Unsupervised learning methods for molecular simulation data
Unsupervised learning is becoming an essential tool to analyze the increasingly large
amounts of data produced by atomistic and molecular simulations, in material science, solid …
amounts of data produced by atomistic and molecular simulations, in material science, solid …
A survey of IoT security based on a layered architecture of sensing and data analysis
The Internet of Things (IoT) is leading today's digital transformation. Relying on a
combination of technologies, protocols, and devices such as wireless sensors and newly …
combination of technologies, protocols, and devices such as wireless sensors and newly …
Improving the open cluster census-II. An all-sky cluster catalogue with Gaia DR3
EL Hunt, S Reffert - Astronomy & Astrophysics, 2023 - aanda.org
Context. Data from the Gaia satellite are revolutionising our understanding of the Milky Way.
With every new data release, there is a need to update the census of open clusters. Aims …
With every new data release, there is a need to update the census of open clusters. Aims …
[HTML][HTML] Predictive maintenance enabled by machine learning: Use cases and challenges in the automotive industry
A Theissler, J Pérez-Velázquez, M Kettelgerdes… - Reliability engineering & …, 2021 - Elsevier
Recent developments in maintenance modelling fueled by data-based approaches such as
machine learning (ML), have enabled a broad range of applications. In the automotive …
machine learning (ML), have enabled a broad range of applications. In the automotive …
[HTML][HTML] Obesity shapes metabolism in the tumor microenvironment to suppress anti-tumor immunity
Obesity is a major cancer risk factor, but how differences in systemic metabolism change the
tumor microenvironment (TME) and impact anti-tumor immunity is not understood. Here, we …
tumor microenvironment (TME) and impact anti-tumor immunity is not understood. Here, we …
Top2vec: Distributed representations of topics
D Angelov - arXiv preprint arXiv:2008.09470, 2020 - arxiv.org
Topic modeling is used for discovering latent semantic structure, usually referred to as
topics, in a large collection of documents. The most widely used methods are Latent Dirichlet …
topics, in a large collection of documents. The most widely used methods are Latent Dirichlet …
A connectomic study of a petascale fragment of human cerebral cortex
We acquired a rapidly preserved human surgical sample from the temporal lobe of the
cerebral cortex. We stained a 1 mm3 volume with heavy metals, embedded it in resin, cut …
cerebral cortex. We stained a 1 mm3 volume with heavy metals, embedded it in resin, cut …
[HTML][HTML] {FLAME}: Taming backdoors in federated learning
With the worldwide COVID-19 pandemic in 2020 and 2021 necessitating working from
home, corporate Virtual Private Networks (VPNs) have become an important item securing …
home, corporate Virtual Private Networks (VPNs) have become an important item securing …
Dark patterns at scale: Findings from a crawl of 11K shopping websites
Dark patterns are user interface design choices that benefit an online service by coercing,
steering, or deceiving users into making unintended and potentially harmful decisions. We …
steering, or deceiving users into making unintended and potentially harmful decisions. We …
A comprehensive subcellular atlas of the Toxoplasma proteome via hyperLOPIT provides spatial context for protein functions
Apicomplexan parasites cause major human disease and food insecurity. They owe their
considerable success to highly specialized cell compartments and structures. These …
considerable success to highly specialized cell compartments and structures. These …