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Improving the Network Lifetime in Wireless Sensor Network for Internet of Thing Applications
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Mobile Wireless sensor networks have acquired a great interest recently due to their capability to provide good solutions and low-priced in multiple fields. Internet of Things (IoT) connects different technologies such as sensing, communication, networking, and cloud computing. It can be used in monitoring, health care and smart cities. The most suitable infrastructure for IoT application is wireless sensor networks. One of the main defiance of WSNs is the power limitation of the sensor node. Clustering model is an actual way to eliminate the inspired power during the transmission of the sensed data to a central point called a Base Station (BS). In this paper, efficient clustering protocols are offered to prolong network lifetime. A kernel-based fuzzy C-means clustering algorithm (KFCM) is adopted to cluster sensor nodes, while a cluster head (CH) is selected for each cluster based on a fuzzy logic system. Results depicts that the new work performs better than the existing algorithms (as Low Energy Adaptive Cluster Hierarchy-Mobile (LEACH-M) and Low Energy Adaptive Cluster Hierarchy-Mobile Enhancement (LEACH-ME)) in terms of network lifetime, energy consumption, packet transmission and stability period.

 

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Publication Date
Wed Mar 31 2021
Journal Name
Electronics
Adaptive Robust Controller Design-Based RBF Neural Network for Aerial Robot Arm Model
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Aerial Robot Arms (ARAs) enable aerial drones to interact and influence objects in various environments. Traditional ARA controllers need the availability of a high-precision model to avoid high control chattering. Furthermore, in practical applications of aerial object manipulation, the payloads that ARAs can handle vary, depending on the nature of the task. The high uncertainties due to modeling errors and an unknown payload are inversely proportional to the stability of ARAs. To address the issue of stability, a new adaptive robust controller, based on the Radial Basis Function (RBF) neural network, is proposed. A three-tier approach is also followed. Firstly, a detailed new model for the ARA is derived using the Lagrange–d’A

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Publication Date
Wed Dec 30 2009
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of the Point Efficiency of Sieve Tray Using Artificial Neural Network
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An application of neural network technique was introduced in modeling the point efficiency of sieve tray, based on a
data bank of around 33l data points collected from the open literature.Two models proposed,using back-propagation
algorithm, the first model network consists: volumetric liquid flow rate (QL), F foctor for gas (FS), liquid density (pL),
gas density (pg), liquid viscosity (pL), gas viscosity (pg), hole diameter (dH), weir height (hw), pressure (P) and surface
tension between liquid phase and gas phase (o). In the second network, there are six parameters as dimensionless
group: Flowfactor (F), Reynolds number for liquid (ReL), Reynolds number for gas through hole (Reg), ratio of weir
height to hole diqmeter

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Publication Date
Sun Aug 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
The role of organizational symmetry in improving the quality of work life an applied research at the University of Information and Communications Technology
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"The aim of the research is to identify the availability of the dimensions of the research variables represented by organizational symmetry and the quality of work-life at the University of Information and Communications Technology, which is one of the formations of the Ministry of Higher Education and Scientific Research in Baghdad, in addition to knowing the relationship and influence between them. The research relied on the descriptive analytical approach based on peer description. The research was analyzed and the research sample consisted of (148) individuals, the sample was chosen using the comprehensive inventory method, data was obtained by relying on the questionnaire which was prepared from ready-made m

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Publication Date
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Comparison Study of Electromyography Using Wavelet and Neural Network
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In this paper we present a method to analyze five types with fifteen wavelet families for eighteen different EMG signals. A comparison study is also given to show performance of various families after modifying the results with back propagation Neural Network. This is actually will help the researchers with the first step of EMG analysis. Huge sets of results (more than 100 sets) are proposed and then classified to be discussed and reach the final.

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Publication Date
Tue Jan 17 2017
Journal Name
International Journal Of Science And Research (ijsr)
Detection System of Varicose Disease using Probabilistic Neural Network
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Publication Date
Thu Nov 17 2022
Journal Name
Journal Of Discrete Mathematical Sciences And Cryptography
Minimum spanning tree application in Covid-19 network structure analysis in the countries of the Middle East
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Coronavirus disease (Covid-19) has threatened human life, so it has become necessary to study this disease from many aspects. This study aims to identify the nature of the effect of interdependence between these countries and the impact of each other on each other by designating these countries as heads for the proposed graph and measuring the distance between them using the ultrametric spanning tree. In this paper, a network of countries in the Middle East is described using the tools of graph theory.

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Publication Date
Sun Dec 31 2017
Journal Name
Al-khwarizmi Engineering Journal
Solving the Inverse Kinematic Equations of Elastic Robot Arm Utilizing Neural Network
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The inverse kinematic equation for a robot is very important to the control robot’s motion and position. The solving of this equation is complex for the rigid robot due to the dependency of this equation on the joint configuration and structure of robot link. In light robot arms, where the flexibility exists, the solving of this problem is more complicated than the rigid link robot because the deformation variables (elongation and bending) are present in the forward kinematic equation. The finding of an inverse kinematic equation needs to obtain the relation between the joint angles and both of the end-effector position and deformations variables. In this work, a neural network has been proposed to solve the problem of inverse kinemati

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Publication Date
Mon Jan 01 2024
Journal Name
Proceedings Of The 31th Minisymposium
Towards the Requirement-Driven Generation and Evaluation of Hyperledger Fabric Network Designs
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Publication Date
Thu May 05 2016
Journal Name
Global Journal Of Engineering Science And Researches
EVALUATE THE RATE OF CONTAMINATION SOILS BY COPPER USING NEURAL NETWORK TECHNIQUE
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The aim of this paper is to design suitable neural network (ANN) as an alternative accurate tool to evaluate concentration of Copper in contaminated soils. First, sixteen (4x4) soil samples were harvested from a phytoremediated contaminated site located in Baghdad city in Iraq. Second, a series of measurements were performed on the soil samples. Third, design an ANN and its performance was evaluated using a test data set and then applied to estimate the concentration of Copper. The performance of the ANN technique was compared with the traditional laboratory inspecting using the training and test data sets. The results of this study show that the ANN technique trained on experimental measurements can be successfully applied to the rapid est

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Publication Date
Fri Apr 12 2019
Journal Name
Journal Of Economics And Administrative Sciences
Balanced Scorecard (BSC) role And Six Sigma in improving strategic performance A sample study of the members of the General Company for Northern Cement
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Assessing performance efficiency is critical to the management need for oversight, planning, and continuous periodic evaluation of the multiple activities of Northern Cement State Company in order to determine the level of achievement of the objectives set, and to correct the deviations and delays that the evaluation shows and limitation of liability. What cannot be measured cannot be managed. The aim of this research is to highlight the impact of using BSC, financial and non-financial, to give comprehensive and clear picture of the company's performance and to measure the quality of its performance by using six-sigma and the level of deviations in achieving the planned goals. Therefore, four-key hypotheses were formulated for th

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