The dataset used to generate IUPAC benchmark Arrhenius parameters for propagation rate coefficients in radical polymerization is extended and reanalyzed, taking into account systematic interlaboratory variation.

Remotely sensed infrared images are often used to assess wildland fire conditions. Separately, fire propagation models are in use to forecast future conditions. In the Dynamic Data Driven Application System (DDDAS) concept, the fire propagation model will react to the image data, which should produce more accurate predictions of fire propagation. In this study we describe a series of image proc...

It was thought previously that cardiac muscle gap junctions provide low-resistance connections between cells and permit the local-circuit current to flow. Some evidences show that myocardial cells may not require low-resistance connections for successful propagation of the action potential (AP). It seems that some other types of mechanisms must be involved in AP propagation. In this article, we...

Propositional satisfiability (SAT) is the archetypal NP-complete problem [1]. A great deal of recent SAT research, particularly on the performance of SAT solvers, has been driven by structured instances, which are obtained by mapping another problem class into SAT. It is possible to efficiently solve a wide range of problems by mapping them into SAT and solving the SAT representation of the pro...

Collective graphical models (CGMs) are a formalism for inference and learning with aggregate data that are motivated by a model for bird migration. We highlight a close connection between approximate MAP inference in CGMs and marginal inference in standard graphical models. The connection leads us to derive a novel Belief Propagation (BP)-style algorithm for collective graphical models. The alg...

The biggest power consumer in data centers is the storage system. Coupled with the fact that disk drives are lowly utilized, disks offer great opportunities for power savings, but any power saving action should be transparent to user traffic. Estimating correctly the performance impact of power saving becomes crucial for the effectiveness of power saving. Here, we develop a methodology that qua...

Due to interference, path loss, multipath fading, background noise, and many other factors, wireless communication normally cannot provide a wireless link with both a high data rate and a long transmission range. To address this problem, striping network traffic in parallel over multiple lower-data-rate but longer-transmission-range wireless channels may be used. In this paper, we propose a new...

This paper proposes a subspace clustering algorithm by introducing attribute weights in the affinity propagation algorithm. A new step is introduced to the affinity propagation process to iteratively update the attribute weights based on the current partition of the data. The relative magnitude of the attribute weights can be used to identify the subspaces in which clusters are embedded. Experi...

Emerging patterns (EP) represent a class of interaction structures and have recently been proposed as a tool for data mining. Especially, EP have been applied to the production of new types of classifiers during classification in data mining. Traditional clustering and pattern mining algorithms are inadequate for handling the analysis of high dimensional gene expression data or the analysis of ...