Technische Universität Darmstadt

About: Technische Universität Darmstadt is a education organization based out in Darmstadt, Germany. It is known for research contribution in the topics: Computer science & Context (language use). The organization has 17316 authors who have published 40619 publications receiving 937916 citations. The organization is also known as: Darmstadt University of Technology & University of Darmstadt.

The ECO data set and the performance of non-intrusive load monitoring algorithms

Abstract: Non-intrusive load monitoring (NILM) is a popular approach to estimate appliance-level electricity consumption from aggregate consumption data of households. Assessing the suitability of NILM algorithms to be used in real scenarios is however still cumbersome, mainly because there exists no standardized evaluation procedure for NILM algorithms and the availability of comprehensive electricity consumption data sets on which to run such a procedure is still limited. This paper contributes to the solution of this problem by: (1) outlining the key dimensions of the design space of NILM algorithms; (2) presenting a novel, comprehensive data set to evaluate the performance of NILM algorithms; (3) describing the design and implementation of a framework that significantly eases the evaluation of NILM algorithms using different data sets and parameter configurations; (4) demonstrating the use of the presented framework and data set through an extensive performance evaluation of four selected NILM algorithms. Both the presented data set and the evaluation framework are made publicly available.

Caloric Effects in Ferroic Materials: New Concepts for Cooling†

Abstract: Refrigeration is one of the main sinks of the German and European electricity consumption and accordingly contributes to worldwide CO2 emissions. High reduction potentials are envisaged if caloric effects in solid materials are used. The recent discovery of giant entropy changes associated with ferroelastic phase transformations promises higher efficiency. Ferroic transitions enhance the entropy change of magneto-, elasto-, baro-, and electro-caloric effects. Furthermore, because the refrigerant is in a solid state, this technology completely eliminates the need for halofluorocarbon refrigerants having a high global-warming potential. The smaller footprint for operation and the scalable mechanism open up further applications such as cooling of microsystems. While the principal feasibility of magnetocaloric refrigeration is already evident, it requires large magnetic fields (>2 T) which hampers wide industrial and commercial application. It is expected that this obstacle can be overcome by materials with lower hysteresis and by using stress- or electric fields. In order to accelerate research on ferroic cooling, the Deutsche Forschungsgemeinschaft (DFG) decided to establish the priority program SPP 1599 in April 2011. In this article we will address the major challenges for introducing ferroic materials in practical cooling applications: energy efficiency, effect size, and fatigue behavior. Solid state cooling in this sense can be based on the following “ferroic-caloric” classes of materials: ferroelastic shape memory alloys, ferromagnetic shape memory alloys, and ferroelectric materials and their possible combinations in materials with “multicaloric” effects. The open questions require the interdisciplinary collaboration of material scientists, engineers, physicists, and mathematicians.

The CoNLL-2010 Shared Task: Learning to Detect Hedges and their Scope in Natural Language Text

Abstract: The CoNLL-2010 Shared Task was dedicated to the detection of uncertainty cues and their linguistic scope in natural language texts. The motivation behind this task was that distinguishing factual and uncertain information in texts is of essential importance in information extraction. This paper provides a general overview of the shared task, including the annotation protocols of the training and evaluation datasets, the exact task definitions, the evaluation metrics employed and the overall results. The paper concludes with an analysis of the prominent approaches and an overview of the systems submitted to the shared task.