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8th International Conference on Signal and Image Processing, ICSIP 2023

作者： Yuan, Xiaochen Sun, Ying Zhang, Qiyuan Macao Polytechnic University Faculty of Applied Sciences Macao China Macau University of Science and Technology School of Computer Science and Engineering Macao China

ISBN: (纸本)9798350397932

Cover lossless robust watermarking technology is one of the frontier hotspots in the field of information hiding. It can fully restore the original image without external attacks, while when there is an attack, it can extract robust watermarks for secure verification. Most of the countermeasures proposed in the literature are robust to geometric attacks, but most schemes are less imperceptible, mainly due to the fixed location of the embeddings. In this paper, we propose a Zernike moments-based robust and reversible watermarking scheme. It embeds robust watermarks in low-order Zernike moments to keep their rotational invariance, thus it can be used for information authentication and is not easy to detect. Then the reversible watermark is embedded outside the robust watermark region as compensation information to fully restore the original image. The proposed scheme enables the image has the ability to restore the image and secure verification at the same time. Theoretical and simulation results show that it has better bit error rate and imperceptibility. © 2023 IEEE.

关键词： Bit error rate

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A Novel Multiple Dependent State Sampling Plan Based on Time Truncated Life Tests Using Mean Lifetime

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computers, Materials & Continua 2022年第12期73卷 4611-4626页

作者： Pramote Charongrattanasakul Wimonmas Bamrungsetthapong Poom Kumam Division of Mathematics Department of Mathematics and Computer ScienceFaculty of Science and TechnologyRajamangala University of Technology KrungthepBangkok10120Thailand Division of Applied Statistics Department of Mathematics and Computer ScienceFaculty of Science and TechnologyRajamangala University of Technology ThanyaburiPathum Thani12110Thailand Center of Excellence in Theoretical and Computational Science(TaCS-CoE)&KMUTT Fixed Point Research Laboratory Room SCL 802 Fixed Point LaboratoryScience Laboratory BuildingDepartments of MathematicsFaculty of ScienceKing Mongkut’s University of Technology Thonburi(KMUTT)Bangkok10140Thailand

The design of a new adaptive version of the multiple dependent state(AMDS)sampling plan is presented based on the time truncated life test under the Weibull *** achieved the proposed sampling plan by applying the concept of the double sampling plan and existing multiple dependent state sampling plans.A warning sign for acceptance number was proposed to increase the probability of current lot *** optimal plan parameters were determined simultaneously with nonlinear optimization problems under the producer’s risk and consumer’s risk.A simulation study was presented to support the proposed sampling plan.A comparison between the proposed and existing sampling plans,namely multiple dependent state(MDS)sampling plans and a modified multiple dependent state(MMDS)sampling plan,was considered under the average sampling number and operating characteristic curve *** addition,the use of two real datasets demonstrated the practicality and usefulness of the proposed sampling *** results indicated that the proposed plan is more flexible and efficient in terms of the average sample number compared to the existing MDS and MMDS sampling plans.

关键词： Adaptive version of multiple dependent state sampling plan time truncated life test quality level weibull distribution mean lifetime

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Avoiding renormalization of the elastic transition amplitude in the proton-deuteron scattering calculations

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Physical Review C 2024年第1期110卷 014003-014003页

作者： H. Witała J. Golak R. Skibiński M. Smoluchowski Institute of Physics Faculty of Physics Astronomy and Applied Computer Science

We discuss two approaches which, by applying the screening method, permit one to include the long range proton-proton (pp) Coulomb force in proton-deuteron (pd) momentum-space scattering calculations. In the first one, based on the Alt-Grassberger-Sandhas (AGS) equation, presented in Phys. Rev. C 71, 054005 (2005) and Phys. Rev. C 72, 054004 (2005), one needs to renormalize elastic scattering amplitude before calculating observables. In the second treatment, proposed by us in Eur. Phys. J. A 41, 369 (2009), Eur. Phys. J. A 41, 385 (2009), and arXiv:2310.03433 [***], this renormalization is avoided. For the proton induced deuteron breakup reaction both approaches require renormalization of the corresponding transition amplitudes. We derive the basic equations underlying both methods under the assumption that all contributing partial wave states are included and explain why in our approach renormalization of the elastic scattering amplitude is superfluous. We show that in order to take into account in the screening limit all partial waves it is required that four additional terms, based on the three-dimensional and partial-wave projected pp Coulomb t matrices, identical for both approaches, must appear in transition amplitudes. We investigate the importance of these terms for elastic pd scattering below the breakup threshold.

关键词： Elastic scattering reactions Few-body systems Nuclear reactions

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Security in Social Networks and Media 1

Security in Social Networks and Media

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1st IEEE International Conference on Advances in Electronics, Communication, Computing and Intelligent Information Systems, ICAECIS 2023

作者： Jyothi, A.P. Badiger, Vinayak N Shivakumar, Vinyas Ramaiah University of Applied Sciences Faculty of Engineering and Technology Dept. of Computer Science Karnataka Bengaluru India

ISBN: (纸本)9798350348057

In today's data-driven world, data privacy and security is of utmost importance. Social media platforms have become the main source of data breaches due to the sheer number of users who are exposed to these risks. It is essential to understand the viable risks associated with such breaches in order to ensure that personal data remains secure. In this paper, we have discussed and reviewed the different forms of digital privacy breaches, their risks, possible preventive strategies and responsibilities of Institutions and Governments to handle digital security. © 2023 IEEE.

关键词： Data privacy

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A modeling study of position and orientation of hemodialysis needles and the impact on vascular access 12

A modeling study of position and orientation of hemodialysis...

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12th International Conference on Mathematical Modeling in Physical sciences, IC-MSQUARE 2023

作者： Woraratsoontorn, Pattaraweerin Bunmun, Kanyarat Department of Industrial Physics and Medical Instrumentation Faculty of Applied Science King Mongkut's University of Technology North Bangkok Bangkok10800 Thailand

Patients with chronic kidney disease (CKD) need renal replacement therapy (RRT) and the favored method is hemodialysis (HD). An arteriovenous fistula is the preferred choice of vascular access, with two metal needles used to transfer the blood with waste to the dialysis machine and return the blood without waste from the dialysis machine to the patient's body. However, wounds on the veins can cause blood clots which if left untreated could be life threatening. The hemodialysis needles can cause vascular wall abnormalities. The position and orientation of these needles might cause intimal hyperplasia (IH) and finally lead to blood clots. This study aims to analyze the hemodynamic effects on the vascular endothelium in AVF vascular access. A 15G needle was placed inside a vein at angles of 20°, 40°, and 90° with normal insertion and flipped needle in an idealized cephalic vein with the bore of the needle centrally located, conforming to standard cannulation practice. The 3D model created by SolidWorks consists of shaft, back eye, bevel, and vein only;the vein and 15G needle were assembled together. The mathematical model of blood rheology in this paper used Carreau's law in the fluid domain. It was imported into Ansys CFX for calculation, a finite volume based software, which was implemented to solve the governing equations of the blood flow. The result showed that if the venous needle was not towards the venous return, a vortex appeared at the vein both upstream and downstream due to the venous needle, resulting in wall shear stress at the vein increasing significantly, and the flipped bevel seems to cause higher wall shear stress. For antegrade positioning of the vein vascular access return in the model when normally inserted, it was found that only 1% of the flow out of the back eye and vortex occurred downstream of the vein. Needles placed at a higher angle can increase wall shear stress and pressure on the vein. The flipped bevel is not significant in terms of ei

关键词： Needles

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High energy γγ interactions at the LHeC 31

High energy γγ interactions at the LHeC

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31st International Workshop on Deep Inelastic Scattering, DIS 2024

作者： Forthomme, Laurent Khanpour, Hamzeh Piotrzkowski, Krzysztof Yamazaki, Yuji AGH University Faculty of Physics and Applied Computer Science Al. Mickiewicza 30 Kraków30-055 Poland Physics Department Graduate School of Science Kobe University 1-1 Rokkodai-cho Nada-ku Kobe Japan

The future Large Hadron-electron Collider (LHeC) will operate at a center-of-mass energy of 1.2 TeV, delivering an integrated electron-proton luminosity of approximately 1 ab-1. The high luminosity and clean experimental environment at LHeC promise unique research opportunities, requiring a comprehensive survey of high-energy γγ interactions up to center-of-mass energies of 1 TeV. In this contribution, the potential for scientific discovery is briefly assessed by discussing the γγ processes, particularly the two-photon exclusive production of supersymmetric particles. © Copyright owned by the author(s) under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0).

关键词： Hadrons

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BHJO: A Novel Hybrid Metaheuristic Algorithm Combining the Beluga Whale, Honey Badger, and Jellyfish Search Optimizers for Solving Engineering Design Problems

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computer Modeling in Engineering & sciences 2024年第10期141卷 219-265页

作者： Farouq Zitouni Saad Harous Abdulaziz S.Almazyad Ali Wagdy Mohamed Guojiang Xiong Fatima Zohra Khechiba Khadidja Â Kherchouche Department of Computer Science and Information Technology Kasdi Merbah UniversityP.O.Box 30000OuarglaAlgeria Department of Computer Science College of Computing and InformaticsUniversity of SharjahP.O.Box 27272SharjahUnited Arab Emirates Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied Science Research Center Applied Science Private UniversityAmman11937Jordan Guizhou Key Laboratory of Intelligent Technology in Power System College of Electrical EngineeringGuizhou UniversityGuiyang550025China

Hybridizing metaheuristic algorithms involves synergistically combining different optimization techniques to effectively address complex and challenging optimization *** approach aims to leverage the strengths of multiple algorithms,enhancing solution quality,convergence speed,and robustness,thereby offering a more versatile and efficient means of solving intricate real-world optimization *** this paper,we introduce a hybrid algorithm that amalgamates three distinct metaheuristics:the Beluga Whale Optimization(BWO),the Honey Badger Algorithm(HBA),and the Jellyfish Search(JS)*** proposed hybrid algorithm will be referred to as *** this fusion,the BHJO algorithm aims to leverage the strengths of each *** this hybridization,we thoroughly examined the exploration and exploitation capabilities of the BWO,HBA,and JS metaheuristics,as well as their ability to strike a balance between exploration and *** meticulous analysis allowed us to identify the pros and cons of each algorithm,enabling us to combine them in a novel hybrid approach that capitalizes on their respective strengths for enhanced optimization *** addition,the BHJO algorithm incorporates Opposition-Based Learning(OBL)to harness the advantages offered by this technique,leveraging its diverse exploration,accelerated convergence,and improved solution quality to enhance the overall performance and effectiveness of the hybrid ***,the performance of the BHJO algorithm was evaluated across a range of both unconstrained and constrained optimization problems,providing a comprehensive assessment of its efficacy and applicability in diverse problem ***,the BHJO algorithm was subjected to a comparative analysis with several renowned algorithms,where mean and standard deviation values were utilized as evaluation *** rigorous comparison aimed to assess the performance of the BHJOalgorithmabout its counterparts,shedd

关键词： Global optimization hybridization of metaheuristics beluga whale optimization honey badger algorithm jellyfish search optimizer chaotic maps opposition-based learning

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Large magnetocaloric effect and magnetic properties of EuRhO_(3)

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Journal of Rare Earths 2024年第9期42卷 1724-1729,I0004页

作者： M.Lassri M.Sajieddine A.Elouafi A.El Hachmi S.El Ouahbi R.Moubah Laboratory of Energy and Materials Engineering(LGEM) University of Sultan Moulay SlimaneFaculty of Science and Technology(FST)BP 52323000Béni-MellalMorocco Institute of Applied Physics(IAP)-School of Industrial Management(EMINES) Mohammed Ⅵ Polytechnic UniversityHay Moulay RachidLot 6603150Ben GuerirMorocco National School of Applied Sciences(ENSA) University of Sultan Moulay SlimaneBP 7725000KhouribgaMorocco Laboratory of Mechanics Production and Industrial Engineering(LMPGI)Higher School of Technology of Casablanca(ESTC)University of Hassan Ⅱ CasablancaCasablancaMorocco Laboratory of Radiation on Matter and Instrumentation(LRMI) Faculty of Science and Technology(FST)SettatHassan Ⅰ UniversitySettatMorocco Laboatory of Physics of Advanced Materials and Thermic(LPMAT) Faculty of Science Ain Chock(FSAC)University of Hassan Ⅱ CasablancaCasablancaMorocco

We report on the structural,magnetic,and magnetocaloric properties of EuRhO_(3) *** oxidation states of Eu and Rh ions were studied using X-ray photoelectron spectroscopy(XPS).It is found that the Eu ions are mainly in the divalent oxidation state while the Rh ions have+4 ***_(3) powders are found to be antiferromagnetic with a second order magnetic transition at Neel temperature(T_(N)=2.9 K).Analysis of the magnetic susceptibility versus temperature data in terms of the Curie=Weiss law:(χ=C/(T-θ_(W))) for T>T_(N),yields θ_(W)=-3.1 K and effective magne tic moment μ_(ff)^(exp),which is close to the theoretical value μ_(eff)^(theo).The magnetic entropy change(-Δ_(SM)),was determined by em ploying the thermodynam ic Maxwell's *** μ_0H=5 T and near T_(N),ΔS_(M)^(Max) and relative cooling power(RCP) exhibit large values of 33.7 J/(kg·K) and 238 J/kg,*** large magnitude of-Δ_(SM) and RCP show that the EuRhO_(3) compound could be a potential candidate to be used in cryogenic magnetic refrigeration.

关键词： X-ray photoelectron spectroscopy Cryogenic magnetic refrigeration Magnetic properties Magnetocaloric effect Rare earths

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AI generated route data pre-processing for faster decision making 8

AI generated route data pre-processing for faster decision m...

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8th International Young Engineers Forum on Electrical and computer Engineering, YEF-ECE 2024

作者： Maas, Rene Shevtshenko, Eduard Karaulova, Tatjana TTK University of Applied Sciences Institute of Logistics Faculty of Science and Technology University of Tartu Institute of Computer Science Tallinn Estonia Tallinn University of Technology TTK University of Applied Sciences Department of Mechanical and Industrial Engineering Institute of Logistics Tallinn Estonia

ISBN: (纸本)9798350387643

The industry is constantly generating new data, allowing take advantage of their use to increase manufacturing efficiency through the reutilisation of operational *** such possibility is to use Artificial Intelligence (AI). While AI is heralded as a solution for industry efficiency and accuracy quandaries through process automation, its implementation grapples with the issue of inaccurate production data used for training, giving an erroneous *** article introduces a framework to facilitate the integration of AI tools within companies. The focus is on the accuracy of predicting normative times and selecting alternative routes when accuracy is low. This approach improves the price quotation prediction process, where using AI is practical due to time constraints. Making quick and accurate decisions is crucial for maintaining efficiency in *** elucidate the functionality, the authors have performed a case study in production for the framework's validation. The wood production sector was selected due to its lower operational complexity than machinery construction, resulting in time savings in the planning *** study revealed that the prediction accuracy of AI was 70% on average for operations normative times. To improve this accuracy, the t-Test method to classify operations was used. This approach eliminates operations with low AI prediction accuracy when making price quotations. Through the case study, AI module accuracy reached 80%, while the additional data collection volume decreased by one-Third. © 2024 IEEE.

关键词： Machine Learning Normative Times Wood Industry

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A Comparative Analysis of Liquid Neural Networks and Incremental Learning Approaches for Stock Market Prediction

A Comparative Analysis of Liquid Neural Networks and Increme...

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2025 International Conference on Control, Automation, and Instrumentation, IC2AI 2025

作者： Jammal, Hussein Srour, Farah Salman, Ali Owayjan, Michel Ayoub, Omran Rottondi, Cristina Achkar, Roger American University of Science & Technology Faculty of Engineering and Computer Science Beriut Lebanon Politecnico di Torino Italy Nantes University Saint-Nazaire France University of Applied Sciences of Southern Switzerland Switzerland

ISBN: (纸本)9798331529604

Due to the complexity, challenge, and fast growth of stock markets, they encourage more efficient use of financial resources and the expansion of macroeconomics. Tesla and Apple stock prices fluctuate constantly due to the impact of various industries and market conditions. The extraction of previously unknown patterns and information from time series is central to numerous real-world applications. This paper presents a comparative study of stock market prediction techniques for Tesla and Apple stocks, focusing primarily on the application of Liquid Neural Networks (LNN) and evaluating their performance against Incremental Learning methods. Employing LNN, a novel approach in the field of time-series forecasting, we developed models that leverage the dynamic and flexible structure of LNN to adapt to the complex and non-linear patterns observed in stock prices. The performance of the LNN model was quantitatively assessed using standard metrics: Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and Directional Accuracy. The LNN model achieved an MSE of 0.000317, RMSE of 0.0178, MAE of 0.014131, MAPE of 1.8%, and a Directional Accuracy of 49.36%. In contrast, the Incremental Learning approach yielded an MSE of 0.54355, RMSE of 0.73725, MAE of 0.73158, MAPE of 89.39%, and Directional Accuracy of 28.37%. These results underscore the superior accuracy and effectiveness of LNNs in modeling stock market behaviors compared to traditional Incremental Learning methods. The findings not only demonstrate the potential of LNNs in financial analytics but also suggest avenues for further research into enhancing predictive accuracy and model robustness. © 2025 IEEE.

关键词： Contrastive Learning

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