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The role of artificial intelligence in developing humanities studies from archaeological discovery to historical recording and geographical analysis: Application models
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The Fourth Industrial Revolution represents an advanced stage of technological development, characterized by the integration of digital, physical, and biological technologies, with a strong focus on smart connectivity and advanced data analysis. At the core of this revolution stands Artificial Intelligence (AI), which enables the processing of vast amounts of data, decision-making with speed and accuracy, automation of processes, and enhancement of productivity and quality. This research examines the transformative role of AI in the humanities, particularly in archaeological, historical, and geographical studies, where traditional methods face limitations in handling complex and extensive datasets.The study aims to highlight these limitations, explore the potential of AI in analyzing diverse archaeological data to uncover new patterns, examine its role in processing large historical sources, and investigate its application in spatial data analysis for environmental and urban changes. The main hypothesis posits that AI can reveal patterns and insights unattainable by conventional methods, thereby enhancing understanding of past civilizations, historical trends, and geographical dynamics.Using a descriptive-analytical methodology supported by practical examples, the research illustrates AI applications such as satellite image analysis, artifact examination, and archival data processing. The findings indicate that integrating AI with humanities research not only improves data analysis efficiency but also maintains the critical and interpretive framework of the humanities, enabling a deeper understanding of society, history, and collective awareness in the digital era.The study concluded that integrating artificial intelligence into humanities research not only improves the efficiency and speed of data analysis but also contributes to the development of the research methodology itself, by shifting from descriptive to analytical and predictive studies, while preserving the critical and interpretive dimensions of the humanities. The study also recommends strengthening collaboration between researchers in the humanities and computer science, establishing open-source Arabic digital archives, and training researchers in the use of artificial intelligence tools. This will contribute to broadening the horizons of humanities research and connecting the past with the present within an integrated scientific framework that meets the demands of the digital age.

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Publication Date
Wed Jun 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
A proposed model for disclosing the role of the collective intelligence system in improving joint auditing
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This research aims to present a proposed model for disclosure and documentation when performing the audit according to the joint audit method by using the questions and principles of the collective intelligence system, which leads to improving and enhancing the efficiency of the joint audit, and thus enhancing the confidence of the parties concerned in the outputs of the audit process. As the research problem can be formulated through the following question: “Does the proposed model for disclosure of the role of the collective intelligence system contribute to improving joint auditing?”   

The proposed model is designed for the disclosure of joint auditing and the role

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Publication Date
Thu Jan 01 2026
Journal Name
Sustainable Civil Infrastructures
The Effectiveness of Physical Exercises in Improving Lung Function After COVID-19 Infection: A Physiological Study Using Artificial Intelligence
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The COVID-19 pandemic has deeply affected the respiratory health of people, leaving many sufferers with long term pulmonary problems. Artificial intelligence based physiological analysis of structured exercise program on lung function of recovered COVID 19 patient is studied. The research introduces an integrated data driven approach for assessing the improvement of respiratory through physical training. The approach is to integrate wearable sensor technology with machine learning algorithms. A controlled experimental study with three groups (recovered COVID-19 patients, smokers, healthy individuals) was used as a method. To that aim, each of the participants underwent an eight-week structured aerobic training program that included continuo

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Publication Date
Mon Apr 08 2019
Journal Name
International Journal Of Building Pathology And Adaptation
A scientometric analysis of BIM studies in facilities management
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Purpose

The purpose of this paper is to statistically classify and categorize Building Information Modelling (BIM)-Facility Management (FM) publications in order to extract useful information related to the adoption and use of BIM in FM.

Design/methodology/approach

This study employs a quantitative approach using science mapping techniques to examine BIM-FM publications using Web of Science (WOS) database for the period between 2000 and April 2018.

Findings

The findi

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Publication Date
Mon Aug 01 2022
Journal Name
Baghdad Science Journal
Application of GIS technique in the studies on fish assemblages in Shatt Al-Arab River, Basrah, Iraq
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The present study has examined the spatiotemporal varieties of the demographics of the Shatt Al-Arab River fishes and their relation to some ecological components. The aim is to forecast these groups in the unexplored parts of the waterway with an emphasis on environmental indices of diversity. Three sites in the river were selected as an observation and study of these species, which lasted from March 2019 to February 2020, the study dealt with factors affecting fishes, as Water Temperature (WT), Dissolved Oxygen (DO), Potential Hydrogen Ion (pH), Salinity (Sal), and Transparency (Tra). Gill nets, cast nets, hooks, and hand nets were adopted to collecting fish. The results indicated that the fish population comprises 60 species represent

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Publication Date
Sun Feb 10 2019
Journal Name
Journal Of The College Of Education For Women
An Application Domain Based on General Object Oriented Software Models
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Any software application can be divided into four distinct interconnected domains namely, problem domain, usage domain, development domain and system domain. A methodology for assistive technology software development is presented here that seeks to provide a framework for requirements elicitation studies together with their subsequent mapping implementing use-case driven object-oriented analysis for component based software architectures. Early feedback on user interface components effectiveness is adopted through process usability evaluation. A model is suggested that consists of the three environments; problem, conceptual, and representational environments or worlds. This model aims to emphasize on the relationship between the objects

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Publication Date
Sun Mar 01 2009
Journal Name
Al-khwarizmi Engineering Journal
A Proposed Artificial Intelligence Algorithm for Assessing of Risk Priority for Medical Equipment in Iraqi Hospital
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This paper presents a robust algorithm for the assessment of risk priority for medical equipment based on the calculation of static and dynamic risk factors and Kohnen Self Organization Maps (SOM). Four risk parameters have been calculated for 345 medical devices in two general hospitals in Baghdad. Static risk factor components (equipment function and physical risk) and dynamics risk components (maintenance requirements and risk points) have been calculated. These risk components are used as an input to the unsupervised Kohonen self organization maps. The accuracy of the network was found to be equal to 98% for the proposed system. We conclude that the proposed model gives fast and accurate assessment for risk priority and it works as p

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Publication Date
Wed May 31 2023
Journal Name
Iraqi Geological Journal
Studying the Effect of Permeability Prediction on Reservoir History Matching by Using Artificial Intelligence and Flow Zone Indicator Methods
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The map of permeability distribution in the reservoirs is considered one of the most essential steps of the geologic model building due to its governing the fluid flow through the reservoir which makes it the most influential parameter on the history matching than other parameters. For that, it is the most petrophysical properties that are tuned during the history matching. Unfortunately, the prediction of the relationship between static petrophysics (porosity) and dynamic petrophysics (permeability) from conventional wells logs has a sophisticated problem to solve by conventional statistical methods for heterogeneous formations. For that, this paper examines the ability and performance of the artificial intelligence method in perme

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Publication Date
Sun Mar 03 2013
Journal Name
Baghdad Science Journal
Species of Centaurium Hill. in Iraq and its geographical distribution
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Comparative taxonomic study has been compeleted for the species of the. genus Centaurium Hill. of Iraq. So the morphological characters were studied comparatively for the first time form Iraqi materials. Stems, leaves ,infloresences and reproductive organs characters were a good taxonomic importance. Geographical distrtribution has been done for the species of the genus in addition to the environment information. The results were presented with schedules, tables, maps and micrographs. Taxonomic key for the species separation was also presented.

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Publication Date
Sun Dec 31 2023
Journal Name
Sumer Journal For Pure Science
COVID-19Disease Diagnosis using Artificial Intelligence based on Gene Expression: A Review
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Publication Date
Wed Jan 15 2003
Journal Name
كلية الترا ث الجامعة
Estimating an Exponentiated Expanded Power Function Distribution Using an Artificial Intelligence Algorithm
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The distribution of the expanded exponentiated power function EEPF with four parameters, was presented by the exponentiated expanded method using the expanded distribution of the power function, This method is characterized by obtaining a new distribution belonging to the exponential family, as we obtained the survival rate and failure rate function for this distribution, Some mathematical properties were found, then we used the developed least squares method to estimate the parameters using the genetic algorithm, and a Monte Carlo simulation study was conducted to evaluate the performance of estimations of possibility using the Genetic algorithm GA.