This paper presents a method to integrate GIS and computational models in emergency intelligent decision support system (IDSS) for more scientific and effective loss prevention and disaster manipulation. The value of ...
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This paper presents a method to integrate GIS and computational models in emergency intelligent decision support system (IDSS) for more scientific and effective loss prevention and disaster manipulation. The value of GIS in emergency management arises directly from the benefits of integrating a technology to support spatial decision making. Now many simulation models requiring spatio-temporal information are used to study emergency or disaster scenarios. When they are integrated with GIS for emergency risk analysis and visualization, their effects can be significantly enhanced. Architecture for integration of disaster simulation models with GIS was presented. Disaster evolution prediction, impact areas demarcation, human behavior simulation and real-time data acquisition were integrated and considered in a correlative manner. The results were further visualized on GIS maps for better situation understanding and decision making.
Web-based geographic information systems related research and its applications have been making rapid progress. Computers with fast processing units and large amounts of memory allow for practical applications of time...
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Web-based geographic information systems related research and its applications have been making rapid progress. Computers with fast processing units and large amounts of memory allow for practical applications of time consuming and resource intensive algorithms, both for spatial analysis as well as visualization of large-volume data such as high resolution raster images, DTM and vector data. However, most Web-based geographic information systems are used for presentation of static data, while the area of dynamic and semi-dynamic datavisualization has been mostly neglected. Novel applications of known devices and models such as synthetic aperture radar and oil spill simulations require interactive data presentation, which up until now has been mostly realized using standalone applications or thick Web clients. This paper describes a number of Web-based GIS technologies for presentation of semi-dynamic geographic information retrieved from many different sources. It also describes the possibilities these technologies provide for publishing interactive geospatial data such as oil spill spread animation overlaid on background data (eg. terrain elevation data, satellite imagery) and presented in a geographic context. Web-GIS technologies like ESRI ArcIMS (Arc Internet map server) and open source geoserver with OpenLayers client library were compared during the research. The paper presents their corresponding capabilities, interactive geographic information presentation efficiency as well as general performance when serving considerable amounts of data.
In this demonstration we showcase an interactive analysis tool for researchers working on concept-based video retrieval. By visualizing intermediate concept detection analysis stages, the tool aids in understanding th...
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In this demonstration we showcase an interactive analysis tool for researchers working on concept-based video retrieval. By visualizing intermediate concept detection analysis stages, the tool aids in understanding the success and failure of video concept detection methods. We demonstrate the tool on the domain of pop concert video.
Code clones are similar program structures recurring in software systems. Clone detectors produce much information and a challenge is to identify useful clones depending on the goals of clone analysis. To do so, furth...
Code clones are similar program structures recurring in software systems. Clone detectors produce much information and a challenge is to identify useful clones depending on the goals of clone analysis. To do so, further abstraction, filtering and visualization of cloning information, with the involvement of a human expert, is required. In this paper, we describe a technique for filtering and visualization of cloning information generated by Clone Miner, a clone detection tool presented in our earlier work. Unique benefit and contribution of our approach is that a human expert can define a wide range of filters to extract abstract views of the cloning data using a clone-query system to suit specific needs of clone analysis. We then produce standardized graphical presentations of those views for various types of clone queries. We implemented the technique into an Eclipse plug-in called Clone Visualizer. Clone Visualizer works closely with Clone Miner which not only finds similar code fragments (simple clones) but also finds higher-level abstractions of the cloning information. Our method is the first attempt to address filtering and visualization of those higher level cloning abstractions. We illustrate application of our technique with examples from a clone analysis project with Clone Miner and Clone Visualizer.
Recurrence plots visualize spatial and temporal correlations inside sequence of data. This technique allows the identification of hidden data relationships inside a data sequence. The comparison between recurrence plo...
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ISBN:
(纸本)9781424432455
Recurrence plots visualize spatial and temporal correlations inside sequence of data. This technique allows the identification of hidden data relationships inside a data sequence. The comparison between recurrence plots in order to identify common structures is difficult because the lack of similarity quantification tools in the available software for recurrence plots analysis such as VRA (Visual Recurrence analysis), RQA (Recurrence Quantification analysis) and CRP (Cross Recurrence Plots). In this work a software tool for analysis of structural similarity between recurrent plots is proposed, the tool named RecurrenceVs allows the comparison and quantification of similarity between recurrence plots generated from different sequences of data. Also it allows the generation of a classification by their similarity degree between recurrence plots from a set under study. Different datasets from time series to genomic sequences were used to evaluate the performance and usability of this tool.
We propose a novel postprocessing technique for identifying sets of association rules that expose a user-specified temporal development. We explicitly do not use a learning approach that requires the database to be su...
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We propose a novel postprocessing technique for identifying sets of association rules that expose a user-specified temporal development. We explicitly do not use a learning approach that requires the database to be subdivided into time frames. Instead, a global probabilistic learning method is used for induction. The resulting association rules are then matched against a set of fuzzy concepts. These concepts comprise user-built linguistic propositions that describe the evolution of rules that might be considered interesting. The proposed technique is evaluated on a real-world data set. To present the results, we introduce a modified rule visualization along the way that is an extension of our previous work.
Program comprehension is an important concern in software maintenance because these tasks generally require a degree of knowledge of the system at hand. While the use of dynamic analysis in this process has become inc...
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Program comprehension is an important concern in software maintenance because these tasks generally require a degree of knowledge of the system at hand. While the use of dynamic analysis in this process has become increasingly popular, the literature indicates that dealing with the huge amounts of dynamic information remains a formidable challenge.
The wavelet transform has been shown to be a powerful tool for characterising network ***, the resulting decomposition of a wavelet transform typically forms a high-dimension space. This is obviously problematic on co...
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The wavelet transform has been shown to be a powerful tool for characterising network ***, the resulting decomposition of a wavelet transform typically forms a high-dimension space. This is obviously problematic on compact representations,visualizations, and modelling approaches that are based on these high-dimensional data. In this study, we show how data projection techniques can represent the high-dimensional wavelet decomposition in a low dimensional space to facilitate visual analysis. A low dimensional representation can significantly reduce the model complexity. Hence, features in the data can be presented with a small number of parameters. We demonstrate these projections in the context of network traffic pattern analysis. The experimental results show that the proposed method can effectively discriminate between different application flows, such as FTP and P2P.
Modern automated video analysis systems consist of large networks of heterogeneous sensors. These systems must extract, integrate and present relevant information from the sensors in real-time. This paper addresses so...
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Modern automated video analysis systems consist of large networks of heterogeneous sensors. These systems must extract, integrate and present relevant information from the sensors in real-time. This paper addresses some of the major challenges such systems face: efficient video processing for high-resolution sensors; data fusion across multiple modalities; robustness to changing environmental conditions and video processing errors; and intuitive user interfaces for visualization and analysis. The paper discusses enabling technologies to overcome these challenges and presents a case study of a wide area video analysis system deployed at a port in the state of Florida, USA. The components of the system are also detailed and justified using quantitative and qualitative results.
The overall performance of a computing system increasingly depends on the efficient use of the cache memories. Traditional approaches for cache tuning deploy performance tools to help the user optimize the source prog...
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The overall performance of a computing system increasingly depends on the efficient use of the cache memories. Traditional approaches for cache tuning deploy performance tools to help the user optimize the source program towards a better runtime data locality. Following this conventional way, we developed a set of such toolkits including data profiling, pattern analysis, and performance visualization tools. This paper demonstrates how the toolset can be used step-by-step to understand the cache access behavior of the applications and then achieve optimized program code. The Discrete Wavelet Transform, a common used algorithm for image and video compression, is applied as an example. Our initial experimental results with this sample application show an up to 3.19 speedup in execution time compared to the original implementation.
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