EMD-GM-ARMA Model for Mining Safety Production Situation Prediction by Menglong Wu, Yicheng Ye, Nanyan Hu, Qihu Wang, Huimin Jiang, Wen Li

“…First of all, according to the nonstationary characteristics of the mining safety accident time series, nonstationary original time series were decomposed into high- and low-frequency signals using the EMD algorithm, which represents the overall trend and random disturbances, respectively. …”
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Equiaxed growth of interacting Al–Cu dendrites in thin samples: a phase-field study at copper concentrations relevant for practical applications by Gong, Tong Zhao, Boukellal, Ahmed Kaci, Chen, Yun, Debierre, Jean-Marc

“…The use of a parallel adaptive finite element algorithm introduced recently [Gong et al., Comput. …”
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Image Quality Assessment Based on Multi-Scale Representation and Shifting Transformer by Geng Fu, Ziyu Wang, Cuijuan Zhang, Zerong Qi, Mingzheng Hu, Shujun Fu, Yunfeng Zhang

“…Image Quality Assessment (IQA) is a crucial metric for intelligent control systems and computer vision tasks, such as surveillance, restoration, and fingerprint identification, significantly advancing algorithm development in these areas. Recently, transformer-based algorithms have excelled in computer vision, particularly in image classification, surpassing convolutional neural network (CNN) methods. …”
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An Automatic Recognition Method of Microseismic Signals Based on S Transformation and Improved Gaussian Mixture Model by Kaikai Wang, Chun’an Tang, Ke Ma, Xintang Wang, Qiang Li

“…S transform (ST) and Manifold Learning (ML) methods are introduced to extract the characteristics of the microseismic signals, and Gaussian Mixture Model based on the improved Bee Colony optimization algorithm (IBC-GMM) is established to identify the microseismic signals accurately. …”
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A Reinforcement Learning Model for Optimal Treatment Strategies in Intensive Care: Assessment of the Role of Cardiorespiratory Features by Cristian Drudi, Maximiliano Mollura, Li-wei H. Lehman, Riccardo Barbieri

“…A Markov Decision Process (MDP) was built on the extracted discrete time-series. A policy iteration algorithm was used to obtain the optimal AI policy for the MDP. …”
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Nu—A Marine Life Monitoring and Exploration Submarine System by Ali A. M. R. Behiry, Tarek Dafar, Ahmed E. M. Hassan, Faisal Hassan, Abdullah AlGohary, Mounib Khanafer

“…Nu’s functionality was evaluated in a controlled 2.5-m-deep body of water, focusing on connectivity, maneuverability, and fish identification accuracy. The fish detection algorithm achieved an average precision of 60% in identifying fish presence, while the classification model achieved 97% precision in assigning species labels, with unknown species flagged correctly. …”
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Astronomaly Protege: Discovery through Human-machine Collaboration by Michelle Lochner, Lawrence Rudnick

“…We train PROTEGE on images from the MeerKAT Galaxy Cluster Legacy Survey, leveraging the self-supervised deep learning algorithm Bootstrap Your Own Latent to find a low-dimensional representation of the radio galaxy cutouts. …”
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Measures of Counteracting Domestic Violence Committed by Children: Problematic Aspects by A. S. Bakhaieva

“…The author has analyzed the algorithm of actions, according to which the police now act in case of detection of facts of domestic violence by a child under the age of sixteen. …”
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Development of an interpretable machine learning model based on CT radiomics for the prediction of post acute pancreatitis diabetes mellitus by Xiyao Wan, Yuan Wang, Ziyi Liu, Ziyan Liu, Shuting Zhong, Xiaohua Huang

“…The radiomics model was developed based on the optimal features retained after dimensionality reduction, utilizing the extreme gradient boosting (XGBoost) algorithm. Five-fold cross-validation of the model was used to assess the performance of the model in the training and testing cohorts. …”
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Optimization of Fused Deposition Modeling Parameters for Mechanical Properties of Polylactic Acid Parts Based on Kriging and Cuckoo Search by Yuan Yang, Yiyang Wang, Bowen Xue, Changxu Wang, Bo Yang

“…In response to the problems of poor mechanical properties and difficulty in selecting process parameters for fused deposition modeling (FDM), this paper analyzed the principle of FDM and proposed a parameter optimization method based on a Kriging and Cuckoo Search (CS) algorithm aimed at improving the mechanical properties of 3D printed polylactic acid (PLA) parts. …”
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Fault Diagnosis of Variable Load Bearing Based on Quantum Chaotic Fruit Fly VMD and Variational RVM by Bo Xu, Huipeng Li, Fengxing Zhou, Baokang Yan, Yi Liu, Yajie Ma

“…In order to accurately and effectively diagnose the failure types and damage degree of bearings under variable load conditions, an intelligent diagnostic model based on the variational mode decomposition (VMD) of quantum chaotic fruit fly optimization algorithm (QCFOA) and a multiclassification variational relevance vector machine (VRVM) is proposed. …”
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Dynamic Calibration Method of Multichannel Amplitude and Phase Consistency in Meteor Radar by Yujian Jin, Xiaolong Chen, Songtao Huang, Zhuo Chen, Jing Li, Wenhui Hao

“…In our dynamic calibration, initial coefficients are determined using a sliding correlation algorithm to assign preliminary weights, which are then refined through the proposed method. …”
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Comprehensive benefits evaluation of low impact development using scenario analysis and fuzzy decision approach by Ting Ni, Xiaohong Zhang, Peng Leng, Mark Pelling, Jiuping Xu

“…The framework’s novelty lies in the integration of the hesitant fuzzy weighted average algorithm to handle subjective uncertainties in expert judgment and the incorporation of multi-return period scenarios to enhance the robustness of the evaluation. …”
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Smoothing Photovoltaic Power Fluctuations for Cascade Hydro-PV-Pumped Storage Generation System Based on a Fuzzy CEEMDAN by Lei Chen, Jun Wang, Zhang Sun, Tao Huang, Fan Wu

“…To prevent smoothing insufficient and excessive, the fuzzy CEEMDAN algorithm is used to obtain the target power of the photovoltaic-pumped storage (PV-PS) generation system and the control signal of cascade hydro stations (CHSs) for eliminating large amplitude fluctuations of the PV output. …”
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Characterization and Machine Learning-Driven Property Prediction of a Novel Hybrid Hydrogel Bioink Considering Extrusion-Based 3D Bioprinting by Rokeya Sarah, Kory Schimmelpfennig, Riley Rohauer, Christopher L. Lewis, Shah M. Limon, Ahasan Habib

“…To address this gap, our research presents predictive models using machine learning (ML) algorithms, including polynomial fit (PF), decision tree (DT), and random forest (RF), to estimate bioink viscosity based on component weights and shear rate. …”
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Hybridize Machine Learning Methods and Optimization Techniques to Analyze and Repair Welding Defects via Digital Twin of Jidoka Simulator by Ahmed M. Abed, Tamer S. Gaafar

“…We are creating a “digital Jidoka twin system” (SQ(R/I/E)) with a controller segment programmed with machine learning (ML) algorithms that use the MFEM’s huge and uneven data to sort defects and their causes. …”
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Enhancing Particulate Matter Estimation in Livestock-Farming Areas with a Spatiotemporal Deep Learning Model by Dohyeong Kim, Heeseok Kim, Minseon Hwang, Yongchan Lee, Choongki Min, Sungwon Yoon, Sungchul Seo

“…Using a 200 m × 200 m prediction grid, forecasts were generated for both 1 h and 24 h intervals using the Graz Lagrangian model (GRAL) and a one-dimensional convolutional neural network combined with the long short-term memory algorithm (1DCNN-LSTM). Results highlight the potential of the deep learning model to enhance PM prediction, indicating its promise as an effective alternative or supplement to conventional air dispersion models, particularly in data-scarce areas such as those surrounding livestock farms. …”
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Uncertainty quantification of CT regularized reconstruction within the Bayesian framework by Negin Khoeiniha, Patricio Guerrero, Wim Dewulf

“…To achieve these goals, we apply a rapid regularized Markov Chain Monte Carlo (MCMC) reconstruction method [4, 5], employing the Metropolis-Adjusted Langevin Algorithm (MALA) [6] and its Lipschitz-adaptive variant (LipMALA) [7]. …”
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Developments on a 22 GHz microwave radiometer and reprocessing of 13-year time series for water vapour studies by A. Bell, A. Bell, E. Sauvageat, E. Sauvageat, E. Sauvageat, G. Stober, G. Stober, K. Hocke, K. Hocke, A. Murk, A. Murk

“…This has comprised of a new calibration which has been integrated into the framework for the calibration of other University of Bern radiometers and a new retrieval algorithm. The installation of a new spectrometer on the instrument has also allowed the comparison and correction of past observations. …”
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Using Adipose Measures from Health Care Provider-Based Imaging Data for Discovery by Elliot D. K. Cha, Yogasudha Veturi, Chirag Agarwal, Aalpen Patel, Mohammad R. Arbabshirani, Sarah A. Pendergrass

“…Using a “greedy snake” algorithm and 2,545 CT images from the Geisinger PACS, we measured levels of VAT, SAT, total adipose tissue (TAT), and adipose ratio volumes. …”
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