城市雨洪放大效应驱动因子时空演变规律分析

城市雨洪具有复杂的放大效应,引起该现象较直接的原因包括大暴雨的频繁出现、可渗透地表面积的骤减以及排蓄水能力的改变和排水管网的扩张等。以武汉市为例,选择降雨强度、不透水面积比例、排水管道密度作为洪水放大效应的驱动因子进行趋势分析和演变规律分析,计算表明:从20世纪80年代开始,暴雨雨量和历时明显增加;不透水面在20世纪90年代初增加较快;排水管道在1990~2006年间缓慢增长,2007年跳跃式增长。降雨量和历时的增加使城市洪量增大,排水压力随之上升,在一定程度上增加了内涝几率;不透水面积的逐年增多以及水体等天然蓄水区的减少,不但增加了产流量,也使汇流时间更短,且雨水管渠的建设缩短了天然汇流路径,导致城市洪水呈现峰高量大,洪峰提前的放大效应。研究成果可用于城市雨洪放大效应对其驱动因子的定量响应研究,为进一步量化城市内涝风险与驱动因子间的关系提供依据,从而为内涝风险调控措施提供技术支撑。     

Visual learning and classification of human epithelial type 2 cell images through spontaneous activity patterns

Identifying the presence of anti-nuclear antibody (ANA) in human epithelial type 2 (HEp-2) cells via the indirect immunofluorescence (IIF) protocol is commonly used to diagnose various connective tissue diseases in clinical pathology tests. As it is a labour and time intensive diagnostic process, several computer aided diagnostic (CAD) systems have been proposed. However, the existing CAD systems suffer from numerous shortcomings due to the selection of features, which is commonly based on expert experience. Such a choice of features may not work well when the CAD systems are retasked to another dataset. To address this, in our previous work, we proposed a novel approach that learns a set of filters from HEp-2 cell images. It is inspired by the receptive fields in the mammalian's vision system, since the receptive fields can be thought as a set of filters for similar shapes. We obtain robust filters for HEp-2 cell classification by employing the independent component analysis (ICA) framework. Although, this approach may be held back due to one particular problem; ICA learning requires a sufficiently large volume of training data which is not always available. In this paper, we demonstrate a biologically inspired solution to address this issue via the use of spontaneous activity patterns (SAP). The spontaneous activity patterns, which are related to the spontaneous neural activities initialised by the chemical release in the brain, are found as the typical stimuli for the visual cell development of newborn animals. In the classification system for HEp-2 cells, we propose to model SAP as a set of small image patches containing randomly positioned Gaussian spots. The SAP image patches are generated and mixed with the training images in order to learn filters via the ICA framework. The obtained filters are adopted to extract the set of responses from a HEp-2 cell image. We then employ regions from this set of responses and stack them into “cubic regions”, and apply a classification based on the correlation information of the features. We show that applying the additional SAP leads to a better classification performance on HEp-2 cell images compared to using only the existing patterns for training ICA filters. The improvement on classification is particularly significant when there are not enough specimen images available in the training set, as SAP adds more variations to the existing data that makes the learned ICA model more robust. We show that the proposed approach consistently outperforms three recently proposed CAD systems on two publicly available datasets: ICPR HEp-2 contest and SNPHEp-2.     

3D soft-tissue tracking using spatial-color joint probability distribution and thin-plate spline model

Visual tracking techniques based on stereo endoscope are developed to measure tissue motion in robot-assisted minimally invasive surgery. However, accurate 3D tracking of tissue surfaces remains challenging due to complicated deformation, poor imaging conditions, specular reflections and other dynamic effects during surgery. This study employs a robust and efficient 3D tracking scheme with two independent recursive processes, namely kernel-based inter-frame motion estimation and model-based intra-frame 3D matching. In the first process, target region is represented in joint spatial-color space for robust estimation. By defining a probabilistic similarity measure, a mean-shift-based iterative algorithm is derived for location of the target region in a new image. In the second process, the thin-plate spline model is used to fit the 3D shape of tissue surfaces around the target region. An iterative algorithm based on an efficient second-order minimization technique is derived to compute optimal model parameters. The two processes can be computed in parallel. Their outputs are combined to recover 3D information about the target region. The performance of the proposed method is validated using phantom heart videos and in vivo videos acquired by the daVinci^®${\mathrm{daVinci}}^{\circledR }$ surgical robotic platform and a synthesized data set with known ground truth.     

A comparative study of two wayfinding aids for simulated driving tasks – single-scale and dual-scale GPS aids

Global Positioning System (GPS) is currently the most frequently used wayfinding aid for driving. Yet, GPS is designed to act as a driving guide rather than to help users gain spatial knowledge. Accordingly, GPS might be less usable in situations where such knowledge is required or highly desirable. In this study, we experimentally study the influence of GPS display scales (single-scale vs. dual-scale) using simulated driving tasks in a virtual environment. The single-scale GPS is similar to the regular GPS view. The dual-scale GPS aid is a dual-scale navigation tool that provides two levels of detail, including both detailed and contextual information. The results demonstrate that the dual-scale GPS was more efficient in leading the participants to the destination during the simulated driving and was more useful for the participants to establish spatial awareness and a cognitive map; the dual-scale GPS participants also reported higher subjective evaluations. The proposed dual-scale GPS design and experimental results show some indications for designing new wayfinding aids aimed at increasing wayfinding performance while simultaneously helping users construct a cognitive map.     

Laplacian colormaps: a framework for structure‐preserving color transformations

Mappings between color spaces are ubiquitous in image processing problems such as gamut mapping, decolorization, and image optimization for color‐blind people. Simple color transformations often result in information loss and ambiguities, and one wishes to find an image‐specific transformation that would preserve as much as possible the structure of the original image in the target color space. In this paper, we propose Laplacian colormaps, a generic framework for structure‐preserving color transformations between images. We use the image Laplacian to capture the structural information, and show that if the color transformation between two images preserves the structure, the respective Laplacians have similar eigenvectors, or in other words, are approximately jointly diagonalizable. Employing the relation between joint diagonalizability and commutativity of matrices, we use Laplacians commutativity as a criterion of color mapping quality and minimize it w.r.t. the parameters of a color transformation to achieve optimal structure preservation. We show numerous applications of our approach, including color‐to‐gray conversion, gamut mapping, multispectral image fusion, and image optimization for color deficient viewers.     

Examining the Effects of Conformal Terrain Features in Advanced Head‐Up Displays on Flight Performance and Pilot Situation Awareness

Synthetic vision systems (SVS) render terrain features for pilots through cockpit displays using a GPS database and three‐dimensional graphical models. Enhanced vision systems (EVS) present infrared imagery of terrain using a forward‐looking sensor in the nose of an aircraft. The ultimate goal of SVS and EVS technologies is to support pilots in achieving safety under low‐visibility and night conditions comparable to clear, day conditions. This study assessed pilot performance and situation awareness (SA) effects of SVS and EVS imagery in an advanced head‐up display (HUD) during a simulated landing approach under instrument meteorological conditions. Videos of the landing with various HUD configurations were presented to eight pilots with a superimposed tracking task. The independent variables included four HUD feature configurations (baseline [no terrain imagery], SVS, EVS, and a combination of SVS and EVS), two visibility conditions, and four legs of the flight. Results indicated that SVS increased overall SA but degraded flight path control performance because of visual confusion with other display features. EVS increased flight path control accuracy but decreased system (aircraft) awareness because of visual distractions. The combination of SVS and EVS generated offsetting effects. Display configurations did not affect pilot spatial awareness. Flight performance was not different among phases of the approach, but levels and types of pilot SA did vary from leg to leg. These results are applicable to development of adaptive HUD features to support pilot performance. They support the use of multidimensional measures of SA for insight on pilot information processing with advanced aviation displays. © 2012 Wiley Periodicals, Inc.     

Evaluation of stereo correspondence algorithms and their implementation on FPGA

The accuracy of stereo vision has been considerably improved in the last decade, but real-time stereo matching is still a challenge for embedded systems where the limited resources do not permit fast operation of sophisticated approaches. This work presents an evaluation of area-based algorithms used for calculating distance in stereoscopic vision systems, their hardware architectures for implementation on FPGA and the cost of their accuracies in terms of FPGA hardware resources. The results show the trade-off between the quality of such maps and the hardware resources which each solution demands, so they serve as a guide for implementing stereo correspondence algorithms in real-time processing systems.     

浅谈电子产品对儿童的影响及对策

在现代社会中,平板电脑、智能手机在人们日常生活的方方面面发挥着巨大的作用。通过分析电子产品在儿童和青少年的视力、身体发育、社交能力和学习能力等方面的负面影响,提出了加强亲子陪伴、合理引导控制等应对措施。