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.
This research aims to find out the impact on the receptive style according to the specimen in the collection of material Brawner and retention as students at the Arabic Department at the Faculty of Education for Girls. For confirmation from the goal of the research, the researcher placed two hypotheses, one to two for collections and one for pods. - chosen as the College of Education for Girls / Department of Arabic language for the application of choice Intentionally search experience for reasons of researcher he is teaching them and thus ensures cooperation of teachers and students in them. - selected Division (b) of the fourth grade students of the Arabic language section at random to represent the experimental group, while the Division
... Show MoreTumor necrosis factor-alpha (TNF-α) antagonists’ therapy are expensive and has a non-responsive rate between 30% to 40% in rheumatoid arthritis patients. Genetic variation plays a vital role in the responsiveness to this type of therapy.The aim of this study is to investigate if the presence of genetic polymorphism in the TNF-α gene promoter region at locations -376 G/A (rs1800750), -806 C/T (rs4248158), and -1031 T/C (rs1799964) affects rheumatoid arthritis patient's tendency to be a non-responder to etanercept.
Eighty RA patients on etanercept (ETN) for at least six months were recruited from the Rheumatology Unit at Baghdad Teaching Hospital. Based on The European League Against Rheumatism response (EULAR) criteria, patient
... Show MoreWater pollution has created a critical threat to the environment. A lot of research has been done recently to use surface-enhanced Raman spectroscopy (SERS) to detect multiple pollutants in water. This study aims to use Ag colloid nanoflowers as liquid SERS enhancer. Tri sodium phosphate (Na3PO4) was investigated as a pollutant using liquid SERS based on colloidal Ag nanoflowers. The chemical method was used to synthesize nanoflowers from silver ions. Atomic Force Microscope (AFM), Scanning Electron Microscope (SEM), and X-ray diffractometer (XRD) were employed to characterize the silver nanoflowers. This nanoflowers SERS action in detecting Na3PO4 was reported and analyzed
... Show MoreWireless sensor networks (WSNs) are emerging in various application like military, area monitoring, health monitoring, industry monitoring and many more. The challenges of the successful WSN application are the energy consumption problem. since the small, portable batteries integrated into the sensor chips cannot be re-charged easily from an economical point of view. This work focusses on prolonging the network lifetime of WSNs by reducing and balancing energy consumption during routing process from hop number point of view. In this paper, performance simulation was done between two types of protocols LEACH that uses single hop path and MODLEACH that uses multi hop path by using Intel Care i3 CPU (2.13GHz) laptop with MATLAB (R2014a). Th
... Show MoreIn this work, a fiber-optic biomedical sensor was manufactured to detect hemoglobin percentages in the blood. SPR-based coreless optical fibers were developed and implemented using single and multiple optical fibers. It was also used to calculate refractive indices and concentrations of hemoglobin in blood samples. An optical fiber, with a thickness of 40 nanometers, was deposited on gold metal for the sensing area to increase the sensitivity of the sensor. The optical fiber used in this work has a diameter of 125μm, no core, and is made up of a pure silica glass rod and an acrylate coating. The length of the fiber was 4cm removed buffer and the splicing process was done. It is found in practice that when the sensitive refractive i
... Show MoreA new concrete rheometer is introduced including its innovation, actual design, working rules,
calibration, and reliability. A modified design of Tattersall two-point device is created. Some of
components are purchased from local and foreign markets, while other components and the
manufacturing process are locally fabricated. The matching viscosity method of determining the mixer
viscometer constants is demonstrated and followed to relate torque and rotational speed to yield stress
and viscosity (Bingham parameters). The calibration procedures and its calculation are explained.
Water is used as a Newtonian fluid, while; cement paste (cement + water) with w/c ratio equal to
(0.442) is used as a non-Newtonian fluid. Th
In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve
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