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Scenarios analysis and performance assessment of blockchain integrated in 6G scenarios

science China(Information sciences) 2024年第7期67卷 5-26页

作者： Bo LI Guanjie CHENG Honghao GAO Xueqiang YAN Shuiguang DENG college of computer science and technology Zhejiang University college of computer science and technology Shanghai University 2012 Lab Huawei Technologies Co. Ltd.

Emerging applications such as smart city infrastructures and virtual reality landscapes are setting rigorous benchmarks for 6G mobile networks, requiring elevated levels of confidentiality, integrity, nonrepudiation, authentication, and stringent access controls. Blockchain technology is heralded as a transformative enabler for meeting 6G standards, owing to its intrinsic attributes. However, a gap exists in the holistic investigation of blockchain's applicability in 6G realms, particularly addressing the “whether”, “when”, and“how” of its deployment. Present research trails in developing robust methodologies to gauge blockchain's efficacy within 6G use cases. Addressing this, our study introduces a novel confluence of blockchain with 6G networks, where data resides in distributed Hash tables(DHTs) while their hashes are secured in distributed ledger technology(DLT), harnessing blockchain's core strengths-immutability, traceability, and fortified security. We delineate seven specific 6G use cases poised for enhancement through blockchain integration,and scrutinize the rationale, nature, and timing of this convergence. Furthermore, we devise a comprehensive methodology for assessing blockchain's performance metrics and scalability in 6G environments. Our extensive experimental analyses evaluate the synergistic performance of this integration, revealing that the Quorum blockchain satisfactorily supports 80% of 6G scenarios. The findings suggest that, with appropriate configurations, consortium blockchains are well-equipped to fulfill the demanding performance and scalability requisites of 6G networks.

关键词： blockchain distributed ledger technology (DLT) 6G performance assessment 6G scenarios analysis transaction arrival rate

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A Weakly-Supervised Crowd Density Estimation Method Based on Two-Stage Linear Feature Calibration

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IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 965-981页

作者： Yong-Chao Li Rui-Sheng Jia Ying-Xiang Hu Hong-Mei Sun the college of computer science and Engineering Shandong University of Science and TechnologyQingdao 266590 the Faculty of Information science and Engineering Ocean University of ChinaQingdao 266000China the college of computer science and Engineering Shandong University of Science and TechnologyQingdao 266590China the college of computer science and Engineering Nanjing University of Science and TechnologyNanjing 210000China

In a crowd density estimation dataset,the annotation of crowd locations is an extremely laborious task,and they are not taken into the evaluation metrics.In this paper,we aim to reduce the annotation cost of crowd datasets,and propose a crowd density estimation method based on weakly-supervised learning,in the absence of crowd position supervision information,which directly reduces the number of crowds by using the number of pedestrians in the image as the supervised information.For this purpose,we design a new training method,which exploits the correlation between global and local image features by incremental learning to train the network.Specifically,we design a parent-child network(PC-Net)focusing on the global and local image respectively,and propose a linear feature calibration structure to train the PC-Net simultaneously,and the child network learns feature transfer factors and feature bias weights,and uses the transfer factors and bias weights to linearly feature calibrate the features extracted from the Parent network,to improve the convergence of the network by using local features hidden in the crowd images.In addition,we use the pyramid vision transformer as the backbone of the PC-Net to extract crowd features at different levels,and design a global-local feature loss function(L2).We combine it with a crowd counting loss(LC)to enhance the sensitivity of the network to crowd features during the training process,which effectively improves the accuracy of crowd density estimation.The experimental results show that the PC-Net significantly reduces the gap between fullysupervised and weakly-supervised crowd density estimation,and outperforms the comparison methods on five datasets of Shanghai Tech Part A,ShanghaiTech Part B,UCF_CC_50,UCF_QNRF and JHU-CROWD++.

关键词： Crowd density estimation linear feature calibration vision transformer weakly-supervision learning

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IQABC-Based Hybrid Deployment Algorithm for Mobile Robotic Agents Providing Network Coverage

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Tsinghua science and technology 2024年第2期29卷 589-604页

作者： Shuang Xu Xiaojie Liu Dengao Li Jumin Zhao college of computer science and technology(college of Data science) Taiyuan University of TechnologyTaiyuan 030024China Pengcheng Laboratory Shenzhen 518055China college of Information and computer Taiyuan University of TechnologyTaiyuan 030024China

Working as aerial base stations,mobile robotic agents can be formed as a wireless robotic network to provide network services for on-ground mobile devices in a target area.Herein,a challenging issue is how to deploy these mobile robotic agents to provide network services with good quality for more users,while considering the mobility of on-ground devices.In this paper,to solve this issue,we decouple the coverage problem into the vertical dimension and the horizontal dimension without any loss of optimization and introduce the network coverage model with maximum coverage range.Then,we propose a hybrid deployment algorithm based on the improved quick artificial bee colony.The algorithm is composed of a centralized deployment algorithm and a distributed one.The proposed deployment algorithm deploy a given number of mobile robotic agents to provide network services for the on-ground devices that are independent and identically distributed.Simulation results have demonstrated that the proposed algorithm deploys agents appropriately to cover more ground area and provide better coverage uniformity.

关键词： wireless robotic networks network coverage deployment algorithm improved quick artificial bee colony

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A Video Captioning Method by Semantic Topic-Guided Generation

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computers, Materials & Continua 2024年第1期78卷 1071-1093页

作者： Ou Ye Xinli Wei Zhenhua Yu Yan Fu Ying Yang college of computer science and technology Xi’an University of Science and TechnologyXi’an710054China

In the video captioning methods based on an encoder-decoder,limited visual features are extracted by an encoder,and a natural sentence of the video content is generated using a decoder.However,this kind ofmethod is dependent on a single video input source and few visual labels,and there is a problem with semantic alignment between video contents and generated natural sentences,which are not suitable for accurately comprehending and describing the video contents.To address this issue,this paper proposes a video captioning method by semantic topic-guided generation.First,a 3D convolutional neural network is utilized to extract the spatiotemporal features of videos during the encoding.Then,the semantic topics of video data are extracted using the visual labels retrieved from similar video data.In the decoding,a decoder is constructed by combining a novel Enhance-TopK sampling algorithm with a Generative Pre-trained Transformer-2 deep neural network,which decreases the influence of“deviation”in the semantic mapping process between videos and texts by jointly decoding a baseline and semantic topics of video contents.During this process,the designed Enhance-TopK sampling algorithm can alleviate a long-tail problem by dynamically adjusting the probability distribution of the predicted words.Finally,the experiments are conducted on two publicly used Microsoft Research Video Description andMicrosoft Research-Video to Text datasets.The experimental results demonstrate that the proposed method outperforms several state-of-art approaches.Specifically,the performance indicators Bilingual Evaluation Understudy,Metric for Evaluation of Translation with Explicit Ordering,Recall Oriented Understudy for Gisting Evaluation-longest common subsequence,and Consensus-based Image Description Evaluation of the proposed method are improved by 1.2%,0.1%,0.3%,and 2.4% on the Microsoft Research Video Description dataset,and 0.1%,1.0%,0.1%,and 2.8% on the Microsoft Research-Video to Text dataset,respectively,compared with the existing video c

关键词： Video captioning encoder-decoder semantic topic jointly decoding Enhance-TopK sampling

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4D-MAP:Multipath Adaptive Packet Scheduling for Live Streaming over QUIC

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Journal of computer science & technology 2024年第1期39卷 159-176页

作者：宋丛溪韩彪苏金树 college of computer science and technology National University of Defense TechnologyChangsha 410073China

In recent years,live streaming has become a popular application,which uses TCP as its primary transport protocol.Quick UDP Internet Connections(QUIC)protocol opens up new opportunities for live streaming.However,how to leverage QUIC to transmit live videos has not been studied yet.This paper first investigates the achievable quality of experience(QoE)of streaming live videos over TCP,QUIC,and their multipath extensions Multipath TCP(MPTCP)and Multipath QUIC(MPQUIC).We observe that MPQUIC achieves the best performance with bandwidth aggregation and transmission reliability.However,network fluctuations may cause heterogeneous paths,high path loss,and band-width degradation,resulting in significant QoE deterioration.Motivated by the above observations,we investigate the multipath packet scheduling problem in live streaming and design 4D-MAP,a multipath adaptive packet scheduling scheme over QUIC.Specifically,a linear upper confidence bound(LinUCB)-based online learning algorithm,along with four novel scheduling mechanisms,i.e.,Dispatch,Duplicate,Discard,and Decompensate,is proposed to conquer the above problems.4D-MAP has been evaluated in both controlled emulation and real-world networks to make comparison with the state-of-the-art multipath transmission schemes.Experimental results reveal that 4D-MAP outperforms others in terms of improving the QoE of live streaming.

关键词： multipath transmission live streaming Quick UDP Internet Connections(QUIC) quality of experience(QoE) packet scheduling

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Multi-exit self-distillation with appropriate teachers

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Frontiers of Information technology & Electronic Engineering 2024年第4期25卷 585-599页

作者： Wujie SUN Defang CHEN Can WANG Deshi YE Yan FENG Chun CHEN college of computer science and technology Zhejiang UniversityHangzhou 310000China

Multi-exit architecture allows early-stop inference to reduce computational cost,which can be used in resource-constrained circumstances.Recent works combine the multi-exit architecture with self-distillation to simultaneously achieve high efficiency and decent performance at different network depths.However,existing methods mainly transfer knowledge from deep exits or a single ensemble to guide all exits,without considering that inappropriate learning gaps between students and teachers may degrade the model performance,especially in shallow exits.To address this issue,we propose Multi-exit self-distillation with Appropriate TEachers(MATE)to provide diverse and appropriate teacher knowledge for each exit.In MATE,multiple ensemble teachers are obtained from all exits with different trainable weights.Each exit subsequently receives knowledge from all teachers,while focusing mainly on its primary teacher to keep an appropriate gap for efficient knowledge transfer.In this way,MATE achieves diversity in knowledge distillation while ensuring learning efficiency.Experimental results on CIFAR-100,TinyImageNet,and three fine-grained datasets demonstrate that MATE consistently outperforms state-of-the-art multi-exit self-distillation methods with various network architectures.

关键词： Multi-exit architecture Knowledge distillation Learning gap

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APF-GAN:Exploring asymmetric pre-training and fine-tuning strategy for conditional generative adversarial network

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Computational Visual Media 2024年第1期10卷 187-192页

作者： Yuxuan Li Lingfeng Yang Xiang Li college of computer science Nankai UniversityTianjinChina School of computer science and Engineering Nanjing University of Science and TechnologyNanjingChina

The use of generative adversarial network(GAN)-based models for the conditional generation of image semantic segmentation has shown promising results in recent years.However,there are still some limitations,including limited diversity of image style,distortion of detailed texture,unbalanced color tone,and lengthy training time.To address these issues,we propose an asymmetric pre-training and fine-tuning(APF)-GAN model.

关键词： tuning network asymmetric

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ChatGPT is a Remarkable Tool—For Experts

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Data Intelligence 2024年第1期6卷 240-296页

作者： Amos Azaria Rina Azoulay Shulamit Reches School of computer science Ariel UniversityIsrael Department of computer science Jerusalem College of TechnologyIsrael Department of Mathematics Jerusalem College of TechnologyIsrael

This paper investigates the capabilities of ChatGPT as an automated assistant in diverse domains,including scientific writing,mathematics,education,programming,and healthcare.We explore the potential of ChatGPT to enhance productivity,streamline problem-solving processes,and improve writing style.Furthermore,we highlight the potential risks associated with excessive reliance on ChatGPT in these fields.These limitations encompass factors like incorrect and fictitious responses,inaccuracies in code,limited logical reasoning abilities,overconfidence,and critical ethical concerns of copyright and privacy violation.We outline areas and objectives where ChatGPT proves beneficial,applications where it should be used judiciously,and scenarios where its reliability may be limited.In light of observed limitations,and given that the tool's fundamental errors may pose a special challenge for non-experts,ChatGPT should be used with a strategic methodology.By drawing from comprehensive experimental studies,we offer methods and flowcharts for effectively using ChatGPT.Our recommendations emphasize iterative interaction with ChatGPT and independent verification of its outputs.Considering the importance of utilizing ChatGPT judiciously and with expertise,we recommend its usage for experts who are well-versed in the respective domains.

关键词： limitations utilizing Tool

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Memory-enhanced text style transfer with dynamic style learning and calibration

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science China(Information sciences) 2024年第4期67卷 181-196页

作者： Fuqiang LIN Yiping SONG Zhiliang TIAN Wangqun CHEN Diwen DONG Bo LIU college of computer science and technology National University of Defense Technology Department of computer science and Engineering The Hong Kong University of Science and Technology Strategic Assessments and Consultation Institute Academy of Military Sciences

Text style transfer aims to rephrase a sentence to match the desired style while retaining the original content. As a controllable text generation task, mainstream approaches use content-independent style embedding as control variables to guide stylistic generation. Nonetheless, stylistic properties are contextsensitive even under the same style. For example, “delicious” and “helpful” convey positive sentiments,although they are more likely to describe food and people, respectively. Therefore, desired style signals must vary with the content. To this end, we propose a memory-enhanced transfer method, which learns fine-grained style representation concerning content to assist transfer. Rather than employing static style embedding or latent variables, our method abstracts linguistic characteristics from training corpora and memorizes subdivided content with the corresponding style representations. The style signal is dynamically retrieved from memory using the content as a query, providing a more expressive and flexible latent style space. To address the imbalance between quantity and quality in different content, we further introduce a calibration method to augment memory construction by modeling the relationship between candidate styles.Experimental results obtained using three benchmark datasets confirm the superior performance of our model compared to competitive approaches. The evaluation metrics and case study also indicate that our model can generate diverse stylistic phrases matching context.

关键词： style transfer memory-enhanced method text generation deep learning text representation

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The Effect of Key Nodes on theMalware Dynamics in the Industrial Control Network

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computers, Materials & Continua 2024年第4期79卷 329-349页

作者： Qiang Fu JunWang Changfu Si Jiawei Liu college of computer science and technology Shenyang University of Chemical TechnologyShenyang110142China college of computer science and Engineering Northeastern UniversityShenyang110169China

As industrialization and informatization becomemore deeply intertwined,industrial control networks have entered an era of intelligence.The connection between industrial control networks and the external internet is becoming increasingly close,which leads to frequent security accidents.This paper proposes a model for the industrial control network.It includes a malware containment strategy that integrates intrusion detection,quarantine,and monitoring.Basedonthismodel,the role of keynodes in the spreadofmalware is studied,a comparisonexperiment is conducted to validate the impact of the containment strategy.In addition,the dynamic behavior of the model is analyzed,the basic reproduction number is computed,and the disease-free and endemic equilibrium of the model is also obtained by the basic reproduction number.Moreover,through simulation experiments,the effectiveness of the containment strategy is validated,the influence of the relevant parameters is analyzed,and the containment strategy is optimized.In otherwords,selective immunity to key nodes can effectively suppress the spread ofmalware andmaintain the stability of industrial control systems.The earlier the immunization of key nodes,the better.Once the time exceeds the threshold,immunizing key nodes is almost ineffective.The analysis provides a better way to contain the malware in the industrial control network.

关键词： Key nodes dynamic model industrial control network simulation

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