1. bookVolume 51 (2021): Issue 2 (June 2021)
Zeitschriftendaten
License
Format
Zeitschrift
Erstveröffentlichung
26 Feb 2008
Erscheinungsweise
4 Hefte pro Jahr
Sprachen
Englisch
access type Open Access

Federated Learning for Spanish Ports as an Aid to Digitization

Online veröffentlicht: 17 Jul 2021
Seitenbereich: 1 - 17
Zeitschriftendaten
License
Format
Zeitschrift
Erstveröffentlichung
26 Feb 2008
Erscheinungsweise
4 Hefte pro Jahr
Sprachen
Englisch

1. Acciaro M., Renken K., El Khadiri N.: Technological Change and Logistics Development in European Ports. In European Port Cities in Transition. Springer, Cham. 2020. Search in Google Scholar

2. Alop A.: The main challenges and barriers to the successful “smart shipping”. ransNav: International Journal on Marine Navigation and Safety of Sea Transportation, 13. 2019. Search in Google Scholar

3. Ashrafi M., Acciaro M., Walker T.R., Magnan G.M., Adams M.: Corporate sustainability in Canadian and US maritime ports. Journal of Cleaner Production, 220, 2019. Search in Google Scholar

4. Baccelli O., Morino P.: The role of port authorities in the promotion of logistics integration between ports and the railway system: The Italian experience. Research in Transportation Business & Management, 100451. 2020. Search in Google Scholar

5. Bakopoulou E., Tillman B., Markopoulou A.: A federated learning approach for mobile packet classification.arXiv preprint arXiv:1907.13113. 2019. Search in Google Scholar

6. Bonawitz K., Eichner H., Grieskamp W., Huba D., Ingerman A., Ivanov V., Van Overveldt T.: Towards federated learning at scale: System design.arXiv preprint arXiv:1902.01046. 2019. Search in Google Scholar

7. Castelein B., van Duin R., Geerlings H.: Identifying dominant stakeholder perspectives on sustainability issues in reefer transportation. A Q-method study in the Port of Rotterdam. Sustainability,11(12), 3425. 2019. Search in Google Scholar

8. Chandiramani K., Garg D., Maheswari N.: Performance analysis of distributed and federated learning models on private data. Procedia Computer Science, 165, 2019. Search in Google Scholar

9. da Silva V.L., Kovaleski J.L., Pagani R.N.: Technology transfer in the supply chain oriented to industry 4.0: a literature review. Technology Analysis & Strategic Management, 31(5), 2019. Search in Google Scholar

10. Farooqui M., Gull H., Ilyas M., Iqbal S.Z., Khan M.A.A., Krishna G., Ahmed M.S.: Improving mental healthcare using a human centered internet of things model and embedding Homomorphic encryption scheme for cloud security. Journal of Computational and Theoretical Nanoscience,16(5-6), 2019. Search in Google Scholar

11. Garcia-Alonso L., Monios J., Vallejo-Pinto J.Á.: Port competition through hinterland accessibility: the case of Spain. Maritime Economics & Logistics, 21(2), 2019. Search in Google Scholar

12. Gesé Bordils M.D.M., González-Cancelas N., Serrano B.M.: Study of environmental sustainability in container terminals through KPI. World Scientific News, 145, 2020. Search in Google Scholar

13. Gizelis C.A., Mavroeidakos T., Marinakis A., Litke A., Moulos V.: Towards a Smart Port: The Role of the Telecom Industry. In IFIP International Conference on Artificial Intelligence Applications and Innovations. Springer, Cham, June, 2020. Search in Google Scholar

14. González-Cancelas N., Molina Serrano B., Esteban-Infantes M., Soler-Flores F., Camarero Orive A.: Escenario de digitalización para el Sistema Portuario Español. Revista Transporte y Territorio /22, 2020. DOI 10.34096/rtt.i22.6398. Search in Google Scholar

15. Horn B.E., Nemoto T.: Intermodal Logistics Policies in the EU, the US and Japan. Transport Policy Studies’ Review, 7(4), 2005. Search in Google Scholar

16. Hu C., Jiang J., Wang Z.: Decentralized federated learning: a segmented gossip approach. arXiv preprint arXiv:1908.07782. 2019. Search in Google Scholar

17. Ilin I., Jahn C., Weigell J., Kalyazina S.: Digital Technology Implementation for Smart City and Smart Port Cooperation. In International Conference on Digital Technologies in Logistics and Infrastructure (ICDTLI 2019). Atlantis Press. September, 2019. Search in Google Scholar

18. Kairouz P., McMahan H.B., Avent B., Bellet A., Bennis M., Bhagoji A.N., d’Oliveira R.G.: Advances and open problems in federated learning.arXiv preprint arXiv:1912.04977. 2019. Search in Google Scholar

19. Kakkad V., Patel M., Shah M.: Biometric authentication and image encryption for image security in cloud framework. Multiscale and Multidisciplinary Modeling, Experiments and Design, 2(4), 2019. Search in Google Scholar

20. Karimireddy S.P., Kale S., Mohri M., Reddi S.J., Stich S.U., Suresh A.T. Scaffold: Stochastic controlled averaging for on-device federated learning. arXiv preprint arXiv:1910.06378. 2019. Search in Google Scholar

21. Koh L., Dolgui A., Sarkis J.: Blockchain in transport and logistics-paradigms and transitions. 2020. Search in Google Scholar

22. Kholod I., Yanaki E., Fomichev D., Shalugin E., Novikova E., Filippov E., Nordlund M.: Open-Source Federated Learning Frameworks for IoT: A Comparative Review and Analysis. Sensors, 21(1), 167, 2021 Search in Google Scholar

23. Li F.: The digital transformation of business models in the creative industries: A holistic framework and emerging trends. Technovation, 92, 102012. 2020. Search in Google Scholar

24. Li T., Sahu A.K., Talwalkar A., Smith V.: Federated learning: Challenges, methods, and future directions. IEEE Signal Processing Magazine, 37(3), 2020. Search in Google Scholar

25. Lim W.Y.B., Luong N.C., Hoang D.T., Jiao Y., Liang Y.C., Yang Q., Miao C.: Federated learning in mobile edge networks: A comprehensive survey. IEEE Communications Surveys & Tutorials. 2020. Search in Google Scholar

26. Liu Y., Yuan X., Xiong Z., Kang J., Wang X., Niyato D.: Federated learning for 6g communications: Challenges, methods, and future directions. China Communications, 17(9), 2020. Search in Google Scholar

27. Mańkowska M., Kotowska I., Pluciński M.: Seaports as Nodal Points of Circular Supply Chains: Opportunities and Challenges for Secondary Ports. Sustainability, 12(9), 3926, 2020. Search in Google Scholar

28. Molavi A., Lim G.J., Race B.: A framework for building a smart port and smart port index. International Journal of Sustainable Transportation, 2019. Search in Google Scholar

29. Molina Serrano B., González Cancelas N., Soler Flores F., Camarero Orive A.: Classification and prediction of port variables using Bayesian Networks. Transport Policy, vol. 67, 2017, DOI 10.1016/j.tranpol.2017.07.013. Search in Google Scholar

30. Molina-Serrano B., Gonzalez-Cancelas N., Soler-Flores F.: Artificial intelligence model to analyze sustainability management of maritime ports. DYNA, vol. 93, no. 1, 2018. DOI http://dx.doi.org/10.6036/8508. Search in Google Scholar

31. Molina Serrano B., Gonzalez-Cancelas N., Soler-Flores F.: Hacia la sostenibilidad portuaria mediante modelos probabilísticos: redes bayesianas. Informes de la Construcción, Vol. 70, 549, 2018. DOI 10.3989/id.54678. Search in Google Scholar

32. Nascimento D.L.M., Alencastro V., Quelhas O.L.G., Caiado R.G.G., Garza-Reyes J.A., Rocha-Lona L., Tortorella G.: Exploring Industry 4.0 technologies to enable circular economy practices in a manufacturing context. Journal of Manufacturing Technology Management. 2019. Search in Google Scholar

33. Notteboom T., Lugt L.V.D., Saase N.V., Sel S., Neyens K.: The Role of Seaports in Green Supply Chain Management: Initiatives, Attitudes, and Perspectives in Rotterdam, Antwerp, North Sea Port, and Zeebrugge.Sustainability, 12(4), 1688, 2020. Search in Google Scholar

34. Połap D., Srivastava G., Yu K.: Agent architecture of an intelligent medical system based on federated learning and blockchain technology. Journal of Information Security and Applications, 58, 102748, 2021. Search in Google Scholar

35. Psomakelis E., Nikolakopoulos A., Marinakis A., Psychas A., Moulos V., Varvarigou T., Christou A.: A Scalable and Semantic Data as a Service Marketplace for Enhancing Cloud-Based Applications. Future Internet, 12(5), 77, 2020. Search in Google Scholar

36. Ramaswamy S., Mathews R., Rao K., Beaufays F.: Federated learning for emoji prediction in a mobile keyboard.arXiv preprint arXiv:1906.04329, 2019. Search in Google Scholar

37. Ren J., Wang H., Hou T., Zheng S., Tang C.: Federated learning-based computation offloading optimization in edge computing-supported internet of things. IEEE Access, 7, 2019. Search in Google Scholar

38. Rodrigo González A., González-Cancelas N., Molina Serrano B., Camarero Orive A.: Preparation of a smart port indicator and calculation of a ranking for the Spanish Port System, Logistics, 4, 9; 2020, DOI 10.3390/logistics4020009. Search in Google Scholar

39. Sakulyeva T., Kseniia Z.: The single window mechanism in the field of external sector of the economy. International Journal of Civil Engineering and Technology, 10(2), 2019. Search in Google Scholar

40. Sánchez-Cambronero A., González-Cancelas N., Serrano B.M.: Analysis of port sustainability using the PPSC methodology (PESTEL, Porter, SWOT, CAME). World Scientific News, 146, 2020. Search in Google Scholar

41. Sanders N.R., Boone T., Ganeshan R., Wood J.D.: Sustainable supply chains in the age of AI and digitization: research challenges and opportunities. Journal of Business Logistics, 40(3), 2019. Search in Google Scholar

42. Saragiotis P.: Business process management in the port sector: a literature review. Maritime Business Review. 2019. Search in Google Scholar

43. Sehnem S., Jabbour C.J.C., Pereira S.C.F., de Sousa Jabbour A.B.L.: Improving sustainable supply chains performance through operational excellence: circular economy approach. Resources, Conservation and Recycling, 149, 2019. Search in Google Scholar

44. Smith J.S., Nebgen B.T., Zubatyuk R., Lubbers N., Devereux C., Barros K., Roitberg A.E.: Approaching coupled cluster accuracy with a general-purpose neural network potential through transfer learning. Nature communications, 10(1), 2019. Search in Google Scholar

45. Szalavetz A.: Industry 4.0 and capability development in manufacturing subsidiaries. Technological Forecasting and Social Change, 145, 2019. Search in Google Scholar

46. Tijan E., Agatić A., Jović M., Aksentijević S.: Maritime National Single Window-A Prerequisite for Sustainable Seaport Business. Sustainability, 11(17), 4570, 2019. Search in Google Scholar

47. Tijan E., Jović M., Jardas M., Gulić M.: The Single Window concept in international trade, transport and seaports. Pomorstvo, 33(2), 2019. Search in Google Scholar

48. Vial G.: Understanding digital transformation: A review and a research agenda. The Journal of Strategic Information Systems, 28(2), 2019. Search in Google Scholar

49. Wang X., Han Y., Wang C., Zhao Q., Chen X., Chen M.: In-edge ai: Intelligentizing mobile edge computing, caching and communication by federated learning. IEEE Network, 33(5), 2019. Search in Google Scholar

50. Wang H., Sreenivasan K., Rajput S., Vishwakarma H., Agarwal S., Sohn J.Y., Papailiopoulos D.: Attack of the Tails: Yes, You Really Can Backdoor Federated Learning.arXiv preprint arXiv:2007.05084. 2020. Search in Google Scholar

51. Williams H.E., Bowman S.W., Jung J.T.: The limitations of government databases for analyzing fatal officer-involved shootings in the United States. Criminal Justice Policy Review, 30(2), 2019. Search in Google Scholar

52. Xu J., Wang F.: Federated learning for healthcare informatics. arXiv preprint arXiv:1911.06270. 2019. Search in Google Scholar

53. Yang Q., Liu Y., Chen T., Tong Y.: Federated machine learning: Concept and applications. ACM Transactions on Intelligent Systems and Technology (TIST), 10(2), 2019. Search in Google Scholar

54. Yavas V., Ozkan-Ozen Y.D.: Logistics centers in the new industrial era: A proposed framework for logistics center 4.0. Transportation Research Part E: Logistics and Transportation Review, 135, 101864. 2020. Search in Google Scholar

55. Yoshida N., Nishio T., Morikura M., Yamamoto K., Yonetani R.: Hybrid-FL for Wireless Networks: Cooperative Learning Mechanism Using Non-IID Data.arXiv preprint arXiv:1905.07210. 2019. Search in Google Scholar

56. Zhang C., Li S., Xia J., Wang W., Yan F., Liu Y.: BatchCrypt: Efficient Homomorphic Encryption for Cross-Silo Federated Learning. In Proceedings of the 2020 USENIX Annual Technical Conference (USENIX ATC 2020), April, 2020. Search in Google Scholar

57. Zhao Y., Zhao J., Jiang L., Tan R., Niyato D., Li Z., Liu Y.: Privacy-preserving blockchain-based federated learning for IoT devices. IEEE Internet of Things Journal, 2020. Search in Google Scholar

Recommended articles from Trend MD

Plan your remote conference with Sciendo