Artificial intelligence technologies for more flexible recommendation in uniforms

PurposeThis research aims to collect human body variables via 2D images captured by digital cameras. Based on those human variables, the forecast and recommendation of the Digital Camouflage Uniforms (DCU) for Taiwan's military personnel are made.Design/methodology/approachA total of 375 subjects are recruited (male: 253; female: 122). In this study, OpenPose converts the photographed 2D images into four body variables, which are compared with those of a tape measure and 3D scanning simultaneously. Then, the recommendation model of the DCU is built by the decision tree. Meanwhile, the Euclidean distance of each size of the DCU in the manufacturing specification is calculated as the best three recommendations.FindingsThe recommended size established by the decision tree is only 0.62 and 0.63. However, for the recommendation result of the best three options, the DCU Fitting Score can be as high as 0.8 or more. The results of OpenPose and 3D scanning have the highest correlation coefficient even though the method of measuring body size is different. This result confirms that OpenPose has significant measurement validity. That is, inexpensive equipment can be used to obtain reasonable results.Originality/valueIn general, the method proposed in this study is suitable for applications in e-commerce and the apparel industry in a long-distance, non-contact and non-pre-labeled manner when the world is facing Covid-19. In particular, it can reduce the measurement troubles of ordinary users when purchasing clothing online.

Validity and Effects of Placement of Velocity-Based Training Devices

Velocity-based training (VBT) is a resistance training method by which training variables are manipulated based on kinematic outcomes, e.g., barbell velocity. The better precision for monitoring and manipulating training variables ascribed to VBT assumes that velocity is measured and communicated correctly. This study assessed the validity of several mobile and one stationary VBT device for measuring mean and peak concentric barbell velocity over a range of velocities and exercises, including low- and high-velocity, ballistic and non-ballistic, and plyometric and non-plyometric movements, and to quantify the isolated effect of device attachment point on measurement validity. GymAware (r = 0.90–1, standard error of the estimate, SEE = 0.01–0.08 m/s) and Quantum (r = 0.88–1, SEE = 0.01–0.18 m/s) were most valid for mean and peak velocity, with Vmaxpro (r = 0.92–0.99, SEE = 0.02–0.13 m/s) close behind. Push (r = 0.69–0.96, SEE = 0.03–0.17 m/s) and Flex (r = 0.60–0.94, SEE = 0.02–0.19 m/s) showed poorer validity (especially for higher-velocity exercises), although typical errors for mean velocity in exercises other than hang power snatch were acceptable. Effects of device placement were detectable, yet likely small enough (SEE < 0.1 m/s) to be negligible in training settings.

Location, Location, Location: Accelerometer Placement Affects Steps-Based Physical Activity Outcomes During Pregnancy and Postpartum

As pregnancy progresses, physical changes may affect physical activity (PA) measurement validity. n = 11 pregnant women (30.1 ± 3.8 years) wore ActiGraph GT3X+ accelerometers on the right hip, right ankle, and non-dominant wrist for 3–7 days during the second and third trimesters (21 and 32 weeks, respectively) and 12 weeks postpartum. Data were downloaded into 60-second epochs from which stepping cadence was calculated; repeated-measures analysis of variance was used to determine significant differences among placements. At all time points, the wrist accelerometer measured significantly more daily steps (9930–10 452 steps/d) and faster average stepping cadence (14.5–14.6 steps/min) than either the hip (4972–5944 steps/d, 7.1–8.6 steps/min) or ankle (7161–8205 steps/d, 10.3–11.9 steps/min) placement, while moderate- to vigorous-intensity activity at the wrist (1.2–1.7 min/d) was significantly less than either hip (3.0–5.9 min/d) or ankle (6.1–7.3 min/d). Steps, cadence, and counts were significantly lower for the hip than the ankle at all time points. Kappa calculated for agreement in intensity classification between the various pairwise comparisons ranged from .06 to .41, with Kappa for hip–ankle agreement (.34–.41) significantly higher than for wrist–ankle (.09–.11) or wrist–hip (.06–.16). These data indicate that wrist accelerometer placement during pregnancy likely results in over counting of PA parameters and should be used with caution.

Investigating the reliability and validity of the Toddler Home Learning Environment (THLE) scale

Home learning environments prior to school are well-known predictors of educational trajectories but research has neglected children aged under three. The new Toddler Home Learning Environment (THLE) scale is one response and this paper investigates its reliability and validity. The THLE is an adaptation of the Preschool HLE (PHLE) measure developed by the Effective Pre-School Primary and Secondary Education (EPPSE) investigation in the 1990s. The THLE was developed as part of the Evaluation of Children’s Centers in England (ECCE) investigation that followed a sample of 2,608 of families from 14 to 38 months. The THLE was administered at 14 months, the PHLE at 38. The 8-item THLE evidences internal consistency via statistical reliability coefficients and Confirmatory Factor Analysis plus measurement validity via statistically significant and research-appropriate associations with the PHLE, three measures of child development, and child and parent demographics. This paper moves the HLE literature forward with a new parental self-report scale of the HLE that is for use with toddlers.

Estimated seroprevalence of SARS-CoV-2 antibodies among adults in Orange County, California

Clinic-based estimates of SARS-CoV-2 may considerably underestimate the total number of infections. Access to testing in the US has been heterogeneous and symptoms vary widely in infected persons. Public health surveillance efforts and metrics are therefore hampered by underreporting. We set out to provide a minimally biased estimate of SARS-CoV-2 seroprevalence among adults for a large and diverse county (Orange County, CA, population 3.2 million). We implemented a surveillance study that minimizes response bias by recruiting adults to answer a survey without knowledge of later being offered SARS-CoV-2 test. Several methodologies were used to retrieve a population-representative sample. Participants (n = 2979) visited one of 11 drive-thru test sites from July 10th to August 16th, 2020 (or received an in-home visit) to provide a finger pin-prick sample. We applied a robust SARS-CoV-2 Antigen Microarray technology, which has superior measurement validity relative to FDA-approved tests. Participants include a broad age, gender, racial/ethnic, and income representation. Adjusted seroprevalence of SARS-CoV-2 infection was 11.5% (95% CI: 10.5–12.4%). Formal bias analyses produced similar results. Prevalence was elevated among Hispanics (vs. other non-Hispanic: prevalence ratio [PR] = 1.47, 95% CI 1.22–1.78) and household income < $50,000 (vs. > $100,000: PR = 1.42, 95% CI: 1.14 to 1.79). Results from a diverse population using a highly specific and sensitive microarray indicate a SARS-CoV-2 seroprevalence of ~ 12 percent. This population-based seroprevalence is seven-fold greater than that using official County statistics. In this region, SARS-CoV-2 also disproportionately affects Hispanic and low-income adults.

Generalized word shift graphs: a method for visualizing and explaining pairwise comparisons between texts

A common task in computational text analyses is to quantify how two corpora differ according to a measurement like word frequency, sentiment, or information content. However, collapsing the texts’ rich stories into a single number is often conceptually perilous, and it is difficult to confidently interpret interesting or unexpected textual patterns without looming concerns about data artifacts or measurement validity. To better capture fine-grained differences between texts, we introduce generalized word shift graphs, visualizations which yield a meaningful and interpretable summary of how individual words contribute to the variation between two texts for any measure that can be formulated as a weighted average. We show that this framework naturally encompasses many of the most commonly used approaches for comparing texts, including relative frequencies, dictionary scores, and entropy-based measures like the Kullback–Leibler and Jensen–Shannon divergences. Through a diverse set of case studies ranging from presidential speeches to tweets posted in urban green spaces, we demonstrate how generalized word shift graphs can be flexibly applied across domains for diagnostic investigation, hypothesis generation, and substantive interpretation. By providing a detailed lens into textual shifts between corpora, generalized word shift graphs help computational social scientists, digital humanists, and other text analysis practitioners fashion more robust scientific narratives.

Metrology of solid materials and substances porosity and permeability

The monograph is dedicated to current problem which is the development of appliance of centralised system of characterising the solid materials and substances porosity and permeability unit’s realisation and transfer methodology. The monograph considered the mix of means and methods allowing to increase the measurement validity and accuracy, to maintain a possibility of measuring equipment refreshing with more accomplished instruments, as well as to expand national measurement and calibration capabilities of the highest accuracy. The monograph is intended for metrologists, scientific workers, engineers, pre- and post-graduate students of oil & gas qualifications, as well as experts whose studies are to develop, test, verify and use the means of measurement of gas specific adsorption, specific surface and specific volume of pores, pore size, effective porosity and gas permeability coefficient for solid materials and substances.