Pusat Pengajian Kejuruteraaan Elektrik dan Elektronik - Tesis

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    Impact Of Differential Pair Routing Discontinuities On Signal Integrity In Printed Circuit Board Design
    (2013-02)
    Adanan, Omar Mukhtar
    Differential pair routing on Printed Circuit Board (PCB) is widely used as interconnect due to its excellent signal integrity performance, However, differential pair is not immune to the impact of routing discontinuities. This research analyzed and quantified the impact several types of routing discontinuities on differential pair. These routing discontinuities are routing over split plane, routing over void, 45° bend routing and serpentine routing. The results of this research are based on Full-wave 3D modeling and simulation. The cross-sectional differential pair configuration parameters are based on SATA 3rd Generation industrial standard. Four types of analysis have been done for each of the routing discontinuities, which are S-parameter, TDR, Model Eye-Diagram and Full Channel Transient Analysis. Based on configuration parameters used in this research, the differential pair routing with routing discontinuities degrade the signal integrity performance especially above 3GHz. Routing discontinuities also cause the characteristic impedance of differential routing to change and lead to impedance mismatch. Different types of routing discontinuities have different impact characteristics. As for routing over split plane and void, the higher the number of split planes or voids higher the degradation in signal integrity. As for serpentine and 45° degree bend, inconsistence spacing within differential pair traces causes the signal integrity performance to degrade. x
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    Detection And Segmentation Of Mass Region In Mammogram Image
    (2014-01)
    Ting, Shyue Siong
    Breast cancer is the most common form of cancer and continues to be a significant public health problem amongst women around the world. Early detection is the most promising way to decrease the number of patient suffering from this disease. Currently, mammography is an effective diagnostic technique for early detection of breast cancer. Numerous studies have been carried out to develop Computer-Aided Diagnosis (CAD) system to help radiologists. Unfortunately, none of the proposed techniques provide good results in both mass detection and segmentation. Thus, in this study, an automated system to detect and segment the true mass regions of any size, shape and margin in mammogram image is proposed. Initially, the Mean Median Intersection Point (MMIP) algorithm is proposed to obtain a point in the intensity histogram to be set as threshold value to segment the breast region and distinguish it from the background in the mammogram image. Then, a modified contrast enhancement technique, namely Multi-Stage Contrast Enhancement (MSCE) technique is proposed to increase the contrast between the mass and breast tissue regions. Finally, an automated seed based region growing process for mass detection and segmentation is proposed. In the proposed technique, the seed point that produces the smallest smoothness descriptor value is set as the initial mass centre for the region growing process. In order to produce results which mimic true mass region, the enhanced mammogram image is multiplied with the Gaussian function centred at a seed point location.
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    8-Bit High Resolution Pipelined Analog-To-Digital Converter (ADC) With High Unity-Gain Bandwidth Operational Transconductance Amplifier (OTA)
    (2019-02)
    Idros, Norhamizah
    High unity-gain bandwidth operational transconductance amplifier (OTA) for high resolution 8-bit pipelined analog-to-digital converter (ADC) was designed to satisfy the differential non-linearity (DNL) of ±1 LSB and conversion time less than 20 /js. The resolution of pipelined ADC is limited by open-loop DC gain provided by the OTA that acts as the core element in developing the ADC. The existing design of folded cascode OTA does not has a high open-loop DC gain to maintain the resolution of 8-bit. The choice of folded cascode is the best suited architecture for high resolution switched capacitor application as compared to the other topology.
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    Evaluation of uav-based lora wireless communications under various scenarios
    (2023-05-01)
    Teoh Theng Kah
    This research evaluates the performance of UAV (Unmanned Aerial Vehicle)-based and Non-UAV-based LoRa wireless communication under various scenario. LoRa is a long-range, low-power wireless communication technology that has become increasingly popular for IOT (Internet of Things) and other applications, due to its long-range capabilities, low power consumption, and low cost. In this study, the LoRa technology is used to establish wireless communication between a ground-based gateway (Receiver) and a moving UAV-based or Non-UAV-based end-node (Transmitter) that tested within 1 kilometer scope, for the purpose of evaluating the functionality and the signal disturbance of LoRa for both indoor and outdoor. The performance of the communication is evaluated under different scenarios, including varying distances between the gateway and the end-node, different environments (indoor and outdoor), different antenna types and battery power consumption upon data transmission. The main performance metrics that used in the evaluation are the RSSI (Received Signal Strength Indicator) and PRR (Packet Reception Rate). The results of the evaluation show that the UAV-based and Non-UAV-based LoRa technology can provide reliable and efficient wireless communication and optimum battery power consumption of the data transmission setting, with good performance tested within 1 kilometer distance and in various environments. The findings of this study can provide useful insights and guidance for the design and implementation of LoRa-based wireless communication systems for UAV applications.
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    Visual stimuli-based dynamic commands with single channel electroencephalography for reactive brain-computer interface applications
    (2023-05-01)
    Teo Jia Hui
    The brain-computer interface (BCI) technology is widely used to control robotic devices using electroencephalogram (EEG) signals. Normal eye blinks are usually treated as artifacts within the recorded EEG signals but voluntary eye blinks which will cause distinct signal deflections can be introduced into BCI applications as control commands. This study designed a new reactive BCI paradigm using single-channel EEG device which combined visual stimuli and voluntary eye blinks to work on motorized actuators with different speed profiles. This proposal consisted of an EEG decoder that applied on machine learning methods to improve the accuracy of the system. Multilayer perceptron (MLP) neural network and Gaussian Process model (GPM) had been proposed to minimize the mismatches between required and actual transmitted commands. Results from thirty subjects showed that the GPM could achieve the highest 90% accuracy and lowest 1.51cm/s mean absolute error whereas MLP showed slightly better performance (86% accuracy and 1.76cm/s mean absolute error) than other comparing methods. The implementation of Hanning filter showed improvement to minimize unwanted errors in the system. Female-based model could perform slightly better than generic model on female-only test data set whereas male-based model performed similarly as generic model on male-only test data set. While other learning models were susceptible to different types of stimuli, the proposed GPM could perform consistently to demonstrate its high generalization and make it a more suitable option over MLP and other methods on such BCI system.