Khairul Najmy Abdul Rani
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Preferred name
Khairul Najmy Abdul Rani
Official Name
Abdul Rani, Khairul Najmy
Alternative Name
Rani, Khairul Najmy Abdul
Rani, Khairul Najmy Abd
Rani, K. N.A.
Abdul Rani, K. N.
Rani, Khairul N.Abdul
Abdul Rani, Khairul Najmy
Rani, K. N.Abdul
Main Affiliation
Scopus Author ID
57210770305
Researcher ID
GBP-6810-2022

Research Output

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  • Publication
    Hybridization of strength pareto multiobjective optimization with modified cuckoo search algorithm for rectangular array
    ( 2017)
    Khairul Najmy Abdul Rani
    ;
    Mohamedfareq Abdulmalek
    ;
    Hasliza A Rahim @ Samsuddin
    ;
    Neoh Siew Chin
    ;
    Alawiyah Abd Wahab
    This research proposes the various versions of modified cuckoo search (MCS) metaheuristic algorithm deploying the strength Pareto evolutionary algorithm (SPEA) multiobjective (MO) optimization technique in rectangular array geometry synthesis. Precisely, the MCS algorithm is proposed by incorporating the Roulette wheel selection operator to choose the initial host nests (individuals) that give better results, adaptive inertia weight to control the positions exploration of the potential best host nests (solutions), and dynamic discovery rate to manage the fraction probability of finding the best host nests in 3-dimensional search space. In addition, the MCS algorithm is hybridized with the particle swarm optimization (PSO) and hill climbing (HC) stochastic techniques along with the standard strength Pareto evolutionary algorithm (SPEA) forming the MCSPSOSPEA and MCSHCSPEA, respectively. All the proposed MCS-based algorithms are examined to perform MO optimization on Zitzler–Deb–Thiele’s (ZDT’s) test functions. Pareto optimum trade-offs are done to generate a set of three non-dominated solutions, which are locations, excitation amplitudes, and excitation phases of array elements, respectively. Overall, simulations demonstrates that the proposed MCSPSOSPEA outperforms other compatible competitors, in gaining a high antenna directivity, small half-power beamwidth (HPBW), low average side lobe level (SLL) suppression, and/or significant predefined nulls mitigation, simultaneously.
  • Publication
    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 H.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.
  • Publication
    A hybrid modified method of the sine cosine algorithm using latin hypercube sampling with the cuckoo search algorithm for optimization problems
    ( 2020-11-01)
    Rosli S.J.
    ;
    Hasliza A Rahim @ Samsuddin
    ;
    Khairul Najmy Abdul Rani
    ;
    Ruzelita Ngadiran
    ;
    R Badlishah Ahmad
    ;
    Yahaya N.Z.
    ;
    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.
  • Publication
    Flexible UWB Compact Circular Split-Ring Slotted Wearable Textile Antenna for Off-Body Millimetre-Wave 5G Mobile Communication
    ( 2020-01-01)
    Lee H.W.
    ;
    Hasliza A Rahim @ Samsuddin
    ;
    Abdulmalek M.
    ;
    R Badlishah Ahmad
    ;
    Jamaluddin M.H.
    ;
    Muzammil Jusoh
    ;
    Mohsin D.A.
    ;
    Wee Fwen Hoon
    ;
    Ismahayati Adam
    ;
    Yahya N.Z.
    ;
    Khairul Najmy Abdul Rani
    A flexible ultra-wideband (UWB) compact circular split-ring slotted wearable textile antenna for off-body 28 GHz fifth-generation (5G) mobile communication is proposed. The proposed antenna is implemented using low-cost felt textile substrates and copper. The proposed 5G wearable antenna of compact circular split-ring slotted with enhanced bandwidth of 0.5% with the resonance frequency of 28 GHz is presented. The S11 for patch antenna with slot exhibited 43.4% more than the patch antenna without slot. The results also exhibited that the bending angle of 10° and 20° perform better return loss than in flat condition, up to 14% for patch antenna with slot against without the slot.
  • Publication
    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
    ;
    Mustafa W.A.
    ;
    Muzammil Jusoh
    ;
    Mohd Najib Mohd Yasin
    ;
    Thennarasan Sabapathy
    ;
    Abdulmalek M.
    ;
    Ariffin W.S.F.W.
    ;
    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.
  • Publication
    1×4 Patch Array All-Textile Antenna for WLAN Applications
    ( 2020-09-28)
    Mashaghba H.A.
    ;
    Hasliza A Rahim @ Samsuddin
    ;
    Soh Ping Jack
    ;
    Mohamedfareq Abdulmalek
    ;
    Ismahayati Adam
    ;
    Muzammil Jusoh
    ;
    Mohd Najib Mohd Yasin
    ;
    Thennarasan Sabapathy
    ;
    Khairul Najmy Abdul Rani
    This paper proposes the design of 1×4 patch array all-Textile antenna for Wireless Local Area Networks (WLAN) applications. The wearable antenna needs to have low profile and lightweight since such antenna is intended to operate in the vicinity of the human body. The key parameters are studied to determine their effects towards the performance of the antenna. The proposed design uses ShieldIt as the top radiator and ground plane, while fabric Felt is used as a substrate, sandwiched between the top radiator and ground plane.The obtained results show that there is improvement in the proposed array antenna in terms of gain enhancement and impedance bandwidth, maximum up to 143.6% and 19.08%, respectively, against single patch structure.
  • Publication
    Linear antenna array synthesis using the enhanced and hybrid cuckoo search metaheuristic algorithms
    ( 2014)
    Khairul Najmy Abdul Rani
    The antenna geometry synthesis plays an important role to determine the physical layout of the antenna array, which produces the radiation pattern closest to the actual desired pattern. The synthesis can be realized by defining the location of antenna array elements, and by choosing suitable excitation of amplitude, and excitation phase applied on the antenna array elements. Many synthesis techniques are done through suppressing the side lobe level (SLL) and/or mitigating prescribed nulls while simultaneously maintaining or improving the major lobe radiation intensity. Studies show that some conventional analytical, numerical, and modern evolutionary algorithm (EA) or evolutionary computation (EC) techniques have certain limitations in antenna array geometry synthesis. This includes beamwidth expanding and directivity saturation in amplitude tapering, exhaustive checking impairment in analytical method, disparity predicament between local and global search accelerators in particle swarm optimization (PSO), and drawbacks of crossover and mutation operators in genetic algorithm (GA). This thesis presents the sequential development of enhanced and hybrid versions of cuckoo search (CS) metaheuristic algorithm as an alternative of EA/EC technique for symmetric linear antenna array synthesis. Firstly, the proposal of the modified CS (MCS) algorithm through the integration with the Roulette wheel selection operator, dynamic inertia weight, and dynamic discovery rate controlling the best solutions exploration for a single objective (SO) optimization. Secondly, there is the hybridization of MCS with PSO (MCSPSO), and MCS with GA (MCSGA) in both SO and weighted−sum multiobjective (MO) approaches. Thirdly, the proposed amalgamation of MCS with strength Pareto evolutionary algorithm (MCSSPEA), hill climbing (HC) stochastic method within MCSSPEA algorithm (MCSHCSPEA), and PSO within MCSSPEA algorithm (MCSPSOSPEA) equipped with distance expansion formulae to reduce local trap problem. These newly techniques are specifically for Pareto MO optimization to find non−dominated solutions including element location, excitation amplitude, and excitation phase. All the tested algorithms development, source code writing, and results execution are performed using MATLAB scientific software. The optimal solutions are then compared against corresponding counterparts. Based on simulation results, the proposed MCSPSO outperforms other SO and weighted−sum MO algorithms whereas the proposed MCSPSOSPEA algorithm surpasses other tested Pareto MO algorithms in SLL suppression and/or nulls mitigation whilst achieving a high linear antenna directivity, and small half−power beamwidth (HPBW), respectively.
  • Publication
    1×4 Patch Array All-Textile Antenna for WLAN Applications
    ( 2020-09-28)
    Mashaghba H.A.
    ;
    Hasliza A Rahim @ Samsuddin
    ;
    Ping Jack Soh
    ;
    Abdulmalek Mohamedfareq
    ;
    Ismahayati Adam
    ;
    Muzammil Jusoh
    ;
    Mohd Najib Mohd Yasin
    ;
    Thennarasan Sabapathy
    ;
    Khairul Najmy Abdul Rani
    This paper proposes the design of 1×4 patch array all-Textile antenna for Wireless Local Area Networks (WLAN) applications. The wearable antenna needs to have low profile and lightweight since such antenna is intended to operate in the vicinity of the human body. The key parameters are studied to determine their effects towards the performance of the antenna. The proposed design uses ShieldIt as the top radiator and ground plane, while fabric Felt is used as a substrate, sandwiched between the top radiator and ground plane.The obtained results show that there is improvement in the proposed array antenna in terms of gain enhancement and impedance bandwidth, maximum up to 143.6% and 19.08%, respectively, against single patch structure.
  • Publication
    A hybrid modified method of the sine cosine algorithm using latin hypercube sampling with the cuckoo search algorithm for optimization problems
    ( 2020-11-01)
    Rosli S.J.
    ;
    Hasliza A Rahim @ Samsuddin
    ;
    Khairul Najmy Abdul Rani
    ;
    Ruzelita Ngadiran
    ;
    R Badlishah Ahmad
    ;
    Yahaya N.Z.
    ;
    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.
  • Publication
    Mobile Green E-Waste Management Systems using IoT for Smart Campus
    ( 2021-07-26)
    Khairul Najmy Abdul Rani
    ;
    Hasliza A Rahim @ Samsuddin
    ;
    Ong B.T.
    ;
    Muzammil Jusoh
    ;
    Mohd Najib Mohd Yasin
    ;
    Thennarasan Sabapathy
    ;
    Wan Azani Wan Mustafa
    ;
    Mohd Aminudin Jamlos
    ;
    R Badlishah Ahmad
    ;
    Hammood D.A.
    This paper presents the design and development of mobile "green"electronic waste (e-waste) management systems using Internet of Things (IoT) for smart campus. The system uses Raspberry Pi 3 Model B v1.2 microcontroller for monitoring e-waste object detection, e-waste count, and bin percentage level, respectively. TensorFlow Lite application programming interface (API) is used to run Single Shot Multibox Detector (SSD)Lite-MobileNet-v2 model trained on Microsoft Common Objects in Context (MSCOCO) dataset for e-waste object detection in image. All the monitoring data are stored and retrieved in ThingSpeak cloud platform using Hypertext Transfer Protocol (HTTP) and Message Queuing Telemetry Transport (MQTT) protocol over the Internet and displayed via interactive Android-based mobile user interface (UI). Furthermore, automatic e-mail notification will be sent to waste collector for bin collection whenever e-waste bin percentage level is greater than predetermined threshold value of 80% full.