2019 14th Annual Conference System of Systems Engineering (SoSE)最新文献_第6页

Stored System Inherent Availability Optimization from a System of Systems Physics of Failure Perspective 从系统物理失效角度看存储系统固有可用性优化

2019 14th Annual Conference System of Systems Engineering (SoSE) Pub Date : 2019-05-01 DOI: 10.1109/SYSOSE.2019.8753871

Douglas L. Van Bossuyt, B. O’Halloran, Matthew Morningstar

{"title":"Stored System Inherent Availability Optimization from a System of Systems Physics of Failure Perspective","authors":"Douglas L. Van Bossuyt, B. O’Halloran, Matthew Morningstar","doi":"10.1109/SYSOSE.2019.8753871","DOIUrl":"https://doi.org/10.1109/SYSOSE.2019.8753871","url":null,"abstract":"Stored systems of systems (SoS) such as weapons systems in magazines and storage depots, spare equipment for nuclear power plants, and other stored SoS can sit in storage for decades before use. Failures that impact inherent availability can result from diurnal temperature cycles and other storage issues. Individual storage locations within a storage facility can undergo different diurnal temperature cycles which can impact time to failure of specific systems within the SoS due to physics of failure mechanisms (e.g.: transistor failure from repeated thermal cycles). Other issues such as test and maintenance cycles; certain stored systems being the favored extended test system or in the case of weapons systems used on aircraft, favored sortie systems; and other SoS-specific issues can contribute to reduced inherent availability. This paper presents a method of optimizing contributors to inherent availability from a SoS perspective, and using both individual system failure data and SoS cost information. The result is a stored SoS that is optimized to either meet service life requirements, or a stored SoS that is optimized to extend service life beyond the design basis, or a stored SoS that is optimized to increase inherent availability while meeting service life requirements. A case study of a stored SoS weapons system for aircraft is presented to illustrate the method.","PeriodicalId":133413,"journal":{"name":"2019 14th Annual Conference System of Systems Engineering (SoSE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128692295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Low-Cost Heterogeneous Unmanned Ground Vehicle (UGV) Testbed for Systems of Autonomous Vehicles Research 面向自主车辆系统研究的低成本异构无人地面车辆(UGV)试验台

2019 14th Annual Conference System of Systems Engineering (SoSE) Pub Date : 2019-05-01 DOI: 10.1109/SYSOSE.2019.8753850

A. Jaimes, Javier González, Alexander Ibarra, P. Benavidez, M. Jamshidi

引用次数: 1

A Pipeline Approach in Identifying Important Input Features from Neural Networks 神经网络重要输入特征识别的管道方法

2019 14th Annual Conference System of Systems Engineering (SoSE) Pub Date : 2019-05-01 DOI: 10.1109/SYSOSE.2019.8753849

Y. He, Chih Lai, D. Martinovic-Weigelt, Zezheng Long

{"title":"A Pipeline Approach in Identifying Important Input Features from Neural Networks","authors":"Y. He, Chih Lai, D. Martinovic-Weigelt, Zezheng Long","doi":"10.1109/SYSOSE.2019.8753849","DOIUrl":"https://doi.org/10.1109/SYSOSE.2019.8753849","url":null,"abstract":"Neural networks are well-known for their powerful capability in producing high prediction accuracy. However, due to the non-linear calculations in the network, it is very difficult for users to understand which input features are important in leading to final predictions. In this study, we propose a two-step pipeline approach that uses two sets of linear models to estimates feature importance in the input dataset $X$ that leads to the class prediction specified in Y. More specifically, the first linear regression model derives the feature importance in $X$ in explaining the Z-code that was extracted from any hidden layer of a trained neural network. The second linear classification model captures the importance in the Z- code in predicting the target class Y. We then combine the first $X$ to $Z$ importance with the second $Z$ to $Y$ importance together to approximate the non-linear importance from $X$ to Y. The experiments conducted in this study also show that our method is sound and stable in selecting the truly important features from input datasets regardless how a neural network was constructed with different parameters such as activation functions or the number of hidden layers.","PeriodicalId":133413,"journal":{"name":"2019 14th Annual Conference System of Systems Engineering (SoSE)","volume":"32 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130736282","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Development of Secure System of Systems Needing a Rapid Deployment 需要快速部署的系统的安全系统开发

2019 14th Annual Conference System of Systems Engineering (SoSE) Pub Date : 2019-05-01 DOI: 10.1109/SYSOSE.2019.8753857

Nan Messe, Nicolas Belloir, Vanea Chiprianov, Imane Cherfa, Régis Fleurquin, Salah Sadou

引用次数: 1

ORBDeepOdometry - A Feature-Based Deep Learning Approach to Monocular Visual Odometry ORBDeepOdometry -一种基于特征的深度学习方法的单目视觉里程测量

2019 14th Annual Conference System of Systems Engineering (SoSE) Pub Date : 2019-05-01 DOI: 10.1109/SYSOSE.2019.8753848

Karthik Sivarama Krishnan, F. Sahin

{"title":"ORBDeepOdometry - A Feature-Based Deep Learning Approach to Monocular Visual Odometry","authors":"Karthik Sivarama Krishnan, F. Sahin","doi":"10.1109/SYSOSE.2019.8753848","DOIUrl":"https://doi.org/10.1109/SYSOSE.2019.8753848","url":null,"abstract":"Visual Odometry (VO) is an application of computer vision which helps in autonomous navigation of Self-Driving vehicles, Robots etc. The odometry pose of the vehicle can be estimated using the consecutive frames based on monocular or stereo camera setup mounted on the vehicle. The Simultaneous Localization and Mapping (SLAM) based approaches have shown phenomenal results in predicting the vehicle odometry. Deep Learning based approaches are emerging in the field of computer vision and are outperforming other classic algorithms. But, visual odometry is one of the field where deep learning approaches have not yet been exploited largely. This paper proposes the use of Deep Learning based pipeline approach to solve the problem of visual odometry. The paper boosts the performance of deep learning approach by extracting quite more features before training the network. This paper proposes the use of ORB based feature extractor along with Convolutional Neural Network based dimensionality reduction and stacking multiple deep LSTM's for modelling the sequential data. In this case, the KITTI vision Benchmark dataset is used to model the network. The accuracy of the network is examined by calculating the error between the predicted odometry output and the ground truth odometry output. The results are compared with different Convolutional Neural Network (CNN) architectures proposed for the same task. The average translation error from the proposed system is 11.99% and the average rotational error from the proposed system is 0.0462 degrees per meter.","PeriodicalId":133413,"journal":{"name":"2019 14th Annual Conference System of Systems Engineering (SoSE)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130636354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

Metamodeling NATO Operation Orders: a proof-of-concept to deal with digitalization of the battlefield 北约作战命令元建模:处理战场数字化的概念验证

2019 14th Annual Conference System of Systems Engineering (SoSE) Pub Date : 2019-05-01 DOI: 10.1109/SYSOSE.2019.8753885

Nicolas Belloir, J. Buisson, O. Bartheye

{"title":"Metamodeling NATO Operation Orders: a proof-of-concept to deal with digitalization of the battlefield","authors":"Nicolas Belloir, J. Buisson, O. Bartheye","doi":"10.1109/SYSOSE.2019.8753885","DOIUrl":"https://doi.org/10.1109/SYSOSE.2019.8753885","url":null,"abstract":"Digitalization of the whole society changes the way Systems-of-Systems have to be considered. Remaining independently operated and managed, SoS increase their collaboration skills using shared or cooperated information systems. People can be seen as particular digital sub-systems due to smart equipments they can use. Military operations, which are considered as typical SoS, are no exception to this fact. New operational doctrines have to be created to take advantage of those new capabilities. In this paper, we propose to develop methods and tools inspired by software engineering to create new automated capabilities in battlefield engineering. More precisely, we explain the direction which should be considered in the area of battlefield engineering in order to deal with those new capabilities. Inspired from Model-Based Engineering, we realized a proof-of-concept showing how to change textual operation orders with graphical ones. The latter can be exported in a common standardized format, that enables digital interpretation. We present the OPORD-ML language which is based on a metamodel inspired from a NATO operation order standard. It is supported by an automatically generated tool.","PeriodicalId":133413,"journal":{"name":"2019 14th Annual Conference System of Systems Engineering (SoSE)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122135311","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Error Rate Analysis of Physical Layer Security for Sub-6 GHz 5G Network Planning Sub-6 GHz 5G网络规划物理层安全错误率分析

2019 14th Annual Conference System of Systems Engineering (SoSE) Pub Date : 2019-05-01 DOI: 10.1109/SYSOSE.2019.8753853

Patrick Ormond, Anil Kumar Yerrapragada, B. Kelley

引用次数: 2

Cybersecurity as a Centralized Directed System of Systems Using SoS Explorer as a Tool 使用SoS Explorer作为工具的集中定向系统的网络安全

2019 14th Annual Conference System of Systems Engineering (SoSE) Pub Date : 2019-05-01 DOI: 10.1109/SYSOSE.2019.8753872

Lirim Ashiku, C. Dagli

{"title":"Cybersecurity as a Centralized Directed System of Systems Using SoS Explorer as a Tool","authors":"Lirim Ashiku, C. Dagli","doi":"10.1109/SYSOSE.2019.8753872","DOIUrl":"https://doi.org/10.1109/SYSOSE.2019.8753872","url":null,"abstract":"The vast advancements in computing technology and the profound reliance on inter-connected systems has led to a significant growth of cyber-attack incidents. The incidents can propagate from within or outside of organizations, thus ensuing detrimental consequences such as business conducting disruptions, market brand degradation, settlement charges, regulatory compliance issues, etc. The ability to withstand such interference is essential to maintaining a vital and competitively advantageous organization. This paper analyzes coexisting vulnerabilities and the utilization of innovative and effective mechanisms to identify and block undesirable emergence through a centrally controlled and directed SoS approach. The paper will use SoS Explorer as a tool to architect, model and optimize the many objective cybersecurity complex system dealing with securing from exploiting threats through threat-inhibiting systems. The tool provides an intuitive and interactive visualization enabling the user to produce “what-if” analysis on various scenarios, especially for time evolving dynamics of cybersecurity, through generated optimization functional architecture solutions. The paper will further discuss vulnerability exploitation and cybersecurity implications on banking domain describing speculative observations followed by future research directions.","PeriodicalId":133413,"journal":{"name":"2019 14th Annual Conference System of Systems Engineering (SoSE)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125805224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9

Generated Voltage Control of EV PMSM for Maximizing Energy Recovery Rate using Switched Resonant L-C 基于开关谐振L-C的EV永磁同步电机电压控制以实现能量回收率最大化

2019 14th Annual Conference System of Systems Engineering (SoSE) Pub Date : 2019-05-01 DOI: 10.1109/SYSOSE.2019.8753832

Keonho Park, Sungchul Jung, Seungtaik Kim, Jongsun Ko

引用次数: 3

On the Application of MIMO Space-Time Coding to Physical Layer Security in sub-6 GHz 5G MIMO空时编码在sub-6 GHz 5G物理层安全中的应用

2019 14th Annual Conference System of Systems Engineering (SoSE) Pub Date : 2019-05-01 DOI: 10.1109/SYSOSE.2019.8753826

Patrick Ormond, Anil Kumar Yerrapragada, B. Kelley

引用次数: 2