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

These days, it is crucial to discern between different types of human behavior, and artificial intelligence techniques play a big part in that.  The characteristics of the feedforward artificial neural network (FANN) algorithm and the genetic algorithm have been combined to create an important working mechanism that aids in this field. The proposed system can be used for essential tasks in life, such as analysis, automation, control, recognition, and other tasks. Crossover and mutation are the two primary mechanisms used by the genetic algorithm in the proposed system to replace the back propagation process in ANN. While the feedforward artificial neural network technique is focused on input processing, this should be based on the proce

Impressed current cathodic protection controlled by computer gives the ideal solution to the changes in environmental factors and long term coating degradation. The protection potential distribution achieved and the current demand on the anode can be regulated to protection criteria, to achieve the effective protection for the system.

In this paper, cathodic protection problem of above ground steel storage tank was investigated by an impressed current of cathodic protection with controlled potential of electrical system to manage the variation in soil resistivity. Corrosion controller has been implemented for above ground tank in LabView where tank's bottom potential to soil was manipulated to the desired set poi

Steganography is a technique of concealing secret data within other quotidian files of the same or different types. Hiding data has been essential to digital information security. This work aims to design a stego method that can effectively hide a message inside the images of the video file.  In this work, a video steganography model has been proposed through training a model to hiding video (or images) within another video using convolutional neural networks (CNN). By using a CNN in this approach, two main goals can be achieved for any steganographic methods which are, increasing security (hardness to observed and broken by used steganalysis program), this was achieved in this work as the weights and architecture are randomized. Thus,

Cloud storage provides scalable and low cost resources featuring economies of scale based on cross-user architecture. As the amount of data outsourced grows explosively, data deduplication, a technique that eliminates data redundancy, becomes essential. The most important cloud service is data storage. In order to protect the privacy of data owner, data are stored in cloud in an encrypted form. However, encrypted data introduce new challenges for cloud data deduplication, which becomes crucial for data storage. Traditional deduplication schemes cannot work on encrypted data. Existing solutions of encrypted data deduplication suffer from security weakness. This paper proposes a combined compressive sensing and video deduplication to maximize

Solar photovoltaic (PV) system has emerged as one of the most promising technology to generate clean energy. In this work, the performance of monocrystalline silicon photovoltaic module is studied through observing the effect of necessary parameters: solar irradiation and ambient temperature. The single diode model with series resistors is selected to find the characterization of current-voltage (I-V) and power-voltage (P-V) curves by determining the values of five parameters ( ). This model shows a high accuracy in modeling the solar PV module under various weather conditions. The modeling is simulated via using MATLAB/Simulink software. The performance of the selected solar PV module is tested experimentally for differ