Encryption of digital color image is the process of conversion original digital color image into an encrypted one to protect the image from hacking or to prevent an authorized person to get the valuable information located in the color image. The process of color image encryption-decryption is very important issue in human activities and here in this paper we will introduce a new simple, efficient and highly secure method to be used for color image encryption-decryption. The proposed method will be tested and implemented, the efficiency parameters of the proposed method will be calculated and will be compared with other methods parameters to prove the efficiency issues of the proposed method.
A novel methodology to manipulate wave file and create a feature array for each wave file will be introduced, this array can be used later on to recognize the voice file. A set of experiments will be performed in order to prove the uniqueness of the calculated feature array, and that the created feature array for a certain wave file does not match any other feature array for other wave files. The proposed methodology will minimize the efforts of voice recognition by mean of minimizing the time of feature array creation and minimizing the size of the calculated array.
General TermsVoice recognitions, artificial intelligence
KeywordsWave file, feature array, histogram.
Steganography is the technique of hiding secret data (message) within any media such as digital color image. In this paper we will merge steganography process with cryptography process in order to increase the security of the proposed method. The steganography process will based on LSB method, while the cryptography process will based on generating a huge private key and selecting a special function for encryption decryption. The proposed method will be implemented in order to calculate some performance parameters to prove the efficiency of the proposed method.
Astrocytes, the predominant glial cell type in the brain, were traditionally considered as merely passive supportive cells without any important roles in synaptic information processing. In contrast, the contemporary view was given rise to show that astrocytes play active roles in synaptic neurotransmission and information processing. Hence, recently two terms have been emerged, tripartite synapse, to describe the communication between an astrocyte and two neurons, and the term astrocytic syncytium or astrocytic network to describe the communication among the astrocytes by gap junction. Therefore, we propose mathematical models for tripartite synapseand astrocytic syncytium based on twostate kinetics models, several probabilistic methods and Spiking Neural Network (SNN) to introduce new Artificial Astrocytic Syncytium (AAS) model. The simulation results have shown that proposed model could represent the cellular intrinsic properties of astrocyte based on the spatial and temporal aspects to emulate the astrocytic network functions related to cognitive, learning and memory.
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