Volume 10 | Issue 5 |

 Abstract

The monthly rainfall projections are compared to actual data after training and testing to confirm the model's accuracy. When particular parameters are employed, the model can accurately anticipate monthly rainfall data, according to the findings of this study. Rainfall prediction is one of the most studied areas since it affects the lives and property of many people. Previous rainfall prediction models used a complicated combination of mathematical instruments, but these were insufficient to reach a higher categorization rate. In this study, we propose novel ways for calculating monthly rainfall using Machine Learning Algorithms. Rainfall forecasts are based on quantitative information about the current state of the atmosphere. Complex input-to-output mappings can be learned using a variety of machine learning approaches. The dynamic structure of the atmosphere makes precise rainfall prediction difficult. To forecast future rainfall conditions, the variation in previous year's circumstances must be used. We supported the use of machine Learning Algorithms based on a variety of factors such as temperature, humidity, and wind. Because the suggested algorithm forecasts rainfall based on prior data for a specific geographic area, this prediction will be extremely accurate. When compared to standard rainfall prediction techniques, the model's performance is more accurate.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Machine Learning, Linear Regression, Random Forest, Ridge Regression, Lasso Regression, Support Vector Machine.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Mathematics Teachers, Interaction with students, Student related Activities, Secondary School level.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Fingerprint Identification, Automatic marking and storing of attendance, GSM module.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Retrofitting, Compressive strength, Flexural strength, Basalt Fiber Reinforced Polymer (BFRP), Aramid Fiber Reinforced Polymer (AFRP), Compression Testing Machine (CTM), Universal testing machine (UTM)

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The main goal of the paper is to obtain quantitative describing the actuality of internet shopping in the case of the India in order to explain the development of internet shopping and its impact on consumer behavior. The paper build on the relevant literature and at the same time examines consumer behavior by questionnaires. Furthermore, the future development of internet shopping will be measured and deep comparison of consumer behavior between different countries. This paper support the research questions that including recent trends and various issues in internet shopping, and principle factors for consumer behavior. Also, the result of the study shows that internet consumer trust and perceived risk have strong impacts on their purchasing decisions. Consumer`s trust, privacy concerns, security concerns are the major factors for using internet for shopping, the trust on websites influence to the purchasing decision of any consumer. More specifically, the empirical result suggests how the E-commerce companies make marketing strategies according the research data and analyzing result.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

E-commerce, internet shopping, World Wide Web, consumer behavior, privacy and security, consumer trust.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Artificial Intelligence, Virtual Manufacturing, Machine learning, Deep learning

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Humankind has met its basic need for food production through agriculture. Decades ago, farmers mostly grew food for their consumption or sale with others in the same village or neighborhood. They were mostly independent. However, in the present era, the manufacturing environment is changing significantly from self-sufficiency to commercialization. Scientific advances in crops, the use of fertilizers, pesticides, pesticides, and mechanization of agriculture have resulted in a significant increase in agricultural production and thus an increase in commodities and commodity surpluses. Advanced production is accompanied by increased urbanization, changes in incomes, consumer lifestyles and eating habits, and strengthening ties with external markets. Consumers today are not limited to rural areas where food is produced. In addition, as the demand for processed food or semi-finished products increases, the cost of agricultural products is required to rise. These changes require food commodities to move from producers to consumers in the form of value-added products. As one of the most important fields for human endurance. Farmers are people who support agriculture. Agriculture has proven disadvantageous to small farmers as there are agents who earn significantly more than farmers.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Agricultural sector, Trading, Local market, weather forecasting, yield prediction, authentication, Middleman problem.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Kaziranga National Park of Assam has witnessed a long successful conservation history for which the earlier game sanctuary of Kaziranga becomes Kaziranga National Park subsequently and further to the present high status of world heritage site and tiger reserve. Despite such tremendous success in conservation process, the park for its survival and thriving is, however, bound to fight against a number of challenges. Some challenges originate from the natural disaster caused by the perennial floods while some others are caused by human activities. In this academic work, a modest and sincere attempt has been made to examine various challenges/threats confronted by the park and the conservative strategies and measures adopted by the park management for addressing such challenges.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

: Kaziranga National Park, Challenges, Conservation practices, Park management, Flood.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

To develop an AI based android app for society management system to make it more efficient , secure and enhanced workflow of society

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Android App, AI, Society, Management

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

NEEDS ANALYSIS, TEACHING, LEARNING, UNDERGRADUATE, PROFESSIONAL DEVELOPMENT

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Creative Commons Attribution 4.0 and The Open Definition