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Multi-Resolution Hierarchical Structure for Efficient Data Aggregation and Mining of Big Data
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Big data analysis is essential for modern applications in areas such as healthcare, assistive technology, intelligent transportation, environment and climate monitoring. Traditional algorithms in data mining and machine learning do not scale well with data size. Mining and learning from big data need time and memory efficient techniques, albeit the cost of possible loss in accuracy. We have developed a data aggregation structure to summarize data with large number of instances and data generated from multiple data sources. Data are aggregated at multiple resolutions and resolution provides a trade-off between efficiency and accuracy. The structure is built once, updated incrementally, and serves as a common data input for multiple mining and learning algorithms. Data mining algorithms are modified to accept the aggregated data as input. Hierarchical data aggregation serves as a paradigm under which novel …

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Publication Date
Wed Sep 20 2023
Journal Name
Baghdad Science Journal
Synthesis, Characterization and Bioactivity Evaluation for Some Metal Ions Complexes with New Ligand Derived from 2-hydroxy-1- napthaldehyed
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The newly synthesized Schiff base ligand (E)-2-((2-phenylhydrazono)methyl)naphthalen-1-ol (phenyl hydrazine derivative), is allowed to react with each of the next mineral ion: Ni2+, Cu2+, Zn2+andCd2+successfully resulting to obtain new metal complexes with different geometric shape. The formation of Schiff base complexes and also the origin Schiff base is indicated using LC-Mass that manifest the obtained molar mass, FT-IR proved the occurrence of coordination through N of azobenzene and O of OH by observing the shifting in azomethines band and appearing of M-N and N-O bands. Moreover, we can also detect by such apparatus, the presence of aquatic water molecule inside the coordination sphere. UV-Vis spectra of all resultants reveale

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Publication Date
Wed Oct 30 2024
Journal Name
Internet Technology Letters
Using <scp>5G</scp> Standards for Smart Healthcare Applications and Designing an Artificial Intelligence‐Based Industry 4.0 Communication System
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ABSTRACT<p>The introduction of Industry 4.0, to improve Internet of Things (IoT) standards, has sparked the creation of 5G, or highly sophisticated wireless networks. There are several barriers standing in the way of 5G green communication systems satisfying the expectations for faster networks, more user capacity, lower resource consumption, and cost‐effectiveness. 5G standards implementation would speed up data transmission and increase the reliability of connected devices for Industry 4.0 applications. The demand for intelligent healthcare systems has increased globally as a result of the introduction of the novel COVID‐19. Designing 5G communication systems presents research problems such as optimizing </p> ... Show More
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Publication Date
Thu Aug 24 2023
Journal Name
Environmental Monitoring And Assessment
Rice husk coated with copper oxide nanoparticles for 17α-ethinylestradiol removal from an aqueous solution: adsorption mechanisms and kinetics
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The 17 α-ethinylestradiol (EE2) adsorption from aqueous solution was examined using a novel adsorbent made from rice husk powder coated with CuO nanoparticles (CRH). Advanced analyses of FTIR, XRD, SEM, and EDSwere used to identify the classification parameters of a CRH-like surface morphology, configuration, and functional groups. The rice husk was coated with CuO nanoparticles, allowing it to create large surface area materials with significantly improved textural qualities with regard to functional use and adsorption performance, according to a detailed characterization of the synthesized materials. The adsorption process was applied successfully with elimination effectiveness of 100% which can be kept up to 61.3%. The parameters of ads

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Publication Date
Tue Mar 28 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Nitric Oxide, Peroxynitrite and Malondialdehyde Levels as Markers for Nitrosative/Oxidative Stress in Iraqi Patients with Systemic Lupus Erythematosus
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Systemic lupus Erythematosus is an autoimmune disease of unknown aetiology affecting multiple organ system. Reactive nitrogen and oxygen species are claimed to play a role in this disease. However, the potential of Nitrosative/Oxidative Stress to elicit an autoimmune, response remain till now largely unexplored in humans. This study was done to investigate the status and contribution of nitrosative/oxidative stress in Iraqi patients for systemic lupus erythematosus. Blood samples from 19 patients with systemic lupus erythematosus and 19 age-and sex- matched apparently healthy controls were evaluated for serum levels of nitrosative/oxidative stress markers including nitric oxide, peroxynitrite and malondialdehyde. Nitric oxide levels were

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Publication Date
Fri Oct 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Reforming the insurance sector and its role in stimulation gross domestic product in Iraq for the period (2014-2018)
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The main purpose of the research is to demonstrate the importance of the insurance sector in the economy through its role in providing security for all economic sectors and thus stimulating the gross domestic product and reducing dependence on the output of the oil sector, which may expose the Iraqi economy to several problems and imbalances, I have found that there is a great weakness in the role of the insurance sector in Iraq at the level of government, companies and individuals, and the reason for this is the lack of policies supporting the insurance sector and the lack of work in the strategy of economic diversity and the decrease of security awareness by individuals so became Developing the sector to ensure the urgent need

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Publication Date
Thu Aug 01 2024
Journal Name
Water Practice &amp; Technology
Artificial neural network and response surface methodology for modeling oil content in produced water from an Iraqi oil field
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ABSTRACT<p>The majority of the environmental outputs from gas refineries are oily wastewater. This research reveals a novel combination of response surface methodology and artificial neural network to optimize and model oil content concentration in the oily wastewater. Response surface methodology based on central composite design shows a highly significant linear model with P value &lt;0.0001 and determination coefficient R2 equal to 0.747, R adjusted was 0.706, and R predicted 0.643. In addition from analysis of variance flow highly effective parameters from other and optimization results verification revealed minimum oily content with 8.5 ± 0.7 ppm when initial oil content 991 ppm, tempe</p> ... Show More
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Publication Date
Wed Jun 01 2022
Journal Name
Applied Energy
Novel mathematical modeling, performance analysis, and design charts for the typical hybrid photovoltaic/phase-change material (PV/PCM) system
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Publication Date
Sun Feb 10 2019
Journal Name
Journal Of The College Of Education For Women
Building the Test of Drawing Skill for the Female students of Kindergartens' Department
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The research issue and its importance concentrate on the importance of choosing and
preparing the kindergarten's teacher educationally ,psychologically and artistically ,and other
aspects because of their need for several skills such as the drawing skill for kindergarten
curriculums include a various artistic experiences and activities as well as for the drawing
importance for the child .And from this, the research goals raise from to prepare a test that
measures the drawing skill for kindergarten students and measure the drawing skill in all four
kindergarten students at the kindergarten department and recognize the differences level for
these students . In order to achieve the first goal in the research ,the resear

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Publication Date
Thu Dec 01 2016
Journal Name
المجلة العربية للعلوم و نشر الأبحاث
Assessment of Carbonate Rocks , Western Desert of Iraq as Dimension Stones for Building
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Publication Date
Thu Sep 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of Some Methods for Estimating Mixture of Linear Regression Models with Application
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 A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the others

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