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Euromicro Symposium on Digital System Design

作者： José L. Risco-Martín David Atienza J. Ignacio Hidalgo Juan Lanchares Department of Computer Architecture and Automation Complutense University of Madrid Madrid Spain

New multimedia embedded applications are increasingly dynamic, and rely on Dynamically-allocated data Types (DDTs) to store their data. The optimization of DDTs for each target embedded system is a time-consuming process due to the large design space of possible DDTs implementations. Thus, suitable exploration methods for embedded design metrics (memory accesses, memory usage and power consumption) need to be developed. This paper presents a design flow to tackle the optimization of DDTs in multimedia applications. By profiling of the original desktop application and using evolutionary algorithms, the proposed approach is able to find solutions 1584x faster than other state-of-the-art heuristics in an automated way. Moreover, we study the use of elitist Multi-Objective Evolutionary Algorithms (MOEAs) to explore DDT implementations, which offer 75% more optimal solutions to the system designer for the implementation of the final embedded application. To this end, we analyze the quality of the solutions by comparing three MOEAS and other optimization heuristics. Our results in two object-oriented multimedia embedded applications show that elitist MOEAs (NSGA-ii and SPEA2) offer better solutions than simple non-elitist schemes (VEGA) and alternative well-known optimization heuristics.

关键词： Evolutionary computation Design optimization Application software Energy consumption Design methodology Embedded system Algorithm design and analysis Computer architecture Digital systems Design automation

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静息状态默认脑活动网络的初步检验--听觉呈现语言任务

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中国医学影像技术 2008年第2期24卷 205-208页

作者：孙国祥刘君赵小虎王培军席芊董宁欣王国良同济大学附属同济医院设备物资处上海200065 同济大学附属同济医院医学影像科上海200065

目的利用fMRI技术,通过听觉呈现语言任务,探讨刺激呈现通道对负激活脑区的影响,进一步检验静息状态人脑默认活动假说。方法13名健康成年志愿者参加实验。进行2次fMRI实验。实验1(简单任务)任务期要求受试者听无意义假词;实验2(复杂任务... 详细信息

目的利用fMRI技术,通过听觉呈现语言任务,探讨刺激呈现通道对负激活脑区的影响,进一步检验静息状态人脑默认活动假说。方法13名健康成年志愿者参加实验。进行2次fMRI实验。实验1(简单任务)任务期要求受试者听无意义假词;实验2(复杂任务)要求受试者听真词并作词语属性判断(具体或抽象)。静息期要求受试者闭眼、静卧,不要做任何主动思维活动。利用SPM2软件进行数据处理。先分析单个被试,然后行组间比较。采用反减法获得负激活图。并把本次实验结果与以往视觉呈现任务结果进行比较。结果初级视觉皮层与初级听觉皮层的负激活存在明显的通道依赖性,听觉呈现刺激引起视觉皮层负激活,视觉呈现刺激时听觉皮层表现为负激活。非任务依赖性负激活脑区包括扣带回后部/楔前叶(BA31/30)、扣带回前部(BA24/32)、两侧颞上回(BA8)、两颞下回前部(BA20)、两侧顶下小叶(BA39/40)。这些区域的负激活与刺激呈现通道方式及特定刺激任务无关。该负激活脑区模式与人类默认脑活动网络基本一致。结论刺激呈现通道是影响任务依赖性负激活的因素之一,探讨负激活问题时应该考虑到这一因素。同时,本研究进一步验证了静息状态时人脑默认活动假说。

关键词：磁共振成像负激活默认活动网络语言听觉

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Interactive visual exploration of a large spatio-temporal dataset: Reflections on a geovisualization mashup

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IEEE TRANSACTIONS ON visualIZATION AND COMPUTER GRAPHICS 2007年第6期13卷 1176-1183页

作者： Wood, Jo Dykes, Jason Slingsby, Aidan Clarke, Keith City Univ London Dept Informat Sci London England Univ Calif Santa Barbara Dept Geog Santa Barbara CA 93106 USA

Exploratory visual analysis is useful for the preliminary investigation of large structured, multifaceted spatio-temporal datasets. This process requires the selection and aggregation of records by time, space and attribute, the ability to transform data and the flexibility to apply appropriate visual encodings and interactions. We propose an approach inspired by geographical 'mashups' in which freely-available functionality and data are loosely but flexibly combined using de facto exchange standards. Our case study combines MySQL, PHP and the LandSerf GIS to allow Google Earth to be used for visual synthesis and interaction with encodings described in KML. This approach is applied to the exploration of a log of 1.42 million requests made of a mobile directory service. Novel combinations of interaction and visual encoding are developed including spatial 'tag clouds', 'tag maps', 'data dials' and multi-scale density surfaces. Four aspects of the approach are informally evaluated: the visual encodings employed, their success in the visual exploration of the clataset, the specific tools used and the 'rnashup' approach. Preliminary findings will be beneficial to others considering using mashups for visualization. The specific techniques developed may be more widely applied to offer insights into the structure of multifarious spatio-temporal data of the type explored here.

关键词： large dataset visualization text and document visualization multiresolution visualization geographic visualization applications of infovis

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Fast training of Self Organizing Maps for the visual exploration of molecular compounds

Fast training of Self Organizing Maps for the visual explora...

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International Joint conference on Neural Networks

作者： Fiannaca, Antonino Di Fatta, Giuseppe Rizzo, Riccardo Urso, Alfonso Gaglio, Salvatore CNR ICAR I-00185 Rome Italy Univ Reading Sch Syst Engn Reading Berks England Univ Palermo DINFO Palermo Italy

ISBN: (纸本)9781424413799

visual exploration of scientific data in life science area is a growing research field due to the large amount of available data. The Kohonen's Self Organizing Map (SOM) is a widely used tool for visualization of multidimensional data. In this paper we present a fast learning algorithm for SOMs that uses a simulated annealing method to adapt the learning parameters. The algorithm has been adopted in a data analysis framework for the generation of similarity maps. Such maps provide an effective tool for the visual exploration of large and multi-dimensional input spaces. The approach has been applied to data generated during the High Throughput Screening of molecular compounds;the generated maps allow a visual exploration of molecules with similar topological properties. The experimental analysis on real world data from the National Cancer Institute shows the speed up of the proposed SOM training process in comparison to a traditional approach. The resulting visual landscape groups molecules with similar chemical properties in densely connected regions.

关键词： Self organizing maps

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analysis guided visual exploration of multivariate data 07

Analysis guided visual exploration of multivariate data

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IEEE Symposium on visual Analytics Science and Technology

作者： Yang, Di Rundensteiner, Elke A. Ward, Matthew O. Worcester Polytech Inst Worcester MA USA

ISBN: (纸本)9781424416592

visualization systems traditionally focus on graphical representation of information. They tend not to provide integrated analytical services that could aid users in tackling complex knowledge discovery tasks. Users' exploration in such environments is usually impeded due to several problems: 1) valuable information is hard to discover when too much data is visualized on the screen;2) Users have to manage and organize their discoveries off line, because no systematic discovery management mechanism exists;3) their discoveries based on visual exploration alone may lack accuracy;4) and they have no convenient access to the important knowledge learned by other users. To tackle these problems, it has been recognized that analytical tools must be introduced into visualization systems. In this paper, we present a novel analysis-guided exploration system, called the Nugget Management System (NMS). It leverages the collaborative effort of human comprehensibility and machine computations to facilitate users' visual exploration processes. Specifically, NMS first extracts the valuable information (nuggets) hidden in datasets based on the interests of users. Given that similar nuggets may be re-discovered by different users, NMS consolidates the nugget candidate set by clustering based on their semantic similarity. To solve the problem of inaccurate discoveries, localized data mining techniques are applied to refine the nuggets to best represent the captured patterns in datasets. Lastly, the resulting well-organized nugget pool is used to guide users' exploration. To evaluate the effectiveness of NMS, we integrated NMS into Xmd-vTool, a freeware multivariate visualization system. User studies were performed to compare the users' efficiency and accuracy in finishing tasks on real datasets, with and without the help of NMS. Our user studies confirmed the effectiveness of NMS.

关键词： visual analytics visual knowledge discovery discovery management analysis guided exploration

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Geographically weighted visualization: Interactive graphics for scale-varying exploratory analysis

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IEEE TRANSACTIONS ON visualIZATION AND COMPUTER GRAPHICS 2007年第6期13卷 1161-1168页

作者： Dykes, Jason Brunsdon, Chris City Univ London Dept Informat Sci London EC1V 0HB England Univ Leicester Dept Geog Leicester LE1 7RH Leics England

We introduce a series of geographically weighted (GW) interactive graphics, or geowigs, and use them to explore spatial relationships at a range of scales. We visually encode information about geographic and statistical proximity and variation in novel ways through gw-choropleth maps, multivariate gw-boxplots, gw-shading and scalograms. The new graphic types reveal information about GW statistics at several scales concurrently. We impernent these views in prototype software containing dynamic links and GW interactions that encourage exploration and refine them to consider directional geographies. An informal evaluation uses interactive GW techniques to consider Guerry's clataset of 'moral statistics', casting doubt on correlations originally proposed through visual analysis, revealing new local anomalies and suggesting multivariate geographic relationships. Few attempts at visually synthesising geography with multivariate statistical values at multiple scales have been reported. The geowigs proposed here provide informative representations of multivariate local variation, particularly when combined with interactions that coordinate views and result in gw-shading. We argue that they are widely applicable to area and point-based geographic data and provide a set of methods to support visual analysis using GW statistics through which the effects of geography can be explored at multiple scales.

关键词： geographical weighting exploratory data analysis scale multivariate directional interaction coordinated views

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20 years of four HCI conferences: A visual exploration

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INTERNATIONAL JOURNAL OF HUMAN-COMPUTER INTERACTION 2007年第3期23卷 239-285页

作者： Henry, Nathalie Goodell, Howard Elmqvist, Niklas Fekete, Jean-Daniel Univ Paris Sud INRIA LRI Orsay France Univ Sydney Sydney NSW 2006 Australia

We present a visual exploration of the field of human-computer interaction (HCI) through the author and article metadata of four of its major conferences: the ACM conferences on Computer-Human Interaction (CHI), User Interface Software and Technology, and Advanced visual Interfaces and the IEEE Symposium on Information visualization. This article describes many global and local patterns we discovered in this data set, together with the exploration process that produced them. Some expected patterns emerged, such as that-like most social networks-coauthorship and citation networks exhibit a power-law degree distribution, with a few widely collaborating authors and highly cited articles. Also, the prestigious and long-established CHI conference has the highest impact (citations by the others). Unexpected insights included that the years when a given conference was most selective are not correlated with those that produced its most highly referenced articles and that influential authors have distinct patterns of collaboration. An interesting sidelight is that methods from the HCI field-exploratory data analysis by information visualization and direct-manipulation interaction-proved useful for this analysis. They allowed us to take an open-ended, exploratory approach, guided by the data itself. As we answered our original questions, new ones arose;as we confirmed patterns we expected, we discovered refinements, exceptions, and fascinating new ones.

关键词： Human-computer interaction Ergonomics User interfaces (Computer systems) Interactive computer systems Computer systems visual programming languages (Computer science) Social networks Information storage & retrieval systems Online social networks

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visual exploration and evaluation of climate-related simulation data

Visual exploration and evaluation of climate-related simulat...

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2007 Winter Simulation conference

作者： Nocke, Thomas Flechsig, Michael Boehm, Uwe Potsdam Inst Climate Impact Res PIK D-14473 Potsdam Germany

ISBN: (纸本)9781424413058

Large, heterogeneous volumes of simulation data are calculated and stored in many disciplines, e.g. in climate and climate impact research. To gain insight, current climate analysis applies statistical methods and model sensitivity analyzes in combination with standard visualization techniques. However, there are some obstacles for researchers in applying the full functionality of sophisticated visualization, exploiting the available interaction and visualization functionality in order to go beyond data presentation tasks. In particular, there is a gap between available and actually applied multi-variate visualization techniques. Furthermore, visual data comparison of simulation (and measured) data is still a challenging task. Consequently, this paper introduces a library of visualization techniques, tailored to support exploration and evaluation of climate simulation data. These techniques are integrated into the easy-to-use visualization framework SimEnvVis - designed as a front-end user interface to a simulation environment - which provides a high level of user support generating visual representations.

关键词： visualization

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Everyday life discoveries: Mining and visualizing activity patterns in social science diary data

Everyday life discoveries: Mining and visualizing activity p...

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11th International conference on Information visualization (IV 2007)

作者： Vrotsou, Katerina Ellegard, Kajsa Cooper, Matthew Linkoping Univ Norrkoping Visualizat & Interact Studio Linkoping Sweden Linkoping Univ TEMA Technol & Social Change Linkoping Sweden

ISBN: (纸本)9780769529004

The ability to identify and examine patterns of activities is a key tool for social and behavioural science. In the past this has been done by statistical or purely visual methods but automated sequential pattern analysis through sophisticated data mining and visualization tools for pattern location. and evaluation can open up new possibilities for interactive exploration of the data. This paper describes the addition of a sequential pattern identification method to the visual activity-analysis tool, visual-TimePAcTS, and its effectiveness in the process of pattern. analysis in social science diary data. The results have shown that the method correctly identifies patterns and conveys them effectively to the social scientist in a manner that allows them quick and easy understanding of the significance of the patterns.

关键词： data mining

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SIMVIS: Interactive visual analysis of large and time-dependent 3D simulation data

SIMVIS: Interactive visual analysis of large and time-depend...

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2007 Winter Simulation conference

作者： Doleisch, Helmut VRVis Res Ctr A-1220 Vienna Austria

ISBN: (纸本)9781424413058

SimVis is a novel technology for the interactive visual analysis of large and complex flow data which results from Computational Fluid Dynamics (CFD) simulation. The new technology which has been researched and developed over the last years at the VRVis Research Center in Vienna, introduces a new approach for interactive graphical exploration and analysis of time-dependent data (computed on large three-dimensional grids, and resulting in a multitude of different scalar/vector values for each cell of these grids). In this paper the major new technological concepts of the SimVis approach are presented and real-world application examples are given.

关键词： Computational fluid dynamics

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