ASTERISK TEXT STEGANOGRAPHY TOOL A HIGHLY SECURE TEXT STEGANOGRAPHY APPROACH
Published In: INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTER, ELECTRONICS AND ELECTRICAL ENGINEERING
Author(s): ABHIJIT SHARAD THAKKER
Abstract: Steganography is the art and science of writing hidden messages in such a way that no one, apart from the sender and intended recipient, suspects the existence of the message, a form of security through obscurity. Steganography can be used to hide a message intended for later retrieval by a specific individual or group. In this case the aim is to prevent the message being detected by any other party. Steganography and encryption are both used to ensure data confidentiality. Steganography hides the existence of secret message and in the best case nobody can see that both parties are communicating in secret. This text steganography tool will help quick, efficient and highly secure text message transfers.
- Publication Date: 28-Apr-2013
- DOI: 10.15224/978-981-07-6260-5-02
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SAW SENSOR ARRAY DATA FUSION FOR CHEMICAL CLASS RECOGNITION OF VOLATILE ORGANIC COMPOUNDS
Published In: INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTER, ELECTRONICS AND ELECTRICAL ENGINEERING
Author(s): KENSHI HAYASHI , SUNIL K. JHA
Abstract: Present study deals the development of data fusion based artificial intelligence unit for the chemical sensor array based electronic nose (E-Nose) system. We focus particularly on feature level fusion of model surface acoustic wave (SAW) sensor array response for chemical class identification of volatile organic compounds (VOCs). Three methods are used for feature extraction namely: principal component analysis (PCA); independent component analysis (ICA) and kernel principal component analysis (KPCA). Fused features are generated with three unsupervised fusion schemes and validated in combination with support vector machine (SVM) classifier. Study is concluded by the analysis of 12 model SAW sensor array data sets. It suggests that amongst the three feature fusion schemes; feature fusion by summation result highest class recognition rate of VOCs.
- Publication Date: 28-Apr-2013
- DOI: 10.15224/978-981-07-6260-5-03
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- Downloads: 0