Image quality assessment

Quality assessment is an integral stage in the processing and analysis of digital images in various automated systems. With the increase in the number and variety of devices that allow receiving data in various digital formats, as well as the expansion of human activities in which information technology (IT) is used, the need to assess the quality of the data obtained is growing. As well as the bar grows for the requirements for their quality.The article describes the factors that deteriorate the quality of digital images, areas of application of image quality assessment functions, a method for normalizing proximity measures, classes of digital images and their possible distortions, image databases available on the Internet for conducting experiments on assessing image quality with visual assessments of experts.

N. Belknap's Four-Valued Logic, Belknap Computer and New Proximity Functions for Comparing Discrete Objects

The idea of ​​Belknap's four-valued logic is that modern computers should function normally not only with the true values ​​of the input information, but also under the conditions of inconsistency and incompleteness of true failures. Belknap's logic introduces four true values: T (true - true), F (false - false), N (none - nobody, nothing, none), B (both - the two, not only the one but also the other). For ease of work with these true values, the following designations are introduced: (1, 0, n, b). Belknap's logic can be used to obtain estimates of proximity measures for discrete objects, for which the functions Jaccard and Needhem, Russel and Rao, Sokal and Michener, Hamming, etc. are used. In this case, it becomes possible to assess the proximity, recognition and classification of objects in conditions of uncertainty when the true values ​​are taken from the set (1, 0, n, b). Based on the architecture of the Hamming neural network, neural networks have been developed that allow calculating the distances between objects described using true values ​​(1, 0, n, b). Keywords: four-valued Belknap logic, Belknap computer, proximity assessment, recognition and classification, proximity function, neural network.

USE OF PROPOSALITY MEASURES IN THE PROBLEM OF DISTRIBUTING THE PRODUCTION PROGRAM BY THE SCHEDULED PERIOD ON THE BASIS OF THE SIMILARITY OF THE SIMILARITY OF DAKE, JACKARD, MAXFEDOR, OTIA, RAO, TANIMOTO

The distribution of the production program of many production options for planned periods of various durations is relevant for modern production. The specificity of this production is that from the same parts, assemblies (assembly units), many modifications and sizes of products can be assembled to satisfy more consumers. The complexes of work on individual products is neither a repetition of each other, nor completely different, but have some similarities and individual differences, and the production time is less than the planned period. In the work, the authors expressed the opinion that if the duration of the production cycle is less than the planned period, then the structural and technological features of individual products cannot be ignored in the tasks of distributing the production program (volume-calendar planning tasks). This statement is erroneous. Using such specifics, it is possible to improve the economic indicators of such production, and we have shown in this paper. The combination of similar structural and technological products in separate planning periods increases the specialization of production in separate periods, reduces losses from equipment downtime, increases labor productivity and reduces the load on the operating manager by reducing the number of planning and accounting units in each period. In the work, proximity measures are proposed based on the known similarity coefficients, since it is more convenient to algorithmize the distribution process of the production program. The authors proved that the proposed measures correspond to the Frechet axiomatics.

A comparative analysis of proximity measures to determine the Lithuanian population structure

In this paper the multidimensional scaling, the principal coordinate and principal component methods for the Lithuanian population structure have investigated, taken that the proximity measures are Euclid, Gower, Bray-Curtis, Kulczynski, Jaccard and Morisita. The genome-wide single nucleotide polymorphism genetic data analyzed. A comparative analysis of proximity measures performed. The results of visualization are also presented.

Extending Proximity Measures to Attributed Networks for Community Detection

Proximity measures on graphs are extensively used for solving various problems in network analysis, including community detection. Previous studies have considered proximity measures mainly for networks without attributes. However, attribute information, node attributes in particular, allows a more in-depth exploration of the network structure. This paper extends the definition of a number of proximity measures to the case of attributed networks. To take node attributes into account, attribute similarity is embedded into the adjacency matrix. Obtained attribute-aware proximity measures are numerically studied in the context of community detection in real-world networks.

Socioeconomic patterning of food and drink advertising at public transport stops in Edinburgh, UK

Objective: Outdoor advertisements for food and drink products form a large part of the food environment and they disproportionately promote unhealthy products. However, less is known about the social patterning of such advertisements. The main aim of this study was to explore the socioeconomic patterning of food and drink advertising at bus stops in Scotland’s capital city, Edinburgh. Design: Bus stop advertisements were audited to identify food/drink adverts and classify them by food/drink category (i.e. ‘advert category’). This data was then linked to area-based deprivation and proximity measures. Neighbourhood deprivation was measured using the bus stop x/y co-ordinates, which were converted to postcodes to identify the matching 2012 deprivation level via the Scottish Index of Multiple Deprivation (SIMD). Distance to schools and leisure centres were also collected using location data. Generalized Estimating Equations (GEE) and linear regression analyses were used to assess associations between the promotion of advert categories and deprivation and proximity to schools/leisure centres, respectively. Setting: Edinburgh city, United Kingdom Results: 561 food/drink advertisements were identified across 349 bus stops, with eight advertisement categories noted and included in the final analysis, including alcohol, fast food outlets and confectionary. The majority of adverts were for ‘unhealthy’ food and drink categories, however there was no evidence for any socioeconomic patterning of these advertisements. There was no evidence of a relationship between advertisements and proximity to schools and leisure centres. Conclusions: While there is no evidence for food and drink advertising being patterned by neighbourhood deprivation, the scale of unhealthy advertising is an area for policy evaluations and interventions on the control of such outdoor advertising.

Leveraging multifaceted proximity measures among developers in predicting future collaborations to improve the social capital of software projects

Social capital is an asset earned by people through their social connections. One of the motivations among developers to contribute to open source development and maintenance tasks is to earn social capital. Recent studies suggest that the social capital of the project has an impact on the sustained participation of the developers in open source software (OSS). One way to improve the social capital of the project is to help the developers in connecting with their peers. However, to the best of our knowledge, there is no prior research which attempts to predict future collaborations among developers and establish the significance of these collaborations on improving the social capital at the project level. To address this research gap, in this paper, we model the past collaborations among developers on version control system (VCS) and issue tracking system (ITS) as homogeneous and heterogeneous developer social network (DSN). Along with the novel path count based features, defined on proposed heterogeneous DSN, multifaceted proximity features are used to generate a feature set for machine learning classifiers. Our experiments performed on 5 popular open source projects (Spark, Kafka, Flink, WildFly, Hibernate) indicate that the proposed approach can predict the future collaborations among developers on both the platforms i.e. VCS as well as ITS with a significant accuracy (AUROC up to 0.85 and 0.9 for VCS and ITS respectively). A generic metric- recall of gain in social capital is proposed to investigate the efficacy of these predicted collaborations in improving the social capital of the project. We also concretised this metric on various measures of social capital and found that collaborations predicted by our approach have significant potential to improve the social capital at project level (e.g. Recall of gain in cohesion index up to 0.98 and Recall of gain in average godfather index up to 0.99 for VCS). We also showed that structure of collaboration network has an impact on the accuracy and usefulness of predicted collaborations. Since the past research suggests that many newcomers abandon the open source project due to social barriers which they face after joining the project, our research outcomes can be used to build the recommendation systems which might help to retain such developers by improving their social ties based on similar skills/interests.

Export Product Scope of Russian Firms and Proximity to Local Comparative Advantages

This paper explores the relationship between the structure of regional comparative advantages and the dynamics of the export product scope of Russian manufacturing enterprises. For this purpose, indices of revealed technological proximity of industries are calculated on the basis of data on types of economic activities and the export product scope of Russian enterprises. The methodology for calculating these indicators is based on the assumption that technologically closer types of activities are, to a certain degree, more often co-produced and co-exported within the boundaries of individual enterprises. This measure of technological proximity has several advantages over the traditionally used indicators. Estimates show that the constructed indices reflect different aspects of technological proximity of industries and can be considered as composite indicators. Technological proximity measures are used to calculate the index of product proximity to the structure of export comparative advantages of Russian regions. This index is statistically related to the probability of a product being included in the export product scope of a Russian exporter, to the probability of the product being excluded from the export product scope and, as a result, to the value and dynamics of exports of this product by the regional enterprises. These findings indicate that there is a relationship between the current structure of the regional comparative advantage and the direction in which the range of exports of Russian enterprises located in this region evolves. The results of the study can be used for designing economic policy measures aimed at diversification of production and export of the Russian regions, in particular on the basis of existing producers and exporters, as well as applied by the firms themselves to detect the most promising directions of activity expansion taking into account the production structure of the region which the given firm is located at.

Proximity measures based on KKT points for constrained multi-objective optimization

An important aspect of optimization algorithms, for instance evolutionary algorithms, are termination criteria that measure the proximity of the found solution to the optimal solution set. A frequently used approach is the numerical verification of necessary optimality conditions such as the Karush–Kuhn–Tucker (KKT) conditions. In this paper, we present a proximity measure which characterizes the violation of the KKT conditions. It can be computed easily and is continuous in every efficient solution. Hence, it can be used as an indicator for the proximity of a certain point to the set of efficient (Edgeworth-Pareto-minimal) solutions and is well suited for algorithmic use due to its continuity properties. This is especially useful within evolutionary algorithms for candidate selection and termination, which we also illustrate numerically for some test problems.

Tobacco retail environment and smoking: a systematic review of geographic exposure measures and implications for future studies

Introduction To review the geographical exposure measures used to characterize the tobacco environment in terms of density of and proximity to tobacco outlets, and its association with smoking-related outcomes. Methods We used PubMed and Google Scholar to find articles published until December 2019. The search was restricted to studies which 1) measured the density of and/or proximity to tobacco outlets and 2) included associations with smoking outcomes. The extraction was coordinated by several observers. We gathered data on the place of exposure, methodological approaches, and smoking outcomes. Results Forty articles were eligible out of 3,002 screened papers. Different density and proximity measures were described. 47.4% density calculations were based on simple counts (number of outlets within an area). Kernel Density Estimations and other measures weighted by the size of the area (outlets/sq km), population, and road length were identified. 81.3% of the articles which assessed proximity to tobacco outlets used length distances estimated through the street network. Higher density values were mostly associated with higher smoking prevalence (76.2%), greater tobacco use and smoking initiation (64.3%); and lower cessation outcomes (84.6%). Proximity measures were not associated with any smoking outcome except with cessation (62.5%). Conclusion Associations between the density of tobacco outlets and smoking outcomes were found regardless of the exposure measure applied. Further research is warranted to better understand how proximity to tobacco outlets may influence on smoking outcomes. This systematic review discusses methodological gaps in the literature and provides insights for future studies exploring the tobacco environment. Implications Our findings pose some methodological lessons to improve the exposure measures on the tobacco outlet environment. To solve these methodological gaps is crucial to understanding the influence of the tobacco environment on the smoking outcomes. Activity spaces should be considered in further analyses since individuals are exposed to tobacco beyond their residence or school neighbourhood. Further studies in this research area demand density estimations weighted by the size of the area, population, or road length; or measured using Kernel Density Estimations. Proximity calculations should be measured through the street network and should consider travel times apart from the length-distance.