The Degree of Congruence between Test Standards and Test Documentation with in Journal Publications

1996 ◽  
Vol 56 (2) ◽  
pp. 209-214 ◽  
Author(s):  
Audrey L. Qualls ◽  
Angela D. Moss
2007 ◽  
Vol 35 (2) ◽  
pp. 94-117 ◽  
Author(s):  
James A. Popio ◽  
John R. Luchini

Abstract This study compares data from the two Society of Automotive Engineers test methods for rolling resistance: J-2452 (Stepwise Coast-Down) and J-1269 (Equilibrium) steady state. The ability of the two methods to evaluate tires was examined by collecting data for 12 tires. The data were analyzed and the data showed that the two methods ranked the tires the same after the data were regressed and the rolling resistance magnitude was calculated at the Standard Reference Condition. In addition, analysis of the two methods using this matched set of testing provided an opportunity to evaluate each of these test standards against the other. It was observed that each test has merits absent from the other.


2010 ◽  
Author(s):  
Ken Yasuda ◽  
Marc Woodka ◽  
Michael Polcha ◽  
Daniel Pinkham

BMJ Open ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. e051821
Author(s):  
Lisa Bero ◽  
Rosa Lawrence ◽  
Louis Leslie ◽  
Kellia Chiu ◽  
Sally McDonald ◽  
...  

ObjectiveTo compare results reporting and the presence of spin in COVID-19 study preprints with their finalised journal publications.DesignCross-sectional study.SettingInternational medical literature.ParticipantsPreprints and final journal publications of 67 interventional and observational studies of COVID-19 treatment or prevention from the Cochrane COVID-19 Study Register published between 1 March 2020 and 30 October 2020.Main outcome measuresStudy characteristics and discrepancies in (1) results reporting (number of outcomes, outcome descriptor, measure, metric, assessment time point, data reported, reported statistical significance of result, type of statistical analysis, subgroup analyses (if any), whether outcome was identified as primary or secondary) and (2) spin (reporting practices that distort the interpretation of results so they are viewed more favourably).ResultsOf 67 included studies, 23 (34%) had no discrepancies in results reporting between preprints and journal publications. Fifteen (22%) studies had at least one outcome that was included in the journal publication, but not the preprint; eight (12%) had at least one outcome that was reported in the preprint only. For outcomes that were reported in both preprints and journals, common discrepancies were differences in numerical values and statistical significance, additional statistical tests and subgroup analyses and longer follow-up times for outcome assessment in journal publications.At least one instance of spin occurred in both preprints and journals in 23/67 (34%) studies, the preprint only in 5 (7%), and the journal publications only in 2 (3%). Spin was removed between the preprint and journal publication in 5/67 (7%) studies; but added in 1/67 (1%) study.ConclusionsThe COVID-19 preprints and their subsequent journal publications were largely similar in reporting of study characteristics, outcomes and spin. All COVID-19 studies published as preprints and journal publications should be critically evaluated for discrepancies and spin.


2021 ◽  
Vol 15 (2) ◽  
pp. 101153
Author(s):  
Fang Xu ◽  
Guiyan Ou ◽  
Tingcan Ma ◽  
Xianwen Wang
Keyword(s):  

2019 ◽  
Vol 52 (9-10) ◽  
pp. 1344-1353 ◽  
Author(s):  
Gang Chen ◽  
Weigong Zhang ◽  
Xu Li ◽  
Bing Yu

To solve the shortcomings of existing control methods for an electromagnetic direct drive vehicle robot driver, including large speed tracking error and large mileage deviation, a new adaptive speed control method for the electromagnetic direct drive vehicle robot driver based on fuzzy logic is proposed in this paper. The electromagnetic direct drive vehicle robot driver adapts an electromagnetic linear motor as its drive mechanism. The control system structure is designed. The coordinated controller for multiple manipulators is presented. Moreover, an adaptive speed controller for the electromagnetic direct drive vehicle robot driver is proposed to achieve the accurate tracking of desired speed. Experiments are conducted using a Ford FOCUS car. Performances of the proposed method, proportional–integral–derivative, and fuzzy neural network are compared and analyzed. Experimental results demonstrate that the proposed control method can accurately track the target speed, and it can inhabit the change of speed caused by interference under different test conditions, and it has small mileage deviation, which can meet the requirements of national vehicle test standards.


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