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Information Centric Networking Based Cooperative Caching Framework for 5G Communication Systems

computers, Materials & Continua 2024年第9期80卷 3945-3966页

作者： R.Mahaveerakannan Thanarajan Tamilvizhi Sonia Jenifer Rayen Osamah Ibrahim Khalaf Habib Hamam Department of Computer Science and Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical SciencesChennai602105India Department of Computer Science and Engineering Panimalar Engineering CollegeChennai600123India Department of Computer Science and Engineering Sathyabama Institute of Science and TechnologyChennai600119India Department of Solar Energy Al-Nahrain Research Center for Renewable EnergyAl-Nahrain UniversityJadriyaBaghdad64074Iraq Faculty of Engineering Universitéde MonctonNew BrunswickE1A3E9Canada Hodmas University College Mogadishu521376Somalia Bridges for Academic Excellence Tunis1002Tunisia School of Electrical Engineering University of JohannesburgAuckland ParkJohannesburg2006South Africa

The demands on conventional communication networks are increasing rapidly because of the exponential expansion of connected multimedia *** light of the data-centric aspect of contemporary communication,the information-centric network(ICN)paradigm offers hope for a solution by emphasizing content retrieval by name instead of *** 5G networks are to meet the expected data demand surge from expanded connectivity and Internet of Things(IoT)devices,then effective caching solutions will be required tomaximize network throughput andminimize the use of ***,an ICN-based Cooperative Caching(ICN-CoC)technique has been used to select a cache by considering cache position,content attractiveness,and rate *** findings show that utilizing our suggested approach improves caching regarding the Cache Hit Ratio(CHR)of 84.3%,Average Hop Minimization Ratio(AHMR)of 89.5%,and Mean Access Latency(MAL)of 0.4 *** a framework,it suggests improved caching strategies to handle the difficulty of effectively controlling data consumption in 5G *** improvements aim to make the network run more smoothly by enhancing content delivery,decreasing latency,and relieving *** improving 5G communication systems’capacity tomanage the demands faced by modern data-centric applications,the research ultimately aids in advancement.

关键词： Information-centric networking caching schemes 5G communication non-negative matrix factorization(NMF) weighted clustering algorithm

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Performance Comparison of the Invasive Weed Optimization K-Means Algorithm With Particle Swarm Optimization K-Means for Banking Data 6

Performance Comparison of the Invasive Weed Optimization K-M...

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6th International Conference on Cybernetics and Intelligent System, ICORIS 2024

作者： Suwirmayanti, Ni Luh Gede Pivin Putra, I. Ketut Gede Darma Sudarma, Made Sukarsa, I. Made Setyaningsih, Emy Department of Computer Systems Faculty of Informatics and Computer Institut Teknologi dan Bisnis STIKOM Bali Bali Indonesia Department of Information Technology Faculty of Engineering Udayana University Jimbaran Hill Bali Indonesia Department of Electrical Engineering Faculty of Engineering Udayana University Jimbaran Hill Bali Indonesia Department of Computer Systems Engineering Faculty of Applied Science Universitas AKPRIND Indonesia Yogyakarta Indonesia

ISBN: (纸本)9798331539603

Banking produces extensive and diverse data, so a clustering process is needed to understand customer behavior patterns and transactions more effectively. This clustering has been widely utilized with the K-Means algorithm due to its simplicity and efficiency. However, this algorithm is limited in determining the optimal cluster center, affecting the accuracy of the clustering results. This study proposes applying two metaheuristic algorithms, Invasive Weed Optimization (IWO) and Particle Swarm Optimization (PSO), as additional solutions combined with K-Means. These two algorithms were chosen because of their ability to find global solutions and convergence speed to handle large and complex banking data. The results show the superiority of IWOKM compared to PSOKM in terms of SSE and DBI. From the SSE value, IWOKM produces a lower value (3029.77), which indicates that this method is better at minimizing clustering errors and producing more accurate clustering than PSOKM (80007.09). From the DBI value, IWOKM also produces a better value (1.6684) than PSOKM (1.6782), which shows that the clusters produced by IWOKM are more compact and more separated. However, in terms of computation time, PSOKM is more efficient, with a faster average computation time. Although IWOKM produces better clustering quality, PSOKM offers advantages in terms of processing speed. This finding confirms that the selection of the IWO algorithm is more appropriate for use on datasets with characteristics such as the German Credit Dataset. © 2024 IEEE.

关键词： Invasive weed optimization

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A Simplified Technique Of Design For Double Density Wavelets With Enhanced Denoising APPLICATIONS 40

A Simplified Technique Of Design For Double Density Wavelets...

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40th National Radio science Conference, NRSC 2023

作者： Fahmy, Gamal Fahmy, Mamdouh F. Fahmy, Omar Galala University Faculty of Computer Science and Engineering Egypt Assiut University Electrical Engineering Dept. Assiut Egypt Badr University in Cairo Electrical Engineering Dept. Egypt

ISBN: (纸本)9798350311440

Denoising Images is a crucial step in noise removal in any data or image communication problem. Recently two image denoising techniques were presented that depends on bivariate analysis. These two techniques were called Double Density Discrete Wavelet Transform (DD DWT) and Double Density Dual Tree Complex Wavelet Transform (DD CWT). They relayed on the decomposition of noisy images with either DD CWT or DD DWT decompositions. This decomposition was after the bivariate based shrinkage technique was applied to exploit the wavelet parent and children correlation for better denoising performance. In this paper we present a novel filter design technique for a DD DWT structure for denoising applications. It composed of 3 dimensional cascaded orthogonal sections. This proposed 3-channel Double Density Wavelet decomposition structure is simple and is fast in terms of convergence. It overcomes most problems for other filter design techniques of being slowly iterative and relays on randomness in parameter optimization. The proposed filter design DD-DWT structure guarantees the Perfect Reconstruction PR and the Alias Cancellation AC conditions and is suitable for VLSI iterative designs. Illustrative examples for the usage of the proposed DD-DWT based design in different image denoising applications are shown in comparison with other denoising structures from recent literature. © 2023 IEEE.

关键词： Image denoising

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Hyperbolic Distance Based on EMD and Diffusion for Hyperspectral Imaging

Hyperbolic Distance Based on EMD and Diffusion for Hyperspec...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Elad Lavi Amir Bourvine Ya-Wei Eileen Lin Ronen Talmon Taub Faculty of Computer Science Technion Viterbi Faculty of Electrical and Computer Engineering Technion

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

In this paper, we introduce EMD-Based Hyperbolic Diffusion Distance (EMD-HDD), a new method for constructing a meaningful distance metric for hierarchical data with latent hierarchical structure. Our method relies on hyperbolic geometry, diffusion geometry, and the Earth Mover’s Distance (EMD). Specifically, our method embeds data points into a product manifold of hyperbolic spaces, allowing us to recover the hidden hierarchical structure encoded by the mutual relationships between features. We demonstrate the effectiveness of EMD-HDD through experiments on five hyperspectral imaging datasets, showcasing its capability to capture and reveal the intrinsic hierarchical structures inherent in such data.

关键词： Manifolds Geometry Measurement Earth Imaging Signal processing Acoustics Speech processing Hyperspectral imaging

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MetaCon: Revitalizing Internet Congestion Control with Meta-Reinforcement Learning

MetaCon: Revitalizing Internet Congestion Control with Meta-...

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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Bai, He Li, Hui Que, Jianming Zhang, Minglong Chong, Peter Han Joo Sudheera, Kalupahana Liyanage Kushan Pei, Xinyuan School of Electronic and Computer Engineering Peking University Shenzhen China School of Computer Science Fuyao University of Science and Technology Fuzhou China Department of Electrical and Computer Engineering Mississippi State University Starkville United States School of Engineering Computer and Mathematical Sciences Auckland University of Technology Auckland New Zealand Department of Electrical and Information Engineering Faculty of Engineering University of Ruhuna Sri Lanka

ISBN: (纸本)9798350368741

Effective congestion control algorithms (CCAs) are crucial for the smooth operation of Internet communication infrastructure. CCAs adjust transmission rates based on congestion signals, optimizing resource utilization and user experience. However, existing studies, both rule-based and learning-based CCAs, often struggle with generalization and underperform when deployed in real-world environments. When applied to unseen network conditions, hand-crafted schemes or pre-trained models may experience significant performance degradation. To address this challenge, we propose MetaCon, a novel adaptive Internet congestion control approach based on meta-reinforcement learning. MetaCon leverages knowledge learned from prior scenarios to quickly adapt to new environments. Experimental results show that MetaCon outperforms existing algorithms by exhibiting superior generalization and achieving better transmission performance across a wide variety of network conditions. © 2025 IEEE.

关键词： communication network congestion control meta-learning reinforcement learning transport protocol

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Volumetric Corpus Callosum segmentation integrated to inCCsight software for supporting DTI-based studies

Volumetric Corpus Callosum segmentation integrated to inCCsi...

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Medical Imaging 2023: computer-Aided Diagnosis

作者： Alcantara, João Vitor Rodrigues, Joany Julio, Paulo Rogério Appenzeller, Simone Rittner, Leticia School of Electrical and Computer Engineering University of Campinas Brazil Rheumatology Department Faculty of Medical Science University of Campinas Brazil

ISBN: (纸本)9781510660359

The Corpus Callosum is the major interhemispheric commisure and, because of its highly organized fibers, it is often studied using diffusion tensor images (DTI). A firstnecessary step for CC studies is its segmentation, preferably automated. Since most available softwares are not able to perform CC volumetric segmentation, and the only ones that do it, are based on T1-weighted images and not DTI, this work presents the extension of an open-source software, called inCCsight, incorporating a DTI-based CC volumetric segmentation method into it. The software is open-source and offers the possibility of incorporating customized plots and integrating other segmentation and/or parcellation methods by the user. © 2023 SPIE.

关键词： Open source software

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Visualizing Code Syntax: Empowering Developers with a Global View for Enhanced Code Quality Evaluation 16

Visualizing Code Syntax: Empowering Developers with a Global...

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16th International Conference on Advanced computer Theory and engineering, ICACTE 2023

作者： Adjel, Chaima Atil, Fadila Meslati, Djamel Laboratory Lisco University Badji Mokhtar-Annaba Faculty of Electrical Engineering and Computing Computer Science Departement Annaba Algeria

ISBN: (纸本)9798350317534

This article discusses the issues that come with system evolution, specifically the challenges of comprehending and maintaining old code created by unreachable developers. In this instance, we want to highlight the value of using code visualization to get a global perspective of the components and their dependencies, since this can assist in recognizing any possible structural problems. Additionally, visualization can shed light on the code's scalability and performance properties. A well-written program with clear syntax that respects low coupling and separation of concerns makes system maintenance and evolution easier, which saves time and money. Adopting a scalable and flexible language also makes maintenance and development smoother. In this paper, we made a visualization of Mage code in order to evaluate its syntax flexibility and scalability. © 2023 IEEE.

关键词： Visualization

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SEMU5G: an Emulator for Improving Model Accuracy and Performance Evaluation of 5G Network Core Architectures based on SDN 10

SEMU5G: an Emulator for Improving Model Accuracy and Perform...

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10th International Conference on Wireless and Telematics, ICWT 2024

作者： Zaki Hamidi, Eki Ahmad Lazuardi, Arga Valen Rahmansyah, Muhammad Litfan Novel Bajri, Salman Alfarizi Tulloh, Rohmat Negara, Ridha Muldina Ahdan, Syaiful Jupriyadi UIN Sunan Gunung Djati Bandung Electrical Engineering Department Bandung Indonesia Telkom University Telecommunication Technology School of Applied Science Bandung Indonesia The University Center of Excellence Intelligent Sensing-IoT Telkom University Indonesia Telkom University School of Electrical Engineering Bandung Indonesia Universitas Teknokrat Indonesia Faculty of Engineering & Computer Science Indonesia Institut Teknologi Bandung School of Electrical Engineering and Informatics Bandung Indonesia Universitas Teknokrat Indonesia Faculty of Engineering and Computer Science Bandarlampung Indonesia

ISBN: (纸本)9798350377057

The rapid advancement of 5G Radio Access Network (RAN) architecture is facilitating the construction of 5G networks, marking a significant milestone in telecommunications evolution. Given the complexity of the 5G core architecture, traditional simulation methods are insufficient, necessitating novel approaches. Emulator systems are crucial for creating dynamic, controlled environments that enable exploration of real-world scenarios without physical constraints. SEMU5G, a 5G core emulator, SDN controller, and RAN simulator, utilizes Open5GS implemented in Docker Container for test system flexibility and isolation. Additionally, an SDN controller is integrated to monitor data flows in the User Plane Function (UPF) and gNB simulated by UERANSIM in Mininet-WiFi. This comprehensive integration facilitates effective and flexible real-world exploration, providing a dynamic and controlled test environment for 5G core research. Scenario testing comprises two stages: firstly, a fixed network topology is employed to compare resource usage and confirm successful SEMU5G integration. Secondly, a mobile network topology is utilized to implement a mobile device scenario and compare the Quality of Service (QoS) of SEMU5G with other available emulators. These stages ensure thorough evaluation of SEMU5G's performance and its comparative advantage over existing solutions. © 2024 IEEE.

关键词： Wi-Fi

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Enhancing single-lead electrocardiogram arrhythmia detection with empirical mode decomposition

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Neural Computing and Applications 2025年第17期37卷 11583-11605页

作者： Issa, Mohamed F. Yousry, Ahmed Tuboly, Gergely Wang, Zeyu Zoltan, Juhasz Selim, Mazen M. AbuEl-Atta, Ahmed H. Department of Scientific Computing Faculty of Computers and Artificial Intelligence Benha University Benha13511 Egypt Department of Computer Science Faculty of Computers and Artificial Intelligence Benha University Benha13511 Egypt Department of Electrical Engineering and Information Systems University of Pannonia Veszprem8200 Hungary Department of Mechatronics Delta University for Science and Technology Gamasa35712 Egypt

Cardiac arrhythmias pose a significant challenge to health care, requiring accurate and reliable detection methods to enable early diagnosis and treatment. However, traditional ECG beat classification methods often lack robustness and fail to generalize effectively to diverse clinical scenarios, particularly when using single-lead-I recordings, which are less studied compared to lead II. To address this gap, this paper proposes a novel method that combines deep learning and empirical mode decomposition (EMD) for arrhythmia detection using single-lead-I ECG recordings obtained with electrodes on each hand. The hybrid model comprises 149 layers of one-dimensional convolution, max pooling, and residual blocks. By leveraging EMD, it classifies ECG beats into normal beats, premature ventricular contractions, and atrial premature beats with high sensitivity (99.86%, 99.72%, and 99.84%, respectively) using the first four intrinsic mode functions (IMFs). The proposed method is applicable in clinical and out-of-hospital monitoring scenarios, and an accompanying web application provides real-time analysis and diagnostic results. This approach addresses a critical gap in lead-I ECG analysis, enhancing diagnostic precision and expanding the scope of ECG applications in health care. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2025.

关键词： Empirical mode decomposition

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Ocean Swell Height Estimation From Spaceborne GNSS-R Data Using Tree Model Based Machine Learning Methods 13

Ocean Swell Height Estimation From Spaceborne GNSS-R Data Us...

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13th IEEE/OES Current, Waves and Turbulence Measurement, CWTM 2024

作者： Bu, Jinwei Wang, Qiulan Liu, Xinyu Li, Linghui Zhang, Yongfeng Huang, Weimin Kunming University of Science and Technology Faculty of Land Resources Engineering Kunming China Memorial University of Newfoundland Department of Electrical and Computer Engineering St. John's Canada

ISBN: (纸本)9798350393910

Global navigation satellite system-reflectometry (GNSS-R), as an emerging observation method, has recently been applied to the retrieval of swell height. Existing research typically uses feature observables extracted from delay Doppler maps (DDMs) to construct empirical geophysical model functions (GMFs) for estimating swell height. However, using multiple variable parameters as model inputs poses significant challenges. For this purpose, we study the development of a multivariate regression model for swell height estimation using spaceborne GNSS-R data from the CYGNSS satellite and machine learning methods based on tree models (i.e. Random Forest (RF), Decision Tree (DT), Gradient Boosting Decision Tree (GBDT), eXtreme Gradient Boosting (XGBoost), and Light Gradient Boosting Machine (LightGBM)). To test the performance of the proposed model, ERA5 and Wavewatch III (WW3) data were used as reference data. The results showed that when ERA5 was used as the reference data, the proposed RF model performed the best among the five models, with root mean square error (RMSE) and correlation coefficient (CC) being better than 0.411 m and 0.83, respectively. When WW3 was used as reference, the RMSE and CC are better than 0.496 m and 0.84 m, respectively. The method proposed in this article provides a new approach for inverting global swell heights using CYGNSS data. © 2024 IEEE.

关键词： Decision trees

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