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Showing 581 - 600 results of 2,280 for search '(( variables function coefficiency. ) OR ( variables function efficient. ))*', query time: 0.22s Refine Results
  1. 581

    Correlation between Rainfall and Runoff in Fuchun River Basin Based on Copula Functions and Kernel Density Estimation by YANG Sheng-mei, ZHU De-kang, CHENG Xiang, LI Bo, ZHU Yan-ze, MA Wen-sheng

    Published 2025-05-01
    “…The Gaussian was selected to estimate the marginal distributions of hydrological variables in the Fuchun River Basin, demonstrating higher simulation accuracy without relying on any distribution assumption.(2) By estimating the Kendall and Spearman rank correlation coefficients of the bivariate functions of Gaussian-Copula, t-Copula, Clayton-Copula, Frank-Copula, and Gumbel-Copula, and comparing them with the Kendall and Spearman rank correlation coefficients of the original observed data, it was found that Gaussian-Copula and Gumbel-Copula were closer to the observed data.(3) By calculating the Euclidean distance, the fitting performance of the Copula functions was evaluated. …”
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  2. 582

    An Integrated Slacks-Based Measure of Super-Efficiency with Input Saving and Output Surplus Scaling Factors and its Application in Paper Chemical Mills by Dong Guo, Zheng-Qun Cai

    Published 2020-01-01
    “…This paper revises the usual slacks-based measure of super-efficiency by incorporating input saving and output surplus scaling factors into the objection function for measuring DMUs. …”
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  3. 583

    Relationship between functional movement screening (FMS) scores and balance and strength performance in young male athletes by Şükran İribalcı, Mert Aydoğmuş, Serkan Revan, Harun Genç

    Published 2024-12-01
    “…Shapiro-Wilk test was applied to determine if the data were normally distributed, Pearson’s correlation coefficient analysis was used measure linear correlation, and Spearman’s rank correlation coefficient (ρ) was determined to measure the strength and direction of correlation between variables. …”
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  4. 584

    Detecting changes in retinal function: Analysis with Non-Stationary Weibull Error Regression and Spatial enhancement (ANSWERS). by Haogang Zhu, Richard A Russell, Luke J Saunders, Stefano Ceccon, David F Garway-Heath, David P Crabb

    Published 2014-01-01
    “…Furthermore, the spatial correlation utilised in ANSWERS was shown to improve the ability to detect deterioration, compared to equivalent models without spatial correlation, especially in short follow-up series. ANSWERS is a new efficient method for detecting changes in retinal function. …”
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  5. 585

    On Estimation of Distribution Function Using Dual Auxiliary Information under Nonresponse Using Simple Random Sampling by Saddam Hussain, Mi Zichuan, Sardar Hussain, Anum Iftikhar, Muhammad Asif, Sohail Akhtar, Sohaib Ahmad

    Published 2020-01-01
    “…In this paper, we proposed two new families of estimators using the supplementary information on the auxiliary variable and exponential function for the population distribution functions in case of nonresponse under simple random sampling. …”
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  6. 586

    The Use of High-Density SNP Array to Map Homozygosity in Consanguineous Families to Efficiently Identify Candidate Genes: Application to Woodhouse-Sakati Syndrome by Molly B. Sheridan, Elizabeth Wohler, Denise A. S. Batista, Carolyn Applegate, Julie Hoover-Fong

    Published 2015-01-01
    “…DCAF17, encoding a transmembrane nuclear protein of uncertain function, was the only gene identified in a homozygous region known to cause hypogonadotropic hypogonadism. …”
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  7. 587
  8. 588

    Finite Element Modeling for Buckling Analysis of Tapered Axially Functionally Graded Timoshenko Beam on Elastic Foundation by Masoumeh Soltani

    Published 2020-11-01
    “…In this study, an efficient finite element model with two degrees of freedom per node is developed for buckling analysis of axially functionally graded (AFG) tapered Timoshenko beams resting on Winkler elastic foundation. …”
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  9. 589

    Evaluation the correlation between Inulin and Cystatin C with kidney function tests and GFR in patients with renal disorders by Nawar Mohsin Abd-alaziz, Wasan Nazhan Hussein

    Published 2020-03-01
    “… Background: Kidneys are important organs in the human body because of their great importance in assisting the body to remove waste products that resulting from food metabolism through renal filtration of blood plasma from unwanted substances and excreted through diuresis and recover substances that body needs to the blood, relative effectiveness of the kidney can be estimated by measuring the efficiency of glomerular filteration rate (GRF), represented by amount of inulin filtrate into renal tubules for a specified period of time, any difference in normal value indicates the presence of a disorder in the kidney, which affects on performance of its functions and occurrence of imbalance in internal environment of the body, and leads to disrupting functions of other parts of the body, measuring rate of renal filtration is one of the best ways to know function of the kidneys and diagnose various kidney diseases and prevent their development. …”
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  10. 590

    Gráfico de controle de regressão aplicado na monitoração de processos Regression control chart applied in process monitoring by Luciane Flores Jacobi, Adriano Mendonça Souza, João Eduardo da Silva Pereira

    Published 2002-01-01
    “…This research, therefore, it presents an efficient technique to control simultaneous by correlated variables.…”
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  11. 591
  12. 592

    Polymer-Functionalized Magnetic Nanoparticles for Targeted Quercetin Delivery: A Potential Strategy for Colon Cancer Treatment by Júlia Borges de Macedo, Julia Narayana Schoroeder Bueno, Carla Cristine Kanunfre, José Ricardo de Arruda Miranda, Andris Figueiroa Bakuzis, Priscileila Colerato Ferrari

    Published 2025-04-01
    “…<b>Methods</b>: After FA-CS synthesis and 3<sup>2</sup> factorial design, polymer-functionalized MNPs were produced for quercetin loading, characterized, and evaluated by drug dissolution and cytotoxicity assay. …”
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  13. 593
  14. 594

    Machine learning predicts improvement of functional outcomes in spinal cord injury patients after inpatient rehabilitation by Mohammad Rasoolinejad, Irene Say, Peter B. Wu, Xinran Liu, Yan Zhou, Yan Zhou, Nathan Zhang, Emily R. Rosario, Daniel C. Lu, Daniel C. Lu, Daniel C. Lu

    Published 2025-08-01
    “…The ability to accurately predict functional outcomes for SCI patients is essential for optimizing rehabilitation strategies, guiding patient and family decision making, and improving patient care.MethodsWe conducted a retrospective analysis of 589 SCI patients admitted to a single acute rehabilitation facility and used the dataset to train advanced machine learning algorithms to predict patients' rehabilitation outcomes. …”
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  15. 595

    Innovative machine learning-based prediction of early airway hyperresponsiveness using baseline pulmonary function parameters by Hua Yang, Xingru Zhao, Zhuochang Chen, Lihong Yang, Guihua Zhao, Chenxiao Xu, Jinyi Xu

    Published 2025-08-01
    “…This study explores the potential of baseline pulmonary function parameters, particularly small airway indices, in predicting AHR and develops a machine learning-based model to improve screening efficiency and reduce unnecessary BPT referrals.MethodsThis retrospective study analyzed baseline pulmonary function data and BPT results from Henan Provincial People’s Hospital (May to September 2024). …”
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  16. 596

    SOLVING ENGINEERING OPTIMIZATION PROBLEMS WITH THE SWARM INTELLIGENCE METHODS by A. V. Panteleev, M. D. Evdokimova

    Published 2017-05-01
    “…The purpose of each task is to minimize the cost and weight of the construction. The object functions in optimization practical problem are nonlinear functions with a lot of variables and a complex layer surface indentations. …”
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  17. 597

    Coordinated regulation of water use-efficiency-cost in a winter wheat-summer maize rotation system and optimization of water allocation strategies by Li Zhao, Congying Han, Yinong Li, Baozhong Zhang, Yulu Zheng, Jiabing Cai

    Published 2025-09-01
    “…A multi-objective nonlinear programming model was developed, incorporating triangular fuzzy numbers, accuracy functions, and credibility constraints, to balance actual yield (AY), irrigation water productivity (IWP), and total cost (TC). …”
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  18. 598

    Unveiling potential: Hybrid nanofluid-driven strategies for maximizing electrical efficiency in Photovoltaic Thermal Systems with trapezoidal flow channel for coolant purposes by A.A. Alderremy, Abid A. Memon, A.M. Obalalu, T.H. El-Ghareeb, Amsalu Fenta

    Published 2024-12-01
    “…The PV/T system features a simple configuration, with mono-crystalline silicon above the flow channel, copper functioning as the absorber, and a trapezoidal-shaped flow channel. …”
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  19. 599

    DIFFERENCES IN AGRICULTURAL RETURNS IN SESAME PRODUCTION: AN EMPIRICAL EVIDENCE OF EFFICIENCY IN FACTOR INPUT ALLOCATION IN RINGIM LOCAL GOVERNMENT AREA, JIGAWA STATE, NIGERIA by Tohib Oyeyode OBALOLA, Abdullahi Abbas YAKUBU

    Published 2023-01-01
    “…The results also reveal net farm income and return on naira invested of N 46,190.59 and 1.54 respectively, an indication of a profitable enterprise. The semi-log functional form gave the best fit based on the normal econometric criteria with coefficient of multiple determination of 0.312 implying that about 31 percent of the variation in yield of sesame was explained by the specified explanatory variables. …”
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  20. 600

    Hypercubes to identify geomarkers of rapid cystic fibrosis lung disease progression by Yizi Cheng, Cole Brokamp, Erika Rasnick Manning, Elizabeth L. Kramer, Patrick H. Ryan, Rhonda D. Szczesniak, Emrah Gecili

    Published 2025-08-01
    “…Although geomarkers have been linked to pulmonary outcomes in other respiratory diseases, it is unknown which have the greatest predictive power for rapid lung function decline in CF. Methods We adapted an existing statistical procedure, which arranges candidate variables in a k-dimensional hypercube, where the hypercube forms a set of variables for a multi-stage selection process involving complex longitudinal data. …”
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