Titlebook: Asia Pacific Advanced Network; First International Damayanthi Herath,Susumu Date,Jilong Wang Conference proceedings 2024 The Editor(s) (if

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Au?enfinanzierung als Fremdfinanzierungirst time, this paper presents a RISC-V-based soft processor SCA framework (referred to as .) to perform power-based, electromagnetic radiation-based and execution time-based SCA attacks against cryptographic algorithms and to test countermeasures on soft processor systems. The proposed . framework

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https://doi.org/10.1007/978-3-8349-9939-9ds the next generation Beyond 5G (B5G)/6G. However, AI-driven attacks on these services are a major concern in reaching the full potential of this future vision. Identifying how resilient the AI models are against attacks is an important aspect that should be carefully evaluated before adopting thes

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Conference proceedings 2024 Sri Lanka,.during August 24–25, 2023..The 10 full papers and 1 short papers included in this book were carefully reviewed and.selected from 37 submissions. They are organized in topical sections as follows:?artificial intelligence and machine learning, accelerated computing and distributed systems and communications and networking..

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Communications in Computer and Information Sciencehttp://image.papertrans.cn/b/image/162920.jpg

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978-3-031-51134-9The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl

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,Illuminating the?Roads: Night-to-Day Image Translation for?Improved Visibility at?Night,GAN model was trained on the generated dataset. To facilitate a comprehensive comparison, a well-established pre-trained night-to-day image translation model from ToDayGAN was selected as the benchmark. According to the comparison analysis, the supervised GAN model provided 16.32 dB of average Peak-

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Predicting the Smear Conversion of Pulmonary Tuberculosis Patients Using Machine Learning,ility in predicting smear status is supported by the heatmap analysis. Future work includes further validation on larger and more diverse datasets, consideration of potential limitations, and exploration of advanced techniques like deep learning. The developed neural network model shows promise in c