检索结果-内蒙古大学图书馆

14th IEEE Global Engineering Education Conference, EDUCON 2023

作者： Madathil, Nisha Thorakkattu Alrabaee, Saed Al-Kfairy, Mousa Damseh, Rafat Belkacem, Abdelkader N College of IT United Arab Emirates University Department of Information Systems and Security United Arab Emirates College of Technological Innovation Zayed University Dubai United Arab Emirates College of IT Department of Computer Science and Software Engineering United Arab Emirates University United Arab Emirates College of IT Department of Computer Engineering and Networks United Arab Emirates University United Arab Emirates

ISBN: (纸本)9798350399431

Education is essential for achieving many Sustainable Development Goals (SDGs). Therefore, the education system focuses on empowering more educated people and improving the quality of the education system. One of the latest technologies to enhance the quality of education is Artificial Intelligence (AI)-based Machine Learning (ML). As a result, ML has a significant influence on the education system. ML is currently widely applied in the education system for various tasks, such as creating models by monitoring student performance and activities that accurately predict student outcomes, their engagement in learning activities, decision-making, problem-solving capabilities, etc. In this research, we provide a survey of machine learning frameworks for both distributed (clusters of schools and universities) and centralized (university or school) educational institutions to predict the quality of students' learning outcomes and find solutions to improve the quality of their education system. Additionally, this work explores the application of ML in teaching and learning for further improvements in the learning environment for centralized and distributed education systems. © 2023 IEEE.

关键词： Sustainable development

来源：评论

学校读者我要写书评

暂无评论

Public Key Infrastructure Approaches Based on Blockchain

Public Key Infrastructure Approaches Based on Blockchain

引用

IEEE SSD International Multi-Conference on systems, Signals and Devices

作者： Dena S. Alani Ali M Sagheer College of Education for Women University of Anbar Anbar Iraq Department of Computer Networks Systems College of Computer Science and Information Technology University of Anbar Anbar Iraq

ISBN: (数字)9798350374131

ISBN: (纸本)9798350374148

Public-key infrastructure or PKI, is the fundamental technology that makes safe online information sharing possible. But PKI is vulnerable to failures of Certificate Authorities (CAs), which could allow illegal certificates to be issued to the end users. The security of the corresponding end users is at danger if a CA is compromised, as seen by numerous recent breaches. Blockchain technology is a new solution that has the ability to address the issues with traditional PKI systems, specifically the removal of single points of failure and the quick response to CA flaws. Blockchain technology facilitates the management and archiving of digital certificates in an unchangeable, publicly accessible ledger, producing a history log that can be completely tracked. In this article, the classical and modern blockchain-based PKI strategies were explained in addition to illustrating the limitations of each strategy. Finally, this article analyzed PKI methods by comparing their features according to a number of parameters.

关键词： Privacy Scalability Public key Information sharing Authentication Blockchains Encryption

来源：评论

学校读者我要写书评

暂无评论

Optimizing Connections:Applied Shortest Path Algorithms for MANETs

引用

computer Modeling in Engineering & sciences 2024年第10期141卷 787-807页

作者： Ibrahim Alameri Jitka Komarkova Tawfik Al-Hadhrami Abdulsamad Ebrahim Yahya Atef Gharbi Faculty of Medical Sciences Jabir Ibn Hayyan Medical UniversityAlkufaNajaf54001Iraq Faculty of Economics and Administration University of PardubiceStudentskaPardubice53210Czech Republic Computer Science Department School of Science and TechnologyNottingham Trent UniversityNottinghamNG118NSUK Department of Information Technology College of Computing and Information TechnologyNorthern Border UniversityArar91431Saudi Arabia Department of Information System College of Computing and Information TechnologyNorthern Border UniversityArar91431Saudi Arabia

This study is trying to address the critical need for efficient routing in Mobile Ad Hoc networks(MANETs)from dynamic topologies that pose great challenges because of the mobility of *** objective was to delve into and refine the application of the Dijkstra’s algorithm in this context,a method conventionally esteemed for its efficiency in static ***,this paper has carried out a comparative theoretical analysis with the Bellman-Ford algorithm,considering adaptation to the dynamic network conditions that are typical for *** paper has shown through detailed algorithmic analysis that Dijkstra’s algorithm,when adapted for dynamic updates,yields a very workable solution to the problem of real-time routing in *** results indicate that with these changes,Dijkstra’s algorithm performs much better computationally and 30%better in routing optimization than Bellman-Ford when working with configurations of sparse *** theoretical framework adapted,with the adaptation of the Dijkstra’s algorithm for dynamically changing network topologies,is novel in this work and quite different from any traditional *** adaptation should offer more efficient routing and less computational overhead,most apt in the limited resource environment of ***,from these findings,one may derive a conclusion that the proposed version of Dijkstra’s algorithm is the best and most feasible choice of the routing protocol for MANETs given all pertinent key performance and resource consumption indicators and further that the proposed method offers a marked improvement over traditional *** paper,therefore,operationalizes the theoretical model into practical scenarios and also further research with empirical simulations to understand more about its operational effectiveness.

关键词： Dijkstra’s algorithm optimization complexity analysis shortest path first comparative algorithm analysis nondeterministic polynomial(NP)-complete

来源：评论

学校读者我要写书评

暂无评论

Joint Power Allocation and Task Scheduling for Data Offloading in Non-Geostationary Orbit Satellite networks

引用

IEEE Transactions on Network and Service Management 2025年第3期22卷 2882-2896页

作者： He, Lijun Jia, Ziye Wang, Juncheng Lansard, Erick Han, Zhu Yuen, Chau China University of Mining and Technology School of Information and Control Engineering Xuzhou221116 China Xidian University State Key Laboratory of Integrated Services Networks Xi’an710071 China Nanjing University of Aeronautics and Astronautics College of Electronic and Information Engineering Nanjing211106 China Southeast University National Mobile Communications Research Laboratory Nanjing211111 China Hong Kong Baptist University Department of Computer Science Kowloon Tsai Hong Kong Nanyang Technological University School of Electrical and Electronics Engineering Jurong West 639798 Singapore University of Houston Department of Electrical and Computer Engineering HoustonTX77004 United States Kyung Hee University Department of Computer Science and Engineering Seoul446-701 Korea Republic of

In Non-Geostationary Orbit Satellite networks (NGOSNs) with a large number of battery-carrying satellites, proper power allocation and task scheduling are crucial to improving data offloading efficiency. In this work, we jointly optimize power allocation and task scheduling to achieve energy-efficient data offloading in NGOSNs. Our goal is to properly balance the minimization of the total energy consumption and the maximization of the sum weights of tasks. Due to the tight coupling between power allocation and task scheduling, we first derive the optimal power allocation solution to the joint optimization problem with any given task scheduling policy. We then leverage the conflict graph model to transform the joint optimization problem into an Integer Linear Programming (ILP) problem with any given power allocation strategy. We explore the unique structure of the ILP problem to derive an efficient semidefinite relaxation-based solution. Finally, we utilize the genetic framework to combine the above special solutions as a two-layer solution for the original joint optimization problem. Simulation results demonstrate that our proposed solution can properly balance the reduction of total energy consumption and the improvement of the sum weights of tasks, thus achieving superior system performance over the current literature. © 2004-2012 IEEE.

关键词： Geostationary satellites

来源：评论

学校读者我要写书评

暂无评论

Advanced Techniques for Dynamic Malware Detection and Classification in Digital Security Using Deep Learning

引用

computers, Materials & Continua 2025年第6期83卷 4575-4606页

作者： Taher Alzahrani Information System Department College of Computer and Information ScienceImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11673Saudi Arabia

The rapid evolution of malware presents a critical cybersecurity challenge,rendering traditional signature-based detection methods ineffective against novel *** growing threat affects individuals,organizations,and governments,highlighting the urgent need for robust malware detection *** machine learning-based approaches rely on static and dynamicmalware analysis and often struggle to detect previously unseen threats due to their dependency on predefined *** machine learning algorithms(MLAs)offer promising detection capabilities,their reliance on extensive feature engineering limits real-time *** learning techniques mitigate this issue by automating feature extraction but may introduce computational overhead,affecting deployment *** research evaluates classical MLAs and deep learningmodels to enhance malware detection performance across diverse *** proposed approach integrates a novel text and imagebased detection framework,employing an optimized Support Vector Machine(SVM)for textual data analysis and EfficientNet-B0 for image-based malware *** analysis,conducted across multiple train-test splits over varying timescales,demonstrates 99.97%accuracy on textual datasets using SVM and 96.7%accuracy on image-based datasets with EfficientNet-B0,significantly improving zero-day malware ***,a comparative analysis with existing competitive techniques,such as Random Forest,XGBoost,and CNN-based(Convolutional Neural Network)classifiers,highlights the superior performance of the proposed model in terms of accuracy,efficiency,and robustness.

关键词： Machine learning EffiicientNet B0 malimg dataset XceptionNet malware detection deep learning techniques support vector machines(SVM)

来源：评论

学校读者我要写书评

暂无评论

An Efficient Real-Time Moroccan Automatic License Plate Recognition system Based on the YOLO Object Detector 6th

An Efficient Real-Time Moroccan Automatic License Plate Reco...

引用

6th International Conference on Big Data Cloud and Internet of Things, BDIoT 2022

作者： Ouardirhi, Zainab Mahmoudi, Sidi Ahmed Zbakh, Mostapha El Ghmary, Mohamed Benjelloun, Mohammed Abdelali, Hamd Ait Derrouz, Hatim Communication Networks Department ENSIAS Mohammed V University in Rabat Rabat Morocco Mons Belgium Department of Computer Science FSDM Sidi Mohamed Ben Abdellah University Fez Morocco Microelectronics Embedded System Department Moroccan Foundation for Advanced Science Innovation and Research Rabat Morocco

ISBN: (纸本)9783031283864

In this paper, we adopt a powerful deep neural network (DNN) to tackle the problems of detecting car license plates (LPs) and recognizing Arabic letters in natural scene images. Our Automatic License Plate Recognition (ALPR) system is built using state-of-the-art methodologies and techniques to provide the optimal speed/accuracy trade-off at each level. Images of vehicles and Moroccan and European LPs were used to train the neural networks. The system was able to correctly detect and recognize in the test set all the characters existing in a LP with an accuracy of 91.11% and 98.89% taking into account that only one character is misread. Using a high-end GPU, our system likewise produced outstanding real-time execution results. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Economic and social effects

来源：评论

学校读者我要写书评

暂无评论

Optimal Deep Hybrid Boltzmann Machine Based Arabic Corpus Classification Model

引用

computer systems science & Engineering 2023年第9期46卷 2755-2772页

作者： Mesfer Al Duhayyim Badriyya B.Al-onazi Mohamed K.Nour Ayman Yafoz Amal S.Mehanna Ishfaq Yaseen Amgad Atta Abdelmageed Gouse Pasha Mohammed Department of Computer Science College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj16273Saudi Arabia Department of Language Preparation Arabic Language Teaching InstitutePrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversityMakkah 24211Saudi Arabia Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia Department of Digital Media Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11845Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Natural Language Processing(NLP)for the Arabic language has gained much significance in recent *** most commonly-utilized NLP task is the‘Text Classification’*** main intention is to apply the Machine Learning(ML)approaches for automatically classifying the textual files into one or more pre-defined *** ML approaches,the first and foremost crucial step is identifying an appropriate large dataset to test and train the *** of the trending ML techniques,i.e.,Deep Learning(DL)technique needs huge volumes of different types of datasets for training to yield the best *** current study designs a new Dice Optimization with a Deep Hybrid Boltzmann Machinebased Arabic Corpus Classification(DODHBM-ACC)model in this *** presented DODHBM-ACC model primarily relies upon different stages of pre-processing and the word2vec word embedding *** Arabic text classification,the DHBM technique is *** technique is a hybrid version of the Deep Boltzmann Machine(DBM)and Deep Belief Network(DBN).It has the advantage of learning the decisive intention of the classification *** adjust the hyperparameters of the DHBM technique,the Dice Optimization Algorithm(DOA)is exploited in this *** experimental analysis was conducted to establish the superior performance of the proposed DODHBM-ACC *** outcomes inferred the better performance of the proposed DODHBM-ACC model over other recent approaches.

关键词： Arabic corpus text classification machine learning deep learning dice optimization

来源：评论

学校读者我要写书评

暂无评论

A systematic Literature Review on Cybersecurity Risk Management in Smart Cities

A Systematic Literature Review on Cybersecurity Risk Managem...

引用

International Conference on Artificial Intelligence in Information and Communication (ICAIIC)

作者： Jawaher Alshehri Almaha Alhamed M M Hafizur Rahman Department of Computer Networks & Communications King Faisal University College of Computer Science and Information Technology Al Hofuf Al Hassa Saudi Arabia

A smart city is a digital and intelligent city that uses communication and information technology (ICT) that contains different types of technology methods to meet the needs of current and future generations regarding economic, social, cultural, and environmental aspects. Smart cities face many risks in technology, which make their management difficult and easy to attack. The concept of smart cities has emerged as a promising solution to face various urban challenges. In addition, it has been determined that a 38.7 percent increase in smart city risk management significantly increased the number of attacks across the TOE (technology, organization, and environment) categories. The research aims to highlight the role of cybersecurity risk management in smart cities, including preventing threats and the essential attacks that face smart cities. To strengthen the security and resilience of smart cities, it is crucial to comprehend the unique difficulties and dangers related to cybersecurity in these urban environments and take necessary steps accordingly. The primary objective of this research is to enhance the cybersecurity risk management role in smart cities, thereby guaranteeing the sustainable and secure growth of technologically sophisticated metropolitan regions. Index Terms-Cybersecurity risk management, smart cities, risk management, internet of things (IoT), artificial intelligence.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Comprehensive Analysis of Hate Speech Detection and Recognition Utilising Advanced Machine Learning Algorithms and Techniques 3

A Comprehensive Analysis of Hate Speech Detection and Recogn...

引用

3rd IEEE International Conference on Automation and Computation, AUTOCOM 2025

作者： Mannepalli, Praveen Kumar Sharma, Saurabh Rajput, Neha Kalamdhad, Sanjay Chandigarh University Department of Computer Science & Engineering Mohali India Chandigarh University Department of Computer Science and Engineering Mohali India Chandigarh University Department of Computer Science and Engineering Punjab India St. Vincent Pallotti College of Engineering and Technology Department of Computer Science & Business System Nagpur India

ISBN: (纸本)9798331542375

Social networking sites have come into demand as a way of sharing ideas and opinions with other people. But unfortunately, people tend to misuse social media to write nasty comments. Victims' lives might be negatively impacted by behaviours that are abusive and humiliating. Social networks give people a great tool to share information on ideas on multiple topics and opinions. However, these platforms are often abused to announce toxic and offensive comments, which eventually negatively affect victims and demographics. This study offers a thorough method for identifying hate speech (HS) on social media by utilising cutting-edge ML algorithms. A publicly available Twitter dataset containing 159,571 tweets classified into six categories, including toxic and identity hatred, was utilised. The methodology comprises data collection, conditioning, and categorisation that employs BiLSTM, which is particularly appropriate for the tasks demanding contextual sensitivity. These operations include symbol removing, stemming and stop-word eliminating, feature extraction using TF-IDF, and using the Bag-of-Words model. For classification of the data between hate and non-hate, the dataset is then split into training and testing datasets and the BiLSTM model used to provide classifications for the text. The evaluation of the BiLSTM model demonstrates superior performance, achieving an accuracy86%, a precision90%, a recall86%, and an F1-score88% • A comparison between the model and other models such as SVM and CNN reveals the strength of the BiLSTM in contextual classification tasks. The results demonstrate that BiLSTM can tackle problems with hate speech detection, providing a strong answer to the problem of harmful content on social media and helping to make the internet a better place for everyone. © 2025 IEEE.

关键词： Tweets

来源：评论

学校读者我要写书评

暂无评论

LESSONS LEARNED FROM THE COVID-19 PANDEMIC: AN ANALYSIS OF REGIONAL PHILIPPINE DATA AND COVID-19 OUTCOMES

LESSONS LEARNED FROM THE COVID-19 PANDEMIC: AN ANALYSIS OF R...

引用

2023 Philippine Geomatics Symposium, PhilGEOS 2023

作者： Gaano, J.B. Rule, C. Celeste, J. Bongolan, V.P. Rivera, R.L. Caoili, S.E. System Modeling and Simulation Lab Department of Computer Science College of Engineering University of the Philippines – Diliman Quezon City Philippines Center for Informatics University of San Agustin Iloilo Philippines College of Social Work and Community Development UP Diliman Philippines UP College of Medicine Philippines

Variations in indicators which may affect COVID-19 outcomes exist among regions in the Philippines. These variations suggest that the impacts of the pandemic differ not only between countries but also within regions and local areas in a country. This study aims to investigate COVID-19 outcomes (case fatality rate or CFR, incidence rate and hospitalization rate) over time and their correlation with regional healthcare and population factors during different phases of the pandemic across the 17 regions of the Philippines. These outcomes were chosen because they are readily available from government data sources, and are simple to work with. We mark five 100-day time periods of the COVID-19 pandemic in the country. The COVID-19 dataset was based on data maintained by the department of Health (DOH). Spearman’s rank correlation coefficient analysis was used to examine the link between COVID-19 outcomes region-specific indicators referring to population and access to health care resources. Despite their higher vaccination coverage, regions with greater access to health care resources may still be susceptible to future COVID-19 outbreaks due to their urban and densely populated nature. However, vaccines remain effective in reducing COVID-19 hospitalizations in these regions. Therefore, it is crucial to focus on increasing vaccination coverage in rural, underserved regions and implement targeted outbreak control measures in densely populated areas. © Author(s) 2024.

关键词： COVID-19

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：