Design and fabrication of a 24-channel acousto-optic spatial light modulator

Acousto-optic (AO) devices are important spatial light modulators. They can be used as light-beam deflectors, rf true-time-delay lines, etc. To increase their spur-free dynamic range, we present what to our knowledge is a novel multichannel AO device structure, in which different channels have different carrier frequencies, so a wideband signal can automatically be decomposed into a set of narrow-band signals. Design, fabrication, and testing of this 24-channel, 10-mus AO spatial light modulator are addressed.     

单磁悬浮系统的纵向解耦控制研究

磁悬浮系统是复杂的强耦合系统,研究中未充分考虑轨道的弹性形变,会造成磁浮列车和轨道之间产生耦合振动的现象,而考虑这一因素对系统的影响无疑增加了研究的难度;为了便于问题的求解,采用非线性系统理论解耦的方法,对单电磁铁悬浮系统进行纵向解耦控制,并对解耦后的子系统进行极点配置使其满足要求的性能指标;仿真结果表明该方法有效地使复杂问题简单化,并且能够实现系统的全局稳定和良好的动态性能.     

基于PolyTrans的IGES文件简化

CAD软件与基于多边形的3D软件之间数据转换需求不断增加,但是CAD模型复杂度和精细度却越来越高,数据转换的难度变大.为了解决这一难题,结合PolyTrans,分析如何解决一般3D软件难以导入大型的IGES(Initial Graphics Exchange Specifi-cation)文件的问题.从PolyTrans模型简化模块的理论依据着手,研究如何控制多边形的数量、降低文件的复杂性和减少文件的数量,使大型CAD装配模型能顺利地以单个实体形式导入Lightwave、3DS MAX以及Maya类的3D软件.并结合具体科研项目,给出了模型优化前后各指标参数对比情况.     

Agent long-term coalition credit

Agent trust researches become more and more important because they will ensure good interactions among the software agents in large-scale open systems. Moreover, individual agents often interact with long-term coalitions such as some E-commerce web sites. So the agents should choose a coalition based on utility and trust. Unfortunately, few studies have been done on agent coalition credit and there is a need to do it in detail. To this end, a long-term coalition credit model (LCCM) is presented. Furthermore, the relationship between coalition credit and coalition payoff is also attended. LCCM consists of internal trust based on agent direct interactions and external reputation based on agent direct observation. Generalization of LCCM can be demonstrated through experiments applied in both cooperative and competitive domain environment. Experimental results show that LCCM is capable of coalition credit computation efficiently and can properly reflect various factors effect on coalition credit. Another important advantage that is a useful and basic property of credit is that LCCM can effectively filter inaccurate or lying information among interactions.     

Evaluation of Landsat 8 OLI imagery for unsupervised inland water extraction

The successful launch of the Landsat 8 satellite continues the Earth observation of the Landsat series, which has been taking place for nearly 40 years. With the increase in the band number and the improved spectral range compared with the previous Landsat imagery, it will be possible to expand the application of the new Landsat 8 imagery. The purpose of this study is to explore water extraction based on the new Landsat 8 Operational Land Imager (OLI) imagery. According to the specific inland water conditions (clear water, turbid water, and eutrophic water), a number of highly adaptable water indices are assessed for water extraction using Landsat OLI imagery. The results show that clear water is the easiest to extract among the different types of waterbodies, with the highest average accuracy of 97%. The highest-accuracy methods are the automated water extraction index for shadow pixels (AWEI_sh), the normalized difference water index using bands 4 and 7 (NDWI₄₇), and the normalized difference water index using bands 3 and 7 (NDWI₃₇), with accuracies of 98.55%, 95.50%, and 96.61%, corresponding to clear water, turbid water, and eutrophic water, respectively. Through the analysis of the different methods for optimal band selection, the seventh band OLI7 (shortwave infrared 2, SWIR-2) of Landsat OLI shows the best performance in water identification. When applying the water indices to water extraction, Otsu’s algorithm has been used to automatically select the water threshold. Using extensive experiments with Otsu’s algorithm and a manual method, it was found that Otsu’s algorithm can replace manual selection and has the ability to select an accurate threshold for water extraction.     

Wireless channel extraction analyzing based on graph theory

Wireless channels comprise various signal characteristics that correspond to different features. This research applies digital signal processing to first excavate and categorize various features found in the channel data. Then, borrowing from graph theory, fast clustering analysis and decision tree modeling are introduced to identify unique “fingerprint” characteristics. Finally, two scenarios were tested using artificial neural networks to identify and verify their applicability in different geographical locations.