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1061
Beyond Spirometry: Linking Wasted Ventilation to Exertional Dyspnea in the Initial Stages of COPD
Published 2024-12-01“…Pulmonary function tests estimating the extension of the wasted ventilation and selected cardiopulmonary exercise testing variables can, therefore, shed unique light on the genesis of patients’ out-of-proportion dyspnea. …”
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1062
Application of Machine Learning for Bulbous Bow Optimization Design and Ship Resistance Prediction
Published 2025-03-01“…To solve the problem of insufficient accuracy in the single surrogate model, this study proposes a CBR surrogate model that integrates convolutional neural networks with backpropagation and radial basis function models. The coordinates of the control points of the NURBS surface at the bulbous bow are taken as the design variables. …”
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1063
Parametric Survival Models of Hemodialysis Patients in Relation with Patient-Related Factors
Published 2020-12-01“…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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1064
Optimizing physical education schedules for long-term health benefits
Published 2025-06-01“…The developed DL model integrates convolutional neural network (CNN) layers to capture spatial features and long short-term memory (LSTM) layers to extract temporal patterns from demographic and activity-related variables. These features are combined through a fusion layer, and a customized loss function is employed to accurately predict fitness scores.ResultsExtensive experimental evaluation demonstrates that the proposed model consistently outperforms competitive baseline models. …”
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1065
Optimizing the Production of LNG and NGL from Arab Crudes and Wet Gases
Published 1995-01-01“…The developed model should be utilized as a useful tool to help the design of an efficient processing of natural gases. A great deal of the unlimited what if questions can be answered using this model. …”
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1066
Flow-based cytometric analysis of cell cycle via simulated cell populations.
Published 2010-04-01“…We present a new approach to the handling and interrogating of large flow cytometry data where cell status and function can be described, at the population level, by global descriptors such as distribution mean or co-efficient of variation experimental data. …”
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1067
A Knowledge-Driven Smart System Based on Reinforcement Learning for Pork Supply-Demand Regulation
Published 2025-07-01“…Around the core of the system, a nonlinear constrained optimization model is established, which uses adjustments to newly retained gilts as decision variables and minimizes supply-demand squared errors as its objective function, incorporating multi-dimensional factors such as pig growth dynamics, epidemic impacts, consumption trends, and international trade into its analytical framework. …”
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1068
A LINEAR SIMULATION MODEL FOR OPTIMIZING CROP STRUCTURE IN ORDER TO MAXIMIZE INCOME IN A VEGETAL AGRICULTURAL FARM
Published 2023-01-01“…The model included: the 8 unknown variables for the cultivated area with 8 crops: wheat, rye, barley, peas, rape, soybean, maize and sunflower, 14 restrictions regarding Diesel fuel, fertilizers, herbicides, total surface, expenditures, income, and area per each crop, and objective - function f(Max) Income. …”
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1069
Performance evaluation of atmospheric water generation in different climates using thermoelectric cooling
Published 2025-04-01“…In contrast, the variable voltage mode improves efficiency by 30 %, albeit with a lower water yield. …”
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1070
Mechanical and Civil Engineering Optimization with a Very Simple Hybrid Grey Wolf—JAYA Metaheuristic Optimizer
Published 2024-11-01“…The proposed SHGWJA was tested very successfully in seven “real-world” engineering optimization problems taken from various fields, such as civil engineering, aeronautical engineering, mechanical engineering (included in the CEC 2020 test suite on real-world constrained optimization problems) and robotics; these problems include up to 14 optimization variables and 721 nonlinear constraints. Two representative mathematical optimization problems (i.e., Rosenbrock and Rastrigin functions) including up to 1000 variables were also solved. …”
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1071
Multi-Objective Optimization Methods for University Campus Planning and Design—A Case Study of Dalian University of Technology
Published 2025-07-01“…A five-dimensional objective system—comprising energy efficiency, spatial quality, economic cost, ecological benefits, and cultural expression—was established, alongside the identification and standardization of 29 key variables to construct mapping relationships among objective functions. …”
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1072
Semantic ECG hash similarity graph
Published 2025-07-01“…Subsequently, a lightweight linear hash function is utilized to produce a hash representation for the unseen signal. …”
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1073
Structural strength analysis and optimization of converter lug based on Kriging model
Published 2022-07-01“…In this paper, machine learning methods were considered to approximate the functional relationships between design variables and responses. …”
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1074
An Optimization Model for Shell Plate Seam Landing Using Minimum Manufacturing Cost and a Solution by Genetic Algorithm
Published 2024-01-01“…In this paper, a new optimization model and its solution method for the landing of seams and butts (for convenience, seam and butt are simply called seam) on the ship hull surface are proposed in order to improve the shipbuilding efficiency. The minimum manufacturing cost of ship hull shell plates (SHSPs) is the objective function, the rules and requirements for the seam position and the size of a single shell plate are the constraints, and the position and shape of the seam are the design variables. …”
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1075
Neuro-Evolution of Augmenting Topologies for Dynamic Scheduling of Flexible Job Shop Problem
Published 2024-09-01“…This study introduces a neuro-evolution of augmenting topologies (NEAT) algorithm aimed at optimizing the scheduling efficiency in flexible job shops by minimizing both maximum completion and average lag times, taking into account variables like sporadic job arrivals, variable machining durations, tool wear, preventive maintenance, and equipment failures. …”
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1076
Implications of thermal stratification and radiative heat flux in blood-based ternary and dihybrid nanomaterial flow through a stretchable cylinder
Published 2025-09-01“…Non-dimensional mathematical model representing the physical phenomenon is solved through NDSolve function of Mathematica. Behavior of micropolar THNF and HNF velocity and thermal field versus influential variables are investigated. …”
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1077
Center of Largest Area Defuzzifier Vnit VLSI Architecture
Published 2023-02-01“…The functional analysis has revealed that the proposed architecture is implementing COLA based defuzzifier efficiently and accurately. …”
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1078
Thermoelastic damping in piezothermoelastic nanobeam resonators under the strain gradient theory with micro-inertia and non-fourier heat conduction
Published 2025-06-01“…To account for small-scale effects, the Helmholtz free energy density is defined as a function of the strain tensor, strain gradient tensor, electric field vector, and temperature field, considering these parameters as independent state variables. …”
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1079
Non-Similar Analysis of Boundary Layer Flow and Heat Transfer in Non-Newtonian Hybrid Nanofluid over a Cylinder with Viscous Dissipation Effects
Published 2025-03-01“…Non-similar system of PDEs are obtained with efficient conversion variables. The dimensionless PDEs are truncated using a local non-similarity approach up to third level and numerical solution is evaluated using MATLAB built-in-function bvp4c. …”
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1080
Proposing Optimized Random Forest Models for Predicting Compressive Strength of Geopolymer Composites
Published 2024-10-01“…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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