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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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Introduction to the Special Issue on“Innovation and Application of Intelligent Processing of Data,Information and Knowledge in E-Commerce”

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Computer Modeling in Engineering & Sciences 2022年第4期131卷 19-21页

作者： honghao gao Jung Yoon Kim Yuyu Yin School of Computer Engineering and Science Shanghai UniversityShanghaiChina Department of Game Media College of Future IndustryGachon UniversitySeongnam-si13120Gyeonggi-doSouth Korea School of Computer Hangzhou Dianzi UniversityHangzhouChina

In the context of E-Commerce eco-system,there are hundreds of millions of consumers,thousands of businesses and shops,and hundreds of delivery people.Large E-Commerce businesses such as Alibaba Group need to support a large number of applications and business modules,and cater for hundreds of business requirements and independent changes on a daily basis.The intersection of these information technologies and business models provides ample research opportunities in intelligent processing of data,information and knowledge.In this special issue,we have accepted 7 papers from open calls and invitations.A summary of these papers is outlined below.

关键词： hundreds intersection invitation

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Towards machine-learning-driven effective mashup recommendations from big data in mobile networks and the Internet-of-Things

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Digital Communications and Networks 2023年第1期9卷 138-145页

作者： Yueshen Xu Zhiying Wang honghao gao Zhiping Jiang Yuyu Yin Rui Li School of Computer Science and Technology Xidian UniversityXi'an710126China School of Computer Engineering and Science Shanghai UniversityShanghai200444China School of Computer Science and Technology Hangzhou Dianzi UniversityHangzhou310018China

A large number of Web APIs have been released as services in mobile communications,but the service provided by a single Web API is usually limited.To enrich the services in mobile communications,developers have combined Web APIs and developed a new service,which is known as a mashup.The emergence of mashups greatly increases the number of services in mobile communications,especially in mobile networks and the Internet-of-Things(IoT),and has encouraged companies and individuals to develop even more mashups,which has led to the dramatic increase in the number of mashups.Such a trend brings with it big data,such as the massive text data from the mashups themselves and continually-generated usage data.Thus,the question of how to determine the most suitable mashups from big data has become a challenging problem.In this paper,we propose a mashup recommendation framework from big data in mobile networks and the IoT.The proposed framework is driven by machine learning techniques,including neural embedding,clustering,and matrix factorization.We employ neural embedding to learn the distributed representation of mashups and propose to use cluster analysis to learn the relationship among the mashups.We also develop a novel Joint Matrix Factorization(JMF)model to complete the mashup recommendation task,where we design a new objective function and an optimization algorithm.We then crawl through a real-world large mashup dataset and perform experiments.The experimental results demonstrate that our framework achieves high accuracy in mashup recommendation and performs better than all compared baselines.

关键词： Mashup recommendation Big data Machine learning Mobile networks Internet-of-Things

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BCI+VR Rehabilitation Design of Closed-Loop Motor Imagery Based on the Degree of Drug Addiction

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China Communications 2022年第2期19卷 62-72页

作者： Xuelin Gu Banghua Yang Shouwei gao honghao gao Linfeng Yan Ding Xu Wen Wang School of Mechanical and Electrical Engineering and Automation Shanghai UniversityShanghai 200444China School of Computer Engineering and Science Shanghai UniversityShanghai 200444China Department of Radiology&Functional and Molecular Imaging Key Lab of Shaanxi Province Tangdu HospitalFourth Military Medical UniversityXi’anShaanxi 710038China Shanghai Drug Rehabilitation Administration Bureau Shanghai 200080China

After abusing drugs for long,drug users will experience deteriorated self-control cognitive ability,and poor emotional regulation.This paper designs a closed-loop virtual-reality(VR),motorimagery(MI)rehabilitation training system based on brain-computer interface(BCI)(MI-BCI+VR),aiming to enhance the self-control,cognition,and emotional regulation of drug addicts via personalized rehabilitation schemes.This paper is composed of two parts.In the first part,data of 45 drug addicts(mild:15;moderate:15;and severe:15)is tested with electroencephalogram(EEG)and near-infrared spectroscopy(NIRS)equipment(EEG-NIRS)under the dual-mode,synchronous signal collection paradigm.Using these data sets,a dual-modal signal convolutional neural network(CNN)algorithm is then designed based on decision fusion to detect and classify the addiction degree.In the second part,the MIBCI+VR rehabilitation system is designed,optimizing the Filter Bank Common Spatial Pattern(FBCSP)algorithm used in MI,and realizing MI-EEG intention recognition.Eight VR rehabilitation scenes are devised,achieving the communication between MI-BCI and VR scene models.Ten subjects are selected to test the rehabilitation system offline and online,and the test accuracy verifies the feasibility of the system.In future,it is suggested to develop personalized rehabilitation programs and treatment cycles based on the addiction degree.

关键词： drug addiction degree brain-computer interface,motor imagery virtual reality drug addiction rehabilitation

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Guest Editorial

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Digital Communications and Networks 2022年第6期8卷 865-867页

作者： honghao gao Ramon J.Duran Barroso Zhiyuan Tan School of Computer Engineering and Science Shanghai UniversityChina Universidad de Valladolid Spain School of Computing Edinburgh Napier UniversityUK

Special issue on Collaborative computing to information fusion for5GIoTsocialdata With the development of 5G IoT technology,a large amount of social data is generated every day.How to handle these social data has become a critical problem.Information Fusion with Collaborative Computing aims to help academia and industry understand data,information and resources.Thus,in this special issue,we selected the following highquality papers from open submissions.A summary is outlined below.

关键词： handle problem IoT

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Frontiers of Computer Science 2020年第5期14卷 89-97页

作者： Fangfang Liu Yan Shen Tienan Zhang honghao gao School of Computer Engineering and Science Shanghai UniversityShanghai200444China Computing Center Shanghai UniversityShanghai200444China

Knowledge bases(KBs)are far from complete,necessitating a demand for KB completion.Among various methods,embedding has received increasing attention in recent years.PTransE,an important approach using embedding method in KB completion,considers multiple-step relation paths based on TransE,but ignores the association between entity and their related entities with the same direct relationships.In this paper,we propose an approach called EP-TransE,which considers this kind of association.As a matter of fact,the dissimilarity of these related entities should be taken into consideration and it should not exceed a certain threshold.EPTransE adjusts the embedding vector of an entity by comparing it with its related entities which are connected by the same direct relationship.EPTransE further makes the euclidean distance between them less than a certain threshold.Therefore,the embedding vectors of entities are able to contain rich semantic information,which is valuable for KB completion.In experiments,we evaluated our approach on two tasks,including entity prediction and relation prediction.Experimental results show that our idea of considering the dissimilarity of related entities with the same direct relationships is effective.

关键词： KB completion related entity embedding representation relation path translation operation

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人原代单核细胞经地塞米松刺激后的吞噬功能及转录组变化研究

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解放军医学院学报 2024年第3期45卷 276-282页

作者：程莉曹腾宇刘蓓高泓浩袁顺宗于洋黄文荣解放军医学院北京100853 解放军总医院第五医学中心血液病医学部北京100071 解放军总医院第一医学中心输血医学科北京100853

背景噬血淋巴组织细胞增多症(hemophagocytic lymphohistiocytosis,HLH)是由于多种原因导致的过度的全身性炎症反应和器官功能障碍,高剂量的地塞米松常用于抑制炎症,血清可溶性VSIG4(sVSIG4)可作为评估巨噬细胞活化的标志物用于诊断HLH... 详细信息

背景噬血淋巴组织细胞增多症(hemophagocytic lymphohistiocytosis,HLH)是由于多种原因导致的过度的全身性炎症反应和器官功能障碍,高剂量的地塞米松常用于抑制炎症,血清可溶性VSIG4(sVSIG4)可作为评估巨噬细胞活化的标志物用于诊断HLH。目的探究地塞米松刺激人原代单核细胞高表达VSIG4后的吞噬功能及基因转录表达变化,并筛选关键表达基因和通路。方法体外分离人外周血单个核细胞,使用磁珠分选法阳选出CD14^(+)单核细胞,加入地塞米松刺激,使用qPCR、流式细胞术和Western blot分别在mRNA和蛋白水平上检测VSIG4的表达,并用Western blot检测细胞培养上清中sVSIG4的表达,在地塞米松刺激VSIG4表达的同时检测单核细胞吞噬功能;利用RNA-seq对地塞米松刺激前后的人原代单核细胞差异基因进行测序,并进行KEGG通路富集和蛋白质互作分析,通过节点分析找到hub基因和关键信号通路。结果体外地塞米松刺激单核细胞在mRNA和蛋白水平促进VSIG4表达上调(P<0.01),具有剂量依赖性和时间依赖性;地塞米松刺激的单核细胞过表达VSIG4会发生胞外段剪切生成sVSIG4;地塞米松刺激的VSIG4^(+)单核细胞吞噬作用增强(P<0.01)。RNA-seq差异分析中,共有491个差异表达基因,其中上调159个,下调332个;KEGG通路富集显示差异基因主要集中在EB病毒感染、新冠病毒感染、补体和凝血级联反应、NOD样受体信号通路、嘧啶代谢、C型凝集素受体信号通路、吞噬小体、金黄色葡萄球菌感染、Ⅰ型糖尿病、RIG-Ⅰ样受体信号通路、Toll样受体信号通路等信号通路(P<0.05);从PPI网络确定了20个hub基因。结论体外地塞米松刺激人原代单核细胞可以促进VSIG4表达上调,同时生成sVSIG4,VSIG4^(+)单核细胞可能具有更强的吞噬功能。转录组分析提示部分炎症相关基因和信号通路可能与VSIG4的表达调控和噬血淋巴组织细胞增多症的发病机制有关。

关键词：地塞米松 VSIG4 单核细胞转录组测序吞噬

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张新之《红楼梦》评点品第术语考论

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红楼梦学刊 2023年第1期 81-97页

作者：高红豪上海第二工业大学外语与文化传播学院 201209

将“神品”“叙事能品”等品第术语运用于小说的文法批评,是张新之《红楼梦》评点的主要特色与理论贡献。这些品第术语常以文法加品第的形式组合存在,主要受明代经史评点影响。张新之在叙事与写人两个方面分别赋予品第以不同内涵,叙事... 详细信息

将“神品”“叙事能品”等品第术语运用于小说的文法批评,是张新之《红楼梦》评点的主要特色与理论贡献。这些品第术语常以文法加品第的形式组合存在,主要受明代经史评点影响。张新之在叙事与写人两个方面分别赋予品第以不同内涵,叙事上追求技巧与微言大义,写人上区分个性与逼真的艺术效果,从而体现了张新之的“红楼观”。张新之的理论贡献体现在品第术语的系统性运用、价值序列的构建与批评视角的拓展。通过对张新之品第批评话语的梳理考辨,既可以加深我们对《红楼梦》艺术特性的认识,也有助于我们建构具有本土化特色的中国古代小说理论话语体系。

关键词：张新之品第术语文法评点经史评点

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基于超级账本的集群联邦优化模型

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计算机工程 2023年第1期49卷 22-30页

作者：李尤慧子俞海涛殷昱煜高洪皓杭州电子科技大学计算机学院杭州310018 上海大学计算机工程与科学学院上海200444 韩国嘉泉大学计算机工程系城南461701

联邦学习作为分布式机器学习框架,在数据不离开本地的情况下,通过共享模型参数达到协作训练的目标,一定程度上解决了隐私保护问题,但其存在中心参数服务器无法应对单点故障、潜在恶意客户端梯度攻击、客户端数据偏态分布导致训练性能低... 详细信息

联邦学习作为分布式机器学习框架,在数据不离开本地的情况下,通过共享模型参数达到协作训练的目标,一定程度上解决了隐私保护问题,但其存在中心参数服务器无法应对单点故障、潜在恶意客户端梯度攻击、客户端数据偏态分布导致训练性能低下等问题。将去中心化的区块链技术与联邦学习相结合,提出基于超级账本的集群联邦优化模型。以超级账本作为分布式训练的架构基础,客户端初始化后在本地训练向超级账本传输模型参数及分布信息,通过聚类优化联邦学习模型在客户端数据非独立同分布下的训练表现。在此基础上,随机选举客户端成为领导者,由领导者代替中央服务器的功能,领导者根据分布相似度和余弦相似度聚类并下载模型参数聚合,最后客户端获取聚合模型继续迭代训练。以EMNIST数据集为例,数据非独立同分布情况下该模型平均准确率为79.26%,较FedAvg提高17.26%,在保证准确率的前提下,较集群联邦学习训练至收敛的通信轮次减少36.3%。

关键词：区块链超级账本联邦学习隐私保护智能合约

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Prevalence of bacteria, fungi, and virus coinfections with SARS-CoV-2 Omicron variant among patients with severe COVID-19 in Guangzhou, China, winter 2022

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Biosafety and Health 2024年第2期6卷 92-97页

作者： Qinghong Fan Mengling Jiang Jun Zhang Guofang Tang Ming gao Yingfen Wen Xizi Deng Jun Dai honghao Lai Peng Qian Yaqing Lin Ruiying He Liya Li Yueping Li Zhengtu Li Xuesong Liu Yimin Li Na Yu Yun Lan Fengyu Hu Feng Li Institute of Infectious Diseases Guangzhou Eighth People's HospitalGuangzhou Medical UniversityGuangzhou 510440China State Key Laboratory of Respiratory Disease National Clinical Research Center for Respiratory DiseaseGuangzhou Institute of Respiratory Healththe First Affiliated Hospital of GuangzhouMedicalUniversityGuangzhou510120China Guangzhou Laboratory Guangzhou 510700China

The status of coinfection during the national outbreak of severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)Omicron BA.5.2 or BF.7 in China in the winter of 2022,which is suspected to contribute substantially to the overloaded severe cases,needs to be investigated.We analyzed the coinfection status of 385 severe patients infected with the Omicron variant in Guangzhou using metagenomic sequencing.We found that 317(82.3%)patients were coinfected with at least one additional pathogen(s),including bacteria(58.7%),fungi(27.1%)and viruses(73.5%).Pseudomonas aeruginosa(P.aeruginosa)(24.2%),Staphylococcus aureus(S.aureus)(14.0%),andKlebsiella pneumoniae(K.pneumonia)(13.4%)ranked as the top three coinfected bacteria.Aspergillus fumigatus(A.fumigatus)(39.5%),Pneumocystis jirovecii(P.jirovecii)(24.4%)andCanidia albicans(C.albicans)(22.1%)were the top three coinfected fungi.Epstein-Barr virus(EBV)(63.1%),Human herpesvirus 7(HHV-7)(34.8%),and Herpes simplex virus 1(HSV-1)(32.6%)were the top three coinfected viruses.Of note,the detection of multiple coinfections of potential pathogenic bacteria,fungi,and viruses,despite lacking consistent patterns,highlighted a complicated synergistic contribution to disease severity.Our study presents the most comprehensive spectrum of bacterial,fungal,and viral coinfections in Omicron-associated severe coronavirus disease 2019(COVID-19),implying that the coinfection of conditional pathogens might synergistically deteriorate the Omicron infection outcomes.

关键词： SARS-CoV-2 Omicron BA.5.2 Omicron BF.7 Coinfection Severeinfection

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