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 prot
... Show MoreKnowing the distribution of the mechanical rock properties and in-situ stresses for the field of interest is essential for many applications concerning reservoir geomechanics, including wellbore instability analysis, hydraulic fracturing, sand production, reservoir compaction, subsidence and water/gas injection throughout the filed life cycle. Determining the rock's mechanical properties is challenging because they cannot be directly measured at the borehole. The recovered carbonate core samples are limited and only provide discrete data for specific depths. This study focuses on creating a detailed 1D geomechanical model of the Mishrif reservoir in the Nasriyah oil field to identify the fault regime type for each unit in the format
... Show MoreIn 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
... Show MoreThis study is planned with the aim of constructing models that can be used to forecast trip production in the Al-Karada region in Baghdad city incorporating the socioeconomic features, through the use of various statistical approaches to the modeling of trip generation, such as artificial neural network (ANN) and multiple linear regression (MLR). The research region was split into 11 zones to accomplish the study aim. Forms were issued based on the needed sample size of 1,170. Only 1,050 forms with responses were received, giving a response rate of 89.74% for the research region. The collected data were processed using the ANN technique in MATLAB v20. The same database was utilized to
The aim of this paper is to approximate multidimensional functions f∈C(R^s) by developing a new type of Feedforward neural networks (FFNS) which we called it Greedy ridge function neural networks (GRGFNNS). Also, we introduce a modification to the greedy algorithm which is used to train the greedy ridge function neural networks. An error bound are introduced in Sobolov space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result in [1]).
This study examines the impact of different curing methods on the compressive strength of concrete. It investigates techniques such as air curing, periodic water spraying, full water submersion, and polyethylene encasement. Artificial neural network models were employed to evaluate the compressive strength under each curing condition. A model for calculating compressive strength that considers surrounding conditions was created using an artificial neural network. The current study’s figures were generated using this model. The research thoroughly examined the impact of curing environments and concrete mix components on strength properties, taking into account factors such as tempera
Steganography is a technique of concealing secret data within other quotidian files of the same or different types. Hiding data has been essential to digital information security. This work aims to design a stego method that can effectively hide a message inside the images of the video file. In this work, a video steganography model has been proposed through training a model to hiding video (or images) within another video using convolutional neural networks (CNN). By using a CNN in this approach, two main goals can be achieved for any steganographic methods which are, increasing security (hardness to observed and broken by used steganalysis program), this was achieved in this work as the weights and architecture are randomized. Thus,
... Show MoreDue to the high mobility and dynamic topology of the FANET network, maintaining communication links between UAVs is a challenging task. The topology of these networks is more dynamic than traditional mobile networks, which raises challenges for the routing protocol. The existing routing protocols for these networks partly fail to detect network topology changes. Few methods have recently been proposed to overcome this problem due to the rapid changes of network topology. We try to solve this problem by designing a new dynamic routing method for a group of UAVs using Hybrid SDN technology (SDN and a distributed routing protocol) with a highly dynamic topology. Comparison of the proposed method performance and two other algorithms is simula
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