Biometrie am BBI — Chancen und Randbedingungen

Der Betreiber eines Verkehrsflughafens muss Bereiche, die nicht allgemein zug?nglich sind, gegen unberechtigten Zugang sichern und darf, soweit es sich um sicherheitsempfindliche Bereiche handelt, den Zugang nur berechtigten Personen gestatten. Der Flughafenbetreiber gibt dazu an die Zutrittsberechtigten Ausweise aus, mit denen diese sich beim Betreten des Sicherheitsbereiches authentifizieren müssen. Für den neuen Flughafen Berlin-Brandenburg International BBI wird auf den Ausweisen wegen der stark wachsenden Anzahl der zu überprüfenden Personen als zus?tzliches Authentifizierungselement eine biometrische Referenz gespeichert. Bei der Auswahl des biometrischen Verfahrens sind die besonderen Bedingungen von Verkehrsflugh?fen in Betracht zu ziehen.     

“From microtiter plates to droplets” tools for micro-fluidic droplet processing

Droplet-based microfluidic allows high throughput experimentation in with low volume droplets. Essential fluidic process steps are on the one hand the proper control of the droplet composition and on the other hand the droplet processing, manipulation and storage. Beside integrated fluidic chips, standard PTFE-tubings and fluid connectors can be used in combination with appropriate pumps to realize almost all necessary fluidic processes. The segmented flow technique usually operates with droplets of about 100–500 nL volume. These droplets are embedded in an immiscible fluid and confined by channel walls. For the integration of segmented flow applications in established research workflows—which are usually base on microtiter plates—robotic interface tools for parallel/serial and serial/parallel transfer operations are necessary. Especially dose–response experiments are well suited for the segmented flow technique. We developed different transfer tools including an automated “gradient take-up tool” for the generation of segment sequences with gradually changing composition of the individual droplets. The general working principles are introduced and the fluidic characterizations are given. As exemplary application for a dose–response experiment the inhibitory effect of antibiotic tetracycline on Escherichia coli bacteria cultivated inside nanoliter droplets was investigated.     

Integration of beamforming and uncertainty-of-observation techniques for robust ASR in multi-source environments

This paper presents a new approach for increasing the robustness of multi-channel automatic speech recognition in noisy and reverberant multi-source environments. The proposed method uses uncertainty propagation techniques to dynamically compensate the speech features and the acoustic models for the observation uncertainty determined at the beamforming stage. We present and analyze two methods that allow integrating classical multi-channel signal processing approaches like delay and sum beamformers or Zelinski-type Wiener filters, with uncertainty-of-observation techniques like uncertainty decoding or modified imputation. An analysis of the results on the PASCAL-CHiME task shows that this approach consistently outperforms conventional beamformers with a minimal increase in computational complexity. The use of dynamic compensation based on observation uncertainty also outperforms conventional static adaptation with no need of adaptation data.     

In situ exploration of large dynamic networks

The analysis of large dynamic networks poses a challenge in many fields, ranging from large bot-nets to social networks. As dynamic networks exhibit different characteristics, e.g., being of sparse or dense structure, or having a continuous or discrete time line, a variety of visualization techniques have been specifically designed to handle these different aspects of network structure and time. This wide range of existing techniques is well justified, as rarely a single visualization is suitable to cover the entire visual analysis. Instead, visual representations are often switched in the course of the exploration of dynamic graphs as the focus of analysis shifts between the temporal and the structural aspects of the data. To support such a switching in a seamless and intuitive manner, we introduce the concept of in situ visualization--a novel strategy that tightly integrates existing visualization techniques for dynamic networks. It does so by allowing the user to interactively select in a base visualization a region for which a different visualization technique is then applied and embedded in the selection made. This permits to change the way a locally selected group of data items, such as nodes or time points, are shown--right in the place where they are positioned, thus supporting the user's overall mental map. Using this approach, a user can switch seamlessly between different visual representations to adapt a region of a base visualization to the specifics of the data within it or to the current analysis focus. This paper presents and discusses the in situ visualization strategy and its implications for dynamic graph visualization. Furthermore, it illustrates its usefulness by employing it for the visual exploration of dynamic networks from two different fields: model versioning and wireless mesh networks.     

Generating feature spaces for linear algorithms with regularized sparse kernel slow feature analysis

Without non-linear basis functions many problems can not be solved by linear algorithms. This article proposes a method to automatically construct such basis functions with slow feature analysis (SFA). Non-linear optimization of this unsupervised learning method generates an orthogonal basis on the unknown latent space for a given time series. In contrast to methods like PCA, SFA is thus well suited for techniques that make direct use of the latent space. Real-world time series can be complex, and current SFA algorithms are either not powerful enough or tend to over-fit. We make use of the kernel trick in combination with sparsification to develop a kernelized SFA algorithm which provides a powerful function class for large data sets. Sparsity is achieved by a novel matching pursuit approach that can be applied to other tasks as well. For small data sets, however, the kernel SFA approach leads to over-fitting and numerical instabilities. To enforce a stable solution, we introduce regularization to the SFA objective. We hypothesize that our algorithm generates a feature space that resembles a Fourier basis in the unknown space of latent variables underlying a given real-world time series. We evaluate this hypothesis at the example of a vowel classification task in comparison to sparse kernel PCA. Our results show excellent classification accuracy and demonstrate the superiority of kernel SFA over kernel PCA in encoding latent variables.     

The smart car seat: personalized monitoring of vital signs in automotive applications

Embedded wireless sensors are important components of mobile distributed computing networks, and one of the target applications areas is health care. The preservation of mobility for senior citizens is one of the key issues in maintaining an independent lifestyle. Thus health technologies inside a car can contribute both to safety issues (supervision of driver fitness) as well as healthcare issues by monitoring vitals signs imperceptibly. In this paper, three embedded measurement techniques for non-contact monitoring of vital signals have been investigated. Specifically, capacitive electrocardiogram (cECG) monitoring, mechanical movement analysis (ballistocardiogram, BCG) using piezo-foils and inductive impedance monitoring were examined regarding their potential for integration into car seats. All three sensing techniques omit the need for electroconductive contact to the human body, but require defined mechanical boundary conditions (stable distances or, in the case of BCG, frictional connection). The physical principles of operation, the specific boundary conditions regarding automotive integration and the results during wireless operation in a running car are presented. All three sensors were equipped with local intelligence by incorporating a microcontroller. To eliminate the need for additional cabling, a wireless Bluetooth communication module was added and used to transmit data to a measurement PC. Finally, preliminary results obtained during test drives on German city roads and highways are discussed.