An Evolutionary System for Better Automatic Software Repair

2020 ◽  
pp. 383-406
Author(s):  
Yuan Yuan ◽  
Wolfgang Banzhaf
Keyword(s):  
Evolutionary System ◽  
Automatic Software

POLITICAL IDEOLOGY AS AN EVOLUTIONARY SYSTEM (TO THE THEORY OF COGNITIVE-IDEOLOGICAL MATRICES)

2020 ◽  
Author(s):  
Mikhail Konstantinov
Keyword(s):  
Political Ideology ◽  
Evolutionary System ◽  
Consciousness Level ◽  
The Past ◽  
Political Ideologies ◽  
Morphological Approach ◽  
Main Gene ◽  
Individual Consciousness ◽  
The Individual ◽  
Sociological Studies

The aim of the article is to concretize the concept of political ideology in the aspect of its matrix structure and in the context of the cognitive-evolutionary approach. Based on Michael Frieden's morphological approach to the analysis of ideological consciousness, the concept of cognitive-ideological matrices is introduced, which allows us to describe the process of transition from proto-ideological to ideological concepts proper, especially at the level of individual consciousness. The identification of the ideological concept as the main “gene” of conceptual variability and inheritance made it possible to describe the main parameters of the evolution of political ideologies and associate it with changes taking place at the individual consciousness level. The described concept was tested in a series of sociological studies of youth consciousness conducted in 2015-2016 and 2018-2020. As a result of the study, it was possible to first identify the “zero level” of ideology, at which the minds of young respondents are potentially open to the influence of diverse and often mutually exclusive ideological orientations, and second, to pinpoint the changes that have occurred in the cognitive ideological matrices of Rostov-on-Don students over the past five years. This study was conducted by scientists from the southern Federal University.

scholarly journals Retinal vascular fractal dimensions and their association with macrovascular cardiac disease.

2021 ◽  
Author(s):  
Sebastian Dinesen ◽  
Pia Søndergaard Jensen ◽  
Maria Bloksgaard ◽  
Søren Leer Blindbæk ◽  
Jo G.R. De Mey ◽  
...  
Keyword(s):  
Confidence Interval ◽  
Cardiac Disease ◽  
Artery Bypass ◽  
Fractal Dimensions ◽  
Macrovascular Disease ◽  
Control Group ◽  
Vascular Structure ◽  
Non Invasive ◽  
Automatic Software ◽  
Multivariable Regression

Introduction As the only part of the human vasculature, retina is available for direct, non-invasive inspection. Retinal vascular fractal dimension (DF) is a method to measure the structure of the retinal vascular tree, with higher non-integer values between 1 and 2 representing a more complex and dense retinal vasculature. Retinal vascular structure has been associated with a variety of systemic diseases and this study examined the association of DF and macrovascular cardiac disease in a case-control design. Methods Retinal fundus photos were captured with Topcon TRC-50X in 38 persons that had coronary artery bypass grafting (CABG, cases) and 37 cardiovascular healthy controls. The semi-automatic software VAMPIRE was used to measure retinal DF. Results Patients with CABG had lower DF of the retinal main venular vessels compared to the control group (1.15 vs. 1.18, p=0.01). In a multivariable regression model adjusted for gender and age, eyes in the fourth quartile with higher DF were less likely to have CABG compared to patients in the first (OR, 7.20; 95% confidence interval, 1.63 to 31.86; p=0.009) and second quartile (OR, 8.25; 95% confidence interval, 1.70 to 40.01; p=0.009). Conclusions This study demonstrates that lower complexity of main venular vessels associates with higher risk of having CABG. The research supports the hypothesis that the retinal vascular structure can be used to assess non-ocular macrovascular disease.

scholarly journals Quantitative Breast Density in Contrast-Enhanced Mammography

2021 ◽  
Vol 10 (15) ◽  
pp. 3309
Author(s):  
Gisella Gennaro ◽  
Melissa L. Hill ◽  
Elisabetta Bezzon ◽  
Francesca Caumo
Keyword(s):  
Breast Density ◽  
Potential Role ◽  
Multiple Correlation Coefficient ◽  
Low Energy ◽  
Coefficient Of Determination ◽  
Contrast Enhanced ◽  
Increased Risk ◽  
Significant Difference ◽  
Automatic Software ◽  
The Relationship

Contrast-enhanced mammography (CEM) demonstrates a potential role in personalized screening models, in particular for women at increased risk and women with dense breasts. In this study, volumetric breast density (VBD) measured in CEM images was compared with VBD obtained from digital mammography (DM) or tomosynthesis (DBT) images. A total of 150 women who underwent CEM between March 2019 and December 2020, having at least a DM/DBT study performed before/after CEM, were included. Low-energy CEM (LE-CEM) and DM/DBT images were processed with automatic software to obtain the VBD. VBDs from the paired datasets were compared by Wilcoxon tests. A multivariate regression model was applied to analyze the relationship between VBD differences and multiple independent variables certainly or potentially affecting VBD. Median VBD was comparable for LE-CEM and DM/DBT (12.73% vs. 12.39%), not evidencing any statistically significant difference (p = 0.5855). VBD differences between LE-CEM and DM were associated with significant differences of glandular volume, breast thickness, compression force and pressure, contact area, and nipple-to-posterior-edge distance, i.e., variables reflecting differences in breast positioning (coefficient of determination 0.6023; multiple correlation coefficient 0.7761). Volumetric breast density was obtained from low-energy contrast-enhanced spectral mammography and was not significantly different from volumetric breast density measured from standard mammograms.

scholarly journals Evaluation of an AI-based, automatic coronary artery calcium scoring software

2019 ◽  
Vol 30 (3) ◽  
pp. 1671-1678 ◽  
Author(s):  
Mårten Sandstedt ◽  
Lilian Henriksson ◽  
Magnus Janzon ◽  
Gusten Nyberg ◽  
Jan Engvall ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Coronary Artery ◽  
Coronary Artery Calcium ◽  
Rank Test ◽  
Agatston Score ◽  
Risk Category ◽  
Automatic Method ◽  
Calcium Scoring ◽  
Excellent Correlation ◽  
Automatic Software

Abstract Objectives To evaluate an artificial intelligence (AI)–based, automatic coronary artery calcium (CAC) scoring software, using a semi-automatic software as a reference. Methods This observational study included 315 consecutive, non-contrast-enhanced calcium scoring computed tomography (CSCT) scans. A semi-automatic and an automatic software obtained the Agatston score (AS), the volume score (VS), the mass score (MS), and the number of calcified coronary lesions. Semi-automatic and automatic analysis time were registered, including a manual double-check of the automatic results. Statistical analyses were Spearman’s rank correlation coefficient (⍴), intra-class correlation (ICC), Bland Altman plots, weighted kappa analysis (κ), and Wilcoxon signed-rank test. Results The correlation and agreement for the AS, VS, and MS were ⍴ = 0.935, 0.932, 0.934 (p < 0.001), and ICC = 0.996, 0.996, 0.991, respectively (p < 0.001). The correlation and agreement for the number of calcified lesions were ⍴ = 0.903 and ICC = 0.977 (p < 0.001), respectively. The Bland Altman mean difference and 1.96 SD upper and lower limits of agreements for the AS, VS, and MS were − 8.2 (− 115.1 to 98.2), − 7.4 (− 93.9 to 79.1), and − 3.8 (− 33.6 to 25.9), respectively. Agreement in risk category assignment was 89.5% and κ = 0.919 (p < 0.001). The median time for the semi-automatic and automatic method was 59 s (IQR 35–100) and 36 s (IQR 29–49), respectively (p < 0.001). Conclusions There was an excellent correlation and agreement between the automatic software and the semi-automatic software for three CAC scores and the number of calcified lesions. Risk category classification was accurate but showing an overestimation bias tendency. Also, the automatic method was less time-demanding. Key Points • Coronary artery calcium (CAC) scoring is an excellent candidate for artificial intelligence (AI) development in a clinical setting. • An AI-based, automatic software obtained CAC scores with excellent correlation and agreement compared with a conventional method but was less time-consuming.

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