Approaches to measuring average and median wages in Russia and abroad: data sources and users

This article focuses on the measurement of average and median wages, which are closely related to indicators of living standards. We reveal the problem of insufficient discussion of current issues in labor income measurement in contemporary Russian economic literature. The aim of this article is to contribute to the scientific substantiation of the relationship between methodology, procedure, and algorithm in measuring the average and median wages of wage earners in the Russian Federation (RF). The novelty of this study lies in comparing primary indicators from the Russian Federal State Statistics Service (Rosstat) and foreign companies and formulating conclusions about significant differences between estimates from the United States, Europe, and Russia in the studied area. A comparative analysis of Rosstat’s (Russia) estimates of average and median wages shows an inverse relationship to those of US and European companies. To address the problems of significant discrepancies and unreliability of Russian figures, we propose streamlining the relationship between the concepts of “methodology,” “procedure,” and “algorithm” in measuring average and median wages in the RF. To this end, we propose meaningfully linking “methodology” with formulas for calculating average wages, “procedure” with the object of measurement, and “algorithm” with the source/subject of measurement and users of measurement results. We focus on the experiences of American and European companies as being very important, primarily in the context of users of these indicators, i.e., company employees. Informing wage earners about the results of average and median wage measurements could be an effective tool for overcoming labor income inequality in the RF

DEVELOPMENT OF AEROSPACE IMAGES PRELIMINARY PROCESSING METHOD FOR SUBSEQUENT RECOGNITION AND IDENTIFICATION OF VARIOUS OBJECTS

Nowadays, the application of hyperspectral images is vital for every section of the humanity life such as agrotechnical research for the field condition state and water security. This article presents a new lossless data compression algorithm focused on the processing of hyperspectral aerospace images. The algorithm takes into account inter-band correlation and difference transformations to effectively reduce the range of initial values. correlation allows you to find the best reference channel that defines the sequence of operations in the algorithm, which contributes to a significant increase in the compression ratio while maintaining high data quality. The practical implementation of the algorithm lies in the process of the transfer the lower size file with high efficiency for unmanned aerial vehicle and satellites to save more computational resources. This method demonstrates high computational efficiency and can be applied to various tasks that require efficient storage and transmission of hyperspectral images. The importance of processing hyperspectral data and the problems associated with their volume and complexity of analysis were described. Current approaches to data compression are considered and their limitations are identified, which justifies the need to develop new methods. The relevance and necessity of effective compression algorithms for aerospace applications is emphasized. An analysis of existing methods and algorithms for compressing hyperspectral data was carried out. Particular attention is paid to approaches that use cross-channel correlation and difference transformations. The effectiveness of current methods is evaluated and their shortcomings are identified, which serves as a justification for the development of a new algorithm. A developed lossless data compression algorithm based on the use of inter-band correlation and difference transformations was described. The stages of forming groups of channels and the selection of optimal compression parameters are considered in detail. The method of determining the reference channel, which sets the sequence of operations in the algorithm, which provides more efficient data compression, is especially noted. The advantages and possible limitations of the new approach, as well as its potential for practical use, are discussed. It was noted that the developed method successfully solves the problems associated with the volume of hyperspectral data, providing a high compression ratio without quality loss. The prospects for further development of the algorithm and its application in various fields of science and technology are discussed

MATHEMATICAL FRAMEWORK FORMULATION AND IMPLEMENTATION FOR HYPERSPECTRAL AEROSPACE IMAGES PROCESSING

This paper proposes a preprocessing algorithm for aerospace hyperspectral images based on a mathematical apparatus effectively applied in pre-compression transformation problems. In particular, several methods have been analyzed for hyperspectral image (signal) preprocessing from the point of view of digital signal processing algorithms. These mathematical methods are used for problems of filtering signals from noise of different natures and for compression and restoration of signals after their transmission through communication channels. The results of comparative analysis of preparatory processing of lossy compression algorithms based on wavelet analysis, discrete and orthogonal transforms are also given, demonstrating minimization of loss level of reconstructed decoded images. The performance of the proposed preprocessing algorithms with quality metrics is presented to evaluate the quality of the reconstructed hyperspectral aerospace images. The results of this study can be applied and used in the tasks of special processing of hyperspectral images, as well as fundamental knowledge of mathematical apparatuses of the proposed orthogonal preprocessing, considering the specificity of the data which is very important in obtaining images ready for compression for the subsequent identification of objects of the Earth's surface and using such mathematical transformations at the hyperspectral image preprocessing stage before compression provides efficient archiving of the obtained data, while reducing the communication channel load. Through the use of quality metrics of the reconstructed images, the preprocessing algorithm provides an understanding of the threshold of the peak signal-to-noise ratio value and the efficiency of its application to calculate and minimize the loss rate

Development of domestic nutrition additives

This paper discusses the create a qualitatively new domestic lizotsim-contained natural biological corrector (NBC) with an effective use of its technology in the production of meat and dairy products competitive directional

Determination of the speed of a microprocessor relay protection device of open architecture with a reed switch and the industrial internet of things

The paper presents the development of a microprocessor-based relay protection device on open architecture. Currently, there is a problem with modern microprocessor relay protection: the impossibility to replace the damaged element with alternatives from other manufacturers. The solution to this problem is the use of devices with open architecture. The study developed a structural model of a microprocessor-based relay protection device based on an open architecture with the industrial Internet of things application. Open architecture is achieved through open protocols and the principle of modularity. The industrial Internet of things technology transfers the control action of triggering blocking. A microprocessor-based relay protection device prototype based on an open architecture was developed. The simulation of the developed device was conducted. The appearance of higher harmonics and aperiodic components in the short-circuit current was not considered during modeling. Due to the study's limitations in the form of lack of load, current and voltage sensors, such as Hall sensors, and inductance coils, the subject of this study is only the speed of operation. A high multiplicity current generation setup was assembled for experimental testing. The developed relay protection device on an open architecture trips faster than the traditional solution. The application of the Internet of Things allowed it to ensure the blocking of non-selective tripping. The obtained results are provided by structural simplification compared to traditional solutions and speed of information transfer with the application of the Internet of things. The developed open architecture device with the industrial Internet of things technology application gives new possibilities for relay protection systems, including flexibility to meet the requirements in connection with the introduction of distributed powe

Development of compression algorithms for hyperspectral aerospace images based on discrete orthogonal transformations

The paper describes the development of compression algorithms for hyperspectral aerospace images based on discrete orthogonal transformations for the purpose of subsequent compression in Earth remote sensing systems. As compression algorithms necessary to reduce the amount of transmitted information, it is proposed to use the developed compression methods based on Walsh-Hadamard transformations and discrete-cosine transformation. The paper considers a methodology for developing lossy and high-quality compression algorithms during recovery, taking into account which an adaptive algorithm for compressing hyperspectral AI and the generated quantization table has been developed. The conducted studies have shown that the proposed lossy algorithms have sufficient efficiency for use and can be applied when transmitting hyperspectral remote sensing data in conditions of limited buffer memory capacity and bandwidth of the communication channel

Hyperspectral regression lossless compression algorithm of aerospace images

In this work, we propose an algorithm for compressing lossless hyperspectral aerospace images, which is characterized by the use of a channel-difference linear regression transformation, which significantly reduces the range of data changes and increases the degree of compression. The main idea of the proposed conversion is to form a set of pairs of correlated channels with the subsequent creation of the transformed blocks without losses using regression analysis. This analysis allows you to reduce the size of the channels of the aerospace image and convert them before compression. The transformation of the regressed channel is performed on the values of the constructed regression equation model. An important step is coding with the adapted Huffman algorithm. The obtained comparison results of the converted hyperspectral AI suggest the effectiveness of the stages of regression conversion and multi-threaded processing, showing good results in the calculation of compression algorithms

Methodology for Developing Algorithms for Compressing Hyperspectral Aerospace Images used on Board Spacecraft

The paper describes a method for constructing and developing algorithms for compressing hyperspectral aerospace images (AI) of hardware implementation for subsequent use in remote sensing Systems (RSS). The developed compression methods based on differential and discrete transformations are proposed as compression algorithms necessary for reducing the amount of transmitted information. The paper considers a method for developing compression algorithms, which is used to develop an adaptive algorithm for compressing hyperspectral AI using programmable devices. Studies have shown that the proposed algorithms have sufficient efficiency for use and can be applied on Board spacecraft when transmitting hyperspectral remote sensing data in conditions of limited buffer memory capacity and communication channel bandwidth

Lossless compression of hyperspectral images with pre-byte processing and intra-bands correlation

This paper considers an approach to the compression of hyperspectral remote sensing data by an original multistage algorithm to increase the compression ratio using auxiliary data processing with its byte representation as well as with its intra-bands correlation. A set of the experimental results for the proposed approach of effectiveness estimation and its comparison with the well-known universal and specialized compression algorithms is presented

Lossless compression of hyperspectral images with pre-byte processing and intra-bands correlation

This paper considers an approach to the compression of hyperspectral remote sensing data by an original multistage algorithm to increase the compression ratio using auxiliary data processing with its byte representation as well as with its intra-bands correlation. A set of the experimental results for the proposed approach of effectiveness estimation and its comparison with the well-known universal and specialized compression algorithms is presented.Este documento se refiere a la compresión de datos hiperespectrales de teleobservación de la tierra mediante la sugerencia de un algoritmo de múltiples etapas para aumentar la relación de compresión, utilizando una formación de datos auxiliares de gran redundancia en su presentación de bytes y teniendo en cuenta la correlación intra-bandas. Aquí se presentan los resultados de los estudios sobre la eficacia de la compresión de imágenes hiperespectrales espaciales realizadas por el algoritmo de compresión propuesto con software de compresión universal y especializado