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Results: 41
Ambidextrous Learning in Buyer-Supplier Relationships
Achieving competitive advantage in a dynamic environment requires firms to exploit their current capabilities and explore new opportunities through innovation. Organizational learning theory refers to these two types of focused...
Once reinforced random walk on Z × Γ

We revisit Vervoort’s unpublished paper (Vervoort (2002)) on the once reinforced random walk, and prove that this process is recurrent on any graph of the form Z × Γ, with Γ a finite graph, for sufficiently large...

A COMPUTATIONAL FRAMEWORK FOR EDGE-PRESERVING REGULARIZATION IN DYNAMIC INVERSE PROBLEMS

We devise efficient methods for dynamic inverse problems, where both the quantities of interest and the forward operator (measurement process) may change in time. Our goal is to solve for all the quantities of interest...

Semantics derived automatically from language corpora contain human-like biases
Machine learning is a means to derive artificial intelligence by discovering patterns in existing data. Here, we show that applying machine learning to ordinary human language results in human-like semantic biases. We replicated...
Semantics derived automatically from language corpora contain human-like biases
Machine learning is a means to derive artificial intelligence by discovering patterns in existing data. Here, we show that applying machine learning to ordinary human language results in human-like semantic biases. We replicated...
Once reinforced random walk on Z × Γ

We revisit Vervoort’s unpublished paper (Vervoort (2002)) on the once reinforced random walk, and prove that this process is recurrent on any graph of the form Z × Γ, with Γ a finite graph, for sufficiently large...

A COMPUTATIONAL FRAMEWORK FOR EDGE-PRESERVING REGULARIZATION IN DYNAMIC INVERSE PROBLEMS

We devise efficient methods for dynamic inverse problems, where both the quantities of interest and the forward operator (measurement process) may change in time. Our goal is to solve for all the quantities of interest...

Artificial Neural Network Dual Hesitant Fermatean Fuzzy Implementation in Transportation of COVID-19 Vaccine
This article, in order to address impreciseness, initiated the notion of dual hesitant fermatean fuzzy sets (DHFFSs), as a generalization of the combination of dual hesitant fuzzy set (DHFS), dual hesitant Pythagorean fuzzy set...
CMOS Radio Frequency Energy Harvester (RFEH) with Fully On-Chip Tunable Voltage-Booster for Wideband Sensitivity Enhancement.
Radio frequency energy harvesting (RFEH) is one form of renewable energy harvesting currently seeing widespread popularity because many wireless electronic devices can coordinate their communications via RFEH, especially in CMOS...
Published by: Micromachines
Impact of Correlated Noise on the Mass Precision of Earth-analog Planets in Radial Velocity Surveys
Characterizing the masses and orbits of near-Earth-mass planets is crucial for interpreting observations from future direct imaging missions (e.g., HabEx, LUVOIR). Therefore, the Exoplanet Science Strategy report recommended...
Hybrid Artificial Intelligence-Based Models for Prediction of Death Rate in India Due to COVID-19 Transmission
COVID-19 prediction models are highly welcome and necessary for authorities to make informed decisions. Traditional models, which were used in the past, were unable to reliably estimate death rates due to procedural flaws. The...

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