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.
A set of ten drug compounds containing an amino group in the structure were determined theoretically. The parameters were entered into a model to forecast the optimal values of practical (log P) medicinal molecules. The drugs were evaluated theoretically using different types of calculations which are AM1, PM3, and Hartree Fock at the basis set (HF/STO-3G). The Physico-chemical data like (entropy, total energy, Gibbs Free Energy,…etc were computed and played an important role in the predictions of the practical lipophilicity values. Besides, Eigenvalues named HOMO and LUMO were determined. Linearity was shown when correlated between the experimental data with the evaluated physical properties. The statistical analysis was used to analy
... Show MoreA theoretical study by using computer model is presented to study the energy characteristics of the vibrational – rotational levels as a function of the vibrational and rotational quantum number, respectively. The calculations were based on the basis of a multilevel model taking into account the non-equilibrium population of the rotational levels. The computational investigation has been performed to examine the vibrational-rotational characteristics of some hydrogen halides chemical laser molecules. This program takes into account the various molecules of chemical lasers such as, Hydrogen Fluoride (HF), Deuterium Fluoride (DF), Hydrogen Chloride (HCl), and Deuterium Chloride (DCl). The practical difficulties associated with this
... Show MoreThis paper presents comprehensive analysis and investigation for 1550nm and 1310nm ring optical modulators employing an electro-optic polymer infiltrated silicon-plasmonic hybrid phase shifter. The paper falls into two parts which introduce a theoretical modeling framework and performance assessment of these advanced modulators, respectively. In this part, analytical expressions are derived to characterize the coupling effect in the hybrid phase shifter, transmission function of the modulator, and modulator performance parameters. The results can be used as a guideline to design compact and wideband optical modulators using plasmonic technology
The aerodynamic characteristics of the forward swept wing aircraft have been studied theoretically and experimentally. Low order panel method with the Dirichlet boundary condition have been used to solve the case of the steady, inviscid and compressible flow. Experimentally, a model was manufactured from wood to carry out the tests. The primary objective of the experimental work was the measurements of the wake dimensions and orientation, velocity defect along the wake and the wake thickness. A blower type low speed (open jet) wind tunnel was used in the experimental work. The mean velocity at the test section was (9.3 m/s) and the Reynolds number based on the mean aerodynamic chord and the mean velocity was (0.46x105). The measurements sho
... Show MoreThe information revolution، the new language has become one for all the peoples of the world through handling and exchange and to participate in all key areas (economic، cultural and scientific) and Accounting episode of this revolution has turned most of the traditional systems (manual) in companies to automated systems، this transformation in the regulations summoned from the auditors that develops their traditional examination automated systems so had to provide tools for auditing help auditors to keep abreast of developments and as a result there is no evidence checksum Local Private audited automated systems came search to provide evidence helps auditors for guidance as part of COBIT، which provides audit procedures Detailed inf
... Show MoreMany academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Deci
... Show MoreMany academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Tre
... Show MoreAdministrative procedures in various organizations produce numerous crucial records and data. These
records and data are also used in other processes like customer relationship management and accounting
operations.It is incredibly challenging to use and extract valuable and meaningful information from these data
and records because they are frequently enormous and continuously growing in size and complexity.Data
mining is the act of sorting through large data sets to find patterns and relationships that might aid in the data
analysis process of resolving business issues. Using data mining techniques, enterprises can forecast future
trends and make better business decisions.The Apriori algorithm has bee