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  1. 321

    Structural optimization of stiffened panel structures with continuous and discrete design variables using deep reinforcement learning by Ryota NONAMI, Mitsuru KITAMURA

    Published 2025-05-01
    “…To overcome such an environment, in this study, an optimization flow for structural optimization is considered, and states, actions, and rewards appropriately representing design variables, constraint conditions, and objective functions are discussed. …”
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    Article
  2. 322

    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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  3. 323

    An Efficient Sparse Twin Parametric Insensitive Support Vector Regression Model by Shuanghong Qu, Yushan Guo, Renato De Leone, Min Huang, Pu Li

    Published 2025-07-01
    “…Similar to twin parametric insensitive support vector regression (TPISVR), STPISVR constructs a pair of nonparallel parametric insensitive bound functions to indirectly determine the regression function. …”
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  4. 324

    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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    Article
  5. 325

    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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    Article
  6. 326

    Computationally Efficient Hybrid Downscaling of Surf Zone Hydrodynamics: Methodology and Evaluation by E. R. Echevarria, S. Contardo, B. Pérez‐Díaz, R. K. Hoeke, B. Leighton, C. Trenham, L. Cagigal, F. J. Méndez

    Published 2025-06-01
    “…Abstract We present a hybrid surf‐zone model that combines numerical simulations and statistical/machine learning techniques, enabling accurate calculations of nearshore wave and hydrodynamic parameters with high computational efficiency. The approach involves defining representative forcing conditions, carrying out numerical model (XBeach) simulations for these cases, and training machine learning models capable of predicting selected model output variables. …”
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  9. 329

    Efficiency of the Outpatient Diabetes Care System in Czechia: A Geodemographic Perspective by Kateřina Brázová, Luděk Šídlo, Jan Bělobrádek

    Published 2024-09-01
    “…The paper examines the intensity and structure of the use of health services and outlines the current functioning thereof in the context of diabetes care in Czechia. …”
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  10. 330

    Weight illusions explained by efficient coding based on correlated natural statistics by Paul M. Bays

    Published 2024-12-01
    “…We show that the precision with which human observers estimate object weight varies as a function of both mass and volume in a manner consistent with the estimated joint distribution of those properties among everyday objects. …”
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    Article
  11. 331

    Analyzing the influence of regulatory capture on environmental efficiency within institutional frameworks by Feng Wang, Feng Wang, Farooq Muhammad Sabil, Farooq Muhammad Sabil, Nazia Feroze, Cheng Tongshun, Faisal Feroze

    Published 2025-07-01
    “…It utilizes provincial-level panel data from China and applies the Slack-Based Measure (SBM) model to assess environmental efficiency. Key institutional variables—including indicators of government quality and legal robustness—are incorporated to examine how they interact with and influence the effects of regulatory capture.ResultsFindings reveal that regulatory capture significantly hinders regional environmental efficiency. …”
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    Enhanced Lightweight YOLO Model for Efficient Vehicle Detection in Satellite Imagery by Mohamad Haniff Junos, Anis Salwa Mohd Khairuddin, Elmi Abu Bakar, Ahmad Faizul Hawary

    Published 2025-06-01
    “…Vehicle detection in satellite images is a challenging task due to the variability in scale and resolution, complex background, and variability in object appearance. …”
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    A Method for Solving LiDAR Waveform Decomposition Parameters Based on a Variable Projection Algorithm by Ke Wang, Guolin Liu, Qiuxiang Tao, Luyao Wang, Yang Chen

    Published 2020-01-01
    “…First, using a variable projection algorithm, we separated the linear (amplitude) and nonlinear (center position and width) parameters in the Gaussian function model; the linear parameters are expressed with nonlinear parameters by the function. …”
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  17. 337

    DANNET: deep attention neural network for efficient ear identification in biometrics by Deepthy Mary Alex, Kalpana Chowdary M., Hanan Abdullah Mengash, Venkata Dasu M., Natalia Kryvinska, Chinna Babu J., Ajmeera Kiran

    Published 2024-12-01
    “…This shift has highlighted the need for reliable biometric systems that can function effectively even when facial features are partially obscured. …”
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  18. 338

    Using Wearable Inertial Sensors to Estimate Kinematic Parameters and Variability in the Table Tennis Topspin Forehand Stroke by Ziemowit Bańkosz, Sławomir Winiarski

    Published 2020-01-01
    “…The large intraindividual variability in movement was probably functional (i.e., motor adjustment and injury avoidance). …”
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    Safety Performance Functions for Low-Volume Roads by Gianluca Dell’Acqua, Francesca Russo

    Published 2011-12-01
    “…The research study presented here has been used to calibrate crash prediction models (CPMs) per kilometer per year. The coefficients of the CPMs are estimated using a non-linear multi-variable regression analysis utilizing the least – square method. …”
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