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2020 IEEE 15th International Conference of System of Systems Engineering (SoSE)最新文献

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A system-of-systems meta-architecting approach for seru production system design 用于服务生产系统设计的系统的元架构方法
Pub Date : 2020-06-01 DOI: 10.1109/SoSE50414.2020.9130488
Samuel Vanfossan, C. Dagli, Benjamin J. Kwasa
Sponsored by expedient technologic innovation, consumers frequently expect manufacturer offerings to exhibit extensive product variety and regular product advancement. These expectations have rendered many traditional production practices less applicable. Chiefly impacted is the notion of mass produced, low-variety artifacts via massive assembly lines. These operations have difficulty meeting the high-customization, short life-cycle requirements imposed by contemporary demand. Many industries and organizations have begun the transformation from these rigid assembly mechanisms to a more versatile, cellular production strategy known as seru production. To facilitate this transition, methods are needed to aid manufacturers in appropriately selecting and arranging seru system components, a critical step in seru system design. Herein, a generalized model is proposed utilizing a system-of-systems architecting approach to determine the component assembly best suiting the needs of the manufacturing entity. Candidate architectures are generated and evaluated using a multi-objective genetic algorithm from which a preferred alternative is selected through a fuzzy inference system. Directing this genetic algorithm, domain-independent objectives are presented, maintaining applications to most seru production design scenarios. The proposed method is then applied to a camera production example, culminating in the identification of a well-performing architecture. The presented method should find increased use as organizations further adopt this flexible production methodology.
在权宜之计技术创新的赞助下,消费者经常期望制造商提供广泛的产品品种和定期的产品进步。这些期望使得许多传统的生产方法不再适用。主要受到影响的是通过大规模装配线大规模生产的低品种人工制品的概念。这些操作难以满足当代需求所强加的高定制化、短生命周期的要求。许多行业和组织已经开始从这些严格的组装机制转变为一种更通用的、被称为血清生产的细胞生产策略。为了促进这种过渡,需要帮助制造商适当选择和安排血清系统组件的方法,这是血清系统设计的关键步骤。在此基础上,提出了一种通用模型,利用系统的体系结构方法来确定最适合制造实体需求的组件装配。候选架构使用多目标遗传算法生成和评估,其中通过模糊推理系统选择首选方案。针对这种遗传算法,提出了领域独立的目标,使应用程序保持在最复杂的生产设计场景中。然后将所提出的方法应用于相机生产示例,最终确定了性能良好的体系结构。随着组织进一步采用这种灵活的生产方法,所提出的方法应该得到更多的使用。
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引用次数: 5
MBSE Product Line Engineering – Variability Overview lost? MBSE产品线工程-变异性概述丢失?
Pub Date : 2020-06-01 DOI: 10.1109/SoSE50414.2020.9130503
Martin Kortwinkel
The article introduces an approach and framework that combines both variability in product line development and reuse of product line assets in customer projects using proven architecture frameworks with some enhancements in one approach.
本文介绍了一种方法和框架,它结合了产品线开发中的可变性和客户项目中产品线资产的重用,使用经过验证的体系结构框架,并在其中一种方法中进行了一些增强。
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引用次数: 1
Neural Network Controllers in Chemical Technologies 化学技术中的神经网络控制器
Pub Date : 2020-06-01 DOI: 10.1109/SoSE50414.2020.9130425
Karol Kiš, Martin Klauco, A. Mészáros
Chemical technologies benefit greatly from optimization-based control strategies. This paper addressed the problem of substituting the optimization based controller with a neural network (NN). The NN-based controller offers several advantages, first it can be derived in an analytical form and second, it can make the closed-loop implementation tunable. It is not possible to incorporate these aspects into optimizationbased controller easily.The contribution is also to address the problem of the quality of the neural net, that approximates the control law. We show, which activation functions and structure yield the best approximation.
化工技术从基于优化的控制策略中受益匪浅。研究了用神经网络(NN)代替基于优化的控制器的问题。基于神经网络的控制器有几个优点,首先,它可以以解析形式推导,其次,它可以使闭环实现可调。将这些方面轻易地整合到基于优化的控制器中是不可能的。其贡献还在于解决神经网络的质量问题,即近似控制律的问题。我们证明了哪种激活函数和结构产生最佳近似。
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引用次数: 4
Elderly Health Promotion using Multiple Ball-robots based on Evolutionary Robot 基于进化机器人的多球机器人促进老年人健康
Pub Date : 2020-06-01 DOI: 10.1109/SoSE50414.2020.9130424
Wei Quan, Haibin Zhang, N. Kubota
Eldercare is one of the most important healthcare concerns, particularly in countries whose populations are rapidly aging. Moreover, Globally the population of elderly people living alone is rising with an increasing number of people living with dementias. This paper proposes a health promotion system by using ball robot to motivate exercising for the elderly. Specifically, we use perceptual system of evolutionary robot detection based on fuzzy control. By utilizing the searching information in a limited indoor space, the robot ball can be navigated toward a target direction in real-time. In this paper, we propose a time-series of a searching method based on a steady-state genetic algorithm for visual perception. The search of the multiple robot agent is done by multi-resolution method for decreasing search space. Next, we use relative position distance and radius of the ball robot as inputs to the fuzzy controller. Therefore, we get the output value, speed and direction angle, as robot’s moving command of next state. Experimental results of boccia exercise also show the effectiveness and the practicality of the proposed robot system for typical healthcare services.
老年人护理是最重要的医疗保健问题之一,特别是在人口迅速老龄化的国家。此外,在全球范围内,独居老年人的数量正在增加,痴呆症患者的数量也在增加。本文提出了一种利用球机器人激励老年人运动的健康促进系统。具体来说,我们采用了基于模糊控制的进化机器人感知检测系统。利用在有限的室内空间内的搜索信息,机器人球可以实时地向着目标方向移动。本文提出了一种基于稳态遗传算法的时间序列视觉感知搜索方法。采用减小搜索空间的多分辨率方法对多机器人智能体进行搜索。接下来,我们使用球机器人的相对位置距离和半径作为模糊控制器的输入。从而得到输出值、速度和方向角,作为机器人下一状态的移动指令。在典型的医疗服务中,滚珠运动的实验结果也表明了所提出的机器人系统的有效性和实用性。
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引用次数: 0
Research on Capability Architecture Construction Methodology to System of Systems 系统之系统的能力架构构建方法研究
Pub Date : 2020-06-01 DOI: 10.1109/SoSE50414.2020.9130557
Jing Zhang, Yu Zhang, Yan He, Fei Xu
Many different kinds of actions and businesses would be involved when analyzing a System of Systems (SoS), such as modeling, simulation, evaluation, optimization and so on. Because of the essential characteristics of SoS, i.e. the high-complexity, plenty elements, massive relationships, uncertain conditions, and varied human factors, etc., it’s difficult to deal with a SoS effectively. Capability Analysis is a good solution to SoS research. And the most important step of SoS Capability Analysis (SoSCA) is to construct Capability Architecture (CArch) at very beginning. So as to clarify the corresponding SoS capability requirements, and declare the uniform specification and descriptions for the particular SoS missions. Then the SoS missions could be divided into several sub-missions and be dealt with jointly or respectively according to the coherent principles. Furthermore, all the analysis results could be integrated reasonably to avoid unnecessary diffusion or conflict. Yet, constructing SoS CArch would be a much more difficult and complex procedure, because there aren’t the standardized systematic methods or procedures to guide SoS CArch’s design, exploitation and application. To solve the problem, this paper would research the basal primary issue and try to support an effective methodology, i.e. CArchMeth, for SoS CArch construction. CArchMeth could be summarized as Domain Analysis, mainly including Mission Domain, Capability Domain, Method Domain, and Object Domain. The realized CArch could associate each aspect of the special SoS, such as the mission, the capability, the supporting element system, and so on. Then the requirement analysis, configurations description, components, workflow, resources and the pivotal principles of CArchMeth would be discussed respectively. Furthermore, some application would be supported to clarify the effect of CArchMeth.
在分析系统的系统(so)时,会涉及许多不同类型的操作和业务,例如建模、仿真、评估、优化等。由于SoS的本质特点是复杂性高、要素多、关系大、条件不确定、人为因素多变等,因此很难有效地处理SoS。能力分析是SoS研究的一个很好的解决方案。而SoS能力分析(SoSCA)最重要的一步是能力体系结构(CArch)的构建。从而明确相应的SoS能力需求,并针对特定的SoS任务声明统一的规范和描述。然后可以将紧急行动任务分成若干个子任务,按照连贯的原则共同或分别处理。此外,所有的分析结果可以合理地整合,避免不必要的扩散或冲突。然而,由于没有标准化的系统方法或程序来指导SoS CArch的设计、开发和应用,因此构建SoS CArch将是一个更加困难和复杂的过程。为了解决这个问题,本文将研究基础的主要问题,并试图支持一种有效的方法,即CArchMeth,用于SoS的CArch构建。CArchMeth可以概括为域分析,主要包括任务域、能力域、方法域和对象域。所实现的协同作战系统可以将特种作战系统的各个方面,如任务、能力、支撑要素系统等联系起来。然后分别讨论了需求分析、配置描述、组件、工作流、资源和CArchMeth的关键原理。此外,一些应用将支持澄清CArchMeth的效果。
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引用次数: 1
Advanced Monkey Testing for connected autonomous systems 连接自主系统的高级猴子测试
Pub Date : 2020-06-01 DOI: 10.1109/SoSE50414.2020.9130467
M. Hillebrand, Matthias Greinert, R. Dumitrescu, O. Herzog
Sensors, actuators, machine learning, communication and robotics are paving the way for the introduction of autonomous systems. Autonomous Systems in safety-critical applications require resilient operation of the intended functionality throughout the mission. Especially they must be safe and highly available. However, it is not possible to fully anticipate evolving threats, vulnerabilities and faults during the lifetime of those systems. This requires a resilient systems architecture of the autonomous system. Therefore, a thorough testing and evaluation of such systems is mandatory. In this paper, we present a monkey testing framework for evaluating resilience capabilities of autonomous systems. The framework contains a set of agents with specific role concepts and strategy sets. The framework can be applied to virtual, physical and hybrid testbeds. Due to its modularity the framework is extensible, scalable and also adaptable to different autonomous systems (e.g. mobile robot, manipulator). The monkey testing framework is able to work pseudo-randomized and thus reproducible on a connected system. A logging mechanism annotates the data so that the data can be used for machine learning (e.g. anomaly detection algorithm, selfhealing). We applied the framework on a mobile robotic system in virtual scenarios.
传感器、执行器、机器学习、通信和机器人技术正在为引入自主系统铺平道路。在安全关键应用中,自主系统需要在整个任务过程中弹性运行预期功能。特别是它们必须是安全的和高度可用的。然而,在这些系统的生命周期内,完全预测不断发展的威胁、漏洞和故障是不可能的。这需要自治系统的弹性系统架构。因此,必须对这些系统进行彻底的测试和评估。在本文中,我们提出了一个猴子测试框架来评估自治系统的弹性能力。该框架包含一组具有特定角色概念和策略集的代理。该框架可应用于虚拟、物理和混合测试平台。由于其模块化的框架是可扩展的,可伸缩的,也适用于不同的自治系统(如移动机器人,机械手)。猴子测试框架能够工作伪随机,因此可在连接的系统上重现。日志机制注释数据,以便数据可以用于机器学习(例如异常检测算法,自修复)。我们将该框架应用于虚拟场景下的移动机器人系统。
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引用次数: 0
Satisfaction analysis of public services using Evidential Network model 基于证据网络模型的公共服务满意度分析
Pub Date : 2020-06-01 DOI: 10.1109/SoSE50414.2020.9130501
Jiang Jiang, Yaqian You, Jianbin Sun, Xuan-nan Li
Public services are one of the basic functions of governments. How to improve the quality of public services under the limited budget has attracted significant attention. Most studies have tried to analysis the satisfaction of public services from statistical description or subjective decomposition. In this study, the evidential network model is employed to describe the relationship between the public services to analysis the satisfaction of them systematically. The advantage of the Evidential Network model is that the relationship between the public services can be represented using directed acyclic graph, and the subjective uncertainty in the relationship can be reflected by the D-S evidence theory. This study uses the Evidential Network structure learning approach to mine the relationship between public services from the questionnaire data, and analyzes the satisfaction of public services on this basis. A case study of the China General Social Survey (2015) is presented to demonstrate the methodology proposed in this study.
公共服务是政府的基本职能之一。如何在有限的预算下提高公共服务的质量,引起了人们的极大关注。大多数研究都试图从统计描述或主观分解的角度来分析公共服务满意度。本研究采用证据网络模型来描述公共服务之间的关系,系统分析公共服务的满意度。证据网络模型的优势在于,公共服务之间的关系可以用有向无环图来表示,关系中的主观不确定性可以用D-S证据理论来反映。本研究采用证据网络结构学习方法,从调查问卷数据中挖掘公共服务之间的关系,并在此基础上分析公共服务满意度。本文以中国综合社会调查(2015)为例,对本文提出的研究方法进行了论证。
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引用次数: 0
Towards a Tool-Based Approach for Dynamically Generating Co-Simulation Scenarios based on complex Smart Grid System Architectures 一种基于工具的基于复杂智能电网系统架构动态生成联合仿真场景的方法
Pub Date : 2020-06-01 DOI: 10.1109/SoSE50414.2020.9130514
C. Binder, Michael Fischinger, C. Neureiter, G. Lastro, Katharina Polanec, Jounes-Alexander Gross
The advancement of the electricity system in the upcoming years faces major challenges due to the rising number of decentralized and self-managed participants that individually react to the current load. These participants, regardless whether being an electric Vehicle or a Photovoltaic System, can have diverse behaviors, whose interplaying one mutual system is still widely unexplored. As conventional engineering methods reach their limits when trying to predict the collective behaviors of such Systems of Systems (SoS), the utilization of advanced tools such as the SGAM Toolbox and Mosaik framework is necessary. Each of the tools provide a distinct functionality in their unique field of application, however, their interconnection has yet to be introduced. Therefore, this work has been dedicated to explore the possibility of extending an SGAM based model so that the generation of components and their behavior for usage in the Co-Simulation environment of Mosaik is supported. The developed artifacts are thereby evaluated with a suitable realworld case study making use of different kinds of Electric Vehicle (EV) behaviors. Based on the results of this approach, entire Co-Simulation scenarios can be set up according to previously modeled Smart Grid architectures, which enables the analysis of different system behaviors in a considerably simplified way.
由于越来越多的分散和自我管理的参与者单独对当前负载做出反应,未来几年电力系统的发展将面临重大挑战。这些参与者,无论是电动汽车还是光伏系统,都可以有不同的行为,它们之间的相互作用仍然是一个广泛未被探索的相互系统。由于传统的工程方法在试图预测这些系统的系统(SoS)的集体行为时达到了极限,因此有必要利用先进的工具,如sgram工具箱和Mosaik框架。每个工具都在其独特的应用领域中提供了独特的功能,但是,它们之间的互连尚未引入。因此,这项工作一直致力于探索扩展基于sgram的模型的可能性,以便支持在Mosaik的联合仿真环境中使用的组件及其行为的生成。因此,通过使用不同类型的电动汽车(EV)行为的合适的现实案例研究来评估开发的工件。基于该方法的结果,可以根据先前建模的智能电网架构建立整个联合仿真场景,从而能够以相当简化的方式分析不同的系统行为。
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引用次数: 2
One-Shot Re-identification using Image Projections in Deep Triplet Convolutional Network 基于图像投影的深度三重卷积网络单次再识别
Pub Date : 2020-06-01 DOI: 10.1109/SoSE50414.2020.9130423
Gábor Kertész, I. Felde
Representation learning of images using deep neural networks have shown great results in classificational tasks. In case of instance recognition, or object re-identification other approaches are used. Siamese architectured convolutional networks were the first approach to learn from semantic distances, and give the similarity of two inputs. Triplet networks apply the triplet loss based on the furthest positive and the closest negative pair. In this paper we present a method to apply multi-directional image projections as an initial transformation to compress image data, whereafter the discriminative ability remains. After performing the training on vehicle images, the model is evaluated by measuring the one-shot classification accuracy.
使用深度神经网络的图像表示学习在分类任务中显示出了很好的效果。在实例识别或对象再识别的情况下,使用其他方法。Siamese结构的卷积网络是第一个从语义距离中学习的方法,并给出两个输入的相似性。三重态网络基于最远的正对和最近的负对应用三重态损失。本文提出了一种利用多向图像投影作为初始变换来压缩图像数据的方法,在此基础上保留了图像数据的判别能力。在对车辆图像进行训练后,通过测量单次分类准确率对模型进行评价。
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引用次数: 6
A Roadmap for Sustainability for a Community in The Netherlands 荷兰社区可持续发展路线图
Pub Date : 2020-06-01 DOI: 10.1109/SoSE50414.2020.9130472
G. Muller
The sustainability transition is a systems of systems challenge to the power ‘n’. The amount of systems and organizations that is involved is inconceivable for most humans. A roadmap is a means to structure much information and to help humans and organizations to understand their role in this transition. This paper describes a roadmap for a local municipality in the Netherlands. It explains the roadmap contents and the current experiences in using and evolving the roadmap. The general response to the roadmap is quite positive. However, we need to evolve the roadmap to turn it into a living entity that is helping the sustainability transition.
可持续性转型是一个系统的系统挑战的力量“n”。涉及的系统和组织的数量对大多数人来说是不可想象的。路线图是一种构建大量信息并帮助人们和组织了解他们在此转换中的角色的方法。本文描述了荷兰一个地方自治市的路线图。它解释了路线图的内容以及目前使用和发展路线图的经验。对路线图的总体反应是相当积极的。然而,我们需要发展路线图,把它变成一个活生生的实体,帮助可持续发展转型。
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引用次数: 1
期刊
2020 IEEE 15th International Conference of System of Systems Engineering (SoSE)
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