Browsing by Type "journal-article"
Results Per Page
Sort Options
-
Publication2-SAT discrete Hopfield neural networks optimization via Crow search and fuzzy dynamical clustering approach( 2024)
;Caicai Feng ;Saratha SathasivamMuraly Velavan<abstract> <p>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.</p> </abstract> -
Publication2D LiDAR based reinforcement learning for Multi-Target path planning in unknown environment( 2023)
;Nasr AbdalmananGlobal 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.11 26 -
PublicationA Bio-Inspired herbal tea flavour assessment techniqueHerbal-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.
-
PublicationA biomimetic sensor for the classification of honeys of different floral origin and the detection of adulteration( 2011-08)
;Norazian Subari ;Nazifah Ahmad Fikri ;Mohd Noor Ahmad ;Mahmad Nor JaafarSupri A. GhaniThe 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.18 19 -
PublicationA disposable sensor for assessing Artocarpus Heterophyllus L. (Jackfruit) maturity( 2003)
;Maxsim Sim ;Mohd Noor Ahmad ;Chang JuChang CheenThe 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.2 11 -
PublicationA 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 -
PublicationA Fuzzy-Based Angle-of-Arrival Estimation System (AES) using Radiation Pattern Reconfigurable (RPR) antenna and modified gaussian membership function( 2019)
;R. Badlishah, Ahmad ;Mohd Haizal Jamaluddin ;Muhammad Ramlee Kamarudin ;L. Murukesan LoganathanSoh Ping JackAngle-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 11 -
PublicationA heuristic ranking approach on capacity benefit margin determination using pareto-based evolutionary programming technique( 2015)
;Muhammad Murtadha Othman ;Ismail Musirin ;Mahmud Fotuhi-FiruzabadAbbas Rajabi-GhahnaviehThis paper introduces a novel multiobjective approach for capacity benefit margin (CBM) assessment taking into account tie-line reliability of interconnected systems. CBM is the imperative information utilized as a reference by the load-serving entities (LSE) to estimate a certain margin of transfer capability so that a reliable access to generation through interconnected system could be attained. A new Pareto-based evolutionary programming (EP) technique is used to perform a simultaneous determination of CBM for all areas of the interconnected system. The selection of CBM at the Pareto optimal front is proposed to be performed by referring to a heuristic ranking index that takes into account system loss of load expectation (LOLE) in various conditions. Eventually, the power transfer based available transfer capability (ATC) is determined by considering the firm and nonfirm transfers of CBM. A comprehensive set of numerical studies are conducted on the modified IEEE-RTS79 and the performance of the proposed method is numerically investigated in detail. The main advantage of the proposed technique is in terms of flexibility offered to an independent system operator in selecting an appropriate solution of CBM simultaneously for all areas.4 10 -
PublicationA hybrid approach of knowledge-driven and data-driven reasoning for activity recognition in smart homes( 2019)
;Rossi SetchiHiromitsu NishizakiAccurate activity recognition plays a major role in smart homes to provide assistance and support for users, especially elderly and cognitively impaired people. To realize this task, knowledge-driven approaches are one of the emerging research areas that have shown interesting advantages and features. However, several limitations have been associated with these approaches. The produced models are usually incomplete to capture all types of human activities. This resulted in the limited ability to accurately infer users’ activities. This paper presents an alternative approach by combining knowledge-driven with data-driven reasoning to allow activity models to evolve and adapt automatically based on users’ particularities. Firstly, a knowledge-driven reasoning is presented for inferring an initial activity model. The model is then trained using data-driven techniques to produce a dynamic activity model that learns users’ varying action. This approach has been evaluated using a publicly available dataset and the experimental results show the learned activity model yields significantly higher recognition rates compared to the initial activity model.19 16 -
PublicationA hybrid sensing approach for pure and adulterated honey classification( 2012)
;Norazian Subari ;Junita Mohamad SalehThis paper presents a comparison between data from single modality and fusion methods to classify Tualang honey as pure or adulterated using Linear Discriminant Analysis (LDA) and Principal Component Analysis (PCA) statistical classification approaches. Ten different brands of certified pure Tualang honey were obtained throughout peninsular Malaysia and Sumatera, Indonesia. Various concentrations of two types of sugar solution (beet and cane sugar) were used in this investigation to create honey samples of 20%, 40%, 60% and 80% adulteration concentrations. Honey data extracted from an electronic nose (e-nose) and Fourier Transform Infrared Spectroscopy (FTIR) were gathered, analyzed and compared based on fusion methods. Visual observation of classification plots revealed that the PCA approach able to distinct pure and adulterated honey samples better than the LDA technique. Overall, the validated classification results based on FTIR data (88.0%) gave higher classification accuracy than e-nose data (76.5%) using the LDA technique. Honey classification based on normalized low-level and intermediate-level FTIR and e-nose fusion data scored classification accuracies of 92.2% and 88.7%, respectively using the Stepwise LDA method. The results suggested that pure and adulterated honey samples were better classified using FTIR and e-nose fusion data than single modality data.2 8 -
PublicationA new method of rice moisture content determination using voxel weighting-based from radio tomography images( 2021)
;Nurul Amira Mohd Ramli ;Anita AhmadRuzairi Abdul RahimThis manuscript presents a new method to monitor and localize the moisture distribution in a rice silo based on tomography images. Because the rice grain is naturally hygroscopic, the stored grains’ quality depends on their level of moisture content. Higher moisture content leads to fibre degradation, making the grains too frail and possibly milled. If the moisture is too low, the grains become brittle and are susceptible to higher breakage. At present, the single-point measurement method is unreliable because the moisture build-up inside the silo might be distributed unevenly. In addition, this method mostly applies gravimetric analysis, which is destructive. Thus, we proposed a radio tomographic imaging (RTI) system to address these problems. Four simulated phantom profiles at different percentages of moisture content were reconstructed using Newton’s One-Step Error Reconstruction and Tikhonov Regularization algorithms. This simulation study utilized the relationship between the maximum voxel weighting of the reconstructed RTI image and the percentage of moisture content. The outcomes demonstrated promising results, in which the weighting voxel linearly increased with the percentage of moisture content, with a correlation coefficient higher than 0.95 was obtained. Therefore, the results support the possibility of using the RTI approach for monitoring and localizing the moisture distribution inside the rice silo.4 6 -
PublicationA novel disposable biosensor based on SiNWs/AuNPs modified-screen printed electrode for dengue virus DNA oligomer detection( 2015)
;Jahwarhar Izuan Abd Rashid ;Nor Azah Yusof ;Jaafar AbdullahReza HajianIn this paper, a disposable screen-printed gold electrode (SPGE) utilized of silicon nanowires (SiNWs) and gold nanoparticles as sensing material was fabricated for detection of DNA oligomers related to dengue virus. First, SiNWs/AuNPs-SPGE was developed by the dispersion of SiNWs in 3-aminopropyltriethoxysilane (0.5%) onto bare SPGE. Second, the AuNPs decoration on SiNWs-SPGE surface was functionalized using dithiopropionic acid through a self-assembly monolayer technique. The electrochemical response of methylene blue (MB) as a redox indicator toward synthetic DNA oligomer after hybridization on SiNWs/AuNPs-SPGE was recorded by cyclic voltammetry and differential pulse voltammetry techniques. The results demonstrated that the reduction peak current of MB was significantly decreased after DNA hybridization process. In addition, the developed biosensor showed a good storage stability and could achieve a linear range of 1 × 10−11 − 1 × 10−7 M (R = 0.98) with the detection limit of 1.63 × 10−12 M.3 9 -
PublicationA patch antenna with enhanced gain and bandwidth for sub-6 GHz and sub-7 GHz 5G wireless applications(MDPI, 2023)
;Shehab Khan Noor ;Ali Hanafiah Rambe ;Hamsakutty Vettikalladi ;Ali M. AlbishiMohamed HimdiThis paper presents a novel microstrip patch antenna design using slots and parasitic strips to operate at the n77 (3.3–4.2 GHz)/n78 (3.3–3.8 GHz) band of sub-6 GHz and n96 (5.9–7.1 GHz) band of sub-7 GHz under 5G New Radio. The proposed antenna is simulated and fabricated using an FR-4 substrate with a relative permittivity of 4.3 and copper of 0.035 mm thickness for the ground and radiating planes. A conventional patch antenna with a slot is also designed and fabricated for comparison. A comprehensive analysis of both designs is carried out to prove the superiority of the proposed antenna over conventional dual-band patch antennas. The proposed antenna achieves a wider bandwidth of 160 MHz at 3.45 GHz and 220 MHz at 5.9 GHz, with gains of 3.83 dBi and 0.576 dBi, respectively, compared to the conventional patch antenna with gains of 2.83 dBi and 0.1 dBi at the two frequencies. Parametric studies are conducted to investigate the effect of the parasitic strip’s width and length on antenna performance. The results of this study have significant implications for the deployment of high-gain compact patch antennas for sub-6 GHz and sub-7 GHz 5G wireless communications and demonstrate the potential of the proposed design to enhance performance and efficiency in these frequency bands. -
PublicationA Point-of-Care immunosensor for human chorionic gonadotropin in clinical urine samples using a cuneated polysilicon nanogap Lab-on-Chip( 2015)
;S. R. Balakrishnan ;H. R. Ramayya ;M. Iqbal Omar ;R. HaarindraprasadP. VeeradasanHuman chorionic gonadotropin (hCG), a glycoprotein hormone secreted from the placenta, is a key molecule that indicates pregnancy. Here, we have designed a cost-effective, label-free, in situ point-of-care (POC) immunosensor to estimate hCG using a cuneated 25 nm polysilicon nanogap electrode. A tiny chip with the dimensions of 20.5 × 12.5 mm was fabricated using conventional lithography and size expansion techniques. Furthermore, the sensing surface was functionalized by (3-aminopropyl)triethoxysilane and quantitatively measured the variations in hCG levels from clinically obtained human urine samples. The dielectric properties of the present sensor are shown with a capacitance above 40 nF for samples from pregnant women; it was lower with samples from non-pregnant women. Furthermore, it has been proven that our sensor has a wide linear range of detection, as a sensitivity of 835.88 μA mIU-1 ml-2 cm-2 was attained, and the detection limit was 0.28 mIU/ml (27.78 pg/ml). The dissociation constant Kd of the specific antigen binding to the anti-hCG was calculated as 2.23 ± 0.66 mIU, and the maximum number of binding sites per antigen was Bmax = 22.54 ± 1.46 mIU. The sensing system shown here, with a narrow nanogap, is suitable for high-throughput POC diagnosis, and a single injection can obtain triplicate data or parallel analyses of different targets. -
PublicationA portable automatic endpoint detection system for amplicons of loop mediated isothermal amplification on microfluidic compact disk platform( 2015)
;Shah Uddin ;Fatimah Ibrahim ;Abkar Sayad ;Aung Thiha ;Koh Pei ;Mas Mohktar ;Jongman ChoKwai ThongIn recent years, many improvements have been made in foodborne pathogen detection methods to reduce the impact of food contamination. Several rapid methods have been developed with biosensor devices to improve the way of performing pathogen detection. This paper presents an automated endpoint detection system for amplicons generated by loop mediated isothermal amplification (LAMP) on a microfluidic compact disk platform. The developed detection system utilizes a monochromatic ultraviolet (UV) emitter for excitation of fluorescent labeled LAMP amplicons and a color sensor to detect the emitted florescence from target. Then it processes the sensor output and displays the detection results on liquid crystal display (LCD). The sensitivity test has been performed with detection limit up to 2.5 × 10−3 ng/µL with different DNA concentrations of Salmonella bacteria. This system allows a rapid and automatic endpoint detection which could lead to the development of a point-of-care diagnosis device for foodborne pathogens detection in a resource-limited environment.4 42 -
PublicationA potentiometric indirect uric acid sensor based on ZnO nanoflakes and immobilized uricase( 2012)
;Syed M. Usman Ali ;Zafar Hussain Ibupoto ;Muhammad KashifMagnus WillanderIn the present work zinc oxide nanoflakes (ZnO-NF) structures with a wall thickness around 50 to 100 nm were synthesized on a gold coated glass substrate using a low temperature hydrothermal method. The enzyme uricase was electrostatically immobilized in conjunction with Nafion membrane on the surface of well oriented ZnO-NFs, resulting in a sensitive, selective, stable and reproducible uric acid sensor. The electrochemical response of the ZnO-NF-based sensor vs. a Ag/AgCl reference electrode was found to be linear over a relatively wide logarithmic concentration range (500 nM to 1.5 mM). In addition, the ZnO-NF structures demonstrate vast surface area that allow high enzyme loading which results provided a higher sensitivity. The proposed ZnO-NF array-based sensor exhibited a high sensitivity of ~66 mV/ decade in test electrolyte solutions of uric acid, with fast response time. The sensor response was unaffected by normal concentrations of common interferents such as ascorbic acid, glucose, and urea1 8 -
PublicationA proposed aerobic granules size development scheme for aerobic granulation process( 2015-04)
;Norhayati Abdullah ;Ali Yuzir ;Gustaf Olsson ;Myzairah Salmiati ;Mohd Fadhil Mohd Hamdzah ;Siti Aqlima Din ;Khalilah Abdul Ahmad ;Aznah Nor Khalil ;Zainura Zainon AnuarZaini NoorAerobic granulation is increasingly used in wastewater treatment due to its unique physical properties and microbial functionalities. Granule size defines the physical properties of granules based on biomass accumulation. This study aims to determine the profile of size development under two physicochemical conditions. Two identical bioreactors namely Rnp and Rp were operated under non-phototrophic and phototrophic conditions, respectively. An illustrative scheme was developed to comprehend the mechanism of size development that delineates the granular size throughout the granulation. Observations on granules’ size variation have shown that activated sludge revolutionised into the form of aerobic granules through the increase of biomass concentration in bioreactors which also determined the changes of granule size. Both reactors demonstrated that size transformed in a similar trend when tested with and without illumination. Thus, different types of aerobic granules may increase in size in the same way as recommended in the aerobic granule size development scheme. -
PublicationA reconfigurable WiMAX antenna for directional and broadside application( 2013-04-25)
;M. F. Jamlos ;M. R. KamarudinA novel reconfigurable compact patch array antenna for directional and broadside application is proposed. The presented antenna has successfully been able to function for directional beam at 320° or 35° and divisive broadside beam at 43° and 330°. This is realized in the unique form of aperture coupled spiral feeding technique and positioning of the radiating elements at 0°, 90,° and 180°. The switchable feature is effectively performed by the configuration of three PIN diodes. All PIN diodes are positioned at the specific location of the aperture coupled structure. It is discovered in simulation that the switches can be represented with a copper strip line or touchstone (TS) block . The proposed antenna design operates at 2.37 GHz to 2.41 GHz and has a maximum gain of 6.4 dB and efficiency of 85.97%. Such antenna produces a broadside HPBW with a wider bandwidth covering from −90° to 90° compared to the normal microstrip antenna which could only provide HPBW of −50° to 50°. Moreover, the proposed antenna has small physical dimension of 100 mm by 100 mm. The simulation and measurement results have successfully exhibited the idea of the presented antenna performance. Therefore, the antenna is sufficiently competent in the smart WiMAX antenna application.9 9 -
PublicationA Review of Antennas for Picosatellite Applications( 2017)
;Abdul Halim Lokman ;Ping Jack Soh ;Herwansyah Lago ;Symon K. Podilchak ;Suramate Chalermwisutkul ;Mohd Faizal Jamlos ;Prayoot AkkaraekthalinSteven GaoCube Satellite (CubeSat) technology is an attractive emerging alternative to conventional satellites in radio astronomy, earth observation, weather forecasting, space research, and communications. Its size, however, poses a more challenging restriction on the circuitry and components as they are expected to be closely spaced and very power efficient. One of the main components that will require careful design for CubeSats is their antennas, as they are needed to be lightweight, small in size, and compact or deployable for larger antennas. This paper presents a review of antennas suitable for picosatellite applications. An overview of the applications of picosatellites will first be explained, prior to a discussion on their antenna requirements. Material and antenna topologies which have been used will be subsequently discussed prior to the presentation of several deployable configurations. Finally, a perspective and future research work on CubeSat antennas will be discussed in the conclusion. -
PublicationA Review of Genetic Algorithm: Operations and Applications( 2024)This article presents a review of the Genetic Algorithm (GA), a prominent optimization technique inspired by natural selection and genetics. In the context of rapidly evolving computational methodologies, GA have gained considerable attention for their efficacy in solving complex optimization problems across various domains. The background highlights the growing significance of optimization techniques in addressing real-world challenges. However, the inherent complexity and diversity of problems necessitate versatile approaches like GA. The problem statement underscores the need to explore the underlying operations and applications of GA to provide a nuanced understanding of their capabilities and limitations. The objectives of this review encompass delving into the fundamental genetic operators, such as selection, crossover, and mutation, while examining their role in maintaining diversity and converging toward optimal solutions. Methodology-wise, a systematic analysis of existing literature is undertaken to distil key insights and trends in GA applications. The main findings show the adaptability of GA in tackling problems spanning engineering, economics, bioinformatics, and beyond. By facilitating the discovery of optimal or near-optimal solutions within large solution spaces, GA proves its mettle in scenarios where traditional methods fall short. The conclusion underscores the enduring relevance of GA in the optimization landscape, emphasizing their potential to remain a pivotal tool for addressing intricate real-world challenges, provided their parameters are fine-tuned judiciously to balance exploration and exploitation.