Comparing measures of model selection for penalized splines in Cox models

This article presents an application and a simulation study of model fit criteria for selecting the optimal degree of smoothness for penalized splines in Cox models. The criteria considered were the Akaike information criterion, the corrected AIC, two formulations of the Bayesian information criterion, and a generalized cross-validation method. The estimated curves selected by the five methods were compared to each other in a study of rectal cancer mortality in autoworkers. In the stimulation study, we estimated the fit of the penalized spline models in six exposure-response scenarios, using the five model fit criteria. The methods were compared on the basis of a mean squared error score and the power and size of hypothesis tests for any effect and for detecting nonlinearity. All comparisons were made across a range in the total sample size and number of cases.     

Comprehensive Automation for Specialty Crops: Year 1 results and lessons learned

Comprehensive Automation for Specialty Crops is a project focused on the needs of the specialty crops sector, with a focus on apples and nursery trees. The project’s main thrusts are the integration of robotics technology and plant science; understanding and overcoming socio-economic barriers to technology adoption; and making the results available to growers and stakeholders through a nationwide outreach program. In this article, we present the results obtained and lessons learned in the first year of the project with a reconfigurable mobility infrastructure for autonomous farm driving. We then present sensor systems developed to enable three real-world agricultural applications—insect monitoring, crop load scouting, and caliper measurement—and discuss how they can be deployed autonomously to yield increased production efficiency and reduced labor costs.     

Integration of MODIS-derived metrics to assess interannual variability in snowpack, lake ice, and NDVI in southwest Alaska

Impacts of global climate change are expected to result in greater variation in the seasonality of snowpack, lake ice, and vegetation dynamics in southwest Alaska. All have wide-reaching physical and biological ecosystem effects in the region. We used Moderate Resolution Imaging Spectroradiometer (MODIS) calibrated radiance, snow cover extent, and vegetation index products for interpreting interannual variation in the duration and extent of snowpack, lake ice, and vegetation dynamics for southwest Alaska. The approach integrates multiple seasonal metrics across large ecological regions.Throughout the observation period (2001-2007), snow cover duration was stable within ecoregions, with variable start and end dates. The start of the lake ice season lagged the snow season by 2 to 3 months. Within a given lake, freeze-up dates varied in timing and duration, while break-up dates were more consistent. Vegetation phenology varied less than snow and ice metrics, with start-of-season dates comparatively consistent across years. The start of growing season and snow melt were related to one another as they are both temperature dependent. Higher than average temperatures during the El Niño winter of 2002-2003 were expressed in anomalous ice and snow season patterns. We are developing a consistent, MODIS-based dataset that will be used to monitor temporal trends of each of these seasonal metrics and to map areas of change for the study area.     

A bootstrap goodness of fit test for the generalized Pareto distribution

This paper proposes a bootstrap goodness of fit test for the Generalized Pareto distribution (GPd) with shape parameter γ. The proposed test is an intersection–union test which tests separately the cases of γ≥0 and γ<0 and rejects if both cases are rejected. If the test does not reject, then it is known whether the shape parameter γ is either positive or negative. A Monte Carlo simulation experiment was conducted to assess the power of performance of the intersection–union test. The GPd hypothesis was tested on a data set containing Mexico City’s ozone levels. ¹     

Thermal and cardiovascular strain imposed by motorcycle protective clothing under Australian summer conditions

Motorcycle protective clothing can be uncomfortably hot during summer, and this experiment was designed to evaluate the physiological significance of that burden. Twelve males participated in four, 90-min trials (cycling 30 W) across three environments (25, 30, 35 °C [all 40% relative humidity]). Clothing was modified between full and minimal injury protection. Both ensembles were tested at 25 °C, with only the more protective ensemble investigated at 30 and 35 °C. At 35 °C, auditory canal temperature rose at 0.02 °C min^?1 (SD 0.005), deviating from all other trials (p < 0.05). The thresholds for moderate (>38.5 °C) and profound hyperthermia (>40.0 °C) were predicted to occur within 105 min (SD 20.6) and 180 min (SD 33.0), respectively. Profound hyperthermia might eventuate in ~10 h at 30 °C, but should not occur at 25 °C. These outcomes demonstrate a need to enhance the heat dissipation capabilities of motorcycle clothing designed for summer use in hot climates, but without compromising impact protection.

Practitioner’s Summary:

Motorcycle protective clothing can be uncomfortably hot during summer. This experiment was designed to evaluate the physiological significance of this burden across climatic states. In the heat, moderate (>38.5 °C) and profound hyperthermia (>40.0 °C) were predicted to occur within 105 and 180 min, respectively.     

The impact of map orientation and generalisation on congestion decisions: a comparison of schematic-egocentric and topographic-allocentric maps

Map information for drivers is usually presented in an allocentric-topographic form (as with printed maps) or in an egocentric-schematic form (as with road signs). The advent of new variable message boards on UK motorways raises the possibility of presenting road maps to reflect congestion ahead. Should these maps be allocentric-topographic or egocentric-schematic? This was assessed in an eye tracking study, with participants viewing maps of a motorway network in order to identify whether any congestion was relevant to their intended route. The schematic-egocentric maps were responded to most accurately with shorter fixation durations suggesting easier processing. In particular, the driver's entrance and intended exit from the map were attended to more in the allocentric maps. Individual differences in mental rotation ability also seem to contribute to poor performance on allocentric maps. The results favour schematic-egocentric maps for roadside congestion information, but also provide theoretical insights into map-rotation and individual differences. Statement of Relevance: This study informs designers and policy makers about optimum representations of traffic congestion on roadside variable message signs and, furthermore, demonstrates that individual differences contribute to problems with processing certain sign types. Schematic-egocentric representations of a motorway network produced the best results, as noted in behavioural and eye movement measures.     

Fuzzy clustering of time series in the frequency domain

Traditional and fuzzy cluster analyses are applicable to variables whose values are uncorrelated. Hence, in order to cluster time series data which are usually serially correlated, one needs to extract features from the time series, the values of which are uncorrelated. The periodogram which is an estimator of the spectral density function of a time series is a feature that can be used in the cluster analysis of time series because its ordinates are uncorrelated. Additionally, the normalized periodogram and the logarithm of the normalized periodogram are also features that can be used. In this paper, we consider a fuzzy clustering approach for time series based on the estimated cepstrum. The cepstrum is the spectrum of the logarithm of the spectral density function. We show in our simulation studies for the typical generating processes that have been considered, fuzzy clustering based on the cepstral coefficients performs very well compared to when it is based on other features.     

Regression models for grouped survival data: Estimation and sensitivity analysis

In this study, regression models are evaluated for grouped survival data when the effect of censoring time is considered in the model and the regression structure is modeled through four link functions. The methodology for grouped survival data is based on life tables, and the times are grouped in k intervals so that ties are eliminated. Thus, the data modeling is performed by considering the discrete models of lifetime regression. The model parameters are estimated by using the maximum likelihood and jackknife methods. To detect influential observations in the proposed models, diagnostic measures based on case deletion, which are denominated global influence, and influence measures based on small perturbations in the data or in the model, referred to as local influence, are used. In addition to those measures, the local influence and the total influential estimate are also employed. Various simulation studies are performed and compared to the performance of the four link functions of the regression models for grouped survival data for different parameter settings, sample sizes and numbers of intervals. Finally, a data set is analyzed by using the proposed regression models.     

ONTRACK: Dynamically adapting music playback to support navigation

Listening to music on personal, digital devices whilst mobile is an enjoyable, everyday activity. We explore a scheme for exploiting this practice to immerse listeners in navigation cues. Our prototype, ONTRACK, continuously adapts audio, modifying the spatial balance and volume to lead listeners to their target destination. First we report on an initial lab-based evaluation that demonstrated the approach’s efficacy: users were able to complete tasks within a reasonable time and their subjective feedback was positive. Encouraged by these results we constructed a handheld prototype. Here, we discuss this implementation and the results of field-trials. These indicate that even with a low-fidelity realisation of the concept, users can quite effectively navigate complicated routes.

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