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A Specific NH<sub>3</sub> Gas Sensor of a Thick MWCNTs-OH Network for Detection at Room Temperature
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NH3 gas sensor was fabricated based on deposited of Functionalized Multi-Walled Carbon Nanotubes (MWCNTs-OH) suspension on filter paper substrates using suspension filtration method. The structural, morphological and optical properties of the MWCNTs film were characterized by XRD, AFM and FTIR techniques. XRD measurement confirmed that the structure of MWCNTs is not affected by the preparation method. The AFM images reflected highly ordered network in the form of a mat. The functional groups and types of bonding have appeared in the FTIR spectra. The fingerprint (C-C stretch) of MWCNTs appears in 1365 cm-1, and the backbone of CNTs observed at 1645 cm-1. A homemade sensing device was used to evaluate the fabrication network toward NH3 gas at ppm levels as well as the response to sensitivity by changing the concentration. MWCNTs-OH network of 8mm thickness showed an increase in resistance upon exposure to the NH3 gas. The sensor exhibits a good sensitivity for low concentration of NH3 gas at room temperature. The sensitivities of the network were 2.5% at 14ppm, 5.3% at 27ppm and 17.6% at 68ppm. Further investigations showed that the network was specific sensitive to NH3 gas in the environment and not affected by the amount of ambient air.

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Publication Date
Wed Apr 02 2014
Journal Name
Journal Of Theoretical And Applied Information Technology
TUMOR BRAIN DETECTION THROUGH MR IMAGES: A REVIEW OF LITERATURE
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Today’s modern medical imaging research faces the challenge of detecting brain tumor through Magnetic Resonance Images (MRI). Normally, to produce images of soft tissue of human body, MRI images are used by experts. It is used for analysis of human organs to replace surgery. For brain tumor detection, image segmentation is required. For this purpose, the brain is partitioned into two distinct regions. This is considered to be one of the most important but difficult part of the process of detecting brain tumor. Hence, it is highly necessary that segmentation of the MRI images must be done accurately before asking the computer to do the exact diagnosis. Earlier, a variety of algorithms were developed for segmentation of MRI images by usin

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Publication Date
Sun Jun 27 2021
Journal Name
Iraqi National Journal Of Nursing Specialties
Detection of Depression among Nurses Providing Care for Patients with COVID-19 at Baqubah Teaching Hospital
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Objectives: The present study aims at detecting the depression among nurses who provide care for infected patients with corona virus phenomenon and to find out relationships between the depression and their demographic characteristics of age, gender, marital status, type of family, education, and years of experience of nurses in heath institutions, infection by corona virus, and their participation in training courses.
Methodology: A descriptive study is established for a period from October 10th, 2020 to April 15th, 2021. The study is conducted on a purposive (non-probability) sample of (100) nurse who are providing care for patients with COVID-19 and they are selected from the isolation wards. The instrument of the study is develope

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Publication Date
Wed May 25 2022
Journal Name
Iraqi Journal Of Science
Determination of Electrons Temperature and Density For Ag, Zn, and Cu metals using Plasma jet System at atmospheric pressure
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      Under atmospheric pressure, an argon plasma stream was sustained and its plasma characteristics were examined. The emission spectra of plasma created in a plasma jet system using argon gas were observed for three metals (Ag, Zn, and Cu) for the anode and varied flow rates ranging from 1–4 L/min. at constant voltage, and normal atmospheric pressure. The spectral lines of excited Ar, Ag, Zn, and Cu species were identified at a wavelength of (650–900) nm .The Debye length, sphere, and temperature of an electron are all measured. Optical emission spectrometer (OES) equipment was used to capture the spectrum produced by the plasma at various argon gas flow rates.The temperature and density of the electron (Te) and (n

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Publication Date
Thu Dec 19 2024
Journal Name
Ieee Explorer
A Novel Flow Priority and Continuity Control Mechanism in SDN Network
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In recent days, the escalating need to seamlessly transfer data traffic without discontinuities across the Internet network has exerted immense pressure on the capacity of these networks. Consequently, this surge in demand has resulted in the disruption of traffic flow continuity. Despite the emergence of intelligent networking technologies such as software-defined networking, network cloudification, and network function virtualization, they still need to improve their performance. Our proposal provides a novel solution to tackle traffic flow continuity by controlling the selected packet header bits (Differentiated Services Code Point (DSCP)) that govern the traffic flow priority. By setting the DSCP bits, we can determine the appropriate p

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Publication Date
Thu Sep 01 2016
Journal Name
2016 8th Computer Science And Electronic Engineering (ceec)
Class-specific pre-trained sparse autoencoders for learning effective features for document classification
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Publication Date
Fri Sep 30 2011
Journal Name
Al-khwarizmi Engineering Journal
Composition and Temperature Dependence of Excess Volume of Heavy Oil-Stocks Mixtures + (Gas oil or Toluene or Reformate)
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Binary mixtures of three, heavy oil-stocks was subjected to density measurements at temperatures of 30, 35 and 40 °C. and precise data was acquired on the volumetric behavior of these systems. The results are reported in terms of equations for excess specific volumes of mixtures. The heavy oil-stocks used were of good varity, namely 40 stock, 60 stock, and 150 stock. The lightest one is 40 stock with °API gravity 33.69 while 60 stock is a middle type and 150 stock is a heavy one, with °API gravity 27.74 and 23.79 respectively. Temperatures in the range of 30-40 °C have a minor effect on excess volume of heavy oil-stock binary mixture thus, insignificant expansion or shrinkage is observed by increasing the temperature this effect beco

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Publication Date
Tue Apr 30 2024
Journal Name
Iraqi Journal Of Science
Credit Card Fraud Detection Challenges and Solutions: A Review
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     Credit card fraud has become an increasing problem due to the growing reliance on electronic payment systems and technological advances that have improved fraud techniques. Numerous financial institutions are looking for the best ways to leverage technological advancements to provide better services to their end users, and researchers used various protection methods to provide security and privacy for credit cards. Therefore, it is necessary to identify the challenges and the proposed solutions to address them.  This review provides an overview of the most recent research on the detection of fraudulent credit card transactions to protect those transactions from tampering or improper use, which includes imbalance classes, c

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Publication Date
Fri Mar 23 2018
Journal Name
Entropy
Methods and Challenges in Shot Boundary Detection: A Review
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Publication Date
Tue Feb 28 2017
Journal Name
Journal Of Engineering
Non-Isothermal Crystallization Kinetics Model of PBT/ MWCNTs Nanocomposites
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The non-isothermal crystallization kinetics and crystalline properties of nanocomposites poly butyleneterephthalate, [PBT] /multiwalled-carbon nanotubes (MWCNTs) were tested by differential scanning calorimetry (DSC). PBT/(MWCNTs) nanocomposite was prepared by ultrasonicated of MWCNTs (0.5, 1, 2, 4 wt %) in dichloromethane (DCM) and after that the powdered PBT polymer was added to the MWCNTs solution. The non-isothermal crystallization results show that increasing the MWCNTs contents, decreased the melting temperature (Tm) of PBT/(MWCNTs) nanocomposite as compared with pure PBT, while resulting in improving the degree of crystallinity. These results indicated that a little amount of MWCNTs can be evident strong nucleating agent in PBT na

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Publication Date
Thu Mar 30 2023
Journal Name
Iraqi Journal Of Science
A Tri-Gene Ontology Migration Operator for Improving the Performance of Meta-heuristics in Complex Detection Problems
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      Detecting protein complexes in protein-protein interaction (PPI) networks is a challenging problem in computational biology. To uncover a PPI network into a complex structure, different meta-heuristic algorithms have been proposed in the literature. Unfortunately, many of such methods, including evolutionary algorithms (EAs), are based solely on the topological information of the network rather than on biological information. Despite the effectiveness of EAs over heuristic methods, more inherent biological properties of proteins are rarely investigated and exploited in these approaches. In this paper, we proposed an EA with a new mutation operator for complex detection problems. The proposed mutation operator is formulated und

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