The distribution of Si content in tensile deformed ductile cast iron has been characterized using electron microscopy and correlated to the strain distribution determined based on 3D tomography data collected before and after tensile deformation and digital volume correlation analysis. The results show that the high plastic strain regions localize in bands consisting of large graphite nodules and deformed matrix with high Si content connecting the graphite nodules in the first-to-solidify regions. The bands are aligned about 45 with respect to the loading direction, which is close to the maximum shear direction. 

The Internet of Things (IoT) aims at linking smart objects that are relevantto the user and embedding intelligence into the environment. It is more and moreaccepted in the scientific community and expected by end users, that pervasive servicesshould be able to adapt to the circumstances or situation in which a computingtask takes place, and maybe even detect all relevant parameters for this purpose. Workpresented in this paper addresses the challenge of bringing together concepts and experiencesfrom two different areas: context modeling and ontology matching. Currentwork in the field of automatic ontology matching does not sufficiently take into accountthe context of the user during the matching process. The main contributions of thispaper are (1) the introduction of the concept of “context” in the ontology matchingprocess, (2) an approach for context-based semantic matching, which is building on different(weighted) levels of overlap for a better ranking of alignment elements dependingon user’s context, (3) an evaluation of the context-based matching in experiments andfrom user’s perspectives.

Cyber-Physics System (CPS) is a relatively new term assuming tight integration of physical systems andcyber (IT) systems interacting in real time. Such systems aim at providing a flexible and extensibleinfrastructure supporting a variety of inputs (e.g. sensor-based and customer needs) and outputs(actuators or indicators/displays). CPSs rely on communication, computation and control infrastructuresto provide for efficient utilization of logistics infrastructure resources. In this context, Logistics-as-a-Service (LaaS) is a logistics network of organizations, people, information and resources supported byservice-oriented cyber-physical systems. Intelligent multimodal logistics network is an important node inthe worldwide logistics, involved in moving a product from supplier to customer or providing anaccompanying service. The paper presents a generic architecture scheme for LaaS, which is based onrepresenting elements of the logistics networks as services. In this environment, the role of anapplication ontology and integration of individual and organizational competences is investigated andthe use of ontology matching for finding suitable resources in a multi-lingual logistics network isdiscussed.

Interoperability is a feature required by the Semantic Web. It is provided by the ontology matching methods and algorithms. But now ontologies are presented not only in English, but in other languages as well. It is important to use an automatic translation for obtaining correct matching pairs in multilingual ontology matching. The translation into many languages could be based on the Google Translate API, the Wiktionary database, etc. From the point of view of the balance of presence of many languages, of manually crafted translations, of a huge size of a dictionary, the most promising resource is the Wiktionary. It is a collaborative project working on the same principles as the Wikipedia. The parser of the Wiktionary was developed and the machine-readable dictionary was designed. The data of the machine-readable Wiktionary are stored in a relational database, but with the help of D2R server the database is presented as an RDF store. Thus, it is possible to get lexicographic information (definitions, translations, synonyms) from web service using SPARQL requests. In the case study, the problem entity is a task of multilingual ontology matching based on Wiktionary data accessible via SPARQL endpoint. Ontology matching results obtained using Wiktionary were compared with results based on Google Translate API.

Semantic web technologies show great promise in usage scenarios that involve information logistics. This paper is an experience report on improving the semantic web ontology underlying an application used in expert finding. We use ontology design patterns to find and correct poor design choices, and align the application ontology to commonly used semantic web ontologies in order to increase the interoperability of the ontology and application. Lessons learned and problems faced are discussed, and possible future developments of the project mapped out.

Digital libraries face similar challenges as enterprise information sources and the Internet: a fast growing amount of digital content requires enhanced ways of supporting information seeking. This paper presents an approach to context-based retrieval in Digital Libraries (DLs). The proposed approach includes creation of a profile representing general information demand of a user (abstract context), and use of ontology matching to identify the documents relevant to the operational context representing the current information demand of the user. A profile represents the user’s interests as a DL reader and after creation is dynamically updated based on the changes in the user’s interests. The identification of documents relevanсе is carried out by matching the user profile ontology against the digital library ontology. Semantic distance calculation is based on the use of a thesaurus.