A novel approach to compute the high frequency radar cross-section (RCS) of complex targets is described in this paper.From the three views or the sectional views of the target, target is geometrically modeled by non-...A novel approach to compute the high frequency radar cross-section (RCS) of complex targets is described in this paper.From the three views or the sectional views of the target, target is geometrically modeled by non-uniform rational B-spline (NURBS) parametric surfaces using the software CNFEOV developed by oneself which constructs NURBS representation of complex target from engineering orthographic views. RCS is obtained through PO, PTD, MEC and IBC techniques. When calculating RCS of the target, it is necessary to get the unit normal vector to surface illumi- nated by radar and the value Z which is the distance from the point on the surface to radar. ln this novel approach, the unit normal vector to the surface can be obtained either by the Phong rendering model, in which the color components (RGB) of every pixel on the image are equal to the coordinate components of the normal, or by the NURBS expressions. The value Z can be achieved by software or hardware Z-buffer. The effects of the size of image on the RCS of target are discussed and the correct method is recommended. The RCS of the perfect conducting sphere, cylinder and dihedral as well as the coated cylinder, as some examples, are computed. The accuracy of the method is verified by comparing the numerical results with those obtained by using other methods.展开更多
A method to detect traffic dangers based on visual attention model of sparse sampling was proposed. The hemispherical sparse sampling model was used to decrease the amount of calculation which increases the detection ...A method to detect traffic dangers based on visual attention model of sparse sampling was proposed. The hemispherical sparse sampling model was used to decrease the amount of calculation which increases the detection speed. Bayesian probability model and Gaussian kernel function were applied to calculate the saliency of traffic videos. The method of multiscale saliency was used and the final saliency was the average of all scales, which increased the detection rates extraordinarily. The detection results of several typical traffic dangers show that the proposed method has higher detection rates and speed, which meets the requirement of real-time detection of traffic dangers.展开更多
目的为了适应铸造CAE技术的网络化趋势,满足铸造CAE系统前置处理模块对STL模型高级渲染的功能性需求,开发一款足以媲美OpenGL渲染环境下复杂三维图形渲染效果的Web版的STL模型查看器程序——STLViewer。方法仿效Windows桌面程序的运行...目的为了适应铸造CAE技术的网络化趋势,满足铸造CAE系统前置处理模块对STL模型高级渲染的功能性需求,开发一款足以媲美OpenGL渲染环境下复杂三维图形渲染效果的Web版的STL模型查看器程序——STLViewer。方法仿效Windows桌面程序的运行方式和界面风格,选择单页面设计方案。选用Visual Studio 2019开发平台,利用HTML5、CSS3和JavaScript技术设计程序界面。深入研究基于WebGL的STL模型可视化技术,按照依托场景环境活动模型渲染的技术路线,进行STLViewer各功能模块的开发。结果设计并实现了STLViewer,该程序功能完整性良好、内部逻辑结构合理高效。STLViewer融隐式交互和显式交互于一体,具有本地STL模型的随机性访问、活动模型的多样化交互、模型姿态的智能化跟踪、视图动画的多方式呈现、模型导出的便捷化操作等特点,实现了网络环境下STL模型的高级渲染功能。结论STLViewer作为一款性能卓越的STL模型查看器程序,既可辅助用户制订合理的网格剖分方案,又能带来优良的用户体验,在实际应用中得到了良好效果。展开更多
得益于近期具有世界知识的大规模预训练模型的迅速发展,基于大模型的具身智能在各类任务中取得了良好的效果,展现出强大的泛化能力与在各领域内广阔的应用前景.鉴于此,对基于大模型的具身智能的工作进行了综述,首先,介绍大模型在具身智...得益于近期具有世界知识的大规模预训练模型的迅速发展,基于大模型的具身智能在各类任务中取得了良好的效果,展现出强大的泛化能力与在各领域内广阔的应用前景.鉴于此,对基于大模型的具身智能的工作进行了综述,首先,介绍大模型在具身智能系统中起到的感知与理解作用;其次,对大模型在具身智能中参与的需求级、任务级、规划级和动作级的控制进行了较为全面的总结;然后,对不同具身智能系统架构进行介绍,并总结了目前具身智能模型的数据来源,包括模拟器、模仿学习以及视频学习;最后,对基于大语言模型(Large language model,LLM)的具身智能系统面临的挑战与发展方向进行讨论与总结.展开更多
连续刚构拱组合铁路桥是一种具有复杂结构形式和施工工序繁多的桥梁类型。为实现对该类型桥梁施工过程的全面监控和管理,以目前在建最大跨径无砟轨道高墩大跨连续刚构拱组合体系桥为背景,阐述BIM技术在该领域取得的研究成果,通过BIM技...连续刚构拱组合铁路桥是一种具有复杂结构形式和施工工序繁多的桥梁类型。为实现对该类型桥梁施工过程的全面监控和管理,以目前在建最大跨径无砟轨道高墩大跨连续刚构拱组合体系桥为背景,阐述BIM技术在该领域取得的研究成果,通过BIM技术对连续刚构拱组合梁桥进行参数化建模、施工动态模拟,以Visual Studio 2022作为开发平台开发了线形与应力监控系统,系统包含数据管理、测点设计、接口设计、模型应用等四大功能模块,对施工监控数据进行有效管理。研究结果表明:采用基于BIM数据驱动的参数化建模技术,提高了建模效率和准确性。桥梁线形数据的可视化表达简化了监控数据与设计值的对比工作,可视化模拟施工工况和动态预警提示功能为桥梁线形的发展规律分析提供参考。实现了监测数据与桥梁BIM模型的关联,方便数据存储和查找,同时可以直观地比较实测值与理论值的误差是否超限,简化了监测数据统计和对比工作。该软件系统为铁路桥梁工程的设计、施工和监测提供有力支持。展开更多
文摘A novel approach to compute the high frequency radar cross-section (RCS) of complex targets is described in this paper.From the three views or the sectional views of the target, target is geometrically modeled by non-uniform rational B-spline (NURBS) parametric surfaces using the software CNFEOV developed by oneself which constructs NURBS representation of complex target from engineering orthographic views. RCS is obtained through PO, PTD, MEC and IBC techniques. When calculating RCS of the target, it is necessary to get the unit normal vector to surface illumi- nated by radar and the value Z which is the distance from the point on the surface to radar. ln this novel approach, the unit normal vector to the surface can be obtained either by the Phong rendering model, in which the color components (RGB) of every pixel on the image are equal to the coordinate components of the normal, or by the NURBS expressions. The value Z can be achieved by software or hardware Z-buffer. The effects of the size of image on the RCS of target are discussed and the correct method is recommended. The RCS of the perfect conducting sphere, cylinder and dihedral as well as the coated cylinder, as some examples, are computed. The accuracy of the method is verified by comparing the numerical results with those obtained by using other methods.
基金Project(50808025)supported by the National Natural Science Foundation of ChinaProject(20090162110057)supported by the Doctoral Fund of Ministry of Education of China
文摘A method to detect traffic dangers based on visual attention model of sparse sampling was proposed. The hemispherical sparse sampling model was used to decrease the amount of calculation which increases the detection speed. Bayesian probability model and Gaussian kernel function were applied to calculate the saliency of traffic videos. The method of multiscale saliency was used and the final saliency was the average of all scales, which increased the detection rates extraordinarily. The detection results of several typical traffic dangers show that the proposed method has higher detection rates and speed, which meets the requirement of real-time detection of traffic dangers.
文摘目的为了适应铸造CAE技术的网络化趋势,满足铸造CAE系统前置处理模块对STL模型高级渲染的功能性需求,开发一款足以媲美OpenGL渲染环境下复杂三维图形渲染效果的Web版的STL模型查看器程序——STLViewer。方法仿效Windows桌面程序的运行方式和界面风格,选择单页面设计方案。选用Visual Studio 2019开发平台,利用HTML5、CSS3和JavaScript技术设计程序界面。深入研究基于WebGL的STL模型可视化技术,按照依托场景环境活动模型渲染的技术路线,进行STLViewer各功能模块的开发。结果设计并实现了STLViewer,该程序功能完整性良好、内部逻辑结构合理高效。STLViewer融隐式交互和显式交互于一体,具有本地STL模型的随机性访问、活动模型的多样化交互、模型姿态的智能化跟踪、视图动画的多方式呈现、模型导出的便捷化操作等特点,实现了网络环境下STL模型的高级渲染功能。结论STLViewer作为一款性能卓越的STL模型查看器程序,既可辅助用户制订合理的网格剖分方案,又能带来优良的用户体验,在实际应用中得到了良好效果。
文摘得益于近期具有世界知识的大规模预训练模型的迅速发展,基于大模型的具身智能在各类任务中取得了良好的效果,展现出强大的泛化能力与在各领域内广阔的应用前景.鉴于此,对基于大模型的具身智能的工作进行了综述,首先,介绍大模型在具身智能系统中起到的感知与理解作用;其次,对大模型在具身智能中参与的需求级、任务级、规划级和动作级的控制进行了较为全面的总结;然后,对不同具身智能系统架构进行介绍,并总结了目前具身智能模型的数据来源,包括模拟器、模仿学习以及视频学习;最后,对基于大语言模型(Large language model,LLM)的具身智能系统面临的挑战与发展方向进行讨论与总结.
文摘连续刚构拱组合铁路桥是一种具有复杂结构形式和施工工序繁多的桥梁类型。为实现对该类型桥梁施工过程的全面监控和管理,以目前在建最大跨径无砟轨道高墩大跨连续刚构拱组合体系桥为背景,阐述BIM技术在该领域取得的研究成果,通过BIM技术对连续刚构拱组合梁桥进行参数化建模、施工动态模拟,以Visual Studio 2022作为开发平台开发了线形与应力监控系统,系统包含数据管理、测点设计、接口设计、模型应用等四大功能模块,对施工监控数据进行有效管理。研究结果表明:采用基于BIM数据驱动的参数化建模技术,提高了建模效率和准确性。桥梁线形数据的可视化表达简化了监控数据与设计值的对比工作,可视化模拟施工工况和动态预警提示功能为桥梁线形的发展规律分析提供参考。实现了监测数据与桥梁BIM模型的关联,方便数据存储和查找,同时可以直观地比较实测值与理论值的误差是否超限,简化了监测数据统计和对比工作。该软件系统为铁路桥梁工程的设计、施工和监测提供有力支持。
