Optimization Design of Dynamic Cable Configuration Considering Thermo-Mechanical Coupling Effects by Ying Li, Guanggen Zou, Suchun Yang, Dongsheng Qiao, Bin Wang

“…The framework employs a Radial Basis Function (RBF) surrogate model coupled with NSGA-II algorithm, yielding validated Pareto solutions (≤6.15% max error vs. simulations). Results demonstrate universal reduction in extreme responses across optimized configurations, with the thermo-mechanically optimized solution achieving 20.24% fatigue life enhancement. …”
Get full text

MM-iTransformer: A Multimodal Approach to Economic Time Series Forecasting with Textual Data by Shangyang Mou, Qiang Xue, Jinhui Chen, Tetsuya Takiguchi, Yasuo Ariki

“…Compared to models relying solely on historical price data, the proposed framework achieves a substantial reduction in Mean Squared Error (MSE) loss, with improvements of up to 26.79%. …”
Get full text

Development and Implementation of a Clinical Decision Support System to Enhance Efficiency and Accuracy in Medication Prescription Review in a Tertiary Care Hospital: A Retrospecti... by Lin M, He Y, He P, Jiang H, Luo H, Dai H, Yu L

“…Among them, 63,219 (30.34%) and 61,258 (28.08%) patients received alerts, respectively, showing a significant reduction of 2.26% (aHR=0.896, 95% CI 0.885– 0.908; P< 0.001). …”
Get full text

Breast lesion classification via colorized mammograms and transfer learning in a novel CAD framework by Abbas Ali Hussein, Morteza Valizadeh, Mehdi Chehel Amirani, Sedighe Mirbolouk

“…It is clear from these results that the developed method does not only advance the state-of-the-art in technical terms, but also provides radiologists with a practical tool to aid in the reduction of diagnostic errors and increase the detection of early breast cancer.…”
Get full text

The Algorithm for Recognizing Superposition of Wave Aberrations from Focal Pattern Based on Partial Sums by Sergey G. Volotovsky, Pavel A. Khorin, Aleksey P. Dzyuba, Svetlana N. Khonina

“…Due to the peculiarities of the focal pattern, some types of the considered superpositions are recognized ambiguously from the intensity pattern in the focal plane by standard error-reduction algorithms. It is numerically shown that when recognizing superpositions of Zernike functions from the intensity pattern in the focal plane, the use of step-by-step optimization in combination with the Levenberg–Marquardt algorithm yields good results only with an initial approximation close to the solution. …”
Get full text

Modeling the influence of streamwise flow field acceleration on the aerodynamic performance of an actuator disk by C. P. Zengler, N. Troldborg, M. Gaunaa

“…The new model accurately captures this behavior and significantly reduces the prediction error compared to classical momentum theory, where the effect of the background flow acceleration is disregarded. …”
Get full text

Multi-modality deep learning for pulse prediction in homogeneous nonlinear systems via parametric conversion by Hao Zhang, Linshan Sun, Jack Hirschman, Sergio Carbajo

“…Our results demonstrate a 73% reduction in prediction error and an 83% improvement in computational efficiency compared to conventional neural networks. …”
Get full text

Minimizing Interference in Robotic Rehabilitation via Asymmetric Stiffness Force Fields by Yasuhiro Kato, Sho Sakaino, Toshiaki Tsuji

“…The experimental results revealed that the proposed approach demonstrated a similar reduction in movement error compared to the conventional stiffness approach. …”
Get full text

A UAV-Assisted STAR-RIS Network with a NOMA System by Jiyin Lan, Yuyang Peng, Mohammad Meraj Mirza, Fawaz AL-Hazemi

“…Simulation results show that the proposed scheme achieves up to 22% improvement in achievable rate and significant reduction in bit error rate (BER) compared to benchmark schemes, demonstrating its effectiveness in integrating STAR-RIS and UAV in NOMA networks.…”
Get full text

The effect of resizing on the natural appearance of scintigraphic images: an image similarity analysis by Siraj Ghassel, Amir Jabbarpour, Jochen Lang, Eric Moulton, Eric Moulton, Ran Klein, Ran Klein, Ran Klein, Ran Klein

“…For downsampling, both linear interpolation and sliding window summation yielded similar outcomes for a reduction factor of 2. However, for a reduction factor of 4, only sliding window summation resulted in image similarity metrics in agreement with those at the target grid size.ConclusionsThe study underlines the importance of applying appropriate resizing techniques in nuclear medical imaging to produce realistic images at the target grid size.…”
Get full text

Political risk and macroeconomic effect of housing prices in South Africa by Thomas Habanabakize, Zandri Dickason

“…To achieve this objective, the study applies Vector Autoregressive (VAR) model, the Johansen test for cointegration, Vector Error Correction Model (VECM) and Granger causality test on monthly data starting from January 2002 to December 2019. …”
Get full text

A study on monthly sales forecasting of new energy vehicles in urban areas using the WOA-BiGRU model. by Xiangtu Li

“…The WOA-BiGRU model outperforms both the standalone BiGRU and PSO models, achieving a Mean Absolute Error (MAE) of 3051.89, which is 526.18 lower than the BiGRU model and 104.72 lower than that of the PSO model. …”
Get full text

Continuous respiratory rate monitoring through temporal fusion of ECG and PPG signals. by Yuxuan Lin, Xinyue Song, Yan Zhao, Chunlin Zhang, Xiaorong Ding

“…Validation on two public datasets - the Capnobase dataset (42 subjects) and the BIDMC dataset (53 subjects) - showed that the proposed method attained a mean absolute error (MAE) of 1.39 breaths/min and 3.29 breaths/min for RR estimation, respectively, achieving an average 11.61% reduction in MAE compared to existing state-of-the-art approaches. …”
Get full text

Semi-Supervised Learning of Statistical Models for Natural Language Understanding by Deyu Zhou, Yulan He

“…In addition, the proposed framework shows superior performance than two other baseline approaches, a hybrid framework combining HVS and HM-SVMs and discriminative training of HVS, with a relative error reduction rate of about 25% and 15% being achieved in F-measure.…”
Get full text

Data-Driven Pavement Performance: Machine Learning-Based Predictive Models by Mohammad Fahad, Nurullah Bektas

“…Results indicate that LightGBM and CatBoost outperform other models, achieving the lowest mean squared error and highest R² values. In contrast, linear regression and KNN demonstrated the lowest performance, with MSE values up to 188% higher than CatBoost. …”
Get full text

Stream Nutrient Load and Concentration Estimation From Minimal Measurements by Wasif Bin Mamoon, Kun Zhang, Mitul Luhar, Anthony J. Parolari

“…Sparse measurements (20–80 per year) at optimal sampling times and locations were sufficient to accurately estimate nutrient concentrations and loads (error <±2% for NOx; <±9% for total phosphorus). DSS promises to enable cost‐effective water quality monitoring.…”
Get full text

Measurement of ferromagnetic pipe wall thickness by magnetic flux leakage method by A.E. Goldstein, K.A. Stryapchev

“…The method considers the distance between the pipe edge and the measurement plane of the magnetic field strength thereby enabling a 10-fold reduction in the error of the wall thickness measurement induced by the edge effect. …”
Get full text

Augmentation of Semantic Processes for Deep Learning Applications by Maximilian Hoffmann, Lukas Malburg, Ralph Bergmann

“…The results indicate a large potential with a reduction of the prediction error of up to 53%.…”
Get full text

Stability Study of Multicomponent Mixtures to Support Carbon Metrology by Dias Florbela A., Palma Cristina, Costa Carlos J.

“…The stability study was conducted over one year, employing statistical evaluation using the Normalized Error (En) function in accordance with the international standard ISO 13528:2022 for statistical methods.…”
Get full text

OT-PCA: New Key-Recovery Plaintext-Checking Oracle Based Side-Channel Attacks on HQC with Offline Templates by Haiyue Dong, Qian Guo

“…Our method addresses critical challenges in optimizing key-related information extraction, including maximizing decryption output entropy and ensuring error pattern independence, through the use of genetic-style algorithms. …”
Get full text