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Sustainable Utilization of Machine-Vision-Technique-Based Algorithm in Objective Evaluation of Confocal Microscope Images
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Confocal microscope imaging has become popular in biotechnology labs. Confocal imaging technology utilizes fluorescence optics, where laser light is focused onto a specific spot at a defined depth in the sample. A considerable number of images are produced regularly during the process of research. These images require methods of unbiased quantification to have meaningful analyses. Increasing efforts to tie reimbursement to outcomes will likely increase the need for objective data in analyzing confocal microscope images in the coming years. Utilizing visual quantification methods to quantify confocal images with naked human eyes is an essential but often underreported outcome measure due to the time required for manual counting and estimation. The current method (visual quantification methods) of image quantification is time-consuming and cumbersome, and manual measurement is imprecise because of the natural differences among human eyes’ abilities. Subsequently, objective outcome evaluation can obviate the drawbacks of the current methods and facilitate recording for documenting function and research purposes. To achieve a fast and valuable objective estimation of fluorescence in each image, an algorithm was designed based on machine vision techniques to extract the targeted objects in images that resulted from confocal images and then estimate the covered area to produce a percentage value similar to the outcome of the current method and is predicted to contribute to sustainable biotechnology image analyses by reducing time and labor consumption. The results show strong evidence that t-designed objective algorithm evaluations can replace the current method of manual and visual quantification methods to the extent that the Intraclass Correlation Coefficient (ICC) is 0.9.

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Publication Date
Sun Mar 26 2023
Journal Name
Wasit Journal Of Pure Sciences
Covid-19 Prediction using Machine Learning Methods: An Article Review
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The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system

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Publication Date
Wed Apr 16 2025
Journal Name
International Journal Of Engineering Pedagogy (ijep)
Utilizing Machine Learning Techniques to Predict University Students' Digital Competence
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Given the importance of possessing the digital competence (DC) required by the technological age, whether for teachers or students and even communities and governments, educational institutions in most countries have sought to benefit from modern technologies brought about by the technological revolution in developing learning and teaching and using modern technologies in providing educational services to learners. Since university students will have the doors to work opened in all fields, the research aims to know their level of DC in artificial intelligence (AI) applications and systems utilizing machine learning (ML) techniques. The descriptive approach was used, as the research community consisted of students from the University

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Publication Date
Mon Jan 01 2024
Journal Name
Bio Web Of Conferences
Forecasting Cryptocurrency Market Trends with Machine Learning and Deep Learning
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Cryptocurrency became an important participant on the financial market as it attracts large investments and interests. With this vibrant setting, the proposed cryptocurrency price prediction tool stands as a pivotal element providing direction to both enthusiasts and investors in a market that presents itself grounded on numerous complexities of digital currency. Employing feature selection enchantment and dynamic trio of ARIMA, LSTM, Linear Regression techniques the tool creates a mosaic for users to analyze data using artificial intelligence towards forecasts in real-time crypto universe. While users navigate the algorithmic labyrinth, they are offered a vast and glittering selection of high-quality cryptocurrencies to select. The

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Publication Date
Mon Mar 01 2010
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
A Proposed Algorithm for Steganography
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Publication Date
Wed Jun 12 2019
Journal Name
Dirasat: Human And Social Sciences
Teaching by pause technique in the classroom
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Communication represents the essence of language learning. Since the unspecified evolution of conveying information, human beings have been employing the main constituents of language with short pauses. Although the punctuation marks necessitate short expressions among thought group of words in writing, human language demand for understanding how and when to pause orally. This paper presents the pause technique in the classroom. It signifies the relation between pausing and lecturing in the class and determines its sufficient time-management to interact with college learners of different specializations. The conduct study reviewed teaching pause technique in the empirical studies at Special Education and Communication Disorders of Pennsylva

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Publication Date
Sun Jan 01 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
Sustainable communities rating system within the context of Iraqi cities characteristics
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Abstract<p>Rating systems for evaluating the sustainability of communities are an essential tool that is increasingly applied throughout the developed world to set criteria indicators to optimize the physical, social, economic, and environmental potential within such communities. Rating systems vary based on existing disparities among societies and their unique building and physical planning practices. Iraqi cities lacked the adaptation of a formal methodology or sustainability rating system to correctly measure the built environment’s sustainability indicators. This research attempts to review the most substantial rating systems to measure the sustainability of communities worldwide to form a</p> ... Show More
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Publication Date
Sat Oct 04 2025
Journal Name
Journal Of The College Of Basic Education
Objective trends of university theses and dissertations of the College of Political Science at the University of Baghdad: an analytical study
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The research sought to identify the objective trends of postgraduate students at the College of Political Science - University of Baghdad for the period from 2000-2012 through the objective trends of university theses and dissertations and what are the most and least studied topics, with a re-adjustment of previously studied topics towards topics that serve issues of concern to society and avoiding topics that have been studied a lot to avoid repetition. The research came out with the following results, the most prominent of which are: The total number of what was accomplished in this college is 401 theses and dissertations, and the dissertations had the largest share of them, as their percentage reached 69%, with 275 theses compared to 126

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Publication Date
Mon Mar 08 2021
Journal Name
Baghdad Science Journal
Development of six-degree of freedom strapdown terrestrial INS algorithm
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Many of accurate inertial guided missilc systems need to use more complex mathematical calculations and require a high speed processing to ensure the real-time opreation. This will give rise to the need of developing an effcint

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Publication Date
Sun Nov 27 2022
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The strategic vision and its impact on the growth strategy of insurance companies: Applied research in the Iraqi General Insurance Company
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The subject of the strategic vision is of great importance to all companies because they live in an environment of rapid change in various areas of life. Supports the performance of its operations in a better way, towards appropriate strategic growth and achieving success. The research aims to determine the level of interest of the researched company in the research variables (strategic vision and growth strategy), and the importance of the research came in being an attempt to provide the theoretical and scientific foundations for the research variables (strategic vision and growth strategy). As for the research method, it was relied on the descriptive analytical method, relying on the questionnaire as a means of obtaining data from the

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Publication Date
Wed Mar 20 2024
Journal Name
Journal Of Petroleum Research And Studies
Advanced Machine Learning application for Permeability Prediction for (M) Formation in an Iraqi Oil Field
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Permeability estimation is a vital step in reservoir engineering due to its effect on reservoir's characterization, planning for perforations, and economic efficiency of the reservoirs. The core and well-logging data are the main sources of permeability measuring and calculating respectively. There are multiple methods to predict permeability such as classic, empirical, and geostatistical methods. In this research, two statistical approaches have been applied and compared for permeability prediction: Multiple Linear Regression and Random Forest, given the (M) reservoir interval in the (BH) Oil Field in the northern part of Iraq. The dataset was separated into two subsets: Training and Testing in order to cross-validate the accuracy

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