Hybrid LDPC-STBC communications system based on chaos
Publication Date
Sat Jan 01 2022
Journal Name
Geotechnical Engineering And Sustainable Construction
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Publication Date
Sat Feb 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Revealing the potentials of 3D modelling techniques; a comparison study towards data fusion from hybrid sensors
Abstract<p>The vast advantages of 3D modelling industry have urged competitors to improve capturing techniques and processing pipelines towards minimizing labour requirements, saving time and reducing project risk. When it comes to digital 3D documentary and conserving projects, laser scanning and photogrammetry are compared to choose between the two. Since both techniques have pros and cons, this paper approaches the potential issues of individual techniques in terms of time, budget, accuracy, density, methodology and ease to use. Terrestrial laser scanner and close-range photogrammetry are tested to document a unique invaluable artefact (Lady of Hatra) located in Iraq for future data fusion sc</p>
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Publication Date
Mon Mar 07 2022
Journal Name
Journal Of Inorganic And Organometallic Polymers And Materials
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Publication Date
Thu Sep 01 2022
Journal Name
Structures
(9)
(7)
Publication Date
Thu Jan 01 2026
Journal Name
Bioresource Technology
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Publication Date
Thu Nov 01 2018
Journal Name
International Journal Of Biomathematics
A non-conventional hybrid numerical approach with multi-dimensional random sampling for cocaine abuse in Spain
This paper introduces a non-conventional approach with multi-dimensional random sampling to solve a cocaine abuse model with statistical probability. The mean Latin hypercube finite difference (MLHFD) method is proposed for the first time via hybrid integration of the classical numerical finite difference (FD) formula with Latin hypercube sampling (LHS) technique to create a random distribution for the model parameters which are dependent on time [Formula: see text]. The LHS technique gives advantage to MLHFD method to produce fast variation of the parameters’ values via number of multidimensional simulations (100, 1000 and 5000). The generated Latin hypercube sample which is random or non-deterministic in nature is further integ
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(2)
Publication Date
Mon Nov 01 2021
Journal Name
Energy Reports
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(84)
Publication Date
Tue Sep 01 2020
Journal Name
Petroleum
Reversible and irreversible adsorption of bare and hybrid silica nanoparticles onto carbonate surface at reservoir condition
Nanofluid
Silica nanoparticles
Wettability
Contact angle
Surface treatment
Adsorption
Salinity
Carbonate reservoir
Carbonate
Realistic implementation of nanofluids in subsurface projects including carbon geosequestration and enhanced oil recovery requires full understanding of nanoparticles (NPs) adsorption behaviour in the porous media. The physicochemical interactions between NPs and between the NP and the porous media grain surface control the adsorption behavior of NPs. This study investigates the reversible and irreversible adsorption of silica NPs onto oil-wet and water-wet carbonate surfaces at reservoir conditions. Each carbonate sample was treated with different concentrations of silica nanofluid to investigate NP adsorption in terms of nanoparticles initial size and hydrophobicity at different temperatures, and pressures. Aggregation behaviour and the
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Publication Date
Tue Jun 22 2021
Journal Name
Expert Systems
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(2)
Publication Date
Sat Jan 01 2022
Journal Name
Ieee Access
Wrapper and Hybrid Feature Selection Methods Using Metaheuristic Algorithms for English Text Classification: A Systematic Review
Metaheuristics
Feature extraction
Text categorization
Classification algorithms
Systematics
Search problems
Business
Feature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall
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