In the history of bridge engineering, demand has always been the primary driving force for development. Driven by the huge demand for construction since China’s reform and opening-up, Chinese bridge has leapt forward...In the history of bridge engineering, demand has always been the primary driving force for development. Driven by the huge demand for construction since China’s reform and opening-up, Chinese bridge has leapt forward both quantitatively and qualitatively in three major stages, by completing the transition from “follower” to “competitor,” and nally to “leader.” A new future is emerging for Chinese bridge engi- neering. As an important part of China’s transportation infrastructure, the bridge engineering industry is facing challenges in this new era on how to support the construction of a new form of transportation. This paper provides a summary of the status of bridge technology in China, based on a basic analysis of stock demand, incremental demand, and management demand. It is our belief that the Chinese bridge engi- neering industry must ful ll three outstanding requirements: construction ef ciency, management effec- tiveness, and long-term service. Intelligent technology based on information technology provides a new opportunity for innovation in bridge engineering. As a result, the development path of bridge engineering needs to be changed. This paper puts forward the idea of developing a third-generation bridge project that is characterized by intelligence, and discusses this project’s implications, development focus, and plan. In this way, this work provides a direction for the improvement of the core competitiveness of China’s bridge engineering industry.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
文摘In the history of bridge engineering, demand has always been the primary driving force for development. Driven by the huge demand for construction since China’s reform and opening-up, Chinese bridge has leapt forward both quantitatively and qualitatively in three major stages, by completing the transition from “follower” to “competitor,” and nally to “leader.” A new future is emerging for Chinese bridge engi- neering. As an important part of China’s transportation infrastructure, the bridge engineering industry is facing challenges in this new era on how to support the construction of a new form of transportation. This paper provides a summary of the status of bridge technology in China, based on a basic analysis of stock demand, incremental demand, and management demand. It is our belief that the Chinese bridge engi- neering industry must ful ll three outstanding requirements: construction ef ciency, management effec- tiveness, and long-term service. Intelligent technology based on information technology provides a new opportunity for innovation in bridge engineering. As a result, the development path of bridge engineering needs to be changed. This paper puts forward the idea of developing a third-generation bridge project that is characterized by intelligence, and discusses this project’s implications, development focus, and plan. In this way, this work provides a direction for the improvement of the core competitiveness of China’s bridge engineering industry.
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).
