Ali Yeon Md Shakaff
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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

Research Output
Now showing 1 - 10 of 34
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Publication

An Analysis of Interpolation Implementation for LNS Addition and Subtraction Function in Positive Region

2016 , Siti Zarina Md Naziri , Rizalafande Che Ismail , Ali Yeon Md Shakaff

Interpolation 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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Implementation of LNS addition and subtraction function with co-transformation in positive and negative region: A comparative analysis

2016 , Siti Zarina Md Naziri , Rizalafande Che Ismail , Ali Yeon Md Shakaff

The 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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Classifying sources influencing Indoor Air Quality (IAQ) using Artificial Neural Network (ANN)

2015 , Shaharil Mad Saad , Allan Melvin Andrew , Ali Yeon Md Shakaff , Abdul Rahman Mohd Saad , Azman Muhamad Yusof @ Kamarudin , Ammar Zakaria

Monitoring indoor air quality (IAQ) is deemed important nowadays. A sophisticated IAQ monitoring system which could classify the source influencing the IAQ is definitely going to be very helpful to the users. Therefore, in this paper, an IAQ monitoring system has been proposed with a newly added feature which enables the system to identify the sources influencing the level of IAQ. In order to achieve this, the data collected has been trained with artificial neural network or ANN—a proven method for pattern recognition. Basically, the proposed system consists of sensor module cloud (SMC), base station and service-oriented client. The SMC contain collections of sensor modules that measure the air quality data and transmit the captured data to base station through wireless network. The IAQ monitoring system is also equipped with IAQ Index and thermal comfort index which could tell the users about the room’s conditions. The results showed that the system is able to measure the level of air quality and successfully classify the sources influencing IAQ in various environments like ambient air, chemical presence, fragrance presence, foods and beverages and human activity.

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Labview™ for Nutra-Biostrip in Herbal Quality Assessment

2004 , Mohd Noor Ahmad , Maxsim Yap Mee Sim , Mohd Kamal Mohamed Ramly Nil , Ali Yeon Md Shakaff , Chang Chew Cheen

In this work, we introduce the approach on the development of a stand-alone laptop based data acquisition of an array sensor system, namely Nutra-BioStrip coupled with pattern recognition algorithm for herbal quality assessment. The array sensor system control program, developed in Lab View 6. 1 programming languages allow data acquired from the array sensor to be analyzed by means of Principal Component Analysis (PCA) and displayed in the form of an interactive twodimensional cluster mapping with detail statistical analysis results for rapid and real-time herbal quality assessment.

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Feasibility analysis of indoor 3D localization system with UWB using least squares trilateration

2025-06 , Syed Muhammad Mamduh Syed Zakaria , Ammar Zakaria , Latifah Munirah Kamarudin , Ali Yeon Md Shakaff , Muhamad Naqib Mohd Shukri

Accurate 3D Localization is very important for a wide range of applications, such as indoor navigation, industrial robotics, and motion tracking. This research focuses on indoor 3D positioning systems using ultra-wideband (UWB) devices. Two localization experiments were conducted using the Least Squares Trilateration method. In the first experiment, anchors were at the same height, while in the second, they were at varying heights. The lowest percentage errors in the first experiment were 0% at the x-axis, 0.21% at the y-axis, and 19.75% at the z-axis. In the second experiment, the lowest percentage errors in the experiment were 1.98% at the x-axis, 0.68% at the y-axis, and 17.86% at the z-axis, demonstrating improved accuracy with varied anchor heights at the axis. This work shows the z-axis measurements are unreliable and noisy due to the limited intersection of signal waves of each anchor in a same height anchors setup.

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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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Performance analysis of the microsoft kinect sensor for 2D Simultaneous Localization and Mapping (SLAM) techniques

2014 , Kamarulzaman Kamarudin , Syed Muhammad Mamduh Syed Zakaria , Ali Yeon Md Shakaff , Ammar Zakaria

This 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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Implementation of LNS addition and subtraction function with co-transformation in positive and negative region: A comparative analysis

2017-01-03 , Siti Zarina Md Naziri , Rizalafande Che Ismail , Ali Yeon Md Shakaff

The 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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Pollutant recognition based on supervised machine learning for Indoor air quality monitoring systems

2017 , Shaharil Mad Saad , Allan Melvin Andrew , Ali Yeon Md Shakaff , Mohd Mat Dzahir , Mohamed Hussein , Maziah Mohamad , Zair Ahmad

Indoor air may be polluted by various types of pollutants which may come from cleaning products, construction activities, perfumes, cigarette smoke, water-damaged building materials and outdoor pollutants. Although these gases are usually safe for humans, they could be hazardous if their amount exceeded certain limits of exposure for human health. A sophisticated indoor air quality (IAQ) monitoring system which could classify the specific type of pollutants is very helpful. This study proposes an enhanced indoor air quality monitoring system (IAQMS) which could recognize the pollutants by utilizing supervised machine learning algorithms: multilayer perceptron (MLP), K-nearest neighbour (KNN) and linear discrimination analysis (LDA). Five sources of indoor air pollutants have been tested: ambient air, combustion activity, presence of chemicals, presence of fragrances and presence of food and beverages. The results showed that the three algorithms successfully classify the five sources of indoor air pollution (IAP) with a classification rate of up to 100 percent. An MLP classifier with a model structure of 9-3-5 has been chosen to be embedded into the IAQMS. The system has also been tested with all sources of IAP presented together. The result shows that the system is able to classify when single and two mixed sources are presented together. However, when more than two sources of IAP are presented at the same period, the system will classify the sources as ‘unknown’, because the system cannot recognize the input of the new pattern.

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Classification of agarwood oil using an electronic nose

2010 , Wahyu Hidayat , Ali Yeon Md Shakaff , Mohd Noor Ahmad , Abdul Hamid Adom

Presently, 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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