The journal of Meteorological and Environmental Research[ISSN:2152-3940]has been included and stored by the following famous databases:CA,CABI,CSA,EBSCO,UPD,AGRIS,EA,Chinese Science and Technology Periodical Database,...The journal of Meteorological and Environmental Research[ISSN:2152-3940]has been included and stored by the following famous databases:CA,CABI,CSA,EBSCO,UPD,AGRIS,EA,Chinese Science and Technology Periodical Database,and CNKI,as well as Library of Congress,United States.展开更多
The journal of Meteorological and Environmental Research[ISSN:2152-3940]has been included and stored by the following famous databases:CA,CABI,CSA,EBSCO,UPD,AGRIS,EA,Chinese Science and Technology Periodical Database,...The journal of Meteorological and Environmental Research[ISSN:2152-3940]has been included and stored by the following famous databases:CA,CABI,CSA,EBSCO,UPD,AGRIS,EA,Chinese Science and Technology Periodical Database,and CNKI,as well as Library of Congress,United States.展开更多
The authors regret that the original publication of this paper did not include Jawad Fayaz as a co-author.After further discussions and a thorough review of the research contributions,it was agreed that his significan...The authors regret that the original publication of this paper did not include Jawad Fayaz as a co-author.After further discussions and a thorough review of the research contributions,it was agreed that his significant contributions to the foundational aspects of the research warranted recognition,and he has now been added as a co-author.展开更多
Objectives:Electronic health records(EHRs)offer valuable real-world data(RWD)for Chinese medicine research.However,significant methodological challenges remain in developing integrative Chinese-Western medicine(ICWM)d...Objectives:Electronic health records(EHRs)offer valuable real-world data(RWD)for Chinese medicine research.However,significant methodological challenges remain in developing integrative Chinese-Western medicine(ICWM)databases.This study aims to establish a best-practice methodological framework,referred to as BRIDGE,to guide the construction of ICWM databases using EHRs.Methods:We developed the methodological framework through a comprehensive process,including systematic literature review,synthesis of empirical experiences,thematic expert discussions,and consultation with an external panel to reach consensus.Results:The BRIDGE framework outlines 6 core components for ICWM-EHR database development:Overall design,database architecture,data extraction and linkage,data governance,data verification,and data quality evaluation.Key data elements include variables related to study population,treatment or exposure,outcomes,and confounders.These databases support various research applications,particularly in evaluating the effectiveness and safety of integrative therapies.To demonstrate its practical value,we developed an ICWM-EHR database on women’s reproductive lifespan,encompassing 2,064,482 patients.This database captures women’s health conditions across the life course,from reproductive age to older adulthood.Conclusions:The BRIDGE methodological framework provides a standardized approach to building high-quality ICWM-EHR databases.It offers a unique opportunity to strengthen the methodological rigor and real-world relevance of Chinese medicine research in integrated healthcare settings.展开更多
A distinctive feature of scholarly communities today is exploring topics and concepts in interdisciplinary and international contexts. This observation is increasingly apparent and visible in advancing our thinking an...A distinctive feature of scholarly communities today is exploring topics and concepts in interdisciplinary and international contexts. This observation is increasingly apparent and visible in advancing our thinking and policies related to human/environmental worlds at local, regional, and global scales. Maps are an important part of these innovative and ongoing research approaches. In this context, we consider urban forests a topic meriting more attention of scholars studying the geographic and environmental intersections of the natural sciences with the social sciences and humanities. We construct two innovative knowledge bases, one a conceptual framework based on major themes and concepts related to mapping urban forests using key words of the first 100 results of a Google Scholar query and a second using the number of Google Scholar hyperlinks about mapping urban forests in 244 capital cities. We discovered that the constructed world maps reveal vast global unevenness in our knowledge about urban forests in hyperlink numbers and ratios, results that merit further attention by disciplinary, international and interdisciplinary scholarly communities.展开更多
AI-driven materials databases are transforming research by integrating experimental and computational data to enhance discovery and optimization.Platforms such as Digital Catalysis Platform(DigCat)and Dynamic Database...AI-driven materials databases are transforming research by integrating experimental and computational data to enhance discovery and optimization.Platforms such as Digital Catalysis Platform(DigCat)and Dynamic Database of Solid-State Electrolyte(DDSE)demonstrate how machine learning and predictive modeling can improve catalyst and solid-state electrolyte development.These databases facilitate data standardization,high-throughput screening,and cross-disciplinary collaboration,addressing key challenges in materials informatics.As AI techniques advance,materials databases are expected to play an increasingly vital role in accelerating research and innovation.展开更多
The EU’s Artificial Intelligence Act(AI Act)imposes requirements for the privacy compliance of AI systems.AI systems must comply with privacy laws such as the GDPR when providing services.These laws provide users wit...The EU’s Artificial Intelligence Act(AI Act)imposes requirements for the privacy compliance of AI systems.AI systems must comply with privacy laws such as the GDPR when providing services.These laws provide users with the right to issue a Data Subject Access Request(DSAR).Responding to such requests requires database administrators to identify information related to an individual accurately.However,manual compliance poses significant challenges and is error-prone.Database administrators need to write queries through time-consuming labor.The demand for large amounts of data by AI systems has driven the development of NoSQL databases.Due to the flexible schema of NoSQL databases,identifying personal information becomes even more challenging.This paper develops an automated tool to identify personal information that can help organizations respond to DSAR.Our tool employs a combination of various technologies,including schema extraction of NoSQL databases and relationship identification from query logs.We describe the algorithm used by our tool,detailing how it discovers and extracts implicit relationships from NoSQL databases and generates relationship graphs to help developers accurately identify personal data.We evaluate our tool on three datasets,covering different database designs,achieving an F1 score of 0.77 to 1.Experimental results demonstrate that our tool successfully identifies information relevant to the data subject.Our tool reduces manual effort and simplifies GDPR compliance,showing practical application value in enhancing the privacy performance of NOSQL databases and AI systems.展开更多
In China, the vast majority of the bibliographic databases is commercial, such as China National Knowledge Infrastructure （CNKI）, Wanfang Database, Longyuan Journal Net, CQVIP Company, however, there are also non-pr...In China, the vast majority of the bibliographic databases is commercial, such as China National Knowledge Infrastructure （CNKI）, Wanfang Database, Longyuan Journal Net, CQVIP Company, however, there are also non-profit open access （OA） databases, such as journal database jointly established by Chinese Academy of Social Sciences （CASS） and National Social Science Fund. The commercial bibliographic databases have to face many difficulties： intellectual property disputes, the benefit distribution between the hardcopy periodical and the commercial bibliographic database, the lack of quality assessment about the commercial bibliographic databases, the need of improving digital technology as well as the lack of a unified database regulation, which restricts the development of commercial bibliographic databases. This paper puts forward the countermeasures from the perspective of how to enhance the governmental management; how to protect the intellectual property fight; how to improve the technical standard of the commercial bibliographic databases; how to build interest distribution between the hardcopy periodical and the commercial bibliographic database; how to improve the quality of commercial bibliographic databases; and how to improve the industrial chain of the commercial bibliographic databases.展开更多
Traditionally,nonlinear time history analysis(NLTHA)is used to assess the performance of structures under fu-ture hazards which is necessary to develop effective disaster risk management strategies.However,this method...Traditionally,nonlinear time history analysis(NLTHA)is used to assess the performance of structures under fu-ture hazards which is necessary to develop effective disaster risk management strategies.However,this method is computationally intensive and not suitable for analyzing a large number of structures on a city-wide scale.Surrogate models offer an efficient and reliable alternative and facilitate evaluating the performance of multiple structures under different hazard scenarios.However,creating a comprehensive database for surrogate mod-elling at the city level presents challenges.To overcome this,the present study proposes meta databases and a general framework for surrogate modelling of steel structures.The dataset includes 30,000 steel moment-resisting frame buildings,representing low-rise,mid-rise and high-rise buildings,with criteria for connections,beams,and columns.Pushover analysis is performed and structural parameters are extracted,and finally,incorporating two different machine learning algorithms,random forest and Shapley additive explanations,sensitivity and explain-ability analyses of the structural parameters are performed to identify the most significant factors in designing steel moment resisting frames.The framework and databases can be used as a validated source of surrogate modelling of steel frame structures in order for disaster risk management.展开更多
Discovery of materials using“bottom-up”or“top-down”approach is of great interest in materials science.Layered materials consisting of two-dimensional(2D)building blocks provide a good platform to explore new mater...Discovery of materials using“bottom-up”or“top-down”approach is of great interest in materials science.Layered materials consisting of two-dimensional(2D)building blocks provide a good platform to explore new materials in this respect.In van der Waals(vdW)layered materials,these building blocks are charge neutral and can be isolated from their bulk phase(top-down),but usually grow on substrate.In ionic layered materials,they are charged and usually cannot exist independently but can serve as motifs to construct new materials(bottom-up).In this paper,we introduce our recently constructed databases for 2D material-substrate interface(2DMSI),and 2D charged building blocks.For 2DMSI database,we systematically build a workflow to predict appropriate substrates and their geometries at substrates,and construct the 2DMSI database.For the 2D charged building block database,1208 entries from bulk material database are identified.Information of crystal structure,valence state,source,dimension and so on is provided for each entry with a json format.We also show its application in designing and searching for new functional layered materials.The 2DMSI database,building block database,and designed layered materials are available in Science Data Bank at https://doi.org/10.57760/sciencedb.j00113.00188.展开更多
Clustering, in data mining, is a useful technique for discovering interesting data distributions and patterns in the underlying data, and has many application fields, such as statistical data analysis, pattern recogni...Clustering, in data mining, is a useful technique for discovering interesting data distributions and patterns in the underlying data, and has many application fields, such as statistical data analysis, pattern recognition, image processing, and etc. We combine sampling technique with DBSCAN algorithm to cluster large spatial databases, and two sampling based DBSCAN (SDBSCAN) algorithms are developed. One algorithm introduces sampling technique inside DBSCAN, and the other uses sampling procedure outside DBSCAN. Experimental results demonstrate that our algorithms are effective and efficient in clustering large scale spatial databases.展开更多
The necessity and the feasibility of introducing attribute weight into digital fingerprinting system are given. The weighted algorithm for fingerprinting relational databases of traitor tracing is proposed. Higher wei...The necessity and the feasibility of introducing attribute weight into digital fingerprinting system are given. The weighted algorithm for fingerprinting relational databases of traitor tracing is proposed. Higher weights are assigned to more significant attributes, so important attributes are more frequently fingerprinted than other ones. Finally, the robustness of the proposed algorithm, such as performance against collusion attacks, is analyzed. Experimental results prove the superiority of the algorithm.展开更多
To solve the problems of shaving and reusing information in the information system, a rules-based ontology constructing approach from object-relational databases is proposed. A 3-tuple ontology constructing model is p...To solve the problems of shaving and reusing information in the information system, a rules-based ontology constructing approach from object-relational databases is proposed. A 3-tuple ontology constructing model is proposed first. Then, four types of ontology constructing rules including class, property, property characteristics, and property restrictions ave formalized according to the model. Experiment results described in Web ontology language prove that our proposed approach is feasible for applying in the semantic objects project of semantic computing laboratory in UC Irvine. Our approach reduces about twenty percent constructing time compared with the ontology construction from relational databases.展开更多
Data acquisition and modeling are the two important, difficult and costful aspects in a Cybercity project. 2D-GIS is mature and can manage a lot of spatial data. Thus 3D-GIS should make the best of data and technology...Data acquisition and modeling are the two important, difficult and costful aspects in a Cybercity project. 2D-GIS is mature and can manage a lot of spatial data. Thus 3D-GIS should make the best of data and technology of 2D-GIS. Construction of a useful synthetic environment requires integration of multiple types of information like DEM, texture images and 3D representation of objects such as buildings. In this paper, the method for 3D city landscape data model and visualization based on integrated databases is presented. Since the data volume of raster are very huge, special strategies(for example, pyramid gridded method) must be adopted in order to manage raster data efficiently. Three different methods of data acquisition, the proper data structure and a simple modeling method are presented as well. At last, a pilot project of Shanghai Cybercity is illustrated.展开更多
As the typical peer-to-peer distributed networks, blockchain systemsrequire each node to copy a complete transaction database, so as to ensure newtransactions can by verified independently. In a blockchain system (e.g...As the typical peer-to-peer distributed networks, blockchain systemsrequire each node to copy a complete transaction database, so as to ensure newtransactions can by verified independently. In a blockchain system (e.g., bitcoinsystem), the node does not rely on any central organization, and every node keepsan entire copy of the transaction database. However, this feature determines thatthe size of blockchain transaction database is growing rapidly. Therefore, with thecontinuous system operations, the node memory also needs to be expanded tosupport the system running. Especially in the big data era, the increasing networktraffic will lead to faster transaction growth rate. This paper analyzes blockchaintransaction databases and proposes a storage optimization scheme. The proposedscheme divides blockchain transaction database into cold zone and hot zone usingexpiration recognition method based on Least Recently Used (LRU) algorithm. Itcan achieve storage optimization by moving unspent transaction outputs outsidethe in-memory transaction databases. We present the theoretical analysis on theoptimization method to validate the effectiveness. Extensive experiments showour proposed method outperforms the current mechanism for the blockchaintransaction databases.展开更多
Most knowledgeable people agree that networking and routing technologies have been around about 25 years. Routing is simultaneously the most complicated function of a network and the most important. It is of the same ...Most knowledgeable people agree that networking and routing technologies have been around about 25 years. Routing is simultaneously the most complicated function of a network and the most important. It is of the same kind that more than 70% of computer application fields are MIS applications. So the challenge in building and using a MIS in the network is developing the means to find, access, and communicate large databases or multi databases systems. Because general databases are not time continuous, in fact, they can not be streaming, so we can't obtain reliable and secure quality of service by deleting some unimportant datagrams in the databases transmission. In this article, we will discuss which kind of routing protocol is the best type for large databases or multi databases systems transmission in the networks.展开更多
A weighted algorithm for watermarking relational databases for copyright protection is presented. The possibility of watermarking an attribute is assigned according to its weight decided by the owner of the database. ...A weighted algorithm for watermarking relational databases for copyright protection is presented. The possibility of watermarking an attribute is assigned according to its weight decided by the owner of the database. A one-way hash function and a secret key known only to the owner of the data are used to select tuples and bits to mark. By assigning high weight to significant attributes, the scheme ensures that important attributes take more chance to be marked than less important ones. Experimental results show that the proposed scheme is robust against various forms of attacks, and has perfect immunity to subset attack.展开更多
In this paper, constrained K closest pairs query is introduced, wbich retrieves the K closest pairs satisfying the given spatial constraint from two datasets. For data sets indexed by R trees in spatial databases, thr...In this paper, constrained K closest pairs query is introduced, wbich retrieves the K closest pairs satisfying the given spatial constraint from two datasets. For data sets indexed by R trees in spatial databases, three algorithms are presented for answering this kind of query. Among of them, two-phase Range＋Join and Join＋Range algorithms adopt the strategy that changes the execution order of range and closest pairs queries, and constrained heap-based algorithm utilizes extended distance functions to prune search space and minimize the pruning distance. Experimental results show that constrained heap-base algorithm has better applicability and performance than two-phase algorithms.展开更多
The technique of Knowlege Discovery in Databases (KDD) to learn valuable knowledge hidden in network alarm databases is introduced. To get such knowledge, we propose an efficient method based on sliding windows (named...The technique of Knowlege Discovery in Databases (KDD) to learn valuable knowledge hidden in network alarm databases is introduced. To get such knowledge, we propose an efficient method based on sliding windows (named as Slidwin) to discover different episode rules from time squential alarm data. The experimental results show that given different thresholds parameters, large amount of different rules could be discovered quickly.展开更多
It is a period of information explosion. Especially for spatial information science, information can be acquired through many ways, such as man made planet, aeroplane, laser, digital photogrammetry and so on. Spatial...It is a period of information explosion. Especially for spatial information science, information can be acquired through many ways, such as man made planet, aeroplane, laser, digital photogrammetry and so on. Spatial data sources are usually distributed and heterogeneous. Federated database is the best resolution for the share and interoperation of spatial database. In this paper, the concepts of federated database and interoperability are introduced. Three heterogeneous kinds of spatial data, vector, image and DEM are used to create integrated database. A data model of federated spatial databases is given.展开更多
文摘The journal of Meteorological and Environmental Research[ISSN:2152-3940]has been included and stored by the following famous databases:CA,CABI,CSA,EBSCO,UPD,AGRIS,EA,Chinese Science and Technology Periodical Database,and CNKI,as well as Library of Congress,United States.
文摘The journal of Meteorological and Environmental Research[ISSN:2152-3940]has been included and stored by the following famous databases:CA,CABI,CSA,EBSCO,UPD,AGRIS,EA,Chinese Science and Technology Periodical Database,and CNKI,as well as Library of Congress,United States.
文摘The authors regret that the original publication of this paper did not include Jawad Fayaz as a co-author.After further discussions and a thorough review of the research contributions,it was agreed that his significant contributions to the foundational aspects of the research warranted recognition,and he has now been added as a co-author.
基金supported by the National Key Research&Development Program of China(No.2024YFC3505800)the National Natural Science Foundation of China(Nos.82474334,82474335 and 72174132)+3 种基金National Science Fund for Distinguished Young Scholars(No.82225049)the Key Research&Development Projects of Sichuan Provincial Department of Science and Technology(Nos.2024YFFK0174 and 2024YFFK0152)1.3.5 Project for Disciplines of Excellence,West China Hospital,Sichuan University(Nos.ZYYC24010 and ZYGD23004)the Special Fund for Traditional Chinese Medicine of Sichuan Provincial Administration of Traditional Chinese Medicine(No.2024zd023).
文摘Objectives:Electronic health records(EHRs)offer valuable real-world data(RWD)for Chinese medicine research.However,significant methodological challenges remain in developing integrative Chinese-Western medicine(ICWM)databases.This study aims to establish a best-practice methodological framework,referred to as BRIDGE,to guide the construction of ICWM databases using EHRs.Methods:We developed the methodological framework through a comprehensive process,including systematic literature review,synthesis of empirical experiences,thematic expert discussions,and consultation with an external panel to reach consensus.Results:The BRIDGE framework outlines 6 core components for ICWM-EHR database development:Overall design,database architecture,data extraction and linkage,data governance,data verification,and data quality evaluation.Key data elements include variables related to study population,treatment or exposure,outcomes,and confounders.These databases support various research applications,particularly in evaluating the effectiveness and safety of integrative therapies.To demonstrate its practical value,we developed an ICWM-EHR database on women’s reproductive lifespan,encompassing 2,064,482 patients.This database captures women’s health conditions across the life course,from reproductive age to older adulthood.Conclusions:The BRIDGE methodological framework provides a standardized approach to building high-quality ICWM-EHR databases.It offers a unique opportunity to strengthen the methodological rigor and real-world relevance of Chinese medicine research in integrated healthcare settings.
文摘A distinctive feature of scholarly communities today is exploring topics and concepts in interdisciplinary and international contexts. This observation is increasingly apparent and visible in advancing our thinking and policies related to human/environmental worlds at local, regional, and global scales. Maps are an important part of these innovative and ongoing research approaches. In this context, we consider urban forests a topic meriting more attention of scholars studying the geographic and environmental intersections of the natural sciences with the social sciences and humanities. We construct two innovative knowledge bases, one a conceptual framework based on major themes and concepts related to mapping urban forests using key words of the first 100 results of a Google Scholar query and a second using the number of Google Scholar hyperlinks about mapping urban forests in 244 capital cities. We discovered that the constructed world maps reveal vast global unevenness in our knowledge about urban forests in hyperlink numbers and ratios, results that merit further attention by disciplinary, international and interdisciplinary scholarly communities.
文摘AI-driven materials databases are transforming research by integrating experimental and computational data to enhance discovery and optimization.Platforms such as Digital Catalysis Platform(DigCat)and Dynamic Database of Solid-State Electrolyte(DDSE)demonstrate how machine learning and predictive modeling can improve catalyst and solid-state electrolyte development.These databases facilitate data standardization,high-throughput screening,and cross-disciplinary collaboration,addressing key challenges in materials informatics.As AI techniques advance,materials databases are expected to play an increasingly vital role in accelerating research and innovation.
基金supported by the National Natural Science Foundation of China(No.62302242)the China Postdoctoral Science Foundation(No.2023M731802).
文摘The EU’s Artificial Intelligence Act(AI Act)imposes requirements for the privacy compliance of AI systems.AI systems must comply with privacy laws such as the GDPR when providing services.These laws provide users with the right to issue a Data Subject Access Request(DSAR).Responding to such requests requires database administrators to identify information related to an individual accurately.However,manual compliance poses significant challenges and is error-prone.Database administrators need to write queries through time-consuming labor.The demand for large amounts of data by AI systems has driven the development of NoSQL databases.Due to the flexible schema of NoSQL databases,identifying personal information becomes even more challenging.This paper develops an automated tool to identify personal information that can help organizations respond to DSAR.Our tool employs a combination of various technologies,including schema extraction of NoSQL databases and relationship identification from query logs.We describe the algorithm used by our tool,detailing how it discovers and extracts implicit relationships from NoSQL databases and generates relationship graphs to help developers accurately identify personal data.We evaluate our tool on three datasets,covering different database designs,achieving an F1 score of 0.77 to 1.Experimental results demonstrate that our tool successfully identifies information relevant to the data subject.Our tool reduces manual effort and simplifies GDPR compliance,showing practical application value in enhancing the privacy performance of NOSQL databases and AI systems.
文摘In China, the vast majority of the bibliographic databases is commercial, such as China National Knowledge Infrastructure （CNKI）, Wanfang Database, Longyuan Journal Net, CQVIP Company, however, there are also non-profit open access （OA） databases, such as journal database jointly established by Chinese Academy of Social Sciences （CASS） and National Social Science Fund. The commercial bibliographic databases have to face many difficulties： intellectual property disputes, the benefit distribution between the hardcopy periodical and the commercial bibliographic database, the lack of quality assessment about the commercial bibliographic databases, the need of improving digital technology as well as the lack of a unified database regulation, which restricts the development of commercial bibliographic databases. This paper puts forward the countermeasures from the perspective of how to enhance the governmental management; how to protect the intellectual property fight; how to improve the technical standard of the commercial bibliographic databases; how to build interest distribution between the hardcopy periodical and the commercial bibliographic database; how to improve the quality of commercial bibliographic databases; and how to improve the industrial chain of the commercial bibliographic databases.
基金financial support from Teesside University to support the Ph.D.programme of the first author.
文摘Traditionally,nonlinear time history analysis(NLTHA)is used to assess the performance of structures under fu-ture hazards which is necessary to develop effective disaster risk management strategies.However,this method is computationally intensive and not suitable for analyzing a large number of structures on a city-wide scale.Surrogate models offer an efficient and reliable alternative and facilitate evaluating the performance of multiple structures under different hazard scenarios.However,creating a comprehensive database for surrogate mod-elling at the city level presents challenges.To overcome this,the present study proposes meta databases and a general framework for surrogate modelling of steel structures.The dataset includes 30,000 steel moment-resisting frame buildings,representing low-rise,mid-rise and high-rise buildings,with criteria for connections,beams,and columns.Pushover analysis is performed and structural parameters are extracted,and finally,incorporating two different machine learning algorithms,random forest and Shapley additive explanations,sensitivity and explain-ability analyses of the structural parameters are performed to identify the most significant factors in designing steel moment resisting frames.The framework and databases can be used as a validated source of surrogate modelling of steel frame structures in order for disaster risk management.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.61888102,52272172,and 52102193)the Major Program of the National Natural Science Foundation of China(Grant No.92163206)+2 种基金the National Key Research and Development Program of China(Grant Nos.2021YFA1201501 and 2022YFA1204100)the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDB30000000)the Fundamental Research Funds for the Central Universities.
文摘Discovery of materials using“bottom-up”or“top-down”approach is of great interest in materials science.Layered materials consisting of two-dimensional(2D)building blocks provide a good platform to explore new materials in this respect.In van der Waals(vdW)layered materials,these building blocks are charge neutral and can be isolated from their bulk phase(top-down),but usually grow on substrate.In ionic layered materials,they are charged and usually cannot exist independently but can serve as motifs to construct new materials(bottom-up).In this paper,we introduce our recently constructed databases for 2D material-substrate interface(2DMSI),and 2D charged building blocks.For 2DMSI database,we systematically build a workflow to predict appropriate substrates and their geometries at substrates,and construct the 2DMSI database.For the 2D charged building block database,1208 entries from bulk material database are identified.Information of crystal structure,valence state,source,dimension and so on is provided for each entry with a json format.We also show its application in designing and searching for new functional layered materials.The 2DMSI database,building block database,and designed layered materials are available in Science Data Bank at https://doi.org/10.57760/sciencedb.j00113.00188.
基金Supported by the Open Researches Fund Program of L IESMARS(WKL(0 0 ) 0 30 2 )
文摘Clustering, in data mining, is a useful technique for discovering interesting data distributions and patterns in the underlying data, and has many application fields, such as statistical data analysis, pattern recognition, image processing, and etc. We combine sampling technique with DBSCAN algorithm to cluster large spatial databases, and two sampling based DBSCAN (SDBSCAN) algorithms are developed. One algorithm introduces sampling technique inside DBSCAN, and the other uses sampling procedure outside DBSCAN. Experimental results demonstrate that our algorithms are effective and efficient in clustering large scale spatial databases.
文摘The necessity and the feasibility of introducing attribute weight into digital fingerprinting system are given. The weighted algorithm for fingerprinting relational databases of traitor tracing is proposed. Higher weights are assigned to more significant attributes, so important attributes are more frequently fingerprinted than other ones. Finally, the robustness of the proposed algorithm, such as performance against collusion attacks, is analyzed. Experimental results prove the superiority of the algorithm.
基金supported by the National Natural Science Foundation of China (60471055)the National "863" High Technology Research and Development Program of China (2007AA01Z443)
文摘To solve the problems of shaving and reusing information in the information system, a rules-based ontology constructing approach from object-relational databases is proposed. A 3-tuple ontology constructing model is proposed first. Then, four types of ontology constructing rules including class, property, property characteristics, and property restrictions ave formalized according to the model. Experiment results described in Web ontology language prove that our proposed approach is feasible for applying in the semantic objects project of semantic computing laboratory in UC Irvine. Our approach reduces about twenty percent constructing time compared with the ontology construction from relational databases.
文摘Data acquisition and modeling are the two important, difficult and costful aspects in a Cybercity project. 2D-GIS is mature and can manage a lot of spatial data. Thus 3D-GIS should make the best of data and technology of 2D-GIS. Construction of a useful synthetic environment requires integration of multiple types of information like DEM, texture images and 3D representation of objects such as buildings. In this paper, the method for 3D city landscape data model and visualization based on integrated databases is presented. Since the data volume of raster are very huge, special strategies(for example, pyramid gridded method) must be adopted in order to manage raster data efficiently. Three different methods of data acquisition, the proper data structure and a simple modeling method are presented as well. At last, a pilot project of Shanghai Cybercity is illustrated.
基金supported by Researchers Supporting Project(No.RSP-2020/102)King Saud University,Riyadh,Saudi Arabiathe National Natural Science Foundation of China(Nos.61802031,61772454,61811530332,61811540410)+4 种基金the Natural Science Foundation of Hunan Province,China(No.2019JGYB177)the Research Foundation of Education Bureau of Hunan Province,China(No.18C0216)the“Practical Innovation and Entrepreneurial Ability Improvement Plan”for Professional Degree Graduate students of Changsha University of Science and Technology(No.SJCX201971)Hunan Graduate Scientific Research Innovation Project,China(No.CX2019694)This work is also supported by the Programs of Transformation and Upgrading of Industries and Information Technologies of Jiangsu Province(No.JITC-1900AX2038/01).
文摘As the typical peer-to-peer distributed networks, blockchain systemsrequire each node to copy a complete transaction database, so as to ensure newtransactions can by verified independently. In a blockchain system (e.g., bitcoinsystem), the node does not rely on any central organization, and every node keepsan entire copy of the transaction database. However, this feature determines thatthe size of blockchain transaction database is growing rapidly. Therefore, with thecontinuous system operations, the node memory also needs to be expanded tosupport the system running. Especially in the big data era, the increasing networktraffic will lead to faster transaction growth rate. This paper analyzes blockchaintransaction databases and proposes a storage optimization scheme. The proposedscheme divides blockchain transaction database into cold zone and hot zone usingexpiration recognition method based on Least Recently Used (LRU) algorithm. Itcan achieve storage optimization by moving unspent transaction outputs outsidethe in-memory transaction databases. We present the theoretical analysis on theoptimization method to validate the effectiveness. Extensive experiments showour proposed method outperforms the current mechanism for the blockchaintransaction databases.
基金Supported by National Natural Science Foundation of China(6 98730 2 7)
文摘Most knowledgeable people agree that networking and routing technologies have been around about 25 years. Routing is simultaneously the most complicated function of a network and the most important. It is of the same kind that more than 70% of computer application fields are MIS applications. So the challenge in building and using a MIS in the network is developing the means to find, access, and communicate large databases or multi databases systems. Because general databases are not time continuous, in fact, they can not be streaming, so we can't obtain reliable and secure quality of service by deleting some unimportant datagrams in the databases transmission. In this article, we will discuss which kind of routing protocol is the best type for large databases or multi databases systems transmission in the networks.
基金Supported by the Aeronautics Science Foundation of China (02F52033), the High-Technology Research Project of Jiangsu Province (BG2004005) and Youth Research Foundation of Qufu Normal Univer-sity(XJ02057)
文摘A weighted algorithm for watermarking relational databases for copyright protection is presented. The possibility of watermarking an attribute is assigned according to its weight decided by the owner of the database. A one-way hash function and a secret key known only to the owner of the data are used to select tuples and bits to mark. By assigning high weight to significant attributes, the scheme ensures that important attributes take more chance to be marked than less important ones. Experimental results show that the proposed scheme is robust against various forms of attacks, and has perfect immunity to subset attack.
基金Supported by National Natural Science Foundationof China (60073045)
文摘In this paper, constrained K closest pairs query is introduced, wbich retrieves the K closest pairs satisfying the given spatial constraint from two datasets. For data sets indexed by R trees in spatial databases, three algorithms are presented for answering this kind of query. Among of them, two-phase Range＋Join and Join＋Range algorithms adopt the strategy that changes the execution order of range and closest pairs queries, and constrained heap-based algorithm utilizes extended distance functions to prune search space and minimize the pruning distance. Experimental results show that constrained heap-base algorithm has better applicability and performance than two-phase algorithms.
基金Supported by the National86 3High-Tech Project!(863-306-Z705-0 2 ) National Natural Science F oundation of China!(69896240)
文摘The technique of Knowlege Discovery in Databases (KDD) to learn valuable knowledge hidden in network alarm databases is introduced. To get such knowledge, we propose an efficient method based on sliding windows (named as Slidwin) to discover different episode rules from time squential alarm data. The experimental results show that given different thresholds parameters, large amount of different rules could be discovered quickly.
基金Supported by the National Nature Science Foundation under"Outstanding Young Researchers"(495 2 5 10 1)
文摘It is a period of information explosion. Especially for spatial information science, information can be acquired through many ways, such as man made planet, aeroplane, laser, digital photogrammetry and so on. Spatial data sources are usually distributed and heterogeneous. Federated database is the best resolution for the share and interoperation of spatial database. In this paper, the concepts of federated database and interoperability are introduced. Three heterogeneous kinds of spatial data, vector, image and DEM are used to create integrated database. A data model of federated spatial databases is given.
