, Waleed K.; Gwalani, Harsha; Algarni, Saeed M. & Saeedi, Kawther
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
Personal Internet of Things (PIoT): What Is It Exactly?
This article provides a big picture of PIoT architecture, vision, and future research scope. The exploratory study of PIoT is in its infancy, which will explore the expansion of new use cases, service requirements, and the proliferation of PIoT devices. This is a preprint version of this article.
Date:
May 14, 2021
Creator:
Sahoo, Biswa P. S.; Mohanty, Saraju P.; Puthal, Deepak & Pillai, Prashant
Object Type:
Article
System:
The UNT Digital Library
PhenoGeneRanker: Gene and Phenotype Prioritization Using Multiplex Heterogeneous Networks
Article
Date:
July 20, 2021
Creator:
Dursun, Cagatay; Kwitek, Anne E. & Bozdag, Serdar
Object Type:
Article
System:
The UNT Digital Library
Recent advances in processing negation
This article surveys previous work on negation with an emphasis on computational approaches.
Date:
December 17, 2021
Creator:
Morante, Roser & Blanco, Eduardo
Object Type:
Article
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
Weak-Light Image Enhancement Method Based on Adaptive Local Gamma Transform and Color Compensation
This article proposes a correction method for image enhancement models based on an adaptive local gamma transformation and color compensation inspired by the illumination reflection model. It is demonstrated that the proposed method adaptively reduces the influence of uneven illumination to avoid overenhancement and improves the visual effect of low-light images.
Date:
June 25, 2021
Creator:
Wang, Wencheng; Yuan, Xiaohui; Chen, Zhenxue; Wu, Xiaojin & Gao, Zairui
Object Type:
Article
System:
The UNT Digital Library