Deep Learning Based 3D Visualization Health Condition Monitoring Method for Anchor Digging Machines by YANG Xueqi, GAO Xinqin, ZHENG Haiyang, YANG Jun

“…This study integrates deep learning and 3D visualization technology, designs a comprehensive health monitoring system framework, and proposes a health monitoring method for anchor digging machines.MethodsBased on deep learning, a data-driven remaining useful life (RUL) prediction method was proposed for key components of anchor digging machines. …”
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Arctic tern-optimized weighted feature regression system for predicting bridge scour depth by Jui-Sheng Chou, Asmare Molla

“…Comparative analyses against single AI models, conventional ensemble models, hybrid techniques, and empirical methods demonstrate that ATO-WFLSSVR's reliability outperforms others in performance evaluation metrics. …”
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An Evaluation of the Precision of Ocular Trauma Score and Factors for Poor Visual Outcomes in Open Globe Injury: A Retrospective Analysis of Resourcelimited Hospital Settings by Takarn Oughtkaew, Siwatus Puangrab

“… Objective: To evaluate the accuracy and validity of ocular trauma scores (OTS) among patients with open globe injury (OGI) in rural hospital settings and to identify the determinants predicting poor visual outcomes. …”
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Evaluation and analysis of risk factors for fractured vertebral recompression post-percutaneous kyphoplasty: a retrospective cohort study based on logistic regression analysis by YingLun Zhao, Bo Li, Lu Qian, XueMing Chen, YanHui Wang, LiBin Cui, Yuan Xin, Liang Liu

“…Objective To identify independent risk factors for postoperative recompression and develop predictive models for risk assessment. Methods We retrospectively analyzed 284 OVCF patients treated with PKP, grouped by recompression status. …”
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A new method for multi-factor capacity review of underground gas storage under complex geological conditions by HU Jun, YANG Jiakun, XU Hongcheng, ZHOU Dongliang, XU Feng, SHI Yuxia, ZHANG Siyuan, SONG Lina, PEI Gen, FAN Jiayi

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Sound quality control method of 110 kV transformer based on distributed variable stiffness dynamic vibration absorber by Cai Zeng, Xing Du, Songbo Guo, Jian Han, Xiaoqiong He, Xinbiao Xiao

“…To measure the actual impact of transformer noise on humans more effectively, this paper proposes to introduce the sound quality evaluation method into the evaluation of transformer noise. …”
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Machine learning based method for forecasting short-term passenger flow in urban rail stations by HU Mingwei, SHI Xiaolong, WU Wenlin, HE Guoqing

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Evaluating Bias Correction Methods Using Annual Maximum Series Rainfall Data from Observed and Remotely Sensed Sources in Gauged and Ungauged Catchments in Uganda by Martin Okirya, JA Du Plessis

“…Four bias correction methods, Quantile Mapping (QM), Linear Transformation (LT), Delta Multiplicative (DM), and Polynomial Regression (PR), were evaluated using daily rainfall data from four gauged stations (Gulu, Soroti, Jinja, Mbarara). …”
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Quality of explanation in medical articles: A systematic review by Seyedeh Zahra Hashemi Nejad, Keyvan Salehi

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Evaluation of the structural models of the human reference proteome: AlphaFold2 versus ESMFold by Matteo Manfredi, Castrense Savojardo, Pier Luigi Martelli, Rita Casadio

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Explainable Ensemble Learning Model for Residual Strength Forecasting of Defective Pipelines by Hongbo Liu, Xiangzhao Meng

“…This approach resolves the issues of excessive iterations and high computational costs associated with conventional hyperparameter optimization methods, significantly enhancing the model’s predictive performance. …”
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A corrosion risk assessment method for underground gas storage ground pipeline based on data and knowledge dual drivers by BI Caixia

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CARBOXYHEMOGLOBIN LEVELS IN PRETERM NEONATAL LATE-ONSET SEPSIS: TO PREDICT OR NOT TO PREDICT by GONCA VARDAR, Eren Ozek

“… Abstract Background: To evaluate carboxyhemoglobin (COHb) levels in diagnosing late-onset sepsis (LOS) in preterm neonates. …”
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Methodology Based on BERT (Bidirectional Encoder Representations from Transformers) to Improve Solar Irradiance Prediction of Deep Learning Models Trained with Time Series of Spati... by Llinet Benavides-Cesar, Miguel-Ángel Manso-Callejo, Calimanut-Ionut Cira

“…Accurate solar resource forecasting is important because of the inherent variability associated with solar energy and its significant impact on the cost for energy producers. The traditional method applied in solar irradiance forecasting involves two main phases, related to (1) data selection and (2) model selection, training, and evaluation. …”
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Predictive features analysis and nomogram construction for predicting depression in elderly patients by Wei Lin, Zijun Zhao, Yingshan Yu, Hongbin Chen

“…The Comprehensive Geriatric Assessment (CGA), a multidimensional approach, evaluates medical, psychological, and functional capacities to identify highrisk individuals and may be correlated with depression in the elderly.MethodsFrom 2021 to 2023, a total of 219 geriatric patients were recruited. …”
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Predicting Burn Mortality Using a Simple Novel Prediction Model by Sneha Sharma, Raman Tandon

“…Background Prediction of outcome for burn patients allows appropriate allocation of resources and prognostication. …”
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A Probability-Based Framework for Evaluating Slope Failure Under Rainfall Using Coupled Finite Element Analysis by Nadarajah Ravichandran, Tharshikka Vickneswaran

“…Deterministic limit equilibrium methods are typically used to evaluate the stability of slopes in terms of Factor of Safety (FoS), considering the worst-case scenario. …”
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Predictive value of a self-administered frailty screening questionnaire for the effectiveness of functional rehabilitation evaluated with the locomotor functional independence meas... by Jan Chrusciel, Ramatoulaye Ndoye, Biné-Mariam Ndiongue, Marie-Anne Fournier, Fariba Kabirian, Manon Pondjikli, Valentine Dutheillet-de-Lamothe, Gilles Berrut, Yves Rolland, Stéphane Sanchez

“…Functional gain can be evaluated with classic scales, such as the locomotor subscale of the Functional Independence Measure. …”
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Federated Learning Enhanced MLP–LSTM Modeling in an Integrated Deep Learning Pipeline for Stock Market Prediction by Jayaraman Kumarappan, Elakkiya Rajasekar, Subramaniyaswamy Vairavasundaram, Ketan Kotecha, Ambarish Kulkarni

“…The proposed method is implemented in python. This suggests that using Federated Learning along with MLP and LSTM as the components of this vector enhanced the function increasing its capacity and reliability in predicting the trends of stocks. …”
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Design, Synthesis, and Biological Evaluation of New Analogs of Aurein 1.2 Containing Non-Proteinogenic Amino Acids by Nora Angelova, Ivan Iliev, Veronica Nemska, Tatyana Dzimbova, Nelly Georgieva, Dancho Danalev, Emilia Naydenova

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