Estimating data divergence in cloud computing storage systems

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Generalizações do conceito de distância, i-distâncias, distâncias intervalares e topologia

In this dissertation we present some generalizations for the concept of distance by using more general value spaces, such as: fuzzy metrics, probabilistic metrics and generalized metrics. We show how such generalizations may be useful due to the possibility that the distance between two objects could carry more information about the objects than in the case where the distance is represented just by a real number. Also in this thesis we propose another generalization of distance which encompasses the notion of interval metric and generates a topology in a natural way. Several properties of this generalization are investigated, and its links with other existing generalizations

A global empirical system for probabilistic seasonal climate prediction

Preparing for episodes with risks of anomalous weather a month to a year ahead is an important challenge for governments, non-governmental organisations, and private companies and is dependent on the availability of reliable forecasts. The majority of operational seasonal forecasts are made using process-based dynamical models, which are complex, computationally challenging and prone to biases. Empirical forecast approaches built on statistical models to represent physical processes offer an alternative to dynamical systems and can provide either a benchmark for comparison or independent supplementary forecasts. Here, we present a simple empirical system based on multiple linear regression for producing probabilistic forecasts of seasonal surface air temperature and precipitation across the globe. The global CO2-equivalent concentration is taken as the primary predictor; subsequent predictors, including large-scale modes of variability in the climate system and local-scale information, are selected on the basis of their physical relationship with the predictand. The focus given to the climate change signal as a source of skill and the probabilistic nature of the forecasts produced constitute a novel approach to global empirical prediction. Hindcasts for the period 1961–2013 are validated against observations using deterministic (correlation of seasonal means) and probabilistic (continuous rank probability skill scores) metrics. Good skill is found in many regions, particularly for surface air temperature and most notably in much of Europe during the spring and summer seasons. For precipitation, skill is generally limited to regions with known El Niño–Southern Oscillation (ENSO) teleconnections. The system is used in a quasi-operational framework to generate empirical seasonal forecasts on a monthly basis.

Efficient algorithms for dynamic probabilistic safety assessment. An application to convex damage domain.

The design of nuclear power plant has to follow a number of regulations aimed at limiting the risks inherent in this type of installation. The goal is to prevent and to limit the consequences of any possible incident that might threaten the public or the environment. To verify that the safety requirements are met a safety assessment process is followed. Safety analysis is as key component of a safety assessment, which incorporates both probabilistic and deterministic approaches. The deterministic approach attempts to ensure that the various situations, and in particular accidents, that are considered to be plausible, have been taken into account, and that the monitoring systems and engineered safety and safeguard systems will be capable of ensuring the safety goals. On the other hand, probabilistic safety analysis tries to demonstrate that the safety requirements are met for potential accidents both within and beyond the design basis, thus identifying vulnerabilities not necessarily accessible through deterministic safety analysis alone. Probabilistic safety assessment (PSA) methodology is widely used in the nuclear industry and is especially effective in comprehensive assessment of the measures needed to prevent accidents with small probability but severe consequences. Still, the trend towards a risk informed regulation (RIR) demanded a more extended use of risk assessment techniques with a significant need to further extend PSA’s scope and quality. Here is where the theory of stimulated dynamics (TSD) intervenes, as it is the mathematical foundation of the integrated safety assessment (ISA) methodology developed by the CSN(Consejo de Seguridad Nuclear) branch of Modelling and Simulation (MOSI). Such methodology attempts to extend classical PSA including accident dynamic analysis, an assessment of the damage associated to the transients and a computation of the damage frequency. The application of this ISA methodology requires a computational framework called SCAIS (Simulation Code System for Integrated Safety Assessment). SCAIS provides accident dynamic analysis support through simulation of nuclear accident sequences and operating procedures. Furthermore, it includes probabilistic quantification of fault trees and sequences; and integration and statistic treatment of risk metrics. SCAIS comprehensively implies an intensive use of code coupling techniques to join typical thermal hydraulic analysis, severe accident and probability calculation codes. The integration of accident simulation in the risk assessment process and thus requiring the use of complex nuclear plant models is what makes it so powerful, yet at the cost of an enormous increase in complexity. As the complexity of the process is primarily focused on such accident simulation codes, the question of whether it is possible to reduce the number of required simulation arises, which will be the focus of the present work. This document presents the work done on the investigation of more efficient techniques applied to the process of risk assessment inside the mentioned ISA methodology. Therefore such techniques will have the primary goal of decreasing the number of simulation needed for an adequate estimation of the damage probability. As the methodology and tools are relatively recent, there is not much work done inside this line of investigation, making it a quite difficult but necessary task, and because of time limitations the scope of the work had to be reduced. Therefore, some assumptions were made to work in simplified scenarios best suited for an initial approximation to the problem. The following section tries to explain in detail the process followed to design and test the developed techniques. Then, the next section introduces the general concepts and formulae of the TSD theory which are at the core of the risk assessment process. Afterwards a description of the simulation framework requirements and design is given. Followed by an introduction to the developed techniques, giving full detail of its mathematical background and its procedures. Later, the test case used is described and result from the application of the techniques is shown. Finally the conclusions are presented and future lines of work are exposed.

ProbFAST: Probabilistic Functional Analysis System Tool

Background: The post-genomic era has brought new challenges regarding the understanding of the organization and function of the human genome. Many of these challenges are centered on the meaning of differential gene regulation under distinct biological conditions and can be performed by analyzing the Multiple Differential Expression (MDE) of genes associated with normal and abnormal biological processes. Currently MDE analyses are limited to usual methods of differential expression initially designed for paired analysis. Results: We proposed a web platform named ProbFAST for MDE analysis which uses Bayesian inference to identify key genes that are intuitively prioritized by means of probabilities. A simulated study revealed that our method gives a better performance when compared to other approaches and when applied to public expression data, we demonstrated its flexibility to obtain relevant genes biologically associated with normal and abnormal biological processes. Conclusions: ProbFAST is a free accessible web-based application that enables MDE analysis on a global scale. It offers an efficient methodological approach for MDE analysis of a set of genes that are turned on and off related to functional information during the evolution of a tumor or tissue differentiation. ProbFAST server can be accessed at http://gdm.fmrp.usp.br/probfast.

Monte Carlo investigation of the critical behavior of Stavskaya's probabilistic cellular automaton

Stavskaya's model is a one-dimensional probabilistic cellular automaton (PCA) introduced in the end of the 1960s as an example of a model displaying a nonequilibrium phase transition. Although its absorbing state phase transition is well understood nowadays, the model never received a full numerical treatment to investigate its critical behavior. In this Brief Report we characterize the critical behavior of Stavskaya's PCA by means of Monte Carlo simulations and finite-size scaling analysis. The critical exponents of the model are calculated and indicate that its phase transition belongs to the directed percolation universality class of critical behavior, as would be expected on the basis of the directed percolation conjecture. We also explicitly establish the relationship of the model with the Domany-Kinzel PCA on its directed site percolation line, a connection that seems to have gone unnoticed in the literature so far.

Coupled reliability and boundary element model for probabilistic fatigue life assessment in mixed mode crack propagation

Fatigue and crack propagation are phenomena affected by high uncertainties, where deterministic methods fail to predict accurately the structural life. The present work aims at coupling reliability analysis with boundary element method. The latter has been recognized as an accurate and efficient numerical technique to deal with mixed mode propagation, which is very interesting for reliability analysis. The coupled procedure allows us to consider uncertainties during the crack growth process. In addition, it computes the probability of fatigue failure for complex structural geometry and loading. Two coupling procedures are considered: direct coupling of reliability and mechanical solvers and indirect coupling by the response surface method. Numerical applications show the performance of the proposed models in lifetime assessment under uncertainties, where the direct method has shown faster convergence than response surface method. (C) 2010 Elsevier Ltd. All rights reserved.

Assembling a consistent set of sentences in relational probabilistic logic with stochastic independence

We examine the representation of judgements of stochastic independence in probabilistic logics. We focus on a relational logic where (i) judgements of stochastic independence are encoded by directed acyclic graphs, and (ii) probabilistic assessments are flexible in the sense that they are not required to specify a single probability measure. We discuss issues of knowledge representation and inference that arise from our particular combination of graphs, stochastic independence, logical formulas and probabilistic assessments. (C) 2007 Elsevier B.V. All rights reserved.

Probabilistic logic with independence

This paper investigates probabilistic logics endowed with independence relations. We review propositional probabilistic languages without and with independence. We then consider graph-theoretic representations for propositional probabilistic logic with independence; complexity is analyzed, algorithms are derived, and examples are discussed. Finally, we examine a restricted first-order probabilistic logic that generalizes relational Bayesian networks. (c) 2007 Elsevier Inc. All rights reserved.

A hybrid probabilistic criterion for market-based transmission expansion planning

Market-based transmission expansion planning gives information to investors on where is the most cost efficient place to invest and brings benefits to those who invest in this grid. However, both market issue and power system adequacy problems are system planers’ concern. In this paper, a hybrid probabilistic criterion of Expected Economical Loss (EEL) is proposed as an index to evaluate the systems’ overall expected economical losses during system operation in a competitive market. It stands on both investors’ and planner’s point of view and will further improves the traditional reliability cost. By applying EEL, it is possible for system planners to obtain a clear idea regarding the transmission network’s bottleneck and the amount of losses arises from this weak point. Sequentially, it enables planners to assess the worth of providing reliable services. Also, the EEL will contain valuable information for moneymen to undertake their investment. This index could truly reflect the random behaviors of power systems and uncertainties from electricity market. The performance of the EEL index is enhanced by applying Normalized Coefficient of Probability (NCP), so it can be utilized in large real power systems. A numerical example is carried out on IEEE Reliability Test System (RTS), which will show how the EEL can predict the current system bottleneck under future operational conditions and how to use EEL as one of planning objectives to determine future optimal plans. A well-known simulation method, Monte Carlo simulation, is employed to achieve the probabilistic characteristic of electricity market and Genetic Algorithms (GAs) is used as a multi-objective optimization tool.

Probabilistic Action System Trace Semantics

Action systems are a construct for reasoning about concurrent, reactive systems, in which concurrent behaviour is described by interleaving atomic actions. Sere and Troubitsyna have proposed an extension to action systems in which actions may be expressed and composed using discrete probabilistic choice as well as demonic nondeterministic choice. In this paper we develop a trace-based semantics for probabilistic action systems. This semantics provides a simple theoretical base on which practical refinement rules for probabilistic action systems may be justified.

Perceptual quality metrics applied to still image compression

We present a review of perceptual image quality metrics and their application to still image compression. The review describes how image quality metrics can be used to guide an image compression scheme and outlines the advantages, disadvantages and limitations of a number of quality metrics. We examine a broad range of metrics ranging from simple mathematical measures to those which incorporate full perceptual models. We highlight some variation in the models for luminance adaptation and the contrast sensitivity function and discuss what appears to be a lack of a general consensus regarding the models which best describe contrast masking and error summation. We identify how the various perceptual components have been incorporated in quality metrics, and identify a number of psychophysical testing techniques that can be used to validate the metrics. We conclude by illustrating some of the issues discussed throughout the paper with a simple demonstration. (C) 1998 Elsevier Science B.V. All rights reserved.

Spatial and temporal variation in distribution of mangroves in Moreton Bay, subtropical Australia: a comparison of pattern metrics and change detection analyses based on aerial photographs

An assessment of the changes in the distribution and extent of mangroves within Moreton Bay, southeast Queensland, Australia, was carried out. Two assessment methods were evaluated: spatial and temporal pattern metrics analysis, and change detection analysis. Currently, about 15,000 ha of mangroves are present in Moreton Bay. These mangroves are important ecosystems, but are subject to disturbance from a number of sources. Over the past 25 years, there has been a loss of more than 3800 ha, as a result of natural losses and mangrove clearing (e.g. for urban and industrial development, agriculture and aquaculture). However, areas of new mangroves have become established over the same time period, offsetting these losses to create a net loss of about 200 ha. These new mangroves have mainly appeared in the southern bay region and the bay islands, particularly on the landward edge of existing mangroves. In addition, spatial patterns and species composition of mangrove patches have changed. The pattern metrics analysis provided an overview of mangrove distribution and change in the form of single metric values, while the change detection analysis gave a more detailed and spatially explicit description of change. An analysis of the effects of spatial scales on the pattern metrics indicated that they were relatively insensitive to scale at spatial resolutions less than 50 m, but that most metrics became sensitive at coarser resolutions, a finding which has implications for mapping of mangroves based on remotely sensed data. (C) 2003 Elsevier Science B.V. All rights reserved.

Choice of macroinvertebrate metrics to evaluate stream conditions in Atlantic Forest, Brazil

The development of biomonitoring programs based on the macroinvertebrate community requires the understanding of species distribution patterns, as well as of the responses of the community to anthropogenic stressors. In this study, 49 metrics were tested as potential means of assessing the condition of 29 first- and second-order streams located in areas of differing types of land use in So Paulo State, Brazil. Of the sampled streams, 15 were in well-preserved regions in the Atlantic Forest, 5 were among sugarcane cultivations, 5 were in areas of pasture, and 4 were among eucalyptus plantations. The metrics were assessed against the following criteria: (1) predictable response to the impact of human activity; (2) highest taxonomic resolution, and (3) operational and theoretical simplicity. We found that 18 metrics were correlated with the environmental and spatial predictors used, and seven of these satisfied the selection criteria and are thus candidates for inclusion in a multimetric system to assess low-order streams in So Paulo State. These metrics are family richness; Ephemeroptera, Plecoptera and Trichoptera (EPT) richness; proportion of Megaloptera and Hirudinea; proportion of EPT; Shannon diversity index for genus; and adapted Biological Monitoring Work Party biotic index.

Probabilistic modelling of CO2 corrosion laboratory data using neural networks

The present paper addresses two major concerns that were identified when developing neural network based prediction models and which can limit their wider applicability in the industry. The first problem is that it appears neural network models are not readily available to a corrosion engineer. Therefore the first part of this paper describes a neural network model of CO2 corrosion which was created using a standard commercial software package and simple modelling strategies. It was found that such a model was able to capture practically all of the trends noticed in the experimental data with acceptable accuracy. This exercise has proven that a corrosion engineer could readily develop a neural network model such as the one described below for any problem at hand, given that sufficient experimental data exist. This applies even in the cases when the understanding of the underlying processes is poor. The second problem arises from cases when all the required inputs for a model are not known or can be estimated with a limited degree of accuracy. It seems advantageous to have models that can take as input a range rather than a single value. One such model, based on the so-called Monte Carlo approach, is presented. A number of comparisons are shown which have illustrated how a corrosion engineer might use this approach to rapidly test the sensitivity of a model to the uncertainities associated with the input parameters. (C) 2001 Elsevier Science Ltd. All rights reserved.