1640 papers
This paper presents a secure, scalable IoT-based animal health monitoring system that integrates real-time sensor data and machine learning with role-based access control and post-quantum cryptography to defend against future quantum threats while maintaining efficient performance.
This research proposes a Digital Twin-driven framework to optimize net-zero retrofitting for the UK's existing building stock, identifying significant adoption barriers through a mixed-method study and recommending policy and collaborative strategies to bridge the gap between digital innovation and decarbonization goals.
This paper presents a cost-effective visual-inertial odometry system for mobile robots that leverages commodity handheld devices to estimate displacement along constrained axes by filtering sensor noise, suppressing drift during stationary phases, and seamlessly integrating GPS for outdoor operation, thereby providing a zero-integration-cost logging solution for structured field robotics.
This study employs a Hybrid Choice Model to demonstrate that dedicated bike lanes and positive latent perceptions of station accessibility significantly drive bike-sharing adoption in Gorgan, Iran, leading to the development of a Station Suitability Index that optimizes system placement and yields substantial annual economic and environmental benefits.
This study demonstrates that compact salinity gradient solar ponds utilizing hybrid nanoparticle-enhanced phase change materials achieve superior thermal performance and heat retention compared to conventional systems, with machine learning models accurately predicting these outcomes to enable intelligent optimization of small-scale solar thermal storage.
This paper proposes a data-driven tensor product-based modeling and control methodology for nonlinear damped Lotka-Volterra systems, utilizing pseudo-inverse calculations and polynomial approximations to derive state matrices and Computed Torque Control inputs, with its effectiveness validated through both simulations and physical analog computer experiments.
This paper presents a multi-mode decoupled hyperelastic constitutive model, implemented in ABAQUS via a VUMAT subroutine, to accurately simulate and predict the nonlinear, anisotropic forming behavior and deformation mechanisms of three-dimensional angle-interlock preforms over complex surfaces.
This study presents a large-scale, expert-annotated dataset of 48,453 thematic maps from 1990 to 2025, constructed via an integrated computational workflow, to systematically analyze the evolution of cartographic design patterns, revealing distinct stylistic differences between journal and web maps while providing a foundational resource for empirical aesthetics and intelligent map design.
HelioTR-Atlas is a reproducible framework that integrates measured satellite direct irradiance with station-validated, lapse-rate-corrected thermodynamic data to deliver explainable, high-resolution photovoltaic yield assessments in complex terrain, demonstrating that while irradiance dictates spatial yield patterns, temperature primarily governs performance ratios.
This paper presents a robust trajectory tracking system for a bionic fish robot that integrates a complex-valued central pattern generator network, driven by gyroscope feedback to control fins and tail, with a model predictive control-based position controller under an extended Featherstone dynamics model to effectively navigate straight and circular paths despite external disturbances.