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Design of New Hybrid Neural Controller for Nonlinear CSTR System based on Identification
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This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm namely Particle Swarm Optimization (PSO) algorithm. The numerical simulation results show that the hybrid NARMA-L2 controller with PSO algorithm is more accurate than BPA in terms of achieving fast learning and adjusting the parameters model with minimum number of iterations, minimum number of neurons in the hybrid network and the smooth output one step ahead prediction controller response for the nonlinear CSTR system without oscillation.

 

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Publication Date
Sat Oct 09 2021
Journal Name
Nanomaterials
Investigation of Heat Transfer Enhancement in a Triple Tube Latent Heat Storage System Using Circular Fins with Inline and Staggered Arrangements
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Inherent fluctuations in the availability of energy from renewables, particularly solar, remain a substantial impediment to their widespread deployment worldwide. Employing phase-change materials (PCMs) as media, saving energy for later consumption, offers a promising solution for overcoming the problem. However, the heat conductivities of most PCMs are limited, which severely limits the energy storage potential of these materials. This study suggests employing circular fins with staggered distribution to achieve improved thermal response rates of PCM in a vertical triple-tube heat exchanger involving two opposite flow streams of the heat-transfer fluid (HTF). Since heat diffusion is not the same at various portions of the PCM unit,

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Publication Date
Thu May 30 2024
Journal Name
Iraqi Journal Of Science
Bifurcation and Stability Analysis of Stagnation Point for Fluid Flow in an Inclined Channel with Inclined Magnetic Field for Peristaltic Transport
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Streamlined peristaltic transport patterns, bifurcations of equilibrium points, and effects of an inclined magnetic field and channel are shown in this study. The incompressible fluid has been the subject of the model's investigation. The Reynolds values for evanescence and an infinite wavelength are used to constrain the flow while it is being studied in a slanted channel with a slanted magnetic field. The topologies over their domestic and cosmopolitan bifurcations are investigated for the outcomes, and notion of the dynamical system are employed. The Mathematica software is used to solve the nonlinear autonomous system. The flow is found to have three different flow distributions namely augmented, trapping and backward flow. Outc

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Publication Date
Sat Aug 18 2018
Journal Name
Journal Of Engineering And Applied Sciences
Performance Evaluation of Transport Protocols for Mobile Ad Hoc Networks
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Mobile Ad hoc Networks (MANETs) is a wireless technology that plays an important role in several modern applications which include military, civil, health and real-time applications. Providing Quality of Service (QoS) for this application with network characterized by node mobility, infrastructure-less, limitation resource is a critical issue and takes greater attention. However, transport protocols effected influential on the performance of MANET application. This study provides an analysis and evaluation of the performance for TFRC, UDP and TCP transport protocols in MANET environment. In order to achieve high accuracy results, the three transport protocols are implemented and simulated with four different network topology which are 5, 10

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Publication Date
Mon May 01 2023
Journal Name
Journal Of Engineering
Measuring the Attribute Accuracy and Completeness for the OpenStreetMap Roads Networks for Two Regions in Iraq
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The OpenStreetMap (OSM) project aims to establish a free geospatial database for the entire world which is editable by international volunteers. The OSM database contains a wide range of different types of geographical data and characteristics, including highways, buildings, and land use regions. The varying scientific backgrounds of the volunteers can affect the quality of the spatial data that is produced and shared on the internet as an OSM dataset. This study aims to compare the completeness and attribute accuracy of the OSM road networks with the data supplied by a digitizing process for areas in the Baghdad and Thi-Qar governorates. The analyses are primarily based on calculating the portion of the commission (extr

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Publication Date
Sat Sep 30 2023
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The effect of operational efficiency on some financial indicators according to the CAMEL model of banking financial stability: An applied research on a sample of Iraqi private banks for the period 2010-2020
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Abstract

          The research aims to determine the nature of the Iraqi market in terms of banking financial stability and the extent impact of the operational efficiency on it, Accordingly, chosen 15 relational banks were chosen as an intentional sample that could represent the Iraqi banking system for the period 2010-2020. The operational efficiency variable was measured according to the data envelope model, and banking financial stability used  CAMELS model which includes five indicators (capital adequacy, asset quality, management quality, profitability, and liquidity), so for testing the research hypotheses used the random regression model by adopting the S

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Publication Date
Fri May 12 2023
Journal Name
Bulletin Of The Chemical Society Of Ethiopia
SYNTHESIS, CHARACTERIZATION, ANTIMICROBIAL STUDIES, AND MOLECULAR DOCKING STUDIES OF TRANSITION METAL COMPLEXES FORMED FROM A BENZOTHIAZOLE-BASED AZO LIGAND
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The azo ligand obtained from the diazotization reaction of 2-aminobenzothiazole and 4- nitroaniline yielded a novel series of complexes with Co(II), Ni(II), Cu(II), and Zn(II) ions. The complexes were investigated using spectral techniques such as UV-Vis, FT-IR, 1H and 13C NMR spectroscopic analyses, LC-MS and atomic absorption spectrometry, electrical conductivity, and magnetic susceptibility. The molar ratio of the synthesized compounds was determined using the ligand exchange ratio, which revealed the metal-ligand ratios in the isolated complexes were 1:2. The synthesized complexes were tested for antimicrobial activity against S. aureus, E. coli, C. albicans, and C. tropicalis bacterial species. Additionally, their binding affinities we

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Publication Date
Tue Jan 01 2019
Journal Name
Ieee Access
Sensing Performance of Modified Single Mode Optical Fiber Coated With Nanomaterials-Based Ammonia Sensors Operated in the C-Band
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Publication Date
Tue Sep 02 2025
Journal Name
Chemistry & Biodiversity
Synthesis, In Silico, and Biological Evaluation of Non‐Hydroxamate Benzoic Acid–Based Derivatives as Potential Histone Deacetylase Inhibitors (HDACi)
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ABSTRACT<p>Unregulated epigenetic modifications, including histone acetylation/deacetylation mediated by histone acetyltransferases (HATs) and histone deacetylases (HDACs), contribute to cancer progression. HDACs, often overexpressed in cancer, downregulate tumor suppressor genes, making them crucial targets for treatment. This work aimed to develop non‐hydroxamate benzoic acid–based HDAC inhibitors (HDACi) with comparable effect to the currently four FDA‐approved HDACi, which are known for their poor solubility, poor distribution, and significant side effects. All compounds were structurally verified using FTIR, <sup>1</sup>HNMR, <sup>13</sup>CNMR, and mass spectrometry. In silico ana</p> ... Show More
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Publication Date
Wed Nov 23 2022
Journal Name
Dental Hypotheses
Remineralization of Dentine Caries Using Moringa Oleifera Based Nano-Silver Fluoride: A Single-Blinded, Randomized, Active-Controlled Clinical Trial
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Publication Date
Sat Apr 30 2022
Journal Name
Revue D'intelligence Artificielle
Performance Evaluation of SDN DDoS Attack Detection and Mitigation Based Random Forest and K-Nearest Neighbors Machine Learning Algorithms
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Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne

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