Impact of Correlated Measurement Errors on Some Efficient Classes of Estimators by Anoop Kumar, Shashi Bhushan, Shivam Shukla, Walid Emam, Yusra Tashkandy, Rajesh Gupta

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Estimation of Unknown Object Measures in a Chemical Weighing Design with Correlated Errors by Małgorzata Graczyk, Bronisław Ceranka

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Improving the efficiency of learning-based error mitigation by Piotr Czarnik, Michael McKerns, Andrew T. Sornborger, Lukasz Cincio

“…Error mitigation will play an important role in practical applications of near-term noisy quantum computers. …”
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Study of the interval width of features for improving forecasting efficiency of the transport flow intensity by I. N. Pugachev, N. G. Sheshera, D. Yе. Grigorov

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Kendallknight: An R package for efficient implementation of Kendall's correlation coefficient computation. by Mauricio Vargas Sepulveda

“…The kendallknight package introduces an efficient implementation of Kendall's correlation coefficient computation, significantly improving the processing time for large datasets without sacrificing accuracy. …”
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Estimation of Filtration Efficiency – from Simple Correlations to Digital Fluid Dynamics by Przekop Rafał

“…The classical theory of depth filtration of aerosol particles in fibrous structures is based on the assumption of existing single fibre efficiency, which may be used to recalculate the overall efficiency of entire filter. …”
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Energy-Efficient Node Selection Algorithms with Correlation Optimization in Wireless Sensor Networks by Hongju Cheng, Zhihuang Su, Daqiang Zhang, Jaime Lloret, Zhiyong Yu

“…The sensing data of nodes is generally correlated in dense wireless sensor networks, and the active node selection problem aims at selecting a minimum number of nodes to provide required data services within error threshold so as to efficiently extend the network lifetime. …”
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Correlation of Calibration Parameters for HPGe Detector Efficiency Based on Monte Carlo Simulation by LI Yan1, SHAN Chenyu2, GU Weiguo1, WANG Dezhong1

“…This study provides a practical method for correcting detection efficiency errors caused by variations in crystal diameter, offering a more efficient approach to calibrating HPGe detectors for radioactive waste measurements.…”
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Efficient Multipath Mitigation in GNSS Using Dynamic Selection and Weighting of Early-Late Correlators by Ayoub Bengherabi, Mustapha Flissi, Khaled Rouabah, Salim Attia, Diana W. Dawoud, Yassine Himeur, Shadi Atalla, Wathiq Mansoor

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Velocity Errors Associated with Application of Inertial Methods for Detecting Rail Surface Short-Wavelength Irregularities by A. V. Bolshakova, A. M. Boronahin, D. Yu. Larionov, L. N. Podgornaya, A. N. Tkachenko, R. V. Shalymov, E. D. Churyaev

“…The implemented correlation analysis allows compensation of high-velocity errors when determining the defects. …”
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Novel efficient estimators of finite population mean in simple random sampling by Khazan Sher, Muhammad Iqbal, Hameed Ali, Soofia Iftikhar, Maggie Aphane, Ahmed Audu

“…A rigorous theoretical examination is conducted, deriving first-order bias and Mean Square Error (MSE) expressions to elucidate the estimators' properties. …”
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Research and Application on Automatic Stratigraphic Sequence Division and Comparison Method Based on Integrated Prediction Error Filter Analysis by NING Weifeng, WANG Caizhi, JIANG Qingchun, LIU Yingming, WANG Hao, WEI Xingyun, LIN Yaoqiang

“…Combined with the derivative dynamic time warping algorithm and dynamic programming method for multi-well sequence stratigraphic correlation, a set of automatic sequence stratigraphic division and correlation methods is proposed. …”
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TransformerPayne: Enhancing Spectral Emulation Accuracy and Data Efficiency by Capturing Long-range Correlations by Tomasz Różański, Yuan-Sen Ting, Maja Jabłońska

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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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Process Reliability Evaluation Method of Turning Large Pitch External Thread by JIANG Bin, WANG Sen, LI Zhe, ZHANG Wei, WU Pei-jun

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Some ratio type predictive estimators for estimation of the average water level of a river using season as an auxiliary attribute by Muhammad Rafaqat, Hina Khan

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Audit experiences in investigational medicinal product management and errors in clinical trials by Yunjeong Kim, Heeyoung Lee

“…To address these issues, clinical trial systems should implement regular error monitoring, standardized procedures, and comprehensive staff training to ensure safer and more efficient trials.…”
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SAR Observation Error Estimation Based on Maximum Relative Projection Matching by Y. Zhang, B. P. Wang, Y. Fang, Z. X. Song

“…First, the method estimates the precise position parameters of the reference position by the sparse reconstruction method of joint error parameters. Second, a relative error estimation model is constructed based on the maximum correlation of base-space projection. …”
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Physics-based parameters selection and machine learning driven prediction of pool boiling bubble departure diameter by Uzair Sajjad, Yu-Hao Chu, Haseeb Yaqoob, Akash Sengupta, Hafiz Muhammad Ali, Khalid Hamid, Wei-Mon Yan

“…A comparison was also done to the existing correlations and it was found that neural networks have much better efficiency and accuracy than the empirical correlations for the considered data range and thus can be an essential tool to predict the bubble diameter.…”
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Lightweight error-tolerant edge detection using memristor-enabled stochastic computing by Lekai Song, Pengyu Liu, Jingfang Pei, Yang Liu, Songwei Liu, Shengbo Wang, Leonard W. T. Ng, Tawfique Hasan, Kong-Pang Pun, Shuo Gao, Guohua Hu

“…By integrating memristors into compact logic circuits, we realise lightweight stochastic logics for stochastic number encoding and processing with well-regulated probabilities and correlations. This stochastic and probabilistic computational nature allows the stochastic logics to perform edge detection in edge visual scenarios characterised by high-level errors. …”
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