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Systematic development of an autonomous robotic car for fire-fighting based on the interactive design approach
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Fire incidences are classed as catastrophic events, which mean that persons may experience mental distress and trauma. The development of a robotic vehicle specifically designed for fire extinguishing purposes has significant implications, as it not only addresses the issue of fire but also aims to safeguard human lives and minimize the extent of damage caused by indoor fire occurrences. The primary goal of the AFRC is to undergo a metamorphosis, allowing it to operate autonomously as a specialized support vehicle designed exclusively for the task of identifying and extinguishing fires. Researchers have undertaken the tasks of constructing an autonomous vehicle with robotic capabilities, devising a universal algorithm to be employed in the robotic firefighting process, and designing a fuzzy controller algorithm that can be used in all expected scenarios. The use of a fuzzy logic algorithm in this design demonstrates the usefulness of this system, all factors are involved in which cases are previously identified and taught, as well as the overall map of the premises have been uploaded so that the system can identify the exact place of the fire source, and two types of fire have also been examined. When the performance of the foam pump, water pump, and robotic car motors is compared to the data from the flam sensor, temperature sensor and GPS data, it demonstrates a high responsiveness in terms of applying the appropriate approach based on the type of fire due to the probable action for which the system has been trained. This will have the benefit of shortening the required process for fire extinguishment and using the appropriate fire extinguishing tools. This technology may be used to put out flames, deploy in different areas, and handle a variety of fire scenarios inside buildings

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Publication Date
Wed Apr 15 2020
Journal Name
Al-mustansiriyah Journal Of Science
Adaptation Proposed Methods for Handling Imbalanced Datasets based on Over-Sampling Technique
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Classification of imbalanced data is an important issue. Many algorithms have been developed for classification, such as Back Propagation (BP) neural networks, decision tree, Bayesian networks etc., and have been used repeatedly in many fields. These algorithms speak of the problem of imbalanced data, where there are situations that belong to more classes than others. Imbalanced data result in poor performance and bias to a class without other classes. In this paper, we proposed three techniques based on the Over-Sampling (O.S.) technique for processing imbalanced dataset and redistributing it and converting it into balanced dataset. These techniques are (Improved Synthetic Minority Over-Sampling Technique (Improved SMOTE),  Border

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Publication Date
Thu Nov 17 2022
Journal Name
Journal Of Information And Optimization Sciences
Hybrid deep learning model for Arabic text classification based on mutual information
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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
PDCNN: FRAMEWORK for Potato Diseases Classification Based on Feed Foreword Neural Network
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         The economy is exceptionally reliant on agricultural productivity. Therefore, in domain of agriculture, plant infection discovery is a vital job because it gives promising advance towards the development of agricultural production. In this work, a framework for potato diseases classification based on feed foreword neural network is proposed. The objective of this work  is presenting a system that can detect and classify four kinds of potato tubers diseases; black dot, common scab, potato virus Y and early blight based on their images. The presented PDCNN framework comprises three levels: the pre-processing is first level, which is based on K-means clustering algorithm to detect the infected area from potato image. The s

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Publication Date
Tue Feb 28 2023
Journal Name
Applied System Innovation
Earthquake Hazard Mitigation for Uncertain Building Systems Based on Adaptive Synergetic Control
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This study presents an adaptive control scheme based on synergetic control theory for suppressing the vibration of building structures due to earthquake. The control key for the proposed controller is based on a magneto-rheological (MR) damper, which supports the building. According to Lyapunov-based stability analysis, an adaptive synergetic control (ASC) strategy was established under variation of the stiffness and viscosity coefficients in the vibrated building. The control and adaptive laws of the ASC were developed to ensure the stability of the controlled structure. The proposed controller addresses the suppression problem of a single-degree-of-freedom (SDOF) building model, and an earthquake control scenario was conducted and simulat

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Publication Date
Tue Sep 01 2020
Journal Name
Asian Journal Of Pharmacy And Pharmacology
Clinical manifestations and maternal outcomes of COVID-19 in pregnancy: A systematic review
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Publication Date
Wed Jul 31 2024
Journal Name
Cureus
Neuro-Ophthalmic Manifestations of Carotid Cavernous Fistulas: A Systematic Review and Meta-Analysis
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Publication Date
Sun Apr 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Effect of Development International Financial Reporting Standards (IFRS) in Quality of Accounting Information for sample of banks listed on the Iraq Stock Exchange
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The bodies responsible for the organization of accounting in the world seek to keep abreast of repaid development, by provide the information required by users, which they need to make efficient decision that return them to the desired benefits, and avoid the risks they could face if they made their decision based on misleading information, or insufficient, or not accurate, Hence, the IASB has undertaken to review the standards, and make the necessary adjustment and clarifications to remove the ambiguities that some of the paragraphs may have in IFRS issued.

And the Iraqi Central Bank obliges banks to convert from local accounting standards to apply IFRS only a step towards keeping pace with developments

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Publication Date
Wed Jan 04 2017
Journal Name
Iraqi Journal Of Science
Histological study of the Isotretinoin drug effect on the intrauterine prenatal development in the pregnant mice
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Publication Date
Mon Sep 23 2019
Journal Name
Baghdad Science Journal
New Approach for Solving Three Dimensional Space Partial Differential Equation
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This paper presents a new transform method to solve partial differential equations, for finding suitable accurate solutions in a wider domain. It can be used to solve the problems without resorting to the frequency domain. The new transform is combined with the homotopy perturbation method in order to solve three dimensional second order partial differential equations with initial condition, and the convergence of the solution to the exact form is proved. The implementation of the suggested method demonstrates the usefulness in finding exact solutions. The practical implications show the effectiveness of approach and it is easily implemented in finding exact solutions.

       Finally, all algori

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Publication Date
Fri Jan 01 2021
Journal Name
Annals Of Pure And Applied Mathematics
Linear Regression Model Using Bayesian Approach for Iraqi Unemployment Rate
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In this paper we used frequentist and Bayesian approaches for the linear regression model to predict future observations for unemployment rates in Iraq. Parameters are estimated using the ordinary least squares method and for the Bayesian approach using the Markov Chain Monte Carlo (MCMC) method. Calculations are done using the R program. The analysis showed that the linear regression model using the Bayesian approach is better and can be used as an alternative to the frequentist approach. Two criteria, the root mean square error (RMSE) and the median absolute deviation (MAD) were used to compare the performance of the estimates. The results obtained showed that the unemployment rates will continue to increase in the next two decade

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