Performance and reliability prediction for evolving service-oriented software systems

During software system evolution, software architects intuitively trade off the different architecture alternatives for their extra-functional properties, such as performance, maintainability, reliability, security, and usability. Researchers have proposed numerous model-driven prediction methods based on queuing networks or Petri nets, which claim to be more cost-effective and less error-prone than current practice. Practitioners are reluctant to apply these methods because of the unknown prediction accuracy and work effort. We have applied a novel model-driven prediction method called Q-ImPrESS on a large-scale process control system from ABB consisting of several million lines of code. This paper reports on the achieved performance prediction accuracy and reliability prediction sensitivity analyses as well as the effort in person hours for achieving these results.     

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.     

Diterpene structure elucidation from 13cnmr spectra with inductive logic programming

We present a novel application ofInductive Logic Programming (ILP) to the problem of diterpene structure elucidation from 13 CNMR spectra. Diterpenes are organic compounds oflow molecular weight with a skeleton of 20 carbon atoms. They are of significant chemical and commercial interest because oftheir use as lead compounds in the search for new pharmaceutical effectors. The interpretation of diterpene 13 CNMR spectra normally requires specialists with detailed spectroscopic knowledge and substantial experience in natural products chemistry, specifically knowledge on peak patterns and chemical structures. Given a database ofpeak patterns for diterpenes with known structure, we apply several ILP approaches to discover correlations between peak patterns and chemical structure. The approaches used include first - order inductive learning, relational instance based learning, induction oflogical decision trees, and inductive constraint logic. Performance close to that of domain experts is achieved, which suffices for practical use.     

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.     

Accelerated Visualization of Dynamic Molecular Surfaces

Molecular surfaces play an important role in studying the interactions between molecules. Visualizing the dynamic behavior of molecules is particularly interesting to gain insights into a molecular system. Only recently it has become possible to interactively visualize dynamic molecular surfaces using ray casting techniques. In this paper, we show how to further accelerate the construction and the rendering of the solvent excluded surface (SES) and the molecular skin surface (MSS). We propose several improvements to reduce the update times for displaying these molecular surfaces. First, we adopt a parallel approximate Voronoi diagram algorithm to compute the MSS. This accelerates the MSS computation by more than one order of magnitude on a single core. Second, we demonstrate that the contour‐buildup algorithm is ideally suited for computing the SES due to its inherently parallel structure. For both parallel algorithms, we observe good scalability up to 8 cores and, thus, obtain interactive frame rates for molecular dynamics trajectories of up to twenty thousand atoms for the SES and up to a few thousand atoms for the MSS. Third, we reduce the rendering time for the SES using tight‐fitting bounding quadrangles as rasterization primitives. These primitives also accelerate the rendering of the MSS. With these improvements, the interactive visualization of the MSS of dynamic trajectories of a few thousand atoms becomes for the first time possible. Nevertheless, the SES remains a few times faster than the MSS.     

Interactive High‐Quality Visualization of Higher‐Order Finite Elements

Higher‐order finite element methods have emerged as an important discretization scheme for simulation. They are increasingly used in contemporary numerical solvers, generating a new class of data that must be analyzed by scientists and engineers. Currently available visualization tools for this type of data are either batch oriented or limited to certain cell types and polynomial degrees. Other approaches approximate higher‐order data by resampling resulting in trade‐offs in interactivity and quality. To overcome these limitations, we have developed a distributed visualization system which allows for interactive exploration of non‐conforming unstructured grids, resulting from space‐time discontinuous Galerkin simulations, in which each cell has its own higher‐order polynomial solution. Our system employs GPU‐based raycasting for direct volume rendering of complex grids which feature non‐convex, curvilinear cells with varying polynomial degree. Frequency‐based adaptive sampling accounts for the high variations along rays. For distribution across a GPU cluster, the initial object‐space partitioning is determined by cell characteristics like the polynomial degree and is adapted at runtime by a load balancing mechanism. The performance and utility of our system is evaluated for different aeroacoustic simulations involving the propagation of shock fronts.     

Visuelle Analyse medizinischer Daten

In der Medizin werden gro?e Mengen an Daten generiert, die sich auf diagnostische Prozeduren, Behandlungsentscheidungen und Ergebnisse der Behandlung beziehen. Medizinische Bilddaten, z. B. Computertomografie (CT) und Kernspintomografiedaten (MRT), werden h?ufig akquiriert. Diese Daten müssen effizient analysiert werden, um klinische Entscheidungen ad?quat zu unterstützen. Insbesondere müssen Bildanalysetechniken, wie die Segmentierung und Quantifizierung anatomischer Strukturen und die visuelle Exploration der Daten, integriert werden. Neben den Anforderungen der individuellen Behandlung ergeben sich weitere Herausforderungen für die Datenauswertung aus den Bedürfnissen der klinischen Forschung, der ?ffentlichen Gesundheitsvorsorge und der Epidemiologie. Die Rolle des Benutzers ist hier die eines Forschers, der Daten untersucht und dabei z. B. potenzielle Korrelationen zwischen Risikofaktoren und der Entstehung von Erkrankungen analysiert. Die visuelle Exploration, bei der oft mehrere koordinierte Ansichten genutzt werden, und statistische Analysen müssen dazu geeignet integriert werden. Oft sind dabei die r?umliche (geografische) Verteilung der Patienten und die zeitliche Entwicklung von Erkrankungsf?llen wesentlich. Daher müssen die medizinischen Daten in ihrem r?umlichen und zeitlichen Bezug repr?sentiert werden, sodass eine enge Verbindung zwischen geografischen Informationssystemen und der Datenvisualisierung entsteht.     

Interfacial instability of liquid films coating the walls of a parallel-plate channel and sheared by a gas flow

The stability and coupling of liquid films coating the walls of a parallel-plate channel and sheared by a pressure-driven gas flow along the channel center plane is studied. The films are susceptible to a long-wavelength instability. For sufficiently low Reynolds numbers and thick gas layers, the dynamic behavior is found to be described by two coupled nonlinear partial differential equations. A linear stability analysis is conducted under the condition that the material properties and the initial undisturbed liquid-film thicknesses are equal. The linear analysis is utilized to determine whether the interfaces are predominantly destabilized by the variations of the shear stress or by the pressure gradient acting upon them. The analysis of the weakly nonlinear equations performed for this case shows that instabilities corresponding to a vanishing Reynolds number are absent from the system. Moreover, for this configuration, the patterns emerging along the two interfaces are found to be identical in the long-time limit, implying that the films are fully synchronized. A different setup, where the liquid films have identical material properties but their undisturbed thicknesses differ, is studied numerically. The results show that, even for this configuration, the interfacial waves remain phase-synchronized and closely correlated for an extended period of time. These findings are particularly relevant for gaseous flow through narrow ducts with liquid-coated walls.     

Detecting and preventing replay attacks in industrial automation networks operated with profinet IO

Modern industrial facilities consist of controllers, actuators and sensors that are connected via traditional IT equipment. The ongoing integration of these systems into the communication network yields to new threats and attack possibilities. In industrial networks, often distinct communication protocols like Profinet IO (PNIO) are used. These protocols are often not supported by typical network security tools. In this work, we present two attack techniques that allow to take over the control of a PNIO device, enabling an attacker to replay previously recorded traffic. We model attack detection rules and propose an intrusion detection system (IDS) for industrial networks which is capable of detecting those replay attacks by correlating alerts from traditional IT IDS with specific PNIO alarms. As an additional effort, we introduce defense in depth mechanisms in order to prevent those attacks from taking effect in the physical world. Thereafter, we evaluate our IDS in a physical demonstrator and compare it with another IDS dedicated to securing PNIO networks. In a conceptual design, we show how network segmentation with flow control allows for preventing some, but not all of the attacks.