2026 January-1 - 203 articles
Real-world image denoising faces a critical trade-off: Convolutional Neural Network (CNN)-based methods are computationally efficient but limited in capturing long-range dependencies, while Transformer-based approaches achieve superior global modelin...
Improving responsiveness and efficiency in production systems requires an understanding of how manufacturing flexibility and inventory management interact under conditions of uncertainty. This study examines the combined effect of four types of flexi...
This paper introduces an Improved Red-Billed Blue Magpie Optimizer (IRBMO) to enhance the Maximum Second-Order Cyclostationary Blind Deconvolution (CYCBD) method, which traditionally depends on manual, experience-based setting of its key parameters (...
The traditional finite element method (FEM) usually exhibits significant numerical dispersion error for solving the Helmholtz equation in relatively high-frequency range, resulting in insufficiently accurate solutions. To address this problem, this p...
In recent years, payment schemes in healthcare have garnered attention for their potential impact on service delivery and cost management. This paper explores the impact of the bundled payment scheme (BP) on hospital outpatient services, focusing on...
This work investigates the relationship between the parastrophes of some notion of inverses in quasigroups. Our findings reveal that, of the 5 parastrophes of LIP quasigroup, (23) parastrophe is a LIP quasigroup, (12) and (132) parastrophes are RIP q...
This paper is devoted to the investigation of the proper strict efficient solutions to a set optimization problem with a partial set order relation. Firstly, the notion of proper strict efficient solution defined by the Minkowski difference is introd...
The concordance correlation coefficient (CCC) is a popular measure of agreement between two continuous variables but is highly sensitive to outliers and data contamination. In this study, we propose a robust reformulation of the CCC by replacing clas...
This study examines the logistical challenges arising in omni-channel retailing, where the interaction between traditional stores and online channels requires flexible and efficient transportation planning. In particular, the growth of Buy-Online-and...
This study presents a novel fifth-order unequal-sized trigonometric weighted essentially non-oscillatory (US-TWENO) scheme and a novel hybrid US-TWENO (HUS-TWENO) scheme with a novel troubled cell indicator in a finite difference framework to address...
The estimation of correlation matrices in high-dimensional data streams presents a fundamental conflict between computational efficiency and statistical robustness. Moment-based estimators, such as Pearson’s correlation, offer linear
Dual-channel retailing empowers the manufacturer to benefit from market opportunities by producing customized items that fulfill client requirements. The manufacturer and retailer sell customized products, which allow customers to express their chose...
Each of the studied manifolds has a pair of B-metrics, interrelated by an almost contact structure. The case where each of these metrics gives rise to an
Indirect fear effects profoundly influence predator–prey dynamics by reducing prey reproduction. Whereas previous studies have investigated fear effects or self-diffusion separately in Leslie–Gower models, the novelty of this work lies in...
The integrate-and-dump filter is a core component of satellite navigation receivers, enabling the tracking of navigation satellite signals and significantly influencing receiver performance. Currently, satellite navigation receivers, particularly onb...
Large language models are increasingly used in code generation and developer tools, yet their robustness to ethically problematic natural language embedded in source code is underexplored. In this work, we study content-safety vulnerabilities arising...
In today’s dynamic and global business landscape, economic profitability is essential for creating and sustaining competitive advantage. Nevertheless, a critical gap persists in the literature regarding the application of advanced optimization...
We introduce KORIE, a curated benchmark of 748 Korean retail receipts designed to evaluate scene text detection, Optical Character Recognition (OCR), and Information Extraction (IE) under challenging digitization conditions. Unlike existing large-sca...
The Peak Age of Information (PAoI) quantifies the freshness of updates used in cyber-physical systems (CPSs), realized within the Internet of Things (IoT) paradigm, encompassing devices, networks, and control algorithms. Consequently, PAoI is a criti...
The sideslip angle is a key state for evaluating the lateral stability of a vehicle. Its accurate estimation is crucial for active safety and intelligent driving assistance systems. To improve the estimation accuracy and robustness of the sideslip an...
As a transition from offline to online shopping is taking place in many societies, many studies have been conducted to align products with user preferences. However, the existing collaborative filtering technology has a small number of user–ite...
The current manuscript is concerned with the uniqueness and existence of a solution for a new class of
Multimodal forecasting is increasingly needed to maintain energy levels, storage capacity, and compute efficiency in off-grid, renewable-powered cloud environments. Variable sensor quality, uncertain interactions with renewable energy, and rapidly ch...
In this paper, Artificial Intelligence (AI) is developed for studying the Boussinesq Paradigm equation and so called b-equation based on Physics-Informed Cellular Neural Networks (PICNNs). The models studied here come from fluid dynamics. Machine lea...
Nonlinear transport of tracer particles immersed in a sheared dilute gas with inelastic collisions is analyzed within the framework of the Boltzmann kinetic equation. Two different yet complementary approaches are employed to obtain exact results. Fi...
Timely detection and handling of substation defects plays a foundational role in ensuring the stable operation of power systems. Existing substation defect detection methods fail to make full use of the temporal information contained in substation in...
Constrained optimization problems (COPs) are frequent in engineering design yet remain challenging due to complex search spaces and strict feasibility requirements. Existing swarm-based optimizers often rely on penalty functions or algorithm-specific...
Classifying demographic groups of humans from gait patterns is desirable from several long-standing diagnostic and monitoring perspectives. IMU recorded gait patterns are mapped into a nonlinear dynamic representation space using criticality analysis...
This paper presents a narrative review of the contextualization and contribution offered by vision–language models (VLMs) for human-centric understanding in images. Starting from the correlation between humans and their context (background) and...
The aim of this paper is to introduce Leonardo finite operator polynomials and obtain some of their new properties. We first present the recurrence relation provided by Leonardo finite operator polynomials. Then, we give a Binet-like formula, generat...
Radiology report generation, which aims to relieve the heavy workload of radiologists and reduce the risks of misdiagnosis and overlooked diagnoses, is of great significance in current clinical medicine. Most existing methods mainly formulate radiolo...
Growing climate concerns and rising consumer awareness of sustainability have reshaped strategic interactions in platform-based supply chains. This study examines how a manufacturer and an e-commerce platform make channel and fulfillment decisions un...
Accurately forecasting the dynamic linkages among carbon, energy, and stock markets is essential for effective risk management and the design of energy transition strategies. This study proposes a BOHB-optimized Multivariable Graph Neural Network (BO...
Cyberbullying has become a pervasive threat on social media, impacting the safety and wellbeing of users worldwide. Most existing studies focus on monolingual content, limiting their applicability to online environments. This study aims to develop an...
This paper introduces a novel Bayesian Fractional Weibull (BFW) regression framework, which generalizes the classical Weibull accelerated failure time model using fractional calculus. The proposed methodology addresses key challenges in big data reli...
It has been well established that individuals employ different decision strategies depending on the task environment, and these strategies differ in the amount of information search and time required to reach a decision. The present study developed p...
We propose a general methodology for constructing dynamic performance indicators (or strength metrics) in any sport that relies on comparative outcomes among competitors, using chronological positional data. Specifically, we develop a family of stren...
The Traveling Salesman Problem (TSP) is a classic combinatorial optimization problem with broad applications in logistics and smart agriculture. However, despite significant progress in Transformer-based deep reinforcement learning methods, two major...
In this research paper, we introduce the notions of hyperbolic ∗-Ricci solitons and gradient hyperbolic ∗-Ricci solitons. We study the hyperbolic ∗-Ricci solitons on a three-dimensional
Multi-robot rescue path planning (MRRPP) is critical for ensuring the rapid and effective completion of post-disaster rescue tasks. Most studies focus on minimizing the length of rescue paths, the number of robots, and rescue time, neglecting the tas...
Price is a pivotal determinant of market demand, as higher prices typically reduce sales while lower prices stimulate them. Thus, incorporating price-dependent demand into inventory models is both realistic and necessary. In practice, limited storage...
An age-distributed immuno-epidemiological model with information-based vaccination proposed in this work represents a system of integro-differential equations with compartments for the numbers of susceptible individuals, infected individuals, vaccina...
Path planning in complex, dynamic environments presents a significant challenge. Deep Reinforcement Learning (DRL) offers an end-to-end solution but suffers from critical sample inefficiency and a “cold-start” problem. Imitation Learning...
The pervasive misuse of Duty-Free Quota Abuse Smuggling has seriously undermined fiscal and market order. This study breaks through the traditional model’s assumption of complete rationality and establishes a Multi-Phase Dynamic Decision-Making...
Network slicing in 5G systems enables different Quality of Service (QoS) for heterogeneous Vehicle-to-Everything (V2X) applications, yet efficiently allocating resource blocks from both 5G base stations and roadside units (RSUs) across multiple slice...
With the development of heavy-haul trains towards long formation and large axle load, the longitudinal impulse problem of trains is aggravated not only by improving the transport capacity of railway freight cars, but also by the braking characteristi...
The Internet of Medical Things (IoMT) interconnects medical devices, software applications, and healthcare services through the internet to enable the transmission and analysis of health data. IoMT facilitates seamless patient care and supports real-...
In some previous works we gave algorithms for determining generators of power integral basis in sextic fields with a quadratic subfield, under certain restrictions. The purpose of the present paper is to extend those methods to the general case, when...
In this paper, the authors investigate a partial inverse spectral problem for Sturm–Liouville operators with frozen arguments on star-shaped graphs. The problem is to reconstruct the potential on one edge from the known potentials on the other...
Graph Neural Networks (GNNs) have achieved remarkable success in graph structure learning, but recent research reveals their vulnerability to carefully designed perturbations. To address this, ProGNN, a GNN model based on graph properties, was propos...
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