Fraunhofer-Publica

The Fraunhofer-Publica has been successfully documenting the research results of the Fraunhofer-Gesellschaft for over 30 years. The platform enables the collaborative linking of research-relevant objects and disseminates within the international scientific community.

The Fraunhofer-Publica thus fulfils its responsibility to promote the transfer of knowledge and know-how to industry and society.

Categories

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Research outputs

As an application-oriented research organisation, Fraunhofer aims to conduct highly innovative and solution-oriented research - for the benefit of society and to strengthen the German and European economy.

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Projects

Fraunhofer is tackling the current challenges facing industry head on. By pooling their expertise and involving industrial partners at an early stage, the Fraunhofer Institutes involved in the projects aim to turn original scientific ideas into marketable products as quickly as possible.

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Researchers

Scientific achievement and practical relevance are not opposites - at Fraunhofer they are mutually dependent. Thanks to the close organisational links between Fraunhofer Institutes and universities, science at Fraunhofer is conducted at an internationally first-class level.

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Institutes

The Fraunhofer-Gesellschaft is the leading organisation for applied research in Europe. Institutes and research facilities work under its umbrella at various locations throughout Germany.

Recent Additions

  • Publication
    Verbesserte Rutschhemmung von Sicherheitsschuhen durch Berücksichtigung der individuellen Biomechanik des Trägers - RuBio
    ( 2023)
    Schlüter, Bernadette
    ;
    Koplin, Christof
    ;
    Jaeger, Raimund
    Im Projekt "Rubio" wurde untersucht, ob durch den Einfluss der Biomechanik des Trägers die Rutschsicherheit eines Sicherheitsschuhs maßgeblich beeinflusst wird. Hierzu wurde vom Projektpartner molibso eine Messanordnung entwickelt, mit der der Einfluss des individuellen Gangprofils auf die Rutschhemmung eines Sicherheitsschuhs analysiert und quantifiziert werden kann.
  • Publication
    Improved Decision Making in Venture Capital through Machine Learning?
    ( 2022)
    Niazi, Moska
    ;
    Sachs, Moritz Karl orcid-logo
    ;
    Unbescheiden, Matthias
    Im Rahmen dieser Arbeit soll untersucht werden, wie der Investitionsentscheidungsprozess in der Venture Capital Branche computergestützt verbessert werden kann. Dieser besteht aus den Schritten Deal Origination, Deal Screening, Deal Evaluation und Deal Structuring, welche durchlaufen werden, bevor es zu einer Investitionsentscheidung kommt. Nach einer Investition kommen noch die Post-Investment Activities hinzu. Das Ziel der Optimierung des Investitionsprozesses ist es, zum einen im Interesse der Venture Capital Fonds, die Fehlallokation von finanziellen Ressourcen zu reduzieren als auch die Produktivität im Unternehmen zu steigern. Zum anderen ist es im Interesse der Startup-Unternehmen, von potenziellen Investoren bemerkt und für die Umsetzung ihrer innovativen Ideen finanziert zu werden. Im letzten Jahrzehnt ist der Trend zum Einsatz von Softwaresystemen mit modernsten Big Data Technologien, wie z. B. der Künstlichen Intelligenz, in der Venture Capital Branche aufgefallen. Dieser führt zu einem technologischen Wettrüsten und einer Umstrukturierung der Branche. Hierdurch motiviert, ergeben sich eine Reihe neuer psychologischer und informationstechnischer Forschungspunkte rund um den kompletten Investitionsprozess. Ziel dieser Arbeit ist es, kognitive Biases und ihre Auswirkungen auf den Investitionsprozess zu beleuchten und begründete Vorschläge zu liefern, wie diese durch passende Methoden durch Decision Support Systems abgemildert oder erkannt werden können.
  • Publication
    Mitigating Bias in Venture Capital
    ( 2022)
    Liu, Yingqian
    ;
    Sachs, Moritz Karl orcid-logo
    ;
    Unbescheiden, Matthias
    Based on review from literatures, 11 bias plus 6 sub-bias, which are similarity bias (including religion background, syndication/network ties and social/personal ties), continuation bias (including sunk cost effects, escalation of commitment and status-quo bias), self-attribution bias, overconfidence bias, reputation bias, risk propensity bias, visual cues bias, linguistic presentation bias, mood/emotion bias, look-ahead bias and local bias, during decision making process from venture capitalists were summarized in this thesis, impacts on decision making process were indicated, available measures against specific bias were also mentioned. Furthermore, four traditional methods, which are Bayesian casual maps, repertory grid, analytical hierarchical process and analytical network process, to mitigate the overall bias were illustrated. Going forwards, some computer-based methods with help from machine learning were then being pointed out and described. At last, a conclusion was made, limitations and future works were outlooked.

Most viewed

  • Publication
    Chip array electrodes for simultaneous stripping analysis of trace metals
    ( 1995)
    Uhlig, A.
    ;
    Paeschke, M.
    ;
    Schnakenberg, U.
    ;
    Lisec, T.
    ;
    Hintsche, R.
  • Research Project
    01IN509B/5
  • Publication
    Production Planning and Control within Supply Chains
    ( 1996)
    Arnold, J.
    ;
    Dudenhausen, H.-M.
    ;
    Halmosi, H.
    A high degree of both complexity and uncertainty within supply chains make production planning and control difficult. Nowadays, several Production Planning and Control Systems try to optimise the supply chain's individual links, called manufacturing sites. Independent systems, i.e. systems which are not connected via networks, are not capable of planning and controlling the complete supply chain efficiently and effectively. The entities of a supply chain vary in market power, purchasing strategies, etc., and this leads to different relationships between them. In order to plan and control the entire supply chain a distributed, networked system is needed which is configurable for all structures within the chain. In this paper a generic and configurable planning and control component is presented with which a system for supply chains can be built modularly. Three case studies accompany the different planning approaches.