In recent years, Wireless Sensor Networks (WSNs) are attracting more attention in many fields as they are extensively used in a wide range of applications, such as environment monitoring, the Internet of Things, industrial operation control, electric distribution, and the oil industry. One of the major concerns in these networks is the limited energy sources. Clustering and routing algorithms represent one of the critical issues that directly contribute to power consumption in WSNs. Therefore, optimization techniques and routing protocols for such networks have to be studied and developed. This paper focuses on the most recent studies and algorithms that handle energy-efficiency clustering and routing in WSNs. In addition, the prime issues in these networks are discussed and summarized using comparison tables, including the main features, limitations, and the kind of simulation toolbox. Energy efficiency is compared between some techniques and showed that according to clustering mode “Distributed” and CH distribution “Uniform”, HEED and EECS are best, while in the non-uniform clustering, both DDAR and THC are efficient. According to clustering mode “Centralized” and CH distribution “Uniform”, the LEACH-C protocol is more effective.
Commercial fish catch in the Iraqi marine waters from December 2018 to December 2019 was investigated. The study is based on three stations: the first station is located at the Shatt Al-Arab estuary, the second represents the area between the Shatt Al-Arab Estuary and open marine waters, and the third is associated with the Iraqi territorial marine waters. The total weight of the catch was 1881 kg, represented by 500, 654, and 727 kg in the first, second and third stations respectively. The third station was the highest with a majority of the family Sciaenidae by 464 kg, while the lowest was the family Scombridae by 0.5 kg. The total number of species included 37 species, belonging to 27 genera, 19 families, and 6 orders, the largest ord
... Show MoreColloidal silver nanoparticles were prepared by single step green synthesis using aqueous extracts of the leaves of thyme as a function of different molar concentration of AgNO3 (1,2,3,4 mM(. The Field Emission Scanning Electron Microscopy (FESEM), UV-Visible and X-ray diffraction (XRD) were used to characterize the resultant AgNPs. The surface Plasmon resonance was observed at wavelength of 444 nm. The four intensive peaks of XRD pattern indicate the crystalline nature and the face centered cubic structure of the AgNPs. The average crystallite size of the AgNPs ranged from 18 to 22 nm. The FESEM image illustrated the well dispersion of the AgNPs and the spherical shape of the nanoparticles with a particle size distribution be
... Show MoreThe characteristics of sulfur nanoparticles were studied by using atomic force microscope (AFM) analysis. The atomic force microscope (AFM) measurements showed that the average size of sulfur nanoparticles synthesized using thiosulfate sodium solution through the extract of cucurbita pepo extra was 93.62 nm. Protecting galvanized steel from corrosion in salt media was achieved by using sulfur nanoparticles in different temperatures. The obtained data of thermodynamic in the presence of sulfur nanoparticles referred to high value as compares to counterpart in the absence of sulfur nanoparticles, the high inhibition efficiency (%IE) and corrosion resistance were at high temperature, the corrosion rate or weig
... Show MoreBackground: This research describes the methodology used for the preparation of selenium nanoparticles from Pseudomonas aeruginosa and their administration to lambs for lipid profile checking, administration of selenium nanoparticles as a medication in lambs results in hypolipidemia. Aim: The study aimed to investigate the potential of selenium nanoparticles in improving lipid profiles in lambs. Methods: Healthy lambs (n=10) of similar age and weight were selected for the study. The animals were housed in individual pens with free access to water and a standard diet. The lambs were randomly divided into two groups: the control group (n=5) and the treatment group (n=5). The control group received a standard diet, while the treatme
... Show MoreThe Internet of Things (IoT) is an expanding domain that can revolutionize different industries. Nevertheless, security is among the multiple challenges that it encounters. A major threat in the IoT environment is spoofing attacks, a type of cyber threat in which malicious actors masquerade as legitimate entities. This research aims to develop an effective technique for detecting spoofing attacks for IoT security by utilizing feature-importance methods. The suggested methodology involves three stages: preprocessing, selection of important features, and classification. The feature importance determines the most significant characteristics that play a role in detecting spoofing attacks. This is achieved via two techniques: decision tr
... Show MoreThis work is licensed under a Creative Commons Attribution 4.0 International License. Abstract This study examines the working capital management