Results 201 to 210 of about 751,571 (292)

The impact of obstacle parameters on mid-high frequency noise propagation in comprehensive mining workfaces and safety implications. [PDF]

Sci Rep
Jia G, Yang M, Jiang D, Guo J, Liu M, Tao Y.   +5 more
europepmc   +1 more source

Mining time-series data using discriminative subsequences

, 2014
Time-series data is abundant, and must be analysed to extract usable knowledge. Local-shape-based methods offer improved performance for many problems, and a comprehensible method of understanding both data and models. For time-series classification, we transform the data into a local-shape space using a shapelet transform.
openaire   +1 more source

Machine Learning Driven Inverse Design of Broadband Acoustic Superscattering

Advanced Intelligent Discovery, EarlyView.
Multilayer acoustic superscatterers are designed using machine learning to achieve broadband superscattering and strong sound insulation. By incorporating a weighted mean absolute error into the loss function, the forward and inverse neural networks accurately map structural parameters to spectral responses.
Lijuan Fan, Xiangliang Zhang, Ying Wu
wiley   +1 more source

Gas concentration prediction based on SSA algorithm with CNN-BiLSTM-attention. [PDF]

Sci Rep
Xing W, Yang Y, Zhang Y, Yang Y.
europepmc   +1 more source

Crater Observing Bioinspired Rolling Articulator (COBRA)

Advanced Intelligent Systems, EarlyView.
Crater Observing Bio‐inspired Rolling Articulator (COBRA) is a modular, snake‐inspired robot that addresses the mobility challenges of extraterrestrial exploration sites such as Shackleton Crater. Incorporating snake‐like gaits and tumbling locomotion, COBRA navigates both uneven surfaces and steep crater walls.
Adarsh Salagame, Henry Noyes, Eric Sihite, Arash Kalantari, Alireza Ramezani   +4 more
wiley   +1 more source

Deep learning-based anomaly detection framework for hydraulic support systems in mining safety. [PDF]

Sci Rep
Xin W, Liu L, Wang J, Zheng X.
europepmc   +1 more source

Roadmap on Artificial Intelligence‐Augmented Additive Manufacturing

Advanced Intelligent Systems, EarlyView.
This Roadmap outlines the transformative role of artificial intelligence‐augmented additive manufacturing, highlighting advances in design, monitoring, and product development. By integrating tools such as generative design, computer vision, digital twins, and closed‐loop control, it presents pathways toward smart, scalable, and autonomous additive ...
Ali Zolfagharian, Liuchao Jin, Qi Ge, Wei‐Hsin Liao, Andrés Díaz Lantada, Francisco Franco Martínez, Tianyu Zhang, Tao Liu, Charlie C. L. Wang, Mohammad Hossein Mosallanejad, Reza Ghanavati, Abdollah Saboori, Alejandro De Blas De Miguel, William Solórzano‐Requejo, Yi Cai, Xiangyang Dong, Huangyi Qu, Najmeh Samadiani, Guangyan Huang, Austin Downey, Yanzhou Fu, Lang Yuan, Tsz‐Kwan (Glory) Lee, Arbind Agrahari Baniya, Eisha Waseem, Abdul Rahman Sani, Abbas Z. Kouzani, Yijia Wu, Markus P. Nemitz, Masoud Shirzad, Dageon Oh, Seung Yun Nam, Amedeo Franco Bonatti, Irene Chiesa, Gabriele Maria Fortunato, Giovanni Vozzi, Carmelo De Maria, Mahdi Bodaghi   +37 more
wiley   +1 more source

Mechanical properties of rock cutting by disc cutters and feasibility analysis of mechanical mining in Jinchuan No. 3 Mine with hard rock. [PDF]

Sci Rep
Zhao J, Huang D, Zhu D.
europepmc   +1 more source

Data‐Driven Insights into Rare Earth Mineralization: Machine Learning Applications Using Functional Material Synthesis Data

Advanced Intelligent Systems, EarlyView.
Hydrothermal synthesis records for rare‐earth compounds are repurposed to learn mineralization rules. An extreme gradient boosting model ingests precursors, additives, and engineered descriptors to predict product phases, crystallization temperature, and pH. Feature importance indicates dominant thermodynamic control with kinetic modulation, suggesting
Juejing Liu, Xiaoxu Li, Yifu Feng, Zheming Wang, Kevin M. Rosso, Xiaofeng Guo, Xin Zhang   +6 more
wiley   +1 more source