Titlebook: Artificial Intelligence of Things; First International Rama Krishna Challa,Gagangeet Singh Aujla,Kanika S Conference proceedings 2024 The

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Conclusion and Future Research Directions,sed the Mathsat Constraint Solver to collect the data by running the GNU Coreutils program and Busybox utilities. The performance comparison of the different solvers was done over three constraint datasets.

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Conclusions and Future Research Directionschine learning algorithms on various factors and their trade-off for prediction. The experimental results indicate that Orthogonal Matching Pursuit is the best algorithm for this problem. We make our dataset available for further research.

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Securing IoT Using Supervised Machine Learningmising approach for IoT security due to their ability to detect and classify malicious data. This paper provides a comprehensive overview of supervised machine learning methods used for IoT security, including various classifiers and data engineering techniques. We have further demonstrated how effe

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Prediction Based Load Balancing in Cloud Computing Using Conservative Q-Learning Algorithmthe demand basis. Cloud Computing carry amendments, and the revolution of the Information Technology industries emerged with its popularization and applications. Balancing is one of the best solutions for efficient utilization of resources and is extensively considered to be the most important metho

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A Comparative Analysis of Android Malware Detection Using Deep Learningf the proposed models on different data types is compared in terms of accuracy and loss. This experiment achieved a higher accuracy of 99.66% with dynamic features and a lower accuracy of 85.74% with combined features. Similarly, we achieved a minimal loss of 0.06 with dynamic analysis and a higher