Data Processing Decisions Research Articles

Issues Related to Measuring and Interpreting Objectively Measured Sedentary Behavior Data

The use of objective measures of sedentary behavior has increased over the past decade; however, as is the case for objectively measured physical activity, methodological decisions before and after data collection are likely to influence the outcomes. The aim of this article is to review the evidence on different methodological decisions made by researchers when examining sedentary behavior. The different issues researchers may encounter when measuring sedentary behavior have been divided into (a) activity monitor placement; (b) epochs, cut points, and non-wear time definitions; (c) criteria for sedentary behavior bouts and breaks; and (d) combining motion and posture data. This article recommends that (a) activity monitors should be placed on the thigh and combined with a data reduction approach that estimates inclination, especially in children and adults; and (b) researchers should clearly report their data processing decisions to enhance the ability to evaluate and compare studies in the future. However, the article also highlights a dearth of methodological evidence to inform the use of objective measures of sedentary behavior. Based on the gaps in the literature, research recommendations, which require addressing to develop a best practice protocol when measuring sedentary behavior objectively, have been made.

WSN in cyber physical systems: Enhanced energy management routing approach using software agents

Recently, the cyber physical system has emerged as a promising direction to enrich the interactions between physical and virtual worlds. Meanwhile, a lot of research is dedicated to wireless sensor networks as an integral part of cyber physical systems. A wireless sensor network (WSN) is a wireless network consisting of spatially distributed autonomous devices that use sensors to monitor physical or environmental conditions. These autonomous devices, or nodes, combine with routers and a gateway to create a typical WSN system. Shrinking size and increasing deployment density of wireless sensor nodes implies the smaller equipped battery size. This means emerging wireless sensor nodes must compete for efficient energy utilization to increase the WSN lifetime. The network lifetime is defined as the time duration until the first sensor node in a network fails due to battery depletion. One solution for enhancing the lifetime of WSN is to utilize mobile agents. In this paper, we propose an agent-based approach that performs data processing and data aggregation decisions locally i.e., at nodes rather than bringing data back to a central processor (sink). Our proposed approach increases the network lifetime by generating an optimal routing path for mobile agents to transverse the network. The proposed approach consists of two phases. In the first phase, Dijkstra’s algorithm is used to generate a complete graph to connect all source nodes in a WSN. In the second phase, a genetic algorithm is used to generate the best-approximated route for mobile agents in a radio harsh environment to route the sensory data to the base-station. To demonstrate the feasibility of our approach, a formal analysis and experimental results are presented.

Accelerometer Test-Retest Reliability by Data Processing Algorithms: Results From the Twin Cities Walking Study

The purpose of this study was to determine 1) the test-retest reliability of adult accelerometer-measured physical activity, and 2) how data processing decisions affect physical activity levels and test-retest reliability. 143 people wore the ActiGraph accelerometer for 2 7-day periods, 1 to 4 weeks apart. Five algorithms, varying nonwear criteria (20 vs. 60 min of 0 counts) and minimum wear requirements (6 vs. 10 hrs/day for ≥ 4 days) and a separate algorithm requiring ≥ 3 counts per min and ≥ 2 hours per day, were used to process the accelerometer data. Processing the accelerometer data with different algorithms resulted in different levels of counts per day, sedentary, and moderate-to-vigorous physical activity. Reliability correlations were very good to excellent (ICC = 0.70-0.90) for almost all algorithms and there were no significant differences between physical activity measures at Time 1 and Time 2. This paper presents the first assessment of test-retest reliability of the Actigraph over separate administrations in free-living subjects. The ActiGraph was highly reliable in measuring activity over a 7-day period in natural settings but data were sensitive to the algorithms used to process them.

Leaf area index uncertainty estimates for model–data fusion applications

Estimates of data uncertainties are required to integrate different observational data streams as model constraints using model–data fusion. We describe an approach with which random and systematic uncertainties in optical measurements of leaf area index [LAI] can be quantified. We use data from a measurement campaign at the spruce-dominated Howland Forest AmeriFlux site for illustrative purposes. We made measurements along two transects (one in a mature stand, one in a recently harvested shelterwood) before sunset on successive days using both the Li-Cor LAI-2000 plant canopy analyzer and digital hemispherical photography (DHP). The random measurement uncertainty (1 σ) at a given point for a single measurement is about 5% for LAI-2000 and 10% for DHP. These uncertainties are small compared to potential systematic biases due to instrument calibration errors and data processing decisions, which are estimated to be 10–20% for each instrument. Sampling uncertainty (due to the spatial variability along each transect where we conducted our measurements) is an additional, but again relatively small, uncertainty. Assumptions about clumping parameters, for which standard literature values are typically used, remain large sources of uncertainty. This analysis can also be used to develop strategies to reduce measurement uncertainties.

Comparative analysis (CASP): A proposal for quantifying seismic data processing

Seismic data processing decisions are often made through a conventional procedure of technical-commercial tendering. This, and the review of slick brochures, impressive CVs, and long lists of worldwide processing experiences, more often than not win the contract for the lowest bidder. A routine processing project then proceeds with regular quality control meetings in which client representatives visually inspect various tests and make on-the-spot decisions for this gap or that window.