ETSI releases a Technical Report on autonomic network management and control applying machine learning and other AI algorithms

Sophia Antipolis, 5 March 2020

The ETSI Technical Committee on Core Network and Interoperability Testing (TC INT) has just released a Technical Report, ETSI TR 103 626, providing a mapping of architectural components for autonomic networking, cognitive networking and self-management. This architecture will serve the self-managing Future Internet.

The ETSI TR 103 626 provides a mapping of architectural components developed in the European Commission (EC) WiSHFUL and ORCA Projects, using the ETSI Generic Autonomic Networking Architecture (GANA) model.

The objective is to illustrate how the ETSI GANA model specified in the ETSI specification TS 103 195-2 can be implemented when using the components developed in these two projects. The Report also shows how the WiSHFUL architecture augmented with virtualization and hardware acceleration techniques can implement the GANA model. This will guide implementers of autonomics components for autonomic networks in their optimization of their GANA implementations.

The TR addresses autonomic decision-making and associated control-loops in wireless network architectures and their associated management and control architectures. The mapping of the architecture also illustrates how to implement self-management functionality in the GANA model for wireless networks, taking into consideration another Report ETSI TR 103 495, where GANA cognitive algorithms for autonomics, such as machine learning and other AI algorithms, can be applied.

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Location: East Hall
Organized By: Learning Seminar in Algebraic Combinatorics - Department of Mathematics

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Event Begins: Wednesday, November 13, 2024 12:00pm
Location: Tribute Room, 1322
Organized By: Sessions @ Michigan

Join us for an engaging "Lunch and Learn" event hosted by the Eileen Lappin Weiser Center for the Learning Sciences. As part of our inaugural series celebrating the theme of curiosity, we invite you to a thought-provoking conversation featuring Kishonna L. Gray, Professor of Information and Matthew Solomon, Professor of Film, Television, and Media, facilitated by Professors Natalie Davis and Jon Wargo.

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Bring your lunch, your questions, and your curiosity! Please register due to limited space.

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Please register (in-person or online) for each workshop you plan to attend. You can register for individual or multiple workshops. December 9, 2024 | 9:30am to 12:00pm (Africa/Addis_Ababa) | In-person and online December 9, 2024 | 1:00pm to 3:30pm (Africa/Addis_Ababa) | In-person and online December 10, 2024 | 9:30am to 12:45pm (Africa/Addis_Ababa) | In-person and […]

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scPROTEIN: a versatile deep graph contrastive learning framework for single-cell proteomics embedding  Nature.com

Imputation of label-free quantitative mass spectrometry-based proteomics data using self-supervised deep learning  Nature.com

A multi-species benchmark for training and validating mass spectrometry proteomics machine learning models  Nature.com

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We want to dedicate this episode to Bakker who passed away in August 2023, only a few months after giving her TED Talk. Her research and legacy continue to inspire.

TED Radio Hour+ subscribers now get access to bonus episodes, with more ideas from TED speakers and a behind the scenes look with our producers. A Plus subscription also lets you listen to regular episodes (like this one!) without sponsors. Sign-up at plus.npr.org/ted

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Artificial intelligence is powerful, but what about natural intelligence? This hour, TED speakers explore the intrinsic genius in animal language, insect behavior, plant anatomy and our immune system.

Guests include neuroscientist Greg Gage, computational neuroscientist Frances Chance, social psychoneuroimmunologist Keely Muscatell and environmental researcher Karen Bakker.

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