Visual and semantic interpretability of projections of high dimensional data for classification tasks

A number of visual quality measures have been introduced in visual analytics literature in order to automatically select the best views of high dimensional data from a large number of candidate data projections. These methods generally concentrate on the interpretability of the visualization and pay little attention to the interpretability of the projection axes. In this paper, we argue that interpretability of the visualizations and the feature transformation functions are both crucial for visual exploration of high dimensional labeled data. We present a two-part user study to examine these two related but orthogonal aspects of interpretability. We first study how humans judge the quality of 2D scatterplots of various datasets with varying number of classes and provide comparisons with ten automated measures, including a number of visual quality measures and related measures from various machine learning fields. We then investigate how the user perception on interpretability of mathematical expressions relate to various automated measures of complexity that can be used to characterize data projection functions. We conclude with a discussion of how automated measures of visual and semantic interpretability of data projections can be used together for exploratory analysis in classification tasks.Comment: Longer version of the VAST 2011 poster. http://dx.doi.org/10.1109/VAST.2011.610247

An AeroCom initial assessment – optical properties in aerosol component modules of global models

The AeroCom exercise diagnoses multi-component aerosol modules in global modeling. In an initial assessment simulated global distributions for mass and mid-visible aerosol optical thickness (aot) were compared among 20 different modules. Model diversity was also explored in the context of previous comparisons. For the component combined aot general agreement has improved for the annual global mean. At 0.11 to 0.14, simulated aot values are at the lower end of global averages suggested by remote sensing from ground (AERONET ca. 0.135) and space (satellite composite ca. 0.15). More detailed comparisons, however, reveal that larger differences in regional distribution and significant differences in compositional mixture remain. Of particular concern are large model diversities for contributions by dust and carbonaceous aerosol, because they lead to significant uncertainty in aerosol absorption (aab). Since aot and aab, both, influence the aerosol impact on the radiative energy-balance, the aerosol (direct) forcing uncertainty in modeling is larger than differences in aot might suggest. New diagnostic approaches are proposed to trace model differences in terms of aerosol processing and transport: These include the prescription of common input (e.g. amount, size and injection of aerosol component emissions) and the use of observational capabilities from ground (e.g. measurements networks) or space (e.g. correlations between aerosol and clouds)

Color Textured Image Segmentation Using ICICM - Interval Type-2 Fuzzy C-Means Clustering Hybrid Approach

Segmentation is an essential process in image because of its wild application such as image analysis, medical image analysis, pattern reorganization, etc. Color and texture are most significant low-level features in an image. Normally, color-textured image segmentation consists of two steps: (i) extracting the feature and (ii) clustering the feature vector. This paper presents the hybrid approach for color texture segmentation using Haralick features extracted from the Integrated Color and Intensity Co-occurrence Matrix (ICICM). Then, Extended- Interval Type-2 Fuzzy C-means clustering algorithm is used to cluster the obtained feature vectors into several classes corresponding to the different regions of the textured image. Experimental results show that the proposed hybrid approach could obtain better cluster quality and segmentation results compared to state-of-art image segmentation algorithms

Collinear antiferromagnetic phases of a frustrated spin-12\frac{1}{2} J1J_{1}--J2J_{2}--J1⊥J_{1}^{\perp} Heisenberg model on an AAAA-stacked bilayer honeycomb lattice

The zero-temperature quantum phase diagram of the spin-$\frac{1}{2}$ $J_{1}$--$J_{2}$--$J_{1}^{\perp}$ model on an $AA$-stacked bilayer honeycomb lattice is investigated using the coupled cluster method (CCM). The model comprises two monolayers in each of which the spins, residing on honeycomb-lattice sites, interact via both nearest-neighbor (NN) and frustrating next-nearest-neighbor isotropic antiferromagnetic (AFM) Heisenberg exchange iteractions, with respective strengths $J_{1} > 0$ and $J_{2} \equiv \kappa J_{1}>0$. The two layers are coupled via a comparable Heisenberg exchange interaction between NN interlayer pairs, with a strength $J_{1}^{\perp} \equiv \delta J_{1}$. The complete phase boundaries of two quasiclassical collinear AFM phases, namely the N\'{e}el and N\'{e}el-II phases, are calculated in the $\kappa \delta$ half-plane with $\kappa > 0$. Whereas on each monolayer in the N\'{e}el state all NN pairs of spins are antiparallel, in the N\'{e}el-II state NN pairs of spins on zigzag chains along one of the three equivalent honeycomb-lattice directions are antiparallel, while NN interchain spins are parallel. We calculate directly in the thermodynamic (infinite-lattice) limit both the magnetic order parameter $M$ and the excitation energy $\Delta$ from the $s^{z}_{T}=0$ ground state to the lowest-lying $|s^{z}_{T}|=1$ excited state (where $s^{z}_{T}$ is the total $z$ component of spin for the system as a whole, and where the collinear ordering lies along the $z$ direction) for both quasiclassical states used (separately) as the CCM model state, on top of which the multispin quantum correlations are then calculated to high orders ($n \leq 10$) in a systematic series of approximations involving $n$-spin clusters. The sole approximation made is then to extrapolate the sequences of $n$th-order results for $M$ and $\Delta$ to the exact limit, $n \to \infty$

The Value Driven Pharmacist: Basics of Access, Cost, and Quality 2nd Edition

https://digitalcommons.butler.edu/butlerbooks/1017/thumbnail.jp

Experimental Analysis of Neighborhood Effects

Families, primarily female-headed minority households with children, living in high-poverty public housing projects in five U.S. cities were offered housing vouchers by lottery in the Moving to Opportunity program. Four to seven years after random assignment, families offered vouchers lived in safer neighborhoods that had lower poverty rates than those of the control group not offered vouchers. We find no significant overall effects of this intervention on adult economic self-sufficiency or physical health. Mental health benefits of the voucher offers for adults and for female youth were substantial. Beneficial effects for female youth on education, risky behavior, and physical health were offset by adverse effects for male youth. For outcomes exhibiting significant treatment effects, we find, using variation in treatment intensity across voucher types and cities, that the relationship between neighborhood poverty rate and outcomes is approximately linear.