digitado

Blockchain networks now underpin mission-critical services in finance, healthcare, supply-chain logistics, and digital governance, yet production deployments continue to suffer severe resilience failures ranging from Byzantine consensus violations to cross-chain bridge exploits that have collectively caused losses exceeding $2 billion. The root cause is a critical tooling gap: ex- isting frameworks such as BlockBench and Hyperledger Caliper evaluate only crash-fault performance and provide neither ad- versarial fault modelling nor automated remediation guidance, leaving operators without a rigorous means […]

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Open, well-documented datasets are essential for the reproducible development of vision systems for urban utility management. This Data Descriptor presents a curated RGB object-detection benchmark of four classes associated with electrical distribution and street-level utility assets: Inspection Chamber, Overhead-to-Underground Transition, General Protection Box, and Transformer Substation. The public release contains 997 valid image-label pairs partitioned into 698 training, 150 validation, and 149 test images. Images were acquired during 2019 in multiple localities across Spain, predominantly with a mobile […]

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The concept of the technological singularity is applied here to architecture (of buildings, not software). This is the point at which non-human intelligence surpasses ordinary human cognitive limits. AI betters mainstream architectural culture in one crucial aspect — its capacity to evaluate design that adapts to human emotional health. Postwar building architecture as an institutional power system rewards abstraction and stylistic conformity through media prestige while not accounting for embodied human experience. By narrowing judgment criteria, architectural studio […]

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Immutable code and steep transaction fees make smart contract deployment uniquely unforgiving. While continuous integration (CI/CD) pipelines excel at catching standard software bugs, applying exhaustive security tests to Web3 applications severely bottlenecks development through massive computational overhead and gas consumption. This paper presents a testing architecture designed specifically to resolve this tension between security depth and execution speed. The system pipelines three core engines. First, an AI-driven pre-execution gate flags immediate vulnerabilities. Next, a structural reduction module applies […]

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Wildfire spread prediction demands hyper-local accuracy at scales unattainable by traditional physics-based models or coarse satellite observations. This paper introduces a novel Digital Twin AI framework leveraging 5G IoT mesh networks to deliver real-time, 10m×10m resolution fire propagation forecasts with 5-60-minute lead times. Deployed across 1,200 self-healing sensor nodes, the system fuses multi-modal environmental data thermal anomalies, 3D winds profiles, dynamic fuel moisture at 100Hz through graph attention networks, feeding physics-informed neural twins synchronized via unscented Kalman filtering. […]

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Reinforcement learning (RL) in mobile edge computing (MEC) faces critical challenges of data heterogeneity, communication overhead, and limited generalization across diverse preferences and system configurations. We propose Adaptive Reinforcement Learning Offloading (ARLO), a unified framework integrating adaptive dissimilarity measures for federated learning with generalizable multi-objective optimization for computation offloading. The Adaptive Dissimilarity Measure module leverages parameter dissimilarity with Lagrangian multipliers to mitigate model drift under Non-IID data and loss dissimilarity to reduce communication overhead via adaptive aggregation. The […]

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In partial multi-label learning (PML), each instance is associated with a set of candidate labels containing both ground-truth and noisy labels. The presence of noisy labels disrupts the correspondence between features and labels, degrading classification performance. To address this challenge, we propose a novel PML method based on feature-label modal alignment (PML-MA), which treats features and labels as two complementary modalities and restores their consistency through systematic alignment. Specifically, PML-MA first employs low-rank orthogonal decomposition to generate pseudo-labels […]

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