La reciente sentencia dictada por el Juzgado de lo Mercantil de Barcelona en enero de 2024 ha supuesto el primer pronunciamiento de un tribunal español sobre una cuestión tan controvertida como los non-fungible tokens (conocidos comúnmente como NFTs) y su relación con los derechos de autor. Este trabajo busca realizar un análisis sobre las características esenciales de los NFTs y la posible afectación de las obras de propiedad intelectual que en muchas ocasiones estos activos llevan vinculadas. Para ello, se combina una exposición teórica desde el punto de vista doctrinal español e internacional de los elementos definitorios que componen un NFT, con una aproximación práctica comparada a través de la reciente casuística jurisdiccional sobre la cuestión. Con ello, el trabajo busca dar una visión actualizada de la problemática y aportar posibles vías de solución a una cuestión reciente que todavía permanece abierta desde el punto de vista del derecho de autor.
본 연구의 목적은 허딩과 소유욕이 수용 행위에 미치는 효과의 타당성을 검증하고자 하는 것이다. 연구방법으로는 대체불가능토큰(Non Fungible Token)을 이용한 경험이 있는 221명으로부터 수집된 자료를 SPSS 27.0과 AMOS 27 프로그램을 사용하여 기술적 통계분석, 탐색적 요인 분석과 가설검증을 위해 구조방정식 모형을 이용하였다. 검증을 통하여 다음과 같이 분석하였다. 첫째, 허딩이 과업기술적합성(Task Technology Fit)모형에 미치는 영향을 분석한 결과, 유의성이 있는 것으로 나타났다. 둘째, 소유욕이 과업기술적합성에 미치는 영향을 분석한 결과, 소유욕이 과업기술적합성에 통계적으로 영향을 미치는 것으로 분석되었다. 셋째, 과업기술적합성이 수용 행위에 미치는 영향을 분석한 결과, 긍정적인 영향을 주었다. 본 연구의 시사점은 블록체인 기술을 이용한 대체불가능토큰 특성을 이용하여 과업과 그에 적합한 기술을 조합하여 업무의 생산성을 향상시킬 수 있으며 과업기술적합성을 매개변수로 수용 행위가 이루어진다는 것을 확인하였다.
Blockchain has moved from a cryptocurrency infrastructure to a coordination technology for modern communication systems. This review examines how blockchain is being embedded into next-generation communication environments, with particular attention to Internet of Things deployments, edge-cloud collaboration, cyber-physical infrastructures, security and privacy management, smart grids, vehicular networking, and emerging 5G/6G ecosystems. Following the logic of recent survey work on blockchain-enabled communications, the article synthesizes representative peer-reviewed studies, clarifies the blockchain mechanisms that matter for communication engineering, and organizes the literature around application layers rather than isolated protocols. The review shows that blockchain creates value when communication systems require shared trust, auditable automation, decentralized identity, incentive-compatible coordination, or tamper-resistant data exchange across organizational boundaries. At the same time, real deployment remains constrained by throughput, latency, storage overhead, interoperability, privacy leakage, governance complexity, and uneven energy efficiency across consensus designs. Building on both communication-network research and information-systems scholarship, the article develops an integrated analytical view of when blockchain genuinely improves communication architectures and when lighter coordination mechanisms are preferable. The paper concludes by identifying future directions around lightweight consensus, AI-native blockchain orchestration, cross-chain communication fabrics, privacy-preserving verification, and programmable trust for 6G and autonomous infrastructures.
Multi-Agent AI Systems (MAS) rely on the cooperative actions of autonomous agents to meet difficult and rapidly changing issues in analysis and business strategy. In contrast to single-agent models, MAS includes different agents that team up, change as needed and function in real time. Thanks to its decentralized and modular design, businesses can scale their activities, maintain good stability and flex their operations as market situations change. With the help of advanced AI like Generative AI, MAS can examine huge datasets, perform market simulations and support smart decisions from leaders. Such algorithms are applied to everything from setting creative prices to improving supply chains, assessing risks and detecting fraud in the financial industry. The use of MAS makes it possible for tasks to be split and completed by multiple processors, which helps reduce workflow trouble spots. Additionally, its ability to respond to uncertainty and make quick, real-world decisions makes MAS a vital instrument for industries needing both agility and innovation. With MAS, organizations become stronger competitors by streamlining their work processes, encouraging innovation and solving problems on many scales. The future success of MAS comes from its power to change how businesses run smoothly by working with present technology and developing together with the company's needs.
The increasing demand for cloud computing services has led to the rapid expansion of cloud data centers, which consume significant amounts of energy and contribute substantially to global CO2 emissions. As the IT industry grows, the environmental impact of these data centers becomes an urgent concern. Green Cloud Computing (GCC) has emerged as a solution to mitigate this impact by focusing on energy efficiency and reducing carbon footprints while maintaining the necessary functionality and performance of cloud infrastructures. However, traditional blockchain consensus algorithms such as Proof of Work (PoW) and Proof of Stake (PoS) face limitations regarding energy consumption and scalability, which exacerbates the environmental burden. This study proposes a quantum-inspired blockchain consensus algorithm designed to optimize energy consumption and reduce latency in cloud data centers. By integrating quantum principles such as superposition and entanglement, the algorithm enhances task scheduling and resource utilization, enabling more energy-efficient operations without sacrificing performance. Simulations in a green cloud environment showed that the quantum-inspired algorithm resulted in up to a 30% reduction in energy usage compared to traditional consensus methods, with a 40% improvement in consensus processing time. These results suggest that quantum-inspired algorithms hold significant potential for enhancing the sustainability of cloud infrastructures by improving energy efficiency and scalability. Furthermore, this study discusses the feasibility of implementing quantum-inspired algorithms on classical hardware, addressing challenges in scalability and integration into existing blockchain frameworks. The findings provide valuable insights into the potential of quantum-inspired technologies to drive energy-efficient solutions in cloud computing.
Introduction. In the context of Ukraine's European integration course and the state's implementation of the decentralization reform, the importance of local self-government as the basis for the development of territorial communities is increasing. Particularly relevant are the issues of filling local budgets with revenues to ensure that local authorities perform their functions, adequately finance social and economic programs, and create the preconditions for improving the quality of life of the population. Problem Statement. Filling local budgets with funds, creating a financial basis for the development of local self-government. Purpose. Research on changes in local budget revenue formation caused by the implementation of decentralization reforms in Ukraine (with a focus on territorial community budgets), determination of losses incurred by local treasuries and the additional revenues they received in the pre-war (before the start of full-scale war) period of reform (2015–2021), justification of ways to preserve budget revenues in an inflationary economy. Methods. The article uses general scientific methods, namely: descriptive, statistical and economic, monographic, and theoretical generalization. Results. The changes in the formation of local budget revenues (with a focus on the budgets of territorial communities) that took place in Ukraine during the implementation of the decentralization reform in 2015-2021 are described. The amounts of losses and additional revenues received by budgets as a result of the changes implemented are calculated. The methods enshrined in current legislation that allow budget revenues to be protected from inflationary depreciation are described. Conclusions. The implementation of the decentralization reform in Ukraine was accompanied by significant changes in budgetary and tax rules, including the introduction of new/termination of existing mandatory payments, revision of certain elements of taxes and fees, and changes in the proportions of payments distributed among budgets. These changes did not have an unambiguous impact on local government revenues, causing them to increase on the one hand and decrease on the other. The level of real increase in local government budget revenues for the period from 2014 to 2021 (38 %) recorded in the paper indicates that the reform has increased the financial capacity of territorial communities. It is determined that an important role in preserving local budget revenues is played by the relevant ways used by the legislator, including the revision of tax rates, minimum wages and subsistence minimums, and indexation of the monetary value of land plots. The author emphasizes the actual application of a unified approach to the formation of revenues of the budgets of territorial communities (regardless of their status – rural, settlement, city) from 2021. The author identifies the consistently high role of personal income tax and the growing role of local taxes and fees, excise tax and rent in filling local budgets, which has a positive impact on the level of financial support for territorial communities and creates prerequisites for their development.
This research investigates how inclusive digital finance affects corporate green technological innovation, environmental decentralization, and how green transformational leadership moderates these relationships. As finance becomes more digitalized, especially in an inclusive manner, it encourages corporations to adopt sustainable practices, such as green technology integration, and to further decentralize their adaptive environmental strategies. This research applies the Resource-Based View (RBV) theory to explore the role of digital finance in promoting organizational green innovations, and the Ability-Motivation-Opportunity (AMO) leadership framework regarding the innovation mediating role of leadership. This study seeks to its address empirical research gaps regarding the role of inclusive digital finance in fostering environmentally sustainable corporate practices from an environmental and financial inclusivity perspective. The anticipated results would inform policy and practice in digital finance as a driver for sustainable corporate green innovations.
The rapid progress of large-scale models, including foundational and generative, brings to the forefront the tension between data-driven innovation and core privacy concerns. Such contracts as the GDPR and the undue privacy threats of data aggregation make centralized training approaches less desirable. To analyze the data’s distributed characteristics and their application to FLO, we investigate the role of federation analytics in a plausible paradigm that shunts data. In this paper, we present a new federated learning (FL) framework enhanced with cutting-edge privacy technologies (PET) such as Differential privacy for user-level formal guarantees of confidentiality, and strengthened secure Multi-Party Computation (SMPC), which guards the model updates. This paper studies more recent approaches to resolving the principal challenges of FL: statistical heterogeneity, communication bottlenecks, and vulnerability to adversarial attacks. We greatly appreciate what this new method portends, especially for training large language models (LLMs) and the more delicate areas of healthcare and finance. By evaluating certain existing limitations, such as the complexities of federated fine- tuning and model fairness, it is clear that an architecture with exemplary performance in FL serves as a model for scalable, secure, and privacy cop.
Aldi Bastiatul Fawait, Muh Jamil, Sitti Rahmah, Sugiarto Sugiarto
Perkembangan teknologi blockchain dalam beberapa tahun terakhir memberikan dampak besar terhadap sistem keuangan global, salah satunya melalui Ethereum (ETH) yang berfungsi sebagai aset kripto sekaligus fondasi ekosistem smart contract. Namun, volatilitas tinggi harga ETH membuat metode prediksi tradisional sulit menangkap pola nonlinier yang kompleks. Penelitian ini menerapkan metode Long Short-Term Memory (LSTM) untuk memprediksi harga ETH menggunakan data time-series dari investing.com periode 1 Januari 2021 hingga 21 Agustus 2025. Model LSTM dengan tiga lapisan menghasilkan performa baik dengan MAE 0,0387 dan R² 0,9741 pada data latih, serta MAE 22,59% dan R² 80,55% pada data uji. Hasil ini membuktikan bahwa LSTM efektif dalam mempelajari pola fluktuasi harga ETH meskipun akurasi pada data baru masih dapat ditingkatkan. Kontribusi penelitian ini adalah memperkuat literatur terkait prediksi kripto berbasis data jangka panjang sekaligus memberikan manfaat praktis bagi investor dan regulator dalam memahami dinamika volatilitas ETH.
Mr. Aditya S. G., Mr. Ram Anil Ainkar, Prof. Ms. Pranalini Joshi
The current Know Your Customer (KYC) ecosystem is largely built on centralized systems, which are vulnerable to data breaches, incur high operational costs, and often require customers to repeat verification steps unnecessarily [1], [2]. Such centralized designs concentrate sensitive data in single repositories, creating “honeypots” that conflict with modern data privacy standards like the General Data Protection Regulation (GDPR) [3], [4]. At the same time, the transparent nature of public Distributed Ledger Technology(DLT) presents challenges for maintaining privacy in financial transactions, giving rise to what is often called the “Blockchain-PrivacyParadox” [5]. This survey explores cutting-edge DLT-based solutions that integrate Self-Sovereign Identity (SSI) and Zero-KnowledgeProof (ZKP) techniques. Key challenges in current approaches include scalability limitations in certain permissioned blockchains [6],inadequate mechanisms to fully support GDPR’s Right to Erasure [3], [4], [7], and the absence of reliable protocols to ensure legal access for Anti-Money Laundering (AML) compliance when users are uncooperative [8], [9].
Narendar Kumar, Surendar Kumar, Abdul Waqar, Clavincy Francis Yohanes Ngantung
This research article provides the design of an in-person and remote voting system, while at the same time ensuring the privacy of users that would guarantee openness, transparency, and at the same time fraud-free results. The aim is to solve various common problems associated with most conventional elections including fraud, vote manipulation, through adaptation of the usage of a safe, highly transparent decentralized logical Hyperledger Fabric-based system provided by blockchain implementation. The methodology in this article is to be implemented for the sheer reason of urgency needed in making a more secure and transparent system for voting, considering even the rising frauds in elections. The addition of Zero Knowledge Proof (ZKP) guarantees that votes are confident and correct, yet anonymous between a voter and their vote. Biometric identification makes the system resistant to double spending. This incorporation of technologies ensures there is privacy and immutability against the double transactions, which, in turn, would be put in place as foundation for the future to be provided wherein every process in an election becomes safe and transparent. Innovation via creating a voting system to be trusted to meet today's demands and set standards for future electoral processes.
Abstract: The transition from centralized digital ecosystems to decentralized, trust - driven architectures represents a defining paradigm shift in Customer Experience (CX). This paper presents a strategic blueprint for leveraging block chain technologies to build secure, transparent, and interoperable customer - centric environments between 2025 and 2030. Through a comprehensive review of market forecasts, enterprise case studies, and emerging regulatory frameworks, the study demonstrates how decentralized identity (DID), verifiable credentials, and tokenized loyalty systems fundamentally reshape customer engagement, ownership of personal data, and trust models. Findings indicate that block chain adoption empowers customers with self - sovereign identity control, enhances privacy compliance, and delivers measurable efficiency gains in verification, loyalty management, and supply - chain transparency. Case evidence from leading enterprises — including JPMorgan, AXA, Santander, and Accenture — highlights significant improvements in transaction speed, operational costs, and customer engagement. Despite challenges such as legacy system integration and GDPR - related constraints, hybrid architectures, Layer - Two scalability, and permissioned block chain environments provide viable adoption pathways. This paper concludes that block chain is not a supplementary technology for CX, but a foundational enabler of decentralized trust, competitive differentiation, and customer - driven digital ecosystems. Keywords: Block chain; Customer Experience (CX), Decentralized Identity (DID), Verifiable Credentials, Tokenized Loyalty Programs, Digital Trust, Self - Sovereign Identity, Smart Contracts, Hybrid Data Architecture, GDPR Compliance, Enterprise Digital Transformation, Web3 Customer Strategy
Climate governance is entering a period of turbulence, with policy reversals in some democracies and rapid expansions elsewhere. This paper compares how centralized, decentralized (federal), and polycentric/hybrid governance designs shape mitigation and adaptation outcomes. Using a qualitative comparative approach across China, the United States, Canada, Türkiye, Norway, and Saudi Arabia, assessing policy ambition, legal instruments, implementation capacity, subnational authority, stakeholder participation, finance mobilization, and equity considerations. A qualitative comparative approach is applied across six country cases - China, the United States, Canada, Türkiye, Norway, and Saudi Arabia - evaluating policy ambition, legal instruments, implementation capacity, subnational authority, stakeholder participation, finance mobilization, and equity considerations. Insights are then extended to the Central Asian context, where climate governance remains predominantly centralized, shaped by Soviet-era institutional legacies, uneven local capacity, and constrained civic participation. The analysis demonstrates that no model is universally superior; the most effective arrangements combine top-down coherence with bottom-up experimentation and social legitimacy. Norway’s polycentric governance model and Türkiye’s hybrid approach illustrate how localized climate planning can be integrated within broader national frameworks. For Central Asia, pragmatic hybrid pathways are recommended that align national targets and financing with empowered regional pilots, transparent monitoring, and inclusive engagement. These context-sensitive combinations offer the best prospects for durable emissions reductions, climate resilience, and just transition outcomes in the region.
Stanislav I. Trofimov, Leonid Voskov, Mikhail Komarov
In the face of growing competition in the transportation market, companies are looking for new ways to improve operational efficiency and reduce fleet maintenance costs. This article presents an innovative vehicle technical condition management model that describes a mechanism for assessing the condition of vehicles using distributed ledger technology (DLT) and smart contracts. An information system for automating maintenance is proposed that can perform monitoring functions and initiate vehicle maintenance without human intervention by automatically registering operation and maintenance events, as well as using smart contracts to launch predefined actions. This level of automation allows timely prevention of unplanned breakdowns, which directly contributes to an increase in the service life of vehicles. The proposed solution allows transport companies to automate decision-making processes on maintenance, reduce transport downtime and optimize operating costs. The model ensures transparency of vehicle operation data, increases trust in information and shortens the decision-making chain. The solution is of particular value for public transport companies, where uninterrupted transportation and passenger safety are critically important.
Open access
Transportation Systems and Logistics
Advanced Research in Systems and Signal Processing
Cryptocurrency is a highly volatile digital asset, necessitating accurate and adaptive forecasting methods. This study implements a Long Short-Term Memory (LSTM) model to predict the daily closing prices of two leading cryptocurrencies Bitcoin (BTC) and Ethereum (ETH) using historical data from Yahoo Finance and Binance. To enhance data richness and model robustness, datasets from both sources were vertically merged. The methodological framework included data preprocessing, Min–Max normalization, formation of 24-day sliding input windows, and training across three data split ratios (70:30, 80:20, and 90:10). Model performance was evaluated using the Root Mean Squared Error (RMSE). Results indicate that the LSTM model achieved high prediction accuracy, with the lowest RMSE values of 0.0137 for BTC and 0.0152 for ETH using the combined dataset with a 90:10 split. Beyond modeling, a web-based application was developed using Streamlit, enabling users to perform real-time predictions and export results. This study contributes to the field of cryptocurrency forecasting by demonstrating that multi-source data integration significantly improves predictive accuracy and model generalization. The proposed framework offers both theoretical insights and practical tools for researchers and investors in financial technology.
We present a graphics processing unit (GPU)-accelerated Proof-of-Work (PoW) blockchain design tailored for secure healthcare data management. Our Compute Unified Device Architecture (CUDA)-optimized PoW achieves throughput improvements of approximately 5× to 100× and reduces block-formation latency compared to Central Processing Unit (CPU) mining, making blockchain practical for high-volume health records. We benchmark against standard platforms-Bitcoin, known for its robust security but slow block times; Ethereum (legacy PoW), widely adopted yet less efficient; and Hyperledger Fabric, a permissioned enterprise framework-to quantify performance gains. Empirical tests show GPU-Advanced Encryption Standard in Counter Mode (AES-CTR) processes large health-record payloads in under one second, while our PoW mining throughput improves by approximately 5×, to 100× relative to unaccelerated baselines. We also evaluate end-to-end encryption latency and discuss privacy trade-offs, including that lightweight Advanced Encryption Standard (AES) yields minimal delay, whereas fully homomorphic methods, although privacy-preserving, remain impractical for real-time permissionless blockchains and are not included in our design. We explicitly address regulatory compliance: personal health data are stored off-chain (e.g., Interplanetary File System [IPFS]), preserving the "right to erasure" via deletion of off-chain records, and we implement strict access controls to meet Health Insurance Portability and Accountability Act (HIPAA) security rules. The design includes validator selection rules that limit Sybil attacks by requiring costly work (or stake) and supports post-quantum cryptographic agility (e.g., Falcon signatures). We define our research question ("Can CUDA-accelerated PoW enable a high-performance yet compliant health data blockchain?") and hypothesize that GPU parallelism will yield substantial increases in speed. Results confirm our hypothesis: throughput and latency are significantly improved while preserving data privacy and compliance. This work makes a comprehensive contribution by detailing implementation methods, performance benchmarking, and analysis of security and legal requirements in a unified blockchain framework for healthcare.
Objective: This research aims to develop a comprehensive framework to identify and prevent money laundering in Decentralized Finance (DeFi) by leveraging big data analytics, integrating advanced machine learning algorithms, and network analysis techniques to address the challenges of pseudonymity and decentralization inherent to this ecosystem. Research Design & Methods: This research utilizes a mixed method approach with machine learning analysis based on Elliptic Dataset and qualitative policy study, applying graph models and classification algorithms to detect illegal transactions with precision in the context of imbalanced data. Findings: The results show that the MLP and GCN models achieve high accuracy (98% and 97.3%) and excellent recall (99.5% and 99.4%) on the Elliptic Dataset, significantly outperforming traditional methods. Exploratory data analysis and graph visualization confirmed that illegal transactions form denser clusters and more complex paths, indicating a layering pattern. Implications and Recommendations: Theoretically, this research extends the application of big data and graph theory to new financial systems, providing a blueprint for future RegTech and FinTech research. Practically, the framework offers tangible tools for regulators, law enforcement, and DeFi platforms to enhance AML capabilities, supporting the development of real-time monitoring tools and risk assessment models. Contribution and Value Added: The main contribution of this research is the development of a robust and adaptive big data analytics-based AML framework, which effectively addresses the unique challenges of DeFi.
Abstract The global financial markets are being changed by DeFi's ability to remove central actors to facilitate peer-to-peer transactions. DeFi promotes efficiency, globalization, and economic inclusion, and at the same time, it has raised tax compliance. This study attempts to bridge the gaps by analyzing available scholarly and policy-oriented research, along with recent regulatory initiatives. The study concludes that the tax compliance challenges posed by DeFi's Decentralization, Shrouded Identity, and Composability Features are serious and can overcome the traditional tax reporting mechanisms. The study also suggests the broad directions of gaps in the literature to be addressed in policy-driven and empirical studies in the future. Keywords: DeFi, Blockchain, Tax Compliance, Fintech
Recently, digitalization has been progressing in various fields, especially the use of blockchain technology used in virtual assets such as Bitcoin. Based on blockchain technology, new paradigms are emerging, such as creating non-fungible tokens that cannot be forged or altered, and establishing a system that provides financial services and products without intermediaries. In particular, with the advent of NFT, digital content is given asset and economic value, and as a result, transactions such as issuance and transfer occur, income increases. For this reason, the necessity of taxation was emphasized, and for that reason, the taxation relationship began to be analyzed, but it is difficult to judge the taxation relationship because the judicial legal relationship surrounding the NFT, such as the rights of the NFT holder, is not clear. In this regard, Japan's tax processing guidelines, which clarify the tax relationship between issuing and transferring digital art and reselling, have its own meaning. If you look at the contents, the copyright is usually reserved only by the creator in the case of the NFT transaction that connects digital art, and the NFT is often granted only rights such as permission to use the work. Therefore, in primary distribution, it is subject to miscellaneous income or business income, and in secondary distribution, where rights are transferred due to the transfer of NFT, it is subject to transfer income or business income. Non-fungible tokens, on the other hand, are used in various fields in terms of their properties and functions. Therefore, we have to consider how to deal with various issues individually and specifically. In terms of tax law, it is also necessary to categorize NFT in consideration of this and then tax them according to economic substance. In this study, the taxation relationship was examined by classifying it into securities-type NFT, payment-type NFT, and other NFT.