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Some Results on Ricci-Yamabe Soliton and Its Cosmological Models

IAENG International Journal of applied mathematics 2025年第4期55卷 979-983页

作者： Pandey, Pankaj Yadav, Santosh Kumar Sharma, Kamakshi Chaturvedi, Braj Bhushan Department of Mathematics School of Chemical Engineering and Physical Sciences Lovely Professional University Punjab Phagwara144411 India Department of Mathematics School of Computer Science & Artificial Intelligence SR University Telangana Warangal506371 India Department of Pure & Applied Mathematics Guru Ghasidas Vishwavidyalaya Chhattisgarh Bilaspur495009 India

This article aims to investigate the characteristics of Ricci-Yamabe Soliton (briefly: (RYS)n). We study the cosmological models on (RYS)4 under Lorentzian para Sasakian (LPS)4 spacetime. Parallel Ricci tensor, Poisson structure and gradient property also reveal on (RYS)n. Example of (RYS)4 constructed to verify the results. © (2025), (International Association of Engineers). All rights reserved.

关键词： Solitons

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On Error-Based Step Size Control for Discontinuous Galerkin Methods for Compressible Fluid Dynamics

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应用数学与计算数学学报 2025年第1期7卷 3-39页

作者： Hendrik Ranocha Andrew R.Winters Hugo Guillermo Castro Lisandro Dalcin Michael Schlottke-Lakemper Gregor J.Gassner Matteo Parsani Applied Mathematics University of HamburgBundesstr.5520146 HamburgGermany Department of Mathematics Applied Mathematics Linköping UniversityLinköpingSweden Extreme Computing Research Center(ECRC) Computer Electrical and Mathematical Science and Engineering Division(CEMSE)King Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Saudi Arabia Applied and Computational Mathematics RWTH Aachen UniversityAachenGermany High-Performance Computing Center Stuttgart University of StuttgartStuttgartGermany Department of Mathematics and Computer Science University of CologneCologneGermany Center for Data and Simulation Science University of CologneCologneGermany Extreme Computing Research Center(ECRC) Computer Electrical and Mathematical Science and Engineering Division(CEMSE)King Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Saudi Arabia Physical Science and Engineering Division(PSE) King Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Saudi Arabia

We study a temporal step size control of explicit Runge-Kutta(RK)methods for com-pressible computational fluid dynamics(CFD),including the Navier-Stokes equations and hyperbolic systems of conservation laws such as the Euler *** demonstrate that error-based approaches are convenient in a wide range of applications and compare them to more classical step size control based on a Courant-Friedrichs-Lewy(CFL)*** numerical examples show that the error-based step size control is easy to use,robust,and efficient,e.g.,for(initial)transient periods,complex geometries,nonlinear shock captur-ing approaches,and schemes that use nonlinear entropy *** demonstrate these properties for problems ranging from well-understood academic test cases to industrially relevant large-scale computations with two disjoint code bases,the open source Julia pack-ages *** with *** and the C/Fortran code SSDC based on PETSc.

关键词： Explicit Runge-Kutta(RK)methods Step size control Compressible fluid dynamics Adaptivity in space and time Shock capturing

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Simulation of Electromagnetic Wave Propagation in Graphene-Coated 1D Photonic Crystals Using the Finite Volume Method

Simulation of Electromagnetic Wave Propagation in Graphene-C...

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2024 International Conference on Interdisciplinary Physics, ICIPs 2024

作者： Negara, Teguh Puja Hardhienata, Hendradi Alatas, Husin Study Program of Computer Science Faculty of Mathematics and Natural Science Universitas Pakuan Bogor Indonesia Theoretical Physics Division Department of Physics Faculty of Mathematics and Natural Science IPB University Bogor Indonesia

A numerical study on the interaction of electromagnetic waves with photonic crystals with one-dimensional periodicity has been carried out using the Finite Volume method. The photonic crystals with one-dimensional periodicity consists of 7 alternating layers of and with thicknesses of and, respectively. Electromagnetic field components have been simulated to propagate through the photonic crystal structure, experiencing reflection and transmission at each layer of the structure. The simulation results show the occurrence of absorption precisely at the Bragg frequency by the photonic crystal, which is referred to as the photonic band gap (PBG). A comparison of the simulation results has been conducted using different fluxes, such as the Lax-Friedrichs and upwind schemes, under PBG conditions. The results show smoother absorption using the Lax-Friedrichs scheme. Additionally, the use of a single-layer graphene on the front side of the photonic crystal has shown more perfect absorption compared to without the single-layer graphene. Therefore, the integrated graphene-photonic crystal system can be used as a perfect reflector. The simulation runs well using effective absorbing boundary conditions (ABCs) to reduce wave reflections at the edges of the computational window. Based on the simulation results, the Finite Volume method has been proven to be a powerful tool in describing electromagnetic wave propagation through photonic crystal systems with or without graphene. These findings provide a foundational model for fabrication approaches and holds potential for future advancements in sensor technologies, moreover two-dimensional and three-dimensional structures. © 2025 Institute of Physics Publishing. All rights reserved.

关键词： Photonic band gap

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Integrative Analysis of Gene Co-Expression Networks Combined with Flux Balance Analysis of Metabolic Models for Insights into Chronic Obstructive Pulmonary Disease 10

Integrative Analysis of Gene Co-Expression Networks Combined...

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10th International Conference on Digital Arts, Media and Technology and 8th ECTI Northern Section Conference on Electrical, Electronics, computer and Telecommunications Engineering, ECTI DAMT and NCON 2025

作者： Paklao, Thummarat Suratanee, Apichat Plaimas, Kitiporn Chulalongkorn University Faculty of Science Department of Mathematics and Computer Science Bangkok Thailand King Mongkut's University of Technology North Bangkok Faculty of Applied Science Department of Mathematics Bangkok Thailand

ISBN: (纸本)9798331543273

Chronic obstructive pulmonary disease (COPD) is a complex respiratory condition involving multifaceted molecular mechanisms. Differential gene expression analysis has identified genes with significant up-regulation and down-regulation in COPD patients compared to healthy controls, as well as those exhibiting high expression variability. However, relying solely on gene expression analysis is insufficient to fully understand these mechanisms. Therefore, in this study, we propose combining gene expression analysis, its co-expression network, and flux balance-based metabolic models to gain a deeper understanding of the disease's complexity. This integration has revealed several metabolic subsystems associated with COPD and established a concordance between flux values and gene expression in COPD-related clusters. It demonstrates how effectively computational approaches can capture the molecular and metabolic alterations underlying COPD and align with experimental outcomes. The findings also offer biomarkers and pathways that can serve as a foundation for the development of COPD treatments. In summary, this study highlights the efficacy of an integrative computational approach that merges gene expression analysis, co-expression networks, and flux balance-based metabolic models. This methodology establishes connections between gene expression and metabolic flux while providing a valuable framework for future computational investigations and therapeutic strategies targeting COPD. © 2025 IEEE.

关键词： Transcription

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Synergizing vision transformer with ensemble of deep learning model for accurate kidney stone detection using CT imaging

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Alexandria Engineering Journal 2025年 127卷 357-373页

作者： Alzughaibi, Arwa Alanazi, Adwan A. Alshahrani, Mohammed Hilali Jaghdam, Ines Hassaballa, Abaker A. Applied college Taibah University Madinah Saudi Arabia Department of Computer Science and Information College of Computer Science and Engineering University of Hail Hail Saudi Arabia Department of Computer Sciences Applied College Najran University Najran66462 Saudi Arabia Department of Computer Science and Information Technology Applied College Princess Nourah bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia Center for Scientific Research and Entrepreneurship Northern Border University Arar73213 Saudi Arabia Department of Mathematics Faculty of Science Northern Border University Arar73213 Saudi Arabia

The disease of Kidney stones is a risky disease for individuals all over the world. Many people with kidney stones in the early phase do not detect it as an illness, and it harms the organ gradually. Precise analysis of kidney illness is vital, as it is a major health concern that needs accurate detection for appropriate and effective treatment. CT scans are one of the most extensively accessible imaging models, and they are employed for effective diagnosis. Deep learning (DL) techniques are gradually identified as beneficial tools for analyzing illness in the medical field. However, present techniques employing deep networks often meet low accuracy and overfitting challenges, demanding further alteration for optimum performance. This study presents a Leveraging Flying Foxes Optimization with an Ensemble of Deep Learning for Accurate Kidney Stone Detection (LFFOEDL-AKSD) technique in CT scans. The presented LFFOEDL-AKSD technique mainly focuses on detecting kidney stones using CI imaging. At first, the presented LFFOEDL-AKSD technique applies the pre-processing phase, which involves image resizing for uniform CT scan dimensions and data augmentation through transformations like rotation and flipping to reduce overfitting, sobel filtering (SF) sharpens edges, and the data is separated into training, validation, and testing sets for model development. The presented LFFOEDL-AKSD technique employs the swin transformer (ST) model for the feature extraction method. Furthermore, the majority voting ensemble of three DL approaches, such as the graph convolutional network (GCN), temporal convolutional network (TCN), and three-dimensional convolutional autoencoder (3D-CAE) approaches, are employed to increase the precision and reliability of the kidney stone recognition. Finally, the presented LFFOEDL-AKSD technique implements the flying foxes optimization (FFO) approach for the hyperparameter tuning involved in the ensemble learning models. An extensive experiment is conduct

关键词： Flying foxes optimization Ensemble deep learning Kidney stone detection CI imaging Swin transformer

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Investigating the Impact of Language-Adaptive Fine-Tuning on Sentiment Analysis in Hausa Language Using AfriBERTa 1

Investigating the Impact of Language-Adaptive Fine-Tuning on...

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1st Workshop on Language Models for Low-Resource Languages, LoResLM 2025 - co-located at the 31st International Conference on Computational Linguistics, COLING 2025

作者： Sani, Sani Abdullahi Muhammad, Shamsuddeen Hassan Jarvis, Devon School of Computer Science and Applied Mathematics University of the Witwatersrand Johannesburg South Africa Department of Computing Imperial College London United Kingdom

ISBN: (纸本)9798891762152

Sentiment analysis (SA) plays a vital role in Natural Language Processing (NLP) by identifying sentiments expressed in text. Although significant advances have been made in SA for widely spoken languages, low-resource languages such as Hausa face unique challenges, primarily due to a lack of digital resources. This study investigates the effectiveness of Language-Adaptive Fine-Tuning (LAFT) to improve SA performance in Hausa. We first curate a diverse, unlabeled corpus to expand the model’s linguistic capabilities, followed by applying LAFT to adapt AfriBERTa specifically to the nuances of the Hausa language. The adapted model is then fine-tuned on the labeled NaijaSenti sentiment dataset to evaluate its performance. Our findings demonstrate that LAFT gives modest improvements, which may be attributed to the use of formal Hausa text rather than informal social media data. Nevertheless, the pre-trained AfriBERTa model significantly outperformed models not specifically trained on Hausa, highlighting the importance of using pre-trained models in low-resource contexts. This research emphasizes the necessity for diverse data sources to advance NLP applications for low-resource African languages. We will publish the code and the data set to encourage further research and facilitate reproducibility in low-resource NLP. © 2025 Association for Computational Linguistics.

关键词： Computational linguistics

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Degree reduction of ball Said-Ball surfaces using an enhanced coot optimization algorithm

Degree reduction of ball Said-Ball surfaces using an enhance...

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作者： Hu, Gang Dou, Wanting Du, Bo Department of Applied Mathematics Xi'an University of Technology Xi'an China School of Computer Science and Engineering Xi'an University of Technology Xi'an China

Degree reduction of ball Said-Ball (BSB) surface is a complex and unsolved problem in computer-aided design (CAD) and computer graphics (CG), which has potential application prospects in many engineering fields of geometric modeling. In this paper, the degree reduction of BSB surface is transformed into the optimization problems of center surface and radius function, and the improved coot optimization algorithm is used to solve it. An effective method to solve the degree reduction of BSB surface by intelligent optimization algorithm is proposed. Firstly, the degree reduction of BSB surface is decomposed into center surface reduction and radius function reduction, and the objective function and constraint conditions are determined according to the optimization idea, then the degree reduction optimization model of center surface and radius function is established. Secondly, an enhanced coot (ECOOT for short) algorithm is proposed, which combines chain strategy, dispersed foraging strategy, and quadratic interpolation strategy. Compared with the original algorithm, ECOOT algorithm has better convergence performance and higher calculation accuracy. Finally, the proposed ECOOT algorithm is used to solve the degree reduction optimization model, and the optimal center surface and minimum distance radius function of the BSB surface after degree reduction are obtained. The experimental results show that the ECOOT algorithm can effectively solve the problem of degree reduction for BSB surface, the degree reduction error is reduced by about 20% compared to the original COOT algorithm, and is superior to other intelligent optimization algorithms in accuracy, robustness, and convergence. © 2023 John Wiley & Sons, Ltd.

关键词： Optimization

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Enhancing Urban Air Quality with Smart Vehicle Exhaust Management

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Operations Research Forum 2025年第2期6卷 1-24页

作者： Tyagi, Vaishali Dubey, Roshan Singh, Suraj Ram, Mangey Department of Applied Sciences & Humanities ABES Institute of Technology Uttar Pradesh Ghaziabad India Department of Computer Science & Engineering ABES Institute of Technology Uttar Pradesh Ghaziabad India Department of Mathematics Computer Science and Engineering Graphic Era Deemed to be University Uttarakhand Dehradun India

Air pollution is the contamination of the indoor or outdoor environment by any chemical, physical, or biological agent that modifies the natural characteristics of the atmosphere. Burning gasoline and diesel fuel creates harmful byproducts like nitrogen dioxide, carbon monoxide, hydrocarbons, benzene, and formaldehyde. This study proposes a sensor-based model to control vehicular pollution by monitoring emission levels and preventing vehicles from operating if their pollution exceeds government standards. The proposed model consists of a smoke sensor, particulate sensors, carbon monoxide sensors, along with Arduino based microcontroller, data logger, LCD display, and GPRS modem. Using the block diagram, a mathematical model has been developed and some differential equations by using Markov process have been generated. This Markov-based model gives the information about the failure causes and working of the proposed system. Some reliability matrices like availability, mean time between failure (MTBF), and sensitivity analysis have been evaluated with the help of Laplace transform and illustrated with the help of graphs. Also, the failure cases of the system and its cost analysis have been done along with all the numerical calculations required for the successful operation of the model. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.

关键词： Air pollution Cost analysis Failure cases Markov process Reliability Sensor system

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Enhanced Emotion Recognition Using a Hybrid Autoencoder-LSTM Model Optimized with a Hybrid ACO-WOA Algorithm for Hyperparameter Tuning

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International Journal of Advanced computer science and Applications 2025年第4期16卷 861-876页

作者： Waiker, Vinod Ramesh, Janjhyam Venkata Naga Bala, Ms Kiran Krishnaiah, V.V. Jaya Rama Jackulin, T. Muniyandy, Elangovan Shahin, Osama R. Datta Meghe Institute of Management Studies Maharashtra Nagpur India Department of CSE Graphic Era Hill University Dehradun248002 India Department of CSE Graphic Era Deemed To Be University Uttarakhand Dehradun248002 India Department of Computer Science College of Engineering and Computer Science Jazan University Jazan Saudi Arabia Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Andhra Pradesh Vaddeswaram India Department of CSE Panimalar Engineering College Tamil Nadu Chennai India Department of Biosciences-Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai602 105 India Applied Science Research Center Applied Science Private University Amman Jordan Department of Computer Science College of Computer and Information Sciences Jouf University Saudi Arabia Physics and Mathematics Department Faculty of Engineering Helwan University Helwan Egypt

Emotion recognition is vital in the human computer interaction because it improves interaction. Therefore, this paper proposes an improved method for emotion recognition regarding the Hybrid Autoencoder-Long Short-Term Memory (LSTM) model and the newly developed hybrid approach of the Ant Colony Optimization (ACO) and Whale Optimization Algorithm (WOA) for hyperparameters tuning. In this case, Autoencoder can reduce input data dimensionality for input data and find the features relevant for the model’s work. In addition, LSTM is able to work with temporal structures of sequential inputs like speech and videos. The contribution of this research lies in the novel combination method of ACO-WOA which aims at tweaking hyperparameters of Autoencoder-LSTM model. Global aspect of ACO and WOA thereby improve the search efficiency and the accuracy of the proposed emotion recognition system and its generalization capacity. In context with the benchmark dataset for the experimentations of emotion recognition, it has established the efficiency of the proposed model in terms of the conventional methods. Recall rates in recognitive intended various emotions and different modalities were also higher in the hybrid Autoencoder-LSTM model. The optimization algorithms like the ACO-WOA also supported in reducing the computational cost which arose due to hyperparameters tuning. The implementation of this paper is done through Python Software. This implementation shows a high accuracy of 94.12% and 95.94% for audio datasets and image datasets respectively when compared with other deep learning models of Conv LSTM and VGG16. Therefore, the research shows that the presented hybrid approach can be a useful solution for successfully employing emotion recognition for enhancing the creation of the empathetic AI systems and for improving user interactions within various fields including healthcare, entertainment, and customer support. © (2025), (science and Information Organization). All rights

关键词： Ant colony optimization

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Experimental Evaluation of Road-Crossing Decisions by Autonomous Wheelchairs Against Environmental Factors 8th

Experimental Evaluation of Road-Crossing Decisions by Auto...

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8th International Conference on Intelligent Transport Systems, INTSYS 2024

作者： Corradini, Franca Grigioni, Carlo Antonucci, Alessandro Guzzi, Jérôme Flammini, Francesco University of Applied Sciences and Arts of Southern Switzerland IDSIA Lugano Switzerland University of Florence Department of Mathematics and Computer Science "Ulisse Dini" Florence Italy

ISBN: (纸本)9783031863691

Safe road crossing by autonomous wheelchairs can be affected by several environmental factors such as adverse weather conditions influencing the accuracy of sensors based on artificial vision. Previous studies have addressed experimental evaluation of multi-sensor information fusion to support road-crossing decisions in autonomous wheelchairs. In this study, we focus on the experimental evaluation of its tracking performance against outdoor environmental factors such as fog, rain, darkness, etc. It is rather intuitive that those factors can negatively affect the tracking performance;therefore our aim is to quantify through a set of metrics how the performance of the single sensors and their information fusion changes when such external factors are present. This is a first step in designing warning strategies in a novel framework based on the MAPE-k feedback loop established for the sensor system. System reconfiguration to reduce the reputation of less accurate sensors can then be set, thus improving overall safety. The problem is analysed within the context of the European project REXASI-PRO which aims to design a trustworthy autonomous wheelchairs supported by drones in which security, safety, ethics, and explainability are entangled to improve autonomy for people with reduced mobility. Results have been achieved by using an available laboratory dataset realised for a simplified framework in a road-crossing scenario and by applying appropriate software filters to simulate different environmental conditions. © ICST Institute for computer sciences, Social Informatics and Telecommunications Engineering 2025.

关键词： Data fusion

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