Combining external cavity quantum cascade lasers and MOEMS technology: An approach for miniaturization and fast wavelength scanning
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: 2014DOI: 10.1109/ICECCS.2014.17
Keyword(s): Big Data,cloud computing,social networking (online),AACT,Amazon,Facebook,Google,MapReduce,Yahoo!,adaptive auto-configuration to,adaptive automatic configuration tool,big data,bulk data processing,cloud computing framework,hadoop,hardware configuration,industrial organizations,mathematical model,optimal configuration,performance optimization,software configuration,tuning parameters,Benchmark testing,Cloud computing,Computers,Hardware,Mathematical model,Optimization,Sys
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Combining external cavity quantum cascade lasers and MOEMS technology: An approach for miniaturization and fast wavelength scanning
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| contributor author | Ambacher, O. | |
| contributor author | Ostendorf, R. | |
| contributor author | Bleh, D. | |
| contributor author | Merten, A. | |
| contributor author | Grahmann, J. | |
| contributor author | Schmidt, R. | |
| contributor author | Kunzer, M. | |
| contributor author | Hugger, S. | |
| contributor author | Wagner, J. | |
| date accessioned | 2020-03-12T21:06:02Z | |
| date available | 2020-03-12T21:06:02Z | |
| date issued | 2014 | |
| identifier other | 6924608.pdf | |
| identifier uri | http://libsearch.um.ac.ir:80/fum/handle/fum/1036977?locale-attribute=en | |
| format | general | |
| language | English | |
| publisher | IEEE | |
| title | Combining external cavity quantum cascade lasers and MOEMS technology: An approach for miniaturization and fast wavelength scanning | |
| type | Conference Paper | |
| contenttype | Metadata Only | |
| identifier padid | 8163230 | |
| subject keywords | Big Data | |
| subject keywords | cloud computing | |
| subject keywords | social networking (online) | |
| subject keywords | AACT | |
| subject keywords | Amazon | |
| subject keywords | ||
| subject keywords | ||
| subject keywords | MapReduce | |
| subject keywords | Yahoo! | |
| subject keywords | adaptive auto-configuration to | |
| subject keywords | adaptive automatic configuration tool | |
| subject keywords | big data | |
| subject keywords | bulk data processing | |
| subject keywords | cloud computing framework | |
| subject keywords | hadoop | |
| subject keywords | hardware configuration | |
| subject keywords | industrial organizations | |
| subject keywords | mathematical model | |
| subject keywords | optimal configuration | |
| subject keywords | performance optimization | |
| subject keywords | software configuration | |
| subject keywords | tuning parameters | |
| subject keywords | Benchmark testing | |
| subject keywords | Cloud computing | |
| subject keywords | Computers | |
| subject keywords | Hardware | |
| subject keywords | Mathematical model | |
| subject keywords | Optimization | |
| subject keywords | Sys | |
| identifier doi | 10.1109/ICECCS.2014.17 | |
| journal title | ptical MEMS and Nanophotonics (OMN), 2014 International Conference on | |
| filesize | 432257 | |
| citations | 0 |