This paper deals with the computation of ground resistance, surface voltage, touch voltage and step voltage, to mesh with horizontal wires arranged in different angles. The computerprogram implemented used in the mat...
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ISBN:
(纸本)9781467387576
This paper deals with the computation of ground resistance, surface voltage, touch voltage and step voltage, to mesh with horizontal wires arranged in different angles. The computerprogram implemented used in the mathematical modeling is based on the method proposed by Heppe, which allows obtaining the grounding parameters for homogeneous soil and soil stratified in two layers. Furthermore, the results obtained by the Variable Currents Method (VCM) have been compared to traditional methods and the simplified method of ANSI-IEEE Std. 80/2013. They also present the results using a grounding grid with wires on various angles.
The aim of this study was to test the correlation between a two dimensional (2D) and three dimensional (3D) biomechanical photogrammetric model, with inspiratory and expiratory lung capacities in adolescents. This was...
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Synchronization of transcutaneous functional electrical stimulation (TFES) with the spontaneous inspiration and expiration phases is a new approach for respiratory rehabilitation. One of the requirements for proper op...
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ISBN:
(纸本)9781424492695
Synchronization of transcutaneous functional electrical stimulation (TFES) with the spontaneous inspiration and expiration phases is a new approach for respiratory rehabilitation. One of the requirements for proper operation is the identification of cough events to automatically change the stimulation parameters in order to increase muscle strength during the cough. The aim of this work is to assess the viability in detection of cough events with a mechanomyographic (MMG) sensor on the abdominal region, and to evaluate if it can be used simultaneously with the synchronized TFES system. An MMG sensor was placed in contact with skin lined with the last ribs, above the rectus abdominis muscle and the linea alba. Two tests were accomplished which included quiet breathing, speaking and coughing episodes. The developed system efficiently distinguishes quiet breathing and coughing signals, but speaking is still confused with coughing episodes. The MMG sensor suffered detectable amplitude changes mainly during the forced expiration phase of the cough, but it could also detect the compression phase at lower amplitude. Therefore, the MMG system can be used for cough detection in this application.
In this paper heuristics are proposed for finding the shortest loopless path, from a source node to a target node, that visits a given set of nodes in a directed graph, such that it can be protected using a node-disjo...
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In this paper heuristics are proposed for finding the shortest loopless path, from a source node to a target node, that visits a given set of nodes in a directed graph, such that it can be protected using a node-disjoint path. This type of problem may arise due to network management constraints. The problem of calculating the shortest path that visits a given set of nodes is at least as difficult as the traveling salesman problem, and it has not received much attention. Nevertheless an efficient integer linear programming (ILP) formulation has been recently proposed for this problem. Here, the ILP formulation is adapted to include the constraint that the obtained path will be able to be protected by a node-disjoint path. Computational experiments show that this approach, namely in large networks, may fail to obtain a solution in a reasonable amount of time. Therefore three versions of a heuristic are proposed, for which extensive computational results show that they are able to find a solution in most cases, and that the calculated solutions present an acceptable relative error regarding the cost of the optimal active path. Further the CPU time required by the heuristics is significantly smaller than the required by the used ILP solver.
This work presents a methodology for using Principal Component Analysis (PCA) and Genetic programming (GP) for the classification of multi-class objects found in digital images. The image classification process is per...
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This work presents a methodology for using Principal Component Analysis (PCA) and Genetic programming (GP) for the classification of multi-class objects found in digital images. The image classification process is performed by using features extracted from images, through feature extraction algorithms, reduced by PCA and labeled by similarity comparing with other previously classified objects. GP uses two sets of elements: terminals, composed by the features extracted by PCA; and non-terminals, composed by algebraic operations. The fitness function was defined by the product of sensibility and specificity, two performance measures. A penalty term is also used to decrease the number of nodes of the tree, while minimally affecting the quality of solutions. The proposed approach was applied to set of 2739 digital images divided into objects representing airplanes, motorbikes, background from google, faces and watch classes, provided by the Caltech101 image database. The proposed approach was compared with SVM, Naïve Bayes and C4.5. Results suggest that the approach PCA+GP is able to evolve solutions for the problem as a simple classification rule with true positive rate above 70%. Additionally, we observe that PCA+PG obtained results slightly better than SVM and C4.5, besides these methods give a result that is not comprehensible by humans.
Background: Experimental and epidemiological studies indicate an association between exposure to particulate matter (PM) air pollution and increased risk of type 2 diabetes. In view of the high and increasing prevalen...
Background: Experimental and epidemiological studies indicate an association between exposure to particulate matter (PM) air pollution and increased risk of type 2 diabetes. In view of the high and increasing prevalence of diabetes, we aimed to quantify the burden of type 2 diabetes attributable to PM2·5 originating from ambient and household air pollution. Methods: We systematically compiled all relevant cohort and case-control studies assessing the effect of exposure to household and ambient fine particulate matter (PM2·5) air pollution on type 2 diabetes incidence and mortality. We derived an exposure–response curve from the extracted relative risk estimates using the MR-BRT (meta-regression—Bayesian, regularised, trimmed) tool. The estimated curve was linked to ambient and household PM2·5 exposures from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019, and estimates of the attributable burden (population attributable fractions and rates per 100 000 population of deaths and disability-adjusted life-years) for 204 countries from 1990 to 2019 were calculated. We also assessed the role of changes in exposure, population size, age, and type 2 diabetes incidence in the observed trend in PM2·5-attributable type 2 diabetes burden. All estimates are presented with 95% uncertainty intervals. Findings: In 2019, approximately a fifth of the global burden of type 2 diabetes was attributable to PM2·5 exposure, with an estimated 3·78 (95% uncertainty interval 2·68–4·83) deaths per 100 000 population and 167 (117–223) disability-adjusted life-years (DALYs) per 100 000 population. Approximately 13·4% (9·49–17·5) of deaths and 13·6% (9·73–17·9) of DALYs due to type 2 diabetes were contributed by ambient PM2·5, and 6·50% (4·22–9·53) of deaths and 5·92% (3·81–8·64) of DALYs by household air pollution. High burdens, in terms of numbers as well as rates, were estimated in Asia, sub-Saharan Africa, and South Am
Presents the introductory welcome message from the conference proceedings. May include the conference officers' congratulations to all involved with the conference event and publication of the proceedings record.
Presents the introductory welcome message from the conference proceedings. May include the conference officers' congratulations to all involved with the conference event and publication of the proceedings record.
This paper proposes an economic dispatch strategy to accommodate photovoltaic (PV) generation, using the solar radiation historical data. The stochastic scenario based economic dispatch approach is formulated in the c...
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ISBN:
(纸本)9781479979943
This paper proposes an economic dispatch strategy to accommodate photovoltaic (PV) generation, using the solar radiation historical data. The stochastic scenario based economic dispatch approach is formulated in the context of a power system with photovoltaic generators. The stochastic nature of PV power is represented through scenarios. The strategy proposed addresses the improvement of system ability to maintain the power balance while minimizing the management costs of power system. The benefits of this approach are illustrated using a modified version of the IEEE 30-bus test system. The results obtained show that the proposed model is appropriated to accommodate the estimation error of PV generation, while providing economic benefits.
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