Die Marktbearbeitung in der Automobilzulieferindustrie : Strategien, Erfolgsfaktoren und Fallstricke

Die sich verändernden Marktgegebenheiten in der Automobilindustrie stellen das Management von Automobilzulieferunternehmen vor immer neue Herausforderungen. Durch neue Einkaufs- bzw. Beschaffungskonzepte der Automobilhersteller, wie z.B. Outsourcing, Global Sourcing, Single Sourcing und Modular/System Sourcing, verändert sich das Gesicht der Automobilzulieferindustrie mit hoher Drehzahl. Das Institut für Marktorientierte Unternehmensführung (IMU) der Universität Mannheim und die Unternehmensberatung Prof. Homburg & Partner haben im Rahmen einer Analyse der gesamten Automobilzulieferindustrie zum Thema „Marktbearbeitung“ eine Vollerhebung bei insgesamt 1.024 Geschäftsbereichen der größten 313 internationalen Automobilzulieferern aller Wertschöpfungsstufen durchgeführt. Die Bestandsaufnahme liefert interessante Ergebnisse: Beispielsweise gelingt es erfolgreichen Automobilzulieferern bei der Marktbearbeitung wesentlich besser, sich zu fokussieren. Entscheidend dabei ist eine engere Produktpalette, die international angeboten wird. Dies gelingt mittelständischen Automobilzulieferern meist besser als sogenannten „Mega-Suppliern“. Außerdem ist, aufgrund der hohen Bedeutung der Qualität, zwar fast jeder der untersuchten Automobilzulieferer zertifiziert, aber gleichzeitig werden nicht alle Instrumente des Qualitätsmanagements systematisch eingesetzt. Neben der ausführlichen Darstellung der Bestandsaufnahme der Marktbearbeitung werden Erfolgsfaktoren aus insgesamt sechs verschiedenen Bereichen der Marktbearbeitung vorgestellt

Likelihood Non-Gaussianity in Large-Scale Structure Analyses

Standard present day large-scale structure (LSS) analyses make a major assumption in their Bayesian parameter inference --- that the likelihood has a Gaussian form. For summary statistics currently used in LSS, this assumption, even if the underlying density field is Gaussian, cannot be correct in detail. We investigate the impact of this assumption on two recent LSS analyses: the Beutler et al. (2017) power spectrum multipole ($P_\ell$) analysis and the Sinha et al. (2017) group multiplicity function ($\zeta$) analysis. Using non-parametric divergence estimators on mock catalogs originally constructed for covariance matrix estimation, we identify significant non-Gaussianity in both the $P_\ell$ and $\zeta$ likelihoods. We then use Gaussian mixture density estimation and Independent Component Analysis on the same mocks to construct likelihood estimates that approximate the true likelihood better than the Gaussian $pseudo$-likelihood. Using these likelihood estimates, we accurately estimate the true posterior probability distribution of the Beutler et al. (2017) and Sinha et al. (2017) parameters. Likelihood non-Gaussianity shifts the $f\sigma_8$ constraint by $-0.44\sigma$, but otherwise, does not significantly impact the overall parameter constraints of Beutler et al. (2017). For the $\zeta$ analysis, using the pseudo-likelihood significantly underestimates the uncertainties and biases the constraints of Sinha et al. (2017) halo occupation parameters. For $\log M_1$ and $\alpha$, the posteriors are shifted by $+0.43\sigma$ and $-0.51\sigma$ and broadened by $42\%$ and $66\%$, respectively. The divergence and likelihood estimation methods we present provide a straightforward framework for quantifying the impact of likelihood non-Gaussianity and deriving more accurate parameter constraints.Comment: 33 pages, 7 figure

A Highly Accurate Query-Recovery Attack against Searchable Encryption using Non-Indexed Documents

Cloud data storage solutions offer customers cost-effective and reduced data management. While attractive, data security issues remain to be a core concern. Traditional encryption protects stored documents, but hinders simple functionalities such as keyword search. Therefore, searchable encryption schemes have been proposed to allow for the search on encrypted data. Efficient schemes leak at least the access pattern (the accessed documents per keyword search), which is known to be exploitable in query recovery attacks assuming the attacker has a significant amount of background knowledge on the stored documents. Existing attacks can only achieve decent results with strong adversary models (e.g. at least 20% of previously known documents or require additional knowledge such as on query frequencies) and they give no metric to evaluate the certainty of recovered queries. This hampers their practical utility and questions their relevance in the real-world. We propose a refined score attack which achieves query recovery rates of around 85% without requiring exact background knowledge on stored documents; a distributionally similar, but otherwise different (i.e., non-indexed), dataset suffices. The attack starts with very few known queries (around 10 known queries in our experiments over different datasets of varying size) and then iteratively recovers further queries with confidence scores by adding previously recovered queries that had high confidence scores to the set of known queries. Additional to high recovery rates, our approach yields interpretable results in terms of confidence scores.Comment: Published in USENIX 2021. Full version with extended appendices and removed some typo

Fluid-limit Cosmological Simulations Starting from the Big Bang

The cosmic large-scale structure (LSS) provides a unique testing ground for connecting fundamental physics to astronomical observations. Modelling the LSS requires numerical $N$-body simulations or perturbative techniques that both come with distinct shortcomings. Here we present the first unified numerical approach, enabled by new time integration and discreteness reduction schemes, and demonstrate its convergence at the field level. In particular, we show that our simulations (1) can be initialised directly at time zero, and (2) can be made to agree with high-order Lagrangian perturbation theory in the fluid limit. This allows fast, self-consistent, and UV-complete forward modelling of LSS observables.Comment: 5+10 pages, 4+7 figures. Comments are very welcome

Practical yet Provably Secure: Complex Database Query Execution over Encrypted Data

Encrypted databases provide security for outsourced data. In this work novel encryption schemes supporting different database query types are presented enabling complex database queries over encrypted data. For specific constructions enabling exact keyword queries, range queries, database joins and substring queries over encrypted data we prove security in a formal framework, present a theoretical runtime analysis and provide an assessment of practical performance characteristics

Hybrid biometric template protection:Resolving the agony of choice between bloom filters and homomorphic encryption

Abstract Bloom filters (BFs) and homomorphic encryption (HE) are prominent techniques used to design biometric template protection (BTP) schemes that aim to protect sensitive biometric information during storage and biometric comparison. However, the pros and cons of BF‐ and HE‐based BTPs are not well studied in literature. We investigate the strengths and weaknesses of these two approaches since both seem promising from a theoretical viewpoint. Our key insight is to extend our theoretical investigation to cover the practical case of iris recognition on the ground that iris (1) benefits from the alignment‐free property of BFs and (2) induces huge computational burdens when implemented in the HE‐encrypted domain. BF‐based BTPs can be implemented to be either fast with high recognition accuracy while missing the important privacy property of ‘unlinkability’, or to be fast with unlinkability‐property while missing the high accuracy. HE‐based BTPs, on the other hand, are highly secure, achieve good accuracy, and meet the unlinkability‐property, but they are much slower than BF‐based approaches. As a synthesis, we propose a hybrid BTP scheme that combines the good properties of BFs and HE, ensuring unlinkability and high recognition accuracy, while being about seven times faster than the traditional HE‐based approach

Electroweak corrections to γZ\gamma Z production at hadron colliders

In this paper we present the results from a calculation of the full electroweak one-loop corrections for $\gamma Z$ vector-boson pair production at hadron colliders. The cases of proton--antiproton as well as proton--proton collisions, at the Tevatron and the LHC, respectively, are considered. Results are presented for the distribution of the $\gamma Z$ invariant mass and for the transverse momentum of the final-state photon. The higher-order electroweak effects are numerically significant, in particular for probing possible anomalous gauge-boson couplings

Development of a pilot site for high temperature heat pumps, with high temperature mine thermal energy storage as heat source

A pilot plant for high temperature heat pumps (HTHP’s) combined with high temperature mine thermal energy storage (HT-MTES) is developed at the Fraunhofer IEG location of Bochum. The aim of the plant is to inject renewable heat into the district heating (DH) grid. The HT-MTES is a seasonal thermal storage: heat is injected during the summer and successively extracted during the cold season. A HTHP, hydraulically connected to the storage, transfers heat to the DH gri