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As a fundamental phenomenon in nature, randomness has a wide range of applications in the fields of science and engineering. Among different types of random number generators (RNG), quantum random number generator (QRNG) is a kind of promising RNG as it can provide provable true random numbers based on the inherent randomness of fundamental quantum processes. Nevertheless, the randomness from a QRNG can be diminished (or even destroyed) if the devices (especially the entropy source devices) are not perfect or ill-characterized. To eliminate the practical security loopholes from the source, sourceindependent QRNGs, which allow the source to have arbitrary and unknown dimensions, have been introduced and become one of the most important semi-device-independent QRNGs. Herein a method that enables ultra-fast unpredictable quantum random number generation from quadrature fluctuations of quantum optical field without any assumptions on the input states is proposed. Particularly, to estimate a lower bound on the extractable randomness that is independent from side information held by an eavesdropper, a new security analysis framework is established based on the extremality of Gaussian states, which can be easily extended to design and analyze new semi-device-independent continuous variable QRNG protocols. Moreover, the practical imperfections of the QRNG including the effects of excess noise, finite sampling range, finite resolution and asymmetric conjugate quadratures are taken into account and quantitatively analyzed. Finally, the proposed method is experimentally demonstrated to obtain high secure random number generation rates of 15.07 Gbits/s in off-line configuration and can potentially achieve 6 Gbits/s by real-time post-processing.High Speed Continuous Variable Source-Independent Quantum Random Number Generation 2 IntroductionRandom numbers are of extreme importance for a wide range of applications in both scientific and commercial fields [1], such as numerical simulations, lottery games and cryptography. A significant example is the quantum key distribution (QKD), in which the true random numbers are essential for both quantum states preparation and detection to guarantee unconditional security [2][3][4]. Classical pseudo random number generators (PRNG), which are based on the computational algorithms, have been widely used in modern information systems. However, due to the deterministic and thus predictable features of the algorithms, PRNG are not suitable for certain applications where true randomness is required. Distinct from the PRNG, true random number generators (TRNG) extract randomness from physical random processes [5]. An important type of TRNGs is the quantum random number generator (QRNG), which is based on the intrinsic randomness of fundamental quantum processes and can provide truly unpredictable and irreproducible random numbers [6][7][8].The existing QRNG protocols can be mainly classified into three different categories as in Ref.[7], i.e. the practical, device-independent and semi-device-ind...

In neural abstractive summarization, the conventional sequence-to-sequence (seq2seq) model often suffers from repetition and semantic irrelevance. To tackle the problem, we propose a global encoding framework, which controls the information flow from the encoder to the decoder based on the global information of the source context. It consists of a convolutional gated unit to perform global encoding to improve the representations of the source-side information. Evaluations on the LCSTS and the English Gigaword both demonstrate that our model outperforms the baseline models, and the analysis shows that our model is capable of generating summary of higher quality and reducing repetition 1 .

Preface xi 1 Introduction 1 1.1 Interconnection of HV power system components 2 1.1.1 Alternating voltage systems 2 1.1.2 Direct-voltage systems 8 1.2 Insulation coordination 9 1.3 High-voltage test levels 1.3.1 Power-frequency voltages 1.3.2 Lightning-impulse voltages 1.3.3 Switching surges 1.3.4 Very fast transient tests (VFTT) 1.3.5 Direct-voltage tests 1.4 Power system developments 1.4.1 Reliability requirements 1.4.2 Condition of present assets 1.4.3 Extension of power system life 1.4.4 New systems and equipment 1.5 Future insulation monitoring requirements 1.6 Summary 1.7 References 1.8 Problems 18 2 Insulating materials utilized in power-system equipment 2.1 Review of insulating materials 2.1.1 Gases 2.1.2 Vacuum 2.1.3 Liquids 2.1.4 Solids vi

Designing 3D objects from scratch is difficult, especially when the user intent is fuzzy and lacks a clear target form. We facilitate design by providing reference and inspiration from existing model contexts. We rethink model design as navigating through different possible combinations of part assemblies based on a large collection of pre-segmented 3D models. We propose an interactive sketch-to-design system, where the user sketches prominent features of parts to combine. The sketched strokes are analysed individually, and more importantly, in context with the other parts to generate relevant shape suggestions via adesign galleryinterface. As a modelling session progresses and more parts get selected, contextual cues become increasingly dominant, and the model quickly converges to a final form. As a key enabler, we use pre-learned part-based contextual information to allow the user to quickly explore different combinations of parts. Our experiments demonstrate the effectiveness of our approach for efficiently designing new variations from existing shape collections.

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