The use of concrete has been widespread in our society in housing and infrastructure, despite the environmental cost associated with its production. Its decay poses a social, economic, and environmental problem. Curre...
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This paper presents the summary of the Efficient Face Recognition Competition (EFaR) held at the 2023 International Joint Conference on Biometrics (IJCB 2023). The competition received 17 submissions from 6 different ...
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To address the challenges of sample utilization efficiency and managing temporal dependencies, this paper proposes an efficient path planning method for mobile robot in dynamic environments based on an improved twin d...
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To address the challenges of sample utilization efficiency and managing temporal dependencies, this paper proposes an efficient path planning method for mobile robot in dynamic environments based on an improved twin delayed deep deterministic policy gradient (TD3) algorithm. The proposed method, named PL-TD3, integrates prioritized experience replay (PER) and long short-term memory (LSTM) neural networks, which enhance both sample efficiency and the ability to handle time-series data. To verify the effectiveness of the proposed method, simulation and practical experiments were designed and conducted. In the simulation experiments, both static and dynamic obstacles were included in the test environment, along with experiments to assess generalization capabilities. The algorithm demonstrated superior performance in terms of both execution time and path efficiency. The practical experiments, based on the assumptions from the simulation tests, further confirmed that PL-TD3 has improved the effectiveness and robustness of path planning for mobile robot in dynamic environments.
Knowledge resource and information system/technology (IS/IT) capability have been considered to improve firm performance, however there is still a gap regarding the sustainability of supply chain to face and recover f...
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The operation of industrial facilities is a broad field for optimization. Industrial plants are often a) composed of several components, b) linked using network technology, c) physically interconnected and d) complex ...
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作者：
dos Santos, Paulo S.S.Mendes, Joãode Almeida, José M.M.M.Pastoriza-Santos, IsabelCoelho, Luís C.C.INESC TEC
Institute for Systems and Computer Engineering Technology and Science Rua Dr. Roberto Frias Porto4200-465 Portugal Faculty of Engineering
University of Porto Rua Dr. Roberto Frias Porto4200-465 Portugal Department of Physics
School of Science and Technology University of Trás-os-Montes e Alto Douro Vila Real5001-801 Portugal CINBIO
Universidad de Vigo Campus Universitario Lagoas Marcosende Vigo36310 Spain
Vigo36312 Spain FCUP
University of Porto Rua do Campo Alegre Porto4169-007 Portugal CIQUP
Chemistry Research Unit FCUP Univ. of Porto Porto4169-007 Portugal
The increasing demand for precise chemical and biological sensing has led to the development of highly efficient plasmonic optical fiber sensors. Therefore, it is essential to optimize and match the operating waveleng...
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The paper discusses the issues of using the tools of affective computations in the management of energy facilities, taking into account the emotional state of operators. The analysis of known approaches in this direct...
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ISBN:
(纸本)9781665407281
The paper discusses the issues of using the tools of affective computations in the management of energy facilities, taking into account the emotional state of operators. The analysis of known approaches in this direction of research is carried out. A diagram of the decision support process and a complex of management mechanisms are proposed, taking into account the use of emotionally colored information. The results of a computational experiment for the problem of classifying emotionally colored information are considered. To assess the emotional state of the operator, the best results can be obtained using a neural convolutional network.
This paper presents the summary of the Efficient Face Recognition Competition (EFaR) held at the 2023 International Joint Conference on Biometrics (IJCB 2023). The competition received 17 submissions from 6 different ...
This paper presents the summary of the Efficient Face Recognition Competition (EFaR) held at the 2023 International Joint Conference on Biometrics (IJCB 2023). The competition received 17 submissions from 6 different teams. To drive further development of efficient face recognition models, the submitted solutions are ranked based on a weighted score of the achieved verification accuracies on a diverse set of benchmarks, as well as the deployability given by the number of floating-point operations and model size. The evaluation of submissions is extended to bias, cross-quality, and large-scale recognition benchmarks. Overall, the paper gives an overview of the achieved performance values of the submitted solutions as well as a diverse set of baselines. The submitted solutions use small, efficient network architectures to reduce the computational cost, some solutions apply model quantization. An outlook on possible techniques that are underrepresented in current solutions is given as well.
Partnerships for science Education (PAFSE) is a case study of project-based learning applied to real-world problems connected with public health and sustainable development. The EU-funded project organizes science edu...
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