Showing 141 - 160 results of 1,457 for search '(( variables function efficient. ) OR ( variables function efficiency. ))*', query time: 0.08s Refine Results
  1. 141

    Increasing constraint of aridity on tree intrinsic water use efficiency by Mengjie Wang, Shushi Peng, Zihan Lu, Xiangtao Xu, Andrew Felton, Anping Chen

    Published 2025-08-01
    “…Abstract The intrinsic water use efficiency (W) of trees serves as a key variable linking water and carbon fluxes in forest ecosystems. …”
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    Article
  2. 142

    Acid-Activated Biochar for Efficient Elimination of Amoxicillin From Wastewater by David Adu-Poku, Selina Ama Saah, Patrick Opare Sakyi, Charles Kwame Bandoh, Benjamin Agyei-Tuffour, David Azanu, Michael Oteng-Peprah, Issifu Hawawu, Samuel Azibere, Kweku Amaning Affram

    Published 2024-01-01
    “…In exploring the potential of agricultural waste as an efficient adsorbent, acid-activated coconut husk biochar was prepared, characterized and applied to remove amoxicillin from wastewater. …”
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  3. 143

    Numerical modeling for optimized sediment deflection with variable submergence over a row of submerged vanes by Vikalp Chauhan, Ellora Padhi, Gopal Das Singhal

    Published 2025-04-01
    “…This research examines the potential for improved sediment deflection efficiency through the optimisation of variable submergence. …”
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  4. 144

    Hereditary angioedema diagnosis evaluation score (HADES): A new clinical scoring system for predicting hereditary angioedema with C1 inhibitor deficiency by Ricardo Zwiener, MD, Rafael Zamora, MD, Carlos María Galmarini, MD, PhD, Laura Brion, PhD, Laura Arias, MD, Andrea Pino, MD, Paula Rozenfeld, PhD

    Published 2025-05-01
    “…Objective: We developed a predictive score using clinical variables for suspected HAE patients with C1 inhibitor deficiency (HAE-C1INH) to increase suspicion of HAE and thus improve diagnosis. …”
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    Article
  5. 145

    A STUDY OF THE DETERMINANTS OF THE OLIVE CROP PRODUCTION IN NINEVEH PROVINCE: BASHIQA DISTRICT AS A CASE STUDY FOR THE SEASON 2010 by Abdul Salam Hussein, Salah Fahmi Shaba

    Published 2017-06-01
    “…The Output of the olive crop was considered as the explanatory variable and the total cost in Iraqi Dinar is considered as dependant variable. …”
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  6. 146

    Significance of dissipative flow on a second-grade nanofluid with variable thermal properties on the stretching surface by Zia Ullah, Aamir Abbas Khan, Shalan Alkarni, Abhinav Kumar, N. Beemkumar, Tushar Aggarwal, Ashwin Jacob, Jajneswar Nanda, Feyisa Edosa Merga

    Published 2025-05-01
    “…Boundary conditions are used for the analysis of heat and mass transmission. Stream functions and similarity variables are utilized to reduce the complexity of the governed PDEs (partial differential equations) and altered into ODEs (ordinary differential equations). …”
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  7. 147

    Neuro-fuzzy control of bilateral teleoperation system with transmission timedelay and force feedback using Arduino Due board by Hakima Rahem, Rabah Mellah, Massinissa Zidane, Abdelhakim Saim

    Published 2025-06-01
    “…In order to demonstrate the efficiency, adaptability and advantages of ANFIS controller, several comparative experiments are carried out using different controllers (ANFIS, conventional PI and PI regulator with the modified wave variable method PI+MWVM). …”
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  8. 148
  9. 149

    Improving the Minimum Free Energy Principle to the Maximum Information Efficiency Principle by Chenguang Lu

    Published 2025-06-01
    “…The G theory is based on the P-T probability framework and, therefore, allows for the use of truth, membership, similarity, and distortion functions (related to semantics) as constraints. Based on the study of the <i>R</i>(<i>G</i>) function and logical Bayesian Inference, this paper proposes the Semantic Variational Bayesian (SVB) and the Maximum Information Efficiency (MIE) principle. …”
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  10. 150

    Efficient bit labeling in factorization machines with annealing for traveling salesman problem by Shota Koshikawa, Aruto Hosaka, Tsuyoshi Yoshida

    Published 2025-07-01
    “…Abstract To efficiently determine an optimum parameter combination in a large-scale problem, it is essential to convert the parameters into available variables in actual machines. …”
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  11. 151

    Efficient curve fitting with penalized B-splines for oceanographic and ecological applications by Kwan-Young Bak, Dong-Young Lee, Ju-Seong Lee, Hee-Jung Jee, R. Jisung Park, Ja-Yong Koo, Jae-Hwan Jhong

    Published 2025-07-01
    “…The total variation penalty controls curve smoothness by penalizing abrupt changes in the estimated function, while the group penalty ensures that all response variables share a consistent set of knots, enhancing interpretability. …”
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  12. 152

    The dichotomy of human decision-making: An experimental assessment of stone tool efficiency. by David Nora, João Marreiros, Walter Gneisinger, Antonella Pedergnana, Telmo Pereira

    Published 2025-01-01
    “…This strongly suggests that each raw material used in archaeological contexts to produce blanks should be evaluated for its efficiency. In addition, it may be pertinent to extend this approach to other blunt artefactssuch as scrapers, burins, anvils, and hammerstones when investigating aspects of interconnected behaviours such as artefact variability, resource economy, group mobility, and site function. …”
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  13. 153

    PRODUCTIVITY AND EFFICIENCY OF MAIZE (ZEA MAYS) FARMERS IN ADAMAWA STATE, NIGERIA by Abdu Karniliyus TASHIKALMA, Dengle Yuniyus GIROH

    Published 2024-01-01
    “…Education and extension contact were statistically significant (p≤0.05) and increase technical efficiency among respondents. Furthermore, the stochastic cost function analysis indicated that 80.24% variations in allocative efficiencies were as a result of the variables included in the model. …”
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  14. 154

    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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  15. 155

    Technical Efficiency of Sweet Potato Production: A Stochastic Frontier Analysis by Godfrey C. Onuwa, Solomon T. Folorunsho, Ganiyu Binuyo, Mercy Emefiene, Onyekwere P. Ifenkwe

    Published 2021-08-01
    “…Data collected was analyzed using descriptive statistics and stochastic frontier production function. The socioeconomic variables of the respondents affected their farm efficiency and level of farm output. …”
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  16. 156

    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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  17. 157

    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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  18. 158
  19. 159

    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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  20. 160