Carnegie Mellon University

About: Carnegie Mellon University is a education organization based out in Pittsburgh, Pennsylvania, United States. It is known for research contribution in the topics: Population & Robot. The organization has 36317 authors who have published 104359 publications receiving 5975734 citations. The organization is also known as: CMU & Carnegie Mellon.

Security in wireless sensor networks

Abstract: They are susceptible to a variety of attacks, including node capture, physical tampering, and denial of service, while prompting a range of fundamental research challenges.

Attention and weight in person perception: The impact of negative and extreme behavior.

Abstract: Social perceivers process selected aspects of the stimulus array presented by another person. This article argues that such selectivity is based on the informativeness of person attributes. Properties of the attribute itself—its evaluative extremity (distance from the scale midpoint) and its evaluative valence (positive or negative)—can make it informative. Informative attributes attract selective attention at input and also carry extra weight in the final impression. In the present research, negativity and extremity were manipulated across two separate behavioral dimensions, sociability and civic activism, and over 16 stimulus persons. Perceivers saw two prescaled behavior photographs for each stimulus person and controlled a slide changer switch—this provided a measure of attention as looking time. Perceivers also rated each stimulus person's likability, providing a measure of relative weight for each slide. Weights were derived from Anderson's information integration model. Perceivers preferentially weighted behaviors that were extreme or negative, and the behavioral measure of attention (looking time) replicated the predicted pattern. The results are discussed in light of controversies over the rationality of social information processing.

Continuous Lattices and Domains

Abstract: Information content and programming semantics are just two of the applications of the mathematical concepts of order, continuity and domains. The authors develop the mathematical foundations of partially ordered sets with completeness properties of various degrees, in particular directed complete ordered sets and complete lattices. Uniquely, they focus on partially ordered sets that have an extra order relation, modelling the notion that one element 'finitely approximates' another, something closely related to intrinsic topologies linking order and topology. Extensive use is made of topological ideas, both by defining useful topologies on the structures themselves and by developing close connections with numerous aspects of topology. The theory so developed not only has applications to computer science but also within mathematics to such areas as analysis, the spectral theory of algebras and the theory of computability. This authoritative, comprehensive account of the subject will be essential for all those working in the area.

Oases: Robust de novo RNA-seq assembly across the dynamic range of expression levels

Abstract: Motivation: High-throughput sequencing has made the analysis of new model organisms more affordable. Although assembling a new genome can still be costly and difficult, it is possible to use RNA-seq to sequence mRNA. In the absence of a known genome, it is necessary to assemble these sequences de novo, taking into account possible alternative isoforms and the dynamic range of expression values. Results: We present a software package named Oases designed to heuristically assemble RNA-seq reads in the absence of a reference genome, across a broad spectrum of expression values and in presence of alternative isoforms. It achieves this by using an array of hash lengths, a dynamic filtering of noise, a robust resolution of alternative splicing events and the efficient merging of multiple assemblies. It was tested on human and mouse RNA-seq data and is shown to improve significantly on the transABySS and Trinity de novo transcriptome assemblers. Availability and implementation: Oases is freely available under the GPL license at www.ebi.ac.uk/~zerbino/oases/ Contact: ude.cscu@onibrezd Supplementary information: Supplementary data are available at Bioinformatics online.