The Experts below are selected from a list of 210 Experts worldwide ranked by ideXlab platform
Erika Micheli - One of the best experts on this subject based on the ideXlab platform.
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Creating a novel comprehensive soil classification system by sequentially adding taxa from existing systems
Geoderma Regional, 2017Co-Authors: Philip Hughes, David J. Palmer, Jonathan Hempel, Jingyi Huang, Budiman Minasny, Alexander B. Mcbratney, Erika MicheliAbstract:Abstract Many different soil classification systems exist around the world and soil profile descriptions have always been difficult to successfully translate between taxonomic systems. In order to do this, there is the requirement for a comprehensive soil classification. This database needs to be comprehensive, non-duplicated, have the capacity for other suitable taxa to be added to, and at the same time to be small and simple. In this paper, we proposed a nearest-neighbour distance calculated based on the principal component space of the soil variables to Remove Redundancy of the existing soil classification and evaluate the equivalence between the different soil classification system. After removing the Redundancy, Great Groups of the New Zealand Classification and Australian Soil Classification and Soil Groups of the World Reference Base for Soil Resources were sequentially added to the Great Groups of the US Soil Taxonomy. This resulted in a comprehensive soil classification. The comprehensive soil classification allowed for the further addition of taxa from other soil classification and was capable of robustly allocating unknown soil profiles via either hard or fuzzy classification methods. The possibility merging and simplifying of such different systems demonstrates the possibility of similar mergers with taxonomies of other nations, creating a fully populated taxonomic space – a truly global or universal soil classification system.
Luce Morin - One of the best experts on this subject based on the ideXlab platform.
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Three-Dimensional Image Processing (3DIP) and Applications - Space carving MVD sequences for modeling natural 3D scenes
Three-Dimensional Image Processing (3DIP) and Applications II, 2012Co-Authors: Youssef Alj, Guillaume Boisson, Philippe Bordes, Muriel Pressigout, Luce MorinAbstract:This paper presents a 3D modeling system designed for Multi-view Video plus Depth (MVD) sequences. The aim is to Remove Redundancy in both texture and depth information present in the MVD data. To this end, a volumetric framework is employed in order to merge the input depth maps. Hereby a variant of the Space Carving algorithm is proposed. Voxels are iteratively carved by ray-casting from each view, until the 3D model be geometrically consistent with every input depth map. A surface mesh is then extracted from this volumetric representation thanks to the Marching Cubes algorithm. Subsequently, to address the issue of texture modeling, a new algorithm for multi-texturing the resulting surface is presented. This algorithm selects from the set of input images the best texture candidate to map a given mesh triangle. The best texture is chosen according to a photoconsistency metric. Tests and results are provided using still images from usual MVD test-sequences.
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Space Carving MVD Sequences for Modeling Natural 3D Scenes
2012Co-Authors: Youssef Alj, Guillaume Boisson, Philippe Bordes, Muriel Pressigout, Luce MorinAbstract:This paper presents a 3D modeling system designed for Multi-view Video plus Depth (MVD) sequences. The aim is to Remove Redundancy in both texture and depth information present in the MVD data. To this end, a volumetric framework is employed in order to merge the input depth maps. Hereby a variant of the Space Carving algorithm is proposed. Voxels are iteratively carved by ray-casting from each view, until the 3D model be geometrically consistent with every input depth map. A surface mesh is then extracted from this volumetric representation thanks to the Marching Cubes algorithm. Subsequently, to address the issue of texture modeling, a new algorithm for multi-texturing the resulting surface is presented. This algorithm selects from the set of input images the best texture candidate to map a given mesh triangle. The best texture is chosen according to a photoconsistency metric. Tests and results are provided using still images from usual MVD test-sequences.
Philip Hughes - One of the best experts on this subject based on the ideXlab platform.
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Creating a novel comprehensive soil classification system by sequentially adding taxa from existing systems
Geoderma Regional, 2017Co-Authors: Philip Hughes, David J. Palmer, Jonathan Hempel, Jingyi Huang, Budiman Minasny, Alexander B. Mcbratney, Erika MicheliAbstract:Abstract Many different soil classification systems exist around the world and soil profile descriptions have always been difficult to successfully translate between taxonomic systems. In order to do this, there is the requirement for a comprehensive soil classification. This database needs to be comprehensive, non-duplicated, have the capacity for other suitable taxa to be added to, and at the same time to be small and simple. In this paper, we proposed a nearest-neighbour distance calculated based on the principal component space of the soil variables to Remove Redundancy of the existing soil classification and evaluate the equivalence between the different soil classification system. After removing the Redundancy, Great Groups of the New Zealand Classification and Australian Soil Classification and Soil Groups of the World Reference Base for Soil Resources were sequentially added to the Great Groups of the US Soil Taxonomy. This resulted in a comprehensive soil classification. The comprehensive soil classification allowed for the further addition of taxa from other soil classification and was capable of robustly allocating unknown soil profiles via either hard or fuzzy classification methods. The possibility merging and simplifying of such different systems demonstrates the possibility of similar mergers with taxonomies of other nations, creating a fully populated taxonomic space – a truly global or universal soil classification system.
Guomei Zhang - One of the best experts on this subject based on the ideXlab platform.
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VTC-Fall - Simplified Optimal Scheduling (SOS) for Network Coded Wireless Multicast
2018 IEEE 88th Vehicular Technology Conference (VTC-Fall), 2018Co-Authors: Nadieh Moghadam, Guomei ZhangAbstract:A Simplified Optimal Scheduling (SOS) scheme for network coded wireless multicast is studied in this paper. Specifically, a complexity reduction method proposed to make the existing algorithms more practical. Our objective is to Remove Redundancy while maintaining the maximum throughput. We formulate it as a Mixed Integer Non Linear Programming (MINLP) problem and propose a network coding based packet scheduling scheme that finds the optimal solution. Finally, the simulation results corroborate our method.
Zaida Lutheyschulten - One of the best experts on this subject based on the ideXlab platform.
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evolutionary profiles derived from the qr factorization of multiple structural alignments gives an economy of information
Journal of Molecular Biology, 2005Co-Authors: Patrick Odonoghue, Zaida LutheyschultenAbstract:We present a new algorithm, based on the multidimensional QR factorization, to Remove Redundancy from a multiple structural alignment by choosing representative protein structures that best preserve the phylogenetic tree topology of the homologous group. The classical QR factorization with pivoting, developed as a fast numerical solution to eigenvalue and linear least-squares problems of the form A x = b , was designed to re-order the columns of A by increasing linear dependence. Removing the most linear dependent columns from A leads to the formation of a minimal basis set which well spans the phase space of the problem at hand. By recasting the problem of Redundancy in multiple structural alignments into this framework, in which the matrix A now describes the multiple alignment, we adapted the QR factorization to produce a minimal basis set of protein structures which best spans the evolutionary (phase) space. The non-redundant and representative profiles obtained from this procedure, termed evolutionary profiles, are shown in initial results to outperform well-tested profiles in homology detection searches over a large sequence database. A measure of structural similarity between homologous proteins, Q H , is presented. By properly accounting for the effect and presence of gaps, a phylogenetic tree computed using this metric is shown to be congruent with the maximum-likelihood sequence-based phylogeny. The results indicate that evolutionary information is indeed recoverable from the comparative analysis of protein structure alone. Applications of the QR ordering and this structural similarity metric to analyze the evolution of structure among key, universally distributed proteins involved in translation, and to the selection of representatives from an ensemble of NMR structures are also discussed.