Efficient Solution to Electromagnetic Scattering Problems of Bodies of Revolution by Compressive Sensing

Under the theory structure of compressive sensing （CS）, an underdetermined equation is deduced for describing the discrete solution of the electromagnetic integral equation of body of revolution （BOR）, which will result in a small-scale impedance matrix. In the new linear equation system, the small-scale impedance matrix can be regarded as the measurement matrix in CS, while the excited vector is the measurement of unknown currents. Instead of solving dense full rank matrix equations by the iterative method, with suitable sparse representation, for unknown currents on the surface of BOR, the entire current can be accurately obtained by reconstructed algorithms in CS for small-scale undetermined equations. Numerical results show that the proposed method can greatly improve the computgtional efficiency and can decrease memory consumed.

Aerial Extent Analysis and Environmental Problems Identification of Matasagar and Sukhsagar Wetlands in Bangladesh Using GIS and Remote Sensing Tools

Bangladesh is a land of wetlands. Basically, most of them are freshwater wetlands and have great influence on the primary economic activities such as agriculture and fisheries of the country. Due to its important role in the harmonizing ecosystem, wetlands demand much attention as a significant part of our environment. Matasagar and Sukhsagar are very important historical wetlands of Bangladesh. But those are endangered today due to lack of public awareness of the dangers of their activities to the environment and unbridled profit making activities of the commercial users of the wetlands. Comparisons of maps and Google images from 1933 to present have shown that the forest areas of the wetlands have been progressively destroyed, and these have greatly affected the biodiversity of these areas mentioned. GIS (Geographic Information System) and remote sensing techniques are used to identify the changes in the aerial extent of those wetlands. This study also tried to explore present environmental conditions by in-situ observation. This is high time;some serious steps should be taken to ensure the conservation and preservation of these areas mentioned.

Retrieval of Land-surface Temperature from AMSR2 Data Using a Deep Dynamic Learning Neural Network

It is more difficult to retrieve land surface temperature(LST) from passive microwave remote sensing data than from thermal remote sensing data, because the emissivities in the passive microwave band can change more easily than those in the thermal infrared band. Thus, it is very difficult to build a stable relationship. Passive microwave band emissivities are greatly influenced by the soil moisture, which varies with time. This makes it difficult to develop a general physical algorithm. This paper proposes a method to utilize multiple-satellite, sensors and resolution coupled with a deep dynamic learning neural network to retrieve the land surface temperature from images acquired by the Advanced Microwave Scanning Radiometer 2(AMSR2), a sensor that is similar to the Advanced Microwave Scanning Radiometer Earth Observing System(AMSR-E). The AMSR-E and MODIS sensors are located aboard the Aqua satellite. The MODIS LST product is used as the ground truth data to overcome the difficulties in obtaining large scale land surface temperature data. The mean and standard deviation of the retrieval error are approximately 1.4° and 1.9° when five frequencies(ten channels, 10.7, 18.7, 23.8, 36.5, 89 V/H GHz) are used. This method can effectively eliminate the influences of the soil moisture, roughness, atmosphere and various other factors. An analysis of the application of this method to the retrieval of land surface temperature from AMSR2 data indicates that the method is feasible. The accuracy is approximately 1.8° through a comparison between the retrieval results with ground measurement data from meteorological stations.

Review of the Impact of Grassland Degradation on Ecosystem Service Value

In recent years, grassland degradation has become one of China’s most critical environmental problems due to the interaction of natural environmental factors and human causes. Based on the systematic analysis of the spatial characteristics of grassland degradation and the current research status of environmental drivers, this paper summarizes and summarizes the research methods on the impact of grassland degradation on natural ecological service function and social and economic value to understand further the natural ecological service function of grassland degradation and its impact on social and economic benefits. The results show that since the function of grassland ecosystem service is much larger than the biomass value it provides, we should focus on the effective management of grassland from the design concept of ecological service function to achieve the sustainable development of grassland. We should do an excellent job in the comprehensive application of various ecosystems and service value evaluation methods in the future.

Primary Research of EIT Inverse Problem Based on CS （Compressed Sensing） Technique

EIT （electrical impedance tomography） problem should be represented by a group of partial differential equation, in numerical calculation： the nonlinear problem should be linearization approximately, and then linear equations set is obtained, so EIT image reconstruct problem should be considered as a classical ill-posed, ill-conditioned, linear inverse problem. Its biggest problem is the number of unknown is much more than the number of the equations, this result in the low imaging quality. Especially, it can not imaging in center area. For this problem, we induce the CS technique into EIT image reconstruction algorithm. The main contributions in this paper are： firstly, built up the relationship between CS and EIT definitely; secondly, sparse reconstruction is a critical step in CS, built up a general sparse regularization model based on EIT; finally, gives out some EIT imaging models based on sparse regularization method. For different scenarios, compared with traditional Tikhonov regularization （smooth regularization） method, sparse reconstruction method is not only better at anti-noise, and imaging in center area, but also faster and better resolution.

New Approach for Limited-Angle Problems in Electron Microscope Based on Compressed Sensing

New advances within the recently rediscovered field of Compressed Sensing (CS) have opened for a great variety of new possibilities in the field of image reconstruction and more specifically in medical image reconstruction. In this work, a new approach using a CS-based algorithm is proposed and used in order to solve limited-angle problems (LAPs), like the ones that typically occur in computed tomography or electron microscope. This approach is based on a variant of the Robbins-Monro stochastic approximation procedure, developed by Egaziarian, using regularization by a spatially adaptive filter. This proposal consists on filling the gaps of missing or unobserved data with random noise and enabling a spatially adaptive denoising filter to regularize the data and reveal the underlying topology. This method was tested on different 3D transmission electron microscope datasets that presented different missing data artifacts (e.g, wedge or cone shape). The test results show a great potential for solving LAPs using the proposed technique.

The Hard Problem of Consciousness from a Bio-Psychological Perspective

Chalmers introduced the hard problem of consciousness as a profound gap between experience and physical concepts. Philosophical theories were based on different interpretations concerning the qualia/concept gap, such as interactive dualism （Descartes）, as well as mono aspect or dual aspect monism. From a bio-psychological perspective, the gap can be explained by the different activity of two mental functions realizing a mental representation of extra-mental reality. The function of elementary sensation requires active sense organs, which create an uninterrupted physical chain from extra-mental reality to the brain and reflect the present. The function of categorizing reflection no longer needs sense organs, so that the physical chain to extra-mental reality is interrupted and now reflects the past. Whereas elementary sensation is an open system, categorizing reflection remains a closed system, separated from extra-mental reality. This creates the potentiality/reality gap, since prediction from the closed to the open system remains always uncertain. Elementary sensation is associated to specific qualia for each sense organ. Chalmers also attributed qualia to thoughts, with more neutral thought qualia. Thus at the qualia level, there is also an important gap, but now between specific sense qualia and neutral thought qualia. Since all physical concepts are simultaneously linked to neutral thought qualia, the hard problem might be explained by a qualia/qualia gap instead of a qualia/concept gap. The mental function of categorizing reflection induces the change from sense qualia to thought qualia by a categorization process. The specific sense qualia mosaic of an apple is reduced to physical concepts with neutral qualia by progressive categorization first to fruit, then to food, to chemicals and finally to calories. This might explain the gap felt in the hard problem, since specific sense qualia are completely different from neutral thought qualia, so that the hard problem could already be encountered at the qualia level. Since the gap of the hard problem is due to the interaction of different mental functions, it is compatible with a philosophical monism.

铸牢中华民族共同体意识融入民族地区语言教育对策研究

民族地区语言教育发展是推动各族群众交往交流交融,促进民族团结的重要举措。民族地区只有不断加强国家通用语言文字教育才能更好地适应当前阶段的客观需要,加强民族间的交往交流交融,实现书同文、语同音、心相通、情相融。文章基于民族地区通用语言教育对于铸牢中华民族共同体意识的重要意义,通过梳理既有文献及研究成果,了解当前民族语言教育发展现状,就部分民族地区语言教育存在的突出问题,提出了加强语言教育师资队伍、加大语言教育投入力度、推广普及国家通用语言文字、增强课程思政在语言教育课堂的融合程度四条策略,并认为在民族地区推广普及国家通用语言文字,要开拓创新,多措并举,多管齐下,切实解决当前存在的问题,加快推进民族地区语言教育进程,以语言相通促进各族群众的沟通交流和国家认同,进而铸牢中华民族共同体意识。

基于问题探索的文献导读教学模式探析

依据认知失调理论和认知主义教学理论,提出基于问题探索为核心的文献导读教学模式。该教学模式以与课程教学目标紧密联系的问题意识培养为核心,以文献导读为手段,用“起惑——文献推荐——探索——解惑”的逻辑思路重构教学流程,实现高等教育课程教学完整性、互动性、高深性的教学要求。

论自然主义道德责任问题的困境——对功能规范型归责理论的再思考

基于自然化的“功能”概念来处理道德责任问题是颇为切合当代主流世界观的一种进路。沿着这一思路,晓非就“否决功能如何说明自主行为中的自由感”“如何基于功能式同一性标准应对操纵难题”与“‘功能规范型’模型如何说明道德归责的规范性”等问题展开了颇有新意的探讨。围绕这三个主题,还需要进一步探讨以下观点:升级版的否决功能假说本身存在着削弱自由感的风险;借助功能同一性标准的思路切中了操纵难题的一个当代启示,即公正的归责需要清晰锁定表面行动背后的核心决策来源;当前版本的“功能规范型”归责理论尚未彻底摆脱实用主义困境。

中国民族思想史研究述论

民族思想是人类对历史和现实中民族和民族问题的基本认识,中国民族思想史就是在多民族中国国家发展历史过程中形成并且不断发展的民族思想及其实践过程,中国民族思想史最显著的特征是鲜明的时代性,是在解决民族问题实践过程中的智慧表达。在以铸牢中华民族共同体意识为主线的新时代,研究中国民族思想史对于中华民族共同体的建设和铸牢中华民族共同体意识的实践都具有重大的学术价值和实践意义。

基于Elastic-net正则化的神经网络方法求解反问题

神经网络已经成为求解反问题的热点方法之一,引入elastic-net正则项作为神经网络中损失函数的惩罚项防止求解过程的过度拟合,并通过交叉训练实现基于elastic-net正则项的神经网络的算法.通过压缩感知和图像去模糊2个数值实验,验证elastic-net正则项防止过度拟合的可行性和有效性.此外,当变换矩阵条件数较大时,在较低的训练轮次下可以达到较好的训练效果.

遥感监测技术在江西省重点河湖库“清四乱”中的应用研究

为及时排查与整改处置影响河湖库面貌及功能发挥的乱占、乱采、乱堆、乱建问题,探索利用遥感监测手段开展定期监测,充分发挥卫星遥感影像高时间分辨率和高空间分辨率的优势,为河湖库“四乱”问题高频度遥感监测提供数据保障。结合江西省重点河湖库遥感监测实施案例,通过构建遥感解译标志、生成“四乱”问题疑似图斑数据库、采用无人机辅助实地核实等技术手段开展遥感监测,对监测成果进行科学分析,为河湖管理及行政执法提供科学依据和决策支持。

卫星遥感在河湖岸线保护与利用监测中的应用

主要结合当前河湖长制与推进“四乱”问题治理常态化、规范化管理需求,通过套合河湖岸线规划数据,利用高分辨率卫星遥感影像数据,在制定河湖“乱占、乱堆、乱采和乱建”遥感解译分类标准基础上,以人机交互的方式提取疑似河湖“四乱”问题,并辅助外业核查,研制了一套利用卫星遥感技术开展河湖岸线保护与开发利用的技术路线与方法。研究结果表明:借助卫星遥感技术,可实现对河湖“四乱”问题的大范围、多频次、精准化监测,为河湖管护与河湖“四乱”问题治理提供一套完整、科学、可靠的解决方案。

以航天遥感为主题的问题驱动式研究生教学模式探索——以图像处理与成像技术课程为例

产教融合创新能力培养是我国新时代研究生教育的研究方向之一。该文结合航天遥感的行业特点,把研究生教育跟航天需求方案论证、问题驱动创新结合起来,探索新时代研究生更贴近产业需求的培养模式。从生活中常见的手机拍照入手,将专业遥感相机与“遥感手机”作对比,抛出问题并引导研究生拆解问题,查阅文献资料获取手机摄像头的主要成像参数,逐步分析计算手机作为遥感载荷对地成像的分辨力指标,引导学生对比专业遥感相机的成像指标参数,激发讨论热情,适当归纳结论,最终回归到图像处理与成像技术这门研究生课程的深层知识讲解。在提高课堂教学效率的同时,将目前航天遥感领域的产业状况与当下研究生教学紧密结合在一起,探索产教融合的研究生培养新模式。

思政课问题式专题化团队教学改革下高职院校大学生思政课获得感研究

思政课是落实立德树人根本任务的关键课程,高职院校大学生思政课获得感直接关系到立德树人根本任务的实现。近年来,在思政课问题式专题化团队教学改革下,高职院校思政课发生了全局性、根本性的转变,课程总体获得感显著提升,但也有一些老问题和新情况亟须解决。面对学生、教师、问题、专题等影响思政课获得感的主要因素,要从教学三要素、问题式设计、专题化构建和教学团队建设等方面进行有益思考,为提升思政课获得感强基、锚向、聚能、护航。

“双碳”目标下广西居民环保素质对绿色消费的影响研究

本文基于广西7个重点城市的实地调研数据,结合环保素质理论和计划行为理论,从居民的环保素质角度出发,通过环保价值观、环保责任感和环保问题感知三个变量与绿色消费建立影响机制模型,运用结构方程模型进行数据分析。研究结果表明,环保价值观、环保责任感、环保问题感知分别对绿色消费具有正向的显著性影响作用,其中环保价值观对于绿色消费的影响相较其他变量更大。基于此,为进一步促进广西绿色消费发展,政府应积极引导居民强化绿色消费动因,实现绿色消费常规化;推动企业完善绿色消费产业链,提升绿色发展水平;加快绿色消费体系建设,助力绿色转型发展。政府、企业、居民三者应各尽其责,群策群力,推动广西居民形成绿色低碳的生产方式和生活方式。

基于Compressed Sensing框架的图像多描述编码方法

基于新兴的压缩感知(Compressed Sensing,CS)理论,提出了一种抗丢包能力强且结构简单易实现的多描述编码方法.首先对变换后的图像进行交织抽取分块,再对各子块进行随机观测、量化、打包形成多个描述子码流.解码端根据接收码流情况通过求解优化问题重建原图像.由于随机观测过程简单易实现,故该方法可以以较低的计算复杂度构造出较多的描述子.实验结果表明,在同样的丢包率下,本文方法的重构质量(PSNR)明显优于SPIHT多描述编码方法,且计算复杂度较低.

基于遥感的木里煤矿区矿山地质环境监测及评价

为揭示木里煤矿开采对生态环境的破坏程度,通过2010年和2013年2期高分辨遥感影像监测,野外调查和水土样品采集,开展了矿山地质环境问题和承载力的调查,查明了问题并对其破坏程度和承载能力进行了评价。结果表明,矿区地形地貌景观和土地资源占压与破坏严重,河水受到Cu、Pb、Cr和Zn的污染,土壤受到Cd、As污染,高山草甸和沼泽地破坏及退化现象严重,冻土含水层结构遭到破坏,地质环境承载力适中。评价结果可为政府和矿山企业开展矿山地质环境恢复治理提供基础资料。

中国人社会心态的经验结构及量表编制

对当今中国社会心态的研究,因缺乏标准化的测量工具而难以深入。为此,该研究在参考已有研究基础上,确定了生活满意感、社会压力感、政府信任感、社会公平感、社会安全感和社会问题感六个方面的测量指标,选取较大样本经过预测和正式施测,并采用验证性因素分析对量表结构进行验证。结果表明量表具有良好的信度,且结构与数据拟合较好,可以作为对中国人社会心态进行量化研究的测量工具。