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96,811 results · page 287 of 4,034
Caleb Price, Mckenzie Curtis
No abstract is available for this record.
Isabel Palomo-Domínguez, Rodrigo Elías-Zambrano, Miglé Eleonora Černikovaitė
El presente artículo aborda la realidad digital reciente y el contexto contemporáneo, con el objetivo de comprender la casuística de los NFT en Europa a través de dos casos de expansión comparativos: el español y el lituano. Metodológicamente, el estudio adopta un enfoque híbrido, combinando la revisión teórica de los Non-Fungible Tokens con técnicas empíricas de recolección de datos, como entrevistas en profundidad y encuestas. De manera preliminar, se realizó un análisis bibliométrico utilizando la base de datos Scopus, lo que permitió identificar y seleccionar los artículos más influyentes publicados en revistas de alto impacto. Esta fase inicial facilitó la delimitación de los ejes temáticos y subtemáticos que sostienen el desarrollo del trabajo. Los resultados indican que la mayoría de los estudios revisados emplean metodologías cualitativas y aportan marcos conceptuales para la aplicación práctica de los NFT, validando su relevancia en campos como la publicidad, la comunicación y las artes. El análisis de contenido identifica seis líneas principales: características, expansión, aplicaciones, repercusiones, percepciones del mercado y marco jurídico. Además, el estudio evidencia el potencial de los NFT para la diversificación y conectividad de la industria cultural, así como su creciente relevancia en entornos de realidad virtual y aumentada, destacando su papel como herramienta innovadora en la transformación digital del arte y la comunicación.
Christos Makridis
No abstract is available for this record.
Kumar Rohan
No abstract is available for this record.
Rayhan Abbrar
No abstract is available for this record.
Lin William Cong, Simon Mayer, Daniel Rabetti
No abstract is available for this record.
Djamel Eddine Hakim Ghorab, Farid Mokhati, Mostafa Anouar Ghorab
No abstract is available for this record.
Preethi, Mohammed Mujeer Ulla, R. Sapna, Dr Raghavendra M Devadas · 6 authors
No abstract is available for this record.
T. Niklas Kroner, Idrees Mohammed, Clara Vega
No abstract is available for this record.
Changhao Wu, Jitao Wang, Junwei Xu, Weili Han · 5 authors
No abstract is available for this record.
Tiago Ferreira Cavazin
<b>RESUMO</b>O presente artigo analisa as estratégias de otimização de gas na rede Ethereum, focando na interação técnica entre os opcodes da Ethereum Virtual Machine (EVM) e a eficiência das estruturas de dados. Com a evolução da rede e a implementação de atualizações críticas como o EIP-1559 e o upgrade Dencun, a economia de recursos computacionais tornou-se um imperativo não apenas para a viabilidade financeira das transações, mas também para a escalabilidade e segurança de contratos inteligentes. O estudo detalha os custos associados às operações de armazenamento (Storage), memória volátil (Memory) e calldata, explorando o impacto de novas funcionalidades como o armazenamento transitório (EIP-1153). Através de uma revisão sistemática de literatura técnica e benchmarks algorítmicos, demonstra-se que a escolha criteriosa de tipos de dados, o empacotamento de variáveis (variable packing) e a substituição de padrões de iteração por mapeamentos podem reduzir significativamente o consumo de gas. Conclui-se que a otimização de alto nível deve ser acompanhada por uma compreensão profunda da arquitetura de baixo nível da EVM, assegurando que a redução de custos não comprometa a integridade lógica do sistema.<br>
Rodica Doina Zmaranda, Attila-Imre Kovacs, Daniela Elena Popescu, Alexandrina Mirela Pater
Securing electronic health records (EHR) requires strong guarantees for confidentiality, integrity, access control, and auditability. Traditional centralized architectures rely on database-level protection and internal logging, which remain vulnerable to insider misuse and undetected data modification. This study proposes a practical hybrid architecture in which medical content is stored encrypted off-chain, while blockchain is used selectively as a governance and evidence layer. An Ethereum-based prototype was designed and implemented to support integrity anchoring of medical documents, patient-controlled consent management, and immutable audit trails for critical actions. In the implemented solution, the actual medical content is not stored on-chain. Instead, the blockchain stores only document-related metadata, cryptographic hashes, document references, and access-control information, while the sensitive medical data remains encrypted and stored off-chain. This design supports GDPR-oriented data minimization, since the immutable blockchain layer does not contain raw medical records or directly identifiable medical content. The prototype separates confidentiality from blockchain immutability. Medical document confidentiality is handled at the application and off-chain storage level, while the blockchain is used for integrity verification, consent management, and auditability. Encryption keys are not stored on-chain, which prevents the blockchain layer from becoming a repository of sensitive or directly exploitable medical information. Security mechanisms are integrated directly into application flows, including hash-based tamper detection and on-chain verification of access rights. The prototype is evaluated through realistic operational scenarios, analyzing security properties, performance, and transaction cost implications. Results show that, relative to a DB-only baseline, the hybrid approach provides structurally stronger support for integrity verification, traceability, and accountability without exposing sensitive medical data on-chain. The study also highlights practical limitations related to latency and costs in public blockchain environments, supporting a selective on-chain design focused on high-value operations.
Lucas Dünnes, Jens Eckberg
No abstract is available for this record.
Rachid Bourday, Ali Zaaouat, Issam Aattouchi, M. Ait Kerroum
Predicting cryptocurrency prices with precision is crucial for strategic financial planning, enabling stakeholders to mitigate risks in the highly unpredictable nature of digital assets. This paper presents an innovative framework combining Bidirectional Long Short-Term Memory (Bi-LSTM) and Graph Attention Networks (GATs) to improve forecasting accuracy for Ethereum. The Bi-LSTM analyzes time-based trends in historical price and trading volume over a 90-day horizon, whereas GATs examine correlations between critical market features, including 20-day and 30-day moving averages, through attention-focused techniques. When applied to Ethereum's historical price data, the model achieves an MSE of 0.0021, RMSE of 0.046, and MAE of 0.032, exceeding traditional LSTM-based approaches. These outcomes highlight the advantages of fusing sequential neural architectures with graph-structured relational modeling to refine predictive accuracy. By unifying time-series and graph-structured data analysis, this study contributes to the advancement of financial analytics powered by deep learning, equipping traders and researchers with an actionable tool to refine trading tactics within Ethereum's dynamic ecosystem.
Guoyu Zheng, Yining Hu
No abstract is available for this record.
Wassim Sliti, Félix Cuadrado, Leandro Campos Hernáez, Juan C. Dueñas
Illicit activities and coordinated manipulations in the Non-Fungible Tokens (NFT) market remain significant concerns, driven by the pseudonymous and publicly transparent nature of blockchain transactions and the lack of market oversight. In this study, we introduce a novel framework for detecting suspicious behavior in NFT trading ecosystems through temporal graph analysis. Our approach represents the market as a large-scale, time-evolving transactional graph, capturing realistic market dynamics and the complex interactions between traders.By leveraging temporal graphs, we track not only connections between traders but also the evolution of these interactions over time, including their sequence, rhythm, and frequency, enabling the identification of anomalous behaviors that static graph representations cannot reveal and that may warrant further examination. Using an optimized temporal cycle-detection algorithm, we extract connected groups of wallets for in-depth behavioral analysis, uncovering patterns indicative of unusual coordinated manipulation. To overcome the absence of labeled ground-truth validation data, we employ a temporal motif–based validation, demonstrating that flagged entities exhibit trading behaviors significantly deviating from standard market dynamics. Our results highlight the potential of temporal graph–based methodologies to provide a scalable and effective risk-profiling and market-surveillance tool, assisting analysts and regulatory entities in narrowing the investigation space within the large, permissionless NFT markets and enhancing surveillance, risk detection, and regulatory oversight in decentralized NFT markets.
Andry Alamsyah, Nurdiana Safitri, Dian Puteri Ramadhani
Non-Fungible Tokens (NFTs) have emerged as a new organizational layer of digital exchange, raising questions about how participation, concentration, and community formation are structured within on-chain markets. Understanding whether these structures differ systematically across blockchain ecosystems with distinct asset orientations requires examining ecosystem-level interaction patterns. Most studies focus on specific collections or single platforms, offering limited insight into how connectivity, concentration, and community structure vary across markets with different NFT use cases. This study compares Ethereum and Polygon, two major NFT platforms with distinct dominant asset orientations (investment-oriented vs utility-oriented), to examine how their transaction networks differ at the ecosystem level. Using 3.9 million NFT transactions from May 2022 to May 2024, we apply network analysis to assess connectivity, centralization, community structure, and temporal dynamics. The findings show highly skewed interaction patterns in both ecosystems, with a small subset of addresses accounting for a disproportionate share of activity. Polygon networks exhibit higher modular segmentation and sharper upper-tail dominance, with communities aligning near-perfectly with application-specific boundaries, whereas Ethereum networks display comparatively more integrated, crosscollection interaction structure. These contrasts are interpreted as ecosystem-level structural patterns conditional on each chain's market composition and dominant NFT use cases, offering socio-technical insights into how participation concentrates and communities form across blockchain-based digital markets.
Vaibhav Dureja
No abstract is available for this record.
Yuyang Zhao, Fernando Bacao, YanLing Li, Ping Dong · 6 authors
No abstract is available for this record.
Ahmad Alsuwaidi, Irénée Dondjio
No abstract is available for this record.
Xiaoyun Rong, Xi Zhao, Gengzhong Feng, Xiaoni Lu
No abstract is available for this record.
Reem E. Mohamed, Mukhtar Hussain, Zahra Jadidi, Ernest Foo · 5 authors
No abstract is available for this record.
Muhammad Umair
No abstract is available for this record.
Sanela Nikolić, Biljana Leković
The main objective of this paper is to outline the psychological aspects of trading in the music NFT (non-fungible tokens) ecosystem, with special emphasis on the psychological background of buying NFTs. Since the most important feature of NFTs is the acquisition of ownership enabled by technological solutions, we assume that each purchase of a token does not only imply an economic exchange of ownership, but also the activation of psychological ownership. Having in mind that psychological ownership is a relative category that depends, among other factors, on the nature of the target to which it is attached, our investigation is conceptual rather than empirical. By connecting the already identified cores of psychological ownership to the characteristics of some of the most prominent music NFT drops, we aim to theoretically define general dimensions of psychological ownership through which emotional and social connections to music NFTs as objects of ownership emerge. We conclude that the NFT market reinforces psychological ownership by providing consumers valuable outcomes. In terms of music NFTs, the concept of psychological ownership can be explained by several intertwined dimensions that create emotional and social connections and motivate users to purchase these digital goods. These include a sense of unique possession, identity and self-expression, a sense of belonging to a community, and investment opportunities. The NFT drops discussed illustrate how leveraging different aspects of psychological ownership can transform a music release into a special experience that reshapes the relationship between fans and musicians. Examining fans’ purchases of music NFTs from a psychological perspective can help musicians better understand blockchain users’ behaviour towards music, which is essential for developing NFTs into a sustainable digital format for music revenue.