scholarly journals CPU utilization prediction method based on composite model

2020 ◽  
Vol 1693 ◽  
pp. 012112
Author(s):  
Benran Hu ◽  
Wuzhuo Peng ◽  
Yanjun Li ◽  
Jiyuan Ren ◽  
Yiqun Li
Keyword(s):  
Prediction Method ◽  
Composite Model ◽  
Cpu Utilization

PERFORMANCE OF CPU UTILIZATION FOR IPv6 TUNNELING MECHANISMS ON LINUX BASED TESTBED

2014 ◽  
Vol 2 (1) ◽  
pp. 30-42
Author(s):  
A.S. Wahid ◽  
◽  
M. Othman ◽  
O. Sembiyev ◽  
M.H. Selamat ◽  
...  
Keyword(s):  
Cpu Utilization

Multilocus Analysis of Genetic Susceptibility to Myocardial Infarction in Russians: Replication Study

Acta Naturae ◽  
2017 ◽  
Vol 9 (4) ◽  
pp. 74-83
Author(s):  
N. G. Kukava ◽  
B. V. Titov ◽  
G. J. Osmak ◽  
N. A. Matveeva ◽  
O. G. Kulakova ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
Genetic Markers ◽  
Prognostic Significance ◽  
Cumulative Effect ◽  
Mthfr Gene ◽  
Composite Model ◽  
Replication Study ◽  
Epistatic Interactions ◽  
Multilocus Analysis ◽  
Lipid Metabolism Genes

In search of genetic markers of myocardial infarction (MI) risk, which have prognostic significance for Russians, we performed a replication study of MI association with genetic variants of PCSK9 (rs562556), APOE (epsilon polymorphism, rs7412 and rs429358), LPL (rs320), MTHFR (rs1801133), eNOS (rs2070744), and the 9p21 region (rs1333049) in 405 patients with MI and 198 controls. Significant MI association was observed with variants of the lipid metabolism genes (PCSK9, APOE and LPL), and of eNOS. The SNPs in the MTHFR gene and the 9p21 region were not significantly associated with MI one by one but were included in several different MI-associated allelic combinations identified by multilocus analysis. Since we have not revealed nonlinear epistatic interactions between the components of the identified combinations, we postulate that the cumulative effect of genes that form a combination arises from the summation of their small independent contributions. The prognostic significance of the additive composite model built from the PCSK9, APOE, LPL, and eNOS genes as genetic markers was assessed using ROC analysis. After we included these markers in the previously published composite model of individual genetic risk of MI, the prognostic efficacy in our sample reached AUC = 0.676. However, the results obtained in this study certainly need to be replicated in an independent sample of Russians.

Selection of a leading edge noise prediction method for PNoise

2018 ◽  
pp. 214-223
Author(s):  
AM Faria ◽  
MM Pimenta ◽  
JY Saab Jr. ◽  
S Rodriguez
Keyword(s):  
Wind Turbine ◽  
Turbine Blades ◽  
Prediction Method ◽  
Leading Edge ◽  
Wind Farms ◽  
Broadband Noise ◽  
Turbulence Energy ◽  
Noise Prediction ◽  
Migration Routes ◽  
Turbulent Inflow

Wind energy expansion is worldwide followed by various limitations, i.e. land availability, the NIMBY (not in my backyard) attitude, interference on birds migration routes and so on. This undeniable expansion is pushing wind farms near populated areas throughout the years, where noise regulation is more stringent. That demands solutions for the wind turbine (WT) industry, in order to produce quieter WT units. Focusing in the subject of airfoil noise prediction, it can help the assessment and design of quieter wind turbine blades. Considering the airfoil noise as a composition of many sound sources, and in light of the fact that the main noise production mechanisms are the airfoil self-noise and the turbulent inflow (TI) noise, this work is concentrated on the latter. TI noise is classified as an interaction noise, produced by the turbulent inflow, incident on the airfoil leading edge (LE). Theoretical and semi-empirical methods for the TI noise prediction are already available, based on Amiet’s broadband noise theory. Analysis of many TI noise prediction methods is provided by this work in the literature review, as well as the turbulence energy spectrum modeling. This is then followed by comparison of the most reliable TI noise methodologies, qualitatively and quantitatively, with the error estimation, compared to the Ffowcs Williams-Hawkings solution for computational aeroacoustics. Basis for integration of airfoil inflow noise prediction into a wind turbine noise prediction code is the final goal of this work.

Prediction Method of a System with Continuous Change Parameters Considering SNR Fluctuation

2018 ◽  
Vol 138 (9) ◽  
pp. 1075-1081
Author(s):  
Yasuhide Kobayashi ◽  
Mitsuyuki Saito ◽  
Yuki Amimoto ◽  
Wataru Wakita
Keyword(s):  
Prediction Method ◽  
Continuous Change

Validation of a Belt Model for Prediction of Hub Forces from a Rolling Tire4

2009 ◽  
Vol 37 (2) ◽  
pp. 62-102 ◽  
Author(s):  
C. Lecomte ◽  
W. R. Graham ◽  
D. J. O’Boy
Keyword(s):  
Internal Pressure ◽  
Equations Of Motion ◽  
Three Dimensional ◽  
Prediction Method ◽  
Analytical Models ◽  
Beam Model ◽  
Impedance Boundary ◽  
Bending Waves ◽  
Tire Rotation ◽  
Three Dimensional Models

Abstract An integrated model is under development which will be able to predict the interior noise due to the vibrations of a rolling tire structurally transmitted to the hub of a vehicle. Here, the tire belt model used as part of this prediction method is first briefly presented and discussed, and it is then compared to other models available in the literature. This component will be linked to the tread blocks through normal and tangential forces and to the sidewalls through impedance boundary conditions. The tire belt is modeled as an orthotropic cylindrical ring of negligible thickness with rotational effects, internal pressure, and prestresses included. The associated equations of motion are derived by a variational approach and are investigated for both unforced and forced motions. The model supports extensional and bending waves, which are believed to be the important features to correctly predict the hub forces in the midfrequency (50–500 Hz) range of interest. The predicted waves and forced responses of a benchmark structure are compared to the predictions of several alternative analytical models: two three dimensional models that can support multiple isotropic layers, one of these models include curvature and the other one is flat; a one-dimensional beam model which does not consider axial variations; and several shell models. Finally, the effects of internal pressure, prestress, curvature, and tire rotation on free waves are discussed.

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