Towards sustainable industry 4.0: A green real-time IIoT multitask scheduling architecture for distributed 3D printing services

As the keystones of the personalized manufacturing, the Industrial Internet of Things (IIoT) consolidated with 3D printing pave the path for the era of Industry 4.0 and smart manufacturing. By resembling the age of craft manufacturing, Industry 4.0 expedites the alteration from mass production to mass customization. When distributed 3D printers (3DPs) are shared and collaborated in the IIoT, a promising dynamic, globalized, economical, and time-effective manufacturing environment for customized products will appear. However, the optimum allocation and scheduling of the personalized 3D printing tasks (3DPTs) in the IIoT in a manner that respects the customized attributes submitted for each model while satisfying not only the real-time requirements but also the workload balancing between the distributed 3DPs is an inevitable research challenge that needs further in-depth investigations. Therefore, to address this issue, this paper proposes a real-time green-aware multi-task scheduling architecture for personalized 3DPTs in the IIoT. The proposed architecture is divided into two interconnected folds, namely, allocation and scheduling. A robust online allocation algorithm is proposed to generate the optimal allocation for the 3DPTs. This allocation algorithm takes into consideration meeting precisely the customized user-defined attributes for each submitted 3DPT in the IIoT as well as balancing the workload between the distributed 3DPs simultaneously with improving their energy efficiency. Moreover, meeting the predefined deadline for each submitted 3DPT is among the main objectives of the proposed architecture. Consequently, an adaptive real-time multi-task priority-based scheduling (ARMPS) algorithm has been developed. The built ARMPS algorithm respects both the dynamicity and the real-time requirements of the submitted 3DPTs. A set of performance evaluation tests has been performed to thoroughly investigate the robustness of the proposed algorithm. Simulation results proved the robustness and scalability of the proposed architecture that surpasses its counterpart state-of-the-art architectures, especially in high-load environments.     

多频段脑功能网络融合的阿尔茨海默病分类

将图论与机器学习方法相结合的阿尔茨海默病计算机辅助中,脑网络的构建大多是基于滤波去噪后的全频段BOLD信号匹配,忽略了不同脑活动信息的差异.因此,本文提出了一种多频段脑功能网络融合模型.首先将离散小波变换应用于BOLD信号中,得到不同频域下的体素信号,而后计算同频信号的相关性,获取不同频段下相关矩阵.而后计算所有矩阵的网络特征,在特征选择后基于SVM对患者进行分类.从实验结果可以看出,分频下的脑功能网络特征与未分频网络相比能在一定程度上提高分类的准确性;体素级网络由于可以更加详细的表达脑网络的变化,其分类效果要优于脑区级.     

融合知识图谱的网络安全违法行为识别系统

《网络安全法》是我国第一部关于网络安全的综合立法,与大众的互联网生活息息相关.因此,一款面向大众的《网络安全法》智能违法行为识别系统有助于规范互联网行为.然而,现有智能违法行为识别系统构建方法难以适应《网络安全法》,这是由于:首先,现有方法需要专业司法语言进行交互,不适应普通大众的语言体系.其次,现有方法需要大量的案例训练模型,不适应案例匮乏的《网络安全法》.针对这些问题,本文提出了一个面向《网络安全法》的智能违法行为识别系统.该系统主要利用知识图谱技术解决上述问题,在构建网络安全法知识图谱的基础上,通过将普通用户的自然语言与知识图谱中的违法事件实体和违法主体实体进行实体链接的方式获得更强的特征,提高违法行为识别系统在训练集较为匮乏的条件下的准确度.通过在真实数据集上的实验,表明了提出的系统的准确度有明显提高.     

一种基于图卷积网络的文本多标签学习方法

多标签学习广泛应用于文本分类、标签推荐、主题标注等.最近,基于深度学习技术的多标签学习受到广泛关注,针对如何在多标签学习中有效挖掘并利用高阶标签关系的问题,提出一种基于图卷积网络探究标签高阶关系的模型TMLLGCN.该模型采用GCN的映射函数从数据驱动的标签表示中生成对象分类器挖掘标签高阶关系.首先,采用深度学习方法提取文本特征,然后以数据驱动方式获得基础标签关联表示矩阵,为更好地建模高阶关系及提高模型效果,在基础标签关联表示矩阵上考虑未标记标签集对已知标签集的影响进行标签补全,并以此相关性矩阵指导GCN中标签节点之间的信息传播,最后将提取的文本特征应用到学习高阶标签关系的图卷积网络分类器进行端到端训练,综合标签关联和特征信息作为最终的预测结果.在实际多标签数据集上的实验结果表明,提出的模型能够有效建模标签高阶关系且提升了多标签学习的效果.     

一种基于有向二分图模型和贝叶斯网络的入侵检测方法

针对入侵检测中存在的非确定性推理问题,文章提出一种基于二分图模型和贝叶斯网络的入侵检测方法,该方法利用二分有向图模型表示入侵和相关特征属性之间的因果拓扑关系,利用训练数据中获取模型的概率参数,最后使用最大可能解释对转化后的推理问题进行推理,并通过限定入侵同时发生的数目来提高检测效率。实验表明,该方法具有较高的检测率和很好的鲁棒性。     

Routing with multiple quality-of-services constraints: An approximation perspective

Finding a path that satisfies multiple Quality-of-Service (QoS) constraints is vital to the deployment of current emerged services. However, existing algorithms are not very efficient and effective at finding such a path. Moreover, few works focus on three or more QoS constraints. In this paper, we present an enhanced version of fully polynomial time approximation scheme (EFPTAS) for multiconstrainted path optimal (MCOP) problem. Specifically, we make four major contributions. We first allow the proposed algorithm to construct an auxiliary graph, through which the QoS parameters on each of the finding path can be guaranteed not to exceed the given constraints. Then we adopt a concept, called nonlinear definition of path constraints in EFPTAS for reducing both time and space complexity. Also, we enable EFPTAS to run iteratively to facilitate a progressive refinement of the finding result. In addition to these, we identify some “deployment” issues for proposed algorithm, the essential steps that how and when the EFPTAS takes place are presented. By analyzing the proposed algorithm theoretically, we find that the presented EFPTAS can find a (1+ε)-approximation path in the network with time complexity O(|E||V|/ε) (where |E| is the number of edges and |V| is the number of nodes), which outperforms the previous best-known algorithm for MCOP. We conduct an extensive comparison between the algorithm presented in this paper and previous best-known study experimentally, our results indicate that EFPTAS can find a path with low complexity and preferable quality.     

基于多信号流模型的模型封装与解包技术

随着科技的快速发展,设备系统的复杂程度越来越高,多信号流模型是系统测试性分析的常用模型,为解决复杂系统建模分析时对其各分系统信息保密问题,提出了一种基于多信号流模型的模型封装与解包方法。该方法首先确定了封装模块数据信息并实现封装,然后构建封装模块测试信息描述表,描述了封装模块内部故障、内部测试与外部信息的关系以及封装模块本身对外部信息的影响,实现了模块的解包。实验表明,该描述方法可以有效地屏蔽了被封装的分系统模型的技术信息,有利于各分系统设计者之间的信息保密,同时利用该描述方法,还可以有效地减少测试性分析所需的时间。     

压力容器CAD绘图软件包的研究

本文结合压力容器计算机辅助设计软件的研制,研究了利用AUTOCAD开发计算机辅助设计专用软件的几个关键性问题;主要有程序绘图,汉字信息、绘图数据的显示和选择以及与绘图程序的连接、专用软件的控制结构设计和内存管理等问题;提出了一整套设计新颖,使用方便,运行高效的解决方法。     

基于图像内容层次表征的遥感图像 分割方法

提出基于图像内容层次表征的高分辨率遥感图像快速多精度分割方法。首先根据初始分割结果建立区域邻接图(RAG),并将其定义为马尔可夫随机场(MRF);然后引入光谱、形状和边缘等图像特征进行层次合并,通过记录层次合并过程获得图像内容的层次表征;最后根据层次表征中不同层级对象之间的关系快速生成任意不同精度的分割结果,以满足不同应用的需求。利用QuickBird卫星图像进行实验和评价的结果表明,本文方法具有较高的精度和效率。     

带有局部控制因子的图割光流估计

提出一种带有局部空间项控制因子的图割光流估计算法,能判断和处理光流场的平移遮挡现象。文中分析了平移遮挡的形成机理,构造了遮挡判别公式,基于本次的正向和反向光流场,依靠遮挡判别结果调节局部空间项控制因子,建立下次的能量泛函,加强背景区域对遮挡区域的平滑作用,隔绝运动区域对遮挡区域的平滑作用,从而构造出新结构的网络流图。另外,该算法被证明可以阻断遮挡误判在各次图割优化过程间的传递,从而使逐次α-扩散移动图割光流算法具有自适应处理遮挡的能力。通过与Ground-truth光流场的实验对比,表明该算法能较好地判断与处理遮挡导致的光流场无效区域。