AIMC Topic: Risk-Taking

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Behavioural Models of Risk-Taking in Human-Robot Tactile Interactions.

Sensors (Basel, Switzerland) May 16, 2023
Touch can have a strong effect on interactions between people, and as such, it is expected to be important to the interactions people have with robots. In an earlier work, we showed that the intensity of tactile interaction with a robot can change ho...
Social Interaction Touch Touch Perception Risk-Taking Humans Robotics
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A hybrid neural network for driving behavior risk prediction based on distracted driving behavior data.

PloS one Jan 25, 2022
Distracted driving behavior is one of the main factors of road accidents. Accurately predicting the risk of driving behavior is of great significance to the active safety of road transportation. The large amount of information collected by the sensor...
Accidents, Traffic Attention Risk-Taking Humans Neural Networks, Computer Models, Biological Distracted Driving
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The Robot Made Me Do It: Human-Robot Interaction and Risk-Taking Behavior.

Cyberpsychology, behavior and social networking Nov 18, 2020
Empirical evidence has shown that peer pressure can impact human risk-taking behavior. With robots becoming ever more present in a range of human settings, it is crucial to examine whether robots can have a similar impact. Using the balloon analogue ...
Adult Humans Male Young Adult Robotics Decision Making Social Behavior Peer Influence Risk-Taking
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Improve Aggressive Driver Recognition Using Collision Surrogate Measurement and Imbalanced Class Boosting.

International journal of environmental research and public health Mar 31, 2020
Real-time recognition of risky driving behavior and aggressive drivers is a promising research domain, thanks to powerful machine learning algorithms and the big data provided by in-vehicle and roadside sensors. However, since the occurrence of aggre...
Female Male Big Data Accidents, Traffic Humans Machine Learning Algorithms Risk-Taking Automobile Driving Recognition, Psychology Aggression
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A genome-wide multiphenotypic association analysis identified candidate genes and gene ontology shared by four common risky behaviors.

Aging Feb 22, 2020
BACKGROUND: Risky behaviors can lead to huge economic and health losses. However, limited efforts are paid to explore the genetic mechanisms of risky behaviors.
Gene Ontology Neurogenesis Risk-Taking Genetic Predisposition to Disease Polymorphism, Single Nucleotide Intelligence Humans Phenotype Autism Spectrum Disorder Transcriptome Genome-Wide Association Study
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FastEmbed: Predicting vulnerability exploitation possibility based on ensemble machine learning algorithm.

PloS one Feb 6, 2020
In recent years, the number of vulnerabilities discovered and publicly disclosed has shown a sharp upward trend. However, the value of exploitation of vulnerabilities varies for attackers, considering that only a small fraction of vulnerabilities are...
Risk-Taking Proof of Concept Study Computer Security Information Systems Forecasting Confidentiality Data Collection Machine Learning Algorithms
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Predicting Future Driving Risk of Crash-Involved Drivers Based on a Systematic Machine Learning Framework.

International journal of environmental research and public health Jan 25, 2019
The objective of this paper is to predict the future driving risk of crash-involved drivers in Kunshan, China. A systematic machine learning framework is proposed to deal with three critical technical issues: 1. defining driving risk; 2. developing r...
Risk Assessment China Models, Theoretical Decision Trees Accidents, Traffic Automobile Driving Machine Learning Risk-Taking Forecasting Humans Risk Factors
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Pedestrian's risk-based negotiation model for self-driving vehicles to get the right of way.

Accident; analysis and prevention Jan 17, 2019
Negotiations among drivers and pedestrians are common on roads, but it is still challenging for a self-driving vehicle to negotiate for its right of way with other human road users, especially pedestrians. Currently, the self-driving vehicles are pro...
Automobiles Pedestrians Accidents, Traffic Negotiating Time Factors Humans Risk-Taking Models, Theoretical Artificial Intelligence Decision Making
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Machine-learning prediction of adolescent alcohol use: a cross-study, cross-cultural validation.

Addiction (Abingdon, England) Dec 21, 2018
BACKGROUND AND AIMS: The experience of alcohol use among adolescents is complex, with international differences in age of purchase and individual differences in consumption and consequences. This latter underlines the importance of prediction modelin...
Male Underage Drinking Adolescent Risk-Taking Cohort Studies Algorithms Forecasting Humans Female Neural Networks, Computer Support Vector Machine Machine Learning Australia Child Regression Analysis Canada Cross-Cultural Comparison Logistic Models
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Identifying substance use risk based on deep neural networks and Instagram social media data.

Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology Oct 24, 2018
Social media may provide new insight into our understanding of substance use and addiction. In this study, we developed a deep-learning method to automatically classify individuals' risk for alcohol, tobacco, and drug use based on the content from th...
Substance-Related Disorders Risk Assessment Alcoholism Deep Learning Risk-Taking Social Media Humans Adult Sensitivity and Specificity
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