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Performance evaluation of Kubernetes cluster federation using Kubefed

We have entered the multi-cloud and hybrid age. The inevitable trend in cloud computing is application-oriented multi-cloud and multi-cluster architecture. Today's cloud applications must abide by a wide range of laws and rules. It is doubtful that a single cluster can follow all the rules. The scope of compliance for each cluster is decreased by the multiple cluster technique. We can move workloads between Kubernetes suppliers to benefit from new features and costs. This paper aims to describe an integration between multiple clusters running on the same cloud and evaluate their performance based on the Kubernetes Cluster Federation system. Some experimental evaluations were carried out with this goal in mind (Cloud Evaluation Experiment Methodology – CEEM) to monitor system resource behavior and availability, including network, disk, CPU, and memory. The test environment consists of a manually deployed Kubernetes cluster that was created. Azure Kubernetes Service (AKS) is the Cloud service provider considered. The Cluster Federation was performed using the Kubernetes Cluster Federation (KubeFed).

Published by: Ben-Salem Banguena E., Dr. T. Uma Devi

Author: Ben-Salem Banguena E.

Paper ID: V9I2-1192

Paper Status: published

Published: April 21, 2023

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Research Paper

Phytochemical studies in blue-green and green algae

A Systematic study of plant crude drugs is embraced through the consideration of both primary and secondary metabolites which are derived from the process of metabolism. The primary metabolites such as carbohydrates, proteins, and lipids are used as food for human beings whereas the secondary metabolites such as phenols, alkaloids, flavonoids, lectins, steroids, and saponins are used for therapeutic purposes. The chemical composition of algae varies to some extent based on the growth conditions namely temperature, light, PH, and availability of nutrients. In the present investigation the presence of qualitative and quantitative phytochemicals namely Carbohydrates, proteins, Phenols, and flavonoids were carried out in Blue green alga Microchaete tenera and Green Algae Nitella tenuissima and Sphaeroplea annulina. The estimated carbohydrate rich in Nitella tenuissima (504mg/100gm) as compared to Sphaeroplea annulina (413mg/100gm) and Microchaete tenera, (301gm/100gm). Protein rich in Nitella tenuissima (624gm/100gm) as compared to Microchaete tenera (496mg/100gm).and Sphaeroplea annulina (350mg/100gm) and Phenol rich in Nitella tenuissima (252mg/100gm) as compared to Microchaete tenera, (204mg/100gm).and Sphaeroplea annulina (186mg/100gm).

Published by: Dr. Prashant Kumar

Author: Dr. Prashant Kumar

Paper ID: V9I2-1185

Paper Status: published

Published: April 20, 2023

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Research Paper

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

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Research Paper

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

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Research Paper

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

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Research Paper

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

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