检索结果-内蒙古大学图书馆

26th International Conference on Advanced Communications Technology, ICACT 2024

作者： Kuzmina, Ekaterina Tefikova, Meriem Volkov, Artem Muthanna, Ammar Ateya, Abdelhamied A. Koucheryavy, Andrey Saint-Petersburg State University of Telecommunications Department of Telecommunication Networks and Data Transmission Saint Petersburg Russia Zagazig University Department of Electronics and Communications Engineering Zagazig44519 Egypt College of Computer and Information Sciences Prince Sultan University Eias Data Science Lab Riyadh11586 Saudi Arabia

ISBN: (纸本)9791188428120

This paper provides a real-time fog computing model based on a microservice architecture that enables testing and modeling of eventual implementations of ultra-reliable low-latency communications (uRLLC) services. The work provides fog-based architecture for sixth-generation cellular (6G) applications, including telepresence and uRLLC. A testbed of a robot swarm was developed to prototype the proposed network architecture. Computing tasks are offloaded and handled based on a proposed microservice scheme introduced to meet the 6G requirements. Furthermore, we developed a novel migration scheme for the proposed architecture to support the mobility of end devices. The optimum server for migrating computing tasks is allocated by solving a proposed optimization problem using particle swarm optimization (PSO). All proposed algorithms were implemented in the developed prototype. The proposed work is introduced to provide an architectural foundation for testing fog-based 6G applications and services and to implement and test novel network methods in the future. © 2024 Global IT Research Institute - GIRI.

关键词： Fog

来源：评论

学校读者我要写书评

暂无评论

Task Offloading and Resource Allocation in IoT Based Mobile Edge Computing Using Deep Learning

引用

computers, Materials & Continua 2023年第8期76卷 1463-1477页

作者： Ily s Abdullaev Natalia Prodanova KAruna Bhaskar ELaxmi Lydia Seifedine Kadry Jungeun Kim Dean of the Faculty of Economics Department of Management and MarketingFaculty of EconomicsUrgench State UniversityUrganch220100Uzbekistan Basic Department Financial Control Analysis and Audit of Moscow Main Control DepartmentPlekhanov Russian University of EconomicsMoscow117997Russia Department of Computer Science and Engineering KL Deemed to UniversityVaddeswaramGunturAndhra PradeshIndia Department of Computer Science and Engineering GMR Institute of TechnologyAndhra PradeshRajamIndia Department of Applied Data Science Noroff University CollegeKristiansandNorway Artificial Intelligence Research Center(AIRC) Ajman UniversityAjman346United Arab Emirates Department of Electrical and Computer Engineering Lebanese American UniversityByblosLebanon Department of Software Kongju National UniversityCheonan31080Korea

Recently,computation offloading has become an effective method for overcoming the constraint of a mobile device(MD)using computationintensivemobile and offloading delay-sensitive application tasks to the remote cloud-based data *** city benefitted from offloading to edge *** a mobile edge computing(MEC)network in multiple *** comprise N MDs and many access points,in which everyMDhasM independent real-time *** study designs a new Task Offloading and Resource Allocation in IoT-based MEC using Deep Learning with Seagull Optimization(TORA-DLSGO)*** proposed TORA-DLSGO technique addresses the resource management issue in the MEC server,which enables an optimum offloading decision to minimize the system *** addition,an objective function is derived based on minimizing energy consumption subject to the latency requirements and restricted *** TORA-DLSGO technique uses the deep belief network(DBN)model for optimum offloading ***,the SGO algorithm is used for the parameter tuning of the DBN *** simulation results exemplify that the TORA-DLSGO technique outperformed the existing model in reducing client overhead in the MEC systems with a maximum reward of 0.8967.

关键词： Mobile edge computing seagull optimization deep belief network resource management parameter tuning

来源：评论

学校读者我要写书评

暂无评论

Multi-Tree Genetic Programming for Learning Color and Multi-Scale Features in Image Classification

引用

IEEE Transactions on Evolutionary Computation 2024年 1-1页

作者： Fan, Qinglan Bi, Ying Xue, Bing Zhang, Mengjie School of Computer Science and Technology Shandong University of Finance and Economics Jinan China School of Electrical and Information Engineering Zhengzhou University Zhengzhou China Center for Data Science and Artificial Intelligence and School of Engineering and Computer Science Victoria University of Wellington Wellington New Zealand

data-efficient image classification, which focuses on achieving accurate classification performance with limited labeled data, has garnered significant attention. Genetic programming (GP) has achieved impressive progress in image classification, particularly in scenarios involving small amounts of labeled data. GP research typically focuses on designing tree-based model representations to learn useful image features for classification. However, most GP methods are proposed for gray-scale images and ignore the color features. Furthermore, the existing GP methods typically learn features on a single scale/resolution, restricting potential accuracy enhancements. To address these issues, this paper proposes a new multi-tree GP In single-tree GP (or simply GP), each individual consists of a single tree. In contrast, in multi-tree GP, each individual comprises multiple trees. representation for image feature learning and classification. In each individual, three trees are included to extract discriminative features from the red, green, and blue channels of the image. With the new image resizing layer in the tree representation, the proposed approach can achieve multi-scale feature extraction, i.e., flexibly learning fine-grained details and coarse-grained structures in the image, improving the classification performance. In addition, since a limitation of GP is premature convergence due to a decline in population diversity, this paper develops a hybrid parent selection method consisting of tournament and lexicase selection to increase population diversity, find the best individual, and improve classification accuracy. The experiments on six image classification datasets indicate that the proposed approach outperforms state-of-the-art neural network-based and GP-based methods in almost all comparisons. Further analyses demonstrate the effectiveness of each component and the potentially high interpretability of the proposed approach. IEEE

关键词： Genetic programming

来源：评论

学校读者我要写书评

暂无评论

MOMENTS AND LARGE DEVIATIONS FOR SUPERCRITICAL BRANCHING PROCESSES WITH IMMIGRATION IN RANDOM ENVIRONMENTS

引用

Acta Mathematica Scientia 2022年第1期42卷 49-72页

作者： Chunmao HUANG Chen WANG Xiaoqiang WANG Department of Mathematics Harbin Institute of Technology(Weihai)Weihai 264209China School of Data and Computer Science Sun Yat-sen UniversityGuangzhou 510006China School of Mathematics and Statistics Shandong UniversityWeihai 264209China

Let(Z_(n))be a branching process with immigration in a random environmentξ,whereξis an independent and identically distributed sequence of random *** show asymptotic properties for all the moments of Z_(n) and describe the decay rates of the n-step transition *** applications,a large deviation principle for the sequence log Z_(n) is established,and related large deviations are also studied.

关键词： branching process with immigration random environment moments harmonic moments large deviations

来源：评论

学校读者我要写书评

暂无评论

Enhancing IoT Security with Self-Adaptive Blockchain-Based Intrusion Detection System

Enhancing IoT Security with Self-Adaptive Blockchain-Based I...

引用

2023 Intelligent Computing and Control for Engineering and Business Systems, ICCEBS 2023

作者： Naik, Pramod Kumar Mannanuddin, Khaja Sundaresan, K. Sah, Swati Patil, Harshal Firos, A. Dayananda Sagar University Department Cse Bangalore India School of Computer Science & Ai Sr University Telangana Warangal India Karpagam Institute of Technology. Coimbatore Anna University Department of Artificial Intelligence and Data Science Chennai India School of Set Sharda University Greater Noida India Pune India Rono-Hills Department of Computer Science and Engineering Arunachal Pradesh Doimukh India

ISBN: (纸本)9798350394580

The extensive adoption of Internet of Things (IoT) devices has resulted in a revolution across a variety of business sectors by presenting previously unimaginable prospects for connection and automation. Despite this, there has been a significant increase in the usage of IoT, which has led to important security issues. This research presents a ground-breaking security solution known as the Self-Adaptive Blockchain-Based Intrusion Detection System (SAB-IDSI), which was developed particularly for Internet of Things (IoT) settings. In order to determine how well SAB-IDSI performs in contrast to traditional Intrusion Detection Systems (IDS), a series of experiments and assessments were carried out. The findings indicate that there was a significant increase in the accuracy of the intrusion detection. The outstanding capability of SAB-IDSI to reliably detect genuine incursions while limiting false alarms is demonstrated by its accuracy, which is 96.2%. False alerts are kept to a minimum. In addition to this, it has a very high recall rate of 94.8%, which ensures that it has a very high capture rate of genuine incursions. The fact that SAB-IDSI has a balanced F1-Score of 95.5% further validates its overall efficacy in the detection of intrusions. The average reaction time of 12.5 milliseconds for SAB-IDSI is clear evidence of its effectiveness in rapidly responding to threats, greatly surpassing the performance of traditional IDS. This highlights its potential for timely threat mitigation, which is essential in situations where time is of the essence. In addition to this, SAB-IDSI has a significantly lower energy consumption rate, which demonstrates its potential to increase the amount of time that Internet of Things devices may remain operational while also lowering total energy expenses. © 2023 IEEE.

关键词： Blockchain Decentralized Intrusion Detection IoT Security Machine Learning Self-Adaptive

来源：评论

学校读者我要写书评

暂无评论

Quantum Computing's Double-Edged Sword Unravelling the Vulnerabilities in Quantum Key Distribution for Enhanced Network Security

Quantum Computing's Double-Edged Sword Unravelling the Vulne...

引用

2023 IEEE International Conference on Next Generation Electronics, NEleX 2023

作者： Anantraj, I. Umarani, B. Karpagavalli, C. Usharani, C. Lakshmi, S. Jothi Sri Krishna College of Engineering and Technology Department of Computer Science and Business Systems Coimbatore India Kongunadu College of Engineering and Technology Department of Electronics and Communication Engineering Namakkal India Ramco Institute of Technology Department of Artificial Intelligence and Data Science Rajapalayam India

ISBN: (纸本)9798350319088

Quantum computing has emerged as both a boon and a bane in the realm of network security. This paper delves into the intriguing interplay between quantum computing and the vulnerabilities of Quantum Key Distribution (QKD) protocols, a cornerstone of secure quantum communication. While QKD offers unmatched security through the principles of quantum mechanics, it is not impervious to attacks in the age of rapidly advancing quantum computing. We examine these vulnerabilities, highlighting the challenges of ensuring the long-term security of quantum networks in a post-quantum world. Through a comprehensive exploration of threat models and the practicality of QKD, we uncover potential weaknesses in quantum network security. In particular, we investigate QKD's susceptibility to evolving quantum algorithms, hardware vulnerabilities, and post-processing security concerns. This work aims to provide a roadmap for understanding and addressing these vulnerabilities, ensuring the continued robustness of quantum communication networks, and fostering the development of post-quantum cryptographic solutions. As quantum computing advances, its implications for quantum network security are far-reaching. This study underlines the critical need for research and innovation in securing quantum communication. By unravelling the vulnerabilities within Quantum Key Distribution and exploring post-quantum cryptographic alternatives, this research contributes to the development of more resilient and secure quantum networks, safeguarding sensitive information and communications in an increasingly quantum-enabled world. © 2023 IEEE.

关键词： Quantum cryptography

来源：评论

学校读者我要写书评

暂无评论

Healthy/Glaucoma Fundus Retinal Image Classification using Butterfly Algorithm Optimized ResNet-Features

引用

Procedia computer science 2025年 258卷 1804-1812页

作者： Ramya Mohan Seifedine Kadry Sahar Yassine Venkatesan Rajinikanth Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences (SIMATS) Chennai 602105 TN India Department of applied data science Noroff University College Kristiansand Norway

Hospitals frequently use medical image supported disease diagnosis to identify diseases and evaluates their severity. Automation in image examination is normally preferred to reduce the diagnostic burden. Developing a Deep-Learning Tool (DLT) to analyze the fundus-photography (FP) labeled as healthy/glaucoma class is the aim of this research. Different phases in this DLT involves the following; collection of FP database from image repository and resizing it to 224x224x3 pixels, feature extraction using ResNet (RN) model, feature reduction using the Brownian-Butterfly Algorithm (BBA), serial concatenation of features to obtain fused-features (FF), and executing the binary classification using 3-fold cross validation. This work utilized a two-fold training in order to improve detection accuracy with the FP data. This investigation is executed using individual and FF to verify the DLT’s performance. The results of this research validates that, the K-Nearest Neighbor (KNN) assisted classification provides 100% accuracy when FF based investigation is executed.

关键词： Healthcare global health fundus image ResNet butterfly algorithm classification

来源：评论

学校读者我要写书评

暂无评论

Modeling Layout Reading Order as Ordering Relations for Visually-rich Document Understanding

Modeling Layout Reading Order as Ordering Relations for Visu...

引用

2024 Conference on Empirical Methods in Natural Language Processing, EMNLP 2024

作者： Zhang, Chong Tu, Yi Zhao, Yixi Yuan, Chenshu Chen, Huan Zhang, Yue Chai, Mingxu Guo, Ya Zhu, Huijia Zhang, Qi Gui, Tao School of Computer Science Fudan University Shanghai China Shanghai Key Laboratory of Intelligent Information Processing Shanghai China Ant Tiansuan Security Lab Ant Group Hangzhou China School of Statistics and Data Science Nankai University Tianjin China Institute of Modern Languages and Linguistics Fudan University Shanghai China

ISBN: (纸本)9798891761643

Modeling and leveraging layout reading order in visually-rich documents (VrDs) is critical in document intelligence as it captures the rich structure semantics within documents. Previous works typically formulated layout reading order as a permutation of layout elements, i.e. a sequence containing all the layout elements. However, we argue that this formulation does not adequately convey the complete reading order information in the layout, which may potentially lead to performance decline in downstream VrD tasks. To address this issue, we propose to model the layout reading order as ordering relations over the set of layout elements, which have sufficient expressive capability for the complete reading order information. To enable empirical evaluation on methods towards the improved form of reading order prediction (ROP), we establish a comprehensive benchmark dataset including the reading order annotation as relations over layout elements, together with a relation-extraction-based method that outperforms previous methods. Moreover, to highlight the practical benefits of introducing the improved form of layout reading order, we propose a reading-order-relation-enhancing pipeline to improve model performance on any arbitrary VrD task by introducing additional reading order relation inputs. Comprehensive results demonstrate that the pipeline generally benefits downstream VrD tasks: (1) with utilizing the reading order relation information, the enhanced downstream models achieve SOTA results on both two task settings of the targeted dataset;(2) with utilizing the pseudo reading order information generated by the proposed ROP model, the performance of the enhanced models has improved across all three models and eight cross-domain VrD-IE/QA task settings without targeted optimization. © 2024 Association for Computational Linguistics.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

Contour and key point based eye feature extraction

Contour and key point based eye feature extraction

引用

2023 International Conference on Image, Signal Processing, and Pattern Recognition, ISPP 2023

作者： Wang, Yue Wan, Yaping Min, Xiaoshan Fan, Zhiqing He, Yasha Zou, Gang School of Computer Science University of South China Hengyang421001 China Hunan Medical Big Data International Science and Technology Cooperation Base Hengyang421001 China Xiangya School of Medicine Central South University Changsha410205 China School of Computer Science and Technology North University of China Taiyuan030000 China Hunan ZhongkeZhuying Intelligent Technology Research Institute Changsha410205 China

ISBN: (纸本)9781510666351

The use of eye movements for identifying intrinsic human psychological changes is a hot topic, and the identification of eye states in specific scenarios is the basis for analyzing the test taker's instantaneous psychological response state and thus for testing implicit driving quality deficits. Infrared eye images are difficult to visualize eye movements, and traditional eye image processing results are not suitable for eye state analysis. In order to make the eye images show the eye movements, a feature extraction method based on contours and key point is proposed for infrared eye images. To extract the eye contour features, the iris and eyelid contours are extracted based on the variation of gray values between the points located on the boundary and their surroundings;for the extraction of eye key point features, a network design with a combination of dlib and residual structure is used to extract the pupil and eyelid key points, respectively. The experimental results show that the method can represent the relative positions of the pupil, iris and eyelid separately with little computational effort, which can intuitively show the eye movement and thus reduce the stress of subsequent eye state recognition. © 2023 SPIE.

关键词： Eye movements

来源：评论

学校读者我要写书评

暂无评论

3L-AODV: Three Layer Security Protocol for Grayhole Attack Mitigation in MANET 8th

3L-AODV: Three Layer Security Protocol for Grayhole Attack ...

引用

8th International Congress on Information and Communication Technology, ICICT 2023

作者： Kamel, Mohammed B. M. Abdullah, Wisam Dawood Hamoud, Alaa Khalaf Valadares, Dalton C. G. Shareiyat, Ammar Ligeti, Peter Department of Computer Algebra Eotvos Lorand University Budapest Hungary Institute for Data Science Cloud Computing and IT Security Furtwangen University of Applied Sciences Furtwangen im Schwarzwald Germany Department of Computer Science University of Kufa Najaf Iraq Department of Computer Science University of Tikrit Tikrit Iraq Department of Computer Information Systems University of Basrah Basrah Iraq Virtus RDI Center Federal University of Campina Grande Campina Grande Brazil Federal Institute of Pernambuco Pernambuco Caruaru Brazil Department of CSS University of Stockholm Stockholm Sweden Department of Vulnerability Operations Center Orange Cyberdefense Stockholm Sweden

ISBN: (纸本)9789819930425

As the mobile ad hoc networks infrastructure has no centralized points of connections, the traffic from a source to a destination passes through number of intermediate nodes. When more than one neighbor node is available, the traffic passes through one of them based on some criteria. If a node behaves maliciously in all of the connections and drops the traffic, it creates a security blackhole, while a malicious node that behaves normally is some of the connections creates a security grayhole. Since the malicious node behaves normally in some connections, mitigating this attack is challenging. In this paper, we proposed 3L-AODV, a security protocol that uses three layers of protection and detection to mitigate the grayhole attack. As it does not require any modification on the AODV protocol, it can be implemented on any network that its routing is based on AODV. The analysis of our results shows that 3L-AODV could mitigate the grayhole attack without affecting the performance of the network. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Mobile ad hoc networks

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：