Mobile mapping is applied widely in society, for example, in asset management, fleet management, construction planning, road safety, and maintenance optimization. Yet, further advances in these ...technologies are called for. Advances can be radical, such as changes to the prevailing paradigms in mobile mapping, or incremental, such as the state-of-the-art mobile mapping methods. With current multi-sensor systems in mobile mapping, laser-scanned data are often registered in point clouds with the aid of global navigation satellite system (GNSS) positioning or simultaneous localization and mapping (SLAM) techniques and then labeled and colored with the aid of machine learning methods and digital camera data. These multi-sensor platforms are beginning to undergo further advancements via the addition of multi-spectral and other sensors and via the development of machine learning techniques used in processing this multi-modal data. Embedded systems and minimalistic system designs are also attracting attention, from both academic and commercial perspectives.This book contains the accepted publications of the Special Issue 'Advances in Mobile Mapping Technologies' of the Remote Sensing journal. It consists of works introducing a new mobile mapping dataset (‘Paris CARLA 3D’), system calibration studies, SLAM topics, and multiple deep learning works for asset detection. We, the Guest Editors, Ville Lehtola from University of Twente, Netherlands, Andreas Nüchter from University of Würzburg, Germany, and François Goulette from Mines Paris- PSL University, France, wish to thank all the authors who contributed to this collection.
The Leidenfrost effect, namely the levitation of drops on hot solids
, is known to deteriorate heat transfer at high temperature
. The Leidenfrost point can be elevated by texturing materials to ...favour the solid-liquid contact
and by arranging channels at the surface to decouple the wetting phenomena from the vapour dynamics
. However, maximizing both the Leidenfrost point and thermal cooling across a wide range of temperatures can be mutually exclusive
. Here we report a rational design of structured thermal armours that inhibit the Leidenfrost effect up to 1,150 °C, that is, 600 °C more than previously attained, yet preserving heat transfer. Our design consists of steel pillars serving as thermal bridges, an embedded insulating membrane that wicks and spreads the liquid and U-shaped channels for vapour evacuation. The coexistence of materials with contrasting thermal and geometrical properties cooperatively transforms normally uniform temperatures into non-uniform ones, generates lateral wicking at all temperatures and enhances thermal cooling. Structured thermal armours are limited only by their melting point, rather than by a failure in the design. The material can be made flexible, and thus attached to substrates otherwise challenging to structure. Our strategy holds the potential to enable the implementation of efficient water cooling at ultra-high solid temperatures, which is, to date, an uncharted property.
Interpolation by polynomials on equispaced points is not always convergent due to the Runge phenomenon, and also, the interpolation process is exponentially ill-conditioned. By taking advantage of ...the optimality of the interpolation processes on the Chebyshev-Lobatto nodes, one of the best strategies to defeat the Runge phenomenon is to use the mock-Chebyshev nodes for polynomial interpolation. Mock-Chebyshev nodes asymptotically follow the Chebyshev distribution, and they are selected from a sufficiently large set of equispaced nodes. However, there are few studies in the literature regarding the computation of these points.
In a recent paper 1, we have introduced a fast algorithm for computing the mock-Chebyshev nodes for a given set of (n+1) Chebyshev-Lobatto points using the distance between each pair of consecutive points. In this study, we propose a modification of the algorithm by changing the function to compute the quotient of the distance and show that this modified algorithm is also fast and stable; and gives a more accurate grid satisfying the conditions of a mock-Chebyshev grid with the complexity being O(n). Some numerical experiments using the points obtained by this modified algorithm are given to show its effectiveness and numerical results are also provided. A bivariate generalization of the mock-Chebyshev nodes to the Padua interpolation points is discussed.
A giant electrocaloric effect (ECE) near room temperature is reported in a lead‐free bulk inorganic material. By tuning Ba(ZrxTi1–x)O3 compositions which also exhibit relaxor ferroelectric response ...to near the invariant critical point, the Ba(ZrxTi1–x)O3 bulk ceramics at x ∼ 0.2 exhibit a large adiabatic temperature drop of 4.5 K, a large isothermal entropy change of 8 J kg−1 K−1, and a large EC coefficient (|ΔTc/ΔE| = 0.52 × 10−6 KmV−1 and ΔS/ΔE = 0.93 × 10−6 J m kg−1 K−1 V−1) over a 30 K temperature range. These properties added together indicate a general solution of the electrocaloric materials with high performance for practical cooling applications.
A giant electrocaloric effect (ECE), i.e., a large adiabatic temperature drop (ΔTc) with a high electrocaloric coefficient (ΔTc/ΔE), is demonstrated in a modified lead‐free ferroelectric ceramic, BaTiO3, over a broad temperature range near the invariant critical point (ICP). Multiphase coexistence near ICP provides a larger entropy change compared with that of a pure ferroelectric–paraelectric transition. When coupled with the relaxor behavior, this leads to the observed giant ECE in BZT (x = 0.2) over a broad temperature range
Any triangle in an isotropic plane has a circumcircle u and incircle i. It turns out that there are infinitely many triangles with the same circumcircle u and incircle i. This one-parameter family of ...triangles is called a poristic system of triangles. We study the trace of the centroid, the Feuerbach point, the symmedian point, the Gergonne point, the Steiner point and the Brocard points for such a system of triangles. We also study the traces of some further points associated with the triangles of the poristic family, and we prove that the vertices of the contact triangle, tangential triangle and anticomplementary triangle move on circles while the initial triangle traverses the poristic family.
A core idea in the context of mechanochemistry is that applying an external tensile force along a reaction coordinate should enhance the chemical reaction of interest. Here, we analyze perturbed ...generic molecular structures: schematic models of triatomics, ABC, and tetraatomics, AABB. They are used to demonstrate that pulling does usually not use the “reaction coordinate,” but opens new reaction pathways. Within development of these models we use the concept of Newton trajectories for a theory of mechanochemistry. However, we find cases where the theory of Newton trajectories is not applicable. For all cases, we define the curve of force‐displaced stationary points, and we discuss the importance of barrier breakdown points and valley‐ridge inflection points. The examples use Morse potentials for bonds and simple angle functions and are demonstrated by assumed real values for the potential parameters. On the basis of the systematic study of some generic models we explain a set of already observed experimental mechanochemical phenomena in specific molecular systems and we apply the results to the strength of chemical bonds.
A core idea in the context of mechanochemistry is that applying an external tensile force along a reaction coordinate should enhance the chemical reaction of interest. Triatomic models are used to demonstrate that pulling does usually not use the “reaction coordinate,” but instead opens completely new reaction pathways. The concept of Newton trajectories is used to develop a theory of mechanochemistry.
Vegetation is crucial for sustainable and resilient cities providing various ecosystem services and well-being of humans. However, vegetation is under critical stress with rapid urbanization and ...expanding infrastructure footprints. Consequently, mapping of this vegetation is essential in the urban environment. Recently, deep learning (DL) for point cloud semantic segmentation has shown significant progress. Advanced models attempt to obtain state-of-the-art performance on benchmark datasets, comprising multiple classes and representing real-world scenarios. However, class-specific segmentation with respect to vegetation points has not been explored. Therefore, selection of a DL model for vegetation points segmentation is ambiguous. To address this problem, we provide a comprehensive assessment of point-based DL models for semantic segmentation of vegetation class. We have selected seven representative-point-based models, namely, PointCNN, KPConv (omni-supervised), RandLANet, SCFNet, PointNeXt, SPoTr, and PointMetaBase. These models are investigated on three different datasets, specifically Chandigarh, Toronto3D, and Kerala, which are characterized by diverse nature of vegetation and varying scene complexity combined with changing per-point features and classwise composition. PointMetaBase and KPConv (omni-supervised) achieve the highest mIoU on the Chandigarh (95.24%) and Toronto3D datasets (91.26%), respectively while PointCNN provides the highest mIoU on the Kerala dataset (85.68%). The article develops a deeper insight, hitherto not reported, into the working of these models for vegetation segmentation and outlines the ingredients that should be included in a model specifically for vegetation segmentation. This article is a step toward the development of a novel architecture for vegetation points segmentation.
The aim of this paper is to present a generalization of Nadler's fixed point principle for the case of multi-valued graph contractions. Also, a strict fixed point theorem is obtained. Connections to ...some variational analysis concepts are discussed and applications to generalized coupled fixed point problems are given.
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