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1.
An end-to-end framework for extracting observable cues of depression from diary recordings
Izidor Mlakar, Umut Arioz, Urška Smrke, Nejc Plohl, Valentino Šafran, Matej Rojc, 2024, original scientific article

Abstract: Because of the prevalence of depression, its often-chronic course, relapse and associated disability, early detection and non-intrusive monitoring is a crucial tool for timely diagnosis and treatment, remission of depression and prevention of relapse. In this way, its impact on quality of life and well-being can be limited. Current attempts to use artificial intelligence for the early classification of depression are mostly data-driven and thus non-transparent and lack effective means to deal with uncertainties. Therefore, in this paper, we propose an end-to-end framework for extracting observable depression cues from diary recordings. Furthermore, we also explore its feasibility for automatic detection of depression symptoms using observable behavioural cues. The proposed end-to-end framework for extracting depression was used to evaluate 28 video recordings from the Symptom Media dataset and 27 recordings from the DAIC-WOZ dataset. We compared the presence of the extracted features between recordings of individuals with and without a depressive disorder. We identified several cues consistent with previous studies in terms of their differentiation between individuals with and without depressive disorder across both datasets among language (i.e., use of negatively valanced words, use of first-person singular pronouns, some features of language complexity, explicit mentions of treatment for depression), speech (i.e., monotonous speech, voiced speech and pauses, speaking rate, low articulation rate), and facial cues (i.e., rotational energy of head movements). The nature/context of the discourse, the impact of other disorders and physical/psychological stress, and the quality and resolution of the recordings all play an important role in matching the digital features to the relevant background. In this way, the work presented in this paper provides a novel approach to extracting a wide range of cues relevant to the classification of depression and opens up new opportunities for further research.
Keywords: digital biomarkers of depression, facial cues, speech cues, language cues, deep learning, end-to-end pipeline, artificial intelligence
Published in DKUM: 17.01.2025; Views: 0; Downloads: 1
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2.
Analysis of pipeline vibration
Jurij Avsec, Urška Novosel, 2019, original scientific article

Abstract: Vibrations occur in almost all energy systems. This article presents an analysis of vibrations in pipelines under the influence of fluxes of displaced persons with a pressure difference or with the help of electromagnetic forces. For this purpose, we analysed pipelines of different diameters and the flow of crude oil within the pipelines.
Keywords: pipeline vibration, pipeline fluid flow, continuous vibration
Published in DKUM: 05.12.2023; Views: 285; Downloads: 7
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3.
Gender gap in Slovakia : selected problems of education and career
Katarína Danielová, Viliam Lauko, 2016, original scientific article

Abstract: The article focuses on the gap between women education and their career. Women’s education has significantly increased in a few last years, but their position on the labour market has been more difficult in comparison with men. The share of economical active women and also the share of working women with higher education have been growing till the present time. However, it is questionable how do women use their higher education in career or whether they can build even some career. We have used the data from Statistical Office of the Slovak Republic and some problems have been presented in the area of Slovakia on the level of regions (kraje).
Keywords: gender gap, education, career, Slovakia, leaky pipeline
Published in DKUM: 17.04.2018; Views: 1439; Downloads: 125
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4.
Deformation and energy parameters of fracture of steel of the main gas pipeline
P. O. Maruščak, Sergey Panin, Ulyana Polyvana, Tomaž Vuherer, Anna Guzanová, Janette Brezinová, 2015, original scientific article

Abstract: By example of steel 17G1S, the regularities in the impact fracture of Charpy specimens at normal and low temperatures are described. The relationship between the energy parameters of fracture (impact toughness) and the deformation response of the material (the height of shear lips) of the specimens from the pipe steel is established. The micromechanisms of impact fracture of the material are described. At 20 °C and –30 °C, focal splitting of the material was observed on the fracture surface of specimens; at –60 °C, the material failed in a brittle manner by the mechanism of cleavage.
Keywords: impact toughness, main gas pipeline, failure analysis
Published in DKUM: 08.08.2017; Views: 1135; Downloads: 382
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5.
Low temperature impact toughness of the main gas pipeline steel after long-term degradation
P. O. Maruščak, Irina Danyliuk, R.T. Biščak, Tomaž Vuherer, 2014, original scientific article

Abstract: The correlation of microstructure, temperature and Charpy V-notch impact properties of a steel 17G1S pipeline steel was investigated in this study. Within the concept of physical mesomechanics, the dynamic failure of specimens is represented as a successive process of the loss of shear stability, which takes place at different structural/scale levels of the material. Characteristic stages are analyzed for various modes of failure, moreover, typical levels of loading and oscillation periods, etc. are determined. Relations between low temperature derived through this test, microstructures and Charpy (V-notch) toughness test results are also discussed in this paper.
Keywords: impact toughness, fracture, damage, gas pipeline, steel, degradation
Published in DKUM: 03.04.2017; Views: 1497; Downloads: 453
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