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.
This research Sheds highlights the procedural protections that must be enjoyed by the consumer in the face of the product, which is the protection of no less dangerous than the substantive protection of our obligations and duties delivered by the legislature upon the product of consumer interest, what is the benefit of the right if the access road to him complicated, so know The consumer has a right to the face of the product, but leaves the claim, either to ignorance For access to this right either to the difficulty of connecting to him.
That this research modest attempt we tried through which to focus on the way to the consumer behavior of arrived right, as we tried to highlight the weaknesses and the complexity of the procedure to
Density Functional Theory (DFT) calculations were carried out to study the thermal cracking for acenaphthylene molecule to estimate the bond energies for breaking C8b-C5a , C5a-C5 , C5-C4 , and C5-H5 bonds as well as the activation energies. It was found that for C8b-C5a , C5-C4 , and C5-H5 reactions it is often possible to identify one pathway for bond breakage through the singlet or triplet states. The atomic charges , dipole moment and nuclear – nuclear repulsion energy supported the breakage bond .Also, it was found that the activation energy value for C5-H5 bond breakage is lower than that required for C8b-C5a , C5a-C5 , C5-C4 bonds which refer to C5-H5 bond in acenaphthylene molecule are weaker than C8b-C5a , C5a-C5 , C5-C
... Show MoreToday, problems of spatial data integration have been further complicated by the rapid development in communication technologies and the increasing amount of available data sources on the World Wide Web. Thus, web-based geospatial data sources can be managed by different communities and the data themselves can vary in respect to quality, coverage, and purpose. Integrating such multiple geospatial datasets remains a challenge for geospatial data consumers. This paper concentrates on the integration of geometric and classification schemes for official data, such as Ordnance Survey (OS) national mapping data, with volunteered geographic information (VGI) data, such as the data derived from the OpenStreetMap (OSM) project. Useful descriptions o
... Show MoreSTAG proteins, which are part of the cohesin complex and encoded by the STAG genes, are known as Irr1/Scc3 in yeast and as SA/STAG/stromalin in mammals. There are more variants as there are alternate splice sites, maybe three open reading frames (ORFs) code for three main proteins, including: SA1 (STAG1), SA2 (STAG2) and SA3 (STAG3). The cohesin protein complex has various essential roles in eukaryotic cell biology. This study compared the expression of the STAG1 gene in four different breast cancer cell lines, including: MCF-7, T-47D, MDA-MB-468, and MDA-MB-231 and normal breast tissue. RNA was extracted from these cell lines and mRNA was converted to cDNA, and then expression of the STAG1 gene was quantified by three sets of specific prim
... Show MoreThe region-based association analysis has been proposed to capture the collective behavior of sets of variants by testing the association of each set instead of individual variants with the disease. Such an analysis typically involves a list of unphased multiple-locus genotypes with potentially sparse frequencies in cases and controls. To tackle the problem of the sparse distribution, a two-stage approach was proposed in literature: In the first stage, haplotypes are computationally inferred from genotypes, followed by a haplotype coclassification. In the second stage, the association analysis is performed on the inferred haplotype groups. If a haplotype is unevenly distributed between the case and control samples, this haplotype is labeled
... Show MoreThe present theoretical study analyzes the legacy of the Chicago School of Urban Sociology and evaluates it in the light of the growth and development of Chicago City and the establishment of sociology in it. Sociology has become an academic discipline recognized in the United States of America in the late nineteenth century, particularly, after the establishment of the first department of sociology in the University of Chicago in 1892. That was during the period of the rapid industrialization and sustainable growth of the Chicago City. The Chicago School relied on Chicago City in particular, as one of the American cities that grew and expanded rapidly in the first two decades of the twentieth century. At the end of the nineteenth centur
... Show MoreRecommender Systems are tools to understand the huge amount of data available in the internet world. Collaborative filtering (CF) is one of the most knowledge discovery methods used positively in recommendation system. Memory collaborative filtering emphasizes on using facts about present users to predict new things for the target user. Similarity measures are the core operations in collaborative filtering and the prediction accuracy is mostly dependent on similarity calculations. In this study, a combination of weighted parameters and traditional similarity measures are conducted to calculate relationship among users over Movie Lens data set rating matrix. The advantages and disadvantages of each measure are spotted. From the study, a n
... Show MoreIn this research، a comparison has been made between the robust estimators of (M) for the Cubic Smoothing Splines technique، to avoid the problem of abnormality in data or contamination of error، and the traditional estimation method of Cubic Smoothing Splines technique by using two criteria of differentiation which are (MADE، WASE) for different sample sizes and disparity levels to estimate the chronologically different coefficients functions for the balanced longitudinal data which are characterized by observations obtained through (n) from the independent subjects، each one of them is measured repeatedly by group of specific time points (m)،since the frequent measurements within the subjects are almost connected an
... Show MoreHand gestures are currently considered one of the most accurate ways to communicate in many applications, such as sign language, controlling robots, the virtual world, smart homes, and the field of video games. Several techniques are used to detect and classify hand gestures, for instance using gloves that contain several sensors or depending on computer vision. In this work, computer vision is utilized instead of using gloves to control the robot's movement. That is because gloves need complicated electrical connections that limit user mobility, sensors may be costly to replace, and gloves can spread skin illnesses between users. Based on computer vision, the MediaPipe (MP) method is used. This method is a modern method that is discover
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