Shadow generation for volumetric data sets

Z -buffer technique for fast and efficient shadow generation. Volumetric data contain information about the grid points only. Such data do not provide surface information that could be projected immediately onto the shadow map. To solve this problem, we have implemented two techniques. The first uses a modified adaptive version of the well-known marching cubes algorithm for the special characteristics of medical data sets. The algorithm uses material properties for a precise representation of object boundaries, generating volumetric objects quickly and effectively. There are two representations of the same data set: we use a view-independent approximation to display shadows and the original representation of the volume for object visualization in full precision. The second algorithm uses a ray-tracing approach to create shadow maps. The same routine is used for object rendering, but is restricted to depth-value generation. Semitransparent objects are handled by storing an intensity profile in addition to the depth value.     

A type-merging algorithm for extracting an isosurface from volumetric data

A new approach for reducing the number of triangles representing an isosurface in volumetric data is presented. The basic idea is to classify the configurations of the marching cubes approach into types. Surface patches traversing neighboring cubes of the same type can be merged into patches, which can be approximated with fewer and larger triangles. Experimental results show that the number of triangles is about 50% of that obtained with the marching cubes algorithm, with comparable image quality. The execution time is somewhat longer than that of the marching cubes algorithm.     

SimCon: A context simulator for supporting evaluation of smart building applications when faced with uncertainty

Smart Building Applications (SBAs) adapt their behaviour in response to context information generated by sensors present in the smart building. SBA developers must account for uncertainty in the accuracy of context information resulting from imperfection in the sensing technology and potentially complex interactions between the sensed phenomenon, the sensor and the physical environment. To address this challenge, context simulators which generate simulated context information have been developed. A number of key challenges must be addressed before such a simulation-based SBA prototyping approach can become widely used. First, any context simulator must be flexible in its approach to simulating context so that it supports evaluating different mixes of SBAs using a selection of methods most suitable to the evaluation task at hand. Second, the context simulator must support simulating uncertainty in context as uncertainty can cause an SBA to function incorrectly. Finally, the process of setting up a simulation should be efficient in use, satisfying to the developer and also, be effective in correctly evaluating the SBA behaviour. This paper presents the SimCon model which addresses these challenges by supporting simulation of context, in particular location context, with configurable levels of uncertainty for evaluating SBAs using visualisation. The SimCon model has been implemented in a simulation, configuration and visualisation tool set which has undergone a number of evaluations with SBA developers to determine and improve its level of usability, the most recent of which is presented here.     

Some techniques for visualizing surfaces in four-dimensional space

The issues of visualizing two-dimensional surfaces in four-dimensional space are discussed, including methods to specify the orientation of objects and of projection centres, to determine silhouette points of a 2-surface with respect to projections and to calculate the normal of a projected 2-surface from its normal plane in 4-space. We have implemented an interactive 4D display system on a z-buffer graphics workstation. Preliminary experiments show that such a 4D display system can give valuable insights into high-dimensional geometry. Some examples are presented illustrating nonuniform material property display, offset curve geometry and collision detection.     

Industrial environmental performance evaluation: A Markov-based model considering data uncertainty

Commonly, operational aspects of an industrial process are not included when evaluating the process environmental performance. These aspects are important as operational failures can intensify adverse environmental impacts or can diminish the chance of making any amelioration. This paper proposes to include these operational aspects by applying a method called Industrial Environmental Performance Evaluation. To have a reliable environmental performance measure for assisting policy-making in an organization, two types of uncertainty are considered in the proposed method. The first type is the epistemic uncertainty due to imperfect knowledge about the environmental impacts of the process. Epistemic uncertainty is considered by using the potential probability of material release during operating and non-operating periods of the process. The second type is aleatory uncertainty due to potential stochastic behaviour of the process. Aleatory uncertainty is modelled through a Markov-based model and is considered by the state probability distribution vectors. The proposed method is employed to analyze an existing formaldehyde production process as a case study. The analysis shows the relation between environmental and operational performances of the process. Process owners can use this analysis for improving the environmental and operational aspects of their process and achieve accuracy in their environmental decisions.     

Design and evaluation of a decision support system in a water balance application

Visualization has become a vital tool for representing the results of scientific models in decision support applications. Both the raw data and the models from which these visualizations are derived usually have considerable uncertainty associated with them. Decision-makers are typically presented with results from these models with little or no insight as to the reliability of the information shown. For effective decisions to be made, a decision support system should allow collaborative participation from scientists and decision-makers, and it should display the locations, magnitudes, and sources of uncertainty in the results. This research work discusses a software application for visualizing the results of a water balance model and its associated uncertainty. The effectiveness of the application and its visual presentation methods were incrementally tested and improved through usability engineering principles.     

Experimental evaluation of uncertainty in hand-arm vibration measurements

Hand-arm vibration measurements are necessary for vibration exposure risk assessment and for the determination of vibration emission values in hand-guided machines. It has been reported that there is a high degree of uncertainty associated with this kind of measurement. The main goal of the present work is to investigate which factors cause uncertainty in hand-arm vibration evaluation and how much they contribute to the total uncertainty of the measurements. Some experiments were carried out in order to evaluate separately the factors relating to instrumentation and the methods of fixing accelerometers. The experiments were performed with handles belonging to real machines while being handheld by an operator. The results of this investigation show that the fixing method and the accelerometer behaviour are the two main sources of uncertainty. The total uncertainty of the measurements in this work, considering both instrumentation and fixing method, reaches up to 8% of the values measured. It is concluded that the adaptors for fixing the accelerometer with metallic stripe hose clips cause less uncertainty than handheld adaptors and should therefore be used as the first option.

Relevance to industry

A good accuracy in hand-arm measurements is the key for a correct assessment of the risk of developing HAVS (Hand-Arm Vibration Syndrome). Knowledge of the uncertainty factors will help the technicians who carry out the measurements to improve their quality.     

科学考察空间数据WebGIS信息发布及可视化研究

为有效共享科学考察第一手数据资料,结合考察采样及调查数据的时空特性,采用WebGIS及RIA Flex等最新网络及可视化技术,提出一种在线发布科考空间信息的系统框架,实现多元科学考察数据基于WebGIS的空间信息发布与可视化表达.基于J2EE架构设计与实现多元科考空间数据的统一访问Web服务接口,完成空间数据内容的统一...     

RMAP: a system for visualizing data in multidimensional relevance space

exact relevance measures of the objects are not significant. We flatten the multidimensionality of the feature space into a 2D relevance map, capturing the inter-relations among the features. The prototype, extract information from the World Wide Web from query engines, automatically categorizes and clusters the information and allow the user to visualize.     

A language for the classification and shading of multivariate volume data

A novel, language-based interface to the specification of multivariate volume classification and shading algorithms has been implemented. The system facilitates experimentation by providing access to data relevant to volume classification and shading (scalars, gradients, and gradient magnitudes) in a C-like language environment. The user writes code to calculate opacity and colour on a per voxel basis. The code is interpreted and compiled in a transparent fashion and then executed on a volume data-set. The output is a volume primitive suitable for input to standard volume rendering algorithms.     

An image construction method for visualizing managerial data

High volume data with complicated relationships can render human decision-making a frustrating task. Computer-generated visualization is an approach that can assist decision-makers in gaining insight into the data so that eventually superior solutions can be developed. Current research in visualization has addressed how to deal with high volume data that have some inherent structures (such as hierarchy, network, or geographical relationships). Many management domains, however, have data that lack obvious structures to provide a base for computer-generated visualization. This paper reports a specially designed technique for visualizing such management data. Data objects involved in the decision-making tasks are assigned with geometry (called visual abstract) in Euclidean space. Then a set of image construction rules are applied to connect multiple visual abstracts into images that can be displayed on a computer screen. We use two business domains, manufacturing production planning and resource constrained project scheduling, to illustrate this visualization technique.     

Adaptive generation of surfaces in volume data

A widespread approach to generating polygonal approximations of iso-surfaces or contour surfaces in volume data is the socalled marching-cubes algorithm. This algorithm, however, has the disadvantage that the number of polygonal chains generated is considerable. The splitting-box algorithm presented here reduces the number of polygonal chains by adapting their size to the shape of the surface. The resulting polygonal chains offer a wide spectrum for representing the contour surface. An exact representation is achieved by a new type of generic patches calculated from the polygonal chains. Approximations of different quality may be obtained by combining the algorithm generating the patches with simple triangulations.     

Error analysis of ticket vending machines: comparing analytic and empirical data

An error analysis was performed on the three ticket vending machines installed at London underground and overground train stations. A brief analytic inspection, resulting in a set of predicted errors, was followed by lengthy empirical observations of successes, failures and errors occurring during machine use. There were two observational phases, 5 years apart. Comparisons were made between the patterns of error-making on the three machines, using error categories derived from the initial analysis. It was found that these comparisons were sufficient to account for most of the between-machine and between-phase differences, although some unattributed errors remained. It was also found that much of the observed pattern of error-making had been predicted by the initial inspection, and it is suggested that, for relatively simple interfaces such as these, the method (Dialogue Error Analysis) is sufficient to identify and prioritize most problems that will occur in use. Attempt was also made to relate the observed error categories to influential taxonomies of human error.     

Two techniques of sensitivity and uncertainty analysis of fuzzy expert systems

Problems characterized by qualitative uncertainty described by expert judgments can be addressed by the fuzzy logic modeling paradigm, structured within a so-called fuzzy expert system (FES) to handle and propagate the qualitative, linguistic assessments by the experts. Once constructed, the FES model should be verified to make sure that it represents correctly the experts’ knowledge. For FES verification, typically there is not enough data to support and compare directly the expert- and FES-inferred solutions. Thus, there is the necessity to develop indirect methods for determining whether the expert system model provides a proper representation of the expert knowledge. A possible way to proceed is to examine the importance of the different input factors in determining the output of the FES model and to verify whether it is in agreement with the expert conceptualization of the model. In this view, two sensitivity and uncertainty analysis techniques applicable to generic FES models are proposed in this paper with the objective of providing appropriate tools of verification in support of the experts in the FES design phase. To analyze the insights gained by using the proposed techniques, a case study concerning a FES developed in the field of human reliability analysis has been considered.     

Effect of spatial data resolution on uncertainty

The effect that the resolution of spatial data has on uncertainty is important to many areas of research. In order to understand this better, the effect of changing resolution is considered for a range of data. An estimate is presented for how the average uncertainty of each grid value varies with grid size, which is shown to be in good agreement with observed uncertainties. The effect of bilinear interpolation is also investigated and is observed to provide no reduction in uncertainty relative to uninterpolated data. Finally, the effects of combining aggregated spatial data are found to obey standard properties of error propagation, which means that the presented estimate of uncertainty can be used to estimate resolution-related uncertainty in spatial model results, relative to the input data. The study quantitatively demonstrates the important role of the spatial autocorrelation of data in uncertainties associated with the resolution of spatial data.     

Progress in scientific visualization

This paper surveys recent work in the visualization of molecules, scalar fields, and vector fields.     

On the use of second-order derivatives and metamodel-based Monte-Carlo for uncertainty estimation in aerodynamics

This article addresses the delicate issue of estimating physical uncertainties in aerodynamics. Usually, flow simulations are performed in a fully deterministic approach, although in real life operational uncertainty arises due to unpredictable factors that alter the flow conditions. In this article, we present and compare two methods to account for uncertainty in aerodynamic simulation. Firstly, automatic differentiation tools are used to estimate first- and second-order derivatives of aerodynamic coefficients with respect to uncertain variables, yielding an estimate of expectation and variance values (Method of Moments). Secondly, metamodelling techniques (radial basis functions, kriging) are employed in conjunction with Monte-Carlo simulations to derive statistical information. These methods are demonstrated for 3D Eulerian flows around the wing of a business aircraft at different regimes subject to uncertain Mach number and angle of attack.     

A new approach to visualizing time-varying sensitivity indices for environmental model diagnostics across evaluation time-scales

Assessing the time-varying sensitivity of environmental models has become a common approach to understand both the value of different data periods for estimating specific parameters, and as part of a diagnostic analysis of the model structure itself (i.e. whether dominant processes are emerging in the model at the right times and over the appropriate time periods). It is not straightforward to visualize these results though, given that the window size over which the time-varying sensitivity is best integrated generally varies for different parameters. In this short communication we present a new approach to visualizing such time-varying sensitivity across time scales of integration. As a case study, we estimate first order sensitivity indices with the FAST (Fourier Amplitude Sensitivity Test) method for a typical conceptual rainfall–runoff model. The resulting plots can guide data selection for model calibration, support diagnostic model evaluation and help to define the timing and length of spot gauging campaigns in places where long-term calibration data are not yet available.     

利用有序数据结构实现Shear-Warp加速算法

提出一种有序数据结构,在不影响算法效果的前提下,改进并加速Shear-Warp算法的运行速度.将体数据每个层片编码成以体素值为序的有序数组,依据不透明度函数确定不透明体素所对应的体素值范围.通过对有序数组的截取,快速定位不透明体素,跳过所有的透明体素,提高绘制速度.在普通配置计算机上验证该算法,绘制过程一般在数秒内即可完成.该算法思路明晰、操作便捷,在不影响图像质量的前提下显著提高绘制速度,满足实时性的要求.