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.
Abstract\
In this research, estimated the reliability of water system network in Baghdad was done. to assess its performance during a specific period. a fault tree through static and dynamic gates was belt and these gates represent logical relationships between the main events in the network and analyzed using dynamic Bayesian networks . As it has been applied Dynamic Bayesian networks estimate reliability by translating dynamic fault tree to Dynamic Bayesian networks and reliability of the system appreciated. As was the potential for the expense of each phase of the network for each gate . Because there are two parts to the Dynamic Bayesian networks and two part of gate (AND), which includes the three basic units of the
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The current research aims to construct a scale for the nine types of students’ personality according to Rob Fitzel model. To do this, (162) items were formed that present the nine types of personality with (18) items for each type. To test the validity of the scale, a sample of (584) students of Al-Mustansrya University were chosen. The data of their responses was analyzed by using factor analysis. The findings explored (9) factors as one factor for each type of personality with (12) items for each one. Then, the reliability of the scale was found by using the test-retest method and Alfa Cronbach method.
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 MoreGlobal Navigation Satellite Systems (GNSS) have become an integral part of wide range of applications. One of these applications of GNSS is implementation of the cellular phone to locate the position of users and this technology has been employed in social media applications. Moreover, GNSS have been effectively employed in transportation, GIS, mobile satellite communications, and etc. On the other hand, the geomatics sciences use the GNSS for many practical and scientific applications such as surveying and mapping and monitoring, etc.
In this study, the GNSS raw data of ISER CORS, which is located in the North of Iraq, are processed and analyzed to build up coordinate time series for the purpose of detection the
... Show MoreThe detection for Single Escherichia Coli Bacteria has attracted great interest and in biology and physics applications. A nanostructured porous silicon (PS) is designed for rapid capture and detection of Escherichia coli bacteria inside the micropore. PS has attracted more attention due to its unique properties. Several works are concerning the properties of nanostructured porous silicon. In this study PS is fabricated by an electrochemical anodization process. The surface morphology of PS films has been studied by scanning electron microscope (SEM) and atomic force microscope (AFM). The structure of porous silicon was studied by energy-dispersive X-ray spectroscopy (EDX). Details of experimental methods and results are given and discussed
... Show MoreAmong the different passive techniques heat pipe heat exchanger (HPHE) seems to be the most effective one for energy saving in heating ventilation and air conditioning system (HVAC). The applications for nanofluids with high conductivity are favorable to increase the thermal performance in HPHE. Even though the nanofluid has the higher heat conduction coefficient that dispels more heat theoretically but the higher concentration will make clustering .Clustering is a problem that must be solved before nanofluids can be considered for long-term practical uses. Results showed that the maximum value of relative power is 0.13 mW at nanofluid compared with other concentrations due to the low density of nanofluid at this concentration. For highe
... Show MoreBotnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet
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