As of February 2025, English was the most popular language for web content, with over 49.4 percent of websites using it. Spanish ranked second, with six percent of web content, while the content in the German language followed, with 5.6 percent. English as the leading online language United States and India, the countries with the most internet users after China, are also the world's biggest English-speaking markets. The internet user base in both countries combined, as of January 2023, was over a billion individuals. This has led to most of the online information being created in English. Consequently, even those who are not native speakers may use it for convenience. Global internet usage by regions As of October 2024, the number of internet users worldwide was 5.52 billion. In the same period, Northern Europe and North America were leading in terms of internet penetration rates worldwide, with around 97 percent of its populations accessing the internet.

The PerfLoc Prize Competition (https://perfloc.nist.gov) was developed by NIST during 2015-2017 and was run during 2017-2018. The Competition was concluded with a single winner on May 16, 2018. However, NIST believes the data collected for the PerfLoc Competition is still of value to the R&D community, because there is still room to develop better signal processing and data fusion algorithms that would fuse various types of smartphone data collected in this project to develop indoor localization apps with higher localization accuracy. For that reason, NIST continues to make the PerfLoc data available to the R&D community.One thing has changed compared to when the PerfLoc Competition was running in 2017-2018. It is no longer possible for app developers to upload the location estimates generated by their apps at the PerfLoc website for performance evaluation purposes and to get statistics of localization accuracy. However, the PerfLoc data is still useful, because there is training data with ground-truth location annotation that would be useful to anyone wishing to develop indoor localization apps and getting an idea of the performance of their apps.“There are a total of 14 files that can be downloaded from this web page (see below). The descriptions for these files can be found at the relevant PerfLoc web pages (https://www.nist.gov/ctl/pscr/perfloc-user-guide and https://www.nist.gov/ctl/pscr/perfloc-data.”

This statistic shows the usage of translation services for foreign shopping websites in the Nordics in 2015. 16 percent of respondents from Denmark, Norway and Sweden stated that they have used an online translation tool to help them to make a purchase from a foreign website.

Translation Services Market size was valued at USD 1.55 Billion in 2024 and is projected to reach USD 1.85 Billion by 2031, growing at a CAGR of 2.02% from 2024 to 2031.

The growing demand for non-English languages will drive the translation services market. As globalization progresses, organizations are increasingly reaching out to non-English speaking regions, demanding content translation into multiple local languages in order to effectively interact with broad audiences.

One of the primary factors driving this trend is the expanding economic dominance of emerging markets like China, India and Brazil. These countries have big populations with inadequate English ability; thus, firms must supply content in native languages in order to effectively reach these markets. Furthermore, the growth of the internet and digital platforms have made it simpler for businesses to reach and target worldwide audiences, hence increasing the demand for multilingual content.

Furthermore, industries such as healthcare, legal and education are experiencing a surge in demand for translation services to meet the different linguistic backgrounds of their clients and stakeholders. Governments and multinational organizations also demand translation services to improve cross-border communication and collaboration.

The rise of social media and user-generated content has also increased demand for translation services, as organizations attempt to maintain a consistent and engaging presence in multiple languages and areas. As a result, the growing relevance of non-English languages is a major driver of the translation services market’s growth and change.

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 15, 2013. TRIPLES provides full public access to the data and reagents generated from ongoing functional analysis of the yeast genome. Using a novel transposon-tagging approach, we have analyzed disruption phenotypes, gene expression, and protein localization on a genome-wide scale in Saccharomyces. The data generated from this study may be accessed through our database, TRIPLES ; additionally, all reagents generated in this study are freely available from on-line order forms (linked to TRIPLES as well). multipurpose, mini-transposon, mutant alleles, phenotypes, protein localization, gene expression, Saccharomyces cerevisiae, Web-accessible database, transposon-mutagenized yeast strains, downloaded, tab-delimited, text file, protein localization data, fluorescent micrographs, staining patterns, indirect immunofluorescence analysis of indicated epitope-tagged proteins, subcellular localization of the yeast proteome, visual library, Nucleic Acid Sequence Data Library (GenBank), clone report, graphic map, transposon insertions (represented as flags)

Intramolecular transfer of phosphate during collision-induced dissociation (CID) in ion-trap mass spectrometers has recently been described. Because phosphorylation events are assigned to discrete serine, threonine, and tyrosine residues based on the presence of site-determining ions in MS/MS spectra, phosphate transfer may invalidate or confound site localization in published large-scale phosphorylation data sets. Here, we present evidence for the occurrence of this phenomenon using synthetic phosphopeptide libraries, specifically for doubly charged species. We found, however, that the extent of the transfer reaction was insufficient to cause localization of phosphorylation sites to incorrect residues. We further compared CID to electron-transfer dissociation (ETD) for site localization using synthetic libraries and a large-scale yeast phosphoproteome experiment. The agreement in site localization was >99.5 and 93%, respectively, suggesting that ETD-based site localization is no more reliable than CID. We conclude that intramolecular phosphate transfer does not affect the reliability of current or past phosphorylation data sets.

HindEnCorp parallel texts (sentence-aligned) come from the following sources:

Tides, which contains 50K sentence pairs taken mainly from news articles. This dataset was originally col- lected for the DARPA-TIDES surprise-language con- test in 2002, later refined at IIIT Hyderabad and provided for the NLP Tools Contest at ICON 2008 (Venkatapathy, 2008).

Commentaries by Daniel Pipes contain 322 articles in English written by a journalist Daniel Pipes and translated into Hindi.

EMILLE. This corpus (Baker et al., 2002) consists of three components: monolingual, parallel and annotated corpora. There are fourteen monolingual sub- corpora, including both written and (for some lan- guages) spoken data for fourteen South Asian lan- guages. The EMILLE monolingual corpora contain in total 92,799,000 words (including 2,627,000 words of transcribed spoken data for Bengali, Gujarati, Hindi, Punjabi and Urdu). The parallel corpus consists of 200,000 words of text in English and its accompanying translations into Hindi and other languages.

Smaller datasets as collected by Bojar et al. (2010) include the corpus used at ACL 2005 (a subcorpus of EMILLE), a corpus of named entities from Wikipedia (crawled in 2009), and Agriculture domain parallel corpus.



For the current release, we are extending the parallel corpus using these sources:

Intercorp (Čermák and Rosen,2012) is a large multilingual parallel corpus of 32 languages including Hindi. The central language used for alignment is Czech. Intercorp’s core texts amount to 202 million words. These core texts are most suitable for us because their sentence alignment is manually checked and therefore very reliable. They cover predominately short sto- ries and novels. There are seven Hindi texts in Inter- corp. Unfortunately, only for three of them the English translation is available; the other four are aligned only with Czech texts. The Hindi subcorpus of Intercorp contains 118,000 words in Hindi.

TED talks 3 held in various languages, primarily English, are equipped with transcripts and these are translated into 102 languages. There are 179 talks for which Hindi translation is available.

The Indic multi-parallel corpus (Birch et al., 2011; Post et al., 2012) is a corpus of texts from Wikipedia translated from the respective Indian language into English by non-expert translators hired over Mechanical Turk. The quality is thus somewhat mixed in many respects starting from typesetting and punctuation over capi- talization, spelling, word choice to sentence structure. A little bit of control could be in principle obtained from the fact that every input sentence was translated 4 times. We used the 2012 release of the corpus.

Launchpad.net is a software collaboration platform that hosts many open-source projects and facilitates also collaborative localization of the tools. We downloaded all revisions of all the hosted projects and extracted the localization (.po) files.

Other smaller datasets. This time, we added Wikipedia entities as crawled in 2013 (including any morphological variants of the named entitity that appears on the Hindi variant of the Wikipedia page) and words, word examples and quotes from the Shabdkosh online dictionary.

The dataset used for the Ptakopět experiment on outbound machine translation. It consists of screenshots of web forms with user queries entered. The queries are available also in a text form. The dataset comprises two language versions: English and Czech. Whereas the English version has been fully post-processed (screenshots cropped, queries within the screenshots highlighted, dataset split based on its quality etc.), the Czech version is raw as it was collected by the annotators.

Data from Transnationalizing Modern Languages (09-2018)

Transnationalizing Modern Languages: Mobility, Identity and Translation in Modern Italian Cultures (TML) (funded by the AHRC under the ‘Translating Cultures’ theme, 2014-17)

PI Charles Burdett, University of Bristol. CIs Jenny Burns (Warwick), Loredana Polezzi (Warwick/Cardiff), Derek Duncan (St Andrews), Margaret Hills de Zarate (QMU)

RAs: Barbara Spadaro (Bristol), Carlo Pirozzi (St Andrews), Marco Santello (Warwick), Naomi Wells (Warwick), Luisa Percopo (Cardiff)

PhD students: Iacopo Colombini (St Andrews), Georgia Wall (Warwick)

Below is a short description of the project. Within the repository, there is a longer description of TML and each folder is accompanied by an explanatory text.

The project investigates practices of linguistic and cultural interchange within communities and individuals and explores the ways in which cultural translation intersects with linguistic translation in the everyday lives of people. The project has used as its primary object of enquiry the 150-year history of Italy as a nation state and its patterns of emigration and immigration. TML has concentrated on a series of exemplary cases, representative of the geographic, historical and linguistic map of Italian mobility. Focussing on the cultural associations that each community has formed, it examines the wealth of publications and materials that are associated with these organizations.

Working closely with researchers from across Modern Languages, the project has sought to demonstrate the principle that language is most productively apprehended in the frame of translation and the national in the frame of the transnational. TML is contributing to the development of a new framework for the disciplinary field of MLs, one which puts the interaction of languages and cultures at its core.

The principles of co-production and co-research lie at the core of the project and TML has worked closely with a very extensive range of partners. It has worked closely with Castlebrae and Drummond Community High Schools and with cultural associations across the world. The project exhibition, featuring the research of the project and including the work of photographer Mario Badagliacca, was curated by Viviana Gravano and Giulia Grechi of Routes Agency. Project events in the UK have drawn on the expertise of Rita Wilson (Monash), the writer Shirin Ramzanali Fazel and all members of the Advisory Board. The project, in close collaboration with the University of Namibia (UNAM) and the Phoenix Project (Cardiff), has been followed by ‘TML: Global Challenges’.

An algorithm for the assignment of phosphorylation sites in peptides is described. The program uses tandem mass spectrometry data in conjunction with the respective peptide sequences to calculate site probabilities for all potential phosphorylation sites. Tandem mass spectra from synthetic phosphopeptides were used for optimization of the scoring parameters employing all commonly used fragmentation techniques. Calculation of probabilities was adapted to the different fragmentation methods and to the maximum mass deviation of the analysis. The software includes a novel approach to peak extraction, required for matching experimental data to the theoretical values of all isoforms, by defining individual peak depths for the different regions of the tandem mass spectrum. Mixtures of synthetic phosphopeptides were used to validate the program by calculation of its false localization rate versus site probability cutoff characteristic. Notably, the empirical obtained precision was higher than indicated by the applied probability cutoff. In addition, the performance of the algorithm was compared to existing approaches to site localization such as Ascore. In order to assess the practical applicability of the algorithm to large data sets, phosphopeptides from a biological sample were analyzed, localizing more than 3000 nonredundant phosphorylation sites. Finally, the results obtained for the different fragmentation methods and localization tools were compared and discussed.

Experimental data for "Data on localization of the T-DNA insertion site in Arabidopsis line SALK_146824C" manuscript

As of 2024, 99 percent of adults in the United States between 18 and 49 years were internet users, making it the age group with the highest level of internet penetration in the country. A further share of 97 percent of adults using the internet were between 18 and 29 years old. Mobile internet usage Mobile internet usage continues to surge in the United States, with 96.2 percent of internet users accessing the web via phones as of the third quarter of 2023. In April 2024, YouTube's mobile app led with a 74 percent audience reach, while TikTok topped weekly engagement among social apps. Mobile apps and privacy Mobile apps became an essential part of mobile users, this high usage raised new concerns about data privacy. By June 2023, three in four internet users supported data localization to protect their information. Additionally, As of September 2024, 13.5 percent of paid iOS apps stated that they collected user data, with 88 percent of this data used to enhance app functionality.

News translation is a recurring WMT task. The test set is a collection of parallel corpora consisting of about 1500 English sentences translated into 5 languages (Chinese, Czech, Estonian, German, Finnish, Russian, Turkish) and additional 1500 sentences from each of the 7 languages translated to English. The sentences were selected from dozens of news websites and translated by professional translators.

The training data consists of parallel corpora to train translation models, monolingual corpora to train language models and development sets for tuning. Some training corpora were identical from WMT 2017 (Europarl, Common Crawl, SETIMES2, Russian-English parallel data provided by Yandex, Wikipedia Headlines provided by CMU) and some were update (United Nations, CzEng v1.7, News Commentary v13, monolingual news data). Additionally, the EU Press Release parallel corpus for German, Finnish and Estonian was added.

AbstractIntroduction NIST 2008 Open Machine Translation (OpenMT) Evaluation, Linguistic Data Consortium (LDC) catalog number LDC2010T21 and isbn 1-58563-567-7, is a package containing source data, reference translations and scoring software used in the NIST 2008 OpenMT evaluation. It is designed to help evaluate the effectiveness of machine translation systems. The package was compiled and scoring software was developed by researchers at NIST, making use of broadcast, newswire and web data and reference translations collected and developed by LDC. The objective of the NIST Open Machine Translation (OpenMT) evaluation series is to support research in, and help advance the state of the art of, machine translation (MT) technologies -- technologies that translate text between human languages. Input may include all forms of text. The goal is for the output to be an adequate and fluent translation of the original. The MT evaluation series started in 2001 as part of the DARPA TIDES (Translingual Information Detection, Extraction) program. Beginning with the 2006 evaluation, the evaluations have been driven and coordinated by NIST as NIST OpenMT. These evaluations provide an important contribution to the direction of research efforts and the calibration of technical capabilities in MT. The OpenMT evaluations are intended to be of interest to all researchers working on the general problem of automatic translation between human languages. To this end, they are designed to be simple, to focus on core technology issues and to be fully supported. The 2008 task was to evaluate translation from Arabic to English, Chinese to English, English to Chinese (newswire only) and Urdu to English. Selected human reference translations and system translations for the NIST MT08 test sets are contained in NIST Open Machine Translation 2008 Evaluation (MT08) Selected Reference and System Translations LDC2010T01. Additional information about these evaluations may be found at the NIST Open Machine Translation (OpenMT) Evaluation website. Data This release contains 494 documents with corresponding sets of four separate human expert reference translations. The source data is comprised of Arabic, Chinese, English and Urdu newswire, broadcast and weblog and newsgroup data collected by LDC in 2007. The newswire and broadcast material are from Asharq Al-Awsat (Arabic), Agence France-Presse (Arabic, Chinese, English), Al-Ahram (Arabic), Al Hayat (Arabic), Assabah (Arabic), An Nahar (Arabic), Al-Quds Al-Arabi (Arabic), Xinhua News Agency (Arabic, Chinese, English), Central News Service (Chinese), Guangming Daily (Chinese), People's Daily (Chinese), People's Liberation Army Daily (Chinese), British Broadcasting Corporation (Urdu), Daily Jang (Urdu), Pakistan News Service (Urdu), Voice of America (Urdu), Associated Press (English), New York Times (English) and Los Angeles Times/Washington Post Newswire Service (English). For each language, the test set consists of two files: a source and a reference file. Each file contains four independent translations of the data set. The evaluation year, source language, test set (which, by default, is "evalset"), version of the data, and source vs. reference file (with the latter being indicated by "-ref") are reflected in the file name. A reference file contains four independent reference translations unless noted otherwise in the accompanying README.txt. DARPA TIDES MT and NIST OpenMT evaluations used SGML-formatted test data until 2008 and XML-formatted test data thereafter. This files in this package are povided in both formats.

Machine Translation Software: Provides AI-powered translation across multiple languages.Translation Management Systems: Manages translation projects, workflows, and quality control.Cloud-based Translation Platforms: Offer scalable and on-demand translation services.Neural Machine Translation (NMT) Tools: Enables highly accurate and fluent translations.Customization and Integration: Services provide tailored solutions and integrate with other systems to enhance efficiency. Recent developments include: Feb 2023: RWS has announced the launch of its TrainAI brand, which will provide clients with full, end-to-end data collection, annotation, and validation services for all types of AI data - in any language, at any scale. TrainAI will also offer machine translation and AI training data services to enhance the quality of machine learning models and AI applications for the biggest organizations in the world., Sept 2022: A language services provider in the MENA region created Tarjama, an Arabic machine translation (AMT) website called Tarjama Translate, with a focus on companies who want quick access to translation in order to reach Arabic-speaking customers..

This dataset was created in October-December 2022 for the National Library of Scotland's Data Foundry by Gustavo Candela, National Librarian’s Research Fellowship in Digital Scholarship 2022-23.

This output is based on the Bibliography of Scottish Literature in Translation (BOSLIT) dataset and is the result of the transformation to RDF described in a research article published in the Journal of Information Science.

For more information about the project, visit the Data Foundry Fellowship page.

References

Candela, G. (2023). Towards a semantic approach in GLAM Labs: The case of the Data Foundry at the National Library of Scotland. Journal of Information Science. https://doi.org/10.1177/01655515231174386

Crowdsourced Testing Market Valuation – 2024-2031

Crowdsourced Testing Market was valued at USD 1.83 Billion in 2024 and is projected to reach USD 3.51 Billion by 2031, growing at a CAGR of 9.37% from 2024 to 2031.

Global Crowdsourced Testing Market Drivers

Cost-Effectiveness: Crowdsourced testing offers a cost-effective alternative to traditional in-house testing teams. By leveraging a global network of testers, companies can reduce overhead costs and achieve faster time-to-market.

Scalability: Crowdsourced testing provides unparalleled scalability. Companies can quickly scale up or down their testing efforts to meet specific project demands without incurring significant overhead costs.

Diverse Testing Coverage: A global network of testers can provide diverse perspectives and test scenarios, ensuring comprehensive coverage of different devices, operating systems, and geographic locations.

Global Crowdsourced Testing Market Restraints

Quality Concerns: Ensuring consistent quality and reliability can be a challenge in a distributed testing environment. Companies need to implement effective quality assurance measures to mitigate risks.

Security Risks: Data privacy and security concerns are paramount in crowdsourced testing. Companies must have robust security protocols in place to protect sensitive information.

This data set accompanies "An Automated Radio-Telemetry System (ARTS) for Monitoring Small Mammals".

The behavior of small fossorial mammals, such as voles, is extremely difficult to observe in natural environments. Small mammals were traditionally studied with labor intensive methods such as trapping and recapture or radio telemetry via homing, which require week/months of work and produce static home range estimates.

In pursuit of better understanding natural history and behavioral ecology we implemented an automated radio telemetry system (ARTS) to continuously monitor small mammals. We used an isotropic antenna array coupled with broadband receivers to estimate animal positions with nonlinear least squares, nonparameteric, and Bayesian trilateration methods. We then used Lomb-Scargle periodograms to estimate activity patterns of freely-behaving Prairie voles.

List of all documents included in the corpus of a study assessing the extent to which linguistic diversity is taken into account in strategic planning for HIV/AIDS health care and communication in development contexts. The study is entitled 'Multilingualism and strategic planning for HIV/AIDS-related health care and communication' and is available from Wellcome Open Research. The corpus comprises all policy documents and reports relevant to HIV/AIDS health care and communication authored by the Department for International Development, UK, The Global Fund, and the Ministries of Health and National AIDS commissions in Burkina Faso, Ghana and Senegal. Documents were selected for analysis following principles of systematicity and comprehensiveness. For each of the organisations or government departments in question, we used their official websites to search for all documents relevant to HIV/AIDS. We limited the scope only by document type, restricting our corpus to policy documents (including funding guidelines) and reports, rather than encompassing a broader range of documents such as press releases or research papers. We did not limit the searches by date, including in the corpus any policy documents or reports which the organisation or government department in question made available via their website during the periods in which we gathered our data (November-December 2018 and May-July 2019). In cases where the government website was not functioning, we identified relevant documents through step-by-step processes which are described in detail in the research article itself.