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Particle swarm optimization technique-based prediction of peak ground acceleration of Iraq’s tectonic regions
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Peak ground acceleration (PGA) is one of the critical factors that affect the determination of earthquake intensity. PGA is generally utilized to describe ground motion in a particular zone and is able to efficiently predict the parameters of site ground motion for the design of engineering structures. Therefore, novel models are developed to forecast PGA in the case of the Iraqi database, which utilizes the particle swarm optimization (PSO) approach. A data set of 187 historical ground-motion recordings in Iraq’s tectonic regions was used to build the explicit proposed models. The proposed PGA models relate to different seismic parameters, including the magnitude of the earthquake (Mw), average shear-wave velocity (VS30), focal depth (FD), and nearest epicenter distance (REPi) to a seismic station. The derived PGA models are remarkably simple and straightforward and can be used reliably for pre-design purposes. The proposed PGA models (i.e., models I and II) obtained via the explicit formula produced using the PSO method are highly correlated to the actual PGA records owing to low coefficients of variation (CoV) of approximately 2.12% and 2.06%, and mean values (i.e., close to 1.0) of approximately 1.005 and 1.004. Lastly, high-frequency, low absolute relative error (ARE), which is below 5%, is recorded for the proposed models, thereby showing an acceptable error distribution.

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Compression-based Data Reduction Technique for IoT Sensor Networks
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Energy savings are very common in IoT sensor networks because IoT sensor nodes operate with their own limited battery. The data transmission in the IoT sensor nodes is very costly and consume much of the energy while the energy usage for data processing is considerably lower. There are several energy-saving strategies and principles, mainly dedicated to reducing the transmission of data. Therefore, with minimizing data transfers in IoT sensor networks, can conserve a considerable amount of energy. In this research, a Compression-Based Data Reduction (CBDR) technique was suggested which works in the level of IoT sensor nodes. The CBDR includes two stages of compression, a lossy SAX Quantization stage which reduces the dynamic range of the

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Publication Date
Fri Dec 31 2010
Journal Name
International Journal Of Advancements In Computing Technology
A proposed Technique for Information Hiding Based on DCT
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The aim of this work is to design an algorithm which combines between steganography andcryptography that can hide a text in an image in a way that prevents, as much as possible, anysuspicion of the hidden textThe proposed system depends upon preparing the image data for the next step (DCT Quantization)through steganographic process and using two levels of security: the RSA algorithm and the digitalsignature, then storing the image in a JPEG format. In this case, the secret message will be looked asplaintext with digital signature while the cover is a coloured image. Then, the results of the algorithmare submitted to many criteria in order to be evaluated that prove the sufficiency of the algorithm andits activity. Thus, the proposed algorit

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Publication Date
Mon Jan 28 2013
Journal Name
Spie Proceedings
Enhancement of security for free space optics based on reconfigurable chaotic technique
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Free Space Optical (FSO) technology offers highly directional, high bandwidth communication channels. This technology can provide fiber-like data rate over short distances. In order to improve security associated with data transmission in FSO networks, a secure communication method based on chaotic technique is presented. In this paper, we have turned our focus on a specific class of piece wise linear one-dimensional chaotic maps. Simulation results indicate that this approach has the advantage of possessing excellent correlation property. In this paper we examine the security vulnerabilities of single FSO links and propose a solution to this problem by implementing the chaotic signal generator “reconfigurable tent map”. As synchronizat

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Publication Date
Wed Jul 01 2015
Journal Name
Advanced Powder Technology
Characterization of nano-silica prepared from local silica sand and its application in cement mortar using optimization technique
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Publication Date
Wed Mar 24 2021
Journal Name
Ieee Access
Smart IoT Network Based Convolutional Recurrent Neural Network With Element-Wise Prediction System
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An Intelligent Internet of Things network based on an Artificial Intelligent System, can substantially control and reduce the congestion effects in the network. In this paper, an artificial intelligent system is proposed for eliminating the congestion effects in traffic load in an Intelligent Internet of Things network based on a deep learning Convolutional Recurrent Neural Network with a modified Element-wise Attention Gate. The invisible layer of the modified Element-wise Attention Gate structure has self-feedback to increase its long short-term memory. The artificial intelligent system is implemented for next step ahead traffic estimation and clustering the network. In the proposed architecture, each sensing node is adaptive and able to

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Publication Date
Sun Dec 09 2018
Journal Name
Baghdad Science Journal
An Epidemiological, Diagnostic, and Therapeutic Study of the Leishmania tropica Parasite in Iraq’s Anbar Province
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This paper involved the registration of 1,936 cases of infection of the Leishmania tropica parasite observed at hospitals and health centers in Ramadi, Fallujah, Baghdadi, and Hit during 2017. The results revealed that the highest rates of infection were found in Ramadi and Fallujah. The 1-10 years age group recorded the highest rate at 35.5%. There was no significant difference (p ≥ 0.05) between the sexes. December and January saw the highest rate of infection, where the rate in rural townships was found to be 65.5%, higher than in urban regions which saw a rate of 34.4%. Facial lesions were the most prominent area of infection, recorded at a rate of 41.3%. The study also included an examination of 180 rodents (94 mice and 86 black r

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Publication Date
Mon Jul 01 2019
Journal Name
International Journal Of Swarm Intelligence Research
A New Strategy Based on GSABAT to Solve Single Objective Optimization Problem
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This article proposes a new strategy based on a hybrid method that combines the gravitational search algorithm (GSA) with the bat algorithm (BAT) to solve a single-objective optimization problem. It first runs GSA, followed by BAT as the second step. The proposed approach relies on a parameter between 0 and 1 to address the problem of falling into local research because the lack of a local search mechanism increases intensity search, whereas diversity remains high and easily falls into the local optimum. The improvement is equivalent to the speed of the original BAT. Access speed is increased for the best solution. All solutions in the population are updated before the end of the operation of the proposed algorithm. The diversification f

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Publication Date
Sat Dec 01 2018
Journal Name
2018 Third Scientific Conference Of Electrical Engineering (scee)
An Intelligent Cognitive System Design for Mobile Robot based on Optimization Algorithm
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Publication Date
Sat Jun 29 2013
Journal Name
Wireless Personal Communications
A Low Cost Route Optimization Scheme for Cluster-Based Proxy MIPv6 Protocol
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Publication Date
Sat Jun 30 2007
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Drag Forces under Longitudinal Interaction of Two Particle
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Direct measurements of drag force on two interacting particles  arranged in the longitudinal direction for particle Reynolds numbers varying from J O to 103 are conducted using a micro-force measurement system. The effect of the interparticle distance and Reynolds number on the drag forces  is examined. An empirical equation is obtained to describe the effect of the interparticle distance (l/d) on the dimensionless drag.

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