2 resultados para Time-dependent data

em QSpace: Queen's University - Canada


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BACKGROUND: Moderate-to-vigorous physical activity (MVPA) is an important determinant of children’s physical health, and is commonly measured using accelerometers. A major limitation of accelerometers is non-wear time, which is the time the participant did not wear their device. Given that non-wear time is traditionally discarded from the dataset prior to estimating MVPA, final estimates of MVPA may be biased. Therefore, alternate approaches should be explored. OBJECTIVES: The objectives of this thesis were to 1) develop and describe an imputation approach that uses the socio-demographic, time, health, and behavioural data from participants to replace non-wear time accelerometer data, 2) determine the extent to which imputation of non-wear time data influences estimates of MVPA, and 3) determine if imputation of non-wear time data influences the associations between MVPA, body mass index (BMI), and systolic blood pressure (SBP). METHODS: Seven days of accelerometer data were collected using Actical accelerometers from 332 children aged 10-13. Three methods for handling missing accelerometer data were compared: 1) the “non-imputed” method wherein non-wear time was deleted from the dataset, 2) imputation dataset I, wherein the imputation of MVPA during non-wear time was based upon socio-demographic factors of the participant (e.g., age), health information (e.g., BMI), and time characteristics of the non-wear period (e.g., season), and 3) imputation dataset II wherein the imputation of MVPA was based upon the same variables as imputation dataset I, plus organized sport information. Associations between MVPA and health outcomes in each method were assessed using linear regression. RESULTS: Non-wear time accounted for 7.5% of epochs during waking hours. The average minutes/day of MVPA was 56.8 (95% CI: 54.2, 59.5) in the non-imputed dataset, 58.4 (95% CI: 55.8, 61.0) in imputed dataset I, and 59.0 (95% CI: 56.3, 61.5) in imputed dataset II. Estimates between datasets were not significantly different. The strength of the relationship between MVPA with BMI and SBP were comparable between all three datasets. CONCLUSION: These findings suggest that studies that achieve high accelerometer compliance with unsystematic patterns of missing data can use the traditional approach of deleting non-wear time from the dataset to obtain MVPA measures without substantial bias.

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The formulation of a geotechnical model and the associated prediction of the mechanical behaviour is a challenge engineers need to overcome in order to optimize tunnel design and meet project requirements. Special challenges arise in cases where rocks and rockmasses are susceptible to time-effects and time-dependent processes govern. Progressive rockmass deformation and instability, time-dependent overloading of support and delayed failures are commonly the result of time-dependent phenomena. The research work presented in this thesis serves as an attempt to provide more insight into the time-dependent behaviour of rocks. Emphasis is given on investigating and analyzing creep deformation and time-dependent stress relaxation phenomenon at the laboratory scale and in-depth analyses are presented. This thesis further develops the understanding of these phenomena and practical yet scientific tools for estimating and predicting the long-term strength and the maximum stress relaxation of rock materials are proposed. The identification of the existence of three distinct behavioural stages during stress relaxation is presented and discussed. The main observations associated with time-dependent behaviour are employed in numerical analyses and applied at the tunnel scale. A new approach for simulating and capturing the time-dependent behaviour coupled with the tunnel advancement effect is also developed and analyzed. Guidance is provided to increase the understanding of the support-rockmass interaction and the main implications and significance of time-dependent behaviour associated with rock tunnelling are discussed. The work presented in this thesis advances the scientific understanding of time-dependent rock and rockmass behaviour, increases the awareness of how such phenomena are captured numerically, and lays out a framework for dealing with such deformations when predicting tunnel deformations. Practical aspects of this thesis are also presented, which will increase their usage in the associated industries and close the gap between the scientific and industry communities.