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A novel data offloading scheme for QoS optimization in 5G based internet of medical things
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The internet of medical things (IoMT), which is expected the lead to the biggest technology in worldwide distribution. Using 5th generation (5G) transmission, market possibilities and hazards related to IoMT are improved and detected. This framework describes a strategy for proactively addressing worries and offering a forum to promote development, alter attitudes and maintain people's confidence in the broader healthcare system without compromising security. It is combined with a data offloading system to speed up the transmission of medical data and improved the quality of service (QoS). As a result of this development, we suggested the enriched energy efficient fuzzy (EEEF) data offloading technique to enhance the delivery of data transmission at the original targeted location. Initially, healthcare data was collected. Preprocessing is achieved by the normalization method. An EEEF data offloading scheme is proposed. A fruit fly optimization (FFO) technique is utilized. The performance metrics such as energy consumption, delay, resource utilization, scalability, and packet loss are analyzed and compared with existing techniques. The future scope will make use of a revolutionary optimization approach for IoMT.

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Publication Date
Tue Sep 11 2018
Journal Name
Iraqi Journal Of Physics
Estimation of kidney tumor volume in CT images using medical image segmentation techniques
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Kidney tumors are of different types having different characteristics and also remain challenging in the field of biomedicine. It becomes very important to detect the tumor and classify it at the early stage so that appropriate treatment can be planned. Accurate estimation of kidney tumor volume is essential for clinical diagnoses and therapeutic decisions related to renal diseases. The main objective of this research is to use the Computer-Aided Diagnosis (CAD) algorithms to help the early detection of kidney tumors that addresses the challenges of accurate kidney tumor volume estimation caused by extensive variations in kidney shape, size and orientation across subjects.
In this paper, have tried to implement an automated segmentati

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Publication Date
Thu Jul 01 2021
Journal Name
Chemical Methodologies
Novel Synthesis of Some N-Hydroxy Phthalimide Derivatives with Investigation of Its Corrosion Inhibition for Carbon Steel in HCl Solution
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In the current study, new derivatives were synthesized by reaction of N-hydroxyphthalimide with chloro acetyl chloride in the presence of Et3N as a base to form 1,3-dioxoisoindolin-2-yl 2-chloroacetate (B1), which in turn enters several reactions with different amines where it interacts with primary amines to give 1,3-dioxoisoindolin-2-yl acetate derivatives (B2-B4) in basic medium, in the same way it interacts with these amines but with adding KNCS to form thiourea derivatives (B5-B7). It also reacts with diamines to give bis(azanediyl) derivatives (compounds B8-B10). The prepared derivatives were diagnosed using infrared FTIR and 1HNMR,13CNMR for some derivatives. Compounds B4, B5 and B9 were measured as corrosion inhibitors the inhibitio

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Publication Date
Sun Dec 30 2018
Journal Name
Journal Of Pure And Applied Microbiology (jpam)
Optimization Kerosene Bio-degradation by a Local Soil Bacterium Isolate Klebsiella pneumoniae Sp. pneumonia
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Isolated Bacteria from the roots of barley were studied; two stages of processes Isolated and screening were applied in order to find the best bacteria to remove kerosene from soil. The active bacteria are isolated for kerosene degradation process. It has been found that Klebsiella pneumoniae sp. have the highest kerosene degradation which is 88.5%. The optimum conditions of kerosene degradation by Klebsiella pneumonia sp. are pH5, 48hr incubation period, 35°C temperature and 10000ppm the best kerosene concentration. The results 10000ppm showed that the maximum kerosene degradation can reach 99.58% after 48 h of incubation. Higher Kerosene degradation which was 99.83% was obtained at pH5. Kerosene degradation was found to be maximum at 3

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Publication Date
Sun Dec 30 2018
Journal Name
Journal Of Pure And Applied Microbiology
Optimization Kerosene Bio-degradation by a Local Soil Bacterium Isolate Klebsiella pneumoniae Sp. pneumonia
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Isolated Bacteria from the roots of barley were studied; two stages of processes Isolated and screening were applied in order to nd the best bacteria to remove kerosene from soil. The acve bacteria are isolated for kerosene degradaon process. It has been found that Klebsiella pneumoniae sp. have the highest kerosene degradaon which is 88.5%. The opmum condions of kerosene degradaon by Klebsiella pneumonia sp. are pH5, 48hr incubaon period, 35°C temperature and 10000ppm the best kerosene concentraon. The results 10000ppm showed that the maximum kerosene degradaon can reach 99.58% aer 48 h of incubaon. Higher Kerosene degradaon which was 99.83% was obtained at pH5. Kerosene degradaon was found

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Publication Date
Fri Jan 01 2010
Journal Name
Conference Proceedings
Assessing the accuracy of 'crowdsourced' data and its integration with official spatial data sets
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Scopus
Publication Date
Tue Sep 01 2020
Journal Name
Clinical Plasma Medicine
Breast cancer treatment using cold atmospheric plasma generated by the FE-DBD scheme
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Background Cold atmospheric plasma (CAP) is widely used in the cancer therapy field. This type of plasma is very close to room temperature. This paper illustrates the effects of CAP on breast cancer tissues both in vivo and in vitro. Methods The mouse mammary adenocarcinoma cell line AN3 was used for the in vivo study, and the MCF7, AMJ13, AMN3, and HBL cell lines were used for the in vitro study. A floating electrode-dielectric barrier discharge (FE-DBD) system was used. The cold plasma produced by the device was tested against breast cancer cells. Results The induced cytotoxicity percentages were 61.7%, 68% and 58.07% for the MCF7, AMN3, and AMJ13 cell lines, respectively, whereas the normal breast tissue HBL cell line exhibited very li

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Publication Date
Sat Oct 01 2022
Journal Name
Journal Of Computational Science
Novel approximate solution for fractional differential equations by the optimal variational iteration method
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Publication Date
Sat Oct 01 2022
Journal Name
Journal Of Computational Science
Novel approximate solution for fractional differential equations by the optimal variational iteration method
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Publication Date
Tue Aug 22 2023
Journal Name
Microbial Science Archives
Unveiling Westiellopsis akinetica: a novel species in the Iraqi habitat, and contrasting its distinctive attributes with Westiellopsis prolifica
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This is the first record of a new species of cyanobacteria Westiellopsis akinetica in the Iraqi environment, Samples were collected on June 2013 and the existence of it was not documented before. We isolated and purified this species ten years ago in Iraq, but we couldn't identify accurately based on all taxonomic handbooks. This is due to the species features being different from the other documented species in the available taxonomic lectures. It resembled many species by morphological characteristics such as Fischerella muscicola, Fischerella thermalis, Westiellopsis biateralis SA16. Westiellopsis interrupta, Westiellopsis persica SA33, Westiellopsis prolifica and Symphyonema bifilamentata. Describing a new species of the Westiellops

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Publication Date
Wed Feb 06 2013
Journal Name
Eng. & Tech. Journal
A proposal to detect computer worms (malicious codes) using data mining classification algorithms
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Malicious software (malware) performs a malicious function that compromising a computer system’s security. Many methods have been developed to improve the security of the computer system resources, among them the use of firewall, encryption, and Intrusion Detection System (IDS). IDS can detect newly unrecognized attack attempt and raising an early alarm to inform the system about this suspicious intrusion attempt. This paper proposed a hybrid IDS for detection intrusion, especially malware, with considering network packet and host features. The hybrid IDS designed using Data Mining (DM) classification methods that for its ability to detect new, previously unseen intrusions accurately and automatically. It uses both anomaly and misuse dete

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