In this research work, a simulator with time-domain visualizers and configurable parameters using a continuous time simulation approach with Matlab R2019a is presented for modeling and investigating the performance of optical fiber and free-space quantum channels as a part of a generic quantum key distribution system simulator. The modeled optical fiber quantum channel is characterized with a maximum allowable distance of 150 km with 0.2 dB/km at =1550nm. While, at =900nm and =830nm the attenuation values are 2 dB/km and 3 dB/km respectively. The modeled free space quantum channel is characterized at 0.1 dB/km at =860 nm with maximum allowable distance of 150 km also. The simulator was investigated in terms of the execution of the BB84 p

<p>The demand for internet applications has increased rapidly.  Providing quality of service (QoS) requirements for varied internet application is a challenging task. One important factor that is significantly affected on the QoS service is the transport layer. The transport layer provides end-to-end data transmission across a network. Currently, the most common transport protocols used by internet application are TCP (Transmission Control Protocol) and UDP (User Datagram Protocol). Also, there are recent transport protocols such as DCCP (data congestion control protocol), SCTP (stream congestion transmission protocol), and TFRC (TCP-friendly rate control), which are in the standardization process of Internet Engineering Task

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

The current work discusses the removal of brilliant dyes. These dyes were Brilliant Cresyl Blue (BCB) and Brilliant Green (BG) by the use of poly acrylic acid hydrogel beads (PAA). We examined the adsorption isotherms and found that the factors preferring it are temperature and salt, shaking effects, wet PAA, (BCB) and (BG) follows Freundlich equation more than other equations. Based on the results, there is a positive correlation between adsorption of dyes (BCB and BG) and temperature (Endothermic process). We calculated the thermodynamic functions (ΔG, ΔS, and ΔH). The ion strength effects on the adsorptions at (20 °C) increased adsorption if the salt concentrations is high. We treated the kinetics outcomes based on Lagergren Equation

The performance of a batch undivided electrochemical reactor with a rotating cylinder electrode of woven-wire (60 mesh size), stainless steel 316, is examined for the removal of copper from synthetic solution of o.5 M sodium chloride containing 125 ppm at pH ≈ 3.5. The effect of total applied current, rotation speed on the figures of merit of the reactor is analyzed. For an applied current of 300 mA at 100 rpm, the copper concentration decreased from 125 to  mg l^-1 after 60 min of electrolysis with a specific energy consumption of 1.75 kWh kg^-1 and a normalized space velocity of 1.62 h^-1. The change in concentration was higher when the total applied currents were increased because of the turbulence