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Enhancing Arabic Cyberbullying Detection with End-to-End Transformer Model

computer Modeling in engineering & Sciences 2024年第11期141卷 1651-1671页

作者： Mohamed A.Mahdi Suliman Mohamed Fati Mohamed A.G.Hazber Shahanawaj Ahamad Sawsan A.Saad Information and Computer Science Department College of Computer Science and EngineeringUniversity of Ha’ilHa’il55476Saudi Arabia Information Systems Department College of Computer and Information SciencesPrince Sultan UniversityRiyadh11586Saudi Arabia Software Engineering Department College of Computer Science and EngineeringUniversity of Ha’ilHa’il55476Saudi Arabia Computer Engineering Department College of Computer Science and EngineeringUniversity of Ha’ilHa’il55476Saudi Arabia

Cyberbullying,a critical concern for digital safety,necessitates effective linguistic analysis tools that can navigate the complexities of language use in online *** tackle this challenge,our study introduces a new approach employing Bidirectional Encoder Representations from the Transformers(BERT)base model(cased),originally pretrained in *** model is uniquely adapted to recognize the intricate nuances of Arabic online communication,a key aspect often overlooked in conventional cyberbullying detection *** model is an end-to-end solution that has been fine-tuned on a diverse dataset of Arabic social media(SM)tweets showing a notable increase in detection accuracy and sensitivity compared to existing *** results on a diverse Arabic dataset collected from the‘X platform’demonstrate a notable increase in detection accuracy and sensitivity compared to existing methods.E-BERT shows a substantial improvement in performance,evidenced by an accuracy of 98.45%,precision of 99.17%,recall of 99.10%,and an F1 score of 99.14%.The proposed E-BERT not only addresses a critical gap in cyberbullying detection in Arabic online forums but also sets a precedent for applying cross-lingual pretrained models in regional language applications,offering a scalable and effective framework for enhancing online safety across Arabic-speaking communities.

关键词： Cyberbullying offensive detection Bidirectional Encoder Representations from the Transformers(BERT) continuous bag of words Social Media natural language processing

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Improved Twin Support Vector Machine Algorithm and Applications in Classification Problems

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China Communications 2024年第5期21卷 261-279页

作者： Sun Yi Wang Zhouyang Beijing University of Posts and Telecommunications School of Computer Science(National Pilot Software Engineering School) Beijing University of Posts and Telecommunications International School

The distribution of data has a significant impact on the results of *** the distribution of one class is insignificant compared to the distribution of another class,data imbalance *** will result in rising outlier values and ***,the speed and performance of classification could be greatly *** the above problems,this paper starts with the motivation and mathematical representing of classification,puts forward a new classification method based on the relationship between different classification *** with the vector characteristics of the actual problem and the choice of matrix characteristics,we firstly analyze the orderly regression to introduce slack variables to solve the constraint problem of the lone *** we introduce the fuzzy factors to solve the problem of the gap between the isolated points on the basis of the support vector *** introduce the cost control to solve the problem of sample ***,based on the bi-boundary support vector machine,a twostep weight setting twin classifier is *** can help to identify multitasks with feature-selected patterns without the need for additional optimizers,which solves the problem of large-scale classification that can’t deal effectively with the very low category distribution gap.

关键词： fuzzy ordered regression(OR) relaxing variables twin support vector machine

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EEG-Based Emotion Recognition during Mobile Gameplay

EEG-Based Emotion Recognition during Mobile Gameplay

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2024 International Conference on engineering and Computing, ICECT 2024

作者： Khan, Shaheryar Hassan Raheel, Aasim Majid, Muhammad Anwar, Syed Muhammad Arsalan, Aamir UET Department of Computer Engineering Taxila Pakistan UET Department of Software Engineering Taxila Pakistan FJWU Department of Software Engineering Rawalpindi Pakistan

ISBN: (纸本)9798350349719

The gaming industry, encompassing both console and mobile platforms, has experienced remarkable growth in recent years. Assessing emotional responses during gameplay presents a significant challenge. This study employs electroen-cephalography (EEG) signals to discern players' emotions while engaged in mobile gaming. Specifically, two popular mobile games, Temple Run and Subway Surfers, were chosen to represent diverse gaming environments. Each game underwent three separate trials, during which EEG data was collected using a commercially available 4-channel MUSE headband. Following each trial, players indicated their emotional state on a 9-point valence and arousal scale. Statistical analysis, including a t-Test, was conducted on the valence and arousal scores for both games, revealing a significant difference in emotional responses (p 0.05). Player data was labeled using the majority voting technique based on the three trials. Features were extracted from both the frequency domain and time domain which were used to classify valence and arousal into two classes using support vector machine (SVM) and k-nearest neighbor (KNN) classifiers. The KNN classifier achieved the highest accuracy rates, with 80.55. © 2024 IEEE.

关键词： Emotion Recognition

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Eleven-point discrete perturbation-handling ZNN algorithm applied to tracking control of MIMO nonlinear system under various disturbances

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Neural Computing and Applications 2025年第5期37卷 3455-3472页

作者： Huang, Meichun Mao, Mingzhi Zhang, Yunong School of Computer Science and Engineering Sun Yat-sen University Guangzhou510006 China School of Software Engineering Sun Yat-sen University Zhuhai519082 China

The multiple-input–multiple-output nonlinear system (MIMO-NS) is a hot research topic in various science and application fields. To solve the tracking control (TC) problem of MIMO-NS effectively, a zeroing neuro-PID controller and a continuous perturbation-handling ZNN (CPHZNN) model are proposed. The proposed model robustly handles various internal perturbations generated by external disturbances. To achieve high-precision computation, a novel 11-point Zhang time discretization (ZTD) formula with order-5 precision is designed. By employing this formula, an 11-point discrete perturbation-handling ZNN (11P-DPHZNN) algorithm with order-6 precision is proposed, aiming at providing real-time solution to the TC problem. Theoretical analyses verify the convergence performance of the proposed 11P-DPHZNN algorithm under four types of perturbations. Moreover, numerical and comparative experiments substantiate the effectiveness, superiority, and perturbation resistance of the proposed 11P-DPHZNN algorithm under various perturbations. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Three term control systems

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Intelligent obstacle avoidance algorithm for safe urban monitoring with autonomous mobile drones

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Journal of Electronic Science and Technology 2024年第4期22卷 19-36页

作者： Didar Yedilkhan Abzal E.Kyzyrkanov Zarina A.Kutpanova Shadi Aljawarneh Sabyrzhan K.Atanov Department of Computer Engineering Astana IT UniversityAstana010000Kazakhstan Department of Computer and Software Engineering L.N.Gumilyov Eurasian National UniversityAstana010000Kazakhstan Department of Automation and Control Systems L.N.Gumilyov Eurasian National UniversityAstana010000Kazakhstan Department of Software Engineering Jordan University of Science and TechnologyIrbid22110Jordan

The growing field of urban monitoring has increasingly recognized the potential of utilizing autonomous technologies,particularly in drone *** deployment of intelligent drone swarms offers promising solutions for enhancing the efficiency and scope of urban condition *** this context,this paper introduces an innovative algorithm designed to navigate a swarm of drones through urban landscapes for monitoring *** primary challenge addressed by the algorithm is coordinating drone movements from one location to another while circumventing obstacles,such as *** algorithm incorporates three key components to optimize the obstacle detection,navigation,and energy efficiency within a drone ***,the algorithm utilizes a method to calculate the position of a virtual leader,acting as a navigational beacon to influence the overall direction of the ***,the algorithm identifies observers within the swarm based on the current *** further refine obstacle avoidance,the third component involves the calculation of angular velocity using fuzzy *** approach considers the proximity of detected obstacles through operational rangefinders and the target’s location,allowing for a nuanced and adaptable computation of angular *** integration of fuzzy logic enables the drone swarm to adapt to diverse urban conditions dynamically,ensuring practical obstacle *** proposed algorithm demonstrates enhanced performance in the obstacle detection and navigation accuracy through comprehensive *** results suggest that the intelligent obstacle avoidance algorithm holds promise for the safe and efficient deployment of autonomous mobile drones in urban monitoring applications.

关键词： Drone swarms Fuzzy logic Intelligent solution Smart city Urban monitoring

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AGCLNDA: Enhancing the Prediction of ncRNA-Drug Resistance Association Using Adaptive Graph Contrastive Learning

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IEEE Journal of Biomedical and Health Informatics 2025年第6期29卷 4524-4533页

作者： Fan, Yanhao Zhang, Che Hu, Xiaowen Huang, Zhijian Deng, Lei School of Computer Science and Engineering Central South University Changsha410083 China School of software Xinjiang University Urumqi830046 China

Non-coding RNAs (ncRNAs), which do not encode proteins, have been implicated in chemotherapy resistance in cancer treatment. Given the high costs and time requirements of traditional biological experiments, there is an increasing need for computational models to predict ncRNA-drug resistance associations. In this study, we introduce AGCLNDA, an adaptive contrastive learning method designed to uncover these associations. AGCLNDA begins by constructing a bipartite graph from existing ncRNA-drug resistance data. It then utilizes a light graph convolutional network (LightGCN) to learn vector representations for both ncRNAs and drugs. The method assesses resistance association scores through the inner product of these vectors. To tackle data sparsity and noise, AGCLNDA incorporates learnable augmented view generators and denoised view generators, which provide contrastive views for enhanced data augmentation. Comparative experiments demonstrate that AGCLNDA outperforms five other advanced methods. Case studies further validate AGCLNDA as an effective tool for predicting ncRNA-drug resistance associations. The code and dataset for AGCLNDA are available at https://***/one-melon/AGCLNDA. © 2013 IEEE.

关键词： Graph neural networks

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Topological Evaluation of Certain computer Networks by Contraharmonic-Quadratic Indices

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computers, Materials & Continua 2023年第2期74卷 3795-3810页

作者： Ahmed M.Alghamdi Khalid Hamid Muhammad Waseem Iqbal M.Usman Ashraf Abdullah Alshahrani Adel Alshamrani Department of Software Engineering College of Computer Science and EngineeringUniversity of JeddahJeddah21493Saudi Arabia Department of Computer Science Superior UniversityLahore54000Pakistan Department of Software Engineering Superior UniversityLahore54000Pakistan Department of Computer Science GC Women UniversitySialkot53310Pakistan Department of Computer Science and Artificial Intelligence College of Computer Science and EngineeringUniversity of JeddahJeddah21493Saudi Arabia Department of Cybersecurity College of Computer Science and Engineering at University of JeddahJeddah21493Saudi Arabia

In various fields,different networks are used,most of the time not of a single kind;but rather a mix of at least two *** kinds of networks are called bridge networks which are utilized in interconnection networks of PC,portable networks,spine of internet,networks engaged with advanced mechanics,power generation interconnection,bio-informatics and substance intensify *** number that can be entirely calculated by a graph is called graph *** mathematical graph invariants have been portrayed and utilized for connection investigation during the latest twenty ***,no trustworthy evaluation has been embraced to pick,how much these invariants are associated with a network graph or subatomic *** this paper,it will discuss three unmistakable varieties of bridge networks with an incredible capacity of assumption in the field of computer science,chemistry,physics,drug industry,informatics and arithmetic in setting with physical and manufactured developments and networks,since Contraharmonic-quadratic invariants(CQIs)are recently presented and have different figure qualities for different varieties of bridge graphs or *** study settled the geography of bridge graphs/networks of three novel sorts with two kinds of CQI and Quadratic-Contraharmonic Indices(QCIs).The deduced results can be used for the modeling of the above-mentioned networks.

关键词： Bridge networks invariants Quadratic-Contraharmonic Indices maple network graph molecular graph

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Abstract Interpretation for PLONKish Circuits 34

Abstract Interpretation for PLONKish Circuits

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34th Annual International Conference on Collaborative Advances in software and Computing, CASCON 2024

作者： Soureshjani, Fatemeh Heidari Gorzny, Jan Polytechnique Montréal Computer Engineering and Software Engineering Department Canada Zircuit Canada

ISBN: (纸本)9798331504830

Zero-knowledge proof systems are becoming powerful tools in domains like blockchain networks. In this work, we improve abstract interpretation methods to sanity check PLONKish arithmetizations of computation, such as those used in the Halo2 zero-knowledge proof system. Our work aims to improve the accuracy of checks for unused gates, assigned but unconstrained values, and possibly under-constrained circuits, all of which may indicate a bug in the circuits. We show how copy constraints and arbitrary lookup functions can be used in abstract interpretation based analysis of these circuits. We are motivated to revisit this topic as these circuits, through their use in general purpose blockchain networks, may be responsible for the security of millions of dollars in cryptocurrency. © 2024 IEEE.

关键词： Blockchain

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GazeREC-Net: Advancing Gaze Restoration in Low-Light Conditions

IAENG International Journal of Computer Science

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IAENG International Journal of computer Science 2024年第12期51卷 2034-2042页

作者： Ku, Jiayin Wang, Li School of Computer Science and software Engineering University of Science and Technology Liaoning Anshan114051 China College of Computer Science and Tech nology Liaoning Anshan114051 China

Gaze estimation technology is essential for applications such as human-computer interaction, augmented reality, and virtual reality. However, its accuracy is significantly compromised in low-light conditions due to degraded image quality. To address this, we developed GazeREC-Net, an innovative gaze restoration method. We simulated low-light conditions on the MPIIFaceGaze and ColumbiaGaze datasets, creating a specialized degraded dataset for training and testing our model. GazeREC-Net combines Fourier transform techniques with advanced image restoration algorithms, significantly enhancing image quality and optimizing gaze information recovery and extraction in low-light environments. Our evaluations using Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM) metrics demonstrated a PSNR improvement of 7.64% and an SSIM improvement of 5.75% compared to HINet. Additionally, GazeREC-Net outperformed CFTNet and other existing gaze estimation models, including Gaze-TR, Dilated-Net, CA-Net, L2CS-Net, and MTGLS, in reducing gaze estimation error. These findings validate the effectiveness of GazeREC-Net in low-light conditions and offer new research directions for applying gaze estimation technologies in complex lighting environments. © (2024), (International Association of Engineers). All rights reserved.

关键词： Augmented reality

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Is GPT-4 Conscious?

Journal of Artificial Intelligence and Consciousness

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Journal of Artificial Intelligence and Consciousness 2024年第1期11卷 1-16页

作者： Tait, Izak Bensemann, Joshua Wang, Ziqi Computer Science and Software Engineering Department Auckland University of Technology NAOInstitute The University of Auckland

GPT-4 (Generative Pre-Trained Transformer 4) is often heralded as a leading commercial AI offering, sparking debates over its potential as a steppingstone toward Artificial General Intelligence. But does it possess consciousness? This paper investigates this key question using the nine qualitative measurements of the Building Blocks theory. GPT-4's design, architecture, and implementation are compared to each of the building blocks of consciousness to determine whether it has achieved the requisite milestones to be classified as conscious or, if not, how close to consciousness GPT-4 is. Our assessment is that, while GPT-4 in its native configuration is not currently conscious, current technological research and development is sufficient to modify GPT-4 to have all the building blocks of consciousness. Consequently, we argue that the emergence of a conscious AI model is plausible in the near term. The paper concludes with a comprehensive discussion of the ethical implications and societal ramifications of engineering conscious AI entities. © 2024 World Scientific Publishing Company.

关键词： Artificial Intelligence Consciousness Ethics GPT-4 Philosophy of Mind Sentience

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