PPT-APE: An Annotation Language and Middleware for Energy-Efficient Mobile Application Development

Nima Nikzad Octav Chipara and William G Griswold nnikzadcsucsdedu Dept of Computer Science and Engineering UC San Diego Dept of Computer Science University of Iowa . Thesis Proposal. Tao Huang. taohuang@cs.indiana.edu. Outline. Introduction. Motivation. Related System Survey. Research Issues. Milestones. Contributions. Introduction. Annotation Definitions. A commentary on an object that: (Cousins et al. 2000). BCB 660. October 20, 2011. From Carson Holt. Annotations. Automated. Ab. initio. (based on genomic sequence alone). Involves comparisons to known proteins (BLAST similarity). Sequence motifs such as start/stop . Presenter:. Brian Johns. About Capita’s software services. Capita’s software services division is a leading supplier of software solutions to the local government, social housing, library, health, insurance further education and higher . Massimo Poesio. University of . Essex. Part 1: Intro, . Microtask. . crowdsourcing. ANNOTATED CORPORA: . AN ERA OF PLENTY?. With the release of the . OntoNotes. and ANC corpora for English and a number of corpora for other languages (Prague Dependency Treebank especially) we may think we won’t need to do any more annotation for a while . by Saltanat Mashirova. Distributed applications. Distributed applications have distinctly different characteristics than conventional desktop or back office applications in that the right answer delivered too late can become the wrong answer, i.e., failure to meet key . Abstract. A large number of organizations today generate and share textual descriptions of their products, services, and actions. Such collections of textual data contain significant amount of structured information, which remains buried in the unstructured text. While information extraction algorithms facilitate the extraction of structured relations, they are often expensive and inaccurate, especially when operating on top of text that does not contain any instances of the targeted structured information. . Authors: Joe Futrelle, Amber York. . @ Woods Hole Oceanographic Institution. Imaging FlowCytobot. (Heidi Sosik et al). HabCam. (Scott . Gallager. et al). SeaBED. (. Hanumat. Singh et al). Phytoplankton . “. Have we become a little chubby around the waist?”. Günter Hipler, swissbib project, University of Basel Library . Thoughts and proposals for more components and flexibility in the VuFind 2/3 architecture based on principles of Zend Framework 3. Prof. Nalini . Venkatasubramanian. . &. Prof. Yusuf . Sarwar. Dept. of Information & Computer Science. University of California, Irvine. Intro to Distributed Systems Middleware. 2. CS 237/. NetSys. Lecture 3. Gene Finding and Sequence Annotation. Objectives of this lecture. Introduce you to basic concepts and approaches of gene finding. Show you differences between gene prediction for prokaryotic and eukaryotic genomes. Alberto Di Meglio (CERN). Project Director. Outline. What is EMI?. EMI Vision and Objectives. How does it work?. Conclusions. 06/10/2010. EMI Overview v. 3.0. 2. Outline. What is EMI?. EMI Vision and Objectives. Tool. (. TART). Outline. Pragmatics & Corpora. Speech/Dialogue-Act Annotation. The DART Approach. From DART to . TART. Observations & Issues. Intended Features. Potential Applications. Pragmatics & Corpora. However, genomes are large and complex and visualizing this information is not easy. You need to imagine that the raw annotation information, by itself, can be contained in a text file, which could include positional information (coordinates relative to the reference genome) and different features (e.g. annotation type – gene, mRNA, intron/exon, variant, UTR, etc.). Addison Snell, CEO. addison. @intersect360.com. Technical Computing. Top-line missions: . Find the oil. Design the minivan. Cure the disease. Driven by price/performance. Fast adoption of new technologies, algorithms, and approaches.