Enterprise Integration and Interoperability for Big Data-Driven Processes in the Frame of Industry 4.0.

Traditional manufacturing businesses lack the standards, skills, processes, and technologies to meet today's challenges of Industry 4.0 driven by an interconnected world. Enterprise Integration and Interoperability can ensure efficient communication among various services driven by big data. However, the data management challenges affect not only the technical implementation of software solutions but the function of the whole organization. In this paper, we bring together Enterprise Integration and Interoperability, Big Data Processing, and Industry 4.0 in order to identify synergies that have the potential to enable the so-called "Fourth Industrial Revolution." On this basis, we propose an architectural framework for designing and modeling Industry 4.0 solutions for big data-driven manufacturing operations. We demonstrate the applicability of the proposed framework through its instantiation to predictive maintenance, a manufacturing function that increasingly concerns manufacturers due to the high costs, safety issues, and complexity of its application.

SEMPATH Ontology: modeling multidisciplinary treatment schemes utilizing semantics.

A dramatic increase of demand for provided treatment quality has occurred during last decades. The main challenge to be confronted, so as to increase treatment quality, is the personalization of treatment, since each patient constitutes a unique case. Healthcare provision encloses a complex environment since healthcare provision organizations are highly multidisciplinary. In this paper, we present the conceptualization of the domain of clinical pathways (CP). The SEMPATH (SEMantic PATHways) Oontology comprises three main parts: 1) the CP part; 2) the business and finance part; and 3) the quality assurance part. Our implementation achieves the conceptualization of the multidisciplinary domain of healthcare provision, in order to be further utilized for the implementation of a Semantic Web Rules (SWRL rules) repository. Finally, SEMPATH Ontology is utilized for the definition of a set of SWRL rules for the human papillomavirus) disease and its treatment scheme.

A holistic environment for the design and execution of self-adaptive clinical pathways.

One of the main challenges to be confronted by modern health care, so as to increase treatment quality, is the personalization of treatment. The treatment personalization requires the continuous reconfiguration and adaptation of the selected treatment schemes according to the "current" clinical status of each patient and "current" circumstances inside a health care organization that change rapidly, as well as the updated medical knowledge. In this paper, we present an innovative software environment that provides an integrated IT solution concerning the adaptation of health care processes (clinical pathways) during execution time. The software comprises a health care process execution engine assisted by a semantic infrastructure for reconfiguring the clinical pathways. During the execution of clinical pathways, the system reasons over the rules and reconfigures the next steps of the treatment. A graphical designer interface is implemented for the definition of the rule-set for the clinical pathways adaptation in a user-friendly way.

NEURON: enabling autonomicity in wireless sensor networks.

Future Wireless Sensor Networks (WSNs) will be ubiquitous, large-scale networks interconnected with the existing IP infrastructure. Autonomic functionalities have to be designed in order to reduce the complexity of their operation and management, and support the dissemination of knowledge within a WSN. In this paper a novel protocol for energy efficient deployment, clustering and routing in WSNs is proposed that focuses on the incorporation of autonomic functionalities in the existing approaches. The design of the protocol facilitates the design of innovative applications and services that are based on overlay topologies created through cooperation among the sensor nodes.