Automated classification of oral potentially malignant disorders and oral squamous cell carcinoma using a convolutional neural network framework: a cross-sectional studyResearch in... by Cristina Saldivia-Siracusa, Eduardo Santos Carlos de Souza, Arnaldo Vitor Barros da Silva, Anna Luíza Damaceno Araújo, Caíque Mariano Pedroso, Tarcília Aparecida da Silva, Maria Sissa Pereira Sant'Ana, Felipe Paiva Fonseca, Hélder Antônio Rebelo Pontes, Marcos G. Quiles, Marcio Ajudarte Lopes, Pablo Agustin Vargas, Syed Ali Khurram, Alexander T. Pearson, Mark W. Lingen, Luiz Paulo Kowalski, Keith D. Hunter, André Carlos Ponce de Leon Ferreira de Carvalho, Alan Roger Santos-Silva

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Continuous prediction of knee joint angle in lower limbs based on sEMG: a method combining an improved ZOA optimizer and attention-enhanced GRU by Jian Lv, Binhao Huang, Ligang Qiang

“…Experimental evaluations across three motion tasks—level walking, stair ascent, and stair descent—demonstrated that the proposed method achieved a minimum root mean square error (RMSE) of 1.31°, with over 50% reduction in feature dimensionality, significantly outperforming Genetic Algorithm (GA), Zebra Optimization Algorithm (ZOA), Liver Cancer Algorithm (LCA), and Pied Kingfisher Optimizer (PKO). …”
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Visceral obesity anthropometric indicators as predictors of acute pancreatitis severity by Kaier Gu, Wenxuan Shang, Dingzhou Wang

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Identifying network state-based Parkinson’s disease subtypes using clustering and support vector machine models by Benedictor Alexander Nguchu, Benedictor Alexander Nguchu, Yifei Han, Yanming Wang, Peter Shaw

“…IntroductionParkinson’s disease (PD) heterogeneity poses challenges to the current development of discovering the best therapeutic targets.MethodsHere, we employ K-means and hierarchical clustering algorithms on data from the Parkinson’s Progression Markers Initiative (PPMI) to identify network-specific patterns that describe PD subtypes using the optimal number of brain features. …”
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Crowding distance and IGD-driven grey wolf reinforcement learning approach for multi-objective agile earth observation satellite scheduling by He Wang, Weiquan Huang, Sindri Magnússon, Tony Lindgren, Chen Chen, Junyu Wu, Yanjie Song

“…The experimental results show that the algorithm excels at solving the MOAEOSSP, outperforming competing algorithms across several metrics and demonstrating its effectiveness for complex optimization problems.…”
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Construction and Application Analysis of an Intelligent Distribution Network Identification System Based on Deep Neural Networks by Yu Ma

“…Then, a DNN model was constructed for topological identification and enhances the model scalability through incremental and transfer learning mechanisms. In addition, the Cross-Validation Grid Search Algorithm (GSA) was used to optimize the hyperparameters to ensure that the model can achieve the optimal performance on different data sets. …”
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Three-Dimensional Point Cloud Displacement Analysis for Tunnel Deformation Detection Using Mobile Laser Scanning by Mahamadou Camara, Liying Wang, Ze You

“…A custom segmentation algorithm partitions the tunnel cross-section linings into individual shield rings, enabling detailed and time-resolved displacement tracking. …”
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Inversion of multiphase tectonic stress field and fracture evolution in shale gas reservoirs by WANG Jiawei, ZHANG Bohu, HU Yao, HE Zhengyi, HU Xinxin, CHEN Wei, LUO Chao

“…The research indicates that numerical simulation methods and neural network algorithms effectively invert the crustal stress field across multiple stages. …”
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Beyond the Current Curve: A Novel Curve Warning System Considering Subsequent Curve Speed Limits by N. S. Manikandan, Ganesan Kaliyaperumal

“…We evaluate the existing path-tracking algorithms across various speed scenarios (50, 70, and 80 km/h) and different speed considerations: curve-aware speed and our proposed adjacent curve-speed-limit-aware speed. …”
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Integrating infiltration processes in hybrid downscaling methods to estimate sub-surface soil moisture by Mo Zhang, Yong Ge, Jianghao Wang

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Bio-Inspired Metaheuristics in Deep Learning for Brain Tumor Segmentation: A Decade of Advances and Future Directions by Shoffan Saifullah, Rafał Dreżewski, Anton Yudhana, Wahyu Caesarendra, Nurul Huda

“…Through bibliometric mapping, methodological synthesis, and performance analysis, we highlight trends in algorithm usage, application domains (e.g., preprocessing, architecture search), and segmentation outcomes measured by metrics such as Dice Similarity Coefficient (DSC), Jaccard Index (JI), Hausdorff Distance (HD), and ASSD. …”
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Enhanced clustering techniques for lithofacies and electrofacies identification in post-salt carbonate and siliciclastic reservoirs: a case study from the campos basin, Brazil by Abel Carrasquilla, Herson Rocha

“…Subsequently, nine unsupervised classification techniques-including eight clustering algorithms (e.g., k-means, k-medoids, Gaussian mixture models, spectral clustering, k-nearest neighbors, subtractive fuzzy clustering, fuzzy c-means, and agglomerative hierarchical clustering) and one neural-based mapping method (competitive neural network) - were applied. …”
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The prediction of karst-collapse susceptibility levels based on the ISSA-ELM integrated model by Jiaxin Wang, Ying Yang, Xian Yang, Yulong Lu, Yang Liu, Da Hu, Yongjia Hu

“…The methodology incorporates two key innovations: first, it applies a Singer chaotic mapping technique to enhance the sparrow search algorithm (SSA), effectively mitigating local optima entrapment by increasing population diversity and enhancing global search capabilities. …”
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Riparian habitat quality and seasonality drives spatiotemporal habitat ecology of sympatric Asian otters in southern Western Ghats by Ankit Moun, Tharmalingam Ramesh, Tharmalingam Ramesh, Riddhika Kalle, Riddhika Kalle

“…In dynamic ecosystems, we have scant knowledge on the interactive role of season and local riparian habitat conditions in driving spatiotemporal habitat use of sympatric semi-aquatic mustelids.MethodologyWe conducted seasonal monitoring of 169-196 riverine segments (250 m) in 2020 and 2021 to measure the sign encounter rates of Asian small-clawed otter (SCL) and smooth-coated otter (SCO) and recorded 29 riparian habitat variables.ResultsOur self-organizing map algorithm characterized alarge multivariate habitat data into six habitat clusters representing a gradient of riparian habitat conditions. …”
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A Longitudinal Perspective on Digital Skills for Everyday Life: Measurement and Empirical Evidence by Kiran Kappeler

“…To address these gaps, this article compares self-reported measures of digital skills and knowledge of datafication and algorithmization in everyday internet use and maps the evolution of their relevance for digital everyday life. …”
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探討強化學習演算法之素材推薦機制與AI學習履歷之學習者感知 Learner Perceptions of AI-Powered Learning Portfolios and Personalized Material Recommendation Mechanisms in Reinforcement Learning Algorithms... by 曾建維 Jian-Wei Tzeng, 黃天麒 Tien-Chi Huang, 薛承祐 Cheng-Yu Hsueh, 廖英淞 Ying-Song Liao

“…The exponential growth of big data in recent years has positioned artificial intelligence as a focal point of inquiry across various fields. Machine learning has catalyzed substantial advancements in the field of data science. …”
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Short-Term Power Load Prediction of VMD-LSTM Based on ISSA Optimization by Shuai Wu, Huafeng Cai

“…The Improved Sparrow Search Algorithm (ISSA), which integrates piecewise chaotic mapping into population initialization to augment the global exploration capability, is employed to fine-tune LSTM hyperparameters, thereby enhancing the prediction precision. …”
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Enhancing gender equity in resume job matching via debiasing-assisted deep generative model and gender-weighted sampling by Swati Tyagi, Anuj, Wei Qian, Jiaheng Xie, Rick Andrews

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The Controlling Factors and Prediction of Deep-Water Mass Transport Deposits in the Pliocene Qiongdongnan Basin, South China Sea by Jiawang Ge, Xiaoming Zhao, Qi Fan, Weixin Pang, Chong Yue, Yueyao Chen

“…A random forest artificial intelligence algorithm was established. The mean value of the squared residuals of the model was 0.043, and the fitting degree was 82.52. …”
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Detection of out-of-seam and out-of-scope mining using double filtering method by Chong Wang, Pengzhi Cui, Guodong Song, Zhiming Xu, Jiajun Qin

“…This data is then analyzed using Simultaneous Localization and Mapping (SLAM) algorithms, and cross-validated against officially approved mine maps. …”
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