scholarly journals Quality Control of Pre-1948 Cooperative Observer Network Data

2005 ◽  
Vol 22 (11) ◽  
pp. 1691-1705 ◽  
Author(s):  
Kenneth E. Kunkel ◽  
David R. Easterling ◽  
Kenneth Hubbard ◽  
Kelly Redmond ◽  
Karen Andsager ◽  
...  
Keyword(s):  
Quality Control ◽  
Limited Resources ◽  
Second Step ◽  
Precipitation Data ◽  
Screening Criteria ◽  
Temperature And Precipitation ◽  
Data Value ◽  
Control Procedures ◽  
Special Quality

Abstract A recent comprehensive effort to digitize U.S. daily temperature and precipitation data observed prior to 1948 has resulted in a major enhancement in the computer database of the records of the National Weather Service’s cooperative observer network. Previous digitization efforts had been selective, concentrating on state or regional areas. Special quality control procedures were applied to these data to enhance their value for climatological analysis. The procedures involved a two-step process. In the first step, each individual temperature and precipitation data value was evaluated against a set of objective screening criteria to flag outliers. These criteria included extreme limits and spatial comparisons with nearby stations. The following data were automatically flagged: 1) all precipitation values exceeding 254 mm (10 in.) and 2) all temperature values whose anomaly from the monthly mean for that station exceeded five standard deviations. Additional values were flagged based on differences with nearby stations; in this case, metrics were used to rank outliers so that the limited resources were concentrated on those values most likely to be invalid. In the second step, each outlier was manually assessed by climatologists and assigned one of the four following flags: valid, plausible, questionable, or invalid. In excess of 22 400 values were manually assessed, of which about 48% were judged to be invalid. Although additional manual assessment of outliers might further improve the quality of the database, the procedures applied in this study appear to have been successful in identifying the most flagrant errors.

What is the quality of quality control procedures?

1981 ◽  
Vol 41 (1) ◽  
pp. 1-14 ◽  
Author(s):  
Carl-Henric de Verdier ◽  
Torgny Groth ◽  
James O. Westgard
Keyword(s):  
Quality Control ◽  
Control Procedures

scholarly journals Book review – Standards, quality control, and measurement sciences in 3D printing and additive manufacturing

2017 ◽  
Vol 3 (2) ◽  
Author(s):  
Tuan Anh Tran
Keyword(s):  
Quality Control ◽  
Additive Manufacturing ◽  
3D Printing ◽  
Fast Pace ◽  
Control Procedures ◽  
3D Printed

There is a gap between 3D Printing’s fast pace of development and the acceptance of 3D Printing technologies by other industries and applications. This hesitation comes mostly from unanswered questions about the consistency, reproducibility, and quality of 3D printed products. Although the list of excellent examples demonstrating its potential keeps expanding, a wide and thorough adoption of the technology requires crucial, yet currently missing elements including consensus standards, quality control procedures, and measuring methodologies. Progress in developing these elements, however, has been rather limited.

The Role of Microscopy in Quality Control, Litigation and Forensic Studies of Hides, Skins and Leather

2001 ◽  
Vol 7 (S2) ◽  
pp. 470-471
Author(s):  
Robin H Cross
Keyword(s):  
Quality Control ◽  
Mechanical Damage ◽  
Source Material ◽  
Growth Stages ◽  
Leather Industry ◽  
Chemical Damage ◽  
Control Procedures ◽  
Finishing Processes

The economic importance of animal hides and skins as the source material for the natural leather industry is significant world-wide, and in some countries of the developing world the livelihood of a large proportion of the population depends upon it. Consequently, it is understandable that anything affecting the quality of the source material and the finished product has major economic, industrial and sociological significance. It is also inevitable that a product that is so widely-used in many ways by most of the population will become an important source of evidence in forensic investigations.Quality control procedures in the leather industry involve monitoring the progress of the hides and skins from the growth stages of the animal, through the slaughter, storage, transportation, curing, tanning and finishing processes, to the sale and distribution of the finished product. There are many factors during these stages that can affect quality of finished leather, amongst the most important of which are mechanical and parasite damage during growth, biodeterioration and mechanical damage between slaughter and curing, mechanical, heat and chemical damage during curing, tanning and finishing.

scholarly journals ARTEMIS, THE 14C AMS FACILITY OF THE LMC14 NATIONAL LABORATORY: A STATUS REPORT ON QUALITY CONTROL AND MICROSAMPLE PROCEDURES

Radiocarbon ◽  
2020 ◽  
pp. 1-16
Author(s):  
Christophe Moreau ◽  
Cyrielle Messager ◽  
Bernard Berthier ◽  
Stéphane Hain ◽  
Bruno Thellier ◽  
...  
Keyword(s):  
Quality Control ◽  
Statistical Tests ◽  
National Laboratory ◽  
Status Report ◽  
Mural Paintings ◽  
Control Procedures ◽  
Accurate Procedure ◽  
Primary And Secondary Standards ◽  
Routine Procedures

ABSTRACT Quality control procedures have been developed at the Laboratoire de Mesure du Carbone 14 (LMC14) national laboratory throughout the years of operation. Routine procedures are applied to sample preparation depending on their composition and their size. The tuning of the ARTEMIS AMS facility, hosted by the LMC14 laboratory, uses an accurate procedure. A batch of unknown samples is measured with accompanying samples (primary and secondary standards and blanks), which give a powerful set of data to control the quality of each measurement. A homemade database has been created to store the sample information and study the evolution of the accompanying samples. The LMC14 laboratory participated in the Sixth International Radiocarbon Intercomparison, SIRI. The results are presented here, with statistical tests to assess the quality of the preparations and measurements done at the LMC14 national laboratory. To obtain a reliable radiocarbon (14C) age by AMS, 1 mg of sample is required in routine analysis. Recently, the LMC14 developed a new procedure dedicated to microsamples, allowing the size of samples to be reduced and contributing to opening 14C dating to materials that were previously unreachable. This new procedure has been successfully tested on valuable Cultural Heritage samples: lead white mural paintings.

scholarly journals Quality Control of Raw Materials on Red Snapper (Lutjanus sp.) Freezing Process in PT. Tridaya Jaya Manunggal Pasuruan East Java

2021 ◽  
Vol 10 (2) ◽  
pp. 85
Author(s):  
Winona Valeria Siregar ◽  
M. Nur Ghoyatul Amin
Keyword(s):  
Quality Control ◽  
Production Process ◽  
Raw Materials ◽  
Secondary Data ◽  
Red Snapper ◽  
Second Grade ◽  
Freezing Process ◽  
Market Values ◽  
Control Procedures

Red snappers are fishery commodities which have high market values. Raw materials of red snappers are important elements which determine the quality of the final products. Therefore, an enhancement of raw materials quality should be conducted through quality supervision and examination when the raw materials are retrieved, stored, and about to enter production process. The aim of this fieldwork practice is to find out the raw materials quality control on red snapper freezing process in PT. Tridaya Jaya Manunggal Pasuruan, East Java. The data taken consists of primary and secondary data which are processed descriptively. Data collection techniques through observation, interviews, active participation and literature review. PT. Tridaya Jaya Manunggal has implemented quality control on production process, starting from raw materials retrieval until these raw materials become final products. The quality control of raw red snappers were done in accordance with the quality control procedures which are plan, do, check, and action. The results of implementing quality control which were executed with organoleptic examination, temperature, Total Volatile Base (TVB), microbiology, and heavy metals on raw red snappers. Raw materials which didn’t meet the required standard were rejected, and then they were processed to be second grade products.

scholarly journals Qoala-T: A supervised-learning tool for quality control of automatic segmented MRI data

2018 ◽  
Author(s):  
Eduard T. Klapwijk ◽  
Ferdi van de Kamp ◽  
Mara van der Meulen ◽  
Sabine Peters ◽  
Lara M. Wierenga
Keyword(s):  
Quality Control ◽  
Supervised Learning ◽  
Area Under The Curve ◽  
High Sensitivity ◽  
Poor Quality ◽  
Developmental Studies ◽  
Quality Ratings ◽  
Control Procedures ◽  
Processing Errors

AbstractPerforming quality control to detect image artifacts and data-processing errors is crucial in structural magnetic resonance imaging, especially in developmental studies. Currently, many studies rely on visual inspection by trained raters for quality control. The subjectivity of these manual procedures lessens comparability between studies, and with growing study sizes quality control is increasingly time consuming. In addition, both inter-rater as well as intra-rater variability of manual quality control is high and may lead to inclusion of poor quality scans and exclusion of scans of usable quality. In the current study we present the Qoala-T tool, which is an easy and free to use supervised-learning model to reduce rater bias and misclassification in manual quality control procedures. First, we manually rated quality of N = 784 FreeSurfer-processed T1-weighted scans. Different supervised-learning models were then compared to predict manual quality ratings. Results show that the Qoala-T tool using random forests is able to predict scan quality with both high sensitivity and specificity (mean area under the curve (AUC) = 0.98). In addition, the Qoala-T tool was also able to adequately predict the quality of a novel unseen dataset (N = 112; mean AUC = 0.95). These outcomes indicate that using Qoala-T in other datasets could greatly reduce the time needed for quality control. More importantly, this procedure could further help to reduce variability related to manual quality control, thereby benefiting the comparability of data quality between studies.

Current practices in manufacturing locally-made ceramic pot filters for water treatment in developing countries

2013 ◽  
Vol 3 (2) ◽  
pp. 252-261 ◽  
Author(s):  
Justine Rayner ◽  
Brian Skinner ◽  
Daniele Lantagne
Keyword(s):  
Quality Control ◽  
Water Treatment ◽  
Best Practice ◽  
Diarrheal Disease ◽  
Microbiological Quality ◽  
Household Water Treatment ◽  
Production Methods ◽  
Household Water ◽  
Control Procedures

Locally produced ceramic pot filters have been shown to improve the microbiological quality of household drinking water and reduce the burden of diarrheal disease in users. They are considered one of the most promising household water treatment methods. However, overarching manufacturing and quality control guidelines do not exist for the 35 decentralized filter factories in 18 countries that currently produce filters. In this study, we conducted manufacturing process surveys with 25 filter factories worldwide to document production methods and identify areas where manufacturing and quality control guidelines are needed. Our results show that manufacturing processes vary widely both between and within factories, including the consistency of materials, manufacturing methods, and quality control practices. These variations pose concerns about the consistency and quality of locally produced filters in the absence of standardized quality control procedures. We propose areas where manufacturing guidelines are needed to assist factories in producing consistently high quality filters, and identify topics where further research is needed to refine manufacturing recommendations. These results guided the development of a best practice manual that described consensus-based recommendations to advance consistent, quality-controlled filter production world-wide.

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