Weather display symbology affects pilot behavior and decision-making

ObjectiveTo examine the basic discriminability of weather display symbols and to assess the effects of weather display symbology on pilot behavior and decision-making.MethodDuring a cockpit simulation, 24 instrument-rated general aviation (GA) pilots were randomly allocated to one of three simulation groups. Pilots flew a Cessna 172 single-engine GA aircraft under Visual Meteorological Conditions (VMC) and Instrument Meteorological Conditions (IMC) while avoiding hazardous weather. We manipulated the weather display so that each pilot group used a different weather symbology (i.e., symbols and colors). We measured dependent variables for weather avoidance, communication, weather display usage, and cognitive engagement (i.e., oxygenation from Functional Near-Infrared [fNIR] measures). During a change-detection experiment, 20 naïve participants performed a detection task of changes in Aviation Routine Weather Reports (METARs), precipitation, Significant Meteorological Information (SIGMET), lightning, and time-stamp images.ResultsThe simulation outcome showed credible pilot group differences in weather deviations, cognitive engagement, and weather display usage. The change-detection experiment revealed credible differences in discriminability of METAR, SIGMET, and lightning symbols.ConclusionSymbol and color variations in weather displays contribute to perceptual asymmetries which affect pilot behavior and decision-making. We recommend the development of cockpit applications that use weather data to automatically track hazardous conditions and alert the pilot of potential weather conflicts or weather changes.     

Effects of modes of cockpit automation on pilot performance and workload in a next generation flight concept of operation

The objective of this study was to compare the effects of various forms of advanced cockpit automation for flight planning on pilot performance and workload under a futuristic concept of operation. A lab experiment was conducted in which airline pilots flew simulated tailored arrivals to an airport using three modes of automation (MOAs), including a control‐display unit (CDU) to the aircraft flight management system, an enhanced CDU (CDU+), and a continuous descent approach (CDA) tool. The arrival scenario required replanning to avoid convective activity and was constrained by a minimum fuel requirement at the initial approach fix. The CDU and CDU+ modes allowed for point‐by‐point path planning or selection among multiple standard arrivals, respectively. The CDA mode completely automated the route replanning for pilots. It was expected that the higher‐level automation would significantly reduce pilot workload and improve overall flight performance. In general, results indicated that the MOAs influenced pilot performance and workload responses according to hypotheses. This study provides new knowledge about the relationship of cockpit automation and interface features with pilot performance and workload in a novel next generation–style flight concept of operation. © 2012 Wiley Periodicals, Inc.     

纹理特征在SAR图像变化检测中的应用

城区变化检测可以提供大量关于土地利用和城市发展的信息,是变化检测技术的重要应用之一。根据合成孔径雷达(SAR)图像特点,针对城区环境的特定应用,提出了纹理差值变化检测方法。该方法采用纹理特征代替灰度信息来体现图像特点,并使用差值变化检测来获取城区变化情况。实验结果表明,对于大多数特征,纹理差值法获得了较高的变化检测正确率,检测性能有了大幅度的提高。     

Change impact graphs: Determining the impact of prior codechanges

The source code of a software system is in constant change. The impact of these changes spreads out across the software system and may lead to the sudden manifestation of failures in unchanged parts. To help developers fix such failures, we propose a method that, in a pre-processing stage, analyzes prior code changes to determine what functions have been modified. Next, given a particular period of time in the past, the functions changed during that period are propagated throughout the rest of the system using the dependence graph of the system. This information is visualized using Change Impact Graphs (CIGs). Through a case study based on the Apache Web Server, we demonstrate the benefit of using CIGs to investigate several real defects.     

北京奥运主场馆区航空真彩色影像的变化检测与分析

中国科学院遥感应用研究所在科技部“科技奥运”专项经费和中科院创新经费的支持下设立了“奥运环境动态监测”课题, 计划从2001 年开始到2008 年每年6~7月航飞一次, 获取真彩色影像、统计分析年施工进度, 将变化信息提供给奥组委和网上发布。介绍了奥运主场馆区2001 年、2002 年和2003 年3 年变化信息的检测技术方法和统计结果。     

基于多模态局部转向核的脑部多发性硬化检测算法研究

容积效应和伪影现象是MR影像处理中的重要影响因素,单模态处理方法易受两者影响。提出一种改进的基于多模态局部转向核的方法来检测大脑中的多发性硬化。该方法利用多模态脑MR影像和大脑近似轴对称的先验知识来进行大脑情况的变化检测。局部转向核能够度量像素与其周围环境的相似程度,因此该方法将局部转向核作为特征,用余弦相似性来衡量差异性。实验结果表明,多模态的引入减少了容积效应和伪影现象,改善了检测效果。     

高分辨率光学遥感影像变化检测算法在地震灾情调查中的应用

遥感卫星可快速、动态地获取地震灾区大范围的高分辨率影像,已成为快速获取震后灾情信息的主要技术手段之一。基于震后灾情调查中广泛使用的光学遥感数据和变化检测算法,首先对遥感数据及其产品进行了归纳总结,在此基础上综述了基于高分辨率遥感影像的变化检测算法在震害提取中的应用,阐述了基于像元和面向对象两类变化检测方法的基本原理和优缺点,讨论和总结了应用中存在的问题和不足,以期为未来地震应急中的灾情调查工作提供参考。     

Error Analysis of Change Detection based on Land Cover in High Resolution Remote Sensing Images in Urban Areas

Land use/land cover change detection using high spatial resolution remote sensing image is an important content in land monitoring.However,the problems of shadow,image registration,threshold selection,detection method selection and image post-processing are more prominent in high-resolution images compared with that in medium and low resolution images,which result in more difficulties and uncertainties.Change detection of land cover was carried out base on aerial color images between 2009 and 2012 in Xianlin District of Nanjing,and the errors were analyzed in terms of intra-class and inter-class.The results show that the inter-class error accounted for 97.6% in the omission error,and the intra-class error accounted for 87.1% in the commission error.According to the error sources,72.6% of the false negative pixels are derived from the detection method,43.6% of the false positive pixels are come from detection method while 39.7% from radiation inconsistent.The analysis results in the paper provided reference for the development of new change detection algorithm.     

基于对象级分类的土地覆盖动态变化及趋势分析

以广东省东莞市2005~2008年SPOT 5遥感影像为主要数据源,采用对象级分类后比较的变化检测技术,从土地覆盖类型的面积总量、相互转移等方面多层次分析了研究区域4 a土地覆盖的变化情况。在此基础上,利用马尔科夫链模型对该区域未来5 a的土地覆盖动态变化及演变趋势进行了分析和预测,为广东省土地覆盖变化研究提供典型案例分析,以达到全面把握研究区土地覆盖变化规律的目标。结果表明:研究区域的土地覆盖变化基本趋势表现为城镇建设用地总量持续增加以及耕地和园林地面积总量减少,其中城镇建设用地和农业耕地变化幅度较大,其他类型土地变化相对稳定。增加的城镇建设用地主要来源于耕地的人为减少,农业垦殖环境将趋于恶化。研究结果可为研究区合理有效地利用土地以促进土地可持续发展、推进城市化进程奠定决策上的技术基础。     

基于非下采样Shearlet和几何结构的遥感图像无监督变化检测

提出了基于非下采样Shearlet和几何结构的遥感图像无监督变化检测新算法。首先将两幅SAR图像相减取绝对值得到差异图像,然后利用基于非下采样Shearlet自适应贝叶斯阈值去噪算法对差异图像进行去噪处理来减少噪声的影响。最后根据差异图像的局部几何特征和邻域信息构造跨特征矢量,再利用模糊C-means聚类算法对跨特征矢量聚类,聚类的结果为变化类和未变化类即最终的变化检测结果。实验证明:该算法对噪声的抗噪性能平稳而且有效,可以得到较好的检测结果。     

聚合级CGF队形变换的仿真

文章以美军坦克排为例,提出了用逼近法建立队形变换这一战术动作的数学模型,并探讨了用计算机仿真实现的方法,该技术已在装甲兵数字化部队作战仿真实验室中得到应用。     

天津滨海新区-曹妃甸典型地区土地利用演变分析

根据1984、2000、2006和2009年4期Landsat影像,运用分类后比较法以及土地利用演变的时空分析方法,探讨和分析天津滨海新区和河北曹妃甸地区近30 a的土地利用变化特征和规律,阐明了研究区土地利用变化的区域特点,为土地可持续利用提供有效的决策支持。结果表明：坑塘水面是两个区域最主要的土地利用类型,尤其在曹妃甸地区,坑塘水面占用比例达60%~70%。1984~2009年两地区围海造地面积呈增加趋势,有“向海洋要土地”的发展趋势。土地利用变化的主要特征为耕地减少和建设用地、坑塘水面增加,2000年以后土地利用变化趋势尤为显著。滨海新区建设用地重心有西南方向移动的趋势,其他土地利用类型重心均有向东向北迁移的趋势,曹妃甸地区各土地类型均有明显的南移趋势。     

基于Landsat影像的北京植被覆盖度变化趋势分析

植被覆盖状况是决定大城市地区生态环境质量的重要因素之一,但在快速城市化进程下城市内部及周边地区植被覆盖的动态变化状况尚不清晰,需结合遥感数据进行分析.以北京市为研究区,基于Landsat影像获取植被覆盖度的空间分布,计算移动窗口内植被覆盖度的均值和标准差,将其分别作为表征局部植被覆盖水平和植被覆盖度异质性的指标,采用M...     

厦门岛及其邻域海岸线变化的遥感动态监测

利用美国Landsat TM/ETM+卫星影像,分1989、1995和2000年3个时相,研究了福建省厦门市从1989~2000年的岸线变化情况。岸线变化的信息主要通过变化检测和信息提取等一系列遥感技术来获得。研究结果表明,厦门市在所研究的1989~2000年期间,海域面积共减少了7.54 km²,这主要是由于城市用地扩展和养殖业发展占用了海域的面积。分时段研究表明,从1995~2000年,海域减少的面积明显要比1989~1995年期间来的多,这从一个侧面反映了厦门在1995~2000年间,城市建设和经济发展对土地提出了更高的需求。     

湖北省兴山县10 年土地利用/覆盖变化遥感监测分析

利用多平台遥感影像和地理辅助信息获取土地利用/覆盖信息是遥感应用的一个重要方面。选择三峡库区湖北省兴山县作为研究区域, 以两期TM 和SPOT 影像为土地利用/覆盖信息提取的遥感信息源, 并在分类过程中结合该地区的地理辅助信息。通过对分类结果分析, 林地和耕地是兴山县两大用地类型, 运用数据运算规则, 获取土地利用/覆盖动态转换矩阵, 对兴山县10 年间土地利用/覆盖变化趋势及引起土地利用/覆盖模式变化的原因进行分析和评价。     

基于Petri网行为包含和行为继承的业务流程变化域传播分析

业务流程建模问题一直是业务流程管理的核心问题,其目的是为了灵活地适应变化的商务需求,但在建模过程中也会出现一系列的问题,有些模型之间甚至存在着相同的问题,因此会出现变化域传播的现象。已有的方法主要是从边界变迁的减少和内部边界变迁的减少来分析模型的变化域传播,因而具有一定的局限性。为了研究模型间的变化域传播问题,基于源模型和目标模型之间存在的迹等价及行为包含关系,通过给定源模型的变化域,提出了基于行为继承的变化域传播分析方法来寻找目标模型的变化域。最后,通过一个具体的流程实例进一步说明了该方法的可行性。     

Comparison of Tasseled Cap-based Landsat data structures for use in forest disturbance detection

Landsat satellite data has become ubiquitous in regional-scale forest disturbance detection. The Tasseled Cap (TC) transformation for Landsat data has been used in several disturbance-mapping projects because of its ability to highlight relevant vegetation changes. We used an automated composite analysis procedure to test four multi-date variants of the TC transformation (called “data structures” here) in their ability to facilitate identification of stand-replacing disturbance. Data structures tested included one with all three TC indices (brightness, greenness, wetness), one with just brightness and greenness, one with just wetness, and one called the Disturbance Index (DI) which is a novel combination of the three TC indices. Data structures were tested in the St. Petersburg region of Russia and in two ecologically distinct regions of Washington State in the US. In almost all cases, the TC variants produced more accurate change classifications than multi-date stacks of the original Landsat reflectance data. In general, there was little overall difference between the TC-derived data structures. However, DI performed better than the others at the Russian study area, where slower succession rates likely produce the most durable disturbance signal. Also, at the highly productive western Washington site, where the disturbance signal is likely the most ephemeral, DI and wetness performed worse than the larger data structures when a longer monitoring interval was used (eight years between image acquisitions instead of four). This suggests that both local forest recovery rates and the re-sampling interval should be considered in choosing a Landsat transformation for use in stand-replacing disturbance detection.     

Snow Cover Change Analysis within the Year of Typical Area in Tianshan Mountains

Using the observation snow cover data from Landsat TM and ETM+ from January 2000 to May 2001, the inter annual temporal and spatial characteristics of snow cover over middle Tianshan mountains are analyzed. Combining with digital elevation model (DEM) data, the distribution of snow cover in different terrain conditions and different altitude per-month are acquired. After analyzing the spatial distribution and temporal variation regulation of snow cover, it comes to a conclusion that the snow cover within year is correlated with altitude, aspect and slope. On the whole, the ratio of snow cover within year increases when the altitude increases and it decreases when the slope increases. The average height of snow cover boundary is high in summer and autumn but low in spring and winter. The difference of snow cover in aspect west and east is obvious in certain times, but the difference is less than that of the aspect north and south. This study provides a scientific support for utilization of water resource and the research of climate and environment in Tianshan Mountains.     

Change of basis algorithms for surfaces in CAGD

The computational complexity of general change of basis algorithms from one bivariate polynomial basis of degree n to another bivariate polynomial basis of degree n using matrix multiplication is O(n⁴). Applying blossoming and duality, we derive change of basis algorithms with computational complexity O(n³) between two important classes of polynomial bases used for representing surfaces in CAGD: B-bases and L-bases. Change of basis algorithms for B-bases follow from their blossoming property; change of basis algorithms for L-bases follow from the duality between L-bases and B-bases. The Bézier and multinomial bases are special cases of both B-bases and L-bases, so these algorithms can be used to convert between the Bézier and multinomial forms. We also show that the bivariate Horner evaluation algorithm for the multinomial basis is dual to the bivariate de Boor evaluation algorithm for B-patches.     

Genetic algorithms for optimality of data hiding in digital images

This paper investigates the scope of usage of Genetic Algorithms (GA) for data hiding in digital images. The tool has been explored in this topic of research to achieve an optimal solution in multidimensional nonlinear problem of conflicting nature that exists among imperceptibility, robustness, security and payload capacity. Two spatial domain data hiding methods are proposed where GA is used separately for (i) improvement in detection and (ii) optimal imperceptibility of hidden data in digital images respectively. In the first method, GA is used to achieve a set of parameter values (used as Key) to represent optimally the derived watermark in the form of approximate difference signal used for embedding. In the second method, GA is used for finding out values of parameters, namely reference amplitude (A) and modulation index (μ) both with linear and non linear transformation functions, for achieving the optimal data imperceptibility. Results on robustness for both the methods against linear, non linear filtering, noise addition, and lossy compression as well as statistical invisibility of the hidden data are reported here for some benchmark images.