Based on some necessary conditions for double pyramidal central configurations with a concave pentagonal base, for any given ratio of masses, the existence and uniqueness of a class of double pyramidal central configu...Based on some necessary conditions for double pyramidal central configurations with a concave pentagonal base, for any given ratio of masses, the existence and uniqueness of a class of double pyramidal central configurations with a concave pentagonal base in 7-body problems are proved and the range of the ratio between radius and half-height is obtained, within which the 7 bodies involved form a central configuration or form uniquely a central configuration.展开更多
Automatically mapping a requirement specification to design model in Software Engineering is an open complex problem. Existing methods use a complex manual process that use the knowledge from the requirement specifica...Automatically mapping a requirement specification to design model in Software Engineering is an open complex problem. Existing methods use a complex manual process that use the knowledge from the requirement specification/modeling and the design, and try to find a good match between them. The key task done by designers is to convert a natural language based requirement specification (or corresponding UML based representation) into a predominantly computer language based design model—thus the process is very complex as there is a very large gap between our natural language and computer language. Moreover, this is not just a simple language conversion, but rather a complex knowledge conversion that can lead to meaningful design implementation. In this paper, we describe an automated method to map Requirement Model to Design Model and thus automate/partially automate the Structured Design (SD) process. We believe, this is the first logical step in mapping a more complex requirement specification to design model. We call it IRTDM (Intelligent Agent based requirement model to design model mapping). The main theme of IRTDM is to use some AI (Artificial Intelligence) based algorithms, semantic representation using Ontology or Predicate Logic, design structures using some well known design framework and Machine Learning algorithms for learning over time. Semantics help convert natural language based requirement specification (and associated UML representation) into high level design model followed by mapping to design structures. AI method can also be used to convert high level design structures into lower level design which then can be refined further by some manual and/or semi automated process. We emphasize that automation is one of the key ways to minimize the software cost, and is very important for all, especially, for the “Design for the Bottom 90% People” or BOP (Base of the Pyramid People).展开更多
基金Natural Science Foundation of China (No.19871096)
文摘Based on some necessary conditions for double pyramidal central configurations with a concave pentagonal base, for any given ratio of masses, the existence and uniqueness of a class of double pyramidal central configurations with a concave pentagonal base in 7-body problems are proved and the range of the ratio between radius and half-height is obtained, within which the 7 bodies involved form a central configuration or form uniquely a central configuration.
文摘Automatically mapping a requirement specification to design model in Software Engineering is an open complex problem. Existing methods use a complex manual process that use the knowledge from the requirement specification/modeling and the design, and try to find a good match between them. The key task done by designers is to convert a natural language based requirement specification (or corresponding UML based representation) into a predominantly computer language based design model—thus the process is very complex as there is a very large gap between our natural language and computer language. Moreover, this is not just a simple language conversion, but rather a complex knowledge conversion that can lead to meaningful design implementation. In this paper, we describe an automated method to map Requirement Model to Design Model and thus automate/partially automate the Structured Design (SD) process. We believe, this is the first logical step in mapping a more complex requirement specification to design model. We call it IRTDM (Intelligent Agent based requirement model to design model mapping). The main theme of IRTDM is to use some AI (Artificial Intelligence) based algorithms, semantic representation using Ontology or Predicate Logic, design structures using some well known design framework and Machine Learning algorithms for learning over time. Semantics help convert natural language based requirement specification (and associated UML representation) into high level design model followed by mapping to design structures. AI method can also be used to convert high level design structures into lower level design which then can be refined further by some manual and/or semi automated process. We emphasize that automation is one of the key ways to minimize the software cost, and is very important for all, especially, for the “Design for the Bottom 90% People” or BOP (Base of the Pyramid People).
