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A Hybrid Approach: Dynamic Diagnostic Rules for Sensor Systems in Industry 4.0 Generated by Online Hyperparameter Tuned Random Forest

Ahlam Mallak, Madjid Fathi
2020 Sci  
In this work, a hybrid component Fault Detection and Diagnosis (FDD) approach for industrial sensor systems is established and analyzed, to provide a hybrid schema that combines the advantages and eliminates  ...  Moreover, it shines light on a new utilization of Random Forest (RF) together with model-based diagnosis, beyond its ordinary data-driven application.  ...  Funding: This research was funded by the DFG research grants LO748/11-1 and OB384/5-1. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/sci2040075 fatcat:kec7wdou5zelli7xvgat3tsuua

A Hybrid Approach: Dynamic Diagnostic Rules for Sensor Systems in Industry 4.0 Generated by Online Hyperparameter Tuned Random Forest

Ahlam Mallak, Madjid Fathi
2020 Sci  
In this work, a hybrid component Fault Detection and Diagnosis (FDD) approach for industrial sensor systems is established and analyzed, to provide a hybrid schema that combines the advantages and eliminates  ...  Moreover, it shines the light on a new utilization of Random Forest (RF) together with model-based diagnosis, beyond its ordinary data-driven application.  ...  Funding: This research was funded by the DFG research grants LO748/11-1 and OB384/5-1. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/sci2040061 fatcat:kpwatw25fjdtbcjeo7r6gfqegi

Smart Manufacturing Real-Time Analysis Based on Blockchain and Machine Learning Approaches

Zeinab Shahbazi, Yung-Cheol Byun
2021 Applied Sciences  
The hybrid prediction model used in this system uses the Random Forest classification technique to remove the sensor data outliers and donate fault detection through the manufacturing system.  ...  The growth of data production in the manufacturing industry causes the monitoring system to become an essential concept for decision-making and management.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/app11083535 fatcat:ogrvq5vfxze2fkcsjnu56ffdlq

A Survey of Fault Management in Network Virtualization Environments: Challenges and Solutions

Sihem Cherrared, Sofiane Imadali, Eric Fabre, Gregor Gossler, Imen Grida Ben Yahia
2019 IEEE Transactions on Network and Service Management  
We propose a new classification of the recent fault management research achievements in the network virtualization environments and compare their major contributions and shortcomings.  ...  With the softwarization of 5G, MNOs are seeking new revenue sources and models.  ...  We also thank Christian JACQUENET and Ian HAY for their careful reading of the survey and their constructive remarks.  ... 
doi:10.1109/tnsm.2019.2948420 fatcat:r5xzkybqmjfebdoturu2g72uaa

DAG-based attack and defense modeling: Don't miss the forest for the attack trees

Barbara Kordy, Ludovic Piètre-Cambacédès, Patrick Schweitzer
2014 Computer Science Review  
The great advantage of graph-based approaches lies in combining user friendly, intuitive, visual features with formal semantics and algorithms that allow for qualitative and quantitative analysis.  ...  In this paper we focus on graphical methods for analysis of attack and defense scenarios.  ...  To overcome limitations of static fault trees, dynamic fault trees [76, 77] were invented by Dugan et al. in the early 1990s.  ... 
doi:10.1016/j.cosrev.2014.07.001 fatcat:aie7uxdorjclnb5ctgg5nrczqi

DAG-Based Attack and Defense Modeling: Don't Miss the Forest for the Attack Trees [article]

Barbara Kordy, Ludovic Piètre-Cambacédès, Patrick Schweitzer
2013 arXiv   pre-print
DAGs allow for a hierarchical decomposition of complex scenarios into simple, easily understandable and quantifiable actions.  ...  The objective of this survey is to present a complete overview of graphical attack and defense modeling techniques based on DAGs.  ...  Acknowledgments The authors would like to thank Sjouke Mauw and Pieter Hartel for their comments on a preliminary version of this survey, which helped them to improve the paper.  ... 
arXiv:1303.7397v1 fatcat:fiebxymrd5dcnmnufddaoaqlaa

Constraints meet concurrency

Jacopo Mauro
2015 Constraints  
Thank you for your patience, your constant presence and guidance. Needless to say, I am also in debt with my coauthors:  ...  For the development of this framework we used the concurrent language Jolie following the Service Oriented paradigm.  ...  For this reason my first thanks goes to all the professors, assistants, colleagues and friends with whom I have had the pleasure to interact with in these years.  ... 
doi:10.1007/s10601-015-9218-6 fatcat:7cjwl2p4anfkvbpahjnklrs7my

Reformist Framework for Improving Human Security for Mobile Robots in Industry 4.0

Anand Singh Rajawat, Pradeep Bedi, S. B. Goyal, Piyush Kumar Shukla, Atef Zaguia, Aakriti Jain, Mohammad Monirujjaman Khan, Sikandar Ali
2021 Mobile Information Systems  
systems, and collision prevention strategies and minimizing their impact to proposed approach for Human Security with Mobile Robots in Industry 4.0 using SDN and CPS with GMM-GM machine learning model  ...  These changes have been reflected in industrial robotic safety standards for the last 20 years.  ...  A static environment with little path planning is their domain-for example, a rapid spreading random tree based on random sampling.  ... 
doi:10.1155/2021/4744220 fatcat:h4353wqfcngbrblr5x4wxnmtgi

An Intelligent Multi-Agent Based Detection Framework for Classification of Android Malware [chapter]

Mohammed Alam, Son Thanh Vuong
2014 Lecture Notes in Computer Science  
to transmit the information to server side classifiers for analysis, and to receive classification results from the server side agents.  ...  It is also the most vulnerable device due to its open nature of software installation, ability to dynamically load code during runtime, and lack of updates to known vulnerabilities even on popular versions  ...  The parameters that we experimented with included the number of decision trees in the Random Forest, the number of random features compared at a decision node for each decision tree, and the depth of each  ... 
doi:10.1007/978-3-319-09912-5_19 fatcat:h2452vxonfb5bjva6rfjlusubq

2020 Index IEEE Transactions on Industrial Informatics Vol. 16

2020 IEEE Transactions on Industrial Informatics  
Forests-Based Model for Ultra-Short-Term Prediction of PV Characteristics; TII Jan. 2020 202-214 Imran, A., see Hussain, B., TII Aug. 2020 4986-4996 Imran, M., see Fu, S., TII Sept. 2020 6013-6022  ...  -5149 Meng, K., see Zhang, Y., TII July 2020 4390-4402 Meng, K., Jia, Y., Yang, H., Niu, F., Wang, Y., and Sun, D., Motion Planning and Robust Control for the Endovascular Navigation of a Microrobot  ...  ., +, TII Sept. 2020 5780-5791 Enhanced Random Forest With Concurrent Analysis of Static and Dynamic Nodes for Industrial Fault Classification.  ... 
doi:10.1109/tii.2021.3053362 fatcat:blfvdtsc3fdstnk6qoaazskd3i

QoS-aware Energy Management and Node Scheduling Schemes for Sensor Network-based Surveillance Applications

Diya Thomas, Rajan Shankaran, Quan Z. Sheng, Mehmet Orgun, Michael Hitchens, Mehedi Masud, Wei Ni, Subhas Mukhopadhyay, MD. Jalil Piran
2020 IEEE Access  
We have provided a detailed classification and evaluation of various node scheduling schemes in terms of their ability to fulfill essential QoS requirements, namely coverage, connectivity, fault tolerance  ...  We have compared the efficacy of a few well known graph-based scheduling schemes with suitable performance analysis graph.  ...  Menon, SCMS School of Engineering and Technology, India, for useful discussions and the comments in improving the presentation of the manuscript.  ... 
doi:10.1109/access.2020.3046619 fatcat:gdo4qhrw4ncrdcze2gzrloikti

Snapshot of Energy Optimization Techniques to Leverage Life of Wireless Sensor Network

Kavya A P, D J Ravi
2021 International Journal of Advanced Computer Science and Applications  
Energy Optimization in Wireless Sensor Network (WSN) deals with the techniques which targets higher degree of energy efficiency using resource-constraint sensor nodes with minimal inclusion of any different  ...  It is anticipated that the study findings of this manuscript will offer a true picture of study effectiveness in dealing with energy challenges so that favorable direction of investigation towards evolving  ...  comparison Naïve Bayes not found to be an effective Chu et al. [37] Classification of data fault Naïve Bayes Higher accuracy in fault detection Dynamic faults not accessed in the study Fu  ... 
doi:10.14569/ijacsa.2021.0120714 fatcat:neasx3zauvhylho3so7yh2yv6y

A Survey of Machine Learning Applied to Computer Architecture Design [article]

Drew D. Penney, Lizhong Chen
2019 arXiv   pre-print
Notably, machine learning based strategies often surpass prior state-of-the-art analytical, heuristic, and human-expert approaches.  ...  Recent work, however, has explored broader applicability for design, optimization, and simulation.  ...  [21] introduced a completely static-analysis-based framework using a random forest model for binary classification.  ... 
arXiv:1909.12373v1 fatcat:o4nscgkjfbes7kqwmtjvvgl3oa

An integrated framework for wireless sensor network management

Lutful Karim, Qusay H. Mahmoud, Nidal Nasser, Nargis Khan
2012 Wireless Communications and Mobile Computing  
Thus, we introduce an efficient approach for each of localization, data scheduling, routing, and data aggregation; and compare the performance of proposed approaches with existing ones in terms of network  ...  of the proposed framework, and validate the results through statistical analysis.  ...  Clustering protocols can be classified as (i) static and (ii) dynamic.  ... 
doi:10.1002/wcm.2260 fatcat:v5c47wegibaspclbhfbszk2bgy

Bivariate, Cluster and Suitability Analysis of NoSQL Solutions for Different Application Areas [article]

Samiya Khan, Xiufeng Liu, Syed Arshad Ali, Mansaf Alam
2019 arXiv   pre-print
Random forest classification was used to determine the most relevant features for applications and correspondingly a decision tree-based prediction model was proposed, implemented and deployed in the form  ...  Furthermore, cluster analysis of the dataset was used to create categories of solutions to present a statistically supported classification scheme.  ...  The techniques used for this purpose were random forest classification [299] and decision tree classification [155] .  ... 
arXiv:1911.11181v1 fatcat:nme77ygk75dwjionumfkgko72u
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