Search alternatives:
coefficient. » efficient. (Expand Search)
Showing 101 - 120 results of 963 for search 'variables function coefficient.', query time: 0.16s Refine Results
  1. 101

    Experimental Study: Stress Path Coefficient in Unconsolidated Sands: Effects of Re-Pressurization and Depletion Hysteresis by Sabyasachi Prakash, Michael Myers, George Wong, Lori Hathon, Duane Mikulencak

    Published 2024-12-01
    “…It investigates the variability of horizontal stress path coefficient as a function of changing pore pressure (depressurization and re-pressurization) in unconsolidated sandstone reservoirs. …”
    Get full text
    Article
  2. 102

    Method of calculating the acoustical wave reflection coefficient from a not-sharp boundary of two media by Marek HAGEL

    Published 2015-07-01
    “…Changes in the physical properties of the transient layer, determined by the changes in its material parameters, occur along its thickness and can by described by arbitrary one-variable functions. Results of theoretical calculations of the reflection coefficient were given for chosen cases of material parameter changes in the transient layer and they were compared with results of measurements conducted on a physical model. …”
    Get full text
    Article
  3. 103

    Carotid Intima-Media Thickness and Visit-to-Visit HbA1c Variability Predict Progression of Chronic Kidney Disease in Type 2 Diabetic Patients with Preserved Kidney Function by Akiko Takenouchi, Ayaka Tsuboi, Miki Kurata, Keisuke Fukuo, Tsutomu Kazumi

    Published 2016-01-01
    “…Subclinical atherosclerosis and long-term glycemic variability predict deterioration of chronic kidney disease (as defined by incident or worsening CKD) in type 2 diabetic patients with preserved kidney function.…”
    Get full text
    Article
  4. 104

    Evaluation of remote sensing soil moisture data products with a new approach to analyse footprint mismatch with in-situ measurements by Qiuxia Xie, Li Jia, Massimo Menenti, Qiting Chen, Jingxue Bi, Yonghui Chen, Chunmei Wang, Xinju Yu

    Published 2024-12-01
    “…SMAP L3.0, ASCAT V3.0, ESA/CCI V7.1 and GLDAS V2.2) are vital for applications in hydrology, climate variability, and agriculture. This study uses a new SSM evaluation approach by combining temporal evolution, Coefficient of Variation (CV), Cumulative Distribution Function (CDF), evaluation metrics, and Triple Collocation Analysis (TCA) to assess SSM accuracy and spatial–temporal variability, particularly the impact of footprint mismatch when comparing retrieved SSM with in-situ measurements. …”
    Get full text
    Article
  5. 105

    Resolving structural variability in network models and the brain. by Florian Klimm, Danielle S Bassett, Jean M Carlson, Peter J Mucha

    Published 2014-03-01
    “…Large-scale white matter pathways crisscrossing the cortex create a complex pattern of connectivity that underlies human cognitive function. Generative mechanisms for this architecture have been difficult to identify in part because little is known in general about mechanistic drivers of structured networks. …”
    Get full text
    Article
  6. 106
  7. 107

    Effects of Mental Fatigue on Gait Performance and Variability by Ali Zardosht, Jessie Daw, Lee T Atkins, C Roger James, Hyung Suk Yang

    Published 2025-01-01
    “…OBJECTIVES Mental fatigue has been shown to negatively impact physical performance, including motor skills and neuromuscular function. This study aimed to investigate the effects of mental fatigue on gait performance and variability in healthy young male adults. …”
    Get full text
    Article
  8. 108
  9. 109

    Multiyear Measurements of the Aerosol Absorption Coefficient Near the Surface in a Small-Sized Urban Area in Portugal by Sérgio Nepomuceno Pereira, Frank Wagner, Ana Maria Silva

    Published 2014-01-01
    “…Also, a strong negative correlation between the aerosol absorption coefficient and the wind speed was verified, and an exponential decay function was found to fit very well to the data. …”
    Get full text
    Article
  10. 110

    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.…”
    Get full text
    Article
  11. 111

    Bio-optical variability of particulate matter in the Southern Ocean by Juan Li, Juan Li, David Antoine, David Antoine, Yannick Huot

    Published 2024-10-01
    “…Here, we combined field measurements from hydrographic casts from two research voyages and from autonomous profiling floats (BGC-Argo) to examine particulate bio-optical properties and relationships among several ecologically and optically important variables, namely the phytoplankton chlorophyll a concentration (Chl), the particulate absorption coefficient (ap), the particulate backscattering coefficient (bbp), and the particulate organic carbon (POC) concentration. …”
    Get full text
    Article
  12. 112

    Spatial variability of the snow depth on mountain slope in Svalbard by P. A. Chernous, N. I. Osokin, R. A. Chernov

    Published 2018-09-01
    “…The study was carried out to estimate the spatial variability of snow cover depths in avalanche centers of the mountain slopes of Svalbard. …”
    Get full text
    Article
  13. 113

    The Zhegalkin Polynomial of Multiseat Sole Sufficient Operator by Leonid Y. Bystrov, Egor V. Kuzmin

    Published 2023-06-01
    “…The value of it allows one to determine the self-duality of a Boolean function. It is proved that the preserving 0 and 1 or preserving neither 0 nor 1 Boolean function is self-dual if and only if the dual remainder of its corresponding Zhegalkin polynomial is equal to 0 for any sets of function variable values. …”
    Get full text
    Article
  14. 114

    Related factors and prognostic significance of predialysis blood pressure variability by LV Yu-feng, DONG Hai-xia

    Published 2018-01-01
    “…Objective To study the clinical variables that may plausibly influence predialysis systolic blood pressure variability(SBPV),and to investigate the correlations of predialysis SBPV with all-cause mortality in patients receiving prevalent maintenance hemodialysis(MHD).Methods A total of 50 patients were enrolled in the study.All the blood pressure values before each dialysis were recorded between March and May in 2011.The mean systolic pressure(SBP)was calculated,and SBPV was estimated with the coefficient of variability.During the three months,clinical data and related biochemical parameters were collected,and echocardiography was carried out to detect cardiac structure and function.Death events were recorded during the next five years.Results The predialysis SBPV was 8.5% ±2.1%.SBPV showed a positive correlation with the age,body mass index(BMI)and left atrial diameter(LAD)(P<0.05 for all).Meantime,SBPV showed a negative correlation with the serum creatinine(SCr),average DBP,parathyroid hormone(PTH),doses of calcium carbonate and activated vitamin D(P<0.05).Patients with diabetes mellitus(DM),coronary artery disease(CAD)or taking alfablocker had higher SBPV(P<0.05).SBPV was used as a variate for conducting the multiple linear regression analysis,after adjustment,the seven variables of age,DM,CAD,BMI,LAD,SCr and taking alfa-blocker maintained their associations with predialysis SBPV(P<0.05).The equation of R~2=0.630.During 5 years of follow-up,12 patients died(24.0%).The Kaplan-meier survival analysis showed that the predialysis SBPV elevation was associated with the mortality rate(P<0.01).Conclusions Advanced age,the history of DM and/or CAD,lower SCr,higher BMI and LAD,and taking alpha-blocker were the independent risk factors of increased predialysis SBPV.The predialysis SBPV increase is associated with all-cause mortality in patients given prevalent MHD.…”
    Get full text
    Article
  15. 115

    Inter-phantom variability in digital mammography: implications for quality control by Gisella Gennaro, Gilberto Contento, Andrea Ballaminut, Francesca Caumo

    Published 2025-04-01
    “…Variability was assessed by calculating intra- and inter-phantom variances and coefficients of variation (COVs). …”
    Get full text
    Article
  16. 116

    Modeling the Impact of Fabrication Variabilities on the Performance of Silicon Avalanche Photodetectors by David Liu, Luca F. Errico, Matteo G. C. Alasio, Mike Zhu, Enrico Bellotti

    Published 2024-01-01
    “…This work presents a systematic study of the sensitivities of silicon avalanche photodiode (APD) performance metrics, including gain, excess noise, and bandwidth, to potential variabilities in the fabrication process. The APDs simulations are performed using a state-of-the-art Full-Band Monte Carlo (FBMC) device simulator with the integrated band structure and scattering rates calculated <inline-formula><tex-math notation="LaTeX">$\mathit{ab{-}initio}$</tex-math></inline-formula> with density-functional theory (DFT). …”
    Get full text
    Article
  17. 117

    A novel extraction model optimization with effective separation coefficient for rare earth extraction process using improve differential evolution by Fangping Xu, Hui Yang, Jianyong Zhu, Wenjia Chang

    Published 2025-04-01
    “…This model also facilitates the construction of an optimized objective function for determining the effective separation coefficient. …”
    Get full text
    Article
  18. 118

    A study on the effect of spatially variation rainfall on urban flooding by Jinping Zhang, Ruyu Wang, Xuechun Li, Zhiwei Li, Yao Wang, Xi Zhang

    Published 2025-12-01
    “…A three-dimensional probabilistic model, incorporating the variation coefficient, total rainfall, and flooding risk, was constructed using the Copula function. …”
    Get full text
    Article
  19. 119

    Heart Rate Variability Time-Domain Analysis Across Glaucoma Subtypes by Yuto Yoshida, Hinako Takei, Misaki Ukisu, Keigo Takagi, Masaki Tanito

    Published 2025-04-01
    “…This study aimed to investigate the association between different glaucoma subtypes and the following time-domain heart rate variability (HRV) parameters: the standard deviation of normal-to-normal intervals (SDNN), the square root of the mean of the sum of the squared differences between adjacent normal-to-normal intervals (RMSSD), and the coefficient of variation of R-R intervals (CVRR). …”
    Get full text
    Article
  20. 120

    Factors associated with high glucose variability in patients with type 1 diabetes by V. V. Klimontov, Ju. F. Semenova, A. I. Korbut

    Published 2022-10-01
    “…BACKGROUND: High glucose variability (GV) is recognized as a risk factor for vascular diabetic complications and hypoglycemia. …”
    Get full text
    Article