Relación entre comunidad íctica y cobertura vegetal riparia en dos períodos hidrológicos (Eje Cafetero, Colombia) by María Angélica Pérez-Mayorga, Saúl Prada-Pedreros

“…Therewere no significant differences (P>0.05) among the structural variables, the HYPE and the RVC. According to r and r2 the diet of most fish species did not vary as a function of RVC and HYPE; however, according to the CCA diet varies as a function of HYPE but not of RVC. …”
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The Effect of Hydraulic Partitioning on Prediction the Rate of Bed Load Transport in Gravel-bed Rivers using Support Vector Machine by Kiyoumars Roushangar, Mohammad Hosseini, Saman Shahnazi

“…After optimization of parameters for kernel function, the bed load transport rate was predicted and obtained results from different models were investigated in terms of correlation coefficient (R), Root mean square error (RMSE) and Nash-Sutcliffe (NSE). in order to assess the capability of SVM in quantification of bed load under varied hydraulic conditions, Froude number (Fr) and bed slope of channel (S0) were selected as a parameters describing the hydraulic conditions and median diameter of the sediment particles (D50) and shear Reynolds number (Re*) were considered as a representative of sediment characteristic. …”
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The Macroeconomic Framework of Support Analysis for Sustainable Businesses Development by Constantin Mitrut, Cristina Bălăceanu, Mihaela Gruiescu, Daniela Serban

“…The present research is based on a multifactorial liniar regression model which outlines the direct correlation between the dependent variable welfare and the independent variable of concentration measured by the Gini coefficient of wealth concentration, on the one hand, and by the GDP level, on the other hand, at the level of year 2012. …”
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A Novel Structural Modification Method for Vibration Reduction: Stiffness Sensitivity Analysis with Principal Strain Application by Jiajun Hong, Takuya Yoshimura

“…The sensitivity is evaluated as a differential coefficient of the target response with respect to the design variable, e.g., stiffness or mass. …”
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Distributionally Robust Variational Quantum Algorithms With Shifted Noise by Zichang He, Bo Peng, Yuri Alexeev, Zheng Zhang

“…We model the noise level as a random variable with an unknown probability density function (PDF), and we assume that the PDF may shift within an uncertainty set. …”
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Predicting heat transfer Performance in transient flow of CNT nanomaterials with thermal radiation past a heated spinning sphere using an artificial neural network: A machine learn... by S.R. Mishra, P.K. Pattnaik, Rupa Baithalu, P.K. Ratha, Subhajit Panda

“…An efficient heat transfer phenomenon using nanofluid have greater challenges in various industries, engineering application the recent trend. …”
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Parametric Survival Models of Hemodialysis Patients in Relation with Patient-Related Factors by Reem Yousif MEKKI, Mohamed Hassan MUDAWI, Manahil Saidahmed MUSTAFA, Altaiyb Omer Ahmed MOHMMED, Ahmed Bakheet Abd ALLA, Abdel Rahman AHMED

“…Based on the Cox-Snell Residuals and AIC, BIC, and Gompertz (PH) model is an efficient model than other when the values of (AIC=662.21), (BIC=703.83) and (R2=0.211) where maintained Study assessed that the variables dealing with univariate models were signifi cant but had a signifi cant effect on hemodialysis survival. …”
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Trajectory Planning Method in Time-Variant Wind Considering Heterogeneity of Segment Flight Time Distribution by Man Xu, Jian Wang, Qiuqi Wu

“…This study aims to optimize a reliable and efficient trajectory by minimizing the Mean-Excess Flight Time (MEFT). …”
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A Simple and Effective KAN-Based Architecture for Accurate Battery RUL Prediction by Guangzai Ye, Li Feng, Jianlan Guo, Yuqiang Chen, Shufei Li

“…Our approach integrates a VMD-based denoising mechanism, compressed into a more compact KAN model via knowledge distillation, to mitigate noise efficiently. It also incorporates a channel-independent KANs structure with a regularized weighted loss function to handle variable-specific degradation patterns. …”
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Evaluating the Potential Use of Wearable Fitness Devices as a Measure of Outcomes in Orthopaedics by Jordan Henderson BS, Santiago Logan-Baca BS, Sara Kisiel BS, Fadi Muheidat PhD, David Jaffe MD

“…Surveys utilized were the Foot and Ankle Ability Measure Computerized Adaptive Testing (FAAM CAT), PROMIS physical function, mobility and pain interference scores, and Visual Analog Scale (VAS). …”
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Correlation method of processing the image of the surface microrelief to determine its roughness by Alexey D. Abramov, Dmitry S. Klyuev

“…For these functions, the average amplitudes Ucp of the variable components of the correlation coefficients are calculated and the analytical dependence of the GOST roughness parameter Ra on Ucp is constructed. …”
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Establishing a novel model to assess exercise capacity in chronic heart failure based on stress echocardiography by Huan Cen, Sinan Chen, Shen Feng, Xiankun Chen, Huiying Zhu, Wei Jiang, Han Zhang, Hongmei Liu, Bo Liu, Weihui Lu, Pengtao Sun

“…The analytical features of all patients in the four phases (rest, warm‐up, peak and recovery phases) of ESE included the following parameters: left ventricular (LV) systolic function, LV systolic function reserve, LV diastolic function, LV diastolic function reserve and right ventricular function. …”
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FUNGSI GREEN UNTUK PERSAMAAN DIFUSI-ADVEKSI DENGAN SYARAT BATAS DIRICHLET by Josua Josua, Evi Noviani, Fransiskus Fran

“…Mathematically, diffusion-advection equation can be written as  where  is concentration of material in the fluid, stands for the advection velocity, and  for diffusion coefficient. In this paper, a solution  is sought by using the Green’s function concept. …”
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Proposing Optimized Random Forest Models for Predicting Compressive Strength of Geopolymer Composites by Feng Bin, Shahab Hosseini, Jie Chen, Pijush Samui, Hadi Fattahi, Danial Jahed Armaghani

“…We present a comparative analysis of two hybrid models, Harris Hawks Optimization with Random Forest (HHO-RF) and Sine Cosine Algorithm with Random Forest (SCA-RF), against traditional regression methods and classical models like the Extreme Learning Machine (ELM), General Regression Neural Network (GRNN), and Radial Basis Function (RBF). Using a comprehensive dataset derived from various scientific publications, we focus on key input variables including the fine aggregate, GGBS, fly ash, sodium hydroxide (NaOH) molarity, and others. …”
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Cognitive performance classification of older patients using machine learning and electronic medical records by Monika Richter-Laskowska, Ewelina Sobotnicka, Adam Bednorz

“…Various ML techniques are evaluated to classify cognitive performance levels based on input features such as sociodemographic variables, lab results, comorbidities, Body Mass Index (BMI), and functional scales. …”
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Theoretical and technical concept of cemented backfill material for flexible enhanced thermal energy storage in coal underground space by Chao LYU, Wenyu LYU, Qiang SUN, Panshi XIE, Ding LANG, Songtao JI, Jianjun HU

“…The research status of backfill mining is analyzed based on the current coal mining technology and the scientific concept of "cemented backfill material for flexible enhanced thermal energy storage (CBM–FETES)" is proposed by integrating the idea of functional filling. The core of CBM–FETES is to ensure the four essential conditions: the suitability of geological conditions, the feasibility of thermal storage and extraction technologies, high efficiency in heat and mass transfer, and the safety and stability of the operational cycle. …”
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Assessing the Effectiveness of DL-Clustering for Energy Optimization in Wireless Sensor Networks by Shailaja S. Halli, Poornima G Patil

“…Determining the fitness function allows us to estimate the player's stability over these variables. …”
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Nonparametric Test for Logistic Regression with Application to Italian Enterprises’ Propensity for Innovation by Stefano Bonnini, Michela Borghesi

“…In this work, a nonparametric method is proposed to jointly test the significance of the regression coefficient estimates in a logistic regression model and identify which explanatory variables are effective in predicting the binary response. …”
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A Reliable Approach for Solving Transmission Network Expansion Planning with Objective of Planning Cost Reduction by Yongqiu Liu

“…The candidate plans are evaluated using a fitness function that considered objective function for transmission expansion planning problem is composed of two terms. …”
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Design of Reinforcement Learning Guidance Law for Antitorpedo Torpedoes by Zhong Wang, Zhiwen Wen, Weitong Cui, Daming Zhou, Pei Wang

“…Integrating engineering design, the intelligent guidance law for antitorpedo torpedoes proposed in this article selects the rate of change in the line-of-sight angle as the state variable, designs a reward function based on interception results, and designs a discretized behavior space based on the commonly used proportional guidance coefficient selection range. …”
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