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Showing 1,181 - 1,200 results of 2,280 for search 'variable function (((coefficient. OR efficiency.) OR efficiency.) OR efficient.)', query time: 0.13s Refine Results
  1. 1181

    Enhancing wireless applications through reconfigurable electro-mechanical reflectarray antenna design for beam steering by Behrokh Beiranvand, Rashid Mirzavand

    Published 2024-12-01
    “…The proposed design involves multiple reflective strips at variable heights, enabling significant adaptability to incident waves at various angles. …”
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  2. 1182

    Preference set-based design method for qualitative assessments using dominance-based rough set approach by Shotaro OYAMA, Takeo KATO

    Published 2025-04-01
    “…The preference set-based design (PSD) method enhances design efficiency by providing an adjustment range that reflects the preferences of the designer in the quantitative design variables and performance. …”
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  3. 1183

    Synthesis of evasive maneuver control of unmanned aerial vehicle for terminal restrictions by N. Y. Polovinchuk, S. V. Ivanov, L. I. Kotelnitskaya

    Published 2018-07-01
    “…The FV (flying vehicle) control is organized with maximum efficiency. Herewith, the maneuvering FV trajectory must satisfy the requirements of optimality for some given functions of the phase variables at the final time and the conditions of its path through a specified terminal area space. …”
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  4. 1184

    Integrated neural network framework for multi-object detection and recognition using UAV imagery by Mohammed Alshehri, Tingting Xue, Tingting Xue, Ghulam Mujtaba, Yahya AlQahtani, Nouf Abdullah Almujally, Ahmad Jalal, Ahmad Jalal, Hui Liu, Hui Liu, Hui Liu

    Published 2025-07-01
    “…Deep SORT is employed for efficient vehicle tracking, while CSRNet facilitates high-density vehicle counting. …”
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    Article
  5. 1185

    The Design and Analysis of a Lightweight Robotic Arm Based on a Load-Adaptive Hoisting Mechanism by Ruchao Wang, Zhiguo Lu, Yiru Wang, Zhongqing Li

    Published 2025-02-01
    “…The proposed design integrates a spring-loaded rope and a variable radius reel into the gripper, enabling efficient load adaptability with minimal structural complexity. …”
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  6. 1186

    A Simple and Effective KAN-Based Architecture for Accurate Battery RUL Prediction by Guangzai Ye, Li Feng, Jianlan Guo, Yuqiang Chen, Shufei Li

    Published 2025-01-01
    “…Our approach integrates a VMD-based denoising mechanism, compressed into a more compact KAN model via knowledge distillation, to mitigate noise efficiently. It also incorporates a channel-independent KANs structure with a regularized weighted loss function to handle variable-specific degradation patterns. …”
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  7. 1187

    Beyond Spirometry: Linking Wasted Ventilation to Exertional Dyspnea in the Initial Stages of COPD by J. Alberto Neder, Giles Santyr, Brandon Zanette, Miranda Kirby, Marina Pourafkari, Matthew D. James, Sandra G. Vincent, Carrie Ferguson, Chu-Yi Wang, Nicolle J. Domnik, Devin B. Phillips, Janos Porszasz, William W. Stringer, Denis E. O’Donnell

    Published 2024-12-01
    “…Pulmonary function tests estimating the extension of the wasted ventilation and selected cardiopulmonary exercise testing variables can, therefore, shed unique light on the genesis of patients’ out-of-proportion dyspnea. …”
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  8. 1188

    Bankruptcy rules and sustainable water management: A MODSIM-NSGAII simulation multi-objective optimization framework for equitable transboundary water allocation by Bentolhoda Asl-Rousta, S. Jamshid Mousavi

    Published 2025-06-01
    “…This study addresses these challenges by introducing a new optimal bankruptcy rule (OpPro rule) through a simulation-optimization model (MODSIM-NSGAII), where MODSIM simulates the spatial and temporal variability of water resources, and the NSGA-II optimization algorithm includes two objective functions of maximizing basin-wide ecological sustainability and maximizing economic efficiency reflecting ''equitable and reasonable utilization'' of water. …”
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  9. 1189

    p53 transactivation and the impact of mutations, cofactors and small molecules using a simplified yeast-based screening system. by Virginia Andreotti, Yari Ciribilli, Paola Monti, Alessandra Bisio, Mattia Lion, Jennifer Jordan, Gilberto Fronza, Paola Menichini, Michael A Resnick, Alberto Inga

    Published 2011-01-01
    “…<h4>Methodology/principal findings</h4>Given the many factors that might influence p53 function, including expression levels, mutations, cofactor proteins and small molecules, we expanded our previously described yeast-based system to provide the opportunity for efficient investigation of their individual and combined impacts in a miniaturized format. …”
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  10. 1190

    Optimization Design of Fast Neutron Target Station Beam Extraction Based on Genetic Algorithm by QIN Ziqian1, 2, 3, TAN Xinjian2, 3, ZHANG Xiaodong2, 3, PAN Qingquan1, LIU Xiao2, 3

    Published 2025-03-01
    “…Therefore, the aforementioned parameters are used as variables, and the three important indicators are taken as the objective function. …”
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  11. 1191

    Evaluating Sensitivity of the Ranking of Forest Fuel Treatments to Manager’s Risk Attitudes and the Importance of Treatment Objectives, Montana, USA by Tony Prato, Travis Paveglio

    Published 2019-01-01
    “…The conceptual framework involves (1) defining a utility function on an index that is a weighted average of fuel treatment objectives and incorporates a manager’s risk attitude; (2) using the utility function to calculate utility values for FTSs; (3) applying the stochastic efficiency with respect to a function method to utility values to obtain certainty equivalents (CEs); and (4) ranking FTSs based on statistically significant differences in median CEs for pairs of FTSs. …”
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  12. 1192

    A robust deep learning approach for photovoltaic power forecasting based on feature selection and variational mode decomposition by Mokhtar Ali, Abdelkerim Souahlia, Abdelhalim Rabehi, Mawloud Guermoui, Ali Teta, Imad Eddine Tibermacine, Abdelaziz Rabehi, Mohamed Benghanem

    Published 2025-08-01
    “…To further enhance model inputs, Variational Mode Decomposition (VMD) is applied to extract informative Intrinsic Mode Functions (IMFs) from the selected features. A comparative evaluation of the models indicates that recurrent neural networks, particularly GRU and LSTM, deliver superior performance across various metrics, including RMSE, MAE, nRMSE, nMAE, R², and the correlation coefficient. …”
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  13. 1193

    How Does Digital Banking-Driven Financial Inclusion Affect Income Inequality in Türkiye? by Ahmet Usta

    Published 2023-08-01
    “…As for the empirical evidence, the study employs the dynamic ordinary least squares method to obtain long-run coefficients, a vector autoregressive model to obtain short-run dynamics through impulse response functions with biascorrected bootstrap confidence intervals that account for the bias and skewness of the small sample, and a causality analysis. …”
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  14. 1194

    Robust IoT Activity Recognition via Stochastic and Deep Learning by Xuewei Wang, Shihao Wang, Xiaoxi Zhang, Chunsheng Li

    Published 2025-04-01
    “…Additionally, our framework incorporates IoT security measures designed to safeguard data integrity and privacy, marking a significant advancement over existing methods in both efficiency and effectiveness.…”
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    Article
  15. 1195

    Factors Determining Trade Credit Dynamics During Crisis: Panel Data Analysis for Macedonian Firms by F. Deari, V. V. Lakshina

    Published 2019-05-01
    “…The study includes a review of the literature on commercial credit factors; elaborately analyzed descriptive statistics of the collected data and dependent variable variance; tests for unobservable effects and their functional form; evaluation of panel regression and interpretation of the results. …”
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  16. 1196

    fNIRS neurofeedback facilitates emotion regulation: Exploring individual differences over the ventrolateral prefrontal cortex by Yiwei Li, Sijin Li, Hua Li, Yuyao Tang, Dandan Zhang

    Published 2025-03-01
    “…Participants in the experimental group underwent VLPFCNF training over eight sessions across two consecutive days, while those in the sham group received random signals from functional near-infrared spectroscopy (fNIRS). To investigate individual variability, participants in the experimental group were further categorized as high or low-efficacy groups based on their training efficiency, determined by the regression slope of VLPFC activity over the sessions. …”
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  17. 1197

    Stochastic Transportation Problem with Multichoice Random Parameter by Talari Ganesh, K. K. Paidipati, Christophe Chesneau

    Published 2023-01-01
    “…This paper deals with the situation of multiple random choices along with multiple objective functions of the transportation problem. Due to the uncertainty in the environment, the choices of the cost coefficients are considered multichoice random parameters. …”
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  18. 1198

    Analysis of value-based healthcare (VBHC) framework by incremental cost-effectiveness of surgical and therapeutic interventions: a retrospective study at tertiary private health gr... by Mona Khamis, Zainab Almoosa, Marie Santos, Engineer Diaa Kamal, Suhail Yaghmor, Muhammad Daniyal, Abbas Al Mutair

    Published 2025-08-01
    “…Abstract Background Rising healthcare costs have led to the adoption of value-based healthcare (VBHC), emphasizing patient outcomes and cost efficiency. This study evaluates VBHC in a tertiary private health group, focusing on cost-effectiveness using the median incremental cost-effectiveness ratio (ICER). …”
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  19. 1199

    Color image hybrid noise filtering algorithm based on deep convolution neural network by Yongfei Yu, Yuanjian Yan

    Published 2024-12-01
    “…Then, the probability density function and noise probability density function of Gaussian noise are calculated to determine the hybrid noise feature points of color image. …”
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  20. 1200

    Ridge regression and its applications in genetic studies. by M Arashi, M Roozbeh, N A Hamzah, M Gasparini

    Published 2021-01-01
    “…On the other hand, the efficiency of the rank ridge regression estimator is highly dependent on the ridge parameter. …”
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