Akram M. Zeki

A secure audio steganography approach

A wide range of steganography techniques has been described in this paper. Beside the evaluation of embedding parameters for the existing techniques, two problems -weaknesses- of substitution techniques are investigated which if they could be solved, the large capacity - strength- of substitution techniques would be practical. Furthermore, a novel, principled approach to resolve the problems is presented. Using the proposed genetic algorithm, message bits are embedded into multiple, vague and higher LSB layers, resulting in increased robustness.

An approach to improve the robustness of substitution techniques of audio steganography

Steganography is a technique used to transmit hidden information by modifying an audio signal in an imperceptible manner. The transmission must be possible in spite of subsequent imperceptible alterations (attacks) of the modified signal. We propose a novel approach of substitution technique of audio steganography. Using genetic algorithm, message bits are embedded into multiple, vague and higher LSB layers, resulting in increased robustness. The robustness specially would be increased against those intentional attacks which try to reveal the hidden message and also some unintentional attacks like noise addition as well.

Robust audio steganography via genetic algorithm

Steganography is a technique used to transmit hidden information by modifying an audio signal in an imperceptible manner. The transmission must be possible in spite of subsequent imperceptible alterations (attacks) of the modified signal. We propose a novel approach of substitution technique of audio steganography. Using genetic algorithm, message bits are embedded into multiple, vague and higher LSB layers, resulting in increased robustness. The robustness specially would be increased against those intentional attacks which try to reveal the hidden message and also some unintentional attacks like noise addition as well.

Properties of digital image watermarking

Digital image watermarking techniques have been developed widely in recent years to maintain the broadcasting media and content authentication, broadcast monitoring, copy control, and many other applications. Therefore, many studies have used digital image watermarking to solve these problem. This paper highlights digital image watermarking. It starts with a basic model of digital image watermarking, it discusses the main requirements and applications. Moreover, it reviews some of the techniques and algorithm used in image watermarking. In addition, digital image watermarking attacks are discussed. Lastly, Watermarking evaluation system is described.

Segmentation techniques for online Arabic handwriting Recognition: A survey

This paper presents and compares techniques that have been used to segment Arabic handwriting scripts in online recognition systems. Those techniques attempt to segment cursive Arabic words into characters, or segment characters into small strokes that can be recognized via the recognition system. The structure and strategy of those reviewed techniques are explained in this article. The strengths and weaknesses of using these techniques will also be discussed.

A Novel Approach for Audio Watermarking

This paper presents a novel, principled approach to resolve the remained problems of substitution technique of audio watermarking. Using the proposed genetic algorithm, message bits are embedded into multiple, vague and higher LSB layers, resulting in increased robustness. The robustness specially would be increased against those intentional attacks which try to reveal the hidden message and also some unintentional attacks like noise addition as well.

Recognition Techniques for Online Arabic Handwriting Recognition Systems

Online recognition of Arabic handwritten text has been an on-going research problem for many years. Generally, online text recognition field has been gaining more interest lately due to the increasing popularity of hand-held computers, digital notebooks and advanced cellular phones. However, different techniques have been used to build several online handwritten recognition systems for Arabic text, such as Neural Networks, Hidden Markov Model, Template Matching and others. Most of the researches on online text recognition have divided the recognition system into these three main phases which are preprocessing phase, feature extraction phase and recognition phase which considers as the most important phase and the heart of the whole system. This paper presents and compares techniques that have been used to recognize the Arabic handwriting scripts in online recognition systems. Those techniques attempt to recognize Arabic handwritten words, characters, digits or strokes. The structure and strategy of those reviewed techniques are explained in this article. The strengths and weaknesses of using these techniques will also be discussed.

Problems of writing on digital surfaces in online handwriting recognition systems

Nowadays, keyboards and mice are the basic input devices for personal computers. Nevertheless, these devices may not remain as the only way of transmitting electronic data to computers. Other methods may become necessary, particularly with regard to the size of newer mobile devices and the method of transmission. Hand-held computers, mobile technology, for example, present significant opportunities for alternative devices that work in forms smaller than the traditional keyboard and mouse. In addition, the need for more natural human-machine interfaces becomes more important due to computer usage reaches a larger number of people worldwide. However, these new ways of human-machine interfaces have some problems while connecting to the computers. This paper presents and highlights some of these problems in the field of script recognition. This paper also illustrates the used techniques to overcome these matters.

Orthogonal Wavelet Support Vector Machine for Predicting Crude Oil Prices

Previous studies mainly used radial basis, sigmoid, polynomial, linear, and hyperbolic functions as the kernel function for computation in the neurons of conventional support vector machine (CSVM) whereas orthogonal wavelet requires less number of iterations to converge than these listed kernel functions. We proposed an orthogonal wavelet support vector machine (OSVM) model for predicting the monthly prices of West Texas Intermediate crude oil prices. For evaluation purposes, we compared the performance of our results with that of the CSVM, and multilayer perceptron neural network (MLPNN). It was found to perform better than the CSVM, and the MLPNN. Moreover, the number of iterations, and time computational complexity of the OSVM model is less than that of CSVM, and MLPNN. Experimental results suggest that the OSVM is effective, robust, and can efficiently be used for crude oil price prediction. Our proposal has the potentials of advancing the prediction accuracy of crude oil prices, which makes it suitable for building intelligent decision support systems.

Automatic interactive security monitoring system

Over the years an increasing demand for an automated security system begins to emerge. Many applications that help in protecting life and properties are being developed. Most of them are aimed at improving the work of security personnel and security agencies. However, security is a responsibility of everyone not only the security agencies or security personnel alone. This paper present an interactive security monitoring system based on passive infrared motion detection sensor, which will capture the image of any intruding persons and share it to the entire people that are using the system on both Android platform and in an online portal display. The people on the system can communicate with each other and post information to a commonly accessible board in the online system to discuss any issues or to see if anyone recognizes the felons/intruder on the images. Images of interest can then be transmitted to law enforcement authorities. This could be use in anywhere that needs to be protected against intruder. It will be best use in kindergarten, primary school and or in a neighborhood. That is why we call it neighborhood watch security system (NWSS). Preliminaries evaluation indicated an accurate image captured in a real time with an avoidance of false alarm.