Correction: Data-Driven Approach for Understanding the Impact of Weather on Commercial Flight Path

2019 ◽  
Author(s):  
Jung-Hyun Kim ◽  
Kisun Song ◽  
Seulki Kim ◽  
Dimitri N. Mavris
Keyword(s):  
Flight Path ◽  
Data Driven ◽  
Data Driven Approach ◽  
Commercial Flight ◽  
The Impact

La orientación al dato, nuevos desafíos

Tábula ◽  
2021 ◽  
Author(s):  
Miguel Ángel Amutio Gómez
Keyword(s):  
European Union ◽  
Digital Transformation ◽  
Data Driven ◽  
The European Union ◽  
Data Preservation ◽  
The Future ◽  
Data Driven Approach ◽  
New Challenges ◽  
The Impact

La orientación al dato en el contexto de la transformación digital lleva aparejada la aparición de nuevas regulaciones, dinámicas de gobernanza y roles, y servicios, junto con las correspondientes prácticas, instrumentos y estándares. A la vez se suscitan retos en relación con la ciberseguridad y la preservación de los datos. En este artículo se exponen la transformación digital y la orientación al dato, la proyección de lo anterior en la administración digital, el contexto de la Unión Europea, trayectoria y su orientación, aspectos de la interoperabilidad, ciberseguridad y preservación de los datos, cuestiones de gobernanza y roles en la orientación al dato y, finalmente, unas conclusiones. The data-driven approach in the context of digital transformation entails the appearance of new regulations, governance dynamics and roles, and services, together with the corresponding practices, instruments and standards. At the same time new challenges appear in relation to cybersecurity and data preservation. This article presents the digital transformation and data-driven approach, the impact in digital administration, the context of the European Union, trajectory and orientation towards the future, along with aspects of interoperability, cybersecurity and data preservation, as well as issues of governance and roles in data orientation and finally some conclusions.

A Data-Driven Approach using Machine Learning to Enable Real-Time Flight Path Planning

2020 ◽  
Author(s):  
Jung-Hyun Kim ◽  
Simon I. Briceno ◽  
Cedric Y. Justin ◽  
Dimitri Mavris
Keyword(s):  
Machine Learning ◽  
Path Planning ◽  
Real Time ◽  
Flight Path ◽  
Data Driven ◽  
Data Driven Approach

scholarly journals A data-driven approach to characterize the impact of connected and autonomous vehicles on traffic flow

2020 ◽  
pp. 1-9
Author(s):  
Amir Bahador Parsa ◽  
Ramin Shabanpour ◽  
Abolfazl (Kouros) Mohammadian ◽  
Joshua Auld ◽  
Thomas Stephens
Keyword(s):  
Traffic Flow ◽  
Autonomous Vehicles ◽  
Data Driven ◽  
Data Driven Approach ◽  
The Impact

Will the relevance of review language and destination attractions be helpful? A data-driven approach

2020 ◽  
pp. 135676672095035
Author(s):  
Sunyoung Hlee ◽  
Hyunae Lee ◽  
Chulmo Koo ◽  
Namho Chung
Keyword(s):  
Online Reviews ◽  
Data Driven ◽  
Online Review ◽  
Cognitive Fit ◽  
Theoretical Contribution ◽  
Language Style ◽  
Data Driven Approach ◽  
Managerial Implications ◽  
Tourism Destinations ◽  
The Impact

Because tourism destinations are difficult to assess in certain standard aspects, the factors that contribute to the helpfulness of reviews remain largely unknown. Moreover, the helpfulness of online reviews has not been explored in terms of the interaction between language style (high- vs. low-cognitive) and attraction type (hedonic vs. utilitarian). Hence, this study examines the impact of language style on the helpfulness of an online review of an attraction, depending on the type of attraction and the meaning of the destination. This study’s data included 8,032 reviews of four attractions (2 hedonic x 2 utilitarian), drawn from TripAdvisor in two different meanings of destinations. Specifically, our findings indicate that when a reviewer posts a utilitarian attraction of the destination, high-cognitive language is perceived to be more helpful. First, we discuss the theoretical contribution of our study using cognitive fit theory, and then provide the study’s managerial implications.

scholarly journals Discovery of the Environmental Factors Affecting Urban Dwellers’ Mental Health: A Data-Driven Approach

2020 ◽  
Vol 17 (21) ◽  
pp. 8167
Author(s):  
Chao Wu ◽  
Pei Zheng ◽  
Xinyuan Xu ◽  
Shuhan Chen ◽  
Nasi Wang ◽  
...  
Keyword(s):  
Mental Health ◽  
Environmental Factors ◽  
Mental States ◽  
Data Driven ◽  
Neural Network Modeling ◽  
Starting Point ◽  
Data Driven Approach ◽  
Linear And Nonlinear ◽  
The Impact ◽  
Maximal Information Coefficient

Mental health is the foundation of health and happiness as well as the basis for an individual’s meaningful life. The environmental and social health of a city can measure the mental state of people living in a certain areas, and exploring urban dwellers’ mental states is an important factor in understanding and better managing cities. New dynamic and granular urban data provide us with a way to determine the environmental factors that affect the mental states of urban dwellers. The characteristics of the maximal information coefficient can identify the linear and nonlinear relationships so that we can fully identify the physical and social environmental factors that affect urban dwellers’ mental states and further test these relationships through linear and nonlinear modeling. Taking the Greater London as an example, we used data from the London Datastore to discover the environmental factors that had the highest correlation with urban mental health from 2015 to 2017 and to prove that they had a high nonlinear correlation through neural network modeling. This paper aimed to use a data-driven approach to find environmental factors that had not yet received enough attention and to provide a starting point for research by establishing hypotheses for further exploration of the impact of environmental factors on mental health.

scholarly journals Immunodietica: A data-driven approach to investigate interactions between diet and autoimmune disorders

2019 ◽  
Author(s):  
Iosif M. Gershteyn ◽  
Leonardo M.R. Ferreira
Keyword(s):  
Risk Factor ◽  
Autoimmune Disease ◽  
Autoimmune Disorders ◽  
Data Driven ◽  
Human Autoimmune Disease ◽  
Future Studies ◽  
Peptide Epitopes ◽  
Data Driven Approach ◽  
The Impact ◽  
Pork Consumption

AbstractAutoimmunity is on the rise around the globe. Diet has been proposed as a risk factor for autoimmunity and shown to modulate the severity of several autoimmune disorders. Yet, the interaction between diet and autoimmunity in humans remains largely unstudied. Here, we systematically interrogated commonly consumed animals and plants for peptide epitopes previously implicated in human autoimmune disease. A total of fourteen species investigated could be divided into three broad categories regarding their content in human autoimmune epitopes, which we represented using a new metric, the Gershteyn-Ferreira index (GF index). Strikingly, pig contains a disproportionately high number of unique autoimmune epitopes compared to all other species analyzed. This work uncovers a potential new link between pork consumption and autoimmunity in humans and lays the foundation for future studies on the impact of diet on the pathogenesis and progression of autoimmune disorders.

scholarly journals Measuring sign complexity: Comparing a theory-driven and a data-driven approach

2022 ◽  
Author(s):  
Justine Mertz ◽  
Chiara Annucci ◽  
Valentina Aristodemo ◽  
Beatrice Giustolisi ◽  
Doriane Gras ◽  
...  
Keyword(s):  
Error Rates ◽  
Data Driven ◽  
Sign Languages ◽  
Fine Grained ◽  
Geometry Model ◽  
Feature Geometry ◽  
Data Driven Approach ◽  
Two Measures ◽  
Orientation Movement ◽  
The Impact

The study of articulatory complexity has proven to yield useful insights into the phonological mechanisms of spoken languages. In sign languages, this type of knowledge is scarcely documented. The current study compares a data-driven measure and a theory-driven measure of complexity for signs in French Sign Language (LSF). The former measure is based on error rates of handshape, location, orientation, movement and sign fluidity in a repetition task administered to non-signers; the latter measure is derived by applying a feature-geometry model of sign description on the same set of signs. A significant correlation is found between the two measures for the overall complexity. When looking at the impact of individual phonemic classes on complexity, a significant correlation is found for handshape and location but not for movement. We discuss how these results indicate that a fine-grained theoretical model of sign phonology/phonetics reflects the degree of complexity as resulting from the perceptual and articulatory properties of signs.

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