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Interdisciplinary Data Analysis

Ana Carolina Lorena, Anne Magaly de Paula Canuto
2018 New generation computing  
The papers submitted to BRACIS 2016 represented a broad range of research developed in Brazil and other countries. In 2016, a total of 176 submissions were received.  ...  The emphasis of BRACIS is on original theories and novel applications of these models, and the proceedings are traditionally published by the IEEE Computer Society Press.  ...  The paper is entitled ''Fault Detection in Hard Disk Drives Based on a Semi Parametric Model and Statistical Estimators''.  ... 
doi:10.1007/s00354-017-0030-2 fatcat:h4lhci4ac5f5thoseofxiz7ozy

A survey of online failure prediction methods

Felix Salfner, Maren Lenk, Miroslaw Malek
2010 ACM Computing Surveys  
In contrast to classical reliability methods, online failure prediction is based on runtime monitoring and a variety of models and methods that use the current state of a system and, frequently, the past  ...  To capture the wide spectrum of approaches concerning this area, a taxonomy has been developed, whose different approaches are explained and major concepts are described in detail.  ...  Failure models: The presented methods are capable of predicting hard disk drive failures based on SMART values, which are representing the internal conditions of disk drives.  ... 
doi:10.1145/1670679.1670680 fatcat:qdexmtipkvajrpney7mwhdsaoe

Failure Prediction, Lead Time Estimation and Health Degree Assessment for Hard Disk Drives Using Voting based Decision Trees

Kamaljit Kaur, Kuljit Kaur
2019 Computers Materials & Continua  
Hard Disk drives (HDDs) are an essential component of cloud computing and big data, responsible for storing humongous volumes of collected data.  ...  Every year, about 10% disk drives used in servers crash at least twice, lead to data loss, recovery cost and lower reliability.  ...  The paradigm of anomaly detection for the failure forecasting of HDDs was exploited. Their system uses non-parametric and semi-parametric techniques.  ... 
doi:10.32604/cmc.2019.07675 fatcat:q7x5lrv3rzeuvcfuu65x6umyuq

An automated low-cost condition monitoring system for quality control of automotive speedometers

A Al-Habaibeh, R M Parkin
2003 Proceedings of the Institution of mechanical engineers. Part B, journal of engineering manufacture  
A novelty detection approach is optimized to characterize thè normal' conditions of the speedometers and to reject any speedometers that are not so categorized on the basis of the sound waves produced  ...  Citation: AL-HABAIBEH, A. and PARKIN, R.M., 2003. An automated lowcost condition monitoring system for quality control of automotive speedometers.  ...  Three main methods are used to model the PDF: parametric methods [12] , non-parametric methods [13] and semi-parametric methods [14] .  ... 
doi:10.1243/095440503772680695 fatcat:jumxr3kcy5estjy6oh4opmihte

Errors and Faults [chapter]

Ana Gainaru, Franck Cappello
2015 Computer Communications and Networks  
This chapter focuses on offering an overview of failures observed in real large-scale systems and their characteristics, with an emphasis on modeling, detection, and prediction.  ...  tolerance is a crucial one.  ...  This chapter is build on material from publications co-authored with numerous colleagues.  ... 
doi:10.1007/978-3-319-20943-2_2 fatcat:44yvw6pozjbxlmhbz7kafvcapq

Automatic Optical Inspection of Solder Ball Burn Defects on Head Gimbal Assembly

Jirarat Ieamsaard, Paisarn Muneesawang, Frode Sandnes
2018 Journal of Failure Analysis and Prevention  
The detection of low quality solder joint quality in hard disk drive (HDD) manufacturing is a time consuming, error-prone and costly process that is often performed manually.  ...  The first method uses a Support Vector Machine (SVM) for fault detection and the second method uses vertical edge detection to identify solder ball and pad burning defects.  ...  It has been estimated that hard disk drives (HDDs) account for 52% of this information [1] and the HDD market is expected to grow further [2] .  ... 
doi:10.1007/s11668-018-0426-4 fatcat:ix7g2y5b75awzdc4xz66ouidtu

Basic research on machinery fault diagnostics: Past, present, and future trends

Xuefeng Chen, Shibin Wang, Baijie Qiao, Qiang Chen
2017 Frontiers of Mechanical Engineering  
On the basis of the review of basic theory of machinery fault diagnosis and its practical applications in engineering, the paper concludes with a brief discussion on the future trends and challenges in  ...  Research on machinery Fault diagnostics has grown rapidly in recent years.  ...  reproduction in any medium, provided the appropriate credit is given to the original author(s) and the source, and a link is provided to the Creative Commons license, indicating if changes were made.  ... 
doi:10.1007/s11465-018-0472-3 fatcat:xngm4jcct5berhuf33rqoxfc6i

Machine learning methods for wind turbine condition monitoring: A review

Adrian Stetco, Fateme Dinmohammadi, Xingyu Zhao, Valentin Robu, David Flynn, Mike Barnes, John Keane, Goran Nenadic
2019 Renewable Energy  
This paper reviews the recent literature on machine learning (ML) models that have been used for condition monitoring in wind turbines (e.g. blade fault detection or generator temperature monitoring).  ...  Neural networks, support vector machines and decision trees are most commonly used. We conclude with a discussion of the main areas for future work in this domain.  ...  The authors are thankful to all colleagues and partners on the HOME Offshore project (http://homeoffshore.org/). Appendix A. Feature processing 1  ... 
doi:10.1016/j.renene.2018.10.047 fatcat:r3wb7pjlsnfxtpmgiioexmkdby

2019-2020 Index IEEE Transactions on Industrial Electronics Vol. 67

2020 IEEE transactions on industrial electronics (1982. Print)  
Dual Time-Scale Unscented Kalman Filter; TIE Jan. 2020 442-450 Jiang, K., Yan, F., and Zhang, H., Data-Driven Modeling and UFIR-Based Out-let NO x Estimation for Diesel-Engine SCR Systems; TIE June 2020  ...  Batch-End Quality Model-ing and Monitoring Based on Optimized Sparse Partial Least Squares; TIE May 2020 4098-4107 Jiang, S., Li, L., Xu, H., Xu, J., Gu, G., and Shull, P.B., Stretchable e-Skin Patch  ...  ., +, TIE Jan. 2020 677-685 Hard disks Quadruple-Stage Actuator System for Magnetic-Head Positioning System in Hard Disk Drives.  ... 
doi:10.1109/tie.2020.3045338 fatcat:gljm7ngg3fakvmnfswcbb5vwiu

Predictive Reliability and Fault Management in Exascale Systems

Ramon Canal, Carles Hernandez, Rafa Tornero, Alessandro Cilardo, Giuseppe Massari, Federico Reghenzani, William Fornaciari, Marina Zapater, David Atienza, Ariel Oleksiak, Wojciech PiĄtek, Jaume Abella
2020 ACM Computing Surveys  
Estimating application's robustness based on fault statistics and effective usage of resources minimizes application crashes and helps determine optimal resource utilization.  ...  Estimating application's robustness based on fault statistics and effective usage of resources will minimize application crashes and help determining optimal resource utilization.  ... 
doi:10.1145/3403956 fatcat:77xcpnevmnc5jfpj6ynhwdng3m

Failure Prediction – An Application in the Railway Industry [chapter]

Pedro Pereira, Rita P. Ribeiro, João Gama
2014 Lecture Notes in Computer Science  
In fact, states that failure detection techniques for anomaly detection in engineering applications can spread from Parametric or Non-Parametric Statistical Modelling to Neural Networks.  ...  Fault detection using numerical techniques based on mathematical system models is a well-established subject and a lot of survey papers and books have been written, such as Isermann (1984) , Basseville  ...  Figure 24 -Statistical Tests for Duration Distribution Cycles Applying Kruskal Wallis Tests it cannot be accepted that the distribution of Duration is the same across all months, at a 0.05 significance  ... 
doi:10.1007/978-3-319-11812-3_23 fatcat:pj62rnicvnhgpejd4qb6pa5lxa

Detecting Discontinuities in Large Scale Systems

Haroon Malik, Ian J. Davis, Michael W. Godfrey, Douglas Neuse, Serge Mankovskii
2014 2014 IEEE/ACM 7th International Conference on Utility and Cloud Computing  
Analysts need to identify discontinuities in performance data so that they can a) remove the discontinuities from the data before building a forecast model and b) retrain an existing forecast model on  ...  In this paper, we present and evaluate our proposed approach to help data center analysts and cloud providers automatically detect discontinuities.  ...  Accessing I/O storage devices, such as hard drives, are usually among the slowest part of a transaction.  ... 
doi:10.1109/ucc.2014.44 dblp:conf/ucc/MalikDGNM14 fatcat:wea73tklifhezj5ucov3rdwvii

Resilience and fault tolerance in high-performance computing for numerical weather and climate prediction

Tommaso Benacchio, Luca Bonaventura, Mirco Altenbernd, Chris D Cantwell, Peter D Düben, Mike Gillard, Luc Giraud, Dominik Göddeke, Erwan Raffin, Keita Teranishi, Nils Wedi
2021 The international journal of high performance computing applications  
Numerical examples showcase the performance of the techniques in addressing faults, with particular emphasis on iterative solvers for linear systems, a staple of atmospheric fluid flow solvers.  ...  and backup-based methods for the systems.  ...  Acknowledgements We thank the authors of Agullo et al. (2016a Agullo et al. ( , 2016b)) , namely E Agullo, L Giraud, A Guermouche, J Roman, P Salas, and M Zounon, for the permission to report the  ... 
doi:10.1177/1094342021990433 fatcat:tfhovb6xmfemtkgzzrkpiiiju4

A Survey on Automatic Parameter Tuning for Big Data Processing Systems

Herodotos Herodotou, Yuxing Chen, Jiaheng Lu
2020 ACM Computing Surveys  
We investigate existing approaches on parameter tuning for both batch and stream data processing systems and classify them into six categories: rule-based, cost modeling, simulation-based, experiment-driven  ...  : Data statistics are almost never available for MapReduce and Spark applications, since data often reside in semi-or un-structured files and are opaque until accessed [58] .  ...  A few experimental logs and some input statistics are typically required to establish the model. (3) Simulation-based approaches build performance prediction models based on modular or complete system  ... 
doi:10.1145/3381027 fatcat:7aglimtuwze25boptuano4ufdy

Implementation of System Operation Modes for Health Management and Failure Prognosis in Cyber-Physical Systems

Santiago Ruiz-Arenas, Zoltán Rusák, Ricardo Mejía-Gutierrez, Imre Horváth
2020 Sensors  
This article proposes a failure prognosis method, which combines time series-based forecasting methods with statistically based classification techniques in order to investigate system degradation and  ...  This method utilizes a new approach based on the concept of the system operation mode (SOM) that offers a novel perspective for health management that allows monitoring the system behavior, through the  ...  the wear problem of magnetic heads used in hard disk drives (HDDs), by implementing Wiener processes with measurement errors  ... 
doi:10.3390/s20082429 pmid:32344705 pmcid:PMC7219508 fatcat:lvcsjxkpuvftxf6jll3gamg4uu
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