We show the results of microsecond resolution radio data analysis focused on flux measurements of single pulses of PSR B1133+16. The data were recorded at 4.85 and 8.35 GHz with 0.5- and 1.1-GHz ...bandwidth, respectively, using Radio Telescope Effelsberg (Max-Planck-Institut fur Radioastronomie). The most important conclusion of the analysis is that the strongest single pulse emission at 4.85 and 8.35 GHz contributes almost exclusively to the trailing part of the leading component of the pulsar mean profile, whereas studies at lower frequencies report that the contribution is spread almost uniformly, covering all phases of the pulsar mean profile. We also estimate the radio emission heights to be around 1-2 per cent of the light-cylinder radius, which is in agreement with previous studies. Additionally, these observations allowed us to add two more measurements of the flux density to the PSR B1133+16 broad-band radio spectrum, covering frequencies from 16.7 MHz up to 32 GHz. We fit two different models to the spectrum: a broken power law and a spectrum based on the flicker-noise model, which represents the spectrum in a simpler, but similarly accurate, way. PUBLICATION ABSTRACT
A framework for learning query concepts in image classification Ratan, A.L.; Maron, O.; Grimson, W.E.L. ...
Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149),
1999, Letnik:
1
Conference Proceeding
In this paper, we adapt the Multiple Instance Learning paradigm using the Diverse Density algorithm as a way of modeling the ambiguity in images in order to learn "visual concepts" that can be used ...to classify new images. In this framework, a user labels an image as positive if the image contains the concept. Each example image is a bag of instances (sub-images) where only the bag is labeled-not the individual instances (sub-images). From a small collection of positive and negative examples, the system learns the concept and uses it to retrieve images that contain the concept from a large database. The learned "concepts" are simple templates that capture the color, texture and spatial properties of the class of images. We introduced this method earlier in the domain of natural scene classification using simple, low resolution sub-images as instances. In this paper, we extend the bag generator (the mechanism which takes an image and generates a set of instances) to generate more complex instances using multiple cues on segmented high resolution images. We show that this method can be used to learn certain object class concepts (e.g. cars) in addition, to natural scenes.
Aims. We aim to investigate the flux density modulation from pulsars and the specific behaviour of the modulation index versus frequency. Methods. Several pulsars were observed with the Effelsberg ...radio telescope at 8.35 GHz. Their flux density time series were corrected for interstellar scintillation effects. Results. We present measurements of modulation indices for eight pulsars. We confirm the presence of a critical frequency at ∼1 GHz for these pulsars (including three new ones from this study). We derived intrinsic modulation indices for the resulting flux density time series. Our data analysis revealed strong single pulses detected from five pulsars.
Given a set of models and some training data, we would like to find the model that best describes the data. Finding the model with the lowest generalization error is a computationally expensive ...process, especially if the number of testing points is high or if the number of models is large. Optimization techniques such as hill climbing or genetic algorithms are helpful but can end up with a model that is arbitrarily worse than the best one or cannot be used because there is no distance metric on the space of discrete models. In this paper we develop a technique called `racing' that tests the set of models in parallel, quickly discards those models that are clearly inferior and concentrates the computational effort on differentiating among the better models. Racing is especially suitable for selecting among lazy learners since training requires negligible expense, and incremental testing using leave-one-out cross validation is efficient. We use racing to select among various lazy learning algorithms and to find relevant features in applications ranging from robot juggling to lesion detection in MRI scans.
Flicker noise pulsar radio spectra Krzeszowski, K; Maron, O; Słowikowska, A ...
arXiv (Cornell University),
06/2014
Paper, Journal Article
Odprti dostop
We present new results of fitting 108 spectra of radio pulsars with the flicker noise model proposed by Loehmer et al. (2008) and compare them with the spectral indices of power-law fits published by ...Maron et al. (2000). The fits to the model were carried out using the Markov chain Monte Carlo (MCMC) method appropriate for the non-linear fits. Our main conclusion is that pulsar radio spectra can be statistically very well described by the flicker noise model over wide frequency range from a few tens of MHz up to tens of GHz. Moreover, our dataset allows us to conduct statistical analysis of the model parameters. As our results show, there is a strong negative correlation between the flicker noise spectrum model parameters log \(S_0\) and \(n\) and a strong positive relationship between n and the power-law spectral index \(\alpha\). The latter implies that their physical meaning is similar, however the flicker noise model has an advantage over broken power-law model. Not only it describes the spectra in higher frequency range with only two parameters, not counting scaling factor \(S_0\), but also it shows smooth transition from flat to steep behaviour at lower and higher frequencies, respectively. On the other hand, there are no correlations of the flicker noise model parameters \(S_0\), \(\tau\) and \(n\) with any of pulsar physical properties.
We show the results of microsecond resolution radio data analysis focused on flux measurements of single pulses of PSR B1133+16. The data were recorded at 4.85 GHz and 8.35 GHz with 0.5 GHz and 1.1 ...GHz bandwidth, respectively, using Radio Telescope Effelsberg (MPIfR). The most important conclusion of the analysis is, that the strongest single pulse emission at 4.85 GHz and 8.35 GHz contributes almost exclusively to the trailing part of the leading component of the pulsar mean profile, whereas studies at lower frequencies report that the contribution is spread almost uniformly covering all phases of the pulsar mean profile. We also estimate the radio emission heights to be around 1%--2% of the light cylinder radius which is in agreement with previous studies. Additionally these observations allowed us to add two more measurements of the flux density to the PSR B1133+16 broadband radio spectrum covering frequencies from 16.7 MHz up to 32 GHz. We fit two different models to the spectrum: the broken power law and the spectrum based on flicker noise model, which represents the spectrum in a simpler but similarly accurate way.
Mon.Not.Roy.Astron.Soc. 357 (2005) 873-880 We present the computation of effective refractive coefficients for
inhomogeneous two-component grains with 3 kinds of inclusions with ${\rm
...m_{incl}=3.0+4.0i, 2.0+1.0i, 2.5+0.0001i}$ and a matrix with ${\rm
m_m=1.33+0.01i}$ for 11 volume fractions of inclusions from 0% to 50% and
wavelengths ${\rm\lambda}$=0.5, 1.0, 2.0 and 5.0 ${\rm \mu m}$. The
coefficients of extinction for these grains have been computed using a discrete
dipole approximation (DDA). Computation of the extinction by the same method
for grains composed of a matrix material with randomly embedded inclusions has
been carried out for different volume fractions of inclusions. A comparison of
extinction coefficients obtained for both models of grain materials allows to
choose the best mixing rule for a mixture. In cases of inclusions with ${\rm
m_{incl}}$=2.0+1.0i and 2.5+0.0001i the best fit for the whole wavelengths
range and volume fractions of inclusions from 0 to 50% has been obtained for
Lichtenecker mixing rule. In case of ${\rm m_{incl}=3.0+4.0i}$ the fit for the
whole wavelength range and volume fractions of inclusions from 0 to 50% is not
very significant but the best has been obtained for Hanai rule. For volume
fractions of inclusion from 0 to 15% a very good fit has been obtained for the
whole wavelength range for Rayleigh and Maxwell-Garnett mixing rules.
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