Refine
Year of publication
- 2024 (55)
- 2023 (116)
- 2022 (146)
- 2021 (154)
- 2020 (172)
- 2019 (196)
- 2018 (173)
- 2017 (155)
- 2016 (161)
- 2015 (176)
- 2014 (167)
- 2013 (174)
- 2012 (164)
- 2011 (189)
- 2010 (187)
- 2009 (189)
- 2008 (157)
- 2007 (149)
- 2006 (160)
- 2005 (130)
- 2004 (161)
- 2003 (106)
- 2002 (130)
- 2001 (106)
- 2000 (108)
- 1999 (109)
- 1998 (99)
- 1997 (99)
- 1996 (81)
- 1995 (78)
- 1994 (87)
- 1993 (59)
- 1992 (54)
- 1991 (29)
- 1990 (39)
- 1989 (45)
- 1988 (57)
- 1987 (32)
- 1986 (19)
- 1985 (34)
- 1984 (22)
- 1983 (20)
- 1982 (29)
- 1981 (20)
- 1980 (36)
- 1979 (24)
- 1978 (34)
- 1977 (14)
- 1976 (13)
- 1975 (12)
- 1974 (3)
- 1973 (2)
- 1972 (2)
- 1971 (1)
- 1968 (1)
Institute
- Fachbereich Medizintechnik und Technomathematik (1693)
- Fachbereich Elektrotechnik und Informationstechnik (719)
- IfB - Institut für Bioengineering (624)
- Fachbereich Energietechnik (589)
- INB - Institut für Nano- und Biotechnologien (557)
- Fachbereich Chemie und Biotechnologie (552)
- Fachbereich Luft- und Raumfahrttechnik (497)
- Fachbereich Maschinenbau und Mechatronik (283)
- Fachbereich Wirtschaftswissenschaften (222)
- Solar-Institut Jülich (165)
Language
- English (4935) (remove)
Document Type
- Article (3285)
- Conference Proceeding (1170)
- Part of a Book (195)
- Book (146)
- Doctoral Thesis (32)
- Conference: Meeting Abstract (29)
- Patent (25)
- Other (10)
- Report (10)
- Conference Poster (6)
Keywords
- Biosensor (25)
- Finite-Elemente-Methode (12)
- Einspielen <Werkstoff> (10)
- CAD (8)
- civil engineering (8)
- Bauingenieurwesen (7)
- Blitzschutz (6)
- FEM (6)
- Gamification (6)
- Limit analysis (6)
We consider a binary multivariate regression model where the conditional expectation of a binary variable given a higher-dimensional input variable belongs to a parametric family. Based on this, we introduce a model-based bootstrap (MBB) for higher-dimensional input variables. This test can be used to check whether a sequence of independent and identically distributed observations belongs to such a parametric family. The approach is based on the empirical residual process introduced by Stute (Ann Statist 25:613–641, 1997). In contrast to Stute and Zhu’s approach (2002) Stute & Zhu (Scandinavian J Statist 29:535–545, 2002), a transformation is not required. Thus, any problems associated with non-parametric regression estimation are avoided. As a result, the MBB method is much easier for users to implement. To illustrate the power of the MBB based tests, a small simulation study is performed. Compared to the approach of Stute & Zhu (Scandinavian J Statist 29:535–545, 2002), the simulations indicate a slightly improved power of the MBB based method. Finally, both methods are applied to a real data set.
This book provides a compact introduction to the bootstrap method. In addition to classical results on point estimation and test theory, multivariate linear regression models and generalized linear models are covered in detail. Special attention is given to the use of bootstrap procedures to perform goodness-of-fit tests to validate model or distributional assumptions. In some cases, new methods are presented here for the first time.
The text is motivated by practical examples and the implementations of the corresponding algorithms are always given directly in R in a comprehensible form. Overall, R is given great importance throughout. Each chapter includes a section of exercises and, for the more mathematically inclined readers, concludes with rigorous proofs. The intended audience is graduate students who already have a prior knowledge of probability theory and mathematical statistics.
The first and last mile of a railway journey, in both freight and transit applications, constitutes a high effort and is either non-productive (e.g. in the case of depot operations) or highly inefficient (e.g. in industrial railways). These parts are typically managed on-sight, i.e. with no signalling and train protection systems ensuring the freedom of movement. This is possible due to the rather short braking distances of individual vehicles and shunting consists. The present article analyses the braking behaviour of such shunting units. For this purpose, a dedicated model is developed. It is calibrated on published results of brake tests and validated against a high-definition model for low-speed applications. Based on this model, multiple simulations are executed to obtain a Monte Carlo simulation of the resulting braking distances. Based on the distribution properties and established safety levels, the risk of exceeding certain braking distances is evaluated and maximum braking distances are derived. Together with certain parameters of the system, these can serve in the design and safety assessment of driver assistance systems and automation of these processes.
Within the framework of the project a genderand diversity-oriented teaching evaluation and modern, media-supported blended learning approaches were used in order to achieve the intended goals. First research results of the literature and status quo analysis were already implemented and tested in newly designed teaching approaches, for example in a multidisciplinary introductory lecture of civil engineering at RWTH Aachen University.
The main objective of the BATIMASS project was to address how the energy balance in relatively lightweight steel buildings can be improved by building in ‘active thermal mass’ (ATM) into the building fabric. This was achieved through concept design, dynamic thermal modelling and testing of a number of potentially viable systems and concepts. A significant programme of thermal simulation modelling was undertaken utilising the thermally equivalent slab (TES) concept to model the passive thermal capacity effect of profiled, composite metal floor decks. It is apparent from the modelling results that thermal mass is a highly complex phenomenon which is highly dependent upon building type, occupancy patterns, climate and many other aspects of the building design and servicing strategy. The ATM systems developed, both conceptually and for prototype testing, focussed on water-cooled composite slabs, the Cofradal floor system and the phase change material (PCM) Energain. In addition to laboratory testing of prototypes, whole building monitoring was undertaken at the Kubik building in Spain and the RWTH test building in Germany. Advanced thermal modelling was also undertaken to estimate the likely benefits of the ATM concept designs developed and for comparison with the test results. In addition to thermal testing, structural tests were conducted on composite floor specimens incorporating embedded water pipes. This Final Report presents the results of the activities carried out under this RFCS contract RFSR CT 2012 00033. The work carried out is reported in six major sections corresponding to the technical Work Packages of the project. Only summaries of the work carried out are provided in this report; all work undertaken is fully reported in the formal project deliverables.
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.