Norshamsuri Ali @ Hasim
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Norshamsuri Ali @ Hasim
Official Name
Norshamsuri, Ali
Translated Name
Ali
Alternative Name
Ali, N.
Hashim, N. B.A.
Main Affiliation
Scopus Author ID
58768841500
Researcher ID
L-8205-2016

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  • Publication
    Prediction model for spectroscopy using python programming
    ( 2021-12)
    A A M Ismail
    ;
    Norshamsuri Ali @ Hasim
    ;
    Mohd Shafiq Amirul
    ;
    Rosdisham Endut
    ;
    Syed Alwee Aljunid Syed Junid
    This paper is motivated by searching for the perfect pattern for the spectroscopy spectra using artificial neural networks (ANN) using python programming coding. The pattern from the spectroscopy is based on the absorption and emission of light and other radiation by materials in relation to the wavelength dependence of these processes. Spectral equipment such as spectrometers, spectral analysers, spectrographs, or spectrophotometers is utilised to determine spectrum values. The problem in this spectroscopy is to identify the sample or analyte, which can be solved by a prediction model for spectroscopy using Python. These problems occur when finding the best algorithm of pre-processing techniques that can predict any model accurately into an understandable format for prediction models. Various types of pre-processing techniques have been used, such as Multiplicative Scatter Correction (MSC), Inverse MSC, Extended MSC (EMSC), Extended Inverse MSC, de-trending, Standard Normal Variate (SNV) and normalisation in order to get a better r2 value. In this project, we find the r2 and the root mean square error (RMSE) to evaluate the prediction values and the actual values. First, choosing pre-processing techniques and then finding the best statistical method for constructing predictive models that produce high accuracy. We used ANN in this project as a prediction model. Based on the results, we managed to achieve our objective, which is that the prediction model has more than 90% of accuracy. Furthermore, the results show that our prediction model has 1.0 accuracy at 100 Epoch with a 0.3 learning rate. Finally, we can conclude that our prediction model can be used to predict the spectroscopy-based data format.
  • Publication
    Enrichment of wireless data transmission based on visible light communication for triple play service application
    ( 2020-01-08)
    Mat N.R.N.
    ;
    Mohd Rashidi Che Beson
    ;
    Syed Alwee Aljunid Syed Junid
    ;
    Rosdisham Endut
    ;
    Norshamsuri Ali @ Hasim
    In this paper, the performance of the LiFi-IoT based on VLC for point-to-point (P2P) topology has been investigated. LiFi-IoT offers a possibility to deploy high speed (∼1 Gbps) wireless data for future network access optical wireless communication (UOWC). Result shows that, the LED threshold current of 16 mA corresponds to a voltage of 0.6 V. At the injection current of 30 mA, the LED has an output optical power of 18 mW for data transmission to be carried out under the optical communication environment based on Line of Sight (LoS).
  • Publication
    Prediction of soil macronutrient (nitrate and phosphorus) using near-infrared (NIR) spectroscopy and machine learning
    ( 2020-01-08)
    Laili A.R.
    ;
    Rosdisham Endut
    ;
    Norshamsuri Ali @ Hasim
    ;
    Laili M.H.
    ;
    Amirul M.S.
    ;
    Syed Alwee Aljunid Syed Junid
    ;
    Mohd Rashidi Che Beson
    ;
    Ismail M.N.M.
    Determination of basic soil macronutrients such as nitrogen (N), phosphorus (P) and potassium (K) that dissolve from organic matter (OM) prior to the plantation of fruit and vegetable corps is one of the important process of soil preparation towards precision farming. In this paper comparative analysis is performed for detection algorithm on OM, (N) and (P) sample using near infrared spectroscopy (NIRS) spectrometer in reflective mode with an effective range of 900nm to 1700nm. In pre-processing we execute data dimension reduction by combining multiple feature selection such as data normalization, permutation feature importance, principle component analysis, fisher linear discriminant and filter-based feature selection. Pre-processing able to reduce 50% data dimension. For prediction model development we combine with multiple classification algorithm such as multiclass decision jungle, decision forest, logistic regression and neural network to come out with highest accuracy of N and P detection. We conclude that near infrared spectroscopy combines with feature selection and multiclass classification able to determine nitrogen and phosphorus.
  • Publication
    Estimation of Harumanis (Mangifera indica L.) Sweetness using Near-Infrared (NIR) Spectroscopy
    ( 2020-03-20)
    Sabri, Mohd Shafiq Amirul
    ;
    Rosdisham Endut
    ;
    Mohd Rashidi Che Beson
    ;
    Syed Alwee Aljunid Syed Junid
    ;
    Norshamsuri Ali @ Hasim
    ;
    Laili M.H.
    ;
    Laili A.R.
    ;
    Ismail M.N.M.
    Harumanis mango quality demanded by consumers is depending on the sweetness level of the fruit. The sweetness is evaluated by brix percentage using refractometer as a representative factor correlated with near-infrared (NIR) spectroscopy spectral absorbance. NIR spectroscopy method of sampling have been tested to overcome the time consuming, complex chemical analysis more importantly invasive sampling methods in order to determine the sugar content in mangoes. Spectral absorbance data from range 941 nm to 1685 nm of mango skin is correlated with Brix reading then tested through five pre-processing techniques. Data calibration and prediction of both data is evaluated using Partial Least Square Regression (PLSR) model. In the final analysis, Unit vector normalization (UVN) technique has achieved as a best pre-processing technique for predicting results, with the coefficient of determination (R2) values of 0.9836 and root mean square error (RMSE) values of 0.3131. Overall, the correlation of NIRS absorbance data and Brix data can be obtained using PLSR model with UVN pre-processing technique. Henceforth, we can conclude that the NIRS method of sampling can be used to identify sugar content in Harumanis mango by using time saving, non-invasive and less laborious method of sampling.
  • Publication
    Effect of nanoshell geometries, sizes, and quantum emitter parameters on the sensitivity of plasmon-exciton hybrid nanoshells for sensing application
    (Nature Research, 2023)
    Arezoo Firoozi
    ;
    Angela Amphawan
    ;
    Reza Khordad
    ;
    Ahmad Mohammadi
    ;
    Tahmineh Jalali
    ;
    Collins Okon Edet
    ;
    Norshamsuri Ali @ Hasim
    A proposed nanosensor based on hybrid nanoshells consisting of a core of metal nanoparticles and a coating of molecules is simulated by plasmon-exciton coupling in semi classical approach. We study the interaction of electromagnetic radiation with multilevel atoms in a way that takes into account both the spatial and the temporal dependence of the local fields. Our approach has a wide range of applications, from the description of pulse propagation in two-level media to the elaborate simulation of optoelectronic devices, including sensors. We have numerically solved the corresponding system of coupled Maxwell-Liouville equations using finite difference time domain (FDTD) method for different geometries. Plasmon-exciton hybrid nanoshells with different geometries are designed and simulated, which shows more sensitive to environment refractive index (RI) than nanosensor based on localized surface plasmon. The effects of nanoshell geometries, sizes, and quantum emitter parameters on the sensitivity of nanosensors to changes in the RI of the environment were investigated. It was found that the cone-like nanoshell with a silver core and quantum emitter shell had the highest sensitivity. The tapered shape of the cone like nanoshell leads to a higher density of plasmonic excitations at the tapered end of the nanoshell. Under specific conditions, two sharp, deep LSPR peaks were evident in the scattering data. These distinguishing features are valuable as signatures in nanosensors requiring fast, noninvasive response.
  • Publication
    Geometrical optimization of lithium niobate on insulator rib waveguide for quantum communication application
    (AIP Publishing, 2020)
    Nor Roshidah Yusof
    ;
    Norshamsuri Ali @ Hasim
    ;
    P. Kolenderski
    ;
    Nor Azura Malini Ahmad Hambali
    ;
    Syed Alwee Aljunid Syed Junid
    Recently, thin film Lithium niobate has been recognized as an alternative material to silicon based technology due to its capability to support a broader range for quantum communication system. With the aim to operate within single photon application, we demonstrate the mode distribution, propagation constant and effective refractive indices of the Lithium Niobate on Insulator rib waveguide which operates at both fundamental wavelength, 1550 nm and second harmonic wavelength, 775 nm, respectively by using Finite Element Method. The etched depth and width of the core was varied from 340 to 400 nm and 700 to 1400 nm, respectively with the thickness of slab is fixed at 100 nm. From the result, it shows the effective refractive index increases gradually with the increment of etched depth and width of core, respectively. At second harmonic wavelength, the effective refractive indices and propagation constant shows a significant increment compare to observation at 1550 nm with an ability to produce both fundamental mode and first order mode across the structure.
  • Publication
    Quantum information entropy of heavy mesons in the presence of a point-like defect
    (Elsevier, 2023)
    Carlos Alberto Santos Almeida
    ;
    Collins Okon Edet
    ;
    Francisco Cleiton E. Lima
    ;
    Norshamsuri Ali @ Hasim
    ;
    Muhammad Asjad
    Using Schrödinger's formalism, we investigate the quantum eigenstates of the heavy mesons trapped by a point-like defect and by Cornell's potential. One implements this defect to the model considering a spherical metric profile coupled to it. Furthermore, the Nikiforov–Uvarov method is applied to theory to study the quantum eigenstates of the heavy mesons. To calculate the quantum information entropy (QIE), one considers the wave functions that describe the charmonium and bottomonium states. To explore the QIE, we use the well-known Shannon's entropy formulated at the position and reciprocal space. The analysis of the QIE gives us relevant information about how the quantum information change with the variation of the point-like defect. Consequently, considering the Bialynicki-Birula and Mycielski (BBM) relation, we show how this defect influences the quarkonium position and momentum uncertainty measures.
  • Publication
    Comparison of the Electrical Performance of AlN and HfO2 Passivation Layer in AlGaN/GaN HEMT
    ( 2023)
    Zikri Zulkifli
    ;
    Norshamsuri Ali @ Hasim
    ;
    Shaili Falina
    ;
    Hiroshi Kawarada
    ;
    Mohamed Fauzi Packeer Mohamed
    ;
    Mohd Syamsul
    Different material thicknesses with medium and high dielectric constants impacts the performance and reliability of high electron mobility transistor devices. The effect of varying the thickness of the passivation layer on the device performance is still unclear. Two different insulator layers with a medium dielectric and a high dielectric constant, namely Aluminium Nitride and Hafnium Oxide, are used as passivation layers in AlGaN/GaN HEMT. Both material performance, which was simulated via COMSOL software by varying the thickness, and the drain current output were compared. The passivation layer thickness of 10nm at Vds=6 V and Vgs=5 V, HfO2 outperforms AlN with an output drain current of 39 mA compared to 35 mA, respectively. It was observed that HfO2 can attain a higher threshold voltage, Vth, as compared to the AlN because of the influence of its material properties that show a direct proportional relationship between Vth and the dielectric constant. Using a high dielectric constant material like HfO2, we observe the ON-voltage gradually decreases as the thickness of the passivation layer increases. Out of all the thicknesses simulated for HfO2 and AlN, 10 nm produced the highest drain current output instead of a layer thickness of 20nm.
  • Publication
    Linear and nonlinear optical properties of symmetric and asymmetric double triangular quantum dots withinside the presence of magnetic field
    (John Wiley and Sons Inc., 2024-10)
    Emre Bahadir AL
    ;
    Norshamsuri Ali @ Hasim
    ;
    Rosdisham Endut
    ;
    Syed Alwee Aljunid Syed Junid
    ;
    Norshah Rizal Ali
    ;
    Nor Roshidah Yusof
    Linear and third‐order nonlinear optical absorption coefficients and relative refractive index changes in symmetric and asymmetric double triangular quantum dots are examined theoretically. The dependence of these optical properties on the magnetic field is examined. After calculating energies and wave functions within the effective mass and parabolic band approaches, analytical expressions of linear and nonlinear optical properties are obtained using the compact density matrix approach and iterative method. Numerical calculations are presented for typical GaAs/AlGaAs material. The results show that the magnetic field causes different effects on the and transitions. Moreover, the calculated results also reveal that the resonance frequency and nonlinear contribution are different in symmetric and asymmetric structures. As a result, it is concluded that the magnetic field plays a vital and important role in the electronic and optical properties of the system and can be used to tune the inter‐subband transitions and change the corresponding optical sensitivities.
  • Publication
    Determination of probability density, position and momentum uncertainties, and information theoretic measures using a class of inversely quadratic Yukawa potential
    (Nature Research, 2025)
    Etido P. Inyang
    ;
    A. E. L. Aouami
    ;
    Norshamsuri Ali @ Hasim
    ;
    Rosdisham Endut
    ;
    N. R. Ali
    ;
    Syed Alwee Aljunid Syed Junid
    This study utilizes the Nikiforov-Uvarov method to solve the Schrödinger equation for the class of inversely quadratic Yukawa potential (CIQYP), deriving both the energy equation and the normalized wave function. Shannon entropy and Fisher information in both position and momentum spaces are analyzed for low-energy states using the wave function. The Bialynicki-Birula-Mycielski and Stam-Cramer-Rao inequalities are satisfied for the Shannon and Fisher information entropies, illustrating the complementary uncertainties inherent in position and momentum in quantum mechanics. The study underscores the interplay between position and momentum Fisher entropies, reinforcing the Heisenberg uncertainty principle, which imposes limits on the precise simultaneous measurement of conjugate variables. Eigenvalues of the CIQYP for three diatomic molecules (N₂, O₂, and NO) are obtained using their respective data, revealing that the bound state energy spectra of these diatomic molecules increase as both the principal quantum number and angular momentum quantum number rise. Expectation values were numerically determined, and the potential model simplifies to the Kratzer potential under specific boundary conditions, thereby ensuring analytical accuracy. The energy spectra of diatomic molecules such as I₂ and CO are examined, showing that for a fixed principal quantum number, the energy spectrum increases with increasing angular momentum quantum number, in very good agreement with previously obtained results using different analytical methods.