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Structural modeling of a typical gas turbine system

Naresh YADAV, Irshad Ahmad KHAN, Sandeep GROVER

《能源前沿（英文）》 2012年第6卷第1期页码 57-79 doi: 10.1007/s11708-011-0164-8

摘要： This paper presents an approach for the structural modeling and analysis of a typical gas turbine system. This approach has been applied to the systems and subsystems, which are integral parts of a typical gas turbine system. Since a gas turbine system performance is measured in terms of fluid flow energy transformations across its various assemblies and subassemblies, the performance of such subsystems affects the overall performance of the gas turbine system. An attempt has been made to correlate the associativity of such subsystems contributing to overall gas turbine system functional evaluation using graph theoretic approach. The characteristic equations at the system level as well as subsystem level have been developed on the basis of associativity of various factors affecting their performance. A permanent function has been proposed for the functional model of a gas turbine system, which further leads to selection, identification and optimal evaluation of gas turbine systems.

关键词： system modeling gas turbine system evaluation graph theoretic approach

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一种构建网络安全知识图谱的实用方法 Article

贾焰, 亓玉璐, 尚怀军, 江荣, 李爱平

《工程（英文）》 2018年第4卷第1期页码 53-60 doi: 10.1016/j.eng.2018.01.004

摘要：

网络攻击的形式复杂多变，检测和预测这些动态类型的攻击是一项充满挑战的任务。在当前的许多领域中，对于知识图谱的研究已经非常成熟。目前，有学者提出将知识图谱的概念与网络安全结合在一起来构建网络安全知识库，这是一件非常有意义的工作。基于这种理念，本文提出了一个构建网络安全知识图谱的方法和基于五元组模型的推演规则。本文使用机器学习的方法来抽取实体，然后构建本体，从而构建网络安全知识库。在构建网络安全知识库的过程中，使用Stanford NER 来训练提取器，然后利用提取器抽取所需的相关信息。本文提出的推演规则是基于五元组模型的，新的属性是通过计算公式推导得到的，新的关系是基于路径排序算法，同样是通过计算公式推导得到的。

关键词：网络安全知识图谱知识推演

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Classifying multiclass relationships between ASes using graph convolutional network

《工程管理前沿（英文）》页码 653-667 doi: 10.1007/s42524-022-0217-1

摘要： Precisely understanding the business relationships between autonomous systems (ASes) is essential for studying the Internet structure. To date, many inference algorithms, which mainly focus on peer-to-peer (P2P) and provider-to-customer (P2C) binary classification, have been proposed to classify the AS relationships and have achieved excellent results. However, business-based sibling relationships and structure-based exchange relationships have become an increasingly nonnegligible part of the Internet market in recent years. Existing algorithms are often difficult to infer due to the high similarity of these relationships to P2P or P2C relationships. In this study, we focus on multiclassification of AS relationship for the first time. We first summarize the differences between AS relationships under the structural and attribute features, and the reasons why multiclass relationships are difficult to be inferred. We then introduce new features and propose a graph convolutional network (GCN) framework, AS-GCN, to solve this multiclassification problem under complex scenes. The proposed framework considers the global network structure and local link features concurrently. Experiments on real Internet topological data validate the effectiveness of our method, that is, AS-GCN. The proposed method achieves comparable results on the binary classification task and outperforms a series of baselines on the more difficult multiclassification task, with an overall metrics above 95%.

关键词： autonomous system multiclass relationship graph convolutional network classification algorithm Internet topology

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Game theoretic analysis of environmental impact assessment system in China

CHENG Hongguang, PU Xiao, GONG Li, QI Ye

《环境科学与工程前沿（英文）》 2007年第1卷第4期页码 448-453 doi: 10.1007/s11783-007-0071-8

摘要： Environmental impact assessment (EIA) system has been established in China since 1973. In present EIA cases, there are four participants in general: governments, enterprises, EIA organizations and the public. The public has held re

关键词： public impact assessment Environmental impact general

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一种知识引导的基于中医学信息的药材推荐方法 Research Article

金哲,张引,苗嘉旭,杨易,庄越挺,潘云鹤

《信息与电子工程前沿（英文）》 2023年第24卷第10期页码 1416-1429 doi: 10.1631/FITEE.2200662

摘要：在中国几千年历史中，中医一直是人们关注的焦点。近年来，随着人工智能技术的兴起，部分研究开始以数据驱动的方式学习中医的方剂，即根据病人的症状推荐一组药材。现有大多数药材推荐模型忽略了中医领域的知识，例如药材和症状之间的关系，中药药方形成逻辑，等等。本文提出一种以知识为引导、结合中医学信息的药材推荐方法。本文使用的知识包括从中医典籍及处方中提取的知识图谱，以此得到症状和药材之间的交互和共生关系。利用这些信息，基于图注意力网络提取症状和药材的特征向量。在此基础上，将处方学等中医学信息加入到预测层中，提高了模型对药材的预测能力。最后，在中医处方数据集上进行的实验表明，该方法优于目前主流的药材推荐算法。

关键词：中医；药材推荐；知识图谱；图注意力网络

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锥形凹模缩口力的理论计算与试验验证

胡成武,罗文波,彭炎荣

《中国工程科学》 2005年第7卷第6期页码 54-56

摘要：

缩口力是导致薄壁筒形件缩口失稳的重要因素。为了提高缩口力的计算精度，M·B·斯德洛日夫和E·π·翁克索夫综合考虑板厚变化、加工硬化及磨擦等因素的影响，分别提出了圆筒形件缩口力的计算方法；通过实例对该两种方法的计算结果进行了分析，并与实验数据做了比较。结果表明，两种方法的计算结果十分接近，而且与实验数据相吻合。

关键词：缩口力理论计算试验验证

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大规模图计算系统综述 Review

Ning LIU, Dong-sheng LI, Yi-ming ZHANG, Xiong-lve LI

《信息与电子工程前沿（英文）》 2020年第21卷第3期页码 384-404 doi: 10.1631/FITEE.1900127

摘要：图是描述实体之间关系的一种重要数据结构。现实世界中许多应用领域非常依赖图数据。然而，由于图计算应用与传统应用的显著差异，利用通用平台处理图计算应用是低效的，这极大推动了专用图计算系统的研究。本综述系统地对图算法和图计算应用进行分类，将现有图计算系统划分为通用和专用系统，并详细总结。深入分析图计算系统的实现技术，包括编程模型、分区策略、通信模型、执行模型和容错机制。最后，分析图计算领域最新进展，并提出有待进一步研究的4个问题。

关键词：图算法；图计算应用；图计算系统

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基于渐进式蚁群优化的多处理器任务分配 Article

Hamid Reza BOVEIRI

《信息与电子工程前沿（英文）》 2017年第18卷第4期页码 498-510 doi: 10.1631/FITEE.1500394

摘要：任务调度优化是多处理器环境（如并行和分布式系统）取得良好性能所面临的最重要挑战之一。目前大多数任务调度算法基于列表调度法，该方法的基本思路是，以列表的形式准备一系列待调度的节点，赋予这些节点不同优先级，然后不断去除列表中优先级最高的节点，并将其分配给具有最早开始时间（Earliest start time, EST）的处理器。由此可见，该算法的完成时间主要由两大因素决定：（1）任务分配顺序的选择（次序子问题）；（2）选定顺序的任务如何分配给处理器（分配子问题）。已有文献提出了许多解决次序子问题的好办法，但分配子问题少有人涉及。本文研究结果显示：传统的按照最早开始时间分配任务的方法并非最优；基于蚁群优化算法，得到一种新的方法，可以获得高效得多的调度方案。

关键词：蚁群优化；列表调度；多处理器任务图调度；并行与分布式系统

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基于非正交多址接入的雾无线接入网络中网络效益最大化的资源分配：博弈论方法 Research Article

曹雪妍,闫实,张洪铭

《信息与电子工程前沿（英文）》 2022年第23卷第10期页码 1546-1561 doi: 10.1631/FITEE.2100341

摘要：

基于非正交多址接入(NOMA)的雾无线接入网(F-RANs)提供了高频谱效率、超低延迟和巨大的网络吞吐量，这得益于雾接入点(F-APs)的边缘计算和通信功能。同时，在缓存阶段，具有缓存功能的F-APs负责进行大量多媒体文件的边缘缓存和传输，从而可以进一步降低传输能量和负担。工业界普遍需要的是在基于NOMA的F-RANs中高效的资源分配，包括缓存放置(CP)和无线电资源分配(RRA)，这是提高网络性能的关键。为此，本文首先描述了一种基于NOMA的F-RAN，其中具有缓存功能的F-APs通过NOMA协议与无线电远程单元同时为用户设备提供服务。在此基础上，提出一种基于网络效益最大化的资源分配问题，该效益同时考虑了缓存成本、收益和通信能效。本文将此NP难问题分解为两个子问题，即CP子问题和RRA子问题。最后，我们提出一种迭代方法和一种基于Stackelberg博弈的方法来求解各子问题。数值结果表明，在基于NOMA的F-RANs中，与现有资源分配方案相比，所提出的方法可以显著提高网络效益。

关键词：雾无线接入网；非正交多址接入；博弈论；缓存放置；资源分配

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Detecting large-scale underwater cracks based on remote operated vehicle and graph convolutional neural

Wenxuan CAO; Junjie LI

《结构与土木工程前沿（英文）》 2022年第16卷第11期页码 1378-1396 doi: 10.1007/s11709-022-0855-8

摘要： It is of great significance to quickly detect underwater cracks as they can seriously threaten the safety of underwater structures. Research to date has mainly focused on the detection of above-water-level cracks and hasn’t considered the large scale cracks. In this paper, a large-scale underwater crack examination method is proposed based on image stitching and segmentation. In addition, a purpose of this paper is to design a new convolution method to segment underwater images. An improved As-Projective-As-Possible (APAP) algorithm was designed to extract and stitch keyframes from videos. The graph convolutional neural network (GCN) was used to segment the stitched image. The GCN’s m-IOU is 24.02% higher than Fully convolutional networks (FCN), proving that GCN has great potential of application in image segmentation and underwater image processing. The result shows that the improved APAP algorithm and GCN can adapt to complex underwater environments and perform well in different study areas.

关键词： underwater cracks remote operated vehicle image stitching image segmentation graph convolutional neural network

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Distributed coordination inmulti-agent systems: a graph Laplacian perspective

Zhi-min HAN,Zhi-yun LIN,Min-yue FU,Zhi-yong CHEN

《信息与电子工程前沿（英文）》 2015年第16卷第6期页码 429-448 doi: 10.1631/FITEE.1500118

摘要： This paper reviews some main results and progress in distributed multi-agent coordination from a graph Laplacian perspective. Distributed multi-agent coordination has been a very active subject studied extensively by the systems and control community in last decades, including distributed consensus, formation control, sensor localization, distributed optimization, etc. The aim of this paper is to provide both a comprehensive survey of existing literature in distributed multi-agent coordination and a new perspective in terms of graph Laplacian to categorize the fundamental mechanisms for distributed coordination. For different types of graph Laplacians, we summarize their inherent coordination features and specific research issues. This paper also highlights several promising research directions along with some open problems that are deemed important for future study.

关键词： Multi-agent systems Distributed coordination Graph Laplacian

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Efficacy of intelligent diagnosis with a dynamic uncertain causality graph model for rare disorders of

Dongping Ning, Zhan Zhang, Kun Qiu, Lin Lu, Qin Zhang, Yan Zhu, Renzhi Wang

《医学前沿（英文）》 2020年第14卷第4期页码 498-505 doi: 10.1007/s11684-020-0791-8

摘要： Disorders of sex development (DSD) are a group of rare complex clinical syndromes with multiple etiologies. Distinguishing the various causes of DSD is quite difficult in clinical practice, even for senior general physicians because of the similar and atypical clinical manifestations of these conditions. In addition, DSD are difficult to diagnose because most primary doctors receive insufficient training for DSD. Delayed diagnoses and misdiagnoses are common for patients with DSD and lead to poor treatment and prognoses. On the basis of the principles and algorithms of dynamic uncertain causality graph (DUCG), a diagnosis model for DSD was jointly constructed by experts on DSD and engineers of artificial intelligence. “Chaining” inference algorithm and weighted logic operation mechanism were applied to guarantee the accuracy and efficiency of diagnostic reasoning under incomplete situations and uncertain information. Verification was performed using 153 selected clinical cases involving nine common DSD-related diseases and three causes other than DSD as the differential diagnosis. The model had an accuracy of 94.1%, which was significantly higher than that of interns and third-year residents. In conclusion, the DUCG model has broad application prospects as a computer-aided diagnostic tool for DSD-related diseases.

关键词： disorders of sex development (DSD) intelligent diagnosis dynamic uncertain causality graph

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认知无线网络中一种基于投影梯度的多用户功率控制方法 None

Yun-zheng TAO, Chun-yan WU, Yu-zhen HUANG, Ping ZHANG

《信息与电子工程前沿（英文）》 2018年第19卷第3期页码 367-378 doi: 10.1631/FITEE.1700067

摘要： 5G网络被认为能够支持未来爆炸性增长的数据需求，这主要得益于不断增长的高速移动用户数量以及人与物之间的交互预期。认知无线电（cognitive radio, CR）是提高频谱利用率的有效技术之一，可适应日益增长的数据流量和稀缺的频谱资源。本文研究了基于衬垫式频谱共享的认知无线网络中的次用户功率控制问题。与现有文献大多通过假设单一主用户或者单一信道来简化问题不同，本文研究了多主用户多次用户多信道这一更符合实际的场景。我们将功率控制问题描述为一个具有耦合约束的非合作博弈，其帕累托最优性和最大次网络吞吐量可通过纳什均衡解得。为得到该纳什均衡解，首先提出一种基于投影梯度的动态模型，证明该模型的平衡点等价于原博弈的纳什均衡，并提出一种集中式算法求解该平衡点。仿真结果验证了所提出算法的收敛性、有效性和优势，并且在网络规模增大的情况下验证了算法的鲁棒性。

关键词：认知无线网络；多用户功率控制；非合作博弈；纳什均衡；投影梯度

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Erratum to: Soft-HGRNs: soft hierarchical graph recurrent networks for multi-agent partially observable

Yixiang REN, Zhenhui YE, Yining CHEN, Xiaohong JIANG, Guanghua SONG

《信息与电子工程前沿（英文）》 2023年第24卷第3期页码 480-480 doi: 10.1631/FITEE.22e0073

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基于探针图的并行型图顶点着色DNA计算模型 Article

许进, 强小利, 张凯, 张成, 杨静

《工程（英文）》 2018年第4卷第1期页码 61-77 doi: 10.1016/j.eng.2018.02.011

摘要：

目前DNA 计算机研究中遇到的最大瓶颈是解空间指数爆炸问题，即随着问题规模的增大，所需要作为信息处理“数据”的DNA分子呈指数级增大。本文提出了一种新颖的图顶点着色DNA计算模型，该模型正是围绕着如何克服解空间指数爆炸问题以及如何提高运行速度而设计的。其主要贡献有：①通过如下三种方法来克服解空间指数爆炸问题：顶点颜色集的确定方法；子图分解方法以及子图中的顶点优化排序方法；②设计了一种并行型聚合酶链反应（PCR）操作技术，应用这种技术一次可以对图中多条边来删除非解，使得生物操作次数大大减少，极大地提高了运行速度。本文以一个3-着色的61 个顶点的图为例，实验表明，99% 的非可行解在构建初始解空间时就被删除，并利用DNA 自组装和并行PCR 方法，通过识别、拼接以及组装等技术得到解。由于该模型对任意61 个顶点的图是同样的操作方法，这就意味着，该模型的搜索能力可以达到O(359)。

关键词： DNA计算图顶点着色问题聚合酶链反应（PCR）