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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 Mar 31 2015
Journal Name
Al-khwarizmi Engineering Journal
Influence of Coating with Some Natural Based Materials on the Erosion Wear Behavior of Glass Fiber Reinforced Epoxy Resin
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Abstract 

In the present study, composites were prepared by Hand lay-up molding. The composites constituents were epoxy resin as a matrix, 6% volume fractions of glass fibers (G.F) as reinforcement and 3%, 6% volume fractions of preparation natural material (Rice Husk Ash, Carrot Powder, and Sawdust) as filler. Studied the erosion wear behavior and coating by natural wastes (Rice Husk Ash) with epoxy resin after erosion. The results showed the non – reinforced epoxy have lower resistance erosion than natural based material composites and the specimen (Epoxy+6%glass fiber+6%RHA) has higher resistance erosion than composites reinforced with carrot powder and sawdust  at 30cm , angle 60

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Publication Date
Sat Dec 30 2023
Journal Name
Traitement Du Signal
Optimizing Acoustic Feature Selection for Estimating Speaker Traits: A Novel Threshold-Based Approach
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Publication Date
Tue Apr 30 2024
Journal Name
Iraqi Journal Of Science
Topology-Based Modularity and Modularity Density for Detecting Protein Complexes: A Comparative Study
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     Binary relations or interactions among bio-entities, such as proteins, set up the essential part of any living biological system. Protein-protein interactions are usually structured in a graph data structure called "protein-protein interaction networks" (PPINs). Analysis of PPINs into complexes tries to lay out the significant knowledge needed to answer many unresolved questions, including how cells are organized and how proteins work. However, complex detection problems fall under the category of non-deterministic polynomial-time hard (NP-Hard) problems due to their computational complexity. To accommodate such combinatorial explosions, evolutionary algorithms (EAs) are proven effective alternatives to heuristics in solvin

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Publication Date
Thu Dec 01 2022
Journal Name
Journal Of Engineering
Deep Learning-Based Segmentation and Classification Techniques for Brain Tumor MRI: A Review
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Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

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Publication Date
Tue Aug 06 2013
Journal Name
Robotica
Function approximation technique-based adaptive virtual decomposition control for a serial-chain manipulator
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SUMMARY<p>The virtual decomposition control (VDC) is an efficient tool suitable to deal with the full-dynamics-based control problem of complex robots. However, the regressor-based adaptive control used by VDC to control every subsystem and to estimate the unknown parameters demands specific knowledge about the system physics. Therefore, in this paper, we focus on reorganizing the equation of the VDC for a serial chain manipulator using the adaptive function approximation technique (FAT) without needing specific system physics. The dynamic matrices of the dynamic equation of every subsystem (e.g. link and joint) are approximated by orthogonal functions due to the minimum approximation errors produced. The contr</p> ... Show More
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Publication Date
Fri Mar 25 2022
Journal Name
Asian Journal Of Biochemistry, Genetics And Molecular Biology
Evaluation of the Simple Sequence Repeats to Work as a Phase Variation with the Neisseria meningitidis Genome
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Background: The most crucial mechanism of genetic variation in N. meningitidis is the slipped strand mispairing, this mechanism generates Phase variation using simple sequence repeat (SSR) and is commonly used by the N. meningitidis to escape the immune system despite its function in eradicating the pathogenic and commensal bacteria. Some of simple sequence repeats (SSRs) that located within the genome works as phase variation while other SSRs have no role in generating phase variation mechanisms. Therefore, Aim: the main goal of the current in silico study was to detect the probability of SSR to enroll with phase variation for the entire N. meningitidis genome. Methods: Different criteria were used to judge SSR as

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Publication Date
Wed Mar 15 2023
Journal Name
Bionatura
Cytotoxic potential activity of quercetin derivatives on MCF-7 breast cancer cell line
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Many previous investigations have found quercetin to be a powerful antioxidant and antitumor flavonoid, but its poor bioavailability has limited its use. This current study investigated the effects of two newly synthesized Quercetin Schiff bases containing 2-amino thiadiazole-5-thiol (Q1), and its benzyl derivatives (Q2) on MCF-7 human breast cancer cells. Cell viability and apoptosis were assessed to determine the toxic effects of Q1 and Q2. Cytotoxicity valuation showed that both compounds inhibited MCF-7 cell growth, and lactate dehydrogenase (LDH) activity increased in a dose-dependent aspect compared to the control group. Comet assay results observed that Q1 and Q2 induce more serious DNA damage than the control (untreated cell

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Publication Date
Sat Sep 30 2023
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Audit of accounting disclosure for potential liabilities and contingent obligations In light of the Corona pandemic and its reflection on the auditor's opinion: Applied research in the National Insurance Company
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Abstract:

                The research aims to identify how to audit potential liabilities and contingent liabilities in light of the pandemic and its reflection on the auditor's report. The research problem is represented by the complexity of the process of checking potential liabilities and contingent liabilities in insurance companies, which was negatively reflected in the auditor's neutral technical opinion. The researchers hypothesize that auditing potential liabilities and contingent liabilities in light of the Corona pandemic is positively reflected in the auditor's report. The research concludes that the process of checking potential liabilities and contingent liabilities is

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Publication Date
Sat Jul 01 2023
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Audit of accounting disclosure for potential liabilities and contingent obligations In light of the Corona pandemic and its reflection on the auditor's opinion: . Applied research in the National Insurance Company
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                 Accounting disclosure is the main means and effective tool for communicating business results to users in support of their decisions, especially those with thought and specialization from academics and professionals in the field of accounting and auditing about the importance of accounting disclosure and transparency in financial reports.

Contingent liabilities represent commitments based on the occurrence of one or more events in the future to confirm the value due, the party entitled to it, the maturity date, or to confirm the existence of the obligation itself, and therefore they should not be recognized as a contingent liability i

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Publication Date
Thu Dec 01 2016
Journal Name
Journal Of Engineering
A Laboratory Study Attempt of Flow and Energy Dissipation in Stepped Spillways
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A new laboratory study conducted on stepped spillways in order to investigate their efficiency of dissipating flow energy. All previous study on stepped spillway indicated that the flow energy dissipation decreased as increasing in discharge. Increasing in the step numbers and the spillway slope led to energy dissipation decrease. In this study, an experimental attempt to increase energy dissipation at variable discharges was performed on stepped spillway and that leads to decreasing the cost of initiating the stilling basin or may be ignoring it. Five spillways were constructed from concrete and tested to investigate and compare among them. Three were roughed by gravel with different size for each one, one of them was s

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