Relationship between the Solar Radiation and Surface Temperature in Perlis

2012 ◽  
Vol 512-515 ◽  
pp. 143-147 ◽  
Author(s):  
Ismail Daut ◽  
Mohd Irwan Yusoff ◽  
Safwati Ibrahim ◽  
Muhamad Irwanto ◽  
Gomesh Nsurface

Statistical models for predicting the solar radiation have been developed. In any prediction of the solar radiation, an understanding of its characteristics is of fundamental importance. This study presents an investigation of a relationship between solar radiation and surface temperature in Perlis, Northern Malaysia for the year of 2006. To achieve this, the data are presented in daily averaged maximum and minimum surface temperature, and daily averaged solar radiation. Since the scatter plots represent the straight line, the linear regression model was selected to estimate the solar radiation. It was found that the linear correlation coefficient value is 0.7473 shows that a strong linear relationship between solar radiation and surface temperature. The analysis of variance R2 is 0.5585 that is; about 56 percent of the variability in temperature is accounted for by the straight-line fit to solar radiation. Based on the results, the fitted model is adequate to represent the estimation of solar radiation.

2002 ◽  
Vol 22 (2) ◽  
pp. 240-244 ◽  
Author(s):  
József Varga ◽  
Zsolt Szabo

Logan's graphical model is a robust estimation of the total distribution volume (DVt) of reversibly bound radiopharmaceuticals, but the resulting DVt values decrease with increasing noise. The authors hypothesized that the noise dependence can be reduced by a linear regression model that minimizes the sum of squared perpendicular rather than vertical ( y) distances between the data points and fitted straight line. To test the new method, 15 levels of simulated noise (repeated 2,000 times) were added to synthetic tissue activity curves, calculated from two different sets of kinetic parameters. Contrary to the traditional method, there was no ( P > 0.05) or dramatically decreased noise dependence with the perpendicular model. Real dynamic 11C (+) McN5652 serotonin transporter binding data were processed either by applying Logan analysis to average counts of large areas or by averaging the Logan slopes of individual-voxel data. There were no significant differences between the parameters when the perpendicular regression method was used with both approaches. The presented experiments show that the DVt calculated from the Logan plot is much less noise dependent if the linear regression model accounts for errors in both the x and y variables, allowing fast creation of unbiased parametric images from dynamic positron-emission tomography studies.


2012 ◽  
Vol 18 ◽  
pp. 1402-1412 ◽  
Author(s):  
S. Ibrahim ◽  
I. Daut ◽  
Y.M. Irwan ◽  
M. Irwanto ◽  
N. Gomesh ◽  
...  

2021 ◽  
Vol 23 (Supplement_G) ◽  
Author(s):  
Sofia Miceli ◽  
Velia Cassano ◽  
Elvira Clausi ◽  
Vittoria Monaco ◽  
Giuseppe Armentaro ◽  
...  

Abstract Recent studies demonstrated that in normoglucose-tolerant subjects (NGT), 1-h post load plasma glucose value ≥155 mg/dL, during OGTT, identifies a worse cardio-metabolic risk profile with increased risk for Type 2 Diabetes Mellitus (T2DM). T2DM patients present increased oxidative stress, due to high blood glucose levels, which plays a central role in the development of CV events. The aim of our study was to evaluate the correlation between oxidative stress and subclinical myocardial damage, assessed with speckle tracking echocardiography, in NGT patients with 1-h post load ≥155 mg/dL vs. NGT < 155 subjects, impaired glucose tolerance (IGT) and T2DM patients. We enrolled 100 Caucasian patients (61 M, 39 W, mean age 61.4 ± 10.7) afferent to CATAMERI study. Main exclusion criteria were CV complications, history of malignant or chronic respiratory disease, alcohol, drug influencing glucose metabolism or smoking abuse. All subjects underwent clinical and laboratory evaluation, OGTT and HOMA-IR. The serum values of the markers of oxidative stress (8-isoprostane and NOX-2) were assessed with ELISA sandwich. Statistical analysis was performed with ANOVA test, linear correlation analysis and stepwise multivariate linear regression model. According to OGTT results, subjects were divided into 4 groups: NGT < 155 (n = 30), NGT ≥ 155 (n = 24), IGT (n = 28), T2DM (n = 18). Serum levels of 8-isoprostane and NOX-2 were significantly increased (P < 0.0001) in NGT  ≥ 155 compared to NGT < 155 group, but similar with IGT, indicating an increase in oxidative stress with the worsening of the metabolic status. The left global systolic function, evaluated as myocardial deformation and global longitudinal strain (GLS), appeared progressively lower proceeding from the NGT < 155 group to the T2DM group (P < 0.0001). Moreover, for similar values of ejection fraction (EF), NGT ≥ 155 subjects presented reduced GLS compared to NGT < 155 (P = 0.001), but similar to IGT patients. The linear correlation analysis showed that endo/epi ratio was significantly and inversely correlated with 1 h post load glycaemia (r = −0.632, P < 0.0001), NOX-2 (r = −0.638, P < 0.0001), 8-isoprostane (r = −0.508, P < 0.0001); GLS was inversely correlated with 1 h post load glycaemia (r = −0.734, P < 0.0001) and directly and significantly correlated with 8-isoprostane (r = 0.564, P < 0.0001), NOX-2 (r = 0.625, P < 0.0001). From stepwise multivariate linear regression model, NOX-2 resulted the major predictor of endo/epi ratio, justifying 40.7% of its variation. 1-h post load glycaemia was the second predictor of endo/epi ratio justifying another 9.2% of its variation. Similarly 1-h post load glycaemia was the strongest predictor of the GLS, explaining 53.9% of its variation. Our study demonstrated that NGT ≥ 155 subjects present functional alterations of myocardial contractile fibres, compared to NGT < 155 subjects, but similar to IGT, and these alterations are correlated with oxidative stress. Moreover, GLS is able to identify early alterations in the contractility of subendocardial longitudinal fibres long before the alteration of EF. This data have a central role in ongoing research on the association between hyperglycaemia at 1-h post load and CV risk.


2013 ◽  
Vol 2 (3) ◽  
pp. 121-126 ◽  
Author(s):  
Michael S. Okundamiya ◽  
Israel E. Okpamen

The growing anxiety on the negative effects of fossil fuels on the environment and the global emission reduction targets call for a more extensive use of renewable energy alternatives. Efficient solar energy utilization is an essential solution to the high atmospheric pollution caused by fossil fuel combustion. Global solar radiation (GSR) data, which are useful for the design and evaluation of solar energy conversion system, are not measured at the forty-five meteorological stations in Nigeria. The dearth of the measured solar radiation data calls for accurate estimation. This study proposed a temperature-based linear regression, for predicting the monthly average daily GSR on horizontal surfaces, at Warri (latitude 5.020N and longitude 7.880E) an oil city located in the south-south geopolitical zone, in Nigeria. The proposed model is analyzed based on five statistical indicators (coefficient of correlation, coefficient of determination, mean bias error, root mean square error, and t-statistic), and compared with the existing sunshine-based model for the same study. The results indicate that the proposed temperature-based linear regression model could replace the existing sunshine-based model for generating global solar radiation data. Keywords: air temperature; empirical model; global solar radiation; regression analysis; renewable energy; Warri


2018 ◽  
Vol 11 (4) ◽  
pp. 617
Author(s):  
Elkin Perez ◽  
Ivan Dario Toro Jaramillo

Purpose: The transformation and exploitation of knowledge are part of the absorptive capacity carried out. The article presents, from a linear regression model, the analysis of these two dimensions in 155 organizations in Brazil and 61 in Colombia.Design/methodology/approach: The methodology uses analysis of variance method and a linear regression model. The findings and Conclusions suggest the existence of a positive linear correlation between transformation and exploitation of external knowledge inside the studied organizations.Findings: The analysis of variance method and a linear regression model applied to a sample of 61 Colombian SMEs (Dane, 2012) and 155 SMEs of Brazilian ones (IBGE, 2011), results showed the existence of a positive linear correlation between the variables “transformation” and “exploitation” of knowledge, which shows interdependence between these two dimensions that make up the realized absorptive capacity.Practical implications: Research helps to show that if a high level of development of the capacity of knowledge transformation leads to a high level of organizational knowledge exploitation is verified.Originality/value: The empirical demonstration of the relationship between the dimensions that are part of the absorption capacity carried out, has been very little proven in the world. The research presents the first measurement that in organizations of Brazil and Colombia is carried out on the absorption capacity carried out.


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