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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
Fri Dec 31 2021
Journal Name
Political Sciences Journal
The Effect of the change of Energy Factor on the American-Russian Competition in Europe
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Receipt date:3/13/2021 accepted date:5/26/2021 Publication date:12/31/2021

Creative Commons License This work is licensed under a Creative Commons Attribution 4.0 International License.

energy is one of the strategic resources within international politics, and this is through the existing competition between the international powers on it, and the global powers have begun to rely on interest in new areas, such as import, depending on new projects an

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Publication Date
Sat Jan 01 2022
Journal Name
Materials Research Express
Thermochromic and opacity behaviors in vanadium dioxide nanofilms: a theoretical study
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Abstract<p>Vanadium dioxide nanofilms are one of the most essential materials in electronic applications like smart windows. Therefore, studying and understanding the optical properties of such films is crucial to modify the parameters that control these properties. To this end, this work focuses on investigating the opacity as a function of the energy directed at the nanofilms with different thicknesses (1–100) nm. Effective mediator theories (EMTs), which are considered as the application of Bruggeman’s formalism and the Looyenga mixing rule, have been used to estimate the dielectric constant of VO<sub>2</sub> nanofilms. The results show different opacity behaviors at different w</p> ... Show More
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Publication Date
Tue Jun 09 2015
Journal Name
Arab World English Journal (awej)
Investigating Socio-pragmatic Failure in Cross-cultural Translation: A Theoretical Perspective
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Pragmatics of translation is mainly concerned with how social contexts have their own influence on both the source text (ST) initiator's linguistic choices and the translator's interpretation of the meanings intended in the target text (TT). In translation, socio-pragmatic failure(SPF), as part of cross-cultural failure, generally refers to a translator's misuse or misunderstanding of the social conditions placed on language in use. In addition, this paper aims to illustrate the importance of SPF in cross-cultural translation via identifying that such kind of failure most likely leads to cross-cultural communication breakdown. Besides, this paper attempts to answer the question of whether translators from English into Arabic or vice versa h

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Publication Date
Sat Jan 01 2022
Journal Name
Materials Research Express
Thermochromic and opacity behaviors in vanadium dioxide nanofilms: a theoretical study
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Abstract<p>Vanadium dioxide nanofilms are one of the most essential materials in electronic applications like smart windows. Therefore, studying and understanding the optical properties of such films is crucial to modify the parameters that control these properties. To this end, this work focuses on investigating the opacity as a function of the energy directed at the nanofilms with different thicknesses (1–100) nm. Effective mediator theories (EMTs), which are considered as the application of Bruggeman’s formalism and the Looyenga mixing rule, have been used to estimate the dielectric constant of VO<sub>2</sub> nanofilms. The results show different opacity behaviors at different w</p> ... Show More
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Publication Date
Wed Apr 01 2015
Journal Name
Journal Of Economics And Administrative Sciences
Evaluation of Drinking Waters’ projects in accordance with the standard Malcolm Baldrige Award for Excellence in the framework of total quality management / applied research in Water Department of Baghdad
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The research aims to evaluate the selected projects from the water Department of Baghdad, according to a standard for total quality management and to achieve this goal , adopted the case study method to get to know how close or turn away those projects in the management of Standard Malcolm Baldrige Award for Excellence in Quality Management its comprehensive one scales the world's most famous in this area , in order to draw a general framework to evaluate how project management can benefit from this approach to modern management , input from the entrances of the comprehensive management reform and development.

Be standard Malcolm Baldrige Award of several elements: - leadership , strategic planning , foc

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Publication Date
Sat Aug 02 2025
Journal Name
Engineering, Technology &amp; Applied Science Research
A New Method for Face-Based Recognition Using a Fuzzy Face Deep Model
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Face recognition is a crucial biometric technology used in various security and identification applications. Ensuring accuracy and reliability in facial recognition systems requires robust feature extraction and secure processing methods. This study presents an accurate facial recognition model using a feature extraction approach within a cloud environment. First, the facial images undergo preprocessing, including grayscale conversion, histogram equalization, Viola-Jones face detection, and resizing. Then, features are extracted using a hybrid approach that combines Linear Discriminant Analysis (LDA) and Gray-Level Co-occurrence Matrix (GLCM). The extracted features are encrypted using the Data Encryption Standard (DES) for security

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Publication Date
Fri Mar 01 2024
Journal Name
Iaes International Journal Of Artificial Intelligence (ij-ai)
Analyzing the behavior of different classification algorithms in diabetes prediction
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<span lang="EN-US">Diabetes is one of the deadliest diseases in the world that can lead to stroke, blindness, organ failure, and amputation of lower limbs. Researches state that diabetes can be controlled if it is detected at an early stage. Scientists are becoming more interested in classification algorithms in diagnosing diseases. In this study, we have analyzed the performance of five classification algorithms namely naïve Bayes, support vector machine, multi layer perceptron artificial neural network, decision tree, and random forest using diabetes dataset that contains the information of 2000 female patients. Various metrics were applied in evaluating the performance of the classifiers such as precision, area under the c

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Publication Date
Thu Jun 20 2019
Journal Name
Baghdad Science Journal
An Analysis on the Applicability of Meta-Heuristic Searching Techniques for Automated Test Data Generation in Automatic Programming Assessment
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Automatic Programming Assessment (APA) has been gaining lots of attention among researchers mainly to support automated grading and marking of students’ programming assignments or exercises systematically. APA is commonly identified as a method that can enhance accuracy, efficiency and consistency as well as providing instant feedback on students’ programming solutions. In achieving APA, test data generation process is very important so as to perform a dynamic testing on students’ assignment. In software testing field, many researches that focus on test data generation have demonstrated the successful of adoption of Meta-Heuristic Search Techniques (MHST) so as to enhance the procedure of deriving adequate test data for efficient t

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Publication Date
Sun Jun 02 2013
Journal Name
Baghdad Science Journal
Computational Optimization of the Radial and Spiral Distortion Aberration Coefficients of Magnetic Deflector
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Abstract:The optimum design of the magnetic deflector with the lowest values of the radial and spiral distortion aberration coefficients was computed. The optimized calculations were made using three models, Glaser bell-shaped, Grivet-lenz and exponential models. By using the optimum axial field distribution, the pole pieces shape which gave rise to those field distributions was found by using the reconstruction method. The calculations show that the results of the three models coincide at the lower values of the excitation parameter. In general the Glaser- bell shaped model gives the optimum results at the whole range of the excitation parameter under investigation.The negative values of the spiral distortion aberration coefficient appears

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Publication Date
Thu Mar 01 2018
Journal Name
Composite Structures
Computational homogenization of the elastic and thermal properties of superconducting composite MgB2 wire
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