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Now showing items 51-60 of 144
An integrated framework of data-driven, metaheuristic, and mechanistic modeling approach for biomass pyrolysis
(
Elsevier
, 2022 , Article)
This study presents an integrated hybrid framework of data-driven (cascade forward neural network (CFNN)), metaheuristic (artificial bee colony (ABC)), and a mechanistic modeling (Aspen simulation) approach for the biomass ...
Performance evaluation of time-frequency image feature sets for improved classification and analysis of non-stationary signals: Application to newborn EEG seizure detection
(
Elsevier B.V.
, 2017 , Article)
This study demonstrates that a time-frequency (TF) image pattern recognition approach offers significant advantages over standard signal classification methods that use t-domain only or f-domain only features. Two approaches ...
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 ...
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 ...
Machine Learning Methods for Dysgraphia Screening with Online Handwriting Features
(
Institute of Electrical and Electronics Engineers Inc.
, 2022 , Conference Paper)
Dysgraphia, a major learning disorder that primarily interferes with writing skills can hinder the academic track of children unless recognized in the early stage. The diversity in the symptoms, as well as the emergence ...
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
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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 ...
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 ...
Enhancing Safety in Geological Carbon Sequestration: Supervised Machine Learning for Early Detection and Mitigation of CO2 Leakage in Injection Wells
(
International Petroleum Technology Conference (IPTC)
, 2024 , Conference Paper)
The efficient and safe operation of CO2 injection wells during geological sequestration is crucial for successful carbon capture and storage (CCS) projects. This study explores the application of machine learning in creating ...
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, ...