scholarly journals Citation Trend of Indian Physics and Astronomy Research during 2005 2020 through the Lens of Some New Indicators

2021 ◽  
Vol 42 (1) ◽  
pp. 30-37
Author(s):  
Gopinath Das ◽  
Bidyarthi Dutta ◽  
Anup Kumar Das
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Research Output ◽  
Fundamental Equation ◽  
Temporal Variations ◽  
Time Span ◽  
Average Error ◽  
Regression Equations ◽  
Close Proximity ◽  
Coefficients Of Variations

The indicator Citation Swing Factor (CSF) has recently been developed to quantitatively measure the diffusion process from h-core zone to h-core excess zone. This paper calculated CSF for Indian physics and astronomy research output appeared in selective Indian journals since 2005 to 2020. The theoretical values of CSF are also calculated on the basis of its fundamental equation and same was compared it with the respective observed values. The average error over entire time span is found 2.26 per cent indicating close proximity between theoretically expected and practically observed values. Besides, three other scientometric indicators are introduced here, viz. Time-Normalised Total Cited Ratio (TC), Time-Normalised Cited Uncited Ratio (CU) and Time-Normalised Total Uncited Ratio (TU). Of these four indicators, the variation of TC is highest (1.76), followed by TU (0.53), CU (0.37) and CSF(E) (0.09), as evident from the values of respective Coefficients of Variations. The numerical values of these indicators are found out for the same sample and the temporal variations along with their mutual interrelationships are determined by regression analysis. It is observed that the three indicators, TC, CU and TU are mutually interrelated through the following linear regression equations, i.e. TC = -0.76 + 1.88*TU and CU = -0.201 + 0.34*TU.

scholarly journals Cephalometric Floating Norms as a Guide toward a Harmonious Individual Craniofacial Pattern among Filipinos

2009 ◽  
Vol 79 (6) ◽  
pp. 1162-1168 ◽  
Author(s):  
Marian Almyra Sevilla-Naranjilla ◽  
Ingrid Rudzki-Janson
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Multiple Regression Analysis ◽  
Multiple Regression ◽  
Standard Error ◽  
Pearson Correlation ◽  
Linear Regression Analysis ◽  
Regression Equations ◽  
Correlated Variables ◽  
The Individual

Abstract Objective: To construct a harmony box based on correlated cephalometric variables, which may serve as a valuable diagnostic tool in orthodontic treatment planning, by analyzing the harmonious relationships of existing individual craniofacial patterns among Filipinos. Materials and Methods: Eighty-one subjects, 37 females and 44 males, were selected from the student population of a University according to established inclusion criteria. Five cephalometric angular measurements were obtained and digitized. Pearson correlation coefficients described the high association among the five variables. The bivariate linear regression analysis was used to construct a harmony box, which contained the cephalometric floating norms of the five correlated variables. Multiple regression analysis and the standard error of the estimate were calculated to construct the harmony schema, which describes the individual craniofacial pattern. Results: Correlations between the five variables were significant at .001 and .05 levels. Linear regression equations with corresponding r2 and standard error of the estimate (SE) were illustrated as the harmony box. The multiple correlation coefficient R, the adjusted R2, and the SE when one of the five measured variables was predicted from the remaining four by means of a multiple regression analysis were displayed as the harmony schema. Conclusion: The cephalometric floating norms describing the individual craniofacial pattern among Filipinos were established based on five correlated variables in the form of a harmony box.

Proton NMR Analysis of Octane Number for Motor Gasoline: Part IV

1992 ◽  
Vol 46 (8) ◽  
pp. 1294-1300 ◽  
Author(s):  
M. Ichikawa ◽  
N. Nonaka ◽  
H. Amano ◽  
I. Takada ◽  
S. Ishimori ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Aromatic Compounds ◽  
Octane Number ◽  
Proton Magnetic Resonance ◽  
Linear Regression Analysis ◽  
Regression Equations ◽  
Nmr Analysis ◽  
Motor Gasoline ◽  
The Relationship

Software (a program) for predicting the octane number of motor gasoline by proton magnetic resonance (PMR) spectrometry has been formulated. At the same time, a method has been studied to predict the composition of gasoline (in terms of the contents of paraffin, olefin, and aromatic compounds). The formulated program was evaluated by using it to predict the octane numbers of 31 samples of marketed summer gasoline (including 16 regular and 15 premium products), whose octane numbers and compositions were identified according to the ASTM standards. Also, the relationship between the PMR spectrum and gasoline composition was subjected to linear regression analysis by using the 31 samples whose octane numbers were calculated, and the appropriateness of the resultant regression equations was assessed. This report concerns the results of the study in which the octane numbers of the 31 samples were satisfactorily predicted by the formulated program and useful linear regression equations were obtained for the prediction of the composition of gasoline.

PENGARUH PENGEMBANGAN DAN MOTIVASI TERHADAP PRESTASI KERJA PEGAWAI DI PT. BEKASI SURYA PRATAMA

2020 ◽  
Vol 2 (2) ◽  
pp. 251-275
Author(s):  
Hendra Lesmana
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Job Performance ◽  
Significant Influence ◽  
Work Performance ◽  
Linear Regression Analysis ◽  
Regression Equations ◽  
F Test ◽  
Performance Variable ◽  
The Third

  This study aims to determine and analyze (1) the influence of development on employee job performance (2) the influence of  motivation on employee job performance (3) the influence of development and  motivation together towards achievement of employees in PT. Bekasi Surya Pratama. The experiment was conducted at PT. Bekasi Surya Pratama with 49 respondents and the research conducted from July to November 2010. The analysis is carried out linear regression analysis, analysis of determination, t test and F test. The hypotheses were (1) the influence of development (X1) will be increased employees  job performance (Y) (2) the influence of motivation (X2) will be increased employees job performance (Y) (3) the influence of development (X1) and motivation (X2) are jointly working towards increased employees job performance (Y)  in PT. Bekasi Surya Pratama. Based on the testing of the first hypothesis might be any positive and significant influence between development (X1 variable) with Job Performance (variable Y) of employees in the PT. Bekasi Surya Pratama based tcount of 2.142, was larger than ttable  (ttable = 2.01). Thus the Ha accepted and H0 is rejected. Based on the testing of the second hypothesis might be any positive and significant influence between motivation (variable X2) with Job Performance (variable Y) of employees in PT. Bekasi Surya Pratama based tcount of 3.706, was larger than ttable  (ttable = 2.01). Thus the Ha accepted and H0 is rejected. Based on the testing of the third hypothesis might be any positive and significant influence between development (variable X1) and  Motivation (X2) with Job Performance (variable Y) of employees in the PT. Bekasi Surya Pratama based on the value of F test Based on calculations, the value of  Fcount  = 201.311. Fcount greater than Ftable (Ftable = 3.20). Thus the Ha accepted and H0 is rejected. The result of linear regression equations to show the effect of development (X1) and motivation (X2) on work performance (Y) employees in the PT. Bekasi Surya Pratama obtained Y = 2.491 +0.358 X1 +0.645 X2.

Is antiglycolysis required for routine glucose analysis?

1979 ◽  
Vol 25 (12) ◽  
pp. 2038-2039 ◽  
Author(s):  
K Sazama ◽  
E A Robertson ◽  
R A Chesler
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Continuous Flow ◽  
Linear Regression Analysis ◽  
Serum Glucose ◽  
Time Span ◽  
Plasma Samples ◽  
Specimen Handling ◽  
The Difference ◽  
Glucose Analysis

Abstract We obtained -68 pairs of simultaneously drawn serum and fluoride-oxalate plasma samples from patients and analyzed them by a continuous-flow (AutoAnalyzer II) glucose oxidase method. Glucose concentrations ranged from 370 to 3530 mg/L. Glucose concentrations for samples obtained in the fluoride-oxalate preservative averaged 42 +/- 35 mg/L (mean +/- SD) higher than serum. The magnitude of this difference was independent of glucose concentration. Linear-regression analysis of 270 pairs for which the time from collection to separation was recorded indicated that the difference between serum and plasma increased by 0.32 mg/L per minute of delay over a time span of 15 to 295 min. These differences are smaller than those described in standard textbooks. We conclude that, with the specimen-handling process used in our hospital, serum glucose determinations are clinically acceptable.

scholarly journals Cephalometric Floating Norms for Czech Adults

2012 ◽  
Vol 113 (4) ◽  
pp. 271-278
Author(s):  
Adam Řeháček ◽  
M. Janega ◽  
P. Hofmanová ◽  
T. Dostálová
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Multiple Regression Analysis ◽  
Multiple Regression ◽  
Standard Error ◽  
Regression Equations ◽  
Model Combining ◽  
Skeletal Pattern ◽  
The Face ◽  
The Individual

The purpose of this study was to establish floating cephalometric norms for the description of the individual skeletal pattern in Czech adults. Floating norms provide a method of analysis that uses the variability of the associations among suitable cephalometric measures, on the basis of the regression model combining both sagittal and vertical skeletal parameters. Harmony box is a simple and useful tool for diagnostics of orthodontic anomalies according to individual cephalometric norms. 118 subjects, 53 male and 65 female, from Czech population were selected. The method of multiple regression analysis was used to determine interdependence among five cephalometric variables of the sample. Linear regression equations with corresponding r2 and standard error of the estimate (SE) were then illustrated as the harmony box. The results construct a harmony box based on correlated cephalometric variables. The multiple regression analysis of the data is graphically illustrated as a harmony schema which divides harmony box in three zones according to the type of the face – prognathic, orthognathic and retrognathic. The cephalometric floating norms describing the individual craniofacial pattern among Czech adults were established based on five correlated variables in the form of a harmony box.

scholarly journals The Model of Heavy Industries Profitability

2021 ◽  
Vol 12 (4) ◽  
pp. 1596-1604
Author(s):  
R. Nasution, Et. al.
Keyword(s):  
Regression Analysis ◽  
Data Analysis ◽  
Linear Regression ◽  
Cost Efficiency ◽  
Stock Exchange ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Time Span ◽  
Business Conditions ◽  
Ease Of Access

The purpose of this study was to analyze the influence of cash turnover, receivebles turnover and sales on profitability of Astra International registered on Indonesian Stock Exchange within the time span of  eight years (2011 to 2018). Methods of data analysis using the classic assumption test, multiple linear regression analysis, F test, and t test. The Finding  of this study  were cash turnover, receivable turnover,and sales have  a simultaneously affect on profitability of Firm, Whereas  the two variables, cash turnover and sales had a partially positive affect on profitability  of Firm, Meanwhile  receivable turnover had a partially negative affect on profitability  of Firm. The implication of this study to the firm in facing challenging business conditions is to implement cost efficiency programs that emphasize various innovative steps and at the same time focus on the availability of distribution support, ease of access and guaranteed product and service quality for customers.  

scholarly journals Is cranial multi-detector computed tomography imaging valuable for stature estimation in Egyptian population?

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Rana Adel ◽  
Hala Mohamed Ahmed ◽  
Osama A. Hassan ◽  
Ehab A. Abdelgawad
Keyword(s):  
Computed Tomography ◽  
Regression Analysis ◽  
Linear Regression ◽  
Linear Regression Analysis ◽  
Regression Equations ◽  
Simple Linear Regression ◽  
Stature Estimation ◽  
Egyptian Population ◽  
Orbital Height ◽  
Multi Detector Computed Tomography

Abstract Background and objectives Stature estimation is an initial and essential component of any medico-legal investigations. However, it becomes more challenging when only skull remains are available. So, the goal of this study is to assess stature estimation using cranial multi-detector computed tomography (MDCT) images in a sample of the Egyptian population. Methods This clinical study was conducted on 150 Egyptian subjects underwent cranium MDCT with age ranged from 21 to 60 years. The measurements used were maximum cranial breadth, minimum frontal breadth, upper facial breadth, bizygomatic breadth, orbital height, orbital breadth, parietal chord, bimastoidale, maximum cranial length, basion-bregma height, cranial base length, and basion-prosthion length. Results The results revealed that stature and craniofacial measurements of males were significantly higher than those of females, all measurements were significantly positively correlated with stature in pooled cases, but the correlation coefficient differs in separate sex. Simple linear regression for stature estimation showed that the least standard error of estimate (SEE) values for the regression equations obtained when using bizygomatic breadth in pooled cases (7.9 cm) and in males only (5.7 cm), while in females using parietal chord had the least SEE (6.8 cm). Using multiple and stepwise regression analysis reported lower SEE values than simple linear regression analysis. Conclusion On the basis of this study, it is concluded that the cranial measurements obtained from MDCT images have limited utility in stature estimation among Egyptians, but could be used as an alternative method in cases where the best predictors, such as long bones, are not available.

scholarly journals Analysis of Window Components Affecting U-Value Using Thermal Transmittance Test Results and Multiple Linear Regression Analysis

2018 ◽  
Vol 2018 ◽  
pp. 1-7
Author(s):  
Sang-Tae No ◽  
Jun-Sik Seo
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Thermal Performance ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Design Stage ◽  
Regression Equations ◽  
Test Results ◽  
Window System

Currently, global warming is accelerating, and many countries are trying to reduce greenhouse emission by enforcing low energy building. And the thermal performance of the windows is one of the factors that greatly influence the heating and cooling energy consumption of buildings. According to the development of the window system, the thermal performance of the windows is greatly improved. There are simulations and tests for window thermal performance evaluation techniques, but both are time consuming and costly. The purpose of this study is to develop a convenient method of predicting U-value at the window system design stage by multiple linear regression analysis. 532 U-value test results were collected, and window system components were set as independent values. As a result, the number of windows (single or double) among the components of the window has the greatest effect on the U-value. In this research, two regression equations for predicting U-value of window system were suggested, and the estimated standard errors of equations were 0.2569 in single window and 0.2039 in double window.

Analytical Representation of the van Everdingen-Hurst Aquifer Influence Functions for Reservoir Simulation

1985 ◽  
Vol 25 (03) ◽  
pp. 405-406 ◽  
Author(s):  
J.R. Fanchi
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Reservoir Simulation ◽  
Linear Regression Analysis ◽  
Computer Work ◽  
Influence Functions ◽  
Regression Equations ◽  
Dimensionless Time ◽  
Influx Rate ◽  
Reservoir Simulator

Abstract Linear regression analysis has been used to develop some simple analytical expressions for the van Everdingen-Hurst aquifer influx influence functions. Regression results are presented for a variety of aquifer radius/reservoir radius ratios. The regression equations are designed for use in reservoir engineering applications, especially reservoir simulation. Introduction A reservoir-aquifer system can be modeled by using a reservoir simulator in which small gridblocks define the reservoir and increasingly larger gridblocks define the aquifer. This approach has the disadvantage of increased computer storage and computing time requirements because additional gridblocks are needed to model the aquifer. A widely used and more cost-effective means of representing an aquifer is to compute aquifer influx with an analytical model. Among the more popular analytical aquifer models in use today is the Carter-Tracy modification of the van Everdingen-Hurst unsteadystate aquifer influx calculation. The Carter-Tracy aquifer influx rate calculation requires information about dimensionless pressure p and its first derivative P as functions of dimensionless time t . Usually, the relationship between t and p is available in the reservoir simulator in tabular form for the infinite acting constant terminal rate case only. The program determines p and p for a given t by using a numerical program determines p and p for a given t by using a numerical interpolation scheme. An alternative approach that requires less computer work while providing equivalent or greater accuracy than the table look-up method is presented here. Description of Method A linear regression analysis has been used to develop analytical representations of the Carter-Tracy influence functions. The regression equations, the regression coefficients, correlation range limits, and measures of the linear regression validity are presented in Table 1 for a number of commonly encountered r/r cases. Plots of these expressions are shown in Figs. 1a and 1b. JPT P. 405

scholarly journals Corruption as a Factor Forming the Level of Domestic Trust: Topological Model and Regressional Analysis

2020 ◽  
pp. 49-61
Author(s):  
N.Y. Yegorova ◽  
E.A. Koroleva ◽  
A.V. Gorlov
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Research Methods ◽  
Topological Model ◽  
General View ◽  
Regression Equations ◽  
Correlation And Regression Analysis ◽  
Relationship Of ◽  
The Relationship ◽  
Scenario Approach

The article discusses the concepts of trust and corruption in society and explores the interdependence between them using the international Edelman Trust Barometer (ETB) Corruption Perceptions Index (CPI). Research methods are: 1) the topological model proposed by the authors, built on the averaged values of these indices; 2) correlation and regression analysis; 3) scenario approach based on the formation of «range corridors». The analysis of the topological model was carried out, on the basis of which the zones of low, medium and high levels of corruption were identified, with a characteristic specific type of relationship between the ETB and CPI indices; the general view of the dependence of the level of trust on corruption in the form of a horizontal S-shaped curve is approximately defined. Statistically significant linear regression equations were obtained, reflecting the relationship of the considered indices for three countries (Germany, Colombia, France).

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