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A Theoretical Framework for Big Data Analytics Based on Computational Intelligent Algorithms with the Potential to Reduce Energy Consumption
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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.

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Publication Date
Wed Jan 01 2020
Journal Name
Technologies And Materials For Renewable Energy, Environment And Sustainability: Tmrees20
Form factor calculations for some light nuclei in the framework of electron scattering
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Publication Date
Wed Apr 14 2021
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Estimation of domestic urban electricity consumption: A case study of Baghdad, Iraq
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Electricity consumption for household purposes in urban areas widely affects the general urban consumption compared to other commercial and industrial uses, as household electricity consumption is affected by many factors related to the physical aspects of the residential area such as temperature, housing unit area, and coverage ratio, as well as social and economic factors such as family size and income, to reach the extent of the influence of each of the above factors on the amount of electricity consumed for residential uses, a selected sample of a residential area in the city of Baghdad was studied and a field survey conducted of the characteristics of that sample and the results analyzed and modeled statistically in relation to the amo

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Publication Date
Tue Dec 01 2020
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
A Haptic feedback system based on leap motion controller for prosthetic hand application
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Leap Motion Controller (LMC) is a gesture sensor consists of three infrared light emitters and two infrared stereo cameras as tracking sensors. LMC translates hand movements into graphical data that are used in a variety of applications such as virtual/augmented reality and object movements control. In this work, we intend to control the movements of a prosthetic hand via (LMC) in which fingers are flexed or extended in response to hand movements. This will be carried out by passing in the data from the Leap Motion to a processing unit that processes the raw data by an open-source package (Processing i3) in order to control five servo motors using a micro-controller board. In addition, haptic setup is proposed using force sensors (F

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Publication Date
Thu Jan 01 2026
Journal Name
Ieee Access
SD-GPON: A Dynamic Prioritization for Efficient Traffic Management Based on Controlling DSCP
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Publication Date
Thu Jan 14 2021
Journal Name
Reviews In Inorganic Chemistry
A review on TiO<sub>2</sub>-based composites for superior photocatalytic activity
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Abstract<p>Heterogeneous photocatalysts was a promising material for removing organic pollutants. Titanium dioxide (TiO<sub>2</sub>) was a suitable photocatalyst for its cost efficiency and high stability to reduce various pollutants. Enhancing TiO<sub>2</sub> photocatalyst performance by doping with changed metals or non-metal ions and organic compounds have been reviewed. These methods could enhance photoelectrochemical activity via: (i) by a donor of electrons via electron-donor agents that would produce particular defects in TiO<sub>2</sub> structure and capture transporters of charge; (ii) by reducing recombination rate of the charge transporters and increasi</p> ... Show More
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Publication Date
Thu Oct 01 2015
Journal Name
Al-academy
The Factors influencing to the cognition operation & its Data: وفاء جاسم محمد
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The present research deals with the influencing factors which depends on the way perceptual of the graphic designer which enters in the design logos of the loco European health, where the search include four chapters, the researcher reviewed in the chapter 0ne the methodical frame of the research ,as reviewed in the second chapter the theoretical frame, and the previous studies which included three sections, the first section included the perceptual understandable and types of it, and the second section included the influencing factors in the designer perceptual ways and its division . While the third section included the perceptual in graphic designer through the percepted shapes and the relation with ground and colors for express the i

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Publication Date
Mon Feb 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Evaluation of real estate investment projects with framework theory of real options: A case study in the shopping center project (Baghdad Mall)
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Focused research aims to provide a framework cognitive analytical nature of real estate investments and how they evaluated in the light of the assessment tools of modern theory of real options, and the possibility to rely on that theory in the detection of the true value of projects, real estate investments that would maximize the value of the investment decision taken, and the analysis of those projects that arise in the real estate markets and environments is the organization, which she was to make sure cases and high-risk, compared with entrances techniques, discounted cash flow (net present value). Based on the assumption lies in the possibility of the application of the implic

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Publication Date
Tue Jun 01 2010
Journal Name
Al-khwarizmi Engineering Journal
Comparison of the RLS and LMS Algorithms to Remove Power Line Interference Noise from ECG Signal
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    Biomedical signal such as ECG is extremely important in the diagnosis of patients and is commonly recorded with a noise. Many different kinds of noise exist in biomedical environment such as Power Line Interference Noise (PLIN). Adaptive filtering is selected to contend with these defects, the adaptive filters can adjust the filter coefficient with the given filter order. The objectives of this paper are: first an application of the Least Mean Square (LMS) algorithm, Second is an application of the Recursive Least Square (RLS) algorithm to remove the PLIN. The LMS and RLS algorithms of the adaptive filter were proposed to adapt the filter order and the filter coefficients simultaneously, the performance of existing LMS

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Publication Date
Wed Sep 01 2021
Journal Name
Iraqi Journal Of Physics
Theoretical Calculations of the Cross-sections for (n,α) and (n,xα) reactions on the Structural Material for Fusion Reactor 46-50Ti
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The biggest problem of structural materials for fusion reactor is the damage caused by the fusion product neutrons to the structural material. If this problem is overcomed, an important milestone will be left behind in fusion energy. One of the important problems of the structural material is that nuclei forming the structural material interacting with fusion neutrons are transmuted to stable or radioactive nuclei via (n, x) (x; alpha, proton, gamma etc.) reactions. In particular, the concentration of helium gas in the structural material increases through deuteron- tritium (D-T) and (n, α) reactions, and this increase significantly changes the microstructure and the properties of the structural materials. T

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Publication Date
Wed Sep 23 2020
Journal Name
Artificial Intelligence Research
Hybrid approaches to feature subset selection for data classification in high-dimensional feature space
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This paper proposes two hybrid feature subset selection approaches based on the combination (union or intersection) of both supervised and unsupervised filter approaches before using a wrapper, aiming to obtain low-dimensional features with high accuracy and interpretability and low time consumption. Experiments with the proposed hybrid approaches have been conducted on seven high-dimensional feature datasets. The classifiers adopted are support vector machine (SVM), linear discriminant analysis (LDA), and K-nearest neighbour (KNN). Experimental results have demonstrated the advantages and usefulness of the proposed methods in feature subset selection in high-dimensional space in terms of the number of selected features and time spe

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