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ESTIMATION OF MUNICIPAL SOLID WASTE GENERATION AND LANDFILL VOLUME GENERATION AND LANDFILL VOLUME USING ARTIFICIAL NEURAL NETWORKS
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Publication Date
Fri Aug 15 2025
Journal Name
Journal Port Science Research
The Antimicrobial Characteristics of Some Natural Remedies in Root Canal Disinfection and Artificial Intelligence (AI): A Review
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The primary goal of root canal treatment (RCT) is to expel the presence of any necrotic or vital tissue, microbes and their byproducts from the canal space before press forward with the following steps of the RCT procedures. Although this is difficult to attain, various strives had been practiced by employing chemical and mechanical methods to eliminate as much microorganisms as possible and make the canal space valid for the obturation materials to be received. The aim of this review is to demonstrate some of what new remedies that could be used as root canal disinfectant by summarizing the recent studies regarding the efficacy of different natural products against the most persistence microbiota that could be responsible for most

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Publication Date
Mon Jun 30 2025
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
USE OF SHRIMP WASTE POWDER (METAPENAEUS AFFINIS) AND PROTEASE ENZYME IN BROILERS FEED AND ITS EFFECT ON PHYSIOLOGICAL AND MICROBIAL CHARACTERISTICS AND INDICATORS OF FAT OXIDATION IN MEAT
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This study was conducted in the poultry field of the Department of Animal Production/ College of Agricultural Engineering Sciences / University of Baghdad for the period from 42 days. Aiming to know the effect of using shrimp waste powder (Metapenaeus Affinis) and enzyme in broilers diet on physiological and microbial performance and indicators of fat oxidation in meat. 250 one-day-old ROSS308 chicks were used. The chicks were fed on diets containing shrimp waste treated with enzyme and not treated with protease enzyme by 0,4,6 %. The experiment included five treatments, with 5 replicates for each treatment, and each replicate contained 10 birds. The results showed a significant decrease (P≤0.05) in the concentration of ALT and AS

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Publication Date
Sat Jan 01 2022
Journal Name
Iop Conference Series: Earth And Environmental Science
Some Properties of Concrete Containing Waste Brick As Partial Replacement Of Coarse Aggregate And Addition Of Nano Brick Powder
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Abstract<p>The accumulation of construction and demolition waste is one of the major problems in modern construction. Hence, this research investigates the use of waste brick in concrete. Seven different concrete mixes were investigated in this study: a control concrete mix, three mixes with volumetric replacement (10, 20, and 30)% of natural aggregate with brick aggregate, and two mixes with the addition of nano brick powder at a percentage level of 5– 10% by weight of cementitious materials. And the last one was mixed with 10% nano brick and 10% coarse brick aggregate. The experimental results for the additive of nano brick powder showed an enhancement in mechanical properties (compressive, </p> ... Show More
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Publication Date
Sun Mar 31 2024
Journal Name
Plant Science Today
Extraction of Synephrine from Waste Peels of Citrus sinensis and Green Synthesis of Gold Nanoparticles from it against Dermatophytes
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The main object of the current work was to determine the antifungal efficiency of secondary metabolites product called synephrine that extracted from Citrus sinesis peels and the ability of synephrine to biosynthesis gold nanoparticles from HAucl4 which consider environmentally favourable method, then determine their activity against pathogenic human dermatophyte. The identification of synephrine done by Thin layer chromatography (TLC), High Performance Liquid Chromatography (HPLC) and The Fourier Transform Infrared (FTIR). The characterization of gold nanoparticles by using Ultra Violet-Visible Spectroscopy (UV-Vis), Field – Emission Scanning Electron Microscopy (FESEM) and Fourier Transform Infrared (FTIR), confirmed the biosynt

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Publication Date
Mon Oct 01 2018
Journal Name
International Journal Of Electrical And Computer Engineering
Load balance in data center SDN networks
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In the last two decades, networks had been changed according to the rapid changing in its requirements. The current Data Center Networks have large number of hosts (tens or thousands) with special needs of bandwidth as the cloud network and the multimedia content computing is increased. The conventional Data Center Networks (DCNs) are highlighted by the increased number of users and bandwidth requirements which in turn have many implementation limitations. The current networking devices with its control and forwarding planes coupling result in network architectures are not suitable for dynamic computing and storage needs. Software Defined networking (SDN) is introduced to change this notion of traditional networks by decoupling control and

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Publication Date
Wed Apr 01 2009
Journal Name
2009 Ieee Wireless Communications And Networking Conference
Power Efficiency Maximization in Cognitive Radio Networks
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Cognitive radio technology is used to improve spectrum efficiency by having the cognitive radios act as secondary users to access primary frequency bands when they are not currently being used. In general conditions, cognitive secondary users are mobile nodes powered by battery and consuming power is one of the most important problem that facing cognitive networks; therefore, the power consumption is considered as a main constraint. In this paper, we study the performance of cognitive radio networks considering the sensing parameters as well as power constraint. The power constraint is integrated into the objective function named power efficiency which is a combination of the main system parameters of the cognitive network. We prove the exi

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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
6G Wireless Communications Networks: A Comprehensive Survey
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Publication Date
Mon Jun 05 2023
Journal Name
Journal Of Engineering
Removal of Cu2+, Pb2+ , And Ni 2+ Ions From Simulated Waste Water By Ion Exchange Method On Zeolite And Purolite C105 Resin
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The removal of heavy metal ions from wastewater by ion exchange resins ( zeolite and purolite C105), was investigated. The adsorption process, which is pH dependent, shows maximum removal of metal ions at pH 6 and 7 for zeolite and purolite C105 for initial metal ion
concentrations of 50-250 mg/l, with resin dose of 0.25-3 g. The maximum ion exchange capacity was found to be 9.74, 9.23 and 9.71 mg/g for Cu2+, Pb2+, and Ni2+ on zeolite respectively, while on purolite C105 the maximum ion exchange capacity was found to be 9.64 ,8.73 and 9.39 for Cu2+, Pb2+, and Ni2+ respectively. The maximum removal was 97-98% for Cu2+ and Ni2+ and 92- 93% for Pb2+ on zeolite, while it was 93-94% for Cu2+, 96-97% for Ni2+, and 87-88% for Pb2+ on puroli

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Publication Date
Wed Oct 15 2014
Journal Name
International Journal Of Advanced Research
A survey/ Development of Passive Optical Access Networks Technologies
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The bandwidth requirements of telecommunication network users increased rapidly during the last decades. Optical access technologies must provide the bandwidth demand for each user. The passive optical access networks (PONs) support a maximum data rate of 100 Gbps by using the Orthogonal Frequency Division Multiplexing (OFDM) technique in the optical access network. In this paper, the optical broadband access networks with many techniques from Time Division Multiplexing Passive Optical Networks (TDM PON) to Orthogonal Frequency Division Multiplex Passive Optical Networks (OFDM PON) are presented. The architectures, advantages, disadvantages, and main parameters of these optical access networks are discussed and reported which have many ad

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Early Diagnose Alzheimer's Disease by Convolution Neural Network-based Histogram Features Extracting and Canny Edge
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Alzheimer's disease (AD) increasingly affects the elderly and is a major killer of those 65 and over. Different deep-learning methods are used for automatic diagnosis, yet they have some limitations. Deep Learning is one of the modern methods that were used to detect and classify a medical image because of the ability of deep Learning to extract the features of images automatically. However, there are still limitations to using deep learning to accurately classify medical images because extracting the fine edges of medical images is sometimes considered difficult, and some distortion in the images. Therefore, this research aims to develop A Computer-Aided Brain Diagnosis (CABD) system that can tell if a brain scan exhibits indications of

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