The exponential growth of audio data shared over the internet and communication channels has raised significant concerns about the security and privacy of transmitted information. Due to high processing requirements, traditional encryption algorithms demand considerable computational effort for real-time audio encryption. To address these challenges, this paper presents a permutation for secure audio encryption using a combination of Tent and 1D logistic maps. The audio data is first shuffled using Tent map for the random permutation. The high random secret key with a length equal to the size of the audio data is then generated using a 1D logistic map. Finally, the Exclusive OR (XOR) operation is applied between the generated key and the sh

This paper presents a modified training method for Recurrent Neural Networks. This method depends on the Non linear Auto Regressive (NARX) model with Modified Wavelet Function as activation function (MSLOG) in the hidden layer. The modified model is known as Modified Recurrent Neural (MRN). It is used for identification Forward dynamics of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot. This model is also used in the design of Direct Inverse Control (DIC). This method is compared with Recurrent Neural Networks that used Sigmoid activation function (RS) in the hidden layer and Recurrent Neural Networks with Wavelet activation function (RW). Simulation results shows that the MRN model is bett

Business organizations have faced many challenges in recent times, most important of which is information technology, because it is widely spread and easy to use. Its use has led to an increase in the amount of data that business organizations deal with an unprecedented manner. The amount of data available through the internet is a problem that many parties seek to find solutions for. Why is it available there in this huge amount randomly? Many expectations have revealed that in 2017, there will be devices connected to the internet estimated at three times the population of the Earth, and in 2015 more than one and a half billion gigabytes of data was transferred every minute globally. Thus, the so-called data mining emerged as a

A new bio-electrochemical system was proposed for simultaneous removal of organic matters and salinity from actual domestic wastewater and synthetically prepared saline water, respectively. The performance of a three-chambered microbial osmotic fuel cell (MOFC) provided with forward osmosis (FO) membrane and cation exchange membrane (CEM) was evaluated with respect to the chemical oxygen demand (COD) removal from wastewater, electricity generation, and desalination of saline water. The MOFC wasinoculated with activated sludge and fueled with actual domestic wastewater. Results revealed that maximum removal efficiency of COD from wastewater, TDS removal efficiency from saline water, power density, and current density were

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The Artificial Neural Network methodology is a very important & new subjects that build's the models for Analyzing, Data Evaluation, Forecasting & Controlling without depending on an old model or classic statistic method that describe the behavior of statistic phenomenon, the methodology works by simulating the data to reach a robust optimum model that represent the statistic phenomenon & we can use the model in any time & states, we used the Box-Jenkins (ARMAX) approach for comparing, in this paper depends on the received power to build a robust model for forecasting, analyzing & controlling in the sod power, the received power come from

أثبتت الشبكات المحددة بالبرمجيات (SDN) تفوقها في معالجة مشاكل الشبكة العادية مثل قابلية التوسع وخفة الحركة والأمن. تأتي هذه الميزة من SDN بسبب فصل مستوى التحكم عن مستوى البيانات. على الرغم من وجود العديد من الأوراق والدراسات التي تركز على إدارة SDN، والرصد، والتحكم، وتحسين QoS، إلا أن القليل منها يركز على تقديم ما يستخدمونه لتوليد حركة المرور وقياس أداء الشبكة. كما أن المؤلفات تفتقر إلى مقارنات بين الأدوات والأ