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Using a parsimonious model, this paper analyzes a dockless bike-sharing (DLB) service that competes with walking and a generic motorized mode. The DLB operator chooses a fleet size and a fare schedule that dictate the level of service (LOS) as measured by ...
What is good, less good, or bad architecture? This issue of OASE examines how shifting appreciations, for very diverse reasons, can function as a productive misunderstanding, and as a lever to advance architectural criticism and pry thinking about architec ...
In the wealthy and orderly city of Geneva, Switzerland, accommodation centres built in haste between the 1950s and the 1980s to house seasonal guestworkers from southern Europe are still standing and still inhabited. Today's residents are precarious worker ...
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 ...
Thanks to fundamental discoveries from neuroscience, biology and others, we have achieved a deeper understanding of how we interact with our environment. It is time to bring this knowledge back to architecture: we have access to the essential ingredients o ...
The increasing development of social networks provides a unique source for analyzing human dynamics in the modern age. In this paper, we analyze the top-one Internet forum in China ("Tianya Club") and identify the statistical properties of hotspots, which ...
Local Binary Descriptors (LBDs) are good at matching image parts, but how much information is actually carried? Surprisingly, this question is usually ignored and replaced by a comparison of matching performances. In this paper, we directly address it by t ...
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 ...
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 ...