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Enhanced Chain-Cluster Based Mixed Routing Algorithm for Wireless Sensor Networks
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Energy efficiency is a significant aspect in designing robust routing protocols for wireless sensor networks (WSNs). A reliable routing protocol has to be energy efficient and adaptive to the network size. To achieve high energy conservation and data aggregation, there are two major techniques, clusters and chains. In clustering technique, sensor networks are often divided into non-overlapping subsets called clusters. In chain technique, sensor nodes will be connected with the closest two neighbors, starting with the farthest node from the base station till the closest node to the base station. Each technique has its own advantages and disadvantages which motivate some researchers to come up with a hybrid routing algorithm that combines the full advantages of both cluster and chain techniques such as CCM (Chain-Cluster based Mixed routing). In this paper, introduce a routing algorithm relying on CCM algorithm called (Enhanced Chain-Cluster based Mixed routing) algorithm E-CCM. Simulation results show that E-CCM algorithm improves the performance of CCM algorithm in terms of three performance metrics which are: energy consumption, network lifetime, and (FND and LND). MATLAB program is used to develop and test the simulation process in a computer with the following specifications: windows 7 (32-operating system), core i5, RAM 4 GB, hard 512 GB.

 

 

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Publication Date
Sun May 01 2022
Journal Name
Journal Of Engineering
Attitude and Altitude Control of Quadrotor Carrying a Suspended Payload using Genetic Algorithm
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The need for quick airborne transportation is critical, especially in emergencies. Drones with suspended payloads might be used to accomplish quick airborne transportation. Due to the environment or the drone's motion, the slung load may oscillate and lead the drone to fall. The altitude and attitude controls are the backbones of the drone's stability, and they must be adequately designed. Because of their symmetrical and simple structure, quadrotor helicopters are one of the most popular drone classes. In this work, a genetic algorithm with two weighted terms fitness function is used to adjust a Proportional-Integral-Derivative (PID) controller to compensate for the altitude and attitude controllers in a quadrotor drone

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Publication Date
Wed Feb 27 2019
Journal Name
Journal Of Nano Research
A Specific NH<sub>3</sub> Gas Sensor of a Thick MWCNTs-OH Network for Detection at Room Temperature
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NH3 gas sensor was fabricated based on deposited of Functionalized Multi-Walled Carbon Nanotubes (MWCNTs-OH) suspension on filter paper substrates using suspension filtration method. The structural, morphological and optical properties of the MWCNTs film were characterized by XRD, AFM and FTIR techniques. XRD measurement confirmed that the structure of MWCNTs is not affected by the preparation method. The AFM images reflected highly ordered network in the form of a mat. The functional groups and types of bonding have appeared in the FTIR spectra. The fingerprint (C-C stretch) of MWCNTs appears in 1365 cm-1, and the backbone of CNTs observed at 1645 cm-1. A homemade sensi

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Publication Date
Thu Apr 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Comparison Branch and Bound Algorithm with Penalty Function Method for solving Non-linear Bi-level programming with application
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The problem of Bi-level programming is to reduce or maximize the function of the target by having another target function within the constraints. This problem has received a great deal of attention in the programming community due to the proliferation of applications and the use of evolutionary algorithms in addressing this kind of problem. Two non-linear bi-level programming methods are used in this paper. The goal is to achieve the optimal solution through the simulation method using the Monte Carlo method using different small and large sample sizes. The research reached the Branch Bound algorithm was preferred in solving the problem of non-linear two-level programming this is because the results were better.

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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Preparation, Characterization & Biological activity for Some Iron(II) Complexes Containing Mixed Ligands (Benzilazine & Semicarbazone) & Study of Laser Effect on Them
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The research included preparation of new iron(II) complexes with mixed ligands including benzilazine(BA) and semicarbazone ligands {benzilsemicarbazone- BSCH or benzilbis(semicarba-zone)- BBSCH2 or salicylaldehydesemicarbazone- SSCH2 or benzoinsemicarbazone- B'SCH2}.by classical and microwave methods. The resulted complexes have been characterized using chemical and physical methods. The study suggested that the above ligands form ionic complexes having formulae [Fe(SCHi)(BA)(Cl)m](Cl)2-m {where SCH, BSCH, BBSCH2, SSCH¬2 or B'SCH2 ligands; m=1 or 2}. Hexacoordinated mononuclear complexes have been investigated by this study and having octahedral geometries. The effect of laser ray type visible region have been studied on solid ligands and

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Publication Date
Mon Mar 11 2019
Journal Name
Baghdad Science Journal
Developing Load Balancing for IoT - Cloud Computing Based on Advanced Firefly and Weighted Round Robin Algorithms
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The evolution of the Internet of things (IoT) led to connect billions of heterogeneous physical devices together to improve the quality of human life by collecting data from their environment. However, there is a need to store huge data in big storage and high computational capabilities.   Cloud computing can be used to store big data.  The data of IoT devices is transferred using two types of protocols: Message Queuing Telemetry Transport (MQTT) and Hypertext Transfer Protocol (HTTP). This paper aims to make a high performance and more reliable system through efficient use of resources. Thus, load balancing in cloud computing is used to dynamically distribute the workload across nodes to avoid overloading any individual r

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Publication Date
Mon Jan 01 2024
Journal Name
Baghdad Science Journal
A Theoretical Investigation of Chemical Bonding of a Heterometallic Trinuclear Cluster Containing Iridium and Ruthenium: [(Cp*Ir) (CpRu)2 (μ3-H) (μ-H)3] by QTAIM Approach
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  Numerous integral and local electron density’s topological parameters of significant metal-metal and metal-ligand bonding interactions in a trinuclear tetrahydrido cluster [(Cp* Ir) (Cp Ru)23-H) (μ-H)3]1 (Cp = η5 -C5Me5), (Cp* = η5 -C5Me4Et) were calculated and interpreted by using the quantum theory of atoms in molecules (QTAIM). The properties of bond critical points such as the delocalization indices δ (A, B), the electron density ρ(r), the local kinetic energy density G(r), the Laplacian of the electron density 2ρ(r), the local energy density

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Publication Date
Tue Jan 01 2019
Journal Name
International Journal Of Supply Chain Management
The effect of internal training and auditing of auditors on supply chain management: An empirical study in listed companies of Iraqi stock exchange for the period 2012-2015
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Publication Date
Mon Jan 01 2018
Journal Name
Journal Of Physics Conference Series
Enhanced phot-respons of porous silicon photo- detectors by embedding Titanium -dioxide nano-particles
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: Porous silicon (n-PS) films can be prepared by photoelectochemical etching (PECE) Silicon chips n - types with 15 (mA /cm2), in15 minutes etching time on the fabrication nano-sized pore arrangement. By using X-ray diffraction measurement and atomic power microscopy characteristics (AFM), PS was investigated. It was also evaluated the crystallites size from (XRD) for the PS nanoscale. The atomic force microscopy confirmed the nano-metric size chemical fictionalization through the electrochemical etching that was shown on the PS surface chemical composition. The atomic power microscopy checks showed the roughness of the silicon surface. It is also notified (TiO2) preparation nano-particles that were prepared by pulse laser eradication in e

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Publication Date
Sat Oct 04 2025
Journal Name
Mesopotamian Journal Of Computer Science
Enhanced IOT Cyber-Attack Detection Using Grey Wolf Optimized Feature Selection and Adaptive SMOTE
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The Internet of Things (IoT) has significantly transformed modern systems through extensive connectivity but has also concurrently introduced considerable cybersecurity risks. Traditional rule-based methods are becoming increasingly insufficient in the face of evolving cyber threats.  This study proposes an enhanced methodology utilizing a hybrid machine-learning framework for IoT cyber-attack detection. The framework integrates a Grey Wolf Optimizer (GWO) for optimal feature selection, a customized synthetic minority oversampling technique (SMOTE) for data balancing, and a systematic approach to hyperparameter tuning of ensemble algorithms: Random Forest (RF), XGBoost, and CatBoost. Evaluations on the RT-IoT2022 dataset demonstrat

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Publication Date
Wed Jan 01 2025
Journal Name
Ieee Access
Enhanced Spectral Efficiency in RIS-Assisted MIMO Systems Through Joint Precoding and RIS Configuration
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