Deep learning predicts infrastructure quality in Africa using satellite imagery.
problem Expensive and limited monitoring of infrastructure quality in developing regions.
method Convolutional neural network trained on Landsat 8 and Sentinel 1 satellite imagery.
result AUROC scores of 0.881 for Electricity, 0.862 for Sewerage, 0.739 for Piped Water, and 0.786 for Roads.
Study assesses 'big data' in materials science, highlighting challenges.
problem Understanding what constitutes 'big data' in materials science.
method Selected examples of machine learning models, data quality, and infrastructure requirements.
result Big data presents unique challenges in materials science.
The prevalent view in the economics literature is that a high level of infrastructure investment is a precursor to economic growth. China is especially held up as a model to emulate. Based on the largest dataset of its kind, this paper punctures the twin myths that, first, infrastructure creates economic value, and, se…
Infrastructure monitors AI/ML radiology models across multiple sites.
problem Monitoring and improving AI/ML radiology models across multiple sites.
method Interactive radiology reporting, centralized cloud system, post-marketing surveillance.
result Efficient monitoring and iterative development of AI/ML models without radiologist burden.
This paper ranks Latin American countries based on AI potential.
problem Identifying emerging AI powers in Latin America.
method Ranking based on infrastructure, education, and finance.
result Argentina, Colombia, Uruguay, Costa Rica, and Ecuador are new emerging powers in AI.
Model uses satellite imagery to assess road quality.
problem Inefficient monitoring of road investments in developing regions.
method Convolutional neural networks on high-resolution satellite imagery.
result Models achieve 88% binary and 73% 5-category classification accuracy.
The study reveals fundamental limits of fraud detection in card payment networks.
problem Fraud detection in card payment networks is challenging due to structural information impairments.
method Formalized card authorization as a sequential decision problem with delayed feedback, derived minimax regret lower bound.
result Improving issuer reporting quality or reducing censorship can yield larger reductions in the regret floor than increasing model complexity.
Study generates synthetic fNIRS data and applies machine learning for improved neuroimaging.
problem Scarcity of high-quality fNIRS neuroimaging datasets.
method Synthetic data generation using Monte Carlo simulations and machine learning.
result Improved accuracy and efficiency of fNIRS tomography.
Paper explores AIaaS on SDI, offering services in smart sectors.
problem Complexity of infrastructures driving AIaaS.
method Proposes architectural scheme based on SDIs with AI-aaS applications.
result Experimental results for three AI-aaS applications.
Paper trains language models without memorizing user data.
problem Training production-scale language models with user privacy.
method Federated Learning with Differentially Private Federated Averaging (DP-FedAvg).
result Demonstrated training of a production NWP model with user-level differential privacy.
Machine learning monitors fueling infrastructure reliability.
problem Ensuring reliability of alternative fueling infrastructure for ZEV adoption.
method Unsupervised temporal clustering algorithm and survey analysis.
result Infrastructure performance and reliability determined for hydrogen stations in California.
VTrackIt creates a synthetic dataset with infrastructure and vehicle info for AVs.
problem Lack of infrastructure and pooled vehicle info in existing AV datasets.
method Developed VTrackIt, a synthetic dataset with intelligent infrastructure and pooled vehicle info, and introduced InfraGAN for trajectory predictions.
result VTrackIt reduces high-risk edge cases in AV trajectory predictions.
The Economist recently reported that infrastructure spending is the largest it is ever been as a share of world GDP. With $22 trillion in projected investments over the next ten years in emerging economies alone, the magazine calls it the "biggest investment boom in history." The efficiency of infrastructure planning a…
The article first describes characteristics of major infrastructure projects. Second, it documents a much neglected topic in economics: that ex ante estimates of costs and benefits are often very different from actual ex post costs and benefits. For large infrastructure projects the consequence is cost overruns, benefi…
Study creates a global living index to assess quality of life.
problem Long-term impacts of global economic changes on living conditions.
method Machine learning framework combining socio-economic factors.
result Developed a practical tool for policymakers to identify areas needing improvement.
Cryptocurrency markets show similar returns but different volatility responses to infrastructure and regulatory shocks.
problem Understanding how cryptocurrency markets differentiate between infrastructure and regulatory shocks.
method Event-level block bootstrap inference on 31 cryptocurrency events across Bitcoin, Ethereum, Solana, and Cardano (2019-2025).
result No statistically significant difference in cumulative abnormal returns between infrastructure failures and regulatory enforcement.
Study uses Perelman and Ricci flow methods to analyze economic inequality.
problem Impact of socio-economic challenges and technological progress on economic inequality.
method Perelman model and Ricci flow methods.
result Technological innovations and social protection programs reduce inequality.
A novel outlier score detects new road infrastructure images.
problem Detecting newly observed road infrastructure images.
method Entropy-based outlier score using directed nearest neighbor graphs.
result High potential of the proposed technique in identifying outliers.
We combine Bayesian networks (BNs) and structural reliability methods (SRMs) to create a new computational framework, termed enhanced Bayesian network (eBN), for reliability and risk analysis of engineering structures and infrastructure. BNs are efficient in representing and evaluating complex probabilistic dependence …
Natural disasters can have catastrophic impacts on the functionality of infrastructure systems and cause severe physical and socio-economic losses. Given budget constraints, it is crucial to optimize decisions regarding mitigation, preparedness, response, and recovery practices for these systems. This requires accurate…
Hybrid framework predicts Arctic permafrost decline, risks infrastructure, and provides tools.
problem Tackles permafrost decline and infrastructure risk assessment in Arctic territories.
method Hybrid physics-machine learning framework integrating 2.9 million observations.
result Projects mean permafrost fraction decline of -20.3 pp under RCP8.5 forcing, with high-risk zones identified.
This study analyzes dynamic connectedness in global supply chain infrastructure portfolios, identifying key risk factors and extreme events.
problem Understanding dynamic connectedness in global supply chain infrastructure portfolios under various risk factors and extreme events.
method Time-varying parameter vector autoregression (TVP-VAR) model to study spillover and interconnectedness of risk factors.
result Risk shocks influence dynamic connectedness between portfolios and risk factors, and extreme events affect investment outcomes.
IntraLayer connects digital finance platforms efficiently.
problem Inefficient interconnectivity in digital finance.
method Core infrastructure and adaptive fiscal policy.
result Optimised transactional efficiency for various agents.
This paper argues, first, that a major problem in the planning of large infrastructure projects is the high level of misinformation about costs and benefits that decision makers face in deciding whether to build, and the high risks such misinformation generates. Second, it explores the causes of misinformation and risk…
QFlow learns to prioritize video streaming to improve quality of experience.
problem Inconsistent video streaming quality due to network inefficiency.
method Develops a learning approach to dynamically allocate resources for video streaming.
result Demonstrates improved video quality for all clients at a wireless access point.
Research quantifies financial exclusion risks in UK, focusing on cash infrastructure and socio-economic factors.
problem Localised financial exclusion in the UK as cash infrastructure declines.
method Developed a composite indicator using various input variables.
result Financial exclusion is more prevalent in deprived communities and affluent areas.
Fragmented exchanges arise due to speed advantages in high-activity regions.
problem Fragmentation of distributed securities exchanges due to speed advantages in high-activity regions.
method Economic model and Monte Carlo simulations of a decentralized exchange with two miner clusters.
result Speed advantage increases with infrastructure asymmetry between regions.
Deep learning detects cyber-attacks in smart grid systems.
problem Cyber-attacks on smart grid systems.
method Deep learning-based intrusion detection system trained on industrial dataset.
result Proposed system outperforms Naive Bayes, SVM, and Random Forest.
An Ensemble Anomaly Detection Framework for Risk Calculation Integrity
problem Detecting errors in risk valuation outputs
method Ensemble Quality Assessment Framework (EQAF)
result Achieves F1 scores of 61-79% across four datasets
Automated road infrastructure mapping using connected vehicle data and deep learning.
problem Manual identification of intersections is laborious and time-consuming.
method Geohashing, YOLOv5 algorithm for classification of road segments and intersections.
result Overall classification accuracy of 95%, with high F1 scores for straight roads and intersections.
Methodology measures financial impacts using existing credit loss infrastructure.
problem Measuring the impact of financial scenarios on expected credit losses.
method Captures scenario effects through changes in default probabilities; uses existing provisioning infrastructure.
result Methodology validated through standardized climate scenario exercise in Canada and Quebec.
Develops a framework to assess infrastructure reliability under natural and malicious events.
problem Assessing reliability and costs of infrastructure under various hazards.
method Coupling mechanical reliability analyses with economical reliability analyses using probabilistic considerations.
result Indicators of probable cost of failure for infrastructure, aiding safety investments.
The study examines how modernizing settlement infrastructure affects inside money elasticity and network efficiency.
problem Understanding the impact of modernizing settlement infrastructure on inside money elasticity and network efficiency.
method Constructed a panel dataset of 809 reform events across 24 advanced economies, decomposed into economic channels and phases, and used a T2S event-study and synthetic control method.
result Modernizing settlement infrastructure generates network-conditional balance sheet efficiencies, with an estimated +13.4 percent efficiency recovery from 2027-2032.
Paper proposes a new topology for AML analysis using Poincaré embeddings.
problem Complex money laundering schemes and regulatory constraints hinder AML analysis and information sharing.
method Proposes a new topology for AML analysis using Poincaré embeddings.
result Demonstrates improved AML analysis and information sharing through Poincaré embeddings.
New methods detect roads in low-res satellite data, overcoming visibility challenges.
problem Detecting roads in low-resolution satellite imagery, especially those hard to see.
method Two deep learning frameworks for ordinal classification of road types from satellite time series data.
result Models can identify large and medium-sized roads from Sentinel-2 imagery.
Edge filters reduce video data transmission to datacenters.
problem Strain on wide area network infrastructure due to video camera deployments.
method FilterForward system with lightweight edge filters and microclassifiers.
result Reduces bandwidth use by an order of magnitude.
Proposes a multi-objective variational autoencoder for smart infrastructure damage detection.
problem Detecting and diagnosing damage in smart infrastructure using multi-way data.
method Multi-objective variational autoencoder (MVA) method for smart infrastructure damage detection and diagnosis.
result The method accurately detects structural damage, estimates severity, and captures damage locations.
Optimizes electric aircraft deployment for Canadian aviation to reduce emissions.
problem Limited fleet capacity and operational structure hinder electric aircraft transition.
method Multi-period mixed-integer linear programming (MILP) framework.
result Electric aircraft can reduce emissions by over 70% within five years.
Despite incredible recent advances in machine learning, building machine learning applications remains prohibitively time-consuming and expensive for all but the best-trained, best-funded engineering organizations. This expense comes not from a need for new and improved statistical models but instead from a lack of sys…
This paper optimizes resource allocation for crowdsourced live streaming to improve viewer experience and reduce costs.
problem Improving viewer quality of experience (QoE) in crowdsourced live streaming.
method A prediction-driven resource allocation framework using machine learning to predict viewer numbers and proactively allocate resources.
result Maximizes viewer QoE and minimizes resource allocation costs through precise resource provisioning.
Neural MMO simulates MMOs to study multiagent intelligence.
problem Limited research environments for multiagent intelligence.
method Developed a new game environment inspired by MMOs.
result Standard methods can learn interesting behaviors in MMOs.
Surrogate models enhance digital twin technology for dynamic systems.
problem Lack of clarity and effective methods for digital twin applications.
method Exploration of Gaussian process (GP) emulators within digital twin framework.
result Surrogate models like GP emulators are effective for digital twin development.
We collect and analyze the data for working time, life expectancy, and the pair output and infrastructure of industrializing nations. During S-functional recovery from disaster the pair's time shifts yield 25 years for the infrastructure's physical lifetime. At G7 level the per capita outputs converge and the time shif…
Model trains from wifi traces to infer public transport levels.
problem Estimate the level of service of a city-wide public transport network.
method Robust unsupervised clustering for train movement inference; classification model for real-time commuter patterns.
result Accurately estimated demand-supply gap from connected devices.
Deep neural networks detect cyberthreats from Twitter.
problem Scalable processing of cybersecurity information from social media.
method Convolutional and bidirectional LSTM networks for tweet classification and named entity recognition.
result Pipeline achieves high true positive and F1-score rates for threat detection.
This article presents results from the first statistically significant study of cost escalation in transportation infrastructure projects. Based on a sample of 258 transportation infrastructure projects worth US$90 billion and representing different project types, geographical regions, and historical periods, it is fou…
Open-source Vizier optimizes complex systems for Google and beyond.
problem Optimizing large-scale systems with multiple objectives and constraints.
method Distributed, fault-tolerant, flexible API for blackbox optimization.
result OSS Vizier supports a wide range of optimization problems and is available as open-source.
A machine learning model improves MV CDSS accuracy.
problem Limited input data for MV CDSS due to missing physiologic monitoring device information.
method Developed a machine learning classifier for 5 MV modes with high accuracy.
result Average F1-score of 97.52% for per-breath classification.