In order to provide a quantitative analysis and verification method for activity diagrams based business process modeling, a formal definition of activity diagrams is introduced. And the basic requirements for activit...In order to provide a quantitative analysis and verification method for activity diagrams based business process modeling, a formal definition of activity diagrams is introduced. And the basic requirements for activity diagrams based business process models are proposed. Furthermore, the standardized transformation technique between business process models and basic Petri nets is presented and the analysis method for the soundness and well-structured properties of business processes is introduced.展开更多
The current standard Unified Modeling Language(UML) could not model framework flexibility and extendibility adequately due to lack of appropriate constructs to distinguish framework hot-spots from kernel elements. A n...The current standard Unified Modeling Language(UML) could not model framework flexibility and extendibility adequately due to lack of appropriate constructs to distinguish framework hot-spots from kernel elements. A new UML profile that may customize UML for framework modeling was presented using the extension mechanisms of UML, providing a group of UML extensions to meet the needs of framework modeling. In this profile, the extended class diagrams and sequence diagrams were defined to straightforwardly identify the hot-spots and describe their instantiation restrictions. A transformation model based on design patterns was also put forward, such that the profile based framework design diagrams could be automatically mapped to the corresponding implementation diagrams. It was proved that the presented profile makes framework modeling more straightforwardly and therefore easier to understand and instantiate.展开更多
As one of Chinese minority languages,Tibetan speech recognition technology was not researched upon as extensively as Chinese and English were until recently.This,along with the relatively small Tibetan corpus,has resu...As one of Chinese minority languages,Tibetan speech recognition technology was not researched upon as extensively as Chinese and English were until recently.This,along with the relatively small Tibetan corpus,has resulted in an unsatisfying performance of Tibetan speech recognition based on an end-to-end model.This paper aims to achieve an accurate Tibetan speech recognition using a small amount of Tibetan training data.We demonstrate effective methods of Tibetan end-to-end speech recognition via cross-language transfer learning from three aspects:modeling unit selection,transfer learning method,and source language selection.Experimental results show that the Chinese-Tibetan multi-language learning method using multilanguage character set as the modeling unit yields the best performance on Tibetan Character Error Rate(CER)at 27.3%,which is reduced by 26.1%compared to the language-specific model.And our method also achieves the 2.2%higher accuracy using less amount of data compared with the method using Tibetan multi-dialect transfer learning under the same model structure and data set.展开更多
电力系统复杂应用软件的开发必能采用先进的软件工程学方法。统一建模语言 ( U nified Modeling L anguage,U ML )是近年来软件工程领域内取得的最重要成果之一。文章介绍了 UML 的产生背景及特点 ,然后详细讨论了 U ML在智能继电保护...电力系统复杂应用软件的开发必能采用先进的软件工程学方法。统一建模语言 ( U nified Modeling L anguage,U ML )是近年来软件工程领域内取得的最重要成果之一。文章介绍了 UML 的产生背景及特点 ,然后详细讨论了 U ML在智能继电保护整定计算及管理系统 ( ICAPE)开发中的应用。结果表明 ,统一建模语言 ( UML )具有标准性、系统性、可视化、自动化等优点 ,在电力系统复杂软件的开发中 ,将其合理地应用于软件开发的各个阶段 ,有助于提高软件开发效率及软件质量。因此 ,UML展开更多
文摘In order to provide a quantitative analysis and verification method for activity diagrams based business process modeling, a formal definition of activity diagrams is introduced. And the basic requirements for activity diagrams based business process models are proposed. Furthermore, the standardized transformation technique between business process models and basic Petri nets is presented and the analysis method for the soundness and well-structured properties of business processes is introduced.
文摘The current standard Unified Modeling Language(UML) could not model framework flexibility and extendibility adequately due to lack of appropriate constructs to distinguish framework hot-spots from kernel elements. A new UML profile that may customize UML for framework modeling was presented using the extension mechanisms of UML, providing a group of UML extensions to meet the needs of framework modeling. In this profile, the extended class diagrams and sequence diagrams were defined to straightforwardly identify the hot-spots and describe their instantiation restrictions. A transformation model based on design patterns was also put forward, such that the profile based framework design diagrams could be automatically mapped to the corresponding implementation diagrams. It was proved that the presented profile makes framework modeling more straightforwardly and therefore easier to understand and instantiate.
基金This work was supported by three projects.Zhao Y received the Grant with Nos.61976236 and 2020MDJC06Bi X J received the Grant with No.20&ZD279.
文摘As one of Chinese minority languages,Tibetan speech recognition technology was not researched upon as extensively as Chinese and English were until recently.This,along with the relatively small Tibetan corpus,has resulted in an unsatisfying performance of Tibetan speech recognition based on an end-to-end model.This paper aims to achieve an accurate Tibetan speech recognition using a small amount of Tibetan training data.We demonstrate effective methods of Tibetan end-to-end speech recognition via cross-language transfer learning from three aspects:modeling unit selection,transfer learning method,and source language selection.Experimental results show that the Chinese-Tibetan multi-language learning method using multilanguage character set as the modeling unit yields the best performance on Tibetan Character Error Rate(CER)at 27.3%,which is reduced by 26.1%compared to the language-specific model.And our method also achieves the 2.2%higher accuracy using less amount of data compared with the method using Tibetan multi-dialect transfer learning under the same model structure and data set.
