A Data-Driven Approach Based on Deep Neural Network Regression for Predicting the Compressive Strength of Steel Fiber Reinforced Concrete by Nhat-Duc Hoang, Van-Duc Tran

“…Experimental results show that the L1 regularization helps achieve the most desired performance, with a coefficient of determination (R2) of roughly 0.96. Notably, an asymmetric loss function is used along with Nadam to decrease the percentage of overestimated cases from 50.83% to 27.08%. …”
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Estimativa das temperaturas máximas e mínimas do ar para a região do Circuito das Frutas, SP Estimation of maximum and minimum air temperatures for the "Circuito das Frutas" region... by Ludmila Bardin, Mário J. Pedro Júnior, Jener F. L. de Moraes

“…Also, maps with the spacial variability of the maximum and minimum mean monthly and annual temperatures are presented for the region.…”
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The Effect of Vocal Rehabilitation on Patients with Vocal Cord Paralysis by Mila Bunijevac, Andrijana Mikić, Maša Đurišić

“…Measures of central tendency, measures of variability, one-factor analysis of variance, t-test for independent samples, chi-square test and interclass correlation coefficient were applied in statistical data processing. …”
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Exploring restoration efforts from a social lens: statistical models reveal relationships between salmon habitat restoration efforts and ecological and social characteristics of th... by Brittany D King, Robert Fonner

“…We specified statistical models to explain the variation in the number of restoration worksites undertaken in subwatersheds as a function of environmental and social variables. Using a common set of explanatory variables, we fit four models to examine the distribution of worksites associated with particular types of restoration actions (instream, riparian, land acquisition, and fish passage) and a fifth model to examine the distribution of all aquatic-based restoration worksites across action types. …”
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FVPNet: A Fuzzy Visual Positioning Perception Network for Small Object Segmentation in Remote Sensing Images by Yu Yan, Jindong Xu, Qianpeng Chong, Guangyi Wei, Zhixiang Wang

“…Furthermore, grayscale variability intensifies boundary uncertainty, complicating accurate segmentation. …”
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Evaluating Machine Learning Models for Predicting Hardness of AlCoCrCuFeNi High-Entropy Alloys by Uma Maheshwera Reddy Paturi, Muhammad Ishtiaq, Pasupuleti Lakshmi Narayana, Anoop Kumar Maurya, Seong-Woo Choi, Nagireddy Gari Subba Reddy

“…This study evaluates the predictive capabilities of various machine learning (ML) algorithms for estimating the hardness of AlCoCrCuFeNi high-entropy alloys (HEAs) based on their compositional variables. Among the ML methods explored, a backpropagation neural network (BPNN) model with a sigmoid activation function exhibited superior predictive accuracy compared to other algorithms. …”
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Process engineering by Ahmed Mohamed Farid Shaaban, Azza Ibrahim Hafez, Mona Amin Abdel-Fatah, Nabil Mahmoud Abdel-Monem, Mohamed Hanafy Mahmoud

“…The solution diffusion model was used to develop power correlations to calculate the permeate side solute mass transfer coefficient as a function of effective cross-flow Reynolds number. …”
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End-to-End Stroke Imaging Analysis Using Effective Connectivity and Interpretable Artificial Intelligence by Wojciech Ciezobka, Joan Falco-Roget, Cemal Koba, Alessandro Crimi

“…The goal of this pipeline is to define an efficient brain representation for connectivity in stroke data derived from magnetic resonance imaging. …”
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Reconstructing Equatorial Electron Flux Measurements From Low‐Earth‐Orbit: A Conjunction Based Framework by D. L. Stumbaugh, J. Bortnik, S. G. Claudepierre

“…For each conjunction, we fit the equatorial pitch angle distribution (PAD) parameterized by the function JD=C⋅sinNα. The resulting conjunction data set contains the POES electron flux measurements, L and magnetic local time coordinates, geomagnetic activity Auroral Electrojet index, and C and N coefficients from the PAD fit for each conjunction. …”
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RP-18 HPLC Analysis of Drugs’ Ability to Cross the Blood-Brain Barrier by Anna W. Sobańska, Adam Hekner, Elżbieta Brzezińska

“…On the other hand, discriminant function analyses involving log k and (log k)/PSA as discriminating variables separated the CNS+ and CNS− compounds with the success rate ca. 90%. …”
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Frequency Stability Analysis Based on Full State Model in Autonomous-Synchronization Voltage Source Interfaced Power System by Zhenyao LI, Deqiang GAN, Moude LUAN, Guoqing HE

“…Then, the parameters of the autonomous-synchronization voltage source model are compared with those of the synchronous machine model, and it is proved that the function of the governor is equivalent to increasing the system damping, which can reduce the steady-state error of the system frequency after being disturbed. …”
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Artificial Neural Network (ANN) Modeling of Plasma and Ultrasound-assisted Air Drying of Cumin Seeds by M. Namjoo, M. Moradi, M. A. Nematollahi, H. Golbakhshi

“…Therefore, the wavelet-based neural network (WNN), the multilayer perceptron neural network (MLPNN), and the radial-basis function neural network (RBFNN), as three well-known artificial neural networks models, were used to map the inputs and output data and the results were compared with the Multiple Quadratic Regression (MQR) analysis. …”
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Research on optimization strategies of university ideological and political parenting models under the empowerment of digital intelligence by Fan Lv

“…It constructs the no-incentive, cost-sharing, and collaborative cooperation models, respectively, and obtains the optimal trajectories for the degree of effort, the subsidy coefficient, the optimal benefit function, and the digital and intelligent technology stock. …”
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Assessment of Intrarenal Artery Doppler Resistive Index in Normotensive Patients and Patients with Essential Hypertension by Obinna E. Abonyi, Uloma B. Nwogu, Vitus K. Ika, Julius A. Agbo, Beatrice U. Maduka, Sharonrose O. Nwadike

“…The renal resistive index (RRI) is a useful tool for assessing kidney function in hypertensive patients, but population-specific data are scarce. …”
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Association between TSH Values and GFR Levels in Euthyroid Cases with Metabolic Syndrome by H. Keskin, K. Cadirci, K. Gungor, T. Karaaslan, T. Usta, A. Ozkeskin, A. Musayeva, F. Yesildal, F. Isman, H. Y. Zengin

“…Partial correlation coefficients were calculated to investigate the relationship between the eGFR values and several other numerical variables while controlling for age and BMI in addition to the adjusted gender effect. …”
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Investigating factors affecting the quality of water resources by multivariate analysis and soft computing approaches by Bing Cheng, Xinyu Liu, Keke Guo, Ahmad Rastegarnia

“…Therefore, Na+, Cl+, Na%, CO3 −, and SO4 2− were used as input variables (independent variables), and EC, TDS, and SAR were used as output variables (dependent variables). …”
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Long-term conservation tillage breaks the plough pan and promotes the development of preferential flow by Jinze Han, Jianye Li, Qiang Chen, Xingyi Zhang

“…Macropores and preferential flow critically regulate soil hydrological functions and ecosystem services in agricultural systems. …”
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Stochastic Analysis of Nonlinear Vehicle-Track Coupled Dynamic System and Its Application in Vehicle Operation Safety Evaluation by Fu-Shan Liu, Zhi-Ping Zeng, Wei-Dong Wang, Abdulmumin Ahmed Shuaibu

“…The nonlinear coupled vehicle-track dynamic system is used to accurately describe the wheel-rail contact state. The stochastic function-spectral representation is used to simulate the random track irregularity in the time domain for the first time; consequently, the frequency components in the irregularity are preserved and random variables are reduced. …”
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A multi-objective robust possibilistic programming approach to designing sustainable and reliable closed-loop supply chain network (case study: aluminum industry) by Sajad Amirian, Maghsoud Amiri, Mohammad Taghi Taghavifard

“…The mathematical model developed in this research is of mixed integer linear programming type, which is implemented in GAMS software to solve it and find Pareto optimal solutions.Findings: The accuracy of the overall performance of the proposed model has been evaluated with four examples (based on the coefficients of the objective functions) from a case study in the aluminium industry. …”
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Assessing the Accuracy and Reliability of the Monitored Augmented Rehabilitation System for Measuring Shoulder and Elbow Range of Motion by Samuel T. Lauman, Lindsey J. Patton, Pauline Chen, Shreya Ravi, Stephen J. Kimatian, Sarah E. Rebstock

“…Accurate range of motion (ROM) assessment is essential for evaluating musculoskeletal function and guiding rehabilitation, particularly in pediatric populations. …”
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