Advances in Systems Science and Applications

Correlations of the Sojourn Times of Subtasks in Fork-Join Queueing Systems with M|M|1-type Subsystems

Anastasia V. Gorbunova, Alexey V. Lebedev — Mon, 15 Jul 2024 10:50:29 +0000

The article analyzes the relationship between the residence times of subtasks in the fork-join subsystems of the queuing system. When arriving the fork-join system, the task is divided into subtasks, each of which is serviced in its own subsystem, the task is considered serviced after the completion of all subtasks that originally comprised it servicing.
There is a dependence between the residence times of subtasks in subsystems, which affects the main performance indicators of the system, for example, the response times, which greatly complicates their analysis. The paper examines the characteristics of the existing dependence. In particular, with the help of generating functions and the Laplace-Stieltjes transformation, exact expressions for the Pearson and Spearman correlation coefficients are obtained.
In addition, using a combination of several methods, including the Nelder-Mead optimization method, the estimation of the Kendall correlation coefficient was obtained, and the model for the response time estimation based on the resulting correlation coefficients was described.
Despite the many works on the study of fork-join queuing systems, there are practically no articles devoted to the correlation analysis of the temporal metrics of the model. Therefore, this article can become one of the first in this area, laying the foundation for the study of the correlation dependence and its influence on the performance parameters of the model, not only for the classical case of M|M|1 subsystems, but also for more complex architectures of this system.

Piecewise Levenberg-Marquardt Method for Generalized Nash Equilibrium Problems

Alexey Izmailov, Evgeniy Uskov, Yan Zhibai — Mon, 15 Jul 2024 10:52:20 +0000

We consider the constrained piecewise Levenberg--Marquardt method globalized by linesearch, and apply it to ``min'' reformulations of the optimality systems for generalized Nash equilibrium problems. Numerical comparison of the performance of this method with some relevant existing alternatives is provided.

Economic Development of Countries and Health Technology Assessment (HTA) in Healthcare Decision Making

Dmitry Meshkov, Ludeña Moreira Genesis Marley, Elena Makeeva, Alexey Lobanov — Mon, 15 Jul 2024 10:54:16 +0000

The research indicated the relationship between the formal criteria of Health Technology Assessment (HTA) availability and the economic development of countries considering HTA to be an indicator for the effectiveness of the healthcare management process. HTA is at the very end of the evidence data generation. It makes possible forecasting medical, economic and social outcomes of healthcare management decisions and is the base for rational use of healthcare resources. Effective allocation of healthcare funds leads to an increase in human capital and economic development opportunities followed by the overall healthcare expenditures growth. The number of countries using HTA increases with the growth of per capita GDP, reaching a maximum in the countries with 40-50 thousand USD GDP per capita value range and decreases with further growth of this indicator. The low level of economic development, characterized by a low per capita GDP, makes it difficult to implement HTA due to strict regulations aimed at expenditures decrease and preventing using effectiveness criteria for health management assessment. Nevertheless, a significant number of low-income countries (below 10 thousand USD) per capita GDP are striving to improve the efficiency of health management and are at different stages of the HTA creation and implementation into healthcare systems. The opposite countries with high (above 50 thousand USD) per capita GDP are mostly tax haven countries (offshore zones) and as a rule these indicators are not linked with the real economic and industrial development. These countries do not use HTA for expert support of healthcare management decisions. Regional international cooperation increases the possibility of creating and using HTA in both low and high per capita GDP countries.

Stability Analysis of Switched Positive Persidskii Systems with Distributed and Unbounded Delays

Alexander Aleksandrov, Natalya Andriyanova — Mon, 15 Jul 2024 10:56:02 +0000

Switched positive Persidskii systems with distributed and unbounded delays are studied. Right-hand sides of these systems are linear combinations of nonlinearities of a sector type. Special constructions of diagonal Lyapunov--Krasovskii functionals are proposed and conditions are derived under which the absolute stability of the considered systems can be proved with the aid of such functionals. The developed approaches are applied to the stability analysis of a mechanical system with switched nonlinear positional forces and to a problem of mobile agent deployment. Results of numerical simulations are presented confirming the theoretical conclusions.

The Mean-Field Approximation for the SCARDO Model in the Case of 3-element Opinion Space: Fixed Points and Exact Solutions

Vladislav N. Gezha, Ivan V. Kozitsin — Mon, 15 Jul 2024 10:57:40 +0000

We analyze the SCARDO model in the case of the 3-element opinion space under specific constraints on the transition table parameters that allows to link the problem at stake to the case of the 2-element opinion space that has been thoroughly studied previously. We characterize the properties of fixed points and support our findings by numerical experiments. Further, we manage to find out those settings that ensure the system almost surely reaches a specific domain in the phase space, after which its behavior can be predicted analytically.

Exploring the Relationship between Cardiac Disease and Patterns of 12-Lead ECG through Neural Network: A Comprehensive Review

Mon, 15 Jul 2024 10:59:17 +0000

Heart disease is a significant public health concern, affecting a large number of people worldwide daily. With a shortage of qualified cardiologists, particularly in low-income countries, the diagnosis and management of heart disease can be challenging. The electrocardiogram (ECG) is the primary diagnostic tool for heart disease, but interpreting ECG reports requires the expertise of a qualified cardiologist, making it time-consuming and costly. To address this issue, automated ECG signal interpretation is necessary. Hence, this article has made an encyclopedic review of the existing literature. The article includes demonstration of frequently utilized data sets and tools and techniques for this domain. Therefore, a framework is proposed based on the observation of existing works. The proposed framework aims to improve the analysis of ECG reports for both cardiologists and non-experts. Our framework considers the 12-lead ECG, the different types of leads, wave patterns, and their relationship with heart disease. The objective is to produce reliable and accurate results while reducing analysis time. The proposed framework is inherent to improve the diagnosis and management of heart disease by enabling a wider range of healthcare providers and individuals to interpret ECG reports. This could lead to earlier detection and treatment of heart disease, which could improve outcomes and save lives.

Practical Applicability of the Metric Approach for a Scheduling Problem

Alexander Lazarev, Darya Lemtyuzhnikova, Ilja Kudinov — Mon, 15 Jul 2024 11:01:56 +0000

A given special case of NP-complete scheduling problem can be approximated by solving a special case of similar problem with the same precedence graph. We construct a metric space over a set of special cases of this problem and consider the statistical relationship between distance between a pair of special cases of the under consideration and the average error of the approximated solution. Sethi, Gabow, Coffman's and Fujii's algorithms for this problem are used. It is shown that the absolute and the relative error of the objective function decreases over the density of a graph with a fixed number of jobs. In general case, relative non-zero error value increases with the number of jobs.

Savage's Solution to the Problem of Three-Currency Deposit Diversification: Program Tools and Modeling Results

Vitaly Molostvov — Mon, 15 Jul 2024 11:05:34 +0000

This paper presents the development of computing tools for finding optimal structures of multi-currency deposits in terms of guaranteed risk under uncertain exchange rates. The approach utilizes Savage's minimax regret concept to calculate risk and guaranteed risk functions explicitly, assuming only the limits of possible changes in uncertain parameters are known. The Excel environment implements the algorithm for calculating the optimal solution that minimizes income loss due to incomplete information. Computational experiments analyzed the dependence of the optimal guaranteed risk on problem parameters, such as interest rates of currencies and boundaries of uncertain factors. The results can be used to analyze financial management problems in conditions of incomplete information.

Adjusting the Parameters of a PID Controller with an Asymmetric Fuzzy Algorithm for an Automotive Suspension System

Tuan Anh Nguyen — Mon, 15 Jul 2024 11:08:30 +0000

A suspension system plays a crucial role in ensuring the smoothness of a car when traveling on roads. This paper proposes using the active suspension system equipped with a hydraulic actuator to replace a conventional passive suspension. Unlike previous publications, this study uses a Hybrid PID algorithm, combining a conventional PID controller and a fuzzy solution with two distinct inputs. The coefficients of the PID controller are flexibly adjusted by the fuzzy algorithm. Therefore, it can more respond to complex motion conditions. Calculations are performed with the MATLAB-Simulink software for four specific cases. According to the research findings, the maximum and RMS values of vehicle body acceleration and displacement significantly decrease when applying the hybrid algorithm to the active suspension system. In the last case, these values are only 16.69% and 36.90% when comparing Fuzzy PID and Passive situations. In general, the smoothness of the sprung mass can be guaranteed in all survey cases.

Text Classification Technologies in Document Categorization Systems. A Survey

Alla Kravets, Dmitry Semenochkin — Mon, 15 Jul 2024 11:10:20 +0000

This paper presents a literature review from 2013 to 2022 on technologies and datasets used in the field of text classification. The review covered 110 sources from 5 scientific databases, the main criterion for inclusion was the presence of an experimental part involving a classifier or other technologies related to the classification process. The study reviewed the classification process and highlighted three main stages of text classification: data preparation, classifier training, and evaluation of results. Using Kitchenham's Systematic Literature Review methodology, scholarly articles dealing with text classification problems were collected and analyzed. A sample of 243 articles was obtained, and after screening, a resulting sample of 110 articles was obtained. Guided by the two research questions posed, this sample was analyzed and the results of the analysis were presented in graphical format. For each of the identified stages of classification, the frequency of use of the main technologies used in a particular stage was analyzed. Each technology was reviewed within its respective source. In addition, considerable attention was given to analyzing the different datasets used for text classification, with a particular focus on the less frequently used ones. An analysis of the frequency of use of datasets concluded that researchers often use proven and popular datasets to demonstrate the effectiveness of their method. Datasets are less frequently used to solve localized text classification problems. One notable trend identified in the analysis is the increasing prevalence of deep learning technologies in text classification. These technologies, including neural networks, recurrent neural networks (RNNs), convolutional neural networks (CNNs), transformers, and attention mechanisms, have gained considerable popularity among researchers. This study provides valuable insights into the evolution of text classification by shedding light on a variety of technologies, approaches, and datasets used by researchers. As text classification continues to evolve and diversify, this review can be a valuable resource for scholars and practitioners in the field, providing.

Data Storage with Increased Survivability and Reliability Based on the Residue Number System

Nikolay Kucherov — Mon, 15 Jul 2024 11:11:56 +0000

The paper considers the principles of building reliable data storage and processing systems in cloud-fog environment. The factors affecting the reliability and survivability of systems are an-alyzed and the main types of failures are given. The principles of introducing information re-dundancy to improve reliability, as well as corrective capabilities and error detection algorithms of RNS codes are considered. A scheme of data processing and storage in fog with increased re-liability is proposed. Monte Carlo modeling is carried out, and the results and conclusions are given, the probability distribution of failure occurrence is constructed, showing that failure probabilities obey the gamma probability distribution.

Lyapunov Functions for Periodic Selector-Linear Difference Inclusions

Mikhail Morozov — Mon, 15 Jul 2024 11:13:33 +0000

The paper considers periodic selector-linear difference inclusions. A class of time-periodic quasi-quadratic Lyapunov functions is distinguished, as well as parametric classes of piecewise-quadratic and piecewise-linear Lyapunov functions. These functions establish necessary and sufficient conditions for asymptotic stability. An example leading to periodic selector-linear differential and difference inclusions is given. The results can find applications in the stability analysis of control systems with periodic parameters, in particular, servomechanisms whose elements operate on alternating current, control systems with amplitude-frequency modulation.

A Generalized Bi-Objective Scheduling Algorithm for Batch-of-Tasks on Heterogeneous Computing System

Mikhail G. Babenko — Mon, 15 Jul 2024 11:15:07 +0000

The high energy consumption of data centers and its contribution towards greenhouse gases demand energy-efficient management of resources. Energy consumption of computing resources encourages the development of bi-objective scheduling algorithms optimizing the makespan of jobs and energy consumption of computing resources. In general, the problem of job scheduling and bi-objective optimization falls in the NP-complete combinatorial optimization problem category. To address the bi-objective scheduling problem, a generalized bi-objective scheduling algorithm (Z*) for Batch-of-Tasks (BoT) applications on the Heterogeneous Computing System (HCS) has been proposed. The BoT represents the set of independent tasks from multiple applications, and the HCS represents the computational environment consisting of processors with different frequencies. To schedule tasks, the Z* algorithm takes decisions using the optimization function of energy consumption and completion time of tasks based on the given weights. The weight could be fractional or integer, so the Z* algorithm represents a set of different algorithms. The proposed algorithm is beneficial for cloud data centers/service-oriented computing to execute customer jobs based on the demand, whether the customer needs high throughput or low cost of execution.

Solving the Energy Consumption Barrier in Brackish Water Reverse Osmosis Desalination Plants: A Genetic Algorithm and Energy Recovery Approach

Mohammed Moumni, Massour El Aoud Mohamed, Moumni Fatima Zahra — Mon, 15 Jul 2024 11:16:37 +0000

Reverse osmosis desalination is an effective technology for supplying potable water to regions facing water stress. However, this process consumes a significant amount of energy, limiting its widespread adoption globally. This study aims to analyze the variations in specific energy consumption (SEC) in the reverse osmosis desalination process for brackish water at a plant in Morocco, considering the feed water parameters. Additionally, the study examines energy consumption with and without the implementation of energy recovery devices at this plant, which produces 10 million cubic meters of water annually.
A genetic algorithm is utilized to identify the optimal combination of design and operational parameters to achieve the lowest SEC. The findings indicate that incorporating energy recovery devices in the future design of the plant could reduce the SEC by up to 30%.

The Effect of Space Flight Factors on the Correction Disorders of the Vaginal and Cervical Microflora in Ground-Based Models

Mon, 15 Jul 2024 11:18:08 +0000

This work shows results of a comprehensive study of the vaginal and cervical microflora of women participating in a ground-based model experiment simulating some factors of space flight. Experiments with dry immersion allow to simulate such factors of a space flight as physical inactivity and microgravity, as well as the redistribution of liquid media associated with them. 16 volunteers, participated in 5-days dry immersion experiment, used an oral prebiotic drug based on lactoferrin and intravaginal probiotic capsules based on Lactobacillus acidophilus. It was found that the oral use of lactoferrin has a delayed positive effect on the state of the microflora of the vagina and cervical canal of volunteers. This effect is especially pronounced on the 35th day after the end of the immersion. While the use of probiotic capsules has a faster effect, noticeable after 5 days of use during immersion. The combination of lactoferrin and probiotic capsules did not give noticeable effect, which can be explained both by a small group of volunteers or lack of a synergistic effect of these drugs. One of the means that can give high efficiency in the prevention of the dysbiosis of the vaginal microflora are intravaginal capsules made of autostrains isolated individually from each volunteer and addition of lactoferrin into the capsules, the effectiveness of which when using locally was also proven in previously conducted studies in gynecological patients.