Home Energy Consumption Feedback: A User Survey

Buildings account for a relevant fraction of the energy consumed by a country, up to 20-40% of the yearly energy consumption. If only electricity is considered, the fraction is even bigger, reaching around 73% of the total electricity consumption, equally divided into residential and commercial dwellings. Building and Home Automation have a potential to profoundly impact current and future buildings' energy efficiency by informing users about their current consumption patterns, by suggesting more efficient behaviors, and by pro-actively changing/modifying user actions for reducing the associated energy wastes. In this paper we investigate the capability of an automated home to automatically, and timely, inform users about energy consumption, by harvesting opinions of residential inhabitants on energy feedback interfaces. We report here the results of an on-line survey, involving nearly a thousand participants, about feedback mechanisms suggested by the research community, with the goal of understanding what feedback is felt by home inhabitants easier to understand, more likely to be used, and more effective in promoting behavior changes. Contextually, we also collect and distill users' attitude towards in-home energy displays and their preferred locations, gathering useful insights on user-driven design of more effective in-home energy display

Aerospace Medicine and Biology: A continuing bibliography with indexes supplement 201

This bibliography lists 191 reports, articles, and other documents introduced into the NASA scientific and technical information system in December 1979

Aerospace medicine and biology: A continuing bibliography with indexes (supplement 406)

This bibliography lists 346 reports, articles and other documents introduced into the NASA Scientific and Technical Information System during Oct. 1995. Subject coverage includes: aerospace medicine and physiology, life support systems and man/system technology, protective clothing, exobiology and extraterrestrial life, planetary biology, and flight crew behavior and performance

Hybrid data-based modelling in oncology: successes, challenges and hopes

International audienceIn this review we make the statement that hybrid models in oncology are required as a mean for enhanced data integration. In the context of systems oncology, experimental and clinical data need to be at the heart of the models developments from conception to validation to ensure a relevant use of the models in the clinical context. The main applications pursued are to improve diagnosis and to optimize therapies.We first present the Successes achieved thanks to hybrid modelling approaches to advance knowledge, treatments or drug discovery. Then we present the Challenges than need to be addressed to allow for a better integration of the model parts and of the data into the models. And Finally, the Hopes with a focus towards making personalised medicine a reality. Mathematics Subject Classification. 35Q92, 68U20, 68T05, 92-08, 92B05

A Geodesign Decision Support Environment for Integrating Management of Resource Flows in Spatial Planning

Improving waste and resource management entails working on interrelations between different material flows, territories and groups of actors. This calls for new decision support tools for translating the complex information on flows into accessible knowledge usable by stakeholders in the spatial planning process. This article describes an open source tool based on the geodesign approach, which links the co-creation of design proposals together with stakeholders, impact simulations informed by geographic contexts, systems thinking, and digital technology—the Geodesign Decision Support Environment. Though already used for strategic spatial planning, the potential of geodesign for waste management and recycling is yet to be explored. This article draws on empirical evidence from the pioneering application of the tool to promote spatially explicit circular economy strategies in the Amsterdam Metropolitan Area

Who Said That? Towards a Machine-Prediction-Based Approach to Tursiops Truncatus Whistle Localization and Attribution in a Reverberant Dolphinarium

Dolphin communication research is an active period of growth. Many researchers expect to find significant communicative capacity in dolphins given their known sociality and large and complex brains. Moreover, given dolphins’ known acoustic sensitivity, serving their well-studied echolocation ability, some researchers have speculated that dolphin communication is mediated in large part by a sophisticated “vocal” language. However, evidence supporting this belief is scarce. Among most dolphin species, a particular tonal class of call, termed the whistle, has been identified as socially important. In particular, for the common bottlenose dolphin, Tursiops truncatus – arguably the focal species of most dolphin cognitive and communication research – research has fixated on “signature whistles,” individuallydistinctive whistles that seem to convey an individual’s identity to conspecifics, can be mimicked, and can be modulated under certain circumstances in ways that may or may not be communicative. Apart from signature whistles, most studies of dolphin calls concern group-based repertoires of whistles and other, pulse-form call types. However, studies of individual repertoires of non-signature whistles, and the phenomenon of combined signature and non-signature vocal exchanges among dolphins, are conspicuously rare in the literature, tending to be limited by either extreme subject confinement or sparse attributions of vocalizer identity. Nevertheless, such studies constitute a logical prerequisite to an understanding of the communicative potential of whistles. This absence can be explained by a methodological limitation in the way in which dolphin sounds are recorded. In particular, no established method exists for recording the whistles of an entire social group of dolphins so as to reliably attribute them to their vocalizers. This thesis proposes a dolphinarium-based system for achieving audio recording with whistle attribution, as well as visual behavioral tracking. Towards achieving the proposed system, I present foundational work involving the installation of permanent hydrophone arrays and cameras in a dolphinarium that enforces strict animal safety regulations. Attributing tonal sounds via the process of sound localization – estimation of a sound’s point of origin based on the physical properties of its propagation – in a highly reverberant environment is a notoriously difficult problem, resistant to many conventional signal processing techniques. This thesis will provide evidence of this difficulty, and also a demonstration of a highly e↵ective machine-learning-based solution to the problem. This thesis also provides miscellaneous hardware and the pieces of a computational pipeline towards completion of the full proposed, automated system. Once completed, the proposed system will provide an enormous data stream that will lend itself to large-scale studies of individual repertoires of non-signature whistles and combined signature and non-signature vocal exchanges among an invariant group of socializing dolphins, representing a unique and necessary achievement in dolphin communication research