Aortic valve disease occurs due to calcification deposits on the area of leaflets within the human heart. It is progressive over time where it can affect the mechanism of the heart valve. To avoid the risk of surgery for vulnerable patients especially senior citizens, a new method has been introduced: Transcatheter Aortic Valve Implantation (TAVI), which places a synthetic catheter within the patient's valve. This entails a procedure of aortic annulus sizing, which requires manual measurement of the scanned images acquired from Computed Tomographic (CT) by experts. The step requires intensive efforts, though human error may still eventually lead to false measurement. In this research, image processing techniques are implemented onto cardiac CT images to achieve an automated and accurate measurement of the heart annulus. The image is first put through pre-processing for noise filtration and image enhancement. Then, a marker image is computed using the combination of opening and closing operations where the foreground image is marked as a feature while the background image is set to zero. Marker image is used to control the watershed transformation and also to prevent oversegmentation. This transformation has the advantage of fast computational and oversegmentation problems, which usually appear with the watershed transform can be solved with the introduction of marker image. Finally, the measurement of aortic annulus from the image data is obtained through morphological operations. Results affirm the approach's ability to achieve accurate annulus measurements compared to conventional techniques.

In assisted reproductive treatment, monitoring of follicular size using serial ultrasound is essential to access ovarian response. Traditional method requires doctors to measure the follicle size manually which will lead to inaccurate findings. As for more consistent and reliable parameter of follicular growth, an automated feature description may offer better accuracy in estimating to the response. In this study, by using two-dimensional ultrasound to acquire data from the ovaries, the ultrasound result will indicate the feature description automatically without manual calculation. This automated feature description is developed based on image processing technique using canny edge-detection method in MATLAB. It provides the analysis of the features based on area, perimeter, compactness, major and minor axis and centroid dataset to identify the follicle size

Endometriosis cyst or endometrium is commonly found in women with subfertility. Traditionally, medical technologies fail to detect the disease automatically and it is fully dependent on the doctors to determine the peritoneal disease where it may lead to inaccurate findings. A method of assessment may give more accurate detection without the need for surgical procedure, especially in monitoring disease recurrence. This will avoid surgical risk and will not delay the management. In this study, the feature description is developed using pattern recognition, involving image processing techniques; the ultrasonic images is used as input in which the region of interest of images, image segmentation, feature extraction are studied

Diagnostic tools such as Point-of-Care (POC) analysis usually requires an on-site testing and measurements. Hence, to ease the fluid sample handling, microfluidics technology has been opted frequently to be incorporated with lab-on-chip (LOC). Therefore, an easy and conventional method of design and fabrication of the microfluidic device implemented. In this study, the device is fabricated with Polydimethylsiloxane (PDMS) and SU-8 using soft lithography technique. Herein, we focus on fluid transportation which is applied in clinical diagnostics and the transfer rate to the desired position as well as the fluid leakage during the transportation. Hence, the microfluidic sample transport channeling provides a practical solution for POC technological advances to study the biological systems that yield a better result in quantitative measurements and providing researchers new tools for life science research.

An all-optical demultiplexing of 40-Gb/s DPSK OTDM channels by using Raman-amplifier-soliton-compressor (RASC) flexible control-window is demonstrated. In comparison with other scheme, the function of RASC is not only as a control gate controller but also to amplify the signal with picosecond width-tunable output signal. Error free operation was achieved for the proposed all-optical 1:4 demultiplexer over all time demultiplexed 10 Gb/s return-to-zero (RZ)-differential phase-shift keying (DPSK) signals with less than 2-dB power penalties at 10(-9) bit-error-rate (BER). The experimental results show that this scheme is expected to be scalable toward higher bit-rates.

Renewable energy (RE) is one of the leading industry blooming around the globe. The usage of renewable energy benefits the entire nation in all ways such the social, culture and environment. Besides that, the hike in the fossil fuel price in the market increase the demand in industry for the search of renewable energy as a conventional method to generate electricity. However, installation of solar photovoltaic (PV) for electricity generation might be not a good mitigation for the problem whereby some internal issues to be rectified and to be stabilized for the better power quality to be generated. Therefore, this paper study on voltage stability analysis on power grid with integrated solar PV system. The stability of voltage has to be taken care to avoid major problem occurrence such as voltage sag. Besides, the installation of PV can produce different PV penetrating rate which indirectly affects the voltage stability. This studies on the voltage stability problems integration of photovoltaic to IEEE-14 bus networks. In this research project NVSI used to find the weak bus for injection of three phase fault for fault analysis. The faulted bus was mitigated by using the photovoltaic system.

This research presents an application of Charge-Coupled Device (CCD) linear sensor and laser diode in an optical tomography system. Optical tomography is a non-invasive and non-intrusive method of capturing a cross-sectional image of multiphase flow. The measurements are based on the final light intensity received by the sensor and this approach is limited to detect solid objects only. The aim of this research is to analyse and demonstrate the capability of laser with a CCD in an optical tomography system for detecting objects with different clarity in crystal clear water. Experiments for detecting transparent objects were conducted. The object's diameter and image reconstruction can also be observed. As a conclusion, this research has successfully developed a non-intrusive and non-invasive optical tomography system that can detect objects in crystal clear water.

Real life phenomena found in various fields such as engineering, physics, biology and communication theory can be modeled as nonlinear higher order ordinary differential equations, particularly the Duffing oscillator. Analytical solutions for these differential equations can be time consuming whereas, conventional numerical solutions may lack accuracy. This research propose a block multistep method integrated with a variable order step size (VOS) algorithm for solving these Duffing oscillators directly. The proposed VOS Block method provides an alternative numerical solution by reducing computational cost (time) but without loss of accuracy. Numerical simulations are compared with known exact solutions for proof of accuracy and against current numerical methods for proof of efficiency (steps taken).

A two-point block backward difference technique is established for solving nonlinear Riccati differential equations directly. The proposed method is coded using a variable order step size (VOS) algorithm. The advantage of the two-point block method is its programmability to implement parallel programming techniques. Combination of the block method and VOS algorithm allows for a significant reduction of computation cost in comparison to conventional methods. With an added advantage of the recursive relationship between integration coefficients of different orders, the proposed two-point block method provides efficient computation without loss of accuracy.

Arabic Collocation Learning Strategies have been marginalized in the Arabic language curriculum system, but scholars acknowledge that it is a dominant strategy used by students, especially in the learning of foreign languages with moderate capabilities. This study examines the level of use, of Arabic language collocation strategies among Arabic language students in public universities. For that purpose, a set of Likert scale questionnaires were distributed to Arabic language students studying in public universities, who are in their final year of study. This study uses simple random sampling. A total of 344 students from eight public universities participated in this study. The findings show that collocation learning strategies in Arabic language are dominant even though they are at a moderate scale of use. This study proposes a new Arabic collocation learning strategy based on recognition, mastery techniques (understanding, repetition, highlighting, dictionary, social and imagery) and applications. The findings also discovered that collocation learning strategies should be utilized by students especially with regards to the autonomous role in using specific strategies and techniques to enhance competency in the Arabic language, especially in collocation.

Aortic stenosis (AS) is a condition where the calcification deposit within the heart leaflets narrows the valve and restricts the blood from flowing through it. This disease is progressive over time where it may affect the mechanism of the heart valve. To alleviate this condition without resorting to surgery, which runs the risk of mortality, a new method of treatment has been introduced: Transcatheter Aortic Valve Implantation (TAVI), in which imagery acquired from real-time echocardiogram (Echo) are needed to determine the exact size of aortic annulus. However, Echo data often suffers from speckle noise and low pixel resolution, which may result in incorrect sizing of the annulus. Our study therefore aims to perform an automated detection and measurement of aortic annulus size from Echo imagery. Two stages of algorithm are presented - image denoising and object detection. For the removal of speckle noise, Wavelet thresholding technique is applied. It consists of three sequential steps; applying linear discrete wavelet transform, thresholding wavelet coefficients and performing linear inverse wavelet transform. For the next stage of analysis, several morphological operations are used to perform object detection as well as valve sizing. The results showed that the automated system is able to produce more accurate sizing based on ground truth.