Project to represent Indian languages in a common script. Have chosen Devnagari (as opposed to English) as it seems to represent most languages correctly.
Sources:
Visual - various maths sites (credits to original creator)
Questions - Dong Zong's Textbook
suitable for SUEC (Maths), SPM (Maths and Add Maths) too
[GAN by Hung-yi Lee]Part 1: General introduction of GANNAVER Engineering
Generative Adversarial Network and its Applications on Speech and Natural Language Processing, Part 1.
발표자: Hung-yi Lee(국립 타이완대 교수)
발표일: 18.7.
Generative adversarial network (GAN) is a new idea for training models, in which a generator and a discriminator compete against each other to improve the generation quality. Recently, GAN has shown amazing results in image generation, and a large amount and a wide variety of new ideas, techniques, and applications have been developed based on it. Although there are only few successful cases, GAN has great potential to be applied to text and speech generations to overcome limitations in the conventional methods.
In the first part of the talk, I will first give an introduction of GAN and provide a thorough review about this technology. In the second part, I will focus on the applications of GAN to speech and natural language processing. I will demonstrate the applications of GAN on voice I will also talk about the research directions towards unsupervised speech recognition by GAN.conversion, unsupervised abstractive summarization and sentiment controllable chat-bot.
Children, obey your parents in the Lord: for this is right. Honour thy father and mother; which is the first commandment with promise; That it may be well with thee, and thou mayest live long on the earth. Ephesians 6:1-3
[GAN by Hung-yi Lee]Part 2: The application of GAN to speech and text processingNAVER Engineering
Generative Adversarial Network and its Applications on Speech and Natural Language Processing, Part 2.
발표자: Hung-yi Lee(국립 타이완대 교수)
발표일: 18.7.
Generative adversarial network (GAN) is a new idea for training models, in which a generator and a discriminator compete against each other to improve the generation quality. Recently, GAN has shown amazing results in image generation, and a large amount and a wide variety of new ideas, techniques, and applications have been developed based on it. Although there are only few successful cases, GAN has great potential to be applied to text and speech generations to overcome limitations in the conventional methods.
In the first part of the talk, I will first give an introduction of GAN and provide a thorough review about this technology. In the second part, I will focus on the applications of GAN to speech and natural language processing. I will demonstrate the applications of GAN on voice I will also talk about the research directions towards unsupervised speech recognition by GAN.conversion, unsupervised abstractive summarization and sentiment controllable chat-bot.
Enhancing Performance with Globus and the Science DMZGlobus
ESnet has led the way in helping national facilities—and many other institutions in the research community—configure Science DMZs and troubleshoot network issues to maximize data transfer performance. In this talk we will present a summary of approaches and tips for getting the most out of your network infrastructure using Globus Connect Server.
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
Sources:
Visual - various maths sites (credits to original creator)
Questions - Dong Zong's Textbook
suitable for SUEC (Maths), SPM (Maths and Add Maths) too
[GAN by Hung-yi Lee]Part 1: General introduction of GANNAVER Engineering
Generative Adversarial Network and its Applications on Speech and Natural Language Processing, Part 1.
발표자: Hung-yi Lee(국립 타이완대 교수)
발표일: 18.7.
Generative adversarial network (GAN) is a new idea for training models, in which a generator and a discriminator compete against each other to improve the generation quality. Recently, GAN has shown amazing results in image generation, and a large amount and a wide variety of new ideas, techniques, and applications have been developed based on it. Although there are only few successful cases, GAN has great potential to be applied to text and speech generations to overcome limitations in the conventional methods.
In the first part of the talk, I will first give an introduction of GAN and provide a thorough review about this technology. In the second part, I will focus on the applications of GAN to speech and natural language processing. I will demonstrate the applications of GAN on voice I will also talk about the research directions towards unsupervised speech recognition by GAN.conversion, unsupervised abstractive summarization and sentiment controllable chat-bot.
Children, obey your parents in the Lord: for this is right. Honour thy father and mother; which is the first commandment with promise; That it may be well with thee, and thou mayest live long on the earth. Ephesians 6:1-3
[GAN by Hung-yi Lee]Part 2: The application of GAN to speech and text processingNAVER Engineering
Generative Adversarial Network and its Applications on Speech and Natural Language Processing, Part 2.
발표자: Hung-yi Lee(국립 타이완대 교수)
발표일: 18.7.
Generative adversarial network (GAN) is a new idea for training models, in which a generator and a discriminator compete against each other to improve the generation quality. Recently, GAN has shown amazing results in image generation, and a large amount and a wide variety of new ideas, techniques, and applications have been developed based on it. Although there are only few successful cases, GAN has great potential to be applied to text and speech generations to overcome limitations in the conventional methods.
In the first part of the talk, I will first give an introduction of GAN and provide a thorough review about this technology. In the second part, I will focus on the applications of GAN to speech and natural language processing. I will demonstrate the applications of GAN on voice I will also talk about the research directions towards unsupervised speech recognition by GAN.conversion, unsupervised abstractive summarization and sentiment controllable chat-bot.
Enhancing Performance with Globus and the Science DMZGlobus
ESnet has led the way in helping national facilities—and many other institutions in the research community—configure Science DMZs and troubleshoot network issues to maximize data transfer performance. In this talk we will present a summary of approaches and tips for getting the most out of your network infrastructure using Globus Connect Server.
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
zkStudyClub - Reef: Fast Succinct Non-Interactive Zero-Knowledge Regex ProofsAlex Pruden
This paper presents Reef, a system for generating publicly verifiable succinct non-interactive zero-knowledge proofs that a committed document matches or does not match a regular expression. We describe applications such as proving the strength of passwords, the provenance of email despite redactions, the validity of oblivious DNS queries, and the existence of mutations in DNA. Reef supports the Perl Compatible Regular Expression syntax, including wildcards, alternation, ranges, capture groups, Kleene star, negations, and lookarounds. Reef introduces a new type of automata, Skipping Alternating Finite Automata (SAFA), that skips irrelevant parts of a document when producing proofs without undermining soundness, and instantiates SAFA with a lookup argument. Our experimental evaluation confirms that Reef can generate proofs for documents with 32M characters; the proofs are small and cheap to verify (under a second).
Paper: https://eprint.iacr.org/2023/1886
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Elevating Tactical DDD Patterns Through Object Calisthenics
Devnagari project
1. INTRODUCTION
This work was born out of the idea that can we use the Devanagari script to represent as many Indian
languages as possible, albeit with suitable modifications where necesary. It is an experimental attempt to
write all of them in a common script. I am sure this is something people have thought about, and even
attempted. For example, the Unicode consortium lists symbols for transcription of Dravidian languages in
Devanagari. However, none of these are available to the common man to read and understand.
What differentiates this work from possible other academic works is that articles from various regional
newspapers were chosen for the text. I am grateful to all the authors/newspapers. All copyright rests with
the publishers of the newspapers and/or the respective authors. This compilation does not claim credit for
any of the text, it only renders some of these in the Devanagari script (five of these -viz- Hindi, Marathi,
Nepali, Sanskrit and Konkani were already rendered in this script, these are produced as-is with small
modifications). Also, this compilation doesn't agree or disagree with the contents in the various articles.
These were randomly chosen from the various language newspapers.
Of course language and script are closely linked. However, trying to write various languages in a single
script, in my opinion, could lead to a better understanding of the various languages that make up our
country. Maybe it will show us a way in learning a new language when we move to a new city. After all, a
new script is the biggest barrier to learning a new language. It may also help in NRIs teaching their children
Indian languages.
Requst you all to read it and give inputs on better representation. This is only the first draft – I plan to
correct mistakes as aIso include more langauges in the second draft. I am available at
devnagari.uniscript@gmail.com.
A special mention to Sri Jyothsna (Jo), who worked hard in talking to people regarding this and requesting
them to contribute. This work wouldn't have been possible without her.
Jai Hind !
Aditya Rao
Bangalore
2. ACKNOWLEDGEMENTS
This work wouldn't have been possible without people taking up the idea and actually working on rendering
the various artilces in Devanagari. Following are the contributors who made this experimental task possible:
Language Contributor
Telugu Sri Jyothsna Yeleswarapu
Punjabi Taranveer Singh Bajaj
Kannada Ravishankara Shastry
Gujarati Karan Kaushik
Malayalam Priya Chacko
Bengali Abhishek Jha
Thanks to:
• The Unicode consortium for the code charts (http://www.unicode.org/charts/). The mapping
wouldn't have been possible without these charts.
• Quillpad, a free online Indian language typing tool ( www.quillpad.in). A lot of contributors used it
for easy transliteration into Devanagari.
• The Unicode Character Map utility from http://www-atm.physics.ox.ac.uk/user/iwi/charmap.html.
This helped in rendering Devanagari characters.
• http://anandabazar-unicode.appspot.com/ for the script to convert the selected article from non-
standard Bengali to standard Unicode Bengali. It was disheartening to learn that Anandabazar
Patrika, the largest Indian Bengali news paper, doesn't use a Unicode compliant font.
3. SECTION 1
This section contains articles in languages that are naturally represented in Devanagari. These are
reproduced as-is, with only changes for punctuation (English language punctuation) and numerals (Arabic
numerals) made, where needed. Find below some information on Devanagari reproduced from Wikipedia
(http://en.wikipedia.org/wiki/Devanagari).
Devanagari is the main script used to write Hindi, Marathi, and Nepali. Since the 19th century, Devanagari
has been the most commonly used script for Sanskrit. Devanagari is also employed for Bhojpuri, Gujari,
Pahari (Garhwali and Kumaoni), Konkani, Magahi, Maithili, Marwari, Bhili, Newari, Santhali, Tharu, and
sometimes Sindhi, Dogri, Sherpa and Kashmiri. It was formerly used to write Gujarati.
Although the Devanagari script is used as a standard to write modern Hindi, the schwa (' ə') implicit in each
consonant of the script is "obligatorily deleted" at the end of words and in certain other contexts, unlike in
Sanskrit. This phenomenon has been termed the "schwa syncope rule" or the "schwa deletion rule" of Hindi.
One formalization of this rule has been summarized as ə -> ø | VC_CV. In other words, when a vowel-
preceded consonant is followed by a vowel-succeeded consonant, the schwa inherent in the first consonant
is deleted. However, this formalization is inexact and incomplete (i.e. sometimes deletes a schwa when it
shouldn't or, at other times, fails to delete it when it should), and can yield errors. As a result of schwa
syncope, the Hindi pronunciation of many words differs from that expected from a literal Sanskrit-style
rendering of Devanagari. For instance, र म is Rām (not Rāma), रचन is Rachnā (not Rachanā), वद is Véd (not
Véda) and नमक न is Namkeen (not Namakeen). The name of the script in Hindi itself is pronounced Devnagri
and not Devanagari.
7. ‘आ आ䂁 ’ ∏䂁j䂁 泀7䂁o 䂁 E䂁 䀶 䂁 䂁- S䂁+䂁 蠀 अ@6 ^Ⰰ
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;䂁+蠀 आ䂁蠀. +l d 蠀‡ 䂁. M 䂁 अd अ 蠀 $蠀S䂁 䂁䂁. +䂁EM 䂁 v 䂁 䂁泀W अ +. 泀. 䂁Š䂁[ 䂁 z 䂁 अ 䀶∏क्तϖ
泀 E7䂁o 䂁 आ G 䂁 䂁 [ 䂁‰ 䂁 䂁d 䂁 7蠀 ‹7.
The above article is on the “Lancet India Series” published on the 18 th of January, 2011 in LokSatta, a
leading Marathi Daily. It can be accessed from
8. NEPALI
Original Nepali Article in Devanagari Script
+䂁䂁 䂁 ' 泀d 泀 ∏इ泀䂁蠀 泀䂁 6 +蠀 Œ䂁
h ∏;䂁| W 泀䂁 䂁 छ ∏ 䂁Ⰰ䂁' 䂁a अ 䂁 छ. Œ䂁
h
䂁泀' 泀 䂁䂁 vN+ ;䂁 䂁 छ 泀7䂁 L䂁a Œ䂁 䂁
h 䂁 F∏䂁 ∏ए ∏ए 䂁. Œ䂁
h 䂁䂁蠀tW
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䂁dछ 泀 䂁. अ a Œ䂁 䂁‡ +E∏E आ
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h
50 + 8 ‡泀 䀸Ā 䂁इ 䂁 䂁dछ. Œ䂁 䂁
h ‘䂁 Eइ泀䂁蠀
䂁j7
M 泀7䂁 L䂁a ( 䂁 䂁 छ鞩N 6 Eए +蠀
䂁 ڳ 䂁 䂁; 䂁Ā䂁 Eइ泀䂁蠀
h +蠀 Œ䂁 䂁
h +䂁䂁 䂁 泀䂁 6 䂁dछ. 泀7䂁 L䂁a
䂁 h '
䂁a 䂁 䂁;
h
∏इ泀䂁蠀 छ EF∏泀 d 䂁 ;䂁j d … ˆए छ.
䂁j7
M Œ䂁
h ∏M vN+, + vN+ 泀 䂁䂁 vN+ 䂁
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;䂁 䂁0, 䂁. - द्र䂁a 䂁
䂁j7+蠀
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अ r泀䂁䂁 䂁 䂁 ڳ䂁 +䂁 䂁a+蠀 Œ䂁
h अ)L [䂁 䂁 W 泀䂁 䀸[ d E泀蠀 +蠀 W 泀 䂁 泀䂁 3E ;䂁 泀7 䂁‡
泀$䂁 E A ( 䂁 $ 泀7䂁 L䂁a +䂁䂁 䂁 䂁|
∏䂁䂁 䂁‡ 䂁Āz 泀 Œ䂁
h 泀$䂁 䂁 अ@䂁6 …
( 䂁 泀$䂁 䂁
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䂁 dS 泀䂁 泀 蠀0+蠀 ∏䂁泀 䂁 䂁0䂁 䂁 䂁8+ए 䂁
䂁 䂁a 䂁泀蠀 W+䂁 䂁 E䂁n E 8 F 泀 䂁 䂁 䂁 F d
अd 泀䂁; ( 䂁 泀$7 䂁䂁 䂁@ आ ) 䂁 6ڳ 䂁 G䂁 泀 䂁泀+蠀 ( +䂁ई 2 䂁 o 䂁䀸 蠀 [䂁
2+ 泀 ˜+ 泀 䂁 6 ( एe ) +䂁ई M76 a +蠀 䂁‡䂁䀸 蠀 +™
䂁š E 泀 蠀 छ ∏ 蠀 䂁䂁इŽ 2+ 泀 ˜+ 泀 䂁 6
E 䂁 @ 2030 F M76 a +蠀 ' dS7 E A +™ 泀䂁tWए 䂁ए 䂁 छ …. 泀 蠀0अ 䂁泀 एe -
E
76 a +蠀
M d䂁 E 6 2010 +™ 泀䂁tWए @ 泀 +䂁ई ∏䂁泀 +蠀 䂁䂁8 + E 泀 蠀 छ. ए एe - +䂁ई
∏䂁泀 䂁‡ 2030 - F M76 a +蠀 䂁‡䂁䀸 蠀 +™ 泀䂁tWए छ. ए एe -
E 泀蠀 e 泀蠀‡泀 泀 ए 泀 )dN0 泀
' 䂁6 䂁 “ˆ 䂁 अC $ ए 蠀 0+蠀 䀸 E E +蠀 एe +䂁ई 泀7 a +蠀 䂁‡䂁䀸 䂁 +䂁 E 䂁6䂁泀7
dS䂁+ (
›8 8 +蠀泀 䂁 E泀蠀 泀 ∏;䂁| 䂁 ' 泀 䂁泀8 8 +蠀泀 䂁 E A 䂁 䂁
䂁 䂁 o 䂁ए 䂁 छ …. ( +䂁ई 2 䂁 o 䂁䀸 蠀 एe 䀸[ 6 䂁 @
' d䀶 +E䂁䀸 蠀 F d䀶 䂁
@ G‡
आ 䂁 ' +䂁䂁 泀䂁 6 a 泀蠀W䂁 8 ' 䂁)d• + 80W泀 䂁 d . 䂁6䂁泀7 䂁 j €
9. )d䀶 䂁 @ 1987 䂁 ~ 䂁 䂁 ' d . 1994 䂁 क्त 泀䂁 䂁䂁 ∏䂁+蠀 16 8 F 泀 䂁
[ 蠀 䂁j6
e+ 䂁 䀸 +™ 䂁 ;䂁 ( 䂁䂁 䂁䀸 蠀 ' 76 8+इए 䂁. +䂁䂁 泀䂁 6 䂁 䀸r泀䂁䂁 泀䂁蠀 䂁 䂁 䂁
;䂁8∏d ڳ䂁 +䂁 +䂁ई [ 䂁+ d䂁 E 6 蠀 '
W $ 䂁泀. [䂁䂁a 䀸[ 6 䂁 G 䂁ए泀
䂁0䂁 䂁 䂁 E 6 蠀 䂁Ⰰ䂁' 䂁a ∏ 䂁इ छ. 䂁 泀 䂁泀, 䂁E 泀 䂁 , L䂁 蠀䂁 L@䂁 +蠀 䂁 E
आ䂁b छ +蠀 +䂁䂁 泀䂁 6 䂁泀 䂁 6 Eए 䂁 ;䂁 䂁 䂁
W 䂁䀶 L 6‡ $蠀S+䂁ई '
E䂁䀸 蠀छ.
The above Nepali article is from Rachanakar, Sikkim's first online bi-lingual newspaper, published in
November 2010. It can be accessed from http://www.rachanakaar.com/sampa_nep.html
10. SANSKRIT
Original Sanskrit Article in Devanagari Script
रु- 2011
M 䂁 泀 䂁L j N0 䂁 䂁“ 蠀 ∏䂁 䂁䂁 泀蠀 7䂁6‡ 泀䂁^ L S . ए …. `N 泀•
M रु-
M
80䂁 }E䂁 अd 6E泀 䂁0 ‡ 䂁䂁䂁 L Mरु 80䂁 }E䂁 E泀 80䂁 }E䂁 Mरु
' E 䂁 E 䂁
Mरु E泀L 䂁0 ‡䂁䂁䂁 ' L@䂁 蠀 o 䂁 泀f76-C䂁 … 䀸¤N 䂁䂁䂁
䂁8+ 䂁䂁 …². 7䂁6‡ 泀䂁^ o
蠀 L 䂁 L 䂁
अ; 䂁 䂁 24 䂁 泀䂁䂁䀶䂁䂁蠀䂁 अ ' 䂁6 䂁泀
䂁䂁L ' ˆ ;j 䂁䂁 …². E 䂁jA आ ~ S蠀 7䂁6‡ 泀䂁^ L
泀蠀G䂁䂁䂁 - 䂁 䂁 h 蠀 600 ‡a• 泀8 䀶 泀¦$ 䂁 …². अ)L … 䂁jAऽ; )[ )¨ 䂁;
䂁7 䀶
∏䂁 w rw
䂁䂁L 蠀 इ' ∏䂁7. 蠀dद्र 䂁6 䂁泀L 泀蠀+ 䂁 泀䂁^ 䂁 蠀. ए …. ' • 䂁泀 䂁蠀 अC $L@䂁 蠀
आ …. ∏䂁j 䂁7 7䂁6‡ 泀䂁^ 蠀o अ 蠀 䂁 䂁 泀蠀G䂁䂁䂁 - 䂁 䂁 $䂁 䂁 ‰
䂁泀ª䀶 )L . 䀸r泀 7䂁6‡ vN+蠀o
W vN+L 䂁 F ‰ G ' 䂁 䂁 6d . ए 䂁
蠀 䂁 0«䂁' 0« 蠀䂁 䂁 ' | d 蠀o इ[ 䂁 …. +
∏䂁C $ ए …. ;䂁 䂁@ 䂁' @∏M6[䂁䂁 ∏䂁j 䂁7 Mरु- 蠀“EڠMरु E泀蠀 E+泀蠀G 䂁 䂁E6' 䂁67䂁 ∏M8 L䂁 泀7
L 䂁 䂁 6 .
蠀 䂁 L 䂁 泀℈[ ∏M 蠀 䂁L 䂁d 泀 䂁6 䂁泀 泀 . NE vN+
' 泀蠀G 䂁 ,+- §
G ' w§
रु
M 0䂁+ E泀 䂁 $䂁
䂁泀∏ 䂁8 ' 䀸䂁䂁 . ¯[ 泀蠀+ … 䂁+ L
䀶䂁 ~ 䂁L@䂁 ° +䂁. … 䂁A䂁.
∏䂁j 䂁7 आ 泀䂁+ 䂁 䂁 泀 F∏M 泀7䂁 䂁泀7䂁 … 18% 0 䂁 0 आ ²䂁 䂁 6 蠀. अ ए䂁 अ8∏䂁;
h 䂁 䂁6t7
अ 䀶 䂁 ' अ䂁䂁 …. 䂁 ° ;䂁 䂁@, 䂁䂁 ए …. ए. 泀䂁 䂁䂁 , ;䂁 0“ 泀, 0䂁 ,¡ d䂁 蠀 @, ए ….
[ 䂁泀䂁 7,, 䂁䂁 ,泀 d䂁蠀0 L䂁䂁 , 䀸 䂁䂁 ,泀 ° | + 䂁 Ed 䂁@ … ∏䂁 䂁 )L@ 䂁 आ ….
The above article was published on 17 th of January, 2011 in Sudharma, India's premier Sanskrit Daily. It can
be accessed from http://sudharma.epapertoday.com/epaper/?yr=2011mth=1d=17pg=1
11. KONKANI
Original Article in Devanagari Script
䂁䂁䂁€L 'आ䂁06' इ 䂁泀 䀸N 䂁 䂁 80e䂁泀
䂁䂁䂁€L @䂁 泀G+. 31 आ ڠ蠀 'आ䂁06' इ 䂁泀 F䂁 d 䂁 8∏ 泀 NM 䀸N 䂁 अ0 80e䂁泀 泀
अ䂁䂁䂁+ 鞩द्र. 䂁6䂁泀7 S䂁+ 䂁 䂁+䂁. 䂁6䂁泀7 S䂁+ 䂁 䂁+ 䂁GG 䂁 ' 䂁v 䂁 आ䂁蠀0䂁 䂁. अ 䀶 h इ 䂁泀
泀䂁 N आ 䂁䂁 आ䂁. आ80G+. 0 泀 अ0鞩F䂁7+䂁 .
䂁蠀 इ 䂁泀 +蠀 ˜+l ‡ 泀䂁 䂁泀v 䂁 आ G 䂁 o 䂁 䂁 䂁o 䂁 䂁GG 䂁 䂁䂁䂁 ' 䂁67 䂁G+ . 泀$7 अ 䀶 䂁o 䂁
आ G 䂁 o 䂁 䂁 䂁o 䂁 䂁蠀 ˜+l ‡ 䂁G+蠀 अ0蠀 आ泀 䂁G+蠀 . ´䂁 ˆ ‡䂁• 䂁 W䂁 泀 䂁䂁泀䂁䂁 蠀 आ䂁+蠀 S अ0
~䂁䂁7䂁 आ +鞩 䂁 N 鞩 `NG+鞩.
आ䂁06 䂁 ‡. L䂁 䂁 䂁䂁 F䂁 d 䂁 8∏ 泀 䂁. NM @ 䂁䂁 ' ڠ 泀 䂁䂁 䂁泀䂁䂁 泀 +蠀 अ0鞩
䂁6䂁泀7 S䂁+ 䂁 F䂁7+䂁 .
आ䂁06 䂁 ‡. 䂁 䂁 䂁 a ' आ泀U蠀N' 䂁 䂁 ∏ E 蠀+䂁 अ0鞩 S䂁+ 䂁 F䂁7+䂁 .
आ䂁06 E䂁'
h 䂁67 L@蠀 आ泀U蠀N 䂁 䂁 ∏ E 蠀+䂁. 䂁 7 䂁 [ 泀䂁䂁 } ˆ蠀䂁 䂁 . 䂁蠀WM 䂁 䂁 䂁eϖ 䂁
अ0鞩 䂁6䂁泀7 S 泀䂁 泀 蠀0䂁 F䂁7+䂁 .
The above article is from SunaParant, a Konkani daily from Goa, published on January 18, 2011. It can be
accessed from http://www.goacom.com/sunaparant_download.php?pdf=suna180111.pdf
12. SECTION 2
This section contains articles in languages that are not naturally represented in
Devanagari. This represents the thrust of this experimental work.
13. TELUGU
Telugu to Devanagari Mapping
అ ఆ ఇ ఈ ఉ ఊ ఋౠఌ ౡఎ ఏ ఐ ఒ ఓ ఔ అ蠀 అ蠀
अ आइ ई 䀸 䂁 ¯ ॠ ऌ ॡ ऎ ए ऐ ऒ ( अ अ
క ఖ గ ఘ ఙ చ ఛ జ ఝ ఞ ట థ డ ఢ ణ త థ ద ధ న ప ఫ బ భ మ
W E ˆ ङ छ U ञ ‡ N ƒ 7 @ 䂁 䀶 e ∏
యర ఱ ల ళ వ శ ష స హ క
泀 „ + ڠ䂁 0 j 䂁 $ Ⰰ
Illustration of the mapping
Original Article in Telugu Script Article rendered in Devanagari
ఈ సహ7蠀9: ;蠀 ద=బ:蠀 蠀ర蠀భ蠀6 ᢄڠర䄈 ఒకపక1 తన ఆC‹క పగ ई 䂁½䂁)ª䂁 泀¾ N 䂁 䂁ª䂁
䂁泀 ∏ + ∏䂁泀 … ऒ 2 आ @6
ప=蠀త蠀I Jన7឴ڠసļMļ, మరోపక1 భద។ڠ컬 పరRSన సļళĀĐ
E' '
0䂁d E䂁 䂁 EL M 蠀 泀 2 ∏द्र 䂁 泀
విజయవ蠀త蠀I స蠀ఘC䀸蠀Y蠀దļ ˍ[Ғ. అ7ధారణ రీ6 పెC឴ڠపోయిన 䂁䂁•ڠ ;䂁 䂁 E䂁 ˆ;j6)d 䂁 蠀 ¾• 䂁8+. अ 䂁䀶䂁泀7 泀.' +
¾泀E ' 䂁 ' , ~ M䂁䂁[ 䂁‡䂁 , 䂁 L 䂁 … ऎE䂁 L d
ˍSb cSక, dˁfతgక టవ蠀, కి7Mi ఎగڠసžMనl ఉగļద蠀, ᢄڠర䄈,
䀸€䂁䂁䂁 , ∏䂁泀 …, अ˜ˆ' L 䂁d+ ~ ' 泀蠀 E䂁 अ 䂁 अ 泀L d
అm7Miల※ వˁҐక蠀I అʹ అనžసCసžMనl విధాbలž , పెరžగžతžనl
;䂁䀶䂁 䂁+, ¾रुE d 䂁䂁 ' L‡+ L 䂁 ‡;䂁
L 䂁蠀0
మావోయిసžtల సమసˁ వ蠀₭వి పసžMత蠀 ˞శ蠀 ఎదžw1蠀టžనl భద។ڠ컬 పరRSన
ऎ䂁रु d‡d ∏द्र 䂁 泀 ¾ 䂁䂁•+ڠ )d ! 9 0䂁
పెనž సļళĀ6 Jl! 9=త蠀 అC‹ѐѠవ‣ʹ䄰 పప蠀చ蠀6 ᢄڠర䄈నž సమžYత
आ @6 䂁8∏䂁;
+
h ∏䂁泀Á L@䂁 + ' 8+; 䂁, 䂁䂁'
7‹న蠀6 Ғ b, దా =蠀యžత పగ పథ蠀 ~తM蠀 అవరోధాల మయ蠀!
0䂁)d
E' @ r अ䂁泀 䀶䂁+ ! ∏䂁泀[+ , ;䂁䂁蠀0䂁G+
ᢄڠర䄈6, వి˞=6• ఉనlļCకి АА విసžగž కҒ឴ڠసžMనl ఈ పెనž సļళĀనž
䀸d 䂁䂁 泀 M =䂁 ;䂁 E 8+ ELrd ई ¾ 䂁䂁•ڠ
అధిగƒ蠀„蠀దž※ ఉనlత 7‹యి6 Аw捴 చC捴蠀„蠀దž※ †లžI మన˞శ蠀
अ 䀶E8 鞩䂁 䀸d L@䂁' + M “' ‰ 鞩䂁 䂁+E䂁 䂁蠀0
త឴ڠన అరˋతనž 7ధి蠀Y蠀దా? సļ‹ల ర‰లž సžڍవడ蠀6 Cకితన蠀, E अ䂁6 䂁 䀶 䂁䂁? L@M+ ' 76 䂁+ 䂁N + ; 泀 ,
Đలžమ蠀ద蠀 ఉڠˁ឴7ڠ退మˁ蠀 మ蠀ద•Žతన蠀 వ蠀₭ļ₭ పCⰧ甮Ғ•M ఈ + 䂁,
䀸 EL䂁䂁F , 䂁E䂁`N 䂁 ‡䂁䂁 ‡' 泀08+L 蠀 ई
ద=బ:蠀6 మన蠀 7ధి蠀Yన అరˋత ఏ蠀% అర‹మ’蠀తž蠀ʹ. 䂁 䂁ª䂁 + 䂁 䀶 अ䂁6 ए ‡ अ@6 䂁 䂁.
జమžg ѐⰧ甮g“, అరž”చ• ప˞–ల విషయ蠀6ˍSb అనžసCసžMనl విధాbలపెS F 䂁b 泀, अरु7䂁 +
䂁蠀 ;䂁j + 䂁 अ 泀L d
;䂁䀶䂁 䂁+ 䂁蠀0 ~ क्त 蠀L d आd䂁 , ڠअ- 泀䂁+ अ䂁 ए
మన˞శ蠀 వˁకM蠀 „సžMనl ఆ蠀ڠళన , అభˁ蠀త켨ϖలనž అʹ ఏమాత។蠀 Ǩతరž
䂁S W䂁 रु 蠀 N +蠀䂁! अ + ∏䂁泀 ;䂁j + 䂁 अ 泀 蠀
„యడ蠀 5దž! అసలž ᢄڠర䄈 విషయ蠀6 ڠ컬నž అనžసC蠀„ విధాbl
;䂁䀶䂁 䂁)d 䂁 M N 䂁E䂁 䂁 A8 䂁 蠀 ¾• 䂁8+. 泀¾ N 䂁蠀0䂁+