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Classification methods from machine learning are receiving a lot of attention in the transportation modelling community. This is motivated by the access to large databases, and to various success stories reported in this research community. Discrete choice ...
Process output and profitability of the operations are mainly determined by how the equipment is being used. The production planning, operations and machine maintenance influence the overall equipment effectiveness (OEE) of the machinery, resulting in more ...
Urbanisation is known as a fundamental driver of actual land use change. A good understanding of how catchments are affected by urbanisation (particularly in terms of water quantity and quality) is necessary to be able to propose more sustainable approache ...
A large part of the research utilizing the concept of Macroscopic Fundamental Diagram (MFD) relies heavily on the PL model, an approximation of the trip completion rate derived for steady states. There exists an alternative method to the PL approximation. ...
Gadolinium‐loaded nanomicelles show promise as future magnetic resonance imaging (MRI) contrast agents (CAs). Their increased size and high gadolinium (Gd) loading gives them an edge in proton relaxivity over smaller molecular Gd‐complexes. Their size and ...
This contribution uses metaphors originated in the Dynamical Systems Theory to describe the potential pathways in the evolution of human societies and how, through the accumulation of tensions at critical points, bifurcations can emerge, for the good or th ...
Designing the underlying mechanical structure of lower limb exoskeletons for assistance and rehabilitation is a demanding task that requires a good understanding of the interaction that takes place between the exoskeleton and the human user wearing it. Oft ...
State-of-the-art immutable collections have wildly differing performance characteristics across their operations, often forcing programmers to choose different collection implementations for each task. Thus, changes to the program can invalidate the choice ...
A quantum-implementable neural network, namely quantum probability neural network (QPNN) model, is proposed in this paper. QPNN can use quantum parallelism to trace all possible network states to improve the result. Due to its unique quantum nature, this m ...
Technology downscaling is expected to amplify a variety of reliability concerns in future digital systems. A good understanding of reliability threats is crucial for the creation of efficient mitigation techniques. This survey performs a systematic classif ...