Adaptive Voxel-Division Method of GNSS Water Vapor Tomography and Its Application in Data Assimilation by Yongjie Ma, Qingzhi Zhao, Duoduo Jiang, Wanqiang Yao, Yibin Yao, Jinfang Yin, Hongwu Guo, Yuan Zhai, Ying Xu, Ruikun Wang, Qingfang Chen, Jingyu Zhang

“…The average improvement rate of the root-mean-square error (RMSE) in the water vapor profile ranges from 10.6% to 48.7%, while that in the integrated water vapor is 19.0–42.9% . …”
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Data‐Driven Theoretical Modeling of Centrifugal Step Emulsification and Its Application in Comprehensive Multiscale Analysis by Xin Wang, Xiaolu Cai, Chao Wan, Huijuan Yuan, Shunji Li, Yiwei Zhang, Ran Zhao, Yuxi Qin, Yiwei Li, Bi‐Feng Liu, Peng Chen

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The application of blockchain with a comparative approach and its impact on risk, flexibility and internal control evaluation by mohammadsadegh aminipoor, HamidReza GholamniaRoshan, azadeh kiapour, Iman Dadashi

“…Abstract The purpose of the current research is the application of blockchain with a comparative approach of its effect on risk, flexibility and evaluation of internal control. …”
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PENERAPAN STANDAR PROSEDUR OPERASIONAL DENGAN SISTEM APLIKASIPENERBITAN POLIS ASURANSI JIWA SYARIAH KUMPULAN PT XYZ by LUkman Anthoni

“…This is certainly to reduce errors, say human error and improve the effectiveness and efficiency of the Company's operations. …”
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An enhanced buck-boost converter for photovoltaic diagnosis application: Accurate MPP tracker and I-V tracer by Yassine Chouay, Mohammed Ouassaid

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Combined application of FTAN and cross-spectra analysis to ambient noise recorded by a microseismic monitoring network by Ilaria Barone, Alessandro Brovelli, Giorgio Tango, Sergio Del Gaudio, Giorgio Cassiani

“…It was shown that using a one-year time window these errors are reduced to 0.3%.…”
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Deep learning-based dual monitoring system for power forecasting and fault detection in nuclear power applications by Mingzhe Lyu, Helin Gong, Zhang Chen, Jiangyu Wang, Mingxiao Zhong, Zhiyong Wang, Qing Li, Zefei Pan

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On Joint Progressively Censored Gumbel Type-II Distributions: (Non-) Bayesian Estimation with an Application to Physical Data by Mustafa M. Hasaballah, Mahmoud E. Bakr, Oluwafemi Samson Balogun, Arwa M. Alshangiti

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Effectiveness of smartphone technology for detection of paediatric ocular diseases—a systematic review by Sruthi Vijendran, Yash Alok, Neetha I. R. Kuzhuppilly, Jayasheela R. Bhat, Yogish S. Kamath

“…Twelve smartphone applications assessed refractive errors using visual acuity tests or photorefraction, five detected amblyogenic risk factors, six identified strabismus, and three targeted leukocoria. …”
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Structural Damage Identification Using PID-Based Search Algorithm: A Control-Theory Inspired Application by Kuang Shi, Tingting Sun

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DIFFERENTIATION OF POLYNOMIALS IN SEVERAL VARIABLES OVER GALOIS FIELDS OF FUZZY CARDINALITY AND APPLICATIONS TO REED-MULLER CODES by V. M. Deundyak, N. S. Mogilevskaya

“…The proposed scheme feature is that it enables to protect data, both from the nonlegitimate access, and from unintentional errors; herewith, one  and  the  same  mathematical  apparatus  is  used  in  both cases. …”
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A novel hybrid CLARA and fuzzy time series Markov chain model for predicting air pollution in Jakarta by Nurtiti Sunusi, Ankaz As Sikib, Sumanta Pasari

“…Forecasting accuracy results for SO₂ and CO in Jakarta, based on Mean Absolute Error (MAE) and Root Mean Square Error (RMSE), showed excellent performance, underscoring the efficacy of the CLARA-FTSMC hybrid approach in predicting air pollution levels. • The CLARA-FTSMC hybrid method demonstrates high effectiveness in analyzing large datasets, addressing the limitations of previous hybrid clustering fuzzy time series methods. • The number of fuzzy time series partitions is optimally determined based on clustering results obtained through the gap statistic approach, ensuring robust partitioning. • The forecasting accuracy of the CLARA-FTSMC hybrid method, evaluated using MAE and RMSE, showed excellent performance in predicting daily air pollution levels of SO₂ and CO in Jakarta.…”
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Practical techniques for high-precision measurements on near-term quantum hardware and applications in molecular energy estimation by Keijo Korhonen, Hetta Vappula, Adam Glos, Marco Cattaneo, Zoltán Zimborás, Elsi-Mari Borrelli, Matteo A. C. Rossi, Guillermo García-Pérez, Daniel Cavalcanti

“…Abstract Achieving high-precision measurements on near-term quantum devices is critical for advancing quantum computing applications. Quantum computers suffer from high readout errors, making quantum simulations with high accuracy requirements particularly challenging. …”
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The Parameter-Optimized Recursive Sliding Variational Mode Decomposition Algorithm and Its Application in Sensor Signal Processing by Yunyi Liu, Wenjun He, Tao Pan, Shuxian Qin, Zhaokai Ruan, Xiangcheng Li

“…The PO-RSVMD algorithm optimizes RSVMD in the following two ways: First, an iterative termination condition based on modal component error mutation judgment is introduced to prevent over-decomposition. …”
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Optimizing Rotary Cement Kiln modelling: A comparative analysis of metaheuristics in a real-world application by Miguel Ángel Castán-Lascorz, Antonio Alcaide-Moreno, Jorge Arroyo

“…This study introduces a real-world metaheuristic application designed to minimize the simulation errors of a novel one-dimensional (1D) numerical model of a rotary cement kiln, calibrated by Computational Fluid Dynamics (CFD) results. …”
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Research on a Quality Control Method for L Band Second-Level Radiosonde toward Assimilation Applications by Dan WANG, Jincheng WANG, Weihong TIAN

“…Since 2003， the World Meteorological Organization （WMO） proposed and coordinated a switch from traditional radiosonde format （TAC code） to second-resolution binary （BUFR） report， which leads the assimilation of second radiosonde data in numerical prediction model becoming the future trend.Data quality control is a key and basic work before assimilation application.In addition， the observational error characteristics of Lband second-level radiosonde are significantly different from that of conventional radiosonde.Therefore， a two-step quality control method for assimilation application is developed in this paper.The first step integrates conventional radiosonde quality control procedures and inserts several additional steps according to the data characteristics of second-level radiosonde， which aims at eliminating human-observation errors as much as possible.The second step introduces a dynamic blacklist checking module into the assimilation system， at the same time remaining the old OMB （observation minus background） check method， so as to control the representative deviation between the observation and the model background.By comparing and analyzing the statistical characteristics of the observation samples before and after the quality control procedure， and combining them with the actual assimilation analysis results of the NWP model， the rationality of the two-step quality control procedure has been comprehensively verified.It reveals that the data anomaly is greatly reduced after the two-step quality control procedure， at the same time the OMB is closer to a Gaussian distribution.Moreover， the validity of data assimilation is enhanced leading to a better assimilation analysis effect.The work lays a foundation for the future operational application of L-band second-level radiosonde data in GRAPES （Global/Regional Assimilation and Prediction System） model.…”
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Selection of appropriate multispectral camera exposure settings and radiometric calibration methods for applications in phenotyping and precision agriculture by Vaishali Swaminathan, J. Alex Thomasson, Robert G. Hardin, Nithya Rajan, Rahul Raman

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Development of machine learning-based standalone GUI application for predicting hydraulic conductivity and compaction parameters of lateritic soils by Lateef Bankole Adamolekun, Muyideen Alade Saliu, Abiodun Ismail Lawal, Ismail Adeniyi Okewale

“…The models’ performance was compared using coefficient of determination (R2), root mean squared error (RMSE), mean absolute percentage error (MAPE) and mean absolute error (MAE). …”
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Applicability Analysis of Reduced-Order Methods with Proper Orthogonal Decomposition for Neutron Diffusion in Molten Salt Reactor by Zhengyang Zhou, Ming Lin, Maosong Cheng, Yuqing Dai, Xiandi Zuo

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Research on Multi-Factor Coastal Waterway Depth Prediction and Application Based on Attention-Enhanced LSTM Model by LING Ganzhan, HAN Yu, WANG Jiawei, JIE Weiwei, TANG Ruikai, HU Jiakai, LIU Xiang, LIANG Guangyue, CAO Lu, LIANG Ming

“…Compared to the traditional model, the MAE error is reduced by 65%–72%, and the R² coefficient increases by 2.2%–5.6%, demonstrating superior predictive accuracy and stability. …”
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