Commercial phosphor-converted white LEDs(pc-WLEDs)face two inherent limitations,namely blue light hazard and low color rendering index,due to the use of blue LEDs as excitation source.To address these challenges,viole...Commercial phosphor-converted white LEDs(pc-WLEDs)face two inherent limitations,namely blue light hazard and low color rendering index,due to the use of blue LEDs as excitation source.To address these challenges,violet LEDs are proposed as an alternative solution.Currently,phosphors that can be efficiently excited by violet light(with wavelengths from 400 to 420 nm)remain under development still.In this study,we utilize large language models to construct a comprehensive database of Eu^(2+)and Ce^(3+)doped phosphors for discovering novel violet-excited phosphors.A total of 822 phosphor data entries,including elemental compositions,crystal structures and excitation/emission wavelengths,have been extracted and validated from 9551 research papers.Compared with Ce^(3+)doped phosphors,the Eu^(2+)are in general more suited for violet-excited phosphors,as well as red-emitting phosphors.In particular,Eu^(2+)doped nitrides and sulfides are worth of exploration for violet-excited phosphors.This database is expected to be useful in the future development of phosphors for pc-WLEDs based on artificial intelligence methods.The datasets in this article are listed in Science Data Bank at http://doi.org/10.57760/sciencedb.34314.展开更多
tRNA-derived small RNAs(tsRNAs),as a class of regulatory small noncoding RNA,have been implicated in a wide variety of human diseases.Large amounts of tsRNA–disease associations have been identified in recent years f...tRNA-derived small RNAs(tsRNAs),as a class of regulatory small noncoding RNA,have been implicated in a wide variety of human diseases.Large amounts of tsRNA–disease associations have been identified in recent years from accumulating studies.However,repositories for cataloging the detailed information on tsRNA–disease associations are scarce.In this study,we provide a tsRNADisease database by integrating experimentally and computationally supported tsRNA–disease associations from manual curation of literatures and other related resources.tsRNADisease contains 5571 manually curated associations between 4759 tsRNAs and 166 diseases with experimental evidence from 346 studies.In addition,it also contains 5013 predicted associations between 1297 tsRNAs and 111 diseases.tsRNADisease provides a user-friendly interface to browse,retrieve,and download data conveniently.This database can improve our understanding of tsRNA deregulation in diseases and serve as a valuable resource for investigating the mechanism of disease-related tsRNAs.tsRNADisease is freely available at http://www.compgenelab.info/tsRNADisease.展开更多
Sepsis poses a serious threat to patient survival,making timely risk assessment crucial.Predicting in-hospital mortality based on clinical indicators can aid in making better clinical decisions.Previous studies have f...Sepsis poses a serious threat to patient survival,making timely risk assessment crucial.Predicting in-hospital mortality based on clinical indicators can aid in making better clinical decisions.Previous studies have focused on classifier selection but lacked a comprehensive analysis of feature selection and data preprocessing.This study optimized machine learning models for sepsis mortality prediction by:(1)comprehensively comparing feature selection and classification methods to identify the best combination,(2)building a high-performing model with fewer features,and(3)identifying key clinically relevant indicators.Methods:Using the MIMIC-III sepsis cohort,we conducted a comprehensive analysis to determine the optimal model,including data preprocessing,data balance,classifier selection,and feature selection.Feature importance was further analyzed to identify the key predictors of in-hospital mortality.Results:The proposed Synthetic Minority Oversampling Technique-Random Forest Recursive Feature Elimination-Extreme Gradient Boosting(SMOTE-(RF-RFE)-XGB)model achieved high predictive performance with a mean Area Under the Curve(AUC)of 0.8507,while reducing the number of features from 78 to 39.Compared to other feature selection methods evaluated in this study and those reported in related literature,Random Forest Recursive Feature Elimination(RF-RFE)offers the best trade-off between accuracy,feature compactness,and stability.Additionally,feature importance rankings consistently identified Acute Physiology Score Ⅲ(APS Ⅲ),Ventilation on First Day,and Depression as the top three most influential predictors,besides the Length of Stay in ICU and Hospital.Conclusions:This study addresses key gaps by conducting a comprehensive evaluation of classifiers and feature selection methods for predicting in-hospital mortality in patients with sepsis.The proposed SMOTE-(RFRFE)-XGB model achieved a high predictive performance and stability with a compact feature set.APS III,Ventilation on First Day,and Depression were consistently identified as key predictors besides Length of Stay in ICU and Hospital.展开更多
Background:The purpose of this study was to analyze and classify adverse drug events(ADEs)related to ceftazidime/avibactam reported in the Food and Drug Administration Adverse Event Reporting System(FAERS)database and...Background:The purpose of this study was to analyze and classify adverse drug events(ADEs)related to ceftazidime/avibactam reported in the Food and Drug Administration Adverse Event Reporting System(FAERS)database and to evaluate their potential safety signals since the drug’s market introduction.Methods:This analysis systematically extracted and filtered FAERS data for ceftazidime/avibactam from its market launch in 2015 to the last quarter of 2024,utilizing the Medical Dictionary for Regulatory Activities(MedDRA)terminology for ADE recoding.The analysis employed the reporting odds ratio(ROR)method to assess the strength of ADE signals and to identify significant diseases associated with infections,the hepatobiliary system,the urinary system,and the nervous system.Results:A review of 540 adverse reaction reports revealed significant signals of adverse effects related to infections,hepatobiliary disorders,urinary system issues,and neurological impairments,including pathogen resistance,liver and kidney function impairment,encephalopathy,thrombocytopenia,and toxic epidermal necrolysis.However,these issues require further clinical attention.Conclusion:Ceftazidime/avibactam is associated with a range of adverse reactions,necessitating enhanced clinical monitoring,particularly in patients with underlying liver or kidney dysfunction.Continuous risk assessment and vigilant monitoring are critical for its clinical use.However,this study is limited by inherent reporting biases and confounders associated with the spontaneous reporting database(FAERS).Future research should validate these signals through prospective cohort and mechanistic studies and explore personalized risk management strategies for high-risk populations.展开更多
Primary liver cancer (PLC) is a major global healthchallenge, ranking as the sixth most common andthird most fatal malignancy worldwide, according toGLOBOCAN 2022 estimates[1]. This high mortalityrate underscores the ...Primary liver cancer (PLC) is a major global healthchallenge, ranking as the sixth most common andthird most fatal malignancy worldwide, according toGLOBOCAN 2022 estimates[1]. This high mortalityrate underscores the aggressive nature of thedisease and the significant burden it places on globalhealthcare systems. Although primary preventionremains the cornerstone of liver cancer control,improving outcomes for patients already diagnosedis equally critical for mitigating the impact of thedisease.展开更多
Robust cooperative unmanned aerial vehicle(UAV)formation in complex 3D environments is hampered by reward sparsity and inefficient collaboration.To address this,we propose context-aware relational agent learning(CORAL...Robust cooperative unmanned aerial vehicle(UAV)formation in complex 3D environments is hampered by reward sparsity and inefficient collaboration.To address this,we propose context-aware relational agent learning(CORAL),a novel multi-agent deep reinforcement learning framework.CORAL synergistically integrates two modules:(1)a novelty-based intrinsic reward module to drive efficient exploration and(2)an explicit relational learning module that allows agents to predict peer intentions and enhance coordination.Built on a multi-agent Actor-Critic architecture,CORAL enables agents to balance self-interest with group objectives.Comprehensive evaluations in a high-fidelity simulation show that our method significantly outperforms state-of-theart baselines like multi-agent deep deterministic policy gradient(MADDPG)and monotonic value function factorisation for deep multi-agent reinforcement learning(QMIX)in path planning efficiency,collision avoidance,and scalability.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
For a transaction processing system to operate effectively and efficiently in cloud environments, it is important to distribute huge amount of data while guaranteeing the ACID （atomic, consistent, isolated, and dura...For a transaction processing system to operate effectively and efficiently in cloud environments, it is important to distribute huge amount of data while guaranteeing the ACID （atomic, consistent, isolated, and durable） properties. Moreover, database partition and migration tools can help transplanting conventional relational database systems to the cloud environment rather than rebuilding a new system. This paper proposes a database distribution management （DBDM） system, which partitions or replicates the data according to the transaction behaviors of the application system. The principle strategy of DBDM is to keep together the data used in a single transaction, and thus, avoiding massive transmission of records in join operations. The proposed system has been implemented successfully. The preliminary experiments show that the DBDM performs the database partition and migration effectively. Also, the DBDM system is modularly designed to adapt to different database management system （DBMS） or different partition algorithms.展开更多
This paper presents a development o f the extended Cellular Automata9CA),based on relational databases(RDB),to model dynamic interactions amon g spatial objects.The integration o f Geographical Information System(GIS)...This paper presents a development o f the extended Cellular Automata9CA),based on relational databases(RDB),to model dynamic interactions amon g spatial objects.The integration o f Geographical Information System(GIS)and CA has the great advantage of simu lationg geographical processes.But standard CA has some restrictions i n cellular shape and neighbourhood and neighbour rules,which restrict the CA’s ability to simulate complex,real world environ-ments.This paper discusses a cell’s spatialrelationbasedonthe spatialobject’s geometricalandmon-geometricalc haracter-istics,and extends the cell’s neighbour definition,and considers that the cell’s neighbour lies in the forms of not on ly spa-tial adjacency but also attribute co rrelation.This paper then puts forw ard that spatial relations between t wo different cells can be divided into three types,including spatial adjacency,neighbour hood and complicated separation.Ba sed on tradition-al ideas,it is impossible to settle CA’s restrictions completely.RDB-based CA is an academic experiment,in which some fields ard desighed to describe the essential information needed to define and select a cell’s neighbour.The culture innovation diffusion system has mul tiple forms of space diffusion and in herited characteristics that the RD B-based CA is capable of simulating more effectiv ely.Finally this paper details a successful case study on the diffusion o f fashion wear trends.Compared to the original CA,the RDB-based CA is a more natural and efficient representation of human k nowl-edge over space,and is an effective t ol in simulation complex systems that have multiple forms of spatial diff usion.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
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
Enhanced understanding of how sampling techniques affect estimates of the global U-Pb age-distribution have, in turn, constrained U-Pb database design. Recent studies indicate that each continent has a unique age-dist...Enhanced understanding of how sampling techniques affect estimates of the global U-Pb age-distribution have, in turn, constrained U-Pb database design. Recent studies indicate that each continent has a unique age-distribution, as determined by zircon ages dated by the U-Pb isotope method. Likewise, broad regions within a continent also exhibit diverse age-distributions. To achieve a reliable estimate of the global distribution, the heterogenous composition of the continental crust requires sampling as many regions as feasibly possible. To attain this goal, and to provide a method for calculating age histograms, the records from a recent global U-Pb compilation are supplemented with 281,631 new records. These additions increase the database size to 700,598 records. In addition, the data are now restructured and made available as a relational database. After filtering the records by the six age-models included with the database, the results reveal two problems that might generally be unrecognized. First, an abrupt switch in the best-age at any given point(such as 1000 Ma) from ^(206)Pb/^(238)U ages to ^(207)Pb/^(206)Pb ages artificially depresses the age-distribution at the cutoff point. Second, rejecting analyses based on either absolute discordance or the magnitude of 2σ precision errors artificially depresses the age-distribution between 900 Ma and 2000 Ma. The results indicate that, when estimating the global U-Pb age-distribution, the methods for determining best-age and for rejecting records both require some attention. Possible solutions include using either an Accuracy Model or a Precision Model for estimating best-age, and then including all U-Pb records in the estimate, rather than rejecting any of them.展开更多
This paper presents a cadastral spatial data storage structure based on relational database,the method and the procedure to realize it.The paper consists of three parts.In the first part,some existing problems in some...This paper presents a cadastral spatial data storage structure based on relational database,the method and the procedure to realize it.The paper consists of three parts.In the first part,some existing problems in some developed cadastral management systems are discussed.These problems are the following four.1) The security of cadastral spatial data is difficult to be assured.2) It is difficult to varify cadastral data and the integrality of cadastral data is difficult to be kept.3) To transmit and share cadastral data is difficult.4) The efficiency of data access is low.In the second part,the feasibility of using relational database to store spatial data is analyzed and a new cadastral spatial data storage structure is presented.At the same time,the related table structures and field descriptions are given,and then the merits and demerits of this storage structure are analyzed in detail.In the last part,through a real example,the detailed methods to make the new storage structure a reality are given.Moreover,some involving key techniques of the new storage structure are discussed.These techniques are:1) the application of database transaction,2) the application of database trigger,3) and the application of secure recovery of database.展开更多
Compression is an intuitive way to boost the performance of a database system. However, compared with other physical database design techniques, compression consumes large amount of CPU power. There is a trade-off bet...Compression is an intuitive way to boost the performance of a database system. However, compared with other physical database design techniques, compression consumes large amount of CPU power. There is a trade-off between the re- duction of disk access and the overhead of CPU processing. Automatic design and adaptive administration of database systems are widely demanded, and the automatic selection of compression schema to compromise the trade-off is very important. In this paper, we present a model with novel techniques to integrate a rapidly convergent agent-based evolution framework, i.e. the SWAF (SWarm Algorithm Framework), into adaptive attribute compression for relational database. The model evolutionally consults statistics of CPU load and IO bandwidth to select compression schemas considering both aspects of the trade-off. We have im- plemented a prototype model on Oscar RDBMS with experiments highlighting the correctness and efficiency of our techniques.展开更多
In this paper,the entity_relation data model for integrating spatio_temporal data is designed.In the design,spatio_temporal data can be effectively stored and spatiao_temporal analysis can be easily realized.
We developed a parallel object relational DBMS named PORLES. It uses BSP model as its parallel computing model, and monoid calculus as its basis of data model. In this paper, we introduce its data model, parallel que...We developed a parallel object relational DBMS named PORLES. It uses BSP model as its parallel computing model, and monoid calculus as its basis of data model. In this paper, we introduce its data model, parallel query optimization, transaction processing system and parallel access method in detail.展开更多
Data transformation is the core process in migrating database from relational database to NoSQL database such as column-oriented database. However,there is no standard guideline for data transformation from relational...Data transformation is the core process in migrating database from relational database to NoSQL database such as column-oriented database. However,there is no standard guideline for data transformation from relational database toNoSQL database. A number of schema transformation techniques have been proposed to improve data transformation process and resulted better query processingtime when compared to the relational database query processing time. However,these approaches produced redundant tables in the resulted schema that in turnconsume large unnecessary storage size and produce high query processing timedue to the generated schema with redundant column families in the transformedcolumn-oriented database. In this paper, an efficient data transformation techniquefrom relational database to column-oriented database is proposed. The proposedschema transformation technique is based on the combination of denormalizationapproach, data access pattern and multiple-nested schema. In order to validate theproposed work, the proposed technique is implemented by transforming data fromMySQL database to MongoDB database. A benchmark transformation techniqueis also performed in which the query processing time and the storage size arecompared. Based on the experimental results, the proposed transformation technique showed significant improvement in terms query processing time and storagespace usage due to the reduced number of column families in the column-orienteddatabase.展开更多
This paper focused on the integration of case base and relational database management system (RDBMS). The organizational and commercial impact will be far greater if the case based reasoning (CBR) system is integrated...This paper focused on the integration of case base and relational database management system (RDBMS). The organizational and commercial impact will be far greater if the case based reasoning (CBR) system is integrated with main stream information system, which is exemplified by RDBMS. The scalability, security and robustness provided by a commercial RDBMS facilitate the CBR system to manage the case base. The virtual table in relational database (RDB) is important for CBR systems to implement the flexibility of case template. It was discussed how to implement a flexible and succinct case template, and a mapping model between case template and RDB was proposed. The key idea is to build the case as the virtual view of underlying data.展开更多
In this paper, we propose a new method based on index to realize IR-style Chinese keyword search with ranking strategies in relational databases. This method creates an index by using the related information of tuple ...In this paper, we propose a new method based on index to realize IR-style Chinese keyword search with ranking strategies in relational databases. This method creates an index by using the related information of tuple words and presents a ranking strategy in terms of the nature of Chinese words. For a Chinese keyword query, the index is used to match query search words and the tuple words in index quickly, and to compute similarities between the query and tuples by the ranking strategy, and then the set of identifiers of candidate tuples is generated. Thus, we retrieve top-N results of the query using SQL selection statements and output the ranked answers according to the similarities. The experimental results show that our method is efficient and effective.展开更多
基金National Key Research and Development Program of China(2021YFB3500501)。
文摘Commercial phosphor-converted white LEDs(pc-WLEDs)face two inherent limitations,namely blue light hazard and low color rendering index,due to the use of blue LEDs as excitation source.To address these challenges,violet LEDs are proposed as an alternative solution.Currently,phosphors that can be efficiently excited by violet light(with wavelengths from 400 to 420 nm)remain under development still.In this study,we utilize large language models to construct a comprehensive database of Eu^(2+)and Ce^(3+)doped phosphors for discovering novel violet-excited phosphors.A total of 822 phosphor data entries,including elemental compositions,crystal structures and excitation/emission wavelengths,have been extracted and validated from 9551 research papers.Compared with Ce^(3+)doped phosphors,the Eu^(2+)are in general more suited for violet-excited phosphors,as well as red-emitting phosphors.In particular,Eu^(2+)doped nitrides and sulfides are worth of exploration for violet-excited phosphors.This database is expected to be useful in the future development of phosphors for pc-WLEDs based on artificial intelligence methods.The datasets in this article are listed in Science Data Bank at http://doi.org/10.57760/sciencedb.34314.
基金supported by the National Natural Science Foundation of China(91959106)the Foundation of the Shanghai Municipal Education Commission(24RGZNC02)+4 种基金Shanghai Key Laboratory of Intelligent Information Processing,Fudan University(IIPL-2025-RD3-02)Key University Science Research Project of Anhui Province(2023AH030108)Climbing Peak Training Program for Innovative Technology team of Yijishan Hospital,Wannan Medical College(PF201904)Peak Training Program for Scientific Research of Yijishan Hospital,Wannan Medical College(GF2019G15)the talent project of the First Affiliated Hospital of Wannan Medical College(Yijishan Hospital of Wannan Medical College)(YR202422).
文摘tRNA-derived small RNAs(tsRNAs),as a class of regulatory small noncoding RNA,have been implicated in a wide variety of human diseases.Large amounts of tsRNA–disease associations have been identified in recent years from accumulating studies.However,repositories for cataloging the detailed information on tsRNA–disease associations are scarce.In this study,we provide a tsRNADisease database by integrating experimentally and computationally supported tsRNA–disease associations from manual curation of literatures and other related resources.tsRNADisease contains 5571 manually curated associations between 4759 tsRNAs and 166 diseases with experimental evidence from 346 studies.In addition,it also contains 5013 predicted associations between 1297 tsRNAs and 111 diseases.tsRNADisease provides a user-friendly interface to browse,retrieve,and download data conveniently.This database can improve our understanding of tsRNA deregulation in diseases and serve as a valuable resource for investigating the mechanism of disease-related tsRNAs.tsRNADisease is freely available at http://www.compgenelab.info/tsRNADisease.
文摘Sepsis poses a serious threat to patient survival,making timely risk assessment crucial.Predicting in-hospital mortality based on clinical indicators can aid in making better clinical decisions.Previous studies have focused on classifier selection but lacked a comprehensive analysis of feature selection and data preprocessing.This study optimized machine learning models for sepsis mortality prediction by:(1)comprehensively comparing feature selection and classification methods to identify the best combination,(2)building a high-performing model with fewer features,and(3)identifying key clinically relevant indicators.Methods:Using the MIMIC-III sepsis cohort,we conducted a comprehensive analysis to determine the optimal model,including data preprocessing,data balance,classifier selection,and feature selection.Feature importance was further analyzed to identify the key predictors of in-hospital mortality.Results:The proposed Synthetic Minority Oversampling Technique-Random Forest Recursive Feature Elimination-Extreme Gradient Boosting(SMOTE-(RF-RFE)-XGB)model achieved high predictive performance with a mean Area Under the Curve(AUC)of 0.8507,while reducing the number of features from 78 to 39.Compared to other feature selection methods evaluated in this study and those reported in related literature,Random Forest Recursive Feature Elimination(RF-RFE)offers the best trade-off between accuracy,feature compactness,and stability.Additionally,feature importance rankings consistently identified Acute Physiology Score Ⅲ(APS Ⅲ),Ventilation on First Day,and Depression as the top three most influential predictors,besides the Length of Stay in ICU and Hospital.Conclusions:This study addresses key gaps by conducting a comprehensive evaluation of classifiers and feature selection methods for predicting in-hospital mortality in patients with sepsis.The proposed SMOTE-(RFRFE)-XGB model achieved a high predictive performance and stability with a compact feature set.APS III,Ventilation on First Day,and Depression were consistently identified as key predictors besides Length of Stay in ICU and Hospital.
基金Intramural Project of The First Affiliated Hospital of Guangxi University of Chinese Medicine(2018QN008).
文摘Background:The purpose of this study was to analyze and classify adverse drug events(ADEs)related to ceftazidime/avibactam reported in the Food and Drug Administration Adverse Event Reporting System(FAERS)database and to evaluate their potential safety signals since the drug’s market introduction.Methods:This analysis systematically extracted and filtered FAERS data for ceftazidime/avibactam from its market launch in 2015 to the last quarter of 2024,utilizing the Medical Dictionary for Regulatory Activities(MedDRA)terminology for ADE recoding.The analysis employed the reporting odds ratio(ROR)method to assess the strength of ADE signals and to identify significant diseases associated with infections,the hepatobiliary system,the urinary system,and the nervous system.Results:A review of 540 adverse reaction reports revealed significant signals of adverse effects related to infections,hepatobiliary disorders,urinary system issues,and neurological impairments,including pathogen resistance,liver and kidney function impairment,encephalopathy,thrombocytopenia,and toxic epidermal necrolysis.However,these issues require further clinical attention.Conclusion:Ceftazidime/avibactam is associated with a range of adverse reactions,necessitating enhanced clinical monitoring,particularly in patients with underlying liver or kidney dysfunction.Continuous risk assessment and vigilant monitoring are critical for its clinical use.However,this study is limited by inherent reporting biases and confounders associated with the spontaneous reporting database(FAERS).Future research should validate these signals through prospective cohort and mechanistic studies and explore personalized risk management strategies for high-risk populations.
基金National Key Project of Research and Development Program of China[2021YFC2500404].
文摘Primary liver cancer (PLC) is a major global healthchallenge, ranking as the sixth most common andthird most fatal malignancy worldwide, according toGLOBOCAN 2022 estimates[1]. This high mortalityrate underscores the aggressive nature of thedisease and the significant burden it places on globalhealthcare systems. Although primary preventionremains the cornerstone of liver cancer control,improving outcomes for patients already diagnosedis equally critical for mitigating the impact of thedisease.
基金supported by the STI 2030 Major Projects(No.2022ZD0208804)the National Natural Science Foundation of China(No.62473017)。
文摘Robust cooperative unmanned aerial vehicle(UAV)formation in complex 3D environments is hampered by reward sparsity and inefficient collaboration.To address this,we propose context-aware relational agent learning(CORAL),a novel multi-agent deep reinforcement learning framework.CORAL synergistically integrates two modules:(1)a novelty-based intrinsic reward module to drive efficient exploration and(2)an explicit relational learning module that allows agents to predict peer intentions and enhance coordination.Built on a multi-agent Actor-Critic architecture,CORAL enables agents to balance self-interest with group objectives.Comprehensive evaluations in a high-fidelity simulation show that our method significantly outperforms state-of-theart baselines like multi-agent deep deterministic policy gradient(MADDPG)and monotonic value function factorisation for deep multi-agent reinforcement learning(QMIX)in path planning efficiency,collision avoidance,and scalability.
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 Taiwan Ministry of Economic Affairs and Institute for Information Industry under the project titled "Fundamental Industrial Technology Development Program (1/4)"
文摘For a transaction processing system to operate effectively and efficiently in cloud environments, it is important to distribute huge amount of data while guaranteeing the ACID （atomic, consistent, isolated, and durable） properties. Moreover, database partition and migration tools can help transplanting conventional relational database systems to the cloud environment rather than rebuilding a new system. This paper proposes a database distribution management （DBDM） system, which partitions or replicates the data according to the transaction behaviors of the application system. The principle strategy of DBDM is to keep together the data used in a single transaction, and thus, avoiding massive transmission of records in join operations. The proposed system has been implemented successfully. The preliminary experiments show that the DBDM performs the database partition and migration effectively. Also, the DBDM system is modularly designed to adapt to different database management system （DBMS） or different partition algorithms.
基金Under the auspices of the National Natural Science Foundation of China(No.40071071)
文摘This paper presents a development o f the extended Cellular Automata9CA),based on relational databases(RDB),to model dynamic interactions amon g spatial objects.The integration o f Geographical Information System(GIS)and CA has the great advantage of simu lationg geographical processes.But standard CA has some restrictions i n cellular shape and neighbourhood and neighbour rules,which restrict the CA’s ability to simulate complex,real world environ-ments.This paper discusses a cell’s spatialrelationbasedonthe spatialobject’s geometricalandmon-geometricalc haracter-istics,and extends the cell’s neighbour definition,and considers that the cell’s neighbour lies in the forms of not on ly spa-tial adjacency but also attribute co rrelation.This paper then puts forw ard that spatial relations between t wo different cells can be divided into three types,including spatial adjacency,neighbour hood and complicated separation.Ba sed on tradition-al ideas,it is impossible to settle CA’s restrictions completely.RDB-based CA is an academic experiment,in which some fields ard desighed to describe the essential information needed to define and select a cell’s neighbour.The culture innovation diffusion system has mul tiple forms of space diffusion and in herited characteristics that the RD B-based CA is capable of simulating more effectiv ely.Finally this paper details a successful case study on the diffusion o f fashion wear trends.Compared to the original CA,the RDB-based CA is a more natural and efficient representation of human k nowl-edge over space,and is an effective t ol in simulation complex systems that have multiple forms of spatial diff usion.
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 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Enhanced understanding of how sampling techniques affect estimates of the global U-Pb age-distribution have, in turn, constrained U-Pb database design. Recent studies indicate that each continent has a unique age-distribution, as determined by zircon ages dated by the U-Pb isotope method. Likewise, broad regions within a continent also exhibit diverse age-distributions. To achieve a reliable estimate of the global distribution, the heterogenous composition of the continental crust requires sampling as many regions as feasibly possible. To attain this goal, and to provide a method for calculating age histograms, the records from a recent global U-Pb compilation are supplemented with 281,631 new records. These additions increase the database size to 700,598 records. In addition, the data are now restructured and made available as a relational database. After filtering the records by the six age-models included with the database, the results reveal two problems that might generally be unrecognized. First, an abrupt switch in the best-age at any given point(such as 1000 Ma) from ^(206)Pb/^(238)U ages to ^(207)Pb/^(206)Pb ages artificially depresses the age-distribution at the cutoff point. Second, rejecting analyses based on either absolute discordance or the magnitude of 2σ precision errors artificially depresses the age-distribution between 900 Ma and 2000 Ma. The results indicate that, when estimating the global U-Pb age-distribution, the methods for determining best-age and for rejecting records both require some attention. Possible solutions include using either an Accuracy Model or a Precision Model for estimating best-age, and then including all U-Pb records in the estimate, rather than rejecting any of them.
文摘This paper presents a cadastral spatial data storage structure based on relational database,the method and the procedure to realize it.The paper consists of three parts.In the first part,some existing problems in some developed cadastral management systems are discussed.These problems are the following four.1) The security of cadastral spatial data is difficult to be assured.2) It is difficult to varify cadastral data and the integrality of cadastral data is difficult to be kept.3) To transmit and share cadastral data is difficult.4) The efficiency of data access is low.In the second part,the feasibility of using relational database to store spatial data is analyzed and a new cadastral spatial data storage structure is presented.At the same time,the related table structures and field descriptions are given,and then the merits and demerits of this storage structure are analyzed in detail.In the last part,through a real example,the detailed methods to make the new storage structure a reality are given.Moreover,some involving key techniques of the new storage structure are discussed.These techniques are:1) the application of database transaction,2) the application of database trigger,3) and the application of secure recovery of database.
基金Project (No. 2004AA4Z3010) supported by the National Hi-Tech Research and Development Program (863) of China
文摘Compression is an intuitive way to boost the performance of a database system. However, compared with other physical database design techniques, compression consumes large amount of CPU power. There is a trade-off between the re- duction of disk access and the overhead of CPU processing. Automatic design and adaptive administration of database systems are widely demanded, and the automatic selection of compression schema to compromise the trade-off is very important. In this paper, we present a model with novel techniques to integrate a rapidly convergent agent-based evolution framework, i.e. the SWAF (SWarm Algorithm Framework), into adaptive attribute compression for relational database. The model evolutionally consults statistics of CPU load and IO bandwidth to select compression schemas considering both aspects of the trade-off. We have im- plemented a prototype model on Oscar RDBMS with experiments highlighting the correctness and efficiency of our techniques.
基金Project supported by the National Surveying Technical Fund(No.200_07)
文摘In this paper,the entity_relation data model for integrating spatio_temporal data is designed.In the design,spatio_temporal data can be effectively stored and spatiao_temporal analysis can be easily realized.
文摘We developed a parallel object relational DBMS named PORLES. It uses BSP model as its parallel computing model, and monoid calculus as its basis of data model. In this paper, we introduce its data model, parallel query optimization, transaction processing system and parallel access method in detail.
基金supported by Universiti Putra Malaysia Grant Scheme(Putra Grant)(GP/2020/9692500).
文摘Data transformation is the core process in migrating database from relational database to NoSQL database such as column-oriented database. However,there is no standard guideline for data transformation from relational database toNoSQL database. A number of schema transformation techniques have been proposed to improve data transformation process and resulted better query processingtime when compared to the relational database query processing time. However,these approaches produced redundant tables in the resulted schema that in turnconsume large unnecessary storage size and produce high query processing timedue to the generated schema with redundant column families in the transformedcolumn-oriented database. In this paper, an efficient data transformation techniquefrom relational database to column-oriented database is proposed. The proposedschema transformation technique is based on the combination of denormalizationapproach, data access pattern and multiple-nested schema. In order to validate theproposed work, the proposed technique is implemented by transforming data fromMySQL database to MongoDB database. A benchmark transformation techniqueis also performed in which the query processing time and the storage size arecompared. Based on the experimental results, the proposed transformation technique showed significant improvement in terms query processing time and storagespace usage due to the reduced number of column families in the column-orienteddatabase.
文摘This paper focused on the integration of case base and relational database management system (RDBMS). The organizational and commercial impact will be far greater if the case based reasoning (CBR) system is integrated with main stream information system, which is exemplified by RDBMS. The scalability, security and robustness provided by a commercial RDBMS facilitate the CBR system to manage the case base. The virtual table in relational database (RDB) is important for CBR systems to implement the flexibility of case template. It was discussed how to implement a flexible and succinct case template, and a mapping model between case template and RDB was proposed. The key idea is to build the case as the virtual view of underlying data.
文摘In this paper, we propose a new method based on index to realize IR-style Chinese keyword search with ranking strategies in relational databases. This method creates an index by using the related information of tuple words and presents a ranking strategy in terms of the nature of Chinese words. For a Chinese keyword query, the index is used to match query search words and the tuple words in index quickly, and to compute similarities between the query and tuples by the ranking strategy, and then the set of identifiers of candidate tuples is generated. Thus, we retrieve top-N results of the query using SQL selection statements and output the ranked answers according to the similarities. The experimental results show that our method is efficient and effective.
