By proposing tools that help for the accomplishment of tasks in almost all sectors of activities, computer science has revolutionized the world in a general way. Nowadays, it addresses the peculiarities of peoples thr...By proposing tools that help for the accomplishment of tasks in almost all sectors of activities, computer science has revolutionized the world in a general way. Nowadays, it addresses the peculiarities of peoples through their culture in order to produce increasingly easy-to-use software for end users: This is the aim of software localization. Localizing a software consists among other things, in adapting its GUI according to the end user culture. We propose in this paper a generic approach allowing accomplishing this adaptation, even for multi-user applications like gaming applications, collaborative editors, etc. Techniques of functional interpretations of abstracts structures parameterized by algebras, constitute the formal base of our approach.展开更多
移动应用是近10年来兴起的新型计算模式,深刻地影响人民的生活方式.移动应用主要以图形用户界面(graphical user interface,GUI)方式交互,而对其进行人工测试需要消耗大量人力和物力.为此,研究者提出针对移动应用GUI的测试自动生成技术...移动应用是近10年来兴起的新型计算模式,深刻地影响人民的生活方式.移动应用主要以图形用户界面(graphical user interface,GUI)方式交互,而对其进行人工测试需要消耗大量人力和物力.为此,研究者提出针对移动应用GUI的测试自动生成技术以提升测试效率并检测潜在缺陷.收集了145篇相关论文,系统地梳理、分析和总结现有工作.提出了“测试生成器-测试环境”研究框架,将该领域的研究按照所属模块进行分类.特别地,依据测试生成器所基于的方法,将现有方法大致分为基于随机、基于启发式搜索、基于模型、基于机器学习和基于测试迁移这5个类别.此外,还从缺陷类别和测试动作等其他分类维度梳理现有方法.收集了该领域中较有影响力的数据集和开源工具.最后,总结当前面临的挑战并展望未来的研究方向.展开更多
为了及时有效地发现桥梁病害,克服目前人工目测方法固有的费时、费力且易受主观因素影响的缺陷,提出一种基于卷积神经网络的轻量化桥梁病害智能识别方法。在保持原MobileNetV2网络模型宽度不变的情况下,通过减少网络中瓶颈模块的数量,...为了及时有效地发现桥梁病害,克服目前人工目测方法固有的费时、费力且易受主观因素影响的缺陷,提出一种基于卷积神经网络的轻量化桥梁病害智能识别方法。在保持原MobileNetV2网络模型宽度不变的情况下,通过减少网络中瓶颈模块的数量,并在其中嵌入Squeeze and Excitation通道注意力机制,使新网络能够更有效地学习和利用特征通道之间的关系,以提升网络识别性能。结果表明:经过缩减瓶颈模块和嵌入通道注意力机制两次改进的网络模型,实现了98.78%的识别准确率,较改进前提高了2.85%,计算量也较改进前减少了23.02 M;将改进后的网络模型引入Matlab的GUI界面,将代码可视化为可以独立使用的桥梁病害识别系统,为风化、钢筋锈蚀、开裂和孔洞四种桥梁病害的高效识别提供便利。展开更多
Steganography is a technology that discreetly embeds secret information into the redundant space of a carrier,enabling covert communication.As generative models continue to advance,steganography has evolved from tradi...Steganography is a technology that discreetly embeds secret information into the redundant space of a carrier,enabling covert communication.As generative models continue to advance,steganography has evolved from traditional modification-based methods to generative steganography,which includes generative linguistic and image based forms.However,while large model agents are rapidly emerging,no method has exploited the stable redundant space in their action processes.Inspired by this insightful observation,we propose a steganographic method leveraging large model agents,employing their actions to conceal secret messages.In this paper,we introduce StegoAgent,a generative steganography framework based on graphical user interface(GUI)agents,which effectively demonstrates the remarkable potential and effectiveness of large model agent-based steganographic methods.展开更多
文摘By proposing tools that help for the accomplishment of tasks in almost all sectors of activities, computer science has revolutionized the world in a general way. Nowadays, it addresses the peculiarities of peoples through their culture in order to produce increasingly easy-to-use software for end users: This is the aim of software localization. Localizing a software consists among other things, in adapting its GUI according to the end user culture. We propose in this paper a generic approach allowing accomplishing this adaptation, even for multi-user applications like gaming applications, collaborative editors, etc. Techniques of functional interpretations of abstracts structures parameterized by algebras, constitute the formal base of our approach.
文摘移动应用是近10年来兴起的新型计算模式,深刻地影响人民的生活方式.移动应用主要以图形用户界面(graphical user interface,GUI)方式交互,而对其进行人工测试需要消耗大量人力和物力.为此,研究者提出针对移动应用GUI的测试自动生成技术以提升测试效率并检测潜在缺陷.收集了145篇相关论文,系统地梳理、分析和总结现有工作.提出了“测试生成器-测试环境”研究框架,将该领域的研究按照所属模块进行分类.特别地,依据测试生成器所基于的方法,将现有方法大致分为基于随机、基于启发式搜索、基于模型、基于机器学习和基于测试迁移这5个类别.此外,还从缺陷类别和测试动作等其他分类维度梳理现有方法.收集了该领域中较有影响力的数据集和开源工具.最后,总结当前面临的挑战并展望未来的研究方向.
文摘目前,针对聚晶金刚石复合片(Polycrystalline Diamond Compact,PDC)钻头软件的开发主要集中在领眼钻头上,对领眼-扩眼钻头软件的研究还未见报道,并且PDC钻头破岩性能分析常基于有限元仿真分析方法开展,存在效率较低、时间成本大、灵活度不高的局限性,极大地限制了钻头设计研发进度。为此,设计了基于Matlab/图形用户界面(Graphical User Interface,GUI)的领眼-扩眼钻头破岩性能分析平台,旨在提供一个高效的工具,用于领眼-扩眼钻头破岩性能的评估与优化。该平台利用Matlab软件的数值计算和GUI图像处理功能,采用零点遍历法,结合切削齿的切削受力模型,能够计算切削齿的切削参数和领眼-扩眼钻头的受力情况,根据环境地层参数快速优选出最佳的钻扩组合类型,并且分析出领眼-扩眼钻头水力学特性,实现其破岩性能分析功能。结果表明,该软件适应性强、效率高,能在短时间内进行批量化的不同布齿结构领眼-扩眼钻头破岩性能分析,对提高领眼-扩眼钻头设计研发具有重要指导意义。
文摘为了及时有效地发现桥梁病害,克服目前人工目测方法固有的费时、费力且易受主观因素影响的缺陷,提出一种基于卷积神经网络的轻量化桥梁病害智能识别方法。在保持原MobileNetV2网络模型宽度不变的情况下,通过减少网络中瓶颈模块的数量,并在其中嵌入Squeeze and Excitation通道注意力机制,使新网络能够更有效地学习和利用特征通道之间的关系,以提升网络识别性能。结果表明:经过缩减瓶颈模块和嵌入通道注意力机制两次改进的网络模型,实现了98.78%的识别准确率,较改进前提高了2.85%,计算量也较改进前减少了23.02 M;将改进后的网络模型引入Matlab的GUI界面,将代码可视化为可以独立使用的桥梁病害识别系统,为风化、钢筋锈蚀、开裂和孔洞四种桥梁病害的高效识别提供便利。
基金supported in part by the National Natural Science Foundation of China under Grant Nos.62472398 and U2336206.
文摘Steganography is a technology that discreetly embeds secret information into the redundant space of a carrier,enabling covert communication.As generative models continue to advance,steganography has evolved from traditional modification-based methods to generative steganography,which includes generative linguistic and image based forms.However,while large model agents are rapidly emerging,no method has exploited the stable redundant space in their action processes.Inspired by this insightful observation,we propose a steganographic method leveraging large model agents,employing their actions to conceal secret messages.In this paper,we introduce StegoAgent,a generative steganography framework based on graphical user interface(GUI)agents,which effectively demonstrates the remarkable potential and effectiveness of large model agent-based steganographic methods.
