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Implementation of artificial neural network to achieve speed control and power saving of a belt conveyor system
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According to the importance of the conveyor systems in various industrial and service lines, it is very desirable to make these systems as efficient as possible in their work. In this paper, the speed of a conveyor belt (which is in our study a part of an integrated training robotic system) is controlled using one of the artificial intelligence methods, which is the Artificial Neural Network (ANN). A visions sensor will be responsible for gathering information about the status of the conveyor belt and parts over it, where, according to this information, an intelligent decision about the belt speed will be taken by the ANN controller. ANN will control the alteration in speed in a way that gives the optimized energy efficiency through the conveyor belt motion. An optimal speed controlling mechanism of the conveyor belt is presented by detecting smartly the parts' number and weights using the vision sensor, where the latter will give sufficient visualization about the system. Then image processing will deliver the important data to ANN, which will optimally decide the best conveyor belt speed. This decided speed will achieve the aim of power saving in belt motion. The proposed controlling system will optimally switch the speed of the conveyor belt system to ON, OFF and idle status in order to minimize the consumption of energy in the conveyor belt. As the conveyor belt is fully loaded it moves at its maximum speed. But if the conveyor is partially loaded, the speed will be adjusted accordingly by the ANN. If no loading existed, the conveyor will be stopped. By this way, a very significant energy amount in addition to cost will be saved. The developed conveyor belt system will modernize industrial manufacturing lines, besides reducing energy consumption and cost and increasing the conveyor belts lifetime

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Publication Date
Sun Dec 01 2019
Journal Name
Ieee Xplore
A Hybrid Modified Lightweight Algorithm Combined of Two Cryptography Algorithms PRESENT and Salsa20 Using Chaotic System
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Cryptography algorithms play a critical role in information technology against various attacks witnessed in the digital era. Many studies and algorithms are done to achieve security issues for information systems. The high complexity of computational operations characterizes the traditional cryptography algorithms. On the other hand, lightweight algorithms are the way to solve most of the security issues that encounter applying traditional cryptography in constrained devices. However, a symmetric cipher is widely applied for ensuring the security of data communication in constraint devices. In this study, we proposed a hybrid algorithm based on two cryptography algorithms PRESENT and Salsa20. Also, a 2D logistic map of a chaotic system is a

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Publication Date
Wed Jun 01 2022
Journal Name
Baghdad Science Journal
Design and Performance Investigation of a Solar- Powered Biological Greywater Treatment System in the Iraqi Climate
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            The increase in population resulted in an increase in the consumption of water. The present work investigates the performance of a recycling solar- powered greywater treatment system for the purposes of irrigation, used to reduce the amount of waste grey water and reduce electricity consumption and reduce the costs of constructing large scale water treatment plants. The system consumes about 3814W per hour and provides water treatment about 1.4 m3 per day. The proposed system is designed to    residential, office and governmental buildings application. Tests are conducted in an office building at the Ministry of Science and Technology site in Baghdad. Laboratorial water samples testing analyses are co

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Publication Date
Thu Feb 01 2018
Journal Name
Applied Energy
Solidification enhancement of PCM in a triplex-tube thermal energy storage system with nanoparticles and fins
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Publication Date
Sun Dec 02 2012
Journal Name
Baghdad Science Journal
Stability of Back Propagation Training Algorithm for Neural Networks
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In this paper, we derive and prove the stability bounds of the momentum coefficient µ and the learning rate ? of the back propagation updating rule in Artificial Neural Networks .The theoretical upper bound of learning rate ? is derived and its practical approximation is obtained

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Publication Date
Mon Oct 02 2023
Journal Name
Journal Of Engineering
The Applicability of Multiple MCDM Techniques for Implementation in the Priority of Road Maintenance
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Priority of road maintenance can be viewed as a process influenced by decision-makers with varying decision-making power. Each decision-maker may have their view and judgment depending on their function and responsibilities. Therefore, determining the priority of road maintenance can be thought of as a process of MCDM. Regarding the priority of road maintenance, this is a difficult MCDM problem involving uncertainty, qualitative criteria, and possible causal relationships between choice criteria. This paper aims to examine the applicability of multiple MCDM techniques, which are used for assessing the priority of road maintenance, by adapting them to this sector. Priority of road maintenance problems subject to internal

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Publication Date
Thu Jun 27 2024
Journal Name
Journal Of Image And Graphics
ALL-FABNET: Acute Lymphocytic Leukemia Segmentation Using a Flipping Attention Block Decoder-Encoder Network
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Melanoma, a highly malignant form of skin cancer, affects individuals of all genders and is associated with high mortality rates, especially in advanced stages. The use of tele-dermatology has emerged as a proficient diagnostic approach for skin lesions and is particularly beneficial in rural areas with limited access to dermatologists. However, accurately, and efficiently segmenting melanoma remains a challenging task due to the significant diversity observed in the morphology, pigmentation, and dimensions of cutaneous nevi. To address this challenge, we propose a novel approach called DenseUNet-169 with a dilated convolution encoder-decoder for automatic segmentation of RGB dermascopic images. By incorporating dilated convolution,

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Publication Date
Wed Nov 12 2025
Journal Name
Journal Of Baghdad College Of Dentistry
The effect of curvature angle and rotational speed on the cyclic fatigue of three types of rotary instrument (In vitro): comparative study
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Background: The fracture of instruments within root canal during endodontic treatment is a common incidence, fracture because of fatigue through flexure occurs due to metal fatigue, this study aimed to assess the effect of curvature angle and rotational speed on the cyclic fatigue of different type of Endodontic NiTi Rotary Instruments and compare among them. Materials and method: Three types of rotary instruments with tip size 0.25: ProTaPer F2 (Densply, Malifier) Revo-S SU( 0.06 taper, MicroMega) and RaCe system (0.06 taper, FKG, Dentaire), Forty file of each instrument were used within two canals with angle of curvature (40 &60 )at two speed (250&400)RPM, twelve group were formed for all instruments(total number=120),ten file fo

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Publication Date
Sun Oct 01 2017
Journal Name
Iecon 2017 - 43rd Annual Conference Of The Ieee Industrial Electronics Society
Optimal second order integral sliding mode control for a flexible joint robot manipulator
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The flexible joint robot manipulators provide various benefits, but also present many control challenges such as nonlinearities, strong coupling, vibration, etc. This paper proposes optimal second order integral sliding mode control (OSOISMC) for a single link flexible joint manipulator to achieve robust and smooth performance. Firstly, the integral sliding mode control is designed, which consists of a linear quadratic regulator (LQR) as a nominal control, and switching control. This control guarantees the system robustness for the entire process. Then, a nonsingularterminal sliding surface is added to give a second order integral sliding mode control (SOISMC), which reduces chartering effect and gives the finite time convergence as well. S

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Publication Date
Mon Sep 01 2014
Journal Name
Al-khwarizmi Engineering Journal
Trajectory Tracking Control for a Wheeled Mobile Robot Using Fractional Order PIaDb Controller
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Nowadays, Wheeled Mobile Robots (WMRs) have found many applications as industry, transportation, inspection, and other fields. Therefore, the trajectory tracking control of the nonholonomic wheeled mobile robots have an important problem. This work focus on the application of model-based on Fractional Order  PIaDb (FOPID) controller for trajectory tracking problem. The control algorithm based on the errors in postures of mobile robot which feed to FOPID controller to generate correction signals that transport to  torque for each driven wheel, and by means of dynamics model of mobile robot these torques used to compute the linear and angular speed to reach the desired pose. In this work a dynamics model of

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Publication Date
Tue Aug 06 2013
Journal Name
Robotica
Function approximation technique-based adaptive virtual decomposition control for a serial-chain manipulator
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SUMMARY<p>The virtual decomposition control (VDC) is an efficient tool suitable to deal with the full-dynamics-based control problem of complex robots. However, the regressor-based adaptive control used by VDC to control every subsystem and to estimate the unknown parameters demands specific knowledge about the system physics. Therefore, in this paper, we focus on reorganizing the equation of the VDC for a serial chain manipulator using the adaptive function approximation technique (FAT) without needing specific system physics. The dynamic matrices of the dynamic equation of every subsystem (e.g. link and joint) are approximated by orthogonal functions due to the minimum approximation errors produced. The contr</p> ... Show More
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