The scientific community has begun using new information and communication technologies to increase the efficiency with which publications are disseminated. The trend is most marked in some areas of physics, where research papers are first circulated in the form of electronic unrefereed preprints through a service known as arXiv. In the first half of this paper, I explain how arXiv works, and describe the conceptual backstage and its growing influence. I will look at the motives behind the developing technologies and focus on the views of promoters and makers of the system. In the second half of the paper, I look at the eventual fate of papers initially circulated with arXiv. While it is argued that preprints are sufficient for the everyday scientific practice, nearly every paper in some specialities finds its way into formally peer-reviewed journals and proceedings. I argue that the continuation of traditional publication practices, in spite of their costs and inefficiencies when compared with arXiv, suggests that formally certified publication still has important roles. Certified publication verifies the relevance of scientific work and establishes professional credentials in the outer rings of the community, whose members are not sufficiently embedded in esoteric networks to make appropriate judgements on the basis of reading papers in isolation, or even through consultation.

The acoustic behavior of ceiling absorbers can be predicted under different surface reaction assumptions: Local and extended reaction. This study aims to experimentally validate acoustic transfer functions near a ceiling absorber in an anechoic chamber based on the two surface reaction models. First, a ceiling absorber with two mounting conditions is modeled by equivalent fluid models, such as Delany-Bazley's, Miki's, and Komatsu's model, in various ways: (1) Local vs extended reaction and (2) plane-wave vs spherical-wave incidence. For a single absorber under anechoic conditions, the acoustic transfer functions for four source-receiver pairs are simulated using a pressure-based image source model, and then compared with measurements. For a rigid backing condition, both the local and extended reaction models agree well with the measurement. For an absorber backed by an air cavity, the extended reaction model agrees better at larger incidence angles at lower frequencies than the local reaction model.

This article is an analytic register of recent European efforts in the making of 'autonomous' robots to address what is imagined as Europe's societal challenges. The paper describes how an emerging techno-epistemic network stretches across industry, science, policy and law to legitimize and enact a robotics innovation agenda. Roadmap is the main metaphor and organizing tool in working across the disciplines and sectors, and in aligning these heterogeneous actors with a machinecentric vision along a path to make way for 'new kinds' of robots. We describe what happens as this industry-dominated project docks in a public-private partnership with pan-European institutions and a legislative initiative on robolaw. Emphasizing the co-production of robotics and European innovation politics, we observe how well-known uncertainties and scholarly debates about machine capabilities and human-machine configurations, are unexpectedly played out in legal scholarship and institutions as a controversy and a significant problem for human-centered legal K. Rommetveit et al. 3frameworks. European robotics are indeed driving an increase in speculative ethics and a new-found weight of possible futures in legislative practice.

Abstract:Understanding home activities is important in social research to study aspects of home life, e.g., energy-related practices and assisted living arrangements. Common approaches to identifying which activities are being carried out in the home rely on self-reporting, either retrospectively (e.g., interviews, questionnaires, and surveys) or at the time of the activity (e.g., time use diaries). The use of digital sensors may provide an alternative means of observing activities in the home. For example, temperature, humidity and light sensors can report on the physical environment where activities occur, while energy monitors can report information on the electrical devices that are used to assist the activities. One may then be able to infer from the sensor data which activities are taking place. However, it is first necessary to calibrate the sensor data by matching it to activities identified from self-reports. The calibration involves identifying the features in the sensor data that correlate best with the self-reported activities. This in turn requires a good measure of the agreement between the activities detected from sensor-generated data and those recorded in self-reported data. To illustrate how this can be done, we conducted a trial in three single-occupancy households from which we collected data from a suite of sensors and from time use diaries completed by the occupants. For sensor-based activity recognition, we demonstrate the application of Hidden Markov Models with features extracted from mean-shift clustering and change points analysis. A correlation-based feature selection is also applied to reduce the computational cost. A method based on Levenshtein distance for measuring the agreement between the activities detected in the sensor data and that reported by the participants is demonstrated. We then discuss how the features derived from sensor data can be used in activity recognition and how they relate to activities recorded in time use diaries.