Determinations of fracture network connections would help the investigators remove those ＂meaningless＂ no-flow-passing fractures, providing an updated and more effective fracture network that could considerably impr...Determinations of fracture network connections would help the investigators remove those ＂meaningless＂ no-flow-passing fractures, providing an updated and more effective fracture network that could considerably improve the computation efficiency in the pertinent numerical simulations of fluid flow and solute transport. The effective algorithms with higher computational efficiency are needed to accomplish this task in large-scale fractured rock masses. A new approach using R tree indexing was proposed for determining fracture connection in 3D stochastically distributed fracture network. By com- paring with the traditional exhaustion algorithm, it was observed that from the simulation results, this approach was much more effective; and the more the fractures were investigated, the more obvious the advantages of the approach were. Furthermore, it was indicated that the runtime used for creating the R tree indexing has a major part in the total of the runtime used for calculating Minimum Bounding Rectangles （MBRs）, creating the R tree indexing, precisely finding out fracture intersections, and identifying flow paths, which are four important steps to determine fracture connections. This proposed approach for the determination of fracture connections in three-dimensional fractured rocks are expected to provide efficient preprocessing and critical database for practically accomplishing numerical computation of fluid flow and solute transport in large-scale fractured rock masses.展开更多
Existing speech retrieval systems are frequently confronted with expanding volumes of speech data.The dynamic updating strategy applied to construct the index can timely process to add or remove unnecessary speech dat...Existing speech retrieval systems are frequently confronted with expanding volumes of speech data.The dynamic updating strategy applied to construct the index can timely process to add or remove unnecessary speech data to meet users’real-time retrieval requirements.This study proposes an efficient method for retrieving encryption speech,using unsupervised deep hashing and B+ tree dynamic index,which avoid privacy leak-age of speech data and enhance the accuracy and efficiency of retrieval.The cloud’s encryption speech library is constructed by using the multi-threaded Dijk-Gentry-Halevi-Vaikuntanathan(DGHV)Fully Homomorphic Encryption(FHE)technique,which encrypts the original speech.In addition,this research employs Residual Neural Network18-Gated Recurrent Unit(ResNet18-GRU),which is used to learn the compact binary hash codes,store binary hash codes in the designed B+tree index table,and create a mapping relation of one to one between the binary hash codes and the corresponding encrypted speech.External B+tree index technology is applied to achieve dynamic index updating of the B+tree index table,thereby satisfying users’needs for real-time retrieval.The experimental results on THCHS-30 and TIMIT showed that the retrieval accuracy of the proposed method is more than 95.84%compared to the existing unsupervised hashing methods.The retrieval efficiency is greatly improved.Compared to the method of using hash index tables,and the speech data’s security is effectively guaranteed.展开更多
为提高网格环境下海量空间数据管理与并行化处理效率,将网格环境下的分布并行处理技术与空间索引相融合,提出了一种空间索引框架(grid slot and hash Rtree,GSHR-Tree).该索引树结构基于散列hash表和动态空间槽,结合R树结构的范围查询...为提高网格环境下海量空间数据管理与并行化处理效率,将网格环境下的分布并行处理技术与空间索引相融合,提出了一种空间索引框架(grid slot and hash Rtree,GSHR-Tree).该索引树结构基于散列hash表和动态空间槽,结合R树结构的范围查询优势和哈希表结构的高效单key查询,分析改进了索引结构的组织和存储.构造了适合于大规模空间数据的网格并行空间计算的索引结构,该索引树算法根据空间数据划分策略,动态分割空间槽,并将它们映射到多个节点机上.每个节点机再将其对应空间槽中的空间对象组织成R树,以大节点R树方式在多个节点上分布索引数据.以空间范围查询并行处理的系统响应时间为性能评估指标,通过模拟实验证明,该GSHR-Tree索引满足了当前网格环境空间索引的需要,并具有设计合理、性能高效的特点.展开更多
Processing a join over unbounded input streams requires unbounded memory, since every tuple in one infinite stream must be compared with every tuple in the other. In fact, most join queries over unbounded input stream...Processing a join over unbounded input streams requires unbounded memory, since every tuple in one infinite stream must be compared with every tuple in the other. In fact, most join queries over unbounded input streams are restricted to finite memory due to sliding window constraints. So far, non-indexed and indexed stream equijoin algorithms based on sliding windows have been proposed in many literatures. However, none of them takes non-equijoin into consideration. In many eases, non-equijoin queries occur frequently. Hence, it is worth to discuss how to process non-equijoin queries effectively and efficiently. In this paper, we propose an indexed join algorithm for supporting non-equijoin queries. The experimental results show that our indexed non-equijoin techniques are more efficient than those without index.展开更多
Being one of the most expensive components of an electrical power plant, the failures of a power transformer can result in serious power system issues. So fault diagnosis for power transformer is highly important to e...Being one of the most expensive components of an electrical power plant, the failures of a power transformer can result in serious power system issues. So fault diagnosis for power transformer is highly important to ensure an uninterrupted power supply. Due to information transmission mistakes as well as arisen errors while processing data in surveying and monitoring state information of transformer, uncertain and incomplete information may be produced. Based on these points, this paper presents an intelligent fault diagnosis method of power transformer using fuzzy fault tree analysis (FTA) and beta distribution for failure possibility estimation. By using the technique we proposed herein, the continuous attribute values are transformed into the fuzzy numbers to give a realistic estimate of failure possibility of a basic event in FTA. Further, it explains a new approach based on Euclidean distance between fuzzy numbers, to rank the basic events in accordance with their Fuzzy Importance Index.展开更多
With the continuous growth of exponential data in IoT,it is usually chosen to outsource data to the cloud server.However,cloud servers are usually provided by third parties,and there is a risk of privacy leakage.Encry...With the continuous growth of exponential data in IoT,it is usually chosen to outsource data to the cloud server.However,cloud servers are usually provided by third parties,and there is a risk of privacy leakage.Encrypting data can ensure its security,but at the same time,it loses the retrieval function of IoT data.Searchable Encryption(SE)can achieve direct retrieval based on ciphertext data.The traditional searchable encryption scheme has the problems of imperfect function,low retrieval efficiency,inaccurate retrieval results,and centralized cloud servers being vulnerable and untrustworthy.This paper proposes an Efficient searchable encryption scheme supporting fuzzy multi-keyword ranking search on the blockchain.The blockchain and IPFS are used to store the index and encrypted files in a distributed manner respectively.The tamper resistance of the distributed ledger ensures the authenticity of the data.The data retrieval work is performed by the smart contract to ensure the reliability of the data retrieval.The Local Sensitive Hash(LSH)function is combined with the Bloom Filter(BF)to realize the fuzzy multi-keyword retrieval function.In addition,to measure the correlation between keywords and files,a new weighted statistical algorithm combining RegionalWeight Score(RWS)and Term Frequency–Inverse Document Frequency(TF-IDF)is proposed to rank the search results.The balanced binary tree is introduced to establish the index structure,and the index binary tree traversal strategy suitable for this scheme is constructed to optimize the index structure and improve the retrieval efficiency.The experimental results show that the scheme is safe and effective in practical applications.展开更多
基金Supported by the Major State Basic Research Development Program of China （973 Program） （2010CB428804） the National Science Foundation ot China （40672172） and the Major Science and Technology Program for Water Pollution Control and Treatment（2009ZX07212-003）
文摘Determinations of fracture network connections would help the investigators remove those ＂meaningless＂ no-flow-passing fractures, providing an updated and more effective fracture network that could considerably improve the computation efficiency in the pertinent numerical simulations of fluid flow and solute transport. The effective algorithms with higher computational efficiency are needed to accomplish this task in large-scale fractured rock masses. A new approach using R tree indexing was proposed for determining fracture connection in 3D stochastically distributed fracture network. By com- paring with the traditional exhaustion algorithm, it was observed that from the simulation results, this approach was much more effective; and the more the fractures were investigated, the more obvious the advantages of the approach were. Furthermore, it was indicated that the runtime used for creating the R tree indexing has a major part in the total of the runtime used for calculating Minimum Bounding Rectangles （MBRs）, creating the R tree indexing, precisely finding out fracture intersections, and identifying flow paths, which are four important steps to determine fracture connections. This proposed approach for the determination of fracture connections in three-dimensional fractured rocks are expected to provide efficient preprocessing and critical database for practically accomplishing numerical computation of fluid flow and solute transport in large-scale fractured rock masses.
基金supported by the NationalNatural Science Foundation of China(No.61862041).
文摘Existing speech retrieval systems are frequently confronted with expanding volumes of speech data.The dynamic updating strategy applied to construct the index can timely process to add or remove unnecessary speech data to meet users’real-time retrieval requirements.This study proposes an efficient method for retrieving encryption speech,using unsupervised deep hashing and B+ tree dynamic index,which avoid privacy leak-age of speech data and enhance the accuracy and efficiency of retrieval.The cloud’s encryption speech library is constructed by using the multi-threaded Dijk-Gentry-Halevi-Vaikuntanathan(DGHV)Fully Homomorphic Encryption(FHE)technique,which encrypts the original speech.In addition,this research employs Residual Neural Network18-Gated Recurrent Unit(ResNet18-GRU),which is used to learn the compact binary hash codes,store binary hash codes in the designed B+tree index table,and create a mapping relation of one to one between the binary hash codes and the corresponding encrypted speech.External B+tree index technology is applied to achieve dynamic index updating of the B+tree index table,thereby satisfying users’needs for real-time retrieval.The experimental results on THCHS-30 and TIMIT showed that the retrieval accuracy of the proposed method is more than 95.84%compared to the existing unsupervised hashing methods.The retrieval efficiency is greatly improved.Compared to the method of using hash index tables,and the speech data’s security is effectively guaranteed.
文摘为提高网格环境下海量空间数据管理与并行化处理效率,将网格环境下的分布并行处理技术与空间索引相融合,提出了一种空间索引框架(grid slot and hash Rtree,GSHR-Tree).该索引树结构基于散列hash表和动态空间槽,结合R树结构的范围查询优势和哈希表结构的高效单key查询,分析改进了索引结构的组织和存储.构造了适合于大规模空间数据的网格并行空间计算的索引结构,该索引树算法根据空间数据划分策略,动态分割空间槽,并将它们映射到多个节点机上.每个节点机再将其对应空间槽中的空间对象组织成R树,以大节点R树方式在多个节点上分布索引数据.以空间范围查询并行处理的系统响应时间为性能评估指标,通过模拟实验证明,该GSHR-Tree索引满足了当前网格环境空间索引的需要,并具有设计合理、性能高效的特点.
基金Supported by the National Natural Science Foun-dation of China (60473073)
文摘Processing a join over unbounded input streams requires unbounded memory, since every tuple in one infinite stream must be compared with every tuple in the other. In fact, most join queries over unbounded input streams are restricted to finite memory due to sliding window constraints. So far, non-indexed and indexed stream equijoin algorithms based on sliding windows have been proposed in many literatures. However, none of them takes non-equijoin into consideration. In many eases, non-equijoin queries occur frequently. Hence, it is worth to discuss how to process non-equijoin queries effectively and efficiently. In this paper, we propose an indexed join algorithm for supporting non-equijoin queries. The experimental results show that our indexed non-equijoin techniques are more efficient than those without index.
文摘Being one of the most expensive components of an electrical power plant, the failures of a power transformer can result in serious power system issues. So fault diagnosis for power transformer is highly important to ensure an uninterrupted power supply. Due to information transmission mistakes as well as arisen errors while processing data in surveying and monitoring state information of transformer, uncertain and incomplete information may be produced. Based on these points, this paper presents an intelligent fault diagnosis method of power transformer using fuzzy fault tree analysis (FTA) and beta distribution for failure possibility estimation. By using the technique we proposed herein, the continuous attribute values are transformed into the fuzzy numbers to give a realistic estimate of failure possibility of a basic event in FTA. Further, it explains a new approach based on Euclidean distance between fuzzy numbers, to rank the basic events in accordance with their Fuzzy Importance Index.
基金funded by the Jilin Provincial Department of Education Scientific Research Project(Project No.JJKH20250872KJ).
文摘With the continuous growth of exponential data in IoT,it is usually chosen to outsource data to the cloud server.However,cloud servers are usually provided by third parties,and there is a risk of privacy leakage.Encrypting data can ensure its security,but at the same time,it loses the retrieval function of IoT data.Searchable Encryption(SE)can achieve direct retrieval based on ciphertext data.The traditional searchable encryption scheme has the problems of imperfect function,low retrieval efficiency,inaccurate retrieval results,and centralized cloud servers being vulnerable and untrustworthy.This paper proposes an Efficient searchable encryption scheme supporting fuzzy multi-keyword ranking search on the blockchain.The blockchain and IPFS are used to store the index and encrypted files in a distributed manner respectively.The tamper resistance of the distributed ledger ensures the authenticity of the data.The data retrieval work is performed by the smart contract to ensure the reliability of the data retrieval.The Local Sensitive Hash(LSH)function is combined with the Bloom Filter(BF)to realize the fuzzy multi-keyword retrieval function.In addition,to measure the correlation between keywords and files,a new weighted statistical algorithm combining RegionalWeight Score(RWS)and Term Frequency–Inverse Document Frequency(TF-IDF)is proposed to rank the search results.The balanced binary tree is introduced to establish the index structure,and the index binary tree traversal strategy suitable for this scheme is constructed to optimize the index structure and improve the retrieval efficiency.The experimental results show that the scheme is safe and effective in practical applications.
