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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
Thu Aug 17 2017
Journal Name
Journal Of Health, Medicine And Nursing
Adherence to Guidelines of Secondary Prevention in patients with Ischemic Heart Disease in a Tertiary Cardiac Center
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Coronary heart disease (CHD) is the leading cause of death in United State (U.S.). Controlling of modifiable risk factors such as smoking, hypertension (HT), diabetes mellitus (D.M.), dyslipidemia, physical inactivity & obesity will prevent other serious cardiovascular complications

Publication Date
Tue Jun 28 2022
Journal Name
Research Journal Of Pharmacy And Technology
A Case-control Study to Determine Metalloproteinase-12 and Lysyl Oxidase Levels in Iraqi women with Osteoporosis
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The current study aimed to ascertain the levels of matrix metalloproteinase-12 (MMP-12) and Lysyl oxidase (LOX) in osteoporosis patients and their correlation with alkaline phosphatase (ALP), magnesium (Mg), vitamin D (Vit D), calcium (Ca), phosphorus (P), and T-score %. 110 participants recruited from Baghdad Teaching Hospital, Iraq, were enrolled in this study from November 2019 to March 2020). The participants were divided into two groups: Group 1 comprised 60 osteoporotic women and group 2 consisted of 50 healthy women. (MMP and LOX) were estimated using a quantitative enzyme-linked immunosorbent assay (ELISA. The results showed significant differences in serum LOX, age, ALP, Mg, and T-score %, while no significant differences i

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Publication Date
Tue Dec 01 2020
Journal Name
Baghdad Science Journal
A Modified Support Vector Machine Classifiers Using Stochastic Gradient Descent with Application to Leukemia Cancer Type Dataset
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Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca

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Publication Date
Fri Apr 03 2026
Journal Name
Journal Of Electrochemical Science And Engineering
Synergistic effects of NH<sub>2</sub>-MIL-101(Fe) metal-organic framework and Pd nanoparticles for sensitive determination of norepine­phrine in the presence of acetaminophen
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An electrochemical sensor based on an amino-functionalized iron NH2-MIL-101(Fe) metal-organic framework (MOF)/Pd nanoparticles (NPs) composite-modified screen-printed elec­trode (SPE) is prepared for the simultaneous determination of norepinephrine (NEPI) and acetaminophen (ACP). The NH2-MIL-101(Fe) MOF/Pd NPs/SPE electrochemical sensor shows a significant enhancement in the response peak current of NEPI, as compared to bare SPE. This suggests that the unique features of NH2-MIL-101(Fe) MOF/Pd NPs composite-mo­di­fied SPE improve the electro­catalytic oxidation of NEPI. Such a synergistic effect bet­ween NH2-MIL-101(Fe) MOF and Pd NPs results in a significant enhancement in the res­pon­se, where the MOF's high surface area co

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Publication Date
Sun Apr 24 2022
Journal Name
Egyptian Journal Of Chemistry
A novel Tubular Electrochemical Reactor with a Spiral Design of Anode for Treatment of Petroleum Refinery Wastewater
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Publication Date
Sun Jan 01 2017
Journal Name
Biochemical And Cellular Archives
Response of red cabbage to the adding wheat peatand spraying with its extract and organic nutrient vegeamino on qualitative characteristics of heads
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Publication Date
Wed Aug 31 2022
Journal Name
Al-kindy College Medical Journal
A Spotlight on the Experience of E-learning as a Learning Method for the Undergraduate Pediatric Nursing Students in Iraq during the COVID-19 Pandemic
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    The emergence of COVID-19 has resulted in an unprecedented escalation in different aspects of human activities, including medical education. Students and educators across academic institutions have confronted various challenges in following the guidelines of protection against the disease on one hand and accomplishing learning curricula on the other hand. In this short view, we presented our experience in implementing e-learning to the undergraduate nursing students during the present COVID-19 pandemic emphasizing the learning content, barriers, and feedback of students and educators. We hope that this view will trigger the preparedness of nursing faculties in Iraq to deal with this new modality of learning and improve it should t

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Publication Date
Fri Oct 01 2021
Journal Name
International Journal Of Mechanical Engineering And Robotics Research
Proportional-Derivative PD Vibration Control with Adaptive Approximation Compensator for a Nonlinear Smart Thin Beam Interacting with Fluid
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This work is concerned with the vibration attenuation of a smart beam interacting with fluid using proportional-derivative PD control and adaptive approximation compensator AAC. The role of the AAC is to improve the PD performance by compensating for unmodelled dynamics using the concept of function approximation technique FAT. The key idea is to represent the unknown parameters using the weighting coefficient and basis function matrices/vectors. The weighting coefficient vector is updated using Lyapunov theory. This controller is applied to a flexible beam provided with surface bonded piezo-patches while the vibrating beam system is submerged in a fluid. Two main effects are considered: 1) axial stretching of the vibrating beam that leads

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Publication Date
Tue Feb 28 2023
Journal Name
Iraqi Geological Journal
Depositional Architecture and Stratigraphic Framework of Albian Succession in Balad and Nasiyia Oil Fields
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The Albian Carbonate-clastic succession in the present study is represented by the Mauddud and Nahr Umr formations were deposited during the Albian stage within the Wasia Group More than 200 thin sections of cores and cuttings in addition to well logs data for Nahr Umr and Mauddud formations from 4 boreholes within two oil fields (Ba-4, Ba-8, Ns-2 and Ns-4) were used to interpret the different associations facies as well as the facies architectures to describe the sedimentary framework of the basin and development the petrophysical properties. Seven major microfacies were diagnosed in the carbonate succession of the Mauddud Formation, while the Nar Umr Formation includes five lithofacies; their grain types characteristic and deposit

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Publication Date
Tue Jul 01 2025
Journal Name
Mastering The Minds Of Machines
The Intersection of AI and the Internet of Things (IoT): Transforming Data into Intelligence
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