人体热调节的有限元分析

本文根据人体的热调节机制建立了二维人体热调节的有限元模型，并设计了相应的实验对该模型进行了验证，实验结果与计算结果吻合较好，本模型对于以人体－环境热交换为内容的工程实践和理论研究有较高的应用价值。     

Distribution of chlorophyll and harmful algal blooms (HABs): A review on space based studies in the coastal environments of Chinese marginal seas

Monitoring of spatial and temporal distribution of chlorophyll (Chl-a) concentrations in the aquatic milieu is always challenging and often interesting. However, the recent advancements in satellite digital data play a significant role in providing outstanding results for the marine environmental investigations. The present paper is aimed to review ‘remote sensing research in Chinese seas’ within the period of 24 years from 1978 to 2002. Owing to generalized distributional pattern, the Chl-a concentrations are recognized high towards northern Chinese seas than the southern. Moreover, the coastal waters, estuaries, and upwelling zones always exhibit relatively high Chl-a concentrations compared with offshore waters. On the basis of marine Chl-a estimates obtained from satellite and other field measured environmental parameters, we have further discussed on the applications of satellite remote sensing in the fields of harmful algal blooms (HABs), primary production and physical oceanographic currents of the regional seas. Concerned with studies of HABs, satellite remote sensing proved more advantageous than any other conventional methods for large-scale applications. Probably, it may be the only source of authentic information responsible for the evaluation of new research methodologies to detect HABs. At present, studies using remote sensing methods are mostly confined to observe algal bloom occurrences, hence, it is essential to coordinate the mechanism of marine ecological and oceanographic dynamic processes of HABs using satellite remote sensing data with in situ measurements of marine environmental parameters. The satellite remote sensing on marine environment and HABs is believed to have a great improvement with popular application of technology.     

Results from the ESA SREM monitors and comparison with existing radiation belt models

The Standard Radiation Environment Monitor (SREM) is a simple particle detector developed for wide application on ESA satellites. It measures high-energy protons and electrons of the space environment with a 20° angular resolution and limited spectral information. Of the ten SREMs that have been manufactured, four have so far flown. The first model on STRV-1c functioned well until an early spacecraft failure. The other three are on-board, the ESA spacecraft INTEGRAL, ROSETTA and PROBA-1. Another model is flying on GIOVE-B, launched in April 2008 with three L-2 science missions to follow: both Herschel and Planck in 2008, and GAIA in 2011). The diverse orbits of these spacecraft and the common calibration of the monitors provides a unique dataset covering a wide range of B-L* space, providing a direct comparison of the radiation levels in the belts at different locations, and the effects of geomagnetic shielding. Data from the PROBA/SREM and INTEGRAL/IREM are compared with existing radiation belt models.     

Solar activity prediction studies and services in NAOC

Solar activity prediction services started in 1960’s in National Astronomical Observatories, Chinese Academy of Sciences (NAOC). As one of the members of the International Space Environment Service (ISES), Regional Warning Center of China (RWC-China) was set up in 1990’s. Solar Activity Prediction Center (SAPC), as one of the four sub-centers of RWC-China, is located in NAOC. Solar activity prediction studies and services in NAOC cover short-term, medium-term, and long-term forecast of solar activities. Nowadays, certain prediction models, such as solar X-ray flare model, solar proton event model, solar 10 cm radio flux model, have been established for the practical prediction services. Recently, more and more physical analyses are introduced in the studies of solar activity prediction, such as the magnetic properties of solar active regions and magnetic structure of solar atmosphere. Besides traditional statistics algorithms, Machine Learning and Artificial Intelligence techniques, such as Support Vector Machine (SVM) method, are employed in the establishment of forecast models. A Web-based integrated platform for solar activity data sharing and forecast distribution is under construction.     

改进体育课堂教学质量的几点思考

本文对现在体育教学方法提出了几点改进意见。目的是为了提高体育课的教学质量，增强学生的身体健康。     

基于任务科目的直升机飞行品质评定试飞技术研究

主要对ADS-33E中飞行品质评定的要求进行分析,从任务科目、响应类型和可用感示环境3个维度进行飞行品质的等级评定研究,提出了直升机飞行品质综合评定的试飞技术研究思路,并对某型号直升机的试飞结果和有关问题进行了初步分析。     

洗出滤波算法在飞行模拟器中的应用

介绍了六自由度运动平台的洗出滤波算法及其在飞行器地面滑跑阶段的实现。根据飞行仿真模块的输出,通过坐标变换、比例限制、信号洗出和滤波等,形成运动平台的驱动信号。该算法在不增加系统硬件的前提下,充分利用液压缸现有行程,逼真地模拟飞机俯仰、滚转、偏航、升降、纵向和侧向平移运动。     

编制摸拟器设计和性能数据要求的初步考虑

在研制飞行模拟器时，飞行模拟器的设计和性能数据是必需的。这些数据不仅是形成满足飞行模拟器各种规范和标准要求的基础，而且也是构成模拟器逼真度要求的基础。根据国际航空运输协会的要求，初步讨论了编制飞行模拟器设计和性能数据要求所考虑的因素。     

多功能实验室环境条件保障装置的设计

介绍了维持计量检定工作环境条件保障装置的设计方法，该装置可实现实验室温，湿度的测量与控制，有方便的通讯接口便于与计算机连接，并附加有多点时间控制电路以实现提前预热仪器设备提高工作效率的功能。     

基于深度增强学习的卫星姿态控制方法

针对卫星在执行丢弃载荷或捕获目标等复杂任务时遭遇的姿态突然发生变化的问题,采用深度增强学习方法对卫星姿态进行控制,使卫星恢复稳定状态。具体来说,首先搭建飞行器的姿态动力学环境,并将连续的控制力矩输出离散化,然后采用Deep Q Network算法进行卫星自主姿态控制训练,以姿态角速度趋于稳定作为奖励获得离散行为的最优智能输出。仿真试验表明,面向空间卫星姿态控制的深度增强学习算法能够在卫星受到突发随机扰动后稳定卫星姿态,并能有效解决传统PD控制器依赖被控对象质量参数的难题。所提出的方法采用自主学习的方式对卫星姿态进行控制,具有很强的智能性和一定的普适性,在未来卫星执行复杂空间任务中的智能控制方面有着很好的应用潜力。