A Weighted Algorithm for Watermarking Relational Databases

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.

A Distribution Management System for Relational Databases in Cloud Environments

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.

A Novel Ranking Framework for Linked Data from Relational Databases

This paper investigates the problem of ranking linked data from relational databases using a rank-ing framework. The core idea is to group relationships by their types, then rank the types, and finally rank the instances attached to each type. The ranking criteria for each step considers the mapping rules and heterogeneous graph structure of the data web. Tests based on a social network dataset show that the linked data ranking is effective and easier for people to understand. This approach benefits from utilizing relationships deduced from mapping rules based on table schemas and distinguishing the relationship types, which results in better ranking and visualization of the linked data.

Fast Algorithms of Mining Probability Functional Dependency Rules in Relational Database

This paper defines a new kind of rule, probability functional dependency rule. The functional dependency degree can be depicted by this kind of rule. Five algorithms, from the simple to the complex, are presefited to mine this kind of rule in different condition. The related theorems are proved to ensure the high efficiency and the correctness of the above algorithms.

A New Integrated System of Logic Programming and Relational Database

Based on the study of the current two methods—interpretation and compilation—for the integration of logic programming and relational database,a new precompilation-based interpretive approach is proposed.It inherits the advantages of both methods,but overcomes the drawbacks of theirs.A new integrated system based on this approach is presented,which has been implemented on Micro VAX Ⅱ and applied to practise as the kernel of the GKBMS knowledge base management system.Also discussed are the key implementation techniques,including the coupling of logic and relational database systems,the compound of logic and relational database languages,the partial evaluation and static optimization of user's programs,fact scheduling and version management in problem-solving.

A Logical Design Method for Relational Databases Based on Generalization and Aggregation Semantics

In this paper, a series of design methods for relational databases based on generalization and aggregation sematics is set up. The relationship between a class and its subclass is considered as a scheme constraint. The concept of inheritance dependencies, which describes the multiple inheritance among schemes,is presented in the paper. It is shown that the inference rules for inheritance dependencies are sound and complete. Furthermore, a series of results about the closure of inheritance dependencies and the minimal set of inheritance dependencies, which are analogues to functional dependencies, is obtained. In order to describe the aggregation semalltics, the concept of aggregation dependencies is given. It is easy to implement these constraints under relational database management systems.

Mapping integrity constraint ontology to relational databases

Integrity constraint is a formula that checks whether all necessary information has been explicitly provided. It can be added into ontology to guarantee the data-centric application. In this paper,a set of constraint axioms called IC-mapping axioms are stated. Based on these axioms,a special ontology with integrity constraint,which is adapted to map ontology knowledge to data in relational databases,is defined. It＇s generated through our checking and modification. Making use of the traditional mapping approaches,it can be mapped to relational databases as a normal ontology. Unlike what in the past,a novel mapping approach named IC-based mapping is proposed in accordance with such special ontology. The detailed algorithm is put forward and compared with other existing approaches used in Semantic Web applications. The result shows that our method is advanced to the traditional approaches.

Using Multivalued Logic in Relational Database Containing Null Value

In this paper, several kinds of multivalued logic for relational database and their developing process are presented on the basis of null value's semantics. A new 5 valued logic is led into relational database containing null talue. The feasibility and necessity of using 5 valued logic are expounded. Comparative calculation and logical calculation under 5 valued logic are defined at the end of the paper.

PORLES:A Parallel Object Relational Database System

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.

An Efficient Schema Transformation Technique for Data Migration from Relational to Column-Oriented Databases

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.

An Efficient Algorithm for Processing Multi-Relation Queries in Relational Databases

After a relation scheme R is decomposed into the set of schemes ρ={R_1,...,R_n},we may pose queries as if R existed in the database,taking a join of R_i's,when it is necessary to implement the query.Suppose a query involves a set of attributes S(?)R,we want to find the smallest subset of ρ whose union includes S.We prove that the problem is NP-complete and present a polynomial-bounded approximation algorithm.A subset of ρ whose union includes S and has a decomposition into 3NF with a lossless join and preservation of dependencies is given in the paper.

Use of Component Integration Services in Multidatabase Systems: A Feasible Solution for Integrating Academic Institutions or Commercial Industries

The book chapter is an extended version of the research paper entitled “Use of Component Integration Services in Multidatabase Systems”, which is presented and published by the 13th ISITA, the National Conference of Recent Trends in Mathematical and Computer Sciences, T.M.B. University, Bhagalpur, India, January 3-4, 2015. Information is widely distributed across many remote, distributed, and autonomous databases (local component databases) in heterogeneous formats. The integration of heterogeneous remote databases is a difficult task, and it has already been addressed by several projects to certain extents. In this chapter, we have discussed how to integrate heterogeneous distributed local relational databases because of their simplicity, excellent security, performance, power, flexibility, data independence, support for new hardware technologies, and spread across the globe. We have also discussed how to constitute a global conceptual schema in the multidatabase system using Sybase Adaptive Server Enterprise’s Component Integration Services (CIS) and OmniConnect. This is feasible for higher education institutions and commercial industries as well. Considering the higher educational institutions, the CIS will improve IT integration for educational institutions with their subsidiaries or with other institutions within the country and abroad in terms of educational management, teaching, learning, and research, including promoting international students’ academic integration, collaboration, and governance. This will prove an innovative strategy to support the modernization and large expansion of academic institutions. This will be considered IT-institutional alignment within a higher education context. This will also support achieving one of the sustainable development goals set by the United Nations: “Goal 4: ensure inclusive and quality education for all and promote lifelong learning”. However, the process of IT integration into higher educational institutions must be thoroughly evaluated, identifying the vital data access points. In this chapter, Section 1 provides an introduction, including the evolution of various database systems, data models, and the emergence of multidatabase systems and their importance. Section 2 discusses component integration services (CIS), OmniConnect and considering heterogeneous relational distributed local databases from the perspective of academics, Section 3 discusses the Sybase Adaptive Server Enterprise (ASE), Section 4 discusses the role of component integration services and OmniConnect of Sybase ASE under the Multidatabase System, Section 5 shows the database architectural framework, Section 6 provides an implementation overview of the global conceptual schema in the multidatabase system, Section 7 discusses query processing in the CIS, and finally, Section 8 concludes the chapter. The chapter will help our students a lot, as we have discussed well the evolution of databases and data models and the emergence of multidatabases. Since some additional useful information is cited, the source of information for each citation is properly mentioned in the references column.

The method of design for seismic data database system based on tree structure

With the massive growth of the seismic data, it is required a new method to manage them. In this paper, the design method will be reported about relational database based on tree structure. Comparing with other designs, it is not only simpler and easier to organize data, but also can simplify the design process of the database. This method has been used to design database of the earthquake monitor center station of the earthquake monitoring system for the Yangtze River Three Gorges Project and has shown good results.

A Novel Database Watermarking Technique Using Blockchain as Trusted Third Party

With widespread use of relational database in various real-life applications,maintaining integrity and providing copyright protection is gaining keen interest of the researchers.For this purpose,watermarking has been used for quite a long time.Watermarking requires the role of trusted third party and a mechanism to extract digital signatures(watermark)to prove the ownership of the data under dispute.This is often inefficient as lots of processing is required.Moreover,certain malicious attacks,like additive attacks,can give rise to a situation when more than one parties can claim the ownership of the same data by inserting and detecting their own set of watermarks from the same data.To solve this problem,we propose to use blockchain technology—as trusted third party—along with watermarking for providing a means of rights protection of relational databases.Using blockchain for writing the copyright information alongside watermarking helps to secure the watermark as changing the blockchain is very difficult.This way,we combined the resilience of our watermarking scheme and the strength of blockchain technology—for protecting the digital rights information from alteration—to design and implement a robust scheme for digital right protection of relational databases.Moreover,we also discuss how the proposed scheme can also be used for version control.The proposed technique works with nonnumeric features of relational database and does not target only selected tuple or portion(subset)from the database for watermark embedding unlike most of the existing techniques;as a result,the chances of subset selection containing no watermark decrease automatically.The proposed technique employs zerowatermarking approach and hence no intentional error(watermark)is added to the original dataset.The results of the experiments proved the effectiveness of the proposed scheme.

XML-based Data Processing in Network Supported Collaborative Design

In the course of network supported collaborative design, the data processing plays a very vital role. Much effort has been spent in this area, and many kinds of approaches have been proposed. Based on the correlative materials, this paper presents extensible markup language （XML） based strategy for several important problems of data processing in network supported collaborative design, such as the representation of standard for the exchange of product model data （STEP） with XML in the product information expression and the management of XML documents using relational database. The paper gives a detailed exposition on how to clarify the mapping between XML structure and the relationship database structure and how XML-QL queries can be translated into structured query language （SQL） queries. Finally, the structure of data processing system based on XML is presented.

Data Mining as a Technique for Healthcare Approach

Data Mining, also known as knowledge discovery in data (KDC), is the process of uncovering patterns and other valuable information from large data sets. According to https://www.geeksforgeeks.org/data-mining/, it can be referred to as knowledge mining from data, knowledge extraction, data/pattern analysis, data archaeology, and data dredging. With advance research in health sector, there is multitude of Data available in healthcare sector. The general problem then becomes how to use the existing information in a more useful targeted way. Data Mining therefore is the best available technique. The objective of this paper is to review and analyse some of the different Data Mining Techniques such as Application, Classification, Clustering, Regression, etc. applied in the Domain of Healthcare.

Dealing with Empty and Overabundant Answers to Flexible Queries

In traditional database applications, queries intend to retrieve data satisfying precise conditions. As a result, thousands of data can be retrieved (overabundant answer) or, even worse, no data at all (empty answer). In both cases, the queries must be reformulated to produce more significant results and, typically, many related queries are submitted by a user before he can be finally satisfied. To overcome these problems, this paper proposes a unified solution in the framework of flexible queries with fuzzy semantics. This solution, based on the concept of semantic proximity and implemented in a tool for flexible query answering, allows the automatic reformulation of queries with empty or overabundant answers.

Searching Databases with Keywords

Traditionally, SQL query language is used to search the data in databases. However, it is inappropriate for end-users, since it is complex and hard to learn. It is the need of end-user, searching in databases with keywords, like in web search engines. This paper presents a survey of work on keyword search in databases. It also includes a brief introduction to the SEEKER system which has been developed.

CLASCN： Candidate Network Selection for Efficient Top-κ Keyword Queries over Databases

Keyword Search Over Relational Databases （KSORD） enables casual or Web users easily access databases through free-form keyword queries. Improving the performance of KSORD systems is a critical issue in this area. In this paper, a new approach CLASCN （Classification, Learning And Selection of Candidate Network） is developed to efficiently perform top-κ keyword queries in schema-graph-based online KSORD systems. In this approach, the Candidate Networks （CNs） from trained keyword queries or executed user queries are classified and stored in the databases, and top-κ results from the CNs are learned for constructing CN Language Models （CNLMs）. The CNLMs are used to compute the similarity scores between a new user query and the CNs from the query. The CNs with relatively large similarity score, which are the most promising ones to produce top-κ results, will be selected and performed. Currently, CLASCN is only applicable for past queries and New All-keyword-Used （NAU） queries which are frequently submitted queries. Extensive experiments also show the efficiency and effectiveness of our CLASCN approach.

EST Pipeline System: Detailed and Automated EST Data Processing and Mining

Expressed sequence tags (ESTs) are widely used in gene survey research these years. The EST Pipeline System, software developed by Hangzhou Genomics Institute (HGI), can automatically analyze different scalar EST sequences by suitable methods. All the analysis reports, including those of vector masking, sequence assembly, gene annotation, Gene Ontology classification, and some other analyses, can be browsed and searched as well as downloaded in the Excel format from the web interface, saving research efforts from routine data processing for biological rules embedded in the data.