The document discusses gradient-based fault isolation techniques. It begins by explaining the need for both fault detection and fault isolation in industrial processes. It then discusses commonly used residual-based approaches for fault detection and introduces the motivation for gradient-based fault isolation approaches. These approaches use partial derivatives of models to identify the process variables most responsible for detected faults. The document outlines some tools for visualizing fault isolation results and discusses opportunities to improve gradient aggregation methods and further narrow isolation performance gaps. It concludes that gradient-based techniques can perform fault isolation without prior fault information and more development is still needed to strengthen results.
In the wild, a user’s experience of your website can vary greatly due to network latency, browser rendering and your backend server processing. You need to be able to measure the user experience with standard metrics. Luckily your favorite web tool, the browser, can provide this data to you. Sending this browser data back to your site is called Real User Monitoring (RUM).
In this session, we will explore how to measure web performance that your users are experiencing. We will cover the W3C standards for timings and how to analyze them. How can you capture this information from your user’s browser and transmit that back to your webserver for analysis? We will look at an open source project Boomerang which provides JavaScript code that you can run in your web pages to gather this data. Then we will review a few options for customization and analysis of the data.
In the wild, a user’s experience of your website can vary greatly due to network latency, browser rendering and your backend server processing. You need to be able to measure the user experience with standard metrics. Luckily your favorite web tool, the browser, can provide this data to you. Sending this browser data back to your site is called Real User Monitoring (RUM).
In this session, we will explore how to measure web performance that your users are experiencing. We will cover the W3C standards for timings and how to analyze them. How can you capture this information from your user’s browser and transmit that back to your webserver for analysis? We will look at an open source project Boomerang which provides JavaScript code that you can run in your web pages to gather this data. Then we will review a few options for customization and analysis of the data.
Joe Laszlo, Senior Director of IAB’s Mobile Marketing Center of Excellence, and a panel of IAB members who worked on MRAID shared their experiences drafting these specs and answered member questions about implementation, how this will impact the mobile advertising landscape, and discussed next steps for 2012.
Kawecki, Barbara, and Michael Levine-Clark, “NISO’s DDA Initiative: Cross-Industry Stakeholders Express PDA to Improve the Landscape for All,” Charleston Conference, Charleston, S.C., November 9, 2012.
F. Serdio, E. Lughofer, K. Pichler, T. Buchegger, M. Pichler and H. Efendic, Reducing False Positives for Residual-Based On-line Fault Detection by Means of Filters, IEEE International Conference on Systems, Man and Cybernetics, SMC 2014, San Diego, USA, pp. 2803-2808.
F. Serdio, A.-C. Zavoianu, E. Lughofer, K. Pichler, T. Buchegger and H. Efendic, Hybrid Genetic-Fuzzy Systems for Improved Performance in Residual-Based Fault Detection, World Congress on Natural and Biologically Inspired Computing, NaBIC 2014, Porto, Portugal, 2014, pp. 91-96.
Joe Laszlo, Senior Director of IAB’s Mobile Marketing Center of Excellence, and a panel of IAB members who worked on MRAID shared their experiences drafting these specs and answered member questions about implementation, how this will impact the mobile advertising landscape, and discussed next steps for 2012.
Kawecki, Barbara, and Michael Levine-Clark, “NISO’s DDA Initiative: Cross-Industry Stakeholders Express PDA to Improve the Landscape for All,” Charleston Conference, Charleston, S.C., November 9, 2012.
F. Serdio, E. Lughofer, K. Pichler, T. Buchegger, M. Pichler and H. Efendic, Reducing False Positives for Residual-Based On-line Fault Detection by Means of Filters, IEEE International Conference on Systems, Man and Cybernetics, SMC 2014, San Diego, USA, pp. 2803-2808.
F. Serdio, A.-C. Zavoianu, E. Lughofer, K. Pichler, T. Buchegger and H. Efendic, Hybrid Genetic-Fuzzy Systems for Improved Performance in Residual-Based Fault Detection, World Congress on Natural and Biologically Inspired Computing, NaBIC 2014, Porto, Portugal, 2014, pp. 91-96.
Study of Software Defect Prediction using Forward Pass RNN with Hyperbolic Ta...ijtsrd
For the IT sector and software specialists, software failure prediction and proneness have long been seen as crucial issues. Conventional methods need prior knowledge of errors or malfunctioning modules in order to identify software flaws inside an application. By using machine learning approaches, automated software fault recovery models allow the program to substantially forecast and recover from software problems. This feature helps the program operate more efficiently and lowers errors, time, and expense. Using machine learning methods, a software fault prediction development model was presented, which might allow the program to continue working on its intended mission. Additionally, we assessed the models performance using a variety of optimization assessment benchmarks, including accuracy, f1 measure, precision, recall, and specificity. Convolutional neural networks and its hyperbolic tangent functions are the basis of the deep learning prediction model FPRNN HTF Forward Pass RNN with Hyperbolic Tangent Function technique. The assessment procedure demonstrated the high accuracy rate and effective application of CNN algorithms. Moreover, a comparative measure is used to evaluate the suggested prediction model against other methodologies. The gathered data demonstrated the superior performance of the FPRNN HTF technique. Swati Rai | Dr. Kirti Jain "Study of Software Defect Prediction using Forward Pass RNN with Hyperbolic Tangent Function" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-7 | Issue-6 , December 2023, URL: https://www.ijtsrd.com/papers/ijtsrd60159.pdf Paper Url: https://www.ijtsrd.com/humanities-and-the-arts/education/60159/study-of-software-defect-prediction-using-forward-pass-rnn-with-hyperbolic-tangent-function/swati-rai
International Journal on Cybernetics & Informatics ( IJCI) is an open access peer- reviewed journal that focuses on the areas related to cybernetics which is information, control and system theory, understands the design and function of any system and the relationship among these applications. This journal aims to provide a platform for exchanging ideas in new emerging trends that needs more focus and exposure and will attempt to publish proposals that strengthen our goals.
Km4City Smart City API: an integrated support for mobility servicesPaolo Nesi
AbstractThe main technical issues regarding smart city solutions are related todata gathering, aggregation, reasoning, access, and service delivering via Smart City APIs (Application Program Interfaces). Aggregated and re-conciliated data (open and private, static and real time) should be exploitable by reasoning/smart algorithms for enabling sophisticated service delivering. Different kinds of Smart City APIs enable Smart City Services and Applications, while their effectiveness depends on the architectural solutions to pass from data to services for city users and operators. To this end, a comparison of the state of the art solutions for data aggregation was performed, by putting in evidence the needs of semantic interoperable aggregated data, to provide smart services. This paper presents the work performed in the context of the Sii-Mobility national smart city project on mobility and transport integrated with services. Sii-Mobility is grounded on Km4City ontology and tools for smart city data aggregation and service production. To this end, Sii-Mobility/Km4City APIs have been compared to the state of the art solutions. Finally, the API consumption related data in the recent period are presented. Keywords smart city, smart city ontology, smart city API, smart mobility, multidomain smart city, smart services.
IEEE Smartcomp
Top 10 Read Articles in International Journal of Security, Privacy and Trust ...ClaraZara1
With the simplicity of transmission of data over the web increasing, there has more prominent need for adequate security mechanisms. Trust management is essential to the security framework of any network. In most traditional networks both wired and wireless centralized entities play pivotal roles in trust management. The International Journal of Security, Privacy and Trust Management ( IJSPTM ) is an open access peer reviewed journal that provides a platform for exchanging ideas in new emerging trends that needs more focus and exposure and will attempt to publish proposals that strengthen our goals.
A Review on Feature Extraction Techniques and General Approach for Face Recog...Editor IJCATR
In recent time, alongwith the advances and new inventions in science and technology, fraud people and identity thieves are
also becoming smarter by finding new ways to fool the authorization and authentication process. So, there is a strong need of efficient
face recognition process or computer systems capable of recognizing faces of authenticated persons. One way to make face recognition
efficient is by extracting features of faces. Several feature extraction techniques are available such as template based, appearancebased,
geometry based, color segmentation based, etc. This paper presents an overview of various feature extraction techniques
followed in different reasearches for face recognition in the field of digital image processing and gives an approach for using these
feature extraction techniques for efficient face recognition
Ph.D. Thesis: A Methodology for the Development of Autonomic and Cognitive In...Universita della Calabria,
Doctoral Defence in ICT (Università della Calabria, Italy). Ph.D. candidate Claudio Savaglio. Thesis title: A Methodology for the Development of Autonomic and Cognitive Internet of Things Ecosystems.
Top Software Engineering & Applications Research articles of 2019ijseajournal
The International Journal of Software Engineering & Applications (IJSEA) is a bi-monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the Software Engineering & Applications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern software engineering concepts & establishing new collaborations in these areas.
Results may vary: Collaborations Workshop, Oxford 2014Carole Goble
Thoughts on computational science reproducibility with a focus on software. Given at the Software Sustainability Institute's 2014 Collaborations Workshop
Accounting for people is the first step of every manpower-based organization in today’s world. Hence, it takes up a signification amount of energy and value in the form of money from respective organizations for both implementing a suitable system for manpower management as well as maintaining that same system. Although this amount of expenditure for big organizations is near to nothing, rather just a formality, it does not hold as much truth for small organizations such as schools, colleges, and even universities to a certain degree. This is the first point. The second point for discussion is that much work has been done to solve this issue. Various technologies like Biometrics, RFID, Bluetooth, GPS, QR Code, etc., have been used to tackle the issues of attendance collection. This study paves the path for researchers by reviewing practical methods and technologies used for existing attendance systems
Keynote on software sustainability given at the 2nd Annual Netherlands eScience Symposium, November 2014.
Based on the article
Carole Goble ,
Better Software, Better Research
Issue No.05 - Sept.-Oct. (2014 vol.18)
pp: 4-8
IEEE Computer Society
http://www.computer.org/csdl/mags/ic/2014/05/mic2014050004.pdf
http://doi.ieeecomputersociety.org/10.1109/MIC.2014.88
http://www.software.ac.uk/resources/publications/better-software-better-research
This presentation by Morris Kleiner (University of Minnesota), was made during the discussion “Competition and Regulation in Professions and Occupations” held at the Working Party No. 2 on Competition and Regulation on 10 June 2024. More papers and presentations on the topic can be found out at oe.cd/crps.
This presentation was uploaded with the author’s consent.
Have you ever wondered how search works while visiting an e-commerce site, internal website, or searching through other types of online resources? Look no further than this informative session on the ways that taxonomies help end-users navigate the internet! Hear from taxonomists and other information professionals who have first-hand experience creating and working with taxonomies that aid in navigation, search, and discovery across a range of disciplines.
Sharpen existing tools or get a new toolbox? Contemporary cluster initiatives...Orkestra
UIIN Conference, Madrid, 27-29 May 2024
James Wilson, Orkestra and Deusto Business School
Emily Wise, Lund University
Madeline Smith, The Glasgow School of Art
0x01 - Newton's Third Law: Static vs. Dynamic AbusersOWASP Beja
f you offer a service on the web, odds are that someone will abuse it. Be it an API, a SaaS, a PaaS, or even a static website, someone somewhere will try to figure out a way to use it to their own needs. In this talk we'll compare measures that are effective against static attackers and how to battle a dynamic attacker who adapts to your counter-measures.
About the Speaker
===============
Diogo Sousa, Engineering Manager @ Canonical
An opinionated individual with an interest in cryptography and its intersection with secure software development.
Acorn Recovery: Restore IT infra within minutesIP ServerOne
Introducing Acorn Recovery as a Service, a simple, fast, and secure managed disaster recovery (DRaaS) by IP ServerOne. A DR solution that helps restore your IT infra within minutes.
Getting started with Amazon Bedrock Studio and Control Tower
IEEE WCCI 2014
1. Gradient-based Fault Isolation
Residual-based Fault Detection Systems
Francisco Serdio Fernández
Department of Knowledge-Based Mathematical Systems
Johannes Kepler University Linz, Austria
WCCI 2014 / July 6-11 / Beijing, China
francisco.serdio@jku.at
for
http://www.flll.Francisco Serdio jku.at/staff/francisco
2. Why Fault Detection (FD) ?
Why Fault Isolation (FI) ?
FD with Residual-based approaches
Motivation of the FI Gradient-based approaches
Tools to depict Fault Isolation
Results
Can do we more ?
Conclusions
WCCI 2014 / July 6-11 / Beijing, China
francisco.serdio@jku.at
http://www.flll.Francisco Serdio jku.at/staff/francisco
3. WCCI 2014 / July 6-11 / Beijing, China
francisco.serdio@jku.at
Why Fault Detection?
http://www.flll.Francisco Serdio jku.at/staff/francisco
4. Why Fault Detection?
Products with high quality demands
High quality is required also in the production chain
High quality is required also in the supply chain
[1] D. Blanchard. Supply Chain Management Best Practices. John Wiley & Sons,
Hoboken, NJ, USA, 2007.
Continuity in the production lines
Minimum down-time
[2] R. Iserman. Fault-Diagnosis Applications. Model-Based Condition Monitoring:
Actuators, Drives, Machinery, Plants, Sensors, and Fault-tolerant Systems. Springer,
Berlin Heidelberg, Germany, 2011.
WCCI 2014 / July 6-11 / Beijing, China
francisco.serdio@jku.at
High quality processes imply
http://www.flll.Francisco Serdio jku.at/staff/francisco
5. WCCI 2014 / July 6-11 / Beijing, China
francisco.serdio@jku.at
Why Fault Detection?
http://www.flll.Francisco Serdio jku.at/staff/francisco
6. Manual supervision is not affordable or in some
cases simply impossible
The precision of manual supervision usually depends
on the experience of the operators
and even on their performance on a given day
[3] E. Lughofer, J.E. Smith, P. Caleb-Solly, M. Tahir, C. Eitzinger, D. Sannen and M.
Nuttin. (2009). Human-machine interaction issues in quality control based on on-line
image classication. IEEE Transactions on Systems, Man and Cybernetics, part A:
Systems and Humans, 39(5), 960-971.
WCCI 2014 / July 6-11 / Beijing, China
francisco.serdio@jku.at
Why Fault Detection?
Manual process supervision
http://www.flll.Francisco Serdio jku.at/staff/francisco
7. Why Fault Detection (FD) ?
Why Fault Isolation (FI) ?
FD with Residual-based approaches
Motivation of the FI Gradient-based approaches
Tools to depict Fault Isolation
Results
Can do we more ?
Conclusions
WCCI 2014 / July 6-11 / Beijing, China
francisco.serdio@jku.at
http://www.flll.Francisco Serdio jku.at/staff/francisco
9. Why Fault Isolation?
Multiple sensor networks turned out to emerge
in industrial settings and factories
Huge amount of sensors and actuators to check
Manual supervision is not affordable or in some
cases simply impossible
Any valuable information regarding where the fault
is
located could be a great aid for the operator
WCCI 2014 / July 6-11 / Beijing, China
francisco.serdio@jku.at
Isolation !
http://www.flll.Francisco Serdio jku.at/staff/francisco
10. Why Fault Detection (FD) ?
Why Fault Isolation (FI) ?
FD with Residual-based approaches
Motivation of the FI Gradient-based approaches
Tools to depict Fault Isolation
Results
Can do we more ?
Conclusions
WCCI 2014 / July 6-11 / Beijing, China
francisco.serdio@jku.at
http://www.flll.Francisco Serdio jku.at/staff/francisco
11. FD with Residual-based approaches
Algebraic relationships among different sensors
Difference relationships among different sensor
outputs and actuator inputs
Inconsistencies, expressed as residuals, can be
used for detection and isolation purposes
[4] V. Venkatasubramanian, R. Rengaswamy, S. Kavuri and K. Yin. (2003). A review of
process fault detection and diagnosis: Part iii: Process history based methods.
Computers & Chemical Engineering, 27(3), 327-346.
WCCI 2014 / July 6-11 / Beijing, China
francisco.serdio@jku.at
Analytical Redundancy
Direct redundancy
Temporal redundancy
http://www.flll.Francisco Serdio jku.at/staff/francisco
12. FD with Residual-based approaches
Analytical Redundancy graphically
Moving from the signal space to the residual space: illustrating an untypical signal pattern
WCCI 2014 / July 6-11 / Beijing, China
francisco.serdio@jku.at
http://www.flll.Francisco Serdio jku.at/staff/francisco
13. Tracking residuals within a dynamic tolerance band
WCCI 2014 / July 6-11 / Beijing, China
francisco.serdio@jku.at
http://www.flll.Francisco Serdio jku.at/staff/francisco
14. Recall FD with Residual-based
approaches
More information regarding Fault Detection in
[5] F. Serdio, E. Lughofer, K. Pichler, T. Buchegger and H. Efendic, Data-Driven Residual-Based
Fault Detection for Condition Monitoring in Rolling Mills. Proceedings of the IFAC Conference on
Manufacturing Modeling, Management and Control, MIM '2013, St. Petersburg, Russia, 2013, pp.
1546-1551. (Winner of MIM 2013 Best paper award)
[6] F. Serdio, E. Lughofer, K. Pichler, T. Buchegger, and H. Efendic, Residual-based Fault Detection
using Soft Computing techniques for Condition Monitoring at Rolling Mills. Information Sciences,
vol. 259, pp. 304–330, 2014.
[7] F. Serdio, E. Lughofer, K. Pichler, T. Buchegger, M. Pichler and H. Efendic, Multivariate Fault
Detection using Vector Autoregressive Moving Average and Orthogonal Transformation in the
residual Space. Annual Conference of the Prognostics and Health Management Society, PHM 2013,
New Orleans, LA, USA, 2013, pp. 548-555.
[8] F. Serdio, E. Lughofer, K. Pichler, T. Buchegger, and H. Efendic, Fault Detection in Multisensor
Networks based on Multivariate Time-series Models and Orthogonal Transformations.
Information Fusion, vol. under revision (minor), 2014.
WCCI 2014 / July 6-11 / Beijing, China
francisco.serdio@jku.at
http://www.flll.Francisco Serdio jku.at/staff/francisco
15. Why Fault Detection (FD) ?
Recall FD with Residual-based approaches
Why Fault Isolation (FI) ?
Motivation of the FI Gradient-based approaches
Tools to depict Fault Isolation
Results
Can do we more?
Conclusions
WCCI 2014 / July 6-11 / Beijing, China
francisco.serdio@jku.at
http://www.flll.Francisco Serdio jku.at/staff/francisco
16. Motivation of the FI Gradient-based
approaches
We are blind about faults
We do not know how a fault looks like
We do not have fault patterns (labeled data)
Process variable contribution plot
There is an extension to non-linear PCA
It reverts back to the original process variables
[9] P. Miller, R. Swanson, and C. Heckler, Contribution plots: A missing link in multivariate quality
control. Applied Mathematics and Computer Science, vol. 8, p. 775792, 1998.
[10] F. Jia, E. Martin, and A. Morris, Nonlinear principal components analysis with application to
process fault detection. International Journal of Systems Science, vol. 31, p. 14731487, 2001.
WCCI 2014 / July 6-11 / Beijing, China
francisco.serdio@jku.at
There is literature about PCA
http://www.flll.Francisco Serdio jku.at/staff/francisco
17. Motivation of the FI Gradient-based
approaches
Partial derivatives !
With respect to a specific dimension can indicate the
relative importance of the corresponding variable
(channel) on that function
Can be computed according to the model expression
Can be computed by means of numeric tricks
We can plug a FI system to any FD model !
WCCI 2014 / July 6-11 / Beijing, China
francisco.serdio@jku.at
http://www.flll.Francisco Serdio jku.at/staff/francisco
18. Motivation of the FI Gradient-based
approaches
How do we revert back to the original process
variables?
We compute the gradients of the model variables
We aggregate the gradients
We get a candidate responsible variable
WCCI 2014 / July 6-11 / Beijing, China
francisco.serdio@jku.at
We take the warning models
Crisp decision
Fuzzy decision
http://www.flll.Francisco Serdio jku.at/staff/francisco
19. Aggregating gradients
Biggest gradient as faulty channel
A channel is either (properly) isolated or not
Several channels are proposed as faulty
There are normalized against the channel with the
highest gradient aggregation
By definition, it will produce always better results than
its crisp counterpart
WCCI 2014 / July 6-11 / Beijing, China
francisco.serdio@jku.at
Crisp decision
Winner takes all approach
Fuzzy decision
http://www.flll.Francisco Serdio jku.at/staff/francisco
20. Why Fault Detection (FD) ?
FD with Residual-based approaches
Why Fault Isolation (FI) ?
Motivation of the FI Gradient-based approaches
Tools to depict Fault Isolation
Results
Can do we more ?
Conclusions
WCCI 2014 / July 6-11 / Beijing, China
francisco.serdio@jku.at
http://www.flll.Francisco Serdio jku.at/staff/francisco
21. Tools to depict Fault Isolation
WCCI 2014 / July 6-11 / Beijing, China
francisco.serdio@jku.at
http://www.flll.Francisco Serdio jku.at/staff/francisco
22. Why Fault Detection (FD) ?
FD with Residual-based approaches
Why Fault Isolation (FI) ?
Motivation of the FI Gradient-based approaches
Tools to depict Fault Isolation
Results
Can do we more?
Conclusions
WCCI 2014 / July 6-11 / Beijing, China
francisco.serdio@jku.at
http://www.flll.Francisco Serdio jku.at/staff/francisco
23. WCCI 2014 / July 6-11 / Beijing, China
francisco.serdio@jku.at
Results
http://www.flll.Francisco Serdio jku.at/staff/francisco
24. WCCI 2014 / July 6-11 / Beijing, China
francisco.serdio@jku.at
Results
http://www.flll.Francisco Serdio jku.at/staff/francisco
25. Why Fault Detection (FD) ?
FD with Residual-based approaches
Why Fault Isolation (FI) ?
Motivation of the FI Gradient-based approaches
Tools to depict Fault Isolation
Results
Can do we more ?
Conclusions
WCCI 2014 / July 6-11 / Beijing, China
francisco.serdio@jku.at
http://www.flll.Francisco Serdio jku.at/staff/francisco
26. Can do we more ?
We must work in how to aggregate the
gradients
Weight the gradients with other data
We are using violation degree of the threshold
We are using quality of the model
Goal: narrow the Fault Isolation Gap (FIG)
WCCI 2014 / July 6-11 / Beijing, China
francisco.serdio@jku.at
Time frames (sliding windows)
http://www.flll.Francisco Serdio jku.at/staff/francisco
27. Why Fault Detection (FD) ?
FD with Residual-based approaches
Why Fault Isolation (FI) ?
Motivation of the FI Gradient-based approaches
Tools to depict Fault Isolation
Results
Can do we more ?
Conclusions
WCCI 2014 / July 6-11 / Beijing, China
francisco.serdio@jku.at
http://www.flll.Francisco Serdio jku.at/staff/francisco
28. Conclusions
We can perform Fault Isolation (FI) without
information about the faults
Only based on warning models and gradients
We have introduced new tools to depict FI
We must still strength the results
WCCI 2014 / July 6-11 / Beijing, China
francisco.serdio@jku.at
Graphically
Numerically
http://www.flll.Francisco Serdio jku.at/staff/francisco
29. Thanks a lot for your attention!
WCCI 2014 / July 6-11 / Beijing, China
{francisco.serdio,edwin.lughofer}@jku.at
http://www.flll.jku.at/staff/{Francisco Serdio, Dr. Edwin Lughofer francisco,lughofer}