950 resultados para human-action recognition
Resumo:
Human-robot interaction is an interdisciplinary research area which aims at integrating human factors, cognitive psychology and robot technology. The ultimate goal is the development of social robots. These robots are expected to work in human environments, and to understand behavior of persons through gestures and body movements. In this paper we present a biological and realtime framework for detecting and tracking hands. This framework is based on keypoints extracted from cortical V1 end-stopped cells. Detected keypoints and the cells’ responses are used to classify the junction type. By combining annotated keypoints in a hierarchical, multi-scale tree structure, moving and deformable hands can be segregated, their movements can be obtained, and they can be tracked over time. By using hand templates with keypoints at only two scales, a hand’s gestures can be recognized.
Resumo:
Dissertation presented to obtain the Ph.D degree in Biochemistry
Resumo:
Este recurso ayuda al profesor a explicar el contenido de la materia de Educación para la Ciudadanía a los alumnos de la etapa 4 del curriculo nacional inglés (key stage 4) y del General Certificate Secondary Education (GCSE). Dispone de actividades fotocopiables que apoyan y complementan a los cinco libros del estudiante; también incorpora fuentes adicionales de información para fomentar en los estudiantes habilidades de investigación.
Resumo:
Over the years, the MCF7 human breast cancer cell line has provided a model system for the study of cellular and molecular mechanisms in oestrogen regulation of cell proliferation and in progression to oestrogen and antioestrogen independent growth. Global gene expression profiling has shown that oestrogen action in MCF7 cells involves the coordinated regulation of hundreds of genes across a wide range of functional groupings and that more genes are down regulated than upregulated. Adaptation to long-term oestrogen deprivation, which results in loss of oestrogen-responsive growth, involves alterations to gene patterns not only at early time points (0-4 weeks) but continuing through to later times (20-55 weeks), and even involves alterations to patterns of oestrogen-regulated gene expression. Only 48% of the genes which were regulated >= 2-fold by oestradiol in oestrogen-responsive cells retained this responsiveness after long-term oestrogen deprivation but other genes developed de novo oestrogen regulation. Long-term exposure to fulvestrant, which resulted in loss of growth inhibition by the antioestrogen, resulted in some very large fold changes in gene expression up to 10,000-fold. Comparison of gene profiles produced by environmental chemicals with oestrogenic properties showed that each ligand gave its own unique expression profile which suggests that environmental oestrogens entering the human breast may give rise to a more complex web of interference in cell function than simply mimicking oestrogen action at inappropriate times. (C) 2009 Elsevier Ltd. All rights reserved.
Resumo:
BACKGROUND: In order to maintain the most comprehensive structural annotation databases we must carry out regular updates for each proteome using the latest profile-profile fold recognition methods. The ability to carry out these updates on demand is necessary to keep pace with the regular updates of sequence and structure databases. Providing the highest quality structural models requires the most intensive profile-profile fold recognition methods running with the very latest available sequence databases and fold libraries. However, running these methods on such a regular basis for every sequenced proteome requires large amounts of processing power.In this paper we describe and benchmark the JYDE (Job Yield Distribution Environment) system, which is a meta-scheduler designed to work above cluster schedulers, such as Sun Grid Engine (SGE) or Condor. We demonstrate the ability of JYDE to distribute the load of genomic-scale fold recognition across multiple independent Grid domains. We use the most recent profile-profile version of our mGenTHREADER software in order to annotate the latest version of the Human proteome against the latest sequence and structure databases in as short a time as possible. RESULTS: We show that our JYDE system is able to scale to large numbers of intensive fold recognition jobs running across several independent computer clusters. Using our JYDE system we have been able to annotate 99.9% of the protein sequences within the Human proteome in less than 24 hours, by harnessing over 500 CPUs from 3 independent Grid domains. CONCLUSION: This study clearly demonstrates the feasibility of carrying out on demand high quality structural annotations for the proteomes of major eukaryotic organisms. Specifically, we have shown that it is now possible to provide complete regular updates of profile-profile based fold recognition models for entire eukaryotic proteomes, through the use of Grid middleware such as JYDE.