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Revealing the potentials of 3D modelling techniques; a comparison study towards data fusion from hybrid sensors
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Abstract<p>The vast advantages of 3D modelling industry have urged competitors to improve capturing techniques and processing pipelines towards minimizing labour requirements, saving time and reducing project risk. When it comes to digital 3D documentary and conserving projects, laser scanning and photogrammetry are compared to choose between the two. Since both techniques have pros and cons, this paper approaches the potential issues of individual techniques in terms of time, budget, accuracy, density, methodology and ease to use. Terrestrial laser scanner and close-range photogrammetry are tested to document a unique invaluable artefact (Lady of Hatra) located in Iraq for future data fusion scenario. Insight investigations of the factors affecting data processing and modelling in individual comparing techniques are discussed and analysed. Qualitative and quantitative statistical analysis was applied based on multiple criteria, such as level of automation (LOA), accuracy and point cloud integrity towards the adaption of data fusion approaches and co-registering frameworks for optimal deliverables.</p>
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Publication Date
Tue Jan 31 2017
Journal Name
Journal Of Engineering
A Study on the Removal of Direct Blue 71 Dye From Textile Wastewater Produced From State Company of Cotton Industries by Electrocoagulation Using Aluminum Electrodes
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The removal of direct blue 71 dye from a prepared wastewater was studied employing batch electrocoagulation (EC) cell. The electrodes of aluminum were used. The influence of process variables which include initial pH (2.0-12.0), wastewater conductivity (0.8 -12.57) mS/cm , initial dye concentration (30 -210) mg/L, electrolysis time  (3-12) min, current density (10-50) mA/cm2   were studied in order to maximize the color removal from wastewater. Experimental results showed that the color removal yield increases with increasing pH until pH 6.0 after that it decreased with increasing pH. The color removal increased with increasing current density, wastewater conductivity, electrolysis time, and decreased with increasing the concen

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Publication Date
Sun Sep 24 2023
Journal Name
Journal Of Al-qadisiyah For Computer Science And Mathematics
Iris Data Compression Based on Hexa-Data Coding
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Iris research is focused on developing techniques for identifying and locating relevant biometric features, accurate segmentation and efficient computation while lending themselves to compression methods. Most iris segmentation methods are based on complex modelling of traits and characteristics which, in turn, reduce the effectiveness of the system being used as a real time system. This paper introduces a novel parameterized technique for iris segmentation. The method is based on a number of steps starting from converting grayscale eye image to a bit plane representation, selection of the most significant bit planes followed by a parameterization of the iris location resulting in an accurate segmentation of the iris from the origin

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Publication Date
Tue Dec 07 2021
Journal Name
2021 14th International Conference On Developments In Esystems Engineering (dese)
Content Based Image Retrieval Based on Feature Fusion and Support Vector Machine
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Publication Date
Sun Dec 04 2016
Journal Name
Baghdad Science Journal
A study of anti fungal activity of a combination of essential oils from medical herbs against water molds
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The aim of this study is to evaluate the anti fungal activity of a combination of essential oils against water molds. HPLC analysis was done to evaluate the quantity and quality of the active compounds in this combination which extracted from three herbs( Peppermint Menthapiperita ,Thyme Thymusvulgaris, Common sage Salvia officinalis L.) and the active compounds are Camphor,Menthol,,Thujone and Thymol with different concentrations. In this study (MIC) , (MFC) were measured and (LD50) determined after 48,96 h from fingerlings treatment of common carp in aquariums .The results of (MIC) were 0.025µl/ml for Aphanomyces sp. and 0.015µl/ml for both Achlya sp. and Fusariumsolani which showed significant differences(p<0.05) from Malachite gre

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Publication Date
Mon Jan 01 2024
Journal Name
Ieee Access
Transfer Learning and Hybrid Deep Convolutional Neural Networks Models for Autism Spectrum Disorder Classification From EEG Signals
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Publication Date
Mon Jun 30 2025
Journal Name
مجلة القادسية للقانون والعلوم السياسية
Insurance of Unlawful Risks: Towards a Reinterpretation of Public Policy in Light of the Protection of Innocent Victims and Freedom of Contract
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The issue of insurance against unlawful risks raises a jurisprudential and judicial debate between two opposing trends: the first considers coverage of these risks invalid due to their impact on public order or morals, while the second—which this research analyses—calls for the possibility of covering these risks in specific circumstances, based on contractual considerations in accordance with the principle that the contract is the law of the contracting parties, and based on the obligation to compensate the harmed third party—the victim—who has no connection to the unlawful act. In this context, our research highlights that contractual considerations can justify coverage of some unlawful risks, provided that the goal is to achieve

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Publication Date
Wed Oct 18 2023
Journal Name
Ieee Access
A New Imputation Technique Based a Multi-Spike Neural Network to Handle Missing Data in the Internet of Things Network (IoT)
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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Exploring the Challenges of Diagnosing Thyroid Disease with Imbalanced Data and Machine Learning: A Systematic Literature Review
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Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise

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Publication Date
Fri Nov 01 2019
Journal Name
Journal Of Physics: Conference Series
Data Processing, Storage, and Analysis: Applying Computational Procedures to the Case of a Falling Weight Deflectomer (FWD)
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In the field of civil engineering, the adoption and use of Falling Weight Deflectometers (FWDs) is seen as a response to the ever changing and technology-driven world. Specifically, FWDs refer to devices that aid in evaluating the physical properties of a pavement. This paper has assessed the concepts of data processing, storage, and analysis via FWDs. The device has been found to play an important role in enabling the operators and field practitioners to understand vertical deflection responses upon subjecting pavements to impulse loads. In turn, the resultant data and its analysis outcomes lead to the backcalculation of the state of stiffness, with initial analyses of the deflection bowl occurring in conjunction with the measured or assum

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Publication Date
Fri Nov 28 2025
Journal Name
Al–bahith Al–a'alami
The Media and Shaping the Public's Mental Image towards the Transitional Justice
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Media plays an important role in shaping the mental image of their audiences for individuals, groups and organizations, States and peoples. It is the window through which overlooks the masses on events and issues, and in the light of their exposure to these means are their opinions and impressions.

Despite the importance of direct experiences in shaping opinions, drawing pictures and impressions, it is inevitable to rely on these means as individuals can not engage in direct experiences with thousands of events, issues and topics that concern their community and other societies.

There is no doubt that media is of great importance at the present time, because of its significant impact in the management of the course of pol

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