Within the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amount of energy, especially during the training phase. The transmission of big data between service providers, users and data centres emits carbon dioxide as a result of high power consumption. This chapter proposes a theoretical framework for big data analytics using computational intelligent algorithms that has the potential to reduce energy consumption and enhance performance. We suggest that researchers should focus more attention on the issue of energy within big data analytics in relation to computational intelligent algorithms, before this becomes a widespread and urgent problem.
One wide-ranging category of open source data is that referring to geospatial information web sites. Despite the advantages of such open source data, including ease of access and cost free data, there is a potential issue of its quality. This article tests the horizontal positional accuracy and possible integration of four web-derived geospatial datasets: OpenStreetMap (OSM), Google Map, Google Earth and Wikimapia. The evaluation was achieved by combining the tested information with reference field survey data for fifty road intersections in Baghdad, Iraq. The results indicate that the free geospatial data can be used to enhance authoritative maps especially small scale maps.
This paper presents a hybrid approach for solving null values problem; it hybridizes rough set theory with intelligent swarm algorithm. The proposed approach is a supervised learning model. A large set of complete data called learning data is used to find the decision rule sets that then have been used in solving the incomplete data problem. The intelligent swarm algorithm is used for feature selection which represents bees algorithm as heuristic search algorithm combined with rough set theory as evaluation function. Also another feature selection algorithm called ID3 is presented, it works as statistical algorithm instead of intelligent algorithm. A comparison between those two approaches is made in their performance for null values estima
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The common types of movement disorders are ; dystonia which is a syndrome of repetitive muscle contractions. While , Huntington disease is autosomal dominant progressive neurodegenerative disorder, which is characterized by involuntary movements (“chorea”).
Tetrabenazine therapy has been shown to effectively control this movements compared with placebo.
Design the proper dosing approach for patients treated with tetrabenazine with genotype polymorphisms and their hepatic effect on patients.
A prospective case controlled study was carried on 50 patients whom divided into 2 groups :first group involved 25 patients who had cho
... Show MorePurpose: clarify the integrative relationship of strategic leadership skills and effective management and the role of those skills combined or individually in achieving effective management.
Research design: The researchers used the quantitative method by surveying a class sample from the heads of the executive departments in a group of Iraqi private banks, consisting of (106) individuals according to the (VUCA Prime) methodology for effective management and the ten skills model for Johansen. The questionnaire was analyzed using a model of the structural equation.
Findings: The most prominent results of the research were the presence of a weak ro
... Show MoreWith the study of synthesizing new organic compounds and exploring biological potency. Aryldiazenyl derivatives (2-5) were carried out by coupling of diazonium salt of 4-aminoacetophenone (1) and miscellaneous active methylene compounds such as: acetylacetone, ethyl cyanoacetate, dimedone or methyl acetoacetate. Moreover substituted 1,2,3-triazole (7-9) were synthesized by the cyclization of 1-(4-azidophenyl) ethanone (6); (which was obtained by coupling of diazonium salt (1) with sodium azid); with acetylacetone, methyl acetoacetate or methyl cyanoacetate, respectively. The structures of the prepared compounds were promoted by IR, H1NMR and UV/Visible spectra. Further, they were examined in vetro for antibacterial activity against five str
... Show MoreBy unusual method for separating two isomers of a substituted nitro-coumarin using a soxhlet extractor and in controlling temperature to get a selective nitration reaction, several new Schiff base coumarins were synthesized from nitro coumarins as starting material, which were reduced by Fe in glacial acetic acid to produce corresponding amino coumarin derivatives. Then the latter was reacted with different aromatic aldehydes to produce the desired Schiff bases derivatives. After characterization by Fourier transform infrared (FT-IR), Proton nuclear magnetic resonance (1HNMR) and Carbon-13 nuclear magnetic resonance (C-NMR), all these compounds were evaluated as potential Antimicrobial and Antioxidant Agents.
The use of medicinal plant preparations to clean and disinfect root canal infection is gaining popularity. The aim of this study was to evaluate the bioactive composition of leaf extracts of Moringa oleifera plants cultivated in Iraq (specifically Baghdad) and their antimicrobial activity against selected root canal pathogens for potential application in endodontic treatment. Materials and Methods. Moringa leaf extracts were prepared either through cold maceration or warm digestion techniques to perform an ethanolic or aqueous extraction, respectively. Phytochemical detection was performed before thin layer chromatography (TLC) and high-performance liquid chromatography (HPLC) to measure flavonoids and phenolic compounds within both
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