Over the past few years, ear biometrics has attracted a lot of attention. It is a trusted biometric for the identification and recognition of humans due to its consistent shape and rich texture variation. The ear presents an attractive solution since it is visible, ear images are easily captured, and the ear structure remains relatively stable over time.  In this paper, a comprehensive review of prior research was conducted to establish the efficacy of utilizing ear features for individual identification through the employment of both manually-crafted features and deep-learning approaches. The objective of this model is to present the accuracy rate of person identification systems based on either manually-crafted features such as D

This dissertation depends on study of the topological structure in graph theory as well as introduce some concerning concepts, and generalization them into new topological spaces constructed using elements of graph. Thus, it is required presenting some theorems, propositions, and corollaries that are available in resources and proof which are not available. Moreover, studying some relationships between many concepts and examining their equivalence property like locally connectedness, convexity, intervals, and compactness. In addition, introducing the concepts of weaker separation axioms in α-topological spaces than the standard once like, α-feebly Hausdorff, α-feebly regular, and α-feebly normal and studying their properties. Furthermor

In this paper, method of steganography in Audio is introduced for hiding secret data in audio media file (WAV). Hiding in audio becomes a challenging discipline, since the Human Auditory System is extremely sensitive. The proposed method is to embed the secret text message in frequency domain of audio file. The proposed method contained two stages: the first embedding phase and the second extraction phase. In embedding phase the audio file transformed from time domain to frequency domain using 1-level linear wavelet decomposition technique and only high frequency is used for hiding secreted message. The text message encrypted using Data Encryption Standard (DES) algorithm. Finally; the Least Significant bit (LSB) algorithm used to hide secr

This paper is concerned with introducing and studying the first new approximation operators using mixed degree system and second new approximation operators using mixed degree system which are the core concept in this paper. In addition, the approximations of graphs using the operators first lower and first upper are accurate then the approximations obtained by using the operators second lower and second upper sincefirst accuracy less then second accuracy. For this reason, we study in detail the properties of second lower and second upper in this paper. Furthermore, we summarize the results for the properties of approximation operators second lower and second upper when the graph G is arbitrary, serial 1, serial 2, reflexive, symmetric, tra

In cognitive radio networks, there are two important probabilities; the first probability is important to primary users called probability of detection as it indicates their protection level from secondary users, and the second probability is important to the secondary users called probability of false alarm which is used for determining their using of unoccupied channel. Cooperation sensing can improve the probabilities of detection and false alarm. A new approach of determine optimal value for these probabilities, is supposed and considered to face multi secondary users through discovering an optimal threshold value for each unique detection curve then jointly find the optimal thresholds. To get the aggregated throughput over transmission