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.
Surfaces quality is one of the most specified customer requirements for machine parts. The major indication of surfaces quality on machined parts is surface roughness. The research aim is to study the cutting conditions and their effects on the surface roughness. This paper utilizes regression models to predict surface roughness over the machining time for variety of cutting conditions in turning. In the experimental part for turning, different types of materials (Aluminum alloy, Copper alloy, and Gray cast iron) were considered with different cutting speed ( ) and feed rate ( ). A mathematical Model depending on statistical-mathematical method between surface roughness (Rz ) and cutting condition ( , ) were derived, for the three materials
... Show MoreThe consumption of fresh fruits has increased nowadays due to the lifestyle of the consumers. Maintaining the quality and nutritional value of cut fruits during storage is difficult compared to whole fruits. Deterioration of internal and external quality usually occurs in freshly harvested fruits. It is necessary to use different techniques to maintain the quality and increase the shelf life of the freshly cut product. This research studied the effect of treating apple slices with cold plasma once and with filtered water again on quality characteristics (hardness, moisture content, sugar content, carbohydrate content, and color) after being stored for five days. The best treatment was determined using two different pressures of the plasma j
... Show MoreNutrient enrichment of Sawa lake water was made using different nitrogen and phosphorus concentrations during autumn and spring at three stations. Different concentrations of nitrogen, phosphorus and N: P ratios were used to test variations in phytoplankton population dynamics. Nitrogen at a concentration of 25 µmole.l-1 and N: P ratio of 10:1 gave highest phytoplankton cell number at all stations and seasons. A total of 64 algal taxa dominated by Bacillariophyceae followed by Cyanophyceae and Chlorophyceae were identified. The values of Shannon index of diversity were more than one in the studied stations.
A mathematical method with a new algorithm with the aid of Matlab language is proposed to compute the linear equivalence (or the recursion length) of the pseudo-random key-stream periodic sequences using Fourier transform. The proposed method enables the computation of the linear equivalence to determine the degree of the complexity of any binary or real periodic sequences produced from linear or nonlinear key-stream generators. The procedure can be used with comparatively greater computational ease and efficiency. The results of this algorithm are compared with Berlekamp-Massey (BM) method and good results are obtained where the results of the Fourier transform are more accurate than those of (BM) method for computing the linear equivalenc
... Show MoreThe study aimed to prepare a measure of metacognitive thinking commensurate with learning the skill, preparing educational units using the Claus Meyer model for metacognitive thinking, and learning the skill of defending the court in volleyball. To identify the effect of educational units using the model (and Claus Meyer) for metacognitive thinking and learning the skill of defending the court in volleyball. The two researchers used the experimental approach with the design of the experimental and control groups.The research community consisted of students of the second stage / College of Physical Education and Sports Sciences / University of Baghdad for the academic year 2021-2022, whose number is (385) st
... Show MoreThe seasonal behavior of the light curve for selected star SS UMI and EXDRA during outburst cycle is studied. This behavior describes maximum temperature of outburst in dwarf nova. The raw data has been mathematically modeled by fitting Gaussian function based on the full width of the half maximum and the maximum value of the Gaussian. The results of this modeling describe the value of temperature of the dwarf novae star system leading to identify the type of elements that each dwarf nova consisted of.
Data centric techniques, like data aggregation via modified algorithm based on fuzzy clustering algorithm with voronoi diagram which is called modified Voronoi Fuzzy Clustering Algorithm (VFCA) is presented in this paper. In the modified algorithm, the sensed area divided into number of voronoi cells by applying voronoi diagram, these cells are clustered by a fuzzy C-means method (FCM) to reduce the transmission distance. Then an appropriate cluster head (CH) for each cluster is elected. Three parameters are used for this election process, the energy, distance between CH and its neighbor sensors and packet loss values. Furthermore, data aggregation is employed in each CH to reduce the amount of data transmission which le
... Show MoreThe Migration is one of the important dynamic population movement phenomena in population studies because of its great impact in changing many demographic characteristics between the region of origin and arrival. And the multiplicity of forms and types according to the different reasons for it and the motives that prompted the population to move, as well as the currents and their size are also different according to the different causes, and here there are many types of migration, and many of them have been studied at the local and regional levels, and as long as the population is in a continuous dynamic movement, other types of migration are generated. (Al Douri, 2015, 230) &nbs
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