Browsing Ammar Zakaria, Associate Professor Dr. by Author "abuhassan@unimap.edu.my"

Now showing items 1-4 of 4

    • Braitenberg swarm vehicles for odour plume tracking in laminar airflow 

      Syed Muhammad Mamduh, Syed Zakaria; Kamarulzaman, Kamarudin; Shaharil, Mad Saad; Ali Yeon, Md Shakaff, Prof. Dr.; Ammar, Zakaria; Abu Hassan, Abdullah, Dr. (Institute of Electrical and Electronics Engineers (IEEE), 2013-04)
      This paper presents an algorithm to trace an odour plume using swarm robots in laminar airflow. The algorithm proposed here aims to bridge the gap between single and multiple element systems by mimicking and enhancing ...

    • 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, ...

    • Enhancing conductive polymer performance using eggshell for ammonia sensor 

      Supri, Abdul Ghani, Prof. Madya Dr.; Ammar, Zakaria; Ali Yeon, Md. Shakaff, Prof. Dr.; Abu Hassan, Abdullah, Dr.; Mohd Noor, Ahmad, Prof, Dr. (Penerbit Universiti Sains Malaysia, 2012)
      Polyaniline/eggshell powder composites are proposed as a novel ammonia detecting sensor. The conductive composite is prepared by mixing eggshell powder and polyaniline using polymerisation process, blended in an appropriate ...

    • 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 ...