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

A simple setup of random number generator is proposed. The random number generation is based on the shot-noise fluctuations in a p-i-n photodiode. These fluctuations that are defined as shot noise are based on a stationary random process whose statistical properties reflect Poisson statistics associated with photon streams. It has its origin in the quantum nature of light and it is related to vacuum fluctuations. Two photodiodes were used and their shot noise fluctuations were subtracted. The difference was applied to a comparator to obtain the random sequence.

Polarization manipulation elements operating at visible wavelengths represent a critical component of quantum communication sub-systems, equivalent to their telecom wavelength counterparts. The method proposed involves rotating the optic axis of the polarized input light by an angle of 45 degree, thereby converting the fundamental transverse electric (TE0) mode to the fundamental transverse magnetic (TM0) mode. This paper outlines an integrated gallium phosphide-waveguide polarization rotator, which relies on the rotation of a horizontal slot by 45 degree at a wavelength of 700 nm. This will ultimately lead to the conception of a mode hybridization phenomenon in the waveguide. The simulation results demonstrate a polarization co

This paper develops a fuzzy multi-objective model for solving aggregate production planning problems that contain multiple products and multiple periods in uncertain environments. We seek to minimize total production cost and total labor cost. We adopted a new method that utilizes a Zimmermans approach to determine the tolerance and aspiration levels. The actual performance of an industrial company was used to prove the feasibility of the proposed model. The proposed model shows that the method is useful, generalizable, and can be applied to APP problems with other parameters.

Cassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has

Background: Consideration of mandibular third molar is important from orthodontic perspective due to several factors such as, lower anterior arch crowding, relapse in lower anterior region, interference with uprighting of mandibular first and second molars during anchorage preparation and molar distalization. The aims of this study were to assess of gender differences in the mandibular third molar position and compare and evaluate whether there is any differences in the results provided by CT scan and lateral reconstructed radiograph. Materials and Methods: The sample of present study consisted of 39 patients (18 males and 21 females) with age range 11-15 years. CT images for patients who were attending at Al Suwayra General Hospital/the C