Оценка эффективности страховой деятельности Республики Беларусь

Материалы междунар. научно-практической конференции 15-16 ноября 2001 года

Portfolio Cost Management in Offshore Software Development Outsourcing Relationships from Vendor's Perspective: a Systematic Literature Review Protocol

Abstract: CONTEXT

(R1496) Impact of Electronic States of Conical Shape of Indium Arsenide/Gallium Arsenide Semiconductor Quantum Dots

Semiconductor quantum dots (QDs) have unique atom-like properties. In this work, the electronic states of quantum dot grown on a GaAs substrate has been studied. The analytical expressions of electron wave function for cone-like quantum dot on the semiconductor surface has been obtained and the governing eigen value equation has been solved, thereby obtaining the dependence of ground state energy on radius and height of the cone-shaped -dots. In addition, the energy of eigenvalues is computed for various length and thickness of the wetting layer (WL). We discovered that the eigen functions and energies are nearly associated with the GaAs potential

Impact Of Missing Data Imputation On The Fairness And Accuracy Of Graph Node Classifiers

Analysis of the fairness of machine learning (ML) algorithms recently attracted many researchers' interest. Most ML methods show bias toward protected groups, which limits the applicability of ML models in many applications like crime rate prediction etc. Since the data may have missing values which, if not appropriately handled, are known to further harmfully affect fairness. Many imputation methods are proposed to deal with missing data. However, the effect of missing data imputation on fairness is not studied well. In this paper, we analyze the effect on fairness in the context of graph data (node attributes) imputation using different embedding and neural network methods. Extensive experiments on six datasets demonstrate severe fairness issues in missing data imputation under graph node classification. We also find that the choice of the imputation method affects both fairness and accuracy. Our results provide valuable insights into graph data fairness and how to handle missingness in graphs efficiently. This work also provides directions regarding theoretical studies on fairness in graph data.Comment: Accepted at IEEE International Conference on Big Data (IEEE Big Data

Numerical investigation of the slope stability under the rainfall infiltration of different intensities and duration using finite element code

This research presents a numerical analysis using the two-dimensional finite element code, PLAXIS 2D, to explore the impact of rainfall infiltration on slope stability through a fully coupled deformation flow analysis. In the numerical model, the soil is represented as an elastic-perfect plastic material, and its shear strength is modeled using the Mohr-Coulomb model. Using the 2D finite element method, the study explores the combined effects of varying rectilinear slope geometries, soil types, rainfall intensities, and durations on slope stability. Diverse slope configurations with significant variations in slope height and angle were considered. The results imply that the stability of the slope is significantly influenced by both the rainfall intensity and duration. Moreover, the influence of rainfall duration and intensity on slope stability is more pronounced for clayey soil and slopes with a steep angle. The findings of this study will provide guidelines to engineers in assessing the potential risk of slope failure under varying rainfall intensities and durations

An Efficient Classification of Emotions in Students\u27 Feedback using Deep Neural Network

Background and Objective: In both the corporate and academic worlds, the collection and analysis of feedback (product evaluation, social media debate, and student input) has long been a significant topic. The traditional approaches to collect student feedback focused on data collection and analysis via questionnaires. However, the student makes comments on social media sites that need to be looked at to improve educational standards at schools.Methods: The purpose of this work is to construct a deep neural network-based system to assess students\u27 feedback and emotions found in the reviews. Our approach applies a Deep Learning-based Bi-LSTM Model to a benchmark student input dataset. It would categorize students\u27 feedback about their instructors according to their emotional states, such as love, happiness, fury, and disdain.Results: The experimental findings demonstrate that the proposed approach outperforms both benchmark studies and state-of-the-art machine learning classifiers

New firm survival in developing countries: evidence from Kosovo

This paper examines both newborn firm survival and firm turnover in Kosovo using the population of new firms and registry information on active firms from 2008 to 2012. Survival analysis is employed to analyze the impact of firm- and industry-level characteristics on survival. We find that the hazard rate has an inverted U-shape relationship with both firm age and firm size. The risk of failure increases over the first two years and later decreases. In addition, firms with one employee and more than 10 employees enjoy better survival prospects than medium-sized companies. Interestingly, very large firms do not face fewer risks than very small companies. When compared to other developing countries, entry rates are lower but survival rates are higher. These features seem to be a distinctive characteristic of Kosovo

Pathogen-specific burdens of community diarrhoea in developing countries: A multisite birth cohort study (MAL-ED)

Background: Most studies of the causes of diarrhoea in low-income and middle-income countries have looked at severe disease in people presenting for care, and there are few estimates of pathogen-specific diarrhoea burdens in the community.Methods: We undertook a birth cohort study with not only intensive community surveillance for diarrhoea but also routine collection of non-diarrhoeal stools from eight sites in South America, Africa, and Asia. We enrolled children within 17 days of birth, and diarrhoeal episodes (defined as maternal report of three or more loose stools in 24 h, or one loose stool with visible blood) were identified through twice-weekly home visits by fieldworkers over a follow-up period of 24 months. Non-diarrhoeal stool specimens were also collected for surveillance for months 1-12, 15, 18, 21, and 24. Stools were analysed for a broad range of enteropathogens using culture, enzyme immunoassay, and PCR. We used the adjusted attributable fraction (AF) to estimate pathogen-specific burdens of diarrhoea.|Findings: Between November 26, 2009, and February 25, 2014, we tested 7318 diarrhoeal and 24 310 non-diarrhoeal stools collected from 2145 children aged 0-24 months. Pathogen detection was common in non-diarrhoeal stools but was higher with diarrhoea. Norovirus GII (AF 5·2%, 95% CI 3·0-7·1), rotavirus (4·8%, 4·5-5·0), Campylobacter spp (3·5%, 0·4-6·3), astrovirus (2·7%, 2·2-3·1), and Cryptosporidium spp (2·0%, 1·3-2·6) exhibited the highest attributable burdens of diarrhoea in the first year of life. The major pathogens associated with diarrhoea in the second year of life were Campylobacter spp (7·9%, 3·1-12·1), norovirus GII (5·4%, 2·1-7·8), rotavirus (4·9%, 4·4-5·2), astrovirus (4·2%, 3·5-4·7), and Shigella spp (4·0%, 3·6-4·3). Rotavirus had the highest AF for sites without rotavirus vaccination and the fifth highest AF for sites with the vaccination. There was substantial variation in pathogens according to geography, diarrhoea severity, and season. Bloody diarrhoea was primarily associated with Campylobacter spp and Shigella spp, fever and vomiting with rotavirus, and vomiting with norovirus GII.Interpretation: There was substantial heterogeneity in pathogen-specific burdens of diarrhoea, with important determinants including age, geography, season, rotavirus vaccine usage, and symptoms. These findings suggest that although single-pathogen strategies have an important role in the reduction of the burden of severe diarrhoeal disease, the effect of such interventions on total diarrhoeal incidence at the community level might be limited