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Results: 57,874
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  • Larizatti Zacharias, L. G., di Beo Oliveira, L., Harano Alves, V., Guichet, X., & Peyerl, D. (2023). The Future of Diesel: Paths and New Alternatives to Energy Security and Sustainability. In D. Peyerl, S. Relva, & V. Da Silva (Eds.), Energy transition in Brazil (pp. 173-192). (The Latin American Studies Book Series). Springer. https://doi.org/10.1007/978-3-031-21033-4_11
  • da Silveira Cachola, C., Antunes Costa de Andrade, A. C., Schneid Lopes, L., Mateus Moretto, E., & Peyerl, D. (2023). Trends and Prospects for Transport Fuel Consumption in Brazil. In D. Peyerl, S. Relva, & V. Da Silva (Eds.), Energy transition in Brazil (pp. 193-210). (The Latin American Studies Book Series). Springer. https://doi.org/10.1007/978-3-031-21033-4_12
  • Vieira da Silva Filho, S., Oliveira Barbosa, M., & Peyerl, D. (2023). How Can Renewable Natural Gas Boost Sustainable Energy in Brazil? In D. Peyerl, S. Relva, & V. Da Silva (Eds.), Energy transition in Brazil (pp. 211-225). (The Latin American Studies Book Series). Springer. https://doi.org/10.1007/978-3-031-21033-4_13
  • Yoshiaki Kamigauti, L., Fontenelle, A. L., Coutinho, F., Heuminski de Ávila, A. M., & Peyerl, D. (2023). The Main Challenges of the Brazilian Energy Governance for the Mitigation and Adaptation to Climate Change. In D. Peyerl, S. Relva, & V. Da Silva (Eds.), Energy transition in Brazil (pp. 227-244). (The Latin American Studies Book Series). Springer. https://doi.org/10.1007/978-3-031-21033-4_14
  • Ciotta, M., Peyerl, D., & Larizatti Zacharias, L. G. (2023). Effect of the COVID-19 Pandemic on the Brazilian Energy Sector. In D. Peyerl, S. Relva, & V. Da Silva (Eds.), Energy transition in Brazil (pp. 245-258). (The Latin American Studies Book Series). Springer. https://doi.org/10.1007/978-3-031-21033-4_15
  • Peyerl, D., Relva, S., & Da Silva, V. (Eds.) (2023). Energy transition in Brazil. (The Latin American Studies Book Series). Springer. https://doi.org/10.1007/978-3-031-21033-4
  • Zhang, J., Cheng, L., Liu, C., Zhao, Z., & Mao, Y. (2023). Cost-aware scheduling systems for real-time workflows in cloud: An approach based on Genetic Algorithm and Deep Reinforcement Learning. Expert Systems With Applications, 234, Article 120972. https://doi.org/10.1016/j.eswa.2023.120972
  • Chen, S., Huang, G., Lin, S., Jiang, W., & Zhao, Z. (2023). Overlapping Community Discovery Algorithm Based on Three-Level Neighbor Node Influence. In Y. Xu, H. Yan, H. Teng, J. Cai, & J. Li (Eds.), Machine Learning for Cyber Security: 4th International Conference, ML4CS 2022, Guangzhou, China, December 2–4, 2022 : proceedings (Vol. II, pp. 335-344). (Lecture Notes in Computer Science; Vol. 13656). Springer. https://doi.org/10.1007/978-3-031-20099-1_28
  • Li, J., Li, J., Xie, C., Liang, Y., Qu, K., Cheng, L., & Zhao, Z. (2023). PipCKG-BS: A Method to Build Cybersecurity Knowledge Graph for Blockchain Systems via the Pipeline Approach. Journal of Circuits, Systems and Computers, 32(16), Article 2350274. https://doi.org/10.1142/S0218126623502742
  • Geng, J., Chen, Z., Wang, Y., Woisetschläger, H., Schimmler, S., Mayer, R., Zhao, Z., & Rong, C. (2023). A Survey on Dataset Distillation: Approaches, Applications and Future Directions. In E. Elkind (Ed.), Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence: IJCAI 2023, Macao, S.A.R, 19-25 August 2023 (Vol. 10, pp. 6610-6618). International Joint Conferences on Artificial Intelligence. https://doi.org/10.24963/ijcai.2023/741
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