Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Stefan Thal"'
Publikováno v:
Respiratory Medicine Case Reports, Vol 36, Iss , Pp 101603- (2022)
Spontaneous pneumothorax (SP) in women of reproductive age with causes such as thoracic endometriosis syndrome (TES) presents a diagnostic and therapeutic challenge. A 33-year-old women was treated conservatively with chest tube insertion for a first
Externí odkaz:
https://doaj.org/article/23715a3c0afd48fea34c329391cf29d0
Autor:
Stefan Thal
Publikováno v:
physiopraxis. 2:20-25
Zirka ein Sechstel aller Menschen leidet unter chronischen Kopfschmerzen. Sie führen nicht selten zu verminderter Lebensqualität und zu regelmäßigem Medikamentenkonsum. Zudem sind die volkswirtschaftlichen Kosten beträchtlich. Physiotherapie hil
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6471a8dfaea1ae570da0d5c01ffb38f3
https://doi.org/10.1055/s-0032-1308389
https://doi.org/10.1055/s-0032-1308389
Publikováno v:
Journal of Theoretical and Applied Electronic Commerce Research, Vol 17, Iss 1, Pp 345-359 (2022)
Although research on risk management (RM) in small- and medium-sized enterprises (SMEs) in general and regarding supply chains (SCs) has increased recently, our understanding is still rather fragmented and underdeveloped. This refers particularly to
Externí odkaz:
https://doaj.org/article/7051772d67e64bf087d1ce6e1f1629de
Publikováno v:
Frontiers in Psychology, Vol 14 (2023)
Artificial Intelligence (AI) as decision support for personnel preselection, e.g., in the form of a dashboard, promises a more effective and fairer selection process. However, AI-based decision support systems might prompt decision makers to thoughtl
Externí odkaz:
https://doaj.org/article/7a8fdd7aade0445fb2146cb17acd3248
Publikováno v:
Administrative Sciences, Vol 13, Iss 11, p 231 (2023)
Despite the high potential of artificial intelligence (AI), its actual adoption in recruiting is low. Explanations for this discrepancy are scarce. Hence, this paper presents an exploratory interview study investigating HR professionals’ beliefs ab
Externí odkaz:
https://doaj.org/article/d9257095577e4f52a402d230856d8f9f
Autor:
Florian Königstorfer, Stefan Thalmann
Publikováno v:
Journal of Responsible Technology, Vol 11, Iss , Pp 100043- (2022)
Artificial Intelligence (AI) promises huge potential for businesses but due to its black-box character has also substantial drawbacks. This is a particular challenge in regulated use cases, where software needs to be certified or validated before dep
Externí odkaz:
https://doaj.org/article/d1159494642a470382c7b46980d125e4
Publikováno v:
Applied Sciences, Vol 13, Iss 5, p 3088 (2023)
Taking the multi-component perspective in Predictive Maintenance (PdM) is one promising approach to improve prediction quality. Therefore, detection and modeling of interdependencies within systems are important, especially as systems become more com
Externí odkaz:
https://doaj.org/article/c34fdb64e344457ba4a4a475e66b6a4e
Autor:
Peter Egger, Dominik Geringer, Gerwald Gindra-Vady, Christina Gruber, Elisabeth Paar, Lukas Reiter, Karl Stöger, Stefan Thalmann
Publikováno v:
Austrian Law Journal, Vol 6, Iss 1, Pp 37-53 (2019)
This paper discusses various legal challenges of the “digitisation of the single market”. The question arises to which extent the current regulatory framework appears suitable to deal with the presented challenges of digitisation and where addi
Externí odkaz:
https://doaj.org/article/d9ae44a59d514d949d175aac61550010
Autor:
Milot Gashi, Heimo Gursch, Hannes Hinterbichler, Stefan Pichler, Stefanie Lindstaedt, Stefan Thalmann
Publikováno v:
Sensors, Vol 22, Iss 8, p 2837 (2022)
Predictive Maintenance (PdM) is one of the most important applications of advanced data science in Industry 4.0, aiming to facilitate manufacturing processes. To build PdM models, sufficient data, such as condition monitoring and maintenance data of
Externí odkaz:
https://doaj.org/article/3fac0c24ebe141b896df7d7f383ca560
Autor:
Matej Vuković, Stefan Thalmann
Publikováno v:
Journal of Manufacturing and Materials Processing, Vol 6, Iss 1, p 10 (2022)
Industry 4.0 radically alters manufacturing organization and management, fostering collection and analysis of increasing amounts of data. Advanced data analytics, such as machine learning (ML), are essential for implementing Industry 4.0 and obtainin
Externí odkaz:
https://doaj.org/article/c82fc8b4147549c8b388b52c7657cc26