UniMAP RIS :: Browsing by Type "journal-article"

Publication

2-SAT discrete Hopfield neural networks optimization via Crow search and fuzzy dynamical clustering approach

( 2024)

Caicai Feng

;

Saratha Sathasivam

;

Nurshazneem Roslan

;

Muraly Velavan

Within the swiftly evolving domain of neural networks, the discrete Hopfield-SAT model, endowed with logical rules and the ability to achieve global minima of SAT problems, has emerged as a novel prototype for SAT solvers, capturing significant scientific interest. However, this model shows substantial sensitivity to network size and logical complexity. As the number of neurons and logical complexity increase, the solution space rapidly contracts, leading to a marked decline in the model's problem-solving performance. This paper introduces a novel discrete Hopfield-SAT model, enhanced by Crow search-guided fuzzy clustering hybrid optimization, effectively addressing this challenge and significantly boosting solving speed. The proposed model unveils a significant insight: its uniquely designed cost function for initial assignments introduces a quantification mechanism that measures the degree of inconsistency within its logical rules. Utilizing this for clustering, the model utilizes a Crow search-guided fuzzy clustering hybrid optimization to filter potential solutions from initial assignments, substantially narrowing the search space and enhancing retrieval efficiency. Experiments were conducted with both simulated and real datasets for 2SAT problems. The results indicate that the proposed model significantly surpasses traditional discrete Hopfield-SAT models and those enhanced by genetic-guided fuzzy clustering optimization across key performance metrics: Global minima ratio, Hamming distance, CPU time, retrieval rate of stable state, and retrieval rate of global minima, particularly showing statistically significant improvements in solving speed. These advantages play a pivotal role in advancing the discrete Hopfield-SAT model towards becoming an exemplary SAT solver. Additionally, the model features exceptional parallel computing capabilities and possesses the potential to integrate with other logical rules. In the future, this optimized model holds promise as an effective tool for solving more complex SAT problems. </abstract>

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Publication

2D LiDAR based reinforcement learning for Multi-Target path planning in unknown environment

( 2023)

Nasr Abdalmanan

;

Kamarulzaman Kamarudin

;

Muhammad Aizat Abu Bakar

;

Mohd Hafiz Fazalul Rahiman

;

Ammar Zakaria

;

Syed Muhammad Mamduh Syed Zakaria

;

Latifah Munirah Kamarudin

Global path planning techniques have been widely employed in solving path planning problems, however they have been found to be unsuitable for unknown environments. Contrarily, the traditional Q-learning method, which is a common reinforcement learning approach for local path planning, is unable to complete the task for multiple targets. To address these limitations, this paper proposes a modified Q-learning method, called Vector Field Histogram based Q-learning (VFH-QL) utilized the VFH information in state space representation and reward function, based on a 2D LiDAR sensor. We compared the performance of our proposed method with the classical Q-learning method (CQL) through training experiments that were conducted in a simulated environment with a size of 400 square pixels, representing a 20-meter square map. The environment contained static obstacles and a single mobile robot. Two experiments were conducted: experiment A involved path planning for a single target, while experiment B involved path planning for multiple targets. The results of experiment A showed that VFH-QL method had 87.06% less training time and 99.98% better obstacle avoidance compared to CQL. In experiment B, VFH-QL method was found to have an average training time that was 95.69% less than that of the CQL method and 83.99% better path quality. The VFH-QL method was then evaluated using a benchmark dataset. The results indicated that the VFH-QL exhibited superior path quality, with efficiency of 94.89% and improvements of 96.91% and 96.69% over CQL and SARSA in the task of path planning for multiple targets in unknown environments.

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Publication

3D spacer fabric structured airflow channel for enhanced solar desalination with efficient multi-energy harvesting

(Elsevier B.V., 2025)

Can Ge

;

Duo Xu

;

Xiao Feng

;

Heng Du

;

Ze, Chen

;

Ong Hui Lin

;

Chong Gao

;

Guilong Yan

;

Jian Fang

Solar steam generation (SSG) is a sustainable way to drive seawater desalination and wastewater purification with green environmental energies including solar radiation, ambient heat, and airflow. Airflow is ubiquitous in outdoor environments, however, the utilization of airflow for accelerated evaporation through structure engineering remains unclear. Herein, environmental energies are efficiently utilized in an integrated way with the rational design of 3D spacer fabric. Carbon fiber bundles with broadband photothermal conversion ability and Tencel yarns with superior hydrophilicity are fabricated into the 3D spacer fabric. The stereoscopic airflow channel, wide evaporation surface area, and separated layers are constructed to optimize airflow pathways. Heat loss is reduced through the accelerated evaporation cooling effect. Extra ambient heat is harvested for cold evaporation by efficient airflow utilization. The evaporation rate of 3D spacer fabric reaches 5.15 kg·m−2·h−1 under a convective airflow of 3.5 m·s−1, which is twice the rate of traditional plain fabrics. The outstanding salt resistance is realized due to the separate design of photothermal and water supply layers as well as the continuous water circulation. The structural engineering of condenser devices is also investigated for enhanced airflow utilization. Overall, this work presents an effective and comprehensive multi-energy harvesting strategy to achieve rapid and durable SSG for practical clean water production.

Publication

A 0.7 GHz and 0.9 GHz efficient and compact dual-band rectifier for ambient radio frequency energy harvesting

(Institute of Advanced Engineering and Science (IAES), 2025)

Raja Nor Azrin Raja Yunus

;

Ismahayati Adam

;

Mohd Najib Mohd Yasin

;

Surajo Muhammad

;

Abdulrahman Amin Ahmed Ghaleb

;

Wan Zuki Azman Wan Muhamad

This study introduces a compact dual-band rectifier utilizing a single and multi-stub matching network (MN) technique. The rectifier consists of two branches, each incorporating a single block stub and two blocks stub to generate two frequency susceptance blocks, subsequently transformed into a meandered line. The proposed rectifier operates at two frequency bands of 0.7 GHz and 0.9 GHz and is fabricated on an RT/Duroid 5880 printed circuit board (PCB) with dimensions of 37×25×1.6 mm using an entire ground architecture. Simulation and measurement results show that the rectifier has a power conversion efficiency (PCE) of 67.77% and 66.35% at 0.7 GHz and 70.31% and 71.22% at 0.9 GHz with input power of 0 dBm, respectively. The rectified voltage is 1.79 V DC across a 5 kΩ load terminal (RL) with 5 dBm input power and is capable of sensing low input power down to -30 dBm. This feature makes the rectifier a promising solution for powering low-power devices from ambient energy.

Publication

A BIM-based model checking in the green building maintenance: a review

(Emerald Publishing, 2023)

Zul-Atfi Ismail

Purpose: This paper aims to identify the different system approach using building information modelling (BIM) technology that is equipped with automated evaluation processes. BIM research has mainly focused on theoretical models of acceptance in the green building (GB) maintenance industry. However, BIM has the potential to the competency’s performance and design knowledge of building control instrument. Realising this potential requires a study of BIM at the maintenance planning level, which is considered to be BIM-based model checking (BMC). BMC and its effect in the maintenance planning have not been sufficiently investigated. Design/methodology/approach: The aim of this paper is to present a critical review of literature on the theoretical background of BMC practices and the main features of information and communication technology tools and techniques in the GB maintenance projects. Findings: A theoretical framework of BMC is developed and presented. The proposed model incorporates requirement for maintaining a competency’s performance on maintenance planning schemes of GB projects and the importance of early integration of BMC in the design phase to identify alternative methods to cogenerate, monitor and optimise BMC. Originality/value: It is found that variables facilitating BMC are integrated at different GB maintenance environments levels and are shaped by the context. Directions for future research are presented.

Publication

A Bio-Inspired herbal tea flavour assessment technique

( 2014)

Nur Zatul 'Iffah Zakaria

;

Masnan, Maz Jamilah

;

Ammar Zakaria

;

Ali Yeon Md Shakaff

Herbal-based products are becoming a widespread production trend among manufacturers for the domestic and international markets. As the production increases to meet the market demand, it is very crucial for the manufacturer to ensure that their products have met specific criteria and fulfil the intended quality determined by the quality controller. One famous herbal-based product is herbal tea. This paper investigates bio-inspired flavour assessments in a data fusion framework involving an e-nose and e-tongue. The objectives are to attain good classification of different types and brands of herbal tea, classification of different flavour masking effects and finally classification of different concentrations of herbal tea. Two data fusion levels were employed in this research, low level data fusion and intermediate level data fusion. Four classification approaches; LDA, SVM, KNN and PNN were examined in search of the best classifier to achieve the research objectives. In order to evaluate the classifiers' performance, an error estimator based on k-fold cross validation and leave-one-out were applied. Classification based on GC-MS TIC data was also included as a comparison to the classification performance using fusion approaches. Generally, KNN outperformed the other classification techniques for the three flavour assessments in the low level data fusion and intermediate level data fusion. However, the classification results based on GC-MS TIC data are varied.

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Publication

A biomimetic sensor for the classification of honeys of different floral origin and the detection of adulteration

( 2011-08)

Ammar Zakaria

;

Ali Yeon Md Shakaff

;

Masnan, Maz Jamilah

;

Norazian Subari

;

Nazifah Ahmad Fikri

;

Abdul Hamid Adom

;

Mohd Noor Ahmad

;

Mahmad Nor Jaafar

;

Latifah Munirah Kamarudin

;

Abdul Hallis Abdul Aziz

;

Abu Hassan Abdullah

;

Supri A. Ghani

The major compounds in honey are carbohydrates such as monosaccharides and disaccharides. The same compounds are found in cane-sugar concentrates. Unfortunately when sugar concentrate is added to honey, laboratory assessments are found to be ineffective in detecting this adulteration. Unlike tracing heavy metals in honey, sugar adulterated honey is much trickier and harder to detect, and traditionally it has been very challenging to come up with a suitable method to prove the presence of adulterants in honey products. This paper proposes a combination of array sensing and multi-modality sensor fusion that can effectively discriminate the samples not only based on the compounds present in the sample but also mimic the way humans perceive flavours and aromas. Conversely, analytical instruments are based on chemical separations which may alter the properties of the volatiles or flavours of a particular honey. The present work is focused on classifying 18 samples of different honeys, sugar syrups and adulterated samples using data fusion of electronic nose (e-nose) and electronic tongue (e-tongue) measurements. Each group of samples was evaluated separately by the e-nose and e-tongue. Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) were able to separately discriminate monofloral honey from sugar syrup, and polyfloral honey from sugar and adulterated samples using the e-nose and e-tongue. The e-nose was observed to give better separation compared to e-tongue assessment, particularly when LDA was applied. However, when all samples were combined in one classification analysis, neither PCA nor LDA were able to discriminate between honeys of different floral origins, sugar syrup and adulterated samples. By applying a sensor fusion technique, the classification for the 18 different samples was improved. Significant improvement was observed using PCA, while LDA not only improved the discrimination but also gave better classification. An improvement in performance was also observed using a Probabilistic Neural Network classifier when the e-nose and e-tongue data were fused.

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Publication

A compact 2.4 GHz L-Shaped microstrip patch antenna for ISM-Band Internet of Things (IoT) applications

(MDPI, 2023)

Muhammad Fitra Zambak

;

Samir Salem Al-Bawri

;

Muzammil Jusoh

;

Ali Hanafiah Rambe

;

Hamsakutty Vettikalladi

;

Ali M. Albishi

;

Mohamed Himdi

Wireless communication technology integration is necessary for Internet of Things (IoT)-based applications to make their data easily accessible. This study proposes a new, portable L-shaped microstrip patch antenna with enhanced gain for IoT 2.4 GHz Industrial, Scientific, and Medical (ISM) applications. The overall dimensions of the antenna are 28 mm × 21 mm × 1.6 mm (0.22λo × 0.17λo × 0.013λo, with respect to the lowest frequency). The antenna design is simply comprised of an L-shape strip line, with a full ground applied in the back side and integrated with a tiny rectangular slot. According to investigations, the developed antenna is more efficient and has a greater gain than conventional antennas. The flexibility of the antenna’s matching impedance and performance are investigated through several parametric simulations. Results indicate that the gain and efficiency can be enhanced through modifying the rectangular back slot in conjunction with fine-tuning the front L-shaped patch. The finalized antenna operates at 2.4 GHz with a 98% radiation efficiency and peak gains of 2.09 dBi (measured) and 1.95 dBi (simulated). The performance of the simulation and measurement are found to be in good agreement. Based on the performance that was achieved, the developed L-shaped antenna can be used in a variety of 2.4 GHz ISM bands and IoT application environments, especially for indoor localization estimation scenarios, such as smart offices and houses, and fourth-generation (4G) wireless communications applications due to its small size and high fractional bandwidth.

Publication

A comparative analysis of technical efficiency, technological change and total factor productivity in selected ASEAN+3 countries

(Inderscience Enterprises Ltd., 2023-07)

Noorazeela Zainol Abidin

;

Ishak Yussof

;

Zulkefly Abdul Karim

;

Mohd Shahidan Shaari

Total factor productivity (TFP) growth in ASEAN+3 countries exhibits varied trends. This is due to the fact that each country has different skills and different levels of technological advancement. This study aims to analyse the trends in technical efficiency (TEC), technological change (TC) and TFP growth using the Malmquist productivity index method. The analysis is based on data ranging from 1981 to 2014 in selected ASEAN+3 countries. The results show that during the periods 1981–1985, 1986–1990, 1991–1995, 1996–2000 and 2001–2005, the contribution of TEC to TFP growth was higher than that of TC. However, during the periods 2006–2010 and 2011–2014, the contribution of TC to TFP growth was higher than that of TEC. Therefore, it is imperative for the countries to improve the quality of inputs such as labour. Hence, skilled workers are indispensable to produce higher productivity.

Publication

A comparative finite element analysis of regular and topologically optimised dental implants for mechanical and fatigue responses evaluation

(Faculty of Engineering. International Islamic University Malaysia, 2023)

Muhammad Ikman Ishak

;

Siti Noor Fazliah Mohd Noor

;

Ruslizam Daud

;

Muhammad Hafiz Ummah Abu Bakar Bakri

Topology optimisation is a prominent method to improve the performance of any systems by optimising geometrical factors to save materials without compromising the system functionality. Currently, there is limited published data discussing the topologically optimised dental implants that makes the matter still unclear. This study aimed to evaluate the mechanical and fatigue behaviours of regular and topologically optimised dental implant designs using 3-D FEA. Geometrical models were developed in accordance with ISO 14801 using SolidWorks 2020 before being analysed in ANSYS 18.1. The new implant design was created by topology optimisation analysis. The material properties of all parts were assumed to be isotropic, linearly elastic, and homogenous. Nine different compressive load values ranging from 100 to 500 N were applied on the loading structure as separated cases. The vertical and bottom surfaces of the holder were fully constrained. The results showed that the topologically optimised implant recorded about 12.3% lower implant stress than the regular implant. Both implant designs revealed a comparable displacement result with a percentage difference of only 2.3%. The optimised design was also found to produce longer fatigue life and approximately 12.3% higher safety factor compared to the regular design. The increase in the compressive load value has increased the stress and deformation, whilst decreased the fatigue life and safety factor in both designs. Although it was estimated that the volume of the new implant could be reduced to about 24% of the traditional one, the implant functionality may still be retained or even be improved.

Publication

A comparative study of dual cylinders and triangle bluff bodies for piezoelectric energy harvesting

(IOP Publishing, 2023)

Mohd Nor Fakhzan Mohd Kazim

;

Y J Zhe

;

Zambri Harun

;

Mohd Zaki Nuawi

;

Mohammad Rasidi Rasani

;

Muhd Nur Rahman Yahya

The flow patterns behind tandem bluff bodies can be used to generate electricity in piezoelectric energy harvesters. The vortices and wakes that form behind the bluff bodies create a pressure differential, which can be used to deform a piezoelectric film. In this study, we investigated the performance of dual triangle and dual cylinder bluff bodies in tandem at varying Reynolds numbers, Re, and spacing ratios, D. We compared the flow patterns behind the two types of bluff bodies. Sixteen hot wire anemometers were placed at different locations to measure the velocity developed behind the dual bluff bodies in tandem. The results showed that the velocities behind the cylinder bluff bodies were initially higher than those behind the triangle bluff bodies at lower Re. This is because the cylinder bluff bodies create a more turbulent flow, which results in higher velocities at lower Re. The best distance between the two bluff bodies was 3D and 5D, where the output velocities were maximized at more than 12ms-1. However, for dual triangle, the velocities eventually became higher than those behind the cylinder bluff bodies at higher Re and lower separation ratios (1D and 2D). 3D was the best distance for triangle to produce a higher velocity pattern, and this was best observed when Re = 10k, which is the lowest inlet velocity set. The results of the experiments are expected to show that the dual triangle bluff bodies produce higher velocities than the dual triangle bluff bodies, which will lead to a higher amount of energy being harvested. The results show that the amount of energy harvested were increase with increasing Re and decreasing D. The information enhancement can be done with turbulence analysis which could lead to the development of more efficient and versatile piezoelectric energy harvester.

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Publication

A comparative study of numerical modelling and analysis for large articulated pendulums

(Semarak Ilmu Publishing, 2025-05)

Siti Fatimah Azzahra Ahmad Noh

;

Mohamad Ezral Baharudin

;

Mohd Zakimi Zakaria

;

Mohd Sazli Saad

;

Azuwir Mohd Nor

In this article, we present a large system of multiple pendulums, also articulated pendulums, with twenty pendulums as a multibody model. The main objective of the study is to compare the computational time efficiency of two multibody formulations: the augmented Lagrangian and the recursive method for each articulated system. The equations of motion were derived for each formulation and the fourth- and fifth-order Runge-Kutta methods were utilised to solve for the equations by representing the kinematics and dynamics of the systems numerically. The computational times that corresponded to the manipulated step size and tolerance were compared for both formulations. The results showed that the augmented Lagrangian formulation had a significant divergence towards the negative y-axis at tolerance 0.1s for all modified step sizes. The animations also demonstrated elongation for specific pendulums based on the step size selection at a tolerance 0.1s. The recursive method, on the other hand, produced the best-fit plots and stable results for all xy-position and velocity-time plots for each adjusted step size and tolerance. Therefore, the recursive method is concluded to be more efficient than the augmented Lagrangian formulation in solving large open-loop multibody systems.

Publication

A comparison of double-end partial discharge localization algorithms in power cables

(MDPI, 2023)

Asfarina Abu Bakar

;

Chai Chang Yii

;

Chin Kui Fern

;

Yoong Hou Pin

;

Herwansyah Lago

;

Mohamad Nur Khairul Hafizi Rohani

The double-end partial discharge (PD) measurement method is the most common method for measuring and localizing PD sources in power cables. The sensitivity of the PD sensor, the processing speed of the data acquisition unit, and the method of the PD localization algorithm are the three main keys to ensuring the accuracy of the PD source localization on power cables. A new multi-end PD localization algorithm known as segmented correlation trimmed mean (SCTM) has recently demonstrated excellent accuracy in the localization of PD sources on power cables. The algorithm, however, is only applicable to multi-end PD measurement methods. In this paper, the mathematical equation of the SCTM algorithm is customized to match the double-end PD measurement method. A MATLAB simulation was conducted to assess the performance of the SCTM algorithm in the double-end PD measurement method. The maximum peak detection (MPD) algorithm, segmented correlation (SC), and SCTM algorithm were compared as PD localization algorithms. The SC algorithms have shown that identifying the correlation bond between two cues instead of the peak of the PD signal in the MPD algorithm significantly increases the PD localization accuracy. The results show that the SCTM algorithm outperforms the MPD and SC algorithms in terms of accuracy.

Publication

A comprehensive study: AI literacy as a component of media literacy

(Semarak Ilmu Publishing, 2025-11)

Miharaini Md Ghani

;

Wan Azani Wan Mustafa

;

Durratul Laquesha Shaiful Bakhtiar

;

Moh. Khairudin

The widespread use of AI-based technologies has sparked educational, social, and political interest in AI training. Education systems must prepare individuals for a world with AI. AI literacy is a cognitive and pedagogical difficulty. AI's language and intricacies need redefining literacy. Because these systems are easy to use, more individuals are utilizing them than those with limited conceptualizations (such as an inability to grasp the future relevance of these systems) or competencies (like an inability to comprehend how these systems function). The study investigates the increasing significance of artificial intelligence (AI) literacy within the context of media literacy. As AI technologies permeate various aspects of modern media, the capacity to comprehend and engage critically with these systems has become essential. The paper begins by analyzing the intricate intersection of AI and media, focusing on content creation, dissemination, and consumption. It then emphasizes the importance of AI literacy, which is the ability to comprehend, implement, and evaluate AI technologies critically, similar to traditional media literacy skills. Finally, the paper proposes that AI literacy, as part of media literacy, entails understanding how these systems function and their ethical and societal implications. The paper's conclusion offers a comprehensive framework for incorporating AI literacy into media education curricula, aiming to empower individuals to navigate, evaluate, and responsibly participate in the evolving AI-mediated media landscape.

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Publication

A critical study of the existing issues in circular economy practices during movement control order: can BIM fill the gap?

(Emerald, 2022)

Zul-Atfi Ismail

The improper evaluation and information management of circular economy (CE) (i.e. design, planning, supply chain, waste pile and material hazard) is critical for public health and is a major problem in the waste management of precast concrete (PC) building manufacture and construction and demolition wastes industry. The CE model is particularly problematic for PC building construction projects where the standard practices for the total number of waste building materials are not appropriate and do not match the safe disposal design specification, such as the recent number increase in the Malaysian illegal construction waste pile during the Movement Control Order (11 March 2021, about 5 out of 29 landfills related to states enforcing Act 672). The study aims to develop a framework application (i.e. Building Information Modelling [BIM]) that supports intelligent waste recycling management and sophisticated CE model system solutions. Design/methodology/approach: Thus, the development of a new BIM-based programming algorithm approach is proposed for optimising CE in accordance with the needs of the current PC building construction schemes. As a precursor to this study, the concepts of CE practices are reviewed and the main features of BIM tools and techniques currently being employed on such projects are presented. Findings: Sophisticated CE system solutions are described as an essential component of this optimisation to reduce the amount of waste generated at the end of the life cycle of PC building construction projects and to better manage the resources used throughout it. Originality/value: Finally, the potential for a research framework for developing such a system in the future is presented.

Publication

A DCV performance in IAQ services during COVID-19: a study of the contractor in Malaysia

(Emerald Publishing, 2025-02)

Zul-Atfi Ismail

Demand-controlled ventilation (DCV) plays a significant role in human life by providing safe, reliable and cost-effective services that are environmentally friendly and enhance occupant satisfaction and building energy efficiency. Significant decisions are made at the early stages of building sector DCV systems, requiring effective tools to avoid measurement errors and failures in Volatile Organic Compound (VOC) generation. The continuous upgrading of this sector is necessary to respond to technological advances, environmental changes and increased ventilation demands. Integrating indoor air quality (IAQ) and machine learning algorithms (MLA) proves promising, as the scope of DCV typically does not extend beyond the footprint of the building; it does not encompass IAQ within a Corona Virus Disease 2019 (COVID-19) infection risk information. Therefore, integrating IAQ with MLA provides a comprehensive overview of the building sector’s DCV systems. However, this integration poses challenges, particularly in DCV activities, as they are among the most complex systems involving numerous processes critical for making important decisions. This study aims to identify how digitalized construction environments can integrate DCV into their processes.

Publication

A disposable sensor for assessing Artocarpus Heterophyllus L. (Jackfruit) maturity

( 2003)

Maxsim Sim

;

Mohd Noor Ahmad

;

Ali Yeon Md Shakaff

;

Chang Ju

;

Chang Cheen

The purpose of this work was an attempt to monitor the ripeness process and to investigate the different maturity stages of jackfruit by chemometric treatment of the data obtained from the disposable sensor. Response of the sensor strip fabricated using screen- printing technology was analyzed using Principal Component Analysis (PCA) and the classification model constructed by means of Canonical Discriminant Analysis (CDA) enable unknown maturity stages of jackfruit to be identified. Results generated from the combination of the two classification principles show the capability and the performance of the sensor strip towards jackfruit analysis.

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Publication

A first principles study of Palladium-based full Heusler ferromagnetic Pd2MnSb compound

( 2023)

Zeshan Zada

;

Abdul Ahad Khan

;

Ali H. Reshak

;

Abdul Munam Khan

;

Shakeel S.

;

Dania Ali

;

Muhammad Ismail

;

Muhammad Mahyiddin Ramli

34 12

Publication

A Fuzzy-Based Angle-of-Arrival Estimation System (AES) using Radiation Pattern Reconfigurable (RPR) antenna and modified gaussian membership function

( 2019)

Mohd Ilman Jais

;

Thennarasan Sabapathy

;

Muzammil Jusoh

;

R. Badlishah, Ahmad

;

Mohd Haizal Jamaluddin

;

Muhammad Ramlee Kamarudin

;

Phak Len Al Eh Kan

;

L. Murukesan Loganathan

;

Soh Ping Jack

Angle-of-arrival (AOA) estimation is an important factor in various wireless sensing applications, especially localization systems. This paper proposes a new type of AOA estimation sensor node, known as AOA-estimation system (AES) where the received signal strength indication (RSSI) from multiple radiation pattern reconfigurable (RPR) antennas are used to calculate the AOA. In the proposed framework, three sets of RPR antennas have been used to provide a coverage of 15 regions of radiation patterns at different angles. The salient feature of this RPR-based AOA estimation is the use of Fuzzy Inferences System (FIS) to further enhance the number of estimation points. The introduction of a modified FIS membership function (MF) based on Gaussian function resulted in an improved 85% FIS aggregation percentage between the fuzzy input and output. This later resulted in a low AOA error (of less than 5%) and root-mean- square error (of less than 8◦ ).

1 26

Publication

A gain-enhanced multiband frequency and pattern reconfigurable antenna for Wi-Fi 6E and 5G new radio wireless standards

(John Wiley and Sons Ltd, 2024-10)

M. Ganesh

;

N. S. Raghava

;

Thennarasan Sabapathy

;

Yashna Sharma

In this paper, a multiband hybrid reconfigurable antenna with enhanced gain is reported to support Wi‐Fi 6E, indoor WLAN, and 5G new radio (NR) wireless standards. The reported structure consists of a half‐hexagonal‐shaped radiating element along with two symmetrical rectangular single‐split resonators interconnected via two PIN diodes to achieve multiband frequency and pattern reconfigurability of the proposed antenna and a single‐layer frequency selective surface (FSS) to enhance the gain. By configuring these PIN diodes in three distinct modes, the reported antenna allows for independent reconfigurability to support multipurpose sub‐6GHz and Wi‐Fi 6E (3.3, 3.5, 5.1, 5.3, and 6.5 GHz) wireless standards, respectively. The results also showed that the antenna is capable of maintaining a frequency of 6.5 GHz in all modes while reconfiguring its radiation pattern in three different directions, namely, 265°, 13°, and 337° on the xz plane. The gain of the proposed hybrid reconfigurable antenna is enhanced by an FSS‐based reflector placed below the radiating structure at a distance of to the lowest operating frequency (3.3 GHz), and the gain is enhanced by 2–4 dBi as compared without FSS. The reported hybrid reconfigurable antenna is implemented on an FR‐4 substrate with a depth of 1.6 mm and a relative permittivity of 4.4. For validation of the proposed structure, the experimental results are compared with the simulated results.

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