The scatter plot is a well-known method of visualizing pairs of two-dimensional continuous variables. Multidimensional data can be depicted in a scatter plot matrix. They are intuitive and easy-to-use, but often have a high degree of overlap which may occlude a significant portion of data. In this paper, we propose variable binned scatter plots to allow the visualization of large amounts of dat...

Time and time-oriented data are pivotal for many Visual Analytics scenarios [AMST11]. In principle, the time dimension can be represented using the display space (static mapping, e.g., line plot) or physical time (dynamic mapping, e.g., animation). Dynamic mapping is more direct and, thus, a promising visual metaphor. However, there are contradicting results on its effectiveness for analytical ...

In this paper we introduce a new method for robust principal component analysis. Classical PCA is based on the empirical covariance matrix of the data and hence it is highly sensitive to outlying observations. In the past, two robust approaches have been developed. The first is based on the eigenvectors of a robust scatter matrix such as the MCD or an S-estimator, and is limited to relatively l...

An external electric field (EEF) can impact a broad range of catalytic processes beyond redox systems. Computational design catalysts under EEFs targeting specific operation conditions essentially requires accurate predictions the response complex physicochemical system to collective parameters such as EEF strength/direction and temperature. Here, we develop first-principles-based multiscale ap...

The scatter plot is a commonly used assessment tool for identifying temporal patterns in the occurrence of behavior problems. However, the extent to which such patterns are frequently observed is unknown because little research has evaluated the general utility of the scatter plot. We conducted a large-scale analysis of within- and across-day occurrences of problem behavior by conducting contin...

In this paper we present an application of single cluster visualization (SCV) a technique to visualize single clusters of high-dimensional data. This method maps a single cluster to the plane trying to preserve the relative distances of feature vectors to the corresponding prototype vector. Thus, fuzzy clustering results representing relative distances in the form of a partition matrix as well ...

When it comes to multimodal image registration, mutual information (MI) seems to hold the biggest market share. However, MI has a number of serious flaws, not the least of which is the quantization effect caused by histogram binning. We propose a novel registration method that, like MI, is motivated by the distribution of points in the joint intensity scatter plot (JISP). However, we avoid the ...

In order to study the adaptation of rice lines to drought stress and to identify the tolerant and sensitive lines, 150 pure lines in RIL population each derived from a cross between two Iranian rice varieties Gharib and Sepidroud were investigated. Augment design based on the randomized complete block design (RCBD) was used with 6 check cultivars and 4 replications in 2013-2014 growing season. ...

Recently, there has been an interest in methods for filtering large scatter plot spaces for interesting patterns. However, user interaction remains crucial in starting an explorative analysis in a large scatter plot space. We introduce an approach for explorative search and navigation in large sets of scatter plot diagrams. By means of a sketch-based query interface, users can start the explora...