Application of fuzzy logic in finding the optimal filter in optoacoustics problems

Denoising is an important step in the early stage of signal preprocessing in optoacoustic applications. The efficiency of such modern noise removal methods as wavelet or curvlet filtering depends significantly on the numerical combinations and forms of wavelet transform parameters, and the multidimensional extension of such filters is rather non-trivial. These issues are serious obstacle for using of these highly effective filters in the tasks of optoacoustic reconstruction, especially in real laboratorial or medical practice. The objective of our study was to find the optimal filter, convenient for use in laboratorian and medical practice, when the types of noise are a priori unknown, and the filter settings should not take much time. In the offered work spatial filters which have only one parameter of adjustment - the size of a window are considered. Three-dimensional extensions of such well-established denoising techniques, as mean filter, median filter, their adaptive variants (Wiener spatial filter and modified median filter), as well as iterative truncated arithmetic mean filter were analyzed. The proposed filters were tested on a test set that contains versions of Shepp-Logan's three-dimensional phantom with mixtures of Gaussian and alpha-stable noise, as well as speckle noise. The identification of the best filter for simultaneous suppression of these types of interference was carried out using the theory of fuzzy sets. In our tests, a modified median filter and an iterative truncated arithmetic mean filter were rated as the best choice when the goal is to minimize aberrations when noise is not known a priory.

Bernoulli multi-armed bandit problem under delayed feedback

Online learning under delayed feedback has been recently gaining increasing attention. Learning with delays is more natural in most practical applications since the feedback from the environment is not immediate. For example, the response to a drug in clinical trials could take a while. In this paper, we study the multi-armed bandit problem with Bernoulli distribution in the environment with delays by evaluating the Explore-First algorithm. We obtain the upper bounds of the algorithm, the theoretical results are applied to develop the software framework for conducting numerical experiments.

Review of neural approaches for conditional text generation

The article is devoted to the review of conditional test generation, one of the most promising fields of natural language processing and artificial intelligence. Specifically, we explore monolingual local sequence transduction tasks: paraphrase generation, grammatical and spelling errors correction, text simplification. To give a better understanding of the considered tasks, we show examples of good rewrites. Then we take a deep look at such key aspects as publicly available datasets with the splits (training, validation, and testing), quality metrics for proper evaluation, and modern solutions based primarily on modern neural networks. For each task, we analyze its main characteristics and how they influence the state-of-the-art models. Eventually, we investigate the most significant shared features for the whole group of tasks in general and for approaches that provide solutions for them.

Scene Change Localization in a Video

Millions of videos are uploaded each day to Youtube and similar platforms. One of the many issues that these services face is the extraction of useful metadata. There are a lot of tasks that arise with the processing of videos. For example, putting an ad is better in the middle of a video, and as an advertiser, one would probably prefer to show the ad in between scene cuts, where it would be less intrusive. Another example is when one would like to watch only through the most interesting or important pieces of video recording. In many cases, it is better to have an automatic scene cut detection approach instead of manually labeling thousands of videos. The scene change detection can help to analyze video-stream automatically: which characters appear in which scenes, how they interact and for how long, their relations and importance, and also to track many other issues. The potential solution can rely on different facts: objects appearance, contrast or intensity changed, other colorization, background chang, and also sound changes. In this work, we propose the method for effective scene change detection, which is based on thresholding, and also fade-in/fade-out scene analysis. It uses computer vision and image analysis approaches to identify the scene cuts. Experiments demonstrate the effectiveness of the proposed scene change detection approach.

The impact of management on the behavior of an isolated logistics population

The article considers the isolated population described by the logistic equation and studies the influence of management on the change of its number. Depending on the value of the control parameter, there are three different cases of behavior of an isolated population. In the first case, when the quota is equal to the corresponding value, depending on the initial value, the population either goes to a stationary value, or dies out. In the second case, when the quota does not exceed the established value, depending on the initial population size, the population either goes to the largest stationary point, or dies out. And in the third case, when the quota exceeds the established value, regardless of the initial population size, the population dies out. Stationary points for stability in all three cases are studied and graphs of population behavior depending on different initial conditions are presented.

Analysis of educational and professional programs in the specialty 122 Computer Science in terms of program learning outcomes

The article presents an analysis of the educational and professional program "Informatics" of the first (bachelor's) level of higher education in the sphere of knowledge 12 "Information Technology", specialty 122 "Computer Science", implemented at the Faculty of Computer Science and Cybernetics, Taras National University of Kyiv Shevchenko with educational and professional programs of the same level and specialty of other institutions of higher education of Ukraine in terms of program results. During the analysis, they were compared with the approved standard of the first (bachelor's) level of higher education in the specialty 122 "Computer Science". In order to analyze the authors developed a database of educational programs. The ratio of program results in different programs by common specialty is analyzed.

Simulation of a strictly φ-sub-Gaussian generalized fractional Brownian motion

In the paper, we consider the problem of simulation of a strictly φ-sub-Gaussian generalized fractional Brownian motion. Simulation of random processes and fields is used in many areas of natural and social sciences. A special place is occupied by methods of simulation of the Wiener process and fractional Brownian motion, as these processes are widely used in financial and actuarial mathematics, queueing theory etc. We study some specific class of processes of generalized fractional Brownian motion and derive conditions, under which the model based on a series representation approximates a strictly φ-sub-Gaussian generalized fractional Brownian motion with given reliability and accuracy in the space C([0; 1]) in the case, when φ(x) = (|x|^p)/p, |x| ≥ 1, p > 1. In order to obtain these results, we use some results from the theory of φ-sub-Gaussian random processes. Necessary simulation parameters are calculated and models of sample pathes of corresponding processes are constructed for various values of the Hurst parameter H and for given reliability and accuracy using the R programming environment.

Fast calculations of Jackknife covariance matrix estimator

We consider data in which each observed subject belongs to one of different subpopulations (components). The true number of component which a subject belongs to is unknown, but the researcher knows the probabilities that a subject belongs to a given component (concentration of the component in the mixture). The concentrations are different for different observations. So the distribution of the observed data is a mixture of components’ distributions with varying concentrations. A set of variables is observed for each subject. Dependence between these variables is described by a nonlinear regression model. The coefficients of this model are different for different components. Normality of estimator for nonlinear regression parameters is demonstrated under general assumptions. A mixture of logistic regression models with continuous response is considered as an example. In the paper we construct confidence ellipsoids for the regression parameters based on the modified least squares estimators. The covariances of these estimators are estimated by the multiple modifications of jackknife technique. Performance of the obtained confidence ellipsoids is assessed by simulations.

Approximation of density of potentials for the flat viscoelastic bodies with inclusions, bounded by a piecewise smooth contours

An approach for approximating unknown densities of potentials in the study of the stressed state of a flat viscoelastic piecewise homogeneous body with inclusions, bounded by piecewise smooth contours, is proposed. The method is based on the construction of a system of boundary-time integral equations to determine the unknown densities of potentials along the contours of the inclusions. The approximation of the unknown densities of potentials was performed taking into account the singularity of the stressed state of a flat viscoelastic body near the angular point of the dividing line of the regions.

Optimization of power distribution of network channels based on Orlin's algorithm

The article proposes an algorithm for solving the problem of optimal distribution of the capacity of data transmission channels between providers and Internet users. A mathematical model of the problem of distribution of a limited homogeneous resource with transport-type constraints is formulated. A solution method based on Orlin's stream algorithm is considered. A practical application of the algorithm for solving a real distribution problem is proposed. The results of the capacity of the channels of the computer network are obtained with a perspective increase in the capacity of the connections represented by the intervals of the planned changes. An analysis of the solutions obtained with different number of switching servers was made, conclusions about the choice of the provider to meet the optimal information needs of users were made.