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State of charge estimation for a group of lithium-ion batteries using long short-term memory neural network
(
Elsevier
, 2022 , Article)
The present paper estimates for the first time the State of Charge (SoC) of a high capacity grid-scale lithium-ion battery storage system used to improve the power profile in a distribution network. The proposed long ...
Developing future human-centered smart cities: Critical analysis of smart city security, Data management, and Ethical challenges
(
Elsevier
, 2022 , Article Review)
As the globally increasing population drives rapid urbanization in various parts of the world, there is a great need to deliberate on the future of the cities worth living. In particular, as modern smart cities embrace ...
Arabic natural language processing for Qur'anic research: a systematic review
(
Springer Nature
, 2023 , Article)
The Qur'an is a fourteen centuries old divine book in Arabic language that is read and followed by almost two billion Muslims globally as their sacred religious text. With the rise of Islam, the Arabic language gained ...
Methodological considerations for identifying multiple plasma proteins associated with all-cause mortality in a population-based prospective cohort
(
Nature Research
, 2021 , Article)
Novel methods to characterize the plasma proteome has made it possible to examine a wide range of proteins in large longitudinal cohort studies, but the complexity of the human proteome makes it difficult to identify robust ...
Predictive ANN models for varying filler content for cotton fiber/PVC composites based on experimental load displacement curves
(
Elsevier Ltd
, 2020 , Article)
In this paper, artificial neural network (ANN) models are developed to predict the load-displacement curves for better understanding the behavior of cotton fiber/polyvinyl chloride (PVC) composites. Series of experiments ...
Data-driven modeling to predict the load vs. displacement curves of targeted composite materials for industry 4.0 and smart manufacturing
(
Elsevier Ltd
, 2021 , Article)
This work presents an approach for smart manufacturing focusing on Industry 4.0 to predict the load vs. displacement curve of targeted cotton fiber/Polypropylene (PP) composite materials while complying with the required ...
Optimal filler content for cotton fiber/PP composite based on mechanical properties using artificial neural network
(
Elsevier Ltd
, 2020 , Other)
In this paper, a machine learning-based approach has been proposed to integrate artificial intelligence during the designing of fiber-reinforced polymeric composites. With the help of the proposed approach, an artificial ...
Machine learning for prediction of the uniaxial compressive strength within carbonate rocks
(
Springer Science and Business Media Deutschland GmbH
, 2023 , Article)
The Uniaxial Compressive Strength (UCS) is an essential parameter in various fields (e.g., civil engineering, geotechnical engineering, mechanical engineering, and material sciences). Indeed, the determination of UCS in ...
Dairy Cow Rumination Detection: A Deep Learning Approach
(
Springer Science and Business Media Deutschland GmbH
, 2020 , Conference Paper)
Cattle activity is an essential index for monitoring health and welfare of the ruminants. Thus, changes in the livestock behavior are a critical indicator for early detection and prevention of several diseases. Rumination ...
Factors Affecting Student Satisfaction Towards Online Teaching: A Machine Learning Approach
(
Springer Science and Business Media Deutschland GmbH
, 2022 , Conference Paper)
During the outbreak of the Covid-19 pandemic, universities were forced to adopt technology and collaboration tools to reinforce online teaching and sustain their operations. This radical change pushes universities, ...