Automatic Raga Recognition in Hindustani Classical Music

Raga is the central melodic concept in Hindustani Classical Music. It has a complex structure, often characterized by pathos. In this paper, we describe a technique for Automatic Raga Recognition, based on pitch distributions. We are able to successfully classify ragas with a commendable accuracy on our test dataset.Comment: Seminar on Computer Music, RWTH Aachen, http://hpac.rwth-aachen.de/teaching/sem-mus-17/Reports/Alekh.pd

Ontology-based Classification and Analysis of non- emergency Smart-city Events

Several challenges are faced by citizens of urban centers while dealing with day-to-day events, and the absence of a centralised reporting mechanism makes event-reporting and redressal a daunting task. With the push on information technology to adapt to the needs of smart-cities and integrate urban civic services, the use of Open311 architecture presents an interesting solution. In this paper, we present a novel approach that uses an existing Open311 ontology to classify and report non-emergency city-events, as well as to guide the citizen to the points of redressal. The use of linked open data and the semantic model serves to provide contextual meaning and make vast amounts of content hyper-connected and easily-searchable. Such a one-size-fits-all model also ensures reusability and effective visualisation and analysis of data across several cities. By integrating urban services across various civic bodies, the proposed approach provides a single endpoint to the citizen, which is imperative for smooth functioning of smart cities

An integrated ontology-based approach for patent classification in medical engineering

Medical engineering (ME) is an interdisciplinary domain with short innovation cycles. Usually, researchers from several fields cooperate in ME research projects. To support the identification of suitable partners for a project, we present an integrated approach for patent classification combining ideas from topic modeling, ontology modeling & matching, bibliometric analysis, and data integration. First evaluation results show that the use of semantic technologies in patent classification can indeed increase the quality of the results