Advances in Complex Systems

Modern agriculture is increasingly embracing cloud manufacturing and service-oriented models, creating demand for traceability technologies that are non-invasive, shareable, and accessible on demand. Accurate identification of each agricultural product at the individual level is a key link in traceability, ensuring reliable and continuous information throughout the entire supply chain. Convention…

Low-light images typically suffer from reduced visibility, blurred edges, and corrupted details. Traditional Retinex-based enhancement frameworks have been widely developed, yet they expose a fundamental trade-off: structure-preserving enhancement often amplifies noise, while noise suppression tends to oversmooth critical structures. Addressing this antagonism requires a principled framework that…

This paper introduces an innovative framework for managing crowd movement through the use of a Convolutional Neural Network (CNN) to classify crowd density into four congestion levels and generate a congestion map. This information is then utilized by a Genetic Algorithm (GA) to determine safer walking routes that balance travel distance and congestion. The hybrid system is applied during the Haj…

This work investigates the thermal and flow properties of a rotating hybrid nanofluid comprising TiO 2 – Ag nanoparticles in a water-ethylene glycol matrix across a linearly extending sheet, emphasising dissipative heat effects under magnetohydrodynamic (MHD) conditions. An essential innovation involves the amalgamation of the Fourier numerical approach with the XGBoost machine learning model to …

Industrial robots have become another important manufacturing equipment in addition to machine tools due to their advantages such as large working range and flexible working modes. However, compared with machine tools, larger errors restrict their application in precision-dependent scenarios. The robot's processing error is directly related to the system configuration. Under the same task, differ…

Super-resolution is a technique that enhances image quality by transforming lowresolution images into high-resolution representations. In medical imaging, image quality plays a crucial role in early diagnosis and clinical workflow efficiency. However, due to hardware limitations, low-dose acquisition requirements, and patient motion, medical images often suffer from significant information loss. …

The aim of this study is to propose a stochastic radial basis (RB) artificial neural network (ANN) and the scale conjugate gradient (SCG) called as RB-ANN-SCG for the the diarrhea disease model including treatment and vaccination (DDMTV). The diarrhea disease system is basically a susceptible, infected and recovered model that includes the factor of treatment and vaccination. The dataset is obtai…

The solution of ordinary differential equations is an essential activity in most sciences because it represents the of different systems, both in the physics and biology spheres. Non-analytical methods to solve ODEs, however, may be tricky, particularly the non-linear equations. The proposed study suggests a system of solving initial value problems of ODEs with advanced Runge-Kutta algorithms, wh…

The linear inverted pendulum (LIP) model with preview control is a standard approach for gait planning in bipedal humanoid robots. However, its inherent simplifications lead to significant model errors that compromise walking stability. To address this, we propose a compensation strategy that integrates two core components: a compensation controller based on a multi-link model and a joint torque …

Models for spin systems, known from statistical physics, are applied analogously in economic modeling in the form of agent-based models. The models discussed in the econophysics literature all use the state variable T, which, in physics, represents the temperature of a system. However, there is little evidence on how temperature can be measured in econophysics, so that the models can be applied. …

This paper develops a comprehensive theoretical framework for analyzing quality dynamics in oligopsony markets where numerous producers compete for limited consumer attention under information asymmetries. Motivated by artificial intelligence marketplaces and similar digital platforms, we establish existence and uniqueness conditions for optimal quality provision by heterogeneous producers and pr…

Real-time AI-enabled multimedia networking in cloud-based digital learning systems requires high-quality, low-latency data transfer for effective, continuous learning. Managing changing traffic loads and delivering multimedia content like live lectures and video lessons requires adaptive fraudulent data control. Academic Fraudulent data management systems frequently have static parameter setting,…

The Industrial Internet of Things (IIoT) has reshaped Industry 4.0 by enabling large-scale connectivity among intelligent devices and supporting new levels of digital automation and analytics. However, the distributed nature of IIoT, together with Industrial 5G connectivity, heterogeneous sensing devices, IT/OT convergence, edge computing, and time-sensitive networking, significantly expands the …

Graph Neural Networks (GNNs) have demonstrated strong practical value in graph classification tasks. However, graph data often contains sensitive information, making privacy protection an urgent practical need. Traditional privacy protection technologies have key limitations: anonymization is prone to re-identification via auxiliary knowledge, secure multi-party computation has high communication…

The catenary system is the power source of high-speed trains and it contains critical components such as droppers and messenger wires. During train operation, the messenger wire vibrates in conjunction with the catenary. In order to obtain a more realistic vibration performance of the droppers, it is necessary to consider the vibration of the messenger wire. In this paper, the vibration equation …

Accurate valuation of options, among the most significant financial derivatives, is critical for the stability and efficiency of the derivatives market. This paper presents a practical and reproducible implementation workflow for solving multi-asset Black–Scholes (BS) pricing partial differential equations (PDEs) using adaptive finite elements in COMSOL Multiphysics. The backward differentiation …

Amid escalating global food security challenges, global food trade has become increasingly pivotal in securing national food supplies and stabilizing nutritional availability. However, the identification of food export drivers remains hindered by fragmented indicator systems and the limitations of linear causality methods in capturing complex, nonlinear dynamics. In this study, we construct a com…

The emergence of excessive social media use has raised significant concerns in the twenty-first century, necessitating urgent attention to mitigate potential adverse consequences. To address this challenge, a range of preventive strategies, such as advertising campaigns and awareness programs, are being utilized to highlight the negative impacts of digital technologies. Employing advanced mathema…

This study presents a two-dimensional nonlinear mathematical model to investigate the dynamic interaction between healthcare resources and artificial intelligence (AI) adoption in the healthcare sector. The model is inspired by classical predator–prey dynamics, where healthcare resources represent the foundational system that supports AI deployment, while AI adoption evolves through interaction w…

This paper presents a comprehensive review of the Social Laser Theory (SLT) as a natural extension of the broader framework of Quantum-Like Modeling (QLM). While QLM applies the mathematical formalism of quantum theory — such as Hilbert space representations, interference, and non-commutative observables — to model context-dependent and non-classical phenomena in cognition, decision-making, and s…