图像描述是对指定图片进行自然语言描述,在现阶段的研究中大多是基于编码器-解码器结构进行的,为提升图像描述的精确度还可以引入注意力机制,使用模型在编码器-解码器架构基础上,同时引入了一种基于AoA(Attention on Attention)的新的...图像描述是对指定图片进行自然语言描述,在现阶段的研究中大多是基于编码器-解码器结构进行的,为提升图像描述的精确度还可以引入注意力机制,使用模型在编码器-解码器架构基础上,同时引入了一种基于AoA(Attention on Attention)的新的改进注意力机制,使注意力机制轻量化的同时将注意力结果和查询结果的相关性进行确定,来增强图片与词之间的相关性,最后输出自然语言。在公共数据集MSCOCO和Flickr30k作对比验证,通过实验结果与传统一般的注意力机制模型评价结果相比,在进行图像文本描述时使用的改进注意力机制模型,加快了整体模型的收敛速率,提高了相关评价指标并增强了模型性能,有显著的优越性。展开更多
This paper proposes a method of data-flow testing for Web services composition. Firstly, to facilitate data flow analysis and constraints collecting, the existing model representation of business process execution lan...This paper proposes a method of data-flow testing for Web services composition. Firstly, to facilitate data flow analysis and constraints collecting, the existing model representation of business process execution language （BPEL） is modified in company with the analysis of data dependency and an exact representation of dead path elimination （DPE） is proposed, which over-comes the difficulties brought to dataflow analysis. Then defining and using information based on data flow rules is collected by parsing BPEL and Web services description language （WSDL） documents and the def-use annotated control flow graph is created. Based on this model, data-flow anomalies which indicate potential errors can be discovered by traversing the paths of graph, and all-du-paths used in dynamic data flow testing for Web services composition are automatically generated, then testers can design the test cases according to the collected constraints for each path selected.展开更多
Actual software development processes define the different steps developers have to perform during a development project. Usually these development steps are not described independently from each other—a more or less...Actual software development processes define the different steps developers have to perform during a development project. Usually these development steps are not described independently from each other—a more or less formal flow of development step is an essential part of the development process definition. In practice, we observe that often the process definitions are hardly used and very seldom “lived”. One reason is that the predefined general process flow does not reflect the specific constraints of the individual project. For that reasons we claim to get rid of the process flow definition as part of the development process. Instead we describe in this paper an approach to smartly assist developers in software process execution. The approach observes the developer’s actions and predicts his next development step based on the project process history. Therefore we apply machine learning resp. sequence learning approaches based on a general rule based process model and its semantics. Finally we show two evaluations of the presented approach: The data of the first is derived from a synthetic scenario. The second evaluation is based on real project data of an industrial enterprise.展开更多
Document classification is widely applied in many scientific areas and academic environments, using NLP techniques and term extraction algorithms like CValue, TfIdf, TermEx, GlossEx, Weirdness and the others like. Nev...Document classification is widely applied in many scientific areas and academic environments, using NLP techniques and term extraction algorithms like CValue, TfIdf, TermEx, GlossEx, Weirdness and the others like. Nevertheless, they mainly have weaknesses in extracting most important terms when input text has not been rectified grammatically, or even has non-alphabetic methodical and math or chemical notations, and cross-domain inference of terms and phrases. In this paper, we propose a novel Text-Categorization and Term-Extraction method based on human-expert choice of classified categories. Papers are the training phase substances of the proposed algorithm. They have been already labeled with some scientific pre-defined field specific categories, by a human expert, especially one with high experiences and researches and surveys in the field. Our approach thereafter extracts (concept) terms of the labeled papers of each category and assigns all to the category. Categorization of test papers is then applied based on their extracted terms and further comparing with each category’s terms. Besides, our approach will produce semantic enabled outputs that are useful for many goals such as knowledge bases and data sets complement of the Linked Data cloud and for semantic querying of them by some languages such as SparQL. Besides, further finding classified papers’ gained topic or class will be easy by using URIs contained in the ontological outputs. The experimental results, comparing LPTC with five well-known term extraction algorithms by measuring precision and recall, show that categorization effectiveness can be achieved using our approach. In other words, the method LPTC is significantly superior to CValue, TfIdf, TermEx, GlossEx and Weirdness in the target study. As well, we conclude that higher number of papers for training, even higher precision we have.展开更多
基于位置的服务被认为是继短信之后电信增值业务发展的下一次高潮,在前期所提出的一种面向电信增值业务领域的流程描述语言XPL(extended-calling process language)的基础上,进一步提出了一种描述地理信息服务的语言GDL(geography descr...基于位置的服务被认为是继短信之后电信增值业务发展的下一次高潮,在前期所提出的一种面向电信增值业务领域的流程描述语言XPL(extended-calling process language)的基础上,进一步提出了一种描述地理信息服务的语言GDL(geography description language),GDL可以和XPL配合使用,共同描述基于位置的电信服务.XPL和GDL具有抽象层次高,使用灵活简单,开发业务速度快的特点.还介绍了支持XPL和GDL的业务生成系统.该业务生成系统基于SOA(services-oriented architecture,面向服务的构架),适用于网络融合条件下的业务生成.展开更多
为了满足ATS软件平台通用化和标准化的要求,以STD(测试和信号定义,IEEE1641)标准为基础,借鉴该标准中信号分类及处理的方法,制定了基于STD标准的测试流程描述语言;该测试流程描述语言以中文为基础,并采用了近似工作中使用的词汇和语法...为了满足ATS软件平台通用化和标准化的要求,以STD(测试和信号定义,IEEE1641)标准为基础,借鉴该标准中信号分类及处理的方法,制定了基于STD标准的测试流程描述语言;该测试流程描述语言以中文为基础,并采用了近似工作中使用的词汇和语法来实现对测试流程的标准化描述,目的是为方便装备工程师对被测对象(unit under test,UUT)测试流程及信号特征进行标准化描述;以差分信号为例,采用LabWindows/CVI对基于STD标准的信号处理方法进行了仿真演示;最后,以某虚拟装备为被测对象,利用该流程描述语言进行了标准化描述,并给出了应用该描述文档开发的测试程序。展开更多
文摘图像描述是对指定图片进行自然语言描述,在现阶段的研究中大多是基于编码器-解码器结构进行的,为提升图像描述的精确度还可以引入注意力机制,使用模型在编码器-解码器架构基础上,同时引入了一种基于AoA(Attention on Attention)的新的改进注意力机制,使注意力机制轻量化的同时将注意力结果和查询结果的相关性进行确定,来增强图片与词之间的相关性,最后输出自然语言。在公共数据集MSCOCO和Flickr30k作对比验证,通过实验结果与传统一般的注意力机制模型评价结果相比,在进行图像文本描述时使用的改进注意力机制模型,加快了整体模型的收敛速率,提高了相关评价指标并增强了模型性能,有显著的优越性。
基金the National Natural Science Foundation of China(60425206, 60503033)National Basic Research Program of China (973 Program, 2002CB312000)Opening Foundation of State Key Laboratory of Software Engineering in Wuhan University
文摘This paper proposes a method of data-flow testing for Web services composition. Firstly, to facilitate data flow analysis and constraints collecting, the existing model representation of business process execution language （BPEL） is modified in company with the analysis of data dependency and an exact representation of dead path elimination （DPE） is proposed, which over-comes the difficulties brought to dataflow analysis. Then defining and using information based on data flow rules is collected by parsing BPEL and Web services description language （WSDL） documents and the def-use annotated control flow graph is created. Based on this model, data-flow anomalies which indicate potential errors can be discovered by traversing the paths of graph, and all-du-paths used in dynamic data flow testing for Web services composition are automatically generated, then testers can design the test cases according to the collected constraints for each path selected.
文摘Actual software development processes define the different steps developers have to perform during a development project. Usually these development steps are not described independently from each other—a more or less formal flow of development step is an essential part of the development process definition. In practice, we observe that often the process definitions are hardly used and very seldom “lived”. One reason is that the predefined general process flow does not reflect the specific constraints of the individual project. For that reasons we claim to get rid of the process flow definition as part of the development process. Instead we describe in this paper an approach to smartly assist developers in software process execution. The approach observes the developer’s actions and predicts his next development step based on the project process history. Therefore we apply machine learning resp. sequence learning approaches based on a general rule based process model and its semantics. Finally we show two evaluations of the presented approach: The data of the first is derived from a synthetic scenario. The second evaluation is based on real project data of an industrial enterprise.
文摘Document classification is widely applied in many scientific areas and academic environments, using NLP techniques and term extraction algorithms like CValue, TfIdf, TermEx, GlossEx, Weirdness and the others like. Nevertheless, they mainly have weaknesses in extracting most important terms when input text has not been rectified grammatically, or even has non-alphabetic methodical and math or chemical notations, and cross-domain inference of terms and phrases. In this paper, we propose a novel Text-Categorization and Term-Extraction method based on human-expert choice of classified categories. Papers are the training phase substances of the proposed algorithm. They have been already labeled with some scientific pre-defined field specific categories, by a human expert, especially one with high experiences and researches and surveys in the field. Our approach thereafter extracts (concept) terms of the labeled papers of each category and assigns all to the category. Categorization of test papers is then applied based on their extracted terms and further comparing with each category’s terms. Besides, our approach will produce semantic enabled outputs that are useful for many goals such as knowledge bases and data sets complement of the Linked Data cloud and for semantic querying of them by some languages such as SparQL. Besides, further finding classified papers’ gained topic or class will be easy by using URIs contained in the ontological outputs. The experimental results, comparing LPTC with five well-known term extraction algorithms by measuring precision and recall, show that categorization effectiveness can be achieved using our approach. In other words, the method LPTC is significantly superior to CValue, TfIdf, TermEx, GlossEx and Weirdness in the target study. As well, we conclude that higher number of papers for training, even higher precision we have.
文摘为了满足ATS软件平台通用化和标准化的要求,以STD(测试和信号定义,IEEE1641)标准为基础,借鉴该标准中信号分类及处理的方法,制定了基于STD标准的测试流程描述语言;该测试流程描述语言以中文为基础,并采用了近似工作中使用的词汇和语法来实现对测试流程的标准化描述,目的是为方便装备工程师对被测对象(unit under test,UUT)测试流程及信号特征进行标准化描述;以差分信号为例,采用LabWindows/CVI对基于STD标准的信号处理方法进行了仿真演示;最后,以某虚拟装备为被测对象,利用该流程描述语言进行了标准化描述,并给出了应用该描述文档开发的测试程序。
