Database Modeling and Design

2014 ◽  
pp. 83-118
Author(s):  
Elvis C. Foster ◽  
Shripad V. Godbole
Keyword(s):  
2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Ying Wu ◽  
Jikun Liu

AbstractWith the rapid development of gymnastics technology, novel movements are also emerging. Due to the emergence of various complicated new movements, higher requirements are put forward for college gymnastics teaching. Therefore, it is necessary to combine the multimedia simulation technology to construct the human body rigid model and combine the image texture features to display the simulation image in texture form. In the study, GeBOD morphological database modeling was used to provide the data needed for the modeling of the whole-body human body of the joint and used for dynamics simulation. Simultaneously, in order to analyze and summarize the technical essentials of the innovative action, this experiment compared and analyzed the hem stage of the cross-headstand movement of the subject and the hem stage of the 180° movement. Research shows that the method proposed in this paper has certain practical effects.


Author(s):  
Scott G. Danielson

Abstract An engineering database modeling telephone outside plant networks is developed. Semantic and relational database design methodologies are used with the semantic data model developed based on an extended entity-relationship approach. This logical model is used to generate a normalized relational data structure. This database holds engineering data supporting engineering analyses, engineering work order generation procedures, and network planning activities. The database has been linked to separate network analysis programs and CAD-based network maps by a database application.


2008 ◽  
pp. 187-207 ◽  
Author(s):  
Z.. M. Ma

Fuzzy set theory has been extensively applied to extend various data models and resulted in numerous contributions, mainly with respect to the popular relational model or to some related form of it. To satisfy the need of modeling complex objects with imprecision and uncertainty, recently many researches have been concentrated on fuzzy semantic (conceptual) and object-oriented data models. This chapter reviews fuzzy database modeling technologies, including fuzzy conceptual data models and database models. Concerning fuzzy database models, fuzzy relational databases, fuzzy nested relational databases, and fuzzy object-oriented databases are discussed, respectively.


2003 ◽  
pp. 1
Author(s):  
Terry Halpin ◽  
Ken Evans ◽  
Patrick Hallock ◽  
Bill Maclean

Author(s):  
Terry Halpin

When using natural language, people typically refer to individual things by using proper names or definite descriptions. Data modeling languages differ considerably in their support for such linguistic reference schemes. Understanding these differences is important for modeling reference schemes within such languages and for transforming models from one language to another. This article provides a comparative review of reference scheme modeling within the Unified Modeling Language (version 2.5), the Barker dialect of Entity Relationship modeling, Object-Role Modeling (version 2), relational database modeling, and the Web Ontology Language (version 2.0). The author identifies which kinds of reference schemes can be captured within these languages as well as those reference schemes that cannot be. The author's analysis covers simple reference schemes, compound reference schemes, disjunctive reference and context-dependent reference schemes.


2009 ◽  
pp. 338-361
Author(s):  
Z. M. Ma

Information systems have become the nerve center of current computer-based engineering applications, which hereby put the requirements on engineering information modeling. Databases are designed to support data storage, processing, and retrieval activities related to data management, and database systems are the key to implementing engineering information modeling. It should be noted that, however, the current mainstream databases are mainly used for business applications. Some new engineering requirements challenge today’s database technologies and promote their evolvement. Database modeling can be classified into two levels: conceptual data modeling and logical database modeling. In this chapter, we try to identify the requirements for engineering information modeling and then investigate the satisfactions of current database models to these requirements at two levels: conceptual data models and logical database models. In addition, the relationships among the conceptual data models and the logical database models for engineering information modeling are presented in the chapter viewed from database conceptual design.


2009 ◽  
pp. 105-125 ◽  
Author(s):  
Z.M. Ma

Fuzzy set theory has been extensively applied to extend various data models and resulted in numerous contributions, mainly with respect to the popular relational model or to some related form of it. To satisfy the need of modeling complex objects with imprecision and uncertainty, recently many researches have been concentrated on fuzzy semantic (conceptual) and object-oriented data models. This chapter reviews fuzzy database modeling technologies, including fuzzy conceptual data models and database models. Concerning fuzzy database models, fuzzy relational databases, fuzzy nested relational databases, and fuzzy object-oriented databases are discussed, respectively.


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