An Efficient Coupled Genetic Algorithm-NLP Method for Heat Exchanger Network Synthesis

“…Solving such problems leads to difficulties in the optimization of continuous and binary variables. This paper presents a new efficient and robust method in which structural parameters are optimized by genetic algorithm (G.A.) and continuous variables are handled due to a modified objective function for maximum energy recovery (MER). …”
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On a geometric approach to the estimation of interpolation projectors by Mikhail V. Nevskii, Alexey Y. Ukhalov

“…Here $\sigma S$ is the result of homothety of $S$ with respect to the center of gravity with coefficient $\sigma$. Let $d\geqslant n+1,$ $\varphi_1(x),\ldots,\varphi_d(x)$ be linearly independent monomials in $n$ variables, and $\varphi_1(x)\equiv 1,$ $\varphi_2(x)=x_1,\ \ldots, \varphi_{n+1}(x)=x_n.$ Put $\Pi:=$lin$(\varphi_1,\ldots,\varphi_d).$ The interpolation projector $P: C(\Omega)\to \Pi$ with a set of nodes $x^{(1)},\ldots, x^{(d)} \in \Omega$ is defined by equalities $Pf\left(x^{(j)}\right)=f\left(x^{(j)}\right).$ Denote by $\|P\|_{\Omega}$ the norm of $P$ as an operator from $C(\Omega)$ to $C(\Omega)$ . …”
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A domain free of the zeros of the partial theta function by V. Kostov

“…For each $q$ fixed, $\theta$ is an entire function of order $0$ in the variable~$x$. When $q$ is real and $q\in (0,0.3092\ldots )$, $\theta (q,.)$ is a function of the Laguerre-P\'olya class $\mathcal{L-P}I$. …”
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Comparison of Different Numerical Models for Solidification of Paraffin-Based PCMs and Evaluation of the Effect of Variable Mushy Zone Constant by Milad Tajik Jamalabad, Cristobal Cortes, Javier Pallarés, Antonia Gil, Inmaculada Arauzo

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Multi-UAV Cooperative Suspension Control Strategy Considering Variable Rope Length and Load Posture Coupling Effect by Yi Wang, Kang Li, Xuefu Li, Jingyu Wang, Pengbo Yu

“…On this basis, the traditional dynamic model is improved, with a focus on the impact of variable rope length, analyzing the dynamic coupling relationship between rope length and swing angle, and constructing related coupling error functions to improve the stability and control accuracy of the system. …”
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Evaluation of the Efficiency of Metaheuristic Algorithms in the Optimal Design of Pile Wall Retaining Systems by Farshad Taiyari

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Experimental Study on Desorption Characteristics of Coalbed Methane under Variable Loading and Temperature in Deep and High Geothermal Mine by Haifeng Ma, Lingjie Wang, Housheng Jia, Jucai Chang, YingMing Li, Xiangyang Zhang, Zuxiang Hu, Zhiqiang Yin

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Machine learning-based smart irrigation controller for runoff minimization in turfgrass irrigation by Sambandh Dhal, Jorge Alvarado, Ulisses Braga-Neto, Benjamin Wherley

“…The synthetic data were derived from observations collected from irrigation plots at the Texas A&M University Turfgrass Laboratory in Texas, United States, with Soil Wetting Efficiency Index (SWEI) serving as the target variable. …”
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Beyond Global Metrics: The U-Smile Method for Explainable, Interpretable, and Transparent Variable Selection in Risk Prediction Models by Katarzyna B. Kubiak, Agata Konieczna, Anna Tyranska-Fobke, Barbara Więckowska

“…Variable selection (VS) is a critical step in developing predictive binary classification (BC) models. …”
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The Role of Profitability and Liquidity in Meeting the Feasibility Standards of Sharia Banking with Capital Adequacy as A Moderating Variable in Indonesia by Padli Pawaid Yahya, Joko Setyono

“…Control variables include Net Profit Margin (NPM), Operational Efficiency (BOPO), and Loan to Deposit Ratio (LDR). …”
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Model-Based Control Allocation During State Transitions of a Variable Recruitment Fluidic Artificial Muscle Bundle by Jeong Yong Kim, Matthew Bryant

“…FAMs can be bundled together in parallel to exhibit variable recruitment functionality, which is an activation strategy inspired by how motor units (MUs) in skeletal muscle are recruited. …”
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An efficient eigenvector-based crossover for differential evolution: Simplifying with rank-one updates by Tae Jong Choi

“…We propose a new approach to enhancing the efficiency of the differential evolution (DE) algorithm, specifically targeting rotational invariance. …”
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Photocatalytic Efficiency of TiO2-Biomass Loaded Mixture for Wastewater Treatment by Devagi Kanakaraju, Soon Pang Wong

“…Surface morphology, functional groups, and elemental analysis supported observations of the ability of TiO2/MSB mixture to remove COD. …”
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Modeling fin efficiency considering transverse temperature gradients in rocket engine cooling channels by Volodymyr Sliusariev, Valerii Bucharskyi

“…This study aims to improve the accuracy of methods for determining fin efficiency. Its goal is to derive calculation relationships for finning coefficients that account for transverse temperature non-uniformity within the fin cross-section. …”
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Enhancing CAR T‐cell therapy manufacturing efficiency through semi‐automated bioprocessing by Jason Isaacson, Prajakta Bhanap, Nicholas Putnam, Jasmine Padilla, Nujhat Fatima, Max Dotson, Danny Hayoun, Moloud Ahmadi, Gertrude Nonterah, Yongchang Ji

“…Automated CAR T‐cell manufacturing methods that use software to control the equipment used in the process can help overcome the roadblocks associated with manual manufacturing, ultimately enabling a reduction in variability, increased efficiency, improved product quality and better data management. …”
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Analysis of Bulk Queueing Model with Load Balancing and Vacation by Subramani Palani Niranjan, Suthanthiraraj Devi Latha, Sorin Vlase, Maria Luminita Scutaru

“…Cloud computing using power BI can be analyzed based on server load balancing. The function that determines the probability of the queue size at any given time is derived for the specified queueing model using the supplementary variable technique with the remaining time as the supplementary variable. …”
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How Can We Manage Repairing a Broken Finite Vibrating String? Solutions to the Problem I by Vladimir L. Borsch

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Optimization of non-smooth functions via differentiable surrogates. by Shikun Chen, Zebin Huang, Wenlong Zheng

“…These models are commonly used to predict outputs based on a combination of fixed parameters and adjustable variables. A key transition in optimization involves moving beyond simple prediction to determine optimal variable values. …”
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Gene function revealed at the moment of stochastic gene silencing by Shreyan Gupta, James J. Cai

“…In this study, we introduce the single-cell Stochastic Gene Silencing (scSGS) method, which leverages the natural variability in single-cell gene expression to decipher gene function. …”
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Scalable Processing of Glass with Multi‐Functional Cu Coating by Dan Wang, Xuelu Zhang, Yan Xing, Guanghua Liu, Hui Wu, Wei Pan

“…Abstract Functional glass has been intensively studied as a future material with improved comfort, safety, and practicality across a variety of settings, including industrial, and residential environments. …”
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