Entropy-Argumentative Concept of Computational Phonetic Analysis of Speech Taking into Account Dialect and Individuality of Phonation

In this article, the concept (i.e., the mathematical model and methods) of computational phonetic analysis of speech with an analytical description of the phenomenon of phonetic fusion is proposed. In this concept, in contrast to the existing methods, the problem of multicriteria of the process of cognitive perception of speech by a person is strictly formally presented using the theoretical and analytical apparatus of information (entropy) theory, pattern recognition theory and acoustic theory of speech formation. The obtained concept allows for determining reliably the individual phonetic alphabet inherent in a person, taking into account their inherent dialect of speech and individual features of phonation, as well as detecting and correcting errors in the recognition of language units. The experiments prove the superiority of the proposed scientific result over such common Bayesian concepts of decision making using the Euclidean-type mismatch metric as a method of maximum likelihood and a method of an ideal observer. The analysis of the speech signal carried out in the metric based on the proposed concept allows, in particular, for establishing reliably the phonetic saturation of speech, which objectively characterizes the environment of speech signal propagation and its source

Study of the Operation Process of the E-Commerce Oriented Ecosystem of 5Ge Base Station, Which Supports the Functioning of Independent Virtual Network Segments

According to specifications, flexible services for traffic management should be implemented within the 5G platform in order to improve its efficiency, which is and will remain an actual task. For the first time, the article presented here proposes a mathematical model for the operation process of an e-commerce-oriented ecosystem of a 5Ge base station, the information environment of which supports the operation of independent virtual network segments that provide terminal–segment information interaction services. In contrast to existing models, the presented model describes the studied process as a multi-pipeline queuing system, the inputs of which are coordinated with the flows of requests for communication with the relevant virtual network segments. The distribution of the total resources between the weighted virtual network segments in the simulated system is dynamically conducted by the appropriate software control mechanism. It considers the address intensities of new incoming requests and the maintenance of received incoming requests, but throughout the scale of the information environment of the 5Ge base station ecosystem. Based on the created mathematical model, a functional algorithm for the forced termination of an active terminal–segment information interaction session in the overloaded virtual network segment and the control mechanism of the distribution of the released system resources between other virtual network segments that takes into account the degree of their overload are formulated. The simulation and computational experiments showed that the implemented forced termination algorithm and system resource management mechanism allow the 5Ge base station to continue receiving incoming requests despite the overload of individual virtual network segments. It is empirically shown that the proposed services are effectively scaled concerning the value that is generally available for the distribution of the number of system resources and the allocation method within the guaranteed amounts of system resources for individual virtual network segments

Study of the Operation Process of the E-Commerce Oriented Ecosystem of 5Ge Base Station, Which Supports the Functioning of Independent Virtual Network Segments

According to specifications, flexible services for traffic management should be implemented within the 5G platform in order to improve its efficiency, which is and will remain an actual task. For the first time, the article presented here proposes a mathematical model for the operation process of an e-commerce-oriented ecosystem of a 5Ge base station, the information environment of which supports the operation of independent virtual network segments that provide terminal–segment information interaction services. In contrast to existing models, the presented model describes the studied process as a multi-pipeline queuing system, the inputs of which are coordinated with the flows of requests for communication with the relevant virtual network segments. The distribution of the total resources between the weighted virtual network segments in the simulated system is dynamically conducted by the appropriate software control mechanism. It considers the address intensities of new incoming requests and the maintenance of received incoming requests, but throughout the scale of the information environment of the 5Ge base station ecosystem. Based on the created mathematical model, a functional algorithm for the forced termination of an active terminal–segment information interaction session in the overloaded virtual network segment and the control mechanism of the distribution of the released system resources between other virtual network segments that takes into account the degree of their overload are formulated. The simulation and computational experiments showed that the implemented forced termination algorithm and system resource management mechanism allow the 5Ge base station to continue receiving incoming requests despite the overload of individual virtual network segments. It is empirically shown that the proposed services are effectively scaled concerning the value that is generally available for the distribution of the number of system resources and the allocation method within the guaranteed amounts of system resources for individual virtual network segments

Investigation of the Information Interaction of the Sensor Network End IoT Device and the Hub at the Transport Protocol Level

The study examines the process of information transfer between the sensor network end IoT device and the hub at the transport protocol level focused on using the 5G platform. The authors interpreted the researched process as a semi-Markov (focused on the dynamics of the size of the protocol sliding window) process with two nested Markov chains (the first characterizes the current size of the sliding window, and the second, the number of data blocks sent at the current value of this characteristic). As a result, a stationary distribution of the size of the sliding window was obtained both for the resulting semi-Markov process and for nested Markov chains, etc. A recursive approach to the calculation of the mentioned stationary distribution is formalized. This approach is characterized by linear computational complexity. Based on the obtained stationary distribution of the size of the sliding window, a distribution function is formulated that characterizes the bandwidth of the communication channel between the entities specified in the research object. Using the resulting mathematical apparatus, the Window Scale parameter of the TCP Westwood+ protocol was tuned. Testing has shown the superiority of the modified protocol over the basic versions of the BIC TCP, TCP Vegas, TCP NewReno, and TCP Veno protocols in conditions of data transfer between two points in the wireless sensor network environment

Modeling a session of subject-system interaction in a wireless communication infrastructure with a mixed resource

The article examines the subject-system interaction session, where the system is understood as a base station, and the subject is understood as a mobile communication device. The peculiarity of the study is taking into account the phenomenon relevant to modern communication infrastructures, which is that the base station supports the division of information traffic into a subspace of guaranteed personalized traffic and a subspace of general-purpose traffic. The study considers a highly critical empirical emergency when the general-purpose traffic subspace may cease to be available at any time. The presented mathematical apparatus describes the impact of such an emergency on the active communication sessions supported by the system in receiving new incoming requests of increasing intensity. To characterize this emergency situation, expressions adapted for practical application are presented to calculate such qualitative parameters as the probability of stability, the probability of failure, and unavailability

Decentralized Coordination of Temperature Control in Multiarea Premises

With local control of a large number of objects that mutually influence each other, the problem of coordinating local control systems to achieve the best overall result arises. If the structure of the system (the number of control objects and the parameters of interaction) can change frequently, then the process of setting up/training a centralized coordinator will take an unacceptably large part of the action time and require a significant amount of resources. In this work, the use of decentralized coordination is proposed to solve the problem. As a basic task for research on decentralized coordination control of objects that mutually influence each other, stabilizing the comfort temperatures was set in multizone rooms using movable heaters. Providing individual thermal comfort is an important problem. In particular, there are many multiarea premises with conflicting requirements for the comfort of habitats. This problem can be solved with the help of movable heaters and air conditioners. However, the presence of heat flows between areas with different specified parameters makes it difficult to adjust them. The work aims to improve the quality of thermal control in multiarea premises with a dynamic structure for the location of movable heaters. To achieve this goal, we proposed the concept of Movable Smart Heaters (MSH). A group of Movable Smart Heaters that could influence each other and exchange information forms a dynamic system with a changing structure since switching on/off or moving one MSH to another area changes the mutual influence and connections in the system. The criteria for control quality are defined and evaluated. The proposed coordination algorithms make it possible to optimize the operating modes of the system automatically when its structure and/or settings are changed. Simulation of the system is performed with the use of a worked-out modelling library in Scilab. The results of comparing the MSH system’s efficiency show an increase in comfort while reducing energy consumption

Information Technology for Maximizing Energy Consumption for Useful Information Traffic in a Dense Wi-Fi 6/6E Ecosystem

In Wi-Fi standards, a relatively narrow range of frequency spectrums is declared as working, on the operation of which additional restrictions are imposed in different countries. When creating dense wireless network ecosystems focused on massive information traffic, this circumstance causes significant interference even in the case of using Wi-Fi 6/6E-compatible equipment. An effective solution to this problem is the implementation of a centralized management mechanism for the relevant parameters of the target network ecosystem. The growing attention to ecology and rational use of electricity makes the problem of maximizing energy consumption for useful information traffic in a dense Wi-Fi 6/6E ecosystem an urgent task. Only the addressed information traffic between the transmitter and the target subscriber, which are subjects of the OFDMA technology and the MU-MIMO multiple access system (with an emphasis on the latter), is considered useful. To solve the problem, the authors formalized the Wi-Fi 6/6E ecosystem’s energy consumption model, which takes into account the specifics of OFDMA and MU-MIMO, the influence of the communication channel characteristics on the speed of target information transfer, and detailed energy consumption for maintaining the network infrastructure in a functional state. Based on the created model, the research problem is represented by the difference between two monotonic functions, relative to which the problem of optimization with restrictions is set. The process of solving this problem is presented in the form of information technology with a branch-and-bound hierarchy and a nested unconditional optimization problem. The results of simulated modelling in the MATLAB-NS3 environment showed a significant advantage of the authors’ approach. The energy power consumption by the Wi-Fi 6/6E ecosystem, the parameters of which were adjusted with the help of the authors’ information technology, decreased by more than four times

Entropy-metric estimation of the small data models with stochastic parameters

The formalization of dependencies between datasets, taking into account specific hypotheses about data properties, is a constantly relevant task, which is especially acute when it comes to small data. The aim of the study is to formalize the procedure for calculating optimal estimates of probability density functions of parameters of linear and nonlinear dynamic and static small data models, created taking into account specific hypotheses regarding the properties of the studied object. The research methodology includes probability theory and mathematical statistics, information theory, evaluation theory, and stochastic mathematical programming methods. The mathematical apparatus presented in the article is based on the principle of maximization of information entropy on sets determined as a result of a small number of censored measurements of “input'' and “output'' entities in the presence of noise. These data structures became the basis for the formalization of linear and nonlinear dynamic and static models of small data with stochastic parameters, which include both controlled and noise-oriented input and output measurement entities. For all variants of the above-mentioned small data models, the tasks of determining the optimal estimates of the probability density functions of the parameters were carried out. Formulated optimization problems are reduced to the forms canonical for the stochastic linear programming problem with probabilistic constraints

Parameterization of the Stochastic Model for Evaluating Variable Small Data in the Shannon Entropy Basis

The article analytically summarizes the idea of applying Shannon’s principle of entropy maximization to sets that represent the results of observations of the “input” and “output” entities of the stochastic model for evaluating variable small data. To formalize this idea, a sequential transition from the likelihood function to the likelihood functional and the Shannon entropy functional is analytically described. Shannon’s entropy characterizes the uncertainty caused not only by the probabilistic nature of the parameters of the stochastic data evaluation model but also by interferences that distort the results of the measurements of the values of these parameters. Accordingly, based on the Shannon entropy, it is possible to determine the best estimates of the values of these parameters for maximally uncertain (per entropy unit) distortions that cause measurement variability. This postulate is organically transferred to the statement that the estimates of the density of the probability distribution of the parameters of the stochastic model of small data obtained as a result of Shannon entropy maximization will also take into account the fact of the variability of the process of their measurements. In the article, this principle is developed into the information technology of the parametric and non-parametric evaluation on the basis of Shannon entropy of small data measured under the influence of interferences. The article analytically formalizes three key elements: -instances of the class of parameterized stochastic models for evaluating variable small data; -methods of estimating the probability density function of their parameters, represented by normalized or interval probabilities; -approaches to generating an ensemble of random vectors of initial parameters

Parameterization of the Stochastic Model for Evaluating Variable Small Data in the Shannon Entropy Basis

The article analytically summarizes the idea of applying Shannon’s principle of entropy maximization to sets that represent the results of observations of the “input” and “output” entities of the stochastic model for evaluating variable small data. To formalize this idea, a sequential transition from the likelihood function to the likelihood functional and the Shannon entropy functional is analytically described. Shannon’s entropy characterizes the uncertainty caused not only by the probabilistic nature of the parameters of the stochastic data evaluation model but also by interferences that distort the results of the measurements of the values of these parameters. Accordingly, based on the Shannon entropy, it is possible to determine the best estimates of the values of these parameters for maximally uncertain (per entropy unit) distortions that cause measurement variability. This postulate is organically transferred to the statement that the estimates of the density of the probability distribution of the parameters of the stochastic model of small data obtained as a result of Shannon entropy maximization will also take into account the fact of the variability of the process of their measurements. In the article, this principle is developed into the information technology of the parametric and non-parametric evaluation on the basis of Shannon entropy of small data measured under the influence of interferences. The article analytically formalizes three key elements: -instances of the class of parameterized stochastic models for evaluating variable small data; -methods of estimating the probability density function of their parameters, represented by normalized or interval probabilities; -approaches to generating an ensemble of random vectors of initial parameters