QC Data Research Articles

Reliability analysis of the bearing capacity of a shallow foundation resting on cohesive soil

In recent years, there have been considerable advances in the characterization of soil variability and its application in geotechnical designs. It is recognized that in using reliability-based design it is necessary to consider all sources of uncertainty in the analysis and incorporate them in the geotechnical design. It is also necessary to examine the reliability-based approach in relation to deterministic approaches. In this study, cone tip resistance (qc) data obtained from a static cone penetration test on a stiff clay deposit are analyzed by using random field theory; and statistical parameters, such as the mean, variance, and autocorrelation function, are estimated in evaluating the reliability of the allowable bearing capacity of a strip footing founded on the above deposit.Key words: reliability-based design, soil variability, random field, variance, autocorrelation function, bearing capacity.

The uncertainty of a result from a linear calibration

The standard error of a result obtained from a straight line calibration is given by a well known ISO-endorsed expression. Its derivation and use are explained and the approach is extended for any function that is linear in the coefficients, with an example of a weighted quadratic calibration in ICPAES. When calculating the standard error of an estimate, if QC data is available it is recommended to use the repeatability of the instrumental response, rather than the standard error of the regression, in the equation.

MO-B-I-617-01: MR Accreditation Program Quality Control - Beyond Just the Scans and Measurements

In recent years, the American College of Radiology (ACR) MR Accreditation Program (MRAP) has been adopted by more than 3000 facilities. Those sites agree to follow a quality control program set up and monitored by the medical physicist or MR scientist. They also agree to undergo initial and annual equipment evaluations by the medical physicist / MR scientist. There are several published documents, including the ACR Phantom Test Guidance and the 2001 ACR MR QC Manual, which describe required phantom tests and performance criteria. While helpful in assisting sites with the submission of phantom images for accreditation, these documents allow great discretion to the medical physicist in setting up the QC program without providing similar guidance in troubleshooting problems for a wide variety of scanners. A consulting medical physicist may see a wide variety of scanners, each for a short period of time, and needs to be able to provide the site with useful recommendations beyond the pass/fail status of the phantom tests. The physicist must gather this information from existing QC data and tests performed with the ACR and other readily-available phantoms. This lecture will describe additional information which can be gathered from those data to produce recommendations for improving MR image quality. Educational Objectives: 1. Understand basic MR QC tests using the ACR and on-site phantoms and how the results of those tests can be combined and analyzed to troubleshoot problems. 2. Understand how QC test availability and results may vary depending on scanner manufacturer. 3. Understand how technologist QC data may be analyzed to troubleshoot QC problems.

Evaluation of Liquefaction Potential Using Neural Networks Based on Adaptive Resonance Theory

The incomprehensible loss of lives and extensive damages to transportation facilities caused by earthquakes emphasize the need for robust and reliable methods for evaluating the liquefaction potential of sites. Traditional methods for evaluating liquefaction potential are based on correlating data from the standard penetration test (blow count, N), cone penetration test (cone resistance, qc), or the shear wave velocity ( Vs) with the cyclic stress ratio. These methods are unable to incorporate the complex influence of various soil and in situ state parameters. This problem encouraged the development of numerous nontraditional methods such as artificial neural networks that try to learn and account for the influence of various soil and in situ state properties. The possibility of using neural networks based on adaptive resonance theory (ART) for the prediction of liquefaction potential was explored. These networks have been shown to be far more efficient and reliable than the commonly used backpropagation artificial neural network and other multilayer perceptrons. Two Fuzzy ARTMAP (FAM) models were developed and tested with qc and Vs data obtained from past case histories. The qc-and Vs-based FAM models gave overall successful prediction rates of 98% and 97%, respectively. The promising results obtained by the FAM models exemplify the potential of nontraditional computing methods for evaluating liquefaction potential.

Compound library management.

The increasing size of the collections used for drug-discovery purposes has demanded both hardware and software automation of compound management in order to cope with the increasing demands of HTS. Splitting the collection into a number of copies in different formats is a desirable approach to keep a balance between rapid response to the demands and best storage conditions. Flexibility to different assay configurations can be provided with the appropriate selection of liquid handlers, and the informatic management systems should be accessible to keep track of the samples and link them to a variety of information that can help interpret HTS data. In this respect, QC data on the compounds and quality checks of the equipment used are highly desirable. It is also prudent for a large organization with different research sites to have a unified database and compatible plate format and concentration in order to be able to exchange samples and share screening results. The accomplishment of all the previous requirements is the only way to ensure an efficient and effective compound library management.

Implementation, management and continuous quality improvement of point-of-care testing in an academic health care setting

Point-of-care testing (POCT) has economic and medical benefits in the areas of immediate medical management, resource utilization and time management. Starting with bedside glucose, the Mount Sinai Medical Center has, over the past 11 years, implemented 23 POC tests, spanning complexity from blood gas/electrolyte testing to occult blood, in compliance with all regulatory and accreditation requirements. QC data are reviewed on a daily and weekly basis and all patient results are in the electronic medical record. A variety of healthcare workers; nurses, physicians, respiratory therapists and technologists, perform testing. Since POCT impacts on a variety of hospital departments, proper implementation and management requires a multi-disciplinary team approach with focus on the financial, regulatory, quality assurance and data integration issues. Established in 1996, the institutional committee, with laboratory leadership, handles the establishment, compliance review and future direction setting of the program. In 1999, over 1300 individuals performed over 440,000 POC tests within the institution. A formalized continuous quality improvement (CQI) program for the POCT program was developed in the fall of 1999. All testing sites are reviewed on a monthly basis for various quality indicators that cover QC performance, maintenance performance, proficiency testing, patient identification, and alert value confirmations.

Role and use of expert systems within the clinical laboratory

Artificial intelligence can be used, mainly in the form of knowledge based systems, for different parts of clinical laboratory activity. Most of the iterative tasks for control and validation, or for maintenance or repair of automated instruments can be assisted by specialized software. There are now specific programmes (i) for control and validation of the request, where the goal is to modify the requesting behaviour of the physician, using protocol driven requests and immediate feedback, incorporating simultaneously a check of test request redundancy, (ii) for helping in equipment trouble-shooting, (iii) for technical and biological validation because too many QC data are issued from large equipment to be checked and used properly by the technologist whilst the pathologist can be assisted for the final revision of reports and (iv) for assistance in the interpretation of laboratory reports, one of the most valuable aspects of the pathologist's participation in the patient care process.

Statistical analysis of QC data and estimation of fuel rod behaviour

The behaviour of fuel rods while in reactor is influenced by many parameters. As far as fabrication is concerned, fuel pellet diameter and density, and inner cladding diameter are important examples. Statistical analyses of quality control data show a scatter of these parameters within the specified tolerances. At present it is common practice to use a combination of superimposed unfavorable tolerance limits (worst case dataset) in fuel rod design calculations. Distributions are not considered. The results obtained in this way are very conservative but the degree of conservatism is difficult to quantify. Probabilistic calculations based on distributions allow the replacement of the worst case dataset by a dataset leading to results with known, defined conservatism. This is achieved by response surface methods and Monte Carlo calculations on the basis of statistical distributions of the important input parameters. The procedure is illustrated by means of two examples.

Microcomputer Storage and Analysis of Quality Control Data in Clinical Microbiology

A microcomputer system was devised for storage and analysis of microbiology quality control data, using a system with 10 megabytes of disk storage capacity on a fixed disk. This provides rapid entry and retrieval of data and considerable storage capacity. Special programs were written in BASIC to accept QC data for media, reagents, and susceptibility tests. Rapid data entry is achieved by having a rapid access disk device with a terminal specifically for QC data. Results are entered daily or at times when tests are done and stored on the disk storage device. The data can be recalled for complete printing or summarization and weekly reports can be generated. This system has the potential to eliminate QC paperwork, thus conserving storage space, while allowing detailed retrospective analysis.

Defect analysis using QC data : R. C. McBride. Semiconductor Int., 82 (February 1983)

Defect analysis using QC data : R. C. McBride. Semiconductor Int., 82 (February 1983)