Siti Arpah Ahmad

Performance evaluation between IPv4 and IPv6 on MPLS Linux platform

This paper presents the performance evaluation between IPv4 and IPv6 with Linux MPLS tunnel. MPLS Linux tunneling is used to transport IPv6 data stream over IPv4 network for interoperable IPv4 and IPv6 deployment. The performance metrics such as jitter, datagram/packet loss and bandwidth were measured in both TCP and UPD traffic flow. The experiment test-bed was constructed using virtual machine tool for simulating the IPv4, IPv6, and the MPLS tunneling mechanism. This study revealed that IPv6 offered better performance than IPv4 in almost all of the testing except in TCP transfer. In addition, MPLS tunnel improved performance in packet transfer for TCP transfer, UDP transfer and bandwidth testing.

The effect of sharp contrast-limited adaptive histogram equalization (SCLAHE) on Intra-oral dental radiograph images

Radiographic interpretation is crucial for the excellence of quality patient care. Image enhancements can contribute to better image that allow the clinician to derive the optimum amount of information from the radiographic data. However, the degree of enhancement applied to the original image can produce distortions that will lead to misinterpretation. This research presents the effect of Intra-oral dental x-ray images before and after processing with sharp contrast-limited adaptive histogram equalization (SCLAHE) in order to detect the effectiveness of this option on diagnostic ability. In this study 10 intra-oral periapical dental x-ray images (4 upper jaw molar and 6 lower jaw molar) were evaluated by six dentists and were scored from 1 – 5 for the overall image quality based on their perception of the image quality and the presence of the tooth pathologies. Results show that SCLAHE have the positive effect on providing better information for dentists.

Classification of surface electromyographic signal using fuzzy logic for prosthesis control application

This paper describes the classification stage of an electromyographic (EMG) control system for prosthetic hand application. Moving ApEn was used as main method to extract features from the two channels of surface EMG signal at the forearm of the upper limb. A fuzzy logic system is used to classify the extracted information in discriminating the final grip posture. The results demonstrate the ability of the system to classify the information related to different grip postures.

Multichannel EMG data acquisition system: Design and temporal analysis during human ankle joint movements

This paper presents the implementation of four channel Electromyography (EMG) signal acquisition system for acquiring the EMG signal of the lower limb muscles during ankle joint movements. Furthermore, some post processing and statistical analysis for the recorded signal were presented. Four channels were implemented using instrumentation amplifier (INA114) for pre-amplification stage then the amplified signal subjected to the band pass filter to eliminate the unwanted signals. Operational amplifier (OPA2604) was involved for the main amplification stage to get the output signal in volts. The EMG signals were detected during movement of the ankle joint of a healthy subject. Then the signal was sampled at the rate of 2 kHz using NI6009 DAQ and Labview used for displaying and storing the acquired signal. For EMG temporal representation, mean absolute value (MAV) analysis algorithm is used to investigate the level of the muscles activity. This data will be used in future as a control input signal to drive the ankle joint exoskeleton robot.

Windows registry analysis for forensic investigation

Cyber attack comes in various approach and forms, either internally or externally. Remote access and spyware are forms of cyber attack leaving an organization to be susceptible to vulnerability. This paper investigates illegal activities and potential evidence of cyber attack through studying the registry on the Windows 7 Home Premium (32 bit) Operating System in using the application Virtual Network Computing (VNC) and keylogger application. The aim is to trace the registry artifacts left by the attacker which connected using Virtual Network Computing (VNC) protocol within Windows 7 Operating System (OS). The analysis of the registry focused on detecting unwanted applications or unauthorized access to the machine with regard to the user activity via the VNC connection for the potential evidence of illegal activities by investigating the Registration Entries file and image file using the Forensic Toolkit (FTK) Imager. The outcome of this study is the findings on the artifacts which correlate to the user activity.

Recommended surface EMG electrode position for wrist extension and flexion

To obtain a high-quality surface electromyography (EMG) recording, the signal must be acquired as far as possible from the muscle innervation and tendon zone. This study presents a technique to indicate better electrode positions for surface EMG of the upper limb muscles during wrist extension and flexion. Ten volunteers participated in this research. Surface EMG signals were collected from flexor carpi radialis and extensor carpi radialis muscles. Three different electrode positions with 2 cm internal distance between the bipolar electrodes were investigated. The duration of muscle contraction was selected using the mean absolute value method for quantification, and the qualitative signal was observed through visual inspection. The power spectral density and signal-to-noise ratio were applied to compare and select the most feasible electrode position. The optimal signal from the flexor carpi radialis muscles was presented at 90%. The optimal position for the extensor carpi radialis muscles was shown at 90% of the electrode position over the forearm length. The presented method should be observed as an important step in every surface EMG application and research to ensure high quality of the signal.

Variations of Adaptive Histogram Equalization (AHE) analysis on intra-oral dental radiograph

Medical images, such as dental radiographs, suffer of low contrasts and noise which make it difficult to identify disease characteristics. This work utilizes the variation of Adaptive Histogram Equalization (AHE) towards enhancing the intra-oral dental radiograph. The algorithms used are AHE, Contrast Limited Adaptive Histogram Equalization (CLAHE), Sharpening Adaptive Histogram, Equalization (SAHE), Sharpening Median Adaptive Histogram Equalization (SMAHE) and Sharpening Contrast Limited Adaptive Histogram equalization (SCLAHE). These image enhancement algorithms variation are aim to test the noise, blurring and low contrast factors of the intra-oral dental image. The characteristic of the original and enhanced images are compared using image histogram. Results show that histogram of SCLAHE is the closest towards mimicking the original image histogram but with better pixel distribution, thus make the image visually clearer. The performance among the enhanced images is further compared using Contrast Improvement Index (CII), Signal to Noise Ratio (SNR) and Root Mean Square Error (RMSE). Results show that SCLAHE able to get the highest SNR, but the lowest CII and RMSE.

Analysis of routing protocols of VoIP VPN over MPLS network

Voice over internet protocols (VoIP)s quality communication relies significantly on the network; however guarantee the best quality of the traffic is difficult. This paper analyzes the performance of VoIP traffic in Border Gateway Protocol (BGP) -Multiprotocol Label Switching (MPLS) IP Virtual Private Network (VPN) between two interior routing protocols namely Enhanced Interior Gateway Protocol (EIGRP) and Open Shortest Path First (OSPF). The combination of MPLS and conventional routing improve the forwarding mechanism, scalability and overall network performance. OPNET Modeler 14.5 is used to simulate both scenarios and metrics such as delay, jitter and mean opinion score (MOS) value are measured. The simulation result shows OSPF and BGP-MPLS VPN provides better infrastructure for VoIP VPN application.

The Performance of Compound Enhancement Algorithm on Abnormality Detection Analysis of Intra-oral Dental Radiograph Images

Dentists look for abnormality in radiograph for determining any diseases that may appear at the apices of the teeth. However poor quality of the radiograph produces weak visual signal that may produce misleading interpretations. Hence the quality of radiograph influence dentists’ decision that reflects the success or failure of any suggested treatments. Thus this work aim to analyze the abnormality found in intra-oral dental radiographs by comparing the original images with images that had been enhanced using compound enhancement algorithms (CEA) namely Sharp Adaptive Histogram Equalization (SAHE) and Sharp Contrast adaptive histogram equalization (SCLAHE). Results show that SCLAHE enhanced images provide slight improvement, compared to the original images, in detecting widen periodontal ligament space abnormality

Parallel Laplacian Edge Detection Performance Analysis on Green Cluster Architecture

The current trend of computer hardware declining and the speed of personal computer increasing had lead to opportunity of parallel programming. This paper presents the implementation of parallel Laplacian edge detection on cluster of four used personal computers. The algorithm was developed using C# language and had utilized the Message Passing Interface (MPI) library for parallel implementation. Comparison between sequential versus parallel implementation had been made based on sequential time taken for varies of images sizes. Results show significant time improvement as well as performance efficiency earned using parallel computing platform focusing on image processing Laplacian edge detection algorithm.