by the examples of two European research projects JHelioviewer and FLARECAST. Talk given for a Taiwanese delegation at the University of Applied Sciences FHNW, Switzerland.
FLARECAST - Das Automatische Vorhersagesystem für SonnenflaresFLARECAST
Vortrag zum Europäischen H2020 Forschungsprojekt FLARECAST an der Fachhochschule Nordwestschweiz FHNW: Über die Notwendigkeit, Sonnenflares besser vorhersagen zu können, die Kommunikation mit verschiedenen Nutzergruppen und den Einsatz von Machine Learning für die Automatisierung der Vorhersagen.
This is a workshop introducing participants to solar observation and forecasting solar flares preparing them to contribute to the Sunspotter citizen science project. Developed in the context of the FLARECAST public engagement programme, it can be used by anyone interested in communicating solar science.
FLARECAST - Das Automatische Vorhersagesystem für SonnenflaresFLARECAST
Vortrag zum Europäischen H2020 Forschungsprojekt FLARECAST an der Fachhochschule Nordwestschweiz FHNW: Über die Notwendigkeit, Sonnenflares besser vorhersagen zu können, die Kommunikation mit verschiedenen Nutzergruppen und den Einsatz von Machine Learning für die Automatisierung der Vorhersagen.
This is a workshop introducing participants to solar observation and forecasting solar flares preparing them to contribute to the Sunspotter citizen science project. Developed in the context of the FLARECAST public engagement programme, it can be used by anyone interested in communicating solar science.
Uv sensor that measures ‘hidden’ origins of space weatherSherry Huang
A physicist at the National Institute of Standards and Technology (NIST) has helped NASA scientists observe a “hidden” layer of the Sun where violent space weather can originate, by positioning a crucial UV sensor inside a space-borne instrument.
Better Hackathon 2020 ETHZ - Comparing Static And Dynamic Effects Of EarthquakesPRBETTER
As part of the final BETTER Hackathon, project partners prepared 4 hackathon exercises. ETHZ organised this exercise as the challenge promoter for the Geohazards thematic area. This open exercise featured the use of Binder and purposely provided cloud resources but could also be run locally through a Docker image and Docker Compose. The focus of this half-day exercise was to find a convenient way of exploitation of Co-seismic interferograms, by using developed BETTER pipelines. The idea was to produce geocoded maps combining automatically the important results to have a convenient visualisation that helps interpreting results.Participants were expected to be familiar with the Jupyter environment (Python 3) and the most common EO libraries (e.g. GDAL). The recorded part includes the introduction of the exercise in the context of the BETTER project.
We show how deep learning can be effectively applied to remote sensing. Many problems we faced, solutions we have had discovered were highlighted too. Remotely sensed data, unlike other vision tasks are very challenging and posses extra difficulties. Objects are very small compared to the image size, and even small pixel sizes of 8*10 pixel can contain huge amount of informations.
To the best of our knowledge there is no automated or simi-automated tool that uses deep learning to detect features from satellite imagery.
The Copernicus programme (REGULATION (EU) No 377/2014) is a cornerstone of the European Union´ efforts:
To monitor the Earth, its environment and ecosystems
To ensure its citizens are prepared and protected for crises, security risks and natural or man-made disasters
Copernicus as user driven Programme
Places a world of insight (data and information) about our planet at the disposal of citizens, public authorities and policy makers, scientists, entrepreneurs and businesses on a full, free and open basis
Is a tool for economic development and a driver for the digital economy
Quantifying Error in Training Data for Mapping and Monitoring the Earth System - A Workshop on “Quantifying Error in Training Data for Mapping and Monitoring the Earth System” was held on January 8-9, 2019 at Clark University, with support from Omidyar Network’s Property Rights Initiative, now PlaceFund.
Uv sensor that measures ‘hidden’ origins of space weatherSherry Huang
A physicist at the National Institute of Standards and Technology (NIST) has helped NASA scientists observe a “hidden” layer of the Sun where violent space weather can originate, by positioning a crucial UV sensor inside a space-borne instrument.
Better Hackathon 2020 ETHZ - Comparing Static And Dynamic Effects Of EarthquakesPRBETTER
As part of the final BETTER Hackathon, project partners prepared 4 hackathon exercises. ETHZ organised this exercise as the challenge promoter for the Geohazards thematic area. This open exercise featured the use of Binder and purposely provided cloud resources but could also be run locally through a Docker image and Docker Compose. The focus of this half-day exercise was to find a convenient way of exploitation of Co-seismic interferograms, by using developed BETTER pipelines. The idea was to produce geocoded maps combining automatically the important results to have a convenient visualisation that helps interpreting results.Participants were expected to be familiar with the Jupyter environment (Python 3) and the most common EO libraries (e.g. GDAL). The recorded part includes the introduction of the exercise in the context of the BETTER project.
We show how deep learning can be effectively applied to remote sensing. Many problems we faced, solutions we have had discovered were highlighted too. Remotely sensed data, unlike other vision tasks are very challenging and posses extra difficulties. Objects are very small compared to the image size, and even small pixel sizes of 8*10 pixel can contain huge amount of informations.
To the best of our knowledge there is no automated or simi-automated tool that uses deep learning to detect features from satellite imagery.
The Copernicus programme (REGULATION (EU) No 377/2014) is a cornerstone of the European Union´ efforts:
To monitor the Earth, its environment and ecosystems
To ensure its citizens are prepared and protected for crises, security risks and natural or man-made disasters
Copernicus as user driven Programme
Places a world of insight (data and information) about our planet at the disposal of citizens, public authorities and policy makers, scientists, entrepreneurs and businesses on a full, free and open basis
Is a tool for economic development and a driver for the digital economy
Quantifying Error in Training Data for Mapping and Monitoring the Earth System - A Workshop on “Quantifying Error in Training Data for Mapping and Monitoring the Earth System” was held on January 8-9, 2019 at Clark University, with support from Omidyar Network’s Property Rights Initiative, now PlaceFund.
Talk by Dr. Ioannis Kontogiannis on the occasion of a school visit at the Aikaterini Laskarides Foundation Athens, Greece: The Sun, the star in our solar system, what it means for the earth, how it works, how we observe it using telescopes and satellites, how it was observed in history, and how it produces weather in space.
Solar eruptions and their manifestation, solar flares, are the most spectacular phenomena in the solar system. Albeit fairly harmless for life on Earth, they do affect astronauts, space infrastructure and applications that rely on it. An accurate solar flare prediction is, therefore, necessary to protect space-based infrastructure and personnel. To this end, Greece is coordinating scientists from six European countries via the European Commission FLARECAST project, aiming to produce an innovative solar flare prediction tool. The talk offers an introduction to prediction methods and tools, including the challenges these present (http://flarecast.eu/).
Talk by Dr. Ioannis Kontogiannis at Ellinogermaniki Agogi, Athens, Greece, about the European H2020 research project FLARECAST, including information about the Sun and its activity, the history of solar research, the workings of the magnetic sun, solar flares and their effects on Earth.
La couronne solaire : du calme à la tempêteFLARECAST
Présentation à lôccasion de ALCOR (Astronomie et Lumières du Campus d'Orsay) par Éric Buchlin
Institut d'astrophysique spatiale CNRS/Université Paris-Sud, Orsay, 23 Novembre 2016
Talk at the Interactive Exhibition of Science and Technology of Eugenides Foundation, Athens Greece, in January 4th 2006. It was given as part of the outreach of the FLARECAST project.
by the examples of FLARECAST and jHelioviewer.
Presentation held on the occasion of a Taiwanese delegation visiting the School of Engineering, FHNW Windisch, Switzerland.
André Csillaghy, October 2015
Artificial intelligence in space exploration venkat vajradhar - mediumvenkatvajradhar1
Since we can’t travel billions of years back in time not yet, anyway one of the best ways to understand how our universe evolved is to create computer simulations of the process using what we do know about it.
Objects close to the eye shut out much larger objects on the horizon; and splendors born only of the earth eclipse the stars. So it is with people who sometimes cover the entire disc of eternity with a dollar, and so quench transcendent glories with a little shining dust. ~ Edwin Hubbel Chapin
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
A Study of The Relationship Among Parameters of M/X Solar Flares via Associat...CSCJournals
This paper introduces a method to study the relation among parameters that can cause the origin of M/X solar flares. Solar flares, especially flares of types M and X, make the Earth’s atmosphere more ionized and have an effect on radio signals, which can cause disruptions in wireless communications. This situation points out to the need for better identification of the parameters involved in M/X solar flares. The method is based on four categorical parameters and their relations. Relations are demonstrated by association rules which were extracted by the APRIORI algorithm and the most promising rules were filtered by support and confidence metrics. Results of the most promising rules had been compared by application to different periods of the 23rd and the 24th solar cycles.
Nowadays, artificial intelligence has become a popular phenomenon in automation. If we talk about satellite communication, we know that maintaining a satellite every time is a big thing, because security, data and information are carried by the satellite and it is a major harm in the world.
Workshop for 7-9 year-old children about the magnetic Sun solar activity. They observe the Sun with telescopes and on satellite images, and build their own magnetic Sun. Part of the FLARECAST outreach programme.
This is a generic space weather forecast that can be adapted to your public event. Insert the latest images and videos from http://sdo.gsfc.nasa.gov/data, http://helioviewer.ias.u-psud.fr/helioviewer and, for the latest auroras, http://spaceweathergallery.com.
We designed it for science fair-like situations with passer byes stopping wherever they find something that catches their interest. We combined it with sunspot observation using several telescopes and hands-on activities related to ultraviolet light.
When we first presented the forecast, we soon realized that all those wonderful slides we had prepared were too much for the audience. There were simply too many new concepts involved. The very idea of there existing such a thing as weather in space was new to most visitors. We spent much more time discussing every single slide than expected. So we radically reduced the number of slides to five and focused on data/images where phenomena can directly be observed.
Of course, this may be adapted if the situation is more like that of a regular talk and the audience more familiar with the topic.
This workshop introduces 10-13 years old children to space weather, solar-flare forecasting and the SunSpotter citizen science project.
Hanna Sathiapal, FLARECAST outreach 2015-2017
Die Sonne beobachten und Sonnenexplosionen vorhersagenFLARECAST
Eine andere Version der Präsentation zum Kinderworkshop Einführung in SunSpotter Citizen Science am Ferienplausch, Hochschule für Technik FHNW Windisch, Switzerland
André Csillaghy, April 2016
Die Sonne beobachten und Sonnenexplosionen vorhersagenFLARECAST
Präsentation zum Kinderworkshop Einführung in SunSpotter Citizen Science am Ferienplausch, Hochschule für Technik FHNW Windisch, Switzerland
Marco Soldati, August 2015
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...pchutichetpong
M Capital Group (“MCG”) expects to see demand and the changing evolution of supply, facilitated through institutional investment rotation out of offices and into work from home (“WFH”), while the ever-expanding need for data storage as global internet usage expands, with experts predicting 5.3 billion users by 2023. These market factors will be underpinned by technological changes, such as progressing cloud services and edge sites, allowing the industry to see strong expected annual growth of 13% over the next 4 years.
Whilst competitive headwinds remain, represented through the recent second bankruptcy filing of Sungard, which blames “COVID-19 and other macroeconomic trends including delayed customer spending decisions, insourcing and reductions in IT spending, energy inflation and reduction in demand for certain services”, the industry has seen key adjustments, where MCG believes that engineering cost management and technological innovation will be paramount to success.
MCG reports that the more favorable market conditions expected over the next few years, helped by the winding down of pandemic restrictions and a hybrid working environment will be driving market momentum forward. The continuous injection of capital by alternative investment firms, as well as the growing infrastructural investment from cloud service providers and social media companies, whose revenues are expected to grow over 3.6x larger by value in 2026, will likely help propel center provision and innovation. These factors paint a promising picture for the industry players that offset rising input costs and adapt to new technologies.
According to M Capital Group: “Specifically, the long-term cost-saving opportunities available from the rise of remote managing will likely aid value growth for the industry. Through margin optimization and further availability of capital for reinvestment, strong players will maintain their competitive foothold, while weaker players exit the market to balance supply and demand.”
Opendatabay - Open Data Marketplace.pptxOpendatabay
Opendatabay.com unlocks the power of data for everyone. Open Data Marketplace fosters a collaborative hub for data enthusiasts to explore, share, and contribute to a vast collection of datasets.
First ever open hub for data enthusiasts to collaborate and innovate. A platform to explore, share, and contribute to a vast collection of datasets. Through robust quality control and innovative technologies like blockchain verification, opendatabay ensures the authenticity and reliability of datasets, empowering users to make data-driven decisions with confidence. Leverage cutting-edge AI technologies to enhance the data exploration, analysis, and discovery experience.
From intelligent search and recommendations to automated data productisation and quotation, Opendatabay AI-driven features streamline the data workflow. Finding the data you need shouldn't be a complex. Opendatabay simplifies the data acquisition process with an intuitive interface and robust search tools. Effortlessly explore, discover, and access the data you need, allowing you to focus on extracting valuable insights. Opendatabay breaks new ground with a dedicated, AI-generated, synthetic datasets.
Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
As Europe's leading economic powerhouse and the fourth-largest hashtag#economy globally, Germany stands at the forefront of innovation and industrial might. Renowned for its precision engineering and high-tech sectors, Germany's economic structure is heavily supported by a robust service industry, accounting for approximately 68% of its GDP. This economic clout and strategic geopolitical stance position Germany as a focal point in the global cyber threat landscape.
In the face of escalating global tensions, particularly those emanating from geopolitical disputes with nations like hashtag#Russia and hashtag#China, hashtag#Germany has witnessed a significant uptick in targeted cyber operations. Our analysis indicates a marked increase in hashtag#cyberattack sophistication aimed at critical infrastructure and key industrial sectors. These attacks range from ransomware campaigns to hashtag#AdvancedPersistentThreats (hashtag#APTs), threatening national security and business integrity.
🔑 Key findings include:
🔍 Increased frequency and complexity of cyber threats.
🔍 Escalation of state-sponsored and criminally motivated cyber operations.
🔍 Active dark web exchanges of malicious tools and tactics.
Our comprehensive report delves into these challenges, using a blend of open-source and proprietary data collection techniques. By monitoring activity on critical networks and analyzing attack patterns, our team provides a detailed overview of the threats facing German entities.
This report aims to equip stakeholders across public and private sectors with the knowledge to enhance their defensive strategies, reduce exposure to cyber risks, and reinforce Germany's resilience against cyber threats.
1. Big Data in Science
by the examples of two European research projects:
JHelioviewer and FLARECAST
Institute of 4D Technologies & Data Science i4Ds
School of Engineering
University of Applied Sciences and Arts
Northwestern Switzerland FHNW
André Csillaghy, Simon Felix, Michael Graber
JHelioviewer
2. The tool offers new possibilities for
analyzing solar eruptions and the
ejection of huge masses of matter as
seen in this screenshot.
JHelioviewer is an ESA project.
i4Ds developed the 3D - functionalities.
JHelioviewer
Visualzation software for accessing large archives of high quality solar image data
JHelioviewer
3. Image: NASA/SDO
This is where most data processed by JHelioviewer come from:
the NASA’s spacecraft Solar Dynamic Observatory, a space telescope
delivering high resolution data in unprecedented quantities.
4. Solar activity affects the Earth.
When a solar storm hits the Earth,
charged particles from the sun
interact with the atmosphere
generating the polar lights.
This is the beautiful side of solar activity.
Image: Joshua Strang, United States Airforce
Why so much effort for understanding the sun?
5. However, there is also a downside to solar activity.
A solar storm hitting the Earth may affect
electronics both on the ground and in space.
The more dependent we become on space based
technology, the more important precautionary
measures are.
We study the sun to reliably predict space weather
in order to better protect our vulnerable assets on
the ground and in space.
6. FLARECAST
Flare Likelihood and Region Eruption Forecasting
FLARECAST is a European research project for developing
a fully automated solar-flare forecasting system with
an unmatched accuracy compared to existing facilities.
Project partners
• University of Genova / CNR, Italy
• Trinity College Dublin, Ireland
• Met Office, UK
• Academy of Sciences Athens, Greece
• University of Paris Sud / CNRS, France
• University of Applied Sciences and the Arts FHNW, Switzerland
7. FLARECAST will analyze huge amounts of data in order to develop an
automatic prediction system for future space weather events.
Image: quadtec.com
8. Information of interest are extracted from images
using advanced image processing techniques.
Image: NASA/SDO
9. We use machine learning algorithms for automatic detection of structures and
features on the solar surface. The result will be a software that automatically
predicts the risk of a solar explosion.
Graph: datarobot.com
10. Once successfully implemented for big data
sets in space weather prediction, the prediction
system will be transferred to other areas such
as energy management, transportation or the
management of large cities.