Box renormalization as a 'black box'

keywords:
Box mapping
puzzle map
renormalization
rigidity
local connectivity

uk: Математика, природничі науки

description: The concept of a complex box mapping (or puzzle mapping) is a generalization of the classical notion of polynomial-like map to the case when one allows for countably many components in the domain and finitely many components in the range of the mapping. In one-dimensional dynamics, box mappings appear naturally as first return maps to certain nice sets, and hence one arrives at a notion of box renormalization. We say that a rational map is box renormalizable if the first return map to a well-chosen neighborhood of the set of critical points (intersecting the Julia set) has a structure of a box mapping. In our talk, we will discuss various features of general box mappings, as well as so-called dynamically natural box mappings, focusing on their rigidity properties. We will then show how these results can be used almost as 'black boxes' to conclude similar rigidity properties for box renormalizable rational maps. We will give several examples to illustrate this procedure, these examples include, most prominently, complex polynomials of arbitrary degree and their Newton maps. (The talk is based on joint work with Trevor Clark, Oleg Kozlovski, Dierk Schleicher and Sebastian van Strien.)

uk: вхід без авторизації


Story of the Feigenbaum point

Mikhail Lyubich

type: Person

cs: Matematika

de: Mathematik

fi: matematiikka

uk: Математика

en: Mathematics

fr: Mathématiques

da: Matematik

es: Matemáticas

nl: Wiskunde

de: Mathematik, Naturwissenschaften

uk: Математика, природничі науки

en: Mathematics, Natural Sciences

description: The Feigenbaum point is a remarkable parameter in the quadratic family focusing some of the deepest phenomena of non-linear dynamics (regular vs chaotic behavior, rigidity and MLC, universal self-similarity and renormalization). A theory of this point has been under construction for about 45 years. I will outline this story, completing it with one missing piece, MLC at this point (based on a joint work with Dima Dudko).

TIB AV-Portal

type: Service

type: WebContent

type: MediaObject

@language: en

cs: přihlášení není vyžadováno

de: keine Anmeldung erforderlich

uk: вхід без авторизації

en: no login required

nl: geen login vereist

name: Centre International de Rencontres Mathématiques (CIRM)

addressCountry: FR

addressLocality: Marseille

addressRegion: Provence-Alpes-Côte d'Azur

type: Organization

cs: Video

de: Video

fi: Video

uk: Відео

en: Video

fr: Vidéo

da: Video

nl: Video

es: Video


keywords:
combination theorems
rational dynamics
reflection groups
Fuchsian groups
univalent maps
Schwarz reflection maps
univalent maps
Welding homeomorphisms
conformal removality
orbit equivalence

uk: Математика, природничі науки

description: Combination theorems play an important role in several areas of dynamics, geometry, and group theory. In this talk, we will expound a framework to conformally combine Kleinian (reflection) groups and (anti-)holomorphic rational maps in a single dynamical plane. In the anti-holomorphic setting, such hybrid dynamical systems are generated by Schwarz reflection maps arising from univalent rational maps. A crucial technical ingredient of this study is a recently developed David surgery technique that turns hyperbolic conformal dynamical systems to parabolic ones. We will also mention numerous consequences of this theory, including 1. an explicit dynamical connection between various rational Julia and Kleinian limit sets,2. existence of new classes of welding homeomorphisms and conformally removable Julia/limit sets, and3. failure of topological orbit equivalence rigidity for Fuchsian groups acting on the circle.

uk: вхід без авторизації

name: Interbreeding in conformal dynamics, and its applications near and far


keywords:
rational dynamics
Julia sets
invariant graphs
Thurston maps
obstructions
decomposition theory

uk: Математика, природничі науки

description: There are various classical and more recent decomposition results in mapping class group theory, geometric group theory, and complex dynamics (which include celebrated results by Bill Thurston). We will discuss several natural decompositions that arise in the study of rational maps, such as Pilgrim's canonical decomposition and Levy decomposition (by Bartholdi and Dudko). I will also introduce a new decomposition of rational maps based on the topology of their Julia sets (obtained jointly with Dima Dudko and Dierk Schleicher). At the end of the talk, we will briefly consider connections of this novel decomposition to geometric group theory and self-similar groups.

uk: вхід без авторизації

name: Decomposition results in rational dynamics


keywords:
Holomorphic dynamics
transcendental dynamics
transversality
quadratic differentials

uk: Математика, природничі науки

uk: вхід без авторизації

name: Tips of tongues in the double standard family


A combinatorial Thurston theory

keywords:
Thurston theory
topological polynomials
branched covers
mapping class groups

uk: Математика, природничі науки

description: Thurston proved that a post-critically finite branched cover of the plane is either equivalent to a polynomial (that is: conjugate via a mapping class) or it has a topological obstruction. We use topological techniques — adapting tools used tostudy mapping class groups — to produce an algorithm that determines when a branched cover is equivalent to a polynomial, and if it is, determines which polynomial a branched cover is equivalent to. This is joint work with Jim Belk, Justin Lanier, and Dan Margalit.

uk: вхід без авторизації


keywords:
transcendental dynamical systems
Thurston theory
quadratic differentials
Teichmüller space

uk: Математика, природничі науки

description: Thurston's topological characterization theory asks whether there is a holomorphic dynamical system that realizes topological (even combinatorial) data, this often allows to describe all possible dynamical systems in a certain parameter space. I work on extending Thurston topological characterization theory to different classes of transcendental functions. In my talk I will start with some explicit families of functions for which we have established an extension of Thurston's theory, and then describe further extensions by compositions of such functions. The presented ideas are part of my PhD thesis under the supervision of Dierk Schleicher. This is work in progress.

uk: вхід без авторизації

name: Transcendental Thurston Theory for entire functions and compositions


TIB AV-Portal - Tutorial (2022)

cs: Informatika

de: Informatik

fi: tietojenkäsittelytiede

uk: Комп'ютерні науки

en: Computer Science

fr: Informatique

da: Datalogi

es: Ciencias de la Computación

nl: Informatica

uk: Бібліотекознавство, документознавство

en: Information and Library Sciences

de: Geisteswissenschaften

uk: Гуманітарні науки

en: Humanities

cs: Technické vědy

de: Ingenieurwissenschaften

fi: tekniikka

uk: Інженерія

en: Engineering Sciences

fr: Ingénierie

da: Ingeniørvidenskab

es: Ingeniería

nl: Engineering

@language: de

uk: вхід без авторизації

Technische Informationsbibliothek (TIB)

addressCountry: DE

addressLocality: Hanover

addressRegion: Lower Saxony


uk: Математика, природничі науки

uk: вхід без авторизації

name: The Portable Extensible Toolkit for Scientific Computing


uk: Математика, природничі науки

uk: вхід без авторизації

name: Krylov subspace solvers and preconditioners


uk: Математика, природничі науки

uk: вхід без авторизації

name: Domain decomposition, hybrid methods, coarse space corrections


uk: Математика, природничі науки

uk: вхід без авторизації

name: A gentle introduction to parallel programming using OpenMP


OpenCL introduction

uk: Математика, природничі науки

uk: вхід без авторизації


uk: Математика, природничі науки

uk: вхід без авторизації

name: Algorithms for future emerging technologies


uk: Математика, природничі науки

uk: вхід без авторизації

name: Overview of architectures and programming language for parallel computing


Tutorial with Freefem++

uk: Математика, природничі науки

uk: вхід без авторизації


uk: Математика, природничі науки

uk: вхід без авторизації

name: Reduced basis methods: approximation of PDE's, interpolation and a posteriori estimate


uk: Математика, природничі науки

uk: вхід без авторизації

name: Introduction to data assimilation: Kalman filters and ensembles


uk: Математика, природничі науки

uk: вхід без авторизації

name: Data assimilation training course @ CEMRACS: introduction and variational algorithms


Linear solvers for reservoir simulation

uk: Математика, природничі науки

description: In this presentation, we will first present the main goals and principles of reservoir simulation. Then we will focus on linear systems that arise in such simulation. The main HPC challenge is to solve those systems efficiently on massively parallel computers. The specificity of those systems is that their convergence is mostly governed by the elliptic part of the equations and the linear solver needs to take advantage of it to be efficient. The reference method in reservoir simulation is CPR-AMG which usually relies on AMG to solve the quasi elliptic part of the system. We will present some works on improving AMG scalability for the reservoir linear systems (work done in collaboration with CERFACS). We will then introduce an on-going work with INRIA to take advantage of their enlarged Krylov method (EGMRES) in the CPR method.

uk: вхід без авторизації


uk: Математика, природничі науки

description: I will review (some of) the HPC solution strategies developed in Feel++. We present our advances in developing a language specific to partial differential equations embedded in C++. We have been developing the Feel++ framework (Finite Element method Embedded Language in C++) to the point where it allows to use a very wide range of Galerkin methods and advanced numerical methods such as domain decomposition methods including mortar and three fields methods, fictitious domain methods or certified reduced basis. We shall present an overview of the various ingredients as well as some illustrations. The ingredients include a very expressive embedded language, seamless interpolation, mesh adaption, seamless parallelisation. As to the illustrations, they exercise the versatility of the framework either by allowing the development and/or numerical verification of (new) mathematical methods or the development of large multi-physics applications - e.g. fluid-structure interaction using either an Arbitrary Lagrangian Eulerian formulation or a levelset based one; high field magnets modeling which involves electro-thermal, magnetostatics, mechanical and thermo-hydraulics model; ... - The range of users span from mechanical engineers in industry, physicists in complex fluids, computer scientists in biomedical applications to applied mathematicians thanks to the shared common mathematical embedded language hiding linear algebra and computer science complexities.

uk: вхід без авторизації

name: High performance computing with Feel++: applications and numerical methods


uk: Математика, природничі науки

description: Facing energy future is one of the large challenges of the world, with numerous implications for R&D strategy of energy companies. One of the Total R&D missions is the development of competences on advanced technologies, such as Advanced Computing (HPC), Material sciences, Biotechnologies, Nanotechnologies, New analytical techniques, IT Technologies. HPC allows also tackling the challenge in code coupling: both a horizontal direction -multi-physics-, (chemistry and transport, or structural mechanics, acoustics, fluid dynamics, and thermal heat transfer, ...) and in the vertical direction -multi-scale models- (i.e. from continuum to mesoscale to molecular dynamics to quantum chemistry) which requires bridging space and time scales that span many orders of magnitude. This leads to improve at the same time more accurate physical model and numerical methods and algorithms and these improvements of numerical simulations will be illustrated by their application, use and impact in Total strategic activities such as: seismic, depth imaging by solving waves equation; oil reservoir modeling by solving transport, thermal and chemical equations; multi scale process modeling and control, such as slurry loop process; mechanical structures and geomecanics.

uk: вхід без авторизації

name: Multiple applications of HPC and Numerical Simulations in Total Group


uk: Математика, природничі науки

description: In domain decomposition methods, most of the computational cost lies in the successive solutions of the local problems in subdomains via forward-backward substitutions and in the orthogonalization of interface search directions. All these operations are performed, in the best case, via BLAS-1 or BLAS-2 routines which are inefficient on multicore systems with hierarchical memory. A way to improve the parallel efficiency of the method consists in working with several search directions, since multiple forward-backward substitutions and reorthogonalizations involve BLAS-3 routines. In the case of a problem with several right-hand-sides, using a block Krylov method is a straightforward way to work with multiple search directions. This will be illustrated with an application in electromagnetism using FETI-2LM method. For problems with a single right-hand-side, deriving several search directions that make sense from the optimal one constructed by the Krylov method is not so easy. The recently developed S-FETI method gives a very good approach that does not only improve parallel efficiency but can also reduce the global computational cost in the case of very heterogeneous problems.

uk: вхід без авторизації

name: Efficient iterative solvers: FETI methods with multiple search directions


uk: Математика, природничі науки

description: We review how to bound the error between the unknown weak solution of a PDE and its numerical approximation via a fully computable a posteriori estimate. We focus on approximations obtained at an arbitrary step of a linearization (Newton-Raphson, fixed point, ...) and algebraic solver (conjugate gradients, multigrid, domain decomposition, ...). Identifying the discretization, linearization, and algebraic error components, we design local stopping criteria which keep them in balance. This gives rise to a fully adaptive inexact Newton method. Numerical experiments are presented in confirmation of the theory.

uk: вхід без авторизації

name: A posteriori error estimates and solver adaptivity in numerical simulations

name: Centre International de Rencontres Mathématiques (CIRM)


uk: Математика, природничі науки

description: We review Optimized Schwarz waveform relaxation methods which are space-time domain decomposition methods. The main ideas are explained on the heat equation, and extension to advection-diffusion equations are illustrated by numerical results. We present the Schwarz for TrioCFD project, which aims at using this kind of methods for the Stokes equations.

uk: вхід без авторизації

name: Optimized Schwarz waveform relaxation methods: theory and applications


uk: Математика, природничі науки

description: Parametrized PDE (Partial Differential Equation) Apps are PDE solvers which satisfy stringent per-query performance requirements: less-than or approximate 5-second problem specification time; less-than or approximate 5-second problem solution time, field and outputs; less-than or approximate 5% solution error, specified metrics; less-than or approximate 5-second solution visualization time. Parametrized PDE apps are relevant in many-query, real-time, and interactive contexts such as design, parameter estimation, monitoring, and education. In this talk we describe and demonstrate a PDE App computational methodology. The numerical approach comprises three ingredients: component => system synthesis, formulated as a static-condensation procedure; model order reduction, informed by evanescence arguments at component interfaces (port reduction) and low-dimensional parametric manifolds in component interiors (reduced basis techniques); and parallel computation, implemented in a cloud environment. We provide examples in acoustics and also linear elasticity.

uk: вхід без авторизації

name: Parametrized model order reduction for component-to-system synthesis


uk: Математика, природничі науки

description: A front data assimilation system named FIREFLY has been developed at CERFACS in collaboration with the University of Maryland to better estimate the environmental conditions (biomass properties, near-surface wind). We discuss the sequential application of the ensemble Kalman filter (EnKF) in FIREFLY for correcting in a spatially-distributed way, input parameters in order to better track the fire front position. In particular, using a polynomial chaos surrogate to mimic the wildfire spread model in the EnKF algorithm was found in collaboration with LIMSI to be a promising strategy to reduce the computational cost of FIREFLY. We also discuss the way we represent the distance between simulated and observed fronts. In the CEMRACS project, a new discrepancy operator will be introduced to better represent the match (or mismatch) between simulated fronts and mid-infrared observations in collaboration with INRIA. This front level-set data assimilation derived from image processing and designed for electrophysiology will be extended to wildfire spread monitoring.

uk: вхід без авторизації

name: Data-driven wildfire behavior modelling: focus on front level-set data assimilation


uk: Математика, природничі науки

uk: вхід без авторизації

name: A discussion about the impact of scalability constraint on the design of futur dynamical kernels of NWP models


uk: Математика, природничі науки

description: In this talk we overview some of the challenges of cardiac modeling and simulation of the electrical depolarization of the heart. In particular, we will present a strategy allowing to avoid the 3D simulation of the thin atria depolarization but only solve an asymptotic consistent model on the mid-surface. In a second part, we present a strategy for estimating a cardiac electrophysiology model from front data measurements using sequential parallel data assimilation strategy.

uk: вхід без авторизації

name: Modeling and data assimilation in cardiac electrophysiology


uk: Математика, природничі науки

description: Climate models simulate atmospheric flows interacting with many physical processes. Because they address long time scales, from centuries to millennia, they need to be efficient, but not at the expense of certain desirable properties, especially conservation of total mass and energy. Most of my talk will explain the design principles behind DYNAMICO, a highly scalable unstructured-mesh energy-conserving finite volume/mimetic finite difference atmospheric flow solver and potential successor of LMD-Z, a structured-mesh (longitude-latitude) solver currently operational as part of IPSL-CM, the Earth System Model developed by Institut Pierre Simon Laplace (IPSL). Specifically, the design exploits the variational structure of the equations of motion and their Hamiltonian formulation, so that the conservation of energy requires only that the discrete grad and div operators be compatible, i.e. that a discrete integration by parts formula holds. I will finish my talk by sketching how the desirable properties of DYNAMICO may be obtained with a different approach based on mixed finite elements (FEM). Indeed while DYNAMICO is very fast and scalable, it is low-order and higher-order accuracy may be desirable. While FEM methods can provide higher-order accuracy, they are computationally more expensive. They offer a viable path only if the performance gap compared to finite differences is not too large. The aim of the CEMRACS project A-HA is to evaluate how wide this gap may be, and whether it can be narrowed by using a recently proposed duality-based approach to assemble the various matrices involved in a FEM method.

uk: вхід без авторизації

name: High performance climate modelling: mimetic finite differences, and beyond?


uk: Математика, природничі науки

description: The heart undergoes some highly complex multi-scale multi-physics phenomena that must be accounted for in order to adequately model the biomechanical behavior of the complete organ. In this respect, a major focus of our work has been on formulating modeling ingredients that satisfy the most crucial thermomechanical requirements - in particular as regards energy balances - throughout the various forms of physical and scale-related couplings. This has led to a "beating heart" model for which some experimental and clinical validations have already been obtained. Concurrently, with the objective of building "patient-specific" heart models, we have investigated some original approaches inspired from data assimilation concepts to benefit from the available clinical data, with a particular concern for medical imaging. By combining the two fundamental sources of information represented by the model and the data, we are able to extract some most valuable quantitative knowledge on a given heart, e.g. as regards some uncertain constitutive parameter values characterizing a possible pathology, with important perspectives in diagnosis assistance. In addition, once the overall uncertainty has been adequately controlled via this adjustment process, the model can be expected to become "predictive", hence should provide clinically-relevant quantitative information, both in the current state of the patient and under various scenarii of future evolutions, such as for therapy planning.

uk: вхід без авторизації

name: Direct and inverse biomechanical modeling of the heart: From sarcomeres to organ, with experimental assessments and patient-specific clinical validations


uk: Математика, природничі науки

description: When solving wave scattering problems with the Boundary Element Method (BEM), one usually faces the problem of storing a dense matrix of huge size which size is proportional to the (square of) the number N of unknowns on the boundary of the scattering object. Several methods, among which the Fast Multipole Method (FMM) or the H-matrices are celebrated, were developed to circumvent this obstruction. In both cases an approximation of the matrix is obtained with a O(N log(N)) storage and the matrix-vector product has the same complexity. This permits to solve the problem, replacing the direct solver with an iterative method. The aim of the talk is to present an alternative method which is based on an accurate version of the Fourier based convolution. Based on the non-uniform FFT, the method, called the sparse cardinal sine decomposition (SCSD) ends up to have the same complexity than the FMM for much less complexity in the implementation. We show in practice how the method works, and give applications in as different domains as Laplace, Helmholtz, Maxwell or Stokes equations. This is a joint work with Matthieu Aussal.

uk: вхід без авторизації

name: The sparse cardinal sine decomposition and applications


uk: Математика, природничі науки

description: An ubiquitous problem in applied science is the recovery of physical phenomenons, represented by multivariate functions, from uncomplete measurements. These measurements typically have the form of pointwise data, but could also be obtained by linear functional. Most often, recovery techniques are based on some form of approximation by finite dimensional space that should accurately capture the unknown multivariate function. The first part of the course will review fundamental tools from approximation theory that describe how well relevant classes of multivariate functions can be described by such finite dimensional spaces. The notion of (linear or nonlinear) n-width will be developped, in relation with reduced modeling strategies that allow to construct near-optimal approximation spaces for classes of parametrized PDE's. Functions of many variables that are subject to the curse of dimensionality, will also be discussed. The second part of the course will review two recovery strategies from uncomplete measurements: weighted least-squares and parametrized background data-weak methods. An emphasis will be put on the derivation of sample distributions of minimal size for ensuring optimal convergence estimates.

uk: вхід без авторизації

name: Theory of approximation of high-dimensional functions - lecture 2


uk: Математика, природничі науки

description: Many physical phenomena deal with a fluid interacting with a moving rigid or deformable structure. These kinds of problems have a lot of important applications, for instance, in aeroelasticity, biomechanics, hydroelasticity, sedimentation, etc. From the analytical point of view as well as from the numerical point of view they have been studied extensively over the past years. We will mainly focus on viscous fluid interacting with an elastic structure. The purpose of the present lecture is to present an overview of some of the mathematical and numerical difficulties that may be encountered when dealing with fluid–structure interaction problems such as the geometrical nonlinearities or the added mass effect and how one can deal with these difficulties.

uk: вхід без авторизації

name: Mathematical and numerical analysis of some fluid structure interaction problems - Lecture 1


uk: Математика, природничі науки

uk: вхід без авторизації

name: Mathematical and numerical analysis of some fluid structure interaction problems - Lecture 2


uk: Математика, природничі науки

uk: вхід без авторизації

name: Mathematical and numerical analysis of some fluid structure interaction problems - Lecture 3


uk: Математика, природничі науки

uk: вхід без авторизації

name: Mathematical and numerical analysis of some fluid structure interaction problems - Lecture 4


Darcy problem and crowd motion modeling

uk: Математика, природничі науки

description: We describe here formal analogies between the Darcy equations, that describe the flow of a viscous fluid in a porous medium, and some problems arising from the handing of congestion in crowd motion models. At the microscopic level, individuals are identified to rigid discs, and the dual handling of the non overlapping constraint leads to discrete Darcy-like equations with a unilateral constraint that involves the velocities and interaction pressures, and that are set on the contact network. At the macroscopic level, a similar problem is obtained, that is set on the congested zone. We emphasize the differences between the two settings: at the macroscopic level, a straight use of the maximum principle shows that congestion actually favors evacuation, which is in contradiction with experimental evidence. On the contrary, in the microscopic setting, the very particular structure of the discrete differential operators makes it possible to reproduce observed "Stop and Go waves", and the so called "Faster is Slower" effect.

uk: вхід без авторизації


uk: Математика, природничі науки

description: At the end of the 70', Littlejohn [1, 2, 3] shed new light on what is called the Gyro-Kinetic Approximation. His approach incorporated high-level mathematical concepts from Hamiltonian Mechanics, Differential Geometry and Symplectic Geometry into a physical affordable theory in order to clarify what has been done for years in the domain. This theory has been being widely used to deduce the numerical methods for Tokamak and Stellarator simulation. Yet, it was formal from the mathematical point of view and not directly accessible for mathematicians. This talk will present a mathematically rigorous version of the theory. The way to set out this Gyro-Kinetic Approximation consists of the building of a change of coordinates that decouples the Hamiltonian dynamical system satisfied by the characteristics of charged particles submitted to a strong magnetic field into a part that concerns the fast oscillation induced by the magnetic field and a other part that describes a slower dynamics. This building is made of two steps. The goal of the first one, so-called "Darboux Algorithm", is to give to the Poisson Matrix (associated to the Hamiltonian system) a form that would achieve the goal of decoupling if the Hamiltonian function does not depend on one given variable. Then the second change of variables (which is in fact a succession of several ones), so-called "Lie Algorithm", is to remove the given variable from the Hamiltonian function without changing the form of the Poisson Matrix. (Notice that, beside this Geometrical Gyro-Kinetic Approximation Theory, an alternative approach, based on Asymptotic Analysis and Homogenization Methods was developed in Frenod and Sonnendrücker [5, 6, 7], Frenod, Raviart and Sonnendrücker [4], Golse and Saint-Raymond [9] and Ghendrih, Hauray and Nouri [8].)

uk: вхід без авторизації

name: The geometrical gyro-kinetic approximation


uk: Математика, природничі науки

description: In this talk, I will introduce the stochastic downscaling method (SDM) that borrows techniques from small scale turbulence (S.B. Pope) for the simulation of wind flows thanks to hybrid methods (deterministic-stochastic). I will present the downscaling method used to refine a wind forecast at a sufficiently small scale, and the way wind turbines are implemented in the model. Comparisons with traditional numerical methods (LES) and validation w.r.t. experimental data will also be provided.

uk: вхід без авторизації

name: Wind energy: from downscaled forecasts to mills production - Part 1


uk: Математика, природничі науки

description: We show how to combine numerical schemes and calibration of systems of o.d.e. to provide efficient feedback strategies for the biological decontamination of water resources. For natural resources, we retain to introduce any bacteria in the resource and treat it aside preserving a constant volume of the resource at any time. The feedback strategies are derived from the minimal time synthesis of the system of o.d.e.

uk: вхід без авторизації

name: Bioremediation of natural resources: how optimization and numerical simulations can help? - Part 2


uk: Математика, природничі науки

uk: вхід без авторизації

name: Numerical methods for mean field games - Lecture 2: Monotone finite difference schemes

name: Centre International de Rencontres Mathématiques (CIRM)


uk: Математика, природничі науки

uk: вхід без авторизації

name: Numerical methods for mean field games - Lecture 1: Introduction to the system of PDEs and its interpretation. Uniqueness of classical solutions


uk: Математика, природничі науки

description: We consider competitive capacity investment for a duopoly of two distinct producers. The producers are exposed to stochastically fluctuating costs and interact through aggregate supply. Capacity expansion is irreversible and modeled in terms of timing strategies characterized through threshold rules. Because the impact of changing costs on the producers is asymmetric, we are led to a nonzero-sum timing game describing the transitions among the discrete investment stages. Working in a continuous-time diffusion framework, we characterize and analyze the resulting Nash equilibrium and game values. Our analysis quantifies the dynamic competition effects and yields insight into dynamic preemption and over-investment in a general asymmetric setting. A case-study considering the impact of fluctuating emission costs on power producers investing in nuclear and coal-fired plants is also presented.

uk: вхід без авторизації

name: Capacity expansion games with application to competition in power generation investments


uk: Математика, природничі науки

description: We introduce a new strategy for the solution of Mean Field Games in the presence of major and minor players. This approach is based on a formulation of the fixed point step in spaces of controls. We use it to highlight the differences between open and closed loop problems. We illustrate the implementation of this approach for linear quadratic and finite state space games, and we provide numerical results motivated by applications in biology and cyber-security.

uk: вхід без авторизації

name: Mean field games with major and minor players


An introduction to BSDE

uk: Математика, природничі науки

description: Backward stochastic differential equations have been a very successful and active tool for stochastic finance and insurance for some decades. More generally they serve as a central method in applications of control theory in many areas. We introduce BSDE by looking at a simple utility optimization problem in financial stochastics. We shall derive an important class of BSDE by applying the martingale optimality principle to solve an optimal investment problem for a financial agent whose income is partly affected by market external risk. We then present the basics of existence and uniqueness theory for solutions to BSDE the coefficients of which satisfy global Lipschitz conditions.

uk: вхід без авторизації


uk: Математика, природничі науки

description: Recently, an important research activity on mean field games (MFGs for short) has been initiated by the pioneering works of Lasry and Lions: it aims at studying the asymptotic behavior of stochastic differential games (Nash equilibria) as the number n of agents tends to infinity. The field is now rapidly growing in several directions, including stochastic optimal control, analysis of PDEs, calculus of variations, numerical analysis and computing, and the potential applications to economics and social sciences are numerous.

uk: вхід без авторизації

name: Numerical methods for mean field games - Lecture 3: Variational MFG and related algorithms for solving the discrete system of nonlinear equations


uk: Математика, природничі науки

uk: вхід без авторизації

name: Particle algorithm for McKean SDE: a short review on numerical analysis


Cubature methods and applications

uk: Математика, природничі науки

description: The talk will have two parts: In the first part, I will go over some of the basic feature of cubature methods for approximating solutions of classical SDEs and how they can be adapted to solve Backward SDEs. In the second part, I will introduce some recent results on the use of cubature method for approximating solutions of McKean-Vlasov SDEs.

uk: вхід без авторизації


uk: Математика, природничі науки

description: We propose a mean field kinetic model for systems of rational agents interacting in a game theoretical framework. This model is inspired from non-cooperative anonymous games with a continuum of players and Mean-Field Games. The large time behavior of the system is given by a macroscopic closure with a Nash equilibrium serving as the local thermodynamic equilibrium. Applications of the presented theory to social and economical models will be given.

uk: вхід без авторизації

name: On the interplay between kinetic theory and game theory


Model-free control and deep learning

uk: Математика, природничі науки

description: In this talk I will present some recent developments in model-free reinforcement learning applied to large state spaces, with an emphasis on deep learning and its role in estimating action-value functions. The talk will cover a variety of model-free algorithms, including variations on Q-Learning, and some of the main techniques that make the approach practical. I will illustrate the usefulness of these methods with examples drawn from the Arcade Learning Environment, the popular set of Atari 2600 benchmark domains.

uk: вхід без авторизації


uk: Математика, природничі науки

description: We first introduce the Metropolis-Hastings algorithm. We then consider the Random Walk Metropolis algorithm on Rn with Gaussian proposals, and when the target probability measure is the n-fold product of a one dimensional law. It is well-known that, in the limit n tends to infinity, starting at equilibrium and for an appropriate scaling of the variance and of the timescale as a function of the dimension n, a diffusive limit is obtained for each component of the Markov chain. We generalize this result when the initial distribution is not the target probability measure. The obtained diffusive limit is the solution to a stochastic differential equation nonlinear in the sense of McKean. We prove convergence to equilibrium for this equation. We discuss practical counterparts in order to optimize the variance of the proposal distribution to accelerate convergence to equilibrium. Our analysis confirms the interest of the constant acceptance rate strategy (with acceptance rate between 1/4 and 1/3).

uk: вхід без авторизації

name: The Metropolis Hastings algorithm: introduction and optimal scaling of the transient phase


uk: Математика, природничі науки

description: Optimal vector quantization has been originally introduced in Signal processing as a discretization method of random signals, leading to an optimal trade-off between the speed of transmission and the quality of the transmitted signal. In machine learning, similar methods applied to a dataset are the historical core of unsupervised classification methods known as “clustering”. In both case it appears as an optimal way to produce a set of weighted prototypes (or codebook) which makes up a kind of skeleton of a dataset, a signal and more generally, from a mathematical point of view, of a probability distribution. Quantization has encountered in recent years a renewed interest in various application fields like automatic classification, learning algorithms, optimal stopping and stochastic control, Backward SDEs and more generally numerical probability. In all these various applications, practical implementation of such clustering/quantization methods more or less rely on two procedures (and their countless variants): the Competitive Learning Vector Quantization (CLVQ) which appears as a stochastic gradient descent derived from the so-called distortion potential and the (randomized) Lloyd's procedure (also known as k- means algorithm, nu ees dynamiques) which is but a fixed point search procedure. Batch version of those procedures can also be implemented when dealing with a dataset (or more generally a discrete distribution).

uk: вхід без авторизації

name: Optimal vector quantization: from signal processing to clustering and numerical probability


Branching for PDEs

uk: Математика, природничі науки

description: Branching methods have recently been developed to solve some PDEs. Starting from Mckean formulation, we give the initial branching method to solve the KPP equation. We then give a formulation to solve non linear equation with a non linearity polynomial in the value function u. The methodology is extended for general non linearities in the value function u. Then we develop the methodology to solve non linear equation with non linearities polynomial in u and Du with convergence results. At last we give some numerical schemes to solve the semi-linear case and even the full non linear case but currently without convergence results.

uk: вхід без авторизації


uk: Математика, природничі науки

description: I will review several relaxations of the classical Monge Optimal Transport problem using a dynamic “time” extension and discuss the corresponding available numerical methods. They also apply to some instances of variational mean field games.

uk: вхід без авторизації

name: Dynamic formulations of optimal transportation and variational MFGs


Bandits in auctions (& more)

uk: Математика, природничі науки

description: In this talk, I will introduce the classical theory of multi-armed bandits, a field at the junction of statistics, optimization, game theory and machine learning, discuss the possible applications, and highlights the new perspectives and open questions that they propose We consider competitive capacity investment for a duopoly of two distinct producers. The producers are exposed to stochastically fluctuating costs and interact through aggregate supply. Capacity expansion is irreversible and modeled in terms of timing strategies characterized through threshold rules. Because the impact of changing costs on the producers is asymmetric, we are led to a nonzero-sum timing game describing the transitions among the discrete investment stages. Working in a continuous-time diffusion framework, we characterize and analyze the resulting Nash equilibrium and game values. Our analysis quantifies the dynamic competition effects and yields insight into dynamic preemption and over-investment in a general asymmetric setting. A case-study considering the impact of fluctuating emission costs on power producers investing in nuclear and coal-fired plants is also presented.

uk: вхід без авторизації


keywords: optimal hierarchies for Multilevel Monte Carlo

uk: Математика, природничі науки

description: We will first recall, for a general audience, the use of Monte Carlo and Multi-level Monte Carlo methods in the context of Uncertainty Quantification. Then we will discuss the recently developed Adaptive Multilevel Monte Carlo (MLMC) Methods for (i) It Stochastic Differential Equations, (ii) Stochastic Reaction Networks modeled by Pure Jump Markov Processes and (iii) Partial Differential Equations with random inputs. In this context, the notion of adaptivity includes several aspects such as mesh refinements based on either a priori or a posteriori error estimates, the local choice of different time stepping methods and the selection of the total number of levels and the number of samples at different levels. Our Adaptive MLMC estimator uses a hierarchy of adaptively refined, non-uniform time discretizations, and, as such, it may be considered a generalization of the uniform discretization MLMC method introduced independently by M. Giles and S. Heinrich. In particular, we show that our adaptive MLMC algorithms are asymptotically accurate and have the correct complexity with an improved control of the multiplicative constant factor in the asymptotic analysis. In this context, we developed novel techniques for estimation of parameters needed in our MLMC algorithms, such as the variance of the difference between consecutive approximations. These techniques take particular care of the deepest levels, where for efficiency reasons only few realizations are available to produce essential estimates. Moreover, we show the asymptotic normality of the statistical error in the MLMC estimator, justifying in this way our error estimate that allows prescribing both the required accuracy and confidence level in the final result. We present several examples to illustrate the above results and the corresponding computational savings.

uk: вхід без авторизації

name: Multilevel and multi-index sampling methods with applications - Lecture 1: Adaptive strategies for Multilevel Monte Carlo


uk: Математика, природничі науки

description: In this lecture, we shall discuss the key steps involved in the use of least squares regression for approximating the solution to BSDEs. This includes how to obtain explicit error estimates, and how these error estimates can be used to tune the parameters of the numerical scheme based on complexity considerations. The algorithms are based on a two stage approximation process. Firstly, a suitable discrete time process is chosen to approximate the of the continuous time solution of the BSDE. The nodes of the discrete time processes can be expressed as conditional expectations. As we shall demonstrate, the choice of discrete time process is very important, as its properties will impact the performance of the overall numerical scheme. In the second stage, the conditional expectation is approximated in functional form using least squares regression on synthetically generated data – Monte Carlo simulations drawn from a suitable probability distribution. A key feature of the regression step is that the explanatory variables are built on a user chosen finite dimensional linear space of functions, which the user specifies by setting basis functions. The choice of basis functions is made on the hypothesis that it contains the solution, so regularity and boundedness assumptions are used in its construction. The impact of the choice of the basis functions is exposed in error estimates. In addition to the choice of discrete time approximation and the basis functions, the Markovian structure of the problem gives significant additional freedom with regards to the Monte Carlo simulations. We demonstrate how to use this additional freedom to develop generic stratified sampling approaches that are independent of the underlying transition density function. Moreover, we demonstrate how to leverage the stratification method to develop a HPC algorithm for implementation on GPUs. Thanks to the Feynmann-Kac relation between the the solution of a BSDE and its associated semilinear PDE, the approximation of the BSDE can be directly used to approximate the solution of the PDE. Moreover, the smoothness properties of the PDE play a crucial role in the selection of the hypothesis space of regressions functions, so this relationship is vitally important for the numerical scheme. We conclude with some draw backs of the regression approach, notably the curse of dimensionality.

uk: вхід без авторизації

name: Least squares regression Monte Carlo for approximating BSDES and semilinear PDES


uk: Математика, природничі науки

description: In this talk we first quickly present a classical and simple model used to describe flow in porous media (based on Darcy's Law). The high heterogeneity of the media and the lack of data are taken into account by the use of random permability fields. We then present some mathematical particularities of the random fields frequently used for such applications and the corresponding theoretical and numerical issues. After giving a short overview of various applications of this basic model, we study in more detail the problem of the contamination of an aquifer by migration of pollutants. We present a numerical method to compute the mean spreading of a diffusive set of particles representing a tracer plume in an advecting flow field. We deal with the uncertainty thanks to a Monte Carlo method and use a stochastic particle method to approximate the solution of the transport-diffusion equation. Error estimates will be established and numerical results (obtained by A.Beaudoin et al. using PARADIS Software) will be presented. In particular the influence of the molecular diffusion and the heterogeneity on the asymptotic longitudinal macrodispersion will be investigated thanks to numerical experiments. Studying qualitatively and quantitatively the influence of molecular diffusion, correlation length and standard deviation is an important question in hydrogeolgy.

uk: вхід без авторизації

name: Subsurface flow with uncertainty : applications and numerical analysis issues


uk: Математика, природничі науки

description: Stochastic models are used in many scientific fields, including mechanics, physics, life sciences, queues and social-network studies, chemistry. Stochastic modeling is necessary when deterministic ones cannot capture features of the dynamics, for instance, to represent effects of unresolved small-scale fluctuations, or when systems are subjected to important inherent noise. Often, stochastic models are not completely known and involve some calibrated parameters that should be considered as uncertain. In this case, it is critical to assess the impact of the uncertain model parameters on the stochastic model predictions. This is usually achieved by performing a sensitivity analysis (SA) which characterizes changes in a model output when the uncertain parameters are varied. In the case of a stochastic model, one classically applies the SA to statistical moments of the prediction, estimating, for instance, the derivatives with respect to the uncertain parameters of the output mean and variance. In this presentation, we introduce new approaches of SA in a stochastic system based on variance decomposition methods (ANOVA, Sobol). Compared to previous methods, our SA methods are global, with respect to both the parameters and stochasticity, and decompose the variance into stochastic, parametric and mixed contributions. We consider first the case of uncertain Stochastic Differential Equations (SDE), that is systems with external noisy forcing and uncertain parameters. A polynomial chaos (PC) analysis with stochastic expansion coefficients is proposed to approximate the SDE solution. We first use a Galerkin formalism to determine the expansion coefficients, leading to a hierarchy of SDEs. Under the mild assumption that the noise and uncertain parameters are independent, the Galerkin formalism naturally separates parametric uncertainty and stochastic forcing dependencies, enabling an orthogonal decomposition of the variance, and consequently identify contributions arising from the uncertainty in parameters, the stochastic forcing, and a coupled term. Non-intrusive approaches are subsequently considered for application to more complex systems hardly amenable to Galerkin projection. We also discuss parallel implementations and application to derived quantity of interest, in particular, a novel sampling strategy for non-smooth quantities of interest but smooth SDE solution. Numerical examples are provided to illustrate the output of the SA and the computational complexity of the method. Second, we consider the case of stochastic simulators governed by a set of reaction channels with stochastic dynamics. Reformulating the system dynamics in terms of independent standardized Poisson processes permits the identification of individual realizations of each reaction channel dynamic and a quantitative characterization of the inherent stochasticity sources. By judiciously exploiting the inherent stochasticity of the system, we can then compute the global sensitivities associated with individual reaction channels, as well as the importance of channel interactions. This approach is subsequently extended to account for the effects of uncertain parameters and we propose dedicated algorithms to perform the Sobols decomposition of the variance into contributions from an arbitrary subset of uncertain parameters and stochastic reaction channels. The algorithms are illustrated in simplified systems, including the birth-death, Schlgl, and Michaelis-Menten models. The sensitivity analysis output is also contrasted with a local derivative-based sensitivity analysis method.

uk: вхід без авторизації

name: Global sensitivity analysis in stochastic systems


uk: Математика, природничі науки

description: Uncertainty quantification (UQ) in the context of engineering applications aims aims at quantifying the effects of uncertainty in the input parameters of complex models on their output responses. Due to the increased availability of computational power and advanced modelling techniques, current simulation tools can provide unprecedented insight in the behaviour of complex systems. However, the associated computational costs have also increased significantly, often hindering the applicability of standard UQ techniques based on Monte-Carlo sampling. To overcome this limitation, metamodels (also referred to as surrogate models) have become a staple tool in the Engineering UQ community. This lecture will introduce a general framework for dealing with uncertainty in the presence of expensive computational models, in particular for reliability analysis (also known as rare event estimation). Reliability analysis focuses on the tail behaviour of a stochastic model response, so as to compute the probability of exceedance of a given performance measure, that would result in a critical failure of the system under study. Classical approximation-based techniques, as well as their modern metamodel-based counter-parts will be introduced.

uk: вхід без авторизації

name: Metamodels for uncertainty quantification and reliability analysis


keywords: Partial Differential Equations with random inputs

uk: Математика, природничі науки

description: We describe and analyze the Multi-Index Monte Carlo (MIMC) and the Multi-Index Stochastic Collocation (MISC) method for computing statistics of the solution of a PDE with random data. MIMC is both a stochastic version of the combination technique introduced by Zenger, Griebel and collaborators and an extension of the Multilevel Monte Carlo (MLMC) method first described by Heinrich and Giles. Instead of using first-order differences as in MLMC, MIMC uses mixed differences to reduce the variance of the hierarchical differences dramatically. These mixed differences yield new and improved complexity results, which are natural generalizations of Giles's MLMC analysis, and which increase the domain of problem parameters for which we achieve the optimal convergence. On the same vein, MISC is a deterministic combination technique based on mixed differences of spatial approximations and quadratures over the space of random data. Provided enough mixed regularity, MISC can achieve better complexity than MIMC. Moreover, we show that, in the optimal case, the convergence rate of MISC is only dictated by the convergence of the deterministic solver applied to a one-dimensional spatial problem. We propose optimization procedures to select the most effective mixed differences to include in MIMC and MISC. Such optimization is a crucial step that allows us to make MIMC and MISC computationally efficient. We show the effectiveness of MIMC and MISC in some computational tests using the mimclib open source library, including PDEs with random coefficients and Stochastic Interacting Particle Systems. Finally, we will briefly discuss the use of Markovian projection for the approximation of prices in the context of American basket options.

uk: вхід без авторизації

name: Multilevel and multi-index sampling methods with applications - Lecture 2: Multilevel and Multi-index Monte Carlo methods for the McKean-Vlasov equation


uk: Математика, природничі науки

uk: вхід без авторизації

name: Lecture 1: Introduction to HPC, random generation, and OpenMP


uk: Математика, природничі науки

uk: вхід без авторизації

name: Lecture 2: Introduction to HPC - MPI: design of parallel program and MPI

name: Centre International de Rencontres Mathématiques (CIRM)


Project evaluation under uncertainty

uk: Математика, природничі науки

description: Industrial strategic decisions have evolved tremendously in the last decades towards a higher degree of quantitative analysis. Such decisions require taking into account a large number of uncertain variables and volatile scenarios, much like financial market investments. Furthermore, they can be evaluated by comparing to portfolios of investments in financial assets such as in stocks, derivatives and commodity futures. This revolution led to the development of a new field of managerial science known as Real Options. The use of Real Option techniques incorporates also the value of flexibility and gives a broader view of many business decisions that brings in techniques from quantitative finance and risk management. Such techniques are now part of the decision making process of many corporations and require a substantial amount of mathematical background. Yet, there has been substantial debate concerning the use of risk neutral pricing and hedging arguments to the context of project evaluation. We discuss some alternatives to risk neutral pricing that could be suitable to evaluation of projects in a realistic context with special attention to projects dependent on commodities and non-hedgeable uncertainties. More precisely, we make use of a variant of the hedged Monte-Carlo method of Potters, Bouchaud and Sestovic to tackle strategic decisions. Furthermore, we extend this to different investor risk profiles. This is joint work with Edgardo Brigatti, Felipe Macias, and Max O. de Souza. If time allows we shall also discuss the situation when the historical data for the project evaluation is very limited and we can make use of certain symmetries of the problem to perform (with good estimates) a nonintrusive stratified resampling of the data. This is joint work with E. Gobet and G. Liu.

uk: вхід без авторизації


Splitting algorithm for nested events

uk: Математика, природничі науки

description: Consider a problem of Markovian trajectories of particles for which you are trying to estimate the probability of a event. Under the assumption that you can represent this event as the last event of a nested sequence of events, it is possible to design a splitting algorithm to estimate the probability of the last event in an efficient way. Moreover you can obtain a sequence of trajectories which realize this particular event, giving access to statistical representation of quantities conditionally to realize the event. In this talk I will present the "Adaptive Multilevel Splitting" algorithm and its application to various toy models. I will explain why it creates an unbiased estimator of a probability, and I will give results obtained from numerical simulations.

uk: вхід без авторизації


uk: Математика, природничі науки

description: We propose a novel projection-based particle method for solving the McKean-Vlasov stochastic differential equations. Our approach is based on a projection-type estimation of the marginal density of the solution in each time step. The projection-based particle method leads in many situation to a significant reduction of numerical complexity compared to the widely used kernel density estimation algorithms. We derive strong convergence rates and rates of density estimation. The convergence analysis in the case of linearly growing coefficients turns out to be rather challenging and requires some new type of averaging technique. This case is exemplified by explicit solutions to a class of McKean-Vlasov equations with affine drift. The performance of the proposed algorithm is illustrated by several numerical examples.

uk: вхід без авторизації

name: Projected particle methods for solving McKean Vlasov SDEs


uk: Математика, природничі науки

description: The valuation of American options (a widespread type of financial contract) requires the numerical solution of an optimal stopping problem. Numerical methods for such problems have been widely investigated. Monte-Carlo methods are based on the implementation of dynamic programming principles coupled with regression techniques. In lower dimension, one can choose to tackle the related free boundary PDE with deterministic schemes. Pricing of American options will therefore be inevitably heavier than the one of European options, which only requires the computation of a (linear) expectation. The calibration (fitting) of a stochastic model to market quotes for American options is therefore an a priori demanding task. Yet, often this cannot be avoided: on exchange markets one is typically provided only with market quotes for American options on single stocks (as opposed to large stock indexes - e.g. S&P500 - for which large amounts of liquid European options are typically available). In this talk, we show how one can derive (approximate, but accurate enough) explicit formulas - therefore replacing other numerical methods, at least in a low-dimensional case - based on asymptotic calculus for diffusions. More precisely: based on a suitable representation of the PDE free boundary, we derive an approximation of this boundary close to final time that refines the expansions known so far in the literature. Via the early premium formula, this allows to derive semi-closed expressions for the price of the American put/call. The final product is a calibration recipe of a Dupire's local volatility to American option data. Based on joint work with Pierre Henry-Labordère.

uk: вхід без авторизації

name: Some asymptotic results about American options and volativity


Mean Field Control with Congestion

uk: Математика, природничі науки

description: The theory of mean field type control (or control of MacKean-Vlasov) aims at describing the behaviour of a large number of agents using a common feedback control and interacting through some mean field term. The solution to this type of control problem can be seen as a collaborative optimum. We will present the system of partial differential equations (PDE) arising in this setting: a forward Fokker-Planck equation and a backward Hamilton-Jacobi-Bellman equation. They describe respectively the evolution of the distribution of the agents' states and the evolution of the value function. Since it comes from a control problem, this PDE system differs in general from the one arising in mean field games. Recently, this kind of model has been applied to crowd dynamics. More precisely, in this talk we will be interested in modeling congestion effects: the agents move but try to avoid very crowded regions. One way to take into account such effects is to let the cost of displacement increase in the regions where the density of agents is large. The cost may depend on the density in a non-local or in a local way. We will present one class of models for each case and study the associated PDE systems. The first one has classical solutions whereas the second one has weak solutions. Numerical results based on the Newton algorithm and the Augmented Lagrangian method will be presented. This is joint work with Yves Achdou.

uk: вхід без авторизації


uk: Математика, природничі науки

description: In this work, we consider the discretization of some nonlinear Fokker-Planck-Kolmogorov equations. The scheme we propose preserves the non-negativity of the solution, conserves the mass and, as the discretization parameters tend to zero, has limit measure-valued trajectories which are shown to solve the equation. This convergence result is proved by assuming only that the coefficients are continuous and satisfy a suitable linear growth property with respect to the space variable. In particular, under these assumptions, we obtain a new proof of existence of solutions for such equations. We apply our results to several examples, including Mean Field Games systems and variations of the Hughes model for pedestrian dynamics.

uk: вхід без авторизації

name: On the discretization of some nonlinear Fokker-Planck-Kolmogorov equations and applications


uk: Математика, природничі науки

description: The mathematical framework of variational inequalities is a powerful tool to model problems arising in mechanics such as elasto-plasticity where the physical laws change when some state variables reach a certain threshold [1]. Somehow, it is not surprising that the models used in the literature for the hysteresis effect of non-linear elasto-plastic oscillators submitted to random vibrations [2] are equivalent to (finite dimensional) stochastic variational inequalities (SVIs) [3]. This presentation concerns (a) cycle properties of a SVI modeling an elasto-perfectly-plastic oscillator excited by a white noise together with an application to the risk of failure [4,5]. (b) a set of Backward Kolmogorov equations for computing means, moments and correlation [6]. (c) free boundary value problems and HJB equations for the control of SVIs. For engineering applications, it is related to the problem of critical excitation [7]. This point concerns what we are doing during the CEMRACS research project. (d) (if time permits) on-going research on the modeling of a moving plate on turbulent convection [8]. This is a mixture of joint works and / or discussions with, amongst others, A. Bensoussan, L. Borsoi, C. Feau, M. Huang, M. Laurière, G. Stadler, J. Wylie, J. Zhang and J.Q. Zhong.

uk: вхід без авторизації

name: Stochastic variational inequalities for random mechanics


uk: Математика, природничі науки

description: We analyse how reverting Random Number Generator can be efficiently used to save memory in solving dynamic programming equation. For SDEs, it takes the form of forward and backward Euler scheme. Surprisingly the error induced by time reversion is of order 1.

uk: вхід без авторизації

name: Forward and backward simulation of Euler scheme


de: Geschichte

uk: Історія

en: History

uk: Гуманітарні науки

description: Im ihrem digitalen Montagsvortrag am 7. Februar 2022, um 18.30 Uhr, berichtet die niederländisch-us-amerikanische Wissenschaftlerin Annemieke Milks über neue Erkenntnisse zu den ältesten Holzwaffen der Welt. Funde aus Großbritannien und Deutschland weisen ein Alter von bis zu 400.000 Jahren auf. Milks stellt die Speere aus Schöningen im Detail vor und führt in die ethnologische und experimentelle Forschung ein, die unser Verständnis ihrer Verwendung verbessert hat. Dabei geht sie unter anderem der Frage nach, auf welche Tiere mit diesen Waffen Jagd gemacht wurde und wo ähnliche Waffen nachgewiesen werden konnten. Anhand von Experimenten wurde versucht nachzuvollziehen, welche Reichweite die Jäger mit diesen Waffen hatten und welche Jagdstrategie sie demnach verfolgt haben könnten.

uk: вхід без авторизації

name: The oldest weapons: revealing the secrets of the Schöningen Spears

name: Niedersächsisches Landesamt für Denkmalpflege (NLD)


keywords: Denkmalpflege Architekturgeschichte

de: Architektur, Innenarchitektur

uk: Архітектура, дизайн інтер'єру

en: Architecture, Interior Architecture

description: 2020 starteten das Niedersächsische Landesamt für Denkmalpflege, die Bet Tfila – Forschungsstelle für jüdische Architektur an der Technischen Universität Braunschweig und das Center for Jewish Art an der Hebrew University of Jerusalem das Projekt »Niedersachsen – Eine jüdische Topografie«, gefördert durch PRO*Niedersachsen. Die »Jüdische Topografie Niedersachsen« stellt Informationen über historische Bauten und Einrichtungen jüdischer Gemeinschaften online zur Verfügung. Auf dem Gebiet des heutigen Niedersachsen gab es bis zur Zerstörung und Vernichtung in der Zeit des Nationalsozialismus in weit über hundert Orten jüdische Gemeinschaften mit einer Vielzahl religiöser, sozialer und kultureller Einrichtungen. Die meisten ihrer Synagogen, Betsäle, Ritualbäder und Religionsschulen sind heute verloren oder oft entstellend umgebaut, und auch auf den überwiegend erhaltenen Friedhöfen sind die Folgen von Schändungen und Zerstörungen unübersehbar. Dennoch zeugen zahlreiche Orte und Objekte von jüdischer Kultur und Geschichte, aber auch von lokaler und regionaler Erinnerungsarbeit und nicht zuletzt vom Leben in den heutigen jüdischen Gemeinden. Am 7. März 2022, ab 18.30 Uhr, präsentiert die Projektgruppe erste Ergebnisse ihrer Forschungen.

uk: вхід без авторизації


uk: Гуманітарні науки

description: Bis 2018 wurde Niedersachsen flächendeckend mit Airborne Laser Scanning erfasst. Überraschend zeigten sich in den bewaldeten Flächen zahlreiche kleine Graben- und Wallanlagen, die bislang in der Archäologischen Datenbank ADABweb nicht verzeichnet waren. Große Probleme bereiten weiterhin die funktionale Deutung sowie die Datierung der Anlagen. Der mit ALS-Grafiken reich bestückte Vortag will die Zuhörerinnen und Zuhörer mit hineinnehmen in die Frage: Was haben wir denn da?

uk: вхід без авторизації

name: Kleine Graben-Wall-Anlagen in Niedersachsen im Airborne Laser Scanning / LiDAR


Never Forgotten – Never Again

uk: Гуманітарні науки

description: Am 7. April 2022, dem 28. Jahrestag des Gedenkens an den Völkermord gegen die Volksgruppe der Tutsi in Ruanda, eröffnet im Niedersächsischen Landesamt für Denkmalpflege eine Ausstellung ein, die den Aufbau einer Gedenkstätte in Murambi beschreibt, an dem zwei Restauratorinnen im Rahmen eines internationalen Kooperationsprojekt mit dem Universitätsklinikum Hamburg-Eppendorf beteiligt waren. In Erinnerung an die 100 Tage des Genozids von 1994 ist die Ausstellung vom bis zum 5. Juli 2022 für Besucherinnen und Besucher geöffnet. Die Ausstellung dokumentiert das Murambi-Projekt, das im Sommer 2016 begann. In einem großen Projekt des Universitätsklinikums Hamburg und des NLD berieten zwei archäologische Restauratorinnen die Gedenkstätte Murambi vor Ort und halfen dabei, die Leichname der Ermordeten zu erhalten. Die beiden Expertinnen waren bereits vertraut mit dem Umgang mit Moorleichen. Sie entwickelten ein Reinigungskonzept und stellten es im April 2017 der National Commission for the Fight against Genocide aus Ruanda in Hamburg vor. Es folgten mehrere Arbeitsaufenthalte in Murambi mit der Einrichtung von Arbeitsplätzen, Schulung der ruandischen Kolleginnen und Kollegen und Entwicklung eines Ausstellungs- sowie Monitoringkonzepts. Alle Arbeitsschritte und Ergebnisse konnten bereits auf verschiedenen internationalen Kongressen präsentiert werden. Nun informiert die speziell auf das Murambi-Projekt zugeschnittene Ausstellung »Never Forgotten – Never Again« im NLD über die eindrucksvolle Arbeit vor Ort. Im ihrem Montagsvortrag am 4. April geben die beiden Restauratorinnen, Monika Lehmann und Dorte Schaarschmidt, sowie der frühere Leiter des Instituts für Rechtsmedizin der Universitätsklinik Hamburg Eppendorf, Prof. Dr. med. Klaus Püschel, der das Projekt initiiert hat, eine Einführung in die Ausstellung. Zudem ist eine Dokumentation des Videografen Christian Burkert über den letzten Arbeitsbesuch des Teams in Ruanda zu sehen.

uk: вхід без авторизації


uk: Гуманітарні науки

description: Die Hünenburg bei Watenstedt, das war bis 1998 ein Bodendenkmal im Landkreis Helmstedt, über deren Datierung nur vage Anhaltspunkte vorlagen. Ein früheisenzeitliches Urnengräberfeld in 800 m Entfernung war eine weitere Fundstelle, ebenso wie zwei jungbronzezeitliche gegossene Bronzebecken, die irgendwo am Fluß Soltau weit südlich der Befestigung ausgepflügt worden waren. 25 Jahre und unzählige Grabungskampagnen später ist die Hünenburg ein bronzezeitliches Herrschaftszentrum, besitzt eine über 25 ha große Aussensiedlung, ist ein Zentrum der Metallverarbeitung, zeigt vielfältige Bestattungssitten und kann auch ein ausgedehntes Kultareal vorweisen. Einige Highlights und herausragende Funde werden vorgestellt und in einen größeren Zusammenhang eingeordnet. Fast mit jeder Grabungskampagne waren neue, völlig überraschende Funde zu bestaunen.

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name: Die bronzezeitliche Hünenburg im Landkreis Helmstedt: Gießformen, zerrupfte Bestattungen und ein mysteriöses Kultareal


uk: Комп'ютерні науки

description: This research is about the development of an EIA decision support system that effectively integrates and visualizes the results of the EIA review process and related information such as BIM/GIS, modeling data, and sensor data. The final goal is to improve the EIA process so that not only experts but also non-experts can participate in the EIA process and easily understand the EIA statemnets using innovative technologies such as 3D GIS and Easy Finger real-time simulation. The final system will be developed and opend as an open source. This research is 5 years long project funded by Minstry of Environment, South Korea. This talk will focus on the 1st year's research outcome and future plans.

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name: A Research on EIA(Environment Impact Assessment) Data Visualization Technology using

name: Open Source Geospatial Foundation (OSGeo)


uk: Комп'ютерні науки

description: This approach has several shortcomings due to limitations of raster data formats. When compared to vectors, the other common geospatial data format, rasters are less precise, hold less information, and are less conducive to smaller area constructs, such as building outlines and parcels, and are less accessible to the broader scientific community because of the special handling required. Given these shortcomings, we propose a vector analytical framework for population modeling. The framework is designed to combine all of the lines defining the input layers so that fields enclosed by those lines (i.e. polygons) are uniformly attributable to each of the input layers. This richer data stack allows for the development of models with more complex logic that are straightforward to implement and explain, as well as increasing the accessibility of modeled estimates and intermediate layers to a broader audience.

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name: A Vector Analytical Framework For Population Modeling


uk: Комп'ютерні науки

description: El presente trabajo es un caso de éxito en la actualización de un catastro municipal utilizando herramientas libres, realizado en el distrito de Hohenau, departamento de Itapúa, Paraguay. Fue posible migrar los registros catastrales a un Sistema de Informaciones Geográficas Institucional, mediante el cual fueron integrados 3 departamentos de la municipalidad. Se trabajo con 19 barrios, 524 manzanas y 5.798 parcelas. Fueron actualizados 3.553 registros de construcciones e incorporadas 2.009 nuevos bloques , generando un incremento del 57%, lo cual se tradujo a un aumento del potencial de recaudación del impuesto inmobiliario de 64%.

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name: Actualización de un Catastro Municipal Utilizando SIG Libre, un caso de éxito en Paraguay


uk: Комп'ютерні науки

description: Working in large open source projects, can be challenging, especially trying to keep everyone on the same page, and generating code that has enough similarities to allow shared maintenance. The advent of platforms like GitHub also made it easier for one time contributors to participate, generating in the process a fair amoumt of “review stress” in the project maintainers. The presentations covers automated QA tools as a way to make code more uniform, avoid introduction of some types of technical debt, and reduce review efforts on pull requests, while also raising the level of the review.

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name: Adding Quality Assurance to open source projects: experiences from GeoTools, GeoWebCache an GeoServer


uk: Комп'ютерні науки

description: Partners throughout the environmental world often struggle with integrating the right data, information, and analysis tools into their workflows. This happens for a variety of reasons, but often can be reduced to the fact that they are under-resourced to make use of new opportunities. There are increasingly sophisticated tools and datasets that are being made available, however the uptake of these capabilities, especially to inform local-scale decision making, is lagging within the environmental sector. To overcome this challenge, there is a need for partners to play an integrating role in the environmental world; focusing on ensuring local partners are aware of the emerging resources that now exist to address their challenges, have access to the software and technology needed to seamlessly incorporate it in their workflows, and understand their unique challenges without relying on a "one size fits all" approach. This session will focus on lessons learned from the work of the Center for Geospatial Analysis working with partners of all sizes to help identify pathways that deliver real improvements to decision making by integrating data and technology. Additionally, the session will highlight remaining large scale "questions" that deserve additional focus from the FOSS4G community about how new efforts can be focused on solving these challenges.

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name: Addressing the Last Mile Delivery Challenge in Environmental Data


uk: Комп'ютерні науки

description: PEARL, the Planetary Computer Land Cover Mapping Platform, uses state of the art ML and AI technologies to drastically reduce the time required to produce an accurate land cover map. Scientists and mappers get access to pre-trained, high performing starter models, and high resolution imagery (e.g. NAIP) hosted on Microsoft Azure. The land cover mapping tool manages the infrastructure for running inference at scale, visualizes model predictions, shows the model’s per class performance, allows for adding new training classes, and allows users to retrain the model. The tool helps harness the power of expert human mappers and scientists through immediate model evaluation metrics, easy retraining cycles and instant user feedback within the UI.

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name: Al Accelerated Human-in-the-Loop Land Use and Land Cover Mapping


uk: Комп'ютерні науки

description: This talk walks through a new algorithm for compressing JSON data, including GeoJSON. The JSON-to-Code algorithm compresses JSON data by converting it using recursive variable assignment into valid code that generates the JSON data. No prior coding experience required as the talk is at a high-level.

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name: Algorithm Talk: JSON-to-Code Compression


uk: Комп'ютерні науки

description: Water and Sanitation Corporation (WASAC) developed GIS system for rural water management by using FOSS4G software together with Japan International Cooperation Agency (JICA) since 2018. WASAC conducted the data collection by using QGIS and QField, then offline data sharing became available for all over the country of Rwanda until the JICA project ended in December 2019. Our achievements of the project was presented in FOSS4G 2019 Bucharest (see video). Although JICA project ended, WASAC still continue developing more advanced vector tiles’ based Web GIS system with former JICA expert - Jin IGARASHI. Our new online site is available here. Now all of our stakeholders can browse water supply data in Rwanda. We established this new web service for free of charge by using Github pages because of budget limitation. We also make our vector tiles data available as open data at Github and openAFRICA. This new vector tiles project was also developed under the technical support of The United Nations Vector Tile Toolkits.We would like to share how we are using this application to manage water and how we want to develop in the future.

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name: An implementation of FOSS4G - QGIS, QField and Vector Tiles for rural water supply management in Rwanda


uk: Комп'ютерні науки

description: Elasticsearch is a well-known NoSQL database to store and process large amounts of data, including geospatial types like points and polygons. There is a broad ecosystem of tools to help to ingest data into Elasticsearch, including some usual geospatial suspects like GDAL. Finally, Kibana is the goto solution for visualizing and making sense of all the data stored in a cluster of Elasticsearch nodes. In this talk, we will explore two archetypical use cases: on the one hand, archiving and processing information from moving or static events and, on the other, working with large amounts of data associated with a small set of asset locations. Examples of the first scenario would be tracking vehicles or databases of urban events like crime or inspection locations, while the second could be weather data archives or IoT systems. We will see how to ingest and enrich geospatial data into your cluster with these two use cases. Then we will explore some of Elasticsearch's geospatial capabilities. Finally, we will see how Kibana applications like Maps, Lens, Canvas, or Dashboards can help you visualizing and understanding your data. Finally, we want to take the opportunity to show to the community some of the latest developments made by the Kibana Maps team, like our new alerting capabilities or the support for vector tiles in Kibana and Elasticsearch.

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name: An overview of the Elastic stack geospatial capabilities


uk: Комп'ютерні науки

description: Agriculture comprises vital economic sectors producing food, agro-industrial feedstock, and energy and provides environmental services through managing soil, water, air, and biodiversity holistically. Agriculture including forestry also contributes to managing and reducing risks from natural disasters such as floods, droughts, landslides, and avalanches. Farming with its close contact to nature provides the socio-economic infrastructure to maintain cultural heritage. Farmers are also conservers of forests, pastures, fallow lands, and their natural resources and, in turn, of the environment. Agriculture today is a composite activity involving many actors and stakeholders in agri-food chains that produce and provide food and agricultural commodities to consumers. In addition to farmers, there are farm input suppliers, processors, transporters, and market intermediaries each playing their roles to make these chains efficient. Presentation will present analysis and the the vision of the EO4Agri project about the role of Earth observations in agriculture. The increasing economic, social, and environmental needs of agriculture pose many challenges for the upcoming years. This topic is closely related to the strategies of the United Nations and the European Union on sustainability. The United Nations adopted 17 Sustainable Development Goals in 2015 as part of the 2030 Agenda for Sustainable Development. The European Union presented in 2019 the European Green Deal - a roadmap to make the European economy sustainable. This white paper aims to stress the importance of knowledge management for agriculture to address these challenges. The role of Earth observation in this knowledge management is analysed including its current gaps and limitations. The white paper focuses on the definition of key problems, analysis data gaps, delivery platforms, analytical platforms, and final recommendations for future policies and financing. This document serves as an input for the future Strategic Research Agenda and the Policy Roadmap.

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name: Analysis of potential needs of Agriculture Sector for EO analysis


uk: Комп'ютерні науки

description: In recent years, the password to get into the club of the “cool kids” in technology has been Artificial Intelligence, also referred to as AI by the “it” group. AI has grown greatly in popularity and application with Geo Gecko also recently jumping on the train by starting to work on some Machine learning models which are a subset of the great AI. We have been building models to identify different crops using sentinel 1 and sentinel 2 images. This work has given us a front row seat in the implementation of the much-glorified machine learning algorithms. It is from this position that we are able to discuss our insights in regard to how “intelligent” this subset of artificial intelligence really is. Also having experienced the non-romantic side of machine learning (spoiler alert) which is data accessing, cleaning and preprocessing, we will discuss these in depth, alongside the break throughs we made to overcome them, and the recommendations that we have for the newbies. We intend for this talk to give ML enthusiasts a quick dose of reality so that they can take off the training wheels and get to know what really happens in Machine Learning.

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name: Artificial Unintelligence: Fverything we did wrong


uk: Комп'ютерні науки

description: The complex realities of changing climate and biodiversity are imperfectly understood. Bioacoustics is a conservation tool, going where human ears cannot stay and listen. Locally-informed machine learning analysis leads to big data insights, empowering informed decision making. Networks of bioacoustic recorders in some of Earth’s most biodiverse and vulnerable regions (near Everest in Nepal, Madidi National Park in Bolivia, and the Chesapeake Bay watershed in the United States) are bearing witness to a changing climate. More than 1850 days of audio data already collected provide a powerful dataset for studying species distributions. Machine learning (ML) turns this data into information to understand climate change and biodiversity. MLmodels are being trained for a dozen species in Nepal, Bolivia, and USA. Analyzed data show location and time of species vocalization. Modeling can expand rapidly as labeled data is collaboratively created by local experts. Preliminary results from Nepal show that a rare bird species was identified 1,000 feet higher in elevation than previously recorded: probable proof of concept that bird species are migrating uphill with changing climate. Bioacoustics is a valuable tool for species population surveys and biodiversity monitoring.

uk: вхід без авторизації

name: Bioacoustics and Machine Learning for Avian Species Presence Surveys


Caching time changes in maps

uk: Комп'ютерні науки

description: Open History Map aims to display the changes that happened in the past both from a political as well as a social and topographical point of view. the storage of these multi-dimensional changes has an enormous impact on the way the map is visualized. For this reason we needed to develop a caching system that was on one side flexible enough to display a non-quantizable dimension (time) and give us the possibility to pre-cache the whole system into a distributable package for easy local usage and possibly fast update of the package. The caching system itself is backend independent and defines a process to simplify access to a mix of discreet (x,y,z) and continuous (t) identifiers for independently variating geospatial datasets.

uk: вхід без авторизації


uk: Комп'ютерні науки

description: So far, we are storing and backing up with the aim of preservation our national heritage numerical data such as vector and raster databases, cartographic and geodetic works, old photography and other documents; whatever their nature and their physical supports are (numeric cartridge, floppy disks, optical magnetic disks, CD-R and DVD-R). In fact, resources are scares and Open Source gives us the advantage of using these resources more efficiently; we are taking advantages from them to make our organization better with QGIS and PostgreSQL/PostGIS to migrate from Shapefiles to rows. Our methodology might be elementary but as far as we believe, not only we would like to share our experiences from our lessons learned; but also developing countries might have same problematic as us regarding to how to preserve their old heritage data. At the end, we would like to present our future long term objective related to the creation of a metadata portal for rational management and optimal use of this archiving system.

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name: Case study of data storage for preservation of our archiving system at the National Geographic and Hydrographic Institute of Madagascar


uk: Комп'ютерні науки

description: In Brazil, we face a big challenge of not having the cycling infrastructure data openly available for our cities. We've developed the first cycling maps platform containing all Brazilian cities, leveraging the data and collaborativeness of OpenStreetMap (OSM). It's an open-source web application, free and accessible from computer or smartphone, aimed at both the average citizen who wants to know more about their city and researchers and policymakers that now have easy access to standardized data.

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name: CicloMapa: a web platform to democratize access to bike maps with OpenStreetMap


CityJSON: 3D city models for everyone

uk: Комп'ютерні науки

description: This is a presentation about CityJSON and the variety of open source tools that are available around it. CityJSON is a file format that can be used to exchange 3D city models. The talk will focus mainly on ninja, the QGIS plugin and the Blender plugin and some details about their developments and our plans for them will be shown. A brief overview of all software options will be presented and the suitability to different applications will be investigated. Also, certain other state-of-the-art developments regarding CityJSON will be mentioned (e.g. dissemination through OGC API Features, serving data through 3D Tiles and versioning of CityJSON models).

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uk: Комп'ютерні науки

description: Ciudad Limpia Valdivia is a Web and Mobile application which attempts to tackle some of the aforementioned issues for the Municipality of Valdivia in Chile. It is based on Free and Open Source Software and it is currently in the last stage of prototyping. Its development has incorporated geospatial analyses as well as some tools from computational intelligence and machine learning. In particular, approximately one year of the municipality's waste collection routes captured by Satellite Navigation Systems have been used to study the system’s behaviour for a target neighborhood. Also, surveys were conducted in that neighborhood to evaluate the interest in the application and to assess its potential impact. The waste collection routes dataset will now be used to train a system capable of estimating the arrival of the corresponding waste collection truck to a particular point selected by the user, using machine learning techniques. The “real-time” position of the trucks is shown in the application, thus giving feedback to the user of the current status of the service. Another important feature of the application is the illegal dumping reporting that will be received by the municipality. Ciudad Limpia Valdivia's goal is to be a bridge of communication between the citizens and the municipality. This paper will present the general concept design of the whole application, the survey’s results, the current development status and preliminary analyses of the routes dataset. It will also discuss the next stages in the project as well as future work after the prototyping phase is finished. Additionally, the discussion will address the importance of Free and Open Source Software in this kind of application with a social impact in the community.

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name: Ciudad Limpia Valdivia: A Mobile and Web based Smart Solution based on FOSS technology to support Municipal and household waste collection


uk: Комп'ютерні науки

description: As the rapid changes in the landscape of the coastal communities in the Philippine archipelago are undeniably felt brought by the strong typhoons from the Pacific ocean due to the rising global temperature or climate change. This study aims to visualize the accessibility of birthing facilities in the Philippines using the Department of Health’s (DOH) 2020 data that may be used on existing and open frameworks for climate adaptation and disaster adaptation considering that the Philippines ranks 5th among ASEAN nations based on a smart city analysis by the Innovation Cities program. This can be attributed to weak data infrastructure for centralized health systems and the lack of open data and access to information brought about by policy gaps in the National Freedom of Information act on disclosing public information that eventually affected the economy. Furthermore, this study aims to organize activities in various communities in the country on improving city planning and operations can make the Geographical Isolated and Disadvantaged Areas (GIDA) more accessible to government services and make the local government responsive to emerging needs of the population using the Sendai framework where the needs of improvements in maternal mortality in the country have largely stagnated ever since the early 90s.

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name: Climate Adaptation from the State of Birthing Facility Accessibility for Women in the Philippines in the year 2020


uk: Комп'ютерні науки

description: Current research is focusing extensively on building Cloud based open source solutions for big geospatial data analytics in Cloud computing environments. Massive amounts of geospatially-tagged movement and micro blogging data are collected and analysed regularly. Nevertheless, movement data per se is insufficient for uncovering the possibilities for decision-informing analytics which could help in reducing the undesirable effects of climate change. For instance, answering advanced queries such as 'what are the Top-5 districts in Buenos Aires capital city in Argentina in terms of vehicle mobility data where the index of Particulate Matters PM10 is greater than 50'. Other equivalent queries are required for assisting the strategic decisions regarding health-focused smart city policies. For instance, for insightful analytics that help municipalities in designing future city infrastructures that prioritize the health of citizens. For instance, by lowering the number of vehicles that are allowed entering into highly polluted zones in peak hours of the day. In addition, this information is useful for designing mobile interactive geo-maps for city lightweight dwellers in order to inform them which streets to avoid passing-through during specific hours of a day to avoid being subjected to high-levels of vehicle-caused air-borne pollutants such as PM10. However, answering such a query would require joining real-time mobility and meteorological data. Stock versions of the current Cloud-based open-source geospatial management systems do not include intrinsic solutions for such scenarios. Future research frontiers are expected to focus on designing geospatial Cloud open-source systems which allows integration with other contextual data. In this talk we will show case some of the few available Cloud-based big spatial data management frameworks and how they can be utilized as springboards for further development so that they become mature enough to support the decisions that aim to mitigate the mobility-caused climate change problems. We will walkthrough an example that shows how we could tweak an open-source geospatial framework for answering such multi-domain queries. We will conclude the talk with short discussion of open research frontiers in this direction. For instance, because the arriving data which needs to be ingested is huge , approximate query processing should be considered a priority, thus summarizing the data (for example histograms), could be even before forwarding it through the network to a Cloud-based deployment (for example, injecting samplers on the Edge devices near the source of data).

uk: вхід без авторизації

name: Cloud-based Geospatial open systems for mitigating climate change: research directions, challenges, and future perspectives


uk: Комп'ютерні науки

description: In this talk, we aim to present the geo-spatial community efforts of visualizing the geospatial spread of the COVID-19 pandemic in Romania since its beginning in March 2020 until the present time. Geo-spatial.org’s Covid-19 app, built entirely on FOSS, delivers correct, complete and updated official information on the virus spread in Romania. Our platform contains several maps and graphs depicting the different dimensions of the pandemic in Romania, ranging from confirmed cases/deaths/healed patients and related statistics, to hospital infrastructure, quarantine zones to pollution/mobility indexes, as well as other impact indicators of this epidemic in our country. Unfortunately, the Romanian authorities have failed in communicating the evolution of the COVID-19, resulting in numerous glitches in different reports. Thus, we have been volunteering our time to collect detailed information from the local/national media, compare it to the official reporting, sort it and deliver it in a structured manner. One year in the pandemic and the situation has not improved. With a notable, but a too limited exception, the Romanian authorities have not changed their opaque policy of interacting with the community. Thus, the COVID-19 geo-spatial.org team has continued to support the data mapping efforts and the open data community. The application is built using Node.js, PostgreSQL+PostGIS, R on the backend and OpenLayers, Angular, charts.js, Plotly and D3.js for the frontend. The source code is on GitHub, MIT licensed. The infrastructure is supported by Sage Group on AWS and by Carto.

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name: Using FOSS4G to track the COVID-19 evolution in Romania

name: Open Source Geospatial Foundation (OSGeo)


uk: Комп'ютерні науки

description: Too cluttered visualizations, confusing jargon, scary technology and communicating with the geo-data illiterate.. For many people, GIS technology is hard to understand. So how do we design and build a map application showing a huge amount of geo-data accompanied by the elaborate functionality to discovered it? Adding more and more buttons, layers, panels, pop-ups, legends, draw tools, scale-bars and GIS terms makes an application confusing, scary and technically hard to understand for the crowd.. These days we have an incredible amount of (open-source) geo-spatial data, remote sensing data and insights, plus the tools to share them with the world! But how do we communicate with an audience that does not understand our jargon like: “CSV” or “polygon”. Let alone know that the term “heat map”, means something completely different then what a cartographer means. I often find myself confused and tangled up in conversations where, as a GIS and cartographic professional, you speak a different language then your clients. Also working together with other web-developers and data-designers, shows me how we have to educate and direct them into our GIS world. Join the discussion about how to make user friendly, eye-blinking digestible, (non-technological scary), geo-data visualization for the web! I will show you some examples and share my opinion to get you started on thinking about what it means to share our geo-spatial insights with the world. We will follow different perspectives of the geo-data illiterate and get inspired by data visualization techniques, web design and interaction design.

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name: “Let’s put it on the map!” How to design a cuddly, eye-blinking digestible and accessible geo-data visualization?


3D Urban data in QGIS

uk: Комп'ютерні науки

description: 3D data become more and more common these days. Sensors like drones or "streetview" cars produce large amounts of images used to create 3D models through photogrammetry. 3D editing software also eases the production of 3D models, especially for BIM. AI systems begin to be ready to generate 3D objects of the world. It is now frequent for municipalities to acquire a full 3D dataset of all urban objects. These datasets pose a certain amount of issues : how to visualize them efficiently ? How to integrate these 3D data with other GIS data ? How to make them available on the web ? How to manage this data with my favorite GIS software ? We worked on these issues in order to be able to manage urban data efficiently in QGIS. Based on the emerging 3D capabilities of QGIS, we explored the 3D Tiles format and implemented it in QGIS, so as to be able to visualize large amount of urban data. In this presentation, we will present our work on urban data visualization, the state of the art in QGIS 3D visualization, and future work planned in this area. We will showcase the features with a real-world example.

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