ACCESS-NRI’s Post

Know Locating. Paul Larkin and I have been around enough know a few things about locating. Do we know everything? No. But here's what we know for sure: 1.     Locating is 100% science where results are repeatable and predictable when all factors are known. 2.     All factors are never 100% known, so locating becomes a mix of art and science. 3. The art is knowing how to analyze information to determine the next step. Here's a throwback video shot on campus at Staking University in 2005. Paul and I team up to show the cause-and-effect of a far-end ground.

BrainPOP Science, our award-winning science solution 🏆 complements your curriculum to bring multi-dimensional science to life. Middle schoolers see themselves as scientists and engineers as they are guided through immersive investigations. See for yourself with a sample investigation: https://brnpop.co/42gn16x

This breakthrough could reduce the power consumption of AI data centers by 30%. Power is likely to grow from 24% of the operating cost to 38% given the growing demand for AI through 2026. NVDA out performs Intel in terms of perf/watt by 700 to 800%

Mapping the space of all possible #system states is itself a component artefact and configuration entity in the cartography it seeks to map. This kind of globally #recursive (as referential, relational) self-inflection is usually brushed under the carpet and left, deferred as "someone else's problem" and hardly if ever avails itself of linear self-enclosure. This offset and abrogate disavowal is a #function of the ways in which systems of knowledge and communication quite naturally* seek methods of protecting their own source code and primary control mechanism. This is a piece on #entropy, on combinatorial complexity. It vectors towards and aims somewhat beyond the effusive logical decompression that more maps, more models and yet more language invokes around themselves. There is a core, globally recursive discontinuity here - distributed in, across and as the entire surface of the possibility space it inflates with telos, experience, adaptive #learning or growth. The problem is not that there are not enough descriptions and #models of such a process, there are far too many models and descriptions. The absence of binding epistemological unity precisely is that unity. *assumption - unpacking this is larger than catered for by a LinkedIn post.

I am featured in the new QUT advertisement, check it out below! #Roboticsfortherealworld

🔍 Ever pondered the power of simulation-based experiential learning in research? 🤔 Join Dr. Trent Grundmeyer from Drake University as he delves into the fascinating realm of simulations in education. Watch now! #Research #Education #Simulation 🎓✨ https://lnkd.in/e69ffcr6

Super excited to talk and discuss deep learning for science and engineering at AMLD!

👀 In the evolving landscape of European #research and #innovation, building systems that are #InclusiveByDesign is essential for ensuring that all researchers and institutions can fully participate. Simplifying processes, streamlining information flow, and reducing the complexity of instruments are key to removing barriers and promoting greater #inclusivity across #Europe. As we anticipate the release of Prof. Manuel Heitor Manuel Heitor's report on the interim evaluation of #HorizonEurope this week, these reflections are particularly timely. Through the YERUN #FP10VideoSeries, #researchers and #researchmanagers from YERUN member universities share their perspectives on how inclusivity can shape the future of European research: 🔹 Prof. Daniela Kalafatovic, Sveučilište u Rijeci / University of Rijeka, shares her insights on the crucial need for higher investments to fund all quality research ideas with the potential for impact. ➡ https://lnkd.in/dK5SnHA5 🔹 Prof. Przemyslaw Zywiczynski, Nicolaus Copernicus University in Torunń, discusses how to widen participation in research funding. He highlights the need to simplify application procedures to boost participation of under-represented countries in research. ➡ https://lnkd.in/deun4xag 🔹 Prof. Felix Wensveen, Sveučilište u Rijeci / University of Rijeka, highlights that the key to improving access to research funds is enabling researchers to focus on answering the research questions. ➡ https://lnkd.in/dQ8Ep9jT 🔹 Prof. Sanja Bahun, University of Essex, emphasises the crucial role of social sciences, arts, and humanities in research, and the need for greater integration of these fields to make research funding inclusive-by-design and to unleash its full benefits. ➡ https://lnkd.in/dhTGEd_F 🔹Eevi Laukkanen, University of Eastern Finland, explains that excellent science, when inclusive and interdisciplinary, delivers excellent impact. ➡ https://lnkd.in/dXkU8SnB YERUN is dedicated to creating a more #attractive, #impactful, and #inclusive European #researchframework. Our vision for FP10 is to support high-quality research, encourage collaborative efforts, and provide equal opportunities. 👉 https://lnkd.in/d4G5d7Z9 👉 https://lnkd.in/dVJpqsfm

Reminder - NITheCS Mini-school: 'Vector lattices with a view to applications in stochastic processes' - Prof Bruce Watson (WITS, CoE-MaSS, NITheCS). Attend the 4th of 4 lectures online today @ 14h00 - https://buff.ly/3y5lJR2 #mathematics #vectorlattices

🌟 Exciting Update from Our Research Team! 🌟 I am thrilled to announce the publication of our latest research in the proceedings of SIAM SDM 2024. This work represents a significant leap forward in the use of generative models for environmental modeling, specifically in predicting scenes and events. 📄 Title: "Spatial-Temporal Augmented Adaptation via Cycle-Consistent Adversarial Network: An Application in Streamflow Prediction" 🤝 Collaboration: A big shout-out to my advisor Professor Xiaowei Jia, whose insights and expertise were invaluable throughout this research journey. 🔍 About the Research: In this study, we've taken cycle-consistent adversarial networks to new heights. By leveraging time series image sequences, our model learns to adapt images across diverse domains controlled by temporal variations. This technique allows us to accurately model weather impacts and transfer essential data from richly labeled domains to those with sparse labels, significantly enhancing prediction. 📖 Full paper: https://lnkd.in/df6SqCKg 🎥 Our presentation: https://lnkd.in/dqv_ai5T Your feedback and insights are welcome!