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Research Article

DEVELOPMENT OF NEURAL NETWORK-BASED ELECTRONIC NOSE FOR HERBS RECOGNITION

The ability to classify distinctive odor pattern for aromatic plants species provides significant impact in food industry especially for herbs. Each herbs species has a unique physicochemical and a distinctive odors. This project emphasizes on the techniques of artificial intelligence (AI) to distinguish distinctive odor pattern for herbs. Neural Network method has been exploited for the classification and optimization of various odor patterns. Based on AI techniques, Neural Network-based

A. Che Soh, K. K.Chow, U. K. Mohammad Yusuf, A. J. Ishak, M. K. Hassan, S. Khamis

International Journal on Smart Sensing and Intelligent Systems , ISSUE 2, 584–609

Short Communication

Endophytic Detection in Selected European Herbal Plants

A total of 181 cultivable endophytic bacterial isolates were collected from stems of 13 species of herbs inhabiting Europe (Poland): Chelido­nium majus L., Elymus repens L., Erigeron annuus L., Euphrasia rostkoviana Hayne, Foeniculum vulgare L., Geranium pratense L., Humulus lupulus L., Matricaria chamomilla L., Mentha arvensis L., Papaver rhoeas L., Rosmarinus officinalis L., Solidago gigantea L. and Vinca minor L. The isolates were screened for their antifungal activity and fifty three

Agata Goryluk-Salmonowicz, Monika Piórek, Hanna Rekosz-Burlaga, Marcin Studnicki, Mieczysław Błaszczyk

Polish Journal of Microbiology , ISSUE 3, 369–375

research-article

Forest fire detection using wireless sensor networks

Premsai Dasari, Gundam Krishna Jayanth Reddy, Abhishek Gudipalli

International Journal on Smart Sensing and Intelligent Systems , ISSUE 1, 1–8

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