Multi-Sensor Context-Awareness in Mobile Devices and Smart Artefacts

The use of context in mobile devices is receiving increasing attention in mobile and ubiquitous computing research. In this article we consider how to augment mobile devices with awareness of their environment and situation as context. Most work to date has been based on integration of generic context sensors, in particular for location and visual context. We propose a different approach based on integration of multiple diverse sensors for awareness of situational context that can not be inferred from location, and targeted at mobile device platforms that typically do not permit processing of visual context. We have investigated multi-sensor context-awareness in a series of projects, and report experience from development of a number of device prototypes. These include development of an awareness module for augmentation of a mobile phone, of the Mediacup exemplifying context-enabled everyday artifacts, and of the Smart-Its platform for aware mobile devices. The prototypes have been explored in various applications to validate the multi-sensor approach to awareness, and to develop new perspectives of how embedded context-awareness can be applied in mobile and ubiquitous computing

Quantitative Photoacoustic Imaging in the Acoustic Regime using SPIM

While in standard photoacoustic imaging the propagation of sound waves is modeled by the standard wave equation, our approach is based on a generalized wave equation with variable sound speed and material density, respectively. In this paper we present an approach for photoacoustic imaging, which in addition to recovering of the absorption density parameter, the imaging parameter of standard photoacoustics, also allows to reconstruct the spatially varying sound speed and density, respectively, of the medium. We provide analytical reconstruction formulas for all three parameters based in a linearized model based on single plane illumination microscopy (SPIM) techniques

On Spectral Deformations and Singular Weyl Functions for One-Dimensional Dirac Operators

We investigate the connection between singular Weyl-Titchmarsh-Kodaira theory and the double commutation method for one-dimensional Dirac operators. In particular, we compute the singular Weyl function of the commuted operator in terms of the data from the original operator. These results are then applied to radial Dirac operators in order to show that the singular Weyl function of such an operator belongs to a generalized Nevanlinna class $N_{\kappa_0}$ with $\kappa_0=\lfloor|\kappa| + \frac{1}{2}\rfloor$, where $\kappa\in \mathbb{R}$ is the corresponding angular momentum.Comment: 13 page

Developing User Interfaces for Wearable Computers: Don't Stop to Point and Click

Typical usage scenarios for wearable computers are support of users doing a certain task, e.g. aircraft repair or military applications. If the user is moving while using the wearable some restriction for the user interface apply. In this paper we present some of these restrictions and suggest a wearable user interface taking these findings into account. 1 Introduction The term "Wearable Computer" is used for a wide range of personal technologies, such as watches and mobile phones with enhance

Histamine release after intravenous application of short-acting hypnotics. A comparison of etomidate, Althesin (CT1341) and propanidid

The subject of histamine release was investigated in 16 volunteers by means of plasma histamine determination after the administration of etornidate, Althesin, propanidid, and Cremophor EL. Althesin and propanidid caused release of histamine in various degrees of frequency. Blood pressure changes were rather pronounced with both anaesthetic agents; tachycardia reached its maximum in the first and second minute, which seems to be an argument against histamine release as the underlying cause of this reaction. Histamine was, indeed, only released to such an extent (with the exception of one borderline case) that no clinical symptoms other than secretion of gastric juice and erythema were to be expected. After the application of etomidate and Cremophor EL an increase in plasma histamine was not detectable. Changes in the differential blood picture in terms of a decrease in basophils only occurred after Althesin and propanidid; not, however, after etomidate and Cremophor EL. Etomidate is, therefore, the first hypnotic drug for intravenous application which is unlikely to cause chemical histamine release

An adaptive protocol for distributed beamforming

We study distributed adaptive beamforming in networks of wireless nodes. In particular, we observe that for the synchronisation of carrier phases, distinct algorithmic configurations are optimal in various environmental settings and propose a protocol that utilises organic computing principles to find optimum parameters. Furthermore, we study the impact of different modulation schemes on the bit error rate of a signal sequence transmitted collaboratively by distributed devices via adaptive beamforming

A miniaturized display network for situated glyphs

We demonstrate a novel approach for building situated information systems using wirelessly connected miniaturized displays. These displays are spatially distributed in a physical work environment and present situated glyphs - human-readable abstract graphical signs - to provide activity centric notification and feedback. The demo will showcase how such miniaturized display networks can be used in dynamic workplaces, e.g., a hospital to support complex activities

Towards a lightweight mobile semantic-based approach for enhancing interaction with smart objects

This work describes a semantic extension for a user-smart object interaction model based on the ECA paradigm (Event-Condition-Action). In this approach, smart objects publish their sensing (event) and action capabilities in the cloud and mobile devices are prepared to retrieve them and act as mediators to configure personalized behaviours for the objects. In this paper, the information handled by this interaction system has been shaped according several semantic models that, together with the integration of an embedded ontological and rule-based reasoner, are exploited in order to (i) automatically detect incompatible ECA rules configurations and to (ii) support complex ECA rules definitions and execution. This semantic extension may significantly improve the management of smart spaces populated with numerous smart objects from mobile personal devices, as it facilitates the configuration of coherent ECA rules

Forecasting household packaging waste generation : a case study

Nowadays, house packaging waste (HPW) materials acquired a great deal of importance, due to environmental and economic reasons, and therefore waste collection companies place thousands of collection points (ecopontos) for people to deposit their HPW. In order to optimize HPW collection process, accurate forecasts of the waste generation rates are needed. Our objective is to develop forecasting models to predict the number of collections per year required for each ecoponto by evaluating the relevance of ten proposed explanatory factors for HPW generation. We developed models based on two approaches: multiple linear regression and artificial neural networks (ANN).The results obtained show that the best ANN model, which achieved an R 2 of 0.672 and MAD of 9.1, slightly outperforms the best regression model (R 2 of 0.636, MAD of 10.44). The most important factors to estimate HPW generation rates are related to ecoponto characteristics and to the population and economic activities around each ecoponto location.Fundação para a Ciência e a Tecnologia (FCT

Household packaging waste management

Household packaging waste (HPW) has an important environmental impact and economic relevance. Thus there are networks of collection points (named “ecopontos” in Portugal) where HPW may be deposited for collection by waste management companies. In order to optimize HPW logistics, accurate estimates of the waste generation rates are needed to calculate the number of collections required for each ecoponto in a given period of time. The most important factors to estimate HPW generation rates are linked to the characteristics of the population and the social and economic activities around each ecoponto location. We developed multiple linear regression models and artificial neural networks models to forecast the number of collections per year required for each location. For operational short term planning purposes, these forecasts need to be adjusted for seasonality in order to determine the required number of collections for the relevant planning period. In this paper we describe the methodology used to obtain these forecasts.This research has been partially supported by COMPETE: POCI-01-0145-FEDER007043 and FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2013.info:eu-repo/semantics/publishedVersio