The Hierarchical Agglomerative Clustering with Gower index: a methodology for automatic design of OLAP cube in ecological data processing context

International audienceThe OLAP systems can be an improvement for ecological studies. In fact, ecology studies, follows and analyzes phenomenon across space and time and according to several parameters. OLAP systems can provide to ecologists browsing in a large dataset. One focus of the current research on OLAP system is the automatic design of OLAP cubes and of data warehouse schemas. This kind of works makes accessible OLAP technology to non information technology experts. But to be efficient, the automatic OLAP building must take into account various cases. Moreover the OLAP technology is based on the concept of hierarchy. Thereby the hierarchical clustering methods are often used by OLAP system designer. In this article, we propose using hierarchical agglomerative clustering with a metric that comes from ecological studies (the Gower similarity index) to build automatically hierarchical dimensions in an OLAP cube. With this similarity index we can perform a hierarchical clustering on heterogeneous datasets that contains qualitative and quantitative variables. We offer a prototypical automatic system which builds dimension for an OLAP cube and we measure the performances of this system according to the number of clustered individuals and according to the number of variables used for clustering. Thanks to these measures we can offer an approximation of performances with a large dataset. Thereby the Gower index in a hierarchical agglomerative clustering permits the management of heterogeneous dataset with missing values in a context of automatic building of OLAP cube. With this methodology, we can build new dimensions based on hierarchies in the data, which are not evident. The data mining methods can complete the expert knowledge during the design of an OLAP cube, because these methods can explain the inherent structure of the data

Une nouvelle approche mixte d'enrichissement de dimensions dans un schéma multidimensionnel en constellation Application à la biodiversité des oiseaux

International audienceLes entrepôts de données (DW) et les systèmes OLAP sont des technologies d'analyse en ligne pour de grands volumes de données, basés sur les be-soins des utilisateurs. Leur succès dépend essentiellement de la phase de conception où les exigences fonctionnelles sont confrontées aux sources de données (méthodologie de conception mixte). Cependant, les méthodes de conception existantes semblent parfois inefficaces, lorsque les décideurs définissent des exi-gences fonctionnelles qui ne peuvent être déduites à partir des sources de don-nées (approche centrée sur les données), ou lorsque le décideur n'a pas intégré tous ces besoins durant la phase de conception (approche centrée sur l'utilisa-teur). Cet article propose une nouvelle méthodologie mixte d'enrichissement de schémas en constellation, où l'approche classique de conception est améliorée grâce à la fouille de données dans le but de créer de nouvelles hiérarchies au sein d'une dimension. Un prototype associé est également présenté

3D image acquisition system based on shape from focus technique

agent Agrosup Dijon de l'UMREcolDurGEAPSIThis paper describes the design of a 3D image acquisition system dedicated to natural complex scenes composed of randomly distributed objects with spatial discontinuities. In agronomic sciences, the 3D acquisition of natural scene is difficult due to the complex nature of the scenes. Our system is based on the Shape from Focus technique initially used in the microscopic domain. We propose to adapt this technique to the macroscopic domain and we detail the system as well as the image processing used to perform such technique. The Shape from Focus technique is a monocular and passive 3D acquisition method that resolves the occlusion problem affecting the multi-cameras systems. Indeed, this problem occurs frequently in natural complex scenes like agronomic scenes. The depth information is obtained by acting on optical parameters and mainly the depth of field. A focus measure is applied on a 2D image stack previously acquired by the system. When this focus measure is performed, we can create the depth map of the scene

Enrichissement de schéma multidimensionnel en constellation grâce à la Classification Ascendante Hiérarchique

National audienceLes hiérarchies sont des structures cruciales dans un entrepôt de don-nées puisqu'elles permettent l'agrégation de mesures dans le but de proposer une vue analytique plus ou moins globale sur les données entreposées, selon le niveau hiérarchique auquel on se place. Cependant, peu de travaux s'intéressent à la construction de hiérarchies, via un algorithme de fouille de données, pre-nant en compte le contexte multidimensionnel de la dimension concernée. Dans cet article, nous proposons donc un algorithme, implémenté sur une architecture ROLAP, permettant d'enrichir une dimension avec des données factuelles

Etude et modélisation du comportement des gouttelettes de produits phytosanitaires sur les feuilles de vignes par imagerie ultra-rapide et analyse de texture

Dans le contexte actuel de diminution des pollutions d origine agricole, laréduction des apports d intrants devient un enjeu primordial. En France, laviticulture est l activité qui possède le taux le plus important de traitementsphytosanitaires par unité de surface. Elle représente, à elle seule, 20% de laconsommation annuelle de pesticides. Par conséquent, il est nécessaire d étudierle devenir des pesticides appliqués afin de réduire les quantités perduesdans l environnement. Dans le cadre de la réduction d apport de produitsphytosanitaires dans les vignes, de nombreux travaux ont été effectués sur lamodélisation du comportement d un spray de gouttelettes et sa répartitionau niveau de la parcelle et de l air environnant. Cependant, il est égalementimportant de s intéresser au comportement de la gouttelette directement auniveau de la feuille. Les progrès dans le domaine de l imagerie et la diminutiondu coût des systèmes ont rendus ces systèmes beaucoup plus attractifs.Le travail de cette thèse consiste en la mise en place d un système d imagerierapide qui permet l observation du comportement à l impact de gouttelettesrépondant aux conditions de pulvérisation. Les caractéristiques ainsi que lecomportement associé de chaque gouttelette sont extraits grâce à une méthodede suivi d objets. Une analyse statistique basée sur un nombre représentatifde résultats permet ensuite d évaluer de manière robuste le devenir d unegoutte en fonction de ses caractéristiques. Parallèlement, un paramètre décrivantl état de surface de la feuille est également étudié grâce à l imagerie : larugosité qui joue un rôle prédominant dans la compréhension des mécanismesd adhésionIn the domain of vineyard precision spraying research, one of the most importantobjectives is to minimize the volume of phytosanitary products ejected bya sprayer in order to be more environmentally respectful with more effectivevine leaf treatments. Unfortunaltely, even if lot of works have been carriedout at a parcel scale, mainly on losses caused by drift, less works have beencarried out at the leaf scale in order to understand which parameters influencethe spray quality. Since few years, recent improvements in image processing,sensitivity of imaging systems and cost reduction have increased the interestof high-speed imaging techniques. Analyzing the behavior of droplets afterimpact with the leaf thanks to high speed imaging technology is a relevantsolution. By this way, we propose a droplets behavior analyzing process invineyard spraying context based on high-speed acquision system combinedwith image processing techniques. This process allows us to extract dropletsparameters. Therefore, a statistical study is processed in order to determinethe effects of droplets parameters on leaf impact or to predict behavior of asingle droplet. Since this behavior is strongly related to leaf surface, we alsopropose to validate a natural leaf roughness characterization method basedon texture analysisDIJON-BU Doc.électronique (212319901) / SudocSudocFranceF

Large-scale nonlinear dimensionality reduction for network intrusion detection

International audienceNetwork intrusion detection (NID) is a complex classification problem. In this paper, we combine classification with recent and scalable nonlinear dimensionality reduction (NLDR) methods. Classification and DR are not necessarily adversarial, provided adequate cluster magnification occurring in NLDR methods like $t$-SNE: DR mitigates the curse of dimensionality, while cluster magnification can maintain class separability. We demonstrate experimentally the effectiveness of the approach by analyzing and comparing results on the big KDD99 dataset, using both NLDR quality assessment and classification rate for SVMs and random forests. Since data involves features of mixed types (numerical and categorical), the use of Gower's similarity coefficient as metric further improves the results over the classical similarity metric

Synergetic-methodological analysis of contemporary geopolitical scenarios and risks / Y. S. Yaskevich

Выявляются философские основания современных геополитических сценариев и рисков в пространстве синергетической методологии. Обосновывается тезис о том, что методологический анализ геостратегий и рискогенности общества постмодерна следует проводить в контексте интеграции национальных государств в мировое экономическое и политическое сообщество с учетом приоритетов национальной безопасности, суверенитета отдельных стран, ответственности за принимаемые решения на глобальном и национальном уровнях. = Substantial models of modern geopolitical scenarios in space of synergetic methodology and a riskiness of modern society are considered. The thesis that the methodological analysis of geopolitical scenarios and risks should be carried out in the context of integration of the national states into world economic and political community taking into account priorities of national security, the sovereignty of the certain countries, responsibility for the made decisions at the global and national levels locates

Improvements of image processing for wheat ear counting

peer reviewedOne of the most important activity of agricultural research insititutes concerns the agronomical experiments done under different conditions needing many land observations and valuations to quantify several variables. These observations, although generally accurate, are visually done by the agriculturist technicians and present numerous drawbacks: penibility, weak productivity, numerous labor force, limited sampling … Two feasibility studies lead in our laboratory recently have shown that some of the previous observations, and particularly the counting of the number of wheat ear per m², can be done by color and/or texture image processing for images taken directly in the field with a specific acquisition system. This paper describes the improvements of the previous studies concerning the image acquisition system, and especially the illumination control, and the justification of different hypothesis on the number of classes to detect in an image. The use of a cluster validity index has allowed to prove that 3 classes to determine all the objects in a wheat ear image are not sufficient. A correlation with a study based on the size of the analysis window is currently under investigation to improve the ear detection, which is now of 6%, compared to manual counting done by agriculturist technicians

A semi-automatic design methodology for (Big) Data Warehouse transforming facts into dimensions

International audienceA decision support system is used by decision makers for a long time. But, in some cases, the originally designed multidimensional schema does not cover the entire needs of decision makers, which can change over time. One such unfulfilled needs, is using facts to describe dimension members. In this article, we propose a methodology to transform the constellation schema of a data warehouse by integrating factual data into a dimension. The proposed methodology and algorithms enrich a constellation multidimensional schema with new analytical possibilities for decision makers. This enrichment has repercussions for the entire multidimensional schema that are managed by multidimensional modeling, hierarchy calculation and the hierarchy version. In this article, we present a theoretical view of the proposed methodology supported by a case study, an implemented prototype and a complete evaluation based on a standard benchmark