Titlebook: Mobile Platforms and Development Environments; Sumi Helal,Raja Bose,Wendong Li Book 2012 Springer Nature Switzerland AG 2012

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A Distributed Multi-key Generation Protocol with a New Complaint Management Strategy and the fact of not being identified to do illegal crimes. That is why several researches focus on implementing identity tracing to avoid the flaws related to privacy protection in Blockchain applications..In this paper, we propose a Distributed Multi-Key Generation (DMKG) protocol without private

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Reliability Evaluation of Inverter Based on Accelerated Degradation Test,r. Take the voltage as the accelerated stress, setting 0.8 as the linear growth proportion coefficient of stress levels, through the detection of the inverter IGBT collector emitter voltage state and diode voltage to judge the wear condition of the inverter. The accelerated model is obtained through

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The Yeast Three-Hybrid System for Protein Interactionsstanding the complex biological processes in the living cell. Several techniques have been developed to elucidate the conformation of large protein complexes, dynamic protein complex rearrangement and transient protein interactions. Yeast two-hybrid system is a well-established method to analyze bin

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Apoorva Shastri,Mihir Deshpandeuch schemes, which have been numerically evaluated and/or experimentally tested with discrete components or with a PIC (Photonic Integrated Circuit) realization of the crypto-systems. Finally, we outline some recent developments of the chaos secure transmission technique.

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Optimal Broadcast in Shared Spectrum Radio Networks,by contrast, solves the problem in . rounds, when ., and in . rounds, when . is smaller. It accomplishes this improvement by deploying a self-regulating relay strategy in which receivers that already know useful information coordinate themselves to efficiently assist the source’s broadcast. We conclude by proving these bounds tight for most cases.

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The Biofilm Model of Freter: A Review,om a large Thai medical text. Using the naïve Bayes as the base classifier for ensemble learning, the proposed method achieves the accuracy of 89.24%, which is an improvement of 9.91%, 7.54%, 5.25% over conventional naïve Bayes, non-ensemble version, and flat penalty setting profile.