Part I. The Haskell 98 Language: 1 Introduction 2 Lexical structure 3 Expressions 4 Declarations and bindings 5 Modules 6 Predefined types and classes 7 Basic input/output 8 Standard prelude 9 Syntax reference 10 Specification of derived instances 11 Compiler pragmas Part II The Haskell 98 Libraries: 12 Rational numbers 13 Complex numbers 14 Numeric functions 15 Indexing operations 16 Arrays 17 List utilities 18 Maybe utilities 19 Character utilities 20 Monad utilities 21 Input/output 22 Directory functions 23 System functions 24 Dates and times 25 Locales 26 CPU time 27 Random numbers Bibliography.

Haskell 98 language and libraries : the revised report

There is a new generation of emoticons, called emojis, that is increasingly being used in mobile communications and social media. In the past two years, over ten billion emojis were used on Twitter. Emojis are Unicode graphic symbols, used as a shorthand to express concepts and ideas. In contrast to the small number of well-known emoticons that carry clear emotional contents, there are hundreds of emojis. But what are their emotional contents? We provide the first emoji sentiment lexicon, called the Emoji Sentiment Ranking, and draw a sentiment map of the 751 most frequently used emojis. The sentiment of the emojis is computed from the sentiment of the tweets in which they occur. We engaged 83 human annotators to label over 1.6 million tweets in 13 European languages by the sentiment polarity (negative, neutral, or positive). About 4% of the annotated tweets contain emojis. The sentiment analysis of the emojis allows us to draw several interesting conclusions. It turns out that most of the emojis are positive, especially the most popular ones. The sentiment distribution of the tweets with and without emojis is significantly different. The inter-annotator agreement on the tweets with emojis is higher. Emojis tend to occur at the end of the tweets, and their sentiment polarity increases with the distance. We observe no significant differences in the emoji rankings between the 13 languages and the Emoji Sentiment Ranking. Consequently, we propose our Emoji Sentiment Ranking as a European language-independent resource for automated sentiment analysis. Finally, the paper provides a formalization of sentiment and a novel visualization in the form of a sentiment bar.

Sentiment of Emojis.

http://languagelog.ldc.upenn.edu/myl/Barras2001.pdf

Transcriber: Development and use of a tool for assisting speech corpora production

This specification defines the Document Object Model Level 2, a platform- and language-neutral interface that allows programs and scripts to dynamically access and update the content, structure and style of documents. The Document Object Model Level 2 builds on the Document Object Model Level 1. The DOM Level 2 is made of a set of core interfaces to create and manipulate the structure and contents of a document and a set of optional modules. These modules contain specialized interfaces dedicated to XML, HTML, an abstract view, generic stylesheets, Cascading Style Sheets, Events, traversing the

/pdf/document-object-model-dom-level-2-specification-4enq3fv9hy.pdf

Document Object Model (DOM) Level 2 Specification

I - Models and Software Development Introduction Building a Model in VDM++: an Overview VDM++ Tool Support II - Modelling Object-oriented Systems in VDM++ Defining Data Defining Functionality Modelling Unordered Collections Modelling Ordered Collections Modelling Relationships III - Modelling in Practice: Three Case Studies Model Structuring: The Enigma Cipher Combining Views: The CSLaM System TradeOne: From Enterprise Architecture to Business Application IV - From Models to Code Concurrency in VDM++ Model Quality Implementing in Java A - Solutions to exercises Bibliography List of Acronyms Subject Index Definitions Index

Ken Whistler

Papers

The Unicode Standard, Version 3.0