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Artículo
Two deep learning approaches to forecasting disaggregated freight flows: convolutional and encoder–decoder recurrent
(Springer, 2021)
Time series forecasting of disaggregated freight flow is a key issue in decision-making by port authorities. For this purpose and to test new deep learning techniques we have selected seven time series of imported goods ...
Artículo
DISCERNER: Dynamic selection of resource manager in hyper-scale cloud-computing data centres
(Elsevier, 2021)
Data centres constitute the engine of the Internet, and run a major portion of large web and mobile applications, content delivery and sharing platforms, and Cloud-computing business models. The high performance of such ...
Artículo
Machine learning regression to boost scheduling performance in hyper-scale cloud-computing data centres
(Elsevier, 2022)
Data centres increase their size and complexity due to the increasing amount of heterogeneous work loads and patterns to be served. Such a mix of various purpose workloads makes the optimisation of resource management ...
Artículo
SLA-aware operational efficiency in AI-enabled service chains: challenges ahead
(Springer, 2022)
Service providers compose services in service chains that require deep integra tion of core operational information systems across organizations. Additionally, advanced analytics inform data-driven decision-making in ...
Artículo
Statistically Representative Metrology of Nanoparticles via Unsupervised Machine Learning of TEM Images
(MDPI, 2021)
The morphology of nanoparticles governs their properties for a range of important applica tions. Thus, the ability to statistically correlate this key particle performance parameter is paramount in achieving accurate ...
Artículo
Integrating pathway knowledge with deep neural networks to reduce the dimensionality in single-cell RNA-seq data
(BMC, 2022)
Background: Single-cell RNA sequencing (scRNA-seq) data provide valuable insights into cellular heterogeneity which is significantly improving the current knowledge on biology and human disease. One of the main applications ...
Artículo
Improving models for environmental applications of LiDAR: Novel approaches based on soft computing
(IOS Press, 2016)
This work proposes novel methodologies to improve the use of Light Detection And Ranging (LiDAR) for environ mental purposes, especially for thematic mapping (LiDAR only or fused with other remote sensors) and the estimation ...
Artículo
Automated Deployment of a Spark Cluster with Machine Learning Algorithm Integration
(Elsevier, 2020)
The vast amount of data stored nowadays has turned big data analytics into a very trendy research field. The Spark distributed computing platform has emerged as a dominant and widely used paradigm for cluster deployment ...
Artículo
LEAPME: learning-based property matching with embeddings
(Elsevier, 2022)
Data integration tasks such as the creation and extension of knowledge graphs involve the fusion of heterogeneous entities from many sources. Matching and fusion of such entities require to also match and combine their ...
Artículo
CAFE: Knowledge graph completion using neighborhood-aware features
(Elsevier, 2021)
Knowledge Graphs (KGs) currently contain a vast amount of structured information in the form of entities and relations. Because KGs are often constructed automatically by means of information extraction processes, they ...