Robust Filtering for Linear Equality Constrained Systems by Chuanbo Wen, Yunze Cai, Xiaoming Xu

“…Finally, a numerical example is presented to demonstrate the applicability of the proposed method.…”
Get full text

Adaptive Modulation Tracking for High-Precision Time-Delay Estimation in Multipath HF Channels by Qiwei Ji, Huabing Wu

“…High-frequency (HF) communication is critical for applications such as over-the-horizon positioning and ionospheric detection. …”
Get full text

Electrotactile proprioception training improves finger control accuracy and potential mechanism is proprioceptive recalibration by Rachen Ravichandran, James L. Patton, Hangue Park

“…Finger aperture control error was measured before and after the training (baseline, 15-min post, 24-h post). …”
Get full text

Methods of high voltage generation by cascading amplifiers by A. Dovhal, Yu. Tuz

“…The use of an additive error correction scheme significantly reduced signal distortion, improving its quality. …”
Get full text

GMTP: Enhanced Travel Time Prediction with Graph Attention Network and BERT Integration by Ting Liu, Yuan Liu

“…Additionally, two self-supervised tasks are designed for improved model accuracy and robustness. (3) Results: The fine-tuned model had comparatively optimal performance metrics with significant reductions in Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and Root Mean Squared Error (RMSE). (4) Conclusions: Ultimately, the integration of this model into travel time prediction, based on two large-scale real-world trajectory datasets, demonstrates enhanced performance and computational efficiency.…”
Get full text

A dynamic examination of the digital circuit implementing the Fitzhugh-Nagumo neuron model with emphasis on low power consumption and high precision. by Mehdi Nadiri Andabili, Soheila Nazari, Tohid Moosazadeh

“…As a result of its low power consumption, minimal error rates, and high-frequency capabilities, the proposed hardware demonstrates effectiveness and utility across a range of applications, including the simulation of learning processes in the nervous system that are based on nonlinear and chaotic behaviors.…”
Get full text

Prediction of stress-strain behavior of rock materials under biaxial compression using a deep learning approach. by Changsheng Li, Xinsong Zhang

“…The LSTM-AE approach uses the LSTM network to construct both the encoder and decoder, where the encoder extracts features from the input data and the decoder generates the target sequence for prediction. The mean square error (MSE), root mean square error (RMSE), mean absolute error (MAE), and coefficient of determination (R2) of the predicted and true values are used as the evaluation metrics. …”
Get full text

Large Scale Asset Detection Within Railway Scene Point Cloud Data From Mobile Laser Scanning by Bram Ton, Rick Akster

“…This analysis reveals that location accuracy is not yet sufficient for engineering applications. The analysis indicates that the largest contribution to this error originates from the random error. …”
Get full text

On Schröder-Type Series Expansions for the Lambert <i>W</i> Function by Roy M. Howard

“…For the principal branch, a proposed approximation yields, for a series of order 128, a relative error bound below 10⁻¹³⁶. For the negative one branch, a proposed approximation yields, for a series of order 128, a relative error bound below 10⁻¹⁴³. …”
Get full text

A Comprehensive Evaluation of Monocular Depth Estimation Methods in Low-Altitude Forest Environment by Jiwen Jia, Junhua Kang, Lin Chen, Xiang Gao, Borui Zhang, Guijun Yang

“…On the Mid-Air dataset, the Transformer-based DepthAnything demonstrates a 54.2% improvement in RMSE for the global error metric compared to the CNN-based Adabins. On the LOBDM dataset, the CNN-based MiDas has the depth edge completeness error of 93.361, while the Transformer-based Metric3D demonstrates the significantly lower error of only 5.494. …”
Get full text

Wearable IoT (w-IoT) artificial intelligence (AI) solution for sustainable smart-healthcare by Gurdeep Singh

“…It covers performance results rendering research science communication on machine learning models for time series analysis, regression and classification to implement defined and adaptive thresholds, adopting standard deviation and moving average, computing mean square error (MSE), root mean square error (RSME) and mean absolute error (MAE) values, utilizing exponential moving average results on multiple features, prominently targeting resting heartrate data. …”
Get full text

A wavelet-guided transformer approach for autofocus in brightfield biological microscopy by Wangka Yang, Meini Lv, Zhenming Yu, Jiawei Deng

“…Experiments conducted on a locally collected dataset demonstrate that WGT-Net achieves a mean absolute error (MAE) of 0.0869 and a root mean square error (RMSE) of 0.101, achieving 28.69% and 32.39% reductions in MAE and RMSE, respectively, compared with state-of-the-art methods, and completing predictions within milliseconds. …”
Get full text

Dynamic Adaptive Cross-Domain Mean Approximation by LI Huimin, MA Jianwei, ZANG Shaofei, SONG Yanbing

“…For this reason, this paper firstly improves CDMA by introducing an adaptation factor and designing dynamic CDMA to evaluate the edge distribution error and conditional distribution error between the source and target domains. …”
Get full text

Graph theoretic and machine learning approaches in molecular property prediction of bladder cancer therapeutics by Huiling Qin, Atef F. Hashem, Muhammad Farhan Hanif, Osman Abubakar Fiidow

“…The performance of the models is analyzed using metrics such as Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and the coefficient of determination $$(R^2)$$ . …”
Get full text

Almost linear decoder for optimal geometrically local quantum codes by Quinten Eggerickx, Adam Wills, Ting-Chun Lin, Kristiaan De Greve, Min-Hsiu Hsieh

“…Geometrically local quantum codes, which are error-correction codes embedded in R^{D} with checks acting only on qubits within a fixed spatial distance, have garnered significant interest. …”
Get full text

Study on Predicting Blueberry Hardness from Images for Adjusting Mechanical Gripper Force by Hao Yin, Wenxin Li, Han Wang, Yuhuan Li, Jiang Liu, Baogang Li

“…The error falls within the acceptable range for the safety factor design. …”
Get full text

Design and assessment of even parity generator and checker circuits for nanoscale communication networks using quantum dots by Saeid Seyedi, Hatam Abdoli

“…These improvements indicate the potential of the proposed circuits for low-power and small-area error detection mechanisms in nanoscale communication systems.…”
Get full text

Static power model for CMOS and FPGA circuits by Anas Razzaq, Andy Ye

“…Abstract In Ultra‐Low‐Power (ULP) applications, power consumption is a key parameter for process independent architectural level design decisions. …”
Get full text

SOLUSI PENDEKATAN PERSAMAAN GELOMBANG FRAKSIONAL NON LINEAR MENGGUNAKAN NEW VERSION OF OPTIMAL HOMOTOPY ASYMPTOTIC METHOD by Faiqul Fikri, Eddy Djauhari, Endang Rusyaman

“…Non-linear differential equations with fractional derivative order are mathematical models that are widely used in modeling physical phenomena, one of the applications of these models is non-linear fractional wave equations. …”
Get full text

Gradient-based optimization for parameter identification of lithium-ion battery model for electric vehicles by Motab Turki Almousa, Mohamed R. Gomaa, Mostafa Ghasemi, Mohamed Louzazni

“…Defining proper parameters for lithium-ion battery models is a challenge for several applications, including automobiles powered by electricity. …”
Get full text