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Effective management of water resources is possible only with an effectively organized monitoring system. After the emergence and development of information theory, the concept of information entropy found its place in the field of the development of water monitoring systems. The purpose of this work is to review research related to the construction of water monitoring systems and networks that applied the entropy theory in the design process. Methodology. Entropy terms used in the construction of water monitoring systems are summarized. Recent applications of the entropy concept for water monitoring system designs classified by precipitation are reviewed; flow and water level; water quality; soil moisture and groundwater. The integrated method of designing multifactorial monitoring systems is also highlighted. Results. The review analyzes studies and their implementation in the design of water monitoring networks based on entropy. The use of various methods of information theory and their adaptation for use in the design of monitoring networks is demonstrated, with the goal of network design methods being the selection of stations that provide the most information for the monitoring network, while being independent of each other. Through extensive testing, information theory has proven to be a reliable tool for evaluating and designing an optimal water monitoring network. Scientific novelty. This review focuses on studies that have applied information theory or information entropy to construct monitoring networks and systems. Information theory was developed by Shannon in the middle of the last century to measure the information content of a data set and was subsequently applied to solving water resources problems. To date, there are no review studies regarding the design of water monitoring networks based on the concept that entropy will be able to characterize the information specific to the monitoring station or monitoring networks. The main goal is to have the maximum amount of information. Practical significance. The optimal design of the monitoring network can be built based on the specified design criteria; however, the practical application of a new optimal monitoring network is rarely evaluated in a hydrological or other model. It is also important to identify the benefits of entropy-based network design to convince decision-makers of the importance of entropy-based approaches. The optimal network can be subjective, based on the choices made during the entropy calculation and the design method chosen, especially when additional objective functions are considered in the design. This applies to the method chosen to construct the optimal monitoring network, whether it is found using an iterative method where one station is added at a time, or a collection of stations that are added simultaneously. Research has also shown that data length, catchment scale, and the order can affect optimal network design. when using discrete entropy, it was shown that the binning method affects the final network design. Therefore, when selecting options based on the intended application of the monitoring network, a clear understanding and further research is needed to provide recommendations specific to water monitoring networks. In particular, more work is needed on the spatial and temporal scaling of the entropy calculation data to provide robust recommendations for decision-makers.

The article substantiates the problem of translators’ interpretations of information entropy cases in time-remote original texts on the example of William Shakespeare’s plays in the process of translators’ creative reproduction of the original works in the target language. The purpose of the article is to identify the factors that determine the difference in translators’ interpretations and their manifestations in chronologically distant Ukrainian retranslations of the 19th–21st centuries. The tasks of the research are the following: to describe the theoretical basis of the research by determining the specifics of translator’s interpretation and the phenomenon of information entropy from the standpoint of translation theory and practice; to show the influence of different extralingual factors on the process and result of Ukrainian retranslations. The research material is taken from Shakespeare’s tragedies “Romeo and Juliet” (1594) and “Hamlet, Prince of Denmark” (1600), which serve as samples of Early Modern English at the turn of the 16th and 17th centuries, and their chronologically distant Ukrainian retranslations of the 19th–21st centuries. The research methodology incorporates not only general scientific methods, as well as empirical methods in order to substantiate the theoretical basis of the research, but also methods of discourse analysis (cultural and historical, comparative-linguistic-cultural), methods of literary analysis (biographical, hermeneutic, interpretive-textual), methods of linguistic analysis (etymological, contextual, descriptive, semantic, and stylistic) and methods of contrastive translation and transformational analysis, which are used to determine the changes in the scope of information expressed by the units of analysis in the timeremote original texts and in chronologically distant Ukrainian retranslations of the 19th – 21st centuries. The article argues that the difference in translators’ interpretations and, consequently, the variety of retranslations are taken into account by different objective and subjective extralingual factors that influence the process and result of retranslations in cases of information entropy. The objective factors are the historically different social and cultural contexts in which the original texts of the 16th–17th centuries and their chronologically distant Ukrainian retranslations of the 19th–21st centuries are created; the literary trends dominating at the corresponding epochs that influence the author’s and translators’ artistic styles. The subjective factors are translators’ creative personalities that reflect their perception of the surrounding world and personal worldviews determined by their different life experience and social background. Objective and subjective factors, which cause different interpretations of information entropy cases in the time-remote original text and presentation of different scope of information in chronologically distant Ukrainian retranslations, are interrelated and interdependent. If all the factors are the same, i.e. the translators belong to one and the same historical period of time, adhere to the same literary trend and have the same cultural and social background, the translators’ interpretations coincide. At least one of the factors being different, the translators’ interpretations of information entropy cases differ which is a prerequisite for the diachronic plurality in translation of time-remote Shakespeare’s tragedies by Ukrainian translators of the 19th–21st centuries.

Effective management of water resources is possible only with an effectively organized monitoring system. After the emergence and development of information theory, the concept of information entropy found its place in the field of the development of water monitoring systems. The purpose of this work is to review research related to the construction of water monitoring systems and networks that applied the entropy theory in the design process. Methodology. Entropy terms used in the construction of water monitoring systems are summarized. Recent applications of the entropy concept for water monitoring system designs classified by precipitation are reviewed; flow and water level; water quality; soil moisture and groundwater. The integrated method of designing multifactorial monitoring systems is also highlighted. Results. The review analyzes studies and their implementation in the design of water monitoring networks based on entropy. The use of various methods of information theory and their adaptation for use in the design of monitoring networks is demonstrated, with the goal of network design methods being the selection of stations that provide the most information for the monitoring network, while being independent of each other. Through extensive testing, information theory has proven to be a reliable tool for evaluating and designing an optimal water monitoring network. Scientific novelty. This review focuses on studies that have applied information theory or information entropy to construct monitoring networks and systems. Information theory was developed by Shannon in the middle of the last century to measure the information content of a data set and was subsequently applied to solving water resources problems. To date, there are no review studies regarding the design of water monitoring networks based on the concept that entropy will be able to characterize the information specific to the monitoring station or monitoring networks. The main goal is to have the maximum amount of information. Practical significance. The optimal design of the monitoring network can be built based on the specified design criteria; however, the practical application of a new optimal monitoring network is rarely evaluated in a hydrological or other model. It is also important to identify the benefits of entropy-based network design to convince decision-makers of the importance of entropy-based approaches. The optimal network can be subjective, based on the choices made during the entropy calculation and the design method chosen, especially when additional objective functions are considered in the design. This applies to the method chosen to construct the optimal monitoring network, whether it is found using an iterative method where one station is added at a time, or a collection of stations that are added simultaneously. Research has also shown that data length, catchment scale, and the order can affect optimal network design. when using discrete entropy, it was shown that the binning method affects the final network design. Therefore, when selecting options based on the intended application of the monitoring network, a clear understanding and further research is needed to provide recommendations specific to water monitoring networks. In particular, more work is needed on the spatial and temporal scaling of the entropy calculation data to provide robust recommendations for decision-makers. [ABSTRACT FROM AUTHOR]

The subject of the research is the optimization of the composition of the project portfolio based on the entropy concept. The aim of the study is to experimentally test the model for optimizing the portfolio of a project-oriented organization and substantiate its applicability in practice in management processes to ensure their effectiveness. Research objectives: forming a model taking into account the accepted value of the organization; formation of initial data on the organization and alternative projects; portfolio optimization by model and interpretation of results. Research methods: system analysis, functional analysis, operations research. Results. A model has been developed for forming a portfolio structure from projects of two categories – operational and development; the optimization criterion is to minimize the discrepancy between the desired and actually provided value of the organization. The restrictions take into account the maximum allowable energy limit and the minimum allowable value limit. As a result of the study, the applicability and adequacy of the model for optimizing the portfolio structure of a project-oriented organization were substantiated. The model makes it possible to obtain solutions on the optimal structure of a portfolio of projects in terms of its value under given resource constraints (in the form of a share of total energy and output energy) and energy entropy. The studies substantiated the possibility of adjusting the model in terms of the optimization criterion (maximizing value, minimizing energy entropy) and adding restrictions on the maximum permissible border of information entropy and energy efficiency. Conclusions. The model under consideration is characterized by wide practical application, taking into account its possible adjustment without changing the basic essence, taking into account the specifics of a particular field of activity or organization. The practical use of the main indicators of the entropy concept - information entropy, temperature, energy entropy, which characterize the state of organizations, allowing to identify hidden problems before they are reflected on the traditional indicators of organizational performance is demonstrated. Taking this into account, the structure of the project portfolio is being formed within the framework of the considered approach.

An important component of streaming large amounts of information are algorithms for compressing information flow. Which in turn are divided into lossless compression algorithms (entropic) - Shannon, Huffman, arithmetic coding, conditional compression - LZW, and other information cone injections and lossy compression algorithms - such as mp3, jpeg and others. It is important to follow a formal strategy when building a lossy compression algorithm. It can be formulated as follows. After describing the set of objects that are atomic elements of exchange in the information flow, it is necessary to build an abstract scheme of this description, which will determine the boundary for abstract sections of this scheme, which begins the allowable losses. Approaches to the detection of an abstract scheme that generates compression algorithms with allowable losses can be obtained from the context of the subject area. For example, an audio stream compression algorithm can divide a signal into simple harmonics and leave among them those that are within a certain range of perception. Thus, the output signal is a certain abstraction of the input, which contains important information in accordance with the context of auditory perception of the audio stream and is represented by less information. A similar approach is used in the mp3 format, which is a compressed representation. Unlike lossy compression algorithms, entropic compression algorithms do not require context analysis, but can be built according to the frequency picture. Among the known algorithms for constructing such codes are the Shannon-Fano algorithm, the Huffman algorithm and arithmetic coding. Finding the information entropy for a given Shannon code is a trivial task. The inverse problem, namely finding the appropriate Shannon codes that have a predetermined entropy and with probabilities that are negative integer powers of two, is quite complex. It can be solved by direct search, but a significant disadvantage of this approach is its computational complexity. This article offers an alternative technique for finding such codes. [ABSTRACT FROM AUTHOR]

The reconnaissance data processing plays much role in warfare. The validity of this information is one of the most necessities for staff correct decision-making. Information entropy is a measure of data uncertainty. In information theory the concept of entropy describes how much information there is in signal or event. Information entropy relates to uncertainty amount concerning an event associated with given probability distribution. In this paper, the main importance of information entropy has been shown. In the same time, the application of both information entropy and expert evaluation methods in reconnaissance data processing has been considered. In consideration of the several sources of reconnaissance data, the calculation method of this information validity assessment has been offered on the basis of information entropy and expert evaluation.

The article is dedicated to the problem of rating Ukraine’s higher educational institutions in terms of scientific activity and the study of the influence of weighting factors on the position of a university in the ranking. The initial information space used in this work makes it possible to determine the potential of scientific activity in terms of staffing and resources provision as well as its effectiveness in terms of quality of the training of scientific staff (students, graduate students, young scientists, etc.), financial results of scientific and publication activities. As the objects of the research 98 universities of Ukraine are selected. On the basis of the maximum entropy method, the weighting factors that determine the significance of each initial indicator of the information space are calculated. Using the taxonomic method, integral estimates in terms of potential, effectiveness and scientific activity for each institution in whole are calculated with and without the use of the weighting factors. The analysis of the received scores of the universities is carried out, changes in the positions under influence of the weighting factors are investigated. It is concluded that the use of the weighting factors in calculating the integral estimate of the scientific activity of Ukrainian universities did not lead to shifts among the first (the strongest) and the last (the weakest) universities. But changes in the positions in the ranking, sometimes quite significant, took place in most of the universities occupying the middle positions. Thus, due to the weighting factors, the influence of outlying cases on individual indicators is leveled, which allows obtaining more stable, fair and informative results of rating the scientific activity of universities.

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The article characterizes population trading service in Kharkiv region. The brief analysis of the previous human-geographical research on trading sector was given. The system approach in human geography was emphasized, the research is based on this approach. The definition of “social and geographical system” was given. The essence of the social and geographical system local classifications was revealed. They include indicators of system development (indexes sum of the social and geographical system statistical parameters; projection square of the social and geographical system state in the multidimensional space on plane (by the graphanalytical method), development uniformity; information entropy, given information entropy) and development dynamic – trajectory parameters (cosine of an angle between social and geographical system trajectory and optimal trajectory; distance traveled by a social and geographical system in the multidimensional feature space (L); distance between the current point and the minimal development point (coordinates beginning) (L0); distance from the current point to the maximum development point (end point) (L1); progress coefficient). Among cities of regional subordination the city of Kharkiv is highlighted by system development indicators, since it is the biggest city in the region, characterized the highest level of socio-economic development. Among Kharkiv region’s district the highest values of system development have Kharkivs'kyy, Krasnohrads'kyy, Derhachivs'kyy districts, the lowest – Kupyans'kyy, Krasnohrads'kyy, Kolomats'kyy districts. Districts with the relatively high level of social and economic development have higher polygon square, indexes sum, information entropy, given information entropy. The farthest districts, with the relatively low level of social and economic development are characterized lower parameters. [ABSTRACT FROM AUTHOR]