scholarly journals Waging War from Remote Cubicles: How Workers Cope with Technologies That Disrupt the Meaning and Morality of Their Work

2021 ◽  
Author(s):  
Madeleine Rauch ◽  
Shahzad (Shaz) Ansari
Keyword(s):  
Air Force ◽  
Emerging Technology ◽  
Moral Values ◽  
Unmanned Vehicles ◽  
Working Environment ◽  
Social Structures ◽  
Multiple Data ◽  
Technology Changes ◽  
Spatio Temporal ◽  
Iconic Representations

Technologies are known to alter social structures in the workplace, reconfigure roles and relationships, and disrupt status hierarchies. However, less attention has been given to how an emerging technology disrupts the meaning and moral values that tether people to their work and render it meaningful. To understand how workers respond to such an emerging technology, we undertook an inductive, qualitative study of military personnel working in unmanned aerial vehicles, or drone operations, for the U.S. Air Force. We draw on multiple data sources, including personal diaries kept by personnel involved in drone operations. We identified three characteristics of drone technology: remote-split operations, remote piloting of unmanned vehicles, and interaction through iconic representations. Our analysis suggests that drone technology has revolutionized warfare by (1) creating distanciated intimacy, (2) dissolving traditional spatio-temporal boundaries between work and personal life, and (3) redefining the legal and moral parameters of work. Drone program workers identified with these changes to their working environment in contradictory ways, which evoked emotional ambivalence about right and wrong. However, their organization gave them little help in alleviating their conflicting feelings. We illuminate how workers cope with such ambivalence when a technology transforms the meaning and morality of their work. We extend theory by showing that workers’ responses to a changed working environment as a result of a remote technology are not just based on how the technology changes workers’ tasks, roles, and status but also on how it affects their moral values.

Spatial and temporal dynamics of Pacific capelin Mallotus catervarius in the Gulf of Alaska: implications for ecosystem-based fisheries management

2020 ◽  
Vol 637 ◽  
pp. 117-140 ◽  
Author(s):  
DW McGowan ◽  
ED Goldstein ◽  
ML Arimitsu ◽  
AL Deary ◽  
O Ormseth ◽  
...  
Keyword(s):  
Temporal Dynamics ◽  
Marine Ecosystem ◽  
Gulf Of Alaska ◽  
Data Series ◽  
Limited Information ◽  
Important Species ◽  
Multiple Data ◽  
Spatial And Temporal Dynamics ◽  
Spawning Areas ◽  
Spatio Temporal

Pacific capelin Mallotus catervarius are planktivorous small pelagic fish that serve an intermediate trophic role in marine food webs. Due to the lack of a directed fishery or monitoring of capelin in the Northeast Pacific, limited information is available on their distribution and abundance, and how spatio-temporal fluctuations in capelin density affect their availability as prey. To provide information on life history, spatial patterns, and population dynamics of capelin in the Gulf of Alaska (GOA), we modeled distributions of spawning habitat and larval dispersal, and synthesized spatially indexed data from multiple independent sources from 1996 to 2016. Potential capelin spawning areas were broadly distributed across the GOA. Models of larval drift show the GOA’s advective circulation patterns disperse capelin larvae over the continental shelf and upper slope, indicating potential connections between spawning areas and observed offshore distributions that are influenced by the location and timing of spawning. Spatial overlap in composite distributions of larval and age-1+ fish was used to identify core areas where capelin consistently occur and concentrate. Capelin primarily occupy shelf waters near the Kodiak Archipelago, and are patchily distributed across the GOA shelf and inshore waters. Interannual variations in abundance along with spatio-temporal differences in density indicate that the availability of capelin to predators and monitoring surveys is highly variable in the GOA. We demonstrate that the limitations of individual data series can be compensated for by integrating multiple data sources to monitor fluctuations in distributions and abundance trends of an ecologically important species across a large marine ecosystem.

scholarly journals Inter-comparison of daily precipitation products for large-scale hydro-climatic applications over Canada

2017 ◽  
Vol 21 (4) ◽  
pp. 2163-2185 ◽  
Author(s):  
Jefferson S. Wong ◽  
Saman Razavi ◽  
Barrie R. Bonsal ◽  
Howard S. Wheater ◽  
Zilefac E. Asong
Keyword(s):  
Large Scale ◽  
Spatial And Temporal Variability ◽  
The North ◽  
Global Precipitation Climatology Centre ◽  
Multiple Data ◽  
Geographical Regions ◽  
Central Canada ◽  
Different Seasons ◽  
Spatio Temporal ◽  
Global Precipitation

Abstract. A number of global and regional gridded climate products based on multiple data sources are available that can potentially provide reliable estimates of precipitation for climate and hydrological studies. However, research into the consistency of these products for various regions has been limited and in many cases non-existent. This study inter-compares several gridded precipitation products over 15 terrestrial ecozones in Canada for different seasons. The spatial and temporal variability of the errors (relative to station observations) was quantified over the period of 1979 to 2012 at a 0.5° and daily spatio-temporal resolution. These datasets were assessed in their ability to represent the daily variability of precipitation amounts by four performance measures: percentage of bias, root mean square error, correlation coefficient, and standard deviation ratio. Results showed that most of the datasets were relatively skilful in central Canada. However, they tended to overestimate precipitation amounts in the west and underestimate in the north and east, with the underestimation being particularly dominant in northern Canada (above 60° N). The global product by WATCH Forcing Data ERA-Interim (WFDEI) augmented by Global Precipitation Climatology Centre (GPCC) data (WFDEI [GPCC]) performed best with respect to different metrics. The Canadian Precipitation Analysis (CaPA) product performed comparably with WFDEI [GPCC]; however, it only provides data starting in 2002. All the datasets performed best in summer, followed by autumn, spring, and winter in order of decreasing quality. Findings from this study can provide guidance to potential users regarding the performance of different precipitation products for a range of geographical regions and time periods.

scholarly journals The Next Century of Air Power

2003 ◽  
Vol 125 (11) ◽  
pp. 34-40
Author(s):  
Paul D. Nielsen ◽  
Ahmed K. Noor ◽  
Samuel L. Venneri
Keyword(s):  
Air Force ◽  
Research Laboratory ◽  
Unmanned Vehicles ◽  
Air Power ◽  
Us Air Force ◽  
Wide Range ◽  
The Us ◽  
Directed Energy ◽  
Air Force Research Laboratory ◽  
Non Destructive

The US Air Force has been pursuing the transformation of air and space power through development of technologies that yield new capabilities and by adopting novel operational concepts that enhance our ability to achieve desired military effects. Maturing a comprehensive set of technologies is the mission of the Air Force Research Laboratory. The transformation includes migrating military capabilities to unmanned platforms for a wide range of air applications and developing new directed energy capabilities, which produce effects on the battlefield ranging from the traditional destruction of enemy equipment to the revolutionary non-lethal, non-destructive stopping of advancing enemy troops. Vehicles being planned at the Air Force Research Laboratory include unmanned planes for surveillance and reconnaissance. Combat operations of the future may see officers giving commands to fleets of unmanned vehicles that are able to carry out orders on their own. Although precision munitions are smaller, more precise, and more autonomous, weapons using directed energy are beginning to emerge.

Management of Health, Environment and Safety (HES) in Royal Norwegian am Force (RNoAF) Flight Operations

1997 ◽  
Vol 41 (2) ◽  
pp. 744-748
Author(s):  
Vivianne Fonne ◽  
Anthony S. Wagstaff
Keyword(s):  
Air Force ◽  
Weather Conditions ◽  
Working Environment ◽  
Flight Operations ◽  
Concept Of Health ◽  
Military Aviation ◽  
Task Requirements ◽  
Chemical Factors ◽  
Physical And Chemical ◽  
New System

The Royal Norwegian Air Force (RNoAF) performs a large number of mission types. Many of these missions are undertaken in exceedingly difficult operational environments. Because of the challenges presented by seasonal variations, poor weather conditions and demanding operational task requirements, the importance of an optimal working environment to ensure crew health and safe flight operations should be emphasized. In the Norwegian concept of Health, Environment and Safety (HES), all aspects of the working environment have been taken into consideration, including human factors, ergonomics, physical and chemical factors as well as social and organizational psychology. As civilian legislation excludes military aviation in this area, the RNoAF has developed a new system that allows HES improvements to be implemented in a more efficient way. This system is based on a new military regulation for HES in RNoAF flight operations. Good coordination of HES issues, predictability and standard handling procedures are key elements in this system which is meant to be an effective managerial tool for correct HES decision-making.

A step by step procedure for multivariate modeling

2021 ◽  
Author(s):  
Claudia Cappello ◽  
Sandra De Iaco ◽  
Monica Palma ◽  
Sabrina Maggio
Keyword(s):  
Covariance Structure ◽  
Space Time ◽  
Temporal Data ◽  
Multivariate Geostatistics ◽  
Correlated Variables ◽  
Multiple Data ◽  
Step Procedure ◽  
Complete Procedure ◽  
Spatio Temporal ◽  
Selection Of

<p><span><span>In environmental sciences, it is very common to observe spatio-temporal multiple data concerning several correlated variables which are measured in time over a monitored spatial domain. In multivariate Geostatistics, the analysis of these correlated variables requires the estimation and modelling of the spatio-temporal multivariate covariance structure.<br>In the literature, the linear coregionalization model (LCM) has been widely used, in order to describe the spatio-temporal dependence which characterizes two or more variables. In particular, the LCM model requires the identification of the basic independent components underlying the analyzed phenomenon, and this represents a tough task. In order to overcome the aforementioned problem, this contribution provides a complete procedure where all the necessary steps to be followed for properly detect the basic space-time components for the phenomenon under study, together with some computational advances which support the selection of an ST-LCM.<br>The implemented procedure and the related algorithms are applied on a space-time air quality dataset.<br>Note that the proposed procedure can help practitioners to reproduce all the modeling stages and to replicate the analysis for different multivariate spatio-temporal data.</span></span></p>

Developing spatio-temporal models using multiple data types for evaluating population trends and habitat usage

2019 ◽  
Vol 76 (6) ◽  
pp. 1748-1761 ◽  
Author(s):  
Arnaud Grüss ◽  
James T Thorson
Keyword(s):  
Distribution Patterns ◽  
Early Years ◽  
Population Trends ◽  
Red Snapper ◽  
Data Types ◽  
Multiple Data ◽  
Temporal Models ◽  
Habitat Usage ◽  
Spatio Temporal ◽  
Combined Data

Abstract Spatio-temporal models have become key tools for evaluating population trends and habitat usage. We developed a spatio-temporal modelling framework employing a combination of encounter/non-encounter, count, and biomass data collected by different monitoring programs (“combined data”). The three data types are predicted using a computationally efficient approximation to a compound Poisson-gamma process. We fitted spatio-temporal models to combined data for Gulf of Mexico (GOM) red snapper (Lutjanus campechanus) for 2006–2014. These spatio-temporal models provided insights into GOM red snapper spatial distribution patterns, which we corroborated by comparing to past predictions generated using only encounter/non-encounter data. However, relying on biomass and count data in addition to encounter/non-encounter data also allowed us to reconstruct biomass trends for GOM red snapper and to examine patterns of distribution shifts and range expansion/contraction for this population for the first time. Moreover, combining multiple data types improved the precision of reconstructed population trends and some variables quantifying habitat usage. Finally, scenarios and simulation experiments conditioned upon red snapper data showed that the improvement in fitting to combined data is greater when biomass data for the study population are lacking for an entire subregion and, to a lesser extent, for an entire time period (e.g. in early years).

scholarly journals Facilitating insights with a user adaptable dashboard, illustrated by airport connectivity data

2018 ◽  
Vol 1 ◽  
pp. 1-6
Author(s):  
Ieva Dobraja ◽  
Menno-Jan Kraak ◽  
Yuri Engelhardt
Keyword(s):  
Temporal Patterns ◽  
Data Representation ◽  
Data Exploration ◽  
Temporal Data ◽  
Movement Data ◽  
Graphical Data ◽  
Multiple Data ◽  
Multi Temporal ◽  
Spatio Temporal ◽  
Heterogeneous Multiscale

Since the movement data exist, there have been approaches to collect and analyze them to get insights. This kind of data is often heterogeneous, multiscale and multi-temporal. Those interested in spatio-temporal patterns of movement data do not gain insights from textual descriptions. Therefore, visualization is required. As spatio-temporal movement data can be complex because size and characteristics, it is even challenging to create an overview of it. Plotting all the data on the screen will not be the solution as it likely will result into cluttered images where no data exploration is possible. To ensure that users will receive the information they are interested in, it is important to provide a graphical data representation environment where exploration to gain insights are possible not only in the overall level but at sub-levels as well. A dashboard would be a solution the representation of heterogeneous spatio- temporal data. It provides an overview and helps to unravel the complexity of data by splitting data in multiple data representation views. The adaptability of dashboard will help to reveal the information which cannot be seen in the overview.

scholarly journals Window Operators for Processing Spatio-Temporal Data Streams on Unmanned Vehicles

2020 ◽  
Vol 1 ◽  
pp. 1-23
Author(s):  
Tobias Werner ◽  
Thomas Brinkhoff
Keyword(s):  
Data Streams ◽  
Unmanned Vehicles ◽  
Vehicle Speed ◽  
Temporal Data ◽  
Data Stream Management ◽  
Time Intervals ◽  
Stream Management ◽  
Data Stream Management Systems ◽  
Spatio Temporal ◽  
Sliding Distance

Abstract. Unmanned aerial and submersible vehicles are used in an increasing number of applications especially for data collection in misanthropic environments. During a mission, such vehicles generate multiple spatio-temporal data streams suitable to be processed by data stream management systems (DSMS). The main approach of a DSMS is limiting the elements of a stream by using sliding and tilting windows with time intervals as temporal condition. However, due to varying vehicle speed and limited on-board resources, such temporal windows do not provide adequate support for spatio-temporal problems. For solving this problem, we propose a set of six new spatio-temporal window operators in this paper. This set comprises of sliding distance, tilting distance, tilting waypoint, session distance, jumping distance and an area window to limit stream elements based on spatial conditions. Each of the listed operators provides an individual behaviour to support sophisticated applications like spatial interpolation and forecasting. An evaluation based on an example trajectory shows the benefit of the presented operators for spatio-temporal applications.

scholarly journals Taking full advantage of the diverse assemblage of data at hand to produce time series of abundance. A case study on Atlantic salmon populations of Brittany

2021 ◽  
Author(s):  
Clément Lebot ◽  
Marie-Andrée Arago ◽  
Laurent Beaulaton ◽  
Gaëlle Germis ◽  
Marie Nevoux ◽  
...  
Keyword(s):  
Time Series ◽  
Data Collection ◽  
Atlantic Salmon ◽  
Full Advantage ◽  
Fishing Effort ◽  
Clear Trend ◽  
Multiple Data ◽  
Spatio Temporal ◽  
Catch Statistics ◽  
Transfer Of Information

Estimation of abundance with wide spatio-temporal coverage is essential to the assessment and management of wild populations. But, in many cases, data available to estimate abundance time series have diverse forms, variable quality over space and time and they stem from multiple data collection procedures. We developed a Hierarchical Bayesian Modelling (HBM) approach that take full advantage of the diverse assemblage of data at hand to estimate homogeneous time series of abundances irrespective of the data collection procedure. We apply our approach to the estimation of adult abundances of 18 Atlantic salmon populations of Brittany (France) from 1987 to 2017 using catch statistics, environmental covariates and fishing effort. Additional data of total or partial abundance collected in 4 closely monitored populations are also integrated into the analysis. The HBM framework allows the transfer of information from the closely monitored populations to the others. Our results reveal no clear trend in the abundance of adult returns in Brittany over the period studied.

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