This book consists of different accepted papers of the conference. Firstly, the artificial intelligence and its application-related topics are provided. Secondly, cloud computing and related topics are also provided.
The book has been designed to help research organisations and business leaders from across industries to transform their organisations into AI-driven disruptors. The utility of the technology in the face of massive globally interconnected complexity is explored. The significant characteristics of IEMAICLOUD are the promotion of inevitable dialogue between scientists, researchers, engineers, corporate’s and scholar’s students to mitigate the gap between academia, industry and governmental ethics which has been fostered through keynote speeches, workshops, panel discussion and oral presentations by eminent researchers in relevant field. The industry personnel depict cutting-edge researches in artificial intelligence and cloud computing to convey academia regarding real-time scenario and practical findings. Conference has been well equipped with talks by industry experts on the state of the art in computer science, lectures by eminent scientists designed to inspire and inform presentations by innovative researchers coming from 20+ countries from Europe and abroad. There has been discussion-oriented sessions and networking breaks to enable collaborations.
Papers consist abstract, result, discussions and conclusions by the help of different tables and diagrams.
Table of Content
Mathematical Modelling to Predict Fuel Consumption in a Blast Furnace Using Artificial Neural Networks.- ‘A Hybrid Model based on Behavioural and Situational Context to Detect Best Time to deliver Notifications on mobile devices’.- Peculiarities of Image Recognition by the Hopfield Neural Network.- PDCloud EX Software Defined Network.- Business Analytics: Trends and Challenges.- Security Operation Modes for Enhancement of Utility Computer Network Security.- ‘Design and Analysis of Digital Compressed ECG Sensing Encoder for Io T Health Monitoring Devices’.
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