This paper provides an overview of Advanced Practice Nursing(APN)in the USA,Canada,Australia and Hong Kong.It is based upon documents presented to the China Medical Board(CMB)China Nursing Network(CNN)as background fo...This paper provides an overview of Advanced Practice Nursing(APN)in the USA,Canada,Australia and Hong Kong.It is based upon documents presented to the China Medical Board(CMB)China Nursing Network(CNN)as background for discussions held by the CNN in Shanghai.It discusses the APN role in these countries and regions according to topics identified by the CNN.These are APN educational preparation;role legitimacy;capacity requirements;scope of practice,domains of activities and limited rights for prescription and referral;professional promotion ladder;accreditation system;and,perfor-mance evaluation system.Both Canada and Australia have adapted many aspects of the USA model of APN to fit their specific legislative requirements and local conditions.Hong Kong has taken a different path which may be of interest in the Chinese context.展开更多
The famous Embrechts-Goldie-Veraverbeke formula shows that, in the classical Cramér-Lundberg risk model, the ruin probabilities satisfy $R(x, \infty ) \sim \rho ^{ - 1} \bar F_e (x)$ if the claim sizes are heavy-...The famous Embrechts-Goldie-Veraverbeke formula shows that, in the classical Cramér-Lundberg risk model, the ruin probabilities satisfy $R(x, \infty ) \sim \rho ^{ - 1} \bar F_e (x)$ if the claim sizes are heavy-tailed, where Fe denotes the equilibrium distribution of the common d.f. F of the i.i.d. claims, ? is the safety loading coefficient of the model and the limit process is for x → ∞. In this paper we obtain a related local asymptotic relationship for the ruin probabilities. In doing this we establish two lemmas regarding the n-fold convolution of subexponential equilibrium distributions, which are of significance on their own right.展开更多
As a major component of speech signal processing, speech emotion recognition has become increasingly essential to understanding human communication. Benefitting from deep learning, many researchers have proposed vario...As a major component of speech signal processing, speech emotion recognition has become increasingly essential to understanding human communication. Benefitting from deep learning, many researchers have proposed various unsupervised models to extract effective emotional features and supervised models to train emotion recognition systems. In this paper, we utilize semi-supervised ladder networks for speech emotion recognition. The model is trained by minimizing the supervised loss and auxiliary unsupervised cost function. The addition of the unsupervised auxiliary task provides powerful discriminative representations of the input features, and is also regarded as the regularization of the emotional supervised task. We also compare the ladder network with other classical autoencoder structures. The experiments were conducted on the interactive emotional dyadic motion capture (IEMOCAP) database, and the results reveal that the proposed methods achieve superior performance with a small number of labelled data and achieves better performance than other methods.展开更多
文摘This paper provides an overview of Advanced Practice Nursing(APN)in the USA,Canada,Australia and Hong Kong.It is based upon documents presented to the China Medical Board(CMB)China Nursing Network(CNN)as background for discussions held by the CNN in Shanghai.It discusses the APN role in these countries and regions according to topics identified by the CNN.These are APN educational preparation;role legitimacy;capacity requirements;scope of practice,domains of activities and limited rights for prescription and referral;professional promotion ladder;accreditation system;and,perfor-mance evaluation system.Both Canada and Australia have adapted many aspects of the USA model of APN to fit their specific legislative requirements and local conditions.Hong Kong has taken a different path which may be of interest in the Chinese context.
基金This work was supported by the National Natural Science Foundation of China (Grant No. 10071081).
文摘The famous Embrechts-Goldie-Veraverbeke formula shows that, in the classical Cramér-Lundberg risk model, the ruin probabilities satisfy $R(x, \infty ) \sim \rho ^{ - 1} \bar F_e (x)$ if the claim sizes are heavy-tailed, where Fe denotes the equilibrium distribution of the common d.f. F of the i.i.d. claims, ? is the safety loading coefficient of the model and the limit process is for x → ∞. In this paper we obtain a related local asymptotic relationship for the ruin probabilities. In doing this we establish two lemmas regarding the n-fold convolution of subexponential equilibrium distributions, which are of significance on their own right.
基金supported by National Natural Science Foundation of China(Nos.61425017 and 61773379)the National Key Research&Development Plan of China(No.2017YFB1002804)
文摘As a major component of speech signal processing, speech emotion recognition has become increasingly essential to understanding human communication. Benefitting from deep learning, many researchers have proposed various unsupervised models to extract effective emotional features and supervised models to train emotion recognition systems. In this paper, we utilize semi-supervised ladder networks for speech emotion recognition. The model is trained by minimizing the supervised loss and auxiliary unsupervised cost function. The addition of the unsupervised auxiliary task provides powerful discriminative representations of the input features, and is also regarded as the regularization of the emotional supervised task. We also compare the ladder network with other classical autoencoder structures. The experiments were conducted on the interactive emotional dyadic motion capture (IEMOCAP) database, and the results reveal that the proposed methods achieve superior performance with a small number of labelled data and achieves better performance than other methods.
