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On The Symbolic 2-plithogenic Fermat's Non-Linear Diophantine Equation

Neutrosophic Sets and Systems 2023年 59卷 13-21页

作者： Alrawashdeh, Heba Al-Basheer, Othman Hajjari, Arwa Faculty of Computer Information Systems The University of Jordan Aqaba Jordan Sudan University of Science and Technology Faculty of Science Khartoum Sudan Cairo University Department of Mathematics Cairo Egypt

This paper is dedicated to find all symbolic 2-plithogenic integer solutions for the symbolic 2-plithogenic Fermat's Diophantine equation Xn + Yn = Zn for n ≥ 3. We prove that it has exactly 27 solutions, and we ... 详细信息

关键词： Fermat's Diophantine equation symbolic 2-plithogenic integer symbolic 2-plithogenic ring

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Semi-analytic solution of the nonlinear Sharma-Tasso-Olver equation via ramadan group integral transform and accelerated adomian decomposition

Journal of Umm Al-Qura University for Applied Sciences

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Journal of Umm Al-Qura University for Applied sciences 2025年 1-14页

作者： Ramadan, Mohamed A. Mansour, Mariam M. A. El-Shazly, Naglaa M. Mathematics and Computer Science Department Faculty of Science Menoufia University Menoufia Shibin El-Koom Egypt Department of Basic Science Modern Academy of Computer Science and Management Technology Cairo Maadi Egypt

This work focuses on finding an approximate solution to the Sharma-Tasso-Olive (STO) equation. The approach combines accelerated Adomian decomposition (ADM) with the Ramadan group integral transform (RGT) to tackle these nonlinear partial differential equations. Two analytical solution forms are analyzed to evaluate the accuracy and effectiveness of the proposed method. The results demonstrate that the suggested technique yields a rapidly convergent series solution for the STO equation. The paper emphasizes that these semi-analytic methods are powerful tools applicable in engineering and physics for approximating solutions to such nonlinear equations. The resulting series can offer a closed-form solution. Ultimately, the accelerated RGT-ADM variant outperforms the traditional RGT combined with standard Adomian decomposition due to its faster convergence and the elimination of the need for complex Adomian polynomials. © The Author(s) 2025.

关键词： Accelerated variant of Adomain Accuracy Approximate solutions Computational efficiency Convergence rate Nonlinear partial differential equations Numerical methods Polynomial calculations Ramdan group transform Semi-analytic methods Series solutions Sharma-Tasso-Olive equation

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An Integrated Theoretical Model for Cloud Computing Adoption in Universities of Yemen 1

An Integrated Theoretical Model for Cloud Computing Adoption...

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1st International Conference on Emerging Technologies for Dependable Internet of Things, ICETI 2024

作者： Al-Hashedi, Abdullah Almekhlafi, Nabil Othman, Mohamed Tahar Ben Ghallab, Abdullatif Department of Information Technology University of Science and Technology Sana’a Yemen Department of Computer Science Qassim University Buraydah Saudi Arabia Department of Computer Science University of Science and Technology Sana’a Yemen

ISBN: (纸本)9798331533557

Several studies have been conducted in several sectors to determine the factors influencing the adoption of cloud computing (CC) technology at the individual or organizational level. These studies demonstrated the ability of CC to reduce expenses and provide high flexibility in resource management. However, studies in Yemen and Yemeni higher education institutions (HEIs) are still scarce, and no institution has adopted CC due to security and privacy concerns. This research developed an integrated theoretical model to investigate the factors affecting the adoption of CC in Yemeni HEIs. The developed theoretical model is based on the models of the technology and organization environment (TOE) framework and the diffusion of innovations model. A quantitative approach was used, and partial least squares structural equation modeling (PLS-SEM) was used to analyze and validate the proposed model on the basis of data from 170 participants from academics and IT employees at Yemen universities. The findings revealed that relative advantage, compatibility, security concerns, technological readiness, and senior management support had a significant effect on the adoption of CC in Yemeni HEIs. This study contributes to identifying the most important factors influencing the adoption of CC in HEIs. In addition, I presented a conceptual framework that combines the two theories of DOI-TOE. The results of this research may help HEIs develop a strategy for the adoption of CC by recognizing the key factors in their institutions. © 2024 IEEE.

关键词： Cloud platforms

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Multi-layered access control based auto tuning relational key implications in enterprise-level multi-tenancy

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Multimedia Tools and Applications 2025年第17期84卷 17805-17836页

作者： Henge, Santosh Kumar Rajakumar, R. Prasanna, P. Parivazhagan, A. Hu, Yu-Chen Chen, Wu-Lin Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation KL University AP Vaddeswaram India Centre for Automation School of Computer Science and Engineering Vellore Institute of Technology Chennai India Department of Computer Science and Engineering Veltech Rangarajan Dr Sagunthala R &D Institute of Science and Technology Chennai India Department of CSE Kalasalingam Academy of Research and Education Tamilnadu Krishnankoil India Department of Computer Science Xitun District Tunghai University No. 1727 Sec. 4 Boulevard Taichung City407224 Taiwan Department of Computer Science and Information Management Providence University Taichung City Taiwan

This article discusses the importance of cloud-based multi-tenancy in private–public-private secure cloud environments, which is achieved through the isolation of end-user data and resources into tenants to ensure data confidentiality and integrity. Maintaining secure access control is a complex and critical task in multi-tenant cloud environments, and researchers have proposed innovative methods for implementing security, privacy, and authenticity. However, several challenges remain. The proposed research addresses these challenges by presenting a layered approach to multi-tenancy in an enterprise-level cloud environment. The study has three main objectives: (1) to describe and analyze the complexities of enterprise-based multi-tenancy and proposed technical solutions in a tabular format;(2) to propose multi-tenant test cases across application, software, infrastructure, and network as a service environment;and (3) to present a collaborative, relational optimal key-based multi-tenancy access control model. The proposed access control model involves integrating various secure layers, such as intranet, extranet, intra-extranet, and using feasible relational optimal keys to provide secure multi-tenant access control among various tenants of single and multiple enterprises. This model provides secure data transmission by integrating various multi-layer data filters and secure blades. The layered multi-tenancy approach offers many benefits and technical feasibilities to avoid security and privacy issues in enterprise-based multi-tenant environments. The process achieved a 93% secure mapping rate to authenticate all IN and OUT data access transactions among the various multi-tenancy of similar and distinct enterprises. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Virtualization

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3D Object Detection for Autonomous Driving: A Comprehensive Review 6

3D Object Detection for Autonomous Driving: A Comprehensive ...

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6th International Conference on Computing and Informatics, ICCI 2024

作者： Nagiub, Ahmed Soliman Ghoniemy, Said Fayez, Mahmoud Khaled, Heba Computer System Department Faculty of Computer and information Science Ain Shams University Cairo Egypt

ISBN: (纸本)9798350373875

accurate perception is a critical component in enabling autonomous vehicles to understand their driving environment. The acquisition of 3D information about objects, including their location and pose, is essential for achieving this understanding. This survey paper presents a comprehensive review of 3D object detection techniques specifically tailored for autonomous vehicles. The survey begins with an introduction to 3D object detection, elucidating the significance of the third dimension in perceiving the driving environment. It explores the types of sensors utilized in this context and the corresponding data extracted from these sensors. Additionally, the survey investigates the different types of datasets employed, including their formats, sizes, and provides a comparative analysis. Furthermore, the paper categorizes and thoroughly examines the perception methods employed for 3D object detection, based on the diverse range of sensors utilized. Each method is evaluated based on its effectiveness in accurately detecting objects in a three-dimensional space. Additionally, the evaluation metrics used to assess the performance of these methods are discussed. By offering a comprehensive overview of 3D object detection techniques for autonomous vehicles, this survey aims to advance the field of perception systems. It serves as a valuable resource for researchers and practitioners, providing insights into the techniques, sensors, and evaluation metrics employed in 3D object detection for autonomous vehicles. © 2024 IEEE.

关键词： Object detection

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An Optimal Distribution of RSU for Improving Self-Driving Vehicle Connectivity

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computers, Materials & Continua 2022年第2期70卷 3311-3319页

作者： Khattab Alheeti Abdulkareem Alaloosy Haitham Khalaf Abdulkareem Alzahrani Duaa Al_Dosary Department of Computer Networking System College of Computer Sciences and Information TechnologyUniversity of AnbarRamadiIraq College of Medicine University of AnbarRamadiIraq Department of Computer Science Faculty of Computer Science and Information TechnologyAlbaha UniversityAlbahaSaudi Arabia College of Computer Sciences and Information Technology University of AnbarRamadiIraq

Self-driving and semi-self-driving cars play an important role in our daily *** effectiveness of these cars is based heavily on the use of their surrounding areas to collect sensitive and vital ***,external infrastructures also play significant roles in the transmission and reception of control data,cooperative awareness messages,and caution *** this case,roadside units are considered one of themost important communication *** distribution of these infrastructures will overburden the spread of self-driving vehicles in terms of cost,bandwidth,connectivity,and radio coverage *** this paper,a new distributed roadside unit is proposed to enhance the performance and connectivity of these ***,this approach is based primarily on k-means to find the optimal location of each roadside *** addition,this approach supports dynamicmobility with a long period of connectivity for each ***,this system can adapt to various locations(e.g.,highways,rural areas,urban environments).The simulation results of the proposed system are reflected in its efficiency and ***,the system can achieve a high connectivity rate with a low error rate while reducing costs.

关键词： Self-driving cars roadside unit autonomous vehicles distributed systems connectivity

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Impolite Words Detection Algorithm for Standard Thai and Thai Regional Dialects 28

Impolite Words Detection Algorithm for Standard Thai and Tha...

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28th International computer science and Engineering Conference, ICSEC 2024

作者： Charungchit, Kanida Abhiratthanarath, Nannapas Khancome, Chouvalit Rajabhat Rajanagarindra University Faculty of Science and Technology Department of Information Technology Chachoengsao Thailand Ramkhamhaeng University Faculty of Science Department of Computer Scienc Bangkok Thailand

ISBN: (纸本)9798350366860

Impolite word detection, also known as rude word detection, is a natural language processing (NLP) technique designed to identify inappropriate or offensive language in texts and various media. This technique aims to prevent the use of language that could be considered inappropriate or cause discomfort in online communities and communication applications. This research article introduces a novel approach for detecting impolite Thai words, encompassing various Thai dialects, and identifying the regional origin of the offensive words. The new algorithm employs multiple dictionaries;each stored using inverted lists based on character positions rather than direct word storage. This dictionary structure enables the search process to achieve 100% efficiency with no errors. Experimental results from a program developed to detect impolite words in standard Thai, as well as Northern, Southern, and Northeastern Thai dialects, demonstrated 100% accuracy, significantly outperforming previous detection algorithms. Additionally, the new algorithm outperformed current Generative AI models, even without considering sentence context or utilizing AI. © 2024 IEEE.

关键词： Linguistics

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Development of a Lightweight Model for Handwritten Dataset Recognition: Bangladeshi City Names in Bangla Script

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computers, Materials & Continua 2024年第8期80卷 2633-2656页

作者： MdMahbubur Rahman Tusher Fahmid Al Farid MdAl-Hasan Abu Saleh Musa Miah Susmita Roy Rinky Mehedi Hasan Jim Sarina Mansor MdAbdur Rahim Hezerul Abdul Karim Department of Computer Science and Engineering Bangladesh Army University of Science and Technology(BAUST)Saidpur5310Bangladesh Faculty of Engineering Multimedia UniversityCyberjaya63100Malaysia Pabna University of Science and Technology Pabna6600Bangladesh

The context of recognizing handwritten city names,this research addresses the challenges posed by the manual inscription of Bangladeshi city names in the Bangla *** today’s technology-driven era,where precise tools for reading handwritten text are essential,this study focuses on leveraging deep learning to understand the intricacies of Bangla *** existing dearth of dedicated datasets has impeded the progress of Bangla handwritten city name recognition systems,particularly in critical areas such as postal automation and document ***,no prior research has specifically targeted the unique needs of Bangla handwritten city name *** bridge this gap,the study collects real-world images from diverse sources to construct a comprehensive dataset for Bangla Hand Written City name *** emphasis on practical data for system training enhances *** research further conducts a comparative analysis,pitting state-of-the-art(SOTA)deep learning models,including EfficientNetB0,VGG16,ResNet50,DenseNet201,InceptionV3,and Xception,against a custom Convolutional Neural Networks(CNN)model named“Our CNN.”The results showcase the superior performance of“Our CNN,”with a test accuracy of 99.97% and an outstanding F1 score of 99.95%.These metrics underscore its potential for automating city name recognition,particularly in postal *** study concludes by highlighting the significance of meticulous dataset curation and the promising outlook for custom CNN *** encourages future research avenues,including dataset expansion,algorithm refinement,exploration of recurrent neural networks and attention mechanisms,real-world deployment of models,and extension to other regional languages and *** recommendations offer exciting possibilities for advancing the field of handwritten recognition technology and hold practical implications for enhancing global postal services.

关键词： Handwritten recognition Bangladeshi city names Bangla handwritten city name automated postal services

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RobustFace: a novel image restoration technique for face adversarial robustness improvement

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Multimedia Tools and Applications 2025年第11期84卷 8965-8993页

作者： Sadu, Chiranjeevi Das, Pradip K. Yannam, V Ramanjaneyulu Nayyar, Anand Department of Computer Science and Engineering RGUKT Nuzvid Andhra Pradesh Nuzvid India Department of Computer Science and Engineering IIT Guwahati Assam Guwahati India School of Technology Woxsen University Telangana Hyderabad India Graduate School Faculty of Information Technology Duy Tan University Da Nang550000 Viet Nam

Machine Learning (ML) models, particularly Deep Learning (DL), have made rapid progress and achieved significant milestones across various applications, including numerous safety-critical contexts. However, these models have recently been discovered to be susceptible to adversarial attacks, which are well-crafted input images. The primary objective of this paper is to propose a novel methodology titled "RobustFace", which is based on deep image restoration networks, that significantly improves the facial adversarial robustness of various image-classification models. Adversarial images are created using the Private Fast Gradient Sign Method (P-FGSM), StyleGAN and Fast Landmark Manipulation (FLM) methods. The adversarial images are then enhanced using deep image restoration networks to bring back them into the original space. The encoded weighted local magnitude patterns (WLMP) are extracted and provided to different types of classifiers to detect facial adversarial images from the clean images. The effectiveness of RobustFace has been demonstrated on two real-world datasets and experimental outcomes show that it significantly improves facial adversarial robustness on all evaluating classifiers. It improves the highest classification accuracy from 98.75% to 99.00% on P-FGSM attacks, from 77.94% to 85.25% on adversarial attacks generated by StyleGAN and from 65.52% to 69.50% for FLM attacks. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Image reconstruction

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Cat Swarm Algorithm Generated Based on Genetic Programming Framework Applied in Digital Watermarking

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computers, Materials & Continua 2025年第5期83卷 3135-3163页

作者： Shu-Chuan Chu Libin Fu Jeng-Shyang Pan Xingsi Xue Min Liu School of Artificial Intelligence Nanjing University of Information Science and TechnologyNanjing210000China College of Computer Science and Engineering Shandong University of Science and TechnologyQingdao266000China Department of Information Management Chaoyang University of TechnologyTaichung40601TaiwanChina School of Information Science and Engineering Fujian University of TechnologyFuzhou350000China Key Laboratory of Hydrometeorological Disaster Mechanism and Warning of Ministry of Water Resource Nanjing University of Information Science and TechnologyNanjing210000China

Evolutionary algorithms have been extensively utilized in practical ***,manually designed population updating formulas are inherently prone to the subjective influence of the *** programming(GP),characterized by its tree-based solution structure,is a widely adopted technique for optimizing the structure of mathematical models tailored to real-world *** paper introduces a GP-based framework(GPEAs)for the autonomous generation of update formulas,aiming to reduce human *** modifications to tree-based GP have been instigated,encompassing adjustments to its initialization process and fundamental update operations such as crossover and mutation within the *** designing suitable function sets and terminal sets tailored to the selected evolutionary algorithm,and ultimately derive an improved update *** Cat Swarm Optimization Algorithm(CSO)is chosen as a case study,and the GP-EAs is employed to regenerate the speed update formulas of the *** validate the feasibility of the GP-EAs,the comprehensive performance of the enhanced algorithm(GP-CSO)was evaluated on the CEC2017 benchmark ***,GP-CSO is applied to deduce suitable embedding factors,thereby improving the robustness of the digital watermarking *** experimental results indicate that the update formulas generated through training with GP-EAs possess excellent performance scalability and practical application proficiency.

关键词： Cat swarm algorithm genetic programming digital watermarking update mode mode generation framework

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