Development of Algorithm for Calculating Data Packet Transmission Delay in Software-Defined Networks

The relevance of this type of network is associated with the development and improvement of protocols, methods, and tools to verify routing policies and algorithmic models describing various aspects of SDN, which determined the purpose of this study. The main purpose of this work is to develop specialized methods to estimate the maximum end-to-end delay during packet transmission using SDN infrastructure. The methods of network calculus theory are used to build a model for estimating the maximum transmission delay of a data packet. The basis for this theory is obtaining deterministic evaluations by analyzing the best and worst-case scenarios for individual parts of the network and then optimally combining the best ones. It was found that the developed method of theoretical evaluation demonstrates high accuracy. Consequently, it is shown that the developed algorithm can estimate SND performance. It is possible to conclude the configuration optimality of elements in the network by comparing the different possible configurations. Furthermore, the proposed algorithm for calculating the upper estimate for packet transmission delay can reduce network maintenance costs by detecting inconsistencies between network equipment settings and requirements. The scientific novelty of these results is that it became possible to calculate the achievable upper data delay in polynomial time even in the case of arbitrary tree topologies, but not only when the network handlers are located in tandem. Doi: 10.28991/ESJ-2022-06-05-010 Full Text: PD

Trainable Regularization in Dense Image Matching Problems

This study examines the development of specialized models designed to solve image-matching problems. The purpose of this research is to develop a technique based on energy tensor aggregation for dense image matching. This task is relevant within the framework of computer systems since image comparison makes it possible to solve current problems such as reconstructing a three-dimensional model of an object, creating a panorama scene, ensuring object recognition, etc. This paper examines in detail the key features of the image matching process based on the use of binocular stereo reconstruction and the features of calculating energies during this process, and establishes the main parts of the proposed method in the form of diagrams and formulas. This research develops a machine learning model that provides solutions to image matching problems for real data using parallel programming tools. A detailed description of the architecture of the convolutional recurrent neural network that underlies this method is given. Appropriate computational experiments were conducted to compare the results obtained with the methods proposed in the scientific literature. The method discussed in this article is characterized by better efficiency, both in terms of the speed of work execution and the number of possible errors. Doi: 10.28991/HIJ-2023-04-03-011 Full Text: PD

Tezosentan reduces the microvascular filtration coefficient in isolated lungs from rats subjected to cecum ligation and puncture

INTRODUCTION: We recently demonstrated that the non-selective endothelin-1 (ET-1) receptor blocker tezosentan antagonizes ovine acute lung injury (ALI) following infusion of endotoxin or ET-1 by reducing the enhanced lung microvascular pressure, although we could not exclude the possibility of a simultaneous decline in microvascular permeability. In the present study, our aim was to find out if tezosentan reverses the rise in microvascular filtration coefficient (Kfc) in rat lungs that have been isolated and perfused 12 h after cecum ligation and puncture (CLP) or infusion of ET-1. METHODS: Wistar rats (n = 42) were subjected to CLP. Postoperatively, rats were randomized to a CLP group (n = 7) and a CLP + tezosentan group (n = 7); the latter received tezosentan 30 mg/kg. A sham-operated group (n = 5) underwent laparotomy without CLP. Twelve hours postoperatively, the lungs were isolated and perfused with blood from similarly treated rats that also were used to assess plasma concentration of ET-1 and protein kinase Cα (PKCα) in lung tissue. Additionally, isolated blood perfused lungs from healthy rats were randomized to a control group (n = 8), an ET-1 group (n = 7) subjected to pulmonary arterial injection of ET-1 10 nM, and an ET-1 + tezosentan group (n = 7) that received tezosentan 30 mg/kg. All lung preparations received papaverine 0.1 μg/kg added to the perfusate for vasoplegia. Pulmonary hemodynamic variables, Kfc and lung compliance (C(L)) were assessed. RESULTS: After CLP, the plasma concentration of ET-1 increased. Papaverine abolished the vasoconstrictor response to ET-1 and the pulmonary vascular pressures remained close to baseline throughout the experiments. Both CLP and injection of ET-1 caused significant changes in Kfc and C(L )that were prevented in tezosentan-treated rats. Compared to sham-operated animals, CLP increased the content of PKCα by 50% and 70% in the cytosolic and the membrane fractions of lung tissue homogenates, respectively. Tezosentan prevented the upregulation of PKCα in the membrane fraction. CONCLUSION: In rat lungs isolated and perfused after CLP, tezosentan precludes both the increase in Kfc and the upregulation of PKCα in the membrane fraction of lung tissue

Development of an Algorithm for Multicriteria Optimization of Deep Learning Neural Networks

Nowadays, machine learning methods are actively used to process big data. A promising direction is neural networks, in which structure optimization occurs on the principles of self-configuration. Genetic algorithms are applied to solve this nontrivial problem. Most multicriteria evolutionary algorithms use a procedure known as non-dominant sorting to rank decisions. However, the efficiency of procedures for adding points and updating rank values in non-dominated sorting (incremental non-dominated sorting) remains low. In this regard, this research improves the performance of these algorithms, including the condition of an asynchronous calculation of the fitness of individuals. The relevance of the research is determined by the fact that although many scholars and specialists have studied the self-tuning of neural networks, they have not yet proposed a comprehensive solution to this problem. In particular, algorithms for efficient non-dominated sorting under conditions of incremental and asynchronous updates when using evolutionary methods of multicriteria optimization have not been fully developed to date. To achieve this goal, a hybrid co-evolutionary algorithm was developed that significantly outperforms all algorithms included in it, including error-back propagation and genetic algorithms that operate separately. The novelty of the obtained results lies in the fact that the developed algorithms have minimal asymptotic complexity. The practical value of the developed algorithms is associated with the fact that they make it possible to solve applied problems of increased complexity in a practically acceptable time. Doi: 10.28991/HIJ-2023-04-01-011 Full Text: PD

Development and Algorithmization of a Method for Analyzing the Degree of Uniqueness of Personal Medical Data

The purpose of this investigation is to develop a method for quantitative assessment of the uniqueness of personal medical data (PMD) to improve their protection in medical information systems (MIS). The relevance of the goal is due to the fact that impersonal PMD can form unique combinations that are potentially of interest to intruders and threaten to reveal the patient's identity and medical confidentiality. Existing approaches were analyzed, and a new method for quantifying the degree of uniqueness of PMD was proposed. A weakness in existing approaches is the assumption that an attacker will use exact matching to identify people. The novelty of the method proposed in this paper lies in the fact that it is not limited to this hypothesis, although it has its limitations: it is not applicable to small samples. The developed method for determining the PMD uniqueness coefficient is based on the assumption of a multidimensional distribution of features, characterized by a covariance matrix, and a normal distribution, which provides the most reliable reflection of the existing relationships between features when analyzing large data samples. The results obtained in computational experiments show that efficiency is no worse than that of focus groups of specialized experts. Doi: 10.28991/HIJ-2023-04-01-09 Full Text: PD

Extravascular lung water assessed by transpulmonary single thermodilution and postmortem gravimetry in sheep

INTRODUCTION: Acute lung injury is associated with accumulation of extravascular lung water (EVLW). The aim of the present study was to compare two methods for quantification of EVLW: transpulmonary single thermodilution (EVLW(ST)) and postmortem gravimetric (EVLW(G)). METHODS: Eighteen instrumented and awake sheep were randomly assigned to one of three groups. All groups received Ringer's lactate (5 ml/kg per hour intravenously). To induce lung injury of different severities, sheep received Escherichia coli lipopolysaccharide 15 ng/kg per min intravenously for 6 hours (n = 7) or oleic acid 0.06 ml/kg intravenously over 30 min (n = 7). A third group (n = 4) was subjected to sham operation. Haemodynamic variables, including EVLW(ST), were measured using a PiCCOplus monitor (Pulsion Medical Systems, Munich, Germany), and the last measurement of EVLW(ST )was compared with EVLW(G). RESULTS: At the end of experiment, values for EVLW(ST )(mean ± standard error) were 8.9 ± 0.6, 11.8 ± 1.0 and 18.2 ± 0.9 ml/kg in the sham-operated, lipopolysaccharide and oleic acid groups, respectively (P < 0.05). The corresponding values for EVLWI(G )were 6.2 ± 0.3, 7.1 ± 0.6 and 11.8 ± 0.7 ml/kg (P < 0.05). Ranges of EVLWI(ST )and EVLWI(G )values were 7.5–21.0 and 4.9–14.5 ml/kg. Regression analysis between in vivo EVLW(ST )and postmortem EVLW(G )yielded the following relation: EVLW(ST )= 1.30 × EVLW(G )+ 2.32 (n = 18, r = 0.85, P < 0.0001). The mean bias ± 2 standard deviations between EVLW(ST )and EVLW(G )was 4.9 ± 5.1 ml/kg (P < 0.001). CONCLUSION: In sheep, EVLW determined using transpulmonary single thermodilution correlates closely with gravimetric measurements over a wide range of changes. However, transpulmonary single thermodilution overestimates EVLW as compared with postmortem gravimetry

Recombinant human activated protein C ameliorates oleic acid-induced lung injury in awake sheep

Introduction: Acute lung injury (ALI) may arise both after sepsis and non-septic inflammatory conditions and is often associated with the release of fatty acids, including oleic acid (OA). Infusion of OA has been used extensively to mimic ALI. Recent research has revealed that intravenously administered recombinant human activated protein C (rhAPC) is able to counteract ALI. Our aim was to find out whether rhAPC dampens OA-induced ALI in sheep. Methods: Twenty-two yearling sheep underwent instrumentation. After 2 days of recovery, animals were randomly assigned to one of three groups: (a) an OA+rhAPC group (n = 8) receiving OA 0.06 mL/kg infused over the course of 30 minutes in parallel with an intravenous infusion of rhAPC 24 mg/kg per hour over the course of 2 hours, (b) an OA group (n = 8) receiving OA as above, or (c) a sham-operated group (n = 6). After 2 hours, sheep were sacrificed. Hemodynamics was assessed by catheters in the pulmonary artery and the aorta, and extravascular lung water index (EVLWI) was determined with the single transpulmonary thermodilution technique. Gas exchange was evaluated at baseline and at cessation of the experiment. Data were analyzed by analysis of variance; a P value of less than 0.05 was regarded as statistically significant. Results: OA induced profound hypoxemia, increased right atrial and pulmonary artery pressures and EVLWI markedly, and decreased cardiac index. rhAPC counteracted the OA-induced changes in EVLWI and arterial oxygenation and reduced the OA-induced increments in right atrial and pulmonary artery pressures. Conclusions: In ovine OA-induced lung injury, rhAPC dampens the increase in pulmonary artery pressure and counteracts the development of lung edema and the derangement of arterial oxygenation

Tezosentan-induced attenuation of lung injury in endotoxemic sheep is associated with reduced activation of protein kinase C

INTRODUCTION: Studies in vitro reveal that endothelin-1 (ET-1) activates the α isoform of protein kinase C (PKC-α) in cultures of endothelial cells, thereby deranging cellular integrity. Sepsis and endotoxemia are associated with increased plasma concentrations of ET-1 that induce acute lung injury (ALI). We recently reported that non-selective ET-1 receptor blockade attenuates ALI in sheep by reducing the endotoxin-induced increase in extravascular lung water index (EVLWI). The aim of this study was to find out whether this attenuation is associated with reduced translocation of PKC-α from the cytosolic to the membrane fraction of lung tissue homogenate. METHODS: Seventeen awake, instrumented sheep were randomly assigned to a sham-operated group (n = 3), a lipopolysaccharide (LPS) group (n = 7) receiving an intravenous infusion of Escherichia coli 15 ng/kg per min for 24 hours, and a tezosentan group (n = 7) subjected to LPS and, from 4 hours, an intravenous injection of tezosentan 3 mg/kg followed by infusion at 1 mg/kg per hour for the reminder of the experiment. Pulmonary micro-occlusion pressure (Pmo), EVLWI, plasma concentrations of ET-1, tumor necrosis factor-a (TNF-a), and interleukin-8 (IL-8) were determined every 4 hours. Western blotting was used to assess PKC-α. RESULTS: In non-treated sheep a positive correlation was found between the plasma concentration of ET-1 and Pmo in the late phase of endotoxemia (12 to 24 hours). A positive correlation was also noticed between Pmo and EVLWI in the LPS and the LPS plus tezosentan groups, although the latter was significantly reduced in comparison with LPS alone. In both endotoxemic groups, plasma concentrations of ET-1, TNF-α, and IL-8 increased. In the LPS group, the cytosolic fraction of PKC-α decreased by 75% whereas the membrane fraction increased by 40% in comparison with the sham-operated animals. Tezosentan completely prevented the changes in PKC-α in both the cytosolic and the membrane fractions, concomitantly causing a further increase in the plasma concentrations of ET-1, TNF-α, and IL-8. CONCLUSION: In endotoxemic sheep, ET-1 receptor blockade alleviates lung injury as assessed by a decrease in EVLWI paralleled by a reduction in Pmo and the prevention of activation of PKC-α