Results of a User Study on 2D Hurricane Visualization

We present the results from a user study looking at the ability of observers to mentally integrate wind direction and magnitude over a vector field. The data set chosen for the study is an MM5 (PSU/NCAR Mesoscale Model) simulation of Hurricane Lili over the Gulf of Mexico as it approaches the southeastern United States. Nine observers participated in the study. This study investigates the effect of layering on the observer's ability to determine the magnitude and direction of a vector field. We found a tendency for observers to underestimate the magnitude of the vectors and a counter‐clockwise bias when determining the average direction of a vector field. We completed an additional study with two observers to try to uncover the source of the counter‐clockwise bias. These results have direct implications to atmospheric scientists, but may also be able to be applied to other fields that use 2D vector fields.     

单片机仿真器EMV—51的工作原理及其使用中问题的解决方法

介绍了单片机仿真器的工作原理，提出了在实际使用中所遇到的一些问题，并给出了解决这些问题的办法。     

Continuous Levels‐of‐Detail and Visual Abstraction for Seamless Molecular Visualization

Molecular visualization is often challenged with rendering of large molecular structures in real time. We introduce a novel approach that enables us to show even large protein complexes. Our method is based on the level‐of‐detail concept, where we exploit three different abstractions combined in one visualization. Firstly, molecular surface abstraction exploits three different surfaces, solvent‐excluded surface (SES), Gaussian kernels and van der Waals spheres, combined as one surface by linear interpolation. Secondly, we introduce three shading abstraction levels and a method for creating seamless transitions between these representations. The SES representation with full shading and added contours stands in focus while on the other side a sphere representation of a cluster of atoms with constant shading and without contours provide the context. Thirdly, we propose a hierarchical abstraction based on a set of clusters formed on molecular atoms. All three abstraction models are driven by one importance function classifying the scene into the near‐, mid‐ and far‐field. Moreover, we introduce a methodology to render the entire molecule directly using the A‐buffer technique, which further improves the performance. The rendering performance is evaluated on series of molecules of varying atom counts.     

Scalable Symmetry Detection for Urban Scenes

In this paper, we present a novel method for detecting partial symmetries in very large point clouds of 3D city scans. Unlike previous work, which has only been demonstrated on data sets of a few hundred megabytes maximum, our method scales to very large scenes: We map the detection problem to a nearest‐neighbour problem in a low‐dimensional feature space, and follow this with a cascade of tests for geometric clustering of potential matches. Our algorithm robustly handles noisy real‐world scanner data, obtaining a recognition performance comparable to that of state‐of‐the‐art methods. In practice, it scales linearly with scene size and achieves a high absolute throughput, processing half a terabyte of scanner data overnight on a dual socket commodity PC.     

Developing a Simple NMR Interface: WWNMR

We have designed and implemented an automated walkup NMR computer application for use by synthetic chemists. The Wyeth Walkup NMR (WWNMR) application is a TCL/TK graphical user interface front-end to Varian's NMR automation routines. The key feature of WWNMR is that the chemists are isolated from the spectrometer's control program (VNMR) and only enter information to WWNMR windows for a sample to be run. The resulting data can be printed out on paper, or stored on disk for easy access by all users at their desktops. Proton and carbon NMR experiments are available. An overview of the WWNMR application will be presented.     

Possibility of grain size prediction in AA5754 aluminium ingots using neural networks

Abstract

The approach to the grain size prediction in AA5754 Al alloy ingots based on artificial neural networks (ANN) has been used in the present study. The ANN has been trained on data that was measured in the real industrial conditions during the process of direct chill Al ingots casting. A very complex relation between the numerous casting parameters and the microstructure of the ingots justifies the application of neural networks, which are known for mapping complex and non-linear systems. A feed forward ANN model with the resilient back-propagation learning algorithm and weight decay regularisation has been developed to relate the grain size to casting rate, meniscus level, casting temperature, water flow for the metal mould cooling and speed of wire for master alloy addition. The results obtained from the ANN are found to be consistent with the theoretical researches and experience from the foundry.     

Generation of Scattering Functions for Mobile Communication Channel: A Computer Simulation Approach

In this paper, an algorithm of generation of thescattering function by computer simulation for the WSSUSurban mobile communication channel is studied. Thescattering function, which contains much valuable information of the channel, is calculatedthrough three approaches. The empirical measuredparameter database and recommended standard methods areused to generate the scattering function as the firstand second approaches. An in-service measurement ofthe GSM network is performed in Singapore, in thefrequency range 935-960 MHz using the Rohde and SchwarzChannel Sounder. The data collected are used for the calculation, as the third approach. Thefour main characteristics of the channel, the Dopplerspread B_d, the multipath spreadT_m, the coherence time t, and thecoherence bandwidth f, are observed. The computer-calculated scattering function isshown to be an accurate and effective tool forsimulation of WSSUS channels. As a result, a softwarepackage is developed and utilized in the X-Windowenvironment for the simulation of the urban mobilecommunication channel. It can meet most of therequirements of both the system designers and theservice providers.     

Relativistic Effects for Time‐Resolved Light Transport

We present a real‐time framework which allows interactive visualization of relativistic effects for time‐resolved light transport. We leverage data from two different sources: real‐world data acquired with an effective exposure time of less than 2 picoseconds, using an ultra‐fast imaging technique termed femto‐photography, and a transient renderer based on ray‐tracing. We explore the effects of time dilation, light aberration, frequency shift and radiance accumulation by modifying existing models of these relativistic effects to take into account the time‐resolved nature of light propagation. Unlike previous works, we do not impose limiting constraints in the visualization, allowing the virtual camera to explore freely a reconstructed 3D scene depicting dynamic illumination. Moreover, we consider not only linear motion, but also acceleration and rotation of the camera. We further introduce, for the first time, a pinhole camera model into our relativistic rendering framework, and account for subsequent changes in focal length and field of view as the camera moves through the scene.     

Process simulation of powder injection moulding: identification of significant parameters during mould filling phase

Abstract

Simulating and optimising the powder injection process are complex problems since a number of linked material, geometry and process variables have to be considered. In addition, it is very difficult to identify critical parameters for designing binder systems, feedstocks, parts, moulds and processing conditions owing to the fact that multiple objective functions have to be considered. Towards the goal of identifying the level of significance of various material, process and geometry parameters during powder injection moulding, a systematic procedure for sensitivity analysis has been successfully developed for the mould filling phase of the PIM process. In this sensitivity analysis, all input parameters were defined for the mould filling simulation and all output parameters for optimum design of part, mould and processing conditions and dimensionless sensitivity values for all input and output parameters were calculated, which allow parameters with different units to be compared quantitatively. The sensitivity analysis procedure developed will be an invaluable tool for both the design engineer in the PIM industry who has to determine the critical input parameters for given design targets, as well as for the production engineer who has to optimise and monitor the production stage.     

Instant Propagation of Sparse Edits on Images and Videos

The ability to quickly and intuitively edit digital contents has become increasingly important in our everyday life. We propose a novel method for propagating a sparse set of user edits (e.g., changes in color, brightness, contrast, etc.) expressed as casual strokes to nearby regions in an image or video with similar appearances. Existing methods for edit propagation are typically based on optimization, whose computational cost can be prohibitive for large inputs. We re‐formulate propagation as a function interpolation problem in a high‐dimensional space, which we solve very efficiently using radial basis functions. While simple to implement, our method significantly improves the speed and space cost of existing methods, and provides instant feedback of propagation results even on large images and videos.