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alkej-509
Prediction of Equilibrium Mixing Index and Optimum Mixing Time for Three solid materials in Fluidized Column
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     Equilibrium and rate of mixing of free flowing solid materials are found using gas fluidized bed. The solid materials were sand (size 0.7 mm), sugar (size0.7 mm) and 15% cast iron used as a tracer. The fluidizing gas was air with velocity ranged from 0.45-0.65 m/s while the mixing time was up to 10 minutes. The mixing index for each experiment was calculated by averaging the results of 10 samples taken from different radial and axial positions in fluidized QVF column 150 mm ID and 900 mm height.

     The experimental results were used in solving a mathematical model of mixing rate and mixing index at an equilibrium proposed by Rose. The results show that mixing index increases with increasing air velocity and mixing time until it reaches an optimum value then decrease to an equilibrium value. The results also show the dependency of the mixing index on the particle size of the tracer component.

      The statistical analysis of the obtained theoretical mixing index versus the experimental mixing index shows that the standard error is 0.92 % (about 1 %) with the correlation coefficient of 0.9857 and the total residual of 0.002 for the ninth observation of the mixing index (theoretical versus experimental) over 95% confidence level.

 

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Publication Date
Tue Jun 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Using the Critical Path Method (CPM) for scheduling the project (paving the Amil Sayid Al-Ayyam Street with a length of 1.25 km) In terms of Decresing the time
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The implementation of the concept of project scheduling in the organizations generally requires a set of procedures and requirements, So, most important of all is the understanding and knowledge of the tools and techniques which are called the methods of scheduling projects. Consequently, the projects of the municipality administration in the holy governorate of Karbala suffer from the problem of delaying their projects and chaos in the ways of implementation. To provide assistance to this directorate and to demonstrate how to schedule projects using one of the advanced scientific methods that proved their ability to schedule any project and its potential to accelerate the time of completion, as well as ease of use and effectiven

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Publication Date
Thu Jan 31 2019
Journal Name
Journal Of The College Of Education For Women
Psychological Barriers and Their Relationship in Cope with University Life at University' Students
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Current Thesis has aimed to identify : The Psychological barriers for university students , Differences in psychological barriers depending on the variable sex (Males – Females) , Adjustment to College life for university students, Differences in Adjustment to College at university life depending on the variable sex (Males – Females), and finally, The correlation between psychological barriers and Adjustment to College life. The researcher has prepared a sample consisted of (100) male and female students who were randomly selected from university students, The researcher has adopted a measure of (2002) to measure the psychological barriers, also the researcher adjustment scale with university life.
The results showed that universi

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Publication Date
Mon Dec 02 2024
Journal Name
Engineering, Technology & Applied Science Research
An Artificial Neural Network Prediction Model of GFRP Residual Tensile Strength
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This study uses an Artificial Neural Network (ANN) to examine the constitutive relationships of the Glass Fiber Reinforced Polymer (GFRP) residual tensile strength at elevated temperatures. The objective is to develop an effective model and establish fire performance criteria for concrete structures in fire scenarios. Multilayer networks that employ reactive error distribution approaches can determine the residual tensile strength of GFRP using six input parameters, in contrast to previous mathematical models that utilized one or two inputs while disregarding the others. Multilayered networks employing reactive error distribution technology assign weights to each variable influencing the residual tensile strength of GFRP. Temperatur

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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of Applied Engineering Science
Rutting prediction of hot mix asphalt mixtures reinforced by ceramic fibers
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One of the most severe problems with flexible asphalt pavements is permanent deformation in the form of rutting. Accordingly, the practice of adding fiber elements to asphalt mix to improve performance under dynamic loading has grown significantly in order to prevent rutting distress and ensure a safe and long-lasting road surface. This paper explores the effects of a combination of ceramic fiber (CF), a low-cost, easily available mineral fiber, and thermal insulator fiber reinforced to enhance the Marshall properties and increase the rutting resistance of asphalt mixes at high temperatures. Asphalt mixtures with 0%, 0.75%, 1.5%, and 2.25% CF content were prepared, and Marshall stability and wheel tracking tests were employed to stu

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Publication Date
Wed Dec 14 2016
Journal Name
Journal Of Baghdad College Of Dentistry
Time of Emergence of Permanent Teeth and Impact of Nutritional Status among 4-15 Years Old Children and Teenagers in Basrah City /Iraq
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Background: The timing of eruption of permanent teeth is of considerable importance to the dental health planning for diagnostic, preventive and therapeutic measures for children and teenagers. The purposes of this study were to determine timing of maxillary and mandibular permanent teeth emergence (except third molars) and to evaluate the effect nutritional status by anthropometric measures on the eruption time of permanent teeth, investigations had been done according to jaw and gender variations. Materials and Methods: This study was conducted among four to fifteen years old children and teenagers from kindergarten and schools in Basrah city in the south region of Iraq. The total sample composed of 1807 children and teenagers that were

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Publication Date
Fri Mar 01 2019
Journal Name
Optical Fiber Technology
Highly sensitive measurement of surrounding refractive index using tapered trench–assisted multicore fiber
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Publication Date
Sat Jan 01 2022
Journal Name
Proceedings Of International Conference On Computing And Communication Networks
Automatic Health Speech Prediction System Using Support Vector Machine
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Publication Date
Sat Aug 01 2015
Journal Name
International Journal Of Computer Science And Mobile Computing
Image Compression based on Non-Linear Polynomial Prediction Model
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Publication Date
Fri May 01 2020
Journal Name
Journal Of Electrical And Electronics Engineering
HF Wave Propagation Prediction Based On Passive Oblique Ionosonde
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High frequency (HF) communications have an important role in long distances wireless communications. This frequency band is more important than VHF and UHF, as HF frequencies can cut longer distance with a single hopping. It has a low operation cost because it offers over-the-horizon communications without repeaters, therefore it can be used as a backup for satellite communications in emergency conditions. One of the main problems in HF communications is the prediction of the propagation direction and the frequency of optimum transmission (FOT) that must be used at a certain time. This paper introduces a new technique based on Oblique Ionosonde Station (OIS) to overcome this problem with a low cost and an easier way. This technique uses the

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Publication Date
Mon Sep 30 2024
Journal Name
Iraqi Journal Of Science
Attention-Deficit Hyperactivity Disorder Prediction by Artificial Intelligence Techniques
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Attention-Deficit Hyperactivity Disorder (ADHD), a neurodevelopmental disorder affecting millions of people globally, is defined by symptoms of hyperactivity, impulsivity, and inattention that can significantly affect an individual's daily life. The diagnostic process for ADHD is complex, requiring a combination of clinical assessments and subjective evaluations. However, recent advances in artificial intelligence (AI) techniques have shown promise in predicting ADHD and providing an early diagnosis. In this study, we will explore the application of two AI techniques, K-Nearest Neighbors (KNN) and Adaptive Boosting (AdaBoost), in predicting ADHD using the Python programming language. The classification accuracies obtained w

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