Hasliza A Rahim @ Samsuddin
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Preferred name
Hasliza A Rahim @ Samsuddin
Official Name
A Rahim @ Samsuddin, Hasliza
Alternative Name
A. Rahim, Hasliza
Rahim, Hasliza A.
Rahim Samsuddin, H. A.
Rahim, Hasliza Abdul
Rahim, Hazliza A.
Rahim, H. A.
Rahim, H.
Hasliza,
Rahim H, Abd
RahimAtSamusuddin, Hasliza A.
A Rahim, Hasliza
Rahim At Samsuddin, Hasliza A.
ARahim, H.
Rahim Samsuddin, A. Hasliza
Rahim At Samsuddin, H. A.
Rahim, Hasliza Abd
Rahim, Hasliza
Rahim At Shamsuddin, H. A.
Main Affiliation
Scopus Author ID
57202496362
Researcher ID
ABE-3328-2020

Research Output

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  • Publication
    Data-driven audiogram classifier using data normalization and multi-stage feature selection
    (Elsevier, 2023)
    Abeer Elkhouly
    ;
    Allan Melvin Andrew
    ;
    Nidhal Abdulaziz
    ;
    Hasliza A Rahim @ Samsuddin
    ;
    Mohd Fareq Abd Malek
    ;
    Shafiquzzaman Siddique
    Audiograms are used to show the hearing capability of a person at different frequencies. The filter bank in a hearing aid is designed to match the shape of patients’ audiograms. Configuring the hearing aid is done by modifying the designed filters’ gains to match the patient’s audiogram. There are few problems faced in achieving this objective successfully. There is a shortage in the number of audiologists; the filter bank hearing aid designs are complex; and, the hearing aid fitting process is tiring. In this work, a machine learning solution is introduced to classify the audiograms according to the shapes based on unsupervised spectral clustering. The features used to build the ML model are peculiar and describe the audiograms better. Different normalization methods are applied and studied statistically to improve the training data set. The proposed Machine Learning (ML) algorithm outperformed the current existing models, where, the accuracy, precision, recall, specificity, and F-score values are higher. The reason for the better performance is the use of multi-stage feature selection to describe the audiograms precisely. This work introduces a novel ML technique to classify audiograms according to the shape, which, can be integrated to the future and existing studies to change the existing practices in classifying audiograms.
  • Publication
    Green Nanocomposite-Based metamaterial electromagnetic absorbers: Potential, current developments and future perspectives
    ( 2020)
    Nurul Fatihah Nabila Yah
    ;
    Hasliza A Rahim @ Samsuddin
    ;
    Mohdfareq Abdulmalek
    ;
    Soh Ping Jack
    ;
    R. Badlishah, Ahmad
    ;
    Muzammil Jusoh
    ;
    Lee Yeng Seng
    ;
    Mohd Haizal Jamaluddin
    ;
    Mohd Najib Mohd Yasin
      17  17
  • Publication
    Electromagnetic modelling of bundle of single-walled carbon nanotubes with circular geometry for antenna applications
    ( 2017-06-10)
    Yaseen Jurn
    ;
    Mohamed Fareq Abdul Malek
    ;
    Hasliza A Rahim @ Samsuddin
    ;
    Sawsen Mahmood
    ;
    Liu Wei Wen
    This paper aims to present an effective electromagnetic (EM) modelling approach for circular bundle of single-walled carbon nanotubes (CBSWCNTs), based on the electrical conductivity, relative complex permittivity and linear distribution impedance by applying General Ohms law for this bundle. The equivalent single conductor material (ESCM) model for personification the CB-SWCNTs is presented in this paper. The main target of this modelling approach is to estimate and investigate the EM properties of CBSWCNTs using common EM engineering tool solver CST (MWS). For this purpose, the CB-SWCNTs and ESCM dipole antennas will be designed and implemented using CST (MWS). Mathematically, the equivalent conductivity model, relative complex permittivity and other parameters of the CB-SWCNTs will be derived in this paper and considered as equivalent material parameters for the ESCM. This modelling technique is expected to provide new avenues for designing different antenna structures.
      2  17
  • Publication
    Potential of Nanocellulose Composite for Electromagnetic Shielding
    ( 2017-12-11)
    Nurul Fatihah Nabila Yah
    ;
    Hasliza A Rahim @ Samsuddin
    ;
    Yeng Seng Lee
    ;
    Wee Fwen Hoon
    ;
    Mohd Fareq Malek
    ;
    Nik Adilah Hanin Zahri
    ;
    Hayati Hasibuan Zainal
    Nowadays, most people rely on the electronic devices for work, communicating with friends and family, school and personal enjoyment. As a result, more new equipment or devices operates in higher frequency were rapidly developed to accommodate the consumers need. However, the demand of using wireless technology and higher frequency in new devices also brings the need to shield the unwanted electromagnetic signals from those devices for both proper operation and human health concerns. This paper highlights the potential of nanocellulose for electromagnetic shielding using the organic environmental nanocellulose composite materials. In addition, the theory of electromagnetic shielding and recent development of green and organic material in electromagnetic shielding application has also been reviewed in this paper. The use of the natural fibers which is nanocelllose instead of traditional reinforcement materials provides several advantages including the natural fibers are renewable, abundant and low cost. Furthermore, added with other advantages such as lightweight and high electromagnetic shielding ability, nanocellulose has a great potential as an alternative material for electromagnetic shielding application.
      1  30