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.
The current research aims to identify the time-management skills based on the post-test of the experimental group as well as to examine the effect of a training program on developing the skills of managing time among the study sample. To achieve the research objectives, the researcher designed a scale of time management skill included (30) paragraphs. The research reached that the training program is significantly effective in managing and organizing time. There are statistically significant differences in pre-posttest between the experimental and control groups.
The dynamical behavior of a two-dimensional continuous time dynamical system describing by a prey predator model is investigated. By means of constructing suitable Lyapunov functional, sufficient condition is derived for the global asymptotic stability of the positive equilibrium of the system. The Hopf bifurcation analysis is carried out. The numerical simulations are used to study the effect of periodic forcing in two different parameters. The results of simulations show that the model under the effects of periodic forcing in two different parameters, with or without phase difference, could exhibit chaotic dynamics for realistic and biologically feasible parametric values.
The flavonoglycone hesperidin is recognized as a potent anti-inflammatory, anticancer, and antioxidant agent. However, its poor bioavailability is a crucial bottleneck regarding its therapeutic activity. Gold nanoparticles are widely used in drug delivery because of its unique properties that differ from bulk metal. Hesperidin loaded gold nanoparticles were successfully prepared to enhance its stability and bioactive potential, as well as to minimize the problems associated with its absorption. The free radical scavenging activities of hesperidin, gold nanoparticles, and hesperidin loaded gold nanoparticles were compared with that of Vitamin C and subsequently evaluated in vitro using 2,2-diphenyl-1-picrylhydrazyl assay. The antioxi
... Show MoreThe DC electrical conductivity properties of Ge60Se40-xTex alloy with x = 0, 5, 10, 15 and 20). The samples were formed in the form of discs with the thickness of 0.25–0.30 cm and the diameter of 1.5 cm. Samples were pressed under a pressure of 6 tons per cm2 , using a ton hydraulic press. They were prepared after being pressed using a ton hydraulic press using a hydraulic press. Melting point technology use to preper the samples. Continuous electrical conductivity properties were recorded from room temperature to 475 K. Experimental data indicates that glass containing 15% Te has the highest electrical conductivity allowing maximum current through the sample compared to Lu with other samples. Therefore, it is found that the DC co
... Show MoreSpatial data analysis is performed in order to remove the skewness, a measure of the asymmetry of the probablitiy distribution. It also improve the normality, a key concept of statistics from the concept of normal distribution “bell shape”, of the properties like improving the normality porosity, permeability and saturation which can be are visualized by using histograms. Three steps of spatial analysis are involved here; exploratory data analysis, variogram analysis and finally distributing the properties by using geostatistical algorithms for the properties. Mishrif Formation (unit MB1) in Nasiriya Oil Field was chosen to analyze and model the data for the first eight wells. The field is an anticline structure with northwest- south
... Show MoreBackground: The cells of periodontium contain many intracellular enzymes like (alkaline phosphatase ALP) that are released outside into the saliva and gingival crevicular fluid (GCF) after destruction of periodontal tissue. The aim of study was to determine the activity of this enzyme in saliva and its relation to the salivary flow rate, PH and clinical periodontal parameters in patients with chronic periodontitis. Subject, Materials and methods: Sample population consist of 75 individuals ;divided into four groups , the first group (15):control subject, the second group (20):mild chronic periodontitis, the third group(20) moderate chronic periodontitis and the fourth group (20) sever chronic periodontitis, Measurements of plaque index (PL
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