Machine Learning-Based Environment-Aware GNSS Integrity Monitoring for Urban Air Mobility by Oguz Kagan Isik, Ivan Petrunin, Antonios Tsourdos

“…This study introduces a novel machine learning-based GNSS integrity monitoring framework that incorporates environment recognition to create environment-specific error models. Using a comprehensive Hardware-in-the-Loop (HIL) simulation setup, extensive data were generated for suburban, urban, and urban canyon environments to train and validate the models. …”
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Multi-Task Learning for Joint Indoor Localization and Blind Channel Estimation in OFDM Systems by Maria Camila Molina, Iness Ahriz, Lounis Zerioul, Michel Terré

“…Results based on experimental data using the proposed solution show a 50th percentile localization error of 1.62 m for 3-tap channels and 0.89 m for 10-tap channels.…”
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Reliability and validity of OpenPose for measuring HKA angle in dynamic walking videos in patients with knee osteoarthritis by Fanghong Ge, Changjiang Wu, Fangjun Ge, Shenghao Xu, Jianlin Xiao

“…Compared with radiography, the pose estimation method exhibited a fixed error of 0.131°. This is the first study to examine the feasibility of measuring the HKA angle from frontal-view videos of patients walking normally by using the pose estimation method. …”
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Transfer Learning-Based Detection of Pile Defects in Low-Strain Pile Integrity Testing by Övünç Öztürk, Tuğba Özacar, Bora Canbula

“…Low-strain pile integrity testing (LSPIT) is widely used for defect detection; however, conventional manual interpretation of reflectograms is both time-consuming and susceptible to human error. This study presents a deep learning-driven approach utilizing transfer learning with convolutional neural networks (CNNs) to automate pile defect detection. …”
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Broadband Polarization-Insensitive Metamaterial Perfect Absorbers Using Topology Optimization by Sze Ming Fu, Yan Kai Zhong, Nyan Ping Ju, Ming-Hsiang Tu, Bo-Ruei Chen, Albert Lin

“…Here, nontapered shape-optimized HMM absorbers are proposed, which facilitates the fabrication and promotes the large-area applications such as thermophotovoltaics (TPV). In the synthesis of the optimal patterns, we use 5-harmonic rigorously coupled wave analysis (RCWA) and experimental trials to shorten the trial-and-error time. …”
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Unveiling the hidden depths: advancements in underwater image enhancement using deep learning and auto-encoders by Jaisuraj Bantupalli, Amal John Kachapilly, Sanjukta Roy, Pavithra L. K.

“…The performance of the model is evaluated and compared with various traditional and deep learning based image enhancement techniques using the quality measures structural similarity index (SSIM), peak signal-to-noise ratio (PSNR) and mean squared error (MSE). This research aims to address the critical limitations of current techniques by offering a superior method for underwater image enhancement by improving color fidelity and better information extraction capabilities for various applications. …”
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Robust higher-order numerical scheme for solving time-fractional singularly perturbed parabolic partial differential equations with large delay in time by Habtamu Getachew Kumie, Awoke Andargie Tiruneh, Getachew Adamu Derese

“…The uniform stability analysis and the bounds of the truncation error are performed. The convergence of the numerical scheme is proved in the maximum norm. …”
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Calculating the Optimal Point Cloud Density for Airborne LiDAR Landslide Investigation: An Adaptive Approach by Zeyuan Liao, Xiujun Dong, Qiulin He

“…In this study, we propose a method to quantify DEM quality by combining the RMSE of elevation and terrain complexity, analyzing the DEM quality error curves constructed with different point cloud densities by a discrete difference peak-seeking method, to determine the optimal ground point density, and then constructing an ICP-NN algorithm for predicting the collected point cloud density. …”
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A novel framework to identify delamination location/size in BFRP pipe based on convolutional neural network (CNN) algorithm hybrid with capacitive sensors by Wael A. Altabey

“…The proposed method results converge with available traditional methods in the literature for assessing the delamination location/size such as the response surface methodology (RSM), and the error band from the diagonal line is less than 4.86 and 1.14 degrees for location and size respectively, thus validating the proposed technique's reliability, accuracy, and applicability for the relevant structures.…”
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Correctness Coverage Evaluation for Medical Multiple-Choice Question Answering Based on the Enhanced Conformal Prediction Framework by Yusong Ke, Hongru Lin, Yuting Ruan, Junya Tang, Li Li

“…Empirical results demonstrate that the enhanced CP framework achieves user-specified average (or marginal) error rates on the test set. Moreover, the results show that the test set’s average prediction set size (APSS) decreases as the risk level increases. …”
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Event-Based Visual/Inertial Odometry for UAV Indoor Navigation by Ahmed Elamin, Ahmed El-Rabbany, Sunil Jacob

“…Compared with the state-of-the-art U-SLAM algorithm, our approach achieves a substantial reduction in the mean positional error and RMSE in simulated environments, showing up to 50% and 47% reductions along the <i>x</i>- and <i>y</i>-axes, respectively. …”
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Prediction of instability of formwork concrete pier based on big data machine learning for secondary mining without coal pillar mining by Yanhui Zhu, Ye Tian, Peilin Gong, Kang Yi, Tong Zhao

“…A Gaussian process regression (GPR)-based stress prediction model was developed (optimal kernel: ARD-Rational-Quadratic-Kernel, with MSE = 1.3463, RMSE = 1.1603, MAE = 0.6138, and MAPE = 0.4041), demonstrating significantly higher accuracy than linear regression models (error reduced by 1–2 orders of magnitude) and BP neural networks (MSE = 2.0962). …”
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Adaptive-optical 3D microscopy for microfluidic multiphase flows by Clemens Bilsing, Erik Nützenadel, Sebastian Burgmann, Jürgen Czarske, Lars Büttner

“…We demonstrate that the adaptive optics correction is able to reduce this systematic error. Hence, the adaptive optics system can pave the way to a deeper understanding of water droplet formation and detachment which can help to improve the efficiency of fuels cells.…”
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Feasibility of EfficientDet-D3 for Accurate and Efficient Void Detection in GPR Images by Sung-Pil Shin, Sang-Yum Lee, Tri Ho Minh Le

“…Traditional methods of analyzing ground-penetrating radar (GPR) data are labor-intensive and error-prone. This study presents a novel approach using the EfficientDet-D3 deep learning model for automated void detection in GPR images. …”
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Gradient Boosting-Based Simultaneous Classification and Regression Approach by Rawabi Alwanin, Ouiem Bchir, Mohamed Maher Ben Ismail

“…The optimization of this dual task is formulated using a novel joint cost function that minimizes the total error of both classification and regression tasks during the learning phase. …”
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Leveraging Hybrid RF-VLP for High-Accuracy Indoor Localization with Sparse Anchors by Bangyan Lu, Yongyun Li, Yimao Sun, Yanbing Yang

“…Comprehensive experiments are performed to evaluate the performance of the positioning system, and the results show that the proposed system achieves an overall root mean square error (RMSE) of 26.1 cm, representing a 28.5% improvement in positioning accuracy compared to traditional RF-based positioning methods, which makes it highly feasible for deployment.…”
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A Novel Framework for Road Information Extraction From Low-Cost MMS Point Clouds by Baris Suleymanoglu, Metin Soycan

“…The results showed that the mean absolute error for longitudinal slope in the forward and return directions was 0.1% and 0.08%, respectively, while the cross-slope values exhibited deviations of 0.19% and 0.21% compared to the reference data. …”
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Student’s t Kernel-Based Maximum Correntropy Criterion Extended Kalman Filter for GPS Navigation by Dah-Jing Jwo, Yi Chang, Yun-Han Hsu, Amita Biswal

“…A fixed-point iterative algorithm is used for state update, and a new posterior error covariance expression is derived. The simulation results demonstrate that STMCCEKF outperforms conventional filters in positioning accuracy and robustness, particularly in environments with impulsive noise and multipath interference. …”
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Enhanced Pose Estimation for Badminton Players via Improved YOLOv8-Pose with Efficient Local Attention by Yijian Wu, Zewen Chen, Hongxing Zhang, Yulin Yang, Weichao Yi

“…The experimental results show that the proposed ELA-enhanced YOLOv8-Pose model consistently achieves superior accuracy across multiple evaluation metrics, including the mean squared error (MSE), object keypoint similarity (OKS), and percentage of correct keypoints (PCK), highlighting its effectiveness and potential for broader applications in sports vision tasks.…”
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A VMD-TCN-Based Method for Predicting the Vibrational State of Scaffolding in Super High-Rise Building Construction by Ping Zhu, Gen Liu, Jian Wang, Pengfei Wang

“…Compared to predictions using raw, undecomposed signals, the VMD-TCN model reduces the root mean square error (RMSE) by 43.9%, 43.2%, and 34.7% for 1 min, 3 min, and 5 min prediction tasks, respectively, while improving the coefficient of determination (R²) by 21.0%, 33.0%, and 37.6%. …”
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