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We present the results of Monte Carlo mass-loss predictions for massive stars covering a wide range of stellar parameters. We critically test our predictions against a range of observed massloss rates – in light of the recent discussions on wind clumping. We also present a model to compute the clumping-induced polarimetric variability of hot stars and we compare this with observations of Luminous Blue Variables, for which polarimetric variability is larger than for O and Wolf-Rayet stars. Luminous Blue Variables comprise an ideal testbed for studies of wind clumping and wind geometry, as well as for wind strength calculations, and we propose they may be direct supernova progenitors.
Faced with the triad of time-cost-quality, the realization of production tasks under economic conditions is not trivial. Since the number of Artificial-Intelligence-(AI)-based applications in business processes is increasing more and more nowadays, the efficient design of AI cases for production processes as well as their target-oriented improvement is essential, so that production outcomes satisfy high quality criteria and economic requirements. Both challenge production management and data scientists, aiming to assign ideal manifestations of artificial neural networks (ANNs) to a certain task. Faced with new attempts of ANN-based production process improvements [8], this paper continues research about the optimal creation, provision and utilization of ANNs. Moreover, it presents a mechanism for AI case-based reasoning for ANNs. Experiments clarify continuously improving ANN knowledge bases by this mechanism empirically. Its proof-of-concept is demonstrated by the example of four production simulation scenarios, which cover the most relevant use cases and will be the basis for examining AI cases on a quantitative level.
We describe a framework to support the implementation of web-based systems to manipulate data stored in relational databases. Since the conceptual model of a relational database is often specified as an entity-relationship (ER) model, we propose to use the ER model to generate a complete implementation in the declarative programming language Curry. This implementation contains operations to create and manipulate entities of the data model, supports authentication, authorization, session handling, and the composition of individual operations to user processes. Furthermore and most important, the implementation ensures the consistency of the database w.r.t. the data dependencies specified in the ER model, i.e., updates initiated by the user cannot lead to an inconsistent state of the database. In order to generate a high-level declarative implementation that can be easily adapted to individual customer requirements, the framework exploits previous works on declarative database programming and web user interface construction in Curry.
Helping overcome distance, the use of videoconferencing tools has surged during the pandemic. To shed light on the consequences of videoconferencing at work, this study takes a granular look at the implications of the self-view feature for meeting outcomes. Building on self-awareness research and self-regulation theory, we argue that by heightening the state of self-awareness, self-view engagement depletes participants’ mental resources and thereby can undermine online meeting outcomes. Evaluation of our theoretical model on a sample of 179 employees reveals a nuanced picture. Self-view engagement while speaking and while listening is positively associated with self-awareness, which, in turn, is negatively associated with satisfaction with meeting process, perceived productivity, and meeting enjoyment. The criticality of the communication role is put forward: looking at self while listening to other attendees has a negative direct and indirect effect on meeting outcomes; however, looking at self while speaking produces equivocal effects.
Nested complementation plays an important role in expressing counter- i.e. star-free and first-order definable languages and their hierarchies. In addition, methods that compile phonological rules into finite-state networks use double-nested complementation or “double negation”. This paper reviews how the double-nested complementation extends to a relatively new operation, generalized restriction (GR), coined by the author (Yli-Jyrä and Koskenniemi 2004). This operation encapsulates a double-nested complementation and elimination of a concatenation marker, diamond, whose finite occurrences align concatenations in the arguments of the operation. The paper demonstrates that the GR operation has an interesting potential in expressing regular languages, various kinds of grammars, bimorphisms and relations. This motivates a further study of optimized implementation of the operator.
Enforcing security policies to distributed systems is difficult, in particular, when a system contains untrusted components. We designed AspectKE*, a distributed AOP language based on a tuple space, to tackle this issue. In AspectKE*, aspects can enforce access control policies that depend on future behavior of running processes. One of the key language features is the predicates and functions that extract results of static program analysis, which are useful for defining security aspects that have to know about future behavior of a program. AspectKE* also provides a novel variable binding mechanism for pointcuts, so that pointcuts can uniformly specify join points based on both static and dynamic information about the program. Our implementation strategy performs fundamental static analysis at load-time, so as to retain runtime overheads minimal. We implemented a compiler for AspectKE*, and demonstrate usefulness of AspectKE* through a security aspect for a distributed chat system.
Association between skeletal robustness and physical activity in schoolchildren - First results
(2011)
This article describes a HMM-based word-alignment method that can selectively enforce a contiguity constraint. This method has a direct application in the extraction of a bilingual terminological lexicon from a parallel corpus, but can also be used as a preliminary step for the extraction of phrase pairs in a Phrase-Based Statistical Machine Translation system. Contiguous source words composing terms are aligned to contiguous target language words. The HMM is transformed into a Weighted Finite State Transducer (WFST) and contiguity constraints are enforced by specific multi-tape WFSTs. The proposed method is especially suited when basic linguistic resources (morphological analyzer, part-of-speech taggers and term extractors) are available for the source language only.
Interdisziplinäres Zentrum für Musterdynamik und Angewandte Fernerkundung Workshop vom 9. - 10. Februar 2006
Being "in the game"
(2008)
When people describe themselves as being “in the game” this is often thought to mean they have a sense of presence, i.e. they feel like they are in the virtual environment (Brown/Cairns 2004). Presence research traditionally focuses on user experiences in virtual reality systems (e.g. head mounted displays, CAVE-like systems). In contrast, the experience of gaming is very different. Gamers willingly submit to the rules of the game, learn arbitrary relationships between the controls and the screen output, and take on the persona of their game character. Also whereas presence in VR systems is immediate, presence in gaming is gradual. Due to these differences, one can question the extent to which people feel present during gaming. A qualitative study was conducted to explore what gamers actually mean when they describe themselves as being “in the game.” Thirteen gamers were interviewed and the resulting grounded theory suggests being “in the game” does not necessarily mean presence (i.e. feeling like you are the character and present in the VE). Some people use this phrase just to emphasize their high involvement in the game. These findings differ with Brown and Cairns as they suggest at the highest state of immersion not everybody experiences presence. Furthermore, the experience of presence does not appear dependent on the game being in the first person perspective or the gamer being able to empathize with the character. Future research should investigate why some people experience presence and others do not. Possible explanations include: use of language, perception of presence, personality traits, and types of immersion.