967 resultados para ZTA,Zero Trust,Microsegmentazione,Sicurezza,Scalabilità,Overlay network


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We study the spreading of contagious diseases in a population of constant size using susceptible-infective-recovered (SIR) models described in terms of ordinary differential equations (ODEs) and probabilistic cellular automata (PCA). In the PCA model, each individual (represented by a cell in the lattice) is mainly locally connected to others. We investigate how the topological properties of the random network representing contacts among individuals influence the transient behavior and the permanent regime of the epidemiological system described by ODE and PCA. Our main conclusions are: (1) the basic reproduction number (commonly called R(0)) related to a disease propagation in a population cannot be uniquely determined from some features of transient behavior of the infective group; (2) R(0) cannot be associated to a unique combination of clustering coefficient and average shortest path length characterizing the contact network. We discuss how these results can embarrass the specification of control strategies for combating disease propagations. (C) 2009 Elsevier B.V. All rights reserved.

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Second-order phase locked loops (PLLs) are devices that are able to provide synchronization between the nodes in a network even under severe quality restrictions in the signal propagation. Consequently, they are widely used in telecommunication and control. Conventional master-slave (M-S) clock-distribution systems are being, replaced by mutually connected (MC) ones due to their good potential to be used in new types of application such as wireless sensor networks, distributed computation and communication systems. Here, by using an analytical reasoning, a nonlinear algebraic system of equations is proposed to establish the existence conditions for the synchronous state in an MC PLL network. Numerical experiments confirm the analytical results and provide ideas about how the network parameters affect the reachability of the synchronous state. The phase-difference oscillation amplitudes are related to the node parameters helping to design PLL neural networks. Furthermore, estimation of the acquisition time depending on the node parameters allows the performance evaluation of time distribution systems and neural networks based on phase-locked techniques. (c) 2008 Elsevier GmbH. All rights reserved.

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The discrete-time neural network proposed by Hopfield can be used for storing and recognizing binary patterns. Here, we investigate how the performance of this network on pattern recognition task is altered when neurons are removed and the weights of the synapses corresponding to these deleted neurons are divided among the remaining synapses. Five distinct ways of distributing such weights are evaluated. We speculate how this numerical work about synaptic compensation may help to guide experimental studies on memory rehabilitation interventions.

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The competition among the companies depends on the velocity and efficience they can create and commercialize knowledge in a timely and cost-efficient manner. In this context, collaboration emerges as a reaction to the environmental changes. Although strategic alliances and networks have been exploited in the strategic literature for decades, the complexity and continuous usage of these cooperation structures, in a world of growing competition, justify the continuous interest in both themes. This article presents a scanning of the contemporary academic production in strategic alliances and networks, covering the period from January 1997 to august 2007, based on the top five journals accordingly to the journal of Citation Report 2006 in the business and management categories simultaneously. The results point to a retraction in publications about strategic alliances and a significant growth in the area of strategic. networks. The joint view of strategic alliances and networks, cited by some authors a the evolutionary path of study, still did not appear salient. The most cited topics found in the alliance literature are the governance structure, cooperation, knowledge transfer, culture, control, trust, alliance formation,,previous experience, resources, competition and partner selection. The theme network focuses mainly on structure, knowledge transfer and social network, while the joint vision is highly concentrated in: the subjects of alliance formation and the governance choice.

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The zero-inflated negative binomial model is used to account for overdispersion detected in data that are initially analyzed under the zero-Inflated Poisson model A frequentist analysis a jackknife estimator and a non-parametric bootstrap for parameter estimation of zero-inflated negative binomial regression models are considered In addition an EM-type algorithm is developed for performing maximum likelihood estimation Then the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes and some ways to perform global influence analysis are derived In order to study departures from the error assumption as well as the presence of outliers residual analysis based on the standardized Pearson residuals is discussed The relevance of the approach is illustrated with a real data set where It is shown that zero-inflated negative binomial regression models seems to fit the data better than the Poisson counterpart (C) 2010 Elsevier B V All rights reserved

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Hydrochemical processes involved in the development of hydromorphic Podzols are a major concern for the upper Amazon Basin because of the extent of the areas affected by such processes and the large amounts of organic carbon and associated metals exported to the rivers. The dynamics and chemical composition of ground and surface waters were studied along an Acrisol-Podzol sequence lying in an open depression of a plateau. Water levels were monitored along the sequence over a period of 2 years by means of piezometers. Water was sampled in zero-tension lysimeters for groundwater and for surface water in the drainage network of the depression. The pH and concentrations of organic carbon and major elements (Si, Fe and Al) were determined. The contrasted changes reported for concentrations of Si, organic carbon and metals (Fe, Al) mainly reflect the dynamics of the groundwater and the weathering conditions that prevail in the soils. Iron is released by the reductive dissolution of Fe oxides, mostly in the Bg horizons of the upslope Acrisols. It moves laterally under the control of hydraulic gradients and migrates through the iron-depleted Podzols where it is exported to the river network. Aluminium is released from the dissolution of Al-bearing minerals (gibbsite and kaolinite) at the margin of the podzolic area but is immobilized as organo-Al complexes in spodic horizons. In downslope positions, the quick recharge of the groundwater and large release of organic compounds lead to acidification and a loss of metals (mainly Al), previously stored in the Podzols.

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Blends of soybean oil (SO) and fully hydrogenated soybean oil (FHSBO), with 10, 20, 30, 40, and 50% (w/w) FHSBO content were interesterified under the following conditions: 20 min reaction time, 0.4% sodium methoxide catalyst, and 500 rpm stirring speed, at 100 A degrees C. The original and interesterified blends were examined for triacylglycerol composition, thermal behavior, microstructure, crystallization kinetics, and polymorphism. Interesterification produced substantial rearrangement of the triacylglycerol species in all the blends, reduction of trisaturated triacylglycerol content and increase in monounsaturated-disaturated and diunsaturated-monosaturated triacylglycerols. Evaluation of thermal behavior parameters showed linear relations with FHSBO content in the original blends. Blend melting and crystallization thermograms were significantly modified by the randomization. Interesterification caused significant reductions in maximum crystal diameter in all blends, in addition to modifying crystal morphology. Characterization of crystallization kinetics revealed that crystal formation induction period (tau (SFC)) and maximum solid fat content (SFC(max)) were altered according to FHSBO content in the original blends and as a result of the random rearrangement. Changes in Avrami constant (k) and exponent (n) indicated, respectively, that-as compared with the original blends-interesterification decreased crystallization velocities and modified crystallization processes, altering crystalline morphology and nucleation mechanism. X-ray diffraction analyses revealed that interesterification altered crystalline polymorphism. The interesterified blends showed a predominance of the beta` polymorph, which is of more interest for food applications.

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Blends of soybean oil (50) and fully hydrogenated soybean oil (FHSBO), with 10%, 20%, 30%, 40% and 50% FHSBO (w/w) content were interesterified under the following conditions: 0.4% sodium methoxide, 500 rpm stirring, 100 degrees C, 20 min. The original and interesterified blends were examined for triacylglycerol composition, melting point, solid fat content (SFC) and consistency. Interesterification caused considerable rearrangement of triacylglycerol species, reduction of trisaturated triacylglycerol content and increase in monounsaturated and diunsaturated triacylglycerols, resulting in lowering of respective melting points. The interesterified blends displayed reduced SFC at all temperatures and more linear melting profiles as compared with the original blends. Yield values showed increased plasticity in the blends after the reaction. Isosolid diagrams before and after the reaction showed no eutectic interactions. The 90:10, 80:20, 70:30 and 60:40 interesterified SO:FHSBO blends displayed characteristics suited to application, respectively, as liquid shortening, table margarine, baking/confectionery fat and all-purpose shortenings/biscuit-filing base. (C) 2009 Elsevier Ltd. All rights reserved.

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The Brazilian Network of Food Data Systems (BRASILFOODS) has been keeping the Brazilian Food Composition Database-USP (TBCA-USP) (http://www.fcf.usp.br/tabela) since 1998. Besides the constant compilation, analysis and update work in the database, the network tries to innovate through the introduction of food information that may contribute to decrease the risk for non-transmissible chronic diseases, such as the profile of carbohydrates and flavonoids in foods. In 2008, data on carbohydrates, individually analyzed, of 112 foods, and 41 data related to the glycemic response produced by foods widely consumed in the country were included in the TBCA-USP. Data (773) about the different flavonoid subclasses of 197 Brazilian foods were compiled and the quality of each data was evaluated according to the USDAs data quality evaluation system. In 2007, BRASILFOODS/USP and INFOODS/FAO organized the 7th International Food Data Conference ""Food Composition and Biodiversity"". This conference was a unique opportunity for interaction between renowned researchers and participants from several countries and it allowed the discussion of aspects that may improve the food composition area. During the period, the LATINFOODS Regional Technical Compilation Committee and BRASILFOODS disseminated to Latin America the Form and Manual for Data Compilation, version 2009, ministered a Food Composition Data Compilation course and developed many activities related to data production and compilation. (C) 2010 Elsevier Inc. All rights reserved.

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Brazilian social thought draws on the inspiration of past masters the common denominator of whose work is probably a deep humanism. Confronting the challenges of a fluid, ever-changing reality is now a matter of survival. The idea of climate change has made the environment, long relegated to second place, a matter of much wider interest and concern. The other great problem is poverty, and here, while there have been undeniable advances, much remains to be done. The main challenge is producing forms of social organization that will allow ordinary citizens to have an impact on what really matters. Developing policy in these areas has engaged the efforts of a wide range of experts from a variety of fields. Whereas university-educated intellectuals once formed an intelligentsia, today they are engaged in practical politics and much more often function as agents who link social actors together than as mere elaborators of theories.

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The concept of the virtual organization (VO) has engendered great interest in the literature, yet there is still little common understanding of the concept, as evidenced by the multitude of labels applied to VOs. In this article, we focus on a “Weberian-ideal-type” definition of the interorganizational VO, posited in our earlier work (Kasper-Fuehrer and Ashkanasy 2001). We argue, however, that this definition left unanswered critical questions relating to the nature and effects of interorganizational VOs. We answer these questions here by explicating the terms in the definition and deriving ten corollaries, or “natural consequences” of our definition. The corollaries posit that interorganizational VOs are temporary in nature, are network organizations, are independent, and are based on swift trust. We suggest further that interorganizational VOs enable small to medium enterprises to exploit market opportunities, and enable VO member organizations to create a value-adding partnership. We also identify information and communication technology (ICT) as the essential enabler of VOs. Finally, we argue that interorganizational VOs act as a single organizational unit and that they therefore constitute a uniquely distinguishable organizational form. We conclude with suggestions for further research, including trust, organizational behavior, transaction economics, virtual HRM, and business strategy.

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This paper discusses a multi-layer feedforward (MLF) neural network incident detection model that was developed and evaluated using field data. In contrast to published neural network incident detection models which relied on simulated or limited field data for model development and testing, the model described in this paper was trained and tested on a real-world data set of 100 incidents. The model uses speed, flow and occupancy data measured at dual stations, averaged across all lanes and only from time interval t. The off-line performance of the model is reported under both incident and non-incident conditions. The incident detection performance of the model is reported based on a validation-test data set of 40 incidents that were independent of the 60 incidents used for training. The false alarm rates of the model are evaluated based on non-incident data that were collected from a freeway section which was video-taped for a period of 33 days. A comparative evaluation between the neural network model and the incident detection model in operation on Melbourne's freeways is also presented. The results of the comparative performance evaluation clearly demonstrate the substantial improvement in incident detection performance obtained by the neural network model. The paper also presents additional results that demonstrate how improvements in model performance can be achieved using variable decision thresholds. Finally, the model's fault-tolerance under conditions of corrupt or missing data is investigated and the impact of loop detector failure/malfunction on the performance of the trained model is evaluated and discussed. The results presented in this paper provide a comprehensive evaluation of the developed model and confirm that neural network models can provide fast and reliable incident detection on freeways. (C) 1997 Elsevier Science Ltd. All rights reserved.