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Comparative classification of spectrally overlapping Allium seed genotypes using Vis-NIR spectroscopy and hyperspectral imaging with chemometric, machine, and deep learning models
Novel Cement-Free UHPC with High Gamma-Ray Resistance Using Calcium Oxide-Activated Slag, Iron and Barite Powders, and Steel Fibers
Strengthening of Two-Way RC Flat Slabs for Punching Shear Using Steel Dowels and CFRP Sheet with EBROG and EBRIG Methods: An Experimental Study
Improving prediction accuracy of CSM-CERES-Wheat model for water and nitrogen response using a modified Penman-Monteith equation in a semi-arid region
Comparative classification of spectrally overlapping Allium seed genotypes using Vis-NIR spectroscopy and hyperspectral imaging with chemometric, machine, and deep learning models
Comparative classification of spectrally overlapping Allium seed genotypes using Vis-NIR spectroscopy and hyperspectral imaging with chemometric, machine, and deep learning models
Predicting hydrogen production in porous foams for steam methane reforming: A combined approach using computational fluid dynamics and machine learning regression models
Comparative classification of spectrally overlapping Allium seed genotypes using Vis-NIR spectroscopy and hyperspectral imaging with chemometric, machine, and deep learning models
Single-atom catalysts (SACs) for CO <sub>2</sub> to CO conversion using Cu, Ni, and Co on graphene flakes support; a DFT study
Comparative classification of spectrally overlapping Allium seed genotypes using Vis-NIR spectroscopy and hyperspectral imaging with chemometric, machine, and deep learning models
Trace analysis of basic drugs in micro-volume human plasma samples using a simple device combined with a gas chromatography-flame ionization detector
Promising label-free trapping, isolation and detection of extracellular vesicles, using an interdigitated microelectrode array integrated in a microfluidic cell: theoretical and experimental assessments
Predicting hydrogen production in porous foams for steam methane reforming: A combined approach using computational fluid dynamics and machine learning regression models
MSc Supervision
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