Using Quantitative Characteristics of Document Images for Identification of Laser Printers

The article provides a brief overview of the current state of the theory and practice of identifying laser printers and the results of research work aimed at discovering individual features of the printing mechanism of a laser printer.The author analyses the scheme of a laser printer, describes the printing cycle, presents the main results of the analysis of a printer’s mechanism and the influence of its individual parts on the optical density of printing. The method of assessment of the optical density of the print by the digital image of the printed document is proposed, the complex of the necessary technical and program tools is described.A hypothesis on the correlation between fluctuations in the optical density of printing of solid fills and fluctuations in the area of printed elements was put forward and confirmed; a visual representation of the study results in graphical form is presented, the relationship between the shape of the obtained graphs and defects of the printer’s components and parts is substantiated. The author proposes ways to detect the inhomogeneity of printing density on text arrays based on changes in the area of printed elements and processing of the results, which allows comparing distributions for texts printed in fonts of different sizes and styles. Based on experimental material, the individuality of the form of the obtained distributions and the possibility of their use as identifying features of the printing device are substantiated.

Land use uncertainty in transportation forecast

Using an integrated land use and travel model system implemented for the Puget Sound region in Washington state, a Bayesian Melding technique is applied to represent variations in land use outcomes, and is propagated into travel choices across a multi-year agent-based simulation. A scenario is considered where zoned capacity is increased around light rail stations. Samples are drawn from the posterior distribution of households to generate travel model inputs. They allow for propagation of land use uncertainty into travel choices, which are themselves assessed for uncertainty by comparing against observed data. Resulting travel measures of zonal vehicle miles traveled (VMT) per capita and light rail station boardings indicate the importance of comparing distributions rather than point forecasts. Results suggest decreased VMT per capita in zones near light rail stations and increased boardings at certain stations with existing development, and less significant impacts around stations with lower initial development capacity. In many cases, individual point level comparisons of scenarios would lead to very different conclusions. Altogether, this finding adds to a line of work demonstrating the policy value of incorporating uncertainty in integrated models and provides a method for assessing these variations in a systematic way.

Comparing distributions of ordinal data

To compare distributions of ordinal data such as individuals’ responses on Likert-type scale variables summarizing subjective well-being, we should not apply the toolbox of methods developed for cardinal variables such as income. Instead, we should use an analogous toolbox that accounts for the ordinal nature of the responses. In this article, I review these methods and introduce a new command, ineqord, for undertaking distributional comparisons. As the empirical illustrations demonstrate, ineqord can be used for dominance checks as well as for estimation of indices of polarization and inequality.

Comparison of staff and resident health status ratings in care homes

BackgroundMany care home residents cannot self-report their own health status. Previous studies have shown differences between staff and resident ratings. In 2012, we collected 10 168 pairs of health status ratings using the howRu health status measure. This paper examines differences between staff and resident ratings.MethodHowRu is a short generic person-reported outcome measure with four items: pain or discomfort (discomfort), feeling low or worried (distress), limited in what you can do (disability) and require help from others (dependence). A summary score (howRu score) is also calculated. Mean scores are shown on a 0–100 scale. High scores are better than low scores. Differences between resident and staff reports (bias) were analysed at the item and summary level by comparing distributions, analysing correlations and a modification of the Bland-Altman method.Results and conclusionsDistributions are similar superficially but differ statistically. Spearman correlations are between 0.55 and 0.67. For items, more than 92.9% of paired responses are within one class; for the howRu summary score, 66% are within one class. Mean differences (resident score minus staff score) on 0–100 scale are pain and discomfort (−1.11), distress (0.67), discomfort (1.56), dependence (3.92) and howRu summary score (1.26). The variation is not the same for different severities. At higher levels of pain and discomfort, staff rated their discomfort and distress as better than residents. On the other hand, staff rated disability and dependence as worse than did residents. This probably reflects differences in perspectives. Red amber green (RAG) thresholds of 10 and 5 points are suggested for monitoring changes in care home mean scores.

distcomp: Comparing distributions

In this article, I introduce the distcomp command, which assesses whether two distributions differ at each possible value while controlling the probability of any false positive, even in finite samples. I discuss syntax and the underlying methodology (from Goldman and Kaplan [2018, Journal of Econometrics 206: 143–166]). Multiple examples illustrate the distcomp command, including revisiting the experimental data of Gneezy and List (2006, Econometrica 74: 1365–1384) and the regression discontinuity design of Cattaneo, Frandsen, and Titiunik (2015, Journal of Causal Inference 3: 1–24).

Measuring Geographic Distribution for Political Research

Political scientists are increasingly interested in the geographic distribution of political and economic phenomena. Unlike distribution measures at the individual level, geographic distributions depend on the “unit question” in which researchers choose the appropriate political subdivision to analyze, such as nations, subnational regions, urban and rural areas, or electoral districts. We identify concerns with measuring geographic distribution and comparing distributions within and across political units. In particular, we highlight the potential for threats to inference based on the modifiable areal unit problem (MAUP), whereby measuring concepts at different unit aggregations alters the observed value. We offer tangible options for researchers to improve their research design and data analysis to limit the MAUP. To help manage the measurement error when the unit of observation is unclear or appropriate data are not available, we introduce a new measure of geographic distribution that accounts for fluctuations in the scale and number of political units considered. We demonstrate using Monte Carlo simulations that our measure is more reliable and stable across political units than commonly used indicators because it reduces measurement fluctuations associated with the MAUP.

Arrival Traffic Separations Modelling By Using Continuous Probability Distributions

This article presents a method that allows to analyze selected aspects of past arrival traffic by modelling distributions of time separations of arriving aircraft in a chosen navigationpoint of Terminal Manoeuvring Area with the use of continuous probability distributions. Modelling arriving aircraft time separations distribution with continuous probability density functions allows to apply various mathematical tools to analyze separations distributions. Moreover, by comparing distributions parameters, quantitative analysis of separations for days with various arrival traffic intensity can be performed. Assumptions, mathematical model, application in the exemplary experimental scenario with an airport and days with low and high traffic intensity, and results are presented in this article. Real air traffic data was used for the experimental scenario. Outcomes show that the method can be used for air traffic post-analysis, e.g assessment of maintaining separation.