Mathematics

16 pages, 3431 KiB

Open AccessArticle

Sample Inflation Interpolation for Consistency Regularization in Remote Sensing Change Detection

by Zuo Jiang, Haobo Chen and Yi Tang

Mathematics 2024, 12(22), 3577; https://doi.org/10.3390/math12223577 (registering DOI) - 15 Nov 2024

Semi-supervised learning has gained significant attention in the field of remote sensing due to its ability to effectively leverage both a limited number of labeled samples and a large quantity of unlabeled data. An effective semi-supervised learning approach utilizes unlabeled samples to enforce [...] Read more.

Semi-supervised learning has gained significant attention in the field of remote sensing due to its ability to effectively leverage both a limited number of labeled samples and a large quantity of unlabeled data. An effective semi-supervised learning approach utilizes unlabeled samples to enforce prediction consistency under minor perturbations, thus reducing the model’s sensitivity to noise and suppressing false positives in change-detection tasks. This principle underlies consistency regularization-based methods. However, while these methods enhance noise robustness, they also risk overlooking subtle but meaningful changes, leading to information loss and missed detections. To address this issue, we introduce a simple yet efficient method called Sample Inflation Interpolation (SII). This method leverages labeled sample pairs to mitigate the information loss caused by consistency regularization. Specifically, we propose a novel data augmentation strategy that generates additional change samples by combining existing supervised change samples with calculated proportions of change areas. This approach increases both the quantity and diversity of change samples in the training set, effectively compensating for potential information loss and reducing missed detections. Furthermore, to prevent overfitting, small perturbations are applied to the generated sample pairs and their labels. Experiments conducted on two public change detection (CD) datasets validate the effectiveness of our proposed method. Remarkably, even with only 5% of labeled training data, our method achieves performance levels that closely approach those of fully supervised learning models. Full article

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19 pages, 17340 KiB

Open AccessArticle

TTG-Text: A Graph-Based Text Representation Framework Enhanced by Typical Testors for Improved Classification

by Carlos Sánchez-Antonio, José E. Valdez-Rodríguez and Hiram Calvo

Mathematics 2024, 12(22), 3576; https://doi.org/10.3390/math12223576 (registering DOI) - 15 Nov 2024

Abstract

Recent advancements in graph-based text representation, particularly with embedding models and transformers such as BERT, have shown significant potential for enhancing natural language processing (NLP) tasks. However, challenges related to data sparsity and limited interpretability remain, especially when working with small or imbalanced [...] Read more.

Recent advancements in graph-based text representation, particularly with embedding models and transformers such as BERT, have shown significant potential for enhancing natural language processing (NLP) tasks. However, challenges related to data sparsity and limited interpretability remain, especially when working with small or imbalanced datasets. This paper introduces TTG-Text, a novel framework that strengthens graph-based text representation by integrating typical testors—a symbolic feature selection technique that refines feature importance while reducing dimensionality. Unlike traditional TF-IDF weighting, TTG-Text leverages typical testors to enhance feature relevance within text graphs, resulting in improved model interpretability and performance, particularly for smaller datasets. Our evaluation on a text classification task using a graph convolutional network (GCN) demonstrates that TTG-Text achieves a 95% accuracy rate, surpassing conventional methods and BERT with fewer required training epochs. By combining symbolic algorithms with graph-based models, this hybrid approach offers a more interpretable, efficient, and high-performing solution for complex NLP tasks. Full article

(This article belongs to the Special Issue Recent Trends and Advances in the Natural Language Processing)

21 pages, 495 KiB

Open AccessArticle

On the Evolution Operators of a Class of Linear Time-Delay Systems

by Manuel De la Sen

Mathematics 2024, 12(22), 3575; https://doi.org/10.3390/math12223575 (registering DOI) - 15 Nov 2024

Abstract

This paper studies the properties of the evolution operators of a class of time-delay systems with linear delayed dynamics [...] Full article

(This article belongs to the Special Issue New Trends in Nonlinear Analysis)

31 pages, 474 KiB

Open AccessArticle

Analysis of a Mathematical Model of Zoonotic Visceral Leishmaniasis (ZVL) Disease

by Goni Umar Modu, Suphawat Asawasamrit, Abdulfatai Atte Momoh, Mathew Remilekun Odekunle, Ahmed Idris and Jessada Tariboon

Mathematics 2024, 12(22), 3574; https://doi.org/10.3390/math12223574 (registering DOI) - 15 Nov 2024

Abstract

This research paper attempts to describe the transmission dynamic of zoonotic visceral leishmaniasis with the aid of a mathematical model by considering the asymptomatic stages in humans and animals. The disease is endemic in several countries. Data used in the research are obtained [...] Read more.

This research paper attempts to describe the transmission dynamic of zoonotic visceral leishmaniasis with the aid of a mathematical model by considering the asymptomatic stages in humans and animals. The disease is endemic in several countries. Data used in the research are obtained from the literature while some are assumed based on the disease dynamic. The consideration of both asymptomatic and the symptomatic infected individuals is incorporated in both humans and animals (reservoir), as well as lines of treatment for the human population. It is found that the model has two fixed points; the VL-free fixed point and the VL-endemic fixed point. Stability analysis of the fixed points shows that the VL-free fixed point is globally asymptotically stable whenever the basic reproduction number is less than one and the VL-endemic fixed point is globally asymptotically stable whenever the basic reproduction number is greater than one. Sensitivity analysis is conducted for the parameters in the basic reproduction number, and the profile of each state variable is also depicted using the data obtained from the literature and those assumed. The transmission probability from infected sandflies to animals, transmission probability from infected animals to sandflies, per capita biting rate of sandflies of animals, and rate of transfer from symptomatic infected animals to the recovered class are among the most sensitive parameters that have the greatest influence on the basic reproduction number. Moreover, the value of the basic reproduction number is obtained to be 0.98951, which may require further study, as the margin between potential disease control and outbreak is thin. Full article

(This article belongs to the Special Issue Mathematical Biology and Its Applications to Disease Modeling)

30 pages, 928 KiB

Open AccessArticle

A Matheuristic Approach Based on Variable Neighborhood Search for the Static Repositioning Problem in Station-Based Bike-Sharing Systems

by Julio Mario Daza-Escorcia and David Álvarez-Martínez

Mathematics 2024, 12(22), 3573; https://doi.org/10.3390/math12223573 (registering DOI) - 15 Nov 2024

Abstract

In this paper, we study a novel static bike-sharing repositioning problem. There is a set of stations spread over a given area, each containing a number of operative bikes, damaged bikes, and free slots. The customers may pick up an operative bike [...] Read more.

In this paper, we study a novel static bike-sharing repositioning problem. There is a set of stations spread over a given area, each containing a number of operative bikes, damaged bikes, and free slots. The customers may pick up an operative bike from a station, use it, and return it to another station. Each station should have a target number of operative bikes to make it likely to meet customer demands. Furthermore, the damaged bikes should be removed from the stations. Given a fleet of available vehicles, the repositioning problem consists of designing the vehicles’ routes and calculating the number of operative (usable) and damaged (unusable) bikes that will be moved (loading instructions/loading policy) between stations and/or the depot. The objective is to minimize the weighted sum of the deviation from the target number of bikes for each station, the number of damaged bikes not removed, and the total time used by vehicles. To solve this problem, we propose a matheuristic based on a variable neighborhood search combined with several improving algorithms, including an integer linear programming model to optimize loading instructions. The algorithm was tested in instances based on real-world data and could find good solutions in reasonable computing times. Full article

29 pages, 3171 KiB

Open AccessArticle

Enhanced Semi-Supervised Medical Image Classification Based on Dynamic Sample Reweighting and Pseudo-Label Guided Contrastive Learning (DSRPGC)

by Kun Liu, Ji Liu and Sidong Liu

Mathematics 2024, 12(22), 3572; https://doi.org/10.3390/math12223572 (registering DOI) - 15 Nov 2024

Abstract

In semi-supervised learning (SSL) for medical image classification, model performance is often hindered by the scarcity of labeled data and the complexity of unlabeled data. This paper proposes an enhanced SSL approach to address these challenges by effectively utilizing unlabeled data through a [...] Read more.

In semi-supervised learning (SSL) for medical image classification, model performance is often hindered by the scarcity of labeled data and the complexity of unlabeled data. This paper proposes an enhanced SSL approach to address these challenges by effectively utilizing unlabeled data through a combination of pseudo-labeling and contrastive learning. The key contribution of our method is the introduction of a Dynamic Sample Reweighting strategy to select reliable unlabeled samples, thereby improving the model’s utilization of unlabeled data. Additionally, we incorporate multiple data augmentation strategies based on the Mean Teacher (MT) model to ensure consistent outputs across different perturbations. To better capture and integrate multi-scale features, we propose a novel feature fusion network, the Medical Multi-scale Feature Fusion Network (MedFuseNet), which enhances the model’s ability to classify complex medical images. Finally, we introduce a pseudo-label guided contrastive learning (PGC) loss function that improves intra-class compactness and inter-class separability of the model’s feature representations. Extensive experiments on three public medical image datasets demonstrate that our method outperforms existing SSL approaches, achieving 93.16% accuracy on the ISIC2018 dataset using only 20% labeled data, highlighting the potential of our approach to advance medical image classification under limited supervision. Full article

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23 pages, 686 KiB

Open AccessArticle

A System of Tensor Equations over the Dual Split Quaternion Algebra with an Application

by Liuqing Yang, Qing-Wen Wang and Zuliang Kou

Mathematics 2024, 12(22), 3571; https://doi.org/10.3390/math12223571 (registering DOI) - 15 Nov 2024

Abstract

In this paper, we propose a definition of block tensors and the real representation of tensors. Equipped with the simplification method, i.e., the real representation along with the M-P inverse, we demonstrate the conditions that are necessary and sufficient for the system of [...] Read more.

In this paper, we propose a definition of block tensors and the real representation of tensors. Equipped with the simplification method, i.e., the real representation along with the M-P inverse, we demonstrate the conditions that are necessary and sufficient for the system of dual split quaternion tensor equations

(A *_{N} X, X *_{S} C) = (B, D)

, when its solution exists. Furthermore, the general expression of the solution is also provided when the solution of the system exists, and we use a numerical example to validate it in the last section. To the best of our knowledge, this is the first time that the aforementioned tensor system has been examined on dual split quaternion algebra. Additionally, we provide its equivalent conditions when its Hermitian solution

X = X^{*}

and

η

-Hermitian solutions

X = X^{η *}

exist. Subsequently, we discuss two special dual split quaternion tensor equations. Last but not least, we propose an application for encrypting and decrypting two color videos, and we validate this algorithm through a specific example. Full article

(This article belongs to the Special Issue Advances of Linear and Multilinear Algebra)

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15 pages, 451 KiB

Open AccessArticle

Optimal Control of Hydrocarbons’ Hydrogenation with Catalysts

by Maxim Sakharov, Kamila Koledina and Irek Gubaydullin

Mathematics 2024, 12(22), 3570; https://doi.org/10.3390/math12223570 (registering DOI) - 15 Nov 2024

Abstract

In this paper, the optimal control problem of hydrocarbons’ hydrogenation was investigated in the presence of two catalysts—Nickel–Kieselguhr and Raney Nickel. This multistage chemical reaction holds significant practical importance, particularly in the production of high-density fuels. The optimal control problem was reformulated as [...] Read more.

In this paper, the optimal control problem of hydrocarbons’ hydrogenation was investigated in the presence of two catalysts—Nickel–Kieselguhr and Raney Nickel. This multistage chemical reaction holds significant practical importance, particularly in the production of high-density fuels. The optimal control problem was reformulated as a nonlinear global optimization problem and addressed using a modified Mind Evolutionary Computation algorithm. The proposed modifications include methods designed to ensure solution feasibility and ease of practical implementation. Using the proposed method, the performance of the two catalysts was compared under constant temperature conditions and with optimal control strategies. The results demonstrate that selecting an effective catalyst has a greater impact on the reaction’s efficiency than temperature control alone, with the Raney Nickel catalyst consistently outperforming the Nickel–Kieselguhr catalyst by at least 17%. Additionally, the optimization approach was applied to identify a new set of catalyst parameters. The newly obtained catalyst parameters allowed for the improvement of the results of the Raney Nickel catalyst by 18%. The results of all numerical experiments and implementation details are described in the paper. Full article

(This article belongs to the Section Mathematics and Computer Science)

25 pages, 506 KiB

Open AccessArticle

Discrete Pseudo-Quasi Overlap Functions and Their Applications in Fuzzy Multi-Attribute Group Decision-Making

by Mei Jing, Jingqian Wang, Mei Wang and Xiaohong Zhang

Mathematics 2024, 12(22), 3569; https://doi.org/10.3390/math12223569 - 15 Nov 2024

Abstract

The overlap function, a continuous aggregation function, is widely used in classification, decision-making, image processing, etc. Compared to applications, overlap functions have also achieved fruitful results in theory, such as studies on the fundamental properties of overlap functions, various generalizations of the concept, [...] Read more.

The overlap function, a continuous aggregation function, is widely used in classification, decision-making, image processing, etc. Compared to applications, overlap functions have also achieved fruitful results in theory, such as studies on the fundamental properties of overlap functions, various generalizations of the concept, and the construction of additive and multiplicative generators based on overlap functions. However, most of the research studies on the overlap functions mentioned above assume commutativity and continuity, which can limit their practical applications. In this paper, we remove the symmetry and continuity from overlap functions and define discrete pseudo-quasi-overlap functions on finite chains. Meanwhile, we also discuss their related properties. Then, we introduce pseudo-quasi-overlap functions on sub-chains and construct discrete pseudo-quasi-overlap functions on finite chains using these sub-chain functions. Unlike quasi-overlap functions on finite chains generated by the ordinal sum, discrete pseudo-quasi-overlap functions on finite chains constructed through pseudo-quasi-overlap functions on different sub-chains are dissimilar. Eventually, we remove the continuity from pseudo-automorphisms and propose the concept of pseudo-quasi-automorphisms. Based on this, we utilize pseudo-overlap functions, pseudo-quasi-automorphisms, and integral functions to obtain discrete pseudo-quasi-overlap functions on finite chains; moreover, we apply them to fuzzy multi-attribute group decision-making. The results indicate that—compared to overlap functions and pseudo-overlap functions—discrete pseudo-quasi-overlap functions on finite chains have stronger flexibility and a wider range of practical applications. Full article

(This article belongs to the Special Issue Fuzzy Sets and Fuzzy Systems)

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12 pages, 374 KiB

Open AccessReview

Exploring the Percolation Phenomena in Quantum Networks

by Chuanxin Wang, Xinqi Hu and Gaogao Dong

Mathematics 2024, 12(22), 3568; https://doi.org/10.3390/math12223568 - 15 Nov 2024

Abstract

Quantum entanglement as a non-local correlation between particles is critical to the transmission of quantum information in quantum networks (QNs); the key challenge lies in establishing long-distance entanglement transmission between distant targets. This issue aligns with percolation theory, and as a result, an [...] Read more.

Quantum entanglement as a non-local correlation between particles is critical to the transmission of quantum information in quantum networks (QNs); the key challenge lies in establishing long-distance entanglement transmission between distant targets. This issue aligns with percolation theory, and as a result, an entanglement distribution scheme called “Classical Entanglement Percolation” (CEP) has been proposed. While this scheme provides an effective framework, “Quantum Entanglement Percolation” (QEP) indicates a lower percolation threshold through quantum preprocessing strategies, which will modify the network topology. Meanwhile, an emerging statistical theory known as “Concurrence Percolation” reveals the unique advantages of quantum networks, enabling entanglement transmission under lower conditions. It fundamentally belongs to a different universality class from classical percolation. Although these studies have made significant theoretical advancements, most are based on an idealized pure state network model. In practical applications, quantum states are often affected by thermal noise, resulting in mixed states. When these mixed states meet specific conditions, they can be transformed into pure states through quantum operations and further converted into singlets with a certain probability, thereby facilitating entanglement percolation in mixed state networks. This finding greatly broadens the application prospects of quantum networks. This review offers a comprehensive overview of the fundamental theories of quantum percolation and the latest cutting-edge research developments. Full article

(This article belongs to the Special Issue Complex Network Modeling: Theory and Applications, 2nd Edition)

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21 pages, 1206 KiB

Open AccessArticle

Optimal Carbon Pricing and Carbon Footprint in a Two-Stage Production System Under Cap-and-Trade Regulation

by Huo-Yen Tseng, Yung-Fu Huang, Chung-Jen Fu and Ming-Wei Weng

Mathematics 2024, 12(22), 3567; https://doi.org/10.3390/math12223567 - 15 Nov 2024

Abstract

Integrating low-carbon design into products is crucial for reducing carbon emissions throughout their life cycle and promoting sustainable development. Addressing the uncertainty in the carbon footprint resulting from the unknown choice of product material solutions. This paper considers ABC (activity-based costing) along with [...] Read more.

Integrating low-carbon design into products is crucial for reducing carbon emissions throughout their life cycle and promoting sustainable development. Addressing the uncertainty in the carbon footprint resulting from the unknown choice of product material solutions. This paper considers ABC (activity-based costing) along with the components’ carbon footprint and scrap return issues to illustrate the above challenge in a two-stage production-inventory system with imperfect processes. We determine the optimal production and sales strategies that maximize total profit per unit time. An algorithm is developed to identify these optimal solutions. To illustrate the effectiveness of the proposed model and algorithm, two numerical examples from the Taiwan die casting industry are presented. Additionally, a sensitivity analysis is conducted to provide valuable managerial insights. Full article

(This article belongs to the Special Issue Advances in Modern Supply Chain Management and Information Technology)

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23 pages, 503 KiB

Open AccessFeature PaperArticle

Mathematical Formalization and Applications to Data with Excess of Zeros and Ones of the Unit-Proportional Hazard Inflated Models

by Guillermo Martínez-Flórez, Roger Tovar-Falón and Héctor W. Gómez

Mathematics 2024, 12(22), 3566; https://doi.org/10.3390/math12223566 - 15 Nov 2024

Abstract

In this study, we model the rate or proportion of a specific phenomenon using a set of known covariates. To fit the regression model, which explains the phenomenon within the intervals

(0, 1)

,

[0, 1)

, [...] Read more.

In this study, we model the rate or proportion of a specific phenomenon using a set of known covariates. To fit the regression model, which explains the phenomenon within the intervals

(0, 1)

,

[0, 1)

,

(0, 1]

, or

[0, 1]

, we employ a logit link function. This approach ensures that the model’s predictions remain within the appropriate range of zero to one. In cases of inflation at zero, one, or both, the logit link function is similarly applied to model the dichotomous Bernoulli-type variable with a multinomial response. The findings demonstrate that the model yields a non-singular information matrix, ensuring valid statistical inference. This ensures the invertibility of the information matrix, allowing for hypothesis testing based on likelihood statistics regarding the parameters in the model. This is not possible with other asymmetric models, such as those derived from the skew-normal distribution, which has a singular information matrix at the boundary of the skewness parameter. Finally, empirical results show the model’s effectiveness in analyzing proportion data with inflation at zero and one, proving its robustness and practicality for analyzing bounded data in various fields of research. Full article

(This article belongs to the Special Issue New Advances in Distribution Theory and Its Applications)

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15 pages, 294 KiB

Open AccessArticle

On Convergence of Toeplitz Quantization of the Sphere

by Yanlin Li, Mohamed Lemine H. Bouleryah and Akram Ali

Mathematics 2024, 12(22), 3565; https://doi.org/10.3390/math12223565 - 14 Nov 2024

Abstract

In this paper, we give an explicit expression of the Toeplitz quantization of a

C^{\infty}

smooth function on the sphere and show that the sequence of spectra of Toeplitz quantization of the function determines its decreasing rearrangement. We also use Toeplitz quantization [...] Read more.

In this paper, we give an explicit expression of the Toeplitz quantization of a

C^{\infty}

smooth function on the sphere and show that the sequence of spectra of Toeplitz quantization of the function determines its decreasing rearrangement. We also use Toeplitz quantization to prove a version of Szegö’s Theorem. Full article

(This article belongs to the Special Issue Advances in Differential Geometry and Its Applications, 2nd Edition)

12 pages, 321 KiB

Open AccessArticle

Calibration of the Ueno’s Shadow Rate Model of Interest Rates

by Lenka Košútová and Beáta Stehlíková

Mathematics 2024, 12(22), 3564; https://doi.org/10.3390/math12223564 - 14 Nov 2024

Abstract

Shadow rate models of interest rates are based on the assumption that the interest rates are determined by an unobservable shadow rate. This idea dates back to Fischer Black, who understood the interest rate as an option that cannot become negative. Its possible [...] Read more.

Shadow rate models of interest rates are based on the assumption that the interest rates are determined by an unobservable shadow rate. This idea dates back to Fischer Black, who understood the interest rate as an option that cannot become negative. Its possible zero values are consequences of negative values of the shadow rate. In recent years, however, the negative interest rates have become a reality. To capture this behavior, shadow rate models need to be adjusted. In this paper, we study Ueno’s model, which uses the Vasicek process for the shadow rate and adjusts its negative values when constructing the short rate. We derive the probability properties of the short rate in this model and apply the maximum likelihood estimation method to obtain the parameters from the real data. The other interest rates are—after a specification of the market price of risk—solutions to a parabolic partial differential equation. We solve the equation numerically and use the long-term rates to fit the market price of risk. Full article

(This article belongs to the Special Issue Recent Advances on Nonlinear Models in Mathematical Finance, 2nd Edition)

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20 pages, 6939 KiB

Open AccessArticle

A Steepest Ascent Analysis Based on an Experimental Approach for the Hardening Process of a Steel Alloy

by Paulo Eduardo García-Nava, Gabriel Plascencia-Barrera, Luis Alberto Rodríguez-Picón, Roal Torres-Sánchez and Rafael García-Martínez

Mathematics 2024, 12(22), 3563; https://doi.org/10.3390/math12223563 - 14 Nov 2024

Abstract

A significant number of alloyed metals applied for different purposes are currently available in industry. The hardness of a piece is an important parameter to consider. The tempering process is widely used to change a metal’s hardness, which is obtained using a hardness [...] Read more.

A significant number of alloyed metals applied for different purposes are currently available in industry. The hardness of a piece is an important parameter to consider. The tempering process is widely used to change a metal’s hardness, which is obtained using a hardness test. Once the response is obtained, a way to evaluate the system is by performing an analysis of variance to verify the significance of terms and obtain a regression equation to improve the response. The aim of this work is to illustrate the implementation of an experimental approach based on the steepest ascent method and stopping rules for optimization purposes by considering the hardening process of the steel alloy 4140. The regression coefficients obtained from an experimental design were used to build the steepest path of improvement. The Myers and Khuri stopping rule and the enhanced parabolic stopping rule were applied to determine the best value while individual experimentation is developed. The obtained results, discussion, and a conclusive analysis are disclosed in this document. Full article

(This article belongs to the Special Issue Mathematical Applications in Industrial Engineering)

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25 pages, 2072 KiB

Open AccessFeature PaperArticle

Full Forward Kinematics of Lower-Mobility Planar Parallel Continuum Robots

by Oscar Altuzarra, Mónica Urizar, Kerman Bilbao and Alfonso Hernández

Mathematics 2024, 12(22), 3562; https://doi.org/10.3390/math12223562 - 14 Nov 2024

Abstract

In rigid lower-mobility parallel manipulators the motion of the end-effector is partially constrained due to a combination of passive kinematic pairs and rigid components. Translational mechanisms, such as the Delta manipulator, are the most common ones among this type of mechanisms. When flexible [...] Read more.

In rigid lower-mobility parallel manipulators the motion of the end-effector is partially constrained due to a combination of passive kinematic pairs and rigid components. Translational mechanisms, such as the Delta manipulator, are the most common ones among this type of mechanisms. When flexible elements are introduced, as in Parallel Continuum Manipulators, the constraint is no longer rigid, and new challenges arise in performing certain motions depending on the degree of compliance. Mobility analysis shifts from being purely a geometric issue to one that heavily relies on force distribution within the mechanism. Simply converting classical lower-mobility rigid parallel mechanisms into Parallel Continuum Mechanisms may yield unexpected outcomes. This work, making use of a planar parallel continuum Delta manipulator, on the one hand, presents two different approaches to solve the Forward Kinematics of planar continuum manipulators, and, on the other hand, explores some challenges and issues in assessing the resultant workspace for different design alternatives of this kind of flexible manipulators. Full article

(This article belongs to the Special Issue Applied Mathematics to Mechanisms and Machines II)

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16 pages, 488 KiB

Open AccessArticle

Model-Following Preview Control for a Class of Linear Descriptor Systems with Actuator Failures

by Chen Jia and Li Li

Mathematics 2024, 12(22), 3561; https://doi.org/10.3390/math12223561 - 14 Nov 2024

Abstract

This paper considers the model-following preview control problem for a class of continuous-time descriptor systems with actuator failures. Firstly, the model-following problem is transformed into an optimal preview control problem by utilizing restricted equivalent transformations and the construction of augmented systems. After discussing [...] Read more.

This paper considers the model-following preview control problem for a class of continuous-time descriptor systems with actuator failures. Firstly, the model-following problem is transformed into an optimal preview control problem by utilizing restricted equivalent transformations and the construction of augmented systems. After discussing the relationship between the stabilizability and detectability of the augmented system and the corresponding characteristics of the controlled system, the model-following preview controller of the original descriptor system is obtained by integrating on the controller of the augmented system. Finally, an application to electrical circuit system is used for assessment purposes. The simulation results demonstrate the effectiveness of the proposed controller. Full article

23 pages, 5357 KiB

Open AccessArticle

Convective Heat Transfer in Uniformly Accelerated and Decelerated Turbulent Pipe Flows

by Ismael Essarroukh and José M. López

Mathematics 2024, 12(22), 3560; https://doi.org/10.3390/math12223560 - 14 Nov 2024

Abstract

This study presents a detailed investigation of the temporal evolution of the Nusselt number (

N u

) in uniformly accelerated and decelerated turbulent pipe flows under a constant heat flux using direct numerical simulations. The influence of different acceleration and deceleration rates [...] Read more.

This study presents a detailed investigation of the temporal evolution of the Nusselt number (

N u

) in uniformly accelerated and decelerated turbulent pipe flows under a constant heat flux using direct numerical simulations. The influence of different acceleration and deceleration rates on heat transfer is systematically studied, addressing a gap in the previous research. The simulations confirm several key experimental findings, including the presence of three distinct phases in the Nusselt number temporal response—delay, recovery, and quasi-steady phases—as well as the characteristics of thermal structures in unsteady pipe flow. In accelerated flows, the delay in the turbulence response to changes in velocity results in reduced heat transfer, with average

N u

values up to

48 %

lower than those for steady-flow conditions at the same mean Reynolds number. Conversely, decelerated flows exhibit enhanced heat transfer, with average

N u

exceeding steady values by up to

42 %

due to the onset of secondary instabilities that amplify turbulence. To characterize the

N u

response across the full range of acceleration and deceleration rates, a new model based on a hyperbolic tangent function is proposed, which provides a more accurate description of the heat transfer response than previous models. The results suggest the potential to design unsteady periodic cycles, combining slow acceleration and rapid deceleration, to enhance heat transfer compared to steady flows. Full article

(This article belongs to the Special Issue Numerical Simulation and Methods in Computational Fluid Dynamics)

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27 pages, 1901 KiB

Open AccessArticle

Multiobjective Route Optimization for Multimodal Cold Chain Networks Considering Carbon Emissions and Food Waste

by Yong Peng, Yali Zhang, Dennis Z. Yu and Yijuan Luo

Mathematics 2024, 12(22), 3559; https://doi.org/10.3390/math12223559 - 14 Nov 2024

Abstract

The cold chain logistics industry faces significant challenges in terms of transportation costs and carbon emissions. It is imperative to plan multimodal transportation routes efficiently to address these issues, minimize food waste, and reduce carbon emissions. This paper focuses on four key optimization [...] Read more.

The cold chain logistics industry faces significant challenges in terms of transportation costs and carbon emissions. It is imperative to plan multimodal transportation routes efficiently to address these issues, minimize food waste, and reduce carbon emissions. This paper focuses on four key optimization objectives for multimodal cold chain transport: minimizing total transportation time, costs, carbon emissions, and food waste. To tackle these objectives, we propose a high-dimensional multiobjective route optimization model for multimodal cold chain networks. Our approach involves the development of a multiobjective evolutionary algorithm, utilizing Monte Carlo simulation and a one-by-one selection strategy. We evaluate the proposed algorithm’s performance by analyzing various convergence and distribution indicators. The average values for the minimum total transportation time, transportation cost, carbon emission cost, and cargo loss rate derived from the proposed algorithm ultimately converge to 6721.7, 5184.4, 301.5, and 0.21, respectively, demonstrating the effectiveness of the algorithmic solution. Additionally, we benchmark our algorithm against the existing literature to showcase its efficiency in solving high-dimensional multi-objective route optimization problems. Furthermore, we investigate the impact of different parameters, such as carbon tax rates, temperature, and cargo activation energy, on carbon emissions, and food waste. Moreover, we conduct a real-world case study to apply our approach to solving a practical business problem related to multimodal cold chain transportation. The insights gained from this research offer valuable decision-making support for multimodal carriers in developing low-carbon and environmentally friendly transportation strategies to efficiently transport perishable goods. Full article

(This article belongs to the Special Issue Mathematical Programming, Optimization and Operations Research)

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