1710 papers
This paper introduces a temperature-frequency-tuned impedance spectroscopy approach combined with interpretable full-spectrum modeling and unsupervised learning to overcome the nonlinearity and sensitivity limitations of metal oxide semiconductor gas sensors, enabling robust, linear, and accurate detection of individual and mixed gases.
This paper presents a cost-effective framework for retrofitting legacy belt conveyor systems with multi-sensor monitoring and SCADA-based visualization to enable real-time operational tracking and predictive maintenance, thereby facilitating their transition to Industry 4.0 standards.
This paper proposes AQ-MC, a controller framework for multi-router Wi-Fi sensing networks that dynamically coordinates measurement rates and active node subsets to ensure sensing activities remain within strict airtime and quality-of-service (QoS) penalty budgets, thereby enabling feasible coexistence with ordinary WLAN traffic.
This paper proposes Stability-Aware Configuration Maintenance (SACM), a controller-side method for cooperative Wi-Fi sensing that minimizes configuration update frequency and data overhead by rejecting feasible rate-tier replacements unless their utility gain outweighs the transition cost, as demonstrated through offline replay evaluations.
This study utilizes Taguchi design of experiments, ANOVA, and machine learning regression to optimize FDM process parameters for PET-G, identifying layer thickness as the most influential factor and determining that a 0.20 mm layer thickness, 250°C nozzle temperature, and 60% infill density yield the superior tensile properties.
This study proposes and evaluates an integrated solar-wind powered hydrogen refueling system with battery storage for maritime vessels, demonstrating through simulation and economic analysis that a hybrid configuration with optimized storage offers the most reliable and cost-effective solution for overcoming renewable intermittency and achieving scalable green hydrogen production.
This study synthesizes evidence from twelve DOI-verified sources to conclude that while the technical foundations of construction swarm robotics are mature, their transfer to the Peruvian Andes is currently constrained by regulatory and institutional gaps, necessitating a staged, principle-based readiness framework rather than immediate adoption.
This paper proposes TPCNet, a novel lightweight transformer-based framework that directly estimates precoders via a multi-scale residual and attention-enhanced autoencoder architecture to eliminate explicit CSI reconstruction, thereby achieving superior performance and reduced computational complexity with inherent scalability for 5G-Advanced massive MIMO systems.
This paper proposes a three-phase implementation framework for Peru to address its critical road infrastructure deficit by leveraging AI and Big Data to industrialize modular pavement production, demonstrating significant improvements in efficiency, cost, and quality compared to traditional methods.
This paper proposes the Cloud-based Adaptive Dynamic Budgeting (CADB) model, a methodological framework that leverages cloud computing and real-time Peruvian data sources to dynamically update construction project budgets, offering superior adaptability and cost-deviation tracking compared to traditional static methods, while acknowledging the need for future empirical validation.