Automated Performance Tuning of Data Management Systems with Materializations and Indices

Automated performance tuning of data management systems offer various benefits such as improved performance, declined administration costs, and reduced workloads to database administrators (DBAs). Currently, DBAs tune the performance of database systems with a little help from the database servers. In this paper, we propose a new technique for automated performance tuning of data management systems. Firstly, we show how to use the periods of low workload time for performance improvements in the periods of high workload time. We demonstrate that extensions of a database system with materialised views and indices when a workload is low may contribute to better performance for a successive period of high workload. The paper proposes several online algorithms for continuous processing of estimated database workloads and for the discovery of the best plan for materialised view and index database extensions and of elimination of the extensions that are no longer needed. We present the results of experiments that show how the proposed automated performance tuning technique improves the overall performance of a data management system.

System View of Product Data Management and Its Application

A product data management system for a manufacturing enterprise is to make sure that the proper product data can be communicated to the right people at the right time.This paper describes a system analysis paradigm for data analysis in a product data management(PDM)development.Three aspects of the paradigm,i.e.,function,structure and behavior are rep- resented.The use of the paradigm explains why so many kinds of objects are necessary in a commercial database matrix and what models are available for developing a PDM application.As another result,a lot of models are derived from the analysis of product data system paradigm to model product data and PDM database definitions.

DID Code:A Bridge Connecting the Materials Genome Engineering Database w让h Inheritable Integrated Intelligent Manufacturing

A data identifier(DID)is an essential tag or label in all kinds of databases—particularly those related to integrated computational materials engineering(ICME),inheritable integrated intelligent manufacturing(I3M),and the Industrial Internet ofThings.With the guidance and quick acceleration of the developme nt of advanced materials,as envisioned by official documents worldwide,more investigations are required to construct relative numerical standards for material informatics.This work proposes a universal DID format consisting of a set of build chains,which aligns with the classical form of identifier in both international and national standards,such as ISO/IEC 29168-1:2000,GB/T 27766-2011,GA/T 543.2-2011,GM/T 0006-2012,GJB 7365-2011,SL 325-2014,SL 607-201&WS 363.2-2011,and QX/T 39-2005.Each build chain is made up of capital letters and numbers,with no symbols.Moreover,the total length of each build chain is not restricted,which follows the formation of the Universal Coded Character Set in the international standard of ISO/IEC 10646.Based on these rules,the proposed DID is flexible and convenient for extendi ng and sharing in and between various cloud-based platforms.Accordingly,classical two-dimensional(2D)codes,including the Hanxin Code,Lots Perception Matrix(LP)Code,Quick Response(Q.R)code,Grid Matrix(GM)code,and Data Matrix(DM)Code,can be constructed and precisely recognized and/or decoded by either smart phones or specific machines.By utilizing these 2D codes as the fingerprints of a set of data linked with cloud-based platforms,progress and updates in the composition-processing-structure-property-performance workflow process can be tracked spontaneously,paving a path to accelerate the discovery and manufacture of advanced materials and enhance research productivity,performance,and collaboration.

Accomplishment and challenge of materials database toward big data

The history and current status of materials data activities from handbook to database are reviewed, with introduction to some important products. Through an example of prediction of interfacial thermal resistance based on data and data science methods, we show the advantages and potential of material informatics to study material issues which are too complicated or time consuming for conventional theoretical and experimental methods. Materials big data is the fundamental of material informatics. The challenges and strategy to construct materials big data are discussed, and some solutions are proposed as the results of our experiences to construct National Institute for Materials Science（NIMS） materials databases.

Materials databases for the computational materials scientist

Until recently, many computational materials scientists have shown little interest in materials databases. This is now changing be-cause the amount of computational data is rapidly increasing and the potential for data mining provides unique opportunities for discovery and optimization. Here, a few examples of such opportunities are discussed relating to structural analysis and classification, discovery of correlations between materials properties, and discovery of unsuspected compounds.

Development of materials database system for cae system of heat treatment based on data mining technology

Computer simulation for materials processing needs a huge database containing a great deal of various physical properties of materials. In order to employ the accumulated large data on materials heat treatment in the past years, it is significant to develop an intelligent database system. Based on the data mining technology for data analysis, an intelligent database web tool system of computer simulation for heat treatment process named as IndBASEweb-HT was built up. The architecture and the arithmetic of this system as well as its application were introduced.

Database Management System Construction for the Evaluation Results of Intensive Land Use in the Development Areas of Hunan Province

Using spatial data integration and database technology,analyzing and integrating the assessment results in all the development zones at different time in Hunan Province,the paper is intended to construct the database and managerial system for the assessment results of land use intensity in development zones,thus formulating"one map"of Hunan Development zones and realizing the integrated management and application of the assessment results in all the development zones at any time of Hunan above the provincial level.It has been proved that the system has good application effect and promising development in land management for land management departments and development zones.

Forensic data management and database systems in forensic investigations for cases of missing and unidentified persons in Brazil

Forensic investigations,especially those related to missing persons and unidentified remains,produce different types of data that must be managed and understood.The data collected and produced are extensive and originate from various sources:the police,non-governmental organizations(NGOs),medical examiner offices,specialised forensic teams,family members,and others.Some examples of information include,but are not limited to,the investigative background information,excavation data of burial sites,antemortem data on missing persons,and postmortem data on the remains of unidentified individuals.These complex data must be stored in a secured place,analysed,compared,shared,and then reported to the investigative actors and the public,especially the families of missing persons,who should be kept informed of the investigation.Therefore,a data management system with the capability of performing the tasks relevant to the goals of the investigation and the identification of an individual,while respecting the deceased and their families,is critical for standardising investigations.Data management is crucial to assure the quality of investigative processes,and it must be recognised as a holistic integrated system.The aim of this article is to discuss some of the most important components of an effective forensic data management system.The discussion is enriched by examples,challenges,and lessons learned from the erratic development and launching of databases for missing and unidentified persons in Brazil.The main objective of this article is to bring attention to the urgent need for an effective and integrated system in Brazil.

Study on Material ManagementSystem of Coal Enterprise Basedon Data Warehouse

On the bas is of the reality of material supply management of the coal enterprise, this paper expounds plans of material management systems based on specific IT, and indicates the deficiencies, the problems of them and the necessity of improving them. The structure, models and data organizing schema of the material management decision support system are investigated based on a new data management technology (data warehousing technology).

Application Research on Big Data in Material Bidding and Procurement Management

The 21st century is an era of rapid development of informatization.Under the background of the development of this era,people are increasingly researching the application of information technology.The application of big data technology is the development and application trend of an information technology formed after the rapid development of modem information technology.Big data technology has been applied to the development of many industries,including the material bidding and procurement management as well.With the aid of scientific analysis of big data,it is possible to help material procurement management to analyze the corresponding bidding procurement information,which is an important guarantee for improving its bidding procurement management capabilities.In view of this,this article has conducted special research on the application of big data in material bidding and procurement management,hoping to provide references for the application of big data technology in material bidding and procurement management with the help of the research in this article.

A new product family mining method based on PLM database

Product family(PF) is the most important part of product platform. A new method is proposed to mine PF based on multi-space product data in PLM database. Product structure tree(PST) and bill of material(BOM) are used as the data source. A PF can be obtained by mining physics space, logic space and attribute space of product data. In this work, firstly, a PLM database is described, consisting of data organization form, data structure, and data characteristics. Then the PF mining method introduces the sequence alignment techniques used in bio-informatics, which mainly includes data pre-processing, regularization, mining algorithm and cluster analysis. Finally, the feasibility and effectiveness of the proposed method are verified by a case study of high and middle pressure valve, demonstrating a feasible method to obtain PF from PLM database.

A MAPPING APPROACH TO RESOLVING SCHEMA INCOMPATIBILITY IN A FEDERATED DATABASE SYSTEM

Schema incompatibility is a major challenge to a federated database systemfor data sharing among heterogeneous,multiple and autonomous databases.This paperpresents a mapping approach based on import schema,export schema and domain conver-sion function,through which schema incompatibility problems such as naming conflict,domain incompatibility and entity definition incompatibility can be resolved effectively.The implementation techniques are also discussed.

Hypertext Technique and its Application to Engineering Data Management

Since the late of previous decade, hypertext technique has been applied in many areas. A hypertext data model with version control which is applied to a digital delivery for engineering documents named Optical Disk based Electronic Archives Management System(ODEAMS) is presented first and it has successfully solved some problems in engineering data management. Then, this paper describes some details to implement the hypertext network in ODEAMS after introducing the requirements and characters of engineering data management.

An Open Architecture and Implementation for Product Data Management

In this paper, an open architecture and its implementation for product data management are presented. The system architecture, product data definition model, and a set of components of the architecture are discussed in detail. Especially, the principle and some mechanism of one of the components, an object oriented database management system GH-EODB, are discussed in more detail. The architecture is extensible and adaptable.

Construction of databases:advances and significance in clinical research

Widely used in clinical research, the database is a new type of data management automation technology and the most efficient tool for data management. In this article, we first explain some basic concepts, such as the definition, classification, and establishment of databases. Afterward, the workflow for establishing databases, inputting data, verifying data, and managing databases is presented. Meanwhile, by discussing the application of databases in clinical research, we illuminate the important role of databases in clinical research practice. Lastly, we introduce the reanalysis of randomized controlled trials(RCTs) and cloud computing techniques, showing the most recent advancements of databases in clinical research.

Development on management and sharing of data collected in Chinese Antarctic and Arctic Research Expeditions

Combined with the current status of Antarctic data management and the characteristics of polar science data resulted from Chinese Antarctic and Arctic Research Expeditions, the Chinese Polar Science Database System(CPSDS) has been designed and established in 2002. The infrastructure, technical standard, mechanism of sharing data of this system are reviewed in this article. Meanwhile, the development of Chinese polar data management is summarized. As the metadata is the powerful and useful tool for managing and disseminating scientific data, the metadata is also used as “search engine” of CPSDS. Besides, the trend of data management and sharing is also discussed.

The Development of a PC Based Platform for Experimental Data Management

Acomputerized platform for multi-channel physiological signals is developed in our lab to highly improve the recording and review for the output of The Polygraph System. The platform mainly consists of a Pentium III PC and a high speed A/D converter and is supported by Visual Basic 6.0 and Microsoft Access 2 000. The platform has powerful functions for data acquisition, real-time waveform display and review. It has proved its reliability and flexibility through practical animal experiments. Besides, its modulized program design provides interfaces for further data processing and analysis.

Design and Implementation of Highly Secure Residents Management System Using Blockchain

This article presents the design and implementation of highly secure and reliable database system for resident records management system using blockchain technology. Blockchain provides highly secure and reliable data access environment. In blockchain, several data fragments are packed into one block and all blocks are connected to form the chain of blocks. In our prototype, each event of resident such as birth, moving, employment and so on, is assigned to data fragment and certain amount of data fragment, says 20 fragments are packed into block. We also developed the web application interface to avoid installing any applications in users’ PC or smartphone. Prototype development proved the possibility to use the blockchain technology to large amount of data management system with highly secure and reliable features.

User Instructions for the Dynamic Database of Solid-State Electrolyte 2.0(DDSE 2.0)

The Dynamic Database of Solid-State Electrolyte(DDSE)is an advanced online platform offering a comprehensive suite of tools for solid-state battery research and development.Its key features include statistical analysis of both experimental and computational solid-state electrolyte(SSE)data,interactive visualization through dynamic charts,user data assessment,and literature analysis powered by a large language model.By facilitating the design and optimization of novel SSEs,DDSE serves as a critical resource for advancing solid-state battery technology.This Technical Report provides detailed tutorials and practical examples to guide users in effectively utilizing the platform.

基于Data Window的数据管理与更新机制的研究与应用

介绍了DataWindow控件管理数据的基本原理和处理流程 ,并深入阐述了DataWindow对象的四个缓冲区 (PrimaryBuffer,DeleteBuffer,FilterBuffer,OriginalBuffer)的功能和相互关系 ,以及它们之间是如何各司其职 ,协作完成数据的增加、删除、修改 ,并把结果提交给数据库管理系统的基本原理和过程。最后讨论了DataWindow对象的数据更新机制在编程中的一些应用 。