Publications associées à Pratique fondée sur les preuves

OASIS: An integrated optimisation framework for activity scheduling

Activity-based models offer the potential for a far deeper understanding of daily mobility behaviour than trip-based models. Based on the fundamental assumption that travel demand is derived from the need to do activities, they are flexible tools that aim ...

EPFL2024

Artificial intelligence of things for synergizing smarter eco-city brain, metabolism, and platform: Pioneering data-driven environmental governance

Jeffrey Huang, Simon Elias Bibri

Emerging smarter eco-cities, inherently intertwined with environmental governance, function as experimental sites for testing novel technological solutions and implementing environmental reforms aimed at addressing complex challenges. However, despite sign ...

Elsevier2024

Neutrino Signal from a Population of Seyfert Galaxies

Andrii Neronov

IceCube Collaboration has previously reported evidence for a neutrino signal from a Seyfert galaxy NGC 1068. This may suggest that all Seyfert galaxies emit neutrinos. To test this hypothesis, we identify the best candidate neutrino sources among nearby Se ...

Amer Physical Soc2024

A semantic model-based systems engineering approach for assessing the operational performance of metal forming process

Dimitrios Kyritsis, Jinzhi Lu, Xiaochen Zheng

Metal Forming is a basic and essential industrial process to provide materials for constructing complex products. To design an efficient metal forming process, the functional requirements and operational performance are two important aspects to be consider ...

Pergamon-Elsevier Science Ltd2024

To Infinity, and Beyond (Coverage)

Ahmad Hazimeh

The pursuit of software security and reliability hinges on the identification and elimination of software vulnerabilities, a challenge compounded by the vast and evolving complexity of modern systems. Fuzzing has emerged as an indispensable technique for b ...

EPFL2024

When do Minimax-fair Learning and Empirical Risk Minimization Coincide?

Volkan Cevher

Minimax-fair machine learning minimizes the error for the worst-off group. However, empirical evidence suggests that when sophisticated models are trained with standard empirical risk minimization (ERM), they often have the same performance on the worst-of ...

2023

Thermal Conditions in Indoor Environments: Exploring the Reasoning behind Standard-Based Recommendations

Dolaana Khovalyg

Professionals in the building design and operation fields typically look at standards and guidelines as a reliable source of information and guidance with regard to procedural, contractual, and legal scope and requirements that are relevant to accountabili ...

2023

Discussion of ‘Experimental Evaluation of Algorithm-Assisted Human Decision-Making: Application to Pretrial Public Safety Assessment’, part 2

Mats Julius Stensrud, Aaron Leor Sarvet

Imai et al.(IJGHS) have conducted a timely experiment on evaluating a decision support algorithm. However, we are concerned by their choice of estimands which, even if they appear plausible at first, rely on notions and assumptions for which we cannot ever ...

2023

Learning Transformations To Reduce the Geometric Shift in Object Detection

Mathieu Salzmann, Martin Pierre Engilberge, Vidit Vidit

The performance of modern object detectors drops when the test distribution differs from the training one. Most of the methods that address this focus on object appearance changes caused by, e.g., different illumination conditions, or gaps between syntheti ...

Ieee Computer Soc2023

Predicting party switching through machine learning and open data

Silvestro Micera, Emanuele Rossi

Parliament dynamics might seem erratic at times. Predicting future voting patterns could support policy design based on the simulation of voting scenarios. The availability of open data on legislative activities and machine learning tools might enable such ...

CELL PRESS2023