Data analytics including machine learning (ML) is essential to extract insights from production data in modern industries. However, industrial ML is affected by: the low transparency of ML towards non-ML experts; poor and ...

Healthcare using body sensor data has been getting huge research attentions by a wide range of researchers because of its good practical applications such as smart health care systems. For instance, smart wearable sensor-based ...

Brain tumors have been the subject of research for many years. Brain tumors are typically classified into two main groups: benign and malignant tumors. The most common tumor type among malignant brain tumors is known as ...

Recently there has been a series of studies in knowledge graph embedding (KGE), which attempts to learn the embeddings of the entities and relations as numerical vectors and mathematical mappings via machine learning (ML). ...

Background: Within modern health systems, the possibility of accessing a large amount and a variety of data related to patients’ health has increased significantly over the years. The source of this data could be mobile ...

This study deals with fault tree analysis algorithms based on an ontology-based approach in a fuzzy environment. We extend fuzzy fault tree analysis by embedding ontology-based fault tree structures. The ontology-based ...

State-of-the-art approaches for managing Big Data pipelines assume their anatomy is known by design and expressed through adhoc Domain-Specific Languages (DSLs), with insufficient knowledge of the dark data involved in the ...

Automatic knowledge graph (KG) construction is widely used for e.g. data integration, question answering and semantic search. There are many approaches of automatic KG construction. Among which, an important approach is ...

Monitoring of the state, performance, quality of operations and other parameters of equipment and production processes, which is typically referred to as condition monitoring, is an important common practice in many ...