Thennarasan Sabapathy
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Preferred name
Thennarasan Sabapathy
Official Name
Thennarasan, Sabapathy
Alternative Name
Sabapathy, Thennarasan
Sabapathy, Thenna
Sabapathy, T.
Sapabathy, T.
Main Affiliation
Scopus Author ID
35424377200
Researcher ID
AAA-9706-2019

Research Output
Now showing 1 - 7 of 7
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Publication

A novel unsupervised spectral clustering for pure-tone audiograms towards hearing aid filter bank design and initial configurations

2022-01-01 , Elkhouly A. , Allan Melvin Andrew , Hasliza A Rahim @ Samsuddin , Abdulaziz N. , Abdulmalek M. , Mohd Najib Mohd Yasin , Muzammil Jusoh , Thennarasan Sabapathy , Siddique S.

The current practice of adjusting hearing aids (HA) is tiring and time-consuming for both patients and audiologists. Of hearing-impaired people, 40–50% are not satisfied with their HAs. In addition, good designs of HAs are often avoided since the process of fitting them is exhausting. To improve the fitting process, a machine learning (ML) unsupervised approach is proposed to cluster the pure-tone audiograms (PTA). This work applies the spectral clustering (SP) approach to group audiograms according to their similarity in shape. Different SP approaches are tested for best results and these approaches were evaluated by Silhouette, Calinski-Harabasz, and Davies-Bouldin criteria values. Kutools for Excel add-in is used to generate audiograms’ population, annotated using the results from SP, and different criteria values are used to evaluate population clusters. Finally, these clusters are mapped to a standard set of audiograms used in HA characterization. The results indicated that grouping the data in 8 groups or 10 results in ones with high evaluation criteria. The evaluation for population audiograms clusters shows good performance, as it resulted in a Silhouette coefficient >0.5. This work introduces a new concept to classify audiograms using an ML algorithm according to the audiograms’ similarity in shape.

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A Hybrid Mutual Coupling Reduction Technique in a Dual-Band MIMO Textile Antenna for WBAN and 5G Applications

2021-01-01 , Hamza A. Mashagba , Hasliza A Rahim @ Samsuddin , Ismahayati Adam , Jamaluddin M.H. , Mohd Najib Mohd Yasin , Muzammil Jusoh , Thennarasan Sabapathy , Abdulmalek M. , Azremi Abdullah Al-Hadi , Arif Mawardi Ismail , Soh Ping Jack

This paper presents a hybrid mutual coupling reduction technique applied onto a dual-band textile MIMO antenna for wireless body area network and 5G applications. The MIMO antenna consists of two hexagonal patch antennas, each integrated with a split-ring (SR) and a bar slot to operate in dual-band mode at 2.45 GHz and 3.5 GHz. Each patch is dimensioned at 47.2 × 31 mm2. This hybrid technique results in a simple structure, while enabling significant reduction of mutual coupling (MC) between the closely spaced patches (up to 0.1 λ). This technique combines a line patch and a patch rotation technique, explained as follows. First, a line patch is introduced at an optimized distance to enable operation with a broad impedance bandwidth at both target frequencies. One of the patches is then rotated by 90° at an optimized distance, resulting in a significant MC suppression while maintaining the dual and broad impedance bandwidth. The proposed MIMO antenna is further evaluated under several bending configurations to assess its robustness. A satisfactory agreement between simulated and measured results is observed in both planar and bending conditions. Results show that the MIMO antenna achieves an impedance bandwidth of 4.3 % and 6.79 % in the 2.45 GHz and 3.5 GHz band, respectively. Moreover, very low MC (S21 <-30 dB) is achieved, with a low (< 0.002) envelop correlation coefficient, and about 10 dB of diversity gain at both desired frequencies using this technique. Even when bent at an angle of 50° at the x-and y-axes, the antenna bent maintained a realized gain of 1.878 dBi and 4.027 dBi in the lower and upper band, respectively. A robust performance is offered by the antenna against the lossy effects of the human body with good agreements between simulated and measured results.

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Bending Assessment of Dual-band Split Ring-shaped and Bar Slotted All-Textile Antenna for Off-body WBAN/WLAN and 5G Applications

2020-09-28 , Mashaghba Hamza A. , Hasliza A Rahim @ Samsuddin , Soh Ping Jack , Abdulmalek M. , Ismahayati Adam , Muzammil Jusoh , Thennarasan Sabapathy , Mohd Najib Mohd Yasin , Khairul Najmy Abdul Rani

This paper presents a dual-band split ring-shaped and bar slotted textile antenna for potential WBAN/WLAN and 5G applications. The antenna is made using textiles and features a full ground plane to possibly alleviate coupling to the human body. The overall size of the antenna is 70 x 70 mm2, with a patch sized at 47.2 x 31 mm2 0.472 \lambda \times 0.031 \lambda. The antenna is made using ShieldIt Super as its conductive textile and felt as its substrate. To enable its dual-band resonance at 2.45 and 3.5 GHz a split ring-shaped and bar slots are integrated onto the patch. The proposed antenna is evaluated when bent under different radii and at different axes to estimate its performance in terms of reflection coefficient, bandwidth, efficiency and gain. A 10-dB impedance bandwidth of 57 % or 135 MHz (from 2.39 to 2.52 GHz) and 70 % or 240 MHz (from 3.45 to 3.56 GHz) are obtained when evaluated in the planar /bent configuration. The maximum realized gain is 6 dBi for at 3.5 GHz. These performances indicate that the antenna proposed in this work can be potentially improved for applications in WBAN/WLAN and 5G bands.

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Flexible Co-Planar Waveguide (CPW)-Fed Y-Shaped Patch UWB Antenna for Off-Body Communication

2020-03-18 , Kassim S. , Hasliza A Rahim @ Samsuddin , Soh Ping Jack , Abdulmalek M. , Muzammil Jusoh , Jamaluddin M.H. , Sabli N.S. , Yassin M.N. , Thennarasan Sabapathy , Wee Fwen Hoon , Mohamed Nasrun Osman , Ismail N.

This paper intends to design an Ultra-Wideband (UWB) antenna for future Internet of Things (IoT) applications for off-body Wireless Body Area Networks (WBAN) communication. An antenna based on the Y-shaped patch fed using co-planar waveguide (CPW) line, with a full ground plane is designed. It is implemented on two different substrates, namely a 5mm thick Rogers RO4350B and a 5-mm-thick felt textile. Parametric analysis of antenna is performed by changing its critical dimensions and monitoring parameters such as gain, bandwidth, efficiency, radiation pattern when using both substrates. Besides that, the bending effects towards reflection coefficient and radiation patterns are also studied. The final patch size with the Y-shaped slot is 36 × 40 mm2 for both substrates. The antenna is capable of providing coverage for the bands from 8 to 10 GHz. Finally, the antenna designed on RO4350B substrate outperforms the antenna designed on felt by about four times in terms of bandwidth, with 3.3 GHz (7.7-11 GHz).

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A hybrid modified sine cosine algorithm using inverse filtering and clipping methods for low autocorrelation binary sequences

2022-01-01 , Rosli S.J. , Hasliza A Rahim @ Samsuddin , Khairul Najmy Abdul Rani , Ruzelita Ngadiran , Wan Azani Wan Mustafa , Abdulmalek M. , Mohd Najib Mohd Yasin , Muzammil Jusoh , Thennarasan Sabapathy , Wan Nur Suryani Firuz Wan Ariffin , Alkhayyat A.

The essential purpose of radar is to detect a target of interest and provide information concerning the target's location, motion, size, and other parameters. The knowledge about the pulse trains' properties shows that a class of signals is mainlywell suited to digital processing of increasing practical importance. A low autocorrelation binary sequence (LABS) is a complex combinatorial problem. The main problems of LABS are low Merit Factor (MF) and shorter length sequences. Besides, the maximumpossibleMF equals 12.3248 as infinity length is unable to be achieved. Therefore, this study implemented two techniques to propose a new metaheuristic algorithm based on Hybrid Modified Sine Cosine Algorithm with Cuckoo Search Algorithm (HMSCACSA) using Inverse Filtering (IF) and clipping method to achieve better results. The proposed algorithms, LABS-IF and HMSCACSA-IF, achieved better results with two large MFs equal to 12.12 and 12.6678 for lengths 231 and 237, respectively, where the optimal solutions belong to the skew-symmetric sequences. TheMFoutperformed up to 24.335% and 2.708% against the state-of-the-art LABS heuristic algorithm, xLastovka, and Golay, respectively. These results indicated that the proposed algorithm's simulation had quality solutions in terms of fast convergence curve with better optimal means, and standard deviation.

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A hybrid modified method of the sine cosine algorithm using latin hypercube sampling with the cuckoo search algorithm for optimization problems

2020-11-01 , Siti Julia Rosli , Hasliza A Rahim @ Samsuddin , Khairul Najmy Abdul Rani , Yahaya N.Z. , R Badlishah Ahmad , Ruzelita Ngadiran , Abdulmalek M. , Muzammil Jusoh , Mohd Najib Mohd Yasin , Thennarasan Sabapathy , Allan Melvin Andrew

The metaheuristic algorithm is a popular research area for solving various optimization problems. In this study, we proposed two approaches based on the Sine Cosine Algorithm (SCA), namely, modification and hybridization. First, we attempted to solve the constraints of the original SCA by developing a modified SCA (MSCA) version with an improved identification capability of a random population using the Latin Hypercube Sampling (LHS) technique. MSCA serves to guide SCA in obtaining a better local optimum in the exploitation phase with fast convergence based on an optimum value of the solution. Second, hybridization of the MSCA (HMSCA) and the Cuckoo Search Algorithm (CSA) led to the development of the Hybrid Modified Sine Cosine Algorithm Cuckoo Search Algorithm (HMSCACSA) optimizer, which could search better optimal host nest locations in the global domain. Moreover, the HMSCACSA optimizer was validated over six classical test functions, the IEEE CEC 2017, and the IEEE CEC 2014 benchmark functions. The effectiveness of HMSCACSA was also compared with other hybrid metaheuristics such as the Particle Swarm Optimization–Grey Wolf Optimization (PSOGWO), Particle Swarm Optimization–Artificial Bee Colony (PSOABC), and Particle Swarm Optimization–Gravitational Search Algorithm (PSOGSA). In summary, the proposed HMSCACSA converged 63.89% faster and achieved a shorter Central Processing Unit (CPU) duration by a maximum of up to 43.6% compared to the other hybrid counterparts.

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5G Millimeter Wave Wearable Antenna: State-Of-the-Art and Current Challenges

2021-01-01 , Hasliza A Rahim @ Samsuddin , Mashagba H.A. , Yahaya N.Z. , Mohd Najib Mohd Yasin , Jamaluddin M.H. , Muzammil Jusoh , Thennarasan Sabapathy , Ismahayati Adam , Abdulmalek M.

Fifth Generation (5G) is the next evolution of mobile communication that will provide seamless and massive high speed connectivity to the society. Paralleled with the rise of 5G, it is foreseen that wearable devices particularly wearable antenna will be the significant end node for wearable devices in Millimeter Wave (mmWave) frequency bands. Thus, this paper discusses the new development of the 5G sub-6 GHz and mmWave wearable antenna, introduces the research results of the 5G mmWave wearable antenna in recent years, and addresses the key challenges in the development trend of the development trend of the 5G mmWave wearable antenna.

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