An integration experience of a software architecture and a monitoring infrastructure to deploy applications with non‐functional requirements in computing grids

Resource management is an important aspect to consider regarding applications that might have different non‐functional or operational requirements, when running in distributed and heterogeneous environments. In this context, it is necessary to provide the means to specify the required resource constraints and an infrastructure that can adapt the applications in light of the changes in resource availability. We adopted a contract‐based approach to describe and maintain parallel applications that have non‐functional requirements in a Computing Grid context, called ZeliGrid. To form the supporting infrastructure we have designed a software architecture that integrates some of the Globus services, the LDAP and the NWS monitoring services. Some modules that map the contract approach into software artifacts were also integrated to this architecture. This paper addresses the architecture and integration issues of our approach, as well as how we put the pieces together highlighting deployment and implementation details, which have to consider diverse aspects such as monitoring, security and dynamic reconfiguration. Copyright © 2010 John Wiley & Sons, Ltd.     

3D porosity prediction from seismic inversion and neural networks

In this work, we address the problem of transforming seismic reflection data into an intrinsic rock property model. Specifically, we present an application of a methodology that allows interpreters to obtain effective porosity 3D maps from post-stack 3D seismic amplitude data, using measured density and sonic well log data as constraints. In this methodology, a 3D acoustic impedance model is calculated from seismic reflection amplitudes by applying an L₁-norm sparse-spike inversion algorithm in the time domain, followed by a recursive inversion performed in the frequency domain. A 3D low-frequency impedance model is estimated by kriging interpolation of impedance values calculated from well log data. This low-frequency model is added to the inversion result which otherwise provides only a relative numerical scale. To convert acoustic impedance into a single reservoir property, a feed-forward Neural Network (NN) is trained, validated and tested using gamma-ray and acoustic impedance values observed at the well log positions as input and effective porosity values as target. The trained NN is then applied for the whole reservoir volume in order to obtain a 3D effective porosity model. While the particular conclusions drawn from the results obtained in this work cannot be generalized, such results suggest that this workflow can be applied successfully as an aid in reservoir characterization, especially when there is a strong non-linear relationship between effective porosity and acoustic impedance.     

A synergistic model-driven approach for persistence modeling with UML

The Model Driven Development (MDD) approach proposes that models (and model-to-model transformations) play the main role on system development. However, there is not a consensual notation to model persistence based upon object-relational mapping frameworks: while UML lacks specific resources for persistence modeling, the entity-relationship model does not make reference to the dynamic concepts existing in UML.This paper proposes MD-JPA, a UML profile for persistence modeling based on the well-known Java Persistence API 2 (JPA) standard for object-relational mapping, pursuing the modeling of transient and persistent elements in a more coherent and synergistic way. This paper describes the main characteristics of MD-JPA as well as the way that models that adopt such profile can them be used to generate a Java implementation by the application of the proposed model transformations on a MDD approach. Finally, an open source tool was developed to make the results of this work available to the community.     

WCET Analysis of Superscalar Processors Using Simulation With Coloured Petri Nets

Determining a tight WCET of a block of code to be executed on a modern superscalar processor architecture is becoming ever more difficult due to the dynamic behaviour exhibited by current processors, which include dynamic scheduling features such as speculative and out-of-order execution in the context of multiple execution units with deep pipelines. We describe the use of Coloured Petri Nets (CP-nets) in a simulation based approach to this problem. A complex model of a generic processor architecture is described, with emphasis on the modelling strategy for obtaining the WCET and an analysis of the results.     

Contribution of laser microdissection-based technology to proteomic analysis in hepatocellular carcinoma developing on cirrhosis

Hepatocellular carcinoma (HCC) is a major cause of cancer worldwide. Proteomic studies provide opportunities to uncover targets for the diagnosis and treatment of this disease. However, in HCC developing in a setting of cirrhosis, the detection of proteome alterations may be hampered by the increased cellular heterogeneity of tissue when analysing global liver homogenates. The aim of this study was to evaluate whether the identification of proteome alterations in these HCC cases was improved when the differential protein profile between tumour and non-tumour areas of liver was determined using hepatocytes isolated by laser microdissection (LM). Differential profiles established with LM-hepatocytes and liver section homogenates using 2-DE and MS exhibited noticeable differences: 30% of the protein spots with deregulated expression in tumorous LM-samples did not display any modification in homogenates; conversely 15% of proteins altered in tumorous homogenates were not impaired in LM-hepatocytes. These alterations resulted from the presence in cirrhotic liver of fibrotic stroma which displayed a protein pattern different from that determined in LM-hepatocytes. In conclusion, our data demonstrate the interest of LM in distinguishing between fibrotic and hepatocyte proteome alterations and thus the benefit of LM to proteome studies of HCC developing in a context of cirrhosis.     

Étude de la précision de l’estimation de la densité spectrale de puissance croisée,obtenue par transformation de fourier de la fonction de corrélation

The authors compare two different estimators of the crosscorrelation function and show that they give equivalent estimators in the frequency domain. They calculate the first and second order moments of the estimator of the cross-spectral-density (DSPC)due to the statistical errors and the quantification of inputs. From these general formulas, they perform numerical calculations for a particular case and they compare them to practical measurements. They show the interesting fact, that the variance of the statistical errors on the dspc is inferior by estimating its phase than by estimating its module. Furthermore, the quantification of the inputs may influence the variance of the phase of the DSPC estimated.     

FISH ASSEMBLAGES IN NON‐REGULATED AND REGULATED RIVERS FROM PERMANENT AND TEMPORARY IBERIAN SYSTEMS

The effects of river regulation on the hydrological cycle of a river and on the respective fish assemblage may differ according to dam operation purpose and type of river analysed. To assess the spatial and temporal variation of fish assemblages and their response to the hydrological changes caused by two different types of flow regulation, we selected three sampling sites in four rivers with different levels of regulation, two in a permanent river system and another two on a temporary one, which we sampled in four different annual seasons. In the permanent system, hydroelectrical regulation decreased hydrological variability, which affected fluvial specialist species, benefitting the generalist ones, and created a more homogeneous community that presented less intra‐annual variation. In the temporary system, agricultural regulation caused an inversion of the hydrological cycle, maintaining a moderate flow volume throughout the drought period that benefited the introduced, generalist and more tolerant species. Monthly volume was recognized, in a temporal scale, as the most important hydrological feature for assemblages’ structure, predicting the intra‐annual variation of several ecological guilds. This study provides important considerations for dam management and riverine ecosystems conservation. Copyright © 2012 John Wiley & Sons, Ltd.     

A new robust algorithmic for multi-camera calibration with a 1D object under general motions without prior knowledge of any camera intrinsic parameter

In computer vision, camera calibration is a necessary process when the retrieval of information such as angles and distances is required. This paper addresses the multi-camera calibration problem with a single dimension calibration pattern under general motions. Currently, the known algorithms for solving this problem are based on the estimation of vanishing points. However, this estimate is very susceptible to noise, making the methods unsuitable for practical applications. Instead, this paper presents a new calibration algorithm, where the cameras are divided into binocular sets. The fundamental matrix of each binocular set is then estimated, allowing to perform a projective calibration of each camera. Then, the calibration is updated for the Euclidean space, ending the process. The calibration is possible without imposing any restrictions on the movement of the pattern and without any prior information about the cameras or motion. Experiments on synthetic and real images validate the new method and show that its accuracy makes it suitable also for practical applications.     

Corrosion of amorphous and nanocrystalline Fe-based alloys and its influence on their magnetic behavior

Nanocrystalline soft magnetic materials with low coercivity, high saturation magnetization and high permeability are commonly used as cores in transformers and generators in stress and field sensors. The influence of factors connected with corrosion is almost impossible to eliminate. In the present work, a comparative study of the electrochemical behavior of Fe₇₈Si₁₃B₉ and Fe_73.5Si_13.5B₉Nb₃Cu₁ amorphous and nanocrystallized alloys, tested in 0.5 M NaCl solution, has been performed by linear polarization and electrochemical impedance spectroscopy methods. Changes of magnetic properties including coercivity, induction and magnetic retentivity were analyzed. These properties were investigated as a function of the structure of primary amorphous ribbons and as a function of corrosion environment type, in which longitudinally and transversely cut ribbon specimens were exposed for 15 days. The best magnetic properties were found for the Fe₇₈Si₉B₁₃ ribbon after a structural relaxation at a temperature of 350 °C for an hour and for the Fe_73.5Si_13.5B₉Nb₃Cu₁ ribbon after a primary crystallization at a temperature of 550 °C for an hour. Corrosion did not cause the direct degradation of the magnetic properties of the Fe₇₈Si₉B₁₃ and Fe_73.5Si_13.5B₉Nb₃Cu₁ alloys. The corrosion processes occurring on the surface of the Fe_73.5Si_13.5B₉Nb₃Cu₁ alloy ribbon with the amorphous structures improve induction B_s. Most probably it is connected with the decrease of undesirable stresses blocking a motion of magnetic domain walls on the ribbon surface. Changes of corrosion mechanism depending on structure and applied solution were analyzed. The electrochemical impedance experiment were performed at open circuit potential for amorphous and nanocrystalline specimens. Two electrochemical corrosion mechanisms of Fe_73.5Si_13.5B₉Nb₃Cu₁ alloy in 0.5 M NaCl solution were found. Charge transfer control mechanism is typical for amorphous (as received) alloys. Mixed mechanism-mass transport and charge transfer controlled was observed for nanocrystalline Fe_73.5Si_13.5B₉Nb₃Cu₁ alloy.