Institution
Polytechnic University of Turin
Education•Turin, Piemonte, Italy•
About: Polytechnic University of Turin is a education organization based out in Turin, Piemonte, Italy. It is known for research contribution in the topics: Finite element method & Computer science. The organization has 11553 authors who have published 41395 publications receiving 789320 citations. The organization is also known as: POLITO & Politecnico di Torino.
Topics: Finite element method, Computer science, Nonlinear system, Context (language use), Population
Papers published on a yearly basis
Papers
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TL;DR: In this article, the theory of optimal algorithms for problems which cannot be solved exactly is investigated, which allows for the derivation of new and interesting results in parameter estimation and in time series prediction in situations where no reliable statistical hypothesis can be made on the functions and modeling errors involved.
Abstract: This paper deals with the theory of optimal algorithms for problems which cannot be solved exactly. The theory developed allows for the derivation of new and interesting results in parameter estimation and in time series prediction in situations where no reliable statistical hypothesis can be made on the functions and modeling errors involved, but only a bound on them is known, in particular, the derivation of computationally simple optimal algorithms for these two problems is investigated. The practical effectiveness of the algorithms obtained is illustrated by several numerical examples.
252 citations
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TL;DR: In this paper, generic features of eleven dimensional supergravity compactified down to five dimensions on an arbitrary Calabi-Yau threefold were considered and the possible relation with the heterotic string compactified on K 3 × S 1 was discussed.
251 citations
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TL;DR: This study could serve as a reference for managers who wish to initiate an evaluation cycle on the adoption and usage of big data technologies, and points out the most frequently recognized strategic, transactional, transformational and informational benefits and risks related to the usage ofbig data technologies by companies.
251 citations
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TL;DR: A multipurpose UAV (unmanned aerial vehicle) for mountain rescue operations designed to meet environmental requirements for mountainous terrain, assuring the capability of carrying different payloads such as avalanche beacon (ARTVA) with automatic signal recognition and path following algorithms.
Abstract: This paper presents a multipurpose UAV (unmanned aerial vehicle) for mountain rescue operations. The multi-rotors based flying platform and its embedded avionics are designed to meet environmental requirements for mountainous terrain such as low temperatures, high altitude and strong winds, assuring the capability of carrying different payloads (separately or together) such as: avalanche beacon (ARTVA) with automatic signal recognition and path following algorithms for the rapid location of snow-covered body; camera (visible and thermal) for search and rescue of missing persons on snow and in woods during the day or night; payload deployment to drop emergency kits or specific explosive cartridge for controlled avalanche detachment. The resulting small (less than 5 kg) UAV is capable of full autonomous flight (including take-off and landing) of a pre-programmed, or easily configurable, custom mission. Furthermore, the autopilot manages the sensors measurements (i.e. beacons or cameras) to update th...
251 citations
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TL;DR: An analytical model, the Wald analytical long‐distance dispersal (WALD) model, is introduced, based on simplifications to well‐established three‐dimensional Lagrangian stochastic approaches for turbulent scalar transport resulting in a two‐parameter Wald (or inverse Gaussian) distribution.
Abstract: We introduce an analytical model, the Wald analytical long‐distance dispersal (WALD) model, for estimating dispersal kernels of wind‐dispersed seeds and their escape probability from the canopy. The model is based on simplifications to well‐established three‐dimensional Lagrangian stochastic approaches for turbulent scalar transport resulting in a two‐parameter Wald (or inverse Gaussian) distribution. Unlike commonly used phenomenological models, WALD’s parameters can be estimated from the key factors affecting wind dispersal—wind statistics, seed release height, and seed terminal velocity—determined independently of dispersal data. WALD’s asymptotic power‐law tail has an exponent of −3/2, a limiting value verified by a meta‐analysis for a wide variety of measured dispersal kernels and larger than the exponent of the bivariate Student t‐test (2Dt). We tested WALD using three dispersal data sets on forest trees, heathland shrubs, and grassland forbs and compared WALD’s performance with that of ot...
250 citations
Authors
Showing all 11854 results
Name | H-index | Papers | Citations |
---|---|---|---|
Rodney S. Ruoff | 164 | 666 | 194902 |
Silvia Bordiga | 107 | 498 | 41413 |
Sergio Ferrara | 105 | 726 | 44507 |
Enrico Rossi | 103 | 606 | 41255 |
Stefano Passerini | 102 | 771 | 39119 |
James Barber | 102 | 642 | 42397 |
Markus J. Buehler | 95 | 609 | 33054 |
Dario Farina | 94 | 832 | 32786 |
Gabriel G. Katul | 91 | 506 | 34088 |
M. De Laurentis | 84 | 275 | 54727 |
Giuseppe Caire | 82 | 825 | 40344 |
Christophe Fraser | 76 | 264 | 29250 |
Erasmo Carrera | 75 | 829 | 23981 |
Andrea Califano | 75 | 305 | 31348 |
Massimo Inguscio | 74 | 427 | 21507 |