139 research outputs found
Sound Event Detection Using Spatial Features and Convolutional Recurrent Neural Network
This paper proposes to use low-level spatial features extracted from
multichannel audio for sound event detection. We extend the convolutional
recurrent neural network to handle more than one type of these multichannel
features by learning from each of them separately in the initial stages. We
show that instead of concatenating the features of each channel into a single
feature vector the network learns sound events in multichannel audio better
when they are presented as separate layers of a volume. Using the proposed
spatial features over monaural features on the same network gives an absolute
F-score improvement of 6.1% on the publicly available TUT-SED 2016 dataset and
2.7% on the TUT-SED 2009 dataset that is fifteen times larger.Comment: Accepted for IEEE International Conference on Acoustics, Speech and
Signal Processing (ICASSP 2017
Economies of Information Consumer Commodities – An Introduction to Conceptualising Forms of Information Capitalism by Two Cases
Change from tangible and place bound production to more flexible production of intangible information goods has challenged traditional ways of organising production. Innovative operating models have brought up also new logics of doing business, therefore one might suggest that it is not always clear which is the cause and which is the effect. The attention on general discussion is often on the nature of the product, yet at least as interesting is the meta-level, i.e. how the value is created.
The aim of the paper is to examine different operating models, i.e. ways to define operating environment. The focus is on the different models of competitiveness or how end-users are served and functionality of media service is maintained. The paper contributes to discussion on sufficient and sound ways to organise knowledge intensive value creating activities. Reflections to practice are made by examining two cases of content provisioning in digital media
Knowledge Management Challenges in Renewal of R&D Processes in Software Business
A software company operates in a dynamic, knowledge intensive business. To stay competitive in such a business, the R&D processes and their development play a significant role. Knowledge management becomes a factor when organizing knowledge work. This paper is based on a qualitative case study conducted in a software company moving to component based production. In addition to theoretical insights, the paper describes the KM challenges involved in this process and suggests solutions to these. Also some managerial implications are proposed
Cellulose Fibre-Reinforced Biofoam for Structural Applications
Traditionally, polymers and macromolecular components used in the foam industry are mostly derived from petroleum. The current transition to a bio-economy creates demand for the use of more renewable feedstocks. Soybean oil is a vegetable oil, composed mainly of triglycerides, that is suitable material for foam production. In this study, acrylated epoxidized soybean oil and variable amounts of cellulose fibres were used in the production of bio-based foam. The developed macroporous bio-based architectures were characterised by several techniques, including porosity measurements, nanoindentation testing, scanning electron microscopy, and thermogravimetric analysis. It was found that the introduction of cellulose fibres during the foaming process was necessary to create the three-dimensional polymer foams. Using cellulose fibres has potential as a foam stabiliser because it obstructs the drainage of liquid from the film region in these gas-oil interfaces while simultaneously acting as a reinforcing agent in the polymer foam. The resulting foams possessed a porosity of approximately 56%, and the incorporation of cellulose fibres did not affect thermal behaviour. Scanning electron micrographs showed randomly oriented pores with irregular shapes and non-uniform pore size throughout the samples.Peer reviewe
Hygroscopicity of Nucleated Nanoparticles in CLOUD 7 Experiments
We investigated hygroscopicity of nucleated nanoparticles derived from dimethylamine and α-pinene with sulfuric acid during CLOUD 7 (Cosmic Leaving OUtdoor Droplets) campaign at CERN. The hygroscopicity of nucleated nanoparticles from 10 to 20 nm in mobility diameter was measured with a nano tandem differential mobility analyzer (nano-TDMA). Here, we present preliminary results from the CLOUD 7 experiments
Jäljitettävyyttä ja vastuullisuutta palvelevan elinkaaripohjaisen ympäristötiedon hallintamallin määrittely ja käytön kehittäminen elintarvikeketjussa
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