Incorporating 3-dimensional models in online articles

Introduction The aims of this article are to introduce the capability to view and interact with 3-dimensional (3D) surface models in online publications, and to describe how to prepare surface models for such online 3D visualizations. Methods Three-dimensional image analysis methods include image acquisition, construction of surface models, registration in a common coordinate system, visualization of overlays, and quantification of changes. Cone-beam computed tomography scans were acquired as volumetric images that can be visualized as 3D projected images or used to construct polygonal meshes or surfaces of specific anatomic structures of interest. The anatomic structures of interest in the scans can be labeled with color (3D volumetric label maps), and then the scans are registered in a common coordinate system using a target region as the reference. The registered 3D volumetric label maps can be saved in.obj,.ply,.stl, or.vtk file formats and used for overlays, quantification of differences in each of the 3 planes of space, or color-coded graphic displays of 3D surface distances. Results All registered 3D surface models in this study were saved in.vtk file format and loaded in the Elsevier 3D viewer. In this study, we describe possible ways to visualize the surface models constructed from cone-beam computed tomography images using 2D and 3D figures. The 3D surface models are available in the article's online version for viewing and downloading using the reader's software of choice. These 3D graphic displays are represented in the print version as 2D snapshots. Overlays and color-coded distance maps can be displayed using the reader's software of choice, allowing graphic assessment of the location and direction of changes or morphologic differences relative to the structure of reference. The interpretation of 3D overlays and quantitative color-coded maps requires basic knowledge of 3D image analysis. Conclusions When submitting manuscripts, authors can now upload 3D models that will allow readers to interact with or download them. Such interaction with 3D models in online articles now will give readers and authors better understanding and visualization of the results

Fractional anisotropy distributions in 2- to 6-year-old children with autism

Increasing evidence suggests that autism is a disorder of distributed neural networks that may exhibit abnormal developmental trajectories. Characterisation of white matter early in the developmental course of the disorder is critical to understanding these aberrant trajectories

Managing Sensor Data On Urban Traffic

Sensor data on traffic events have prompted a wide range of research issues, related with the so-called ITS (Intelligent Transportation Systems). Data are delivered for both static (fixed) and mobile (embarked) sensors, generating large and complex spatio-temporal series. Research efforts in handling these data range from pattern matching and data mining techniques (for forecasting and trend analysis) to work on database queries (e.g., to construct scenarios). Work on embarked sensors also considers issues on trajectories and moving objects. This paper presents a new kind of framework to manage static sensor data. Our work is based on combining research on analytical methods to process sensor data, and database procedures to query these data. The first component is geared towards supporting pattern matching, whereas the second deals with spatio-temporal database issues. This allows distinct granularities and modalities of analysis of sensor data in space and time. This work was conducted within a project that uses real data, with test conducted on 1000 sensors, during 3 years, in a large French city. © 2008 Springer Berlin Heidelberg.5232 LNCS385394(2007) TheCADDYWebsite, , http://norma.mas.ecp.fr/wikimas/Caddy, CADDYScemama, G., Carles, O., Claire-SITI, Public road Transport Network Management Control: A Unified Approach (2004) 12th IEEE Int. Conf. on Road Transport Information and Control (RTICJoliveau, M., (2008) Reduction of Urban Traffic Time Series from Georeferenced Sensors, and extraction of Spatio-temporal series -in French, , Ph.D thesis, Ecole Centrale Des Arts Et Manufactures Ecole Centrale de ParisJolliffe, I., (1986) Principal Component Analysis, , Springer, New YorkJoliveau, M., Vuyst, F.D., Space-time summarization of multisensor time series. case of missing data (2007) Int. Workshop on Spatial and Spatio-temporal data mining, IEEE SSTDMDempster, A., Laird, N., Rubin, D., Maximum likelihood for incomplete data via the em algorithm (1977) Journal of the Royal Statistical Society series B, 39, pp. 1-38Hugueney, B., Adaptive Segmentation-Based Symbolic Representations of Time Series for Better Modeling and Lower Bounding Distance Measures (2006) Proc. 10th European Conference on Principles and Practice of Knowledge Discovery in Databases, pp. 542-552Hugueney, B., Joliveau, M., Jomier, G., Manouvrier, M., Naja, Y., Scemama, G., Steffan, L., Towards a data warehouse for urban traffic (in french) (2006) Revue des Nouvelles Technologies de L'Information RNTI (B2), pp. 119-137Yi, B.K., Faloutsos, C., Fast time sequence indexing for arbitrary Lp norm (2000) Proc. of the 26th VLBD Conference, pp. 385-394Keogh, E., Chakrabarti, K., Pazzani, M., Mehrotra, S., (2000) Dimensionality reduction for fast similarity search in large time series databases, , Journal of Knowledge and Information SystemsMariotte, L., Medeiros, C.B., Torres, R., Diagnosing Similarity of Oscillation Trends in Time Series (2007) International Workshop on spatial and spatio-temporal data mining -SSTDM, pp. 243-248Mautora, T., Naudin, E., Arcs-states models for the vehicle routing problem with time windows and related problems (2007) Computers and Operations Research, 34, pp. 1061-1084Kriegel, H.P., Kröger, P., Kunath, P., Renz, M., Schmidt, T., Proximity queries in large traffic networks (2007) Proc. ACM GIS, pp. 1-8Kim, K., Lopez, M., Leutenegger, S., Li, K., A Network-based Indexing Method for Trajectories of Moving Objects (2006) LNCS, 4243, pp. 344-353. , Yakhno, T, Neuhold, E.J, eds, ADVIS 2006, Springer, HeidelbergGuting, R., Bohlen, M., Erwig, E., Jensen, C., Lorentzos, N., Schneider, M., Vazirgianis, M., A Foundation for Representing and Querying Moving Objects (2000) ACM Transactions on Database Systems, 25 (2), pp. 1-42Spaccapietra, S., Parent, C., Damiani, M.L., Macedo, J.A., Porto, F., Vangenot, C., A conceptual view on trajectories (2008) Knowledge and Data Engineering, 65 (1), pp. 126-14

Cholestérogenèse hépatique à partir de 14

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Managing sensor traffic data and forecasting unusual behaviour propagation

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Sensor data on traffic events have prompted a wide range of research issues, related with the so-called ITS (Intelligent Transportation Systems). Data are delivered for both static (fixed) and mobile (embedded) sensors, generating large and complex spatio-temporal series. This scenario presents several research challenges, in spatio-temporal data management and data analysis. Management issues involve, for instance, data cleaning and data fusion to support queries at distinct spatial and temporal granularities. Analysis issues include the characterization of traffic behavior for given space and/or time windows, and detection of anomalous behavior (either due to sensor malfunction, or to traffic events). This paper contributes to the solution of some of these issues through a new kind of framework to manage static sensor data. Our work is based on combining research on analytical methods to process sensor data, and data management strategies to query these data. The first aspect is geared towards supporting pattern matching. This leads to a model to study and predict unusual traffic behavior along an urban road network. The second aspect deals with spatio-temporal database issues, taking into account information produced by the model. This allows distinct granularities and modalities of analysis of sensor data in space and time. This work was conducted within a project that uses real data, with tests conducted on 1,000 sensors, during 3 years, in a large French city.143SI279305Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)French Research ProgramConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq

Documenting Changes in a Spatiotemporal Database

Spatiotemporal databases have been extensively used to represent the evolution of geographic phenomena. However, in a large spectrum of geographical applications, users need more than a mere representation of data evolution. For instance, in urban management applications- e.g., cadastral evolution- users often need to know why, how and by whom certain changes have been performed or their impact on the environment. Answers to these queries are not possible unless supplementary information concerning real world events is associated with the corresponding changes in the database. This paper proposes a solution to this problem, which is based on extending a spatiotemporal database with a mechanism for managing documentation on the evolution o

Oxidation of pharmaceuticals during chlorination and advanced processes (H2O2/UV)

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