Abu Hassan Abdullah
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Abu Hassan Abdullah
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Abdullah, Abu Hassan
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26029734700

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  • Publication
    Improved classification of orthosiphon stamineus by data fusion of electronic nose and tongue sensors
    ( 2010)
    Ammar Zakaria
    ;
    Ali Yeon Md Shakaff
    ;
    Abdul Hamid Adom
    ;
    Mohd Noor Ahmad
    ;
    Masnan, Maz Jamilah
    ;
    Abdul Hallis Abdul Aziz
    ;
    Nazifah Ahmad Fikri
    ;
    Abu Hassan Abdullah
    ;
    Latifah Munirah Kamarudin
    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 an electronic tongue (e-tongue). Samples from the different commercial brands were evaluated by the e-tongue and then followed by the e-nose. Applying Principal Component Analysis (PCA) separately on the respective e-tongue and e-nose data, only five distinct groups were projected. However, by employing a low level data fusion technique, six distinct groupings were achieved. Hence, this technique can enhance the ability of PCA to analyze the complex samples of Orthosiphon stamineus. Linear Discriminant Analysis (LDA) was then used to further validate and classify the samples. It was found that the LDA performance was also improved when the responses from the e-nose and e-tongue were fused together.
  • Publication
    Multiple-criteria decision analysis for effect of shoot growth at difference combination nutrient fertilizer NPK for Harumanis mango
    ( 2023)
    Erdy Sulino Mohd Muslim Tan
    ;
    Norasmadi Abdul Rahim
    ;
    Marni Azira Markom
    ;
    Abu Hassan Abdullah
    ;
    Allan Melvin Andrew
    ;
    Aimi Salihah Abdul Nasir
    It is vital to have the correct fertiliser arrangement for effective tree development, fruit yield, and essential fruit quality. The amount of fertiliser suggested with adequate nutrition will be maintained in the soil to supply the needs of the trees as they grow throughout the various growth stages. This study evaluated the effect of different combinations of Nitrogen(N), Phosphorus(P), and Potassium(K) on the vegetative flush physiology of Harumanis mango (Mangifera Indica. L). Single and combinations of N (511g), P(511g), and K(255g) fertilisers were used, which were N, P, NP, and NPK throughout May 2021. The results revealed that the minimum number of mature green leaves and a higher number of healthy panicles were observed in the NPK-treated plants. Moreover, NPK treatment showed the lowest malformation intensity percentage compared to other fertiliser treatments. The data were analysed to obtain the best regrowth pattern of shoots using Multiple-Criteria Decision Analysis (MCDA) techniques. The results on the pattern of regrowth after pruning when federalised with NPK fertiliser showed that the maximum percentage of total vegetative flush was 87.5% and the remaining 12.5% did not reach a satisfactory level according to the MCDA analysis.
      19  3
  • Publication
    Fuzzy logic based prediction of micronutrients demand for harumanis mango growth cycles
    ( 2021-12-01)
    Wan Mohd Nooriman Wan Yahya
    ;
    Abu Hassan Abdullah
    ;
    Norasmadi Abdul Rahim
    ;
    Erdy Sulino Mohd Muslim Tan
    Harumanis is a famous green eating mango cultivar that has been commercially cultivated in Malaysia's state of Perlis. A variety of nutrients are found in soil, all of which are necessary for plant growth. Micronutrients such as Nitrogen (N), Phosphorus (P), and Potassium (K) are essential for Harumanis mango (Mangifera Indica) to growth. The importance of soil fertility in achieving high plant productivity and quality cannot be overstated. It should be used in a moderate amount and in a balanced manner. Predicting appropriate nutrients and the right timing to satisfy the tree's demands is critical. The aim of this study is to create a fuzzy logic-based system to analyse the results of soil tests for nitrogen (N), phosphorus (P), and potassium (K) in the Harumanis mango orchard. The interpreted data are used to estimate N-P-K nutrient levels and indicate the optimal fertilizer solution and application timing for each Harumanis growth stages. The system utilizes Fuzzy Logic Control (FLC) to predict the nutrients demand for Harumanis mango growth. Results shows the system able to calculate and predict values of required N-P-K fertilizer for optimal growth. Thus, assist farmers in predicting the proper amount of N-P-K to apply to Harumanis mango soil.
      2  33
  • Publication
    Cloud-based System for University Laboratories Air Monitoring
    ( 2020-09-21)
    Abu Hassan Abdullah
    ;
    Sukhairi Sudin
    ;
    Mustafa M.H.
    ;
    Fathinul Syahir Ahmad Sa'ad
    ;
    Khairul Azwan Ismail
    ;
    Muhammad Aizat Abu Bakar
    ;
    Mohamed Elshaikh Elobaid Said Ahmed
    ;
    Abdul Ghapar Ahmad
    ;
    Zahari Awang Ahmad
    ;
    Sara Yasina Yusuf
    Indoor air such as house, shopping complex, hospital, university, office and hotel should be monitor for human safety and wellbeing. These closed areas are prone to harmful air pollutants i.e. allergens, smoke, mold, particles radon and hazardous gas. Laboratories in university are special room in which workers (student, technician, teaching/research assistants, researcher and lecturer) conduct their works and experiment. The activities and the environment will generate specific air pollutant which concentration depending to their parameters. Anyone in the environment that exposure to these pollutants may affect safety and health issue. This paper proposes a study of development of a cloud-based electronic nose system for university laboratories air monitoring. The system consists of DSP33-based electronic nose (e-nose) as nodes which measure main indoor air pollutant along with two thermal comfort variables, temperature and relative humidity. The e-noses are placed at five different laboratories for acquiring data in real time. The data will be sent to a web server and the cloud-based system will process, analyse using Neuro-Fuzzy classifier and display on a website in real time. The system will monitor the laboratories air pollutants and thermal comfort by predict the pollutant concentration and dispersion in the area i.e. Air Pollution Index (API). In case of air hazard safety (e.g., gas spills detection and pollution monitoring), the system will alert the security by activate an alarm and through e-mail. The website will display the API of the area in real-time. Results show that the system performance is good and can be used to monitor the air pollutant in the university laboratories.
      39  2
  • Publication
    Development of Ripeness Indicator for Quality Assessment of Harumanis Mango by using Image Processing Technique
    ( 2020-12-18)
    Mohd Nazri Abu Bakar
    ;
    Abu Hassan Abdullah
    ;
    Haniza Yazid
    ;
    Fathinul Syahir Ahmad Sa'ad
    ;
    Ahmad K.
    ;
    Norasmadi Abdul Rahim
    Visual appearance is the main source of information that can be used for quality assessment of mango. In this study, a non-destructive ripeness level estimation for mango of the cultivar Harumanis based on digital image analysis was employed. The changing peel and flesh colour of mango is strongly correlated to ripeness that can be measured as a sensual quality parameter. This measurement of ripeness level has been determined by image analysis technique which needs to attribute external and internal colour feature from image segmentation Multilevel thresholding technique is proposed for colour image segmentation to extract the mango region from the background which every channel of five colour spaces have been applied. Colour analysis technique and Total soluble solids (TSS) is used to compare and evaluate for the prediction. The optimal results were obtained that a∗ channel from L∗a∗b colour space has given more logical and better performance of prediction which is more than 92% accuracy.
      4  29
  • Publication
    Potential of Near-Infrared (NIR) spectroscopy technique for early detection of Insidious Fruit Rot (IFR) disease in Harumanis mango
    ( 2021-12-01)
    Noor Shazliza Zakaria
    ;
    Abu Hassan Abdullah
    ;
    Fathinul Syahir Ahmad Sa'ad
    ;
    Muhamad Khairul Ali Hassan
    ;
    Mohd Nazri Abu Bakar
    ;
    Saad A.R.M.
    ;
    Sukhairi Sudin
    ;
    Ibrahim M.F.
    Harumanis mango 'Insidious Fruit Rot'(IFR), is one of the common issues that hampered the fruit quality and consequently lowered the premium value of Harumanis Mango. Physically and visually the affected fruit does not show any attributes that indicates the presence of IFR on any part of the fruit until it has been cut open. This paper investigates the feasibility of a non-destructive method to screen the Harumanis mango from IFR using near-infra red light and artificial neural network. A common NIR light emitting diodes of 1000nm wavelength was used as the light source to emit NIR light while a photodiode was used to measure the intensity of the reflected NIR light from Harumanis mango. Early detection of IFR were done manually by local expert using acoustic method by flicking fingers to detect any abnormality inside the fruit. Sample data on NIR Spectroscopy reflectance results of 120 samples were used to classify the presence of IFR using neural network. Mean value of NIR reflectance of RBG for Harumanis mango with an incidence of Insidious Fruit Rot are R= 0.651, G= 0.465 and B=0.458, while without IFR are R = 0.211, G=0.15 and B=0.146. Using MATLAB's neural network training tool, a training set regression was obtained with an accuracy value of 0.9805 for prediction of IFR, thus this value is very high in accuracy.
      48  9
  • Publication
    Development of Harumanis Mango Insidious Fruit Rot (IFR) Detection by Utilising Vibration-Based Sensors and PCA with Random Forest
    ( 2023-01-01)
    Salleh N.M.
    ;
    Abu Hassan Abdullah
    ;
    Sukhairi Sudin
    ;
    Noor Shazliza Zakaria
    Utilising single or multiple modalities systems, non-destructive techniques have been used to assess and determine the quality of mango (magnifera indica L.). It is challenging to anticipate and varies by cultivar at what harvest maturity stage will result in the optimum postharvest quality. Insidious Fruit Rot (IFR) is a disease that affects mangoes. When infected with Insidious Fruit Rot (IFR), the mango variety Harumanis does not exhibit exterior mutilation at the time of harvest or during the mature stage. However, a lack of density in the sinus area can occasionally be detected. Traditional ways of locating the diseases or pests living in the mango are useless for the commercialization of the product. This research presents the investigation done on IFR infection detection using piezoelectric vibration sensors and electret microphones. Data derived by the sensors were processed using the PCA and Random Forest methods to determine the non-IFR and the mango afflicted with IFR. The proposed approach achieved correct classification and is expected to be useful for planters in detecting IFR correctly before Harumanis mangoes were marketed.
      2  22
  • Publication
    Integration of asset tracking system through trilateration method as detection mechanism
    ( 2019)
    M A Fadzilla
    ;
    Shahriman Abu Bakar
    ;
    Azizi Harun
    ;
    Mohd Sani Mohamad Hashim
    ;
    Zuradzman Mohamad Razlan
    ;
    Wan Khairunizam Wan Ahmad
    ;
    Z. Ibrahim
    ;
    Abu Hassan Abdullah
    ;
    J.S.C Turner
    ;
    K.A.A Kassim
    ;
    M.S.A Khalid
    ;
    Z. Jawi
    ;
    M.H.M Isa
    ;
    Rizalafande Che Ismail
    Demands for localization system has been growing rapidly in the last several years both for an outdoor and indoor area. In conjunction with this, the capability and reliability of this system to precisely locate and track objects of interest for the indoor area has catered researchers and study on how to do so. One of the major ideas on making it more advance is by incorporating the use of wireless devices into the system. There are numbers of issues that could interrupt the efficiency and success of the system. One of the main problems is the signal loss mainly caused by the attenuation of the signal as they propagate through from the transmitter to the receiver. These attenuations are mostly due to the surface types the signal are traveling on and the objects that are in the Line of Sight in between the transmitter and receiver. In order to ensure the most reliable and efficient wireless connection between transmitter and receiver, a propagation study on the signal is needed for us to analyze and find the best way to trade off the signal attenuation based on the environment surrounding the system. By doing so, a thorough system that has models that can work efficiently even if we are to consider the attenuation factors. The system consists of nodes installed inside the research institute that acts as both transmitter and receivers. The transmitter and receiver will then process the signal that will then determine their location. The receiver is connected to the laptop in order to get a real-time reading so that we will be able to locate the transmitter. A networked of nodes are installed inside the research institute for experiment and the layout of the research is conferred for future references. Data from the experiment are then analyzed and a model for the signal propagation alongside the research institute is created. This model will be able to apprehend the signal attenuation despite the surrounding environment such as furniture and walls. A completed asset tracking system with models of signal attenuation will be built in the future for a more efficient signal transmission.
      35  2
  • Publication
    Development of Cloud-based Electronic Nose for University Laboratories Air Monitoring
    ( 2020-12-18)
    Abu Hassan Abdullah
    ;
    Muhammad Aizat Abu Bakar
    ;
    Saad F.S.A.
    ;
    Sukhairi Sudin
    ;
    Zahari Awang Ahmad
    ;
    Ismail K.A.
    ;
    Mohamed Elshaikh Elobaid Said Ahmed
    Indoor air in area such as house, shopping complex, hospital, university, office and hotel should be monitor for human safety and wellbeing. These closed areas are prone to harmful air pollutants i.e. allergens, smoke, mold, particles, radon and hazardous gas. Laboratories in university are special room in which workers (student, technician, teaching/research assistants, researcher and lecturer) conduct their works and experiments. These activities and the environment will generate air pollutants which concentration depending on their parameters. Anyone in the environment that exposure to these pollutants may have safety and health issue. This paper propose a study of development of a cloud-based electronic nose system for university laboratories air monitoring. The system consists of five dsPIC33-based electronic nose (e-nose) as node which measure main indoor air pollutants along with two thermal comfort variables, i.e. temperature and relative humidity. The nodes are placed at five different laboratories for acquiring air pollutants data in real time. The data will be sent to a web server and the cloud-based system will process, analyse and display by a website in real time. The system will monitor the laboratories main air pollutants and thermal comfort by forecast the contaminants concentration and dispersion in the area. In case of air hazard safety (e.g., gas spills detection and pollution monitoring), the system will alert the security by activate an alarm and through e-mail. The website will display the Air Pollution Index (API) of the area in real-time. Results show that the system performance is good and can be used to monitor the air pollution in the university laboratories.
      8  34
  • Publication
    Defects Detection Algorithm of Harumanis Mango for Quality Assessment Using Colour Features Extraction
    ( 2021-12-01)
    Mohd Nazri Abu Bakar
    ;
    Abu Hassan Abdullah
    ;
    Rahim N.A.
    ;
    Haniza Yazid
    ;
    Zakaria N.S.
    ;
    Omar S.
    ;
    Nik W.M.F.W.
    ;
    Bakar N.A.
    ;
    Sulaiman S.F.
    ;
    Ahmad M.I.
    ;
    Ahmad K.
    ;
    Maliki N.M.
    ;
    Romle S.R.
    Visual defects detection is one of the main problems in the post-harvest processing caused a major production and economic losses in agricultural industry. Manual fruits detection become easy when it is done in small amount, but the result is not consistent which will generate issue in fruit grading. A new fruit quality assessment system is necessary in order to increase the accuracy of classification, more consistencies, efficient and cost effective that would enable the industry to grow accordingly. In this paper, a method based on colour feature extraction for the quality assessment of Harumanis mango is proposed and experimentally validated. This method, including image background removal, defects segmentation and recognition and finally quality classification using Support Vector Machine (SVM) was developed. The results show that the experimental hardware system is practical and feasible, and that the proposed algorithm of defects detection is effective.
      28  2