Low-Complexity Oversampled OTFS Receivers With Reduced Overhead by Narendra Deconda, Srikrishna Bhashyam, Nambi Seshadri, R. David Koilpillai

“…The proposed equalizer provides a significant complexity reduction compared to the existing Message-passing equalizer for a minimal degradation in error performance. …”
Get full text

Heat and Mass Transfer Model of a Cross-flow Heat-source Tower based on the Ɛ-NTU Method by Jia Jikang, Li Nianping, Peng Jinqing, Zhang Nan, Cheng Jianlin, Cui Haijiao

“…The results showed that for the outlet temperature of a heat-source tower, the static relative error was controlled within 4%, and the dynamic relative error was less than 6%. …”
Get full text

An enhanced iTransformer-based early warning system for predicting automotive rental contract breaches. by Ming Jiang, Dongpeng Peng, Haihan Yu, Shu Chen

“…The experimental results demonstrate that the model is highly effective in predicting the vehicle's resident location and future trajectory. The mean square error (MSE), mean absolute error (MAE), and location error reached 0.001, 0.003, and 0.08 kilometers, respectively, which substantiates the model's efficiency and accuracy. …”
Get full text

Unveiling the performance and influential factors of GEDI L2A for building height retrieval by Peimin Chen, Huabing Huang, Peng Qin, Zhenbang Wu, Zixuan Wang, Chong Liu, Na Dong, Jie Wang

“…Building roof type has a moderate impact; flat-roof buildings exhibit a slight advantage over pitched- and curved-roof buildings, with rRMSE reductions of 1.86% and 4.74%, respectively. Neither GEDI beam type nor data acquisition time significantly affect the accuracy of height retrieval. …”
Get full text

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

Advancing sustainable renewable energy: XGBoost algorithm for the prediction of water yield in hemispherical solar stills by Salwa Ahmad Sarow, Hasan Abbas Flayyih, Maryam Bazerkan, Luttfi A. Al-Haddad, Zainab T. Al-Sharify, Ahmed Ali Farhan Ogaili

“…The current work extends these experimental insights through XG-Boost to predict productivity, employing evaluation metrics such as Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Coefficient of Variation of the Root Mean Squared Error (CVRMSE), and the determination coefficient (R2), with resulted values denoted as 0.43708%, 0.95879%, 0.2780%, 0.05290%, 12.2078%, and 0.88144% respectively. …”
Get full text

Advanced vehicle-to-grid control: enhancing energy exchange and power quality with grey wolf optimized bidirectional converters in EV charging infrastructure by Nagarajan Munusamy, Indragandhi Vairavasundaram

“…The proposed approach reduces average error reduction by 15%, grid current Total Harmonic Distortion (THD) by 20%, and DC link voltage surge during load transients from 12.5% to 2.3% compared to typical PI controllers. …”
Get full text

Effect of model’s skill level and frequency of feedback on learning of complex serial aiming task by Gh. Lotfi, F. Hatami, F. Zivari

“…Conclusion: According to Fitz’s speed-accuracy trade-off law, the results are justified as following: since the expert model observers focus on error reduction and increased accuracy in executing complex tasks, their movement time gets longer. …”
Get full text

Trend and prediction of daily incidence of hand, foot, and mouth disease in Shenzhen, 2011 - 2023 with projections to 2024: a Prophet model approach by Wenhai LU, Lixia SONG, Huawei XIONG, Zhigao CHEN, Yan LU, Yanpeng CHENG, Zhen ZHANG

“…Model performance was evaluated using four metrics: mean square error (MSE), mean absolute error (MAE), root mean square error (RMSE), and symmetric mean absolute percentage error (SMAPE). …”
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

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

“…Additionally, interest rate reduction can generate growth in housing demand resulting in the country’s economic improvement.…”
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