42 research outputs found

    Active node determination for correlated data gathering in wireless sensor networks

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    Cataloged from PDF version of article.In wireless sensor network applications where data gathered by different sensor nodes is correlated, not all sensor nodes need to be active for the wireless sensor network to be functional. Given that the sensor nodes that are selected as active form a connected wireless network, the inactive sensor nodes can be turned off. Allowing some sensor nodes to be active and some sensor nodes inactive interchangably during the lifecycle of the application helps the wireless sensor network to have a longer lifetime. The problem of determining a set of active sensor nodes in a correlated data environment for a fully operational wireless sensor network can be formulated as an instance of the connected correlation-dominating set problem. In this work, our contribution is twofold; we propose an effective and runtime-efficient iterative improvement heuristic to solve the active sensor node determination problem, and a benefit function that aims to minimize the number of active sensor nodes while maximizing the residual energy levels of the selected active sensor nodes. Extensive simulations we performed show that the proposed approach achieves a good performance in terms of both network lifetime and runtime efficiency. © 2012 Elsevier B.V. All rights reserved

    Investigation of load balancing scalability in space plasma simulations

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    In this study we report the load-balancing performance issues that are observed during the petascaling of a space plasma simulation code developed at the Finnish Meteorological Institute (FMI). The code models the communication pattern as a hypergraph, and partitions the computational grid using the parallel hypergraph partitioning scheme (PHG) of the Zoltan partitioning framework. The result of partitioning determines the distribution of grid cells to processors. It is observed that the initial partitioning and data distribution phases take a substantial percentage of the overall computation time. Alternative (graph-partitioning-based) schemes that provide better balance are investigated. Comparisons in terms of effect on running time and load-balancing quality are presented. Test results on Juelich BlueGene/P cluster are reported. © 2013 Springer-Verlag

    Analyzing and enhancing OSKI for sparse matrix-vector multiplication

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    Sparse matrix-vector multiplication (SpMxV) is a kernel operation widely used in iterative linear solvers. The same sparse matrix is multiplied by a dense vector repeatedly in these solvers. Matrices with irregular sparsity patterns make it difficult to utilize cache locality effectively in SpMxV computations. In this work, we investigate single- and multiple-SpMxV frameworks for exploiting cache locality in SpMxV computations. For the single-SpMxV framework, we propose two cache-size-aware top-down row/column-reordering methods based on 1D and 2D sparse matrix partitioning by utilizing the column-net and enhancing the row-column-net hypergraph models of sparse matrices. The multiple-SpMxV framework depends on splitting a given matrix into a sum of multiple nonzero-disjoint matrices so that the SpMxV operation is performed as a sequence of multiple input- and output-dependent SpMxV operations. For an effective matrix splitting required in this framework, we propose a cache-size-aware top-down approach based on 2D sparse matrix partitioning by utilizing the row-column-net hypergraph model. The primary objective in all of the three methods is to maximize the exploitation of temporal locality. We evaluate the validity of our models and methods on a wide range of sparse matrices by performing actual runs through using OSKI. Experimental results show that proposed methods and models outperform state-of-the-art schemes.Comment: arXiv admin note: substantial text overlap with arXiv:1202.385

    Risk Factors Associated with Adverse Fetal Outcomes in Pregnancies Affected by Coronavirus Disease 2019 (COVID-19): A Secondary Analysis of the WAPM study on COVID-19

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    To evaluate the strength of association between maternal and pregnancy characteristics and the risk of adverse perinatal outcomes in pregnancies with laboratory confirmed COVID-19. Secondary analysis of a multinational, cohort study on all consecutive pregnant women with laboratory-confirmed COVID-19 from February 1, 2020 to April 30, 2020 from 73 centers from 22 different countries. A confirmed case of COVID-19 was defined as a positive result on real-time reverse-transcriptase-polymerase-chain-reaction (RT-PCR) assay of nasal and pharyngeal swab specimens. The primary outcome was a composite adverse fetal outcome, defined as the presence of either abortion (pregnancy loss before 22 weeks of gestations), stillbirth (intrauterine fetal death after 22 weeks of gestation), neonatal death (death of a live-born infant within the first 28 days of life), and perinatal death (either stillbirth or neonatal death). Logistic regression analysis was performed to evaluate parameters independently associated with the primary outcome. Logistic regression was reported as odds ratio (OR) with 95% confidence interval (CI). Mean gestational age at diagnosis was 30.6\ub19.5 weeks, with 8.0% of women being diagnosed in the first, 22.2% in the second and 69.8% in the third trimester of pregnancy. There were six miscarriage (2.3%), six intrauterine device (IUD) (2.3) and 5 (2.0%) neonatal deaths, with an overall rate of perinatal death of 4.2% (11/265), thus resulting into 17 cases experiencing and 226 not experiencing composite adverse fetal outcome. Neither stillbirths nor neonatal deaths had congenital anomalies found at antenatal or postnatal evaluation. Furthermore, none of the cases experiencing IUD had signs of impending demise at arterial or venous Doppler. Neonatal deaths were all considered as prematurity-related adverse events. Of the 250 live-born neonates, one (0.4%) was found positive at RT-PCR pharyngeal swabs performed after delivery. The mother was tested positive during the third trimester of pregnancy. The newborn was asymptomatic and had negative RT-PCR test after 14 days of life. At logistic regression analysis, gestational age at diagnosis (OR: 0.85, 95% CI 0.8-0.9 per week increase; p<0.001), birthweight (OR: 1.17, 95% CI 1.09-1.12.7 per 100 g decrease; p=0.012) and maternal ventilatory support, including either need for oxygen or CPAP (OR: 4.12, 95% CI 2.3-7.9; p=0.001) were independently associated with composite adverse fetal outcome. Early gestational age at infection, maternal ventilatory supports and low birthweight are the main determinants of adverse perinatal outcomes in fetuses with maternal COVID-19 infection. Conversely, the risk of vertical transmission seems negligible

    Electrical Characterization of GaN Nano Columnar Structures

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    Correlations between the ICIQ-SF score and urodynamic findings

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    Aims: The primary aim of this prospective study was to examine the correlations between "The International Consultation on Incontinence Questionnaire-Short Form (ICIQ-SF)" score and urodynamic findings in patients with urge incontinence. In addition, we aimed to observe the alterations of these parameters with antimuscarinic therapy. Methods: Between January and December 2005, patients referred to our department with urge incontinence were examined. After taking a detailed clinical history, physical examination, and urinalysis, each patient was asked to complete an ICIQ-SF questionnaire. We carried out subtracted cystometry according to a fixed protocol on all patients. Patients who were defined as detrusor overactivity incontinent were given antimuscarinic therapy for 3 months. Following treatment, filling cystometry and ICIQ-SF scoring were repeated in all patients. All pre- and post-treatment data of 18 male and 42 female patients were transferred to the SPSS 11.0 for Windows program, and statistical analyses were performed. Results: The patients' ages ranged from 28 to 70 (mean 49.8) years. We found statistically significant differences between the pre- and post-treatment parameters (mean ICIQ-SF score, first sensation, cystometric capacity, maximum detrusor pressure, compliance; P < 0.01). We found negative correlation between pre-treatment mean ICIQ-SF score and first sensation (correlation coefficient -0.266, P < 0.05) and positive correlation between pre-treatment mean ICIQ-SF score and maximum detrusor pressure (correlation coefficient 0.4, P < 0.01). Conclusions: ICIQ-SF scoring is a practical and reliable method for baseline and post-treatment evaluation of patients with urge incontinence. Significant correlation exists between ICIQ-SF score and urodynamic parameters. © 2007 Wiley-Liss, Inc
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