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Classifier Reuse-Based Contrastive Knowledge Distillation 8

Classifier Reuse-Based Contrastive Knowledge Distillation

引用

8th IEEE international conference on Edge computing and Communications, EDGE 2024

作者： Gao, Zhipeng Yang, Shu Yu, Xinlei Mo, Zijia Rui, Lanlan Yang, Yang Beijing University of Posts and Telecommunications State Key Laboratory of Networking and Switching Technology Beijing China Postdoctoral Research Center Industrial and Commercial Bank of China Beijing China

ISBN: (纸本)9798350368499

As a popular method for model lightweighting, knowledge distillation has seen extensive development in recent years. Nevertheless, it heavily relies on labeled data for training, and in the absence of labeled data support, traditional knowledge distillation encounters significant hurdles. therefore, it is crucial to explore the application of knowledge distillation in this field, aiming to improve the performance of lightweight models within unsupervised edge scenarios. We integrate contrastive learning, the currently prevalent self-supervised learning technique, with knowledge distillation to enhance the model's knowledge distillation task through the assessment of similarity between sample pairs. Concurrently, we utilize a projection head to align features between the student and teacher models, employing the Siamese Classifier method to enable the reuse of the pre-trained classifier in the student model. this obviates the need for retraining the classifier and allows the student to acquire more knowledge from the teacher. A series of experimental results showcases that our model exhibits state-of-the-art performance on the benchmark dataset CIFAR-100, particularly when the ResNet 32× 4 serves as the teacher for instructing the ResNet8 × 4, surpassing other methods on average by 3.8%. © 2024 IEEE.

关键词： Contrastive Learning

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the Influence-Maximizing Node Selection Algorithm Based on Local Isolated Centrality in Large-scale networks Implemented by distributed Graph computing 24

The Influence-Maximizing Node Selection Algorithm Based on L...

引用

24th IEEE international conference on High Performance computing and Communications, 8th IEEE international conference on Data Science and Systems, 20th IEEE international conference on Smart City and 8th IEEE international conference on Dependability in Sensor, Cloud and Big Data Systems and Application, HPCC/DSS/SmartCity/DependSys 2022

作者： Chen, Piaoyang Lei, Rong Deng, Mingsen School of Information Guizhou University of Finance and Economics Guiyang China

ISBN: (纸本)9798350319934

Identifying influence-maximizing (IM) nodes is an effective strategy for designing efficient communication networks or contain the spreading of information for rumors and epidemics with limited budgets. With the growing of the sizes of the social networks, finding solutions to the problem of intfuence - maximizing vertices becomes more and more challenging. Tra-ditionally, the number of users finally affected was the focus. However, the information diffusion speed was becoming a bottle-neck of IM problems. In this paper, we proposed a locality-aware vertex selection strategy based on local isolation centrality (LIC), while the information diffusion experiments used the Independent Cascade (IC) model. the computing scheme was implemented by a distributed graph computing framework. the superiority of the LIC algorithm was confirmed by evaluated on three real-world datasets. It was indistinguishable from algorithms such as K-shell, H-index, degree centrality (DC), local centrality (LC), and VoteRank at the diffusion cascade scale. But it showed better superiority in diffusion speed. More importantly, by comparing LIC with the VoteRank algorithm, which was the closest algorithm on diffusion speed to that of LIC, the huge advantage of the LIC algorithm in terms of time cost was found. We believe that the locality-aware LIC algorithm was more suitable for the influence-maximization problem in very large-scale social networks. © 2022 IEEE.

关键词： Bottles

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A Review of Vertical Switching Algorithms for Heterogeneous Wireless Networks 8

A Review of Vertical Switching Algorithms for Heterogeneous ...

引用

8th international conference on Computer and Communication Systems, ICCCS 2023

作者： Zhou, Kexin Bai, Xiangyu Wang, Zhaoran School of Computer Science Inner Mongolia A.R. Key Laboratory of Wireless Networking and Mobile Computing Inner Mongolia University Inner Mongolia Autonomous Region Hohhot China

ISBN: (纸本)9781665456128

It is expected that the next generation wireless network will provide users with excessive mobile wireless services and cover the ubiquitous network at any time. It is urgent to further study the integration and interoperation technology suitable for the heterogeneous wireless communication system covering the whole environment. the heterogeneous network vertical handoff technology is an important basis of multi-network fusion. therefore, a seamless and efficient handoff mechanism is related to the optimal network performance of heterogeneous wireless networks (HWNs);It allows mobile users to switch from one access network to another to find the best connection for the desired service. In this paper, the recent research on vertical handoff algorithms in wireless networks is reviewed and summarized, and the future research direction is prospected. © 2023 IEEE.

关键词： Heterogeneous networks

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An Overview of Intelligent Algorithm-Based Routing in Delay Tolerant Networks 8

An Overview of Intelligent Algorithm-Based Routing in Delay ...

引用

8th international conference on Computer and Communication Systems, ICCCS 2023

作者： Yao, Lei Bai, Xiangyu Wang, Zhaoran College of Computer Inner Mongolia Key Laboratory of Wireless Networking and Mobile Computing Inner Mongolia University Hohhot China

ISBN: (纸本)9781665456128

Delay tolerant network (DTN) is a new paradigm with the development of wireless technology and mobile Ad-hoc network (MANET). Unlike the stable end-to-end connection in the traditional network, the storage - carry - forward mode is adopted in DTN. Routing optimization is the most basic problem in delay tolerant network. It assumes the heavy responsibility of data transmission, and even determines the performance of the whole network. In recent years, with the development of artificial intelligence, there have been many researches on the use of AI to optimize the routing in DTN. However, the relevant literature is insufficient at present. In this paper, we first introduce the methods related to artificial intelligence, and then summarize and discuss the existing literature from five parts: machine learning classifier, prediction task using machine learning, biological heuristic method, reinforcement learning and artificial intelligence assistance. © 2023 IEEE.

关键词： Heuristic methods

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ReSLB: Load Balanced Workflow for distributed Deep Learning Mass Spectrometry Database 24

ReSLB: Load Balanced Workflow for Distributed Deep Learning ...

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作者： Mocheng, Li Yang, Liu Yang, Ou Zhiguang, Chen Nong, Xiao Tao, Chen College of Computer National University of Defense Technology Institute for Quantum Information State Key Laboratory of High Performance Computing Changsha China College of Computer National University of Defense Technology Changsha China School of Computer Sun Yat-sen University Guangzhou China Beijing China

ISBN: (纸本)9798350319934

the proteomics data analysis pipeline based on the shotgun method requires efficient data processing methods. the parallel algorithm of mass spectrometry database search faces the problems of rapidly expanding database size but low scalability. the heterogeneous database search algorithm based on deep learning is an effective way to solve this problem. Still, the deep learning-based distributed parallel database search algorithm is lacking. this paper analyzes the database searching computational load using a neural network and designs ReSLB, a workflow for the restricted search of mass spectrometry data based on GPU cluster and neural network scoring algorithm. this work aims to ensure the high scalability of future deep learning-based mass spectrometry distributed databases. In the performance estimation of 256 GPUs, the load imbalance of less than 30% and the parallel efficiency of 60% are achieved. Compared with state-of-the-art, the time cost is reduced by 75%, and the parallel efficiency from 1 to 256 GPUs is 3.6x higher than that. © 2022 IEEE.

关键词： Mass spectrometry

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Driver Drowsiness Detection Using Machine Learning Algorithm 8

Driver Drowsiness Detection Using Machine Learning Algorithm

引用

8th international conference on Advanced computing and Communication Systems, ICACCS 2022

作者： Prasath, N. Sreemathy, J. Vigneshwaran, P. Srm Institute of Science and Technology Department of Networking and Communications Tamilnadu Chennai India Sri Eshwar College of Engineering Department of Computer Science Engineering Tamilnadu Coimbatore India

ISBN: (纸本)9781665408165

It is just a short time until self-driving vehicles become omnipresent;be that as it may, human driving management will stay a need for quite a long time. Driver Drowsiness is one of the significant reasons of roadways accidents these days. Hence fatigue and drowsiness detection play a major role in preventing the road accidents. Every year, because of this there is an increase in the number of deaths and injuries globally. Recently, in this decade, many images processing-based approaches were created and used to detect driver's drowsiness status. To minimize the number of accidents, a method is proposed in this paper. the algorithm focuses on the eye closure and yawning ratios. the driver is alarmed, if he/she is feeling sleepy. © 2022 IEEE.

关键词： Aspect ratio

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Feature Based Comparative Analysis of Traditional Intrusion Detection System and Software-Defined networking Based Intrusion Detection System 8

Feature Based Comparative Analysis of Traditional Intrusion ...

引用

8th IEEE international conference on Engineering Technologies and Applied Sciences, ICETAS 2023

作者： Mahar, Iftekhar Ahmed Libing, Wu Rahu, Ghulam Ali Maher, Zulfikar Ahmed Koondhar, Muhammad Yaqoob School of Computer Science Wuhan University China Wuhan China Information Technology Centre Sindh Agriculture University Tandojam Tandojam Pakistan

ISBN: (纸本)9798350327090

Intrusion Detection Systems (IDS) play a crucial role in a comprehensive security framework for an organization by detection and response to security incidents, encompassing both network-based and host-based threats. the selection of IDS components and its configuration depends upon the security requirements of the company and the prevailing threat landscape they encounter. the conventional Intrusion Detection System (IDS) and the Software-Defined networking (SDN) IDS share the common objective of identifying and mitigating network security breaches. However, they diverge notably in terms of their architectural design and operational methodology. this paper presents a comparative analysis between a traditional Intrusion Detection System (IDS) and a Software-Defined networking (SDN) based IDS. It aims to offer a comprehensive examination of both IDS systems, enabling organizations to make informed decisions considering their unique security requirements, network architecture, and operational limitations.. © 2023 IEEE.

关键词： Software defined networking

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Social Media's Impact on Business and Society: A Study 8

Social Media's Impact on Business and Society: A Study

引用

8th international conference on Advanced computing and Communication Systems, ICACCS 2022

作者： Minocha, Lalita Jain, Praveen Singh, Amit Pandey, Pradeep Sharda School of Media Film and Entertainment Sharda University Knowledge Park Iii U.P. Greater Noida India

ISBN: (纸本)9781665408165

Virtually every area of our lives has been profoundly influenced by technology, and Internet is quickly becoming one of the primary platforms for youngsters seeking to socialize. Because of its insatiable ability to get the information sought in a fraction of seconds, Internet has emerged as a necessity for accessing information for teenagers (and people of different ages). As a result, it has become a prerequisite educational tool that parents are finding difficult to refute to their children. Additionally, there has been a rise of social media usage, which has made it possible not only to voice one's thoughts and views but also, to connect with like-minded individuals all over the world. Social media platforms can be beneficial or detrimental, depending on the user and his or her intentions, as well as on the members' alertness and participation. © 2022 IEEE.

关键词： Social networking (online)

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Role of Social Media in Engaging Students: Perspectives from Higher Education 8

Role of Social Media in Engaging Students: Perspectives from...

引用

8th international conference on Advanced computing and Communication Systems, ICACCS 2022

作者： Sharma, Aarti Kaushal, Sanjay Fulzele, Roopali Kumari, Tanu Sharda University India

ISBN: (纸本)9781665408165

Use of social media is increasingly playing a vital role in every field. Social media started with interaction and communication and now has acquired a wider scope. It is playing an important role in every field and people are using it because of its advantages such as quick response, wider reach, low cost, and diverse methods of sharing. Social media is playing an important role also in the field of information technologies, businesses and planning, as well as education. However, this paper is focused specifically on social media's role in the field of education. Social media helps improve the quality of education due to its availability of a variety of methods to teaching and learning. Social media provides learners with the opportunities to learn according to their interests, consequently, it is seen that social media is being implemented by schools [13] and colleges for daily learning activities. © 2022 IEEE.

关键词： Social networking (online)

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Resource Allocation in Cloud computing Using Genetic Algorithm and Neural Network 8

Resource Allocation in Cloud Computing Using Genetic Algorit...

引用

8th IEEE international conference on Smart Cloud, SmartCloud 2023

作者： Manavi, Mahdi Zhang, Yunpeng Chen, Guoning Department of Computer Science University of Houston Houston United States Department of Information Science Technology University of Houston Houston United States

ISBN: (纸本)9798350313505

Cloud computing is one of the most used distributed systems for data processing and data storage. Due to the continuous increase in the size of the data processed by cloud computing, scheduling multiple tasks to maintain efficiency while reducing idle becomes more and more challenging. Efficient cloud-based scheduling is also highly sought by modern transportation systems to improve their security. In this paper, we propose a hybrid algorithm that leverages genetic algorithms and neural networks to improve scheduling. Our method classifies tasks with the Neural Network Task Classification (N2TC) and sends the selected tasks to the Genetic Algorithm Task Assignment (GATA) to allocate resources. It is fairness aware to prevent starvation and considers the execution time, response time, cost, and system efficiency. Evaluations show that our approach outperforms the state-of-the-art method by 3.2% at execution time, 13.3% in costs, and 12.1% at response time. ©2023 IEEE.

关键词： Cloud computing

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