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The rapid evolution of artificial intelligence, especially through multi-modal large language models, has redefined user interactions, enabling responses that are contextually rich and human-like. As AI becomes an integral part of daily…
The Intelligence Studies Network is a comprehensive resource database for publications, events, conferences, and calls for papers in the field of intelligence studies. It offers a novel solution for monitoring, indexing, and visualising…
In science, the lifecycle of software products is typically managed with limited resources while facing unlimited demand. Scientific software requirements are necessarily often dominated by internal project specifications and deadlines, but…
Mercury is a federated metadata harvesting, search and retrieval tool based on both open source and software developed at Oak Ridge National Laboratory. It was originally developed for NASA, and the Mercury development consortium now…
ROScopter is a lean multirotor autopilot built for researchers. ROScopter seeks to accelerate simulation and hardware testing of research code with an architecture that is both easy to understand and simple to modify. ROScopter is designed…
Low-Earth orbit satellite networks can provide global broadband Internet access using constellations of thousands of satellites. Integrating edge computing resources in such networks can enable global low-latency access to compute services,…
The use of virtual data for enhancing the collaboration between large groups of scientists is explored in several ways: - by defining ``virtual'' parameter spaces which can be searched and shared in an organized way by a collaboration of…
Scientific analyses commonly compose multiple single-process programs into a dataflow. An end-to-end dataflow of single-process programs is known as a many-task application. Typically, tools from the HPC software stack are used to…
Robots have inherently limited onboard processing, storage, and power capabilities. Cloud computing resources have the potential to provide significant advantages for robots in many applications. However, to make use of these resources,…
Today's astronomical projects need computational systems capable to store and analyze large amounts of scientific data, to effectively share data with other research Institutes and to easily implement information services to present data…
eROSITA is the primary instrument on the Russian SRG mission. In the first four years of scientific operation after its launch, foreseen for 2014, it will perform a deep survey of the entire X-ray sky. In the soft X-ray band (0.5-2 keV),…
While automated experiments and high-throughput methods are becoming more mainstream in the age of data, empowering individual researchers to capture, collate, and contextualize their data faster and more reproducibly still remains a…
Life sciences research depends heavily on open-source academic software, yet many tools remain underused due to practical barriers. These include installation requirements that hinder adoption and limited developer resources for software…
The reuse of research software is central to research efficiency and academic exchange. The application of software enables researchers with varied backgrounds to reproduce, validate, and expand upon study findings. Furthermore, the…
Radio astronomy observatories with high throughput back end instruments require real-time data processing. While computing hardware continues to advance rapidly, development of real-time processing pipelines remains difficult and…
Performing astronomical data analysis using only personal computers is becoming impractical for the very large data sets produced nowadays. As analysis is not a task that can be automatized to its full extent, the idea of moving processing…
Exoplanet science often involves using the system parameters of real exoplanets for tasks such as simulations, fitting routines, and target selection for proposals. Several exoplanet catalogues are already well established but often lack a…
In recent decades the analysis of data has become increasingly computational. Correspondingly, this has changed how scientific and statistical work is shared. For example, it is now commonplace for underlying analysis code and data to be…
In recent years, the research community has raised serious questions about the reproducibility of scientific work. In particular, since many studies include some kind of computing work, reproducibility is also a technological challenge, not…
Increasing popularity of the serverless computing approach has led to the emergence of new cloud infrastructures working in Container-as-a-Service (CaaS) model like AWS Fargate, Google Cloud Run, or Azure Container Instances. They introduce…