Discussion on Burden Calculation of Ferromanganese Alloy Production

2011 ◽  
Vol 194-196 ◽  
pp. 248-254
Author(s):  
Shao Jun Chu ◽  
Pei Xiao Liu ◽  
Pei Xian Chen
Keyword(s):  
Error Rate ◽  
Total Error ◽  
Reference Value ◽  
Mass Conservation ◽  
Recovery Method ◽  
Total Error Rate ◽  
Calculation Results ◽  
Improve Production Technology ◽  
Technology Product ◽  
Better Than

The burden calculation of ferromanganese alloy was calculated based on the slag composition and designed product. The calculation results showed the total error rate of this method was 1.53% and the error rate of ore, coke and silicon was 4.66%, 1.71%, and 5.66% respectively, which was much better than using the traditional elements recovery method with the total error rate was 8.00% and the silicon error rate reached to 18.55%. This new method is more accurate than the traditional method and much closer to the actual production data. And it can apply to different ferroalloy factories because it is based on phase diagram and the mass conservation law. At the same time, the calculation result can reflect the gap between enterprise production craft level and ideal production level. This method has certain reference value to improve production technology, product quality and economic profit of enterprise.

Biometric scores fusion based on total error rate minimization

2008 ◽  
Vol 41 (3) ◽  
pp. 1066-1082 ◽  
Author(s):  
Kar-Ann Toh ◽  
Jaihie Kim ◽  
Sangyoun Lee
Keyword(s):  
Error Rate ◽  
Total Error ◽  
Total Error Rate

Recursive total error rate minimization

2016 ◽  
Author(s):  
Se-In Jang ◽  
Geok-Choo Tan ◽  
Kar-Ann Toh
Keyword(s):  
Error Rate ◽  
Total Error ◽  
Total Error Rate

Tourniquet use in the prehospital setting: Are they being used appropriately?

2018 ◽  
Vol 13 (1) ◽  
pp. 37-43 ◽  
Author(s):  
Kevin M. Duignan, MS, EMT-B ◽  
Laura C. Lamb, MD ◽  
Monica M. DiFiori, BS ◽  
John Quinlavin, BS ◽  
James M. Feeney, MD, FACS
Keyword(s):  
Emergency Medicine ◽  
Error Rate ◽  
Trauma Center ◽  
Total Error ◽  
First Responders ◽  
Prehospital Setting ◽  
Extremity Injury ◽  
Inclusion Criteria ◽  
Total Error Rate ◽  
Level Ii

Objective: The objective of this study was to evaluate tourniquet use in the Hartford prehospital setting during a 34-month period after the Hartford Consensus was published, which encouraged increasing tourniquet use in light of military research.Design: This was a retrospective review of patients with bleeding from a serious extremity injury to determine appropriateness of tourniquet use or omission.Setting: Level II trauma center between April 2014 and January 2017.Participants: Eighty-four patients met inclusion criteria and were stratified based on tourniquet use during prehospital care.Main Outcome Measures: Five of the 84 patients received a tourniquet. All five of those tourniquets (100 percent of the group, 6.0 percent of the population) were not indicated and deemed inappropriate. Three of the 84 patients did not receive a tourniquet when one was indicated (3.8 percent of the group, 3.6 percent of the population) and these omissions were also deemed inappropriate. Total error rate was 9.5 percent (8/84).Results: There was a significant association between Mangled Extremity Severity Score (MESS) and likelihood of requiring a tourniquet (p = 0.0013) but not between MESS and likelihood of receiving a tourniquet (p = 0.1055). There was also a significant association between wrongly placed tourniquets and the type of providers who placed them [first responders, p = 0.0029; Emergency Medicine Technicians (EMTs), p = 0.0001].Conclusions: Tourniquets are being used inappropriately in the Hartford prehospital setting. Misuse is associated with both EMTs and first responders, highlighting the need for better training and more consistent protocols.

scholarly journals Quotation errors in general science journals

2020 ◽  
Vol 476 (2242) ◽  
pp. 20200538 ◽  
Author(s):  
Neal Smith ◽  
Aaron Cumberledge
Keyword(s):  
Error Rate ◽  
Scientific Discovery ◽  
Total Error ◽  
Error Rates ◽  
High Impact ◽  
Scientific Writing ◽  
General Science ◽  
Total Error Rate ◽  
Academic Fields ◽  
The Future

Due to the incremental nature of scientific discovery, scientific writing requires extensive referencing to the writings of others. The accuracy of this referencing is vital, yet errors do occur. These errors are called ‘quotation errors’. This paper presents the first assessment of quotation errors in high-impact general science journals. A total of 250 random citations were examined. The propositions being cited were compared with the referenced materials to verify whether the propositions could be substantiated by those materials. The study found a total error rate of 25%. This result tracks well with error rates found in similar studies in other academic fields. Additionally, several suggestions are offered that may help to decrease these errors and make similar studies more feasible in the future.

scholarly journals Comparison of Medication History Accuracy Between Nurses and Pharmacy Personnel

2017 ◽  
Vol 32 (1) ◽  
pp. 62-67 ◽  
Author(s):  
Connor Bowman ◽  
Jennifer McKenna ◽  
Phil Schneider ◽  
Brian Barnes
Keyword(s):  
Error Rate ◽  
Community Hospital ◽  
Total Error ◽  
Medication History ◽  
Total Error Rate ◽  
Number Of Patients ◽  
Pharmacy Technicians ◽  
Secondary Outcomes ◽  
The Difference ◽  
Clinically Significant

Purpose: To evaluate the differences in medication history errors made by pharmacy technicians, students, and pharmacists compared to nurses at a community hospital. Methods: One hundred medication histories completed by either pharmacy or nursing staff were repeated and evaluated for errors by a fourth-year pharmacy student. The histories were analyzed for differences in the rate of errors per medication. Errors were categorized by their clinical significance, which was determined by a panel of pharmacists, pharmacy students, and nurses. Errors were further categorized by their origin as either prescription (Rx) or over the counter (OTC). The primary outcome was the difference in the rate of clinically significant errors per medication. Secondary outcomes included the differences in the rate of clinically insignificant errors, Rx errors, and OTC errors. Differences in the types of errors for Rx and OTC medications were also analyzed. Additionally, the number of patients with no errors was compared between both groups. Results: The pharmacy group had a lower clinically significant error rate per medication (0.03 vs 0.09; relative risk [RR] = 0.66; 95% confidence interval [CI]: 0.020-0.093; P = .003). For secondary outcomes, the pharmacy group had a lower total error rate (0.21 vs 0.36, RR = 0.58; 95% CI: 0.041-0.255; P = .007), Rx error rate (0.09 vs 0.27, RR = 0.44; 95% CI: 0.071-0.292; P = .002), and OTC error rate (0.24 vs 0.46; RR = 0.52; 95% CI: 0.057-0.382; P = .009) per medication. The pharmacy group completed 20% more medication histories without Rx errors ( P = .045) and 25% more histories without OTC errors ( P = .041). Conclusion: This study demonstrated that expanded use of pharmacy technicians and students improves the accuracy of medication histories in a community hospital.

Ensemble modeling of E. coli in the Charles River, Boston, Massachusetts, USA

2007 ◽  
Vol 56 (6) ◽  
pp. 39-46 ◽  
Author(s):  
F.L. Hellweger
Keyword(s):  
Time Series ◽  
Error Rate ◽  
Mechanistic Model ◽  
Total Error ◽  
Geometric Mean ◽  
Three Dimensional ◽  
Ensemble Modeling ◽  
Quality Model ◽  
E Coli ◽  
Total Error Rate

A case study of ensemble modeling of Escherichia coli (E. coli) densities in surface waters in the context of public health risk prediction is presented. The output of two different models, mechanistic and empirical, are combined and compared to data. The mechanistic model is a high-resolution, time-variable, three-dimensional coupled hydrodynamic and water quality model. It generally reproduces the mechanisms of E. coli fate and transport in the river, including the presence and absence of a plume in the study area under similar input, but different hydrodynamic conditions caused by the operation of a downstream dam and wind. At the time series station, the model has a root mean square error (RMSE) of 370 CFU/100mL, a total error rate (with respect to the EPA-recommended single sample criteria value of 235 CFU/100mL) (TER) of 15% and negative error rate (NER) of 30%. The empirical model is based on multiple linear regression using the forcing functions of the mechanistic model as independent variables. It has better overall performance (at the time series station), due to a strong correlation of E. coli density with upstream inflow for this time period (RMSE =200 CFU/100mL, TER =13%, NER =1.6%). However, the model is mechanistically incorrect in that it predicts decreasing densities with increasing Combined Sewer Overflow (CSO) input. The two models are fundamentally different and their errors are uncorrelated (R2 =0.02), which motivates their combination in an ensemble. Two combination approaches, a geometric mean ensemble (GME) and an “either exceeds” ensemble (EEE), are explored. The GME model outperforms the mechanistic and empirical models in terms of RMSE (190 CFU/100mL) and TER (11%), but has a higher NER (23%). The EEE has relatively high TER (16%), but low NER (0.8%) and may be the best method for a conservative prediction. The study demonstrates the potential utility of ensemble modeling for pathogen indicators, but significant further research is needed to establish the approach for the Charles River, as outlined in the paper.

Object tracking based on an online learning network with total error rate minimization

2015 ◽  
Vol 48 (1) ◽  
pp. 126-139 ◽  
Author(s):  
Se-In Jang ◽  
Kwontaeg Choi ◽  
Kar-Ann Toh ◽  
Andrew Beng Jin Teoh ◽  
Jaihie Kim
Keyword(s):  
Online Learning ◽  
Object Tracking ◽  
Error Rate ◽  
Total Error ◽  
Learning Network ◽  
Total Error Rate
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