Predicting renal function using fundus photography: role of confounders by Hyun-Woong Park, Hae Ri Kim, Ki Yup Nam, Bum Jun Kim, Taeseen Kang

“…Data including sex, age, and blood creatinine levels were collected for eGFR calculation using the MDRD and CKD-EPI formulas. EfficientNet B3 models were used to predict each parameter. …”
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Physical function evaluation in volleyball training based on intelligent GRNN by Kaiyuan Dong, Borhannudin bin Abdullah, Hazizi bin Abu Saad, Chenxi Lu

“…Abstract This study aims to improve both the evaluation accuracy and the real-time feedback capability in monitoring athletes’ physical function changes during volleyball training. Firstly, based on the framework of the generalized regression neural network, a variable-structure generalized regression neural network (VSGRNN) is proposed and developed. …”
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Viscosity modelling of chlorinated brines in three-component systems with a continuously variable temperature range between 293-323 K by Andrés Soto-Bubert, Rashmi Bhardwaj, Satheeshkumar Rajendran, Roberto Acevedo

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Method of restoring multivariable Boolean function from its derivative by Alexander V. Mazurenko, Nadezhda S. Mogilevskaya

“…Introduction. Boolean functions of several variables are of paramount importance in the coding theory and cryptography. …”
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Bringing Executive Function Testing Online: Assessment Validation Study by Mouna Attarha, Ana Carolina de Figueiredo Pelegrino, Lydia Ouellet, Sarah-Jane Grant, Etienne de Villers-Sidani, Thomas Van Vleet

“…Performance on Freeze Frame was analyzed in relation to self-reported demographic variables and neuropsychological function, using a standardized measure of executive function, the National Institutes of Health Executive Abilities: Measures and Instruments for Neurobehavioral Evaluation and Research (NIH EXAMINER). …”
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Auxiliary identification of depression patients using interpretable machine learning models based on heart rate variability: a retrospective study by Min Yang, Huiqin Zhang, Minglan Yu, Yunxuan Xu, Bo Xiang, Xiaopeng Yao

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Exploring Flexible Penalization of Bayesian Survival Analysis Using Beta Process Prior for Baseline Hazard by Kazeem A. Dauda, Ebenezer J. Adeniyi, Rasheed K. Lamidi, Olalekan T. Wahab

“…Therefore, this study is motivated to adopt the idea of a penalized semi-parametric Bayesian Cox (PSBC) model through elastic-net and group lasso penalty functions (PSBC-EN and PSBC-GL) to incorporate the grouping structure of the covariates (genes) and optimally perform variable selection. …”
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Handling Multiple-Fuel Options in Economic Dispatch of Thermal Power Plants Through a Tight Model Applying Indicator Variables by Hossein Sharifzadeh

“…Thermal power plants play a central role in present power systems because of their high efficiency, fast startup capability, and flexibility to integrate the variability of renewable generations. …”
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Spacecraft Intelligent Fault Diagnosis under Variable Working Conditions via Wasserstein Distance-Based Deep Adversarial Transfer Learning by Gang Xiang, Kun Tian

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Variational Autoencoder Transfer Functions for Onshore Tsunami Hazard Curves by Willington Renteria, Patrick Lynett, Maile McCann, Behzad Ebrahimi, Hong Kie Thio, Ian Robertson, Chris Siverd, Betsy Hicks

“…Once encoded, the data are represented by a normal distribution of latent variables. The VAE then uses a trained decoder to sample the distribution created by the latent variables and reconstruct a continuous hazard function at the onshore location. …”
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Mixed Cost Function and State Constrains Optimal Control Problems by Hugo Leiva, Guido Tapia-Riera, Jhoana P. Romero-Leiton, Cosme Duque

“…In this paper, we analyze an optimal control problem with a mixed cost function, which combines a terminal cost at the final state and an integral term involving the state and control variables. …”
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Cross-Modal Hashing Retrieval Based on Density Clustering by Xiaojun Qi, Xianhua Zeng, Hongmei Tang

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Reservoir water level prediction using combined CEEMDAN-FE and RUN-SVM-RBFNN machine learning algorithms by Lan-ting Zhou, Guan-lin Long, Can-can Hu, Kai Zhang

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Rapid global antenna design by simplex regressors and multi-resolution simulations by Slawomir Koziel, Anna Pietrenko-Dabrowska, Stanislaw Szczepanski, Leifur Leiffson

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Comparative Analysis of Transfer Function Method with Advanced Flood Prediction Techniques by Jafar Chabokpour

“…This now leads to a maximum Nash-Sutcliffe Efficiency of 0.91 for the Saint-Venant equations during the 2019 flood event, followed by ANN with 0.89, ANFIS with 0.87, SVM with 0.85, and lastly, Transfer Function with 0.78. …”
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A Sparse Variable Step-Size Least-Mean-Square Algorithm for Impulsive Noise in a Code-Division Multiple Access System by Mohammad Salman, Ahmed A. F. Youssef, Fahmi Elsayed, Mostafa Rashdan

“…For instance, the cost function is inadequately described when impulsive noise is present, making it impossible for the LMS approach to correctly identify the system. …”
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A MPCC-Based Variable Sampling Time Interleaving Method for a Two-Phase Totem-Pole Bridgeless Boost PFC Converter by Hyun-Gyu Koh, Hyeon-Joon Ko, Yeong-Jun Choi

“…This paper proposes a Model Predictive Current Control (MPCC) based variable sampling time interleaving method to improve the current shaping ability, power conversion efficiency, power density and current ripple reduction of a two-phase totem pole bridgeless boost power factor correction (PFC) converter. …”
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Structural Analysis of Multi-Core Processor and Reliability Evaluation Model by Sergo Tsiramua, Hamlet Meladze, Tinatin Davitashvili, Jose-Maria Sanchez-Sáez, Francisco Criado-Aldeanueva

“…In the present paper, the models of structural analysis and evaluation of efficiency indicators (reliability, fault tolerance, viability, and flexibility) of a multi-core processor with variable structure, equipped with multi-functional cores, are considered. …”
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Fuzzy Logic Technique Based on Classification Function Application in Quality Control by Salman Hussien Omran, Salam Waley Shneen, Batool Ibrahim Jameel, Omar Hassoon, Mohammed A. Fayad, Firas Basim Ismail

“…Fuzzy control charts were used to quickly and accurately identify the production specifications and efficiency. This work uses the triangle membership function to generate fuzzy numbers, which are then transformed into quality control charts for the real data obtained using the proposed ranking function. …”
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Novel Pythagorean fuzzy score function to optimize fuzzy transportation models by Ritu, Tarun Kumar, Jahnvi, Kapil Kumar, Nitesh Dhiman, M.K. Sharma

“…Through comprehensive numerical analysis, In Type-1 IVPFTP the cost dropped from 5.19 to 0.675, for Type-2 IVPFTP cost dropped from 0.2615 to 0.001869 and for Type-3 IVPFTP cost dropped from0.17435 to 0.0013879.Thereafter, it was observed that the proposed score function provides a more optimal transportation cost.Also, our findings demonstrate the significant cost reductions and improved decision-making capabilities across different types of IVPFTP models to highlight the efficiency of the proposed score function in handling uncertainty within the transportation problems.…”
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