Related papers: The challenge of the data in the SRCnetwork
In 2020, ~60PB of archived data will be accessible to the astronomers. But to analyze such a paramount data will be a challenging task. This is basically due to the computational model used to download the data from complex geographically…
The increasing amount of Linked Data and its inherent distributed nature have attracted significant attention throughout the research community and amongst practitioners to search data, in the past years. Inspired by research results from…
The amount of data in the world is expanding rapidly. Every day, huge amounts of data are created by scientific experiments, companies, and end users' activities. These large data sets have been labeled as "Big Data", and their storage,…
Without sufficient information about research data practices occurring in a particular research organisation, there is a risk of mismatching research data service efforts with the needs of its researchers. This study describes how data…
The Square Kilometre Array (SKA) is the next generation radio telescope distinguished by a superb sensitivity due to its large aperture (about one square kilometre) and advanced instrumentation. It will cover a broad range of observing…
The Square Kilometre Array (SKA, https://skatelescope.org) will be the world's largest radio telescope. SKA Science Data Challenges will be regularly issued to the community as part of the science preparatory activities. The purpose of…
This decade, the Square Kilometre Array (SKA) will perform its first observations. Preparations for building dishes, antennas, correlators and infrastructure are well underway. Concurrently, software for the processing of SKA observations…
The possibility of using the SKA for occasional support of scientific space missions should be considered, along with all other science goals, in the design of the array. The benefits of higher data rates from distant spacecraft during high…
Data collected by large-scale instruments, observatories, and sensor networks are key enablers of scientific discoveries in many disciplines. However, ensuring that these data can be accessed, integrated, and analyzed in a democratized and…
With the rapid growth of different massive applications and parallel flow requests in Data Center Networks (DCNs), today's providers are confronting challenges in flow forwarding decisions. Since Software Defined Networking (SDN) provides…
Modelling multiple network data is crucial for addressing a wide range of applied research questions. However, there are many challenges, both theoretical and computational, to address. Network cycles are often of particular interest in…
The Square Kilometre Array (SKA) project is an international effort to build the world's most sensitive radio telescope operating in the 50 MHz to 14 GHz frequency range. Construction of the SKA is divided into phases, with the first phase…
Neural Networks (NNs) have been extensively used for a wide spectrum of real-world regression tasks, where the goal is to predict a numerical outcome such as revenue, effectiveness, or a quantitative result. In many such tasks, the point…
We propose and preliminarily implement a data-mining based platform to assist experts to inspect the increasing amount of spectra with low signal to noise ratio (SNR) generated by large sky surveys. The platform includes three layers:…
The Italian National Health Service is adopting Artificial Intelligence through its technical agencies, with the twofold objective of supporting and facilitating the diagnosis and treatment. Such a vast programme requires special care in…
Advances in technology and computing hardware are enabling scientists from all areas of science to produce massive amounts of data using large-scale simulations or observational facilities. In this era of data deluge, effective coordination…
Basic principles of statistical inference are commonly violated in network data analysis. Under the current approach, it is often impossible to identify a model that accommodates known empirical behaviors, possesses crucial inferential…
The next generation of radio astronomy telescopes are challenging existing data analysis paradigms, as they have an order of magnitude more antennas and larger bandwidth. Foremost amongst these are deep spectral line surveys, because these…
As the amount of data on the World Wide Web continues to grow exponentially, access to semantically structured information remains limited. The Semantic Web has emerged as a solution to enhance the machine-readability of data, making it…
In this paper, a stochastic approximation (SA) based distributed algorithm is proposed to solve the resource allocation (RA) with uncertainties. In this problem, a group of agents cooperatively optimize a separable optimization problem with…