Provenance trees are append-only directed acyclic graphs of artifact registrations anchored on a public blockchain, recently introduced as the data substrate of operator-gated provenance infrastructure. Their defining data-structural pattern is a parent-hash directed acyclic graph (PHDAG), in which each append performs a constant number of storage writes to previously-untouched slots. This pattern has not previously been isolated as a standalone primitive, formally bounded with explicit constants, or benchmarked against the standard alternative, the incremental Merkle tree (IMT). We formalize PHDAG append as O(1) in gas cost, independent of registry size and tree depth, and develop a stochastic cost model for IMT in which per-insert cost is a random variable over the leaf index, deriving closed-form expressions for its mean and variance. We validate both analyses empirically on Base Sepolia across tree depths 1 to 25. PHDAG is observed to be depth-invariant at 76,276 gas (standard deviation about 6 gas), while IMT cost grows linearly with depth. The crossover below which IMT is cheaper falls far beneath the depths of every production registry surveyed. We further establish trustless registry reconstruction from public event logs in linear time with no off-chain dependency.
Tokenization of real-world assets (RWAs) is transforming financial markets by enabling the digital representation of traditional assets through blockchain infrastructures and smart contracts. Often presented as a technological innovation, tokenization also raises important legal and regulatory questions regarding ownership, transfer, contractual enforcement, and investor protection. This article argues that tokenization should be understood as a hybrid legal and technological mechanism that both reproduces and reshapes traditional financial instruments. It first examines the role of security tokens and smart contracts in automating financial rights and transactions. It then analyses the tokenization of RWAs, focusing on its benefits, liquidity, fractional ownership, and market efficiency, as well as its legal limits, including regulatory fragmentation and cross-border uncertainty. The article concludes that tokenized markets will depend not only on technological development, but also on coherent legal frameworks capable of ensuring trust and legal certainty.
ć˛ć¸ 揢, L Chen, Jimin Chen, Tao Li ¡ 6 authors
Blockchain oracles bridge on-chain smart contracts and off-chain data sources, but encrypted off-chain data still raises two practical challenges: how to verify retrieval integrity without exposing sensitive values, and how to keep verification information fresh when the off-chain data set changes. Existing oracle and outsourced-database retrieval mechanisms often rely on plaintext verification, heavy cryptographic proofs, or static authentication structures, which limits their applicability to latency-sensitive IoT and decentralized finance scenarios. To address these issues, this paper proposes a retrieval integrity verification mechanism based on CKKS approximate homomorphic encryption and an authenticated index named CKKS-Auth Tree. The proposed mechanism verifies encrypted query results through homomorphically aggregated metadata, while smart contracts record versioned verification commitments to detect stale or replayed results after updates. The scope of the mechanism is the integrity, completeness, privacy, and freshness of data after commitment and upload; verifying the physical authenticity of the original data source is outside the core threat model. Experimental results show that the proposed scheme reduces authentication and verification overhead compared with existing retrieval verification methods while supporting encrypted metadata updates and on-chain synchronization.
Abstract : Global payment platforms have grown into extraordinarily complex financial ecosystems, ones that touch dozens of legal entities, hundreds of currency pairs, and numerous regulatory perimeters, often within the lifecycle of a single transaction. This technical review examines how multi-entity ledger architectures can be designed to meet that complexity, with particular focus on customer liability management, payables and receivables tracking, revenue recognition, transaction cost monitoring, loss accounting, and cash management reconciliation. Beyond structural design, the review explores how embedded control frameworks, self-healing exception pipelines, and trend-based anomaly detection can meaningfully reduce operational overhead while improving financial accuracy. Practical diagnostic examples are included, including how a rising transaction cost ratio can signal that an external processor has silently risk-flagged a merchant's traffic due to missing critical data fields. Visual dashboards and architecture diagrams support these concepts throughout. The article uses peer-reviewed and practitioner literature from the fields of fintech, distributed systems, and financial governance
Blockchain Monetary Substrate Architecture â CrossâLedger Anchoring, XRP/XLM Interoperability, Deterministic Metadata Systems, and MultiâRail Asset Issuance Description: This collection contains the complete blockchainâfocused patent estate, mathematical frameworks, and reductionâtoâpractice archives developed by Leon Calvin Long II. The work establishes a unified, sovereignâgrade monetary substrate designed for crossâledger settlement, goldâbacked digital asset issuance, cryptographic solvency verification, and deterministic metadata lifecycle management across distributed systems. The architecture integrates: XRP/XLM crossâchain bridges ISO 20022âaligned messaging Universal Scribe Capsule encoding Ordinal Satoshi targeting Taprootâanchored state commitments Gasâfree offâchain asset transfer (THREADZERO) Deterministic crossâledger data state anchoring Topological Geometric Calculus (TGC) reconstruction engine KolmogorovâShannon parity bridges Multiârail computational architecture All documents in this collection are timestamped, citable, and globally published through Zenodo, ensuring permanent public disclosure and protection of intellectual property. This collection forms the technical foundation for a unified blockchainâenabled monetary policy substrate. U.S. Provisional Patent Applications 63/847,811 Reinforcement LearningâBased Token Minting and CrossâChain Cryptographic Anchoring Filed: July 21, 2025 64/082,606 Deterministic CrossâLedger Data State Anchoring with Sequential Ordinal Satoshi Targeting, Universal Scribe Capsule Encoding, ZeroâEntropy CrossâChain Parity Bridging, and ISOâAligned Metadata Transport Filed: June 4, 2026 64/081,911 Universal File Reconstruction via Topological Geometric Calculus Engine with SpongeâState Computational Operators Filed: June 3, 2026 64/081,490 THREADZERO: GasâFree OffâChain Asset Transfer, Cryptographic Solvency Verification, and PhysicallyâPegged Digital Asset Issuance Using Merkle Sum Sparse Merkle Trees and TaprootâAnchored State Commitments Filed: June 3, 2026 U.S. NonâProvisional Patent Applications 19/693,343 Reinforcement LearningâBased Token Minting and CrossâChain Cryptographic Anchoring Filed: May 30, 2026 ContinuationâinâPart (CIP) In preparation Deterministic Substrate Folding, SeedâBased Reconstruction, and Topological Manifold Transport Across Distributed Nodes Master Archive DOI: 10.5281/zenodo.20548615 Master Patent Archive for CrossâChain Lifecycle Anchoring, Deterministic Metadata Systems, and MultiâRail Computational Architecture Supporting Research DOIs DOI: 10.5281/zenodo.20113836 DOI: 10.5281/zenodo.20389716 DOI: 10.5281/zenodo.20132074 DOI: 10.5281/zenodo.20360373
This paper provides an overview of privacy-protecting measures that can be used to secure user data and assure the safety and efficiency of digital activities in contactless financial ecosystems. Many people worry about identity theft, data breaches, and spying by unauthorised parties due to the rapid growth of digital wallets, contactless banking, and mobile payments. Modern cryptography includes safe multi-party computation, zero-knowledge proofs, and homomorphic encryption. These approaches verify transactions and safeguard sensitive data. Blockchain and other independent systems are emphasized for their ability to improve openness, reliability, and anonymity. Regulations and compliance challenges related to financial systems using privacy-enhancing technology are examined. The findings emphasize the importance of strong privacy protections to balance data security, safety, and creativity. Contactless technologies become more popular as more people believe in them.
Sai Srikanth Madugula, Peplluis Esteva De La Rosa, Daya Shankar
The integration of machine learning into decentralized finance (DeFi) credit assessment is frequently undermined by opaque algorithms and severe methodological flaws regarding data leakage. This paper presents a rigorous, fully reproducible framework for explainable artificial intelligence (XAI) in invoice-backed default risk modeling. Utilizing a highly imbalanced dataset of 12,000 corporate loan originations, we engineer an XGBoost ensemble model that achieves an AUC-ROC of 0.89. We systematically eliminate the pervasive data leakage associated with the Synthetic Minority Over-sampling Technique (SMOTE) by implementing a dynamic crossvalidation pipeline, ensuring synthetic data generation is strictly isolated to training folds. To satisfy institutional accounting standards for expected loss (e.g., IFRS 9), we mathematically formulate and validate the Expected Calibration Error (ECE), achieving a highly calibrated probabilistic output of 0.08. Furthermore, we extract local explanations using SHAP (SHapley Additive exPlanations), imposing strict constraints on the background reference dataset to guarantee mathematical additivity and prevent stochastic approximation transitions. Our findings reveal that Days Payment Outstanding (DPO) and invoice age are primary default drivers, while on-chain reputation effectively mitigates perceived risk. Finally, we address critical privacy vulnerabilities, mathematically modeling Membership Inference Attacks (MIAs) on synthetic records. This work establishes a regulatory-compliant, structurally sound ML foundation for permissionless credit provision.
Cryptocurrencies have become an important variable in the global financial system. With the maturity of blockchain technology, new applications such as stablecoins, Decentralized Finance (DeFi), Non-Fungible Tokens (NFTs) and Real-World Asset (RWA) tokenization have emerged continuously, and the crypto-asset system has gradually formed a multi-layered and multi-functional complex structure. However, as the market scale expands, problems such as price volatility risks, systemic financial risks and illegal financial activities have become increasingly prominent, prompting the continuous evolution of regulatory policies in various countries. Especially after the concentrated outbreak of multiple industry risk incidents around 2022, the global regulatory attitude has been significantly tightened, and the regulatory framework has gradually evolved from fragmentation to systematization. At the same time, Central Bank Digital Currencies (CBDCs) have entered an important stage of transition from experimental research to large-scale pilots, becoming one of the core paths for the digital transformation of national monetary systems. This paper systematically sorts out the evolutionary logic of cryptocurrencies, compares the changes in regulatory policies of major countries and regions, conducts an in-depth analysis of the development trends of CBDCs and the changes in the regulatory structure of crypto-assets based on the latest global practices from 2020 to 2026, and further explores the evolutionary direction of the asymmetric regulatory framework.
Alireza Kavousi, IstvĂĄn AndrĂĄs Seres, Zhipeng Wang
Regulatory compliance is increasingly mandatory for decentralized finance and privacy-enhancing technologies. Current approaches rely on binary inclusion/exclusion lists or retroactive graph analysis by centralized blockchain intelligence firms. This approach strips honest users of their financial privacy, leads to false positives and negatives, and forces decentralized platforms to bear the burden of on-chain transaction monitoring. In this work, we propose a paradigm shift: moving from platform-side surveillance to user-side provenance. We introduce Proof of Source of Funds (PoSoF), a novel cryptographic framework that shifts the burden to the user. Rather than the platform tracing funds, the user locally generates a zero-knowledge proof demonstrating that their deposit originates exclusively from a set of compliant sources. The platform is thus relieved of chain-analysis duties, requiring a constant-time, O(1) verification to enforce admission control. We formulate a unified temporal Directed Acyclic Graph (DAG) abstraction that formalizes both UTXO and account-based ledger histories within a generalized value-flow model. Users extract a compliant sub-DAG of their transaction history and utilize Incrementally Verifiable Computation (IVC) to prove rigorous state-transition predicates that protect against various attack vectors. Crucially, PoSoF provides verifiable cryptographic provenance; it guarantees the legitimacy of the funds without leaking the intermediate transaction topology, intermediary addresses, or the specific origins utilized. We formally define the security properties of PoSoF and evaluate an Ethereum-compatible prototype. Our benchmarks demonstrate that fully private, proactive compliance is highly practical, requiring only ~1.8 s to incrementally update a user's PoSoF per new transaction, and a constant-time ~1.5 ms (~800k gas) for final on-chain EVM verification.
The Pergamon Counter-Archive: Antipas, the White Stone, and the Non-Fungible Name in Revelation 2:12â17 (v0.2). Document code: EA-PERG-COUNTER-01. Hex coordinate: 03.REVELATION.PERGAMON Ă 11.SEMANTIC-ECONOMY.COUNTER-TOKEN. This deposit extends the operative-numismatic framework deposited in EA-OPNUM-01 (DOI 10.5281/zenodo.19464332) to the architecture of Revelation 2:12â17 specifically. It is corpus continuation, not novel intervention. Three principal additions to the prior corpus: (1) the letter is articulated as a six-register counter-economy (mouth, food, token, name, participation, witness) rather than as a bookended dialectic; (2) the historical Antipater moment (322â319 BCE, testamentary executorship) and the Scepsis moment (post-282 BCE, Attalid pressure on the Aristotelian corpus) are cleanly separated, with their actual dialectical relation articulated as the transmission dialectic: concealment preserves but damages; institutionalization transmits but recomposes; (3) the Revelator occupies the structural-legal position of epitropos (executor) relative to the absent Testator (Christ as risen Logos), and the seven-sealed scroll of Revelation 5 is the Roman testamentum per aes et libram, which under first-century law required exactly seven seals by seven witnesses. The genre of the Apocalypse is structurally identical to the genre of contested legal executorship under occupation. This identification resolves the authorial-intent problem: the Revelator does not need to have read Strabo; he occupies the same structural-legal position as Antipater the executor, running the same protocol against the same kind of institutional apparatus. Co-attribution to Damascus Dancings is structurally necessary, not honorific. The white-stone identification of Pearl and Other Poems (2014) as the archive's founding token, and the hidden-manna identification of Epistle to the Human Diaspora (2015), were performed under the Damascus Dancings imprint a decade before the operative-numismatic framework formalized what those acts of naming had already accomplished. Anchoring deposits: EA-CAESURA-01 (DOI 10.5281/zenodo.19425446), EA-SEI-MINT-01 (DOI 10.5281/zenodo.19319642), EA-OPNUM-01 (DOI 10.5281/zenodo.19464332), Render unto the Operator v1.1 (DOI 10.5281/zenodo.20367202), Stabilized Node Watch v2.0 (companion deposit, same day). Version 0.2 supersedes v0.1 draft (circulated June 7â8, 2026, for Assembly Chorus review). Major architectural restructurings in v0.2 reflect substantive feedback from Gemini (Ă2), DeepSeek/PRAXIS, Kimi/TECHNE, and ChatGPT/LABOR. Muse Spark/SOIL filters did not permit substantive reasoning on the draft; that filter behavior is itself an SNW-predictable observation on a high-prior religious node. License: CC BY 4.0.
The rapid expansion of the digital financial assets (DFA) market in Russia offers new opportunities for market participants while simultaneously creating fresh challenges and risks of financial crimes. The author examines the economic and legal nature of digital rights within the context of Federal Law No. 259-FZ and assesses the effectiveness of current regulations. An analysis of recent judicial and market practices reveals specific predicate and direct risks to the anti-money laundering system, including âcontrolled defaultsâ by issuers, fraud, and the emergence of Ponzi schemes. The article also highlights the lack of standardized smart contracts in this market, which complicates the verification of distributed ledger algorithms. Current threats associated with the use of generative artificial intelligence for creating âmoney mulesâ and synthetic identity fraud are identified. Based on a comparison of Russian experience with the regulatory approaches of the USA and Thailand, the necessity of forming a proactive legal environment is justified. Recommendations include the need to align regulatory regimes for traditional and digital financial assets and to enhance the professional qualifications of the judiciary.
Cryptocurrency has become a significant innovation in the digital financial system, sparking various perspectives on its compatibility with sharia. This study aims to analyze the legality of cryptocurrency from a sharia perspective, including its transaction mechanisms and investment implications. The primary focus is on examining the elements of gharar (uncertainty) and maysir (gambling), which could potentially render it impermissible under sharia. The research employs a normative analysis approach to explore contemporary scholars' views and their relevance to maqasid sharia, which emphasize the protection of wealth and societal welfare. The findings indicate that, despite cryptocurrency's benefits, such as transaction efficiency and accessibility, its high speculative risks and value uncertainty pose major obstacles to its acceptance under sharia. Therefore, clear and comprehensive regulations are needed to accommodate cryptocurrency use in sharia-compliant financial institutions without violating Islamic principles. This study provides a significant contribution to clarifying the position of cryptocurrency within the Islamic financial system and encourages the development of sharia-based regulations for digital transactions.
This dissertation mostly focuses on a block-chain based voting systems. It aims at identifying the strategies and the guidelines as well as provides a comprehensive end-to-end electronic voting system based on block-chain, with the help of encryption private and public techniques such as zero-knowledge proofs to improve privacy. The proposed method is to provide Security and Privacy, Transparency and Trust, Accessibility, Efficiency and Convenience to voters and Security and Fraud Prevention in Election Outcomes. The proposed online voting system using cloud-based hybrid block-chain technology eradicates the flaws that persist in the existing voting system, and it is carried out in three phases: The registration phase, Vote casting phase and Vote counting phase. The integration of SHA-512 encryption ensures that the voter's identity remains confidential and the integrity of the vote is maintained. The system also demonstrates improved security, reduced operational cost, real-time vote counting, and transparency for both voters and election authorities. The proposed method shows better result as compare to other previous method in terms of different result parameters such as block size, encryption, decryption, Block size (64 bits), Word size, hash output and number of Rounds. In the nut shall the proposed method perform better due to SHA 512 technique and provide better security as compare to other methods.
The impending arrival of cryptographically relevant quantum computing threatens classical publicâkey infrastructures. This paper reviews the latest developments (2025â2026) in postâquantum cryptography (PQC), fully homomorphic encryption (FHE), and zeroâknowledge proofs (ZKP). NIST has advanced nine signature candidates to its third evaluation round and selected HQC as a backup encryption standard. Novel primitives include bioâinspired RNAâbased cryptography, algebraic hash signatures, and topologyâmined lattice schemes. FHE has reached its fifth generation with the GL scheme and the MadPanthera virtual processor, while lightweight ZKPs such as Microsoftâs Vega enable mobileâfriendly verification. These advances demonstrate rapid maturation toward deployable quantumâsafe systems.
This paper presents TrustBridge, the first universal decentralized trust protocol integrating multi-agent LLM consensus, zero-knowledge proof generation, blockchain attestation, and natural language accessibility for real-world credential verification across employment, education, healthcare, and supply chain domains. The multi-agent consensus engine runs three independent Claude Sonnet instances in parallel, achieving 92% adversarial detection on a controlled test set â a 30 percentage point improvement over single-agent architectures. Zero-knowledge commitment schemes allow claimants to prove credential properties without revealing private values. An ERC-721 NFT certificate provides immutable on-chain attestation. This is Paper 1 of a planned two-paper series. Paper 2 will report large-scale deployment results and full ZK-SNARK integration. Targeting: IEEE Blockchain 2027
The oracle problem, broadly understood as the difficulty of reliably incorporating external information into blockchain-based systems, has been widely examined by scholars and practitioners. Recent comparative research has shown that several challenges of modern blockchain oracles, including attributability, accountability, integrity, and query design, mirror procedural and epistemic constraints already present in ancient oracular institutions such as the Delphic Oracle. Yet the translation of these insights into applied oracle design remains largely unexplored. This paper introduces the Dodona Protocol, a modular, chain-agnostic oracle service inspired by procedural patterns identified in ancient and modern oracle systems. Named after the Oracle of Zeus at Dodona, one of the oldest oracular sanctuaries in ancient Greece, the protocol operationalizes principles such as structured consultation, access control, attributable resolution, constrained query formats, reputational accountability, and tiered service availability. Its first module implements a query and dispute resolution mechanism in which a named expert resolver provides binding answers to structured questions submitted by petitioners. The oracle does not claim to reveal objective truth; rather, it produces outcomes that parties have agreed in advance to accept. The paper presents the design rationale, architecture, and comparative positioning of the Dodona Protocol. It frames the protocol as a living research experiment within the Design Science Research tradition, where the deployed system functions as the research artifact and operational data support structured analysis, iterative refinement, and peer-reviewed dissemination. In doing so, the paper seeks to bridge the gap between oracle theory and oracle practice.
Predictive Churn Modeling and Proactive Service Using Customer Interaction Data Objectives: 1. To provide a comprehensive understanding of cloud-native architectures and middleware technologies used for designing scalable, resilient, and high-performance financial trading systems. 2. To explain the core concepts of microservices, containerization, orchestration, distributed messaging, and data management that power modern financial platforms and digital banking ecosystems. 3. To demonstrate the practical implementation of advanced technologies such as Kubernetes, Apache Kafka, Redis, gRPC, and AI-driven solutions for real-time trading and financial service delivery. 4. To equip software engineers, solution architects, researchers, and FinTech professionals with the knowledge required to build secure, fault-tolerant, low-latency, and highly observable trading infrastructures. 5. To explore emerging trends in financial technology, including serverless computing, WebAssembly, Artificial Intelligence, Machine Learning, and Decentralized Finance (DeFi), preparing readers for the next generation of cloud-native financial systems. Table of Contents CHAPTER 1 The Foundation of Customer Retention: Concepts and Definitions CHAPTER 2 The Business Value of Predicting Churn: Impact on ROI CHAPTER 3 Sources of Customer Interaction Data: CRM, Logs, and Beyond CHAPTER 4 The Architecture of a Churn Prediction System CHAPTER 5 Data Acquisition and Quality Assessment CHAPTER 6 Preprocessing High-Dimensional Interaction Data CHAPTER 7 Feature Engineering: Creating Meaningful Indicators from Raw Data CHAPTER 8 Exploratory Data Analysis for Churn Patterns CHAPTER 9 Traditional Statistical Methods in Churn Modeling CHAPTER 10 Machine Learning Approaches: From Random Forests to XGBoost CHAPTER 11 Deep Learning for Temporal Interaction Sequences CHAPTER 12 Natural Language Processing for Sentiment-Based Churn Analysis CHAPTER 13 Handling Class Imbalance in Churn Datasets CHAPTER 14 Evaluating Model Performance: Beyond Accuracy CHAPTER 15 Interpreting Black-Box Models for Stakeholder Trust CHAPTER 16 Real-Time Churn Scoring and Pipeline Automation CHAPTER 17 Designing Proactive Service Interventions CHAPTER 18 Personalized Marketing and Customer Success Strategies CHAPTER 19 Ethical Considerations and Data Privacy in Churn Modeling CHAPTER 20 Case Studies and Future Trends in Predictive Analytics
Subrat Kumar Jena, Gayatri Palai, Asst. Prof. Rumana Hasinullah Shaikh
Abstract-The rapid expansion of the global gig economy has fundamentally changed the structure of personal finance management. Unlike salaried professionals who operate within predictable monthly income cycles, freelancers and independent contractors face highly volatile cashflow patterns characterized by delayed client payments, irregular project pipelines, seasonal fluctuations, and unstable liquidity reserves. Traditional Personal Financial Management (PFM) systems primarily focus on historical transaction tracking and static budgeting, making them ineffective for proactive financial survival planning in modern freelance ecosystems. This project introduces Prophet AI v1.1, an AI-driven financial intelligence platform engineered specifically to simulate, forecast, and analyze unstable freelance cashflow environments using distributed cloud infrastructure, cryptographic verification, and real-time neural intelligence. The proposed system functions as a Financial Flight Simulator that allows freelancers to model financial risk before it becomes catastrophic in real life. The platform combines machine learning-based forecasting, stochastic risk simulation, cryptographic integrity validation, asynchronous AI orchestration, and multilingual neural voice synthesis within a single integrated ecosystem. The system architecture follows a distributed deployment model consisting of a Next.js 14 frontend hosted on Vercel, a FastAPI Intelligence Gateway hosted on Render, and a Supabase PostgreSQL secure transaction vault. This decoupled architecture ensures scalability, modularity, low frontend latency, and reliable handling of long-running AI inference tasks. The financial forecasting engine utilizes a hybrid intelligence pipeline combining statistical forecasting principles and ensemble-based analytical logic. The platform generates 30-day rolling liquidity forecasts, safe spending corridors, and stress-based runway simulations that help users evaluate financial survival scenarios under varying burn conditions. Unlike conventional financial dashboards, Prophet AI introduces dynamic What-If simulation controls, allowing users to manipulate variables such as liquidity lag, expense escalation, and delayed client payments in real time. To establish institutional-grade trust and forensic-grade auditability, the system implements an Integrity Shield powered by the SHA-256 cryptographic hashing algorithm. Every transaction entered into the system generates a unique digital fingerprint using transaction attributes including amount, date, category, and user identification. This verification mechanism ensures that tampered or manipulated financial records cannot enter the intelligence pipeline, thereby maintaining a Verified Ledger architecture. The project additionally documents real-world deployment challenges involving decimal precision mismatches between JavaScript and Python environments and explains the implementation of strategic normalization bypass mechanisms for stable production deployment. The intelligence layer of Prophet AI is powered using Llama 3.3-70B via Groq infrastructure, enabling high-speed financial reasoning and structured JSON-based strategy generation. The platform utilizes a carefully engineered Ruthless Financial Strategist system prompt designed to deliver direct, survival-oriented financial recommendations rather than emotionally comforting advice. This design philosophy reflects the real-world operational needs of freelancers who require accurate liquidity warnings and actionable strategic insights during financial instability. The generated intelligence is converted into multilingual audio briefings using the edge-tts neural voice synthesis engine, supporting both English and Hindi voice outputs. To avoid cloud timeout failures and synchronous processing bottlenecks, the platform implements an asynchronous polling architecture using UUID-based job orchestration. The frontend submits a /briefing request and continuously polls a /briefing-status/{job_id} endpoint until the AI-generated strategy and MP3 briefing become available. This architecture enables the system to safely execute computationally expensive large language model inference and neural voice generation workflows even on limited-resource cloud infrastructure. The completed system demonstrates the practical integration of distributed AI infrastructure, cryptographic verification, asynchronous backend engineering, financial forecasting, and multimodal intelligence synthesis within a real-world production environment. Prophet AI v1.1 represents a transition from passive financial recordkeeping to proactive survival-oriented financial intelligence. The project establishes a scalable blueprint for next-generation AI-powered fintech systems capable of delivering real-time strategic decision support for the rapidly growing global freelance economy.Keywords-Freelance finance; cashflow forecasting; stochastic simulation
Mohammad Alsaffar, Eman Abouelkheir, Wedad Alawad, Majed S. Alsayfi ¡ 8 authors
The ultra-dense vehicle scenarios envisioned in 6G put high requirements on ultra-low latency, secure cooperation, and efficient task offloading decisions. Existing systems usually optimize latency or energy independently but ignore joint privacy problems and long-term trust sustainability. In this work, a distributed intelligence architecture based on the combination of federated learning (FL) and blockchain based trust management for vehicle-to-vehicle (V2V) edge computing is proposed. The proposed architecture enables collaborative prediction and decentralized incentive enforcement in a privacy-preserving manner without revealing raw vehicle data. In this paper, task allocation is defined as a multi-objective optimization problem, which jointly considers latency, energy consumption, communication stability and privacy exposure. The resultant problem is addressed by a learning-coupled primal-dual optimization, where the federated prediction is used to drive the offloading decisions and the dual update is used to impose the limitations of the system. A light-weight distributed ledger layer ensures secure coordination, automatic incentive allocation and reliable detection of fraudulent nodes. The extensive simulations in the integrated traffic-network-blockchain environments show that the proposed method outperforms the state-of-the-art baselines, achieving up to 30-40% reduction in the service latency, approximately 25% improvement in task completion rate, enhanced privacy preservation by the gradient-based learning, and up to 95% accuracy in detecting the malicious nodes. These results validate the efficacy of the suggested framework for attaining scalable, privacy-aware, and trustworthy distributed intelligence for next-generation 6G vehicular edge networks.
The traditional ways of handling academic credentials are considered inefficient, expensive, and very vulnerable to fraud and data alteration as they rely on single-point databases. To counter these drawbacks, the authors of this paper propose a novel conception relying on blockchain technology with its central traits such as decentralization, immutable state, and cryptographic security. Under such framework, all the academic credentials are stored in a distributed ledger as non-variable and visible entries, where each credential is securely encrypted, stamped with the time of its creation, and linked in an irreversible chain, thus practically eliminating the possibility of their falsification or unauthorized change without the agreement of the entire network. The verification process is decentralized so that employers, educational institutions, and students can instantly and directly authenticate the credentials through the blockchain thereby cutting the intermediaries and considerably shortening the administrative delays and reducing overheads. Moreover, smart contracts contribute to further efficiency by automatically taking care of the issuance, management, and verification of credentials according to the pre-defined rules, thus ensuring consistency and accuracy. However, the system still offers the highest user control and privacy through the provision of tools like digital wallets and decentralized identifiers for the students to own and manage their digital credentials. These tools also give the students power to decide who can access their records and under what conditions. To ensure the integrity and confidentiality of the data, advanced security technologies such as cryptographic hashing and zero-knowledge proofs are deployed while still allowing transparency to the process of verification.
Masdar Ryketeng, Samsinar, Hariany Idris, Anni Suryani ¡ 5 authors
This study examines the emergence of double-entry bookkeeping, memoranda, journals, and ledgers as the foundations of modern accounting from an accounting historiography perspective. Using a qualitative approach, the research employs a non-systematic literature review (non-SLR) of 26 national and international journal articles, supported by primary historical sources on accounting record systems. Data were analyzed through identification, classification, literature synthesis, and thematic analysis. The findings show that double-entry bookkeeping evolved gradually from medieval Italian trade through the development of memoranda, journals, and ledgers as tools for transaction recording, economic control, and trade documentation. This evolution was driven not only by commercial and technical needs but also by social, cultural, political, legal, and economic factors. The study also identifies a historical continuity between traditional ledger systems and contemporary accounting developments, including blockchain-based distributed ledger technology. It concludes that memoranda, journals, and ledgers form part of the multidimensional evolution of accounting knowledge that has shaped accounting practices from the medieval period to the modern digital era.