Visual-hint Boundary to Segment Algorithm for Image Segmentation

Image segmentation has been a very active research topic in image analysis area. Currently, most of the image segmentation algorithms are designed based on the idea that images are partitioned into a set of regions preserving homogeneous intra-regions and inhomogeneous inter-regions. However, human visual intuition does not always follow this pattern. A new image segmentation method named Visual-Hint Boundary to Segment (VHBS) is introduced, which is more consistent with human perceptions. VHBS abides by two visual hint rules based on human perceptions: (i) the global scale boundaries tend to be the real boundaries of the objects; (ii) two adjacent regions with quite different colors or textures tend to result in the real boundaries between them. It has been demonstrated by experiments that, compared with traditional image segmentation method, VHBS has better performance and also preserves higher computational efficiency.Comment: 45 page

rEMM: Extensible Markov Model for Data Stream Clustering in R

Clustering streams of continuously arriving data has become an important application of data mining in recent years and efficient algorithms have been proposed by several researchers. However, clustering alone neglects the fact that data in a data stream is not only characterized by the proximity of data points which is used by clustering, but also by a temporal component. The extensible Markov model (EMM) adds the temporal component to data stream clustering by superimposing a dynamically adapting Markov chain. In this paper we introduce the implementation of the R extension package rEMM which implements EMM and we discuss some examples and applications.

Cold electron beams from cryo-cooled, alkali antimonide photocathodes

In this letter we report on the generation of cold electron beams using a Cs3Sb photocathode grown by co-deposition of Sb and Cs. By cooling the photocathode to 90 K we demonstrate a significant reduction in the mean transverse energy validating the long standing speculation that the lattice temperature contribution limits the mean transverse energy or thermal emittance near the photoemission threshold, opening new frontiers in generating ultra-bright beams. At 90 K, we achieve a record low thermal emittance of 0.2 $\mu$m (rms) per mm of laser spot diameter from an ultrafast (sub-picosecond) photocathode with quantum efficiency greater than $7\times 10^{-5}$ using a visible laser wavelength of 690 nm

rEMM: Extensible Markov Model for Data Stream Clustering in R

Clustering streams of continuously arriving data has become an important application of data mining in recent years and efficient algorithms have been proposed by several researchers. However, clustering alone neglects the fact that data in a data stream is not only characterized by the proximity of data points which is used by clustering, but also by a temporal component. The extensible Markov model (EMM) adds the temporal component to data stream clustering by superimposing a dynamically adapting Markov chain. In this paper we introduce the implementation of the <b>R</b> extension package <b>rEMM</b> which implements EMM and we discuss some examples and applications

Evolutionary Signatures In The Formation Of Low-Mass Protostars. II. Toward Reconciling Models And Observations

A long-standing problem in low-mass star formation is the "luminosity problem," whereby protostars are underluminous compared to the accretion luminosity expected both from theoretical collapse calculations and arguments based on the minimum accretion rate necessary to form a star within the embedded phase duration. Motivated by this luminosity problem, we present a set of evolutionary models describing the collapse of low-mass, dense cores into protostars. We use as our starting point the evolutionary model following the inside-out collapse of a singular isothermal sphere as presented by Young & Evans. We calculate the radiative transfer of the collapsing core throughout the full duration of the collapse in two dimensions. From the resulting spectral energy distributions, we calculate standard observational signatures (L(bol), T(bol), L(bol)/L(smm)) to directly compare to observations. We incorporate several modifications and additions to the original Young & Evans model in an effort to better match observations with model predictions; we include (1) the opacity from scattering in the radiative transfer, (2) a circumstellar disk directly in the two-dimensional radiative transfer, (3) a two-dimensional envelope structure, taking into account the effects of rotation, (4) mass-loss and the opening of outflow cavities, and (5) a simple treatment of episodic mass accretion. We find that scattering, two-dimensional geometry, mass-loss, and outflow cavities all affect the model predictions, as expected, but none resolve the luminosity problem. On the other hand, we find that a cycle of episodic mass accretion similar to that predicted by recent theoretical work can resolve this problem and bring the model predictions into better agreement with observations. Standard assumptions about the interplay between mass accretion and mass loss in our model give star formation efficiencies consistent with recent observations that compare the core mass function and stellar initial mass function. Finally, the combination of outflow cavities and episodic mass accretion reduces the connection between observational class and physical stage to the point where neither of the two commonly used observational signatures (T(bol) and L(bol)/L(smm)) can be considered reliable indicators of physical stage.NASA 1224608, 1288664, 1288658, RSA 1377304, NNX 07-AJ72GNSF AST0607793UT Austin University Continuing FellowshipAstronom