Influenza viruses have been responsible for large losses of lives around the world and continue to present a great public health challenge. Antigenic characterization based on hemagglutination inhibition (HI) assay is one of the routine procedures for influenza vaccine strain selection. However, HI assay is only a crude experiment reflecting the antigenic correlations among testing antigens (vi...

We discuss interactive techniques for multidimensional scaling (MDS) and a system, named \XGvis", that implements these techniques. MDS is a method for visualizing proximity data, that is, data where objects are characterized by dissimilarity values for all pairs of objects. MDS constructs maps of these objects in IR k by interpreting the dissimilarities as distances. MDS in its conventional ba...

We propose here a parallel implementation of multidimensional scaling (MDS) method which can be used for visualization of large datasets of multidimensional data. Unlike in traditional approaches, which employ classical minimization methods for finding the global optimum of the “stress function”, we use a heuristic based on particle dynamics. This method allows avoiding local minima and is conv...

We have designed a new efficient dimensionality reduction algorithm in order to investigate new ways of accurately characterizing the biodiversity, namely from a geometric point of view, scaling with large environmental sets produced by NGS (∼ 10 sequences). The approach is based on Multidimensional Scaling (MDS) that allows for mapping items on a set of n points into a low dimensional euclidea...

Ashby, Maddox and Lee (Psychological Science, 5 (3) 144) argue that it can be inappropriate to fit multidimensional scaling (MDS) models to similarity or dissimilarity data that have been averaged across subjects. They demonstrate that the averaging process tends to make dissimilarity data more amenable to metric representations, and conduct a simulation study showing that noisy data generated ...

Multidimensional scaling (MDS) is a technique for visualizing the relationships among data that are similar to each other on very many dimensions. For example, meanings of words such as indefinite pronouns are similar to each other by virtue of being expressed by the same indefinite pronoun in one language or another (Haspelmath 1997). If one compares indefinite pronouns of a large number of la...

We study exclusion processes on the integer lattice in which particles change their velocities due to stickiness. Specifically, whenever two or more particles occupy adjacent sites, they stick together for an extended period of time, and the entire particle system is slowed down until the “collision” is resolved. We show that under diffusive scaling of space and time such processes converge to ...

The analysis of 3D nonrigid objects usually involves the need to deal with a large number of degrees of freedom. When trying to match two such objects, one approach is to map the surfaces into a domain in which the matching process is simple to execute. Limiting the discussion to almost isometric mappings, which describe most natural deformations in nature, one could resort to Canonical forms. ...

In this paper, determining the localization of nodes in a Wireless Sensor Network is a very important task, which involves collaboration between sensor nodes. Localization is a fundamental service since it is relevant to many applications and to the network main functions, such as: routing, communication, cluster creation, network coverage, etc. Collaboration is essential to self-localization, ...

A wide range of applications used in wireless sensor networks requires location information of multimedia sensor nodes. In general, the topographical location information of data acquired by a sensor is applied for smart, interactive multimedia services. However, conventional techniques employ GPS or other location-tracking devices installed on sensor nodes and thus incur additional costs, maki...