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7. Studie Vertriebskompass 2015/2016 / durchgeführt von der FH Aachen und der Siers & Collegen GmbH
(2015)
[Mehrere Beiträge]
(1997)
A Cooperative Work Environment for Evolutionary Software Development / Kurbel, K., Pietsch, W.
(1990)
This Research Briefing, issued in July 2010, concluded that:
- Small and medium-sized enterprises (SMEs) in Europe have long called for a matching legal form valid across the EU (similar to that of the European company (SE) for large firms)
- The main benefits would be the availability of uniform Europe-wide company structures, significant cost reductions for businesses and further integration of the internal market
- Given the differing national views regarding the concrete features of the new legal form there is currently no sign of an agreement being reached at the European level in the short term; however, it is possible that progress will be made in negotiations during the year
- The key issues being discussed in depth are company formation, transnationality and employee participation rights in the new European private company (SPE).
IT Products are viewed and managed differently depending on the perspectives and the stage within the life cycle. A model is presented that integrates different perspectives and stages serving as an aid for the analysis of business models and focused positioning of IT-products. Four generic business models are analysed with regard to the product management function in general and the positioning field for IT-products specifically: off-the-shelf (license), license plus service, project, and system service (incl. cloud computing).
A Portable Implementation of Index Sequential Input-Output [Part 1] / Kurbel, Karl; Pietsch, W.
(1986)
A Portable Implementation of Index Sequential Input-Output [Part 2] / Kurbel, Karl; Pietsch, W.
(1986)
Abschlussarbeiten FAQ / FGA
(2006)
Adaptive logistics : information management for planning and control of small series assembly
(2007)
Der folgende Bericht fasst Erfahrungen zusammen, die in großen Entwicklungsprojekten der Firma Ericsson über mehrere Jahre gesammelt wurden. Ziel war dabei nicht, agile Methoden und Techniken einzusetzen - Agilität war zu der Zeit noch kein Hype-Thema. Vielmehr wurden Schwächen in den eigenen Projekten identifiziert und verbessert. Der Erfahrungsbericht vergleicht Verbesserungen in diesen Projekten mit den Ansätzen der agilen Entwicklung. Als Ergebnis werden folgende Punkte festgehalten: Erstens, einige Praktiken und Werte der agilen Entwicklung lassen sich auch in Großprojekten einsetzen. Zweitens, bei der Skalierung für Großprojekte werden diese Praktiken langsamer getaktet. Drittens, agile Entwicklung ist nicht nur eine Reihe von Praktiken und Werten, agile Entwicklung ist vielmehr auch eine Frage der Entwicklungs- und Projektkultur. Diese kulturelle Änderung lässt sich in Großprojekten deutlich langsamer umsetzen.
AI-based systems are nearing ubiquity not only in everyday low-stakes activities but also in medical procedures. To protect patients and physicians alike, explainability requirements have been proposed for the operation of AI-based decision support systems (AI-DSS), which adds hurdles to the productive use of AI in clinical contexts. This raises two questions: Who decides these requirements? And how should access to AI-DSS be provided to communities that reject these standards (particularly when such communities are expert-scarce)? This chapter investigates a dilemma that emerges from the implementation of global AI governance. While rejecting global AI governance limits the ability to help communities in need, global AI governance risks undermining and subjecting health-insecure communities to the force of the neo-colonial world order. For this, this chapter first surveys the current landscape of AI governance and introduces the approach of relational egalitarianism as key to (global health) justice. To discuss the two horns of the referred dilemma, the core power imbalances faced by health-insecure collectives (HICs) are examined. The chapter argues that only strong demands of a dual strategy towards health-secure collectives can both remedy the immediate needs of HICs and enable them to become healthcare independent.
Supervised machine learning and deep learning require a large amount of labeled data, which data scientists obtain in a manual, and time-consuming annotation process. To mitigate this challenge, Active Learning (AL) proposes promising data points to annotators they annotate next instead of a subsequent or random sample. This method is supposed to save annotation effort while maintaining model performance.
However, practitioners face many AL strategies for different tasks and need an empirical basis to choose between them. Surveys categorize AL strategies into taxonomies without performance indications. Presentations of novel AL strategies compare the performance to a small subset of strategies. Our contribution addresses the empirical basis by introducing a reproducible active learning evaluation (ALE) framework for the comparative evaluation of AL strategies in NLP.
The framework allows the implementation of AL strategies with low effort and a fair data-driven comparison through defining and tracking experiment parameters (e.g., initial dataset size, number of data points per query step, and the budget). ALE helps practitioners to make more informed decisions, and researchers can focus on developing new, effective AL strategies and deriving best practices for specific use cases. With best practices, practitioners can lower their annotation costs. We present a case study to illustrate how to use the framework.
Allgemeines Steuerrecht
(2015)