DuD Report

DuD Report

DuD Report     

Datenschutz-Schutzziele — revisited

Zusammenfassung  Die Arbeit mit Schutzzielen hat sich grunds?tzlich bew?hrt. Sie sind so formuliert, dass sie die Anforderungen an technische und organisatorische Systeme sowohl abstrakt überblickbar als auch in Form von Ma?nahmen hinreichend konkret fa?bar machen. Der Beitrag empfiehlt, sie in Datenschutzgesetze und Vertr?ge aufzunehmen, als Leitlinien für den Entwurf und Betrieb von IT-Infrastrukturen heranzuziehen und in Mechanismen transformiert als WebService-Policies auszudrücken — und unterbreitet einen Strukturierungsvorschlag.     

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.     

Dynamic adhesive force measurements under vertical and horizontal motions of interacting rough surfaces

An instrument to measure dynamic adhesive forces between interacting rough surfaces has been developed. It consists of four parts, namely, main instrument body, vertical positioning system with both micrometer and nanometer positioning accuracies, horizontal positioning system with nanometer positioning accuracy, and custom-built high-resolution, and high dynamic bandwidth capacitive force transducer. The vertical piezoelectric actuator (PZT) controls the vertical (approaching and retracting) motion of the upper specimen, while the horizontal PZT controls the horizontal (reciprocal) motion of the lower specimen. The force transducer is placed in line with the upper specimen and vertical PZT, and directly measures the adhesive forces with a root-mean-square load resolution of 1.7 microN and a dynamic bandwidth of 1.7 kHz. The newly developed instrument enables reliable measurements of near-contact and contact adhesive forces for microscale devices under different dynamic conditions. Using the developed instrument, dynamic pull-in and pull-off force measurements were performed between an aluminum-titanium-carbide sphere and a 10 nm thick carbon film disk sample. Three different levels of contact force were investigated; where for each contact force level the vertical velocity of the upper sample was varied from 0.074 to 5.922 microms, while the lower sample was stationary. It was found that slower approaching and retracting velocities result in higher pull-in and pull-off forces. The noncontact attractive force was also measured during horizontal movement of the lower sample, and it was found that the periodic movements of the lower disk sample also affect the noncontact surface interactions.     

Proof planning with multiple strategies

Proof planning is a technique for theorem proving which replaces the ultra-efficient but blind search of classical theorem proving systems by an informed knowledge-based planning process that employs mathematical knowledge at a human-oriented level of abstraction. Standard proof planning uses methods as operators and control rules to find an abstract proof plan which can be expanded (using tactics) down to the level of the underlying logic calculus.In this paper, we propose more flexible refinements and a modification of the proof planner with an additional strategic level of control above the previous proof planning control. This strategic control guides the cooperation of the problem solving strategies by meta-reasoning.We present a general framework for proof planning with multiple strategies and describe its implementation in the Multi system. The benefits are illustrated by several large case studies, which significantly push the limits of what can be achieved by a machine today.     

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 .     

Deterministic Polymorphic Engineering of MoTe2 for Photonic and Optoelectronic Applications

Developing selective and coherent polymorphic crystals at the nanoscale offers a novel strategy for designing integrated architectures for photonic and optoelectronic applications such as metasurfaces, optical gratings, photodetectors, and image sensors. Here, a direct optical writing approach is demonstrated to deterministically create polymorphic 2D materials by locally inducing metallic 1T′-MoTe₂ on the semiconducting 2H-MoTe₂ host layer. In the polymorphic-engineered MoTe₂, 2H- and 1T′- crystalline phases exhibit strong optical contrast from near-infrared to telecom-band ranges (1–1.5 µm), due to the change in the band structure and increase in surface roughness. Sevenfold enhancement of third harmonic generation intensity is realized with conversion efficiency (susceptibility) of ≈1.7 × 10⁻⁷ (1.1 × 10⁻¹⁹ m² V⁻²) and ≈1.7 × 10⁻⁸ (0.3 × 10⁻¹⁹ m² V⁻²) for 1T′ and 2H-MoTe₂, respectively at telecom-band ultrafast pump laser. Lastly, based on polymorphic engineering on MoTe₂, a Schottky photodiode with a high photoresponsivity of 90 AW⁻¹ is demonstrated. This study proposes facile polymorphic engineered structures that will greatly benefit realizing integrated photonics and optoelectronic circuits.     

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.