Directory of Open Access Journals (Sweden)
Etienne Barilier
2011-12-01
Full Text Available La relation entre la vie et l’œuvre, chez un artiste, n’est jamais une simple relation de cause à effet. L’on peut trouver, à l’origine du Voyage d’hiver de Schubert, comme à celle de la Rhapsodie pour alto de Brahms (dont les paroles, tirées d’un poème de Goethe, racontent elles aussi un voyage hivernal, des douleurs amoureuses. Mais ces deux œuvres transcendent les événements biographiques dont elles sont issues. échappant au narcissisme du moi romantique, elles traduisent deux expériences du temps, cyclique ou progressif, racontent deux voyages spirituels. La douleur d’exister y devient pure présence de la vie, et récit purifié.For an artist, the link between life and work is never a simple cause-effect relationship. The loving pain can be considered as the source of Schubert's Winterreise and of the Brahms Alto Rhapsody as well (the latter being based also upon a poem by Goethe, which tells also a winter journey. But these works transcend the life events from which they arise. Beyond the narcissism of the romantic self, they reflect two experiences of time, cyclical or progressive, and they tell two spiritual journeys. The pain of existence becomes a pure presence of life, and a purified story.
Borel, François
2015-01-01
Guinée : les Peuls du Wassolon — la danse des chasseurs. Enregistrements : Patrick Larue ; textes, traduction et commentaires : Patricia Pailleaud, Daniela Langer et Abdoulaye Diarra. 1 CD (DDD) OCORA C 558679, 1987. En coédition avec Les Films du Village. Nomades du désert : les Peulhs du Niger. Enregistrements, textes et production : Roselyne François et Manuel Gomes. 1 CD Playa Sound PS 65009, [1987]. Ces deux disques, publiés en 1987, ont un seul point commun, qui justifie d’ailleurs ce c...
Les techniques d’optimisation multicritère en optimisation à deux niveaux
Pieume, Calice Olivier
2011-01-01
Cette thèse aborde l'optimisation multicritère et l'optimisation à deux niveaux. L'investigation porte principalement sur les méthodes, les applications et les liens possibles entre les deux classes d'optimisation. Premièrement, nous développons une méthode de résolution des problèmes d'optimisation linéaire multicritère. Pour ce faire, nous introduisons une nouvelle caractérisation des faces efficaces et exploitons le résultat selon lequel l'ensemble des tableaux idéaux associés aux sommets ...
Re, Matteo; Valentini, Giorgio
2012-03-01
Ensemble methods are statistical and computational learning procedures reminiscent of the human social learning behavior of seeking several opinions before making any crucial decision. The idea of combining the opinions of different "experts" to obtain an overall “ensemble” decision is rooted in our culture at least from the classical age of ancient Greece, and it has been formalized during the Enlightenment with the Condorcet Jury Theorem[45]), which proved that the judgment of a committee is superior to those of individuals, provided the individuals have reasonable competence. Ensembles are sets of learning machines that combine in some way their decisions, or their learning algorithms, or different views of data, or other specific characteristics to obtain more reliable and more accurate predictions in supervised and unsupervised learning problems [48,116]. A simple example is represented by the majority vote ensemble, by which the decisions of different learning machines are combined, and the class that receives the majority of “votes” (i.e., the class predicted by the majority of the learning machines) is the class predicted by the overall ensemble [158]. In the literature, a plethora of terms other than ensembles has been used, such as fusion, combination, aggregation, and committee, to indicate sets of learning machines that work together to solve a machine learning problem [19,40,56,66,99,108,123], but in this chapter we maintain the term ensemble in its widest meaning, in order to include the whole range of combination methods. Nowadays, ensemble methods represent one of the main current research lines in machine learning [48,116], and the interest of the research community on ensemble methods is witnessed by conferences and workshops specifically devoted to ensembles, first of all the multiple classifier systems (MCS) conference organized by Roli, Kittler, Windeatt, and other researchers of this area [14,62,85,149,173]. Several theories have been
2002-01-01
NYYD Ensemble'i duost Traksmann - Lukk E.-S. Tüüri teosega "Symbiosis", mis on salvestatud ka hiljuti ilmunud NYYD Ensemble'i CDle. 2. märtsil Rakvere Teatri väikeses saalis ja 3. märtsil Rotermanni Soolalaos, kavas Tüür, Kaumann, Berio, Reich, Yun, Hauta-aho, Buckinx
Trichobezoar gastrique - à propos de deux cas
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Karim Ibn Majdoub Hassani
2010-09-01
Full Text Available Le trichobezoar gastrique est une affection rare (un peu plus d’une dizaine de cas dans la littérature, qui affecte essentiellement des jeunes filles perturbées par des désordres psychologiques. Les auteurs rapportent deux cas de jeunes filles, hospitalisées pour volumineuse masse épigastrique. La fibroscopie gastrique a posé le diagnostic de trichobezoar. Une exérèse chirurgicale a été réalisée à travers une gastrotomie, sans complications. Un suivi psychiatrique des deux patientes a été recommandé. Le trichobezoar gastrique désigne l’accumulation inhabituelle de cheveux au niveau de l’estomac. Son diagnostic est facile en présence d’un contexte de trichophagie évocateur. La fibroscopie œsogastroduodénale est l’examen de référence permettant la visualisation du trichobezoar dont le traitement est essentiellement chirurgical.
Energy Technology Data Exchange (ETDEWEB)
NONE
2004-01-01
The French Senate adopted on January 6, 2004 the project of law which authorizes the ratification of the agreement between France, the European atomic energy community and the IAEA about the enforcement of warranties in the framework of the treaty of interdiction of nuclear weapons in South America and in the Caribbean area signed in Vienna (Austria) on March 21, 2000. The text of this treaty is attached to this law. (J.S.)
Energy Technology Data Exchange (ETDEWEB)
NONE
2004-07-01
This report comments the reasons of the signature of the agreement between France, EURATOM and the IAEA for the reinforcement of IAEA's non-proliferation controls in the South America and Caribbean areas (law project no. 1329). The ratification of this agreement will have only few concrete consequences but will contribute to the promotion of non-proliferation and to the enforcement of warranties in the framework of the treaty of interdiction of nuclear weapons in South America and in the Caribbean area (signed in Vienna, Austria, on March 21, 2000). The commission of foreign affairs adopted this law project on March 3, 2004. (J.S.)
Composed ensembles of random unitary ensembles
Pozniak, M; Kus, M; Pozniak, Marcin; Zyczkowski, Karol; Kus, Marek
1997-01-01
Composed ensembles of random unitary matrices are defined via products of matrices, each pertaining to a given canonical circular ensemble of Dyson. We investigate statistical properties of spectra of some composed ensembles and demonstrate their physical relevance. We discuss also the methods of generating random matrices distributed according to invariant Haar measure on the orthogonal and unitary group.
Intrication de deux atomes en utilisant le blocage de Rydberg
Gaëtan, A.
2010-12-01
Considérons un système quantique constitué de deux sous-systèmes : on dit qu'il est dans un état intriqué s'il existe des corrélations quantiques entre les états de ces derniers. La compréhension et la mise en œuvre d'états intriqués ont de nombreuses applications (métrologie quantique, étude des systèmes fortement corrélés, traitement quantique de l'information, etc.) et constituent le contexte général de ce travail de thèse. Plus en détail, nous démontrons la réalisation d'un état intriqué de deux atomes neutres piégés indépendamment. Pour cela, nous exploitons le phénomène de blocage de Rydberg : lorsqu'on essaie d'exciter simultanément deux atomes séparés de quelques micromètres vers un état de Rydberg donné, la forte interaction entre atomes de Rydberg peut empêcher cette excitation simultanée. Dans ce cas, seul un des deux atomes est excité et l'on génère ainsi des corrélations quantiques entre les états des deux atomes, c'est-à-dire de l'intrication. Dans notre expérience, deux atomes de 87Rb dans l'état fondamental 5S1/2 sont piégés chacun dans une pince optique microscopique, à une distance relative de 4 micromètres. En réalisant des transitions entre l'état 5S1/2 et l'état de Rydberg 58D3/2 par des transitions à deux photons, nous obtenons un état intriqué des deux atomes dans les sous-niveaux |5S1/2, f = 1, mf = 1> et |5S1/2, f = 2, mf = 2>. Afin de quantifier l'intrication, nous mesurons la fidélité par rapport à l'état-cible en réalisant des transitions Raman entre ces deux sous-niveaux. La fidélité des paires d'atomes présentes à la fin de l'expérience est supérieure à la valeur seuil de 0,5, ce qui prouve la création d'un état intriqué.
L'entre-deux-guerres mathématique à travers les thèses soutenues en France
Leloup, Juliette
2009-01-01
L'entre-deux-guerres mathématique est étudié à partir des 242 thèses en sciences mathématiques soutenues en France. Ce corpus est analysé à trois niveaux différents. L'analyse de premier niveau consiste en une analyse quantitative de l'ensemble des doctorats. Elle permet de mettre en évidence les équilibres entre les différents domaines des sciences mathématiques et les différentes facultés de France, celle de Paris et celles de province. Les thèses soutenues en province sont alors étudiées s...
Online Learning with Ensembles
Urbanczik, R
1999-01-01
Supervised online learning with an ensemble of students randomized by the choice of initial conditions is analyzed. For the case of the perceptron learning rule, asymptotically the same improvement in the generalization error of the ensemble compared to the performance of a single student is found as in Gibbs learning. For more optimized learning rules, however, using an ensemble yields no improvement. This is explained by showing that for any learning rule $f$ a transform $\\tilde{f}$ exists,...
Deux approches du risque d'inondation en France
Directory of Open Access Journals (Sweden)
Bruno LEDOUX
1994-12-01
Full Text Available En France, les sources d’informations centralisées sur les risques naturels sont rares. Pourtant, une politique de prévention engagée par l’État nécessite de disposer d’une information à l’échelle nationale, d’évaluer les enjeux et de mobiliser les acteurs. Deux sources d’informations sont décrites et exploitées, qui permettent, par une représentation cartographique nationale, d’amorcer analyses et débats.
Les Sapotaceae de Madagascar, deux nouvelles espèces du genre Mimusops L.
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Richard Randrianaivo
2013-11-01
Full Text Available Members of the family Sapotaceae, occurring in Madagascar’s various forest types, are mostly known as nanto in local dialects; some of their cultural and social values are described here. While the circumscription of Mimusops is well-defined, the delimitation of species within the genus remains unclear and their identification is often difficult. A study of herbarium specimens assigned to this genus deposited in key herbaria, two in Madagascar (TAN and TEF and three outside the country (G, MO and P, revealed two new species: Mimusops boeniensis Randrianaivo sp. nov. and Mimusops masoalensis Randrianaivo sp. nov. This brings the number of Mimusops species recognized in Madagascar to 16. Both of these newly recognized species are illustrated, and detailed information is provided concerning their morphology and the differences between them and other members in the genus, as well as on their ecology and distribution. RÉSUMÉLes Sapotaceae de Madagascar sont rencontrés dans tous les types de forêt de l’île et sont connus sous un même nom vernaculaire sur l’ensemble du territoire, nanto. Les nanto sont importants dans la Société malgache et leur valeur culturelle est décrite ici. La circonscription taxinomique de Mimusops est bien définie. En revanche, la délimitation entre les différentes espèces au sein du genre reste confuse et l’identification des récoltes est souvent difficile. L’étude des spécimens d’herbier connus dans les herbiers nationaux (TAN et TEF et internationaux (G, MO et P nous a néanmoins permis de reconnaitre et de décrire deux nouvelles espèces : Mimusops boeniensis Randrianaivo sp. nov. et Mimusops masoalensis Randrianaivo sp. nov., le nombre d’espèces malgaches de Mimusops passant ainsi de 14 à 16. Cet article s’attache ensuite à fournir une description morphologique détaillée et illustrée de ces deux espèces ainsi que des renseignements sur leur distribution et leur écologie. Les diff
Multilevel ensemble Kalman filtering
Hoel, Håkon; Law, Kody J. H.; Tempone, Raul
2015-01-01
This work embeds a multilevel Monte Carlo (MLMC) sampling strategy into the Monte Carlo step of the ensemble Kalman filter (ENKF), thereby yielding a multilevel ensemble Kalman filter (MLENKF) which has provably superior asymptotic cost to a given accuracy level. The theoretical results are illustrated numerically.
Zerbino, Daniel R; Johnson, Nathan; Juetteman, Thomas; Sheppard, Dan; Wilder, Steven P; Lavidas, Ilias; Nuhn, Michael; Perry, Emily; Raffaillac-Desfosses, Quentin; Sobral, Daniel; Keefe, Damian; Gräf, Stefan; Ahmed, Ikhlak; Kinsella, Rhoda; Pritchard, Bethan; Brent, Simon; Amode, Ridwan; Parker, Anne; Trevanion, Steven; Birney, Ewan; Dunham, Ian; Flicek, Paul
2016-01-01
New experimental techniques in epigenomics allow researchers to assay a diversity of highly dynamic features such as histone marks, DNA modifications or chromatin structure. The study of their fluctuations should provide insights into gene expression regulation, cell differentiation and disease. The Ensembl project collects and maintains the Ensembl regulation data resources on epigenetic marks, transcription factor binding and DNA methylation for human and mouse, as well as microarray probe mappings and annotations for a variety of chordate genomes. From this data, we produce a functional annotation of the regulatory elements along the human and mouse genomes with plans to expand to other species as data becomes available. Starting from well-studied cell lines, we will progressively expand our library of measurements to a greater variety of samples. Ensembl's regulation resources provide a central and easy-to-query repository for reference epigenomes. As with all Ensembl data, it is freely available at http://www.ensembl.org, from the Perl and REST APIs and from the public Ensembl MySQL database server at ensembldb.ensembl.org. Database URL: http://www.ensembl.org. PMID:26888907
Du Lac de Geneve au Lac Baikal: deux metropoles en construction
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Guy Mettan
2006-08-01
'Annemasse dans un ensemble qui atteindrait environ un million d'habitants au total. Le lac Leman (Lac de Geneve faisant office de point commun entre ces villes, la region prendrait le nom de metropole lemanique ou de Bassin lemanique. Ce qui a pour avantage de ne pas mettre Geneve trop en evidence et de ne pas vexer les autres villes dont les noms seraient menaces de disparaitre au profit de Geneve.Pour reussir, ce rapprochement doit respecter quelques principes fondamentaux :1 developper les infrastructures communes et les moyens de communication entre les villes partenaires : la gestion de l''aeroport international de Geneve a ainsi ete ouvert a la France et aux representants de Lausanne. On projette de construire une troisieme voie pour l'autoroute et la ligne de chemin de fer qui relie Geneve a Lausanne. Sur le plan politique, les deputes des deux provin2ces militent dans la meme direction.2 respecter les identites traditionnelles et developper une identite commune autour d'un projet rassembleur. Le projet de fusion a echoue parce qu'il niait l'histoire et les traditions propres a chaque ville. Sans territoire et de tradition protestante calviniste, Geneve est universitaire, internationale, tres urbaine. Lausanne est lutherienne et plus enracinee dans une region agricole et viticole. La culture et l'economie, et surtout la fiscalite ne sont pas les memes. Cela reconnu, il convient malgre tout de developper des projets communs, qui rassemblent les habitants des deux regions et puissent peu a peu forger l'idee d'un destin commun. Pour Geneve et Lausanne, ce pourrait etre la vocation internationale, Geneve etant connue pour ses organisations internationales liees et le siege europeen de l'ONU tandis que Lausanne est devenue la capitale internationale du sport avec le CIO (Comite international olympique et federations sportives. Un deuxieme axe est de profiler l'ensemble de la metropole comme une region du savoir, avec ses universites, ses sieges d'entreprises multinationales et
A Classifier Ensemble of Binary Classifier Ensembles
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Sajad Parvin
2011-09-01
Full Text Available This paper proposes an innovative combinational algorithm to improve the performance in multiclass classification domains. Because the more accurate classifier the better performance of classification, the researchers in computer communities have been tended to improve the accuracies of classifiers. Although a better performance for classifier is defined the more accurate classifier, but turning to the best classifier is not always the best option to obtain the best quality in classification. It means to reach the best classification there is another alternative to use many inaccurate or weak classifiers each of them is specialized for a sub-space in the problem space and using their consensus vote as the final classifier. So this paper proposes a heuristic classifier ensemble to improve the performance of classification learning. It is specially deal with multiclass problems which their aim is to learn the boundaries of each class from many other classes. Based on the concept of multiclass problems classifiers are divided into two different categories: pairwise classifiers and multiclass classifiers. The aim of a pairwise classifier is to separate one class from another one. Because of pairwise classifiers just train for discrimination between two classes, decision boundaries of them are simpler and more effective than those of multiclass classifiers.The main idea behind the proposed method is to focus classifier in the erroneous spaces of problem and use of pairwise classification concept instead of multiclass classification concept. Indeed although usage of pairwise classification concept instead of multiclass classification concept is not new, we propose a new pairwise classifier ensemble with a very lower order. In this paper, first the most confused classes are determined and then some ensembles of classifiers are created. The classifiers of each of these ensembles jointly work using majority weighting votes. The results of these ensembles
Outils de perçage à deux moteurs coaxiaux
MORARU, George; FRANGEARD, Didier
2015-01-01
La présente invention concerne le domaine de l’usinage par enlèvement de matière. L’invention a ainsi pour objet une machine d’usinage et, plus particulièrement, une machine de perçage ou de fraisage. La machine à la particularité d’intégrer deux moteurs électriques destinés à contrôler les mouvements d’avance et de rotation d’un outil, tout en permettant une action d’assistance vibratoire, particulièrement utile pour le perçage de matériaux difficiles à usiner.
Die dramatiese discours in Pas de deux van Hugo Claus
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R. Vaughan
1990-05-01
Full Text Available Drama is action, verbal drama is speech action, and the dramatic text is subject to a similar set of rules as that governing the extra-literary communication situation. Dramatic irony, the very essence of drama itself, is generated by a dual, mutually interactive process of communication, whereby the audience is “written into” the text in a way distinguishing it from other literary genres, and by a systematic flouting of the rules governing communication. Pas de deux demonstrates the peculiar duality of dramatic discourse by its complex exploitation of the breakdown/non-breakdown of Grice’s Co-operative Principle-. communication/non-communication becomes reversible and, therefore, mutually constitutive concepts “releasing meaning” and conveying the “ideology” of this play.
National Aeronautics and Space Administration — Ensemble Data Mining Methods, also known as Committee Methods or Model Combiners, are machine learning methods that leverage the power of multiple models to achieve...
Un capteur d'extensométrie miniature à deux voies
Ferrand, J.C.
1982-01-01
Un capteur d’extensométrie miniature à deux voies a été réalisé. Il permet de mesurer les déformations dans deux directions perpendiculaires, et sa sensibilité est de 5 microdéformations. Il s’applique sur le bois sans collage.
Directory of Open Access Journals (Sweden)
Marin-Garcia Pablo
2010-05-01
Full Text Available Abstract Background The maturing field of genomics is rapidly increasing the number of sequenced genomes and producing more information from those previously sequenced. Much of this additional information is variation data derived from sampling multiple individuals of a given species with the goal of discovering new variants and characterising the population frequencies of the variants that are already known. These data have immense value for many studies, including those designed to understand evolution and connect genotype to phenotype. Maximising the utility of the data requires that it be stored in an accessible manner that facilitates the integration of variation data with other genome resources such as gene annotation and comparative genomics. Description The Ensembl project provides comprehensive and integrated variation resources for a wide variety of chordate genomes. This paper provides a detailed description of the sources of data and the methods for creating the Ensembl variation databases. It also explores the utility of the information by explaining the range of query options available, from using interactive web displays, to online data mining tools and connecting directly to the data servers programmatically. It gives a good overview of the variation resources and future plans for expanding the variation data within Ensembl. Conclusions Variation data is an important key to understanding the functional and phenotypic differences between individuals. The development of new sequencing and genotyping technologies is greatly increasing the amount of variation data known for almost all genomes. The Ensembl variation resources are integrated into the Ensembl genome browser and provide a comprehensive way to access this data in the context of a widely used genome bioinformatics system. All Ensembl data is freely available at http://www.ensembl.org and from the public MySQL database server at ensembldb.ensembl.org.
Le facteur temps ne sonne jamais deux fois
Klein, Etienne
2009-01-01
Chose déroutante, décidément, que le temps. Nous en parlons comme d'une notion familière, évidente, voire domestique, "gérable". Nous parlons même d'un "temps réel" pour évoquer l'instantanéité, c'est-à-dire le temps sur lequel nous n'avons aucune prise. Les physiciens, eux, l'ont couplé à l'espace, en ont fait une variable mathématique, abstraite, qu'ils intègrent dans des théories audacieuses, spectaculaires, si complexes qu'elles sont difficiles à traduire en langage courant. Certains disent même avoir identifié le moteur du temps. Quant aux philosophes, ils ne cessent depuis plus de deux millénaires de soumettre le temps au questionnement : est-il une sorte d'entité primitive, originaire, qui ne dériverait que d'elle-même? Ou procéderait-il au contraire d'une ou plusieurs autres entités, plus fondamentales: la relation de cause à effet, par exemple? Le temps s'écoule-t-il de lui-même ou a-t-il besoin des événements qui s'y déroulent pour passer? S'apparente-t-il au devenir,...
Imprinting and recalling cortical ensembles.
Carrillo-Reid, Luis; Yang, Weijian; Bando, Yuki; Peterka, Darcy S; Yuste, Rafael
2016-08-12
Neuronal ensembles are coactive groups of neurons that may represent building blocks of cortical circuits. These ensembles could be formed by Hebbian plasticity, whereby synapses between coactive neurons are strengthened. Here we report that repetitive activation with two-photon optogenetics of neuronal populations from ensembles in the visual cortex of awake mice builds neuronal ensembles that recur spontaneously after being imprinted and do not disrupt preexisting ones. Moreover, imprinted ensembles can be recalled by single- cell stimulation and remain coactive on consecutive days. Our results demonstrate the persistent reconfiguration of cortical circuits by two-photon optogenetics into neuronal ensembles that can perform pattern completion. PMID:27516599
DEFF Research Database (Denmark)
Hansen, Lars Kai; Salamon, Peter
1990-01-01
We propose several means for improving the performance an training of neural networks for classification. We use crossvalidation as a tool for optimizing network parameters and architecture. We show further that the remaining generalization error can be reduced by invoking ensembles of similar...... networks....
Shared Psychotic Disorder (Folie à Deux in Turkey
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Buket Cinemre
2009-09-01
Full Text Available Shared psychotic disorder or folie à deux is a rare and relatively unknown syndrome. Large case series are needed to find out and clarify the etiological factors and the phenomenology of shared psychotic disorder by comparing the cases from different society and cultures. In this study, we reviewed all reported cases of shared psychotic disorder that had been published or presented in Turkey since 1962. To reach this aim, we have searched Pubmed/Medline, ScienceDirect, Google Scholar, Ulakbim Turkish Medical Index, Turkish Psychiatric Index databases for published records originating from Turkey. We have also manually searched poster abstract books of congresses held in Turkey between 1962 and 2009. All cases eligible for inclusion into this study have been evaluated one by one and grouped as primary or secondary cases. The features of these cases were investigated for a number of variables including age, sex, educational level, occupation, the presence of shared delusion and hallucinations, diagnosis, management, onset of illness, family history, IQ, social isolation, the nature of the relationship and classification system used for diagnosis. The results have showed that the syndrome is more frequently observed among women, within same family members and between sisters. Social isolation was the most common risk factor in these patients and most patients shared hallucinations with their partners along with their delusions. Several secondary cases required antipsychotic drugs for the treatment of their symptoms. Though these features were inline with literature findings, the present findings from Turkish population were different from previous studies with regards to the presence of olfactory hallucinations, absence of grandiose delusions and the number of affected family members. The results mostly supported the challenges and discussions in western countries. To understand this most pathological form of interpersonal relationships
Rodin, Alexander E
2010-01-01
The algorithm of the ensemble pulsar time scale (PT$_{\\rm ens}$) based on the optimal Wiener filtration method has been proposed. This algorithm allows the separation of the contributions to the post-fit pulsar timing residuals of the atomic clock and pulsar itself. Filters were designed with the use of the cross-spectra of the timing residuals. The method has been applied to the timing data of six millisecond pulsars. Direct comparison with the classical method of the weighted average showed that use of the optimal Wiener filters before averaging allows noticeably to improve the fractional instability of the ensemble time scale. Application of the proposed method to the most stable millisecond pulsars with the fractional instability $\\sigma_z < 10^{-15}$ may improve the fractional instability of PT$_{\\rm ens}$ up to the level $\\sim 10^{-16}$.
Yin, D. S.; Gao, Y. P.; Zhao, S. H.
2016-05-01
Millisecond pulsars can generate another type of time scale that is totally independent of the atomic time scale, because the physical mechanisms of the pulsar time scale and the atomic time scale are quite different from each other. Usually the pulsar timing observational data are not evenly sampled, and the internals between data points range from several hours to more than half a month. What's more, these data sets are sparse. And all these make it difficult to generate an ensemble pulsar time scale. Hence, a new algorithm to calculate the ensemble pulsar time scale is proposed. Firstly, we use cubic spline interpolation to densify the data set, and make the intervals between data points even. Then, we employ the Vondrak filter to smooth the data set, and get rid of high-frequency noise, finally adopt the weighted average method to generate the ensemble pulsar time scale. The pulsar timing residuals represent clock difference between the pulsar time and atomic time, and the high precision pulsar timing data mean the clock difference measurement between the pulsar time and atomic time with a high signal to noise ratio, which is fundamental to generate pulsar time. We use the latest released NANOGRAV (North American Nanohertz Observatory for Gravitational Waves) 9-year data set to generate the ensemble pulsar time scale. This data set is from the newest NANOGRAV data release, which includes 9-year observational data of 37 millisecond pulsars using the 100-meter Green Bank telescope and 305-meter Arecibo telescope. We find that the algorithm used in this paper can lower the influence caused by noises in timing residuals, and improve long-term stability of pulsar time. Results show that the long-term (> 1 yr) frequency stability of the pulsar time is better than 3.4×10-15.
Effective Visualization of Temporal Ensembles.
Hao, Lihua; Healey, Christopher G; Bass, Steffen A
2016-01-01
An ensemble is a collection of related datasets, called members, built from a series of runs of a simulation or an experiment. Ensembles are large, temporal, multidimensional, and multivariate, making them difficult to analyze. Another important challenge is visualizing ensembles that vary both in space and time. Initial visualization techniques displayed ensembles with a small number of members, or presented an overview of an entire ensemble, but without potentially important details. Recently, researchers have suggested combining these two directions, allowing users to choose subsets of members to visualization. This manual selection process places the burden on the user to identify which members to explore. We first introduce a static ensemble visualization system that automatically helps users locate interesting subsets of members to visualize. We next extend the system to support analysis and visualization of temporal ensembles. We employ 3D shape comparison, cluster tree visualization, and glyph based visualization to represent different levels of detail within an ensemble. This strategy is used to provide two approaches for temporal ensemble analysis: (1) segment based ensemble analysis, to capture important shape transition time-steps, clusters groups of similar members, and identify common shape changes over time across multiple members; and (2) time-step based ensemble analysis, which assumes ensemble members are aligned in time by combining similar shapes at common time-steps. Both approaches enable users to interactively visualize and analyze a temporal ensemble from different perspectives at different levels of detail. We demonstrate our techniques on an ensemble studying matter transition from hadronic gas to quark-gluon plasma during gold-on-gold particle collisions. PMID:26529728
Effective Visualization of Temporal Ensembles.
Hao, Lihua; Healey, Christopher G; Bass, Steffen A
2016-01-01
An ensemble is a collection of related datasets, called members, built from a series of runs of a simulation or an experiment. Ensembles are large, temporal, multidimensional, and multivariate, making them difficult to analyze. Another important challenge is visualizing ensembles that vary both in space and time. Initial visualization techniques displayed ensembles with a small number of members, or presented an overview of an entire ensemble, but without potentially important details. Recently, researchers have suggested combining these two directions, allowing users to choose subsets of members to visualization. This manual selection process places the burden on the user to identify which members to explore. We first introduce a static ensemble visualization system that automatically helps users locate interesting subsets of members to visualize. We next extend the system to support analysis and visualization of temporal ensembles. We employ 3D shape comparison, cluster tree visualization, and glyph based visualization to represent different levels of detail within an ensemble. This strategy is used to provide two approaches for temporal ensemble analysis: (1) segment based ensemble analysis, to capture important shape transition time-steps, clusters groups of similar members, and identify common shape changes over time across multiple members; and (2) time-step based ensemble analysis, which assumes ensemble members are aligned in time by combining similar shapes at common time-steps. Both approaches enable users to interactively visualize and analyze a temporal ensemble from different perspectives at different levels of detail. We demonstrate our techniques on an ensemble studying matter transition from hadronic gas to quark-gluon plasma during gold-on-gold particle collisions.
Deux nouvelles lèvres de Cassidae au PPNB
Directory of Open Access Journals (Sweden)
Gaëlle Le Dosseur
2008-03-01
Full Text Available En 2008, deux nouvelles lèvres de Cassidae ont été mises au jour sur deux sites néolithiques (Néolithique Précéramique B : PPNB du Levant Sud : Beisamoun et Yiftahel. Il s’agit d’objets façonnés sur la lèvre externe de coquillages méditerranéens appelés Phalium granulatum. Des aménagements pour la suspension (perforations aux extrémités laissent penser que ces objets ont été utilisés comme pendentifs ou qu’ils ont été cousus sur des vêtements ou des accessoires. Ces découvertes alimentent la discussion sur l’approvisionnement en matières premières mais aussi sur les parentés culturelles et les singularités de chaque site à cette époque. Si l’usage de lèvres de Cassidae est partagé par de nombreux sites PPNB, les modes de fabrication et de suspension ne sont pas strictement les mêmes sur tous. Ces variations reflètent-elles une évolution des modes de suspension dans le temps (au cours du PPNB moyen/récent ? Ou révèlent-elles des choix « contemporains » distincts, qui contribueraient à définir l’identité propre de chaque site ? Après le Néolithique, l’usage des lèvres de Cassidae se poursuit aux Âges des métaux. À cette époque plus qu’au Néolithique, ces objets sont retrouvés dans des contextes funéraires. Il est difficile de savoir si cette situation résulte des méthodes de fouilles distinctes adoptées sur les sites néolithiques et sur ceux des Âges des métaux ou si elle est une réalité archéologique. Dans le second cas, on pourrait proposer que le sens donné aux lèvres de Cassidae, en partie reflété par le lieu de dépôt, a pu évoluer avec le temps.Two more cassid lips for the PPNBBeisamoun and Yiftahel In 2008, two new cassid lips have been found on two Neolithic sites (Pre Pottery Neolithic B, in the Southern Levant: Beisamoun and Yiftahel. These objects are shaped on the external lip of shells coming from the Mediterranean Sea and called Phalium
L’histoire du malade. Croisement de deux anthropologies
Directory of Open Access Journals (Sweden)
Pauline Labey
2010-05-01
Full Text Available L’histoire des malades peut intégrer l’anthropologie de deux manières. Tout d’abord, elle peut utiliser l’anthropologie comme source de méthode et de questionnement. En écrivant une histoire de l’homme malade, l’historien se doit de saisir une situation corporelle individuelle et ses conséquences sociales dans un quotidien. Il interroge donc une société sur son rapport au corps, lorsqu’il est atteint par le mal, et sur son rapport à la norme, lorsqu’on s’en écarte. Ensuite, l’histoire des malades peut porter sur l’anthropologie comme discours, produit dans une période donnée. L’anthropologie est dès lors abordée en tant qu’objet de recherche. En croisant pratique et discours, il est possible de saisir les conséquences individuelles de l’évènement maladie. Pour le Moyen Age central, enjeux spirituels et enjeux institutionnels peuvent s’éclairer, grâce à cette double utilisation de l’anthropologie.The history of those who suffer from illness may integrate anthropology in two ways. First, anthropology can be used as method and a mode of questioning. In writing history of the sick, the historian must grasp a particular physiological situation and its social consequences in everyday life. He must question a society about its relationship with the body when it is affected by illness, and about what happens when an individual departs from the norm of health. Second, a history of the sick can use anthropology as a discourse, the product of a given period. In this case, anthropology is used as a subject of research. Combining practice and discourse, it is possible to apprehend individual consequences of an illness-event. This dual use of anthropology may clarify the spiritual and institutional consequences of illness in the central Middle Ages.La storia dei malati può integrare l’antropologia in due modi. In primo luogo, può utilizzare l’antropologia come fonte di metodi e di interrogativi
Multilevel ensemble Kalman filtering
Hoel, Hakon
2016-06-14
This work embeds a multilevel Monte Carlo sampling strategy into the Monte Carlo step of the ensemble Kalman filter (EnKF) in the setting of finite dimensional signal evolution and noisy discrete-time observations. The signal dynamics is assumed to be governed by a stochastic differential equation (SDE), and a hierarchy of time grids is introduced for multilevel numerical integration of that SDE. The resulting multilevel EnKF is proved to asymptotically outperform EnKF in terms of computational cost versus approximation accuracy. The theoretical results are illustrated numerically.
Tibetan Song and Dance Ensemble
Institute of Scientific and Technical Information of China (English)
1996-01-01
THE chief members of the TibetanSong and Dance Ensemble areTibetan,but also include Hui,Lhoba and Monba artists.This ensemble mainly performs Tibetan traditional music,dance and Tibetan opera.Programs can be divided into three categories,folk,traditional palace and monastery styles.The program of this ensemble includes the Tibetan symphony instrumental the Tibetan symphony instrumental suite "Ceremony in the Snowy Region."the palace dance "Karer"passages of the traditional Tibetan
Le lupus systémique juvénile familial: à propos de deux familles
Krich, Sanaa; Inani, Kawtar; Meziane, Mariame; Souilmi, Fatima Zohta; Atmani, Samir; Hida, Mustapha; Harmouch, Taoufik; Amarti, Afaf; Mernissi, Fatima Zohra
2015-01-01
Le lupus érythémateux systémique (LES) juvénile est une connectivite rare, d’évolution plus sévère que chez l'adulte. Les cas familiaux sont exceptionnels. Il s'agissait de deux familles (5 patients atteints), chez qui on a objectivé un LES juvénile chez deux sæurs âgées de 14 ans et 6 ans respectivement chez la première famille, deux frères, âgés de 20 ans et 6 ans respectivement plus une sæur âgée de 10 ans chez la deuxième famille. Dans tout les cas le diagnostic de lupus systémique a été ...
DEFF Research Database (Denmark)
2004-01-01
Within the framework of the PSO-Ensemble project (FU2101) a demo application has been created. The application use ECMWF ensemble forecasts. Two instances of the application are running; one for Nysted Offshore and one for the total production (except Horns Rev) in the Eltra area. The output is...
Representative Ensembles in Statistical Mechanics
V. I. YUKALOV
2007-01-01
The notion of representative statistical ensembles, correctly representing statistical systems, is strictly formulated. This notion allows for a proper description of statistical systems, avoiding inconsistencies in theory. As an illustration, a Bose-condensed system is considered. It is shown that a self-consistent treatment of the latter, using a representative ensemble, always yields a conserving and gapless theory.
Botnet analysis using ensemble classifier
Directory of Open Access Journals (Sweden)
Anchit Bijalwan
2016-09-01
Full Text Available This paper analyses the botnet traffic using Ensemble of classifier algorithm to find out bot evidence. We used ISCX dataset for training and testing purpose. We extracted the features of both training and testing datasets. After extracting the features of this dataset, we bifurcated these features into two classes, normal traffic and botnet traffic and provide labelling. Thereafter using modern data mining tool, we have applied ensemble of classifier algorithm. Our experimental results show that the performance for finding bot evidence using ensemble of classifiers is better than single classifier. Ensemble based classifiers perform better than single classifier by either combining powers of multiple algorithms or introducing diversification to the same classifier by varying input in bot analysis. Our results are showing that by using voting method of ensemble based classifier accuracy is increased up to 96.41% from 93.37%.
On Ensemble Nonlinear Kalman Filtering with Symmetric Analysis Ensembles
Luo, Xiaodong
2010-09-19
The ensemble square root filter (EnSRF) [1, 2, 3, 4] is a popular method for data assimilation in high dimensional systems (e.g., geophysics models). Essentially the EnSRF is a Monte Carlo implementation of the conventional Kalman filter (KF) [5, 6]. It is mainly different from the KF at the prediction steps, where it is some ensembles, rather then the means and covariance matrices, of the system state that are propagated forward. In doing this, the EnSRF is computationally more efficient than the KF, since propagating a covariance matrix forward in high dimensional systems is prohibitively expensive. In addition, the EnSRF is also very convenient in implementation. By propagating the ensembles of the system state, the EnSRF can be directly applied to nonlinear systems without any change in comparison to the assimilation procedures in linear systems. However, by adopting the Monte Carlo method, the EnSRF also incurs certain sampling errors. One way to alleviate this problem is to introduce certain symmetry to the ensembles, which can reduce the sampling errors and spurious modes in evaluation of the means and covariances of the ensembles [7]. In this contribution, we present two methods to produce symmetric ensembles. One is based on the unscented transform [8, 9], which leads to the unscented Kalman filter (UKF) [8, 9] and its variant, the ensemble unscented Kalman filter (EnUKF) [7]. The other is based on Stirling’s interpolation formula (SIF), which results in the divided difference filter (DDF) [10]. Here we propose a simplified divided difference filter (sDDF) in the context of ensemble filtering. The similarity and difference between the sDDF and the EnUKF will be discussed. Numerical experiments will also be conducted to investigate the performance of the sDDF and the EnUKF, and compare them to a well‐established EnSRF, the ensemble transform Kalman filter (ETKF) [2].
The Ensembl gene annotation system.
Aken, Bronwen L; Ayling, Sarah; Barrell, Daniel; Clarke, Laura; Curwen, Valery; Fairley, Susan; Fernandez Banet, Julio; Billis, Konstantinos; García Girón, Carlos; Hourlier, Thibaut; Howe, Kevin; Kähäri, Andreas; Kokocinski, Felix; Martin, Fergal J; Murphy, Daniel N; Nag, Rishi; Ruffier, Magali; Schuster, Michael; Tang, Y Amy; Vogel, Jan-Hinnerk; White, Simon; Zadissa, Amonida; Flicek, Paul; Searle, Stephen M J
2016-01-01
The Ensembl gene annotation system has been used to annotate over 70 different vertebrate species across a wide range of genome projects. Furthermore, it generates the automatic alignment-based annotation for the human and mouse GENCODE gene sets. The system is based on the alignment of biological sequences, including cDNAs, proteins and RNA-seq reads, to the target genome in order to construct candidate transcript models. Careful assessment and filtering of these candidate transcripts ultimately leads to the final gene set, which is made available on the Ensembl website. Here, we describe the annotation process in detail.Database URL: http://www.ensembl.org/index.html. PMID:27337980
Diurnal Ensemble Surface Meteorology Statistics
U.S. Environmental Protection Agency — Excel file containing diurnal ensemble statistics of 2-m temperature, 2-m mixing ratio and 10-m wind speed. This Excel file contains figures for Figure 2 in the...
The entropy of network ensembles
Bianconi, Ginestra
2008-01-01
In this paper we generalize the concept of random networks to describe networks with non trivial features by a statistical mechanics approach. This framework is able to describe ensembles of undirected, directed as well as weighted networks. These networks might have not trivial community structure or, in the case of networks embedded in a given space, non trivial distance dependence of the link probability. These ensembles are characterized by their entropy which evaluate the cardinality of ...
Similarity measures for protein ensembles
DEFF Research Database (Denmark)
Lindorff-Larsen, Kresten; Ferkinghoff-Borg, Jesper
2009-01-01
Analyses of similarities and changes in protein conformation can provide important information regarding protein function and evolution. Many scores, including the commonly used root mean square deviation, have therefore been developed to quantify the similarities of different protein conformations...... a synthetic example from molecular dynamics simulations. We then apply the algorithms to revisit the problem of ensemble averaging during structure determination of proteins, and find that an ensemble refinement method is able to recover the correct distribution of conformations better than standard single...
Deformed Ginibre ensembles and integrable systems
Energy Technology Data Exchange (ETDEWEB)
Orlov, A.Yu., E-mail: orlovs@ocean.ru
2014-01-17
We consider three Ginibre ensembles (real, complex and quaternion-real) with deformed measures and relate them to known integrable systems by presenting partition functions of these ensembles in form of fermionic expectation values. We also introduce double deformed Dyson–Wigner ensembles and compare their fermionic representations with those of Ginibre ensembles.
Mise au point de deux nouveaux matériaux à base de cobalt
CEA
2014-01-01
Des chercheurs du CEA, du CNRS, du Collège de France et de l’Université de Grenoble ont mis au point deux nouveaux matériaux à base de cobalt capables de remplacer le platine, métal rare et cher, dans la production d’hydrogène à partir d’eau (électrolyse). L’un peut fonctionner en solution aqueuse de pH neutre. Le second constitue le premier matériau catalytique « commutable » et sans métaux nobles jamais créé capable d’intervenir dans les deux réactions chimiques essentielles à l’électrolys...
Tuberculose multirésistante chez l'enfant: à propos de deux cas
Slimani, Hajar; Bricha, Myriem; Sqalli, Fatima-Ezzahra; Hammi, Sanaa; Bourkadi, Jamal-Eddine
2016-01-01
La tuberculose multirésistante chez l'enfant est une forme grave de la tuberculose, présentant un problème majeur de santé surtout dans les pays en voie de développement. Nous présentons le cas de deux enfants suivis dans notre formation pour tuberculose multirésistante mis sous schéma thérapeutique de deuxième ligne. PMID:27279953
Note sur deux espèces de Lepidocyclina des Indes Néerlandaises
Schlumberger, C.
1899-01-01
Je dois à l’obligeance de Monsieur K. MARTIN professeur de Géologie à l’Université de Leiden l’envoi pour ma collection de foraminifères de quelques doubles des roches rapportées de Java par Monsieur VERBEEK et j’ai eu la bonne fortune d’y rencontrer deux espèces d’Orbitoïdes du sous-genre Lepidocyc
Sur deux espèces D'anthessius (Copepoda) des Indes Orientales
Stock, J.H.
1964-01-01
Les espèces du genre Anthessius Della Valle, 1880, sont associées de façon très préférentielle à deux classes de Mollusques: les Pélécypodes et les Gastéropodes. Notre connaissance taxonomique du genre progresse actuellement de manière très rapide. Il y a cinq ans seulement, on ne connaissait que 11
Tuberculose multirésistante chez l'enfant: à propos de deux cas
Slimani, Hajar; Bricha, Myriem; Sqalli, Fatima-Ezzahra; Sanaa HAMMI; Bourkadi, Jamal-Eddine
2016-01-01
La tuberculose multirésistante chez l'enfant est une forme grave de la tuberculose, présentant un problème majeur de santé surtout dans les pays en voie de développement. Nous présentons le cas de deux enfants suivis dans notre formation pour tuberculose multirésistante mis sous schéma thérapeutique de deuxième ligne.
Le chondrosarcome naso-sinusien: à propos de deux cas et revue de la literature
Touati, Mohamed Mliha; Chihani, Mehdi; Darouassi, Youssef; Lakouichmi, Mohammed; Tourabi, Khalid; Bouaity, Brahim; Ammar, Haddou
2014-01-01
Le chondrosarcome est une tumeur maligne très destructrice d'origine cartilagineuse, osseuse et mesnchymateuse. La localisation au niveau de la tête et cou est rare et le siège naso sinusien est encore plus rare. Nous rapportons deux observations de chondrosarcome du sinus maxillaire droit et sphéno ethmoïdale. Le but de notre travail est de montrer à travers ces deux cas cliniques, l'intérêt de la tomodensitométrie et de la résonance magnétique dans la présemption diagnostique en corrélation avec la clinique et l'endoscopie,de discuter le choix de la voix et la technique d'abord chirurgical et la surveillance post opératoire. A travers ces deux observations nous soulignerons les difficultés que pose cette tumeur à l'anatomopathologiste pour différencier entre chondrome et chondrosarcome. PMID:25810801
Ensemble algorithms in reinforcement learning.
Wiering, Marco A; van Hasselt, Hado
2008-08-01
This paper describes several ensemble methods that combine multiple different reinforcement learning (RL) algorithms in a single agent. The aim is to enhance learning speed and final performance by combining the chosen actions or action probabilities of different RL algorithms. We designed and implemented four different ensemble methods combining the following five different RL algorithms: Q-learning, Sarsa, actor-critic (AC), QV-learning, and AC learning automaton. The intuitively designed ensemble methods, namely, majority voting (MV), rank voting, Boltzmann multiplication (BM), and Boltzmann addition, combine the policies derived from the value functions of the different RL algorithms, in contrast to previous work where ensemble methods have been used in RL for representing and learning a single value function. We show experiments on five maze problems of varying complexity; the first problem is simple, but the other four maze tasks are of a dynamic or partially observable nature. The results indicate that the BM and MV ensembles significantly outperform the single RL algorithms. PMID:18632380
Estimating preselected and postselected ensembles
Energy Technology Data Exchange (ETDEWEB)
Massar, Serge [Laboratoire d' Information Quantique, C.P. 225, Universite libre de Bruxelles (U.L.B.), Av. F. D. Rooselvelt 50, B-1050 Bruxelles (Belgium); Popescu, Sandu [H. H. Wills Physics Laboratory, University of Bristol, Tyndall Avenue, Bristol BS8 1TL (United Kingdom); Hewlett-Packard Laboratories, Stoke Gifford, Bristol BS12 6QZ (United Kingdom)
2011-11-15
In analogy with the usual quantum state-estimation problem, we introduce the problem of state estimation for a pre- and postselected ensemble. The problem has fundamental physical significance since, as argued by Y. Aharonov and collaborators, pre- and postselected ensembles are the most basic quantum ensembles. Two new features are shown to appear: (1) information is flowing to the measuring device both from the past and from the future; (2) because of the postselection, certain measurement outcomes can be forced never to occur. Due to these features, state estimation in such ensembles is dramatically different from the case of ordinary, preselected-only ensembles. We develop a general theoretical framework for studying this problem and illustrate it through several examples. We also prove general theorems establishing that information flowing from the future is closely related to, and in some cases equivalent to, the complex conjugate information flowing from the past. Finally, we illustrate our approach on examples involving covariant measurements on spin-1/2 particles. We emphasize that all state-estimation problems can be extended to the pre- and postselected situation. The present work thus lays the foundations of a much more general theory of quantum state estimation.
CME Ensemble Forecasting - A Primer
Pizzo, V. J.; de Koning, C. A.; Cash, M. D.; Millward, G. H.; Biesecker, D. A.; Codrescu, M.; Puga, L.; Odstrcil, D.
2014-12-01
SWPC has been evaluating various approaches for ensemble forecasting of Earth-directed CMEs. We have developed the software infrastructure needed to support broad-ranging CME ensemble modeling, including composing, interpreting, and making intelligent use of ensemble simulations. The first step is to determine whether the physics of the interplanetary propagation of CMEs is better described as chaotic (like terrestrial weather) or deterministic (as in tsunami propagation). This is important, since different ensemble strategies are to be pursued under the two scenarios. We present the findings of a comprehensive study of CME ensembles in uniform and structured backgrounds that reveals systematic relationships between input cone parameters and ambient flow states and resulting transit times and velocity/density amplitudes at Earth. These results clearly indicate that the propagation of single CMEs to 1 AU is a deterministic process. Thus, the accuracy with which one can forecast the gross properties (such as arrival time) of CMEs at 1 AU is determined primarily by the accuracy of the inputs. This is no tautology - it means specifically that efforts to improve forecast accuracy should focus upon obtaining better inputs, as opposed to developing better propagation models. In a companion paper (deKoning et al., this conference), we compare in situ solar wind data with forecast events in the SWPC operational archive to show how the qualitative and quantitative findings presented here are entirely consistent with the observations and may lead to improved forecasts of arrival time at Earth.
Ensemble Equivalence for Distinguishable Particles
Directory of Open Access Journals (Sweden)
Antonio Fernández-Peralta
2016-07-01
Full Text Available Statistics of distinguishable particles has become relevant in systems of colloidal particles and in the context of applications of statistical mechanics to complex networks. In this paper, we present evidence that a commonly used expression for the partition function of a system of distinguishable particles leads to huge fluctuations of the number of particles in the grand canonical ensemble and, consequently, to nonequivalence of statistical ensembles. We will show that the alternative definition of the partition function including, naturally, Boltzmann’s correct counting factor for distinguishable particles solves the problem and restores ensemble equivalence. Finally, we also show that this choice for the partition function does not produce any inconsistency for a system of distinguishable localized particles, where the monoparticular partition function is not extensive.
Excitation energies from ensemble DFT
Borgoo, Alex; Teale, Andy M.; Helgaker, Trygve
2015-12-01
We study the evaluation of the Gross-Oliveira-Kohn expression for excitation energies E1-E0=ɛ1-ɛ0+∂E/xc,w[ρ] ∂w | ρ =ρ0. This expression gives the difference between an excitation energy E1 - E0 and the corresponding Kohn-Sham orbital energy difference ɛ1 - ɛ0 as a partial derivative of the exchange-correlation energy of an ensemble of states Exc,w[ρ]. Through Lieb maximisation, on input full-CI density functions, the exchange-correlation energy is evaluated accurately and the partial derivative is evaluated numerically using finite difference. The equality is studied numerically for different geometries of the H2 molecule and different ensemble weights. We explore the adiabatic connection for the ensemble exchange-correlation energy. The latter may prove useful when modelling the unknown weight dependence of the exchange-correlation energy.
Ensemble teleportation under suboptimal conditions
International Nuclear Information System (INIS)
The possibility of teleportation is certainly the most interesting consequence of quantum non-separability. In the present paper, the feasibility of teleportation is examined on the basis of the rigorous ensemble interpretation of quantum mechanics if non-ideal constraints are imposed on the teleportation scheme. Importance is attached both to the case of noisy Einstein-Podolsky-Rosen (EPR) ensembles and to the conditions under which automatic teleportation is still possible. The success of teleportation is discussed using a new fidelity measure which avoids the weaknesses of previous proposals
The Partition Ensemble Fallacy Fallacy
Nemoto, K; Nemoto, Kae; Braunstein, Samuel L.
2002-01-01
The Partition Ensemble Fallacy was recently applied to claim no quantum coherence exists in coherent states produced by lasers. We show that this claim relies on an untestable belief of a particular prior distribution of absolute phase. One's choice for the prior distribution for an unobservable quantity is a matter of `religion'. We call this principle the Partition Ensemble Fallacy Fallacy. Further, we show an alternative approach to construct a relative-quantity Hilbert subspace where unobservability of certain quantities is guaranteed by global conservation laws. This approach is applied to coherent states and constructs an approximate relative-phase Hilbert subspace.
Ensemble algorithms in reinforcement learning
Wiering, Marco A; van Hasselt, Hado
2008-01-01
This paper describes several ensemble methods that combine multiple different reinforcement learning (RL) algorithms in a single agent. The aim is to enhance learning speed and final performance by combining the chosen actions or action probabilities of different RL algorithms. We designed and imple
Multimodel ensembles of wheat growth
DEFF Research Database (Denmark)
Martre, Pierre; Wallach, Daniel; Asseng, Senthold;
2015-01-01
Crop models of crop growth are increasingly used to quantify the impact of global changes due to climate or crop management. Therefore, accuracy of simulation results is a major concern. Studies with ensembles of crop models can give valuable information about model accuracy and uncertainty, but ...
Comparaison de deux modèles de comportement viscoplastique à variables internes
Lévêque, E.; Delobelle, P.
1994-02-01
The aim of this paper is about the comparison between two unified models with internal variables which have been established with 17-12MoSPH austenitic stainless steel experimental results. One is developed at the National Office of Aerospatial Research and Studies, the other, at the Applied Mechanical Laboratory of Besançon. The study proved their validity when applicated to a well known experimental loadings at high temperature, 500-600 °C. The two models report correctly the phenomena corresponding to classical loadings like monotonic traction, creep and cyclic hardening. However, there are important differences about transient creep and cyclic hardening under stress control. In the present state of the models, the progressive strain under uni or bidirectional loading (1D and 2D ratchet) is strongly overestimated. However, it is shown that it is possible to correctly describe the two types of progressive strain after taking into account a few modifications in the definition of the evolutionary laws for the tensorial variables of kinematical hardenings. Finally, the comparison does not allow to prefer one of the two models. Il s'agit dans cet article de comparer deux modèles viscoplastiques unifiés à variables internes établis à partir de résultats expérimentaux concernant l'acier austénitique inoxydable 17-12MoSPH ; l'un développé à l'Office National d'Etudes et Recherches Aérospatiales, l'autre au Laboratoire de Mécanique Appliquée de Besançon. L'étude a permis la validation des deux modèles par rapport à une base de données expérimentales aux températures élevées, 550 et 600 °C. Les deux modèles traduisent correctement les phénomènes inhérents à des chargements, classiques de traction monotone, fluage et d'écrouissage cyclique à déformation imposée. Par contre, on note des différences importantes en ce qui concerne l'hésitation au fluage et les essais cycliques à contrainte imposée. Dans leur version initiale les deux mod
Global Ensemble Forecast System (GEFS) [1 Deg.
National Oceanic and Atmospheric Administration, Department of Commerce — The Global Ensemble Forecast System (GEFS) is a weather forecast model made up of 21 separate forecasts, or ensemble members. The National Centers for Environmental...
Territorialisation et circulation des échanges sociaux dans deux sites de la banlieue parisienne
Benveniste, Annie
2000-01-01
L'article analyse la construction de nouvelles territorialités en liaison avec le développement des mouvements ethno-religieux. Deux sites ont été choisis qui avaient fait l'objet d'une recherche sur la ségrégation résidentielle : Sarcelles et Garges-les-Gonesse. L'analyse porte d'abord sur les transformations des espaces, leur appropriation et la recombinaison du public et du privé qui permet de s'émanciper des contraintes de la relégation. Elle porte ensuite sur les nouvelles formes de soli...
Modélisation et simulation des usagers deux roues motorisés dans ARCHISIM
Bonte, L; ESPIE, S; Mathieu, P.
2006-01-01
Le but de ce travail est de proposer une approche permettant la simulation des usagers de deux-roues motorisés dans un modèle de trafic existant : ARCHISIM. ARCHISIM est un projet de l'INRETS qui a pour but de simuler l'évolution du trafic comme étant le résultat des différents comportements des acteurs de la simulation. Nous montrerons les différences avec les autres usagers de la route (automobilistes, piétons) et pourquoi ces comportements ne sont pas applicables, dans le cadre d'ARCHISIM,...
Optimisation de la fonction MLI d’un onduleur de tension deux-niveaux
Capitaneanu, Stephan Laurentiu
2002-01-01
La fonction MLI (Modulation en Largeur d'Impulsion) ou PWM (Pulse Width Modulation) joue le rôle d'interface entre la partie commande d’un variateur de vitesse et la machine électrique associée. Cette fonction agit sur l'onduleur de tension (ou de courant) de la partie puissance du variateur et joue un rôle essentiel avec des conséquences sur toutes les performances du système. Nos travaux prennent en compte la machine asynchrone commandée à travers l'onduleur de tension deux-niveaux. Plusieu...
Directory of Open Access Journals (Sweden)
TOLEDO Ma Del Mar
1993-07-01
Full Text Available Une première caractérisation des truites de mer des rivières du Nord de l'Espagne (Asturies est réalisée à partir de l'analyse de la structure de taille et d'âge, ainsi que celle de l'alimentation et des paramètres reproducteurs des poissons adultes. Les truites proviennent des captures réalisées à la ligne (de juin à août sur les rivières Cares et Narcea et par pêche électrique sur les zones de frayères du Narcea durant la saison de reproduction (novembre à janvier. Les truites de mer échantillonnées durant la saison de pêche ont une structure d'âge semblable sur les deux cours d'eau. Environ 85% des individus sont restés deux ans en eau douce avant de descendre en mer, et plus de 95% d'entre eux appartiennent aux classes d'âge de mer 0 + et 1 + . L'importance relative des poissons de 0 + de mer (finnock est légèrement plus élevée dans le Cares (68% que dans le Narcea (51 %. Le rapport des sexes est en faveur des femelles, quelle que soit la classe d'âge de mer. La structure d'âge marin des truites capturées en période de reproduction ne diffère pas de celle observée durant la saison de pêche, bien que montrant une haute proportion de 0 + de mer (32% de l'ensemble des poissons matures. Le taux de maturation chez les truites de 0 + de mer est particulièrement élevé ( 81% parmi les femelles et 100% chez les mâles et tous les individus des autres classes d'âge de mer sont matures. Le nombre d'oeufs (de 571 à 2086 oeufs par femelle et l'index gonadosomatique sont positivement corrélés à la taille et à l'âge de mer des femelles. La truite de mer se nourrit activement en eau douce durant la remontée estivale, puisque 81 % des estomacs examinés étaient pleins. Elle consomme principalement des Epheméroptères, des Diptères et des Trichoptères, mais son alimentation inclut également des proies d'origine terrestre, essentiellement des Arthropodes.
Spectral diagonal ensemble Kalman filters
Kasanický, Ivan; Vejmelka, Martin
2015-01-01
A new type of ensemble Kalman filter is developed, which is based on replacing the sample covariance in the analysis step by its diagonal in a spectral basis. It is proved that this technique improves the aproximation of the covariance when the covariance itself is diagonal in the spectral basis, as is the case, e.g., for a second-order stationary random field and the Fourier basis. The method is extended by wavelets to the case when the state variables are random fields, which are not spatially homogeneous. Efficient implementations by the fast Fourier transform (FFT) and discrete wavelet transform (DWT) are presented for several types of observations, including high-dimensional data given on a part of the domain, such as radar and satellite images. Computational experiments confirm that the method performs well on the Lorenz 96 problem and the shallow water equations with very small ensembles and over multiple analysis cycles.
Symanzik flow on HISQ ensembles
Bazavov, A; Brown, N; DeTar, C; Foley, J; Gottlieb, Steven; Heller, U M; Hetrick, J E; Laiho, J; Levkova, L; Oktay, M; Sugar, R L; Toussaint, D; Van de Water, R S; Zhou, R
2013-01-01
We report on a scale determination with gradient-flow techniques on the $N_f = 2 + 1 + 1$ HISQ ensembles generated by the MILC collaboration. The lattice scale $w_0/a$, originally proposed by the BMW collaboration, is computed using Symanzik flow at four lattice spacings ranging from 0.15 to 0.06 fm. With a Taylor series ansatz, the results are simultaneously extrapolated to the continuum and interpolated to physical quark masses. We give a preliminary determination of the scale $w_0$ in physical units, along with associated systematic errors, and compare with results from other groups. We also present a first estimate of autocorrelation lengths as a function of flowtime for these ensembles.
Simple Deep Random Model Ensemble
ZHANG, XIAO-LEI; Wu, Ji
2013-01-01
Representation learning and unsupervised learning are two central topics of machine learning and signal processing. Deep learning is one of the most effective unsupervised representation learning approach. The main contributions of this paper to the topics are as follows. (i) We propose to view the representative deep learning approaches as special cases of the knowledge reuse framework of clustering ensemble. (ii) We propose to view sparse coding when used as a feature encoder as the consens...
Ensemble Modeling of Cancer Metabolism
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Tahmineh eKhazaei
2012-05-01
Full Text Available The metabolic behaviour of cancer cells is adapted to meet their proliferative needs, with notable changes such as enhanced lactate secretion and glucose uptake rates. In this work, we use the Ensemble Modeling (EM framework to gain insight and predict potential drug targets for tumour cells. EM generates a set of models which span the space of kinetic parameters that are constrained by thermodynamics. Perturbation data based on known targets are used to screen the entire ensemble of models to obtain a sub-set, which is increasingly predictive. EM allows for incorporation of regulatory information and captures the behaviour of enzymatic reactions at the molecular level by representing reactions in the elementary reaction form. In this study, a metabolic network consisting of 58 reactions is considered and accounts for glycolysis, the pentose phosphate pathway, lipid metabolism, amino acid metabolism, and includes allosteric regulation of key enzymes. Experimentally measured intracellular and extracellular metabolite concentrations are used for developing the ensemble of models along with information on established drug targets. The resulting models predicted transaldolase (TALA and succinyl-CoA ligase (SUCOAS1m to cause a significant reduction in growth rate when repressed, relative to currently known drug targets. Furthermore, the results suggest that the synergetic repression of transaldolase and glycine hydroxymethyltransferase (GHMT2r will lead to a three-fold decrease in growth rate compared to the repression of single enzyme targets.
Ensemble learning incorporating uncertain registration.
Simpson, Ivor J A; Woolrich, Mark W; Andersson, Jesper L R; Groves, Adrian R; Schnabel, Julia A
2013-04-01
This paper proposes a novel approach for improving the accuracy of statistical prediction methods in spatially normalized analysis. This is achieved by incorporating registration uncertainty into an ensemble learning scheme. A probabilistic registration method is used to estimate a distribution of probable mappings between subject and atlas space. This allows the estimation of the distribution of spatially normalized feature data, e.g., grey matter probability maps. From this distribution, samples are drawn for use as training examples. This allows the creation of multiple predictors, which are subsequently combined using an ensemble learning approach. Furthermore, extra testing samples can be generated to measure the uncertainty of prediction. This is applied to separating subjects with Alzheimer's disease from normal controls using a linear support vector machine on a region of interest in magnetic resonance images of the brain. We show that our proposed method leads to an improvement in discrimination using voxel-based morphometry and deformation tensor-based morphometry over bootstrap aggregating, a common ensemble learning framework. The proposed approach also generates more reasonable soft-classification predictions than bootstrap aggregating. We expect that this approach could be applied to other statistical prediction tasks where registration is important. PMID:23288332
Optimally choosing small ensemble members to produce robust climate simulations
International Nuclear Information System (INIS)
This study examines the subset climate model ensemble size required to reproduce certain statistical characteristics from a full ensemble. The ensemble characteristics examined are the root mean square error, the ensemble mean and standard deviation. Subset ensembles are created using measures that consider the simulation performance alone or include a measure of simulation independence relative to other ensemble members. It is found that the independence measure is able to identify smaller subset ensembles that retain the desired full ensemble characteristics than either of the performance based measures. It is suggested that model independence be considered when choosing ensemble subsets or creating new ensembles. (letter)
Variations discursives dans deux situations contrastées de la presse ordinaire
Moirand, Sophie
2009-01-01
Cette étude vise à comparer deux discours sur la science : l’un, mis au jour à partir d’un corpus constitué d’articles référant au domaine de l’astronomie, renvoie à la situation prototypique de la vulgarisation scientifique, dans laquelle le médiateur tient son rôle de gestionnaire discursif entre l’univers de la science et celui du public ; l’autre, mis au jour à partir d’un corpus constitué d’articles publiés à propos de la maladie de la vache folle et des organismes génétiquement modifiés...
Regards actuels sur la muséographie d’entre-deux-guerres
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François Poncelet
2008-10-01
Full Text Available Durant l’entre-deux-guerres, la muséographie des musées d’art présente des évolutions remarquables. De nouvelles pratiques de mise en exposition sont élaborées, se développent et, pour certaines, perdurent jusqu’à aujourd’hui. Les débats dont elles sont issues ressemblent parfois singulièrement aux discussions qui animent les musées d’art actuels. Un regard en arrière s’impose …During the interwar period a remarkable evolution has been in museography of art galleries. New practices are elaborated, developed and continued for a long time – actually up to now for some. The debates in which they originated sometimes strangely resemble the discussions that animate the museums today. A look to back is necessary…
Simulation numérique du bruit de frottement lors du contact de deux surfaces rugueuses
Dang, Viet Hung; Le Bot, Alain
2010-01-01
Le bruit généré lors du frottement de deux surfaces rugueuses l'une contre l'autre révèle des régimes et des propriétés très étonnantes [1]. Cependant les expérimentations [2], bien que fondamentales, ne donnent pas accès aux grandeurs mécaniques locales comme les chocs inter-aspérités, les déformations, et pressions locales Cette étude propose une approche numérique avec un modèle 1D basé sur la résolution des équations mécaniques par la technique de décomposition modale. Le traitement des ...
Elections présidentielles 2007, typologie des candidats. Les deux France
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Michel Bussi
2007-04-01
Full Text Available Depuis près de 25 ans, la géographie électorale de la France a été en grande partie marquée par la forte spatialisation du vote Front national, qui coupait en deux, d’Est en Ouest, le territoire national. Cependant, si cette « lune brune » s’est avérée durable de 1988 à 2007, les autres candidats apparaissaient jusqu’à présent indifférents à ce clivage géographique. L’un des enseignements de ce scrutin semble l’élargissement de ce clivage Est/Ouest à d’autres courants, en particulier à l’...
Wind Power Prediction using Ensembles
DEFF Research Database (Denmark)
Giebel, Gregor; Badger, Jake; Landberg, Lars;
2005-01-01
offshore wind farm and the whole Jutland/Funen area. The utilities used these forecasts for maintenance planning, fuel consumption estimates and over-the-weekend trading on the Leipzig power exchange. Othernotable scientific results include the better accuracy of forecasts made up from a simple...... superposition of two NWP provider (in our case, DMI and DWD), an investigation of the merits of a parameterisation of the turbulent kinetic energy within thedelivered wind speed forecasts, and the finding that a “naïve” downscaling of each of the coarse ECMWF ensemble members with higher resolution HIRLAM did...
Gibbs Ensembles of Nonintersecting Paths
Borodin, Alexei
2008-01-01
We consider a family of determinantal random point processes on the two-dimensional lattice and prove that members of our family can be interpreted as a kind of Gibbs ensembles of nonintersecting paths. Examples include probability measures on lozenge and domino tilings of the plane, some of which are non-translation-invariant. The correlation kernels of our processes can be viewed as extensions of the discrete sine kernel, and we show that the Gibbs property is a consequence of simple linear relations satisfied by these kernels. The processes depend on infinitely many parameters, which are closely related to parametrization of totally positive Toeplitz matrices.
A Localized Ensemble Kalman Smoother
Butala, Mark D.
2012-01-01
Numerous geophysical inverse problems prove difficult because the available measurements are indirectly related to the underlying unknown dynamic state and the physics governing the system may involve imperfect models or unobserved parameters. Data assimilation addresses these difficulties by combining the measurements and physical knowledge. The main challenge in such problems usually involves their high dimensionality and the standard statistical methods prove computationally intractable. This paper develops and addresses the theoretical convergence of a new high-dimensional Monte-Carlo approach called the localized ensemble Kalman smoother.
Ensemble Methods Foundations and Algorithms
Zhou, Zhi-Hua
2012-01-01
An up-to-date, self-contained introduction to a state-of-the-art machine learning approach, Ensemble Methods: Foundations and Algorithms shows how these accurate methods are used in real-world tasks. It gives you the necessary groundwork to carry out further research in this evolving field. After presenting background and terminology, the book covers the main algorithms and theories, including Boosting, Bagging, Random Forest, averaging and voting schemes, the Stacking method, mixture of experts, and diversity measures. It also discusses multiclass extension, noise tolerance, error-ambiguity a
Gouvernance et planification de deux périphéries multifonctionnelles
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Cécile Faliès
2010-02-01
Full Text Available L’objectif de cet article est d’établir une mise en perspective entre deux terrains périurbains : Quilpué (au Chili et Lurín (au Pérou. Au-delà de l’analyse de leur composition et de leur fonctionnement, l’intérêt est de souligner l’enjeu existant autour de leur planification. Mais dans un contexte de faible régulation par l’Etat et avec un manque d’outils de planification applicables à ces espaces hybrides, ni vraiment urbains, ni vraiment ruraux, leur gouvernance est délicate. Ainsi, la multifonctionnalité de ces deux territoires, qui présuppose des conflits d’intérêt entre les différents acteurs, engendre la participation de la société civile ainsi que des projets visant des recompositions territoriales.Este articulo tiene como objetivo establecer una mirada cruzada entre dos terrenos periurbanos : Quilpué (en Chile y Lurín (en Perú. Mas allá de analizar su composición y su funcionamiento, el interés de este articulo reside en señalar las problemáticas principales en lo referente a la planificación territorial de espacios periurbanos. Pero, la débil regulación por parte del Estado y una falta de instrumentos de planificación adaptados a estos espacios híbridos, ni totalmente urbanos, ni totalmente rurales, hacen que su gobernanza sea una cuestión delicada. Es así que la multifuncionalidad de estos territorios, presupone conflictos de interés entre los distintos actores presentes. Esto esta engendrando la participación de la sociedad civil y proyectos que conducen a recomposiciones territoriales.
Analysis of mesoscale forecasts using ensemble methods
Gross, Markus
2016-01-01
Mesoscale forecasts are now routinely performed as elements of operational forecasts and their outputs do appear convincing. However, despite their realistic appearance at times the comparison to observations is less favorable. At the grid scale these forecasts often do not compare well with observations. This is partly due to the chaotic system underlying the weather. Another key problem is that it is impossible to evaluate the risk of making decisions based on these forecasts because they do not provide a measure of confidence. Ensembles provide this information in the ensemble spread and quartiles. However, running global ensembles at the meso or sub mesoscale involves substantial computational resources. National centers do run such ensembles, but the subject of this publication is a method which requires significantly less computation. The ensemble enhanced mesoscale system presented here aims not at the creation of an improved mesoscale forecast model. Also it is not to create an improved ensemble syste...
Measuring social interaction in music ensembles.
Volpe, Gualtiero; D'Ausilio, Alessandro; Badino, Leonardo; Camurri, Antonio; Fadiga, Luciano
2016-05-01
Music ensembles are an ideal test-bed for quantitative analysis of social interaction. Music is an inherently social activity, and music ensembles offer a broad variety of scenarios which are particularly suitable for investigation. Small ensembles, such as string quartets, are deemed a significant example of self-managed teams, where all musicians contribute equally to a task. In bigger ensembles, such as orchestras, the relationship between a leader (the conductor) and a group of followers (the musicians) clearly emerges. This paper presents an overview of recent research on social interaction in music ensembles with a particular focus on (i) studies from cognitive neuroscience; and (ii) studies adopting a computational approach for carrying out automatic quantitative analysis of ensemble music performances. PMID:27069054
Interpreting Tree Ensembles with inTrees
Deng, Houtao
2014-01-01
Tree ensembles such as random forests and boosted trees are accurate but difficult to understand, debug and deploy. In this work, we provide the inTrees (interpretable trees) framework that extracts, measures, prunes and selects rules from a tree ensemble, and calculates frequent variable interactions. An rule-based learner, referred to as the simplified tree ensemble learner (STEL), can also be formed and used for future prediction. The inTrees framework can applied to both classification an...
A Gaussian mixture ensemble transform filter
Reich, Sebastian
2011-01-01
We generalize the popular ensemble Kalman filter to an ensemble transform filter where the prior distribution can take the form of a Gaussian mixture or a Gaussian kernel density estimator. The design of the filter is based on a continuous formulation of the Bayesian filter analysis step. We call the new filter algorithm the ensemble Gaussian mixture filter (EGMF). The EGMF is implemented for three simple test problems (Brownian dynamics in one dimension, Langevin dynamics in two dimensions, ...
Energy Technology Data Exchange (ETDEWEB)
Cohen-Tannoudji, G. [Commissariat a l' Energie Atomique, Saclay (France). Centre d' Etudes Nucleaires
1968-07-01
A phenomenological model suited for the description of arbitrary two-body reactions at high energies is presented and applied to the analysis of {pi} - nucleon, K - nucleon, et K-bar - nucleon scattering.The idea is that the Regge-pole model does not take into account the whole content of the unitarity relation and has to be modified, as is currently done in one-particle exchange models, so that it may include absorptive corrections.In terms of a rather economical set of free parameters,we obtain a satisfactory agreement with all available data, including the recent evidence for a nonvanishing polarization in {pi}{sup -} p {pi}{sup 0} n reaction. We then reinterpret our parametrization of the amplitudes in terms of poles and branch points in the complex angular-momentum plane for the crossed channel. (author) [French] Un modele phenomenologique adapte a la description des reactions a deux corps a haute energie est presente et applique a l'analyse des diffusions {pi} - nucleon, K - nucleon, et K-bar - nucleon. L'idee essentielle est que le modele d'echange de poles de Regge ne tient pas compte du contenu total de la relation d'unitarite et doit etre modifie, comme cela a ete propose dans le cas de l'echange de particules, de facon a tenir compte de corrections de type absortif. Au moyen d'un ensemble relativement economique de parametres libres nous obtenons un accord satisfaisant avec tous les resultats disponibles, y compris l'existence recemment mise en evidence d'une polarisation non nulle dans la reaction {pi}{sup -} p {pi}{sup 0} n. Nous interpretons notre fa n d'ecrire les amplitudes au moyen de poles et de points de branchement dans le plan complexe du moment angulaire pour la voie croisee. (auteur)
Faire territoire au quotidien dans les grands ensembles HLM
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Denis la Mache
2012-05-01
Full Text Available Cet article propose une lecture anthropologique de la manière dont les habitants des grands ensembles de périphéries urbaines délimitent, administrent, transforment matériellement et symboliquement les espaces et les lieux de leur quotidien pour faire territoire. Nous nous intéresserons à la fabrication de ces entités spatiales dont chaque individu se donne la liberté de disposer chaque jour selon un usage singulier et qu’il entoure d’un champ symbolique spécifique, garant d’identité. Ces « fabrications sociospatiales » seront abordées à partir d’une recherche empirique menée auprès d’habitants de deux terrains d’enquêtes situés dans des périphéries de villes moyennes.This paper proposes an anthropological reading of how the inhabitants of large urban peripheries define, administer, and process their daily spaces and places from a material as much as symbolical point of view to give sense to their territory. We will focus on the making of these spatial entities, witch everyone can dispose of everyday individually, to guarantee their identity. These “socio spatial creations” will be based on an empirical research, that is to say surveys conducted among the suburbians of two towns.
Approximation et précision : deux facettes d'une même réalité
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Asnes Maria
2014-07-01
Full Text Available L'approximation et la précision semblent être à deux pôles opposés: en effet, l'approximation est souvent considérée comme l'imprécision étant donné qu'elle fournit une représentation inexacte d'une valeur connue ou inconnue. Pourtant, la langue nous confronte avec des cas où le même terme peut avoir un sens tantôt approximatif tantôt précis. S'agit-il alors de deux emplois complètement distincts ou de deux effets de sens issus du même noyau sémantique? Cette étude prend comme objet l'adverbe plutôt qui manifeste des emplois approximatifs ainsi que précis.. A travers l'étude de ce terme on montrera que l'approximation et la précision ne sont pas toujours des termes opposés, mais qu'ils relèvent de deux facettes d'une même réalité de base.
Visualizing ensembles in structural biology.
Melvin, Ryan L; Salsbury, Freddie R
2016-06-01
Displaying a single representative conformation of a biopolymer rather than an ensemble of states mistakenly conveys a static nature rather than the actual dynamic personality of biopolymers. However, there are few apparent options due to the fixed nature of print media. Here we suggest a standardized methodology for visually indicating the distribution width, standard deviation and uncertainty of ensembles of states with little loss of the visual simplicity of displaying a single representative conformation. Of particular note is that the visualization method employed clearly distinguishes between isotropic and anisotropic motion of polymer subunits. We also apply this method to ligand binding, suggesting a way to indicate the expected error in many high throughput docking programs when visualizing the structural spread of the output. We provide several examples in the context of nucleic acids and proteins with particular insights gained via this method. Such examples include investigating a therapeutic polymer of FdUMP (5-fluoro-2-deoxyuridine-5-O-monophosphate) - a topoisomerase-1 (Top1), apoptosis-inducing poison - and nucleotide-binding proteins responsible for ATP hydrolysis from Bacillus subtilis. We also discuss how these methods can be extended to any macromolecular data set with an underlying distribution, including experimental data such as NMR structures. PMID:27179343
Hierarchical Bayes Ensemble Kalman Filtering
Tsyrulnikov, Michael
2015-01-01
Ensemble Kalman filtering (EnKF), when applied to high-dimensional systems, suffers from an inevitably small affordable ensemble size, which results in poor estimates of the background error covariance matrix ${\\bf B}$. The common remedy is a kind of regularization, usually an ad-hoc spatial covariance localization (tapering) combined with artificial covariance inflation. Instead of using an ad-hoc regularization, we adopt the idea by Myrseth and Omre (2010) and explicitly admit that the ${\\bf B}$ matrix is unknown and random and estimate it along with the state (${\\bf x}$) in an optimal hierarchical Bayes analysis scheme. We separate forecast errors into predictability errors (i.e. forecast errors due to uncertainties in the initial data) and model errors (forecast errors due to imperfections in the forecast model) and include the two respective components ${\\bf P}$ and ${\\bf Q}$ of the ${\\bf B}$ matrix into the extended control vector $({\\bf x},{\\bf P},{\\bf Q})$. Similarly, we break the traditional backgrou...
Visualizing ensembles in structural biology.
Melvin, Ryan L; Salsbury, Freddie R
2016-06-01
Displaying a single representative conformation of a biopolymer rather than an ensemble of states mistakenly conveys a static nature rather than the actual dynamic personality of biopolymers. However, there are few apparent options due to the fixed nature of print media. Here we suggest a standardized methodology for visually indicating the distribution width, standard deviation and uncertainty of ensembles of states with little loss of the visual simplicity of displaying a single representative conformation. Of particular note is that the visualization method employed clearly distinguishes between isotropic and anisotropic motion of polymer subunits. We also apply this method to ligand binding, suggesting a way to indicate the expected error in many high throughput docking programs when visualizing the structural spread of the output. We provide several examples in the context of nucleic acids and proteins with particular insights gained via this method. Such examples include investigating a therapeutic polymer of FdUMP (5-fluoro-2-deoxyuridine-5-O-monophosphate) - a topoisomerase-1 (Top1), apoptosis-inducing poison - and nucleotide-binding proteins responsible for ATP hydrolysis from Bacillus subtilis. We also discuss how these methods can be extended to any macromolecular data set with an underlying distribution, including experimental data such as NMR structures.
Joys of Community Ensemble Playing: The Case of the Happy Roll Elastic Ensemble in Taiwan
Hsieh, Yuan-Mei; Kao, Kai-Chi
2012-01-01
The Happy Roll Elastic Ensemble (HREE) is a community music ensemble supported by Tainan Culture Centre in Taiwan. With enjoyment and friendship as its primary goals, it aims to facilitate the joys of ensemble playing and the spirit of social networking. This article highlights the key aspects of HREE's development in its first two years…
Layered Ensemble Architecture for Time Series Forecasting.
Rahman, Md Mustafizur; Islam, Md Monirul; Murase, Kazuyuki; Yao, Xin
2016-01-01
Time series forecasting (TSF) has been widely used in many application areas such as science, engineering, and finance. The phenomena generating time series are usually unknown and information available for forecasting is only limited to the past values of the series. It is, therefore, necessary to use an appropriate number of past values, termed lag, for forecasting. This paper proposes a layered ensemble architecture (LEA) for TSF problems. Our LEA consists of two layers, each of which uses an ensemble of multilayer perceptron (MLP) networks. While the first ensemble layer tries to find an appropriate lag, the second ensemble layer employs the obtained lag for forecasting. Unlike most previous work on TSF, the proposed architecture considers both accuracy and diversity of the individual networks in constructing an ensemble. LEA trains different networks in the ensemble by using different training sets with an aim of maintaining diversity among the networks. However, it uses the appropriate lag and combines the best trained networks to construct the ensemble. This indicates LEAs emphasis on accuracy of the networks. The proposed architecture has been tested extensively on time series data of neural network (NN)3 and NN5 competitions. It has also been tested on several standard benchmark time series data. In terms of forecasting accuracy, our experimental results have revealed clearly that LEA is better than other ensemble and nonensemble methods. PMID:25751882
Rydberg ensemble based CNOTN gates using STIRAP
Gujarati, Tanvi; Duan, Luming
2016-05-01
Schemes for implementation of CNOT gates in atomic ensembles are important for realization of quantum computing. We present here a theoretical scheme of a CNOTN gate with an ensemble of three-level atoms in the lambda configuration and a single two-level control atom. We work in the regime of Rydberg blockade for the ensemble atoms due to excitation of the Rydberg control atom. It is shown that using STIRAP, atoms from one ground state of the ensemble can be adiabatically transferred to the other ground state, depending on the state of the control atom. A thorough analysis of adiabatic conditions for this scheme and the influence of the radiative decay is provided. We show that the CNOTN process is immune to the decay rate of the excited level in ensemble atoms. This work is supported by the ARL, the IARPA LogiQ program, and the AFOSR MURI program.
Popular Ensemble Methods: An Empirical Study
Maclin, R; 10.1613/jair.614
2011-01-01
An ensemble consists of a set of individually trained classifiers (such as neural networks or decision trees) whose predictions are combined when classifying novel instances. Previous research has shown that an ensemble is often more accurate than any of the single classifiers in the ensemble. Bagging (Breiman, 1996c) and Boosting (Freund and Shapire, 1996; Shapire, 1990) are two relatively new but popular methods for producing ensembles. In this paper we evaluate these methods on 23 data sets using both neural networks and decision trees as our classification algorithm. Our results clearly indicate a number of conclusions. First, while Bagging is almost always more accurate than a single classifier, it is sometimes much less accurate than Boosting. On the other hand, Boosting can create ensembles that are less accurate than a single classifier -- especially when using neural networks. Analysis indicates that the performance of the Boosting methods is dependent on the characteristics of the data set being exa...
Bouallegue, Zied Ben; Theis, Susanne E; Pinson, Pierre
2015-01-01
Probabilistic forecasts in the form of ensemble of scenarios are required for complex decision making processes. Ensemble forecasting systems provide such products but the spatio-temporal structures of the forecast uncertainty is lost when statistical calibration of the ensemble forecasts is applied for each lead time and location independently. Non-parametric approaches allow the reconstruction of spatio-temporal joint probability distributions at a low computational cost.For example, the ensemble copula coupling (ECC) method consists in rebuilding the multivariate aspect of the forecast from the original ensemble forecasts. Based on the assumption of error stationarity, parametric methods aim to fully describe the forecast dependence structures. In this study, the concept of ECC is combined with past data statistics in order to account for the autocorrelation of the forecast error. The new approach which preserves the dynamical development of the ensemble members is called dynamic ensemble copula coupling (...
ENCORE: Software for Quantitative Ensemble Comparison.
Directory of Open Access Journals (Sweden)
Matteo Tiberti
2015-10-01
Full Text Available There is increasing evidence that protein dynamics and conformational changes can play an important role in modulating biological function. As a result, experimental and computational methods are being developed, often synergistically, to study the dynamical heterogeneity of a protein or other macromolecules in solution. Thus, methods such as molecular dynamics simulations or ensemble refinement approaches have provided conformational ensembles that can be used to understand protein function and biophysics. These developments have in turn created a need for algorithms and software that can be used to compare structural ensembles in the same way as the root-mean-square-deviation is often used to compare static structures. Although a few such approaches have been proposed, these can be difficult to implement efficiently, hindering a broader applications and further developments. Here, we present an easily accessible software toolkit, called ENCORE, which can be used to compare conformational ensembles generated either from simulations alone or synergistically with experiments. ENCORE implements three previously described methods for ensemble comparison, that each can be used to quantify the similarity between conformational ensembles by estimating the overlap between the probability distributions that underlie them. We demonstrate the kinds of insights that can be obtained by providing examples of three typical use-cases: comparing ensembles generated with different molecular force fields, assessing convergence in molecular simulations, and calculating differences and similarities in structural ensembles refined with various sources of experimental data. We also demonstrate efficient computational scaling for typical analyses, and robustness against both the size and sampling of the ensembles. ENCORE is freely available and extendable, integrates with the established MDAnalysis software package, reads ensemble data in many common formats, and can
DUPONT,A
2001-01-01
Au début du xX siècle se développe chez les économistes l'exigence d'un rapprochement de type nouveau entre la théorie et la réalité, rapprochement pensé dans la perspective de la mesure. L'économie quantitative s'élabore tout particulièrement à partir de 1910, autour de deux approches majeures.' l'empirisme et l'économétrie. Nous prendrons comme référent le champ de recherche du cycle des affaires pour comprendre et analyser les points communs et les divergences entre ces deux programmes, ca...
Passeport pour les deux infinis vers l'infiniment grand, vers l'infiniment petit
Descotes-Genon, Sébastien; Kerhoas-Cavata, Sophie; Paul, Jacques; Robert, Jean-Luc; Royole-Degieux, Perrine
2016-01-01
Où commence l'infiniment grand ? Où finit l'infiniment petit ? Les chercheurs ont identifié le rayonnement fossile émis il y a 13,8 milliards d'année et qui permet de remonter aux origines de l'Univers. A l'opposé, le modèle standard a identifié 12 particules élémentaires et trois forces fondamentales qui permettent de décrire la constitution ultime de la matière. Est-ce à dire que tout est terminé, que plus rien n'est à découvrir ? Certainement pas ! Tandis que les outils d'observation deviennent plus précis, la nécessité d'établir des passerelles entre l'infiniment grand et l'infini petit devient pressante. Dans cette nouvelle édition actualisée, les plus grands spécialistes présentent un panorama des connaissances actuelles des deux infinis.
Congo belge et littérature de jeunesse dans l'entre-deux-guerres
Directory of Open Access Journals (Sweden)
Laurence Boudart
2012-01-01
Full Text Available Méconnue de la critique, la littérature coloniale belge pour la jeunesse de langue française ouvre néanmoins des perspectives intéressantes quant à l'histoire du fait colonial mais aussi, plus largement, à tout le questionnement identitaire induit par le rapport à l'autre et à l'ailleurs. C'est dans ce contexte que nous étudions trois ouvrages majeurs de la période de l'entre-deux-guerres : Tante Julia découvre le Congo (Roger Ransy, 1932, Jeannot gosse d’Afrique (Jeanne Maquet-Tombu, 1935 et Bamboula le petit homme noir (Franz Hellens, 1942, adapté de Bass-Bassina-Boulou, 1922. Nous veillons à montrer par quels moyens ces récits coloniaux pour l'enfance constituent un lieu privilégié où l'on peut, soit rallier, soit questionner l'idéologie.
Passeport pour les deux infinis vers l'infiniment grand, vers l'infiniment petit
Arnaud, Nicolas; Kerhoas-Cavata, Sophie; Paul, Jacques; Robert-Esil, Jean-Luc; Royole-Degieux, Perrine
2013-01-01
Où commence l'infiniment grand ? Où finit l'infiniment petit ? Les chercheurs ont identifié le rayonnement fossile émis il y a 13,7 milliards d'année et qui permet de remonter aux origines de l'Univers. A l'opposé, le modèle standard a identifié 12 particules élémentaires et trois forces fondamentales qui permettent de décrire la constitution ultime de la matière. Est-ce à dire que tout est terminé, que plus rien n'est à découvrir ? Certainement pas ! Tandis que les outils d'observation deviennent plus précis, la nécessité d'établir des passerelles entre l'infiniment grand et l'infini petit devient pressante. Dans ce livre illustré en couleur, les plus grands spécialistes présentent un panorama des connaissances actuelles pour voyager à la découverte des deux infinis. Cette nouvelle édition à jour tient compte des derniers réusultats du LHC dans sa quête du fameux boson de Higgs, et intègre les premières images du rayonnement fossile provenant du satellite Planck.
Hybrid Data Assimilation without Ensemble Filtering
Todling, Ricardo; Akkraoui, Amal El
2014-01-01
The Global Modeling and Assimilation Office is preparing to upgrade its three-dimensional variational system to a hybrid approach in which the ensemble is generated using a square-root ensemble Kalman filter (EnKF) and the variational problem is solved using the Grid-point Statistical Interpolation system. As in most EnKF applications, we found it necessary to employ a combination of multiplicative and additive inflations, to compensate for sampling and modeling errors, respectively and, to maintain the small-member ensemble solution close to the variational solution; we also found it necessary to re-center the members of the ensemble about the variational analysis. During tuning of the filter we have found re-centering and additive inflation to play a considerably larger role than expected, particularly in a dual-resolution context when the variational analysis is ran at larger resolution than the ensemble. This led us to consider a hybrid strategy in which the members of the ensemble are generated by simply converting the variational analysis to the resolution of the ensemble and applying additive inflation, thus bypassing the EnKF. Comparisons of this, so-called, filter-free hybrid procedure with an EnKF-based hybrid procedure and a control non-hybrid, traditional, scheme show both hybrid strategies to provide equally significant improvement over the control; more interestingly, the filter-free procedure was found to give qualitatively similar results to the EnKF-based procedure.
Nonequilibrium representative ensembles for isolated quantum systems
International Nuclear Information System (INIS)
An isolated quantum system is considered, prepared in a nonequilibrium initial state. In order to uniquely define the system dynamics, one has to construct a representative statistical ensemble. From the principle of least action it follows that the role of the evolution generator is played by a grand Hamiltonian, but not merely by its energy part. A theorem is proved expressing the commutators of field operators with operator products through variational derivatives of these products. A consequence of this theorem is the equivalence of the variational equations for field operators with the Heisenberg equations for the latter. A finite quantum system cannot equilibrate in the strict sense. But it can tend to a quasi-stationary state characterized by ergodic averages and the appropriate representative ensemble depending on initial conditions. Microcanonical ensemble, arising in the eigenstate thermalization, is just a particular case of representative ensembles. Quasi-stationary representative ensembles are defined by the principle of minimal information. The latter also implies the minimization of an effective thermodynamic potential. -- Highlights: → The evolution of a nonequilibrium isolated quantum system is considered. → The grand Hamiltonian is shown to be the evolution generator. → A theorem is proved connecting operator commutators with variational derivatives. → Quasi-stationary states are described by representative ensembles. → These ensembles, generally, depend on initial conditions.
MSEBAG: a dynamic classifier ensemble generation based on `minimum-sufficient ensemble' and bagging
Chen, Lei; Kamel, Mohamed S.
2016-01-01
In this paper, we propose a dynamic classifier system, MSEBAG, which is characterised by searching for the 'minimum-sufficient ensemble' and bagging at the ensemble level. It adopts an 'over-generation and selection' strategy and aims to achieve a good bias-variance trade-off. In the training phase, MSEBAG first searches for the 'minimum-sufficient ensemble', which maximises the in-sample fitness with the minimal number of base classifiers. Then, starting from the 'minimum-sufficient ensemble', a backward stepwise algorithm is employed to generate a collection of ensembles. The objective is to create a collection of ensembles with a descending fitness on the data, as well as a descending complexity in the structure. MSEBAG dynamically selects the ensembles from the collection for the decision aggregation. The extended adaptive aggregation (EAA) approach, a bagging-style algorithm performed at the ensemble level, is employed for this task. EAA searches for the competent ensembles using a score function, which takes into consideration both the in-sample fitness and the confidence of the statistical inference, and averages the decisions of the selected ensembles to label the test pattern. The experimental results show that the proposed MSEBAG outperforms the benchmarks on average.
L’analyse du discours et ses entre-deux : notes sur son histoire au Brésil
Puccinelli Orlandi, Eni
2014-01-01
À Paul Henry pour l’excellence théorique avec laquelle, dès le début, il a exploré la force et les nuances de l’analyse du discours. Introduction Mettant hors du champ de la réflexion discursive la notion d’« intervalle », je propose une pratique matérialiste de l’analyse du discours par son inscription dans un espace d’« entre-deux », jusqu’au sein même de l’histoire des théories linguistiques. À la différence de celle d’intervalle, l’idée d’entre-deux renvoie à des espaces simultanément hab...
Derivation of Mayer Series from Canonical Ensemble
Wang, Xian-Zhi
2016-02-01
Mayer derived the Mayer series from both the canonical ensemble and the grand canonical ensemble by use of the cluster expansion method. In 2002, we conjectured a recursion formula of the canonical partition function of a fluid (X.Z. Wang, Phys. Rev. E 66 (2002) 056102). In this paper we give a proof for this formula by developing an appropriate expansion of the integrand of the canonical partition function. We further derive the Mayer series solely from the canonical ensemble by use of this recursion formula.
Description de deux usages non subordonnants de la forme « alors que »
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Lafontaine Fanny
2014-07-01
Une fois la dichotomie entre emplois subordonnants et non subordonnants établie, nous affinerons la description de ces derniers en montrant avec une autre série de propriétés syntaxiques (tels que le statut paradigmatique/syntagmatique des énoncés, la relation d’ordre, la contiguïté… que ces énoncés relèvent de deux organisations grammaticales remarquables.
Ensemble Dynamics and Bred Vectors
Balci, Nusret; Restrepo, Juan M; Sell, George R
2011-01-01
We introduce the new concept of an EBV to assess the sensitivity of model outputs to changes in initial conditions for weather forecasting. The new algorithm, which we call the "Ensemble Bred Vector" or EBV, is based on collective dynamics in essential ways. By construction, the EBV algorithm produces one or more dominant vectors. We investigate the performance of EBV, comparing it to the BV algorithm as well as the finite-time Lyapunov Vectors. We give a theoretical justification to the observed fact that the vectors produced by BV, EBV, and the finite-time Lyapunov vectors are similar for small amplitudes. Numerical comparisons of BV and EBV for the 3-equation Lorenz model and for a forced, dissipative partial differential equation of Cahn-Hilliard type that arises in modeling the thermohaline circulation, demonstrate that the EBV yields a size-ordered description of the perturbation field, and is more robust than the BV in the higher nonlinear regime. The EBV yields insight into the fractal structure of th...
Cooperative effects of neuronal ensembles.
Rose, G; Siebler, M
1995-01-01
Electrophysiological properties of neurons as the basic cellular elements of the central nervous system and their synaptic connections are well characterized down to a molecular level. However, the behavior of complex noisy networks formed by these constituents usually cannot simply be derived from the knowledge of its microscopic parameters. As a consequence, cooperative phenomena based on the interaction of neurons were postulated. This is a report on a study of global network spike activity as a function of synaptic interaction. We performed experiments in dissociated cultured hippocampal neurons and, for comparison, simulations of a mathematical model closely related to electrophysiology. Numeric analyses revealed that at a critical level of synaptic connectivity the firing behavior undergoes a phase transition. This cooperative effect depends crucially on the interaction of numerous cells and cannot be attributed to the spike threshold of individual neurons. In the experiment a drastic increase in the firing level was observed upon increase of synaptic efficacy by lowering of the extracellular magnesium concentration, which is compatible with our theoretical predictions. This "on-off" phenomenon demonstrates that even in small neuronal ensembles collective behavior can emerge which is not explained by the characteristics of single neurons. PMID:8542966
A 4D-Ensemble-Variational System for Data Assimilation and Ensemble Initialization
Bowler, Neill; Clayton, Adam; Jardak, Mohamed; Lee, Eunjoo; Jermey, Peter; Lorenc, Andrew; Piccolo, Chiara; Pring, Stephen; Wlasak, Marek; Barker, Dale; Inverarity, Gordon; Swinbank, Richard
2016-04-01
The Met Office has been developing a four-dimensional ensemble variational (4DEnVar) data assimilation system over the past four years. The 4DEnVar system is intended both as data assimilation system in its own right and also an improved means of initializing the Met Office Global and Regional Ensemble Prediction System (MOGREPS). The global MOGREPS ensemble has been initialized by running an ensemble of 4DEnVars (En-4DEnVar). The scalability and maintainability of ensemble data assimilation methods make them increasingly attractive, and 4DEnVar may be adopted in the context of the Met Office's LFRic project to redevelop the technical infrastructure to enable its Unified Model (MetUM) to be run efficiently on massively parallel supercomputers. This presentation will report on the results of the 4DEnVar development project, including experiments that have been run using ensemble sizes of up to 200 members.
Transition from Poisson to circular unitary ensemble
Indian Academy of Sciences (India)
Vinayak; Akhilesh Pandey
2009-09-01
Transitions to universality classes of random matrix ensembles have been useful in the study of weakly-broken symmetries in quantum chaotic systems. Transitions involving Poisson as the initial ensemble have been particularly interesting. The exact two-point correlation function was derived by one of the present authors for the Poisson to circular unitary ensemble (CUE) transition with uniform initial density. This is given in terms of a rescaled symmetry breaking parameter Λ. The same result was obtained for Poisson to Gaussian unitary ensemble (GUE) transition by Kunz and Shapiro, using the contour-integral method of Brezin and Hikami. We show that their method is applicable to Poisson to CUE transition with arbitrary initial density. Their method is also applicable to the more general ℓ CUE to CUE transition where CUE refers to the superposition of ℓ independent CUE spectra in arbitrary ratio.
Data assimilation the ensemble Kalman filter
Evensen, Geir
2006-01-01
Covers data assimilation and inverse methods, including both traditional state estimation and parameter estimation. This text and reference focuses on various popular data assimilation methods, such as weak and strong constraint variational methods and ensemble filters and smoothers.
Irreplaceability of Neuronal Ensembles after Memory Allocation
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Naoki Matsuo
2015-04-01
Full Text Available Lesion studies suggest that an alternative system can compensate for damage to the primary region employed when animals acquire a memory. However, it is unclear whether functional compensation occurs at the cellular ensemble level. Here, we inhibited the activities of a specific subset of neurons activated during initial learning by utilizing a transgenic mouse that expresses tetanus toxin (TeNT under the control of the c-fos promoter. Notably, suppression interfered with relearning while sparing the ability to acquire and express fear memory for a distinct context. These results suggest that the activity of the initial ensemble is preferentially dedicated to the same learning and that it is not replaceable once it is allocated. Our results provide substantial insights into the machinery underlying how the brain allocates individual memories to discrete neuronal ensembles and how it ensures that repetitive learning strengthens memory by reactivating the same neuronal ensembles.
Reversible Projective Measurement in Quantum Ensembles
Khitrin, Anatoly; Lee, Jae-Seung
2010-01-01
We present experimental NMR demonstration of a scheme of reversible projective measurement, which allows extracting information on outcomes and probabilities of a projective measurement in a non-destructive way, with a minimal net effect on the quantum state of an ensemble. The scheme uses reversible dynamics and weak measurement of the intermediate state. The experimental system is an ensemble of 133Cs (S = 7/2) nuclei in a liquid-crystalline matrix.
Controlling balance in an ensemble Kalman filter
G. A. Gottwald
2014-01-01
We present a method to control unbalanced fast dynamics in an ensemble Kalman filter by introducing a weak constraint on the imbalance in a spatially sparse observational network. We show that the balance constraint produces significantly more balanced analyses than ensemble Kalman filters without balance constraints and than filters implementing incremental analysis updates (IAU). Furthermore, our filter with the weak constraint on imbalance produces good rms error statisti...
Calibrating ensemble reliability whilst preserving spatial structure
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Jonathan Flowerdew
2014-03-01
Full Text Available Ensemble forecasts aim to improve decision-making by predicting a set of possible outcomes. Ideally, these would provide probabilities which are both sharp and reliable. In practice, the models, data assimilation and ensemble perturbation systems are all imperfect, leading to deficiencies in the predicted probabilities. This paper presents an ensemble post-processing scheme which directly targets local reliability, calibrating both climatology and ensemble dispersion in one coherent operation. It makes minimal assumptions about the underlying statistical distributions, aiming to extract as much information as possible from the original dynamic forecasts and support statistically awkward variables such as precipitation. The output is a set of ensemble members preserving the spatial, temporal and inter-variable structure from the raw forecasts, which should be beneficial to downstream applications such as hydrological models. The calibration is tested on three leading 15-d ensemble systems, and their aggregation into a simple multimodel ensemble. Results are presented for 12 h, 1° scale over Europe for a range of surface variables, including precipitation. The scheme is very effective at removing unreliability from the raw forecasts, whilst generally preserving or improving statistical resolution. In most cases, these benefits extend to the rarest events at each location within the 2-yr verification period. The reliability and resolution are generally equivalent or superior to those achieved using a Local Quantile-Quantile Transform, an established calibration method which generalises bias correction. The value of preserving spatial structure is demonstrated by the fact that 3×3 averages derived from grid-scale precipitation calibration perform almost as well as direct calibration at 3×3 scale, and much better than a similar test neglecting the spatial relationships. Some remaining issues are discussed regarding the finite size of the output
Ensemble methods for noise in classification problems
Verbaeten, Sofie; Van Assche, Anneleen
2003-01-01
Ensemble methods combine a set of classifiers to construct a new classifier that is (often) more accurate than any of its component classifiers. In this paper, we use ensemble methods to identify noisy training examples. More precisely, we consider the problem of mislabeled training examples in classification tasks, and address this problem by pre-processing the training set, i.e. by identifying and removing outliers from the training set. We study a number of filter techniques that are based...
Deux modèles de fondation dans les Recherches logiques
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Thomas Nenon
2009-02-01
Full Text Available Cette étude essaye d’établir qu’il y a deux notions très différentes de « fondation » à l’œuvre dans les Recherches logiques de Husserl. Dans la IIIème Recherche, où le terme est formellement introduit, lorsqu’il se demande quels sont les contenus qui peuvent exister d’une manière autonome (indépendants et lesquels peuvent exister uniquement en tant que moments d’autre chose (dépendants, Husserl suit ce que j’appelle un « modèle ontologique ». Selon ce modèle, le concret possède une priorité sur à l’abstrait qui est fondé en lui. Dans la VIème Recherche, en revanche, Husserl s’oriente principalement sur un « modèle gnoséologique » qui voit le complexe comme fondé sur ce qui est relativement simple, étant donné que les expériences d’ordre supérieur (telles les perceptions de types d’objets plus complexes sont « fondées sur » des expériences plus simples, bien qu’elles ne puissent pas y être réduites. L’exemple principal ici est celui des intuitions catégoriales : fondées sur les intuitions sensibles, elles n’y sont pas réductibles. Mais cette distinction entre deux sens différents du terme de « fondation » peut également nous aider à mieux comprendre de nombreuses thèses husserliennes plutôt controversées. Par exemple, elle peut nous permettre de mieux comprendre dans quelle mesure faire l’expérience d’un être humain comme un tout se fonde sur l’expérience d’un corps physique, et cela même si l’étant que nous rencontrons inclut à la fois des aspects corporels et des aspects spirituels – les deux étant vus, d’une manière essentielle, comme des moments de cette unique personne qui fait l’objet de notre expérience.This essay attempts to establish that there are two very different notions of “foundation” at work in Husserl’s Logical Investigation. In the Third Investigation where the term is formally introduced, Husserl is using what
Towards a GME ensemble forecasting system: Ensemble initialization using the breeding technique
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Jan D. Keller
2008-12-01
Full Text Available The quantitative forecast of precipitation requires a probabilistic background particularly with regard to forecast lead times of more than 3 days. As only ensemble simulations can provide useful information of the underlying probability density function, we built a new ensemble forecasting system (GME-EFS based on the GME model of the German Meteorological Service (DWD. For the generation of appropriate initial ensemble perturbations we chose the breeding technique developed by Toth and Kalnay (1993, 1997, which develops perturbations by estimating the regions of largest model error induced uncertainty. This method is applied and tested in the framework of quasi-operational forecasts for a three month period in 2007. The performance of the resulting ensemble forecasts are compared to the operational ensemble prediction systems ECMWF EPS and NCEP GFS by means of ensemble spread of free atmosphere parameters (geopotential and temperature and ensemble skill of precipitation forecasting. This comparison indicates that the GME ensemble forecasting system (GME-EFS provides reasonable forecasts with spread skill score comparable to that of the NCEP GFS. An analysis with the continuous ranked probability score exhibits a lack of resolution for the GME forecasts compared to the operational ensembles. However, with significant enhancements during the 3 month test period, the first results of our work with the GME-EFS indicate possibilities for further development as well as the potential for later operational usage.
Meaning of temperature in different thermostatistical ensembles.
Hänggi, Peter; Hilbert, Stefan; Dunkel, Jörn
2016-03-28
Depending on the exact experimental conditions, the thermodynamic properties of physical systems can be related to one or more thermostatistical ensembles. Here, we survey the notion of thermodynamic temperature in different statistical ensembles, focusing in particular on subtleties that arise when ensembles become non-equivalent. The 'mother' of all ensembles, the microcanonical ensemble, uses entropy and internal energy (the most fundamental, dynamically conserved quantity) to derive temperature as a secondary thermodynamic variable. Over the past century, some confusion has been caused by the fact that several competing microcanonical entropy definitions are used in the literature, most commonly the volume and surface entropies introduced by Gibbs. It can be proved, however, that only the volume entropy satisfies exactly the traditional form of the laws of thermodynamics for a broad class of physical systems, including all standard classical Hamiltonian systems, regardless of their size. This mathematically rigorous fact implies that negative 'absolute' temperatures and Carnot efficiencies more than 1 are not achievable within a standard thermodynamical framework. As an important offspring of microcanonical thermostatistics, we shall briefly consider the canonical ensemble and comment on the validity of the Boltzmann weight factor. We conclude by addressing open mathematical problems that arise for systems with discrete energy spectra. PMID:26903095
Conductor gestures influence evaluations of ensemble performance.
Morrison, Steven J; Price, Harry E; Smedley, Eric M; Meals, Cory D
2014-01-01
Previous research has found that listener evaluations of ensemble performances vary depending on the expressivity of the conductor's gestures, even when performances are otherwise identical. It was the purpose of the present study to test whether this effect of visual information was evident in the evaluation of specific aspects of ensemble performance: articulation and dynamics. We constructed a set of 32 music performances that combined auditory and visual information and were designed to feature a high degree of contrast along one of two target characteristics: articulation and dynamics. We paired each of four music excerpts recorded by a chamber ensemble in both a high- and low-contrast condition with video of four conductors demonstrating high- and low-contrast gesture specifically appropriate to either articulation or dynamics. Using one of two equivalent test forms, college music majors and non-majors (N = 285) viewed sixteen 30 s performances and evaluated the quality of the ensemble's articulation, dynamics, technique, and tempo along with overall expressivity. Results showed significantly higher evaluations for performances featuring high rather than low conducting expressivity regardless of the ensemble's performance quality. Evaluations for both articulation and dynamics were strongly and positively correlated with evaluations of overall ensemble expressivity. PMID:25104944
Folie a deux: a case report [v1; ref status: indexed, http://f1000r.es/SD4pSL
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Sobia Haqqi
2012-09-01
Full Text Available Folie a deux, to date, remains a rare, yet a challenging psychiatric diagnosis. We discuss two cases that were identified in our out-patient clinics. One case was lost to follow up, while the other one showed improvement over time with appropriate management. Conclusion: As with any rare disorder, recognition and correct referral for rare diagnosis like folie a deux is of paramount importance.
Ensemble postprocessing for probabilistic quantitative precipitation forecasts
Bentzien, S.; Friederichs, P.
2012-12-01
Precipitation is one of the most difficult weather variables to predict in hydrometeorological applications. In order to assess the uncertainty inherent in deterministic numerical weather prediction (NWP), meteorological services around the globe develop ensemble prediction systems (EPS) based on high-resolution NWP systems. With non-hydrostatic model dynamics and without parameterization of deep moist convection, high-resolution NWP models are able to describe convective processes in more detail and provide more realistic mesoscale structures. However, precipitation forecasts are still affected by displacement errors, systematic biases and fast error growth on small scales. Probabilistic guidance can be achieved from an ensemble setup which accounts for model error and uncertainty of initial and boundary conditions. The German Meteorological Service (Deutscher Wetterdienst, DWD) provides such an ensemble system based on the German-focused limited-area model COSMO-DE. With a horizontal grid-spacing of 2.8 km, COSMO-DE is the convection-permitting high-resolution part of the operational model chain at DWD. The COSMO-DE-EPS consists of 20 realizations of COSMO-DE, driven by initial and boundary conditions derived from 4 global models and 5 perturbations of model physics. Ensemble systems like COSMO-DE-EPS are often limited with respect to ensemble size due to the immense computational costs. As a consequence, they can be biased and exhibit insufficient ensemble spread, and probabilistic forecasts may be not well calibrated. In this study, probabilistic quantitative precipitation forecasts are derived from COSMO-DE-EPS and evaluated at more than 1000 rain gauges located all over Germany. COSMO-DE-EPS is a frequently updated ensemble system, initialized 8 times a day. We use the time-lagged approach to inexpensively increase ensemble spread, which results in more reliable forecasts especially for extreme precipitation events. Moreover, we will show that statistical
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Philippe Chardin
2010-01-01
Full Text Available Cet article tente, à partir d’une comparaison d’ensemble entre les deux grands romans modernes de Flaubert, Madame Bovary et L’Éducation sentimentale, et d’une superposition d’exemples significatifs empruntés à chacun d’eux, de montrer que la série des contrastes qui viennent tout de suite à l’esprit ne doit pas dissimuler des variations subtiles autour des mêmes schémas narratifs et des mêmes paysages psychiques : aussi bien pour ce qui est du pôle négatif des ridicules (« bovarysme » impénitent de Frédéric et des infortunes (analogies entre les épreuves traversées, notamment en matière d’« éducation sentimentale » que pour ce qui est du pôle du positif — plus implicite chez Flaubert — incluant une sorte de principe de réhabilitation partielle des « premiers plans » et la permanence de tout un romantisme de la singularité, de la révolte, de l’élection par le malheur, de la passion, du désir.With a global comparison between Flaubert’s two chief modern novels, Madame Bovary and L’Éducation sentimentale, and a superposition of suggestive examples taken from both of them, this article intends to prove that the sequence of contrasts that firstly appear must not conceal the subtle variations on the same narrative patterns and the same psychological climates. We can notice this phenomena as well as for the negative poles of ridiculous features (Frederic’s impenitent “bovarysme” and misfortunes (analogies between the trials that have to be faced by the heroes — especially those of the “sentimental journey”, as for the positive pole — more implicit in Flaubert’s prose — that implies a kind of partial rehabilitation principle of the main characters, and the persistence of romanticism, a whole romanticism with singularity, revolt, election through unhappiness, passion and desire.
A Unification of Ensemble Square Root Kalman Filters
Nerger, Lars; Janjic Pfander, Tijana; Schröter, Jens; Hiller, Wolfgang
2012-01-01
In recent years, several ensemble-based Kalman filter algorithms have been developed that have been classified as ensemble square-root Kalman filters. Parallel to this development, the SEIK (Singular ``Evolutive'' Interpolated Kalman) filter has been introduced and applied in several studies. Some publications note that the SEIK filter is an ensemble Kalman filter or even an ensemble square-root Kalman filter. This study examines the relation of the SEIK filter to ensemble square-root filters...
On the Convergence of the Ensemble Kalman Filter
Mandel, Jan; Cobb, Loren; Beezley, Jonathan D.
2009-01-01
Convergence of the ensemble Kalman filter in the limit for large ensembles to the Kalman filter is proved. In each step of the filter, convergence of the ensemble sample covariance follows from a weak law of large numbers for exchangeable random variables, the continuous mapping theorem gives convergence in probability of the ensemble members, and $L^p$ bounds on the ensemble then give $L^p$ convergence.
A multisite seasonal ensemble streamflow forecasting technique
Bracken, Cameron; Rajagopalan, Balaji; Prairie, James
2010-03-01
We present a technique for providing seasonal ensemble streamflow forecasts at several locations simultaneously on a river network. The framework is an integration of two recent approaches: the nonparametric multimodel ensemble forecast technique and the nonparametric space-time disaggregation technique. The four main components of the proposed framework are as follows: (1) an index gauge streamflow is constructed as the sum of flows at all the desired spatial locations; (2) potential predictors of the spring season (April-July) streamflow at this index gauge are identified from the large-scale ocean-atmosphere-land system, including snow water equivalent; (3) the multimodel ensemble forecast approach is used to generate the ensemble flow forecast at the index gauge; and (4) the ensembles are disaggregated using a nonparametric space-time disaggregation technique resulting in forecast ensembles at the desired locations and for all the months within the season. We demonstrate the utility of this technique in skillful forecast of spring seasonal streamflows at four locations in the Upper Colorado River Basin at different lead times. Where applicable, we compare the forecasts to the Colorado Basin River Forecast Center's Ensemble Streamflow Prediction (ESP) and the National Resource Conservation Service "coordinated" forecast, which is a combination of the ESP, Statistical Water Supply, a principal component regression technique, and modeler knowledge. We find that overall, the proposed method is equally skillful to existing operational models while tending to better predict wet years. The forecasts from this approach can be a valuable input for efficient planning and management of water resources in the basin.
Haberman, Jason; Brady, Timothy F; Alvarez, George A
2015-04-01
Ensemble perception, including the ability to "see the average" from a group of items, operates in numerous feature domains (size, orientation, speed, facial expression, etc.). Although the ubiquity of ensemble representations is well established, the large-scale cognitive architecture of this process remains poorly defined. We address this using an individual differences approach. In a series of experiments, observers saw groups of objects and reported either a single item from the group or the average of the entire group. High-level ensemble representations (e.g., average facial expression) showed complete independence from low-level ensemble representations (e.g., average orientation). In contrast, low-level ensemble representations (e.g., orientation and color) were correlated with each other, but not with high-level ensemble representations (e.g., facial expression and person identity). These results suggest that there is not a single domain-general ensemble mechanism, and that the relationship among various ensemble representations depends on how proximal they are in representational space. PMID:25844624
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Quirino Cordeiro Júnior
2003-09-01
Full Text Available Quadros de transtorno psiquiátrico induzido (folie à deux são raros. Porém, sua prevalência pode ser de 5-25% nos casos de delírio de infestação parasitária. Relatamos o caso de uma paciente de 62 anos de idade com sintomas psicóticos que, há cerca de 15 anos, está vivendo com sua irmã mais nova. Como a paciente não estava mais apresentando sintomas, sua irmã decidiu não administrar-lhe mais antipsicótico. A paciente voltou a apresentar quadro psicótico marcado por delírio de infestação parasitária, acompanhado por alucinações visuais. Sua irmã, que não tinha história de qualquer transtorno psiquiátrico prévio, passou a acreditar que realmente a paciente estava infestada e que ela mesma fora contaminada. Esse relato de caso objetiva discutir a associação existente entre folie à deux e delírio de infestação parasitária.Shared psychiatric disorder (folie à deux is a rare condition. But its prevalence can be 5-25% in patients with delusional parasitic infestation. We report the a case of a 62 years-old female with psychotic symptoms. For 15 years, she has lived with her younger sister. Since the patient was well-controled, her sister interrupted her antipsychotic drug administration. So, the patient initiated delusional parasitic infestation accompanied by visual hallucinations. Her sister, who did not have psychiatric history, initiated to believe that the patient was really infested. Moreover, she started to believe that was infested by the patient. This case report aims to discuss the relation between folie à deux and delusional parasitic infestation.
DEFF Research Database (Denmark)
Ben Bouallègue, Zied; Heppelmann, Tobias; Theis, Susanne E.;
2015-01-01
Probabilistic forecasts in the form of ensemble of scenarios are required for complex decision making processes. Ensemble forecasting systems provide such products but the spatio-temporal structures of the forecast uncertainty is lost when statistical calibration of the ensemble forecasts...... is applied for each lead time and location independently. Non-parametric approaches allow the reconstruction of spatio-temporal joint probability distributions at a low computational cost.For example, the ensemble copula coupling (ECC) method consists in rebuilding the multivariate aspect of the forecast...... from the original ensemble forecasts. Based on the assumption of error stationarity, parametric methods aim to fully describe the forecast dependence structures. In this study, the concept of ECC is combined with past data statistics in order to account for the autocorrelation of the forecast error...
Simulations in generalized ensembles through noninstantaneous switches
Giovannelli, Edoardo; Cardini, Gianni; Chelli, Riccardo
2015-10-01
Generalized-ensemble simulations, such as replica exchange and serial generalized-ensemble methods, are powerful simulation tools to enhance sampling of free energy landscapes in systems with high energy barriers. In these methods, sampling is enhanced through instantaneous transitions of replicas, i.e., copies of the system, between different ensembles characterized by some control parameter associated with thermodynamical variables (e.g., temperature or pressure) or collective mechanical variables (e.g., interatomic distances or torsional angles). An interesting evolution of these methodologies has been proposed by replacing the conventional instantaneous (trial) switches of replicas with noninstantaneous switches, realized by varying the control parameter in a finite time and accepting the final replica configuration with a Metropolis-like criterion based on the Crooks nonequilibrium work (CNW) theorem. Here we revise these techniques focusing on their correlation with the CNW theorem in the framework of Markovian processes. An outcome of this report is the derivation of the acceptance probability for noninstantaneous switches in serial generalized-ensemble simulations, where we show that explicit knowledge of the time dependence of the weight factors entering such simulations is not necessary. A generalized relationship of the CNW theorem is also provided in terms of the underlying equilibrium probability distribution at a fixed control parameter. Illustrative calculations on a toy model are performed with serial generalized-ensemble simulations, especially focusing on the different behavior of instantaneous and noninstantaneous replica transition schemes.
Ensemble habitat mapping of invasive plant species
Stohlgren, T.J.; Ma, P.; Kumar, S.; Rocca, M.; Morisette, J.T.; Jarnevich, C.S.; Benson, N.
2010-01-01
Ensemble species distribution models combine the strengths of several species environmental matching models, while minimizing the weakness of any one model. Ensemble models may be particularly useful in risk analysis of recently arrived, harmful invasive species because species may not yet have spread to all suitable habitats, leaving species-environment relationships difficult to determine. We tested five individual models (logistic regression, boosted regression trees, random forest, multivariate adaptive regression splines (MARS), and maximum entropy model or Maxent) and ensemble modeling for selected nonnative plant species in Yellowstone and Grand Teton National Parks, Wyoming; Sequoia and Kings Canyon National Parks, California, and areas of interior Alaska. The models are based on field data provided by the park staffs, combined with topographic, climatic, and vegetation predictors derived from satellite data. For the four invasive plant species tested, ensemble models were the only models that ranked in the top three models for both field validation and test data. Ensemble models may be more robust than individual species-environment matching models for risk analysis. ?? 2010 Society for Risk Analysis.
Caractérisation Numérique et Expérimentale des Interactions entre deux Hydroliennes
Mycek, Paul; Gaurier, Benoît; Germain, Grégory; LOTHODÉ, Corentin; Pinon, Grégory; Rivoalen, Elie
2013-01-01
National audience; L'implantation et le développement de fermes d'hydroliennes sont soumis à la compréhension des effets d'interaction entre de telles machines. En nous inspirant de suggestions a priori sur la disposition de fermes de convertisseurs d'énergie marine, nous nous proposons de mettre en évidence les interactions entre deux hydroliennes à axe horizontal, en pleine eau. Des essais expérimentaux ont été réalisés dans le canal à houle et courant de l'IFREMER à Boulogne-sur-Mer, sur d...
Semaine d'Etude Mathématiques et Entreprises 1 : Deux problèmes sur les parcs solaires.
Aguillon, Nina; Benzekry, Sebastien; Bettinelli, Jérémie; Bochard, Pierre; Bonnotte, Nicolas; Delgado, Gabriel; Imbert-Gérard, Lise-Marie; Lepoultier, Guilhem; Navoret, Laurent; Parini, Enea
2011-01-01
Le premier problème consiste à étudier le placement quasi-optimal de parcs de panneaux solaires dans une région géographique définie. Si on suppose que la puissance d'un parc est directement proportionnelle à sa surface, on voudra maximiser la somme des surfaces des parcs. Néanmoins, la construction de tels parcs solaires est souvent soumise à des contraintes légales portant sur la puissance maximale de chaque parc et sur la distance entre deux parcs. Les idées proposées dans ce rapport tiend...
Control and Synchronization of Neuron Ensembles
Li, Jr-Shin; Ruths, Justin
2011-01-01
Synchronization of oscillations is a phenomenon prevalent in natural, social, and engineering systems. Controlling synchronization of oscillating systems is motivated by a wide range of applications from neurological treatment of Parkinson's disease to the design of neurocomputers. In this article, we study the control of an ensemble of uncoupled neuron oscillators described by phase models. We examine controllability of such a neuron ensemble for various phase models and, furthermore, study the related optimal control problems. In particular, by employing Pontryagin's maximum principle, we analytically derive optimal controls for spiking single- and two-neuron systems, and analyze the applicability of the latter to an ensemble system. Finally, we present a robust computational method for optimal control of spiking neurons based on pseudospectral approximations. The methodology developed here is universal to the control of general nonlinear phase oscillators.
Matrix averages relating to Ginibre ensembles
Energy Technology Data Exchange (ETDEWEB)
Forrester, Peter J [Department of Mathematics and Statistics, University of Melbourne, Victoria 3010 (Australia); Rains, Eric M [Department of Mathematics, California Institute of Technology, Pasadena, CA 91125 (United States)], E-mail: p.forrester@ms.unimelb.edu.au
2009-09-25
The theory of zonal polynomials is used to compute the average of a Schur polynomial of argument AX, where A is a fixed matrix and X is from the real Ginibre ensemble. This generalizes a recent result of Sommers and Khoruzhenko (2009 J. Phys. A: Math. Theor. 42 222002), and furthermore allows analogous results to be obtained for the complex and real quaternion Ginibre ensembles. As applications, the positive integer moments of the general variance Ginibre ensembles are computed in terms of generalized hypergeometric functions; these are written in terms of averages over matrices of the same size as the moment to give duality formulas, and the averages of the power sums of the eigenvalues are expressed as finite sums of zonal polynomials.
Clustering-based selective neural network ensemble
Institute of Scientific and Technical Information of China (English)
FU Qiang; HU Shang-xu; ZHAO Sheng-ying
2005-01-01
An effective ensemble should consist of a set of networks that are both accurate and diverse. We propose a novel clustering-based selective algorithm for constructing neural network ensemble, where clustering technology is used to classify trained networks according to similarity and optimally select the most accurate individual network from each cluster to make up the ensemble. Empirical studies on regression of four typical datasets showed that this approach yields significantly smaller en semble achieving better performance than other traditional ones such as Bagging and Boosting. The bias variance decomposition of the predictive error shows that the success of the proposed approach may lie in its properly tuning the bias/variance trade-offto reduce the prediction error (the sum of bias2 and variance).
Luminescence simulations of ensembles of silicon nanocrystals
Energy Technology Data Exchange (ETDEWEB)
Lockwood, Ross; Meldrum, Al [Department of Physics, University of Alberta, Edmonton (Canada)
2009-05-15
The luminescence of silicon nanocrystals (NCs) has attracted a great deal of interest due to the numerous potential photonic applications of light-emitting silicon. However, the excitation mechanisms and cluster-cluster interactions in densely-packed ensembles, as well as the recombination processes that influence the emission spectrum and lifetime are not yet well understood. In order to generate a more complete picture of the controlling parameters in the luminescence, a dynamic Monte Carlo model that incorporates several key physical processes for luminescent nanocrystal ensembles is developed. The model simulates Forster-type multipole energy transfer, tunnelling interactions, radiative decay and non-radiative trapping in physically realistic (lognormal) distributions of silicon NCs. The results of the simulation illustrate the effects of the NC size distribution, homogeneous and inhomogeneous broadening, NC packing density, and non-radiative trapping on the ensemble luminescence spectrum. (copyright 2009 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim) (orig.)
Embedded random matrix ensembles in quantum physics
Kota, V K B
2014-01-01
Although used with increasing frequency in many branches of physics, random matrix ensembles are not always sufficiently specific to account for important features of the physical system at hand. One refinement which retains the basic stochastic approach but allows for such features consists in the use of embedded ensembles. The present text is an exhaustive introduction to and survey of this important field. Starting with an easy-to-read introduction to general random matrix theory, the text then develops the necessary concepts from the beginning, accompanying the reader to the frontiers of present-day research. With some notable exceptions, to date these ensembles have primarily been applied in nuclear spectroscopy. A characteristic example is the use of a random two-body interaction in the framework of the nuclear shell model. Yet, topics in atomic physics, mesoscopic physics, quantum information science and statistical mechanics of isolated finite quantum systems can also be addressed using these ensemb...
Circular β ensembles, CMV representation, characteristic polynomials
Institute of Scientific and Technical Information of China (English)
SU ZhongGen
2009-01-01
In this note we first briefly review some recent progress in the study of the circular β ensemble on the unit circle, where 0 > 0 is a model parameter. In the special cases β = 1,2 and 4, this ensemble describes the joint probability density of eigenvalues of random orthogonal, unitary and sympletic matrices, respectively. For general β, Killip and Nenciu discovered a five-diagonal sparse matrix model, the CMV representation. This representation is new even in the case β = 2; and it has become a powerful tool for studying the circular β ensemble. We then give an elegant derivation for the moment identities of characteristic polynomials via the link with orthogonal polynomials on the unit circle.
Ensemble Kalman methods for inverse problems
International Nuclear Information System (INIS)
The ensemble Kalman filter (EnKF) was introduced by Evensen in 1994 (Evensen 1994 J. Geophys. Res. 99 10143–62) as a novel method for data assimilation: state estimation for noisily observed time-dependent problems. Since that time it has had enormous impact in many application domains because of its robustness and ease of implementation, and numerical evidence of its accuracy. In this paper we propose the application of an iterative ensemble Kalman method for the solution of a wide class of inverse problems. In this context we show that the estimate of the unknown function that we obtain with the ensemble Kalman method lies in a subspace A spanned by the initial ensemble. Hence the resulting error may be bounded above by the error found from the best approximation in this subspace. We provide numerical experiments which compare the error incurred by the ensemble Kalman method for inverse problems with the error of the best approximation in A, and with variants on traditional least-squares approaches, restricted to the subspace A. In so doing we demonstrate that the ensemble Kalman method for inverse problems provides a derivative-free optimization method with comparable accuracy to that achieved by traditional least-squares approaches. Furthermore, we also demonstrate that the accuracy is of the same order of magnitude as that achieved by the best approximation. Three examples are used to demonstrate these assertions: inversion of a compact linear operator; inversion of piezometric head to determine hydraulic conductivity in a Darcy model of groundwater flow; and inversion of Eulerian velocity measurements at positive times to determine the initial condition in an incompressible fluid. (paper)
Efficient inference of protein structural ensembles
Lane, Thomas J; Beauchamp, Kyle A; Pande, Vijay S
2014-01-01
It is becoming clear that traditional, single-structure models of proteins are insufficient for understanding their biological function. Here, we outline one method for inferring, from experiments, not only the most common structure a protein adopts (native state), but the entire ensemble of conformations the system can adopt. Such ensemble mod- els are necessary to understand intrinsically disordered proteins, enzyme catalysis, and signaling. We suggest that the most difficult aspect of generating such a model will be finding a small set of configurations to accurately model structural heterogeneity and present one way to overcome this challenge.
SEIK - the unknown ensemble Kalman filter
Nerger, Lars; Janjic Pfander, Tijana; Hiller, Wolfgang; Schröter, Jens
2009-01-01
The SEIK filter (Singular "Evolutive" Interpolated Kalman filter) hasbeen introduced in 1998 by D.T. Pham as a variant of the SEEK filter,which is a reduced-rank approximation of the Extended KalmanFilter. In recent years, it has been shown that the SEIK filter isan ensemble-based Kalman filter that uses a factorization rather thansquare-root of the state error covariance matrix. Unfortunately, theexistence of the SEIK filter as an ensemble-based Kalman filter withsimilar efficiency as the la...
Ensemble computing for the petroleum industry
International Nuclear Information System (INIS)
Computer downsizing is one of the most often used buzzwords in today's competitive business, and the petroleum industry is at the forefront of this revolution. Ensemble computing provides the key for computer downsizing with its first incarnation, i.e., workstation farms. This paper concerns the importance of increasing the productivity cycle and not just the execution time of a job. The authors introduce the concept of ensemble computing and workstation farms. The they discuss how different computing paradigms can be addressed by workstation farms
Jane Eyre between the Wars Jane Eyre entre les deux guerres
Directory of Open Access Journals (Sweden)
Patsy Stoneman
2009-07-01
Full Text Available L’un des héritages que Charlotte Brontë laissa derrière elle avec son roman Jane Eyre, c’est une trame qui fut indéfiniment recyclée dans le roman féminin. Une femme jeune, isolée et désargentée rencontre un homme plus riche et plus âgé qu’elle, au tempérament morose et au passé mystérieux dans lequel se trouve une épouse démente et mauvaise. Dans le monde de Charlotte Brontë, la société offre peu d’alternatives au mariage pour une femme qui ne peut compter que sur elle-même pour subvenir à ses besoins, et même le dénouement tranché de Jane Eyre n’est qu’une version plus égalitaire du mariage traditionnel. Sa structure triangulaire, toutefois, s’est avérée fertile pour les écrivains qui examinèrent les relations hommes/femmes dans des époques sociales ultérieures. Dans l’Angleterre d’entre-deux-guerres, les femmes de la classe moyenne étaient, comme le formule Virginia Woolf, « on the bridge » entre la maison privée et le monde professionnel. La plupart des obstacles légaux qui leur barraient l’accès à l’instruction et à l’emploi disparaissaient, mais l’éthos de la domesticité imprimait encore sa marque sur les attentes émotionnelles des femmes. Dans cet article, j’examine quatre romans qui utilisent l’intrigue de Jane Eyre afin de tracer les contours des possibilités qui s’offraient aux femmes à cette époque. Il s’agit de Vera d’Elizabeth von Arnim (1921, The Weather in the Streets de Rosamond Lehmann (1936, South Riding de Winifred Holtby (1936 et Rebecca de Daphne du Maurier (1938. La distinction que Tania Modleski dresse entre la romance (‘romance’ – dans laquelle la peur ou le dégoût initial de l’héroïne pour le héros se transforme en amour – et le gothique (‘gothic’ – où le processus est inverse – souligne que ces romans modernes ne peuvent envisager autre chose qu’un dénouement gothique à une situation à l’origine romantique
Total probabilities of ensemble runoff forecasts
Olav Skøien, Jon; Bogner, Konrad; Salamon, Peter; Smith, Paul; Pappenberger, Florian
2016-04-01
Ensemble forecasting has for a long time been used as a method in meteorological modelling to indicate the uncertainty of the forecasts. However, as the ensembles often exhibit both bias and dispersion errors, it is necessary to calibrate and post-process them. Two of the most common methods for this are Bayesian Model Averaging (Raftery et al., 2005) and Ensemble Model Output Statistics (EMOS) (Gneiting et al., 2005). There are also methods for regionalizing these methods (Berrocal et al., 2007) and for incorporating the correlation between lead times (Hemri et al., 2013). Engeland and Steinsland Engeland and Steinsland (2014) developed a framework which can estimate post-processing parameters which are different in space and time, but still can give a spatially and temporally consistent output. However, their method is computationally complex for our larger number of stations, and cannot directly be regionalized in the way we would like, so we suggest a different path below. The target of our work is to create a mean forecast with uncertainty bounds for a large number of locations in the framework of the European Flood Awareness System (EFAS - http://www.efas.eu) We are therefore more interested in improving the forecast skill for high-flows rather than the forecast skill of lower runoff levels. EFAS uses a combination of ensemble forecasts and deterministic forecasts from different forecasters to force a distributed hydrologic model and to compute runoff ensembles for each river pixel within the model domain. Instead of showing the mean and the variability of each forecast ensemble individually, we will now post-process all model outputs to find a total probability, the post-processed mean and uncertainty of all ensembles. The post-processing parameters are first calibrated for each calibration location, but assuring that they have some spatial correlation, by adding a spatial penalty in the calibration process. This can in some cases have a slight negative
1999-01-01
Le présent document concerne l'attribution de deux contrats pour la fourniture de fils supraconducteurs émaillés de quatre types différents (fil 1, fil 2, fil 3 et fil 4) destinés aux aimants de correction du LHC. Un appel d'offres (IT-2649/LHC/LHC) a été adressé le 13 juillet 1999 à quatre entreprises dans quatre Etats membres, trois entreprises au Japon et trois entreprises aux Etats-Unis. A la date de clôture, le CERN avait reçu cinq offres. Il est demandé au Comité des finances d'approuver la négociation de deux contrats: 1. d'une part avec IGC (USA) pour la fourniture de fils supraconducteurs 1 et 2 destinés aux aimants de correction du LHC pour un prix total net de 996 074 dollars des Etats-Unis, non révisable, avec une option pour la fourniture de fils 1 et 2 supplémentaires représentant 20% de la quantité initiale pour un prix total net de 199 215 dollars des Etats-Unis, révisable, ce qui porte le montant total à 1 195 289 dollars US, révisable pour l'option. Au taux de change in...
Ensemble. Mobile Learning to Promote Social Inclusion
G. Bonaiuti; Ranieri, M.; P. Ravotto
2010-01-01
Final English Booklet of Ensemble project. Mobile learning, or m-learning, is the new term that is gaining ground in the educational technology vocabulary. The project has tried to find out how mobile devices could be integrated into learning settings to improve social inclusion.
Canonical Ensemble Model for Black Hole Radiation
Indian Academy of Sciences (India)
Jingyi Zhang
2014-09-01
In this paper, a canonical ensemble model for the black hole quantum tunnelling radiation is introduced. In this model the probability distribution function corresponding to the emission shell is calculated to second order. The formula of pressure and internal energy of the thermal system is modified, and the fundamental equation of thermodynamics is also discussed.
Semi-classical approximation and microcanonical ensemble
International Nuclear Information System (INIS)
For quantum mechanical systems with spherically symmetric potential the improved W.K.B. approximation of Elworthy and Truman corresponds to the classical microcanonical ensemble in the limit where (h/2π) goes to zero, at least for small time. (orig.)
NYYD Ensemble ja Riho Sibul / Anneli Remme
Remme, Anneli, 1968-
2001-01-01
Gavin Bryarsi teos "Jesus' Blood Never Failed Me Yet" NYYD Ensemble'i ja Riho Sibula esituses 27. detsembril Pauluse kirikus Tartus ja 28. detsembril Rootsi- Mihkli kirikus Tallinnas. Kaastegevad Tartu Ülikooli Kammerkoor (Tartus) ja kammerkoor Voces Musicales (Tallinnas). Kunstiline juht Olari Elts
Conductor gestures influence evaluations of ensemble performance
Directory of Open Access Journals (Sweden)
Steven eMorrison
2014-07-01
Full Text Available Previous research has found that listener evaluations of ensemble performances vary depending on the expressivity of the conductor’s gestures, even when performances are otherwise identical. It was the purpose of the present study to test whether this effect of visual information was evident in the evaluation of specific aspects of ensemble performance, articulation and dynamics. We constructed a set of 32 music performances that combined auditory and visual information and were designed to feature a high degree of contrast along one of two target characteristics: articulation and dynamics. We paired each of four music excerpts recorded by a chamber ensemble in both a high- and low-contrast condition with video of four conductors demonstrating high- and low-contrast gesture specifically appropriate to either articulation or dynamics. Using one of two equivalent test forms, college music majors and nonmajors (N = 285 viewed sixteen 30-second performances and evaluated the quality of the ensemble’s articulation, dynamics, technique and tempo along with overall expressivity. Results showed significantly higher evaluations for performances featuring high rather than low conducting expressivity regardless of the ensemble’s performance quality. Evaluations for both articulation and dynamics were strongly and positively correlated with evaluations of overall ensemble expressivity.
AUC-Maximizing Ensembles through Metalearning.
LeDell, Erin; van der Laan, Mark J; Peterson, Maya
2016-05-01
Area Under the ROC Curve (AUC) is often used to measure the performance of an estimator in binary classification problems. An AUC-maximizing classifier can have significant advantages in cases where ranking correctness is valued or if the outcome is rare. In a Super Learner ensemble, maximization of the AUC can be achieved by the use of an AUC-maximining metalearning algorithm. We discuss an implementation of an AUC-maximization technique that is formulated as a nonlinear optimization problem. We also evaluate the effectiveness of a large number of different nonlinear optimization algorithms to maximize the cross-validated AUC of the ensemble fit. The results provide evidence that AUC-maximizing metalearners can, and often do, out-perform non-AUC-maximizing metalearning methods, with respect to ensemble AUC. The results also demonstrate that as the level of imbalance in the training data increases, the Super Learner ensemble outperforms the top base algorithm by a larger degree. PMID:27227721
Partition Function of Interacting Calorons Ensemble
Deldar, Sedigheh
2015-01-01
We present a method for computing the partition function of a caloron ensemble taking into account the interaction of calorons. We focus on caloron-Dirac string interaction and show that the metric that Diakonov and Petrov offered works well in the limit where this interaction occurs. We suggest computing the correlation function of two polyakov loops by applying Ewald's method.
Partition function of interacting calorons ensemble
Deldar, S.; Kiamari, M.
2016-01-01
We present a method for computing the partition function of a caloron ensemble taking into account the interaction of calorons. We focus on caloron-Dirac string interaction and show that the metric that Diakonov and Petrov offered, works well in the limit where this interaction occurs. We suggest computing the correlation function of two polyakov loops by applying Ewald's method.
The Hydrologic Ensemble Prediction Experiment (HEPEX)
Wood, Andy; Wetterhall, Fredrik; Ramos, Maria-Helena
2015-04-01
The Hydrologic Ensemble Prediction Experiment was established in March, 2004, at a workshop hosted by the European Center for Medium Range Weather Forecasting (ECMWF), and co-sponsored by the US National Weather Service (NWS) and the European Commission (EC). The HEPEX goal was to bring the international hydrological and meteorological communities together to advance the understanding and adoption of hydrological ensemble forecasts for decision support. HEPEX pursues this goal through research efforts and practical implementations involving six core elements of a hydrologic ensemble prediction enterprise: input and pre-processing, ensemble techniques, data assimilation, post-processing, verification, and communication and use in decision making. HEPEX has grown through meetings that connect the user, forecast producer and research communities to exchange ideas, data and methods; the coordination of experiments to address specific challenges; and the formation of testbeds to facilitate shared experimentation. In the last decade, HEPEX has organized over a dozen international workshops, as well as sessions at scientific meetings (including AMS, AGU and EGU) and special issues of scientific journals where workshop results have been published. Through these interactions and an active online blog (www.hepex.org), HEPEX has built a strong and active community of nearly 400 researchers & practitioners around the world. This poster presents an overview of recent and planned HEPEX activities, highlighting case studies that exemplify the focus and objectives of HEPEX.
Tiered Evaluation in Large Ensemble Settings.
Scott, David
1998-01-01
Discusses the use of a tiered evaluation system (TES) that allows students to work at different levels, enables teachers to assess progress objectively, and presents students with appropriate challenges in the music ensembles. Focuses on how TES works and its advantages, considers the challenges and flexibility of TES, and provides samples. (CMK)
Toward Manipulating Quantum Information with Atomic Ensembles
Lukin, M.D.; André, A.; Eisaman, M.D.; Hohensee, M.; Phillips, D.F.; Wal, C.H. van der; Walsworth, R.L.; Zibrov, A.S.
2003-01-01
We review several ideas for manipulation of quantum information using atomic ensembles and photons and describe some preliminary experiments toward their implementation. In particular, we review a technique that allows for robust transfer of quantum states between light fields and metastable states
Lorentz-invariant ensembles of vector backgrounds
International Nuclear Information System (INIS)
We consider gauge field theories in the presence of ensembles of vector backgrounds. While Lorentz invariance is explicitly broken in the presence of any single background, here, the Lorentz invariance of the theory is restored by averaging over a Lorentz-invariant ensemble of backgrounds, i.e., a set of background vectors that is mapped onto itself under Lorentz transformations. This framework is used to study the effects of a non-trivial but Lorentz-invariant vacuum structure or mass dimension two vector condensates by identifying the background with a shift of the gauge field. Up to now, the ensembles used in the literature comprise configurations corresponding to non-zero field tensors together with such with vanishing field strength. We find that even when constraining the ensembles to pure gauge configurations, the usual high-energy degrees of freedom are removed from the spectrum of asymptotic states in the presence of said backgrounds in Euclidean and in Minkowski space. We establish this result not only for the propagators to all orders in the background and otherwise at tree level but for the full propagator
Large Ensembles of Regional Climate Projections
Massey, Neil; Allen, Myles; Hall, Jim
2016-04-01
Projections of regional climate change have great utility for impact assessment at a local scale. The CORDEX climate projection framework presents a method of providing these regional projections by driving a regional climate model (RCM) with output from CMIP5 climate projection runs of global climate models (GCM). This produces an ensemble of regional climate projections, sampling the model uncertainty, the forcing uncertainty and the uncertainty of the response of the climate system to the increase in greenhouse gas (GHG) concentrations. Using the weather@home project to compute large ensembles of RCMs via volunteer distributed computing presents another method of generating projections of climate variables and also allows the sampling of the uncertainty due to internal variability. weather@home runs both a RCM and GCM on volunteer's home computers, with the free-running GCM driving the boundaries of the RCM. The GCM is an atmosphere only model and requires forcing at the lower boundary with sea-surface temperature (SST) and sea-ice concentration (SIC) data. By constructing SST and SIC projections, using projections of GHG and other atmospheric gases, and running the weather@home RCM and GCM with these forcings, large ensembles of projections of climate variables at regional scales can be made. To construct the SSTs and SICs, a statistical model is built to represent the response of SST and SIC to increases in GHG concentrations in the CMIP5 ensemble, for both the RCP4.5 and RCP8.5 scenarios. This statistical model uses empirical orthogonal functions (EOFs) to represent the change in the long term trend of SSTs in the CMIP5 projections. A multivariate distribution of the leading principle components (PC) is produced using a copula and sampled to produce a timeseries of PCs which are recombined with the EOFs to generate a timeseries of SSTs, with internal variability added from observations. Hence, a large ensemble of SST projections is generated, with each SST
Space Applications for Ensemble Detection and Analysis Project
National Aeronautics and Space Administration — Ensemble Detection is both a measurement technique and analysis tool. Like a prism that separates light into spectral bands, an ensemble detector mixes a signal...
Ensemble-based Kalman Filters in Strongly Nonlinear Dynamics
Institute of Scientific and Technical Information of China (English)
Zhaoxia PU; Joshua HACKER
2009-01-01
This study examines the effectiveness of ensemble Kalman filters in data assimilation with the strongly nonlinear dynamics of the Lorenz-63 model, and in particular their use in predicting the regime transition that occurs when the model jumps from one basin of attraction to the other. Four configurations of the ensemble-based Kalman filtering data assimilation techniques, including the ensemble Kalman filter, ensemble adjustment Kalman filter, ensemble square root filter and ensemble transform Kalman filter, are evaluated with their ability in predicting the regime transition (also called phase transition) and also are compared in terms of their sensitivity to both observational and sampling errors. The sensitivity of each ensemble-based filter to the size of the ensemble is also examined.
Global Ensemble Forecast System (GEFS) [2.5 Deg.
National Oceanic and Atmospheric Administration, Department of Commerce — The Global Ensemble Forecast System (GEFS) is a weather forecast model made up of 21 separate forecasts, or ensemble members. The National Centers for Environmental...
Analyse expérimentale du comportement biomécanique de deux types d'implants d'ostéosynthèse
Gómez Clemente, Raquel
2010-01-01
Ce projet s´inscrit dans une étude sur l´analyse du comportement biomécanique de deux types d´implants d´ostéosynthèse des fractures condyliennes latérales du coude chez le chien. Il est en relation avec l´entreprise SYNTHES qui fabrique les vis qui vont être utilisées dans l´étude, et des vétérinaires. Ces deux types d´implants sont deux vis différentes, une pleine et une cannulée. Dans ce projet la problématique de l´étude, et la recherche bibliographique faite pour étudier des angles, posi...
Evaluation of an ensemble-based incremental variational data assimilation
Yang, Yin; Robinson, Cordelia; Heitz, Dominique; Mémin, Etienne
2014-01-01
In this work, we aim at studying ensemble based optimal control strategies for data assimilation. Such formulation nicely combines the ingredients of ensemble Kalman filters and variational data assimilation (4DVar). In the same way as variational assimilation schemes, it is formulated as the minimization of an objective function, but similarly to ensemble filter, it introduces in its objective function an empirical ensemble-based background-error covariance and works in an off-line smoothing...
Black Hole Statistical Mechanics and The Angular Velocity Ensemble
Thomson, Mitchell
2012-01-01
An new ensemble - the angular velocity ensemble - is derived using Jaynes' method of maximising entropy subject to prior information constraints. The relevance of the ensemble to black holes is motivated by a discussion of external parameters in statistical mechanics and their absence from the Hamiltonian of general relativity. It is shown how this leads to difficulty in deriving entropy as a function of state and recovering the first law of thermodynamics from the microcanonical and canonical ensembles applied to black holes.
Ensembles of signal transduction models using Pareto Optimal Ensemble Techniques (POETs).
Song, Sang Ok; Chakrabarti, Anirikh; Varner, Jeffrey D
2010-07-01
Mathematical modeling of complex gene expression programs is an emerging tool for understanding disease mechanisms. However, identification of large models sometimes requires training using qualitative, conflicting or even contradictory data sets. One strategy to address this challenge is to estimate experimentally constrained model ensembles using multiobjective optimization. In this study, we used Pareto Optimal Ensemble Techniques (POETs) to identify a family of proof-of-concept signal transduction models. POETs integrate Simulated Annealing (SA) with Pareto optimality to identify models near the optimal tradeoff surface between competing training objectives. We modeled a prototypical-signaling network using mass-action kinetics within an ordinary differential equation (ODE) framework (64 ODEs in total). The true model was used to generate synthetic immunoblots from which the POET algorithm identified the 117 unknown model parameters. POET generated an ensemble of signaling models, which collectively exhibited population-like behavior. For example, scaled gene expression levels were approximately normally distributed over the ensemble following the addition of extracellular ligand. Also, the ensemble recovered robust and fragile features of the true model, despite significant parameter uncertainty. Taken together, these results suggest that experimentally constrained model ensembles could capture qualitatively important network features without exact parameter information.
Data assimilation in integrated hydrological modeling using ensemble Kalman filtering
DEFF Research Database (Denmark)
Rasmussen, Jørn; Madsen, H.; Jensen, Karsten Høgh;
2015-01-01
Groundwater head and stream discharge is assimilated using the ensemble transform Kalman filter in an integrated hydrological model with the aim of studying the relationship between the filter performance and the ensemble size. In an attempt to reduce the required number of ensemble members...
A COMPREHENSIVE EVOLUTIONARY APPROACH FOR NEURAL NETWORK ENSEMBLES AUTOMATIC DESIGN
Bukhtoyarov, V.; Semenkin, E.
2010-01-01
A new comprehensive approach for neural network ensembles design is proposed. It consists of a method of neural networks automatic design and a method of automatic formation of an ensemble solution on the basis of separate neural networks solutions. It is demonstrated that the proposed approach is not less effective than a number of other approaches for neural network ensembles design.
Hermon, Ella
2015-01-01
La gestion de l’eau, conçue comme un patrimoine culturel par le filtre de son histoire, est indissociable des écosystèmes des bords de l’eau que nous avons identifiés avec le concept de RIPARIA. Sa définition comme concept environnemental à la recherche d’une méthode d’analyse systémique puise ses racines dans l’évolution diachronique des concepts environnementaux des deux rives de l’Atlantique. Deux approches parallèles de la définition de concepts environnementaux, ont ...
Directory of Open Access Journals (Sweden)
A.H. CHAPMAN
1998-09-01
Full Text Available A case of folie à deux dissociative (dissociative hysteria disorder in an 8 and 12 year-old sister and brother is presented. Illnesses of this type are very rare and there is little medical literature on this subject. Our patients, almost simultaneously, abruptly had complete loss of memory, disorientation, loss of awareness about who they were, and much anxiety, which lasted about 15 hours. Both patients were physically well and no abnormalities were found on physical examination, routines laboratory tests and EEG studies. Speculations about the emotional and interpersonal causes of this illness in these two patients are given.É apresentado um caso da desordem dissociativa folie à deux (histeria dissociativa em um casal de irmãos, sendo que o menino tem 12 anos e a menina 8. Doenças desse tipo são raras e existem poucas referências sobre o assunto na literatura médica. Os pacientes por nós atendidos, de repente e quase simultaneamente, apresentaram distúrbios acentuados da memória, desorientação, perda de auto-identidade e muita ansiedade; esse estado confusional durou aproximadamente 15 horas. Os dois tinham boa saúde física e não apresentavam anormalidades no exame clínico. Os exames laboratoriais de rotina estavam normais. Foram avaliados por meio de EEGs que estavam dentro dos limites da normalidade. Na discussão, são apresentadas considerações especulativas sobre as causas emocionais e interpessoais que possam ter propiciado o aparecimento dessa desordem nos dois pacientes.
Deux extraits commentés des Basses Œuvres1 de ‘Abduh Khāl
Lagrange, Frédéric
2014-01-01
Le romancier saoudien ‘Abduh Khāl, dans son roman Tarmī bi‑sharar (Les Basses Œuvres) paru en 2009 et couronné par l’International Prize for Arab Fiction en 2010, tend un miroir peu flatteur au Royaume wahhabite : ce monologue d’un tortionnaire violeur au service d’un mystérieux Maître du Palais dans une Djedda déformée par l’affairisme figurant allégoriquement le régime présente un pays corrompu par sa soumission à l’absolutisme. Deux extraits sont ici commentés, en soulignant les rapports i...
Mamoudou, Savadogo; Lassina, Dao; Fla, Koueta
2015-01-01
Nous rapportons deux cas d'infection à Pseudomonas aeruginosa: un cas de méningite et un cas d'infection urinaire. Les auteurs rappellent qu’à côté des étiologies classiques des méningites et des infections urinaires, des germes résistants comme Pseudomonas aeruginosa peuvent être responsables d'infections à localisation méningées et urinaires et dont il faut connaître pour une bonne prise en charge. Le traitement de ces infections requiert un antibiogramme au regard de la grande capacité de résistance de Pseudomonas aeruginosa en milieu hospitalier. La limitation des gestes invasifs et l'application rigoureuse des mesures de prévention des infections en milieu hospitalier contribueront à lutter efficacement contre ces infections en milieu de soins. PMID:26491521
À propos du compte rendu des deux volumes de Chants populaires de la Grande Lande, de Félix Arnaudin
Mabru, Lothaire
2010-01-01
Dans le précédent volume des Cahiers de musiques traditionnelles, Eliane Gauzit et Pierre Bec ont produit un compte rendu concernant les deux tomes des Chants populaires de la Grande Lande de Félix Arnaudin, auxquels j’avais participé. Dans ce texte ils m’accusent de manque de rigueur scientifique et de négligence dans mon travail d’édition des chants collectés par Arnaudin. Ce n’est pas la première fois qu’ils s’en prennent à moi à ce sujet, puisqu’ils ont publiquement émis leurs critiques à...
Écritures hypermédiatiques: remarques sur deux cédéroms d'auteur
Clément, Jean
2000-01-01
L'avènement du livre numérique fait apparaître de nouvelles formes d'écriture. Dans le domaine de la fiction, en particulier, on assiste à la naissance d'un nouveau genre à la croisée des jeux vidéos, de l'hypertexte et de la littérature expérimentale. À travers deux exemples, ce sont quelques-unes des caractéristiques du genre qui sont étudiées ici : refondation du pacte de lecture, dissémination des énoncés, nouvelles modalités narratives, déconstruction du récit, interactivité....
Quark ensembles with the infinite correlation length
International Nuclear Information System (INIS)
A number of exactly integrable (quark) models of quantum field theory with the infinite correlation length have been considered. It has been shown that the standard vacuum quark ensemble—Dirac sea (in the case of the space-time dimension higher than three)—is unstable because of the strong degeneracy of a state, which is due to the character of the energy distribution. When the momentum cutoff parameter tends to infinity, the distribution becomes infinitely narrow, leading to large (unlimited) fluctuations. Various vacuum ensembles—Dirac sea, neutral ensemble, color superconductor, and BCS state—have been compared. In the case of the color interaction between quarks, the BCS state has been certainly chosen as the ground state of the quark ensemble
Rotationally invariant ensembles of integrable matrices
Yuzbashyan, Emil A.; Shastry, B. Sriram; Scaramazza, Jasen A.
2016-05-01
We construct ensembles of random integrable matrices with any prescribed number of nontrivial integrals and formulate integrable matrix theory (IMT)—a counterpart of random matrix theory (RMT) for quantum integrable models. A type-M family of integrable matrices consists of exactly N -M independent commuting N ×N matrices linear in a real parameter. We first develop a rotationally invariant parametrization of such matrices, previously only constructed in a preferred basis. For example, an arbitrary choice of a vector and two commuting Hermitian matrices defines a type-1 family and vice versa. Higher types similarly involve a random vector and two matrices. The basis-independent formulation allows us to derive the joint probability density for integrable matrices, similar to the construction of Gaussian ensembles in the RMT.
Ensemble Forecasting of Major Solar Flares
Guerra, J A; Uritsky, V M
2015-01-01
We present the results from the first ensemble prediction model for major solar flares (M and X classes). Using the probabilistic forecasts from three models hosted at the Community Coordinated Modeling Center (NASA-GSFC) and the NOAA forecasts, we developed an ensemble forecast by linearly combining the flaring probabilities from all four methods. Performance-based combination weights were calculated using a Monte Carlo-type algorithm by applying a decision threshold $P_{th}$ to the combined probabilities and maximizing the Heidke Skill Score (HSS). Using the probabilities and events time series from 13 recent solar active regions (2012 - 2014), we found that a linear combination of probabilities can improve both probabilistic and categorical forecasts. Combination weights vary with the applied threshold and none of the tested individual forecasting models seem to provide more accurate predictions than the others for all values of $P_{th}$. According to the maximum values of HSS, a performance-based weights ...
Ensemble annealing of complex physical systems
Habeck, Michael
2015-01-01
Algorithms for simulating complex physical systems or solving difficult optimization problems often resort to an annealing process. Rather than simulating the system at the temperature of interest, an annealing algorithm starts at a temperature that is high enough to ensure ergodicity and gradually decreases it until the destination temperature is reached. This idea is used in popular algorithms such as parallel tempering and simulated annealing. A general problem with annealing methods is that they require a temperature schedule. Choosing well-balanced temperature schedules can be tedious and time-consuming. Imbalanced schedules can have a negative impact on the convergence, runtime and success of annealing algorithms. This article outlines a unifying framework, ensemble annealing, that combines ideas from simulated annealing, histogram reweighting and nested sampling with concepts in thermodynamic control. Ensemble annealing simultaneously simulates a physical system and estimates its density of states. The...
Face Recognition using Optimal Representation Ensemble
Li, Hanxi; Gao, Yongsheng
2011-01-01
Recently, the face recognizers based on linear representations have been shown to deliver state-of-the-art performance. In real-world applications, however, face images usually suffer from expressions, disguises and random occlusions. The problematic facial parts undermine the validity of the linear-subspace assumption and thus the recognition performance deteriorates significantly. In this work, we address the problem in a learning-inference-mixed fashion. By observing that the linear-subspace assumption is more reliable on certain face patches rather than on the holistic face, some Bayesian Patch Representations (BPRs) are randomly generated and interpreted according to the Bayes' theory. We then train an ensemble model over the patch-representations by minimizing the empirical risk w.r.t the "leave-one-out margins". The obtained model is termed Optimal Representation Ensemble (ORE), since it guarantees the optimality from the perspective of Empirical Risk Minimization. To handle the unknown patterns in tes...
Statistical ensembles for money and debt
Viaggiu, Stefano; Lionetto, Andrea; Bargigli, Leonardo; Longo, Michele
2012-10-01
We build a statistical ensemble representation of two economic models describing respectively, in simplified terms, a payment system and a credit market. To this purpose we adopt the Boltzmann-Gibbs distribution where the role of the Hamiltonian is taken by the total money supply (i.e. including money created from debt) of a set of interacting economic agents. As a result, we can read the main thermodynamic quantities in terms of monetary ones. In particular, we define for the credit market model a work term which is related to the impact of monetary policy on credit creation. Furthermore, with our formalism we recover and extend some results concerning the temperature of an economic system, previously presented in the literature by considering only the monetary base as a conserved quantity. Finally, we study the statistical ensemble for the Pareto distribution.
Eigenstate Gibbs Ensemble in Integrable Quantum Systems
Nandy, Sourav; Das, Arnab; Dhar, Abhishek
2016-01-01
The Eigenstate Thermalization Hypothesis implies that for a thermodynamically large system in one of its eigenstates, the reduced density matrix describing any finite subsystem is determined solely by a set of {\\it relevant} conserved quantities. In a generic system, only the energy plays that role and hence eigenstates appear locally thermal. Integrable systems, on the other hand, possess an extensive number of such conserved quantities and hence the reduced density matrix requires specification of an infinite number of parameters (Generalized Gibbs Ensemble). However, here we show by unbiased statistical sampling of the individual eigenstates with a given finite energy density, that the local description of an overwhelming majority of these states of even such an integrable system is actually Gibbs-like, i.e. requires only the energy density of the eigenstate. Rare eigenstates that cannot be represented by the Gibbs ensemble can also be sampled efficiently by our method and their local properties are then s...
Ensemble Robustness of Deep Learning Algorithms
Feng, Jiashi; Zahavy, Tom; Kang, Bingyi; Xu, Huan; Mannor, Shie
2016-01-01
The question why deep learning algorithms perform so well in practice has attracted increasing research interest. However, most of well-established approaches, such as hypothesis capacity, robustness or sparseness, have not provided complete explanations, due to the high complexity of the deep learning algorithms and their inherent randomness. In this work, we introduce a new approach~\\textendash~ensemble robustness~\\textendash~towards characterizing the generalization performance of generic ...
Ensemble Data Assimilation: Algorithms and Software
Nerger, Lars
2014-01-01
Ensemble data assimilation is nowadays applied to various problems to estimate a model state and model parameters by combining the model predictions with observational data. At the Alfred Wegener Institute, the assimilation focuses on ocean-sea ice models and coupled ocean-biogeochemical models. The high dimension of realistic models requires particularly efficient algorithms that are also usable on supercomputers. For the application of such filters, the Parallel Data Assimilation Framework ...
Analysis and optimization of weighted ensemble sampling
Aristoff, David
2016-01-01
We give a mathematical framework for weighted ensemble (WE) sampling, a binning and resampling technique for efficiently computing probabilities in molecular dynamics. We prove that WE sampling is unbiased in a very general setting that includes adaptive binning. We show that when WE is used for stationary calculations in tandem with a Markov state model (MSM), the MSM can be used to optimize the allocation of replicas in the bins.
Staying Thermal with Hartree Ensemble Approximations
Salle, M; Vink, Jeroen C
2000-01-01
Using Hartree ensemble approximations to compute the real time dynamics of scalar fields in 1+1 dimension, we find that with suitable initial conditions, approximate thermalization is achieved much faster than found in our previous work. At large times, depending on the interaction strength and temperature, the particle distribution slowly changes: the Bose-Einstein distribution of the particle densities develops classical features. We also discuss variations of our method which are numerically more efficient.
Support Vector Machine Ensemble Based on Genetic Algorithm
Institute of Scientific and Technical Information of China (English)
LI Ye; YIN Ru-po; CAI Yun-ze; XU Xiao-ming
2006-01-01
Support vector machines (SVMs) have been introduced as effective methods for solving classification problems.However, due to some limitations in practical applications,their generalization performance is sometimes far from the expected level. Therefore, it is meaningful to study SVM ensemble learning. In this paper, a novel genetic algorithm based ensemble learning method, namely Direct Genetic Ensemble (DGE), is proposed. DGE adopts the predictive accuracy of ensemble as the fitness function and searches a good ensemble from the ensemble space. In essence, DGE is also a selective ensemble learning method because the base classifiers of the ensemble are selected according to the solution of genetic algorithm. In comparison with other ensemble learning methods, DGE works on a higher level and is more direct. Different strategies of constructing diverse base classifiers can be utilized in DGE.Experimental results show that SVM ensembles constructed by DGE can achieve better performance than single SVMs,bagged and boosted SVM ensembles. In addition, some valuable conclusions are obtained.
Spatially Coupled Ensembles Universally Achieve Capacity under Belief Propagation
Kudekar, Shrinivas; Urbanke, Ruediger
2012-01-01
We investigate spatially coupled code ensembles. For transmission over the binary erasure channel, it was recently shown that spatial coupling increases the belief propagation threshold of the ensemble to essentially the maximum a-priori threshold of the underlying component ensemble. This explains why convolutional LDPC ensembles, originally introduced by Felstrom and Zigangirov, perform so well over this channel. We show that the equivalent result holds true for transmission over general binary-input memoryless output-symmetric channels. More precisely, given a desired error probability and a gap to capacity, we can construct a spatially coupled ensemble which fulfills these constraints universally on this class of channels under belief propagation decoding. In fact, most codes in that ensemble have that property. The quantifier universal refers to the single ensemble/code which is good for all channels but we assume that the channel is known at the receiver. The key technical result is a proof that under b...
Various multistage ensembles for prediction of heating energy consumption
Directory of Open Access Journals (Sweden)
Radisa Jovanovic
2015-04-01
Full Text Available Feedforward neural network models are created for prediction of daily heating energy consumption of a NTNU university campus Gloshaugen using actual measured data for training and testing. Improvement of prediction accuracy is proposed by using neural network ensemble. Previously trained feed-forward neural networks are first separated into clusters, using k-means algorithm, and then the best network of each cluster is chosen as member of an ensemble. Two conventional averaging methods for obtaining ensemble output are applied; simple and weighted. In order to achieve better prediction results, multistage ensemble is investigated. As second level, adaptive neuro-fuzzy inference system with various clustering and membership functions are used to aggregate the selected ensemble members. Feedforward neural network in second stage is also analyzed. It is shown that using ensemble of neural networks can predict heating energy consumption with better accuracy than the best trained single neural network, while the best results are achieved with multistage ensemble.
Multivariate localization methods for ensemble Kalman filtering
Roh, S.
2015-12-03
In ensemble Kalman filtering (EnKF), the small number of ensemble members that is feasible to use in a practical data assimilation application leads to sampling variability of the estimates of the background error covariances. The standard approach to reducing the effects of this sampling variability, which has also been found to be highly efficient in improving the performance of EnKF, is the localization of the estimates of the covariances. One family of localization techniques is based on taking the Schur (element-wise) product of the ensemble-based sample covariance matrix and a correlation matrix whose entries are obtained by the discretization of a distance-dependent correlation function. While the proper definition of the localization function for a single state variable has been extensively investigated, a rigorous definition of the localization function for multiple state variables that exist at the same locations has been seldom considered. This paper introduces two strategies for the construction of localization functions for multiple state variables. The proposed localization functions are tested by assimilating simulated observations experiments into the bivariate Lorenz 95 model with their help.
Gradient Flow Analysis on MILC HISQ Ensembles
Bazavov, A; Brown, N; DeTar, C; Foley, J; Gottlieb, Steven; Heller, U M; Hetrick, J E; Komijani, J; Laiho, J; Levkova, L; Oktay, M; Sugar, R L; Toussaint, D; Van de Water, R S; Zhou, R
2014-01-01
We report on a preliminary scale determination with gradient-flow techniques on the $N_f = 2 + 1 + 1$ HISQ ensembles generated by the MILC collaboration. The ensembles include four lattice spacings, ranging from 0.15 to 0.06 fm, and both physical and unphysical values of the quark masses. The scales $\\sqrt{t_0}/a$ and $w_0/a$ are computed using Symanzik flow and the cloverleaf definition of $\\langle E \\rangle$ on each ensemble. Then both scales and the meson masses $aM_\\pi$ and $aM_K$ are adjusted for mistunings in the charm mass. Using a combination of continuum chiral perturbation theory and a Taylor series ansatz in the lattice spacing, the results are simultaneously extrapolated to the continuum and interpolated to physical quark masses. Our preliminary results are $\\sqrt{t_0} = 0.1422(7)$fm and $w_0 = 0.1732(10)$fm. We also find the continuum mass-dependence of $w_0$.
Ras Conformational Ensembles, Allostery, and Signaling.
Lu, Shaoyong; Jang, Hyunbum; Muratcioglu, Serena; Gursoy, Attila; Keskin, Ozlem; Nussinov, Ruth; Zhang, Jian
2016-06-01
Ras proteins are classical members of small GTPases that function as molecular switches by alternating between inactive GDP-bound and active GTP-bound states. Ras activation is regulated by guanine nucleotide exchange factors that catalyze the exchange of GDP by GTP, and inactivation is terminated by GTPase-activating proteins that accelerate the intrinsic GTP hydrolysis rate by orders of magnitude. In this review, we focus on data that have accumulated over the past few years pertaining to the conformational ensembles and the allosteric regulation of Ras proteins and their interpretation from our conformational landscape standpoint. The Ras ensemble embodies all states, including the ligand-bound conformations, the activated (or inactivated) allosteric modulated states, post-translationally modified states, mutational states, transition states, and nonfunctional states serving as a reservoir for emerging functions. The ensemble is shifted by distinct mutational events, cofactors, post-translational modifications, and different membrane compositions. A better understanding of Ras biology can contribute to therapeutic strategies. PMID:26815308
Gradient Flow Analysis on MILC HISQ Ensembles
Energy Technology Data Exchange (ETDEWEB)
Brown, Nathan [Washington U., St. Louis; Bazavov, Alexei [Brookhaven; Bernard, Claude [Washington U., St. Louis; DeTar, Carleton [Utah U.; Foley, Justin [Utah U.; Gottlieb, Steven [Indiana U.; Heller, Urs M. [APS, New York; Hetrick, J. E. [U. Pacific, Stockton; Komijani, Javad [Washington U., St. Louis; Laiho, Jack [Syracuse U.; Levkova, Ludmila [Utah U.; Oktay, M. B. [Utah U.; Sugar, Robert [UC, Santa Barbara; Toussaint, Doug [Arizona U.; Van de Water, Ruth S. [Fermilab; Zhou, Ran [Fermilab
2014-11-14
We report on a preliminary scale determination with gradient-flow techniques on the $N_f = 2 + 1 + 1$ HISQ ensembles generated by the MILC collaboration. The ensembles include four lattice spacings, ranging from 0.15 to 0.06 fm, and both physical and unphysical values of the quark masses. The scales $\\sqrt{t_0}/a$ and $w_0/a$ are computed using Symanzik flow and the cloverleaf definition of $\\langle E \\rangle$ on each ensemble. Then both scales and the meson masses $aM_\\pi$ and $aM_K$ are adjusted for mistunings in the charm mass. Using a combination of continuum chiral perturbation theory and a Taylor series ansatz in the lattice spacing, the results are simultaneously extrapolated to the continuum and interpolated to physical quark masses. Our preliminary results are $\\sqrt{t_0} = 0.1422(7)$fm and $w_0 = 0.1732(10)$fm. We also find the continuum mass-dependence of $w_0$.
Multivariate localization methods for ensemble Kalman filtering
Directory of Open Access Journals (Sweden)
S. Roh
2015-05-01
Full Text Available In ensemble Kalman filtering (EnKF, the small number of ensemble members that is feasible to use in a practical data assimilation application leads to sampling variability of the estimates of the background error covariances. The standard approach to reducing the effects of this sampling variability, which has also been found to be highly efficient in improving the performance of EnKF, is the localization of the estimates of the covariances. One family of localization techniques is based on taking the Schur (entry-wise product of the ensemble-based sample covariance matrix and a correlation matrix whose entries are obtained by the discretization of a distance-dependent correlation function. While the proper definition of the localization function for a single state variable has been extensively investigated, a rigorous definition of the localization function for multiple state variables has been seldom considered. This paper introduces two strategies for the construction of localization functions for multiple state variables. The proposed localization functions are tested by assimilating simulated observations experiments into the bivariate Lorenz 95 model with their help.
Multivariate localization methods for ensemble Kalman filtering
Roh, S.
2015-05-08
In ensemble Kalman filtering (EnKF), the small number of ensemble members that is feasible to use in a practical data assimilation application leads to sampling variability of the estimates of the background error covariances. The standard approach to reducing the effects of this sampling variability, which has also been found to be highly efficient in improving the performance of EnKF, is the localization of the estimates of the covariances. One family of localization techniques is based on taking the Schur (entry-wise) product of the ensemble-based sample covariance matrix and a correlation matrix whose entries are obtained by the discretization of a distance-dependent correlation function. While the proper definition of the localization function for a single state variable has been extensively investigated, a rigorous definition of the localization function for multiple state variables has been seldom considered. This paper introduces two strategies for the construction of localization functions for multiple state variables. The proposed localization functions are tested by assimilating simulated observations experiments into the bivariate Lorenz 95 model with their help.
Quantum statistical ensemble for emissive correlated systems
Shakirov, Alexey M.; Shchadilova, Yulia E.; Rubtsov, Alexey N.
2016-06-01
Relaxation dynamics of complex quantum systems with strong interactions towards the steady state is a fundamental problem in statistical mechanics. The steady state of subsystems weakly interacting with their environment is described by the canonical ensemble which assumes the probability distribution for energy to be of the Boltzmann form. The emergence of this probability distribution is ensured by the detailed balance of the transitions induced by the interaction with the environment. Here we consider relaxation of an open correlated quantum system brought into contact with a reservoir in the vacuum state. We refer to such a system as emissive since particles irreversibly evaporate into the vacuum. The steady state of the system is a statistical mixture of the stable eigenstates. We found that, despite the absence of the detailed balance, the stationary probability distribution over these eigenstates is of the Boltzmann form in each N -particle sector. A quantum statistical ensemble corresponding to the steady state is characterized by different temperatures in the different sectors, in contrast to the Gibbs ensemble. We investigate the transition rates between the eigenstates to understand the emergence of the Boltzmann distribution and find their exponential dependence on the transition energy. We argue that this property of transition rates is generic for a wide class of emissive quantum many-body systems.
Atarraf, Karima; Chater, Lamiae; Arroud, Mounir; Afifi, My Abderrahman
2014-01-01
L'histiocytose X ou histiocytose de Langerhans est une maladie de l'enfant et de l'adulte jeune. Dont l'incidence est estimée à 1 cas sur 200 000 par an. C'est une maladie au spectre clinique très divers, allant du simple granulome éosinophile à la forme grave multiviscérale avec dysfonctionnement d'organe. Les auteurs rapportent deux observations concernant deux localisations assez rares de cette maladie, au niveau du pubis chez le premier enfant, et au niveau de la scapula chez le deuxième. Chez nos deux malades la localisation était focale, et l’évolution était favorable. A travers ces deux observations, nous allons essayer de décrire les différents aspects cliniques et radiologiques et discuter a travers une revue de littérature les démarches diagnostiques et thérapeutiques de cette maladie rare. PMID:25478049
Ensemble Data Assimilation Without Ensembles: Methodology and Application to Ocean Data Assimilation
Keppenne, Christian L.; Rienecker, Michele M.; Kovach, Robin M.; Vernieres, Guillaume
2013-01-01
Two methods to estimate background error covariances for data assimilation are introduced. While both share properties with the ensemble Kalman filter (EnKF), they differ from it in that they do not require the integration of multiple model trajectories. Instead, all the necessary covariance information is obtained from a single model integration. The first method is referred-to as SAFE (Space Adaptive Forecast error Estimation) because it estimates error covariances from the spatial distribution of model variables within a single state vector. It can thus be thought of as sampling an ensemble in space. The second method, named FAST (Flow Adaptive error Statistics from a Time series), constructs an ensemble sampled from a moving window along a model trajectory. The underlying assumption in these methods is that forecast errors in data assimilation are primarily phase errors in space and/or time.
De praeceptis ferendis: good practice in multi-model ensembles
Directory of Open Access Journals (Sweden)
I. Kioutsioukis
2014-06-01
Full Text Available Ensembles of air quality models have been formally and empirically shown to outperform single models in many cases. Evidence suggests that ensemble error is reduced when the members form a diverse and accurate ensemble. Diversity and accuracy are hence two factors that should be taken care of while designing ensembles in order for them to provide better predictions. There exists a trade-off between diversity and accuracy for which one cannot be gained without expenses of the other. Theoretical aspects like the bias-variance-covariance decomposition and the accuracy-diversity decomposition are linked together and support the importance of creating ensemble that incorporates both the elements. Hence, the common practice of unconditional averaging of models without prior manipulation limits the advantages of ensemble averaging. We demonstrate the importance of ensemble accuracy and diversity through an inter-comparison of ensemble products for which a sound mathematical framework exists, and provide specific recommendations for model selection and weighting for multi model ensembles. To this end we have devised statistical tools that can be used for diagnostic evaluation of ensemble modelling products, complementing existing operational methods.
Seasonal hydrological ensemble forecasts over Europe
Arnal, Louise; Wetterhall, Fredrik; Stephens, Elisabeth; Cloke, Hannah; Pappenberger, Florian
2016-04-01
This study investigates the limits of predictability in dynamical seasonal discharge forecasting, in both space and time, over Europe. Seasonal forecasts have an important socioeconomic value. Applications are numerous and cover hydropower management, spring flood prediction, low flow prediction for navigation and agricultural water demands. Additionally, the constant increase in NWP skill for longer lead times and the predicted increase in the intensity and frequency of hydro-meteorological extremes, have amplified the incentive to promote and further improve hydrological forecasts on sub-seasonal to seasonal timescales. In this study, seasonal hydrological forecasts (SEA), driven by the ECMWF's System 4 in hindcast mode, were analysed against an Ensemble Streamflow Prediction (ESP) benchmark. The ESP was forced with an ensemble of resampled historical meteorological observations and started with perfect initial conditions. Both forecasts were produced by the LISFLOOD model, run on the pan-European scale with a spatial resolution of 5 by 5 km. The forecasts were issued monthly on a daily time step, from 1990 until the current time, up to a lead time of 7 months. The seasonal discharge forecasts were analysed against the ESP on a catchment scale in terms of their accuracy, skill and sharpness, using a diverse set of verification metrics (e.g. KGE, CRPSS and ROC). Additionally, a reverse-ESP was constructed by forcing the LISFLOOD model with a single perfect meteorological set of observations and initiated from an ensemble of resampled historical initial conditions. The comparison of the ESP with the reverse-ESP approach enabled the identification of the respective contribution of meteorological forcings and hydrologic initial conditions errors to seasonal discharge forecasting uncertainties in Europe. These results could help pinpoint target elements of the forecasting chain which, after being improved, could lead to substantial increase in discharge predictability
Cavity-Controlled Chemistry in Molecular Ensembles
Herrera, Felipe; Spano, Frank C.
2016-06-01
The demonstration of strong and ultrastrong coupling regimes of cavity QED with polyatomic molecules has opened new routes to control chemical dynamics at the nanoscale. We show that strong resonant coupling of a cavity field with an electronic transition can effectively decouple collective electronic and nuclear degrees of freedom in a disordered molecular ensemble, even for molecules with high-frequency quantum vibrational modes having strong electron-vibration interactions. This type of polaron decoupling can be used to control chemical reactions. We show that the rate of electron transfer reactions in a cavity can be orders of magnitude larger than in free space for a wide class of organic molecular species.
Supervised Ensemble Classification of Kepler Variable Stars
Bass, Gideon
2016-01-01
Variable star analysis and classification is an important task in the understanding of stellar features and processes. While historically classifications have been done manually by highly skilled experts, the recent and rapid expansion in the quantity and quality of data has demanded new techniques, most notably automatic classification through supervised machine learning. We present an expansion of existing work on the field by analyzing variable stars in the {\\em Kepler} field using an ensemble approach, combining multiple characterization and classification techniques to produce improved classification rates. Classifications for each of the roughly 150,000 stars observed by {\\em Kepler} are produced separating the stars into one of 14 variable star classes.
Cavity-controlled chemistry in molecular ensembles
Herrera, Felipe
2015-01-01
The demonstration of strong and ultrastrong coupling regimes of cavity QED with polyatomic molecules has opened new routes to control chemical dynamics at the nanoscale. We show that strong resonant coupling of a cavity field with an electronic transition can effectively decouple collective electronic and nuclear degrees of freedom in a disordered molecular ensemble, even for molecules with high-frequency quantum vibrational modes having strong electron-vibration interactions. This type of polaron decoupling can be used to control chemical reactions. We show that the rate of electron transfer reactions in a cavity can be orders of magnitude larger than in free space, for a wide class of organic molecular species.
Probabilistic Flash Flood Forecasting using Stormscale Ensembles
Hardy, J.; Gourley, J. J.; Kain, J. S.; Clark, A.; Novak, D.; Hong, Y.
2013-12-01
Flash flooding is one of the most costly and deadly natural hazards in the US and across the globe. The loss of life and property from flash floods could be mitigated with better guidance from hydrological models, but these models have limitations. For example, they are commonly initialized using rainfall estimates derived from weather radars, but the time interval between observations of heavy rainfall and a flash flood can be on the order of minutes, particularly for small basins in urban settings. Increasing the lead time for these events is critical for protecting life and property. Therefore, this study advances the use of quantitative precipitation forecasts (QPFs) from a stormscale NWP ensemble system into a distributed hydrological model setting to yield basin-specific, probabilistic flash flood forecasts (PFFFs). Rainfall error characteristics of the individual members are first diagnosed and quantified in terms of structure, amplitude, and location (SAL; Wernli et al., 2008). Amplitude and structure errors are readily correctable due to their diurnal nature, and the fine scales represented by the CAPS QPF members are consistent with radar-observed rainfall, mainly showing larger errors with afternoon convection. To account for the spatial uncertainty of the QPFs, we use an elliptic smoother, as in Marsh et al. (2012), to produce probabilistic QPFs (PQPFs). The elliptic smoother takes into consideration underdispersion, which is notoriously associated with stormscale ensembles, and thus, is good for targeting the approximate regions that may receive heavy rainfall. However, stormscale details contained in individual members are still needed to yield reasonable flash flood simulations. Therefore, on a case study basis, QPFs from individual members are then run through the hydrological model with their predicted structure and corrected amplitudes, but the locations of individual rainfall elements are perturbed within the PQPF elliptical regions using Monte
Bayesian ensemble refinement by replica simulations and reweighting
Hummer, Gerhard
2015-01-01
We describe different Bayesian ensemble refinement methods, examine their interrelation, and discuss their practical application. With ensemble refinement, the properties of dynamic and partially disordered (bio)molecular structures can be characterized by integrating a wide range of experimental data, including measurements of ensemble-averaged observables. We start from a Bayesian formulation in which the posterior is a functional that ranks different configuration space distributions. By maximizing this posterior, we derive an optimal Bayesian ensemble distribution. For discrete configurations, this optimal distribution is identical to that obtained by the maximum entropy "ensemble refinement of SAXS" (EROS) formulation. Bayesian replica ensemble refinement enhances the sampling of relevant configurations by imposing restraints on averages of observables in coupled replica molecular dynamics simulations. We find that the strength of the restraint scales with the number of replicas and we show that this sca...
A Framework for Non-Equilibrium Statistical Ensemble Theory
Institute of Scientific and Technical Information of China (English)
BI Qiao; HE Zu-Tan; LIU Jie
2011-01-01
Since Gibbs synthesized a general equilibrium statistical ensemble theory, many theorists have attempted to generalized the Gibbsian theory to non-equilibrium phenomena domain, however the status of the theory of nonequilibrium phenomena can not be said as firm as well established as the Gibbsian ensemble theory. In this work, we present a framework for the non-equilibrium statistical ensemble formalism based on a subdynamic kinetic equation (SKE) rooted from the Brussels-Austin school and followed by some up-to-date works. The constructed key is to use a similarity transformation between Gibbsian ensembles formalism based on Liouville equation and the subdynamic ensemble formalism based on the SKE. Using this formalism, we study the spin-Boson system, as cases of weak coupling or strongly coupling, and obtain the reduced density operators for the Canonical ensembles easily.
Skill forecasting from ensemble predictions of wind power
DEFF Research Database (Denmark)
Pinson, Pierre; Nielsen, Henrik Aalborg; Madsen, Henrik;
2009-01-01
ensemble predictions are derived from the conversion of ECMWF and NCEP ensemble forecasts of meteorological variables to wind power ensemble forecasts, as well as by a lagged average approach alternative. The ability of prediction risk indices calculated from the various types of ensembles forecasts...... risk indices aiming to give a comprehensive signal on the expected level of forecast uncertainty. Ensemble predictions of wind generation are used as input. A proposal for the definition of prediction risk indices is given. Such skill forecasts are based on the spread of ensemble forecasts (i.e. a set...... of alternative scenarios for the coming period) for a single prediction horizon or over a took-ahead period. It is shown on the test case of a Danish offshore wind farm how these prediction risk indices may be related to several levels of forecast uncertainty (and potential energy imbalances). Wind power...
Random matrix ensembles with column/row constraints: II
International Nuclear Information System (INIS)
We numerically analyze the random matrix ensembles of real-symmetric matrices with column/row constraints for many system conditions e.g. disorder type, matrix-size and basis-connectivity. The results reveal a rich behavior hidden beneath the spectral statistics and also confirm our analytical predictions, presented in part I of this paper, about the analogy of their spectral fluctuations with those of a critical Brownian ensemble which appears between Poisson and Gaussian orthogonal ensemble. (paper)
Enhanced ensemble-based 4DVar scheme for data assimilation
Yang, Yin; Robinson, Cordelia; Heitz, Dominique; Mémin, Etienne
2015-01-01
International audience Ensemble based optimal control schemes combine the components of ensemble Kalman filters and variational data assimilation (4DVar). They are trendy because they are easier to implement than 4DVar. In this paper, we evaluate a modified version of an ensemble based optimal control strategy for image data assimilation. This modified method is assessed with a Shallow Water model combined with synthetic data and original incomplete experimental depth sensor observations. ...
Data assimilation with the weighted ensemble Kalman filter
Papadakis, Nicolas; Mémin, Etienne; Cuzol, Anne; Gengembre, Nicolas
2010-01-01
In this paper, two data assimilation methods based on sequential Monte Carlo sampling are studied and compared: the ensemble Kalman filter and the particle filter. Each of these techniques has its own advantages and drawbacks. In this work, we try to get the best of each method by combining them. The proposed algorithm, called the weighted ensemble Kalman filter, consists to rely on the Ensemble Kalman Filter updates of samples in order to define a proposal distribution for the particle filte...
Black Hole Statistical Mechanics and The Angular Velocity Ensemble
Thomson, Mitchell; Dyer, Charles C.
2012-01-01
An new ensemble - the angular velocity ensemble - is derived using Jaynes' method of maximising entropy subject to prior information constraints. The relevance of the ensemble to black holes is motivated by a discussion of external parameters in statistical mechanics and their absence from the Hamiltonian of general relativity. It is shown how this leads to difficulty in deriving entropy as a function of state and recovering the first law of thermodynamics from the microcanonical and canonica...
Unconditional two-mode squeezing of separated atomic ensembles
Parkins, A S; Solano, E
2005-01-01
We propose schemes for the unconditional preparation of a two-mode squeezed state of effective bosonic modes realized in a pair of atomic ensembles interacting collectively with optical cavity and laser fields. The scheme uses Raman transitions between stable atomic ground states and under ideal conditions produces pure entangled states in the steady state. The scheme works both for ensembles confined within a single cavity and for ensembles confined in separate, cascaded cavities.
Enhanced Sampling in the Well-Tempered Ensemble
Bonomi, M.; Parrinello, M
2009-01-01
We introduce the well-tempered ensemble (WTE) which is the biased ensemble sampled by well-tempered metadynamics when the energy is used as collective variable. WTE can be designed so as to have approximately the same average energy as the canonical ensemble but much larger fluctuations. These two properties lead to an extremely fast exploration of phase space. An even greater efficiency is obtained when WTE is combined with parallel tempering. Unbiased Boltzmann averages are computed on the ...
Bayesian ensemble refinement by replica simulations and reweighting
Hummer, Gerhard; Köfinger, Jürgen
2015-12-01
We describe different Bayesian ensemble refinement methods, examine their interrelation, and discuss their practical application. With ensemble refinement, the properties of dynamic and partially disordered (bio)molecular structures can be characterized by integrating a wide range of experimental data, including measurements of ensemble-averaged observables. We start from a Bayesian formulation in which the posterior is a functional that ranks different configuration space distributions. By maximizing this posterior, we derive an optimal Bayesian ensemble distribution. For discrete configurations, this optimal distribution is identical to that obtained by the maximum entropy "ensemble refinement of SAXS" (EROS) formulation. Bayesian replica ensemble refinement enhances the sampling of relevant configurations by imposing restraints on averages of observables in coupled replica molecular dynamics simulations. We show that the strength of the restraints should scale linearly with the number of replicas to ensure convergence to the optimal Bayesian result in the limit of infinitely many replicas. In the "Bayesian inference of ensembles" method, we combine the replica and EROS approaches to accelerate the convergence. An adaptive algorithm can be used to sample directly from the optimal ensemble, without replicas. We discuss the incorporation of single-molecule measurements and dynamic observables such as relaxation parameters. The theoretical analysis of different Bayesian ensemble refinement approaches provides a basis for practical applications and a starting point for further investigations.
Bayesian ensemble refinement by replica simulations and reweighting.
Hummer, Gerhard; Köfinger, Jürgen
2015-12-28
We describe different Bayesian ensemble refinement methods, examine their interrelation, and discuss their practical application. With ensemble refinement, the properties of dynamic and partially disordered (bio)molecular structures can be characterized by integrating a wide range of experimental data, including measurements of ensemble-averaged observables. We start from a Bayesian formulation in which the posterior is a functional that ranks different configuration space distributions. By maximizing this posterior, we derive an optimal Bayesian ensemble distribution. For discrete configurations, this optimal distribution is identical to that obtained by the maximum entropy "ensemble refinement of SAXS" (EROS) formulation. Bayesian replica ensemble refinement enhances the sampling of relevant configurations by imposing restraints on averages of observables in coupled replica molecular dynamics simulations. We show that the strength of the restraints should scale linearly with the number of replicas to ensure convergence to the optimal Bayesian result in the limit of infinitely many replicas. In the "Bayesian inference of ensembles" method, we combine the replica and EROS approaches to accelerate the convergence. An adaptive algorithm can be used to sample directly from the optimal ensemble, without replicas. We discuss the incorporation of single-molecule measurements and dynamic observables such as relaxation parameters. The theoretical analysis of different Bayesian ensemble refinement approaches provides a basis for practical applications and a starting point for further investigations.
Fractional exclusion statistics and the Random Matrix Boson Ensemble
Hernández-Quiroz, Saul; Benet, Luis; Flores, Jorge; Cocho, Germinal
2012-01-01
The k-body Gaussian Embedded Ensemble of Random Matrices is considered for N bosons distributed on two single-particle levels. When k = N, the ensemble is equivalent to the Gaussian Orthogonal Ensemble (GOE), and when k = 2 it corresponds to the Two-body Random Ensemble (TBRE) for bosons. It is shown that the energy spectrum leads to a rank function which is of the form of a discrete generalized beta distribution. The same distribution is obtained assuming N non-interacting quasiparticles that obey the fractional exclusion statistics introduced by Haldane two decades ago.
Relation between native ensembles and experimental structures of proteins
DEFF Research Database (Denmark)
Best, R. B.; Lindorff-Larsen, Kresten; DePristo, M. A.;
2006-01-01
Data Bank ensembles; moreover, we show that the effects of uncertainties in structure determination are insufficient to explain the results. These results highlight the importance of accounting for native-state protein dynamics in making comparisons with ensemble-averaged experimental data and suggest......Different experimental structures of the same protein or of proteins with high sequence similarity contain many small variations. Here we construct ensembles of "high-sequence similarity Protein Data Bank" (HSP) structures and consider the extent to which such ensembles represent the structural...
Ensemble Kalman filtering with residual nudging
Directory of Open Access Journals (Sweden)
Xiaodong Luo
2012-10-01
Full Text Available Covariance inflation and localisation are two important techniques that are used to improve the performance of the ensemble Kalman filter (EnKF by (in effect adjusting the sample covariances of the estimates in the state space. In this work, an additional auxiliary technique, called residual nudging, is proposed to monitor and, if necessary, adjust the residual norms of state estimates in the observation space. In an EnKF with residual nudging, if the residual norm of an analysis is larger than a pre-specified value, then the analysis is replaced by a new one whose residual norm is no larger than a pre-specified value. Otherwise, the analysis is considered as a reasonable estimate and no change is made. A rule for choosing the pre-specified value is suggested. Based on this rule, the corresponding new state estimates are explicitly derived in case of linear observations. Numerical experiments in the 40-dimensional Lorenz 96 model show that introducing residual nudging to an EnKF may improve its accuracy and/or enhance its stability against filter divergence, especially in the small ensemble scenario.
Hsaing Waing: Classical Ensemble of Myanmar
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Chalermkit Kengkeaw
2013-09-01
Full Text Available Hsaing Waing is a classical music ensemble and a prominent culturalidentity of Myanmar. The Hsaing Waing ensemble consists of many instruments such as the Pat Waing, Muang Hsaing, Hne, Chauk Lon Bat, Byaung, Wa, Wallet Kok, Yakin, Si, and Mong. The earliest historical record of the Hsaing Waing is in 1544 where the Pat Waing and possibly the Hsaing Waing, was in royal service at the court of King Tabinshwehti of the Taungoo dynasty and prospered under the Kaunbaun dynasty up to colonial rule. During colonization, Hsaing Waing’s popularity declined but other innovations were introduced such as modern recording mediums and broadcasts which transferred the popularity of Hsaing Waing to a broader public audience and brought innovation to religious music, ceremonial rituals, fusion of westernmusical instruments such as the piano, violin and mandolin. The wealth of knowledge and numbers of connoisseur during the Kaunbaun dynasty led to the transfer of knowledge to many apprentices which were responsible for the development and adaptation and continuation of Hsaing Waing during colonization, socialism and independence. The transfer of knowledge was carried out by previous generations through apprentices, family members, close relatives and inspired individuals. The factors for the successful inheritance of Hsaing Waing are management, education, musicians and opportunity.
Ensemble Kalman filtering with residual nudging
Luo, X.
2012-10-03
Covariance inflation and localisation are two important techniques that are used to improve the performance of the ensemble Kalman filter (EnKF) by (in effect) adjusting the sample covariances of the estimates in the state space. In this work, an additional auxiliary technique, called residual nudging, is proposed to monitor and, if necessary, adjust the residual norms of state estimates in the observation space. In an EnKF with residual nudging, if the residual norm of an analysis is larger than a pre-specified value, then the analysis is replaced by a new one whose residual norm is no larger than a pre-specified value. Otherwise, the analysis is considered as a reasonable estimate and no change is made. A rule for choosing the pre-specified value is suggested. Based on this rule, the corresponding new state estimates are explicitly derived in case of linear observations. Numerical experiments in the 40-dimensional Lorenz 96 model show that introducing residual nudging to an EnKF may improve its accuracy and/or enhance its stability against filter divergence, especially in the small ensemble scenario.
Deterministic Mean-Field Ensemble Kalman Filtering
Law, Kody J. H.
2016-05-03
The proof of convergence of the standard ensemble Kalman filter (EnKF) from Le Gland, Monbet, and Tran [Large sample asymptotics for the ensemble Kalman filter, in The Oxford Handbook of Nonlinear Filtering, Oxford University Press, Oxford, UK, 2011, pp. 598--631] is extended to non-Gaussian state-space models. A density-based deterministic approximation of the mean-field limit EnKF (DMFEnKF) is proposed, consisting of a PDE solver and a quadrature rule. Given a certain minimal order of convergence k between the two, this extends to the deterministic filter approximation, which is therefore asymptotically superior to standard EnKF for dimension d<2k. The fidelity of approximation of the true distribution is also established using an extension of the total variation metric to random measures. This is limited by a Gaussian bias term arising from nonlinearity/non-Gaussianity of the model, which arises in both deterministic and standard EnKF. Numerical results support and extend the theory.
Folie à Deux – A Clinical Case of Folie Imposée in a Mother/Child Relationship
Directory of Open Access Journals (Sweden)
Marta Nascimento
2013-11-01
Full Text Available Background: Even though the origin of the concept of shared delusion is not consensual, the term folie a deux was introduced in 1877 by two french researchers – Lasègue and Falret. According to the original concept, a person (inductor, cognitively dominant, develops a delusional idea that progressively imposes to a second person (induced, with whom he keeps a close relationship. The four psychopathologic subtypes known – folie imposée, folie simultanée, folie communiquée and folie induite, were described in the final of the XIX century, but its classification and conceptualization was assigned to the american researcher Gralnick (1942. Aim, materials and methods: It is intended to highlight some clinical aspects of the shared delusion disorder, its epidemiological and psycopathogenic characterization and therapeutical approach. In order to achieve it, the authors presented a clinical case report and respective non systematic literature review. Results: It is a case of shared delusion of the type folie imposée in a pair mother/son. The inductor (son suffers from bipolar disorder and asperger syndrome and shared with his mother (induced and carer a persecutory delusion. Conclusions: It is highlighted the importance of a social isolation context and close contact between both members in the genesis of the disease; it is discussed the subject of the cognitive dominance between the inductor and the induced and the implications of the separation of the pair mother/son, as primary therapeutic action.
Folie à Deux – A Clinical Case of Folie Imposée in a Mother/Child Relationship
Directory of Open Access Journals (Sweden)
Marta Nascimento
2012-12-01
Full Text Available Background: Even though the origin of the concept of shared delusion is not consensual, the term folie a deux was introduced in 1877 by two french researchers – Lasègue and Falret. According to the original concept, a person (inductor, cognitively dominant, develops a delusional idea that progressively imposes to a second person (induced, with whom he keeps a close relationship. The four psychopathologic subtypes known – folie imposée, folie simultanée, folie communiquée and folie induite, were described in the final of the XIX century, but its classification and conceptualization was assigned to the american researcher Gralnick (1942. Aim, materials and methods: It is intended to highlight some clinical aspects of the shared delusion disorder, its epidemiological and psycopathogenic characterization and therapeutical approach. In order to achieve it, the authors presented a clinical case report and respective non systematic literature review. Results: It is a case of shared delusion of the type folie imposée in a pair mother/son. The inductor (son suffers from bipolar disorder and asperger syndrome and shared with his mother (induced and carer a persecutory delusion. Conclusions: It is highlighted the importance of a social isolation context and close contact between both members in the genesis of the disease; it is discussed the subject of the cognitive dominance between the inductor and the induced and the implications of the separation of the pair mother/son, as primary therapeutic action.
Institute of Scientific and Technical Information of China (English)
Jun Kyung KAY; Hyun Mee KIM; Young-Youn PARK; Joohyung SON
2013-01-01
Using the Met Office Global and Regional Ensemble Prediction System (MOGREPS) implemented at the Korea Meteorological Administration (KMA),the effect of doubling the ensemble size on the performance of ensemble prediction in the warm season was evaluated.Because a finite ensemble size causes sampling error in the full forecast probability distribution function (PDF),ensemble size is closely related to the efficiency of the ensemble prediction system.Prediction capability according to doubling the ensemble size was evaluated by increasing the number of ensembles from 24 to 48 in MOGREPS implemented at the KMA.The initial analysis perturbations generated by the Ensemble Transform Kalman Filter (ETKF) were integrated for 10 days from 22 May to 23 June 2009.Several statistical verification scores were used to measure the accuracy,reliability,and resolution of ensemble probabilistic forecasts for 24 and 48 ensemble member forecasts.Even though the results were not significant,the accuracy of ensemble prediction improved slightly as ensemble size increased,especially for longer forecast times in the Northern Hemisphere.While increasing the number of ensemble members resulted in a slight improvement in resolution as forecast time increased,inconsistent results were obtained for the scores assessing the reliability of ensemble prediction.The overall performance of ensemble prediction in terms of accuracy,resolution,and reliability increased slightly with ensemble size,especially for longer forecast times.
Rôle de la radiothérapie dans le traitement de l'améloblastome: à propos de deux cas
El Mazghi, Abderrahman; Bouhafa, Touria; El Kacemi, Hanan; Loukili, Kaoutar; Chbani, Laila; Kebdani, Taieb; Hassouni, Khalid
2014-01-01
L'améloblastome est une tumeur odontogène bénigne mais à pouvoir agressif et invasif local important. C'est une tumeur rare, elle représente 1% des tumeurs des maxillaires. Le rôle de la radiothérapie dans son traitement est actuellement démontré pour les tumeurs inopérables. Nous rapportons 2 cas d'améloblastomes mandibulaires chez deux patients qui ont bénéficié d'une radiothérapie externe à la dose de 60 Gy. L’évolution a été marquée par une rémission complète de la maladie dans les deux cas avec un recul de 2 et 5 ans. PMID:25722762
Risque de Défaut et Risque de Liquidité : Une Etude de Deux Composantes du Spread de Crédit
Hayette Gatfaoui
2003-01-01
La marge de taux obligataire ou encore le spread de crédit est réputé(e) pour son rôle de mesure du risque de crédit. Dans ce contexte, l’attention est portée à deux de ses principales composantes : le risque de défaut et le risque de liquidité. L’évolution du risque de défaut dépend alors de l’articulation entre ces deux quantités que l’on ne sait pas encore distinguer l’une de l’autre. Dans un contexte de crise financière, le risque de défaut l’emporte sur le risque de liquidité, ce qui se ...
Van Elslande, P.; Fouquet, K.; Vincensini, M.; Nussbaum, F.; Roynard, M.
2008-01-01
Cette étude a pour objectif d'appréhender et mieux comprendre les interactions de facteurs et les mécanismes en jeu dans les accidents des deux-roues motorisés. Elle vise également à mettre en évidence la diversité de ces accidents de façon à permettre la définition de mesures plus adaptée à chaque problème en jeu. Les deux-roues motorisés se distinguent des autres modes de transport terrestres par des différences d'ordre dynamique, perceptif, mais aussi comportemental, attitudinal et social....
Directory of Open Access Journals (Sweden)
Mariam Faransis
2013-11-01
La présente étude en illustre un cas, en décrivant la composition d’un extrait de La neige en deuil, en termes de paramètres énonciatifs discursifs, dits, par l’auteure, plans de référence, reformulation, notionnelle et terminologique, de la distinction d’É. BENVENISTE de deux plans d’énonciation : plan de l’histoire vs plan du discours, et en montrant comment l’articulation de la composition donne lieu à l’alternance de deux axes narratifs, décrits, à leur tour, par des concepts narratologiques pris à G. GENETTE, pour circonscrire, par là, les fonctions correspondantes et leur intérêt dans l’économie générale du roman.
Raynaud, Suzanne; Lacaze, Yannick; Bruguier, Olivier; La Boisse (de), Henri; Fabre, René
2008-01-01
Les tables à marqueterie de pierre ont été créées comme catalogues pour présenter les pierres marbrières disponibles sur le marché au xviie et xviiiesiècle. Notre étude porte sur deux tables dont le plateau est une marqueterie de pierres marbrières provenant très majoritairement de la région Languedoc-Roussillon. Dans les deux cas, la marqueterie de pierre est montée sur un support en mortier, technique de fabrication connue dans les ateliers français. Le plus célèbre de ces ateliers est l’at...
Matile-Ferrero, D.; Couturier, Guy
1993-01-01
#Ceroplastes flosculoides$ Matile-Ferrero n.sp. (Coccidae) et #Austrotachardiella sexcordata$ Matile-Ferrero n.sp. (Kerriidae), sont décrits et illustrés. Les deux espèces sont des ravageurs d'une Myrtacée cultivée, #Myrciaria dubia$, en Amazonie péruvienne. #Austrotachardiella trilobata$ (Mendes) n.comb. est transférée de #Tachardiella$ Cockerell. (Résumé d'auteur)
Guelilia, Zakaria; Loison, Renaud; Gillard, Raphaël
2015-01-01
National audience Dans ce papier, une méthode rapide et rigoureuse (MM-DG-FDTD) est proposée, validée et exploitée pour analyser électromagnétiquement des problèmes multi-échelles de transmission entre deux antennes ULB dans lesquels la position de l'antenne de réception varie.
Ensemble Forecast: A New Approach to Uncertainty and Predictability
Institute of Scientific and Technical Information of China (English)
无
2005-01-01
Ensemble techniques have been used to generate daily numerical weather forecasts since the 1990s in numerical centers around the world due to the increase in computation ability. One of the main purposes of numerical ensemble forecasts is to try to assimilate the initial uncertainty (initial error) and the forecast uncertainty (forecast error) by applying either the initial perturbation method or the multi-model/multiphysics method. In fact, the mean of an ensemble forecast offers a better forecast than a deterministic (or control) forecast after a short lead time (3 5 days) for global modelling applications. There is about a 1-2-day improvement in the forecast skill when using an ensemble mean instead of a single forecast for longer lead-time. The skillful forecast (65% and above of an anomaly correlation) could be extended to 8 days (or longer) by present-day ensemble forecast systems. Furthermore, ensemble forecasts can deliver a probabilistic forecast to the users, which is based on the probability density function (PDF)instead of a single-value forecast from a traditional deterministic system. It has long been recognized that the ensemble forecast not only improves our weather forecast predictability but also offers a remarkable forecast for the future uncertainty, such as the relative measure of predictability (RMOP) and probabilistic quantitative precipitation forecast (PQPF). Not surprisingly, the success of the ensemble forecast and its wide application greatly increase the confidence of model developers and research communities.
Modality-Driven Classification and Visualization of Ensemble Variance
Energy Technology Data Exchange (ETDEWEB)
Bensema, Kevin; Gosink, Luke J.; Obermaier, Harald; Joy, Kenneth
2016-10-01
Advances in computational power now enable domain scientists to address conceptual and parametric uncertainty by running simulations multiple times in order to sufficiently sample the uncertain input space. While this approach helps address conceptual and parametric uncertainties, the ensemble datasets produced by this technique present a special challenge to visualization researchers as the ensemble dataset records a distribution of possible values for each location in the domain. Contemporary visualization approaches that rely solely on summary statistics (e.g., mean and variance) cannot convey the detailed information encoded in ensemble distributions that are paramount to ensemble analysis; summary statistics provide no information about modality classification and modality persistence. To address this problem, we propose a novel technique that classifies high-variance locations based on the modality of the distribution of ensemble predictions. Additionally, we develop a set of confidence metrics to inform the end-user of the quality of fit between the distribution at a given location and its assigned class. We apply a similar method to time-varying ensembles to illustrate the relationship between peak variance and bimodal or multimodal behavior. These classification schemes enable a deeper understanding of the behavior of the ensemble members by distinguishing between distributions that can be described by a single tendency and distributions which reflect divergent trends in the ensemble.
Practice Makes Perfect?: Effective Practice Instruction in Large Ensembles
Prichard, Stephanie
2012-01-01
Helping young musicians learn how to practice effectively is a challenge faced by all music educators. This article presents a system of individual music practice instruction that can be seamlessly integrated within large-ensemble rehearsals. Using a step-by-step approach, large-ensemble conductors can teach students to identify and isolate…
An iterative ensemble Kalman filter for reservoir engineering applications
Krymskaya, M.V.; Hanea, R.G.; Verlaan, M.
2009-01-01
The study has been focused on examining the usage and the applicability of ensemble Kalman filtering techniques to the history matching procedures. The ensemble Kalman filter (EnKF) is often applied nowadays to solving such a problem. Meanwhile, traditional EnKF requires assumption of the distributi
Exact ensemble density-functional theory for excited states
Yang, Zeng-hui; Pribram-Jones, Aurora; Burke, Kieron; Needs, Richard J; Ullrich, Carsten A
2014-01-01
We construct exact Kohn-Sham potentials for the ensemble density-functional theory (EDFT) of excited states from the ground and excited states of helium. The exchange-correlation potential is compared with current approximations, which miss prominent features. The ensemble derivative discontinuity is tested, and the virial theorem is proven and illustrated.
A Comparison of Ensemble Kalman Filters for Storm Surge Assimilation
Altaf, M. U.
2014-08-01
This study evaluates and compares the performances of several variants of the popular ensembleKalman filter for the assimilation of storm surge data with the advanced circulation (ADCIRC) model. Using meteorological data from Hurricane Ike to force the ADCIRC model on a domain including the Gulf ofMexico coastline, the authors implement and compare the standard stochastic ensembleKalman filter (EnKF) and three deterministic square root EnKFs: the singular evolutive interpolated Kalman (SEIK) filter, the ensemble transform Kalman filter (ETKF), and the ensemble adjustment Kalman filter (EAKF). Covariance inflation and localization are implemented in all of these filters. The results from twin experiments suggest that the square root ensemble filters could lead to very comparable performances with appropriate tuning of inflation and localization, suggesting that practical implementation details are at least as important as the choice of the square root ensemble filter itself. These filters also perform reasonably well with a relatively small ensemble size, whereas the stochastic EnKF requires larger ensemble sizes to provide similar accuracy for forecasts of storm surge.
Competitive Learning Neural Network Ensemble Weighted by Predicted Performance
Ye, Qiang
2010-01-01
Ensemble approaches have been shown to enhance classification by combining the outputs from a set of voting classifiers. Diversity in error patterns among base classifiers promotes ensemble performance. Multi-task learning is an important characteristic for Neural Network classifiers. Introducing a secondary output unit that receives different…
Improving land resource evaluation using fuzzy neural network ensembles
XUE, Y.-J.; HU, Y.-M.; Liu, S.-G.; YANG, J.-F.; CHEN, Q.-C.; BAO, S.-T.
2007-01-01
Land evaluation factors often contain continuous-, discrete- and nominal-valued attributes. In traditional land evaluation, these different attributes are usually graded into categorical indexes by land resource experts, and the evaluation results rely heavily on experts' experiences. In order to overcome the shortcoming, we presented a fuzzy neural network ensemble method that did not require grading the evaluation factors into categorical indexes and could evaluate land resources by using the three kinds of attribute values directly. A fuzzy back propagation neural network (BPNN), a fuzzy radial basis function neural network (RBFNN), a fuzzy BPNN ensemble, and a fuzzy RBFNN ensemble were used to evaluate the land resources in Guangdong Province. The evaluation results by using the fuzzy BPNN ensemble and the fuzzy RBFNN ensemble were much better than those by using the single fuzzy BPNN and the single fuzzy RBFNN, and the error rate of the single fuzzy RBFNN or fuzzy RBFNN ensemble was lower than that of the single fuzzy BPNN or fuzzy BPNN ensemble, respectively. By using the fuzzy neural network ensembles, the validity of land resource evaluation was improved and reliance on land evaluators' experiences was considerably reduced. ?? 2007 Soil Science Society of China.
Ensembles and their modules as objects of cartosemiotic inquiry
Directory of Open Access Journals (Sweden)
Hansgeorg Schlichtmann
2010-01-01
Full Text Available The structured set of signs in a map face -- here called map-face aggregate or MFA -- and the associated marginal notes make up an ensemble of modules or components (modular ensemble. Such ensembles are recognized where groups of entries are intuitively viewed as complex units, which includes the case that entries are consulted jointly and thus are involved in the same process of sign reception. Modular ensembles are amenable to semiotic study, just as are written or pictorial stories. Four kinds (one of them mentioned above are discussed in detail, two involving single MFAs, the other two being assemblages of maps, such as atlases. In terms of their internal structure, two types are recognized: the combinate (or grouping, in which modules are directly linked by combinatorial relations (example above, and the cumulate (or collection (of documents, in which modules are indirectly related through some conceptual commonality (example: series of geological maps. The discussion then turns to basic points concerning modular ensembles (identification of a module, internal organization of an ensemble, and characteristics which establish an ensemble as a unit and further to a few general semiotic concepts as they relate to the present research. Since this paper originated as a reaction to several of A. Wolodtschenko’s recent publications, it concludes with comments on some of his arguments which pertain to modular ensembles.
Thermal Insulation Distribution Pattern of Layered Clothing Ensemble
Institute of Scientific and Technical Information of China (English)
李俊; 韦鸿发; 刘岩; 张渭源
2004-01-01
With a thermal manikin, the distribution pattern of thermal insulation in multi-layered clothing ensemble is studied. It is found that the thermal insulation of multi-layered clothing ensemble has certain statistical relationship with the thermal insulation of each layer, and the prediction equation has been established.
Directory of Open Access Journals (Sweden)
Kazuo Saito
2012-01-01
Full Text Available The effect of lateral boundary perturbations (LBPs on the mesoscale breeding (MBD method and the local ensemble transform Kalman filter (LETKF as the initial perturbations generators for mesoscale ensemble prediction systems (EPSs was examined. A LBPs method using the Japan Meteorological Agency's (JMA's operational one-week global ensemble prediction was developed and applied to the mesoscale EPS of the Meteorological Research Institute for the World Weather Research Programme, Beijing 2008 Olympics Research and Development Project. The amplitude of the LBPs was adjusted based on the ensemble spread statistics considering the difference of the forecast times of the JMA's one-week EPS and the associated breeding/ensemble Kalman filter (EnKF cycles. LBPs in the ensemble forecast increase the ensemble spread and improve the accuracy of the ensemble mean forecast. In the MBD method, if LBPs were introduced in its breeding cycles, the growth rate of the generated bred vectors is increased, and the ensemble spread and the root mean square errors (RMSEs of the ensemble mean are further improved in the ensemble forecast. With LBPs in the breeding cycles, positional correspondences to the meteorological disturbances and the orthogonality of the bred vectors are improved. Brier Skill Scores (BSSs also showed a remarkable effect of LBPs in the breeding cycles. LBPs showed a similar effect with the LETKF. If LBPs were introduced in the EnKF data assimilation cycles, the ensemble spread, ensemble mean accuracy, and BSSs for precipitation were improved, although the relative advantage of LETKF as the initial perturbations generator against MDB was not necessarily clear. LBPs in the EnKF cycles contribute not to the orthogonalisation but to prevent the underestimation of the forecast error near the lateral boundary.The accuracy of the LETKF analyses was compared with that of the mesoscale 4D-VAR analyses. With LBPs in the LETKF cycles, the RMSEs of the
ARM Cloud Retrieval Ensemble Data Set (ACRED)
Energy Technology Data Exchange (ETDEWEB)
Zhao, C; Xie, S; Klein, SA; McCoy, R; Comstock, JM; Delanoë, J; Deng, M; Dunn, M; Hogan, RJ; Jensen, MP; Mace, GG; McFarlane, SA; O’Connor, EJ; Protat, A; Shupe, MD; Turner, D; Wang, Z
2011-09-12
This document describes a new Atmospheric Radiation Measurement (ARM) data set, the ARM Cloud Retrieval Ensemble Data Set (ACRED), which is created by assembling nine existing ground-based cloud retrievals of ARM measurements from different cloud retrieval algorithms. The current version of ACRED includes an hourly average of nine ground-based retrievals with vertical resolution of 45 m for 512 layers. The techniques used for the nine cloud retrievals are briefly described in this document. This document also outlines the ACRED data availability, variables, and the nine retrieval products. Technical details about the generation of ACRED, such as the methods used for time average and vertical re-grid, are also provided.
Predicting protein dynamics from structural ensembles
Copperman, J
2015-01-01
The biological properties of proteins are uniquely determined by their structure and dynamics. A protein in solution populates a structural ensemble of metastable configurations around the global fold. From overall rotation to local fluctuations, the dynamics of proteins can cover several orders of magnitude in time scales. We propose a simulation-free coarse-grained approach which utilizes knowledge of the important metastable folded states of the protein to predict the protein dynamics. This approach is based upon the Langevin Equation for Protein Dynamics (LE4PD), a Langevin formalism in the coordinates of the protein backbone. The linear modes of this Langevin formalism organize the fluctuations of the protein, so that more extended dynamical cooperativity relates to increasing energy barriers to mode diffusion. The accuracy of the LE4PD is verified by analyzing the predicted dynamics across a set of seven different proteins for which both relaxation data and NMR solution structures are available. Using e...
Optimal Spatial Prediction Using Ensemble Machine Learning.
Davies, Molly Margaret; van der Laan, Mark J
2016-05-01
Spatial prediction is an important problem in many scientific disciplines. Super Learner is an ensemble prediction approach related to stacked generalization that uses cross-validation to search for the optimal predictor amongst all convex combinations of a heterogeneous candidate set. It has been applied to non-spatial data, where theoretical results demonstrate it will perform asymptotically at least as well as the best candidate under consideration. We review these optimality properties and discuss the assumptions required in order for them to hold for spatial prediction problems. We present results of a simulation study confirming Super Learner works well in practice under a variety of sample sizes, sampling designs, and data-generating functions. We also apply Super Learner to a real world dataset. PMID:27130244
Modeling Coordination Problems in a Music Ensemble
DEFF Research Database (Denmark)
Frimodt-Møller, Søren R.
2008-01-01
This paper considers in general terms, how musicians are able to coordinate through rational choices in a situation of (temporary) doubt in an ensemble performance. A fictitious example involving a 5-bar development in an unknown piece of music is analyzed in terms of epistemic logic, more...... specifically a multi-agent system, where it is shown that perfect coordination can only be certain to take place if the musicians have common knowledge of certain rules of the composition. We subsequently argue, however, that the musicians need not agree on the central features of the piece of music in order...... to coordinate. Such coordination can be described in terms of Michael Bacharach's theory of variable frames as an aid to solve game theoretic coordination problems....
Le Pape, G; Lassalle, J M
1979-10-01
Des enregistrements continus d'activité locomotrice ont été effectués sur des souris mâles isolées des lignées Balb/c et C57bl/6, vivant en cages d'élevage ou en milieu semi- naturel. Les résultats montrent que les différences entre ces deux situations ne sont pas perçues de la même façon par les animaux des deux lign'ees: alors qu'en cages d'élevage les souris des deux lignées experiment la même quantité totale d'activaté, en milieu semi-naturel les souris Balb/c sont plus actives que les C57bl/6. En outre, l≐s différences observées entre les lignées pour la repartition de l'activité au cours du nycthèmere s'inversent lorsque l'on passe d'une situation à l'autre. L'étude de la variabilité fait aparaître une dispersion plus grande des performances dans la lignée C57bl/6 en cages d'élevage, alors qu'en milieu semi-naturel la dispersion est plus chez Bal/c.
Directory of Open Access Journals (Sweden)
Freyburger L.
2011-11-01
Full Text Available L’innocuité de deux vaccins commercialisés en France contre la babésiose canine – Nobivac Piro® (NP et Pirodog® (P – a été étudiée. Leur impact local, général et biochimique a été comparé, en conditions expérimentales maîtrisées, sur un groupe témoin (T et deux groupes vaccinés deux fois à 21 jours d’intervalle. Tous les chiens ont présenté une réaction locale modérée. Cependant, le groupe NP a présenté une réaction locale significativement plus intense que le groupe P. Ceci est objectivé par les paramètres cliniques et biologiques. Aucune différence statistiquement significative n’est mise en évidence entre les évolutions des groupes P et T.
Directory of Open Access Journals (Sweden)
Katia Boissevain
2006-11-01
Full Text Available Cet article examine les pratiques rituelles contemporaines d’hommes et de femmes qui se rendent à deux sanctuaires tunisois dédiés à Sayyida Mannûbiyya, sainte du xiiie siècle. Cette sainte ambivalente s’inscrit dans deux registres de légitimité religieuse, le soufisme lettré, à travers son affiliation à la confrérie Shâdhiliyya, et une dimension plus locale. L’une et l’autre de ces voies donnent lieu à deux types de cérémonies religieuses, la ḥaḍra des femmes avec ses danses de possession et les séances de dhikr des hommes, disciples shâdhilî-s. Pourtant, on ne peut séparer un rapport au sacré féminin qui serait particulièrement corporel d’un rapport au sacré masculin plus intellectuel. La ḥaḍra comme le dhikr engagent pleinement le corps des participants dans un dialogue avec le sacré tout en puisant leur légitimité dans des sources distinctes, la confrérie Shâdhîliyya pour le dhikr et la dimension miraculeuse de Khiḍr pour la ḥaḍra
Directory of Open Access Journals (Sweden)
Birginie, J. M.
2000-09-01
Full Text Available Not available
Se presentan los resultados de un estudio comparativo de la resistencia a la alteración en atmósfera de niebla salina de dos rocas calizas utilizadas en la construcción de monumentos en Francia y en España. Las modificaciones experimentadas por las probetas durante este ensayo se han valorado utilizando tres métodos: la medida de la evolución del peso, la medida de la velocidad de propagación de ultrasonidos y el análisis visual de las modificaciones superficiales por un sistema de barrido mediante luz láser de las superficies (método de triangulación luz láser-cámara y posterior tratamiento de imágenes. La comparación de los resultados obtenidos muestra que los tres métodos ofrecen una información complementaria que permite caracterizar de manera precisa el proceso de alteración y su evolución durante el ensayo. Es, sin embargo, el método de análisis mediante el sistema láser-cámara el que ofrece más posibilidades para describir y comparar de manera objetiva la morfología y la evolución de la desagregación arenosa observada sobre las dos rocas calizas alteradas artificialmente.
[fr] Nous présentons les résultats d'une étude comparative de la résistance à l'altération au brouillard salin de deux pierres utilisées dans la construction de monuments en France et en Espagne. Les transformations subies par les échantillons au cours de l'essai de vieillissement ont été évaluées eu utilisant trois méthodes: l'évolution de la masse, la mesure de la vitesse de propagation d'ultrasons et l'analyse visuelle automatisée des désagrégations superficielles au moyen d'un système de balayage par plan laser de la surface (triangulation laser-caméra. La comparaison de l'ensemble de ces résultats démontre que les trois méthodes non destructives fournissent des informations complémentaires qui permettent de caractériser les processus d'altération et leur évolution. C'est néanmoins l
Halu, Arda; Bianconi, Ginestra
2013-01-01
Spatial networks range from the brain networks, to transportation networks and infrastructures. Recently interacting and multiplex networks are attracting great attention because their dynamics and robustness cannot be understood without treating at the same time several networks. Here we present maximal entropy ensembles of spatial multiplex and spatial interacting networks that can be used in order to model spatial multilayer network structures and to build null models of real datasets. We show that spatial multiplex naturally develop a significant overlap of the links, a noticeable property of many multiplexes that can affect significantly the dynamics taking place on them. Additionally, we characterize ensembles of spatial interacting networks and we analyse the structure of interacting airport and railway networks in India, showing the effect of space in determining the link probability.
An educational model for ensemble streamflow simulation and uncertainty analysis
Directory of Open Access Journals (Sweden)
A. AghaKouchak
2013-02-01
Full Text Available This paper presents the hands-on modeling toolbox, HBV-Ensemble, designed as a complement to theoretical hydrology lectures, to teach hydrological processes and their uncertainties. The HBV-Ensemble can be used for in-class lab practices and homework assignments, and assessment of students' understanding of hydrological processes. Using this modeling toolbox, students can gain more insights into how hydrological processes (e.g., precipitation, snowmelt and snow accumulation, soil moisture, evapotranspiration and runoff generation are interconnected. The educational toolbox includes a MATLAB Graphical User Interface (GUI and an ensemble simulation scheme that can be used for teaching uncertainty analysis, parameter estimation, ensemble simulation and model sensitivity. HBV-Ensemble was administered in a class for both in-class instruction and a final project, and students submitted their feedback about the toolbox. The results indicate that this educational software had a positive impact on students understanding and knowledge of uncertainty in hydrological modeling.
Ensemble-based Probabilistic Forecasting at Horns Rev
DEFF Research Database (Denmark)
Pinson, Pierre; Madsen, Henrik
2009-01-01
of probabilistic forecasts, the resolution of which may be maximized by using meteorological ensemble predictions as input. The paper concentrates on the test case of the Horns Rev wind form over a period of approximately 1 year, in order to describe, apply and discuss a complete ensemble-based probabilistic...... forecasting methodology. In a first stage, ensemble forecasts of meteorological variables are converted to power through a suitable power curve model. This modelemploys local polynomial regression, and is adoptively estimated with an orthogonal fitting method. The obtained ensemble forecasts of wind power...... the benefit of yielding predictive distributions that are of increased reliability (in a probabilistic sense) in comparison with the raw ensemble forecasts, at the some time taking advantage of their high resolution. Copyright (C) 2008 John Wiley & Sons, Ltd....
Induced Ginibre ensemble of random matrices and quantum operations
Fischmann, J; Khoruzhenko, B A; Sommers, H -J; Zyczkowski, K
2011-01-01
A generalisation of the Ginibre ensemble of non-Hermitian random square matrices is introduced. The corresponding probability measure is induced by the ensemble of rectangular Gaussian matrices via a quadratisation procedure. We derive the joint probability density of eigenvalues for such induced Ginibre ensemble and study various spectral correlation functions for complex and real matrices, and analyse universal behaviour in the limit of large dimensions. In this limit the eigenvalues of the induced Ginibre ensemble cover uniformly a ring in the complex plane. The real induced Ginibre ensemble is shown to be useful to describe statistical properties of evolution operators associated with random quantum operations, for which the dimensions of the input state and the output state do differ.
Excitations and benchmark ensemble density functional theory for two electrons
Pribram-Jones, Aurora; Trail, John R; Burke, Kieron; Needs, Richard J; Ullrich, Carsten A
2014-01-01
A new method for extracting ensemble Kohn-Sham potentials from accurate excited state densities is applied to a variety of two electron systems, exploring the behavior of exact ensemble density functional theory. The issue of separating the Hartree energy and the choice of degenerate eigenstates is explored. A new approximation, spin eigenstate Hartree-exchange (SEHX), is derived. Exact conditions that are proven include the signs of the correlation energy components, the virial theorem for both exchange and correlation, and the asymptotic behavior of the potential for small weights of the excited states. Many energy components are given as a function of the weights for two electrons in a one-dimensional flat box, in a box with a large barrier to create charge transfer excitations, in a three-dimensional harmonic well (Hooke's atom), and for the He atom singlet-triplet ensemble, singlet-triplet-singlet ensemble, and triplet bi-ensemble.
Ensemble Bayesian forecasting system Part I: Theory and algorithms
Herr, Henry D.; Krzysztofowicz, Roman
2015-05-01
The ensemble Bayesian forecasting system (EBFS), whose theory was published in 2001, is developed for the purpose of quantifying the total uncertainty about a discrete-time, continuous-state, non-stationary stochastic process such as a time series of stages, discharges, or volumes at a river gauge. The EBFS is built of three components: an input ensemble forecaster (IEF), which simulates the uncertainty associated with random inputs; a deterministic hydrologic model (of any complexity), which simulates physical processes within a river basin; and a hydrologic uncertainty processor (HUP), which simulates the hydrologic uncertainty (an aggregate of all uncertainties except input). It works as a Monte Carlo simulator: an ensemble of time series of inputs (e.g., precipitation amounts) generated by the IEF is transformed deterministically through a hydrologic model into an ensemble of time series of outputs, which is next transformed stochastically by the HUP into an ensemble of time series of predictands (e.g., river stages). Previous research indicated that in order to attain an acceptable sampling error, the ensemble size must be on the order of hundreds (for probabilistic river stage forecasts and probabilistic flood forecasts) or even thousands (for probabilistic stage transition forecasts). The computing time needed to run the hydrologic model this many times renders the straightforward simulations operationally infeasible. This motivates the development of the ensemble Bayesian forecasting system with randomization (EBFSR), which takes full advantage of the analytic meta-Gaussian HUP and generates multiple ensemble members after each run of the hydrologic model; this auxiliary randomization reduces the required size of the meteorological input ensemble and makes it operationally feasible to generate a Bayesian ensemble forecast of large size. Such a forecast quantifies the total uncertainty, is well calibrated against the prior (climatic) distribution of
Bhatt, Divesh
2009-01-01
We perform first path sampling simulations of conformational transitions of semi--atomistic protein models. We generate an ensemble of pathways for conformational transitions between open and closed forms of adenylate kinase using weighted ensemble path sampling method. Such an ensemble of pathways is critical in determining the important regions of configuration space sampled during a transition. To different semi--atomistic models are used: one is a pure Go model, whereas the other includes level of residue specificity via use of Miyajawa--Jernigan type interactions and hydrogen bonding. For both the models, we find that the open form of adenylate kinase is more flexible and the the transition from open to close is significantly faster than the reverse transition. We find that the transition occurs via the AMP binding domain snapping shut at a fairly fast time scale. On the other hand, the flexible lid domain fluctuates significantly and the shutting of the AMP binding domain does not depend upon the positi...
Robust Ensemble Filtering and Its Relation to Covariance Inflation in the Ensemble Kalman Filter
Luo, Xiaodong
2011-12-01
A robust ensemble filtering scheme based on the H∞ filtering theory is proposed. The optimal H∞ filter is derived by minimizing the supremum (or maximum) of a predefined cost function, a criterion different from the minimum variance used in the Kalman filter. By design, the H∞ filter is more robust than the Kalman filter, in the sense that the estimation error in the H∞ filter in general has a finite growth rate with respect to the uncertainties in assimilation, except for a special case that corresponds to the Kalman filter. The original form of the H∞ filter contains global constraints in time, which may be inconvenient for sequential data assimilation problems. Therefore a variant is introduced that solves some time-local constraints instead, and hence it is called the time-local H∞ filter (TLHF). By analogy to the ensemble Kalman filter (EnKF), the concept of ensemble time-local H∞ filter (EnTLHF) is also proposed. The general form of the EnTLHF is outlined, and some of its special cases are discussed. In particular, it is shown that an EnKF with certain covariance inflation is essentially an EnTLHF. In this sense, the EnTLHF provides a general framework for conducting covariance inflation in the EnKF-based methods. Some numerical examples are used to assess the relative robustness of the TLHF–EnTLHF in comparison with the corresponding KF–EnKF method.
Soil texture reclassification by an ensemble model
Cisty, Milan; Hlavcova, Kamila
2015-04-01
a prerequisite for solving some subsequent task, this bias is propagated to the subsequent modelling or other work. Therefore, for the sake of achieving more general and precise outputs while solving such tasks, the authors of the present paper are proposing a hybrid approach, which has the potential for obtaining improved results. Although the authors continue recommending the use of the mentioned parametric PSD models in the proposed methodology, the final prediction is made by an ensemble machine learning algorithm based on regression trees, the so-called Random Forest algorithm, which is built on top of the outputs of such models, which serves as an ensemble members. An improvement in precision was proved, and it is documented in the paper that the ensemble model worked better than any of its constituents. References Nemes, A., Wosten, J.H.M., Lilly, A., Voshaar, J.H.O.: Evaluation of different procedures to interpolate particle-size distributions to achieve compatibility within soil databases. Geoderma 90, 187- 202 (1999) Hwang, S.: Effect of texture on the performance of soil particle-size distribution models. Geoderma 123, 363-371 (2004) Botula, Y.D., Cornelis, W.M., Baert, G., Mafuka, P., Van Ranst, E.: Particle size distribution models for soils of the humid tropics. J Soils Sediments. 13, 686-698 (2013)
Belden, Jesse; Jandron, Michael; Truscott, Tadd
2012-11-01
A Waboba® (WAter BOuncing BAll) demonstrates remarkable water skipping behavior, even at relatively large impact angles. The highly compliant nature of these elastic spheres results in significant deformation into a disk-like shape upon impact. The increased wetted area and force coefficient generates a large hydrodynamic force that more readily lifts the ball off the water surface. However, elasticity introduces some surprising phenomena, such as material waves that propagate on the sphere and interact with the water cavity. Depending upon impact conditions, material waves may propagate in various directions combining to create multiple modes of deformation and complicated fluid-structure interactions. Furthermore, the timescales of deformation and wave propagation depend on the material properties and impact conditions. In this talk, we will discuss skipping regimes in terms of impact parameters and material properties and relate failed skipping behavior to the structure-fluid interaction caused by deformation. The critical timescales for deformation, wave propagation and collision will be related to the relevant physical parameters of the problem.
Huijsman, H.S.C.
1958-01-01
Mycena nucicola Huijsm. sp. nov. — Fig. 1 — Pusillima, tota alba, solitaria ad nuces dejectas Coryli avellanae; pileo usque ad 2 mm lato, conico-elevato vel hemisphaerico, pulverulento; lamellis subventricosis; stipite 12—22 X 0,15—2 mm, subfarinoso, disco basali minuto, pulverulento; sporis 7—9 X 4
Mol, Annemarie
2013-01-01
Le choix individuel est un idéal largement partagé. Le fait n’a rien d’étrange car qui aimerait être soumis aux autres ? Ce livre cherche pourtant à remettre en question cet idéal. Je ne questionne pas le choix en général mais plutôt sa généralisation. D’autres idéaux, comme « le bon soin », sont en effet mis à mal par cette généralisation. Dans le domaine des soins de santé, auquel ce livre est consacré, « le choix du patient » et « le bon soin » peuvent parfois se compléter, mais le plus so...
Ensemble-type numerical uncertainty information from single model integrations
Energy Technology Data Exchange (ETDEWEB)
Rauser, Florian, E-mail: florian.rauser@mpimet.mpg.de; Marotzke, Jochem; Korn, Peter
2015-07-01
We suggest an algorithm that quantifies the discretization error of time-dependent physical quantities of interest (goals) for numerical models of geophysical fluid dynamics. The goal discretization error is estimated using a sum of weighted local discretization errors. The key feature of our algorithm is that these local discretization errors are interpreted as realizations of a random process. The random process is determined by the model and the flow state. From a class of local error random processes we select a suitable specific random process by integrating the model over a short time interval at different resolutions. The weights of the influences of the local discretization errors on the goal are modeled as goal sensitivities, which are calculated via automatic differentiation. The integration of the weighted realizations of local error random processes yields a posterior ensemble of goal approximations from a single run of the numerical model. From the posterior ensemble we derive the uncertainty information of the goal discretization error. This algorithm bypasses the requirement of detailed knowledge about the models discretization to generate numerical error estimates. The algorithm is evaluated for the spherical shallow-water equations. For two standard test cases we successfully estimate the error of regional potential energy, track its evolution, and compare it to standard ensemble techniques. The posterior ensemble shares linear-error-growth properties with ensembles of multiple model integrations when comparably perturbed. The posterior ensemble numerical error estimates are of comparable size as those of a stochastic physics ensemble.
Diagnostic studies of ensemble forecast "jumps"
Magnusson, Linus; Hewson, Tim; Ferranti, Laura; Rodwell, Mark
2016-04-01
During 2015 we saw exceptional consistency in successive seasonal forecasts produced at ECMWF, for the winter period 2015/16, right across the globe. This winter was characterised by a well-predicted and unusually strong El Nino, and some have ascribed the consistency to that. For most of December this consistency was mirrored in the (separate) ECMWF monthly forecast system, which correctly predicted anomalously strong (mild) zonal flow, over the North Atlantic and western Eurasia, even in forecasts for weeks 3 and 4. In monthly forecasts in general these weeks are often devoid of strong signals. However in late December and early January strong signals, even in week 2, proved to be incorrect, most notably over the North Atlantic and Eurasian sectors. Indeed on at least two occasions the outcome was beyond the ensemble forecast range over Scandinavia. In one of these conditions flipped from extreme mild to extreme cold as a high latitude block developed. Temperature prediction is very important to many customers, notably those dealing with renewable energy, because cold weather causes increased demand but also tends to coincide with reduced wind power production. So understandably jumps can cause consternation amongst some customer groups, and are very difficult to handle operationally. This presentation will discuss the results of initial diagnostic investigations into what caused the "ensemble jumps", particularly at the week two lead, though reference will also be made to a related shorter range (day 3) jump that was important for flooding over the UK. Initial results suggest that an inability of the ECMWF model to correctly represent convective outbreaks over North America (that for winter-time were quite extreme) played an important role. Significantly, during this period, an unusually large amount of upper air data over North America was rejected or ascribed low weight. These results bear similarities to previous diagnostic studies at ECMWF, wherein major
Construction of High-accuracy Ensemble of Classifiers
Directory of Open Access Journals (Sweden)
Hedieh Sajedi
2014-04-01
Full Text Available There have been several methods developed to construct ensembles. Some of these methods, such as Bagging and Boosting are meta-learners, i.e. they can be applied to any base classifier. The combination of methods should be selected in order that classifiers cover each other weaknesses. In ensemble, the output of several classifiers is used only when they disagree on some inputs. The degree of disagreement is called diversity of the ensemble. Another factor that plays a significant role in performing an ensemble is accuracy of the basic classifiers. It can be said that all the procedures of constructing ensembles seek to achieve a balance between these two parameters, and successful methods can reach a better balance. The diversity of the members of an ensemble is known as an important factor in determining its generalization error. In this paper, we present a new approach for generating ensembles. The proposed approach uses Bagging and Boosting as the generators of base classifiers. Subsequently, the classifiers are partitioned by means of a clustering algorithm. We introduce a selection phase for construction the final ensemble and three different selection methods are proposed for applying in this phase. In the first proposed selection method, a classifier is selected randomly from each cluster. The second method selects the most accurate classifier from each cluster and the third one selects the nearest classifier to the center of each cluster to construct the final ensemble. The results of the experiments on well-known datasets demonstrate the strength of our proposed approach, especially applying the selection of the most accurate classifiers from clusters and employing Bagging generator.
Ensemble Deep Learning for Biomedical Time Series Classification
Directory of Open Access Journals (Sweden)
Lin-peng Jin
2016-01-01
Full Text Available Ensemble learning has been proved to improve the generalization ability effectively in both theory and practice. In this paper, we briefly outline the current status of research on it first. Then, a new deep neural network-based ensemble method that integrates filtering views, local views, distorted views, explicit training, implicit training, subview prediction, and Simple Average is proposed for biomedical time series classification. Finally, we validate its effectiveness on the Chinese Cardiovascular Disease Database containing a large number of electrocardiogram recordings. The experimental results show that the proposed method has certain advantages compared to some well-known ensemble methods, such as Bagging and AdaBoost.
An Improved Particle Swarm Optimization Algorithm Based on Ensemble Technique
Institute of Scientific and Technical Information of China (English)
SHI Yan; HUANG Cong-ming
2006-01-01
An improved particle swarm optimization (PSO) algorithm based on ensemble technique is presented. The algorithm combines some previous best positions (pbest) of the particles to get an ensemble position (Epbest), which is used to replace the global best position (gbest). It is compared with the standard PSO algorithm invented by Kennedy and Eberhart and some improved PSO algorithms based on three different benchmark functions. The simulation results show that the improved PSO based on ensemble technique can get better solutions than the standard PSO and some other improved algorithms under all test cases.
Filtering single atoms from Rydberg blockaded mesoscopic ensembles
Petrosyan, David; Mølmer, Klaus
2015-01-01
We propose an efficient method to filter out single atoms from trapped ensembles with unknown number of atoms. The method employs stimulated adiabatic passage to reversibly transfer a single atom to the Rydberg state which blocks subsequent Rydberg excitation of all the other atoms within the ensemble. This triggers the excitation of Rydberg blockaded atoms to short lived intermediate states and their subsequent decay to untrapped states. Using an auxiliary microwave field to carefully engineer the dissipation, we obtain a nearly deterministic single-atom source. Our method is applicable to small atomic ensembles in individual microtraps and in lattice arrays.
Deterministic entanglement of Rydberg ensembles by engineered dissipation
DEFF Research Database (Denmark)
Dasari, Durga; Mølmer, Klaus
2014-01-01
We propose a scheme that employs dissipation to deterministically generate entanglement in an ensemble of strongly interacting Rydberg atoms. With a combination of microwave driving between different Rydberg levels and a resonant laser coupling to a short lived atomic state, the ensemble can...... be driven towards a dark steady state that entangles all atoms. The long-range resonant dipole-dipole interaction between different Rydberg states extends the entanglement beyond the van der Walls interaction range with perspectives for entangling large and distant ensembles....
Ensemble Deep Learning for Biomedical Time Series Classification
2016-01-01
Ensemble learning has been proved to improve the generalization ability effectively in both theory and practice. In this paper, we briefly outline the current status of research on it first. Then, a new deep neural network-based ensemble method that integrates filtering views, local views, distorted views, explicit training, implicit training, subview prediction, and Simple Average is proposed for biomedical time series classification. Finally, we validate its effectiveness on the Chinese Cardiovascular Disease Database containing a large number of electrocardiogram recordings. The experimental results show that the proposed method has certain advantages compared to some well-known ensemble methods, such as Bagging and AdaBoost.
Ensemble estimators for multivariate entropy estimation
Sricharan, Kumar
2012-01-01
The problem of estimation of density functionals like entropy and mutual information has received much attention in the statistics and information theory communities. A large class of estimators of functionals of the probability density suffer from the curse of dimensionality, wherein the exponent in the MSE rate of convergence decays increasingly slowly as the dimension $d$ of the samples increases. In particular, the rate is often glacially slow of order $O(T^{-{\\gamma}/{d}})$, where $T$ is the number of samples, and $\\gamma>0$ is a rate parameter. Examples of such estimators include kernel density estimators, $k$-NN density estimators, $k$-NN entropy estimators, intrinsic dimension estimators and other examples. In this paper, we propose a weighted convex combination of an ensemble of such estimators, where optimal weights can be chosen such that the weighted estimator converges at a much faster dimension invariant rate of $O(T^{-1})$. Furthermore, we show that these optimal weights can be determined by so...
Asymptotic expansions for the Gaussian unitary ensemble
DEFF Research Database (Denmark)
Haagerup, Uffe; Thorbjørnsen, Steen
2012-01-01
Let g : R ¿ C be a C8-function with all derivatives bounded and let trn denote the normalized trace on the n × n matrices. In Ref. 3 Ercolani and McLaughlin established asymptotic expansions of the mean value ¿{trn(g(Xn))} for a rather general class of random matrices Xn, including the Gaussian...... Unitary Ensemble (GUE). Using an analytical approach, we provide in the present paper an alternative proof of this asymptotic expansion in the GUE case. Specifically we derive for a random matrix Xn that where k is an arbitrary positive integer. Considered as mappings of g, we determine the coefficients...... aj(g), j ¿ N, as distributions (in the sense of L. Schwarts). We derive a similar asymptotic expansion for the covariance Cov{Trn[f(Xn)], Trn[g(Xn)]}, where f is a function of the same kind as g, and Trn = n trn. Special focus is drawn to the case where and for ¿, µ in C\\R. In this case the mean and...
Variety of synchronous regimes in neuronal ensembles
Komarov, M. A.; Osipov, G. V.; Suykens, J. A. K.
2008-09-01
We consider a Hodgkin-Huxley-type model of oscillatory activity in neurons of the snail Helix pomatia. This model has a distinctive feature: It demonstrates multistability in oscillatory and silent modes that is typical for the thalamocortical neurons. A single neuron cell can demonstrate a variety of oscillatory activity: Regular and chaotic spiking and bursting behavior. We study collective phenomena in small and large arrays of nonidentical cells coupled by models of electrical and chemical synapses. Two single elements coupled by electrical coupling show different types of synchronous behavior, in particular in-phase and antiphase synchronous regimes. In an ensemble of three inhibitory synaptically coupled elements, the phenomenon of sequential synchronous dynamics is observed. We study the synchronization phenomena in the chain of nonidentical neurons at different oscillatory behavior coupled with electrical and chemical synapses. Various regimes of phase synchronization are observed: (i) Synchronous regular and chaotic spiking; (ii) synchronous regular and chaotic bursting; and (iii) synchronous regular and chaotic bursting with different numbers of spikes inside the bursts. We detect and study the effect of collective synchronous burst generation due to the cluster formation and the oscillatory death.
Model error estimation in ensemble data assimilation
Directory of Open Access Journals (Sweden)
S. Gillijns
2007-01-01
Full Text Available A new methodology is proposed to estimate and account for systematic model error in linear filtering as well as in nonlinear ensemble based filtering. Our results extend the work of Dee and Todling (2000 on constant bias errors to time-varying model errors. In contrast to existing methodologies, the new filter can also deal with the case where no dynamical model for the systematic error is available. In the latter case, the applicability is limited by a matrix rank condition which has to be satisfied in order for the filter to exist. The performance of the filter developed in this paper is limited by the availability and the accuracy of observations and by the variance of the stochastic model error component. The effect of these aspects on the estimation accuracy is investigated in several numerical experiments using the Lorenz (1996 model. Experimental results indicate that the availability of a dynamical model for the systematic error significantly reduces the variance of the model error estimates, but has only minor effect on the estimates of the system state. The filter is able to estimate additive model error of any type, provided that the rank condition is satisfied and that the stochastic errors and measurement errors are significantly smaller than the systematic errors. The results of this study are encouraging. However, it remains to be seen how the filter performs in more realistic applications.
Protective clothing ensembles and physical employment standards.
McLellan, Tom M; Havenith, George
2016-06-01
Physical employment standards (PESs) exist for certain occupational groups that also require the use of protective clothing ensembles (PCEs) during their normal work. This review addresses whether these current PESs appropriately incorporate the physiological burden associated with wearing PCEs during respective tasks. Metabolic heat production increases because of wearing PCE; this increase is greater than that because of simply the weight of the clothing and can vary 2-fold among individuals. This variation negates a simple adjustment to the PES for the effect of the clothing on metabolic rate. As a result, PES testing that only simulates the weight of the clothing and protective equipment does not adequately accommodate this effect. The physiological heat strain associated with the use of PCEs is also not addressed with current PESs. Typically the selection tests of a PES lasts less than 20 min, whereas the requirement for use of PCE in the workplace may approach 1 h before cooling strategies can be employed. One option that might be considered is to construct a heat stress test that requires new recruits and incumbents to work for a predetermined duration while exposed to a warm environmental temperature while wearing the PCE. PMID:27277562
Emergent order in ensembles of active spinners
van Zuiden, Benjamin C.; Paulose, Jayson; Irvine, William T. M.; Bartolo, Denis; Vitelli, Vincenzo
Interacting self-propelled particles is proxy to model many living systems from cytoskeletal motors to bird flocks, while also providing a framework to investigate fundamental questions in non equilibrium statistical mechanics. A surge of recent studies have shown that self-propulsion significantly modifies the phase behavior of particles interacting via potential interactions. A prototypical example is the so-called Motility Induced Phase Separation occurring in ensembles of self-propelled hard spheres. In stark contrast, our understanding of active spinning, as opposed to self-propulsion, remains very scarce. Here, we study a system of self-spinning dimers, interacting via soft repulsive forces. Upon varying the density and activity, we observe a range of emergent phases characterized by different degrees of spatiotemporal order in the position and orientation of the dimers. Changes in bulk properties, including crystallization, melting, and freezing, are reflected in the collective motion of the particles. We rationalize our numerical findings theoretically and demonstrate some of these concepts in a active granular experiment.
Cluster ensembles, quantization and the dilogarithm
DEFF Research Database (Denmark)
Fock, Vladimir; Goncharov, Alexander B.
2009-01-01
A cluster ensemble is a pair of positive spaces (i.e. varieties equipped with positive atlases), coming with an action of a symmetry group . The space is closely related to the spectrum of a cluster algebra [ 12 ]. The two spaces are related by a morphism . The space is equipped with a closed -form...... the algebra of functions on the -deformed -space has a large center, which includes the algebra of functions on the original -space. The main example is provided by the pair of moduli spaces assigned in [ 7 ] to a topological surface with a finite set of points at the boundary and a split semisimple algebraic...... group . It is an algebraic-geometric avatar of higher Teichmüller theory on related to . We suggest that there exists a duality between the and spaces. In particular, we conjecture that the tropical points of one of the spaces parametrise a basis in the space of functions on the Langlands dual space. We...
Orchestrating Distributed Resource Ensembles for Petascale Science
Energy Technology Data Exchange (ETDEWEB)
Baldin, Ilya; Mandal, Anirban; Ruth, Paul; Yufeng, Xin
2014-04-24
Distributed, data-intensive computational science applications of interest to DOE scientific com- munities move large amounts of data for experiment data management, distributed analysis steps, remote visualization, and accessing scientific instruments. These applications need to orchestrate ensembles of resources from multiple resource pools and interconnect them with high-capacity multi- layered networks across multiple domains. It is highly desirable that mechanisms are designed that provide this type of resource provisioning capability to a broad class of applications. It is also important to have coherent monitoring capabilities for such complex distributed environments. In this project, we addressed these problems by designing an abstract API, enabled by novel semantic resource descriptions, for provisioning complex and heterogeneous resources from multiple providers using their native provisioning mechanisms and control planes: computational, storage, and multi-layered high-speed network domains. We used an extensible resource representation based on semantic web technologies to afford maximum flexibility to applications in specifying their needs. We evaluated the effectiveness of provisioning using representative data-intensive ap- plications. We also developed mechanisms for providing feedback about resource performance to the application, to enable closed-loop feedback control and dynamic adjustments to resource allo- cations (elasticity). This was enabled through development of a novel persistent query framework that consumes disparate sources of monitoring data, including perfSONAR, and provides scalable distribution of asynchronous notifications.
General approaches in ensemble quantum computing
Indian Academy of Sciences (India)
V Vimalan; N Chandrakumar
2008-01-01
We have developed methodology for NMR quantum computing focusing on enhancing the efficiency of initialization, of logic gate implementation and of readout. Our general strategy involves the application of rotating frame pulse sequences to prepare pseudopure states and to perform logic operations. We demonstrate experimentally our methodology for both homonuclear and heteronuclear spin ensembles. On model two-spin systems, the initialization time of one of our sequences is three-fourths (in the heteronuclear case) or one-fourth (in the homonuclear case), of the typical pulsed free precession sequences, attaining the same initialization efficiency. We have implemented the logical SWAP operation in homonuclear AMX spin systems using selective isotropic mixing, reducing the duration taken to a third compared to the standard re-focused INEPT-type sequence. We introduce the 1D version for readout of the rotating frame SWAP operation, in an attempt to reduce readout time. We further demonstrate the Hadamard mode of 1D SWAP, which offers 2N-fold reduction in experiment time for a system with -working bits, attaining the same sensitivity as the standard 1D version.
Directory of Open Access Journals (Sweden)
G. Thirel
2010-08-01
Full Text Available The use of ensemble streamflow forecasts is developing in the international flood forecasting services. Ensemble streamflow forecast systems can provide more accurate forecasts and useful information about the uncertainty of the forecasts, thus improving the assessment of risks. Nevertheless, these systems, like all hydrological forecasts, suffer from errors on initialization or on meteorological data, which lead to hydrological prediction errors. This article, which is the second part of a 2-part article, concerns the impacts of initial states, improved by a streamflow assimilation system, on an ensemble streamflow prediction system over France. An assimilation system was implemented to improve the streamflow analysis of the SAFRAN-ISBA-MODCOU (SIM hydro-meteorological suite, which initializes the ensemble streamflow forecasts at Météo-France. This assimilation system, using the Best Linear Unbiased Estimator (BLUE and modifying the initial soil moisture states, showed an improvement of the streamflow analysis with low soil moisture increments. The final states of this suite were used to initialize the ensemble streamflow forecasts of Météo-France, which are based on the SIM model and use the European Centre for Medium-range Weather Forecasts (ECMWF 10-day Ensemble Prediction System (EPS. Two different configurations of the assimilation system were used in this study: the first with the classical SIM model and the second using improved soil physics in ISBA. The effects of the assimilation system on the ensemble streamflow forecasts were assessed for these two configurations, and a comparison was made with the original (i.e. without data assimilation and without the improved physics ensemble streamflow forecasts. It is shown that the assimilation system improved most of the statistical scores usually computed for the validation of ensemble predictions (RMSE, Brier Skill Score and its decomposition, Ranked Probability Skill Score, False Alarm
Spectroscopic properties of inhomogeneously broadened spin ensembles in a cavity
DEFF Research Database (Denmark)
Kurucz, Zoltan; Wesenberg, Janus; Mølmer, Klaus
2011-01-01
The enhanced collective coupling to weak quantum fields may turn atomic or spin ensembles into an important component in quantum information processing architectures. Inhomogeneous broadening can, however, significantly reduce the coupling and the lifetime of the collective excitation...
Phase-selective entrainment of nonlinear oscillator ensembles
Zlotnik, Anatoly; Nagao, Raphael; Kiss, István Z.; Li-Shin, Jr.
2016-03-01
The ability to organize and finely manipulate the hierarchy and timing of dynamic processes is important for understanding and influencing brain functions, sleep and metabolic cycles, and many other natural phenomena. However, establishing spatiotemporal structures in biological oscillator ensembles is a challenging task that requires controlling large collections of complex nonlinear dynamical units. In this report, we present a method to design entrainment signals that create stable phase patterns in ensembles of heterogeneous nonlinear oscillators without using state feedback information. We demonstrate the approach using experiments with electrochemical reactions on multielectrode arrays, in which we selectively assign ensemble subgroups into spatiotemporal patterns with multiple phase clusters. The experimentally confirmed mechanism elucidates the connection between the phases and natural frequencies of a collection of dynamical elements, the spatial and temporal information that is encoded within this ensemble, and how external signals can be used to retrieve this information.
Prediction of Weather Impacted Airport Capacity using Ensemble Learning
Wang, Yao Xun
2011-01-01
Ensemble learning with the Bagging Decision Tree (BDT) model was used to assess the impact of weather on airport capacities at selected high-demand airports in the United States. The ensemble bagging decision tree models were developed and validated using the Federal Aviation Administration (FAA) Aviation System Performance Metrics (ASPM) data and weather forecast at these airports. The study examines the performance of BDT, along with traditional single Support Vector Machines (SVM), for airport runway configuration selection and airport arrival rates (AAR) prediction during weather impacts. Testing of these models was accomplished using observed weather, weather forecast, and airport operation information at the chosen airports. The experimental results show that ensemble methods are more accurate than a single SVM classifier. The airport capacity ensemble method presented here can be used as a decision support model that supports air traffic flow management to meet the weather impacted airport capacity in order to reduce costs and increase safety.
Time and ensemble averaging in time series analysis
Latka, Miroslaw; Jernajczyk, Wojciech; West, Bruce J
2010-01-01
In many applications expectation values are calculated by partitioning a single experimental time series into an ensemble of data segments of equal length. Such single trajectory ensemble (STE) is a counterpart to a multiple trajectory ensemble (MTE) used whenever independent measurements or realizations of a stochastic process are available. The equivalence of STE and MTE for stationary systems was postulated by Wang and Uhlenbeck in their classic paper on Brownian motion (Rev. Mod. Phys. 17, 323 (1945)) but surprisingly has not yet been proved. Using the stationary and ergodic paradigm of statistical physics -- the Ornstein-Uhlenbeck (OU) Langevin equation, we revisit Wang and Uhlenbeck's postulate. In particular, we find that the variance of the solution of this equation is different for these two ensembles. While the variance calculated using the MTE quantifies the spreading of independent trajectories originating from the same initial point, the variance for STE measures the spreading of two correlated r...
An educational model for ensemble streamflow simulation and uncertainty analysis
Directory of Open Access Journals (Sweden)
A. AghaKouchak
2012-06-01
Full Text Available This paper presents a hands-on modeling toolbox, HBV-Ensemble, designed as a complement to theoretical hydrology lectures, to teach hydrological processes and their uncertainties. The HBV-Ensemble can be used for in-class lab practices and homework assignments, and assessment of students' understanding of hydrological processes. Using this model, students can gain more insights into how hydrological processes (e.g., precipitation, snowmelt and snow accumulation, soil moisture, evapotranspiration and runoff generation are interconnected. The model includes a MATLAB Graphical User Interface (GUI and an ensemble simulation scheme that can be used for not only hydrological processes, but also for teaching uncertainty analysis, parameter estimation, ensemble simulation and model sensitivity.
Ensembles on configuration space classical, quantum, and beyond
Hall, Michael J W
2016-01-01
This book describes a promising approach to problems in the foundations of quantum mechanics, including the measurement problem. The dynamics of ensembles on configuration space is shown here to be a valuable tool for unifying the formalisms of classical and quantum mechanics, for deriving and extending the latter in various ways, and for addressing the quantum measurement problem. A description of physical systems by means of ensembles on configuration space can be introduced at a very fundamental level: the basic building blocks are a configuration space, probabilities, and Hamiltonian equations of motion for the probabilities. The formalism can describe both classical and quantum systems, and their thermodynamics, with the main difference being the choice of ensemble Hamiltonian. Furthermore, there is a natural way of introducing ensemble Hamiltonians that describe the evolution of hybrid systems; i.e., interacting systems that have distinct classical and quantum sectors, allowing for consistent descriptio...
Ensemble vs. time averages in financial time series analysis
Seemann, Lars; Hua, Jia-Chen; McCauley, Joseph L.; Gunaratne, Gemunu H.
2012-12-01
Empirical analysis of financial time series suggests that the underlying stochastic dynamics are not only non-stationary, but also exhibit non-stationary increments. However, financial time series are commonly analyzed using the sliding interval technique that assumes stationary increments. We propose an alternative approach that is based on an ensemble over trading days. To determine the effects of time averaging techniques on analysis outcomes, we create an intraday activity model that exhibits periodic variable diffusion dynamics and we assess the model data using both ensemble and time averaging techniques. We find that ensemble averaging techniques detect the underlying dynamics correctly, whereas sliding intervals approaches fail. As many traded assets exhibit characteristic intraday volatility patterns, our work implies that ensemble averages approaches will yield new insight into the study of financial markets’ dynamics.
HIGH-RESOLUTION ATMOSPHERIC ENSEMBLE MODELING AT SRNL
Energy Technology Data Exchange (ETDEWEB)
Buckley, R.; Werth, D.; Chiswell, S.; Etherton, B.
2011-05-10
The High-Resolution Mid-Atlantic Forecasting Ensemble (HME) is a federated effort to improve operational forecasts related to precipitation, convection and boundary layer evolution, and fire weather utilizing data and computing resources from a diverse group of cooperating institutions in order to create a mesoscale ensemble from independent members. Collaborating organizations involved in the project include universities, National Weather Service offices, and national laboratories, including the Savannah River National Laboratory (SRNL). The ensemble system is produced from an overlapping numerical weather prediction model domain and parameter subsets provided by each contributing member. The coordination, synthesis, and dissemination of the ensemble information are performed by the Renaissance Computing Institute (RENCI) at the University of North Carolina-Chapel Hill. This paper discusses background related to the HME effort, SRNL participation, and example results available from the RENCI website.
Savannah River National Laboratory Involvement in the European ENSEMBLE Program
Energy Technology Data Exchange (ETDEWEB)
Buckley, R. L.; Addies, Robert P.
2005-10-24
Many atmospheric transport and dispersion models now exist to provide consequence assessment during emergency response to near-field releases. One way of estimating the uncertainty for a given forecast is to statistically analyze an ensemble of results from several models. ENSEMBLE is a European Union program that utilizes an internet-based system to ingest transport results from numerous modeling agencies. This paper addresses the involvement of the Savannah River National Laboratory (SRNL) in ENSEMBLE, and the resulting improvements in SRNL modeling capabilities. SRNL, the only United States agency involved in the ENSEMBLE program, uses a prognostic atmospheric numerical model (the Regional Atmospheric Modeling System, RAMS) to provide three-dimensional and time-varying meteorology as input to a stochastic Lagrangian particle mode . The model design used by SRNL is discussed, including recent upgrades to the system using parallel processing which allows for finer grid resolution in the generation of the meteorology.
Clustering Categorical Data:A Cluster Ensemble Approach
Institute of Scientific and Technical Information of China (English)
He Zengyou(何增友); Xu Xiaofei; Deng Shengchun
2003-01-01
Clustering categorical data, an integral part of data mining,has attracted much attention recently. In this paper, the authors formally define the categorical data clustering problem as an optimization problem from the viewpoint of cluster ensemble, and apply cluster ensemble approach for clustering categorical data. Experimental results on real datasets show that better clustering accuracy can be obtained by comparing with existing categorical data clustering algorithms.
Assessing creativity in computer music ensembles: a computational approach
Comajuncosas, Josep M.
2016-01-01
Over the last decade Laptop Orchestras and Mobile Ensembles have proliferated. As a result, a large body of research has arisen on infrastructure, evaluation, design principles and compositional methodologies for Computer Music Ensembles (CME). However, little has been addressed and very little is known about the challenges and opportunities provided by CMEs for creativity in musical performance. Therefore, one of the most common issues CMEs have to deal with is the lack of ...
Sensitivity tests for an ensemble Kalman filter for aerosol assimilation
N. A. J. Schutgens; T. Miyoshi; Takemura, T.; Nakajima, T
2010-01-01
We present sensitivity tests for a global aerosol assimilation system utilizing AERONET observations of AOT (aerosol optical thickness) and AAE (aerosol Ångström exponent). The assimilation system employs an ensemble Kalman filter which requires optimization of three numerical parameters: ensemble size n_{ens}, local patch size n_{patch} and inflation factor ρ. In addition, experiments are performed to test ...
On the distribution of eigenvalues of certain matrix ensembles
International Nuclear Information System (INIS)
Invariant random matrix ensembles with weak confinement potentials of the eigenvalues, corresponding to indeterminate moment problems, are investigated. These ensembles are characterized by the fact that the mean density of eigenvalues tends to a continuous function with increasing matrix dimension contrary to the usual cases where it grows indefinitely. It is demonstrated that the standard asymptotic formulae are not applicable in these cases and that the asymptotic distribution of eigenvalues can deviate from the classical ones. (author)
Monthly Ensembles in Algal Bloom Predictions on the Baltic Sea
Roiha, Petra; Westerlund, Antti; Stipa, Tapani
2010-05-01
In this work we explore the statistical features of monthly ensembles and their capability to predict biogeochemical conditions in the Baltic Sea. Operational marine environmental modelling has been considered hard, and consequently there are very few operational ecological models. Operational modelling of harmful algal blooms is harder still, since it is difficult to separate the algal species in models, and in general, very little is known of HAB properties. We present results of an ensemble approach to HAB forecasting in the Baltic, and discuss the applicability of the forecasting method to biochemical modelling. It turns out that HABs are indeed possible to forecast with useful accuracy. For modelling the algal blooms in Baltic Sea we used FMI operational 3-dimensional biogeochemical model to produce seasonal ensemble forecasts for different physical, chemical and biological variables. The modelled variables were temperature, salinity, velocity, silicate, phosphate, nitrate, diatoms, flagellates and two species of potentially toxic filamentous cyanobacteria nodularia spumigena and aphanizomenon flos-aquae. In this work we concentrate to the latter two. Ensembles were produced by running the biogeochemical model several times and forcing it on every run with different set of seasonal weather parameters from ECMWF's mathematically perturbed ensemble prediction forecasts. The ensembles were then analysed by statistical methods and the median, quartiles, minimum and maximum values were calculated for estimating the probable amounts of algae. Validation for the forecast method was made by comparing the final results against available and valid in-situ HAB data.
Ensembles of a small number of conformations with relative populations
Energy Technology Data Exchange (ETDEWEB)
Vammi, Vijay, E-mail: vsvammi@iastate.edu; Song, Guang, E-mail: gsong@iastate.edu [Iowa State University, Bioinformatics and Computational Biology Program, Department of Computer Science (United States)
2015-12-15
In our previous work, we proposed a new way to represent protein native states, using ensembles of a small number of conformations with relative Populations, or ESP in short. Using Ubiquitin as an example, we showed that using a small number of conformations could greatly reduce the potential of overfitting and assigning relative populations to protein ensembles could significantly improve their quality. To demonstrate that ESP indeed is an excellent alternative to represent protein native states, in this work we compare the quality of two ESP ensembles of Ubiquitin with several well-known regular ensembles or average structure representations. Extensive amount of significant experimental data are employed to achieve a thorough assessment. Our results demonstrate that ESP ensembles, though much smaller in size comparing to regular ensembles, perform equally or even better sometimes in all four different types of experimental data used in the assessment, namely, the residual dipolar couplings, residual chemical shift anisotropy, hydrogen exchange rates, and solution scattering profiles. This work further underlines the significance of having relative populations in describing the native states.
Evolutionary Ensemble for In Silico Prediction of Ames Test Mutagenicity
Chen, Huanhuan; Yao, Xin
Driven by new regulations and animal welfare, the need to develop in silico models has increased recently as alternative approaches to safety assessment of chemicals without animal testing. This paper describes a novel machine learning ensemble approach to building an in silico model for the prediction of the Ames test mutagenicity, one of a battery of the most commonly used experimental in vitro and in vivo genotoxicity tests for safety evaluation of chemicals. Evolutionary random neural ensemble with negative correlation learning (ERNE) [1] was developed based on neural networks and evolutionary algorithms. ERNE combines the method of bootstrap sampling on training data with the method of random subspace feature selection to ensure diversity in creating individuals within an initial ensemble. Furthermore, while evolving individuals within the ensemble, it makes use of the negative correlation learning, enabling individual NNs to be trained as accurate as possible while still manage to maintain them as diverse as possible. Therefore, the resulting individuals in the final ensemble are capable of cooperating collectively to achieve better generalization of prediction. The empirical experiment suggest that ERNE is an effective ensemble approach for predicting the Ames test mutagenicity of chemicals.
Knowledge based cluster ensemble for cancer discovery from biomolecular data.
Yu, Zhiwen; Wongb, Hau-San; You, Jane; Yang, Qinmin; Liao, Hongying
2011-06-01
The adoption of microarray techniques in biological and medical research provides a new way for cancer diagnosis and treatment. In order to perform successful diagnosis and treatment of cancer, discovering and classifying cancer types correctly is essential. Class discovery is one of the most important tasks in cancer classification using biomolecular data. Most of the existing works adopt single clustering algorithms to perform class discovery from biomolecular data. However, single clustering algorithms have limitations, which include a lack of robustness, stability, and accuracy. In this paper, we propose a new cluster ensemble approach called knowledge based cluster ensemble (KCE) which incorporates the prior knowledge of the data sets into the cluster ensemble framework. Specifically, KCE represents the prior knowledge of a data set in the form of pairwise constraints. Then, the spectral clustering algorithm (SC) is adopted to generate a set of clustering solutions. Next, KCE transforms pairwise constraints into confidence factors for these clustering solutions. After that, a consensus matrix is constructed by considering all the clustering solutions and their corresponding confidence factors. The final clustering result is obtained by partitioning the consensus matrix. Comparison with single clustering algorithms and conventional cluster ensemble approaches, knowledge based cluster ensemble approaches are more robust, stable and accurate. The experiments on cancer data sets show that: 1) KCE works well on these data sets; 2) KCE not only outperforms most of the state-of-the-art single clustering algorithms, but also outperforms most of the state-of-the-art cluster ensemble approaches.
Concrete ensemble Kalman filters with rigorous catastrophic filter divergence.
Kelly, David; Majda, Andrew J; Tong, Xin T
2015-08-25
The ensemble Kalman filter and ensemble square root filters are data assimilation methods used to combine high-dimensional, nonlinear dynamical models with observed data. Ensemble methods are indispensable tools in science and engineering and have enjoyed great success in geophysical sciences, because they allow for computationally cheap low-ensemble-state approximation for extremely high-dimensional turbulent forecast models. From a theoretical perspective, the dynamical properties of these methods are poorly understood. One of the central mysteries is the numerical phenomenon known as catastrophic filter divergence, whereby ensemble-state estimates explode to machine infinity, despite the true state remaining in a bounded region. In this article we provide a breakthrough insight into the phenomenon, by introducing a simple and natural forecast model that transparently exhibits catastrophic filter divergence under all ensemble methods and a large set of initializations. For this model, catastrophic filter divergence is not an artifact of numerical instability, but rather a true dynamical property of the filter. The divergence is not only validated numerically but also proven rigorously. The model cleanly illustrates mechanisms that give rise to catastrophic divergence and confirms intuitive accounts of the phenomena given in past literature.
Improving ensemble forecasting with q-norm bred vectors
Pazo, Diego; Lopez, Juan Manuel; Rodriguez, Miguel Angel
2016-04-01
Error breeding is a popular and simple method to generate initial perturbations for use in ensemble forecasting that is used for operational purposes in many weather/climate centres worldwide. There is a widespread belief among practitioners that the type of norm used in the periodic normalizations of BVs does not have an effect on the performance of ensemble forecasting systems. However, we have recently reported that BVs constructed with different norms have indeed very different dynamical and spatial properties. In particular, BVs constructed with the 0-norm or geometric norm has nice properties (e.g. enhancement of the ensemble diversity), which in principle render it more adequate to construct ensembles than other norm types like the Euclidean one. These advantages are clearly demonstrated here in a simple experiment of ensemble forecasting for the Lorenz-96 model with ensembles of BVs. Our simple numerical assimilation experiment shows how the increased statistical diversity of geometric BVs leads to improved scores regarding forecasting capabilities as compared with BVs constructed with the standard Euclidean norm.
Hybrid Intrusion Detection Using Ensemble of Classification Methods
Directory of Open Access Journals (Sweden)
M.Govindarajan
2014-01-01
Full Text Available One of the major developments in machine learning in the past decade is the ensemble method, which finds highly accurate classifier by combining many moderately accurate component classifiers. In this research work, new ensemble classification methods are proposed for homogeneous ensemble classifiers using bagging and heterogeneous ensemble classifiers using arcing classifier and their performances are analyzed in terms of accuracy. A Classifier ensemble is designed using Radial Basis Function (RBF and Support Vector Machine (SVM as base classifiers. The feasibility and the benefits of the proposed approaches are demonstrated by the means of real and benchmark data sets of intrusion detection. The main originality of the proposed approach is based on three main parts: preprocessing phase, classification phase and combining phase. A wide range of comparative experiments are conducted for real and benchmark data sets of intrusion detection. The accuracy of base classifiers is compared with homogeneous and heterogeneous models for data mining problem. The proposed ensemble methods provide significant improvement of accuracy compared to individual classifiers and also heterogeneous models exhibit better results than homogeneous models for real and benchmark data sets of intrusion detection.
Three-model ensemble wind prediction in southern Italy
Torcasio, Rosa Claudia; Federico, Stefano; Calidonna, Claudia Roberta; Avolio, Elenio; Drofa, Oxana; Landi, Tony Christian; Malguzzi, Piero; Buzzi, Andrea; Bonasoni, Paolo
2016-03-01
Quality of wind prediction is of great importance since a good wind forecast allows the prediction of available wind power, improving the penetration of renewable energies into the energy market. Here, a 1-year (1 December 2012 to 30 November 2013) three-model ensemble (TME) experiment for wind prediction is considered. The models employed, run operationally at National Research Council - Institute of Atmospheric Sciences and Climate (CNR-ISAC), are RAMS (Regional Atmospheric Modelling System), BOLAM (BOlogna Limited Area Model), and MOLOCH (MOdello LOCale in H coordinates). The area considered for the study is southern Italy and the measurements used for the forecast verification are those of the GTS (Global Telecommunication System). Comparison with observations is made every 3 h up to 48 h of forecast lead time. Results show that the three-model ensemble outperforms the forecast of each individual model. The RMSE improvement compared to the best model is between 22 and 30 %, depending on the season. It is also shown that the three-model ensemble outperforms the IFS (Integrated Forecasting System) of the ECMWF (European Centre for Medium-Range Weather Forecast) for the surface wind forecasts. Notably, the three-model ensemble forecast performs better than each unbiased model, showing the added value of the ensemble technique. Finally, the sensitivity of the three-model ensemble RMSE to the length of the training period is analysed.
EnsembleGASVR: A novel ensemble method for classifying missense single nucleotide polymorphisms
Rapakoulia, Trisevgeni
2014-04-26
Motivation: Single nucleotide polymorphisms (SNPs) are considered the most frequently occurring DNA sequence variations. Several computational methods have been proposed for the classification of missense SNPs to neutral and disease associated. However, existing computational approaches fail to select relevant features by choosing them arbitrarily without sufficient documentation. Moreover, they are limited to the problem ofmissing values, imbalance between the learning datasets and most of them do not support their predictions with confidence scores. Results: To overcome these limitations, a novel ensemble computational methodology is proposed. EnsembleGASVR facilitates a twostep algorithm, which in its first step applies a novel evolutionary embedded algorithm to locate close to optimal Support Vector Regression models. In its second step, these models are combined to extract a universal predictor, which is less prone to overfitting issues, systematizes the rebalancing of the learning sets and uses an internal approach for solving the missing values problem without loss of information. Confidence scores support all the predictions and the model becomes tunable by modifying the classification thresholds. An extensive study was performed for collecting the most relevant features for the problem of classifying SNPs, and a superset of 88 features was constructed. Experimental results show that the proposed framework outperforms well-known algorithms in terms of classification performance in the examined datasets. Finally, the proposed algorithmic framework was able to uncover the significant role of certain features such as the solvent accessibility feature, and the top-scored predictions were further validated by linking them with disease phenotypes. © The Author 2014.
Directory of Open Access Journals (Sweden)
E. Crestani
2013-04-01
Full Text Available Estimating the spatial variability of hydraulic conductivity K in natural aquifers is important for predicting the transport of dissolved compounds. Especially in the nonreactive case, the plume evolution is mainly controlled by the heterogeneity of K. At the local scale, the spatial distribution of K can be inferred by combining the Lagrangian formulation of the transport with a Kalman-filter-based technique and assimilating a sequence of time-lapse concentration C measurements, which, for example, can be evaluated on site through the application of a geophysical method. The objective of this work is to compare the ensemble Kalman filter (EnKF and the ensemble smoother (ES capabilities to retrieve the hydraulic conductivity spatial distribution in a groundwater flow and transport modeling framework. The application refers to a two-dimensional synthetic aquifer in which a tracer test is simulated. Moreover, since Kalman-filter-based methods are optimal only if each of the involved variables fit to a Gaussian probability density function (pdf and since this condition may not be met by some of the flow and transport state variables, issues related to the non-Gaussianity of the variables are analyzed and different transformation of the pdfs are considered in order to evaluate their influence on the performance of the methods. The results show that the EnKF reproduces with good accuracy the hydraulic conductivity field, outperforming the ES regardless of the pdf of the concentrations.
Sur deux mémoires de d'Alembert l'un concernant le calcul des probabilités, l'autre l'inoculation
Diderot, Denis
2015-01-01
Extrait : ""M. d'Alembert vient de publier ses Opuscules mathématiques. Il y a dans ce recueil deux mémoires qu'il n'est pas impossible de réduire à la langue ordinaire de la raison. L'un a pour objet le calcul des probabilités ; calcul dont l'application a tant d'importance et d'étendu. C'est proprement la science physico-mathématique de la vie. L'autre traite des avantages ou désavantages de l'inoculation.""
Tucci, Ingrid
2010-01-01
Comment s’articulent la question des inégalités sociales et de leur évolution et la question des modes de participation développés par les descendants de migrants au sein de cadres nationaux spécifiques aux niveaux historique, culturel, institutionnel et structurel ? Cet article se fonde sur l’exploitation de deux grandes enquêtes (l’enquête Étude de l’histoire familiale pour la France et le Panel socio-économique pour l’Allemagne) pour montrer que les modes de participation à l’école et au m...
Fabrice Dannequin
2004-01-01
Etudier le capitalisme peut se réaliser de façon fructueuse par la comparaison/confrontation d'auteurs comme Fernand Braudel et Joseph Schumpeter. Certes, le marché et le capitalisme sont imbriqués chez l'économiste, alors que chez l'historien les activités capitalistes ne constituent qu'une des modalités de l'échange au sein d'une tripartition. Néanmoins, dans les deux approches, les institutions, comme la monnaie et la concurrence, jouent un rôle fondamental. Le capitalisme connaît égalemen...
Chaplier, Claire; Crosnier, Élisabeth
2014-01-01
Actuellement, dans les formations universitaires Lansad-sciences (langues pour spécialistes d'autres disciplines), les enseignants-chercheurs doivent repenser l'enseignement de l'anglais en raison des contraintes institutionnelles. Dans cet article, nous décrivons l'expérience que nous avons menée auprès d'étudiants en 2ème année de master (M2) à travers deux dispositifs hybrides. Nous émettons l'hypothèse qu'un module d'anglais dans lequel la dimension psycho-affective est au centre de la mi...
Vanuytrecht, E.; Raes, D.; Willems, P.; Semenov, M.
2012-04-01
Global Circulation Models (GCMs) are sophisticated tools to study the future evolution of the climate. Yet, the coarse scale of GCMs of hundreds of kilometers raises questions about the suitability for agricultural impact assessments. These assessments are often made at field level and require consideration of interactions at sub-GCM grid scale (e.g., elevation-dependent climatic changes). Regional climate models (RCMs) were developed to provide climate projections at a spatial scale of 25-50 km for limited regions, e.g. Europe (Giorgi and Mearns, 1991). Climate projections from GCMs or RCMs are available as multi-model ensembles. These ensembles are based on large data sets of simulations produced by modelling groups worldwide, who performed a set of coordinated climate experiments in which climate models were run for a common set of experiments and various emissions scenarios (Knutti et al., 2010). The use of multi-model ensembles in climate change studies is an important step in quantifying uncertainty in impact predictions, which will underpin more informed decisions for adaptation and mitigation to changing climate (Semenov and Stratonovitch, 2010). The objective of our study was to evaluate the effect of the spatial scale of climate projections on climate change impacts for cereals in Belgium. Climate scenarios were based on two multi-model ensembles, one comprising 15 GCMs of the Coupled Model Intercomparison Project phase 3 (CMIP3; Meehl et al., 2007) with spatial resolution of 200-300 km, the other comprising 9 RCMs of the EU-ENSEMBLES project (van der Linden and Mitchell, 2009) with spatial resolution of 25 km. To be useful for agricultural impact assessments, the projections of GCMs and RCMs were downscaled to the field level. Long series (240 cropping seasons) of local-scale climate scenarios were generated by the LARS-WG weather generator (Semenov et al., 2010) via statistical inference. Crop growth and development were simulated with the Aqua
Formation Of Architectural Ensembles And Complexes Of Historic Towns Of Uzbekistan
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Manoev Said Bahronovich
2015-03-01
Full Text Available Abstract Historical architectural monuments of Uzbekistan attracts attention with their geometrical and compositional harmony. This harmony is one of the fundamentals of Central Asian Islamic architecture which based on decision of Middle Age architects to create ensemble in every case from local ensembles up to whole city ensemble. We can observe this kind of solutions in Ensembles Registrant and Gur Emir in Samarkand in Ensembles Kosh Madrasa and Labi Khovuz in Bukhara in Ensembles Dorus Saodat and Dorut Tilovat in Shakhrisabs in the whole city ensemble of Khiva and many others.
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G. Thirel
2010-04-01
Full Text Available The use of ensemble streamflow forecasts is developing in the international flood forecasting services. Such systems can provide more accurate forecasts and useful information about the uncertainty of the forecasts, thus improving the assessment of risks. Nevertheless, these systems, like all hydrological forecasts, suffer from errors on initialization or on meteorological data, which lead to hydrological prediction errors. This article, which is the second part of a 2-part article, concerns the impacts of initial states, improved by a streamflow assimilation system, on an ensemble streamflow prediction system over France. An assimilation system was implemented to improve the streamflow analysis of the SAFRAN-ISBA-MODCOU (SIM hydro-meteorological suite, which initializes the ensemble streamflow forecasts at Météo-France. This assimilation system, using the Best Linear Unbiased Estimator (BLUE and modifying the initial soil moisture states, showed an improvement of the streamflow analysis with low soil moisture increments. The final states of this suite were used to initialize the ensemble streamflow forecasts of Météo-France, which are based on the SIM model and use the European Centre for Medium-range Weather Forecasts (ECMWF 10-day Ensemble Prediction System (EPS. Two different configurations of the assimilation system were used in this study: the first with the classical SIM model and the second using improved soil physics in ISBA. The effects of the assimilation system on the ensemble streamflow forecasts were assessed for these two configurations, and a comparison was made with the original (i.e. without data assimilation and without the improved physics ensemble streamflow forecasts. It is shown that the assimilation system improved most of the statistical scores usually computed for the validation of ensemble predictions (RMSE, Brier Skill Score and its decomposition, Ranked Probability Skill Score, False Alarm Rate, etc., especially
Combining 2-m temperature nowcasting and short range ensemble forecasting
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A. Kann
2011-12-01
Full Text Available During recent years, numerical ensemble prediction systems have become an important tool for estimating the uncertainties of dynamical and physical processes as represented in numerical weather models. The latest generation of limited area ensemble prediction systems (LAM-EPSs allows for probabilistic forecasts at high resolution in both space and time. However, these systems still suffer from systematic deficiencies. Especially for nowcasting (0–6 h applications the ensemble spread is smaller than the actual forecast error. This paper tries to generate probabilistic short range 2-m temperature forecasts by combining a state-of-the-art nowcasting method and a limited area ensemble system, and compares the results with statistical methods. The Integrated Nowcasting Through Comprehensive Analysis (INCA system, which has been in operation at the Central Institute for Meteorology and Geodynamics (ZAMG since 2006 (Haiden et al., 2011, provides short range deterministic forecasts at high temporal (15 min–60 min and spatial (1 km resolution. An INCA Ensemble (INCA-EPS of 2-m temperature forecasts is constructed by applying a dynamical approach, a statistical approach, and a combined dynamic-statistical method. The dynamical method takes uncertainty information (i.e. ensemble variance from the operational limited area ensemble system ALADIN-LAEF (Aire Limitée Adaptation Dynamique Développement InterNational Limited Area Ensemble Forecasting which is running operationally at ZAMG (Wang et al., 2011. The purely statistical method assumes a well-calibrated spread-skill relation and applies ensemble spread according to the skill of the INCA forecast of the most recent past. The combined dynamic-statistical approach adapts the ensemble variance gained from ALADIN-LAEF with non-homogeneous Gaussian regression (NGR which yields a statistical mbox{correction} of the first and second moment (mean bias and dispersion for Gaussian distributed continuous
Wei, Guanghong; Xi, Wenhui; Nussinov, Ruth; Ma, Buyong
2016-06-01
All soluble proteins populate conformational ensembles that together constitute the native state. Their fluctuations in water are intrinsic thermodynamic phenomena, and the distributions of the states on the energy landscape are determined by statistical thermodynamics; however, they are optimized to perform their biological functions. In this review we briefly describe advances in free energy landscape studies of protein conformational ensembles. Experimental (nuclear magnetic resonance, small-angle X-ray scattering, single-molecule spectroscopy, and cryo-electron microscopy) and computational (replica-exchange molecular dynamics, metadynamics, and Markov state models) approaches have made great progress in recent years. These address the challenging characterization of the highly flexible and heterogeneous protein ensembles. We focus on structural aspects of protein conformational distributions, from collective motions of single- and multi-domain proteins, intrinsically disordered proteins, to multiprotein complexes. Importantly, we highlight recent studies that illustrate functional adjustment of protein conformational ensembles in the crowded cellular environment. We center on the role of the ensemble in recognition of small- and macro-molecules (protein and RNA/DNA) and emphasize emerging concepts of protein dynamics in enzyme catalysis. Overall, protein ensembles link fundamental physicochemical principles and protein behavior and the cellular network and its regulation. PMID:26807783
Relations entre associations féminines palestiniennes des deux côtés de la Ligne verte
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Elisabeth Marteu
2009-03-01
Full Text Available Les associations féminines arabes en Israël entretiennent des relations diverses avec leurs homologues des Territoires palestiniens. Basés sur des solidarités nationales, des coopérations professionnelles et/ou une assistance humanitaire croissante, les contacts entre Palestiniens des deux côtés de la Ligne verte sont en constante reconfiguration. Cet article se propose d’étudier les rapports transfrontaliers entre populations palestiniennes d’Israël et des Territoires occupés à l’aune de leur mobilisation féminine. En étudiant les liens qui se sont tissés entre associations de femmes dans les espaces israélo-palestiniens, cette recherche permet de comprendre les réajustements de la solidarité interpalestinienne. Si le déclenchement en 2000 de la seconde Intifada a renforcé les citoyens arabes dans leur affirmation d’une identité palestinienne, les enjeux immédiats de leur mobilisation sociale et politique restent ancrés dans les frontières de l’Etat israélien. De la même manière, la détérioration de la situation humanitaire dans les Territoires palestiniens conditionne la localisation des répertoires d’action des organisations civiles. Ainsi, quand bien même certains mouvements nationalistes et islamiques arabes défendraient l’idée d’une mobilisation palestinienne transfrontalière, les réalités et les priorités locales limitent, pour l’heure, toute concrétisation d’envergure.Arab women’s organizations in Israel maintain various relations with their Palestinian counterparts. Based on national solidarities, professional cooperations and/or increasing humanitarian assistance, contacts between Palestinians through the Green Line are in constant reconfiguration. This paper focuses on women’s mobilization in order to highlight transborder relations between Palestinian people from Israel and the Palestinian Territories. By studying links that developped between women’s organizations in the
On the proper use of Ensembles for Predictive Uncertainty assessment
Todini, Ezio; Coccia, Gabriele; Ortiz, Enrique
2015-04-01
Probabilistic forecasting has become popular in the last decades. Hydrological probabilistic forecasts have been based either on uncertainty processors (Krzysztofowic, 1999; Todini, 2004; Todini, 2008) or on ensembles, following meteorological traditional approaches and the establishment of the HEPEX program (http://hepex.irstea.fr. Unfortunately, the direct use of ensembles as a measure of the predictive density is an incorrect practice, because the ensemble measures the spread of the forecast instead of, following the definition of predictive uncertainty, the conditional probability of the future outcome conditional on the forecast. Only few correct approaches are reported in the literature, which correctly use the ensemble to estimate an expected conditional predictive density (Reggiani et al., 2009), similarly to what is done when several predictive models are available as in the BMA (Raftery et al., 2005) or MCP(Todini, 2008; Coccia and Todini, 2011) approaches. A major problem, limiting the correct use of ensembles, is in fact the difficulty of defining the time dependence of the ensemble members, due to the lack of a consistent ranking: in other words, when dealing with multiple models, the ith model remains the ith model regardless to the time of forecast, while this does not happen when dealing with ensemble members, since there is no definition for the ith member of an ensemble. Nonetheless, the MCP approach (Todini, 2008; Coccia and Todini, 2011), essentially based on a multiple regression in the Normal space, can be easily extended to use ensembles to represent the local (in time) smaller or larger conditional predictive uncertainty, as a function of the ensemble spread. This is done by modifying the classical linear regression equations, impliying perfectly observed predictors, to alternative regression equations similar to the Kalman filter ones, allowing for uncertain predictors. In this way, each prediction in time accounts for both the predictive
Regionalization of post-processed ensemble runoff forecasts
Olav Skøien, Jon; Bogner, Konrad; Salamon, Peter; Smith, Paul; Pappenberger, Florian
2016-05-01
For many years, meteorological models have been run with perturbated initial conditions or parameters to produce ensemble forecasts that are used as a proxy of the uncertainty of the forecasts. However, the ensembles are usually both biased (the mean is systematically too high or too low, compared with the observed weather), and has dispersion errors (the ensemble variance indicates a too low or too high confidence in the forecast, compared with the observed weather). The ensembles are therefore commonly post-processed to correct for these shortcomings. Here we look at one of these techniques, referred to as Ensemble Model Output Statistics (EMOS) (Gneiting et al., 2005). Originally, the post-processing parameters were identified as a fixed set of parameters for a region. The application of our work is the European Flood Awareness System (www.efas.eu" target="_blank">http://www.efas.eu), where a distributed model is run with meteorological ensembles as input. We are therefore dealing with a considerably larger data set than previous analyses. We also want to regionalize the parameters themselves for other locations than the calibration gauges. The post-processing parameters are therefore estimated for each calibration station, but with a spatial penalty for deviations from neighbouring stations, depending on the expected semivariance between the calibration catchment and these stations. The estimated post-processed parameters can then be used for regionalization of the postprocessing parameters also for uncalibrated locations using top-kriging in the rtop-package (Skøien et al., 2006, 2014). We will show results from cross-validation of the methodology and although our interest is mainly in identifying exceedance probabilities for certain return levels, we will also show how the rtop package can be used for creating a set of post-processed ensembles through simulations.
Quantifying Monte Carlo uncertainty in ensemble Kalman filter
Energy Technology Data Exchange (ETDEWEB)
Thulin, Kristian; Naevdal, Geir; Skaug, Hans Julius; Aanonsen, Sigurd Ivar
2009-01-15
This report is presenting results obtained during Kristian Thulin PhD study, and is a slightly modified form of a paper submitted to SPE Journal. Kristian Thulin did most of his portion of the work while being a PhD student at CIPR, University of Bergen. The ensemble Kalman filter (EnKF) is currently considered one of the most promising methods for conditioning reservoir simulation models to production data. The EnKF is a sequential Monte Carlo method based on a low rank approximation of the system covariance matrix. The posterior probability distribution of model variables may be estimated fram the updated ensemble, but because of the low rank covariance approximation, the updated ensemble members become correlated samples from the posterior distribution. We suggest using multiple EnKF runs, each with smaller ensemble size to obtain truly independent samples from the posterior distribution. This allows a point-wise confidence interval for the posterior cumulative distribution function (CDF) to be constructed. We present a methodology for finding an optimal combination of ensemble batch size (n) and number of EnKF runs (m) while keeping the total number of ensemble members ( m x n) constant. The optimal combination of n and m is found through minimizing the integrated mean square error (MSE) for the CDFs and we choose to define an EnKF run with 10.000 ensemble members as having zero Monte Carlo error. The methodology is tested on a simplistic, synthetic 2D model, but should be applicable also to larger, more realistic models. (author). 12 refs., figs.,tabs
Bayesian Processor of Ensemble for Precipitation Forecasting: A Development Plan
Toth, Z.; Krzysztofowicz, R.
2006-05-01
The Bayesian Processor of Ensemble (BPE) is a new, theoretically-based technique for probabilistic forecasting of weather variates. It is a generalization of the Bayesian Processor of Output (BPO) developed by Krzysztofowicz and Maranzano for processing single values of multiple predictors into a posterior distribution function of a predictand. The BPE processes an ensemble of a predictand generated by multiple integrations of a numerical weather prediction (NWP) model, and optimally fuses the ensemble with climatic data in order to quantify uncertainty about the predictand. As is well known, Bayes theorem provides the optimal theoretical framework for fusing information from different sources and for obtaining the posterior distribution function of a predictand. Using a family of such distribution functions, a given raw ensemble can be mapped into a posterior ensemble, which is well calibrated, has maximum informativeness, and preserves the spatio-temporal and cross-variate dependence structure of the NWP output fields. The challenge is to develop and test the BPE suitable for operational forecasting. This talk will present the basic design components of the BPE, along with a discussion of the climatic and training data to be used in its potential application at the National Centers for Environmental Prediction (NCEP). The technique will be tested first on quasi-normally distributed variates and next on precipitation variates. For reasons of economy, the BPE will be applied on the relatively coarse resolution grid corresponding to the ensemble output, and then the posterior ensemble will be downscaled to finer grids such as that of the National Digital Forecast Database (NDFD).
Critical adsorption and critical Casimir forces in the canonical ensemble.
Gross, Markus; Vasilyev, Oleg; Gambassi, Andrea; Dietrich, S
2016-08-01
Critical properties of a liquid film between two planar walls are investigated in the canonical ensemble, within which the total number of fluid particles, rather than their chemical potential, is kept constant. The effect of this constraint is analyzed within mean-field theory (MFT) based on a Ginzburg-Landau free-energy functional as well as via Monte Carlo simulations of the three-dimensional Ising model with fixed total magnetization. Within MFT and for finite adsorption strengths at the walls, the thermodynamic properties of the film in the canonical ensemble can be mapped exactly onto a grand canonical ensemble in which the corresponding chemical potential plays the role of the Lagrange multiplier associated with the constraint. However, due to a nonintegrable divergence of the mean-field order parameter profile near a wall, the limit of infinitely strong adsorption turns out to be not well-defined within MFT, because it would necessarily violate the constraint. The critical Casimir force (CCF) acting on the two planar walls of the film is generally found to behave differently in the canonical and grand canonical ensembles. For instance, the canonical CCF in the presence of equal preferential adsorption at the two walls is found to have the opposite sign and a slower decay behavior as a function of the film thickness compared to its grand canonical counterpart. We derive the stress tensor in the canonical ensemble and find that it has the same expression as in the grand canonical case, but with the chemical potential playing the role of the Lagrange multiplier associated with the constraint. The different behavior of the CCF in the two ensembles is rationalized within MFT by showing that, for a prescribed value of the thermodynamic control parameter of the film, i.e., density or chemical potential, the film pressures are identical in the two ensembles, while the corresponding bulk pressures are not. PMID:27627242
Critical adsorption and critical Casimir forces in the canonical ensemble
Gross, Markus; Vasilyev, Oleg; Gambassi, Andrea; Dietrich, S.
2016-08-01
Critical properties of a liquid film between two planar walls are investigated in the canonical ensemble, within which the total number of fluid particles, rather than their chemical potential, is kept constant. The effect of this constraint is analyzed within mean-field theory (MFT) based on a Ginzburg-Landau free-energy functional as well as via Monte Carlo simulations of the three-dimensional Ising model with fixed total magnetization. Within MFT and for finite adsorption strengths at the walls, the thermodynamic properties of the film in the canonical ensemble can be mapped exactly onto a grand canonical ensemble in which the corresponding chemical potential plays the role of the Lagrange multiplier associated with the constraint. However, due to a nonintegrable divergence of the mean-field order parameter profile near a wall, the limit of infinitely strong adsorption turns out to be not well-defined within MFT, because it would necessarily violate the constraint. The critical Casimir force (CCF) acting on the two planar walls of the film is generally found to behave differently in the canonical and grand canonical ensembles. For instance, the canonical CCF in the presence of equal preferential adsorption at the two walls is found to have the opposite sign and a slower decay behavior as a function of the film thickness compared to its grand canonical counterpart. We derive the stress tensor in the canonical ensemble and find that it has the same expression as in the grand canonical case, but with the chemical potential playing the role of the Lagrange multiplier associated with the constraint. The different behavior of the CCF in the two ensembles is rationalized within MFT by showing that, for a prescribed value of the thermodynamic control parameter of the film, i.e., density or chemical potential, the film pressures are identical in the two ensembles, while the corresponding bulk pressures are not.
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Détrie Catherine
2014-07-01
Notre but est non seulement de pointer la complexité des systèmes représentationnels de l’autre, mais aussi de faire émerger les prémices de systèmes organisés et complexes. En effet, chemin faisant, au-delà de la description des stéréotypes de l’Afrique dans deux discours présidentiels français, s’esquisse la problématique des idéologies et du déjà-dit qui gouverne la production des discours, dans un contexte bien précis qui impose ses contraintes : les relations franco-africaines. Dans un tel contexte, marqué par les thématiques, entre autres, de l’interculturalité, de la gestion délicate d’un passé commun, de relations de dominance, la catégorisation de l’autre est un acte de pouvoir, lourd de conséquences tant il participe à la construction ou à la reconduction de l’ordre social. La stéréotypie apparaît donc comme un lieu privilégié où s’élabore l’ipséité : nommer l’autre, c’est aussi mettre en scène le soi-même. Deux constats principaux se dégagent de cette analyse : d’une part, la permanence de schémas antinomiques issus de l’idéologie coloniale dans le discours de Nicolas Sarkozy, suggérant que l’idéologie du développement et l’idéologie coloniale entretiennent entre elles non seulement des relations de rupture, mais aussi de continuité, d’autre part, le fait que l’impératif économique du développement constitue le dénominateur commun à l’ensemble des stéréotypes, qui, en retour, servent d’arguments pour cette conclusion.
Verification of the Forecast Errors Based on Ensemble Spread
Vannitsem, S.; Van Schaeybroeck, B.
2014-12-01
The use of ensemble prediction systems allows for an uncertainty estimation of the forecast. Most end users do not require all the information contained in an ensemble and prefer the use of a single uncertainty measure. This measure is the ensemble spread which serves to forecast the forecast error. It is however unclear how best the quality of these forecasts can be performed, based on spread and forecast error only. The spread-error verification is intricate for two reasons: First for each probabilistic forecast only one observation is substantiated and second, the spread is not meant to provide an exact prediction for the error. Despite these facts several advances were recently made, all based on traditional deterministic verification of the error forecast. In particular, Grimit and Mass (2007) and Hopson (2014) considered in detail the strengths and weaknesses of the spread-error correlation, while Christensen et al (2014) developed a proper-score extension of the mean squared error. However, due to the strong variance of the error given a certain spread, the error forecast should be preferably considered as probabilistic in nature. In the present work, different probabilistic error models are proposed depending on the spread-error metrics used. Most of these models allow for the discrimination of a perfect forecast from an imperfect one, independent of the underlying ensemble distribution. The new spread-error scores are tested on the ensemble prediction system of the European Centre of Medium-range forecasts (ECMWF) over Europe and Africa. ReferencesChristensen, H. M., Moroz, I. M. and Palmer, T. N., 2014, Evaluation of ensemble forecast uncertainty using a new proper score: application to medium-range and seasonal forecasts. In press, Quarterly Journal of the Royal Meteorological Society. Grimit, E. P., and C. F. Mass, 2007: Measuring the ensemble spread-error relationship with a probabilistic approach: Stochastic ensemble results. Mon. Wea. Rev., 135, 203
Hierarchical Bayes Ensemble Kalman Filter for geophysical data assimilation
Tsyrulnikov, Michael; Rakitko, Alexander
2016-04-01
In the Ensemble Kalman Filter (EnKF), the forecast error covariance matrix B is estimated from a sample (ensemble), which inevitably implies a degree of uncertainty. This uncertainty is especially large in high dimensions, where the affordable ensemble size is orders of magnitude less than the dimensionality of the system. Common remedies include ad-hoc devices like variance inflation and covariance localization. The goal of this study is to optimize the account for the inherent uncertainty of the B matrix in EnKF. Following the idea by Myrseth and Omre (2010), we explicitly admit that the B matrix is unknown and random and estimate it along with the state (x) in an optimal hierarchical Bayes analysis scheme. We separate forecast errors into predictability errors (i.e. forecast errors due to uncertainties in the initial data) and model errors (forecast errors due to imperfections in the forecast model) and include the two respective components P and Q of the B matrix into the extended control vector (x,P,Q). Similarly, we break the traditional forecast ensemble into the predictability-error related ensemble and model-error related ensemble. The reason for the separation of model errors from predictability errors is the fundamental difference between the two sources of error. Model error are external (i.e. do not depend on the filter's performance) whereas predictability errors are internal to a filter (i.e. are determined by the filter's behavior). At the analysis step, we specify Inverse Wishart based priors for the random matrices P and Q and conditionally Gaussian prior for the state x. Then, we update the prior distribution of (x,P,Q) using both observation and ensemble data, so that ensemble members are used as generalized observations and ordinary observations are allowed to influence the covariances. We show that for linear dynamics and linear observation operators, conditional Gaussianity of the state is preserved in the course of filtering. At the forecast
An adaptive additive inflation scheme for Ensemble Kalman Filters
Sommer, Matthias; Janjic, Tijana
2016-04-01
Data assimilation for atmospheric dynamics requires an accurate estimate for the uncertainty of the forecast in order to obtain an optimal combination with available observations. This uncertainty has two components, firstly the uncertainty which originates in the the initial condition of that forecast itself and secondly the error of the numerical model used. While the former can be approximated quite successfully with an ensemble of forecasts (an additional sampling error will occur), little is known about the latter. For ensemble data assimilation, ad-hoc methods to address model error include multiplicative and additive inflation schemes, possibly also flow-dependent. The additive schemes rely on samples for the model error e.g. from short-term forecast tendencies or differences of forecasts with varying resolutions. However since these methods work in ensemble space (i.e. act directly on the ensemble perturbations) the sampling error is fixed and can be expected to affect the skill substiantially. In this contribution we show how inflation can be generalized to take into account more degrees of freedom and what improvements for future operational ensemble data assimilation can be expected from this, also in comparison with other inflation schemes.
Ensemble Forecasting of Major Solar Flares -- First Results
Pulkkinen, A. A.; Guerra, J. A.; Uritsky, V. M.
2015-12-01
We present the results from the first ensemble prediction model for major solar flares (M and X classes). Using the probabilistic forecasts from three models hosted at the Community Coordinated Modeling Center (NASA-GSFC) and the NOAA forecasts, we developed an ensemble forecast by linearly combining the flaring probabilities from all four methods. Performance-based combination weights were calculated using a Monte-Carlo-type algorithm that applies a decision threshold PthP_{th} to the combined probabilities and maximizing the Heidke Skill Score (HSS). Using the data for 13 recent solar active regions between years 2012 - 2014, we found that linear combination methods can improve the overall probabilistic prediction and improve the categorical prediction for certain values of decision thresholds. Combination weights vary with the applied threshold and none of the tested individual forecasting models seem to provide more accurate predictions than the others for all values of PthP_{th}. According to the maximum values of HSS, a performance-based weights calculated by averaging over the sample, performed similarly to a equally weighted model. The values PthP_{th} for which the ensemble forecast performs the best are 25 % for M-class flares and 15 % for X-class flares. When the human-adjusted probabilities from NOAA are excluded from the ensemble, the ensemble performance in terms of the Heidke score, is reduced.
Quantumness of correlations, quantumness of ensembles and quantum data hiding
International Nuclear Information System (INIS)
We study the quantumness of correlations for ensembles of bi- and multi-partite systems and relate it to the task of quantum data hiding. Quantumness is here intended in the sense of minimum average disturbance under local measurements. We consider a very general framework, but focus on local complete von Neumann measurements as the cause of the disturbance, and, later on, on the trace-distance as a quantifier of the disturbance. We discuss connections with entanglement and previously defined notions of quantumness of correlations. We prove that a large class of quantifiers of the quantumness of correlations are entanglement monotones for pure bipartite states. In particular, we define an entanglement of disturbance for pure states, for which we give an analytical expression. Such a measure coincides with negativity and concurrence for the case of two qubits. We compute general bounds on disturbance for both single states and ensembles, and consider several examples, including the uniform Haar ensemble of pure states, and pairs of qubit states. Finally, we show that the notion of ensemble quantumness of correlations is most relevant in quantum data hiding. Indeed, while it is known that entanglement is not necessary for a good quantum data-hiding scheme, we prove that ensemble quantumness of correlations is necessary. (paper)
Ensemble Forecasting of Volcanic Emissions in Hawai’i
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Andre Kristofer Pattantyus
2015-03-01
Full Text Available Deterministic model forecasts do not convey to the end users the forecast uncertainty the models possess as a result of physics parameterizations, simplifications in model representation of physical processes, and errors in initial conditions. This lack of understanding leads to a level of uncertainty in the forecasted value when only a single deterministic model forecast is available. Increasing computational power and parallel software architecture allows multiple simulations to be carried out simultaneously that yield useful measures of model uncertainty that can be derived from ensemble model results. The Hybrid Single Particle Lagrangian Integration Trajectory and Dispersion model has the ability to generate ensemble forecasts. A meteorological ensemble was formed to create probabilistic forecast products and an ensemble mean forecast for volcanic emissions from the Kilauea volcano that impacts the state of Hawai’i. The probabilistic forecast products show uncertainty in pollutant concentrations that are especially useful for decision-making regarding public health. Initial comparison of the ensemble mean forecasts with observations and a single model forecast show improvements in event timing for both sulfur dioxide and sulfate aerosol forecasts.
Properties of the Affine Invariant Ensemble Sampler in high dimensions
Huijser, David; Brewer, Brendon J
2015-01-01
We present theoretical and practical properties of the affine-invariant ensemble sampler Markov chain Monte Carlo method. In high dimensions the affine-invariant ensemble sampler shows unusual and undesirable properties. We demonstrate this with an $n$-dimensional correlated Gaussian toy problem with a known mean and covariance structure, and analyse the burn-in period. The burn-in period seems to be short, however upon closer inspection we discover the mean and the variance of the target distribution do not match the expected, known values. This problem becomes greater as $n$ increases. We therefore conclude that the affine-invariant ensemble sampler should be used with caution in high dimensional problems. We also present some theoretical results explaining this behaviour.
A Flexible Approach for the Statistical Visualization of Ensemble Data
Energy Technology Data Exchange (ETDEWEB)
Potter, K. [Univ. of Utah, Salt Lake City, UT (United States). SCI Institute; Wilson, A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Bremer, P. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Williams, Dean N. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Pascucci, V. [Univ. of Utah, Salt Lake City, UT (United States). SCI Institute; Johnson, C. [Univ. of Utah, Salt Lake City, UT (United States). SCI Institute
2009-09-29
Scientists are increasingly moving towards ensemble data sets to explore relationships present in dynamic systems. Ensemble data sets combine spatio-temporal simulation results generated using multiple numerical models, sampled input conditions and perturbed parameters. While ensemble data sets are a powerful tool for mitigating uncertainty, they pose significant visualization and analysis challenges due to their complexity. We present a collection of overview and statistical displays linked through a high level of interactivity to provide a framework for gaining key scientific insight into the distribution of the simulation results as well as the uncertainty associated with the data. In contrast to methods that present large amounts of diverse information in a single display, we argue that combining multiple linked statistical displays yields a clearer presentation of the data and facilitates a greater level of visual data analysis. We demonstrate this approach using driving problems from climate modeling and meteorology and discuss generalizations to other fields.
Matrix product purifications for canonical ensembles and quantum number distributions
Barthel, Thomas
2016-09-01
Matrix product purifications (MPPs) are a very efficient tool for the simulation of strongly correlated quantum many-body systems at finite temperatures. When a system features symmetries, these can be used to reduce computation costs substantially. It is straightforward to compute an MPP of a grand-canonical ensemble, also when symmetries are exploited. This paper provides and demonstrates methods for the efficient computation of MPPs of canonical ensembles under utilization of symmetries. Furthermore, we present a scheme for the evaluation of global quantum number distributions using matrix product density operators (MPDOs). We provide exact matrix product representations for canonical infinite-temperature states, and discuss how they can be constructed alternatively by applying matrix product operators to vacuum-type states or by using entangler Hamiltonians. A demonstration of the techniques for Heisenberg spin-1 /2 chains explains why the difference in the energy densities of canonical and grand-canonical ensembles decays as 1 /L .
Generalized Hypergeometric Ensembles: Statistical Hypothesis Testing in Complex Networks
Casiraghi, Giona; Scholtes, Ingo; Schweitzer, Frank
2016-01-01
Statistical ensembles define probability spaces of all networks consistent with given aggregate statistics and have become instrumental in the analysis of relational data on networked systems. Their numerical and analytical study provides the foundation for the inference of topological patterns, the definition of network-analytic measures, as well as for model selection and statistical hypothesis testing. Contributing to the foundation of these important data science techniques, in this article we introduce generalized hypergeometric ensembles, a framework of analytically tractable statistical ensembles of finite, directed and weighted networks. This framework can be interpreted as a generalization of the classical configuration model, which is commonly used to randomly generate networks with a given degree sequence or distribution. Our generalization rests on the introduction of dyadic link propensities, which capture the degree-corrected tendencies of pairs of nodes to form edges between each other. Studyin...
Probabilistic Quantitative Precipitation Forecasting Using Ensemble Model Output Statistics
Scheuerer, Michael
2013-01-01
Statistical post-processing of dynamical forecast ensembles is an essential component of weather forecasting. In this article, we present a post-processing method that generates full predictive probability distributions for precipitation accumulations based on ensemble model output statistics (EMOS). We model precipitation amounts by a generalized extreme value distribution that is left-censored at zero. This distribution permits modelling precipitation on the original scale without prior transformation of the data. A closed form expression for its continuous rank probability score can be derived and permits computationally efficient model fitting. We discuss an extension of our approach that incorporates further statistics characterizing the spatial variability of precipitation amounts in the vicinity of the location of interest. The proposed EMOS method is applied to daily 18-h forecasts of 6-h accumulated precipitation over Germany in 2011 using the COSMO-DE ensemble prediction system operated by the Germa...
Purification of an unpolarized spin ensemble into entangled singlet pairs
Greiner, Johannes N; Wrachtrup, Jörg
2016-01-01
Dynamical polarization of nuclear spin ensembles is of central importance for magnetic resonance studies, precision sensing and for applications in quantum information theory. Here we propose a scheme to generate long-lived singlet pairs in an unpolarized nuclear spin ensemble which is dipolar coupled to the electron spins of a Nitrogen Vacancy center in diamond. The quantum mechanical back-action induced by frequent spin-selective readout of the NV centers allows the nuclear spins to pair up into maximally entangled singlet pairs. Counterintuitively, the robustness of the pair formation to dephasing noise improves with increasing size of the spin ensemble. We also show how the paired nuclear spin state allows for enhanced sensing capabilities of NV centers in diamond.
Locally Accessible Information of Multisite Quantum Ensembles Violates Monogamy
De, Aditi Sen
2011-01-01
Locally accessible information is a useful information-theoretic physical quantity of an ensemble of multiparty quantum states. We find it has properties akin to quantum as well as classical correlations of single multiparty quantum states. It satisfies monotonicity under local quantum operations and classical communication. However we show that it does not follow monogamy, an important property usually satisfied by quantum correlations, and actually violates any such relation to the maximal extent. Violation is obtained even for locally indistinguishable, but globally orthogonal, multisite ensembles. The results assert that while single multiparty quantum states are monogamous with respect to their shared quantum correlations, ensembles of multiparty quantum states may not be so. The results have potential implications for quantum communication systems.
Generation of Exotic Quantum States of a Cold Atomic Ensemble
DEFF Research Database (Denmark)
Christensen, Stefan Lund
can be created and characterized. First we consider a spin-squeezed state. This state is generated by performing quantum non-demolition measurements of the atomic population difference. We show a spectroscopically relevant noise reduction of -1.7dB, the ensemble is in a many-body entangled state......Over the last decades quantum effects have become more and more controllable, leading to the implementations of various quantum information protocols. These protocols are all based on utilizing quantum correlation. In this thesis we consider how states of an atomic ensemble with such correlations...... — a nanofiber based light-atom interface. Using a dual-frequency probing method we measure and prepare an ensemble with a sub-Poissonian atom number distribution. This is a first step towards the implementation of more exotic quantum states....
Adaptive calibration of (u,v)‐wind ensemble forecasts
DEFF Research Database (Denmark)
Pinson, Pierre
2012-01-01
the adaptive calibration of ECMWF ensemble forecasts of (u,v)‐wind at 10 m above ground level over Europe over a three‐year period between December 2006 and December 2009. Substantial improvements in (bivariate) reliability and in various deterministic/probabilistic scores are observed. Finally, the...... sufficient reliability. The original framework introduced here allows for an adaptive bivariate calibration of these ensemble forecasts. The originality of this methodology lies in the fact that calibrated ensembles still consist of a set of (space–time) trajectories, after translation and dilation. In...... parallel, the parameters of the models employed for improving the stochastic properties of the generating processes involved are adaptively and recursively estimated to accommodate smooth changes in the process characteristics and to lower computational costs. The approach is applied and evaluated based on...
Representations and Ensemble Methods for Dynamic Relational Classification
Rossi, Ryan A
2011-01-01
Temporal networks are ubiquitous and evolve over time by the addition, deletion, and changing of links, nodes, and attributes. Although many relational datasets contain temporal information, the majority of existing techniques in relational learning focus on static snapshots and ignore the temporal dynamics. We propose a framework for discovering temporal representations of relational data to increase the accuracy of statistical relational learning algorithms. The temporal relational representations serve as a basis for classification, ensembles, and pattern mining in evolving domains. The framework includes (1) selecting the time-varying relational components (links, attributes, nodes), (2) selecting the temporal granularity, (3) predicting the temporal influence of each time-varying relational component, and (4) choosing the weighted relational classifier. Additionally, we propose temporal ensemble methods that exploit the temporal-dimension of relational data. These ensembles outperform traditional and mor...
Optical properties of indium phosphide nanowire ensembles at various temperatures
Energy Technology Data Exchange (ETDEWEB)
Lohn, Andrew J; Onishi, Takehiro; Kobayashi, Nobuhiko P [Baskin School of Engineering, University of California Santa Cruz, Santa Cruz, CA 95064 (United States); Nanostructured Energy Conversion Technology and Research (NECTAR), Advanced Studies Laboratories, University of California Santa Cruz-NASA Ames Research Center, Moffett Field, CA 94035 (United States)
2010-09-03
Ensembles that contain two types (zincblende and wurtzite) of indium phosphide nanowires grown on non-single crystalline surfaces were studied by micro-photoluminescence and micro-Raman spectroscopy at various low temperatures. The obtained spectra are discussed with the emphasis on the effects of differing lattice types, geometries, and crystallographic orientations present within an ensemble of nanowires grown on non-single crystalline surfaces. In the photoluminescence spectra, a typical Varshni dependence of band gap energy on temperature was observed for emissions from zincblende nanowires and in the high temperature regime energy transfer from excitonic transitions and band-edge transitions was identified. In contrast, the photoluminescence emissions associated with wurtzite nanowires were rather insensitive to temperature. Raman spectra were collected simultaneously from zincblende and wurtzite nanowires coexisting in an ensemble. Raman peaks of the wurtzite nanowires are interpreted as those related to the zincblende nanowires by a folding of the phonon dispersion.
Quantum teleportation between remote atomic-ensemble quantum memories
Bao, Xiao-Hui; Li, Che-Ming; Yuan, Zhen-Sheng; Lu, Chao-Yang; Pan, Jian-Wei
2012-01-01
Quantum teleportation and quantum memory are two crucial elements for large-scale quantum networks. With the help of prior distributed entanglement as a "quantum channel", quantum teleportation provides an intriguing means to faithfully transfer quantum states among distant locations without actual transmission of the physical carriers. Quantum memory enables controlled storage and retrieval of fast-flying photonic quantum bits with stationary matter systems, which is essential to achieve the scalability required for large-scale quantum networks. Combining these two capabilities, here we realize quantum teleportation between two remote atomic-ensemble quantum memory nodes, each composed of 100 million rubidium atoms and connected by a 150-meter optical fiber. The spinwave state of one atomic ensemble is mapped to a propagating photon, and subjected to Bell-state measurements with another single photon that is entangled with the spinwave state of the other ensemble. Two-photon detection events herald the succe...
Evaluation of LDA Ensembles Classifiers for Brain Computer Interface
Arjona, Cristian; Pentácolo, José; Gareis, Iván; Atum, Yanina; Gentiletti, Gerardo; Acevedo, Rubén; Rufiner, Leonardo
2011-12-01
The Brain Computer Interface (BCI) translates brain activity into computer commands. To increase the performance of the BCI, to decode the user intentions it is necessary to get better the feature extraction and classification techniques. In this article the performance of a three linear discriminant analysis (LDA) classifiers ensemble is studied. The system based on ensemble can theoretically achieved better classification results than the individual counterpart, regarding individual classifier generation algorithm and the procedures for combine their outputs. Classic algorithms based on ensembles such as bagging and boosting are discussed here. For the application on BCI, it was concluded that the generated results using ER and AUC as performance index do not give enough information to establish which configuration is better.
Ensembles of detectors for online detection of transient changes
Artemov, Alexey; Burnaev, Evgeny
2015-12-01
Classical change-point detection procedures assume a change-point model to be known and a change consisting in establishing a new observations regime, i.e. the change lasts infinitely long. These modeling assumptions contradicts applied problems statements. Therefore, even theoretically optimal statistics in practice very often fail when detecting transient changes online. In this work in order to overcome limitations of classical change-point detection procedures we consider approaches to constructing ensembles of change-point detectors, i.e. algorithms that use many detectors to reliably identify a change-point. We propose a learning paradigm and specific implementations of ensembles for change detection of short-term (transient) changes in observed time series. We demonstrate by means of numerical experiments that the performance of an ensemble is superior to that of the conventional change-point detection procedures.
Enhanced Sampling in the Well-Tempered Ensemble
Bonomi, M.; Parrinello, M.
2010-05-01
We introduce the well-tempered ensemble (WTE) which is the biased ensemble sampled by well-tempered metadynamics when the energy is used as collective variable. WTE can be designed so as to have approximately the same average energy as the canonical ensemble but much larger fluctuations. These two properties lead to an extremely fast exploration of phase space. An even greater efficiency is obtained when WTE is combined with parallel tempering. Unbiased Boltzmann averages are computed on the fly by a recently developed reweighting method [M. Bonomi , J. Comput. Chem. 30, 1615 (2009)JCCHDD0192-865110.1002/jcc.21305]. We apply WTE and its parallel tempering variant to the 2d Ising model and to a Gō model of HIV protease, demonstrating in these two representative cases that convergence is accelerated by orders of magnitude.
Circular β ensembles,CMV representation,characteristic polynomials
Institute of Scientific and Technical Information of China (English)
2009-01-01
In this note we first briefly review some recent progress in the study of the circular β ensemble on the unit circle,where β > 0 is a model parameter.In the special cases β = 1,2 and 4,this ensemble describes the joint probability density of eigenvalues of random orthogonal,unitary and sympletic matrices,respectively.For general β,Killip and Nenciu discovered a five-diagonal sparse matrix model,the CMV representation.This representation is new even in the case β = 2;and it has become a powerful tool for studying the circular β ensemble.We then give an elegant derivation for the moment identities of characteristic polynomials via the link with orthogonal polynomials on the unit circle.
Campagne Seacarib 2: Decrochements et frontieres de plaques dans les Caraibes
Mercier de Lepinay, B.
1990-01-01
In November/December 1987, the R/V Jean-Charcot conducted geophysical surveys (Seabeam bathymetry, single-channel seismic reflection, gravimetry and magnetism) along the northern caribbean boundary, between Cuba, Haiti and Jamaica (Pointe-a-Pitre/Santiago de Cuba/Fort-de-France). During that cruise, we focused our attention on the following themes: the transition between typical oceanic crust and thinned continental crust associated with early rifting; the structures associated with the Orien...
Efficient Kernel-Based Ensemble Gaussian Mixture Filtering
Liu, Bo
2015-11-11
We consider the Bayesian filtering problem for data assimilation following the kernel-based ensemble Gaussian-mixture filtering (EnGMF) approach introduced by Anderson and Anderson (1999). In this approach, the posterior distribution of the system state is propagated with the model using the ensemble Monte Carlo method, providing a forecast ensemble that is then used to construct a prior Gaussian-mixture (GM) based on the kernel density estimator. This results in two update steps: a Kalman filter (KF)-like update of the ensemble members and a particle filter (PF)-like update of the weights, followed by a resampling step to start a new forecast cycle. After formulating EnGMF for any observational operator, we analyze the influence of the bandwidth parameter of the kernel function on the covariance of the posterior distribution. We then focus on two aspects: i) the efficient implementation of EnGMF with (relatively) small ensembles, where we propose a new deterministic resampling strategy preserving the first two moments of the posterior GM to limit the sampling error; and ii) the analysis of the effect of the bandwidth parameter on contributions of KF and PF updates and on the weights variance. Numerical results using the Lorenz-96 model are presented to assess the behavior of EnGMF with deterministic resampling, study its sensitivity to different parameters and settings, and evaluate its performance against ensemble KFs. The proposed EnGMF approach with deterministic resampling suggests improved estimates in all tested scenarios, and is shown to require less localization and to be less sensitive to the choice of filtering parameters.
Numerical weather prediction model tuning via ensemble prediction system
Jarvinen, H.; Laine, M.; Ollinaho, P.; Solonen, A.; Haario, H.
2011-12-01
This paper discusses a novel approach to tune predictive skill of numerical weather prediction (NWP) models. NWP models contain tunable parameters which appear in parameterizations schemes of sub-grid scale physical processes. Currently, numerical values of these parameters are specified manually. In a recent dual manuscript (QJRMS, revised) we developed a new concept and method for on-line estimation of the NWP model parameters. The EPPES ("Ensemble prediction and parameter estimation system") method requires only minimal changes to the existing operational ensemble prediction infra-structure and it seems very cost-effective because practically no new computations are introduced. The approach provides an algorithmic decision making tool for model parameter optimization in operational NWP. In EPPES, statistical inference about the NWP model tunable parameters is made by (i) generating each member of the ensemble of predictions using different model parameter values, drawn from a proposal distribution, and (ii) feeding-back the relative merits of the parameter values to the proposal distribution, based on evaluation of a suitable likelihood function against verifying observations. In the presentation, the method is first illustrated in low-order numerical tests using a stochastic version of the Lorenz-95 model which effectively emulates the principal features of ensemble prediction systems. The EPPES method correctly detects the unknown and wrongly specified parameters values, and leads to an improved forecast skill. Second, results with an atmospheric general circulation model based ensemble prediction system show that the NWP model tuning capacity of EPPES scales up to realistic models and ensemble prediction systems. Finally, a global top-end NWP model tuning exercise with preliminary results is published.
Ensemble data assimilation for the reconstruction of mantle circulation
Bocher, Marie; Coltice, Nicolas; Fournier, Alexandre; Tackley, Paul
2016-04-01
The surface tectonics of the Earth is the result of mantle dynamics. This link between internal and surface dynamics can be used to reconstruct the evolution of mantle circulation. This is classically done by imposing plate tectonics reconstructions as boundary conditions on numerical models of mantle convection. However, this technique does not account for uncertainties in plate tectonics reconstructions and does not allow any dynamical feedback of mantle dynamics on surface tectonics to develop. Mantle convection models are now able to produce surface tectonics comparable to that of the Earth to first order. We capitalize on these convection models to propose a more consistent integration of plate tectonics reconstructions into mantle convection models. For this purpose, we use the ensemble Kalman filter. This method has been developed and successfully applied to meteorology, oceanography and even more recently outer core dynamics. It consists in integrating sequentially a time series of data into a numerical model, starting from an ensemble of possible initial states. The initial ensemble of states is designed to represent an approximation of the probability density function (pdf) of the a priori state of the system. Whenever new observations are available, each member of the ensemble states is corrected considering both the approximated pdf of the state, and the pdf of the new data. Between two observation times, each ensemble member evolution is computed independently, using the convection model. This technique provides at each time an approximation of the pdf of the state of the system, in the form of a finite ensemble of states. We perform synthetic experiments to assess the efficiency of this method for the reconstruction of mantle circulation.
Four-dimensional Localization and the Iterative Ensemble Kalman Smoother
Bocquet, M.
2015-12-01
The iterative ensemble Kalman smoother (IEnKS) is a data assimilation method meant for efficiently tracking the state ofnonlinear geophysical models. It combines an ensemble of model states to estimate the errors similarly to the ensemblesquare root Kalman filter, with a 4D-variational analysis performed within the ensemble space. As such it belongs tothe class of ensemble variational methods. Recently introduced 4DEnVar or the 4D-LETKF can be seen as particular casesof the scheme. The IEnKS was shown to outperform 4D-Var, the ensemble Kalman filter (EnKF) and smoother, with low-ordermodels in all investigated dynamical regimes. Like any ensemble method, it could require the use of localization of theanalysis when the state space dimension is high. However, localization for the IEnKS is not as straightforward as forthe EnKF. Indeed, localization needs to be defined across time, and it needs to be as much as possible consistent withthe dynamical flow within the data assimilation variational window. We show that a Liouville equation governs the timeevolution of the localization operator, which is linked to the evolution of the error correlations. It is argued thatits time integration strongly depends on the forecast dynamics. Using either covariance localization or domainlocalization, we propose and test several localization strategies meant to address the issue: (i) a constant and uniformlocalization, (ii) the propagation through the window of a restricted set of dominant modes of the error covariancematrix, (iii) the approximate propagation of the localization operator using model covariant local domains. Theseschemes are illustrated on the one-dimensional Lorenz 40-variable model.
Bailleau, Francis; Pattegay, Patrice; Fontaine, Séverine; Menzel, Abdel
2014-01-01
Cet article repose sur une recherche ethnologique concernant la vie ordinaire des jeunes dans deux quartiers défavorisés de deux villes moyennes, l’une, traditionnellement bourgeoise, l’autre, traditionnellement ouvrière, intégrant un passé riche en luttes économiques et sociales. Un couple de jeunes enquêteurs a passé trois mois dans chaque quartier, vivant avec les jeunes.L’organisation de l’espace dans les « quartiers » et la fonction de la ville-centre engendrent des conséquences majeures...
TAALBI, Amina
2016-01-01
Notre travail s’est basé principalement sur une étude de la variabilité chimique et l’intérêt économique des huiles essentielles de deux menthes sauvages de l’ouest algérien: Mentha pulegium et Mentha rotundifolia. Ces deux menthes, largement répandue en Algérie, de la famille des Lamiaceae sont connus dans le monde pour leurs propriétés thérapeutiques (antiseptique, antinévralgique, analgésique…) et l’intérêt économique de leurs huiles essentielles....
Bred vectors with customizable scale: 'À la carte' ensemble perturbations
Homar Santaner, V.; Stensrud, D. J.
2009-09-01
Short-range forecasts of severe weather are one of the most challenging tasks faced by the atmospheric science community. Our persistent failure to generate accurate numerical forecasts of tornadoes, large hail, heavy precipitation or strong wind events is caused by two fundamental aspects of numerical forecast systems: the chaotic nature of the governing equations and the large uncertainties in both the atmospheric state and the models that govern its evolution. Currently, we cope with both sources of error by describing the state of the atmosphere in a probabilistic manner. In this framework, forecasting becomes predicting the probability density function (pdf) of future states, given the pdf of initial states that are compatible with available observations and previous forecasts. This probabilistic perspective is often created by generating ensembles of deterministic predictions that are aimed at sampling the most important sources of uncertainty in the forecasting system. The ensemble generation/sampling strategy is a crucial aspect of their performance and various methods have been proposed. Although global forecasting offices have been using ensembles of perturbed initial conditions for medium-range operational forecasts since 1994, no consensus exists regarding the optimum sampling strategy for high resolution short-range ensemble forecasts with predicting skill in the mesoscale. Bred vectors, however, have been hypothesized to better capture the growing modes in the highly nonlinear mesoscale dynamics of severe episodes than singular vectors or observation perturbations. Yet even this technique is not able to produce enough diversity in the ensembles to accurately and routinely predict extreme phenomena such as severe weather. Thus, we propose a new method to generate ensembles of initial conditions perturbations that is based on the breeding technique. Given a standard bred mode, a set of customized perturbations is derived with specified amplitudes and
FOXP3 ensembles in T-cell regulation.
Li, Bin; Samanta, Arabinda; Song, Xiaomin; Furuuchi, Keiji; Iacono, Kathryn T; Kennedy, Sarah; Katsumata, Makoto; Saouaf, Sandra J; Greene, Mark I
2006-08-01
Our recent studies have identified dynamic protein ensembles containing forkhead box protein 3 (FOXP3) that provide insight into the molecular complexity of suppressor T-cell activities, and it is our goal to determine how these ensembles regulate FOXP3's transcriptional activity in vivo. In this review, we summarize our current understanding of how FOXP3 expression is induced and how FOXP3 functions in vivo as a transcriptional regulator by assembling a multisubunit complex involved in histone modification as well as chromatin remodeling. PMID:16903909
A new ensemble model for short term wind power prediction
DEFF Research Database (Denmark)
Madsen, Henrik; Albu, Razvan-Daniel; Felea, Ioan;
2012-01-01
As the objective of this study, a non-linear ensemble system is used to develop a new model for predicting wind speed in short-term time scale. Short-term wind power prediction becomes an extremely important field of research for the energy sector. Regardless of the recent advancements in the re......-search of prediction models, it was observed that different models have different capabilities and also no single model is suitable under all situations. The idea behind EPS (ensemble prediction systems) is to take advantage of the unique features of each subsystem to detain diverse patterns that exist in the dataset...
ENSEMBLE methods to reconcile disparate national long range dispersion forecasts
DEFF Research Database (Denmark)
Mikkelsen, Torben; Galmarini, S.; Bianconi, R.;
2003-01-01
and Web-based software evaluation and exchange tools have been created for real-time reconciliation and harmonisation of real-time dispersion forecastsfrom meteorological and emergency centres across Europe during an accident. The new ENSEMBLE software tools is available to participating national....... ENSEMBLE addresses the problem of achieving a common coherent strategy across European national emergency management when national long-range dispersion forecasts differ from one another during an accidentalatmospheric release of radioactive material. A series of new decision-making “ENSEMBLE” procedures...
Normal random matrix ensemble as a growth problem
Teodorescu, R.; Bettelheim, E.; Agam, O.; Zabrodin, A.; Wiegmann, P.
2004-01-01
In general or normal random matrix ensembles, the support of eigenvalues of large size matrices is a planar domain (or several domains) with a sharp boundary. This domain evolves under a change of parameters of the potential and of the size of matrices. The boundary of the support of eigenvalues is a real section of a complex curve. Algebro-geometrical properties of this curve encode physical properties of random matrix ensembles. This curve can be treated as a limit of a spectral curve which...
Molecular Dynamics Simulation of Glass Transition Behavior of Polyimide Ensemble
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
The effect of chromophores to the glass transition temperature of polyimide ensemble has been investigated by means of molecular dynamics simulation in conjunction with barrier analysis. Simulated Tg results indicated a good agreement with experimental value. This study showed the MD simulation could estimate the effect of chromophores to the Tg of polyimide ensemble conveniently and an estimation approach method had a surprising deviation of Tg from experiment. At the same time, a polyimide structure with higher barrier energy was designed and validated by MD simulation.
A Brief Tutorial on the Ensemble Kalman Filter
Mandel, Jan
2009-01-01
The ensemble Kalman filter (EnKF) is a recursive filter suitable for problems with a large number of variables, such as discretizations of partial differential equations in geophysical models. The EnKF originated as a version of the Kalman filter for large problems (essentially, the covariance matrix is replaced by the sample covariance), and it is now an important data assimilation component of ensemble forecasting. EnKF is related to the particle filter (in this context, a particle is the s...
Reservoir History Matching Using Ensemble Kalman Filters with Anamorphosis Transforms
Aman, Beshir M.
2012-12-01
This work aims to enhance the Ensemble Kalman Filter performance by transforming the non-Gaussian state variables into Gaussian variables to be a step closer to optimality. This is done by using univariate and multivariate Box-Cox transformation. Some History matching methods such as Kalman filter, particle filter and the ensemble Kalman filter are reviewed and applied to a test case in the reservoir application. The key idea is to apply the transformation before the update step and then transform back after applying the Kalman correction. In general, the results of the multivariate method was promising, despite the fact it over-estimated some variables.
Echchaoui, Abdelmoughit; Benyachou, Malika; Hafidi, Jawad; Fathi, Nahed; Mohammadine, Elhamid; ELmazouz, Samir; Gharib, Nour-eddine; Abbassi, Abdellah
2014-01-01
Les malformations anorectales chez l'adulte sont des anomalies congénitales rares du tube digestif qui prédominent chez le sexe féminin. Notre étude porte sur deux observations de malformation anorectale basses vues et traitées au stade adulte par les 2 équipes (plasticiens et viscéralistes) à l'Hôpital Avicenne à Rabat. Il s'agit d'un homme de 24 ans avec une dyschésie anale l'autre cas est une femme de 18 ans avec une malformation anovulvaire Les caractéristiques cliniques combinées avec les imageries radiologiques (lavement baryté, et la manométrie anorectale) ont confirmé qu'il s'agit d'une malfomation anorectale basse. Les deux cas sont corrigés par une reconstruction sphinctérienne, réimplantation anale avec anoplastie périnéale. Les suites opératoires étaient simples, pas de souffrance cutanée ou nécrose, avec changement de pansement gras chaque jour. Le résultat fonctionnel (la continence) était favorable pour les 2 patients. La présentation des MAR à l’âge adulte est rare, d’étiologie mal connu, elles apparaissent selon le mode sporadique. Les caractéristiques cliniques, couplées à l'imagerie (lavement baryté, IRM pelvienne), l'endoscopie et la manométrie anorectale, permettent de confirmer le diagnostic et classer ces anomalies en 3 types: basses, intermédiaires, et hautes. Les formes basses sont traités d'emblée par une réimplantation anale et anoplastie périnéale simple tels nos deux cas, elles peuvent être traités dans certains cas par un abaissement anorectale associé à une plastie V-Y permettant ainsi un emplacement anatomique correct de l'anus; alors que les formes hautes ou intermédiaires relèvent d'une chirurgie complexe avec souvent une dérivation digestive transitoire. Contrairement aux autres formes, Les formes basses ont un pronostic fonctionnel favorable. PMID:25667689
Directory of Open Access Journals (Sweden)
Bois P.
2006-11-01
Full Text Available Durant les dix dernières années, la théorie des sous-ensembles flous a connu un intérêt croissant grâce aux travaux de Zadeh [1]. Cette théorie a vu son champ d'application s'étendre à différentes branches des mathématiques pures et appliquées en particulier à la topologie, à la théorie des graphes, des automates et à la reconnaissance des formes. Son but est d'analyser l'imprécision qui se glisse partout dans le comportement humain et dans la connaissance humaine. Cet article donne deux applications de la théorie des sous-ensembles flous à la prospection sismique. La première concerne l'interprétation d'une section sismique qui consiste à tracer une carte du sous-sol montrant la position des différents horizons sismiques situés au dessous de la surface du sol. Le problème qui se pose au sismicien est de trouver la structure géologique correspondante dans un plan vertical à la surface du sol. La seconde est la détermination de la nature des réservoirs contenant des hydrocarbures. On utilisera une méthode s'appuyant sur la reconnaissance des formes avec apprentissage préalable. Cette méthode consiste à comparer la nature d'un réservoir qui a été foré à celle d'un réservoir inconnu. Le réservoir connu joue le rôle du moniteur dans le processus d'apprentissage. Pour ce faire, un algorithme est conçu utilisant la méthode de Burg appliquée à des portions de traces sismiques représentatives des deux réservoirs. Enfin, une analyse floue des données représentant ces deux réservoirs sert de critère pour décider s'ils sont de nature identique ou différente. During the past decade, interest in fuzzy subsets theory has led to the development of a well-organized theory developed by Zadeh [1]. This theory has grown up, exploring and developing various branches of pure and applied mathematics, including topology, graph theory, mapping, automata and pattern recognition. Basically, the theory of fuzzy subsets
Takehiro, Naoki; Liu, Ping; Bergbreiter, Andreas; K. Nørskov, Jens; Behm, R. Juergen
2014-01-01
The adsorption of hydrogen on structurally well defined PdAu-Pd(111) monolayer surface alloys was investigated in a combined experimental and theoretical study, aiming at a quantitative understanding of the adsorption and desorption properties of individual PdAu nanostructures. Combining the structural information obtained by high resolution scanning tunneling microscopy (STM), in particular on the abundance of specific adsorption ensembles at different Pd surface concentrations, with informa...
Gomez, Anne-Sophie
2014-01-01
Au début des années 2000, plusieurs jeunes réalisateurs germanophones s’emparèrent de la matière des contes pour en proposer une vision plus personnelle, articulée autour d’effets de réminiscence, de variation et d’ellipse. Notre étude se concentre sur deux exemples. Le premier est celui de Milchwald (Le Bois lacté) réalisé en 2003 par le jeune cinéaste allemand Christoph Hochhäusler. Dans ce long-métrage, le spectateur identifie aisément des motifs empruntés au conte Hänsel et Gretel, comme ...
Arnaud et Hoël, deux évêques du Mans au service de Guillaume le Conquérant
Hillion, Yannick
2005-01-01
Après sa fragile conquête du comté du Maine en 1063, le duc de Normandie Guillaume devait absolument contrôler l’évêché du Mans face à l’Anjou conquérant et à l’aristocratie mancelle, elle-même encline à retrouver son indépendance. Le choix du duc, devenu roi d’Angleterre en 1066, se porta sur deux clercs, Arnaud et Hoël, dont les épiscopats caractérisèrent l’occupation normande du comté, de 1065 à 1096. Arnaud et Hoël, issu sans doute d’une même famille cléricale avranchine, sont des « homin...
Réflexions sur deux mémoires inconciliables : celle du maître et celle de l’esclave
Barthélemy, Gérard
2007-01-01
En s’appuyant notamment sur le cas d’Haïti, l’auteur tente de démontrer qu’il est pratiquement impossible qu’anciens maîtres et anciens esclaves puissent commémorer de façon conjointe la fin de l’esclavage ou l’émancipation générale. En effet, les deux protagonistes ne sauraient partager une vue commune de leur passé et, si le paysan haïtien d’aujourd’hui ne conserve plus, par exemple, que le souvenir de la fin de la contrainte exercée sur lui ainsi que celui d’une victoire sur son ancien maî...
Roy, Didier; Oudeyer, Pierre-Yves
2016-01-01
Deux dispositifs robotiques pour l'enseignement de l'informatique et de la robotique.IniRobot repose sur l'usage du robot Thymio II, conçu notamment par l'EPFL (Lausanne), et s'adresse principalement aux élèves de l'école primaire et du début du collège.Poppy Education utilise la plateforme Poppy développé par l'équipe de recherche Flowers d'Inria BSO et est destiné aux élèves de fin de collège, de lycée et de l'enseignement supérieur.Les robots utilisés sont open-source et libres, avec la pa...
Abdelmoughit ECHCHAOUI; Benyachou, Malika; Hafidi, Jawad; Fathi, Nahed; Mohammadine, Elhamid; ELmazouz, Samir; Gharib, Nour-eddine; Abbassi, Abdellah
2014-01-01
Les malformations anorectales chez l'adulte sont des anomalies congénitales rares du tube digestif qui prédominent chez le sexe féminin. Notre étude porte sur deux observations de malformation anorectale basses vues et traitées au stade adulte par les 2 équipes (plasticiens et viscéralistes) à l'Hôpital Avicenne à Rabat. Il s'agit d'un homme de 24 ans avec une dyschésie anale l'autre cas est une femme de 18 ans avec une malformation anovulvaire Les caractéristiques cliniques combinées avec le...
L'évolution de l'activisme actionnarial en France au cours des deux dernières décennies
Girard, Carine; Gates, Stephen
2013-01-01
Le paysage de la recherche portant sur l'activisme actionnarial a beaucoup évolué au cours de ces deux dernières décennies, depuis les recherches fondatrices dont le socle est la théorie positive de l'agence. L'objectif de cette étude exploratoire est d'illustrer cette évolution, à travers une synthèse des travaux empiriques menés dans un contexte institutionnel et légal peu connu des chercheurs anglo-saxons : le contexte français. De cette synthèse, nous proposerons un nouveau modèle concept...
Quantum aspects of cavity optomechanics with atomic ensembles and ensemble arrays
Stamper-Kurn, Dan
2012-06-01
While the motion of a many-atom ensemble of atoms interacting strongly with a single mode of an optical resonator can be devilishly complicated, under favorable conditions, the cavity can be made to interact with and to sense just one, or just a few, normal modes of the gaseous system. This leads to an atoms-based realization of cavity optomechanics, directly analogous to experiments in which one seeks to observe the motion of suspended mirrors, cantilevers, and membranes at the quantum limits of precision. I will discuss our progress toward demonstrating and understanding the distinctively quantum mechanical aspects of both the ``opto'' and ``mechanical'' portions of cavity optomechanical systems. Specifically, I will report on the observation of the ponderomotive squeezing of light by a mechanical oscillator, and of strong motional sideband asymmetry that demonstrates the quantization of collective atomic motion and quantifies the energy flux into the mechanical system due to quantum measurement backaction. I will conclude by describing our approach to realizing strong cavity coupling to a multi-mode mechanical system, specifically to an array of distinguishable mechanical oscillators. [4pt] The work reported in this talk was performed in collaboration with members of my research group, including Thierry Botter, Nathaniel Brahms, Daniel Brooks, Thomas Purdy and Sydney Schreppler, and was supported by the AFOSR and NSF.
Directory of Open Access Journals (Sweden)
Audrey Ogès
2015-12-01
Full Text Available Cet article instruit un parallèle entre deux auteures du Pacifique : Déwé Görödé et Chantal Spitz, l'une kanak, l'autre polynésienne. Il montre comment ces deux femmes expriment leurs souffrances, dans une position anti-coloniale. Ceci se traduit dans l'écriture, où le refus des normes et des formes liées à la culture française est omniprésent : transgressions des genres, déconstruction des codes grammaticaux, recours à des formes linguistiques jugées « familières » ou « populaires », expression de la révolte et de la violence.... Elles assument cette nouvelle parole, et ce nouveau style d'écriture, qui est le leur, accédant ainsi à une liberté nouvelle. Colonial violences and subversive writing in Déwé Görödé and Chantal Spitz books. Abstract: Déwé Görödé and Chantal Spitz are two postcolonial writers from the Pacific, the first one is Kanak and the second one is Polynesian. These two women free and rebellious don't respect the norms in their books : they want to show the violence of the colonialism in their countries. Their style is dashing and broken : these writers don't respect the grammatical norms, as they put it, and the art of writing reflects their free state of mind. This singular writing is the affirmation of their freedom.
Directory of Open Access Journals (Sweden)
NIHOUARN A.
1990-10-01
Full Text Available La production d'un hybride mâle sauvage x femelle domestique, chez la truite commune (Salmo trutta a parfois été proposée pour le repeuplement (CUINAT, 1971. Nos précédents travaux (MAISSE et al., 1983 ont montré que ces sujets sont plus difficiles à élever que ceux dont les deux parents sont domestiques. La présente étude a porté sur la comparaison des performances des hybrides et des domestiques déversés simultanément dans un ruisseau où la reproduction de la truite est compromise par le colmatage du fond. Les déversements ont été effectués sur la totalité du ruisseau, en mai, deux années de suite. Des inventaires ont été réalisés sur des secteurs représentatifs en mai, avant les déversements, et en octobre. Les résultats ont montré que les taux d'implantation, tant en 0+ qu'en 1+, ne différaient pas suivant l'origine des poissons. De plus, sur chacun des secteurs inventoriés, les individus d'origine domestique ont gardé l'avantage de taille qu'ils avaient au moment du déversement. L'intérêt d'un tel croisement est discuté en fonction des diverses stratégies de repeuplement à mettre en œuvre.
Scale-free brain ensemble modulated by phase synchronization
Institute of Scientific and Technical Information of China (English)
Dan WU; Chao-yi LI; Jie LIU; Jing LU; De-zhong YAO
2014-01-01
To listen to brain activity as a piece of music, we proposed the scale-free brainwave music (SFBM) technology, which could translate the scalp electroencephalogram (EEG) into music notes according to the power law of both EEG and music. In the current study, this methodology was further extended to a musical ensemble of two channels. First, EEG data from two selected channels are translated into musical instrument digital interface (MIDI) sequences, where the EEG parameters modulate the pitch, duration, and volume of each musical note. The phase synchronization index of the two channels is computed by a Hilbert transform. Then the two MIDI sequences are integrated into a chorus according to the phase synchronization index. The EEG with a high synchronization index is represented by more consonant musical intervals, while the low index is expressed by inconsonant musical intervals. The brain ensemble derived from real EEG segments illustrates differences in harmony and pitch distribution during the eyes-closed and eyes-open states. Furthermore, the scale-free phenomena exist in the brainwave ensemble. Therefore, the scale-free brain ensemble modulated by phase synchronization is a new attempt to express the EEG through an auditory and musical way, and it can be used for EEG monitoring and bio-feedback.
ENSEMBLE methods to reconcile disparate national long range dispersion forecasting
Energy Technology Data Exchange (ETDEWEB)
Mikkelsen, T.; Galmarini, S.; Bianconi, R.; French, S. (eds.)
2003-11-01
ENSEMBLE is a web-based decision support system for real-time exchange and evaluation of national long-range dispersion forecasts of nuclear releases with cross-boundary consequences. The system is developed with the purpose to reconcile among disparate national forecasts for long-range dispersion. ENSEMBLE addresses the problem of achieving a common coherent strategy across European national emergency management when national long-range dispersion forecasts differ from one another during an accidental atmospheric release of radioactive material. A series of new decision-making 'ENSEMBLE' procedures and Web-based software evaluation and exchange tools have been created for real-time reconciliation and harmonisation of real-time dispersion forecasts from meteorological and emergency centres across Europe during an accident. The new ENSEMBLE software tools is available to participating national emergency and meteorological forecasting centres, which may choose to integrate them directly into operational emergency information systems, or possibly use them as a basis for future system development. (au)
Wave Extremes in the North East Atlantic from Ensemble Forecasts
Breivik, Øyvind; Bidlot, Jean-Raymond; Carrasco, Ana; Saetra, Øyvind; 10.1175/JCLI-D-12-00738.1
2013-01-01
A method for estimating return values from ensembles of forecasts at advanced lead times is presented. Return values of significant wave height in the North-East Atlantic, the Norwegian Sea and the North Sea are computed from archived +240-h forecasts of the ECMWF ensemble prediction system (EPS) from 1999 to 2009. We make three assumptions: First, each forecast is representative of a six-hour interval and collectively the data set is then comparable to a time period of 226 years. Second, the model climate matches the observed distribution, which we confirm by comparing with buoy data. Third, the ensemble members are sufficiently uncorrelated to be considered independent realizations of the model climate. We find anomaly correlations of 0.20, but peak events (>P97) are entirely uncorrelated. By comparing return values from individual members with return values of subsamples of the data set we also find that the estimates follow the same distribution and appear unaffected by correlations in the ensemble. The a...
Ensemble prediction experiments using conditional nonlinear optimal perturbation
Institute of Scientific and Technical Information of China (English)
无
2009-01-01
Two methods for initialization of ensemble forecasts are compared, namely, singular vector (SV) and conditional nonlinear optimal perturbation (CNOP). The comparison is done for forecast lengths of up to 10 days with a three-level quasi-geostrophic (QG) atmospheric model in a perfect model scenario. Ten cases are randomly selected from 1982/1983 winter to 1993/1994 winter (from December to the following February). Anomaly correlation coefficient (ACC) is adopted as a tool to measure the quality of the predicted ensembles on the Northern Hemisphere 500 hPa geopotential height. The results show that the forecast quality of ensemble samples in which the first SV is replaced by CNOP is higher than that of samples composed of only SVs in the medium range, based on the occurrence of weather re-gime transitions in Northern Hemisphere after about four days. Besides, the reliability of ensemble forecasts is evaluated by the Rank Histograms. The above conclusions confirm and extend those reached earlier by the authors, which stated that the introduction of CNOP improves the forecast skill under the condition that the analysis error belongs to a kind of fast-growing error by using a barotropic QG model.
Malignancy and Abnormality Detection of Mammograms using Classifier Ensembling
Directory of Open Access Journals (Sweden)
Nawazish Naveed
2011-07-01
Full Text Available The breast cancer detection and diagnosis is a critical and complex procedure that demands high degree of accuracy. In computer aided diagnostic systems, the breast cancer detection is a two stage procedure. First, to classify the malignant and benign mammograms, while in second stage, the type of abnormality is detected. In this paper, we have developed a novel architecture to enhance the classification of malignant and benign mammograms using multi-classification of malignant mammograms into six abnormality classes. DWT (Discrete Wavelet Transformation features are extracted from preprocessed images and passed through different classifiers. To improve accuracy, results generated by various classifiers are ensembled. The genetic algorithm is used to find optimal weights rather than assigning weights to the results of classifiers on the basis of heuristics. The mammograms declared as malignant by ensemble classifiers are divided into six classes. The ensemble classifiers are further used for multiclassification using one-against-all technique for classification. The output of all ensemble classifiers is combined by product, median and mean rule. It has been observed that the accuracy of classification of abnormalities is more than 97% in case of mean rule. The Mammographic Image Analysis Society dataset is used for experimentation.
Enhancing COSMO-DE ensemble forecasts by inexpensive techniques
Directory of Open Access Journals (Sweden)
Zied Ben Bouallègue
2013-02-01
Full Text Available COSMO-DE-EPS, a convection-permitting ensemble prediction system based on the high-resolution numerical weather prediction model COSMO-DE, is pre-operational since December 2010, providing probabilistic forecasts which cover Germany. This ensemble system comprises 20 members based on variations of the lateral boundary conditions, the physics parameterizations and the initial conditions. In order to increase the sample size in a computationally inexpensive way, COSMO-DE-EPS is combined with alternative ensemble techniques: the neighborhood method and the time-lagged approach. Their impact on the quality of the resulting probabilistic forecasts is assessed. Objective verification is performed over a six months period, scores based on the Brier score and its decomposition are shown for June 2011. The combination of the ensemble system with the alternative approaches improves probabilistic forecasts of precipitation in particular for high precipitation thresholds. Moreover, combining COSMO-DE-EPS with only the time-lagged approach improves the skill of area probabilities for precipitation and does not deteriorate the skill of 2 m-temperature and wind gusts forecasts.
Enhancing COSMO-DE ensemble forecasts by inexpensive techniques
Energy Technology Data Exchange (ETDEWEB)
Ben Bouallegue, Zied; Theis, Susanne E.; Gebhardt, Christoph [Deutscher Wetterdienst, Offenbach am Main (Germany)
2013-02-15
COSMO-DE-EPS, a convection-permitting ensemble prediction system based on the high-resolution numerical weather prediction model COSMO-DE, is pre-operational since December 2010, providing probabilistic forecasts which cover Germany. This ensemble system comprises 20 members based on variations of the lateral boundary conditions, the physics parameterizations and the initial conditions. In order to increase the sample size in a computationally inexpensive way, COSMO-DE-EPS is combined with alternative ensemble techniques: the neighborhood method and the time-lagged approach. Their impact on the quality of the resulting probabilistic forecasts is assessed. Objective verification is performed over a six months period, scores based on the Brier score and its decomposition are shown for June 2011. The combination of the ensemble system with the alternative approaches improves probabilistic forecasts of precipitation in particular for high precipitation thresholds. Moreover, combining COSMO-DE-EPS with only the time-lagged approach improves the skill of area probabilities for precipitation and does not deteriorate the skill of 2 m-temperature and wind gusts forecasts. (orig.)
Power to Detect Intervention Effects on Ensembles of Social Networks
Sweet, Tracy M.; Junker, Brian W.
2016-01-01
The hierarchical network model (HNM) is a framework introduced by Sweet, Thomas, and Junker for modeling interventions and other covariate effects on ensembles of social networks, such as what would be found in randomized controlled trials in education research. In this article, we develop calculations for the power to detect an intervention…
Nonlinear stability and ergodicity of ensemble based Kalman filters
Tong, Xin T.; Majda, Andrew J.; Kelly, David
2016-02-01
The ensemble Kalman filter (EnKF) and ensemble square root filter (ESRF) are data assimilation methods used to combine high dimensional, nonlinear dynamical models with observed data. Despite their widespread usage in climate science and oil reservoir simulation, very little is known about the long-time behavior of these methods and why they are effective when applied with modest ensemble sizes in large dimensional turbulent dynamical systems. By following the basic principles of energy dissipation and controllability of filters, this paper establishes a simple, systematic and rigorous framework for the nonlinear analysis of EnKF and ESRF with arbitrary ensemble size, focusing on the dynamical properties of boundedness and geometric ergodicity. The time uniform boundedness guarantees that the filter estimate will not diverge to machine infinity in finite time, which is a potential threat for EnKF and ESQF known as the catastrophic filter divergence. Geometric ergodicity ensures in addition that the filter has a unique invariant measure and that initialization errors will dissipate exponentially in time. We establish these results by introducing a natural notion of observable energy dissipation. The time uniform bound is achieved through a simple Lyapunov function argument, this result applies to systems with complete observations and strong kinetic energy dissipation, but also to concrete examples with incomplete observations. With the Lyapunov function argument established, the geometric ergodicity is obtained by verifying the controllability of the filter processes; in particular, such analysis for ESQF relies on a careful multivariate perturbation analysis of the covariance eigen-structure.
Boundary conditions in first order gravity: Hamiltonian and Ensemble
Aros, Rodrigo
2005-01-01
In this work two different boundary conditions for first order gravity, corresponding to a null and a negative cosmological constant respectively, are studied. Both boundary conditions allows to obtain the standard black hole thermodynamics. Furthermore both boundary conditions define a canonical ensemble. Additionally the quasilocal energy definition is obtained for the null cosmological constant case.
Entropy Maximization in the Force Network Ensemble for Granular Solids
Tighe, B.P.; Van Eerd, A.R.T.; Vlugt, T.J.H.
2008-01-01
A long-standing issue in the area of granular media is the tail of the force distribution, in particular, whether this is exponential, Gaussian, or even some other form. Here we resolve the issue for the case of the force network ensemble in two dimensions. We demonstrate that conservation of the to
ENSEMBLE methods to reconcile disparate national long range dispersion forecasting
International Nuclear Information System (INIS)
ENSEMBLE is a web-based decision support system for real-time exchange and evaluation of national long-range dispersion forecasts of nuclear releases with cross-boundary consequences. The system is developed with the purpose to reconcile among disparate national forecasts for long-range dispersion. ENSEMBLE addresses the problem of achieving a common coherent strategy across European national emergency management when national long-range dispersion forecasts differ from one another during an accidental atmospheric release of radioactive material. A series of new decision-making 'ENSEMBLE' procedures and Web-based software evaluation and exchange tools have been created for real-time reconciliation and harmonisation of real-time dispersion forecasts from meteorological and emergency centres across Europe during an accident. The new ENSEMBLE software tools is available to participating national emergency and meteorological forecasting centres, which may choose to integrate them directly into operational emergency information systems, or possibly use them as a basis for future system development. (au)
A benchmark for reaction coordinates in the transition path ensemble.
Li, Wenjin; Ma, Ao
2016-04-01
The molecular mechanism of a reaction is embedded in its transition path ensemble, the complete collection of reactive trajectories. Utilizing the information in the transition path ensemble alone, we developed a novel metric, which we termed the emergent potential energy, for distinguishing reaction coordinates from the bath modes. The emergent potential energy can be understood as the average energy cost for making a displacement of a coordinate in the transition path ensemble. Where displacing a bath mode invokes essentially no cost, it costs significantly to move the reaction coordinate. Based on some general assumptions of the behaviors of reaction and bath coordinates in the transition path ensemble, we proved theoretically with statistical mechanics that the emergent potential energy could serve as a benchmark of reaction coordinates and demonstrated its effectiveness by applying it to a prototypical system of biomolecular dynamics. Using the emergent potential energy as guidance, we developed a committor-free and intuition-independent method for identifying reaction coordinates in complex systems. We expect this method to be applicable to a wide range of reaction processes in complex biomolecular systems.
Characterizing RNA ensembles from NMR data with kinematic models
DEFF Research Database (Denmark)
Fonseca, Rasmus; Pachov, Dimitar V.; Bernauer, Julie;
2014-01-01
the conformational landscapes of 3D RNA encoded by NMR proton chemical shifts. KGSrna resolves motionally averaged NMR data into structural contributions; when coupled with residual dipolar coupling data, a KGSrna ensemble revealed a previously uncharacterized transient excited state of the HIV-1 trans...
Measures of trajectory ensemble disparity in nonequilibrium statistical dynamics
Crooks, Gavin E.; Sivak, David A.
2011-06-01
Many interesting divergence measures between conjugate ensembles of nonequilibrium trajectories can be experimentally determined from the work distribution of the process. Herein, we review the statistical and physical significance of several of these measures, in particular the relative entropy (dissipation), Jeffreys divergence (hysteresis), Jensen-Shannon divergence (time-asymmetry), Chernoff divergence (work cumulant generating function), and Rényi divergence.
Measures of trajectory ensemble disparity in nonequilibrium statistical dynamics
Energy Technology Data Exchange (ETDEWEB)
Crooks, Gavin; Sivak, David
2011-06-03
Many interesting divergence measures between conjugate ensembles of nonequilibrium trajectories can be experimentally determined from the work distribution of the process. Herein, we review the statistical and physical significance of several of these measures, in particular the relative entropy (dissipation), Jeffreys divergence (hysteresis), Jensen-Shannon divergence (time-asymmetry), Chernoff divergence (work cumulant generating function), and Renyi divergence.
Ensemble approach for hydrological forecasting in ungauged catchments
Randrianasolo, Annie; Ramos, Maria-Helena; Andreassian, Vazken
2013-04-01
This study focuses on the application of ensemble approaches to forecast flows in ungauged catchments. The aim is to study the best strategy to search for information in gauged "donor" basins and to transfer it to the ungauged site. We investigate what information is needed to set up a rainfall-runoff model and to perform forecast updating in real time. These two components of a flood forecasting system are thus decoupled in our approach. The methodology adopted integrates the scenarios of regional transfer of information and the scenarios of ensemble weather forecasting together in a forecasting system. The approach of ensemble forecasting is thus generalised to the particular case of hydrological forecasting in ungauged basins. The study is based on 211 catchments in France and on an archive of about 4.5 years of ensemble forecasts of rainfall, which are used for hydrological modelling on a daily time step. Flow forecasts are evaluated with special attention paid to the attributes of reliability and accuracy of the forecasts. The results show that forecast reliability in ungauged sites can be improved by using several sets of parameters from neighbour catchments, while forecast accuracy is improved with the transfer of updating information from gauged neighbour catchments.
Path planning in uncertain flow fields using ensemble method
Wang, Tong; Le Maître, Olivier P.; Hoteit, Ibrahim; Knio, Omar M.
2016-08-01
An ensemble-based approach is developed to conduct optimal path planning in unsteady ocean currents under uncertainty. We focus our attention on two-dimensional steady and unsteady uncertain flows, and adopt a sampling methodology that is well suited to operational forecasts, where an ensemble of deterministic predictions is used to model and quantify uncertainty. In an operational setting, much about dynamics, topography, and forcing of the ocean environment is uncertain. To address this uncertainty, the flow field is parametrized using a finite number of independent canonical random variables with known densities, and the ensemble is generated by sampling these variables. For each of the resulting realizations of the uncertain current field, we predict the path that minimizes the travel time by solving a boundary value problem (BVP), based on the Pontryagin maximum principle. A family of backward-in-time trajectories starting at the end position is used to generate suitable initial values for the BVP solver. This allows us to examine and analyze the performance of the sampling strategy and to develop insight into extensions dealing with general circulation ocean models. In particular, the ensemble method enables us to perform a statistical analysis of travel times and consequently develop a path planning approach that accounts for these statistics. The proposed methodology is tested for a number of scenarios. We first validate our algorithms by reproducing simple canonical solutions, and then demonstrate our approach in more complex flow fields, including idealized, steady and unsteady double-gyre flows.
Accounting for three sources of uncertainty in ensemble hydrological forecasting
Directory of Open Access Journals (Sweden)
A. Thiboult
2015-07-01
Full Text Available Seeking for more accuracy and reliability, the hydrometeorological community has developed several tools to decipher the different sources of uncertainty in relevant modeling processes. Among them, the Ensemble Kalman Filter, multimodel approaches and meteorological ensemble forecasting proved to have the capability to improve upon deterministic hydrological forecast. This study aims at untangling the sources of uncertainty by studying the combination of these tools and assessing their contribution to the overall forecast quality. Each of these components is able to capture a certain aspect of the total uncertainty and improve the forecast at different stage in the forecasting process by using different means. Their combination outperforms any of the tool used solely. The EnKF is shown to contribute largely to the ensemble accuracy and dispersion, indicating that the initial condition uncertainty is dominant. However, it fails to maintain the required dispersion throughout the entire forecast horizon and needs to be supported by a multimodel approach to take into account structural uncertainty. Moreover, the multimodel approach contributes to improve the general forecasting performance and prevents from falling into the model selection pitfall since models differ strongly in their ability. Finally, the use of probabilistic meteorological forcing was found to contribute mostly to long lead time reliability. Particular attention needs to be paid to the combination of the tools, especially in the Ensemble Kalman Filter tuning to avoid overlapping in error deciphering.
Stokes identification in an atomic ensemble using a filtering system
Institute of Scientific and Technical Information of China (English)
Luo Xiao-Ming; Ning Bo; Chen Li-Qing; Zhou Yue; Zhong Zhi-Ping; Jiang Shuo
2009-01-01
Polarization filtering and atomic cell filtering are applied in the identification of Stokes signals in an atomic ensemble, and reduce the noise to a level of 10~(-5) and 10~(-4) respectively. Good Stokes signals are then obtained. In this article the two filtering systems and the final Stokes output are presented, and the optimization of the polarization filtering system is highlighted.
The Wilson loop in the Gaussian Unitary Ensemble
Gurau, Razvan
2016-01-01
Using the supersymmetric formalism we compute exactly at finite $N$ the expectation of the Wilson loop in the Gaussian Unitary Ensemble and derive an exact formula for the spectral density at finite $N$. We obtain the same result by a second method relying on enumerative combinatorics and show that it leads to a novel proof of the Harer-Zagier series formula.
Ligand and ensemble effects in adsorption on alloy surfaces
DEFF Research Database (Denmark)
Liu, Ping; Nørskov, Jens Kehlet
2001-01-01
Density functional theory is used to study the adsorption of carbon monoxide, oxygen and nitrogen on various Au/Pd(111) bimetallic alloy surfaces. By varying the Au content in the surface we are able to make a clear separation into geometrical (or ensemble) effects and electronic (or ligand......) effects determining the adsorption properties....
Conceptualizing Conceptual Teaching: Practical Strategies for Large Instrumental Ensembles
Tan, Leonard
2016-01-01
Half a century ago, calls had already been made for instrumental ensemble directors to move beyond performance to include the teaching of musical concepts in the rehearsal hall. Relatively recent research, however, suggests that conceptual teaching remains relatively infrequent during rehearsals. Given the importance of teaching for long-term…
Ensemble: an Architecture for Mission-Operations Software
Norris, Jeffrey; Powell, Mark; Fox, Jason; Rabe, Kenneth; Shu, IHsiang; McCurdy, Michael; Vera, Alonso
2008-01-01
Ensemble is the name of an open architecture for, and a methodology for the development of, spacecraft mission operations software. Ensemble is also potentially applicable to the development of non-spacecraft mission-operations- type software. Ensemble capitalizes on the strengths of the open-source Eclipse software and its architecture to address several issues that have arisen repeatedly in the development of mission-operations software: Heretofore, mission-operations application programs have been developed in disparate programming environments and integrated during the final stages of development of missions. The programs have been poorly integrated, and it has been costly to develop, test, and deploy them. Users of each program have been forced to interact with several different graphical user interfaces (GUIs). Also, the strategy typically used in integrating the programs has yielded serial chains of operational software tools of such a nature that during use of a given tool, it has not been possible to gain access to the capabilities afforded by other tools. In contrast, the Ensemble approach offers a low-risk path towards tighter integration of mission-operations software tools.
Cavity quantum electrodynamics with a Rydberg-blocked atomic ensemble
DEFF Research Database (Denmark)
Guerlin, Christine; Brion, Etienne; Esslinger, Tilman;
2010-01-01
The realization of a Jaynes-Cummings model in the optical domain is proposed for an atomic ensemble. The scheme exploits the collective coupling of the atoms to a quantized cavity mode and the nonlinearity introduced by coupling to high-lying Rydberg states. A two-photon transition resonantly cou...
Korean Percussion Ensemble ("Samulnori") in the General Music Classroom
Kang, Sangmi; Yoo, Hyesoo
2016-01-01
This article introduces "samulnori" (Korean percussion ensemble), its cultural background, and instructional methods as parts of a classroom approach to teaching upper-level general music. We introduce five of eight sections from "youngnam nong-ak" (a style of samulnori) as a repertoire for teaching Korean percussion music to…
Ensemble modeling for aromatic production in Escherichia coli.
Directory of Open Access Journals (Sweden)
Matthew L Rizk
Full Text Available Ensemble Modeling (EM is a recently developed method for metabolic modeling, particularly for utilizing the effect of enzyme tuning data on the production of a specific compound to refine the model. This approach is used here to investigate the production of aromatic products in Escherichia coli. Instead of using dynamic metabolite data to fit a model, the EM approach uses phenotypic data (effects of enzyme overexpression or knockouts on the steady state production rate to screen possible models. These data are routinely generated during strain design. An ensemble of models is constructed that all reach the same steady state and are based on the same mechanistic framework at the elementary reaction level. The behavior of the models spans the kinetics allowable by thermodynamics. Then by using existing data from the literature for the overexpression of genes coding for transketolase (Tkt, transaldolase (Tal, and phosphoenolpyruvate synthase (Pps to screen the ensemble, we arrive at a set of models that properly describes the known enzyme overexpression phenotypes. This subset of models becomes more predictive as additional data are used to refine the models. The final ensemble of models demonstrates the characteristic of the cell that Tkt is the first rate controlling step, and correctly predicts that only after Tkt is overexpressed does an increase in Pps increase the production rate of aromatics. This work demonstrates that EM is able to capture the result of enzyme overexpression on aromatic producing bacteria by successfully utilizing routinely generated enzyme tuning data to guide model learning.
Glycosylation site prediction using ensembles of Support Vector Machine classifiers
Directory of Open Access Journals (Sweden)
Silvescu Adrian
2007-11-01
Full Text Available Abstract Background Glycosylation is one of the most complex post-translational modifications (PTMs of proteins in eukaryotic cells. Glycosylation plays an important role in biological processes ranging from protein folding and subcellular localization, to ligand recognition and cell-cell interactions. Experimental identification of glycosylation sites is expensive and laborious. Hence, there is significant interest in the development of computational methods for reliable prediction of glycosylation sites from amino acid sequences. Results We explore machine learning methods for training classifiers to predict the amino acid residues that are likely to be glycosylated using information derived from the target amino acid residue and its sequence neighbors. We compare the performance of Support Vector Machine classifiers and ensembles of Support Vector Machine classifiers trained on a dataset of experimentally determined N-linked, O-linked, and C-linked glycosylation sites extracted from O-GlycBase version 6.00, a database of 242 proteins from several different species. The results of our experiments show that the ensembles of Support Vector Machine classifiers outperform single Support Vector Machine classifiers on the problem of predicting glycosylation sites in terms of a range of standard measures for comparing the performance of classifiers. The resulting methods have been implemented in EnsembleGly, a web server for glycosylation site prediction. Conclusion Ensembles of Support Vector Machine classifiers offer an accurate and reliable approach to automated identification of putative glycosylation sites in glycoprotein sequences.
Enriching the Ensemble Experience for Students with Visual Impairments
Siligo, Wayne Roy
2005-01-01
This article will give music educators some practical tools and information for helping students with visual impairments enjoy the ensemble experience. The author has used these tools as music director at the California School for the Blind (CSB) and as a musician who is visually impaired. All observations and techniques mentioned here come out of…
Directory of Open Access Journals (Sweden)
Jean-Pierre Hassoun
2010-12-01
Full Text Available L’article repose sur une enquête ethnographique conduite en 2008-2009 à Manhattan auprès de huit entrepreneurs devenus Chef et/ou managers de restaurant après avoir immigré à New York. Aucun d’entre eux n’a été formé dans une institution culinaire et tous proposent des cuisines de régions du monde (Afrique, Afrique du Nord encore absentes, ou peu présentes à New York. A partir de deux études de cas plus détaillées, l’auteur s’interroge sur les stratégies marchandes autour de cette altérité et les limites du cosmopolitisme propre au « globalisme ». La trajectoire du restaurateur se transforme en héritage par le biais d’un ego-récit qui s’utilise comme une ressource commerciale. Les restaurateurs intériorisent les désirs des clients. Plus que la recherche de goûts inconnus ou d’une altérité radicale imaginée comme authentique, ceux-ci veulent avant tout identifier les ingrédients ingérés, avoir une idée de leur provenance, et respecter un ensemble (instable de normes nutritionnelles subsumé aujourd’hui à Manhattan par la catégorie indigène healthy. Les restaurateurs anticipent ces désirs en opérant sur les plats un travail de retrait, de séparation et de substitution des ingrédients. L’exotisme s’est mis au régime.This paper is based on ethnographic fieldwork (november 2008-january 2009 in Manhattan with eight entrepreneurs who became Chef and/or restaurant manager after they immigrated in New York. Not any one has an academic culinary background and they all propose food from regions (Africa, and North Africa which are not yet offered (or not much offered in the city. The author stresses on two cases studies to question informal market strategies, cosmopolitanism and globalism limits. Restaurant owner’s trajectory – a narrative which becomes a heritage - is used as a market resource. Restaurants internalize and anticipate customers’ desires; In fact town people doesn
Quantum repeater with Rydberg-blocked atomic ensembles in fiber-coupled cavities
DEFF Research Database (Denmark)
Brion, Etienne; Carlier, F.; Akulin, M.;
2012-01-01
We propose and analyze a quantum repeater architecture in which Rydberg-blocked atomic ensembles inside optical cavities are linked by optical fibers. Entanglement generation, swapping, and purification are achieved through collective laser manipulations of the ensembles and photon transmission...
A genetic ensemble approach for gene-gene interaction identification
Directory of Open Access Journals (Sweden)
Ho Joshua WK
2010-10-01
Full Text Available Abstract Background It has now become clear that gene-gene interactions and gene-environment interactions are ubiquitous and fundamental mechanisms for the development of complex diseases. Though a considerable effort has been put into developing statistical models and algorithmic strategies for identifying such interactions, the accurate identification of those genetic interactions has been proven to be very challenging. Methods In this paper, we propose a new approach for identifying such gene-gene and gene-environment interactions underlying complex diseases. This is a hybrid algorithm and it combines genetic algorithm (GA and an ensemble of classifiers (called genetic ensemble. Using this approach, the original problem of SNP interaction identification is converted into a data mining problem of combinatorial feature selection. By collecting various single nucleotide polymorphisms (SNP subsets as well as environmental factors generated in multiple GA runs, patterns of gene-gene and gene-environment interactions can be extracted using a simple combinatorial ranking method. Also considered in this study is the idea of combining identification results obtained from multiple algorithms. A novel formula based on pairwise double fault is designed to quantify the degree of complementarity. Conclusions Our simulation study demonstrates that the proposed genetic ensemble algorithm has comparable identification power to Multifactor Dimensionality Reduction (MDR and is slightly better than Polymorphism Interaction Analysis (PIA, which are the two most popular methods for gene-gene interaction identification. More importantly, the identification results generated by using our genetic ensemble algorithm are highly complementary to those obtained by PIA and MDR. Experimental results from our simulation studies and real world data application also confirm the effectiveness of the proposed genetic ensemble algorithm, as well as the potential benefits of
Incorporating RNA-seq data into the zebrafish Ensembl genebuild.
Collins, John E; White, Simon; Searle, Stephen M J; Stemple, Derek L
2012-10-01
Ensembl gene annotation provides a comprehensive catalog of transcripts aligned to the reference sequence. It relies on publicly available species-specific and orthologous transcripts plus their inferred protein sequence. The accuracy of gene models is improved by increasing the species-specific component that can be cost-effectively achieved using RNA-seq. Two zebrafish gene annotations are presented in Ensembl version 62 built on the Zv9 reference sequence. Firstly, RNA-seq data from five tissues and seven developmental stages were assembled into 25,748 gene models. A 3'-end capture and sequencing protocol was developed to predict the 3' ends of transcripts, and 46.1% of the original models were subsequently refined. Secondly, a standard Ensembl genebuild, incorporating carefully filtered elements from the RNA-seq-only build, followed by a merge with the manually curated VEGA database, produced a comprehensive annotation of 26,152 genes represented by 51,569 transcripts. The RNA-seq-only and the Ensembl/VEGA genebuilds contribute contrasting elements to the final genebuild. The RNA-seq genebuild was used to adjust intron/exon boundaries of orthologous defined models, confirm their expression, and improve 3' untranslated regions. Importantly, the inferred protein alignments within the Ensembl genebuild conferred proof of model contiguity for the RNA-seq models. The zebrafish gene annotation has been enhanced by the incorporation of RNA-seq data and the pipeline will be used for other organisms. Organisms with little species-specific cDNA data will generally benefit the most. PMID:22798491
A variational ensemble scheme for noisy image data assimilation
Yang, Yin; Robinson, Cordelia; Heitz, Dominique; Mémin, Etienne
2014-05-01
Data assimilation techniques aim at recovering a system state variables trajectory denoted as X, along time from partially observed noisy measurements of the system denoted as Y. These procedures, which couple dynamics and noisy measurements of the system, fulfill indeed a twofold objective. On one hand, they provide a denoising - or reconstruction - procedure of the data through a given model framework and on the other hand, they provide estimation procedures for unknown parameters of the dynamics. A standard variational data assimilation problem can be formulated as the minimization of the following objective function with respect to the initial discrepancy, η, from the background initial guess: δ« J(η(x)) = 1∥Xb (x) - X (t ,x)∥2 + 1 tf∥H(X (t,x ))- Y (t,x)∥2dt. 2 0 0 B 2 t0 R (1) where the observation operator H links the state variable and the measurements. The cost function can be interpreted as the log likelihood function associated to the a posteriori distribution of the state given the past history of measurements and the background. In this work, we aim at studying ensemble based optimal control strategies for data assimilation. Such formulation nicely combines the ingredients of ensemble Kalman filters and variational data assimilation (4DVar). It is also formulated as the minimization of the objective function (1), but similarly to ensemble filter, it introduces in its objective function an empirical ensemble-based background-error covariance defined as: B ≡ )(Xb - )T>. (2) Thus, it works in an off-line smoothing mode rather than on the fly like sequential filters. Such resulting ensemble variational data assimilation technique corresponds to a relatively new family of methods [1,2,3]. It presents two main advantages: first, it does not require anymore to construct the adjoint of the dynamics tangent linear operator, which is a considerable advantage with respect to the method's implementation, and second, it enables the handling of a flow
The Oral Tradition in the Sankofa Drum and Dance Ensemble: Student Perceptions
Hess, Juliet
2009-01-01
The Sankofa Drum and Dance Ensemble is a Ghanaian drum and dance ensemble that focusses on music in the Ewe tradition. It is based in an elementary school in the Greater Toronto Area and consists of students in Grade 4 through Grade 8. Students in the ensemble study Ghanaian traditional Ewe drumming and dancing in the oral tradition. Nine students…
Kramer, John R.
2012-01-01
Classical guitar ensembles are increasing in the United States as popular alternatives to band, choir, and orchestra. Classical guitar ensembles are offered at many middle and high schools as fine arts electives as one of the only options for classical guitarists to participate in ensembles. The purpose of this study was to explore the development…
Reconstruction of the coupling architecture in an ensemble of coupled time-delay systems
Sysoev, I. V.; Ponomarenko, V. I.; Prokhorov, M. D.
2012-08-01
A method for reconstructing the coupling architecture and values in an ensemble of time-delay interacting systems with an arbitrary number of couplings between ensemble elements is proposed. This method is based on reconstruction of the model equations of ensemble elements and diagnostics of the coupling significance by successive trial exclusion or adding coupling coefficients to the model.
Generating precipitation ensembles for flood alert and risk management
Caseri, Angelica; Javelle, Pierre; Ramos, Maria-Helena; Leblois, Etienne
2015-04-01
Floods represent one of the major natural disasters that are often responsible for fatalities and economic losses. Flood warning systems are needed to anticipate the arrival of severe events and mitigate their impacts. Flood alerts are particularly important for risk management and response in the nowcasting of flash floods. In this case, precipitation fields observed in real time play a crucial role and observational uncertainties must be taken into account. In this study, we investigate the potential of a framework which combines a geostatistical conditional simulation method that considers information from precipitation radar and rain gauges, and a distributed rainfall-runoff model to generate an ensemble of precipitation fields and produce probabilistic flood alert maps. We adapted the simulation method proposed by Leblois and Creutin (2013), based on the Turning Band Method (TBM) and a conditional simulation approach, to consider the temporal and spatial characteristics of radar data and rain gauge measurements altogether and generate precipitation ensembles. The AIGA system developed by Irstea and Météo-France for predicting flash floods in the French Mediterranean region (Javelle et al., 2014) was used to transform the generated precipitation ensembles into ensembles of discharge at the outlet of the studied catchments. Finally, discharge ensembles were translated into maps providing information on the probability of exceeding a given flood threshold. A total of 19 events that occurred between 2009 and 2013 in the Var region (southeastern France), a region prone to flash floods, was used to illustrate the approach. Results show that the proposed method is able to simulate an ensemble of realistic precipitation fields and capture peak flows of flash floods. This was shown to be particularly useful at ungauged catchments, where uncertainties on the evaluation of flood peaks are high. The results obtained also show that the approach developed can be used to
Active Diverse Learning Neural Network Ensemble Approach for Power Transformer Fault Diagnosis
Directory of Open Access Journals (Sweden)
Yu Xu
2010-10-01
Full Text Available An ensemble learning algorithm was proposed in this paper by analyzing the error function of neural network ensembles, by which, individual neural networks were actively guided to learn diversity. By decomposing the ensemble error function, error correlation terms were included in the learning criterion function of individual networks. And all the individual networks in the ensemble were leaded to learn diversity through cooperative training. The method was applied in Dissolved Gas Analysis based fault diagnosis of power transformer. Experiment results show that, the algorithm has higher accuracy than IEC method and BP network. In addition, the performance is more stable than conventional ensemble method, i.e., Bagging and Boosting.
Evaluating reliability and resolution of ensemble forecasts using information theory
Weijs, Steven; van de Giesen, Nick
2010-05-01
Ensemble forecasts are increasingly popular for the communication of uncertainty towards the public and decision makers. Ideally, an ensemble forecast reflects both the uncertainty and the information in a forecast, which means that the spread in the ensemble should accurately represent the true uncertainty. For ensembles to be useful, they should be probabilistic, as probability is the language to precisely describe an incomplete state of knowledge, that is typical for forecasts. Information theory provides the ideal tools to deal with uncertainty and information in forecasts. Essential to the use and development of models and forecasts are ways to evaluate their quality. Without a proper definition of what is good, it is impossible to improve forecasts. In contrast to forecast value, which is user dependent, forecast quality, which is defined as the correspondence between forecasts and observations, can be objectively defined, given the question that is asked. The evaluation of forecast quality is known as forecast verification. Numerous techniques for forecast verification have been developed over the past decades. The Brier score (BS) and the derived Ranked Probability Score (RPS) are among the most widely used scores for measuring forecast quality. Both of these scores can be split into three additive components: uncertainty, reliability and resolution. While the first component, uncertainty, just depends on the inherent variability in the forecasted event, the latter two measure different aspects of the quality of forecasts themselves. Resolution measures the difference between the conditional probabilities and the marginal probabilities of occurrence. The third component, reliability, measures the conditional bias in the probability estimates, hence unreliability would be a better name. In this work, we argue that information theory should be adopted as the correct framework for measuring quality of probabilistic ensemble forecasts. We use the information
Ensemble-Based Assimilation of Aerosol Observations in GEOS-5
Buchard, V.; Da Silva, A.
2016-01-01
MERRA-2 is the latest Aerosol Reanalysis produced at NASA's Global Modeling Assimilation Office (GMAO) from 1979 to present. This reanalysis is based on a version of the GEOS-5 model radiatively coupled to GOCART aerosols and includes assimilation of bias corrected Aerosol Optical Depth (AOD) from AVHRR over ocean, MODIS sensors on both Terra and Aqua satellites, MISR over bright surfaces and AERONET data. In order to assimilate lidar profiles of aerosols, we are updating the aerosol component of our assimilation system to an Ensemble Kalman Filter (EnKF) type of scheme using ensembles generated routinely by the meteorological assimilation. Following the work performed with the first NASA's aerosol reanalysis (MERRAero), we first validate the vertical structure of MERRA-2 aerosol assimilated fields using CALIOP data over regions of particular interest during 2008.
Weighted ensemble transform Kalman filter for image assimilation
Directory of Open Access Journals (Sweden)
Sebastien Beyou
2013-01-01
Full Text Available This study proposes an extension of the Weighted Ensemble Kalman filter (WEnKF proposed by Papadakis et al. (2010 for the assimilation of image observations. The main focus of this study is on a novel formulation of the Weighted filter with the Ensemble Transform Kalman filter (WETKF, incorporating directly as a measurement model a non-linear image reconstruction criterion. This technique has been compared to the original WEnKF on numerical and real world data of 2-D turbulence observed through the transport of a passive scalar. In particular, it has been applied for the reconstruction of oceanic surface current vorticity fields from sea surface temperature (SST satellite data. This latter technique enables a consistent recovery along time of oceanic surface currents and vorticity maps in presence of large missing data areas and strong noise.
Ensemble polarimetric SAR image classification based on contextual sparse representation
Zhang, Lamei; Wang, Xiao; Zou, Bin; Qiao, Zhijun
2016-05-01
Polarimetric SAR image interpretation has become one of the most interesting topics, in which the construction of the reasonable and effective technique of image classification is of key importance. Sparse representation represents the data using the most succinct sparse atoms of the over-complete dictionary and the advantages of sparse representation also have been confirmed in the field of PolSAR classification. However, it is not perfect, like the ordinary classifier, at different aspects. So ensemble learning is introduced to improve the issue, which makes a plurality of different learners training and obtained the integrated results by combining the individual learner to get more accurate and ideal learning results. Therefore, this paper presents a polarimetric SAR image classification method based on the ensemble learning of sparse representation to achieve the optimal classification.
ENSEMBLE DESIGN OF MASQUERADER DETECTION SYSTEMS FOR INFORMATION SECURITY
Directory of Open Access Journals (Sweden)
T. Subbulakshmi
2011-01-01
Full Text Available Masqueraders are a category of intruders who impersonate other people on a computer system and use this entry point to use the information stored in the systems or throw other attacks into the network. This paper focuses on Ensemble Design of a Masquerader Detection System using Decision trees and Support Vector Machines for classification with two kernel functions linear and linear BSpline. The key idea is to find out specific patterns of command sequence that tells about user behaviour on a system, and use them to build classifiers that can perfectly recognize anomalous and normal behaviour. Real time truncated command line data set collected from a debian Linux server is used for performance comparison of the developed classifiers with the standard truncated command line data set of Schonlau[4]. The results show that Ensemble Design of Masquerader Detection Systems is much faster than individual Decision trees or Support Vector Machines.
Hippocampal ensemble dynamics timestamp events in long-term memory.
Rubin, Alon; Geva, Nitzan; Sheintuch, Liron; Ziv, Yaniv
2015-01-01
The capacity to remember temporal relationships between different events is essential to episodic memory, but little is currently known about its underlying mechanisms. We performed time-lapse imaging of thousands of neurons over weeks in the hippocampal CA1 of mice as they repeatedly visited two distinct environments. Longitudinal analysis exposed ongoing environment-independent evolution of episodic representations, despite stable place field locations and constant remapping between the two environments. These dynamics time-stamped experienced events via neuronal ensembles that had cellular composition and activity patterns unique to specific points in time. Temporally close episodes shared a common timestamp regardless of the spatial context in which they occurred. Temporally remote episodes had distinct timestamps, even if they occurred within the same spatial context. Our results suggest that days-scale hippocampal ensemble dynamics could support the formation of a mental timeline in which experienced events could be mnemonically associated or dissociated based on their temporal distance. PMID:26682652
An Ensemble of Neural Networks for Stock Trading Decision Making
Chang, Pei-Chann; Liu, Chen-Hao; Fan, Chin-Yuan; Lin, Jun-Lin; Lai, Chih-Ming
Stock turning signals detection are very interesting subject arising in numerous financial and economic planning problems. In this paper, Ensemble Neural Network system with Intelligent Piecewise Linear Representation for stock turning points detection is presented. The Intelligent piecewise linear representation method is able to generate numerous stocks turning signals from the historic data base, then Ensemble Neural Network system will be applied to train the pattern and retrieve similar stock price patterns from historic data for training. These turning signals represent short-term and long-term trading signals for selling or buying stocks from the market which are applied to forecast the future turning points from the set of test data. Experimental results demonstrate that the hybrid system can make a significant and constant amount of profit when compared with other approaches using stock data available in the market.
Common Axioms for Inferring Classical Ensemble Dynamics and Quantum Theory
Parwani, R R
2005-01-01
Within a hamiltonian framework, the same set of physically motivated axioms is used to construct both the classical ensemble Hamilton-Jacobi equation and Schrodingers equation. Crucial roles are played by the assumptions of universality and simplicity (Occam's Razor) which restrict the number and type of of arbitrary constants that appear in the hamiltonian. In this approach, non-relativistic quantum theory is seen as the unique single parameter extension of the classical ensemble dynamics. The method is contrasted with other related constructions in the literature. Possible generalisation to the relativistic case, and some consequences of relaxing the axioms, are also discussed: for example, simple extensions of the linear Schrodinger equation lead to higher-derivative nonlinear corrections that are possibly related to gravity.
Novel algorithm for constructing support vector machine regression ensemble
Institute of Scientific and Technical Information of China (English)
Li Bo; Li Xinjun; Zhao Zhiyan
2006-01-01
A novel algorithm for constructing support vector machine regression ensemble is proposed. As to regression prediction, support vector machine regression(SVMR) ensemble is proposed by resampling from given training data sets repeatedly and aggregating several independent SVMRs, each of which is trained to use a replicated training set. After training, several independently trained SVMRs need to be aggregated in an appropriate combination manner. Generally, the linear weighting is usually used like expert weighting score in Boosting Regression and it is without optimization capacity. Three combination techniques are proposed, including simple arithmetic mean,linear least square error weighting and nonlinear hierarchical combining that uses another upper-layer SVMR to combine several lower-layer SVMRs. Finally, simulation experiments demonstrate the accuracy and validity of the presented algorithm.
Generalized Ensemble Sampling of Enzyme Reaction Free Energy Pathways
Wu, Dongsheng; Fajer, Mikolai I.; Cao, Liaoran; Cheng, Xiaolin; Yang, Wei
2016-01-01
Free energy path sampling plays an essential role in computational understanding of chemical reactions, particularly those occurring in enzymatic environments. Among a variety of molecular dynamics simulation approaches, the generalized ensemble sampling strategy is uniquely attractive for the fact that it not only can enhance the sampling of rare chemical events but also can naturally ensure consistent exploration of environmental degrees of freedom. In this review, we plan to provide a tutorial-like tour on an emerging topic: generalized ensemble sampling of enzyme reaction free energy path. The discussion is largely focused on our own studies, particularly ones based on the metadynamics free energy sampling method and the on-the-path random walk path sampling method. We hope that this mini presentation will provide interested practitioners some meaningful guidance for future algorithm formulation and application study. PMID:27498634
On an average over the Gaussian Unitary Ensemble
Mezzadri, F
2009-01-01
We study the asymptotic limit for large matrix dimension N of the partition function of the unitary ensemble with weight exp(-z^2/2x^2 + t/x - x^2/2). We compute the leading order term of the partition function and of the coefficients of its Taylor expansion. Our results are valid in the range N^(-1/2) < z < N^(1/4). Such partition function contains all the information on a new statistics of the eigenvalues of matrices in the Gaussian Unitary Ensemble (GUE) that was introduced by Berry and Shukla (J. Phys. A: Math. Theor., Vol. 41 (2008), 385202, arXiv:0807.3474). It can also be interpreted as the moment generating function of a singular linear statistics.
Ensembles of Protein Molecules as Statistical Analog Computers
Eliashberg, V
2003-01-01
A class of analog computers built from large numbers of microscopic probabilistic machines is discussed. It is postulated that such computers are implemented in biological systems as ensembles of protein molecules. The formalism is based on an abstract computational model referred to as Protein Molecule Machine (PMM). A PMM is a continuous-time first-order Markov system with real input and output vectors, a finite set of discrete states, and the input-dependent conditional probability densities of state transitions. The output of a PMM is a function of its input and state. The components of input vector, called generalized potentials, can be interpreted as membrane potential, and concentrations of neurotransmitters. The components of output vector, called generalized currents, can represent ion currents, and the flows of second messengers. An Ensemble of PMMs (EPMM) is a set of independent identical PMMs with the same input vector, and the output vector equal to the sum of output vectors of individual PMMs. T...
Ensemble dispersion forecasting - Part 1. Concept, approach and indicators
DEFF Research Database (Denmark)
Galmarini, S.; Bianconi, R.; Klug, W.;
2004-01-01
The paper presents an approach to the treatment and analysis of long-range transport and dispersion model forecasts. Long-range is intended here as the space scale of the order of few thousands of kilometers known also as continental scale. The method is called multi-model ensemble dispersion...... of harmful volatile substances, in particular radionuclides to the atmosphere. The ensemble dispersion approach and indicators provide a way to reduce several model results to few concise representations that include an estimate of the models' agreement in predicting a specific scenario. The parameters...... proposed are particularly suited for long-range transport and dispersion models although they can also be applied to short-range dispersion and weather fields. (C) 2004 Elsevier Ltd. All rights reserved....
Current path in light emitting diodes based on nanowire ensembles
International Nuclear Information System (INIS)
Light emitting diodes (LEDs) have been fabricated using ensembles of free-standing (In, Ga)N/GaN nanowires (NWs) grown on Si substrates in the self-induced growth mode by molecular beam epitaxy. Electron-beam-induced current analysis, cathodoluminescence as well as biased μ-photoluminescence spectroscopy, transmission electron microscopy, and electrical measurements indicate that the electroluminescence of such LEDs is governed by the differences in the individual current densities of the single-NW LEDs operated in parallel, i.e. by the inhomogeneity of the current path in the ensemble LED. In addition, the optoelectronic characterization leads to the conclusion that these NWs exhibit N-polarity and that the (In, Ga)N quantum well states in the NWs are subject to a non-vanishing quantum confined Stark effect. (paper)
Two-point Correlator Fits on HISQ Ensembles
Bazavov, A; Bouchard, C; DeTar, C; Du, D; El-Khadra, A X; Foley, J; Freeland, E D; Gamiz, E; Gottlieb, Steven; Heller, U M; Hetrick, J E; Kim, J; Kronfeld, A S; Laiho, J; Levkova, L; Lightman, M; Mackenzie, P B; Neil, E T; Oktay, M; Simone, J N; Sugar, R L; Toussaint, D; Van de Water, R S; Zhou, R
2012-01-01
We present our methods to fit the two point correlators for light, strange, and charmed pseudoscalar meson physics with the highly improved staggered quark (HISQ) action. We make use of the least-squares fit including the full covariance matrix of the correlators and including Gaussian constraints on some parameters. We fit the correlators on a variety of the HISQ ensembles. The lattice spacing ranges from 0.15 fm down to 0.06 fm. The light sea quark mass ranges from 0.2 times the strange quark mass down to the physical light quark mass. The HISQ ensembles also include lattices with different volumes and with unphysical values of the strange quark mass. We use the results from this work to obtain our preliminary results of $f_D$, $f_{D_s}$, $f_{D_s}/f_{D}$, and ratios of quark masses presented in another talk [1].
Control of inhomogeneous atomic ensembles of hyperfine qudits
Mischuck, Brian E; Deutsch, Ivan H
2011-01-01
We study the ability to control d-dimensional quantum systems (qudits) encoded in the hyperfine spin of alkali-metal atoms through the application of radio- and microwave-frequency magnetic fields in the presence of inhomogeneities in amplitude and detuning. Such a capability is essential to the design of robust pulses that mitigate the effects of experimental uncertainty and also for application to tomographic addressing of particular members of an extended ensemble. We study the problem of preparing an arbitrary state in the Hilbert space from an initial fiducial state. We prove that inhomogeneous control of qudit ensembles is possible based on a semi-analytic protocol that synthesizes the target through a sequence of alternating rf and microwave-driven SU(2) rotations in overlapping irreducible subspaces. Several examples of robust control are studied, and the semi-analytic protocol is compared to a brute force, full numerical search. For small inhomogeneities, < 1%, both approaches achieve average fide...
Ensemble meteorological reconstruction using circulation analogues of 1781–1785
Directory of Open Access Journals (Sweden)
P. Yiou
2013-09-01
Full Text Available This paper uses a method of atmospheric flow analogues to reconstruct an ensemble of atmospheric variables (namely sea-level pressure, surface temperature and wind speed between 1781 and 1785. The properties of this ensemble are investigated and tested against observations of temperature. The goal of the paper is to assess whether the atmospheric circulation during the Laki volcanic eruption (in 1783 and the subsequent winter were similar to the conditions that prevailed in the winter 2009/2010 and during spring 2010. We find that the three months following the Laki eruption in June 1783 barely have analogues in 2010. The cold winter of 1783/1784 yields circulation analogues in 2009/2010. Our analysis suggests that it is unlikely that the Laki eruption was responsible for the cold winter of 1783/1784, of the relatively short memory of the atmospheric circulation.
Impact of hybrid GSI analysis using ETR ensembles
Indian Academy of Sciences (India)
V S Prasad; C J Johny
2016-04-01
Performance of a hybrid assimilation system combining 3D Var based NGFS (NCMRWF Global ForecastSystem) with ETR (Ensemble Transform with Rescaling) based Global Ensemble Forecast (GEFS) ofresolution T-190L28 is investigated. The experiment is conducted for a period of one week in June 2013and forecast skills over different spatial domains are compared with respect to mean analysis state.Rainfall forecast is verified over Indian region against combined observations of IMD and NCMRWF.Hybrid assimilation produced marginal improvements in overall forecast skill in comparison with 3DVar. Hybrid experiment made significant improvement in wind forecasts in all the regions on verificationagainst mean analysis. The verification of forecasts with radiosonde observations also show improvementin wind forecasts with the hybrid assimilation. On verification against observations, hybrid experimentshows more improvement in temperature and wind forecasts at upper levels. Both hybrid and operational3D Var failed in prediction of extreme rainfall event over Uttarakhand on 17 June, 2013.
Loschmidt echoes in two-body random matrix ensembles
Pižorn, Iztok; Prosen, Tomaž; Seligman, Thomas H.
2007-07-01
Fidelity decay is studied for quantum many-body systems with a dominant independent particle Hamiltonian resulting, e.g., from a mean field theory with a weak two-body interaction. The diagonal terms of the interaction are included in the unperturbed Hamiltonian, while the off-diagonal terms constitute the perturbation that distorts the echo. We give the linear response solution for this problem in a random matrix framework. While the ensemble average shows no surprising behavior, we find that the typical ensemble member as represented by the median displays a very slow fidelity decay known as “freeze.” Numerical calculations confirm this result and show that the ground state even on average displays the freeze. This may contribute to explanation of the “unreasonable” success of mean field theories.
Operational hydrological data assimilation with the recursive ensemble Kalman filter
Directory of Open Access Journals (Sweden)
H. K. McMillan
2013-01-01
Full Text Available This paper describes the design and use of a recursive ensemble Kalman filter (REnKF to assimilate streamflow data in an operational flow forecasting system of seven catchments in New Zealand. The REnKF iteratively updates past and present model states (soil water, aquifer and surface storages, with lags up to the concentration time of the catchment, to improve model initial conditions and hence flow forecasts. We found the REnKF overcame instabilities in the standard EnKF, which were associated with the natural lag time between upstream catchment wetness and flow at the gauging locations. The forecast system performance was correspondingly improved in terms of Nash–Sutcliffe score, persistence index and bounding of the measured flow by the model ensemble. We present descriptions of filter design parameters and explanations and examples of filter behaviour, as an information source for other groups wishing to assimilate discharge observations for operational forecasting.
A Multiresolution Ensemble Kalman Filter using Wavelet Decomposition
Hickmann, Kyle S
2015-01-01
We present a method of using classical wavelet based multiresolution analysis to separate scales in model and observations during data assimilation with the ensemble Kalman filter. In many applications, the underlying physics of a phenomena involve the interaction of features at multiple scales. Blending of observational and model error across scales can result in large forecast inaccuracies since large errors at one scale are interpreted as inexact data at all scales. Our method uses a transformation of the observation operator in order to separate the information from different scales of the observations. This naturally induces a transformation of the observation covariance and we put forward several algorithms to efficiently compute the transformed covariance. Another advantage of our multiresolution ensemble Kalman filter is that scales can be weighted independently to adjust each scale's effect on the forecast. To demonstrate feasibility we present applications to a one dimensional Kuramoto-Sivashinsky (...
Observation Quality Control with a Robust Ensemble Kalman Filter
Roh, Soojin
2013-12-01
Current ensemble-based Kalman filter (EnKF) algorithms are not robust to gross observation errors caused by technical or human errors during the data collection process. In this paper, the authors consider two types of gross observational errors, additive statistical outliers and innovation outliers, and introduce a method to make EnKF robust to gross observation errors. Using both a one-dimensional linear system of dynamics and a 40-variable Lorenz model, the performance of the proposed robust ensemble Kalman filter (REnKF) was tested and it was found that the new approach greatly improves the performance of the filter in the presence of gross observation errors and leads to only a modest loss of accuracy with clean, outlier-free, observations.
Continuous Measurement Quantum State Tomography of Atomic Ensembles
Riofrío, Carlos A
2011-01-01
Quantum state tomography is a fundamental tool in quantum information processing. It allows us to estimate the state of a quantum system by measuring different observables on many identically prepared copies of the system. This is, in general, a very time-consuming task that requires a large number of measurements. There are, however, systems in which the data acquisition can be done more efficiently. In fact, an ensemble of quantum systems can be prepared and manipulated by external fields while being continuously and collectively probed, producing enough information to estimate its state. This provides a basis for continuous measurement quantum tomography. In this protocol, an ensemble of identically prepared systems is collectively probed and controlled in a time-dependent manner to create an informationally complete continuous measurement record. The measurement history is then inverted to determine the state at the initial time. We use two different estimation methods: maximum likelihood and compressed s...
4D-Var or Ensemble Kalman Filter
Kalnay, E.; Li, H.; Yang, S.; Miyoshi, T.; Ballabrera, J.
2007-05-01
We consider the relative advantages of two advanced data assimilation systems, 4D-Var and ensemble Kalman filter (EnKF), currently in use or considered for operational implementation. We explore the impact of tuning assimilation parameters such as the assimilation window length and background error covariance in 4D-Var, the variance inflation in EnKF, and the effect of model errors and reduced observation coverage in both systems. For short assimilation windows EnKF gives more accurate analyses. Both systems reach similar levels of accuracy if long windows are used for 4D-Var, and for infrequent observations, when ensemble perturbations grow nonlinearly and become non-Gaussian, 4D-Var attains lower errors than EnKF. Results obtained with variations of EnKF using operational models and both simulated and real observations are reviewed. A table summarizes the pros and cons of the two methods.
Macrostate equivalence of two general ensembles and specific relative entropies
Mori, Takashi
2016-08-01
The two criteria of ensemble equivalence, i.e., macrostate equivalence and measure equivalence, are investigated for a general pair of states. Macrostate equivalence implies the two ensembles are indistinguishable by the measurement of macroscopic quantities obeying the large-deviation principle, and measure equivalence means that the specific relative entropy of these two states vanishes in the thermodynamic limit. It is shown that measure equivalence implies a macrostate equivalence for a general pair of states by deriving an inequality connecting the large-deviation rate functions to the specific relative Renyi entropies. The result is applicable to both quantum and classical systems. As applications, a sufficient condition for thermalization, the time scale of quantum dynamics of macrovariables, and the second law with strict irreversibility in a quantum quench are discussed.
On Black Hole Entropy Corrections in the Grand Canonical Ensemble
Mahapatra, Subhash; Sarkar, Tapobrata
2011-01-01
We study entropy corrections due to thermal fluctuations for asymptotically AdS black holes in the grand canonical ensemble. To leading order, these can be expressed in terms of the black hole response coefficients via fluctuation moments. We also analyze entropy corrections due to mass and charge fluctuations of R-charged black holes, and our results indicate an universality in the logarithmic corrections to charged AdS black hole entropy in various dimensions.
Using ensemble data assimilation to forecast hydrological flumes
Amour, I.; Mussa, Z.; Bibov, A.; Kauranne, T.
2013-01-01
Data assimilation, commonly used in weather forecasting, means combining a mathematical forecast of a target dynamical system with simultaneous measurements from that system in an optimal fashion. We demonstrate the benefits obtainable from data assimilation with a dam break flume simulation in which a shallow-water equation model is complemented with wave meter measurements. Data assimilation is conducted with a Variational Ensemble Kalman Filter (VEnKF) algorithm. The resu...
Work producing reservoirs: Stochastic thermodynamics with generalized Gibbs ensembles.
Horowitz, Jordan M; Esposito, Massimiliano
2016-08-01
We develop a consistent stochastic thermodynamics for environments composed of thermodynamic reservoirs in an external conservative force field, that is, environments described by the generalized or Gibbs canonical ensemble. We demonstrate that small systems weakly coupled to such reservoirs exchange both heat and work by verifying a local detailed balance relation for the induced stochastic dynamics. Based on this analysis, we help to rationalize the observation that nonthermal reservoirs can increase the efficiency of thermodynamic heat engines. PMID:27627226
Quantum parallelism as a tool for ensemble spin dynamics calculations
Alvarez, Gonzalo A.; Danieli, Ernesto P.; Levstein, Patricia R.; Pastawski, Horacio M.
2007-01-01
Efficient simulations of quantum evolutions of spin-1/2 systems are relevant for ensemble quantum computation as well as in typical NMR experiments. We propose an efficient method to calculate the dynamics of an observable provided that the initial excitation is "local". It resorts a single entangled pure initial state built as a superposition, with random phases, of the pure elements that compose the mixture. This ensures self-averaging of any observable, drastically reducing the calculation...
The Beta-MANOVA Ensemble with General Covariance
Dubbs, Alexander; Edelman, Alan
2013-01-01
We find the joint generalized singular value distribution and largest generalized singular value distributions of the $\\beta$-MANOVA ensemble with positive diagonal covariance, which is general. This has been done for the continuous $\\beta > 0$ case for identity covariance (in eigenvalue form), and by setting the covariance to $I$ in our model we get another version. For the diagonal covariance case, it has only been done for $\\beta = 1,2,4$ cases (real, complex, and quaternion matrix entries...
Poisson ensembles of loops of one-dimensional diffusions
Lupu, Titus
2013-01-01
141 pages We study the analogue of Poisson ensembles of Markov loops ("loop soups") in the setting of one-dimensional diffusions. We give a detailed description of the corresponding intensity measure. The properties of this measure on loops lead us to an extension of Vervaat's bridge-to-excursion transformation that relates the bridges conditioned by their minimum and the excursions of all the diffusion we consider and not just the Brownian motion. Further we describe the Poisson point pro...
Fluctuations in a quasi-stationary shallow cumulus cloud ensemble
Directory of Open Access Journals (Sweden)
M. Sakradzija
2015-01-01
Full Text Available We propose an approach to stochastic parameterisation of shallow cumulus clouds to represent the convective variability and its dependence on the model resolution. To collect information about the individual cloud lifecycles and the cloud ensemble as a whole, we employ a large eddy simulation (LES model and a cloud tracking algorithm, followed by conditional sampling of clouds at the cloud-base level. In the case of a shallow cumulus ensemble, the cloud-base mass flux distribution is bimodal, due to the different shallow cloud subtypes, active and passive clouds. Each distribution mode can be approximated using a Weibull distribution, which is a generalisation of exponential distribution by accounting for the change in distribution shape due to the diversity of cloud lifecycles. The exponential distribution of cloud mass flux previously suggested for deep convection parameterisation is a special case of the Weibull distribution, which opens a way towards unification of the statistical convective ensemble formalism of shallow and deep cumulus clouds. Based on the empirical and theoretical findings, a stochastic model has been developed to simulate a shallow convective cloud ensemble. It is formulated as a compound random process, with the number of convective elements drawn from a Poisson distribution, and the cloud mass flux sampled from a mixed Weibull distribution. Convective memory is accounted for through the explicit cloud lifecycles, making the model formulation consistent with the choice of the Weibull cloud mass flux distribution function. The memory of individual shallow clouds is required to capture the correct convective variability. The resulting distribution of the subgrid convective states in the considered shallow cumulus case is scale-adaptive – the smaller the grid size, the broader the distribution.
Probabilistic Determination of Native State Ensembles of Proteins
DEFF Research Database (Denmark)
Olsson, Simon; Vögeli, Beat Rolf; Cavalli, Andrea;
2014-01-01
The motions of biological macromolecules are tightly coupled to their functions. However, while the study of fast motions has become increasingly feasible in recent years, the study of slower, biologically important motions remains difficult. Here, we present a method to construct native state...... of biomolecules very efficiently. The approach may allow for a dramatic reduction in the computational as well as experimental resources needed to obtain accurate conformational ensembles of biological macromolecules in a statistically sound manner....
Stochastic ensembles, conformationally adaptive teamwork, and enzymatic detoxification.
Atkins, William M; Qian, Hong
2011-05-17
It has been appreciated for a long time that enzymes exist as conformational ensembles throughout multiple stages of the reactions they catalyze, but there is renewed interest in the functional implications. The energy landscape that results from conformationlly diverse poteins is a complex surface with an energetic topography in multiple dimensions, even at the transition state(s) leading to product formation, and this represents a new paradigm. At the same time there has been renewed interest in conformational ensembles, a new paradigm concerning enzyme function has emerged, wherein catalytic promiscuity has clear biological advantages in some cases. "Useful", or biologically functional, promiscuity or the related behavior of "multifunctionality" can be found in the immune system, enzymatic detoxification, signal transduction, and the evolution of new function from an existing pool of folded protein scaffolds. Experimental evidence supports the widely held assumption that conformational heterogeneity promotes functional promiscuity. The common link between these coevolving paradigms is the inherent structural plasticity and conformational dynamics of proteins that, on one hand, lead to complex but evolutionarily selected energy landscapes and, on the other hand, promote functional promiscuity. Here we consider a logical extension of the overlap between these two nascent paradigms: functionally promiscuous and multifunctional enzymes such as detoxification enzymes are expected to have an ensemble landscape with more states accessible on multiple time scales than substrate specific enzymes. Two attributes of detoxification enzymes become important in the context of conformational ensembles: these enzymes metabolize multiple substrates, often in substrate mixtures, and they can form multiple products from a single substrate. These properties, combined with complex conformational landscapes, lead to the possibility of interesting time-dependent, or emergent
Stochastic Ensembles, Conformationally Adaptive Teamwork and Enzymatic Detoxification
Atkins, William M.; Qian, Hong
2011-01-01
It has been appreciated for a long time that enzymes exist as conformational ensembles throughout multiple stages of the reactions they catalyze, but there is renewed interest in the functional implications. The energy landscape that results from conformationlly diverse poteins is a complex surface with an energetic topography in multiple dimensions, even at the transition state(s) leading to product formation, and this represents a new paradigm. Nearly simultaneous with the renewed interest ...
Classical model for bulk-ensemble NMR quantum computation
Schack, R.; Caves, C. M.
1999-01-01
We present a classical model for bulk-ensemble NMR quantum computation: the quantum state of the NMR sample is described by a probability distribution over the orientations of classical tops, and quantum gates are described by classical transition probabilities. All NMR quantum computing experiments performed so far with three quantum bits can be accounted for in this classical model. After a few entangling gates, the classical model suffers an exponential decrease of the measured signal, whe...
Force network ensemble: a new approach to static granular matter
Saarloos, van, W.; Snoeijer, J. H.; Vlugt, T.J.H.; Hecke, van, M.
2004-01-01
An ensemble approach for force distributions in static granular packings is developed. This framework is based on the separation of packing and force scales, together with an a-priori flat measure in the force phase space under the constraints that the contact forces are repulsive and balance on every particle. We show how the formalism yields realistic results, both for disordered and regular ``snooker ball'' configurations, and obtain a shear-induced unjamming transition of the type propose...
Disease-associated mutations that alter the RNA structural ensemble.
Directory of Open Access Journals (Sweden)
Matthew Halvorsen
2010-08-01
Full Text Available Genome-wide association studies (GWAS often identify disease-associated mutations in intergenic and non-coding regions of the genome. Given the high percentage of the human genome that is transcribed, we postulate that for some observed associations the disease phenotype is caused by a structural rearrangement in a regulatory region of the RNA transcript. To identify such mutations, we have performed a genome-wide analysis of all known disease-associated Single Nucleotide Polymorphisms (SNPs from the Human Gene Mutation Database (HGMD that map to the untranslated regions (UTRs of a gene. Rather than using minimum free energy approaches (e.g. mFold, we use a partition function calculation that takes into consideration the ensemble of possible RNA conformations for a given sequence. We identified in the human genome disease-associated SNPs that significantly alter the global conformation of the UTR to which they map. For six disease-states (Hyperferritinemia Cataract Syndrome, beta-Thalassemia, Cartilage-Hair Hypoplasia, Retinoblastoma, Chronic Obstructive Pulmonary Disease (COPD, and Hypertension, we identified multiple SNPs in UTRs that alter the mRNA structural ensemble of the associated genes. Using a Boltzmann sampling procedure for sub-optimal RNA structures, we are able to characterize and visualize the nature of the conformational changes induced by the disease-associated mutations in the structural ensemble. We observe in several cases (specifically the 5' UTRs of FTL and RB1 SNP-induced conformational changes analogous to those observed in bacterial regulatory Riboswitches when specific ligands bind. We propose that the UTR and SNP combinations we identify constitute a "RiboSNitch," that is a regulatory RNA in which a specific SNP has a structural consequence that results in a disease phenotype. Our SNPfold algorithm can help identify RiboSNitches by leveraging GWAS data and an analysis of the mRNA structural ensemble.
Nucleon structure from 2+1-flavor dynamical DWF ensembles
Abramczyk, Michael; Lytle, Andrew; Ohta, Shigemi
2016-01-01
Nucleon isovector vector- and axialvector-current form factors, the renormalized isovector transversity and scalar charge, and the bare quark momentum and helicity moments of isovector structure functions are reported with improved statistics from two recent RBC+UKQCD 2+1-flavor dynamical domain-wall fermions ensembles: Iwasaki\\(\\times\\)DSDR gauge \\(32^3\\times64\\) at inverse lattice spacing of 1.38 GeV and pion mass of 249 and 172 MeV.
ANALYSIS OF SST IMAGES BY WEIGHTED ENSEMBLE TRANSFORM KALMAN FILTER
Sai, Gorthi; Beyou, Sébastien; Memin, Etienne
2011-01-01
International audience This paper presents a novel, efficient scheme for the analysis of Sea Surface Temperature (SST) ocean images. We consider the estimation of the velocity fields and vorticity values from a sequence of oceanic images. The contribution of this paper lies in proposing a novel, robust and simple approach based onWeighted Ensemble Transform Kalman filter (WETKF) data assimilation technique for the analysis of real SST images, that may contain coast regions or large areas o...
Global large time dynamics and the generalized Gibbs ensemble
Gurarie, Victor
2012-01-01
We study the large time dynamics of a macroscopically large quantum systems under a sudden quench. We show that, first of all, for a generic system in the thermodynamic limit the Gibbs distribution correctly captures the large time dynamics of its global observables. In contrast, for an integrable system, the generalized Gibbs ensemble captures its global large time dynamics only if the system can be thought of as a number of noninteracting uncorrelated fermionic degrees of freedom. The condi...
Aspects of dynamical dimensional reduction in multigraph ensembles of CDT
Giasemidis, Georgios; Zohren, Stefan
2012-01-01
We study the continuum limit of a "radially reduced" approximation of Causal Dynamical Triangulations (CDT), so-called multigraph ensembles, and explain why they serve as realistic toy models to study the dimensional reduction observed in numerical simulations of four-dimensional CDT. We present properties of this approximation in two, three and four dimensions comparing them with the numerical simulations and pointing out some common features with 2+1 dimensional Horava-Lifshitz gravity.
Ensemble Learned Vaccination Uptake Prediction using Web Search Queries
Hansen, Niels Dalum; Lioma, Christina; Mølbak, Kåre
2016-01-01
We present a method that uses ensemble learning to combine clinical and web-mined time-series data in order to predict future vaccination uptake. The clinical data is official vaccination registries, and the web data is query frequencies collected from Google Trends. Experiments with official vaccine records show that our method predicts vaccination uptake eff?ectively (4.7 Root Mean Squared Error). Whereas performance is best when combining clinical and web data, using solely web data yields...
Stochastic ensembles, conformationally adaptive teamwork, and enzymatic detoxification.
Atkins, William M; Qian, Hong
2011-05-17
It has been appreciated for a long time that enzymes exist as conformational ensembles throughout multiple stages of the reactions they catalyze, but there is renewed interest in the functional implications. The energy landscape that results from conformationlly diverse poteins is a complex surface with an energetic topography in multiple dimensions, even at the transition state(s) leading to product formation, and this represents a new paradigm. At the same time there has been renewed interest in conformational ensembles, a new paradigm concerning enzyme function has emerged, wherein catalytic promiscuity has clear biological advantages in some cases. "Useful", or biologically functional, promiscuity or the related behavior of "multifunctionality" can be found in the immune system, enzymatic detoxification, signal transduction, and the evolution of new function from an existing pool of folded protein scaffolds. Experimental evidence supports the widely held assumption that conformational heterogeneity promotes functional promiscuity. The common link between these coevolving paradigms is the inherent structural plasticity and conformational dynamics of proteins that, on one hand, lead to complex but evolutionarily selected energy landscapes and, on the other hand, promote functional promiscuity. Here we consider a logical extension of the overlap between these two nascent paradigms: functionally promiscuous and multifunctional enzymes such as detoxification enzymes are expected to have an ensemble landscape with more states accessible on multiple time scales than substrate specific enzymes. Two attributes of detoxification enzymes become important in the context of conformational ensembles: these enzymes metabolize multiple substrates, often in substrate mixtures, and they can form multiple products from a single substrate. These properties, combined with complex conformational landscapes, lead to the possibility of interesting time-dependent, or emergent
New constructions of WOM codes using the Wozencraft ensemble
Shpilka, Amir
2011-01-01
In this paper we give several new constructions of WOM codes. The novelty in our constructions is the use of the so called Wozencraft ensemble of linear codes. Specifically, we obtain the following results. We give an explicit construction of a two-write Write-Once-Memory (WOM for short) code that approaches capacity, over the binary alphabet. More formally, for every \\epsilon>0, 0
Work producing reservoirs: Stochastic thermodynamics with generalized Gibbs ensembles
Horowitz, Jordan M.; Esposito, Massimiliano
2016-08-01
We develop a consistent stochastic thermodynamics for environments composed of thermodynamic reservoirs in an external conservative force field, that is, environments described by the generalized or Gibbs canonical ensemble. We demonstrate that small systems weakly coupled to such reservoirs exchange both heat and work by verifying a local detailed balance relation for the induced stochastic dynamics. Based on this analysis, we help to rationalize the observation that nonthermal reservoirs can increase the efficiency of thermodynamic heat engines.
Snapshots of Anderson localization beyond the ensemble average
El-Dardiry, Ramy G. S.; Faez, Sanli; Lagendijk, Ad
2012-09-01
We study (1+1)D transverse localization of electromagnetic radiation at microwave frequencies directly by two-dimensional spatial scans. Since the longitudinal direction can be mapped onto time, our experiments provide unique snapshots of the buildup of localized waves. The evolution of the wave functions is compared with semianalytical calculations. Studies beyond ensemble averages reveal counterintuitive surprises. Oscillations of the wave functions are observed in space and explained in terms of a beating between the eigenstates.
The Use of Artificial-Intelligence-Based Ensembles for Intrusion Detection: A Review
Directory of Open Access Journals (Sweden)
Gulshan Kumar
2012-01-01
Full Text Available In supervised learning-based classification, ensembles have been successfully employed to different application domains. In the literature, many researchers have proposed different ensembles by considering different combination methods, training datasets, base classifiers, and many other factors. Artificial-intelligence-(AI- based techniques play prominent role in development of ensemble for intrusion detection (ID and have many benefits over other techniques. However, there is no comprehensive review of ensembles in general and AI-based ensembles for ID to examine and understand their current research status to solve the ID problem. Here, an updated review of ensembles and their taxonomies has been presented in general. The paper also presents the updated review of various AI-based ensembles for ID (in particular during last decade. The related studies of AI-based ensembles are compared by set of evaluation metrics driven from (1 architecture & approach followed; (2 different methods utilized in different phases of ensemble learning; (3 other measures used to evaluate classification performance of the ensembles. The paper also provides the future directions of the research in this area. The paper will help the better understanding of different directions in which research of ensembles has been done in general and specifically: field of intrusion detection systems (IDSs.
Bouallegue, Zied Ben
2015-01-01
The assessment of the high-resolution ensemble weather prediction system COSMO-DE-EPS is achieved with the perspective of using it for renewable energy applications. The performance of the ensemble forecast is explored focusing on global radiation, the main weather variable affecting solar power production, and on quantile forecasts, key probabilistic products for the energy sector. First, the ability of the ensemble system to capture and resolve the observation variability is assessed. Secondly, the potential benefit of the ensemble forecasting strategy compared to a single forecast approach is quantitatively estimated. A new metric called ensemble added value is proposed, aiming at a fair comparison of an ensemble forecast with a single forecast, when optimized to the users' needs. Hourly mean forecasts are verified against pyranometer measurements over verification periods covering 2013. The results show in particular that the added value of the ensemble approach is season-dependent and increases with the ...
Thermodynamics and kinetics of a molecular motor ensemble.
Baker, J E; Thomas, D D
2000-10-01
If, contrary to conventional models of muscle, it is assumed that molecular forces equilibrate among rather than within molecular motors, an equation of state and an expression for energy output can be obtained for a near-equilibrium, coworking ensemble of molecular motors. These equations predict clear, testable relationships between motor structure, motor biochemistry, and ensemble motor function, and we discuss these relationships in the context of various experimental studies. In this model, net work by molecular motors is performed with the relaxation of a near-equilibrium intermediate step in a motor-catalyzed reaction. The free energy available for work is localized to this step, and the rate at which this free energy is transferred to work is accelerated by the free energy of a motor-catalyzed reaction. This thermodynamic model implicitly deals with a motile cell system as a dynamic network (not a rigid lattice) of molecular motors within which the mechanochemistry of one motor influences and is influenced by the mechanochemistry of other motors in the ensemble. PMID:11023881
Quantum teleportation between remote atomic-ensemble quantum memories.
Bao, Xiao-Hui; Xu, Xiao-Fan; Li, Che-Ming; Yuan, Zhen-Sheng; Lu, Chao-Yang; Pan, Jian-Wei
2012-12-11
Quantum teleportation and quantum memory are two crucial elements for large-scale quantum networks. With the help of prior distributed entanglement as a "quantum channel," quantum teleportation provides an intriguing means to faithfully transfer quantum states among distant locations without actual transmission of the physical carriers [Bennett CH, et al. (1993) Phys Rev Lett 70(13):1895-1899]. Quantum memory enables controlled storage and retrieval of fast-flying photonic quantum bits with stationary matter systems, which is essential to achieve the scalability required for large-scale quantum networks. Combining these two capabilities, here we realize quantum teleportation between two remote atomic-ensemble quantum memory nodes, each composed of ∼10(8) rubidium atoms and connected by a 150-m optical fiber. The spin wave state of one atomic ensemble is mapped to a propagating photon and subjected to Bell state measurements with another single photon that is entangled with the spin wave state of the other ensemble. Two-photon detection events herald the success of teleportation with an average fidelity of 88(7)%. Besides its fundamental interest as a teleportation between two remote macroscopic objects, our technique may be useful for quantum information transfer between different nodes in quantum networks and distributed quantum computing. PMID:23144222
Gradient flow and scale setting on MILC HISQ ensembles
Bazavov, A; Brown, N; DeTar, C; Foley, J; Gottlieb, Steven; Heller, U M; Komijani, J; Laiho, J; Levkova, L; Sugar, R L; Toussaint, D; Van de Water, R S
2015-01-01
We report on a scale determination with gradient-flow techniques on the $N_f=2+1+1$ HISQ ensembles generated by the MILC collaboration. The ensembles include four lattice spacings, ranging from approximately 0.15 to 0.06 fm, and both physical and unphysical values of the quark masses. The scales $\\sqrt{t_0}/a$ and $w_0/a$ and their tree-level improvements, $\\sqrt{t_{0,{\\rm imp}}}$ and $w_{0,{\\rm imp}}$, are computed on each ensemble using Symanzik flow and the cloverleaf definition of the energy density $E$. Using a combination of continuum chiral perturbation theory and a Taylor-series ansatz for the lattice-spacing and strong-coupling dependence, the results are simultaneously extrapolated to the continuum and interpolated to physical quark masses. We determine the scales $\\sqrt{t_0} = 0.1416({}_{-5}^{+8})$ fm and $w_0 = 0.1717({}_{-11}^{+12})$ fm, where the errors are sums, in quadrature, of statistical and all systematic errors. The precision of $w_0$ and $\\sqrt{t_0}$ is comparable to or more precise than...
Ensemble bayesian model averaging using markov chain Monte Carlo sampling
Energy Technology Data Exchange (ETDEWEB)
Vrugt, Jasper A [Los Alamos National Laboratory; Diks, Cees G H [NON LANL; Clark, Martyn P [NON LANL
2008-01-01
Bayesian model averaging (BMA) has recently been proposed as a statistical method to calibrate forecast ensembles from numerical weather models. Successful implementation of BMA however, requires accurate estimates of the weights and variances of the individual competing models in the ensemble. In their seminal paper (Raftery etal. Mon Weather Rev 133: 1155-1174, 2(05)) has recommended the Expectation-Maximization (EM) algorithm for BMA model training, even though global convergence of this algorithm cannot be guaranteed. In this paper, we compare the performance of the EM algorithm and the recently developed Differential Evolution Adaptive Metropolis (DREAM) Markov Chain Monte Carlo (MCMC) algorithm for estimating the BMA weights and variances. Simulation experiments using 48-hour ensemble data of surface temperature and multi-model stream-flow forecasts show that both methods produce similar results, and that their performance is unaffected by the length of the training data set. However, MCMC simulation with DREAM is capable of efficiently handling a wide variety of BMA predictive distributions, and provides useful information about the uncertainty associated with the estimated BMA weights and variances.
Ensemble feature selection integrating elitist roles and quantum game model
Institute of Scientific and Technical Information of China (English)
Weiping Ding; Jiandong Wang; Zhijin Guan; Quan Shi
2015-01-01
To accelerate the selection process of feature subsets in the rough set theory (RST), an ensemble elitist roles based quantum game (EERQG) algorithm is proposed for feature selec-tion. Firstly, the multilevel elitist roles based dynamics equilibrium strategy is established, and both immigration and emigration of elitists are able to be self-adaptive to balance between exploration and exploitation for feature selection. Secondly, the utility matrix of trust margins is introduced to the model of multilevel elitist roles to enhance various elitist roles’ performance of searching the optimal feature subsets, and the win-win utility solutions for feature selec-tion can be attained. Meanwhile, a novel ensemble quantum game strategy is designed as an intriguing exhibiting structure to perfect the dynamics equilibrium of multilevel elitist roles. Final y, the en-semble manner of multilevel elitist roles is employed to achieve the global minimal feature subset, which wil greatly improve the fea-sibility and effectiveness. Experiment results show the proposed EERQG algorithm has superiority compared to the existing feature selection algorithms.
Downscaling a perturbed physics ensemble over the CORDEX Africa domain
Buontempo, Carlo; Williams, Karina; McSweeney, Carol; Jones, Richard; Mathison, Camilla; Wang, Chang
2014-05-01
We present here the methodology and the results of 5-member ensemble simulation of the climate of Africa for the period 1950-2100 using climate modelling system PRECIS over the CORDEX Africa domain. The boundary conditions for the regional model simulations were selected from a 17-member perturbed physics ensemble based on the HadCM3 global climate model (Murphy et al. 2007) following the methodology described in McSweeney et al 2012. Such an approach was selected in order to provide a good representation of the overall ensemble spread over a number of sub regions while at the same time avoiding members which have demonstrate particularly unrealistic characteristics in their baseline climate. In the simulations a special attention was given to the representation of some inland water bodies, such as lake Victoria, whose impact on the regional climate was believed to be significant thus allowing for the representation of some regional processes (e.g. land-lake breezes) that were not represented in the global models. In particular the SSTs of the lakes were corrected to better represent the local climatological values. The results suggest that RCM simulations improve the fit to observations of precipitation and temperature in most of the African sub-regions (e.g. North Africa, West Sahel). Also, the range of RCM projections is often different to those from the GCMs in these regions. We discuss the reasons for and links between these results and their implications for use in informing adaptation policy at regional level.
Adaptive Ensemble with Human Memorizing Characteristics for Data Stream Mining
Directory of Open Access Journals (Sweden)
Yanhuang Jiang
2015-01-01
Full Text Available Combining several classifiers on sequential chunks of training instances is a popular strategy for data stream mining with concept drifts. This paper introduces human recalling and forgetting mechanisms into a data stream mining system and proposes a Memorizing Based Data Stream Mining (MDSM model. In this model, each component classifier is regarded as a piece of knowledge that a human obtains through learning some materials and has a memory retention value reflecting its usefulness in the history. The classifiers with high memory retention values are reserved in a “knowledge repository.” When a new data chunk comes, most useful classifiers will be selected (recalled from the repository and compose the current target ensemble. Based on MDSM, we put forward a new algorithm, MAE (Memorizing Based Adaptive Ensemble, which uses Ebbinghaus forgetting curve as the forgetting mechanism and adopts ensemble pruning as the recalling mechanism. Compared with four popular data stream mining approaches on the datasets with different concept drifts, the experimental results show that MAE achieves high and stable predicting accuracy, especially for the applications with recurring or complex concept drifts. The results also prove the effectiveness of MDSM model.
Ensemble forecasting of potential habitat for three invasive fishes
Poulos, Helen M.; Chernoff, Barry; Fuller, Pam L.; Butman, David
2012-01-01
Aquatic invasive species pose major ecological and economic threats to aquatic ecosystems worldwide via displacement, predation, or hybridization with native species and the alteration of aquatic habitats and hydrologic cycles. Modeling the habitat suitability of alien aquatic species through spatially explicit mapping is an increasingly important risk assessment tool. Habitat modeling also facilitates identification of key environmental variables influencing invasive species distributions. We compared four modeling methods to predict the potential continental United States distributions of northern snakehead Channa argus (Cantor, 1842), round goby Neogobius melanostomus (Pallas, 1814), and silver carp Hypophthalmichthys molitrix (Valenciennes, 1844) using maximum entropy (Maxent), the genetic algorithm for rule set production (GARP), DOMAIN, and support vector machines (SVM). We used inventory records from the USGS Nonindigenous Aquatic Species Database and a geographic information system of 20 climatic and environmental variables to generate individual and ensemble distribution maps for each species. The ensemble maps from our study performed as well as or better than all of the individual models except Maxent. The ensemble and Maxent models produced significantly higher accuracy individual maps than GARP, one-class SVMs, or DOMAIN. The key environmental predictor variables in the individual models were consistent with the tolerances of each species. Results from this study provide insights into which locations and environmental conditions may promote the future spread of invasive fish in the US.
Optimization of multi-model ensemble forecasting of typhoon waves
Directory of Open Access Journals (Sweden)
Shun-qi Pan
2016-01-01
Full Text Available Accurately forecasting ocean waves during typhoon events is extremely important in aiding the mitigation and minimization of their potential damage to the coastal infrastructure, and the protection of coastal communities. However, due to the complex hydrological and meteorological interaction and uncertainties arising from different modeling systems, quantifying the uncertainties and improving the forecasting accuracy of modeled typhoon-induced waves remain challenging. This paper presents a practical approach to optimizing model-ensemble wave heights in an attempt to improve the accuracy of real-time typhoon wave forecasting. A locally weighted learning algorithm is used to obtain the weights for the wave heights computed by the WAVEWATCH III wave model driven by winds from four different weather models (model-ensembles. The optimized weights are subsequently used to calculate the resulting wave heights from the model-ensembles. The results show that the Optimization is capable of capturing the different behavioral effects of the different weather models on wave generation. Comparison with the measurements at the selected wave buoy locations shows that the optimized weights, obtained through a training process, can significantly improve the accuracy of the forecasted wave heights over the standard mean values, particularly for typhoon-induced peak waves. The results also indicate that the algorithm is easy to implement and practical for real-time wave forecasting.
Four types of ensemble coding in data visualizations.
Szafir, Danielle Albers; Haroz, Steve; Gleicher, Michael; Franconeri, Steven
2016-01-01
Ensemble coding supports rapid extraction of visual statistics about distributed visual information. Researchers typically study this ability with the goal of drawing conclusions about how such coding extracts information from natural scenes. Here we argue that a second domain can serve as another strong inspiration for understanding ensemble coding: graphs, maps, and other visual presentations of data. Data visualizations allow observers to leverage their ability to perform visual ensemble statistics on distributions of spatial or featural visual information to estimate actual statistics on data. We survey the types of visual statistical tasks that occur within data visualizations across everyday examples, such as scatterplots, and more specialized images, such as weather maps or depictions of patterns in text. We divide these tasks into four categories: identification of sets of values, summarization across those values, segmentation of collections, and estimation of structure. We point to unanswered questions for each category and give examples of such cross-pollination in the current literature. Increased collaboration between the data visualization and perceptual psychology research communities can inspire new solutions to challenges in visualization while simultaneously exposing unsolved problems in perception research. PMID:26982369
Probabilistic infrasound propagation using ensemble based atmospheric perturbations
Smets, Pieter; Evers, Läslo
2015-04-01
The state of the atmosphere is of utmost importance for infrasound propagation. In propagation modelling, still, the true state of the atmosphere is mainly represented by the analysis. The analysis is the best deterministic estimate of the atmosphere using a data assimilation system existing of a General Circulation Model (GCM). However, the analysis excludes error variances of both model and observations. In addition, the coarse resolution of GCM results in averaging of, e.g., clouds or gravity waves, over larger regions known as parameterisation. Consequentially, arrivals due to fine-scale structure in wind and temperature can be missing. Therefore, infrasound propagation including the atmospheric best-estimate error variances based on the ensemble model is proposed. The ensemble system exists of model perturbations with an amplitude comparable to analysis error estimates to obtain a probability density function rather than one specific state as obtained from a deterministic system. The best-estimate analysis error variances are described by a set of perturbations using the European Centre for Medium-range Weather Forecasts (ECMWF) Ensemble Data Assimilation (EDA) system. Probabilistic infrasound propagation using 3-D ray tracing is demonstrated by one year of mining activity, e.g., blasting, in Gällivare, northern Sweden, observed at infrasound array IS37 in Norway, part of the International Monitoring System (IMS) for verification of the Comprehensive Nuclear-Test-Ban Treaty (CTBT). Probabilistic infrasound propagation is compared with the standard deterministic result obtained using the analysis.
Geometric integrator for simulations in the canonical ensemble
Tapias, Diego; Sanders, David P.; Bravetti, Alessandro
2016-08-01
We introduce a geometric integrator for molecular dynamics simulations of physical systems in the canonical ensemble that preserves the invariant distribution in equations arising from the density dynamics algorithm, with any possible type of thermostat. Our integrator thus constitutes a unified framework that allows the study and comparison of different thermostats and of their influence on the equilibrium and non-equilibrium (thermo-)dynamic properties of a system. To show the validity and the generality of the integrator, we implement it with a second-order, time-reversible method and apply it to the simulation of a Lennard-Jones system with three different thermostats, obtaining good conservation of the geometrical properties and recovering the expected thermodynamic results. Moreover, to show the advantage of our geometric integrator over a non-geometric one, we compare the results with those obtained by using the non-geometric Gear integrator, which is frequently used to perform simulations in the canonical ensemble. The non-geometric integrator induces a drift in the invariant quantity, while our integrator has no such drift, thus ensuring that the system is effectively sampling the correct ensemble.
Ensemble of ground subsidence hazard maps using fuzzy logic
Park, Inhye; Lee, Jiyeong; Saro, Lee
2014-06-01
Hazard maps of ground subsidence around abandoned underground coal mines (AUCMs) in Samcheok, Korea, were constructed using fuzzy ensemble techniques and a geographical information system (GIS). To evaluate the factors related to ground subsidence, a spatial database was constructed from topographic, geologic, mine tunnel, land use, groundwater, and ground subsidence maps. Spatial data, topography, geology, and various ground-engineering data for the subsidence area were collected and compiled in a database for mapping ground-subsidence hazard (GSH). The subsidence area was randomly split 70/30 for training and validation of the models. The relationships between the detected ground-subsidence area and the factors were identified and quantified by frequency ratio (FR), logistic regression (LR) and artificial neural network (ANN) models. The relationships were used as factor ratings in the overlay analysis to create ground-subsidence hazard indexes and maps. The three GSH maps were then used as new input factors and integrated using fuzzy-ensemble methods to make better hazard maps. All of the hazard maps were validated by comparison with known subsidence areas that were not used directly in the analysis. As the result, the ensemble model was found to be more effective in terms of prediction accuracy than the individual model.
Comprehensive Study on Lexicon-based Ensemble Classification Sentiment Analysis
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Łukasz Augustyniak
2015-12-01
Full Text Available We propose a novel method for counting sentiment orientation that outperforms supervised learning approaches in time and memory complexity and is not statistically significantly different from them in accuracy. Our method consists of a novel approach to generating unigram, bigram and trigram lexicons. The proposed method, called frequentiment, is based on calculating the frequency of features (words in the document and averaging their impact on the sentiment score as opposed to documents that do not contain these features. Afterwards, we use ensemble classification to improve the overall accuracy of the method. What is important is that the frequentiment-based lexicons with sentiment threshold selection outperform other popular lexicons and some supervised learners, while being 3–5 times faster than the supervised approach. We compare 37 methods (lexicons, ensembles with lexicon’s predictions as input and supervised learners applied to 10 Amazon review data sets and provide the first statistical comparison of the sentiment annotation methods that include ensemble approaches. It is one of the most comprehensive comparisons of domain sentiment analysis in the literature.
Cloud-Aerosol-Radiation (CAR ensemble modeling system
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X.-Z. Liang
2013-04-01
Full Text Available A Cloud-Aerosol-Radiation (CAR ensemble modeling system has been developed to incorporate the largest choices of alternative parameterizations for cloud properties (cover, water, radius, optics, geometry, aerosol properties (type, profile, optics, radiation transfers (solar, infrared, and their interactions. These schemes form the most comprehensive collection currently available in the literature, including those used by the world leading general circulation models (GCMs. The CAR provides a unique framework to determine (via intercomparison across all schemes, reduce (via optimized ensemble simulations, and attribute specific key factors for (via physical process sensitivity analyses the model discrepancies and uncertainties in representing greenhouse gas, aerosol and cloud radiative forcing effects. This study presents a general description of the CAR system and illustrates its capabilities for climate modeling applications, especially in the context of estimating climate sensitivity and uncertainty range caused by cloud-aerosol-radiation interactions. For demonstration purpose, the evaluation is based on several CAR standalone and coupled climate model experiments, each comparing a limited subset of the full system ensemble with up to 896 members. It is shown that the quantification of radiative forcings and climate impacts strongly depends on the choices of the cloud, aerosol and radiation schemes. The prevailing schemes used in current GCMs are likely insufficient in variety and physically biased in a significant way. There exists large room for improvement by optimally combining radiation transfer with cloud property schemes.
Local Ensemble Kalman Particle Filters for efficient data assimilation
Robert, Sylvain
2016-01-01
Ensemble methods such as the Ensemble Kalman Filter (EnKF) are widely used for data assimilation in large-scale geophysical applications, as for example in numerical weather prediction (NWP). There is a growing interest for physical models with higher and higher resolution, which brings new challenges for data assimilation techniques because of the presence of non-linear and non-Gaussian features that are not adequately treated by the EnKF. We propose two new localized algorithms based on the Ensemble Kalman Particle Filter (EnKPF), a hybrid method combining the EnKF and the Particle Filter (PF) in a way that maintains scalability and sample diversity. Localization is a key element of the success of EnKFs in practice, but it is much more challenging to apply to PFs. The algorithms that we introduce in the present paper provide a compromise between the EnKF and the PF while avoiding some of the problems of localization for pure PFs. Numerical experiments with a simplified model of cumulus convection based on a...
Probability Maps for the Visualization of Assimilation Ensemble Flow Data
Hollt, Thomas
2015-05-25
Ocean forecasts nowadays are created by running ensemble simulations in combination with data assimilation techniques. Most of these techniques resample the ensemble members after each assimilation cycle. This means that in a time series, after resampling, every member can follow up on any of the members before resampling. Tracking behavior over time, such as all possible paths of a particle in an ensemble vector field, becomes very difficult, as the number of combinations rises exponentially with the number of assimilation cycles. In general a single possible path is not of interest but only the probabilities that any point in space might be reached by a particle at some point in time. In this work we present an approach using probability-weighted piecewise particle trajectories to allow such a mapping interactively, instead of tracing quadrillions of individual particles. We achieve interactive rates by binning the domain and splitting up the tracing process into the individual assimilation cycles, so that particles that fall into the same bin after a cycle can be treated as a single particle with a larger probability as input for the next time step. As a result we loose the possibility to track individual particles, but can create probability maps for any desired seed at interactive rates.
A robust activity marking system for exploring active neuronal ensembles
Sørensen, Andreas T; Cooper, Yonatan A; Baratta, Michael V; Weng, Feng-Ju; Zhang, Yuxiang; Ramamoorthi, Kartik; Fropf, Robin; LaVerriere, Emily; Xue, Jian; Young, Andrew; Schneider, Colleen; Gøtzsche, Casper René; Hemberg, Martin; Yin, Jerry CP; Maier, Steven F; Lin, Yingxi
2016-01-01
Understanding how the brain captures transient experience and converts it into long lasting changes in neural circuits requires the identification and investigation of the specific ensembles of neurons that are responsible for the encoding of each experience. We have developed a Robust Activity Marking (RAM) system that allows for the identification and interrogation of ensembles of neurons. The RAM system provides unprecedented high sensitivity and selectivity through the use of an optimized synthetic activity-regulated promoter that is strongly induced by neuronal activity and a modified Tet-Off system that achieves improved temporal control. Due to its compact design, RAM can be packaged into a single adeno-associated virus (AAV), providing great versatility and ease of use, including application to mice, rats, flies, and potentially many other species. Cre-dependent RAM, CRAM, allows for the study of active ensembles of a specific cell type and anatomical connectivity, further expanding the RAM system’s versatility. DOI: http://dx.doi.org/10.7554/eLife.13918.001 PMID:27661450
Ensemble Solar Forecasting Statistical Quantification and Sensitivity Analysis: Preprint
Energy Technology Data Exchange (ETDEWEB)
Cheung, WanYin; Zhang, Jie; Florita, Anthony; Hodge, Bri-Mathias; Lu, Siyuan; Hamann, Hendrik F.; Sun, Qian; Lehman, Brad
2015-12-08
Uncertainties associated with solar forecasts present challenges to maintain grid reliability, especially at high solar penetrations. This study aims to quantify the errors associated with the day-ahead solar forecast parameters and the theoretical solar power output for a 51-kW solar power plant in a utility area in the state of Vermont, U.S. Forecasts were generated by three numerical weather prediction (NWP) models, including the Rapid Refresh, the High Resolution Rapid Refresh, and the North American Model, and a machine-learning ensemble model. A photovoltaic (PV) performance model was adopted to calculate theoretical solar power generation using the forecast parameters (e.g., irradiance, cell temperature, and wind speed). Errors of the power outputs were quantified using statistical moments and a suite of metrics, such as the normalized root mean squared error (NRMSE). In addition, the PV model's sensitivity to different forecast parameters was quantified and analyzed. Results showed that the ensemble model yielded forecasts in all parameters with the smallest NRMSE. The NRMSE of solar irradiance forecasts of the ensemble NWP model was reduced by 28.10% compared to the best of the three NWP models. Further, the sensitivity analysis indicated that the errors of the forecasted cell temperature attributed only approximately 0.12% to the NRMSE of the power output as opposed to 7.44% from the forecasted solar irradiance.
Accounting for three sources of uncertainty in ensemble hydrological forecasting
Thiboult, Antoine; Anctil, François; Boucher, Marie-Amélie
2016-05-01
Seeking more accuracy and reliability, the hydrometeorological community has developed several tools to decipher the different sources of uncertainty in relevant modeling processes. Among them, the ensemble Kalman filter (EnKF), multimodel approaches and meteorological ensemble forecasting proved to have the capability to improve upon deterministic hydrological forecast. This study aims to untangle the sources of uncertainty by studying the combination of these tools and assessing their respective contribution to the overall forecast quality. Each of these components is able to capture a certain aspect of the total uncertainty and improve the forecast at different stages in the forecasting process by using different means. Their combination outperforms any of the tools used solely. The EnKF is shown to contribute largely to the ensemble accuracy and dispersion, indicating that the initial conditions uncertainty is dominant. However, it fails to maintain the required dispersion throughout the entire forecast horizon and needs to be supported by a multimodel approach to take into account structural uncertainty. Moreover, the multimodel approach contributes to improving the general forecasting performance and prevents this performance from falling into the model selection pitfall since models differ strongly in their ability. Finally, the use of probabilistic meteorological forcing was found to contribute mostly to long lead time reliability. Particular attention needs to be paid to the combination of the tools, especially in the EnKF tuning to avoid overlapping in error deciphering.
Ensemble Kinetic Modeling of Metabolic Networks from Dynamic Metabolic Profiles
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Gengjie Jia
2012-11-01
Full Text Available Kinetic modeling of metabolic pathways has important applications in metabolic engineering, but significant challenges still remain. The difficulties faced vary from finding best-fit parameters in a highly multidimensional search space to incomplete parameter identifiability. To meet some of these challenges, an ensemble modeling method is developed for characterizing a subset of kinetic parameters that give statistically equivalent goodness-of-fit to time series concentration data. The method is based on the incremental identification approach, where the parameter estimation is done in a step-wise manner. Numerical efficacy is achieved by reducing the dimensionality of parameter space and using efficient random parameter exploration algorithms. The shift toward using model ensembles, instead of the traditional “best-fit” models, is necessary to directly account for model uncertainty during the application of such models. The performance of the ensemble modeling approach has been demonstrated in the modeling of a generic branched pathway and the trehalose pathway in Saccharomyces cerevisiae using generalized mass action (GMA kinetics.
Relire l’histoire coloniale au XVIIIe siècle. L’édition critique de l’Histoire des deux Indes
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Platania, Marco
2014-02-01
Full Text Available En 1781, Guillaume-Thomas Raynal (1713-1796, ancien directeur du “Mercure de France” et l’un des membres les mieux connus de la République des Lettres, s’exile de Paris pour se soustraire au décret du Parlement (25 mai qui voulait son emprisonnement. Il ne regagnera la France qu’en 1784, et Paris seulement en 1790. Qu’est-ce qui lui avait attiré la rage du Parlement? La Cour de Paris s’en était prise à quatre volumes qui venaient de paraître sous le nom de Raynal: l’Histoire politique et philosophique de l’établissement et du commerce des Européens dans les deux Indes. Cette oeuvre, célèbre à l’époque, est aujourd’hui l’objet d’une importante édition critique – la première qui en a jamais été faite. Cette entreprise éditoriale récente se saisit d’un moment important de la vie intellectuelle de la France d’Ancien Régime et de la circulation d’informations à l'échelle non seulement européenne mais mondiale. L’Histoire des deux Indes (comme elle fut appelée à l’époque et comme on l’appellera ici fut en effet un épisode remarquable à maints égards: elle eut un énorme succès commercial et suscita un débat national et international touchant non seulement l’Europe, mais aussi les Amériques. Sa diffusion tient d’un côté aux stratégies publicitaires mises en oeuvre par Raynal et ses éditeurs, mais aussi à l’actualité du sujet dont ils se saisirent: l’expansion coloniale et le développement du commerce extérieur décidaient de la fortune de nombreux citoyens (administrateurs, commerçants, ingénieurs, matelots et des finances des états; les découvertes géographiques et anthropologiques suscitaient la curiosité du public et maintes controverses autour des peuples et des civilisations jusqu’alors inconnus.
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Dilson Ferreira Cruz
2011-10-01
Full Text Available Le présent article se propose d’établir un dialogue productif entre la sémiotique du discours (ou greimassienne et la rhétorique, en examinant deux contes de l’écrivain brésilien Joaquim Maria Machado de Assis (1839-1908 intitulés Teoria do medalhão [« Théorie du médaillon »] et O espelho [« Le miroir »]. Ces deux textes, très différents dans leur forme et leur contenu, présentent un point commun : ils discutent un processus de « déconstruction d’identité ». Ainsi, dans le premier, un père se propose d’amener son fils à adopter un comportement et un discours vides – dépourvus, donc, d’identité – pour atteindre le prestige dans une société d’apparences. Dans le second, nous assistons à un processus involontaire de perte d’identité, ce qui extrapole des aspects discursifs pour s’emparer du sujet, en menaçant son existence même.This paper aims to promote a productive dialogue between French Semiotics (Greimas and Rhetoric, by analyzing two short tales by the Brazilian writer Joaquim Maria Machado de Assis (1839-1908, entitled Teoria do medalhão [“Theory of the medalhão”] and O espelho [“The mirror”]. Though very different in form and content, the two texts share a common point: both of them discuss some kind of “identity deconstruction” process. Thus, in the first tale, a father proposes to teach his son how to adopt an empty – and therefore devoid of identity – discourse and behavior so as to reach success in a society of appearances. In the second tale, we observe an involuntary process of identity loss, which goes beyond discourse and takes possession of the individual subject, thereby threatening his very existence.
Towards reliable seasonal ensemble streamflow forecasts for ephemeral rivers
Bennett, James; Wang, Qj; Li, Ming; Robertson, David
2016-04-01
Despite their inherently variable nature, ephemeral rivers are an important water resource in many dry regions. Water managers are likely benefit considerably from even mildly skilful ensemble forecasts of streamflow in ephemeral rivers. As with any ensemble forecast, forecast uncertainty - i.e., the spread of the ensemble - must be reliably quantified to allow users of the forecasts to make well-founded decisions. Correctly quantifying uncertainty in ephemeral rivers is particularly challenging because of the high incidence of zero flows, which are difficult to handle with conventional statistical techniques. Here we apply a seasonal streamflow forecasting system, the model for generating Forecast Guided Stochastic Scenarios (FoGSS), to 26 Australian ephemeral rivers. FoGSS uses post-processed ensemble rainfall forecasts from a coupled ocean-atmosphere prediction system to force an initialised monthly rainfall runoff model, and then applies a staged hydrological error model to describe and propagate hydrological uncertainty in the forecast. FoGSS produces 12-month streamflow forecasts; as forecast skill declines with lead time, the forecasts are designed to transit seamlessly to stochastic scenarios. The ensemble rainfall forecasts used in FoGSS are known to be unbiased and reliable, and we concentrate here on the hydrological error model. The FoGSS error model has several features that make it well suited to forecasting ephemeral rivers. First, FoGSS models the error after data is transformed with a log-sinh transformation. The log-sinh transformation is able to normalise even highly skewed data and homogenise its variance, allowing us to assume that errors are Gaussian. Second, FoGSS handles zero values using data censoring. Data censoring allows streamflow in ephemeral rivers to be treated as a continuous variable, rather than having to model the occurrence of non-zero values and the distribution of non-zero values separately. This greatly simplifies parameter
Slette, Aslaug Louise
2014-01-01
Abstract This thesis aims at understanding the roles and characteristics of aural awareness in ensemble rehearsals, within the contexts of higher music education and Western classical music. The overall idea of the subject area of aural training as a complementary discipline in undergraduate studies, is that it should inform and support performance activities, and lead to aural awareness. For example, one may expect music students to be aurally aware in their unsupervised, curricular ensem...
A pena e a espada: a Revue des Deux Mondes e a intervenção francesa no México
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Maria Ligia Coelho Prado
2014-12-01
Full Text Available Este artigo analisa os textos publicados pela Revue des Deux Mondes a respeito do México, entre 1840 e 1870. A revista expressava a opinião de grupos de intelectuais próximos ao poder político, entendidos aqui como representantes dos interesses nacionais franceses. O México se distinguia, na América Latina, como centro principal de suas atenções. A revista elaborou imagens da França como o mais importante país latino que olhava para sua "irmã de sangue", a nação mexicana, com o desejo de dirigir seus passos. Os artigos lembravam o glorioso passado da França e insistiam na necessidade do país se interpor ao avanço, na região, de sua grande rival, a Grã-Bretanha, e da nova "ameaça", os Estados Unidos. Os articulistas estimularam seus leitores a pensarem a França como grande potência colocada em lugar de preeminência internacional legitimado por sua história, cultura e civilização.
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Lucile Arnoux-Farnoux
2015-12-01
Full Text Available Pendant l’entre-deux-guerres, certaines revues littéraires grecques adoptent uneattitude hellénocentriste, tandis que d’autres s’ouvrent au contraire largement à l’étranger.Cette ouverture se manifeste bien sûr par la publication d’oeuvres en traduction, maisaussi par un intérêt grandissant pour les revues étrangères, et en particulier françaises,qui se marque par l’emprunt d’articles et surtout par la création de rubriques spécialisées.Le but de ce travail est de mettre en lumière l’existence de relations privilégiées entrerevues grecques et revues françaises comme vecteurs de transferts culturels –qu’il s’agissede la reprise de modèles éditoriaux ou de la circulation de textes, d’idées ou même decollaborateurs–, d’évaluer la part que la traduction prend dans l’établissement de cesrelations et enfin de déterminer si on peut ou non parler dans ces cas de “réseau derevues”, comme cela a été fait dans d’autres contextes européens.
Lessons from Climate Modeling on the Design and Use of Ensembles for Crop Modeling
Wallach, Daniel; Mearns, Linda O.; Ruane, Alexander C.; Roetter, Reimund P.; Asseng, Senthold
2016-01-01
Working with ensembles of crop models is a recent but important development in crop modeling which promises to lead to better uncertainty estimates for model projections and predictions, better predictions using the ensemble mean or median, and closer collaboration within the modeling community. There are numerous open questions about the best way to create and analyze such ensembles. Much can be learned from the field of climate modeling, given its much longer experience with ensembles. We draw on that experience to identify questions and make propositions that should help make ensemble modeling with crop models more rigorous and informative. The propositions include defining criteria for acceptance of models in a crop MME, exploring criteria for evaluating the degree of relatedness of models in a MME, studying the effect of number of models in the ensemble, development of a statistical model of model sampling, creation of a repository for MME results, studies of possible differential weighting of models in an ensemble, creation of single model ensembles based on sampling from the uncertainty distribution of parameter values or inputs specifically oriented toward uncertainty estimation, the creation of super ensembles that sample more than one source of uncertainty, the analysis of super ensemble results to obtain information on total uncertainty and the separate contributions of different sources of uncertainty and finally further investigation of the use of the multi-model mean or median as a predictor.
Conservation of Mass and Preservation of Positivity with Ensemble-Type Kalman Filter Algorithms
Janjic, Tijana; Mclaughlin, Dennis; Cohn, Stephen E.; Verlaan, Martin
2014-01-01
This paper considers the incorporation of constraints to enforce physically based conservation laws in the ensemble Kalman filter. In particular, constraints are used to ensure that the ensemble members and the ensemble mean conserve mass and remain nonnegative through measurement updates. In certain situations filtering algorithms such as the ensemble Kalman filter (EnKF) and ensemble transform Kalman filter (ETKF) yield updated ensembles that conserve mass but are negative, even though the actual states must be nonnegative. In such situations if negative values are set to zero, or a log transform is introduced, the total mass will not be conserved. In this study, mass and positivity are both preserved by formulating the filter update as a set of quadratic programming problems that incorporate non-negativity constraints. Simple numerical experiments indicate that this approach can have a significant positive impact on the posterior ensemble distribution, giving results that are more physically plausible both for individual ensemble members and for the ensemble mean. In two examples, an update that includes a non-negativity constraint is able to properly describe the transport of a sharp feature (e.g., a triangle or cone). A number of implementation questions still need to be addressed, particularly the need to develop a computationally efficient quadratic programming update for large ensemble.
Heteroscedastic Extended Logistic Regression for Post-Processing of Ensemble Guidance
Messner, Jakob W.; Mayr, Georg J.; Wilks, Daniel S.; Zeileis, Achim
2014-05-01
To achieve well-calibrated probabilistic weather forecasts, numerical ensemble forecasts are often statistically post-processed. One recent ensemble-calibration method is extended logistic regression which extends the popular logistic regression to yield full probability distribution forecasts. Although the purpose of this method is to post-process ensemble forecasts, usually only the ensemble mean is used as predictor variable, whereas the ensemble spread is neglected because it does not improve the forecasts. In this study we show that when simply used as ordinary predictor variable in extended logistic regression, the ensemble spread only affects the location but not the variance of the predictive distribution. Uncertainty information contained in the ensemble spread is therefore not utilized appropriately. To solve this drawback we propose a new approach where the ensemble spread is directly used to predict the dispersion of the predictive distribution. With wind speed data and ensemble forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF) we show that using this approach, the ensemble spread can be used effectively to improve forecasts from extended logistic regression.
Time-consistent calibration of short-term regional wind power ensemble forecasts
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Stephan Späth
2015-04-01
Full Text Available With increasing wind power capacity, accurate uncertainty forecasts get more and more important for grid integration. The uncertainty of forecasts can be quantified by ensemble forecasts. We use ensemble forecasts from the COSMO-DE EPS to generate short-term ensemble forecasts of regionally aggregated wind power. The wind power forecasts are generated by an optimised regional power curve model that is based on minimum score estimation and leads to wind power forecasts with small deterministic errors. Remaining bias and dispersion errors in the wind power forecasts are removed by statistical post-processing (also called calibration with ensemble model output statistics and the temporal rank correlation of the raw ensemble is maintained by ensemble copula coupling. The verification of raw and calibrated ensembles shows both strong improvements by calibration and the benefit of ensuring time consistency with ensemble copula coupling. The improvements are indicated by the multivariate energy score as well as in a proposed univariate verification approach that is based on integrated wind power forecast and measurement trajectories. Slight deficits in time consistency of the forecasts remain because the theoretical assumptions of ensemble copula coupling are not always fulfilled as the COSMO-DE EPS is based on distinguishable ensemble members. The more training days are used for calibration against measurements of regionally aggregated wind power, the lower is the improvement by calibration which contradicts former results for different variables like wind speed.
Hopson, T. M.
2014-12-01
One potential benefit of an ensemble prediction system (EPS) is its capacity to forecast its own forecast error through the ensemble spread-error relationship. In practice, an EPS is often quite limited in its ability to represent the variable expectation of forecast error through the variable dispersion of the ensemble, and perhaps more fundamentally, in its ability to provide enough variability in the ensembles dispersion to make the skill-spread relationship even potentially useful (irrespective of whether the EPS is well-calibrated or not). In this paper we examine the ensemble skill-spread relationship of an ensemble constructed from the TIGGE (THORPEX Interactive Grand Global Ensemble) dataset of global forecasts and a combination of multi-model and post-processing approaches. Both of the multi-model and post-processing techniques are based on quantile regression (QR) under a step-wise forward selection framework leading to ensemble forecasts with both good reliability and sharpness. The methodology utilizes the ensemble's ability to self-diagnose forecast instability to produce calibrated forecasts with informative skill-spread relationships. A context for these concepts is provided by assessing the constructed ensemble in forecasting district-level humidity impacting the incidence of meningitis in the meningitis belt of Africa, and in forecasting flooding events in the Brahmaputra and Ganges basins of South Asia.
Hybrid ensemble 4DVar assimilation of stratospheric ozone using a global shallow water model
Allen, Douglas R.; Hoppel, Karl W.; Kuhl, David D.
2016-07-01
Wind extraction from stratospheric ozone (O3) assimilation is examined using a hybrid ensemble 4-D variational assimilation (4DVar) shallow water model (SWM) system coupled to the tracer advection equation. Stratospheric radiance observations are simulated using global observations of the SWM fluid height (Z), while O3 observations represent sampling by a typical polar-orbiting satellite. Four ensemble sizes were examined (25, 50, 100, and 1518 members), with the largest ensemble equal to the number of dynamical state variables. The optimal length scale for ensemble localization was found by tuning an ensemble Kalman filter (EnKF). This scale was then used for localizing the ensemble covariances that were blended with conventional covariances in the hybrid 4DVar experiments. Both optimal length scale and optimal blending coefficient increase with ensemble size, with optimal blending coefficients varying from 0.2-0.5 for small ensembles to 0.5-1.0 for large ensembles. The hybrid system outperforms conventional 4DVar for all ensemble sizes, while for large ensembles the hybrid produces similar results to the offline EnKF. Assimilating O3 in addition to Z benefits the winds in the hybrid system, with the fractional improvement in global vector wind increasing from ˜ 35 % with 25 and 50 members to ˜ 50 % with 1518 members. For the smallest ensembles (25 and 50 members), the hybrid 4DVar assimilation improves the zonal wind analysis over conventional 4DVar in the Northern Hemisphere (winter-like) region and also at the Equator, where Z observations alone have difficulty constraining winds due to lack of geostrophy. For larger ensembles (100 and 1518 members), the hybrid system results in both zonal and meridional wind error reductions, relative to 4DVar, across the globe.
HIDALGO, Maud; RAGOT-COURT, Isabelle; EYSSARTIER, Chloé
2015-01-01
La présente étude se donne pour objectifs d'appréhender les attitudes des automobilistes vis-à-vis de la Circulation Inter-Files (CIF) des conducteurs de 2RM et d'explorer leur discours à propos des situations problématiques (sur le plan pratique ou opératoire) qu'ils rencontrent lorsqu'ils sont confrontés à cette pratique ainsi que les stratégies de régulation qu'ils mettent en place pour les résoudre. Trois caractéristiques sont prises en compte : les deux premières caractérisent les automo...
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K. Kobayashi
2015-12-01
Full Text Available This paper presents a study on short-term ensemble flood forecasting specifically for small dam catchments in Japan. Numerical ensemble simulations of rainfall from the Japan Meteorological Agency Nonhydrostatic Model are used as the input data to a rainfall–runoff model for predicting river discharge into a dam. The ensemble weather simulations use a conventional 10 km and a high-resolution 2 km spatial resolution. A distributed rainfall–runoff model is constructed for the Kasahori dam catchment (approx. 70 km2 and applied with the ensemble rainfalls. The results show that the hourly maximum and cumulative catchment-average rainfalls of the 2 km-resolution JMA-NHM ensemble simulation are more appropriate than the 10 km-resolution rainfalls. All the simulated inflows based on the 2 and 10 km rainfalls become larger than the flood discharge of 140 m3 s−1; a threshold value for flood control. The inflows with the 10 km-resolution ensemble rainfall are all considerably smaller than the observations, while, at least one simulated discharge out of 11 ensemble members with the 2 km-resolution rainfalls reproduces the first peak of the inflow at the Kasahori dam with similar amplitude to observations, although there are spatiotemporal lags between simulation and observation. To take positional lags into account of the ensemble discharge simulation, the rainfall distribution in each ensemble member is shifted so that the catchment-averaged cumulative rainfall of the Kasahori dam maximizes. The runoff simulation with the position-shifted rainfalls show much better results than the original ensemble discharge simulations.
Ndoua, Claude Cyrille Noa; Fattouh, Meyssam; Mirdat, Shamsa; Kemfang, Jean Dupont; Kasia, Jean Marie; Pace, Christophe Di
2014-01-01
L'accouchement gémellaire différé définit un accouchement en deux ou plusieurs temps, avec l'expulsion spontanée d'un premier fœtus au deuxième ou au troisième trimestre, et un prolongement de la grossesse pour obtenir un accouchement du ou des fœtus restants en gestation le plus proche possible du terme. Cette technique est mise en œuvre, en cas de grossesse gémellaire pour prévenir la prématurité du fœtus restant après l'expulsion très prématurée d'un premier fœtus. Nous rapportons deux cas...
Khemiri, Karim; Ben Hmida, Fayçal; Ragot, José; Gossa, Moncef
2008-01-01
International audience Dans cette communication, on propose d'utiliser le filtre de Kalman à deux étages pour estimer l'état et les défauts de systèmes stochastiques à temps variant et à temps discret. Ces défauts sont générés par un processus stochastique et affectent, par des actions additives, l'équation d'état et l'équation de mesure. Deux cas de figure sont analysés. Le premier suppose que les propriétés statistiques du modèle de défaut sont connues, par contre dans le second cas les ...
Exploring the calibration of a wind forecast ensemble for energy applications
Heppelmann, Tobias; Ben Bouallegue, Zied; Theis, Susanne
2015-04-01
In the German research project EWeLiNE, Deutscher Wetterdienst (DWD) and Fraunhofer Institute for Wind Energy and Energy System Technology (IWES) are collaborating with three German Transmission System Operators (TSO) in order to provide the TSOs with improved probabilistic power forecasts. Probabilistic power forecasts are derived from probabilistic weather forecasts, themselves derived from ensemble prediction systems (EPS). Since the considered raw ensemble wind forecasts suffer from underdispersiveness and bias, calibration methods are developed for the correction of the model bias and the ensemble spread bias. The overall aim is to improve the ensemble forecasts such that the uncertainty of the possible weather deployment is depicted by the ensemble spread from the first forecast hours. Additionally, the ensemble members after calibration should remain physically consistent scenarios. We focus on probabilistic hourly wind forecasts with horizon of 21 h delivered by the convection permitting high-resolution ensemble system COSMO-DE-EPS which has become operational in 2012 at DWD. The ensemble consists of 20 ensemble members driven by four different global models. The model area includes whole Germany and parts of Central Europe with a horizontal resolution of 2.8 km and a vertical resolution of 50 model levels. For verification we use wind mast measurements around 100 m height that corresponds to the hub height of wind energy plants that belong to wind farms within the model area. Calibration of the ensemble forecasts can be performed by different statistical methods applied to the raw ensemble output. Here, we explore local bivariate Ensemble Model Output Statistics at individual sites and quantile regression with different predictors. Applying different methods, we already show an improvement of ensemble wind forecasts from COSMO-DE-EPS for energy applications. In addition, an ensemble copula coupling approach transfers the time-dependencies of the raw
Generation of a Solar Wind Ensemble for Space Weather Forecasting
Hassan, E.; Morley, S.; Steinberg, J. T.
2015-12-01
Knowing the upstream solar wind conditions is essential in forecasting the variations in the geomangetic field and the status of the Earth's ionosphere. Most data-driven simulations or data-assimilation codes, used for space weather forecasting, are based on the solar wind measurements at 1 AU, or more specifically at the first Lagrangian orbit (L1), such as observations from the Advanced Composition Explorer (ACE). However, L1 measurements may not represent the solar wind conditions just outside the magnetosphere. As a result, time-series measurements from L1 by themselves are not adequate to run simulations to derive probabilistic forecasts of the magnetosphere and ionosphere. To obtain confidence levels and uncertainty estimates, a solar wind ensemble data set is desirable. Therefore we used three years of measurements atACE advected using the flat delay method to the Interplanetary Monitoring Platform (IMP8) spacecraft location. Then, we compared both measurements to establish Kernel Density Estimation (KDE) functions for IMP8 measurements based on ACE measurements. In addition, we used a 4-categorization scheme to sort the incoming solar wind into ejecta, coronal-hole-origin, sector-reversal-regions, and streamer-belt-origin categories at both ACE and IMP8. We established the KDE functions for each category and compared with the uncategorized KDE functions. The location of the IMP8 spacecraft allows us to use these KDE functions to generate ensemble of solar wind data close to Earth's magnetopause. The ensemble can then be used to forecast the state of the geomagnetic field and the ionosphere.
Ensemble Ionospheric Total Electron Content Forecasting during Storms
Chartier, A.; Mitchell, C. N.; Lu, G.; Anderson, J. L.; Collins, N.; Hoar, T. J.; Bust, G. S.; Matsuo, T.
2014-12-01
Earth's ionosphere presents a threat to human activities such as satellite positioning and timing, radio communications and surveillance. Nowcasts and forecasts of the ionosphere could help mitigate these damaging effects. Recent advances in the field of ionospheric imaging, as well as new storm-time ionospheric forecasting results are presented here. The approach combines globally distributed GPS Total Electron Content (TEC) measurements with an ensemble of coupled thermosphere-ionosphere models in order to produce short-term forecasts during a storm. One-hour forecast accuracy is much better than a climatological model run. Using this ensemble approach, it is possible to infer the neutral O/N2 ratio from TEC measurements so that subsequent TEC forecasts are improved. A review of ionospheric physics and data assimilation will also be given. The term data assimilation refers to a group of techniques designed to estimate atmospheric or oceanic states. In practice, data assimilation techniques seek to improve modeled estimates of the atmospheric state by incorporating observations. The relationship between data assimilation and forecasting is explored with reference to the physics of the thermosphere-ionosphere system. The work presented here uses the Data Assimilation Research Testbed (DART), which is an ensemble Kalman filter data assimilation framework. This is combined with a version of the Thermosphere Ionosphere Electrodynamics General Circulation Model (TIEGCM) that has been modified to accept more detailed solar and geomagnetic driver specifications. Future directions of work include the inference of Solar and geomagnetic drivers from the data assimilation process as well as coupling with lower-atmospheric models.
Local polynomial method for ensemble forecast of time series
Directory of Open Access Journals (Sweden)
S. Regonda
2005-01-01
Full Text Available We present a nonparametric approach based on local polynomial regression for ensemble forecast of time series. The state space is first reconstructed by embedding the univariate time series of the response variable in a space of dimension (D with a delay time (τ. To obtain a forecast from a given time point t, three steps are involved: (i the current state of the system is mapped on to the state space, known as the feature vector, (ii a small number (K=α*n, α=fraction (0,1] of the data, n=data length of neighbors (and their future evolution to the feature vector are identified in the state space, and (iii a polynomial of order p is fitted to the identified neighbors, which is then used for prediction. A suite of parameter combinations (D, τ, α, p is selected based on an objective criterion, called the Generalized Cross Validation (GCV. All of the selected parameter combinations are then used to issue a T-step iterated forecast starting from the current time t, thus generating an ensemble forecast which can be used to obtain the forecast probability density function (PDF. The ensemble approach improves upon the traditional method of providing a single mean forecast by providing the forecast uncertainty. Further, for short noisy data it can provide better forecasts. We demonstrate the utility of this approach on two synthetic (Henon and Lorenz attractors and two real data sets (Great Salt Lake bi-weekly volume and NINO3 index. This framework can also be used to forecast a vector of response variables based on a vector of predictors.
Ensemble approaches to structural seismology: seek many rather than one
Sambridge, M.; Bodin, T.; Tkalcic, H.; Gallagher, K.
2011-12-01
For the past forty years seismologists have built models of the Earth's seismic structure over local, regional and global distance scales using derived quantities of a seismogram covering the frequency spectrum. A feature common to (almost) all cases is the objective of building a single `best' Earth model, in some sense. This is despite the fact that the data by themselves often do not require, or even allow, a single best fit Earth model to exist. It is widely recognized that many seismic inverse problems are ill-posed and non-unique and hence require regularization or additional constraints to obtain a single structural model. Interpretation of optimal models can be fraught with difficulties, particularly when formal uncertainty estimates become heavily dependent on the regularization imposed. An alternative approach is to embrace the non-uniqueness directly and employ an inference process based on parameter space sampling. Instead of seeking a best model within an optimization framework one seeks an ensemble of solutions and derives properties of that ensemble for inspection. While this idea has itself been employed for more than 30 years, it is not commonplace in seismology. Recent work has shown that trans-dimensional and hierarchical sampling methods have some considerable benefits for seismological problems involving multiple parameter types, uncertain data errors and/or uncertain model parameterizations. Rather than being forced to make decisions on parameterization, level of data noise and weights between data types in advance, as is often the case in an optimization framework, these choices can be relaxed and instead constrained by the data themselves. Limitations exist with sampling based approaches in that computational cost is often considered to be high for large scale structural problems, i.e. many unknowns and data. However there are a surprising number of areas where they are now feasible. This presentation will describe recent developments in
The Pierrot Ensembles: Chronicle and Catalogue, 1912-2012
Dromey, Christopher
2012-01-01
2012 is the centenary of the first performance of Arnold Schoenberg’s Pierrot lunaire, Op. 21, and over the last hundred years its mixed chamber ensemble has become, in all its protean forms, a principal line-up for modern music. This book, the first of its kind, chronicles the ensemble’s evolution from Pierrot’s earliest performances, monitoring its influence on the Continent as well as upon Walton, Britten, Lutyens and Searle in Britain. In particular, it watches the growth of The Pierrot P...