scholarly journals Simpler hydrostatics component of UNBabc mapping function using nonlinear curve fitting method

2016 ◽  
Author(s):  
Siti Rahimah Batcha ◽  
Hamzah Sakidin ◽  
Asmala Ahmad
Keyword(s):  
Curve Fitting ◽  
Mapping Function ◽  
Fitting Method ◽  
Nonlinear Curve Fitting ◽  
Curve Fitting Method ◽  
Nonlinear Curve

Kinetic study of the Jaffé reaction for quantifying creatinine in serum: 1. Alkalinity controlled with NaOH.

1987 ◽  
Vol 33 (2) ◽  
pp. 278-285 ◽  
Author(s):  
H L Pardue ◽  
B L Bacon ◽  
M G Nevius ◽  
J W Skoug
Keyword(s):  
Curve Fitting ◽  
Interactive Effects ◽  
Kinetic Behavior ◽  
Factorial Experimental Design ◽  
Fitting Method ◽  
Nonlinear Curve Fitting ◽  
Relative Standard ◽  
Standard Additions ◽  
Curve Fitting Method ◽  
Nonlinear Curve

Abstract We studied the kinetic behavior of the reaction of alkaline picrate and creatinine and evaluated a nonlinear curve-fitting method for quantifying creatinine in serum. Using a 3 X 3 factorial experimental design, we evaluated interactive effects among temperature and concentrations of creatinine, picrate, and NaOH. We found no evidence of interference by glucose or unconjugated bilirubin; the effects of the acetoacetate reaction, which is fast, are easily compensated by the curve-fitting method. The reaction with human serum albumin is very complex, but its effects are compensated by the curve-fitting method and by preparing standards containing 50 g of albumin per liter. Calibration plots are linear under a wide variety of conditions for both aqueous standards and standard additions of creatinine to pooled serum. Reproducibility studies with standards containing creatinine at 2, 10, and 20 mg/L yielded relative standard deviations (RSD) of 8.2, 2.5, and 1.3%, corresponding to absolute variations of 0.16, 0.25, and 0.26 mg/L. The average SD for 17 sera containing creatinine at 15-50 mg/L was 0.7 mg/L. The averages of ratios (as percent) of determined vs expected concentrations in 17 sera with added creatinine (7.27 mg/L) were 97.8% for aqueous standards, 99.9% for standards with added albumin.

Using A Segmented Voltage Sweep Mode and A Gaussian Curve Fitting Method to Improve Heavy Metal Measurement System Performance

2012 ◽  
Vol 19 (2) ◽  
pp. 381-394
Author(s):  
José Pereira ◽  
Octavian Postolache ◽  
Pedro Girão
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Measurement System ◽  
Curve Fitting ◽  
System Performance ◽  
Redox Potentials ◽  
Voltage Sweep ◽  
Gaussian Curve ◽  
Fitting Method ◽  
Curve Fitting Method

Using A Segmented Voltage Sweep Mode and A Gaussian Curve Fitting Method to Improve Heavy Metal Measurement System PerformanceThis paper presents a voltammetric segmented voltage sweep mode that can be used to identify and measure heavy metals' concentrations. The proposed sweep mode covers a set of voltage ranges that are centered around the redox potentials of the metals that are under analysis. The heavy metal measurement system can take advantage of the historical database of measurements to identify the metals with higher concentrations in a given geographical area, and perform a segmented sweep around predefined voltage ranges or, alternatively, the system can perform a fast linear voltage sweep to identify the voltammetric current peaks and then perform a segmented voltage sweep around the set of voltages that are associated with the voltammetric current peaks. The paper also includes the presentation of two auto-calibration modes that can be used to improve system's reliability and proposes the usage of a Gaussian curve fitting of voltammetric data to identify heavy metals and to evaluate their concentrations. Several simulation and experimental results, that validate the theoretical expectations, are also presented in the paper.

An additional branch free algebraic B-spline curve fitting method

2010 ◽  
Vol 26 (6-8) ◽  
pp. 801-811 ◽  
Author(s):  
Mingxiao Hu ◽  
Jieqing Feng ◽  
Jianmin Zheng
Keyword(s):  
Curve Fitting ◽  
B Spline ◽  
Spline Curve ◽  
Fitting Method ◽  
Additional Branch ◽  
Curve Fitting Method

Evaluation of a predictive curve-fitting method for processing data from flow systems

1993 ◽  
Vol 272 (1) ◽  
pp. 125-134 ◽  
Author(s):  
James M. Jordan ◽  
Michael D. Love ◽  
Harry L. Pardue
Keyword(s):  
Curve Fitting ◽  
Processing Data ◽  
Fitting Method ◽  
Flow Systems ◽  
Curve Fitting Method

A Curve Fitting Method for Detecting Valve Stiction in Oscillating Control Loops

2007 ◽  
Vol 46 (13) ◽  
pp. 4549-4560 ◽  
Author(s):  
Q. Peter He ◽  
Jin Wang ◽  
Martin Pottmann ◽  
S. Joe Qin
Keyword(s):  
Curve Fitting ◽  
Control Loops ◽  
Fitting Method ◽  
Valve Stiction ◽  
Curve Fitting Method
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