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 influx of data in bioinformatics is primarily in the form of DNA, RNA, and protein sequences. This condition places a significant burden on scientists and computers. Some genomics studies depend on clustering techniques to group similarly expressed genes into one cluster. Clustering is a type of unsupervised learning that can be used to divide unknown cluster data into clusters. The k-means and fuzzy c-means (FCM) algorithms are examples of algorithms that can be used for clustering. Consequently, clustering is a common approach that divides an input space into several homogeneous zones; it can be achieved using a variety of algorithms. This study used three models to cluster a brain tumor dataset. The first model uses FCM, whic

Attacking a transferred data over a network is frequently happened millions time a day. To address this problem, a secure scheme is proposed which is securing a transferred data over a network. The proposed scheme uses two techniques to guarantee a secure transferring for a message. The message is encrypted as a first step, and then it is hided in a video cover.  The proposed encrypting technique is RC4 stream cipher algorithm in order to increase the message's confidentiality, as well as improving the least significant bit embedding algorithm (LSB) by adding an additional layer of security. The improvement of the LSB method comes by replacing the adopted sequential selection by a random selection manner of the frames and the pixels wit

Various activities taking place within the city of Baghdad have significantly contributed to organic pollution in Rivers Tigris and Diyala. The present study aimed to assess some physical, chemical and biological aspects of six sites on Rivers Tigris and Diyala as they flow through the city of Baghdad. Monthly samples were collected for the period January to December, 2005. Marked differences in the physical and chemical characteristics of water were noted between the two rivers’ sites. Average values during the study period of dissolved oxygen, biochemical oxygen demand, particulate organic matter, nitrate, phosphate and total dissolved solids for Tigris and Diyala were 7.8,4.7; 2.4,10.4; 350.1,921.4;7.8,13.9;1.2,4.8;814,2176 mg / l re

      Genus Eucalyptus belongs to the family Myrtaceae that consists of more than 700 species, various hybrids and varieties. The majorly distributed species that are grown in Iraq are Eucalyptus alba, E. macarthurii, E. siderophloia and E. camaldulensis, E. tereticornis, E. vicina. Most Eucalyptus species are highly dependent on rainfall, and this is challenged by climatic changes owing to global warming making it difficult to effectively match the availability of mature trees and the market demand, especially for use as power transmission poles. With the widespread availability of other naturally occurring Eucalyptus species, it has become important to determine the genetic diversity and to analyze the phenotypic tra

In this paper, introduce a proposed multi-level pseudo-random sequence generator (MLPN). Characterized by its flexibility in changing generated pseudo noise (PN) sequence according to a key between transmitter and receiver. Also, introduce derive of the mathematical model for the MLPN generator. This method is called multi-level because it uses more than PN sequence arranged as levels to generation the pseudo-random sequence. This work introduces a graphical method describe the data processing through MLPN generation. This MLPN sequence can be changed according to changing the key between transmitter and receiver. The MLPN provides different pseudo-random sequence lengths. This work provides the ability to implement MLPN practically

       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

This study deals with air pollution tolerance index (APTI) and anatomical variation in leaves of two species of terrestrial plants Ficus sp. and Conocarpus sp. that have bee commonly the separated along roadsides in many stations within Babylon province. APTI values of both species were less than 10 during study period which represented sensitivity of these plants to air pollution. There are Anatomical responses to pollution in the leaves of both studied species. Main adaptations included increased thickness of parenchyma cell walls with clear dark deposits in sections of Ficus sp. from sections of stations 2 and 4 which represent polluted stations. Conocarpus sp. main adaptation included stomata increased in density and decreased in size w

Seasonal variations of the species composition and abundance of Cladocera were studied in two stations at the end of the Tigris River and one station at the confluence of the Tigris with Euphrates area, at the beginning of the Shatt Al-Arab River in Al-Qurnah North of Basrah Province, from October 2015 to August 2016. Samples of zooplankton were collected by plankton net 100-µm. mesh size. The population density of Cladocera ranged between 1 Ind /m³ during summer and 211 Ind./m³ during winter at station 1 (Al-Jewaber Bridge). A total of 16 species of Cladocera belonging to 12 genera were recorded in the study. The average density of Cladocera ranged from 23.2 ind./m³ at Station 2 (Hamayon Bridge) to 53.7 Ind./m³

Aim: The aim of this study was to investigate babesiosis in dogs of different breeds and ages and of both sexes in Baghdad Province by molecular detection of Babesia canis using conventional polymerase chain reaction (PCR) and sequencing followed by phylogenetic analyses. Materials and Methods: Blood samples were collected from 310 dogs of different ages and breeds, and of both sexes in different areas of Baghdad Province from December 2018 to September 2019; during clinical examinations, body temperature, pulse, respiratory rate, and signs of diseases were recorded. PCR was used to amplify a specific 450-bp fragment of the 18S rRNA gene of B. canis. PCR products were sequenced, and MEGA 6.0 software was used for analysis. Chi-squar