Augmenting spatial awareness with Haptic Radar

2006 ◽  
Author(s):  
Alvaro Cassinelli ◽  
Carson Reynolds ◽  
Masatoshi Ishikawa
Keyword(s):  
Spatial Awareness

Borders as penal transplants: Control of territory, mobility and illegality in West Africa

2021 ◽  
pp. 136248062199545
Author(s):  
Eva Magdalena Stambøl
Keyword(s):  
West Africa ◽  
Social Control ◽  
Crime Control ◽  
Border Studies ◽  
Border Security ◽  
Mobility Control ◽  
Spatial Awareness ◽  
Control Order ◽  
Political Technology ◽  
Geographical Scope

This article explores an increasingly significant trend in crime and mobility control that has received scant criminological attention: border externalization, specifically scrutinizing land border security-building by international actors in West Africa. Going beyond the usual focus on migration in border studies, it develops a criminologically grounded theorization of the border as a political technology of crime control and its relationship to the state. This is done by arguing that borders, theorized as ‘penal transplants’ embodying specific (western) visions of state, political power, social control/order and territoriality, are transformed and often distorted when performed in ‘heterarchical’ contexts in the global South. Further, empirically based concepts from ‘the periphery’ are suggested to enrich border criminology, broadening its geographical scope and spatial awareness.

scholarly journals A Vision-Based Social Distancing and Critical Density Detection System for COVID-19

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4608
Author(s):  
Dongfang Yang ◽  
Ekim Yurtsever ◽  
Vishnu Renganathan ◽  
Keith A. Redmill ◽  
Ümit Özgüner
Keyword(s):  
Visual Cues ◽  
Detection System ◽  
Critical Density ◽  
Region Of Interest ◽  
Spatial Awareness ◽  
Real Time System ◽  
Effective Measure ◽  
Social Distancing ◽  
Record Data ◽  
Real World Datasets

Social distancing (SD) is an effective measure to prevent the spread of the infectious Coronavirus Disease 2019 (COVID-19). However, a lack of spatial awareness may cause unintentional violations of this new measure. Against this backdrop, we propose an active surveillance system to slow the spread of COVID-19 by warning individuals in a region-of-interest. Our contribution is twofold. First, we introduce a vision-based real-time system that can detect SD violations and send non-intrusive audio-visual cues using state-of-the-art deep-learning models. Second, we define a novel critical social density value and show that the chance of SD violation occurrence can be held near zero if the pedestrian density is kept under this value. The proposed system is also ethically fair: it does not record data nor target individuals, and no human supervisor is present during the operation. The proposed system was evaluated across real-world datasets.

FEATURES

2015 ◽  
Vol 19 (10) ◽  
pp. 17-35 ◽  
Keyword(s):  
Big Data ◽  
Disease Management ◽  
Clinical Research ◽  
Health Informatics ◽  
Healthcare Management ◽  
Spatial Awareness ◽  
Digital Tool ◽  
Future Health ◽  
Research Sector ◽  
The Future

Amplifying Spatial Awareness via GIS — Tech which brings Healthcare Management, Preventative & Predictive Measures under the same Cloud When it is not just about size, you gotta' be Smart, too! Chew on It! How Singapore-based health informatics company MHC Asia Group crunches big-data to uncover your company's health Digital tool when well-used, it is Passion Carving the Digital Route to Wellness Big Data, Bigger Disease Management and Current preparations to manage the Future Health of Singaporeans A Conversation with Mr Arun Puri Extreme Networks: Health Solutions Big Data in Clinical Research Sector

TASKILLAN: A Simulation to Predict the Validity of Multiple Resource Models of Aviation Workload

1988 ◽  
Vol 32 (2) ◽  
pp. 168-172 ◽  
Author(s):  
Christopher D. Wickens ◽  
Kelly Harwood ◽  
Leon Segal ◽  
Inge Tkalcevic ◽  
Bill Sherman
Keyword(s):  
Task Performance ◽  
Model Validation ◽  
Predictive Models ◽  
Spatial Awareness ◽  
Level Flight ◽  
Helicopter Flight ◽  
Processing Resources ◽  
Multiple Resource ◽  
Multiple Task ◽  
Over Time

The objective of this research was to establish the validity of predictive models of workload in the context of a controlled simulation of a helicopter flight mission. The models that were evaluated contain increasing levels of sophistication regarding their assumptions about the competition for processing resources underlying multiple task performance. Ten subjects performed the simulation which involved various combinations of a low level flight task with three cognitive side tasks, pertaining to navigation, spatial awareness and computation. Side task information was delivered auditorily or visually. Results indicated that subjective workload is best predicted by relatively simple models that simply integrate the total demands of tasks over time (r = 0.65). In contrast, performance is not well predicted by these models (r < .10), but is best predicted by models that assume differential competition between processing resources (r = 0.47). The relevance of these data to predictive models and to the use of subjective measures for model validation is discussed.

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