Quality control in the polypropylene manufacturing process: An efficient, data-driven approach

2014 ◽  
Vol 132 (3) ◽  
pp. n/a-n/a ◽  
Author(s):  
Zhong Cheng ◽  
Xinggao Liu
Keyword(s):  
Quality Control ◽  
Manufacturing Process ◽  
Data Driven ◽  
Data Driven Approach ◽  
Efficient Data

scholarly journals A Data-driven Approach for General Visual Quality Control in a Robotic Workcell

2019 ◽  
Vol 1335 ◽  
pp. 012013
Author(s):  
Simon Reich ◽  
Florian Teich ◽  
Minija Tamosiunaite ◽  
Florentin Wörgötter ◽  
Tatyana Ivanovska
Keyword(s):  
Quality Control ◽  
Visual Quality ◽  
Data Driven ◽  
Data Driven Approach

scholarly journals Classification of Ventricular Arrhythmias Based on a Data Driven Approach

2021 ◽  
Author(s):  
Matthew Hotradat
Keyword(s):  
Real Time ◽  
Ventricular Arrhythmias ◽  
Data Driven ◽  
Term Therapy ◽  
Computationally Efficient ◽  
Therapy Options ◽  
Data Driven Approach ◽  
Efficient Data ◽  
Long Term Therapy ◽  
Over Time

Ventricular arrhythmias (VA) are dangerous pathophysiological conditions affecting the heart which evolve over time resulting in different manifestations such as ventricular tachycardia (VT), organized VF (OVF), and disorganized VF (DVF). Success of resuscitation for patients is greatly impacted by the type of VA and swift administration of appropriate therapy options. This thesis attempts to arrive at computationally efficient, data driven approaches for classifying and tracking VAs over time for two purposes: (1) ‘in-hospital’ scenarios for planning long-term therapy options, and (2) ‘out-of-hospital’ scenarios for tracking progression/segregation of VAs in near real-time. Using a database of 61 60-s ECG VA segments, maximum classification accuracies of 96.7% (AUC=0.993) and 87% (AUC=0.968) were achieved for VT vs. VF and OVF vs. DVF classification for ‘in-hospital’/offline analysis. Two near real-time approaches were also developed for ‘out-of-hospital’ VA incidents with results demonstrating the high potential to track VA progression and segregation over time.

scholarly journals “Gap hunting” to characterize clustered probe signals in Illumina methylation array data

2016 ◽  
Author(s):  
Shan V. Andrews ◽  
Christine Ladd-Acosta ◽  
Andrew P. Feinberg ◽  
Kasper D. Hansen ◽  
M. Daniele Fallin
Keyword(s):  
Association Studies ◽  
Data Driven ◽  
Probe Type ◽  
450K Array ◽  
Methylation Array ◽  
Association Analyses ◽  
Data Driven Approach ◽  
Efficient Data ◽  
Dna Strand ◽  
Clustered Distributions

AbstractBackgroundThe Illumina 450K array has been widely used in epigenetic association studies. Current quality-control (QC) pipelines typically remove certain sets of probes, such as those containing a SNP or with multiple mapping locations. An additional set of potentially problematic probes are those with DNA methylation (DNAm) distributions characterized by two or more distinct clusters separated by gaps. Data-driven identification of such probes may offer additional insights for downstream analyses.ResultsWe developed a procedure, termed “gap hunting”, to identify probes showing clustered distributions. Among 590 peripheral blood samples from the Study to Explore Early Development, we identified 11,007 “gap probes”. The vast majority (9,199) are likely attributed to an underlying SNP(s) or other variant in the probe, although SNP-affected probes exist that do not produce a gap signals. Specific factors predict which SNPs lead to gap signals, including type of nucleotide change, probe type, DNA strand, and overall methylation state. These expected effects are demonstrated in paired genotype and 450k data on the same samples. Gap probes can also serve as a surrogate for the local genetic sequence on a haplotype scale and can be used to adjust for population stratification.ConclusionsThe characteristics of gap probes reflect potentially informative biology. QC pipelines may benefit from an efficient data-driven approach that “flags” gap probes, rather than filtering such probes, followed by careful interpretation of downstream association analyses. Our results should translate directly to the recently released Illumina 850K EPIC array given the similar chemistry and content design.

scholarly journals Classification of Ventricular Arrhythmias Based on a Data Driven Approach

2021 ◽  
Author(s):  
Matthew Hotradat
Keyword(s):  
Real Time ◽  
Ventricular Arrhythmias ◽  
Data Driven ◽  
Term Therapy ◽  
Computationally Efficient ◽  
Therapy Options ◽  
Data Driven Approach ◽  
Efficient Data ◽  
Long Term Therapy ◽  
Over Time

Ventricular arrhythmias (VA) are dangerous pathophysiological conditions affecting the heart which evolve over time resulting in different manifestations such as ventricular tachycardia (VT), organized VF (OVF), and disorganized VF (DVF). Success of resuscitation for patients is greatly impacted by the type of VA and swift administration of appropriate therapy options. This thesis attempts to arrive at computationally efficient, data driven approaches for classifying and tracking VAs over time for two purposes: (1) ‘in-hospital’ scenarios for planning long-term therapy options, and (2) ‘out-of-hospital’ scenarios for tracking progression/segregation of VAs in near real-time. Using a database of 61 60-s ECG VA segments, maximum classification accuracies of 96.7% (AUC=0.993) and 87% (AUC=0.968) were achieved for VT vs. VF and OVF vs. DVF classification for ‘in-hospital’/offline analysis. Two near real-time approaches were also developed for ‘out-of-hospital’ VA incidents with results demonstrating the high potential to track VA progression and segregation over time.

Emerging Techniques for the Characterization of Nano-Mechanical Properties of Integrated Circuit Components

2008 ◽  
Author(s):  
Nicholas Randall ◽  
Rahul Premachandran Nair
Keyword(s):  
Mechanical Properties ◽  
Quality Control ◽  
Integrated Circuits ◽  
Integrated Circuit ◽  
Manufacturing Process ◽  
Solder Bumps ◽  
Initial Work ◽  
Circuit Components ◽  
Materials Used

Abstract With the growing complexity of integrated circuits (IC) comes the issue of quality control during the manufacturing process. In order to avoid late realization of design flaws which could be very expensive, the characterization of the mechanical properties of the IC components needs to be carried out in a more efficient and standardized manner. The effects of changes in the manufacturing process and materials used on the functioning and reliability of the final device also need to be addressed. Initial work on accurately determining several key mechanical properties of bonding pads, solder bumps and coatings using a combination of different methods and equipment has been summarized.

Extended-Range Prediction with Low-Dimensional, Stochastic-Dynamic Models: A Data-driven Approach

2012 ◽  
Author(s):  
Michael Ghil ◽  
Mickael D. Chekroun ◽  
Dmitri Kondrashov ◽  
Michael K. Tippett ◽  
Andrew Robertson ◽  
...  
Keyword(s):  
Dynamic Models ◽  
Data Driven ◽  
Stochastic Dynamic ◽  
Extended Range ◽  
Data Driven Approach ◽  
Low Dimensional
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