IJSRET » September 2, 2024

Daily Archives: September 2, 2024

Uncategorized

Development and Implementation of Python Applications for 2d Geometry Learning

Development and Implementation of Python Applications for 2d Geometry Learning
Authors:-By. Quyen Vo Truong Ngoc

Abstract-In the contemporary educational landscape, integrating technology with traditional learning methods has shown to enhance comprehension and engagement among students. This project explores the application of Python programming to facilitate the learning of 2D geometry. Python, known for its simplicity and powerful libraries, is utilized to create interactive tools and visual aids for understanding fundamental geometric concepts. This study details the development and implementation of a Python-based application designed to assist students in visualizing and computing various 2D geometric shapes, including points, lines, triangles, squares, and circles. The application leverages libraries such as Matplotlib, Pygame, and Turtle to render shapes and perform calculations related to area, perimeter, and other geometric properties. Preliminary results indicate that students using the application show improved understanding and retention of geometric principles compared to traditional methods. This paper discusses the methodology, key features of the application, and its potential impact on enhancing geometry education. Future directions include expanding the application’s capabilities and adapting it for different educational levels.

DOI: 10.61137/ijsret.vol.10.issue4.210

Published by:
Uncategorized

Detection of Landuse Land Cover Changes by using Maximum Likelihood Algorithm Application on Landsat Satellite Images

Detection of Landuse Land Cover Changes by using Maximum Likelihood Algorithm Application on Landsat Satellite Images
Authors:-Priyanka Gupta, Sharda Haryani, V.B. Gupta

Abstract-The identification of the LULC classes for the Mandsaur district Madhya Pradesh, India is the main objective of this research. The satellite images used in the analysis. Based on pixel-by-pixel supervised categorization of Landsat satellite images taken between 2003 and 2023 using the Arc-GIS tool across 20 year period, the work makes use of maximum likelihood approach. Various classifications of land use and land cover features are considered to predict overall changes, including populated areas, water bodies, agricultural land, forests and desert terrain. Landsat 8 photos from 2023 and remotely sensed Landsat 5 images from 2003 were used to detect changes inorder to accomplish this goal. The five LULC classes for the Mandsaur region are explained in this paper. The maximum likelihood algorithm is used in this work to compare the LULC classes for the Mandsaur region. The validation of the results for the supervised classification using MLC yielded kappa coefficients of 0.8263 and 0.7841 for 2023 and 2003 respectively. Land cover classification should benefit greatly from the application of MLC algorithms.

DOI: 10.61137/ijsret.vol.10.issue4.209

Published by:
Uncategorized

An Analyze the Trends for GST Revenue Collection in Uttar Pradesh

An Analyze the Trends for GST Revenue Collection in Uttar Pradesh
Authors:-Research Scholar Mani Shanker Lal Dwivedi, Assistant Professor Dr. Nancy Gupta

Abstract-GST is an Indirect Tax which has replaced many Indirect Taxes in India. The Goods and Service Tax Act was passed in the Parliament on 29th March 2017. The Act came into effect on 1st July 2017; Goods & Services Tax Law in India is a comprehensive, Multi- stage, destination-based tax that is levied on every value addition. In simple words, Goods and Service Tax (GST) is an indirect tax levied on the supply of goods and services. This law has replaced many indirect tax laws that previously existed in India. GST is one indirect tax for the entire country. This article deals with Analysis of GST Collection of India.

DOI: 10.61137/ijsret.vol.10.issue4.208

Published by:
× How can I help you?