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This Special Issue "Differential Geometrical Theory of Statistics" collates selected invited and contributed talks presented during the conference GSI'15 on "Geometric Science of Information" which was held at the Ecole Polytechnique, Paris-Saclay Campus, France, in October 2015 (Conference web site: http://www.see.asso.fr/gsi2015).
Entropy --- Coding Theory --- Maximum entropy --- Information geometry --- Computational Information Geometry --- Hessian Geometry --- Divergence Geometry --- Information topology --- Cohomology --- Shape Space --- Statistical physics --- Thermodynamics
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This Special Issue of the journal Entropy, titled “Information Geometry I”, contains a collection of 17 papers concerning the foundations and applications of information geometry. Based on a geometrical interpretation of probability, information geometry has become a rich mathematical field employing the methods of differential geometry. It has numerous applications to data science, physics, and neuroscience. Presenting original research, yet written in an accessible, tutorial style, this collection of papers will be useful for scientists who are new to the field, while providing an excellent reference for the more experienced researcher. Several papers are written by authorities in the field, and topics cover the foundations of information geometry, as well as applications to statistics, Bayesian inference, machine learning, complex systems, physics, and neuroscience.
Markov random fields --- information theory --- Fisher information --- entropy --- maximum pseudo-likelihood estimation --- Bezout matrix --- Sylvester matrix --- tensor Sylvester matrix --- Stein equation --- Vandermonde matrix --- stationary process --- matrix resultant --- Fisher information matrix --- information geometry --- dually flat structure --- decomposable divergence --- (?,?)
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With their helical structure, cholesteric liquid crystals figure prominently in liquid crystal science. The selective reflection of light is their flagship property, and they offer a myriad of applications as advanced optical materials with multiscale properties. The cholesteric structure is also a ubiquitous design in the animal and plant kingdoms. This book contains eight contributions on fundamental investigations about defects, textures and structures of cholesteric materials, and experimental studies aimed at applications such as temperature sensors, head-up displays for improving automobile driving safety, or smart windows.
chirality --- cholesterics --- nanorods --- Onsager theory --- polydispersity --- liquid-crystalline dispersions of DNA --- cholesteric and hexagonal packing of DNA --- theoretically calculated and experimental circular dichroism spectra --- textures of the DNA liquid-crystalline phases --- “re-entrant” cholesteric phase of DNA --- anthracyclines drugs --- chelate complexes --- nanobridges --- “rigid” particles of DNA --- dielectric heating --- cholesteric liquid crystals --- uniform lying helix --- cholesteric liquid crystal --- two-length scale surface wrinkling --- capillary shape equation --- anisotropic surface energy --- liquid crystal --- cholesteric --- nematic --- conical boundary conditions --- orientational structure --- director configuration --- topological defect --- cholesteric liquid crystals --- polymer --- radical polymerization --- cationic polymerization --- electro-optical property --- microstructure --- geometry phase --- cholesteric liquid crystal --- head-up display --- liquid crystal --- cholesteric liquid crystals --- optical fiber --- side-polished fiber --- sensor
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Cryptography lies at the heart of most technologies deployed today for secure communications. At the same time, mathematics lies at the heart of cryptography, as cryptographic constructions are based on algebraic scenarios ruled by group or number theoretical laws. Understanding the involved algebraic structures is, thus, essential to design robust cryptographic schemes. This Special Issue is concerned with the interplay between group theory, symmetry and cryptography. The book highlights four exciting areas of research in which these fields intertwine: post-quantum cryptography, coding theory, computational group theory and symmetric cryptography. The articles presented demonstrate the relevance of rigorously analyzing the computational hardness of the mathematical problems used as a base for cryptographic constructions. For instance, decoding problems related to algebraic codes and rewriting problems in non-abelian groups are explored with cryptographic applications in mind. New results on the algebraic properties or symmetric cryptographic tools are also presented, moving ahead in the understanding of their security properties. In addition, post-quantum constructions for digital signatures and key exchange are explored in this Special Issue, exemplifying how (and how not) group theory may be used for developing robust cryptographic tools to withstand quantum attacks.
cryptography --- non-commutative cryptography --- one-way functions --- NP-Completeness --- key agreement protocol --- group theory --- symmetry --- Engel words --- alternating group --- WalnutDSA --- digital signatures --- post-quantum cryptography --- cryptanalysis --- braid groups --- algorithms in groups --- group-based cryptography --- Reed–Solomon codes --- key equation --- Berlekamp–Massey algorithm --- Sugiyama et al. algorithm --- euclidean algorithm --- numerical semigroup --- Weierstrass semigroup --- semigroup ideal --- error-correcting code --- algebraic-geometry code --- lightweight cryptography --- permutation group --- block cipher --- generalized self-shrinking generator --- t-modified self-shrinking generator --- pseudo-random number generator --- statistical randomness tests --- cryptography --- pseudorandom permutation --- block cipher --- ideal cipher model --- beyond birthday bound --- provable security --- group key establishment --- group theory --- provable security --- protocol compiler
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Currently, the use of computational fluid dynamics (CFD) solutions is considered as the state-of-the-art in the modeling of unsteady nonlinear flow physics and offers an early and improved understanding of air vehicle aerodynamics and stability and control characteristics. This Special Issue covers recent computational efforts on simulation of aerospace vehicles including fighter aircraft, rotorcraft, propeller driven vehicles, unmanned vehicle, projectiles, and air drop configurations. The complex flow physics of these configurations pose significant challenges in CFD modeling. Some of these challenges include prediction of vortical flows and shock waves, rapid maneuvering aircraft with fast moving control surfaces, and interactions between propellers and wing, fluid and structure, boundary layer and shock waves. Additional topic of interest in this Special Issue is the use of CFD tools in aircraft design and flight mechanics. The problem with these applications is the computational cost involved, particularly if this is viewed as a brute-force calculation of vehicle’s aerodynamics through its flight envelope. To make progress in routinely using of CFD in aircraft design, methods based on sampling, model updating and system identification should be considered.
wake --- bluff body --- square cylinder --- DDES --- URANS --- turbulence model --- large eddy simulation --- Taylor–Green vortex --- numerical dissipation --- modified equation analysis --- truncation error --- MUSCL --- dynamic Smagorinsky subgrid-scale model --- kinetic energy dissipation --- computational fluid dynamics (CFD) --- microfluidics --- numerical methods --- gasdynamics --- shock-channel --- microelectromechanical systems (MEMS) --- discontinuous Galerkin finite element method (DG–FEM) --- fluid mechanics --- characteristics-based scheme --- multi-directional --- Riemann solver --- Godunov method --- bifurcation --- wind tunnel --- neural networks --- modeling --- unsteady aerodynamic characteristics --- high angles of attack --- hypersonic --- wake --- chemistry --- slender-body --- angle of attack --- detection --- after-body --- S-duct diffuser --- flow distortion --- flow control --- vortex generators --- aeroelasticity --- reduced-order model --- flutter --- wind gust responses --- computational fluid dynamics --- convolution integral --- sharp-edge gust --- reduced order aerodynamic model --- geometry --- meshing --- aerodynamics --- CPACS --- MDO --- VLM --- Euler --- CFD --- variable fidelity --- multi-fidelity --- aerodynamic performance --- formation --- VLM --- RANS --- hybrid reduced-order model --- quasi-analytical --- aeroelasticity --- flexible wings --- subsonic --- wing–propeller aerodynamic interaction --- p-factor --- installed propeller --- overset grid approach
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The last few years have been characterized by a tremendous development of quantum information and probability and their applications, including quantum computing, quantum cryptography, and quantum random generators. In spite of the successful development of quantum technology, its foundational basis is still not concrete and contains a few sandy and shaky slices. Quantum random generators are one of the most promising outputs of the recent quantum information revolution. Therefore, it is very important to reconsider the foundational basis of this project, starting with the notion of irreducible quantum randomness. Quantum probabilities present a powerful tool to model uncertainty. Interpretations of quantum probability and foundational meaning of its basic tools, starting with the Born rule, are among the topics which will be covered by this issue. Recently, quantum probability has started to play an important role in a few areas of research outside quantum physics—in particular, quantum probabilistic treatment of problems of theory of decision making under uncertainty. Such studies are also among the topics of this issue.
quantum logic --- groups --- partially defined algebras --- quasigroups --- viable cultures --- quantum information theory --- bit commitment --- protocol --- entropy --- entanglement --- orthogonality --- quantum computation --- Gram–Schmidt process --- quantum probability --- potentiality --- complementarity --- uncertainty relations --- Copenhagen interpretation --- indefiniteness --- indeterminism --- causation --- randomness --- quantum information --- quantum dynamics --- entanglement --- algebra --- causality --- geometry --- probability --- quantum information theory --- realism --- reality --- entropy --- correlations --- qubits --- probability representation --- Bayes’ formula --- quantum entanglement --- three-qubit random states --- entanglement classes --- entanglement polytope --- anisotropic invariants --- quantum random number --- vacuum state --- maximization of quantum conditional min-entropy --- quantum logics --- quantum probability --- holistic semantics --- epistemic operations --- Bell inequalities --- algorithmic complexity --- Borel normality --- Bayesian inference --- model selection --- random numbers --- quantum-like models --- operational approach --- information interpretation of quantum theory --- social laser --- social energy --- quantum information field --- social atom --- Bose–Einstein statistics --- bandwagon effect --- social thermodynamics --- resonator of social laser --- master equation for socio-information excitations --- quantum contextuality --- Kochen–Specker sets --- MMP hypergraphs --- Greechie diagrams --- quantum foundations --- probability --- irreducible randomness --- random number generators --- quantum technology --- entanglement --- quantum-like models for social stochasticity --- contextuality
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The Special Issue (SI) “Recent Advances in GPR Imaging” offers an up-to-date overview of state-of-the-art research activities dealing with the development of Ground Penetrating Radar (GPR) technology and its recent advances in imaging in the different fields of application. In fact, the advances experimented with over the last few decades with regard to the appearance of new GPR systems and the need to manage large amounts of data suggest an increasing interest in the development of new signal processing algorithms and modeling, as well as in the use of three-dimensional (3D) imaging techniques.
doline --- karst --- land cultivation --- morphometrical analysis --- distributive analysis --- conglomerate --- LiDAR --- digital elevation model (DEM) --- ground penetrating radar (GPR) --- Kranjsko polje --- ground penetrating radar --- electrical resistivity imaging --- quarry --- marble --- ground penetrating radar --- electromagnetic propagation in nonhomogeneous media --- time-domain analysis --- GPR --- clutter --- backscattering --- scattering modelling --- ground-penetrating radar --- terrestrial laser scanning --- infrared thermography --- archaeology --- 3D visualization --- toGPRi --- variational mode decomposition --- empirical mode decomposition --- IMF-slices --- GPR data processing --- GPR imaging --- time-frequency analysis --- ground penetrating radar --- non-destructive testing --- near-surface geophysics --- test site --- Ground Penetrating Radar --- railways --- signal frequency analysis --- track geometry --- railway events --- spectral domain --- network level evaluation --- ground penetrating radar (GPR) --- X-ray diffraction (XRD) --- X-ray fluorescence (XRF) --- karst --- cave sediments --- unroofed caves --- n/a
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The Internet of Things (IoT) has attracted much attention from society, industry and academia as a promising technology that can enhance day to day activities, and the creation of new business models, products and services, and serve as a broad source of research topics and ideas. A future digital society is envisioned, composed of numerous wireless connected sensors and devices. Driven by huge demand, the massive IoT (mIoT) or massive machine type communication (mMTC) has been identified as one of the three main communication scenarios for 5G. In addition to connectivity, computing and storage and data management are also long-standing issues for low-cost devices and sensors. The book is a collection of outstanding technical research and industrial papers covering new research results, with a wide range of features within the 5G-and-beyond framework. It provides a range of discussions of the major research challenges and achievements within this topic.
narrowband --- IoT --- PHY --- NB-IoT --- MAC --- deployment --- survey --- mMTC --- 5G --- grant-free --- scheduling --- URLLC --- ultra-reliable and low-latency communications --- 5G --- deterministic --- time-critical --- reliability --- latency --- aperiodic traffic --- Industry 4.0 --- 5G --- mMTC --- IoT --- CSMA --- SINR --- throughput --- polynomial interpolation --- 5G --- liquid detection --- radio propagation --- dielectric constant --- WCI --- congestion --- estimation --- irregular repetition slotted ALOHA --- medium access control --- random access --- successive interference cancellation --- 5G --- internet of things --- mMTC --- eMBB --- stochastic geometry --- resource allocation --- Internet of Things --- Industry 4.0 --- Internet of Things --- Industrial Internet of Things --- Cyber Physical System --- cloud computing --- fog computing --- edge computing --- smart devices --- smart factory --- industrial automation --- M2M --- heterogeneous networks --- non-orthogonal multiple access --- energy efficiency --- MU association --- power control --- D2D communication --- 5G --- sensor network --- sensor --- end-to-end delay --- USRP --- distributed mechanism --- Raspberry Pi
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This book presents new and original research in Statistical Information Theory, based on minimum divergence estimators and test statistics, from a theoretical and applied point of view, for different statistical problems with special emphasis on efficiency and robustness. Divergence statistics, based on maximum likelihood estimators, as well as Wald’s statistics, likelihood ratio statistics and Rao’s score statistics, share several optimum asymptotic properties, but are highly non-robust in cases of model misspecification under the presence of outlying observations. It is well-known that a small deviation from the underlying assumptions on the model can have drastic effect on the performance of these classical tests. Specifically, this book presents a robust version of the classical Wald statistical test, for testing simple and composite null hypotheses for general parametric models, based on minimum divergence estimators.
sparse --- robust --- divergence --- MM algorithm --- Bregman divergence --- generalized linear model --- local-polynomial regression --- model check --- nonparametric test --- quasi-likelihood --- semiparametric model --- Wald statistic --- composite likelihood --- maximum composite likelihood estimator --- Wald test statistic --- composite minimum density power divergence estimator --- Wald-type test statistics --- Bregman divergence --- general linear model --- hypothesis testing --- influence function --- robust --- Wald-type test --- log-linear models --- ordinal classification variables --- association models --- correlation models --- minimum penalized ?-divergence estimator --- consistency --- asymptotic normality --- goodness-of-fit --- bootstrap distribution estimator --- thematic quality assessment --- relative entropy --- logarithmic super divergence --- robustness --- minimum divergence inference --- generalized renyi entropy --- minimum divergence methods --- robustness --- single index model --- model assessment --- statistical distance --- non-quadratic distance --- total variation --- mixture index of fit --- Kullback-Leibler distance --- divergence measure --- ?-divergence --- relative error estimation --- robust estimation --- information geometry --- centroid --- Bregman information --- Hölder divergence --- indoor localization --- robustness --- efficiency --- Bayesian nonparametric --- Bayesian semi-parametric --- asymptotic property --- minimum disparity methods --- Hellinger distance --- Berstein von Mises theorem --- measurement errors --- robust testing --- two-sample test --- misspecified hypothesis and alternative --- 2-alternating capacities --- composite hypotheses --- corrupted data --- least-favorable hypotheses --- Neyman Pearson test --- divergence based testing --- Chernoff Stein lemma --- compressed data --- Hellinger distance --- representation formula --- iterated limits --- influence function --- consistency --- asymptotic normality --- location-scale family --- n/a
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Geomorphometry is the science of quantitative terrain characterization and analysis, and has traditionally focused on the investigation of terrestrial and planetary landscapes. However, applications of marine geomorphometry have now moved beyond the simple adoption of techniques developed for terrestrial studies, driven by the rise in the acquisition of high-resolution seafloor data and by the availability of user-friendly spatial analytical tools. Considering that the seafloor represents 71% of the surface of our planet, this is an important step towards understanding the Earth in its entirety.This volume is the first one dedicated to marine applications of geomorphometry. It showcases studies addressing the five steps of geomorphometry: sampling a surface (e.g., the seafloor), generating a Digital Terrain Model (DTM) from samples, preprocessing the DTM for subsequent analyses (e.g., correcting for errors and artifacts), deriving terrain attributes and/or extracting terrain features from the DTM, and using and explaining those terrain attributes and features in a given context. Throughout these studies, authors address a range of challenges and issues associated with applying geomorphometric techniques to the complex marine environment, including issues related to spatial scale, data quality, and linking seafloor topography with physical, geological, biological, and ecological processes. As marine geomorphometry becomes increasingly recognized as a sub-discipline of geomorphometry, this volume brings together a collection of research articles that reflect the types of studies that are helping to chart the course for the future of marine geomorphometry.
bedforms --- forage fish --- Pacific sand lance --- sediment habitats --- bathymetry --- currents --- seabed mapping --- marine geology --- submarine topography --- marine geomorphology --- terrain analysis --- multibeam echosounder --- bathymetry --- DEM --- satellite imagery --- multi beam echosounder --- filter --- geomorphology --- coral reefs --- Acoustic applications --- object segmentation --- seafloor --- underwater acoustics --- Cretaceous --- Cenomanian–Turonian --- paleobathymetry --- paleoclimate --- paleoceanography --- reconstruction --- simulation --- shelf-slope-rise --- geomorphometry --- GIS --- spatial scale --- spatial analysis --- terrain analysis --- seafloor geomorphometry --- domes --- volcanoes --- digital elevation models (DEMs) --- Canary Basin --- Atlantic Ocean --- cold-water coral --- carbonate mound --- habitat mapping --- spatial prediction --- image segmentation --- geographic object-based image analysis --- random forest --- accuracy --- confidence --- global bathymetry --- Seabed 2030 --- Nippon Foundation/GEBCO --- seafloor mapping technologies --- seafloor mapping standards and protocols --- benthic habitats --- shelf morphology --- eastern Brazilian shelf --- geomorphometry --- terrain analysis --- bathymetry --- surface roughness --- benthic habitat mapping --- python --- geomorphology --- submerged glacial bedforms --- deglaciation --- sedimentation --- multibeam --- acoustic-seismic profiling --- swath geometry --- multibeam spatial resolution --- integration artefacts --- Multibeam bathymetry --- benthic habitat mapping --- multiscale --- Random Forests --- pockmarks --- automated-mapping --- ArcGIS --- Glaciated Margin --- North Sea --- Malin Basin --- Barents Sea --- bathymetry --- thalwegs --- canyons --- Alaska --- Bering Sea --- multibeam sonar --- carbonate banks --- semi-automated mapping --- polychaete --- Northwestern Australia --- Oceanic Shoals Australian Marine Park --- Bonaparte Basin --- Timor Sea --- bathymetry --- digital terrain analysis --- geomorphometry --- geomorphology --- habitat mapping --- marine remote sensing
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