TUNING TO ROAD AND LOAD PASSIVE SUSPENSIONS MULTI-MODELLING AND OPTIMISATION

This work explores the ability to apply multi-modeling technique of new suspension system based on a shock absorber model VZN (European Patent 1190184/20052). Here are presented the results of their own scientific research on the multi-modelling a auto vehicles suspension systems based on passive hydraulic shock absorbers with variable damping characteristics depending on the position of the sprung mass and road conditions. For such a system was proposed and verified by in Matlab-Simulink simulation, a procedure for optimizing the damping characteristics of the road conditions and load given. Suspension system is represented by a quarter-car multi-model with one degree of freedom and representative way perturbation by white noise. Proposed new criterion function in optimisation self-adaptive passive suspension

Quantifying the Varying Predictive Value of Physical Activity Measures Obtained from Wearable Accelerometers on All-Cause Mortality Over Short to Medium Time Horizons in NHANES 2003-2006

Physical activity measures derived from wearable accelerometers have been shown to be highly predictive of all-cause mortality. Prediction models based on traditional risk factors and accelerometry-derived physical activity measures are developed for five time horizons. The data set contains 2978 study participants between 50 and 85 years old with an average of 13.08 years of follow-up in the NHANES 2003–2004 and 2005–2006. Univariate and multivariate logistic regression models were fit separately for five datasets for one- to five-year all-cause mortality as outcome (number of events 46, 94, 155, 218, and 297, respectively). In univariate models the total activity count (TAC) was ranked first in all five horizons (AUC between 0.831 and 0.774) while the active to sedentary transition probability (ASTP) was ranked second for one- to four-year mortality models and fourth for the five-year all-cause mortality model (AUC between 0.825 and 0.735). In multivariate models age and ASTP were significant in all one- to five-year all-cause mortality prediction models. Physical activity measures are consistently among the top predictors, even after adjusting for demographic and lifestyle variables. Physical activity measures are strong stand-alone predictors and substantially improve the prediction performance of models based on traditional risk factors

The Predictive Performance of Objective Measures of Physical Activity Derived From Accelerometry Data For 5-Year All-Cause Mortality in Older Adults: National Health and Nutritional Examination Survey 2003-2006

Background: Declining physical activity (PA) is a hallmark of aging. Wearable technology provides reliable measures of the frequency, duration, intensity, and timing of PA. Accelerometry-derived measures of PA are compared to established predictors of 5-year all-cause mortality in older adults in terms of individual, relative, and combined predictive performance. Methods: Participants between 50 and 85 years old from the 2003-2006 National Health and Nutritional Examination Survey (NHANES, n = 2978) wore a hip-worn accelerometer in the free-living environment for up to 7 days. A total of 33 predictors of 5-year all-cause mortality (number of events = 297), including 20 measures of objective PA, were compared using univariate and multivariate logistic regression. Results: In univariate logistic regression, the total activity count was the best predictor of 5-year mortality (AUC = 0.771) followed by age (AUC = 0.758). Overall, 9 of the top 10 predictors were objective PA measures (AUC from 0.771 to 0.692). In multivariate regression, the 10-fold cross-validated AUC was 0.798 for the model without objective PA variables (9 predictors) and 0.838 for the forward selection model with objective PA variables (13 predictors). The Net Reclassification Index (NRI) was substantially improved by adding objective PA variables (p \u3c .001). Conclusions: Objective accelerometry-derived PA measures outperform traditional predictors of five-year mortality, including age. This highlights the importance of wearable technology for providing reproducible, unbiased, and prognostic biomarkers of health

Shock Absorbers Multi-Modeling and Suspension Optimization

The standard dampers used by more 90% of vehicles have damping coefficients constant along stroke, so they can’t solve simultaneous all of them, situation solving practically using a relative dampingcoefficient able to made compromise between them. This paper design and simulation testing multi-models of two types of Damp (DSA and VZN). To compare the two types of suspension they are simulated in various road and load conditions. Analysis of simulation results is presente a new VZN shock absorber. This is an invention of the Institute of Mechanics of the Romanian Academy, and patented at European and U.S. [1], [2]. This is Called VZN shock absorber, iscoming from Variable Zeta Necessary acronym, for well moving in all road and load Conditions, Where zeta Represents the relative damping, Which is Adjusted automatically, stepwise, According to the piston positions [3,4,5]. Suspension systems are used in all air and ground transportation to protect that building transportation and cargo transported around against shocks and vibrations induced in the systemfrom the road Modifying damping coefficients (Zeta) function piston position, being correlated with vehicle load and road unevenness