Marie Ullmann

This year, The Nobel Prize in Physics was awarded to scientists who made considerable contributions to Artificial Intelligence research, marking a significant indicator of the advancements in #Computational Sciences. But how can #Physics relate to #ArtificialIntelligence? Big scientific experiments, like the ones in the #LHC, produce a vast amount of data. Identifying rare events or new particles in a big dataset is like finding a needle in a haystack! With challenges such as the High-Luminosity LHC leading to more data generated by the LHC experiments, #Technology that helps select the events worth analysing is essential. AI algorithms are perfectly suited to help process and analyse this data. For example, they can help recognise patterns and anomalies that might indicate new physics phenomena. At CERN, #CERNopenlab contributes to this area of innovation via collaborations with technology providers and research institutions that are developing state-of-the-art platforms, services, and methodologies. We aim to foster the widespread adoption of AI methods and techniques applicable to various AI use-cases, providing the community with access to specific expertise and resources. Many other fields face similar Big Data challenges and can profit from the innovations made within the #HEP community, such as #RadioAstronomy, #ClimateSciences and #HealthSciences. In our mission to accelerate #Computing for science, at CERN openlab we do R&D on AI and HPC through collaborations with our industry and research partners: E4 Computer Engineering SpA, Intel Corporation, Micron Technology, Oracle, Siemens, and Simons Foundation. Read more about this R&D activity 👇

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🎙️ Explore the frontier of human-robot collaboration in our podcast episode featuring Prof. Dr. Elsa Kirchner from the German Research Center for Artificial Intelligence. Discover the EXPECT project's advances in brain-machine interfaces and intuitive interaction. Listen to the episode 👉 https://bit.ly/447LMCL #HMI #BMI #AI #TechPodcast

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Discover easy database integration with Python & StellarDS.io! Our new blog post shows how to capture sensor data using a Raspberry Pi and Bosch BMP180 sensor. Plus, learn to visualize your data in a web app with JavaScript and Google Charts. Read the full tutorial here: 👉 https://lnkd.in/eUsaWVRE #python #StellarDS #DatabaseIntegration #IoT

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Research institutes produce some of the world’s most valuable data: research of human beings, animal/plant life, society’s and cultures, and so much more. Several public research institutes like Helmholtz-Zentrum Berlin (HZB) are using Nextcloud to safeguard research data and provide researchers the organizational and collaboration tools they need. In our blog, discover the Nextcloud software and key features that ensure confidentiality and data protection for research institutes. If you're a research institution, what do you need to protect your data and what tools are your researchers using? #Nextcloudhub #researchdata #dataprotection

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Semantic Interoperability Adds value to Cross-stakeholder Communications In this #oneM2M interview, Laura Daniele describes European Commission (EC) and industry initiatives leading up to a workshop on "Enhancing Semantic Interoperability by SAREF for Digital Twins." In outlining the business benefits, she explains why consumer appliance manufacturers, building managers and smart grid stakeholders want to learn about exchanging information collaboratively between connected devices, platforms and systems as well as across operational processes. European Commission, ETSI SmartM2M, TNO, #IoT #StandardsMatter, #ontology for #digitaltwins, AIOTI, Connectivity Standards Alliance, EEBUS Initiative e.V., ESMIG, HEDGE-IoT https://lnkd.in/eNeQ6KMn

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As #AI Robots are on the rise, are they the next big leap or an emerging risk? ⚙️ Despite industry skepticism persisting, the German Federal Ministry of Economics and Climate Protection plans to regulate their safe use through the launch of new testing centres. 📝🇩🇪 📖 Read the full article now to delve into the debate on AI's safety concerns, versus a future powered by robotics! 💪 🔗 https://lnkd.in/dqyTfTTe 📅 AI Everything Summit, 4 FEB 2025 📍 Abu Dhabi, UAE  📅 AI Everything Exhibition Showcase, 5-6 FEB 2025 📍 Dubai Exhibition Centre (DEC), UAE #AIRobots #MachineLearning #DeepLearning #AiEverythingGLOBAL #AiEG #ArtificialIntelligence #AiEverything #GITEXGLOBAL #GITEXAFRICA #GITEXEUROPE #DevSlam #NorthStarDubai #FintechSurge #FBSummit #MarketingMania #Xverse #Dubai #AbuDhabi #UAE

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The power dissipation of a phototransistor refers to the amount of power that the phototransistor can handle without overheating or getting damaged. It is measured in watts or milliwatts. Phototransistors have a maximum power dissipation rating, often denoted as "Pd". Read More: https://lnkd.in/d4YqRnBR #Insights #Photonics #Industry #Article #Imaging

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This paper proposed a novel #stochastic #geometry #framework to study the #downlink #coverage #performance in a #millimeter #wave (#mmWave) cellular network by jointly considering the polar coordinates of the #Base #Stations (#BSs) with respect to the typical user located at the origin. Specifically, both the Euclidean and the #angular #distances of the BSs in a maximum power-based association policy for the #user #equipment (#UE) are considered to account for realistic beam management considerations, which have been largely ignored in the literature, especially in the cell association phase. For completeness, two other association schemes are considered and exact-form expressions for the coverage probability are derived. Subsequently, the key role of angular distances is highlighted by defining the dominant interferer using angular distance-based criteria instead of Euclidean distance-based, and conducting a dominant interferer-based coverage probability analysis. ---- Harris K. Armeniakos, Athanasios (Thanasis) Kanatas, Harpreet Dhillon More details can be found at this link: https://lnkd.in/eGqS8DFC

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This letter proposes an #iterative #single-#head #attention (#ISHA) mechanism for #multi-#UAV path planning. The ISHA mechanism is run by a communication helper collecting the #state #embeddings of UAVs and distributing an attention score vector to each UAV. The #attention #scores computed by ISHA identify how many interactions with other UAVs should be considered in each UAV’s control #decision-#making. ----Hamid Shiri, Hyowoon Seo, Jihong Park, Mehdi Bennis More details can be found at this link: https://lnkd.in/eAN-ZyZT

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🌍 It's exciting to see external validations of our #PMcardio OMI AI Model from around the world, driven by pioneers like Dr. Sascha Macherey-Meyer and Dr. Christoph Adler from Uniklinik Köln. This study, presented at the biggest German cardiology congress – the 90th DGK Annual Meeting, showcased remarkable diagnostic results for occlusion myocardial infarction.   🔍 Key Highlights from the Validation: 🔹 1,770 chest pain patients evaluated 🔹 diagnostic accuracy of 95.3% 🏥 This study evaluated a retrospective cohort of acute chest pain patients who did not meet the traditional STEMI criteria and presented to German Chest Pain Units (CPU) over the course of 1 year. The outcomes emphasize the model’s precision and robust potential in emergencies, particularly its ability to accurately exclude acute occlusive myocardial infarctions with a specificity of 98.9% and a 100% negative predictive value. 🇩🇪 For more detailed insights, visit: https://lnkd.in/gPY-MEMq 💙 We're grateful to all our cooperating centers and look forward to welcoming more partners as we continue to push the boundaries of cardiovascular diagnostics using AI, with the ultimate goal of improving patient outcomes. #PowerfulMedical #UniklinikKöln #AIinHealthcare #ACS Deutsche Gesellschaft für Kardiologie – Herz- und Kreislaufforschung e.V.

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This paper offers a #Coalitional #Game-#based #Thermal-#aware #Adaptive #Scheduling (#CGTAS) tailored for #heterogeneous #Data #Centers (#DCs) to minimize the #cooling #cost #stemming from excessive heat generated during #compute-#intensive job execution. CGTAS intelligently differentiates incoming jobs based on their thermal profiles and #CPU-#time for optimal thermal outcomes. In addition, it dynamically allocates user jobs to #computing #nodes based on their #real-#time #marginal thermal performance using the Core solution concept from game theory. Finally, unlike existing #Thermal-#aware (#TA) strategies, the proposed design identifies thermally overloaded computing elements using the Core and performs task migrations to optimize #thermal #efficiency.----Saeed Akbar, @Ubaid Ul Akbar, Rahmat Ullah, Zhonglong Zheng More details can be found at this link: https://lnkd.in/gs4NCmVp

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