Now showing 1 - 10 of 22
  • Publication
    Potential of Near-Infrared (NIR) spectroscopy technique for early detection of Insidious Fruit Rot (IFR) disease in Harumanis mango
    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.
  • Publication
    Improved classification of orthosiphon stamineus by data fusion of electronic nose and tongue sensors
    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
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    Marni Azira Markom
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    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.
  • Publication
    Aquaculture monitoring system using multi-layer perceptron neural network and adaptive neuro fuzzy inference system
    The water quality is the most important parameter for aquatic species health and growth. The condition is very critical and is essential to monitor continuously. Poor water quality will affect health, growth and ability of the animal to survive. These also affected their harvesting yields based on the amount and size of the animal. The main water parameters such dissolved oxygen (DO), pH, temperature, salinity and turbidity are monitored and control for good water quality. The data were acquired by the developed instrument and send wirelessly through GPRS/GSM module to cloud-based database. The data were retrieved and the water quality is predicted using fuzzy logic and multi-layer perceptron. MATLAB software was used for the model which is developed based on Mamdani fuzzy interface system. The membership functions of fuzzy were generated, as well as the simulation and analysis of the water quality system. Results show that the performance of fuzzy method can improve system performance in monitoring the water quality. This system also provides alert signals to farmers based on specific limit value for the water quality parameters. This will help the breeders to make certain adjustment to ensure suitable water quality for the aquaculture system.
  • Publication
    Effect of roadways plantation on signal propagation analysis in connected autonomous vehicle communication
    ( 2019)
    J S C Turner
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    Zunaidi Ibrahim
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    M A Fadzilla
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    K A A Kassim
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    M S A Khalid
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    Z Jawi
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    M H M Isa
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    S A Z Murad
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    At present, the development of autonomous vehicle has altered the outlook of modern transportation worldwide. The state-of-the-art vehicular communication for transportation system is advancing, especially in vehicle to infrastructure (V2I) communication. An effective communication between vehicle and infrastructure has become a significant part of autonomous transportation criteria. The necessity for high quality of service communication inspire for good planning and preparation in communication process. Per se, this paper proposes vegetation attenuation models for advance planning of communication process between vehicle to infrastructure, defined mainly by plants, trees and vegetation along the roadways in Malaysia. The channel measurement performed in Universiti Malaysia Perlis test-bed having large tall trees and low shrubs along the routes resulted in several interesting results which would shape the planning of CAV communication. It is observed that communication close to low plantation or shrub requires high power consumption as the range is significantly reduced. It is also learned that certain types of plantations allows for different level of signal attenuation depending on the antenna heights. The research also found out that the attenuation profile follows strictly the log normal distribution and as such certain planning could be made to reshape the communication process to cater for this.
  • Publication
    Defects Detection Algorithm of Harumanis Mango for Quality Assessment Using Colour Features Extraction
    ( 2021-12-01) ; ;
    Rahim N.A.
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    Zakaria N.S.
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    Omar S.
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    Nik W.M.F.W.
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    Bakar N.A.
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    Sulaiman S.F.
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    Ahmad M.I.
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    Ahmad K.
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    Maliki N.M.
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    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.
  • Publication
    Human breathing assessment using Electromyography signal of respiratory muscles
    ( 2017-04-05) ; ;
    Zulkifli Zakaria
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    Sathees Kumar Nataraj
    Breathing is one of the human physiological activities that catch the interest of researchers especially in the area of medical diagnosis and human physiological performance. Mostly, the measurement and data are in form of pressure and volume variables of air intake and outflow. However, using airflow pressure and volume require installment of certain sensor usually on subject's mouth which could discomfort the subject. Another possible method for assessing the breathing pattern is through human respiratory muscles, which are via electromyography signal. In this paper, experiment is done on acquiring the electromyography signal from four respiratory muscles namely sternocleidomastoid, scalene, intercostal muscle and diaphragm with subjects performing four different breathing tasks. Analysis-of-variance test has been done on the Electromyography (EMG) feature data of the four muscles for the four breathing tasks. Results of ANOVA analysis, show that the p-values has a significant different in the four breathing tasks for each muscle.
  • Publication
    Development of aquaculture water quality real-time monitoring using multi-sensory system and internet of things
    Water quality is an important parameter for the health and growth of aquatic species in aquaculture farming system. The threshold values of the water main parameters should be monitored continuously. Contaminated aquaculture water will affect the health, growth and ability of animals to survive. In addition, it will also affect the harvesting yields based on the number and size of the animals. To overcome this problem, the main water parameters, namely temperature, pH, Dissolved Oxygen and Electrical Conductivity are monitored in real-time using a multi-sensory system and the internet of things. Data is acquired by a developed instrument and transmitted wirelessly via a GPRS/GSM module to a web server database. The data obtained are analyzed and monitored through the website and in real-time. Therefore, corrective action could be taken immediately for contaminated water, indicated by water parameters out of range. The system also provides an early signal to farmers based on a specific range of water quality parameters values. This will help farmers make adjustments to ensure appropriate water quality for the aquaculture system.
  • Publication
    Cloud-based System for University Laboratories Air Monitoring
    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.
  • Publication
    Integration of asset tracking system through trilateration method as detection mechanism
    ( 2019)
    M A Fadzilla
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    Z. Ibrahim
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    J.S.C Turner
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    K.A.A Kassim
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    M.S.A Khalid
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    Z. Jawi
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    M.H.M Isa
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    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.