Resonance-valence-bond superconductivity in CuO2 planes

We find the exact ground state of a system of 4 × 4 unit cells described by an effective model for cuprate superconductors. The model has the form of the t - J one, but includes a three-site term t like that derived from the Hubbard model in the large U limit, but of opposite sign for realistic or large O-O hopping. For t > t_c (where t_c/t 0.1 for realistic J and doping) the system undergoes a transition to a phase in which the ground state has a significant overlap with a very simple superconducting resonance-valence-bond (RVB) wave function. In the RVB phase there is a large increase of the d-wave superconducting susceptibility. We calculate the boundary of the RVB phase.     

Performance analysis of available bandwidth estimation tools for grid networks

Modern large-scale grid computing systems for processing advanced science and engineering applications rely on geographically distributed clusters. In such highly distributed environments, estimating the available bandwidth between clusters is a key issue for efficient task scheduling. We analyze the performance of two well known available bandwidth estimation tools, pathload and abget, with the aim of using them in grid environments. Differently than previous investigations (Jain et al., ; Shriram et al., in Passive and active network measurement: 6th international workshop, PAM 2005. Springer, Berlin, 2005), our experiments consider a series of relevant metrics such as accuracy of the estimation, convergence time, degree of intrusion in the grid links, and ability to handle multiple simultaneous estimations. No previous work has analyzed the use of available bandwidth tools for the derivation of efficient grid scheduling.     

An haptic-based immersive environment for shape analysis and modelling

Currently, the design of aesthetic products is a process that requires a set of activities where digital models and physical mockups play a key role. Typically, these are modified (and built) several times before reaching the desired design, increasing the development time and, consequently, the final product cost. In this paper, we present an innovative design environment for computer-aided design (CAD) surface analysis. Our system relies on a direct visuo-haptic display system, which enables users to visualize models using a stereoscopic view, and allows the evaluation of sectional curves using touch. Profile curves are rendered using an haptic device that deforms a plastic strip, thanks to a set of actuators, to reproduce the curvature of the shape co-located with the virtual model. By touching the strip, users are able to evaluate shape characteristics, such as curvature or discontinuities (rendered using sound), and to assess the surface quality. We believe that future computer-aided systems (CAS)/CAD systems based on our approach will contribute in improving the design process at industrial level. Moreover, these will allow companies to reduce the product development time by reducing the number of physical mockups necessary for the product design evaluation and by increasing the quality of the final product, allowing a wider exploration and comparative evaluation of alternatives in the given time.     

Interactive smart battery storage for a PV and wind hybrid energy management control based on conservative power theory

This paper presents interactive smart battery-based storage (BBS) for wind generator (WG) and photovoltaic (PV) systems. The BBS is composed of an asymmetric cascaded H-bridge multilevel inverter (ACMI) with staircase modulation. The structure is parallel to the WG and PV systems, allowing the ACMI to have a reduction in power losses compared to the usual solution for storage connected at the DC-link of the converter for WG or PV systems. Moreover, the BBS is embedded with a decision algorithm running real-time energy costs, plus a battery state-of-charge manager and power quality capabilities, making the described system in this paper very interactive, smart and multifunctional. The paper describes how BBS interacts with the WG and PV and how its performance is improved. Experimental results are presented showing the efficacy of this BBS for renewable energy applications.     

A dynamic default revision mechanism for speculative computation

In this work a default revision mechanism is introduced into speculative computation to manage incomplete information. The default revision is supported by a method for the generation of default constraints based on Bayesian networks. The method enables the generation of an initial set of defaults which is used to produce the most likely scenarios during the computation, represented by active processes. As facts arrive, the Bayesian network is used to derive new defaults. The objective with such a new dynamic mechanism is to keep the active processes coherent with arrived facts. This is achieved by changing the initial set of default constraints during the reasoning process in speculative computation. A practical example in clinical decision support is described.     

Position USBL/DVL sensor-based navigation filter in the presence of unknown ocean currents

This paper presents a novel approach to the design of globally asymptotically stable (GAS) position and velocity filters for Autonomous Underwater Vehicles (AUVs) based directly on the sensor readings of an Ultra-short Baseline (USBL) acoustic array system and a Doppler Velocity Log (DVL). The proposed methodology is based on an equivalent linear time-varying (LTV) system that fully captures the dynamics of the nonlinear system, allowing for the use of powerful linear system analysis and filtering design tools that yield GAS filter error dynamics. Numerical results using Monte Carlo simulations and comparison to the Bayesian Cramér Rao Bound (BCRB) reveal that the performance of the proposed filter is tight to this theoretical estimation error lower bound. In comparison with other approaches, the present solution achieves the same level of performance of the Extended Kalman Filter (EKF), which does not offer GAS guarantees, and outperforms other classical filtering approaches designed in inertial coordinates instead of the body-fixed coordinate frame.     

Diagnostic Tools for Wireless Sensor Networks: A Comparative Survey

The availability of tools to diagnose Wireless Sensor Network (WSN) failures is a key success factor for this type of networks as already demonstrated by several long-running deployments. By nature, WSNs are resource-constrained, fragile, complex to analyse, and failure-prone. Naturally, with the growing number of installations, it is becoming fundamental to efficiently diagnose failures as soon as possible, in order to deal with the underlying causes. In accordance with this, from 2005 onwards, the offer of diagnostic tools has been increasing, as the other base technologies (e.g. networking, operating system, localisation, synchronisation) become reasonably stable. The purpose of this survey is to provide an overview of existing post-deployment WSN diagnostic tools, by briefly presenting their functionality, architecture and constraints, in order to enable a basic understating of each tool. The survey also includes a multi-dimensional comparative analysis of the various tools, based on a proposed classification scheme and evaluation criteria, as well as an identification of the main open research issues. Although the number of diagnostic tools is high and considerable work has been done in this area, we conclude that there are still several challenges concerning post-deployment WSN diagnostic tools, regarding scope, flexibility, generality, mobility and security. Moreover, there is a need for mature, native diagnostic-oriented functionality in WSN platforms and operating systems.     

Using Twitter® as source of information for dietary market research: a study on veganism and plant-based diets

Social media has experienced rapid growth in recent years and has been subjected of discussions on a wide range of topics including new lifestyles and eating habits, providing a great opportunity to obtain spontaneous consumer information. In this sense, the present work aimed to understand the perception of Twitter^® users about themes of veganism and plant-based diets. The social networking data mining methodology was applied to measure the relationship between both terms. The significant differences found were analysed using the global chi-square (χ²) test, and their sources of variation were investigated by the chi-square per cell. The results indicate that the vegan group's posts are more related to the categories of recipes, trends, criticism and negative comments about veganism, being more often citing sources when compared to the other group. The results of the plant-based diet group are more significantly related to the impacts of nutrition, physical activity and consumer health. In conclusion, Twitter^® has proved to be an interesting tool for obtaining data on (re) produced food publications on social media and their results can guide the market and the academic environment in creating new products, services and marketing strategies to answer the needs of specific consumers.