scholarly journals Body sway predicts romantic interest in speed dating

2020 ◽  
Author(s):  
Andrew Chang ◽  
Haley E Kragness ◽  
Wei Tsou ◽  
Dan J Bosnyak ◽  
Anja Thiede ◽  
...  
Keyword(s):  
Real World ◽  
Communication Disorders ◽  
Social Bonding ◽  
Background Music ◽  
Body Sway ◽  
Personality Factors ◽  
Human Society ◽  
Speed Dating ◽  
Novel Approach ◽  
Romantic Interest

Abstract Social bonding is fundamental to human society, and romantic interest involves an important type of bonding. Speed dating research paradigms offer both high external validity and experimental control for studying romantic interest in real-world settings. While previous studies focused on the effect of social and personality factors on romantic interest, the role of non-verbal interaction has been little studied in initial romantic interest, despite being commonly viewed as a crucial factor. The present study investigated whether romantic interest can be predicted by non-verbal dyadic interactive body sway, and enhanced by movement-promoting (‘groovy’) background music. Participants’ body sway trajectories were recorded during speed dating. Directional (predictive) body sway coupling, but not body sway similarity, predicted interest in a long-term relationship above and beyond rated physical attractiveness. In addition, presence of groovy background music promoted interest in meeting a dating partner again. Overall, we demonstrate that romantic interest is reflected by non-verbal body sway in dyads in a real-world dating setting. This novel approach could potentially be applied to investigate non-verbal aspects of social bonding in other dynamic interpersonal interactions such as between infants and parents and in non-verbal populations including those with communication disorders.

scholarly journals Body sway predicts romantic interest in speed dating

2019 ◽  
Author(s):  
Andrew Chang ◽  
Haley Elisabeth Kragness ◽  
Wei Tsou ◽  
Dan J. Bosnyak ◽  
Anja Thiede ◽  
...  
Keyword(s):  
Real World ◽  
Communication Disorders ◽  
Social Bonding ◽  
Background Music ◽  
Body Sway ◽  
Personality Factors ◽  
Human Society ◽  
Speed Dating ◽  
Novel Approach ◽  
Romantic Interest

Social bonding is fundamental to human society, and romantic interest involves an important type of bonding. Speed dating research paradigms offer both high external validity and experimental control for studying romantic interest in real-world settings. While previous studies focused on the effect of social and personality factors on romantic interest, the role of non-verbal interaction has been little studied in initial romantic interest, despite being commonly viewed as a crucial factor. The present study investigated whether romantic interest can be predicted by non-verbal dyadic interactive body sway, and enhanced by movement-promoting (‘groovy’) background music. Participants’ body sway trajectories were recorded during speed dating. Directional (predictive) body sway coupling, but not body sway similarity, predicted interest in a long-term relationship above and beyond rated physical attractiveness. In addition, presence of groovy background music promoted interest in meeting a dating partner again. Overall, we demonstrate that romantic interest is reflected by non-verbal body sway in dyads in a real-world dating setting. This novel approach could potentially be applied to investigate non-verbal aspects of social bonding in other dynamic interpersonal interactions such as between infants and parents and in non-verbal populations including those with communication disorders.

Current Issues: Evidence-Based Practice for the Real World: Thoughts on Clinical Education in Communication Disorders

2010 ◽  
Vol 20 (3) ◽  
pp. 100-105 ◽  
Author(s):  
Anne K. Bothe
Keyword(s):  
Clinical Education ◽  
Real World ◽  
Evidence Based Practice ◽  
Communication Disorders ◽  
University Faculty ◽  
Evidence Based ◽  
Speech Language Pathology ◽  
Basic Principles ◽  
The Real ◽  
Language Pathology

This article presents some streamlined and intentionally oversimplified ideas about educating future communication disorders professionals to use some of the most basic principles of evidence-based practice. Working from a popular five-step approach, modifications are suggested that may make the ideas more accessible, and therefore more useful, for university faculty, other supervisors, and future professionals in speech-language pathology, audiology, and related fields.

scholarly journals Source identification of infectious diseases in networks via label ranking

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0245344
Author(s):  
Jianye Zhou ◽  
Yuewen Jiang ◽  
Biqing Huang
Keyword(s):  
Infectious Diseases ◽  
Real World ◽  
Source Identification ◽  
Human Society ◽  
Practical Applications ◽  
Ranking Algorithms ◽  
Label Ranking ◽  
Infection Source ◽  
And Control ◽  
Complete Observation

Background Outbreaks of infectious diseases would cause great losses to the human society. Source identification in networks has drawn considerable interest in order to understand and control the infectious disease propagation processes. Unsatisfactory accuracy and high time complexity are major obstacles to practical applications under various real-world situations for existing source identification algorithms. Methods This study attempts to measure the possibility for nodes to become the infection source through label ranking. A unified Label Ranking framework for source identification with complete observation and snapshot is proposed. Firstly, a basic label ranking algorithm with complete observation of the network considering both infected and uninfected nodes is designed. Our inferred infection source node with the highest label ranking tends to have more infected nodes surrounding it, which makes it likely to be in the center of infection subgraph and far from the uninfected frontier. A two-stage algorithm for source identification via semi-supervised learning and label ranking is further proposed to address the source identification issue with snapshot. Results Extensive experiments are conducted on both synthetic and real-world network datasets. It turns out that the proposed label ranking algorithms are capable of identifying the propagation source under different situations fairly accurately with acceptable computational complexity without knowing the underlying model of infection propagation. Conclusions The effectiveness and efficiency of the label ranking algorithms proposed in this study make them be of practical value for infection source identification.

scholarly journals Silica-encapsulated DNA tracers for measuring aerosol distribution dynamics in real-world settings

2021 ◽  
Author(s):  
Anne M Luescher ◽  
Julian Koch ◽  
Wendelin J Stark ◽  
Robert N Grass
Keyword(s):  
Real World ◽  
Complex Dynamics ◽  
Quantitative Polymerase Chain Reaction ◽  
Cost Effective ◽  
Confined Space ◽  
Aerosol Dynamics ◽  
Novel Approach ◽  
Aerosol Distribution ◽  
Wide Range ◽  
Series Of Experiments

Aerosolized particles play a significant role in human health and environmental risk management. The global importance of aerosol-related hazards, such as the circulation of pathogens and high levels of air pollutants, have led to a surging demand for suitable surrogate tracers to investigate the complex dynamics of airborne particles in real-world scenarios. In this study, we propose a novel approach using silica particles with encapsulated DNA (SPED) as a tracing agent for measuring aerosol distribution indoors. In a series of experiments with a portable setup, SPED were successfully aerosolized, re-captured and quantified using quantitative polymerase chain reaction (qPCR). Position-dependency and ventilation effects within a confined space could be shown in a quantitative fashion achieving detection limits below 0.1 ng particles per m3 of sampled air. In conclusion, SPED show promise for a flexible, cost-effective and low-impact characterization of aerosol dynamics in a wide range of settings.

scholarly journals Optimising Daily Fantasy Sports Teams with Artificial Intelligence

2020 ◽  
Vol 19 (2) ◽  
pp. 21-35
Author(s):  
Ryan Beal ◽  
Timothy J. Norman ◽  
Sarvapali D. Ramchurn
Keyword(s):  
Real World ◽  
National Football League ◽  
Mixed Integer ◽  
Data Sets ◽  
Fantasy Sports ◽  
Real World Data ◽  
Sports Teams ◽  
Novel Approach ◽  
Four Seasons ◽  
Daily Fantasy Sports

AbstractThis paper outlines a novel approach to optimising teams for Daily Fantasy Sports (DFS) contests. To this end, we propose a number of new models and algorithms to solve the team formation problems posed by DFS. Specifically, we focus on the National Football League (NFL) and predict the performance of real-world players to form the optimal fantasy team using mixed-integer programming. We test our solutions using real-world data-sets from across four seasons (2014-2017). We highlight the advantage that can be gained from using our machine-based methods and show that our solutions outperform existing benchmarks, turning a profit in up to 81.3% of DFS game-weeks over a season.

scholarly journals Identifying and Labeling Potentially Risky Driving: A Multistage Process Using Real-World Driving Data

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Charles Marks ◽  
Arash Jahangiri ◽  
Sahar Ghanipoor Machiani
Keyword(s):  
Real World ◽  
Traffic Accidents ◽  
Network Models ◽  
Multistage Process ◽  
Neural Network Models ◽  
Risky Driving ◽  
Vehicle Accidents ◽  
Driving Behaviors ◽  
Novel Approach ◽  
Risky Driving Behaviors

Every year, over 50 million people are injured and 1.35 million die in traffic accidents. Risky driving behaviors are responsible for over half of all fatal vehicle accidents. Identifying risky driving behaviors within real-world driving (RWD) datasets is a promising avenue to reduce the mortality burden associated with these unsafe behaviors, but numerous technical hurdles must be overcome to do so. Herein, we describe the implementation of a multistage process for classifying unlabeled RWD data as potentially risky or not. In the first stage, data are reformatted and reduced in preparation for classification. In the second stage, subsets of the reformatted data are labeled as potentially risky (or not) using the Iterative-DBSCAN method. In the third stage, the labeled subsets are then used to fit random forest (RF) classification models—RF models were chosen after they were found to be performing better than logistic regression and artificial neural network models. In the final stage, the RF models are used predictively to label the remaining RWD data as potentially risky (or not). The implementation of each stage is described and analyzed for the classification of RWD data from vehicles on public roads in Ann Arbor, Michigan. Overall, we identified 22.7 million observations of potentially risky driving out of 268.2 million observations. This study provides a novel approach for identifying potentially risky driving behaviors within RWD datasets. As such, this study represents an important step in the implementation of protocols designed to address and prevent the harms associated with risky driving.

scholarly journals Evaluating the Performance of Novel JWT Revocation Strategy

2021 ◽  
Author(s):  
László Viktor Jánoky ◽  
Péter Ekler ◽  
János Levendovszky
Keyword(s):  
Access Control ◽  
Real World ◽  
Mathematical Framework ◽  
Web Based ◽  
Novel Approach ◽  
User Access ◽  
Digital Signing

JSON Web Tokens (JWT) provide a scalable, distributed way of user access control for modern web-based systems. The main advantage of the scheme is that the tokens are valid by themselves – through the use of digital signing – also imply its greatest weakness. Once issued, there is no trivial way to revoke a JWT token. In our work, we present a novel approach for this revocation problem, overcoming some of the problems of currently used solutions. To compare our solution to the established solutions, we also introduce the mathematical framework of comparison, which we ultimately test using real-world measurements.

A Novel Approach for Deploying Minimum Sensors in Smart Buildings

2022 ◽  
Vol 6 (1) ◽  
pp. 1-29
Author(s):  
Anshul Agarwal ◽  
Krithi Ramamritham
Keyword(s):  
Real World ◽  
Cyber Physical Systems ◽  
Management Systems ◽  
Physical Systems ◽  
Optimization Framework ◽  
Sensing System ◽  
Novel Approach ◽  
Building Management ◽  
Minimum Number ◽  
Building Management Systems

Buildings, viewed as cyber-physical systems, become smart by deploying Building Management Systems (BMS). They should be aware about the state and environment of the building. This is achieved by developing a sensing system that senses different interesting factors of the building, called as “facets of sensing.” Depending on the application, different facets need to be sensed at various locations. Existing approaches for sensing these facets consist of deploying sensors at all the places so they can be sensed directly. But installing numerous sensors often aggravate the issues of user inconvenience, cost of installation and maintenance, and generation of e-waste. This article proposes how intelligently using the existing information can help to estimate the facets in cyber-physical systems like buildings, thereby reducing the sensors to be deployed. In this article, an optimization framework has been developed, which optimally deploys sensors in a building such that it satisfies BMS requirements with minimum number of sensors. The proposed solution is applied to real-world scenarios with cyber-physical systems. The results indicate that the proposed optimization framework is able to reduce the number of sensors by 59% and 49% when compared to the baseline and heuristic approach, respectively.

Expert and Novice End-User Spreadsheet Debugging

2011 ◽  
Vol 23 (2) ◽  
pp. 57-80 ◽  
Author(s):  
Brian Bishop ◽  
Kevin McDaid
Keyword(s):  
Experimental Data ◽  
Real World ◽  
End Users ◽  
End User ◽  
Novel Approach ◽  
Expert And Novice ◽  
Research Studies

The reliability of end-user developed spreadsheets is poor. Research studies find that 94% of ‘real-world’ spreadsheets contain errors. Although some research has been conducted in the area of spreadsheet testing, little is known about the behaviour or processes of individuals during the debugging task. In this paper, the authors investigate the performance and behaviour of expert and novice end-users in the debugging of an experimental spreadsheet. To achieve this aim, a spreadsheet debugging experiment was conducted, with professional and student participants requested to debug a spreadsheet seeded with errors. The work utilises a novel approach for acquiring experimental data through the unobtrusive recording of participants’ actions using a custom built VBA tool. Based on findings from the experiment, a debugging tool is developed, and its effects on debugging performance are investigated.

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