An enhanced deep learning-based feature extraction framework for moving object detection by Upasana Panigrahi, Prabodh Kumar Sahoo, Manoj Kumar Panda, Aswini Kumar Samantaray, Ganapati Panda

“…The slow-moving object dataset achieved an average F-measure of 98.59% and an average misclassification error of 0.83. In the CD-Net 2014 dataset, the model achieved an average precision of 0.8886, an average recall of 0.8583, an average F-measure of 0.8500, and an average percentage of wrong classification error of 0.8200. …”
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Method for estimating non-measurable parameters of gas turbine engines considering variations in technical condition by Sergiy Yepifanov, Oleksii Bondarenko

“…Instead, it focuses on the direct estimation of non-measurable quantities, which reduces computational complexity and prevents error accumulation during calculation. The objective of the study is to develop a method that minimizes the estimation error of the target non-measurable parameter under the conditions of limited measurements, multicollinearity in the mathematical model, and varying measurement accuracy. …”
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Advanced hybrid machine learning models with explainable AI for predicting residual friction angle in clay soils by Mawuko Luke Yaw Ankah, Shalom Adjei-Yeboah, Yao Yevenyo Ziggah, Edmund Nana Asare

“…Various evaluation metrics, including coefficient of determination (R2), Root Mean Squared Error (RMSE), and Mean Absolute Error (MAE), were used to assess model performance. …”
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Study on Strength Prediction and Material Scheme Optimization for Modified Red Mud Based on Artificial Neural Networks by Qiaoling Ji, Xiuru Jia, Yingjian Wang, Yu Cheng

“…The results show that the BP neural network model has a high prediction accuracy, the relative prediction error is basically within 10%, the root-mean-squared error is less than 0.04, and the correlation coefficient is more than 0.99. …”
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Comparative Analysis of Different Interpolation Methods in Modeling Spatial Distribution of Monthly Precipitation by Yılmaz İçağa, Emin Taş

“…Then, uncertainty analysis by means of PSE (prediction standard error) is applied to SK-CK methods with clear advantages over the IDW method and with the close RMSE values. …”
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A probabilistic approach for building disease phenotypes across electronic health records by David Vidmar, Jessica De Freitas, Will Thompson, John M. Pfeifer, Brandon K. Fornwalt, Noah Zimmerman, Riccardo Miotto, Ruijun Chen

“…Probabilistic phenotypes built using LEVI exhibit low calibration error without the need for labels, allowing for better risk-benefit tradeoffs.…”
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Speaker-Independent Phoneme-Based Automatic Quranic Speech Recognition Using Deep Learning by Samah Al-Zaro, Mahmoud Al-Ayyoub, Osama Al-Khaleel

“…The performance of our model is evaluated using several proposed language models and evaluation metrics, including Word Error Rate (WER) and Phoneme Error Rate (PER). The goal is to show how our model would perform in regard to diverse reciter groups. …”
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Univariate Time Series Analysis of Short-Term Forecasting Horizons Using Artificial Neural Networks: The Case of Public Ambulance Emergency Preparedness by Tichaona W. Mapuwei, Oliver Bodhlyera, Henry Mwambi

“…This study examined the applicability of artificial neural network models in modelling univariate time series ambulance demand for short-term forecasting horizons in Zimbabwe. …”
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Indoor Drone 3-D Tracking Using Reflected Light From Floor Surfaces by Yusei Onishi, Hiroki Watanabe, Masanari Nakamura, Hiromichi Hashizume, Masanori Sugimoto

“…For a linear flight path, the error was 0.31 m. The computation time for 3-D position estimation was 1.12 s. …”
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Enhancing Gamma Knife Cone-beam Computed Tomography Image Quality Using Pix2pix Generative Adversarial Networks: A Deep Learning Approach by Prabhakar Ramachandran, Darcie Anderson, Zachery Colbert, Daniel Arrington, Michael Huo, Mark B Pinkham, Matthew Foote, Andrew Fielding

“…The sCT images were evaluated against ground truth CT scans using image quality assessment metrics, including the structural similarity index (SSIM), mean absolute error (MAE), root mean square error (RMSE), peak signal-to-noise ratio (PSNR), normalized cross-correlation, and dice similarity coefficient. …”
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An analytical examination of the performance assessment of CNN-LSTM architectures for state-of-health evaluation of lithium-ion batteries by Arun Jose, Sonam Shrivastava

“…Precisely determining the State of Health of Lithium-Ion Batteries is essential for maintaining their dependability, security, and durability in diverse applications such as electric vehicles and energy storage systems. …”
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Low-Complexity Ultrasonic Flowmeter Signal Processor Using Peak Detector-Based Envelope Detection by Myeong-Geon Yu, Dong-Sun Kim

“…The system can be involved in various IoT and industrial applications through high energy efficiency and real-time data transmission capabilities. …”
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Augmenting brain-computer interfaces with ART: An artifact removal transformer for reconstructing multichannel EEG signals by Chun-Hsiang Chuang, Kong-Yi Chang, Chih-Sheng Huang, Anne-Mei Bessas

“…We performed comprehensive validations using a wide range of open datasets from various BCI applications, employing metrics like mean squared error and signal-to-noise ratio, as well as sophisticated techniques such as source localization and EEG component classification. …”
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Deep learning based bio-metric authentication system using a high temporal/frequency resolution transform by Sajjad Maleki Lonbar, Akram Beigi, Nasour Bagheri, Nasour Bagheri, Pedro Peris-Lopez, Carmen Camara

“…The results from the NSRDB and MITDB datasets reflect the high reliability of the model, with exceptionally low error rates. This approach could be extended to other biometric modalities or combined with additional layers of security to enhance its practical applications. …”
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On the “Tantawy technique” and other methods for analyzing fractional Fokker–Plank type equations by Aljawhara H Almuqrin, CGL Tiofack, DV Douanla, A Mohamadou, Weaam Alhejaili, Sherif ME Ismaeel, Samir A El-Tantawy

“…The family of Fokker–Planck (FP) equations has been widely used in various physical applications, especially optical physics. It has proven effective in understanding numerous nonlinear phenomena observed in optical fiber. …”
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Subjective and Objective Quality Assessment of Image: A Survey by Pedram Mohammadi, Abbas Ebrahimi-Moghadam, Shahram Shirani

“…With the increasing demand for image-based applications, the efficient and reliable evaluation of image quality has increased in importance. …”
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High-Order Model-Based Robust Control of a Dual-Motor Steer-by-Wire System with Disturbance Rejection by Minhyung Kim, Insu Chung, Junghyun Choi, Kanghyun Nam

“…These results highlight the critical role of high-order modeling in the precision control of dual-motor SbW systems and suggest its applicability in real-time, safety-critical vehicle steering applications.…”
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Research on 3D Modeling Method of Tunnel Surrounding Rock Structural Planes Based on B-Spline Interpolation by Houxiang Liu, Yunxiang Liu, Ming Zhou, Longgang Liu, Jiang Liu, Zhiyong Liu, Hao Li, Pingtao Li

“…In model training and testing, the segmentation network achieved an F1 score of 94.01%, and the final modeling accuracy demonstrated a mean relative error (MRE) below 2.5%, confirming the reliability of the geometric reconstruction. …”
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NetCodeAIoT: Enhancing Augmented Intelligence of Things for Vehicle Systems in 5G Networks by Okuwudili Mathew Ugochukwu, Renata Lopes Rosa, Muhammad Saadi, Demostenes Z. Rodriguez, Frederico G. Guimaraes

“…NetCodeAIoT dynamically adjusts the sparsity level of the decoding matrix, implements unequal error protection network coding, and enables instantaneous decoding of data. …”
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A Study on the Extraction of Satellite Image Information for Two Types of Coastal Fishery Facility Fish Cages and Rafts Influenced by Clouds and Vessels by Ao Chen, Jialu Yu, Junbo Zhang, Gangyi Yu, Rong Wan

“…Extracting the area of fisheries facilities under the influence of clouds and vessels can provide better extraction accuracy and lower omission error. The MROIC model proposed in this study demonstrates high extraction accuracy and strong applicability, offering technical support for government planning in fishery facility areas and aiding in the risk assessment and management efficiency of fishery facility insurance.…”
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