The present volume contains a selection of papers presented at the conference Mapping Parameters of Meaning, an event organized by the GReG (Groupe de Réflexion sur les Grammaires) linguistics research group in the Language Department of the University of Paris Ouest Nanterre on November 19–20, 2010. The book addresses the description of meaning construction processes, and the necessity for new linguistic interface-tools to analyze it in its dynamic and multi-dimensional aspect. Syntax, grammar, prosody, discourse organization, subjective and situational filters are not considered as autonomous systems; on the contrary, they are shown to systematically converge in the process of meaning construction and interpretation. The notion of context is discussed throughout the volume, a major concern being to try and define the precise nature of the link between variable contextual parameters and stable linguistic systems. The book will be of value to anyone interested in the interaction between syntax, semantics and pragmatics in the gradual construction and interpretation of meaning in natural languages, including researchers, students and scholars of formal linguistics, cognitive linguistics and discourse analysis.
A practical introduction to intelligent computer vision theory, design, implementation, and technology The past decade has witnessed epic growth in image processing and intelligent computer vision technology. Advancements in machine learning methods—especially among adaboost varieties and particle filtering methods—have made machine learning in intelligent computer vision more accurate and reliable than ever before. The need for expert coverage of the state of the art in this burgeoning field has never been greater, and this book satisfies that need. Fully updated and extensively revised, this 2nd Edition of the popular guide provides designers, data analysts, researchers and advanced post-graduates with a fundamental yet wholly practical introduction to intelligent computer vision. The authors walk you through the basics of computer vision, past and present, and they explore the more subtle intricacies of intelligent computer vision, with an emphasis on intelligent measurement systems. Using many timely, real-world examples, they explain and vividly demonstrate the latest developments in image and video processing techniques and technologies for machine learning in computer vision systems, including: PRTools5 software for MATLAB—especially the latest representation and generalization software toolbox for PRTools5 Machine learning applications for computer vision, with detailed discussions of contemporary state estimation techniques vs older content of particle filter methods The latest techniques for classification and supervised learning, with an emphasis on Neural Network, Genetic State Estimation and other particle filter and AI state estimation methods All new coverage of the Adaboost and its implementation in PRTools5. A valuable working resource for professionals and an excellent introduction for advanced-level students, this 2nd Edition features a wealth of illustrative examples, ranging from basic techniques to advanced intelligent computer vision system implementations. Additional examples and tutorials, as well as a question and solution forum, can be found on a companion website.
Mathematica combines symbolic and numerical calculations, plots, graphics programming, list calculations and structured documentation into an interactive environment. This book covers the program and shows with practical examples how even more complex problems can be solved with just a few commands. From the reviews: "A valuable introductory textbook on Mathematica and is very useful to scientists and engineers who use Mathematica in their work." -- ZENTRALBLATT MATH
The Glossary of Mapping Sciences, a joint publication of the American Congress on Surveying and Mapping (ACSM), American Society for Photogrammetry and Remote Sensing (ASPRS), and American Society of Civil Engineers (ASCE), contains approximately 10,000 terms that cover the broad professional areas of surveying, mapping and remote sensing. Based on over 150 sources, this glossary west through an extensive review process that included individual experts from the related subject fields and a variety of U.S. federal agencies such as the U.S.Geological Survey. This comprehensive review process helped to ensure the accuracy of the document. The Glossary of Mapping Sciences will find widespread use throughout the related professions and serve as a vehicle to standardize the terminology of the mapping sciences.
This special volume of Advances in Parasitology gives a comprehensive overview of the practical procedures involved in all aspects of global mapping. Coverage includes new research and new data, along with descriptions of new techniques in global mapping. With chapters written by leading experts in the field, it should be a standard for years to come. With an impact factor of 3.9, the series ranks second in the ISI Parasitology subject category. * Includes DVD of global environmental and global population data, including scripts for predicting disease distributions and evaluating the accuracy of these mapped products. * Valuable source of both technical and epidemiological data in this rapidly growing field. * Discusses practical applications of techniques to the study of parasitic and infectious diseases.
Drawing on the work of internationally acclaimed experts in the field, Handbook of Item Response Theory, Volume One: Models presents all major item response models. This first volume in a three-volume set covers many model developments that have occurred in item response theory (IRT) during the last 20 years. It describes models for different response formats or response processes, the need of deeper parameterization due to a multilevel or hierarchical structure of the response data, and other extensions and insights. In Volume One, all chapters have a common format with each chapter focusing on one family of models or modeling approach. An introductory section in every chapter includes some history of the model and a motivation of its relevance. Subsequent sections present the model more formally, treat the estimation of its parameters, show how to evaluate its fit to empirical data, illustrate the use of the model through an empirical example, and discuss further applications and remaining research issues.
Several recent papers underline methodological points that limit the validity of published results in imaging studies in the life sciences and especially the neurosciences (Carp, 2012; Ingre, 2012; Button et al., 2013; Ioannidis, 2014). At least three main points are identified that lead to biased conclusions in research findings: endemic low statistical power and, selective outcome and selective analysis reporting. Because of this, and in view of the lack of replication studies, false discoveries or solutions persist. To overcome the poor reliability of research findings, several actions should be promoted including conducting large cohort studies, data sharing and data reanalysis. The construction of large-scale online databases should be facilitated, as they may contribute to the definition of a “collective mind” (Fox et al., 2014) facilitating open collaborative work or “crowd science” (Franzoni and Sauermann, 2014). Although technology alone cannot change scientists’ practices (Wicherts et al., 2011; Wallis et al., 2013, Poldrack and Gorgolewski 2014; Roche et al. 2014), technical solutions should be identified which support a more “open science” approach. Also, the analysis of the data plays an important role. For the analysis of large datasets, image processing pipelines should be constructed based on the best algorithms available and their performance should be objectively compared to diffuse the more relevant solutions. Also, provenance of processed data should be ensured (MacKenzie-Graham et al., 2008). In population imaging this would mean providing effective tools for data sharing and analysis without increasing the burden on researchers. This subject is the main objective of this research topic (RT), cross-listed between the specialty section “Computer Image Analysis” of Frontiers in ICT and Frontiers in Neuroinformatics. Firstly, it gathers works on innovative solutions for the management of large imaging datasets possibly distributed in various centers. The paper of Danso et al. describes their experience with the integration of neuroimaging data coming from several stroke imaging research projects. They detail how the initial NeuroGrid core metadata schema was gradually extended for capturing all information required for future metaanalysis while ensuring semantic interoperability for future integration with other biomedical ontologies. With a similar preoccupation of interoperability, Shanoir relies on the OntoNeuroLog ontology (Temal et al., 2008; Gibaud et al., 2011; Batrancourt et al., 2015), a semantic model that formally described entities and relations in medical imaging, neuropsychological and behavioral assessment domains. The mechanism of “Study Card” allows to seamlessly populate metadata aligned with the ontology, avoiding fastidious manual entrance and the automatic control of the conformity of imported data with a predefined study protocol. The ambitious objective with the BIOMIST platform is to provide an environment managing the entire cycle of neuroimaging data from acquisition to analysis ensuring full provenance information of any derived data. Interestingly, it is conceived based on the product lifecycle management approach used in industry for managing products (here neuroimaging data) from inception to manufacturing. Shanoir and BIOMIST share in part the same OntoNeuroLog ontology facilitating their interoperability. ArchiMed is a data management system locally integrated for 5 years in a clinical environment. Not restricted to Neuroimaging, ArchiMed deals with multi-modal and multi-organs imaging data with specific considerations for data long-term conservation and confidentiality in accordance with the French legislation. Shanoir and ArchiMed are integrated into FLI-IAM1, the national French IT infrastructure for in vivo imaging.
Discover Ext JS, one of today’s most powerful and highly regarded JavaScript frameworks, with perhaps the best set of GUI widgets around, and a whole host of components that make developing client–side applications a breeze. Using a pragmatic approach, you’ll dissect seven full–fledged applications, covering How Ext JS allows you to create these applications with a slick user interface with a minimum of effort How the other parts of Ext JS aside from the GUI widgets provide many of the capabilities modern applications need, such as Ajax and data mechanisms How other technologies such as Gears can be brought in to make the applications more powerful
