Skip to main content

CreepOnto: An Avant-Garde Scheme for Framing and Evaluating Ontologies Using Domain Knowledge of Creep Mechanism

  • Conference paper
  • First Online:
Data Engineering and Communication Technology

Abstract

A good analysis about a specific field of study is a basic and essential requirement for clarifying various terminologies. Ultimately, this has led to the need for development of ontologies which has proven to be a great asset for individuals and groups that seek to ameliorate the usage of useful unorganised particulars and regenerate it to ensure optimum reusability of the same. This has been further kindled by the contemporary desire for artificial intelligence based systems on content-related theories and mechanisms related to a particular domain. This has created the need for developed ontologies to build on cohesive reasoning purposes. An important domain under material sciences termed creep mechanism has been conceptualised due to lack of well-defined ontologies based on it. In subsequent sections, various concepts related to the study of interest have been identified, defined, and established using the relations between them. Web Protégé, a widely used tool for developing ontologies, aides to provide a well-structured framework for CreepOnto. A flowchart designed based on various classes and acts as a primary source of information for readers by acting as a ready reckoner. An OWL representation of the established ontology presents itself as a cornerstone in making the foundation of ontology using axioms. Finally, its effectiveness is measured using various qualitative and quantitative performance metrics which resulted in a reuse ratio of 0.84.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Chu SNG, Li JCM (1977) Impression creep; a new creep test. J. Mater Sci 2(11):2200–2208

    Article  Google Scholar 

  2. Mordike BL (2002) Creep-resistant magnesium alloys. Mater Sci Eng A 324(1–2):103–112

    Article  Google Scholar 

  3. Cannon WR, Langdon TG (1983) Creep of ceramics. J Mater Sci 18(1):1–50

    Article  Google Scholar 

  4. Weertman J (1957) Steady‐state creep through dislocation climb. J Appl Phys 28(3):362–364

    Google Scholar 

  5. Raj R, Ashby MF (1971) On grain boundary sliding and diffusional creep. Metallur Trans 2(4):1113–1127

    Article  Google Scholar 

  6. Wilkinson DS, Ashby MF (1975) Pressure sintering by power law creep. Acta Metall 23(11):1277–1285

    Article  Google Scholar 

  7. Nabarro FRN (1967) Steady-state diffusional creep. Phil Mag 16(140):231–237

    Article  Google Scholar 

  8. Lin PH, Chou HS, Huang JC, Chuang WS, Jang JSC, Nieh TG (2019) Elevated-temperature creep of high-entropy alloys via nanoindentation. MRS Bull 44(11):860–866

    Article  Google Scholar 

  9. Deepak G, Teja V, Santhanavijayan A (2020) A novel firefly driven scheme for resume parsing and matching based on entity linking paradigm. J Discr Math Sci Cryptogr 23(1):157–165

    Google Scholar 

  10. Deepak G, Santhanavijayan A (2020) Onto best fit: a best-fit occurrence estimation strategy for RDF driven faceted semantic search. Comput Commun 160:284–298

    Article  Google Scholar 

  11. Kumar N, Deepak G, Santhanavijayan A (2020) A novel semantic approach for intelligent response generation using emotion detection incorporating NPMI measure. Procedia Comput Sci 167:571–579

    Article  Google Scholar 

  12. Deepak G, Kumar N, Santhanavijayan A (2020) A semantic approach for entity linking by diverse knowledge integration incorporating role-based chunking. Procedia Comput Sci 167:737–746

    Article  Google Scholar 

  13. Haribabu S, Kumar PSS, Padhy S, Deepak G, Santhanavijayan A, Kumar N (2019) A novel approach for ontology focused inter-domain personalized search based on semantic set expansion. In: 2019 Fifteenth international conference on information processing (ICINPRO), pp. 1–5. IEEE Press

    Google Scholar 

  14. Deepak G, Kumar N, Bharadwaj GVSY, Santhanavijayan A (2019) OntoQuest: an ontological strategy for automatic question generation for e-assessment using static and dynamic knowledge. In: 2019 Fifteenth international conference on information processing (ICINPRO), pp 1–6. IEEE Press

    Google Scholar 

  15. Kaushik IS, Deepak G, Santhanavijayan A (2020) QuantQueryEXP: a novel strategic approach for query expansion based on quantum computing principles. J Discr Math Sci Cryptogr 23(2):573–584

    Google Scholar 

  16. Varghese L, Deepak G, Santhanavijayan A (2019) An IoT analytics approach for weather forecasting using raspberry Pi 3 Model B+. In: 2019 Fifteenth international conference on information processing (ICINPRO), pp 1–5. IEEE Press

    Google Scholar 

  17. Deepak G, Priyadarshini S (2016) A hybrid framework for social tag recommendation using context driven social information. Int J Soc Comput Cyber-Phys Syst 1(4):312–325

    Article  Google Scholar 

  18. Deepak G, Priyadarshini JS (2018) A hybrid semantic algorithm for web image retrieval incorporating ontology classification and user-driven query expansion. In: Advances in big data and cloud computing, pp 41–49. Springer, Singapore

    Google Scholar 

  19. Deepak G, Gulzar Z (2017) Ontoepds: enhanced and personalized differential semantic algorithm incorporating ontology driven query enrichment. J Adv Res Dyn Control Syst 9(Special):567–582

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Saicharan Gadamshetti .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2021 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Gadamshetti, S., Shiddhartha, R., Deepak, G., Santhanavijayan, A. (2021). CreepOnto: An Avant-Garde Scheme for Framing and Evaluating Ontologies Using Domain Knowledge of Creep Mechanism. In: Reddy, K.A., Devi, B.R., George, B., Raju, K.S. (eds) Data Engineering and Communication Technology. Lecture Notes on Data Engineering and Communications Technologies, vol 63. Springer, Singapore. https://doi.org/10.1007/978-981-16-0081-4_18

Download citation

Publish with us

Policies and ethics