SDP system architecture
In this work, the design and implementation of the SDP system architecture for mitigating BFA on RAS starts by identifying prominent RAS assets and their risk level. Then, understanding their operation anatomy through…
Category: 7. Maths
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A contrastive learning framework with dual gates and noise awareness for temporal knowledge graph reasoning
This section evaluates the performance of the DNCL model through extensive experiments conducted on four datasets. A detailed analysis of the experimental results is provided below.
Datasets
This paper performs comprehensive experiments on four…
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Development of a novel extension of Rayleigh distribution with application to COVID-19 data
Simulation study
In this section, we will conduct simulation study to understand the behavior and compare performance of all the estimating approaches discussed in “Estimation methods” section for estimating parameter of the DUS Rayleigh…
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Algorithms for reliable decision-making need causal reasoning
Corbett-Davies, S., Pierson, E., Feller, A., Goel, S. & Huq, A. Algorithmic decision making and the cost of fairness. In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 797–806 (Association for…
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Integrating machine learning and symbolic regression for predicting damage initiation in hybrid FRP bolted connections
Dataset generation using design of experiments
A hybrid dataset generation approach combining Central Composite Design (CCD) and Box-Behnken Design (BBD) was used to efficiently explore the design space. CCD effectively captures quadratic effects…
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Study on multi-parameter optimization of seismic isolation bearings for continuous girder bridges considering interactions among key parameters
Finite element model and seismic input
Engineering background
This study focuses on a four-span seismic isolation continuous girder bridge with a span of 4 × 36 m. The superstructure of the bridge consists of a prestressed concrete box girder…
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Bayesian network structure learning by opposition-based learning
Opposition-based learning
Opposition-based learning was proposed by Hamid R. Tizhoosh25, which is an effective scheme that can improve the convergence speedup of machine intelligence algorithms. The basic principle of opposition-based learning is…
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Smart intrusion detection model to identify unknown attacks for improved road safety and management
ACIDS is meticulously designed to address the critical challenges inherent in intrusion detection for IoV environments, including handling class imbalance, ensuring scalability and adapting to novel attack patterns. The model integrates advanced…
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Efficient field correction of low-cost particulate matter sensors using machine learning, mixed multiplicative/additive scaling and extended calibration inputs
Lelieveld, J. et al. Cardiovascular disease burden from ambient air pollution in Europe reassessed using novel hazard ratio functions. Eur. Heart J. 20, 1590–1596 (2019).
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Bringing evolutionary cancer therapy to the clinic: a systems approach
Gatenby, R. A., Silva, A. S., Gillies, R. J. & Frieden, B. R. Adaptive therapy. Cancer Res. 69, 4894–4903 (2009).
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Gatenby, R. A. A…
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