The generalized ridge estimator and improved adjustments for regression parameters

Metrika ◽  
1977 ◽  
Vol 24 (1) ◽  
pp. 113-124 ◽  
Author(s):  
H. Myoken ◽  
Y. Uchida
2015 ◽  
Vol 36 (1-3) ◽  
pp. 370-384 ◽  
Author(s):  
Aman Ullah ◽  
Alan T. K. Wan ◽  
Huansha Wang ◽  
Xinyu Zhang ◽  
Guohua Zou

Molecules ◽  
2021 ◽  
Vol 26 (12) ◽  
pp. 3682
Author(s):  
Katarína Vizárová ◽  
Izabela Vajová ◽  
Naďa Krivoňáková ◽  
Radko Tiňo ◽  
Zdenko Takáč ◽  
...  

The surface pH is a critical factor in the quality and longevity of materials and products. Traditional fast colorimetric pH detection-based tests such as water quality control or pregnancy tests, when results are determined by the naked eye, cannot provide quantitative values. Using standard pH papers, paper-printed comparison charts, or colorimetric microfluidic paper-based analytical devices is not suitable for such technological applications and quality management systems (QMSs) where the particular tested material should contain a suitable indicator in situ, in its structure, either before or after the process, the technology or the apparatus that are being tested. This paper describes a method based on the combination of impregnation of a tested material with a pH indicator in situ, its exposure to a process of technology whose impact on pH value is to be tested, colorimetric pH measurement, and approximation of pH value using derived pH characteristic parameters (pH-CPs) based on CIE orthogonal and cylindrical color variables. The hypotheses were experimentally verified using the methyl red pH indicator, impregnating the acid lignin-containing paper, and preparing a calibration sample set with pH in the range 4 to 12 using controlled alkalization. Based on the performed measurements and statistical evaluation, it can be concluded that the best pH-CPs with the highest regression parameters for pH are √∆E, ln (a),√∆H (ab), a/L, h/b and ln (b/a). The experimental results show that the presented method allows a good estimation of pH detection of the material surfaces.


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