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The value proposition canvas introduced in 2015 by Pigneur et al. is broadly used by entrepreneurs and intrapreneurs to create new services and products. We decided to apply it for collaborative and blended design thinking activities in a specialization in ...
As the volume of produced data is exponentially increasing, companies tend to rely on distributed systems to meet the surging demand for storage capacity. With the business workflows becoming more and more complex, such systems often consist of or are acce ...
Realtime is an investigation about china’s digital and urban infrastructure, practices and imaginary spaces. Realtime attempts to capture the pace, scale and depth of china’s complex and changing reality. ...
Data are essential to urban building energy models and yet, obtaining sufficient and accurate building data at a large-scale is challenging. Previous studies have highlighted that the data impact on urban case studies has not been sufficiently discussed. T ...
We consider a distributed social learning problem where a network of agents is interested in selecting one among a finite number of hypotheses. The data collected by the agents might be heterogeneous, meaning that different sub-networks might observe data ...
Advances in data acquisition technologies and supercomputing for large-scale simulations have led to an exponential growth in the volume of spatial data. This growth is accompanied by an increase in data complexity, such as spatial density, but also by mor ...
Background The 2014-2016 Ebola outbreak across West Africa was devastating, acting not only as a wake-up call for the global health community, but also as a catalyst for innovative change and global action. Improved infectious disease monitoring is the ste ...
Introduction: Early diagnosis and early treatment have become the gold standard for management of developmental dysplasia of the hip. Surgery is required in case of failed initial treatment. Innominate pelvic osteotomy of Salter (SIO), Pemberton's pericaps ...
Motivation: Unbiased clustering methods are needed to analyze growing numbers of complex data sets. Currently available clustering methods often depend on parameters that are set by the user, they lack stability, and are not applicable to small data sets. ...
In the past two decades, the use of ontologies has been proven to be an effective tool for enriching existing information systems in the digital data modelling domain and exploiting those assets for semantic interoperability. With the rise of Industry 4.0, ...
