Study on Three Positions Framing Kindergarten Play-Based Curriculum in China: Through Analyses of the Attitudes of Teachers to Early Linguistic Education

Since 2001, there is a hot debate on Curriculum Reform of Elementary Education (CRED) in China which is called a debate between Child-centered and Rationalism. The policies of CRED adovates play-based model and since 2017 focuses on Chinese traditional culture learning. However, some people believe play is opposed to linguistic education and the moon in the west is more round than in China. Operating in the paradoxes, Chinese kindergarten teachers always are faced with dilemmas: should the teacher obey the government’s guidance, or satisfy parents’ English learning preference and literacy readiness oriented requirements? Few studies have examined how Chinese kindergarten teachers struggled for early literacy and linguistic education. In this article we examined twenty teachers’ understandings on play-based curriculum and play-literacy relationships. Comparing with the two popular positions toward Chinese play-based linguistic curriculum reforms, Chinese kindergarten teachers tend to hold a golden means. With the professional development of the kindergarten teacher, education approaches in Chinese kindergarten education based on play and local cultures will be used more often and more extensively. Under such circumstances, the English teaching and learning at the kindergarten level is also believed very important to cultivate global citizens and Chinese national citizens

Experimental Analysis of Crop Insurance - Cognitive Bias in Decision Making

This study is set out to explore how cognitive biases, gambler’s fallacy and hot hand effect, exert an effect on individual crop insurance purchase decision. A laboratory experiment comprised of two separate games was used to establish an insurance purchase environment to induce individual’s behavior. The gambler’s fallacy and hot hand effect failed to be found in the experiment. But the subjects’ perceived probability of loss plays a significant role in determine their purchase decisions—the higher probability they predicted, the more likely to buy insurance they were. It is also fascinating to find that the longer the exposure to random risks the subjects had, the more willing to engage in insurance protection they were

Data-driven model-based approaches to condition monitoring and improving power output of wind turbines

The development of the wind farm has grown dramatically in worldwide over the past 20 years. In order to satisfy the reliability requirement of the power grid, the wind farm should generate sufficient active power to make the frequency stable. Consequently, many methods have been proposed to achieve optimizing wind farm active power dispatch strategy. In previous research, it assumed that each wind turbine has the same health condition in the wind farm, hence the power dispatch for healthy and sub-healthy wind turbines are treated equally. It will accelerate the sub-healthy wind turbines damage, which may leads to decrease generating efficiency and increases operating cost of the wind farm. Thus, a novel wind farm active power dispatch strategy considering the health condition of wind turbines and wind turbine health condition estimation method are the proposed. A modelbased CM approach for wind turbines based on the extreme learning machine (ELM) algorithm and analytic hierarchy process (AHP) are used to estimate health condition of the wind turbine. Essentially, the aim of the proposed method is to make the healthy wind turbines generate power as much as possible and reduce fatigue loads on the sub-healthy wind turbines. Compared with previous methods, the proposed methods is able to dramatically reduce the fatigue loads on subhealthy wind turbines under the condition of satisfying network operator active power demand and maximize the operation efficiency of those healthy turbines. Subsequently, shunt active power filters (SAPFs) are used to improve power quality of the grid by mitigating harmonics injected from nonlinear loads, which is further to increase the reliability of the wind turbine system

FlexAuc: Serving Dynamic Demands in a Spectrum Trading Market with Flexible Auction

In secondary spectrum trading markets, auctions are widely used by spectrum holders (SHs) to redistribute their unused channels to secondary wireless service providers (WSPs). As sellers, the SHs design proper auction schemes to stimulate more participants and maximize the revenue from the auction. As buyers, the WSPs determine the bidding strategies in the auction to better serve their end users. In this paper, we consider a three-layered spectrum trading market consisting of the SH, the WSPs and the end users. We jointly study the strategies of the three parties. The SH determines the auction scheme and spectrum supplies to optimize its revenue. The WSPs have flexible bidding strategies in terms of both demands and valuations considering the strategies of the end users. We design FlexAuc, a novel auction mechanism for this market to enable dynamic supplies and demands in the auction. We prove theoretically that FlexAuc not only maximizes the social welfare but also preserves other nice properties such as truthfulness and computational tractability.Comment: 11 pages, 7 figures, Preliminary version accepted in INFOCOM 201

Weighted estimation of the dependence function for an extreme-value distribution

Bivariate extreme-value distributions have been used in modeling extremes in environmental sciences and risk management. An important issue is estimating the dependence function, such as the Pickands dependence function. Some estimators for the Pickands dependence function have been studied by assuming that the marginals are known. Recently, Genest and Segers [Ann. Statist. 37 (2009) 2990-3022] derived the asymptotic distributions of those proposed estimators with marginal distributions replaced by the empirical distributions. In this article, we propose a class of weighted estimators including those of Genest and Segers (2009) as special cases. We propose a jackknife empirical likelihood method for constructing confidence intervals for the Pickands dependence function, which avoids estimating the complicated asymptotic variance. A simulation study demonstrates the effectiveness of our proposed jackknife empirical likelihood method.Comment: Published in at http://dx.doi.org/10.3150/11-BEJ409 the Bernoulli (http://isi.cbs.nl/bernoulli/) by the International Statistical Institute/Bernoulli Society (http://isi.cbs.nl/BS/bshome.htm