2025 November-2 - 162 articles
Multicollinearity is a common issue in regression analyses that occurs when some predictor variables are highly correlated, leading to unstable least squares estimates of model parameters. Various estimation strategies have been proposed to address t...
This paper investigates an infinite-horizon optimal consumption and investment problem for an agent who consumes two types of goods: necessities and luxuries. The agent derives utility from both goods but faces a ratcheting constraint on luxury consu...
Index modulation (IM) has attracted increasing research attention in recent years. Spatial modulation (SM) as a popular IM scheme is effective to increase spectral efficiency using the antenna index to transmit extra information bits. It can also add...
This work presents EDICA, a two-stage architecture for fine-grained image classification, which is a hybrid model for the detection and classification task. The model employs YOLOv8 for the detection stage and an ensemble deep learning model that uti...
Machine learning has emerged as a promising tool to accelerate the screening of lithium–ion battery electrode materials. Gravimetric capacity, a critical performance indicator governing electrode energy density, is intrinsically related to lith...
Deep learning has demonstrated significant promise in medical image analysis; however, standard CNNs frequently encounter challenges in detecting subtle and intricate features vital for accurate diagnosis. To address this limitation, we systematicall...
To address the problems of the traditional Supply–Demand Optimization (SDO) algorithm in wireless sensor network (WSN) node deployment—such as blind search direction, weak global exploration capability, coarse boundary handling, and insuf...
Three-dimensional (3D) scene model retrieval has emerged as a novel and challenging area within content-based 3D model retrieval research. It plays an increasingly critical role in various domains, such as video games, film production, and immersive...
This paper examines
In spite of great successes of the inertial step approach (ISA) in various fields, we are investigating the converse inertial step approach (CISA) for the first time. First, the classical Picard iteration for solving nonexpansive mappings converges w...
Alzheimer’s disease (AD) affects over 55 million individuals worldwide, yet no transformative disease-modifying therapies exist. Mathematical modelling provides a powerful framework to elucidate complex disease mechanisms, predict therapeutic o...
This paper investigates the volatility spillover effects from the crude oil market to domestic stock markets using high-frequency data. We propose an enhanced methodology, the MS-HAR-TVP model, which extends the standard HAR framework. Our model deco...
An Incomplete Atypical femoral fracture is subtle and requires early diagnosis. However, artificial intelligence models for these fractures often fail in real-world clinical settings due to the “domain shift” problem, where performance de...
Predicting wildland fire spread requires numerical schemes that can resolve sharp gradients at the fireline while remaining stable and efficient on practical grids. We develop a compact high-order finite-difference scheme for Hamilton–Jacobi le...
This study addresses the preassigned-time (PDT) projective lag synchronization of octonion-valued BAM neural networks (OV-BAMNNs) through exponential quantized event-triggered control (ETC). First, an OV-BAMNN model incorporating discontinuous activa...
This paper investigates how institutional investors address the double externalities of green innovation (knowledge spillovers and environmental benefits) in China’s transition economy. Methodologically, we integrate fixed-effects econometric m...
This paper introduces a novel closed-loop optimal controller that integrates the Extreme Theory of Functional Connections (X-TFC) with receding horizon control (RHC), referred to as X-TFC-RHC. The controller reformulates a sequence of linearized or q...
The goal of this manuscript is the study of an optimal control problem. It consists on the minimization of the compliance functional when the state equation is the nonlocal p-laplacian and the control is the source of this equation. For this problem,...
In this paper, we shall give a concise review of recent numerical methods of some generalized fractional models. As is elucidated later, the generalized fractional models may arise from either mathematical point of view or application point of view....
Depth from focus (DFF) is an optical, passive method that perceives the dense depth map of a real-world scene by exploiting the focus cue through a focal stack, a sequence of images captured at different focal distances. In DFF methods, first, a focu...
E-learning systems that support personalized learning require sophisticated decision-making methods to adapt content to students optimally. This paper deals with applying multi-criteria decision-making methods in assigning learning objects in an e-le...
Although physics-informed neural networks (PINNs) offer a novel, mesh-free paradigm for computational fluid dynamics (CFD), existing models often suffer from poor stability and insufficient accuracy, particularly when dealing with complex flows at hi...
The research examines how digital inclusive finance reshapes the rural labor market using an auditable index system and an interpretable learning pipeline. We construct a four-pillar framework for the rural labor market covering labor behavior, labor...
This paper presents a hybrid inversion framework that integrates a physics-informed iterative algorithm with a deep learning-based refinement strategy to address the electromagnetic inverse scattering problem of a uniaxial object buried in lossy half...
Transportation planning often involves not only shipment costs but also setup costs associated with deploying vehicles or transport resources. In many practical logistics operations, this setup cost does not remain constant but increases stepwise wit...
The increasing environmental concerns related to aircraft carbon dioxide (CO2) emissions call for efficient fuel-saving strategies. This study proposes an alternative cruising strategy to minimize fuel consumption during the cruise flight phase by in...
This paper presents a comprehensive strategy for addressing tracking and disturbance rejection for both lumped and distributed parameter systems, focusing on infinite-dimensional input and output spaces. Building on the geometric theory of regulation...
The study investigates and analyzes certain qualitative properties of a stochastic dynamical multiscale model for hepatitis B viral infection. By formulating appropriate stochastic Lyapunov functions, the study derives sufficient conditions for the e...
This work explores the issue of identifying sub-synchronous oscillations (SSOs). Regular detection techniques face issues with response timings to variations in viewpoint and adaptability to variations in conditions of the system but our proposed met...
A model of gene regulatory networks with generalized Caputo fractional derivatives with respect to another function is set up in this paper. The main characteristic of the model is the presence of a switching rule, which changes at certain times at b...
The drive system of pure electric vehicles is characterized by high transmission efficiency and a rapid torque response, with the centralized drive configuration being the most commonly adopted. To improve the dynamic performance and reliability of s...
Mainstream DNN-based feature selection methods share a similar design strategy: employing one specially designed feature selection module to learn the importance of features along with the model-training process. While these works achieve great succe...
In this paper, we study the topology of steady gradient Ricci solitons with nonnegative sectional curvature. We apply a characterization theorem for the fundamental group of a positively curved steady gradient Ricci soliton that admits a critical poi...
The purpose of this research is to develop approximate weak and strong stationary conditions for interval-valued multiobjective optimization problems with vanishing constraints (IVMOPVC) involving nonsmooth functions. In many real-world situations, t...
Many authors analyze the chaotic motion of the driven and damped double sine-Gordon equations and compute the Melnikov functions by numerical methods, taking an example to verify good agreement between numerical methods and analytical ones. Unfortuna...
Quantum calculus is a powerful extension of classical calculus, providing novel tools for deriving sharper and more efficient analytical results without relying on limits. This study investigates error estimations for Milne formula-type inequalities...
This article investigates the chaotic features of a novel variable-order fractional Rössler system built with Liouville–Caputo derivatives of variable order. Variable-order fractional (VOF) operators incorporated in the system render its d...
Divisible residuated lattices and MTL algebras are algebraic structures connected with algebras in t-norm-based fuzzy logics, being examples of residuated lattices. They are an important topic in the study of fuzzy logic. The purpose of this paper is...
In recent years, many constrained multi-objective evolutionary algorithms (CMOEAs) have primarily emphasized feasible solutions, overlooking the useful information contained in infeasible ones. This tendency effectively prioritizes feasibility over o...
The elastic support structure is widely employed in rotor systems and has an important influence on the nonlinear vibration of such systems. Nevertheless, coupled motion between elastic supports and bearings has not been taken into account, and the c...
We investigate algebraic and topological properties of subsymmetric polynomials on finite- and infinite-dimensional spaces. In particular, we focus on the problem of the existence of an algebraic basis in the algebra of subsymmetric polynomials, as w...
This study offers a comprehensive study of power quality in industrial rolling mill grids, focusing on total harmonic distortion (THD) and its forecasting under different operational conditions. The research begins with a measurement-based evaluation...
The growth of intelligent manufacturing systems has led to a wealth of computation-intensive tasks with complex dependencies. These tasks require an efficient offloading architecture that balances responsiveness and energy efficiency across distribut...
Large language models (LLMs) have traditionally relegated inference to remote servers, leaving mobile devices as thin clients. Recently, advances in mobile GPUs and NPUs have made on-device inference increasingly feasible, particularly for privacy-se...
This study considers general Markov chains (MCs) with discrete time in an arbitrary phase space. The transition function of the MC generates two operators: T, which acts on the space of measurable functions, and A, which acts on the space of bounded...
Reasoning over Temporal Knowledge Graphs (TKGs) aims to forecast future events based on historical ones. Existing approaches typically enforce strict temporal order constraints among past events; however, such rigidity limits the effective exploitati...
In federated learning, secure aggregation is essential to protect the confidentiality of local model updates, ensuring that the server can access only the aggregated result without exposing individual contributions. However, conventional secure aggre...
The Industrial Internet of Things (IIoT) integrates a wide range of devices and identities, making the protection of sensitive industrial data a critical challenge. However, existing centralized systems still face limitations such as single points of...
This paper is devoted to the investigation of existence and approximate controllability results for a class of fractional integro-differential equations formulated in Fréchet spaces. The analysis is carried out using a generalized version of D...
This paper investigates the asymptotic output tracking problem in probabilistic Boolean control networks by introducing the concept of the tracking region of attraction (TROA). For a constant reference signal, we provide a formal definition of the TR...
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