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Optimal Hybrid Fuzzy PID for Pitch Angle Controller in Horizontal Axis Wind Turbines
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Wind turbine (WT) is now a major renewable energy resource used in the modern world. One of the most significant technologies that use the wind speed (WS) to generate electric power is the horizontal-axis wind turbine. In order to enhance the output power over the rated WS, the blade pitch angle (BPA) is controlled and adjusted in WT. This paper proposes and compares three different controllers of BPA for a 500-kw WT. A PID controller (PIDC), a fuzzy logic controller (FLC) based on Mamdani and Sugeno fuzzy inference systems (FIS), and a hybrid fuzzy-PID controller (HFPIDC) have been applied and compared. Furthermore, Genetic Algorithm (GA) and Particle swarm optimization (PSO) have been applied and compared in order to identify the optimal PID parameters (kp, ki, kd). The objective of GA and PSO is minimized the error signal in output power based on actual WS. The results for three different controllers show that the optimal hybrid FPIDC based on the Sugeno inference system with PSO produces the optimal results regard to reduce the error signal and stable output power under actual WS.

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Publication Date
Sat Oct 20 2018
Journal Name
Journal Of Economics And Administrative Sciences
THE IMPACT OF MANAGEMENT CONTROL SYSTEMS (MCS) ON ORGANIZATIONS PERFORMANCE A LITERATURE REVIEW
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The impact of management control systems (MCS) on organizations performance empirical research has been the subject of numerous studies during the past decade in developed and emerging economies. In the contemporary competitive, complex and changing global business environment, firms are being challenged to adopt business models that enable them to address the strategic uncertainties and risks they face in their business environments. The main issue of this study is that management accounting researchers argue that one of the ways firms can continually rejuvenate themselves to survive and succeed in these complex and uncertain environments is to understand the role of management control systems in Formulating a b

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Publication Date
Sun Jun 02 2019
Journal Name
Journal Of The College Of Languages (jcl)
The vision of Hebrew writers and critics of the future of the Jews in their writings at the end of the 19th century and the beginning of the twentieth c: דעותיהם של הסופרים והמבקרים העבריים על עתידם של היהודים לפי כתבותיהם בשלהי המאה ה-19 ובתחילת המאה ה-20
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It is very known  how great is the  role of the Jewish writers in the system of the Zionist movement. The movement relied on writers and writers to carry out their programs, especially those pertaining to the creation of a "national homeland" for Jews. Most Jewish writers sang of  Palestine even though they were not born there.

    On such a  basis, we have followed closely the writings of writers, critics and others by the end of the nineteenth century and the beginning of the twentieth century. We found that these writings are based on one common question: What is the fate of the Jewish people?

    Most of these writings were accompanied by Theodor Herzl's proj

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Publication Date
Sat Jun 01 2019
Journal Name
Journal Of The College Of Languages (jcl)
An Analytical Study of Viewpoint in Parsi Pour's and Ar-Rikabi's Novels: The Dog and the Long Night and Alibaba's Sad Night as Examples: بررسی تحليلی زاویه¬ی دید در رمان¬های پارسی پور و الرکابی باتكيه بر رمان "سگ و زمستان بلند" و "ليل علی بابا الحزین"
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It is noted in the title that the paper studies the viewpoint in the novel The Dog and the Long Night by the Iranian novelist Shahranoush Parsi Pour and in the novel Alibaba's Sad Night by the Iraqi novelist Abdulkhaliq Ar-Rikabi. Both are well known novelists, and about whose stories and novels many critical books, MA theses, and Ph.D. dissertations have been written. Also, some of their literary works have won prizes. Here, the researcher shed light on the concept of viewpoint, its types, and its importance in novels in general. This was done along with tackling the two viewpoints in both novels, where similarities and differences were identified. For this end, the researcher has adopted the analytic-descriptive appro

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Publication Date
Mon Dec 18 2017
Journal Name
Al-khwarizmi Engineering Journal
Path Planning of an autonomous Mobile Robot using Swarm Based Optimization Techniques
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This paper presents a meta-heuristic swarm based optimization technique for solving robot path planning. The natural activities of actual ants inspire which named Ant Colony Optimization. (ACO) has been proposed in this work to find the shortest and safest path for a mobile robot in different static environments with different complexities. A nonzero size for the mobile robot has been considered in the project by taking a tolerance around the obstacle to account for the actual size of the mobile robot. A new concept was added to standard Ant Colony Optimization (ACO) for further modifications. Simulations results, which carried out using MATLAB 2015(a) environment, prove that the suggested algorithm outperforms the standard version of AC

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Publication Date
Mon Mar 31 2025
Journal Name
International Journal Of Advanced Technology And Engineering Exploration
Breast cancer survival rate prediction using multimodal deep learning with multigenetic features
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Breast cancer is a heterogeneous disease characterized by molecular complexity. This research utilized three genetic expression profiles—gene expression, deoxyribonucleic acid (DNA) methylation, and micro ribonucleic acid (miRNA) expression—to deepen the understanding of breast cancer biology and contribute to the development of a reliable survival rate prediction model. During the preprocessing phase, principal component analysis (PCA) was applied to reduce the dimensionality of each dataset before computing consensus features across the three omics datasets. By integrating these datasets with the consensus features, the model's ability to uncover deep connections within the data was significantly improved. The proposed multimodal deep

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Publication Date
Sun Sep 03 2017
Journal Name
Baghdad Science Journal
Scale-Invariant Feature Transform Algorithm with Fast Approximate Nearest Neighbor
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There is a great deal of systems dealing with image processing that are being used and developed on a daily basis. Those systems need the deployment of some basic operations such as detecting the Regions of Interest and matching those regions, in addition to the description of their properties. Those operations play a significant role in decision making which is necessary for the next operations depending on the assigned task. In order to accomplish those tasks, various algorithms have been introduced throughout years. One of the most popular algorithms is the Scale Invariant Feature Transform (SIFT). The efficiency of this algorithm is its performance in the process of detection and property description, and that is due to the fact that

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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 Oct 01 2023
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Intelligence framework dust forecasting using regression algorithms models
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<span>Dust is a common cause of health risks and also a cause of climate change, one of the most threatening problems to humans. In the recent decade, climate change in Iraq, typified by increased droughts and deserts, has generated numerous environmental issues. This study forecasts dust in five central Iraqi districts using machine learning and five regression algorithm supervised learning system framework. It was assessed using an Iraqi meteorological organization and seismology (IMOS) dataset. Simulation results show that the gradient boosting regressor (GBR) has a mean square error of 8.345 and a total accuracy ratio of 91.65%. Moreover, the results show that the decision tree (DT), where the mean square error is 8.965, c

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Publication Date
Mon Dec 18 2017
Journal Name
Al-khwarizmi Engineering Journal
Experimental Investigation on the Emission Characteristics of a Dual – Fuel Micro Gas Turbine by Injecting Ethanol into Compressor Inlet Air
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Pollutants generation is strongly dependant on the firing temperature and reaction rates of the gaseous reactants in the gas turbine combustion chamber. An experimental study is conducted on a two-shaft T200D micro-gas turbine engine in order to evaluate the impact of injecting ethanol directly into the compressor inlet air on the exhaust emissions. The study is carried out in constant speed and constant load engine tests. Generally, the results showed that when ethanol was added in a concentration of 20% by volume of fuel flow; NOx emission was reduced by the half, while CO and UHC emissions were almost doubled with respect to their levels when burning conventional LPG fuel alone.

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Publication Date
Wed Jul 01 2020
Journal Name
Ieee Transactions On Industrial Electronics
Finite-Time Continuous Terminal Sliding Mode Control of Servo Motor Systems
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In this article, a continuous terminal sliding mode control algorithm is proposed for servo motor systems. A novel full-order terminal sliding mode surface is proposed based on the bilimit homogeneous property, such that the sliding motion is finite-time stable independent of the system’s initial condition. A new continuous terminal sliding mode control algorithm is proposed to guarantee that the system states reach the sliding surface in finitetime. Not only the robustness is guaranteed by the proposed controller but also the continuity makes the control algorithm more suitable for the servo mechanical systems. Finally, a numerical example is presented to depict the advantages of the proposed control algorithm. An application in the rota

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