Impact of government finance scheme on increase in NPAs of banks – A review
The financial structure of the country plays an important role in the development of the country. It saving and investment of all classes in the economy to create wealth. As banks earn money on the basis of interest provide on the loan amount and other schemes. As money lent by the bank have to be recover after particular time period of time. Sadly, sometimes it not goes by the path defined. Many borrowers fail to return money back to the bank in the form of interest on loan taken. So eventually it became non- performing asset on bank and it creates negative impact on the bank. The purpose of this study is to determine the pattern in growth of gross NPAs in banking industry as well as to determine which measures should be taken to save an asset from becoming NPAs. This is an exploratory study which is conducted by involving the data provided by government website data.gov.in. This study identifies the fact that impact of government finance schemes MUDRA on rising of NPAs of banking industry. It also gives solution on how banks should approach towards lending loans under such schemes such that it prevents the asset from becoming NPA in future.
Published by: Mayank Dandhare
Author: Mayank Dandhare
Paper ID: V6I6-1191
Paper Status: published
Published: December 10, 2020
Diabetes detection using various model comparisons
Diabetes is a serious disease in which your body cannot properly control the amount of sugar in your blood because it does not have enough insulin. Diabetes is the most common medical complication during pregnancy, representing 3.3% of all live births. In this, we have a dataset of approximately 1000 people. The decision tree is obtained from Python using which we can predict whether the people present in the dataset suffer from diabetes or not. Diabetes is a disease in which your blood glucose, or blood sugar, levels are too high. When you are pregnant, high blood sugar levels are not good for the baby. Classification of the probability of diabetes is done based on various factors. The main aim of this work is the detection of Diabetes Mellitus using different models and classifies the data as diabetic and non-diabetic. Our health care systems are rich in information but they are poor in knowledge so there is a large need of having techniques and tools for extracting the information from the huge data set so that medical diagnosis can be done. Data Mining is a process of semi-automatically analyzing large databases to find useful patterns. Data mining attempts to discover rules and patterns from data as it deals with large volumes of data, stored primarily on disk. Data mining mainly deals with knowledge discovery in databases.
Published by: Sharath Kumar D. A., Jayanth H. N.
Author: Sharath Kumar D. A.
Paper ID: V6I6-1189
Paper Status: published
Published: December 9, 2020
The impact of state migrant policies on the standards of living of migrant-labourers in India during COVID-19
This research paper elucidates the nature of the migrant policies of the states of Maharashtra and Uttar Pradesh in India, and the role they have played in moulding migration patterns in the past. Furthermore, the paper aims to investigate the effectiveness of these policies in protecting the standards of living of migrant labourers, measured primarily based on their access to basic goods and services which is indicative of their socio-economic security. Lastly, the paper provides future recommendations for policy adaptations based on real life examples to enhance the condition of the migrant labourers of each state.
Published by: Ahaan Chhatwal, Ananya Kalantri, Anushka Mehta, Gayatri Sharma, Mansi Khetan, Moulik Nanda, Nimish Dhawan
Author: Ahaan Chhatwal
Paper ID: V6I6-1186
Paper Status: published
Published: December 4, 2020
Natural scene image classification using CNN
Research mainly focused on CNN model for feature extraction and classification of Images. Convolutional Neural Network (CNN) has demonstrated promising performance in image classification tasks. In this project, the algorithm is used to classify the images or natural scenes into 6 classes. This model at last predicts the accuracy or probabilities of different class labels and this probability is used for the predicting class at the end. This dataset is used for both training and testing purpose. It provides the accuracy rate 84.93%. Images with combination of two scenes creates and ambiguity hence it is difficult for model to classify. Therefore, it leads to failure in algorithm sometimes. Images used in the training purpose are RGB images. The computational time for processing these images is relatively high as compare to other normal images. Stacking the model with more layers and training the network with more image data using clusters of GPUs provide more accurate results of classification of images.
Published by: Jayanth H. N.
Author: Jayanth H. N.
Paper ID: V6I6-1184
Paper Status: published
Published: December 4, 2020
Identification of strategic networks in entrepreneurial networking process: A case study of influencer entrepreneur in fashion startups, Thailand
From social media influencers (SMIs) who gain social capital in the form of follower fan base on social media platforms, developing further career opportunities into a successful entrepreneur. This significant phenomenon has seen the emergence of influencer entrepreneurs utilizing social media platforms to disclose their own personal products or services. Underlying this growing trend is the dynamic interplay of networks and the firm activities. In order to better understand in specify research area, the importance of network dimensions have been conceptualized in start up process. To explore entrepreneurial networking process in which driving influencer entrepreneur into entrepreneurial success. The key implication of the research is the strategic network for achieving entrepreneurial success in firm performance and superior network outcomes. A qualitative research approach enabled triangulated data investigation with both primary and secondary sources to facilitated the emergence of relevant theme; Procurement and supplier relations, research design and development of product, human resource planning and training, management technology and management system , warehouse and logistics distribution, marketing intelligence and marketing (Fashion retailing, marketing and merchandising) and after-sale service and cash collections. The key strategies in fashion start up networking process influencer entrepreneur that uncovered in the study can thereby leveraging chances to turn start ups into success and sustainability and enhanced some network dimensions on how to become more competitive and successful in the future.
Published by: Nipaporn Promthong, Chia-Han,Yang
Author: Nipaporn Promthong
Paper ID: V6I6-1177
Paper Status: published
Published: November 28, 2020
Optimal load forecasting by hybrid the artificial neural network and firefly algorithm
In the smart grid, load forecasting algorithms used for estimating the electricity demand based on historical data. It helps in generating accurate electricity and overcoming the two challenges such as a shortage of electricity and excess generation cost. In the literature, various traditional load forecasting algorithms proposed to predict the electricity demand but never the accurate results. Therefore, advanced algorithms come into the picture such as artificial intelligence algorithms. In this paper, we have hybrid the Artificial Neural Network (ANN) and firefly algorithm for load prediction. Initially, the ANN algorithm is trained based on the historical data then applied to it. After that, the firefly algorithm is used for searching for the optimal learning rate for ANN. The experimental results are performed in the MATLAB 2015a. We have measured various performance analysis parameters and compared with the existing results. From the study, we found that the proposed algorithm gives better accuracy as compared to the existing algorithms
Published by: Rishav, Puneet Jain, Chakshu Goel
Author: Rishav
Paper ID: V6I6-1170
Paper Status: published
Published: November 27, 2020
