Как мы готовимся в Празднику Весны

Эссе посвящено подготовке и проведению популярного в Китае народного праздника Весны.The essay is dedicated to the preparation and carrying out of popular Chinese folk Spring Festival

Learning nonparametric DAGs with incremental information via high-order HSIC

Score-based methods for learning Bayesain networks(BN) aim to maximizing the global score functions. However, if local variables have direct and indirect dependence simultaneously, the global optimization on score functions misses edges between variables with indirect dependent relationship, of which scores are smaller than those with direct dependent relationship. In this paper, we present an identifiability condition based on a determined subset of parents to identify the underlying DAG. By the identifiability condition, we develop a two-phase algorithm namely optimal-tuning (OT) algorithm to locally amend the global optimization. In the optimal phase, an optimization problem based on first-order Hilbert-Schmidt independence criterion (HSIC) gives an estimated skeleton as the initial determined parents subset. In the tuning phase, the skeleton is locally tuned by deletion, addition and DAG-formalization strategies using the theoretically proved incremental properties of high-order HSIC. Numerical experiments for different synthetic datasets and real-world datasets show that the OT algorithm outperforms existing methods. Especially in Sigmoid Mix model with the size of the graph being ${\rm\bf d=40}$, the structure intervention distance (SID) of the OT algorithm is 329.7 smaller than the one obtained by CAM, which indicates that the graph estimated by the OT algorithm misses fewer edges compared with CAM.Source code of the OT algorithm is available at https://github.com/YafeiannWang/optimal-tune-algorithm

The Production-oriented Approach to Teaching English Writing in Chinese Junior High Schools

With the acceleration of globalization, English communicative competence has become a necessary ability in modern society. The teaching of English writing in junior high schools not only improves students’ comprehensive language ability, but also lays a favorable foundation for their future English learning. Writing classes should highlight the importance of writing. But in fact, students’ actual output is neglected. The writing classes exist in name only. Based on the above questions, this research attempts to apply the Production-Oriented Approach (POA) in junior high school English writing teaching which is proposed by Chinese scholar Wen Qiufang. This research aims to find the effectiveness of POA in English writing teaching of Chinese junior high schools. We adopt the experimental research approaches, using classroom observation, interviews and tests to collect research data. Taking a class of 50 students in Grade 8 of junior high school as the research subjects, the researcher carries out the production-oriented English teaching experiment for one semester. It has been found: (1) Compared with traditional English instructions, POA can improve the English writing quality and comprehensive language using ability of junior high school students. (2) Both teachers and students believe that POA can stimulate students’ positive emotional experience, and students have more opportunities to use language in class. Through “enabling”, the quality of students’ language output has been significantly improved

Structural integrity of pipelines using reeling installation method

In the reeling method for installing offshore pipelines, several miles of line are wound onto a large diameter drum onshore mounted on a vessel. The vessel travels to the installation site where the line is unwound gradually installing it to the sea floor. This process involves repeated excursions into the plastic strain range of 1-3%. This study examines three structural integrity issues that arise from the process. A full-scale numerical modeling scheme incorporating nonlinear kinematic hardening plasticity is developed for the reeling/unreeling process. The first issue studied is the degradation of the cross section of pipelines and its effect on the collapse pressure. To capture the ovalization induced and assess its impact on the structural performance of the pipeline in deeper waters, the complete 3-D finite element model and a simplified 2-D model are presented to simulate reeling/unreeling of up to three cycles and subsequent collapsing under external pressure. Comparison of the results of such simulations with experiments highlights when fully a 3-D model is required and when the simpler 2-D model is adequate for evaluating the structural performance of a reeled pipe. The second issue investigated is the discontinuity in pipelines. In order to show how discontinuities in geometry and mechanical properties can lead to buckling and failure, the 3-D numerical model is applied to simulate the reeling/unreeling of pipelines. Discontinuities are shown to result in sharp local changes in accompanied by severe local straining and ovalization. These local effects can be reduced by increasing the applied tension at the expense of additional ovalization of the pipeline. The last part of the study examines the complication brought in by reeling pipes that exhibit Lüders bands. To simulate this process, the material is modeled by a stress–strain response with a negative slope over the extent of the Lüders deformation. During reeling with some back tension, Lüders banding produces inclined bands of localized deformation organized in clusters with distinctly different spatial distribution than that of pure bending. As a consequence, the ovalization develops axial undulations. The influences of problem variables are examined in a detailed parametric study.Engineering Mechanic

Voting Systems with Trust Mechanisms in Cyberspace: Vulnerabilities and Defenses

With the popularity of voting systems in cyberspace, there is growing evidence that current voting systems can be manipulated by fake votes. This problem has attracted many researchers working on guarding voting systems in two areas: relieving the effect of dishonest votes by evaluating the trust of voters, and limiting the resources that can be used by attackers, such as the number of voters and the number of votes. In this paper, we argue that powering voting systems with trust and limiting attack resources are not enough. We present a novel attack named as Reputation Trap (RepTrap). Our case study and experiments show that this new attack needs much less resources to manipulate the voting systems and has a much higher success rate compared with existing attacks. We further identify the reasons behind this attack and propose two defense schemes accordingly. In the first scheme, we hide correlation knowledge from attackers to reduce their chance to affect the honest voters. In the second scheme, we introduce robustness-of-evidence, a new metric, in trust calculation to reduce their effect on honest voters. We conduct extensive experiments to validate our approach. The results show that our defense schemes not only can reduce the success rate of attacks but also significantly increase the amount of resources an adversary needs to launch a successful attack