We propose and demonstrate a new paradigm for active vision research that draws upon recent advances in the fields of artificial life and computer graphics. A software alternative to the prevailing hardware vision mindset, animat vision prescribes artificial animals, or animats, situated in physics-based virtual worlds as autonomous virtual robots with active perception systems. To be operative...

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We present the results of experiments on visualization of magnetic flux distribution and its dynamics in high-temperature superconductors with artificial defects. High-Tc superconductor thin films were equipped with a special arrangement of antidots in order to separate the streams of magnetic flux moving in (or out of) the sample. A possibility to alter the direction and depth of flux penetrat...

In this study, an Artificial Neural Network (ANN) approach is utilized to perform a parametric study on the process of extraction of lubricants from heavy petroleum cuts. To train the model, we used field data collected from an industrial plant. Operational conditions of feed and solvent flow rate, Temperature of streams and mixing rate were considered as the input to the model, whereas the flo...

We present a system for testing turn-taking strategies in a simulation environment, in which artificial dialogue participants exchange audio streams in real time – unlike earlier turn-taking simulations, which interchanged unambiguous symbolic messages. Dialogue participants autonomously determine their turn-taking behaviour, based on their analysis of the incoming audio. We use machine-learnin...

Building ontology for a specific field of research is a very tedious task; yet, very important. Ontologies can help in defining the boundaries of a discipline and identifying new emerging streams of research. Automating this process reduces, if not eliminates, the overhead associated with manual ontology building methods and gives a big jump to continue refining and improving the generated onto...

Besides enabling the segmentation of video streams into moving and background components, detecting moving objects provides a focus of attention for recognition, classification, and activity analysis, making these later stepsmore efficient.Wepropose a novelmodel for image sequences based on self organization through artificial neural networks, that is used both for background modeling, allowing...

Massive Data Flow (MDF) is everywhere these days; from data about neural cells, social insects and genetic networks, to Lifelog (digital storage of a person’s visual and audio life log) and SNS (Social network service) data streams. Current web and device technology has made it possible for us to record detailed and massive data flows of artificial and real living systems. But how can we analyz...

Machine Learning (ML) applications need large volumes of data to train their models so that they can make high-quality predictions. Given digital revolution enablers such as the Internet Things (IoT) and Industry 4.0, this information is generated in quantities terms continuous streams not static datasets it case with most AI (Artificial Intelligence) frameworks. Kafka-ML a novel open-source fr...