A heuristic for the label printing problem

Label printing finds many applications in industry. However, this task is still labor intensive in many printing factories. Since each template can only accommodate a fixed number of labels, an important task is to work out the compositions of templates by allocating suitable labels to each template in order to fulfill the order requirements effectively. The template design could be rather arbitrary, which usually ends up with a lot of excessive printed labels. Enhancing the template design will significantly improve the efficiency of the printing process, and, at the same time, reduce the waste of resources. This motivates the study of more automatic design methods. In this paper, the problem is first formulated as a nonlinear integer programming problem. The main variables in the formulation are the compositions and the printing frequencies of templates. For practical purpose, each type of label is confined to one template only which allows automated packing and handling. The structure of the problems is carefully analyzed and a new algorithm is proposed. Numerical results show that the proposed method is a simple but effective way of generating good template designs.     

Convolutional neural networks recognition algorithm based on PCA

To improve the insufficiency of Synthetic Aperture Radar(SAR) labeled training data for Convolutional Neural Networks(CNN) and the recognition rate for large variations, a novel CNN recognition algorithm is proposed. Firstly, a set of features is extracted from the original data by unsupervised training based on PCA as the initial filter set for CNN. Secondly, in order to accelerate the training speed while avoiding over-fitting, the Rectified Linear Units(ReLU) is adopted as the non-linear function. Thirdly, to strengthen robustness and mitigate the defects of pooling upon features, a probabilistic max-pooling sampling method is introduced and local contrast normalization is exploited on features after the convolutional layer. Experiments demonstrate that our algorithm outperforms the original CNN in recognition rate and achieves better robustness for large variations and complex background.     

一道数字排列题算法演示的C#实现

编程解决实际问题,不仅通过大量的编程实践,掌握一定的编程技巧,同时也需要找到解决问题的正确方案。通过一道数字排列题的解决演示,灵活运用C#语言编程实现该问题算法的可视化演示。     

MPLS网络工程流量分析

多协议标签交换MPLS（Multi-Protocol Label Switching）是一种高效的数据包交换技术,提供了标记、路由、转发等能力．论文使用OPNET软件,对MPLSTE技术在网络流量管理与负载均衡等方面进行仿真对比,与传统的IP网络相比具有更优异的表现。     

Lagrangean relaxation with clusters for point-feature cartographic label placement problems

This paper presents two new mathematical formulations for the point-feature cartographic label placement problem (PFCLP) and a new Lagrangean relaxation with clusters (LagClus) to provide bounds to these formulations. The PFCLP can be represented by a conflict graph and the relaxation divides the graph in small subproblems (clusters) that are easily solved. The edges connecting clusters are relaxed in a Lagrangean way and a subgradient algorithm improves the bounds. The LagClus was successfully applied to a set of instances up to 1000 points providing the best results of those reported in the literature.     

用VB标签控件实现动态效果

在VB程序设计里．标签通常是作为在窗口里显示文字信息的。用活标签的常用属性。并合理使用计时器控件。就能够呈现出动态的文字效果。为窗口界面增添活力。     

Redirection based recovery for MPLS network systems

To provide a reliable backbone network, fault tolerance should be considered in the network design. For a multiprotocol label switching (MPLS) based backbone network, the fault-tolerant issue focuses on how to protect the traffic of a label switched paths (LSP) against node and link failures. In IETF, two well-known recovery mechanisms (protection switching and rerouting) have been proposed. To further enhance the fault-tolerant performance of the two recovery mechanisms, the proposed approach utilizes the failure-free LSPs to transmit the traffic of the failed LSP (the affected traffic). To avoid affecting the original traffic of each failure-free LSP, the proposed approach applies the solution of the minimum cost flow to determine the amount of affected traffic to be transmitted by each failure-free LSP. For transmitting the affected traffic along a failure-free working LSP, IP tunneling technique is used. We also propose a permission token scheme to solve the packet disorder problem. Finally, simulation experiments are performed to show the effectiveness of the proposed approach.     

The labeled maximum matching problem

Given a graph G where a label is associated with each edge, we address the problem of looking for a maximum matching of G using the minimum number of different labels, namely the labeled maximum matching problem. It is a relatively new problem whose application is related to the timetabling problem. We prove it is NP-complete and present four different mathematical formulations. Moreover, we propose an exact algorithm based on a branch-and-bound approach to solve it. We evaluate the performance of our algorithm on a wide set of instances and compare our computational times with the ones required by CPLEX to solve the proposed mathematical formulations. Test results show the effectiveness of our procedure, that hugely outperforms the solver.     

跨域BGP／MPLSVPN在高性能路由器中的实现

提出在高性能路由器中跨域边界网关协议（BGP）／多协议标签交换（MPLS）虚拟专用网（VPN）的高效实现方法。结合协议规范,将转发与控制分离,主控负责对标记的分发与管理,转发引擎实现对MPLS分组的封装与转发。通过在控制层面对标记信息进行预处理,避免VPN业务分组在转发过程中的递归查找问题,使硬件转发数据包仅需一次查表,实现数据包的线速转发。     

一种基于受限约束范围标签传播的半监督学习算法

提出一种基于受限约束范围标签传播的半监督学习算法。首先利用相似性矩阵计算得出概率转移矩阵,进而通过概率转移矩阵得出受限约束范围。然后在约束范围内利用半监督学习框架下的标签传播算法计算基于路径的相似性,路径相似性决定了标签传播的重要路径。由于只使用几条重要的传播路径使得算法中省去计算每一条路径的相似度,计算复杂度大大减少。最终使得标签在带标签数据与未标签数据之间通过几条重要的路径之间传播。实验已经证明此算法的有效性。