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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
Tue Feb 14 2023
Journal Name
Journal Of Educational And Psychological Researches
The Effectiveness of Teaching Practices of Science and Mathematics Teachers Based on the National Framework for Future Skills in the Omani School
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Abstract

The research aims to identify the level of effectiveness of the teaching practices of science and mathematics teachers in light of the national framework for future skills in Omani schools. To achieve the objectives of the study, the researchers used the descriptive approach, as he designed a note card consisting of (30) phrases distributed on three axes: basic skills, practical skills, and technical skills. After verifying the validity and reliability of the tools, they were applied to a sample of (116) teachers. The results of the research revealed that the level of effectiveness of the teaching practices of mathematics teachers has recorded a medium degree with a mean (3.05). The results a

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Publication Date
Wed Aug 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Compare to the conditional logistic regression models with fixed and mixed effects for longitudinal data
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Mixed-effects conditional logistic regression is evidently more effective in the study of qualitative differences in longitudinal pollution data as well as their implications on heterogeneous subgroups. This study seeks that conditional logistic regression is a robust evaluation method for environmental studies, thru the analysis of environment pollution as a function of oil production and environmental factors. Consequently, it has been established theoretically that the primary objective of model selection in this research is to identify the candidate model that is optimal for the conditional design. The candidate model should achieve generalizability, goodness-of-fit, parsimony and establish equilibrium between bias and variab

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Publication Date
Sun Dec 22 2024
Journal Name
Journal Of Petroleum Research And Studies
Optimizing Well Placement with Genetic Algorithms: A Case Study
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Maximizing the net present value (NPV) of oil field development is heavily dependent on optimizing well placement. The traditional approach entails the use of expert intuition to design well configurations and locations, followed by economic analysis and reservoir simulation to determine the most effective plan. However, this approach often proves inadequate due to the complexity and nonlinearity of reservoirs. In recent years, computational techniques have been developed to optimize well placement by defining decision variables (such as well coordinates), objective functions (such as NPV or cumulative oil production), and constraints. This paper presents a study on the use of genetic algorithms for well placement optimization, a ty

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Publication Date
Mon Jul 01 2024
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Serum CXCL 9 as a Potential Biomarker for Patients with Ulcerative Colitis
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Background: Ulcerative colitis (UC) is an inflammatory bowel disease restricted to the large intestine, characterized by superficial ulceration. It is a progressive and chronic disease requiring long-term treatment. Although its etiology remains unknown, it is suggested that environmental factors influence genetically susceptible individuals, leading to the onset of the disease. (C-X-C) ligand 9 is a chemokine that belongs to the CXC chemokine family, it plays a role in the differentiation of immune cells such as cytotoxic lymphocytes, natural killer T cells, and macrophages. Its interaction with its corresponding receptor CXCR3 which is expressed by a variety of cells such as effector T cells, CD8+ cytotoxic T cells, and macrophage

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Publication Date
Sun Jan 01 2017
Journal Name
International Journal Of Advanced Computer Science And Applications
Fast Hybrid String Matching Algorithm based on the Quick-Skip and Tuned Boyer-Moore Algorithms
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Publication Date
Sat Sep 01 2012
Journal Name
Journal Of Economics And Administrative Sciences
A comparison Of Some Semiparametric Estimators For consumption function Regression
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    This article aims to explore the importance of estimating the a semiparametric regression function ,where we suggest a new estimator beside the other combined estimators and then we make a comparison among them by using simulation technique . Through the simulation results we find  that the suggest estimator is the best with the first and second models ,wherealse for the third model we find Burman and Chaudhuri (B&C) is best.

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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
A New Hybrid Meta-Heuristics Algorithms to Solve APP Problems
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Abstract<p>In this paper, a new hybrid algorithm for linear programming model based on Aggregate production planning problems is proposed. The new hybrid algorithm of a simulated annealing (SA) and particle swarm optimization (PSO) algorithms. PSO algorithm employed for a good balance between exploration and exploitation in SA in order to be effective and efficient (speed and quality) for solving linear programming model. Finding results show that the proposed approach is achieving within a reasonable computational time comparing with PSO and SA algorithms.</p>
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Publication Date
Thu Feb 01 2024
Journal Name
International Journal Of Biological Macromolecules
A novel designed nanofibrous mat based on hydroxypropyl methyl cellulose incorporating mango peel extract for potential use in wound care system
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Publication Date
Thu Feb 24 2022
Journal Name
Journal Of Educational And Psychological Researches
The Effectiveness of a Rational Emotional Behavioral Program in Developing Self-Efficacy to Reduce the Burnout among Teachers of Students with Autism Disorder
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The aim of this study is to identify the effectiveness of a rational, emotional, behavioral program in developing self-efficacy to reduce the level of Burnout in 20 teachers of students with autism disorder in Jazan, Saudi Arabia. The proposed program included 12 training sessions. The researcher found that the proposed program has contributed significantly to the development of self-efficacy and reduce the level of Burnout for the targeted subject in this study.

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Publication Date
Wed Jan 01 2020
Journal Name
Cogent Engineering
On the computational aspects of Charlier polynomials
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