We present a new continuous data assimilation algorithm based on ideas that have been developed for designing finite-dimensional feedback controls for dissipative dynamical systems, in particular, in the context of the incompressible two-dimensional Navier–Stokes equations. These ideas are motivated by the fact that dissipative dynamical systems possess finite numbers of determining parameters ...

Functional genomic quantities such as histone modifications, chromatin accessibility, and evolutionary constraint can now be measured in a nearly continuous fashion across the genome. The genome is highly heterogeneous, and the relationships between different functional annotations may be fluid. Here we present an approach for visualizing, quantifying, and determining the statistical significan...

The dominant acoustic modeling methodology based on Hidden Markov Models is known to have certain weaknesses. Partial solutions to these flaws have been presented, but the fundamental problem remains: compression of the data to a compact HMM discards useful information such as time dependencies and speaker information. In this paper, we look at pure example based recognition as a solution to th...

Recent approaches to the problem of inferring a continuous probability distribution from a finite set of data have used a scalar field theory for the form of the prior probability distribution. This paper presents a more general form for the prior distribution that has a geometrical interpretation and can improve the specificity of likely solutions. It is also demonstrated that a numerical samp...

Most real-world databases contain some amount of inaccurate data. Reliability of critical attributes can be evaluated from the values of other attributes in the same data table. This paper presents a new fuzzy-based measure of data reliability in continuous attributes. We partition the relational schema of a database into a subset of input (predicting) and a subset of target (dependent) attribu...

Abstrut-Multimedia information systems have emerged as an essential component of many application domains ranging from library information systems to entertainment technology. This is because these systems utilize a variety of h-an senses to provide an effective means of communicating information. However, most implementations of these systems (based on a workstation) cannot support a continuou...

Intelligent agents need to perceive and correctly interpret the social signals of their interaction partners. In order to support the development of these skills, we establish a process of long-term data acquisition, annotation and continuous model evaluation. We facilitate automatic recording and annotation of unconstrained, multicentric interactions in a smart environment. Finally, we simplif...

We propose a method for learning cyclic causal models from a combination of observational and interventional equilibrium data. Novel aspects of the proposed method are its ability to work with continuous data (without assuming linearity) and to deal with feedback loops. Within the context of biochemical reactions, we also propose a novel way of modeling interventions that modify the activity of...

Data storage systems are being called on to manage continuous media data types, such as digital audio and video. There is a demand by applications for \constrained-latency storage access" (CLSA) to such data: precisely scheduled delivery of data streams. We believe that anticipated quantitative improvements in processor and storage-device performance will not be su cient for current data manage...