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The article completes the study of solutions to the problem of creating distributed QoS monitoring control in IoT and IIoT telecommunications. A multi-agent architecture is used. For the proposed structure of the LSTM network, approaches to the process of its training (configuring the network configuration) are considered, based on the representation of this process in the form of a Markov decision-making process, which made it possible to solve the problem of determining the training times of the network within one epoch, as well as its retraining using a variant of the dynamic programming method -- the iteration algorithm by values, which In the future, it allows you to proceed to the synthesis of an iterative algorithm for dynamically configuring the parameters of the developed LSTM network. [ABSTRACT FROM AUTHOR]

The article continues to review the approach to designing the architecture of a distributed information monitoring system and quality management of communication services provided by the infrastructures of the Internet of Things and the industrial Internet of Things, based on solutions that support machine-to-machine and human-machine interaction. The development of a neural network model of an intelligent monitoring agent based on a recurrent neural network with a long chain of short-term memory elements is proposed. The matrix structure of the LSTM network memory cell is proposed, which takes into account the spatio-temporal correlation of load parameters associated with the time lag of its propagation and is a matrix of connectivity of LSTM network hyperparameters and accumulated values of load parameters of monitoring nodes in the vicinity of a controlled monitoring node, taking into account the characteristics of the time series of propagation of load in stationarity moments.. [ABSTRACT FROM AUTHOR]

The article considers an approach to designing the architecture of a distributed information monitoring and quality management system for communication services provided by the Internet of Things and Industrial Internet of Things infrastructures based on solutions supporting machine-tomachine and human-machine interaction. The choice of a neural network with long Short-Term memory (LSTM) is justified as a theoretical basis for modeling the active node of an information monitoring system. The developed structure of the LSTM network is presented, taking into account the spatial and temporal correlation of the obtained indicators at various observation points of the distributed information monitoring system. The criteria for evaluating the effectiveness of the proposed model for the conditions of information monitoring of non-stationary load in a mode close to real time are substantiated. [ABSTRACT FROM AUTHOR]

Recently discovered specific markers open up new possibilities for the diagnosis of acute kidney injury (AKI) in burn disease in order to optimize the treatment of such patients. Early diagnosis with the involvement of biomarkers prevents the sudden death of burn patients and allows predicting the course of the pathological condition. There are several characteristics that an “ideal” AKI biomarker should conform to: being non-invasive, locally specific, highly sensitive, being a stable molecule at different temperatures and pH values, having the ability to rapidly increase in response to kidney injury (quantify it), remaining at high levels during the episode and decreasing during the recovery period. There is a difference between the biomarkers that can be freely filtered in the glomerulus, so any increase in their plasma concentration (due to damage to other renal tissues) can lead to a high concentration of indicators in the urine (loss of specificity), and high-molecular-weight markers that are not freely filtered and therefore are more specific when measured in urine. Renal function in burn patients is usually determined by blood and urine tests, as biopsy can cause iatrogenic damage and is not commonly used in this cohort. After the onset of AKI, the level of biomarkers remains elevated for a certain period. None of the described indicators is monospecific for AKI; this makes estimating the time of AKI quite difficult. It has been proven that the combination of three biomarkers at two different time points in adults and the combination of two indicators at two time intervals in children allows to increase the reliability of determining AKI up to 0.78. [ABSTRACT FROM AUTHOR]

The article devoted to the approaches to algorithmization of the information management system of a distributed service enterprise. The study of the dependence of the optimal capacity of the service system center on the service area was carried out. The mechanism of optimization of the service area, taking into account organizational and economic constraints, as well as optimization of the service area for mobile sources of applications, is investigated. Processing customer requests must meet the requirements of efficiency, reliability, and efficiency of the corporate information network. In the presence of a single office of a service company, it is not always possible to find an optimal or close to optimal query processing algorithm in terms of performance. The problem of the optimal service area without taking into account restrictions in order to maximize the profit of the enterprise is considered. Models of the functioning of the decision-making subsystem for servicing requests by a service enterprise have been developed, differing in taking into account the service area and the spatial stationarity of customers. [ABSTRACT FROM AUTHOR]

Acute kidney injury (AKI) is a common complication in critically ill burn patients and is associated with serious adverse outcomes, including increased length of hospital stay, development of chronic kidney disease, and increased risk of mortality. The incidence of AKI among burn patients in the intensive care units is 38 (30–46) %. A high percentage of the total burn surface area and a number of individual predisposing factors are considered to be the leading risk factors for AKI. Pathophysiological and morphological changes in the body under the combination of burn disease and kidney damage have certain discrepancies with the classical course of the pathological process in some nosological forms. Despite significant progress in the technologies of fluid resuscitation, intensive care and renal replacement therapy in recent years, the morbidity and mortality rate in such patients remain quite significant. A better understanding of clinical characteristics, early detection and prevention of risk factors for kidney damage in burns, as well as timely medical intervention can effectively reduce morbidity and progression of the pathological process, and also optimize the prognosis in the long run. [ABSTRACT FROM AUTHOR]

The article extends the authors' previous research to the case of discrete response functions. A process consisting of sequential operations is considered. For each operation, you can determine the currently available probability of its error-free (high-quality) execution. By the qualitative performance of the operation, we will understand the achievement of a given level of quality in quantitative proportion to the overall level. The purpose of the article is to build a quality management strategy in which a set of probabilities of quality levels not less than a certain threshold value is achieved, with minimal costs for carrying out appropriate measures. The corresponding optimization problem is presented and a heuristic multistep algorithm for its solution is given. [ABSTRACT FROM AUTHOR]

Over the past 30 years, climate change has taken one of the leading places among the ten main causes of death due to natural disasters. Rising temperatures have been shown to increase emergency department admissions for a wide range of kidney diseases, including acute kidney injury (AKI), chronic kidney disease, kidney stones, and urinary tract infections. The occupational effect of heat stress is also associated with AKI, which can quickly progress to acute kidney failure with high mortality. The basis of the pathogenetic mechanisms of heat-induced AKI is a decrease in the circulating blood volume and electrolyte disturbances due to increased perspiration. Water evaporation from the surface of the skin contributes to dehydration with an increase in serum osmolarity. In response to this, vasopressin is activated, the specific gravity of urine increases, and the amount of urine decreases. The glomerular filtration rate progressively decreases. Hypokalemia develops, which changes to hyperkalemia within 12 hours. Tubular endothelium is damaged, which leads to microthrombosis of afferent and efferent renal arteries, the development of an inflammatory response, and exhaustion of the renal interstitium. Possible rhabdomyolysis and myoglobinemia with subsequent tubular obstruction worsen existing kidney damage. According to the leading mechanism of damage, there are two types of acute heat damage to the kidneys: classical rhabdomyolysis and acute interstitial nephritis. Although modern medical advances have contributed to the development of effective treatment and management strategies (rapid cooling, extracorporeal detoxification methods, etc.), mortality in kidney damage due to general overheating has decreased slightly over the past decades. For health care and industry researchers, it is necessary to identify the harmful occupational conditions that lead to heat stress nephropathy and to develop certain occupational safety strategies. [ABSTRACT FROM AUTHOR]

Purpose. The purpose of this article is to develop a preprocessing method for digital multispectral remote sensing images obtained through optical and infrared means in the electromagnetic spectrum. The method aims to ensure invariance with respect to positional formation conditions that determine spatial and radiometric resolution. By implementing homomorphic filtering in this method, we can significantly increase the informative value of processed imagery. Methodology. The problem solving, including the development of the spatial and radiometric resolution increase ways for multispectral geospatial data are based on the methods of brightness spatial distribution fusion, methods of data dimension reduction, de-correlation techniques and geometric correction of image spatial distributions. Findings. The method of preprocessing digital remote sensing data has been developed, which is a component of the methodology for identifying geometric shapes (GS) of objects in multi-channel aerospace images, allowing for a significant improvement in their recognition efficiency when noise is present. Originality. The method of preprocessing photogrammetric scenes using homomorphic filtering to enhance their informational significance is proposed. The method ensures invariance to positional conditions of fixation, improves the accuracy of further recognition, eliminates the drawbacks of known methods associated with the existence of parametric uncertainty dependence, the features of fixation of species information, low values of information indices of synthesized images, and computational process peculiarities. Practical value. Practical value is consists in improving of identification accuracy of objects GS in digital geospatial data, in significant increasing of raster multispectral images information value and in rising of automated image processing efficiency. The use of the method can greatly enhance the value and usefulness of multispectral photogrammetric images in a wide range of applications, from environmental monitoring to urban planning. [ABSTRACT FROM AUTHOR]

A process consisting of sequential operations is considered. For each operation, you can determine the currently available probability of its error-free (high-quality) execution. By the qualitative performance of the operation, we will understand the achievement of a given level of quality in quantitative proportion to the overall level. The purpose of the article is to build a quality management strategy in which a set of probabilities of quality levels not less than a certain threshold value is achieved, with minimal costs for carrying out appropriate measures. The article presents the decomposition of operations into activities; classification of activities into activities with conditionally linear or asymptotic response; quality assessment in a multi-level control system with response functions of various types; optimization problems and their algorithmic solutions. [ABSTRACT FROM AUTHOR]