The Implementation of Service-Oriented Architectures in the German Banking Industry - A Case Study

The concept of Service-oriented Architecture (SOA) is becoming increasingly important not only in research, but also in practice. SOA has emerged as a major topic, especially in regards to the banking industry as it is one of the cutting-edge industries concerning service-orientation. SOA implementation in the German banking industry varies, with some still in the adoption phase and others already in the SOA operations phase. This has specific implications concerning the SOA Readiness as well as the SOA Maturity of German banks. This paper details the research objective, design, and conduction of a case study in the Germany banking industry investigating the SOA Readiness and SOA Maturity of German banks. Different phases such as SOA adoption and SOA operations and the consequences of SOA during Merger & Acquisition (M&A) conduction are analyzed and evaluated. Finally, the preliminary findings are exhibited

Towards a Generic Governance Model for Service Oriented Architectures

Over the past years, Service-oriented Architecture (SOA) Systems have been recognized more and more as a serious alternative to common monolithic systems for Enterprise Architectures (EA). An SOA provides a flexible means of effectively mapping business processes to IT processes. However, large IT systems require consistent leadership – IT Governance. For SOAs, governance faces new challenges. A number of different approaches for SOA Governance Frameworks exist, which differ extensively in scope and capability, as most of them are product-driven and developed by software companies. In this paper, we outline and compare existing SOA Governance approaches and present our approach - a Generic Governance Model for SOA

Spatio-temporal modeling of avalanche frequencies in the French Alps

AbstractAvalanches threaten mountainous regions, and probabilistic long term hazard evaluation is a useful tool for land use planning and the definition of appropriate mitigation measures. This communication focuses on avalanches counts in the French Alps, and investigates their fluctuations in space and time within a Bayesian hierarchical modeling framework.We have at our disposal a 60 year data set covering the whole French Alps. The considered time scale is the winter. The elementary spatial scale is the township. It is small enough to allow information transfer between neighboring paths and large enough to avoid errors in paths localization. Data are standardized with a variable integrating the number of surveyed paths.A hierarchical Poisson-lognormal model appears well-adapted to depict the observation process with such discrete data. The spatial and temporal effects are assumed independent, and they are considered in the latent layer of the model. The temporal trend is modeled with a cubic spline whereas different spatial dependence sub-models are tested. The latter ones work on different types of supports (continuous field and discrete grid), and at different embedded spatial scales. Model inference and predictive sampling are carried out using Markov Chain Monte Carlo simulation methods. The spatial structure explains the larger part of the relative risks. The spatial dependence is visible at the scale of townships, but with a short range. At the larger scale of the massifs, the spatial dependence is weaker.The regional coherence of the results with the number of avalanche releases suggests that we may also search for other spatially structured variables implicated in the magnitude of avalanches that could help transfer information from one path to another

Recent changes in avalanche activity in the French Alps and their links with climatic drivers: an overview

[Departement_IRSTEA]Eaux [TR1_IRSTEA]RIVAGEInternational audienceThis paper synthetizes our ongoing work on relations between natural avalanche activity and climate change in the French Alps and subregions. Firm results mainly concern occurrences, runout altitudes and high return period avalanches on long time scales (averages over “full” winters and winter-spring sub-seasons) since ~1950. Work in progress concerns extrapolation under future climate, shorter time scales (avalanche cycles), and more generally risk assessment under unstationarity. The strength and interest of the approach rely on the exceptional quality/quantity of avalanche records and snow and weather covariates available/used and on the development of specific statistical treatment methods

Surgery for non-Covid-19 patients during the pandemic.

In the early phase of the Covid-19 pandemic, mainly data related to the burden of care required by infected patients were reported. The aim of this study was to illustrate the timeline of actions taken and to measure and analyze their impact on surgical patients. This is a retrospective review of actions to limit Covid-19 spread and their impact on surgical activity in a Swiss tertiary referral center. Data on patient care, human resources and hospital logistics were collected. Impact on surgical activity was measured by comparing 6-week periods before and after the first measures were taken. After the first Swiss Covid-19 case appeared on February 25, progressively restrictive measures were taken over a period of 23 days. Covid-19 positive inpatients increased from 5 to 131, and ICU patients from 2 to 31, between days 10 and 30, respectively, without ever overloading resources. A 43% decrease of elective visceral surgical procedures was observed after Covid-19 (295 vs 165, p<0.01), while the urgent operations (all specialties) decreased by 39% (1476 vs 897, p<0.01). Fifty-two and 38 major oncological surgeries were performed, respectively, representing a 27% decrease (p = 0.316). Outpatient consultations dropped by 59%, from 728 to 296 (p<0.01). While allowing for maximal care of Covid-19 patients during the pandemic, the shift of resources limited the access to elective surgical care, with less impact on cancer care

COOPERATION MECHANISMS FOR MONITORING AGENTS IN SERVICE-ORIENTED ARCHITECTURES

The Service-Oriented Architecture paradigm (SOA), e.g., realized with Web Services technology, enables enterprises to establish cross-organizational, service-based workflows. An important issue is the monitoring of the fulfillment of Service Level Agreements (SLAs) which define the responsibilities between the participants. Recent research has shown that agent technology is a useful approach in this context. Thus, we present ways for agent cooperation on different levels of abstraction. This cooperation aims at monitoring workflows and especially to react to deviations in different scenarios of SLA violations

A Comparison of Self-Organization Mechanisms in Nature and Information Technology

Successful concepts of self-organization found in natural systems can enable enterprise information systems to address their complexity issues. In this paper, we propose an analysis of self-organization approaches found in natural sciences and information technology. Based on common classes both for application areas and mechanisms, these two fields are compared in order to identify successful concepts, which can be used for the adaptation in information systems research. For illustration purposes, we give a brief example for self-organization in the domain of Service-oriented Architectures, i.e., cooperation mechanisms for agents monitoring services

Investigating the turbulent hot gas in X-COP galaxy clusters

Turbulent processes at work in the intracluster medium perturb this environment, displacing gas, and creating local density fluctuations that can be quantified via X-ray surface brightness fluctuation analyses. Improved knowledge of these phenomena would allow for a better determination of the mass of galaxy clusters, as well as a better understanding of their dynamic assembly. In this work, we aim to set constraints on the structure of turbulence using X-ray surface brightness fluctuations. We seek to consider the stochastic nature of this observable and to constrain the structure of the underlying power spectrum. We propose a new Bayesian approach, relying on simulation-based inference to account for the whole error budget. We used the X-COP cluster sample to individually constrain the power spectrum in four regions and within $R_{500}$. We spread the analysis on the 12 systems to alleviate the sample variance. We then interpreted the density fluctuations as the result of either gas clumping or turbulence. For each cluster considered individually, the normalisation of density fluctuations correlates positively with the Zernike moment and centroid shift, but negatively with the concentration and the Gini coefficient. The spectral index within $R_{500}$ and evaluated over all clusters is consistent with a Kolmogorov cascade. The normalisation of density fluctuations, when interpreted in terms of clumping, is consistent within $0.5 R_{500}$ with the literature results and numerical simulations; however, it is higher between 0.5 and $1 R_{500}$. Conversely, when interpreted on the basis of turbulence, we deduce a non-thermal pressure profile that is lower than the predictions of the simulations within 0.5 $R_{500}$, but still in agreement in the outer regions. We explain these results by the presence of central structural residues that are remnants of the dynamic assembly of the clusters.Comment: Accepted for publication in A&A. Abstract slightly abridged for arXi

Using spatial and spatial-extreme statistics to characterize snow avalanche cycles

In December 2008, an intense avalanche cycle occurred in the eastern part of the southern French Alps. Using this case study, this paper illustrates how spatial statistics can be used to analyse such abnormal temporal clusters of snow avalanches. Spatial regression methods are used to quantify aggregation and gradients and highlight the three day snowfall as the main explanatory factor. A max-stable model is developed to evaluate the snowfall return period, so as to compare the studied cycle with previous ones and with empirical return periods for avalanche counts. (C) 2010 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of Spatial Statistics 201