Hybrid models and biological model reduction with PyDSTool. by Robert Clewley

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Research on Slope Stability Based on Bayesian Gaussian Mixture Model and Random Reduction Method by Jingrong He, Tao Deng, Shouxing Peng, Xing Pang, Daochun Wan, Shaojun Zhang, Xiaoqiang Zhang

“…To address this limitation, this study proposes a novel approach that considers the non-proportional reduction of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>c</mi></semantics></math></inline-formula> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>φ</mi></semantics></math></inline-formula>, without dependence on predefined reduction paths. …”
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A User-Centered Theoretical Model for Future Urban Transit Systems by Gerald B. Imbugwa, Tom Gilb, Manuel Mazzara

“…The paper’s primary contribution is its integrated optimization framework integrating carpooling, micro-mobility, and multi-leg routing in dynamic urban conditions, an absent component in prior single-mode or static models. Our scenario-based analysis demonstrates up to 30% travel time and emissions reduction over stand-alone mobility solutions.…”
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Kinetics Study of the Hydrogen Reduction of Limonite Ore Using an Unreacted Core Model for Flat-Plate Particles by Jindi Huang, Tao Yi, Jing Li, Mingzhou Li, Fupeng Liu, Jinliang Wang

“…Based on the principles of isothermal thermal analysis kinetics and the unreacted core model for flat-plate particles, the mechanism function and kinetic parameters for the reduction of limonite particles were determined. …”
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Fluid Force Reduction and Flow Structure at a Coastal Building with Different Outer Frame Openings Following Primary Defensive Alternatives: An Experiment-Based Review by Kannangara Dissanayakalage Charitha Rangana Dissanayaka, Norio Tanaka

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Possible Nutrient Load Reduction on the Large River Catchment Due to the Best Available Techniques Introduction in Agricultural Production by Briukhanov Aleksandr, Kondratyev Sergey, Shmakova Marina, Vasilev Eduard, Oblomkova Natalia

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Finite-Difference Analysis of Influence of Borehole Diameter and Spacing on Reduction in Rockburst Potential of Burst-Prone Coal Seams by Mikhail O. Eremin, Artyom O. Chirkov, Albert Pazhin, Sergey A. Laptev, Dmitriy V. Chanov

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Bifurcation Branch in a Spatial Heterogeneous Predator–Prey Model with a Nonlinear Growth Rate for the Predator by Lei Kong

“…We also proved that the bounded curve is monotone <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi mathvariant="bold">S</mi></semantics></math></inline-formula>-shaped or fish-hook-shaped (⊂-shaped), as the values of the parameters of the model vary; in the latter case, the model has multiple positive steady-state solutions caused by the spatial heterogeneity of the environment.…”
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Models of Reduction by Otávio Bueno

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Information-Reduction Ability Assessment in the Context of Complex Problem-Solving by Xiaoxuan Bu, Huijia Zheng, Xuetao Tian, Fang Luo

“…Structural validity from the confirmatory factor analysis (CFA) supported a one-factor model of information reduction based on the extracted indicators (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>χ</mi><mn>2</mn></msub></semantics></math></inline-formula> = 14.872, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>d</mi><mi>f</mi></mrow></semantics></math></inline-formula> = 5, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>χ</mi><mn>2</mn></msub></semantics></math></inline-formula>/<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>d</mi><mi>f</mi></mrow></semantics></math></inline-formula> = 2.774, CFI = 0.989, TLI = 0.967, RMSEA = 0.077, SRMR = 0.024). …”
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Real Power Loss Reduction by the Cultivation of Soil Optimization Algorithm by Lenin, K.

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Data Fusion and Dimensionality Reduction for Pest Management in Pitahaya Cultivation by Wilson Chango, Mónica Mazón-Fierro, Juan Erazo, Guido Mazón-Fierro, Santiago Logroño, Pedro Peñafiel, Jaime Sayago

“…Future work will explore hybrid fusion pipelines and sensor-agnostic models to extend generalizability.…”
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Passive Rotor Noise Reduction Through Axial and Angular Blade Spacing Modulation by Chingiz Arystanbekov, Altay Zhakatayev, Basman Elhadidi

“…Additionally, the study accounts for the effect of the blade tip Mach number, concluding that a tip Mach number ranging between <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>0.7</mn></mrow></semantics></math></inline-formula> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>0.9</mn></mrow></semantics></math></inline-formula> is optimal for noise reduction in the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mn>30</mn><mo>∘</mo></msup></semantics></math></inline-formula> configuration. …”
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Kinetic Analysis of Molten Oxide Reduction Using Bottom-Blown Hydrogen Injection by Lijin Lu, Feng Wang, Haifeng Wang, Jian Qiu, Xiaodong Ping

“…The hydrogen utilization rate reached a maximum of 41.87%, then decreased continuously and finally maintained at about 20%. Using the method of model fitting, it was found that the hydrogen-based molten reduction conformed to the phase boundary reaction model (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>G</mi><mfenced separators="|"><mrow><mi>α</mi></mrow></mfenced><mo>=</mo><msup><mrow><mn>1</mn><mo>−</mo><mo>(</mo><mn>1</mn><mo>−</mo><mi>α</mi><mo>)</mo></mrow><mrow><mn>1</mn><mo>/</mo><mn>2</mn></mrow></msup></mrow></semantics></math></inline-formula>), the corresponding mechanism function is <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>f</mi><mfenced separators="|"><mrow><mi>α</mi></mrow></mfenced><mo>=</mo><msup><mrow><mn>2</mn><mo>(</mo><mn>1</mn><mo>−</mo><mi>α</mi><mo>)</mo></mrow><mrow><mn>1</mn><mo>/</mo><mn>2</mn></mrow></msup></mrow></semantics></math></inline-formula>, where α stands for the reduction conversion, and the reaction rate constant <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>k</mi><mo>(</mo><mi>T</mi><mo>)</mo></mrow></semantics></math></inline-formula> is 2.37 × 10⁻⁴ s⁻¹ under the experimental conditions.…”
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DNS over HTTPS Tunneling Detection System Based on Selected Features via Ant Colony Optimization by Hardi Sabah Talabani, Zrar Khalid Abdul, Hardi Mohammed Mohammed Saleh

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Composite reductions for Kripke models by Y. A. Belov.

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Joint Sparse Local Linear Discriminant Analysis for Feature Dimensionality Reduction of Hyperspectral Images by Cong-Yin Cao, Meng-Ting Li, Yang-Jun Deng, Longfei Ren, Yi Liu, Xing-Hui Zhu

“…To address these drawbacks, this paper proposes a novel joint sparse local linear discriminant analysis (JSLLDA) method by integrating embedding regression and locality-preserving regularization into the LDA model for feature dimensionality reduction of HSIs. …”
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Fiber-Optic Sensor Spectrum Noise Reduction Based on a Generative Adversarial Network by Yujie Lu, Qingbin Du, Ruijia Zhang, Bo Wang, Zigeng Liu, Qizhe Tang, Pan Dai, Xiangxiang Fan, Chun Huang

“…Additionally, the proposed algorithm was tested for multimode noise reduction, demonstrating an excellent linearity in temperature response with a <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msup><mrow><mi>R</mi></mrow><mrow><mn>2</mn></mrow></msup></mrow></semantics></math></inline-formula> of 99.95% for its linear fitting and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>99.74</mn><mo>%</mo></mrow></semantics></math></inline-formula> for the temperature response obtained from single-mode fiber sensors. …”
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Energy Optimization in Ultrasound Tomography Through Sensor Reduction Supported by Machine Learning Algorithms by Bartłomiej Baran, Tomasz Rymarczyk, Dariusz Majerek, Piotr Szyszka, Dariusz Wójcik, Tomasz Cieplak, Marcin Gąsior, Marcin Marczuk, Edmund Wąsik, Konrad Gauda

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Stepwise Segmented Skewed Pole Modulation Vibration Reduction Design for Integer-Slot Motors by Huawei Wu, Shaokang Lu, Xiaoyuan Zhu, Weiye Li, Jianping Peng

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