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Titlebook: Advanced Computing Technologies and Applications; Proceedings of 2nd I Hari Vasudevan,Antonis Michalas,Meera Narvekar Conference proceeding

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https://doi.org/10.1057/9781137425959ere is to make use of a lightweight random number generator to be used as private key in ECC- Elliptical Curve Cryptography Hellman system. This would substantially bring down computational costs and thus save resources for they are allocated in the first place.
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Beliefs, Interactions and Preferencesrains and buses to suggest a cost-efficient path to ease the worker’s travel in a new city. The deep learning approach further enhances the recommender system efficiency by approximating rank for each job before recommending them to the worker.
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Making Diplomacy Bots Individual,d value which was determined using stochastic approaches. Thus, the obtained results concerning the detection ability of the autoencoder, compared to that of random forest algorithm, is also encouraging, with autoencoder limiting the percentage of false positive attacks which is proved to be fatal for an intrusion detection system.
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2524-7565 searchers, academics and industry professionals.This book features selected papers presented at the 2nd International Conference on Advanced Computing Technologies and Applications, held at SVKM’s Dwarkadas J. Sanghvi College of Engineering, Mumbai, India, from 28 to 29 February 2020. Covering recen
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https://doi.org/10.1057/9781137425959akes input as voice commands, processes it and performs action accordingly. The system will first record the user action in the form of audio signal. Then, it will process the audio signal to generate the text. At last, it will interpret and perform an appropriate action. The system uses deep neural network (DNN) for speech to text conversion.
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2524-7565 t advances in next-generation computing, the book focuses on recent developments in intelligent computing, such as linguistic computing, statistical computing, data computing and ambient applications..978-981-15-3244-3978-981-15-3242-9Series ISSN 2524-7565 Series E-ISSN 2524-7573
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