Applications of Computer Produced Frequency Distribution Curves

1967 ◽  
Vol 13 (11) ◽  
pp. 917-930 ◽  
Author(s):  
N Ressler ◽  
L S Whitlock
Keyword(s):  
Quality Control ◽  
Frequency Distribution ◽  
Processing System ◽  
Test Methods ◽  
Diagnostic Classification ◽  
Data Processing System ◽  
Validity Of Results ◽  
Frequency Distributions ◽  
Relative Value

Abstract Applications to quality control of a laboratory's own individual frequency distribution curves are described. The method has recently become feasible for routine use, since the curves can now be compiled automatically by means of an electronic data-processing system. Applications described include verification of the validity of results generated by a given method in terms of the frequency distributions obtained for each type of diagnostic classification, and the determination of the constancy of these distributions. The relative value of different test methods can be compared by the success which is achieved in distinguishing diagnostic classifications (as measured by the overlaps of different frequency distribution curves). Individual frequency distributions can also be used to determine the precision required for given test, in order to avoid any loss in the discrimination which can be achieved.

scholarly journals Implementation of a GPS-RO data processing system for the KIAPS-LETKF data assimilation system

2014 ◽  
Vol 7 (11) ◽  
pp. 11927-11956 ◽  
Author(s):  
H. Kwon ◽  
J.-S. Kang ◽  
Y. Jo ◽  
J. H. Kang
Keyword(s):  
Quality Control ◽  
Data Assimilation ◽  
Data Processing ◽  
Weather Prediction ◽  
Processing System ◽  
Data Processing System ◽  
Bending Angle ◽  
Quality Control Process ◽  
Data Assimilation System ◽  
Assimilation System

Abstract. The Korea Institute of Atmospheric Prediction Systems (KIAPS) has been developing a new global numerical weather prediction model and an advanced data assimilation system. As part of the KIAPS Package for Observation Processing (KPOP) system for data assimilation, preprocessing and quality control modules for bending angle measurements of global positioning system radio occultation (GPS-RO) data have been implemented and examined. GPS-RO data processing system is composed of several steps for checking observation locations, missing values, physical values for Earth radius of curvature, and geoid undulation. An observation-minus-background check is implemented by use of a one-dimensional observational bending angle operator and tangent point drift is also considered in the quality control process. We have tested GPS-RO observations utilized by the Korean Meteorological Administration (KMA) within KPOP, based on both the KMA global model and the National Center for Atmospheric Research (NCAR) Community Atmosphere Model-Spectral Element (CAM-SE) as a model background. Background fields from the CAM-SE model are incorporated for the preparation of assimilation experiments with the KIAPS-LETKF data assimilation system, which has been successfully implemented to a cubed-sphere model with fully unstructured quadrilateral meshes. As a result of data processing, the bending angle departure statistics between observation and background shows significant improvement. Also, the first experiment in assimilating GPS-RO bending angle resulting from KPOP within KIAPS-LETKF shows encouraging results.

scholarly journals A Novel Approach to Improve Quality Control by Comparing the Tagged Sequences of Product Traceability

2018 ◽  
Vol 201 ◽  
pp. 05002 ◽  
Author(s):  
Jing-Doo Wang
Keyword(s):  
Quality Control ◽  
Frequency Distribution ◽  
Programming Model ◽  
Intelligent Manufacturing ◽  
Product Line ◽  
Sequential Data ◽  
Improve Quality ◽  
Huge Amount ◽  
Frequency Distributions ◽  
Class Frequency

Quality control is an essential issue for manufacture, especially when the manufacture is towards intelligent manufacturing that is associated with “Internet of thing”(IOT) and “Artificial Intelligence”(AI) to speed up the rate of product line automatically nowadays. To monitor product quality automatically, it is necessary to collect and monitor the data generated by sensors, or to record parameters by machine operators, or to save the types (brands) of materials used when producing products. In this study, it is assumed that the sequences of the traceability of unqualified products are different from that of qualified ones, and these different values (or points) within the sequences result in these products qualified or unqualified. This approach extracts maximal repeats from the tagged sequences of product traceability, and meanwhile computes the class frequency distribution of these repeats, where the classes, e.g. “qualified” or “unqualified”, are derived from the tags. Instead of inspecting all of the sequences of product traceability aimlessly, quality control engineers can filter out those maximal repeats whose frequency distributions are unique to specific classes and then just check the corresponding processes of these repeats. However, from the practical point of view, it should be estimated as a big-data problem to extract these maximal repeats and meanwhile compute their corresponding class frequency distribution from a huge amount of tagged sequential data. To have this work practical, this study uses one previous work that is based on Hadoop MapReduce programming model. and has been applied for an U.S.A patent (US Patent App. 15/208,994). Therefore, it is expected to be able to handle a huge amount of sequences of product traceability. With this approach that can narrow down the range for identifying false points (processes) within product line, it is expected to improve quality control by comparing tagged sequences of product traceability in the future.

scholarly journals Determination of Disk Diffusion and MIC Quality Control Guidelines for High-Dose Cefepime-Tazobactam (WCK 4282), a Novel Antibacterial Combination Consisting of a β-Lactamase Inhibitor and a Fourth-Generation Cephalosporin

2017 ◽  
Vol 55 (10) ◽  
pp. 3130-3134 ◽  
Author(s):  
Stefan Riedel ◽  
Michael D. Huband ◽  
Helio S. Sader ◽  
Robert K. Flamm ◽  
Ronald N. Jones
Keyword(s):  
Quality Control ◽  
Generation Cephalosporin ◽  
Test Methods ◽  
Disk Diffusion ◽  
Fourth Generation ◽  
High Dose ◽  
Gram Negative ◽  
Lactamase Inhibitor

ABSTRACTHigh-dose cefepime-tazobactam (1:1; WCK 4282), a novel antibacterial combination consisting of the β-lactamase inhibitor tazobactam and a fourth-generation cephalosporin, is under clinical development for the treatment of serious Gram-negative infections. A quality control (QC) study was performed to establish disk diffusion and MIC ranges for cefepime-tazobactam for multiple QC reference strains. The cefepime-tazobactam QC ranges for a fixed tazobactam MIC of 8 μg/ml and disk diffusion (30/20-μg disk) test methods were approved by the CLSI Subcommittee on Antimicrobial Susceptibility Testing in January 2015 and January 2016. These QC ranges will be important for accuratein vitroactivity evaluations of cefepime-tazobactam when tested against clinical Gram-negative bacteria during clinical studies and routine patient care.

Applications of Computer Produced Frequency Distribution Curves

1967 ◽  
Vol 13 (11) ◽  
pp. 931-940 ◽  
Author(s):  
N Ressler ◽  
L S Whitlock
Keyword(s):  
Frequency Distribution ◽  
Distribution Curve ◽  
Processing System ◽  
Test Results ◽  
Data Processing System ◽  
Diagnostic Significance ◽  
Frequency Distribution Curve ◽  
Age And Sex ◽  
Probable Diagnosis

Abstract A method is described for determining the diagnostic significance of test results. It is based upon the relation of a test value to a frequency distribution curve of patients with a particular disease, and to a curve of others without that disease. When the two curves overlap at the test value found, the results are evaluated in terms of the probability of the patient corresponding to either of the two curves. The evaluation of results in terms of probabilities is more descriptive than the classification of all answers as either "normal" or "abnormal" and permits the combination of probabilities obtained from a number of tests into a single, resultant probability. The most probable diagnosis of a given patient, based upon all the tests done, or the most discriminating combination of tests for the diagnosis of any disease can be determined. The method permits compensation for such factors as a patient's age and sex, or the stage of a disease. It is nonparametric, and can be performed automatically with a data-processing system.

scholarly journals Implementation of Hybrid Algorithm in Cluster Head using Neural Networks

2021 ◽  
Vol 9 (VI) ◽  
pp. 4147-4152
Author(s):  
Pooja S
Keyword(s):  
Neural Network ◽  
Cluster Head ◽  
Processing System ◽  
Delivery Ratio ◽  
Data Processing System ◽  
Processing Elements ◽  
Packet Delivery ◽  
Neural Organization ◽  
Ratio Energy

A Neural Network is a data processing system consisting of large number of simple, highly interconnected processing elements. In this paper a graphical convention is utilized where hubs are orchestrated in the form of cluster. An epic methodology is presented for choice of group head by the utilization of fake neural organization to expand organization's lifetime in WSN and calculation of steering convention dependent on neural organizations (NNs). In the proposed work, a standard burned-through energy is used for the choice of bunch head and and steering convention LEACH is used. The leftover energy is utilized for making group head and for the determination of bunch head using Neural Network. In the proposed system Using LEACHNN algorithm Throughput, packet delivery ratio ,energy is improved by 20%.

scholarly journals Implementation of a GPS-RO data processing system for the KIAPS-LETKF data assimilation system

2015 ◽  
Vol 8 (3) ◽  
pp. 1259-1273 ◽  
Author(s):  
H. Kwon ◽  
J.-S. Kang ◽  
Y. Jo ◽  
J. H. Kang
Keyword(s):  
Quality Control ◽  
Data Assimilation ◽  
Data Processing ◽  
Weather Prediction ◽  
Processing System ◽  
Data Processing System ◽  
Bending Angle ◽  
Quality Control Process ◽  
Data Assimilation System ◽  
Assimilation System

Abstract. The Korea Institute of Atmospheric Prediction Systems (KIAPS) has been developing a new global numerical weather prediction model and an advanced data assimilation system. As part of the KIAPS package for observation processing (KPOP) system for data assimilation, preprocessing, and quality control modules for bending-angle measurements of global positioning system radio occultation (GPS-RO) data have been implemented and examined. The GPS-RO data processing system is composed of several steps for checking observation locations, missing values, physical values for Earth radius of curvature, and geoid undulation. An observation-minus-background check is implemented by use of a one-dimensional observational bending-angle operator, and tangent point drift is also considered in the quality control process. We have tested GPS-RO observations utilized by the Korean Meteorological Administration (KMA) within KPOP, based on both the KMA global model and the National Center for Atmospheric Research Community Atmosphere Model with Spectral Element dynamical core (CAM-SE) as a model background. Background fields from the CAM-SE model are incorporated for the preparation of assimilation experiments with the KIAPS local ensemble transform Kalman filter (LETKF) data assimilation system, which has been successfully implemented to a cubed-sphere model with unstructured quadrilateral meshes. As a result of data processing, the bending-angle departure statistics between observation and background show significant improvement. Also, the first experiment in assimilating GPS-RO bending angle from KPOP within KIAPS-LETKF shows encouraging results.

The Karolinska Hospital Information System

1974 ◽  
Vol 13 (03) ◽  
pp. 125-140 ◽  
Author(s):  
Ch. Mellner ◽  
H. Selajstder ◽  
J. Wolodakski
Keyword(s):  
Information System ◽  
Data Processing ◽  
Data Base ◽  
Hospital Information System ◽  
Care Delivery ◽  
Traditional Approach ◽  
Processing System ◽  
Systems Design ◽  
Data Processing System ◽  
Karolinska Hospital

The paper gives a report on the Karolinska Hospital Information System in three parts.In part I, the information problems in health care delivery are discussed and the approach to systems design at the Karolinska Hospital is reported, contrasted, with the traditional approach.In part II, the data base and the data processing system, named T1—J 5, are described.In part III, the applications of the data base and the data processing system are illustrated by a broad description of the contents and rise of the patient data base at the Karolinska Hospital.

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