This system description paper introduces the OWL 2 reasoner HermiT. The reasoner is fully compliant with the OWL 2 Direct Semantics as standardised by the World Wide Web Consortium (W3C). HermiT is based on the hypertableau calculus, and it supports a wide range of standard and novel optimisations to improve the performance of reasoning on real-world ontologies. Apart from the standard OWL 2 reasoning task of entailment checking, HermiT supports several specialised reasoning services such as class and property classification, as well as a range of features outside the OWL 2 standard such as DL-safe rules, SPARQL queries, and description graphs. We discuss the system's architecture, and we present an overview of the techniques used to support the mentioned reasoning tasks. We further compare the performance of reasoning in HermiT with that of FaCT++ and Pellet-two other popular and widely used OWL 2 reasoners.

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Software development usually follows well known process models and standards for development processes. However, these are usually diverse and described in natural language which complicates their automation, adaptivity and verification. The need for process formalisation has long been highlighted, and we have provided a formalisation and translation algorithm to that effect in earlier work. However, to systematically and faithfully formalise heterogeneous processes from different standards and process models, there is a need to utilise uniform concepts to underpin the formalisation process. Metamodels and ontologies have been explored recently to lay a foundation for structuring and expressing additional rigour to process formalisation. In this study, we develop an axiom based metamodel utilising powertype patterns as a conceptual framework to underpin homogeneous process formalisation. The advantage of an axiomatic and powertype based metamodel approach lies in its potential to determine the metamodel basic constituents and formalism as well as its extensibility and adaptability. We formalise the metamodel using ontologies while adopting use cases from ISO/IEC 29110 and ISO/IEC 24744 standards for metamodel illustrations. Ontology based process descriptions enable process automated verification and adaptivity capability through the use of ontology reasoning support engines.

How to design efficient scheduling strategy for different environments is a hot topic in cloud computing. In the private cloud of computer science labs in universities, there are several kinds of tasks with different resource requirements, constraints, and lifecycles such as IT infrastructure tasks, course design tasks submitted by undergraduate students, deep learning tasks and and so forth. Taking the actual needs of our laboratory as an instance, these tasks are analyzed, and scheduled respectively by different scheduling strategies. The Batch Scheduler is designed to process tasks in rush time to improve system throughput. Dynamic scheduling algorithm is proposed to tackle long-term lifecycle tasks such as deep learning tasks which are hungry for GPU resources and have dynamically changing priorities. Experiments show that the scheduling strategies proposed in this paper improve resource utilization and efficiency.