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
    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
    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
    Compact bidirectional circularly polarized dedicated short range communication antenna for on-board unit vehicle-to-everything applications
    ( 2020-05-01)
    Rahman N.A.A.
    ;
    Mohd Aminudin Jamlos
    ;
    Jamlos M.F.
    ;
    Soh Ping Jack
    ;
    Norfatihah Bahari
    ;
    Hossain T.M.
    This article presents a newly circularly polarized (CP) antenna for V2X's dedicated short range communications applications. Its CP characteristic is enabled by a 70 Ω sequential phase feeding network and sequential rotation technique designed on top of the substrate. It has features of ≈90° phase difference in sequence between ports of S21 = 2.4°, S31 = −87°, S41 = −180°, and S51 = −276°, resulting in a 2.19 dB axial ratio centered at 5.9 GHz. The length of the SP feeding network to each ports designed in the different form of meander lines are the key to control the generated phase at the center frequency It also contributes to the smaller final size of 0.59λ × 0.59λ. The proposed antenna operated from 5.850 to 5.925 GHz with a gain between 4 and 6 dBi. The gains are radiated in bidirectional mode due to the presence of the complimentary dipoles located on the opposite side of the substrate. These features indicate the suitability of the proposed antenna in compliance to the ITS-G5 OBU V2X standard.
  • Publication
    Reduced Graphene Oxide UWB Array Sensor: High Performance for Brain Tumor Imaging and Detection
    ( 2023-01-01)
    Mohd Aminudin Jamlos
    ;
    Jamlos M.F.
    ;
    Wan Azani Wan Mustafa
    ;
    Othman N.A.
    ;
    Mohamad Nur Khairul Hafizi Rohani
    ;
    Syahrul Affandi Saidi
    ;
    Mohd Sharizan Md Sarip
    ;
    Mohd Al-Hafiz Mohd Nawi
    A low cost, with high performance, reduced graphene oxide (RGO) Ultra-wide Band (UWB) array sensor is presented to be applied with a technique of confocal radar-based microwave imaging to recognize a tumor in a human brain. RGO is used to form its patches on a Taconic substrate. The sensor functioned in a range of 1.2 to 10.8 GHz under UWB frequency. The sensor demonstrates high gain of 5.2 to 14.5 dB, with the small size of 90 mm × 45 mm2, which can be easily integrated into microwave imaging systems and allow the best functionality. Moreover, the novel UWB RGO array sensor is established as a detector with a phantom of the human head. The layers’ structure represents liquid-imitating tissues that consist of skin, fat, skull, and brain. The sensor will scan nine different points to cover the whole one-sided head phantom to obtain equally distributed reflected signals under two different situations, namely the existence and absence of the tumor. In order to accurately detect the tumor by producing sharper and clearer microwave image, the Matrix Laboratory software is used to improve the microwave imaging algorithm (delay and sum) including summing the imaging algorithm and recording the scattering parameters. The existence of a tumor will produce images with an error that is lower than 2 cm.
  • Publication
    Bandwidth enhancement of five-port reflectometer-based ENG DSRR metamaterial for microwave imaging application
    ( 2020-03-01)
    Hossain T.M.
    ;
    Jamlos M.F.
    ;
    Mohd Aminudin Jamlos
    ;
    Dzaharudin F.
    ;
    Ismail M.Y.
    ;
    Al-Bawri S.S.
    ;
    Sugumaran S.
    ;
    Midhat Nabil Ahmad Salimi
    A five-Port Reflectometer (FPR) with the integration of ultra-wideband (UWB) Epsilon Negative (ENG) Double Split Ring Resonator (DSRR) metamaterial array is introduced in this paper for microwave imaging (MWI) application. The designed DSRR consists of two concentric rings with a split in each which are spatially rotated by 180°, formed an inverted structure to exhibit a wide negative epsilon bandwidth of 187 % (from 0.5 GHz to 15 GHz). The FPR is designed using a ring junction topology and semi-circularly curved inter-port transmission lines (TLs) which are placed between five equally spaced ports. Localizing the DSRR metamaterial in a periodic array of 5 × 4 at the ground plane of FPR lead to 79.79 % fractional bandwidth and reflection coefficient within the operating frequencies of 0.991 GHz–2.2576 GHz. Equivalent circuit model has been alluded with an intricate description of different array configurations of the metamaterial unit cell. Comparison of EM simulation and circuit simulation has been performed to validate the equivalent circuit model. It is found that the existence of stray capacitance, Cstray which is represented by the DSRR configurations, significantly influenced the resonant frequency and bandwidth of FPR. Measured results of the proposed design suits well with the simulations and prove higher efficacious applicability of the proposed design for microwave imaging application. A comparison of the reconstructed image also proves its suitability for the microwave imaging application.