Domestic Consumption Simulation and Management Using a Continuous Consumption Management and Optimization Algorithm

The recent changes concerning the consumers’ active participation in the efficient management of load devices for one’s own interest and for the interest of the network operator, namely in the context of demand response, leads to the need for improved algorithms and tools. A continuous consumption optimization algorithm has been improved in order to better manage the shifted demand. It has been done in a simulation and user-interaction tool capable of being integrated in a multi-agent smart grid simulator already developed, and also capable of integrating several optimization algorithms to manage real and simulated loads. The case study of this paper enhances the advantages of the proposed algorithm and the benefits of using the developed simulation and user interaction tool.

A Learning Algorithm and System Approach to Address Exceptional Events in Domestic Consumption Management

The integration of the Smart Grid concept into the electric grid brings to the need for an active participation of small and medium players. This active participation can be achieved using decentralized decisions, in which the end consumer can manage loads regarding the Smart Grid needs. The management of loads must handle the users’ preferences, wills and needs. However, the users’ preferences, wills and needs can suffer changes when faced with exceptional events. This paper proposes the integration of exceptional events into the SCADA House Intelligent Management (SHIM) system developed by the authors, to handle machine learning issues in the domestic consumption context. An illustrative application and learning case study is provided in this paper.

Risk Acceptance in the Furniture Sector: Analysis of Acceptance Level and Relevant Influence Factors

Risk acceptance has been broadly discussed in relation to hazardous risk activities and/or technologies. A better understanding of risk acceptance in occupational settings is also important; however, studies on this topic are scarce. It seems important to understand the level of risk that stakeholders consider sufficiently low, how stakeholders form their opinion about risk, and why they adopt a certain attitude toward risk. Accordingly, the aim of this study is to examine risk acceptance in regard to occupational accidents in furniture industries. The safety climate analysis was conducted through the application of the Safety Climate in Wood Industries questionnaire. Judgments about risk acceptance, trust, risk perception, benefit perception, emotions, and moral values were measured. Several models were tested to explain occupational risk acceptance. The results showed that the level of risk acceptance decreased as the risk level increased. High-risk and death scenarios were assessed as unacceptable. Risk perception, emotions, and trust had an important influence on risk acceptance. Safety climate was correlated with risk acceptance and other variables that influence risk acceptance. These results are important for the risk assessment process in terms of defining risk acceptance criteria and strategies to reduce risks.

Safety climate and its relationship with furniture companies’ safety performance and workers’ risk acceptance

This study aims to analyse the relationship between safety climate and the level of risk acceptance, as well as its relationship with workplace safety performance. The sample includes 14 companies and 403 workers. The safety climate assessment was performed by the application of a Safety Climate in Wood Industries questionnaire and safety performance was assessed with a checklist. Judgements about risk acceptance were measured through questionnaires together with four other variables: trust, risk perception, benefit perception and emotion. Safety climate was found to be correlated with workgroup safety performance, and it also plays an important role in workers’ risk acceptance levels. Risk acceptance tends to be lower when safety climate scores of workgroups are high, and subsequently, their safety performance is better. These findings seem to be relevant, as they provide Occupational, Safety and Health practitioners with a better understanding of workers’ risk acceptance levels and of the differences among workgroups.

Defining risk acceptance criteria in occupational settings: A case study in the furniture industrial sector

The use of appropriate acceptance criteria in the risk assessment process for occupational accidents is an important issue but often overlooked in the literature, particularly when new risk assessment methods are proposed and discussed. In most cases, there is no information on how or by whom they were defined, or even how companies can adapt them to their own circumstances. Bearing this in mind, this study analysed the problem of the definition of risk acceptance criteria for occupational settings, defining the quantitative acceptance criteria for the specific case study of the Portuguese furniture industrial sector. The key steps to be considered in formulating acceptance criteria were analysed in the literature review. By applying the identified steps, the acceptance criteria for the furniture industrial sector were then defined. The Cumulative Distribution Function (CDF) for the injury statistics of the industrial sector was identified as the maximum tolerable risk level. The acceptable threshold was defined by adjusting the CDF to the Occupational, Safety & Health (OSH) practitioners’ risk acceptance judgement. Adjustments of acceptance criteria to the companies’ safety cultures were exemplified by adjusting the Burr distribution parameters. An example of a risk matrix was also used to demonstrate the integration of the defined acceptance criteria into a risk metric. This work has provided substantial contributions to the issue of acceptance criteria for occupational accidents, which may be useful in overcoming the practical difficulties faced by authorities, companies and experts.

Global and Partitioned Multiprocessor Fixed Priority Scheduling with Deferred Pre-emption

This article introduces schedulability analysis for global fixed priority scheduling with deferred preemption (gFPDS) for homogeneous multiprocessor systems. gFPDS is a superset of global fixed priority pre-emptive scheduling (gFPPS) and global fixed priority non-pre-emptive scheduling (gFPNS). We show how schedulability can be improved using gFPDS via appropriate choice of priority assignment and final non-pre-emptive region lengths, and provide algorithms which optimize schedulability in this way. Via an experimental evaluation we compare the performance of multiprocessor scheduling using global approaches: gFPDS, gFPPS, and gFPNS, and also partitioned approaches employing FPDS, FPPS, and FPNS on each processor.

Geodupa - a geography-driven partial membership algorithm

Trabalho apresentado no âmbito do Mestrado em Engenharia Informática, como requisito parcial para obtenção do grau de Mestre em Engenharia Informática

Efficient Legendre spectral tau algorithm for solving two-sided space-time Caputo fractional advection-dispersion equation

In this paper we present the operational matrices of the left Caputo fractional derivative, right Caputo fractional derivative and Riemann–Liouville fractional integral for shifted Legendre polynomials. We develop an accurate numerical algorithm to solve the two-sided space–time fractional advection–dispersion equation (FADE) based on a spectral shifted Legendre tau (SLT) method in combination with the derived shifted Legendre operational matrices. The fractional derivatives are described in the Caputo sense. We propose a spectral SLT method, both in temporal and spatial discretizations for the two-sided space–time FADE. This technique reduces the two-sided space–time FADE to a system of algebraic equations that simplifies the problem. Numerical results carried out to confirm the spectral accuracy and efficiency of the proposed algorithm. By selecting relatively few Legendre polynomial degrees, we are able to get very accurate approximations, demonstrating the utility of the new approach over other numerical methods.

A filter algorithm: comparison with NLP solvers

The purpose of this work is to present an algorithm to solve nonlinear constrained optimization problems, using the filter method with the inexact restoration (IR) approach. In the IR approach two independent phases are performed in each iteration—the feasibility and the optimality phases. The first one directs the iterative process into the feasible region, i.e. finds one point with less constraints violation. The optimality phase starts from this point and its goal is to optimize the objective function into the satisfied constraints space. To evaluate the solution approximations in each iteration a scheme based on the filter method is used in both phases of the algorithm. This method replaces the merit functions that are based on penalty schemes, avoiding the related difficulties such as the penalty parameter estimation and the non-differentiability of some of them. The filter method is implemented in the context of the line search globalization technique. A set of more than two hundred AMPL test problems is solved. The algorithm developed is compared with LOQO and NPSOL software packages.

Algorithm for the Parkinson’s disease behavioural models characterization using a biosensor

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

Understanding the internet banking adoption by Portuguese customers - a unified theory of acceptance and use of technology and perceived risk application.

Trabalho de Projeto apresentado como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação

Chagas' disease: an algorithm for donor screening and positive donor counseling

Classical serological screening assays for Chagas' disease are time consuming and subjective. The objective of the present work is to evaluate the enzyme immuno-assay (ELISA) methodology and to propose an algorithm for blood banks to be applied to Chagas' disease. Seven thousand, nine hundred and ninety nine blood donor samples were screened by both reverse passive hemagglutination (RPHA) and indirect immunofluorescence assay (IFA). Samples reactive on RPHA and/or IFA were submitted to supplementary RPHA, IFA and complement fixation (CFA) tests. This strategy allowed us to create a panel of 60 samples to evaluate the ELISA methodology from 3 different manufacturers. The sensitivity of the screening by IFA and the 3 different ELISA's was 100%. The specificity was better on ELISA methodology. For Chagas disease, ELISA seems to be the best test for blood donor screening, because it showed high sensitivity and specificity, it is not subjective and can be automated. Therefore, it was possible to propose an algorithm to screen samples and confirm donor results at the blood bank.

Diffusional kurtosis imaging using a fast heuristic constrained linear least squares algorithm: a plugin for OsiriX

Diffusion Kurtosis Imaging (DKI) is a fairly new magnetic resonance imag-ing (MRI) technique that tackles the non-gaussian motion of water in biological tissues by taking into account the restrictions imposed by tissue microstructure, which are not considered in Diffusion Tensor Imaging (DTI), where the water diffusion is considered purely gaussian. As a result DKI provides more accurate information on biological structures and is able to detect important abnormalities which are not visible in standard DTI analysis. This work regards the development of a tool for DKI computation to be implemented as an OsiriX plugin. Thus, as OsiriX runs under Mac OS X, the pro-gram is written in Objective-C and also makes use of Apple’s Cocoa framework. The whole program is developed in the Xcode integrated development environ-ment (IDE). The plugin implements a fast heuristic constrained linear least squares al-gorithm (CLLS-H) for estimating the diffusion and kurtosis tensors, and offers the user the possibility to choose which maps are to be generated for not only standard DTI quantities such as Mean Diffusion (MD), Radial Diffusion (RD), Axial Diffusion (AD) and Fractional Anisotropy (FA), but also DKI metrics, Mean Kurtosis (MK), Radial Kurtosis (RK) and Axial Kurtosis (AK).The plugin was subjected to both a qualitative and a semi-quantitative analysis which yielded convincing results. A more accurate validation pro-cess is still being developed, after which, and with some few minor adjust-ments the plugin shall become a valid option for DKI computation

EDP - A new estimation algorithm

The aim of this work project is to analyze the current algorithm used by EDP to estimate their clients’ electrical energy consumptions, create a new algorithm and compare the advantages and disadvantages of both. This new algorithm is different from the current one as it incorporates some effects from temperature variations. The results of the comparison show that this new algorithm with temperature variables performed better than the same algorithm without temperature variables, although there is still potential for further improvements of the current algorithm, if the prediction model is estimated using a sample of daily data, which is the case of the current EDP algorithm.

Acceptance and potential barriers to effective use of diagnostic tests for visceral leishmaniasis in an urban area in Brazil

Abstract: INTRODUCTION: Acceptance of the IT LEISH(r) and direct agglutination test- made in the Laboratório de Pesquisas Clínicas (DAT-LPC) by healthcare professionals and patients suspected of visceral leishmaniasis (VL) in Ribeirão das Neves was evaluated. METHODS: Ninety-two patients and 47 professionals completed three questionnaires. RESULTS: Eighty-eight (96%) patients considered fingertip blood collection a positive test feature, and 86% (37) and 91% of professionals considered the IT LEISH(r) easy to perform and interpret, respectively. All professionals classified the DAT-LPC as simple and easy. CONCLUSIONS: Patients and healthcare professionals in Ribeirão das Neves demonstrated a high degree of acceptance of the IT LEISH(r) and DAT-LPC.