Mental chronometry in big noisy data. by Edmund Wascher, Fariba Sharifian, Marie Gutberlet, Daniel Schneider, Stephan Getzmann, Stefan Arnau

“…In the present study, we systematically evaluated two different approaches to latency estimation (peak latencies and fractional area latencies) with respect to their data quality and the application of noise reduction by jackknifing methods. Additionally, we tested the recently introduced method of Standardized Measurement Error (SME) to prune the dataset. …”
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Radio frequency fingerprint data augmentation for indoor localization based on diffusion model by Haojun AI, Weike ZENG, Jingjie TAO, Jinying XU, Hanxiao CHANG

“…The radio frequency fingerprint indoor localization method ensures the accuracy by collecting a sufficient amount of fingerprints in the offline state to build a dense fingerprint database.A data augmentation method called FPDiffusion was proposed based on diffusion model to reduce the cost of fingerprint acquisition.Firstly, a temporal graph representation of the fingerprint sequence was constructed, the forward process of the diffusion model was accomplished by adding Gaussian noise, and a U-Net was utilized for the reverse process.The loss function of the network was designed according to the characteristics of radio frequency fingerprints.Finally, the computational process for generating dense fingerprints based on sparse fingerprints was presented.Experimental results demonstrate that FPDiffusion achieves 76% and 28% localization error reduction on K-nearest neighbor (KNN) and convolutional neural network (CNN) respectively, and significantly improves localization accuracy on KNN compared to Gaussian process regression (GPR) and GPR-GAN when only a small amount of labeled fingerprints is available.…”
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The Combination of Spectrum Subtraction and Cross-power Spectrum Phase Method for Time Delay Estimation by Feng BIN, Xu LEI

“…In order to solve the problem of large error of delay estimation in low SNR environment, a new delay estimation method based on cross power spectral frequency domain weighting and spectrum subtraction is proposed. …”
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Two-particle calculations with quantics tensor trains: Solving the parquet equations by Stefan Rohshap, Marc K. Ritter, Hiroshi Shinaoka, Jan von Delft, Markus Wallerberger, Anna Kauch

“…The applied methods allow for an exponential increase of the number of grid points included in the calculations, and a corresponding exponential reduction of the computational error, for a linear increase in computational cost.…”
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Introducing an Evolutionary Method to Create the Bounds of Artificial Neural Networks by Ioannis G. Tsoulos, Vasileios Charilogis, Dimitrios Tsalikakis

“…The new method effectively constructs the parameter value range of the artificial neural network with one processing level and sigmoid outputs, both achieving a reduction in training error and preventing the network from experiencing overfitting phenomena. …”
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Reducing time and computing costs in EC-Earth: an automatic load-balancing approach for coupled Earth system models by S. Palomas, M. C. Acosta, G. Utrera, E. Tourigny

“…However, this task traditionally involves manual testing of multiple process allocations by trial and error, requiring significant time investment from researchers and making the process more error-prone, often resulting in a loss of application performance due to the complexity of the task. …”
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OPTIMASI PEMBACAAN SUHU KAMERA TERMAL MENGGUNAKAN REGRESI LINIER by Sevia Indah Purnama, Irmayatul Hikmah, Mas Aly Afandi, Elsa Sri Mulyani

“…The reduction in reading error also occurred by 5.27% at 37 ° C and 6.44% at 38 ° C. …”
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Indoor and Ambient Air Pollution in Chennai, India during COVID-19 Lockdown: An Affordable Sensors Study by Naveen Puttaswamy, V. Sreekanth, Ajay Pillarisetti, Adithi R. Upadhya, Sudhakar Saidam, Balachandar Veerappan, Krishnendu Mukhopadhyay, Sankar Sambandam, Ronak Sutaria, Kalpana Balakrishnan

“…Lockdowns resulted in significant reductions in indoor and ambient PM levels, with the highest reduction observed during lockdown phase 2 (L2) and phase 3 (L3). …”
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Effectiveness and safety of direct oral anticoagulants in patients with atrial fibrillation and chronic kidney disease: a systematic review and meta-analysis of clinical trials by E. M. Mezhonov, Z. M. Safiullina, Y. A. Vyalkina, S. V. Shalaev

“…When analyzing all-cause mortality, direct oral anticoagulant therapy was also associated with a 14% reduction (HR=0.86, 95% CI 0.80–0.92, p<0.001).Conclusion. …”
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Study on the water pressure distribution characteristics of tunnel lining and pressure-reducing capability of by Xinpeng CHEN, Chaoyi WANG, Feng LU, Linlong LI, Feilong ZHAO, Cheng XIONG, Chongjun LUO, Kaimeng MA

“…The maximum prediction error is 8.25%, indicating a high level of accuracy. …”
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An Importance Sampling Method for Generating Optimal Interpolation Points in Training Physics-Informed Neural Networks by Hui Li, Yichi Zhang, Zhaoxiong Wu, Zhe Wang, Tong Wu

“…Experimental results demonstrate that our method achieves a 43% reduction in root mean square error compared to state-of-the-art methods when applied to the one-dimensional Korteweg–De Vries equation.…”
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Design and Simulation of Full State Feedback Controller for DC Motor by K. Love, C. Kriger, T. Nomzamo

“…A reduction in rise time and steady state-error proves that a FSFB controller with integral control performs better than the original closed loop system without a controller. …”
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WDM-PON Free Space Optical (FSO) System Utilizing LDPC Decoding for Enhanced Cellular C-RAN Fronthaul Networks by Dokhyl AlQahtani, Fady El-Nahal

“…Our system transmits 20 Gbps, 16-QAM intensity-modulated orthogonal frequency-division multiplexing (OFDM) signals, achieving a substantial reduction in bit error rate (BER). Numerical results show that the proposed WDM-PON-FSO architecture, augmented with LDPC decoding, maintains reliable transmission over 2 km under strong turbulence conditions.…”
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Prediction of Automotive Wire Harness Aging Based on CNN-biLSTM-Attention by Kun Xia, Qi Zhu, Qingqing Yuan, Jingxia Wang

“…The results show the system achieves a mean absolute error (MAE) of 0.02806, with 32.50% and 62.06% error reduction compared to LSTM and Random Forest models, respectively, demonstrating effective prediction performance.…”
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An Image and State Information-Based PINN with Attention Mechanisms for the Rapid Prediction of Aircraft Aerodynamic Characteristics by Yiduo Kan, Xiangdong Liu, Haikuo Liu

“…Extensive experiments validate the effectiveness of our model for rapid aircraft aerodynamic parameter prediction, achieving a significant reduction in prediction error that improves performance by 29.25% in RMSE and 37.99% in MRE compared to existing methods. …”
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Efficient Learning of Long-Range and Equivariant Quantum Systems by Štěpán Šmíd, Roberto Bondesan

“…For interactions decaying as a power law with exponent greater than twice the dimension of the system, we recover the same efficient logarithmic scaling with respect to the number of qubits, but the dependence on the error worsens to exponential. Further, we show that learning algorithms equivariant under the automorphism group of the interaction hypergraph achieve a sample complexity reduction, leading in particular to a constant number of samples for learning sums of local observables in systems with periodic boundary conditions. …”
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Post-acceleration internal enhancement technology for streak camera and its nonlinear intensity correction by GU Li, YANG Fang, YANG Qinlao

“…The dynamic range error is 7.7% compared with the uncorrected one. …”
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A Hybrid GARCH and Deep Learning Method for Volatility Prediction by Hailabe T. Araya, Jane Aduda, Tesfahun Berhane

“…The model’s forecasting performance was assessed using key evaluation metrics, including mean absolute error (MAE) and root mean squared error (RMSE). Compared to other hybrid models, our new proposed hybrid model demonstrates an average reduction in MAE and RMSE of 60.35% and 60.61%, respectively. …”
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Smooth pursuit and visual occlusion: active inference and oculomotor control in schizophrenia. by Rick A Adams, Laurent U Perrinet, Karl Friston

“…Furthermore, we show that a single deficit in the postsynaptic gain of prediction error units (encoding the precision of posterior beliefs) can account for several features of smooth pursuit in schizophrenia: namely, a reduction in motor gain and anticipatory eye movements during visual occlusion, a paradoxical improvement in tracking unpredicted deviations from target trajectories and a failure to recognise and exploit regularities in the periodic motion of visual targets. …”
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Hygroscopicity of ‘sucupira-branca’ (Pterodon emarginatus Vogel) fruits by Daniel E. C. de Oliveira, Osvaldo Resende, Lílian M. Costa, Glicélia P. Silva, Juliana de F. Sales

“…The models Chung-Pfost, Copace, Modified Halsey, Oswin Modified and Sigma Copace obtained high coefficient of determination (R2) and low chi-square (χ2), relative mean error (P) and estimated mean error (SE), and the Copace model was selected to represent the desorption isotherms. …”
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