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Analytical Equations for the Prediction of the Failure Mode of Reinforced Concrete Beam-Column Joints Based on Interpretable Machine Learning and SHAP Values.
Sensors (Basel)
December 2024
Laboratory of Reinforced Concrete and Seismic Design, Department of Civil Engineering, Democritus University of Thrace, 67100 Xanthi, Greece.
One of the most critical components of reinforced concrete structures are beam-column joint systems, which greatly affect the overall behavior of a structure during a major seismic event. According to modern design codes, if the system fails, it should fail due to the flexural yielding of the beam and not due to the shear failure of the joint. Thus, a reliable tool is required for the prediction of the failure mode of the joints in a preexisting population of structures.
View Article and Find Full Text PDFTemporal Logical Attention Network for Log-Based Anomaly Detection in Distributed Systems.
Sensors (Basel)
December 2024
Department of Computer Science, University of Bristol, Bristol BS8 1QU, UK.
Detecting anomalies in distributed systems through log analysis remains challenging due to the complex temporal dependencies between log events, the diverse manifestation of system states, and the intricate causal relationships across distributed components. This paper introduces a TLAN (Temporal Logical Attention Network), a novel deep learning framework that integrates temporal sequence modeling with logical dependency analysis for robust anomaly detection in distributed system logs. Our approach makes three key contributions: (1) a temporal logical attention mechanism that explicitly models both time-series patterns and logical dependencies between log events across distributed components, (2) a multi-scale feature extraction module that captures system behaviors at different temporal granularities while preserving causal relationships, and (3) an adaptive threshold strategy that dynamically adjusts detection sensitivity based on system load and component interactions.
View Article and Find Full Text PDFAn Experimental Study of the Flexural Bearing Capacity of Reinforced Concrete Beams Damaged by Explosions Using Piezoelectric Smart Aggregates.
Sensors (Basel)
December 2024
School of Safety Science and Emergency Management, Wuhan University of Technology, Wuhan 430064, China.
Two identically sized RC beams were fabricated to investigate the effects of explosive loads on the flexural behaviour of Reinforced Concrete (RC) beams. One of the beams was subjected to an explosive load to induce post-explosion damage, and subsequently, both beams underwent flexural capacity testing. Integrating piezoelectric smart aggregates (SAas) within the beams facilitated continuous observation of the damage conditions, allowing for the assessment of internal concrete deterioration from explosive impacts to bending failures.
View Article and Find Full Text PDFEnhancing Efficiency in Trustless Cryptography: An Optimized SM9-Based Distributed Key Generation Scheme.
Sensors (Basel)
December 2024
Information Security Department, Naval University of Engineering, Wuhan 430033, China.
Intelligent systems are those in which behavior is determined by environmental inputs, and actions are taken to maximize the probability of achieving specific goals. Intelligent systems are widely applied across various fields, particularly in distributed intelligent systems. At the same time, due to the extensive interaction with user data, intelligent systems face significant challenges regarding security.
View Article and Find Full Text PDFDamage and Failure Monitoring of Aerospace Insulation Layers Based on Embedded Fiber Bragg Grating Sensors.
Polymers (Basel)
December 2024
Research Institute of Aero-Engine, Beijing University of Aeronautics and Astronautics, Beijing 102206, China.
Carbon fiber-reinforced polymer (CFRP) composites are widely used in aviation thermal insulation layers due to their high strength-to-weight ratio and excellent high-temperature performance. However, challenges remain regarding their structural integrity and durability under extreme conditions. This study first employed finite element simulation to model the damage evolution of CFRP laminated plates under axial tensile loads and their thermal decomposition behavior in high-temperature environments, providing a theoretical reference.
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