Data-driven seismic mechanical performance evaluation of RC columns based on adaptive optimization ensemble learning method integrating random forest and back propagation neural ne... by Ayong Jiao, Ziqing Jiao, Bin Gao

“…The research results provide a new idea for the efficient evaluation of the seismic performance of RC columns and expand the application potential of ensemble learning in the performance prediction of complex structures.…”
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Simulation and experimental verification of the precision finishing method for optical free-form surface segmentation. by Chenhua Jiang, Enzhong Zhang, Wei Zhang, Jiaqi Hu, Jiechen Guo, Xiaodong Li

“…Finally, experiments revealed a 12.28% reduction in machining path length and a 12.56% reduction in machining time using the segmentation machining method. …”
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State of Health Estimation of Lithium-Ion Batteries Using Fusion Health Indicator by PSO-ELM Model by Jun Chen, Yan Liu, Jun Yong, Cheng Yang, Liqin Yan, Yanping Zheng

“…This optimization enhances the ELM’s performance, addressing instability issues in the standard algorithm. The proposed PSO-ELM model demonstrates superior accuracy in SOH prediction compared with ELM and other methods. …”
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Grade Identification of Raw Nongxiangxing Baijiu Based on Fused Data of Near Infrared Spectroscopy and Gas Chromatography-Mass Spectrometry by ZHANG Wei, ZHANG Guiyu, TUO Xianguo, FU Ni, LI Xiaoping, PANG Tingting, LIU Kecai

“…The results showed that the prediction accuracy of the model based on the spectral feature variables selected by CARS was 89.66%, the prediction accuracy of the model based on KC after feature selection was 94.83%, and the classification accuracy of the model based on the fused data of CARS + KC reached as high as 98.28%. …”
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Auxiliary Diagnosis of Breast Cancer Based on Machine Learning and Hybrid Strategy by Hua Chen, Kehui Mei, Yuan Zhou, Nan Wang, Guangxing Cai

“…Finally, five different machine learning models are used for classification prediction, the best combination of parameters for each model is found using a grid search method, and the final results of each model are derived using a 10-fold cross-validation method. …”
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Collaborative Planning for Distribution Network and PV-ESS in the Marketization Environment by Ping RAO, Yue XIANG, Haotian YAO, Youbo LIU, Junyong LIU

“…Firstly, the benefit coupling model for the subjects in the planning layer was constructed considering photovoltaic prediction errors and agency costs based on the agency transaction mode. …”
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Knowledge Distillation in Object Detection for Resource-Constrained Edge Computing by Arief Setyanto, Theopilus Bayu Sasongko, Muhammad Ainul Fikri, Dhani Ariatmanto, I. Made Artha Agastya, Rakandhiya Daanii Rachmanto, Affan Ardana, In Kee Kim

“…YOLOv4 is a widely used OD model with a backbone for image feature extraction and a prediction layer. Originally, YOLOv4 was designed to use CSPDarkNet53 as its backbone, which requires significant computational power. …”
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SIGMAR1 screened by a GPCR-related classifier regulates endoplasmic reticulum stress in bladder cancer by Jingming Zhuang, Yang Wang, Xinyong Wu, Zijing Peng, Zhengnan Huang, Chao Zhao, Bing Shen

“…Conclusion The construction of a BC-related GPCR-TME classifier enabled the effective prediction of the OS of BC patients and the identification of SIGMAR1, a key factor regulating ER stress in BC. …”
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Preliminary Research on Intelligent Baking Room Dehydration and Drying Technology for Rice Sterile Seeds by Man Luo

“…An adaptive integral sliding mode control algorithm based on Smith prediction was proposed for intelligent baking room temperature. …”
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Bayesian Adaptive Lasso for the Partial Functional Linear Spatial Autoregressive Model by Dengke Xu, Ruiqin Tian, Ying Lu

“…This study introduces a partial functional linear spatial autoregressive model which can explore the relationship between a scalar spatially dependent response variable and predictive variables containing both multiple scalar covariates and a functional covariate. …”
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P85 | ALTERATION OF SUBMUCOSAL AND MYENTERIC GANGLIA IN SEVERE GUT DYSMOTILITY: A QUANTITATIVE MORPHOMETRIC ANALYSIS

“…This reduction remained consistent only in the AN and DEG subgroups. …”
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ANALYSIS OF GENERAL PLOW BODY TRACTIVE RESISTANCE by A. Yu. Izmaylov, A. A. Artyushin, N. E. Evtyushenkov, G. S. Bisenov, V. F. Rozhin, D. N. Kynev

“…Rational forms of the organization of operations enable reduction of standing time of combines, increase capacity of transportation vehicles and by that grain loss reduction owing to reduction reducing of harvest terms. …”
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Medical management after subthalamic stimulation in Parkinson’s disease: a phenotype perspective by Ana Paula BERTHOLO, Carina FRANÇA, Wilma Silva FIORINI, Egberto Reis Barbosa, Rubens Gisbert CURY

“…In a subset of patients with severe dyskinesia before surgery, an initial reduction in levodopa seems to be a more reasonable approach. …”
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Improving the Accuracy in Classification of Blood Pressure from Photoplethysmography Using Continuous Wavelet Transform and Deep Learning by Jiaze Wu, Hao Liang, Changsong Ding, Xindi Huang, Jianhua Huang, Qinghua Peng

“…We have established a new algorithm with high accuracy to predict BP classification from PPG via matching of CWT type and segment length, which is a promising solution for rapid prediction of BP classification from real-time processing of PPG signal on a wearable device.…”
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Ability of verbal autopsy data to detect deaths due to uncontrolled hyperglycaemia: testing existing methods and development and validation of a novel weighted score by Justine I Davies, David Beran, Miles D Witham, Alisha N Wade, Amelia Crampin, Sarah Blackstock, Graham D Ogle

“…Our WS produced a receiver operator curve with area under the curve of 0.952 (95% CI 0.920 to 0.985). However, positive predictive value (PPV) was below 50% when the WS was applied to the development set and the score was dominated by the necessity for a premortem diagnosis of diabetes. …”
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Computed Tomography‐Based Habitat Analysis for Prognostic Stratification in Colorectal Liver Metastases by Chaoqun Zhou, Hao Xin, Lihua Qian, Yong Zhang, Jing Wang, Junpeng Luo

“…Compared with CRS and TBS, the habitat model demonstrated superior predictive accuracy, particularly for DFS and liver‐specific DFS, with higher time‐dependent AUC values and improved model calibration (lower IBS). …”
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An integrated machine learning framework for developing and validating a prognostic risk model of gastric cancer based on endoplasmic reticulum stress-associated genes by Gang Wei, Yan Wang, Ru Liu, Lei Liu

“…This risk model proved to have a good predictive performance for estimating the overall survival of these patients. …”
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Detecting Changes in Soil Fertility Properties Using Multispectral UAV Images and Machine Learning in Central Peru by Lucia Enriquez, Kevin Ortega, Dennis Ccopi, Claudia Rios, Julio Urquizo, Solanch Patricio, Lidiana Alejandro, Manuel Oliva-Cruz, Elgar Barboza, Samuel Pizarro

“…A UAV-captured image was used to predict the spatial distribution of soil parameters, generating fourteen spectral indices and a digital surface model (DSM) from 103 soil plots across 49.83 hectares. …”
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Large language models for accurate disease detection in electronic health records: the examples of crystal arthropathies by Kim Lauper, Denis Mongin, Nils Bürgisser, Samia Mehouachi, Clement P. Buclin, Delphine S. Courvoisier, Etienne Chalot

“…The framework was further validated on 600 paragraphs assessing ‘Calcium Pyrophosphate Deposition Disease (CPPD)’.Results The LLM-based algorithm outperformed the regex method, achieving a 92.7% (88.7%–95.4%) positive predictive value, a 96.6% (94.6%–97.8%) negative predictive value and an accuracy of 95.4% (93.6%–96.7%) for gout. …”
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What are the implications of using individual and combined sources of routinely collected data to identify and characterise incident site-specific cancers? a concordance and valida... by Rachael Williams, Helen Strongman, Krishnan Bhaskaran

“…We calculated positive predictive values and sensitivities of each definition, compared with a gold standard algorithm that used information from all linked data sets to identify first cancers. …”
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