Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse

Self-localizing Smart Cameras and Their Applications

As the prices of cameras and computing elements continue to fall, it has become increasingly attractive to consider the deployment of smart camera networks. These networks would be composed of small, networked computers equipped with inexpensive image sensors. Such networks could be employed in a wide range of applications including surveillance, robotics and 3D scene reconstruction. One critical problem that must be addressed before such systems can be deployed effectively is the issue of localization. That is, in order to take full advantage of the images gathered from multiple vantage points it is helpful to know how the cameras in the scene are positioned and oriented with respect to each other. To address the localization problem we have proposed a novel approach to localizing networks of embedded cameras and sensors. In this scheme the cameras and the nodes are equipped with controllable light sources (either visible or infrared) which are used for signaling. Each camera node can then automatically determine the bearing to all the nodes that are visible from its vantage point. By fusing these measurements with the measurements obtained from onboard accelerometers, the camera nodes are able to determine the relative positions and orientations of other nodes in the network. This localization technology can serve as a basic capability on which higher level applications can be built. The method could be used to automatically survey the locations of sensors of interest, to implement distributed surveillance systems or to analyze the structure of a scene based on the images obtained from multiple registered vantage points. It also provides a mechanism for integrating the imagery obtained from the cameras with the measurements obtained from distributed sensors. We have successfully used our custom made self localizing smart camera networks to implement a novel decentralized target tracking algorithm, create an ad-hoc range finder and localize the components of a self assembling modular robot

Oceanic nitrous oxide distribution and production a stable isotopic approach

Nitrous oxide (N2O) is a biogenic trace gas that has a significant role in global climate change, stratospheric chemistry and in the ocean nitrogen cycle. Its concentration in the ambient air has increased to the current value of 330 ppbv from 275 ppbv (pre-industrial period). The oceans are thought to account for 25-30 % of global N2O emissions. However, the biogeochemical pathways resulting in its formation are not well known. Two microbial pathways, nitrification and denitrification, dominate N2O production with their N2O source product varying with oxygen availability. There is a paucity of N2O data for many oceanic regions, and hence the global budget of N2O is not fully closed. This thesis describes the N2O distribution and its changes with AOU and nutrients along the selected regions in the Southwest Pacific Ocean (SWP) and Northeastern Arabian Sea (NEAS). The comparison of the oxygen minimum zones (OMZs) in NEAS with minimum oxygen concentrations of > 10 μM and the SWP Ocean with minimum oxygen concentrations > 130 μM reveals significant differences in the N2O cycling of both the regions, which is reflected in N2O saturations, dual isotope ratios and isotopomers. At coastal Otago Continental Shelf, N2O distribution was the highest during spring; [N2O], and saturations varied with MSTW > Neritic > SASW. In late autumn, an inverse trend in the distribution of N2O was observed. At the surface, saturations varied between 110 % - 130 % in spring, and it decreased below 100 % during autumn. The results indicate that the Otago coastal region is a source of atmospheric N2O. At the SWP open ocean stations, the minimum [N2O] was always found in the surface layer, with average N2O saturation values of 101 ± 1 % (winter), and 103 ± 1 % (spring) in the STSW, and 102.5 ± 0.5 % in the SASW. These values are similar to the global oceanic mean values (103.5%), derived by Bange et al. (2008). At the NAES, surface mixed layers were poorly oxygenated (20 – 120 µM) relative to the SWP, with a strong oxygen minimum zone (OMZ) present below the mixed layer (25 - 1000 m). The N2O water column distribution showed a single peak structure, with only one broad maximum at mid-depths. The surface saturations are 2 - 4 times higher than the SWP saturations at NAES. N2O sea to air (Fs-a) fluxes indicates that the SWP and NEAS is a source of N2O to the atmosphere, though the extent of the fluxes varies regionally and seasonally. In SWP, below the surface mixed layer [N2O] varied with depth. In the upper thermocline [DO] decreased below that of the surface water whereas [N2O] increased. Beneath the upper thermocline [N2O] in the AAIW increased coincident with an increase in [DO] except at the subantarctic SWP. The maximum [N2O] was found in the CPDW where DO was the minimum. At NEAS N2O saturation were 220 - 630 % in intermediate water (ICW) and 330-390 % in AAIW. A [DO] vs [N2O] inverse relationship and ∆N2O vs AOU positive correlation observed in the SWP as evidence for nitrification as the major formation pathway of N2O. Positive correlations between ∆N2O and nitrate (NO3-) provides further evidence for the nitrification process being the primary source of N2O. For the NAES, ∆N2O vs AOU and ∆N2O vs nitrate suggests formation primarily via nitrification. Stable isotopes and isotopomers of N2O provided more insight into the N2O formation pathways. The depletions in δ 15Nbulk and δ18O in the SWP surface mixed layer, minima in the subsurface, and enrichment at the bottom suggest nitrification, except in the subsurface 200-500 m. The NAES dual isotopes reflect the major role of nitrification especially in the surface and in the OMZ. These different oxygen isotope results suggest oxidation of hydroxylamine (NH2OH) followed by nitric oxide (NO) oxidation (during nitrification) at all depths in the SWP (except at 200-500 m) and NEAS. To examine the formation processes, Δ18O was also determined (δ18ON2O - δ18O of DO). Δ18O was almost constant at all depths for SWP waters, while it showed a minimum (roughly 9 ‰ lower than waters above and below) at 200-500 m except in subantarctic SWP waters. This observation proves the additional contribution to N2O source from nitrifier denitrification at 200-500m in the SWP (except in the subantarctic) and throughout the OMZ in the NEAS. The intramolecular distribution of isotopomers of 15N in N2O and S.P were also supportive of these findings.15N isotope labelled incubation experiments using 15NH4Cl and K15NO3 for the selected stations of Otago Continental Shelf transect also indicated that ammonium oxidation is the major process responsible for the production of N2O

Model-Based Engineering of Collaborative Embedded Systems

This Open Access book presents the results of the "Collaborative Embedded Systems" (CrESt) project, aimed at adapting and complementing the methodology underlying modeling techniques developed to cope with the challenges of the dynamic structures of collaborative embedded systems (CESs) based on the SPES development methodology. In order to manage the high complexity of the individual systems and the dynamically formed interaction structures at runtime, advanced and powerful development methods are required that extend the current state of the art in the development of embedded systems and cyber-physical systems. The methodological contributions of the project support the effective and efficient development of CESs in dynamic and uncertain contexts, with special emphasis on the reliability and variability of individual systems and the creation of networks of such systems at runtime. The project was funded by the German Federal Ministry of Education and Research (BMBF), and the case studies are therefore selected from areas that are highly relevant for Germany’s economy (automotive, industrial production, power generation, and robotics). It also supports the digitalization of complex and transformable industrial plants in the context of the German government's "Industry 4.0" initiative, and the project results provide a solid foundation for implementing the German government's high-tech strategy "Innovations for Germany" in the coming years

Information geometry

This Special Issue of the journal Entropy, titled “Information Geometry I”, contains a collection of 17 papers concerning the foundations and applications of information geometry. Based on a geometrical interpretation of probability, information geometry has become a rich mathematical field employing the methods of differential geometry. It has numerous applications to data science, physics, and neuroscience. Presenting original research, yet written in an accessible, tutorial style, this collection of papers will be useful for scientists who are new to the field, while providing an excellent reference for the more experienced researcher. Several papers are written by authorities in the field, and topics cover the foundations of information geometry, as well as applications to statistics, Bayesian inference, machine learning, complex systems, physics, and neuroscience