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Fast Nondominated Sorting Genetic Algorithm For Multi-Objective Clustering Ensemble 4

Fast Nondominated Sorting Genetic Algorithm For Multi-Object...

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4th international conference on Advances in Computer Technology, Information science and Communications, CTISC 2022

作者： Li, Xu Wang, Jian Yang, Wenlu Wang, Hongjun Southwest Jiaotong University School of Computing and Artificial Intelligence Chengdu China Southwest Jiaotong University School of Information Science and Technology Chengdu China

ISBN: (数字)9781665458726

ISBN: (纸本)9781665458726

Clustering ensemble is to integrate the results of multiple base clustering by consensus function, which can improve the robustness, stability, and accuracy of the clustering algorithm. the existing clustering ensemble methods are basically to design a single consensus algorithm for integration. this paper proposes a fast nondominated sorting genetic algorithm for multi-objective clustering ensemble (NSGAMCE). In this model, two consensus functions are designed to act on the original data and the base clustering results respectively. Secondly, the nondominated sorting genetic algorithm II (NSGA-II) is used to solve the model, and the gene mutation strategy is changed to improve the convergence speed. then, according to the solving process of the model, the corresponding clustering ensemble algorithm is designed. Finally, the standard data set and the comparison algorithm are used to carry out experiments. the experimental results show that the clustering ensemble algorithm has good performance. © 2022 IEEE.

关键词： Genetic algorithms

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Analysis on Role of Quantum computing in Machine Learning 4

Analysis on Role of Quantum Computing in Machine Learning

引用

4th international conference on Cognitive computing and Information Processing, CCIP 2022

作者： Saju, Binju Gopal, Madhwaraj Kango Nithya, B. Asha, V. Kumar, Vikash New Horizon College of Engineering Master of Computer Applications Bengaluru India

ISBN: (纸本)9781665456487

Quantum machine learning is a process by which quantum computers are used to learn from data. It is still in its begining stages of development, but has the potential to be much more efficient than classical machine learning algorithms. the main advantages of machine learning is that it can exploit the massive parallelism of quantum computers. this means that quantum machine learning algorithms can potentially learn from data much faster than classical algorithms. Another advantage is that quantum machine learning algorithms can deal with data that is too large or too complex for classical algorithms. For example, a quantum algorithm could be used to learn from a dataset that is too large to fit into a classical computer's memory. there are still many challenges to overcome before quantum machine learning can be used in practice, but the potential benefits are huge. If successful, Quantum machine learning could revolutionize the field of machine learning and have a profound impact on many other areas of science and technology. © 2022 IEEE.

关键词： Large dataset

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Mitigation of DDoS Attack in SDN using Table Miss-entry 4

Mitigation of DDoS Attack in SDN using Table Miss-entry

引用

4th international conference on Circuits, Control, Communication and computing, I4C 2022

作者： Singh, Vaibhav Rajarajeswari, S. Kanavalli, Anita Sanjeetha, R. MS Ramaiah Institute of Technology Department of Computer Science and Engineering Bangalore560054 India Department of Computer Science and Engineering Sambhram Institute of Technology Bangalore560097 India

ISBN: (纸本)9798350397475

SDNs or Software Defined Networks differ from traditional networks due to the separation of the control and data plane. However, it is this centralized control that makes SDNs prone to DDoS attacks if the network operations are not addressed properly. One of the ways to cause DDoS is through an influx of control messages (PACKET-IN);due to the Flow Table Miss-entry rule, such attacks can be carried out rather easily. In this work, the aim is to look at DDoS attacks targeting the controller by generating large PACKET-IN traffic from switches and overwhelming them with large amounts of new requests. Such an attack causes the controller to not be able to serve even legitimate traffic. this research looks at effective detection and mitigation techniques utilizing the SNORT IDS that may be used to prevent such attacks from causing any significant harm to the network. © 2022 IEEE.

关键词： Controllers

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A Review Paper on IDS in Edge computing or EoT 4

A Review Paper on IDS in Edge Computing or EoT

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international conference on 4th Industrial Revolution Based Technology and Practices, ICFIRTP 2022

作者： Devi, Reshoo Kumar, Amit Kumar, Vivek Saini, Ashish Kumari, Amrita Kumar, Vipin Quantum University Dept. of Computer Science and Engineering India Quantum University GKDU Haridwar and Dept. of Computer Science and Engineering India GKDU Haridwar India

ISBN: (纸本)9798350345919

the main intention of edge computing is to improve network performance by storing and computing data at the edge of the network near the end user. However, its rapid development largely ignores security threats in large-scale computing platforms and their capable applications. therefore, Security and privacy are crucial need for edge computing and edge computing based environment. Security vulnerabilities in edge computing systems lead to security threats affecting edge computing networks. therefore, there is a basic need for an intrusion detection system (IDS) designed for edge computing to mitigate security attacks. Due to recent attacks, traditional algorithms may not be possibility for edge computing. this article outlines the latest IDS designed for edge computing and focuses on the corresponding methods, functions and mechanisms. this review also provides deep understanding of emerging security attacks in edge computing. this article proves that although the design and implementation of edge computing IDS have been studied previously, the development of efficient, reliable and powerful IDS for edge computing systems is still a crucial task. At the end of the review, the IDS developed will be introduced as a future prospect. © 2022 IEEE.

关键词： Edge computing Edge of things (EoT) Intrusion detection system (IDS) Machine learning

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the Russian Segment (RU-VRF) in WLCG Infrastructure: High Performance computing Network 4

The Russian Segment (RU-VRF) in WLCG Infrastructure: High Pe...

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4th international science and Technology conference "Modern Network Technologies", MoNeTec 2022

作者： Velikhov, Vasily E. Korenkov, Vladimir V. Ryabinkin, Eygene A. Dolbilov, Andrey G. Gugel, Yury V. Strizh, Tatiana A. Joint Computing Cluster National Research Center 'Kurchatov Institute' Moscow Russia International Intergovernmental Organization Joint Institute for Nuclear Research Meshcheryakov Laboratory of Information Technologies Dubna Russia

ISBN: (数字)9781665472463

ISBN: (纸本)9781665472463

the paper describes a high-performance computer network optimized for the transmission of experimental data generated by CERN for potential use by the Large Hadron Collider (LHC) network community, including the Russian segment of this network. the Worldwide LHC computing Grid (WLCG) is a global computing infrastructure whose mission is to provide computing resources for storing, distributing and analyzing data generated by the LHC at CERN, making the data equally accessible to all participants, regardless of their physical location. WLCG is a multi-layer distributed computing infrastructure. It provides a community of over 12,200 scientists of 110 nationalities from institutions in over 40 countries with near real-time access to LHC data. WLCG is the world's largest computer network. It is supported by many related national and international networks and projects around the world. Since the beginning of the WLCG Project the Russian computing centers in NRC 'Kurchatov Institute' an JINR have participated with reliable and stable resources as well as personnel for the LHC. Contribution to the ALICE, ATLAS, CMS and LHCb Tier 1 and Tier 2 computing resources (disk and CPUs) in the last 10 years has been substantial. In this paper, we would like to show the evolution and technical updates in the Russian segment Tier1 and Tier 2. the Russian segment is an infrastructure fully integrated into the WLCG. © 2022 IEEE.

关键词： Program processors

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Significant Impact of 5G Technology worldwide: With special reference to specific industries and Countries 7

Significant Impact of 5G Technology worldwide: With special ...

引用

7th international conference on computing, Communication and Security, ICCCS 2022 and 2022 4th international conference on Big data and Computational Intelligence, ICBDCI 2022

作者： Sindhwal, Prakash Rastogi, Neha Sharma, Megha Tyagi, Shagun Joshi, Kapil Mohialden, Yasmin Makki Uttaranchal University Uttaranchal Institute of Management Uttarakhand Dehradun248001 India Graphic Era Hill University School of Management Uttarakhand Dehradun248001 India Uttaranchal Institute of Technology Uttaranchal University Department of CSE Uttarakhand Dehradun India College of Science Mustansiriyah University Computer Science Department Baghdad Iraq

ISBN: (纸本)9798350309904

5G address the following major period of versatile telecom morals past the impending 4G guidelines. After 1G, 2G, 3G, and 4G organizations, it is now a new global distant norm. 5G remote technology is designed to deliver multi-gigabit per second (Gbps) maximum data speeds. Pinnacle downlink throughput execution is projected to be exceedingly high with 5G. the goal of this article is to identify, systematize, and generalize major of 5G technology. In the coming years, 5G networks will be widely deployed. Farmers might use real-Time data to monitor, track, and automate their agricultural operations. At home and at the stadium, sports fans could have more influence over their viewing experience. With peak performance of 20 Gbps, 5G claims to be 20 times faster than *** is assisting in the transformation of a variety of Industrial Internet of things (IIoT) applications. For the first time, new experiences such as augmented reality will become a reality. 5G technology is a fifth-generation invention with a wide range of applications. By 2026, the number of 5G cell phone users is predicted to surpass 3 billion. Many outdated gadgets will need to be replaced because they do not support 5 G. © 2022 IEEE.

关键词： 5G mobile communication systems

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Machine Learning for Load Forecasting in a Green data Center 4

Machine Learning for Load Forecasting in a Green Data Center

引用

4th international conference on Sustainable Technologies for Industry 4.0, STI 2022

作者： Ahmed, Md. Shakil Biswas, Swapnil Rahman, Md. Jobayer Habibur Rahaman Alhadi, Md. Moon, Rifat Ara Motaharul Islam, Md. United International University Dept. of Computer Science and Engineering Bangladesh

ISBN: (纸本)9781665490450

Since green cloud computing became a significant advancement in the world of computing in the past few years, its user base has been consistently expanding. Companies are adding more hosts and servers to their data centers to keep up with the ever-growing demand for cloud services. So, these huge servers use a lot of energy, raise costs, and put out a significant amount of greenhouse gasses. Also, even devices that are not being used use a lot of energy. Also, when CPU use reaches its peak, it is hard to keep node clusters running and use less energy. In this paper, we propose machine learning models to determine the minimum execution time. these models reduce the work done by machines and make sure that requests are managed correctly in data centers. therefore, the purpose of this study is to present an effective strategy for the management of energy with a focus on the sustainability of green cloud data centers. © 2022 IEEE.

关键词： Energy efficiency

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Estimating SIR Model Parameters for Predicting Covid-19 Cases in Bandung City 4

Estimating SIR Model Parameters for Predicting Covid-19 Case...

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4th international conference on Intelligent Cybernetics Technology and Applications, ICICyTA 2024

作者： Bintang, Kahfi M. Binti Alias, Norma Kurniawan, Wandi Yusuf Patrianingsih, Ni Kadek Winda Reganata, Gde Palguna Gunawan, Putu Harry School of Computing Telkom University Bandung40257 Indonesia University Teknologi Malaysia Faculty of Science Johor Skudai81310 Malaysia Universitas Bali Internasional Informatics Department Denpasar Indonesia

ISBN: (纸本)9798331506490

the COVID-19 pandemic has profoundly impacted global public health, with Indonesia among the most severely af-fected. In response, the Bandung City Government implemented various control measures, including the Mayor's Circular on COVID-19 prevention and enforcing restrictions on community activities, known as PPKM. this study applies the Susceptible-Infected-Recovered (SIR) model to analyze the progression of COVID-19 in Bandung City, specifically during the first and second waves. the SIR model was calibrated using historical case data and incorporated the finite probability of recovered individuals becoming susceptible again, which is critical for generating oscillatory solutions in epidemic modeling. the study focused on determining the best transmission rate for both waves. the first wave, occurring between July 4th and October 22nd, 2021, exhibited an optimal transmission rate of 0.38 (MAE: 0.0424). In contrast, the second wave, spanning February 1st to May 15th, 2022, required a higher transmission rate of 0.54 (MAE: 0.0142), reflecting the increased transmissibility of the Omicron variant. Meanwhile, the recovery rate was calculated based on an average incubation period of 14 days, equivalent to 1/14, approximately 0.0714. the results demonstrate that the SIR model successfully captures the epidemic dynamics in the region, providing insights into the effectiveness of governmental policies and restrictions in controlling the virus. Future studies may explore the inclusion of additional parameters, such as vaccination coverage and mobility patterns, which could enhance the model's predictive accuracy. Moreover, hybrid modeling approaches integrating SIR with machine learning may offer more adaptive solutions to rapidly changing epidemic conditions. © 2024 IEEE.

关键词： COVID-19

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Research and implementation of semantic segmentation algorithm for linear structure of Martian landform 4

Research and implementation of semantic segmentation algorit...

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4th international conference on Advances in Computer Technology, Information science and Communications, CTISC 2022

作者： Xiu, Xiaochen Yan, Pengcheng Liang, Jiarui Tian, Xiaolin Sun, Xiujuan Macau University of Science and Technology School of Computer Science and Engineering Faculty of Innovation Engineering China Macau University of Science and Technology Lunar and Planetary Science Laboratory China Guangdong Wengu Testing and Authentication Co. Ltd Environmental Energy Saving Department Guangzhou China

ISBN: (数字)9781665458726

ISBN: (纸本)9781665458726

In this paper, a process proposal is designed to automatically produce datasets for the surface features of remote sensing data. the article takes Mars linear structure as an example for dataset production, and experiments are conducted with the U-Net structure as the recognition network. the results show that the solution can effectively help to produce datasets with relevant surface features and has good scalability. © 2022 IEEE.

关键词： Semantic Segmentation

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A Comparative Study on Application of Artificial Intelligence for Quality Assurance in Manufacturing 4

A Comparative Study on Application of Artificial Intelligenc...

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4th international conference on Inventive Research in computing Applications, ICIRCA 2022

作者： Arora, Aashish Gupta, Rajeev Haryana Ambala India Department of Computer Science and Engineering Haryana Ambala India

ISBN: (数字)9781665497077

ISBN: (纸本)9781665497077

Increasing demands in industrial processes necessitate early fault detection, efficient production, and quality assurance. In the manufacturing process, a s more sensors, smart devices, and cyber-physical networks are interconnected, more data is created. this data might be used to enhance manufacturing procedures and product quality. Machine learning algorithms may improve quality assurance (QA). But integration of artificial intelligence (AI) and machine learning (ML) into manufacturing system seldom have the skills to obtain this data. this paper describes an automated visual inspection system that ensures optical quality. An automated quality assurance platform for additive manufacturing based on machine learning is described in this paper. this paper also presented a comparative feature analysis of existing AI based quality assurance in different application areas of manufacturing. After complete analysis of these techniques, the paper also explored the current challenges and future research directions. © 2022 IEEE.

关键词： Quality assurance

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