IJOER: February 2020

Engineering Journal: published its volume-6, Issue-2, February 2020 with AD Publications

Study of Crystal Structure Profile Fitting of CuO for different Intensities of Gamma Radiation using Rietveld Refinement Method

Abstract The study of crystal structure profile fitting described by Hugo Rietveld named Rietveld Refinement became popular for profile fitting and microstructural analysis. The Rietveld method refines user-selected parameters to minimize the difference between an experimental parameter (observed data) and a model based on the hypothesized crystal structure and instrumental parameters (calculated data). In this paper, profile fitting of CuO has been discussed for different intensities of XRD data. Here Goodness of fitting is kept 1-2. For different dose the goodness of fitting changes.

Keywords— CuO, Powder diffraction, gamma radiation.

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Characterization of fine precipitates evolution in post ageing treatment after friction stir processed 7075Al Alloy

AbstractThe effect of post ageing treatment (140oC for 2h) on the microstructure and mechanical behaviour of FSPed 7075 Al alloy has been studied by Optical microscopy (OM), Field emission scanning electron microscopy (FESEM), Differential scanning calorimetry (DSC), Scanning electron microscopy (SEM), Transmission electron microscopy (TEM), and mechanical properties. Friction stir processing (FSP) is a solid-state surface modification technique to apply for cast aluminium alloys. FSP has a similar metal working principle like FSW (friction stir welding). The alloy has strong age-hardening response with scandium (Sc) inoculated Al-Zn-Mg alloy, on the other hand novelty of FSP only few studies have been carried out to the effect of post ageing treatment on the microstructure, size, morphology and fine dispersion of coherent Al3Sc(L12) type precipitates or ή-phases and its mechanical properties of friction stir processed 7075 Al alloy. The FSPed enhances grain boundary (GB) formation and increases suitable sites for the precipitation of nucleation in post aged 7075 Al alloy. Themechanical properties have been evaluated such as proof strength (σ0. 2) of 122. 9 MPa, ultimate tensile strength (σu) of 256. 4 MPa, ductility (δ) of 8. 6%, Vicker’s hardness in stir zone of 101 HV, strain hardening exponent (n) of 1. 82, and heat input during FSPed of 2. 15 kJ/mm, respectively.

KeywordsAl3Sc and ή precipitates, FSP, mechanical properties, post aged 7075 Al alloy, TEM.

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Naphtol Oligomers and their Electroconductive Compositions

Abstract By oxidative polycondensation reaction of 1- and 2-naphthols, the polyfunctional polyconjugated soluble and meltable oligomers showing the thermostable, semiconductive and paramagnetic properties, as well as high reactivity in the reactions characteristic for aromatic hydroxyl groups have been obtained.

They have been used as active fillers in preparation of electroconductive compositions on the basis of thermoplasts and rubbers. The antistatic polymer-oligomer compositions of LDPE, PP and PS with naphthol oligomers have been obtained. It has been shown that in partial substitution of carbon black by naphthol oligomers in the composition of vulcanizate from BR, the obtained rubbers exhibit high heat-physical, physical-mechanical and electrical properties.

Keywords electroactive polymers, electroconductive compositions, naphtol, oligonaphtol, oxidation, polycondensation.

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Alzheimer’s Detection By Using Neural Networks

Abstract It is very important to get the diagnosis tools in early stage of Alzheimer as it will increase patient’s chances of recovering and it enables the people attending the patient to take better care of him/her. Alzheimer’s disease (shortly AD) is an acute disease with many number of the human deaths mostly people over 60 years. There are number of techniques like blood test, psychological analysis and neuroimaging, are available for the detection of Alzheimer’s disease. Here we present details of work done in detection and classification of the Alzheimer’s disease using neuroimaging techniques. MRI (magnetic resonance imaging) scans of brains are used for detection and classification purpose. First stage is to preprocess the MRI images and then we segment it. Next we do feature extraction from segmented image. These features are stored for the last stage which is classification and detection. Classification and detection is done using artificial neural network (ANN) which is very reliable and accurate technique. Neural network is trained using number of sample data and extracted feature. This leads to more accurate results which will aid in early diagnosis of Alzheimer’s disease.

Keywords Alzheimer’s disease, artificial neural network, classification, magnetic resonance imaging, neuroimaging, positron emission tomography.

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ZnO Modified Bismuth Silicate Glasses Structural and Physical Properties

Abstract Zinc bismuth silicate glasses with compositions were prepared using standard melt-quench techniques and zinc solubility limits were estimated using X-ray diffraction techniques in the bismuth silicate glass scheme. Density was measured using the principle of Archimedes; the molar volume and density decreased with a rise in ZnO in the samples. The temperature of the glass transition ( ) was determined using differential calorimetry scanning (DSC) and is expected to raise with a rise in ZnO content. Raman and FTIR spectra were registered at room temperature and Raman and FTIR analysis demonstrates that in all glass compositions there are asymmetric and symmetric extended vibrations of Si-O bonds in tetrahedral units and with reduction in Bi2O3, the input of symmetric vibrations starts to dominate resulting in enhanced compactness of the glass composition.

Keywords— ZnO, Bismath silicate, DSC,Raman spectra, Infrared spectrum.

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Optimization of IBOM Power Plant (PG9171) using Fault Prediction on Gas Path Analysis

Abstract Almost from the inception of the gas turbine engine (GT), users and engine manufacturers have sought an effective technique to determine the health of the gas-path components (fan, compressors, combustor, turbines) based on available gas-path measurements. The potential of such tools to save money by anticipating the need for overhaul and providing help in work scope definition is substantial, provided they produce reliable results. It furthermore therefore became desirable to monitor the engine performance and diagnose the fault even before the damage is done since the fault can cause permanent damage to the components. Preventive maintenance proves to be a better way considering the longer run. This project thus work describes how modern gas-path analysis can be used as a tool for gas turbine diagnosis. Gas path analysis is studied with the aid of fault predictions obtained from using fuzzy logic was found to be a more suitable method for gas turbine diagnosis because the set of fuzzy rules are described using common language. MATLAB Simulink environment is also used to predict the degree of fault in the gas turbine through its Gas path analysis. The linguistic variables used as inputs are temperature, pressure and speed while the linguistic variable used as output is failure. The universe of discourse for temperature is between [0, 55], pressure is [0, 1000], shaft speed is [0, 5000] and failure which is the fault is [0, 1]. A type 1 fuzzy logic model and the center of gravity method are used as the defuzzification module. From the results it is seen that the value for the highest possible fault is 0.909 and the lowest is 0.217 at 6.3 and 52.7 OC respectively. This research shows that the fault prediction probability increases at higher operating conditions of the gas turbine.

Keywords Gas Turbine, Fault Prediction, Gas Path Analysis, MATLAB Simulink, Fuzzy Logic.

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A Study to Evaluate the Effectiveness of Self Instructional Module on Knowledge and Practice regarding Integrated Management of Neonatal and Childhood Illnesses among Staff Nurses working in Paediatric Wards of Selected Hospitals in Patna, Bihar

Abstract

Introduction: Children are our future and our most precious resources. Today’s children are the citizens of tomorrow’s world. The IMNCI case management component is mainly focused on the classification of the five most common causes of infant mortality (diarrhoea, pneumonia, malaria, measles and malnutrition), identification of treatment, accurate treatment or timely referral, counseling of the mother and giving follow-up care. IMNCI integrated treatment guidelines are devised to assist the health workers to assess the sick child by observing easily recognizable signs. Working through a color-coded system, the health worker classifies the sickness and takes the necessary steps such as urgent referral for medical treatment at a health Centre, medical treatment on the spot or advice for home management.

Method & Material: An evaluative research approach and quasi-experimental research design was adopted. 150 nurses working in pediatric wards of selected hospitals at Patna were selected for the study by using purposive sampling technique. By using knowledge questionnaires, and competency checklists questionnaires.

Results: The study reveals that out of 100% of nurses 3.3% of the nurses had good knowledge before Self-instructional module; majority of the nurses 60% had average knowledge; 36.6% of the nurses had poor knowledge. Whereas majority of the subjects 76.7% had good knowledge, 23.3% nurses had average knowledge after a Self-instructional module in IMNCI. In competency 51.7% had moderate on practice, 38.3% had adequate knowledge on practice, and 10% of the nurses had inadequate knowledge on practice before the Self-instructional module. Whereas majority of the nurses 83.3% had adequate knowledge on practice, 16.7% nurses had moderate knowledge on practice after the Self-instructional module on IMNCI.

Conclusion: There is a positive co-relation observed between the level of knowledge and practice regarding Integrated Management of Neonatal and Childhood Illnesses among staff nurses. The study revealed that Self-instructional module improved the knowledge and practice regarding Integrated Management of Neonatal and Childhood Illness among Staff nurses.

Keywords— Knowledge, Practice IMNCI.

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