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Exploring scattering in a cylindrical duct containing plasma, vacuum, and dielectric media

Optical and Quantum Electronics 2025年第5期57卷 1-22页

作者： Rizvi, Shahana Afzal, Muhammad Department of Mathematics Capital University of Science and Technology Islamabad Pakistan Department of Mathematics and Natural Sciences Center for Applied Mathematics and Bioinformatics Gulf University for Science and Technology Hawally32093 Kuwait

This study investigates the propagation of electromagnetic waves in a perfectly electric conducting cylindrical waveguide with a central chamber filled with cold plasma embedded in vacuum which is covered by dielectric layer in conducting cylinder. The mathematical modeling formulates a boundary value problem which is solved by using the mode-matching technique to analyze the scattering characteristics. This technique relies on the projection of solution on orthogonal bases. The development and application of orthogonality relations are useful to convert the differential system into linear algebraic systems, truncated and inverted for the solution. The validity of the truncated solution is confirmed by verifying the matching conditions, which demonstrate the perfect alignment of electric and magnetic fields at the two interfaces. The investigation focuses on the power flux in different regions of the waveguide, considering both transparency and non-transparency regimes. Computational results demonstrate energy propagation versus the properties of the medium and geometrical parameters of configuration. It is found that the plasma radius alterations do not significantly affect transmission, but influence the number of cut-on modes. In the transparency regime, one cut-on mode, consistently, exists across all chamber regions. In the non-transparency regime, the plasma region has no cut-on mode while the vacuum and dielectric regions exhibit one cut-on mode. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Infrared radiation

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Low-order efficient Adams–Bashforth–Moulton methods for first-order IVPs with oscillating solutions

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Journal of Mathematical Chemistry 2025年第6期63卷 1496-1522页

作者： Lin, Chia-Liang Simos, Theodore E. The Faculty of Art and Design Quzhou College of Technology Quzhou 324000 China School of Mechanical Engineering Hangzhou Dianzi University Er Hao Da Jie 1158 Xiasha Hangzhou 310018 China Center for Applied Mathematics and Bioinformatics Gulf University for Science and Technology West Mishref 32093 Kuwait Section of Mathematics Department of Civil Engineering Democritus University of Thrace Xanthi Greece

The methodology for calculating the phase-lag and amplification-factor for both explicit and implicit multistep methods for first-order differential equations was recently developed by one of the authors. The objective of this study is to develop low-order Adams–Bashforth–Moulton predictor–corrector algorithms that eradicate phase-lag, amplification-factor. The stability regions of the newly established methodologies will also be highlighted. Furthermore, we will examine our results from numerical experiments employing the newly developed approaches. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.

关键词： Adams–Bashforth methods Amplification fitting Initial value problems (IVPs) Multistep methods Numerical solution Phase fitting

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Forecasting Methane Emissions in Kuwait by 2030: A Time Series Approach Using ARIMA

Forecasting Methane Emissions in Kuwait by 2030: A Time Seri...

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IT Innovation and Knowledge Discovery (ITIKD), International Conference on

作者： Aouatef Hellal Jehad Al Dallal Messaoud Djeddou Hydraulic Department Oum El-Bouaghi University Ain Beida Algeria Center for Applied Mathematics and Bioinformatics Gulf University for Science and Technology Kuwait

ISBN: (数字)9798350355468

ISBN: (纸本)9798350355475

Global methane emissions present a major challenge for climate change mitigation, with industrial and agricultural activities contributing significantly to greenhouse gas concentrations. This research applies the ARIMA (Autoregressive Integrated Moving Average) model to forecast Kuwait's annual methane emissions, projecting an annual growth rate of 3.70% between 2023 and 2030. By analyzing historical emissions data from 1850 to 2022, the research provides essential information for environmental policymaking. The model's validation via the autocorrelation function (ACF) and the partial autocorrelation function (PACF) highlights the strengths and limitations of the method. The forecasts emphasize the urgent necessity for targeted emission reduction policies with potential improvements, including the incorporation of explanatory variables, aggregate methods, and regional structural factors.

关键词： Methane Technological innovation Prevention and mitigation Time series analysis Machine learning Predictive models Knowledge discovery Autocorrelation Forecasting Greenhouse gases

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Minimal wave speed and traveling wave in nonlocal dispersion SIS epidemic model with delay

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Boundary Value Problems 2025年第1期2025卷 1-21页

作者： Darazirar, Rassim Yaseen, Rasha M. Mohsen, Ahmed A. Khan, Aziz Abdeljawad, Thabet Department of Mathematics Faculty of Exact Sciences and Informatics Hassiba Benbouali University Chlef 02000 Algeria Department of Biomedical Eng. Al-Khawarzmi college of engineering University of Baghdad Baghdad Iraq Department of Mathematics Open Education College Baghdad Iraq Department of Mathematics College of Education for Pure Science (Ibn Al-Haitham) University of Baghdad Baghdad Iraq Department of Mathematics and Sciences Prince Sultan University P.O. Box 66833 Riyadh 11586 Saudi Arabia Department of Mathematics Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Tamil Nadu Chennai 602105 India Center for Applied Mathematics and Bioinformatics (CAMB) Gulf University for Science and Technology Hawally 32093 Kuwait Department of Mathematics and Applied Mathematics Sefako Makgatho Health Sciences University Medusa Garankuwa 0204 South Africa Department of Mathematics and Applied Mathematics Kyung Hee University 26 Kyungheedae-ro Dongdaemun-gu Seoul 02447 South Korea Department of Medical Research China Medical University Taichung Taichung 40402 Taiwan

This study examines traveling wave solutions of the SIS epidemic model with nonlocal dispersion and delay. The research shows that a key factor in determining whether traveling waves exist is the basic reproduction number R0. In particular, the system permits nontrivial traveling wave solutions for σ≥σ∗ for R0>1, whereas there are no such solutions for σ<σ∗. This is because there is a minimal wave speed σ∗>0. On the other hand, there are no traveling wave solutions when R0≤1. In conclusion, we provide several numerical simulations that illustrate the existence of TWS. © The Author(s) 2025.

关键词： Basic reproduction number Minimal wave speed SIS model Traveling waves

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Predicting Cerebral Stroke: Comparison Between Anomaly Detection Algorithms and Classification Models

Predicting Cerebral Stroke: Comparison Between Anomaly Detec...

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IT Innovation and Knowledge Discovery (ITIKD), International Conference on

作者： Rituparna Sarkar Vaisali Gupta Pranjal Gupta Shantanu Hiwrale Anish Patil Anil Jadhav Jehad Al Dallal Symbiosis Centre for Information Technology Symbiosis International (Deemed University) Pune India Center for Applied Mathematics and Bioinformatics Gulf University for Science and Technology Kuwait

ISBN: (数字)9798350355468

ISBN: (纸本)9798350355475

Cerebral stroke occurs due to hindered blood flow to various parts of the brain, often caused by ischemic blockages or haemorrhagic vascular rupture. These disruptions can lead to severe brain damage or death if not addressed promptly. Annually, over 15 million people worldwide suffer from cerebral stroke, with lifestyle factors such as hypertension and smoking playing a significant role. This study presents a comparative analysis of cerebral stroke prediction models utilizing classification algorithms—Random Forest, XGBoost, Gaussian Naïve Bayes, and KNN—as well as anomaly detection methods such as Local Outlier Factor, Isolation Forest, and Gaussian Probability Distribution. Among these, the Isolation Forest algorithm demonstrated superior performance, achieving a weighted TPR-TNR score of 0.7449, reflecting balanced anomaly detection capabilities in imbalanced datasets. The findings highlight the importance of tailored machine learning solutions for stroke risk prediction. Future work will explore hybrid approaches to enhance detection accuracy while addressing dataset challenges.

关键词： Technological innovation Machine learning algorithms Forestry Predictive models Prediction algorithms Probability distribution Classification algorithms Bayes methods Anomaly detection Random forests

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Data-Driven Insights in Real Estate: Property Recommendation System and House Rent Prediction using Machine Learning

Data-Driven Insights in Real Estate: Property Recommendation...

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IT Innovation and Knowledge Discovery (ITIKD), International Conference on

作者： Ashish Kate Anil Jadhav Sarvarth Patil Thamini Lanjewar Ishita Sreelakshmi K Jehad Al Dallal Symbiosis Centre for Information Technology Symbiosis International (Deemed University) Pune India Center for Applied Mathematics and Bioinformatics Gulf University for Science and Technology Kuwait

ISBN: (数字)9798350355468

ISBN: (纸本)9798350355475

In the fast-changing market of real estate, making an accurate prediction of house rent, along with proper recommendations of properties based on user preferences, is crucial for buyers and agents. In this research, we compared the performance of four models: Linear Regression, Random Forest Regression, SVM, and Decision Tree Regressor, to predict house rent. In addition, we have applied the KNN algorithm as well as the Cosine similarity measure to make property recommendations by using user preferences. Also, we tested the performance of each predictive model by computing Mean Squared Error and R-Squared. The effectiveness of the recommendation system is tested in terms of its property suggestions matching to the preferred properties of users. The results show the outputs for each of the machine learning algorithms and how a combination of predictive model and recommendation techniques is used to improve the user experience in real estate.

关键词： Support vector machines Technological innovation Machine learning algorithms Predictive models Nearest neighbor methods Prediction algorithms User experience Recommender systems Regression tree analysis Random forests

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Financial Anomalies in Bank Subscriptions: Machine Learning and Bayesian Optimization for Term Deposit Analysis

Financial Anomalies in Bank Subscriptions: Machine Learning ...

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IT Innovation and Knowledge Discovery (ITIKD), International Conference on

作者： Ansh Grover Nikhil Jain Manognya Agnihotri Rithani Priyankaa S R Tella Divya Sree Anil Jadhav Jehad Al Dallal Symbiosis Centre for Information Technology Symbiosis International (Deemed University) Pune India Center for Applied Mathematics and Bioinformatics Gulf University for Science and Technology Kuwait

ISBN: (数字)9798350355468

ISBN: (纸本)9798350355475

The study uses the UCI Bank Marketing Dataset and applies the method of unsupervised anomaly detection to investigate customer behavior in the banking industry. In contrast to all other work done in the past, which includes dealing with predicting deposits, here we draw out the main factors of anomalous interactions, such as the job type, interaction duration, and contact timing. Methods like Isolation Forest, Local Outlier Factor, and One-Class SVM are applied to the imbalanced dataset to find anomaly patterns that show that managerial and self-employed jobs are related to specific anomaly patterns. Based on the results, it is suggested that demographic understanding must be integrated with the marketing strategies.

关键词： Support vector machines Surveys Technological innovation Consumer behavior Machine learning Forestry Timing Bayes methods Anomaly detection Optimization

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Numerical simulation of steady incompressible flow of Maxwell hybrid nanofluid (MgO−Ag/H₂O) with thermal and flow behavior analysis

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Nano-Structures and Nano-Objects 2025年 41卷

作者： Abbas, Tasawar Nawaz, R. Department of Mathematics University of Wah Wah Cantt 47040 Pakistan Center for Applied Mathematics and Bioinformatics (CAMB) Gulf University for Science and Technology Hawally 32093 Kuwait

This paper examines the flow and heat transfer characteristics of a hybrid nanofluid (HNF) over a radially stretching sheet under the applied magnetic field with heat transfer. The main objective is to investigate the consequence of the magnetic field strength, heat transfer, and non-Newtonian behavior on the velocity and thermal distribution of the Maxwell hybrid nanofluid (MHNF). The momentum equation captures the contribution due to the magnetic field and heat transfer along with the non-Newtonian viscous dissipation effect. Additionally, the energy equation is formulated to reflect heat transfer dynamics including thermal conduction, viscous dissipation, and a source term. The study also considers the thermophysical properties of the nanofluid, which are dynamic viscosity, density, specific heat, and thermal conductivity modeled through nanoparticle volume fractions. Boundary conditions at the wall and infinite distance are also provided for velocity and temperature profiles. Properties of hybrid nanofluids are computed through established mixing models considering both interactions of nanoparticles dispersed into a base fluid-water and water-based Ag and MgO nanoparticles. The proposed model is aimed at providing insight into the effects of magnetic field strength, heat transfer, and non-Newtonian behavior on the flow and heat transfer features of HNFs. The results show that an increased magnetic field parameter reduces the velocity profile caused by the Lorentz force-induced effect but increases the temperature profile through heat transfer. The slip parameter aids fluid motion by reducing drag but with a higher volume fraction of nanoparticles, thermal conductivity is enhanced while velocity decreases due to an increase in viscosity. © 2025 Elsevier B.V.

关键词： Hybrid nanofluid Incompressible flow Maxwell fluid Numerical simulation

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NON UNIFORM EXPANSION AND ADDITIVE NOISE IMPLY RANDOM HORSESHOES AND RANDOM TOWER

arXiv

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arXiv 2025年

作者： Lamb, Jeroen S.W. Tenaglia, Giuseppe Turaev, Dmitry International Research Center for Neurointelligence The University of Tokyo Tokyo113-0033 Japan Centre for Applied Mathematics and Bioinformatics Department of Mathematics and Natural Sciences Gulf University for Science and Technology Halwally 32093 Kuwait Department of Mathematics Imperial College London LondonSW7 2AZ United Kingdom

We propose a notion of random horseshoe and prove density of random horseshoes and existence of a random young tower with exponential tail for non uniformly expanding random dynamical systems with additive noiseMSC Co... 详细信息

关键词： Lyapunov methods

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Digital Rupee Acceptance Dynamics Through the Lens of Theory of Planned Behaviour

Digital Rupee Acceptance Dynamics Through the Lens of Theory...

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IT Innovation and Knowledge Discovery (ITIKD), International Conference on

作者： Suraj Chandrakant Kamble Shikha Jain Rashmy Moray Jehad Al Dallal Institute of Management Development and Research IMDR® Pune India Symbiosis Institute of Management Studies (SIMS) Symbiosis International Deemed University (SIU) Pune India Center for Applied Mathematics and Bioinformatics Gulf University for Science and Technology Kuwait

ISBN: (数字)9798350355468

ISBN: (纸本)9798350355475

This study aimed to examine the acceptance of the digital rupee by assessing the relationship between users’ attitudes, subjective norms, and perceived behavioral control. The theory of planned behavior is used to analyze the influence of users’ intention to accept digital rupees for financial transactions, emphasizing motivations and barriers affecting users’ intention to use digital rupees. Following the stratified random sampling technique, the responses were collected through a structured questionnaire to represent diverse users. Statistical tools, including regression analysis, ANOVA, and t-test, were applied to achieve the research objectives. The study explored the impact of demographic variables in relation to behavior and identified that occupation significantly affects behavior among users. The findings reveal that positive attitudes, subjective norms, and perceived behavioral control significantly influence the acceptance of digital rupees. The research outcomes contribute to the theoretical frameworks of user behavior towards digital currencies, as well as practical insights into the adoption of digital rupees.

关键词： Technological innovation Attitude control Online banking Government Buildings Knowledge discovery Regression analysis Security Analysis of variance Lenses

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