As the 5G communication networks are being widely deployed worldwide,both industry and academia have started to move beyond 5G and explore 6G communications.It is generally believed that 6G will be established on ubiq...As the 5G communication networks are being widely deployed worldwide,both industry and academia have started to move beyond 5G and explore 6G communications.It is generally believed that 6G will be established on ubiquitous Artificial Intelligence(AI)to achieve data-driven Machine Learning(ML)solutions in heterogeneous and massive-scale networks.However,traditional ML techniques require centralized data collection and processing by a central server,which is becoming a bottleneck of large-scale implementation in daily life due to significantly increasing privacy concerns.Federated learning,as an emerging distributed AI approach with privacy preservation nature,is particularly attractive for various wireless applications,especially being treated as one of the vital solutions to achieve ubiquitous AI in 6G.In this article,we first introduce the integration of 6G and federated learning and provide potential federated learning applications for 6G.We then describe key technical challenges,the corresponding federated learning methods,and open problems for future research on federated learning in the context of 6G communications.展开更多
针对室内环境结构相似的特点,提出一种基于图像序列拓扑关系的移动机器人全局定位算法.首先,提取图像的Gist描述子,并提出一种局部极值算法,将环境划分成若干组不同的图像序列.然后,使用ESN(echo state network)对每一组图像序列在时间...针对室内环境结构相似的特点,提出一种基于图像序列拓扑关系的移动机器人全局定位算法.首先,提取图像的Gist描述子,并提出一种局部极值算法,将环境划分成若干组不同的图像序列.然后,使用ESN(echo state network)对每一组图像序列在时间上进行双序训练,提取鲁棒的图像序列特征,再利用空间上的双向匹配策略实现图像序列特征的匹配.最后,采用HMM(hidden Markov model)对图像序列间的拓扑关系进行建模,将移动机器人全局定位问题转化成有向无环图中最长路径求解问题,并通过实验对该图像序列划分和序列建模方法进行验证.与基于单帧图像匹配的算法、SeqSLAM算法以及Fast-SeqSLAM算法相比,该算法在室内走廊环境和办公环境中均可实现100%的定位.特别是在室内办公环境中,机器人仅需要运动0.80 m便可以对自身进行准确定位.实验结果表明,该算法具有较强的鲁棒性、较高的定位准确性和定位效率.展开更多
为解决由于固定温度SAC(Soft Actor Critic)算法中存在的Q函数高估可能会导致算法陷入局部最优的问题,通过深入分析提出了一个稳定且受限的SAC算法(SCSAC:Stable Constrained Soft Actor Critic)。该算法通过改进最大熵目标函数修复固...为解决由于固定温度SAC(Soft Actor Critic)算法中存在的Q函数高估可能会导致算法陷入局部最优的问题,通过深入分析提出了一个稳定且受限的SAC算法(SCSAC:Stable Constrained Soft Actor Critic)。该算法通过改进最大熵目标函数修复固定温度SAC算法中的Q函数高估问题,同时增强算法在测试过程中稳定性的效果。最后,在4个OpenAI Gym Mujoco环境下对SCSAC算法进行了验证,实验结果表明,稳定且受限的SAC算法相比固定温度SAC算法可以有效减小Q函数高估出现的次数并能在测试中获得更加稳定的结果。展开更多
Searchable symmetric encryption(SSE)has been introduced for secure outsourcing the encrypted database to cloud storage,while maintaining searchable features.Of various SSE schemes,most of them assume the server is hon...Searchable symmetric encryption(SSE)has been introduced for secure outsourcing the encrypted database to cloud storage,while maintaining searchable features.Of various SSE schemes,most of them assume the server is honest but curious,while the server may be trustless in the real world.Considering a malicious server not honestly performing the queries,verifiable SSE(VSSE)schemes are constructed to ensure the verifiability of the search results.However,existing VSSE constructions only focus on single-keyword search or incur heavy computational cost during verification.To address this challenge,we present an efficient VSSE scheme,built on OXT protocol(Cash et al.,CRYPTO 2013),for conjunctive keyword queries with sublinear search overhead.The proposed VSSE scheme is based on a privacy-preserving hash-based accumulator,by leveraging a well-established cryptographic primitive,Symmetric Hidden Vector Encryption(SHVE).Our VSSE scheme enables both correctness and completeness verifiability for the result without pairing operations,thus greatly reducing the computational cost in the verification process.Besides,the proposed VSSE scheme can still provide a proof when the search result is empty.Finally,the security analysis and experimental evaluation are given to demonstrate the security and practicality of the proposed scheme.展开更多
Since 2003, China has carried out the pilot of collective forest tenure reform (CFTR). Inrecent years, there have been lots of researches about evaluation of the CFTR, which are, however,mostly qualitative research wi...Since 2003, China has carried out the pilot of collective forest tenure reform (CFTR). Inrecent years, there have been lots of researches about evaluation of the CFTR, which are, however,mostly qualitative research with little focus on the quantitative research. This paper used the AnalyticHierarchy Process (AHP) and expert assignment method to define the comprehensive evaluation indexes and monitoring indexes of the CFTR. In this study, the authors did a quantitative evaluation of the CFTR in Shaowu, Fujian Province, which was scored as 0.844, indicating more significant effect. The authors investigated 100 farmer households there, and the data showed that the average household income has grown by 49.2% in the 6 years after the CFTR implementation, while the forestry incomehas grown by 108.3%, indicating that farmers’ income increased significantly after the CFTR. Factor analysis shows that CFTR has been the key factor to increase farmers’ income.展开更多
基金supported by the National Research Foundation(NRF),Singapore,under Singapore Energy Market Authority(EMA),Energy Resilience,NRF2017EWT-EP003-041,Singapore NRF2015NRF-ISF001-2277Singapore NRF National Satellite of Excellence,Design Science and Technology for Secure Critical Infrastructure NSoE DeST-SCI2019-0007+4 种基金A*STARNTU-SUTD Joint Research Grant on Artificial Intelligence for the Future of Manufacturing RGANS1906,Wallenberg AI,Autonomous Systems and Software Program and Nanyang Technological University(WASP/NTU)under grant M4082187(4080),and NTU-We Bank JRI(NWJ-2020-004)Alibaba Group through Alibaba Innovative Research(AIR)Program and Alibaba-NTU Singapore Joint Research Institute(JRI),NTU,SingaporeNational Key Research and Development Program of China under Grant 2018YFC0809803 and Grant 2019YFB2101901Young Innovation Talents Project in Higher Education of Guangdong Province,China under grant No.2018KQNCX333in part by the National Science Foundation of China under Grant 61702364。
文摘As the 5G communication networks are being widely deployed worldwide,both industry and academia have started to move beyond 5G and explore 6G communications.It is generally believed that 6G will be established on ubiquitous Artificial Intelligence(AI)to achieve data-driven Machine Learning(ML)solutions in heterogeneous and massive-scale networks.However,traditional ML techniques require centralized data collection and processing by a central server,which is becoming a bottleneck of large-scale implementation in daily life due to significantly increasing privacy concerns.Federated learning,as an emerging distributed AI approach with privacy preservation nature,is particularly attractive for various wireless applications,especially being treated as one of the vital solutions to achieve ubiquitous AI in 6G.In this article,we first introduce the integration of 6G and federated learning and provide potential federated learning applications for 6G.We then describe key technical challenges,the corresponding federated learning methods,and open problems for future research on federated learning in the context of 6G communications.
文摘为解决由于固定温度SAC(Soft Actor Critic)算法中存在的Q函数高估可能会导致算法陷入局部最优的问题,通过深入分析提出了一个稳定且受限的SAC算法(SCSAC:Stable Constrained Soft Actor Critic)。该算法通过改进最大熵目标函数修复固定温度SAC算法中的Q函数高估问题,同时增强算法在测试过程中稳定性的效果。最后,在4个OpenAI Gym Mujoco环境下对SCSAC算法进行了验证,实验结果表明,稳定且受限的SAC算法相比固定温度SAC算法可以有效减小Q函数高估出现的次数并能在测试中获得更加稳定的结果。
基金supported by the National Natural Science Foundation of China (Grant Nos.61932010 and 62072357)the Zhuhai Top Discipline-Information Securitysupported by the China Scholarship Council (CSC)and the Australian Research Council (ARC).
文摘Searchable symmetric encryption(SSE)has been introduced for secure outsourcing the encrypted database to cloud storage,while maintaining searchable features.Of various SSE schemes,most of them assume the server is honest but curious,while the server may be trustless in the real world.Considering a malicious server not honestly performing the queries,verifiable SSE(VSSE)schemes are constructed to ensure the verifiability of the search results.However,existing VSSE constructions only focus on single-keyword search or incur heavy computational cost during verification.To address this challenge,we present an efficient VSSE scheme,built on OXT protocol(Cash et al.,CRYPTO 2013),for conjunctive keyword queries with sublinear search overhead.The proposed VSSE scheme is based on a privacy-preserving hash-based accumulator,by leveraging a well-established cryptographic primitive,Symmetric Hidden Vector Encryption(SHVE).Our VSSE scheme enables both correctness and completeness verifiability for the result without pairing operations,thus greatly reducing the computational cost in the verification process.Besides,the proposed VSSE scheme can still provide a proof when the search result is empty.Finally,the security analysis and experimental evaluation are given to demonstrate the security and practicality of the proposed scheme.
基金funded by the Special Research Program for Public-welfare Forestry "Dynamic Monitoring and Evaluation System Research on Typical Area of CFTR (200804026)"
文摘Since 2003, China has carried out the pilot of collective forest tenure reform (CFTR). Inrecent years, there have been lots of researches about evaluation of the CFTR, which are, however,mostly qualitative research with little focus on the quantitative research. This paper used the AnalyticHierarchy Process (AHP) and expert assignment method to define the comprehensive evaluation indexes and monitoring indexes of the CFTR. In this study, the authors did a quantitative evaluation of the CFTR in Shaowu, Fujian Province, which was scored as 0.844, indicating more significant effect. The authors investigated 100 farmer households there, and the data showed that the average household income has grown by 49.2% in the 6 years after the CFTR implementation, while the forestry incomehas grown by 108.3%, indicating that farmers’ income increased significantly after the CFTR. Factor analysis shows that CFTR has been the key factor to increase farmers’ income.
