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Increasing Safety in Highways Transit Systems by Using Ethical Artificial Intelligence AI
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“Smart city” projects have become fully developed and are actively using video analytics. Our study looks at how video analytics from surveillance cameras can help manage urban areas, making the environment safer and residents happier. Every year hundreds of people fall on subway and railway lines. The causes of these accidents include crowding, fights, sudden health problems such as dizziness or heart attacks, as well as those who intentionally jump in front of trains. These accidents may not cause deaths, but they cause delays for tens of thousands of passengers. Sometimes passers-by have time to react to the event and try to prevent it, or contact station personnel, but computers can react faster in such situations by using ethical AI. Video analytics systems can “see” a person on the tracks instantly, and automatically give trains a red light while issuing an alarm sound, as happens in modern car cameras when they give out sound and images through the associated alarm device in the event of any emergency occurring near the car.

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Publication Date
Fri Jan 24 2025
Journal Name
International Journal Of Sustainable Development And Planning
Simulating Natural Systems for Urban Intelligence: A Case Study of Dora Municipality, Baghdad, for Sustainable Urban Development
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The rapid sprawl in urban areas caused by excessive production and consumption of goods (as driven by local poor social choices) has inevitably resulted in a major burden due to environmental degradation worldwide. Unfortunately, these traditional models of urban planning fail to properly account for the intricacies that permeate a modern city and are deficient in terms of their approach as they shape themselves within an environment largely divorced from natural systems, resulting in vast mismanagement of resources, guiding cities down trajectories where growth destroys both physical and cultural landscapes. As cities suffer from increasing scarcity, we advocate for regeneration and resilience to be embedded in advanced urban design approa

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Publication Date
Thu Dec 28 2017
Journal Name
Al-khwarizmi Engineering Journal
The Effect of Increasing Carbon Concentration Increasing on the Mechanical Properties of TiCx Thin Films
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Carbides or nitrides thin films present materials with good mechanical properties for industrial applications as they can be coatings at low temperatures serve temperature sensitive surfaces. In this work the effect of the C percentage on the mechanical properties represented by the Young modulus (E) of combinatorial magnetron sputtered TiCx (34%x˂65%) has been studied. The structure of the produced films is TiC independent on the C concentration. The mechanical properties are increased with increasing the C concentration up to 50%, and then decreasing with further C % increasing. These results can be explained by considering the resultant residual stresses.

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Publication Date
Mon Feb 01 2016
Journal Name
International Journal Of Applied Mathematics & Statistical Sciences
Topological Structures Using Mixed Degree Systems in Graph Theory
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This paper is concerned with introducing and studying the M-space by using the mixed degree systems which are the core concept in this paper. The necessary and sufficient condition for the equivalence of two reflexive M-spaces is super imposed. In addition, the m-derived graphs, m-open graphs, m-closed graphs, m-interior operators, m-closure operators and M-subspace are introduced. From an M-space, a unique supratopological space is introduced. Furthermore, the m-continuous (m-open and m-closed) functions are defined and the fundamental theorem of the m-continuity is provided. Finally, the m-homeomorphism is defined and some of its properties are investigated.

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Publication Date
Sun Oct 01 2023
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Intelligence framework dust forecasting using regression algorithms models
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<span>Dust is a common cause of health risks and also a cause of climate change, one of the most threatening problems to humans. In the recent decade, climate change in Iraq, typified by increased droughts and deserts, has generated numerous environmental issues. This study forecasts dust in five central Iraqi districts using machine learning and five regression algorithm supervised learning system framework. It was assessed using an Iraqi meteorological organization and seismology (IMOS) dataset. Simulation results show that the gradient boosting regressor (GBR) has a mean square error of 8.345 and a total accuracy ratio of 91.65%. Moreover, the results show that the decision tree (DT), where the mean square error is 8.965, c

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Publication Date
Mon Feb 13 2023
Journal Name
Journal Of Educational And Psychological Researches
Ethical Behavior and its Relationship to Social Media Uses among Female Students at Preparatory Schools in Baghdad
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The current study aims to assess the ethical behavior among female students who are using a social media network in addition to describe the variables of interest (social media use and ethical behavior) among participants, in which to find out the effects of social media on the ethical behavior of high school female students. A quantitative approach was adopted to collect the relevant data for the study, six schools included in this study from the six directorates of education in Baghdad city. Subsequently, SPSS software was applied to analyze the relevant data of the study. To achieve the research objectives, a questionnaire was composed of three sections: Part I: deals with the student's demographic information. Part II: deals with inf

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Publication Date
Sun Dec 30 2007
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of Fractional Hold-Up in RDC Column Using Artificial Neural Network
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In the literature, several correlations have been proposed for hold-up prediction in rotating disk contactor. However,
these correlations fail to predict hold-up over wide range of conditions. Based on a databank of around 611
measurements collected from the open literature, a correlation for hold up was derived using Artificial Neiral Network
(ANN) modeling. The dispersed phase hold up was found to be a function of six parameters: N, vc , vd , Dr , c d m / m ,
s . Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 6.52%
and Standard Deviation (SD) 9.21%. A comparison with selected correlations in the literature showed that the
developed ANN correlation noticeably

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Publication Date
Mon Feb 16 2026
Journal Name
Agribusiness
Economic Analysis of AI‐Driven Resource Efficiency in Sustainable Agriculture in Iraq
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Abstract<p> Water scarcity, rising energy costs, and declining irrigation efficiency are significant barriers to wheat production in Iraq. This study evaluates the economic, environmental, and sustainability impacts of integrating artificial intelligence (AI) into irrigation management under semiarid conditions. Field experiments conducted at the Al‐Ra'id Research Station in Baghdad during the 2025 season compared conventional diesel‐based irrigation with AI‐assisted irrigation that used soil moisture sensors, Internet of Things (IoT) controllers, and predictive weather algorithms. The analysis employed Cobb–Douglas production modeling, cost–benefit analysis, net</p> ... Show More
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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Solving Optimal Control Linear Systems by Using New Third kind Chebyshev Wavelets Operational Matrix of Derivative
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In this paper, a new third kind Chebyshev wavelets operational matrix of derivative is presented, then the operational matrix of derivative is applied for solving optimal control problems using, third kind Chebyshev wavelets expansions. The proposed method consists of reducing the linear system of optimal control problem into a system of algebraic equations, by expanding the state variables, as a series in terms of third kind Chebyshev wavelets with unknown coefficients. Example to illustrate the effectiveness of the method has been presented.

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Publication Date
Mon Jan 01 2024
Journal Name
Open Engineering
Using ANN for well type identifying and increasing production from Sa’di formation of Halfaya oil field – Iraq
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Abstract<p>The current study focuses on utilizing artificial intelligence (AI) techniques to identify the optimal locations of production wells and types for achieving the production company’s primary objective, which is to increase oil production from the Sa’di carbonate reservoir of the Halfaya oil field in southeast Iraq, with the determination of the optimal scenario of various designs for production wells, which include vertical, horizontal, multi-horizontal, and fishbone lateral wells, for all reservoir production layers. Artificial neural network tool was used to identify the optimal locations for obtaining the highest production from the reservoir layers and the optimal well type. Fo</p> ... Show More
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Publication Date
Mon Feb 18 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Auditing Quality According To Artificial Intelligence: Applied Research on A Sample of Regulatory Bodies Working In The Federal Board of Supreme Audit
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The Evolution Of Information Technology And The Use Of Computer Systems Led To Increase Attention To The Use Of Modern Techniques In The Auditing Process , As It Will Overcome Some Of The Human Shortcomings In The Exercise Of Professional Judgment, Then It Can Improve The Efficiency And Effectiveness Of The Audit Process, Where The New Audit Methodologies Espouse The Concept Of Risk Which Includes Strategic Dimension With Regard To The Capacity Of The Entity To Achieve Its Goals, Which Requires Auditors To Rely On Advanced Technology That Can Identify The Factors Which Prevent The Entity From Achieving Its Objectives. The Idea Of Research Is To Preparing An Electronic Program Fer All Audit Work From Planning Through Sampling And Document

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