Hadzli Hashim

Classification of Rubber Tree Leaf Diseases Using Multilayer Perceptron Neural Network

This paper presents about classification of rubber tree leaf diseases through automation and utilizing primary RGB color model. Several rubber tree leaf diseases are been studied for digital RGB color extraction where three sets of rubber tree leaf diseases image are digitally captured under standard and control environment. The identified regions of interest (ROI) of these diseases images are then processed to quantify the normalized indices from the RGB color distribution. This system involved the process of image classification by using artificial neural network where 600 samples were used as training while another 200 samples were for testing. The optimized ANN model in this work has two method which based only on the dominant pixel RGB (mean) and applying principle component analysis (PCA) on the pixel gradation values of each image. The optimized model was evaluated and validated through analysis of the performance indicators. Findings in this work have shown that both models have produced about 70% in diagnostic accuracy with more than 80% achievement for sensitivity. However, model with the applied PCA has lower network size.

Development of Novel Data Compression Technique for Accelerate DNA Sequence Alignment Based on SmithWaterman Algorithm

This paper presents the development of high performance accelerating technique for DNA sequences alignment. The scope of the paper focuses on speed optimization and memory reduction of the existing technique on initialization module. The novel development of the optimization using data compression technique for accelerates the Smith-Waterman (SW) algorithm has been revealed through this paper. This technique has been implemented on hardware based acceleration device. The development is targeted to Altera Cyclone II 2C70 FPGA and using 50MHz oscillator. The code is written in verilog HDL syntax using Quartus 2 version 7.2 and the simulation is verified using Quartus 2 version 7.2 simulator tool. The theoretical analysis and simulation result based on implementation of the design using FPGA are presented and well organized in this paper. The comparative study based on theoretical and simulation results of this technique has been made to accomplish result of analysis. The compilation result for data compression technique development of SW algorithm consisting of 73 logic elements with 93.75% reduction in memory space requirement.

Study on electrical properties of Zinc Oxide thin film

This project focuses on the effect of annealing temperature to electrical properties of deposited Zinc Oxide (ZnO) thin film. ZnO solutions made from Zinc acetate dehydrate (ZnAC), 2-Methoxyethanol and monoethanolmine (MEA) are deposited onto glass substrates using spin coating technique. Deposited films are annealed at various temperatures from 350degC to 500degC in the furnace (Preterm Furnace) for 1 hour. The effect of annealing temperature on the electrical properties is investigated. The electrical properties are characterized using Current-Voltage (I-V) measurement unit (Advantest R6243). I-V characterization shows the films exhibited ohmic contact and the resistivity decreased when annealing temperature increased. This indicates that the electrical properties of the films improved with higher annealing temperature up to 500degC.

Deploying Internet Protocol version 6 (IPv6) over Internet Protocol version 4 (IPv4) tunnel

Internet Protocol version 6 (IPv6) or IP next generation is the protocol that has been designed to replace the existing Internet Protocol version 4 (IPv4). These two protocols are expected to coexist for a number of years during the transition period. A number of IPv4-to-IPv6 transition tools are available to address the various needs of different networks. The two most basic transition tools available are the hybrid stack mechanism and tunneling. A hybrid or dual stack host, implements both IPv4 and IPv6, usually in a single stack in which most of the code is shared by the two protocols. Tunneling is the encapsulation of IPv6 traffic within IPv4 packets so they can be sent over an IPv4 infrastructure, allowing IPv6 hosts and routers to communicate without the need to upgrade the IPv4 infrastructure that exists between them. This paper looks at how tunneling can be performed over existing internetwork infrastructure.

Optimization of DNA Sequences Data to Accelerate DNA Sequence Alignment on FPGA

This paper presents the design and development of high performance accelerating and optimization technique for accelerate the process of DNA sequences alignment. The scope of the paper focuses on memory and speed optimization by optimizing and mapping the DNA sequences data before alignment. This optimization technique is designed based on novel data compression technique in optimizing the numbers of data transmitted from computer to DNA sequences alignment accelerator. Consequently, the numbers of data per serial data transmission for alignment can be optimize and accelerate up to 400% greater than conventional DNA sequences alignment accelerator system. This technique has been design and implemented on hardware based acceleration device and targeted to Altera Cyclone II 2C70 FPGA and using 50MHz oscillator for clock source. The code is written in verilog HDL syntax using Quartus 2 version 7.2 and the simulation is verified using Quartus 2 version 7.2 simulator tools. As a result, the theoretical analysis, simulation and implementation result based on development and implementation of the proposed design on FPGA are presented and well organized in this paper. The comparative study based on theoretical, simulation and implementation results of this technique has been made to accomplish result of analysis.

Video quality of service in Diffserv-aware multiprotocol label switching network

The current trend set by service providers of enhancing the degree of provisions in IP networks while maintaining the optimum quality, has promoted many research activities. These activities include those which aim to introduce improved quality of services for popular Internet services and applications. In this paper, quality of services (QoS) of video transmission on Differentiated Services (DiffServ) with multiprotocol label switching (MPLS) network is being simulated and evaluated by a network Simulator, OPNET. The need of integration of MPLS with DiffServ particularly for the video traffic has been demonstrated in the simulation. The objective of this work is to study the influence of the QoS mechanism via DiffServ-MPLS on network parameters such as packet loss, delay and throughput for different video resolutions. The comprehensive study showed general improvement in the throughput and packet loss particularly of video transmission when using DiffServ-aware MPLS network as compared to when only MPLS or DiffServ is employed.

Outcome Based Education Performance Evaluation on Electrical Engineering laboratory module

Implementing Outcome Based Education (OBE) in evaluating program outcomes is a standard practice nowadays at the Faculty of Electrical Engineering (FEE), Universiti Teknologi MARA (UiTM). Previously, laboratory assessments method was merely based only on lab report submitted by each group of students and the procedure is inconsistence as each module consists of different area of electrical engineering fields and involves many lecturers from various disciplines in the FEE. Furthermore, there were no specific guidelines for grading the report and lecturers would rely on their experiences, resulting large variance of judgments in giving the marks. To overcome such problem, an OBE assessment tool known as Laboratory Sensor Performance Evaluation Course Tool (LAB-SPECT) has been designed recently for evaluating laboratory modules. This tool has taken into account additional students attributes that represents teamwork skill, practical skill and ethical in the lab. With rubrics table provided, it has successfully facilitated lecturers to evaluate students fairly in terms of their Group Related Skills (GRS) besides than the laboratory report. Each of the assessment section in this process is addressing the respective the course outcome (CO) and program outcome (PO). The output plots produced by this tool would be used as indicators for Continual Quality Improvement (CQI) recommendations.

A statistical approach for orchid disease identification using RGB color

This paper presented a statistical approach for recognition of orchid diseases using RGB color analysis. As for features, the scale infection and black leaf spot disease of the orchid have been chosen in this study. Orchid plant with these two category disease samples were taken from a local home orchid collector and captured using digital camera in a controlled environment. The RGB components are extracted as features and statistical analysis specifically error plot and T-Test are utilized for differentiation between orchid either with scale or black leaf spot disease. Initial findings showed that the proposed method is capable to differentiate these two category diseases.

Classification of Rubber Tree Leaf Disease Using Spectrometer

In this paper, the classification of five types of rubber leaf disease by using the spectrometer and SPSS are presented. There are five of leaf disease that have been used as samples which are Oidium secondary leaf fall, Fusicoccum Leaf Blight, Bird eye’s spot and Anthracnose. The reflectance of the infected leaves sample is measured by using MCS600 Carl Zeiss spectrometer. Besides, Aspect Plus, a universal spectroscopy program from Zeiss manages to measure the spectral regions of the leaves sample. Further analysis and justification are completed by using approximate statistical tools from SPSS. The results obtained show that there are strong evidences that these diseases can be discriminated from each other using a spectrometer.

An Intelligent Classification Model for Rubber Seed Clones Based on Shape Features through Imaging Techniques

This paper describes research work in developing an intelligent model for classifying selected rubber tree series clones based on shape features using image processing techniques. Sample of rubber tree seeds are captured using digital camera where the RGB color image are processed involving segmentation algorithm which includes thresholding and morphological technique. Shape features such as area, perimeter and radius are extracted from each image. Two models are being designed. Model 1 is represented by 38 input features while Model 2 is represented by a reduction of input size using Principle Component Analysis (PCA). The inputs for both models are then used to train a multi-layer perceptron Artificial Neural Network (ANN) using Levenberg-Marquardt algorithm. 160 samples are used as training set while another 100 samples are used for testing. The optimized ANN models are then evaluated and validated through analysis of performance indicators regularly applied in classification research work via pattern recognition. Findings in this work have shown that the optimized Model 2 has the best accuracy of 84% with more than 70% achievement for sensitivity and specificity.