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Results: 216,732
Number of items: 216,732
  • Debris-Alazard, T., Ducas, L., Resch, N., & Tillich, J.-P. (2023). Smoothing Codes and Lattices: Systematic Study and New Bounds. IEEE Transactions on Information Theory, 69(9), 6006-6027. https://doi.org/10.1109/TIT.2023.3276921
  • Boyle, E., Couteau, G., Gilboa, N., Ishai, Y., Kohl, L., Resch, N., & Scholl, P. (2023). Oblivious Transfer with Constant Computational Overhead. In C. Hazay, & M. Stam (Eds.), Advances in Cryptology – EUROCRYPT 2023: 42nd Annual International Conference on the Theory and Applications of Cryptographic Techniques, Lyon, France, April 23-27, 2023 : proceedings (Vol. I, pp. 271-302). (Lecture Notes in Computer Science; Vol. 14004). Springer. https://doi.org/10.1007/978-3-031-30545-0_10
  • 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
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