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Regularization of the Inverse Problem for Time Fractional Pseudo-parabolic Equation with Non-local in Time Conditions

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Acta Mathematica Sinica,English Series 2022年第12期38卷 2199-2219页

作者： Nguyen Duc PHUONG Le Dinh LONG Anh Tuan NGUYEN Dumitru BALEANU Faculty of Fundamental Science Industrial University of Ho Chi Minh CityVietnam Division of Applied Mathematics Science and Technology Advanced InstituteVanLang UniversityHoChi Minh CityVietnam Faculty of Technology Van Lang UniversityHo Chi Minh CityVietnam Department of Mathematics Cankaya UniversityAnkaraTurkey Lebanese AmericanUniversity BeirutLebanon Institute of Space Sciences Magurele-BucharestRomania

This paper is devoted to identifying an unknown source for a time-fractional diffusion equation in a general bounded ***,we prove the problem is non-well posed and the stability of the source ***,by using the Modified Fractional Landweber method,we present regularization solutions and show the convergence rate between regularization solutions and sought solution are given under a priori and a posteriori choice rules of the regularization parameter,***,we present an illustrative numerical example to test the results of our theory.

关键词： Source problem fractional pseudo-parabolic problem ill-posed problem convergence estimates regularization

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XAI Based Cattle Identification with YOLO and SIFT Technique

XAI Based Cattle Identification with YOLO and SIFT Technique

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2024 IEEE International Conference on Future Machine Learning and Data science, FMLDS 2024

作者： Katharria, Aashu Pant, Millie Deep, Kusum Devi, Indu Mehta Family School of Data Science and Artificial Intelligence Indian Institute of Technology Roorkee Uttarakhand Roorkee India Applied Mathematics and Scientific Computing Indian Institute of Technology Roorkee Uttarakhand Roorkee India Indian Institute of Technology Roorkee Department of Mathematics Uttarakhand Roorkee India ICAR-National Dairy Research Institute Livestock Production Management Division Haryana Karnal132001 India

ISBN: (纸本)9798350391213

In precision livestock farming, accurate cattle identification is essential for enhancing animal welfare, health monitoring, and productivity, while also supporting traceability and minimizing false insurance claims. This paper presents a novel approach for cattle identification using muzzle prints, with a focus on both efficiency and explainability. Taxicab metric, employed for efficient annotation of muzzle patterns significantly reduces the labeling time for training of YOLOv8 model. YOLOv8 is utilized for detecting muzzle prints in images, followed by SIFT (Scale-Invariant Feature Transform) for feature extraction and matching. The incorporation of Explainable AI (XAI) methods, particularly Grad-CAM, further enhances the transparency and interpretability of the SIFT model. © 2024 IEEE.

关键词： Precision agriculture

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Next Level of Human-Robot Collaboration by Utilizing AI Pose Estimation and Model Predictive Motion Planning Technologies

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IFAC-PapersOnLine 2023年第2期56卷 5313-5319页

作者： Esteban Pozo Bishoy Gerges Mohammed Nafea Frank Schrödel Automation Technology & Robotics Schmalkalden University of Applied Sciences Germany Engineering Mathematics and Computer Science University of Twente Netherlands

Over recent years, there has been a significant focus on Human Robot Interaction (HRI). The aim of this interaction is to create a mutually beneficial partnership between humans and robots, with robots contributing precision, speed, and force, while humans provide experience, intuition, and high-level management and control strategy understanding. One of the most crucial factors in achieving a successful HRI is the guidance of these robots. This paper proposes the use of reliable Hand Detection based on Long Short-Term Memory (LSTM) and intelligent robot motion planning based on Model Predictive Control Methods (MPC) to detect hand signals and communicate with the robot. By utilizing vision systems, a micro controller-based Edge AI approach, and a wired connection, the reaction speed of the robot can be optimized to maintain a safe separation distance between the human operator and the robot, thus enabling a collaborative and safe environment. The effectiveness and capabilities of this automation framework are validated through a case study.

关键词： Optimal Control Artificial Intelligenc Modeling Guidance navigation and control Robots manipulators

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Enhancing Stability in Autonomous Control Systems Through Fuzzy Gain Scheduling (FGS) and Lyapunov Function Analysis

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International Journal of applied and Computational mathematics 2024年第4期10卷 1-15页

作者： Venkatesh, R. Rao, Deepak Dasaratha Sangeetha, V. Subbalakshmi, Ch. Bala Dhandayuthapani, V. Mekala, R. Department of Mathematics Hindusthan Institute of Technology Coimbatore 641032 India Indian Institute of Technology Patna India Department of Computer Science and Engineering Ramaiah Institute of Technology Bangalore India Department of Computer Science and Engineering Guru Nanak Instructions Technical Campus (Autonomous) Ibrahimpatnam Ranga Reddy District Telagana State Hyderabad 501506 India Department of IT College of Computing and Information Sciences University of Technology and Applied Sciences Shinas Campus Shinas Oman Department of Information Technology M.Kumarasamy College of Engineering Tamilnadu Karur India

Traditional control methods may struggle to adapt to the nonlinear and uncertain characteristics in Autonomous Vehicle Control. In recent years, fuzzy control techniques, such as the Takagi–Sugeno fuzzy controller, have emerged as promising approaches for handling such complexities. Fuzzy controllers utilize linguistic variables and fuzzy logic to model system behavior, offering flexibility and robustness in dealing with uncertainties. Furthermore, Lyapunov function analysis provides a powerful tool for assessing the stability of dynamical systems. By employing Lyapunov functions, researchers can mathematically prove the stability of a system and derive stability criteria, contributing to a deeper understanding of system behavior. This paper investigates the enhancement of stability in control systems by employing Fuzzy Gain Scheduling combined with Lyapunov function analysis. Stability is a crucial aspect of control systems, ensuring their reliable and efficient operation in various dynamic environments. Traditional control techniques often struggle to handle the nonlinear and uncertain nature of modern systems. FGS offers a flexible and adaptive approach to control by adjusting controller gains based on system operating conditions. Additionally, Lyapunov function analysis provides a rigorous mathematical framework for stability assessment, enabling the verification of system stability properties. By integrating FGS and Lyapunov function analysis, this research aims to develop a robust control strategy capable of ensuring stability across a range of operating conditions. Simulation and experimental results are presented to demonstrate the effectiveness of the proposed approach in enhancing stability and performance in control systems. Specifically, the settling time was reduced by 20%, and overshoot was minimized to 5% of the steady-state value. Furthermore, in experimental tests conducted on a real-world control system setup, the proposed approach demonstrated rob

关键词： Control systems Fuzzy gain scheduling (FGS) Lyapunov function analysis Performance Simulation Stability

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Availability of Perfect Decomposition in Statistical Linkage Learning for Unitation-based Function Concatenations

arXiv

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arXiv 2025年

作者： Prusik, Michal Frej, Bartosz Przewozniczek, Michal W. Faculty of Pure and Applied Mathematics Wroclaw University of Science and Technology Wroclaw Poland Departament of Systems and Computer Networks Wroclaw University of Science and Technology Wroclaw Poland

Statistical Linkage Learning (SLL) is a part of many state-of-the-art optimizers. The purpose of SLL is to discover variable interdependencies. It has been shown that the effectiveness of SLL-using optimizers is highly dependent on the quality of SLL-based problem decomposition. Thus, understanding what kind of problems are hard or easy to decompose by SLL is important for practice. In this work, we analytically estimate the size of a population sufficient for obtaining a perfect decomposition in case of concatenations of certain unitation-based functions. The experimental study confirms the accuracy of the proposed estimate. Finally, using the proposed estimate, we identify those problem types that may be considered hard for SLL-using optimizers. © 2025, CC BY-NC-ND.

关键词： Adversarial machine learning

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Thermal-Aware Channel Capacity

Thermal-Aware Channel Capacity

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2023 IEEE International Symposium on Information Theory, ISIT 2023

作者： Meng Chee, Yeow Etzion, Tuvi Schouhamer Immink, Kees A. Thanh Nguyen, Tuan Khu Vu, Van Weber, Jos H. Yaakobi, Eitan National University of Singapore Department of Industrial Systems Engineering and Management Singapore Technion - Israel Institute of Technology Department of Computer Science Haifa3200003 Israel Turing Machines Inc. Rotterdam3016 DK Netherlands Singapore University of Technology and Design Science Mathematics and Technology Cluster Singapore Delft University of Technology Department of Applied Mathematics Delft2628 CD Netherlands

ISBN: (纸本)9781665475549

High temperatures in electronic devices have a negative effect on their performance. Various techniques have been proposed and studied to address and combat this thermal challenge. To guarantee that the peak temperature of the devices will be bounded by some maximum temperature, the transmitted signal has to satisfy some *** this motivation, we study the constrained channel that only accepts sequences that satisfy prescribed thermal constraints. The main goal in this paper is to compute the capacity of this channel. We provide the exact capacity of the channel with some certain parameters and we also present some bounds on the capacity in various ***, we consider the model that multiple wires are available to use and find out the smallest number of wires required to satisfy the thermal constraints. © 2023 IEEE.

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Security framework for IoT and deep belief network-based healthcare system using blockchain technology

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International Journal of Electronic Business 2022年第3期17卷 226-243页

作者： Nagarajan, Senthil Murugan Anandhan, Prathik Muthukumaran, V. Uma, K. Kumaran, U. School of Computer Science and Engineering VIT-AP University Andhra Pradesh Amaravati India Department of Computer Science and Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India Department of Mathematics School of Applied Sciences REVA University Bengaluru India School of Advance Sciences Vellore Institute of Technology Vellore India Department of Computer Science and Engineering Amrita Vishwa Vidyapeetham Bengaluru India

Nowadays, the computerisation and information systems need very fast, easier and secure data analysis models. So, blockchain technology and deep learning concepts play important roles for data security and analysis in field of healthcare applications. Blockchain technology has optimal reliability in various sectors like healthcare, security, information management, smart home, etc. In this paper, blockchain technology is used for the healthcare system to provide a secure and reliable data transmission. Furthermore, IoT-based wearable devices are used to collect the data from the patients. Moreover, deep belief network (DBN) is proposed to classify the obtained data in order to predict the type of disease or problems of the patients. The experimental results shows that the proposed framework and classification model abruptly outperforms when compared with other existing techniques. The efficiency of the proposed framework is analysed based on the performance metrics like throughput and latency. The obtained loss ratio for the proposed model seems very less of 0.0126 when compared with other existing techniques like MLP, SVM, ANN, and CNN. The accuracy obtained for the proposed DBN classifier is above 95% for the increase in the number of patients. Copyright © 2022 Inderscience Enterprises Ltd.

关键词： Internet of things

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Modelling and control of a multi-product pipeline transportation process

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International Journal of Information technology (Singapore) 2025年 1-11页

作者： Jiménez-Cabas, Javier Piñeres-Espitia, Gabriel Rodelo-Serrano, Esteban Pamucar, Dragan Ramirez-Leon, Hermes Butt, Shariq Aziz Naz, Sumera Simic, Vladimir Computer Science and Electronic Department Universidad de La Costa Barranquilla Colombia Departamento de Ingeniería Mecánica Universidad Simón Bolívar Barranquilla Venezuela Department of Operations Research and Statistics Faculty of Organizational Sciences University of Belgrade Belgrade Serbia Department of Industrial Engineering & Management Yuan Ze University Taoyuan Taiwan Department of Mechanics and Mathematics Western Caspian University Baku Azerbaijan Faculty of Transport and Traffic Engineering University of Belgrade Vojvode Stepe 305 Belgrade 11010 Serbia Department of Computer Science and Engineering College of Informatics Korea University Seoul 02841 South Korea School of Systems and Technology Department of Computer Science University of Management and Technology Lahore Pakistan Department of Mathematics Division of Science and Technology University of Education Lahore Pakistan

One of the most critical processes in the petroleum industry is transporting crude oil and its derivatives. Usually, it is done, due to easiness and economic aspects, through pipelines;several products, such as gasoline, kerosene, naphtha, and liquefied petroleum gas, among others, are moved in batch processes to both distribution and storage centers or transport ships. Since these transport systems transport different products, many works have focused on developing optimization strategies for scheduling these pipelines. That is, strategies that seek to optimize the use of the pipeline by establishing at what time points certain products must be transported. These strategies would be located at the planning level in the automation pyramid. In this work, on the other hand, different control strategies are proposed for a pipeline, but at the operation level. These strategies would be located at the control level, below the planning strategies in the automation pyramid. A pipeline of three pipe sections is modeled to develop the proposed control strategies, and the mathematical model is validated with actual data. The results show that, first, the proposed model approximates the actual behavior of the pipeline quite well and, second, that the combination of PID and feedforward control is an excellent alternative to implement control strategies for the operation of liquid transportation systems through pipelines. © Bharati Vidyapeeth's Institute of computer Applications and Management 2025.

关键词： control strategies liquid transportation modeling of system

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Building Footprint Extraction in Dense Areas using Super Resolution and Frame Field Learning 12

Building Footprint Extraction in Dense Areas using Super Res...

引用

12th International Conference on Awareness science and technology, iCAST 2023

作者： Nguyen, Vuong Ho, Trong-Anh Vu, Duc-Anh Ngoc Anh, Nguyen Thi Thang, Tran Ngoc Department of Computer Science University of Houston HoustonTX United States Skymap Global Hanoi Viet Nam Nanyang Technological University Singapore School of Applied Mathematics and Informatics Hanoi University of Science and Technology Hanoi Viet Nam

ISBN: (纸本)9798350324693

Despite notable results on standard aerial datasets, current state-of-the-arts fail to produce accurate building footprints in dense areas due to challenging properties posed by these areas and limited data availability. In this paper, we propose a framework to address such issues in polygonal building extraction. First, super resolution is employed to enhance the spatial resolution of aerial image, allowing for finer details to be captured. This enhanced imagery serves as input to a multitask learning module, which consists of a segmentation head and a frame field l earning h ead t o e ffectively h andle t he irregular building structures. Our model is supervised by adaptive loss weighting, enabling extraction of sharp edges and fine-grained polygons which is difficult due to overlapping buildings and low data quality. Extensive experiments on a slum area in India that mimics a dense area demonstrate that our proposed approach significantly outperforms the current state-of-the-art methods by a large margin. © 2023 IEEE.

关键词： Extraction

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Solutions of stationary McKean-Vlasov equation on a high-dimensional sphere and other Riemannian manifolds

arXiv

引用

arXiv 2024年

作者： Shalova, Anna Schlichting, André Department of Mathematics and Computer Science Eindhoven University of Technology Netherlands Institute of Applied Analysis Ulm University Germany

We study stationary solutions of McKean-Vlasov equation on a high-dimensional sphere and other compact Riemannian manifolds. We extend the equivalence of the energetic problem formulation to the manifold setting and characterize critical points of the corresponding free energy functional. On a sphere, we employ the properties of spherical convolution to study the bifurcation branches around the uniform state. We also give a sufficient condition for an existence of a discontinuous transition point in terms of the interaction kernel and compare it to the Euclidean setting. We illustrate our results on a range of system, including the particle system arising from the transformer models and the Onsager model of liquid crystals. Copyright © 2024, The Authors. All rights reserved.

关键词： Spheres

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