Fast Quantitative Correlation Analysis and Information Deviation Analysis for Evaluating the Performances of Image Fusion Techniques

2004 ◽  
Vol 53 (5) ◽  
pp. 1441-1447 ◽  
Author(s):  
Q. Wang ◽  
Y. Shen ◽  
Y. Zhang ◽  
J.Q. Zhang
Keyword(s):  
Correlation Analysis ◽  
Image Fusion ◽  
Quantitative Correlation ◽  
Deviation Analysis

scholarly journals EYE AND FOOT COORDINATION CONTRIBUTION ON PASSING SKILLS IN FUTSAL ATLET AT SDIT IQRA BENGKULU

2018 ◽  
Vol 1 (1) ◽  
Author(s):  
Desrio Windoro
Keyword(s):  
Data Analysis ◽  
Correlation Analysis ◽  
Significant Relationship ◽  
Correlation Method ◽  
Homogeneity Test ◽  
Positive Contribution ◽  
Significance Level ◽  
Practice Test ◽  
Quantitative Correlation ◽  
Normality Test

<p><em>Futsal is one of the most popular extracurricular by students at SDIT IQRA1 of Bengkulu City. This study aims to determine the contribution of eyes and feet coordination towards basic passing skills on futsal athletes at SDIT IQRA 1 of Bengkulu City. The method used in this study is quantitative correlation method. Population in this study is all students of sport futsal extracurricular while the sample is 20 students. The instruments in this study are test of Soccer Wall Volley Test from Barry L. Johnson and to  measure the passing skill by using passing practice test. Prerequisite data analysis used is normality test with Lilliefors, homogeneity test and contribution test. The data analysis used is Product Moment Correlation analysis with 5% significance level. Based on the results of the study, it is found that (1) there is a significant relationship between coordination of eyes and feet (X) to the accuracy of the passing indicated by r count = 0.90977 &gt; r <sub>(0.05) (20</sub>) = 0.444. (2) There is a strong positive contribution of 82.768% between eyes and feet coordination (X) towards passing skill (Y) on futsal athletes at SDIT IQRA 1 of Bengkulu City.</em></p>

Quantitative Study on the Relation between Water Disaster and Grain Production of Hubei Province

2012 ◽  
Vol 424-425 ◽  
pp. 403-409 ◽  
Author(s):  
Tao Li ◽  
Xue Lei Wang ◽  
Wei Wen ◽  
En Hua Li
Keyword(s):  
Correlation Analysis ◽  
Grain Yield ◽  
Quantitative Study ◽  
Grain Production ◽  
Grey Correlation ◽  
Quantitative Correlation ◽  
Irrigated Area ◽  
Grey Correlation Analysis ◽  
The Relationship ◽  
Water Disaster

The grain fluctuation situation of Hubei was analyzed by calculating the grain fluctuation coefficient from 1990s. And the quantitative correlation between grain production and the water disaster was studied by grey correlation analysis. The results were shown as follows. The main water disaster factors impacting grain production were effective irrigated area and planting structure, the relationship degree of which with grain yield is respectively 0.91 and 0.85 ranking the first two among all the selected factors. It was shown that water disaster influenced the grain yield heavily

scholarly journals Evaluating the efficacy of multiple myeloma cell lines as models for patient tumors via transcriptomic correlation analysis

2019 ◽  
Author(s):  
Vishesh Sarin ◽  
Katharine Yu ◽  
Ian D. Ferguson ◽  
Olivia Gugliemini ◽  
Matthew A. Nix ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Correlation Analysis ◽  
Cell Lines ◽  
Large Scale ◽  
Myeloma Cell ◽  
Multiple Myeloma Cell ◽  
Quantitative Correlation ◽  
Immunocompromised Mice ◽  
Rpmi 8226 ◽  
Biological Differences

AbstractMultiple myeloma (MM) cell lines are routinely used to model the disease. However, a long-standing question is how well these cell lines truly represent tumor cells in patients. Here, we employ a recently-described method of transcriptional correlation profiling to compare similarity of 66 MM cell lines to 779 newly-diagnosed MM patient tumors. We found that individual MM lines differ significantly with respect to patient tumor representation, with median R ranging from 0.35-0.54. ANBL-6 was the “best” line, markedly exceeding all others (p < 2.2e-16). Notably, some widely-used cell lines (RPMI-8226, U-266) scored poorly in our patient similarity ranking (48 and 52 of 66, respectively). Lines cultured with interleukin-6 showed significantly improved correlations with patient tumor (p = 9.5e-4). When common MM genomic features were matched between cell lines and patients, only t(4;14) and t(14;16) led to increased transcriptional correlation. To demonstrate utility of our top-ranked line for preclinical studies, we showed that intravenously-implanted ANBL-6 proliferates in hematopoietic organs in immunocompromised mice. Overall, our large-scale quantitative correlation analysis, utilizing emerging datasets, provides a resource informing the MM community of cell lines that may be most reliable for modeling patient disease while also elucidating biological differences between cell lines and tumors.

Monotonic correlation analysis of image quality measures for image fusion

2008 ◽  
Author(s):  
Lance M. Kaplan ◽  
Stephen D. Burks ◽  
Richard K. Moore ◽  
Quang Nguyen
Keyword(s):  
Image Quality ◽  
Correlation Analysis ◽  
Image Fusion ◽  
Quality Measures ◽  
Image Quality Measures

scholarly journals Evaluating the efficacy of multiple myeloma cell lines as models for patient tumors via transcriptomic correlation analysis

Leukemia ◽  
2020 ◽  
Vol 34 (10) ◽  
pp. 2754-2765 ◽  
Author(s):  
Vishesh Sarin ◽  
Katharine Yu ◽  
Ian D. Ferguson ◽  
Olivia Gugliemini ◽  
Matthew A. Nix ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Correlation Analysis ◽  
Cell Lines ◽  
Large Scale ◽  
Myeloma Cell ◽  
Multiple Myeloma Cell ◽  
Quantitative Correlation ◽  
Immunocompromised Mice ◽  
Rpmi 8226 ◽  
Biological Differences

Abstract Multiple myeloma (MM) cell lines are routinely used to model the disease. However, a long-standing question is how well these cell lines truly represent tumor cells in patients. Here, we employ a recently described method of transcriptional correlation profiling to compare similarity of 66 MM cell lines to 779 newly diagnosed MM patient tumors. We found that individual MM lines differ significantly with respect to patient tumor representation, with median R ranging from 0.35 to 0.54. ANBL-6 was the “best” line, markedly exceeding all others (p < 2.2e−16). Notably, some widely used cell lines (RPMI-8226, U-266) scored poorly in our patient similarity ranking (48 and 52 of 66, respectively). Lines cultured with interleukin-6 showed significantly improved correlations with patient tumor (p = 9.5e−4). When common MM genomic features were matched between cell lines and patients, only t(4;14) and t(14;16) led to increased transcriptional correlation. To demonstrate the utility of our top-ranked line for preclinical studies, we showed that intravenously implanted ANBL-6 proliferates in hematopoietic organs in immunocompromised mice. Overall, our large-scale quantitative correlation analysis, utilizing emerging datasets, provides a resource informing the MM community of cell lines that may be most reliable for modeling patient disease while also elucidating biological differences between cell lines and tumors.

scholarly journals Grape pre-evaluation by berry-leaf biochemistry quantitative correlation analysis

2015 ◽  
Vol 10 (50) ◽  
pp. 4543-4553 ◽  
Author(s):  
Ma Miandi ◽  
Yang Yong ◽  
Zhang Hanbo ◽  
Yuan Mingquan ◽  
Zhu Wei ◽  
...  
Keyword(s):  
Correlation Analysis ◽  
Quantitative Correlation ◽  
Leaf Biochemistry
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