整合是网络媒体提高传播效果的根本

网络新闻是重整合还是重原创,这实际体现了网络传播过程中不同的新闻理念。通过试从受众需要、网络媒体所面临的信誉危机、目前网站编辑制作新闻的主要方式以及整合可以实现媒体间的多赢四个层次来阐述,从而论证了重整合是提高网络新闻传播效果的根本。     

Comparison of standard TEC models with a Neural Network based TEC model using multistation GPS TEC around the northern crest of Equatorial Ionization Anomaly in the Indian longitude sector during the low and moderate solar activity levels of the 24th solar cycle

The highest Total Electron Content (TEC) values in the world normally occur at Equatorial Ionization Anomaly (EIA) region resulting in largest ionospheric range delay values observed for any potential Space Based Augmentation System (SBAS). Reliable forecasting of TEC is crucial for satellite based navigation systems. The day to day variability of the location of the anomaly peak and its intensity is very large. This imposes severe limitations on the applicability of commonly used ionospheric models to the low latitude regions. It is necessary to generate a mathematical ionospheric forecasting and mapping model for TEC based on physical ionospheric influencing parameters. A model, IRPE-TEC, has been developed based on real time low latitude total electron content data using GPS measurements from a number of stations situated around the northern crest of the EIA during 2007 through 2011 to predict the vertical TEC values during the low and moderate solar activity levels of the 24th solar cycle. This model is compared with standard ionospheric models like International Reference Ionosphere (IRI) and Parameterized Ionospheric Model (PIM) to establish its applicability in the equatorial region for accurate predictions.     

美军机载导弹防御武器发展现状研究及启示

从美国网络中心机载防御单元(NCADE)的需求背景入手,分析了其技术方案和作战特点,就发展助推段/上升段机载导弹防御武器的必要性、发展思路、关键技术等进行了分析,提出了利用成熟空空导弹派生机载导弹防御武器的初步解决方案。     

参数化航空标准件库的建立

在应用CATIA进行飞机三维建模过程中会经常性地重复用到航空标准件,为提高工作效率,简要介绍通过Visual Basic软件设计的参数化航空标准件库工作界面,该界面实现了在CATIA软件中生成、调用航空标准件三维模型和标准件材料、尺寸以及使用说明等相关信息的查询功能。     

浅谈T型和S型接线器教学策略

T型和S型接线器是程控交换技术的基本交换器件，正确理解接线器的任务、组成、工作方式和工作原理，对学习和分析电话通信网、程控交换机是非常有益的，特别对于电信网工程设计和维护打下良好的基础。     

构建高等数学网络课堂的基本设想

针对当前高等院校高等数学课堂教学中存在的一些缺陷,提出网络课堂与学校课堂相结合是高等数学教学的必然和最佳教学模式,简述高等数学网络课堂的设计和构成。     

基于神经网络的翼盒结构响应重构方法应用

翼盒结构复杂，航行中承载条件恶劣，利用有限测点信息重构其它位置响应对于实时健康监测具有很强的现实意义。通过误差反向传播神经网络训练得到响应之间的非线性关系，建立基于神经网络的响应重构方法，开展有限元分析对其进行数值仿真验证，并将该方法应用于实测随机激励环境下翼盒典型承力结构的响应重构及损伤定位与判断分析。结果表明：采用该方法重构出的预测响应功率谱密度的均方根相对误差不超过1.90 dB，主要频点误差小于10%；判断出翼盒关键测点e 的损伤或故障发生在所截取片段数据3 s 后，其故障特征频率为240 Hz 左右，该方法应用于响应重构预示及健康监测分析具有可行性。     

一种新型的分布式数据采集器(一)

介绍了一种新型的分布式智能数据采集系统──ALPHA900系列数据采集器。该采集器由中国航空工业总公司第三0四研究所与英国ADAS公司联合设计研制。它集中了90年代采集器的优点，如可变字长、可编程智能前端、带温度补偿的连接器、可脱机工作等，并为突出各自功能形成系列。该采集器已成功地投入了工业生产，并且应用于工业过程监测、条件监测或加工监测。该系统使用价格低廉的RS485网络，各种型号模块提供了精确的温度、压力、应变及数字事件和频率等数据的测量及控制，并有相当突出的性能价格比。     

宽带有线综合信息网与多媒体计算机技术研究

本文简要介绍了宽带有线综合信息网与多媒体计算机技术，并对可以将宽带有线综合信息网和多媒体计算机终端实用化的一些关键技术进行了初步的探讨和研究。     

A comparative analysis of SLR,MLR, ANN,XGBoost and CNN for crop height estimation of sunflower using Sentinel-1 and Sentinel-2

Sustainable monitoring and determining the biophysical characteristics of crops is of global importance due to the increase in demand for food. In this context, remote sensing data provide valuable information on crops. This study investigates the relationship between the variables determined from both Synthetic Aperture Radar (SAR) and optical images and crop height. For this purpose, backscatter (σVH, σVV, σVH / σVV) and coherence (?VH, ?VV) of multi-temporal dual-polarized Sentinel-1 and vegetation indices of multi-temporal Sentinel-2 data are analyzed. Two indices, namely, Normalized Difference Vegetation Index (NDVI) and NDVI with the red-edge band (NDVIred), are interpreted to identify the contribution of the red-edge band over the near-infrared band. The Zile District of Tokat province in Turkey where dominantly sunflower cultivation is carried out, was selected as the study area. In the analysis of the data, Simple Linear Regression (SLR), Multiple Linear Regression (MLR), Artificial Neural Network (ANN), EXtreme Gradient Boosting (XGBoost), and Convolutional Neural Network (CNN) were used. In the results of the study, ANN showed the lowest RMSE = 3.083 cm (RMSE%= 11.284) in the stem elongation period. The CNN followed the lowest RMSE for the Inflorescence development and flowering stages 19.223 cm (RMSE%=15.458) and 8.731 cm (RMSE%=5.821), respectively. In the ripening period, XGBoost achieved the lowest RMSE = 8.731 cm (RMSE%=6.091). All the best models in four methods were created using common variables of σVH, σVV, ?VH, ?VV and NDVIred, except ANN which exclude coherence variables. The results concluded that NDVIred contributed more than NDVI which is widely interpreted in previous studies.