The impact of perceived risk on the capital market’s reaction to outsourcing announcements

Outsourcing is a widely accepted option in strategic management, which, like every business venture, bears opportunities and risks. Supplementing the popular area of research on the merits of outsourcing, this paper examines how stockholders rate corporate sourcing decisions with regard to the risk they associate with this transaction. Using event study methodology and multivariate cross-sectional OLS-regression, we analyze a sample of 182 outsourcing transactions in the global financial services industry between 1998 and 2004 in order to investigate the risk-specific drivers of excess returns to shareholders. The analysis studies the impact of risk-specific independent variables, including transaction size, length, outsourced business functionality, and experience with outsourcing. Our findings indicate that risk-mitigating strategies have significant explanatory power, indicating that the capital market’s reaction to an outsourcing announcement might at least partly be forecast. Results show a positive correlation between market reaction and business process outsourcing by financial services companies. We also find strong evidence indicating that capital markets react positively to relatively large transactions compared to the market capitalization of the outsourcing firm. For service providers our results show that traditional IT-related sourcing projects or the insourcing of administrative processes have a significant positive correlation with market reaction.     

Comparison and classification of 3D objects surface point clouds on the example of feet

One of the main tasks of shoe manufacturing is the production of well fitting shoes for different specialized markets. The key to conduct this properly is the analysis of the factors that influence the variations of the foot shape. In this paper methods and results of clustering and analysis of 3D foot surfaces are presented. The data were collected from a study with more than 12,000 feet that have been laser-scanned. The database contains point clouds acquired from persons coming from different regions of the world. Furthermore, additional personal data were collected. Two different methods for quantifying the similarity of 3D surface point clouds are therefore developed. The first method generally works on nearly arbitrary 3D surface point clouds, while the second one is specialized on foot data sets. These similarity measures were used on the data sets of the foot-shape study, together with clustering and feature quality evaluation methods. The purpose was to obtain information about the impact of, and the relationship among, the different factors influencing the shape of a foot. Through the observations of the experiments presented here it was possible to build up a hierarchy of different levels of feature-groups determined by their impact on the foot shape. Furthermore, an investigation of the quality and amount of impact of the features, according to their ability to separate specific subgroups of persons, is shown. Based on these results it was possible to select those features, which result in the largest effect when designing shoes for e.g. the Asian versus European markets.     

Learning optimized features for hierarchical models of invariant object recognition

There is an ongoing debate over the capabilities of hierarchical neural feedforward architectures for performing real-world invariant object recognition. Although a variety of hierarchical models exists, appropriate supervised and unsupervised learning methods are still an issue of intense research. We propose a feedforward model for recognition that shares components like weight sharing, pooling stages, and competitive nonlinearities with earlier approaches but focuses on new methods for learning optimal feature-detecting cells in intermediate stages of the hierarchical network. We show that principles of sparse coding, which were previously mostly applied to the initial feature detection stages, can also be employed to obtain optimized intermediate complex features. We suggest a new approach to optimize the learning of sparse features under the constraints of a weight-sharing or convolutional architecture that uses pooling operations to achieve gradual invariance in the feature hierarchy. The approach explicitly enforces symmetry constraints like translation invariance on the feature set. This leads to a dimension reduction in the search space of optimal features and allows determining more efficiently the basis representatives, which achieve a sparse decomposition of the input. We analyze the quality of the learned feature representation by investigating the recognition performance of the resulting hierarchical network on object and face databases. We show that a hierarchy with features learned on a single object data set can also be applied to face recognition without parameter changes and is competitive with other recent machine learning recognition approaches. To investigate the effect of the interplay between sparse coding and processing nonlinearities, we also consider alternative feedforward pooling nonlinearities such as presynaptic maximum selection and sum-of-squares integration. The comparison shows that a combination of strong competitive nonlinearities with sparse coding offers the best recognition performance in the difficult scenario of segmentation-free recognition in cluttered surround. We demonstrate that for both learning and recognition, a precise segmentation of the objects is not necessary.     

Formal validation of automated policy refinement in the management of network security systems

Policy hierarchies and automated policy refinement are powerful approaches to simplify administration of security services in complex network environments. A crucial issue for the practical use of these approaches is to ensure the validity of the policy hierarchy, i.e. since the policy sets for the lower levels are automatically derived from the abstract policies (defined by the modeller), we must be sure that the derived policies uphold the high-level ones. This paper builds upon previous work on Model-based Management, particularly on the Diagram of Abstract Subsystems approach, and goes further to propose a formal validation approach for the policy hierarchies yielded by the automated policy refinement process. We establish general validation conditions for a multi-layered policy model, i.e. necessary and sufficient conditions that a policy hierarchy must satisfy so that the lower-level policy sets are valid refinements of the higher-level policies according to the criteria of consistency and completeness. Relying upon the validation conditions and upon axioms about the model representativeness, two theorems are proved to ensure compliance between the resulting system behaviour and the abstract policies that are modelled.     

Weighted finite automata over strong bimonoids

We investigate weighted finite automata over strings and strong bimonoids. Such algebraic structures satisfy the same laws as semirings except that no distributivity laws need to hold. We define two different behaviors and prove precise characterizations for them if the underlying strong bimonoid satisfies local finiteness conditions. Moreover, we show that in this case the given weighted automata can be determinized.     

Evaluation of Stereo Matching Costs on Images with Radiometric Differences

Stereo correspondence methods rely on matching costs for computing the similarity of image locations. We evaluate the insensitivity of different costs for passive binocular stereo methods with respect to radiometric variations of the input images. We consider both pixel-based and window-based variants like the absolute difference, the sampling-insensitive absolute difference, and normalized cross correlation, as well as their zero-mean versions. We also consider filters like LoG, mean, and bilateral background subtraction (BilSub) and nonparametric measures like Rank, SoftRank, Census, and Ordinal. Finally, hierarchical mutual information (HMI) is considered as pixelwise cost. Using stereo data sets with ground-truth disparities taken under controlled changes of exposure and lighting, we evaluate the costs with a local, a semiglobal, and a global stereo method. We measure the performance of all costs in the presence of simulated and real radiometric differences, including exposure differences, vignetting, varying lighting, and noise. Overall, the ranking of methods across all data sets and experiments appears to be consistent. Among the best costs are BilSub, which performs consistently very well for low radiometric differences; HMI, which is slightly better as pixelwise matching cost in some cases and for strong image noise; and Census, which showed the best and most robust overall performance.     

Sicherheit ist messbar!

Zusammenfassung  Dieser Beitrag liefert einen überblick über die Sicherheitsmetrik des Open Source Security Testing Methodology Manual (OSSTMM) der Version 3.0 RC15 aus dem Jahre 2008. Das OSSTMM wird vom Institute for Security and Open Methodologies (ISECOM) in Barcelona herausgegeben. Der Artikel geht zun?chst auf die Grundlagen und den Zweck von OSSTMM ein. Anschliessend gibt er eine Einführung in die Sicherheitsmetrik und zeigt dessen Anwendung und Nutzen auf. Eine Abgrenzung zu anderen Methoden und aktuelle offene Probleme im OSSTMM runden den Beitrag ab. Heiko Rudolph 2004 gründete er die adMERITia, mit dem Hauptbet?tigungsfeld der Informationssicherheit. Seit 2006 arbeitet er bei der Non-Profit-Organisation „Institute for Security and Open Methodologies“ (ISECOM) mit. Aaron Brown Security Consultant adMERITia GmbH. Seit 2006 arbeitet er bei der Non-Profit-Organisation „Institute for Security and Open Methodologies“ (ISECOM) mit.     

Thermal response testing of a fractured hard rock aquifer with and without induced groundwater flow

This study quantifies experimentally the influence of groundwater on the thermal conductivity measurements via thermal response tests (TRT) in a fractured hard rock with low matrix permeability. An artificial groundwater flow towards a nearby well was induced by groundwater extraction and a TRT performed simultaneously. The results were compared with a TRT performed 24?days later in the same well without groundwater extraction. The effect of the groundwater flow is shown indirectly by the enhanced effective thermal conductivity and directly through the comparison of temperature profiles before and 4?h after both TRTs. Simulations in FEFLOW show that a groundwater flow velocity of 130–1,300?m?d^?1 through one open horizontal fracture of small volume increases the effective thermal conductivity by 11?% in the studied system.     

Efficient CPU‐based Volume Ray Tracing Techniques

Recent research on high‐performance ray tracing has achieved real‐time performance even for highly complex surface models already on a single PC. In this report, we provide an overview of techniques for extending real‐time ray tracing also to interactive volume rendering. We review fast rendering techniques for different volume representations and rendering modes in a variety of computing environments. The physically‐based rendering approach of ray tracing enables high image quality and allows for easily mixing surface, volume and other primitives in a scene, while fully accounting for all of their optical interactions. We present optimized implementations and discuss the use of upcoming high‐performance processors for volume ray tracing.     

Dynamic Transition Refinement

Refinement of Petri nets is well suited for the hierarchical design of system models. It is used to represent a model at different levels of abstraction.Usually, refinement is a static concept. For many scenarios, however, it is desirable to have a more flexible form of refinement. For example in the context of service updates, e.g. version control in distributed systems, a mechanism for dynamic transition refinement is needed.The requirement of dynamic refinement at runtime is quite strong. Since we would like to redefine the system structure by itself, transition refinement cannot be implemented by a model transformation. Instead, an approach is needed which allows for dynamic net structures that can evolve as an effect of transitions firing. In previous work we introduced nets-within-nets as a formalism for the dynamic refinement of tokens. Here we consider an extension of nets-within-nets that uses special net tokens describing the refinement structure of transitions. Using this formalism it is possible to update refinements, introduce alternative refinements, etc. We present some formal properties of the extended formalism and introduce an example implementation for the tool Renew in the context of workflow modeling.