Steganography is the art of hiding and transmitting data through apparently innocent carriers in an effort to conceal the existence of data. Text, image or audio in an Audio Video Interleave (AVI) multimedia file is adopted in this work.In the first step in this work, AVI file is separated into two parts, video and audio. The video part is a stream of frames, each frame is taken as a separated image stored in a separated Bit-Map (BMP) file.
The present work is an attempt of designing a symbolic based learning system for natural language understanding. The field selected to be the domain of application is the subject of data structure.The technique of learning used is Symbolic Learning which is a combination of two learning strategies Rote Learning and Learning by Instruction.
The problem of handwritten recognition considered to be very important problem because of its numerous applications and theoretical values in the domain of pattern recognition.In this research, models of Neural Networks are used to recognize written characters, applying Artificial Neural Network (ANN) of three types, which are: - Kohenen All Classes in One Network (ACON), Kohenen One Class in One Network(OCON), and Learning Vector Quantization (LVQ).The feature extraction process made use of Haar Wavelet Transformation to extract the parametric features of the
