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

“…In the performance evaluation, quantitative measures like Root-Mean-Square Error (RMSE), and accuracy are seven used. …”
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CPO-VMD Combined With Multiscale Permutation Entropy for Noise Reduction in GNSS Vertical Time Series in Mining Areas by Xu Yang, Xinxin Yao, Xinjian Fang, Xuexiang Yu, Yi Wu, Shicheng Xie

“…Taken together, the CPO-VMD-MPE method proposed in this paper significantly reduces the noise in the time series and provides a better theoretical and methodological reference for deformation analysis and prediction.…”
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Noninvasive estimation of internal spinal alignment in patients with adolescent idiopathic scoliosis using PCdare and back shape asymmetry by Mirko Kaiser, Emily McLaughlin, Martin Bertsch, Christoph J. Laux, Mazda Farshad, Tobia Brusa, Volker M. Koch, William R. Taylor, Saša Ćuković

“…The correlations (IQR) between estimated shape of ISLs and their references were very strong (0.87 (0.24)) to excellent (0.94 (0.03)), and the median root mean square error (IQR) between estimated and reference ISL was 6.9 mm (3.3 mm). …”
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Adaptive Gap-Filling of Multispectral Images at Coarse and Fine Spatial Resolution by Seyedkarim Afsharipour, Li Jia, Massimo Menenti, Hamid Reza Ghafarian Malamiri

“…To evaluate the performance, experiments were conducted using MODIS (coarse-resolution) and Landsat/OLI (fine-resolution) images with artificial gaps (10% –90% ) introduced at varying positions in cloud-free reference images. For coarse-resolution images, the blue band showed the lowest root mean square error (RMSE) of 0.004 to 0.03, while the near-infrared (NIR) band had higher RMSE (0.01–0.05). …”
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A Novel Voronoi-Driven Optimization Approach for Point-Based Sensor Network Deployment by Saeid Doodman, Mir-Abolfazl Mostafavi, Raja Sengupta, Ali Afghantoloee

“…Its performance is evaluated using the root mean square error (RMSE), calculated via an interpolation process that reconstructs the field from sensor positions. …”
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A New Wavelet Transform and Merging Generative Adversarial Network (WTM-GAN) Model for TEC Spatial Inpainting by Kunlin Yang, Yang Liu, Yifei Chen, Zhizhao Liu, Kaiyan Jin, Yanbo Zhu

“…The performance is rigorously tested, achieving root-mean-square errors of 2.117 TECu and 0.908 TECu during both high and low solar activity years, respectively, and it obtains improvement of 0.945 TECu and 0.739 TECu over the comparison models. …”
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Detection of soluble solid content in table grapes during storage based on visible-near-infrared spectroscopy by Yuan Su, Ke He, Wenzheng Liu, Jin Li, Keying Hou, Shengyun Lv, Xiaowei He

“…These results suggest that the application of Vis-NIR spectroscopy technology could effectively detect the SSC in grapes during storage, and it can provide a valuable reference for the rapid assessment of the table grape quality.…”
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Hysteresis feedforward and fuzzy PID feedback compound control of piezoelectric ceramics by Qian Lu, Mengmeng Bai, Dongming Lv, Chao Ma, Bowen Zhao, Chengyang Wang

“…The simulation results show when the input signal frequency is 1 Hz, 15 Hz, 30 Hz and 50 Hz, the root mean square of feedforward combined with fuzzy PID feedback control is reduced by 0.0168 um, 0.0168 um, 0.0413 um, 0.0738 um, and 0.0016 um, 0.003 um, 0.0036 um, 0.0071 um respectively compared with single feedforward control and feedforward combined with PID compound control. …”
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Contamination Status and Health Risk Assessment of 73 Mycotoxins in Four Edible and Medicinal Plants Using an Optimized QuEChERS Pretreatment Coupled with LC-MS/MS by Xiaojing Huang, Rui Feng, Qing Hu, Xiuhong Mao, Heng Zhou

“…This study provides valuable reference for monitoring mycotoxin contamination in similar plants.…”
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Effects of Different Conditions of Water Cooling at High Temperature on the Tensile Strength and Split Surface Roughness Characteristics of Hot Dry Rock by Hanbo Cui, Jupeng Tang, Xintong Jiang

“…This study is expected to provide a reference for the selection of different conditions of water cooling at high temperature for thermal recovery in the Songliao Basin.…”
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Online Trajectory Regeneration for Multirotors via a Proportional-Derivative Physics-Informed Neural Network by Mana Ghanifar, Amir Ali Nikkhah, Milad Kamzan, Mohammad Teshnehlab, Morteza Tayefi

“…Results show that PD-PINN reduces the total three-dimensional root mean square error from 0.7178 meters to 0.1352 meters, an 81.2% improvement over classical methods. …”
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Prediction of transcript isoforms and identification of tissue-specific genes in cucumber by Wenjiao Wang, Chengcheng Shen, Xinqiang Wen, Anqi Li, Qi Gao, Zhaoying Xu, Yuping Wei, Yushun Li, Dailu Guan, Bin Liu

“…Among that, 1,655 annotated genes and 4,214 predicted transcripts were considered as tissue-specific. The root exhibited the highest number of tissue-specific transcripts, followed by shoot apex. …”
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Automatic Robotic Ultrasound for 3D Musculoskeletal Reconstruction: A Comprehensive Framework by Dezhi Sun, Alessandro Cappellari, Bangyu Lan, Momen Abayazid, Stefano Stramigioli, Kenan Niu

“…A custom musculoskeletal phantom was used for validation. Compared to the reference 3D reconstruction result derived from the MRI scan, ARUS achieved a 3D reconstruction root mean square error (RMSE) of 1.22 mm, with a mean error of 0.94 mm and a standard deviation of 0.77 mm. …”
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Towards enhancing field‐based vegetation monitoring: A deep learning approach for species coverage estimation from ground‐level imagery by Pauline Müller, Stefano Puliti, Johannes Breidenbach

“…Often, the area covered by a species is estimated visually within a reference frame. However, such assessments are prone to observer bias and a large variability. …”
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Comparative Analysis of Ultra-Wideband and Mobile Laser Scanning Systems for Mapping Forest Trees under A Forest Canopy by Z. Liu, H. Kaartinen, T. Hakala, H. Hyyti, A. Kukko, A. Kukko, J. Hyyppa, J. Hyyppa, R. Chen

“…The experimental results show that the proposed method can accurately measure tree stem locations under the forest canopy with a root-mean-square-error (RMSE) of 14.44 cm and a mean-absolute-error (MAE) of 12.39 cm, providing accuracy comparable to that of the three tested MLSs. …”
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Estimation of Maize Water Requirements Based on the Low-Cost Image Acquisition Methods and the Meteorological Parameters by Jiuxiao Zhao, Jianping Tao, Shirui Zhang, Jingjing Li, Teng Li, Feifei Shan, Wengang Zheng

“…The Kc calculation model exhibits a root mean square error (<i>RMSE</i>) of 0.053. In terms of ETo estimation, the Optuna-LSTM model with four variables demonstrates the best estimation effect, with a correlation coefficient (<i>R</i>²) of 0.953. …”
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Evaluation of Seven Gap-Filling Techniques for Daily Station-Based Rainfall Datasets in South Ethiopia by Alefu Chinasho, Bobe Bedadi, Tesfaye Lemma, Tamado Tana, Tilahun Hordofa, Bisrat Elias

“…Instead, filling the data gaps using the reference datasets is a better and widely used approach. …”
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Evaluation of low nitrogen resistance of Avena sativa germplasm during the seed germination period by Jing Pan, Zeliang Ju, Xiang Ma, Lianxue Duan, Zhifeng Jia

“…The results of the comprehensive analysis showed that the order of low-N tolerance of each variety was as follows: Qingyongjiu 035> Jiayan No.2> Qingyin No.2> ZNY255> ZNY256, and the results of the present study provide a reference for the further large-scale screening of low-N-tolerant oat resources and the selection of varieties.…”
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Estimation of the duration between HIV seroconversion and HIV diagnosis in different population groups in French Guiana: Strategic information to reduce the proportion of undiagnos... by Mathieu Nacher, Antoine Adenis, Florence Huber, Edouard Hallet, Philippe Abboud, Emilie Mosnier, Bastien Bideau, Christian Marty, Aude Lucarelli, Vanessa Morel, François Lacapère, Loïc Epelboin, Pierre Couppié

“…<h4>Methods</h4>CD4 cell count at HIV sero-conversion and square root of CD4 cell decline were obtained using the CD4 decline in a cohort of HIV-infected persons in the UK, fitting random effect (slope and intercept) multilevel linear regression models. …”
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Research on rock burst prediction based on an integrated model by Junming Zhang, Qiyuan Xia, Hai Wu, Sailei Wei, Zhen Hu, Bing Du, Yuejing Yang, Huaixing Xiong

“…The model outperforms traditional methods in mean absolute error (MAE) and root mean square error (RMSE), providing effective insights and a reference for rockburst risk assessment and disaster prevention in mining operations.…”
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