Asymmetric cluster analysis is one of the most useful methods together with asymmetric multidimensional scaling (MDS) to analyze asymmetric (dis)similarity data. In both methods, visualization of the result of the analysis plays an important role in the analysis. Some methods for visualizing the result of the asymmetric clustering and MDS have been proposed (Saito and Yadohisa, Data Analysis of...

Adults consistently make errors in solving simple multiplication problems. These errors have been explained with reference to the interference between similar problems. In this paper, we apply multidimensional scaling (MDS) to the domain of multiplication problems, to uncover their underlying similarity structure. A tree-sorting task was used to obtain perceived dissimilarity ratings. The deriv...

We present an online system for automatic smart face morphing, which can be accessed at http://facewarping.com. This system morphs the user-uploaded image to “beautify” it by embedding features from a user-selected celebrity. This system consists of three major modules: facial feature point detection, geometry embedding, and image warping. To embed the features of a celebrity face and at the sa...

Many previous studies have examined the ease with which two spatially adjacent textures can be segmented. Our goal is to examine the representational system that determines the appearance of isolated patches of visual texture. To this end, similarity judgments from three subjects were obtained for 20 artificial textures comprising filtered noise. Multidimensional scaling (MDS) revealed that thr...

In this paper we present and evaluate two semantic music mood models relying on metadata extracted from over 180,000 production music tracks sourced from I Like Music (ILM)’s collection. We performed non-metric multidimensional scaling (MDS) analyses of mood stem dissimilarity matrices (1 to 13 dimensions) and devised five different mood tag summarisation methods to map tracks in the dimensiona...

In the context of devising a spatial ear-training system, a study into the perceptual construct ‘ensemble depth’ was executed. Based on the findings of a pilot study into the auditory effects of early reflection (ER) pattern characteristics, exemplary stimuli were created. Changes were highly controlled to allow unidimensional variation of the intended quality. To measure the psychological stru...

According to the generalized context model (GCM) (Nosofsky, 1986 ), people represent categories by storing individual exemplars (or examples) in memory, and classify objects based on their similarity to these stored exemplars. For example, the model assumes that people represent the category of ‘birds’ by storing in memory the vast collection of different sparrows, robins, eagles, ostriches (an...

Social identity theory offers a means to understand attitudes about wolves, with consequences for management support. Using data from mail survey we explored relationships among seven identities (i.e., wolf advocate, hunter, environmentalist, nature enthusiast, farmer, trapper, conservationist) using multidimensional scaling (MDS) and principal components analysis (PCA). We examined how correla...

In this paper, we analyze the nontrivial zeros of Riemann zeta-function using multidimensional scaling (MDS) algorithm and computational visualization features. The as well vectors with several neighboring are interpreted basic elements (points or objects) a data set. Then employ variety different metrics, such Jeffreys Lorentzian ones, to calculate distances between objects. set calculated is ...

Position is an extremely important parameter for each node in most of applications using wireless sensor work (WSN). In this paper, a new distributed localization (DMDS-GC) algorithm is proposed based on the multidimensional scaling (MDS) technique and the geometric correction technique. In DMDS-GC, the entire network is split into several localization clusters (LCs) with sufficient common node...