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Journal articles on the topic 'DeepL'

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Published: 4 June 2021
Last updated: 25 April 2022

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1

Sparenberg, J. M. "Deepl-Independent Potentials from Supersymmetric Inversion." Physical Review Letters 85, no. 13 (September 25, 2000): 2661–64. http://dx.doi.org/10.1103/physrevlett.85.2661.

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Handzel, Zbigniew. "TRANSLATOR DeepL – PRZEŁOM W TŁUMACZENIU KOMPUTEROWYM." ELEKTRONIKA - KONSTRUKCJE, TECHNOLOGIE, ZASTOSOWANIA 1, no. 6 (June 30, 2021): 22–24. http://dx.doi.org/10.15199/13.2021.6.3.

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3

Krüger, Ralph. "Explicitation in Neural Machine Translation." Across Languages and Cultures 21, no. 2 (December 1, 2020): 195–216. http://dx.doi.org/10.1556/084.2020.00012.

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This paper is concerned with the following question: to what extent does neural machine translation (NMT) – a relatively new approach to machine translation (MT), which can draw on richer contextual information than previous MT architectures – perform explicitation shifts in translation and how are these shifts realised in linguistic terms? In order to answer this question, the paper attempts to identify instances of explicitation in the machine-translated version of a research report on carbon dioxide capture and storage. The machine-translated text was created using the publicly available generic NMT system DeepL. The human translation of the research report was analysed in a prior research project for instances of explicitation and implicitation (Krüger 2015). After a brief quantitative di scussion of the frequency and distribution of explicitation shifts identified in the DeepL output as compared to the shifts identified in the human translation of the research report, the paper analyses in detail several examples in which DeepL performed explicitation shifts of various kinds. The quantitative and qualitative analyses are intended to yield a tentative picture of the capacity of state-of-the art neural machine translation systems to perform explicitation shifts in translation. As explicitation is understood in this article as an indicator of translational text–context interaction, the explicitation performance of NMT can – to some extent – be taken to be indicative of the “contextual awareness” of this new MT architecture.
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4

Roiss, Silvia, and Petra Zimmermann González. "DeepL y su potencial para el desarrollo de la capacidad de análisis crítico en la clase de Traducción inversa." Hermēneus. Revista de traducción e interpretación, no. 22 (February 1, 2021): 363–82. http://dx.doi.org/10.24197/her.22.2020.363-382.

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En nuestras clases de Traducción Inversa hemos observado que los alumnos poco experimentados confían de manera casi ciega en el traductor automático DeepL, alentados por el lema de la propia empresa, que lo define como «el mejor traductor del mundo». Nos hemos propuesto corregir el uso indiscriminado del programa y promover un aprendizaje que se centraba en dos objetivos: (1) Que el alumno valore la competencia traductora humana por encima del potencial de DeepL. (2) Que el alumno tome consciencia de la necesidad de una serie de actuaciones para asegurar el uso seguro del traductor automático. A este efecto, organizamos los ejercicios en tres fases: A) Fase de activación: partimos de traducciones fallidas, ofrecidas por el programa, enfocados a reforzar la autoestima del estudiante. B) Fase de profundización: con la ayuda de un catálogo de preguntas concisas, intentamos sensibilizarle para las prestaciones ofrecidas por el programa. C) Fase de consolidación: se organiza el saber adquirido en las fases anteriores.
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Ziganshina, Liliya Eugenevna, Ekaterina V. Yudina, Azat I. Gabdrakhmanov, and Juliane Ried. "Assessing Human Post-Editing Efforts to Compare the Performance of Three Machine Translation Engines for English to Russian Translation of Cochrane Plain Language Health Information: Results of a Randomised Comparison." Informatics 8, no. 1 (February 10, 2021): 9. http://dx.doi.org/10.3390/informatics8010009.

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Cochrane produces independent research to improve healthcare decisions. It translates its research summaries into different languages to enable wider access, relying largely on volunteers. Machine translation (MT) could facilitate efficiency in Cochrane’s low-resource environment. We compared three off-the-shelf machine translation engines (MTEs)—DeepL, Google Translate and Microsoft Translator—for Russian translations of Cochrane plain language summaries (PLSs) by assessing the quantitative human post-editing effort within an established translation workflow and quality assurance process. 30 PLSs each were pre-translated with one of the three MTEs. Ten volunteer translators post-edited nine randomly assigned PLSs each—three per MTE—in their usual translation system, Memsource. Two editors performed a second editing step. Memsource’s Machine Translation Quality Estimation (MTQE) feature provided an artificial intelligence (AI)-powered estimate of how much editing would be required for each PLS, and the analysis feature calculated the amount of human editing after each editing step. Google Translate performed the best with highest average quality estimates for its initial MT output, and the lowest amount of human post-editing. DeepL performed slightly worse, and Microsoft Translator worst. Future developments in MT research and the associated industry may change our results.
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Heinze, A. N., Philip M. Hinz, Matthew Kenworthy, Douglas Miller, and Suresh Sivanandam. "DeepL'‐ andM‐band Imaging for Planets around Vega and ε Eridani." Astrophysical Journal 688, no. 1 (November 20, 2008): 583–96. http://dx.doi.org/10.1086/592100.

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7

Hidalgo-Ternero, Carlos Manuel, and Gloria Corpas Pastor. "Bridging the “gApp”: improving neural machine translation systems for multiword expression detection." Yearbook of Phraseology 11, no. 1 (November 25, 2020): 61–80. http://dx.doi.org/10.1515/phras-2020-0005.

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AbstractThe present research introduces the tool gApp, a Python-based text preprocessing system for the automatic identification and conversion of discontinuous multiword expressions (MWEs) into their continuous form in order to enhance neural machine translation (NMT). To this end, an experiment with semi-fixed verb–noun idiomatic combinations (VNICs) will be carried out in order to evaluate to what extent gApp can optimise the performance of the two main free open-source NMT systems —Google Translate and DeepL— under the challenge of MWE discontinuity in the Spanish into English directionality. In the light of our promising results, the study concludes with suggestions on how to further optimise MWE-aware NMT systems.
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8

Borges, Thais Miranda e., and Janine Maria Mendonça Pimentel. "Avaliação humana da tradução automática de combinações lexicais especializadas: o caso do Google Translate e do DeepL." Belas Infiéis 9, no. 4 (July 29, 2020): 21–43. http://dx.doi.org/10.26512/belasinfieis.v9.n4.2020.26755.

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Este trabalho se propõe a avaliar a tradução automática feita pelos sistemas Google Translate e DeepL especificamente em relação a combinações lexicais especializadas (L’HOMME; BERTRAND, 2000) compostas por verbo+substantivo extraídas de textos jurídicos chamados “cláusulas arbitrais”. Nós apresentamos uma metodologia para selecionar as combinações lexicais especializadas e avaliar a adequação e a fluência das traduções produzidas pelos sistemas em questão. Os resultados obtidos estão alinhados com recentes pesquisas na área de tradução automática baseada em redes neurais (NMT) que indicam que esse tipo de tecnologia tem um desempenho melhor no parâmetro “fluência” do que no parâmetro “adequação” (KOEHN; KNOWLES, 2017). Em relação à precisão terminológica, houve ocorrências de tradução de termos diferentes na língua-fonte para o mesmo termo na língua-alvo em uma mesma frase, o que muitas vezes pode ser inadequado em textos técnicos e contraria a percepção bastante comum de que a tradução automática produz resultados consistentes, sendo mais adequada à tradução especializada. Ainda assim, e apesar das limitações apontadas neste estudo, as avaliações das traduções das combinações lexicais foram bastante satisfatórias.
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9

Falcão, Carolina. "Da Ruptura à Releitura: transformações nos Direitos Humanos no Brasil dos anos 2010." Brasiliana: Journal for Brazilian Studies 10, no. 1 (October 2, 2021): 29–48. http://dx.doi.org/10.25160/bjbs.v10i1.126101.

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In this paper, I propose an analysis of the 2010s in Brazil based on two events that took place in the field of Human Rights in the country: the election of deputy Marco Feliciano for the presidency of the Federal Chamber's Human Rights and Minorities Commission (CDHM), in 2013 and the creation, in 2019, of the Ministry of Women, Family and Human Rights (MMFDH) under the command of Damares Alves. The two facts, read respectively as rupture and re-reading, disclose a correlation of forces that suggests how the Human Rights agenda legitimizes and enhances a given religious agency in the current national political scenario. This scenario, I argue, becomes viable from the discourse against the “gender ideology” in the field of institutional policy in the country, which supported the deepl changes that took place in the course of that decade.
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Roiss, Silvia. "Y las máquinas rompieron a traducir… Consideraciones didácticas en relación con la traducción automática de referencias culturales en el ámbito jurídico." TRANS. Revista de Traductología, no. 25 (December 30, 2021): 491–505. http://dx.doi.org/10.24310/trans.2021.v1i25.11978.

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En esta contribución destacaremos la vulnerabilidad de DeepL en relación con la traducción automática al español de referencias culturales en el ámbito jurídico, concretamente del término jurídico alemán Landgericht. Las incongruencias en el nivel semántico, mayoritariamente, se producen porque la herramienta trabaja desde el enfoque oracional en vez del textual. Por esta razón, daremos unas pautas didácticas acerca de cómo enfrentar este problema en el aula, especialmente en la fase de posedición. En este sentido, ahondamos en cuatro criterios concretos: el criterio material, el criterio de composición, el criterio de jerarquización y el criterio territorial y los completamos con un análisis textual multinivel de la clase textual en cuestión (apostilla). El fin último es ofrecerle al alumno una guía muy completa para que pueda enfrentarse a este desafío con garantías. Lo aquí expuesto es el resultado parcial de un proyecto de innovación docente dirigido por la autora de este artículo.
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11

Bowker, Lynne. "Machine translation and author keywords: A viable search strategy for scholars with limited English proficiency?" Advances in Classification Research Online 29, no. 1 (June 28, 2019): 13. http://dx.doi.org/10.7152/acro.v29i1.15455.

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Author keywords are valuable for indexing articles and for information retrieval (IR). Most scientific literature is published in English. Can machine translation (MT) help researchers with limited English proficiency to search for information? We used two MT systems (Google Translate, DeepL Translator) to translate into English 71 Spanish keywords and 43 French keywords from articles in the domain of Library and Information Science. We then used the English translations to search the Library, Information Science and Technology Abstracts (LISTA) database. Half of the translated keywords returned relevant results. Of the half that did not, 34% were well translated but did not align with LISTA descriptors. Translation-related problems stemming from orthographic variation, synonymy, differing syntactic preferences, and semantic field coverage interfered with IR in just 16% of cases. Some of the MT errors are relatively “predictable” and if knowledge organization systems could be augmented to deal with them, then MT may prove even more useful for searching.
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12

Kur, Maciej. "Method of measuring the effort related to post-editing machine translated outputs produced in the English>Polish language pair by Google, Microsoft and DeepL MT engines: A pilot study." Beyond Philology An International Journal of Linguistics, Literary Studies and English Language Teaching, no. 16/4 (December 11, 2019): 69–99. http://dx.doi.org/10.26881/bp.2019.4.03.

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This article presents the methodology and results of a pilot study concerning the impact of three popular and widely accessible machine translation engines (developed by Google, Microsoft and DeepL companies) on the pace of post-editing work and on the general effort related to post-editing of raw MT outputs. Fourteen volunteers were asked to translate and post-edit two source texts of similar characters and levels of complexity. The results of their work were collected and compared to develop a set of quantitative and qualitative data, which was later used to make assumptions related to the general rate of postediting work and the quality of the post-edited sentences produced by the subjects. The aim of the pilot study described below was to determine whether the applied method can be successfully used in more profound studies on the quality and impact of machine translation in the English->Polish language pair and on the potential of MT solutions on the Polish translation market.
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13

Martikainen, Hanna. "Post-Editing Neural MT in Medical LSP: Lexico-Grammatical Patterns and Distortion in the Communication of Specialized Knowledge." Informatics 6, no. 3 (June 30, 2019): 26. http://dx.doi.org/10.3390/informatics6030026.

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The recent arrival on the market of high-performing neural MT engines will likely lead to a profound transformation of the translation profession. The purpose of this study is to explore how this paradigm change impacts the post-editing process, with a focus on lexico-grammatical patterns that are used in the communication of specialized knowledge. A corpus of 109 medical abstracts pre-translated from English into French by the neural MT engine DeepL and post-edited by master’s students in translation was used to study potential distortions in the translation of lexico-grammatical patterns. The results suggest that neural MT leads to specific sources of distortion in the translation of these patterns, not unlike what has previously been observed in human translation. These observations highlight the need to pay particular attention to lexico-grammatical patterns when post-editing neural MT in order to achieve functional equivalence in the translation of specialized texts.
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Webster, Rebecca, Margot Fonteyne, Arda Tezcan, Lieve Macken, and Joke Daems. "Gutenberg Goes Neural: Comparing Features of Dutch Human Translations with Raw Neural Machine Translation Outputs in a Corpus of English Literary Classics." Informatics 7, no. 3 (August 28, 2020): 32. http://dx.doi.org/10.3390/informatics7030032.

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Due to the growing success of neural machine translation (NMT), many have started to question its applicability within the field of literary translation. In order to grasp the possibilities of NMT, we studied the output of the neural machine system of Google Translate (GNMT) and DeepL when applied to four classic novels translated from English into Dutch. The quality of the NMT systems is discussed by focusing on manual annotations, and we also employed various metrics in order to get an insight into lexical richness, local cohesion, syntactic, and stylistic difference. Firstly, we discovered that a large proportion of the translated sentences contained errors. We also observed a lower level of lexical richness and local cohesion in the NMTs compared to the human translations. In addition, NMTs are more likely to follow the syntactic structure of a source sentence, whereas human translations can differ. Lastly, the human translations deviate from the machine translations in style.
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Maldonado González, María Concepción, and María Liébana González. "Los motores de traducción automática y su uso como herramienta lexicográfica en la traducción de unidades léxicas aisladas." Círculo de Lingüística Aplicada a la Comunicación 88 (October 7, 2021): 189–212. http://dx.doi.org/10.5209/clac.77002.

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Este trabajo ofrece un breve repaso de algunos de los principales sistemas de traducción automática (TA) que conviven actualmente en el mercado, así como de los problemas más comunes a los que nos exponemos al hacer uso de la traducción automática en la traducción de unidades léxicas aisladas, fuera de contexto. El objetivo es señalar, o al menos cuestionar, las limitaciones lingüísticas que presentan los motores de TA y reflexionar sobre la necesidad de incorporar datos lexicográficos a los mismos, con el fin de mejorar su rendimiento. Para ello, evaluaremos, desde un enfoque práctico, el comportamiento de Google Traductor, Bing Microsoft Translator y el traductor de DeepL, en la traducción de unidades léxicas aisladas. Compararemos los resultados que habríamos obtenido si, para las mismas tareas, hubiéramos recurrido a diccionarios bilingües en vez de a motores de TA. Constataremos que la respuesta generada por los motores de TA resulta insuficiente para solucionar con precisión nuestras dudas, y que los datos lexicográficos recogidos en diferentes diccionarios bilingües en línea, por lo general, aportan información lexicográfica más completa y adecuada para satisfacer las necesidades comunicativas del usuario.
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Schmitt, Peter A. "Translation 4.0 – Evolution, Revolution, Innovation or Disruption?" Lebende Sprachen 64, no. 2 (November 5, 2019): 193–229. http://dx.doi.org/10.1515/les-2019-0013.

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Abstract The international translation industry is undergoing fundamental changes with the potential of disrupting the market and the business basis of many freelance translators. This paper outlines the present scenario in the field of non-literary translations, its development, reasons, symptoms and current trends. Analogous to the established concept of “Industry 4.0”, the philosophy of an emerging new translation industry can be called “Translation 4.0”. Challenged by a continuously growing demand for translations, increasingly volatile markets, fierce global competition and aggressive pricing, the translation industry is responding with fully digitized data handling, real-time project management, strictly organized processes, quality control, short response times and comprehensive added-value services for clients. Key variables in this new work environment are fragmentation of projects to accelerate turn-around times, outsourcing, crowdsourcing, teamworking, connectivity, cloud-based translation platforms, integrated – and often compulsory – translation tools and, last but not least, machine translation (MT) and post-editing of MT (PEMT). Due to the closing gap between the quality of human translations (HT) and neural MT (in particular of DeepL), MT will cover a growing share of the low-end translation market volume, with the consequence that translators who cannot offer a substantially better value (i. e. quality/price ratio) than MT will become obsolete. The future will be for translators who have the competencies defined in the EMT (European Masters’ of Translation) and who adapt to the changing translation ecosystem.
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WIESMANN, Eva. "MACHINE TRANSLATION IN THE FIELD OF LAW: A STUDY OF THE TRANSLATION OF ITALIAN LEGAL TEXTS INTO GERMAN." Comparative Legilinguistics 37 (October 23, 2019): 117–53. http://dx.doi.org/10.14746/cl.2019.37.4.

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With the advent of the neural paradigm, machine translation has made another leap in quality. As a result, its use by trainee translators has increased considerably, which cannot be disregarded in translation pedagogy. However, since legal texts have features that pose major challenges to machine translation, the question arises as to what extent machine translation is now capable of translating legal texts or at least certain types of legal text into another legal language well enough so that the post-editing effort is limited, and, consequently, whether a targeted use in translation pedagogy can be considered. In order to answer this question, DeepL Translator, a machine translation system, and MateCat, a CAT system that integrates machine translation, were tested. The test, undertaken at different times and without specific translation memories, provided for the translation of several legal texts of different types utilising both systems, and was followed by systematisation of errors and evaluation of translation results. The evaluation was carried out according to the following criteria: 1) comprehensibility and meaningfulness of the target text; and 2) correspondence between source and target text in consideration of the specific translation situation. Overall, the results are considered insufficient to give post-editing of machine-translated legal texts a bigger place in translation pedagogy. As the evaluation of the correspondence between source and target text was fundamentally worse than with regard to the meaningfulness of the target text, translation pedagogy should respond by raising awareness about differences between machine translation output and human translation in this field, and by improving translation approach and strengthening legal expertise.
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Park, Ingyu, and Unjoo Lee. "Automatic, Qualitative Scoring of the Clock Drawing Test (CDT) Based on U-Net, CNN and Mobile Sensor Data." Sensors 21, no. 15 (August 3, 2021): 5239. http://dx.doi.org/10.3390/s21155239.

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The Clock Drawing Test (CDT) is a rapid, inexpensive, and popular screening tool for cognitive functions. In spite of its qualitative capabilities in diagnosis of neurological diseases, the assessment of the CDT has depended on quantitative methods as well as manual paper based methods. Furthermore, due to the impact of the advancement of mobile smart devices imbedding several sensors and deep learning algorithms, the necessity of a standardized, qualitative, and automatic scoring system for CDT has been increased. This study presents a mobile phone application, mCDT, for the CDT and suggests a novel, automatic and qualitative scoring method using mobile sensor data and deep learning algorithms: CNN, a convolutional network, U-Net, a convolutional network for biomedical image segmentation, and the MNIST (Modified National Institute of Standards and Technology) database. To obtain DeepC, a trained model for segmenting a contour image from a hand drawn clock image, U-Net was trained with 159 CDT hand-drawn images at 128 × 128 resolution, obtained via mCDT. To construct DeepH, a trained model for segmenting the hands in a clock image, U-Net was trained with the same 159 CDT 128 × 128 resolution images. For obtaining DeepN, a trained model for classifying the digit images from a hand drawn clock image, CNN was trained with the MNIST database. Using DeepC, DeepH and DeepN with the sensor data, parameters of contour (0–3 points), numbers (0–4 points), hands (0–5 points), and the center (0–1 points) were scored for a total of 13 points. From 219 subjects, performance testing was completed with images and sensor data obtained via mCDT. For an objective performance analysis, all the images were scored and crosschecked by two clinical experts in CDT scaling. Performance test analysis derived a sensitivity, specificity, accuracy and precision for the contour parameter of 89.33, 92.68, 89.95 and 98.15%, for the hands parameter of 80.21, 95.93, 89.04 and 93.90%, for the numbers parameter of 83.87, 95.31, 87.21 and 97.74%, and for the center parameter of 98.42, 86.21, 96.80 and 97.91%, respectively. From these results, the mCDT application and its scoring system provide utility in differentiating dementia disease subtypes, being valuable in clinical practice and for studies in the field.
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Vercauteren, Gert, Nina Reviers, and Kim Steyaert. "Evaluating the effectiveness of machine translation of audio description: the results of two pilot studies in the English-Dutch language pair." Tradumàtica: tecnologies de la traducció, no. 19 (December 31, 2021): 226–52. http://dx.doi.org/10.5565/rev/tradumatica.288.

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The field of translation is undergoing various profound changes. On the one hand it is being thoroughly reshaped by the advent and constant improvement of new technologies. On the other hand, new forms of translation are starting to see the light of day in the wake of social and legal developments that require that products and content that are created, are accessible for everybody. One of these new forms of translation, is audio description (AD), a service that is aimed at making audiovisual content accessible to people with sight loss. New legislation requires that this content is accessible by 2025, which constitutes a tremendous task given the limited number of people that are at present trained as audio describers. A possible solution would be to use machine translation to translate existing audio descriptions into different languages. Since AD is characterized by short sentences and simple, concrete language, it could be a good candidate for machine translation. In the present study, we want to test this hypothesis for the English-Dutch language pair. Three 30 minute AD excerpts of different Dutch movies that were originally audio described in English, were translated into Dutch using DeepL. The translations were analysed using the harmonized DQF-MQM error typology and taking into account the specific multimodal nature of the source text and the intersemiotic dimension of the original audio description process. The analysis showed that the MT output had a relatively high error rate, particularly in the categories of Accuracy – mistranslation and Fluency – grammar. This seems to indicate that extensive post-editing will be needed, before the text can be used in a professional context.
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林玉惠, 林玉惠. "探討機器翻譯中美味表現之日譯中問題—從翻譯教學的觀點來分析—." 台灣應用日語研究 28, no. 28 (December 2021): 001–32. http://dx.doi.org/10.53106/199875792021120028001.

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<p>本文從翻譯教學實踐出發，以表達美味的詞語為對象，整理出日漢機器翻譯的特點和問題，且比較了兩種翻譯機輸出的譯文，並根據問卷調查的結果，提出了使用日漢機器翻譯時應注意的事項。本文的目的是整理機器翻譯的特點和問題，幫助設計能夠支持學習者的翻譯課。從問卷調查的結果得知：翻譯班的學生對機器翻譯 2（DeepL）的結果比機器翻譯 1（Google）更滿意、機器翻譯對約半數的學生有幫助、70%以上的學生經常使用機器翻譯等。另外，透過本文的調查與分析，使用日漢機器翻譯時應注意以下幾點：（1）聽覺和觸覺相關譯詞的問題主要集中在 &quot;ABAB &quot;型擬聲擬態詞以及 &quot;擬聲擬態詞+と+動詞&quot;、（2）嗅覺相關譯詞的問題多為機器翻譯無法判斷正面或負面的詞意、（3）味覺相關譯詞的問題主要為表達多種口味的譯詞常被誤譯、（4）整體來說，機器翻譯存在著無法配合上下文挑選適當詞語或用法、無法辨識詞語的細微差別和漏譯等問題。</p> <p>&nbsp;</p><p>This paper presents the characteristics and problems of Japanese-Chinese machine translation from the perspective of translation teaching practice, compares the output of two types of translation machines, and suggests things to note when using Japanese-Chinese machine translation based on the results of a questionnaire survey. The purpose of this paper is to organize the characteristics and problems of machine translation and to help design translation lessons that support learning. The results of the survey showed that students in the translation class were more satisfied with the results of Machine Translation 2(DeepL)than Machine Translation 1 (Google), that Machine Translation was helpful to about half of the students, and that more than 70% of the students used Machine Translation frequently. In addition, through the survey and analysis in this paper, the following points should be noted when using Japanese-Chinese machine translation: (1) The problems of auditory and tactile related translations mainly focus on the &quot;&quot;ABAB&quot;&quot; type of prosody and &quot;&quot;prosody + and + verb&quot;&quot;. (2) The problems of olfactory related translations are mostly due to the inability of machine translation to determine the positive or negative meaning of words. (3) The problems of taste related translations are mainly due to the fact that words expressing multiple flavors are often mis-translated. (4) Overall, machine translators are unable to select appropriate words or usage to match the context, and are unable to recognize subtle differences in words and mis-translations.</p> <p>&nbsp;</p>
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Koo, David C. "First Science Results from the DEIMOS/DEEP2 Redshift Survey." Symposium - International Astronomical Union 216 (2005): 353–62. http://dx.doi.org/10.1017/s0074180900196780.

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DEEP2 is a major new Keck spectroscopic survey of 50,000 galaxies that aims to provide a detailed map of the cosmos at redshift z ∼ 1. We present an overview of DEEP2 and its relation to DEEP and its predecessor (DEEP1) in terms of science goals, of the instrument DEIMOS that enables completion of this survey in only a few years, and of the current status of the project. First science projects that use the first 10% of the survey data and their early results are highlighted.
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Zhou, Rongpu, Michael C. Cooper, Jeffrey A. Newman, Matthew L. N. Ashby, James Aird, Christopher J. Conselice, Marc Davis, et al. "Deep ugrizY imaging and DEEP2/3 spectroscopy: a photometric redshift testbed for LSST and public release of data from the DEEP3 Galaxy Redshift Survey." Monthly Notices of the Royal Astronomical Society 488, no. 4 (July 25, 2019): 4565–84. http://dx.doi.org/10.1093/mnras/stz1866.

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ABSTRACT We present catalogues of calibrated photometry and spectroscopic redshifts in the Extended Groth Strip, intended for studies of photometric redshifts (photo-z’s). The data includes ugriz photometry from Canada–France–Hawaii Telescope Legacy Survey (CFHTLS) and Y-band photometry from the Subaru Suprime camera, as well as spectroscopic redshifts from the DEEP2, DEEP3, and 3D-HST surveys. These catalogues incorporate corrections to produce effectively matched-aperture photometry across all bands, based upon object size information available in the catalogue and Moffat profile point spread function fits. We test this catalogue with a simple machine learning-based photometric redshift algorithm based upon Random Forest regression, and find that the corrected aperture photometry leads to significant improvement in photo-z accuracy compared to the original SExtractor catalogues from CFHTLS and Subaru. The deep ugrizY photometry and spectroscopic redshifts are well suited for empirical tests of photometric redshift algorithms for LSST. The resulting catalogues are publicly available at http://d-scholarship.pitt.edu/36064/. We include a basic summary of the strategy of the DEEP3 Galaxy Redshift Survey to accompany the recent public release of DEEP3 data.
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Chagas, Edgar Thiago De Oliveira. "Deep Learning e suas aplicações na atualidade." Revista Científica Multidisciplinar Núcleo do Conhecimento 04, no. 05 (May 8, 2019): 05–26. http://dx.doi.org/10.32749/nucleodoconhecimento.com.br/administracao/deep-learning.

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Dill, H., and H. J. Ulrich. "Geoelectric deep sounding - a contribution to constraining the genesis of siliceous ferromanganese duricrusts on deeply weathered Palaeozoic basement rocks (N Bavaria, FR of Germany)." Zeitschrift für Geomorphologie 31, no. 3 (September 30, 1987): 361–70. http://dx.doi.org/10.1127/zfg/31/1987/361.

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25

Ma, Qianli, Lifeng Shen, and Garrison W. Cottrell. "DeePr-ESN: A deep projection-encoding echo-state network." Information Sciences 511 (February 2020): 152–71. http://dx.doi.org/10.1016/j.ins.2019.09.049.

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Stein, Randy, and Alexander B. Swan. "Deeply Confusing: Conflating Difficulty With Deep Revelation on Personality Assessment." Social Psychological and Personality Science 10, no. 4 (April 4, 2018): 514–21. http://dx.doi.org/10.1177/1948550618766409.

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The factors that contribute to lay expectations of personality assessments are not well understood. Five studies demonstrate that people conflate difficulty of personality assessment items with revelations of deep insights. As a result, popular yet invalid assessments of personality can be seen as “deeper” than assessments from social and personality psychology. In Study 1, participants evaluated items from a popular personality “type” assessment as more difficult and better at revealing deep insights into personality than Big-Five personality inventory items. Studies 2 and 3 replicate this effect experimentally using a manipulation of assessment items’ difficulty. Studies 4 and 5 show that the same effect also holds for a less direct method of supposed personality assessment (e.g., assessments that ask about which colors are associated with trivial concepts). Moderating factors and the popularity of shoddy personality assessments are discussed.
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Nguyen, Thi Phuong Trang, Trong Hai Duong, and Ngan Luu Thuy Nguyen. "DeepO: An ontology-based deep learning system for disease prediction." International Journal of Intelligent Information and Database Systems 1, no. 1 (2021): 1. http://dx.doi.org/10.1504/ijiids.2021.10039599.

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Nguyen, Thi Phuong Trang, Ngan Luu Thuy Nguyen, and Trong Hai Duong. "DeepO: an ontology-based deep learning system for disease prediction." International Journal of Intelligent Information and Database Systems 15, no. 2 (2022): 166. http://dx.doi.org/10.1504/ijiids.2022.121897.

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Fang, Lidong, Pei Ge, Lei Zhang, Weinan E. null, and Huan Lei. "DeePN$^2$: A Deep Learning-Based Non-Newtonian Hydrodynamic Model." Journal of Machine Learning 1, no. 1 (June 2022): 114–40. http://dx.doi.org/10.4208/jml.220115.

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Takahashi, Satoshi. "Deep Color." Journal of The Institute of Image Information and Television Engineers 65, no. 9 (2011): 1308–11. http://dx.doi.org/10.3169/itej.65.1308.

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Yang, Jian-Hua, Peng Shao, Hui Zhou, Yue-Qin Chen, and Liang-Hu Qu. "deepBase: a database for deeply annotating and mining deep sequencing data." Nucleic Acids Research 38, suppl_1 (December 4, 2009): D123—D130. http://dx.doi.org/10.1093/nar/gkp943.

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Kim, Lok-Won. "DeepX: Deep Learning Accelerator for Restricted Boltzmann Machine Artificial Neural Networks." IEEE Transactions on Neural Networks and Learning Systems 29, no. 5 (May 2018): 1441–53. http://dx.doi.org/10.1109/tnnls.2017.2665555.

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Caldeira, João, and Brian Nord. "Deeply uncertain: comparing methods of uncertainty quantification in deep learning algorithms." Machine Learning: Science and Technology 2, no. 1 (December 4, 2020): 015002. http://dx.doi.org/10.1088/2632-2153/aba6f3.

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Zhang, Guoyin, Chengyan Lin, Lihua Ren, Shiyin Li, Shiti Cui, Kaiyu Wang, and Yanan Sun. "Seismic characterization of deeply buried paleocaves based on Bayesian deep learning." Journal of Natural Gas Science and Engineering 97 (January 2022): 104340. http://dx.doi.org/10.1016/j.jngse.2021.104340.

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35

Jakobs, G., G. Rehder, G. Jost, K. Kießlich, M. Labrenz, and O. Schmale. "Comparative studies of pelagic microbial methane oxidation within two anoxic basins of the central Baltic Sea (Gotland Deep and Landsort Deep)." Biogeosciences Discussions 10, no. 7 (July 20, 2013): 12251–84. http://dx.doi.org/10.5194/bgd-10-12251-2013.

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Abstract. Pelagic methane oxidation was investigated in dependence on differing environmental conditions within the redox zone of the Gotland Deep (GD) and Landsort Deep (LD), central Baltic Sea. The redox zone of both deeps, which indicates the transition between oxic and anoxic conditions, was characterized by a pronounced methane concentration gradient between the deep water (GD: 1233 nM, LD: 2935 nM) and the surface water (GD and LD < 10 nM), together with a 13C CH4 enrichment (δ13C CH4 deep water: GD −84‰, LD −71‰ ; redox zone: GD −60‰, LD −20‰ ; δ13C CH4 vs. Vienna Pee Dee Belemnite standard), clearly indicating microbial methane consumption in that specific depth interval. Expression analysis of the methane monooxygenase identified one active type I methanotrophic bacterium in both redox zones. In contrast, the turnover of methane within the redox zones showed strong differences between the two basins (GD: max. 0.12 nM d–1 and LD: max. 0.61 nM d–1), with a four times higher turnover rate constant (k) in the LD (GD: 0.0022 d–1, LD: 0.0079 d–1). Vertical mixing rates for both deeps were calculated on the base of the methane concentration profile and the consumption of methane in the redox zone (GD: 2.5 × 10–6 m2 s–1 LD: 1.6 × 10–5 m2 s–1). Our study identified vertical transport of methane from the deep water body towards the redox zone as well as differing hydrographic conditions within the oxic/anoxic transition zone of these deeps as major factors that determine the pelagic methane oxidation.
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G, Ranganathan. "A Study to Find Facts Behind Preprocessing on Deep Learning Algorithms." Journal of Innovative Image Processing 3, no. 1 (April 27, 2021): 66–74. http://dx.doi.org/10.36548/jiip.2021.1.006.

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In the near future, deep learning algorithms will be incorporated in several applications for assisting the human beings. The deep learning algorithms have the tendency to allow a computer to work on its assumption. Most of the deep learning algorithms mimic the human brain’s neuron connection to leverage an artificial intelligence to the computer system. This helps to improve the operational speed and accuracy on several critical tasks. This paper projects the blocks, which are required for the incorporation of deep learning based algorithm. Also, the paper attempts to deeply analyze the necessity of the preprocessing step over several deep learning based applications.
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Schultheis, Jennifer M., Travis S. Heath, and David A. Turner. "Association Between Deep Sedation from Continuous Intravenous Sedatives and Extubation Failures in Mechanically Ventilated Patients in the Pediatric Intensive Care Unit." Journal of Pediatric Pharmacology and Therapeutics 22, no. 2 (April 1, 2017): 106–11. http://dx.doi.org/10.5863/1551-6776-22.2.106.

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OBJECTIVE The primary objective of this study was to determine whether an association exists between deep sedation from continuous infusion sedatives and extubation failures in mechanically ventilated children. Secondary outcomes evaluated risk factors associated with deep sedation. METHODS This was a retrospective cohort study conducted between January 1, 2009, and October 31, 2012, in the pediatric intensive care unit (PICU) at Duke Children's Hospital. Patients were included in the study if they had been admitted to the PICU, had been mechanically ventilated for ≥48 hours, and had received at least one continuous infusion benzodiazepine and/or opioid infusion for ≥24 hours. Patients were separated into 2 groups: those deeply sedated and those not deeply sedated. Deep sedation was defined as having at least one documented State Behavioral Scale (SBS) of −3 or −2 within 72 hours prior to planned extubation. RESULTS A total of 108 patients were included in the analysis. Both groups were well matched with regard to baseline characteristics. For the primary outcome, there was no difference in extubation failures in those who were deeply sedated compared to those not deeply sedated (14 patients [22.6%] versus 7 patients [15.2%], respectively; p = 0.33). After adjusting for potential risk factors, patients with a higher weight percentile for age (odds ratio [OR] 1.02; 95% confidence interval [CI] 1.00–1.03), lower Glasgow Coma Score (GCS) score prior to intubation (OR 0.85; 95% CI 0.74–0.97), and larger maximum benzodiazepine dose (OR 1.93; 95% CI 1.01–3.71) were associated with greater odds of deep sedation. A higher GCS prior to intubation was significantly associated with increased odds of extubation failure (OR 1.19; 95% CI 1.02–1.39). CONCLUSIONS While there was no statistically significant difference in extubation failures between the 2 groups included in this study, considering the severe consequences of extubation failure, the numerical difference reported may be clinically important.
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38

Jakobs, G., G. Rehder, G. Jost, K. Kießlich, M. Labrenz, and O. Schmale. "Comparative studies of pelagic microbial methane oxidation within the redox zones of the Gotland Deep and Landsort Deep (central Baltic Sea)." Biogeosciences 10, no. 12 (December 3, 2013): 7863–75. http://dx.doi.org/10.5194/bg-10-7863-2013.

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Abstract. Pelagic methane oxidation was investigated in dependence on differing hydrographic conditions within the redox zone of the Gotland Deep (GD) and Landsort Deep (LD), central Baltic Sea. The redox zone of both deeps, which indicates the transition between oxic and anoxic conditions, was characterized by a pronounced methane concentration gradient between the deep water (GD: 1233 nM, 223 m; LD: 2935 nM, 422 m) and the surface water (GD and LD < 10 nM). This gradient together with a 13C CH4 enrichment (δ13C CH4 deep water: GD −84‰, LD −71‰; redox zone: GD −60‰, LD −20‰; surface water: GD −47‰, LD −50‰; δ13C CH4 vs. Vienna Pee Dee Belemnite standard), clearly indicating microbial methane consumption within the redox zone. Expression analysis of the methane monooxygenase identified one active type I methanotrophic bacterium in both redox zones. In contrast, the turnover of methane within the redox zones showed strong differences between the two basins (GD: max. 0.12 nM d−1, LD: max. 0.61 nM d−1), with a nearly four-times-lower turnover time of methane in the LD (GD: 455 d, LD: 127 d). Vertical mixing rates for both deeps were calculated on the base of the methane concentration profile and the consumption of methane in the redox zone (GD: 2.5 × 10–6 m2 s−1, LD: 1.6 × 10–5 m2 s−1). Our study identified vertical transport of methane from the deep-water body towards the redox zone as well as differing hydrographic conditions (lateral intrusions and vertical mixing) within the redox zone of these deeps as major factors that determine the pelagic methane oxidation.
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39

Yoshida, Koichiro. "Deep-seated mycosis." Medical Mycology Journal 55, no. 2 (2014): J55—J56. http://dx.doi.org/10.3314/mmj.55.j55.

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40

Honda, Hitoshi, Brian S Heist, and Ken Kikuchi. "Deep-seated mycosis." Medical Mycology Journal 56, no. 3 (2015): E21—E22. http://dx.doi.org/10.3314/mmj.56.e21.

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41

Watanabe, Akira. "Deep-seated mycosis." Medical Mycology Journal 56, no. 1 (2015): J1—J2. http://dx.doi.org/10.3314/mmj.56.j1.

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Honda, Hitoshi, Brian S Heist, and Ken Kikuchi. "Deep-seated mycosis." Medical Mycology Journal 56, no. 3 (2015): J105—J106. http://dx.doi.org/10.3314/mmj.56.j105.

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43

Yaguchi, Takashi. "Deep-seated mycosis." Medical Mycology Journal 56, no. 4 (2015): J137—J138. http://dx.doi.org/10.3314/mmj.56.j137.

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Mikamo, Hiroshige. "Deep-seated mycosis." Medical Mycology Journal 57, no. 1 (2016): J33—J34. http://dx.doi.org/10.3314/mmj.57.j33.

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45

Jorda, G., M. M. Flexas, M. Espino, and A. Calafat. "Deep flow variability in a deeply incised Mediterranean submarine valley (Blanes canyon)." Progress in Oceanography 118 (November 2013): 47–60. http://dx.doi.org/10.1016/j.pocean.2013.07.024.

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46

Moreira, Ithan, Javier Rivas, Francisco Cruz, Richard Dazeley, Angel Ayala, and Bruno Fernandes. "Deep Reinforcement Learning with Interactive Feedback in a Human–Robot Environment." Applied Sciences 10, no. 16 (August 12, 2020): 5574. http://dx.doi.org/10.3390/app10165574.

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Robots are extending their presence in domestic environments every day, it being more common to see them carrying out tasks in home scenarios. In the future, robots are expected to increasingly perform more complex tasks and, therefore, be able to acquire experience from different sources as quickly as possible. A plausible approach to address this issue is interactive feedback, where a trainer advises a learner on which actions should be taken from specific states to speed up the learning process. Moreover, deep reinforcement learning has been recently widely used in robotics to learn the environment and acquire new skills autonomously. However, an open issue when using deep reinforcement learning is the excessive time needed to learn a task from raw input images. In this work, we propose a deep reinforcement learning approach with interactive feedback to learn a domestic task in a Human–Robot scenario. We compare three different learning methods using a simulated robotic arm for the task of organizing different objects; the proposed methods are (i) deep reinforcement learning (DeepRL); (ii) interactive deep reinforcement learning using a previously trained artificial agent as an advisor (agent–IDeepRL); and (iii) interactive deep reinforcement learning using a human advisor (human–IDeepRL). We demonstrate that interactive approaches provide advantages for the learning process. The obtained results show that a learner agent, using either agent–IDeepRL or human–IDeepRL, completes the given task earlier and has fewer mistakes compared to the autonomous DeepRL approach.
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Hizhniak, Grigorii, Aleksei Amirov, Evgenii Gladkikh, Andrei Kozlov, Vladimir Kolesov, Aleksandr Zakharian, Aleksei Pestrikov, Andrei Chikin, Maksim Komin, and Ralph Harris. "Laboratory tests of DEEPA acid-generating compound." Вестник Пермского национального исследовательского политехнического университета. Геология. Нефтегазовое и горное дело 14 (March 26, 2015): 18–31. http://dx.doi.org/10.15593/2224-9923/2015.14.3.

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48

Liu Xin, 刘鑫, 陈思溢 Chen Siyi, 陈小龙 Chen Xiaolong, and 杜鑫浩 Du Xinhao. "基于深度学习的深层次多尺度特征融合目标检测算法." Laser & Optoelectronics Progress 58, no. 12 (2021): 1210029. http://dx.doi.org/10.3788/lop202158.1210029.

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Bhaskaran, Abhishek, John Fitzgerald, Nicholas Jackson, Sigfus Gizurarson, Kumaraswamy Nanthakumar, and Andreu Porta-Sánchez. "Decrement Evoked Potential Mapping to Guide Ventricular Tachycardia Ablation: Elucidating the Functional Substrate." Arrhythmia & Electrophysiology Review 9, no. 4 (December 24, 2020): 211–18. http://dx.doi.org/10.15420/aer.2020.25.

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Empirical approaches to targeting the ventricular tachycardia (VT) substrate include mapping of late potentials, local abnormal electrogram, pace-mapping and homogenisation of the abnormal signals. These approaches do not try to differentiate between the passive or active role of local signals as the critical components of the VT circuit. By not considering the functional components, these approaches often view the substrate as a fixed anatomical barrier. Strategies to improve the success of VT ablation need to include the identification of critical functional substrate. Decrement-evoked potential (DeEP) mapping has been developed to elucidate this using an extra-stimulus added to a pacing drive train. With knowledge translation in mind, the authors detail the evolution of the DeEP concept by way of a study of simultaneous panoramic endocardial mapping in VT ablation; an in silico modelling study to demonstrate the factors influencing DeEPs; a multicentre VT ablation validation study; a practical approach to DeEP mapping; the potential utility of DeEPs to identify arrhythmogenic atrial substrate; and, finally, other functional mapping strategies.
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Gilbertson, Eric. "Disagreement and Deep Agnosticism." Logos & Episteme 12, no. 1 (2021): 29–52. http://dx.doi.org/10.5840/logos-episteme20211212.

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One defense of the “steadfast” position in cases of peer disagreement appeals to the idea that it's rational for you to remain deeply agnostic about relevant propositions concerning your peer's judgment, that is, to assign no credence value at all to such propositions. Thus, according to this view, since you need not assign any value to the proposition that your peer's judgment is likely to be correct, you need not conciliate, since you can remain deeply agnostic on the question of how the likelihood of your peer's judgment bears on the likelihood of your own. This paper argues that the case for deep agnosticism as a response to peer disagreement fails. Deep agnosticism (as a general thesis) implies that it is sometimes permissible to withhold judgment about whether there is a non-zero chance of a proposition's being true. However, in cases of disagreement where deep agnosticism is supposed to support the steadfast position, such withholding isn't rational. This is because of constraints placed on rational credence by objective probability or chance, which ensure that rational credence adequately reflects strength of evidence.
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