An alternative to the geometric addition method for calculating the rise time of fast oscilloscopes and pulse generators

2017 ◽  
Vol 84 (2) ◽  
Author(s):  
Kai Baaske ◽  
Paul D. Hale ◽  
Thomas Kleine-Ostmann ◽  
Mark Bieler ◽  
Thorsten Schrader
Keyword(s):  
Systematic Error ◽  
Correction Factor ◽  
Rise Time ◽  
New Method ◽  
Time Base ◽  
Large Set ◽  
Addition Method ◽  
Pulse Generators ◽  
Time Base Distortion ◽  
Uncertainty Contribution

AbstractIn this paper, we propose a new method for calculating the rise time of pulse generators and oscilloscopes using a correction factor. This new method is advantageous over the well known geometric rule, also known as the root-sum-of-squares (RSS) rule, because its corresponding uncertainty contribution can be estimated, whereas the uncertainty assigned to the RSS method due to systematic error is typically unknown in any given measurement scenario. In our method, the correction factor is estimated from a large set of representative classical response functions. Furthermore, the systematic error caused by the time base distortion of sampling oscilloscopes is corrected in order to reduce the uncertainty of the calibration process.

Collaborative Study of the Spectrophotometric Determination of Phosphatase Activity in Milk Utilizing a New Alkaline Phosphatase Assay System

1972 ◽  
Vol 55 (3) ◽  
pp. 498-503
Author(s):  
D H Kleyn ◽  
C L Huang
Keyword(s):  
Systematic Error ◽  
Collaborative Study ◽  
Correlation Coefficients ◽  
New Method ◽  
Statistical Comparison ◽  
Alkaline Phosphatase Assay ◽  
Phosphatase Assay ◽  
Method Analysis ◽  
Quantitative Procedure

Abstract A quantitative procedure (modified new method) has been studied that employs phenolphthalein monophosphate as the substrate and dialysis of released phenolphthalein followed by subseqvient measurement of the dialysate in a spectrophotometer at 550 nm. Nine collaborators evaluated 6 unknown samples of milk containing various levels of rawmilk, in triplicate, by the modified new method and the Scharer modified spectrophotometric method. Analysis of variance revealed that the random error of the modified new method was almost twice that of the Scharer technique, while the systematic error of the modified new method was only about ¼ that of the latter method. Two-sample charts indicated that the systematic error of the modified new method was less than that of the Scharer method; this was verified by a statistical comparison which showed that the total analytical error was much lower for the modified new method. A linear relationship was found between the 2 methods by 5 of the collaborators; the correlation coefficients ranged from 0.993 to 0.999. Based on these results, the method has been adopted as official first action for the analysis of milk.

scholarly journals Seasonal variability and descent of mid-latitude sporadic E layers at Arecibo

2009 ◽  
Vol 27 (3) ◽  
pp. 923-931 ◽  
Author(s):  
N. Christakis ◽  
C. Haldoupis ◽  
Q. Zhou ◽  
C. Meek
Keyword(s):  
Lower Thermosphere ◽  
Time Base ◽  
Large Set ◽  
Seasonal Behavior ◽  
Incoherent Scatter ◽  
Electron Density Gradient ◽  
Sporadic E Layers ◽  
Sporadic E Layer ◽  
Sporadic E ◽  
Wind Shears

Abstract. Sporadic E layers (Es) follow regular daily patterns in variability and altitude descent, which are determined primarily by the vertical tidal wind shears in the lower thermosphere. In the present study a large set of sporadic E layer incoherent scatter radar (ISR) measurements are analyzed. These were made at Arecibo (Geog. Lat. ~18° N; Magnetic Dip ~50°) over many years with ISR runs lasting from several hours to several days, covering evenly all seasons. A new methodology is applied, in which both weak and strong layers are clearly traced by using the vertical electron density gradient as a function of altitude and time. Taking a time base equal to the 24-h local day, statistics were obtained on the seasonal behavior of the diurnal and semidiurnal tidal variability and altitude descent patterns of sporadic E at Arecibo. The diurnal tide, most likely the S(1,1) tide with a vertical wavelength around 25 km, controls fully the formation and descent of the metallic Es layers at low altitudes below 110 km. At higher altitudes, there are two prevailing layers formed presumably by vertical wind shears associated mainly with semidiurnal tides. These include: 1) a daytime layer starting at ~130 km around midday and descending down to 105 km by local midnight, and 2) a less frequent and weaker nighttime layer which starts prior to midnight at ~130 km, descending downwards at somewhat faster rate to reach 110 km by sunrise. The diurnal and semidiurnal-like pattern prevails, with some differences, in all seasons. The differences in occurrence, strength and descending speeds between the daytime and nighttime upper layers are not well understood from the present data alone and require further study.

Measuring Dynamic Nonlinearity of Digitizers Affected by Time Base Distortion

2011 ◽  
Vol 60 (2) ◽  
pp. 560-566 ◽  
Author(s):  
Filippo Attivissimo ◽  
Attilio Di Nisio ◽  
Nicola Giaquinto
Keyword(s):  
Time Base ◽  
Time Base Distortion ◽  
Dynamic Nonlinearity

scholarly journals Predicting diabetes-related hospitalizations based on electronic health records

2018 ◽  
Vol 28 (12) ◽  
pp. 3667-3682 ◽  
Author(s):  
Theodora S Brisimi ◽  
Tingting Xu ◽  
Taiyao Wang ◽  
Wuyang Dai ◽  
Ioannis Ch Paschalidis
Keyword(s):  
New England ◽  
Medical Center ◽  
Computational Cost ◽  
Safety Net ◽  
New Method ◽  
Supervised Machine Learning ◽  
Support Vector ◽  
Large Set ◽  
Machine Learning Classification ◽  
Safety Net Hospital

Objective: To derive a predictive model to identify patients likely to be hospitalized during the following year due to complications attributed to Type II diabetes. Methods: A variety of supervised machine learning classification methods were tested and a new method that discovers hidden patient clusters in the positive class (hospitalized) was developed while, at the same time, sparse linear support vector machine classifiers were derived to separate positive samples from the negative ones (non-hospitalized). The convergence of the new method was established and theoretical guarantees were proved on how the classifiers it produces generalize to a test set not seen during training. Results: The methods were tested on a large set of patients from the Boston Medical Center – the largest safety net hospital in New England. It is found that our new joint clustering/classification method achieves an accuracy of 89% (measured in terms of area under the ROC Curve) and yields informative clusters which can help interpret the classification results, thus increasing the trust of physicians to the algorithmic output and providing some guidance towards preventive measures. While it is possible to increase accuracy to 92% with other methods, this comes with increased computational cost and lack of interpretability. The analysis shows that even a modest probability of preventive actions being effective (more than 19%) suffices to generate significant hospital care savings. Conclusions: Predictive models are proposed that can help avert hospitalizations, improve health outcomes and drastically reduce hospital expenditures. The scope for savings is significant as it has been estimated that in the USA alone, about $5.8 billion are spent each year on diabetes-related hospitalizations that could be prevented.

A Burst Capacity Model for Corroded Pipelines Subjected to Combined Internal Pressure and Longitudinal Compression

2021 ◽  
Author(s):  
Shulong Zhang ◽  
Wenxing Zhou
Keyword(s):  
Internal Pressure ◽  
Correction Factor ◽  
Oil And Gas ◽  
Large Set ◽  
Finite Element Analyses ◽  
Longitudinal Compression ◽  
Combined Loads ◽  
Capacity Model ◽  
Proposed Model ◽  
Semi Empirical

Abstract The present study proposes a new semi-empirical burst capacity model for corroded oil and gas pipelines under combined internal pressure and longitudinal compression. The proposed model evaluates the burst capacity of a corroded pipeline under combined loads as the burst capacity of the pipeline under internal pressure only, which is developed in a recently completed study, multiplied by a correction factor to account for the effect of the longitudinal compression. Extensive parametric elastoplastic finite element analyses (FEA) are carried out, the results of which are used as the basis to develop the correction factor as a function of the corrosion defect sizes and magnitude of the longitudinal compressive stress. The proposed model is validated by a large set of parametric FEA and full-scale burst tests reported in the literature, and is shown to provide marked improvements over two existing models, the DNV and RPA-PLLC models, for corroded pipelines under combined loads.

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