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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
Tue Jun 01 2021
Journal Name
Iop Conference Series: Earth And Environmental Science
Simulation of Syngas Addition Effect on Emissions Characteristics, Combustion, and Performance of the Diesel Engine Working under Dual Fuel Mode and Lambda Value of 1.6.
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Abstract<p>The present work aims to study the combustion characteristics related to syngas-diesel dual-fuel engine operates at lambda value of 1.6 operated by five different replacement ratios (RR) of syngas with diesel, which are (10%, 20%, 30 %, 40 % and 50%). ANSYS Workbench (CFD) was used for simulating the combustion of the syngas-diesel dual-fuel engine. The numerical simulations were carried out on the Ricardo-Hydra diesel engine. The simulation results revealed that the diesel engine’s combustion efficiency was enhanced by increasing the diesel replacement with Syngas fuel. The diesel engine’s combustion efficiency The peak in-cylinder temperature was enhanced from 915.9K to 2790.5K </p> ... Show More
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Publication Date
Tue Jan 06 2004
Journal Name
Iraqi Journal Of Science
Cluster and factor analyses R and Q mode technique of geochemical and petrological data of the Shalair Metamorphic Rock Group, Shalair Valley area, Northeastern Iraq
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Publication Date
Sat Aug 01 2020
Journal Name
Journal Of Engineering Science And Technology (jestec)
Influence of A River Water Quality on The Efficiency of Water Treatment Using Artificial Neural Network
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Tigris River is the lifeline that supplies a great part of Iraq with water from north to south. Throughout its entire length, the river is battered by various types of pollutants such as wastewater effluents from municipal, industrial, agricultural activities, and others. Hence, the water quality assessment of the Tigris River is crucial in ensuring that appropriate and adequate measures are taken to save the river from as much pollution as possible. In this study, six water treatment plants (WTPs) situated on the two-banks of the Tigris within Baghdad City were Al Karkh; Sharq Dijla; Al Wathba; Al Karama; Al Doura, and Al Wahda from northern Baghdad to its south, that selected to determine the removal efficiency of turbidity and

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Publication Date
Sun Oct 19 2025
Journal Name
Lecture Notes In Networks And Systems
Utilizing Artificial Intelligence Tools in Enhancing Training of Trainers (ToT) Programs: Modern Approaches and Practical Applications
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Publication Date
Wed Jan 01 2025
Journal Name
Aip Conference Proceedings
Predicting biochemical oxygen demand at Al-Rustumiya wastewater treatment plant inlet using the artificial neural network
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Publication Date
Sun Oct 19 2025
Journal Name
Lecture Notes In Networks And Systems
Using Artificial Intelligence in Analyzing Historical Documents: The Egyptian Libyan Border as a Model (1911–1951)
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Publication Date
Sun Oct 19 2025
Journal Name
Lecture Notes In Networks And Systems
Utilizing Artificial Intelligence Tools in Enhancing Training of Trainers (ToT) Programs: Modern Approaches and Practical Applications
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This study specifically contributes to the urgent need for novel methods in Training of Trainers (ToT) programs which can be more effective and efficient through incorporation of AI tools. By exploring scenarios in which AI could be used to dramatically advance trainer preparation, knowledge-sharing, and skill-building across sectors, the research aims to understand the possibility. This study uses a mixed-methods approach, it surveys 500 trainers and conducts in-depth interviews with a further 50 ToT program directors across diverse industries to evaluate the impact of AI-enhanced ToT programs. The results showcase that the use of AI has a substantial positive effect on trainer performance and program outcomes. AI-enhanced ToT programs, fo

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Publication Date
Wed Apr 15 2020
Journal Name
Journal Of Engineering Science And Technology
INFLUENCE OF A RIVER WATER QUALITY ON THE EFFICIENCY OF WATER TREATMENT USING ARTIFICIAL NEURAL NETWORK
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Publication Date
Mon Jun 01 2015
Journal Name
Journal Of Engineering
Artificial Neural Networks Modeling of Total Dissolved Solid in the Selected Locations on Tigris River, Iraq
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The study aims to predict Total Dissolved Solids (TDS) as a water quality indicator parameter at spatial and temporal distribution of the Tigris River, Iraq by using Artificial Neural Network (ANN) model. This study was conducted on this river between Mosul and Amarah in Iraq on five positions stretching along the river for the period from 2001to 2011. In the ANNs model calibration, a computer program of multiple linear regressions is used to obtain a set of coefficient for a linear model. The input parameters of the ANNs model were the discharge of the Tigris River, the year, the month and the distance of the sampling stations from upstream of the river. The sensitivity analysis indicated that the distance and discharge

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Publication Date
Fri Jan 01 2021
Journal Name
Environmental Pollution
Prediction of sediment heavy metal at the Australian Bays using newly developed hybrid artificial intelligence models
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