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European Control Conference (ECC)

作者： João Victor Galvão Da Mata Anders Hansson Martin S. Andersen Department of Applied Mathematics and Computer Science Technical University of Denmark Department of Electrical Engineering Linköping University.

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

This paper introduces a novel direct approach to system identification of dynamic networks with missing data based on maximum likelihood estimation. Dynamic networks generally present a singular probability density function, which poses a challenge in the estimation of their parameters. By leveraging knowledge about the network's interconnections, we show that it is possible to transform the problem into a more tractable form by applying linear transformations. This results in a nonsingular probability density function, enabling the application of maximum likelihood estimation techniques. Our preliminary numerical results suggest that when combined with global optimization algorithms or a suitable initialization strategy, we are able to obtain a good estimate of the dynamics of the internal systems.

关键词： Maximum likelihood estimation Sensitivity Heuristic algorithms Transfer functions Optimization methods Transforms Probability density function

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Beamforming Design Toward Sum-Rate Maximization for Holographic Active RIS-Aided Uplink Near-Field Communications

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IEEE Internet of Things Journal 2025年第12期12卷 18582-18595页

作者： Singh, Sandeep Singh, Keshav Singh, Sandeep Kumar Shin, Hyundong Duong, Trung Q. National Sun Yat-sen University International Master’s Program in Telecommunication Engineering Kaohsiung80424 Taiwan National Sun Yat-sen University Institute of Communications Engineering Kaohsiung80424 Taiwan Kyung Hee University Department of Electronic Engineering Gyeonggi Yongin17104 Korea Republic of Motilal Nehru National Institute of Technology Allahabad Department of Electronics and Communication Engineering Prayagraj211004 India Memorial University Faculty of Engineering and Applied Science St. John’sA1C 5S7 Canada Queen’s University Belfast School of Electronics Electrical Engineering and Computer Science BelfastBT7 1NN United Kingdom

Holographically driven active reconfigurable intelligent surface (HARIS), leveraging densely packed subwavelength elements, overcomes the limitations of conventional RIS in signal processing, unlocking advanced capabilities for next-generation networks. Thus, to exploit its full potential, this work proposes the integration of HARIS into an Internet of Things (IoT) multiuser uplink near-field-driven wireless communication system. A sum-rate maximization problem is formulated to provide efficient resource utilization by jointly optimizing the equalizer design, power allocation at each IoT user, and the HARIS phase shift, while satisfying strict constraints of Quality-of-Service (QoS) requirement and limited power budget at each IoT user and HARIS. Due to the nonconvex nature of the problem, we propose an alternating optimization (AO)-based algorithm, incorporating techniques, such as minimum-mean-square error (MMSE), convex upper bound approximation, and semidefinite relaxation (SDR). Then, extensive simulations validate the algorithm’s efficacy and convergence, demonstrating up to 63% higher performance with HARIS than passive RIS. Additionally, we highlight that near-field communication yields up to 90% higher sum-rate than hybrid 76% and far-field model 73%. Moreover, we demonstrate the impact of imperfect channel state information (iCSI) on the system performance. © 2014 IEEE.

关键词： Mean square error

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Comparison between alternative droop control strategy, modified droop method and control algorithm technique for parallel-connected converters

AIMS Electronics and Electrical Engineering

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AIMS Electronics and Electrical engineering 2021年第1期5卷 1-23页

作者： Shebani, Muamer M. Tariq Iqbal, M. Quaicoe, John E. Department of Electrical and Computer Engineering Faculty of Engineering and Applied Science Memorial University of Newfoundland St. John’sNL Canada

Most of the active current sharing methods are based on a communication network. The communication link is also used with the improved droop control methods to achieve a precise load current sharing and regulate the voltage at the common DC bus. Conversely, the conventional droop method that is considered a decentralized method becomes more attractive for controlling parallel-connected converters in DC microgrids. The conventional droop methods’ main drawbacks are associated with the unequal load current sharing and voltage deviation at the common DC bus. In this paper, the modified droop method as a conventional droop method is augmented with a virtual droop and adaptive voltage control gains to improve the load current sharing and the voltage regulation, respectively. In contrast with other improved droop approaches, the control approach proposed in the paper does not require a communication link to exchange information between parallel modules. Instead, it uses the converters’ theoretical load regulation characteristics to estimate the voltage set point for each converter locally. The proposed virtual resistive gain manipulates the modified droop method to regulate each module’s droop gain, which ensures equal current sharing. The proposed method also eliminates the tradeoff between current sharing difference and voltage regulation by implementing the adaptive voltage control, which compares the estimated voltage at the point of common coupling with the rated bus value and adjusts the droop gains based on the compared values to ensure a constant voltage at various load conditions. The load current sharing and voltage restoration improvements of the proposed method versus the modified droop method and the control algorithm technique are observed in this paper. The proposed method’s effectiveness is demonstrated by MATLAB/Simulink simulation and validated by an experimental prototype. © 2021 the Author(s), licensee AIMS Press.

关键词： DC-DC converters

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Load-balancing system for SDN data center based on improved ant colony optimization

Load-balancing system for SDN data center based on improved ...

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2024 International Conference on computer Network Security and Software engineering, CNSSE 2024

作者： Zhou, Yue Wu, Wenlong Information Engineering Department Anhui Industry Polytechnic Anhui Tongling244000 China Graduate School La Consolacion University Philippines Bulacan Malolos3000 Philippines Computer Science College Guangzhou College of Applied Science and Technology Guangdong Zhaoqing526072 China

ISBN: (纸本)9781510680234

The load balancing strategy in the traditional network architecture system is limited to the limitations of the closed operating system of the network device and cannot effectively meet various communication environments. In SDN, a new network architecture with open programming, the load balancing system architecture of the SDN data center is designed. The traffic classification module is used to distinguish large and small flows. A load balancing mechanism based on the improved ant colony optimization is proposed for the forwarding of large flows. A weighted ECMP load balancing mechanism is used for the forwarding of small flows. The improved ant colony optimization considers the difference in link load status and optimizes the parameters of the ant colony optimization. Through experimental simulation and comparison with traditional load balancing algorithms ECMP and DLB algorithms, the advantages of the optimized ant colony optimization in terms of delay jitter, average link utilization and other indicators are verified. © 2024 SPIE.

关键词： Ant colony optimization

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Enhancing Convergence Efficiency in Federated Learning Models 25

Enhancing Convergence Efficiency in Federated Learning Model...

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25th International Arab Conference on Information Technology, ACIT 2024

作者： Samara, Ghassan Elhilo, Ala'Mazen Aljaidi, Mohammad Alamleh, Amneh Al-Mousa, Mohammad Rasmi Batyha, Radwan Alazaidah, Raed Bani-Bakr, Alaa Elrashidi, Ali Zarqa University Faculty of It Department of Computer Science Zarqa Jordan Zarqa University Faculty of Information Technology Zarqa Jordan Zarqa University Faculty of Information Technology Department of Data Science and Ai Zarqa Jordan Zarqa University Department of Cybersecurity Zarqa Jordan Applied Science Private University Faculty of Information Technology Amman Jordan Zarqa University Faculty of It Department of Cyber Security Zarqa Jordan University of Business and Technology Department of Electrical Engineering Jeddah21432 Saudi Arabia

ISBN: (纸本)9798331540012

This study evaluates federated learning models' performance compared to centralized models using the MNIST and CIFAR-10 datasets. Four models were tested: two Federated Learning models and two centralized models. The evaluation focused on accuracy, training rounds, and CO2 emissions, to optimize convergence and reducing energy consumption while maintaining strong model performance. The results showed that Federated learning models outperformed centralized models, with the Federated Learning MNIST model achieving 98.79% accuracy compared to 87.93% for the centralized model. Also, the accuracy of the Federated Learning CIFAR-10 model achieved 91.20% accuracy, exceeding the centralized model's 90.14%. The most accuracy improvements happened in the early training rounds. An adjusted hill-climbing technique was used to the centralized models, decreasing the number of iterations and CO2 emissions without significantly reducing accuracy. © 2024 IEEE.

关键词： Adversarial machine learning

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Modeling the One Class of Radionuclide Migration Processes in Soils under Non-Isothermal Conditions Using Perturbation Theory Methods 13

Modeling the One Class of Radionuclide Migration Processes i...

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13th International Conference on Advanced computer Information Technologies, ACIT 2023

作者： Bomba, Andrii Ostapchuk, Oksana Vovk, Roman Kopnicky, Miroslav National University of Water and Environmental Engineering Department of Computer Science and Applied Mathematics Rivne Ukraine Ivano-Frankivsk National Technical University of Oil and Gas Department of Software Engineering Ivano-Frankivsk Ukraine Catholic University in Ružomberok Department of Catholic Theology Spišská Kapitula Slovakia

Based on the synthesis of complex analysis methods, perturbation theory, and characteristics, a new approach has been developed for accounting for osmosis and temperature in predicting the migration processes of radionuclides under non-isothermal conditions in quasi-ideal porous media (in curved regions) bounded by streamlines and equipotential lines. The solution to the corresponding degenerate problem was obtained based on the developed method of nonlinear inversion of boundary value problem solutions into quasi-conformal mappings. An algorithm for calculating a uniformly dynamic grid, streamlines, and speed of ideal filtration field was constructed. With the developed method of characteristics, formulas for the approximate solution of diffusion-convection mass transfer problems in perturbed osmosis and heat filtration fields were obtained. © 2023 IEEE.

关键词： Porous materials

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Dimensional Homogeneity in Classifying Second-Order Differential Invariant Systems for Four-Dimensional Lie Algebras

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International Journal of applied and Computational mathematics 2024年第6期10卷 1-44页

作者： Ayub, Muhammad Sultan, Zahida Mahomed, F.M. Ijaz, Saima Department of Mathematics COMSATS University Islamabad Abbottabad Campus Abbottabad Pakistan Department of Mathematics Azad Jammu and Kashmir University Muzaffarabad Pakistan DSI-NRF Centre of Excellence in Mathematical and Statistical Sciences School of Computer Science and Applied Mathematics University of the Witwatersrand Wits 2050 Johannesburg South Africa Department of Mathematics University of Engineering and Technology Lahore 54000 Pakistan

This research investigates a specific mathematical structure called a nonsingular differential invariant structure, which plays a crucial role in describing physical phenomena through differential equations. Focusing on a four-dimensional Lie algebra in (1+3)-dimensional space, this study classifies these structures. Here, a method is developed to identify second-order differential invariants and showed how they translate into systems of three second-order ordinary differential equations for the specific case of a four-dimensional Lie algebra, and these invariants are presented in the form of list in Table 1. To further refine the analysis, these systems are classified based on their “dimensional homogeneity structure,” which reveals their behavior when scaling all variables. This sub-classification described in Table 2, goes beyond the initial broad categorization, potentially linking these structures to specific physical applications. Novelty: To best of our knowledge, the classification of nonsingular differential invariant structure in (1+3)-dimensional space of four-dimensional real Lie algebras and association of dimensional homogeneity structure in classification scheme are new contributions in algebraic classification problems in literature and never reported before this. Such type of classification scheme is fruitful in analysis of many physical systems. In addition, the algebraic properties of these peculiar invariant systems including integrability, are analysed in a detailed manner both mathematically and from a mechanics viewpoint. © The Author(s), under exclusive licence to Springer Nature India Private Limited 2024.

关键词： Classification Dimensional homogeneity Integrability Lie algebra Nonsingular differential invariants Systems of second-order ODEs

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Adjoint-Free 4D-Var Methods Via Line Search Optimization For Non-Linear Data Assimilation

arXiv

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arXiv 2023年

作者： Nino-Ruiz, Elias D. Diaz-Rodriguez, Jairo Applied Math and Computer Science Laboratory Department of Computer Science Universidad del Norte Colombia Department of Mathematics and Statistics York University Canada

This paper proposes two practical implementations of Four-Dimensional Variational (4D-Var) Ensemble Kalman Filter (4D-EnKF) methods for non-linear data assimilation. Our formulations' main idea is to avoid the intrinsic need for adjoint models in the context of 4D-Var optimization and, even more, to handle non-linear observation operators during the assimilation of observations. The proposed methods work as follows: snapshots of an ensemble of model realizations are taken at observation times, these snapshots are employed to build control spaces onto which analysis increments can be estimated. Via the linearization of observation operators at observation times, a line-search based optimization method is proposed to estimate optimal analysis increments. The convergence of this method is theoretically proven as long as the dimension of control-spaces equals model one. In the first formulation, control spaces are given by full-rank square root approximations of background error covariance matrices via the Bickel and Levina precision matrix estimator. In this context, we propose an iterative Woodbury matrix formula to perform the optimization steps efficiently. The last formulation can be considered as an extension of the Maximum Likelihood Ensemble Filter to the 4D-Var context. This employs pseudo-square root approximations of prior error covariance matrices to build control spaces. Experimental tests are performed by using the Lorenz 96 model. The results reveal that, in terms of Root-Mean-Square-Error values, both methods can obtain reasonable estimates of posterior error modes in the 4D-Var optimization problem. Moreover, the accuracies of the proposed filter implementations can be improved as the ensemble sizes are increased. © 2023, CC BY.

关键词： Optimization

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Hybrid Routing in VANETs Using OLSR and Q-Learning for Enhanced Performance 22

Hybrid Routing in VANETs Using OLSR and Q-Learning for Enhan...

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22nd IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2025

作者： Akermi, Wafa Alyaoui, Nouha Guiloufi, Awatef Benfradj Chabir, Karim Higher Institute of Applied Science and Technology Gafsa University Computer Science and Telecommunications Department Gafsa Tunisia National Engineering School of Gabes (ENIG) Gabes University Laboratory of Modeling Analysis and Control of Systems (MACS) Gabes Tunisia College of Computer Qassim University Departement of Computer Engineering Buraidh Saudi Arabia

ISBN: (纸本)9798331542726

High node mobility, rapid topology changes provide specific challenges for vehicular ad hoc networks (VANETs), which have an immediate impact on the routing protocols' performance. Traditional approaches, like the Optimized Link State Routing (OLSR) protocol, provide proactive route management but fail to fully account for critical dynamic parameters like link stability, relative vehicle speed, node distance, and bandwidth availability. This work proposes a hybrid method combining OLSR with Q-learning to facilitate real-time adaptive routing. The model leverages dynamic metrics to proactively evaluate links while employing Q-learning to optimize routing decisions based on rewards computed from performance factors like delay, packet loss rate, and link duration. Simulation results demonstrate that our approach significantly outperforms classic OLSR. The improvements include reduced packet loss rates, increased average throughput, lower average latency, and a reduction in control overhead. These findings confirm that integrating dynamic metrics and adaptive learning effectively addresses the challenges posed by VANETs. © 2025 IEEE.

关键词： OLSR Q-learning Routing VANET

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Vessels Segmentation in Angiograms Using Convolutional Neural Network: A Deep Learning Based Approach

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computer Modeling in engineering & sciences 2023年第7期136卷 241-255页

作者： Sanjiban Sekhar Roy Ching-Hsien Hsu Akash Samaran Ranjan Goyal Arindam Pande Valentina E.Balas School of Computer Science and Engineering Vellore Institute of TechnologyVellore632014India Department of Computer Science and Information Engineering Asia UniversityTaichung41354Taiwan Department of Medical Research China Medical University HospitalChina Medical UniversityTaichung406Taiwan Guangdong-Hong Kong-Macao Joint Laboratory for Intelligent Micro-Nano Optoelectronic Technology School of Mathematics and Big DataFoshan UniversityFoshan528000China Medica Superspecialty Hospital Kolkata700099India Automation and Applied Informatics Aurel Vlaicu University of AradArad310130Romania

Coronary arterydisease(CAD)has become a significant causeof heart attack,especially amongthose 40yearsoldor *** is a need to develop new technologies andmethods to deal with this *** researchers have proposed image processing-based solutions for CADdiagnosis,but achieving highly accurate results for angiogram segmentation is still a *** different types of angiograms are adopted for CAD *** paper proposes an approach for image segmentation using ConvolutionNeuralNetworks(CNN)for diagnosing coronary artery disease to achieve state-of-the-art *** have collected the 2D X-ray images from the hospital,and the proposed model has been applied to *** augmentation has been performed in this research as it’s the most significant task required to be initiated to increase the dataset’s ***,the images have been enhanced using noise removal techniques before being fed to the CNN model for segmentation to achieve high *** the output,different settings of the network architecture undoubtedly have achieved different accuracy,among which the highest accuracy of the model is 97.61%.Compared with the other models,these results have proven to be superior to this proposed method in achieving state-of-the-art results.

关键词： Angiogram convolution neural network coronary artery disease diagnosis of CAD image segmentation

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