Mohd Aminudin Jamlos
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Preferred name
Mohd Aminudin Jamlos
Official Name
Mohd Aminudin , Jamlos
Alternative Name
Aminuddin Jamlos, Mohd
Jamlos, M. A.
Jamlos, Mohd Aminuddin
Jamlos, Mohd A.
Jamlos, Mohd
Main Affiliation
Scopus Author ID
36010739800
57210119953
Researcher ID
AGU-7505-2022

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  • Publication
    ShareFood:CareHood: An educational mobile application for awareness on food wastage
    ( 2023-06-12)
    Arumugam S.
    ;
    Syed Zulkarnain Syed Idrus
    ;
    Ummi Naiemah Saraih
    ;
    Wahab M.H.A.
    ;
    Noormaizatul Akmar Ishak
    ;
    Wan Azani Wan Mustafa
    ;
    Mohd Aminudin Jamlos
    Approximately one-third of all food produced for human consumption is lost or wasted and the rate of food loss is continuously increasing. This circumstance has resulted in a significant increase in carbon footprint and environmental issues. Lack of awareness has been one of the reasons that caused food wastage issue. The main objectives of this research is 1) to develop a mobile application on food wastage; 2) to create awareness on food wastage issue by using ShareFood:CareHood mobile application; and 3) to conduct usability test on ShareFood:CareHood mobile application in terms of ease of use, user interface and functionality. This paper presents the development of ShareFood:CareHood mobile application, which has the purpose of creating awareness on food wastage issue among the users and at the same time gives the users a chance to play their in reducing food wastage by providing food sharing functions. The outcome of this study is provides optimistic results.
  • Publication
    Ganoderma boninense classification based on near-infrared spectral data using machine learning techniques
    ( 2023-01-15)
    Mohd Hilmi Tan M.I.S.
    ;
    Jamlos M.F.
    ;
    Omar A.F.
    ;
    Kamarulzaman Kamarudin
    ;
    Mohd Aminudin Jamlos
    Ganoderma boninense (G. boninense) infection reduces the productivity of oil palms and causes a severe threat to the palm oil industry. Early detection of G. boninense is vital since there is no effective treatment to stop the continuing spread of the disease unless ergosterol, a biomarker of G. boninense can be detected. There is yet a non-destructive and in-situ technique explored to detect ergosterol. Capability of NIR to detect few biomarkers such as mycotoxin and zearalenone (ZEN) has been proven to pave the way an effort to explore NIR's sensitivity towards detecting ergosterol, as discussed in this paper. A compact hand-held NIR with a measurement range of 900–1700 nm is utilized by scanning the leaves of three oil palm seedlings inoculated with G. boninense while the other three were non-inoculated from 16-weeks-old to 32-weeks-old. Significant changes of spectral reflectance have been notified occur at the wavelength of ∼1450 nm which reflectance of infected sample is higher 0.2–0.4 than healthy sample which 0.1–0.19. The diminishing of the spectral curve at approximately 1450 nm is strongly suspected to happened due to the loss of water content from the leaves since G. boninense attacks the roots and causes the disruption of water supply to the other part of plant. However, a few overlapped NIRs' spectral data between healthy and infected samples require for further validation which chemometric and machine learning (ML) classification technique are chosen. It is found the spectra of healthy samples are scattered on the negative sides of PC-1 while infected samples tend to be on a positive side with large loading coefficients marked significant discriminatory effect on healthy and infected samples at the wavelength of 1310 and 1452 nm. A PLS regression is used on NIR spectra to implement the prediction of ergosterol concentration which shows good corelation of R = 0.861 between the ergosterol concentration and oil palm NIR spectra. Four different ML algorithms are tested for prediction of G. boninense infection: K-Nearest Neighbour (kNN), Naïve Bayes (NB), Support Vector Machine (SVM) and Decision Tree (DT) are tested which depicted DT algorithm achieves a satisfactory overall performance with high accuracy up to 93.1% and F1-score of 92.6% compared to other algorithms. High accuracy shows the capability of the classification model to correctly predict the G. boninense detection while high F1-score indicates that the classification is able to validate the detection of G. boninense correctly with low misclassification rate. The result represents a significant step in the development of a non-destructive and in-situ detection system which validated by both chemometric and machine learning (ML) classification techniques.
  • Publication
    Detection of screw implant on x-ray images using morphology technique
    ( 2020-12-15)
    Salleh N.M.
    ;
    Wan Azani Wan Mustafa
    ;
    Mohd Aminudin Jamlos
    Bones make up the skeleton of the body by attachment points for muscles, which allows human to run, jump, and do actions. It also protects organs from potential damages. Fracture is a medical term for a broken bone when bone has an outside force exerted upon it, there is possibility that the bone cannot withstand the amount of force and break it. These fractures can treat by implanting internal fixations at the fractures such as screw and plates. To diagnose the fractures and follow up the treatment, x-ray taken at the fractured area. X-ray image is one of the oldest photographic films that is mostly used in medical diagnosis and treatment. X-ray image is a very useful modality for the physicians and doctors to determine and analyse the bone fracture, which is an important symptom used for diagnosis, therefore x-ray produce only medium quality image, which will normally affect the information of the image. This paper aims to use a new method to detect the screw implants on human bone by using image binarization technique. Image binarization is the process of separating pixel values into a couple of groups, black as foreground and white as background. Image binarization is an important step in image thresholding. The main objective is to find a new method of image thresholding to of object detection. The method is by developing a new algorithm of image thresholding by making the already exist algorithm as references. The resulting method was analysis based on accuracy, sensitivity, and specificity.
  • Publication
    Line Detection and Monitoring System on Woodball Sport
    ( 2021-06-15)
    Chandrasegaran J.
    ;
    Wan Azani Wan Mustafa
    ;
    Umoruddin N.A.
    ;
    Mahyudin I.S.
    ;
    Mohd Aminudin Jamlos
    ;
    Syed Zulkarnain Syed Idrus
    ;
    Idris A.
    In most sports today, the decisions taken by referees are supported by the use of electronic technology. The detection and monitoring system of the woodball lines serves the same function, helping the referee to take decisions and modernise woodball sports. The modern sport of wood balls depends entirely on out decisions. The line detection technology helps inform the judge whether the ball is OB (out of Bounds), while the monitoring system notifies players, judges, and the crowd whether or not the gating is effective. But the referee's manual assistance is always necessary to start the game after a good gating, since the player cannot touch the wood ball the whole time. Finally, the percentage of precision and error was achieved.
  • Publication
    A triangular MIMO array antenna with a double negative metamaterial superstrate to enhance bandwidth and gain
    ( 2020-08-01)
    Ojo R.
    ;
    Jamlos M.F.
    ;
    Soh Ping Jack
    ;
    Mohd Aminudin Jamlos
    ;
    Norfatihah Bahari
    ;
    Lee Y.S.
    ;
    Al-Bawri S.S.
    ;
    Abdul Karim M.S.
    ;
    Khairi K.A.
    Multiple-input-multiple-output (MIMO) array antenna integrated with the double negative metamaterial superstrate is presented. The triangular metamaterial unit cell is designed by combining two triangular elements positioned in complementary on the same plane at different sizes. Such design with more gaps is used to excite rooms for more capacitance effects to shift the resonance frequency thus enlarging the bandwidth of the MIMO antenna. The unit cell is arranged in 7 × 7 periodic array created a superstrate metamaterial plane where the Cstray exists in parallel between the two consecutive cells. It is found that the existence of Cstray and gaps for each unit cells significantly influenced the bandwidth of the MIMO antenna. The higher value of the capacitance will lead to the negativity of permittivity. The superstrate plane is then located on top of the 4 × 2 MIMO with a gap of 5 mm. The integration resulted in improving the bandwidth to 12.45% (5.65-6.4GHz) compared to only 3.49% bandwidth (5.91-6.12GHz) of the MIMO antenna itself. Moreover, the negative permeability characteristic is created by a strong magnetic field between the complementary unit cells to have 14.05-dBi peak gain. Besides that, the proposed antenna managed to minimize the mutual coupling and improve the mean effective gain, envelope correlation coefficient, and multiplexing efficiency.
  • Publication
    Zero Index Metamaterial of Simulated Split Ring Resonator Element
    ( 2022-01-01)
    Mohd Aminudin Jamlos
    ;
    Othman N.A.
    ;
    Wan Azani Wan Mustafa
    ;
    Hasliza A Rahim @ Samsuddin
    ;
    Alfilh R.H.C.
    ;
    Mohamad Nur Khairul Hafizi Rohani
    Split Ring Resonator of Zero Index metamaterial element has been proposed. The Split Ring Resonator consists of four loops; a more modest loop inside a bigger one, with openings, consolidated into each loop at the far edges, and an expansion of the rectangular loop to realize the gap (split) which permits control of the capacitance. The split ring is designed and simulated using sophisticated simulation software to have accurate simulation results. Two waveguide ports of terminals have been used within the assigned unit cell boundary for the simulated purpose. A parametric study has taken place for the width and length of the split ring resonator to find the optimized design to have zero index at the desired frequency of 2.7 GHz. The optimized dimensions of the split ring resonator are 7.29 mm and 6.0 mm for width and length respectively. The split ring resonator successfully recorded zero index (phase) at the desired frequency of 2.7 GHz for low-frequency applications specifically for GHz ranges.
  • Publication
    IR 4.0: Smart Farming Monitoring System
    ( 2023-01-01)
    Nasir M.F.
    ;
    Mohd Aminudin Jamlos
    ;
    Wan Azani Wan Mustafa
    ;
    Mohamad Nur Khairul Hafizi Rohani
    ;
    Muhammad Zaid Aihsan
    ;
    Habelalmateen M.I.
    ;
    Ramadan G.M.
    The Internet of Things is the current and future of every field that effects everyone's life by making everything smart. The development of Smart Farming Monitoring with the use of the Internet of Things, changes conventional farming methods by not only making them optimal but also effective for farmers and reducing crop wastage. Therefore, Smart Farm Monitoring of IR 4.0 Implementation is designed to provide a system for monitoring environmental factors in farming in real time. This product will help farmers by creating an easy-to-use user view so users can view data. By implementing various types of sensors and applications such as Raspberry Pi 4B as its main controller, Temperature & Humidity sensor (DHT22), Capacitive Soil Moisture sensor, MQ135 sensor, Light Intensity sensor, ThingSpeak and ThingView, farmers will can monitor parameters and this data will be sent to the database for real-time display and storage purposes. The project is expected to create a smart environment conducive to agriculture and reduce labour costs and water wastage and increase productivity and efficiency. The system is achieved, as the intelligent monitoring of agriculture allows real-time monitoring with less time.
  • Publication
    The Development of an Interactive Animation to Prevent Social Media Fraud
    ( 2020-06-17)
    Lun C.W.
    ;
    Syed Zulkarnain Syed Idrus
    ;
    Wan Nor Ashiqin Wan Ali
    ;
    Ishak N.A.
    ;
    Wan Azani Wan Mustafa
    ;
    Mohd Aminudin Jamlos
    ;
    Wahab M.H.A.
    Technology is the creation, invention, methods or systems of something new that has the purpose to overcome human's limitation, so that the creation can help human to complete the task that they cannot do. However, the world is getting advanced day-by-day, and so do the online frauds, where it is getting more types due to the ease of these technologies. People would use these advanced technologies to scam others, especially through social media. Thus, the number of online scam seems to be rising, and it is an appropriate action that someone does to bring benefits only for themselves. This paper is about the development of an interactive animation to increase the awareness of social media frauds among people and ways to prevent it. Subsequently, we created an animation that can raise the awareness of social media fraud among people, and hence they can also learn effective ways to prevent social media fraud from happening.
  • Publication
    Simulation Study of Metamaterial Effect towards Ultra Wide Band Antenna
    ( 2020-09-21)
    Amirah Othman N.
    ;
    Mohd Aminudin Jamlos
    ;
    Wan Azani Wan Mustafa
    ;
    Syed Zulkarnain Syed Idrus
    In this paper, the design of a metamaterial ultra-wideband (UWB) antenna with a goal towards application in microwave imaging systems for detecting unwanted cells in human tissue, such as in cases of breast cancer, heart failure and brain stroke detection is proposed. The metamaterial unit cell is constructed using circular split ring resonator (CSRR) technique and wire, to attain a design layout that simultaneously exhibits both a negative magnetic permeability and a negative electrical permittivity and attached as superstrate in front of the UWB antenna. This design results in an astonishing negative refractive index that enables amplification of the radiated power of this reported antenna, and therefore, high antenna performance. A Rogers (RT5880) substrate material is used to design and print this reported antenna, and has the following characteristics: thickness of 0.51 mm, relative permeability of one, relative permittivity of 2.70 and loss tangent of 0.02. The metamaterial antenna is design to be operated at frequency between 300MHz to 30GHz which is suitable for biomedical application such as Microwave Imaging. The overall metamaterial antenna size is 90 mm 50 mm 0.51 mm. The design and simulation has been carried out using Computer Simulation Technology Microwave Studio (CST MWS).
  • Publication
    IoT-based Machine Learning Comparative Models of Stream Water Parameters Forecasting for Freshwater Lobster
    ( 2024-05-01)
    Bakhit A.A.
    ;
    Sabli N.S.M.
    ;
    Jamlos M.F.
    ;
    Mohd Aminudin Jamlos
    ;
    Ramli N.H.
    ;
    Nordin M.A.H.
    ;
    Alhaj N.A.
    ;
    Ali E.
    Water quality parameters such as dissolved oxygen, pH, and mineral content are important factors for aquaculture. Predictive analytics can predict water conditions in aquaculture and significantly reduce the mortality probability of aquaculture products. This paper applied stream predictive analytics to the freshwater lobster farming dataset where its real-time data supplied by End Node Unit (ENU) which integrated with dissolved oxygen (DO), potential hydrogen (pH), electrical conductivity (EC), and total dissolved solids (TDS). The real-time data of ENU in Structured Query Language (SQL) is normally displayed for remote monitoring and the analytics will only be done after in different processing platform called batch analytics. Instead of batch, this paper demonstrates capability of stream analytics where the real-time data query from ENU streaming through Structured Query Language (SQL) right into R Studio and Autoregressive Integrated Moving Average (ARIMA) predictions executed on the query table simultaneously on the same processing platform. Previously, ARIMA, Neural Network Autoregressive (NNETAR), and Naïve Bayes, were run and evaluated in R Studio to identify the best algorithm for stream analytics. Prediction procedure in R studio start with importing real-time data stored in SQL database and stream into R Studio using command of “dbGetQuery(con,sql)”. These three models evaluated the performance of freshwater lobster water conditions, dissolved oxygen (DO), potential hydrogen (pH), electrical conductivity (EC), and total dissolved solids (TDS). The data was collected for six months, and 70% was used as training data and 30% as test data. Compared to NNETAR and Naïve Bayes, ARIMA fits the entire data set well for 7 days; the ARIMA model exhibited lower absolute errors for pH and electrical conductivity, with errors ranging from 0.04 to 1.7 across days, while the NNETAR model had generally lower errors for TDS, with errors ranging from 0.3 to 0.7; however, the Naïve Bayes model's performance varied, with the lowest error for DO on day (5) 0.15 but higher errors for other parameters and days, including the highest error for electrical conductivity on day (6) 6.2. In conclusion, the average absolute errors for DO, pH, EC, and TDS are 0.163, 0.064, 0.705, and 0.498, respectively. Our findings underscore the efficacy of ARIMA for comprehensive water quality via stream prediction while highlighting the nuanced strengths and weaknesses of each model in forecasting specific parameters. This study contributes to the aquaculture literature by providing a nuanced comparative analysis of predictive models tailored to freshwater lobster farming, emphasizing the imperative role of stream predictive modelling. It enables real-time monitoring of water quality parameters, ensuring prompt interventions to maintain optimal conditions, thereby minimizing risks, enhancing aquaculture productivity, and ultimately contributing to sustainable and efficient freshwater lobster farming practices.