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A sentiment analysis of the Ukraine-Russia War tweets using knowledge graph convolutional networks

International Journal of Information Technology (Singapore) 2025年 1-18页

作者： Menaouer, Brahami Fairouz, Safa Meriem, Mohammed Boulekbachi Mohammed, Sabri Nada, Matta LABAB Laboratory Computer Systems Engineering Department National Polytechnic School of Oran Oran Algeria Computer Systems Engineering Department National Polytechnic School of Oran Oran Algeria TechCICO Laboratory University of Technology of Troyes Troyes France

Nowadays, social networks play a critical role in online social discourse, particularly during major events such as elections, health crises, and wars. Furthermore, individuals have spent significant time on social networks that consume news and express their opinions and viewpoints on various topics, namely, the Russia-Ukraine War. The Ukraine-Russia War is one of the most complicated and unfortunate events of this decade, with many aspects to be considered to have an informed opinion. For this reason, sentiment analysis research can be useful in analyzing sentiments or opinions about the Ukraine-Russia war, such as Twitter (X) posts. In this study, we propose a new deep learning-based sentiment classification model called "Knowledge Graph Convolutional Networks" that predicts and analyzes sentiments concerning the Russia-Ukraine war. There were 500,000 tweets collected in total, however only 410,428 were left for sentiment analysis after cleaning, lemmatization stemming, and deleting duplicate tweets. Results show that "war", "people", "world", "putin", "energy", "gas", "weapon", and "peace" were some of the most frequently occurring words in the tweets. The main aim of this work is to develop a robust system that provides an understanding of public sentiment towards the Russia-Ukraine war on the X platform. Experimental results demonstrate that it is possible to obtain more accurate sentiment classification results by the proposed method. They also have managerial, economic, and research implications. © Bharati Vidyapeeth's Institute of computer Applications and Management 2024.

关键词： Classification Decision support systems Graph Convolutional Networks (GCN) Knowledge graph Knowledge management Opinion mining Twitter sentiment analysis Ukraine-Russia War

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Current and Voltage Scaling for Maximum Transferable Active Power Improvement of Weak-Grid-Tied Grid-Following Inverters 10

Current and Voltage Scaling for Maximum Transferable Active ...

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10th IEEE International Power Electronics and Motion Control Conference, IPEMC 2024 ECCE Asia

作者： Zhou, Weihua Bahrani, Behrooz Monash University Department of Electrical and Computer Systems Engineering Melbourne Australia

ISBN: (纸本)9798350351330

The grid-following inverter's dq admittance model manifests a negative resistance in the low-frequency range due to the phase-locked loop, potentially leading to low-frequency instabilities and limiting the maximum transferable active power (MTAP), especially in weak grid scenarios. This paper introduces a simple and efficient current and voltage scaling scheme to counteract the phase-locked loop's adverse effects, enabling the grid-following inverter to inject per-unit active power even under extremely weak grid conditions. Complemented by a detailed design procedure, this proposed method stands out for its simplicity and effectiveness. Time-domain simulations validate the proposed scheme's efficacy in MTAP enhancement. © 2024 IEEE.

关键词： Voltage scaling

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TRANSIENT STABILITY ENHANCEMENT OF GRID-FORMING TYPE-3 WIND TURBINE GENERATORS 23

TRANSIENT STABILITY ENHANCEMENT OF GRID-FORMING TYPE-3 WIND ...

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23rd Wind and Solar Integration Workshop, WIW 2024

作者： Hajtaleb, Salah Bahrani, Behrooz Electrical and Computer Systems Engineering Department Monash University Melbourne Australia

ISBN: (纸本)9781837242689

Grid-forming control is considered to be essential in the transition to renewables-dominated power systems. However, grid-forming Type-3 wind turbine generators present unique challenges due to their electromechanical coupling with the grid and the limited kinetic energy in their drive-trains. This prevents active power control methods that emulate synchronous-machine behaviour from delivering robust and stable performance in Type-3 turbines. These limitations become more evident during recovery from severe grid disturbances. To overcome these limitations, this paper proposes a lead-compensator (LC)-based approach for synchronisation and active-power control as an alternative to virtual-synchronous-generators (VSG). The proposed approach is intended to demonstrate that the system damping and the overall transient stability can be improved solely by altering the control structure. Therefore, several time-domain studies have been conducted under different grid-strength levels and current-limitation mechanisms, and the comparison of post-fault recovery performance of the two controllers are presented. The results show that excessive active power oscillations and rotor speed deviations observed with VSG control are substantially mitigated using the proposed LC approach. More importantly, this is achieved without compromising inertia and droop settings, or utilising frequency measurements. Reduced turbine mechanical stress and enhanced robustness are among the benefits of this approach. © Energynautics GmbH.

关键词： Kinetic energy

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Python-Based Cross-Platform Impedance Benchmarking Tool (CroZBenMa) for IBR's EMT Models in Matlab/Simulink and PSCAD/EMTDC 10

Python-Based Cross-Platform Impedance Benchmarking Tool (Cro...

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10th IEEE International Power Electronics and Motion Control Conference, IPEMC 2024 ECCE Asia

作者： Zhou, Weihua Mohammed, Nabil Bahrani, Behrooz Monash University Department of Electrical and Computer Systems Engineering Melbourne Australia

ISBN: (纸本)9798350351330

This paper presents a Python-driven graphical user interface (GUI) explicitly crafted for benchmarking the electromagnetic transient (EMT) models of inverter-based resources (IBRs) across Matlab/Simulink and PSCAD/EMTDC platforms through impedance measurement techniques. The GUI ensures a user-friendly experience, enabling seamless interactions between these platforms while offering advanced visualization of impedance measurement results and associated benchmarking errors. This paper delves into the Python-based implementation that powers these features. Through a series of case studies, the tool's efficacy in benchmarking IBR's EMT models is validated. The benchmarking methodology and corresponding GUI design are extensible to other leading EMT platforms such as DIgSILENT/PowerFactory, PSSE, EMTP-RV, EMTP-ATP, and DSAToolsTM/SSAT, fostering expansive and holistic research in the stability analysis of the IBR-based modern power systems. © 2024 IEEE.

关键词： Benchmarking

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WIP: Teaching Basic Concepts of Quantum Computing Using Scratch 54

WIP: Teaching Basic Concepts of Quantum Computing Using Scra...

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54th IEEE Frontiers in Education Conference, FIE 2024

作者： Rosa-Remedios, Carlos Caballero-Gil, Pino Escanez-Exposito, Daniel University of La Laguna Department of Computer Engineering and Systems Tenerife Spain

ISBN: (纸本)9798350351507

This work-in-progress research paper presents an innovative learning methodology based on gamification and the concept of 'building your own knowledge' to motivate and spark students' interest in quantum computing. Using the Scratch platform with younger high school students, basic quantum computing principles are taught through interactive mini-games, focusing on concepts like superposition and entanglement. For older students, a more formal methodology is proposed that uses the Bloch Sphere representation via the CreatiCode platform. This paper discusses an implementation of the proposal with high school groups, including statistical analysis and feedback collection to assess concept acquisition, strengths, weaknesses and student satisfaction. Data is gathered through questionnaires and interviews, enabling comparison with external test groups for comprehensive evaluation. This approach integrates computational thinking, gamification and visual knowledge construction, aligning with STEM education principles and fostering knowledge retention. © 2024 IEEE.

关键词： Gamification

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WIP: Using GeoGebra to Learn the Basics of Post-Quantum Cryptography 54

WIP: Using GeoGebra to Learn the Basics of Post-Quantum Cryp...

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54th IEEE Frontiers in Education Conference, FIE 2024

作者： Perez-Ramos, Edgar Caballero-Gil, Pino Reboso-Morales, Héctor University of La Laguna Department of Computer Engineering and Systems Tenerife Spain

ISBN: (纸本)9798350351507

This work in progress paper describes a proposal to use the GeoGebra environment as a useful didactic and conceptual tool to introduce the basic concepts of the increasingly relevant area of Post-Quantum Cryptography (PQC). The advancement and threat posed by quantum computing present significant challenges to information security. This situation has generated an urgent need to develop cryptographic systems capable of resisting quantum attacks. In this context, PQC has emerged as a crucial research field. However, one of the main challenges facing this field is the scarcity of available educational resources. This paper addresses this issue by creating educational resources focused on lattices using GeoGebra. An activity has been designed to introduce and relate lattices to various mathematical concepts taught in the classroom. The developed activity is completely innovative and aims to make the understanding of PQC more accessible by providing visual and manipulable tools that help students internalize the mathematical and computational principles involved in information security in the post-quantum era. © 2024 IEEE.

关键词： Quantum computers

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Enhancement of UAV Data Security and Privacy via Ethereum Blockchain Technology

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computers, Materials & Continua 2023年第8期76卷 1797-1815页

作者： Sur Singh Rawat Youseef Alotaibi Nitima Malsa Vimal Gupta Department of Computer Science and Engineering JSS Academy of Technical EducationNoida201301India Department of Computer Science College of Computer and Information SystemsUmm Al-Qura UniversityMakkah21955Saudi Arabia

Unmanned aerial vehicles(UAVs),or drones,have revolutionized a wide range of industries,including monitoring,agriculture,surveillance,and supply ***,their widespread use also poses significant challenges,such as public safety,privacy,and ***,targetingUAVs have become more frequent,which highlights the need for robust security *** technology,the foundation of cryptocurrencies has the potential to address these *** study suggests a platform that utilizes blockchain technology tomanage drone operations securely and *** incorporating blockchain technology,the proposed method aims to increase the security and privacy of drone *** suggested platform stores information on a public blockchain located on Ethereum and leverages the Ganache platform to ensure secure and private blockchain *** wallet for Ethbalance is necessary for BCT *** present research finding shows that the proposed approach’s efficiency and security features are superior to existing *** study contributes to the development of a secure and efficient system for managing drone operations that could have significant applications in various *** proposed platform’s security measures could mitigate privacy concerns,minimize cyber security risk,and enhance public safety,ultimately promoting the widespread adoption of *** results of the study demonstrate that the blockchain can ensure the fulfillment of core security needs such as authentication,privacy preservation,confidentiality,integrity,and access control.

关键词： Unmanned aerial vehicles(UAVs) blockchain data privacy network security smart contract Ethereum

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Congruent Feature Selection Method to Improve the Efficacy of Machine Learning-Based Classification in Medical Image Processing

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computer Modeling in engineering & Sciences 2025年第1期142卷 357-384页

作者： Mohd Anjum Naoufel Kraiem Hong Min Ashit Kumar Dutta Yousef Ibrahim Daradkeh Department of Computer Engineering Aligarh Muslim UniversityAligarh202002India College of Computer Science King Khalid UniversityAbha61413Saudi Arabia School of Computing Gachon UniversitySeongnam13120Republic of Korea Department of Computer Science and Information Systems College of Applied SciencesAlMaarefa UniversityRiyadh13713Saudi Arabia Department of Computer Engineering and Information College of Engineering in Wadi AlddawasirPrince Sattam bin Abdulaziz UniversityAl-Kharj16273Saudi Arabia

Machine learning(ML)is increasingly applied for medical image processing with appropriate learning *** applications include analyzing images of various organs,such as the brain,lung,eye,etc.,to identify specific flaws/diseases for *** primary concern of ML applications is the precise selection of flexible image features for pattern detection and region *** of the extracted image features are irrelevant and lead to an increase in computation ***,this article uses an analytical learning paradigm to design a Congruent Feature Selection Method to select the most relevant image *** process trains the learning paradigm using similarity and correlation-based features over different textural intensities and pixel *** similarity between the pixels over the various distribution patterns with high indexes is recommended for disease ***,the correlation based on intensity and distribution is analyzed to improve the feature selection ***,the more congruent pixels are sorted in the descending order of the selection,which identifies better regions than the ***,the learning paradigm is trained using intensity and region-based similarity to maximize the chances of ***,the probability of feature selection,regardless of the textures and medical image patterns,is *** process enhances the performance of ML applications for different medical image *** proposed method improves the accuracy,precision,and training rate by 13.19%,10.69%,and 11.06%,respectively,compared to other models for the selected *** mean error and selection time is also reduced by 12.56%and 13.56%,respectively,compared to the same models and dataset.

关键词： computer vision feature selection machine learning region detection texture analysis image classification medical images

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A Probabilistic Trust Model and Control Algorithm to Protect 6G Networks against Malicious Data Injection Attacks in Edge Computing Environments

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computer Modeling in engineering & Sciences 2024年第10期141卷 631-654页

作者： Borja Bordel Sánchez Ramón Alcarria Tomás Robles Department of Computer Systems Universidad Politécnica de MadridMadrid28031Spain Department of Geospatial Engineering Universidad Politécnica de MadridMadrid28031Spain

Future 6G communications are envisioned to enable a large catalogue of pioneering *** will range from networked Cyber-Physical systems to edge computing devices,establishing real-time feedback control loops critical for managing Industry 5.0 deployments,digital agriculture systems,and essential *** provision of extensive machine-type communications through 6G will render many of these innovative systems autonomous and *** full automation will enhance industrial efficiency significantly,it concurrently introduces new cyber risks and *** particular,unattended systems are highly susceptible to trust issues:malicious nodes and false information can be easily introduced into control ***,Denialof-Service attacks can be executed by inundating the network with valueless *** anomaly detection schemes require the entire transformation of the control software to integrate new steps and can only mitigate anomalies that conform to predefined mathematical *** based on an exhaustive data collection to detect anomalies are precise but extremely *** models,with their limited understanding of mobile networks,can achieve precision rates no higher than 75%.Therefore,more general and transversal protection mechanisms are needed to detect malicious behaviors *** paper introduces a probabilistic trust model and control algorithm designed to address this *** model determines the probability of any node to be *** channels are pruned for those nodes whose probability is below a given *** trust control algorithmcomprises three primary phases,which feed themodel with three different probabilities,which are weighted and ***,anomalous nodes are identified using Gaussian mixture models and clustering ***,traffic patterns are studied using digital Bessel functions and the functional scalar ***,the in

关键词： 6G networks noise injection attacks Gaussian mixture model Bessel function traffic filter Volterra filter

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Fuzzy clustering for electric field characterization and its application to thunderstorm interpretability

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Digital Communications and Networks 2025年第2期11卷 299-307页

作者： Xu Yang Hongyan Xing Xinyuan Ji Wei Xu Witold Pedrycz School of Electronics and Information Engineering Nanjing University of Information Science and TechnologyNanjing 210044China Department of Electrical and Computer Engineering University of AlbertaEdmonton AB T6G 2R3Canada Systems Research Institute Polish Academy of Sciences00-901 WarsawPoland Department of Computer Engineering Faculty of Engineering and Natural SciencesIstinye University34010 IstanbulTurkey

Changes in the Atmospheric Electric Field Signal(AEFS)are highly correlated with weather changes,especially with thunderstorm ***,little attention has been paid to the ambiguous weather information implicit in AEFS *** this paper,a Fuzzy C-Means(FCM)clustering method is used for the first time to develop an innovative approach to characterize the weather attributes carried by ***,a time series dataset is created in the time domain using AEFS *** AEFS-based weather is evaluated according to the time-series Membership Degree(MD)changes obtained by inputting this dataset into the ***,thunderstorm intensities are reflected by the change in distance from a thunderstorm cloud point charge to an AEF ***,a matching relationship is established between the normalized distance and the thunderstorm dominant MD in the space ***,the rationality and reliability of the proposed method are verified by combining radar charts and expert *** results confirm that this method accurately characterizes the weather attributes and changes in the AEFS,and a negative distance-MD correlation is obtained for the first *** detection of thunderstorm activity by AEF from the perspective of fuzzy set technology provides a meaningful guidance for interpretable thunderstorms.

关键词： Atmospheric electric field(AEF) Thunderstorm Fuzzy C-means(FCM) Attribute

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