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Tan, He
Publications (10 of 53) Show all publications
Tarasov, V., Tan, H., Jarfors, A. E. .. & Seifeddine, S. (2020). Fuzzy logic-based modelling of yield strength of as-cast A356 alloy. Neural computing & applications (Print), 32(10), 5833-5844
Open this publication in new window or tab >>Fuzzy logic-based modelling of yield strength of as-cast A356 alloy
2020 (English)In: Neural computing & applications (Print), ISSN 0941-0643, E-ISSN 1433-3058, Vol. 32, no 10, p. 5833-5844Article in journal (Refereed) Published
Abstract [en]

Uncertain and imprecise data are inherent to many domains, e.g. casting lightweight components. Fuzzy logic offers a way to handle such data, which makes it possible to create predictive models even with small and imprecise data sets. Modelling of cast components under fatigue load leads to understanding of material behaviour on component level. Such understanding is important for the design for minimum warranty risk and maximum weight reduction of lightweight cast components. This paper contributes with a fuzzy logic-based approach to model fatigue-related mechanical properties of as-cast components, which has not been fully addressed by the current research. Two fuzzy logic models are constructed to map yield strength to the chemical composition and the rate of solidification of castings for two A356 alloys. Artificial neural networks are created for the same data sets and then compared to the fuzzy logic approach. The comparison shows that although the neural networks yield similar prediction accuracy, they are less suitable for the domain because they are opaque models. The prediction errors exhibited by the fuzzy logic models are 3.53% for the model and 3.19% for the second, which is the same error level as reported in related work. An examination of prediction errors indicated that these are affected by parameters of the membership functions of the fuzzy logic model.

Place, publisher, year, edition, pages
Springer, 2020
Keywords
Fuzzy logic; Membership functions; Artificial neural networks; Prediction accuracy; Mechanical properties prediction; A356 alloy; Cast components
National Category
Materials Engineering Computer Engineering
Identifiers
urn:nbn:se:hj:diva-42912 (URN)10.1007/s00521-019-04056-5 (DOI)XYZ ()2-s2.0-85061300160 (Scopus ID)HOA JTH 2020 (Local ID)HOA JTH 2020 (Archive number)HOA JTH 2020 (OAI)
Funder
Knowledge Foundation, 20170066
Available from: 2019-02-08 Created: 2019-02-08 Last updated: 2020-05-07Bibliographically approved
Tarasov, V., Tan, H. & Adlemo, A. (2019). Automation of software testing process using ontologies. In: J. Dietz, D. Aveiro & J. Filipe (Ed.), Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD: . Paper presented at 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, September 17-19, 2019, Vienna, Austria (pp. 57-66). SciTePress
Open this publication in new window or tab >>Automation of software testing process using ontologies
2019 (English)In: Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD / [ed] J. Dietz, D. Aveiro & J. Filipe, SciTePress, 2019, p. 57-66Conference paper, Published paper (Refereed)
Abstract [en]

Testing of a software system is a resource-consuming activity that requires high-level expert knowledge. Methods based on knowledge representation and reasoning can alleviate this problem. This paper presents an approach to enhance the automation of the testing process using ontologies and inference rules. The approach takes software requirements specifications written in structured text documents as input and produces the output, i.e. test scripts. The approach makes use of ontologies to deal with the knowledge embodied in requirements specifications and to represent the desired structure of test cases, as well as makes use of a set of inference rules to represent strategies for deriving test cases. The implementation of the approach, in the context of an industrial case, proves the validity of the overall approach.

Place, publisher, year, edition, pages
SciTePress, 2019
Keywords
Knowledge Representation, Ontologies, Inference Rules, Test Case Generation, Automated Testing
National Category
Computer Sciences Software Engineering
Identifiers
urn:nbn:se:hj:diva-46589 (URN)10.5220/0008054000570066 (DOI)2-s2.0-85074140225 (Scopus ID)978-989-758-382-7 (ISBN)
Conference
11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, September 17-19, 2019, Vienna, Austria
Available from: 2019-10-17 Created: 2019-10-17 Last updated: 2019-11-19Bibliographically approved
Tan, H., Tarasov, V., Jarfors, A. E. .. & Seifeddine, S. (2019). Fuzzy Logic Based Modelling of Cast Component Properties. Paper presented at 9th IFAC Conference on Manufacturing Modelling, Management and Control MIM 2019: Berlin, Germany, 28–30 August 2019. IFAC-PapersOnLine, 52(13), 1132-1137
Open this publication in new window or tab >>Fuzzy Logic Based Modelling of Cast Component Properties
2019 (English)In: IFAC-PapersOnLine, E-ISSN 2405-8963, Vol. 52, no 13, p. 1132-1137Article in journal (Refereed) Published
Abstract [en]

Digitalization of manufacturing requires building models to represent accumulated data and knowledge on the products and processes. The use of formal knowledge models allows for increase of the automation level leading to more sustainable manufacturing. Casting is important for different industries because it offers a great freedom of designing for weight reduction. This paper presents an approach to modelling of cast component properties that is based on fuzzy logic. The approach includes learning of the fuzzy inference rules from the data. The constructed fuzzy logic models can be used to tune the manufacturing process to produces cast components with desired properties. The evaluation of the results demonstrates that the accuracy of the two created models are 3.58% and 3.15% respectively with the learned fuzzy inference rules being identical to the manually created ones. The presented approach can help to automate the management of cast component manufacturing. 

Place, publisher, year, edition, pages
Elsevier, 2019
Keywords
knowledge modelling; fuzzy logic; fuzzy systems; mechanical properties prediction
National Category
Other Computer and Information Science
Identifiers
urn:nbn:se:hj:diva-47362 (URN)10.1016/j.ifacol.2019.11.348 (DOI)000504282400193 ()2-s2.0-85078888003 (Scopus ID)POA JTH 2019 (Local ID)POA JTH 2019 (Archive number)POA JTH 2019 (OAI)
Conference
9th IFAC Conference on Manufacturing Modelling, Management and Control MIM 2019: Berlin, Germany, 28–30 August 2019
Available from: 2020-01-14 Created: 2020-01-14 Last updated: 2020-02-24Bibliographically approved
Tan, H., Tarasov, V. & Adlemo, A. (2019). Lessons Learned from an Application of Ontologies in Software Testing. In: Adrien Barton, Selja Seppälä, Daniele Porello, et.al. (Ed.), CEUR Workshop Proceedings: . Paper presented at JOWO 2019, The Joint Ontology Workshops, Graz, Austria, September 23-25, 2019.. CEUR-WS, 2518
Open this publication in new window or tab >>Lessons Learned from an Application of Ontologies in Software Testing
2019 (English)In: CEUR Workshop Proceedings / [ed] Adrien Barton, Selja Seppälä, Daniele Porello, et.al., CEUR-WS , 2019, Vol. 2518Conference paper, Published paper (Refereed)
Abstract [en]

Testing of a software system is a resource-consuming activity that requires high-level expert knowledge. In previous work we proposed an ontologybased approach to alleviate this problem. In this paper we discuss the lessons learned from the implementation and application of the approach in a use case from the avionic industry. The lessons are related to the areas of ontology development, ontology evaluation, the OWL language and rule-based reasoning.

Place, publisher, year, edition, pages
CEUR-WS, 2019
Series
CEUR Workshop Proceedings, E-ISSN 1613-0073
Keywords
application of ontologies, OWL, Prolog, lesson learned, test case generation, automated testing
National Category
Software Engineering
Identifiers
urn:nbn:se:hj:diva-47361 (URN)2-s2.0-85077693642 (Scopus ID)
Conference
JOWO 2019, The Joint Ontology Workshops, Graz, Austria, September 23-25, 2019.
Available from: 2020-01-13 Created: 2020-01-13 Last updated: 2020-01-29Bibliographically approved
Adlemo, A., Tan, H. & Tarasov, V. (2018). Test case quality as perceived in Sweden. In: Michael Unterkalmsteiner (Ed.), Proceedings - International Conference on Software Engineering: . Paper presented at 2018 ACM/IEEE 5th International Workshop on Requirements Engineering and Testing, Gothenburg, Sweden, June 02, 2018 (pp. 9-12). ACM Digital Library
Open this publication in new window or tab >>Test case quality as perceived in Sweden
2018 (English)In: Proceedings - International Conference on Software Engineering / [ed] Michael Unterkalmsteiner, ACM Digital Library, 2018, p. 9-12Conference paper, Published paper (Refereed)
Abstract [en]

In order to reach an acceptable level of confidence in the quality of a software product, testing of the software is paramount. To obtain "good" quality software it is essential to rely on "good" test cases. To define the criteria for what make up for a "good" test case is not a trivial task. Over the past 15 years, a short list of publications have presented criteria for "good" test cases but without ranking them based on their importance. This paper presents a non-exhaustive and non-authoritative tentative list of 15 criteria and a ranking of their relative importance. A number of the criteria come from previous publications but also from discussions with our industrial partners. The ranking is based on results collected via a questionnaire that was sent out to a limited number of randomly chosen respondents in the Swedish software industry. This means that the results are more indicative than conclusive.

Place, publisher, year, edition, pages
ACM Digital Library, 2018
Series
Proceedings - International Conference on Software Engineering, ISSN 0270-5257
Keywords
good software test cases, quality criteria, requirement-driven development, test-driven development
National Category
Computer Systems
Identifiers
urn:nbn:se:hj:diva-41033 (URN)10.1145/3195538.3195541 (DOI)2-s2.0-85051230713 (Scopus ID)978-1-4503-5749-4 (ISBN)
Conference
2018 ACM/IEEE 5th International Workshop on Requirements Engineering and Testing, Gothenburg, Sweden, June 02, 2018
Projects
Ontology-based software test case generation
Funder
Knowledge Foundation, 20140170
Available from: 2018-07-22 Created: 2018-07-22 Last updated: 2019-08-21Bibliographically approved
Tarasov, V., Tan, H., Ismail, M., Adlemo, A. & Johansson, M. (2017). Application of inference rules to a software requirements ontology to generate software test cases. In: Dragoni, Mauro; Poveda-Villalón, María; Jimenez-Ruiz, Ernesto (Ed.), OWL: Experiences and Directions – Reasoner Evaluation: 13th International Workshop, OWLED 2016, and 5th International Workshop, ORE 2016, Bologna, Italy, November 20, 2016, Revised Selected Papers (pp. 82-94). Cham: Springer
Open this publication in new window or tab >>Application of inference rules to a software requirements ontology to generate software test cases
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2017 (English)In: OWL: Experiences and Directions – Reasoner Evaluation: 13th International Workshop, OWLED 2016, and 5th International Workshop, ORE 2016, Bologna, Italy, November 20, 2016, Revised Selected Papers / [ed] Dragoni, Mauro; Poveda-Villalón, María; Jimenez-Ruiz, Ernesto, Cham: Springer, 2017, p. 82-94Chapter in book (Refereed)
Abstract [en]

Testing of a software system is resource-consuming activity. One of the promising ways to improve the efficiency of the software testing process is to use ontologies for testing. This paper presents an approach to test case generation based on the use of an ontology and inference rules. The ontology represents requirements from a software requirements specification, and additional knowledge about components of the software system under development. The inference rules describe strategies for deriving test cases from the ontology. The inference rules are constructed based on the examination of the existing test documentation and acquisition of knowledge from experienced software testers. The inference rules are implemented in Prolog and applied to the ontology that is translated from OWL functional-style syntax to Prolog syntax. The first experiments with the implementation showed that it was possible to generate test cases with the same level of detail as the existing, manually produced, test cases.

Place, publisher, year, edition, pages
Cham: Springer, 2017
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 10161
Keywords
Inference Rules, Ontology, OWL, Prolog, Requirement Specification, Test Case Generation
National Category
Computer Sciences Software Engineering
Identifiers
urn:nbn:se:hj:diva-35164 (URN)10.1007/978-3-319-54627-8_7 (DOI)000426195800007 ()2-s2.0-85014455857 (Scopus ID)978-3-319-54627-8 (ISBN)
Projects
Ontology-based Software Test Case Generation (OSTAG)
Funder
Knowledge Foundation, 20140170
Available from: 2017-03-07 Created: 2017-03-07 Last updated: 2019-08-22Bibliographically approved
Tan, H., Adlemo, A., Tarasov, V. & Johansson, M. E. (2017). Evaluation of an Application Ontology. In: Stefano Borgo, Oliver Kutz, Frank Loebe, Fabian Neuhaus, Kemo Adrian, Mihailo Antović, Valerio Basile, Martin Boeker, Diego Calvanese, Tommaso Caselli, Giorgio Colombo, Roberto Confalonieri, Laura Daniele, Jérôme Euzenat, Antony Galton, Dagmar Gromann, Maria M. Hedblom, Heinrich Herre, Inge Hinterwaldner, Andrea Janes, Ludger Jansen, Kris Krois, Antonio Lieto, Claudio Masolo, Rafael Peñaloza, Daniele Porello, Daniele P. Radicioni, Emilio M. Sanfilippo, Daniel Schober, Rossella Stufano, Amanda Vizedom (Ed.), The Joint Ontology Workshops: . Paper presented at Proceedings of the Joint Ontology Workshops 2017 Episode 3: The Tyrolean Autumn of Ontology Bozen-Bolzano, Italy, September 21–23, 2017. CEUR-WS, 2050
Open this publication in new window or tab >>Evaluation of an Application Ontology
2017 (English)In: The Joint Ontology Workshops / [ed] Stefano Borgo, Oliver Kutz, Frank Loebe, Fabian Neuhaus, Kemo Adrian, Mihailo Antović, Valerio Basile, Martin Boeker, Diego Calvanese, Tommaso Caselli, Giorgio Colombo, Roberto Confalonieri, Laura Daniele, Jérôme Euzenat, Antony Galton, Dagmar Gromann, Maria M. Hedblom, Heinrich Herre, Inge Hinterwaldner, Andrea Janes, Ludger Jansen, Kris Krois, Antonio Lieto, Claudio Masolo, Rafael Peñaloza, Daniele Porello, Daniele P. Radicioni, Emilio M. Sanfilippo, Daniel Schober, Rossella Stufano, Amanda Vizedom, CEUR-WS , 2017, Vol. 2050Conference paper, Published paper (Refereed)
Abstract [en]

The work presented in this paper demonstrates an evaluation procedure for a real-life application ontology, coming from the avionics domain. The focus of the evaluation has specifically been on three ontology quality features, namely usability, correctness and applicability. In the paper, the properties of the three features are explained in the context of the application domain, the methods and tools used for the evaluation of the features are presented, and the evaluation results are presented and discussed. The results indicate that the three quality features are significant in the evaluation of our application ontology, that the proposed methods and tools allow for the evaluation of the three quality features and that the inherent quality of the application ontology can be confirmed.

Place, publisher, year, edition, pages
CEUR-WS, 2017
Series
CEUR Workshop Proceedings, ISSN 1613-0073 ; 2050
Keywords
application ontologies, ontology evaluation, ontology quality features, ontology verbalization
National Category
Computer Systems
Identifiers
urn:nbn:se:hj:diva-38902 (URN)2-s2.0-85045576954 (Scopus ID)
Conference
Proceedings of the Joint Ontology Workshops 2017 Episode 3: The Tyrolean Autumn of Ontology Bozen-Bolzano, Italy, September 21–23, 2017
Available from: 2018-02-23 Created: 2018-02-23 Last updated: 2019-08-21Bibliographically approved
Tan, H., Ismail, M., Tarasov, V., Adlemo, A. & Johansson, M. (2016). Development and evaluation of a software requirements ontology. In: Iaakov Exman, Juan Llorens and Anabel Fraga (Ed.), SKY 2016 - 7th International Workshop on Software Knowledge, Proceedings - In conjuction with IC3K 2016: . Paper presented at 7th International Workshop on Software Knowledge - SKY 2016 in conjunction with the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - IC3K 2016, November 9-10, 2016, in Porto, Portugal (pp. 11-18). SciTePress
Open this publication in new window or tab >>Development and evaluation of a software requirements ontology
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2016 (English)In: SKY 2016 - 7th International Workshop on Software Knowledge, Proceedings - In conjuction with IC3K 2016 / [ed] Iaakov Exman, Juan Llorens and Anabel Fraga, SciTePress, 2016, p. 11-18Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents an ontology which has been developed to represent the requirements of a software component pertaining to an embedded system in the avionics industry. The ontology was built based on the software requirements documents and was used to support advanced methods in the subsequent stages of the software development process. In this paper it is described theprocess that was used to build the ontology. Two pertinent quality measures that were applied to the ontology, i.e. usability and applicability, are also described, as well as the methods used to evaluate the quality measures and the result of these evaluations.

Place, publisher, year, edition, pages
SciTePress, 2016
Keywords
Ontology, Software Requirements, Ontology Development, Ontology Evaluation, Avionics Software Development
National Category
Computer Systems
Identifiers
urn:nbn:se:hj:diva-32277 (URN)10.5220/0006079300110018 (DOI)000393154100001 ()2-s2.0-85007006434 (Scopus ID)978-989-758-202-8 (ISBN)
Conference
7th International Workshop on Software Knowledge - SKY 2016 in conjunction with the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - IC3K 2016, November 9-10, 2016, in Porto, Portugal
Projects
Ontology-based Software Test Case Generation (OSTAG)
Funder
Knowledge Foundation, KKS-20140170
Available from: 2016-11-16 Created: 2016-11-16 Last updated: 2019-08-21Bibliographically approved
Resmini, A., Tan, H., Tarasov, V. & Adlemo, A. (2016). #ViewFromTheOffice - Reconceptualizing the Workplace as an Information-based Ecosystem. In: Proceedings of the 6th STS Conference on Socio-technical Ecosystems: . Paper presented at 6th STS Conference on Socio-technical Ecosystems.
Open this publication in new window or tab >>#ViewFromTheOffice - Reconceptualizing the Workplace as an Information-based Ecosystem
2016 (English)In: Proceedings of the 6th STS Conference on Socio-technical Ecosystems, 2016Conference paper, Published paper (Refereed)
Keywords
user experience, workplace, cross-channel, information architecture
National Category
Interaction Technologies
Identifiers
urn:nbn:se:hj:diva-34312 (URN)
Conference
6th STS Conference on Socio-technical Ecosystems
Available from: 2016-12-14 Created: 2016-12-14 Last updated: 2019-08-22Bibliographically approved
Tarasov, V., Tan, H., Adlemo, A., Ismail, M., Mats, J. & Olsson, D. (2015). Ontology-based Software Test Case Generation (OSTAG). In: R. J. Machado, J. Sequeira,H. Plácido da Silva, & J. Filipe (Ed.), European Projects in Knowledge Applications and Intelligent Systems - Volume 1: EPS Lisbon 2016: . Paper presented at European Projects in Knowledge Applications and Intelligent Systems, July 20-23, 2016, Lisbon, Portugal (pp. 135-159). SciTePress
Open this publication in new window or tab >>Ontology-based Software Test Case Generation (OSTAG)
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2015 (English)In: European Projects in Knowledge Applications and Intelligent Systems - Volume 1: EPS Lisbon 2016 / [ed] R. J. Machado, J. Sequeira,H. Plácido da Silva, & J. Filipe, SciTePress, 2015, p. 135-159Conference paper, Published paper (Refereed)
Abstract [en]

Testing is a paramount quality assurance activity in every software developmentproject, especially for embedded, safety critical systems. During thetest process, a lot of effort is put into the generation of test cases. The presentedOSTAG project aimed at developing methods and techniques to automate thesoftware test case generation for black-box testing. The proposed approach wasbased on the creation of a software requirements ontology and the applicationof inference rules on the ontology to derive test cases. The ontology representsknowledge of the requirements, the software system and the corresponding applicationdomain while the inference rules formalize knowledge from documentsand experienced testers in the domain of test planning and test case generation.A software prototype of the approach was implemented and one of the industrialproject partners evaluated the results. An alternative method for generating testcases, based on genetic algorithms, was also explored.

Place, publisher, year, edition, pages
SciTePress, 2015
Keywords
Black-box Testing, Embedded Systems, Genetic Algorithms, Inference Rules, Knowledge Modelling, Model-Based Testing, Ontology Development, Ontology Quality Evaluation, Ontology Verbalisation, OWL, Prolog, Prot´eg´e, Software Requirements Specification, Test Case Generation.
National Category
Computer Systems
Identifiers
urn:nbn:se:hj:diva-43426 (URN)10.5220/0007901301350159 (DOI)978-989-758-356-8 (ISBN)
Conference
European Projects in Knowledge Applications and Intelligent Systems, July 20-23, 2016, Lisbon, Portugal
Funder
Knowledge Foundation, 20140170
Available from: 2019-04-04 Created: 2019-04-04 Last updated: 2019-08-21Bibliographically approved
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