Biophysical characteristics and fire occurrence of cultivated pastures in the Brazilian savanna observed by moderate resolution satellite data

Cultivated pastures are the dominant land-use unit in Brazil, with the cattle raising sector representing ～50% of the total Brazilian emissions of greenhouse gases. About 44% of the Brazilian cattle herd is located in the 204 million ha Cerrado, the Brazilian savanna biome and one of the world's hotspots for conservation, where pasture is still the major driving force behind the ongoing land clearance. In the face of the environmental challenges posed by the Cerrado cultivated pastures, 50% of which are estimated to be already severely degraded and where most of the pasture-related fires in Brazil occur, in this study we report the findings on the use of key Moderate Resolution Imaging Spectroradiometer (MODIS) Land (MODLAND) products for retrieving biophysical patterns and trends of cultivated pastures over the entire Brazilian savanna biome. The areas of Cerrado covered by cultivated pastures were analysed by the following 2008 MODIS products: MOD13Q1 enhanced vegetation index, MOD11A2 land-surface temperature, MOD15A2 leaf area index, and MCD45A1 fire-affected areas. Specifically, 23 MOD13Q1 composites for the whole year of 2008 were used as a net primary productivity proxy. Our results indicate the ability of moderate resolution orbital imagery to consistently depict the main characteristics and regional variation in the biophysical properties of the Cerrado pastures, which clearly depend on management practices, usage, and environmental conditions. In particular, these results corroborate the feasibility of an operational MODIS-based monitoring system providing early fire warnings and overall quality assessments in support of a more efficient and sustainable herd occupation and more appropriate land-use destination.     

Representative cross information potential clustering

This paper proposes an information-theoretic approach for clustering with a new measure of cross information potential and two clustering algorithms. Instead of using all points of the dataset, the proposed measure uses representative points to quantify the interaction between distributions without any loss of the original properties of cross information potential. This brings a double advantage. It decreases the cost of computing the cross information potential, thus drastically reducing the running time. Secondly, it captures the interaction among the data points by utilizing the underlying statistics of the space region centered around the representative points. With this, we have made it possible to use cross information potential in applications where it was not. We also proposed two algorithms for clustering which explore the idea of creating links between regions of the feature space that are highly correlated. We ran several tests and compared the results with single linkage hierarchical algorithm, finite mixture of Gaussians and spectral clustering in both synthetic and real image segmentation datasets. Experiments showed that our approach achieved better results compared to the other algorithms and it was capable of capture the real structure of the data in most cases regardless of its complexity. It also produced good image segmentation with the advantage of a tuning parameter that provides a way of refine segmentation.     

Estimating sustainability impact of high dependable data centers: a comparative study between Brazilian and US energy mixes

The advent of services such as cloud computing, social networks and e-commerce has led to an increased demand for computer resources from data centers. Prominent issues for data center designers are sustainability, cost, and dependability, which are each significantly affected by the redundant architectures required to support these services. Within this context, models are important tools for designers when attempting to quantify these issues before implementing the final architecture. This paper proposes a set of models for the integrated quantification of the sustainability impact, cost, and dependability of data center power and cooling infrastructures. This is achieved with the support of an environment called ASTRO. The approach taken to perform the system dependability evaluation employs a hybrid modeling strategy which recognizes the advantages of both stochastic Petri nets and reliability block diagrams. Additionally, an energy flow model is proposed to estimate the environmental impact and cost of data center architectures whilst respecting the energy constraints of each device. This work also presents a case study which analyzes the environmental impact and dependability metrics as well as the operational energy cost of real-world data center power and cooling architectures within the context of the energy mixes of the US and Brazil.     

A numerical-experimental method for damage location based on rotation fields spatial differentiation

This paper presents a structural damage location method that decreases the number of spatial differentiations needed to compute modal curvature fields. The method is numerically and experimentally applied to isotropic and laminated rectangular plates, respectively. A speckle shear interferometer is used to measure the rotation fields of the laminated plate, while the isotropic plate is analysed by finite elements. It was found that the Gaussian differentiation is the most suited technique to compute the curvature fields. It is also demonstrated the superior performance of the curvature method using measured rotation fields instead of measured displacement fields.     

A finite element model for the analysis of viscoelastic sandwich structures

In this work a finite element model is developed for vibration analysis of active–passive damped multilayer sandwich plates, with a viscoelastic core sandwiched between elastic layers, including piezoelectric layers. The elastic layers are modelled using the classic plate theory and the core is modelled using the Reissener–Mindlin theory. The finite element is obtained by assembly of N “elements” through the thickness, using specific assumptions on the displacement continuity at the interfaces between layers. The lack of finite element plate-shell models to analyse structures with passive and active damping, is the principal motivation for the present development, where the solution of some illustrative examples and the results are presented and discussed.     

Performability modeling of electronic funds transfer systems

Dependability is a paramount requirement for computer systems, since failures can cause a serious economic impact and jeopardize profitability. This paper considers electronic funds transfer (EFT) systems, where computing resources must be used efficiently in order to achieve high availability and reliability for a high quality of the offered service. The design of fault-tolerant computer systems requires their model-based performability evaluation. A stochastic Petri net model of EFT architecture and behavior is presented to evaluate the impact of availability and reliability issues on computational resources. An industrial case study shows the practical usability of the proposed models and techniques.     

MulRoGA: A Multicast Routing Genetic Algorithm approach considering multiple objectives

We solve a multicast routing problem by means of a genetic algorithm (GA) without using multicast trees. The source-destination routes need to fulfill two conflicting objectives: maximization of the common links and minimization of the route sizes. The proposed GA can be characterized by its representation of network links and routes in a variable size multi-chromosome problem; local viability restrictions in order to generate the initial population and define variation operators; selection operators in order to choose the most promising individuals thus preserving diversity, and the fitness function in order to handle the conflicting multiple objectives. The proposed model is called a Multicast Routing Genetic Algorithm (MulRoGA). The model was tested on the 33-node European GéANT WAN network backbone and three other networks (66-node, 100-node and 200-node) randomly generated using the Waxman model on a network topology generator BRITE. On considering each network, a number of solutions were found for changes in the size and node members of the multicast groups, and the source node. The results of the MulRoGA operation suggest a consistent and robust performance in the various cases including comparisons with the methods of unicast shortest path routing, shortest path tree routing (SPT), and simulated annealing (SA) heuristic.     

IMMIView: a multi-user solution for design review in real-time

IMMIView is an interactive system that relies on multiple modalities and multi-user interaction to support collaborative design review. It was designed to offer natural interaction in visualization setups such as large-scale displays, head mounted displays or TabletPC computers. To support architectural design, our system provides content creation and manipulation, 3D scene navigation and annotations. Users can interact with the system using laser pointers, speech commands, body gestures and mobile devices. In this paper, we describe how we design a system to answer architectural user requirements. In particular, our system takes advantage of multiple modalities to provide a natural interaction for design review. We also propose a new graphical user interface adapted to architectural user tasks, such as navigation or annotations. The interface relies on a novel stroke-based interaction supported by simple laser pointers as input devices for large-scale displays. Furthermore, input devices such as speech and body tracking allow IMMIView to support multiple users. Moreover, they allow each user to select different modalities according to their preference and modality adequacy for the user task. We present a multi-modal fusion system developed to support multi-modal commands on a collaborative, co-located, environment, i.e. with two or more users interacting at the same time, on the same system. The multi-modal fusion system listens to inputs from all the IMMIView modules in order to model user actions and issue commands. The multiple modalities are fused based on a simple rule-based sub-module developed in IMMIView and presented in this paper. User evaluation performed over IMMIView is presented. The results show that users feel comfortable with the system and suggest that users prefer the multi-modal approach to more conventional interactions, such as mouse and menus, for the architectural tasks presented.     

A CASE-BASED DECISION SUPPORT SYSTEM FOR INDIVIDUAL STRESS DIAGNOSIS USING FUZZY SIMILARITY MATCHING

Stress diagnosis based on finger temperature (FT) signals is receiving increasing interest in the psycho-physiological domain. However, in practice, it is difficult and tedious for a clinician and particularly less experienced clinicians to understand, interpret, and analyze complex, lengthy sequential measurements to make a diagnosis and treatment plan. The paper presents a case-based decision support system to assist clinicians in performing such tasks. Case-based reasoning (CBR) is applied as the main methodology to facilitate experience reuse and decision explanation by retrieving previous similar temperature profiles. Further fuzzy techniques are also employed and incorporated into the CBR system to handle vagueness, uncertainty inherently existing in clinicians reasoning as well as imprecision of feature values. Thirty-nine time series from 24 patients have been used to evaluate the approach (matching algorithms) and an expert has ranked and estimated similarity. On average goodness-of-fit for the fuzzy matching algorithm is 90% in ranking and 81% in similarity estimation that shows a level of performance close to an experienced expert. Therefore, we have suggested that a fuzzy matching algorithm in combination with CBR is a valuable approach in domains, where the fuzzy matching model similarity and case preference is consistent with the views of domain expert. This combination is also valuable, where domain experts are aware that the crisp values they use have a possibility distribution that can be estimated by the expert and is used when experienced experts reason about similarity. This is the case in the psycho-physiological domain and experienced experts can estimate this distribution of feature values and use them in their reasoning and explanation process.     

Applying Water Vulnerability Indexes for River Segments

The purpose of this paper is to provide an analysis and application of the indexes of water-use conflict in water resources management (i_cm) and planning (i_cp) for the Grande river basin, aiming at identifying potential water-use conflicts and thus providing a basis for the water resources management organization of Bahia state, Brazil. In order to apply the indexes, the minimum reference outflow (Q₉₀) and the long-term average streamflow (Q_lt) were estimated. Water demand was obtained from the water grant database from the Institute of the Environment and Water Resources of the State of Bahia. The results showed that in six stream segments of the basin, the legal water-use grant limit was exceeded. Some advantages of using these indexes are the possibility of assessing water scarcity at a river segment level and the fact that they provide a spatial analysis of potential conflicts in a basin. The analysis of water availability at the drainage segment level allows the management organization to act locally for the mitigation of water-use conflicts or to plan solutions for imminent conflicts.