Ein Kategorienschema zur Kennzeichnung der Tätigkeiten gewerblicher Arbeitnehmer in der Industrie. Ansatz, Entwicklung und Erprobung

"Mit den Feststellungen, daß sich ++ Berufsbezeichnungen und Ausbildungsberufsbilder einerseits zur Erfassung und Beschreibung von Tätigkeitsinhalten kaum eignen, ++ Arbeitsanalysen andererseits zwar Tätigkeitsinhalte abzu bilden vermögen, aber zu aufwendig sind und ihre Ergebnisse für eine übergeordnete Anwendung nicht verschlüssel- und vergleichbar sind, wird die Forderung nach einem handlichen, operablen, praktikablen und vielseitig anwendbaren Instrument zur Charakterisierung menschlicher Tätigkeiten (Tätigkeitsfunktionen) im Arbeitsprozeß erhoben. Nach dem Grundprinzip der Arbeitsteilung wird eine Betriebsaufgabe so lange und so weit in Teilaufgaben aufgegliedert, bis diese (im Rahmen von Mensch-Maschine- und Mensch-MenschSystemen) auf Menschen und Maschinen übertragen werden können. Für den Entwurf eines Schemas menschlicher Tätigkeitsfunktionen sind (innerhalb des Mensch-Maschine-Systems) nur die nicht mechanisierten, von Menschen ausgeübten Tätigkeiten relevant. Folgende Tätigkeitsfunktionen werden unterschieden: Manuelles Bearbeiten, Zusammenfügen/Verbinden/Zerlegen, Befördern mit Körperkraft, Steuern, Überwachen, Prüfen, Registrieren, Ordnen, Bestimmen von Prozeßdaten und Arbeitsabläufen, Menschen führen. Durch Einführung zusätzlicher Differenzierungskriterien kann der Informationsgehalt der einzelnen Tätigkeitsfunktionen und damit der des gesamten Tätigkeitschemas beträchtlich erhöht werdden. Das im Anhang dargestellte Tätigkeitsfunktionen-Schema ist das Ergebnis einer aus der Literatur entwickelten ersten Konzeption, die in wiederholten empirischen Arbeitsplatz- und Tätigkeitsanalysen, in Gesprächen und Diskussionen mit Fachleuten aus Betrieben und einschlägigen Forschungsinstituten zu ihrer jetzigen Endfassung überarbeitet wurde. Das Tätigkeitsschema hat sich dabei im großen und ganzen als brauchbares, empirisch anwendbares und praktikables Instrumentarium zur Erfassung und Beschreibung von Inhalten einfacher Tätigkeiten gewerblicher Arbeitnehmer erwiesen."Tätigkeitsmerkmale, Arbeiter, Klassifikation

Hierarchy and Dynamics of Neural Networks

Contains fulltext : 88364.pdf (publisher's version ) (Open Access

An Architecture Pattern Enabling Safety at Lower Cost and with Higher Performance

International audienceIn both avionic and automotive systems, it might become very costly and/or restricting the functional performance, to prove functions safe in all operational conditions and for 100% of the mission time. This is especially true if the quality of sensor data and of communication data may vary very much. One way to solve this trade-off paradox is to leave part of the safety assessment from design-time to run-time. This paper proposes a general architectural pattern for this, and also how to instantiate this pattern in Integrated Modular Avionics (IMA) for the avionic domain, and in AUTOSAR for the automotive domain. The solutions imply some extensions of ARINC 653 and of AUTOSAR respectively, but they are not in conflict with the existing concepts. The proposed solutions are also fully in-line what is prescribed by the standards for functional safety of the two domains

Cohort Profile: A European Multidisciplinary Network for the Fight against HIV Drug Resistance (EuResist Network)

: The EuResist cohort was established in 2006 with the purpose of developing a clinical decision-support tool predicting the most effective antiretroviral therapy (ART) for persons living with HIV (PLWH), based on their clinical and virological data. Further to continuous extensive data collection from several European countries, the EuResist cohort later widened its activity to the more general area of antiretroviral treatment resistance with a focus on virus evolution. The EuResist cohort has retrospectively enrolled PLWH, both treatment-naïve and treatment-experienced, under clinical follow-up from 1998, in nine national cohorts across Europe and beyond, and this article is an overview of its achievement. A clinically oriented treatment-response prediction system was released and made available online in 2008. Clinical and virological data have been collected from more than one hundred thousand PLWH, allowing for a number of studies on the response to treatment, selection and spread of resistance-associated mutations and the circulation of viral subtypes. Drawing from its interdisciplinary vocation, EuResist will continue to investigate clinical response to antiretroviral treatment against HIV and monitor the development and circulation of HIV drug resistance in clinical settings, along with the development of novel drugs and the introduction of new treatment strategies. The support of artificial intelligence in these activities is essential

First Magnetic Resonance Imaging-Guided Aortic Stenting and Cava Filter Placement Using a Polyetheretherketone-Based Magnetic Resonance Imaging-Compatible Guidewire in Swine: Proof of Concept

The purpose of this study was to demonstrate feasibility of percutaneous transluminal aortic stenting and cava filter placement under magnetic resonance imaging (MRI) guidance exclusively using a polyetheretherketone (PEEK)-based MRI-compatible guidewire. Percutaneous transluminal aortic stenting and cava filter placement were performed in 3 domestic swine. Procedures were performed under MRI-guidance in an open-bore 1.5-T scanner. The applied 0.035-inch guidewire has a PEEK core reinforced by fibres, floppy tip, hydrophilic coating, and paramagnetic markings for passive visualization. Through an 11F sheath, the guidewire was advanced into the abdominal (swine 1) or thoracic aorta (swine 2), and the stents were deployed. The guidewire was advanced into the inferior vena cava (swine 3), and the cava filter was deployed. Postmortem autopsy was performed. Procedural success, guidewire visibility, pushability, and stent support were qualitatively assessed by consensus. Procedure times were documented. Guidewire guidance into the abdominal and thoracic aortas and the inferior vena cava was successful. Stent deployments were successful in the abdominal (swine 1) and thoracic (swine 2) segments of the descending aorta. Cava filter positioning and deployment was successful. Autopsy documented good stent and filter positioning. Guidewire visibility through applied markers was rated acceptable for aortic stenting and good for venous filter placement. Steerability, pushability, and device support were good. The PEEK-based guidewire allows either percutaneous MRI-guided aortic stenting in the thoracic and abdominal segments of the descending aorta and filter placement in the inferior vena cava with acceptable to good device visibility and offers good steerability, pushability, and device suppor

Generating Synthetic Clinical Data that Capture Class Imbalanced Distributions with Generative Adversarial Networks: Example using Antiretroviral Therapy for HIV

Clinical data usually cannot be freely distributed due to their highly confidential nature and this hampers the development of machine learning in the healthcare domain. One way to mitigate this problem is by generating realistic synthetic datasets using generative adversarial networks (GANs). However, GANs are known to suffer from mode collapse thus creating outputs of low diversity. This lowers the quality of the synthetic healthcare data, and may cause it to omit patients of minority demographics or neglect less common clinical practices. In this paper, we extend the classic GAN setup with an additional variational autoencoder (VAE) and include an external memory to replay latent features observed from the real samples to the GAN generator. Using antiretroviral therapy for human immunodeficiency virus (ART for HIV) as a case study, we show that our extended setup overcomes mode collapse and generates a synthetic dataset that accurately describes severely imbalanced class distributions commonly found in real-world clinical variables. In addition, we demonstrate that our synthetic dataset is associated with a very low patient disclosure risk, and that it retains a high level of utility from the ground truth dataset to support the development of downstream machine learning algorithms.Comment: In the near future, we will make our codes and synthetic datasets publicly available to facilitate future research. Follow us on https://healthgym.ai

Revisited Upper Reference Limits for Highly Sensitive Cardiac Troponin T in Relation to Age, Sex, and Renal Function

(1) Background: Highly sensitive cardiac troponin T (hs-cTnT) plays an essential role in the diagnosis of myocardial injury. The upper reference limit of the respective assay is generally applied, irrespective of age, renal function, or sex. We aimed to identify age-adjusted and sex-adjusted upper reference limits in relation to renal function in a large population-based cohort without cardiac diseases. (2) Methods: We included 5428 subjects of the population-based LIFE-Adult cohort, free of diagnosed cardiac diseases. Sex-adjusted and age-adjusted 99th percentiles for hs-cTnT in subjects with preserved renal function were obtained. (3) Results: The hs-cTnT values were higher in men of all age groups. In both sexes, an increasing age positively correlated with higher hs-cTnT values. Hs-cTnT weakly correlated with serum creatinine. The three-dimensional analysis of age, creatinine, and hs-cTnT showed no relevant additional effect of creatinine on hs-cTnT. In men aged above 60 and women above 70, the calculated 99th percentiles clearly exceeded the commonly applied thresholds. (4) Conclusion: Age and sex have a major impact on the serum concentration of hs-cTnT, while renal function does not. We propose to consider age-adjusted and sex-adjusted reference values