The traditional voice call over Global System for Mobile Communications (GSM) and Public Switched Telephone Network (PSTN) is expensive and does not provide a secure end to end voice transmission. However, the growth in telecommunication industry has offered a new way to transmit voice over public network such as internet in a cheap and more flexible way. Due to insecure nature of the public network, the voice call becomes vulnerable to attacks such as eavesdropping and call hijacking. Accordingly, protection of voice call from illegal listening becomes increasingly important.
To this end, an android-based application (named E2ESeVoice application) to transmit voice in a secure way between the end users is proposed based on modified R

Self-driving automobiles are prominent in science and technology, which affect social and economic development. Deep learning (DL) is the most common area of study in artificial intelligence (AI). In recent years, deep learning-based solutions have been presented in the field of self-driving cars and have achieved outstanding results. Different studies investigated a variety of significant technologies for autonomous vehicles, including car navigation systems, path planning, environmental perception, as well as car control. End-to-end learning control directly converts sensory data into control commands in autonomous driving. This research aims to identify the most accurate pre-trained Deep Neural Network (DNN) for predicting the steerin

To ensure fault tolerance and distributed management, distributed protocols are employed as one of the major architectural concepts underlying the Internet. However, inefficiency, instability and fragility could be potentially overcome with the help of the novel networking architecture called software-defined networking (SDN). The main property of this architecture is the separation of the control and data planes. To reduce congestion and thus improve latency and throughput, there must be homogeneous distribution of the traffic load over the different network paths. This paper presents a smart flow steering agent (SFSA) for data flow routing based on current network conditions. To enhance throughput and minimize latency, the SFSA distrib

The automatic estimation of speaker characteristics, such as height, age, and gender, has various applications in forensics, surveillance, customer service, and many human-robot interaction applications. These applications are often required to produce a response promptly. This work proposes a novel approach to speaker profiling by combining filter bank initializations, such as continuous wavelets and gammatone filter banks, with one-dimensional (1D) convolutional neural networks (CNN) and residual blocks. The proposed end-to-end model goes from the raw waveform to an estimated height, age, and gender of the speaker by learning speaker representation directly from the audio signal without relying on handcrafted and pre-computed acou

Monaural source separation is a challenging issue due to the fact that there is only a single channel available; however, there is an unlimited range of possible solutions. In this paper, a monaural source separation model based hybrid deep learning model, which consists of convolution neural network (CNN), dense neural network (DNN) and recurrent neural network (RNN), will be presented. A trial and error method will be used to optimize the number of layers in the proposed model. Moreover, the effects of the learning rate, optimization algorithms, and the number of epochs on the separation performance will be explored. Our model was evaluated using the MIR-1K dataset for singing voice separation. Moreover, the proposed approach achi

      Let R be a commutative ring with identity and M  an unitary R-module. Let (M)  be the set of all submodules of M, and : (M)  (M)  {} be a function. We say that a proper submodule P of M is end--prime if for each   EndR(M) and x  M, if (x)  P, then either x  P + (P) or (M)  P + (P). Some of the properties of this concept will be investigated. Some characterizations of end--prime submodules will be given, and we show that under some assumtions prime submodules and end--prime submodules are coincide.

The Voluntary Obedience has great importance for the modern taxes systems and its management and this is meant the taxpayer whom in charge to pay of his taxes obligations voluntarily , he is very known of himself whereas he prepared his finishing accountings and present them as samples prepared by taxes management and settle the tax sum directly according to specified income , which has an impact to find end to tax evasion as result lead to increase the tax income and achieve the justice for the taxpayer and the state treasury

This paper presents the application of nonlinear finite element models in the analysis of dapped-ends pre-stressed reinforced concrete girders under static loading by using ANSYS software. The girder dimensions are (4.90 m span, 0.40 m depth, 0.20 m width, 0.20 m nib depth, and 0.10 m nib length) and the parameters considered in this research are the pre-stress effect, and strand profile (straight and draped).

    The numerical results are compared with the experimental results of the same girders. The comparisons are carried out in terms of initial prestress effect, load- deflection curve, and failure load. Good agreement was obtained between the analytical and experimental results. Even that, the

This paper presents the application of nonlinear finite element models in the analysis of dappedends pre-stressed reinforced concrete girders under static loading by using ANSYS software. The girder dimensions are (4.90 m span, 0.40 m depth, 0.20 m width, 0.20 m nib depth, and 0.10 m nib length) and the parameters considered in this research are the pre-stress effect, and strand profile (straight and draped). The numerical results are compared with the experimental results of the same girders. The comparisons are carried out in terms of initial prestress effect, load- deflection curve, and failure load. Good agreement was obtained between the analytical and experimental results. Even that, the numerical model was stiffer than the experiment