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3rd International Conference on Electronics and Renewable Systems, ICEARS 2025

作者： Chinnasamy, P. Subashini, B. Nijanthan, Nijanthan Madasamy Raja, G. Swetha, Devulapally Sreenivasulu Reddy, L. School of Computing Kalasalingam Academy of Research and Education Department of Computer Science and Engineering Tamilnadu India School of Computing Srmist Department of Data Science and Business Systems Kattankulathur India Paavai Engineering College Tamilnadu Namakkal India Paavai Engineering College Tamilnadu Namakkal India Vaagdevi Engineering College Dept. of Computer Science and Engineering Warangal Dist. Telangana Bolli Kunta506005 India School of Advanced Sciences Kalasalingam Academy of Research and Education Department of Mathematics Tamilnadu Krishnankoil India

ISBN: (纸本)9798331509675

The rapid advancement of Blockchain technology has led to its widespread application in several domains of digital activities, such as e-government concerns and monetary security. This article presents a smart contract-based Blockchain solution for protecting intellectual property rights in new product development. The proposed solution effectively tackles the challenges associated with the confidentiality of personally identifiable information, efficiency in storing transaction-related information, as well as cooperation and monitoring in IPR. Initially, we create a mathematical model based on smart contract enabled Blockchain and intelligent contracts. Subsequently, we develop algorithms for Blockchain generation, and intelligent contracts. The system is suitable for protecting IPR in a blockchain network, by implementation of distributed identity authentication and real-time extensible storage. These features enhance the security and expandability of circuit copyright protection based on blockchain technology. The experimental results demonstrate that the suggested algorithm has decreased the cost for communication and enhanced the effectiveness of storing information and administration. Furthermore, it demonstrates resilience against many common attacks such as double-spending assaults, while maintaining low cost and overhead. Additionally, it exhibits a superior level of security in comparison to three other competing algorithms. © 2025 IEEE.

关键词： Smart contract

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CONVERGENCE OF DISCONTINUOUS GALERKIN METHODS FOR QUASICONVEX AND RELAXED VARIATIONAL PROBLEMS

arXiv

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arXiv 2025年

作者： Grekas, Georgios Koumatos, Konstantinos Makridakis, Charalambo Vikelis, Andreas Computer Electrical Mathematical Sciences and Engineering Division KAUST Saudi Arabia Department of Mathematics University of Sussex United Kingdom Institute of Applied & Computational Mathematics Foundation for Research & Technology-Hellas Greece Department of Mathematics and Applied Mathematics University of Crete Greece Faculty of Civil Engineering Czech Technical University of Prague Czech Republic

In this work, we establish that discontinuous Galerkin methods are capable of producing reliable approximations for a broad class of nonlinear variational problems. In particular, we demonstrate that these schemes provide essential flexibility by removing inter-element continuity while also guaranteeing convergent approximations in the quasiconvex case. Notably, quasiconvexity is the weakest form of convexity pertinent to elasticity. Furthermore, we show that in the non-convex case discrete minimisers converge to minimisers of the relaxed problem. In this case, the minimisation problem corresponds to the energy defined by the quasiconvex envelope of the original energy. Our approach covers all discontinuous Galerkin formulations known to converge for convex energies. This work addresses an open challenge in the vectorial calculus of variations: developing and rigorously justifying numerical schemes capable of reliably approximating nonlinear energy minimization problems with potentially singular solutions, which are frequently encountered in materials science. © 2025, CC BY.

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Influence of Heat on Fractionalized Nanofluid with Magnetic Field

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International Journal of applied and Computational mathematics 2025年第1期11卷 1-15页

作者： Ramzan, Muhammad Amir, Muhammad Abbas, Shajar Nazar, Mudassar Jan, Rashid Al Agha, Afnan AL Garalleh, Hakim Centre for Advanced Studies in Pure and Applied Mathematics Bahauddin Zakariya University Multan Pakistan Department of Civil Engineering College of Engineering Institute of Energy Infrastructure (IEI) Universiti Tenaga National (UNITEN) Putrajaya Campus Jalan IKRAM-UNITEN Selangor Kajang 43000 Malaysia Mathematics Research Center Near East University TRNC Nicosia 99138 Turkey Department of Mathematical Science College of Engineering Universty of Business and Technology Jeddah 21361 Saudi Arabia

Numerous researchers have been drawn to the rheology of non-Newtonian fluids because of their diverse uses in the engineering and manufacturing fields, such as lubrication, plastic processing, and mining. Additionally, the characteristics of magnetohydrodynamics non-Newtonian fluids permit its widespread application in computer hard drives, loudspeakers, magnetic resonance imaging, the administration of magnetic medicines, and magnetic hyperthermia. The novelty of present study is the use of fourier’s and fick’s laws. The current work is focused on the analysis of heat and mass transfer in a magnetohydrodynamics Maxwell nanofluid flows across an inclined vertical plate because of these possible uses. The values of angle of inclination is chosen in the range 0 to π3. From Table 1, the values of nanoparticles lies in the range of 0.012–0.18. Using suitable non-dimensional variables, ordinary differential equations are created from the modeling equations, and the Laplace transform method is used to solve these equations. Semi-analytical solutions for temperature, concentration, Bio-Convection, and velocity are found after employing the Laplace transform approach to address the issue. The study highlights several key outcomes likes velocity of fluid is increased with increasing values of Gr but decreased with increasing values of Pr, M, and maxwell parameter. The effect of increasing values of parameters R, L1, and N1 are seen to suppress the concentration profile. The bioconvection concentration profile increases with Φ but reduced with increasing values of L2. Furthermore, the comparison between ordinary and fractionalized maxwell fluid has been drawn. The application of the unsteady flow of nanofluid over a plate with the CPC operator has the potential to impact a wide range of solar energy-related technologies and innovations, leading to increased efficiency, sustainability, and the advancement of renewable energy solutions. © The Author(s), under exclusive licence

关键词： Chemical reaction CPC derivative Free convection Magnetic field Maxwell fluid

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Enhancing the Swanepoel method: precise envelope detection of thin-film transmission spectra

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Optics Express 2025年第6期33卷 13376-13400页

作者： Ballester, Manuel Marquez, Almudena P. Lopez-Tapia, Santiago Fernandez, Susana Bass, John Minkov, Dorian Wuersch, Christoph Willomitzer, Florian Marquez, Emilio Katsaggelos, Aggelos K. Computer Science Department Northwestern University EvanstonIL60208 United States Department of Mathematics Faculty of Science University of Cadiz Puerto Real11510 Spain Department of Electrical and Computer Engineering Northwestern University EvanstonIL60208 United States CIEMAT Avenida Complutense 40 Madrid28040 Spain Wyant College of Optical Sciences University of Arizona TucsonAZ85721 United States Sofia1000 Bulgaria Institute for Computational Engineering ICE OST Eastern Switzerland University of Applied Sciences Switzerland Department of Condensed-matter Physics Faculty of Science University of Cadiz Puerto Real11510 Spain

The Swanepoel method is a widely used optical technique for characterizing thin films through normal-incidence transmission measurements. A critical step in this approach involves extracting the upper and lower envelopes of the measured oscillatory spectrum. By analyzing the transmission spectrum and its corresponding envelopes, the Swanepoel procedure enables precise determination of the film refractive index and extinction coefficient. However, even minor inaccuracies in envelope construction can propagate significant errors into the final characterization results. To address this challenge, we present what we believe to be a novel physics-informed optimization algorithm for envelope detection. Our mathematical model reformulates the envelope detection problem as a global optimization task that enforces the physical properties of the Swanepoel envelopes. Extensive validation on fifty randomly generated transmission spectra demonstrates unprecedented accuracy: the method achieves root-mean-square errors (RMSE) below 0.10% for the upper envelope and 0.06% for the lower envelope (more than doubling the accuracy of current state-of-the-art approaches). Furthermore, the proposed model has been assessed with two experimental transmission spectra, demonstrating its robustness and accuracy with real noisy data. We have developed an open-source Python software package (see text below). This software includes not only our innovative envelope construction algorithm but also additional envelope drawing algorithms for comparison and an efficient implementation of the Swanepoel method, enabling complete optical characterization of thin films. © 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Mean square error

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Analysis of Viral and Non-viral Categories of Video Through Social Media Using Machine Learning Techniques 15th

Analysis of Viral and Non-viral Categories of Video Through ...

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15th International Conference on Soft Computing and Pattern Recognition, SoCPaR 2023 and 14th World Congress on Nature and Biologically Inspired Computing, NaBIC 2023

作者： Nagashree, B.A. Satheesh Kumar, S. Muthukumaran, V. Joseph, P. Rose Bindu Amrita Vishwa Vidyapeetham Mysuru Campus Mysuru 570026 India Department of Computer Science School of Applied Sciences REVA University Bangalore India Department of Mathematics College of Engineering and Technology SRM Institute of Science and Technology Chennai India Department of Mathematics Dayananda Sagar College of Engineering Bangalore India

ISBN: (纸本)9783031889912

People frequently use technological means to collect information from many sources, share it with others on social media, and communicate with friends on these platforms. Social media is therefore a crucial new tool for communication. Collaborative wikis, blogs, and content communities are just a few of the tools and technologies that make up social media. YouTube is the most widely used of these. The influencer’s content gets visible to the users of such platforms. The expansion of social media use has enabled massive and rapid spread ability of content, often called virality. This paper aims to examine the virality of different categories of YouTube videos using machine learning technique, where it plays a major role in analysis of YouTube data such as likes, dislikes, comment count and views. YouTube can serve as a path to virality and fabricate online videos, hence finding the correlation analysis among the videos, which enables us to classify the viral and non-viral video categories, thereby analysing the linear relationship among the features (likes, dislike, views and comment count. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： correlation analysis internet social media virality YouTube

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Automated analysis of retinal vascular features, age, sex and disc size in a large cohort of primary open angle glaucoma patients

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ACTA OPHTHALMOLOGICA 2025年第S284期103卷

作者： Van Eijgen, Jan Fhima, Jonathan Reiner-Benaim, Anat Beeckmans, Lennert Abramovich, Or Stalmans, Ingeborg Behar, Joachim A. Department of Ophthalmology University Hospitals UZ Leuven Leuven Department of Neurosciences KU Leuven Research Group Ophthalmology Leuven Technion-IIT Faculty of Biomedical Engineering Haifa Israel Technion-IIT Department of Applied Mathematics Haifa Israel Ben-Gurion University of the Negev Department of Epidemiology Biostatistics and Community Health Sciences Beer-Sheva Israel

Aims/Purpose: Deriving vascular features of retinal images is a proposed noninvasive method to assess vascular health. Although several studies have linked cardiovascular risk to retinal image features, they often rely on limited datasets or have used deep learning approaches with limited explainability. This research introduces an end-to-end method for analyzing the retinal vasculature in large retinal image datasets, applied for primary open angle glaucoma (POAG). Methods: 115,237 retinal images of the UZ Leuven Glaucoma Clinic were extracted. 4858 unique images remain of POAG patients ( n = 3010) and controls ( n = 1848) after image quality assessment, optic disk detection, region of interest definition, automated segmentation of arterioles and venules (LUNet algorithm), and parametrization of the vascular biomarkers (PVBM toolbox). Analysis of covariance and linear mixed models were used to adjust for age, sex and disc size. Results: Both arteriolar and venular diameter, area, length, tortuosity, branching angle, endpoints, intersection points and both mono- as multifractal dimension levels are independently lower in POAG patients and older patients (all p < 0.001), after adjustment for sex, disc size and multiple testing. The multivariate linear mixed models additionally show that the vascular features are significantly influenced by sex and disc size, which necessitates correct adjustment. Conclusions: This is the first time a fully automated end-to-end pipeline is published for the analysis of retinal vascular geometry in a large cohort ( n = 4858). Given the independent similarities in retinal vascular geometry changes between older age and POAG prevalence the theory of pronounced vascular ageing in POAG patients is proposed. This novel approach enables quantitative analysis of eye vasculature and supports the study of its correlation with specific diseases, facilitating reproducible analysis of large datasets and providing explainability to deep learning ap

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Explainable hybrid forecasting model for a 4-node smart grid stability

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Energy Reports 2025年 13卷 4948-4961页

作者： Ghazal, Taher M. Hasan, Mohammad Kamrul Hassan, Rosilah Abdullah, Mustafa Islam, Shayla Ahmad, Munir Department of Networks and Cybersecurity Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman Jordan Faculty of Information Science and Technology Universiti Kebangsaan Malaysia Selangor Bangi43600 Malaysia Electric vehicles engineering department Hourani Center for Applied Scientific Research Al-Ahliyyaesearch Al-Ahliyya Amman University Amman Jordan Institute of Computer Science and Digital Innovation UCSI University Kuala Lumpur56000 Malaysia University College Korea University Seoul02841 Korea Republic of

The 4-Node architecture for smart grids (SGs) distinguishes the operational features to enhance its stability and interruption less power distribution. This architecture contains 1 generator node and 3 consumption nodes to retain the stability of SGs. However, the chances of grid component failure, deficient power distribution, or peak demands result in the 4-node architecture imbalance. To forecast such imbalance towards SG stability, this paper exploits the explainable artificial intelligence (AI) and deep learning models to verify the existence of bias in the 4-node architecture due to the above flaws. For this purpose, in this paper, the component functioning rate and demand-to-distribution ratio are computed and verified to compute the bias. The deep learning model trains the explainable AI model for the potential flaws from the distribution intervals. Using the training using the deep learning model, the 4-node architecture's performance is evaluated to forecast the grid stability for future distributions. The 4-node architecture stability is verified under different loads, peak demands, and device performances using the integrated hybrid model with EAI. The proposed model improved the forecast accuracy by 14.53 % and reduced the loss in flaw detection by 13.41 % for the varying dissemination hours. © 2025 The Authors

关键词： Power grids

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Anisotropic quark stars f（R,Lm,T） in gravity

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Chinese Physics C 2025年第2期 270-281页

作者： Takol Tangphati ?zzet Sakall Ayan Banerjee Anirudh Pradhan School of Science Walailak University Research Center for Theoretical Simulation and Applied Research in Bioscience and Sensing Walailak University Physics Department Eastern Mediterranean University Atrophysics Research Centre School of MathematicsStatistics and Computer ScienceUniversity of Kwa Zulu–Natal Centre for Cosmology Astrophysics and Space ScienceGLA University

We investigated the impact of f（R,Lm,T） gravity on the internal structure of compact stars,expecting this theory to manifest prominently in the high-density cores of such *** considered the algebraic function f（R,Lm,T）=R+αTLm,where a represents the matter-geometry coupling *** specifically chose the matter Lagrangian density Lm=-ρ to explore compact stars with anisotropic *** this end,we employed the MIT bag model as an equation of ***,we numerically solved the hydrostatic equilibrium equations to obtain mass-radius relations for quark stars（QSs）,examining static stability criteria,adiabatic index,and speed of ***,we used recent astrophysical data to constrain the coupling parameter a,which may lead to either larger or smaller masses for QSs,compared to their counterparts in general relativity.

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Deep learning and ensemble methods for anomaly detection in ICS security

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International Journal of Information Technology (Singapore) 2025年第3期17卷 1761-1775页

作者： Hossain, Md. Alamgir Hasan, Tahmid Karovic, jr, Vincent Abdeljaber, Hikmat A. M. Haque, Md. Alimul Ahmad, Sultan Zafar, Aasim Nazeer, Jabeen Mishra, B.K. Department of Computer Science and Engineering State University of Bangladesh South Purbachal Kanchan Dhaka 1461 Bangladesh Department of Computer Science and Engineering Prime University Dhaka Bangladesh Department of Information Systems Faculty of Management Comenius Bratislava Odbojárov 10 Bratislava 25 82005 Slovakia Department of Computer Science Faculty of Information Technology Applied Science Private University Amman 11931 Jordan MEU Research Unit Middle East University Amman 11831 Lebanon Department of Computer Science Veer Kunwar Singh University Bihar Ara India Department of Computer Science College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz University Alkharj 11942 Saudi Arabia University Center for Research and Development (UCRD) Department of Computer Science and Engineering Chandigarh University Gharuan Punjab Mohali 140413 India Department of Computer Science Aligarh Muslim University U.P Aligarh 202002 India P.G. Department of Physics Veer Kunwar Singh University Bihar Ara India

This research addresses the escalating threats to industrial control systems by introducing a novel approach that combines deep learning for feature selection with a robust ensemble-based classification technique to enhance anomaly detection. Our method utilizes a tailored autoencoder architecture to efficiently select features, followed by a Random Forest classifier to ensure reliable and generalizable detection of anomalies. Evaluated on the HAI Security Dataset, the proposed approach demonstrates exceptional performance, with significant improvements in detecting anomalous activities in ICS. The results highlight the method’s potential to enhance ICS security by providing a scalable and adaptable framework that evolves with emerging threats. This study not only advances cybersecurity methodologies for industrial systems but also lays the groundwork for future research, emphasizing the need for innovative and effective security solutions in the face of evolving cyber challenges. © Bharati Vidyapeeth's Institute of computer Applications and Management 2024.

关键词： Anomaly detection in ICS Cyber-resilience in critical infrastructure Deep learning for feature selection Industrial control systems security Random forest classifier for ICS

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Transition metal-functionalized hexagonal bipyramidal boron clusters as high-performance electrocatalysts for hydrogen evolution reaction: A DFT study

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International Journal of Hydrogen Energy 2025年 127卷 912-929页

作者： Hsu, Chou-Yi Ali, Ali B.M. Jamal, Zainab H. Mudhafar, Mustafa Alsailawi, Hasan Ali Abduvalieva, Dilsora Mohamed, A.M.A. Adil, S.K. Alkahtani, Hamad M. Mahariq, Ibrahm Thunderbird School of Global Management Arizona State University Tempe Campus PhoenixAZ85004 United States Air Conditioning Engineering Department College of Engineering University of Warith Al-Anbiyaa Karbala Iraq Centre for Research Impact & Outcome Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura140401 India Department of Medical Physics Faculty of Medical Applied Sciences University of Kerbala Karbala56001 Iraq Department of Anesthesia Techniques and Intensive Care Al-Taff university college Kerbala56001 Iraq Faculty of Dentistry University of Kerbala Karbala56001 Iraq Department of Anesthesia Techniques AlSafwa University College Karbala Iraq Department of Mathematics and Information Technologies Tashkent State Pedagogical University Bunyodkor avenue 27 Tashkent100070 Uzbekistan Department of Metallurgical and Materials Engineering Faculty of Petroleum and Mining Engineering Suez University Suez43512 Egypt Department of Chemistry Chandigarh Engineering College Chandigarh Group of Colleges-Jhanjeri Punjab Mohali140307 India Department of Pharmaceutical Chemistry College of Pharmacy King Saud University P.O. Box 2457 Riyadh11451 Saudi Arabia Department of Mathematics Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Tamil Nadu Chennai602105 India Applied Science Research Center Applied Science Private University Amman Jordan Department of Medical Research China Medical University Hospital China Medical University Taichung Taiwan

This present study investigates the electrocatalytic activity of transition metal-functionalized TaB6 hexagonal bipyramidal boron cluster (M -TaB6: M = Ta, Hf, Ir, Re, W) systems for hydrogen evolution reaction (HER) within the framework of density functional theory (DFT) at the PBE-D3/GenECP/Def2-SVP/LanL2DZ computational method. The study concludes that transition metal modifications significantly contribute to hydrogen chemisorption and catalytic efficiency. Most significantly, Re-TaB6 (−0.765 eV) and W–TaB6 (−0.768 eV) hexagonal bipyramidal surfaces possess nearly ideal Gibbs free energy (ΔGH) for HER, indicating excellent catalytic activity. Calculation of adsorption energy further reveals Hf-TaB6 (−0.829 eV) and B6 (−0.587 eV) with the highest hydrogen interaction, favoring strong chemisorption behavior. The study highlights how transition metal doping enhances catalytic activity by stabilizing hydrogen adsorption and breaking, optimizing the efficiency of HER. © 2025 Hydrogen Energy Publications LLC

关键词： Hydrogen evolution reaction

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