This book presents new work on how Merge and formal features, two basic factors in the Minimalist Program, should determine the syntactic computation of natural language. Merge combines simpler objects into more complex ones. Formal features establish dependencies within objects. In this book leading scholars examine the intricate ways in which these two factors interact to generate well-formed derivations in natural language. It is divided into two parts concerned with formal features and interpretable features - a subset of formal features. The authors combine grammatical theory with the analysis of data drawn from a wide range of languages, both in the adult grammar and in first language acquisition. The mechanisms at work in linguistic computation are considered in relation to a variety of linguistic phenomena, including A-binding, A'-dependencies and reconstruction, agreement, word order, adjuncts, pronouns and complementizers.

It is with greatpleasure that we present the proceedings of the 5th International Symposium on Visual Computing (ISVC 2009), which was held in Las Vegas, Nevada. ISVC o?ers a common umbrella for the four main areas of visual c- puting includingvision,graphics,visualization,andvirtualreality.Thegoalisto provide a forum for researchers, scientists, engineers, and practitioners throu- out the world to present their latest research ?ndings, ideas, developments, and applications in the broader area of visual computing. This year, the program consisted of 16 oral sessions, one poster session, 7 special tracks, and 6 keynote presentations. Also, this year ISVC hosted the Third Semantic Robot Vision Challenge.The responseto the call for papers was verygood;wereceivedover320submissionsfor themainsymposiumfromwhich we accepted 97 papers for oral presentation and 63 papers for poster presen- tion. Special track papers were solicited separately through the Organizing and Program Committees of each track. A total of 40 papers were accepted for oral presentation and 15 papers for poster presentation in the special tracks. All papers were reviewed with an emphasis on potential to contribute to the state of the art in the ?eld. Selection criteria included accuracy and originality of ideas, clarity and signi?cance of results, and presentation quality. The review process was quite rigorous, involving two to three independent blind reviews followed by several days of discussion. During the discussion period we tried to correct anomalies and errors that might have existed in the initial reviews.

This book discusses the principles and practical applications of data science, addressing key topics including data wrangling, statistics, machine learning, data visualization, natural language processing and time series analysis. Detailed investigations of techniques used in the implementation of recommendation engines and the proper selection of metrics for distance-based analysis are also covered. Utilizing numerous comprehensive code examples, figures, and tables to help clarify and illuminate essential data science topics, the authors provide an extensive treatment and analysis of real-world questions, focusing especially on the task of determining and assessing answers to these questions as expeditiously and precisely as possible. This book addresses the challenges related to uncovering the actionable insights in “big data,” leveraging database and data collection tools such as web scraping and text identification. This book is organized as 11 chapters, structured as independent treatments of the following crucial data science topics: Data gathering and acquisition techniques including data creation Managing, transforming, and organizing data to ultimately package the information into an accessible format ready for analysis Fundamentals of descriptive statistics intended to summarize and aggregate data into a few concise but meaningful measurements Inferential statistics that allow us to infer (or generalize) trends about the larger population based only on the sample portion collected and recorded Metrics that measure some quantity such as distance, similarity, or error and which are especially useful when comparing one or more data observations Recommendation engines representing a set of algorithms designed to predict (or recommend) a particular product, service, or other item of interest a user or customer wishes to buy or utilize in some manner Machine learning implementations and associated algorithms, comprising core data science technologies with many practical applications, especially predictive analytics Natural Language Processing, which expedites the parsing and comprehension of written and spoken language in an effective and accurate manner Time series analysis, techniques to examine and generate forecasts about the progress and evolution of data over time Data science provides the methodology and tools to accurately interpret an increasing volume of incoming information in order to discern patterns, evaluate trends, and make the right decisions. The results of data science analysis provide real world answers to real world questions. Professionals working on data science and business intelligence projects as well as advanced-level students and researchers focused on data science, computer science, business and mathematics programs will benefit from this book.

This book constitutes the refereed proceedings of the 21th International Conference on Information and Communications Security, ICICS 2019, held in Beijing, China, in December 2019. The 47 revised full papers were carefully selected from 199 submissions. The papers are organized in topics on malware analysis and detection, IoT and CPS security enterprise network security, software security, system security, authentication, applied cryptograph internet security, machine learning security, machine learning privacy, Web security, steganography and steganalysis.

Geographic data models are digital frameworks that describe the location and characteristics of things in the world around us. With a geographic information system, we can use these models as lenses to see, interpret, and analyze the infinite complexity of our natural and man-made environments. With the geodatabase, a new geographic data model introduced with ArcInfo 8, you can extend significantly the level of detail and range of accuracy with which you can model geographic reality in a database environment.

Presents the latest techniques for analyzing and extracting information from large amounts of data in high-dimensional data spaces The revised and updated third edition of Data Mining contains in one volume an introduction to a systematic approach to the analysis of large data sets that integrates results from disciplines such as statistics, artificial intelligence, data bases, pattern recognition, and computer visualization. Advances in deep learning technology have opened an entire new spectrum of applications. The author—a noted expert on the topic—explains the basic concepts, models, and methodologies that have been developed in recent years. This new edition introduces and expands on many topics, as well as providing revised sections on software tools and data mining applications. Additional changes include an updated list of references for further study, and an extended list of problems and questions that relate to each chapter.This third edition presents new and expanded information that: • Explores big data and cloud computing • Examines deep learning • Includes information on convolutional neural networks (CNN) • Offers reinforcement learning • Contains semi-supervised learning and S3VM • Reviews model evaluation for unbalanced data Written for graduate students in computer science, computer engineers, and computer information systems professionals, the updated third edition of Data Mining continues to provide an essential guide to the basic principles of the technology and the most recent developments in the field.

A novel theory of argument structure based on the order in which verbs and their arguments combine across a variety of languages and language families. Merge is the structure-building operation in Chomsky’s Minimalist Program. In When Arguments Merge, Elise Newman develops a new Merge-based theory of the syntax of argument structure, taking inspiration from wh- questions. She uncovers new connections between disparate empirical phenomena and provides a unified analysis of patterns across many languages and language families, from Mayan to Bantu to Indo-European languages (among others). The result is a syntactic theory with a small inventory of features and categories that can combine in a limited number of ways, capturing the range of argument configurations that we find cross-linguistically in both declarative and interrogative contexts. Newman’s novel approach to argument structure is based on the time at which different kinds of arguments merge and move in the verbal domain. Assuming that all kinds of Merge are driven by features, she proposes that subset relationships between elements bearing different sets of features can constrain the distribution of arguments in unexpected ways and that different feature bundles can predict unusual interactions between arguments in many contexts. The positions of arguments in different contexts have consequences for agreement alignment and case assignment, which are reflected in the Voice of the clause. Examining the order in which verbs and their arguments are combined, she explores the consequences of different orders of combination for the kinds of utterances observed across languages.