Eccentricity Parameters Identification for a Motorized Spindle System Based on Improved Maximum Likelihood Method by Wengui Mao, Chaoliang Hu, Jianhua Li, Zhonghua Huang, Guiping Liu

“…This paper introduces an Advance-Retreat Method (ARM) of the search interval to the maximum likelihood method, the unknown parameter increment obtained by the maximum likelihood method is used as the step size in the iteration, and the Advance-Retreat Method of the search interval is used to adjust the next design point so that the objective function value is gradually decreasing. …”
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Reducing the Parameter Dependency of Phase-Picking Neural Networks with Dice Loss by Yongsoo Park, Gregory C. Beroza

“…Here, we test the Dice loss, which is a preferred loss function for highly imbalanced image segmentation problems. …”
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Optimization of particle filter tracking algorithm based on weakly supervised attribute learning by Hui Zhang, Dawang Shen

“…This method combines weakly supervised learning with energy function optimization to raise the efficiency of image feature annotation in object detection models. …”
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Optimal Collision Energy for Higgs Precision Measurements at the ILC250 by Maria Andrea Siddharta, Tian Junping

“…Afterwards, we will set up, in the framework of Effective Field Theories, a toy Lagrangian, and study the precision of anomalous couplings measurements at the energy points aforementioned. In order to do this, we will build up a chi-squared function at each energy point and look at their contours. …”
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Characterizing changes in the rate of protein-protein dissociation upon interface mutation using hotspot energy and organization. by Rudi Agius, Mieczyslaw Torchala, Iain H Moal, Juan Fernández-Recio, Paul A Bates

“…Our investigations show that, with the use of hotspot descriptors, energies from single-point alanine mutations may be used for the estimation of off-rate mutations to any residue type and also multi-point mutations. …”
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Dynamic reconstruction of electroencephalogram data using RBF neural networks by Xuan Wang, Congcong Du, Xianjin Ke, Jian Zhang, Zheng Zheng, Yayan Yue, Ming Yu

“…Importantly analysis of RBF network fixed-point coordinates revealed distinct age-related.DiscussionThese findings suggest that fixed-point coordinates of RBF networks can serve as quantitative markers aging providing new insights into age-dependent changes in brain dynamics. …”
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Study of High-cycle Fatigue Properties in Bovine Tibia Bones based on Reliability and Scatter-band Predictions by Mahshad Farzannasab, Mohammad Azadi, Hamed Bahmanabadi

“…In this article, the scatter-band and the reliability response of bovine tibia bones were predicted in the load-controlled fatigue condition. The one-point rotary-bending fatigue machine was utilized to carry out standard tests at two different loading levels, 0.4 and 0.6 kg for three various loading frequencies, 10, 20 and 30 Hz for tibia bones. …”
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The Impact of Exercise Training on the Brain and Cognition in Type 2 Diabetes, and its Physiological Mediators: A Systematic Review by Jitske Vandersmissen, Ilse Dewachter, Koen Cuypers, Dominique Hansen

“…Abstract Background Type 2 diabetes (T2DM) affects brain structure and function, and is associated with an increased risk of dementia and mild cognitive impairment. …”
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Deep learning-based semantic segmentation for rice yield estimation by analyzing the dynamic change of panicle coverage by Hyeok-Jin Bak, Eun-Ji Kim, Ji-Hyeon Lee, Sungyul Chang, Dongwon Kwon, Woo-Jin Im, Woon-Ha Hwang, Jae-Ki Chang, Nam-Jin Chung, Wan-Gyu Sang

“…This process distilled key predictive parameters: K (maximum panicle coverage), g (growth rate), d0 (time of maximum growth rate), a (decline rate), and d1 (transition point). These parameters served as predictors in four machine learning regression models (PLSR, RFR, GBR, and XGBR) to estimate yield and its components.ResultsIn panicle segmentation, DeepLabv3+ and LinkNet achieved superior performance (mIoU > 0.81). …”
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Four-Dimensional Path Planning Methodology for Collaborative Robots Application in Industry 5.0 by Ilias Chouridis, Gabriel Mansour, Vasileios Papageorgiou, Michel Theodor Mansour, Apostolos Tsagaris

“…The safety value of dynamic obstacles, the coefficients of the importance of the terms of the agent’s distance to the ending point, and the safety value of dynamic obstacles were introduced in the objective function. …”
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Exploring the Relationship between Spatiotemporal Distribution of Urban Vibrancy and Neighborhood Attributes by Coupling Multi-Source Data: A Case of Nanshan District in Shenzhen by Liu Feng, Tang Zhong, Zhang Liang, Yu Lingmin, Liu Ke

“…Evidently, employment and commuting activities have a ripple effect on economic urban vibrancy throughout the center of the administrative district, making weekday vibrancy surpass that of weekend; 2) Variance of the spatiotemporal distribution of urban vibrancy is improved or inhibited by the characteristic factors, among which, the entertainment function plays a major role as the driving force; additionally, enclosure, Point Of Interest (POI) diversity, road density, and building density have promoting effects on the overall urban vibrancy. …”
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A Dataset for Investigations of Amine-Impregnated Solid Adsorbent for Direct Air Capture by Eryu Wang, Liping Luo, Jiachuan Wang, Jiaxin Dai, Shuangyin Li, Lei Chen, Jia Li

“…Abstract Amine-impregnated solid adsorbents are widely explored for point source capture and direct air capture (DAC) to address climate change. …”
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Research on the optimization method of inventory management of important spare parts of intercity railway. by Dongyan Wang, Ying Sun, Liang Yu, Kun Shen, Junbo Li, Xia Wu

“…To enhance the reliability of intercity railway operations and reduce spare parts management costs, this paper employs the Zebra Optimization Algorithm-Least Squares Support Vector Machine (ZOA-LSSVM) to analyze the reliability of the important Weibull distribution spare parts of the intercity railway and fit the parameters of the reliability function for spare parts. …”
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Digitalization of the planning system at mechanical engineering enterprises: results, problems, prospects by Fomin Semyon, Ermakova Zhanna

“…The study is useful for managers and specialists of machine-building holdings in the functions of planning, production, development, information technology (IT); as well as employees of IT and consulting companies that develop and implement planning systems in the digital environment.…”
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A convolutional neural network model and algorithm driven prototype for sustainable tilling and fertilizer optimization by Sajeev Magesh

“…This paper evaluates whether optimizing tillage intensity, timing, and fertilizer quantity using a convolutional neural network model and algorithm will address these problems. The machine learning model utilizes a camera-captured field image to determine existing tilling intensity on a 7-point scale. …”
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Method for assessing the obsolescence of manufacturing equipment based on the triple bottom line by Marcelo Niehues Schlickmann, João Carlos Espíndola Ferreira, Abner do Canto Pereira

“…Originality This paper describes a novel method that allows a complete evaluation of the state of use of a machine, besides the traditional economic-functional analysis, as well as its application in a large electric machines manufacturing company. …”
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A data-driven cost estimation model for agile development based on Kolmogorov-Arnold Networks and AdamW optimization by Xiaoyan Zhao, Xin Xiong, Zulkefli Mansor, Rozilawati Razali, Mohd Zakree Ahmad Nazri, Liangyu Li

“…Experimental results demonstrate that the proposed KAN-AdamW model achieves superior performance, with a Mean Absolute Error (MAE) of 11,504.08 and a Mean Relative Error (MRE) of 0.12-outperforming traditional Artificial Neural Networks (ANN) and function point-based models. The model also shows strong performance in accuracy and R-squared metrics, indicating high predictive stability and precision. …”
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The impact of direct and indirect digital soil mapping approaches on spatial uncertainty by Gábor Szatmári, László Pásztor

“…Such questions were examined on the example of mapping soil organic carbon (SOC) in the Great Hungarian Plain, Hungary, by combining machine learning with univariate and multivariate geostatistics. …”
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Transcriptional regulation of lineage commitment--a stochastic model of cell fate decisions. by Jose Teles, Cristina Pina, Patrik Edén, Mattias Ohlsson, Tariq Enver, Carsten Peterson

“…Molecular mechanisms employed by individual multipotent cells at the point of lineage commitment remain largely uncharacterized. …”
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Influence of Surface Treatment on Strength Distribution of Vita VMK 68 Dental Porcelains by Serkan Nohut, Ahmet Tasdemir, Suleyman Aykut Korkmaz

“…However, it is still unclear whether the Weibull distribution function is the most appropriate function for fitting the strength data of dental ceramics with different surface treatments. …”
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