护理分层管理的现状与发展趋势

Through implementing hierarchical management and monitor, improving and perfecting the hospital nurse training mechanism, implementing wages and labor outcomes in association with mechanism, further cultivating high-quality and high-level nursing management personnel, constantly improving quality, which maximize all the nursing staff 's enthusiasm and creativity, enhance the cohesion of nursing team, and improve the quality of hospital care.通过实施分层管理，逐层监控，完善和健全医院护士培训机制，实现工资待遇与劳动成果挂钩机制，进一步培养高素质、高层次的护理管理人才，持续质量改进，从而最大限度地发挥了全体护理人员的积极性和创造性，提升了护理队伍的凝聚力，提高了医院的护理质量

Look, Listen and Learn - A Multimodal LSTM for Speaker Identification

Speaker identification refers to the task of localizing the face of a person who has the same identity as the ongoing voice in a video. This task not only requires collective perception over both visual and auditory signals, the robustness to handle severe quality degradations and unconstrained content variations are also indispensable. In this paper, we describe a novel multimodal Long Short-Term Memory (LSTM) architecture which seamlessly unifies both visual and auditory modalities from the beginning of each sequence input. The key idea is to extend the conventional LSTM by not only sharing weights across time steps, but also sharing weights across modalities. We show that modeling the temporal dependency across face and voice can significantly improve the robustness to content quality degradations and variations. We also found that our multimodal LSTM is robustness to distractors, namely the non-speaking identities. We applied our multimodal LSTM to The Big Bang Theory dataset and showed that our system outperforms the state-of-the-art systems in speaker identification with lower false alarm rate and higher recognition accuracy.Comment: The 30th AAAI Conference on Artificial Intelligence (AAAI-16

Dynamical analysis of wind turbine blades based on harmonic response

As the forces applied on the wind turbine blade are irregular, the deformation and concentrated stress of the blade may vary with the load and excitation. And the lamination of composite materials is critical to blade design, it directly affects the performance and power of wind power plants. In this paper, the response characteristics of the wind turbine blade is analyzed by the application of the harmonic response method under different ply angles. Through the simulation results, the performance of the actual blade is estimated, and the rationality of this design is judged. The results demonstrate that the blade displacement response amplitude is the minimum when ply angle is 45°. It is also found that the maximum displacement response occurs in the Y direction (i.e. parallel to the flow direction) by analyzing the displacement of each section in the blade, while the maximum stress is located at blade root