129 research outputs found

    Report of CE on Weight DS

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    In this document, we report the result of our core experiment on the Weight DS. In the last meeting a decision is made to continue the Weight DS CE in order to address: an improvement of the Weight DS syntax which is currently part of the XM document; to demonstrate the benefit to have such component as a basic datatype to provide a large variety of functionalities for various DS; to accomodate for required MPEG-7 functionalities (such as ordering) [1], for specific DS’s (e.g., Segment DS, Semantic DS components)

    Creation of technological specifications for the use of different types of plastics for interior paneling in a low-volume sports car from Bugatti

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    Im folgenden Skript werden Kunststoffe zuerst allgemein betrachtet und ausgewähl-te Kunststoffe (NFK-PP, CFK, ABS-PC, PUR) dann tiefgreifend referiert und analy-siert. Materialkennwerte, Wirtschaftlichkeit und mögliche Einsatzgebiete stellen ei-nen Teil der betrachteten Parameter dar. Des Weiteren werden technologische Vor-gaben für die Konstruktion und Verbindungsmöglichkeiten für diese Werkstoffe herausgearbeitet und gegenübergestellt. Überdies werden innovative Kunststoffe vorgestellt. Naturfaserverstärkte Kunststoffe werden besonders eingehend betrach-tet und potentiell geeignete Klebstoffe (2 K, 1 K- Heißklebstoffe) werden geprüft und analysiert. Mit Das Referenzfahrzeug für die Betrachtung der Kunststoffe ist ein Kleinseriensportwagen von Bugatti

    On the Use of Generative AI to Support In-Line Process Monitoring in Zero-Defect Manufacturing

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    In recent years, the integration of new Artificial Intelligence (AI) techniques and capabilities has emerged as one of most promising research fields to aid the industrial development of smart and zero-defect manufacturing solu-tions. This study explores the potential of generative AI in this field and re-views novel opportunities enabled by generative AI methods, and Generative Adversarial Networks (GANs) in particular, to aid the generation of aug-mented datasets including realistic representations of anomalous process pat-terns. The result is an effective AI framework to learn specific defect features from real data, and reproduce them in an extended way, leading to synthetic but realistic image data that could be used to enhance defect detection and classification performances. The paper reviews the benefits and open chal-lenges associated with the implementation of these techniques, including state-of-the-art examples and real case studies in Additive Manufacturing

    Report of CE on Semantic DS

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    The Semantic DS allows describing the world depicted by the AV content and interpreting that world, i.e., the “about” of the AV content or depicted narrative reality, which sometimes is imaginary. This document reports on the core experiment on the Semantic DS [6]. The CE originally started at the Maui meeting in December 1999 [3]. Progress reports of the CE were provided at the Geneva meeting [1] and at the Beijing meeting [2]. In Beijing, some components of the Semantic DS were promoted to the XM: Semantic DS, Object DS, PersonObject DS, Event DS, State DS, MediaOccurrence DS, SemanticTime DS, SemanticLocation DS, UsageLabel D, and some semantic relations. The main tasks of this core experiment have been the following: 1) To refine the specification of the Semantic DS by solving identified issues; 2) To define the Conceptual DSs; 3) To recommend the standardization of more semantic relations; 4) To investigate the use of membership functions to describe the strength of relations; 5) To generate simple and complex semantic descriptions of multimedia material; 6) To implement a retrieval and browsing application/s that uses the generated descriptions and that shows the functionality of the UsageLabel D, the Conceptual DSs, the State DS, and membership functions for relations, especially; 7) To recommend changes and additions to the Semantic DS based on the results of the experiment. The retrieval application that the CE has accomplished two objectives: (1) to show the utility of the components of the Semantic DS in a retrieval scenario, and (2) to be the software for the MPEG-7 XM platform
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