Generalized Preconditioned MHSS Method for a Class of Complex Symmetric Linear Systems by Cui-Xia Li, Yan-Jun Liang, Shi-Liang Wu

“…Numerical experiments are reported to confirm the efficiency of the proposed methods.…”
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On the Performance of Linear Decreasing Inertia Weight Particle Swarm Optimization for Global Optimization by Martins Akugbe Arasomwan, Aderemi Oluyinka Adewumi

“…Linear decreasing inertia weight (LDIW) strategy was introduced to improve on the performance of the original particle swarm optimization (PSO). …”
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A Simulation Study of Some Restricted Estimators in Restricted Linear Regression Model by Bader Aboud Mohammad, Mustafa Ismaeel Naif

“… When the multicollinearity exists in linear regression model, the result of the Restricted Least Square estimator (RLS) is unstable. …”
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New Inference Procedures for Semiparametric Varying-Coefficient Partially Linear Cox Models by Yunbei Ma, Xuan Luo

“…In biomedical research, one major objective is to identify risk factors and study their risk impacts, as this identification can help clinicians to both properly make a decision and increase efficiency of treatments and resource allocation. A two-step penalized-based procedure is proposed to select linear regression coefficients for linear components and to identify significant nonparametric varying-coefficient functions for semiparametric varying-coefficient partially linear Cox models. …”
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LC oscillator frequency prediction using machine learning linear regression algorithm by Mandar Jatkar, Vasudeva G, Tripti R. Kulkarni, Roopa R. Kulkarni, Aneesh Pandurangi

“…The study proves that log-transformed linear regression works as a basic but efficient method for accurate frequency estimation in resonant LC circuits.…”
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An Unbiased Convex Estimator Depending on Prior Information for the Classical Linear Regression Model by Mustafa I. Alheety, HM Nayem, B. M. Golam Kibria

“…We propose an unbiased restricted estimator that leverages prior information to enhance estimation efficiency for the linear regression model. The statistical properties of the proposed estimator are rigorously examined, highlighting its superiority over several existing methods. …”
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Quasi-Linear Convective Systems in Catalonia Detected Through Radar and Lightning Data by Tomeu Rigo, Carme Farnell

“…Quasi-Linear Convective Systems (QLCSs) are a type of Mesoscale Convective System characterised by their linear shape and association with severe weather phenomena (such as hail, tornadoes, or wind gusts). …”
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Polypropylene blends: Impact of long chain-branched polypropylene on crystallization of linear polypropylene by Soňa Zenzingerová, Jana Navratilova, Lenka Gajzlerová, Michal Kudláček, David Jaška, Lubomir Benicek, Roman Čermák

“…This study compares the efficiency of commercially available sorbitol-based clarifying agent (NA) and varying amounts of long chain-branched polypropylene (LCBPP) acting as a specific α-nucleating agent for linear polypropylene (PP). …”
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Experimental study on the performance of concrete linear cutting by high pressure water jet by Lan Zhang, Jingyan Lu, Haitao Li, Bo Li

“…The results of the study deepen the understanding of the characteristics of high-pressure water jet linear cutting concrete, and lay a theoretical foundation for the selection of parameters for efficient breaking of concrete by water jet.…”
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Synchronization Analysis for Stochastic Inertial Memristor-Based Neural Networks with Linear Coupling by Lixia Ye, Yonghui Xia, Jin-liang Yan, Haidong Liu

“…This paper concerns the synchronization problem for a class of stochastic memristive neural networks with inertial term, linear coupling, and time-varying delay. Based on the interval parametric uncertainty theory, the stochastic inertial memristor-based neural networks (IMNNs for short) with linear coupling are transformed to a stochastic interval parametric uncertain system. …”
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Variational Bayesian EM Algorithm for Quantile Regression in Linear Mixed Effects Models by Weixian Wang, Maozai Tian

“…This paper extends the normal-beta prime (NBP) prior to Bayesian quantile regression in linear mixed effects models and conducts Bayesian variable selection for the fixed effects of the model. …”
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Differences in Swedish and Norwegian pre-service teachers’ explanations of solutions of linear equations by Niclas Larson, Kerstin Larsson

“…Solving linear equations is a cornerstone in the learning of algebra. …”
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Spectrum Allocation Using Integer Linear Programming and Kerr Optical Frequency Combs by Sergio Muñoz-Tapasco, Andrés F. Calvo-Salcedo, Jose A. Jaramillo-Villegas

“…Spectrum allocation methods, such as the Routing, Modulation Level, and Spectrum Assignment (RMLSA) approach, play a crucial role in executing this strategy efficiently. While current algorithms have improved allocation efficiency, further development is necessary to optimize network performance. …”
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Newton-Kantorovich Method for Solving One of the Non-Linear Sturm-Liouville Problems by Hussien A. H. Abugirda, Khaldoun S. Al-Yasiri, Mohammed Kh. Abdullah

“…Also, to show the efficiency of applying this method to solve these problems, a comparison is made in this paper between the Newton-Kantorovich method and the Adomian decomposition method applied to the same non-linear Sturm-Liouville problems under consideration in this work. …”
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Predicting Market Value of Iranian Football Players using Linear Modeling Techniques by Rasool Nazari, Saeid Azari

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Cons-training tensor networks: Embedding and optimization over discrete linear constraints by Javier Lopez-Piqueres, Jing Chen

“…These tensor networks are particularly tailored for modeling distributions with support strictly over the feasible space, offering benefits such as reducing the search space in optimization problems, alleviating overfitting, improving training efficiency, and decreasing model size. Central to our approach is the concept of a quantum region, an extension of quantum numbers traditionally used in $U(1)$ symmetric tensor networks, adapted to capture any linear constraint, including the unconstrained scenario. …”
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Preserving Phase Coherence and Linearity in Cat Qubits with Exponential Bit-Flip Suppression by Harald Putterman, Kyungjoo Noh, Rishi N. Patel, Gregory A. Peairs, Gregory S. MacCabe, Menyoung Lee, Shahriar Aghaeimeibodi, Connor T. Hann, Ignace Jarrige, Guillaume Marcaud, Yuan He, Hesam Moradinejad, John Clai Owens, Thomas Scaffidi, Patricio Arrangoiz-Arriola, Joe Iverson, Harry Levine, Fernando G. S. L. Brandão, Matthew H. Matheny, Oskar Painter

“…These advances are important for the realization of scalable error correction with cat qubits, where large noise bias and low phase-flip error rate enable the use of hardware-efficient outer error-correcting codes.…”
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Blockage detection in pipelines based on linear frequency modulated acoustic reflection method by Haiyuan Yao, Dan Li, Yan Li, Bo Yang, Yang Meng

“…The system's capability to resolve multi-stage blockage boundaries enhances predictive maintenance strategies for ensuring energy-efficient pipeline operations and infrastructure integrity management. …”
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Unsupervised feature selection based on generalized regression model with linear discriminant constraints by Xiangguang Dai, Mingyu Guan, Facheng Dai, Wei Zhang, Tingji Zhang, Hangjun Che, Xiangqin Dai

“…Abstract Unsupervised feature selection (UFS) methods play a crucial role in improving the efficiency of extracting relevant information and reducing computational complexity in the context of big data analysis. …”
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Comparison of Linear and Nonlinear Features of Electroencephalogram to Classify Alcoholic and Non-Alcoholic People by Elizabeth Stewart, Owen Kelly

“…The present study intends to use various types of linear and nonlinear analysis of the EEG signal to classify alcoholics and non-alcoholics and provide a direct comparison of the efficiency of each of the analysis methods. …”
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