jack sewing machine price in chennai,perambur, mylapore, madipakkam - VS SewingMachine
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We present a closed process chain for robotic sewing from CAD design to
the component model to realize a lot-size-one production. To achieve a
better solidity and durability of two overlapping carbon fibre layers,
an automated fibre mat stitching system was developed. At the moment,
the stitching path is predefined and inflexible to minor changes. To
enable a more flexible autonomous stitching process than given through
teach-in programming, sensors are used to calculate the difference
between the CAD sewing track and the actually required stitching
position. The application of the sensor guided stitching process makes
it possible for the robot to handle inaccuracies during inlaying of the
fibre mats into the form autonomously. Additionally, possible obstacles
and mat-ends are detected to realize a stable stitching process.
In performed a case study to contributethe objective of providing an automated system which is notonly capable to assign CRs to the appropriate developers, butalso identify the name of the suspected source files, whichare required to be modified, and estimate time, which isrequired to fix the CR. The underlying assumption is thatthe available CRs together with the information regardingthe developer resolving the CR, set of modified source filesand the time spent to fix the CR would let us extract themapping, which is close to the optimum. This assumptionis to a great extent reasonable because, when manuallyassigning CRs to developers someone would always liketo assign the right task to the right people. In this casestudy we make use of information retrieval and multi-labelmachine learning methods for indexing and classification ofthe textual information given in a CR
We briefly give an overview of our contribution. Wedivided our experimental work into three parts. In the firstpart, we extracted data from the available software repositoryof Mozilla and used the multi-label multi-class approach forlabeling of the CRs. In our case most of the software changerequests are related to the software corrective maintenancetask and are called bug reports. Therefore, we downloadedonly those software change requests that are related to thecorrective maintenance task, i.e., bug reports. However, ourtechniques may also be used for other types of maintenancetasks. In the second part, we used different informationretrieval techniques, and transformed the text data of CRsinto a low dimensional indexed term to document matrix(TDM). A TDM is a matrix whose columns representdocuments like CRs, whereas rows represent the frequencyof the existing key terms in the text of each CR .For indexing we used TF×IDF (term frequency-inversedocument frequency). To reduce the dimension we used,feature selection techniques such asDocument FrequencyThresholdingand re-parameterisation technique i.e.,LatentSemantic Indexing.
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