Random First-Order Linear Discrete Models and Their Probabilistic Solution: A Comprehensive Study by M.-C. Casabán, J.-C. Cortés, J.-V. Romero, M.-D. Roselló

“…The study is based on Random Variable Transformation method. The obtained results are given in terms of the probability density functions of the data, namely, initial condition, forcing term, and diffusion coefficient. …”
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Prox-STA-LSTM: A Sparse Representation for the Attention-Based LSTM Networks for Industrial Soft Sensor Development by Yurun Wang, Yi Huang, Dongsheng Chen, Longyan Wang, Lingjian Ye, Feifan Shen

“…For deep learning based soft sensors, the spatiotemporal attention (STA)-LSTM is a newly emerged technique which provides efficient predictions for quality variables of industrial processes. …”
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Active RIS-NOMA Uplink in URLLC, Jamming Mitigation via Surrogate and Deep Learning by Ghazal Asemian, Mohammadreza Amini, Burak Kantarci

“…The complexity of the optimization problem, involving numerous interacting variables, leads us to develop a deep regression model to predict optimal network configurations, providing a computationally efficient approach as well as reducing the signaling overhead. …”
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Dimensions-Reduced Volterra Digital Pre-Distortion Based On Orthogonal Basis for Band-Limited Nonlinear Opto-Electronic Components by Hananel Faig, Yaron Yoffe, Eyal Wohlgemuth, Dan Sadot

“…However, naive implementation of the Volterra polynomial model usually introduces significant complexity due to the large number of model coefficients. Here, we propose the use of orthogonal polynomial basis functions for efficient DPD implementation. …”
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PENGARUH MUTASI TERHADAP SEMANGAT KERJA PEGAWAI NEGERI SIPIL PADA KANTOR PELAYANAN PAJAK PRATAMA KOTA PEMATANG SIANTAR by Arnimisari Juliana Ambarita, Hatta Ridho

“…The data processed by the correlation coefficient and the determinant Moment Product to see the great influence of the variable X against Y variable. …”
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A nomogram for diagnosis of BI-RADS 4 breast nodules based on three-dimensional volume ultrasound by Xianping Jiang, Chen Chen, Jincao Yao, Liping Wang, Chen Yang, Wei Li, Di Ou, Zhiyan Jin, Yuanzhen Liu, Chanjuan Peng, Yifan Wang, Dong Xu

“…Abstract Objectives The classification of malignant breast nodules into four categories according to the Breast Imaging Reporting and Data System (BI-RADS) presents significant variability, posing challenges in clinical diagnosis. …”
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Fuzzy rank fusion of deep neural networks for weed identification in groundnut crop by Akshay Dheeraj, Rajnish Kumar Chaturvedi, Sapna Nigam, Md. Ashraful Haque, Sudeep Marwaha

“…By combining selective and variable rate spraying, the smart herbicide sprayer effectively manages herbicide amounts. …”
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Multivariate predictive modeling of compressive strength in ground granulated blast furnace slag/fly ash-based alkali-activated concrete by Dina A. Emarah

“…Using a comprehensive dataset of 1590 samples with 14 input variables, it captures the complex, multi-variable dependencies affecting AAC's mechanical behavior. …”
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Inversion and validation of soil water-holding capacity in a wild fruit forest, using hyperspectral technology combined with machine learning by Tingwei Song, Liang Guo, Qian Sun, Guizhen Gao, Jing Chen, Qikun Zhang

“…The results revealed a significant negative correlation between SWHC and the smoothed leaf spectral reflectance, with the best correlation coefficient was r = − 0.59. The use of third-order derivatives and logarithmic second-order derivatives further enhanced this correlation, yielding optimal coefficients of r = − 0.78 and r = − 0.72, respectively. …”
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Estimating Daily Rice Crop Evapotranspiration in Limited Climatic Data and Utilizing the Soft Computing Algorithms MLP, RBF, GRNN, and GMDH by Pouya Aghelpour, Hadigheh Bahrami-Pichaghchi, Farzaneh Karimpour

“…The ETc rates were calculated by seven meteorological variables, the FAO-56 Penman-Monteith equation, and the regional calibrated rice crop coefficient and considered as the reference data. …”
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Enhancing Thermal–Hydraulic Performance in Nuclear Reactor Subchannels with Al₂O₃ Nanofluids: A CFD Analysis by Mohammad A. I. Sardar, Mushfiqur Rahman, Philip Rubini

“…This analysis has been carried out using the RNG k-epsilon turbulence model with standard wall function in ANSYS FLUENT 2022R1. The impact of various flow conditions and nanofluid concentrations has been examined. …”
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First-principles investigation on structural, electronic, and optical properties of (Cd1-xZnx)3As2 by Yu Deng, Xun Ge, Rongxiu Feng, Yunye Liang, Xiaohao Zhou

“…Calculations on the optical properties (dielectric function, absorption coefficient) of (Cd1-xZnx)3As2 show that it behaves well in the near infrared and far infrared. …”
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Mt or not Mt: Temporal variation in detection probability in spatial capture-recapture and occupancy models by Sollmann, Rahel

“…SCR model estimates of abundance, the density-covariate coefficient β and the movement-related scale parameter of the detection function σ were robust to ignoring temporal variation in detection, with relative bias, CV and RMSE of the two models generally being within 4% of each other. …”
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Spatial dependencies between large-scale brain networks. by Robert Leech, Gregory Scott, Robin Carhart-Harris, Federico Turkheimer, Simon D Taylor-Robinson, David J Sharp

“…Many studies show a temporal relationship between task positive and task negative networks that is important for efficient cognitive functioning. Here we provide evidence for a spatial relationship between task positive and negative networks. …”
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Enhanced prediction of heating value of municipal solid waste using hybrid neuro-fuzzy model and decision tree-based feature importance assessment by Oluwatobi Adeleke, Obafemi O. Olatunji, Tien-Chien Jen, Iretioluwa Olawuyi

“…To this end, the feature importance analysis of MSW input variables was carried out using the decision tree regressor with the Gini importance (GI) metrics to identify the most influential variable. …”
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Associations between milk infrared-predicted plasma biomarkers of stress resilience and fertility in dairy cattle: Insights for enhancing breeding programs and herd management by Alessio Cecchinato, Hugo Toledo-Alvarado, Lucio Flavio Macedo Mota, Vittoria Bisutti, Erminio Trevisi, Riccardo Negrini, Sara Pegolo, Stefano Schiavon, Luigi Gallo, Giovanni Bittante, Diana Giannuzzi

“…Pregnancy rate at first service, however, was analyzed using logistic regression and the same explanatory variables. The metabolites linked to liver function and damage, such as aspartate aminotransferase, total bilirubin, and alkaline phosphatase, had a relevant influence on iCF and DO in terms of the hazard ratio (HR). …”
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Machine learning-based model for acute asthma exacerbation detection using routine blood parameters by Youpeng Chen, Junquan Sun, Yabang Chen, Enzhong Li, Jiancai Lu, Huanhua Tang, Yifei Xie, Jiana Zhang, Lesi Peng, Haojie Wu, Zhangkai J. Cheng, Baoqing Sun

“…Background: Acute asthma exacerbations (AAEs) are a leading cause of asthma-related morbidity and mortality, especially in resource-limited settings where pulmonary function tests are unavailable or when patients are unable to cooperate with testing. …”
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Analysis of MAXIM Application Service Quality on User Satisfaction using the E-Service Quality Method by Putri Wulandari, Nur Rachman Dzakiyullah, Asti Ratnasari, Dadang Heksaputra

“…Overall, the quality of Maxim's service towards user satisfaction is not good in terms of the variables of efficiency, system availability, responsiveness, and contact. …”
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Thermo-economic optimization of a hybrid solar-wind energy system for the production of clean hydrogen and electricity by Ali Bedakhanian, Akbar Maleki, Siavash Haghighat

“…The objective functions included total cost rate and total exergy efficiency. …”
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Optimization of household medical waste recycling logistics routes: Considering contamination risks. by Jihui Hu, Ying Zhang, Yanqiu Liu, Jiaqi Hou, Aobei Zhang

“…To enhance the realism of the simulation, traffic congestion is integrated into the vehicle speed function, reflecting the urban roads' variability. …”
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