On the correspondence between abstract dialectical frameworks and nonmonotonic conditional logics

Annals of Mathematics and Artificial Intelligence - The exact relationship between formal argumentation and nonmonotonic logics is a research topic that keeps on eluding researchers despite recent...     

Surface reconstruction for incremental forming

In spite of extensive efforts being made with regard to virtual process optimization technology, the production of prototype parts is still a necessity. With respect to the production of sheet metal parts in low quantities, incremental sheet metal forming (ISMF) is a highly interesting process. ISMF allows the production of complex parts with drastically reduced costs in tooling and machinery compared to conventional processes like deep drawing. However, ISMF, with it’s incremental nature, introduces the need for generating a tool path considering both final geometry and process-induced deviations or constraints. Consequently, for the generation of the tool path a (tool path) surface, with an adequate offset, is necessary. That is why, within the scope of extensive research work at the Institute of Forming Technology and Lightweight Construction (IUL), a special correction module has been developed, determining this offset e.g. depending on the workpiece geometry. This paper presents the algorithm, the application, and the effect on the produced parts. Furthermore, a concept for an extension regarding further constraints like elastic workpiece behavior is presented.     

Investigation of wetting behaviour of hardenable copper based-alloys for brazing applications

ABSTRACT

Tools for machining are exposed to high loads, wear, and elevated temperatures. Commonly, such tools consist of cemented carbides and tool steel. To combine the advantages of both materials, high-quality-joints with high strengths are desired. When brazing these materials, the main challenge is the mismatch of the Coefficient of Thermal Expansion (CTE) and the poor wettability of cemented carbides by molten filler alloys. In this regard, the feasibility of two custom-made alloys (CuNi12Si5, CuNi12Si5B0.4) was analysed. Besides being a cost-efficient alternative, these alloys offer the possibility to modify their mechanical properties by precipitation hardening to reduce stresses within the final joints. Thus, this paper shows that a temperature of 1060°C is suitable for wetting and brazing tests on different substrates.     

Insight into spontaneous recurrent calcium waves in a 3-D cardiac cell based on analysis of a 1-D deterministic model

Calcium dynamics in a cardiac cell are described by a system of 3-D non-linear stochastic partial differential equations. To obtain solutions that have biophysical properties, it is necessary to explore the model parameter space. To decrease the complexity of the parameter search, we reduce the 3-D stochastic model to a 1-D deterministic model. The reduction of the problem from 3-D to 1-D is done through an asymptotic approximation after non-dimensionalization and based on rational biophysical assumptions of the 3-D domain; the stochastic to deterministic transformation is based on the regular property of the 3-D solution. The result of the model reduction proves very effective in reducing the time required to get qualitative as well as quantitative information about parameter regions in the 3-D stochastic model including calcium dynamics (sparks, wave propagation, and recovery) observed in cardiac cells.     

Business process compliance checking – applying and evaluating a generic pattern matching approach for conceptual models in the financial sector

Given the strong increase in regulatory requirements for business processes the management of business process compliance becomes a more and more regarded field in IS research. Several methods have been developed to support compliance checking of conceptual models. However, their focus on distinct modeling languages and mostly linear (i.e., predecessor-successor related) compliance rules may hinder widespread adoption and application in practice. Furthermore, hardly any of them has been evaluated in a real-world setting. We address this issue by applying a generic pattern matching approach for conceptual models to business process compliance checking in the financial sector. It consists of a model query language, a search algorithm and a corresponding modelling tool prototype. It is (1) applicable for all graph-based conceptual modeling languages and (2) for different kinds of compliance rules. Furthermore, based on an applicability check, we (3) evaluate the approach in a financial industry project setting against its relevance for decision support of audit and compliance management tasks.     

Backscatter from the data plane – Threats to stability and security in information-centric network infrastructure

Information-centric networking (ICN) raises data objects to first class routable entities in the network and changes the Internet paradigm from host-centric connectivity to data-oriented delivery. However, current approaches to content routing heavily rely on data-driven protocol events and thereby introduce a strong coupling of the control to the data plane in the underlying routing infrastructure. In this paper, threats to the stability and security of the content distribution system are analyzed in theory, simulations, and practical experiments. We derive relations between state resources and the performance of routers, and demonstrate how this coupling can be misused in practice. We further show how state-based forwarding tends to degrade by decorrelating resources. We identify intrinsic attack vectors present in current content-centric routing, as well as possibilities and limitations to mitigate them. Our overall findings suggest that major architectural refinements are required prior to global ICN deployment in the real world.     

Spatial inverse query processing

Traditional spatial queries return, for a given query object q, all database objects that satisfy a given predicate, such as epsilon range and k-nearest neighbors. This paper defines and studies inverse spatial queries, which, given a subset of database objects Q and a query predicate, return all objects which, if used as query objects with the predicate, contain Q in their result. We first show a straightforward solution for answering inverse spatial queries for any query predicate. Then, we propose a filter-and-refinement framework that can be used to improve efficiency. We show how to apply this framework on a variety of inverse queries, using appropriate space pruning strategies. In particular, we propose solutions for inverse epsilon range queries, inverse k-nearest neighbor queries, and inverse skyline queries. Furthermore, we show how to relax the definition of inverse queries in order to ensure non-empty result sets. Our experiments show that our framework is significantly more efficient than naive approaches.     

Clustering high dimensional data: A graph-based relaxed optimization approach

There is no doubt that clustering is one of the most studied data mining tasks. Nevertheless, it remains a challenging problem to solve despite the many proposed clustering approaches. Graph-based approaches solve the clustering task as a global optimization problem, while many other works are based on local methods. In this paper, we propose a novel graph-based algorithm “GBR” that relaxes some well-defined method even as improving the accuracy whilst keeping it simple. The primary motivation of our relaxation of the objective is to allow the reformulated objective to find well distributed cluster indicators for complicated data instances. This relaxation results in an analytical solution that avoids the approximated iterative methods that have been adopted in many other graph-based approaches. The experiments on synthetic and real data sets show that our relaxation accomplishes excellent clustering results. Our key contributions are: (1) we provide an analytical solution to solve the global clustering task as opposed to approximated iterative approaches; (2) a very simple implementation using existing optimization packages; (3) an algorithm with relatively less computation time over the number of data instances to cluster than other well defined methods in the literature.     

Numerical simulation of cloud droplet formation in a tank

Using the computational fluid dynamics (CFD) code FLUENT 6 together with the fine particle model (FPM), numerical simulations of droplet dynamics in a 12.4 m³ cloud tank were conducted. The coupled fields of water vapor, temperature, flow velocity, particle number concentration, and particle mass concentration inside the cloud tank were computed.The system responses to changes of the wall's temperature and mass fraction of water vapor, respectively, were investigated. Typical times for mixing the cloud tank's contents are in the range of some tens of seconds. The maximum volume-averaged deviations from the mean of temperature and mass fraction of water vapor are around 5% of the respective parameter changes applied to the wall.Time-dependent simulations were performed in order to study the growth of ammonium-sulfate particles in humid air at around room temperature. Supersaturation up to (S_w–1)=8.2×10⁻³ was achieved by the expansion of the gas. The particles were activated and grew rapidly to a maximum diameter of 5.2×10⁻⁶ m after critical supersaturation was reached. After S_w fell again below the equilibrium value, the particles shrank quickly and deactivated roughly 60 s after activation.The spatial inhomogeneities of temperature and water-vapor concentration cause volume-averaged deviations of the particle number N and diameter d_g of up to 2.3% and 36%, respectively.