On the parameterized complexity of computing tree-partitions by Hans L. Bodlaender, Carla Groenland, Hugo Jacob

“…We study the parameterized complexity of computing the tree-partition-width, a graph parameter equivalent to treewidth on graphs of bounded maximum degree. …”
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Enhanced natural parameterized quantum circuit by Yuquan Chen, Yanjun Hou, Zeyuan Wang, Tianyun Wang, Ze Wu, Zhaokai Li, Xinhua Peng

“…However, a challenge in designing parameterized quantum circuits that can fully utilize limited qubit resources while accurately representing classical data remains. …”
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Perfect Roman Domination: Aspects of Enumeration and Parameterization by Kevin Mann, Henning Fernau

“…However, both problems are NP-complete on chordal bipartite graphs. We show that both problems are <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi mathvariant="sans-serif">W</mi><mo>[</mo><mn>1</mn><mo>]</mo></mrow></semantics></math></inline-formula>-complete if parameterized by solution size and FPT if parameterized by the dual parameter or by clique width.…”
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Firefly Algorithm for Polynomial Bézier Surface Parameterization by Akemi Gálvez, Andrés Iglesias

“…The method has been successfully applied to some illustrative examples of open and closed surfaces, including shapes with singularities. Our results show that the method performs very well, being able to yield the best approximating surface with a high degree of accuracy.…”
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Shaping freeform nanophotonic devices with geometric neural parameterization by Tianxiang Dai, Yixuan Shao, Chenkai Mao, Yu Wu, Sara Azzouz, You Zhou, Jonathan A. Fan

“…We further show numerically and experimentally that Neuroshaper can apply to a diversity of nanophotonic devices. …”
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Practical and Parameterized Fingerprinting Through Maximal Filtering for Indoor Positioning by F. Serhan Danis

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Snow albedo and its parameterization for natural systems and climate modeling by D. V. Turkov, E. D. Drozdov, A. A. Lomakin

“…When compared with the old scheme for parameterizing the albedo of snow cover in the LSM SPONSOR model, based on the dependence of the albedo only on the age of the snow, the new scheme showed a significant increase in the quality of albedo calculations: the correlation coefficients between the observed data and the calculation results are 0.78–0.83, which gives determination coefficients of 0.61–0.69. …”
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Jaxkineticmodel: Neural ordinary differential equations inspired parameterization of kinetic models. by Paul van Lent, Olga Bunkova, Bálint Magyar, Léon Planken, Joep Schmitz, Thomas Abeel

“…Despite their widespread use, it remains challenging to parameterize these Ordinary Differential Equations (ODE) for large scale kinetic models. …”
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A Machine Learning-Based Parameterized Tropical Cyclone Precipitation Model by Yi Lu, Jie Yin, Peiyan Chen, Hui Yu, Sirong Huang

“…The TCPM-ML was applied for multiple temporal scale hazard assessment. The results show that: (1) The TCPM-ML not only improved TCPM performance for simulating hourly extreme precipitations, but also preserved the physical meaning of the results, contrary to ML methods; (2) Machine learning algorithms enhanced the TCPM ability to reproduce observations, although the hourly extreme precipitations remained slightly underestimated; (3) Best performance was obtained with the XGBoost or EL algorithms. …”
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Toward Transparency and Consistency: An Open‐Source Optics Parameterization for Clouds and Precipitation by Jing Feng, Raymond Menzel, David Paynter

“…Systematic flux biases may arise if the effective radius is not fully predicted in microphysics due to predefined size and habit distributions. We show that assuming spherical ice crystals underestimates ice‐cloud radiative effects by 3.20 Wm−2 in the longwave TOA and 2.76 Wm−2 in the shortwave TOA. …”
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A Dynamic Smagorinsky Model for Horizontal Turbulence Parameterization in Tropical Cyclone Simulation by Xu Zhang, Qijun Huang, Yulong Ma

“…Abstract The horizontal turbulence parameterization is vital for the intensity and structure forecasting of tropical cyclone (TC) in numerical weather prediction (NWP) models. …”
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Parameterized resetting model captures dose-dependent entrainment of the mouse circadian clock by Kosaku Masuda, Ryusuke Yoshimoto, Ruoshi Li, Takeshi Sakurai, Arisa Hirano

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An Ensemble Learning-Based Predictive Parameterization Approach for Permanent Magnet Synchronous Machines by Sema Nur Ipek, Nur Bekiroglu, Murat Taskiran

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Stochastic convective parameterization improving the simulation of tropical precipitation variability in the NCAR CAM5 by Yong Wang, Guang J. Zhang, George C. Craig

“…To evaluate its impact on tropical precipitation simulation, two experiments are conducted: one with the standard CAM5 and the other with the stochastic scheme incorporated. Results show that the PC stochastic parameterization decreases the frequency of weak precipitation and increases the frequency of strong precipitation, resulting in better agreement with observations. …”
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Modeling and Dynamic Parameterized Predictive Control of Dissolved Oxygen in Dual−Tank Bioreactor Systems by Muhang Li, Ran Tang, Yifei Li, Junning Cui

“…To address these issues, a dynamic parameterized predictive control (DPPC) approach is proposed and validated through simulation and bench−scale experiments. …”
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Underwater Visual Multi-Target Tracking Algorithm Integrating Re-parameterization and Attention Mechanism by Junyi LI, Mingle HE, Chang LIU, Yong XU

“…First, to tackle the diversity of underwater targets and image degradation, an improved YOLOv8 algorithm based on re-parameterization and attention mechanism(RA-YOLOv8) was proposed. …”
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An Investigation of the Characteristics of the Mei–Yu Raindrop Size Distribution and the Limitations of Numerical Microphysical Parameterization by Zhaoping Kang, Zhimin Zhou, Yinglian Guo, Yuting Sun, Lin Liu

“…However, at elevated rainfall rates, the simulated concentration of large raindrops shows no significant increase, resulting in negligible rightward shifting of RSD in the model outputs. …”
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An Empirical Parameterization to Separate Coarse and Fine Mode Aerosol Optical Depth Over Land by Xiaohan Li, Paul Ginoux

“…Validation with independent NOAA GML data sets shows predicted FMF errors mostly within 0.1. Finally, applying this parameterization to MODIS Aqua and Terra data significantly improved satellite‐derived FMF agreement with AERONET compared to previous derivations. …”
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Improving the evapotranspiration estimation by coupling soil moisture and atmospheric variables in the relative evapotranspiration parameterization by Elisabet Walker, Virginia Venturini

“…A sigmoid (Fs) and a logarithmic (Fl) F expression were included in Walker et al.’s (2019a,b) equations to evaluate their impact on the accuracy of ET estimations. The new parameterizations of ET outperformed the original expression, showing root mean square errors lower than 24% of the mean observed ET. …”
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Improving the prediction of potato yield gaps: Solanum-model parameterization and evaluation in southwestern China. by Ying Wang, Muhammad Abdul Rehman Rashid, Shumin Liang, Zulfiqar Ali Sahito, Ju Yang, Zhou Li, Zuo Hu, Zhechao Pan, Qijun Sui

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