Spatio-temporal graph neural networks for power prediction in offshore wind farms using SCADA data by S. Daenens, S. Daenens, S. Daenens, T. Verstraeten, T. Verstraeten, T. Verstraeten, P.-J. Daems, P.-J. Daems, A. Nowé, J. Helsen, J. Helsen, J. Helsen

“…The results show that both the spatial and the spatio-temporal GNN models outperform traditional data-driven power curve methods, achieving reductions in the mean absolute error (MAE) of approximately 22.6 % and 30.3 %, respectively, and in the mean absolute percentage error (MAPE) of around 20.7 % and 30.5 %, respectively. …”
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Enhancing burned area monitoring with VIIRS dataset: A case study in Sub-Saharan Africa by Boris Ouattara, Michael Thiel, Barbara Sponholz, Heiko Paeth, Marta Yebra, Florent Mouillot, Patrick Kacic, Kwame Hackman

“…Based on a stratified random sampling, the validation results demonstrate varying levels of accuracy for the VIIRS-BA product across different confidence levels. The commission error (CE) ranges from 7.8% to 23.4%, while the omission error (OE) falls between 29.4% and 58.8%. …”
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Low-overhead quantum computing with the color code by Felix Thomsen, Markus S. Kesselring, Stephen D. Bartlett, Benjamin J. Brown

“…Fault-tolerant quantum computation demands significant resources: large numbers of physical qubits must be checked for errors repeatedly to protect quantum data as logic gates are implemented in the presence of noise. …”
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A deep learning framework for prediction of crop yield in Australia under the impact of climate change by Haydar Demirhan

“…The reductions in average root mean squared error are 19%, 25%, 37%, and 29% over the benchmark methods. …”
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Experimental study on rock fracture toughness under temperature and confining pressure coupling condition by Bo Cai, Nailing Xiu, Dongxu Li, Haifeng Fu, Xiaodong Dai, Dawei Deng, Hexiang Zhao, Xueyuan Han, Songyang Yuan, Liangang Deng

“…Key findings reveal a temperature-dependent degradation of fracture toughness (40% reduction from 25°C to 200°C at zero confining pressure) and a confining pressure-driven enhancement (76% increase from 0 to 100 MPa at ambient temperature). …”
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Study on carbon emissions of a small hydropower plant in Southwest China by Caihong Tang, Yiling Leng, Pengyu Wang, Jian Feng, Shanghong Zhang, Yujun Yi, Hui Li, Shaoliang Tian

“…The uncertainty was evaluated using the error propagation method. Following analysis, suggestions for carbon footprint reduction measures were proposed. …”
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Surface circulation characterization along the middle southern coastal region of Vietnam from high-frequency radar and numerical modeling by T. H. Tran, T. H. Tran, A. Sentchev, T. To Duy, M. Herrmann, S. Ouillon, S. Ouillon, K. C. Nguyen

“…Both methods achieved a significant reduction (<span class="inline-formula">∼</span> 36 %–40 %) in the error of the surface current velocity fields compared to the measured data. …”
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Design of an improved graph-based model integrating LSTM, LoRaWAN, and blockchain for smart agriculture by Ravi Kumar Munaganuri, Narasimha Rao Yamarthi, Sai Chandana Bolem

“…LSTM networks are chosen here for their high performance in timestamp series prediction tasks with an mean average error (MAE) of 0.02 m3/m3 over a 7-day forecast horizon. …”
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Predictive Model for Erosion Rate of Concrete Under Wind Gravel Flow Based on K-Fold Cross-Validation Combined with Support Vector Machine by Yanhua Zhao, Kai Zhang, Aojun Guo, Fukang Hao, Jie Ma

“…It showed average relative errors of 22% and 31.6% for the Bitter and Oka models, respectively. …”
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Global surface eddy mixing ellipses: spatio-temporal variability and machine learning prediction by Tian Jing, Ru Chen, Chuanyu Liu, Chunhua Qiu, Chunhua Qiu, Cuicui Zhang, Mei Hong

“…This resulted in a spatially averaged correlation increase of over 0.5 for predicting the minor axis and anisotropy, along with a reduction of more than 0.15 in the Normalized Root Mean Square Error. …”
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Control of multi-level quadratic DC-DC boost converter for photovoltaic systems using type-2 fuzzy logic technique-based MPPT approaches by Souheyb Mohammed Belhadj, Bouziane Meliani, Habib Benbouhenni, Sarra Zaidi, Z.M.S. Elbarbary, Mohammed M. Alammer

“…By incorporating type-reduction and interval type-2 fuzzy logic principles, the T2FLC enhances robustness, precision, and adaptability to rapidly changing irradiance and temperature levels. …”
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PMSM sliding-mode control based on novel reaching law and disturbance observer by LIU Jing, LI Hong-wen, DENG Yong-ting

“…The switching gain of SMDO was designed as a function of the observed error of disturbance to suppress chattering of the sliding mode estimated value. …”
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Obstacle avoidance algorithm based on sub-image segmentation and mapping point cloud space by Liya ZHANG, Chenxin LI, Bin LIU, Zhifang YANG

“…As a conventional means of intelligent inspection, inspection robots are of great significance for ensuring the safe production of coal mines and realizing the reduction of personnel and the enhancement of safety underground. …”
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Implementing FFE-MLSD With Improved BER and Reduced Complexity for Long-Reach PAM4 Wireline Receivers by Hanseok Kim, Sihyun Lee, Piljun Jeong, Jaeha Kim, Woo-Seok Choi

“…This paper proposes a PAM4 receiver DSP architecture based on Feed-Forward Equalizer (FFE) and Maximum Likelihood Sequence Detector (MLSD), targeting improved bit-error-rate (BER) performance and reduced hardware complexity. …”
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Bonding behavior of lap-spliced reinforcing bars embedded in ultra-high-performance concrete with steel fibers by Krairerk Aiamsri, Teerasak Yaowarat, Suksun Horpibulsuk, Apichat Suddeepong, Apinun Buritatum, Kanchana Hiranwatthana, Kirati Nitichote

“…This method achieves an error margin below ±16.5%, providing an accurate approach for practitioners. …”
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Cooperative Intelligent Transport Systems: The Impact of C-V2X Communication Technologies on Road Safety and Traffic Efficiency by Jingwen Wang, Ivan Topilin, Anastasia Feofilova, Mengru Shao, Yadong Wang

“…The integration of artificial intelligence, sensors, and machine vision systems enables autonomous vehicles (AVs) to rapidly adapt to changes in the road environment, minimizing human error and significantly reducing collision risks. …”
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Land cover change mitigated 20 % of the total increased evapotranspiration in tropical Lancang-Mekong River Basin during 2001–2019 by Houbing Chen, Yaoliang Chen, Lamin R. Mansaray, Longwei Li, Shusen Wang

“…New hydrological insights for the region: The improved MOD16 algorithm showed better performance with the average Root Mean Square Error decreasing by 0.12 mm/day compared with the original MOD16 ET. …”
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Voice Spoofing Detection Through Residual Network, Max Feature Map, and Depthwise Separable Convolution by Il-Youp Kwak, Sungsu Kwag, Junhee Lee, Youngbae Jeon, Jeonghwan Hwang, Hyo-Jung Choi, Jong-Hoon Yang, So-Yul Han, Jun Ho Huh, Choong-Hoon Lee, Ji Won Yoon

“…Our single model achieved a replay attack detection equal error rate (EER) of 0.30&#x0025; on the evaluation set using an optimized constant Q transform (CQT) feature, outperforming the top ensemble system in the competition, which scored an EER of 0.39&#x0025;. …”
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Sequential Hybrid Beamforming for Radio Stripes by Joumana JOUMANA, Daniel Castanheira, Adao Silva, Rui Dinis, Atilio Gameiro

“…The APs hybrid equalizer is optimized, using as a metric, the mean squared error (MSE) between the transmitted and the AP received signals. …”
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Thermal Bending Simulation and Experimental Study of 3D Ultra-Thin Glass Components for Smartwatches by Shunchang Hu, Peiyan Sun, Zhen Zhang, Guojun Zhang, Wuyi Ming

“…By comparing the numerical simulation results, it was found that within the temperature range of 615–625 °C, a molding pressure of 25–35 MPa, a heating rate of 1.5–2.5 °C/s, a cooling rate of 0.5–1 °C/s, and a pulse pressure of 45–55 Hz, the influence on residual stress and shape deviation in the glass was minimal. The relative error range was within the 20% acceptable limit, according to the experimental validation, which offered crucial direction and ideas for process development.…”
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