– Chapter 10 builds a classification model that classifies whether a customer is going to buy a car with specific features. This research work consisted of four ML models and an analysis of their results. These classifying models were Gaussian Naïve Bayes, decision tree, Karnough Nearest Neighbors and neural networks. The author also attempted to find the best hyperparameter value to obtain the best result from these models. These results are used to compare the accuracies of every model and decide the best model for use in real-time prediction. Here, the author was predicting whether a customer was going to buy a car or not buy a car with particular features available in it. Hence, for this prediction the best accuracy we got was 97.4%, which was given by the decision tree classifier. Also, the neural network had about the same prediction accuracy. Therefore, this ML model can be used by a firm to determine whether or not a new car with specific features will sell well or by a customer wanting to know whether a particular car will be bought by other customers as well.
– Chapter 11 examines the use of AI and ML in political campaigns. It is divided into three sections—the first section explores internet penetration and the influence of social media on the Indian Lok Sabha election; the second section explores the forms of deepfake and automated social media bots and their use during the election campaign; and the final section explores the future of AI and ML in the election campaign in India.
– Chapter 12 attempts to explain the impact of segment routing (SR) in software-defined networking (SDN). For this, the authors implemented three algorithms known as multi-objective particle swarm optimization (MOPSO), advanced MOPSO (A-MOSPO) and minimum interference routing algorithm (MIRA) on a Waxman network topology created randomly having 100 nodes. For performance evaluation, MATLAB and parameters such as throughput, link utilization, and delay were taken as the key parameters for evaluating the above protocols in an SDN environment.
– Chapter 13 discusses the symptoms of COVID-19, precautionary measures against it, ways of spreading the corona-virus, and technologies used to fight it. Also discussed is the impact of COVID-19 on business, financial markets, supply-side and demand-side economics, and international trade on the Indian economy.
– Chapter 14 discusses the convolutional neural network (CNN) used for detecting skin cancer and compares the accuracy of the model by applying a vast dataset by varying the parameters, such as number of layers, activation functions, etc., to find the best suitable parameters for CNN to design the classifier that could give the best accuracy while classifying the images of the seven types of skin cancer.
– Chapter 15 presents the hybrid outcome of the firefly algorithm (FA) and artificial potential field (APF) algorithm for humanoid control, which is preferred in the present study for navigational tasks.
– Chapter 16 proposes a system that considers the student’s academic and behavioral characteristics. The data collected can help faculty members gain a better understanding of a student’s level of knowledge and personality. Based on the information collected, students are grouped into clusters using k-means clustering and a suitable partner is selected for group activities using Irving’s algorithm to enable active learning.
– Chapter 17 discusses how the workload prediction in cloud environments improves proper utilization of resources so that service level agreement remains at a stable level. Hence, the particle swarm optimization (PSO)-based hybrid wavelet weighted k-nearest neighbors (PHWkNN) algorithm is proposed to predict workload in the cloud data center.
– Chapter 18 includes a survey for predicting bankruptcy, in which it was concluded that preprocessed datasets have a better prediction outcome and that ensemble models are more powerful for bankruptcy prediction as compared to the single models.
– Chapter 19 aims to provide a comprehensive review of the research done with respect to the application of AI and ML in the agriculture domain and the key strategies adopted by leading companies like Deere & Company (John Deere, US), Microsoft Corporation, Descartes Labs, ec2ce (Spain), etc., in the agricultural market. The chapter also discusses the current scenario and emerging trends of AI and ML in the Indian agriculture sector. Next, it demonstrates how the application of these technologies has bright prospects in Indian agriculture and can impact the agricultural market in the long term, and how the technological support will boost the agricultural economy by creating new opportunities in agriculture’s operational environments. Finally, it studies the barriers in the application of AI and ML in the Indian context.
The topics presented in each chapter are unique to this book and are based on the unpublished work of the contributing authors. In editing this book, we attempted to bring into discussion all the new trends and experiments for creating an advanced society. We believe this book is ready to serve as a reference for larger audiences such as system architects, practitioners, developers and researchers.
Sandeep Kumar Panda ICFAI Foundation for Higher Education (IFHE), Deemed to be University,Hyderabad, Telangana, India January 2022
Acknowledgments
The preparation of this edited book was like a journey that we had undertaken for several months. We wish to express our heartfelt gratitude to our families, friends, colleagues, and well-wishers for their constant support throughout this journey. We express our gratitude to all the chapter contributors, who allowed us to quote their remarks and work in this book. In particular, we would like to acknowledge the hard work of authors and their cooperation during the revisions of their chapters. We would also like to acknowledge the valuable comments of the reviewers which have enabled us to select these chapters out of the so many chapters we received and also improve the quality of the chapters. We wish to acknowledge and appreciate the Scrivener Publishing, Wiley team for their continuous support throughout the entire process of publication. Our gratitude is extended to the readers, who gave us their trust, and we hope this work guides and inspires them.
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Post Pandemic: The New Advanced Society
Sujata Priyambada Dash
Department of Management, Mesra, Ranchi, India
Abstract
The World Health Organization (WHO) declared the COVID-19 outbreak as a global public health emergency of international concern. The pandemic has increased the suffering of humanity enormously. Loss of income and employment opportunities is the massive adverse effect of the pandemic. Due care needs to be taken by the top-level management of every sector to understand the adverse effect and causes or problems and to build the measures to overcome from the pandemic. The researcher had attempted and discussed the themes viz., areas of management, financial institutions cyber-crime, economic notion, human depression, school and colleges closures, returning of migrant laborers to identify the constraints and to come up with the remedial measures to overcome those constraints and how to build a new advanced society of Post COVID-19 era.
Keywords: Areas of management, financial