Analysis of Heat Transfer and Flow Due to Natural Convection in Air Around Heated Triangular Cylinders of Different Sizes Inside a Square Enclosure

AbstractHeat transfer and flow due to natural convection in air around heated equilateral triangular cylinders of different sizes inside a square enclosure has been analyzed. The triangular cylinder is at higher temperature and the vertical walls of the enclosure are at lower temperature with insulated horizontal walls. The computational model is developed using Ansys Fluent 13 commercial CFD package. The Rayleigh number is varied from 104 to 106. For a given size of enclosure, cylinders of different size are taken corresponding to aspect ratios of 0.2, 0.3, 0.4 and 0.5. Results are presented in the form of contours of isotherm and stream function

Synthesis, characterization of Zinc oxide and assessment of electrical DC conductivity properties

Polymer composites are widely used in electrical devices, sensor materials, electromagnetic interference (EMI) shielding, and other applications. Composites may be customized for any intended application by changing the ratios of the polymeric components. Polyaniline (PANI) is not as sensitive as metal oxides toward gasoline species, and its negative solubility in organic solvents limits its packages, however it's miles suitable as a matrix for instruction of engaging in polymer nanocomposites. Therefore, there has been increasing hobby of the researchers for the education of Nano composites based totally on PANI The fuel for the production of nanometal oxide comes from naturally occurring sources. The weight percentages of such generated metal oxides are altered during chemical polymerization with polyaniline. Composites of polyaniline cellulose and varying weight ratios of Zinc oxide (ZnO) are produced. In synthesised Polyaniline cellulose/ZnO composites, the formation of polymers and their interactions with metal oxides are investigated using Ultraviolet (UV)-vis, Fourier-transform infrared spectroscopy (FTIR), and X Ray Diffraction. The surface morphology of the composites is studied using Scanning electron Microscopy. The characteristics of the specified composites are investigated using electrical dc conductivity electrical conductivity

Synthesis, characterization of Zinc oxide and assessment of electrical DC conductivity properties

Polymer composites are widely used in electrical devices, sensor materials, electromagnetic interference (EMI) shielding, and other applications. Composites may be customized for any intended application by changing the ratios of the polymeric components. Polyaniline (PANI) is not as sensitive as metal oxides toward gasoline species, and its negative solubility in organic solvents limits its packages, however it's miles suitable as a matrix for instruction of engaging in polymer nanocomposites. Therefore, there has been increasing hobby of the researchers for the education of Nano composites based totally on PANI The fuel for the production of nanometal oxide comes from naturally occurring sources. The weight percentages of such generated metal oxides are altered during chemical polymerization with polyaniline. Composites of polyaniline cellulose and varying weight ratios of Zinc oxide (ZnO) are produced. In synthesised Polyaniline cellulose/ZnO composites, the formation of polymers and their interactions with metal oxides are investigated using Ultraviolet (UV)-vis, Fourier-transform infrared spectroscopy (FTIR), and X Ray Diffraction. The surface morphology of the composites is studied using Scanning electron Microscopy. The characteristics of the specified composites are investigated using electrical dc conductivity electrical conductivity

Machine learning for IoT-based smart farming

Agriculture balances food requirements for mankind, and the supply of essential raw materials for many industries is the fundamental occupation in India. Smart farming allows analyzing the growth of crops and the parameters which influence crop growth and supports farmers in their activities, it is more profitable and reduces irrigation wastages. The proposed model is a smart farming system that analyzes the influence of parameters on crop growth and predicts the soil condition using a machine learning algorithm. Temperature, Ph, humidity, gas, and water level are the few most essential parameters to determine the quantity of water required and to find hazardous gas in any agriculture field. This system comprises temperature, pH, humidity, smoke detector, and water level sensor, deployed in an agricultural field, sends data through a microprocessor, developing an IoT device with cloud. In this study, we present a model that predicts soil series with regard to land type and, in accordance with the prediction, suggests appropriate crops. For soil land classification and crop prediction application is developed using KNN algorithms. Three steps are necessary for its implementation: the first is data collecting using sensors placed in an agricultural field, the second is data cleaning and storage, and the third is predictive processing utilizing the ML technique. The results obtained through the algorithms are sent to the cloud, which helps in decision-making in advance

Off-line Signature Verification Based on Fusion of Grid and Global Features Using Neural Networks

Signature is widely used and developed area of research for personal verification and authentication. In this paper Off-line Signature Verification Based on Fusion of Grid and Global Features Using Neural Networks (SVFGNN) is presented. The global and grid features are fused to generate set of features for the verification of signature. The test signature is compared with data base signatures based on the set of features and match/non match of signatures is decided with the help of Neural Network. The performance analysis is conducted on random, unskilled and skilled signature forgeries along with genuine signatures. It is observed that FAR and FRR results are improved in the proposed method compared to the existing algorithm

Crystal structure of 10-[(3-oxo-3H-benzo[f]chromen-1-yl)methyl]-2-trifluoromethyl-9a,10-dihydrobenz[4,5]imidazo[1,2-a]pyrimidin-4(5aH)-one

Crystal structure of 10-[(3-oxo-3H-benzo[f]chromen-1-yl)methyl]-2-trifluoromethyl-9a,10-dihydrobenz[4,5]imidazo[1,2-a]pyrimidin-4(5aH)-on

Analysis of socio-economic factors affecting deprivation of school attendance across Indian districts and its implication on public expenditure

Education is seen as the best mechanism to achieve upward economic and social mobility by vulnerable masses. Even by the government, education is regarded as a proactive initiative through which it can hope to address the problem of regional imbalance in a sustainable manner. Many prior studies have identified various factors which have played significant role in depriving education for masses. However, studies which have identified magnitude of the factors impact in depriving of education are scarce. The present study identifies the causal factors which have deprived school attendance of students among households across Indian districts along with the magnitude of their impact. Through present study we were able to infer that nutrition of children, maternal health, years of schooling and financial inclusion of household played a significant role in affecting their school attendance. Through predictive probability, we were able to assess the magnitude of the impact of the following factors and their implications on public expenditure

Strategies for pigeonpea improvement

In order to feed an ever-increasing population, it is essential to deal yield reducing factors. Climate smart crop varieties that yield more with fewer inputs will be required to achieve the success. In this scenario pigeonpea plays an important role as it can stand in relatively harsh environmental conditions. Hybrid breeding along with the pure line breeding, genetic resources and genomics advances are enriching this crop. However, the pigeonpea improvement program must be re-oriented in order to deal with the yield-reducing factors and to break the yield plateau

Analyzing Usage and Effectiveness Of E-Learning Applications among Rural and Urban Students: An Empirical Study

Although Information communication technology was bound to transform teaching learning pedagogy in developing nations, advent of Covid-19 and subsequent nation-wide lock down has acted as a catalyst for the process. Experience from developed world has shown that Information Communication Technology enhances learning process. In India there has always been a prevalence of dichotomy of resources between rural and urban regions. Government of India has taken initiatives like Provision of Urban Amenities to Rural Areas, Pradhan Mantri Jan Dhan Yojana, Deendayal Upadhyaya Gram Jyoti Yojana, Pradhan Mantri Sahaj Bijli Har Gar Yojana to strengthen socio economic infrastructure in rural area. Along with this some of the State Governments like that of Karnataka and Uttar Pradesh have initiatives to promote digital learning among students in both urban and rural areas. In this context it becomes pertinent to analyze whether students in rural area are on par with the students in urban area to access digital learning. This is even more relevant as nearly 65% of Indian population resides in rural areas. Our research paper aims to suggest appropriate policy suggestions to bridge this gap, if any