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Showing 181 - 200 results of 1,052 for search '(( variable friction efficient. ) OR ( variable function (coefficiency. OR coefficiency.) ))', query time: 0.18s Refine Results
  1. 181

    Optimization Design of Gear Transmission Parameter based on Efficiency Improvement by Rui Su, Gangjun Li, Huazhi Li, Pingping Liu, Yangsen Huang

    Published 2020-11-01
    “…The integral along the length of thread engagement is calculated for the average transmission efficiency expression of gear in meshing process. The expression of the independent variables including active tooth number z1, the transmission ratio i, the friction coefficient f and pressure angle α. …”
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    Article
  2. 182

    A Penalized Orthogonal Kriging Method for Selecting a Global Trend by Xituo Zhang, Guoxing Gao, Jianxin Zhao, Xinmin Li

    Published 2025-04-01
    “…A significant challenge arises when the mean function of the model includes polynomial terms with unknown coefficients, leading to identifiability problems and potentially unreliable results. …”
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    Article
  3. 183

    Optimization of heat transfer and entropy for Maxwell dusty fluid: Significance of Lorentz force and variable viscosity by Aziz Ullah Awan, Sidra Qayyum, Bagh Ali, Fehmi Gamaoun, Nehad Ali Shah, N. Ameer Ahammad, Sohail Nadeem

    Published 2025-09-01
    “…Additionally, the Nusselt number and friction factor are computed. The results demonstrated that the mixed convection parameter and the dusty-fluid interaction variable increase the entropy production and the Bejan number. …”
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    Article
  4. 184

    ON AN INITIAL BOUNDARY–VALUE PROBLEM FOR A DEGENERATE EQUATION OF HIGH EVEN ORDER by Akhmadjon K. Urinov, Dastonbek D. Oripov

    Published 2025-07-01
    “…An estimate for solution of the problem was obtained, which implies its continuous dependence on the given functions.…”
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    Article
  5. 185

    Exponential Squared Loss-Based Robust Variable Selection with Prior Information in Linear Regression Models by Hejun Wei, Tian Jin, Yunquan Song

    Published 2025-07-01
    “…For more than a decade, penalized likelihood frameworks have been the predominant approach for variable selection, where appropriate loss and penalty functions are selected to formulate unconstrained optimization problems. …”
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    Article
  6. 186
  7. 187

    Statistics of the Interplanetary Magnetic Field from 0.1 to 30 au. II. Dynamical Variability by Jiutong Zhao, Shan Wang, Weijie Sun, Xingyu Zhu, Chuanpeng Hou, Qiugang Zong, Jiansen He, Xuzhi Zhou, Chao Yue, Liu Yang, Daniel Heyner

    Published 2025-01-01
    “…Our analysis reveals that the autocorrelation function employed to measure IMF temporal variability is significantly influenced by the heliocentric distance and the solar cycle. …”
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    Article
  8. 188

    Prognostic Significance of Pulse Pressure Variability During Mechanical Thrombectomy in Acute Ischemic Stroke Patients by Benjamin Maïer, Guillaume Turc, Guillaume Taylor, Raphaël Blanc, Michael Obadia, Stanislas Smajda, Jean‐Philippe Desilles, Hocine Redjem, Gabriele Ciccio, William Boisseau, Candice Sabben, Malek Ben Machaa, Mylene Hamdani, Morgan Leguen, Etienne Gayat, Jacques Blacher, Bertrand Lapergue, Michel Piotin, Mikael Mazighi

    Published 2018-09-01
    “…Moreover, pulse pressure (PP) has not been considered as a potent hemodynamic parameter to describe BP variability during MT. We assessed the impact of PP variability on functional outcome in acute ischemic stroke patients with large vessel occlusion during MT. …”
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    Article
  9. 189

    Free Vibration Analysis of Moderately Thick Rectangular Plates with Variable Thickness and Arbitrary Boundary Conditions by Dongyan Shi, Qingshan Wang, Xianjie Shi, Fuzhen Pang

    Published 2014-01-01
    “…Under the current framework, the one displacement and two rotation functions are generally sought, regardless of boundary conditions, as an improved trigonometric series in which several supplementary functions are introduced to remove the potential discontinuities with the displacement components and its derivatives at the edges and to accelerate the convergence of series representations. …”
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    Article
  10. 190

    Variable Selection for Multivariate Failure Time Data via Regularized Sparse-Input Neural Network by Bin Luo, Susan Halabi

    Published 2025-05-01
    “…For linear marginal hazard models, we develop a penalized pseudo-partial likelihood approach with a group LASSO-type penalty applied to the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi mathvariant="sans-serif-italic">ℓ</mi><mn>2</mn></msub></semantics></math></inline-formula> norms of coefficients corresponding to the same covariates across marginal hazard functions. …”
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  11. 191

    Radiative heat and mass transfer of second-grade nanofluid slip flow with variable thermal properties by Zia Ullah, Md. Mahbub Alam, Aamir Abbas Khan, Shalan Alkarni, Feyisa Edosa Merga

    Published 2025-03-01
    “…The objective of this study is to provide deeper insights into how these variables influence fluid flow characteristics and heat transfer in nanofluid. …”
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    Article
  12. 192

    Comparison Study of Method for Calculation of Mesh Efficiency of Involute Gear Pair by Chen Yinglin Chen Jiangyi

    Published 2019-12-01
    “…Taking the distance between pitch point and contact point as a variable, two expressions of instantaneous efficiency of gear pair are derived from the perspective of work and force. …”
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  13. 193
  14. 194

    Efficiency Assessment of a High-Speed Tracked Vehicle Hybrid Powertrain by Ponorac Luka, Blagojević Ivan

    Published 2025-07-01
    “…This is to prove the argument of the efficiency benefits of electrifying the vehicle turning mechanism and eliminating the friction elements slip. …”
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    Article
  15. 195

    Multimodal bearing fault classification under variable conditions: A 1D CNN with transfer learning by Tasfiq E. Alam, Md Manjurul Ahsan, Shivakumar Raman

    Published 2025-09-01
    “…Bearings play an integral role in ensuring the reliability and efficiency of rotating machinery — reducing friction and handling critical loads. …”
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    Article
  16. 196
  17. 197

    Probabilistic analysis of active earth pressures in spatially variable soils using machine learning and confidence intervals by Tran Vu-Hoang, Tan Nguyen, Jim Shiau, Duy Ly-Khuong, Hung-Thinh Pham-Tran

    Published 2025-03-01
    “…Abstract This study introduces a probabilistic framework for assessing active earth pressures in soils exhibiting spatial variability in friction angles and unit weight. These properties are modeled using random fields with log-normal distributions and spatial correlation lengths. …”
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  18. 198
  19. 199

    Upper-Bound Analysis of Slope Reliability Considering Anisotropic Spatial Variability and Reinforcement with Anti-slide Piles by ZHAO Zi-hao, WANG Jia-rui, FU Tao-tao, ZHU En-lin

    Published 2025-01-01
    “…To ensure that the random field demonstrates general rotational anisotropy, the autocorrelation function was transformed through a coordinate system conversion before the decomposition of the autocorrelation coefficient matrix. …”
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  20. 200

    Construction and analysis of one class of cryptographic functions by Zhi-hui OU, Ya-qun ZHAO, Xu LI

    Published 2013-04-01
    “…A novel class of n+t -variable Boolean functions G (x,y) through adding t variables while concatenating t+ 1 Boolean functions (called basic function) was constructed and the Walsh spectrum and autocorrelation coefficient of G(x,y)were given.The relationship between G(x,y)and basic functions by Krawtchouk polynomial and Krawtchouk matrix was studied.Moreover,their cryptographic properties:correlation immunity,propagation and algebraic immunity were investigated.Specially,the detailed relationship between G (x,y) and basic functions when t= 2 was analyzed.In additional,a novel class of multioutput Boolean functions by generalizing the method was constructed and the general Walsh spectrum of the class of multioutput Boolean functions was proposed.Correlation immunity and algebraic immunity of the class of multioutput Boolean functions were analyzed.…”
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