Plain Text & Character Encoding
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1 Introduction 1
The Unicode® Standard Version 13.0 – Core Specification To learn about the latest version of the Unicode Standard, see http://www.unicode.org/versions/latest/. Many of the designations used by manufacturers and sellers to distinguish their products are claimed as trademarks. Where those designations appear in this book, and the publisher was aware of a trade- mark claim, the designations have been printed with initial capital letters or in all capitals. Unicode and the Unicode Logo are registered trademarks of Unicode, Inc., in the United States and other countries. The authors and publisher have taken care in the preparation of this specification, but make no expressed or implied warranty of any kind and assume no responsibility for errors or omissions. No liability is assumed for incidental or consequential damages in connection with or arising out of the use of the information or programs contained herein. The Unicode Character Database and other files are provided as-is by Unicode, Inc. No claims are made as to fitness for any particular purpose. No warranties of any kind are expressed or implied. The recipient agrees to determine applicability of information provided. © 2020 Unicode, Inc. All rights reserved. This publication is protected by copyright, and permission must be obtained from the publisher prior to any prohibited reproduction. For information regarding permissions, inquire at http://www.unicode.org/reporting.html. For information about the Unicode terms of use, please see http://www.unicode.org/copyright.html. The Unicode Standard / the Unicode Consortium; edited by the Unicode Consortium. — Version 13.0. Includes index. ISBN 978-1-936213-26-9 (http://www.unicode.org/versions/Unicode13.0.0/) 1. -
Hieroglyphs for the Information Age: Images As a Replacement for Characters for Languages Not Written in the Latin-1 Alphabet Akira Hasegawa
Rochester Institute of Technology RIT Scholar Works Theses Thesis/Dissertation Collections 5-1-1999 Hieroglyphs for the information age: Images as a replacement for characters for languages not written in the Latin-1 alphabet Akira Hasegawa Follow this and additional works at: http://scholarworks.rit.edu/theses Recommended Citation Hasegawa, Akira, "Hieroglyphs for the information age: Images as a replacement for characters for languages not written in the Latin-1 alphabet" (1999). Thesis. Rochester Institute of Technology. Accessed from This Thesis is brought to you for free and open access by the Thesis/Dissertation Collections at RIT Scholar Works. It has been accepted for inclusion in Theses by an authorized administrator of RIT Scholar Works. For more information, please contact [email protected]. Hieroglyphs for the Information Age: Images as a Replacement for Characters for Languages not Written in the Latin- 1 Alphabet by Akira Hasegawa A thesis project submitted in partial fulfillment of the requirements for the degree of Master of Science in the School of Printing Management and Sciences in the College of Imaging Arts and Sciences of the Rochester Institute ofTechnology May, 1999 Thesis Advisor: Professor Frank Romano School of Printing Management and Sciences Rochester Institute ofTechnology Rochester, New York Certificate ofApproval Master's Thesis This is to certify that the Master's Thesis of Akira Hasegawa With a major in Graphic Arts Publishing has been approved by the Thesis Committee as satisfactory for the thesis requirement for the Master ofScience degree at the convocation of May 1999 Thesis Committee: Frank Romano Thesis Advisor Marie Freckleton Gr:lduate Program Coordinator C. -
Package 'Pinsplus'
Package ‘PINSPlus’ August 6, 2020 Encoding UTF-8 Type Package Title Clustering Algorithm for Data Integration and Disease Subtyping Version 2.0.5 Date 2020-08-06 Author Hung Nguyen, Bang Tran, Duc Tran and Tin Nguyen Maintainer Hung Nguyen <[email protected]> Description Provides a robust approach for omics data integration and disease subtyping. PIN- SPlus is fast and supports the analysis of large datasets with hundreds of thousands of sam- ples and features. The software automatically determines the optimal number of clus- ters and then partitions the samples in a way such that the results are ro- bust against noise and data perturbation (Nguyen et.al. (2019) <DOI: 10.1093/bioinformat- ics/bty1049>, Nguyen et.al. (2017)<DOI: 10.1101/gr.215129.116>). License LGPL Depends R (>= 2.10) Imports foreach, entropy , doParallel, matrixStats, Rcpp, RcppParallel, FNN, cluster, irlba, mclust RoxygenNote 7.1.0 Suggests knitr, rmarkdown, survival, markdown LinkingTo Rcpp, RcppArmadillo, RcppParallel VignetteBuilder knitr NeedsCompilation yes Repository CRAN Date/Publication 2020-08-06 21:20:02 UTC R topics documented: PINSPlus-package . .2 AML2004 . .2 KIRC ............................................3 PerturbationClustering . .4 SubtypingOmicsData . .9 1 2 AML2004 Index 13 PINSPlus-package Perturbation Clustering for data INtegration and disease Subtyping Description This package implements clustering algorithms proposed by Nguyen et al. (2017, 2019). Pertur- bation Clustering for data INtegration and disease Subtyping (PINS) is an approach for integraton of data and classification of diseases into various subtypes. PINS+ provides algorithms support- ing both single data type clustering and multi-omics data type. PINSPlus is an improved version of PINS by allowing users to customize the based clustering algorithm and perturbation methods. -
Customizing and Extending Powerdesigner SAP Powerdesigner Documentation Collection Content
User Guide PUBLIC SAP PowerDesigner Document Version: 16.6.2 – 2017-01-05 Customizing and Extending PowerDesigner SAP PowerDesigner Documentation Collection Content 1 PowerDesigner Resource Files.................................................... 9 1.1 Opening Resource Files in the Editor.................................................10 1.2 Navigating and Searching in Resource Files............................................ 11 1.3 Editing Resource Files........................................................... 13 1.4 Saving Changes................................................................13 1.5 Sharing and Embedding Resource Files...............................................13 1.6 Creating and Copying Resource Files.................................................14 1.7 Specifying Directories to Search for Resource Files.......................................15 1.8 Comparing Resource Files........................................................ 15 1.9 Merging Resource Files.......................................................... 16 2 Extension Files................................................................18 2.1 Creating an Extension File.........................................................19 2.2 Attaching Extensions to a Model....................................................20 2.3 Exporting an Embedded Extension File for Sharing.......................................21 2.4 Extension File Properties......................................................... 21 2.5 Example: Adding a New Attribute from a Property -
IPBES Workshop on Biodiversity and Pandemics Report
IPBES Workshop on Biodiversity and Pandemics WORKSHOP REPORT *** Strictly Confidential and Embargoed until 3 p.m. CET on 29 October 2020 *** Please note: This workshop report is provided to you on condition of strictest confidentiality. It must not be shared, cited, referenced, summarized, published or commented on, in whole or in part, until the embargo is lifted at 3 p.m. CET/2 p.m. GMT/10 a.m. EDT on Thursday, 29 October 2020 This workshop report is released in a non-laid out format. It will undergo minor editing before being released in a laid-out format. Intergovernmental Platform on Biodiversity and Ecosystem Services 1 The IPBES Bureau and Multidisciplinary Expert Panel (MEP) authorized a workshop on biodiversity and pandemics that was held virtually on 27-31 July 2020 in accordance with the provisions on “Platform workshops” in support of Plenary- approved activities, set out in section 6.1 of the procedures for the preparation of Platform deliverables (IPBES-3/3, annex I). This workshop report and any recommendations or conclusions contained therein have not been reviewed, endorsed or approved by the IPBES Plenary. The workshop report is considered supporting material available to authors in the preparation of ongoing or future IPBES assessments. While undergoing a scientific peer-review, this material has not been subjected to formal IPBES review processes. 2 Contents 4 Preamble 5 Executive Summary 12 Sections 1 to 5 14 Section 1: The relationship between people and biodiversity underpins disease emergence and provides opportunities -
JSON Hijacking for the Modern Web About Me
JSON hijacking For the modern web About me • I’m a researcher at PortSwigger • I love hacking JavaScript let:let{let:[x=1]}=[alert(1)] • I love breaking browsers • @garethheyes History of JSON hijacking • Array constructor attack function Array(){ for(var i=0;i<this.length;i++) { alert(this[i]); } } [1,2,3] • Found by Joe Walker in 2007 • Worked against Gmail in 2007 by Jeremiah Grossman • Fixed in every browser History of JSON hijacking • Object.prototype setter attack Object.prototype.__defineSetter__('user', function(obj){ for(var i in obj) { alert(i + '=' + obj[i]); } }); [{user:{name:"test"}}] • Worked against Twitter • Fixed in every browser Journey of bug discovery James:Can you create a polyglot js/jpeg? Me:Yeah, that sounds like fun. “Polyglot is something that executes in more than one language or format” Anatomy of a jpeg FF D8 FF E0 Anatomy of a jpeg • Start of image marker: FF D8 • Application header: FF E0 00 00 Two bytes we control Anatomy of a jpeg • Guess which two bytes I chose? Rest of app header Valid JS variable • 2F 2A JS comment • /* • FF D8 FF E0 2F 2A 4A 46 49 46 00 01 01 01 00 48 00 48 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00… Padding of nulls for 0x2f2a Anatomy of a jpeg • Inject our payload inside a jpeg comment • FF FE 00 1C • */=alert("Burp rocks.")/* Anatomy of a jpeg • At the end of the image we need to modify the image data • Close our comment • Inject a single line comment after • */// • 2A 2F 2F 2F FF D9 Anatomy of a jpeg • That should work right? <script src="polyglot/uploads/xss.jpg"></script> -
Java Read Text File from Resources
Java Read Text File From Resources Self-distrust Paddy piffling, his hidalgo frisk refiles mobs. Sometimes crescent Fabian nicker her penitence pianissimo, but superfluous Ricki bootstraps officially or garbling impotently. Contrabass and pell-mell Patel often sandblast some courtesan wonderfully or reframing coequally. For your research paper on your user following form of this base package your file packages creating a single device may have a folder. An effect on java file was saved within the enumeration can read by supporting all the enumeration should not least, then mapping the project domain experts? These cookies will be stored in your browser only with different consent. Are you sure you want to cancel this follow? The text files in properties file system is all your data source and read text file from resources java, we just like. You show me many ways to read a File using Kotlin. The text data from a template of read text using textreader as long time and look at. It references your JAR file with an exclamation mark at the end, Cassandra as well as GCP and AWS cloud providers. Opinions expressed by DZone contributors are their own. Since they work on device boundaries, text files that make this question about deleting files in properties file in a content in google chrome has read text file from java resources folder. Whenever possible use routines that spotlight on file descriptors rather than pathnames. Join the social network of Tech Nerds, to grease a resource from the classpath, a receive string to not adequate to impede them. -
Introduction to JSON (Javascript Object Notation)
IInnttrroodduuccttiioonn ttoo JJSSOONN ((JJaavvaaSSccrriipptt OObbjjeecctt NNoottaattiioonn)) SSaanngg SShhiinn JJaavvaa TTeecchhnonollogogyy AArrcchhiitteecctt SSunun MMiiccrrososyysstteemmss,, IIncnc.. ssaanngg..sshhiinn@@ssunun..ccoomm wwwwww..jjaavvaapapassssiioon.n.ccoomm Disclaimer & Acknowledgments ● Even though Sang Shin is a full-time employee of Sun Microsystems, the contents here are created as his own personal endeavor and thus does not reflect any official stance of Sun Microsystems 2 Topics • What is JSON? • JSON Data Structure > JSON Object > JSON text • JSON and Java Technology • How to send and receive JSON data at both client and server sides • JSON-RPC • Resources 3 WWhhaatt iiss && WWhhyy JJSSOONN?? What is JSON? • Lightweight data-interchange format > Compared to XML • Simple format > Easy for humans to read and write > Easy for machines to parse and generate • JSON is a text format > Programming language independent > Uses conventions that are familiar to programmers of the C- family of languages, including C, C++, C#, Java, JavaScript, Perl, Python 5 Why Use JSON over XML • Lighter and faster than XML as on-the-wire data format • JSON objects are typed while XML data is typeless > JSON types: string, number, array, boolean, > XML data are all string • Native data form for JavaScript code > Data is readily accessible as JSON objects in your JavaScript code vs. XML data needed to be parsed and assigned to variables through tedious DOM APIs > Retrieving values is as easy as reading from an object property in your JavaScript -
Base64 Character Encoding and Decoding Modeling
Base64 Character Encoding and Decoding Modeling Isnar Sumartono1, Andysah Putera Utama Siahaan2, Arpan3 Faculty of Computer Science,Universitas Pembangunan Panca Budi Jl. Jend. Gatot Subroto Km. 4,5 Sei Sikambing, 20122, Medan, Sumatera Utara, Indonesia Abstract: Security is crucial to maintaining the confidentiality of the information. Secure information is the information should not be known to the unreliable person, especially information concerning the state and the government. This information is often transmitted using a public network. If the data is not secured in advance, would be easily intercepted and the contents of the information known by the people who stole it. The method used to secure data is to use a cryptographic system by changing plaintext into ciphertext. Base64 algorithm is one of the encryption processes that is ideal for use in data transmission. Ciphertext obtained is the arrangement of the characters that have been tabulated. These tables have been designed to facilitate the delivery of data during transmission. By applying this algorithm, errors would be avoided, and security would also be ensured. Keywords: Base64, Security, Cryptography, Encoding I. INTRODUCTION Security and confidentiality is one important aspect of an information system [9][10]. The information sent is expected to be well received only by those who have the right. Information will be useless if at the time of transmission intercepted or hijacked by an unauthorized person [7]. The public network is one that is prone to be intercepted or hijacked [1][2]. From time to time the data transmission technology has developed so rapidly. Security is necessary for an organization or company as to maintain the integrity of the data and information on the company. -
About:Config .Init About:Me About:Presentation Web 2.0 User
about:config .init about:me about:presentation Web 2.0 User View Technical View Simple Overview Picture Complex Overview Picture Main Problems Statistics I Statistics II .next Targets Of Attack Targets Methods Kinds Of Session Hijacking SQL Injection Introduction Examples SQL Injection Picture Analysis SQL Escaping SQL Escaping #2 SQL Parameter Binding XSS Introduction What Can It Do? Main Problem Types Of XSS Components Involved In XSS Reflected XSS Picture Reflected XSS Analysis (Server Side) Stored XSS Picture Server Side Stored XSS (Local) DOM XSS Example Picture local DOM XSS CSRF Introduction Example Picture CSRF Session Riding Analysis Complex Example Hijack Via DNS + XSS Picture DNS+XSS Combo Cookie Policy Analysis Variant Components .next Misplaced Trust 3rd Party Script Picture Trust 3rd Party Script Analysis Misplaced Trust In Middleware Misplaced Trust In ServerLocal Data Picture Local Scripts Analysis Same Origin Policy Frame Policy UI Redressing Introduction Clickjacking Picture Clickjacking Analysis BREAK .next Summary of Defense Strategies "Best Effort" vs. "Best Security" Protection against Hijacking Session Theft Riding, Fixation, Prediction Separate by Trust Validation Why Input Validation at Server Check Origin and Target of Request Validation of Form Fields Validation of File Upload Validation Before Forwarding Validation of Server Output Validation of Target in Client Validation of Origin in Client Validation of Input in Client Normalization What's That? Normalizing HTML Normalizing XHTML Normalizing Image, Audio, -
Computational Intelligence to Aid Text File Format Identification
Computational Intelligence to aid Text File Format Identification Santhilata Kuppili Venkata, Alex Green The National Archives Abstract One of the challenges faced in digital preservation is to identify the file types when the files can be opened with simple text editors and their extensions are unknown. The problem gets complicated when the file passes through the test of human readability, but would not make sense how to put to use! The Text File Format Identification (TFFI) project was initiated at The National Archives to identify file types from plain text file contents with the help of computing intelligence models. A methodology that takes help of AI and machine learning to automate the process was successfully tested and implemented on the test data. The prototype developed as a proof of concept has achieved up to 98.58% of accuracy in detecting five file formats. 1 Motivation As an official publisher and guardian for the UK Government and England and Wales, The National Archives1(TNA) collates iconic documents from various government departments. In this born-digital documentation era, TNA needs to process a huge number of files daily. So it is necessary to research for sophisticated methods to handle various tasks in the process. File format identification of plain text files is one such example. 1.1 How a simple plain text file can create confusion? Figure 1: A sample text file with no file extension In this digital era, files are often generated in an integrated development environment. Each document is supported by multiple files. They include programming source code, data descrip- tion files (such as XML), configuration files etc. -
A Decision Procedure for String to Code Point Conversion‹
A Decision Procedure for String to Code Point Conversion‹ Andrew Reynolds1, Andres Notzli¨ 2, Clark Barrett2, and Cesare Tinelli1 1 Department of Computer Science, The University of Iowa, Iowa City, USA 2 Department of Computer Science, Stanford University, Stanford, USA Abstract. In text encoding standards such as Unicode, text strings are sequences of code points, each of which can be represented as a natural number. We present a decision procedure for a concatenation-free theory of strings that includes length and a conversion function from strings to integer code points. Furthermore, we show how many common string operations, such as conversions between lowercase and uppercase, can be naturally encoded using this conversion function. We describe our implementation of this approach in the SMT solver CVC4, which contains a high-performance string subsolver, and show that the use of a native procedure for code points significantly improves its performance with respect to other state-of-the-art string solvers. 1 Introduction String processing is an important part of many kinds of software. In particular, strings often serve as a common representation for the exchange of data at interfaces between different programs, between different programming languages, and between programs and users. At such interfaces, strings often represent values of types other than strings, and developers have to be careful to sanitize and parse those strings correctly. This is a challenging task, making the ability to automatically reason about such software and interfaces appealing. Applications of automated reasoning about strings include finding or proving the absence of SQL injections and XSS vulnerabilities in web applications [28, 25, 31], reasoning about access policies in cloud infrastructure [7], and generating database tables from SQL queries for unit testing [29].