Gap-filling of land surface temperature in arid regions by combining Landsat 8 and 9 imageries by Fahime Arabi Aliabad, Ebrahim Ghaderpour, Ahmad Mazidi, Fatemeh Houshmandzade

“…In method one, the root mean square error (RMSE) of reconstructed LST reduces by 1.3 °C when using the combined Landsat 8 and 9 images. …”
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Research on Shale Oil Well Productivity Prediction Model Based on CNN-BiGRU Algorithm by Yuan Pan, Xuewei Liu, Fuchun Tian, Liyong Yang, Xiaoting Gou, Yunpeng Jia, Quan Wang, Yingxi Zhang

“…Hyperparameter optimization via grid searching yielded optimal configurations, while field applications demonstrated operational feasibility. Comparative analysis revealed a mean relative error (MRE) of 16.11% between predicted and observed production values, substantiating the model’s predictive competence. …”
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General Framework for Georeferencing and Interpretation of Multi-Resolution LiDAR Data for Fine-Scale Forest Inventory by H. Hanafy, S.-Y. Shin, A. M. Eissa, Y. Hany, S. Park, S. Fei, A. Habib

“…The proposed approach is evaluated in a plantation, demonstrating an F1-score of 100% for tree detection and a 3.1 cm root mean square error (RMSE) for DBH estimation. The results highlight the reliability of the proposed framework for accurately detecting trees and estimating their DBH. …”
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Elastoplastic constitutive model considering the filling and cementation effects for gas hydrate-bearing sediments: development and finite element implementation by Qingmeng Yuan, Qingmeng Yuan, Qingmeng Yuan, Qianyong Liang, Qianyong Liang, Jinqiang Liang, Jinqiang Liang, Zhigang Wang, Zhigang Wang, Lin Yang, Lin Yang, Xuemin Wu, Xuemin Wu, Binbin Guo, Binbin Guo, Yifei Dong, Yifei Dong

“…Based on the user-defined subroutine interface provided by ABAQUS and the modified Euler integral algorithm with error control, the user-defined subroutine (UMAT) is embedded in ABAQUS to implement the finite element model. …”
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DSM-Based Precise Pointing Angle Deviation Measurement Method for Beaconless Free Space Optical Communication by Xueyuan Ao, Yansheng Zou, Yang Zou, Qirun Fan, Xiaoxiao Dai, Chen Liu, Qi Yang, Deming Liu

“…The root means square error (RMSE) of the pointing angle deviation measurement is 14.17 μrad with the incident optical power of −40 dBm. …”
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Prevalence and predictors of unsuccessful tuberculosis treatment outcomes among persons with TB/HIV co-infection in Ghana: a 10-year retrospective study by Alhaji Ibrahim Cobbinah, Jacob Solomon Idan, Kingsley Boakye, Anthony Enimil, Nicholas Karikari Mensah, Ebenezer Adangabe, Sulemana Baba Abdulai, Charles Martyn-Dickens, Aliyu Mohammed

“…Modified Poisson regression with robust standard errors was performed using Stata version 17.0 to identify predictors of unsuccessful outcomes. …”
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An adaptive dual distillation framework for efficient remaining useful life prediction by Xiang Cheng, Jun Kit Chaw, Shafrida Sahrani, Mei Choo Ang, Saraswathy Shamini Gunasekaran, Moamin A. Mahmoud, Halimah Badioze Zaman, Yanfeng Zhao, Fuchen Ren

“…A-DDF outperforms previous methods, achieving a 12% decrease in relative error (MAPE), improving prediction accuracy and stability. …”
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Touch of Privacy: A Homomorphic Encryption-Powered Deep Learning Framework for Fingerprint Authentication by U. Sumalatha, K. Krishna Prakasha, Srikanth Prabhu, Vinod C. Nayak

“…The system, utilizing Euclidean similarity, achieves 99.06% test accuracy with a loss of 0.1692, a True Acceptance Rate (TAR) of 99.19%, a False Rejection Rate (FRR) of 0.81%, a False Acceptance Rate (FAR) of 0%, and a True Rejection Rate (TRR) of 100%, with a minimal Equal Error Rate (EER) of 0.40%. Encrypted templates require only 31 MB for 90 users, averaging 344 KB per fingerprint per user. …”
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Solving the problem of power ripples for a multi-rotor wind turbine system using fractional-order third-order sliding mode algorithms by Habib benbouhenni, Adil Yahdou, Abdelkadir Belhadj Djilali, Nicu Bizon, Ilhami Colak, Z. M. S. Elbarbary, Muneer Parayangat

“…This research confirms the effectiveness and efficiency of the proposed approach in renewable energy applications. It promotes the most efficient and sustainable energy solutions, making it a promising solution in other industrial applications.…”
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Toward automated plantar pressure analysis: machine learning-based segmentation and key point detection across multicenter data by Carlo Dindorf, Jonas Dully, Steven Simon, Dennis Perchthaler, Stephan Becker, Hannah Ehmann, Christian Diers, Christoph Garth, Michael Fröhlich

“…Furthermore, regression-based approaches generated higher errors in key point detection of the interdigital space 2–3 (Median Euclidean distance = 10.06) than in metatarsal area 1 center (Median Euclidean distance = 7.72). …”
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A Study of NOAA-20 VIIRS Band M1 (0.41 µm) Striping over Clear-Sky Ocean by Wenhui Wang, Changyong Cao, Slawomir Blonski, Xi Shao

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Accurate scoliosis vertebral landmark localization on X-ray images via shape-constrained multi-stage cascaded CNNs by Zhiwei Wang, Jinxin Lv, Yunqiao Yang, Yi Lin, Qiang Li, Xin Li, Xin Yang

“…Vertebral landmark localization is a crucial step in various spine-related clinical applications, which requires detecting the corner points of 17 vertebrae. …”
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Image Transmission Utilizing Amplitude Modulation in Rydberg Atomic Antenna by Peng Zhang, Shaoxin Yuan, Mingyong Jing, Jinpeng Yuan, Hao Zhang, Linjie Zhang

“…The pixel information of the color image obtained by atomic demodulation realizes the high-fidelity digital color image transmission, with a root mean square error of 4.806, a mean square signal-to-noise ratio of 1.627, a peak signal-to-noise ratio of 29.998 and a structural similarity index of 0.9589. …”
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Improvised Spectral Efficiency and Channel Estimation Parameters in Visible Light Vehicular Communication by Integrating Simulation of Urban Mobility Data by Ali H. Wheeb, Sudhanshu Maurya, Shaik Karimullah, Fahimuddin Shaik, Subrata Chowdhury, B. V. V. Siva Prasad, Anurag Sinha, Adamya Sood, Syed Abid Hussain

“…Additionally, a mathematical framework is developed to evaluate the impact of vehicular mobility on spectral efficiency and bit error rate (BER) performance across different QAM modulation schemes. …”
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Machine learning model for predicting corneal stiffness and identifying keratoconus based on ocular structures by Longhui Li, Yifan Xiang, Xi Chen, Duoru Lin, Lanqin Zhao, Jun Xiao, Zhenzhe Lin, Jianyu Pang, Xiaotong Han, Lixue Liu, Yuxuan Wu, Zhenzhen Liu, Jingjing Chen, Jing Zhuang, Keming Yu, Haotian Lin

“…Eleven features, including ocular structural parameters, intraocular pressure (IOP), and age were used to train ML regression models for predicting the stiffness parameter at first applanation (SP-A1) and the Corvis biomechanical index for Chinese populations (cCBI) measured by a Corvis ST device. Mean absolute errors (MAEs) and the area under the receiver operating characteristic curve (AUC) were used to evaluate the performance of the models. …”
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Leveraging advanced deep learning and machine learning approaches for snow depth prediction using remote sensing and ground data by Haytam Elyoussfi, Abdelghani Boudhar, Salwa Belaqziz, Mostafa Bousbaa, Karima Nifa, Bouchra Bargam, Abdelghani Chehbouni

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Enhancing Communication Security in Drones Using QRNG in Frequency Hopping Spread Spectrum by J. de Curtò, I. de Zarzà, Juan-Carlos Cano, Carlos T. Calafate

“…Our method introduces a concurrent access protocol for multiple drones to share a QRNG device efficiently, incorporating robust error handling and a shared memory system for random number distribution. …”
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Chronic Kidney Disease Prediction Based On Machine Learning Algorithms by Kethineni Likitha., Nithinchandra, Kumar Narendra, Sk Sajida Sultana.

“…KNN Basic model obtained a root mean square error of 0.5007 with an accuracy of 44.50. The NMF model gave a better result than the first one with RMSE 0.4999 and accuracy 51.50. …”
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Impact of sensorimotor mismatch on virtual reality sickness and user experience: age-related differences in a randomized trial by Elisabeth Jochmann, Thomas Jochmann, Maximilian Weber, Karolin Weigel, Carsten Klingner

“…However, the Mismatch group reported higher levels of exhaustion and frustration compared to the Error-based and Errorless groups, indicating the impact of cognitive strain and task difficulty on user experience. …”
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Performance of Plug-In Augmented ChatGPT and Its Ability to Quantify Uncertainty: Simulation Study on the German Medical Board Examination by Julian Madrid, Philipp Diehl, Mischa Selig, Bernd Rolauffs, Felix Patricius Hans, Hans-Jörg Busch, Tobias Scheef, Leo Benning

“…Additionally, we conducted an analysis to assess how the models justify their answers, the accuracy of their responses, and the error structure of their answers. Bootstrapping and CIs were used to evaluate the statistical significance of our findings. …”
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