An Approach for Classication of Integrated Circuits by a Knowledge Conserving Library Concept

Abstract A simulation based analysis of analog and mixed analog/digital circuits on printed circuit board level requires a lot of information about the involved c omponents. Entering solely the data sheet information into a component library normally disregards structural knowledge which is well{known by the circuit designer. Therefore, the expert knowledge necessary for an optimum use of analysis tools is no more available. This paper presents an approach to overcome this problem. A concept to represent eciently expert knowledge and classication information is introduced and a classication of circuits which conserves the structural information is presented

An Approach for Classification of Integrated Circuits by a Knowledge Conserving Library Concept

A simulation based analysis of analog and mixed analog /digital circuits on printed circuit board level requires a lot of information about the involved components. Entering solely the data sheet information into a component library normally disregards structural knowledge which is well--known by the circuit designer. Therefore, the expert knowledge necessary for an optimum use of analysis tools is no more available. This paper presents an approach to overcome this problem. A concept to represent efficiently expert knowledge and classification information is introduced and a classification of circuits which conserves the structural information is presented. 1 Introduction Physical effects like electromagnetic interference and EMC In addition to component parameters the effective analysis of complex analog and mixed analog /digital components and applications concerning physical effects like electromagnetic interference and EMC needs structural knowledge about the components. Therefore..

Statement to an Insufficient Systematic Review on Viscum album L. Therapy

Up to 88% of oncological patients apply complementary therapies and up to 77% apply complementary mistletoe therapy in the context of integrative oncological approaches. An evidence-based consultation of oncological health professionals regarding complementary therapies used in Germany is missing. Therefore, a new S3-Guideline for Complementary Medicine in the Treatment of Oncological Patients is under development and is anticipated to be finalized in November 2020. It will be based on evidence-based publications and systematic reviews on complementary therapies in oncology. A recently published two-part systematic review on mistletoe treatment in oncology has been reevaluated. Methods. (e latest published systematic two-part review on mistletoe has been systematically proofread and checked in compliance with the Cochrane Handbook for Systematic Reviews of Intervention and the AMSTAR 2 (A MeaSurement Tool to Assess Systematic Reviews) tool. Results. (e here discussed two-part review is incomplete, lacks sound accuracy including insufficient assessment of the risk of bias, and contains imprecise statements. In addition, it does not sufficiently comply with the Cochrane Handbook for Systematic Reviews of Intervention and the AMSTAR 2 tool. Conclusion. In view of the approaching release of a new guideline in the field of complementary therapies in oncology, the present statement draws attention to a lack of profound methodology of conductance of a recently released systematic review on mistletoe. In consequence, a comprehensive overview of published mistletoe studies, i.e., a meta-analysis with a sound methodology of conductance, is necessary

Methoden- und Werkzeugentwicklung fuer den Mikrosystementwurf (METEOR). Teilvorhaben: Entwurf von Mikrosystemen unter Stoerungsgesichtspunkten Teilprojekte 1 und 2: Entwurfsumgebungen. Werkzeuge und Schnittstellen. Sachbericht

SIGLEAvailable from TIB Hannover: F98B889+a / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekBundesministerium fuer Bildung, Wissenschaft, Forschung und Technologie, Bonn (Germany)DEGerman

Industrial Digitalization in the Industry 4.0 era: Classification, Reuse and Authoring of Digital Models on Digital Twin Platforms

Digital Twins (DTs) are real-time digital models that allow for self-diagnosis, self-optimization and self-configuration without the need for human input or intervention. While DTs are a central aspect of the ongoing fourth industrial revolution (I4.0), this leap forward may be reserved for the established, large-cap companies since the adoption of digital technologies among Small and Medium-size Enterprises (SMEs) is still modest. The aim of the H2020 European Project "DIGITbrain" is to support a modular construction of DTs by reusing their fundamental building blocks, i.e., the Models that describe the behavior of the DT, their associated Algorithms and the Data required for the evaluation. By offering these building blocks as a service via a DT Platform (a Digital Twin Environment), the technical barriers among SMEs to adopt these technologies are lowered. This paper describes how digital models can be classified, reused and authored on such DT Platforms. Through experimental analyses of three industrial cases, the paper exemplifies how DTs are employed in relation to product assembly of agricultural robots, polymer injection molding, as well as laser-cutting and sheet-metal forming of aluminum

Artificial intelligence for hospital health care: Application cases and answers to challenges in european hospitals

The development and implementation of artificial intelligence (AI) applications in health care contexts is a concurrent research and management question. Especially for hospitals, the expectations regarding improved efficiency and effectiveness by the introduction of novel AI applications are huge. However, experiences with real-life AI use cases are still scarce. As a first step towards structuring and comparing such experiences, this paper is presenting a comparative approach from nine European hospitals and eleven different use cases with possible application areas and benefits of hospital AI technologies. This is structured as a current review and opinion article from a diverse range of researchers and health care professionals. This contributes to important improvement options also for pandemic crises challenges, e.g., the current COVID-19 situation. The expected advantages as well as challenges regarding data protection, privacy, or human acceptance are re-ported. Altogether, the diversity of application cases is a core characteristic of AI applications in hospitals, and this requires a specific approach for successful implementation in the health care sector. This can include specialized solutions for hospitals regarding human–computer interaction, data management, and communication in AI implementation projects. © 2021 by the authors. Licensee MDPI, Basel, Switzerland