Jornada de Atualização em Informática 2022
Sinopse
A Jornada de Atualização em Informática (JAI) é um evento que se tornou referência na apresentação de tópicos relevantes para a pesquisa e desenvolvimento dentro do Congresso da Sociedade Brasileira de computação. A JAI vem contribuindo de forma significativa com a disseminação de conhecimento de ponta para os alunos, profissionais e pesquisadores em Computação no Brasil. Em sua 41ª edição, são tratados os temas processamento de linguagem natural e aprendizagem profunda; estratégias ágeis em projetos de PD&I; big data e economia circular; e blockchain. O Capítulo 1 (Processamento de Linguagem Natural via Aprendizagem Profunda) apresenta como técnicas de Aprendizagem Profunda podem ser utilizadas na resolução de tarefas de Processamento de Linguagem Natural (PLN), tais como como Classificação e Sumarização de Sentenças, visando o benefício do poder computacional disponível atualmente e da baixa necessidade de engenharia de fatures na utilização destes modelos. O Capítulo 2 (Estratégias Ágeis Aplicadas à Projetos de PD&I: Da Teoria à Prática) discute os principais desafios, conceitos, relatos e estudos de caso da adoção de estratégias ágeis, em particular o framework Scrum, em pesquisa científica voltada para produção de inovação tecnológica. O Capítulo 3 (Big Data e Tecnologias Digitais Aplicadas à Economia Circular: Oportunidades para Cadeias Produtivas mais Sustentáveis) mostra como big data e as tecnologias digitais, tais como internet das coisas, computação em nuvem e blockchain, desempenham um papel chave na economia circular, como atendem às necessidades desses modelos de negócio no contexto, contribuindo para os desafios atuais de sustentabilidade. O Capítulo 4 (Visitando na teoria e na prática o Cartesi RollUps: para além das limitações da Blockchain, uma solução de futuro para aplicativos descentralizados) trata de uma tecnologia promissora - o Cartesi Rollups - que é capaz de alçar Blockchain ao status de padrão das aplicações na internet do futuro, minimizando suas limitações de escalabilidade.
Capítulos:
Downloads
Referências
Ahmad,W., Rasool, A., Javed, A. R., Baker, T., and Jalil, Z. (2021). Cyber security in iot-based cloud computing: A comprehensive survey. Electronics, 11(1):16.
Akbik, A., Bergmann, T., Blythe, D., Rasul, K., Schweter, S., and Vollgraf, R. (2019). FLAIR: An Easy-to-Use Framework for State-of-the-Art NLP. In NAACL 2019, 2019 Annual Conference of the North American Chapter of the Association for Computational Linguistics (Demonstrations), pages 54–59.
Akbik, A., Blythe, D., and Vollgraf, R. (2018). Contextual String Embeddings for Sequence Labeling. In Proceedings of the 27th international conference on computational linguistics, pages 1638–1649.
Ankrah, S. and AL-Tabbaa, O. (2015). Universities– industry collaboration: A systematic review. Scandinavian Journal of Management, 31(3):387–408.
Argento, F. (2021). Rollups: On-chain. https://medium.com/cartesi/rollups-on-chain-d749744a9cb3.
Atta-Owusu, K., Fitjar, R. D., and Rodríguez-Pose, A. (2021). What drives university-industry collaboration? research excellence or firm collaboration strategy? Technological Forecasting and Social Change, 173:121084.
Bahdanau, D., Cho, K., and Bengio, Y. (2014). Neural machine translation by jointly learning to align and translate. arXiv preprint arXiv:1409.0473.
Bammer, G. (2008). Enhancing research collaborations: Three key management challenges. Research Policy, 37(5):875–887.
Barros, M. V., Salvador, R., do Prado, G. F., de Francisco, A. C., and Piekarski, C. M. (2020). Circular economy as a driver to sustainable businesses. page 100006. Elsevier.
Beck, K. and Andres, C. (2004). Extreme Programming Explained: Embrace Change. Addison-Wesley Professional, Boston, 2 edition.
Beck, K., Beedle, M., van Bennekum, A., Cockburn, A., Cunningham, W., Fowler, M., Grenning, J., Highsmith, J., Hunt, A., Jeffries, R., Kern, J., Marick, B., Martin, R. C., Mellor, S., Schwaber, K., Sutherland, J., and Thomas, D. (2001). Manifesto for agile software development.
Benet, J. (2014). Ipfs - content addressed, versioned, p2p file system.
Bengio, Y., Ducharme, R., and Vincent, P. (2000a). A Neural Probabilistic Language Model. Advances in Neural Information Processing Systems, 13.
Bengio, Y., Ducharme, R., and Vincent, P. (2000b). A neural probabilistic language model. Advances in Neural Information Processing Systems, 13.
Benyus, J. M. (1997). Biomimicry: Innovation inspired by nature. Morrow New York, New York: Quill.
Binance, A. (2020). What is ethereum plasma? https://academy.binance.com/en/articles/what-is-ethereum-plasma. Accessed on 2022-05.
bit2me (2020). O que é sharding? https://academy.bit2me.com/pt/o-que-é-sharding/.
Bojanowski, P., Grave, E., Joulin, A., and Mikolov, T. (2017). Enriching Word Vectors with Subword Information. Transactions of the association for computational linguistics, 5:135–146.
Brown, T., Mann, B., Ryder, N., Subbiah, M., Kaplan, J.D., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al. (2020). Language Models are Few-Shot Learners. Advances in neural information processing systems, 33:1877–1901.
Brundtland, G. H. (1987). Our common future—call for action. Environmental Conservation, 14(4):291–294.
Brydges, T. (2021). Closing the loop on take, make, waste: Investigating circular economy practices in the swedish fashion industry. volume 293, page 126245. Elsevier.
Buterin, V. (2021). An incomplete guide to rollups. https://vitalik.ca/general/2021/01/05/rollup.html. Accessed on 2022-04.
Cardoso, M. G., Amboni, N., Lagemann, G. V., and de Andrade, R. O. B. (2018). Fatores facilitadores e restritivos à cooperação universidade e empresa: o caso udesc. Desenvolvimento em Questão, 16(45):273–291.
Cartesi (2022). Cartesi Documentation. https://www.cartesi.io/en/docs/.
Cattell, R. (2011). Scalable sql and nosql data stores. ACM Sigmod Record, 39(4):12–27.
Cer, D., Yang, Y., Kong, S.-y., Hua, N., Limtiaco, N., John, R.S., Constant, N., Guajardo-Céspedes, M., Yuan, S., Tar, C., et al. (2018).Universal sentence encoder. arXiv preprint arXiv:1803.11175.
Chen, X., Memon, H. A., Wang, Y., Marriam, I., and Tebyetekerwa, M. (2021). Circular economy and sustainability of the clothing and textile industry. Materials Circular Economy, 3(1):1–9.
Chollet, F. (2021). Deep Learning with Python. Simon and Schuster.
Ciric, D., Lalic, B., Gracanin, D., Palcic, I., and Zivlak, N. (2018). Agile project management in new product development and innovation processes: Challenges and benefits beyond software domain. In 2018 IEEE International Symposium on Innovation and Entrepreneurship (TEMS-ISIE).
Cohen, D., Lindvall, M., and Costa, P. (2004). An introduction to agile methods. In Advances in Computers, volume 62, pages 1–66. Elsevier.
Cooke, N. J. and Hilton, M. L., editors (2015). Enhancing the Effectiveness of Team Science. The National Academies Press, Washington, DC.
Corso, A. (2019). Performance analysis of proof-of-elapsed-time (poet) consensus in the sawtooth blockchain framework. PhD thesis, University of Oregon.
Côrte-Real, N., Ruivo, P., Oliveira, T., and Popovic, A. (2019). Unlocking the drivers of big data analytics value in firms. Journal of Business Research, 97:160–173.
Cruz, F. (2015). Scrum e Agile em Projetos - Guia Completo: Conquiste sua certificação e aprenda a usar métodos ágeis no seu dia a dia. BRASPORT.
Da Silva, T.L.C., Ferreira, M.G.F., Magalhaes, R.P., De Macêdo, J.A.F., and da Silva Araújo, N. (2020). Rastreador de sintomas da COVID 19. In SBBD.
da Silva, T.L.C., Magalhães, R.P., de Macêdo, J.A., Araújo, D., Araújo, N., de Melo, V., Olímpio, P., Rego, P.A., and Neto, A.V.L. (2019). Improving Named Entity Recognition using Deep Learning with Human in the Loop. In EDBT, pages 594–597.
Dai, A.M. and Le, Q.V. (2015). Semi-Supervised Sequence Learning. Advances in neural information processing systems, 28.
Dastjerdi, A. V. and Buyya, R. (2016). Fog computing: Helping the internet of things realize its potential. Computer, 49(8):112–116.
Daudén-Esmel, C., Castellà-Roca, J., Viejo, A., and Domingo-Ferrer, J. (2021). Lightweight blockchain-based platform for gdpr-compliant personal data management. In 2021 IEEE 5th International Conference on Cryptography, Security and Privacy (CSP), pages 68–73.
De Donno, M., Tange, K., and Dragoni, N. (2019). Foundations and evolution of modern computing paradigms: Cloud, iot, edge, and fog. IEEE Access, 7:150936–150948.
Deepa, N., Pham, Q.-V., Nguyen, D. C., Bhattacharya, S., Prabadevi, B., Gadekallu, T. R., Maddikunta, P. K. R., Fang, F., and Pathirana, P. N. (2022). A survey on blockchain for big data: approaches, opportunities, and future directions. Future Generation Computer Systems.
Devlin, J., Chang, M.-W., Lee, K., and Toutanova, K. (2018). BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. arXiv preprint arXiv:1810.04805.
di Fiori, A.,West, K., and Segnalini, A. (2019). Why science-driven companies should use agile. Harvard Business Review, page 34.
Diddi, S. and Yan, R.-N. (2019). Consumer perceptions related to clothing repair and community mending events: A circular economy perspective. volume 11, page 5306. Multidisciplinary Digital Publishing Institute.
Dong, J. Q. and Yang, C.-H. (2018). Business value of big data analytics: A systems-theoretic approach and empirical test. Information & Management, page 103124.
Douceur, J. R. (2002). The sybil attack. In International workshop on peer-topeer systems, pages 251–260. Springer.
Eichmann, K. (2018). The future client of an energy utility company will be a machine. [link].
Elkington, J. (1997). The triple bottom line. Environmental management: Readings and cases, 2:49–66.
EMF (2012). Towards the circular economy: Economic and business rationale for an accelerated transition. https://ellenmacarthurfoundation.org/. [Online; Acessado em 13-Abril-2021].
EMF (2014). Towards the circular economy: Accelerating the scale-up across global supply chains. Ellen MacArthur Foundation (EMF) Isle of Wight, UK.
EMF (2015). Towards a circular economy: Business rationale for an accelerated transition. Ellen MacArthur Foundation (EMF) Isle of Wight, UK.
EMF (2021). Circulytics - measuring circularity. [link]. [Online; Acessado em 23- junho-2021].
Ernst, C., Ferrer, A. H., and Zult, D. (2005). The end of the multi-fibre arrangement and its implication for trade and employment. ILO Employment Strategy Paper, 16.
Etzkowitz, H. and Zhou, C. (2017a). Hélice tríplice: inovação e empreendedorismo universidade-indústria-governo. Estudos avançados, 31(90):23–48.
Etzkowitz, H. and Zhou, C. (2017b). The triple helix: University–industry–government innovation and entrepreneurship. Routledge.
Feng, F., Yang, Y., Cer, D., Arivazhagan, N., and Wang, W. (2020). Language-agnostic bert sentence embedding. arXiv preprint arXiv:2007.01852.
Ferdous, M. S., Chowdhury, F., and Alassafi, M. O. (2019). In search of self-sovereign identity leveraging blockchain technology. IEEE Access, 7:103059–103079.
Ferrell, O. (2021). Addressing socio-ecological issues in marketing: environmental, social and governance (esg). AMS Review, 11(1):140–144.
Filippova, K., Alfonseca, E., Colmenares, C.A., Kaiser, Ł., and Vinyals, O. (2015). Sentence compression by deletion with lstms. In Proceedings of the 2015 conference on empirical methods in natural language processing, pages 360–368.
Fuente, J. A., García-Sanchez, I. M., and Lozano, M. B. (2017). The role of the board of directors in the adoption of gri guidelines for the disclosure of csr information. Journal of Cleaner Production, 141:737–750.
Gandomi, A. and Haider, M. (2015). Beyond the hype: Big data concepts, methods, and analytics. volume 35, pages 137–144. Elsevier.
Garcia-Torres, S., Rey-Garcia, M., Sáenz, J., and Seuring- Stella, S. (2021). Traceability and transparency for sustainable fashion-apparel supply chains. Emerald Publishing Limited.
Gartner (2022). Gartner glossary. https://www.gartner.com/en/information-technology/glossary/big-data. [Online; Acessado em 25-Maio-2022].
Geissdoerfer, M., Morioka, S. N., de Carvalho, M. M., and Evans, S. (2018). Business models and supply chains for the circular economy. Journal of cleaner production, 190:712–721.
Geissdoerfer, M., Savaget, P., Bocken, N. M., and Hultink, E. J. (2017). The circular economy–a new sustainability paradigm? Journal of cleaner production, 143:757–768.
Gentry, C. (2009). Fully homomorphic encryption using ideal lattices. In STOC ’09.
Géron, A. (2019). Hands-on machine learning with Scikit-Learn, Keras, and TensorFlow: Concepts, tools, and techniques to build intelligent systems. "O’Reilly Media, Inc.".
Goldman, A., Kon, F., Junior, F. P., Polato, I., and Pereira, R. d. F. (2012). Apache Hadoop: conceitos teóricos e práticos, evolução e novas possibilidades, chapter 3, pages 88–136. XXXI Jornadas de Atualizações em Informática (JAI). Sociedade Brasileira de Computação (SBC).
Gonçalves, A. and Silva, C. (2021). Looking for sustainability scoring in apparel: A review on environmental footprint, social impacts and transparency. volume 14, page 3032. Multidisciplinary Digital Publishing Institute.
Gorelik, A. (2019). The Enterprise Big Data Lake: Delivering the Promise of Big Data and Data Science. O’Reilly Media, 1 edition.
Governo Federal, M. d. E. (2021). Guia de requisitos mínimos de segurança e privacidade para aplicativos móveis - lgpd. [link].
Graedel, T. E. (1996). On the concept of industrial ecology. Annual Review of Energy and the Environment, 21(1):69–98.
GRI (2021). Global reporting initiative–sustainability reporting guidelines. https://www.globalreporting.org/. [Online; Acessado em 26-Julho- 2021].
Grimpe, C. and Kaiser, U. (2010). Balancing internal and external knowledge acquisition: The gains and pains from r&d outsourcing. Journal of Management Studies, 47(8):1483–1509.
Gupta, R., Kushwaha, A., Dave, D., and Mahanta, N. R. (2022). Waste management in fashion and textile industry: Recent advances and trends, lifecycle assessment, and circular economy. Emerging Trends to Approaching Zero Waste, pages 215–242.
Gupta, S., Chen, H., Hazen, B. T., Kaur, S., and Gonzalez, E. D. S. (2019). Circular economy and big data analytics: A stakeholder perspective. Technological Forecasting and Social Change, 144:466–474.
Haber, S. and Stornetta, W. S. (1990). How to time-stamp a digital document. In Conference on the Theory and Application of Cryptography, pages 437–455. Springer.
Härting, R.-C., Reichstein, C., and Schad, M. (2018). Potentials of digital business models–empirical investigation of data driven impacts in industry. Procedia Computer Science, 126:1495–1506.
Hausberg, J., Liere-Netheler, K., Packmohr, S., Pakura, S., and Vogelsang, K. (2018). Digital transformation in business research: A systematic literature review and analysis. DRUID18, Copenhagen Business School, Copenhagen, Denmark.
Hayter, C. S., Rasmussen, E., and Rooksby, J. H. (2020). Beyond formal university technology transfer: innovative pathways for knowledge exchange. The Journal of Technology Transfer, 45(1):1–8.
Hidalgo, E. S. (2019). Adapting the Scrum framework for agile project management in science: Case study of a distributed research initiative. Heliyon, 5(3):e01447.
Highsmith, J. A. and Highsmith, J. (2002). Agile Software Development Ecosystems. Addison-Wesley Longman Publishing Co., Inc., USA.
Hilbert, M. (2022). Digital technology and social change: the digital transformation of society from a historical perspective. Dialogues in clinical neuroscience.
Hochreiter, S. and Schmidhuber, J. (1997). Long short-term memory. Neural computation, 9(8):1735–1780.
Hong, Z., Guo, S., Li, P., and Chen, W. (2021). Pyramid: A layered sharding blockchain system. IEEE INFOCOM.
Hospedales, T., Antoniou, A., Micaelli, P., and Storkey, A. (2020). Meta-Learning in Neural Networks: A Survey. arXiv preprint arXiv:2004.05439.
Huq, F. A., Stevenson, M., and Zorzini, M. (2014). Social sustainability in developing country suppliers: An exploratory study in the ready made garments industry of bangladesh. International Journal of Operations & Production Management.
IPCC (2021). Climate change 2021: The physical science basis. contribution of working group i to the sixth assessment report of the intergovernmental panel on climate change. IPCC.
Jake Frankenfield, S. G. A. (2020). Proof of elapsed time (poet) (cryptocurrency). https://www.investopedia.com/terms/p/proof-elapsed-time-cryptocurrency.asp.
Jestratijevic, I., Uanhoro, J. O., and Creighton, R. (2021). To disclose or not to disclose? fashion brands’ strategies for transparency in sustainability reporting. Emerald Publishing Limited.
Jiang, L., Da Xu, L., Cai, H., Jiang, Z., Bu, F., and Xu, B. (2014). An iot-oriented data storage framework in cloud computing platform. IEEE Transactions on Industrial Informatics, 10(2):1443–1451.
Jo, T. (2021). Machine Learning Foundations: Supervised, Unsupervised, and Advanced Learning. Springer Nature.
Johnston, D., Yilmaz, S. O., Kandah, J., Bentenitis, N., Hashemi, F., Gross, R., and Mason, S. (2014). The general theory of decentralized applications. DApps, [link]. pdf.
Júnior, V.O.D.S., Branco, J.A.C., De Oliveira, M.A., Da Silva, T. L. C., Cruz, L.A., and Magalhaes, R.P. (2021). A Natural Language Understanding Model COVID-19 based for chatbots. In 2021 IEEE 21st International Conference on Bioinformatics and Bioengineering(BIBE), pages 1–7. IEEE.
Kanban University (2021). The official guide to the Kanban method. Mauvius Group Inc.
Khan, D., Jung, L. T., and Hashmani, M. A. (2021). Systematic literature review of challenges in blockchain scalability. Applied Sciences, 11(20):9372.
Khan, N., Naim, A., Hussain, M. R., Naveed, Q. N., Ahmad, N., and Qamar, S. (2019). The 51 v’s of big data: survey, technologies, characteristics, opportunities, issues and challenges. In Proceedings of the international conference on omni-layer intelligent systems, pages 19–24.
Khan, S. A. R., Piprani, A. Z., and Yu, Z. (2022). Digital technology and circular economy practices: future of supply chains. Operations Management Research, pages 1–13.
King, S. and Nadal, S. (2012). Ppcoin: Peer-to-peer crypto-currency with proof-of-stake. self-published paper, August, 19:1.
Kirchherr, J., Reike, D., and Hekkert, M. (2017). Conceptualizing the circular economy: An analysis of 114 definitions. Resources, Conservation and Recycling, 127:221–232.
Kostoska, O. and Kocarev, L. (2019). A novel ict framework for sustainable development goals. Sustainability, 11(7):1961.
Koszewska, M. (2019). Circular economy in textiles and fashion—the role of a consumer. In Circular Economy in Textiles and Apparel, pages 183–206. Elsevier.
L., K. (2019). The blockchain scalability problem & the race for visa-like transaction speed. [link].
Laney, D. et al. (2001). 3d data management: Controlling data volume, velocity and variety. META group research note, 6(70):1.
Le, Q. and Mikolov, T. (2014). Distributed representations of sentences and documents. In ICML, pages 1188–1196. PMLR.
Lee, D. D., Kirkpatrick-Husk, K., and Madhavan, R. (2014). Diversity in alliance portfolios and performance outcomes: A meta-analysis. Journal of Management, 43(5):1472–1497.
Lee, I. (2017). Big data: Dimensions, evolution, impacts, and challenges. volume 60, pages 293–303. Elsevier.
Lehrer, C., Wieneke, A., vom Brocke, J., Jung, R., and Seidel, S. (2018). How big data analytics enables service innovation: materiality, affordance, and the individualization of service. Journal of Management Information Systems, 35(2):424–460.
Lerner, S. D. (2015). Rsk. Technical report, Tech. Rep.
Li, J. and Leonas, K. K. (2021). Sustainability topic trends in the textile and apparel industry: a text mining-based magazine article analysis. Journal of Fashion Marketing and Management: An International Journal.
Li, S., Xu, L. D., and Zhao, S. (2015). The internet of things: a survey. Information systems frontiers, 17(2):243–259.
Liu, F., Tong, J., Mao, J., Bohn, R., Messina, J., Badger, L., Leaf, D., et al. (2011). Nist cloud computing reference architecture. NIST special publication, 500(2011):1–28.
Liu, N.F., Gardner, M., Belinkov, Y., Peters, M.E., and Smith, N.A. (2019). Linguistic knowledge and transferability of contextual representations. arXiv preprint arXiv:1903.08855.
Liu, Z., Liu, J., and Osmani, M. (2021). Integration of digital economy and circular economy: Current status and future directions. Sustainability, 13(13):7217.
Louis, A. (2020).A Brief History of Natural Language Processing—Part 2.
Lu, Y. (2019). The blockchain: State-of-the-art and research challenges. Journal of Industrial Information Integration, 15:80–90.
Marquesone, R. d. F. P. (2016). Big Data: Técnicas e tecnologias para extração de valor dos dados. Casa do Código, São Paulo.
Marquesone, R. d. F. P. and Carvalho, T. C. M. B. (2022a). Modelo de implementação de big data como apoio na transição para a economia circular na indústria têxtil. PhD thesis.
Marquesone, R. d. F. P. and Carvalho, T. C. M. d. B. (2022b). Examining the nexus between the vs of big data and the sustainable challenges in the textile industry. Sustainability, 14(8):4638.
Martínez-Caro, E., Cegarra-Navarro, J. G., and Alfonso- Ruiz, F. J. (2020). Digital technologies and firm performance: The role of digital organisational culture. Technological Forecasting and Social Change, 154:119962.
Matlin, S. A., Mehta, G., Hopf, H., Krief, A., Keßler, L., and Kümmerer, K. (2020). Material circularity and the role of the chemical sciences as a key enabler of a sustainable post-trash age. Sustainable Chemistry and Pharmacy, 17:100312.
Mattila, J. (2016). The blockchain phenomenon. Berkeley Roundtable of the International Economy, 16.
Maxwell, G., Poelstra, A., Seurin, Y., andWuille, P. (2019). Simple schnorr multi-signatures with applications to bitcoin. Designs, Codes and Cryptography, 87(9):2139–2164.
Mazzei, M. J. and Noble, D. (2019). Big data and strategy: Theoretical foundations and new opportunities. In Strategy and Behaviors in the Digital Economy. IntechOpen.
McCulloch, W.S. and Pitts, W. (1943). A logical calculus of the ideas immanent in nervous activity. The bullet in of mathematical biophysics, 5(4):115–133.
McDonough, W. and Braungart, M. (2010). Cradle to cradle: Remaking the way we make things. North point press.
McKinsey (2020). Fashion on climate: How the fashion industry can urgently act to reduce its green house gas emission. [link]. [Online; Acessado em 13-Abril-2021].
Mearian, L. (2019). Sharding: What it is and why many blockchain protocols rely on it. [link].
Mendes (org.), M. (2022). Para não esquecer: políticas públicas que empobrecem o Brasil. Autografia, 1 edition.
Mendes de Melo, S., Lima Férrer de Almeida, A., Almada Cruz, L., and Linhares Coelho da Silva, T. (2021). A chat recommender system for covid-19 support based in textual sentence embeddings.In IEEE/WIC/ACM International Conference on Web Intelligence, pages 248–252.
Mikalef, P., Krogstie, J., Pappas, I. O., and Pavlou, P. (2019). Exploring the relationship between big data analytics capability and competitive performance: The mediating roles of dynamic and operational capabilities. Elsevier.
Mikolov, T., Chen, K., Corrado, G., and Dean, J. (2013). Efficient Estimation of Word Representations in Vector Space. arXiv preprint arXiv:1301.3781.
Modgil, S., Gupta, S., Sivarajah, U., and Bhushan, B. (2021). Big data-enabled large-scale group decision making for circular economy: An emerging market context. volume 166, page 120607. Elsevier.
Moorhouse, D. (2020). Making fashion sustainable: Waste and collective responsibility. One Earth, 3(1):17–19.
Moura, E. (2021). Cartesi rollups. [link]. Accessed on 2022-02.
Mungcharoen, T., Varabuntoonvit, V., and Poolsawad, N. (2021). Life Cycle Greenhouse Gas Emissions for Circular Economy. Springer.
Muratov, F., Lebedev, A., Iushkevich, N., Nasrulin, B., and Takemiya, M. (2018). Yac: Bft consensus algorithm for blockchain. arXiv preprint arXiv:1809.00554.
Nakamoto, S. (2008). Bitcoin: A peer-to-peer electronic cash system. Decentralized Business Review, page 21260.
Nakamoto, S. (2008). Bitcoin: A peer-to-peer electronic cash system. Decentralized Business Review, page 21260.
Neumann, M.P.M., Iyyer, M., Gardner, M., Clark, C., Lee, K., and Zettlemoyer, L. (2018). Deep Contextualized Word Representations. arXiv preprint arXiv:1802.05365.
Neves Oliveira, B.S., Fernandes de Oliveira, A., Monteiro de Lira, V., Linhares Coelho da Silva, T., and Fernandes de Macêdo, J.A. (2022). Held: Hierarchical entity-label disambiguation in named entity recognition task using deep learning. Intelligent Data Analysis, 26(3):637–657.
OECD (2015). Frascati Manual 2015. OECD publishing.
OECD and Eurostat (2018). Oslo Manual 2018. OECD publishing.
OmniLayer, C. (2020). Omnilayer documentation. https://github.com/OmniLayer/spec/blob/master/OmniSpecification-v0.6.adoc.
ONU (2021a). Objetivo 12. assegurar padrões de produção e de consumo sustentáveis. https://brasil.un.org/pt-br/sdgs/12. [Online; Acessado em 13-Abril-2021].
ONU (2021b). Objetivos de desenvolvimento sustentável. https://brasil.un.org/pt-br/sdgs. [Online; Acessado em 13-Abril-2021].
Pahlajani, S., Kshirsagar, A., and Pachghare, V. (2019). Survey on private blockchain consensus algorithms. In 2019 1st International Conference on Innovations in Information and Communication Technology (ICIICT), pages 1–6. IEEE.
Pennington, J., Socher, R., and Manning, C.D. (2014).GloVe: Global Vectors for Word Representation. In Proceedings of the 2014 conference on empirical methods in natural language processing(EMNLP), pages 1532–1543.
Pogrebnoy, K. and Yatskevich, O. (2022). Agile or waterfall: Choose the right approach to your software project management. Accessed: May 2022.
Potting, J., Hekkert, M., Worrell, E., and Hanemaaijer, A. (2017). Circular economy: measuring innovation in the product chain. Number 2544. PBL publishers.
Raharjo, T. and Purwandari, B. (2020). Agile project management challenges and mapping solutions: A systematic literature review. In Proceedings of the 3rd International Conference on Software Engineering and Information Management, ICSIM ’20, pages 123–129, New York, NY, USA. Association for Computing Machinery.
Rajasekaran, A. S., Azees, M., and Al-Turjman, F. (2022). A comprehensive survey on blockchain technology. Sustainable Energy Technologies and Assessments, 52:102039.
Ramzan, S., Bajwa, I. S., Ramzan, B., and Anwar, W. (2019). Intelligent data engineering for migration to nosql based secure environments. IEEE Access, 7:69042–69057.
Rani, H. and Saha, G. (2021). Organizations and standards related to textile and fashion waste management and sustainability. In Waste Management in the Fashion and Textile Industries, pages 173–196. Elsevier.
Ranjan, J. (2019). The 10 vs of big data framework in the context of 5 industry verticals. Productivity, 59(4).
Rashidi, H. H., Tran, N. K., Betts, E. V., Howell, L. P., and Green, R. (2019). Artificial intelligence and machine learning in pathology: the present landscape of supervised methods. Academic pathology, 6:2374289519873088.
Rebello, G., Camilo, G., Silva, L., Souza, L., Guimarães, L., Alchieri, E., Greve, F., and Duarte, O. (2019). Correntes de blocos: Algoritmos de consenso e implementação na plataforma hyperledger fabric. Sociedade Brasileira de Computação.
Revoredo, T. (2019). Blockchain: tudo que você precisa saber (potencial e realidade).
Rogers, K. and Hudson, B. (2011). The triple bottom line: The synergies of transformative perceptions and practices for sustainability, with barclay hudson, od practitioner (fall 2011). OD Practitioner.
Rosenblatt, F. (1958). The perceptron: a probabilistic model for information storage and organization in the brain. Psychological review, 65(6):386.
Rumelhart, D.E., Hinton, G.E., and Williams, R.J. (1985).Learning internal representations by error propagation. Technical report, California Univ San Diego La Jolla Inst for Cognitive Science.
Russel, S., Norvig, P., et al. (2013). Artificial intelligence: a modern approach. Pearson Education Limited London.
Sá, C. (2022). Escalabilidade para ethereum com rollups. https://goblockchain.io/escalabilidade-para-ethereum-com-rollups/. Accessed on 2022-05.
SAC (2021). The higg index. https://portal.higg.org/. [Online; Acessado em 28-Junho-2021].
Saha, K., Dey, P. K., and Papagiannaki, E. (2021). Implementing circular economy in the textile and clothing industry. Business Strategy and the Environment, 30(4):1497–1530.
Sandvik, I. M. and Stubbs, W. (2019). Circular fashion supply chain through textile-to-textile recycling. Journal of Fashion Marketing and Management: An International Journal.
Sawadogo, P. and Darmont, J. (2021). On data lake architectures and metadata management. Journal of Intelligent Information Systems, 56(1):97–120.
Schwaber, K. and Sutherland, J. (2020). The Scrum Guide – The Definitive Guide to Scrum: The Rules of the Game. Share-Alike license of Creative Commons.
Shor, P. (1994). Algorithms for quantum computation: discrete logarithms and factoring. In Proceedings 35th Annual Symposium on Foundations of Computer Science, pages 124–134.
Shor, P. W. (1997). Polynomial-time algorithms for prime factorization and discrete logarithms on a quantum computer. SIAM Journal on Computing, 26(5):1484–1509.
Souza, F., Nogueira, R., and Lotufo, R. (2020). BERTimbau: Pretrained BERT Models for Brazilian Portuguese. In Brazilian Conference on Intelligent Systems, pages 403–417.Springer.
Stach., C., Giebler., C., Wagner., M., Weber., C., and Mitschang., B. (2020). Amnesia: A technical solution towards gdpr-compliant machine learning. In Proceedings of the 6th International Conference on Information Systems Security and Privacy - ICISSP,, pages 21–32. INSTICC, SciTePress.
Sun, S. (2008). Organizational culture and its themes. International Journal of Business and Management, 3(12):137–141.
Sutherland, J. (2014). Scrum: The Art of Doing Twice the Work in Half the Time. Random House Publishing Group.
Sutskever, I., Vinyals, O., and Le, Q.V. (2014a). Sequence to Sequence Learning with Neural Networks. Advances in neural information processing systems, 27.
Sutskever, I., Vinyals, O., and Le, Q.V. (2014b). Sequence to sequence learning with neural networks. Advances in neural information processing systems, 27.
Szabo, N. (1996). Smart contracts: building blocks for digital markets. EXTROPY: The Journal of Transhumanist Thought,(16), 18(2):28.
Takeuchi, H. and Nonaka, I. (1986). The new new product development game. Harvard Business Review.
Tas, O. and Kiyani, F. (2007). A survey automatic text summarization. PressAcademia Procedia, 5(1):205–213.
Teixeira, A. and Nehab, D. (2018). The core of cartesi. Whitepaper, Cartesi.
Thorisdottir, T. S. and Johannsdottir, L. (2019). Sustainability within fashion business models: A systematic literature review. Sustainability, 11(8):2233.
Tianchen, W., Miaoyan, X., Han, C., and Yuming, Y. (2021). An in-depth look at rollup’s tech, application, and data. [link]. Accessed on 2022-03.
Torregrossa, F., Allesiardo, R., Claveau, V., Kooli, N., and Gravier, G. (2021).A survey on training and evaluation of word embeddings. International Journal of Data Science and Analytics, 11(2):85–103.
Trentim, M. H. (2017). Gerenciamento de Projetos: Guia para Certificações CAPM e PMP. Atlas, 2 edition.
Truong, N. B., Sun, K., Lee, G. M., and Guo, Y. (2020). Gdpr-compliant personal data management: A blockchain-based solution. IEEE Transactions on Information Forensics and Security, 15:1746–1761.
Tseng, F.-C., Huang, M.-H., and Chen, D.-Z. (2020). Factors of university–industry collaboration affecting university innovation performance. The Journal of Technology Transfer, 45(2):560–577.
UNFCC (2018). Earth’s annual resources budget consumed in just 7 months. [link]. [Online; Acessado em 13-Abril-2021].
Ütebay, B., Çelik, P., and Çay, A. (2020). Textile wastes: Status and perspectives. In Waste in Textile and Leather Sectors. IntechOpen.
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, Ł., and Polosukhin, I. (2017). Attention is All You Need. In Advances in neural information processing systems, pages 5998–6008.
Vial, G. (2019). Understanding digital transformation: A review and a research agenda. The Journal of Strategic Information Systems.
Voita, E. (2020). NLP Course For You.
Wagner, C. S., Whetsell, T. A., and Leydesdorff, L. (2017). Growth of international cooperation in science: Revisiting six case studies. Scientometrics, 110:1633–1652.
Wang, G., Shi, Z. J., Nixon, M., and Han, S. (2019). Sok: Sharding on blockchain. In Proceedings of the 1st ACM Conference on Advances in Financial Technologies, pages 41–61.
Wang, L., Jiang, J., Chieu, H.L., Ong, C.H., Song, D., and Liao, L. (2017).Can syntax help? improving an lstm-based sentence compression model for new domains.In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics(Volume1: LongPapers), pages1385–1393.
Weber, B. and Heidenreich, S. (2018). When and with whom to cooperate? investigating effects of cooperation stage and type on innovation capabilities and success. Long Range Planning, 51(2):334–350.
Webster, J.J. and Kit, C. (1992). Tokenization as the initial phase in NLP. In COLING 1992 Volume 4: The 14th International Conference on Computational Linguistics.
WIKIRATE (2021). Wiki rate. https://wikirate.org/. [Online; Acessado em 28-Junho-2021].
Wood, G. (2014). Ethereum: A secure decentralised generalised transaction ledger. Ethereum Project Yellow Paper, 151.
Wu, K., Ma, Y., Huang, G., and Liu, X. (2021). A first look at blockchain-based decentralized applications. Software: Practice and Experience, 51(10):2033–2050.
Ynalvez, M. A. and Shrum, W. M. (2011). Professional networks, scientific collaboration, and publication productivity in resource-constrained research institutions in a developing country. Research Policy, 40(2):204–216.
Yordanova, Z. (2021). Agile Application for Innovation Projects in Science Organizations - Knowledge Gap and State of Art, volume 1330, pages 108–117. Springer, Cham.
Yordanova, Z., Stoimenov, N., Boyanova, O., and Ivanchev, I. (2019). The long way from science to innovation – a research approach for creating an innovation project methodology. In Business Information Systems.
Yuan, Y. and Wang, F.-Y. (2018). Blockchain and cryptocurrencies: Model, techniques, and applications. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 48(9):1421–1428.
Zaharia, M., Xin, R. S., Wendell, P., Das, T., Armbrust, M., Dave, A., Meng, X., Rosen, J., Venkataraman, S., Franklin, M. J., et al. (2016). Apache spark: a unified engine for big data processing. Communications of the ACM, 59(11):56–65.
Zhang, L., Wang, S., and Liu, B. (2018).Deep learning for sentiment analysis: A survey. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 8(4):e1253.
Zhou, Q., Huang, H., Zheng, Z., and Bian, J. (2020a). Solutions to scalability of blockchain: A survey. IEEE Access, 8:16440–16455.
Zhou, Q., Huang, H., Zheng, Z., and Bian, J. (2020b). Solutions to scalability of blockchain: A survey. IEEE Access, 8:16440–16455.
Zschornack R.S., F., Linhares Coelho da Silva, T., and Fernandes de Macêdo, J.A. (2020). Aspect term extraction using deep learning model with minimal feature engineering. In International Conference on Advanced Information Systems Engineering, pages 185–198. Springer.
Detalhes sobre o formato disponível para publicação: Volume Completo
© O(s) autor(es), 2022.

Esse trabalho foi publicado de acordo com os termos da licença Creative Commons Attribution 4.0 International License
.