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An optimized deep learning model for optical character recognition applications
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The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recognition applications; the proposed method was evaluated for performance in terms of computational accuracy, convergence analysis, and cost.

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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
Sun Dec 15 2019
Journal Name
Al-academy
The strategy of visual thinking and its applications in teaching arts (photography model): نورا عبد الله علي
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The study aims at:
1- Identifying the contemporary educational approaches in teaching arts.
2- The effectiveness of using the visual thinking strategy in photography subject for the first year students in the institute of fine arts/Holy city of Kadhimiyah.
The study sample is made of (30 ) first year students (in the institute of fine arts/in Holy city of Kadhimiyah) distributed into two groups, an experimental group made of (15) students and a control group having the same number of students in order to conduct the test. The test for the visual thinking strategy in the subject of photography has been designed and the validity and reliability for the research tool have been verified. In order to demonstrate the results of the

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Publication Date
Wed Jul 12 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Formulation and Evaluation of Optimized Zaltoprofen Lyophilized Tablets by Zydis Technique
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“Orodispersible Tablet” a tablet that is to be placed in oral cavity where it disperses rapidly by saliva with no need for water before swallowing. Zaltoprofen (ZLP) is one of NSAIDs which is used in the treatment of rheumatoid arthritis and osteoarthritis as well as to relieve inflammation and pain after surgery, injury and tooth extraction. The present study was aimed to prepare rapidly dissolved lyophilized Zaltoprofen tablet with different pharmaceutical excipients and studying the factors affecting pharmaceutical properties like (solubility, disintegration time DT, dissolution, etc.) of tablets. The lyophilized disintegrating tablets (LDTs) were prepared using Zydis technique by lyophilization an aqueous

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Publication Date
Tue Dec 09 2025
Journal Name
Journal Of Al-farahidi’s Arts
Artificial Intelligence Applications in Machine Translation and Their Role in Bridging Semantic Gaps Across Languages: A Comparative Analytical Study of Chat GPT and Deep Seek
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With the fast-growing of neural machine translation (NMT), there is still a lack of insight into the performance of these models on semantically and culturally rich texts, especially between linguistically distant languages like Arabic and English. In this paper, we investigate the performance of two state-of-the-art AI translation systems (ChatGPT, DeepSeek) when translating Arabic texts to English in three different genres: journalistic, literary, and technical. The study utilizes a mixed-method evaluation methodology based on a balanced corpus of 60 Arabic source texts from the three genres. Objective measures, including BLEU and TER, and subjective evaluations from human translators were employed to determine the semantic, contextual an

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Publication Date
Fri Jul 01 2016
Journal Name
International Journal Of Modern Trends In Engineering And Research (ijmter)
An image processing oriented optical mark reader based on modify multi-connect architecture (MMCA)
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Optical Mark Recognition (OMR) is the technology of electronically extracting intended data from marked fields, such as squareand bubbles fields, on printed forms. OMR technology is particularly useful for applications in which large numbers of hand-filled forms need to be processed quickly and with a great degree of accuracy. The technique is particularly popular with schools and universities for the reading in of multiple choice exam papers. This paper proposed OMRbased on Modify Multi-Connect Architecture (MMCA) associative memory, its work in two phases: training phase and recognition phase. The proposed method was also able to detect more than one or no selected choice. Among 800 test samples with 8 types of grid answer sheets and tota

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Publication Date
Thu Sep 20 2018
Journal Name
Www.intechopen.com
Internet of Things (IoT) for Automated and Smart Applications
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Internet of Things (IoT) is a recent technology paradigm that creates a global network of machines and devices that are capable of communicating with each other. Security cameras, sensors, vehicles, buildings, and software are examples of devices that can exchange data between each other. IoT is recognized as one of the most important areas of future technologies and is gaining vast recognition in a wide range of applications and fields related to smart homes and cities, military, education, hospitals, homeland security systems, transportation and autonomous connected cars, agriculture, intelligent shopping systems, and other modern technologies. This book explores the most important IoT automated and smart applications to help the reader u

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Publication Date
Tue Oct 30 2018
Journal Name
Iraqi Journal Of Physics
Synthesized copper nanoparticles by sonoelectrodeposition for gas filter applications
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Copper nanoparticles (CuNPs) were prepared with different diameters by sonoelectrodeposition technique using Electrodeposition process coupled with high-power ultrasound horn (Sonoelectrodeposition). The particle diameter of the CuNPs was adjusted by varying CuSO4 solution acidity (pH) and current density. The morphology and structure of the CuNPs were examined by X-ray diffraction (XRD) and Scanning Electron Microscopy (SEM). It was found that the size of the produced copper nanoparticles ranged between 22 to 77 nm, where the diameter of CuNPs increases with reduction the solution acidity from 0.5 to 1.5 pH and increasing the current density of the deposition from 100 to 400 nm. Finally the produced CuNPs were pressed to fabricate disc

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Publication Date
Wed Dec 13 2017
Journal Name
Al-khwarizmi Engineering Journal
Weldability of New Material Sandwich Steel for Automotive Applications
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Todays, World is faced an energy crisis because of a continuous increasing the consumption of fuels due to intension demand for all types of vehicles. This study is one of the efforts dealing with reduce the weight of vehicles by using a new material of sandwich steel, which consists of two skin steel sheets with core of a polymer material. Resistance spot welding (RSW) can be easily implemented on metals; however a cupper shunt tool was designed to perform the resistance welding of sandwich steel with DP800 cover sheets to resolve a non-conductivity problem of a polymer core. Numerical simulations with SORPAS®3D were employed to test the weldability of this new material and supported by many practical experiments. In conclus

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Publication Date
Sun Jan 13 2019
Journal Name
Iraqi Journal Of Physics
Characterization of CuO thin films for gas sensing applications
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Nanostructural cupric oxide (CuO) films were prepared on Si and glass substrate by pulsed laser deposition technique (PLD) using laser Nd:YAG, using different laser pulses energies from 200 to 600 mJ. The X-ray diffraction pattern (XRD) of the films showed a polycrystalline structure with a monoclinic symmetry and preferred orientation toward (111) plane with nano structure. The crystallite size was increasing with increasing of laser pulse energy. Optical properties was characterized by using UV–vis spectrometer in the wave lengthrange (200-1100) nm at room temperature. The results showed that the transmission spectrum decreases with the laser pulses energy increase. Sensitivity of NO2 gas at different operating temperatures, (50°C,

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