RawNet: Fast End-to-End Neural Vocoder

Neural networks based vocoders have recently demonstrated the powerful ability to synthesize high quality speech. These models usually generate samples by conditioning on some spectrum features, such as Mel-spectrum. However, these features are extracted by using speech analysis module including some processing based on the human knowledge. In this work, we proposed RawNet, a truly end-to-end neural vocoder, which use a coder network to learn the higher representation of signal, and an autoregressive voder network to generate speech sample by sample. The coder and voder together act like an auto-encoder network, and could be jointly trained directly on raw waveform without any human-designed features. The experiments on the Copy-Synthesis tasks show that RawNet can achieve the comparative synthesized speech quality with LPCNet, with a smaller model architecture and faster speech generation at the inference step.Comment: Submitted to Interspeech 2019, Graz, Austri

Information Environment and Gains from Corporate Takeovers

Motivated by the inadequate research in understanding the determinants of takeover wealth creation, as well as the theoretical and practical importance of information environment in the takeover market, this thesis examines the wealth effects of information environment on UK takeovers. It regards information dissemination as a process inherent in takeover announcements, along which, factors capturing the characteristics of information sender, information content, information recipient and market condition, are addressed to form three key research issues. First considered are the wealth effects of misvaluation conditional on information signalled by payment and financing methods of takeovers. The results indicate that a price run-up via an upward revaluation follows undervalued bidders releasing good news (non-equity financed cash deals). Secondly, this research is concerned with the wealth effects of investor sentiment, towards the information released, at a whole market and individual firm level. The results show that high investor sentiment drives up target firms’ announcement returns and further causes an increase in takeover premium. The last issue addressed is the relation between information asymmetry and gains to frequent bidders. The results suggest that information asymmetry declines in a merger series while serial non-equity financed cash deals generate decreasing bidders’ announcement returns since the scale of their upward revaluations continually decreases with subsequent announcements. These three groups of results form a mechanism of information environment’s wealth effect as follows. Takeover announcements release new information. With the arrival of new information investors update their assessments of firm value. The scale of revaluation is determined by a firm’s information asymmetry, the direction of it depends on firm misvaluation, information signalled by takeover announcements and the investor sentiment in interpreting this information

Contribution au réglage de la tension sur un réseau HTA avec producteurs. Apport de la flexibilité de la demande.

Growth of distributed generations (DG) in actual distribution networks will bring voltage issues that cannot be fixed by conventional voltage control means. For the sake of network safety, the size of DG and load in a distribution network is limited by the network parameters. The research described in this thesis aims to propose a voltage control strategy on distribution networks using the flexibility of demand. The voltage control means will consist of the on load tap changer (OLTC), the regulation of DG, and flexible demand. A centralized optimization of MINLP type is proposed to coordinate these voltage control means. It shows if it is not able to remove the voltage constraint with OLTC and reactive power regulation, then it must reduce the active power of DG. In order not to reduce active power of DG, the flexible demand is considered as an active source to take part in voltage control. The demand response (DR) modulation using thermal loads is thus proposed for voltage control. For the thermal load, the cold load pick-up (CLPU) effect must be taken into account in order not to affect the voltage profile after DR action. This work allows us to consider a voltage control strategy more active in smart distribution network and improve the flexibility of network.L’intégration des producteurs décentralisés (DG) dans un réseau de distribution peut modifier le profil de tension et influencer le réglage de tension conventionnel. Pour le bon fonctionnement du réseau, le raccordement des DG ainsi que les charges grosses sont limités par le dimensionnement du réseau. Les travaux de cette thèse ont pour but de proposer une approche du réglage de tension dans un réseau de distribution avec producteur, en appuyant sur la flexibilité de la demande. Les moyens de réglage de tension seront constitués du régleur en charge (OLTC), la régulation de DG ainsi que la demande flexible. Une optimisation centralisée de type MINLP est proposée pour coordonner ces moyens de réglage. Il est montré que si les moyens de l’OLTC et de la puissance réactive ne suffissent pas de lever la contrainte de tension, il faut réduire la puissance active de producteur. Pour le gain de producteur, la demande flexible peut être considérée comme une source active. La modulation de « demand response » (DR) utilisant les charges thermiques est alors proposée au réglage de tension. L’effet de rebond est pris en compte pour les charges thermiques afin de ne pas affecter le profil de tension après l’action de DR. Ces travaux permettent d’envisager un réglage de tension plus active dans le réseau intelligent et augmenter la flexibilité du réseau

Short-term PV power prediction based on the 24 traditional Chinese solar terms and adaboost-GA-BP model

High-precision, short-term power forecasting for photovoltaic systems not only reduces unnecessary energy consumption but also provides power grid security. To this end, in this paper we propose a photovoltaic short-term power forecasting model based on the division of data of the 24 traditional Chinese solar terms and the Adaboost-GA-BP model. The 24 solar terms were condensed from the laws of meteorology, phenology, and seasonal changes to adapt to agricultural times in ancient China and have become intangible cultural heritage. This article first analyzes the numerical characteristics of meteorological factors and demonstrates their close correlation with the turning points of the 24 solar terms. Second, using Standardized Euclidean Distance and Spearman’s Correlation Coefficients to analyze data similarity between the Gregorian half-months and the 24 solar terms divisions for comparative analysis purposes, it is shown that the intragroup data under the division of the 24 solar terms have a higher similarity, leading to an average decrease of 15.68%, 40.57%, 14.68%, and 14.64% in the MAE, MSE, RMSE, and WMAPE of the predicted results, respectively. Finally, based on the data derived from the 24 solar terms, the combined algorithm was compared with the Adaboost-GA-BP model and then was verified. The genetic algorithm and Adaboost were used to optimize the BP neural network algorithm in initial value assignment and neural network structure, resulting in a 23.42%, 18.12%, and 22.28% reduction in the mean values of the MAE, RMSE, and WMAPE of the predicted results, respectively. Analysis of the results show that using the Adaboost-GA-BP model based on the 24 solar terms for short-term photovoltaic power forecasting can improve the accuracy of photovoltaic power forecasting and significantly improve the predictive performance of the model

4K4D: Real-Time 4D View Synthesis at 4K Resolution

This paper targets high-fidelity and real-time view synthesis of dynamic 3D scenes at 4K resolution. Recently, some methods on dynamic view synthesis have shown impressive rendering quality. However, their speed is still limited when rendering high-resolution images. To overcome this problem, we propose 4K4D, a 4D point cloud representation that supports hardware rasterization and enables unprecedented rendering speed. Our representation is built on a 4D feature grid so that the points are naturally regularized and can be robustly optimized. In addition, we design a novel hybrid appearance model that significantly boosts the rendering quality while preserving efficiency. Moreover, we develop a differentiable depth peeling algorithm to effectively learn the proposed model from RGB videos. Experiments show that our representation can be rendered at over 400 FPS on the DNA-Rendering dataset at 1080p resolution and 80 FPS on the ENeRF-Outdoor dataset at 4K resolution using an RTX 4090 GPU, which is 30x faster than previous methods and achieves the state-of-the-art rendering quality. Our project page is available at https://zju3dv.github.io/4k4d/.Comment: Project Page: https://zju3dv.github.io/4k4

Synthèse CIRED 2015 Rapport sur le Congrès International des Réseaux Electriques de Distribution

International audienceUne synthèse globale de la conférence CIRED 2015 fait par des doctorants de plusieurs écoles

Combined analysis of transcriptome and metabolome reveals that sugar, lipid, and phenylpropane metabolism are essential for male fertility in temperature-induced male sterile rice

Photoperiod- and thermosensitive genic male sterility (PTGMS) rice is a vital germplasm resource consisting of two-line hybrid rice in which light and temperature strictly control their fertility changes. Variable environmental conditions present huge risks to the two-lines hybrid seed production. Explaining the regulatory mechanism of male fertility in rice PTGMS lines is an essential prerequisite to ensuring food security production. A group of near-isogenic lines (NILs) of a rice PTGMS line unique to this research group was used for this study. These lines have the same genetic background and regulate male fertility by responding to different temperature changes. Transcriptomic analysis revealed that 315 upregulated genes and 391 regulated genes regulated male fertility in response to temperature changes, and differentially expressed genes (DEGs) were mainly characterized in enrichment analysis as having roles in the metabolic pathways of sugar, lipid and phenylpropanoid. Electron microscopy analysis revealed that a lack of starch accumulation in sterile pollen grains induced by high temperature, with an abnormal exine development and a lack of inner pollen grains. Defective processes for sporopollenin synthesis, sporopollenin transport and pollen wall formation in sterile anthers were verified using qPCR. Targeted metabolomics analysis revealed that most lipids (phospholipids, sphingolipids and fatty acids) and flavonoids (flavones and flavanones) were upregulated in fertile anthers and involved in pollen wall development and male fertility formation, while lignin G units and C-type lignin were the major contributors to pollen wall development. The coding genes for trehalose 6-phosphate phosphatase, beta-1,3-glucanase, phospholipase D and 4-coumarate-CoA ligase are considered essential regulators in the process of male fertility formation. In conclusion, our results indicated that the expression of critical genes and accumulation of metabolites in the metabolism of sugar, lipid, and phenylpropanoid are essential for male fertility formation. The results provide new insights for addressing the negative effects of environmental variation on two-line hybrid rice production