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Evaluating the Performance and Behavior of CNN, LSTM, and GRU for Classification and Prediction Tasks
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     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning models for a variety of tasks under the control of a unified architecture for each proposed model.

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Publication Date
Fri Dec 01 2023
Journal Name
Al-khwarizmi Engineering Journal
Development of an ANN Model for RGB Color Classification using the Dataset Extracted from a Fabricated Colorimeter
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Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob

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Publication Date
Fri Dec 01 2023
Journal Name
Al-khwarizmi Engineering Journal
Development of an ANN Model for RGB Color Classification using the Dataset Extracted from a Fabricated Colorimeter
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Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de

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Publication Date
Mon Oct 01 2018
Journal Name
Al–bahith Al–a'alami
President Trump›s media discourse in the US election Study in electronic news sites - CNN ARABIC Model
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The letter is defined as a message directed by the sender to another party, the future. The aim is to convey, clarify or explain a particular point or subject, and in the form of direct oral communication through speech that contains a set of words and words, The future can discuss the sender directly to exchange ideas with each other, or it may be written and in this case does not require direct interaction between the matchmaker and the recipient. As a result of the different sources and topics of the discourse, and the different types of categories addressed to the speech, and the number, it has been divided into several types.
And schools of discourse analysis emerged in the early eighties of the last century and has spread and ha

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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of The Mechanical Behavior Of Materials
Evaluation of a fire safety risk prediction model for an existing building
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Abstract<p>Fire is one of the most critical risks devastating to human life and property. Therefore, humans make different efforts to deal with fire hazards. Many techniques have been developed to assess fire safety risks. One of these methods is to predict the outbreak of a fire in buildings, and although it is hard to predict when a fire will start, it is critical to do so to safeguard human life and property. This research deals with evaluating the safety risks of the existing building in the city of Samawah/Iraq and determining the appropriateness of these buildings in terms of safety from fire hazards. Twelve parameters are certified based on the National Fire Protection Association (NFPA20</p> ... Show More
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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
Proposition of New Ensemble Data-Intelligence Models for Surface Water Quality Prediction
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Publication Date
Fri Jul 21 2023
Journal Name
Journal Of Engineering
Study the Effect of Ceramic Coating on the Performance and Emissions of Diesel Engine
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In this study, the effect of ceramic coating on the performance and gases emission on diesel engine was investigated. A four-stroke, direct injected, single cylinder, diesel engine was tested at constant speed and at different load conditions without coating. Then, the inlet and exhaust valves faces were coated by about 500µm with ceramic materials. Ceramic layers were made of YttriaStabilized Zirconia (YSZ), and NiCrAl as a bond coat. The coating technique adapted in this work is the flame spray method. The engine with valves ceramiccoated research was tested for the same operation conditions of the engine (without coating). The results indicate a reduction in both fuel consumption by about 7.6% and particulate emissions by about (13

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Publication Date
Wed Jan 01 2020
Journal Name
International Journal Of Innovation, Creativity And Change
The role of the forensic accountant in achieving the integration of accounting and legal performance
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Publication Date
Wed May 31 2023
Journal Name
International Journal Of Sustainable Development And Planning
Prediction of Formal Transformations in City Structure (Kufa as a Model) Based on the Cellular Automation Model and Markov Chains
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The research utilizes data produced by the Local Urban Management Directorate in Najaf and the imagery data from the Landsat 9 satellite, after being processed by the GIS tool. The research follows a descriptive and analytical approach; we integrated the Markov chain analysis and the cellular automation approach to predict transformations in city structure as a result of changes in land utilization. The research also aims to identify approaches to detect post-classification transformations in order to determine changes in land utilization. To predict the future land utilization in the city of Kufa, and to evaluate data accuracy, we used the Kappa Indicator to determine the potential applicability of the probability matrix that resulted from

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Publication Date
Wed Jan 05 2022
Journal Name
International Journal Of Aquatic Science
Effects of Selenium Sources and Concentrations on the Performance, Meat Quality, and Tissue Properties of Broiler Chickens
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We wanted to find out how selenium (Se) affects broiler chicken performance, meat physicochemical properties, and selenium deposition in the tissues of broilers. Each of the 96 experimental pens had 30 chickens and included a total of 2,880 one-day-old broilers (Cobb 500 strain). A factorial design of four-by-three (SY + SS) and eight replicates (SY + SS) was used for the 12 experimental treatments, with selenium levels ranging from 0.15 to 0.60 ppm and organic (SY) or inorganic (SS) sources of selenium and their relationship (SY + SS). There were no differences in performance (P > 0.05) across Se levels or sources. 106 g/day of ADFI, 63 g/day of ADG, and 1.6844 kg/kg of FCR were found to be the averaging values for these three parameters:

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Publication Date
Sun Mar 01 2026
Journal Name
Results In Engineering
Role of mineral filler type and ratio in the rheological, fatigue, and adhesive performance of asphalt mastics
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Mineral fillers are a fundamental component of asphalt mastic and play a critical role in governing the mechanical performance and durability of flexible pavements. Variations in filler type and dosage can substantially alter mastic stiffness, deformation resistance, fatigue behavior, and adhesion. The objective of this study is to systematically evaluate the influence of mineral filler type and filler-to-asphalt (F/A) ratio on the rheological, fatigue, and adhesive performance of asphalt mastics. Three commonly used fillers; limestone dust, Portland cement, and hydrated lime were investigated at four F/A ratios (0.6, 0.8, 1.0, and 1.2). A comprehensive experimental program was conducted, including conventional binder characterization, Mult

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