Electronic nose for volatile and nonvolatile odors identification / Mohamed Abdelkhalek Saad ; Supervised Magda B. Fayek

By:

Mohamed Abdelkhalek Saad

Contributor(s):

Magda B. Fayek []

Material type: Text

TextLanguage: English Publication details: Cairo : Mohamed Abdelkhalek Saad , 2017Description: 67 P. : charts , facsimiles ; 30cmOther title:

الانف الاصطناعية للتعرف على الروائح المتطايرة والغير متطايرة [Added title page title]

Subject(s):

Online resources:

Click here to access online

Available additional physical forms:

Issued also as CD

Dissertation note: Thesis (M.Sc.) - Cairo University - Faculty of Engineering- Department of Computer Engineering Summary: The developed nose can be used in normal environment with no extra odor delivery interface needed. The system comprises a sensor array of four MOS sensor, ATMEL microcontroller and a developed feature extraction algorithm based on a newly proposed feature extraction algorithm. Classification is performed using KNN, where K is optimized for the best accuracy. The system is supported by an extendable interface that allows the nose to learn more odors and use other classification techniques if required. The proposed E-nose has been tested and proved its efficiency in detecting non-volatile odors such as pure fruit juices (Orange, Apple, Pineapple and Grenade juices) and rotten egg and volatile odors such as Butane gas and Grenade perfume with accuracy of 98.6%using KNN(K=1).

Tags from this library: No tags from this library for this title. Log in to add tags.

Average rating: 0.0 (0 votes)

Holdings
Item type	Current library	Home library	Call number	Copy number	Status	Barcode
Thesis	قاعة الرسائل الجامعية - الدور الاول	المكتبة المركزبة الجديدة - جامعة القاهرة	Cai01.13.06.M.Sc.2017.Mo.E (Browse shelf(Opens below))		Not for loan	01010110072816000
CD - Rom	مخـــزن الرســائل الجـــامعية - البدروم	المكتبة المركزبة الجديدة - جامعة القاهرة	Cai01.13.06.M.Sc.2017.Mo.E (Browse shelf(Opens below))	72816.CD	Not for loan	01020110072816000

Browsing المكتبة المركزبة الجديدة - جامعة القاهرة shelves Close shelf browser (Hides shelf browser)

Previous	No cover image available	No cover image available	No cover image available	No cover image available	No cover image available	No cover image available	No cover image available	Next
Previous	Cai01.13.06.M.Sc.2017.Kh.U User location predictions using tree based and markov models /	Cai01.13.06.M.Sc.2017.Kh.U User location predictions using tree based and markov models /	Cai01.13.06.M.Sc.2017.Mo.E Electronic nose for volatile and nonvolatile odors identification /	Cai01.13.06.M.Sc.2017.Mo.E Electronic nose for volatile and nonvolatile odors identification /	Cai01.13.06.M.Sc.2017.Sa.G A genetic based algorithm for conflict resolution /	Cai01.13.06.M.Sc.2017.Sa.G A genetic based algorithm for conflict resolution /	Cai01.13.06.M.Sc.2017.Ya.I Improving VQA models using tree neural networks /	Next

Thesis (M.Sc.) - Cairo University - Faculty of Engineering- Department of Computer Engineering

The developed nose can be used in normal environment with no extra odor delivery interface needed. The system comprises a sensor array of four MOS sensor, ATMEL microcontroller and a developed feature extraction algorithm based on a newly proposed feature extraction algorithm. Classification is performed using KNN, where K is optimized for the best accuracy. The system is supported by an extendable interface that allows the nose to learn more odors and use other classification techniques if required. The proposed E-nose has been tested and proved its efficiency in detecting non-volatile odors such as pure fruit juices (Orange, Apple, Pineapple and Grenade juices) and rotten egg and volatile odors such as Butane gas and Grenade perfume with accuracy of 98.6%using KNN(K=1).

Issued also as CD

There are no comments on this title.

to post a comment.

Click on an image to view it in the image viewer