scholarly journals Human Behavioral Response to Fluctuating Automation Reliability

2021 ◽  
Author(s):  
Jack Hutchinson ◽  
Simon Farrell ◽  
Luke Joseph Gough Strickland ◽  
Shayne Loft
Keyword(s):  
Behavioral Response ◽  
High Reliability ◽  
Human Perception ◽  
Dynamic Environments ◽  
Classification Task ◽  
Reliability Estimates ◽  
Acceptance Rates ◽  
True Reliability ◽  
Classification Reliability ◽  
Over Time

Human perception of automation reliability and automation acceptance behaviours are key to effective human-automation teaming. This study examined factors that impact perceptions of automation reliability over time and the acceptance of automated advice. Participants completed a maritime vessel classification task in which they classified vessels (contacts) with the assistance of automation. In Experiment 1 automation reliability successively switched from high to low (or vice versa). In Experiment 2 automation reliability decreased by varying magnitudes before returning to high. Participants did not initially calibrate to true reliability and experiencing low automation reliability reduced future reliability estimates when experiencing subsequent high reliability. Automation acceptance was predicted by positive differences between participants perception of automation reliability and confidence in their own classification reliability. Experiencing low automation reliability caused perceptions of reliability and automation acceptance rates to diverge. These findings have important implications for training and adaptive human-automation teaming in complex and dynamic environments.

scholarly journals The Perception of Automation Reliability and Acceptance of Automated Advice

2022 ◽  
pp. 001872082110629
Author(s):  
Jack Hutchinson ◽  
Luke Strickland ◽  
Simon Farrell ◽  
Shayne Loft
Keyword(s):  
Cognitive Science ◽  
Critical Factors ◽  
Recency Effects ◽  
Positive Difference ◽  
Reliability Estimates ◽  
The Common ◽  
The Difference ◽  
Acceptance Rates ◽  
True Reliability

Objective Examine (1) the extent to which humans can accurately estimate automation reliability and calibrate to changes in reliability, and how this is impacted by the recent accuracy of automation; and (2) factors that impact the acceptance of automated advice, including true automation reliability, reliability perception, and the difference between an operator’s perception of automation reliability and perception of their own reliability. Background Existing evidence suggests humans can adapt to changes in automation reliability but generally underestimate reliability. Cognitive science indicates that humans heavily weight evidence from more recent experiences. Method Participants monitored the behavior of maritime vessels (contacts) in order to classify them, and then received advice from automation regarding classification. Participants were assigned to either an initially high (90%) or low (60%) automation reliability condition. After some time, reliability switched to 75% in both conditions. Results Participants initially underestimated automation reliability. After the change in true reliability, estimates in both conditions moved towards the common true reliability, but did not reach it. There were recency effects, with lower future reliability estimates immediately following incorrect automation advice. With lower initial reliability, automation acceptance rates tracked true reliability more closely than perceived reliability. A positive difference between participant assessments of the reliability of automation and their own reliability predicted greater automation acceptance. Conclusion Humans underestimate the reliability of automation, and we have demonstrated several critical factors that impact the perception of automation reliability and automation use. Application The findings have potential implications for training and adaptive human-automation teaming.

Literature and the Senses

2021 ◽  
Author(s):  
Holly Dugan
Keyword(s):  
Cultural Study ◽  
Human Perception ◽  
Literary Representations ◽  
Interdisciplinary Field ◽  
The Senses ◽  
Historical Periods ◽  
Over Time ◽  
Culture And Language ◽  
Sensory Studies

Sensory studies is an interdisciplinary field connecting insights from history, anthropology, sociology, philosophy, religion, literature, and art to the scientific study of human perception. Though research in this field draws upon a wide variety of methodologies and focuses on different historical periods and geographical areas, it is unified through a core tenet: that the human sensorium is as much a cultural, historical, and aesthetic phenomenon as it is an environmental and a biological one. Social mores, geographies, religious beliefs, and individual abilities shape perception in uniquely cultural ways. Put more succinctly, sensory studies, as a field, argues for the cultural study of the senses and the sensuous study of culture. And language is squarely at the center of scholarly questions about perception; literary studies thus provides useful methodological tools for understanding not only how we represent visceral experiences (such as sensation) to others through language but also how these strategies have changed over time. The study of literature and the senses emphasizes the important role of language in representing visceral experience and the important role of aesthetics and history in shaping literary representations.

scholarly journals Random regression for modeling yield genetic trajectories in Jatropha curcas breeding

PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0244021
Author(s):  
Marco Antônio Peixoto ◽  
Rodrigo Silva Alves ◽  
Igor Ferreira Coelho ◽  
Jeniffer Santana Pinto Coelho Evangelista ◽  
Marcos Deon Vilela de Resende ◽  
...  
Keyword(s):  
Jatropha Curcas ◽  
Repeated Measures ◽  
Variance Components ◽  
High Reliability ◽  
Genetic Selection ◽  
Information Criterion ◽  
Random Regression ◽  
Ratio Test ◽  
Sib Families ◽  
Over Time

Random regression models (RRM) are a powerful tool to evaluate genotypic plasticity over time. However, to date, RRM remains unexplored for the analysis of repeated measures in Jatropha curcas breeding. Thus, the present work aimed to apply the random regression technique and study its possibilities for the analysis of repeated measures in Jatropha curcas breeding. To this end, the grain yield (GY) trait of 730 individuals of 73 half-sib families was evaluated over six years. Variance components were estimated by restricted maximum likelihood, genetic values were predicted by best linear unbiased prediction and RRM were fitted through Legendre polynomials. The best RRM was selected by Bayesian information criterion. According to the likelihood ratio test, there was genetic variability among the Jatropha curcas progenies; also, the plot and permanent environmental effects were statistically significant. The variance components and heritability estimates increased over time. Non-uniform trajectories were estimated for each progeny throughout the measures, and the area under the trajectories distinguished the progenies with higher performance. High accuracies were found for GY in all harvests, which indicates the high reliability of the results. Moderate to strong genetic correlation was observed across pairs of harvests. The genetic trajectories indicated the existence of genotype × measurement interaction, once the trajectories crossed, which implies a different ranking in each year. Our results suggest that RRM can be efficiently applied for genetic selection in Jatropha curcas breeding programs.

Shapes and Patterns in Visualizing Human Knowledge

2018 ◽  
pp. 1-16
Author(s):  
Grzegorz Osinski ◽  
Veslava Osinska
Keyword(s):  
Middle Ages ◽  
Human Perception ◽  
Human Mind ◽  
Fractal Structures ◽  
Main Hypothesis ◽  
Knowledge Presentation ◽  
Historical Outline ◽  
Effective Visualization ◽  
Different Cultures ◽  
Over Time

The concepts of knowledge presentation have their origin in the early Middle Ages and establish contemporary trends in visualization activity. Using the latest scientific observations, it is possible to conclude that circles and spheres are the most common natural shapes in both micro- and macrospace. The next most often used metaphor in medieval literature is a tree: an instance of fractals that today determines the geometry of nature. The fractals are the strong attractors of human mind space. The problem is how these two forms interact with each other and how they coexist in the context of effective visualization of information. The chapter presents an intercultural historical outline of appropriate graphical forms for knowledge representation. The authors strive to prove the main hypothesis: fractals and spheres contribute to modern complex visualization. The reasons may be sought in human perception and cognition. This chapter discusses visualization problems in the form of tree-like fractal structures embedded in spherical shapes over time, different cultures, and inter-personal relationships.

FINGERPRINT

2012 ◽  
Vol 8 (3) ◽  
pp. 27-44 ◽  
Author(s):  
Eirini Ntoutsi ◽  
Myra Spiliopoulou ◽  
Yannis Theodoridis
Keyword(s):  
Data Streams ◽  
Dynamic Environments ◽  
Incremental Method ◽  
Information Preservation ◽  
Space Reduction ◽  
Cluster Evolution ◽  
Summarization Method ◽  
Changing Patterns ◽  
Changes Over Time ◽  
Over Time

Monitoring and interpretation of changing patterns is a task of paramount importance for data mining applications in dynamic environments. While there is much research in adapting patterns in the presence of drift or shift, there is less research on how to maintain an overview of pattern changes over time. A major challenge is summarizing changes in an effective way, so that the nature of change can be understood by the user, while the demand on resources remains low. To this end, the authors propose FINGERPRINT, an environment for the summarization of cluster evolution. Cluster changes are captured into an “evolution graph,” which is then summarized based on cluster similarity into a fingerprint of evolution by merging similar clusters. The authors propose a batch summarization method that traverses and summarizes the Evolution Graph as a whole and an incremental method that is applied during the process of cluster transition discovery. They present experiments on different data streams and discuss the space reduction and information preservation achieved by the two methods.

scholarly journals How drain flies manage to almost never get washed away

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Nathan B. Speirs ◽  
Gauri A. Mahadik ◽  
Sigurdur T. Thoroddsen
Keyword(s):  
Fluid Dynamics ◽  
Behavioral Response ◽  
Natural Environments ◽  
Hierarchical Roughness ◽  
Wide Range ◽  
Over Time

Abstract Drain flies, Pshycoda spp. (Order Diptera, Family Psychodidae), commonly reside in our homes, annoying us in our bathrooms, kitchens, and laundry rooms. They like to stay near drains where they lay their eggs and feed on microorganisms and liquid carbohydrates found in the slime that builds up over time. Though they generally behave very sedately, they react quite quickly when threatened with water. A squirt from the sink induces them to fly away, seemingly unaffected, and flushing the toilet with flies inside does not necessarily whisk them down. We find that drain flies’ remarkable ability to evade such potentially lethal threats does not stem primarily from an evolved behavioral response, but rather from a unique hair covering with a hierarchical roughness. This covering, that has never been previously explored, imparts superhydrophobicity against large droplets and pools and antiwetting properties against micron-sized droplets and condensation. We examine how this hair covering equips them to take advantage of the relevant fluid dynamics and flee water threats in domestic and natural environments including: millimetric-sized droplets, mist, waves, and pools of water. Our findings elucidate drain flies’ astounding ability to cope with a wide range of water threats and almost never get washed down the drain.

Intelligent Controller for Mobile Robot Based on Heuristic Rule Base Network

2011 ◽  
Vol 403-408 ◽  
pp. 4777-4785
Author(s):  
Singh Mukesh Kumar ◽  
Mishra Deepak Kumar ◽  
R. Parhi Dayal ◽  
Singh Mahendra Prasad
Keyword(s):  
Mobile Robot ◽  
Simple Algorithm ◽  
Human Perception ◽  
Dynamic Environments ◽  
Rule Base ◽  
Heuristic Rule ◽  
Optimum Trajectory ◽  
Intelligent Controller ◽  
Estimation Function ◽  
Base Network

This paper is related to the human perception based idea by using heuristic information for the navigation of mobile robots in cluttered dynamic environments which provides a general, robust, safe and optimized path. The heuristic rule base network consists of a simple algorithm which makes predefined estimation function very smaller. The estimation function should be adequately defined for desired movement in the environments. A navigation system using rule based technique that allows a mobile robot to travel in an environment about, which the robot has no prior knowledge. This heuristic rule is applied in conjunction with artificial neural network. The proposed intelligent controller provides an optimum trajectory which increases the effectiveness of a mobile robot. A series of simulations test has been conducted to show the effectiveness of the proposed algorithm.

scholarly journals Adaptive Approaches Towards Better GA Performance in Dynamic Fitness Landscapes

1994 ◽  
Vol 23 (487) ◽  
Author(s):  
Henrik Hautop Lund
Keyword(s):  
Fitness Landscape ◽  
Dynamic Environments ◽  
Mutation Rates ◽  
Landscape Changes ◽  
Correlation Measure ◽  
The Right ◽  
Changes Over Time ◽  
Adaptive Approaches ◽  
Over Time ◽  
Selection Of

We review different techniques for improving GA performance. By analysing the fitness landscape, a correlation measure between parents and offspring can be provided, and we can estimate effectively which genetic operator to use in the GA for a given fitness landscape. The response to selection equation further tells us how well the GA will do, and combining the two approaches gives us a powerful tool to automatically ensure the selection of the right parameter settings for a given problem. In dynamic environments the fitness landscape changes over time, and the evolved systems should be able to adapt to such changes. By introducing evolvable mutation rates and evolvable fitness formulae, we obtain such systems. The systems are shown to be able to adapt to both internal and external constraints and changes.

scholarly journals Using Item Response Models to Develop a Criterion-Referenced Test to Measure the Students' Achievement in Educational Evaluation

2016 ◽  
Vol 10 (4) ◽  
pp. 727
Author(s):  
N uman S. Al-Musawi
Keyword(s):  
Item Response ◽  
High Reliability ◽  
Educational Evaluation ◽  
Maximum Information ◽  
Item Response Models ◽  
Reliability Estimates ◽  
Criterion Referenced Test ◽  
Criterion Referenced ◽  
University Of Bahrain ◽  
The University

The purpose of the study was to develop a criterion-referenced test to measurestudent's achievement in educational evaluation using item response theory. To achieve this goal, the author constructed a 3-option multiple-choice achievement test of 48 items that was later administered to 348 students enrolled at the University of Bahrain. The findings of study revealed that the students' responses to 31 items fit the Rasch model assumptions while 17 items did not fit the model. All items of the final version of the test, however, were located within the range of the model's infit and outfit indicators. Also, the reliability estimates for persons and items were .87 and .93, respectively, indicating a high reliability of the test, and the maximum information extracted from the three-option test is obtained at the average ability levels. Based on these results, the author recommends using the developed test as a reliable measure of the level of university student's achievement in the subject of educational evaluation

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