Dynamic Tracking of Lung Deformation during Breathing by Using Particle Method by Subas Chhatkuli, Seiichi Koshizuka, Mitsuru Uesaka

“…Comparing with the experimental data, the lung surface displacement during inspiration process was predicted reasonably well. Comparison of numerical prediction with experimental observations showed that the root mean squared error was about 2 mm at lower lobe and less than 1 mm at upper lobe at lung surface.…”
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Research on Temporal and Spatial Distribution Characteristics of Microseismic Events of Slip-Type Rockburst by Kun Xu, Leibo Song, Wenjie Song, Jiangtao He, Liping Li, Ge Yan, Qin Chen, Gang Wang

“…The research results can provide reference for rockburst prediction and prevention in similar deep rock engineering.…”
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Embodied neuromorphic synergy for lighting-robust machine vision to see in extreme bright by Shijie Lin, Guangze Zheng, Ziwei Wang, Ruihua Han, Wanli Xing, Zeqing Zhang, Yifan Peng, Jia Pan

“…This approach enables accurate connections between events and frames in the physics space for swift irradiance prediction, ultimately facilitating rapid control parameter updates. …”
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PLncWX: A Machine-Learning Algorithm for Plant lncRNA Identification Based on WOA-XGBoost by Fei Guo, Zhixiang Yin, Kai Zhou, Jiasi Li

“…Meanwhile, the number of elements in the feature subset was reduced to 23, which effectively improved the prediction accuracy and modeling efficiency.…”
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Exploring Contingency Skill Scores Based on Event Sizes by S. W. Kahler, H. Darsey

“…The scheme is applied to three different input options of a recently published evaluation of the Proton Prediction System (PPS) for SEP events to show differences between numbers‐based and intensity‐based skill scores of the PPS. …”
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Flood Forecasting Simulation in Karst Areas——A Case Study of Jinbao River Basin in Yangshuo by YUAN Meng, HU Haiying, TIAN Tian, ZHU Dantong, CHENG Xiangju

“…The runoff depth errors of the simulated floods in Jinbao River are all less than 20%, the peak time errors are all less than 1 h, and the overall qualification rate is 88.89%, with an average Nash efficiency coefficient of 0.85, which achieves the accuracy of Class B forecasting, and the flood prediction of the Yulong River is also up to the Class B accuracy, which indicates that the constructed model has good applicability to the simulation of runoff in the Jinbao River and other small watersheds in the karst mountainous areas. …”
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Fuzzy Neural Network Applications in Biomass Gasification and Pyrolysis for Biofuel Production: A Review by Vladimir Bukhtoyarov, Vadim Tynchenko, Kirill Bashmur, Oleg Kolenchukov, Vladislav Kukartsev, Ivan Malashin

“…This review not only highlights the ability of FNNs to optimize and predict the performance of gasification and pyrolysis processes but also identifies their role in advancing decision-making frameworks. …”
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Avoiding the Inherent Limitations in Datasets Used for Measuring Aesthetics When Using a Machine Learning Approach by Adrian Carballal, Carlos Fernandez-Lozano, Nereida Rodriguez-Fernandez, Luz Castro, Antonino Santos

“…This paper focuses on the analysis of several datasets used for aesthetic prediction based on ratings from photography websites and psychological experiments. …”
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Mathematical analysis of a model for glucose regulation by Kimberly Fessel, Jeffrey B. Gaither, Julie K. Bower, Trudy Gaillard, Kwame Osei, Grzegorz A. Rempała

“…Additionally, we also present an application of our method to prediction of the time to baseline recovery and calculation of insulin sensitivity and glucose effectiveness, two quantities regarded as significant in diabetes diagnostics.…”
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Unsupervised Domain Adaptation Using Exemplar-SVMs with Adaptation Regularization by Yiwei He, Yingjie Tian, Jingjing Tang, Yue Ma

“…First, we formulate the DAESVMs training classifiers with reducing Maximum Mean Discrepancy (MMD) among domains by mapping data into a latent space and preserving properties of original data, and then, we integrate classifiers to make a prediction for target domain instances. Our experiments were conducted on Office and Caltech10 datasets and verify the effectiveness of the model we proposed.…”
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Deep learning-based strategies for evaluating and enhancing university teaching quality by Ying Gao

“…Experimental results demonstrate that the CNN model achieves prediction accuracies of 92% for “Excellent,” 88% for “Good,” 85% for “Average,” and 80% for “Poor” in the test set. …”
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The Time-Series Production Simulation in Cost Management of New Energy Grid Connection Under the Internet of Things by Shurui Wang

“…The introduced Wasserstein distance improvement method positively enhances the model’s prediction accuracy, with a decrease of 208.4 in Mean Squared Error, a reduction of 145.6 in Root Mean Squared Error, and a decrease of 7.14 in Mean Absolute Error. …”
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A multi-feature dataset of coated end milling cutter tool wear whole life cycle by Na Li, Xiao Wang, Wanzhen Wang, Miaomiao Xin, Dongfeng Yuan, Mingqiang Zhang

“…It is a valuable resource for time series prediction, anomaly detection, and tool wear studies. …”
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Exploration and Analysis of Collaborative Matching Algorithm Empowering Large Data Fiscal Budget by Rui Gong, Xu Zhang

“…Combined with the matching algorithm and linear regression prediction algorithm in data analysis, the financial data is analyzed in depth. …”
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Identification of Behavioral Features of Bridge Structure Based on Static Image Sequences by Guojun Deng, Zhixiang Zhou, Xi Chu, Shuai Shao

“…The research results show that the output data of our NRS method were basically consistent with the finite-element prediction (maximum error: 11.11%) and dial gauge measurement (maximum error: 12.12%); the NRS method is highly sensitive to the actual deformation of the bridge structure under different damage conditions and can capture the deformation in a continuous and accurate manner. …”
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Influence of Fuel Moisture Content and Reactor Temperature on the Calorific Value of Syngas Resulted from Gasification of Oil Palm Fronds by Samson Mekbib Atnaw, Shaharin Anwar Sulaiman, Suzana Yusup

“…Comparison of simulation results for predicting calorific value of syngas with the experimental results showed a satisfactory agreement with a mean error of 0.1 MJ/Nm3. …”
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Introducing a Novel Clustering Method for Distribution Networks to Enhance Network Performance and Ensure Load Supply in the Event of Contingencies: A Fuzzy Function-Based Approa... by Mohamad Reza Mohamadi, Mohammad Sadegh Ghazizadeh, Mohamad Abedini

“…Furthermore, the eigenvalues and eigenvectors of the Graph Laplacian matrix of the distribution network are used to identify the maximum number of cells in the distribution network and the boundary among the generated cells, considering the prediction of distributed generation and consumption load based on fuzzy modeling. …”
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Hydraulic Fracturing Mechanism of Rock Mass under Stress-Damage-Seepage Coupling Effect by Zhengzheng Cao, Yue Wang, Haixiao Lin, Qiang Sun, Xiaogang Wu, Xiaoshuai Yang

“…By analyzing the size and direction of horizontal in situ stress, the shape and extension direction of cracks are judged, which provides an important theoretical basis for water inrush prediction and engineering protection.…”
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Generating a Spatiotemporal Dynamic Map for Traffic Analysis Using Macroscopic Fundamental Diagram by Yudi Li, Lei Zhu, Jian Sun, Ye Tian

“…Transportation simulation and analysis projects that utilize maps with inappropriate fidelity levels carry a significant risk of having poor runtime or poor prediction performance. To address this, researchers use map abstraction method to abstract out a simplified map with fewer links and nodes based on the original full detailed map. …”
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The Reduced-Order Model for Droplet Drift of Aerial Spraying under Random Lateral Wind by Wencheng Li, Wenyun Wang, Xiaomao Huang, Chenyang Li

“…Numerical simulations show that the droplet drift distance can be predicted by measurable lateral wind speed via the reduced-order model approach, which agreed well with the results obtained via the CFD method. …”
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