Slowness and sparseness lead to place, head-direction, and spatial-view cells.

We present a model for the self-organized formation of place cells, head-direction cells, and spatial-view cells in the hippocampal formation based on unsupervised learning on quasi-natural visual stimuli. The model comprises a hierarchy of Slow Feature Analysis (SFA) nodes, which were recently shown to reproduce many properties of complex cells in the early visual system []. The system extracts a distributed grid-like representation of position and orientation, which is transcoded into a localized place-field, head-direction, or view representation, by sparse coding. The type of cells that develops depends solely on the relevant input statistics, i.e., the movement pattern of the simulated animal. The numerical simulations are complemented by a mathematical analysis that allows us to accurately predict the output of the top SFA layer.

Stakeholder engagement in early stage product-service system development for healthcare informatics

This paper presents the findings from four case studies on stakeholder engagement in new health information and communication technology (ICT) product-service system (PSS) development. The degree of connectivity between the new health ICT PSS and its intended operating environment has emerged to be an important contextual factor that may impact the decision of stakeholder engagement in the early stage development process. Along with the proposition of a four-level framework to guide stakeholder identification for new PSS development, three stakeholder engagement propositions that are based on the degree of connectivity are developed. Analysis has shown that there can be two types of connectivity: data and process. Moreover, each connectivity type can be characterized by how much the new PSS is connected with its environment: independent if there is no linkage, linked if it interfaces with, or incorporated if it is embedded into. Furthermore, depending upon whether and to what extent the PSS has data and process connectivity with its intended operating environment, the stakeholder engagement needs in early stage development vary. The propositions presented in this paper provide important directions for future work exploring PSS characterization and stakeholder engagement decision in early stage new PSS development in the healthcare industry. © 2013 PICMET.

Simulating early adoption of alternative fuel vehicles for sustainability

We quantify the conditions that might trigger wide spread adoption of alternative fuel vehicles (AFVs) to support energy policy. Empirical review shows that early adopters are heterogeneous motivated by financial benefits, environmental appeal, new technology, and vehicle reliability. A probabilistic Monte Carlo simulation model is used to assess consumer heterogeneity for early and mass market adopters. For early adopters full battery electric vehicles (BEVs) are competitive but unable to surpass diesels or hybrids due to purchase price premium and lack of charging availability. For mass adoption, simulations indicate that if the purchase price premium of a BEV closes to within 20% of an in-class internal combustion engine (ICE) vehicle, combined with a 60% increase in refuelling availability relative to the incumbent system, BEVs become competitive. But this depends on a mass market that values the fuel economy and CO2 reduction benefits associated with BEVs. We also find that the largest influence on early adoption is financial benefit rather than pro-environmental behaviour suggesting that AFVs should be marketed by appealing to economic benefits combined with pro-environmental behaviour to motivate adoption. Monte Carlo simulations combined with scenarios can give insight into diffusion dynamics for other energy demand-side technologies. © 2012 Elsevier Inc.