Wave Energy Convertor Technology
Ocean contains energy in the form of waves and tidal currents. Both can be used to produce electricity. Differential heating of the earth results in pressure variations in the atmosphere, which causes winds to be generated. Winds transfer some of their energy to the water when they pass over the surface of open bodies of water, resulting in the production of waves. The quantity of energy transferred and the magnitude of the ensuing wave are determined by the following factors: a) wind speed, b) wind speed over time, and c) wind distance. Wave energy conversion devices must generate a system of responding forces in which two or more bodies move relative to each other while at least one body interacts with the waves in order to extract this energy. A system like this can be designed to work with a variety of waves. Energy is extracted directly from surface waves or pressure variations below the surface via wave power devices. Generators store the energy taken from the waves. Offshore and onshore systems can both turn wave energy into electricity.
Published by: Ronit Shirish Shirodkar, Malhar Vitthal Zore, Aaditya Ram Bhogle, Rasika Rajesh Tambe, Nikhil Vijayan Sarojini
Author: Ronit Shirish Shirodkar
Paper ID: V9I2-1176
Paper Status: published
Published: April 20, 2023
A method to detect diseased plant leaves using image processing in MATLAB
In the present World scenario, agricultural farming plays a crucial role as most of people depend on it. But in the current scenario, farmers are finding it hard as the plant leaves are being affected by various diseases in the yield. Tracking plant health and finding parasites for the good crop is essential to lessen disease spread and facilitate effective management practices. In order to bring down this problem and to increase the productivity of the crop, we have put forward a technique for detecting diseased leaves rather than examining them manually. Manual monitoring of leaf disease do not give satisfactory result as naked eye observation is an old method that consumes much time for disease recognition and also needs expertise, hence it is non-effective. In view of this, we introduced a modern technique to find out diseases related to leaves. To overcome the limitations of traditional eye observations, we used a digital image processing technique for fast and accurate disease detection of plant leaves. In our proposed system there exists a software solution for the automatic detection of plant leaf diseases using MATLAB software. The proposed approaches involve image pre-processing and feature extraction. The research work carried out has the potential to be used as an effective tool for the early detection and diagnosis of plant leaf diseases, which aids farmers to take preventive measures to reduce crop loss due to diseases infecting the crop and aids in enhancing economic growth.
Published by: E. Suneetha, Dr. G. Srinivasa Rao, M. Pavani, S.K. Akrimunnisa, Y. Priyanka, R. Geethika
Author: E. Suneetha
Paper ID: V9I2-1184
Paper Status: published
Published: April 20, 2023
Image classification of human action recognition using transfer learning in PyTorch
Over the years, deep learning models have been applied to human action recognition (HAR). due to the enormous amount of labeled data needed to train deep learning models, there has been a significant delay in the absolute development of these models. Data collection in sectors like HAR is challenging, and human labeling is expensive and time-consuming. The current approaches mainly rely on manual data gathering and accurate data labeling, which is carried out by human administration. This frequently leads to a slow and prone to human bias labeling data collection method. To solve these issues, we offered a novel approach to the current data collection techniques [1]. It is generally used that (CNN) is among machine learning models. Since Yann Lecun created this context in 1988, image identification has greatly improved. Transfer learning in image classification has simplified the process of training new models from the beginning and has reduced the number of data points that need to be processed, it was used in this project to classify human actions.
Published by: Amos Oyetoro
Author: Amos Oyetoro
Paper ID: V9I2-1142
Paper Status: published
Published: April 15, 2023
Study on financial literacy and its effects on investment decisions using the Likert scale
Many people seek to educate themselves financially with the goal of saving money and taking advantage of financial products such as easy access to credit, profits gained in favorable circumstances, planning for retirement, and the ease of organizing property or land purchases, among other things. This goal is usually not met or only partly met due to a lack of financial literacy. As a result, we decided to conduct a study into how financially literate the Indian people are and whether financial literacy has anything to do with a person's financial decisions. The purpose of the study was to determine how financial education, financial behavior, financial attitude, and financial awareness affect investment decisions among the residents of Mumbai, India. This study was carried out through sampling, and structured questionnaires were used to acquire primary information.
Published by: Shlok Garodia, Ridhi Saraf, Rishi Kansal, Riya Gupta, Shreya Gupta
Author: Shlok Garodia
Paper ID: V9I2-1179
Paper Status: published
Published: April 15, 2023
An Insight into the Sri Lankan economic crises
Due to years of economic mismanagement, poor administration, and bad policy decisions, Sri Lanka is presently going through one of its most crucial periods in history. Outside forces including the COVID-19 epidemic and Russia's invasion of Ukraine have also exacerbated the nation's issues, leading to its worst-ever crisis in 2022. Now, Sri Lanka is dealing with a number of issues, such as food insecurity, jeopardised livelihoods, and growing safety concerns. Everyone from all walks of life have been affected by the devastation caused by this catastrophe, but the poorest and most defenceless groups have been impacted the hardest. Sri Lanka routinely experiences natural disasters brought on by climate change, which exacerbates the already precarious position. These problems have broad repercussions, especially for weaker households and communities that suffer disproportionately from the current crisis. To solve these issues, immediate action must be made to guarantee enough food supply, stabilise markets, and assist impacted people.
Published by: Nihar Gandhi, Shulmit Madhav
Author: Nihar Gandhi
Paper ID: V9I2-1180
Paper Status: published
Published: April 15, 2023
Design of low power single precision floating point multiplier
The floating-point multiplier is designed to provide high precision and low power for scientific simulations, engineering computations, and financial modeling applications. This paper explains a single precision floating point multiplier architecture using a Vedic multiplier. It takes two single precision floating point numbers as input and produces a single precision hovering point number as output. The proposed architecture uses a pipelined approach to increase the speed of the multiplier and to reduce the power and delay. The pipeline architecture allows multiple operations to be performed simultaneously, resulting in a faster multiplication operation. The proposed architecture generates product mantissa by use of a Vedic multiplier with a carry-save adder using a Multiplexer to reduce the power of the multiplier. The proposed architecture is compared with array multiplier-based single precision floating point multiplier and performance measures such as power and delay. The architecture will be performed in Xilinx Vivado 2016.4 software by selecting the ZED board.
Published by: A. V. Mutyalamma, Dr. G. Srinivasa Rao, K. Krishnaveni, S. Sivanandini, A . Dharani, N. Swathi Vijaya Lakshmi
Author: A. V. Mutyalamma
Paper ID: V9I2-1183
Paper Status: published
Published: April 15, 2023
