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Effects of Small Random Perturbations in the Extended Glass–Kauffman Model of Gene Regulatory Networks Mathematics (IF 2.4) Pub Date : 2024-04-18 Arcady Ponosov, Irina Shlykova, Ramazan I. Kadiev
A mathematical justification of some basic structural properties of stochastically perturbed gene regulatory networks, including those with autoregulation and delay, is offered in this paper. By using the theory of stochastic differential equations, it is, in particular, shown how to control the asymptotic behavior of the diffusion terms in order to not destroy certain qualitative features of the networks
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Disturbing Fuzzy Multi-Attribute Decision-Making Method with If Weight Information Is Disturbing Fuzzy Number Mathematics (IF 2.4) Pub Date : 2024-04-19 Li Li, Jin Yang
Fuzzy multi-attribute decision-making is a hot research topic in which weight information is one of the conditions for forming a complete decision-making model, and it is also an important factor affecting the decision result. In most fuzzy multi-attribute decision-making problems, the weight information is often given in the form of real numbers. However, in real life, the weight information may not
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A Speech Adversarial Sample Detection Method Based on Manifold Learning Mathematics (IF 2.4) Pub Date : 2024-04-19 Xiao Ma, Dongliang Xu, Chenglin Yang, Panpan Li, Dong Li
Deep learning-based models have achieved impressive results across various practical fields. However, these models are susceptible to attacks. Recent research has demonstrated that adversarial samples can significantly decrease the accuracy of deep learning models. This susceptibility poses considerable challenges for their use in security applications. Various methods have been developed to enhance
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RUL Prediction for Piezoelectric Vibration Sensors Based on Digital-Twin and LSTM Network Mathematics (IF 2.4) Pub Date : 2024-04-19 Chengcheng Fu, Cheng Gao, Weifang Zhang
Piezoelectric vibration sensors (PVSs) are widely used in high-temperature environments, such as vibration measurements in aero-engines, because of their high accuracy, small size, and high temperature resistance. Accurate prediction of its RUL (Remaining Useful Life) is essential for applying and maintaining PVSs. Based on PVSs’ characteristics and main failure modes, this work combines the Digital-Twin
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Brain-Inspired Agents for Quantum Reinforcement Learning Mathematics (IF 2.4) Pub Date : 2024-04-19 Eva Andrés, Manuel Pegalajar Cuéllar, Gabriel Navarro
In recent years, advancements in brain science and neuroscience have significantly influenced the field of computer science, particularly in the domain of reinforcement learning (RL). Drawing insights from neurobiology and neuropsychology, researchers have leveraged these findings to develop novel mechanisms for understanding intelligent decision-making processes in the brain. Concurrently, the emergence
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LLE-NET: A Low-Light Image Enhancement Algorithm Based on Curve Estimation Mathematics (IF 2.4) Pub Date : 2024-04-19 Xiujie Cao, Jingjun Yu
Low-light image enhancement is very significant for vision tasks. We introduce Low-light Image Enhancement via Deep Learning Network (LLE-NET), which employs a deep network to estimate curve parameters. Cubic curves and gamma correction are employed for enhancing low-light images. Our research trains a lightweight network to estimate the parameters that determine the correction curve. By the results
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A Coupled, Global/Local Finite Element Methodology to Evaluate the Fatigue Life of Flexible Risers Attached to Floating Platforms for Deepwater Offshore Oil Production Mathematics (IF 2.4) Pub Date : 2024-04-19 Monique de Carvalho Alves, Fabrício Nogueira Corrêa, José Renato Mendes de Sousa, Breno Pinheiro Jacob
This study introduces a Finite Element (FE) hybrid methodology for analyzing deepwater offshore oil and gas floating production systems. In these systems, flexible risers convey the production and are connected to a balcony on one side of the platform. The proposed methodology couples, in a cost-effective manner, the hydrodynamic model of the platform with the FE model that represents the risers and
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Algorithm for Determination of Indicators Predicting Health Status for Health Monitoring Process Optimization Mathematics (IF 2.4) Pub Date : 2024-04-19 Aleksandras Krylovas, Natalja Kosareva, Stanislav Dadelo
This article proposes an algorithm that allows the selection of prognostic variables from a set of 21 variables describing the health statuses of male and female students. The set of variables could be divided into two groups—body condition indicators and body activity indicators. For this purpose, we propose applying the multiple criteria decision methods WEBIRA, entropy-ARAS, and SAW in modelling
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Measurement and Forecasting of Systemic Risk: A Vine Copula Grouped-CoES Approach Mathematics (IF 2.4) Pub Date : 2024-04-19 Huiting Duan, Jinghu Yu, Linxiao Wei
Measuring systemic risk plays an important role in financial risk management to control systemic risk. By means of a vine copula grouped-CoES method, this paper aims to measure the systemic risk of Chinese financial markets. The empirical study indicates that the banking industry has a low risk and a strong ability to resist risks, but also contributes the most of the systemic risk. On the other hand
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Hybrid Optimization Method Based on Coupling Local Gradient Information and Global Evolution Mechanism Mathematics (IF 2.4) Pub Date : 2024-04-19 Caicheng Zhu, Xin Zhao, Xinlei He, Zhili Tang
Multi-objective evolutionary algorithms (MOEA) have attracted much attention because of their good global exploration ability; however, their local search ability near the optimal value is weak, and for large-scale decision-variable optimization problems the number of populations and iterations required by MOEA are very large, so the optimization efficiency is low. Gradient optimization algorithms
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VSD: A Novel Method for Video Segmentation and Storage in DNA Using RS Code Mathematics (IF 2.4) Pub Date : 2024-04-19 Jingwei Hong, Abdur Rasool, Shuo Wang, Djemel Ziou, Qingshan Jiang
As data continue to grow in complexity and size, there is an imperative need for more efficient and robust storage solutions. DNA storage has emerged as a promising avenue to solve this problem, but existing approaches do not perform efficiently enough on video data, particularly for information density and time efficiency. This paper introduces VSD, a pioneering encoding method for video segmentation
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The Stability of Solutions of the Variable-Order Fractional Optimal Control Model for the COVID-19 Epidemic in Discrete Time Mathematics (IF 2.4) Pub Date : 2024-04-19 Meriem Boukhobza, Amar Debbouche, Lingeshwaran Shangerganesh, Juan J. Nieto
This article introduces a discrete-time fractional variable order over a SEIQR model, incorporated for COVID-19. Initially, we establish the well-possedness of solution. Further, the disease-free and the endemic equilibrium points are determined. Moreover, the local asymptotic stability of the model is analyzed. We develop a novel discrete fractional optimal control problem tailored for COVID-19, utilizing
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Hyers–Ulam Stability of 2D-Convex Mappings and Some Related New Hermite–Hadamard, Pachpatte, and Fejér Type Integral Inequalities Using Novel Fractional Integral Operators Via Totally Interval-Order Relations with Open Problem Mathematics (IF 2.4) Pub Date : 2024-04-19 Waqar Afzal, Daniel Breaz, Mujahid Abbas, Luminiţa-Ioana Cotîrlă, Zareen A. Khan, Eleonora Rapeanu
The aim of this paper is to introduce a new type of two-dimensional convexity by using total-order relations. In the first part of this paper, we examine the Hyers–Ulam stability of two-dimensional convex mappings by using the sandwich theorem. Our next step involves the development of Hermite–Hadamard inequality, including its weighted and product forms, by using a novel type of fractional operator
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A Sustainable Supply Chain Model with Low Carbon Emissions for Deteriorating Imperfect-Quality Items under Learning Fuzzy Theory Mathematics (IF 2.4) Pub Date : 2024-04-19 Basim S. O. Alsaedi, Marwan H. Ahelali
In this paper, we develop a two-level supply chain model with low carbon emissions for defective deteriorating items under learning in fuzzy environment by using the double inspection process. Carbon emissions are a major issue for the environment and human life when they come from many sources like different kinds of factories, firms, and industries. The burning of diesel and petrol during the supply
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Spatial Decay Estimates and Continuous Dependence for the Oldroyd Fluid Mathematics (IF 2.4) Pub Date : 2024-04-19 Yuanfei Li
This article investigates the Oldroyd fluid, which is widely used in industrial and engineering environments. When the Oldroyd fluid passes through a three-dimensional semi-infinite cylinder, the asymptotic properties of the solutions are established. On this basis, we also studied the continuous dependence of the viscosity coefficient.
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Rigidity of Holomorphically Projective Mappings of Kähler Spaces with Finite Complete Geodesics Mathematics (IF 2.4) Pub Date : 2024-04-19 Lenka Vítková, Irena Hinterleitner, Josef Mikeš
In this work, we consider holomorphically projective mappings of (pseudo-) Kähler spaces. We determine the conditions for finite complete geodesics that must be satisfied for the mappings to be trivial; i.e., these spaces are rigid.
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Bridging the p-Special Functions between the Generalized Hyperbolic and Trigonometric Families Mathematics (IF 2.4) Pub Date : 2024-04-19 Ali Hamzah Alibrahim, Saptarshi Das
Here, we study the extension of p-trigonometric functions sinp and cosp family in complex domains and p-hyperbolic functions sinhp and the coshp family in hyperbolic complex domains. These functions satisfy analogous relations as their classical counterparts with some unknown properties. We show the relationship of these two classes of special functions viz. p-trigonometric and p-hyperbolic functions
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Modeling the Propagation of Infectious Diseases across the Air Transport Network: A Bayesian Approach Mathematics (IF 2.4) Pub Date : 2024-04-19 Pablo Quirós Corte, Javier Cano, Eduardo Sánchez Ayra, Chaitanya Joshi, Víctor Fernando Gómez Comendador
The COVID-19 pandemic, caused by the SARS-CoV-2 virus, continues to impact the world even three years after its outbreak. International border closures and health alerts severely affected the air transport industry, resulting in substantial financial losses. This study analyzes the global data on infected individuals alongside aircraft types, flight durations, and passenger flows. Using a Bayesian
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Blockchain-Enabled Utility Optimization for Supply Chain Finance: An Evolutionary Game and Smart Contract Based Approach Mathematics (IF 2.4) Pub Date : 2024-04-19 Shenghua Wang, Mengjie Zhou, Sunan Xiang
In recent years, blockchain technology has attracted substantial interest for its capability to transform supply chain management and finance. This paper employs evolutionary game theory to investigate the application of blockchain in mitigating financial risks within supply chains, taking into account the technology’s maturity and the risk preferences of financial institutions. By modeling interactions
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Spatial Constraints on Economic Interactions: A Complexity Approach to the Japanese Inter-Firm Trade Network Mathematics (IF 2.4) Pub Date : 2024-04-19 Eduardo Viegas, Orr Levy, Shlomo Havlin, Hideki Takayasu, Misako Takayasu
The trade distance is an important constraining factor underpinning the emergence of social and economic interactions of complex systems. However, agent-based studies supported by the granular analysis of distances are limited. Here, we present a complexity method that places the actual geographical locations of individual firms in Japan at the epicentre of our research. By combining methods derived
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Bidirectional Tracking Method for Construction Workers in Dealing with Identity Errors Mathematics (IF 2.4) Pub Date : 2024-04-19 Yongyue Liu, Yaowu Wang, Zhenzong Zhou
Online multi-object tracking (MOT) techniques are instrumental in monitoring workers’ positions and identities in construction settings. Traditional approaches, which employ deep neural networks (DNNs) for detection followed by body similarity matching, often overlook the significance of clear head features and stable head motions. This study presents a novel bidirectional tracking method that integrates
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Comparison of MOEAs in an Optimization-Decision Methodology for a Joint Order Batching and Picking System Mathematics (IF 2.4) Pub Date : 2024-04-19 Fabio Maximiliano Miguel, Mariano Frutos, Máximo Méndez, Fernando Tohmé, Begoña González
This paper investigates the performance of a two-stage multi-criteria decision-making procedure for order scheduling problems. These problems are represented by a novel nonlinear mixed integer program. Hybridizations of three Multi-Objective Evolutionary Algorithms (MOEAs) based on dominance relations are studied and compared to solve small, medium, and large instances of the joint order batching and
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DAGOR: Learning DAGs via Topological Sorts and QR Factorization Mathematics (IF 2.4) Pub Date : 2024-04-17 Hao Zuo, Jinshen Jiang, Yun Zhou
Recently, the task of acquiring causal directed acyclic graphs (DAGs) from empirical data has been modeled as an iterative process within the framework of continuous optimization with a differentiable acyclicity characterization. However, learning DAGs from data is an NP-hard problem since the DAG space increases super-exponentially with the number of variables. In this work, we introduce the graph
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A Novel Method for Boosting Knowledge Representation Learning in Entity Alignment through Triple Confidence Mathematics (IF 2.4) Pub Date : 2024-04-18 Xiaoming Zhang, Tongqing Chen, Huiyong Wang
Entity alignment is an important task in knowledge fusion, which aims to link entities that have the same real-world identity in two knowledge graphs. However, in the process of constructing a knowledge graph, some noise may inevitably be introduced, which must affect the results of the entity alignment tasks. The triple confidence calculation can quantify the correctness of the triples to reduce the
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Deep Reinforcement Learning for Network Dismantling: A K-Core Based Approach Mathematics (IF 2.4) Pub Date : 2024-04-18 Tianle Pu, Li Zeng, Chao Chen
Network dismantling is one of the most challenging problems in complex systems. This problem encompasses a broad array of practical applications. Previous works mainly focus on the metrics such as the number of nodes in the Giant Connected Component (GCC), average pairwise connectivity, etc. This paper introduces a novel metric, the accumulated 2-core size, for assessing network dismantling. Due to
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A Two-Stage Method for Aerial Tracking in Adverse Weather Conditions Mathematics (IF 2.4) Pub Date : 2024-04-18 Yuan Feng, Xinnan Xu, Nuoyi Chen, Quanjian Song, Lufang Zhang
To tackle the issue of aerial tracking failure in adverse weather conditions, we developed an innovative two-stage tracking method, which incorporates a lightweight image restoring model DADNet and an excellent pretrained tracker. Our method begins by restoring the degraded image, which yields a refined intermediate result. Then, the tracker capitalizes on this intermediate result to produce precise
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Spectral Properties of Mimetic Operators for Robust Fluid–Structure Interaction in the Design of Aircraft Wings Mathematics (IF 2.4) Pub Date : 2024-04-18 J. de Curtò, I. de Zarzà
This paper presents a comprehensive study on the spectral properties of mimetic finite-difference operators and their application in the robust fluid–structure interaction (FSI) analysis of aircraft wings under uncertain operating conditions. By delving into the eigenvalue behavior of mimetic Laplacian operators and extending the analysis to stochastic settings, we develop a novel stochastic mimetic
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Multi-Objective Optimization for A Partial Disassembly Line Balancing Problem Considering Profit and Carbon Emission Mathematics (IF 2.4) Pub Date : 2024-04-18 Wanlin Yang, Zixiang Li, Chenyu Zheng, Zikai Zhang, Liping Zhang, Qiuhua Tang
Disassembly lines are widely utilized to disassemble end-of-life products. Most of the research focuses on the complete disassembly of obsolete products. However, there is a lack of studies on profit and on carbon emission saved. Hence, this study considers the multi-objective partial disassembly line balancing problem with AND/OR precedence relations to optimize profit, saved carbon emission and line
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Linear Parameter Varying Observer-Based Adaptive Dynamic Surface Sliding Mode Control for PMSM Mathematics (IF 2.4) Pub Date : 2024-04-18 Tongtong Li, Liang Tao, Binzi Xu
This paper presents an adaptive dynamic surface sliding mode control technique to address the issue of system parameter changes in permanent magnet synchronous motor (PMSM) position servo systems. The proposed method involves adopting a linear parameter varying (LPV) observer-based parameter identification algorithm and adaptive control technique. Initially, a mathematical model of the PMSM is established
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Does Herding and Anti-Herding Reflect Portfolio Managers’ Abilities in Emerging Markets? Mathematics (IF 2.4) Pub Date : 2024-04-18 Dachen Sheng, Heather A. Montgomery
This study investigates the relationship between herding behaviors and the abilities of Chinese mutual fund managers. Adapting existing methodologies to suit the low information disclosure environment of the Chinese market, we measure herding behaviors and managers’ abilities. Our analysis goes beyond traditional approaches by examining the contribution of herding outcomes to picking and timing abilities
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Evaluation of the Dynamic Amplification Factors of a Monorail Tourism Transit System Based on Probability Statistics Mathematics (IF 2.4) Pub Date : 2024-04-18 Fengqi Guo, Chenjia Li, Qiaoyun Liao, Yongfeng Yan, Changxing Wu, Liqiang Jiang
The straddle monorail tourist transportation system (MTTS) has developed rapidly in recent years, and its structure is an elevated steel structure with a beam–column system, and the design is executed according to the Safety Code for Large Amusement Rides (GB 8408-2018). However, the impact coefficient value of this code is deemed partially unreasonable. Based on this, relying on the Seven Colors Yunnan
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Enhancing Energy Efficiency of Thermomagnetic Generators: A Comprehensive Study on Frequency and Heat Dissipation Mathematics (IF 2.4) Pub Date : 2024-04-18 Abdulrahman Homadi, Abd Alhamid Rafea Sarhan
This study explores the design and optimization of thermomagnetic generators with a primary emphasis on enhancing energy efficiency. The core objectives revolve around improving power generation and efficient heat dissipation. We conducted an extensive investigation, systematically varying parameters such as dimensions, coil turns, and material properties, including temperatures and magnetization.
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Estimating the Individual Treatment Effect with Different Treatment Group Sizes Mathematics (IF 2.4) Pub Date : 2024-04-18 Luyuan Song, Xiaojun Zhang
Machine learning for causal inference, particularly at the individual level, has attracted intense interest in many domains. Existing techniques focus on controlling differences in distribution between treatment groups in a data-driven manner, eliminating the effects of confounding factors. However, few of the current methods adequately discuss the difference in treatment group sizes. Two approaches
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Using Physics-Informed Neural Networks (PINNs) for Tumor Cell Growth Modeling Mathematics (IF 2.4) Pub Date : 2024-04-16 José Alberto Rodrigues
This paper presents a comprehensive investigation into the applicability and performance of two prominent growth models, namely, the Verhulst model and the Montroll model, in the context of modeling tumor cell growth dynamics. Leveraging the power of Physics-Informed Neural Networks (PINNs), we aim to assess and compare the predictive capabilities of these models against experimental data obtained
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Adaptive Backstepping Time Delay Control for Precision Positioning Stage with Unknown Hysteresis Mathematics (IF 2.4) Pub Date : 2024-04-17 Zhifu Li, Jiawei Li, Tao Weng, Ziyang Zheng
Piezoelectric-actuated precision positioning stages are widely used in high-precision instruments and high-end equipment due to their advantages of high resolution, fast response, and compact size. However, due to the strong nonlinearity of hysteresis, the presence of hysteresis in piezoelectric actuators seriously affects the positioning accuracy of the system. In addition, it is challenging to identify
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A Bibliometric Analysis of a Genetic Algorithm for Supply Chain Agility Mathematics (IF 2.4) Pub Date : 2024-04-17 Weng Hoe Lam, Weng Siew Lam, Pei Fun Lee
As a famous population-based metaheuristic algorithm, a genetic algorithm can be used to overcome optimization complexities. A genetic algorithm adopts probabilistic transition rules and is suitable for parallelism, which makes this algorithm attractive in many areas, including the logistics and supply chain sector. To obtain a comprehensive understanding of the development in this area, this paper
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Instance Segmentation of Sparse Point Clouds with Spatio-Temporal Coding for Autonomous Robot Mathematics (IF 2.4) Pub Date : 2024-04-17 Na Liu, Ye Yuan, Sai Zhang, Guodong Wu, Jie Leng, Lihong Wan
In the study of Simultaneous Localization and Mapping (SLAM), the existence of dynamic obstacles will have a great impact on it, and when there are many dynamic obstacles, it will lead to great challenges in mapping. Therefore, segmenting dynamic objects in the environment is particularly important. The common data format in the field of autonomous robots is point clouds. How to use point clouds to
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Automatic Differentiation-Based Multi-Start for Gradient-Based Optimization Methods Mathematics (IF 2.4) Pub Date : 2024-04-17 Francesco Della Santa
In global optimization problems, diversification approaches are often necessary to overcome the convergence toward local optima. One approach is the multi-start method, where a set of different starting configurations are taken into account to designate the best local minimum returned by the multiple optimization procedures as the (possible) global optimum. Therefore, parallelization is crucial for
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Efficient 5.8 GHz Microstrip Antennas for Intelligent Transportation Systems: Design, Fabrication, and Performance Analysis Mathematics (IF 2.4) Pub Date : 2024-04-17 Muhammet Tahir Guneser, Cihat Seker, Mehmet Izzeddin Guler, Norma Latif Fitriyani, Muhammad Syafrudin
In this study, we designed a high-performance, compact E-shaped microstrip antenna optimized for intelligent transportation systems, operating at 5.8 GHz. Utilizing simulation tools such as CST Studio Suite 2022 Learning Edition, Ansys HFSS 2022 R1, and MATLAB 2022b PCB Antenna Designer, we ensured consistent physical parameters. Fabricated with a 1.6 mm thick FR-4 substrate and a 50 Ω microstrip line-feeding
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Edge Odd Graceful Labeling in Some Wheel-Related Graphs Mathematics (IF 2.4) Pub Date : 2024-04-17 Mohammed Aljohani, Salama Nagy Daoud
A graph’s edge labeling involves the allocation of symbols (colors or numbers) to the edges of a graph governed by specific criteria. Such labeling of a graph G with order n and size m is named edge odd graceful if there is a bijective map φ from the set of edges E(G)={e1,...,em} to the set {1,3,…,2m−1} in a way that the derived transformation φ* from the vertex-set V(G)={v1,...,vn} to the set {0,1
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Contravariant Curvatures of Doubly Warped Product Poisson Manifolds Mathematics (IF 2.4) Pub Date : 2024-04-17 Foued Aloui, Shyamal Kumar Hui, Ibrahim Al-Dayel
In this paper, we investigate the sectional contravariant curvature of a doubly warped product manifold (fB×bF,g˜,Π=ΠB+ΠF) equipped with a product Poisson structure Π, using warping functions and sectional curvatures of its factor manifolds (B,g˜B,ΠB) and (F,g˜F,ΠF). Qualar and null sectional contravariant curvatures of (fB×bF,g˜,Π) are also given. As an example, we construct a four-dimensional Lorentzian
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Stochastic Synchronization of Impulsive Reaction–Diffusion BAM Neural Networks at a Fixed and Predetermined Time Mathematics (IF 2.4) Pub Date : 2024-04-17 Rouzimaimaiti Mahemuti, Ehmet Kasim, Hayrengul Sadik
This paper discusses the synchronization problem of impulsive stochastic bidirectional associative memory neural networks with a diffusion term, specifically focusing on the fixed-time (FXT) and predefined-time (PDT) synchronization. First, a number of more relaxed lemmas are introduced for the FXT and PDT stability of general types of impulsive nonlinear systems. A controller that does not require
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U-Net-Based Learning Using Enhanced Lane Detection with Directional Lane Attention Maps for Various Driving Environments Mathematics (IF 2.4) Pub Date : 2024-04-17 Seung-Hwan Lee, Sung-Hak Lee
Recent advancements in optical and electronic sensor technologies, coupled with the proliferation of computing devices (such as GPUs), have enabled real-time autonomous driving systems to become a reality. Hence, research in algorithmic advancements for advanced driver assistance systems (ADASs) is rapidly expanding, with a primary focus on enhancing robust lane detection capabilities to ensure safe
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Combinatorial Generation Algorithms for Directed Lattice Paths Mathematics (IF 2.4) Pub Date : 2024-04-17 Yuriy Shablya, Arsen Merinov, Dmitry Kruchinin
Graphs are a powerful tool for solving various mathematical problems. One such task is the representation of discrete structures. Combinatorial generation methods make it possible to obtain algorithms that can create discrete structures with specified properties. This article is devoted to issues related to the construction of such combinatorial generation algorithms for a wide class of directed lattice
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Accuracy of Modified Johnson–Cook Modelling of the Blanking Process through Experimental and Numerical Analysis Mathematics (IF 2.4) Pub Date : 2024-04-17 Lotfi Ben Said, Taoufik Kamoun, Hamdi Hentati, Mondher Wali
Metal parts undergo a blanking test that involves experimentation with different process parameters across multiple levels. The presence of uncontrolled burrs (measured as Hbv) significantly affects the precise geometry of the blanked parts, making it a primary concern in precision blanking. Moreover, the maximum blanking force (Fmax) holds considerable significance, as it aids in forecasting fracture
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Summation Formulas for Certain Combinatorial Sequences Mathematics (IF 2.4) Pub Date : 2024-04-17 Yulei Chen, Dongwei Guo
In this work, we establish some characteristics for a sequence, Aα(n,k), including recurrence relations, generating function and inversion formula, etc. Based on the sequence, we derive, by means of the generating function approach, some transformation formulas concerning certain combinatorial numbers named after Lah, Stirling, harmonic, Cauchy and Catalan, as well as several closed finite sums. In
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Improving Unsupervised Network Alignment with Matched Neighborhood Consistency Mathematics (IF 2.4) Pub Date : 2024-04-17 Yan Li, Lei Zhang, Feng Qian
Network alignment is an important technique with applications in diverse domains, such as social network analysis, bioinformatics, and knowledge graph construction. Many of the alignment methods rely on predefined anchor nodes, which are often unavailable in real-world scenarios. To overcome this limitation, we propose MANNA (MAtched Neighbor consistency for Network Alignment), an unsupervised approach
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Analysis of an Interface Crack between Piezoelectric Semiconductor Coating and Elastic Substrate Structure Mathematics (IF 2.4) Pub Date : 2024-04-17 Xiangru Tian, Yali Zhang, Hailiang Ma, Xing Li, Shenghu Ding
Piezoelectric semiconductor materials possess a unique combination of piezoelectric and semiconductor effects, exhibiting multifaceted coupling properties such as electromechanical, acoustic, photoelectric, photovoltaic, thermal, and thermoelectric capabilities. This study delves into the anti-plane mechanical model of an interface crack between a strip of piezoelectric semiconductor material and an
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Stationary Distribution of Stochastic Age-Dependent Population–Toxicant Model with Markov Switching Mathematics (IF 2.4) Pub Date : 2024-04-17 Yanyan Du, Zong Wang
This work focuses on the convergence of the numerical invariant measure for a stochastic age-dependent population–toxicant model with Markov switching. Considering that Euler–Maruyama (EM) has the advantage of fast computation and low cost, explicit EM was used to discretize the time variable. With the help of the p-th moment boundedness of the analytical and numerical solutions of the model, the existence
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A Comprehensive Evaluation of Resilience in Abandoned Open-Pit Mine Slopes Based on a Two-Dimensional Cloud Model with Combination Weighting Mathematics (IF 2.4) Pub Date : 2024-04-17 Liangxing Jin, Pingting Liu, Wenbing Yao, Junjie Wei
The stability of abandoned open-pit mine slopes and their ecological environment are threatened owing to their fragile, complicated, and uncertain characteristics. This study establishes a novel evaluation indicator system for enhancing mine design and environmental protection insight. The weights in the system are assigned using a combined method, which consists of the game theory, the interval analytic
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Evolutionary Game and Simulation Analysis of Food Safety Regulation under Time Delay Effect Mathematics (IF 2.4) Pub Date : 2024-04-15 Tianjun Su, Linhai Wu, Jingxiang Zhang
This study develops a tripartite evolutionary game dynamic model with a time delay effect to analyze the interactions among food enterprise, government regulatory, and food inspection agencies in managing food safety risks. This model enables government regulatory agencies to more accurately assess and predict food safety risks, thereby implementing more effective preventative measures, ensuring the
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Asymptotic and Oscillatory Properties of Third-Order Differential Equations with Multiple Delays in the Noncanonical Case Mathematics (IF 2.4) Pub Date : 2024-04-16 Hail S. Alrashdi, Osama Moaaz, Khaled Alqawasmi, Mohammad Kanan, Mohammed Zakarya, Elmetwally M. Elabbasy
This paper investigates the asymptotic and oscillatory properties of a distinctive class of third-order linear differential equations characterized by multiple delays in a noncanonical case. Employing the comparative method and the Riccati method, we introduce the novel and rigorous criteria to discern whether the solutions of the examined equation exhibit oscillatory behavior or tend toward zero.
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Modeling Error and Nonuniqueness of the Continuous-Time Models Learned via Runge–Kutta Methods Mathematics (IF 2.4) Pub Date : 2024-04-16 Shunpei Terakawa, Takaharu Yaguchi
In the present study, we consider continuous-time modeling of dynamics using observed data and formulate the modeling error caused by the discretization method used in the process. In the formulation, a class of linearized dynamics called Dahlquist’s test equations is used as representative of the target dynamics, and the characteristics of each discretization method for various dynamics are taken
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Lifetime Distribution for a Mixed Redundant System with Imperfect Switch and Components Having Phase–Type Time-to-Failure Distribution Mathematics (IF 2.4) Pub Date : 2024-04-16 Myung-Ki Baek, Heungseob Kim
Recently, a mixed redundancy was introduced among the redundant design strategies to achieve a more reliable system within the equivalent resources. This study deals with a lifetime distribution for a mixed redundant system with an imperfect fault detector/switch. The lifetime distribution model was formulated using a structured continuous Markov chain (CTMC) and considers the time-to-failure (TTF)
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Spatio-Temporal Contrastive Heterogeneous Graph Attention Networks for Session-Based Recommendation Mathematics (IF 2.4) Pub Date : 2024-04-16 Fan Yang, Dunlu Peng
The main goal of session-based recommendation (SBR) is to analyze the list of possible next interaction items through the user’s historical interaction sequence. The existing session recommendation models directly model the session sequence as a graph, and only consider the aggregation of neighbor items based on spatial structure information, ignoring the time information of items. The sparsity of
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New Infinite Classes for Normal Trimagic Squares of Even Orders Using Row–Square Magic Rectangles Mathematics (IF 2.4) Pub Date : 2024-04-16 Can Hu, Fengchu Pan
As matrix representations of magic labelings of related hypergraphs, magic squares and their various variants have been applied to many domains. Among various subclasses, trimagic squares have been investigated for over a hundred years. The existence problem of trimagic squares with singly even orders and orders 16n has been solved completely. However, very little is known about the existence of trimagic
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Modeling and Solution Algorithm for Green Lock Scheduling Problem on Inland Waterways Mathematics (IF 2.4) Pub Date : 2024-04-16 Ziyun Wu, Bin Ji, Samson S. Yu
Inland navigation serves as a vital component of transportation, boasting benefits such as ample capacity and minimal energy consumption. However, it also poses challenges related to achieving navigation efficiency and environmental friendliness. Locks, which are essential for inland waterways, often cause ship passage bottlenecks. This paper focuses on a green lock scheduling problem (GLSP), aiming
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On the Zeros of the Differential Polynomials \({\varphi f^l(f^{(k)})^n-a}\) Mathematics (IF 2.4) Pub Date : 2024-04-16 Jiantang Lu, Junfeng Xu
Letting f be a transcendental meromorphic function, we consider the value distribution of the differential polynomials φfl(f(k))n−a, where φ(¬≡0) is a small function of f, l(≥2), n(≥1), k(≥1) are integers and a is a non-zero constant, and obtain an important inequality concerning the reduced counting function of φfl(f(k))n−a. Our results improve and generalize the results obtained by Xu and Ye, Karmakar
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Temporal High-Order Accurate Numerical Scheme for the Landau–Lifshitz–Gilbert Equation Mathematics (IF 2.4) Pub Date : 2024-04-15 Jiayun He, Lei Yang, Jiajun Zhan
In this paper, a family of temporal high-order accurate numerical schemes for the Landau–Lifshitz–Gilbert (LLG) equation is proposed. The proposed schemes are developed utilizing the Gauss–Legendre quadrature method, enabling them to achieve arbitrary high-order time discretization. Furthermore, the geometrical properties of the LLG equation, such as the preservation of constant magnetization magnitude
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A Comprehensive Interaction in Multiscale Multichannel EEG Signals for Emotion Recognition Mathematics (IF 2.4) Pub Date : 2024-04-15 Yiquan Guo, Bowen Zhang, Xiaomao Fan, Xiaole Shen, Xiaojiang Peng
Electroencephalogram (EEG) is the most preferred and credible source for emotion recognition, where long-short range features and a multichannel relationship are crucial for performance because numerous physiological components function at various time scales and on different channels. We propose a cascade scale-aware adaptive graph convolutional network and cross-EEG transformer (SAG-CET) to explore