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Apex Predator Conservation through Ecosystem Service valuation

Large predators are the most well-known type of animals around the world, ranging from tigers, lions, bears and wolves who roam terrestrial ecosystems, to sea otters and nile crocodiles who maunder aquatic ecosystems. Despite their ubiquitous popularity, their populations are in imminent danger. Large carnivore and predator populations are experiencing a precipitous decline which can lead to a colossal imbalance in ecosystems. Over the past two centuries, predators have experienced geographic range contractions, fragmentation of habitat, and loss of individuals through hunting. This literature review analyzes and explains how the decline in large carnivore and predator populations can lead to indirect consequences within and across ecosystems. Using an ecosystem services valuation approach, this paper demonstrates how large predator conservation is not only economically justified, but imperative for widespread ecosystem stability.

Published by: Arjit Agarwal

Author: Arjit Agarwal

Paper ID: V7I3-1864

Paper Status: published

Published: June 28, 2021

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Research Paper

Experimental analysis of rooftop solar PV modules installation in educational premises

Photovoltaic module solar energy is a renewable source of energy that uses solar radiation to produce electricity. It is worked on the so-called photoelectric effect, by which semiconductor materials are able to absorb photons (light particles) and release electrons, generating an electric current in form of Direct Current. Which then converted into Alternative current with the help of alternator. There is notable research is going on to use various Straight PV Modules and their types of System on the basis of their operation as alternative of electricity. Solar power systems derive clean, pure energy from the sun. Traditional electricity is sourced from fossil fuels such as coal and natural gas. Installing solar panels on home, Educational Institute and open spaces helps combat greenhouse gas emissions and reduces our collective dependence on fossil fuel. In present assessment Installation of roof top solar PV modules for reducing Electricity bill by using On-grid power system by net metering. Here energy generated by this solar pv module solar plant is transmitted to the electricity power grid and on compensation from electricity board Electricity bill reduces to minimum or extra arears provided to consumer. In traditional way to production of electricity fossil fuels is used which continues to rise producing high levels of carbon dioxide (CO2) which climatologists believe is a major cause of global warming. Similarly, electricity from various Electricity Boards and manufactures hikes their prices by day by day which is affect the unbalanced in the cost and profits of the individuals and its show the impact on social economic life of the persons. Whereas solar energy which is get from Sun is in bulk and its cost nothing. Initial Cost and maintenance cost is low as compare to other source energy.

Published by: Harshvardhan Anil Shinde, Dr. Santosh D. Dalvi

Author: Harshvardhan Anil Shinde

Paper ID: V7I3-2178

Paper Status: published

Published: June 28, 2021

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Research Paper

Carbon sequestration potential of silvicultural and horticultural tree species under different multitier cropping systems

Agroforestry plays a better role in increasing agricultural productivity by nutrient recycling, reducing soil erosion, and improving soil fertility and enhancing farm income compared with conventional crop production. Furthermore, it has promising potentials for reducing deforestation while increasing food, fodder, and fuelwood production. Agroforestry practices can reduce the atmospheric concentration of CO2 by increasing carbon storage in biomass, decreasing emission at source and modifying agricultural practices to increase the quantity of carbon stored in soil organic matter. The natural cycling of the carbon is maintained and controlled by a dynamic balance between biological and inorganic processes since the geological history of the earth. In the terrestrial ecosystem, carbon is sequestered in rocks and sediments, wetlands and forests, and in the soils of forestland, grasslands and agricultural land. In this paper, the estimation of the biomass and carbon sequestration rates of silvicultural and horticultural tree species under Horti-silviculture and Agri-Horti-Silviculture agroforestry system has been done. This investigation is proof to substantiate the fact that adoption of agroforestry techniques/systems is not only beneficial to farmers from their economic perspective but at the same time agroforestry systems helps to reduce global warming and rejuvenate the earth’s atmosphere. In four years of study carbon sequestered in the following manner: Grevillea robusta > Dalbergia sissoo > Syzygium cumini> Mangifera indica> Anacardium occidentale > Eucalyptus globules. When compared according to silvicultural and horticultural categories it Syzygium cumini was found most efficient among horticultural tree species while Grevillea robusta was most efficient among selected tree species.

Published by: Ankita Sinha, Hanuman Prasad Sharma

Author: Ankita Sinha

Paper ID: V7I3-2140

Paper Status: published

Published: June 28, 2021

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Research Paper

Plan and simulation of an ANFIS MPPT controller for Solar Power Application in MATLAB

In this paper we present a savvy control procedure for the MPP following of a photovoltaic (PV) framework utilizing versatile neuro-fluffy surmising framework (ANFIS) under factor sun oriented light conditions. For this a sunlight based photovoltaic module and a DC/DC Boost converter is created in MATLAB/SIMULINK climate. At first, MPPT regulators were planned utilizing Perturbation and Observation (P&O) techniques. Be that as it may, this traditional strategy can't adequately follow quickly changing occurrence sunlight-based illumination levels. Henceforth, a savvy MPPT regulator was planned utilizing ANFIS tool kit which draws a lot of energy and creates quick reaction under constantly changing working conditions. The PV module with proposed MPPT regulator was investigated in independent mode. The significant burden with PV framework is its questionable and discontinuous force yield which relies upon climate conditions. PV module alone can't supply solid capacity to the separated burden successfully. To anticipate the force provided to the heap under various working conditions affectability examination has been done for the PV framework with planned MPPT regulator.

Published by: Shiwani Singh, Dr. Pratibha Tiwari

Author: Shiwani Singh

Paper ID: V7I3-2115

Paper Status: published

Published: June 26, 2021

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Research Paper

Forest fire prediction using ML and AI

Forest fire forecasting is crucial for resource allocation, mitigation, and recovery. The risk of forest wildfires is rising all around the planet. Large wildfire frequency and area damaged have increased by more than four and six times in the last five decades, respectively. Oxygen, humidity, and temperature are all essential factors in wildfire risk evaluations. A new forest fire risk prediction method is described, which is based on Support Vector Machines, Logistic Regression, KNN, decision trees, and Random Forest. The findings show that forest fire danger can be predicted with reasonable accuracy. So, using machine learning techniques and algorithms such as Logistic Regression, KNN, SVC, Random Forest, and Decision Tree, we proposed a system to predict the percentage of fire occurrence based on various parameters such as temperature, humidity, and oxygen data entered by the user in the front end

Published by: Adithi M. Shrouthy, Syed Matheen Pasha, Yamini S. R. E., Navya Shree S., Lisha U.

Author: Adithi M. Shrouthy

Paper ID: V7I3-2136

Paper Status: published

Published: June 26, 2021

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Research Paper

Detection and Classification of Malicious Websites

Phishing is an attractive methodology that is used by the attackers to steal personal data from people. Phishing websites are fraudulent web pages used for cyber thefts. They use domain names, similar to that of an original website, send mail and direct messages to lure someone in sharing personal information. Although many new anti-phishing methods are out ,still these attackers innovate new methods to target these. Therefore there is an alarming need to develop new ways to protect people from phishing. The Project uses different models of comparison in classification of phishing websites for detection and prediction using different machine learning models. The main goal of the project is to make Machine Learning Algorithm for data input and prediction and classify URL’s that are malicious . Using python packages(Fastai,Scikit,pandas,Seaborn etc.) the dataset is converted into Distribution Plots and Confusion Matrix.

Published by: Karan Sawhney, Priya D.

Author: Karan Sawhney

Paper ID: V7I3-2143

Paper Status: published

Published: June 26, 2021

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