A method and system for unified authentication management and control of power secondary equipment based on blockchain

Blockchain technology is an advanced database mechanism that allows transparent sharing of information across corporate networks. By analyzing the insufficiency and improvement plan of the operation and maintenance safety management of power secondary equipment, it is proposed to use the operation and maintenance management and control system to select EOS as the underlying scheme of the blockchain, and discuss it based on a trusted blockchain network system

Climate change impact on China food security in 2050

Climate change is now affecting global agriculture and food production worldwide. Nonetheless the direct link between climate change and food security at the national scale is poorly understood. Here we simulated the effect of climate change on food security in China using the CERES crop models and the IPCC SRES A2 and B2 scenarios including CO2 fertilization effect. Models took into account population size, urbanization rate, cropland area, cropping intensity and technology development. Our results predict that food crop yield will increase +3-11 % under A2 scenario and +4 % under B2 scenario during 2030-2050, despite disparities among individual crops. As a consequence China will be able to achieve a production of 572 and 615 MT in 2030, then 635 and 646 MT in 2050 under A2 and B2 scenarios, respectively. In 2030 the food security index (FSI) will drop from +24 % in 2009 to -4.5 % and +10.2 % under A2 and B2 scenarios, respectively. In 2050, however, the FSI is predicted to increase to +7.1 % and +20.0 % under A2 and B2 scenarios, respectively, but this increase will be achieved only with the projected decrease of Chinese population. We conclude that 1) the proposed food security index is a simple yet powerful tool for food security analysis; (2) yield growth rate is a much better indicator of food security than yield per se; and (3) climate change only has a moderate positive effect on food security as compared to other factors such as cropland area, population growth, socio-economic pathway and technology development. Relevant policy options and research topics are suggested accordingly

Pixel Sampling for Style Preserving Face Pose Editing

The existing auto-encoder based face pose editing methods primarily focus on modeling the identity preserving ability during pose synthesis, but are less able to preserve the image style properly, which refers to the color, brightness, saturation, etc. In this paper, we take advantage of the well-known frontal/profile optical illusion and present a novel two-stage approach to solve the aforementioned dilemma, where the task of face pose manipulation is cast into face inpainting. By selectively sampling pixels from the input face and slightly adjust their relative locations with the proposed ``Pixel Attention Sampling" module, the face editing result faithfully keeps the identity information as well as the image style unchanged. By leveraging high-dimensional embedding at the inpainting stage, finer details are generated. Further, with the 3D facial landmarks as guidance, our method is able to manipulate face pose in three degrees of freedom, i.e., yaw, pitch, and roll, resulting in more flexible face pose editing than merely controlling the yaw angle as usually achieved by the current state-of-the-art. Both the qualitative and quantitative evaluations validate the superiority of the proposed approach

Reconstructive and Discriminative Sparse Representation for Visual Object Categorization

International audienceSparse representation was originally used in signal processing as apowerful tool for acquiring, representing and compressinghigh-dimensional signals. Recently, motivated by the great successes it hasachieved, it has become a hot research topic in the domainof computer vision and pattern recognition. In this paper, we propose to adapt sparse representation to the problem of Visual Object Categorization which aims at predicting whether at least one or several objects of some given categories are present in an image. Thus, we have elaborated a reconstructive and discriminative sparserepresentation of images, which integrates a discriminative term, such asFisher discriminative measure or the output of a SVM classifier, intothe standard sparse representation objective function in order tolearn a reconstructive and discriminative dictionary.Experiments carried out on the SIMPLIcity image dataset have clearlyrevealed that our reconstructive and discriminative approach has gained an obviousimprovement of the classification accuracy compared to standard SVMusing image features as input. Moreover, the results have shown that our approach is more efficient than a sparse representation being only reconstructive, which indicates that adding a discriminative term forconstructing the sparse representation is more suitable for thecategorization purpose

Introduction to the special section: the impact of Covid-19 and post-pandemic recovery: China and the world economy

It is indisputable that the Covid-19 pandemic has shaken the world economy and indeed panglobal society in many dimensions. In this Introduction to our Special Section, we examine the dynamics involved, particularly in relation to China and the world economy, and the response policies utilised for post-pandemic recovery based on detailed and critical comments and summaries of the excellent papers collected in this volume. We highlight the impact of the pandemic on global supply chains with a particular focus on China's trade, foreign direct investment, digitalisation and innovation, its cooperation with its major trade partners, as well as the economic outlook of the Chinese economy against the backlock of the pandemic and US-China tensions. How other countries responded to the pandemic is also brought in so as to understand China's response in a broad context and the role of culture and institutions in the process