Variability in photos of the same face

Between-individual variability of body temperature has been little investigated, but is of clinical importance: for example, in detection of neutropenic sepsis during chemotherapy. We studied within-person and between-person variability in temperature in healthy adults and those receiving chemotherapy using a prospective observational design involving 29 healthy participants and 23 patients undergoing chemotherapy. Primary outcome was oral temperature. We calculated each patient’s mean temperature, standard deviation within each patient (within-person variability), and between patients (between-person variability). Secondary analysis explored temperature changes in the three days before admission for neutropenic sepsis. 1,755 temperature readings were returned by healthy participants and 1,765 by chemotherapy patients. Mean participant temperature was 36.16 C (95% CI 36.07–36.26) in healthy participants and 36.32 C (95% CI 36.18–36.46) in chemotherapy patients. Healthy participant within-person variability was 0.40 C (95% CI 0.36–0.44) and between-person variability was 0.26 C (95% CI 0.16–0.35). Chemotherapy patient within-person variability was 0.39 C (95% CI 0.34–0.44) and between-person variability was 0.34 C (95% CI 0.26–0.48). Thus, use of a population mean rather than personalised baselines is probably sufficient for most clinical purposes as between-person variability is not large compared to within-person variability. Standardised guidance and provision of thermometers to patients might help to improve recording and guide management.

Chapter 42 - Within-person variability in job performance

We describe the use of flexible models for representing the shape and grey-level appearance of human faces. These models are controlled by a small number of parameters which can be used to code the overall appearance of a face for image compression and classification purposes. The model parameters control both inter-class and within-class variation. Discriminant analysis techniques are employed to enhance the effect of those parameters affecting inter-class variation, which are useful for classification. We have performed experiments on face coding and reconstruction and automatic face identification. Good recognition rates are obtained even when significant variation in lighting, expression and 3D viewpoint, is allowed. Human faces display significant variation in appearance due to changes in expression, 3D orientation, lighting conditions, hairstyles and so on. A successful automatic face identification system should be capable of suppressing the effect of these factors allowing any face image to be rendered expression-free with standardised 3D orientation and lighting. We describe how the variations in shape and grey-level appearance in face images can be modelled, and present results for a fully automatic face identification system which tolerates changes in expression, viewpoint and lighting.

In research, a shift is noticeable from between-person variability and variable-centered approaches to a combination of between- and withinperson variability, thereby integrating a person-centered approach, or even to standalone research on within-person variability. In many domains of social and behavioral sciences within-person (also called intraindividual) variability was largely ignored or even dismissed as simple noise or measurement error variance. This mini-review examines the added value of within-person variability in different domains of human functioning, such as motivation, emotion, executive functioning, memory and sports. Lastly, future developments in research and practice will be discussed.

To formally identify and contrast the most commonly-employed quantifications of response time inconsistency (RTI) and elucidate their utility for understanding within-person (WP) and between-person (BP) variation in cognitive function with increasing age. Using two measurement burst studies of cognitive aging, we systematically identified and computed five RTI quantifications from select disciplines to examine: (a) correlations among RTI quantifications; (b) the distribution of BP and WP variation in RTI; and (c) the comparability of RTI quantifications for predicting attention switching. Comparable patterns were observed across studies. There was significant variation in RTI BP as well as WP across sessions and bursts. Correlations among RTI quantifications were generally strong and positive both WP and BP, except for the coefficient of variation. Independent prediction models indicated that slower mean response time (RT) and greater RTI were associated with slower attention switching both WP and BP. For selecting simultaneous prediction models, collinearity resulted in inflated standard errors and unstable model estimates. RTI reflects a novel dimension of performance that is a robust and theoretically informative predictor of BP and WP variation in cognitive function. Among the plenitude of RTI quantifications, not all are interchangeable, nor of comparable predictive utility.

Objective: To assess the value of monitoring response to bisphosphonate treatment by means of measuring bone mineral density.Design Secondary analysis of trial data using mixed models.Data source The Fracture Intervention...

Face recognition has been a major research theme over the last two decades. There are several problems to be solved to improve the performance of face recognition. Such major problems involve appearance variation due to pose, illumination, expression, and aging. In particular, aging includes internal and external factors that cause facial appearance variation and, consequently, it is the most difficult problem to handle. In this paper, we propose a face recognition method that is robust against facial appearance variation due to aging. The proposed method employs segmentation verification of frontal face images that consists of the following three steps. (1) Face image segmentation generates three regional subimages from the input face image. (2) A matching score is calculated using gradient features from a pair consisting of the input image and a registered image for each of the three generated subimages and original (whole face) image. We obtain four matching scores. (3) The verifying classifier evaluates the matching score vector formed of the matching scores calculated for each of the four images and predicts the a posteriori probability that two matching images belong to the same person. The results of an experimental evaluation with the FGNET and MORPH face aging datasets clarify the effectiveness of the proposed method for age invariant face recognition.

Temporal variability in urinary levels of drinking water disinfection byproducts dichloroacetic acid and trichloroacetic acid among men

Personal NO 2 exposures of high school students

Some effects of within-person variability in epidemiological studies

To describe the associations of between-person and within-person variability in serum 25-hydroxyvitamin D (25(OH)D), physical activity (PA), and knee pain and dysfunction with muscle mass, strength, and muscle quality over 10 years in community-dwelling older adults. Participants (N = 1033; 51% women; mean age 63 ± 7.4 years) were measured at baseline, 2.5, 5, and 10 years. Lower limb lean mass (LLM) was assessed using dual energy X-ray absorptiometry, lower limb muscle strength (LMS) using a dynamometer, and lower limb muscle quality (LMQ) calculated as LMS/LLM. Knee pain and dysfunction were assessed using the Western Ontario and McMaster Universities Osteoarthritis (WOMAC) index. PA was measured using pedometers. Linear-mixed effect regression models, with adjustment for confounders, were used to estimate the association of within-person and between-person variability in PA, 25(OH)D, and WOMAC scores with muscle mass, strength, and muscle quality. Both between-person and within-person increases in PA were associated with LLM, LMS, and LMQ (all P < 0.05). Within-person and between-person increases in knee pain and dysfunction were associated with LLS and LMQ, but not with LLM (all P < 0.05). Between-person effects showed that higher average 25(OH)D was associated with a higher 10-year average LLM, LMS, and LMQ (all P < 0.05), whereas within-person increases in average 25(OH)D were associated with a higher LMS and LMQ, but not with LLM. Variability in 25(OH)D, pain, and dysfunction within an individual over time is related to muscle changes in that individual. Increasing one's own PA level further increases muscle mass, strength, and quality supporting the clinical recommendation of promoting PA to reduce age-related muscle loss.

In this chapter, we first explain what is meant by between-person variability (or interindividual differences) and within-person variability (or intraindividual variability and change) in employee pro-environmental behaviour. Second, we describe two quantitative daily diary studies that examined both between-person and within-person variability in employee pro-environmental behaviour. Third, we present a conceptual framework for investigating person- and context-related predictors of stable between-person differences and dynamic within-person variability in employee pro-environmental behaviour. Fourth, we discuss different research designs and analytical strategies to investigate between- and within-person variability in employee pro-environmental behaviour. We conclude by discussing implications for organisational practice.

Nonverbal cues are instrumental in animal social interactions, and humans place especial value on facial appearance and displays to predict and interpret others’ behaviours. Several studies have reported that people can judge someone’s political orientation (e.g. Republican vs Democrat) based on facial appearance at greater-than-chance accuracy. This begs the question of the granularity of such judgements. Here, we investigate whether people can judge one aspect of political orientation (attitudes to immigration) based on the facial photographs that politicians use to represent themselves on the European Parliament website. We find no evidence of such ability, and no evidence for an interaction between the judges’ own attitudes to immigration and their accuracy. While many studies report facial manifestations of attitudinal and behavioural proclivities, facial appearance may be a relatively impoverished cue.

A comparative study of facial appearance modeling methods for active appearance models

Facial appearance changes because uncontrolled variations of facial appearances due to illumination, pose, expression, occlusion of non-cooperative subjects and subject-to-camera distance need to be handled to allow for successful recognition. This paper presents a novel image quality assessment model. The model is designed to reduce the influence which is caused by the degradation of facial image quality due to uncontrolled variations of facial appearances, and the degradation can lower the recognition performance. The model assesses the image quality from several aspects: (I) Occlusion measure. (II) Face-to-camera distance measure. (Ill) Pose and expression measure.(IV) Uneven illumination measure. Then noisy score is calculated by the image quality assessment model while higher noisy score's images will be discarded for face recognition, the superior face images are selected by image quality assessment model to obtain best recognition result. Experimental results on CAS-PEAL face databases with varied uncontrolled facial appearances demonstrated that the proposed approach achieved satisfactory recognition rate.