Essays in monetary and financial macroeconomics

This dissertation consists of two chapters. In the first chapter I study the effects of trend inflation on aggregate price and output dynamics and their implications for the effectiveness of monetary stabilization policy. In the second chapter I study the determinants of leverage and asset prices in a general equilibrium model with incomplete markets and collateral requirements

Понятието „търговска тайна“ и задължението за опазването ѝ от работниците и служителите

The paper analyzes the institute of trade secret in Bulgarian legislation in the context of the obligations of the employees and workers. The focus of the study is on the rules of national law and the Law on Protection of Trade Secrets. Based on the analysis, the basic concepts are outlined and the specific obligations of employees and workers for protecting the trade secret. Conclusions and recommendations are made on the application of the legal norms

Super-resolution imaging for the detection of low-energy ion tracks in fine-grained nuclear emulsions

We propose a new wide-field imaging method that exploits the Localized Surface Plasmon Resonance phenomenon to produce super-resolution images with an optical microscope equipped with a custom design polarization analyzer module. In this paper we describe the method and apply it to the analysis of low-energy carbon ion tracks implanted in a nuclear emulsion film. The result is then compared with the measurements of the same tracks carried out at an electronic microscope. The images set side by side show their close similarity. The resolution achieved with the current microscope setup is estimated to be about 50 nm.Comment: 13 pages, 10 figure

Development of an Algorithm for Multicriteria Optimization of Deep Learning Neural Networks

Nowadays, machine learning methods are actively used to process big data. A promising direction is neural networks, in which structure optimization occurs on the principles of self-configuration. Genetic algorithms are applied to solve this nontrivial problem. Most multicriteria evolutionary algorithms use a procedure known as non-dominant sorting to rank decisions. However, the efficiency of procedures for adding points and updating rank values in non-dominated sorting (incremental non-dominated sorting) remains low. In this regard, this research improves the performance of these algorithms, including the condition of an asynchronous calculation of the fitness of individuals. The relevance of the research is determined by the fact that although many scholars and specialists have studied the self-tuning of neural networks, they have not yet proposed a comprehensive solution to this problem. In particular, algorithms for efficient non-dominated sorting under conditions of incremental and asynchronous updates when using evolutionary methods of multicriteria optimization have not been fully developed to date. To achieve this goal, a hybrid co-evolutionary algorithm was developed that significantly outperforms all algorithms included in it, including error-back propagation and genetic algorithms that operate separately. The novelty of the obtained results lies in the fact that the developed algorithms have minimal asymptotic complexity. The practical value of the developed algorithms is associated with the fact that they make it possible to solve applied problems of increased complexity in a practically acceptable time. Doi: 10.28991/HIJ-2023-04-01-011 Full Text: PD