-22b9b34417bc6092a74-64d7 20210930013515428 beie:beie director@blueeyesintelligence.org WEB-FORM International Journal of Recent Technology and Engineering (IJRTE) IJRTE 22773878 10.35940/ijrte.2277-3878 https://www.ijrte.org/ 09 30 2021 10 3 10.35940/ijrte.10.3 https://www.ijrte.org/download/volume-10-issue-3/ Department of Computer Science, Vellore Institute of Technology, Vellore (Tamil Nadu), India. Lakshmisetty Ruthvik Raj Bitra Harsha Vardhan Department of Computer Science, Vellore Institute of Technology, Vellore (Tamil Nadu), India. Mullapudi Raghu Vamsi Department of Computer Science, Vellore Institute of Technology, Vellore (Tamil Nadu), India. Keerthikeshwar Reddy Mamilla Department of Computer Science, Vellore Institute of Technology, Vellore (Tamil Nadu), India. Poorna Chandra Vemula Department of Computer Science, Vellore Institute of Technology, Vellore (Tamil Nadu), India. COVID-19 is a severe and potentially fatal respiratory infection called coronavirus 2 disease (SARS-Co-2). COVID-19 is easily detectable on an abnormal chest x-ray. Numerous extensive studies have been conducted due to the findings, demonstrating how precise the detection of coronas using X-rays within the chest is. To train a deep learning network, such as a convolutional neural network, a large amount of data is required. Due to the recent end of the pandemic, it is difficult to collect many Covid x-ray images in a short period. The purpose of this study is to demonstrate how X-ray imaging (CXR) is created using the Covid CNN model-based convolutional network. Additionally, we demonstrate that the performance of CNNs and various COVID-19 acquisition algorithms can be used to generate synthetic images from data extensions. Alone, with CNN distribution, an accuracy of 85 percent was achieved. The accuracy has been increased to 95% by adding artificial images generated from data. We anticipate that this approach will expedite the discovery of COVID-19 and result in radiological solid programs. We leverage transfer learning in this paper to reduce time complexity and achieve the highest accuracy. 09 30 2021 209 214 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.C6386.0910321 https://www.ijrte.org/wp-content/uploads/papers/v10i3/C63860910321.pdf Department of Civil Engineering, Sri Venkateshwara College of Engineering, Bengaluru (Karnataka), India. Ganesh V Ajey Kumar V G Department of Civil Engineering, Sri Venkateshwara College of Engineering, Bengaluru (Karnataka), India. Aravindan S Department of Civil Engineering, Sri Venkateshwara College of Engineering, Bengaluru (Karnataka), India. Sudha Ravindranath Senior Scientist, Regional Remote Sensing Centre-South, Bengaluru/National Remote Sensing Centre, Hyderabad (Telangana), India. Vidya A Scientist Engineer ‘SE’, Regional Remote Sensing Centre-South, Bengaluru National Remote Sensing Centre, Hyderabad (Telangana), India. Urban floods are increasing frequently and severely. Climate change is usually attributed to urban floods with insufficient evidence. While in certain cases this appears to be true, the influence of landscape change in urban growth is more important. This study analyses development of an urban landscape with the complexity of established cities and combines physiographic data for the assessment of peak surface runoff in the study area, Hebbal valley. A portion of the Cauvery river basin draining into the Pinakini river in the district of Bangalore. It encompasses a 305.21 sq.km region in East Bengaluru and North Bengaluru. The land use and land cover classification was classified as 14 different categories: dark, light, roads and vegetation. The region of study has undergone unpredictable expansion and changes in the Land Use Land Cover in the last two decades. Several flood occurrences have occurred in different regions of Hebbal Valley throughout recent years. Rainfall analysis conducted between 1970 and 2018 with 1596mm of greatest precipitation. For the study, several space and non-space data were collected and thematic maps were produced. Runoff estimates for 2018 were made for 24 micro water sheds in the Hebbal Valley using SCS-CN TR55 technique for urban hydrology. The objective of this study is to determine the quantity of peak runoff produced, to develop better urban management techniques. The finding shows that rush volume has increased in recent years as land use patterns have changed and precipitation intensity has increased substantially over shorter periods. The study suggests spatial intervention efforts to provide suitable buildings and measures for flood flow. 09 30 2021 215 220 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.C6484.0910321 https://www.ijrte.org/wp-content/uploads/papers/v10i3/C64840910321.pdf Research Scholar, Department of Geo-Engineering, College of Engineering, Andhra University, Visakhapatnam (Andhra Pradesh), India. Temesgen Abraham Gebreselassie Prof. P. Jagadeeswara Rao Professor, Department of Geo-Engineering, College of Engineering, Andhra University, Visakhapatnam (Andhra Pradesh), India, This study focuses on establishing adequate public healthcare centers to reduce disease spread and untimely death of human lives in Adama City, Ethiopia. There is considerable evidence, owing to poor geographical accessibility, the primary healthcare facility is not reaching the majority of the population in developing nations. This case study has been carried out to identify and prioritize the suitable areas to develop healthcare centers using a Geographic Information System (GIS). Thematic maps and ancillary data are used to analyze location-allocation analysis in ArcGIS-10.4. Required field data was collected using GPS in Adama, Oromia, Ethiopia, and required supporting data from the Municipality of the City. The density of population is the significant input in calculating the standards for services-based location-allocation. Therefore, road networks, existing healthcare facilities, and population density are the critical parameters considered to identify the new healthcare centers to be established to cater to the people's needs. In addition, land use/cover classes and settlement location, proximity to the existing healthcare centers are also considered in GIS analysis for better results. The study identified eight suitable sites to develop healthcare centers in the city. Therefore, the government can utilize the recommendations for infrastructure development planning to improve healthcare facilities based on the accessibility. 09 30 2021 221 230 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.C6477.0910321 https://www.ijrte.org/wp-content/uploads/papers/v10i3/C64770910321.pdf Department of Computer Science and Engineering, Poojya Dodappa Appa College of Engineering, Kalaburagi (Karnataka), India. K Pooja Dr Shailaja S Assistant Professor, Department of Computer Science and Engineering Poojya Dodappa Appa College, Kalaburagi (Karnataka), India. Multiple applications of cloud servicing can be seen in the field of logical programming as well as IT industries. Complex computations over local machines may demand for plenty of system resources thereby delaying the data processing operations. In order to achieve speed in processing one must opt for cloud computing techniques. Extensive maneuver of cloud services is desirable for scientific computation of user data and application. This will require a platform designed in a way to meet the specific requirements of individual users, providing an ease for moving their data and applications over different devices. Symbolic-Numeric Computation using cloud service platform is presented in the paper. In this approach user tasks are presented in the form of symbolic expressions using languages like Java, C/C++, APIs etc. Proposed work employs Python programming for carrying out compilation process. 09 30 2021 231 235 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.C6482.0910321 https://www.ijrte.org/wp-content/uploads/papers/v10i3/C64820910321.pdf