Multivariate visualization techniques have been applied to a wide variety of visual analysis tasks and a broad range of data types and sources. Their utility has been evaluated in a modest range of simple analysis tasks. In this work, we extend our previous task to a case of time-varying data. We implemented five visualizations of our synthetic test data: three previously evaluated techniques (...

Dissemination of time-varying data is essential in many applications, such as sensor networks, patient monitoring, stock tickers, etc. Often, the raw data have to go through some form of pre-processing, such as cleaning, smoothing, etc, before being disseminated. Such pre-processing often applies mathematical or statistical models to transform the large volumes of raw, point-based data into a m...

In this paper, we present an online adaptive PCA algorithm that is able to compute the full dimensional eigenspace per new time-step of sequential data. The algorithm is based on a one-step update rule that considers all second order correlations between previous samples and the new time-step. Our algorithm has O (n) complexity per new time-step in its deterministic mode and O (1) complexity pe...

Given a set of global (natural) tree parameters measured for many specimens of different ages for a range of species, we have developed a tool that visualizes these parameters over time. The parameters include measures of tree dimensions like heights, diameters, and crown shape, and measures of costs and benefits for growing the tree. We visualize the tree dimensions by animating tree growth ov...

We present algorithms and data structures that support the interactive analysis of the grouping structure of one-, two-, or higher-dimensional time-varying data while varying all defining parameters. Grouping structures characterise important patterns in the temporal evaluation of sets of time-varying data. We follow Buchin et al. [9] who define groups using three parameters: group-size, group-...

This paper presents a digital storytelling approach that generates automatic animations for time-varying data visualization. Our approach simulates the composition and transition of storytelling techniques and synthesizes animations to describe various event features. Specifically, we analyze information related to a given event and abstract it as an event graph, which represents data features ...

In this thesis we contribute to the understanding of the pivotal role of the temporal dimension in networked social systems, previously neglected and now uncovered by the data revolution recently blossomed in this field. To this aim, we first introduce the time-varying networks formalism and analyze some empirical data of social dynamics, extensively used in the rest of the thesis. We discuss t...

The spread of an infection on a real-world social network is determined by the interplay of two processes – the dynamics of the network, whose structure changes over time according to the encounters between individuals, and the dynamics on the network, whose nodes can infect each other after an encounter. Physical encounter is the most common vehicle for the spread of infectious diseases, but d...

in this paper the numerical analysis of flow and time dependent heat transfer of micro-tube conveying nanofluid in laminar flow is investigated. in this study, convection heat transfer of nanofluid and base fluid and transient analysis for time-varying heat flux for time step of 0.0001 second are elucidated. it is observed that the pumping power of nanofluid flowing and the maximum temperature ...

Consensus problems in time-varying networks are studied in this paper. We consider two cases. In the first case, the networks are basically connected and the conditions for reaching consensus are described by means of the algebraic properties of connectivity for network graph. In the second case, the networks are possibly disconnected all time. A concept called integral connectivity of networks...