Marina Kultsova

@INPROCEEDINGS{8316440, 
author={M. Kultsova and D. Matyushechkin and A. Usov and S. Karpova and R. Romanenko}, 
booktitle={2017 8th International Conference on Information, Intelligence, Systems Applications (IISA)}, 
title={Generation of pictograph sequences from the Russian text in the assistive mobile application for people with intellectual and developmental disabilities}, 
year={2017}, 
volume={}, 
number={}, 
pages={1-4}, 
abstract={This paper is devoted to a problem of correct translation of text in Russian to the sequence of pictograms for the mobile application “Travel and Communication Assistant” which supports the mobility and communication of people with intellectual and developmental disabilities. This application provides the possibility to such people to independently perform a known route (for example a route from home to the day care center, from home to the bakery, etc.) under the remote supervision of their caregivers and to communicate with them using text, voice and pictogram messages. A scheme of the process of translating a text in Russian into a sequence of pictograms was proposed and implemented as an extension of web service “Text2Picto” to the Russian language.}, 
keywords={handicapped aids;mobile computing;text analysis;Web services;pictograph sequences;Russian text;assistive mobile application;intellectual disabilities;developmental disabilities;Communication Assistant;mobility;pictogram messages;Text2Picto;Russian language;Databases;Speech;Mobile applications;Electronic mail;Web services;Natural languages;Color}, 
doi={10.1109/IISA.2017.8316440}, 
ISSN={}, 
month={Aug},}

@INPROCEEDINGS{8316444, 
author={M. Kultsova and D. Matyushechkin and A. Usov and S. Karpova and A. Petrenko}, 
booktitle={2017 8th International Conference on Information, Intelligence, Systems Applications (IISA)}, 
title={Assistive technology for complex support of children rehabilitation with autism spectrum disorder}, 
year={2017}, 
volume={}, 
number={}, 
pages={1-5}, 
abstract={This paper is devoted to a problem of complex computer support of children rehabilitation with autism spectrum disorder. This goal is achieved due to the development of computer assistive technology which includes web system for online diagnostics, a mobile application for support of communications using PECS and interactive visual timetable. The proposed assistive technology was design and implemented in accordance with the requirements of specialists from Regional rehabilitation center for children with disabilities “Nadezhda” in Volzhsky city (Russia). At present, the developed web services and mobile applications are tested and evaluated in the rehabilitation center.}, 
keywords={handicapped aids;Internet;medical disorders;mobile computing;patient rehabilitation;Web services;autism spectrum disorder;computer assistive technology;web system;online diagnostics;mobile application;interactive visual timetable;Regional rehabilitation center;complex support;children rehabilitation;complex computer support;Nadezhda;Volzhsky city;web services;mobile applications;Autism;Electronic mail;Visualization;Assistive technology;Mobile applications;Monitoring;Servers}, 
doi={10.1109/IISA.2017.8316444}, 
ISSN={}, 
month={Aug},}

@INPROCEEDINGS{8316445, 
author={S. Regmi and B. K. Bal and M. Kultsova}, 
booktitle={2017 8th International Conference on Information, Intelligence, Systems Applications (IISA)}, 
title={Analyzing facts and opinions in Nepali subjective texts}, 
year={2017}, 
volume={}, 
number={}, 
pages={1-4}, 
abstract={Subjectivity Analysis is a relatively new field of research for the Nepali language. It offers a challenging area which has not been adequately studied till date systematically. Limited works that have been conducted in Nepali include works primarily on polarity detection [7]. In this work, we propose a Supervised Machine Learning based framework for analyzing facts and opinions for Nepali subjective texts. We train three different models using three Supervised Machine Learning Classifiers: (Logistic Regression, Multinomial Naïve Bayes, and Support Vector Machine) and conduct a comparative study based on the metrics: Accuracy, Precision, Recall and F-Measure. Our results show that the task of analyzing subjective sentences and making a distinction between facts and opinions can be conducted with reasonable accuracies close to 70%.}, 
keywords={Bayes methods;learning (artificial intelligence);natural language processing;pattern classification;regression analysis;support vector machines;text analysis;Nepali subjective texts;Supervised Machine Learning Classifiers;Multinomial Naïve Bayes;Support Vector Machine;Subjectivity Analysis;Nepali language;opinion analysis;fact analysis;polarity detection;logistic regression;F-measure;subjective sentence analysis;Support vector machines;Machine learning algorithms;Feature extraction;Sentiment analysis;Logistics;Labeling;Computational modeling;Fact;Opinion;Subjectivity Classification;Machine Learning;TF-IDF;Logistic Regression;Multinomial Naïve Bayes;Support Vector Machine}, 
doi={10.1109/IISA.2017.8316445}, 
ISSN={}, 
month={Aug},}

@ARTICLE{Kultsova2017331,
author={Kultsova, M. and Litovkin, D. and Zhukova, I. and Dvoryankin, A.},
title={Intelligent support of decision making in management of large-scale systems using case-based, rule-based and qualitative reasoning over ontologies},
journal={Communications in Computer and Information Science},
year={2017},
volume={754},
pages={331-349},
doi={10.1007/978-3-319-65551-2_24},
note={cited By 0},
url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-85029418378&doi=10.1007%2f978-3-319-65551-2_24&partnerID=40&md5=6fa75ba7fa4e36ec9cda99997702f9eb},
affiliation={Volgograd State Technical University, Volgograd, Russian Federation},
abstract={The current trend in intelligent support of decision making is an integration of different knowledge representation models and reasoning mechanisms, it allows improving quality and efficiency of obtained decisions. In this paper, we present an ontology-based approach to intelligent support of decision making in the management of large-scale systems using case-based, rule-based and qualitative reasoning. A concept of the reasoning mechanisms integration implies that case-based reasoning (CBR) takes on the role of leading reasoning mechanism, while rule-based (RBR) and qualitative reasoning (QR) support the different phases of CBR-cycle - adaptation and revision phases respectively. The paper describes a modified CBR-cycle and ontological knowledge representation model which supports the proposed concept of reasoning integration. A formal qualitative model of decision making was developed for revision of case solution, it includes the following components: system state model, action model, and assessment model. An ontological representation of the qualitative model was proposed for integration with structural case model in an ontological knowledge base. Implementation of the proposed approach is illustrated by a number of examples of decision making support in various subject domains. © Springer International Publishing AG 2017.},
author_keywords={Intelligent support of decision making;  Knowledge intensive case based reasoning;  Ontological case representation;  Qualitative model},
keywords={Artificial intelligence;  Case based reasoning;  Integration;  Knowledge based systems;  Knowledge representation;  Large scale systems;  Ontology, Case representation;  Casebased reasonings (CBR);  Decision making support;  Intelligent support;  Ontological representation;  Qualitative model;  Qualitative reasoning;  Reasoning mechanism, Decision making},
correspondence_address1={Kultsova, M.; Volgograd State Technical UniversityRussian Federation; эл. почта: marina.kultsova@mail.ru},
editor={Groumpos P., Kravets A., Shcherbakov M., Kultsova M.},
publisher={Springer Verlag},
issn={18650929},
isbn={9783319655505},
language={English},
abbrev_source_title={Commun. Comput. Info. Sci.},
document_type={Conference Paper},
source={Scopus},
}

@ARTICLE{Kultsova2017805,
author={Kultsova, M. and Potseluico, A. and Zhukova, I. and Skorikov, A. and Romanenko, R.},
title={A two-phase method of user interface adaptation for people with special needs},
journal={Communications in Computer and Information Science},
year={2017},
volume={754},
pages={805-821},
doi={10.1007/978-3-319-65551-2_58},
note={cited By 0},
url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-85029459724&doi=10.1007%2f978-3-319-65551-2_58&partnerID=40&md5=64685c530e95317bf3a4db61519e1f7a},
affiliation={Volgograd State Technical University, Volgograd, Russian Federation},
abstract={The paper is devoted to a problem of increasing accessibility of mobile applications for people with disabilities, that requires the creation of specialized adaptive user interfaces. A knowledge-intensive approach to the design of adaptive user interface was proposed on the basis of integration of ontological user modeling and design pattern approach. An ontological model of the adaptive user interface and interface pattern model were developed as well as an ontological knowledge base and pattern database. A two-phase method of user interface adaptation for people with special needs based on the ontological user model, rule-based reasoning over ontology and interface design patterns was developed. The method was implemented in a software tool for user interface developers. The application of the proposed approach is illustrated by a number of examples of user interface design and adaptation for people with special needs. © Springer International Publishing AG 2017.},
author_keywords={Adaptive user interface;  Assistive technologies;  Interface patterns;  Mobile applications;  Ontological user modeling},
keywords={Knowledge based systems;  Mobile computing;  Mobile telecommunication systems;  Ontology;  Phase interfaces, Adaptive user interface;  Assistive technology;  Interface patterns;  Mobile applications;  User Modeling, User interfaces},
correspondence_address1={Kultsova, M.; Volgograd State Technical UniversityRussian Federation; эл. почта: marina.kultsova@mail.ru},
editor={Groumpos P., Kravets A., Shcherbakov M., Kultsova M.},
publisher={Springer Verlag},
issn={18650929},
isbn={9783319655505},
language={English},
abbrev_source_title={Commun. Comput. Info. Sci.},
document_type={Conference Paper},
source={Scopus},
}

@ARTICLE{Anikin2017133,
author={Anikin, A. and Litovkin, D. and Kultsova, M. and Sarkisova, E. and Petrova, T.},
title={Ontology visualization: Approaches and software tools for visual representation of large ontologies in learning},
journal={Communications in Computer and Information Science},
year={2017},
volume={754},
pages={133-149},
doi={10.1007/978-3-319-65551-2_10},
note={cited By 0; Конференция 2nd Conference on Creativity in Intelligent Technologies and Data Science, CIT and DS 2017 ; Дата конференции: с 12 September 2017 по 14 September 2017;  Код конференции:197189},
url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-85029446521&doi=10.1007%2f978-3-319-65551-2_10&partnerID=40&md5=afe223b4bf23023f708f73a0259ee0ae},
affiliation={Volgograd State Technical University, Volgograd, Russian Federation; Volgograd State Socio-Pedagogical University, Volgograd, Russian Federation},
abstract={In this paper, we address the issue of large ontologies visualization for learning. The ontologies can be used to improve the efficiency of the learning when the learner explores a new subject domain and needs its conceptual model. The ontologies can help to overview this new subject domain, to better understand current knowledge, the knowledge that should be got, the subject domain structure, main concepts, relationships between them and relevant information resources. However with increasing the complexity of domain structure, the number of concepts and relationships, it becomes more difficult to overview and understand conceptual model represented with the ontology. We review the approaches to ontology visualization and their implementation in the software tools that can help to resolve this issue. © Springer International Publishing AG 2017.},
author_keywords={Ontology;  Ontology visualization;  Semantic web},
keywords={Computer software;  Semantic Web;  Visualization, Conceptual model;  Domain structure;  Information resource;  Ontology visualizations;  Visual representations, Ontology},
correspondence_address1={Kultsova, M.; Volgograd State Technical UniversityRussian Federation; эл. почта: marina.kultsova@mail.ru},
editor={Groumpos P., Kravets A., Shcherbakov M., Kultsova M.},
sponsors={},
publisher={Springer Verlag},
issn={18650929},
isbn={9783319655505},
language={English},
abbrev_source_title={Commun. Comput. Info. Sci.},
document_type={Conference Paper},
source={Scopus},
}

@Article{Wriggers2008,
author="Wriggers, Peter
and Siplivaya, Marina
and Joukova, Irina
and Slivin, Roman",
title="Intelligent support of the preprocessing stage of engineering analysis using case-based reasoning",
journal="Engineering with Computers",
year="2008",
volume="24",
number="4",
pages="383--404",
abstract="The process of engineering analysis, especially its preprocessing stage, comprises some knowledge-based tasks which influence the quality of the results greatly, require considerable level of expertise from an engineer; the support for these tasks by the contemporary CAE systems is limited. Analysis of the knowledge and reasoning involved in solving these tasks shows that the appropriate support for them by an automated system can be implemented using case-based reasoning (CBR) technology. In this paper the automated knowledge-based system for intelligent support of the preprocessing stage of engineering analysis in the contact mechanics domain is presented which employs the CBR mechanism. The case representation model is proposed which is centered on the structured qualitative model of a technical object. The model is formally represented by the Ontology Web Language Description Logics (OWL DL) ontology. Case retrieval and adaptation algorithms for this model are described which according to the initial tests perform better in the chosen domain then the known prototypes. The automated system is described and a sample problem-solving scenario from the contact mechanics domain is presented. Use of such system can potentially lower costs of engineering analysis by reducing the number of inappropriate decisions and analysis iterations and facilitate knowledge transfer from research into industry.",
issn="1435-5663",
doi="10.1007/s00366-007-0079-5",
url="http://dx.doi.org/10.1007/s00366-007-0079-5"
}