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  • 101.
    Sandkuhl, Kurt
    et al.
    Jönköping University, School of Engineering, JTH. Research area Information Engineering.
    Lundqvist, Magnus
    Jönköping University, School of Engineering, JTH. Research area Information Engineering.
    Tarasov, Vladimir
    Jönköping University, School of Engineering, JTH. Research area Information Engineering. Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    COMPETENCE MODEL FOR COLLABORATIVE DESIGN2006In: Proceedings of 4th Intl. Workshop on Challenges in Collaborative Engineering (CCE’06): , 2006Conference paper (Other academic)
    Abstract [en]

    Collaborative design in dispersed groups of engineers creates various kinds of challenges to technology, organization and social environment. This paper presents an approach to description and representation of the competences needed for a planned collaborative design project. The most important competence areas are identified starting from the nature of design work, problem solving in design teams, and working in distributed groups. The competence model is built structuring these areas according to three perspectives: general, cultural, and occupational competences. An ontological representation is proposed to implement the described model for collaborative design competence. Using an ontology language for representation of collaborative design competence models makes it possible to identify those individuals who are best suited for the collaboration by ontology matching. Finally, a software design team consisting of two persons was interviewed and two competence profiles were created using the developed ontological representation of the model. The modeling of the team members has proved that the proposed approach can be applied to modeling competences needed for collaborative design in engineering fields.

  • 102.
    Sandkuhl, Kurt
    et al.
    Jönköping University, School of Engineering, JTH. Research area Information Engineering.
    Seigerroth, Ulf
    Jönköping University, School of Engineering, JTH. Research area Information Engineering.
    Tarasov, Vladimir
    Jönköping University, School of Engineering, JTH. Research area Information Engineering. Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    Context Modelling for Decision Making in Competence Supply: Experiences from a Military Case2012Conference paper (Refereed)
    Abstract [en]

    Within large organisations, decisions about competence development activities or the assignment of staff members to mission-critical projects have to be based on a clear understanding of the organizational competences and the underlying individual competences. Competence modelling, i.e. the use of enterprise modelling techniques for capturing existing and describing desired organisational and individual competences in enterprises, offers important contributions to this field. However, competence models usually do not capture sufficient context information for supporting decision making in organisations. This paper presents an approach for modelling competence supply contexts based on enterprise modelling, investigates an example from network-based defence and discusses first experiences.

  • 103.
    Sandkuhl, Kurt
    et al.
    Jönköping University, School of Engineering, JTH. Research area Information Engineering.
    Smirnov, Alexander
    St. Petersburg Institute for Informatics and Automation, RAS.
    Mazalov, Vladimir
    Institute of Applied Mathematical Research, KarRC RAS.
    Vdovitsyn, Vladimir
    Institute of Applied Mathematical Research, KarRC RAS.
    Tarasov, Vladimir
    Jönköping University, School of Engineering, JTH. Research area Information Engineering. Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    Krizhanovsky, Andrew
    St. Petersburg Institute for Informatics and Automation, RAS.
    Lin, Feiyu
    Jönköping University, School of Engineering, JTH. Research area Information Engineering.
    Ivashko, Evgeny
    Institute of Applied Mathematical Research, KarRC RAS.
    Context-Based Retrieval in Digital Libraries: Approach and Technological Framework2009In: Digital Libraries: Advanced Methods and Technologies, Digital Collections: Proceedings of the XIth All-Russian research conference RCDL'2009, Petorzavodsk, 2009, p. 151-157Conference paper (Other academic)
    Abstract [en]

    Digital libraries face similar challenges as enterprise information sources and the Internet: a fast growing amount of digital content requires enhanced ways of supporting information seeking. This paper presents an approach to context-based retrieval in Digital Libraries (DLs). The proposed approach includes creation of a profile representing general information demand of a user (abstract context), and use of ontology matching to identify the documents relevant to the operational context representing the current information demand of the user. A profile represents the user’s interests as a DL reader and after creation is dynamically updated based on the changes in the user’s interests. The identification of documents relevanсе is carried out by matching the user profile ontology against the digital library ontology. Semantic distance calculation is based on the use of a thesaurus.

  • 104.
    Sandkuhl, Kurt
    et al.
    Jönköping University, School of Engineering, JTH. Research area Information Engineering.
    Tarasov, Vladimir
    Jönköping University, School of Engineering, JTH. Research area Information Engineering. Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    Comparison of Approaches for Competence Demand Modeling in Flexible Supply Networks2010In: Logistics and Supply Chain Management: German-Russian Perspectives, Proceedings of the 5th German-Russian Logistics Workshop, St, Petersburg, Russia, 2010Conference paper (Other academic)
    Abstract [en]

    In several industrial domains, the adaption of supply strategies  for global market needs resulted in flexible supply networks and other collaborative or networked organization forms. In this context, concepts and approaches from competence management can contribute to capture, systematically develop and integrate organizational competence of the member companies in such networks. The contribution of this paper are (1) to describe two different ways of competence modeling based on enterprise modeling and based on ontology engineering, and (2) the comparison of these two approaches for expressing competence demand. The criteria used for comparing the approaches are (a) requirements derived from the lifecycle of flexible supply networks and (b) criteria assessing the technical characteristics of the demand models.

  • 105.
    Sandkuhl, Kurt
    et al.
    Jönköping University, School of Engineering, JTH. Research area Information Engineering.
    Tarasov, Vladimir
    Jönköping University, School of Engineering, JTH. Research area Information Engineering. Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    Modelling Competence Demand for Flexible Supply Networks2009In: 13th IFAC symposium on Information Control Problems in Manufacturing / [ed] Bakhtadze, Natalia; Dolgui, Alexandre, IFAC , 2009, p. 103-108Conference paper (Other academic)
    Abstract [en]

    Many industrial domains experienced during the last decade a shift towards flexible and collaborative strategies adapted for global markets, like flexible supply networks. Competence management offers concepts and approaches which can be applied to identify, systematically develop and integrate organizational competence of suppliers in such networks. Based on a requirement analysis and two case studies, the paper investigates competence supply in flexible supply networks. The contributions of this paper are (1) requirements to competence management in flexible supply networks, (2) an approach to express competence demand based on enterprise models, and (3) recommendations how to adjust enterprise modelling practices and techniques based on the two cases studies.

  • 106.
    Sandkuhl, Kurt
    et al.
    Jönköping University, School of Engineering, JTH. Research area Information Engineering.
    Tarasov, Vladimir
    Jönköping University, School of Engineering, JTH. Research area Information Engineering. Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    Albertsen, Thomas
    Jönköping University, School of Engineering, JTH. Research area Information Engineering.
    Seigerroth, Ulf
    Jönköping University, School of Engineering, JTH. Research area Information Engineering.
    Competence demand modeling based on enterprise models: KOMO - project report2009Report (Other academic)
  • 107.
    Sandkuhl, Kurt
    et al.
    Jönköping University, School of Engineering, JTH. Research area Information Engineering.
    Tarasov, Vladimir
    Jönköping University, School of Engineering, JTH. Research area Information Engineering. Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    Mazalov, Vladimir
    Institute of Applied Mathematical Research, KarRC RAS.
    Smirnov, Alexander
    St.Petersburg Institute for Informatics and Automation RAS.
    Context based Retrieval in Digital Libraries: Continuing PhD Education and Experimentation (CoReLib2): Final project report2012Report (Other academic)
  • 108.
    Sandkuhl, Kurt
    et al.
    Jönköping University, School of Engineering, JTH. Research area Information Engineering.
    Tarasov, Vladimir
    Jönköping University, School of Engineering, JTH. Research area Information Engineering. Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    Mazalov, Vladimir
    Institute of Applied Mathematical Research, KarRC RAS.
    Smirnov, Alexander
    St.Petersburg Institute for Informatics and Automation RAS.
    Context based Retrieval in Digital Libraries (CoReLib): Final project report2009Report (Other academic)
  • 109.
    Shimizu, Cogan
    et al.
    Data Semantics Lab, Wright State University, US.
    Hammar, Karl
    Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    CoModIDE – The Comprehensive Modular Ontology Engineering IDE2019In: CEUR Workshop Proceedings / [ed] Mari Carmen Suárez-Figueroa, Gong Cheng, Anna Lisa Gentile, Christophe Guéret, Maria Keet, Abraham Bernstein, CEUR-WS , 2019, Vol. 2456, p. 249-252Conference paper (Refereed)
  • 110.
    Skjæveland, Martin G.
    et al.
    University of Oslo.
    Hu, YingjieUniversity at Buffalo.Hammar, KarlJönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).Svátek, VojtěchUniversity of Economics, Prague.Ławrynowicz, AgnieszkaPoznan University of Technology .
    WOP 2018: Workshop on Ontology Design and Patterns2018Conference proceedings (editor) (Refereed)
  • 111.
    Sundell, Håkan
    et al.
    Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL). Univ Boras, Dept Informat Technol, Boras, Sweden.
    Löfström, Tuwe
    Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL). Univ Boras, Dept Informat Technol, Boras, Sweden.
    Johansson, Ulf
    Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL). Univ Boras, Dept Informat Technol, Boras, Sweden.
    Explorative multi-objective optimization of marketing campaigns for the fashion retail industry2018In: Data Science And Knowledge Engineering For Sensing Decision Support / [ed] Liu, J, Lu, J, Xu, Y, Martinez, L & Kerre, EE, World Scientific, 2018, Vol. 11, p. 1551-1558Conference paper (Refereed)
    Abstract [en]

    We show how an exploratory tool for association rule mining can be used for efficient multi-objective optimization of marketing campaigns for companies within the fashion retail industry. We have earlier designed and implemented a novel digital tool for mining of association rules from given basket data. The tool supports efficient finding of frequent itemsets over multiple hierarchies and interactive visualization of corresponding association rules together with numerical attributes. Normally when optimizing a marketing campaign, factors that cause an increased level of activation among the recipients could in fact reduce the profit, i.e., these factors need to be balanced, rather than optimized individually. Using the tool we can identify important factors that influence the search for an optimal campaign in respect to both activation and pro fit. We show empirical results from a real-world case-study using campaign data from a well-established company within the fashion retail industry, demonstrating how activation and profit can be simultaneously targeted, using computer-generated algorithms as well as human-controlled visualization.

  • 112.
    Tan, He
    Jönköping University, School of Engineering, JTH. Research area Information Engineering. Jönköping University, School of Engineering, JTH, Computer and Electrical Engineering. Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    A Method for Building FrameNet-like Corpus for the Biomedical Domain2014In: Proceedings of the 5th International Workshop on Health Text Mining and Information Analysis (Louhi) / [ed] Martin Duneld, Association for Computational Linguistics, 2014, p. 46-53Conference paper (Refereed)
    Abstract [en]

    Semantic Role Labeling (SRL) plays an important role in different text mining tasks. The development of SRL systems for the biomedical area is frustrated by the lack of large-scale domain specific corpora that are annotated with semantic roles. In our previous work, we proposed a method for building FramenNet-like corpus for the area using domain knowledge provided by ontologies. In this paper, we present a framework for supporting the method and the system which we developed based on the framework. In the system we have developed the algorithms for selecting appropriate concepts to be translated into semantic frames, for capturing the information that describes frames from ontology terms, and for collecting example sentence using ontological knowledge.

  • 113.
    Tan, He
    et al.
    Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    Adlemo, Anders
    Jönköping University, School of Engineering, JTH, Computer Science and Informatics.
    Tarasov, Vladimir
    Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    Johansson, Mats E.
    Saab AB, Jönköping, Sweden.
    Evaluation of an Application Ontology2017In: 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 (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.

  • 114.
    Tan, He
    et al.
    Jönköping University, School of Engineering, JTH. Research area Information Engineering. Jönköping University, School of Engineering, JTH, Computer and Electrical Engineering. Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    Barakat, George
    Jönköping University, School of Engineering, JTH, Computer and Electrical Engineering.
    Tarasov, Vladimir
    Jönköping University, School of Engineering, JTH, Computer and Electrical Engineering. Jönköping University, School of Engineering, JTH. Research area Information Engineering. Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    Translating XML Models into OWL Ontologies for Interoperability of Simulation Systems2015In: Proceedings of the 3rd Workshop on Ontologies and Information Systems (WOIS 2015), Tartu, Estonia, August 26, 2015 / [ed] Raimundas Matulevičius, Fabrizio Maria Maggi and Peep Küngas, 2015, p. 116-123Conference paper (Refereed)
    Abstract [en]

    Today XML is a common format supporting interoperabilityand information exchange between systems in the modeling and simulationeld. Although XML enables systems to agree on a common syntaxand understand the exchanged information, systems can misinterpretthem due to their dierent conceptualizations of the domain of interest.In this paper, we present a framework for automatic translation ofXML simulation models which follow the High Level Architecture (HLA) object model template specication, into OWL ontologies. In OWL ontologiesthe semantics of information is formally dened. It provides thebasis for interoperability and information exchange between simulationsystems on semantic level.

  • 115.
    Tan, He
    et al.
    Jönköping University, School of Engineering, JTH. Research area Computer Science and Informatics. Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    Ismail, Muhammad
    Jönköping University, School of Engineering, JTH, Computer Science and Informatics. Jönköping University, School of Engineering, JTH. Research area Computer Science and Informatics.
    Tarasov, Vladimir
    Jönköping University, School of Engineering, JTH. Research area Computer Science and Informatics. Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    Adlemo, Anders
    Jönköping University, School of Engineering, JTH, Computer Science and Informatics. Jönköping University, School of Engineering, JTH. Research area Computer Science and Informatics.
    Johansson, Mats
    Saab Avionics Systems, Jönköping.
    Development and evaluation of a software requirements ontology2016In: 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 (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.

  • 116.
    Tan, He
    et al.
    Jönköping University, School of Engineering, JTH. Research area Information Engineering. Jönköping University, School of Engineering, JTH, Computer and Electrical Engineering. Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    Resmini, Andrea
    Jönköping University, Jönköping International Business School, JIBS, Informatics.
    Tarasov, Vladimir
    Jönköping University, School of Engineering, JTH, Computer and Electrical Engineering. Jönköping University, School of Engineering, JTH. Research area Information Engineering. Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    Adlemo, Anders
    Jönköping University, School of Engineering, JTH, Computer and Electrical Engineering. Jönköping University, School of Engineering, JTH. Research area Information Engineering.
    Workplace innovation in Swedish local organizations - technology aspect: BIS 2015 International Workshops, Poznań, Poland, June 24-26, 2015, Revised Papers2015In: Business Information Systems Workshops / [ed] Witold Abramowicz, 2015, Vol. 228, p. 139-147Conference paper (Refereed)
    Abstract [en]

    Workplace innovation (WI) is important to provide betterwork opportunities and increase productivity. WI at the individual tasklevel concerns the structure of individual work tasks. A number of surveyshave been done that measured WI at the individual task level, howeverthey paid little attention to work environment, in particular to supportivetechnology. This paper presents the case study of WI in two Swedishorganisations with focus on the alignment of ICT and the individual worktasks. We carried out seven interviews of workers at dierent levels ofjob and in dierent sectors. The qualitative data analysis identied fourthemes: business processes, working roles, data sources, and technology.The analysis was facilitated by constructing BPMN (Business ProcessModel Notation) diagrams for the identied business processes. We discoveredthat the supportive technology in the organisations is adequatebut downright traditional. We argue that technology is an important factorand enabler for WI. Finally, we present an architectural model thatprovides a direction for future work on WI taking ICT as the basis.

  • 117.
    Tan, He
    et al.
    Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    Tarasov, Vladimir
    Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    Adlemo, Anders
    Jönköping University, School of Engineering, JTH, Computer Science and Informatics.
    Lessons Learned from an Application of Ontologies in Software Testing2019In: CEUR Workshop Proceedings / [ed] Adrien Barton, Selja Seppälä, Daniele Porello, et.al., CEUR-WS , 2019, Vol. 2518Conference 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.

  • 118.
    Tan, He
    et al.
    Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    Tarasov, Vladimir
    Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    Jarfors, Anders E.W.
    Jönköping University, School of Engineering, JTH, Materials and Manufacturing.
    Seifeddine, Salem
    Jönköping University, School of Engineering, JTH, Materials and Manufacturing.
    Fuzzy Logic Based Modelling of Cast Component Properties2019In: IFAC-PapersOnLine, E-ISSN 2405-8963, Vol. 52, no 13, p. 1132-1137Article in journal (Refereed)
    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. 

  • 119.
    Tarasov, Vladimir
    Jönköping University, School of Engineering, JTH. Research area Information Engineering. Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    Applying intelligent agent technology to create instruction programs1998In: Proceedings of Finnish Data Processing Week (FDPW'97–98) on Developments in Distributed Systems and Data Communications, Petrozavodsk: Petrozavodsk State University , 1998, p. 190-204Conference paper (Other academic)
    Abstract [en]

    This article concerns the problem of creating intellectuallized instruction programs. We suggest applying intelligent agent and multi-agent technologies for the creation of such programs. Two examples, COACH and IDLE, are given of existing systems of this kind. Then we describe the LimTUTOR system which is developed to support the process of teaching students to solve tasks of searching for function limits. Finally we extend LimTUTOR to a multi-agent system to cover di erent aspects of teaching a discipline.

  • 120.
    Tarasov, Vladimir
    Jönköping University, School of Engineering, JTH. Research area Information Engineering. Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    Multi-agent system architecture for supporting the process of distance learning2000In: Learning and teaching science and mathematics in secondary and higher education: proceedings of the fifth Inter-Karelian conference, Petrozavodsk, Russia, 17-19 May, 2000 / [ed] K.M. Sormunen, V.A. Tarasov & S.R. Bogdanov, Joensuu: University of Joensuu , 2000, p. 180-184Conference paper (Other academic)
  • 121.
    Tarasov, Vladimir
    Jönköping University, School of Engineering, JTH. Research area Information Engineering. Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    Ontology-based Approach to Competence Profile Management2012In: Journal of universal computer science (Online), ISSN 0948-695X, E-ISSN 0948-6968, Vol. 18, no 20, p. 2893-2919Article in journal (Refereed)
    Abstract [en]

    Competence management has received much attention during recent years because it contributes to achieving organizational goals and solving problems such as improvement of information or competence supply. Many approaches were proposed to modelling competence and using competence models but there is still a lack of research into structures and utilisation of competence proles in a competence management system. This article addresses this problem by proposing a formal approach to competence prole management. Four project cases are first analysed to elicit requirements of competence prole management, including competence prole operations. After that, an abstract model of competence prole management is formally denedbased on the requirements. Finally, an ontology-based implementation of the abstract model is presented including a software architecture of a competence prole management system. The main contribution of this work is formalization of operations on competence proles and ontology-based implementation of these operations. The proposed implementation architecture can facilitate construction of a competence prole management system.

  • 122.
    Tarasov, Vladimir
    Jönköping University, School of Engineering, JTH. Research area Information Engineering. Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    Using explicit representation of inference search metarules for inference search control in expert systems1997In: Proceedings of the International Conference on Informatics and Control (ICI&C’97), Vol. 2, St. Petersburg, 1997, p. 421-428Conference paper (Other academic)
    Abstract [en]

    This paper considers the use of metalevel tools for inference search control in expertsystems. Offered here are tools for inference search control in the form of a system of languageconstructions, the basic ones of which are inference metarules, control predicates, control labelsand inferences. These tools served as a basis for the development of an inference searchcontrol language designed for the description of query processing control in expert systems.This language allows for more precise description of the logic and techniques of an expert'sreasoning about solving a particular task due to an extended set of control predicates, use of anexplicit labels arrangement for backtracking organization, and description of solution searchstrategies in an explicit way with the help of inference search metarules. The accomplishedprogram implementation of the inference search control language demonstrates possibilities ofthe proposed approach and can form a basis for development of appropriate tools. The designedlanguage is approved in the problem domain connected with the search for functionlimits. A prototype of the knowledge-based system is constructed for solving training tasks ofsearch for function limits.

  • 123.
    Tarasov, Vladimir
    Jönköping University, School of Engineering, JTH. Research area Information Engineering. Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    Using intelligent agent technology for the development of a system teaching how to search for function limits1998In: Proceedings of the Third Inter-Karelian Conference on Teaching Mathematics and Physics in Secondary and Higher Education / [ed] K.M. Sormunen, V.A. Tarasov & V.P. Pjadin, Joensuu: University of Joensuu , 1998, p. 248-253Conference paper (Other academic)
  • 124.
    Tarasov, Vladimir A.
    et al.
    Karelian State Pedagogical University.
    Tarasov, Vladimir
    Jönköping University, School of Engineering, JTH. Research area Information Engineering. Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    Designing answer selection tests in JavaScript2000In: Proceedings of the Fifth Inter-Karelian Conference on Learning and Teaching Science and Mathematics in Secondary and Higher Education / [ed] K.M. Sormunen, V.A. Tarasov & S.R. Bogdanov, Joensuu: University of Joensuu , 2000, p. 175-179Conference paper (Other academic)
  • 125.
    Tarasov, Vladimir A.
    et al.
    Karelian State Pedagogical University.
    Tarasov, Vladimir
    Jönköping University, School of Engineering, JTH. Research area Information Engineering. Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    Designing tools for testing with open-ended questions using Java technology2003In: Towards Meaningful Mathematics and Science Education: Proceedings of the IXX Symposium of the Finnish Mathematics and Science Education Research Association / [ed] L. Haapasalo & K. Sormunen, Joensuu: University of Joensuu , 2003, p. 91-97Conference paper (Other academic)
    Abstract [en]

    This paper presents an approach to designing computerised assessment tools for testing with open-ended questions. Student answers are analysed by comparing them to the correct ones, which are constructed using keywords that are essential for the meaning of the answers. The developed tools were used within a course at the Karelian State Pedagogical University. Students preferred open-ended questions to multiple-choice questions. Applying Java technologies and component-based approaches, allowed us to create flexible tools that could be used with diverse computer platforms and integrated into a learning environment.

  • 126.
    Tarasov, Vladimir A.
    et al.
    Karelian State Pedagogical University.
    Tarasov, Vladimir
    Jönköping University, School of Engineering, JTH. Research area Information Engineering. Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    Kyurshunov, Alexey
    Karelian State Pedagogical University.
    Using XML and the IMS QTI standard for the development of assessment tools2003In: Proceedings of the Sixth Inter-Karelian Conferene on Mathematics and Science Education in the North-East of Europe: History, Traditions, Contemporary Issues / [ed] K.M. Sormunen, V.A. Tarassov & S.R. Bogdanov, Joensuu: University of Joensuu , 2003, p. 312-317Conference paper (Other academic)
    Abstract [en]

    The paper deals with the issue of using the IMS Question and Test Interoperability standard for the development of assessment tools. This standard is based on XML (eXtensible Markup Language) and intended for description of tests at a structural level independent from the computer platform. According to this standard, questions and tests can be represented as plain text, which is marked-up with XML tags. The testing tool reads a test description in XML and parses it to translate into the format used internally in the system. This approach allows to create test descriptions that are highly interchangeable, readable, and reusable.

  • 127.
    Tarasov, Vladimir
    et al.
    Jönköping University, School of Engineering, JTH. Research area Information Engineering. Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    Albertsen, Thomas
    Jönköping University, School of Engineering, JTH. Research area Information Engineering.
    Kashevnik, Alexey
    Sandkuhl, Kurt
    Jönköping University, School of Engineering, JTH. Research area Information Engineering.
    Shilov, Nikolay
    Smirnov, Alexander
    Ontology-Based Competence Management for Team Configuration2007In: Holonic and Multi-Agent Systems for Manufacturing: third International Conference on Industrial Applications of Holonic and Multi-Agent Systems, HoloMAS 2007, Regensburg, Germany, September 3 - 5, 2007; proceedings, Berlin: Springer , 2007, p. 401-410Conference paper (Refereed)
    Abstract [en]

    When manufacturers, distributors and dealers need to collaborate, they form production networks because this provides significant advantages in production variety, flexibility and lead time. Production processes in such networks often spawn different specific tasks that are to be solved by the network members. This requires creation of a team able to tackle the identified problem. When dealing with multiple organizations and multiple processes within a complicated production network, trying to find a member that has required competence can be a laborious, time-consuming process. Developing and main-taining competence profiles of all the relevant parties associated with produc-tion can significantly reduce the time. The paper proposes an approach to team configuration based on competence profiles. The approach utilizes such tech-nologies as ontology management, context management and profiling. Using ontological representation makes it possible to identify those team members who are best suited for the task by ontology matching.

  • 128.
    Tarasov, Vladimir
    et al.
    Jönköping University, School of Engineering, JTH. Research area Information Engineering. Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    Höglund, Pär J.
    Jönköping University, School of Health and Welfare, The Jönköping Academy for Improvement of Health and Welfare.
    de Roos, Paul
    Jönköping University, School of Health and Welfare, The Jönköping Academy for Improvement of Health and Welfare.
    Ontology-Based eService Enabling Collaboration of Researchers in Healthcare2012In: eChallenges e-2012 Conference Proceedings / [ed] Paul Cunningham and Miriam Cunningham, International Information Management Corporation Limited, 2012Conference paper (Refereed)
    Abstract [en]

    eServices in the area of healthcare are developing quickly. Providing services for researchers in healthcare deals with both complex domain and sophisticated requirements. The objective of this paper is to propose an architecture of an online service to support collaboration of healthcare researchers. The service facilitates the task of seeking collaborators for joint work on producing scientific artefacts. The search of potential collaborators is based on matching the researcher's profile against others' profiles. Profiles are ontology-based and composed of all different scientific-related activities and products of a person. A first prototype of the service was developed in the CLICK project to support researchers in the projects funded by the Vinnvård Programme. The interviews with several users showed appreciation of the usefulness of the tool.

  • 129.
    Tarasov, Vladimir
    et al.
    Jönköping University, School of Engineering, JTH. Research area Information Engineering. Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    Johansson, Bengt-Erik
    Umeå Universitet.
    Active learning models and instructional systems2002In: @ – Learning in Higher Education / [ed] F. Buchberger, S. Berghammer & K. Enser, Linz: Trauner Verlag , 2002Chapter in book (Other academic)
    Abstract [en]

    Contemporary society puts forward need for new learning possibilities, which are provided by distance education methods using networked settings. The success of computer-aided instruction is determined by not only involved computer science methods and information technologies but also by deep research into pedagogical methodology. This paper makes an attempt to establish how modern teaching and learning scenarios can be supported by learning technology standards, systems, and specialized computer tools. To give students good learning experience active learning methods ought to be employed in distance education. First, we will consider several learning methods such as case-based learning, team learning/informative testing, learning by designing, discovery learning, and the Jigsaw method. It will allow for determination of what kind of support is needed for students and teachers. Then, we will discuss different learning technology standards, projects and systems to find out what capabilities they provide for the considered methods. Finally, a learning environment architecture will be presented for supporting active learning. The learning environment architecture includes four layers that contain functionality required for active learning. We will dwell upon the functionality and two implementation examples of the environment – PharmaPaC and SwedKid.

  • 130.
    Tarasov, Vladimir
    et al.
    Jönköping University, School of Engineering, JTH. Research area Information Engineering. Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    Krizhanovsky, Andrew
    St.Petersburg Institute for Informatics and Automation RAS.
    Enrichment of Ontology-Based Competence Profiles with Semistructured Wiktionary Data2011In: Perspectives in Business Informatics Research: Local proc. of 10th Int. Conf., BIR 2011. Associated Workshops and Doctoral Consortium / [ed] Laila Niedrite, Renate Strazdina, Benkt Wangler, Riga Technical University , 2011, p. 46-53Conference paper (Refereed)
    Abstract [en]

    Competence supply methods can contribute to information supply solutions by providing information on available competences and making this information accessible to the decision-makers. When competence profiles are stored in a machine-readable form, competence demand can be translated into a formal query to find matching profiles. However, this requires to use exactly the same skill names as the ones from the profile representations. This paper proposes to enrich ontology-based competence profiles with the help of Wiktionary data accessible via a SPARQL endpoint. The endpoint makes it possible to get lexicographic information (definitions, translations, synonyms) from Wiktionary. The procedure of enrichment with synonyms and system architecture supporting it are developed and tested in an experiment with profiles of software developers. The experiment showed the viability of the approach.

  • 131.
    Tarasov, Vladimir
    et al.
    Jönköping University, School of Engineering, JTH. Research area Information Engineering. Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    Lundqvist, Magnus
    Jönköping University, School of Engineering, JTH. Research area Information Engineering.
    Modeling Collaborative Design Competence with Ontologies2007In: International Journal of e-collaboration, ISSN 1548-3673, E-ISSN 1548-3681, Vol. 3, no 4, p. 46-62Article in journal (Refereed)
    Abstract [en]

    Collaborative design in dispersed groups of engineers creates various kinds of challenges to technology, organization and social environment. This paper presents an approach to description and representation of the competences needed for a planned collaborative design project. The most important competence areas are identified starting from the nature of design work, problem solving in design teams, and working in distributed groups. The competence model is built structuring these areas according to three perspectives: general, cultural, and occupational competences. An ontological representation is proposed to implement the described model for collaborative design competence. Using an ontology language for representation of collaborative design competence models makes it possible to identify those individuals who are best suited for the collaboration by ontology matching. Finally, a software design team consisting of two persons was interviewed and two competence profiles were created using the developed ontological representation of the model. The modeling of the team members has proved that the proposed approach can be applied to modeling competences needed for collaborative design in engineering fields.

  • 132.
    Tarasov, Vladimir
    et al.
    Jönköping University, School of Engineering, JTH. Research area Information Engineering. Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    Paulsson, Fredrik
    Umeå Universitet.
    Development of a standard for representation of cases2004In: @ - Learning in Higher Education II / [ed] F. Buchberger & K. Enser, Linz: Trauner Verlag , 2004, p. 81-97Chapter in book (Other academic)
    Abstract [en]

    The goal of learning technology standardisation is to create systematic ways of describing learning material and scenarios. This paper deals with the issue of development of a standard for representation of cases, which are used in case-based learning. The standard is designed for learning technology systems and viewed from the user's perspective. First, IMS QTI was described as an example of standards. Four sample cases were then analysed: one from the PharmaPaC project, two from the SwedKid project, and one from two courses taught at the Department of Interactive Media and Learning. We have proposed a case structure description comprised of parts of a case item, types of case items, different patterns of a case section, and relationship between a case, case section and case item. The developed structure can be used as a basis for elaboration of an informational model of the case standard that may increase the level of case reusability and cooperation between case creators and users. The cases and implications of standards for the users were discussed at an ELHE workshop. The discussion suggested that standards can be a good starting point for creation of learning objects, and the standard for cases can facilitate their use in instruction. Despite there was an opinion that standards could limit creativity of learning objects creators, we believe that the use of standards is not an option but compulsory when learning objects are used. In future work we will develop XML-based notation for description of cases and consider Resource Description Framework to add semantic capabilities. We will also take into consideration standards like IMS Content Packaging and EML (Educational Modelling Language).

  • 133.
    Tarasov, Vladimir
    et al.
    Jönköping University, School of Engineering, JTH. Research area Information Engineering. Jönköping University, School of Engineering, JTH. Research area Information Engineering. Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    Sandkuhl, Kurt
    Jönköping University, School of Engineering, JTH. Research area Information Engineering. Jönköping University, School of Engineering, JTH. Research area Information Engineering.
    On the Role of Competence Models for Business and IT Alignment in Network Organizations2011In: Business Information Systems Workshops: BIS 2011 International Workshops and BPSC International Conference, Poznań, Poland, June 15-17, 2011. Revised Papers / [ed] Witold Abramowicz, Leszek Maciaszek and Krzysztof Węcel, Springer Berlin/Heidelberg, 2011, Vol. 97, p. 208-219Conference paper (Refereed)
    Abstract [en]

    Customer-motivated changes in network organizations lead to alignment of business and IT-infrastructure. This paper investigates the use of competence models in network organizations for more efficient alignment of IT-infrastructure to changed business demands. The paper shows that a competence model is pertinent in a process of aligning an IT-infrastructure to changed business demands. Then, a way is presented of extracting alignment needs from competence information in enterprise models. Finally, our approach for competence profile management is extended with alignment operations. These operations together with other operations on competence profiles form a lifecycle model for competence profile management. Such operationalization allows for support of aligning network organizations to changing business demands.

  • 134.
    Tarasov, Vladimir
    et al.
    Jönköping University, School of Engineering, JTH. Research area Information Engineering. Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    Sandkuhl, Kurt
    Jönköping University, School of Engineering, JTH. Research area Information Engineering.
    Henoch, Bengt
    Using Ontologies for Representation of Individual and Enterprise Competence Models2006In: Proceedings of the 4th IEEE International Conference on Computer Sciences Research, Innovation and Vision for the Future (RIVF 2006): February 12 - 16, 2006, Ho Chi Minh City, Vietnam, Piscataway, NJ.: IEEE Operations Center , 2006, p. 205-212Conference paper (Refereed)
    Abstract [en]

    Awareness of competence and structured competence representations are important elements in different business scenarios such as a company looking for a partner with expertise in a certain industrial sector or new staff member with particular skills. This paper presents the use of ontologies to formally represent competence models describing individual and enterprise competences. The individual competences model includes the three major parts: general competence, cultural competence, and occupational competence. The enterprise competences model consists of two parts: industrial competence and occupational competence. The competence models are defined with a meta-model, the latter being an ontology language. Particular individuals and enterprises are described with competence profiles, which are instances of the models. During a pilot study, five individual competence profiles and four enterprise competence profiles were built. The approach to competence modeling has proved to be able to capture capabilities of individuals with diverse occupational and educational backgrounds. Furthermore, the competence modeling approach proved to be suitable for enterprise competences in different countries due to use of international standard classifications as a basis of the models.

  • 135.
    Tarasov, Vladimir
    et al.
    Jönköping University, School of Engineering, JTH. Research area Information Engineering. Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    Sandkuhl, Kurt
    Jönköping University, School of Engineering, JTH. Research area Information Engineering.
    Lundqvist, Magnus
    Jönköping University, School of Engineering, JTH. Research area Information Engineering.
    Modeling Collaborative Design Competence with Ontologies2010In: Encyclopedia of E-Business Development and Management in the Global Economy / [ed] In Lee, IGI Global , 2010, p. 942-951Chapter in book (Other academic)
    Abstract [en]

    Collaborative design in dispersed groups of engineers creates various kinds of challenges to technology, organization and social environment. Selected examples are knowledge sharing, coordination support or secure tool integration (Jacucci, Pawlak, & Sandkuhl, 2005). Work presented in this chapter is located in the area of formation of teams for collaborative design. The challenge addressed is how to describe and represent the competences needed for a planned collaborative design project in a way that those individuals best suited for the collaboration can be identified. The proposed approach is to apply ontology engineering to modeling competences of individuals, including different competence areas like cultural competences, professional competences or occupational competences.

  • 136.
    Tarasov, Vladimir
    et al.
    Jönköping University, School of Engineering, JTH. Research area Information Engineering. Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    Sandkuhl, Kurt
    Jönköping University, School of Engineering, JTH. Research area Information Engineering.
    Lundqvist, Magnus
    Jönköping University, School of Engineering, JTH. Research area Information Engineering.
    Ontology-based Competence Model for Collaborative Design2009In: Virtual Team Leadership and Collaborative Engineering Advancements: Contemporary Issues and Implications / [ed] Ned Kock, Hershey: Information Science Reference , 2009, p. 188-202Chapter in book (Other academic)
    Abstract [en]

    Collaborative design in dispersed groups of engineers creates various kinds of challenges to technology, organization and social environment. This paper presents an approach to description and representation of the competences needed for a planned collaborative design project. The most important competence areas are identified starting from the nature of design work, problem solving in design teams, and working in distributed groups. The competence model is built structuring these areas according to three perspectives: general, cultural, and occupational competences. An ontological representation is proposed to implement the described model for collaborative design competence. Using an ontology language for representation of collaborative design competence models makes it possible to identify those individuals who are best suited for the collaboration by ontology matching. Furthermore, a software design team consisting of two persons was interviewed and competence profiles were created using the developed ontological representation. Modeling of the team members has confirmed that the proposed approach can be applied to modeling competences needed for collaborative design in engineering fields.

  • 137.
    Tarasov, Vladimir
    et al.
    Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    Seigerroth, Ulf
    Jönköping University, School of Engineering, JTH, Computer Science and Informatics. Jönköping University, Jönköping International Business School, JIBS, Informatics. Jönköping University, Jönköping International Business School, JIBS, Business Administration.
    Sandkuhl, Kurt
    Jönköping University, School of Engineering, JTH, Computer Science and Informatics.
    Ontology development strategies in industrial contexts2019In: Business Information Systems Workshops. BIS 2018. / [ed] Abramowicz W., Paschke A., Cham: Springer, 2019, Vol. 339, p. 156-167Conference paper (Refereed)
    Abstract [en]

    Knowledge-based systems are used extensively to support functioning of enterprises. Such systems need to reflect the aligned business-IT view and create shared understanding of the domain. Ontologies are used as part of many knowledge-bases systems. The industrial context affects the process of ontology engineering in terms of business requirements and technical constraints. This paper presents a study of four industrial cases that included ontology development. The study resulted in identification of seven factors that were used to compare the industrial cases. The most influential factors were found to be reuse of ontologies/models, stakeholder groups involved, and level of applicability of ontology. Finally, four recommendation were formulated for projects intended to create shared understanding in an enterprise.

  • 138.
    Tarasov, Vladimir
    et al.
    Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    Tan, He
    Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    Adlemo, Anders
    Jönköping University, School of Engineering, JTH, Computer Science and Informatics.
    Automation of software testing process using ontologies2019In: 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 (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.

  • 139.
    Tarasov, Vladimir
    et al.
    Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    Tan, He
    Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    Adlemo, Anders
    Jönköping University, School of Engineering, JTH, Computer Science and Informatics.
    Ismail, Muhammad
    Jönköping University, School of Engineering, JTH, Computer Science and Informatics.
    Mats, Johansson
    Saab AB, Avisonics.
    Olsson, Daniel
    AddQ AB.
    Ontology-based Software Test Case Generation (OSTAG)2015In: 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 (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.

  • 140.
    Tarasov, Vladimir
    et al.
    Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    Tan, He
    Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    Ismail, Muhammad
    Jönköping University, School of Engineering, JTH, Computer Science and Informatics.
    Adlemo, Anders
    Jönköping University, School of Engineering, JTH, Computer Science and Informatics.
    Johansson, Mats
    Saab AB.
    Application of inference rules to a software requirements ontology to generate software test cases2017In: 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.

  • 141.
    Tarasov, Vladimir
    et al.
    Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    Tan, He
    Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    Jarfors, Anders E.W.
    Jönköping University, School of Engineering, JTH, Materials and Manufacturing.
    Seifeddine, Salem
    Jönköping University, School of Engineering, JTH, Materials and Manufacturing.
    Fuzzy logic-based modelling of yield strength of as-cast A356 alloy2019In: Neural computing & applications (Print), ISSN 0941-0643, E-ISSN 1433-3058Article in journal (Refereed)
    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.

  • 142.
    Thill, Serge
    et al.
    Donders Institute for Brain, Cognition, and Behaviour Radboud University , Nijmegen, Netherlands and Interaction Lab, School of Informatics University of Skövde, Skövde, Sweden.
    Riveiro, Maria
    Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    Memento hominibus: on the fundamental role of end users in real-world interactions with neuromorphic systems2019Conference paper (Refereed)
    Abstract [en]

    In this contribution, we briefly examine the role of end users in the evaluation and characterisation of sophisticated AI-based systems, such as autonomous vehicles or near-future robots. Indeed, when trying to ensure the safety of learning, perception and control in real world settings, one aspect that needs consideration is that human end users are often part of such settings. We argue that current approaches for considering end users in this respect are insufficient, not the least from a safety perspective, and that this insufficiency will become more acute when transitioning to neuromorphic and/or strongly cognitively inspired solutions. We demonstrate this by borrowing examples from the field of enactivism, which demonstrate that human end users might change the system dynamics of advanced neuromorphic systems when interacting with them, which needs to be taken into consideration. Enactivism might also provide clues as to how to design future evaluation metrics for human-machine teams.

  • 143.
    Vdovitsyn, Vladimir
    et al.
    Institute of Applied Mathematical Research, KarRC RAS.
    Tarasov, Vladimir
    Jönköping University, School of Engineering, JTH. Research area Information Engineering. Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    Applying KBS-technology to a pulp-and-paper mill control automation1996In: Proceedings of II International Scientific and Technical Conference on New Information Technologies in Pulp and Paper Industry, Petrozavodsk, 1996, p. 33-34Conference paper (Other academic)
  • 144.
    Vdovitsyn, Vladimir
    et al.
    Institute of Applied Mathematical Research, KarRC RAS.
    Tarasov, Vladimir
    Jönköping University, School of Engineering, JTH. Research area Information Engineering. Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    Multi-agent system for informational support of collaborative researchers work in a computer network1999In: Proceedings of Finnish Data Processing Week (FDPW'99) on Developments in Distributed Systems and Data Communications, Vol. 2, Petrozavodsk: Petrozavodsk State University , 1999, p. 139-145Conference paper (Other academic)
    Abstract [en]

    The article considers the model of researchers' interaction when conducting a collaborative project. We also propose a multi-agent system architecture for informational support of the process of collaborative research using Internet technologies.

  • 145.
    Ventocilla, Elio
    et al.
    Department of Computer and Systems Sciences, School of Informatics, University of Sk¨ovde, Sk¨ovde, Sweden.
    Riveiro, Maria
    Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    A model for the progressive visualization of multidimensional data structure2020In: Computer Vision, Imaging and Computer Graphics Theory and Applications: 14th International Joint Conference, VISIGRAPP 2019 Prague, Czech Republic, February 25–27, 2019 Revised Selected Papers / [ed] A. P. Cl´audio et al., Cham: Springer, 2020, p. 203-226Conference paper (Refereed)
    Abstract [en]

    This paper presents a model for the progressive visualization and exploration of the structure of large datasets. That is, an abstraction on different components and relations which provide means for constructing a visual representation of a dataset’s structure, with continuous system feedback and enabled user interactions for computational steering, in spite of size. In this context, the structure of a dataset is regarded as the distance or neighborhood relationships among its data points. Size, on the other hand, is defined in terms of the number of data points. To prove the validity of the model, a proof-of-concept was developed as a Visual Analytics library for Apache Zeppelin and Apache Spark. Moreover, nine user studies where carried in order to assess the usability of the library. The results from the user studies show that the library is useful for visualizing and understanding the emerging cluster patterns, for identifying relevant features, and for estimating the number of clusters k.

  • 146.
    Westphal, Florian
    et al.
    Blekinge Tekniska Högskola, Institutionen för datalogi och datorsystemteknik.
    Grahn, Håkan
    Blekinge Tekniska Högskola, Institutionen för datalogi och datorsystemteknik.
    Lavesson, Niklas
    Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL). Blekinge Tekniska Högskola, Institutionen för datalogi och datorsystemteknik.
    Efficient document image binarization using heterogeneous computing and parameter tuning2018In: International Journal on Document Analysis and Recognition, ISSN 1433-2833, E-ISSN 1433-2825, Vol. 21, no 1-2, p. 41-58Article in journal (Refereed)
    Abstract [en]

    In the context of historical document analysis, image binarization is a first important step, which separates foreground from background, despite common image degradations, such as faded ink, stains, or bleed-through. Fast binarization has great significance when analyzing vast archives of document images, since even small inefficiencies can quickly accumulate to years of wasted execution time. Therefore, efficient binarization is especially relevant to companies and government institutions, who want to analyze their large collections of document images. The main challenge with this is to speed up the execution performance without affecting the binarization performance. We modify a state-of-the-art binarization algorithm and achieve on average a 3.5 times faster execution performance by correctly mapping this algorithm to a heterogeneous platform, consisting of a CPU and a GPU. Our proposed parameter tuning algorithm additionally improves the execution time for parameter tuning by a factor of 1.7, compared to previous parameter tuning algorithms. We see that for the chosen algorithm, machine learning-based parameter tuning improves the execution performance more than heterogeneous computing, when comparing absolute execution times. © 2018 The Author(s)

  • 147.
    Westphal, Florian
    et al.
    Blekinge Tekniska Högskola, Institutionen för datalogi och datorsystemteknik.
    Grahn, Håkan
    Blekinge Tekniska Högskola, Institutionen för datalogi och datorsystemteknik.
    Lavesson, Niklas
    Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL). Blekinge Tekniska Högskola, Institutionen för datalogi och datorsystemteknik.
    User Feedback and Uncertainty in User Guided Binarization2018In: International Conference on Data Mining Workshops / [ed] H. Tong, Z. Li, F. Zhu, & J. Yu, IEEE Computer Society, 2018, p. 403-410, article id 8637367Conference paper (Refereed)
    Abstract [en]

    In a child’s development, the child’s inherent ability to construct knowledge from new information is as important as explicit instructional guidance. Similarly, mechanisms to produce suitable learning representations, which can be trans- ferred and allow integration of new information are important for artificial learning systems. However, equally important are modes of instructional guidance, which allow the system to learn efficiently. Thus, the challenge for efficient learning is to identify suitable guidance strategies together with suitable learning mechanisms.

    In this paper, we propose guided machine learning as source for suitable guidance strategies, we distinguish be- tween sample selection based and privileged information based strategies and evaluate three sample selection based strategies on a simple transfer learning task. The evaluated strategies are random sample selection, i.e., supervised learning, user based sample selection based on readability, and user based sample selection based on readability and uncertainty. We show that sampling based on readability and uncertainty tends to produce better learning results than the other two strategies. Furthermore, we evaluate the use of the learner’s uncertainty for self directed learning and find that effects similar to the Dunning-Kruger effect prevent this use case. The learning task in this study is document image binarization, i.e., the separation of text foreground from page background and the source domain of the transfer are texts written on paper in Latin characters, while the target domain are texts written on palm leaves in Balinese script.

  • 148.
    Westphal, Florian
    et al.
    Blekinge Institute of Technology, Karlskrona, Sweden.
    Lavesson, Niklas
    Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL). Blekinge Institute of Technology, Karlskrona, Sweden.
    Grahn, Håkan
    Blekinge Institute of Technology, Karlskrona, Sweden.
    A case for guided machine learning2019In: Machine learning and knowledge extraction: Third IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2019, Canterbury, UK, August 26–29, 2019, Proceedings / [ed] A. Holzinger, P. Kieseberg, A. M. Tjoa & E. Weippl, Cham: Springer, 2019, p. 353-361Conference paper (Refereed)
    Abstract [en]

    Involving humans in the learning process of a machine learning algorithm can have many advantages ranging from establishing trust into a particular model to added personalization capabilities to reducing labeling efforts. While these approaches are commonly summarized under the term interactive machine learning (iML), no unambiguous definition of iML exists to clearly define this area of research. In this position paper, we discuss the shortcomings of current definitions of iML and propose and define the term guided machine learning (gML) as an alternative.

  • 149.
    Westphal, Florian
    et al.
    Blekinge Tekniska Högskola, Institutionen för datalogi och datorsystemteknik.
    Lavesson, Niklas
    Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL). Blekinge Tekniska Högskola, Institutionen för datalogi och datorsystemteknik.
    Grahn, Håkan
    Blekinge Tekniska Högskola, Institutionen för datalogi och datorsystemteknik.
    Document Image Binarization Using Recurrent Neural Networks2018In: Proceedings - 13th IAPR International Workshop on Document Analysis Systems, DAS 2018, 2018, p. 263-268Conference paper (Refereed)
    Abstract [en]

    In the context of document image analysis, image binarization is an important preprocessing step for other document analysis algorithms, but also relevant on its own by improving the readability of images of historical documents. While historical document image binarization is challenging due to common image degradations, such as bleedthrough, faded ink or stains, achieving good binarization performance in a timely manner is a worthwhile goal to facilitate efficient information extraction from historical documents. In this paper, we propose a recurrent neural network based algorithm using Grid Long Short-Term Memory cells for image binarization, as well as a pseudo F-Measure based weighted loss function. We evaluate the binarization and execution performance of our algorithm for different choices of footprint size, scale factor and loss function. Our experiments show a significant trade-off between binarization time and quality for different footprint sizes. However, we see no statistically significant difference when using different scale factors and only limited differences for different loss functions. Lastly, we compare the binarization performance of our approach with the best performing algorithm in the 2016 handwritten document image binarization contest and show that both algorithms perform equally well.

  • 150.
    Westphal, Florian
    et al.
    Department of Computer Science, Blekinge Institute of Technology, Karlskrona, Sweden.
    Lavesson, Niklas
    Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL).
    Grahn, Håkan
    Department of Computer Science, Blekinge Institute of Technology, Karlskrona, Sweden.
    Learning character recognition with graph-based privileged information2019In: Proceedings of the International Conference on Document Analysis and Recognition, ICDAR, IEEE, 2019, p. 1163-1168Conference paper (Refereed)
    Abstract [en]

    This paper proposes a pre-training method for neural network-based character recognizers to reduce the required amount of training data, and thus the human labeling effort. The proposed method transfers knowledge about the similarities between graph representations of characters to the recognizer by training to predict the graph edit distance. We show that convolutional neural networks trained with this method outperform traditional supervised learning if only ten or less labeled images per class are available. Furthermore, we show that our approach performs up to 33% better than a graph edit distance based recognition approach, even if only one labeled image per class is available. 

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