Neptune Trojans: a Revisit and a New Membertwo

Up to now, 17 Neptune Trojan asteroids have been detected with their orbits being well determined by continuous observations. This paper analyzes systematically their orbital dynamics. Our results show that except for two temporary members with relatively short lifespans on Trojan orbits, the vast majority of Neptune Trojans located within their orbital uncertainties may survive in the solar system age. The escaping probability of Neptune Trojans, through slow diffusion in the orbital element space in 4.5 billion years, is estimated to be ～50%. The asteroid 2012 UW177 classified as a Centaur asteroid by the IAU Minor Planet Center currently is in fact a Neptune Trojan. Numerical simulations indicate that it is librating on the tadpole-shaped orbit around the Neptune's L₄ point. It was captured into the current orbit approximately 0.23 million years ago, and will stay there for at least another 1.3 million years in the future. Its high inclination of i ≈ 54^° not only makes it the most inclined Neptune Trojan, but also makes it exhibit the complicated and interesting co-orbital transitions between the leading and trailing Trojans via the quasi-satellite orbit phase.     

结合云计算与大数据的出租房消防安全监管GIS

我国城镇化进程和经济发展效果卓著，但消防建设规划与城市扩张发展之间并不协调。虽然现有研究已经运用GIS技术到消防安全监管当中，但依然存在信息联动性不强，可视化程度低的问题。为此，本文基于地理信息系统技术对城市开发区内地理信息数据、多源多时态遥感及航空影像、巡查数据、出租房数据等进行有效整合完善，以建立时空地理信息大数据。笔者利用虚拟化、云计算等技术建立出租房消防安全动态监管平台。此平台为管理部门提供了基于地理信息的决策支持，提升了出租房管理的高效性和科学性。系统的建成和应用对我国的出租房管理信息化工作的开展具有重要意义。     

大面积硅微条探测器在轨数据压缩算法的设计与实现

硅微条探测器具有位置分辨高、响应快、低噪声、低功耗等优点,广泛应用在各大加速器试验中,测量粒子径迹.新世纪以来,逐渐应用于空间探测领域.计划中的"悟空"2号暗物质粒子探测卫星的硅微条探测器将至数十万计,将产生海量的原始数据.如何实现探测器快速实时的数据压缩,是其需要解决的一大难题.立足于面向空间应用的硅微条探测器在轨实时压缩算法,算法采用FPGA (Field-programmable Gate Array)搭建流水线结构的方式实现,在提高系统集成度、节省逻辑资源的同时,批量数据处理时最高可将数据压缩率提升至38.4 M通道/s.算法结构具有通用性,设计思想和方案将为"悟空"2号的径迹探测器的研制提供参考.     

Prediction of the South China Sea Dipole Using SSA-MEM

ABSTRACT

A dipole structure appears in the sea surface height off the central coast of Vietnam during boreal summer in the South China Sea. This dipole, which possesses a chlorophyll signature associated with higher phytoplankton concentrations arising from nutrient upwelling, is important for the productivity of local fisheries. Multi-satellite sea level anomalies are used to investigate the life cycle of the dipole structure. By applying empirical orthogonal function (EOF) analysis, the third EOF mode (EOF 3) is found to represent the major variations of the dipole structure. By removing the temporal noise of EOF 3, a South China Sea dipole index is defined. This index captures the life cycle of the dipole including its generation, mature strength, and final termination. Both one-dimensional and two-dimensional forecasts are generated using a statistical forecasting method that combines singular-spectrum analysis and the maximum entropy method. The appearance of the dipole structure can be predicted with an accuracy of 78% at one-month lead times and an accuracy of 61% at one-year lead times.     

Site characterization model using least‐square support vector machine and relevance vector machine based on corrected SPT data (Nc)

Statistical learning algorithms provide a viable framework for geotechnical engineering modeling. This paper describes two statistical learning algorithms applied for site characterization modeling based on standard penetration test (SPT) data. More than 2700 field SPT values (N) have been collected from 766 boreholes spread over an area of 220 sqkm area in Bangalore. To get N corrected value (N_c), N values have been corrected (N_c) for different parameters such as overburden stress, size of borehole, type of sampler, length of connecting rod, etc. In three‐dimensional site characterization model, the function N_c=N_c (X, Y, Z), where X, Y and Z are the coordinates of a point corresponding to N_c value, is to be approximated in which N_c value at any half‐space point in Bangalore can be determined. The first algorithm uses least‐square support vector machine (LSSVM), which is related to a ridge regression type of support vector machine. The second algorithm uses relevance vector machine (RVM), which combines the strengths of kernel‐based methods and Bayesian theory to establish the relationships between a set of input vectors and a desired output. The paper also presents the comparative study between the developed LSSVM and RVM model for site characterization. Copyright © 2009 John Wiley & Sons, Ltd.     

智慧城市时空信息云平台建设研究

以完善的云环境建设为支撑,以构建标准安全的防护体系为保障,以时空信息云平台建设为基础,以智慧应用建设为重点,促成跨域、跨部门、跨层级的数据融合,提高城市综合智能化水平,使城市运转更加高效、敏捷、低碳与和谐。     

PMODTRAN: a parallel implementation based on MODTRAN for massive remote sensing data processing

MODerate resolution atmospheric TRANsmission (MODTRAN) is a commercial remote sensing (RS) software package that has been widely used to simulate radiative transfer of electromagnetic radiation through the Earth's atmosphere and the radiation observed by a remote sensor. However, when very large RS datasets must be processed in simulation applications at a global scale, it is extremely time-consuming to operate MODTRAN on a modern workstation. Under this circumstance, the use of parallel cluster computing to speed up the process becomes vital to this time-consuming task. This paper presents PMODTRAN, an implementation of a parallel task-scheduling algorithm based on MODTRAN. PMODTRAN was able to reduce the processing time of the test cases used here from over 4.4 months on a workstation to less than a week on a local computer cluster. In addition, PMODTRAN can distribute tasks with different levels of granularity and has some extra features, such as dynamic load balancing and parameter checking.     

A variable precision rough set approach to knowledge discovery in land cover classification

This paper presents a granular computing approach to spatial classification and prediction of land cover classes using rough set variable precision methods. In particular, it presents an approach to characterizing large spatially clustered data sets to discover knowledge in multi-source supervised classification. The evidential structure of spatial classification is founded on the notions of equivalence relations of rough set theory. It allows expressing spatial concepts in terms of approximation space wherein a decision class can be approximated through the partition of boundary regions. The paper also identifies how approximate reasoning can be introduced by using variable precision rough sets in the context of land cover characterization. The rough set theory is applied to demonstrate an empirical application and the predictive performance is compared with popular baseline machine learning algorithms. A comparison shows that the predictive performance of the rough set rule induction is slightly higher than the decision tree and significantly outperforms the baseline models such as neural network, naïve Bayesian and support vector machine methods.     

国家级格点化定量降水预报系统

利用主客观融合降水反演、降水统计降尺度、降水时间拆分等技术构建了国家级格点化定量降水预报系统。该系统结构合理,模块功能明确,于2014年6月在国家气象中心投入业务使用,生成0~168 h时效,10 km分辨率,逐3 h的格点化定量降水预报产品。通过对2015年第13号热带气旋苏迪罗的格点化降水预报个例检验,结果显示,相比欧洲中期数值预报中心的确定性模式预报和预报员主观预报,该产品能更好地体现台风降水的时空精细化分布特点,对福建东北部和浙江东南部的特大暴雨中心位置表现更准确细致。通过对2015年4—9月的格点化产品整体效果检验,结果显示,相比欧洲中期数值预报中心的确定性模式预报和由反距离客观分析后的预报员主观预报,该产品既能保持和预报员主观预报相同的准确率,同时也能较明显地提高降水预报的时空精细化程度。     

长江中下游地区暖区暴雨特征分析

利用2007到2013年5-9月间常规和非常规资料以及6 h一次的NCEP 1°×1°再分析资料,将长江中下游地区暖区暴雨按天气形势划分为冷锋前暖区暴雨、暖切变暖区暴雨以及副热带高压边缘暖区暴雨三种类型。统计表明暖区暴雨一般发生在距离切变线(锋线)100~300 km的暖区内。主要结论包括:(1)冷锋型降水强度偏弱且分布均匀,集中在5、6月;暖切变型发生次数最多且强度大,主要发生在6、7月长江中下游地区的偏南部;副热带高压边缘型发生次数最少但强度较大,发生在7、8月。暖区暴雨的发生次数及强度在大别山、皖南山区较为集中。(2)暖区暴雨中短时强降水贡献大。(3)冷锋背景下的暖区暴雨一般产生在锋前低压槽中,暴雨落区与高低空急流耦合有紧密联系;暖切变型以低层暖切变线为主要天气背景,地面常有弱静止锋,暖区对流活动与中尺度急流结构、地形强迫等因素存在较高的相关性;副热带高压边缘暖区暴雨与局地的水汽积累和对流不稳定条件的发展有密切关系。据此建立三类暖区暴雨的概念模型。