Technical University of Dortmund

About: Technical University of Dortmund is a education organization based out in Dortmund, Nordrhein-Westfalen, Germany. It is known for research contribution in the topics: Context (language use) & Large Hadron Collider. The organization has 13028 authors who have published 27666 publications receiving 615557 citations. The organization is also known as: Dortmund University & University of Dortmund.

Polarized and unpolarized prompt photon production beyond the leading order.

Abstract: We calculate the complete [ital O]([alpha][alpha][sub [ital s]][sup 2]) corrections to the inclusive cross section for hadronic prompt photon production, both for the unpolarized case and for the case of longitudinal polarization for the incoming hadrons. We present analytical expressions for all our results.

The Health Effects of Aluminum Exposure.

Abstract: Background Aluminum is regularly taken up with the daily diet. It is also used in antiperspirants, as an adjuvant for vaccination, and in desensitization procedures. In this review, we present the scientifically documented harmful effects of aluminum on health and the threshold values associated with them.

Digitization of industrial work: development paths and prospects

Abstract: This paper summarizes considerations and preliminary research results on the consequences of the progressive use of digital technologies in industrial work. The focus is particularly on the situation in German industry, where this development has been intensively discussed as “Industry 4.0”. Starting point is the assumption that currently a far-reaching technology push in industrial production can be observed. In terms of the potential consequences for industrial labor foreseen by the literature, currently contradictory development scenarios are being discussed. For one thing, the volume of potential job losses caused by the new technologies is highly controversial. For another, diverging consequences for job activities and qualifications can be recognized, interpreted as the “upgrading”, respectively “polarization” of skills. What concrete changes actually occur however, is dependent on the influence of numerous factors. Especially, what concept of technology automation is realized in each case, and its respective implementation process, is significant here. The conclusion reached is that, in the medium term, at the most a somewhat limited spread of digital technologies and their consequences can be expected to occur.

What recommenders recommend: an analysis of recommendation biases and possible countermeasures

Abstract: Most real-world recommender systems are deployed in a commercial context or designed to represent a value-adding service, eg, on shopping or Social Web platforms, and typical success indicators for such systems include conversion rates, customer loyalty or sales numbers In academic research, in contrast, the evaluation and comparison of different recommendation algorithms is mostly based on offline experimental designs and accuracy or rank measures which are used as proxies to assess an algorithm's recommendation quality In this paper, we show that popular recommendation techniques--despite often being similar when compared with the help of accuracy measures--can be quite different with respect to which items they recommend We report the results of an in-depth analysis in which we compare several recommendations strategies from different perspectives, including accuracy, catalog coverage and their bias to recommend popular items Our analyses reveal that some recent techniques that perform well with respect to accuracy measures focus their recommendations on a tiny fraction of the item spectrum or recommend mostly top sellers We analyze the reasons for some of these biases in terms of algorithmic design and parameterization and show how the characteristics of the recommendations can be altered by hyperparameter tuning Finally, we propose two novel algorithmic schemes to counter these popularity biases