Mohd Faisal Ibrahim

Optimization of fuzzy model using genetic algorithm for process control application

Abstract A technique for the modeling of nonlinear control processes using fuzzy modeling approach based on the Takagi–Sugeno fuzzy model with a combination of genetic algorithm and recursive least square is proposed. This paper discusses the identification of the parameters at the antecedent and consequent parts of the fuzzy model. For the antecedent fuzzy parameters, genetic algorithm is used to tune them while at the consequent part, recursive least squares approach is used to identify the system parameters. This approach is applied to a process control rig with three subsystems: a heating element, a heat exchanger and a compartment tank. Experimental results show that the proposed approach provides better modeling when compared with Takagi Sugeno fuzzy modeling technique and the linear modeling approach.

Thermal Noise Effect in FTTH Communication Systems

Thermal noise is generated naturally by thermal agitation of electrons in a conductor commonly found in opto-electronic devices. The fact that the optical medium is totally immune to noise does not exclude its occurrence in receiver parts. In communication, thermal noise has a major influence to the quality of the receiver. The lower the thermal noise the higher and more expensive is receiver sensitivity. This paper starts with a tutorial on thermal noise in common communication technologies. The major contribution factor to thermal noise power is also discussed analytically. For more comprehensive view, the includes a study on thermal noise effects network performance in terms of BER, maximum Q-factor, eye height and maximum distance. The fiber-to-the-home network is used as a test field to study the impact of two different values of thermal noise on network parameters. At the end of this paper, thermal noise minimizing techniques are also listed.

Shape-based boundary segmentation assessment for cervical vertebrae classification

Shape-based boundary representation is a critical component in medical imaging-based diagnosis system. Furthermore, accurate boundary representation is also essential in getting good segmentation, feature indexing and classification. This work concentrates on cervical vertebra distortion across the anterior boundary to detect anterior osteophytes and identify its severity. A suitable shape representation, which defines the vertebrae shape boundary must be determined prior to the cervical vertebra model can be constructed. Therefore, two different shape-based representations for vertebral segmentation using active shape model are analysed, which are 9-anatomical point representation (9-APR) and B-spline representation (BSR). The aims is to compare and quantify the precision and accuracy performance of the segmented vertebra with the help of orientation histogram-based indexing and multi-layer perception based on ten-fold cross validation (MLP-TFCV) classifier. Experimental results are assessed based on the segmented boundary outline by using ROC and AUC curves. The results show that the performance of both boundary representations are almost similar where B-SR has a small advantage compared to the 9-APR. The system can be further improved by introducing a statistical sampling method of the anterior points instead of the whole vertebra.

OXADMs: The next generation of optical switching devices

This paper introduces a new optical device model named as an optical cross add and drop multiplexer (OXADM) which has potential use in CWDM metro area networks. The device uses the concepts of combination of optical add/drop multiplexing and optical cross connect between two main transmission lines in order to implement the wavelength routing operation [10]. MEMS optical switches are integrated in the device to make it re-configurable. With excellent features, the device is particularly designed to improve network efficiency, flexibility and survivability [7][8]. The device can be used in point to point, ring or mesh network topology to provide functionality such as routing, supervision, transport, multiplexing and restoration of client digital signals processed predominantly in the optical domain [7]. The wavelengths on each optical trunk can be switched between each other while implementing add and drop functions simultaneously. The multiplexer has undergone performance test at 2.5 Gbps (OC- 48) with BER less than 10-9. The maximum length can be achieved by OXADMs is 71 km without amplification at insertion loss 6 dB. A comparison between OXADM with the previous devices such as, OXC, TRN and OXN is also been studied.

Optical Cross Add and Drop Multiplexer: An Analytical Approach

OXADMs reliability and also survivability of the trunk-line optical network used for data communication. This paper describes the analytical modeling of OXADMs and studies their performance as compared to conventional OXC devices. With two restoration schemes, the OXADM prototype system focuses on providing survivability through restoration against failures by means of linear/multiplex and ring protection. Degradation is expected to be about 2 dB in output power with respect to normal conditions in ring protection activation. The test was carried out at 2.5 Gbps with BER 1 times 10-10 for linear protection while BER 1 times 10-19 (to west) and 1 times 10-13 (to east) were used for ring protection. The method of study involves the building and characterizing of two OXADMs, simulated by using Optisystem and modeling them analytically. Loss characterization and measured OSNR are compared against the analytical values and proven to be similar.

X-Ray image enhancement for anterior Osteophyte diagnosis

Computer assisted system has been implemented virtually in many domains within the field of medical imaging. An automated assessment system based on computer is important for early detection and diagnosis of various diseases. Moreover, image enhancement in medical imaging is a vital component in improving the quality of medical image, so that pre-screening of the disease can be carried accurately without performing any open surgery. Hence, pre-processing module is an important step to enhance the medical image, especially for X-ray modality, which normally affected by artefacts, noise and hardware limitations. A low quality of X-ray image will usually lead to inaccurate diagnosis. Therefore, a semi-automated assessment system has been developed to diagnose Anterior Osteophytes (AO) condition based on X-ray image that focused on cervical vertebrae. The system consists of four main modules: image enhancement, image segmentation, feature extraction and classification. This system is intended to facilitate medical practitioners in screening the AO condition with more accurate and faster diagnosis. A graphical user interface has also been developed to help the medical practitioners to perform the image enhancement easily. The proposed system is tested with 100 cervical X-ray images and the obtained accuracy is 60%. Finally, this system is suitable for real time implementation and can be implemented on most recent desktop technology.

Suspicious Loitering Detection from Annotated CCTV Feed Using CEP Based Approach

Smart Surveillance System is a critical system that enables automated detection of anomalous activities from live CCTV feed. The main challenge that needs to be addressed by the Smart Surveillance System is the ability to understand and detect the activities that are currently occurring within the CCTV feed. Suspicious loitering is considered one of the anomalous activities that precede unwanted events, such as break-ins, burglary, and robbery. In this research, the Complex Event Processing (CEP) approach was selected as the system development approach for developing a Smart Surveillance System. Four types of similarity search-based event detectors, namely the Multi-Layered Event Detector for General Application (MEGA), Temporally Constrained Template Match Detector (TCD), Sliding Window Detector (SWD), and Weighted Sliding Window Detector (WSWD) were tested and evaluated to determine the best suspicious loitering event detector to be used in the Smart Surveillance System. The input data to the detectors comprised manually annotated real CCTV feed which was subjected to three noise conditions: (i) no-noise (0% noise) annotation, (ii) 25% noisy annotation and (iii) 46.8% noisy annotation. The 46.8% noisy annotation is assumed to reflect the real ambient operating condition of the Smart Surveillance System; while the no-noise condition was assumed to reflect the perfect CCTV feed acquisition and annotation process. The performance of the detectors was measured in terms of sensitivity, specificity, detection accuracy, and the area under the Receiver’s Operating Curve (ROC). The results obtained showed that MEGA is the best overall detector for suspicious loitering detection in ambient operating conditions with detection accuracy of 97.20% and area under ROC curve of 0.6117.

Autonomous industrial tank floor inspection robot

Many storage tanks used in industry are inspected manually in order to identify leakage and corrosion. This repetitive task can harm the operator as the operator has to expose themselves to danger inside the tank. The environment of the tank can be harmful because it might contain highly hazardous substances. Additionally, the manual inspection process also requires highly skilled operators for precision. This project proposes the use of an autonomous inspection robot to overcome this problem. The proposed robot is based on the TurtleBot with the Microsoft Kinect camera as a distance sensor. The MinnowBoard MAX board is used as the computing platform running the Robot Operating System (ROS) for tank floor mapping and navigation of the robot. The GMapping Simultaneous Localization and Mapping (SLAM) algorithm is used to do perform the mapping process. Evaluation was performed by comparison against physical measurement of the foyer of the Faculty of Engineering and Built Environment (FKAB) at Universiti Kebangsaan Malaysia (UKM). The results show that the GMapping algorithm is able to generate relatively accurate maps even with the low cost platform and will perform even better with more accurate sensors.

OXADMs: The Comparison with the Existing Device

This paper introduces a new optical device model named as an optical cross add and drop multiplexer (OXADM) which has potential use in CWDM metro area networks. The device uses the concepts of combination of optical add/drop multiplexing and optical cross connect between two main transmission lines in order to implement the wavelength routing operation. MEMS optical switches are integrated in the device to make it re-configurable. With excellent features, the device is particularly designed to improve network efficiency, flexibility and survivability. The device can be used in point to point, ring or mesh network topology to provide functionality such as routing, supervision, transport, multiplexing and restoration of client digital signals processed predominantly in the optical domain. The wavelengths on each optical trunk can be switched between each other while implementing add and drop functions simultaneously. We do a comparison between OXADM with the previous devices such as, OXC, TRN and OXN. The limitation occurs in OXADM as compare with OXC is also studied analytically in the respect of scalability (in term number of ports and operating wavelengths).