The interpretive model of manufacturing: a theoretical framework and research agenda for machine learning in manufacturing

2021 ◽  
pp. 1-35
Author(s):  
Ajit Sharma ◽  
Zhibo Zhang ◽  
Rahul Rai
Keyword(s):  
Machine Learning ◽  
Research Agenda ◽  
Theoretical Framework ◽  
Interpretive Model

Mind wandering as data augmentation: How mental travel supports abstraction

2020 ◽  
Vol 43 ◽  
Author(s):  
Myrthe Faber
Keyword(s):  
Machine Learning ◽  
Data Augmentation ◽  
Mental Content ◽  
Mind Wandering ◽  
Theoretical Framework ◽  
Important Addition

Abstract Gilead et al. state that abstraction supports mental travel, and that mental travel critically relies on abstraction. I propose an important addition to this theoretical framework, namely that mental travel might also support abstraction. Specifically, I argue that spontaneous mental travel (mind wandering), much like data augmentation in machine learning, provides variability in mental content and context necessary for abstraction.

EIMECA: A Proposal for a Model of Collective Environmental Actions

2021 ◽  
Author(s):  
Beatriz Carmona-Moya ◽  
Antonia Calvo-Salguero ◽  
M.Carmen Aguilar-Luzón
Keyword(s):  
Collective Action ◽  
Psychosocial Factors ◽  
Research Agenda ◽  
Theoretical Framework ◽  
Environmental Action ◽  
Environmental Identity ◽  
Group Efficacy ◽  
Negative Affects ◽  
Environmental Actions

The deterioration and destruction of the environment is becoming more and more considerable and greater efforts are needed to stop it. To accomplish this feat, all members of society must identify with environmental problems, with collective environmental action being one of the most relevant means of doing so. From this perspective, the analysis of the psychosocial factors that lead to participation in environmental collective action emerges as a priority objective in the research agenda. Thus, the aim of this study is to examine the role of "environmental identity" as conceptualized by Clayton, as a central axis for explaining environmental collective action. The inclusion of the latter in the theoretical framework of the SIMCA model gives rise to the model that we have called EIMECA. Two studies were conducted, and the results reveal that environmental identity, a variety of negative affects, as well as group efficacy accompanied by hope for a simultaneous additive effect, are critical when it comes to predicting environmental collective action.

Engineering AI Systems

2021 ◽  
pp. 1-19 ◽  
Author(s):  
Jan Bosch ◽  
Helena Holmström Olsson ◽  
Ivica Crnkovic
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Data Quality ◽  
Case Studies ◽  
Research Agenda ◽  
Production Quality ◽  
Research Community ◽  
Design Methods ◽  
Engineering Approach ◽  
Quality Design

Artificial intelligence (AI) and machine learning (ML) are increasingly broadly adopted in industry. However, based on well over a dozen case studies, we have learned that deploying industry-strength, production quality ML models in systems proves to be challenging. Companies experience challenges related to data quality, design methods and processes, performance of models as well as deployment and compliance. We learned that a new, structured engineering approach is required to construct and evolve systems that contain ML/DL components. In this chapter, the authors provide a conceptualization of the typical evolution patterns that companies experience when employing ML as well as an overview of the key problems experienced by the companies that they have studied. The main contribution of the chapter is a research agenda for AI engineering that provides an overview of the key engineering challenges surrounding ML solutions and an overview of open items that need to be addressed by the research community at large.

scholarly journals COPD phenotypes and machine learning cluster analysis: A systematic review and future research agenda

2020 ◽  
Vol 171 ◽  
pp. 106093 ◽  
Author(s):  
Vasilis Nikolaou ◽  
Sebastiano Massaro ◽  
Masoud Fakhimi ◽  
Lampros Stergioulas ◽  
David Price
Keyword(s):  
Machine Learning ◽  
Systematic Review ◽  
Cluster Analysis ◽  
Research Agenda ◽  
Future Research ◽  
Future Research Agenda

scholarly journals Dynamic self- and other-focused emotional intelligence: A theoretical framework and research agenda

2020 ◽  
Vol 86 ◽  
pp. 103958
Author(s):  
Keri A. Pekaar ◽  
Dimitri van der Linden ◽  
Arnold B. Bakker ◽  
Marise Ph. Born
Keyword(s):  
Emotional Intelligence ◽  
Research Agenda ◽  
Theoretical Framework ◽  
Self And Other
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