2020· International Conference on Software Business· pp. 70-85· 9 citations· 27 references
Computer Science
TL;DR
It is found that the key conditions for making these blockchain-based solutions viable are attaining technological maturity and competences, ecosystem thinking and adequate governance of these ecosystems, and finally (3) achieving legal and regulatory predictability.
The digital revolution and the emergence of new technologies are reshaping nearly every domain of life. The monetization of artistic forms is one of the achievements enabled by these tech-nologies. The paper proposes a conceptual model that combines blockchain-based asset tracking with a new way of representing value r...
S. Cabarkapa, Đorđe Mladenović, Milanko Kragović et al.· PROCEEDINGS 13th Internation...· 0 citations
A comprehensive survey of the main blockchain platforms utilized in the digital healthcare, integrated with a comparative analysis, and the implementation of Innovative permissioned Blockchain for eHealth (IBEH) is presented and discussed in detail.
A. Vizzarri, Franco Mazzenga· Applied Sciences· 0 citations
The results indicated the importance of considering factors such as the technology learning curve and citizens’ digital familiarity when designing blockchain-based solutions for the public sector when designing blockchain-based solutions for the public sector.
Iago Fernandes, Pamella Soares, Raphael Saraiva et al.· Anais do XI Workshop sobre A...· 0 citations
The study argues that technical deployment must be accompanied by rules on personal-data protection, legal recognition, node governance, node governance, and measurable pilot-testing criteria, and illustrates differences between centralized and blockchain-based models in terms of integrity assurance, verification time,...
Ilyos Shaydullayev, Sherzod Samarov· Raqamli huquq va innovatsiya...· 0 citations
The author thoroughly reviews how blockchain technology and FinTech innovation can transform financial services, payment systems, and capital markets and examines experimental applications that show the increase in performance in terms of transaction processing, efficiency in encryption, and validation of authorization...
Shipra Yadav, L. Rao, Saumendra Das· International Journal of Adv...· 0 citations
The findings underscore unique trade-offs across platforms: Ethereum supports transparency but is prone to transaction manipulation; Hyperledger ensures strong access control yet faces insider threat challenges; and MedRec enhances patient privacy but lacks robust mobile integration.
Godwin Mandinyenya, Vusumuzi Malele· International Journal of Inf...· 0 citations
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity. The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.
Computer scientist, entrepreneur, and philanthropist will collaborate with the MIT Schwarzman College of Computing to advance AI and scientific discovery.
