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Second Order Sliding Mode Controller Design for Pneumatic Artificial Muscle
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In this paper, first and second order sliding mode controllers are designed for a single link robotic arm actuated by two Pneumatic Artificial Muscles (PAMs). A new mathematical model for the arm has been developed based on the model of large scale pneumatic muscle actuator model. Uncertainty in parameters has been presented and tested for the two controllers. The simulation results of the second-order sliding mode controller proves to have a low tracking error and chattering effect as compared to the first order one. The verification has been done by using MATLAB and Simulink software.

 

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Publication Date
Thu Jan 30 2020
Journal Name
Journal Of Engineering
Study Impact of Unified Power Flow Controller (UPFC) on a Transmission Line Performance under Different Loading Conditions
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Now-a-days the Flexible AC Transmission Systems (FACTS) technology is very effective in improving the power flow along the transmission lines and makes the power system more flexible and controllable. This paper deals with the most robust type of FACTS devices; it’s a Unified Power Flow Controller (UPFC). Many cases have been taken to study how the system behaves in the presence and absence of the UPFC under normal and contingency conditions. The UPFC is a device that can be used to improve the bus voltage, increasing the loadability of the line and reduce the active and reactive power losses in the transmission lines, through controlling the flow of real and reactive power. Both the magnitude and the phase angle of th

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Publication Date
Mon Jun 01 2020
Journal Name
Journal Of Engineering
Artificial Neural Network (ANN) for Prediction of Viscosity Reduction of Heavy Crude Oil using Different Organic Solvents
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The increase globally fossil fuel consumption as it represents the main source of energy around the world, and the sources of heavy oil more than light, different techniques were used to reduce the viscosity and increase mobility of heavy crude oil. this study focusing on the experimental tests  and modeling with Back Feed Forward Artificial Neural Network (BFF-ANN) of the dilution technique to reduce a  heavy oil viscosity that was collected from the south- Iraq oil fields using organic solvents, organic diluents with different weight percentage  (5, 10 and  20 wt.% )  of  (n-heptane, toluene, and a mixture of  different ratio

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Publication Date
Sat Apr 12 2025
Journal Name
Mustansiriyah Journal Of Sports Science
A Review of the Use of Artificial Intelligence Algorithms for Predicting Injuries and Performance in Football Players
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The purpose of this study is to investigate the research on artificial intelligence algorithms in football, specifically in relation to player performance prediction and injury prevention. To accomplish this goal, scholarly resources including Google Scholar, ResearchGate, Springer, and Scopus were used to provide a systematic examination of research done during the last ten years (2015–2025). Through a systematic procedure that included data collection, study selection based on predetermined criteria, categorisation based on AI applications in football, and assessment of major research problems, trends, and prospects, almost fifty papers were found and analysed. Summarising AI applications in football for performance and injury p

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Publication Date
Sun Oct 19 2025
Journal Name
Lecture Notes In Networks And Systems
Challenges of Using Literary Translation and Artificial Intelligence for Postgraduate Students: A Case Study of Baghdad University
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Publication Date
Tue Nov 06 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Assessment of Nurse–Midwives' Knowledge and Practices toward Second Stage of Labor
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Objective: To assess the nurses-midwives' knowledge and practices regarding the management of second stage
of labor and to find out the association between their knowledge and practices and socio-demographic
characteristics and working years and experience.
Methodology: A descriptive study was carried out from March 22nd
, 2008 through 30th June, 2008. A purposive
sample of (75) Nurse-Midwives which was selected from (6) hospitals. A questionnaire was comprised of two
parts: (socio-demographic characteristics and the assessment tool for Nurse-Midwives' knowledge and health
practices performed by them). The questionnaire validity was determined by experts and its reliability was
determined through a pilot study. Th

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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Solution of Second Kind Volterra Integral Equations Using Non-Polynomial Spline Functions
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In this paper we use non-polynomial spline functions to develop numerical methods to approximate the solution of 2nd kind Volterra integral equations. Numerical examples are presented to illustrate the applications of these method, and to compare the computed results with other known methods.

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Publication Date
Tue Dec 30 2014
Journal Name
College Of Islamic Sciences
Historical School in Medina             Until the end of the second century AH
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Medina was according to its importance and religious status the basis for the emergence and emergence of historical schools, it is the emigration of the Prophet  and the presence of the companions , and it was natural to shine the beginnings of historical codification, whether in the process of collecting and codification of the verses of the Koran or the Hadith, and once the pillars settled Islam in the Islamic areas until the Muslims began to go to the city to provide a broader knowledge of the Islamic religion and everything related to the biography of the Prophet and the significance and actions, and in return took the jurists and preservation and readers of the companions and followers to undertake the task of teaching in work

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Publication Date
Wed Jan 01 2025
Journal Name
Lecture Notes In Networks And Systems
Diagnosis of Diabetes Using Artificial Intelligence Programs
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Scientific development has occupied a prominent place in the field of diagnosis, far from traditional procedures. Scientific progress and the development of cities have imposed diseases that have spread due to this development, perhaps the most prominent of which is diabetes for accurate diagnosis without examining blood samples and using image analysis by comparing two images of the affected person for no less than a period. Less than ten years ago they used artificial intelligence programs to analyze and prove the validity of this study by collecting samples of infected people and healthy people using one of the Python program libraries, which is (Open-CV) specialized in measuring changes to the human face, through which we can infer the

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Publication Date
Mon Dec 30 2024
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Reservoir permeability prediction based artificial intelligence techniques
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   Predicting permeability is a cornerstone of petroleum reservoir engineering, playing a vital role in optimizing hydrocarbon recovery strategies. This paper explores the application of neural networks to predict permeability in oil reservoirs, underscoring their growing importance in addressing traditional prediction challenges. Conventional techniques often struggle with the complexities of subsurface conditions, making innovative approaches essential. Neural networks, with their ability to uncover complicated patterns within large datasets, emerge as a powerful alternative. The Quanti-Elan model was used in this study to combine several well logs for mineral volumes, porosity and water saturation estimation. This model goes be

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Publication Date
Sat Jan 01 2011
Journal Name
Journal Of Engineering
FILTRATION MODELING USING ARTIFICIAL NEURAL NETWORK (ANN)
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In this research Artificial Neural Network (ANN) technique was applied to study the filtration process in water treatment. Eight models have been developed and tested using data from a pilot filtration plant, working under different process design criteria; influent turbidity, bed depth, grain size, filtration rate and running time (length of the filtration run), recording effluent turbidity and head losses. The ANN models were constructed for the prediction of different performance criteria in the filtration process: effluent turbidity, head losses and running time. The results indicate that it is quite possible to use artificial neural networks in predicting effluent turbidity, head losses and running time in the filtration process, wi

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