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Mendoza, Argentina

The University of Mendoza is an Argentine non-profit private university in the city of Mendoza with a branch in the city of San Rafael. Wikipedia.

Schluter F.,University of Mendoza
Artificial Intelligence Review | Year: 2012

The problem of learning the Markov network structure from data has become increasingly important in machine learning, and in many other application fields. Markov networks are probabilistic graphical models, a widely used formalism for handling probability distributions in intelligent systems. This document focuses on a technology called independence-based learning, which allows for the learning of the independence structure of Markov networks from data in an efficient and sound manner, whenever the dataset is sufficiently large, and data is a representative sample of the target distribution. In the analysis of such technology, this work surveys the current state-of-the-art algorithms, discussing its limitations, and posing a series of open problems where future work may produce some advances in the area, in terms of quality and efficiency. © 2012 Springer Science+Business Media B.V. Source

Gao Y.,University of Kaiserslautern | Ruestes C.J.,National University of Cuyo | Tramontina D.R.,National University of Cuyo | Tramontina D.R.,University of Mendoza | Urbassek H.M.,University of Kaiserslautern
Journal of the Mechanics and Physics of Solids | Year: 2014

Using molecular-dynamics simulation, we study nanoindentation in fcc (Cu and Al) and bcc (Fe and Ta) metals by a spherical indenter and investigate the size of the plastic zone generated. We find that while it does not strongly depend on crystal structure, surface orientation, and indentation parameters, the extent of the plastic zone is substantially larger before the retraction of the indenter. After retraction, the results are in good agreement with available published data. Plasticity develops by the generation, propagation and reaction of dislocations; they fall into two groups, those that adhere to the indentation pit, and those that have been emitted either into the substrate interior or glide along the surface. The total length of the dislocation network generated roughly follows available geometrical estimates; results for individual surface orientations may, however, differ quite strongly. The radial distribution of the dislocations attached to the indentation pit is computed; as a rule it shows a maximum at some depth below the indentation pit. © 2014 Elsevier Ltd. Source

Gonzalez R.,University of Mendoza | Giribet J.I.,University of Buenos Aires | Patino H.D.,National University of San Juan
Mathematical and Computer Modelling of Dynamical Systems | Year: 2015

New solutions to the navigation problem related to low-cost integrated navigation systems (INS) are often published. Since these new solutions are generally compared with ad hoc mathematical models that are not fully exposed, one cannot be sure of the relative improvements. In this work, complete mathematical model for a low-cost INS is suggested to be used as a benchmarking. As far as the authors’ knowledge, a benchmarking for low-cost INS has not been previously reported. Shown INS comprises a strapdown inertial navigation system, loosely coupled to a GPS receiver. The INS mathematical model is based upon classical navigation equations and classical sensor models, both from recognized authors. The algorithm that details the INS operation is also presented. The benchmarking is provided as an open-source toolbox for MATLAB. Additionally, this work can be taken as a starting point for new practitioners in the INS field. To validate the INS mathematical model, real-world data sets from three different Micro Electro-Mechanical Systems (MEMS) inertial measurement units (IMU) and a GPS receiver are processed. It is observed that obtained RMS errors from the three INS are coherent with the quality of corresponding MEMS IMU. This confirms that the proposed benchmarking is a suitable tool to evaluate objectively new solutions to low-cost INS. © 2014, © 2014 Taylor & Francis. Source

Mercante I.T.,National University of Cuyo | Bovea M.D.,Jaume I University | Ibanez-Fores V.,Jaume I University | Arena A.P.,University of Mendoza
International Journal of Life Cycle Assessment | Year: 2012

Purpose The aim of this study is to develop and analyse a life cycle inventory of construction and demolition waste (C&DW) management systems based on primary data collected directly from Spanish enterprises involved in the life cycle of this type of waste material. Special emphasis is placed on assessing the environmental profile of inert waste sorting and treatment (IWST) facilities. Methods Taking the management of 1 t of C&DW as the functional unit, this study describes the boundaries of the C&DW management system and the scope of the research, which includes all stages from the temporary storage of waste in containers to its recovery or disposal on landfills. Primary data were collected directly from some Spanish enterprises involved in the life cycle of C&DW management: two firms that manufacture containers and bags, two companies responsible for the temporary storage of waste and transporting it, five firms devoted to sorting and treating the waste and two enterprises that operate inert landfills. Special attention was given to the IWST facilities, whose inventory data were related to four phases: pre-treatment and the primary, secondary and tertiary sectors. Finally, indicators were obtained for different impact categories. Results The environmental profiles of IWST facilities for mixed C&DW show that the greatest environmental impacts are produced in primary and tertiary sectors. From the life cycle analysis of C&DW management, it can be seen that transport, sorting and disposal make a net contribution to the environmental impact. Savings are due to the recycling of plastics, metals, aggregates and wood for all the impact assessment categories, except global warming in the case of wood and cardboard. Conclusions Impact of IWST can be reduced by selective collection at source, since it avoids the separation of light fractions at plants. Life cycle assessment of C&DW shows that transportation stage plays a decisive role and recycling is not always beneficial. © 2011 Springer-Verlag. Source

Agosta E.,CONICET | Canziani P.,CONICET | Cavagnaro M.,Equipo Interdisciplinario para el Estudio de Procesos Atmosfericos en el Cambio Global | Cavagnaro M.,University of Mendoza
Journal of Applied Meteorology and Climatology | Year: 2012

Mendoza Province is the major Argentinian vitivinicultural region, and its grape production is fundamental for the national vintage. The 1979-2009 climate-annual grape yield relationships are analyzed, and total grape yield is shown to depend significantly on regional "summer"(October-March) precipitation. Precipitation negatively affects yields through plant disease and damage/destruction by hail. At interannual scales, summer regional precipitation variability can explains 25% of the yield variance. Summer precipitation modulates yield with a 6-8-yr period: wet (dry) summers can be associated with larger (smaller) grape damage/loss probability during the summer preceding the vintage, as well as lower (higher) grape yields in the subsequent annual campaign because of bud damage. With respect tomonthlymean precipitation atMendozaObservatory, wetter Novembers/Decembers can lead to lower yields. Hail during the summer of the previous harvest and during December could lower yields.Winter, late spring, and early summer mean maximum temperatures can impact current and subsequent annual yields: warmer (colder) months are linked to enhanced (decreased) yields. These relationships can be associated with circulation and SST conditions in the equatorial and extratropical Pacific Ocean basin and southern South America: SSTs within the southeastern South Pacific are related to western equatorial Pacific SSTs and convection, which modify circulation and water vapor transport over southern South America. Statistical multilinear modeling shows that the observed relationships among yield, precipitation, and temperature can explain at least 60%of the observed interannual yield variability. It is thus possible to quantitatively estimate, some months in advance, the upcoming vintage's yield. © 2012 American Meteorological Society. Source

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