Relevant bibliographies by topics / Data translation model

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Data translation model'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Data translation model"

1

Marie, Benjamin, and Atsushi Fujita. "Synthesizing Parallel Data of User-Generated Texts with Zero-Shot Neural Machine Translation." Transactions of the Association for Computational Linguistics 8 (November 2020): 710–25. http://dx.doi.org/10.1162/tacl_a_00341.

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Neural machine translation (NMT) systems are usually trained on clean parallel data. They can perform very well for translating clean in-domain texts. However, as demonstrated by previous work, the translation quality significantly worsens when translating noisy texts, such as user-generated texts (UGT) from online social media. Given the lack of parallel data of UGT that can be used to train or adapt NMT systems, we synthesize parallel data of UGT, exploiting monolingual data of UGT through crosslingual language model pre-training and zero-shot NMT systems. This paper presents two different but complementary approaches: One alters given clean parallel data into UGT-like parallel data whereas the other generates translations from monolingual data of UGT. On the MTNT translation tasks, we show that our synthesized parallel data can lead to better NMT systems for UGT while making them more robust in translating texts from various domains and styles.
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Li, Rumeng, Xun Wang, and Hong Yu. "MetaMT, a Meta Learning Method Leveraging Multiple Domain Data for Low Resource Machine Translation." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 05 (April 3, 2020): 8245–52. http://dx.doi.org/10.1609/aaai.v34i05.6339.

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Neural machine translation (NMT) models have achieved state-of-the-art translation quality with a large quantity of parallel corpora available. However, their performance suffers significantly when it comes to domain-specific translations, in which training data are usually scarce. In this paper, we present a novel NMT model with a new word embedding transition technique for fast domain adaption. We propose to split parameters in the model into two groups: model parameters and meta parameters. The former are used to model the translation while the latter are used to adjust the representational space to generalize the model to different domains. We mimic the domain adaptation of the machine translation model to low-resource domains using multiple translation tasks on different domains. A new training strategy based on meta-learning is developed along with the proposed model to update the model parameters and meta parameters alternately. Experiments on datasets of different domains showed substantial improvements of NMT performances on a limited amount of data.
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Cao, Qianyu, and Hanmei Hao. "A Chaotic Neural Network Model for English Machine Translation Based on Big Data Analysis." Computational Intelligence and Neuroscience 2021 (July 2, 2021): 1–12. http://dx.doi.org/10.1155/2021/3274326.

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In this paper, the chaotic neural network model of big data analysis is used to conduct in-depth analysis and research on the English translation. Firstly, under the guidance of the translation strategy of text type theory, the translation generated by the machine translation system is edited after translation, and then professionals specializing in computer and translation are invited to confirm the translation. After that, the errors in the translations generated by the machine translation system are classified based on the Double Quantum Filter-Muttahida Quami Movement (DQF-MQM) error type classification framework. Due to the characteristics of the source text as an informative academic text, long and difficult sentences, passive voice, and terminology translation are the main causes of machine translation errors. In view of the rigorous logic of the source text and the fixed language steps, this research proposes corresponding post-translation editing strategies for each type of error. It is suggested that translators should maintain the logic of the source text by converting implicit connections into explicit connections, maintain the academic accuracy of the source text by adding subjects and adjusting the word order to deal with the passive voice, and deal with semitechnical terms by appropriately selecting word meanings in postediting. The errors of machine translation in computer science and technology text abstracts are systematically categorized, and the corresponding post-translation editing strategies are proposed to provide reference suggestions for translators in this field, to improve the quality of machine translation in this field.
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Yu, Lei, Laurent Sartran, Wojciech Stokowiec, Wang Ling, Lingpeng Kong, Phil Blunsom, and Chris Dyer. "Better Document-Level Machine Translation with Bayes’ Rule." Transactions of the Association for Computational Linguistics 8 (July 2020): 346–60. http://dx.doi.org/10.1162/tacl_a_00319.

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We show that Bayes’ rule provides an effective mechanism for creating document translation models that can be learned from only parallel sentences and monolingual documents a compelling benefit because parallel documents are not always available. In our formulation, the posterior probability of a candidate translation is the product of the unconditional (prior) probability of the candidate output document and the “reverse translation probability” of translating the candidate output back into the source language. Our proposed model uses a powerful autoregressive language model as the prior on target language documents, but it assumes that each sentence is translated independently from the target to the source language. Crucially, at test time, when a source document is observed, the document language model prior induces dependencies between the translations of the source sentences in the posterior. The model’s independence assumption not only enables efficient use of available data, but it additionally admits a practical left-to-right beam-search algorithm for carrying out inference. Experiments show that our model benefits from using cross-sentence context in the language model, and it outperforms existing document translation approaches.
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Luo, Gong-Xu, Ya-Ting Yang, Rui Dong, Yan-Hong Chen, and Wen-Bo Zhang. "A Joint Back-Translation and Transfer Learning Method for Low-Resource Neural Machine Translation." Mathematical Problems in Engineering 2020 (May 31, 2020): 1–11. http://dx.doi.org/10.1155/2020/6140153.

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Neural machine translation (NMT) for low-resource languages has drawn great attention in recent years. In this paper, we propose a joint back-translation and transfer learning method for low-resource languages. It is widely recognized that data augmentation methods and transfer learning methods are both straight forward and effective ways for low-resource problems. However, existing methods, which utilize one of these methods alone, limit the capacity of NMT models for low-resource problems. In order to make full use of the advantages of existing methods and further improve the translation performance of low-resource languages, we propose a new method to perfectly integrate the back-translation method with mainstream transfer learning architectures, which can not only initialize the NMT model by transferring parameters of the pretrained models, but also generate synthetic parallel data by translating large-scale monolingual data of the target side to boost the fluency of translations. We conduct experiments to explore the effectiveness of the joint method by incorporating back-translation into the parent-child and the hierarchical transfer learning architecture. In addition, different preprocessing and training methods are explored to get better performance. Experimental results on Uygur-Chinese and Turkish-English translation demonstrate the superiority of the proposed method over the baselines that use single methods.
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Wahiyudin, Ummi Nadjwa, and Taj Rijal Bin Muhamad Romli. "Tanslating Malay Compounds into Arabic Based on Dynamic Theory and Arabization Method." Journal of Islamic Thought and Civilization 11, no. 1 (June 28, 2021): 43–58. http://dx.doi.org/10.32350/jitc.111.03.

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This study aims at making possible the effective use of machine translation (MT) in interpreting the Malay compounds into Arabic ones following the structure and Arabic style. The necessity of this study arises on account of the weakness of translation quality using online MT and the lack of suitable methods to structure the compounds from the Malay language into Arabic. There are three objectives of this study which are to collect the results of Malay compound translations using online MT into Arabic, analyze the results of the compound translations, and suggest compound translation methods based on dynamic theory and Arabization method. The study uses three online MT as instruments to translate: Google Translate, Microsoft Bing Translator, and Yandex Translator. This qualitative study employs a descriptive approach and analysis method in collecting information and analyzing data. The study focuses on 15 Malay compounds which are later categorized into school names, hospital names, and clinics. The findings of translation have been drawn using the next three MTs and analyzed at three main level: namely grammar level, phonetics and phonology level, and dynamic translation level. From this analysis, 4 out of 15 compound nouns translations data into Arabic are categorized as poor translations for not approaching the structure and Arabic style. In the final stages, the results of the translation collected are formulated and suggested alternative translations based on dynamic theory and methods of Arabization and compound restructuring formula in Arabic. Through this process, the translation results of the compounds can be categorized as translations that can meet the structure and style of the Arabic language. The compound translation model can be proposed as a new translation method for Arabic language users, especially the Arabic translators and students both at school and higher education.
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Robin, Edina. "Translation universals revisited." FORUM / Revue internationale d’interprétation et de traduction / International Journal of Interpretation and Translation 15, no. 1 (August 19, 2017): 51–66. http://dx.doi.org/10.1075/forum.15.1.03rob.

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Abstract According to the results of translation-based empirical research within the descriptive paradigm, transfer operations and the shifts that occur as a result of translators’ interventions are governed by norms, which represent general, standard practices built on informal social consensus (Toury 1995). Based on the scientific analysis of norms and general rules, the so-called translation universals were formulated describing the factors and qualities that distinguish translations from source texts and from authentic texts not produced through translation but originally written in the target language (Baker 1993). In the present study, I aim to summarise the theoretical conclusions drawn so far from the description of these observed translational features, as well as the results of the research into linguistic phenomena and laws that characterise translations in general, then I will synthesise and graphically represent the lessons learned in a theoretical model. Hopefully, it will provide help to understand and process the research data gained so far and in the future.
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Jassem, Krzysztof, and Tomasz Dwojak. "Statistical versus neural machine translation – a case study for a medium size domain-specific bilingual corpus." Poznan Studies in Contemporary Linguistics 55, no. 2 (June 26, 2019): 491–515. http://dx.doi.org/10.1515/psicl-2019-0018.

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Abstract Neural Machine Translation (NMT) has recently achieved promising results for a number of translation pairs. Although the method requires larger volumes of data and more computational power than Statistical Machine Translation (SMT), it is believed to become dominant in near future. In this paper we evaluate SMT and NMT models learned on a domain-specific English-Polish corpus of a moderate size (1,200,000 segments). The experiment shows that both solutions significantly outperform a general-domain online translator. The SMT model achieves a slightly better BLEU score than the NMT model. On the other hand, the process of decoding is noticeably faster in NMT. Human evaluation carried out on a sizeable sample of translations (2,000 pairs) reveals the superiority of the NMT approach, particularly in the aspect of output fluency.
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Faria Shaheen, Dr. Ghulam Ali, and Dr. Kanwal Zahra. "Translating Feminist Identities: A Critical Discourse Analysis of Urdu Translation of Brown’s Work ‘The Dancing Girls of Lahore’." Research Journal of Social Sciences and Economics Review (RJSSER) 2, no. 1 (March 16, 2021): 330–37. http://dx.doi.org/10.36902/rjsser-vol2-iss1-2021(330-337).

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The present paper focuses on the construction and production of gender identities through discursive mechanisms during the process of translation. It also attempts to focus on the various discursive strategies used by the translator in the phenomenon of translation. The data comprise Louis Brown's book 'The Dancing Girls of Lahore' and its Urdu translation by Pakistani male writer and translator Dr. Naeem Tariq. The theoretical and conceptual framework for the present research is based on three dimensional model by Farahzad (2012) in the light of Critical Discourse Analysis. The data related to feminist discourse in both the source text and the target text is selected through the purposive sampling technique. The analysis of the present paper reflects the position of the translator through his lexical and grammatical choices in the process of translation. The findings of the present study reflect the position of male translators and expose the socio-political structure of Pakistani patriarchal society. This study provides various dimensions to explore feminist translations for future researchers.
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Islam Saleem, Haneen, and Hakar Hazim M.Ameen. "Problems Students Face in Translating Discourse Markers from English into Kurdish." Academic Journal of Nawroz University 10, no. 3 (July 13, 2021): 1–8. http://dx.doi.org/10.25007/ajnu.v10n3a1067.

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This paper investigates the problems are found in the translation of discourse markers from English into Kurdish. One of the main problems that discourse markers cause for translators is that discourse markers may have various possible translation choices. Moreover, a discourse marker has many functions, i.e. it may have more than one function. It can be thus used to show a variety of relations between several written discourse parts. Accordingly, a translator has to decide the function that a discourse marker has in a definite context to give the correct translation. In this paper Fraser's Model of discourse markers analysis (1999) has been chosen for investigating discourse markers. As for the data analysis, four students of the Department of Translation at the University of Duhok have been chosen to translate the same text from English into Kurdish to show the difficulties in choosing the correct discourse markers in these four different translations. The results showed that there are no equivalents in choosing the correct discourse markers when translating them into Kurdish.
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Dissertations / Theses on the topic "Data translation model"

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Winegar, Matthew Bryston. "Extending the Abstract Data Model." Digital Commons @ East Tennessee State University, 2005. https://dc.etsu.edu/etd/1007.

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The Abstract Data Model (ADM) was developed by Sanderson [19] to model and predict semantic loss in data translation between computer languages. In this work, the ADM was applied to eight languages that were not considered as part of the original work. Some of the languages were found to support semantic features, such as the restriction semantics for inheritance found in languages like XML Schemas and Java, which could not be represented in the ADM. A proposal was made to extend the ADM to support these semantic features, and the requirements and implications of implementing that proposal were considered.
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Levenberg, Abby D. "Stream-based statistical machine translation." Thesis, University of Edinburgh, 2011. http://hdl.handle.net/1842/5760.

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We investigate a new approach for SMT system training within the streaming model of computation. We develop and test incrementally retrainable models which, given an incoming stream of new data, can efficiently incorporate the stream data online. A naive approach using a stream would use an unbounded amount of space. Instead, our online SMT system can incorporate information from unbounded incoming streams and maintain constant space and time. Crucially, we are able to match (or even exceed) translation performance of comparable systems which are batch retrained and use unbounded space. Our approach is particularly suited for situations when there is arbitrarily large amounts of new training material and we wish to incorporate it efficiently and in small space. The novel contributions of this thesis are: 1. An online, randomised language model that can model unbounded input streams in constant space and time. 2. An incrementally retrainable translationmodel for both phrase-based and grammarbased systems. The model presented is efficient enough to incorporate novel parallel text at the single sentence level. 3. Strategies for updating our stream-based language model and translation model which demonstrate how such components can be successfully used in a streaming translation setting. This operates both within a single streaming environment and also in the novel situation of having to translate multiple streams. 4. Demonstration that recent data from the stream is beneficial to translation performance. Our stream-based SMT system is efficient for tackling massive volumes of new training data and offers-up new ways of thinking about translating web data and dealing with other natural language streams.
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Kim, Pilho. "E-model event-based graph data model theory and implementation /." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/29608.

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Thesis (Ph.D)--Electrical and Computer Engineering, Georgia Institute of Technology, 2010.
Committee Chair: Madisetti, Vijay; Committee Member: Jayant, Nikil; Committee Member: Lee, Chin-Hui; Committee Member: Ramachandran, Umakishore; Committee Member: Yalamanchili, Sudhakar. Part of the SMARTech Electronic Thesis and Dissertation Collection.
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Blackman-Lees, Shellon. "Towards a Conceptual Framework for Persistent Use: A Technical Plan to Achieve Semantic Interoperability within Electronic Health Record Systems." NSUWorks, 2017. http://nsuworks.nova.edu/gscis_etd/998.

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Semantic interoperability within the health care sector requires that patient data be fully available and shared without ambiguity across participating health facilities. The need for the current research was based on federal stipulations that required health facilities provide complete and optimal care to patients by allowing full access to their health records. The ongoing discussions to achieve interoperability within the health care industry continue to emphasize the need for healthcare facilities to successfully adopt and implement Electronic Health Record (EHR) systems. Reluctance by the healthcare industry to implement these EHRs for the purpose of achieving interoperability has led to the current research problem where it was determined that there is no existing single data standardization structure that can effectively share and interpret patient data within heterogeneous systems. The current research used the design science research methodology (DSRM) to design and develop a master data standardization and translation (MDST) model that allowed seamless exchange of healthcare data among multiple facilities. To achieve interoperability through a common data standardization structure, where multiple independent data models can coexist, the translation mechanism incorporated the use of the Resource Description Framework (RDF). Using RDF, a universal exchange language, allowed for multiple data models and vocabularies to be easily combined and interrelated within a single environment thereby reducing data definition ambiguity. Based on the results from the research, key functional capabilities to effectively map and translate health data were documented. The research solution addressed two primary issues that impact semantic interoperability – the need for a centralized standards repository and a framework that effectively maps and translates data between various EHRs and vocabularies. Thus, health professionals have a single interpretation of health data across multiple facilities which ensures the integrity and validity of patient care. The research contributed to the field of design science development through the advancements of the underlying theories, phases, and frameworks used in the design and development of data translation models. While the current research focused on the development of a single, common information model, further research opportunities and recommendations could include investigations into the implementation of these types of artifacts within a single environment at a multi-facility hospital entity.
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Svanberg, Kerstin. "Bringing the history of fashion up-to-date; towards a model for temporal adatation in translation." Thesis, Linnéuniversitetet, Institutionen för språk och litteratur, SOL, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-22629.

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In cultural adaptation, the translator has a solid theoretical ground to stand upon; scholars have elaborated strategies that are helpful to this effect. However, there is little research, if any, to rely upon in the matter of temporal adaptation. The aim of this paper is to fill this gap. The primary data used in this translational study consists of an English source text that was published in 2008 and the resulting target text, translated to Swedish in 2012. Hence, in order for the target text to function in its time, there was a four-year long time gap to fill with accurate and relevant data and in a style that would not deviate from the author’s original intentions; the target text needed to be temporally adapted. In what follows, I will suggest a set of strategies for temporal adaptation. The model is elaborated with strategies for cultural adaptation as a starting point and based upon measures taken to relocate the target text to 2012. The suggested strategies are time bridging, updating, adjustment and omission. These four strategies make up the model that I put forward to bridge the theoretical gap that seems to prevail in the matter of temporal adaptation. However, considering that the data used in this study was relatively limited, the applicability of the strategies may be the scope of future studies.
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Ngô, Van Chan. "Formal verification of a synchronous data-flow compiler : from Signal to C." Phd thesis, Université Rennes 1, 2014. http://tel.archives-ouvertes.fr/tel-01067477.

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Synchronous languages such as Signal, Lustre and Esterel are dedicated to designing safety-critical systems. Their compilers are large and complicated programs that may be incorrect in some contexts, which might produce silently bad compiled code when compiling source programs. The bad compiled code can invalidate the safety properties that are guaranteed on the source programs by applying formal methods. Adopting the translation validation approach, this thesis aims at formally proving the correctness of the highly optimizing and industrial Signal compiler. The correctness proof represents both source program and compiled code in a common semantic framework, then formalizes a relation between the source program and its compiled code to express that the semantics of the source program are preserved in the compiled code.
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Potet, Marion. "Vers l'intégration de post-éditions d'utilisateurs pour améliorer les systèmes de traduction automatiques probabilistes." Phd thesis, Université de Grenoble, 2013. http://tel.archives-ouvertes.fr/tel-00995104.

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Les technologies de traduction automatique existantes sont à présent vues comme une approche prometteuse pour aider à produire des traductions de façon efficace et à coût réduit. Cependant, l'état de l'art actuel ne permet pas encore une automatisation complète du processus et la coopération homme/machine reste indispensable pour produire des résultats de qualité. Une pratique usuelle consiste à post-éditer les résultats fournis par le système, c'est-à-dire effectuer une vérification manuelle et, si nécessaire, une correction des sorties erronées du système. Ce travail de post-édition effectué par les utilisateurs sur les résultats de traduction automatique constitue une source de données précieuses pour l'analyse et l'adaptation des systèmes. La problématique abordée dans nos travaux s'intéresse à développer une approche capable de tirer avantage de ces retro-actions (ou post-éditions) d'utilisateurs pour améliorer, en retour, les systèmes de traduction automatique. Les expérimentations menées visent à exploiter un corpus d'environ 10 000 hypothèses de traduction d'un système probabiliste de référence, post-éditées par des volontaires, par le biais d'une plateforme en ligne. Les résultats des premières expériences intégrant les post-éditions, dans le modèle de traduction d'une part, et par post-édition automatique statistique d'autre part, nous ont permis d'évaluer la complexité de la tâche. Une étude plus approfondie des systèmes de post-éditions statistique nous a permis d'évaluer l'utilisabilité de tels systèmes ainsi que les apports et limites de l'approche. Nous montrons aussi que les post-éditions collectées peuvent être utilisées avec succès pour estimer la confiance à accorder à un résultat de traduction automatique. Les résultats de nos travaux montrent la difficulté mais aussi le potentiel de l'utilisation de post-éditions d'hypothèses de traduction automatiques comme source d'information pour améliorer la qualité des systèmes probabilistes actuels.
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Vestin, Albin, and Gustav Strandberg. "Evaluation of Target Tracking Using Multiple Sensors and Non-Causal Algorithms." Thesis, Linköpings universitet, Reglerteknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-160020.

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Today, the main research field for the automotive industry is to find solutions for active safety. In order to perceive the surrounding environment, tracking nearby traffic objects plays an important role. Validation of the tracking performance is often done in staged traffic scenarios, where additional sensors, mounted on the vehicles, are used to obtain their true positions and velocities. The difficulty of evaluating the tracking performance complicates its development. An alternative approach studied in this thesis, is to record sequences and use non-causal algorithms, such as smoothing, instead of filtering to estimate the true target states. With this method, validation data for online, causal, target tracking algorithms can be obtained for all traffic scenarios without the need of extra sensors. We investigate how non-causal algorithms affects the target tracking performance using multiple sensors and dynamic models of different complexity. This is done to evaluate real-time methods against estimates obtained from non-causal filtering. Two different measurement units, a monocular camera and a LIDAR sensor, and two dynamic models are evaluated and compared using both causal and non-causal methods. The system is tested in two single object scenarios where ground truth is available and in three multi object scenarios without ground truth. Results from the two single object scenarios shows that tracking using only a monocular camera performs poorly since it is unable to measure the distance to objects. Here, a complementary LIDAR sensor improves the tracking performance significantly. The dynamic models are shown to have a small impact on the tracking performance, while the non-causal application gives a distinct improvement when tracking objects at large distances. Since the sequence can be reversed, the non-causal estimates are propagated from more certain states when the target is closer to the ego vehicle. For multiple object tracking, we find that correct associations between measurements and tracks are crucial for improving the tracking performance with non-causal algorithms.
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Scarlato, Michele. "Sicurezza di rete, analisi del traffico e monitoraggio." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2012. http://amslaurea.unibo.it/3223/.

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Il lavoro è stato suddiviso in tre macro-aree. Una prima riguardante un'analisi teorica di come funzionano le intrusioni, di quali software vengono utilizzati per compierle, e di come proteggersi (usando i dispositivi che in termine generico si possono riconoscere come i firewall). Una seconda macro-area che analizza un'intrusione avvenuta dall'esterno verso dei server sensibili di una rete LAN. Questa analisi viene condotta sui file catturati dalle due interfacce di rete configurate in modalità promiscua su una sonda presente nella LAN. Le interfacce sono due per potersi interfacciare a due segmenti di LAN aventi due maschere di sotto-rete differenti. L'attacco viene analizzato mediante vari software. Si può infatti definire una terza parte del lavoro, la parte dove vengono analizzati i file catturati dalle due interfacce con i software che prima si occupano di analizzare i dati di contenuto completo, come Wireshark, poi dei software che si occupano di analizzare i dati di sessione che sono stati trattati con Argus, e infine i dati di tipo statistico che sono stati trattati con Ntop. Il penultimo capitolo, quello prima delle conclusioni, invece tratta l'installazione di Nagios, e la sua configurazione per il monitoraggio attraverso plugin dello spazio di disco rimanente su una macchina agent remota, e sui servizi MySql e DNS. Ovviamente Nagios può essere configurato per monitorare ogni tipo di servizio offerto sulla rete.
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Vincent, Charles, R. Färe, and S. Grosskopf. "A translation invariant pure DEA model." 2015. http://hdl.handle.net/10454/17539.

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Yes
This communication complements the DEA model proposed by Lovell and Pastor (1999), by incorporating both positive and negative criteria in the model. As such, we propose a DEA model, known as pure DEA, using a directional distance function approach.
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Books on the topic "Data translation model"

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Mayer, Felix. Eintragsmodelle für terminologische Datenbanken: Ein Beitrag zur übersetzungsorientierten Terminographie. Tübingen: Narr, 1998.

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Kirk, Nordstrom Darrell, Zachmann Dieter W, and Geological Survey (U.S.), eds. WATEQ4F: A personal computer FORTRAN translation of the geochemical model WATEQ2 with revised data base. Denver, Colo: Dept. of the Interior, U.S. Geological Survey, 1987.

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Merl, Dan, Joseph Lucas, Joseph Nevins, Haige Shen, and Mike West. Trans-study projection of genomic biomarkers in analysis of oncogene deregulation and breast cancer. Edited by Anthony O'Hagan and Mike West. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780198703174.013.6.

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This article focuses on the use of Bayesian concepts and methods in the trans-study projection of genomic biomarkers for the analysis of oncogene deregulation in breast cancer. The objective of the study is to determine the extent to which patterns of gene expression associated with experimentally induced oncogene pathway deregulation can be used to investigate oncogene pathway activity in real human cancers. This is often referred to as the in vitro to in vivo translation problem, which is addressed using Bayesian sparse factor regression analysis for model-based translation and refinement of in vitro generated signatures of oncogene pathway activity into the domain of human breast tumour tissue samples. The article first provides an overview of the role of oncogene pathway deregulation in human cancers before discussing the details of modelling and data analysis. It then considers the findings based on biological evaluation and Bayesian pathway annotation analysis.
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István, Bátori, and Weber Heinz Josef, eds. Neue Ansätze in maschineller Sprachübersetzung: Wissensrepräsentation und Textbezug = New approaches in machine translation : knowledge representation and discourse models. Tübingen: M. Niemeyer, 1986.

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Judge, Abigail M., and Robin M. Deutsch, eds. Overcoming Parent-Child Contact Problems. Oxford University Press, 2017. http://dx.doi.org/10.1093/med:psych/9780190235208.001.0001.

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This book focuses on family-based interventions for the continuum of parent–child problems, including affinity, alignment, justified rejection, alienation, and hybrid cases. Reintegration therapy is often recommended for families with these dynamics, but relatively limited clinical writing and virtually no program evaluation data exist to inform the selection of interventions. This book helps fill this gap. In Part I, the authors review a range of topics related to this specialized area of practice: assessment and clinical decision-making, the state of research evidence for outpatient treatment, and special clinical topics such as the management of countertransference among professional teams and the use of experiential therapies to overcome treatment resistance. Part II highlights one whole-family, psychoeducational approach to parent–child contact problems known as the Overcoming Barriers approach. Founders of this program and affiliated clinicians explicate components of this model in chapters on its therapeutic milieu; psychoeducational groups for rejected parents, favored parents, and children; and coparenting and parent–child interventions. The translation of model components to outpatient practice is also discussed, and program evaluation data are presented. Authors emphasize the evolving nature of this one approach, including areas of overlap with other family interventions, and highlight lessons learned from this innovative program.
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Bullock, Kim, and John J. Barry. Psychiatric Factors. Edited by Barbara A. Dworetzky and Gaston C. Baslet. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190265045.003.0003.

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Psychogenic nonepileptic seizures (PNES) is a multifactorial illness requiring a personalized biopsychosocial (BPS) formulation across the lifespan to understand its causes. This chapter reviews the current evidence focusing on predisposing, precipitating, perpetuating, and prognostic variables (4P’s), merging them into a chronologically based 4P-BPS model. Positive PNES randomized controlled trials suggest that self-efficacy and illness beliefs, avoidance behaviors, trigger sensitization, and comorbid psychiatric disorders are important etiological variables to target during treatment. Epidemiological and neurobiological research suggests that further treatment development focusing on the causal impact of trauma and affect dysregulation is lacking and is warranted going forward. The clinical implications for the evidence to date, as well as recommendations for translating current knowledge into therapeutic behaviors, are discussed.
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Stausberg, Michael, and Steven Engler, eds. The Oxford Handbook of the Study of Religion. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780198729570.001.0001.

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This Handbook offers an authoritative and up-to-date survey of original research in the study of religion. Its fifty-one chapters, written by authors from twelve countries, are organized into seven systematic parts. Part I (“Religion”) comprises chapters on definitions and theories of religion, history/translation, spirituality, and non-religion. Part II (“Theoretical Approaches”) reviews cognitive science, economics, evolutionary theory, feminism/gender theory, hermeneutics, Marxism, postcolonialism, semantics, semiotics, structuralism/poststructuralism, and social theory. Part III (“Modes”) addresses communication, materiality, narrative, performance, sound, space, and time. Part IV (“Environments”) relates religion to economy, law, media, nature, medicine, politics, science, sports, and tourism. Part V (“Topics”) discusses belief, emotion, experience, gift and sacrifice, gods, initiations and transitions, priests/prophets/sorcerers, purity, and salvation. Part VI (“Processes”) deals with differentiation, the disintegration and death of religions, expansion, globalization, individualization/privatization, innovation/tradition, objectification/commoditization, and syncretism/hybridization. Part VII (“The Discipline”) discusses the history and relevance of the study of religion.
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Attardo, Salvatore. The Linguistics of Humor. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780198791270.001.0001.

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This book is the first comprehensive systematic introduction to the linguistics of humor. Assuming no background in humor studies at all, and an elementary knowledge of linguistics, all the terminology and conceptual apparatus of humor studies are introduced, as well as all the linguistic concepts necessary to understand the most up-to-date formulations in the linguistics and applied linguistics of humor. The book is not limited to the theoretical linguistic analyses of humor (for example the General Theory of Verbal humor or the Isotopy Disjunction Model), but has a broad approach encompassing pragmatics, conversation and discourse analysis, ethnomethodology, interactionist and variationist sociolinguistics. Chapters on puns, on the main theories of humor, the semiotics of humor, and on the incongruity-resolution model elucidate the foundations of humor studies, while chapters on the performance of humor, on humor in conversation and discourse, provide the first-ever in-depth discussion and synthesis of the field of the applied linguistics of humor. Chapters on the translation of humor, and on humor in the classroom and in literature broaden the discussion to applications in fields other than linguistics. For the first time ever in a discussion of the linguistics of humor all the fields of linguistics, theoretical and applied alike are given equal treatment and theoretical importance. Thus this book is both a summary of the acquired knowledge about humor and linguistics and a proposal to unify most of the strands of research in a coherent vision.
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Stoddard Jr, Frederick J., David M. Benedek, Mohammed R. Milad, and Robert J. Ursano. Posttraumatic Stress Disorder. Edited by Frederick J. Stoddard, David M. Benedek, Mohammed R. Milad, and Robert J. Ursano. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190457136.003.0003.

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Posttraumatic stress disorder (PTSD) affects people of all ages and backgrounds and causes persistent suffering and impaired function, but its diagnosis offers the opportunity for early intervention. It is the subject of intensive developmental, epidemiological, genetic/genomic, translational, neurobiological, neuropsychological, and psychological research, and emerging computational methods with “big data,” statistical modeling, and machine learning are likely to accelerate this research. The findings from research on PTSD are changing education and the ways clinicians practice, offering the hope for improved care of those experiencing traumatic stress. Those at particular risk for PTSD include children and adolescents, women, soldiers, refugees and survivors of genocide, sexual orientation minorities, racial and ethnic minorities, patients with burns, injuries and medical trauma, and victims of rape, violence, accidents, and disasters. This chapter provides an overview of PTSD, covering Diagnostic and Statistical Manual of Mental Disorders (fifth edition) diagnostic criteria, epidemiology, neurochemistry and neurobiology, biological and psychological models, assessment, and treatment.
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Cohen, Hagit, and Joseph Zohar. The Role of Glucocorticoids in the (Mal)adaptive Response to Traumatic Experience. Edited by Charles B. Nemeroff and Charles R. Marmar. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190259440.003.0038.

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Glucocorticoids (GCs) play a major role in orchestrating the complex physiological and behavioral reactions essential for the maintenance of homeostasis. These compounds enable the organism to prepare for, respond to, and cope with the acute demands of physical and emotional stressors and enable a faster recovery with passage of the threat. A timely and an appropriate GC release commensurate with stressor severity enables the body to properly contain stress responses so as to promote recovery by rapidly restoring homeostasis. Inadequate GC release following stress not only delays recovery by disrupting biological homeostasis but can also interfere with the processing or interpretation of stressful information that results in long-term disruptions in memory integration. A salient example of such an impaired post-traumatic process is post-traumatic stress disorder (PTSD). The findings from recent animal models and translational and clinical neuroendocrine studies summarized in this chapter provide insights shedding light on the apparently contradictory studies of the HPA-axis response to stress. Also included is a review of the basic facts about PTSD and biological data.
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Book chapters on the topic "Data translation model"

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Atzeni, Paolo, Paolo Cappellari, and Philip A. Bernstein. "Model-Independent Schema and Data Translation." In Lecture Notes in Computer Science, 368–85. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11687238_24.

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Li, Zhichao, Yuping Han, Yajing Xu, and Sheng Gao. "Visual Relation Extraction via Multi-modal Translation Embedding Based Model." In Advances in Knowledge Discovery and Data Mining, 538–48. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-93034-3_43.

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Tu, Xinhui, Jing Luo, Bo Li, Tingting He, and Jinguang Gu. "Positional Translation Language Model for Ad-Hoc Information Retrieval." In Advances in Knowledge Discovery and Data Mining, 134–45. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-06605-9_12.

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Chen, Ming, Lin Li, and Qing Xie. "Translation Language Model Enhancement for Community Question Retrieval Using User Adoption Answer." In Web and Big Data, 251–65. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-63579-8_20.

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Wu, Meng-Sung, and Hsin-Min Wang. "A Term Association Translation Model for Naive Bayes Text Classification." In Advances in Knowledge Discovery and Data Mining, 243–53. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-30217-6_21.

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Yao, Liang, Mengyi Liu, Yu Hong, Hao Liu, and Jianmin Yao. "Topic Model Based Adaptation Data Selection for Domain-Specific Machine Translation." In Communications in Computer and Information Science, 162–71. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-2993-6_14.

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Yang, Fang. "Globalized Translation Talent Training Model based on Artificial Intelligence and Big Data." In Advances in Intelligent Systems and Computing, 410–14. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-69096-4_57.

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Koestler, Devin C., and E. Andrés Houseman. "Model-Based Clustering of DNA Methylation Array Data." In Translational Bioinformatics, 91–123. Dordrecht: Springer Netherlands, 2015. http://dx.doi.org/10.1007/978-94-017-9927-0_5.

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Abutalipov, Alikhan, Aigerim Janaliyeva, Medet Mukushev, Antonio Cerone, and Anara Sandygulova. "Handshape Classification in a Reverse Dictionary of Sign Languages for the Deaf." In From Data to Models and Back, 217–26. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-70650-0_14.

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AbstractThis paper showcases the work that aims at building a user-friendly mobile application of a reverse dictionary to translate sign languages to spoken languages. The concept behind the reverse dictionary is the ability to perform a video-based search by demonstrating a handshape in front of a mobile phone’s camera. The user would be able to use this feature in two ways. Firstly, the user would be able to search for a word by showing a handshape for the application to provide a list of signs that contain that handshape. Secondly, the user could fingerspell the word letter by letter in front of the camera for the application to return the sign that corresponds to that word. The user can then look through the suggested videos and see their written translations. To offer other functionalities, the application also has Search by Category and Search by Word options. Currently, the reverse dictionary supports translations from Russian Sign Language (RSL) to Russian language.
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Shekhar, Shashi, Ranga Raju Vatsavai, Sanjay Chawla, and Thomas E. Burk. "Spatial Pictogram Enhanced Conceptual Data Models and Their Translation to Logical Data Models." In Integrated Spatial Databases, 77–104. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/3-540-46621-5_6.

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Conference papers on the topic "Data translation model"

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Liu, Le, Yu Hong, Hao Liu, Xing Wang, and Jianmin Yao. "Effective Selection of Translation Model Training Data." In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers). Stroudsburg, PA, USA: Association for Computational Linguistics, 2014. http://dx.doi.org/10.3115/v1/p14-2093.

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Huang, Yin-Fu, and Yi-Hao Li. "Sentiment Translation Model for Expressing Positive Sentimental Statements." In 2019 International Conference on Machine Learning and Data Engineering (iCMLDE). IEEE, 2019. http://dx.doi.org/10.1109/icmlde49015.2019.00025.

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Yan, Ning. "The Interactive Translation Teaching Model on Learning Outcome." In 2020 International Conference on Big Data and Informatization Education (ICBDIE). IEEE, 2020. http://dx.doi.org/10.1109/icbdie50010.2020.00085.

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Wang, Yu. "A Statistical Model-Based Approach to NE Translation." In 2009 Second International Workshop on Knowledge Discovery and Data Mining (WKDD). IEEE, 2009. http://dx.doi.org/10.1109/wkdd.2009.144.

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An, Tailai, Jiaxing Song, and Weidong Liu. "Incorporating Pre-trained Model into Neural Machine Translation." In 2021 4th International Conference on Artificial Intelligence and Big Data (ICAIBD). IEEE, 2021. http://dx.doi.org/10.1109/icaibd51990.2021.9459048.

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GONG, Li, Josep Crego, and Jean Senellart. "Enhanced Transformer Model for Data-to-Text Generation." In Proceedings of the 3rd Workshop on Neural Generation and Translation. Stroudsburg, PA, USA: Association for Computational Linguistics, 2019. http://dx.doi.org/10.18653/v1/d19-5615.

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Cui, Jia, Yonggang Deng, and Bowen Zhou. "Reinforcing language model for speech translation with auxiliary data." In Understanding (ASRU). IEEE, 2009. http://dx.doi.org/10.1109/asru.2009.5373308.

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Bérard, Alexandre, Zae Myung Kim, Vassilina Nikoulina, Eunjeong Lucy Park, and Matthias Gallé. "A Multilingual Neural Machine Translation Model for Biomedical Data." In Proceedings of the 1st Workshop on NLP for COVID-19 (Part 2) at EMNLP 2020. Stroudsburg, PA, USA: Association for Computational Linguistics, 2020. http://dx.doi.org/10.18653/v1/2020.nlpcovid19-2.16.

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Mitsudo, Y. "Pointing and Retrieving: A Data Translation Model for Real World Computing." In 7th International Conference on Mobile Data Management (MDM'06). IEEE, 2006. http://dx.doi.org/10.1109/mdm.2006.123.

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Atzeni, Paolo, Luigi Bellomarini, Francesca Bugiotti, and Giorgio Gianforme. "A runtime approach to model-independent schema and data translation." In the 12th International Conference. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1516360.1516393.

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Reports on the topic "Data translation model"

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Anderson, T., and S. Steffann. Stateless IP/ICMP Translation for IPv6 Internet Data Center Environments (SIIT-DC): Dual Translation Mode. RFC Editor, February 2016. http://dx.doi.org/10.17487/rfc7756.

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Apicella, M. L., and S. Singh. Integrated Information Support System (IISS). Volume 5. Common Data Model Subsystem. Part 36. DDL to NDDL Translator Test Plan. Fort Belvoir, VA: Defense Technical Information Center, September 1990. http://dx.doi.org/10.21236/ada250469.

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Apicella, M. L., and S. Singh. Integrated Information Support System (IISS). Volume 5. Common Data Model Subsystem. Part 38. DDL to NDDL Translator Build Instructions. Fort Belvoir, VA: Defense Technical Information Center, September 1990. http://dx.doi.org/10.21236/ada250471.

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