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Multi-attribute relation extraction (MARE): simplifying the application of relation extraction
(2021)
Natural language understanding’s relation extraction makes innovative and encouraging novel business concepts possible and facilitates new digitilized decision-making processes. Current approaches allow the extraction of relations with a fixed number of entities as attributes. Extracting relations with an arbitrary amount of attributes requires complex systems and costly relation-trigger annotations to assist these systems. We introduce multi-attribute relation extraction (MARE) as an assumption-less problem formulation with two approaches, facilitating an explicit mapping from business use cases to the data annotations. Avoiding elaborated annotation constraints simplifies the application of relation extraction approaches. The evaluation compares our models to current state-of-the-art event extraction and binary relation extraction methods. Our approaches show improvement compared to these on the extraction of general multi-attribute relations.
The paper industry is the industry with the third highest energy consumption in the European Union. Using recycled paper instead of fresh fibers for papermaking is less energy consuming and saves resources. However, adhesive contaminants in recycled paper are particularly problematic since they reduce the quality of the resulting paper-product. To remove as many contaminants and at the same time obtain as many valuable fibres as possible, fine screening systems, consisting of multiple interconnected pressure screens, are used. Choosing the best configuration is a non-trivial task: The screens can be interconnected in several ways, and suitable screen designs as well as operational parameters have to be selected. Additionally, one has to face conflicting objectives. In this paper, we present an approach for the multi-criteria optimization of pressure screen systems based on Mixed-Integer Nonlinear Programming. We specifically focus on a clear representation of the trade-off between different objectives.
Multi-dimensional fragility analysis of a RC building with components using response surface method
(2017)
Conventional fragility curves describe the vulnerability of the main structure under external hazards. However, in complex structures such as nuclear power plants, the safety or the risk depends also on the components associated with a system. The classical fault tree analysis gives an overall view of the failure and contains several subsystems to the main event, however, the interactions in the subsystems are not well represented. In order to represent the interaction of the components, a method suggested by Cimellaro et al. (2006) using multidimensional performance limit state functions to obtain the system fragility curves is adopted. This approach gives the possibility of deriving the cumulative fragility taking into account the interaction of the response of different components. In this paper, this approach is used to evaluate seismic risk of a representative electrical building infrastructure, including the component, of a nuclear power plant. A simplified model of the structure, with nonlinear material behavior is employed for the analysis in Abaqus©. The input variables considered are the material parameters, boundary conditions and the seismic input. The variability of the seismic input is obtained from selected ground motion time histories of spectrum compatible synthetic ccelerograms. Unlike the usual Monte Carlo methods used for the probabilistic analysis of the structure, a computationally effective response surface method is used. This method reduces the computational effort of the calculations by reducing the required
number of samples.
Multi-interface level sensors and new development in monitoring and control of oil separators
(2006)
In the oil industry, huge saving may be made if suitable multi-interface level measurement systems are employed for effectively monitoring crude oil separators and efficient control of their operation. A number of techniques, e.g. externally mounted displacers, differential pressure transmitters and capacitance rod devices, have been developed to measure the separation process with gas, oil, water and other components. Because of the unavailability of suitable multi-interface level measurement systems, oil separators are currently operated by the trial-and-error approach. In this paper some conventional techniques, which have been used for level measurement in industry, and new development are discussed.
Multi-parameter detection for supporting monitoring and control of biogas processes in agriculture
(2014)
In times of planned obsolescence the demand for sustainability keeps growing. Ideally, a technical system is highly reliable, without failures and down times due to fast wear of single components. At the same time, maintenance should preferably be limited to pre-defined time intervals. Dispersion of load between multiple components can increase a system’s reliability and thus its availability inbetween maintenance points. However, this also results in higher investment costs and additional efforts due to higher complexity. Given a specific load profile and resulting wear of components, it is often unclear which system structure is the optimal one. Technical Operations Research (TOR) finds an optimal structure balancing availability and effort. We present our approach by designing a hydrostatic transmission system.