Measuring Situation Awareness in Training Systems: A Multivariate Approach

2000 ◽  
Vol 44 (11) ◽  
pp. 361-364
Author(s):  
Dennis A. Vincenzi ◽  
Robert T. Hays ◽  
Alton G. Seamon
Keyword(s):  
Situation Awareness ◽  
Human Performance ◽  
Cognitive Task ◽  
Training System ◽  
Multivariate Techniques ◽  
Performance Improvements ◽  
Significant Performance ◽  
Within Subjects ◽  
New Variables ◽  
Ship Handling

The Virtual Environment for Submarine Ship Handling Training (VESUB) project developed, demonstrated, and evaluated the training potential of a VE-based training system. Based on perceptual and cognitive task analyses, and input from subject matter experts, 15 performance variables were developed. These variables were combined and analyzed using multivariate techniques that provided a measure of situation awareness and general ship handling ability. These 2 new variables were then analyzed using an ANOVA with experience (novice or experienced) as the between subjects variable, and scenario session (pre-training or post-training) as the within subjects variable. The results indicated a significant improvement in situation awareness and general ship handling ability for both novice and experienced trainees. The VESUB training system provided the training needed to produce significant performance improvements for novice personnel who knew very little about ship handling, and also provided significant refresher training for experienced personnel. The use of multivariate analyses of specific embedded task measures provided an empirical link between situation awareness and human performance.

Human Performance of Novice Schedulers for Complex Spaceflight Operations Timelines

2021 ◽  
pp. 001872082110589
Author(s):  
Jessica J. Marquez ◽  
Tamsyn Edwards ◽  
John A. Karasinski ◽  
Candice N. Lee ◽  
Megan C. Shyr ◽  
...  
Keyword(s):  
Task Performance ◽  
Situation Awareness ◽  
Human Performance ◽  
Task Complexity ◽  
Lower Number ◽  
Scheduling Problems ◽  
Within Subjects ◽  
Complex Constraints ◽  
Design Scheduling ◽  
Main Effects

Objective Investigate the effects of scheduling task complexity on human performance for novice schedulers creating spaceflight timelines. Background Future astronauts will be expected to self-schedule, yet will not be experts in creating timelines that meet the complex constraints inherent to spaceflight operations. Method Conducted a within-subjects experiment to evaluate scheduling task performance in terms of scheduling efficiency, effectiveness, workload, and situation awareness while manipulating scheduling task complexity according to the number of constraints and type of constraints. Results Each participant ( n = 15) completed a set of scheduling problems. Results showed main effects of the number of constraints and type of constraint on efficiency, effectiveness, and workload. Significant interactions were observed in situation awareness and workload for certain types of constraints. Results also suggest that a lower number of constraints may be manageable by novice schedulers when compared to scheduling activities without constraints. Conclusion Results suggest that novice schedulers' performance decreases with a high number of constraints, and future scheduling aids may need to target a specific type of constraint. Application Knowledge on the effect of scheduling task complexity will help design scheduling systems that will enable self-scheduling for future astronauts. It will also inform other domains that conduct complex scheduling, such as nursing and manufacturing.

scholarly journals An Attention-Based Multilayer GRU Model for Multistep-Ahead Short-Term Load Forecasting

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1639
Author(s):  
Seungmin Jung ◽  
Jihoon Moon ◽  
Sungwoo Park ◽  
Eenjun Hwang
Keyword(s):  
Power Consumption ◽  
Prediction Models ◽  
Short Term Memory ◽  
Load Forecasting ◽  
Input Sequence ◽  
Short Term ◽  
Performance Improvements ◽  
Short Term Load Forecasting ◽  
Significant Performance ◽  
Input Variables

Recently, multistep-ahead prediction has attracted much attention in electric load forecasting because it can deal with sudden changes in power consumption caused by various events such as fire and heat wave for a day from the present time. On the other hand, recurrent neural networks (RNNs), including long short-term memory and gated recurrent unit (GRU) networks, can reflect the previous point well to predict the current point. Due to this property, they have been widely used for multistep-ahead prediction. The GRU model is simple and easy to implement; however, its prediction performance is limited because it considers all input variables equally. In this paper, we propose a short-term load forecasting model using an attention based GRU to focus more on the crucial variables and demonstrate that this can achieve significant performance improvements, especially when the input sequence of RNN is long. Through extensive experiments, we show that the proposed model outperforms other recent multistep-ahead prediction models in the building-level power consumption forecasting.

scholarly journals Data Downlink System in the Vast IOT Node Condition Assisted by UAV, Large Intelligent Surface, and Power and Data Beacon

Sensors ◽  
2020 ◽  
Vol 20 (20) ◽  
pp. 5748
Author(s):  
Zhibo Zhang ◽  
Qing Chang ◽  
Na Zhao ◽  
Chen Li ◽  
Tianrun Li
Keyword(s):  
Communication Systems ◽  
Optimization Problems ◽  
Minimum Energy ◽  
Numerical Algorithms ◽  
Flight Trajectory ◽  
Performance Improvements ◽  
Minimum Energy Consumption ◽  
Significant Performance ◽  
Downlink System ◽  
The Internet Of Things

The future development of communication systems will create a great demand for the internet of things (IOT), where the overall control of all IOT nodes will become an important problem. Considering the essential issues of miniaturization and energy conservation, in this study, a new data downlink system is designed in which all IOT nodes harvest energy first and then receive data. To avoid the unsolvable problem of pre-locating all positions of vast IOT nodes, a device called the power and data beacon (PDB) is proposed. This acts as a relay station for energy and data. In addition, we model future scenes in which a communication system is assisted by unmanned aerial vehicles (UAVs), large intelligent surfaces (LISs), and PDBs. In this paper, we propose and solve the problem of determining the optimal flight trajectory to reach the minimum energy consumption or minimum time consumption. Four future feasible scenes are analyzed and then the optimization problems are solved based on numerical algorithms. Simulation results show that there are significant performance improvements in energy/time with the deployment of LISs and reasonable UAV trajectory planning.

VESTA 3for three-dimensional visualization of crystal, volumetric and morphology data

2011 ◽  
Vol 44 (6) ◽  
pp. 1272-1276 ◽  
Author(s):  
Koichi Momma ◽  
Fujio Izumi
Keyword(s):  
Search Algorithm ◽  
Voronoi Tessellation ◽  
Three Dimensional ◽  
Structure Parameters ◽  
Volumetric Data ◽  
Complex Molecules ◽  
Visualization System ◽  
Performance Improvements ◽  
Significant Performance

VESTAis a three-dimensional visualization system for crystallographic studies and electronic state calculations. It has been upgraded to the latest version,VESTA 3, implementing new features including drawing the external morphology of crystals; superimposing multiple structural models, volumetric data and crystal faces; calculation of electron and nuclear densities from structure parameters; calculation of Patterson functions from structure parameters or volumetric data; integration of electron and nuclear densities by Voronoi tessellation; visualization of isosurfaces with multiple levels; determination of the best plane for selected atoms; an extended bond-search algorithm to enable more sophisticated searches in complex molecules and cage-like structures; undo and redo in graphical user interface operations; and significant performance improvements in rendering isosurfaces and calculating slices.

Fräsen partikelverstärkter Titanmatrix-Verbundwerkstoffe*/Milling of particle-reinforced titanium metal matrix composites

2017 ◽  
Vol 107 (04) ◽  
pp. 301-305
Author(s):  
E. Prof. Uhlmann ◽  
F. Kaulfersch
Keyword(s):  
High Performance ◽  
High Wear Resistance ◽  
Tool Geometry ◽  
Matrix Composites ◽  
Titanium Matrix ◽  
Titanium Matrix Composites ◽  
Performance Improvements ◽  
Significant Performance ◽  
High Temperature Components ◽  
Process Strategy

Partikelverstärkte Titanmatrix-Verbundwerkstoffe erlauben erhebliche Leistungssteigerungen im Bereich hochtemperaturbeanspruchter Struktur- und Funktionsbauteile. Die durch die Partikelverstärkung gesteigerte Verschleißbeständigkeit, Festigkeit und Härte bedeuten eine große Herausforderung an die spanende Bearbeitung derartiger Hochleistungswerkstoffe. Mittels Zerspanuntersuchungen beim Fräsen konnten unter Variation der Werkzeuggeometrie, der Schneidstoffe und der Prozessstrategie Parameterbeiche identifiziert werden, mit denen die prozesssichere Zerspanung partikelverstärkter Titanmatrix-Verbundwerkstoffe möglich ist.   Particle-reinforced titanium matrix composites ensure significant performance improvements of structural and functional high-temperature components. However, the high wear resistance, toughness and hardness due to particle reinforcement is a major challenge in machining these high performance materials. By conducting milling experiments with a variation of tool geometry, cutting material and process strategy, process parameters could be identified that enable efficient machining of particle-reinforced titanium matrix composites.

Level of Automation Forms a Key Aspect of Autonomy Design

2017 ◽  
Vol 12 (1) ◽  
pp. 29-34 ◽  
Author(s):  
Mica R. Endsley
Keyword(s):  
Situation Awareness ◽  
Interface Design ◽  
Human Performance ◽  
Human Cognition ◽  
Level Of Automation ◽  
Out Of The Loop ◽  
Wide Range ◽  
Levels Of Automation ◽  
And Performance ◽  
The Impact

The concept of different levels of automation (LOAs) has been pervasive in the automation literature since its introduction by Sheridan and Verplanck. LOA taxonomies have been very useful in guiding understanding of how automation affects human cognition and performance, with several practical and theoretical benefits. Over the past several decades a wide body of research has been conducted on the impact of various LOAs on human performance, workload, and situation awareness (SA). LOA has a significant effect on operator SA and level of engagement that helps to ameliorate out-of-the-loop performance problems. Together with other aspects of system design, including adaptive automation, granularity of control, and automation interface design, LOA is a fundamental design characteristic that determines the ability of operators to provide effective oversight and interaction with system autonomy. LOA research provides a solid foundation for guiding the creation of effective human–automation interaction, which is critical for the wide range of autonomous and semiautonomous systems currently being developed across many industries.

scholarly journals A Robust Cooperative Modulation Classification Scheme with Intra sensor Fusion for the Time correlated Flat Fading Channels

2020 ◽  
Vol 70 (1) ◽  
pp. 60-65 ◽  
Author(s):  
Goran Marković ◽  
Vlada Sokolović
Keyword(s):  
Fading Channels ◽  
Sensor Fusion ◽  
Large Scale ◽  
Negative Influence ◽  
Modulation Classification ◽  
Distributed Sensors ◽  
Performance Improvements ◽  
Flat Fading ◽  
Significant Performance ◽  
Single Sensor

Networks with distributed sensors, e.g. cognitive radio networks or wireless sensor networks enable large-scale deployments of cooperative automatic modulation classification (AMC). Existing cooperative AMC schemes with centralised fusion offer considerable performance increase in comparison to single sensor reception. Previous studies were generally focused on AMC scenarios in which multipath channel is assumed to be static during a signal reception. However, in practical mobile environments, time-correlated multipath channels occur, which induce large negative influence on the existing cooperative AMC solutions. In this paper, we propose two novel cooperative AMC schemes with the additional intra-sensor fusion, and show that these offer significant performance improvements over the existing ones under given conditions.

scholarly journals A Parallel Event System for Large-Scale Cloud Simulations in DISSECT-CF

2021 ◽  
Author(s):  
Dilshad Hassan Sallo ◽  
Gabor Kecskemeti
Keyword(s):  
Time Management ◽  
Large Scale ◽  
Discrete Event ◽  
Parallel Execution ◽  
Management Scenarios ◽  
Performance Improvements ◽  
Event Simulation ◽  
Independent Events ◽  
Event System ◽  
Significant Performance

Discrete Event Simulation (DES) frameworks gained significant popularity to support and evaluate cloud computing environments. They support decision-making for complex scenarios, saving time and effort. The majority of these frameworks lack parallel execution. In spite being a sequential framework, DISSECT-CF introduced significant performance improvements when simulating Infrastructure as a Service (IaaS) clouds. Even with these improvements over the state of the art sequential simulators, there are several scenarios (e.g., large scale Internet of Things or serverless computing systems) which DISSECT-CF would not simulate in a timely fashion. To remedy such scenarios this paper introduces parallel execution to its most abstract subsystem: the event system. The new event subsystem detects when multiple events occur at a specific time instance of the simulation and decides to execute them either on a parallel or a sequential fashion. This decision is mainly based on the number of independent events and the expected workload of a particular event. In our evaluation, we focused exclusively on time management scenarios. While we did so, we ensured the behaviour of the events should be equivalent to realistic, larger-scale simulation scenarios. This allowed us to understand the effects of parallelism on the whole framework, while we also shown the gains of the new system compared to the old sequential one. With regards to scaling, we observed it to be proportional to the number of cores in the utilised SMP host.

The Performance of Air-Air Ejectors With Triangular Tabbed Driving Nozzles

2006 ◽  
Author(s):  
S. F. McBean ◽  
A. M. Birk
Keyword(s):  
Experimental Investigation ◽  
System Performance ◽  
Experimental Testing ◽  
Back Pressure ◽  
Tube Diameter ◽  
Performance Parameters ◽  
Mixing Performance ◽  
Performance Improvements ◽  
Significant Performance ◽  
Ejector System

This paper describes an experimental investigation into the effects of geometrical variations on ejector system performance when the driving nozzle includes delta mixing tabs. Mixing tabs have been shown to provide good mixing performance with comparable back-pressure penalties to other types of enhanced mixing nozzles. The performance parameters of most interest are pumping, mixing, and back-pressure. Geometric parameters studied include standoff distance, mixing-tube diameter, and tab angle. Experimental testing showed significant performance improvements in mixing and pumping with a decrease in tab angle. Maximum mixing was found to occur with tab angles positioned at 120°. Exceptional mixing was also observed with increased standoff. Back-pressure was shown to increase with increasing standoff and decreasing tab angle, but was not affected by mixing-tube diameter. In addition, a zone of recirculation was identified at the entrance to the mixing-tube. This zone is thought to have an influence on ejector performance.

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