898 resultados para strong consistency


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2000 Mathematics Subject Classification: Primary: 62M10, 62J02, 62F12, 62M05, 62P05, 62P10; secondary: 60G46, 60F15.

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In just a few years cloud computing has become a very popular paradigm and a business success story, with storage being one of the key features. To achieve high data availability, cloud storage services rely on replication. In this context, one major challenge is data consistency. In contrast to traditional approaches that are mostly based on strong consistency, many cloud storage services opt for weaker consistency models in order to achieve better availability and performance. This comes at the cost of a high probability of stale data being read, as the replicas involved in the reads may not always have the most recent write. In this paper, we propose a novel approach, named Harmony, which adaptively tunes the consistency level at run-time according to the application requirements. The key idea behind Harmony is an intelligent estimation model of stale reads, allowing to elastically scale up or down the number of replicas involved in read operations to maintain a low (possibly zero) tolerable fraction of stale reads. As a result, Harmony can meet the desired consistency of the applications while achieving good performance. We have implemented Harmony and performed extensive evaluations with the Cassandra cloud storage on Grid?5000 testbed and on Amazon EC2. The results show that Harmony can achieve good performance without exceeding the tolerated number of stale reads. For instance, in contrast to the static eventual consistency used in Cassandra, Harmony reduces the stale data being read by almost 80% while adding only minimal latency. Meanwhile, it improves the throughput of the system by 45% while maintaining the desired consistency requirements of the applications when compared to the strong consistency model in Cassandra.

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Mestrado em Contabilidade e Gestão das Instituições Financeiras

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The basic motivation of this work was the integration of biophysical models within the interval constraints framework for decision support. Comparing the major features of biophysical models with the expressive power of the existing interval constraints framework, it was clear that the most important inadequacy was related with the representation of differential equations. System dynamics is often modelled through differential equations but there was no way of expressing a differential equation as a constraint and integrate it within the constraints framework. Consequently, the goal of this work is focussed on the integration of ordinary differential equations within the interval constraints framework, which for this purpose is extended with the new formalism of Constraint Satisfaction Differential Problems. Such framework allows the specification of ordinary differential equations, together with related information, by means of constraints, and provides efficient propagation techniques for pruning the domains of their variables. This enabled the integration of all such information in a single constraint whose variables may subsequently be used in other constraints of the model. The specific method used for pruning its variable domains can then be combined with the pruning methods associated with the other constraints in an overall propagation algorithm for reducing the bounds of all model variables. The application of the constraint propagation algorithm for pruning the variable domains, that is, the enforcement of local-consistency, turned out to be insufficient to support decision in practical problems that include differential equations. The domain pruning achieved is not, in general, sufficient to allow safe decisions and the main reason derives from the non-linearity of the differential equations. Consequently, a complementary goal of this work proposes a new strong consistency criterion, Global Hull-consistency, particularly suited to decision support with differential models, by presenting an adequate trade-of between domain pruning and computational effort. Several alternative algorithms are proposed for enforcing Global Hull-consistency and, due to their complexity, an effort was made to provide implementations able to supply any-time pruning results. Since the consistency criterion is dependent on the existence of canonical solutions, it is proposed a local search approach that can be integrated with constraint propagation in continuous domains and, in particular, with the enforcing algorithms for anticipating the finding of canonical solutions. The last goal of this work is the validation of the approach as an important contribution for the integration of biophysical models within decision support. Consequently, a prototype application that integrated all the proposed extensions to the interval constraints framework is developed and used for solving problems in different biophysical domains.

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In this work we studied the asymptotic unbiasedness, the strong and the uniform strong consistencies of a class of kernel estimators fn as an estimator of the density function f taking values on a k-dimensional sphere

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In this work, the paper of Campos and Dorea [3] was detailed. In that article a Kernel Estimator was applied to a sequence of random variables with general state space, which were independent and identicaly distributed. In chapter 2, the estimator´s properties such as asymptotic unbiasedness, consistency in quadratic mean, strong consistency and asymptotic normality were verified. In chapter 3, using R software, numerical experiments were developed in order to give a visual idea of the estimate process

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In this work, we studied the strong consistency for a class of estimates for a transition density of a Markov chain with general state space E ⊂ Rd. The strong ergodicity of the estimates for the density transition is obtained from the strong consistency of the kernel estimates for both the marginal density p(:) of the chain and the joint density q(., .). In this work the Markov chain is supposed to be homogeneous, uniformly ergodic and possessing a stationary density p(.,.)

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In dieser Arbeit geht es um die Schätzung von Parametern in zeitdiskreten ergodischen Markov-Prozessen im allgemeinen und im CIR-Modell im besonderen. Beim CIR-Modell handelt es sich um eine stochastische Differentialgleichung, die von Cox, Ingersoll und Ross (1985) zur Beschreibung der Dynamik von Zinsraten vorgeschlagen wurde. Problemstellung ist die Schätzung der Parameter des Drift- und des Diffusionskoeffizienten aufgrund von äquidistanten diskreten Beobachtungen des CIR-Prozesses. Nach einer kurzen Einführung in das CIR-Modell verwenden wir die insbesondere von Bibby und Sørensen untersuchte Methode der Martingal-Schätzfunktionen und -Schätzgleichungen, um das Problem der Parameterschätzung in ergodischen Markov-Prozessen zunächst ganz allgemein zu untersuchen. Im Anschluss an Untersuchungen von Sørensen (1999) werden hinreichende Bedingungen (im Sinne von Regularitätsvoraussetzungen an die Schätzfunktion) für die Existenz, starke Konsistenz und asymptotische Normalität von Lösungen einer Martingal-Schätzgleichung angegeben. Angewandt auf den Spezialfall der Likelihood-Schätzung stellen diese Bedingungen zugleich lokal-asymptotische Normalität des Modells sicher. Ferner wird ein einfaches Kriterium für Godambe-Heyde-Optimalität von Schätzfunktionen angegeben und skizziert, wie dies in wichtigen Spezialfällen zur expliziten Konstruktion optimaler Schätzfunktionen verwendet werden kann. Die allgemeinen Resultate werden anschließend auf das diskretisierte CIR-Modell angewendet. Wir analysieren einige von Overbeck und Rydén (1997) vorgeschlagene Schätzer für den Drift- und den Diffusionskoeffizienten, welche als Lösungen quadratischer Martingal-Schätzfunktionen definiert sind, und berechnen das optimale Element in dieser Klasse. Abschließend verallgemeinern wir Ergebnisse von Overbeck und Rydén (1997), indem wir die Existenz einer stark konsistenten und asymptotisch normalen Lösung der Likelihood-Gleichung zeigen und lokal-asymptotische Normalität für das CIR-Modell ohne Einschränkungen an den Parameterraum beweisen.

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Markov chain Monte Carlo is a method of producing a correlated sample in order to estimate features of a complicated target distribution via simple ergodic averages. A fundamental question in MCMC applications is when should the sampling stop? That is, when are the ergodic averages good estimates of the desired quantities? We consider a method that stops the MCMC sampling the first time the width of a confidence interval based on the ergodic averages is less than a user-specified value. Hence calculating Monte Carlo standard errors is a critical step in assessing the output of the simulation. In particular, we consider the regenerative simulation and batch means methods of estimating the variance of the asymptotic normal distribution. We describe sufficient conditions for the strong consistency and asymptotic normality of both methods and investigate their finite sample properties in a variety of examples.

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We build the Conditional Least Squares Estimator of 0 based on the observation of a single trajectory of {Zk,Ck}k, and give conditions ensuring its strong consistency. The particular case of general linear models according to 0=( 0, 0) and among them, regenerative processes, are studied more particularly. In this frame, we may also prove the consistency of the estimator of 0 although it belongs to an asymptotic negligible part of the model, and the asymptotic law of the estimator may also be calculated.

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2010 Mathematics Subject Classification: 62F12, 62M05, 62M09, 62M10, 60G42.

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This study arose from an interest in knowing the reality of mental health care in Rio Grande do Norte (RN) on the advances and challenges in the intersectoral agreements paths and consolidation of the Psychosocial Care Network (RAPS) from the state. Considering problematic and concerns were defined as objectives: Identify the knowledge of managers of Rio Grande do Norte on the National Mental Health Policy (PNSM) in the RN State; Describe the activities developed by health professionals in the individual service offered in the CAPS from RN; Understanding the relationship of managers’ knowledge on national mental health policy in professionals’ practice working in the the CAPS from the countryside. It is a descriptive study with a quantitative and qualitative approach, carried out in 30 CAPS from RN’s countryside, where 183 professionals answered a structured questionnaire with closed questions about the activities they do in individual care; and 19 mental health coordinators of municipalities and the state coordinator of RAPS were interviewed about their knowledge on the Mental Health Policy. Data were collected after approval by the Research Ethics Committee of the Federal University of Rio Grande do Norte, with the number 508.430 CAAE: 25851913.7.0000.5537 from August through October of 2014 in 26 municipalities with CAPS from the state. Quantitative data were tabulated and analyzed using a descriptive statistics aided by the software Statistical Package for the Social Scienses (SPSS) version 20.0. The qualitative data were prepared in a corpus and analyzed through software Analyse Lexicale par Contexte d’um Ensemble de Segments de Texte (ALCESTE) that allow to perform textual statistical analysis and categorization from their comments, submitted to Bardin content analysis. Five categories were generated approaching the managers’ knowledge, namely: Back to society: leadership and users’ role and autonomy; The gap between policy and practice; Barriers that affect the service; Structuring the Psychosocial Care Network; Multidisciplinary team: attribuitios and activities. The CAPS professionals’ ages ranged from 20 to 58 years, prevailing females, with 76.5% of the total, the majority were social workers (16.8%), psychologists (15.3%), nurses (14.8%) and nursing technicians (14.8%). The results showed precariousness in care associated with physical workload regard to high workload and low wages of the CAPS professionals' and, also, it was possible to observe a large involvement of professionals in care delivery, despite the difficulties encountered in services. It was found little knowledge in managers regarding the National Mental Health Policy having as causes of this reality the poor education and training of these professionals. The responses of professionals working in care reveals strong consistency with what is expected of a psychosocial care service. Points up as a thesis of this study that the psychiatric reform and mental health policy in Rio Grande do Norte is following a structural expansion process, but with precariousness of services from a still unprepared management to act in a psychosocial context.

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In this paper we axiomatize the strong constrained egalitarian solution (Dutta and Ray, 1991) over the class of weak superadditive games using constrained egalitarianism, order-consistency, and converse order-consistency. JEL classification: C71, C78. Keywords: Cooperative TU-game, strong constrained egalitarian solution, axiomatization.

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The study centers on the power of Right-Wing Authoritarianism (RWA) and Social Dominance Orientation (SDO) as predictors of prejudice against stereotypical and nonstereotypical homosexuals under the threat of death and the threat of uncertainty. Right-wing authoritarianism (RWA) is an individual difference variable that measures the tendency for individuals to unquestionably follow those perceived to be authorities. Social Dominance Orientation (SDO) is an individual difference variable that measures the degree to which an individual prefers inequality among social groups. The RWA and SDO Scales are considered to be two of the strongest predictors of prejudice, such as prejudice against homosexuals. The study focuses on the unique predictive power of these two variables in predicting prejudice against homosexuals. The study also examines the role of situational threat in prejudice, specifically the threat of death (mortality salience) and the threat of uncertainty (uncertainty salience). Competing predictions from theories involving the threat of death (Terror Management Theory) and the threat of uncertainty (Uncertainty Management Theory) are also tested. The preference for expected information in the form of stereotypes concerning male homosexuals (that is, a stereotypical or non-stereotypical homosexual) were tested. The difference between the predictive power ofRWA and SDO was examined by measuring how these variables predict liking of a stereotypical or non-stereotypical homosexual under the threat of death, the threat of uncertainty, or a control condition. Along with completing a measure for RWA and a measure for SDO, participants were asked to think of their own death, of their being uncertain or about watching television then were asked to read about a week in the life of either a stereotypical or non-stereotypical male homosexual. Participants were then asked to evaluate the individual and his essay. Based on the participants' evaluations, results from 180 heterosexual university students show that RWA and SDO are strong predictors for disliking of a stereotypical homosexual under the threat of uncertainty and disliking of a non-stereotypical homosexual under the threat of death. Furthermore, however, results show that RWA is a particularly strong predictor of disliking of a stereotypical homosexual under the threat of uncertainty, whereas SDO is an exceptionally strong predictor of disliking of the non-stereotypical homosexual under the threat of death. This further adds to the notion that RWA and SDO are indeed unique predictors of prejudice. Implications are also explored, including the fact that the study simuhaneously examined the role of individual difference variables and situational threat variables, as well as exploratory analysis on Dominating Authoritarians.

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This study considers the consistency of the role of both the private and public real estate markets within a mixed-asset context. While a vast literature has developed that has examined the potential role of both the private and public real estate markets, most studies have largely relied on both single time horizons and single sample periods. This paper builds upon the analysis of Lee and Stevenson (2005) who examined the consistency of REITs in a US capital market portfolio. The current paper extends that by also analyzing the role of the private market. To address the question, the allocation of both the private and traded markets is evaluated over different holding periods varying from 5- to 20-years. In general the results show that optimum mixed-asset portfolios already containing private real estate have little place for public real estate securities, especially in low risk portfolios and for longer investment horizons. Additionally, mixed-asset portfolios with public real estate either see the allocations to REITs diminished or eliminated if private real estate is also considered. The results demonstrate that there is a still a strong case for private real estate in the mixed-asset portfolio on the basis of an increase in risk-adjusted performance, even if the investor is already holding REITs, but that the reverse is not always the case.