Advanced fractal approach for unsupervised classification of SAR images

Unsupervised classification of Synthetic Aperture Radar (SAR) images is the alternative approach when no or minimum apriori information about the image is available. Therefore, an attempt has been made to develop an unsupervised classification scheme for SAR images based on textural information in present paper. For extraction of textural features two properties are used viz. fractal dimension D and Moran’s I. Using these indices an algorithm is proposed for contextual classification of SAR images. The novelty of the algorithm is that it implements the textural information available in SAR image with the help of two texture measures viz. D and I. For estimation of D, the Two Dimensional Variation Method (2DVM) has been revised and implemented whose performance is compared with another method, i.e., Triangular Prism Surface Area Method (TPSAM). It is also necessary to check the classification accuracy for various window sizes and optimize the window size for best classification. This exercise has been carried out to know the effect of window size on classification accuracy. The algorithm is applied on four SAR images of Hardwar region, India and classification accuracy has been computed. A comparison of the proposed algorithm using both fractal dimension estimation methods with the K-Means algorithm is discussed. The maximum overall classification accuracy with K-Means comes to be 53.26% whereas overall classification accuracy with proposed algorithm is 66.16% for TPSAM and 61.26% for 2DVM.     

Training effectiveness evaluation of helicopter emergency relief based on virtual simulation

Helicopters are playing an increasingly important part in emergency relief, such as earthquake rescue, firefighting and medical transport. With the development of virtual simulation technology, virtual simulation-based training is widely used in the training of the helicopter crew especially for the dangerous and costly missions mentioned above. A complete training effectiveness evaluation method is proposed to evaluate the trainees’ training effect based on virtual simulation in this paper. A key to this method is regarding the complicated process as a discrete event-activity flow system and establishing the evaluation indicator system. Then expert group and Analytical Network Process (ANP) are applied to determine the weight of indicators. When the training data are processed, there is a novel attempt to apply Fuzzy Comprehensive Evaluation (FCE) model to calculate the two categories of indicators. Eventually, an experiment and the analysis were carried out to validate the evaluation method.     

推进经济持续发展 努力缩小贫富差距

本文从经济发展的角度提出农业产业化是促进农村阶层有序合理分化的基础;大力发展多种所有制经济,优化产业结构,开拓就业渠道;加快城市化步伐,缩小农民阶级的规模;加强和改善宏观调控,规范分配和消费市场,建立和完善公正的利益分配机制等社会分层合理化的对策,促进我国的社会分层结构和机制更加健康、合理。     

一种基于混合规则的作业车间计划调度方法

针对多品种小批量生产车间计划调度存在的复杂度高、实用性差等问题,在分析车间计划调度相关的任务、资源和约束等要素的基础上,提出了一种基于混合规则的计划调度编制算法,该算法综合考虑了零件差异性、工艺差异性、设备差异性、以及交货期约束等因素,使得该方法具有可行性高、实用性强等特点,较好地满足了离散制造车间的实际需求.     

一种快速的飞行器布局方案优选方法

本文引用系统模糊优选理论与基于数理统计正交表的设计法相结合来处理飞行器布局方案优选问题，并举例说明具体用法，文中方法对整个飞行器方案选择有一定参考价值。     

浅谈施工企业降低工程成本的有效控制

在目前我国建筑市场竞争激烈的背景下,对于一个建筑企业而言,取得项目施工权固然重要,但合理控制并降低施工成本,在保证施工质量前提下取得相应利润回报更为关键,应从施工前、施工过程中、竣工后三个环节加以有效控制。     

航天航空中急性缺氧条件下功效改变的研究

受试者为84名男性青年和实验工作人员,在低压舱1500、2500、3000、4000、5000和6000米高度上停留60分钟。每次实验一个高度,总共133人次。实验中,记录了数字记忆、听觉警觉和跟踪操作等多项功效指标。应用统计和模型方法对结果进行了分析,并试用模糊集理论对五种基本功效进行综合评定,得到了急性缺氧下功效改变有意义的结果。这些结果可为飞行员执行飞行任务,航天员在船舱内或穿着航天服在舱外执行任务及制订医学保证方案提供了科学依据。     

Direct position determination using single moving rotating linear array: Noncoherent and coherent processing

To improve the resolution and accuracy of Direct Position Determination (DPD), this paper investigates the problem of positioning multiple emitters directly with a single moving Rotating Linear Array (RLA). Firstly, the geometry of the RLA is formulated and analysed. According to its geometry, the intercepted noncoherent signals in multiple interception intervals are modeled. Correspondingly, the MUltiple SIgnal Classification (MUSIC) based noncoherent DPD approach is proposed. Secondly, the synchronous coherent pulse signals are individually considered and formulated. And the coherent DPD approach which aims for localizing this special type of signal is presented by stacking all array responses at different interception intervals. Besides, we also derive the constrained Cramér-Rao Lower Bound (CRLB) expression for both noncoherent and coherent DPD with RLA under the constraint that the altitudes of the emitters are known. At last, computer simulations are included to examine the performance of the proposed approach. The results demonstrate that the localization accuracy and resolution of DPD with single moving linear array can be significantly improved by the array rotation. In addition, coherent DPD with RLA further improves the resolution and increases the maximum emitter number that can be localized compared with the noncoherent DPD with RLA.     

Mapping Regolith and Gossan for Mineral Exploration in the Eastern Kumaon Himalaya,India using hyperion data and object oriented image classification

Crystalline in the Kumaon Himalaya, India near Askot area is a prominent site of the base metal mineralization and gossanised surface. This area is hosted by the sulphides and sulphates of Cu, Pb, Zn and Au and Ag mineralization with the altered rocks like sericite chlorite schist, gneiss etc. Due to the deep weathering this area is also a good illustration site of the gossanised outcrop.     

基于多尺度 3D-2D卷积神经网络的高光谱图像分类

设计提出了 1种针对高光谱图像分类任务的 3D-MSCNN模型。在 PCA降维的基础上,利用 3D空谱特征提 取网络和 2D多尺度特征提取网络实现高光谱图像特征提取,充分发挥高光谱图像空谱信息价值,增强对不同尺度 地表覆盖的表达能力。最后,利用 Softmax分类损失函数实现高光谱图像分类任务。实验结果表明,本文算法在 In. dian Pines和 Pavia University数据集上都取得了较好的分类效果。与 CD-CNN、3D-CNN、SS-Net和 HybirdSN等方法相 比,本文算法能够有效提升总体精度、平均精度和 Kappa系数等客观评价指标。