Development of three dimensional monitoring dataset for tenants variations in broad urban area by spatio-temporal integrating digital house maps and yellow page data

2008 ◽  
Author(s):  
Y. Akiyama ◽  
T. Shibuki ◽  
R. Shibasaki
Keyword(s):  
Urban Area ◽  
Three Dimensional ◽  
Yellow Page ◽  
Spatio Temporal

scholarly journals Accelerated Time and High-Resolution 3D Modeling of the Flow and Dispersion of Noxious Substances over a Gigantic Urban Area—The EMERGENCIES Project

Atmosphere ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 640
Author(s):  
Olivier Oldrini ◽  
Patrick Armand ◽  
Christophe Duchenne ◽  
Sylvie Perdriel ◽  
Maxime Nibart
Keyword(s):  
High Resolution ◽  
Urban Area ◽  
3D Modeling ◽  
Three Dimensional ◽  
Hazardous Materials ◽  
Support Tool ◽  
On Demand ◽  
Simulation Domain ◽  
Dimensional Simulation ◽  
Atmospheric Release

Accidental or malicious releases in the atmosphere are more likely to occur in built-up areas, where flow and dispersion are complex. The EMERGENCIES project aims to demonstrate the operational feasibility of three-dimensional simulation as a support tool for emergency teams and first responders. The simulation domain covers a gigantic urban area around Paris, France, and uses high-resolution metric grids. It relies on the PMSS modeling system to model the flow and dispersion over this gigantic domain and on the Code_Saturne model to simulate both the close vicinity and the inside of several buildings of interest. The accelerated time is achieved through the parallel algorithms of the models. Calculations rely on a two-step approach: the flow is computed in advance using meteorological forecasts, and then on-demand release scenarios are performed. Results obtained with actual meteorological mesoscale data and realistic releases occurring both inside and outside of buildings are presented and discussed. They prove the feasibility of operational use by emergency teams in cases of atmospheric release of hazardous materials.

scholarly journals SPATIO-TEMPORAL DATA ANALYSIS WITH NON-LINEAR FILTERS: BRAIN MAPPING WITH fMRI DATA

2011 ◽  
Vol 19 (3) ◽  
pp. 189
Author(s):  
Karsten Rodenacker ◽  
Klaus Hahn ◽  
Gerhard Winkler ◽  
Dorothea P Auer
Keyword(s):  
Signal To Noise Ratio ◽  
Three Dimensional ◽  
Digital Data ◽  
Linear Filters ◽  
Brain Functions ◽  
Non Linear ◽  
Long Time ◽  
Spatio Temporal ◽  
Sensory Activation ◽  
Temporal Data Analysis

Spatio-temporal digital data from fMRI (functional Magnetic Resonance Imaging) are used to analyse and to model brain activation. To map brain functions, a well-defined sensory activation is offered to a test person and the hemodynamic response to neuronal activity is studied. This so-called BOLD effect in fMRI is typically small and characterised by a very low signal to noise ratio. Hence the activation is repeated and the three dimensional signal (multi-slice 2D) is gathered during relatively long time ranges (3-5 min). From the noisy and distorted spatio-temporal signal the expected response has to be filtered out. Presented methods of spatio-temporal signal processing base on non-linear concepts of data reconstruction and filters of mathematical morphology (e.g. alternating sequential morphological filters). Filters applied are compared by classifications of activations.

Unsteady Hemodynamics in Intracranial Aneurysms With Varying Dome Orientations

2021 ◽  
Vol 143 (6) ◽  
Author(s):  
Abdullah Y. Usmani ◽  
K. Muralidhar
Keyword(s):  
Intracranial Aneurysm ◽  
Three Dimensional ◽  
Parent Artery ◽  
Fluid Loading ◽  
Image Velocimetry ◽  
Flow Reynolds Number ◽  
Fatal Hemorrhage ◽  
Wall Loading ◽  
Spatio Temporal ◽  
Finite Volume Simulation

Abstract Fluid loading within an intracranial aneurysm is difficult to measure but can be related to the shape of the flow passage. The outcome of excessive loading is a fatal hemorrhage, making it necessary for early diagnosis. However, arterial diseases are asymptomatic and clinical assessment is a challenge. A realistic approach to examining the severity of wall loading is from the morphology of the aneurysm itself. Accordingly, this study compares pulsatile flow (Reynolds number Re = 426, Womersley number Wo = 4.7) in three different intracranial aneurysm geometries. Specifically, the spatio-temporal movement of vortices is followed in high aspect ratio aneurysm models whose domes are inclined along with angles of 0, 45, and 90 deg relative to the plane of the parent artery. The study is based on finite volume simulation of unsteady three-dimensional flow while a limited set of particle image velocimetry experiments have been carried out. Within a pulsatile cycle, an increase in inclination (0–90 deg) is seen to shift the point of impingement from the distal end toward the aneurysmal apex. This change in flow pattern strengthens helicity, drifts vortex cores, enhances spatial displacement of the vortex, and generates skewed Dean's vortices on transverse planes. Patches of wall shear stress and wall pressure shift spatially from the distal end in models of low inclination (0–45 deg) and circumscribe the aneurysmal wall for an inclination angle of 90 deg. Accordingly, it is concluded that high angles of inclination increase rupture risks while lower inclinations are comparatively safe.

Mining in Spatio-Temporal Databases

2011 ◽  
pp. 272-293
Author(s):  
Junmei Wang ◽  
Wynne Hsu ◽  
Mong Li Lee
Keyword(s):  
Spatial Databases ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Temporal Databases ◽  
Temporal Data ◽  
Service Patterns ◽  
Sequence Patterns ◽  
Spatial Coordinates ◽  
Spatio Temporal ◽  
Work Done

Recent interest in spatio-temporal applications has been fueled by the need to discover and predict complex patterns that occur when we observe the behavior of objects in the three-dimensional space of time and spatial coordinates. Although the complex and intrinsic relationships among the spatio-temporal data limit the usefulness of conventional data mining techniques to discover the patterns in the spatio-temporal databases, they also lead to opportunities for mining new classes of patterns in spatio-temporal databases. This chapter provides a survey of the work done for mining patterns in spatial databases and temporal databases, and the preliminary work for mining patterns in spatio-temporal databases. We highlight the unique challenges of mining interesting patterns in spatio-temporal databases. We also describe two special types of spatio-temporal patterns: location-sensitive sequence patterns and geographical features for location-based service patterns.

Spatio-temporal disparity between demand and supply of park green space service in urban area of Wuhan from 2000 to 2014

2018 ◽  
Vol 71 ◽  
pp. 49-59 ◽  
Author(s):  
Lijun Xing ◽  
Yanfang Liu ◽  
Xingjian Liu ◽  
Xiaojian Wei ◽  
Yan Mao
Keyword(s):  
Urban Area ◽  
Green Space ◽  
Demand And Supply ◽  
Spatio Temporal ◽  
Temporal Disparity
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