Prodipto Bishnu Angon

Work place: Faculty of Agriculture, Bangladesh Agricultural University, Mymensingh-2202, Bangladesh

E-mail: angonbishnubau@gmail.com

Website:

Research Interests: Data Mining, Agricultural Engineering, Environmental Engineering

Biography

Prodipto Bishnu Angon studies Agriculture at Bangladesh Agricultural University. Main Interested research fields are Mental health, Data analysis, Climate change, Insect detection, Plant stress detection, Environmental sector, Data mining and IoT. His research interests include Genetics and plant breeding.

Author Articles
Behavioral Changes of Children Intelligence for the Extreme Affection of Parents

By Prodipto Bishnu Angon Sujit Mondal Chandona Rani Das Mintu Kumar Bishnu

DOI: https://doi.org/10.5815/ijeme.2021.06.03, Pub. Date: 8 Dec. 2021

A nation's most valuable resource is its children. In the future, a nation will be controlled in the same way that a kid will develop. The majority of parent’s lack expertise about how to help their children develop a positive outlook. We concluded in our study by analyzing the association between parental excessive affection and the development of children's intelligence. Through the use of a questionnaire, information was gathered from 531 families. Whereas 43 percent of parents show excessive affection to their children, while 45 percent lavish proper affection. On the other hand, in our study, 48 percent of the children had an IQ score of less than 49. We have identified the alterations in their child's brain as a result of their parents' blind affection and have also identified remedies to the problem. We analyzed it so that the growth of children's intelligence is not hampered by their parents' excessive affection and that the parents and children enjoy a close relationship with their parents.

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Cropland Mapping Expansion for Production Forecast: Rainfall, Relative Humidity and Temperature Estimation

By Prodipto Bishnu Angon Imrus Salehin Md. Mahbubur Rahman Khan Sujit Mondal

DOI: https://doi.org/10.5815/ijem.2021.05.03, Pub. Date: 8 Oct. 2021

In the modern era agriculture development is the highly contribute field of food security. Data Science is one of the top analysis experimental methods for forecasting and mapping synchronize. In our study, we experiment with three major parameters (Rainfall, Relative Humidity and Temperature) that can be affected crop production rate as well as area-based mapping. To complete the procedure, the cluster groping and prediction system has created a machine learning BOT combined analysis system. Bangladesh and its 13 areas with 46 years of data have visualized with proper analysis and build up a 2D map of each separate production area. Multi Linear Regression (MLR) and KMean Clustering is the main key point algorithm for the production analysis. Experiment analyzing, we can see that some elements of our environment are closely associated with the productivity of the crop. An untactful environmental change on parameters (Rainfall, Humidity, and Temperature) reduces agricultural productivity by 32-38%. Developed model accuracy 91.25% forecasting methodological analysis for production mapping and prediction. Extreme population food security has ensured ICT and Agriculture combine BOT & EVPM method is essential for the scientific world. This study will allow farmers to choose the proper crop in the right environmental condition, which will play a key role in strengthening the economy of the country.

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