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Fabrizio Martinelli's CV. Created with the AltaCV template

Este trabajo presenta la aplicación de un conjunto de articulos con propias teorías de los robots manipuladores y el modelamiento de pinzas. Para ello el brazo humano se modela como un robot manipulador redundante. En particular se aplica el concepto de índices de desempeño para predecir posturas óptimas del brazo durante la realización de tareas. En el estudio se incluyen tanto estructuras estáticas, como tambien los analisis de estabilidad del brazo y los materiales para su respectiva realizacion. This work presents the application of a set of articles with the own theories of the manipulative robots and the modeling of tweezers. For this, the bearing is modeled as a redundant manipulator robot. In particular, the concept of performance indices is applied to predict the optimal postures of the task during the performance of tasks. The study includes both static structures, as well as safety management analyzes and materials for their respective realization.

My resume. Created with the AltaCV template.

Vijayaragava's CV, created with the AltaCV template.

K.M. Imrul Kayes Sikdar's CV

Neeraj Giri's CV, created with the AltaCV template.

About Adversarial Machine Learning

A Template for "How to create a WiFi account" with Re2o Created by Hugo 'klafyvel' Levy-Falk Adapted from LianTze Lim's poster Images belong to their authors. Distributed under Creative Commons CC BY 4.0

The efficiency of a query execution plan depends on the accuracy of the selectivity estimates given to the query optimiser by the cost model. The cost model makes simplifying assumptions in order to produce said estimates in a timely manner. These assumptions lead to selectivity estimation errors that have dramatic effects on the quality of the resulting query execution plans. A convenient assumption that is ubiquitous among current cost models is to assume that attributes are independent with each other. However, it ignores potential correlations which can have a huge negative impact on the accuracy of the cost model. In this paper we attempt to relax the attribute value independence assumption without unreasonably deteriorating the accuracy of the cost model. We propose a novel approach based on a particular type of Bayesian networks called Chow-Liu trees to approximate the distribution of attribute values inside each relation of a database. Our results on the TPC-DS benchmark show that our method is an order of magnitude. more precise than other approaches whilst remaining reasonably efficient in terms of time and space.