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

In this research Artificial Neural Network (ANN) technique was applied to study the filtration process in water treatment. Eight models have been developed and tested using data from a pilot filtration plant, working under different process design criteria; influent turbidity, bed depth, grain size, filtration rate and running time (length of the filtration run), recording effluent turbidity and head losses. The ANN models were constructed for the prediction of different performance criteria in the filtration process: effluent turbidity, head losses and running time. The results indicate that it is quite possible to use artificial neural networks in predicting effluent turbidity, head losses and running time in the filtration process, wi

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

The efficiency of the Honeywords approach has been proven to be a significant tool for boosting password security. The suggested system utilizes the Meerkat Clan Algorithm (MCA) in conjunction with WordNet to produce honeywords, thereby enhancing the level of password security. The technique of generating honeywords involves data sources from WordNet, which contributes to the improvement of authenticity and diversity in the honeywords. The method encompasses a series of consecutive stages, which include the tokenization of passwords, the formation of alphabet tokens using the Meerkat Clan Algorithm (MCA), the handling of digit tokens, the creation of unique character tokens, and the consolidation of honeywords. The optimization of t

In this study, generation of elliptical gears with different teeth profiles of crowned involute, double circular arc (DCA), and combined (crowned involute with DCA) has been developed. The resulting mathematical equations have been computerized and feed to CNC end mill machine to manufacture elliptical gear models with different profiles. These models are investigated in plane polariscope to show the resulting stresses under certain load. Comparison of photo-elastic stress results shows that combined elliptical gears with DCA side as a loaded side have a minimum resulting contact stress with a reduction percentage of 40% compare with contact stresses in counterpart elliptical gear of involute profile (which is commonly u

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

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