A Note on the Inverse Connected p-Median Problem on Block Graphs

Recently, the inverse connected p-median problem on block graphs G(V,E,w) under various cost functions, say rectilinear norm, Chebyshev norm, and bottleneck Hamming distance. Their contributions include finding a necessary and sufficient condition for the connected p-median problem on block graphs, developing algorithms and showing that these problems can be solved in O(n log n) time, where n is the number of vertices in the underlying block graph. Using similar technique, we show that some results are incorrect by a counter-example. Then we redefine some notations, reprove Theorem 1 and redescribe Theorem 2, Theorem 3 and Theorem 4.

The Backup 2-Median Problem on Block Graphs

The backup 2-median problem is a location problem to locate two facilities at vertices with the minimum expected cost where each facility may fail with a given probability. Once a facility fails, the other one takes full responsibility for the services. Here we assume that the facilities do not fail simultaneously. In this paper, we consider the backup 2-median problem on block graphs where any two edges in one block have the same length and the lengths of edges on different blocks may be different. By constructing a tree-shaped skeleton of a block graph, we devise an O（n log n q- m）-time algorithm to solve this problem where n and m are the number of vertices and edges, respectively, in the given block graph.

SMITH NORMAL FORMAL OF DISTANCE MATRIX OF BLOCK GRAPHS

A connected graph, whose blocks are all cliques （of possibly varying sizes）, is called a block graph. Let D（G） be its distance matrix. In this note, we prove that the Smith normal form of D（G） is independent of the interconnection way of blocks and give an explicit expression for the Smith normal form in the case that all cliques have the same size, which generalize the results on determinants.

A class of geodetic blocks with given diameter and girth by subdividing Petersen graph

In this paper,we obtain a class of new geodetic block with given diameter and girth by subdividing Petersen graph.

RESEARCH ON THE BLOCKING FLOW IN A TRANSPORTATION NETWORK──THE GENERAL CONCEPTS AND THEORY OF THE BLOCKING FLOW

Blockage is a kind of phenomenon occurring frequently in modern transportation network. This paper deals with the research work on the blocking now in a network with the help of network flow theory. The blockage phenomena can be divided intO local blockage and network blockage. In this paper, which deals mainly with the latter, the fundamental concepts and definitions of network blocking flow, blocking outset are presented and the related theorems are proved. It is proved that the sufficient and necessary condition for the emergence of a blocking now in a network is the existence of the blocking outset. The necessary conditions for the existence of the blocking outset in a network are analysed and the characteristic cutset of blockage which reflects the all possible situation of blocking nows in the network is defined.In the last part of the paper the mathematical model of the minimum blocking now is developed and the solution to a small network is given.

EIGENVALUES OF A SPECIAL KIND OF SYMMETRIC BLOCK CIRCULANT MATRICES

In this paper, the spectrum and characteristic polynomial for a special kind of symmetric block circulant matrices are given.

On the Supereulerian Index of a Graph

Two methods for determining the supereulerian index of a graph G are given. A sharp upper bound and a sharp lower bound on the supereulerian index by studying the branch bonds of G are got.

RESEARCH ON THE LOCAL BLOCKAGE OF A TRANSPORTATION NETWORK AND ITS MINIMUM FLOW CAPACITY

This paper deals with the research work on the phenomena of local blockage in a transportation network. Onthe basis of introducing the research results in [1], theminimum now capacity problem of a network in the mostseriously blocked situation is studied. With the conceptof complete outset presented in [1], the relationship between the minimum now capacity of a network and its minimum complete cut capacity is discussed, and the reasons for the difference betweent the minimum now capacity of a network and its minimum complete cut capa-city are analysed. In order to get the solution to the problem, the concepts of normalization of a network and its blocking path graph are presented. In the paper it is proved that the necessary and sufficient conditions for the equality between the minumum now capacity and its minumum complete cut capacity are the existence of a feasible flow in the blocking path graph. For the reason that there are some dependent production points in the blocking path graph of a network, the proof about the tenability of the Gale's Theorm for the planat normalized network without circuit is made.

基于自适应时空图神经网络的交通预测

准确的交通预测对城市规划、交通安全有着重要的意义。现有的预测模型大多集中在设计复杂的预定义的图来捕获交通数据的特征。然而,交通数据具有很强的空间依赖性,这意味着道路网络拓扑图的节点之间往往存在着复杂的相关性,并且道路网络的拓扑图随着时间的推移而变化。预定义的图可能无法完整获取交通信息。针对该问题,提出了一个基于自适应时空图神经网络的交通预测模型,首先提出一个图结构学习组件,分别捕获交通网络的宏观和微观信息,将它们集成为最优图邻接矩阵。然后设计一个时空卷积块用以捕获交通数据的时空特性。在METR-LA和PEMS-BAY数据集上展开实验,实验结果表明所提出模型的预测性能优于主流模型。

基于GPA+CBAM的域自适应水下目标检测方法

针对水下目标检测易出现域偏移而导致检测精度下降的现象,文中提出了基于图诱导原型对齐(GPA)的域自适应水下目标检测方法。该方法通过区域建议之间基于图的信息传播得到图像中的实例级特征,导出每个类别的原型表示用于类别级域对齐,从而聚合水下目标的不同模态信息,以此实现源域和目标域的对齐,减少域偏移带来的影响;同时添加了卷积块注意模块(CBAM),使神经网络能够专注于不同水域分布下的实例级特征。实验结果证明该方法能够有效提高发生域偏移时的检测精度。

基于局部图块目标匹配的交通车流跟踪与统计

针对传统目标跟踪算法在实现过程中的局限,提出一种基于局部图块目标匹配(local block-graphs targets matching,-LBTM)的跟踪算法,将其应用于车流跟踪,并验证其有效性。首先,采集视频帧画面中含有目标的多幅图像,并对其进行局部图块分割,得到目标图块;其次,对图块进行目标匹配,通过匹配完成对目标的检测过程,并计算得到最优的目标集合;最后,针对目标集合进行全部帧画面的最小偏差的预测,实现目标的跟踪过程。选取某路口的交通监控视频进行对比验证实验,实验结果表明:所提出的算法可以有效地跟踪车辆,比传统算法有更好的目标检测率和跟踪准确率,并能有效地完成车流统计。

基于Mathews稳定图的矿体可崩性研究

通过对金川III矿区的工程地质调查、矿岩力学性质试验,获得了表征矿山岩体工程质量的多种指标,在分析了这些指标后,选取了节理间距、RQD、地下水、结构面状态和岩石单轴抗压强度指标建立了III矿区的可崩性评价模型。根据可崩性模型统计出了Mathews稳定图法所需要的参数,即RMR值和岩石的单轴抗压强度。根据这些参数,应用Mathews稳定图法中稳定数的计算方法,计算出每个评价区域的稳定数,然后根据稳定数利用Mathews稳定图计算出每个评价区域的持续崩落水力半径,通过对计算结果的分析表明这些区域适合应用自然崩落法进行开采。

基于超级块支配图插装的软件测试工具设计与实现

通过超级块支配图来分析软件测试探针的合理插装位置,可有效地减少插装探针数量,降低代码插装对程序的影响。基于超级块支配图的代码插装原理,设计一种针对C语言的软件自动测试工具(SAT),介绍了该工具中词法语法分析器、静态分析器、代码插装器等主要功能模块的具体实现方案,同时对SAT的插装性能进行了分析。

机电一体化系统建模技术与仿真软件的研究与分析

总结了国际上目前研究的几种可以实现自动向数学模型转化的机电一体化系统理想的物理模型建立的方法,即键合图方法、面向对象的方法、方块图方法、系统图方法和混合Petri网方法。分析研究了由Lancaster大学EDC(Engineering Design Center)中心的研究者们开发的计算机辅助机电一体化系统概念设计的建模与仿真软件Schemebuilder,研究了用键合图方法建模的仿真软件20-sim和使用面向对象方法建模的仿真软件Dymola,以及使用方块图建模的控制系统仿真软件Matlab和机械机构系统仿真软件Adams。最后总结了机电一体化建模与仿真的发展趋势,即机电相结合的机电一体化系统仿真软件为机电一体化系统理想的建模和仿真环境。

考虑时空耦合特性的非侵入式综合能源系统多能设备负荷辨识方法

为了提升非侵入式综合能源系统多能设备负荷辨识的准确性,在充分考虑多能负荷时空耦合特性的基础上,提出了一种基于改进滑动窗口双边累计和(cumlative sum,CUSUM)、图半监督学习(graph semi supervised learning,GBSSL)和改进胶囊网络(improve capsule network,ICapsNet)的非侵入式综合能源系统多能设备负荷辨识方法。首先,引入自适应噪声值选取方法对滑动窗口双边CUSUM算法进行改进,并利用改进后的算法进行事件检测,之后通过GBSSL标记未标记的样本;其次,在CapsNet的基础上,改进相似度和加权求和计算方法,利用残差块结构卷积网络替代原卷积模块,并将极化自注意块引入主胶囊模块,构建ICapsNet;最后,利用不同的非侵入负荷辨识方法对采集的10 150个综合能源负荷数据进行负荷辨识,验证所提方法的优越性。实验结果表明:所提方法相较于BI-GRU、Bagging EL和DNN等主流非侵入负荷辨识方法,P_(recision)、R_(ecall)、F_(macro)和BA指标分别平均提高了1.77%、2.14%、1.94%和1.26%。由此可知所提方法对能够精准地辨识非侵入式综合能源系统多能设备负荷,且具有良好的运算效率和通用性。

部分逆M矩阵的完备式问题

采用图论的方法研究了任意阶非负位置对称的部分矩阵的逆 M矩阵最大化完备式问题 ,给出了相应的算法 .利用此算法可以很方便地求出任意阶非负位置对称的部分矩阵的逆

剖分Petersen图得到的新测地块(英文)

通过剖分Petersen图我们得到了一类新的测地块.由此成功构造了给定直 径为6和围长为11的测地块,解决了近二十年来悬而未决的一个存在性和构造性问题.

汇编程序覆盖测试中分支路径数的计算

说明了覆盖测试是软件测试中的重要方法,是软件动态测试的基本手段。并提出通过基本块存储矩阵和邻接表来处理汇编语言程序流图,从而计算其分支路径数的算法并验证其正确性,为进一步的分支覆盖率计算奠定基础。实验证明,该方法能高效准确地计算出给定汇编程序的分支路径数。

基于AOV图和多叉树的功能块程序编译算法

针对可编程逻辑控制器(PLC)的功能块(Function BlockDiagrams,FBD)程序指令类型多、串并联复杂和多重输出等问题,提出一种基于顶点活动图(Activity on Vertex,AOV)和多叉树的功能块程序编译算法。该算法将功能块程序映射为AOV图,首先用邻接表存储AOV图中的顶点信息和顶点之间的连接信息,对功能块程序进行语法检查,然后通过邻接表建立表示功能块间逻辑关系的多叉树,通过先根遍历算法遍历多叉树确定功能块执行顺序,最后按照遍历顺序和PLC指令结构将功能块程序转换成二进制代码,形成目标程序。该算法能将PLC支持的功能块指令程序编译为目标程序,具有通用性,已经成功应用在PLC开发平台软件PLC_Config中。

基于近邻图改进的块对角子空间聚类算法

块对角表示(BDR)模型可以通过利用线性表示对数据有效地进行聚类,却无法很好地利用高维数据常见的非线性流形结构信息。针对这一问题,提出了基于近邻图改进的块对角子空间聚类(BDRNG)算法来通过近邻图来线性拟合高维数据的局部几何结构,并通过块对角约束来生成具有全局信息的块对角结构。BDRNG同时学习全局信息以及局部数据结构,从而获得更好的聚类表现。由于模型包含近邻图算子和非凸的块对角表示范数,BDRNG采用了交替最小化来优化求解算法。实验结果如下:在噪声数据集上,BDRNG能够生成稳定的块对角结构系数矩阵,这说明了BDRNG对于噪声数据具有鲁棒性;在标准数据集上,BDRNG的聚类表现均优于BDR,尤其在人脸数据集上,相较于BDR,BDRNG的聚类准确度提高了8%。