输电线路山火故障分析及预防

主要对山火引起输电线路跳闸机理、特点进行详细分析,并提出输电线路防山火的预防措施,对输电线路防山火跳闸具有一定指导意义。     

榆林飞播林区土壤地球化学特征

以榆林飞播林区的土壤微生物、土壤养分和土壤可溶性盐为研究对象,对林区土壤可溶性盐的变化规律及其与土壤养分、微生物的相关性进行研究,为水土资源可持续利用以及飞播造林功效的提高提供理论依据。研究表明,研究区土壤属硫酸盐型,土壤层分异特征不显著,土壤仍处于初级发育阶段。土壤总盐与养分的相关性不明显,适当增加K＋利于真菌的存活和生物量的积累,在1 kg土壤中,每增加1gK＋,真菌数量就会增加14个左右。在土层表层,适量减少Cl-能促进土壤细菌的生长,在40 cm 土层的盐分上行过程中出现表聚现象,在土壤中层,出现板结现象,在土壤底层,HCO3-和Na＋质量分数的增加,有利于土壤全氮质量分数的增加,且 HCO3-的影响力最强。     

A new effective and powerful medical image segmentation algorithm based on optimum path snakes

Novel segmentation methods based on models of deformable active contours are constantly proposed and validated in different fields of knowledge, with the aim to make the detection of the regions of interest standard. This paper propose a new method called Optimum Path Snakes (OPS), a new adaptive algorithm and free of parameters to define the total energy of a active contour model with automatic initialization and stop criteria. In the experimental assessment, the OPS is compared against some approaches commonly used in the following fields, such as vector field convolution, gradient vector flow, and other specialists methods for lung segmentation using thorax computed tomography images. The segmentation of regions with stroke was carried out with methods based on region growing, watershed and a specialist level set approach. Statistical validations metrics using Dice coefficient (DC) and Hausdorff distance (HD) were also evaluated, as well as the processing time. The results showed that the OPS is a promising tool for image segmentation, presenting satisfactory results for DC and HD, and, many times, superior to the other algorithms it was compared with, including those generated by specialists. Another advantage of the OPS is that it is not restricted to specific types of images, neither applications.     

SPOT 5在森林资源二类调查应用中数据优化研究

为了实现SPOT 5影像应用于森林资源二类调查过程中影像数据最优的目视效果,首先利用标准差、均值、信息熵、OIF指数等指标对影像融合及目视解译最佳波段进行选取;其次,针对性地引入了亮度信息、空间细节和纹理结构、信息量、光谱特性保持程度等融合效果评价参数,并以高空间分辨率信息继承程度作为重要参数以反映融合影像空间分辨率特征,把最佳波段作为统计对象对常用的9种像素级融合方法进行了融合效果分析。比较得出PCA融合为9种方法中综合最优,影像亮度、空间分辨率信息较高,视觉效果最佳;乘积融合和Brovey融合虽然空间分辨率信息继承程度等指标也较优,但是光谱扭曲太大。小波融合等方法总体光谱特征普遍较好,但是噪声较多,空间分辨率信息不佳,不适用于目视解译。定量评价之后的定性评价分析进一步强调了高空间分辨率信息继承程度做为评价指标的重要性。     

森林火灾移动预警系统的UML建模

林火预警技术是当前研究的热点技术,本文构建了一种基于WSN-GPRS-Internet多网络的森林火灾移动预警系统,实现区域性火险预报。文中建立了该系统的UML模型,并结合JavaME和JavaEE两种技术平台和Struts开源框架设计了JavaME和JavaEE的集成框架,从较高层次可视化地展现了预警系统原型。     

基于北斗卫星的森林火灾监控终端设计

针对传统森林火灾监控方式存在的受地形限制,导致火灾发现不及时和定位难的缺陷,设计了基于北斗卫星的森林火灾监控系统,实现了火灾智能识别和预警,并且可以对火源、火场进行快速定位和信息通报;终端包括烟采集处理模块、图像采集模块、DSP处理模块、ARM主控模块和北斗卫星通信模块五部分,从烟和火焰两个方面对森林实时进行监控,分别采用离子烟雾传感器和DSP火焰识别混合算法,提取火焰图像差值和火焰图像边界参数的方法,提高了识别的准确率;试验证明,系统具有结构简单、使用方便和识别智能化的特点。     

漳州市沿海防护林变化的遥感动态监测

沿海防护林是生态公益林建设的一部分, 是生态环境建设的重要内容。漳州市地处福建沿海,拥有682 km 的海岸线, 因而沿海防护林的建设直接关系到其生态环境和经济的发展。应用遥感技术, 以TM 影像为主要数据源, 分别提取了漳州市1998 年和2000～2001 年的沿海防护林信息, 对提取结果进行比较分析。动态监测结果表明2000～2001 年沿海防护林面积比1998 年有了一定的减少。并对2000～2001 年的沿海防护林作进一步的树种分类分析。从提取结果中可知漳州沿海防护林主要由7 类组成, 以木麻黄为主, 其它依次是未成林造林地、湿地松、相思树、马尾松、红树林、黑松。     

Prediction of human breast and colon cancers from imbalanced data using nearest neighbor and support vector machines

This study proposes a novel prediction approach for human breast and colon cancers using different feature spaces. The proposed scheme consists of two stages: the preprocessor and the predictor. In the preprocessor stage, the mega-trend diffusion (MTD) technique is employed to increase the samples of the minority class, thereby balancing the dataset. In the predictor stage, machine-learning approaches of K-nearest neighbor (KNN) and support vector machines (SVM) are used to develop hybrid MTD-SVM and MTD-KNN prediction models. MTD-SVM model has provided the best values of accuracy, G-mean and Matthew's correlation coefficient of 96.71%, 96.70% and 71.98% for cancer/non-cancer dataset, breast/non-breast cancer dataset and colon/non-colon cancer dataset, respectively. We found that hybrid MTD-SVM is the best with respect to prediction performance and computational cost. MTD-KNN model has achieved moderately better prediction as compared to hybrid MTD-NB (Naïve Bayes) but at the expense of higher computing cost. MTD-KNN model is faster than MTD-RF (random forest) but its prediction is not better than MTD-RF. To the best of our knowledge, the reported results are the best results, so far, for these datasets. The proposed scheme indicates that the developed models can be used as a tool for the prediction of cancer. This scheme may be useful for study of any sequential information such as protein sequence or any nucleic acid sequence.     

面向森林生态学研究的Web处理服务系统

森林是陆地生态系统的主体,森林生态保护与恢复是生态文明建设的重要组成部分.面对森林生态模型单机化、重复开发部署的现状,本文设计并实现一个面向森林生态学研究的Web处理服务系统.该系统根据开放地理空间信息联盟（Open Geospatial Consortium,OGC）制定的空间数据共享及互操作的接口规范,基于WebService技术,实现了面向森林生态学研究的多模型整合,并将模型计算结果进行展示,减少了重复开发和部署工作,提高了数据与服务的共享性.     

多模态融合的特征提取方法在SA检测中的应用

为解决睡眠呼吸暂停(Sleep Apnea,SA)检测中使用传统的机器学习方法需花大量工作在特征工程上导致效率低下,以及模型多以单通道信号进行特征提取存在识别效果不佳的问题,提出一种基于时序卷积网络(Temporal Convolutional Network,TCN)和堆叠稀疏降噪自编码器(Stacked Sparse Denoismg Auto-Encoder,SSDAEs)的多模态特征融合模型来实现特征自动提取。该模型以心电和呼吸2种信号作为输入,首先利用TCN网络提取输入信号的时序特征,然后通过SSDAEs提取信号的浅层与深层的高维特征,对于不同特征空间的心电信号特征和呼吸信号特征采用一个小型神经网络进行特征融合,将该模型与随机森林算法结合,用于解决SA片段检测问题。实验结果表明,该方法在SA片段检测的准确率、灵敏度、特异性分别是91.5%、88.9%、90.8%。通过与以往相关研究对比,验证了该模型的SA检测性能更好,效率更高。