Zobrazeno 1 - 10
of 201
pro vyhledávání: '"Martı́nez, Iñigo"'
Autor:
Martinez, Iñigo
The proliferation and ubiquity of temporal data across many disciplines has sparked interest for similarity, classification and clustering methods specifically designed to handle time series data. A core issue when dealing with time series is determi
Externí odkaz:
http://arxiv.org/abs/2309.14029
The correct functioning of photovoltaic (PV) cells is critical to ensuring the optimal performance of a solar plant. Anomaly detection techniques for PV cells can result in significant cost savings in operation and maintenance (O&M). Recent research
Externí odkaz:
http://arxiv.org/abs/2212.07768
Time series alignment methods call for highly expressive, differentiable and invertible warping functions which preserve temporal topology, i.e diffeomorphisms. Diffeomorphic warping functions can be generated from the integration of velocity fields
Externí odkaz:
http://arxiv.org/abs/2206.08107
Publikováno v:
2021 IEEE International Conference on Big Data, pages 2313-2318
In recent years, the data science community has pursued excellence and made significant research efforts to develop advanced analytics, focusing on solving technical problems at the expense of organizational and socio-technical challenges. According
Externí odkaz:
http://arxiv.org/abs/2201.06310
Autor:
Martinez, Iñigo, Otamendi, Urtzi, Olaizola, Igor G., Solsona, Roger, Maiza, Mikel, Viles, Elisabeth, Fernandez, Arturo, Arzua, Ignacio
Accurate temperature measurements are essential for the proper monitoring and control of industrial furnaces. However, measurement uncertainty is a risk for such a critical parameter. Certain instrumental and environmental errors must be considered w
Externí odkaz:
http://arxiv.org/abs/2201.04069
Publikováno v:
Building and Environment Volume 207, Part B, January 2022, 108495
Recent evidence suggests that SARS-CoV-2, which is the virus causing a global pandemic in 2020, is predominantly transmitted via airborne aerosols in indoor environments. This calls for novel strategies when assessing and controlling a building's ind
Externí odkaz:
http://arxiv.org/abs/2111.01484
Autor:
Otamendi, Urtzi, Martinez, Iñigo, Quartulli, Marco, Olaizola, Igor G., Viles, Elisabeth, Cambarau, Werther
Publikováno v:
Solar Energy, Volume 220, 2021
In the operation & maintenance (O&M) of photovoltaic (PV) plants, the early identification of failures has become crucial to maintain productivity and prolong components' life. Of all defects, cell-level anomalies can lead to serious failures and may
Externí odkaz:
http://arxiv.org/abs/2106.10962
Publikováno v:
Intelligent Distributed Computing XII, 2018
A failure detection system is the first step towards predictive maintenance strategies. A popular data-driven method to detect incipient failures and anomalies is the training of normal behaviour models by applying a machine learning technique like f
Externí odkaz:
http://arxiv.org/abs/2106.09951
Publikováno v:
Communications in Transportation Research, Volume 2, December 2022
Rethinking cities is now more imperative than ever, as society faces global challenges such as population growth and climate change. The design of cities can not be abstracted from the design of its mobility system, and, therefore, efficient solution
Externí odkaz:
http://arxiv.org/abs/2106.09694
Publikováno v:
Big Data Research, Vol. 24, January 2021
Data science has employed great research efforts in developing advanced analytics, improving data models and cultivating new algorithms. However, not many authors have come across the organizational and socio-technical challenges that arise when exec
Externí odkaz:
http://arxiv.org/abs/2106.07287