Conversion to Variable Flow Rate—Advanced Control of a District Heating (DH) System with a Focus on Operational Data by Stanislav Chicherin

“…The results show a significant reduction in excess heat supply during warm days, with improvements in heat demand prediction accuracy (17.3% average error) compared to standard models. …”
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Integrated Platform for Bio-Image Processing and Identification of Cervical Cancer by Larisa-Dalina LAZĂR, Diogen BABUC, Todor IVAŞCU

“…The integration of artificial intelligence in medical imaging can contribute to early detection and contribute to reduction of mortality rates associated with this disease. …”
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Theory of Complex Gravitation by Borros M. Arneth

“…The basic assumption starts with a reduction of all the natural forces into a single force. …”
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Subspace-based local compilation of variational quantum circuits for large-scale quantum many-body simulation by Shota Kanasugi, Yuichiro Hidaka, Yuya O. Nakagawa, Shoichiro Tsutsui, Norifumi Matsumoto, Kazunori Maruyama, Hirotaka Oshima, Shintaro Sato

“…Our estimation suggests that the acceptable physical gate error rate for the LSVQC can be about one order of magnitude larger than that for the Trotterization.…”
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Integrated Sensing and Communication Using Random Padded OTFS with Reduced Interferences by Pavel Karpovich, Tomasz P. Zielinski

“…In turn, the reduction in data carrier interference is achieved by extrapolating the estimate of channel state information. …”
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Electric Vehicle Charging Load Forecasting Method Based on Improved Long Short-Term Memory Model with Particle Swarm Optimization by Xiaomeng Yang, Lidong Zhang, Xiangyun Han

“…Specifically, during winter, the Mean Absolute Error (MAE) is 3.896, a reduction of 6.57% compared to the LSTM model and 10.13% compared to the Gated Recurrent Unit (GRU) model. …”
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A SAR wave-enhanced method combining denoising and texture enhancement for bathymetric inversion by Aijun Cui, Yi Ma, Jingyu Zhang, Ruifu Wang

“…The proposed method improved bathymetric accuracy, reducing mean absolute error (MAE) by up to 4.69 m and mean relative error (MRE) by up to 18 %. …”
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Abnormal sound detection method for coal mine belt conveyors based on convolutional autoencoder by SHEN Long, SHAN Haoran, PEI Wenliang, YANG Guixiang, WANG Yongli

“…Next, the normal operation audio features and the reconstructed normal operation audio features were input into the Mean Squared Error Loss function (MSELoss) to obtain the reconstruction error, with the maximum reconstruction error set as the reconstruction threshold for normal operation audio features. …”
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High-precision position control of hydraulic support pushing system based on quasi-sliding mode by GAO Yuhao, SUN Xing, LI Yang, LIU Wei, LI Jingyan

“…In the sinusoidal response, stable tracking was achieved within 0.2 s, with a peak error of about 0.001 m, representing a reduction of approximately 94.7%, and it exhibited broader bandwidth characteristics. …”
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End-to-end neural automatic speech recognition system for low resource languages by Sami Dhahbi, Nasir Saleem, Sami Bourouis, Mouhebeddine Berrima, Elena Verdú

“…Using synthetic speech and data augmentation techniques can enhance E2E-ASR performance for low-resource languages, reducing word error rates (WERs) and character error rates (CERs). …”
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Advancing smart communities with a deep learning framework for sustainable resource management. by Yongyan Zhao

“…Predictive models received assessment based on Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and R². …”
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A Physics‐Informed Deep Learning Framework for Estimating Thermal Stratification in a Large Deep Reservoir by Yuan He, Xiaofan Yang

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A Refined Astrometric Approach Based on the Precision Premium and its Application to the Jupiter’s Satellite Himalia by Z. J. Zheng, Q. Y. Peng, F. R. Lin, D. Li

“…Since the advent of Gaia catalog, positional precision of a ground-based telescope can be greatly improved by correction of more subtle errors, including positional biases induced by atmospheric turbulence, and some instrumental factors such as geometric distortion and the charge transfer efficiency. …”
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ResT-IMU: A Two-Stage ResNet-Transformer Framework for Inertial Measurement Unit Localization by Yanping Zhu, Jianqiang Zhang, Wenlong Chen, Chenyang Zhu, Sen Yan, Qi Chen

“…Compared with the IMUNet model, ResT-IMU achieves reductions of 0.61 m in ATE and 0.02 m in RTE on the iIMU-TD dataset and reductions of 0.32 m in ATE and 0.33 m in RTE on the RoNIN dataset. …”
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LPRLC: Linear predictive run length coding to improve energy consumption of wireless body area networks by Mahdieh Hajiloo Vakil, Zahra Shirmohammadi

“…First- Linear Predictive Coding (LPC) for data prediction, Second- Error calculation, Third- Error coding with Run Length Encoding (RLE) for data compression. …”
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The potential of combining passenger rail with freight: A New York City case study by Pouria Bacher, Jacqueline M. Klopp, Martina Ortbauer, Maximilian Lackner

“…Environmental Protection Agency data, we estimated emission reductions from replacing trucks with unused subway capacity. …”
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Rapid detection of volatile fatty acids in biogas slurry using near-infrared spectroscopy combined with optimized wavelength selection and partial least squares regression by Honglin Wang, Jinming Liu, Pengfei Li, Chong Tan

“…Model validation yielded determination coefficients of 0.9882, 0.9452, and 0.9483, and root mean square errors of prediction of 0.1193, 0.1178, and 0.5492 for acetic acid, propionic acid, and total acid, respectively, representing reductions of approximately 40 %, 18 %, and 30 % compared to full-spectrum modeling. …”
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Experimental investigation and modeling of heat and moisture transfer beneath asphalt pavements under rainfall conditions by Weihang Hua, Long Jin, Miaomiao Bai, Huimei Zhang

“…Evaporative latent heat significantly suppressed surface warming, reducing the temperature rise at 2 cm by 59.2 %, and delayed heat transfer to deeper layers (reductions of 54.5 %–64.7 %). A cumulative heat flux prediction model, incorporating solar radiation, evaporation, convection, and surface wetting, showed high accuracy (R2 = 0.981 and 0.952; relative errors: 4.1 % and 9.6 %). …”
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Challenges in Collating Spirometry Reference Data for South-Asian Children: An Observational Study. by Sooky Lum, Vassiliki Bountziouka, Philip Quanjer, Samatha Sonnappa, Angela Wade, Caroline Beardsmore, Sunil K Chhabra, Rajesh K Chudasama, Derek G Cook, Seeromanie Harding, Claudia E Kuehni, K V V Prasad, Peter H Whincup, Simon Lee, Janet Stocks

“…Records with transcription errors, missing values for height or spirometry, and implausible values were excluded(n = 110).…”
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Adaptive Echo State Network for crop yield prediction incorporating Fall Armyworm dynamicsMendeley Data by Mulima Chibuye, Jackson Phiri, Phillip Nkunika

“…In cross-validation, the FAW-aware ESN achieves an R² of ∼0.55 and reduces prediction errors by up to 67 % versus unpenalized baselines, closely capturing observed yield reductions exceeding 20 % during severe outbreaks. …”
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