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 32
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Publication

Signal propagation analysis for low data rate wireless sensor network applications in sport grounds and on roads

2012 , David L. Ndzi , M. A. Mohd Arif , Ali Yeon Md Shakaff , Mohd Noor Ahmad , Azizi Harun , Latifah Munirah Kamarudin , Ammar Zakaria , Mohd F. Ramli , Mohammad Shahrazel Razalli

This paper presents results of a study to characterise wire- less point-to-point channel for wireless sensor networks applications in sport hard court arenas, grass fields and on roads. Antenna height and orientation effects on coverage are also studied and results show that for omni-directional patch antenna, node range is reduced by a factor of 2 when the antenna orientation is changed from vertical to horizontal. The maximum range for a wireless node on a hard court sport arena has been determined to be 70m for 0dBm transmission but this reduces to 60m on a road surface and to 50m on a grass field. For horizontal antenna orientation the range on the road is longer than on the sport court which shows that scattered signal components from the rougher road surface combine to extend the communication range. The channels investigated showed that packet error ratio (PER) is dominated by large-scale, rather than small-scale, channel fading with an abrupt transition from low PER to 100% PER. Results also show that large-scale received signal power can be modeled with a 2nd or der log-distance polynomial equation on the sport court and road, but a 1st order model is sufficient for the grassfield. Small-scale signal variations have been found to have a Rice distribution for signal to noise ratio levels greater than 10 dB but the Rice K-factor exhibits significant variations at short distances which can be attributed to the influence of strong ground reflections.

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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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Improved classification of orthosiphon stamineus by data fusion of electronic nose and tongue sensors

2010 , Ammar Zakaria , Ali Yeon Md Shakaff , Abdul Hamid Adom , Mohd Noor Ahmad , Masnan, Maz Jamilah , Abdul Hallis Abdul Aziz , Nazifah Ahmad Fikri , Abu Hassan Abdullah , Latifah Munirah Kamarudin

An improved classification of Orthosiphon stamineus using a data fusion technique is presented. Five different commercial sources along with freshly prepared samples were discriminated using an electronic nose (e-nose) and an electronic tongue (e-tongue). Samples from the different commercial brands were evaluated by the e-tongue and then followed by the e-nose. Applying Principal Component Analysis (PCA) separately on the respective e-tongue and e-nose data, only five distinct groups were projected. However, by employing a low level data fusion technique, six distinct groupings were achieved. Hence, this technique can enhance the ability of PCA to analyze the complex samples of Orthosiphon stamineus. Linear Discriminant Analysis (LDA) was then used to further validate and classify the samples. It was found that the LDA performance was also improved when the responses from the e-nose and e-tongue were fused together.

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Wireless sensor network coverage measurement and planning in mixed crop farming

2014-04-17 , David L. Ndzi , Azizi Harun , Fitri M. Ramli , Latifah Munirah Kamarudin , Ammar Zakaria , Ali Yeon Md Shakaff , Mahmad N. Jaafar , Shikun Zhou , Rohani S Mohamed Farook

Wireless sensor network technology holds great promise for application in a wide range of areas, both to monitor and control a variety of systems. Whilst the use of sensors has found natural applications within the manufacturing sector, application in agriculture is still in its infancy and has been used largely to only monitor the environment. The use of technology in the agricultural sector to improve crop yield, quality and to foster sustainable agriculture can be regarded as one of the areas that will provide food security to the expanding global population and to mitigate food shortage precipitated by unpredictable weather patterns. This paper presents a Wireless Sensor Network coverage measurements in a mixed crop farming, modeling and deployment architecture taking into account the different signal propagation scenarios and attenuation factor of different crops. Most importantly, the paper presents wireless sensor network deployment architecture for a mixed crop trial field over an area of 54,432m2 , which is 4% of the total area to be covered by the final network.

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Arithmetic addition and subtraction function of logarithmic number system in positive region: An investigation

2015 , Siti Zarina Md Naziri , Rizalafande Che Ismail , Ali Yeon Md Shakaff

Logarithmic number system or LNS has become an optimal choice in digital image processing instead of floating point (FP) system based on latest researches in LNS. Digital image processing which deals with a lot of complex operations such as multiplication and division, makes LNS as a great choice of implementation. However, the implementation had been restricted by the addition and subtraction function in LNS arithmetic as these functions entail complex procedures and circuitry. As its huge potential to be a substitution of FP, there is an urgent need for LNS to improve the performance of both operations. Hence, various studies had been conducted in this area, however most of the research concern the implementation of these operations in the negative region. Therefore, this study is conducted with the objective on the exploration of both LNS addition and subtraction operations in the positive region and highlights the potential areas for design modifications and improvements. Then, these enhancements will be combined with other arithmetic functions in creating an optimum LNS design to be utilized in any digital image processing system.

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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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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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The design revolution of logarithmic number system architecture

2014 , Siti Zarina Md Naziri , Rizalafande Che Ismail , Ali Yeon Md Shakaff

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Development of multichannel artificial lipid-polymer membrane sensor for phytomedicine application

2006 , Mohd Noor Ahmad , Zhari Ismail , Oon–Sim Chew , AKM Islam , Ali Yeon Md Shakaff

Quality control of herbal medicines remain a challenging issue towards integrating phytomedicine into the primary health care system. As medicinal plants is a complicated system of mixtures, a rapid and cost-effective evaluation method to characterize the chemical fingerprint of the plant without performing laborious sample preparation procedure is reported. A novel research methodology based on an in-house fabricated multichannel sensor incorporating an array of artificial lipid-polymer membrane as a fingerprinting device for quality evaluation of a highly sought after herbal medicine in the Asean Region namely Eurycoma longifolia (Tongkat Ali). The sensor array is based on the principle of the bioelectronic tongue that mimics the human gustatory system through the incorporation of artificial lipid material as sensing element. The eight non-specific sensors have partially overlapping selectivity and cross-sensitivity towards the targeted analyte. Hence, electrical potential response represented by radar plot is used to characterize extracts from different parts of plant, age, batch-to-batch variation and mode of extraction of E. longifolia through the obtained potentiometric fingerprint profile. Classification model was also developed classifying various E. longifolia extracts with the aid of chemometric pattern recognition tools namely hierarchical cluster analysis (HCA) and principal component analysis (PCA). The sensor seems to be a promising analytical device for quality control based on potentiometric fingerprint analysis of phytomedicine.

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