E-Learning Course Recommender System Using Collaborative Filtering Models

e-Learning is a sought-after option for learners during pandemic situations. In e-Learning platforms, there are many courses available, and the user needs to select the best option for them. Thus, recommender systems play an important role to provide better automation services to users in making course choices. It makes recommendations for users in selecting the desired option based on their preferences. This system can use machine intelligence (MI)-based techniques to carry out the recommendation mechanism. Based on the preferences and history, this system is able to know what the users like most. In this work, a recommender system is proposed using the collaborative filtering mechanism for e-Learning course recommendation. This work is focused on MI-based models such as K-nearest neighbor (KNN), Singular Value Decomposition (SVD) and neural network–based collaborative filtering (NCF) models. Here, one lakh of Coursera’s course review dataset is taken from Kaggle for analysis. The proposed work can help learners to select the e-Learning courses as per their preferences. This work is implemented using Python language. The performance of these models is evaluated using performance metrics such as hit rate (HR), average reciprocal hit ranking (ARHR) and mean absolute error (MAE). From the results, it is observed that KNN is able to perform better in terms of higher HR and ARHR and lower MAE values as compared to other models

Security and Resilience of Cyber Physical Systems

In this era of 5G digital communication, the implementation of industry 4.0 is the need of the hour. The main aim of this industrial revolution is to completely automate the industry for better productivity, correct decision making and increased efficiency. All the concepts of industry 4.0 can only be implemented with the help of Cyber Physical System aka CPS. This is a smart system in which complete mechanism is monitored and controlled by computer-based algorithms. Confidentiality, Integrity and Availability are the three major concern for providing the add on security to any organization or a system. It has become a biggest challenge among the security professionals to secure these cyber physical systems. Hackers and bad guys are planning various kinds of attacks on daily basis on these systems. This book addresses the various security and privacy issues involved in the cyber physical system. There is need to explore the interdisciplinary analysis to ensure the resilience of these systems including different types of cyber threats to these systems. The book highlights the importance of security in preventing, detecting, characterizing and mitigating different types of cyber threats on CPS. The book offers a simple to understand various organized chapters related to the CPS and their security for graduate students, faculty, research scholars and industry professionals