In modern business and trade, digital transformation (DT) has become a key factor in gaining a competitive edge. Rapid developments in blockchain, big data analytics, cloud computing, artificial intelligence (AI), and the Internet of Things (IoT) are changing company models, value generation workflows, and organizational strategies. By combining organizational, strategic, and technological viewpoints, this study offers a multifaceted examination of digital transformation. Secondary data from peer-reviewed literature, international industry publications, and corporate disclosures of top companies, such as Amazon, Alibaba Group, Microsoft, and Tesla, Inc., were analyzed using a descriptive and analytical research design. The study creates a conceptual framework that connects performance results, transformation processes, and digital drivers. The results indicate that ecosystem integration, organizational agility, digital capability development, and strategic alignment are necessary for a successful digital transformation. The paper contributes to digital transformation literature by combining findings from several sectors and putting forth an integrated strategic model that can be empirically validated in further studies; the paper adds to the body of knowledge on digital transformation.
The expansion of blockchain technology and the evolution of digital platforms have led to the emergence of new concepts in contractual relations, of which "smart contracts" are among the most significant. These contracts are designed as blockchain-based computer programs that execute the terms of the parties' agreement in the form of digital codes and enable the automatic performance of obligations without the need for traditional intermediaries. Such features have increased the speed, transparency, and efficiency of transactions. However, the introduction of this technology into the field of contract law has raised fundamental questions regarding the legal nature, validity, and enforcement of such contracts in various legal systems, particularly those based on classical traditions. The aim of this research is to elucidate the legal nature of smart contracts and analyze the challenges of their enforcement in the Iranian legal system. The research method is descriptive-analytical, and data have been collected through library studies and the examination of domestic and international legal sources. Additionally, with a comparative approach, some legislative experiences of other countries in this field have been examined. The findings indicate that, despite technical differences, smart contracts can be analyzed within the framework of general contract rules. The principle of party autonomy and Article 10 of the Civil Code provide the capacity to accept this type of contract, and the Electronic Commerce Law, by recognizing data messages and electronic signatures, has established a basis for the validity of digital transactions. However, challenges such as ascertaining the true intent of the parties, determining liability for technical errors, and the conflict between the immutability feature of blockchain and institutions such as rescission and mutual rescission persist. Accordingly, the formulation of supplementary regulations, the development of legal infrastructure, and the enhancement of specialized knowledge appear essential for the safe and effective utilization of this technology.
A transformação digital dos meios de pagamento tem reconfigurado as relações entre consumidores, empresas, instituições financeiras e plataformas tecnológicas no varejo brasileiro. No setor supermercadista, caracterizado por alto volume de transações, margens reduzidas, intensa concorrência e forte presença no cotidiano das famílias, a inovação financeira representa oportunidade estratégica para ampliar eficiência operacional, fidelização, segurança transacional e inclusão digital. Este artigo analisa a gestão da inovação financeira com blockchain no varejo supermercadista brasileiro, discutindo seus impactos na competitividade empresarial e suas possibilidades como instrumento de inclusão digital e financeira. A pesquisa adota abordagem qualitativa, exploratória e analítico-propositiva, fundamentada em revisão bibliográfica e documental sobre blockchain, ativos virtuais, sistemas de pagamento, varejo alimentar, confiança do consumidor, governança de dados, inclusão financeira e regulação brasileira. O estudo examina aplicações como pagamentos com ativos digitais, stablecoins, tokens de fidelidade, cashback programável, rastreabilidade de produtos, contratos inteligentes com fornecedores e integração com carteiras digitais. Os resultados indicam que a adoção de blockchain pode gerar vantagens competitivas por meio da diferenciação tecnológica, redução de custos transacionais, aumento da transparência, fortalecimento da fidelização e integração com novos ecossistemas financeiros. Contudo, sua implementação enfrenta desafios regulatórios, operacionais, culturais e tecnológicos, incluindo volatilidade dos criptoativos, proteção ao consumidor, segurança cibernética, governança de dados, baixa educação financeira e desigualdades de acesso digital. Conclui-se que a gestão eficaz da inovação financeira com blockchain no varejo supermercadista brasileiro exige adoção gradual, integração com meios de pagamento consolidados, parceria com instituições reguladas, comunicação clara, proteção de dados, capacitação de equipes e estratégias inclusivas centradas no consumidor.
Digital and intelligent fresh-product supply chains increasingly rely on third-party logistics providers (TPLs) to record and disclose transport-process information. However, the TPL bears data-collection and digital-governance costs while capturing only part of the market value created by credible disclosure. This study develops a supplier-led Stackelberg game for a supplier–TPL–retailer supply chain. Contractual terms are negotiated before operation. Conditional on the negotiated contract, the supplier sets the wholesale price, the TPL selects the disclosure level, and the retailer determines the retail price. We derive decentralized equilibria under blockchain and non-blockchain regimes and compare cost-sharing and joint cost-sharing/revenue-sharing contracts. The results show that cost-sharing increases the TPL’s optimal disclosure level, but disclosure upgrades occur through discrete threshold jumps. Blockchain adoption depends jointly on fixed implementation costs and reliability improvements, and cost-sharing alone may not ensure both adoption and high-level disclosure. Introducing revenue-sharing allows the TPL to internalize part of the demand-side value generated by credible disclosure, leading to a Pareto-improving coordination interval for all supply-chain members. The findings provide a mathematical basis for designing incentive-compatible contracts for blockchain-enabled disclosure in digital fresh product supply chains.
The application of blockchain technology in streamlining cross border trade is quite pertinent within the African context, due to the underlying border delays and cumbersome documentation processes. This exploratory research focuses on examining, through case studies, how ten African nations have been applying blockchain technology in comparison to their BRICS counterpart. The study further examines the significance of blockchain technology in streamlining cross-border trade and rules of origin documentation within the context of the African Continental Free Trade Area (AfCFTA). The following nations, such as Egypt, Tunisia, South Africa, Botswana, Mauritius, Rwanda, Ethiopia, Kenya, Nigeria, and Ghana, were selected because they are actively participating in the African Continental Free Trade Area (AfCFTA)'s Guided Trade Initiative (GTI). The other aspect of this research examines the significance of the deployment of distributed ledger technology in BRICS. The significance of this study is to glean lessons from BRICS on the adoption of BCT. Critical realism is the philosophical underpinning of the research. This study applies the inductive approach, qualitative research design, and a case study research strategy. By examining existing case studies of blockchain applications in these selected African and BRICS nations, key lessons are learnt to enhance policy formulation. The result of this research is to enhance policy development on adoption of Block chain technology to build intra-African trade.
How do multiple possible action trajectories progressively narrow into one failing line of activity? While escalation of commitment scholars have long puzzled over this question, their tendency to conflate escalation with persistence and treat commitment as primarily cognitive compromises the concept’s theoretical precision and practical relevance. Adopting a communicative-relational ontology, we reconceptualize escalation as a process of communicatively constituted, ventriloquial attachment. We draw on an in-depth study of an interorganizational team to trace how such an attachment to the idea of working with blockchain technology emerged and progressively intensified in members’ interaction, pulling the team toward a single line of activity while alternatives were increasingly sidelined to a point where detaching became seemingly impossible. Our findings introduce the concept of escalating attachment , emphasizing how escalating processes are dynamic, relational accomplishments that both pull action forward along select lines of activity and hold it in place. This, we claim, resonates with practitioners’ lived experiences of how they not only hold onto an idea but also become progressively held by that very same idea. Further, our insights contribute to the communication as constitutive of organization (CCO) literature by lifting scholars’ focus away from situated (inter)action and toward how (inter)actions connect.
In this paper, we propose a distribution-free test for detecting changepoint in the mean direction of angular data. The uncertainty in angular measurements is quantified through the \textit{square of an angle}, derived from the intrinsic geometry of the torus. It is established that, under the null hypothesis, the test statistic distributionally converges to the Kolmogorov distribution, while under the alternative hypothesis, both the consistency of the test and the asymptotic properties of the changepoint estimator are established. Through extensive simulations, we compare the empirical performance of the proposed method with two existing approaches for angular data and further benchmark it against a test based on the circular arc length distance. Finally, we demonstrate the practical utility of our approach by analyzing the timestamps of extreme events in Bitcoin, Ethereum, and Gold price datasets, where the continuous, high-frequency nature of the data is modeled in the circular framework.
IoT sensor deployments increasingly export measurement streams to edge gateways and content-addressed storage such as IPFS, but access control decisions must be enforced without disclosing sensor owner policies, requester attributes, or stale data versions. Existing blockchain, CP-ABE, and zero-knowledge approaches reduce parts of this leakage, yet they can still expose public policy structure, accept stale Merkle proofs after sensor stream updates, overload provers when policies grow, or leave IPFS gateways vulnerable to bandwidth abuse. This paper proposes zk-Guard-R, a policy-hidden and replay-safe zk-SNARK access control framework for privacy-preserving IoT sensor data sharing. zk-Guard-R replaces public sparse policy matrices with MiMC-Merkle policy commitments verified inside the proof, separates long-lived logical sensor policy roots from frequently updated physical IPFS data roots, binds every proof to an on-chain nonce, and decouples attribute possession from policy interpretation through a bounded stack-based policy interpreter. Numeric sensor-access predicates are represented through committed values and range check gadgets, while an off-chain verification gateway couples accepted proofs with payment channel vouchers before releasing encrypted IPFS chunks. The design contribution is separated from the measured prototype: the full protocol specifies a bounded policy interpreter, whereas the present gnark prototype evaluates the core committed policy, committed attribute, range check, data root, nonce, Solidity verifier, and gateway-metering mechanisms. We implement a gnark BN254/Groth16 research prototype and benchmark it against a matrix-public zk-Guard prototype, a blockchain ABAC baseline, an IoT token/HMAC baseline, and a CP-ABE-style cryptographic-work proxy. For 128 attributes, the zk-Guard-R prototype with MiMC-Merkle commitments uses 425,574 R1CS constraints, generates proofs in 3.12 s, verifies in 0.73 ms, and uses 641 MB peak Go heap allocation. A three-run repeat of the 128-attribute configuration gives a proof-generation mean of 2.80 s with a 0.54 s standard deviation on the same local host, illustrating the runtime variability of prover measurements. We also deploy the generated Solidity verifier on a local Anvil EVM and measure 241,942 gas for a successful verification transaction, and we evaluate a local Kubo/IPFS gateway under valid, replayed, and voucher-limited flood requests. The results show that zk-Guard-R shifts substantial but measurable work to the prover while improving policy confidentiality, freshness, and gateway metering for IPFS-backed IoT sensor data sharing.
AuraOS Paper IX: Objective-Native Capability Commons and Proof-Carrying Contribution Economies Version 2.0 - Expanded Same-Day Edition Author: Dallas Courchene Date: August 7, 2026 Claim range: N51-N100 This expanded same-day edition supersedes the initial August 7, 2026 release of AuraOS Paper IX while preserving its original architectural spine, repository anchor, and defensive prior-art declarations N51-N87. It adds thirteen new combination-scoped declarations, N88-N100, and folds their enabling embodiments into the relevant sections of the paper rather than fragmenting the architecture across a separate follow-on publication. Paper IX develops AuraOS beyond an application-centric or chatbot-centric model into an objective-native, proof-carrying computational and economic substrate. A person, organization, community, institution, or other authorized principal begins with an objective, constraints, rights, privacy requirements, evidence requirements, budget, and authority. Aura then composes a bounded Ephemeral Arena from persistent capability packages, Arena Recipes, humans, AI workers, data, simulators, rule packs, facilities, and services. Verification, semantic-gate execution receipts, provenance, attribution, human/institutional responsibility declarations, canonical-owner disposition, explicit promotion, and deterministic dissolution remain separate stages. The original N51-N87 disclosures establish the core architecture: minimum-sufficient objective compilation; hierarchical evidence hydration; persistent Capability Packages; rebindable Arena Recipes; explicit promotion and dissolution; federated Aura Commons; executable rights; proprietary capability execution without mandatory source disclosure; semantic-gate Attestation DAGs and lazy provenance; durable agent identity bound to bounded internal authority; meaningful-use contribution economics; a proof-carrying Developer Arena; reviewer-independence lineage; causal credit separated from execution traceability; Personal Cognitive Capsules and portable personal SLMs; privacy membranes and semantic translation; governed recursive harness learning; intent-native manifestation and spatial code breadboarding; Aura Places and Convention Arenas; reactive and proactive discovery; an Open Discovery Foundry; physics/digital-twin and bounded social simulation; business incubation; cross-domain sovereign federation; participatory Scientific Arenas; contributed compute and facilities; and a compounding Scientific Capability Commons. The expanded N88-N100 disclosures complete several consequences of that substrate. N88 formalizes a three-speed Architecture Arena and convergence compiler. Fast architectural discovery is separated from medium-speed implementation/hardening and slow constitutional change. Candidate advances become Architectural Delta Objects, are checked against canonical owners, invariants, duplicate-plane risk, threat-model effects, prior art, and proof obligations, and are then compiled into bounded implementation, security, migration, documentation, research, and verification work for the Developer Arena. This allows architectural ideation to move faster than pull-request integration without allowing implementation velocity to rewrite Aura's constitutional planes. N89 introduces a demand/capability graph capable of identifying keystone bottlenecks: missing capabilities, methods, facilities, standards, or processes whose resolution could unlock unusually large numbers of currently blocked objectives. This supports evidence-informed code, research, optimization, replication, falsification, boundary, field-validation, and manufacturing bounties while keeping prioritization advisory and locally governable. N90-N94 extend the architecture into human opportunity, learning, privacy, credentials, professional identity, and creator economics. A privacy-preserving Opportunity Compiler can locally match a person's verified capability evidence, goals, availability, jurisdictional constraints, and disclosure policy to jobs, bounties, research nodes, mentorship, local services, and temporary teams. Learning Arenas can compile capability gaps into progressively verified learning and supervised work. Raw LifeOS and Personal Cognitive Capsule history is explicitly separated from portable verified claims: private longitudinal data remains mutable, correctable, revocable, exportable, and deletable, while only bounded credentials or contribution claims are disclosed. Aura Places may function as evidence-bearing contribution portfolios, but the architecture explicitly rejects a mandatory universal social-credit score. Creator, referral, sponsorship, and educational attribution is divided into graded evidence classes so that exposure or a click cannot be silently misrepresented as unique causality. N95 expands the Scientific Arena into a multi-class research-bounty market that can separately reward discovery, replication, falsification, boundary-condition discovery, optimization, generalization, field validation, and specialized facility execution. Laboratories, universities, private R&D facilities, community research centres, specialist workshops, instruments, and other qualified facilities may satisfy bounded physical-work nodes with explicit protocol, safety, jurisdiction, evidence, and milestone requirements. Negative or boundary results can therefore be economically valuable rather than forcing incentives toward positive confirmation. N96 discloses objective-compiled Ephemeral Institutions: temporary collaboration structures formed when an objective requires people, organizations, Nations or communities, facilities, professional roles, funding sources, data rights, services, and governance responsibilities across existing institutional boundaries. Aura may compile the coordination graph and required agreements, but real principals retain incorporation, contract, procurement, insurance, hiring, equity, and other legal authority. Repeated successful collaboration may later support a human decision to create a durable cooperative, consortium, enterprise, laboratory, or service network. N97-N98 extend the Commons into physical production. Machines, workshops, laboratories, factories, and service providers can expose signed capability manifests describing processes, materials, tolerances, calibration, evidence/certification class, locality, availability, cost, operator requirements, and prohibited uses. A validated design can then be compiled against authorized local production resources without treating substitutions as automatically equivalent. Manufactured artifacts can retain a living lineage containing design version, material/process evidence, machine/facility identity, inspection, repairs, modifications, safety notices, field results, and reuse or recycling pathways. Field failures can generate new repair, redesign, maintenance, material-substitution, or research bounties, closing the cycle from need to research to prototype to production to field learning and back into the Commons. N99 defines AuraNet as a transport-neutral logical network of sovereign principals and capabilities rather than a mandatory peer-to-peer topology. Personal devices, local servers, hosted sovereign data services, community/Nation infrastructure, enterprises, federated personal-data servers, relays, P2P links, offline/intermittent nodes, and future transports may participate if they preserve identity, rights, minimum disclosure, provenance, portability, revocation, and canonical-owner semantics. Cross-border composition remains jurisdiction-aware: privacy technology does not erase law, professional regulation, cultural/community authority, export restrictions, sanctions, data-residency obligations, or a node's right to refuse composition. N100 completes the accountability/economic stack with proof-carrying assurance contracts. A warranty, service-level agreement, professional assurance, or insurance-reference contract may bind a specific artifact/process version, covered predicates, verifier class, provenance root, responsible principal, operating conditions, duration, exclusions, remedies, and responsibility declarations. Machine receipts, cryptographic hashes, verifier results, and human/institutional attestations provide evidence, but they do not manufacture certification, legal liability, insurance coverage, negligence, warranty obligations, or truth. Any such consequence remains the product of an explicit governing contract, law, regulator, insurer, professional body, or other authorized institution. The expanded paper also strengthens the privacy model through a "compute-to-data" principle: when practical, admitted computation should move toward sovereign private data before private data is exported toward external computation. The reference architecture may combine local AI/SLM execution, selective disclosure, Verifiable Credentials, differential privacy, zero-knowledge proofs, multiparty computation, private-set methods, trusted execution, or homomorphic computation according to the threat model; none is treated as a universal anonymization guarantee. The central economic thesis remains that the permanent unit of value need not be a monolithic application. It can be a verified, attributable, rights-bearing capability, method, workflow, scientific result, fabrication process, contribution, credential, or other reusable object that participates in many temporary objective-specific Arenas. Value can therefore become legible through meaningful verified contribution and lineage, while licensing, provenance, attribution, settlement, scientific truth, authority, certification, and human/institutional responsibility remain explicitly separate layers. The combined architecture describes a possible progression from app-centric computing toward a governed Commons of persistent capabilities, portable personal cognition, conve
Abdul Adlim, Babun Suharto, Wildan Khisbullah Suhma, Kholida Ulfi Mubaroka
The rapid development of crypto assets has challenged the classical concept of mal (property) in Islamic jurisprudence because digital assets do not possess tangible physical characteristics traditionally associated with lawful ownership. This study aims to reconstruct the paradigm of mal within contemporary fiqh by examining the legal status of crypto assets through the framework of maqasid al-shari'ah, particularly hifz al-mal, while evaluating the role of smart contracts in reducing contractual uncertainty (gharar). This study employed a qualitative normative legal approach based on literature analysis of classical fiqh, usul al-fiqh, contemporary Islamic legal scholarship, institutional fatwas, and financial regulations. The findings demonstrate that the concept of mal has evolved from a material-based understanding toward a value-oriented paradigm that emphasizes recognized benefit, scarcity, and lawful ownership. Under these criteria, crypto assets may be recognized as mal when supported by legitimate ownership, transparent governance, and productive economic purposes. Smart contracts contribute to minimizing contractual and operational gharar through automated execution and transaction transparency, although they cannot eliminate risks arising from market volatility. This study proposes a reconstructed paradigm of mal that provides a more contextual analytical framework for assessing the legality of digital assets within contemporary Islamic law.
Abstract Financial time-series forecasting lies between AI and market microstructure, but most studies optimise generic error metrics instead of risk-adjusted economic value under realistic frictions. Unlike NLP and vision, the field lacks a shared, reviewer-enforced standard for data handling and evaluation, leading to persistent problems such as data leakage, backtest overfitting and metric-chasing on RMSE/MAE. This paper introduces QFRS a novel, enforceable by reviewers and editors, seven-standard framework and checklist for evaluating and reporting financial asset forecasting and trading claims. QFRS covers quantitative studies on equities (stocks), forex, cryptocurrencies, rates, derivatives (futures, forwards, options, swaps), energy prices, and commodities (gold, oil and silver) and other asset classes. The seven standards specify an end-to-end experimental pipeline, covering (i) dataset construction, (ii) labelling, (iii) point-in-time feature engineering, (iv) leakage-free scaling or normalisation, (v) time-respecting data splits, (vi) evaluation metrics and (vii) cost and slippage-aware backtesting with explicit execution assumptions and decision rules mapping predictions to positions. To validate the standard’s diagnostic value, a compliance audit of Scopus-indexed forex forecasting papers published in 2025 is presented. None of these papers achieved full compliance across all seven standards, with economic backtesting (12.2%) and causal scaling (31.7%) recorded the lowest pass rates. QFRS underpins a public state-of-the-art leaderboard, ensuring that only studies satisfying these standards are ranked, with the goal of shifting the literature from opaque, error-metric-driven results to transparent, economically meaningful and comparable benchmarks. The accompanying leaderboard is available and updated regularly at http://mkhushi.github.io .
This paper introduces the Dynamic External Memory LSTM (DEM-LSTM), a novel deep neural architecture designed to address the hidden state information bottleneck and temporal context decay inherent to standard LSTMs in financial time-series forecasting. By decoupling sequence processing from persistent state storage via an addressable external memory matrix ($M_t$), DEM-LSTM dynamically reads, erases, and updates market context across long sequences without corrupting internal hidden representations. Evaluated across four distinct asset classes—Foreign Exchange (EUR/USD), Commodities (XAU/USD and USOIL), and Cryptocurrencies (BTC/USD)—DEM-LSTM consistently outperforms standard LSTM baselines across all metrics, achieving up to a 41.4% reduction in RMSE on Gold spot prices while maintaining superior stability across high-volatility market regimes.
Skip to content Theory-of-Entropicity-ToE-Research-Lab-The-Aether-Live-Lab-NoteBook Repository navigation Code Issues Pull requests Agents Theory-of-Entropicity-ToE-Research-Lab-The-Aether-Live-Lab-NoteBook/markdown-from-clickup-live-lab-notebook /A-Brief-Introduction-to-Obidi's-Loop-as-an-Accounting-Principle-of-Physics-in-the-Theory-of-Entropicity-(ToE)'s-Formulation-of-Einstein's-Relativistic-Kinematics.md Entropicity Entropicity 3 days ago 296 lines (171 loc) · 17.3 KB Preview Code Blame A Brief Introduction to Obidi's Loop as an Accounting Principle of Physics in the Theory of Entropicity (ToE)'s Reinterpretation, Explanation and Derivation of Einstein's Relativistic Kinematics Without Resorting to Geometric Curvature—EB, TEB, OBE, ERP, ERF, NRT, ELF, EF, ET, RET, OET, CAT Reference(s): https://github.com/Entropicity/Theory-of-Entropicity-ToE-Research-Lab-The-Aether-Live-Lab-NoteBook/blob/9db5cef4433036a544dcc869e2f52ecdc8c5cd02/markdown-from-clickup-live-lab-notebook/Accounting-Principles-of-Obidi's-Theory-of-Entropicity-(ToE)-A%20Brief-Introduction-to-Accounting-Applications-in-Modern-Physics.md In John Onimisi Obidi’s Theory of Entropicity (ToE), Obidi’s Loop serves as the definitive mechanism that strips away Einstein's reliance on four-dimensional spacetime geometry. Instead of treating time dilation, length contraction, and mass increase as the geometric bending of a spacetime fabric, Obidi's Theory of Entropicity (ToE) derives these exact kinematic transformations from strict resource allocation and ledger-balancing rules within a universal, dynamic entropic field. [1, 2, 3] The framework reinterprets Einstein's relativistic kinematics as a literal system of physical bookkeeping, replacing geometric curvature with transactional limits [TL]. [2, 3] 1. The Accounting Framework: The Entropic Budget Equation (EBE) To understand Obidi's Loop, one must first look at the Entropic Accounting Principle (EAP), which models every physical system as a closed account holding a strictly finite, universal resource called the Total Entropic Budget ( E B ) [TEB] / [EB]. [3] Instead of moving through space, an object is actively "rearranging its state" within the entropic field. This finite budget must be continuously balanced and distributed across three competing expense ledgers: [1, 2, 3] E B = Γ Identity + Γ Motion + Γ Interaction The above isObidi's Budget Equation (OBE), where: Γ Identity (The Rest Account [TRA]): The entropic resource spent locally to maintain internal processes (e.g., the ticking of a local clock, chemical bonds, or particle decay). Γ Motion (The Kinetic Account [TKA]): The entropic cost paid to the field to change physical positions relative to other entities. Γ Interaction (The Causal Account [TCA]): The cost allocated to exchanging signals and maintaining field equilibrium. [3] That is: EB = TRA + TKA + TCA = Sum[TRA|TKA|TCA] 2. The Hard Ceiling [THC]: Reinterpreting c as a Throughput Limit In Einstein’s relativity, the speed of light ( c ) is an axiomatic postulate. But in Obidi's Theory of Entropicity (ToE), the speed of light c is a derived transaction limit [DTL]. [2, 4, 5, 6] According to Obidi’s No-Rush Theorem (NRT), the universal entropic field possesses a maximum processing speed—a hardware configuration limit. The constant c represents the absolute maximum rate at which the field can process and redistribute entropic currency ( E B ) per unit of time. [2, 5, 7] Because the field's processing capability is capped at c , a system cannot simply add speed without paying for it from its finite budget. Every increase in external velocity forces a strict, non-negotiable reallocation of resources on the ledger. [2, 3] 3. The Re-Derivation of Kinematics via Ledger Balancing When a system is accelerated, its kinetic ledger ( Γ Motion ) must increase. Because the total entropic budget ( E B ) is capped by the field's maximum throughput ( c ), funds must be forcefully embezzled [extracted/reallocated] from the other ledgers to balance the master sheet. This direct reallocation derives Einstein’s kinematics purely through [physical] accounting mathematics [principles]: [2, 3] A. Time Dilation ( Δ t ′ ) as an Internal Deficit [ID] To fund high-velocity motion ( Γ Motion ), the field reduces the budget allocated to the system's internal identity ledger ( Γ Identity ). Because proper time is defined in ToE as the rate of local entropic change, a depleted identity ledger physically slows down all local tracking mechanisms. Time dilates not because "space is stretching," but because the local system lacks the remaining entropic budget to update its own internal state [IS] at the standard rate. [3, 5] B. Mass Increase ( m ) as an Entropic Tax The Entropic Resistance Principle (ERP) dictates that the field levies a strict transaction tax on rapid reconfigurations. The faster a system attempts to push through the field, the harder the field works to maintain global synchrony. This active drag is quantified as the Entropic Resistance Field (ERF). What Einstein observed as "relativistic mass increase" is reinterpreted by Obidi as the mounting accumulation of entropic overhead costs required to counteract field resistance. [2, 3] C. Length Contraction ( Δ x ′ ) as Spatial Compression [SC] for Balance [8] To preserve global consistency without changing the universal processing speed c , the spatial interval over which an interaction occurs must contract. The physical dimensions contract to minimize the total transactional distance, ensuring that the field can clear the system's movement within the allowed entropic budget window. [2] 4. The Mechanics of Obidi's Loop Obidi's Loop (OL) is the ultimate systemic bottleneck of this accounting framework. It explains why no massive object can ever cross the threshold of c by revealing a mathematical catch-22 built into the Obidi budget equation (OBE). [3] When external energy is continuously pumped into a system to increase its velocity, the ledger undergoes a compounding crisis: [3] 1. Diminishing Returns [DR]: As velocity climbs, the Entropic Resistance Field (ERF) scales exponentially. [3] 2. The Consumption Loop: Every new unit of energy intended to increase velocity ( Γ Motion ) is instead automatically consumed by the rising entropic tax ( E R P ) required to fight the field's resistance. [2, 3] 3. The Trap (Obidi's Entropic Trap—OET): As the velocity asymptotically approaches the cosmic update limit ( c ), the efficiency of energy conversion drops to zero. The harder the system strives to advance, the more its total effort is completely absorbed by the field's resistance. [3] Ultimately, progress becomes unmeasurable and unattainable. The system is permanently locked in Obidi's Loop: it cannot purchase higher velocities because the transaction tax has entirely swallowed its purchasing power. [3] By shifting the paradigm from geometric curvature to a finite resource ledger, Obidi's Theory of Entropicity (ToE) elegantly and flawlessly mirrors the mathematical predictive power of Einstein's Special Relativity while providing a fundamentally distinct, thermodynamic "why" behind the Newtonian and Einsteinian laws of motion. [2, 6, 9] If you would like to examine this framework further, would you prefer to explore the mathematical conversion equations that derive the entropic Lorentz factor (ELF) ( γ ), or look at how this model addresses quantum entanglement delays through the lens of accounting? 🔷 Obidi’s Loop as the Accounting Principle of Physics: How the Theory of Entropicity (ToE) Re‑Derives Einstein’s Relativistic Kinematics Without Geometric Curvature—TEB, OBE, ERP, ERF, NRT, ELF, EF, ET, RET, OET, CAT Modern physics has long treated Einstein’s relativistic kinematics as a geometric consequence of spacetime curvature. But in John Onimisi Obidi’s Audacious Theory of Entropicity (ToE), relativity is not geometric — it is accounting. In Obidi's Theory of Entropicity ToE), Relativity is Accounting! ToE reframes motion, time dilation, mass increase, and length contraction as ledger‑balancing operations inside a finite, universal entropic field. The result is a complete re‑derivation of Einstein’s equations using resource allocation, transaction limits, and entropic bookkeeping rather than spacetime geometry. 📘 1. The Entropic Accounting Principle (EAP) Every physical system possesses a finite Total Entropic Budget (E_B)—TEB. This budget must be continuously allocated across three competing accounts: EB = Γ₍Identity₎ + Γ₍Motion₎ + Γ₍Interaction₎ This is the Obidi Budget Equation (OBE) — the master ledger of ToE. 🧩 Identity Ledger (Γ₍Identity₎) Resources for internal processes: clocks, decay rates, structural stability. 🚀 Motion Ledger (Γ₍Motion₎) The entropic cost of changing position in the field. 🔗 Interaction Ledger (Γ₍Interaction₎) The cost of exchanging signals and maintaining causal consistency. Relativistic effects emerge when these ledgers rebalance under stress. ⚡ 2. The No‑Rush Theorem (NRT): Reinterpreting (c) as a Throughput Limit In ToE, the speed of light c is not a geometric constant — it is the maximum processing speed of the entropic field [EF]. The field cannot update reality faster than (c). This creates a hard ceiling on how much entropic currency can be spent on motion per unit time. Acceleration therefore forces mandatory reallocation of the budget. 📊 3. Ledger‑Based Re-Derivation of Relativistic Kinematics ⏳ A. Time Dilation — The Identity Deficit [ID] Increasing (Γ₍Motion₎) drains (Γ₍Identity₎). With fewer resources for internal updates, the system’s proper time slows. Time dilation becomes an accounting shortfall, not geometric stretching. 🧱 B. Mass Increase — The Entropic Tax [ET] (ERP + ERF) The Entropic Resistance Principle (ERP) states that the field taxes rapid reconfiguration. This tax is enforced by the Entropic Resistance Field (ERF). Relativistic mass increase is si
Over the past few years, Wireless Sensor Networks (WSNs) have been increasingly deployed for numerous sensing and monitoring purposes in environmental monitoring, industrial automation, health monitoring, military surveillance, smart agriculture and disaster management among others. The inherent limitations in terms of processing power, memory, communication bandwidth and energy of sensor nodes make WSNs highly susceptible to malware attacks. A wide variety of malware such as sensor network worms, Trojans, viruses, botnets and ransomware can easily propagate in a network through inter node communication. Such malware can cause serious damage to communication, compromise sensitive data, consume energy of the infected nodes thereby reducing the lifetime of network among others. In the last decade, numerous approaches have been proposed for the detection of malware infecting sensor nodes. These approaches range from traditional signature-based detection and behavior-based detection to more advanced approaches such as machine learning (ML)-based, deep learning (DL) -based, blockchain-based, trust management-based and federated learning-based detection. Most of the existing approaches for malware detection in WSNs have been designed to work on WSNs and have not been tested on real scenarios. Most of the approaches have their own strengths and weaknesses and the most suitable approach for a given application depends on various factors. In this paper, we present a comprehensive review of approaches for the detection of malware infecting sensor nodes in WSNs. We present a taxonomy of reviewed approaches for detection of malware. We also present a discussion on approaches for modeling malware propagation in a WSN as well as review on various categories of malware that have been designed to attack sensor nodes in WSNs along with detection frameworks for different categories of malware. We also present a comparative study of approaches used for the detection of malware in WSNs on the basis of various parameters such as detection accuracy, computational complexity, energy efficiency, scalability, detection latency and deployability. The review and taxonomy presented in this paper will be highly beneficial for researchers and practitioners designing approaches and systems for the detection of malware in WSNs. Various open research challenges in this area have also been discussed in this paper including detection of zero-day malware, designing of intelligent models to be light enough to be deployed on sensor nodes, use of explainable artificial intelligence for detection of malware in WSNs, designing approaches for privacy-preserving collaborative learning in WSNs and designing adaptive security approaches for WSNs.
Ahmed A. Jasim, Noor Riyadh Issa, Hisham A. Shehadeh, Fadhil Mukhlif · 6 authors
Abstract The Wireless Sensor Networks (WSNs), which are deployed in harsh environments, are extremely susceptible to localized battery exhaustion as well as intelligent inside routing threats, especially sinkhole and data falsification attacks. In this paper, we present ECHVM (Enhanced Cluster Head selection by Voting and an ECC-based Blockchain Mechanism), a novel, secure, and energy-efficient routing framework to achieve an optimal trade-off between network security and hardware resource efficiency. We present the ECHVM protocol that combines Elliptic Curve Cryptography (ECC) with a lightweight, local distributed ledger to mitigate risks of centralized authority by transferring the verification of crucial network events from a single, highly vulnerable centralized alert sink node to a decentralized, voting-based consensus among neighboring nodes. In this study, a weighted voting algorithm based on node and distance proximity metrics is applied to cluster head selection, where a 51% neighbor consensus rule is leveraged to validate local ledger transactions against malicious acts. Moreover, a local energy density and topological communication geometry-oriented energy-efficient cluster head (CH) selection algorithm is crafted to ensure balanced CH distribution in the high-density areas of the network structure so as to avoid the premature energy hole problem. Using the standard first-order radio energy model, quantitative simulations performed in MATLAB show that ECHVM achieves a malicious node detection rate of 98.2% and extends the network lifetime by 30% compared to state-of-the-art protocols (e.g., ELSO and SEC-HDT) because of proactive topology defense and rapid node sleeping. The results of statistical validation using the Wilcoxon Signed-Rank test confirm that both the reduction in energy consumption and network longevity offered by ECHVM are highly significant ( p = 0.019), justifying ECHVM as a mathematically sound, permanent, scalable security framework suitable for resource-constrained, dense Internet of Things (IoT) and smart sensing applications for next-generation communication systems.
Perkembangan Artificial Intelligence (AI) telah mendorong transformasi dalam Supply Chain Management (SCM) melalui peningkatan efisiensi operasional, kualitas pengambilan keputusan, dan ketahanan rantai pasok. Penelitian ini bertujuan untuk mengidentifikasi perkembangan penelitian AI dalam SCM, teknologi AI yang dominan, manfaat dan tantangan implementasinya, serta peluang penelitian pada periode 2021–2026. Metode yang digunakan adalah Systematic Literature Review (SLR) dengan menganalisis sepuluh artikel yang relevan dari berbagai sumber ilmiah. Data dianalisis menggunakan pendekatan narrative synthesis untuk mengidentifikasi pola, persamaan, dan perbedaan hasil penelitian. Hasil kajian menunjukkan bahwa Machine Learning merupakan teknologi AI yang paling banyak diterapkan, terutama pada demand forecasting, inventory management, optimasi logistik, dan manajemen risiko. Selain itu, perkembangan penelitian juga mengarah pada pemanfaatan Deep Learning, Computer Vision, Natural Language Processing, Digital Twin, dan integrasi AI dengan Internet of Things serta Blockchain untuk meningkatkan transparansi, fleksibilitas, dan ketahanan rantai pasok. Meskipun implementasi AI memberikan manfaat yang signifikan, masih terdapat tantangan berupa kualitas data, kesiapan infrastruktur digital, keamanan siber, dan kompetensi sumber daya manusia. Penelitian ini memberikan gambaran mengenai tren perkembangan AI dalam SCM sekaligus menjadi referensi bagi pengembangan penelitian dan implementasi AI pada berbagai sektor industri.
Meeting the global demand for fresh, minimally processed food requires us to rethink how we monitor food safety. Traditional laboratory methods are often too slow, labor-intensive, and impractical for real-time applications. To overcome these delays, biosensors have emerged as a rapid, highly sensitive, and cost-effective alternative. This study explores how biosensing technology accurately detects pathogens, chemical contaminants like heavy metals and pesticides, and spoilage indicators across dairy, meat, produce, and packaged foods. What makes these tools truly transformative is their seamless integration with modern digital infrastructure. By combining biosensors with the Internet of Things (IoT), artificial intelligence (AI), nanotechnology, edge computing, and blockchain, we can create intelligent, continuous monitoring systems. These interconnected frameworks allow for real-time, farm-to-fork traceability, enabling early hazard detection, extending shelf life, and significantly reducing food waste through data-driven decisions. Despite this immense potential, bringing smart biosensors to the commercial market involves overcoming distinct practical hurdles. We examine current technical barriers, including biofouling, long-term sensor stability, power management, and high manufacturing costs. More importantly, we highlight the emerging innovations actively solving these bottlenecks, such as biodegradable materials, battery-free platforms, advanced printed electronics, and smart packaging technologies.
Scalable event-driven architectures are now the focus of enterprise supply chain and logistics research as this information is surfaced from transport assets, warehouses, suppliers, platforms and risk environments at a more frequent rate to allow for faster decision making. This review looks at the concepts of peer-reviewed studies of 2015–2025 that have focused on architectures that have the ability to transform distributed events into traceability, resilience, visibility, and automated coordination. The review of the literature shows that there is no single concept but rather scattered concepts in the domain of scalable event-driven logistics within the fields of Internet of Things (IoT) in logistics, Logistics 4.0, big data analytics, blockchain traceability, multi-agent control and digital supply chain twins. These streams have significant challenges around event capture, real time analytics, decentralized provenance, and disruption response. Key gaps remain in latency benchmarking, cross-enterprise semantic interoperability, governance of shared event streams, and validated architecture-level performance evidence. The field is significant due to the increased reliance on enterprise architectures that extend beyond the organizational boundary that are also responsive, auditable and resilient.
This study examines the current state of digital asset auditing and proposes a clearer future vision through a systematic review of relevant literature and prior studies. It highlights the fundamental differences between digital and traditional assets, explains the classification of digital assets and their close association with blockchain technology, and analyzes the existing accounting and auditing frameworks considering international standards and provides a brief overview of the status of Egyptian legislation. The study also discusses the evolving role of auditors and the main stages of the audit process in the digital environment. The findings indicate that rapid digital transformation requires the development of advanced auditing standards and methodologies, and that the adoption of data analytics, smart contracts, and continuous auditing, together with enhancing auditors’ technical and professional competencies, contributes to improving audit quality, transparency, and risk management related to digital assets.
Open access
Security, Politics, and Digital Transformation
Financial Reporting and XBRL
Innovations and Analysis in Business and Education
P. Thanalakshmi, V. G. Kiruthika, J. C. Gokul Abinash, P. Saravanan · 6 authors
Wireless Sensor Networks (WSNs) are vulnerable to malicious nodes and sensor node failures, which compromise data integrity and network reliability. These threats result in incorrect decisions and reduce system trust. To address this, machine learning algorithms enable anomaly detection by identifying abnormal sensor nodes, while blockchain ensures secure and tamper-proof data storage. However, reliable consensus is essential before data validation in the blockchain. A hybrid framework combining ML, blockchain, and a modified HotStuff consensus algorithm with post-quantum cryptographic systems provides secure, fault-tolerant, and quantum-resistant consensus, ensuring trustworthy and resilient WSN operations.
Online voting platforms that rely on classical cryptography and centralized trust anchors face escalating challenges as the demand for secure and transparent digital elections grows. Such systems remain exposed to quantum-era threats, insider manipulation, and delayed audit mechanisms, which together can undermine public confidence and electoral legitimacy. To counter these risks, a quantum-resistant, multi-layer blockchain architecture has been developed to enable remote voting with continuous verifiability and resilience. This architecture resolves key weaknesses through five integrated layers. Quantum-Resistant Distributed Ledger Initialization (QR-DLI) embeds lattice-based cryptography, specifically Kyber and Dilithium variants, directly within the genesis block, ensuring the ledger is tamper-proof from inception and immune to quantum brute-force attacks. The Self-Adaptive Smart Contract Governance Engine (SASCG) introduces dynamic, participation-aware rule adjustments, allowing principled governance without manual overrides and ensuring that voting periods and eligibility rules adapt securely in real time. Homomorphic Vote Encryption with Multi-Authority Shard Key Distribution (HVE-MASKD) guarantees ballot confidentiality and authenticity by combining fully homomorphic encryption with distributed key shares, eliminating single points of trust. The Zero-Knowledge Proof–Based Real-Time Audit Layer (ZKP-RTAL) continuously validates ballot integrity while concealing vote content, creating a public and immutable audit trail. Finally, the Federated Performance & Threat Intelligence Optimizer (FPTIO) aggregates live telemetry and historical attack data to proactively tune consensus parameters and predict potential intrusions without interrupting the election process. Collectively, these layers achieve sub-second cryptographic operations, transaction throughput exceeding 1,500 TPS, over 99 % fraud detection accuracy, and strong scalability. The model provides a future-ready, auditable replacement for current e Voting infrastructures, strengthening digital democracy through post-quantum security, adaptive governance, and intelligent, continuous optimizations.
Multi-cloud adoption has widened the enterprise attack surface to a degree that perimeter-based defence can no longer address. Traffic is now flowing continuously across AWS, Azure, and GCP, and the majority of deployed Zero Trust Architecture (ZTA) systems are still using static rule tables, with no ability to provide an audit trail of the reasoning behind decisions, and with logs stored in datastores that can be modified by an insider without detection. This paper proposes ZT-ChainGuard, a framework that overcomes these three limitations in one architecture that integrates an ensemble machine learning trust-scoring engine, ZTA policy enforcement and a blockchain-based audit trail. The trust-scoring engine is a two-layer stacking ensemble, with XGBoost and Random Forest as base learners, and Logistic Regression as a meta-learner, and it returns a continuous trust score, P(Attack | flow), for each network flow, which is then used to trigger the ZT policy decision at a threshold of 0.5. The explanation of each decision is provided by SHAP values at both the global and per-flow level, and each decision is stored as an immutable, SHA-256 hash-chained block. On CICIDS2017 (2.83 million flows, 14 attack classes) the framework achieves 99.90% accuracy, 99.71% F1-score, and 99.99% ROC-AUC; on ToN-IoT (2.23 million IoT records, 9 attack types) it achieves 99.81% accuracy, 99.88% F1-score, and 100% ROC-AUC. The latency of inferences is 0.006ms per sample, and the overhead of auditing the blockchain is 0.019ms per block. This performance is not just a quirk of a particular split, as it is shown to be stable across the three folds of three-fold cross validation.