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?????й???????????????GNSS???????????????????2010??4??14??????Ms7.1????????и???4??GNSS??????LHAS??LUZH??DLHA??WUSH??????TEC?????????????й???TEC??????????????????????TEC??????????????????LHAS??LUZH??WUSH???4??1????????????TEC?????????????LHAS??LUZH??DLHA???4??5???????????TEC?????????????TEC????????????????????5???????????????????????????й?????????     

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?????й??????????????1992~2005??382??GPS???????????????????????????????????????????????????????????????????仯?????????????????????????????????С?????з?α仯??????:???????72??E??77??E???????????20??1 mm/a?????????77 ??E??82??E???????????12??1 mm/a?????????82??E??92??E?????????????5 mm/a????????????????????????????12 mm/a?????????????????????????????????????82??E???????????????????λ??????????????????Σ????????????????????????????????????????82??E???????????????????????????????????????????????????????????????α??????????????????????????????????Щ?α???????????????????????????С?????????????????????仯????????????????????????????к?????????????????????????????????????????????????Ρ????????????????????????????????????????????????β???????????????????????????????????????????????????????????75??E?????????伷??????17 mm/a???????????????????????????????????75??E???????????????????ε?????????????????????????????     

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??????г??????????????ECMWF??????ERA??Interim???????й????????????????????????????????????ERA??Interim????????????????????ZTD?????????ZWD??????????????????28??GPS???????????ZTD??ZWD???б?????????ECMWF???????ZTD??????????????????????-1 cm??2 cm??ZWD??BJFS??LHAS?????????????????????1 cm??1.6 cm??     

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????GPS??????????????????????????4??1????15??????????????????????????????????2???????????????????????????????????????????????????????￡???????11??UT10:00??13??UT6:00??14??UT6:00-14:00??15??UT14:00-16??00???γ?????Χ???????????????????????????????????????????????4????????????????й??     

利用PSoC实现频率计

频率计的设计以PSoC CY8C29466-24PVXI为核心,由内部模块与外部电路的组合成其硬件电路,软件设计采用C语言。设计包括信号处理、定时器计数及数据显示3个主要部分,可以实现对信号频率的测定。由于设计中采用了分频,而且在PSoC中定时器最多可以达32位,所以频率范围比8位的单片定时器测得要广。     

基于DTW与K-means算法的河北场雨及雨型分区特征研究

深入挖掘气象站点的观测降雨数据,研究区域降雨的雨型规律,对于洪涝灾害预警和减灾措施制订有重要意义.本文基于河北省2005-2017年3189个站点逐小时降雨观测数据,进行"场雨"的划定,进而提取历史上各场雨的累积雨量、时长指标.采用数据挖掘技术中的DTW相似性算法进行场雨雨型的自动归类,将场雨分成Ⅰ-Ⅶ共7种雨型,包括...     

单片机在臭氧消毒控制系统中的应用

介绍了臭氧消毒机控制系统的设计和实现。着重讨论了如何利用定时器协调各种操作，实现使用者控制意图。     

TIMER控件在试题库系统中的应用

用Visual Basic 6.0的定时器控件,给不同的用户设置随机的初始密码,并把用户和密码一起保存在数据库中.     

面向公共安全事件的网络文本大数据结构化研究

网络文本中所包含的相关信息目前已成为公共安全事件紧急救援与影响评估的重要信息源。现有的方法虽然可定向地提取文本信息中事件的各类要素信息,但由于缺乏面向事件的整体建模与解析框架,难以从网络文本中获取系统的事件要素的结构化信息,即所提取的事件要素信息要么不够完整,要么与目标事件不匹配,由此产生的遗漏与谬误难以支撑针对公共安全事件信息的系统分析。为解决该问题,本文提出了面向公共安全事件的网络文本大数据结构化理论框架,首先,建立了公共安全事件的语义框架,并以地震事件为例构建了相应的结构化表结构;其次,应用训练语料的关联标注解决了事件要素与事件无法匹配的难点;最后,通过使用可融合关联信息的文本解析算法,系统提取了事件类型、事件名称、事件时间、事件位置及其他属性,基本实现了网络文本中不同事件信息的结构化。本文以云南邵通鲁甸地震为例,展示了地震事件的网络文本信息的结构化过程与结果,为分析地震所受的关注程度以及救援状况提供了重要参考。在上述研究的基础上,开发了面向公共安全事件的网络文本信息挖掘系统,展示了地震事件文本的结构化解析以及由此实施的事件关注度分析。     

基于现代大地测量手段的青藏高原南缘地壳形变分析

基于2003~2013年GRACE卫星重力、GPS和绝对重力数据对青藏高原南缘地壳形变进行探讨分析。结果表明,拉萨测站1999~2015年垂向隆升速率为1.5 mm/a,显示出拉萨测站持续隆升的特点。结合南加州综合网络构建的远程连续GPS参考站,另外选择TPLJ、CHLM、JMSM测站数据进行分析。GPS结果表明,4个测站2003~2013年平均隆升速率为2.3±0.11 mm/a,GRACE垂向位移时间序列显示4个测站2003~2013年除季节性变化外也具有轻微上升趋势,平均速率为0.35 mm/a。联合绝对重力资料在考虑诸多因素(地壳隆升、侵蚀、GIA等)后得到拉萨测站近年重力变化约为-0.97 μGal/a,青藏高原拉萨测站地下地壳底部增厚速率约为4.4 cm/a,揭示了青藏高原南部地区的地壳形变特征--地壳隆升与底部增厚。     

游标法事件计时器

根据游标法事件计时器的设计原理，给出基于现场可编门阵列(FPGA)的设计方案，并对实现游标法事件计时器的技术难点进行相关分析。     

Forecasts of South China Sea surface temperature anomalies using the Niño indices and dipole mode index as predictors

Based on an empirical orthogonal function (EOF) analysis of the monthly NCEP Optimum Interpolation Sea Surface Temperature (OISST) data in the South China Sea (SCS) after removing the climatological mean and trends of SST, over the period of January 1982 to October 2003, the corresponding TCF correlates best with the Dipole Mode Index (DMI), Niño1+2, Niño3.4, Niño3, and Niño4 indices with time lags of 10, 3, 6, 5, and 6 months, respectively. Thus, a statistical hindcasts in the prediction model are based on a canonical correlation analysis (CCA) model using the above indices as predictors spanning from 1993/1994 to 2003/2004 with a 1–12 month lead time after the canonical variants are calculated, using data from the training periods from January 1982 to December1992. The forecast model is successful and steady when the lead times are 1–12 months. The SCS warm event in 1998 was successfully predicted with lead times from 1–12 months irrespective of the strength or time extent. The prediction ability for SSTA is lower during weak ENSO years, in which other local factors should be also considered as local effects play a relatively important role in these years. We designed the two forecast models: one using both DMI and Niño indices and the other using only Niño indices without DMI, and compared the forecast accuracies of the two cases. The spatial distributions of forecast accuracies show different confidence areas. By turning off the DMI, the forecast accuracy is lower in the coastal areas off the Philippines in the SCS, suggesting some teleconnection may occur with the Indian Ocean in this area. The highest forecast accuracies occur when the forecast interval is five months long without using the DMI, while using both of Niño indices and DMI, the highest accuracies occur when the forecast interval time is eight months, suggesting that the Niño indices dominate the interannual variability of SST anomalies in the SCS. Meanwhile the forecast accuracy is evaluated over an independent test period of more than 11 years (1993/94 to October 2004) by comparing the model performance with a simple prediction strategy involving the persistence of sea surface temperature anomalies over a 1–12 month lead time (the persisted prediction). Predictions based on the CCA model show a significant improvement over the persisted prediction, especially with an increased lead time (longer than 3 months). The forecast model performs steadily and the forecast accuracy, i.e., the correlation coefficients between the observed and predicted SSTA in the SCS are about 0.5 in most middle and southern SCS areas, when the thresholds are greater than the 95% confidence level. For all 1 to 12 month lead time forecasts, the root mean square errors have a standard deviation of about 0.2. The seasonal differences in the prediction performance for the 1–12 month lead time are also examined.     

基于多卫星遥感产品的极端降水监测研究

以中国气象局提供的地面观测站点逐小时降水数据为基准数据,综合评估了目前国际上主流的高分辨率多卫星遥感降水在2015年强台风灿鸿所带来的极端降水事件中的表现。结果表明:1所有的卫星遥感降水产品在此次极端降水事件中对实际降水都存在着低估,其中IMERG系列下经过校正的Final产品IMERG-Final-Calibrated表现得最好;2IMERG-Late-Calibrated在实时产品中表现最好,一定程度上可以满足极端降水事件监测对实时性的要求;3总的来说,在此次极端降水事件中,不管是滞时类产品还是实时类产品,IMERG系列卫星降水的表现均要好于TMPA系列下卫星降水的表现。     

NIM稳频激光器在FG5-112绝对重力仪上的测试分析

利用中国计量科学研究院（NIM）研制的碘稳频He-Ne激光器替换FG5中使用的Winters Model 100碘稳频He-Ne激光器,并进行对比观测实验。实验表明,NIM的碘稳频He-Ne激光器能使FG5绝对重力仪正常工作,完全能够替代Winters Model 100碘稳频He-Ne激光器。