Minicursos do XXX Simpósio Brasileiro de Sistemas Multimídia e Web

A. Ballesteros. Digitocracy: Ruling and being ruled. Philosophies, 5(2):9, 2020.

A. Barredo Arrieta, N. Díaz-Rodríguez, J. Del Ser, A. Bennetot, S. Tabik, A. Barbado, S. Garcia, S. Gil-Lopez, D. Molina, R. Benjamins, R. Chatila, and F. Herrera. Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI. Information Fusion, 58:82 – 115, 2020.

A. Beutel, J. Chen, T. Doshi, H. Qian, A. Woodruff, C. Luu, P. Kreitmann, J. Bischof, and E. H. Chi. Putting Fairness Principles into Practice: Challenges, Metrics, and Improvements. In Conference on AI, Ethics, and Society (AIES), 2019.

A. Dafoe. AI Governance: a Research Agenda. Governance of AI Program, Future of Humanity Institute, 1442:1443, 2018.

A. Hard, K. Rao, R. Mathews, S. Ramaswamy, F. Beaufays, S. Augenstein, H. Eichner, C. Kiddon, and D. Ramage. Federated learning for mobile keyboard prediction, 2019.

A. Hilmkil, S. Callh, M. Barbieri, L. R. Sütfeld, E. L. Zec, and O. Mogren. Scaling federated learning for fine-tuning of large language models. In E. Métais, F. Meziane, H. Horacek, and E. Kapetanios, editors, Natural Language Processing and Information Systems, pages 15–23, Cham, 2021. Springer International Publishing.

A. Jacovi. Trends in explainable ai (xai) literature, 2023.

A. Rai, P. Constantinides, and S. Sarker. Next generation digital platforms: toward human-ai hybrids. Mis Quarterly, 43(1):iii–ix, 2019.

A. Rai. Explainable ai: From black box to glass box. Journal of the Academy of Marketing Science, 48:137–141, 2020.

A. Selbst, D. Boyd, S. Friedler, S. Venkatasubramanian, and J. Vertesi. Fairness and Abstraction in Sociotechnical Systems. In Conference on Fairness, Accountability, and Transparency, 2019.

A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, L. u. Kaiser, and I. Polosukhin. Attention is all you need. In I. Guyon, U. V. Luxburg, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan, and R. Garnett, editors, Advances in Neural Information Processing Systems, volume 30. Curran Associates, Inc., 2017.

Abdelmajid Bouazza, Pascal Molli, et al. 2000. Unifying coupled and uncoupled collaborative work in virtual teams. In ACM CSCW’2000 workshop on collaborative editing systems, Philadelphia, Pennsylvania, USA. 6p.

ABNT NBR 15606-10 (2023). Televisão digital terrestre - codificação de dados e especificações de transmissão para radiofusão digital parte 10: Ginga-html5 – especificação do perfil html5 no ginga. Norma técnica, ABNT, São Paulo, BR.

ABNT NBR 15606-2 (2023). Televisão digital terrestre - codificação de dados e especificações de transmissão para radiofusão digital parte 2: Ginga-ncl para receptores fixos e móveis - linguagem de aplicação xml para codificação de aplicações. Norma técnica, ABNT, São Paulo, BR.

ADVANCED TELEVISION SYSTEMS COMMITTEE. A/321:2024-04 - System Discovery and Signaling. Washington, D.C, April 2024.

ADVANCED TELEVISION SYSTEMS COMMITTEE. A/322:2024-09 - Physical Layer Protocol. Washington, D.C, March 2024.

ADVANCED TELEVISION SYSTEMS COMMITTEE. A/324:2024-04 - Scheduler / Studio to Transmitter Link. Washington, D.C, April 2024.

ADVANCED TELEVISION SYSTEMS COMMITTEE. A/327:2023-06 - ATSC Recommended Practice: Guidelines for the Physical Layer Protocol. Washington, D.C, June 2023.

ADVANCED TELEVISION SYSTEMS COMMITTEE. A/330:2024-04 - Link-Layer Protocol. Washington, D.C, April 2024.

ADVANCED TELEVISION SYSTEMS COMMITTEE. A/331:2024-04 - Signaling, Delivery, Synchronization, and Error Protection. Washington, D.C, April 2024.

Ahmad Hemid,Waleed Shabbir, Abderrahmane Khiat, Christoph Lange, Christoph Quix, and Stefan Decker. 2024. OntoEditor: Real-Time Collaboration via Distributed Version Control for Ontology Development. In European Semantic Web Conference. Springer, 326–341.

Akash Takyar. Prompt engineering: The process, uses, techniques, applications and best practices. [link], 2024. Accessed: 2024-08-11.

Alan Mathison Turing. Computing machinery and intelligence. Mind, 49:433–460, 1950.

Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever. Language models are unsupervised multitask learners. [link], 2019.

Alec Radford, Karthik Narasimhan, Tim Salimans, and Ilya Sutskever. Improving language understanding by generative pre-training. [link], 2018.

Alen George. 2024. Tutorial: How to Build a Real-Time Collaborative App Using CRDT in Angular. [link] Accessed: 2024-10-10.

Andre Esteva, Katherine Chou, Serena Yeung, Nikhil Naik, Ali Madani, Ali Mottaghi, Yun Liu, Eric Topol, Jeff Dean, and Richard Socher. Deep learning-enabled medical computer vision. NPJ Digital Medicine, 4(1):5, 2021.

Andrea De Lucia, Fausto Fasano, Giuseppe Scanniello, and Genny Tortora. 2007. Enhancing collaborative synchronous UML modelling with fine-grained versioning of software artefacts. Journal of Visual Languages & Computing 18, 5 (2007), 492–503.

Andrew Jeffery and Richard Mortier. 2023. AMC: Towards Trustworthy and Explorable CRDT Applications with the Automerge Model Checker. In Proceedings of the 10th Workshop on Principles and Practice of Consistency for Distributed Data (Rome, Italy) (PaPoC ’23). Association for Computing Machinery, New York, NY, USA, 44–50. DOI: 10.1145/3578358.3591326

April Yi Wang, Zihan Wu, Christopher Brooks, and Steve Oney. 2024. "Don’t Step on My Toes": Resolving Editing Conflicts in Real-Time Collaboration in Computational Notebooks. arXiv preprint arXiv:2404.04695 (2024).

Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Ł ukasz Kaiser, and Illia Polosukhin. Attention is all you need. In I. Guyon, U. Von Luxburg, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan, and R. Garnett, editors, Advances in Neural Information Processing Systems, volume 30. Curran Associates, Inc., 2017.

Assange, Julian et al. (2013). "Cypherpunks: Liberdade e o Futuro da Internet". Tradução Cristina Yamagami. São Paulo: Boitempo.

ASSOCIAÇÃO BRASILEIRA DE NORMAS TÉCNICAS. NBR 25601: TV 3.0 - Over-the-Air Physical Layer (A ser publicada). Rio de Janeiro, 2024.

ASSOCIAÇÃO BRASILEIRA DE NORMAS TÉCNICAS. NBR 25602: TV 3.0 - Transport Layer (A ser publicada). Rio de Janeiro, 2024.

ASSOCIAÇÃO BRASILEIRA DE NORMAS TÉCNICAS. NBR 25603: TV 3.0 - Video coding (A ser publicada). Rio de Janeiro, 2024.

ASSOCIAÇÃO BRASILEIRA DE NORMAS TÉCNICAS. NBR 25604: TV 3.0 - Audio coding (A ser publicada). Rio de Janeiro, 2024.

ASSOCIAÇÃO BRASILEIRA DE NORMAS TÉCNICAS. NBR 25605: TV 3.0 - Closed captioning (A ser publicada). Rio de Janeiro, 2024.

ASSOCIAÇÃO BRASILEIRA DE NORMAS TÉCNICAS. NBR 25606: TV 3.0 - Closed signing (A ser publicada). Rio de Janeiro, 2024.

ASSOCIAÇÃO BRASILEIRA DE NORMAS TÉCNICAS. NBR 25607: TV 3.0 - Emergency warning system (A ser publicada). Rio de Janeiro, 2024.

ASSOCIAÇÃO BRASILEIRA DE NORMAS TÉCNICAS. NBR 25608: TV 3.0 - Application coding (A ser publicada). Rio de Janeiro, 2024.

ASSOCIAÇÃO BRASILEIRA DE NORMAS TÉCNICAS. NBR 25609: TV 3.0 - Receivers (A ser publicada). Rio de Janeiro, 2024.

B. Abdollahi and O. Nasraoui. Transparency in Fair Machine Learning: the Case of Explainable Recommender Systems, pages 21–35. Springer International Publishing, Cham, 2018.

B. C. Stahl. Embedding responsibility in intelligent systems: from ai ethics to responsible ai ecosystems. Scientific Reports, 13(1):7586, 2023.

B. H. Zhang, B. Lemoine, and M. Mitchell. Mitigating unwanted biases with adversarial learning, 2018. URL [link].

B. Hitaj, G. Ateniese, and F. Perez-Cruz. Deep models under the gan: Information leakage from collaborative deep learning. In Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security, CCS ’17, page 603–618, New York, NY, USA, 2017. Association for Computing Machinery.

B. Xia, Q. Lu, L. Zhu, S. U. Lee, Y. Liu, and Z. Xing. Towards a Responsible AI Metrics Catalogue: A Collection of Metrics for AI Accountability. In Conference on AI Engineering - Software Engineering for AI, 2024.

B.-C. Han. Infocracy: Digitization and the crisis of democracy. JohnWiley & Sons, 2022.

Barreto, F., Abreu, R. S., and Muchaluat-Saade, D. C. (2023). Tv 3.0: Interação multiusuário para tv digital aberta com ncl 4.0. In Workshop Futuro da TV Digital Interativa - Brazilian Symposium on Multimedia Systems and The Web - WebMedia 2023. SBC.

Barreto, F., Abreu, R. S., Josué, M. I. P., Montevecchi, E. B. B., Valentim, P., and Muchaluat-Saade, D. C. (2024). Providing multimodal and multi-user interactions for digital tv applications. Multimedia Tools and Applications, pages 1–26.

Barreto, F., Abreu, R. S., Montevecchi, E. B. B., Josué, M. I. P., Valentim, P., and Muchaluat-Saade, D. C. (2020). Extending ginga-ncl to specify multimodal interactions with multiple users. In WebMedia ’20: Brazillian Symposium on Multimedia and the Web. SBC.

Barreto, F., Abreu, R. S., Santos, J. A. F. d., and Muchaluat-Saade, D. C. (2019a). Authoring sensory effects in ncl. In Workshop Futuro da TV Digital Interativa - Brazilian Symposium on Multimedia Systems and The Web - WebMedia 2019. SBC.

Barreto, F., Montevecchi, E. B. B., Abreu, R. S., Santos, J. A. F. d., and Muchaluat-Saade, D. C. (2019b). Providing multimodal user interaction in ncl. In Workshop Futuro da TV Digital Interativa - Brazilian Symposium on Multimedia Systems and The Web - WebMedia 2019. SBC.

Beutin, Nikolas; Boran, Daniel (2023). "The Great Web 3.0 Glossary". Fachmedien Recht und Wirtschaft.

Binance (2022). "O que são metadados NFT?". Retrieved from [link]

Brasil (2023). Decreto nº 11.484, de 6 de abril de 2023, Presidência da República. Diário Oficial da União, p. 13, 06/04/2023. Disponível em [link].

BRASIL. Decreto n◦ 11.484, de 6 de abril de 2023. Diário Oficial da República Federativa do Brasil, Brasília, DF, 2023. Dispõe sobre as diretrizes para a evolução do Sistema Brasileiro de Televisão Digital Terrestre e para garantir a disponibilidade de espectro de radiofrequências para a sua implantação. Disponível em: [link]. Acesso em: 02 out. 2024.

Brasil. Estratégia Brasileira de Inteligência Artificial - EBIA. Ministério da Ciência, Tecnologia e Inovações Secretaria de Empreendedorismo e Inovação, 2021. Brasil. Projeto de lei nº 2338, de 2023. [link], 2023. Acesso em: 19/09/2024.

Brasil. Lei nº 13.709, de 14 de agosto de 2018. Diário Oficial [da] República Federativa do Brasil, 2018.

Brasil. Lei nº 13.853, de 8 de julho de 2019. Diário Oficial [da] República Federativa do Brasil, 2019.

Brazilian Digital Terrestrial TV System Forum. CfP Phase 2 / Testing and Evaluation: TV 3.0 Project. [S.l.], March 2021. Disponível em: [link]. Acesso em: 31 dec. 2023.

Brice Nédelec, Pascal Molli, Achour Mostefaoui, and Emmanuel Desmontils. 2013. LSEQ: an adaptive structure for sequences in distributed collaborative editing. In Proceedings of the 2013 ACM Symposium on Document Engineering (Florence, Italy) (DocEng ’13). Association for Computing Machinery, New York, NY, USA, 37–46. DOI: 10.1145/2494266.2494278

Brice Nédelec, Pascal Molli, and Achour Mostefaoui. 2016. Crate: Writing stories together with our browsers. In Proceedings of the 25th International Conference Companion on World Wide Web. 231–234.

Bruna Carolina Rodrigues Cunha, Kamila Rios Da Hora Rodrigues, Isabela Zaine, Elias Adriano Nogueira da Silva, Caio César Viel, and Maria Da Graça Campos Pimentel. 2021. Experience sampling and programmed intervention method and system for planning, authoring, and deploying mobile health interventions: design and case reports. Journal of Medical Internet Research 23, 7 (2021), e24278.

Bruna Carolina Rodrigues da Cunha. 2019. ESPIM: um modelo para guiar o desenvolvimento de sistemas de intervenção a distância. Tese de Doutorado em Ciências de Computação e Matemática Computacional. Instituto de Ciências Matemáticas e de Computação, Universidade de São Paulo, São Carlos. DOI: 10.11606/T.55.2019.tde-29082019-090151 Acesso em: 01 de outubro de 2024.

Buterin, V. (2013). "Ethereum Whitepaper: A Next-Generation Smart Contract and Decentralized Application Platform."Retrieved from [link]

C. A. Ellis and S. J. Gibbs. 1989. Concurrency control in groupware systems. In Proceedings of the 1989 ACM SIGMOD International Conference on Management of Data (Portland, Oregon, USA) (SIGMOD ’89). Association for Computing Machinery, New York, NY, USA, 399–407. DOI: 10.1145/67544.66963

C. Chen, X. Feng, J. Zhou, J. Yin, and X. Zheng. Federated large language model: A position paper. arXiv preprint arXiv:2307.08925, 2023.

C. Dwork. Differential Privacy: A Survey of Results. In Theory and Applications of Models of Computation, 2008.

C. Fung, C. J. Yoon, and I. Beschastnikh. Mitigating sybils in federated learning poisoning. arXiv preprint arXiv:1808.04866, 2018.

C. Janiesch, P. Zschech, and K. Heinrich. Machine learning and deep learning. Electronic Markets, 31(3):685–695, 2021.

C. Katzenbach and L. Ulbricht. Algorithmic governance. Internet Policy Review, 8(4): 1–18, 2019.

C. Mawela. A web-based solution for federated learning with llm based automation. Master’s thesis, C. Mudiyanselage, 2024.

C. Molnar. Interpretable Machine Learning: A Guide for Making Black Box Models Explainable. 2019.

C. Novelli, M. Taddeo, and L. Floridi. Accountability in Artificial Intelligence: What it is and How it works. AI & Society, 39:1871 – 1882, 2023.

C. Ramos, J. C. Augusto, and D. Shapiro. Ambient intelligence—the next step for artificial intelligence. IEEE Intelligent Systems, 23(2):15–18, 2008.

C. Rudin. Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead. Nature machine intelligence, 1(5):206 – 215, 2019.

C. Xie, D.-A. Huang, W. Chu, D. Xu, C. Xiao, B. Li, and A. Anandkumar. Perada: Parameter-efficient federated learning personalization with generalization guarantees. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 23838–23848, June 2024.

C. Zhang, G. Long, T. Zhou, P. Yan, Z. Zhang, C. Zhang, and B. Yang. Dual personalization on federated recommendation. In Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, IJCAI 2023, 19th-25th August 2023, Macao, SAR, China, pages 4558–4566. ijcai.org, 2023.

C. Zhang, Y. Xie, H. Bai, B. Yu, W. Li, and Y. Gao. A survey on federated learning. Knowledge-Based Systems, 216:106775, 2021.

Cercle d’Art des Travailleurs de Plantation Congolaise. Retrieved from [link]

Chainlink (2023). "What Is a Dynamic NFT (dNFT)?"Retrieved from [link]

Chaum, David (1982). “Blind signatures for untraceable payments” in Proc. 2nd Conf. Adv. Cryptol., August 1982

Chengzheng Sun, David Sun, Agustina Ng, Weiwei Cai, and Bryden Cho. 2020c. Real Differences between OT and CRDT under a General Transformation Framework for Consistency Maintenance in Co-Editors. Proc. ACM Hum.-Comput. Interact. 4, GROUP, Article 06 (jan 2020), 26 pages. DOI: 10.1145/3375186

Christian Thum, Michael Schwind, and Martin Schader. 2009. SLIM—A lightweight environment for synchronous collaborative modeling. In 12th International Conference Model Driven Engineering Languages and Systems, MODELS 2009. Springer, 137–151.

Cristian Gadea. 2021. Architectures and Algorithms for Real-Time Web-Based Collaboration. Ph. D. Dissertation. Université d’Ottawa/University of Ottawa.

CTA-5000-F (2023). Web media api snapshot 2023. Especificação cta, CTA.

D. Apley and J. Zhu. Visualizing the Effects of Predictor Variables in Black Box Supervised Learning Models. arXiv preprint arXiv:1612.08468, 2019.

D. Banciu and C. Cîrnu. AI Ethics and Data Privacy Compliance. In Conference on Electronics, Computers and Artificial Intelligence (ECAI), 2022.

D. Chai, L. Wang, K. Chen, and Q. Yang. Secure federated matrix factorization. IEEE Intelligent Systems, 36(5):11–20, 2020.

D. Citron. Technological due process. Washington University Law Review, 85:1249, 2007.

D. Doneda and V. A. Almeida. What is algorithm governance? IEEE Internet Computing, 20(4):60–63, 2016.

D. Doneda, V. A. Almeida, and F. Bruno. O que é a governança de algoritmos. Tecnopolíticas da vigilância: Perspectivas da margem, pages 141–148, 2018.

D. Zhang, B. Xia, Y. Liu, X. Xu, T. Hoang, Z. Xing, M. Staples, Q. Lu, and L. Zhu. Privacy and copyright protection in generative ai: A lifecycle perspective. In Conference on AI Engineering Software Engineering for AI, 2024.

D.-J. Han, D.-Y. Kim, M. Choi, C. G. Brinton, and J. Moon. Splitgp: Achieving both generalization and personalization in federated learning. In IEEE INFOCOM 2023 - IEEE Conference on Computer Communications, pages 1–10, 2023.

DASH INDUSTRY FORUM. Guidelines for Implementation: DASH-IF Interoperability Point for ATSC 3.0). [S.l.], 2018.

David A. Nichols, Pavel Curtis, Michael Dixon, and John Lamping. 1995. High-latency, low-bandwidth windowing in the Jupiter collaboration system. In Proceedings of the 8th Annual ACM Symposium on User Interface and Software Technology (UIST ’95). ACM, 111–120.

David Sun, Chengzheng Sun, Agustina Ng, and Weiwei Cai. 2020a. Real Differences between OT and CRDT in Building Co-Editing Systems and Real World Applications. arXiv:1905.01517 [cs.DC] [link]

David Sun, Chengzheng Sun, Agustina Ng, and Weiwei Cai. 2020b. Real Differences between OT and CRDT in Correctness and Complexity for Consistency Maintenance in Co-Editors. Proc. ACM Hum.-Comput. Interact. 4, CSCW1, Article 21 (may 2020), 30 pages. DOI: 10.1145/3392825

DIGITAL BROADCASTING EXPERTS GROUP. Introduction of "ISDB-T”. [S.l.], 2023. Disponível em: [link]. Acesso em: 22 out. 2022.

Dilshodbek Kuryazov and AndreasWinter. 2014. Representing model differences by delta operations. In 2014 IEEE 18th International Enterprise Distributed Object Computing Conference Workshops and Demonstrations. IEEE, 211–220.

Dilshodbek Kuryazov and AndreasWinter. 2015. Towards Model History Analysis Using Modeling Deltas. Softwaretechnik-Trends Band 35, Heft 2 (2015).

Dilshodbek Kuryazov, AndreasWinter, and Ralf Reussner. 2018. Collaborative modeling enabled by version control. (2018).

DIONÍSIO, V. M. Modulador do sistema ATSC 3.0 usando Gnuradio Companion. 78 p. Dissertação (Mestrado) — Universidade Presbiteriana Mackenzie, São Paulo, Brasil, 2017.

dos Santos, J., Vieira, R., Josué, M. I., Oliveira, K. S., and Muchaluat-Saade, D. C. (2024). Multidevice support in the next generation of the brazilian terrestrial tv system. In IMXw ’24: Proceedings of the 2024 ACM International Conference on Interactive Media Experiences Workshop. ACM.

Douwe Kiela, Edouard Grave, Armand Joulin, and Tomas Mikolov. Efficient largescale multi-modal classification. In Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence and Thirtieth Innovative Applications of Artificial Intelligence Conference and Eighth AAAI Symposium on Educational Advances in Artificial Intelligence, AAAI’18/IAAI’18/EAAI’18. AAAI Press, 2018.

E. Bagdasaryan, A. Veit, Y. Hua, D. Estrin, and V. Shmatikov. How to backdoor federated learning. In Proceedings of Machine Learning Research, volume 108, pages 2938–2948, Online, 26–28 Aug 2020. PMLR.

E. Ferrara. Fairness and Bias in Artificial Intelligence: A Brief Survey of Sources, Impacts, and Mitigation Strategies. Sci, 6(1):3, dec 2023.

E. J. Hu, Y. Shen, P. Wallis, Z. Allen-Zhu, Y. Li, S. Wang, L. Wang, and W. Chen. Lora: Low-rank adaptation of large language models. arXiv preprint arXiv:2106.09685, 2021.

E. Pariser. The filter bubble: What the Internet is hiding from you. penguin UK, 2011.

Elena Yanakieva, Philipp Bird, and Annette Bieniusa. 2023. A Study of Semantics for CRDT-based Collaborative Spreadsheets. In Proceedings of the 10th Workshop on Principles and Practice of Consistency for Distributed Data (Rome, Italy) (PaPoC ’23). Association for Computing Machinery, New York, NY, USA, 37–43. DOI: 10.1145/3578358.3591324

Elias Kuiter, Sebastian Krieter, Jacob Krüger, Gunter Saake, and Thomas Leich. 2021. variED: an editor for collaborative, real-time feature modeling. Empirical Software Engineering 26, 2 (2021), 24.

Ertugrul Portakal. Gpt-4o vs gpt-4: Which model is better? [link], note = Accessed: 2024-08-11, 2024.

EUROPEAN TELECOMMUNICATIONS STANDARDS INSTITUTE. ETSI TS 103 285 V1.3.1 (2020-02) - Digital Video Broadcasting (DVB); MPEG-DASH Profile for Transport of ISO BMFF Based DVB Services over IP Based Networks. Sophia Antipolis, FRANCE, Fev. 2022.

EUROPEAN TELECOMMUNICATIONS STANDARDS INSTITUTE. LTE; Evolved Universal Terrestrial Radio Access (E-UTRA); User Equipment (UE) radio transmission and reception: Etsi ts 136 101 v17.7.0 (2023-01). 650 Route des Lucioles, F-06921 Sophia Antipolis Cedex - France, January 2023. 1651 p. Disponível em: [link]. Acesso em: 25 set. 2023.

European Union. Artificial intelligence act (eu ai act). [link], 2024. Acesso em: 19/09/2024.

European Union. General data protection regulation. [link], 2016. Acesso em: 19/09/2024.

F. A. KhoKhar, J. H. Shah, M. A. Khan, M. Sharif, U. Tariq, and S. Kadry. A review on federated learning towards image processing. Computers and Electrical Engineering, 99:107818, 2022.

F. Amaral. Direito civil - 10ª edição. Saraiva Jur, 2018.

F. Bourse, M. Minelli, M. Minihold, and P. Paillier. Fast homomorphic evaluation of deep discretized neural networks. In H. Shacham and A. Boldyreva, editors, Advances in Cryptology – CRYPTO 2018, pages 483–512, Cham, 2018. Springer International Publishing.

F. Calmon, D. Wei, B. Vinzamuri, K. Ramamurthy, and K. Varshney. Optimized pre-processing for discrimination prevention. In Conference on Neural Information Processing Systems, 2017.

F. Doshi-Velez and B. Kim. Towards a rigorous science of interpretable machine learning. arXiv preprint arXiv:1702.08608, 2017.

F. Hartmann, S. Suh, A. Komarzewski, T. D. Smith, and I. Segall. Federated learning for ranking browser history suggestions, 2019.

F. Kamiran and T. Calders. Data preprocessing techniques for classification without discrimination. Knowl. Inf. Syst., 33(1):1–33, oct 2012.

F. Kamiran, A. Karim, and X. Zhang. Decision theory for discrimination-aware classification. In International Conference on Data Mining, 2012.

FAY, L. et al. An overview of the atsc 3.0 physical layer specification. IEEE Transactions on Broadcasting, v. 62, n. 1, p. 159–171, March 2016. ISSN 0018-9316.

Fórum SBTVD (2020a). Tv 3.0 project. Website. Disponível em [link].

Fórum SBTVD (2020b). Tv 3.0 project - call for proposals. Chamada pública, Fórum SBTVD, São Paulo, BR. Disponível em [link].

Fórum SBTVD (2021). Tv 3.0 project phase 2 - results. Relatório de avaliação de resultados, Fórum SBTVD, São Paulo, BR. Disponível em [link].

FÓRUM SBTVD. TV 3.0 Project - Phase 3 - Over-the-air Physical Layer Field Tests. [S.l.], 2024. Disponível em: [link]. Acesso em: 24 jul. 2024.

FÓRUM SBTVD. TV 3.0 Project - Phase 3 - Over-the-air Physical Layer Laboratory Tests. [S.l.], 2023. Disponível em: [link]. Acesso em: 28 dec. 2023.

FÓRUM SBTVD. TV 3.0 Project. [S.l.], 2023. Disponível em: [link]. Acesso em: 22 out. 2023.

G. Clavell, M. Zamorano, C. Castillo, O. Smith, and A. Matic. Auditing algorithms: On lessons learned and the risks of data minimization. In Conference on AI, Ethics, and Society (AIES), pages 265–271, 2020.

G. Vilone and L. Longo. Explainable Artificial Intelligence: a Systematic Review. arXiv preprint arXiv:2006.00093, 2020.

G. Zhu, X. Liu, J. Niu, S. Tang, X. Wu, and J. Zhang. Dualfed: enjoying both generalization and personalization in federated learning via hierachical representations. arXiv preprint arXiv:2407.17754, 2024.

G20. G20 Ministerial Declaration. [link], 2024. Acesso em: 19/09/2024.

Gabriele Salvati, Christian Santoni, Valentina Tibaldo, and Fabio Pellacini. 2015. Meshhisto: Collaborative modeling by sharing and retargeting editing histories. ACM Transactions on Graphics (TOG) 34, 6 (2015), 1–10.

Geoffrey Litt, Sarah Lim, Martin Kleppmann, and Peter van Hardenberg. 2022a. Peritext: A CRDT for Collaborative Rich Text Editing. Proc. ACM Hum.-Comput. Interact. 6, CSCW2, Article 531 (Nov. 2022), 36 pages. DOI: 10.1145/3555644

Geoffrey Litt, Sarah Lim, Martin Kleppmann, and Peter van Hardenberg. 2022b. Peritext: A CRDT for Collaborative Rich Text Editing. Proc. ACM Hum.-Comput. Interact. 6, CSCW2, Article 531 (nov 2022), 36 pages. DOI: 10.1145/3555644

Gérald Oster, Pascal Urso, Pascal Molli, and Abdessamad Imine. 2006. Data consistency for P2P collaborative editing. In Proceedings of the 2006 20th anniversary conference on Computer supported cooperative work. 259–268.

Google AI. Responsible AI Practices. [link]. Online, acessado em 21/08/2024.

Governo Federal, Ministério da Ciência, Tecnologia e Inovação, and Conselho Nacional de Ciência e Tecnologia. Ia para o bem de todos, 2024. URL [link].

GPAI. Global partnership on artificial intelligence. [link], Acesso em: 19/09/2024. 2020.

Gryfo. Benchmarking de reconhecimento facial destaca as métricas utilizadas pelos grandes players do mercado. [link], 2021.

Guardarian (2023). "Blockchain Layers Explained (L1, L2, L3)". Retrieved from [link]

H. A. Pinto. A utilização da inteligência artificial no processo de tomada de decisões: por uma necessária accountability. Senado Federal, 2019.

H. Anahideh, N. Nezami, and A. Asudeh. On the Choice of Fairness: Finding Representative Fairness Metrics for a given context. arXiv preprint arXiv:2109.05697, pages 1–25, 2021.

H. Brendan McMahan, E. Moore, D. Ramage, S. Hampson, and B. Agüera y Arcas. Communication-efficient learning of deep networks from decentralized data. In Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, AISTATS 2017, volume 54, 2017.

H. N. Cunha Neto, J. Hribar, I. Dusparic, D. M. F. Mattos, and N. C. Fernandes. A survey on securing federated learning: Analysis of applications, attacks, challenges, and trends. IEEE Access, 11:41928–41953, 2023.

H. Su, C. Xiang, and B. Ramesh. Towards confidential chatbot conversations: A decentralised federated learning framework. The Journal of The British Blockchain Association, 2024.

H. Wang, K. Sreenivasan, S. Rajput, H. Vishwakarma, S. Agarwal, J.-y. Sohn, K. Lee, and D. Papailiopoulos. Attack of the tails: Yes, you really can backdoor federated learning. In H. Larochelle, M. Ranzato, R. Hadsell, M. Balcan, and H. Lin, editors, Advances in Neural Information Processing Systems, volume 33, pages 16070–16084. Curran Associates, Inc., 2020.

Haber, S., & Stornetta, W. S. (1991). "How to Time-Stamp a Digital Document."In Journal of Cryptology, 3(2), 99-111.

Haifeng Shen and Chengzheng Sun. 2002. Highlighting: a gesturing communication tool for real-time collaborative systems. In International Conference on Algorithms and Architectures for Parallel Processing 2002. IEEE, 180–187.

HOPKINS, R. Advanced television systems. IEEE Transactions on Consumer Electronics, CE-32, n. 2, p. xi–xvi, May 1986. ISSN 0098-3063.

I. A. Shah, N. Z. Jhanjhi, and S. N. Brohi. Use of AI-Based Drones in Smart Cities. In Cybersecurity Issues and Challenges in the Drone Industry, pages 362–380. 2024.

I. D. Raji, A. Smart, R. N. White, M. Mitchell, T. Gebru, B. Hutchinson, J. Smith-Loud, D. Theron, and P. Barnes. Closing the ai accountability gap: defining an end-to-end framework for internal algorithmic auditing. In Conference on Fairness, Accountability, and Transparency, 2020b.

I. Mironov, K. Talwar, and L. Zhang. Rényi differential privacy of the sampled gaussian mechanism, 2019.

I. Raji, T. Gebru, M. Mitchell, J. Buolamwini, J. Lee, and E. Denton. Saving face: Investigating the ethical concerns of facial recognition auditing. In Conference on AI, Ethics, and Society (AIES), 2020a.

IBM. "O que é aprendizado de Máquina (ML)"Retrieved from: [link]

IBM. 2024. O que é Java Spring Boot? [link] Acessado em 20/08/2024.

INTERNATIONAL ORGANIZATION FOR STANDARDIZATION; INTERNATIONAL ELECTROTECHNICAL COMMISSION. 23009-1:2022 - Information technology — Dynamic Adaptive Streaming over HTTP (DASH) Part 1: Media presentation description and segment format. [S.l.], 2022.

INTERNET ENGINEERING TASK FORCE. RFC 1952 - GZIP file format specification version 4.3. [S.l.], 1996.

INTERNET ENGINEERING TASK FORCE. RFC 5651 - Layered Coding Transport (LCT) Building Block). [S.l.], 2020.

INTERNET ENGINEERING TASK FORCE. RFC 6726 - FLUTE - File Delivery over Unidirectional Transport. [S.l.], 2012.

INTERNET ENGINEERING TASK FORCE. RFC 9223 - Real-Time Transport Object Delivery over Unidirectional Transport (ROUTE). [S.l.], 2022.

Isabela Zaine, David Frohlich, Kamila Rios da Hora Rodrigues, Bruna Carolina Rodrigues da Cunha, Alex Fernando Orlando, Leonardo Fernandes Scalco, and Maria Da Graça Campos Pimentel. 2019b. Promoting Social Connection and Deepen Relations in Older People: Design of Media Parcels towards facilitating Time-based Media Sharing. Journal of Medical Internet Research 21, 10 (2019).

Isabela Zaine, Priscila Benitez, Kamila Rios da Hora Rodrigues, and Maria da Graça Campos Pimentel. 2019a. Applied behavior analysis in residential settings: use of a mobile application to support parental engagement in at-home educational activities. Creative Education 10, 8 (2019), 1883–1903.

ISO/IEC 23005-3:2019 (2019). Information technology — media context and control - part 3: Sensory information. Norma técnica, ISO/IEC, Geneva, SW.

ISO/IEC 27560 (2023). Privacy technologies — consent record information structure. Norma técnica, ISO/IEC, Geneva, SW.

ITU-R BT2075-1 (2017). Integrated broadcast-broadband system. Recomendação uit-r, International Telecommunication Union, Geneva, CH.

ITU-T H.761 (2009). Nested context language (ncl) and ginga-ncl. Standard, International Telecommunication Union, Geneva, CH.

Ivanov, M., Moreno, M. F., and Muchaluat-Saade, D. C. (2024). Automatic preparation of sensory effects. In Proceedings of MMSys ’24: ACM Multimedia Systems Conference 2024. ACM.

J. Angwin, J. Larson, S. Mattu, and L. Kirchner. Machine bias: There’s software used across the country to predict future criminals. and it’s biased against blacks. [link], 2016.

J. Buolamwini and T. Gebru. Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification. In Conference on Fairness, Accountability and Transparency, 2018.

J. Cabrera, M. S. Loyola, I. Magaña, and R. Rojas. Ethical dilemmas, mental health, artificial intelligence, and llm-based chatbots. In International Work-Conference on Bioinformatics and Biomedical Engineering, pages 313–326. Springer, 2023.

J. Howard, E. Laird, Y. Sirotin, R. Rubin, J. Tipton, and A. Vemury. Evaluating Proposed Fairness Models for Face Recognition Algorithms. In International Workshops and Challenges (ICPR), 2022.

J. Koneˇcn`y, H. B. McMahan, F. X. Yu, P. Richtárik, A. T. Suresh, and D. Bacon. Federated learning: Strategies for improving communication efficiency. arXiv preprint arXiv:1610.05492, 2016.

J. Kroll. Accountability in Computer Systems. Oxford University Press New York, 2020.

J. Lunter. Beating the bias in facial recognition technology. Biometric Technology Today, 2020(9):5–7, 2020.

J. Mökander. Auditing of ai: Legal, ethical and technical approaches. DISO, 2:49, 2023.

J. Ren, W. Ni, G. Nie, and H. Tian. Research on resource allocation for efficient federated learning, 2021.

J. Wolff, W. Lehr, and C. S. Yoo. Lessons from GDPR for AI Policymaking. Virginia Journal of Law & Technology, 27(4), 2024.

J. Wu, S. Yang, R. Zhan, Y. Yuan, D. F. Wong, and L. S. Chao. A survey on llmgernerated text detection: Necessity, methods, and future directions. arXiv preprint arXiv:2310.14724, 2023.

J.-H. Eun and S.-S. Hwang. An exploratory study on policy decision making with artificial intelligence: Applying problem structuring typology on success and failure cases. Informatization Policy, 27(4):47–66, 2020.

Janne Lautamäki, Antti Nieminen, Johannes Koskinen, Timo Aho, Tommi Mikkonen, and Marc Englund. 2012. CoRED: browser-based Collaborative Real-time Editor for Java web applications. In Proceedings of the ACM 2012 Conference on Computer Supported Cooperative Work. 1307–1316.

Jason Wei, Maarten Bosma, Vincent Y. Zhao, Kelvin Guu, Adams Wei Yu, Brian Lester, Nan Du, Andrew M. Dai, and Quoc V. Le. Finetuned language models are zero-shot learners. CoRR, abs/2109.01652, 2021.

Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Brian Ichter, Fei Xia, Ed Chi, Quoc Le, and Denny Zhou. Chain-of-thought prompting elicits reasoning in large language models, 2023.

JEON, S. et al. Field trial results for atsc 3.0 txid transmission and detection in single frequency network of seoul. In: 2018 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB). [S.l.: s.n.], 2018. p. 1–4. ISSN 2155-5052.

Jim Bauwens, Kevin De Porre, and Elisa Gonzalez Boix. 2023. [Short paper] Towards improved collaborative text editing CRDTs by using Natural Language Processing. In Proceedings of the 10th Workshop on Principles and Practice of Consistency for Distributed Data (Rome, Italy) (PaPoC ’23). Association for Computing Machinery, New York, NY, USA, 51–55. DOI: 10.1145/3578358.3591330

Joseph Weizenbaum. Eliza—a computer program for the study of natural language communication between man and machine. Commun. ACM, 9(1):36–45, jan 1966.

Josué, M. I. P., Valentim, P. A., and Muchaluat-Saade, D. C. (2023). Tv 3.0: Definição e uso de perfil de telespectador no ambiente de tv digital aberta. In Workshop Futuro da TV Digital Interativa - Brazilian Symposium on Multimedia Systems and The Web - WebMedia 2023. SBC.

K. Cao, Y. Liu, G. Meng, and Q. Sun. An overview on edge computing research. IEEE access, 8:85714–85728, 2020.

Kamila Rodrigues, Isabela Zaine, Brunela Orlandi, and Maria da Graça Pimentel. 2021. Ensinando configurações do smartphone e aplicações sociais para o público 60+ por meio de aulas semanais e intervenções remotas. In Anais do XII Workshop sobre Aspectos da Interação Humano-Computador para a Web Social. SBC, 25–32. DOI: 10.5753/waihcws.2021.17541

Karina de Lima Flauzino, Maria da Graça Campos Pimentel, Samila Sathler Tavares Batistoni, Isabela Zaine, Lilian Ourém Batista Vieira, Kamila Rios da Hora Rodrigues, and Meire Cachioni. 2020. Letramento Digital para Idosos: percepções sobre o ensinoaprendizagem. Educação & Realidade 45 (2020), 1–17.

KAUFFMANN, B. Arquitetura de referência ATSC 3.0 em nuvem pública. 88 p. Dissertação (Mestrado) — Universidade Presbiteriana Mackenzie, São Paulo, Brasil, 2024.

Kent, Charlotte (2021). "Blockchain manifestos: fighting for the imagination of a culture". Burlington Contemporary Issue 5: Utopias.

Kevin Jahns. 2018a. HocusPocus - Collaborative editing. [link]

Kevin Jahns. 2018b. YJS - A CRDT framework with a powerful abstraction of shared data. [link]

Khushwant Virdi, Anup Lal Yadav, Azhar Ashraf Gadoo, and Navjot Singh Talwandi. 2023. Collaborative Code Editors-Enabling Real-Time Multi-User Coding and Knowledge Sharing. In 2023 3rd International Conference on Innovative Mechanisms for Industry Applications (ICIMIA). IEEE, 614–619.

L. Edwards. The EU AI Act: a Summary of its Significance and Scope. Artificial Intelligence (the EU AI Act), 1, 2021.

L. Ferreira, F. Guimarães, and R. Silva. Applying Genetic Programming to Improve Interpretability in Machine Learning Models. In Congress on Evolutionary Computation, 2020.

L. G. Azevedo, E. F. de Souza Soares, R. Souza, and M. F. Moreno. Modern federated database systems: An overview. ICEIS (1), pages 276–283, 2020.

L. Henry, E. Hansen, J. Chimoff, K. Pokstis, M. Kiderman, R. Naim, J. Kossowsky, M. Byrne, S. Lopez-Guzman, K. Kircanski, D. Pine, and M. Brotman. 2024. Selecting an Ecological Momentary Assessment Platform: Tutorial for Researchers. J Med Internet Res 26 (2024), e51125. DOI: 10.2196/51125

L. S. Shapley. A Value for N-person Games. Contributions to the Theory of Games, 28 (2):307 – 317, 1953.

L. Sani, A. Iacob, Z. Cao, B. Marino, Y. Gao, T. Paulik, W. Zhao, W. F. Shen, P. Aleksandrov, X. Qiu, et al. The future of large language model pre-training is federated. arXiv preprint arXiv:2405.10853, 2024.

L. Wang, W. Wang, and B. Li. Cmfl: Mitigating communication overhead for federated learning. In 2019 IEEE 39th International Conference on Distributed Computing Systems (ICDCS), pages 954–964, 2019.

Laria Reynolds and Kyle McDonell. Prompt programming for large language models: Beyond the few-shot paradigm. In Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems, CHI EA ’21, New York, NY, USA, 2021. Association for Computing Machinery.

Laurentino Augusto Dantas, Joab Cavalcante da Silva, and Maria da Graça C. Pimentel. 2024. Desenvolvimento de Editores Colaborativos em Tempo Real: Revisão Rápida. In Workshop de Revisões Sistemáticas de Literatura em Sistemas Multimídias e Web - WebMedia 2024. SBC, 124–142. No prelo.

Laurentino Augusto Dantas, Joab Cavalcante da Silva, Raphael Christian dos Santos Oliveira, Lucas Fidelis Pereira, Kamila Rios da Hora Rodrigues, and Maria da Graça Campos Pimentel. 2023. Descrição do processo de implementação de recursos para autoria colaborativa síncrona na plataforma ESPIM. Caderno Pedagógico 20, 6 (2023), 2244–2269.

Laurentino Augusto Dantas. 2024. Autoria Colaborativa de Intervenções Programadas e Amostragem de Experiências: Um estudo de caso com o ESPIM. (submetida) Tese de Doutorado em Ciências de Computação e Matemática Computacional. Instituto de Ciências Matemáticas e de Computação, Universidade de São Paulo, São Carlos.

LCX (2022). "NFT and NFT Metadata, what’s the difference?". Retrieved from [link]

Leonardo de Freitas Galesky and Luiz Antonio Rodrigues. 2023. Efficient CRDT Synchronization at Scale using a Causal Multicast over a Virtual Hypercube Overlay. In Proceedings of the 11th Latin-American Symposium on Dependable Computing (Fortaleza/ CE, Brazil) (LADC ’22). Association for Computing Machinery, New York, NY, USA, 84–88. DOI: 10.1145/3569902.3569948

Liangrun Da and Martin Kleppmann. 2024. Extending JSON CRDTs with Move Operations. In Proceedings of the 11th Workshop on Principles and Practice of Consistency for Distributed Data (Athens, Greece) (PaPoC ’24). Association for Computing Machinery, New York, NY, USA, 8–14. DOI: 10.1145/3642976.3653030

Liddell, Francis (2022). "The Crypto-Museum: Investigating the impact of blockchain and NFTs on digital ownership, authority, and authenticity in museums". The University of Manchester.

Lilian Ourém Batista Vieira Cliquet, Maria da Graça Campos Pimentel, Samila Sathler Tavares Batistoni, Kamila Rios da Hora Rodrigues, Isabela Zaine, and Meire Cachioni. 2021. Idosos on-line: desenvolvimento de intervenção educativa em letramento digital. Velho-ser: um olhar interdisciplinar sobre o envelhecimento humano (2021), 45–50.

Lilian Ourém Batista Vieira Cliquet, Maria da Graça Campos Pimentel, Samila Sathler Tavares Batistoni, Kamila Rios da Hora Rodrigues, Isabela Zaine, and Meire Cachioni. 2023. Use of smartphones by older adults: characteristics and reports of students enrolled at a University of the Third Age (U3A). PerCursos 24 (2023), 1–30.

Liljeqvist, Ivan (2022). "Layer-2 vs Layer-3: What is the Difference?". Retrieved from [link]

Lima, T. L. P. et al. (2004). "Uma Visão da Web Semântica"In Journal of Information Security and Applications, UFG.

M. Abadi, A. Chu, I. Goodfellow, H. B. McMahan, I. Mironov, K. Talwar, and L. Zhang. Deep learning with differential privacy. In Conference on Computer and Communications Security, 2016.

M. B. Zafar, I. Valera, M. Rodriguez, and K. Gummadi. Fairness beyond disparate treatment & disparate impact: Learning classification without disparate mistreatment. In The Web Conference, 2017.

M. Chen, D. Gündüz, K. Huang, W. Saad, M. Bennis, A. V. Feljan, and H. V. Poor. Distributed learning in wireless networks: Recent progress and future challenges. IEEE Journal on Selected Areas in Communications, 39(12):3579–3605, 2021.

M. Chen, M. Jiang, Q. Dou, Z. Wang, and X. Li. Fedsoup: Improving generalization and personalization in federated learning via selective model interpolation. In H. Greenspan, A. Madabhushi, P. Mousavi, S. Salcudean, J. Duncan, T. Syeda-Mahmood, and R. Taylor, editors, Medical Image Computing and Computer Assisted Intervention – MICCAI 2023, pages 318–328, Cham, 2023. Springer Nature Switzerland.

M. D. Masseno. Das consequências jurídicas da adesão do brasil aos princípios da ocde para a inteligência artificial, especialmente em matéria de proteção de dados. Journal of Law and Sustainable Development, 8(2):113–122, 2020.

M. de Souza Monteiro and L. C. de Castro Salgado. Conversational agents: a survey on culturally informed design practices. Journal on Interactive Systems, 14(1):33–46, 2023.

M. de Souza Monteiro, V. C. Pereira, and L. C. de Castro Salgado. Investigating politeness strategies in chatbots through the lens of conversation analysis. In Anais do XXII Simpósio Brasileiro sobre Fatores Humanos em Sistemas Computacionais. SBC, 2023.

M. Feldman, S. A. Friedler, J. Moeller, C. Scheidegger, and S. Venkatasubramanian. Certifying and Removing Disparate Impact. In Conference on Knowledge Discovery and Data Mining (SIGKDD), 2015.

M. Fredrikson, E. Lantz, S. Jha, S. Lin, D. Page, and T. Ristenpart. Privacy in pharmacogenetics: An end-to-end case study of personalized warfarin dosing. In 23rd {USENIX} Security Symposium ({USENIX} Security 14), pages 17–32, 2014.

M. Gams, I. Y.-H. Gu, A. Härmä, A. Muñoz, and V. Tam. Artificial Intelligence and Ambient Intelligence. Journal of Ambient Intelligence and Smart Environments, 11 (1):71–86, 2019.

M. Goldblum, D. Tsipras, C. Xie, X. Chen, A. Schwarzschild, D. Song, A. Madry, B. Li, and T. Goldstein. Dataset security for machine learning: Data poisoning, backdoor attacks, and defenses. IEEE Transactions on Pattern Analysis and Machine Intelligence, pages 1–1, 2022.

M. Hardt, E. Price, and N. Srebro. Equality of opportunity in supervised learning. In Proceedings of the 30th International Conference on Neural Information Processing Systems, NIPS’16, 2016b.

M. Hardt, E. Price, E. Price, and N. Srebro. Equality of Opportunity in Supervised Learning. In Advances in Neural Information Processing Systems, 2016a.

M. Mäntymäki, M. Minkkinen, T. Birkstedt, and M. Viljanen. Defining organizational ai governance. AI and Ethics, 2(4):603–609, 2022.

M. Minkkinen, J. Laine, and M. Mäntymäki. Continuous auditing of artificial intelligence: a conceptualization and assessment of tools and frameworks. Digital Society (DISO), 1:21, 2022.

M. Paulik, M. Seigel, H. Mason, D. Telaar, J. Kluivers, R. van Dalen, C. W. Lau, L. Carlson, F. Granqvist, C. Vandevelde, et al. Federated evaluation and tuning for on-device personalization: System design & applications. arXiv preprint arXiv:2102.08503, 2021.

M. Ribeiro, S. Singh, and C. Guestrin. Why should I trust you?"Explaining the predictions of any classifier. In Conference on knowledge discovery and data mining (SIGKDD), 2016.

M. S. Jere, T. Farnan, and F. Koushanfar. A taxonomy of attacks on federated learning. IEEE Security & Privacy, 19(2):20–28, 2021.

Marc Shapiro, Nuno Preguiça, Carlos Baquero, and Marek Zawirski. 2011. Conflict-free replicated data types. In Stabilization, Safety, and Security of Distributed Systems: 13th International Symposium, SSS 2011, Grenoble, France, October 10-12, 2011. Proceedings 13. Springer, 386–400.

Maria da Graça Campos Pimentel, AC Rocha, BC Cunha, AF Orlando, O Machado Neto, C Viel, E Antunes, and I Zaine. 2016. Apoio ao envelhecimento no lugar por meio de amostragem de experiências e de intervenção programada. Medicina 49, 2 (2016), 11–12.

Mark S Ackerman, Juri Dachtera, Volkmar Pipek, and Volker Wulf. 2013. Sharing knowledge and expertise: The CSCW view of knowledge management. Computer Supported Cooperative Work (CSCW) 22 (2013), 531–573.

Martin Kleppmann. 2020. Moving elements in list CRDTs. In Proceedings of the 7th Workshop on Principles and Practice of Consistency for Distributed Data (PaPoC ’20). ACM, Article 4, 6 pages. DOI: 10.1145/3380787.3393677

Mazières, David; Shasha, Dennis (2002). "Building secure file systems out of Byzantine storage".

Meire Cachioni, Isabela Zaine, Tássia Monique Chiarelli, Lilian Ourém Batista Vieira Cliquet, Kamila Rios da Hora Rodrigues, Bruna Carolina Rodrigues da Cunha, Leonardo Fernandes Scalco, Brunela Della Maggiori Orlandi, Maria da Graça C. Pimentel, and Samila Sathler Tavares Batistoni. 2019. Aprendizagem ao longo de toda a vida e letramento digital de idosos: um modelo multidisciplinar de intervenção com o apoio de um aplicativo. Revista Brasileira de Ciências do Envelhecimento Humano 16, 1 (2019), 18–24.

Menotti, F. A. (2021). "Decentralization or Recentralization? The Reality of Blockchain Networks."Blockchain and Society Review, 8(3), 198-211.

Merkle, Ralph (1979). "A Digital Signature Based on a Conventional Encryption Function"In Advances in Cryptology - CRYPTO ’79, 369-378.

MINISTÉRIO DAS COMUNICAÇÕES/GABINETE DO MINISTRO. Portaria MCOM N◦ 11476. 2023. Online. Disponível em: [link].

MIYASAKA, H. et al. A study on the scattered pilot pattern of mobile reception for an advanced isdb-t. In: 2020 IEEE International Conference on Consumer Electronics (ICCE). [S.l.: s.n.], 2020. p. 1–4.

Montana, Nicky (2022). "Blockchain layers (L0, L1, L2, L3) in a Diagram". Retrieved from [link]

Moreno, M., Pernisa Júnior, C., Barrere, E., Teixeira, S., Turnes Montezano, C., Shuen Sousa, L.-C., Soares Neto, C., Muchaluat-Saade, D. C., Josué, I., M., dos Santos, J., Colcher, S., Moraes, D., Omaia, D., Araújo, T., and Lemos, G. (2023). R&d progress on tv 3.0 application coding layer. SET INTERNATIONAL JOURNAL OF BROADCAST ENGINEERING, pages 9–21.

N. Kokhlikyan, V. Miglani, M. Martin, E. Wang, B. Alsallakh, J. Reynolds, A. Melnikov, N. Kliushkina, C. Araya, S. Yan, and O. Reblitz-Richardson. Captum: A unified and generic model interpretability library for pytorch, 2020. URL [link].

N. Mehrabi, F. Morstatter, N. Saxena, K. Lerman, and A. Galstyan. A survey on bias and fairness in machine learning. ACM Comput. Surv., 54(6), jul 2021.

N. Patwardhan, S. Marrone, and C. Sansone. Transformers in the real world: A survey on nlp applications. Information, 14(4):242, 2023.

Nabil N Kamel and Robert M Davison. 1998. Applying CSCW technology to overcome traditional barriers in group interactions. Information & Management 34, 4 (1998), 209–219.

Nakamoto, S. (2008). "Bitcoin: A Peer-to-Peer Electronic Cash System". Retrieved from [link]

Netherlands Court of Audit. An Audit of 9 Algorithms used by the Dutch Government. [link], 2022. Online, Accessed 23-08-2024.

Noha Alsulami and Asma Cherif. 2017. Collaborative editing over opportunistic networks: State of the art and challenges. International Journal of Advanced Computer Science and Applications 8, 11 (2017), 264–276.

Numa; Godoy, Gustavo; Teixeira, João (2024). "At the frontier of the metaverse: NFTs, artistic expression, and digital immersions". Metaverse, [S.l.], p. 2449, feb. 2024. ISSN 2810-9791. Available at: [link]. Date accessed:20aug.2024. DOI: 10.54517/m.v5i1.2449.

OECD. Advancing accountability in ai: Governing and managing risks throughout the lifecycle for trustworthy ai. OECD Digital Economy Papers, No. 349, 2023.

OpenAI. Introducing OpenAI o1-preview. [link], 2024. Accessed: 2024-09-15.

P. de Miranda and F. Cavalcanti. Tratado de Direito Privado. Editora Revista dos Tribunais Ltda, 2013.

P. Grother. Demographic differentials in face recognition algorithms. EAB Virtual Event Series-Demographic Fairness in Biometric Systems, 2021.

P. Hu, Z. Lin, W. Pan, Q. Yang, X. Peng, and Z. Ming. Privacy-preserving graph convolution network for federated item recommendation. Artificial Intelligence, 324:103996, 2023.

P. Li, J. Li, Z. Huang, T. Li, C.-Z. Gao, S.-M. Yiu, and K. Chen. Multi-key privacypreserving deep learning in cloud computing. Future Generation Computer Systems, 74:76 – 85, 2017.

P. Lohia, K. Ramamurthy, M. Bhide, D. Saha, K. Varshney, and R. Puri. Bias mitigation post-processing for individual and group fairness. In International Conference on Acoustics, Speech, and Signal Processing (ICASSP)), 2019.

P. Melzi, C. Rathgeb, R. Tolosana, R. Vera-Rodriguez, A. Morales, D. Lawatsch, F. Domin, and M. Schaubert. Synthetic Data for the Mitigation of Demographic Biases in Face Recognition. In Conference on Biometrics (IJCB), 2023.

P. P. Shinde and S. Shah. A review of machine learning and deep learning applications. In 2018 Fourth international conference on computing communication control and automation (ICCUBEA), pages 1–6. IEEE, 2018.

P. Publica. Machine bias. [link], 2024. Online, Accessed in 23-08-2024.

PARK, S. et al. Performance analysis of all modulation and code combinations in atsc 3.0 physical layer protocol. IEEE Transactions on Broadcasting, p. 1–14, 2018. ISSN 0018-9316.

PARK, S. I. et al. Low complexity layered division multiplexing for atsc 3.0. IEEE Transactions on Broadcasting, v. 62, n. 1, p. 233–243, 2016.

Paul Bergmann, Kilian Batzner, Michael Fauser, David Sattlegger, and Carsten Steger. The mvtec anomaly detection dataset: a comprehensive real-world dataset for unsupervised anomaly detection. International Journal of Computer Vision, 129(4):1038–1059, 2021.

Personal Data Protection Commission et al. Model artificial intelligence governance framework. Singapore, Jan, 2020.

Petru Nicolaescu, Mario Rosenstengel, Michael Derntl, Ralf Klamma, and Matthias Jarke. 2018. Near real-time collaborative modeling for view-based web information systems engineering. Information Systems 74 (2018), 23–39.

Postman. 2023. 2023 State of the API Report. Accessed: 2024-06-21.

PRESIDÊNCIA DA REPÚBLICA. DECRETO N◦ 5.820, DE 29 DE JUNHO DE 2006. 2006. Online. Disponível em: [link]. Acesso em: 22 set. 2023.

Q. Xia, W. Ye, Z. Tao, J. Wu, and Q. Li. A survey of federated learning for edge computing: Research problems and solutions. High-Confidence Computing, 1(1):100008, 2021.

Q. Yang, Y. Liu, T. Chen, and Y. Tong. Federated machine learning: Concept and applications. ACM Transactions on Intelligent Systems and Technology (TIST), 10(2):1–19, 2019.

Q. Yang, Y. Liu, T. Chen, and Y. Tong. Federated machine learning: Concept and applications. ACM Transactions on Intelligent Systems and Technology, 10(2):1–19, 2019.

R. Chatila and J. Havens. The IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems. Robotics and well-being, 95:11–16, 2019.

R. D. Zota, I. A. Cîmpeanu, and D. A. Dragomir. Use and design of chatbots for the circular economy. Sensors, 23(11):4990, 2023.

R. Eg, Ö. D. Tønnesen, and M. K. Tennfjord. A scoping review of personalized user experiences on social media: The interplay between algorithms and human factors. Computers in Human Behavior Reports, 9:100253, 2023.

R. Epstein and R. E. Robertson. The search engine manipulation effect (seme) and its possible impact on the outcomes of elections. Proceedings of the National Academy of Sciences, 112(33):E4512–E4521, 2015.

R. Marcinkevics and J. E. Vogt. Interpretability and Explainability: A Machine Learning Zoo Mini-tour. arXiv preprint arXiv:2012.01805, 2020.

R. Ross and V. Pillitteri. Protecting controlled unclassified information in nonfederal systems and organizations. Computer Security Division, Information Technology Laboratory, 2024. DOI: 10.6028/NIST.SP.800-171r3.

RABAÇA, R. S. et al. Evaluation of atsc 3.0 modcods for tv 3.0. In: 2024 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB). [S.l.: s.n.], 2024. p. 1–5.

RABAÇA, R. S. Proposta de um sistema de televisão digital retrocompatível com o ISDB-Tb utilizando LDM. 149 p. Tese (Doutorado) — Universidade Presbiteriana Mackenzie, São Paulo, Brasil, 2022.

Reed Larson and Mihaly Csikszentmihalyi. 1978. Experiential correlates of time alone in adolescence 1. Journal of Personality 46, 4 (1978), 677–693.

Reed Larson and Mihaly Csikszentmihalyi. 2014. The experience sampling method. In Flow and the foundations of positive psychology. Springer, 21–34.

René, G.; Mapes, D. (2019). "The spatial web: how web 3.0 will connect humans, machines and AI to transform the world". Author’s Edition.

Renkai Ma, Yue You, Xinning Gui, and Yubo Kou. 2023. How Do Users Experience Moderation?: A Systematic Literature Review. Proc. ACM Hum.-Comput. Interact. 7, CSCW2, Article 278 (Oct. 2023), 30 pages. DOI: 10.1145/3610069

Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, Russ Altman, Simran Arora, Sydney von Arx, Michael S. Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, Erik Brynjolfsson, and S. Buch. On the opportunities and risks of foundation models. ArXiv, abs/2108.07258, 2021.

Rocket Farm Studios. Gpt-4o: Openai’s newest, most advanced language model. [link], note = Accessed: 2024-08-11, 2024.

Rodolfo S Sanches, Moacir A Ponti, and Kamila R Rodrigues. 2022. Evasao Universitária e Estratégias para Retençao de Alunos com Base em Intervençoes Remotas. In Anais Estendidos do XXI Simpósio Brasileiro de Fatores Humanos em Sistemas Computacionais. SBC, 84–87.

Roy T. Fielding, Richard N. Taylor, Justin R. Erenkrantz, Michael M. Gorlick, Jim Whitehead, Rohit Khare, and Peyman Oreizy. 2017. Reflections on the REST architectural style and "principled design of the modern web architecture"(impact paper award). In Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering (Paderborn, Germany) (ESEC/FSE 2017). Association for Computing Machinery, New York, NY, USA, 4–14. DOI: 10.1145/3106237.3121282

Roy Thomas Fielding. 2000. REST: architectural styles and the design of network-based software architectures. Doctoral dissertation, University of California (2000).

Ruipeng Wei, Ruisheng Zhang, Chen Zhao, Dongmei Yue, and Lian Li. 2009. Design and Implementation of Scientific Collaborative Editing Environment on Chemistry. In International Conference on Grid and Cooperative Computing’2009. IEEE, 188–192.

Ryota Inoue, Yudai Kato, Takushi Goda, Tadachika Ozono, Shun Shiramatsu, and Toramatsu Shintani. 2012. A real-time collaborative mechanism for editing a web page and its applications. In 2012 Fifth International Symposium on Parallel Architectures, Algorithms and Programming. IEEE, 186–193.

S. AbdulRahman, H. Tout, H. Ould-Slimane, A. Mourad, C. Talhi, and M. Guizani. A survey on federated learning: The journey from centralized to distributed on-site learning and beyond. IEEE Internet of Things Journal, 8(7):5476–5497, 2020.

S. Angra and S. Ahuja. Machine learning and its applications: A review. In 2017 international conference on big data analytics and computational intelligence (ICBDAC), pages 57–60. IEEE, 2017.

S. Caldas, J. Koneˇcny, H. B. McMahan, and A. Talwalkar. Expanding the reach of federated learning by reducing client resource requirements. arXiv preprint arXiv:1812.07210, 2018.

S. D’Urso, F. Sciarrone, and M. Temperini. Boulez: A chatbot-based federated learning system for distance learning. In 2023 27th International Conference Information Visualisation (IV), pages 210–215, 2023.

S. Engelmann, V. Scheibe, F. Battaglia, and J. Grossklags. Social media profiling continues to partake in the development of formalistic self-concepts. social media users think so, too. In Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society, pages 238–252, 2022.

S. Garfinkel, J. Near, A. Dajani, P. Singer, and B. Guttman. De-Identifying Government Datasets: Techniques and Governance. In US Department of Commerce, National Institute of Standards and Technology, 2023.

S. Kijewski, E. Ronchi, and E. Vayena. The rise of checkbox ai ethics: a review. AI Ethics, 2024. DOI: 10.1007/s43681-024-00563-x.

S. Lundberg and S. Lee. A unified approach to interpreting model predictions. Advances in Neural Information Processing Systems, 2017.

S. McLennan, A. Fiske, D. Tigard, and et al. Embedded ethics: a proposal for integrating ethics into the development of medical ai. BMC Medical Ethics, 23(6), 2022.

S. Patricia and H. Ali. IEEE CertifAIEd – Ontological Specification for Ethical Privacy. [link], 2022. Online, Acessed: 23-08-2024.

S. Rajendran, J. S. Obeid, H. Binol, R. D‘Agostino, K. Foley, W. Zhang, P. Austin, J. Brakefield, M. N. Gurcan, and U. Topaloglu. Cloud-Based Federated Learning Implementation Across Medical Centers. JCO Clinical Cancer Informatics, 5:1–11, 2021. PMID: 33411624.

S. Ramaswamy, R. Mathews, K. Rao, and F. Beaufays. Federated learning for emoji prediction in a mobile keyboard, 2019.

S. U. Noble. Algorithms of oppression. In Algorithms of Oppression. New York University Press, 2018.

S. Wei and M. Niethammer. The Fairness-Accuracy Pareto Front. Statistical Analysis and Data Mining, 15(3):287–302, 2022.

S. Yan, D. Huang, and M. Soleymani. Mitigating Biases in Multimodal Personality Assessment. In Conference on Multimodal Interaction, 2020.

S.Wang, T. Tuor, T. Salonidis, K. K. Leung, C. Makaya, T. He, and K. Chan. Adaptive Federated Learning in Resource Constrained Edge Computing Systems. IEEE Journal on Selected Areas in Communications, 37(6):1205–1221, 2019.

Sathya, A. R.; Jena, A. K. (2020). "Blockchain Technology: The Trust-Free Systems". In Bitcoin and Blockchain: History and Current Applications. CRC Press.

Sathya, A. R.; Swain, S. K. (2020). "Consensus and Mining in a Nutshell". In Bitcoin and Blockchain: History and Current Applications. CRC Press.

SENATORI, N. O. B.; SUKYS, F. Como preparar trabalhos para cursos de pós-Introdução à televisão e ao sistema PAL-M. 1. ed. Rio de Janeiro: Guanabara Dois, 1984.

Sergeenkov, Andrey (2023). "O que são NFTs dinâmicos? Compreendendo a evolução do NFT"Retrieved from [link]

SET, ABERT, UNIVERSIDADE PRESBITERIANA MACKENZIE. Brazil Digital TV Report. Sao Paulo, SP, Brasil, 2000. Disponível em: [link]. Acesso em: 09 jun. 2024.

Shadaj Laddad, Conor Power, Mae Milano, Alvin Cheung, Natacha Crooks, and Joseph M. Hellerstein. 2022. Keep CALM and CRDT On. Proc. VLDB Endow. 16, 4 (Dec. 2022), 856–863. DOI: 10.14778/3574245.3574268

Shasha, D., & Mazières, D. (2002). "SUNDR: A Distributed File System That Guarantees Consistency."In Proceedings of the 19th ACM Symposium on Operating Systems Principles (SOSP ’02), 121-136.

Shengyu Zhang, Linfeng Dong, Xiaoya Li, Sen Zhang, Xiaofei Sun, Shuhe Wang, Jiwei Li, Runyi Hu, Tianwei Zhang, Fei Wu, and Guoyin Wang. Instruction tuning for large language models: A survey, 2024.

Shin-Ya Katayama, Takushi Goda, Shun Shiramatsu, Tadachika Ozono, and Toramatsu Shintani. 2013. A fast synchronization mechanism for collaborative web applications based on HTML5. In 2013 14th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing. IEEE, 663–668.

Sobirov J.Sh. Kuryazov D.A., Jumanazarov B.B. 2016. Software Model Version Control And Collaboration. [link]. XXI (2016), 6–3.

SODAGAR, I. The mpeg-dash standard for multimedia streaming over the internet. IEEE MultiMedia, v. 18, n. 4, p. 62–67, 2011.

SONG, J. et al. Key technologies and measurements for dtmb-a system. IEEE Transactions on Broadcasting, v. 65, n. 1, p. 53–64, 2019.

Souza, G., Silva, D., Delgado, M., Rodrigues, R., Mendes, P. R. C., Amorim, G. F., Guedes, L. V., and dos Santos, J. A. F. d. (2020). Interactive 360-degree videos in ginga-ncl using head-mounted-displays as second screen devices. In WebMedia ’20: Brazillian Symposium on Multimedia and the Web. SBC.

Szabo, N. (2005). "Bitgold."Retrieved from [link].

T. Che, J. Liu, Y. Zhou, J. Ren, J. Zhou, V. S. Sheng, H. Dai, and D. Dou. Federated learning of large language models with parameter-efficient prompt tuning and adaptive optimization. arXiv preprint arXiv:2310.15080, 2023.

T. F. Privacy. Privacidade no machine learning. [link], 2021.

T. Gillespie. The relevance of algorithms. Media Technologies. : Essays on Communication Materiality and Society, pages 167–194, 2014.

T. Kamishima, S. Akaho, and J. Sakuma. Fairness-aware learning through regularization approach. In 2011 IEEE 11th International Conference on Data Mining Workshops, pages 643–650, 2011. DOI: 10.1109/ICDMW.2011.83.

T. Pagano, R. Loureiro, F. Lisboa, R. Peixoto, G. Guimarães, G. Cruz, M. Araujo, L. Santos, M. Cruz, E. . Oliveira, I. Winkler, and E. Nascimento. Bias and Unfairness in Machine Learning Models: A Systematic Review on Datasets, Tools, Fairness Metrics, and Identification and Mitigation Methods. Big Data and Cognitive Computing, 7(1), 2023.

T. Pereira and S. Marcel. Fairness in Biometrics: A Figure of Merit to Assess Biometric Verification Systems. IEEE Transactions on Biometrics, Behavior, and Identity Science, 4(1):19–29, 2022.

Tadachika Ozono, Robin ME Swezey, Shun Shiramatsu, Toramatsu Shintani, Takushi Goda, Yudai Kato, and Ryota Inoue. 2012. Differential Synchronizaiton Mechanism for a Real-Time Collaborative Web Page Editing System WFE-S. In IIAI International Conference on Advanced Applied Informatics. IEEE, 242–247.

Tadas Baltrušaitis, Chaitanya Ahuja, and Louis-Philippe Morency. Multimodal machine learning: A survey and taxonomy. IEEE Transactions on Pattern Analysis and Machine Intelligence, 41(2):423–443, 2019.

Takeshi Kojima, Shixiang Shane Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa. Large language models are zero-shot reasoners, 2023.

Thomson Reuters Practical Law. Accountability principle. [link], 2024. Accessed: 2024-05-22.

Thore Fechner, Dennis Wilhelm, and Christian Kray. 2015. Ethermap: real-time collaborative map editing. In Proceedings of the 33rd ACM Conference on Human Factors in Computing Systems. 3583–3592.

Tim Jungnickel and Tobias Herb. 2016. Simultaneous editing of JSON objects via operational transformation. In Proceedings of the 31st Annual ACM Symposium on Applied Computing. 812–815.

Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, and Arvind Neelakantan. Language models are few-shot learners, 2020.

Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel Ziegler, Jeffrey Wu, Clemens Winter, Chris Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. Language models are few-shot learners. In H. Larochelle, M. Ranzato, R. Hadsell, M.F. Balcan, and H. Lin, editors, Advances in Neural Information Processing Systems, volume 33, pages 1877–1901. Curran Associates, Inc., 2020.

Toronto Declaration. Toronto declaration. [link], 2018. Acesso em: 19/09/2024.

U. Gasser and V. A. Almeida. A layered model for ai governance. IEEE Internet Computing, 21(6):58–62, 2017.

Ulrike Bath, Sumit Shekhar, Julian Egbert, Julian Schmidt, Amir Semmo, Jürgen Döllner, and Matthias Trapp. 2022. CERVI: collaborative editing of raster and vector images. The Visual Computer 38, 12 (2022), 4057–4070.

UNESCO. Recomendação da UNESCO sobre a Ética da Inteligência Artificial. [link], 2021. Acesso em 19/09/2024.

Using NFT metadata to safely store digital assets - LeftAsExercise. Acesso em: 03 de Junho de 2024. Disponível em: [link]

V. Almeida, J. M. Almeida, and W. Meira. The role of computer science in responsible ai governance. IEEE Internet Computing, 28(3):55–58, 2024.

V. Dignum. Responsibility and artificial intelligence. The oxford handbook of ethics of AI, 4698:215, 2020.

V. Dignum. Responsible Autonomy. In Conference on Autonomous Agents and Multi-Agent Systems (AAMAS), 2017.

V. Smith, A. Shahin, C. Ashurst, and A. Weller. Identifying and Mitigating Privacy Risks Stemming from Language Models: A Survey. arXiv preprint arXiv:2310.01424, 2024.

VALEIRA, G. de M. TV 3.0 MUX. 2024. Apresentação oral com uso de slides no Congresso do SET EXPO 2024.

W. Colombelli. Regulamentação da IA (Inteligência Artificial) na administração pública brasileira: análise do Projeto de Lei n° 21 de 2020 e Projeto de Lei n° 2338 de 2023. B.S. thesis, 2024.

W. Y. B. Lim, N. C. Luong, D. T. Hoang, Y. Jiao, Y.-C. Liang, Q. Yang, D. Niyato, and C. Miao. Federated learning in mobile edge networks: A comprehensive survey. IEEE Communications Surveys & Tutorials, 22(3):2031–2063, 2020.

W3C (2024a). Data privacy vocabulary (dpv). Final w3c community report, W3C.

W3C (2024b). Personal data categories (pd). Final w3c community report, W3C.

Web3 Foundation (2024). "About Web3 Foundation"Retrieved from [link].

Winston, Brian (1993). "A ilusão da revolução". In: Forester, Tom (Ed.). Informática e sociedade I: evolução ou revolução? Tradução de Maria da Conceição Silva e Cunha. Lisboa: Edições Salamandra.

WIRESHARK FOUNDATION. Wireshark - Go Deep. 2024. Online. Disponível em: [link]. Acesso em: 10 out. 2024.

World Wide Web Consortium. "Web 1.0". Retrieved from [link]

World Wide Web Consortium. "Web 2.0". Retrieved from [link]

WU, Y. et al. Cloud transmission: A new spectrum-reuse friendly digital terrestrial broadcasting transmission system. IEEE Transactions on Broadcasting, v. 58, n. 3, p. 329–337, Sept 2012. ISSN 0018-9316.

WU, Y. et al. Overview of digital television development worldwide. Proceedings of the IEEE, v. 94, n. 1, p. 8–21, Jan 2006. ISSN 0018-9219.

X. Cao, T. Ba¸sar, S. Diggavi, Y. C. Eldar, K. B. Letaief, H. V. Poor, and J. Zhang. Communication-efficient distributed learning: An overview. IEEE journal on selected areas in communications, 41(4):851–873, 2023.

X. Fu, H. Wang, and P. Shi. A survey of blockchain consensus algorithms: mechanism, design and applications. Science China Information Sciences, 64:1–15, 2021.

X. Li, M. Xia, J. Jiao, S. Zhou, C. Chang, Y. Wang, and Y. Guo. Hal-ia: A hybrid active learning framework using interactive annotation for medical image segmentation. Medical Image Analysis, 88:102862, 2023.

X. Yao, C. Huang, and L. Sun. Two-stream federated learning: Reduce the communication costs. In 2018 IEEE Visual Communications and Image Processing (VCIP), pages 1–4, 2018.

X. Zhou, M. Xu, Y. Wu, and N. Zheng. Deep model poisoning attack on federated learning. Future Internet, 13(3), 2021.

Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc Le, Ed Chi, Sharan Narang, Aakanksha Chowdhery, and Denny Zhou. Self-consistency improves chain of thought reasoning in language models, 2023.

Y. Bengio, Y. Lecun, and G. Hinton. Deep learning for ai. Communications of the ACM, 64(7):58–65, 2021.

Y. Chen, X. Qin, J. Wang, C. Yu, and W. Gao. Fedhealth: A federated transfer learning framework for wearable healthcare. IEEE Intelligent Systems, 35(4):83–93, 2020.

Y. Jin, Y. Liu, K. Chen, and Q. Yang. Federated learning without full labels: A survey, 2023.

Y. LeCun, Y. Bengio, and G. Hinton. Deep learning. nature, 521(7553):436–444, 2015.

Y. Liu, Y. Kang, X. Zhang, L. Li, Y. Cheng, T. Chen, M. Hong, and Q. Yang. A communication efficient vertical federated learning framework. arXiv preprint arXiv:1912.11187, 2019.

Y. Mansour, M. Mohri, J. Ro, and A. T. Suresh. Three approaches for personalization with applications to federated learning. arXiv preprint arXiv:2002.10619, 2020.

Y. Tian and Y. Zhang. A comprehensive survey on regularization strategies in machine learning. Information Fusion, 80:146–166, 2022. ISSN 1566-2535. DOI: 10.1016/j.inffus.2021.11.005. URL [link].

Y. Yao, J. Duan, K. Xu, Y. Cai, Z. Sun, and Y. Zhang. A survey on large language model (llm) security and privacy: The good, the bad, and the ugly. High-Confidence Computing, 4(2):100211, 2024.

Ye Jiang, Xiaomin Yu, Yimin Wang, Xiaoman Xu, Xingyi Song, and Diana Maynard. Similarity-aware multimodal prompt learning for fake news detection. Information Sciences, 647:119446, 2023.

Z. C. Lipton. The mythos of model interpretability: In machine learning, the concept of interpretability is both important and slippery. Queue, 16(3):31 – 57, 2018.

Z. Obermeyer, B. Powers, C. Vogeli, and S. Mullainathan. Dissecting racial bias in an algorithm used to manage the health of populations. Science, 366(6464):447–453, 2019.

Z. Sun, Y. Xu, Y. Liu, W. He, L. Kong, F. Wu, Y. Jiang, and L. Cui. A survey on federated recommendation systems. IEEE Transactions on Neural Networks and Learning Systems, 2024.

Z. Tao and Q. Li. esgd: Communication efficient distributed deep learning on the edge. In {USENIX} Workshop on Hot Topics in Edge Computing (HotEdge 18), 2018.