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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 Mar 16 2022
Journal Name
International Journal Of Recent Contributions From Engineering, Science & It
Smart Learning based on Moodle E-learning Platform and Digital Skills for University Students
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Publication Date
Mon Oct 02 2023
Journal Name
Journal Of Engineering
Microgrid Integration Based on Deep Learning NARMA-L2 Controller for Maximum Power Point Tracking
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This paper presents a hybrid energy resources (HER) system consisting of solar PV, storage, and utility grid. It is a challenge in real time to extract maximum power point (MPP) from the PV solar under variations of the irradiance strength.  This work addresses challenges in identifying global MPP, dynamic algorithm behavior, tracking speed, adaptability to changing conditions, and accuracy. Shallow Neural Networks using the deep learning NARMA-L2 controller have been proposed. It is modeled to predict the reference voltage under different irradiance. The dynamic PV solar and nonlinearity have been trained to track the maximum power drawn from the PV solar systems in real time.

Moreover, the proposed controller i

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Publication Date
Fri Dec 01 2023
Journal Name
Iraqi Journal Of Physics
Gas Sensor for Hazardous Nitrogen Dioxide Based on TiO2 Nanotube Synthesis via Electrochemical Method
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Because of the quick growth of electrical instruments used in noxious gas detection, the importance of gas sensors has increased. X-ray diffraction (XRD) can be used to examine the crystal phase structure of sensing materials, which affects the properties of gas sensing. This contributes to the study of the effect of electrochemical synthesis of titanium dioxide (TiO2) materials with various crystal phase shapes, such as rutile TiO2 (R-TiO2NTs) and anatase TiO2 (A-TiO2NTs). In this work, we have studied the effect of voltage on preparing TiO2 nanotube arrays via the anodization technique for gas sensor applications. The results acquired from XRD, energy dispersion spectro

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Publication Date
Fri Dec 01 2023
Journal Name
Iraqi Journal Of Physics
Gas Sensor for Hazardous Nitrogen Dioxide Based on TiO2 Nanotube Synthesis via Electrochemical Method
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Because of the quick growth of electrical instruments used in noxious gas detection, the importance of gas sensors has increased. X-ray diffraction (XRD) can be used to examine the crystal phase structure of sensing materials, which affects the properties of gas sensing. This contributes to the study of the effect of electrochemical synthesis of titanium dioxide (TiO2) materials with various crystal phase shapes, such as rutile TiO2 (R-TiO2NTs) and anatase TiO2 (A-TiO2NTs). In this work, we have studied the effect of voltage on preparing TiO2 nanotube arrays via the anodization technique for gas sensor applications. The results acquired from XRD, energy dispersion spectroscopy (EDX), and field emission scanning electron microscopy

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Publication Date
Thu Feb 09 2023
Journal Name
Artificial Intelligence Review
Community detection model for dynamic networks based on hidden Markov model and evolutionary algorithm
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Finding communities of connected individuals in complex networks is challenging, yet crucial for understanding different real-world societies and their interactions. Recently attention has turned to discover the dynamics of such communities. However, detecting accurate community structures that evolve over time adds additional challenges. Almost all the state-of-the-art algorithms are designed based on seemingly the same principle while treating the problem as a coupled optimization model to simultaneously identify community structures and their evolution over time. Unlike all these studies, the current work aims to individually consider this three measures, i.e. intra-community score, inter-community score, and evolution of community over

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Publication Date
Fri Jan 01 2016
Journal Name
Modern Applied Science
Hybrid Methodology for Image Segmentation Based on Active Contour Module and Alpha-Shape Theory
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The concept of the active contour model has been extensively utilized in the segmentation and analysis of images. This technology has been effectively employed in identifying the contours in object recognition, computer graphics and vision, biomedical processing of images that is normal images or medical images such as Magnetic Resonance Images (MRI), X-rays, plus Ultrasound imaging. Three colleagues, Kass, Witkin and Terzopoulos developed this energy, lessening “Active Contour Models” (equally identified as Snake) back in 1987. Being curved in nature, snakes are characterized in an image field and are capable of being set in motion by external and internal forces within image data and the curve itself in that order. The present s

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Publication Date
Fri Oct 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Accounting measurement of intangible assets (websites) within the framework of international financial reporting standards An applied study between a sample of Iraqi commercial banks)
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The websites over time have become one of the important tools for communication between individuals among themselves and between individuals and economic units, and they have emerged as one of the important intangible assets to achieve income, as they have become a competitive tool and a marketing outlet for these units and a main means of communication that it uses to exercise its various major activities and achieve potential economic benefits. Therefore, there was a need to measure and display the value of these sites in the financial statements as intangible assets.  Accordingly, the purpose of the research was to determine the costs of the websites owned by the economic unit by way purchase and sites that were created i

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Publication Date
Tue Dec 30 2008
Journal Name
Al-kindy College Medical Journal
Evaluation of the Potential Role of Serum Selenium in Diabetic Patients
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Background: The altered status of some essential trace elements observed in diabetes could have deleterious influences on the health of the diabetics. Objectives: To estimate and study the potential role of serum Selenium in type 1, type 2 diabetics and healthy subjects; and its relation with lipid profile and glycemic index. Methods: A case control designed study was carried out at the National Diabetes Center (NDC) / Al-Mustansiria University; on a total of 94 participants formed of 32 type 1 diabetics, 32 type 2 diabetics and 30 healthy control participants. Data collected about age, sex and BMI; also, blood samples examined for FPG, HbA1C, serum total cholesterol, HDL cholesterol, non-HDL cholesterol, serum triglyceride and sera were

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Publication Date
Wed Aug 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Comparison Some Estimation Methods Of GM(1,1) Model With Missing Data and Practical Application
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This paper presents a grey model GM(1,1) of the first rank and a variable one and is the basis of the grey system theory , This research dealt  properties of grey model and a set of methods to estimate parameters of the grey model GM(1,1)  is the least square Method (LS) , weighted least square method (WLS), total least square method (TLS) and gradient descent method  (DS). These methods were compared based on two types of standards: Mean square error (MSE), mean absolute percentage error (MAPE), and after comparison using simulation the best method was applied to real data represented by the rate of consumption of the two types of oils a Heavy fuel (HFO) and diesel fuel (D.O) and has been applied several tests to

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Publication Date
Tue Jun 01 2021
Journal Name
Baghdad Science Journal
Experimental and Theoretical Study of Neomycin Sulfate as Corrosion Protection for Titanium in Acid Media
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        The experimental and theoretical methods were studied for inhibition of the corrosion titanium in HCl by using neomycin sulfate drug. The results of neomycin sulfate drug had good corrosion protection for titanium in hydrochloric acid and the inhibition efficiency (%IE) increasing with increasing concentration of drug because the neomycin sulfate drug had adsorption from acid solution on surface of titanium metal. The program of hyperchem-8.07 was used for theoretical study of the drug by molecular mechanics and semi-empirical calculations. Quantum chemical was studied drug absorption and electron transferred from the drug to the Titanium metal, also inhibition potentials of drug attachment with the (LUMO-HOMO) energy gap,

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