Critical (Cyber) Computing:

Challenges and Cases for Industry and Human Domains

Prof. Vyacheslav Kharchenko

National Aerospace University “KhAI” (Kharkiv, Ukraine).

Challenges in area of safety and security critical systems application are discussed. Fundamentals of critical computing are observed considering development and implementation of software, FPGA and other (web, cloud, IoT) technologies for industry (nuclear power stations, aerospace, automotive systems, etc) human (health systems, smart building, etc) domains. Methods, techniques and tools to assess reliability, availability and safety of such systems are analysed. Aspects of cyber safety and cyber security are discussed as well. One of the techniques applied for safety assessment (verification and validation, V&V) of software and FPGA-based systems is (X,Z)-injection testing IT (X is type of faults and vulnerabilities, Z is component of systems). Fault injection testing (X is physical/design fault, Z is hardware/software component) is used as a tool-based technique during independent V&V in safety important NPP Instrumentation and Control systems (I&Cs). This technique is a mandatory to certify platforms and I&Cs against requirements of the standard IEC 61508 “Functional Safety of Electrical/Electronic/Programmable Electronic Safety-related Systems” according with safety integrity level (SIL). FIT is based on design fault injection into the code (VHDL code for FPGA, C code for embedded software, web components, etc), physical faults into programmable chips and HW modules to assess test coverage and fault-tolerance for redundant systems. VIT (vulnerability injection testing) is applied to assess intrusion-tolerance and (cyber) security. Experience of development and implementation of injection-based techniques for NPP I&C is discussed. The developed technique and tool have been applied to verify modules of FPGA-based platform RadICS (RPC Radiy, Kirovograd, Ukraine) during SIL3 certification. To assure safety and security diversity approach is applied. This approach is analysed in point of view regulation, assessment and assuring aspects. Industry/commercial application of multi-version systems is discussed. Diversity related requirements of standards for nuclear and automotive systems are compared. Techniques of diversity metric calculation and decision making for version redundancy selection are analysed.

Designing High-Reliability Health Care

Paul Barach, MD, MPH, Maj(ret.)

Wayne State University School of Medicine, Detroit, United States

Dr. Barach is a physician executive, board-certified in Anesthesia and Critical Care, leads initiatives across clinical departments and support services, spearheading multiple projects and achieving physician alignment with strategic initiatives. He has statistical, quantitative and qualitative expertise, with focus upon measurable impact and revenue optimization. Dr Barach advises and consults to academic medical centers and hospitals on the science of clinical practice improvement; evaluation of practice transformation in diverse settings, and enjoys promoting the implementation of evidence for practice improvement. Further details can be found at: https://www.linkedin.com/in/paulbarach

Formal ontology in scientific information systems.
The case of agri-food sciences

Prof. Piotr Kulicki

The John Paul II Catholic University of Lublin, Poland

In the context of Knowledge Representation an ontology is understood as a formal specification of shared conceptualisation. Ontologies are useful in all situations in which information is to be shared, especially on a large scale, like via the Internet treated as a semantic web. One of the natural areas in which information is to be widely spread is science in which research results are shared among academics and with the wide public. In the lecture ontology of scientific laws will be presented as a tool for the representation of the results extracted from research articles. The way we represent scientific laws is founded on our classification of scientific laws, which is based on the works of K. Ajdukiewicz and W. Krajewski. The classification is described formally and complemented by the specification of requirements for each type of laws in order to obtain a fully fledged ontology. The ontology is used to represent research results from the domain of agri-food science. Examples of the representation of laws taken from scientific papers will be presented along with reasoning algorithms that lead to an automatic generation of new information and identification of research problems in the literature.