Match me if you can: Evidence for a domain-general visual comparison ability

Visual comparison—comparing visual stimuli (e.g., fingerprints) side by side and determining whether they originate from the same or different source (i.e., “match”)—is a complex discrimination task involving many cognitive and perceptual processes. Despite the real-world consequences of this task, which is often conducted by forensic scientists, little is understood about the psychological processes underpinning this ability. There are substantial individual differences in visual comparison accuracy amongst both professionals and novices. The source of this variation is unknown, but may reflect a domain-general and naturally varying perceptual ability. Here, we investigate this by comparing individual differences (N = 248 across two studies) in four visual comparison domains: faces, fingerprints, firearms, and artificial prints. Accuracy on all comparison tasks was significantly correlated and accounted for a substantial portion of variance (e.g., 42% in Exp. 1) in performance across all tasks. Importantly, this relationship cannot be attributed to participants’ intrinsic motivation or skill in other visual-perceptual tasks (visual search and visual statistical learning). This paper provides novel evidence of a reliable, domain-general visual comparison ability.

Thickness record of varves from glacial Ojibway Lake recovered in sediment cores from Frederick House Lake, northeastern Ontario

The thicknesses of 384 rhythmic couplets were measured along a composite sequence of glacial Lake Ojibway glaciolacustrine deposits recovered in two sediment cores from Frederick House Lake, Ontario. The visual comparison of distinctive couplets in the CT-scan radiographs of the Frederick House core samples to photographs of core samples from Reid Lake show a match of ±1 varve number from v1656-v1902, and ±5 varve numbers between v1903-v2010, relative to the regional numbering of the Timiskaming varve series. There are two interpretations for the post-v2010 couplets that fall within the Connaught varve sequence of the regional series. In the first, the interpreted numbering spans from v2066-v2115, which produces a gap of 55 missing varves equivalent to v2011-v2065, and corresponds to the original interpretation of the Connaught varve numbering. The second spans v2011a-v2060a, and represents alternative (a) numbering for the same varves. Varve thickness data are listed in spreadsheet files (.xlsx and .csv formats), and CT-Scan radiograph images of core samples are laid out on a mosaic poster showing the interpreted varve numbering and between-core sample correlations of the varve couplets.

Impact of Measurement Error on the Power Function of Average Control Chart under Non-Normal Population

In the present article, effect of measurement error on the power function of control charts for mean with control limits is considered based on non-normal population. The non-normality is represented by the first four terms of an Edge-worth series. Tabular and visual comparison is also provided for the better comprehension of the significance of measurement error on power function under non-normality.

A geostationary lightning pseudo-observation generator utilizing low frequency ground-based lightning observations

Coincident Geostationary Lightning Mapper (GLM) and National Lightning Detection Network (NLDN) observations are used to build a generator of realistic lightning optical signal in the perspective to simulate Lightning Imager (LI) signal from European NLDN-like observations. Characteristics of GLM and NLDN flashes are used to train different machine learning (ML) models, that predict simulated pseudo-GLM flash extent, flash duration, and event number per flash (targets) from several NLDN flash characteristics. Comparing statistics of observed GLM targets and simulated pseudo-GLM targets, the most suitable ML-based target generators are identified. The simulated targets are then further processed to obtain pseudo-GLM events and flashes. In the perspective of lightning data assimilation, Flash Extent Density (FED) is derived from both observed and simulated GLM data. The best generators simulate accumulated hourly FED sums with a bias of 2% to the observation, while cumulated absolute differences remain of about 22 %. A visual comparison reveals that hourly simulated FED features local maxima at the similar geolocations as the FED derived from GLM observations. However, the simulated FED often exceeds the observed FED in regions of convective cores and high flash rates. The accumulated hourly area with FED>0 flashes per 5 km×5 km pixel simulated by some pseudo-GLM generators differs by only 7% to 8% from the observed values. The recommended generator uses a linear Support Vector Regressor (linSVR) to create pseudo-GLM FED. It provides the best balance between target simulation, hourly FED sum, and hourly electrified area.

Visual Comparison of Guidelines: Method and Application to Potentially Inappropriate Medication Lists

Therapeutic guidelines developed by experts are essential tools for improving therapy and drug prescription. Several guidelines often exist that target the same patient, from different organizations and countries. The case of lists for the detection of potentially inappropriate medications (PIMs) is an example which illustrates how these guidelines can be varied and multiple. In order to have an overview to the divergences and similarities between different lists of PIMs, we propose a visual method to compare PIMs lists, based on set visualization, and we apply it to 5 guidelines.

Visual Comparison of Phylogenetic Trees Through iPhyloC, a New Interactive Web-based Framework

Current side-by-side phylogenetic trees comparison frameworks face two issues: (1) accepting binary trees as input, and (2) assuming input trees having identical or highly overlapping taxa. We present a task abstraction of the problem of side-by-side comparison of two phylogenetic trees and propose a set-based measure for detailed structural comparison between two phylogenetic trees, which can be non-binary and not highly overlapping. iPhyloC is an interactive web-based framework including automatic identification of the common taxa in both trees, comparing input trees in several modes, intuitive design, high usability, scalability to large trees, and cross-platform support. iPhyloC was tested in hypothetical and real biological examples.