Advances in Systems Science and Applications

Copulas and Quantiles in Fork-Join Queueing Systems

2024-04-02T12:56:45+00:00

The article considers a classic fork-join queueing system with a Poisson input flow and exponential service times on homogeneous servers. When entering the system, tasks are divided into smaller components (subtasks), the number of which is equal to the number of subsystems. Then the subtasks are sent for service to the corresponding subsystems, consisting of a storage device of unlimited capacity and one server. The described functioning mechanism allows, using fork-join systems, to simulate processes occurring in many different real physical systems where tasks are parallelized. The article studies the dependence between the sojourn times of subtasks in subsystems, which is at the same time the main reason for the complexity of analyzing such systems. An approach is proposed for determining the quantiles of the response time distribution, while most works in the field of analysis of fork-join systems are concentrated on obtaining approximations only for the mathematical expectation of the response time. In addition, the approximation of the copula of sojourn times of subtasks (parts of one task) by the Gumbel copula and a new Kendall’s correlation coefficient estimation are obtained.

Methods of Estimation and Processing of Aerospace Information in Image Contouring Problem

2024-04-02T12:56:45+00:00

The article proposes approaches to the solution of the segmentation problem of real satellite images based on random Markov vector fields and new statistical textural characteristics for gray-level co-occurrence matrix. The authors introduce a novel image textural characteristic called statistical complexity that successfully distinguishes deterministic structures on naturally or artificially noised images. Software modules have been developed and satellite image examples are processed in order to determine the contours of the land structures and the presence of static and dynamic objects on the ocean surface. A comparison of two segmentation methods on real images has been made, which showed the prospects of their use in automatic image processing.

The Piecewise Levenberg–Marquardt Method

2024-04-02T12:56:45+00:00

We develop sharp local superlinear convergence results for the Levenberg–Marquardt method applied to constrained piecewise smooth equations, under the local Lipschitzian error bound condition for active selections, allowing for nonisolated solutions. We also characterize the level of inexactness allowed when solving subproblems, such that it does not interfere with superlinear convergence rate. Applications to constrained reformulations of complementarity systems, using the “min” complementarity function are also discussed.

A Cauchy Type Problem for Causal Functional Inclusions in Banach Spaces

2024-04-02T12:56:45+00:00

In this paper, we study a Cauchy type problem in Banach spaces for various classes of functional inclusions with causal multioperators. Based on the topological degree theory for condensing multimaps, we prove a global theorem on the existence of trajectories for systems governed by functional inclusions. As an application, we obtain generalizations of existence theorems for a Cauchy type problem for semilinear second order differential inclusions of this type and semilinear differential inclusions of the fractional order 1<q<2.

Optimizing Mechanical Strength in W-30Cu/xTiC Alloys via Solid-State Sintering: A Comprehensive Characterization

2024-04-02T12:56:45+00:00

The objective of this study is to investigate the influence of titanium carbide (TiC) on both the mechanical properties and microstructural characteristics of tungsten-copper (W-Cu) alloys. The manufacturing process adopted for this exploration employs solid-phase sintering, conducted at a temperature of 1,200°C under a uniaxial pressure of 30 MPa. This process is employed to synthesize W-30Cu/xTiC alloy powders, where 'x' denotes the weight percentages of 5, 10, and 15 for TiC. The alloys underwent a comprehensive analysis employing various analytical techniques to assess their mechanical and microstructural properties. These techniques include scanning electron microscopy (SEM), X-ray diffractometry (XRD), density evaluations, hardness tests, and flexural strength testing. Notably, the incorporation of titanium carbide (TiC) resulted in substantial improvements in both hardness and flexural strength, with the alloy containing 15% TiC exhibiting a microhardness value of 1420±5 HV0.1 and a flexural strength of 1745 N/mm². Additionally, the sintering process led to a significant increase in density, rising from 8.6g/cm³ to 13.8g/cm³. These findings underscore the positive impact of TiC and the sintering process on the alloy's mechanical and structural characteristics.

Combined Therapeutic Strategies for Cancer: Integrating Oncolytic Viruses and Inhibitors in a Mathematical Model

2024-04-02T12:56:46+00:00

The greatest cause of death worldwide continues to be cancer, a complicated set of diseases characterized by uncontrolled cell development. Although early identification and therapeutic approaches have improved, the incidence of the disease is still on the rise, demanding continued study into its underlying causes and cutting-edge treatment paradigms. For creative interventions and focused medicines, the variety of cancer kinds, which are influenced by genetics, way of life, and environmental variables, poses both difficulties and opportunities. In this paper, we present a mathematical model to treat cancer with combined therapies, oncolytic viruses and Mitogen-activated protein kinase inhibitors. We demonstrate that our model is both biologically and mathematically well-posed through the existence, the non-negativity and the boundedness of solutions. Furthermore, we study the equilibrium points as well as the stability of these equilibria. Finally, we use numerical simulations to illustrate the effect of this combined therapy on tumor cells.

Synchronization of Inbound and Outbound Flows at Stations in the Model of Freight Transportation Organization

2024-04-02T12:56:46+00:00

This article presents a model for organizing railway freight transportation between two node stations based on the interaction of neighboring stations depending on their technical capabilities and the demand for freight transportation. The main objective of such interaction is to synchronize the inbound and outbound flow at the stations, specifically reducing the degree of inconsistency between the receipt and dispatch of goods at the stations. This characteristic represents the imbalance between the volume of incoming and outgoing goods at the stations per unit of time and is described by a nonnegative function bounded above by unity. Its dynamics are described by a system of differential equations containing a set of parameters characterizing the infrastructure of the stations, the mode of distribution of goods from the final node station, and the demand for freight transportation. The range of parameter variations for which the specified system has a solution has been determined, as well as such a set of these parameters for which the task of synchronizing the inbound and outbound flow at the stations is best solved. It has been found that regardless of the initial value, starting from a certain point in time, the degree of inconsistency between the receipt and dispatch of goods at all stations except the initial node station becomes zero.

Game-Theoretic Models of Quality Management in Organizations under Corruption

2024-04-02T12:56:46+00:00

We consider game theoretic models of the quality management in an organizational system under corruption. A graph theoretic formalization of the process approach in quality management is proposed. In a static case, a problem of quality management in a two-level organizational system under corruption is formalized as an inverse Stackelberg game with an additional viability condition. It is solved by means of Germeier theorem. In a three-level model we analyze how the Principal can constraint corruption by penalties. The conditions under which the Principal rather supports corruption than constraints it are determined. In a dynamic case, a quality indicator is considered as a state variable which changes in a discrete time due to an equation of dynamics. A two-level model of the type "supervisor-agent" is studied first. It is assumed that a quality requirement is obligatory for the agent but he can weaken this requirement in exchange for a bribe to the supervisor. Then we build and analyze a three-level model by adding the Principal that can charge penalties to other players if a bribe is found. The game theoretic models are investigated numerically by means of simulation modeling.

Multistate System Performance Analysis Incorporating Human Error, Mathematical modeling and Reliability Approach

2024-04-02T12:56:46+00:00

This paper proposes a novel framework for analyzing the performance of a Sugar mill (Wahid Sugar Mill, situated in Punjab, India) with human errors, mathematical modeling, and reliability approach. The proposed framework considers the complex interactions between the different components of the Sugar mill and the potential impact of human error on the same. The performance of the considered system is affected by the different components failures and unplanned outages. Considering these facts, a mathematical model is developed for the sugar mill to calculate different reliability measures such as availability, reliability, and MTTF. The mathematical modeling aspect of the framework utilizes Markov chains to model the stochastic behavior of the sugar mill. The authors also perform sensitivity analysis to identify the impact of different components' failure on the performance of the same. The results of the paper demonstrate the potential of the proposed framework in providing valuable insights into the performance of the Sugar Mill under different scenarios, including the impact of human error.

Vision Based Classification of Nocturnal Road Traffic Using a Custom Deep Convolution Neural Network

2024-04-02T12:56:46+00:00

Intelligent Transport Systems (ITS) have emerged as an efficient solution for enhancing road utilization efficiency, ensuring convenient and safe transportation, and reducing energy consumption. This research focuses on addressing the challenge of accurately estimating road traffic congestion, specifically in low visibility and adverse weather conditions such as rainy, overcast, and sunny weather. To tackle this issue, we propose a novel custom macroscopic approach for categorizing road traffic congestion using videos captured during nighttime. The proposed method leverages the power of deep convolutional neural networks (DCNN) to classify traffic into three distinct categories. A custom deep CNN model is developed and trained on nighttime videos from the UCSD public dataset, using 100 epochs. Through a rigorous evaluation by means of this dataset, our model achieves an impressive Correct Classification Rate (CCR) of 98.91%, surpassing the previously known state-of-the-art CCR of 89.47%. This exceptional precision in estimating road traffic congestion in challenging low visibility conditions is achieved thanks to the integration of advanced deep learning techniques and CNNs. The proposed method can be integrated as part of a traffic monitoring system, thus contributing to the advancement of Intelligent Transport Systems and their potential to create cleaner, safer, and more efficient transportation networks.

A New Face Swap Detection Technique for Digital Images

2024-04-02T12:56:46+00:00

In recent years, the rapid development of deep learning-based face image manipulation algorithms and applications became one of the challenges that are facing information forensics and information security systems. Using these applications, one can easily swap the face in a digital image with another face for different intentions where most of them are malicious intentions. Different face swap detection techniques have been presented in recent years to check the authenticity of the face in a digital image. Most of the available techniques are machine-learning or deep-learning based which makes them vulnerable to false detection results in addition to the time-consuming training process. In this paper, a new technique for face swap detection (FSD) is presented based on the image watermarking process. The proposed technique consists of two main algorithms called embedding and authentication algorithms. Several experiments have been conducted to evaluate the performance of the proposed technique and to prove its efficiency in detecting fake faces. The proposed technique outperforms various deep-learning-based techniques because no training is required and the detection accuracy is 100 %. The performance of the proposed FSD technique is promising therefore it is applicable in different practical applications.

Exact Solutions of the Groundwater Filtration Equation via Dynamics

2024-04-02T12:56:46+00:00

The paper is devoted to the application of finite dimensional dynamics of evolutionary partial differential equations to the Boussinesq filtration equation. The Boussinesq equation is a second order nonlinear equation with three independent variables: time and two spatial coordinates. It describes a shape of the groundwater free surface as it flows through a porous medium under the influence of gravity. This paper proposes a method for constructing exact solutions of the equation, based on the method of finite dimensional dynamics. An example of the evolution of the free surface of groundwater is given.