HR Analytics Using Tableau
1) The dataset deals with employee details like age, travel profile, department, designation, monthly income, marital status, salary hike, involvement etc in the company and also attrition rate of the employees in the company 2) We need to determine the attrition of employees in the company 3) We also determine the major causes of attrition of employees in the company and to address it.
Published by: G. Raghav
Author: G. Raghav
Paper ID: V7I6-1156
Paper Status: published
Published: November 8, 2021
A Study on Industrial Labour in India
India is the most industrious country . Labor is The sum of vital utpadanangaddu , laborers economic Development is very Do The sum of important Job category plays . Efficient and skilled workers, are for The real What Wealth of the for The the in COUNTRY . It is important to study the conditions of labor . Done by Industrial labor -in, to General Tulu language islarge and small And cottage industries employing maduvavaragiruttare. But working -in, for The conglomerate INDUSTRIES controlled by the for The Factory Act,-in, , India | Workers done by Industrial, not Do ONLY What pics INDUSTRIAL workers is considered to the BE is also the The sum of the cottage in the industry, working maduttiruvavarannu INDUSTRIAL workers would BE is also the considered . For the industrialization of the Apes slowly goes from being an industrial worker , to the settlement in the number of slower growth . Is, India | for The LARGEST Organized As the INDUSTRIAL working sramikarannu ONLY What INDUSTRIAL workers to the BE is also the considered-in, In 1991,, for The workers of the ONLY What 88.79 -in, for The 4.72 million to workers-in, for The private sector for, karyanirataragiddaru. Of the total 28.5 crore workers in the country, industrial workers account for only 3.17 per cent . 2008, the-in, for The state owned MANUFACTURING sector for working to the workers, for The of the in NUMBER 108. 44 million and 49.5 of the private manufacturing sector . In the same period , the number of organized public sector jobs is 177 million , since the number of private organized sector employees is 92 million rather than the number . Both together and added to the 275 million business agiruttare. For The HIGH in NUMBER of the workers-in, for The Cotton industry and for The Work is now to the , India | is to the BE is also the found.
Published by: Dr. Tejashwini
Author: Dr. Tejashwini
Paper ID: V7I6-1162
Paper Status: published
Published: November 8, 2021
Simulated and observed DO (Dissolved Oxygen) values for selected major stations of spring-fed Kosi River stretch through model WASP (Water Quality Analysis Simulation Program)
The river Kosi is a spring fed river of Indian Himalayan region which quenches the thirst of major population of Kumaon region. The model WASP (Water quality analysis simulation program)is a widely used model suggested by EPA that can help simulate the water quality processes in diverse water bodies as reservoirs, ponds, lakes river like surface water bodies. The analysis in the 4 major selected stations of the stretch for Dissolved Oxygen was found to be 4-11mg/l as measured value whereas simulated values ranged from 1 mg/l to 10mg/l at the origin of the river, whereas at the end point of the river the simulated and measured value ranged from 4mg/l-8mg/l , 6mg/l. The Dissolved oxygen in the water is very essential to estimate the water quality as it directly affects the aquatic life and also signifies the presence of organic matter as well as microorganisms in the water. The continuous variations in the DO levels are observed in the entire stretch. The probable reason is uneven rainfall, scattered population and terrain complexities of the region. The continuous and frequent merging of various springs into the main course river results in frequent fluctuations in the physicochemical parameters of the river. This study is an attempt to comparatively analyse the water quality of the only river of the region with the simulated values from model WASP and observed water quality from daily sampling from the water body.
Published by: Dr. Pooja Rani Sinha, Kireet Kumar, Dr. V. P. Uniyal
Author: Dr. Pooja Rani Sinha
Paper ID: V7I6-1144
Paper Status: published
Published: November 8, 2021
Stock Market prediction made easy with Machine Learning algorithms
The main objective of this paper is to find the best model for predicting the stock market movement. We have tested various models based on machine learning that were previously implemented and during the process, we found out that the Random Forest and Support Vector Machine algorithms were not exploited well. In this paper, we are going to find out a more feasible method to predict the stock market with higher accuracy. We have taken a dataset of stock market prices from previous years and pre-processed the data for real analysis. So, our paper will also be focusing on pre-processing of the raw dataset. After pre-processing, we will be reviewing the use of random forest and support vector machine on the datasets and the outcome it generates. The paper also examines the feasibility of the prediction system in real-world settings and issues associated with the accuracy of predicting the market. If this model achieves higher accuracy than previously implemented machine learning algorithms then it can prove to be a great asset for stockbrokers, institutions, and individual investors.
Published by: Vaibhav Kumar, Rishabh Raj
Author: Vaibhav Kumar
Paper ID: V7I6-1138
Paper Status: published
Published: November 8, 2021
House Price Prediction using Machine Learning
In today's society, everyone wants a home that fits their lifestyle and budget while still providing the facilities they require. House values fluctuate a great deal, indicating that they are typically overstated. Many criteria must be considered when projecting house prices, including the location, number of rooms, carpet area, age of the property, and other fundamental local features. This study seeks to forecast house prices based on all of the main factors that go into deciding the price.
Published by: Aldrin Fernandes, Abdullah Qureshi, Aamir Shaikh, Amit Narote
Author: Aldrin Fernandes
Paper ID: V7I6-1155
Paper Status: published
Published: November 6, 2021
Validated RP–HPLC method for determination of Magaldrate and Simethicone in tablet dosage form
A RP-HPLC method was developed for the estimation of Magaldrate and Simethicone in tablet dosage form which is simple, less time consuming using an economical column. The essay of the sample has been carried out with assay percentage of 99.56% and 101.97% Magaldrate and Simethicone respectively. The developed method has been validated for different parameters like, precision, ID precision, Linearity, Accuracy, Robustness, LOD and LOQ and it is simple, specific accurate and economical.
Published by: K. Chaithanya, Omar Mohammed, P. Satish Kumar
Author: K. Chaithanya
Paper ID: V7I6-1145
Paper Status: published
Published: November 6, 2021
