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alkej-159
Simulation Study of Mass Transfer Coefficient in Slurry Bubble Column Reactor Using Neural Network
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The objective of this study was to develop neural network algorithm, (Multilayer Perceptron), based correlations for the prediction overall volumetric mass-transfer coefficient (kLa), in slurry bubble column for gas-liquid-solid systems. The Multilayer Perceptron is a novel technique based on the feature generation approach using back propagation neural network. Measurements of overall volumetric mass transfer coefficient were made with the air - Water, air - Glycerin and air - Alcohol systems as the liquid phase in bubble column of 0.15 m diameter. For operation with gas velocity in the range 0-20 cm/sec, the overall volumetric mass transfer coefficient was found to decrease with increasing solid concentration. From the experimental work 1575 data points for three systems, were collected and used to predicate  kLa. Using SPSS 17 software, predicting of overall volumetric mass-transfer coefficient (kLa) was carried out and an output of 0.05264 sum of square error was obtained for trained data and 0.01064 for test data.

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Publication Date
Sun Apr 30 2023
Journal Name
Iraqi Journal Of Science
New Mode of On- Line Automation: Chemilumino-Fluoro Metric Method for the Determination of Hydrogen Peroxide by Fluorescence Energy Transfer Using Ploy Acrylic Acid Gel Beads
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Hydrogen peroxide was determined by a new , accurate , sensitive and rapid method via continuous mode of FIA coupled with total luminescence measurement which include the chemiluminescence generated ,based on the oxidation of Luminol which is loaded on poly acrylic acid gel beads by hydrogen peroxide in presence of Cobalt (II) ion as a chemiluminescence catalyst and the fluorescence that was created by the insitu radiation of the released chemiluminescence light. Fluorescien molecule was used as an accepter fluorophore where it is irradiated internally and instantly by the generation of luminol chemiluminescence light as internal source for irradiation of fluorescien molecule (Fluorescence Energy Transfer (FRET) ) . It can easily give fl

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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Recurrent Stroke Prediction using Machine Learning Algorithms with Clinical Public Datasets: An Empirical Performance Evaluation
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Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al

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Publication Date
Sat Feb 08 2025
Journal Name
Journal Of Baghdad College Of Dentistry
Relationship of maximum bite force with craniofacial morphology, body mass and height in an Iraqi adults with different types of malocclusion
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Background: Information concerning the maximum bite force in human population is important to clinical orthodontics. Additionally, the influence of bite force on the vertical stability of any treatment result is important. The new position of the dentition should be compatible with the dynamics of the muscular and occlusal forces in all planes. This study was conducted to 1) to measure and compare maximum bite force, body height and weight among normal occlusion and malocclusion groups (cl I,cl II,cl III) in both gender 2) to evaluate the correlation between bite force and craniofacial morphology, body height and weight. Materials and Methods: The sample consists of 100 Iraqi adult subjects aged 18-25 years. It was classified in to four gr

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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Generative Adversarial Network for Imitation Learning from Single Demonstration
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Imitation learning is an effective method for training an autonomous agent to accomplish a task by imitating expert behaviors in their demonstrations. However, traditional imitation learning methods require a large number of expert demonstrations in order to learn a complex behavior. Such a disadvantage has limited the potential of imitation learning in complex tasks where the expert demonstrations are not sufficient. In order to address the problem, we propose a Generative Adversarial Network-based model which is designed to learn optimal policies using only a single demonstration. The proposed model is evaluated on two simulated tasks in comparison with other methods. The results show that our proposed model is capable of completing co

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Publication Date
Sat Dec 01 2018
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The extent of the industrial company's response to blue market strategy indicators: Applied research
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The current research aims to describe the level of responsiveness and awareness of the officials of the General Company for Construction Industries to the indicators of the blue market strategy of (1. reduction 2. exclusion 3. increase 4. innovation) and the degree of prioritization according to their importance as well as the differences in the responses of the sample investigated according to the personal variables. As a main tool in the collection of data from the sample, which consisted of(34) officers (Associate, Manager, Section Manager, Division Officer) in the company being investigated, and computed mean, standard deviations, percentage weights,and test (x2 )  based on the SPSS. The research reached the following

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Publication Date
Wed Dec 27 2017
Journal Name
Al-khwarizmi Engineering Journal
A New Approach for Designing Multi Information Management System Using XML Technology
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XML is being incorporated into the foundation of E-business data applications. This paper addresses the problem of the freeform information that stored in any organization and how XML with using this new approach will make the operation of the search very efficient and time consuming. This paper introduces new solution and methodology that has been developed to capture and manage such unstructured freeform information (multi information) depending on the use of XML schema technologies, neural network idea and object oriented relational database, in order to provide a practical solution for efficiently management multi freeform information system.

    

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Publication Date
Sun Dec 01 2019
Journal Name
Baghdad Science Journal
Symmetric- Based Steganography Technique Using Spiral-Searching Method for HSV Color Images
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Steganography is defined as hiding confidential information in some other chosen media without leaving any clear evidence of changing the media's features. Most traditional hiding methods hide the message directly in the covered media like (text, image, audio, and video). Some hiding techniques leave a negative effect on the cover image, so sometimes the change in the carrier medium can be detected by human and machine. The purpose of suggesting hiding information is to make this change undetectable. The current research focuses on using complex method to prevent the detection of hiding information by human and machine based on spiral search method, the Structural Similarity Index Metrics measures are used to get the accuracy and quality

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Publication Date
Fri Jun 01 2007
Journal Name
Journal Of Economics And Administrative Sciences
جدلية التنظرية في الذاكرة المنظمة بين متاهة النماذج الصناعية وواقعيةالنموذج الهجين
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جدلية التنظرية في الذاكرة المنظمة بين متاهة النماذج الصناعية وواقعيةالنموذج الهجين

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Publication Date
Sat Sep 30 2023
Journal Name
Al–bahith Al–a'alami
The Role of Website Users in the Consumption of Notifications: A Field Study of Websites
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This research seeks to explore the impact of notifications on enhancing user engagement with websites, primarily through user subscriptions and their interaction with notifications on these websites. The significance of this study lies in its implications for crafting compelling headlines that capture users' attention, streamline their access to journalistic content, and align with the objectives and editorial policies of news websites. It sheds light on the factors influencing users' preferences for specific notifications and their engagement with content based on their individual interests, motivations, and the satisfaction derived from such interactions.
The researcher has reached several key findings, inc

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Publication Date
Tue May 01 2012
Journal Name
Iraqi Journal Of Physics
Early detection of breast cancer mass lesions by mammogram segmentation images based on texture features
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Mammography is at present one of the available method for early detection of masses or abnormalities which is related to breast cancer. The most common abnormalities that may indicate breast cancer are masses and calcifications. The challenge lies in early and accurate detection to overcome the development of breast cancer that affects more and more women throughout the world. Breast cancer is diagnosed at advanced stages with the help of the digital mammogram images. Masses appear in a mammogram as fine, granular clusters, which are often difficult to identify in a raw mammogram. The incidence of breast cancer in women has increased significantly in recent years.
This paper proposes a computer aided diagnostic system for the extracti

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