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Intelligent milling tool wear estimation based on machine learning algorithms
This study introduces an innovative approach to estimate tool wear in milling operations across diverse operational settings, employing a...
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Differentiable visual computing for inverse problems and machine learning
Modern 3D computer graphics technologies are able to reproduce the dynamics and appearance of real-world environments and phenomena, building on...
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Analysis and codesign of electronic–photonic integrated circuit hardware accelerator for machine learning application
Innovations in deep learning technology have recently focused on photonics as a computing medium. Integrating an electronic and photonic approach is...
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Machine Learning Optimization Techniques: A Survey, Classification, Challenges, and Future Research Issues
Optimization approaches in machine learning (ML) are essential for training models to obtain high performance across numerous domains. The article...
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Towards an efficient machine learning model for financial time series forecasting
Financial time series forecasting is a challenging problem owing to the high degree of randomness and absence of residuals in time series data....
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Deep learning-based impact locating using the power spectrum of an acceleration signal on a cantilever beam
This study proposes a deep neural network-based impact locating method on a cantilever beam. The power spectrum of a measured acceleration signal,...
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Machine learning-based model for prediction of optimum TMD parameters in time-domain history
In this study intended for optimum design of tuned mass dampers (TMDs), which is one of the passive control systems, used with the aim of protection,...
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A machine learning approach for health monitoring of a steel frame structure using statistical features of vibration data
The main aim of this study is to present a connection damage identification technique in a plane frame structure using statistical features of...
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Development of seismic fragility curves for RC/MR frames using machine learning methods
Reduction of earthquakes fatality requires a study on seismic risk estimation in various sites. Deriving seismic fragility curves of structures make...
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A machine learning-based data augmentation strategy for structural damage classification in civil infrastructure system
With the explosive growth of available data collected from various sensors and increasingly powerful computing resources, recent advanced in machine...
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Enhancing 3D Reconstruction Accuracy of FIB Tomography Data Using Multi-voltage Images and Multimodal Machine Learning
FIB-SEM tomography is a powerful technique that integrates a focused ion beam (FIB) and a scanning electron microscope (SEM) to capture...
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Machine Learning-Based Detection of API Security Attacks
The Application Programming Interface provides multiple functionalities in the software development task. Collaboration from third-party developers...
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Implementation of Supervised Machine Learning Algorithms for Gait Alteration Classification of the Human Foot
It is very challenging for amputees to walk and adapt to uneven surfaces. It is essential to classify different gait surfaces so that intelligent...
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Machine Learning
This chapter presents the principles of machine learning (ML) as the support for shallow and especially deep learning procedures’ software...
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Machine learning-based digital twin of a conveyor belt for predictive maintenance
The problem of achieving a good maintenance plan is well-known in the modern industry. One of the most promising approaches is predictive...
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Development and comparison of machine-learning algorithms for anomaly detection in 3D printing using vibration data
3D printing is an emerging technology that converts digital models directly into physical objects. However, abnormal vibrations during the 3D...
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Machine learning for physical motion identification using EEG signals: a comparative study of classifiers and hyperparameter tuning
This study addresses the crucial task of accurately classifying brainwave signals associated with distinct brain states, utilizing five supervised...
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Physics Informed Machine Learning (PIML) for Design, Management and Resilience-Development of Urban Infrastructures: A Review
Building resilient and sustainable urban infrastructures is imperative to prepare future generations against new pandemics and climate change...
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Human Activity Recognition Using Supervised Machine Learning Classifiers
One of the machine learning algorithms’ most popular implementations nowadays is activity recognition. It is used, among other things, in biomedical...
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Assessment of HEMM Operators’ Risk Exposure due to Whole-Body Vibration in Underground Metalliferous Mines Using Machine Learning Techniques
Whole-body vibration ( WBV) is a substantial occupational health and safety hazard to heavy earth-moving machinery (HEMM) operators. There is a need...
