In underground mining,the belt is a critical component,as its state directly affects the safe and stable operation of the conveyor.Most of the existing non-contact detection methods based on machine vision can only de...In underground mining,the belt is a critical component,as its state directly affects the safe and stable operation of the conveyor.Most of the existing non-contact detection methods based on machine vision can only detect a single type of damage and they require pre-processing operations.This tends to cause a large amount of calculation and low detection precision.To solve these problems,in the work described in this paper a belt tear detection method based on a multi-class conditional deep convolutional generative adversarial network(CDCGAN)was designed.In the traditional DCGAN,the image generated by the generator has a certain degree of randomness.Here,a small number of labeled belt images are taken as conditions and added them to the generator and discriminator,so the generator can generate images with the characteristics of belt damage under the aforementioned conditions.Moreover,because the discriminator cannot identify multiple types of damage,the multi-class softmax function is used as the output function of the discriminator to output a vector of class probabilities,and it can accurately classify cracks,scratches,and tears.To avoid the features learned incompletely,skiplayer connection is adopted in the generator and discriminator.This not only can minimize the loss of features,but also improves the convergence speed.Compared with other algorithms,experimental results show that the loss value of the generator and discriminator is the least.Moreover,its convergence speed is faster,and the mean average precision of the proposed algorithm is up to 96.2%,which is at least 6%higher than that of other algorithms.展开更多
The reliability of a network is an important indicator for maintaining communication and ensuring its stable operation. Therefore, the assessment of reliability in underlying interconnection networks has become an inc...The reliability of a network is an important indicator for maintaining communication and ensuring its stable operation. Therefore, the assessment of reliability in underlying interconnection networks has become an increasingly important research issue. However, at present, the reliability assessment of many interconnected networks is not yet accurate,which inevitably weakens their fault tolerance and diagnostic capabilities. To improve network reliability,researchers have proposed various methods and strategies for precise assessment. This paper introduces a novel family of interconnection networks called general matching composed networks(gMCNs), which is based on the common characteristics of network topology structure. After analyzing the topological properties of gMCNs, we establish a relationship between super connectivity and conditional diagnosability of gMCNs. Furthermore, we assess the reliability of g MCNs, and determine the conditional diagnosability of many interconnection networks.展开更多
Crossed cubes network is a kind of interconnection structure as a basis for distributed memory parallel computer architecture. Reliability takes an important role in fault tolerant computing on multiprocessor systems....Crossed cubes network is a kind of interconnection structure as a basis for distributed memory parallel computer architecture. Reliability takes an important role in fault tolerant computing on multiprocessor systems. Connectivity is a vital metric to explore fault tolerance and reliability of network structure based on a graph model. Let be a connected graph. The k-conditional edge connectivity is the cardinality of the minimum edge cuts , if any, whose deletion disconnects and each component of has property of minimum degree . The k-conditional connectivity can be defined similarly. In this paper, we determine the k- conditional (edge) connectivity of crossed cubes for small k. And we also prove other properties of .展开更多
Let G =（V, E） be a connected graph and m be a positive integer, the conditional edge connectivity λ;is the minimum cardinality of a set of edges,if it exists, whose deletion disconnects G and leaves each remaining ...Let G =（V, E） be a connected graph and m be a positive integer, the conditional edge connectivity λ;is the minimum cardinality of a set of edges,if it exists, whose deletion disconnects G and leaves each remaining component with minimum degree δ no less than m. This study shows that λ;(Q;) = 2 n,λ;(Q;) = 4 n-4（2 ≤ k ≤ n-1, n ≥ 3） for n-dimensional enhanced hypercube Q;. Meanwhile, another easy proof about λ;（Q;） = 4 n-8, for n ≥ 3 is proposed. The results of enhanced hypercube include the cases of folded hypercube.展开更多
Diagnosability of multiprocessor systems is an important research topic.The system and an interconnection network have an underlying topology,which is usually presented by a graph.In 2012,Peng et al.proposed a metric ...Diagnosability of multiprocessor systems is an important research topic.The system and an interconnection network have an underlying topology,which is usually presented by a graph.In 2012,Peng et al.proposed a metric for fault diagnosis of the graph,namely,the n-neighbor diagnosability that restrains every fault-free node to contain at least n fault-free neighbors.It is difficult to get the n-neighbor diagnosability of the graph from the definition of the n-neighbor diagnosability.Afterwards,some sufficient and necessary conditions are given.It is also difficult to find the n-neighbor diagnosability of the graph from those results.In this paper,we show some new sufficient conditions for the graph to be n-neighbor d-diagnosable under the MM*model.It improves the corresponding result of[Theoretical Computer Science 773(2019)107-114].展开更多
微机电技术、移动计算技术和无线通信技术的飞速发展,促使在现有道路网上快速构建一个自组织、分布式控制的车辆间多跳通信网络成为现实,随之引起了一系列问题亟待解决,例如高速运动车辆间的物理拓扑连通性,它是车用自组织网络(vehicula...微机电技术、移动计算技术和无线通信技术的飞速发展,促使在现有道路网上快速构建一个自组织、分布式控制的车辆间多跳通信网络成为现实,随之引起了一系列问题亟待解决,例如高速运动车辆间的物理拓扑连通性,它是车用自组织网络(vehicular ad hoc network,简称VANET)对用户提供可靠服务的先决条件.针对上述问题,推导得出了一种用于高速公路场景中车用自组织网络1-连通必要条件的概率计算方法,并借助真实的车辆运动轨迹数据做了大量模拟实验.实验结果表明,为了确保网络中不存在孤立节点,每个节点的通信距离应满足Θ(|log(1-p1/n)|/n).展开更多
基金This work was supported by the Shanxi Province Applied Basic Research Project,China(Grant No.201901D111100).Xiaoli Hao received the grant,and the URL of the sponsors’website is http://kjt.shanxi.gov.cn/.
文摘In underground mining,the belt is a critical component,as its state directly affects the safe and stable operation of the conveyor.Most of the existing non-contact detection methods based on machine vision can only detect a single type of damage and they require pre-processing operations.This tends to cause a large amount of calculation and low detection precision.To solve these problems,in the work described in this paper a belt tear detection method based on a multi-class conditional deep convolutional generative adversarial network(CDCGAN)was designed.In the traditional DCGAN,the image generated by the generator has a certain degree of randomness.Here,a small number of labeled belt images are taken as conditions and added them to the generator and discriminator,so the generator can generate images with the characteristics of belt damage under the aforementioned conditions.Moreover,because the discriminator cannot identify multiple types of damage,the multi-class softmax function is used as the output function of the discriminator to output a vector of class probabilities,and it can accurately classify cracks,scratches,and tears.To avoid the features learned incompletely,skiplayer connection is adopted in the generator and discriminator.This not only can minimize the loss of features,but also improves the convergence speed.Compared with other algorithms,experimental results show that the loss value of the generator and discriminator is the least.Moreover,its convergence speed is faster,and the mean average precision of the proposed algorithm is up to 96.2%,which is at least 6%higher than that of other algorithms.
基金supported by National Natural Science Foundation of China (No.62362005)。
文摘The reliability of a network is an important indicator for maintaining communication and ensuring its stable operation. Therefore, the assessment of reliability in underlying interconnection networks has become an increasingly important research issue. However, at present, the reliability assessment of many interconnected networks is not yet accurate,which inevitably weakens their fault tolerance and diagnostic capabilities. To improve network reliability,researchers have proposed various methods and strategies for precise assessment. This paper introduces a novel family of interconnection networks called general matching composed networks(gMCNs), which is based on the common characteristics of network topology structure. After analyzing the topological properties of gMCNs, we establish a relationship between super connectivity and conditional diagnosability of gMCNs. Furthermore, we assess the reliability of g MCNs, and determine the conditional diagnosability of many interconnection networks.
文摘Crossed cubes network is a kind of interconnection structure as a basis for distributed memory parallel computer architecture. Reliability takes an important role in fault tolerant computing on multiprocessor systems. Connectivity is a vital metric to explore fault tolerance and reliability of network structure based on a graph model. Let be a connected graph. The k-conditional edge connectivity is the cardinality of the minimum edge cuts , if any, whose deletion disconnects and each component of has property of minimum degree . The k-conditional connectivity can be defined similarly. In this paper, we determine the k- conditional (edge) connectivity of crossed cubes for small k. And we also prove other properties of .
文摘Let G =（V, E） be a connected graph and m be a positive integer, the conditional edge connectivity λ;is the minimum cardinality of a set of edges,if it exists, whose deletion disconnects G and leaves each remaining component with minimum degree δ no less than m. This study shows that λ;(Q;) = 2 n,λ;(Q;) = 4 n-4（2 ≤ k ≤ n-1, n ≥ 3） for n-dimensional enhanced hypercube Q;. Meanwhile, another easy proof about λ;（Q;） = 4 n-8, for n ≥ 3 is proposed. The results of enhanced hypercube include the cases of folded hypercube.
基金Supported by National Natural Science Foundation of China(Grant No.61772010)。
文摘Diagnosability of multiprocessor systems is an important research topic.The system and an interconnection network have an underlying topology,which is usually presented by a graph.In 2012,Peng et al.proposed a metric for fault diagnosis of the graph,namely,the n-neighbor diagnosability that restrains every fault-free node to contain at least n fault-free neighbors.It is difficult to get the n-neighbor diagnosability of the graph from the definition of the n-neighbor diagnosability.Afterwards,some sufficient and necessary conditions are given.It is also difficult to find the n-neighbor diagnosability of the graph from those results.In this paper,we show some new sufficient conditions for the graph to be n-neighbor d-diagnosable under the MM*model.It improves the corresponding result of[Theoretical Computer Science 773(2019)107-114].
文摘微机电技术、移动计算技术和无线通信技术的飞速发展,促使在现有道路网上快速构建一个自组织、分布式控制的车辆间多跳通信网络成为现实,随之引起了一系列问题亟待解决,例如高速运动车辆间的物理拓扑连通性,它是车用自组织网络(vehicular ad hoc network,简称VANET)对用户提供可靠服务的先决条件.针对上述问题,推导得出了一种用于高速公路场景中车用自组织网络1-连通必要条件的概率计算方法,并借助真实的车辆运动轨迹数据做了大量模拟实验.实验结果表明,为了确保网络中不存在孤立节点,每个节点的通信距离应满足Θ(|log(1-p1/n)|/n).
