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pro vyhledávání: '"Neves, Miguel"'
An effective human-robot collaborative process results in the reduction of the operator's workload, promoting a more efficient, productive, safer and less error-prone working environment. However, the implementation of collaborative robots in industr
Externí odkaz:
http://arxiv.org/abs/2403.05306
Manufacturing assembly tasks can vary in complexity and level of automation. Yet, achieving full automation can be challenging and inefficient, particularly due to the complexity of certain assembly operations. Human-robot collaborative work, leverag
Externí odkaz:
http://arxiv.org/abs/2402.00708
Autor:
Terra-Neves, Miguel, Amaral, José, Lemos, Alexandre, Quintino, Rui, Resende, Pedro, Alegria, Antonio
Graph matching is a fundamental problem in pattern recognition, with many applications such as software analysis and computational biology. One well-known type of graph matching problem is graph isomorphism, which consists of deciding if two graphs a
Externí odkaz:
http://arxiv.org/abs/2312.09995
Autor:
Yang, Aidan Z. H., Brancas, Ricardo, Esteves, Pedro, Aparicio, Sofia, Nadkarni, Joao Pedro, Terra-Neves, Miguel, Manquinho, Vasco, Martins, Ruben
Data analysts use SQL queries to access and manipulate data on their databases. However, these queries are often challenging to write, and small mistakes can lead to unexpected data output. Recent work has explored several ways to automatically synth
Externí odkaz:
http://arxiv.org/abs/2310.03866
Autor:
Neves, Miguel Santos
Publikováno v:
Janus.net, Vol 8, Iss 1, Pp 88-118 (2017)
This article examines the challenges that globalisation poses to States and societies as well as the attempted response strategies, in particular the restructuring of external action based on an economic diplomacy approach, which was consolidated in
Externí odkaz:
https://doaj.org/article/231438e311b84514ad0b95429fa43348
Publikováno v:
Journal of Manufacturing Systems, 59, 426-440, 2021
The development of machine learning algorithms has been gathering relevance to address the increasing modelling complexity of manufacturing decision-making problems. Reinforcement learning is a methodology with great potential due to the reduced need
Externí odkaz:
http://arxiv.org/abs/2304.08375
Autor:
Neves, Miguel, Neto, Pedro
Publikováno v:
Int J Adv Manuf Technol 122, 4235-4245 (2022)
Deep reinforcement learning (DRL) has demonstrated its potential in solving complex manufacturing decision-making problems, especially in a context where the system learns over time with actual operation in the absence of training data. One interesti
Externí odkaz:
http://arxiv.org/abs/2304.06567
In recent years, more people have seen their work depend on data manipulation tasks. However, many of these users do not have the background in programming required to write complex programs, particularly SQL queries. One way of helping these users i
Externí odkaz:
http://arxiv.org/abs/2203.04995
Autor:
Almeida, Francisco C., Jesus, Tiago, Coelho, Ana, Quintas-Neves, Miguel, Gauthreaux, Kathryn, Teylan, Merilee A., Mock, Charles N., Kukull, Walter A., Crary, John F., Oliveira, Tiago Gil
Publikováno v:
In Neurobiology of Aging June 2024 138:10-18
Autor:
Neves, Miguel A.D., Ni, Tiffany T., Mackeigan, Daniel T., Shoara, Aron A., Lei, Xi, Slavkovic, Sladjana, Yu, Si-Yang, Stratton, Tyler W., Gallant, Reid C., Zhang, Dan, Xu, Xiaohong Ruby, Fernandes, Cheryl, Zhu, Guangheng, Hu, Xudong, Chazot, Noa, Donaldson, Logan W., Johnson, Philip E., Connelly, Kim, Rand, Margaret, Wang, Yiming, Ni, Heyu
Publikováno v:
In Research and Practice in Thrombosis and Haemostasis May 2024 8(4)