“通信原理”实验课程的改进与探索

通信原理课程的实验教学环节是课程的重要组成部分,合理改进和设计实验课程,是加深学生对课程的理解和提高学生能力的必要手段。本文就当前通信原理实验课程存在的问题和改进方法进行探讨分析,并在教学中加以运用,取得了较好的效果。     

Equatorial aurora: the aurora-like airglow in the negative magnetic anomaly

The most fantastic optical phenomena in the Earth''s upper atmosphere are the auroras. They are highly informative indicators of solar activity, geomagnetic activity, upper atmospheric structures and dynamics, and magnetospheric energetic particles. An area where the geomagnetic field differs significantly from the expected symmetric dipole, such as at the South Atlantic Anomaly, where the magnetic field intensity is low, gives rise to stronger precipitation of energetic particles into the upper atmosphere. Impact excitation and the subsequent airglow emissions exhibit aurora-like dynamic signatures. Nomenclatures of nonpolar aurora or equatorial auroras are similar to those used with the polar auroras owing to their similar excitation mechanisms. This paper provides an overview of the knowledge and the challenges concerning auroral activity at the South Atlantic Anomaly, or more generally, at the negative magnetic anomaly. We emphasize systematic investigation of the equatorial auroras to reveal the temporal and spatial evolution of the magnetic anomaly and the behaviour of energetic particles in near-Earth space.     

Predicting future dynamics from short-term time series using an Anticipated Learning Machine

Predicting time series has significant practical applications over different disciplines. Here, we propose an Anticipated Learning Machine (ALM) to achieve precise future-state predictions based on short-term but high-dimensional data. From non-linear dynamical systems theory, we show that ALM can transform recent correlation/spatial information of high-dimensional variables into future dynamical/temporal information of any target variable, thereby overcoming the small-sample problem and achieving multistep-ahead predictions. Since the training samples generated from high-dimensional data also include information of the unknown future values of the target variable, it is called anticipated learning. Extensive experiments on real-world data demonstrate significantly superior performances of ALM over all of the existing 12 methods. In contrast to traditional statistics-based machine learning, ALM is based on non-linear dynamics, thus opening a new way for dynamics-based machine learning.     

Olivine-norite rock detected by the lunar rover Yutu-2 likely crystallized from the SPA-impact melt pool

Chang’E-4 landed in the South Pole-Aitken (SPA) basin, providing a unique chance to probe the composition of the lunar interior. Its landing site is located on ejecta strips in Von Kármán crater that possibly originate from the neighboring Finsen crater. A surface rock and the lunar regolith at 10 sites along the rover Yutu-2 track were measured by the onboard Visible and Near-Infrared Imaging Spectrometer in the first three lunar days of mission operations. In situ spectra of the regolith have peak band positions at 1 and 2 μm, similar to the spectral data of Finsen ejecta from the Moon Mineralogy Mapper, which confirms that the regolith''s composition of the landing area is mostly similar to that of Finsen ejecta. The rock spectrum shows similar band peak positions, but stronger absorptions, suggesting relatively fresh exposure. The rock may consist of 38.1 ± 5.4% low-Ca pyroxene, 13.9 ± 5.1% olivine and 48.0 ± 3.1% plagioclase, referred to as olivine-norite. The plagioclase-abundant and olivine-poor modal composition of the rock is inconsistent with the origin of the mantle, but representative of the lunar lower crust. Alternatively, the rock crystallized from the impact-derived melt pool formed by the SPA-impact event via mixing the lunar crust and mantle materials. This scenario is consistent with fast-cooling thermal conditions of a shallow melt pool, indicated by the fine to medium-sized texture (<3 mm) of the rock and the SPA-impact melting model [Icarus 2012; 220: 730–43].     

自然资源要素综合观测指标体系探讨

为了实现自然资源的规范管理和高效利用,需要对其要素进行长期、连续、稳定的综合观测,从而获得相关的基础数据,掌握资源种类、数量、质量和资源间相互作用过程信息。由于目前中国没有形成统一的自然资源观测指标体系,导致不同区域间资源观测和管理存在差异,使得国家尺度上对自然资源的规范化管理和合理利用难以实现。因此,亟需构建一套适用于国家尺度、科学、系统、规范的自然资源要素综合观测指标体系。本文以解决认识自然生态变化规律、预判发展趋势的基础数据支撑能力不足问题为出发点,参考国内外现有观测（监测）指标体系,确立了自然资源要素综合观测指标体系建立和选取的基本原则;在自然资源要素分类的基础上,采用正、反演相结合、模块化等构建方法,建立了由36个归类模块、6个资源要素综合观测系统和若干个赋能模块构成的自然资源要素综合观测指标体系。通过建立大气-地表-地下多层次,个体-景观-区域多尺度的立体化综合观测网,获取自然资源要素数据,以期实现对自然资源的精细化管理、评价和利用。     

北京郊区参与型体育旅游资源时空演化特征及影响因素

体育旅游已成为中国当前体育产业转型升级和旅游消费的热点。为科学认识大都市周边体育旅游资源空间分布特征并优化资源开发布局,本文以北京郊区为案例地,在对参与型体育旅游资源（Participatory Sport Tourism Resources, PSTR）分类基础上,运用空间分析等方法,探讨了1998、2008和2018年参与型体育旅游资源的时空演化特征及影响因素。研究发现：①北京郊区参与型体育旅游资源分为休闲娱乐型、拓展运动型和刺激探险型3类;经统计,休闲娱乐型资源数量最多,刺激探险型资源数量最少但增速最快;就资源集聚度而言,刺激探险型>拓展运动型>休闲娱乐型。②北京郊区PSTR空间分布整体呈现“东南密、西北疏”的特征,且随距中心城区距离的增加,PSTR数量波状递减;1998、20008和2018年北京郊区PSTR分布由西北向东南演进,且趋向中心城区布局的特征越来越显著,PSTR集聚峰值区由距中心城区30~40 km逐步缩减至20~30 km;3类资源的时空演化格局存在显著差异。③北京郊区PSTR空间格局的形成受地形、水系、人口、交通、政策与规划等自然和人文因素的综合影响,在不同因素作用下3类资源呈现不同的空间分布规律。其中,交通是影响空间分布的基础性因素,政策与规划因素发挥着关键性引导作用,一定程度上塑造和强化了PSTR的空间格局。以上研究发现对进一步优化北京郊区体育旅游资源的开发和体育旅游产业的合理布局具有重要理论和实践意义。     

商品进销存管理信息系统的设计

企业采购、销售和库存有机的结合,是企业获得最大的经济效益的关键。本文对商品进销存管理信息系统进行了系统的分析,对系统的功能模块设计进行了描述。该系统有很强的可操作性,实践中取得较好的效果。     

Matlab在《运筹学》教学中的应用

本文分析了高校《运筹学》教学方法中的不足,指出了在《运筹学》教学中加入Matlab语言,并且通过实例验证了利用Matlab教学比传统的教学法更有优势,在实际教学中有些具体的指导意义。