scholarly journals Role of Temporal Diversity in Inferring Social Ties Based on Spatio-Temporal Data

2017 ◽  
Author(s):  
Deshana Desai ◽  
Harsh Nisar ◽  
Rishabh Bhardawaj
Keyword(s):  
Social Ties ◽  
Temporal Data ◽  
Temporal Diversity ◽  
Spatio Temporal

scholarly journals Network architecture determines vein fate during spontaneous reorganization, with a time delay

2021 ◽  
Author(s):  
Sophie Marbach ◽  
Noah Ziethen ◽  
Leonie Bastin ◽  
Felix Baeuerle ◽  
Karen Alim
Keyword(s):  
Time Delay ◽  
Network Architecture ◽  
Force Balance ◽  
Relative Pressure ◽  
Temporal Data ◽  
Vascular Networks ◽  
Local Shear ◽  
Flow Shear Stress ◽  
Spatio Temporal

Vascular networks continuously reorganize their morphology by growing new or shrinking existing veins to optimize function. Flow shear stress on vein walls has been set forth as the local driver for this continuous adaptation. Yet, shear feedback alone cannot account for the observed diversity of network dynamics -- a puzzle made harder by scarce spatio-temporal data. Here, we resolve network-wide vein dynamics and shear during spontaneous reorganization in the prototypical vascular networks of Physarum polycephalum. Our experiments reveal a plethora of vein dynamics (stable, growing, shrinking) that are not directly proportional to local shear. We observe (a) that shear rate sensing on vein walls occurs with a time delay of 1 to 3 min and (b) that network architecture dependent parameters -- such as relative pressure or relative vein resistance -- are key to determine vein fate. We derive a model for vascular adaptation, based on force balance at the vein walls. Together with the time delay, our model reproduces the diversity of experimentally observed vein dynamics, and confirms the role of network architecture. Finally, we observe avalanches of network reorganization events which cause entire clusters of veins to vanish. Such avalanches are consistent with architectural feedback as the vein connections perpetually change with reorganization. As these network architecture dependent parameters are intrinsically connected with the laminar fluid flow in the veins, we expect our findings to play a role across flow-based vascular networks.

Giscience in the Mountain Geography

2010 ◽  
Vol 27 (1-2) ◽  
pp. 81-90
Author(s):  
Krishna Poudel
Keyword(s):  
Spatial Data ◽  
Environmental Data ◽  
Temporal Data ◽  
Observation Systems ◽  
Research Findings ◽  
Temporal And Spatial ◽  
Temporal And Spatial Characteristics ◽  
Mountain Geography ◽  
Different Sources

Mountains have distinct geography and are dynamic in nature compared to the plains. 'Verticality' and 'variation' are two fundamental specificities of the mountain geography. They possess distinct temporal and spatial characteristics in a unique socio-cultural setting. There is an ever increasing need for spatial and temporal data for planning and management activities; and Geo Information (GI) Science (including Geographic Information and Earth Observation Systems). This is being recognized more and more as a common platform for integrating spatial data with social, economic and environmental data and information from different sources. This paper investigates the applicability and challenges of GISscience in the context of mountain geography with ample evidences and observations from the mountain specific publications, empirical research findings and reports. The contextual explanation of mountain geography, mountain specific problems, scientific concerns about the mountain geography, advances in GIScience, the role of GIScience for sustainable development, challenges on application of GIScience in the contexts of mountains are the points of discussion. Finally, conclusion has been made with some specific action oriented recommendations.

Spatial-temporal data collection process models using mobile sinks

2019 ◽  
Vol 942 (12) ◽  
pp. 22-28
Author(s):  
A.V. Materuhin ◽  
V.V. Shakhov ◽  
O.D. Sokolova
Keyword(s):  
Energy Consumption ◽  
Operation Time ◽  
Point Of View ◽  
Process Models ◽  
Temporal Data ◽  
Network Nodes ◽  
Mobile Sinks ◽  
Autonomous Operation ◽  
Data Collection Process ◽  
Spatio Temporal

Optimization of energy consumption in geosensor networks is a very important factor in ensuring stability, since geosensors used for environmental monitoring have limited possibilities for recharging batteries. The article is a concise presentation of the research results in the area of increasing the energy consumption efficiency for the process of collecting spatio-temporal data with wireless geosensor networks. It is shown that in the currently used configurations of geosensor networks there is a predominant direction of the transmitted traffic, which leads to the fact that through the routing nodes that are close to the sinks, a much more traffic passes than through other network nodes. Thus, an imbalance of energy consumption arises in the network, which leads to a decrease in the autonomous operation time of the entire wireless geosensor networks. It is proposed to use the possible mobility of sinks as an optimization resource. A mathematical model for the analysis of the lifetime of a wireless geosensor network using mobile sinks is proposed. The model is analyzed from the point of view of optimization energy consumption by sensors. The proposed approach allows increasing the lifetime of wireless geosensor networks by optimizing the relocation of mobile sinks.

scholarly journals From spatio-temporal data to chronological networks

2019 ◽  
Author(s):  
Didier A. Vega-Oliveros ◽  
Moshé Cotacallapa ◽  
Leonardo N. Ferreira ◽  
Marcos G. Quiles ◽  
Liang Zhao ◽  
...  
Keyword(s):  
Temporal Data ◽  
Spatio Temporal

scholarly journals Pyramidal Framework: Guidance for the Next Generation of GIS Spatial-Temporal Models

2021 ◽  
Vol 10 (3) ◽  
pp. 188
Author(s):  
Cyril Carré ◽  
Younes Hamdani
Keyword(s):  
Conceptual Models ◽  
Future Generations ◽  
Temporal Data ◽  
Temporal Modeling ◽  
Temporal Models ◽  
Gis Data ◽  
Spatio Temporal ◽  
New Interpretation ◽  
Conventional Literature

Over the last decade, innovative computer technologies and the multiplication of geospatial data acquisition solutions have transformed the geographic information systems (GIS) landscape and opened up new opportunities to close the gap between GIS and the dynamics of geographic phenomena. There is a demand to further develop spatio-temporal conceptual models to comprehensively represent the nature of the evolution of geographic objects. The latter involves a set of considerations like those related to managing changes and object identities, modeling possible causal relations, and integrating multiple interpretations. While conventional literature generally presents these concepts separately and rarely approaches them from a holistic perspective, they are in fact interrelated. Therefore, we believe that the semantics of modeling would be improved by considering these concepts jointly. In this work, we propose to represent these interrelationships in the form of a hierarchical pyramidal framework and to further explore this set of concepts. The objective of this framework is to provide a guideline to orient the design of future generations of GIS data models, enabling them to achieve a better representation of available spatio-temporal data. In addition, this framework aims at providing keys for a new interpretation and classification of spatio-temporal conceptual models. This work can be beneficial for researchers, students, and developers interested in advanced spatio-temporal modeling.

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