相关论文: Learning from 25 years of the extensible N-Dimensi…

Radio science data collected from NASA's Deep Space Networks (DSNs) are made available in various formats through NASA's Planetary Data System (PDS). The majority of these data are packed in complex formats, making them inaccessible to…

Sky models used in radio interferometric data processing primarily consist of compact and discrete radio sources. When there is a need to model large scale diffuse structure such as the Galaxy, specialized source models are sought after for…

We have deluge of data in time series format for numerous phenomena. The number of snapshots, resolution and many other factors come into play as we look to identify the dynamics in a given problem. The pre-processing and post-processing…

In the era of mega-constellations, the need for accurate and publicly available information has become fundamental for satellite operators to guarantee the safety of spacecrafts and the Low Earth Orbit (LEO) space environment. This study…

Most research data collections created or used by astronomers are intrinsically multi-dimensional. In contrast, all visual representations of data presented within research papers are exclusively 2-dimensional. We present a resolution of…

The amount of collected data in many scientific fields is increasing, all of them requiring a common task: extract knowledge from massive, multi parametric data sets, as rapidly and efficiently possible. This is especially true in astronomy…

Modern scientific data mainly consist of huge datasets gathered by a very large number of techniques and stored in very diversified and often incompatible data repositories. More in general, in the e-science environment, it is considered as…

The standardisation of gamma-ray astronomical data emerged in recent years as a necessity for the future generation of gamma-ray observatories. Nevertheless, adopting a common format for gamma-ray instruments can already benefit the current…

In 2015, the United Nations put forward 17 Sustainable Development Goals (SDGs) to be achieved by 2030, where data has been promoted as a focus to innovating sustainable development and as a means to measuring progress towards achieving the…

In this paper, a novel data-driven approach named Augmented Imagefication for Fault detection (FD) of aircraft air data sensors (ADS) is proposed. Exemplifying the FD problem of aircraft air data sensors, an online FD scheme on edge device…

Non-negative matrix factorization (NMF) is a fundamental matrix decomposition technique that is used primarily for dimensionality reduction and is increasing in popularity in the biological domain. Although finding a unique NMF is generally…

Relational databases (DBs) are ideal tools to manage bulky and structured data archives. In particular for Astronomy they can be used to fulfill all the requirements of a complex project, i.e. the management of: documents, software (s/w)…

The FITS is the standard file format in astronomy, and it has been extended to agree with astronomical needs of the day. However, astronomical datasets have been inflating year by year. In case of ALMA telescope, a ~ TB scale 4-dimensional…

Data warehouse store and provide access to large volume of historical data supporting the strategic decisions of organisations. Data warehouse is based on a multidimensional model which allow to express user's needs for supporting the…

Nowadays, many scientific areas share the same broad requirements of being able to deal with massive and distributed datasets while, when possible, being integrated with services and applications. In order to solve the growing gap between…

The growing interconnection between software systems increases the need for security already at design time. Security-related properties like confidentiality are often analyzed based on data flow diagrams (DFDs). However, manually analyzing…

For the successful development of the astrophysics and, accordingly, for obtaining more complete knowledge of the Universe, it is extremely important to combine and comprehensively analyze information of various types (e.g., about charged…

The scale and quality of a dataset significantly impact the performance of deep models. However, acquiring large-scale annotated datasets is both a costly and time-consuming endeavor. To address this challenge, dataset expansion…

High-dimensional spatio-temporal dynamics can often be encoded in a low-dimensional subspace. Engineering applications for modeling, characterization, design, and control of such large-scale systems often rely on dimensionality reduction to…

Complex design problems are common in the scientific and industrial fields. In practice, objective functions or constraints of these problems often do not have explicit formulas, and can be estimated only at a set of sampling points through…