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12 Matching Results
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Multi-Objective Response to Co-Resident Attacks in Cloud Environment
This article introduces a novel multi-objective attack response system.
Date:
September 17, 2017
Creator:
Abazari, Farzaneh; Analoui, Morteza & Takabi, Hassan
System:
The UNT Digital Library
Modelling HIV Intervention among Most-at-Risk/Key Population: Case Study of FWSS in Nigeria
This article discusses a novel risk equation for estimating new infections among Females who Sell Sex (FWSS), their clients, and communities.
Date:
September 28, 2017
Creator:
Akwafuo, Sampson; Shattock, Andrew & Mikler, Armin R.
System:
The UNT Digital Library
Role of Artificial Intelligence for Analysis of COVID-19 Vaccination-Related Tweets: Opportunities, Challenges, and Future Trends
Article states that vaccines, though reliable preventative measures for diseases, also raise public concerns; public apprehension and doubts challenge the acceptance of new vaccines including the COVID-19 vaccines. This study is the first attempt to review the role of AI approaches in COVID-19 vaccination-related sentiment analysis.
Date:
September 5, 2022
Creator:
Aljedaani, Wajdi; Saad, Eysha; Rustam, Furqan; de la Torre DĂez, Isabel & Ashraf, Imran
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
System:
The UNT Digital Library
Dynamic intimate contact social networks and epidemic interventions
This article discusses dynamic intimate contact social networks and epidemic interventions.
Date:
September 9, 2008
Creator:
Corley, Courtney; Mikler, Armin R.; Cook, Diane J., 1963- & Singh, Karan P.
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
System:
The UNT Digital Library
Attention-Based Dense Point Cloud Reconstruction From a Single Image
Article proposes a two-stage training dense point cloud generation network.
Date:
September 23, 2019
Creator:
Lu, Qiang; Xiao, Mingjie; Lu, Yiyang; Yuan, Xiaohui & Yu, Ye
System:
The UNT Digital Library
Parallel Texts
Article discussing parallel texts and natural language processing.
Date:
September 21, 2005
Creator:
Mihalcea, Rada, 1974- & Simard, Michel
System:
The UNT Digital Library
Networks and Natural Language Processing
Article discussing networks and natural language processing. The authors present some of the most successful graph-based representations and algorithms used in language processing and try to explain how and why they work.
Date:
September 2008
Creator:
Radev, Dragomir R. & Mihalcea, Rada, 1974-
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
System:
The UNT Digital Library
Natlog: a Lightweight Logic Programming Language with a Neuro-symbolic Touch
Article that introduces Natlog, a lightweight Logic Programming language, sharing Prolog's unification-driven execution model, but with a simplified syntax and semantics. The authors' proof-of-concept Natlog implementation is tightly embedded in the Python-based deep-learning ecosystem with focus on content-driven indexing of ground term datasets. As an overriding of the authors symbolic indexing algorithm, the same function can be delegated to a neural network, serving ground facts to Natlog's resolution engine. The open-source implementation is available as a Python package at t https://pypi.org/project/natlog/.
Date:
September 17, 2021
Creator:
Tarau, Paul
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