Abstract. The existing ontology alignment methods have been trying to automatically obtain semantic correspondences between ontologies. However, they assume that all elements of source ontologies are written by identical languages. In this paper, we have introduced a theoretical idea for building indirect alignment between multilingual ontologies. Thereby, a novel architecture to reuse and compose alignments between ontologies has been designed. For a simple case study, we have collected two multilingual ontologies written by Korean and Swedish languages.

Cyber-physical systems are often developed with an emphasis on the network of computational elements and the linkage between the computational and physical elements. The physical elements are different kinds of Internet of Things devices that carry out desirable and valid tasks from instructions. However, due to the limitations of current individual-based secure products and delivery of services, the requisites of these products and services have started to increase and, hence, the requirements for intelligent automated, networked and mobile devices arise. The current state of communication between the elements in Internet of Things is data exchange and needs step up to next level to improve the interaction with the surrounding devices to augmenting human capabilities. This paper presents an infrastructure for individualised intelligent decision-making and negotiation in cyberphysical systems with smart Internet of Things devices. The decision-making and negotiation is based on individual preferences to provide the best individual-based solutions. The solution is applied to health care, which will permeate throughout the paper.

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As software has become an integral part of most systems, so too have cyber threats become an expected attack vector. This has made the task of reverse engineering software an increasingly necessary and critical skill. Software systems are regarded as the most complex of human designed technologies. Software can be difficult to understand when the source code is provided, but a reverse engineer is restricted to machine code and often intentionally obscured machine code. This makes reverse engineering an extreme technical challenge. This work examines the reverse engineer's cognitive task as abductive reasoning. Abductive reasoning has received significant theoretical attention in the last decade resulting in a broader account of abduction types and methods. Abduction, as the only generative means of inference is essential to hard diagnostic tasks and scientific exploration that require non-deductive and non-inductive hypothesis generation. In particular, we explore manipulative abduction and meta-diagrammatic abduction employed by a reverse engineer to counter falsification of a hypotheses and surprise. With this basis, we are studying the work of reverse engineering with the dual goals of understanding the task and looking at ways AI systems can be constructed to augment reverse engineering. Process philosophy principles of panexperientialism and consciousness are used to form a critique of current AI approaches and some tenants of a novel abductive AI framework are justified.