Results 61 to 70 of about 12,139 (206)

Enhancing Rock Strength Prediction and Features Selection by Coupling Well Log Data and Deep Learning Approaches in Reservoir Geomechanics

International Journal for Numerical and Analytical Methods in Geomechanics, EarlyView.
ABSTRACT Accurate rock strength parameters play a vital role in petroleum and mining operations for sustainable drilling activities, and wellbore stability analysis. This study investigates the applicability of deep learning techniques for assessing data‐driven models, and to conduct parametric sensitivity examination for feature attributes ranking to ...
Mohammad Islam Miah, Md. Shakil Rahaman, Travis Wiens   +2 more
wiley   +1 more source

Data on some socio-economic parameters explaining the movement of extra-EU asylum seekers in Europe

Data in Brief, 2016
This article contains data concerning the movement of extra-EU asylum seekers in Europe. Data used in this paper were collected from the Eurostat database and the UNHCR database.
Silvia Angeloni
doaj   +1 more source

Visibility Constrained Generative Model for Depth-based 3D Facial Pose Tracking

, 2019
In this paper, we propose a generative framework that unifies depth-based 3D facial pose tracking and face model adaptation on-the-fly, in the unconstrained scenarios with heavy occlusions and arbitrary facial expression variations.
Cai, Jianfei, Cham, Tat-Jen, Ngan, King Ngi, Pavlovic, Vladimir, Sheng, Lu   +4 more
core   +1 more source

Modeling spatiotemporal patterns of microplastic pollution in the lupit river using multilinear regression

Scientific Reports
Abstract Despite increasing awareness of microplastics as contaminants, their sources and abundance factors remain poorly understood. This study found widespread microplastic pollution in the Lupit River. Microplastic concentrations were determined from surface water samples once per season.
Raab, Katharina, Wagner, Ralf, Sales, Marie Therese, Uy, Christer John, Salazar, Benedict   +4 more
openaire   +3 more sources

Biosurfactant production by Pseudomonas aeruginosa isolated from mining waste: From genomic analysis to development of a polymeric composite for removal of hexavalent chromium

Polymer International, EarlyView.
Biosurfactant was produced by Pseudomonas aeruginosa using andiroba waste from Amazonia. A biosurfactant–alginate composite (Alg/BioS) was successfully synthesized via ionotropic gelation, and achieved up to 70% Cr6+ removal from water. Abstract Environmental contamination by heavy metals represents a significant challenge due to their persistence in ...
Paulo Diniz Austriaco, Emilly Cruz da Silva, Glenda Sores Gomes, Joane Almeida Alves, Amanda Vidal, Leandro Argolo, Rafaela Ribeiro, Luciana Souza, José Augusto Pires Bitencourt, Leonardo Brasil Felipe, Leonie Asfora Sarubbo, Sidnei Cerqueira dos Santos   +11 more
wiley   +1 more source

The relationship between seasonal mean temperature and most extreme day

Quarterly Journal of the Royal Meteorological Society, EarlyView.
In Northern Hemisphere winter, there is a strong correlation between seasonal mean temperature and coldest daily mean temperature which varies in magnitude from one region to another (with a weaker relationship in summer between mean and hottest day).
Anna Maidens, Hazel E. Thornton, Philip Bett‐Williams, Doug Smith   +3 more
wiley   +1 more source

Recurrence Multilinear Regression Technique for Improving Accuracy of Energy Prediction in Power Systems

Energies
This paper demonstrates how artificial intelligence can be implemented in order to predict the energy needs of daily households using both multilinear regression (MLR) and single linear regression (SLR) methods.
Quota Alief Sias, Rahma Gantassi, Yonghoon Choi, Jeong Hwan Bae   +3 more
doaj   +1 more source

DesMol2, an Effective Tool for the Construction of Molecular Libraries and Its Application to QSAR Using Molecular Topology

Molecules, 2019
A web application, DesMol2, which offers two main functionalities, is presented: the construction of molecular libraries and the calculation of topological indices.
Inma García-Pereira, Riccardo Zanni, Maria Galvez-Llompart, Jorge Galvez, Ramón García-Domenech   +4 more
doaj   +1 more source

Machine learning models for predicting unconfined compressive strength: A case study for Precambrian basement complex rocks from Ado-Ekiti, Southwestern Nigeria

Scientific African, 2023
This study investigates the applicability of four distinct machine learning (ML) models – Random Forest (RF), Relevance Vector Machine (RVM), Support Vector Machine (SVM), and Artificial Neural Network (ANN) - for predicting the unconfined compressive ...
Lekan Olatayo Afolagboye, Damilola Emmanuel Ajayi, Inioluwa Opeyemi Afolabi   +2 more
doaj   +1 more source

Adaptive Higher-order Spectral Estimators

, 2017
Many applications involve estimation of a signal matrix from a noisy data matrix. In such cases, it has been observed that estimators that shrink or truncate the singular values of the data matrix perform well when the signal matrix has approximately low
Gerard, David, Hoff, Peter
core   +1 more source