Browsing Ammar Zakaria, Associate Professor Dr. by Subject "Electronic nose"

Now showing items 1-6 of 6

    • Development of human sensory mimicking system 

      Nazifah, Ahmad Fikri; Ali Yeon, Md Shakaff, Prof. Dr.; Abdul Hamid, Adom, Prof. Madya Dr.; Mohd Noor, Ahmad, Prof. Dr.; Abu Hassan, Abdullah; Ammar, Zakaria; M. A., Markom (American Scientific Publishers, 2011-02)
      Taste (gustatory) and smell (olfactory) are two of the five human senses apart from touch (somatosensory), vision and hearing (auditory). In human and many other vertebrate animals the sense of taste are often used with ...

    • Diagnosis of bacteria for diabetic foot infection using electronic nose technology 

      Nurlisa, Yusuf; Muhammad Iqbal, Omar; Ammar, Zakaria; Azian Azamimi, Abdullah; Latifah Munirah, Kamarudin; Ali Yeon, Md Shakaff, Prof. Dr.; Maz Jamilah, Masnan; Nurhamidah, Zakaria; Yeap, Ewe Juan, Dr; Abu Talib, Othman, Dr.; Mohd Sadek, Yasin (IEEE Computer Society, 2013)
      Foot infections may lead to serious complications if failed to detect at an early stage; especially for diabetic patients. It is necessary to develop an easy and reliable method to identify and classify the causative ...

    • An Electronic Nose system for aromatic rice classification 

      Abu Hassan, Abdullah; Abdul Hamid, Adom, Prof. Madya Dr.; Ali Yeon, Md. Shakaff, Prof. Dr.; Mansur N, Ahmad; Ammar, Zakaria; Nazifah, Ahmad Fikri; Othman, Omar (American Scientific Publishers, 2011-04)
      Aromatic rice is a variety of rice with good cooking qualities such as nice aroma and flavour. It is pricier because it is only suitable to be cultivated in regions with specific climatic and soil conditions. Presently, ...

    • A hybrid sensing approach for pure and adulterated honey classification 

      Norazian, Subari; Junita, Mohamad Saleh, Dr.; Ali Yeon, Md Shakaff, Prof. Dr.; Ammar, Zakaria (MDPI AG, Basel, Switzerland, 2012-10)
      This paper presents a comparison between data from single modality and fusion methods to classify Tualang honey as pure or adulterated using Linear Discriminant Analysis (LDA) and Principal Component Analysis (PCA) statistical ...

    • Improved classification of Orthosiphon stamineus by data fusion of electronic nose and tongue sensors 

      Ammar, Zakaria; Ali Yeon, Md. Shakaff, Prof. Dr.; Abdul Hamid, Adom, Assoc. Prof. Dr.; Mohd Noor, Ahmad; Maz Jamilah, Masnan; Abdul Hallis, Abd Aziz; Nazifah, Ahmad Fikri; Abu Hassan, Abdullah; Latifah Munirah, Kamarudin (MDPI Publishing, 2010-09-28)
      An improved classification of Orthosiphon stamineus using a data fusion technique is presented. Five different commercial sources along with freshly prepared samples were discriminated using an electronic nose (e-nose) and ...

    • Rapid identification method of aerobic bacteria in diabetic foot ulcers using electronic nose 

      Azian Azamimi, Abdullah; Tan, Woei Jing; Chua, Ai Sie; Nurlisa, Yusuf; Mohammad Iqbal, Omar@Ye Htut, Assoc. Prof. Dr.; Ali Yeon, Md Shakaff, Prof. Dr.; Abd Hamid, Adom, Prof. Dr.; Latifah Munirah, Kamarudin, Dr.; Yeap, Ewe Juan, Dr.; Ammar, Zakaria, Dr.; Amizah, Othman, Dr.; Mohd Sadek, Yasin (American Scientific Publishers, 2014-01)
      Diabetic foot ulcer (DFU) is an infection, ulcer or destruction of deep tissue associated with neurological abnormalities, musculoskeletal deformities and various degrees of peripheral vascular disease of lower limb. In ...