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 amo

     The earth's surface comprises different kinds of land cover, water resources, and soil, which create environmental factors for varied animals, plants, and humans. Knowing the significant effects of land cover is crucial for long-term development, climate change modeling, and preserving ecosystems. In this research, the Google Earth Engine platform and freely available Landsat imagery were used to investigate the impact of the expansion and degradation in urbanized areas, watersheds, and vegetative cover on the land surface temperature in Baghdad from 2004 to 2021. Land cover indices such as the Normalized Difference Vegetation Index, Normalized Difference Water Index, and Normalized Difference Built-up Index (NDVI, NDWI, an

Government expenditure represents one of the controlling financial policies in the economic affairs and management of the economic cycle in order to achieve price stability, raise the rate of output growth and decrease the level of unemployment. The price stability represents one of the macroeconomic goals that all countries seek without exception, regardless of the economic philosophy adopted by each country; in addition to this is raising the productive capacity and reaching the actual output to the level of the expected output, that is, the level of output related to the natural unemployment rate or what is sometimes called the Non-inflationary unemployment rate. The restriction of government expenditure (G=T+∆B/iP+∆M/P) is

The materials of soil were affected by multi reasons; such as human activities, floods, tidal waves, ... etc. The change of the soil contents could be measured through different indexes; such as electric conductivities, salinity, concentration of the heavy elements, and concentration of essential elements ... etc. The land cover is affected by natural influences, like tidal energy, which plays a negative role in the salinization of land adjacent to the coasts, causing a problem for soils in all its details represented in changing of the dissolved elements in soil. One of the most important natural factors that cause soil salinity is human activity in all its forms, and one of the most important causes of salinity is the phenomenon o

In this research, damping properties for composite materials were evaluated using logarithmic decrement method to study the effect of reinforcements on the damping ratio of the epoxy matrix. Three stages of composites were prepared in this research. The first stage included preparing binary blends of epoxy (EP) and different weight percentages of polysulfide rubber (PSR) (0%, 2.5%, 5%, 7.5% and 10%). It was found that the weight percentage 5% of polysulfide was the best percentage, which gives the best mechanical properties for the blend matrix. The advantage of this blend matrix is that; it mediates between the brittle properties of epoxy and the flexible properties of a blend matrix with the highest percentage of PSR. The second stage

This paper proposes two hybrid feature subset selection approaches based on the combination (union or intersection) of both supervised and unsupervised filter approaches before using a wrapper, aiming to obtain low-dimensional features with high accuracy and interpretability and low time consumption. Experiments with the proposed hybrid approaches have been conducted on seven high-dimensional feature datasets. The classifiers adopted are support vector machine (SVM), linear discriminant analysis (LDA), and K-nearest neighbour (KNN). Experimental results have demonstrated the advantages and usefulness of the proposed methods in feature subset selection in high-dimensional space in terms of the number of selected features and time spe

The nanocomposite on the base of synthesis Copper iodide
nanoparticles and polyvinyl alcohol (PVA/CuI) with different
concentration of CuI were obtained using casting technique.
PVA/CuI polymer composite samples have been prepared and
subjected to characterizations using FTIR spectroscopy, The FTIR
spectral analysis shows remarkable variation of the absorption peak
positions with increasing CuI concentration. The obtained results by
X-ray diffraction indicated the formation of cubic CuI particles. The
effects of CuI concentrations on the optical properties of the PVA
films were studied in the region of wavelength, (190-1100) nm.
From the derivation of Tauc's relation it was found that the direct
allowed t

The mechanical properties and microstructure of hot-rolled steel are critical in determining its performance in industrial applications, particularly when exposed to elevated temperatures. This study examines the effects of varying temperatures and soaking times on these properties through a series of controlled experiments. The primary objective was to optimize the key response parameters, including tensile strength, yield strength, and elongation, by analyzing the influence of temperature and time. A full factorial design approach was used, applying the desirability function theory to explore all possible combinations and identify optimal processing conditions. The experimental results showed that the soaking time played a critica