Knowledge Based Models and Software Tools for Learning Management in Open Learning Network

Anikin, Anton; Kultsova, Marina; Zhukova, Irina; Sadovnikova, Natalia; Litovkin, Dmitry

doi:10.1007/978-3-319-11854-3_15

Cited by 9 publications

(4 citation statements)

References 5 publications

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“…In their previous works [3,4,5] the authors proposed an ontology-based concept of new learning content creation in open learning network on the base of learning resources retrieval and integration in personal learning collections. The personal learning collection was defined as a set of the learning resources retrieved according to the learner profile, learner's current and outcome competencies and other personal preferences, and set of relations between the resources which define the learning sequence to achieve the learning objectives.…”

Section: Ontology-based Approach To Learning Content Managementmentioning

confidence: 99%

“…5: 1 -author knowledge about the learning course, learning resources and learner; 2,3 -specific learning course ontology (in OWL); 4,5 -learning course ontologies created or modified by the tutor; 6,7 -learning resources annotations created or modified by the tutor; 8 -RacerPro request for the learning resources annotations; 9 -learning resources annotations (in OWL); 10 -RacerPro request for specific learning course ontology; 11 -specific The software tool for creating the personal learning collections Collection Builder [5] was designed and implemented within framework of proposed knowledgebased approach with employment of the object-oriented analysis and C# language (Fig. 6, 7).…”

Section: Software Architecture: Implementation Aspectsmentioning

confidence: 99%

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Ontology-Based Learning Content Management System in Programming Languages Domain

Kultsova

Anikin

Zhukova

et al. 2015

Communications in Computer and Information Science

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Abstract. This paper presents an ontology-based learning content management system to create the personal collections of learning resources. To manage the learning process the set of ontologies (ontologies of learning course domain, electronic learning resources, learner's profile and personal collections) is elaborated as well as the two-stage method and algorithms for retrieval and integration of distributed learning resources into personal collections. In the framework of considered ontology-based approach the software architecture and web application for creating the personal collections of learning resources have been developed. Developed system was applied for creation of personal collections for the course "Programming Languages. C++" in Volgograd State Technical University.

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Section: Ontology-based Approach To Learning Content Managementmentioning

confidence: 99%

Section: Software Architecture: Implementation Aspectsmentioning

confidence: 99%

Ontology-Based Learning Content Management System in Programming Languages Domain

Kultsova

Anikin

Zhukova

et al. 2015

Communications in Computer and Information Science

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“…Differential equations are used to specify the physical processes that have an influence on the health condition of related components [12]. Knowledge‐based models : knowledge‐based models are created by domain experts, although there are no mathematical models to cover their physical behaviour [13]. Data‐driven models : these types of models are based on statistical and learning techniques.…”

Section: Introductionmentioning

confidence: 99%

“…Knowledge‐based models : knowledge‐based models are created by domain experts, although there are no mathematical models to cover their physical behaviour [13].…”

Section: Introductionmentioning

confidence: 99%

Classification model for predictive maintenance of small steam sterilisers

Musabayli¹,

Osman

Dirix³

2020

IET Collaborative Intelligent Manufacturing

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With 35,000 small steam sterilisers in the German market, after‐sales service and maintenance are critical issues for manufacturers and distributors. At present, preventive maintenance is one of the most commonly‐implemented maintenance strategies. However, with an average failure probability of 10%, ∼3500 autoclaves require unplanned repair per year, causing customers’ business interruptions and increased maintenance costs. From the authors’ observation, a predictive failure detection mechanism is needed to prevent failures and reduce the significant safety risk. Hence, this study proposes a predictive maintenance mechanism for small steam sterilisers. The predictive maintenance mechanism is constructed from classification models that categorised the health condition of two critical components in small steam sterilisers, i.e. a vacuum pump and a steam generator. The classification models were built from multisensory data, obtained from 1000 protocol records of CertoClav Vacuum Pro steam sterilisers. They perform exploratory experiments to find a suitable classification model. This study found that the random forest algorithm performed best in terms of accuracy for both the vacuum pump and steam generator data sets (83.5 and 82.0%, respectively). They also found that the features related to the pre‐vacuum stage profoundly influence the condition of the vacuum pump and the steam generator.

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Modern Approaches for Concepts and Relations Extraction for Ontology Learning

Katyshev

Anikin

2022

Novel &Amp; Intelligent Digital Systems: Proceedings of the 2nd International Conference (NiDS 2022)

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Knowledge Based Models and Software Tools for Learning Management in Open Learning Network

Cited by 9 publications

References 5 publications

Ontology-Based Learning Content Management System in Programming Languages Domain

Ontology-Based Learning Content Management System in Programming Languages Domain

Classification model for predictive maintenance of small steam sterilisers

Modern Approaches for Concepts and Relations Extraction for Ontology Learning

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