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Ali Yeon Md Shakaff
Preferred name
Ali Yeon Md Shakaff
Official Name
Ali Yeon, Md Shakaff
Alternative Name
Shakaff, A. Y. M.
Shakaff, A. Y.Md
Shakaff, A. Y.
Shakaff, Ali Y.M.
Main Affiliation
Scopus Author ID
8721012500
Researcher ID
DPT-4421-2022
Now showing
1 - 10 of 34
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PublicationAn Analysis of Interpolation Implementation for LNS Addition and Subtraction Function in Positive RegionInterpolation is among of the most popular approach used in approximating the values in logarithmic number system (LNS) arithmetic design. This method that often combines with lookup tables (LUTs) manages to produce efficient LNS design in area, latency and accuracy. Current research proves that the combination of interpolators with co-transformation in LNS subtraction had shown extreme improvements in terms of speed and area, which is comparable to floating point (FLP) performance. Taking the advantage, this research had been conducted to analyze the implementation of these three interpolators, which are Taylor, Lagrange and modified Lagrange, in a 32-bit environment of the LNS addition and subtraction procedures with the first-order co-transformation in positive region. The designs were analyzed in two categories, which are the accuracy towards FLP and the total memory consumption. The best interpolator was selected based on the most optimum area consumption design with manageable accuracy in FLP limit. The outcome of this analysis could benefit further improvements in LNS design.
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PublicationFeasibility analysis of indoor 3D localization system with UWB using least squares trilateration(Iran University of Science and Technology, 2025-06)
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PublicationImplementation of LNS addition and subtraction function with co-transformation in positive and negative region: A comparative analysis( 2017-01-03)
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PublicationImplementation of LNS addition and subtraction function with co-transformation in positive and negative region: A comparative analysisThe European Logarithmic Microprocessor (ELM) had been an outstanding breakthrough in logarithmic number system (LNS) research history. The processor successfully reaches the par ability of floating-point (FLP) processor with its rapid and accurate design towards FLP. The design was able to improve the LNS addition and subtraction procedure, which are the drawbacks of any implementation of LNS arithmetic. ELM's subtraction operation had adopted a unique approach, which is the first-order co-transformation to overcome the singularity-to-zero issue of the non-linear function in negative region. Therefore, this research had been introduced to extensively compare and analyze the ELM-based addition and subtraction procedures with the same co-transformation technique implemented in positive region. In achieving this, two aspects are considered, which are the accuracy towards FLP and the memory consumption of both procedures in both regions. Conclusively, the exact ELM-based implementation in positive region of both operations could be realized and achieved comparable accuracy and memory area with a slight modification of the operation procedure. The outcome of this analysis could benefit further investigation of optimizing the LNS design for hardware implementation.
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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.
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PublicationPollutant recognition based on supervised machine learning for Indoor air quality monitoring systems( 2017)
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PublicationClassifying sources influencing Indoor Air Quality (IAQ) using Artificial Neural Network (ANN)( 2015)
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PublicationPerformance analysis of the microsoft kinect sensor for 2D Simultaneous Localization and Mapping (SLAM) techniquesThis paper presents a performance analysis of two open-source, laser scanner-based Simultaneous Localization and Mapping (SLAM) techniques (i.e., Gmapping and Hector SLAM) using a Microsoft Kinect to replace the laser sensor. Furthermore, the paper proposes a new system integration approach whereby a Linux virtual machine is used to run the open source SLAM algorithms. The experiments were conducted in two different environments; a small room with no features and a typical office corridor with desks and chairs. Using the data logged from real-time experiments, each SLAM technique was simulated and tested with different parameter settings. The results show that the system is able to achieve real time SLAM operation. The system implementation offers a simple and reliable way to compare the performance of Windows-based SLAM algorithm with the algorithms typically implemented in a Robot Operating System (ROS). The results also indicate that certain modifications to the default laser scanner-based parameters are able to improve the map accuracy. However, the limited field of view and range of Kinect's depth sensor often causes the map to be inaccurate, especially in featureless areas, therefore the Kinect sensor is not a direct replacement for a laser scanner, but rather offers a feasible alternative for 2D SLAM tasks.
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PublicationClassification of agarwood oil using an electronic nosePresently, the quality assurance of agarwood oil is performed by sensory panels which has significant drawbacks in terms of objectivity and repeatability. In this paper, it is shown how an electronic nose (e-nose) may be successfully utilised for the classification of agarwood oil. Hierarchical Cluster Analysis (HCA) and Principal Component Analysis (PCA), were used to classify different types of oil. The HCA produced a dendrogram showing the separation of e-nose data into three different groups of oils. The PCA scatter plot revealed a distinct separation between the three groups. An Artificial Neural Network (ANN) was used for a better prediction of unknown samples.
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PublicationLabview™ for Nutra-Biostrip in Herbal Quality Assessment( 2004)
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