Andrzej Romanowski

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This paper presents results from participatory design studies conducted in a children's hospital. We conducted extensive user studies to understand the specific needs and design constrains in a foetal-heart imaging unit. We describe the lessons learnt in the design process, focusing on the peculiarities of the setting and providing insights to help with the(More)
In this article, we present a novel application domain for human computation, specifically for crowdsourcing, which can help in understanding particle-tracking problems. Through an interdisciplinary inquiry, we built a crowdsourcing system designed to detect tracer particles in industrial tomographic images, and applied it to the problem of bulk solid flow(More)
This papers shows attempt of using prior knowledge in order to learn about the industrial process system behaviour. The system being studied here is the pneumatic conveying of solids monitored with electrical capacitance tomography (ECT). The prior knowledge is the non-invasive measurement information derived on the basis of intentionally introduced(More)
This paper presents the design, implementation and user study of Vertoid - a mobile system for providing context-aware cues that help users limit domestic greenhouse-gas emissions. We have designed an Android-based mobile application that provides user with tips on simple eco-friendly actions in relevant locations. We then conducted a medium-term field(More)
This paper focuses on a context-specific study of how interactive systems can affect human behaviours. In the <i>subRosa</i> project, we employed ambient display technology in order to foster proper learning conditions in a dedicated study room. <i>SubRosa</i> was evaluated through two proof-of-concept studies performed using a high-fidelity prototype.(More)
This paper covers design, implementation and evaluation of a system that may be used to predict future stock prices basing on analysis of data from social media services. The authors took advantage of large datasets available from Twitter micro blogging platform and widely available stock market records. Data was collected during three months and processed(More)
Advanced statistical modelling such as Bayesian framework is a powerful methodology and gives great flexibility in terms of physical phenomena modelling. Unfortunately it is usually associated with very time and resource consuming computing. Therefore it was avoided by engineers in the past. Nowadays, rapid development of computer capabilities enables use(More)
A new method to solve the inverse problem of electrical capacitance tomography is proposed. Our method is based on artificial neural network to estimate the radius of an object present inside a pipeline. This information is useful to predict the distribution of material inside the pipe. The capacitance data used to train and test the neural network is(More)