International Scientific Journals
of Scientific Technical Union of Mechanical Engineering "Industry 4.0"

Cyber-physical systems (CPS) are the core of the Fourth industrial revolution and the Industry 4.0 initiative. They are facing many challenges, addressing them requires attracting and using new methods and techniques from the field of artificial intelligence and big data to make intelligent decisions and perform effective data analysis. Тhe paper presents an analyze of the current trends and challenges in the development of cyber-physical systems and the ever-increasing interest in the methods and approaches of artificial intelligence and its application in the life cycle phases of design, analysis, implementation and maintenance of CPS. There are two aspects that are the focus of attention and analysis: (1) the computing by intelligence and (2) the computing for intelligence. Finally some ideas for using different methods and approaches of artificial intelligence for achieving interoperability and autonomy of CPS are proposed.

In this paper are presented some conclusions on the selection of the LMS to be used. The results of this study give readers information to make their own decisions when choosing an LMS platform based on the needs of their institution. The process of LMS selection is a multi-criteria decision-making problem and an Analytical Hierarchy Process (AHP) was used to assist in building the model and draw decisions. The paper presents an environment ”Network technologies for e-learning”(NTEL) using the offered Model for describing, structuring, and organizing the ontological representation of learning objects through providing a semantic infrastructure. Strategies and methodologies in ontology development and implementation are also discussed.

In order to achieve its goal in using intelligent adaptive and predictive technical systems with self-X functions and cognitive information processing in continuous interaction with environment, the Industry 4.0 initiative implies integration of Cyber-Physical Systems (CPS), the Internet of Things (IoT) and cloud computing leading to what is called "smart factory". This, in turn, faces the CPS with new challenges in terms of increasing the degree of distribution, autonomy, mobility, communication and security of the systems and their components, as well as expanding their functionality in the direction of data analytics, information and knowledge extraction, and increasing their intelligence. This paper discusses and analyses the CPS in the context of Industry 4.0 and the main trends in the development of process automation and control in order to suggest an appropriate and advanced agent based approach for development of CPS for process control. The proposed approach is based on using the following standards – from one side the IEC61499 Standard for agent specification and from other side the IEC62264 and IEC 61512 Standards for defining the different kind of agents in the control system. The presented approaches are illustrated with a partly presented example of development of Injector control system. Finally some conclusions are made.

Enterprise interoperability is the ability of disparate and diverse information and control systems to work together efficiently towards mutually beneficial common goals. Some of the main tasks for achieving enterprise interoperability are connected with data and knowledge access and sharing and by use of model transformation. In this paper are presented and discussed several model transformations between different Technological Spaces: RDB, UML and OWL in order to enable ontology-based access to different models of enterprise data. At the core of the approach is the usage of reference models, based on the standard for enterprise integration ISO/IEC 62264.

The present paper illustrates the current state of affairs for most organizations involved in the sphere of Information technologies that run or strive to run projects in accordance with applicable ISO standards and CMMI. This paper presents the target state of affairs and its design with used technologies. Reaching the goal state is summarized by serialization of metamodels in XML, mapping/parsing of metamodels (in XML) to OWL2 DL (RL profile) ontologies (written/exchangeable in RDF/XML), storages of these semantic metamodels and models (ontologies/semantic data) in advanced RDBMSs with support of ontologies, R2RML mapping of existing project-related relational data to semantic data and storage of semantic data in semantic stores hosted in existing RDBMSs or migration to such ones, extraction of non-relational project-related data and mapping of these logical models to a physical (relational) model and integration in RDBMSs to centralize all project-related data all governed by the defined vocabularies (ontologies of CMMI for Development and ISO 15504/ 12207). Achieving the goal state enables stakeholders to query and infer from project-related semantic data to manage, analyze and assess projects against underlaying standards. Through commonly-accepted adapters, semantic data, metamodels and models are exposed to external applications.

One of the main problems of biomedical informatics in the effort to increase its contribution in knowledge retrieval and decision making is the integration of ever-increasing amounts of information and data from multiple heterogeneous sources and domains – clinical, medical, biological etc. The paper proposes an ontology based approach for integration of biomedical data and information using the Linked Open Data vocabularies and a D2RQ-mapped database. A simple example of semantic integration of heterogeneous biomedical and health data sources is given.