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dc.contributor.authorYee, Nigel
dc.contributor.authorYan, Ashley
dc.date.accessioned2016-06-02T21:16:31Z
dc.date.available2016-06-02T21:16:31Z
dc.date.issued2015-12
dc.identifier.urihttps://hdl.handle.net/10652/3407
dc.description.abstractThis paper presents results from a scoping study undertaken with the intention of demonstrating the applicability of reflectance Near-Infrared (NIR) spectroscopy in classification of pharmaceutical type based on active ingredient. The part of the process selected for the scoping study is the packaging step in the manufacturing of pharmaceuticals. The rationale for the selection of the packaging step is in older processing lines the product is classified after tablet coating and before blister packaging using visual automatic inspection techniques however for 100% conformance a more discriminating technique is required. In this study, NIR spectra (with wavelengths between 400nm and 1100nm) were obtained for samples pertaining to 3 different types of pharmaceuticals Quetiapine, Ibuprofen and Paracetamol. The dimensionality of the data set was reduced using Principal Components and the data was feed into a back propagation neural network configured to classify the data based on active ingredient type. The recognition rates achieved in this study were high enough to suggest that NIR spectroscopy is a viable method of ensuring 100% identification of pharmaceutical type prior to packaging for the pharmaceuticals tested.en_NZ
dc.language.isoenen_NZ
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_NZ
dc.subjectpharmaceuticalsen_NZ
dc.subjectneural networksen_NZ
dc.subjectnear infrared spectrometeren_NZ
dc.subjectactive ingredientsen_NZ
dc.titleNeural network classification of pharmaceutical active ingredient from near infrared spectraen_NZ
dc.typeConference Contribution - Paper in Published Proceedingsen_NZ
dc.rights.holderInstitute of Electrical and Electronics Engineers (IEEE)en_NZ
dc.subject.marsden080108 Neural, Evolutionary and Fuzzy Computationen_NZ
dc.subject.marsden1115 Pharmacology and Pharmaceutical Sciencesen_NZ
dc.identifier.bibliographicCitationYee, N. G., & Yan, A. (2015, December). Neural Network Classification of Pharmaceutical Active Ingredient from Near Infrared Spectra. In IEEE (Ed.), Paper presented at 2nd Institute of Electrical and Electronics Engineers (IEEE) Asia-Pacific World Congress on Computer Science and Engineering (APWC on CSE 2015) (pp.28-34).en_NZ
unitec.institutionUnitec Institute of Technologyen_NZ
unitec.publication.spage28en_NZ
unitec.publication.lpage34en_NZ
unitec.publication.title2nd Institute of Electrical and Electronics Engineers (IEEE) Asia-Pacific World Congress on Computer Science and Engineering (APWC on CSE 2015)en_NZ
unitec.conference.title2nd Institute of Electrical and Electronics Engineers (IEEE) Asia-Pacific World Congress on Computer Science and Engineering (APWC on CSE 2015)en_NZ
unitec.conference.orgInstitute of Electrical and Electronics Engineers (IEEE)en_NZ
unitec.conference.locationShangri-La Fijian Resort, Fijien_NZ
unitec.conference.sdate2015-12-02
unitec.conference.edate2015-12-04
unitec.peerreviewedyesen_NZ
dc.contributor.affiliationUnitec Institute of Technologyen_NZ
unitec.identifier.roms58524en_NZ
unitec.identifier.roms62664
unitec.institution.studyareaComputing


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