Application of artificial neural network to predict slug liquid holdup
Publication Date
Wed Aug 28 2019
Journal Name
Journal Of Engineering
Influence of Liquid Asphalt on Resilient Modules and Permanent Deformation of Recycled Asphalt Concrete
recycled mixture
aged mixture
liquid asphalt
cutback
emulsion.
Tests were performed on Marshall samples and were implemented for permanent deformation and resilient modulus (Mr) under indirect tensile repeated loading (ITRL), with constant stress level. Two types of liquid asphalt (cutback and emulsion) were tried as recycling agents, aged materials that were reclaimed from field (100% RAP), samples were prepared from the aged mixture, and two types of liquid asphalt (cutback and emulsion) with a weight content of 0.5% were utilized to prepare a recycled mixture. A group of twelve samples was prepared for each mixture; six samples were tested directly for ITRL test (three samples at 25˚C and three samples at 40˚C), an average value for ITRL for every three samples was calculated (
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Publication Date
Tue Mar 31 2015
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Production and Evaluation of Liquid Hydrocarbon Fuel from Thermal Pyrolysis of Virgin Polyethylene Plastics
Polyethylene
Thermal
Pyrolysis
Kinetic study
Batch reactor
Plastic.
Pyrolysis of virgin polyethylene plastics was studied in order to produce hydrocarbon liquid fuel. The pyrolysis process carried out for low and high-density polyethylene plastics in open system batch reactor in temperature range of 370 to 450°C.
Thermo-gravimetric analysis of the virgin plastics showed that the degradation ranges were between 326 and 495 °C. The results showed that the optimum temperature range of pyrolysis of polyethylene plastics that gives highest liquid yield (with specific gravity between 0.7844 and 0.7865) was 390 to 410 °C with reaction time of about 35 minutes. Fourier Transform Infrared spectroscopy gave a quite evidence that the produced hydrocarbon liquid fuel consisted ma
... Show MorePublication Date
Wed Jun 05 2024
Journal Name
International Journal Of Engineering Pedagogy (ijep)
The Impact of Artificial Intelligence on Computational Thinking in Education at University
effect
artificial intelligence (AI)
ChatGPT
computational thinking
education
university
achievement
chemistry
computer science
students
This study aims to reveal the role of one of the artificial intelligence (AI) techniques, “ChatGPT,” in improving the educational process by following it as a teaching method for the subject of automatic analysis for students of the Chemistry Department and the subject of computer security for students of the Computer Science Department, from the fourth stage at the College of Education for Pure Science (Ibn Al-Haitham), and its impact on their computational thinking to have a good educational environment. The experimental approach was used, and the research samples were chosen intentionally by the research community. Research tools were prepared, which included a scale for CT that included 12 items and the achievement test in b
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(1)
Publication Date
Fri Dec 15 2023
Journal Name
Al-academy
The role of artificial intelligence in revolutionizing the clothing and textile industry
Artificial Intelligence
industry
Clothing and Textile Industry
The integration of AI technologies is revolutionizing various aspects of the apparel and textile industry, from design and manufacturing to customer experience and sustainability. Through the use of artificial intelligence algorithms, workers in the apparel and textile industry can take advantage of a wealth of opportunities for innovation, efficiency and creativity.
The research aims to display the enormous potential of artificial intelligence in the clothing and textile industry through published articles related to the title of the research using the Google Scholar search engine. The research contributes to the development of the cultural thought of researchers, designers, merchants and the consumer with the importance of integ
Publication Date
Mon Nov 11 2019
Journal Name
Spe
Modeling Rate of Penetration using Artificial Intelligent System and Multiple Regression Analysis
Abstract<p>Over the years, the prediction of penetration rate (ROP) has played a key rule for drilling engineers due it is effect on the optimization of various parameters that related to substantial cost saving. Many researchers have continually worked to optimize penetration rate. A major issue with most published studies is that there is no simple model currently available to guarantee the ROP prediction.</p><p>The main objective of this study is to further improve ROP prediction using two predictive methods, multiple regression analysis (MRA) and artificial neural networks (ANNs). A field case in SE Iraq was conducted to predict the ROP from a large number of parame</p>
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neural network
strength
machine learning
ROP prediction
Upstream Oil & Gas
prediction
ANN model
input parameter
multiple regression analysis
artificial neural network
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Publication Date
Wed Dec 18 2024
Journal Name
Bmc Medical Education
(8)
(7)
Publication Date
Sun Jan 14 2018
Journal Name
Journal Of Engineering
Second Order Sliding Mode Controller Design for Pneumatic Artificial Muscle
PAM
Sliding Mode Controller.
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.
Publication Date
Sat May 31 2025
Journal Name
3rd International Scientific Conference For Human And Social Studies And Epistemological Challenges
Frankenstein Complex in Daniel H. Wilson's Robopocalypse ( ): Artificial Intelligence Conspiracies
With the advent of technology
the fear of losing control has consistently
accompanied humanity. While humans have discovered
invented
and
created many remarkable things
they have also been haunted by the
possibility of their creations turning against them. This fear
often referred to
as the Frankenstein Complex
derives its name from Mary Shelley's
Frankenstein ()
in which Dr. Frankenstein's creation ultimately destroys
its maker. The Frankenstein Complex embodies the subconscious fear of
artificial intelligence (AI) surpassing and potentially dominating humankind.
This apprehension has inspired numerous literary works
including Daniel H.
Wilson’s novels. The present study examines the widespread fear of AI
which has fueled conspiracy theories in literature. These theories have not
only amplified public anxiety but also hindered understanding among those
with limited knowledge of AI and robotics. Dr. Wilson
a robotics expert
uses
his imagination as a driving force for both his writing and his inventions. The
research focuses on incidents leading to the rise of robots
the concept of the
New War
how it was fought
and how it concluded. By comparing
contrasting
and analyzing literary elements and devices with prominent
conspiracy theories
the study highlights the interplay between fiction and
scientific development. The researchers conclude that while many conspiracy
theories contain elements of truth
they often inspire scientists to explore them
further. Additionally
some conspiracy theories warrant serious
consideration. The study recommends acknowledging the Frankenstein
Complex while maintaining faith in the potential benefits of artificial
intelligence.
Publication Date
Thu Dec 28 2017
Journal Name
Al-khwarizmi Engineering Journal
Obstacles Avoidance for Mobile Robot Using Enhanced Artificial Potential Field
Mobile Robot
Local Path Planning
Obstacles Avoidance
Potential Field
In this paper, an enhanced artificial potential field (EAPF) planner is introduced. This planner is proposed to rapidly find online solutions for the mobile robot path planning problems, when the underlying environment contains obstacles with unknown locations and sizes. The classical artificial potential field represents both the repulsive force due to the detected obstacle and the attractive force due to the target. These forces can be considered as the primary directional indicator for the mobile robot. However, the classical artificial potential field has many drawbacks. So, we suggest two secondary forces which are called the midpoint
... Show MorePublication Date
Wed Nov 01 2023
Journal Name
Al-rafidain Journal Of Medical Sciences ( Issn 2789-3219 )
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