Institution
Johannes Kepler University of Linz
Education•Linz, Oberösterreich, Austria•
About: Johannes Kepler University of Linz is a education organization based out in Linz, Oberösterreich, Austria. It is known for research contribution in the topics: Computer science & Thin film. The organization has 6605 authors who have published 19243 publications receiving 385667 citations.
Papers published on a yearly basis
Papers
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TL;DR: The requirement that methodologies for CPS-design should be part of a multi-disciplinary development process within which designers should focus not only on the separate physical and computational components, but also on their integration and interaction is considered.
208 citations
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TL;DR: In this paper, a systematic literature review of management accounting in SMEs is presented, which explains how environmental, staff, and organizational factors significantly influence the organization of SMEs and that SME performance in general benefits from proper management accounting.
Abstract: Management accounting in small and medium-sized enterprises (SMEs) has been an issue of growing interest in the management accounting literature in recent years. However, published research is fragmented, spanning various fields such as accounting, small business and entrepreneurship, general management, and production and operations management. This paper aims to synthesize extant knowledge on management accounting in SMEs and provide concrete suggestions on how to proceed. We performed a systematic literature review, synthesized the results, and identified research gaps. Our findings show that usage of management accounting is not only lower but also different in SMEs compared to larger entities. Based on a comparison of SMEs, the review explains how environmental, staff, and organizational factors significantly influence the organization of management accounting in SMEs and that SME performance in general benefits from proper management accounting. We conclude with several concrete research q...
207 citations
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TL;DR: An evaluation metric for generative models called Fréchet ChemNet distance (FCD) is proposed that can detect whether generated molecules are diverse and have similar chemical and biological properties as real molecules.
Abstract: The new wave of successful generative models in machine learning has increased the interest in deep learning driven de novo drug design. However, method comparison is difficult because of various flaws of the currently employed evaluation metrics. We propose an evaluation metric for generative models called Frechet ChemNet distance (FCD). The advantage of the FCD over previous metrics is that it can detect whether generated molecules are diverse and have similar chemical and biological properties as real molecules.
207 citations
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TL;DR: In this article, a systematic literature review of available research evidence on risk management in small and medium-sized enterprises (SMEs) is presented, which aims to reveal ambiguities, gaps and contradictions in the literature, and to sketch avenues for further research.
Abstract: Purpose – The purpose of this paper is to provide a systematic literature review of available research evidence on risk management in small and medium-sized enterprises (SMEs). The authors aim to reveal ambiguities, gaps and contradictions in the literature, and to sketch avenues for further research. Design/methodology/approach – The authors follow the tenets of Tranfield et al. (2003) for conducting a systematic literature review. Following a key word search and an assessment of fit for this review, 27 papers were analyzed with respect to bibliographical information, research design and findings. Findings – The review identified various types of risks that may occur in SMEs. In addition, the publication analysis demonstrates the importance of a risk management process in SMEs and that the characteristics of SME owners have a significant impact on their business strategies. Research limitations/implications – Additional empirical research on risk identification, risk analysis, strategy implementation and...
206 citations
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TL;DR: In this paper, an apparatus is presented which enables the application of defined portions of mechanical work to the polymer sample in its state of undercooled melt, for the purpose mainly intermittent shear creep is used.
Abstract: An apparatus is presented which enables the application of defined portions of mechanical work to the polymer sample in its state of undercooled melt. For the purpose mainly intermittent shear creep is used. Results are presented for an industrial grade of polypropylene. A three-dimensional picture is presented, in which the resulting numbers of nuclei (per unit volume) are plotted against two responsible parameters: crystallization temperature and mechanical work. With decreasing temperature and with increasing mechanical work the number of nuclei increases by many decades. At sufficiently high mechanical loads a transition to thread-like precursors ("shishs") has been observed previously. Oriented structures (kind of "shish-kebabs") are formed in this way. The periods of shearing applied have always been extremely short compared with the time until crystallization becomes observable. In this way an accumulation of various processes could be avoided. The description of shear induced crystallization, as previously given, is modified in the light of the present results.
205 citations
Authors
Showing all 6718 results
Name | H-index | Papers | Citations |
---|---|---|---|
Wolfgang Wagner | 156 | 2342 | 123391 |
A. Paul Alivisatos | 146 | 470 | 101741 |
Klaus-Robert Müller | 129 | 764 | 79391 |
Christoph J. Brabec | 120 | 896 | 68188 |
Andreas Heinz | 108 | 1078 | 45002 |
Niyazi Serdar Sariciftci | 99 | 591 | 54055 |
Lars Samuelson | 96 | 850 | 36931 |
Peter J. Oefner | 90 | 348 | 30729 |
Dmitri V. Talapin | 90 | 303 | 39572 |
Tomás Torres | 88 | 625 | 28223 |
Ramesh Raskar | 86 | 670 | 30675 |
Siegfried Bauer | 84 | 422 | 26759 |
Alexander Eychmüller | 82 | 444 | 23688 |
Friedrich Schneider | 82 | 554 | 27383 |
Maksym V. Kovalenko | 81 | 360 | 34805 |