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Embedded Neural Network like PID Water Heating Controller Implementing Cycle by Cycle Power Control Scheme
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This paper experimentally investigates the heating process of a hot water supply using a neural network implementation of a self-tuning PID controller on a microcontroller system. The Particle Swarm Optimization (PSO) algorithm employed in system tuning proved very effective, as it is simple and fast optimization algorithm. The PSO method for the PID parameters is executed on the Matlab platform in order to put these parameters in the real-time digital PID controller, which was experimented with in a pilot study on a microcontroller platform. Instead of the traditional phase angle power control (PAPC) method, the Cycle by Cycle Power Control (CBCPC) method is implemented because it yields better power factor and eliminates harmonics in the power supply line. The smoothness of the heating process’s output response, which is a result of both empirical experiments and simulation results, demonstrates the efficacy of the suggested control mechanism, where the output response had a small ripple margin. The system performed according to design expectations and had unimpaired unity power factor throughout its operating range and no ripple was detected during its functioning.

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Publication Date
Thu Jun 01 2023
Journal Name
Journal Of Engineering
Automatic Spike Neural Technique for Slicing Bandwidth Estimated Virtual Buffer-Size in Network Environment
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The Next-generation networks, such as 5G and 6G, need capacity and requirements for low latency, and high dependability. According to experts, one of the most important features of (5 and 6) G networks is network slicing. To enhance the Quality of Service (QoS), network operators may now operate many instances on the same infrastructure due to configuring able slicing QoS. Each virtualized network resource, such as connection bandwidth, buffer size, and computing functions, may have a varied number of virtualized network resources. Because network resources are limited, virtual resources of the slices must be carefully coordinated to meet the different QoS requirements of users and services. These networks may be modifie

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Publication Date
Thu Jun 01 2023
Journal Name
Journal Of Engineering
Fault Location of Doukan-Erbil 132kv Double Transmission Lines Using Artificial Neural Network ANN
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Transmission lines are generally subjected to faults, so it is advantageous to determine these faults as quickly as possible. This study uses an Artificial Neural Network technique to locate a fault as soon as it happens on the Doukan-Erbil of 132kv double Transmission lines network. CYME 7.1-Programming/Simulink utilized simulation to model the suggested network. A multilayer perceptron feed-forward artificial neural network with a back propagation learning algorithm is used for the intelligence locator's training, testing, assessment, and validation. Voltages and currents were applied as inputs during the neural network's training. The pre-fault and post-fault values determined the scaled values. The neural network's p

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Publication Date
Tue Sep 01 2020
Journal Name
Baghdad Science Journal
Developing Arabic License Plate Recognition System Using Artificial Neural Network and Canny Edge Detection
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            In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the roads in all the sections of the country. Arabic vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the proposed system consists of three phases, vehicle license plate localization, character segmentation, and character recognition, the

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Publication Date
Tue Dec 31 2024
Journal Name
Iraqi Geological Journal
Geomechanical Modeling and Artificial Neural Network Technique for Predicting Breakout Failure in Nasiriyah Oilfield
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Wellbore instability is one of the major issues observed throughout the drilling operation. Various wellbore instability issues may occur during drilling operations, including tight holes, borehole collapse, stuck pipe, and shale caving. Rock failure criteria are important in geomechanical analysis since they predict shear and tensile failures. A suitable failure criterion must match the rock failure, which a caliper log can detect to estimate the optimal mud weight. Lack of data makes certain wells' caliper logs unavailable. This makes it difficult to validate the performance of each failure criterion. This paper proposes an approach for predicting the breakout zones in the Nasiriyah oil field using an artificial neural network. It

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Publication Date
Mon Jul 15 2024
Journal Name
2024 46th Annual International Conference Of The Ieee Engineering In Medicine And Biology Society (embc)
Automatic COVID-19 Detection from Chest X-ray using Deep MobileNet Convolutional Neural Network
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Publication Date
Mon Jul 31 2017
Journal Name
Journal Of Engineering
Development of an On-Line Self-Tuning FPGA-PID-PWM Control Algorithm Design for DC-DC Buck Converter in Mobile Applications
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Publication Date
Wed Dec 11 2019
Journal Name
Aip Conference Proceedings
Mass stopping power of alpha particles in liquid water and some gases
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The interaction of charged particles with the chemical elements involved in the synthesis of human tissues is one of the modern techniques in radiation therapy. One of these charged particles are alpha particles, where recent studies have confirmed their ability to generate radiation in a highly toxic localized manner because of its high ionization and short its range. In this work, We focused our study on the interaction of alpha particles with liquid water; since the water represents over 80% of the most-soft tissues, as well as, hydrogen, oxygen, and nitrogen ,because they are key chemical elements involved in the synthesis of most human tissues. The mass stopping powers of alpha particle with HଶO , COଶ, Oଶ, Hଶ and Nଶhave

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Publication Date
Tue May 16 2023
Journal Name
Journal Of Engineering
Traveling Wave Cylindrical Induction Heating System
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The paper deals with the traveling wave cylindrical heating systems. The analysis presented is analytical and a multi-layer model using cylindrical geometry is used to obtain the theoretical results. To validate the theoretical results, a practical model is constructed, tested and the results are compared with the theoretical ones. Comparison showed that the adopted analytical method is efficient in describing the performance of such induction heating systems.

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Publication Date
Sun Apr 08 2018
Journal Name
Al-khwarizmi Engineering Journal
Experimental Study on Solar Air Heating
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Abstract

 

A new type of solar air heater was designed, fabricated, and tested in Baghdad, Iraq winter conditions. The heater consists of two main parts. The horizontal section was filled with the black colored iron chip while the vertical part has five pipes filled with Iraqi paraffin wax. A fan was fixed at the exit of the air. Two cases were studied: when the air moved by natural convection and when forced convection moved it. The studied air heater has proven its effectiveness as it heated the air passing through it to high temperatures. The results manifest that using little air movement makes the temperatures, stored energies, and efficiencies of the two studied cases converge

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Publication Date
Tue Dec 01 2020
Journal Name
Journal Of Engineering
Performance of 2- Link Robot by utilizing Adaptive Sliding Mode Controller
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The Sliding Mode Control (SMC) has been among powerful control techniques increasingly. Much attention is paid to both theoretical and practical aspects of disciplines due to their distinctive characteristics such as insensitivity to bounded matched uncertainties, reduction of the order of sliding equations of motion, decoupling mechanical systems design. In the current study, two-link robot performance in the Classical SMC is enhanced via Adaptive Sliding Mode Controller (ASMC) despite uncertainty, external disturbance, and coulomb friction. The key idea is abstracted as follows: switching gains are depressed to the low allowable values, resulting in decreased chattering motion and control's efforts of the two-link robo

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