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Online High Resolution Stochastic Radiation Radar Imaging using Sparse Covariance Fitting

Stochastic radiation radar (SRR) systems allow for the forming of radar images by transmitting stochastic signals to form the stochastic radiation field and thereby increase the target observation information to achieve high resolution imaging. In this paper, we examine the use of the online SParse Iterative Covariance-based Estimation (SPICE) algorithm to suppress the noise and improve the operat

Surface Classification with Millimeter-Wave Radar Using Temporal Features and Machine Learning

Classification of surfaces using millimeter-wave radar commonly considers the use of polarization-based methods for road condition monitoring. When a surface consists of larger structures, one is instead often interested in monitoring the surface topography, which is typically not resolvable by the limited radar bandwidth. To alleviate this problem, we here consider several phase coherent radar me

Vintergatans alla planeter

Precis som vår egen stjärna, Solen, har planeter kretsande runtom sig så har vi nu börjat upptäcka planeter kretsande runt avlägsna stjärnor därute i Vintergatan. Specialdesignade rymdbaserade teleskop, som COROT och Kepler, tillsammans med markbaserade teleskop, analyserar stjärnornas ljus och letar efter täcken på avlägsna exoplaneter.As there are planets orbiting our own star, the Sun, we have now started discovering planets orbiting distant stars, out in the galaxy. Specially designed space based telescopes, such as COROT and Kepler, are together with ground based telescopes gathering and analyzing light from distant stars, looking for hits that these stars may harbor exoplanets.

Modelling Stem Cells Lineages with Markov Trees

A variational Bayesian EM with smoothed probabilities algorithm for hidden Markov trees (HMT) is proposed for incomplete tree structured data. The full posterior of the HMT parameters is determined and the underflow problems associated with previous algorithms are eliminated. Example results for the prediction of the types of cells in real stem cell lineage trees are presented.

Rosetta och Philae

Under Forskarfredagen 2016 diskuterar vi ESAs rymdsond Rosetta, dess lilla landare Philae, hur de tog sig till kometen 67P och vad de upptäckte där.During Researchers Night 2016 we are discussing ESA's mission Rosetta, its lander Philae, how they traveled to the comet 67P and what they discovered there.

Attitudes as Equipment for Living

This article explores Burke’s concept of attitude through an overview of its use in his writings, connecting it to the concept of literature as equipment for living, using the comic frame and research into the practical impact of attitudes in rhetorical situations, in order to better understand both concepts.

Jorden : En planet bland många

I solsystemet kan vi se åtta planeter, flera dvärgplaneter och mängder av asteroider och kometer kretsande runt Solen. I planetariet kan vi lära oss om Jorden och månen, säsonger och stjärnorna. Vi utforskar solsystemets åtta planeter, lär oss om stjärnbilderna och att bara för att det kallas för "stjärnfall" betyder det inte att stjärnor kan falla från himlavalvet.We have eight planets, quite a few dwarf planets and a lot of asteroids and comets orbiting the Sun. In the planetarium we can learn about the Earth and the Moon, the seasons and the stars. We explore the planets of the solar system, learn about the constellations and discover that just because it is called "a shooting star" does not mean that stars can fall from the skies.

Actio som förkroppsligad attityd : En burkesk och multimodal metod för analys av ickeverbal kommunikation

Denna artikel presenterar en studie av attityder som visas i en medlings­situation i en svensk reality-teveserie om grannkonflikter. Syftet är att utveckla en teoretisk och metodologisk ram för retorisk analys av icke­verbala yttranden. I artikeln skisseras en teori baserad på retorikens actio och Kenneth Burkes syn på förkroppsligad attityd. Actio utforskas genom en multimodal analys, det vill sä

Mean field theory neural networks for feature recognition, content addressable memory and optimization

Various applications of the mean field theory (MFT) technique for obtaining solutions close to optimal minima in feedback networks are reviewed. Using this method in the context of the Boltzmann machine gives rise to a fast deterministic learning algorithm with a performance comparable with that of the backpropagation algorithm (BP) in feature recognition applications. Since MFT learning is bidire