Mathematics, Volume 13, Issue 6

In this paper, a stochastic continuous-time Markov chain (CTMC) model is developed and analyzed to explore the dynamics of cholera. The multitype branching process is used to compute a stochastic threshold for the CTMC model. Latin hypercube sampling...

Colon adenocarcinoma (COAD) demonstrates significant clinical heterogeneity across disease stages, gender, and age groups, posing challenges for unified therapeutic strategies. This study establishes a multi-dimensional stratification framework throu...

Continuous data associated with many real-world events often exhibit non-normal characteristics, which contribute to the difficulty of accurately modeling such data with statistical procedures that rely on normality assumptions. Traditional statistic...

The evaluation of clustering results plays an important role in clustering analysis. Most existing indexes are designed for the evaluation of results from the most-used K-means clustering algorithm; it can identify only spherical clusters rather than...

Let K be a closed convex subset of a real Banach space X, and let F be a map from X to its dual $X^{*}$. We study the so-called variational inequality problem: given $y\in X^{*,},$ does there exist $x_0\in K$ such that (in standard notation) $⟨F\left(x_0\right)-y,x\&m⟩$...

For train control systems, the accuracy of positioning tracking is essential for ensuring the safety and efficiency of operations. Multi-source information fusion techniques can improve positioning accuracy, but the computational limitations of onboa...

Lane changing is a crucial scenario in traffic environments, and accurately recognizing and predicting lane-changing behavior is essential for ensuring the safety of both autonomous vehicles and drivers. Through considering the multi-vehicle informat...

Modular arithmetic is used to apply generalized C-coloured checkerboard patterns to $m\times n$ gridded rectangles, ensuring that colours cycle both horizontally and vertically. This paper yields methods for counting the number of squares of each colou...

We investigated the properties of Ricci semi-symmetric Robertson–Walker spacetimes within the framework of $f(\mathcal{R})$-gravity theory. Initially, we established that Ricci semi-symmetric Robertson–Walker spacetimes are locally isometric to eithe...

This paper addresses the pervasive problem of fake news propagation in social networks. Traditional text-based detection models often suffer from performance degradation over time due to their reliance on evolving textual features. To overcome this l...

In recent years, blockchains have been attracting attention because they are decentralized networks with transparency and trustworthiness. Generally, transactions on blockchain networks with higher transaction fees are processed preferentially compar...

This paper aims to establish a new hybrid class of special polynomials, namely, the Fubini–Bell-based Appell polynomials. The monomiality principle is used to derive the generating function for these polynomials. Several related identities and...

In this study, we analyze the winning percentage of 16 teams that have participated in Major League Baseball since 1901. First, 69 variables for each team are classified into pitching, batting, and fielding using factor analysis, and then the effect...

Surrogate-assisted evolutionary algorithms (SAEAs), which combine the search capabilities of evolutionary algorithms (EAs) with the predictive capabilities of surrogate models, are effective methods for solving expensive optimization problems (EOPs)....

The aim of this paper is to develop a mathematical model for determining coordinates of points in a desired trimetric projection of a three-dimensional object. The desired trimetric projection is quantitatively specified according to the observer&rsq...

It has been conjectured that for each positive integer k and each tree T with bipartite $(Z_1,Z_2)$, every k-connected bipartite graph G with $\delta \left(G\right)\ge k+max\left\{\right|Z_1|,|Z_2\left|\right\}$ admits a subgraph $T^{\prime }\cong T$ such that $G-V\left(T^{\prime }\right)$ is still k-connec...

Distributed Collaborative Learning (DCL) addresses critical challenges in privacy-aware machine learning by enabling indirect knowledge transfer across nodes with heterogeneous feature distributions. Unlike conventional federated learning approaches,...

We investigate in this paper the static radial coordinate-dependent spherically symmetric spacetime in teleparallel $F\left(T\right)$ gravity for a scalar field source. We begin by setting the static field equations (FEs) to be solved and solve the conservation l...

With the advancement of global digital transformation, data trading has become a pivotal element in value circulation and innovation among enterprises. In particular, pricing strategies in the industrial chain’s data trading process critically...

Generalizability theory (GT) provides an all-encompassing framework for estimating accuracy of scores and effects of multiple sources of measurement error when using measures intended for either norm- or criterion-referencing purposes. Structural equ...

Indoor environmental comfort is closely related to human health and well-being. This study aimed to establish a quantitative evaluation model for indoor comprehensive environmental comfort based on multiple physical environmental parameters. Firstly,...

This study presents a comprehensive evaluation of the quick invariant signature (QIS), dynamic time warping (DTW), and a novel hybrid QIS + DTW approach for time series analysis. QIS, a translation and rotation invariant shape descriptor, and DTW, a...

In the era of information overload, location-based social software has gained widespread popularity, and the demand for personalized POI (Point of Interest) recommendation services is growing rapidly. Recommending the next POI is crucial in recommend...

Sentiment analysis in Chinese microblogs is challenged by complex syntactic structures and fine-grained sentiment shifts. To address these challenges, a Contextually Enriched Graph Neural Network (CE-GNN) is proposed, integrating self-supervised lear...

Feature selection is essential in machine learning and data science. Recently, there has been a growing effort to apply various mathematical methods to construct novel feature selection algorithms. In this study, we present a comprehensive state-of-t...

In this paper, we consider a class of nonsmooth weak vector variational-hemivariational inequality problems (abbreviated as, WVVHVIP) in the framework of Hadamard manifolds. By employing an analogous to the KKM lemma, we establish the existence of th...

With the increasing prevalence of intermittent power generation, the volatility, intermittency, and randomness of renewable energy pose significant challenges to the planning and operation of distribution networks. In this study, a data-driven distri...

In this paper, based on the novel generalized Hamilton-real (GHR) calculus, we propose for the first time a quaternion Nesterov accelerated projected gradient algorithm for computing the dominant eigenvalue and eigenvector of quaternion Hermitian mat...

This article presents the Transfer Matrix Method as a mathematical approach for the calculus of different structures that can be discretized into elements using an iterative calculus for future applications in the vehicle industry. Plate calculus is...

This study tackles the challenge of splitting and merging in parametric active contours or snakes. The proposed method comprises three stages: (1) fully 4-connected interpolation, (2) snake splitting, and (3) snakes merging. For this purpose, first,...

This editorial presents 24 research articles published in the Special Issue entitled Geometry of Manifolds and Applications of the MDPI Mathematics journal, which covers a wide range of topics from the geometry of (pseudo-)Riemannian manifolds and th...

We study an optimal consumption, leisure, and investment problem over a finite horizon in a continuous-time financial market with partial borrowing constraints. The agent derives utility from consumption and leisure, with preferences represented by a...

Recent developments in sensors, wireless communications, and data processing technologies are the main drivers for adopting the Internet of Things (IoT) in healthcare systems. IoT-based healthcare systems can enhance the quality of life significantly...

Image encryption is crucial for ensuring the confidentiality and integrity of digital images, preventing unauthorized access and alterations. However, existing encryption algorithms often involve complex mathematical operations or require specialized...

Previous studies typically assume that output constraints are symmetric or time-invariant. However, effectively addressing asymmetric and time-varying output constraints remains an unsolved issue, especially in the case of switched non-square multi-i...

This study presents an advanced second-order sliding-mode guidance law with a terminal impact angle constraint, which ingeniously combines reinforcement learning algorithms with the nonsingular terminal sliding-mode control (NTSM) theory. This hybrid...

This study presents analysis and optimization of a standalone hybrid renewable energy system (HRES) for Adama Science and Technology University’s ICT center in Ethiopia. The proposed hybrid system combines photovoltaic panels, wind turbines, a...

The widespread adoption of deep neural networks (DNNs) in speech recognition has introduced significant security vulnerabilities, particularly from backdoor attacks. These attacks allow adversaries to manipulate system behavior through hidden trigger...

Sampling and reconstruction are indispensable processes in signal processing, and appropriate foundations are crucial for spline reconstruction models. Generalized cardinal polishing splines (GCP-splines) are a class of high-precision explicit spline...

In Industry 4.0, predictive maintenance (PdM) is key to optimising production processes. While its popularity among companies grows, most studies highlight theoretical benefits, with few providing empirical evidence on its economic impact. This study...

In this work, we develop and analyze a novel fractional-order framework to investigate the interactions among oxygen, phytoplankton, and zooplankton under changing climatic conditions. Unlike standard integer-order formulations, our model incorporate...

The parallel dual-slider telescopic leg bipedal robot (L04) is characterized by its simple structure and low leg rotational inertia, which contribute to its walking efficiency. However, end-to-end methods often overlook the robot’s physical str...

Spatial discrete data modeling plays a crucial role in geoscientific data analysis, with accuracy and efficiency being significant factors to consider in the modeling of massive discrete datasets. In this paper, an efficient and regularized modeling...

A novel trajectory tracking control approach for robot manipulators that uses adaptive neural network feedforward compensation plus a sectorial fuzzy controller is presented. We conduct simulation and real-time experiments comparing it with two previ...

This study presents an advanced Sliding Variable-Based Robust Adaptive Control (SVRAC) scheme designed for canonical nonlinear system with unknown dynamic and control gain functions. Leveraging neural network (NN) approximation, the proposed method s...

Hot metal temperature is a key factor affecting the quality and energy consumption of iron and steel smelting. Accurate prediction of the temperature drop in a hot metal ladle is very important for optimizing transport, improving efficiency, and redu...

This paper proposes a traffic prediction-based connected-mode discontinuous reception (C-DRX) approach to enhance energy efficiency and reduce data transmission delay in mobile communication systems. Traditional C-DRX determines user equipment (UE) a...

Encrypted traffic classification is crucial for network security and management, enabling applications like QoS control and malware detection. However, the emergence of new encryption protocols, particularly TLS 1.3, poses challenges for traditional...

This paper focuses on the extreme-value issue of Shannon entropy for joint distributions with specified marginals, a subject of growing interest. It introduces a theorem showing that the coupling with minimal entropy must be essentially order-preserv...

Full-duplex relay networks have been studied to enhance network performance under the assumption that the number and positions of relay nodes are fixed. To account for the practical randomness in the number and locations of relays, this paper investi...