低差错平底特性的非规则LDPC码的设计

介绍了非规则LDPC码的发展并给出了其优势及缺点，重点论述用ACE算法来构造非规则LDPC码从而降低其差错平底特性。对降低非规则LDPC码的差错平底特性的其它方法提出了展望。     

一种弧焊机器人实时激光扫描视觉系统

研制了一种小型高精度弧焊机器人实时激光扫描视觉系统，对其各项性能进行了测试，并进行了抗电弧光干扰试验，结果表明，此系统精度高，抗干扰能力强，检测范围宽，能广泛地应秀于机器人和自动化焊接中。     

一种识别薄板对接接头的视觉方法

对薄板紧密对接接头的识别问题进行了深入的分析，提出了由照明、自适应局部特征提取、全局特征识别和验证融合在一起的视觉识别方法。它克服了电弧光的干扰，识别结果可靠，可以有效地解决薄板紧密对接接头识别这一难题。     

大型自动埋弧焊成套设备的研究

本文介绍了一种结构新颖的埋弧焊成套设备,并就埋弧焊成套设备中的一些主要部件作了分析说明。该设备采用的平移式横梁结构、三点式九滚轮导轨装置以及焊缝自动跟踪装置,对满足同平面内多道长焊缝的焊接有独到之处。     

中频正火焊管的在线矫直

针对焊接油管、套管、锅炉管的焊缝在中频正火热处理时管子弯曲的现象,提出在定径段增设垂直、横向、周向可调的土耳其头机架,对焊管的弯曲实现反弯变形,从而达到在线矫直的目的。     

基于Wallis与距离权重增强的无人机影像拼接缝消除

针对无人机影像拼接缝消除困难的问题,提出了一种基于Wallis匀光和距离权重增强的拼接缝消除算法。首先,应用Wallis匀光消除亮度差异,给出Wallis参数设置方法。然后,提出了一种基于空间相关性的距离权重分配方法,通过增强距离对权重的影响,对拼接缝处的局部纹理错位进行全局优化,起到渐入渐出的平滑过渡效果,消除纹理拼接缝。最后,选取7种不同类型影像对本文方法和其他4种经典算法进行对比,并对8条行带影像进行拼接。实验结果表明：本文算法能高效地消除由于曝光差异与几何变形引起的拼接缝,适用于无人机影像快速处理。     

焊缝跟踪和物料跟踪

介绍宝钢 1 5 5 0热镀锌机组焊缝跟踪和物料跟踪控制系统的配置和功能 ,以及系统应用软件的功能和现场使用情况。     

基于Seam的城市供水管理系统的设计与实现

在基于Java EE(J2EE)软件开发方面,目前流行的软件架构方式是Spring+Hibernate+Struts,它的缺点是开发较慢,难于维护.通过引入JBoss Seam作为主体框架,用于开发基于三层B/S模式的城市供水管理系统,利用JBoss Seam所提供的注释和双向注入,组件的状态管理,以及所集成的大量框架和服务等各类功能,能够加快系统的开发、降低开发及维护难度.系统持久层使用JBoss Seam所集成的Hibernate,表示层使用Seam所推荐的JSF框架、支持JSF的Facelets模板框架以及内置支持Ajax的RichFaces框架,能够快速开发出以构件为中心、模板化的、体现Web2.0风格的页面.     

Neural reactive path planning with Riemannian motion policies for robotic silicone sealing

Due to its excellent chemical and mechanical properties, silicone sealing has been widely used in many industries. Currently, the majority of these sealing tasks are performed by human workers. Hence, they are susceptible to labor shortage problems. The use of vision-guided robotic systems is a feasible alternative to automate these types of repetitive and tedious manipulation tasks. In this paper, we present the development of a new method to automate silicone sealing with robotic manipulators. To this end, we propose a novel neural path planning framework that leverages fractional-order differentiation for robust seam detection with vision and a Riemannian motion policy for effectively learning the manipulation of a sealing gun. Optimal control commands can be computed analytically by designing a deep neural network that predicts the acceleration and associated Riemannian metric of the sealing gun from feedback signals. The performance of our new methodology is experimentally validated with a robotic platform conducting multiple silicone sealing tasks in unstructured situations. The reported results demonstrate that compared with directly predicting the control commands, our neural path planner achieves a more generalizable performance on unseen workpieces and is more robust to human/environment disturbances.     

Multi-operator image retargeting with automatic integration of direct and indirect seam carving

Multi-operator image resizing can preserve important objects and structure in an image by combining multiple image resizing operators. However, traditional multi-operator methods do not take both horizontal and vertical content-aware resizing potential into consideration, which essentially leads to squeeze/stretch effect in the resultant images. In this paper, we propose a new multi-operator scheme that addresses aforementioned issue by integrating direct and indirect seam carving. Compared with previous methods, the proposed scheme remarkably reduces the cost of deciding when to change operators, by employing a newly defined image artifact measure. Furthermore, we propose a novel seam carving enhancement, named ACcumulated Energy Seam Carving (ACESC), as a basic operator to improve global structure preservation. By combining horizontal and vertical seam carving, our scheme preserves the shapes of important objects well. We present typical results to demonstrate the effectiveness of our method. User study shows that our method has high user preference.