Optical Coherence Tomography Angiography in Retinal Vascular Diseases and Choroidal Neovascularization by Rodolfo Mastropasqua, Luca Di Antonio, Silvio Di Staso, Luca Agnifili, Angela Di Gregorio, Marco Ciancaglini, Leonardo Mastropasqua

“…Split spectrum amplitude decorrelation angiography algorithm was used to identify the blood flow within the tissue. …”
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Continuous Sign Language Recognition With Multi-Scale Spatial-Temporal Feature Enhancement by Zhen Wang, Dongyuan Li, Renhe Jiang, Manabu Okumura

“…Firstly, for better continuous frame information exploration, based on the optimal transport algorithm, we first propose a spatial resonance module, which is used to extract the global common spatial features of two adjacent frames along the frame sequence. …”
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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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Trust Region Policy Learning for Adaptive Drug Infusion with Communication Networks in Hypertensive Patients by Mai The Vu, Seong Han Kim, Ha Le Nhu Ngoc Thanh, Majid Roohi, Tuan Hai Nguyen

“…Secondly, a model-free deep reinforcement learning (MF-DRL) algorithm is integrated into the NBC to adjust dynamically the coefficients of the controller. …”
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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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Automatic Recognition Method of Letter Images in English Self-Learning Based on Partial Differential Equation Method by Yu Zhao, Shuping Du, Ran Li, Hong Yue

“…The proposed model can avoid manual initial curve selection and allow stopping conditions to be set in the algorithm. In addition, in the numerical solution of partial differential equations, the existing model uses upwind difference scheme, and the semi-implicit additive operator separation method is adopted in this paper. …”
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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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Re-conceptualizing trafficking-in-persons victimization using latent class analysis: Results from a community study in Cape Town, South Africa by Annah K. Bender, Erica L. Koegler, Edna G. Rich, Nicolette V. Roman, Rumi Kato Price

“…An interdisciplinary, international research team thus launched a study to estimate the prevalence of human trafficking using a computational algorithm in the Western Cape of South Africa. In this paper, we use latent class analysis to identify and empirically categorize 652 individuals at risk for human trafficking based on their response to two sets of indicators for human trafficking experiences. …”
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Adaptive deep feature representation learning for cross-subject EEG decoding by Shuang Liang, Linzhe Li, Wei Zu, Wei Feng, Wenlong Hang

“…Conclusions: The promising results highlight the effectiveness of the ADFR algorithm for EEG decoding and show its potential for practical applications.…”
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Water quality prediction and carbon reduction mechanisms in wastewater treatment in Northwest cities using Random Forest Regression model by Jingjing Sun, Xin Guan, Xiaojun Sun, Xiaojing Cao, Yepei Tan, Jiarong Liao

“…The work first establishes a Random Forest Regression (RFR) model. The RFR algorithm integrates Bagging ensemble learning and random subspace theory to construct multiple decision trees and aggregate their predictions, thereby enhancing the model’s prediction accuracy and stability. …”
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Smart estimation of protective antioxidant enzymes’ activity in savory (Satureja rechingeri L.) under drought stress and soil amendments by Amin Taheri-Garavand, Mojgan Beiranvandi, Abdolreza Ahmadi, Nikolaos Nikoloudakis

“…The current research was carried out to develop a genetic algorithm-based artificial neural network (ΑΝΝ) model able of simulating the levels of antioxidants in savory when using soil amendments [biochar (BC) and superabsorbent (SA)] under drought. …”
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Graph Convolution for Large-Scale Graph Node Classification Task Based on Spatial and Frequency Domain Fusion by Junwen Lu, Lingrui Zheng, Xianmei Hua, Yankun Wang

“…To address these issues, we propose a new GNN algorithm, LEGNN (Local and Global Enhanced Graph Neural Network), which introduces several key improvements over traditional GNN models such as GraphSAGE and GCN:Firstly, LEGNN combines a hybrid convolution method of spatial and spectral convolutions, enabling it to simultaneously capture local neighborhood relationships and global topological structures. …”
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