Stored Procedures Research Articles

Determination of Sodium Tanshinone Iia Sulfonate in Rat Plasma by High Performance Liquid Chromatography and its Application to Pharmacokinetics Studies

A rapid high performance liquid chromatography (HPLC) method for the determination of sodium tanshinone IIA sulfonate (STS) in rat plasma is developed and validated. Sample preparation is accomplished through protein precipitation with methanol. The analyte and internal standard tanshinone I sulfonate are separated on an Agilent Extend C18 analytical column, using a mixture of methanol and triethylamine (0.1) (60:40, v/v) as the mobile phase. The low limit of quantification is 0.2 μg/mL, and the method is linear over the concentration range of 0.2-50 μg/mL for STS. The within- and between-run precisions (RSD) are within 5.8, mean extraction yields are always higher than 93.40, and it proves to be stable during all sample storing, preparation and analytic procedures. The method is successfully applied to a pharmacokinetic study after an intravenous administration of STS to rats at a dose of 6 mg/ kg and pharmacokinetics is described by a three-compartment open model.

Application of High Strength Additives in SMA Asphalt Mixture

At present, SMA mixture generally to the use of SBS modified asphalt, especially in the area of expressway construction in our country, but in recent years, the use of SBS modified asphalt has some problems, for example: SBS of storage stability of modified asphalt is a difficult problem, because SBS and asphalt compatibility between components of the difference, the modified agent and asphalt separation, reduces the performance of SBS modified asphalt; SBS modified asphalt in the stored procedure, the performance will decay, even if not stop stirring, decay cannot avoid, also influence the effect of the use of SBS modified asphalt.

Study on stored procedure implementation oriented to OceanBase

Study on stored procedure implementation oriented to OceanBase

다형의 버그 추적 시스템 마이닝 및 분석을 위한 저장소 독립 모델 설계

본 논문은 다양한 버그 추적 시스템으로부터 추출한 데이터를 통합하여 단일 저장소 모델을 제공하는 UniBAS(Unified Bug Analysis System)를 제안한다. UniBAS는 MSR(Mining Software Repositories) 연구 과정에서의 저장소 추출, 데이터 가공이나 모델 생성과 같은 공통적인 반복 작업을 줄이고, 관련 연구자가 상위 수준의 연구에 보다 집중할 수 있도록 함으로써 해당 연구 수행에 발생하는 복잡도와 비용을 줄여준다. 또한, UniBAS는 데이터 추출 뿐 아니라 질의 기반 분석에 필요한 테이블, 뷰 및 저장 프로시저 등을 자동 생성하며, 수집한 데이터 관리와 외부 도구와의 연동을 위해 다양한 형식의 파일을 생성할 수 있다. 사례 연구로 UniBAS의 유용성을 검증하기 위해 Mozilla사이트의 Firefox프로젝트를 대상으로 실제 중복 버그 리포트를 탐지하는 실험을 진행하였다. 이 과정에서 자동 추출된 자료를 대상으로 질의와 분석이 유연하게 이루어질 수 있었으며, 다양한 자연어 처리 알고리즘 적용을 통해 유효한 실험 결과를 얻을 수 있었다. In this paper, we propose UniBAS(Unified Bug Analysis System) to provide a unified repository model by integrating the extracted data from the heterogeneous bug tracking systems. The UniBAS reduces the cost and complexity of the MSR(Mining Software Repositories) research process and enables the researchers to focus on their logics rather than the tedious and repeated works such as extracting repositories, processing data and building analysis models. Additionally, the system not only extracts the data but also automatically generates database tables, views and stored procedures which are required for the researchers to perform query-based analysis easily. It can also generate various types of exported files for utilizing external analysis tools or managing research data. A case study of detecting duplicate bug reports from the Firfox project of the Mozilla site has been performed based on the UniBAS in order to evaluate the usefulness of the system. The results of the experiments with various algorithms of natural language processing and flexible querying to the automatically extracted data also showed the effectiveness of the proposed system.

A DATA WAREHOUSE DESIGN FOR THE DETECTION OF FRAUD IN THE SUPPLY CHAIN BY USING THE BENFORD’S LAW

Large data volumes and the inability to analyse them enables fraudulent activities to go unnoticed in supply chain management processes such as procurement, warehouse management and inventory management. This fraud increases the cost of the supply chain management and a fraud detection mechanism is necessary to reduce the risk of fraud in this business area. This study was carried out in order to develop a data warehouse design that supports forensic analytics by using the Benford’s law in order to detect fraud. The approach relies on a generic and re-usable store procedure for data analytics. The data warehouse was tested with two datasets collected from an operational supply chain database from the inventory management and warranty claims processes. The results of the research showed that the supply chain data analyzed obeys to Benford’s theory and that parameterized stored procedures with Dynamic SQL provide an excellent tool to analyze data in the supply chain for possible fraud detection. The implications of the results of the study are that the Benford’s law can be used to detect fraud in the supply chain with the help of parameterized stored procedures and a data ware house, this can ease the workload of the fraud analyst in the supply chain function. Although the research only used data from the inventory management and warranty claim processes, the proposed store procedures can be extended to any process in the supply chain making the results generalizable to the supply chain management process.

Bayesian Variable Selection in Linear Regression in One Pass for Large Data Sets.

Bayesian models are generally computed with Markov Chain Monte Carlo (MCMC) methods. The main disadvantage about MCMC methods is the large number of iterations they need to sample the posterior distributions of model parameters, especially for large data sets. On the other hand, variable selection remains a challenging problem due to its combinatorial search space, where Bayesian models are a promising solution. In this work, we study how to accelerate Bayesian model computation for variable selection in linear regression. We propose a fast Gibbs sampler algorithm, a widely used MCMC method, that incorporates several optimizations. We use non-informative and conjugate prior distributions on several model parameters, which enable data set summarization in one pass exploiting an augmented set of sufficient statistics. Thereafter the algorithm can iterate in main memory. Sufficient statistics are indexed with a sparse binary vector to efficiently compute matrix projections based on selected variables. Discovered variable subsets probabilities, selecting and discarding each variable, are stored on a hash table for fast retrieval in future iterations. We study how to integrate our algorithm into a database management system (DBMS), exploiting aggregate User-Defined Functions for parallel data summarization and stored procedures to manipulate matrices with arrays. An experimental evaluation with real data sets evaluates accuracy and time performance, comparing our DBMS-based algorithm, with the R package. Our algorithm is shown to produce accurate results, scale linearly on data set size and run orders of magnitude faster than the R package.

Active in-database processing to support ambient assisted living systems.

As an alternative to the existing software architectures that underpin the development of smart homes and ambient assisted living (AAL) systems, this work presents a database-centric architecture that takes advantage of active databases and in-database processing. Current platforms supporting AAL systems use database management systems (DBMSs) exclusively for data storage. Active databases employ database triggers to detect and react to events taking place inside or outside of the database. DBMSs can be extended with stored procedures and functions that enable in-database processing. This means that the data processing is integrated and performed within the DBMS. The feasibility and flexibility of the proposed approach were demonstrated with the implementation of three distinct AAL services. The active database was used to detect bed-exits and to discover common room transitions and deviations during the night. In-database machine learning methods were used to model early night behaviors. Consequently, active in-database processing avoids transferring sensitive data outside the database, and this improves performance, security and privacy. Furthermore, centralizing the computation into the DBMS facilitates code reuse, adaptation and maintenance. These are important system properties that take into account the evolving heterogeneity of users, their needs and the devices that are characteristic of smart homes and AAL systems. Therefore, DBMSs can provide capabilities to address requirements for scalability, security, privacy, dependability and personalization in applications of smart environments in healthcare.

Today's Tidbit: VoltDB

WELCOME TO CLOUD TIDBITS! In each issue, I'll be looking at a different “tidbit” of technology that I consider unique or eye-catching and of particular interest to IEEE Cloud Computing readers. Today's tidbit is VoltDB, a new cloud database. This system caught my eye for several reasons. First, it's the latest database designed by Michael Stonebraker, the database pioneer best known for Ingres, PostgreSQL, Illustra, Streambase, and more recently, Vertica. But interestingly, in this goaround, Stonebraker declared that he has thrown “all previous database architecture out the window” and “started over with a complete rewrite.”1 What's resulted is something totally different from every other database-including all the columnand table-oriented NoSQL systems. Moreover, VoltDB claims a 50 to 100x speed improvement over other relational database management systems (RDBMSs) and NoSQL systems. It sounds too good to be true. What we have is nothing short of a whole class of SQL, as compared to the “NoSQL” compromises detailed above. This “total rearchitecture,” called NewSQL, supports 100 percent in memory operation, supports SQL and stored procedures, and has a loosely coupled scale-out capability perfectly matched to cloud computing platforms. Wait a minute! That doesn't sound possible. That's precisely why I thought it made for a perfect tidbit.

Fast Distributed Transactions and Strongly Consistent Replication for OLTP Database Systems

As more data management software is designed for deployment in public and private clouds, or on a cluster of commodity servers, new distributed storage systems increasingly achieve high data access throughput via partitioning and replication. In order to achieve high scalability, however, today's systems generally reduce transactional support, disallowing single transactions from spanning multiple partitions. This article describes Calvin, a practical transaction scheduling and data replication layer that uses a deterministic ordering guarantee to significantly reduce the normally prohibitive contention costs associated with distributed transactions. This allows near-linear scalability on a cluster of commodity machines, without eliminating traditional transactional guarantees, introducing a single point of failure, or requiring application developers to reason about data partitioning. By replicating transaction inputs instead of transactional actions, Calvin is able to support multiple consistency levels—including Paxos-based strong consistency across geographically distant replicas—at no cost to transactional throughput. Furthermore, Calvin introduces a set of tools that will allow application developers to gain the full performance benefit of Calvin's server-side transaction scheduling mechanisms without introducing the additional code complexity and inconvenience normally associated with using DBMS stored procedures in place of ad hoc client-side transactions.

Design and Realization of the Process Tracking System for Plate Plant

The purpose of this paper is to improve the process tracking system, in order to meet the factory MES system requirements. Through the research process control systems and single process control system used in iron and steel enterprises in home and abroad, the integrated process control system, tracking control system and data acquisition system were established, and applied to the heat treatment lines of JISCO. In this system, the store procedure was used to complete the transaction processing in the database for improve the flexibility of the system. Practical applications validate the security and stability of performance system.

Migration of Stored Procedure to Distributed Cloud Database

Many legacy applications rely on a single instance relational database. In the age of big data, applications with growing popularity may continue to generate large amount of data. The data would be beyond the limit of a traditional relational database. These applications can be migrated to a distributed database system for acquiring high scalability and performance. But the migration process is complicated especially for user defined stored procedure. In order to obtain the correct behavior, a stored procedure usually has to be rewritten in the application code. This rewriting is usually a time consuming and unpleasant task. This study gives a mechanism for migrating stored procedure from single instance relational database to distributed sharded database without the need of application code rewriting. In the migration solution offered by this study, Oracle stored procedure code is parsed, analyzed, and translated so as to be stored and executed globally in a sharded database.

Research on SQL Performance Optimization of CRM Stored Procedure

In this paper, we research the stored procedure combined with the bank CRM system. Mainly introduces how to improve the efficiency of the stored procedure in ORACLEs PL/SQL in the banks CRM system.

Research on Technology of CRM Stored Procedure

In this paper, it mainly introduces how to realize the stored procedure of the bank CRM with PL/SQL in ORACLE, and the related technologies in the process.

Building Entity Relationship Models for PDDL and Developing Planners Based on Stored Procedures

PDF HTML阅读 XML下载 导出引用 引用提醒 PDDL 的ER 建模以及开发基于存储过程的规划器 DOI: 10.3724/SP.J.1001.2013.04264 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金(61003179, 61100134); 广东省自然科学基金(S2011040001427) Building Entity Relationship Models for PDDL and Developing Planners Based on Stored Procedures Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:随着智能规划的发展,其所面对的问题规模越来越大,而且可以预见以后会更大.现有的研究大多用二级存储扩展空间,其终极形式应该是用数据库进行存储.此外,有很多同一领域的规划问题,其所包含的常量几乎一致,其中必然有可重用信息来帮助加速求解.要更好地利用这些可重用信息也需要数据库.考虑到以上两个问题,首次提出规划领域描述语言PDDL(planning domain description language)的ER 模型(entity relationship model),并基于此模型用存储过程来编写规划器SPP(stored procedure planner).SPP 是完全在数据库内部运行的最优规划器,存取效率高,可充分利用数据库的各种功能.在国际规划大赛IPC(Int’l planning competition)基准领域上的实验结果表明,在有限的机器配置下,SPP 可以求解传统最优规划器不能求解的问题.该工作迈出了在数据库中求解规划问题,从而彻底解决空间问题的第一步. Abstract:With the development of automated planning, the size of problems is getting bigger and bigger, and one can predict that it will become very large in the future. Some existing research work begins to use secondary memories to extend the search space, and it is believed databases are finally used. Besides, many problems that belong to the same domain often have common constants, so there might be a plenty of reusable information to speed up the solution process. To store this information permanently, databases are also needed. Inspired by the above two reasons, this paper first proposes ER (entity relationship) models for PDDL (planning domain description languages) and then develops a stored procedure based automated planner (stored procedure planner, SPP) for the first time. This planner is an optimal one which runs totally inside a database. It stores and accesses data efficiently and takes fully advantages of database features. Experiments on benchmark problems from the Int'l planning competition (IPC) show that this planner can solve problems which cannot be solved by some classical optimal planners in a limited machine configuration. The work in this paper takes the first step for solving planning problems totally in a database so that it is helpful to solve huge-size problems finally. 参考文献 相似文献 引证文献

The Development of Student Information Management System Based on ASP.NET Workflow Technology

With the rapid development of Internet, today's society has entered the Internet era, computer network provides a powerful driving force for social and economic development. Improve the students' management level by means of network technology, has a far-reaching significance to the construction of first-class college. This paper focuses on the management system of student information development of college analysis the current situation of college student management work and the construction goal in the future, the student information management system development significance is discussed. Based on the analysis of the technical characteristics of C/S model and B/S model, and according to the characteristics of Guangxi Agricultural-vocational Technique College learn internet system, the software architecture using B/S model the whole system; to improve the treatment efficiency of development scheme by using stored procedures and triggers; on ASP.NET technology and workflow technology are studied; and discusses how to use ADO.NET to access the database using ASP.NET technology to realize the method. This paper adopts XML technology to realize data exchange, the formation of a standard data exchange platform, make the system more open and extensible.

The Realization of Math Score Query on the Wireless Internet

Wireless internet is gaining wide spread usage in teaching affairs, especially in score query system development. This paper explores how simple Math score query system can be developed for mobile devices and introduces general framework for designing such score query applications. Using the framework, based on Microsoft database software SQL Server 2000, T-SQL clause is employed to program one stored procedure for Math score query. The framework utilizes mobile phones simulator software, Nokia WAP Toolkit, which interacts with a server-side ASP (Active Server Pages) in conjunction with the associated SQL Server database. The design and implementation of the management information system are discussed in the paper, and test results are presented.

An Application of Stored Procedures in a GPS-Based Slope Online Monitoring System for Open-Pit Mine

As for implementing functions in slope online monitoring system by exploiting data acquired via GPS, good and high efficient stored procedures are essential. More importantly, a good designed stored procedure can simultaneously provide decision services for multiple users. By integrating the Client/Server and Browser/Server subsystems, this system explores a much convenient and automatic way to manages the mining area. 18 database tables are designed to support the database operation, such as the GPSSTATICRESULT table that storeds accurate static data and the STATIONINFO table that records all equipment information. Moreover, the design and implementation of stored procedures is analysed to flexibly support complicated system functions. The results indicate that system working with stored procedures has high performance on applications open-pit mine. The results not only confirmed the applicability and effectiveness of stored procedures, but also revealed system with stored procedures has advantages of conveniently managing mining data, timely sending real-time monitoring information, optimizing security of mine production and making auxiliary decision for enterprise.

Design and Implementation of an Intelligent Billing Algorithm for Open Computer Room Management System

Computer room is an important infrastructure of information technology on education for colleges, how to balance the load, calculate fees flexibly, improve resource utilization, service for the teachers and students better is an urgent problem.Firstly, the development trends of computer room management systems are discussed in the paper. Secondly, gives a data model of open computer room management system, which in order to balance the load and improve the utilization efficiency etc. of computer rooms. Finally, gives the intelligent billing algorithm according to the designed data model, and then implemented the algorithm using stored procedure with SQL Server 2005.

Analysis of SQL Injection Attack

SQL injection attacks are a serious security threat to Web applications. They allow attackers to obtain unrestricted access to the databases underlying the applications and to the potentially sensitive information these database contain. Various researchers and practitioners have proposed various methods to address the SQL injection problem. To address this problem, we present an extensive review of the various types of SQL injection attacks known to date. For each type of attack, we provide descriptions and examples of how attacks of that type could be performed. We also present a methodology to prevent SQL injection attacks. It concentrates on the SQL queries and SQL stored procedure where input parameters are injected by the attacker. After a rigorous input validation with our proposed SQL security model will ensure input validation.

Подход к интеграции интеллектуального анализа данных в реляционную СУБД на основе генерации текстов хранимых процедур

The paper introduces an approach to integration of data mining algorithms with relational DBMS. Approach assumes using XML-based markup for data mining algorithms implemented in SQL. User specifies input tables and algorithm parameters. After that system generates persistent stored procedures for specific data mining algorithm. Proposed markup language is described with examples. If there are several algorithms for some data mining problem the most effective algorithm implementation in SQL is generated by means of DBMS command EXPLAIN which shows estimated execution cost. Module structure and API for proposed program system is described.