Fadzilah Siraj

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The advancement in computer technology has encouraged the researchers to develop software for assisting doctors in making decision without consulting the specialists directly. The software development exploits the potential of human intelligence such as reasoning, making decision, learning (by experiencing) and many others. Artificial intelligence is not a(More)
To date, higher educational organizations are placed in a very high competitive environment. To remain competitive, one approach is to tackle the student and administration challenges through the analysis and presentation of data, or data mining. This study presents the results of applying data mining to enrollment data of Sebha University in Libya. The(More)
Digital image processing is a rapidly growing area of computer science since it was introduced and developed in the 1960’s. In the case of flower classification, image processing is a crucial step for computer-aided plant species identification. Colour of the flower plays very important role in image classification since it gives additional(More)
This paper intents to assess the application of artificial neural network in predicting the presence of heart disease, mainly the angina in patients. The prediction and detection of angina are significant in determining the most appropriate form of treatment for these patients. The development of the application involves three main phases. The first phase(More)
Image processing plays an important role in extracting useful information from images. However, the image processing and the process of translating an image into a statistical distribution of low-level features is not an easy task. These tasks are complicated since the acquired image data often noisy, and target objects are influenced by lighting, intensity(More)
Automatic speech recognition (ASR) has made great strides with the development of digital signal processing hardware and software especially using English as the language of choice. In this paper, a new feature extraction method is presented to identify vowels recorded from 80 Malaysian speakers. The features are obtained from Vocal Tract Model based on(More)