Supporting casual interactions between board games on public tabletop displays and mobile devices

As more interactive surfaces enter public life, casual interactions from passersby are bound to increase. Most of these users can be expected to carry a mobile phone or PDA, which nowadays offers significant computing capabilities of its own. This offers new possibilities for interaction between these users’ private displays and large public ones. In this paper, we present a system that supports such casual interactions. We first explore a method to track mobile phones that are placed on a horizontal interactive surface by examining the shadows which are cast on the surface. This approach detects the presence of a mobile device, as opposed to any other opaque object, through the signal strength emitted by the built-in Bluetooth transceiver without requiring any modifications to the devices’ software or hardware. We then go on to investigate interaction between a Sudoku game running in parallel on the public display and on mobile devices carried by passing users. Mobile users can join a running game by placing their devices on a designated area. The only requirement is that the device is in discoverable Bluetooth mode. After a specific device has been recognized, a client software is sent to the device which then enables the user to interact with the running game. Finally, we explore the results of a study which we conducted to determine the effectiveness and intrusiveness of interactions between users on the tabletop and users with mobile devices.     

The hierarchical Tobit model: A case study in Bayesian computing

In this paper we discuss the potentials of a new Bayesian inference tool, called the Gibbs sampler, for the analysis of the censored regression or Tobit model. Tobit models have a wide range of applications in empirical sciences, like econometrics and biometrics. The estimation results of the simple Tobit model will be compared to a hierarchical Tobit model, and the Gibbs sampling approach to the related classical algorithm of expectation-maximisation (EM). The underlying botanical example of this paper is concerned with the censoring mechanism in plant reproduction and proposes the Bayesian Tobit model for the growth relationship between the reproductive part and the rest of the plant.     

Effect of Berezinskii-Kosterlitz-Thouless vortex fluctuations on the nuclear spin relaxation rate

In this work we examine the influence of the diffusive motion of vortices in highly anisotropic high-T_c superconductors near the Berezinskii-Kosterlitz-Thouless (BKT) transition temperature T _bkt on the spin-lattice relaxation rate T ₁ ^–1 .We find a jump in T ₁ ^–1 at the temperature T _bkt .     

Smart Workplaces for older adults: coping ‘ethically’ with technology pervasiveness

Universal Access in the Information Society - Pervasive technologies such as Artificial Intelligence, Virtual Reality and the Internet of Things, despite their great potential for improved...     

Online Acoustic System Identification Exploiting Kalman Filtering and an Adaptive Impulse Response Subspace Model

We introduce a novel algorithm for online estimation of Acoustic Impulse Responses (AIRs) which allows for fast convergence by exploiting prior knowledge about the fundamental structure of AIRs. The proposed method assumes that the variability of AIRs of an acoustic scene is confined to a low-dimensional manifold which is embedded in a high-dimensional space of possible AIR estimates. We discuss various approaches which exploit a training data set of AIRs, e.g., high-accuracy AIR estimates from the acoustic scene, to learn a local affine subspace approximation of the AIR manifold. The model is motivated by the idea of describing the generally nonlinear AIR manifold locally by tangential hyperplanes and its validity is verified for simulated data. Subsequently, we describe how the manifold assumption can be used to enhance online AIR estimates by projecting them onto an adaptively estimated subspace. Motivated by the assumption of manifolds being locally Euclidean, the parameters determining the adaptive subspace are learned from the nearest neighbor AIR training samples to the current AIR estimate. To assess the proximity of training data AIRs to the current AIR estimate, we introduce a probabilistic extension of the Euclidean distance which improves the performance for applications with non-white excitation signals. Furthermore, we describe how model imperfections can be tackled by a soft projection of the AIR estimates. The proposed algorithm exhibits significantly faster convergence properties in comparison to a high-performance state-of-the-art algorithm. Furthermore, we show an improved steady-state performance for speech-excited system identification scenarios suffering from high-level interfering noise and nonunique solutions.

     

Modelling and condition-based control of a flexible and hybrid disassembly system with manual and autonomous workstations using reinforcement learning

Journal of Intelligent Manufacturing - Remanufacturing includes disassembly and reassembly of used products to save natural resources and reduce emissions. While assembly is widely understood in...     

Steady-state O<Subscript>2</Subscript> and CO<Subscript>2</Subscript> diffusion in carbonated mortars produced with blended cements

The diffusion coefficient \(D_{{{\text{O}}_{2} }}\), the porosity and the pore structure of mortars produced with a Portland cement and a range of blended cements containing limestone powder, microsilica, portlandite or slag were measured in the non-carbonated and the carbonated state. Additionally, the setup for measuring O₂ diffusion was adapted to measure also the CO₂ diffusion of the carbonated mortars. The diffusion coefficient \(D_{{{\text{O}}_{2} }}\) and the total porosity were increased in the mortars containing microsilica and slag, while they were decreased in the other mortars due to carbonation. Invariably, the pore structure became coarser in all samples. The relationship between diffusion coefficients \(D_{{{\text{O}}_{2} }}\) and \(D_{{{\text{CO}}_{2} }}\) in the carbonated mortars was always linear, with \(D_{{{\text{O}}_{2} }}\) systematically higher by factor of 1.37. As this factor broadly agrees with what was found in the scant literature about CO₂ diffusion, it could be used for estimating \(D_{{{\text{CO}}_{2} }}\) of carbonated mortar and concrete based on measurements of O₂ diffusion.     

Trap State Effects in PbS Colloidal Quantum Dot Exciton Kinetics Using Photocarrier Radiometry Intensity and Temperature Measurements

Colloidal quantum dots (CQDs) have attracted significant interest for applications in electronic and optoelectronic devices such as photodetectors, light-emitting diodes, and solar cells. However, a poor understanding of charge transport in these nanocrystalline films hinders their practical applications. The photocarrier radiometry (PCR) technique, a frequency-domain photoluminescence method spectrally gated for monitoring radiative recombination photon emissions while excluding thermal infrared photons due to non-radiative recombination, has been applied to PbS CQD thin films for the analysis of charge transport properties. Linear excitation intensity responses of PCR signals were found in the reported experimental conditions. The type and influence of trap states in the coupled PbS CQD thin film were analyzed with PCR temperature- and time-dependent results.