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Much NLP software, e.g., GATE [ 13] and MedLEE [ 14] is implemented using a pipeline of individual modules, each of which is specialized for a particular sub-task, e.g., section and sentence segmentation, part-of-speech tagging, and named-entity recognition.

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Cpipe is implemented using a pipeline construction framework called Bpipe [ 10].

The logic can be implemented using a relatively small number of gates and can be pipelined to provide rapid control of the switch fabric.

The data processing pipeline is implemented using a large field programmable gate array (FPGA) processing subsystem employing fine-grained parallelism.

The current workflow was implemented using the Pipeline Pilot software yet most of its components are available through different resources and consequently it could be implemented using alternative tools.

The map-maker and the navigator are implemented using two cameras, an IBM 7575 robot arm, and a PIPE (Pipelined Image Processing Engine).

rsem/bowtie mapping was implemented using scripts packaged with the trinity pipeline.

The automatic algorithms used within the sequential segmentation pipeline above were implemented using the Insight Toolkit library (ITK, www.itk.org), which offers a range of techniques for 3-D medical image segmentation, including several level-set algorithms.

Currently, most of the individual components of a 'standardisation pipeline' can be implemented using Blue Obelisk tools.

The proposed radix-22 and radix-23 pipelined FFT architectures are modeled and implemented using TSMC 180 nm CMOS technology with a supply voltage of 1.8 V.

The CancerEST pipeline was implemented using Perl 5.8.8 (available at http://www.perl.org).

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