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IEEE Annual Joint Conference: INFOCOM, IEEE computer and Communications Societies

作者： János Tapolcai Péter Babarczi Pin-Han Ho Lajos Rónyai Department of Telecommunications and Media Informatics Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Budapest Hungary Deptartment of Electrical and Computer Engineering University of Waterloo Canada Eötvös Loránd Research Network and Department of Algebra Institute for Computer Science and Control Institute of Mathematics Budapest University of Technology and Economics Budapest Hungary

Fast reroute (FRR) mechanisms that can instantly handle network failures in the data plane are gaining attention in packet-switched networks. In FRR no notification messages are required as the nodes adjacent to the failure are prepared with a routing table such that the packets are re-routed only based on local information. However, designing the routing algorithm for FRR is challenging because the number of possible sets of failed network links and nodes can be extremely high, while the algorithm should keep track of which nodes are aware of the failure. In this paper, we propose a generic algorithmic framework that combines the benefits of Integer Linear Programming (ILP) and an effective approach from graph theory related to constructive graph characterization of k-connected graphs, i.e., edge splitting-off. We illustrate these benefits through arborescence design for FRR and show that (i) due to the ILP we have great flexibility in defining the routing problem, while (ii) the problem can still be solved very fast. We demonstrate through simulations that our framework outperforms state-of-the-art FRR mechanisms and provides better resilience with shorter paths in the arborescences.

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Efficient handling of ACL policy change in SDN using reactive and proactive flow rule installation ( vol 14 , 14976 , 2024 )

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SCIENTIFIC REPORTS 2024年第1期14卷 1-19页

作者： Hussain, Mudassar Amin, Rashid Gantassi, Rahma Alshehri, Asma Hassan Frnda, Jaroslav Raza, Syed Mohsan Department of Computer Science and Creative Technologies Global College of Engineering and Technology CPO Ruwi 112 P.O Box 2546 Muscat Sultanate of Oman Department of Computer Science and IT University of Chakwal Chakwal 48800 Pakistan Department of Computer Science University of Engineering and Technology Taxila 47050 Pakistan Department of Electrical Engineering Chonnam National University Gwangju 61186 South Korea Department of Computer Science College of Computer Engineering and Science Prince Sattam Bin Abdulaziz University Alkharj 16273 Saudi Arabia Department of Quantitative Methods and Economic Informatics Faculty of Operation and Economics of Transport and Communications University of Zilina 01026 Zilina Slovakia Department of Telecommunications Faculty of Electrical Engineering and Computer Science VSB Technical University of Ostrava 70800 Ostrava Czech Republic SAMOVAR Telecom SudParis Institut Polytechnique de Paris 91120 Paris France

Software-defined networking (SDN) is a pioneering network paradigm that strategically decouples the control plane from the data and management planes, thereby streamlining network administration. SDN's centralized network management makes configuring access control list (ACL) policies easier, which is important as these policies frequently change due to network application needs and topology modifications. Consequently, this action may trigger modifications at the SDN controller. In response, the controller performs computational tasks to generate updated flow rules in accordance with modified ACL policies and installs flow rules at the data plane. Existing research has investigated reactive flow rules installation that changes in ACL policies result in packet violations and network inefficiencies. Network management becomes difficult due to deleting inconsistent flow rules and computing new flow rules per modified ACL policies. The proposed solution efficiently handles ACL policy change phenomena by automatically detecting ACL policy change and accordingly detecting and deleting inconsistent flow rules along with the caching at the controller and adding new flow rules at the data plane. A comprehensive analysis of both proactive and reactive mechanisms in SDN is carried out to achieve this. To facilitate the evaluation of these mechanisms, the ACL policies are modeled using a 5-tuple structure comprising Source, Destination, Protocol, Ports, and Action. The resulting policies are then translated into a policy implementation file and transmitted to the controller. Subsequently, the controller utilizes the network topology and the ACL policies to calculate the necessary flow rules and caches these flow rules in hash table in addition to installing them at the switches. The proposed solution is simulated in Mininet Emulator using a set of ACL policies, hosts, and switches. The results are presented by varying the ACL policy at different time instances, inter-packet de

关键词： ACL policy change Management Proactive flow rule installation Reactive flow rule installation SDN Security

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Multimodal Feature Extraction for Memes Sentiment Classification 2

Multimodal Feature Extraction for Memes Sentiment Classifica...

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2nd IEEE Conference on Information Technology and Data Science, CITDS 2022

作者： Ouaari, Sofiane Tashu, Tsegaye Misikir Horvath, Tomas Elte - Eötvös Loránd University Faculty of Informatics Department of Data Science and Engineering Pázmány Péter sétány 1/C Budapest1117 Hungary Institute of Computer Science Faculty of Science Pavol Jozef Šafárik University Jesenná 5 Košice040 01 Slovakia College of Informatics Kombolcha Institute of Technology Wollo University Kombolcha208 Ethiopia

ISBN: (数字)9781665496537

ISBN: (纸本)9781665496537

In this study, we propose feature extraction for multimodal meme classification using Deep Learning approaches. A meme is usually a photo or video with text shared by the young generation on social media platforms that expresses a culturally relevant idea. Since they are an efficient way to express emotions and feelings, a good classifier that can classify the sentiment behind the meme is important. To make the learning process more efficient, reduce the likelihood of overfitting, and improve the generalizability of the model, one needs a good approach for joint feature extraction from all modalities. In this work, we proposed to use different multimodal neural network approaches for multimodal feature extraction and use the extracted features to train a classifier to identify the sentiment in a meme. © 2022 IEEE.

关键词： computer vision

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Blockchain Solution For SMEs Cybersecurity Threats In E-Commerce

Blockchain Solution For SMEs Cybersecurity Threats In E-Comm...

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computer Science and Emerging Technologies (CSET), International Conference on

作者： Firas H. Zawaideh Waheeb Abu-Ulbeh Salameh A. Mjlae Yousef A. Baker El-Ebiary Yazeed Al Moaiad Sunanda Das Department of Cyber Security Faculty of Science and Informaiton Technology Irbid National University Irbid Jordan Cybersecurity Department Faculty of Administrative sciences and Informatics Al-Istiqlal University Palestine CS Department Prince Abdullah bin Ghazi Faculty of Information Technology Al-Balqa Applied University (BAU) Jordan Faculty of Informatics and Computing UniSZA Malaysia Faculty of Computer and Information Technology MEDIU Malaysia School of Computer Science and Engineering Jain University Bangalore India

The rapid growth of electronic commerce (e-commerce) has revolutionized the way Small and Medium-sized Enterprises (SMEs) conduct business, enabling them to reach global markets and unlock new growth opportunities. However, this digital transformation has also exposed SMEs to an escalating array of cybersecurity threats that could compromise their data, financial integrity, and reputation. Blockchain technology, known for its decentralized and immutable nature, has emerged as a potential solution to enhance the security and resilience of e-commerce operations for SMEs. This research paper aims to investigate the current state of cybersecurity preparedness among SMEs engaged in e-commerce and identify the prevalent threats they face in the digital landscape. To achieve this goal, the study incorporates systematic literature review (SLR) method to examine the best technological solution to address the cybersecurity issues faced by e-commerce organizations in this paper of SMEs operating in e-commerce to gather data on their security practices, incident history, and perceptions of cybersecurity risks. In the context of this research, blockchain technology will be explored as a potential mechanism to enhance the security of e-commerce operations for SMEs. The inherent features of blockchain, such as decentralization, transparency, and immutability, could help protect sensitive data and thwart cyberattacks. By exploring the integration of blockchain into e-commerce systems, the research aims to shed light on the potential benefits and challenges associated with its adoption by SMEs. The research findings will not only shed light on the prevailing cybersecurity practices within SMEs and highlight their vulnerabilities but will also explore how blockchain technology can be leveraged to address these challenges. By understanding these patterns and exploring the feasibility of blockchain integration, the research aims to provide comprehensive recommendations for enhancing cy

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Expressivity of Planning with Horn Description Logic Ontologies (Technical Report)

arXiv

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arXiv 2022年

作者： Borgwardt, Stefan Hoffmann, Jörg Kovtunova, Alisa Krötzsch, Markus Nebel, Bernhard Steinmetz, Marcel Faculty of Computer Science Technische Universität Dresden Germany Saarland University Saarland Informatics Campus Germany Faculty of Engineering University of Freiburg Germany

State constraints in AI Planning globally restrict the legal environment states. Standard planning languages make closed-domain and closed-world assumptions. Here we address open-world state constraints formalized by planning over a description logic (DL) ontology. Previously, this combination of DL and planning has been investigated for the light-weight DL DL-Lite. Here we propose a novel compilation scheme into standard PDDL with derived predicates, which applies to more expressive DLs and is based on the rewritability of DL queries into Datalog with stratified negation. We also provide a new rewritability result for the DL Horn-ALCHOIQ, which allows us to apply our compilation scheme to quite expressive ontologies. In contrast, we show that in the slight extension Horn-SROIQ no such compilation is possible unless the weak exponential hierarchy collapses. Finally, we show that our approach can outperform previous work on existing benchmarks for planning with DL ontologies, and is feasible on new benchmarks taking advantage of more expressive *** Codes 68 © 2022, CC BY.

关键词： Data description

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Influence of structural defects on charge density waves in 1T-TaS_(2)

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Nano Research 2023年第8期16卷 11528-11539页

作者： Iaroslav Lutsyk Karol Szalowski Pawel Krukowski Pawel Dabrowski Maciej Rogala Witold Kozlowski Maxime Le Ster Michal Piskorski Dorota A.Kowalczyk Wojciech Rys Rafal Dunal Aleksandra Nadolska Klaudia Toczek Przemyslaw Przybysz Ewa Lacinska Johannes Binder Andrzej Wysmolek Natalia Olszowska Jacek J.Kolodziej Martin Gmitra Takuma Hattori Yuji Kuwahara Guang Bian Tai-Chang Chiang Pawel J.Kowalczyk Faculty of Physics and Applied Informatics University of LodzPomorska 149/15390-236 LodzPoland Faculty of Physics University of WarsawPasteura 502-093 WarsawPoland Faculty of Physics Astronomyand Applied Computer ScienceJagiellonian UniversityLojasiewicza 1130-348 KrakowPoland National Synchrotron Radiation Centre SOLARIS Jagiellonian UniversityCzerwone Maki 9830-392 KrakówPoland Institute of Physics Faculty of SciencePavol JozefŠafárik University in KošicePark Angelinum 904001 KošiceSlovakia Institute of Experimental Physics Slovak Academy of SciencesWatsonova 4704001 KošiceSlovakia Department of Precision Engineering Graduate School of EngineeringOsaka University2-1 Yamada-okaSuita 565-0871Japan Department of Physics and Astronomy University of MissouriColumbiaMissouri 65211USA Department of Physics and Frederick Seitz Materials Research Laboratory University of Illinois at Urbana-ChampaignUrbanaIllinois 61801-3080USA

The influence of intrinsic defects of 1T-TaS_(2)on charge density waves(CDWs)is studied using scanning tunneling microscopy and spectroscopy(STM,STS),angle-resolved photoelectron spectroscopy(ARPES),and density functional theory(DFT).We identify several types of structural defects and find that most have a local character limited to a single CDW site,with a single exception which effectively behaves as a dopant,leading to band-bending and affecting multiple neighboring *** only one type of defect can be observed by STM topographic imaging,all defects are easily resolved in STS *** results indicate modulation of the Mott band gap commensurate with the CDW and breaking of the three-fold symmetry of electronic *** calculations(with included Coulomb interactions)are used to investigate the electronic structure,focusing on both sulfur vacancy and oxygen-sulfur *** sulfur vacancy system,characterized with a metallic behavior,is identified as the origin of one of the experimentally observed ***,the effect of oxidation of 1T-TaS_(2)depends on the substitution site,leading to the heterogeneity of electronic properties.

关键词： structural charge sulfur

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A Generative Approach to Enrich Arabic Story Text with Visual Aids 21

A Generative Approach to Enrich Arabic Story Text with Visua...

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Proceedings of the 10th International Conference on Software and Information engineering

作者： Jezia Zakraoui Somaya Al Maadeed Mohamed Samir Abou El-Seoud Jihad M. Alja'am Moutaz Salah Department of Computer Science and Engineering College of Engineering Qatar university Qatar Department of Computer Science and Engineering College of Engineering Qatar University Qatar Faculty of Informatics and Computer Science The British University in Egypt (BUE) Egypt Department of Computer Science and Engineering College of Engineering Qatar University Qatar

ISBN: (纸本)9781450384315

Enriching the script of a story with visual aids is an effective approach for promoting language learning and literacy development for young children and learners. In this paper, we propose a new system, that can generate short Arabic stories with generated images that accurately represent the story, scene and context of the given input. We use a text generation technique with a text-to-image synthesis network and minimize the human intervention. We build a corpus of Arabic stories with vocabulary and visualizations. The obtained results with various generative models to create text-image contents show the effectiveness of the proposed approach. The system can be used in education and assist the instructors to build stories on different domains. It can be used in distance learning to deliver online tutorials during COVID-19.

关键词： GAN Story visualization Visual Language Learning Story Understanding CLIP

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Navigation Design to Improve Interaction Technique in Multi-Browser Virtual Environment

Navigation Design to Improve Interaction Technique in Multi-...

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International Conference on Cognitive Infocommunications (CogInfoCom)

作者： Mochammad Hannats Hanafi Ichsan Cecilia Sik-Lanyi Tibor Guzsvinecz Department of Electrical Engineering and Information Systems Faculty of Information Technology University of Pannonia Veszprem Hungary Department of Informatics Faculty of Computer Science Brawijaya University Malang Indonesia Hungarian Research Network Budapest Hungary Department of Information Technology and its Applications Faculty of Information Technology University of Pannonia Zalaegerszeg Hungary

ISBN: (数字)9798350378245

ISBN: (纸本)9798350378252

Efficient, precise, and intuitive navigation in a Virtual Environment (VE) or in desktop Virtual Reality (VR) is critical to improving user experience. This research introduces three navigation designs for physical embodiment inside VE using a computer mouse for multi-browser VE in desktop VR based on navigation possibilities. Navigation is intended for the First-Person Shooter (FPS) perspective: Intuitive Navigation (IntuNav), Edge Shift Navigation (EdgeNav), and Twist Shift Navigation (TwistNav). IntuNav uses mouse x and y coordinate movements to move and rotate the camera. EdgeNav relies on the cursor positioning at the edge of the screen for camera rotation and movement. TwistNav uses a middle click and right mouse click for camera movement and rotation. The current navigation design has been implemented in Unity with C#. This research proposed three model designs based on feasible navigation possibilities, which shows that each navigation model has unique advantages that can be adapted to user needs and preferences. Based on the test results using the System Usability Scale, IntuNav and EdgeNav obtained good results and can be used for further development.

关键词： Solid modeling Adaptation models Navigation Virtual environments Cameras User experience C# languages Usability

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CARA: A Hybrid Framework Integrating Swarm AI Agents and Knowledge Graphs for Advanced LLM Reasoning

CARA: A Hybrid Framework Integrating Swarm AI Agents and Kno...

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Advancements in Computing (ICAC), International Conference on

作者： Nirodya Pussadeniya Ruchira Wijesinghe Udaya Wijenayake Bhagya Silva Department of Computer Engineering Faculty of Engineering University of Sri Jayewardenepura Nugegoda Sri Lanka Department of Electrical and Electronic Engineering Faculty of Engineering Sri Lanka Institute of Information Technology Malabe Sri Lanka Center for Excellence in Informatics Electronics Transmission (CIET) Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Information Technology Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (数字)9798331517878

ISBN: (纸本)9798331517885

Language models excel in linguistic processing but often face challenges with complex reasoning tasks that require real-world interaction and multi-step logic. This paper presents the Cognitive Adaptive Reasoning Architecture (CARA), a framework that enhances reasoning by integrating a modular swarm architecture with knowledge graphs (KGs) and specialized agents. These agents, equipped with diverse tools, dynamically adapt to various tasks, actively engaging with real-world data. CARA's continuous memory update cycle ensures each reasoning step is based on up-to-date, contextual KG knowledge, enhancing decision-making. Incorporating human insights further aligns outcomes with nuanced cognition. Experimental results demonstrate CARA's superior performance over larger models, advancing language models' reasoning capabilities for more context-aware, informed decision-making in dynamic environments.

关键词： Adaptation models Adaptive systems Decision making Training data Knowledge graphs Linguistics Cognition Artificial intelligence Standards Context modeling

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An Exploratory Study of Diverse Models and Datasets for Transfer Learning based Image Classification on Sparse Data

An Exploratory Study of Diverse Models and Datasets for Tran...

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Moratuwa engineering Research Conference (MERCon)

作者： Jathurshan Pathmarasa Udaya Wijenayake Ruchire Eranga Wijesinghe Bhagya Nathali Silva Department of Computer Engineering Faculty of Engineering University of Sri Jayewardenepura Nugegoda Sri Lanka Department of Electrical and Electronic Engineering Faculty of Engineering Sri Lanka Institute of Information Technology Malabe Sri Lanka Center for Excellence in Informatics Electronics & Transmission (CIET) Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Information Technology Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (数字)9798331529048

ISBN: (纸本)9798331529055

Transfer learning is a powerful technique for image classification, especially when dealing with limited data. However, selection of the best transfer learning approach and model remains challenging, since the strategy is highly influenced by the scenario. This work conducted a thorough analysis of four transfer learning approaches for binary classification, and multiclass classification using four pretrained models i.e. MobileNetV2, MobileNetV3Large, EfficientNetB0, and EfficientNetB5. The test accuracy was measured with respect to the sample size considering the effects of data augmentation and fine tuning. The key finding of the study revealed that data augmentation has improved the test accuracy by up to $11.8 \%$. Moreover, the lightweight models marked a breakthrough by outperforming large scale models’ accuracy for sparse data settings when fine tuning (FT) and data augmentation (DA) are applied appropriately. Hence, this work provides a comprehensive overview on selecting different transfer learning approaches for sparse data classification by exploring diverse models and datasets, while discussing the consequences and challenges for future real-world applications.

关键词： Knowledge engineering Accuracy Transfer learning Optical wavelength conversion Data augmentation Feature extraction Size measurement Data models Tuning Image classification

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