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Sample records for machine translation approach

  1. English to Sanskrit Machine Translation Using Transfer Based approach

    Science.gov (United States)

    Pathak, Ganesh R.; Godse, Sachin P.

    2010-11-01

    Translation is one of the needs of global society for communicating thoughts and ideas of one country with other country. Translation is the process of interpretation of text meaning and subsequent production of equivalent text, also called as communicating same meaning (message) in another language. In this paper we gave detail information on how to convert source language text in to target language text using Transfer Based Approach for machine translation. Here we implemented English to Sanskrit machine translator using transfer based approach. English is global language used for business and communication but large amount of population in India is not using and understand the English. Sanskrit is ancient language of India most of the languages in India are derived from Sanskrit. Sanskrit can be act as an intermediate language for multilingual translation.

  2. A MOOC on Approaches to Machine Translation

    Science.gov (United States)

    Costa-jussà, Mart R.; Formiga, Lluís; Torrillas, Oriol; Petit, Jordi; Fonollosa, José A. R.

    2015-01-01

    This paper describes the design, development, and analysis of a MOOC entitled "Approaches to Machine Translation: Rule-based, statistical and hybrid", and provides lessons learned and conclusions to be taken into account in the future. The course was developed within the Canvas platform, used by recognized European universities. It…

  3. Machine translation

    Energy Technology Data Exchange (ETDEWEB)

    Nagao, M

    1982-04-01

    Each language has its own structure. In translating one language into another one, language attributes and grammatical interpretation must be defined in an unambiguous form. In order to parse a sentence, it is necessary to recognize its structure. A so-called context-free grammar can help in this respect for machine translation and machine-aided translation. Problems to be solved in studying machine translation are taken up in the paper, which discusses subjects for semantics and for syntactic analysis and translation software. 14 references.

  4. Machine Translation and Other Translation Technologies.

    Science.gov (United States)

    Melby, Alan

    1996-01-01

    Examines the application of linguistic theory to machine translation and translator tools, discusses the use of machine translation and translator tools in the real world of translation, and addresses the impact of translation technology on conceptions of language and other issues. Findings indicate that the human mind is flexible and linguistic…

  5. Dictionary Based Machine Translation from Kannada to Telugu

    Science.gov (United States)

    Sindhu, D. V.; Sagar, B. M.

    2017-08-01

    Machine Translation is a task of translating from one language to another language. For the languages with less linguistic resources like Kannada and Telugu Dictionary based approach is the best approach. This paper mainly focuses on Dictionary based machine translation for Kannada to Telugu. The proposed methodology uses dictionary for translating word by word without much correlation of semantics between them. The dictionary based machine translation process has the following sub process: Morph analyzer, dictionary, transliteration, transfer grammar and the morph generator. As a part of this work bilingual dictionary with 8000 entries is developed and the suffix mapping table at the tag level is built. This system is tested for the children stories. In near future this system can be further improved by defining transfer grammar rules.

  6. Machine Translation Tools - Tools of The Translator's Trade

    DEFF Research Database (Denmark)

    Kastberg, Peter

    2012-01-01

    In this article three of the more common types of translation tools are presented, discussed and critically evaluated. The types of translation tools dealt with in this article are: Fully Automated Machine Translation (or FAMT), Human Aided Machine Translation (or HAMT) and Machine Aided Human...... Translation (or MAHT). The strengths and weaknesses of the different types of tools are discussed and evaluated by means of a number of examples. The article aims at two things: at presenting a sort of state of the art of what is commonly referred to as “machine translation” as well as at providing the reader...... with a sound basis for considering what translation tool (if any) is the most appropriate in order to meet his or her specific translation needs....

  7. A Character Level Based and Word Level Based Approach for Chinese-Vietnamese Machine Translation

    Directory of Open Access Journals (Sweden)

    Phuoc Tran

    2016-01-01

    Full Text Available Chinese and Vietnamese have the same isolated language; that is, the words are not delimited by spaces. In machine translation, word segmentation is often done first when translating from Chinese or Vietnamese into different languages (typically English and vice versa. However, it is a matter for consideration that words may or may not be segmented when translating between two languages in which spaces are not used between words, such as Chinese and Vietnamese. Since Chinese-Vietnamese is a low-resource language pair, the sparse data problem is evident in the translation system of this language pair. Therefore, while translating, whether it should be segmented or not becomes more important. In this paper, we propose a new method for translating Chinese to Vietnamese based on a combination of the advantages of character level and word level translation. In addition, a hybrid approach that combines statistics and rules is used to translate on the word level. And at the character level, a statistical translation is used. The experimental results showed that our method improved the performance of machine translation over that of character or word level translation.

  8. A Character Level Based and Word Level Based Approach for Chinese-Vietnamese Machine Translation.

    Science.gov (United States)

    Tran, Phuoc; Dinh, Dien; Nguyen, Hien T

    2016-01-01

    Chinese and Vietnamese have the same isolated language; that is, the words are not delimited by spaces. In machine translation, word segmentation is often done first when translating from Chinese or Vietnamese into different languages (typically English) and vice versa. However, it is a matter for consideration that words may or may not be segmented when translating between two languages in which spaces are not used between words, such as Chinese and Vietnamese. Since Chinese-Vietnamese is a low-resource language pair, the sparse data problem is evident in the translation system of this language pair. Therefore, while translating, whether it should be segmented or not becomes more important. In this paper, we propose a new method for translating Chinese to Vietnamese based on a combination of the advantages of character level and word level translation. In addition, a hybrid approach that combines statistics and rules is used to translate on the word level. And at the character level, a statistical translation is used. The experimental results showed that our method improved the performance of machine translation over that of character or word level translation.

  9. Machine Translation Effect on Communication

    DEFF Research Database (Denmark)

    Jensen, Mika Yasuoka; Bjørn, Pernille

    2011-01-01

    Intercultural collaboration facilitated by machine translation has gradually spread in various settings. Still, little is known as for the practice of machine-translation mediated communication. This paper investigates how machine translation affects intercultural communication in practice. Based...... on communication in which multilingual communication system is applied, we identify four communication types and its’ influences on stakeholders’ communication process, especially focusing on establishment and maintenance of common ground. Different from our expectation that quality of machine translation results...

  10. Machine Translation

    Indian Academy of Sciences (India)

    Research Mt System Example: The 'Janus' Translating Phone Project. The Janus ... based on laptops, and simultaneous translation of two speakers in a dialogue. For more ..... The current focus in MT research is on using machine learning.

  11. Treatment of Markup in Statistical Machine Translation

    OpenAIRE

    Müller, Mathias

    2017-01-01

    We present work on handling XML markup in Statistical Machine Translation (SMT). The methods we propose can be used to effectively preserve markup (for instance inline formatting or structure) and to place markup correctly in a machine-translated segment. We evaluate our approaches with parallel data that naturally contains markup or where markup was inserted to create synthetic examples. In our experiments, hybrid reinsertion has proven the most accurate method to handle markup, while alignm...

  12. Using the TED Talks to Evaluate Spoken Post-editing of Machine Translation

    DEFF Research Database (Denmark)

    Liyanapathirana, Jeevanthi; Popescu-Belis, Andrei

    2016-01-01

    This paper presents a solution to evaluate spoken post-editing of imperfect machine translation output by a human translator. We compare two approaches to the combination of machine translation (MT) and automatic speech recognition (ASR): a heuristic algorithm and a machine learning method...

  13. Transliteration normalization for Information Extraction and Machine Translation

    Directory of Open Access Journals (Sweden)

    Yuval Marton

    2014-12-01

    Full Text Available Foreign name transliterations typically include multiple spelling variants. These variants cause data sparseness and inconsistency problems, increase the Out-of-Vocabulary (OOV rate, and present challenges for Machine Translation, Information Extraction and other natural language processing (NLP tasks. This work aims to identify and cluster name spelling variants using a Statistical Machine Translation method: word alignment. The variants are identified by being aligned to the same “pivot” name in another language (the source-language in Machine Translation settings. Based on word-to-word translation and transliteration probabilities, as well as the string edit distance metric, names with similar spellings in the target language are clustered and then normalized to a canonical form. With this approach, tens of thousands of high-precision name transliteration spelling variants are extracted from sentence-aligned bilingual corpora in Arabic and English (in both languages. When these normalized name spelling variants are applied to Information Extraction tasks, improvements over strong baseline systems are observed. When applied to Machine Translation tasks, a large improvement potential is shown.

  14. MSD Recombination Method in Statistical Machine Translation

    Science.gov (United States)

    Gros, Jerneja Žganec

    2008-11-01

    Freely available tools and language resources were used to build the VoiceTRAN statistical machine translation (SMT) system. Various configuration variations of the system are presented and evaluated. The VoiceTRAN SMT system outperformed the baseline conventional rule-based MT system in all English-Slovenian in-domain test setups. To further increase the generalization capability of the translation model for lower-coverage out-of-domain test sentences, an "MSD-recombination" approach was proposed. This approach not only allows a better exploitation of conventional translation models, but also performs well in the more demanding translation direction; that is, into a highly inflectional language. Using this approach in the out-of-domain setup of the English-Slovenian JRC-ACQUIS task, we have achieved significant improvements in translation quality.

  15. Translating DVD Subtitles English-German, English-Japanese, Using Example-based Machine Translation

    DEFF Research Database (Denmark)

    Armstrong, Stephen; Caffrey, Colm; Flanagan, Marian

    2006-01-01

    Due to limited budgets and an ever-diminishing time-frame for the production of subtitles for movies released in cinema and DVD, there is a compelling case for a technology-based translation solution for subtitles. In this paper we describe how an Example-Based Machine Translation (EBMT) approach...... to the translation of English DVD subtitles into German and Japanese can aid the subtitler. Our research focuses on an EBMT tool that produces fully automated translations, which in turn can be edited if required. To our knowledge this is the first time that any EBMT approach has been used with DVD subtitle...

  16. Quantum neural network based machine translator for Hindi to English.

    Science.gov (United States)

    Narayan, Ravi; Singh, V P; Chakraverty, S

    2014-01-01

    This paper presents the machine learning based machine translation system for Hindi to English, which learns the semantically correct corpus. The quantum neural based pattern recognizer is used to recognize and learn the pattern of corpus, using the information of part of speech of individual word in the corpus, like a human. The system performs the machine translation using its knowledge gained during the learning by inputting the pair of sentences of Devnagri-Hindi and English. To analyze the effectiveness of the proposed approach, 2600 sentences have been evaluated during simulation and evaluation. The accuracy achieved on BLEU score is 0.7502, on NIST score is 6.5773, on ROUGE-L score is 0.9233, and on METEOR score is 0.5456, which is significantly higher in comparison with Google Translation and Bing Translation for Hindi to English Machine Translation.

  17. Typologically robust statistical machine translation : Understanding and exploiting differences and similarities between languages in machine translation

    NARCIS (Netherlands)

    Daiber, J.

    2018-01-01

    Machine translation systems often incorporate modeling assumptions motivated by properties of the language pairs they initially target. When such systems are applied to language families with considerably different properties, translation quality can deteriorate. Phrase-based machine translation

  18. ADAPTING HYBRID MACHINE TRANSLATION TECHNIQUES FOR CROSS-LANGUAGE TEXT RETRIEVAL SYSTEM

    Directory of Open Access Journals (Sweden)

    P. ISWARYA

    2017-03-01

    Full Text Available This research work aims in developing Tamil to English Cross - language text retrieval system using hybrid machine translation approach. The hybrid machine translation system is a combination of rule based and statistical based approaches. In an existing word by word translation system there are lot of issues and some of them are ambiguity, Out-of-Vocabulary words, word inflections, and improper sentence structure. To handle these issues, proposed architecture is designed in such a way that, it contains Improved Part-of-Speech tagger, machine learning based morphological analyser, collocation based word sense disambiguation procedure, semantic dictionary, and tense markers with gerund ending rules, and two pass transliteration algorithm. From the experimental results it is clear that the proposed Tamil Query based translation system achieves significantly better translation quality over existing system, and reaches 95.88% of monolingual performance.

  19. The Impact of Machine Translation and Computer-aided Translation on Translators

    Science.gov (United States)

    Peng, Hao

    2018-03-01

    Under the context of globalization, communications between countries and cultures are becoming increasingly frequent, which make it imperative to use some techniques to help translate. This paper is to explore the influence of computer-aided translation on translators, which is derived from the field of the computer-aided translation (CAT) and machine translation (MT). Followed by an introduction to the development of machine and computer-aided translation, it then depicts the technologies practicable to translators, which are trying to analyze the demand of designing the computer-aided translation so far in translation practice, and optimize the designation of computer-aided translation techniques, and analyze its operability in translation. The findings underline the advantages and disadvantages of MT and CAT tools, and the serviceability and future development of MT and CAT technologies. Finally, this thesis probes into the impact of these new technologies on translators in hope that more translators and translation researchers can learn to use such tools to improve their productivity.

  20. Rule-based machine translation for Aymara

    NARCIS (Netherlands)

    Coler, Matthew; Homola, Petr; Jones, Mari

    2014-01-01

    This paper presents the ongoing result of an approach developed by the collaboration of a computational linguist with a field linguist that addresses one of the oft-overlooked keys to language maintenance: the development of modern language-learning tools. Although machine translation isn’t commonly

  1. Machine Translation in Post-Contemporary Era

    Science.gov (United States)

    Lin, Grace Hui Chin

    2010-01-01

    This article focusing on translating techniques via personal computer or laptop reports updated artificial intelligence progresses before 2010. Based on interpretations and information for field of MT [Machine Translation] by Yorick Wilks' book, "Machine Translation, Its scope and limits," this paper displays understandable theoretical frameworks…

  2. Efficient Embedded Decoding of Neural Network Language Models in a Machine Translation System.

    Science.gov (United States)

    Zamora-Martinez, Francisco; Castro-Bleda, Maria Jose

    2018-02-22

    Neural Network Language Models (NNLMs) are a successful approach to Natural Language Processing tasks, such as Machine Translation. We introduce in this work a Statistical Machine Translation (SMT) system which fully integrates NNLMs in the decoding stage, breaking the traditional approach based on [Formula: see text]-best list rescoring. The neural net models (both language models (LMs) and translation models) are fully coupled in the decoding stage, allowing to more strongly influence the translation quality. Computational issues were solved by using a novel idea based on memorization and smoothing of the softmax constants to avoid their computation, which introduces a trade-off between LM quality and computational cost. These ideas were studied in a machine translation task with different combinations of neural networks used both as translation models and as target LMs, comparing phrase-based and [Formula: see text]-gram-based systems, showing that the integrated approach seems more promising for [Formula: see text]-gram-based systems, even with nonfull-quality NNLMs.

  3. An analysis of machine translation and speech synthesis in speech-to-speech translation system

    OpenAIRE

    Hashimoto, K.; Yamagishi, J.; Byrne, W.; King, S.; Tokuda, K.

    2011-01-01

    This paper provides an analysis of the impacts of machine translation and speech synthesis on speech-to-speech translation systems. The speech-to-speech translation system consists of three components: speech recognition, machine translation and speech synthesis. Many techniques for integration of speech recognition and machine translation have been proposed. However, speech synthesis has not yet been considered. Therefore, in this paper, we focus on machine translation and speech synthesis, ...

  4. Automatic Evaluation of Machine Translation

    DEFF Research Database (Denmark)

    Martinez, Mercedes Garcia; Koglin, Arlene; Mesa-Lao, Bartolomé

    2015-01-01

    The availability of systems capable of producing fairly accurate translations has increased the popularity of machine translation (MT). The translation industry is steadily incorporating MT in their workflows engaging the human translator to post-edit the raw MT output in order to comply with a s...

  5. Machine vs. human translation of SNOMED CT terms.

    Science.gov (United States)

    Schulz, Stefan; Bernhardt-Melischnig, Johannes; Kreuzthaler, Markus; Daumke, Philipp; Boeker, Martin

    2013-01-01

    In the context of past and current SNOMED CT translation projects we compare three kinds of SNOMED CT translations from English to German by: (t1) professional medical translators; (t2) a free Web-based machine translation service; (t3) medical students. 500 SNOMED CT fully specified names from the (English) International release were randomly selected. Based on this, German translations t1, t2, and t3 were generated. A German and an Austrian physician rated the translations for linguistic correctness and content fidelity. Kappa for inter-rater reliability was 0.4 for linguistic correctness and 0.23 for content fidelity. Average ratings of linguistic correctness did not differ significantly between human translation scenarios. Content fidelity was rated slightly better for student translators compared to professional translators. Comparing machine to human translation, the linguistic correctness differed about 0.5 scale units in favour of the human translation and about 0.25 regarding content fidelity, equally in favour of the human translation. The results demonstrate that low-cost translation solutions of medical terms may produce surprisingly good results. Although we would not recommend low-cost translation for producing standardized preferred terms, this approach can be useful for creating additional language-specific entry terms. This may serve several important use cases. We also recommend testing this method to bootstrap a crowdsourcing process, by which term translations are gathered, improved, maintained, and rated by the user community.

  6. Integrating Automatic Speech Recognition and Machine Translation for Better Translation Outputs

    DEFF Research Database (Denmark)

    Liyanapathirana, Jeevanthi

    translations, combining machine translation with computer assisted translation has drawn attention in current research. This combines two prospects: the opportunity of ensuring high quality translation along with a significant performance gain. Automatic Speech Recognition (ASR) is another important area......, which caters important functionalities in language processing and natural language understanding tasks. In this work we integrate automatic speech recognition and machine translation in parallel. We aim to avoid manual typing of possible translations as dictating the translation would take less time...... to the n-best list rescoring, we also use word graphs with the expectation of arriving at a tighter integration of ASR and MT models. Integration methods include constraining ASR models using language and translation models of MT, and vice versa. We currently develop and experiment different methods...

  7. Machine Translation for Academic Purposes

    Science.gov (United States)

    Lin, Grace Hui-chin; Chien, Paul Shih Chieh

    2009-01-01

    Due to the globalization trend and knowledge boost in the second millennium, multi-lingual translation has become a noteworthy issue. For the purposes of learning knowledge in academic fields, Machine Translation (MT) should be noticed not only academically but also practically. MT should be informed to the translating learners because it is a…

  8. An Overall Perspective of Machine Translation with its Shortcomings

    Directory of Open Access Journals (Sweden)

    Alireza Akbari

    2014-01-01

    Full Text Available The petition for language translation has strikingly augmented recently due to cross-cultural communication and exchange of information. In order to communicate well, text should be translated correctly and completely in each field such as legal documents, technical texts, scientific texts, publicity leaflets, and instructional materials. In this connection, Machine translation is of great importance in translation. The term “Machine Translation” was first proposed by George Artsrouni and Smirnov Troyanski (1933 to design a storage design on paper tape. This paper sought to investigate an overall perspective of Machine Translation models and its metrics in detail. Finally, it scrutinized the ins and outs shortcomings of Machine Translation.

  9. INTEGRATING MACHINE TRANSLATION AND SPEECH SYNTHESIS COMPONENT FOR ENGLISH TO DRAVIDIAN LANGUAGE SPEECH TO SPEECH TRANSLATION SYSTEM

    Directory of Open Access Journals (Sweden)

    J. SANGEETHA

    2015-02-01

    Full Text Available This paper provides an interface between the machine translation and speech synthesis system for converting English speech to Tamil text in English to Tamil speech to speech translation system. The speech translation system consists of three modules: automatic speech recognition, machine translation and text to speech synthesis. Many procedures for incorporation of speech recognition and machine translation have been projected. Still speech synthesis system has not yet been measured. In this paper, we focus on integration of machine translation and speech synthesis, and report a subjective evaluation to investigate the impact of speech synthesis, machine translation and the integration of machine translation and speech synthesis components. Here we implement a hybrid machine translation (combination of rule based and statistical machine translation and concatenative syllable based speech synthesis technique. In order to retain the naturalness and intelligibility of synthesized speech Auto Associative Neural Network (AANN prosody prediction is used in this work. The results of this system investigation demonstrate that the naturalness and intelligibility of the synthesized speech are strongly influenced by the fluency and correctness of the translated text.

  10. Bean Soup Translation: Flexible, Linguistically-Motivated Syntax for Machine Translation

    Science.gov (United States)

    Mehay, Dennis Nolan

    2012-01-01

    Machine translation (MT) systems attempt to translate texts from one language into another by translating words from a "source language" and rearranging them into fluent utterances in a "target language." When the two languages organize concepts in very different ways, knowledge of their general sentence structure, or…

  11. Evaluation of Hindi to Punjabi Machine Translation System

    OpenAIRE

    Goyal, Vishal; Lehal, Gurpreet Singh

    2009-01-01

    Machine Translation in India is relatively young. The earliest efforts date from the late 80s and early 90s. The success of every system is judged from its evaluation experimental results. Number of machine translation systems has been started for development but to the best of author knowledge, no high quality system has been completed which can be used in real applications. Recently, Punjabi University, Patiala, India has developed Punjabi to Hindi Machine translation system with high accur...

  12. Convolutional over Recurrent Encoder for Neural Machine Translation

    Directory of Open Access Journals (Sweden)

    Dakwale Praveen

    2017-06-01

    Full Text Available Neural machine translation is a recently proposed approach which has shown competitive results to traditional MT approaches. Standard neural MT is an end-to-end neural network where the source sentence is encoded by a recurrent neural network (RNN called encoder and the target words are predicted using another RNN known as decoder. Recently, various models have been proposed which replace the RNN encoder with a convolutional neural network (CNN. In this paper, we propose to augment the standard RNN encoder in NMT with additional convolutional layers in order to capture wider context in the encoder output. Experiments on English to German translation demonstrate that our approach can achieve significant improvements over a standard RNN-based baseline.

  13. Telemedicine as a special case of machine translation.

    Science.gov (United States)

    Wołk, Krzysztof; Marasek, Krzysztof; Glinkowski, Wojciech

    2015-12-01

    Machine translation is evolving quite rapidly in terms of quality. Nowadays, we have several machine translation systems available in the web, which provide reasonable translations. However, these systems are not perfect, and their quality may decrease in some specific domains. This paper examines the effects of different training methods when it comes to Polish-English Statistical Machine Translation system used for the medical data. Numerous elements of the EMEA parallel text corpora and not related OPUS Open Subtitles project were used as the ground for creation of phrase tables and different language models including the development, tuning and testing of these translation systems. The BLEU, NIST, METEOR, and TER metrics have been used in order to evaluate the results of various systems. Our experiments deal with the systems that include POS tagging, factored phrase models, hierarchical models, syntactic taggers, and other alignment methods. We also executed a deep analysis of Polish data as preparatory work before automatized data processing such as true casing or punctuation normalization phase. Normalized metrics was used to compare results. Scores lower than 15% mean that Machine Translation engine is unable to provide satisfying quality, scores greater than 30% mean that translations should be understandable without problems and scores over 50 reflect adequate translations. The average results of Polish to English translations scores for BLEU, NIST, METEOR, and TER were relatively high and ranged from 7058 to 8272. The lowest score was 6438. The average results ranges for English to Polish translations were little lower (6758-7897). The real-life implementations of presented high quality Machine Translation Systems are anticipated in general medical practice and telemedicine. Copyright © 2015. Published by Elsevier Ltd.

  14. Findings of the 2014 Workshop on Statistical Machine Translation

    NARCIS (Netherlands)

    Bojar, O.; Buck, C.; Federmann, C.; Haddow, B.; Koehn, P.; Leveling, J.; Monz, C.; Pecina, P.; Post, M.; Saint-Amand, H.; Soricut, R.; Specia, L.; Tamchyna, A.

    2014-01-01

    This paper presents the results of the WMT14 shared tasks, which included a standard news translation task, a separate medical translation task, a task for run-time estimation of machine translation quality, and a metrics task. This year, 143 machine translation systems from 23 institutions were

  15. Findings of the 2010 Joint Workshop on Statistical Machine Translation and Metrics for Machine Translation

    NARCIS (Netherlands)

    Callison-Burch, C.; Koehn, P.; Monz, C.; Peterson, K.; Przybocki, M.; Zaidan, O.F.

    2010-01-01

    This paper presents the results of the WMT10 and MetricsMATR10 shared tasks, which included a translation task, a system combination task, and an evaluation task. We conducted a large-scale manual evaluation of 104 machine translation systems and 41 system combination entries. We used the ranking of

  16. Translation Analysis on Civil Engineering Text Produced by Machine Translator

    Directory of Open Access Journals (Sweden)

    Sutopo Anam

    2018-01-01

    Full Text Available Translation is extremely needed in communication since people have serious problem in the language used. Translation activity is done by the person in charge for translating the material. Translation activity is also able to be done by machine. It is called machine translation, reflected in the programs developed by programmer. One of them is Transtool. Many people used Transtool for helping them in solving the problem related with translation activities. This paper wants to deliver how important is the Transtool program, how effective is Transtool program and how is the function of Transtool for human business. This study applies qualitative research. The sources of data were document and informant. This study used documentation and in dept-interviewing as the techniques for collecting data. The collected data were analyzed by using interactive analysis. The results of the study show that, first; Transtool program is helpful for people in translating the civil engineering text and it functions as the aid or helper, second; the working of Transtool software program is effective enough and third; the result of translation produced by Transtool is good for short and simple sentences and not readable, not understandable and not accurate for long sentences (compound, complex and compound complex thought the result is informative. The translated material must be edited by the professional translator.

  17. Translation Analysis on Civil Engineering Text Produced by Machine Translator

    Science.gov (United States)

    Sutopo, Anam

    2018-02-01

    Translation is extremely needed in communication since people have serious problem in the language used. Translation activity is done by the person in charge for translating the material. Translation activity is also able to be done by machine. It is called machine translation, reflected in the programs developed by programmer. One of them is Transtool. Many people used Transtool for helping them in solving the problem related with translation activities. This paper wants to deliver how important is the Transtool program, how effective is Transtool program and how is the function of Transtool for human business. This study applies qualitative research. The sources of data were document and informant. This study used documentation and in dept-interviewing as the techniques for collecting data. The collected data were analyzed by using interactive analysis. The results of the study show that, first; Transtool program is helpful for people in translating the civil engineering text and it functions as the aid or helper, second; the working of Transtool software program is effective enough and third; the result of translation produced by Transtool is good for short and simple sentences and not readable, not understandable and not accurate for long sentences (compound, complex and compound complex) thought the result is informative. The translated material must be edited by the professional translator.

  18. Findings of the 2011 workshop on statistical machine translation

    NARCIS (Netherlands)

    Callison-Burch, C.; Koehn, P.; Monz, C.; Zaidan, O.F.

    2011-01-01

    This paper presents the results of the WMT11 shared tasks, which included a translation task, a system combination task, and a task for machine translation evaluation metrics. We conducted a large-scale manual evaluation of 148 machine translation systems and 41 system combination entries. We used

  19. Machine Translation from Text

    Science.gov (United States)

    Habash, Nizar; Olive, Joseph; Christianson, Caitlin; McCary, John

    Machine translation (MT) from text, the topic of this chapter, is perhaps the heart of the GALE project. Beyond being a well defined application that stands on its own, MT from text is the link between the automatic speech recognition component and the distillation component. The focus of MT in GALE is on translating from Arabic or Chinese to English. The three languages represent a wide range of linguistic diversity and make the GALE MT task rather challenging and exciting.

  20. Machine Translation Using Constraint-Based Synchronous Grammar

    Institute of Scientific and Technical Information of China (English)

    WONG Fai; DONG Mingchui; HU Dongcheng

    2006-01-01

    A synchronous grammar based on the formalism of context-free grammar was developed by generalizing the first component of production that models the source text. Unlike other synchronous grammars,the grammar allows multiple target productions to be associated to a single production rule which can be used to guide a parser to infer different possible translational equivalences for a recognized input string according to the feature constraints of symbols in the pattern. An extended generalized LR algorithm was adapted to the parsing of the proposed formalism to analyze the syntactic structure of a language. The grammar was used as the basis for building a machine translation system for Portuguese to Chinese translation. The empirical results show that the grammar is more expressive when modeling the translational equivalences of parallel texts for machine translation and grammar rewriting applications.

  1. Word Transition Entropy as an Indicator for Expected Machine Translation Quality

    DEFF Research Database (Denmark)

    Carl, Michael; Schaeffer, Moritz

    2014-01-01

    While most machine translation evaluation techniques (BLEU, NIST, TER, METEOR) assess translation quality based on a set of reference translations, we suggest to evaluate the literality of a set of (human or machine generated) translations to infer their potential quality. We provide evidence whi...

  2. A GRAMMATICAL ADJUSTMENT ANALYSIS OF STATISTICAL MACHINE TRANSLATION METHOD USED BY GOOGLE TRANSLATE COMPARED TO HUMAN TRANSLATION IN TRANSLATING ENGLISH TEXT TO INDONESIAN

    Directory of Open Access Journals (Sweden)

    Eko Pujianto

    2017-04-01

    Full Text Available Google translate is a program which provides fast, free and effortless translating service. This service uses a unique method to translate. The system is called ―Statistical Machine Translation‖, the newest method in automatic translation. Machine translation (MT is an area of many kinds of different subjects of study and technique from linguistics, computers science, artificial intelligent (AI, translation theory, and statistics. SMT works by using statistical methods and mathematics to process the training data. The training data is corpus-based. It is a compilation of sentences and words of the languages (SL and TL from translation done by human. By using this method, Google let their machine discovers the rules for themselves. They do this by analyzing millions of documents that have already been translated by human translators and then generate the result based on the corpus/training data. However, questions arise when the results of the automatic translation prove to be unreliable in some extent. This paper questions the dependability of Google translate in comparison with grammatical adjustment that naturally characterizes human translators' specific advantage. The attempt is manifested through the analysis of the TL of some texts translated by the SMT. It is expected that by using the sample of TL produced by SMT we can learn the potential flaws of the translation. If such exists, the partial of more substantial undependability of SMT may open more windows to the debates of whether this service may suffice the users‘ need.

  3. Machine translation with minimal reliance on parallel resources

    CERN Document Server

    Tambouratzis, George; Sofianopoulos, Sokratis

    2017-01-01

    This book provides a unified view on a new methodology for Machine Translation (MT). This methodology extracts information from widely available resources (extensive monolingual corpora) while only assuming the existence of a very limited parallel corpus, thus having a unique starting point to Statistical Machine Translation (SMT). In this book, a detailed presentation of the methodology principles and system architecture is followed by a series of experiments, where the proposed system is compared to other MT systems using a set of established metrics including BLEU, NIST, Meteor and TER. Additionally, a free-to-use code is available, that allows the creation of new MT systems. The volume is addressed to both language professionals and researchers. Prerequisites for the readers are very limited and include a basic understanding of the machine translation as well as of the basic tools of natural language processing.

  4. Parsing statistical machine translation output

    NARCIS (Netherlands)

    Carter, S.; Monz, C.; Vetulani, Z.

    2009-01-01

    Despite increasing research into the use of syntax during statistical machine translation, the incorporation of syntax into language models has seen limited success. We present a study of the discriminative abilities of generative syntax-based language models, over and above standard n-gram models,

  5. Comparison of Three English-to-Dutch Machine Translations of SNOMED CT Procedures

    NARCIS (Netherlands)

    Cornet, Ronald; Hill, Carly; de Keizer, Nicolette

    2017-01-01

    Dutch interface terminologies are needed to use SNOMED CT in the Netherlands. Machine translation may support in their creation. The aim of our study is to compare different machine translations of procedures in SNOMED CT. Procedures were translated using Google Translate, Matecat, and Thot. Google

  6. An Evaluation of Output Quality of Machine Translation (Padideh Software vs. Google Translate)

    Science.gov (United States)

    Azer, Haniyeh Sadeghi; Aghayi, Mohammad Bagher

    2015-01-01

    This study aims to evaluate the translation quality of two machine translation systems in translating six different text-types, from English to Persian. The evaluation was based on criteria proposed by Van Slype (1979). The proposed model for evaluation is a black-box type, comparative and adequacy-oriented evaluation. To conduct the evaluation, a…

  7. A translator and simulator for the Burroughs D machine

    Science.gov (United States)

    Roberts, J.

    1972-01-01

    The D Machine is described as a small user microprogrammable computer designed to be a versatile building block for such diverse functions as: disk file controllers, I/O controllers, and emulators. TRANSLANG is an ALGOL-like language, which allows D Machine users to write microprograms in an English-like format as opposed to creating binary bit pattern maps. The TRANSLANG translator parses TRANSLANG programs into D Machine microinstruction bit patterns which can be executed on the D Machine simulator. In addition to simulation and translation, the two programs also offer several debugging tools, such as: a full set of diagnostic error messages, register dumps, simulated memory dumps, traces on instructions and groups of instructions, and breakpoints.

  8. Machine Translation - A Gentle Introduction

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 3; Issue 7. Machine Translation - A Gentle Introduction. Durgesh D Rao. General Article Volume 3 Issue 7 July 1998 pp 61-70. Fulltext. Click here to view fulltext PDF. Permanent link: https://www.ias.ac.in/article/fulltext/reso/003/07/0061-0070 ...

  9. Machine Learning Approaches for Clinical Psychology and Psychiatry.

    Science.gov (United States)

    Dwyer, Dominic B; Falkai, Peter; Koutsouleris, Nikolaos

    2018-05-07

    Machine learning approaches for clinical psychology and psychiatry explicitly focus on learning statistical functions from multidimensional data sets to make generalizable predictions about individuals. The goal of this review is to provide an accessible understanding of why this approach is important for future practice given its potential to augment decisions associated with the diagnosis, prognosis, and treatment of people suffering from mental illness using clinical and biological data. To this end, the limitations of current statistical paradigms in mental health research are critiqued, and an introduction is provided to critical machine learning methods used in clinical studies. A selective literature review is then presented aiming to reinforce the usefulness of machine learning methods and provide evidence of their potential. In the context of promising initial results, the current limitations of machine learning approaches are addressed, and considerations for future clinical translation are outlined.

  10. Grammatical Metaphor, Controlled Languageand Machine Translation

    DEFF Research Database (Denmark)

    Møller, Margrethe

    2003-01-01

    It is a general assumption that 1) the readability and clarity of LSP texts written in a controlled language are better than uncontrolled texts and 2) that controlled languages produce better results with machine translation than uncontrolled languages. Controlled languages impose lexical...

  11. Machine Translation as a complex system, and the phenomenon of Esperanto

    NARCIS (Netherlands)

    Gobbo, F.

    2015-01-01

    The history of machine translation and the history of Esperanto have long been connected, as they are two different ways to deal with the same problem: the problem of communication across language barriers. Language can be considered a Complex Adaptive System (CAS), and machine translation too. In

  12. The Dostoevsky Machine in Georgetown: scientific translation in the Cold War.

    Science.gov (United States)

    Gordin, Michael D

    2016-04-01

    Machine Translation (MT) is now ubiquitous in discussions of translation. The roots of this phenomenon - first publicly unveiled in the so-called 'Georgetown-IBM Experiment' on 9 January 1954 - displayed not only the technological utopianism still associated with dreams of a universal computer translator, but was deeply enmeshed in the political pressures of the Cold War and a dominating conception of scientific writing as both the goal of machine translation as well as its method. Machine translation was created, in part, as a solution to a perceived crisis sparked by the massive expansion of Soviet science. Scientific prose was also perceived as linguistically simpler, and so served as the model for how to turn a language into a series of algorithms. This paper follows the rise of the Georgetown program - the largest single program in the world - from 1954 to the (as it turns out, temporary) collapse of MT in 1964.

  13. A Survey of Statistical Machine Translation

    Science.gov (United States)

    2007-04-01

    methods are notoriously sen- sitive to domain differences, however, so the move to informal text is likely to present many interesting challenges ...Och, Christoph Tillman, and Hermann Ney. Improved alignment models for statistical machine translation. In Proc. of EMNLP- VLC , pages 20–28, Jun 1999

  14. The evolution and practical application of machine translation system (1)

    Science.gov (United States)

    Tominaga, Isao; Sato, Masayuki

    This paper describes a development, practical applicatioin, problem of a system, evaluation of practical system, and development trend of machine translation. Most recent system contains next four problems. 1) the vagueness of a text, 2) a difference of the definition of the terminology between different language, 3) the preparing of a large-scale translation dictionary, 4) the development of a software for the logical inference. Machine translation system is already used practically in many industry fields. However, many problems are not solved. The implementation of an ideal system will be after 15 years. Also, this paper described seven evaluation items detailedly. This English abstract was made by Mu system.

  15. Using Linguistic Knowledge in Statistical Machine Translation

    Science.gov (United States)

    2010-09-01

    reproduced in (Belnap and Haeri, 1997)), a sociolinguistic phenomenon where the literary standard differs considerably from the vernacular varieties...Machine Translation Summit (MT-Summit). N. Haeri. 2000. Form and ideology: Arabic sociolinguistics and beyond. Annual Review of Anthropology, 29. D. Hakkani

  16. Findings of the 2009 Workshop on Statistical Machine Translation

    NARCIS (Netherlands)

    Callison-Burch, C.; Koehn, P.; Monz, C.; Schroeder, J.; Callison-Burch, C.; Koehn, P.; Monz, C.; Schroeder, J.

    2009-01-01

    This paper presents the results of the WMT09 shared tasks, which included a translation task, a system combination task, and an evaluation task. We conducted a large-scale manual evaluation of 87 machine translation systems and 22 system combination entries. We used the ranking of these systems to

  17. Integrating source-language context into phrase-based statistical machine translation

    NARCIS (Netherlands)

    Haque, R.; Kumar Naskar, S.; Bosch, A.P.J. van den; Way, A.

    2011-01-01

    The translation features typically used in Phrase-Based Statistical Machine Translation (PB-SMT) model dependencies between the source and target phrases, but not among the phrases in the source language themselves. A swathe of research has demonstrated that integrating source context modelling

  18. Translation: Aids, Robots, and Automation.

    Science.gov (United States)

    Andreyewsky, Alexander

    1981-01-01

    Examines electronic aids to translation both as ways to automate it and as an approach to solve problems resulting from shortage of qualified translators. Describes the limitations of robotic MT (Machine Translation) systems, viewing MAT (Machine-Aided Translation) as the only practical solution and the best vehicle for further automation. (MES)

  19. A Conjoint Analysis Framework for Evaluating User Preferences in Machine Translation.

    Science.gov (United States)

    Kirchhoff, Katrin; Capurro, Daniel; Turner, Anne M

    2014-03-01

    Despite much research on machine translation (MT) evaluation, there is surprisingly little work that directly measures users' intuitive or emotional preferences regarding different types of MT errors. However, the elicitation and modeling of user preferences is an important prerequisite for research on user adaptation and customization of MT engines. In this paper we explore the use of conjoint analysis as a formal quantitative framework to assess users' relative preferences for different types of translation errors. We apply our approach to the analysis of MT output from translating public health documents from English into Spanish. Our results indicate that word order errors are clearly the most dispreferred error type, followed by word sense, morphological, and function word errors. The conjoint analysis-based model is able to predict user preferences more accurately than a baseline model that chooses the translation with the fewest errors overall. Additionally we analyze the effect of using a crowd-sourced respondent population versus a sample of domain experts and observe that main preference effects are remarkably stable across the two samples.

  20. What does Attention in Neural Machine Translation Pay Attention to?

    NARCIS (Netherlands)

    Ghader, H.; Monz, C.; Kondrak, G.; Watanabe, T.

    2017-01-01

    Attention in neural machine translation provides the possibility to encode relevant parts of the source sentence at each translation step. As a result, attention is considered to be an alignment model as well. However, there is no work that specifically studies attention and provides analysis of

  1. Local health department translation processes: potential of machine translation technologies to help meet needs.

    Science.gov (United States)

    Turner, Anne M; Mandel, Hannah; Capurro, Daniel

    2013-01-01

    Limited English proficiency (LEP), defined as a limited ability to read, speak, write, or understand English, is associated with health disparities. Despite federal and state requirements to translate health information, the vast majority of health materials are solely available in English. This project investigates barriers to translation of health information and explores new technologies to improve access to multilingual public health materials. We surveyed all 77 local health departments (LHDs) in the Northwest about translation needs, practices, barriers and attitudes towards machine translation (MT). We received 67 responses from 45 LHDs. Translation of health materials is the principle strategy used by LHDs to reach LEP populations. Cost and access to qualified translators are principle barriers to producing multilingual materials. Thirteen LHDs have used online MT tools. Many respondents expressed concerns about the accuracy of MT. Overall, respondents were positive about its potential use, if low costs and quality could be assured.

  2. Language Model Adaptation Using Machine-Translated Text for Resource-Deficient Languages

    Directory of Open Access Journals (Sweden)

    Sadaoki Furui

    2009-01-01

    Full Text Available Text corpus size is an important issue when building a language model (LM. This is a particularly important issue for languages where little data is available. This paper introduces an LM adaptation technique to improve an LM built using a small amount of task-dependent text with the help of a machine-translated text corpus. Icelandic speech recognition experiments were performed using data, machine translated (MT from English to Icelandic on a word-by-word and sentence-by-sentence basis. LM interpolation using the baseline LM and an LM built from either word-by-word or sentence-by-sentence translated text reduced the word error rate significantly when manually obtained utterances used as a baseline were very sparse.

  3. Machine Translation as a Model for Overcoming Some Common Errors in English-into-Arabic Translation among EFL University Freshmen

    Science.gov (United States)

    El-Banna, Adel I.; Naeem, Marwa A.

    2016-01-01

    This research work aimed at making use of Machine Translation to help students avoid some syntactic, semantic and pragmatic common errors in translation from English into Arabic. Participants were a hundred and five freshmen who studied the "Translation Common Errors Remedial Program" prepared by the researchers. A testing kit that…

  4. Modeling workflow to design machine translation applications for public health practice.

    Science.gov (United States)

    Turner, Anne M; Brownstein, Megumu K; Cole, Kate; Karasz, Hilary; Kirchhoff, Katrin

    2015-02-01

    Provide a detailed understanding of the information workflow processes related to translating health promotion materials for limited English proficiency individuals in order to inform the design of context-driven machine translation (MT) tools for public health (PH). We applied a cognitive work analysis framework to investigate the translation information workflow processes of two large health departments in Washington State. Researchers conducted interviews, performed a task analysis, and validated results with PH professionals to model translation workflow and identify functional requirements for a translation system for PH. The study resulted in a detailed description of work related to translation of PH materials, an information workflow diagram, and a description of attitudes towards MT technology. We identified a number of themes that hold design implications for incorporating MT in PH translation practice. A PH translation tool prototype was designed based on these findings. This study underscores the importance of understanding the work context and information workflow for which systems will be designed. Based on themes and translation information workflow processes, we identified key design guidelines for incorporating MT into PH translation work. Primary amongst these is that MT should be followed by human review for translations to be of high quality and for the technology to be adopted into practice. The time and costs of creating multilingual health promotion materials are barriers to translation. PH personnel were interested in MT's potential to improve access to low-cost translated PH materials, but expressed concerns about ensuring quality. We outline design considerations and a potential machine translation tool to best fit MT systems into PH practice. Copyright © 2014 Elsevier Inc. All rights reserved.

  5. An Evaluative Study of Machine Translation in the EFL Scenario of Saudi Arabia

    Directory of Open Access Journals (Sweden)

    Raneem Khalid Al-Tuwayrish

    2016-02-01

    Full Text Available Artificial Intelligence or AI as it is popularly known and its corollary, Machine Translation (MT have long engaged scientists, thinkers and linguists alike in the twenty first century. However, the wider question that lies in the relation between technology and translation is, What does technology do to language? This is an important question in the current paradigm because new translation technologies, such as, translation memories, data-based machine translation, and collaborative translation, far from being just additional tools, are changing the very nature of the translators’ cognitive activity, social relations, and professional standing. In fact, in some translation situations such as when translating technical materials or subject matter that are not a specialization with human translators, one potentially needs technology.  The purview of this paper, however, is limited to the role of MT in day to day situations where the generic MT tools like Google Translate or Bing Translator are encouraged. Further, it endeavours to weigh and empirically demonstrate the pros and cons of MT with a view to recommending measures for better communication training in the EFL set up of Saudi Arabia. Keywords: AI, MT, translation, technology, necessity, communication

  6. The Integration of Project-Based Methodology into Teaching in Machine Translation

    Science.gov (United States)

    Madkour, Magda

    2016-01-01

    This quantitative-qualitative analytical research aimed at investigating the effect of integrating project-based teaching methodology into teaching machine translation on students' performance. Data was collected from the graduate students in the College of Languages and Translation, at Imam Muhammad Ibn Saud Islamic University, Riyadh, Saudi…

  7. Recycling Texts: Human evaluation of example-based machine translation subtitles for DVD

    DEFF Research Database (Denmark)

    Flanagan, Marian

    2009-01-01

    This project focuses on translation reusability in audiovisual contexts. Specifically, the project seeks to establish (1) whether target language subtitles produced by an Example-Based Machine Translation (EBMT) system are considered intelligible and acceptable by viewers of movies on DVD, and (2...

  8. Finding Translation Examples for Under-Resourced Language Pairs or for Narrow Domains; the Case for Machine Translation

    Directory of Open Access Journals (Sweden)

    Dan Tufis

    2012-07-01

    Full Text Available The cyberspace is populated with valuable information sources, expressed in about 1500 different languages and dialects. Yet, for the vast majority of WEB surfers this wealth of information is practically inaccessible or meaningless. Recent advancements in cross-lingual information retrieval, multilingual summarization, cross-lingual question answering and machine translation promise to narrow the linguistic gaps and lower the communication barriers between humans and/or software agents. Most of these language technologies are based on statistical machine learning techniques which require large volumes of cross lingual data. The most adequate type of cross-lingual data is represented by parallel corpora, collection of reciprocal translations. However, it is not easy to find enough parallel data for any language pair might be of interest. When required parallel data refers to specialized (narrow domains, the scarcity of data becomes even more acute. Intelligent information extraction techniques from comparable corpora provide one of the possible answers to this lack of translation data.

  9. An Evaluation of Online Machine Translation of Arabic into English News Headlines: Implications on Students' Learning Purposes

    Science.gov (United States)

    Kadhim, Kais A.; Habeeb, Luwaytha S.; Sapar, Ahmad Arifin; Hussin, Zaharah; Abdullah, Muhammad Ridhuan Tony Lim

    2013-01-01

    Nowadays, online Machine Translation (MT) is used widely with translation software, such as Google and Babylon, being easily available and downloadable. This study aims to test the translation quality of these two machine systems in translating Arabic news headlines into English. 40 Arabic news headlines were selected from three online sources,…

  10. Modeling and prediction of human word search behavior in interactive machine translation

    Science.gov (United States)

    Ji, Duo; Yu, Bai; Ma, Bin; Ye, Na

    2017-12-01

    As a kind of computer aided translation method, Interactive Machine Translation technology reduced manual translation repetitive and mechanical operation through a variety of methods, so as to get the translation efficiency, and played an important role in the practical application of the translation work. In this paper, we regarded the behavior of users' frequently searching for words in the translation process as the research object, and transformed the behavior to the translation selection problem under the current translation. The paper presented a prediction model, which is a comprehensive utilization of alignment model, translation model and language model of the searching words behavior. It achieved a highly accurate prediction of searching words behavior, and reduced the switching of mouse and keyboard operations in the users' translation process.

  11. Analysis of MultiWord Expression Translation Errors in Statistical Machine Translation

    DEFF Research Database (Denmark)

    Klyueva, Natalia; Liyanapathirana, Jeevanthi

    2015-01-01

    In this paper, we analyse the usage of multiword expressions (MWE) in Statistical Machine Translation (SMT). We exploit the Moses SMT toolkit to train models for French-English and Czech-Russian language pairs. For each language pair, two models were built: a baseline model without additional MWE...... data and the model enhanced with information on MWE. For the French-English pair, we tried three methods of introducing the MWE data. For Czech-Russian pair, we used just one method – adding automatically extracted data as a parallel corpus....

  12. Investigating Connectivity and Consistency Criteria for Phrase Pair Extraction in Statistical Machine Translation

    NARCIS (Netherlands)

    Martzoukos, S.; Costa Florêncio, C.; Monz, C.; Kornai, A.; Kuhlmann, M.

    2013-01-01

    The consistency method has been established as the standard strategy for extracting high quality translation rules in statistical machine translation (SMT). However, no attention has been drawn to why this method is successful, other than empirical evidence. Using concepts from graph theory, we

  13. Empirical Investigation of Optimization Algorithms in Neural Machine Translation

    Directory of Open Access Journals (Sweden)

    Bahar Parnia

    2017-06-01

    Full Text Available Training neural networks is a non-convex and a high-dimensional optimization problem. In this paper, we provide a comparative study of the most popular stochastic optimization techniques used to train neural networks. We evaluate the methods in terms of convergence speed, translation quality, and training stability. In addition, we investigate combinations that seek to improve optimization in terms of these aspects. We train state-of-the-art attention-based models and apply them to perform neural machine translation. We demonstrate our results on two tasks: WMT 2016 En→Ro and WMT 2015 De→En.

  14. Using example-based machine translation to translate DVD subtitles

    DEFF Research Database (Denmark)

    Flanagan, Marian

    between Swedish and Danish and Swedish and Norwegian subtitles, with the company already reporting a successful return on their investment. The hybrid EBMT/SMT system used in the current research, on the other hand, remains within the confines of academic research, and the real potential of the system...... allotted to produce the subtitles have both decreased. Therefore, this market is recognised as a potential real-world application of MT. Recent publications have introduced Corpus-Based MT approaches to translate subtitles. An SMT system has been implemented in a Swedish subtitling company to translate...

  15. A user-based usability assessment of raw machine translated technical instructions

    OpenAIRE

    Doherty, Stephen; O'Brien, Sharon

    2012-01-01

    Despite the growth of statistical machine translation (SMT) research and development in recent years, it remains somewhat out of reach for the translation community where programming expertise and knowledge of statistics tend not to be commonplace. While the concept of SMT is relatively straightforward, its implementation in functioning systems remains difficult for most, regardless of expertise. More recently, however, developments such as SmartMATE have emerged which aim to assist users in ...

  16. Latent domain models for statistical machine translation

    NARCIS (Netherlands)

    Hoàng, C.

    2017-01-01

    A data-driven approach to model translation suffers from the data mismatch problem and demands domain adaptation techniques. Given parallel training data originating from a specific domain, training an MT system on the data would result in a rather suboptimal translation for other domains. But does

  17. An Evaluative Study of Machine Translation in the EFL Scenario of Saudi Arabia

    Science.gov (United States)

    Al-Tuwayrish, Raneem Khalid

    2016-01-01

    Artificial Intelligence or AI as it is popularly known and its corollary, Machine Translation (MT) have long engaged scientists, thinkers and linguists alike in the twenty first century. However, the wider question that lies in the relation between technology and translation is, What does technology do to language? This is an important question in…

  18. Foreign Developments in Information Processing and Machine Translation, No. 1

    Science.gov (United States)

    1960-09-29

    technicians] (Sestier (A.) -- La Traduction automatfguT"" des textes ecrits scJQntifiqaes ej^J^chplc^es dxun langage~ dans__un’"*""* ’’^t^’T^^i...are more and more comprehensible to others than machine translation technicians will result. Sketch of a proaram. This outline of work xtfiich will

  19. The Hermeneutical Approach in Translation Studies

    Directory of Open Access Journals (Sweden)

    Bernd Stefanink

    2017-09-01

    Full Text Available Our aim is to convince the reader of the validity of the hermeneutical approach in translation studies. In a first part, we will show that this validity is based on the fact that the hermeneutical approach integrates factors like subjectivity, intuition, corporeality and creativity in its theoretical reflection, being thus close to the reality of the translation process. In a second part, we will situate this approach in the context of the development of modern translation studies since the 1950s, and show that this development was characterized by a dominating tendency that led from an atomistic to a more and more holistic view of the translation unit, legitimating the holistic approach, which is fundamental in translational hermeneutics. Our third part relates the history of philosophical hermeneutics as the legitimate foundation of translational hermeneutics. In a fourth part, devoted to the “outcoming perspectives”, we will try to reinforce the legitimacy of the hermeneutical approach by showing how it is supported by recent results of research in cognitive science. In order to foster further research in translational hermeneutics we also offer a methodology based on hermeneutic principles to study the translation process. Finally, we give an example of legitimation of a creative problemsolving based on a hermeneutical approach of a translation problem which finds its validation in the results of cognitive research.

  20. Crawl and crowd to bring machine translation to under-resourced languages

    NARCIS (Netherlands)

    Toral Ruiz, Antonio

    2017-01-01

    We present a widely applicable methodology to bring machine translation (MT) to under-resourced languages in a cost-effective and rapid manner. Our proposal relies on web crawling to automatically acquire parallel data to train statistical MT systems if any such data can be found for the language

  1. Machine translation (MT): qualità, produttività, customer satisfaction

    OpenAIRE

    Fellet, Anna

    2010-01-01

    The aim of the present research is to examine the impact of recent technological developments in machine translation (MT) in the language industry. The objectives are: 1. To define the value of MT in terms of suitability and convenience in meeting expressed requirements in those cases where MT is demanded; 2. To examine the potential increase in productivity through a conscious use of the tool; 3. To analyse those activities aimed at satisfying the customer’s explicit and impli...

  2. Improving the quality of automated DVD subtitles via example-based machine translation

    DEFF Research Database (Denmark)

    Armstrong, Stephen; Caffrey, Colm; Flanagan, Marian

    Denoual (2005) discovered that, contrary to popular belief, an Example-Based Machine Translation system trained on heterogeneous data produced significantly better results than a system trained on homogeneous data. Using similar evaluation metrics and a few additional ones, in this paper we show...

  3. CloudLM: a Cloud-based Language Model for Machine Translation

    Directory of Open Access Journals (Sweden)

    Ferrández-Tordera Jorge

    2016-04-01

    Full Text Available Language models (LMs are an essential element in statistical approaches to natural language processing for tasks such as speech recognition and machine translation (MT. The advent of big data leads to the availability of massive amounts of data to build LMs, and in fact, for the most prominent languages, using current techniques and hardware, it is not feasible to train LMs with all the data available nowadays. At the same time, it has been shown that the more data is used for a LM the better the performance, e.g. for MT, without any indication yet of reaching a plateau. This paper presents CloudLM, an open-source cloud-based LM intended for MT, which allows to query distributed LMs. CloudLM relies on Apache Solr and provides the functionality of state-of-the-art language modelling (it builds upon KenLM, while allowing to query massive LMs (as the use of local memory is drastically reduced, at the expense of slower decoding speed.

  4. Functional approaches in translation studies in Germany Functional approaches in translation studies in Germany

    Directory of Open Access Journals (Sweden)

    Paul Kussmaul

    2008-04-01

    Full Text Available In the early phase of translation studies in Germany, contrastive linguistics played a major role. I shall briefly describe this approach so that the functional approach will become clearer by contrast. Influenced by the representatives of stylistique comparée, Vinay/Darbelnet (1968 Wolfram Wilss, for instance, in his early work (1971, 1977 makes frequent use of the notion transposition (German “Ausdrucksverschiebung“, cf. also Catford’s (1965 term shift. As a whole, of course, Wilss’ work has a much broader scope. More recently, he has investigated the role of cognition (1988 and the various factors in translator behaviour (1996. Nevertheless, transposition is still a very important and useful notion in describing the translation process. The need for transpositions arises when there is no possibility of formal one-to-one correspondence between source and target-language structures. The basic idea is that whenever there is a need for transposition, we are faced with a translation problem. In the early phase of translation studies in Germany, contrastive linguistics played a major role. I shall briefly describe this approach so that the functional approach will become clearer by contrast. Influenced by the representatives of stylistique comparée, Vinay/Darbelnet (1968 Wolfram Wilss, for instance, in his early work (1971, 1977 makes frequent use of the notion transposition (German “Ausdrucksverschiebung“, cf. also Catford’s (1965 term shift. As a whole, of course, Wilss’ work has a much broader scope. More recently, he has investigated the role of cognition (1988 and the various factors in translator behaviour (1996. Nevertheless, transposition is still a very important and useful notion in describing the translation process. The need for transpositions arises when there is no possibility of formal one-to-one correspondence between source and target-language structures. The basic idea is that whenever there is a need for

  5. Extracting Date/Time Expressions in Super-Function Based Japanese-English Machine Translation

    Science.gov (United States)

    Sasayama, Manabu; Kuroiwa, Shingo; Ren, Fuji

    Super-Function Based Machine Translation(SFBMT) which is a type of Example-Based Machine Translation has a feature which makes it possible to expand the coverage of examples by changing nouns into variables, however, there were problems extracting entire date/time expressions containing parts-of-speech other than nouns, because only nouns/numbers were changed into variables. We describe a method for extracting date/time expressions for SFBMT. SFBMT uses noun determination rules to extract nouns and a bilingual dictionary to obtain correspondence of the extracted nouns between the source and the target languages. In this method, we add a rule to extract date/time expressions and then extract date/time expressions from a Japanese-English bilingual corpus. The evaluation results shows that the precision of this method for Japanese sentences is 96.7%, with a recall of 98.2% and the precision for English sentences is 94.7%, with a recall of 92.7%.

  6. Comparative Human and Automatic Evaluation of Glass-Box and Black-Box Approaches to Interactive Translation Prediction

    Directory of Open Access Journals (Sweden)

    Torregrosa Daniel

    2017-06-01

    Full Text Available Interactive translation prediction (ITP is a modality of computer-aided translation that assists professional translators by offering context-based computer-generated continuation suggestions as they type. While most state-of-the-art ITP systems follow a glass-box approach, meaning that they are tightly coupled to an adapted machine translation system, a black-box approach which does not need access to the inner workings of the bilingual resources used to generate the suggestions has been recently proposed in the literature: this new approach allows new sources of bilingual information to be included almost seamlessly. In this paper, we compare for the first time the glass-box and the black-box approaches by means of an automatic evaluation of translation tasks between related languages such as English–Spanish and unrelated ones such as Arabic–English and English–Chinese, showing that, with our setup, 20%–50% of keystrokes could be saved using either method and that the black-box approach outperformed the glass-box one in five out of six scenarios operating under similar conditions. We also performed a preliminary human evaluation of English to Spanish translation for both approaches. On average, the evaluators saved 10% keystrokes and were 4% faster with the black-box approach, and saved 15% keystrokes and were 12% slower with the glass-box one; but they could have saved 51% and 69% keystrokes respectively if they had used all the compatible suggestions. Users felt the suggestions helped them to translate faster and easier. All the tools used to perform the evaluation are available as free/open–source software.

  7. Adaptation of machine translation for multilingual information retrieval in the medical domain.

    Science.gov (United States)

    Pecina, Pavel; Dušek, Ondřej; Goeuriot, Lorraine; Hajič, Jan; Hlaváčová, Jaroslava; Jones, Gareth J F; Kelly, Liadh; Leveling, Johannes; Mareček, David; Novák, Michal; Popel, Martin; Rosa, Rudolf; Tamchyna, Aleš; Urešová, Zdeňka

    2014-07-01

    We investigate machine translation (MT) of user search queries in the context of cross-lingual information retrieval (IR) in the medical domain. The main focus is on techniques to adapt MT to increase translation quality; however, we also explore MT adaptation to improve effectiveness of cross-lingual IR. Our MT system is Moses, a state-of-the-art phrase-based statistical machine translation system. The IR system is based on the BM25 retrieval model implemented in the Lucene search engine. The MT techniques employed in this work include in-domain training and tuning, intelligent training data selection, optimization of phrase table configuration, compound splitting, and exploiting synonyms as translation variants. The IR methods include morphological normalization and using multiple translation variants for query expansion. The experiments are performed and thoroughly evaluated on three language pairs: Czech-English, German-English, and French-English. MT quality is evaluated on data sets created within the Khresmoi project and IR effectiveness is tested on the CLEF eHealth 2013 data sets. The search query translation results achieved in our experiments are outstanding - our systems outperform not only our strong baselines, but also Google Translate and Microsoft Bing Translator in direct comparison carried out on all the language pairs. The baseline BLEU scores increased from 26.59 to 41.45 for Czech-English, from 23.03 to 40.82 for German-English, and from 32.67 to 40.82 for French-English. This is a 55% improvement on average. In terms of the IR performance on this particular test collection, a significant improvement over the baseline is achieved only for French-English. For Czech-English and German-English, the increased MT quality does not lead to better IR results. Most of the MT techniques employed in our experiments improve MT of medical search queries. Especially the intelligent training data selection proves to be very successful for domain adaptation of

  8. Personalized translational epilepsy research - Novel approaches and future perspectives: Part II: Experimental and translational approaches.

    Science.gov (United States)

    Bauer, Sebastian; van Alphen, Natascha; Becker, Albert; Chiocchetti, Andreas; Deichmann, Ralf; Deller, Thomas; Freiman, Thomas; Freitag, Christine M; Gehrig, Johannes; Hermsen, Anke M; Jedlicka, Peter; Kell, Christian; Klein, Karl Martin; Knake, Susanne; Kullmann, Dimitri M; Liebner, Stefan; Norwood, Braxton A; Omigie, Diana; Plate, Karlheinz; Reif, Andreas; Reif, Philipp S; Reiss, Yvonne; Roeper, Jochen; Ronellenfitsch, Michael W; Schorge, Stephanie; Schratt, Gerhard; Schwarzacher, Stephan W; Steinbach, Joachim P; Strzelczyk, Adam; Triesch, Jochen; Wagner, Marlies; Walker, Matthew C; von Wegner, Frederic; Rosenow, Felix

    2017-11-01

    Despite the availability of more than 15 new "antiepileptic drugs", the proportion of patients with pharmacoresistant epilepsy has remained constant at about 20-30%. Furthermore, no disease-modifying treatments shown to prevent the development of epilepsy following an initial precipitating brain injury or to reverse established epilepsy have been identified to date. This is likely in part due to the polyetiologic nature of epilepsy, which in turn requires personalized medicine approaches. Recent advances in imaging, pathology, genetics, and epigenetics have led to new pathophysiological concepts and the identification of monogenic causes of epilepsy. In the context of these advances, the First International Symposium on Personalized Translational Epilepsy Research (1st ISymPTER) was held in Frankfurt on September 8, 2016, to discuss novel approaches and future perspectives for personalized translational research. These included new developments and ideas in a range of experimental and clinical areas such as deep phenotyping, quantitative brain imaging, EEG/MEG-based analysis of network dysfunction, tissue-based translational studies, innate immunity mechanisms, microRNA as treatment targets, functional characterization of genetic variants in human cell models and rodent organotypic slice cultures, personalized treatment approaches for monogenic epilepsies, blood-brain barrier dysfunction, therapeutic focal tissue modification, computational modeling for target and biomarker identification, and cost analysis in (monogenic) disease and its treatment. This report on the meeting proceedings is aimed at stimulating much needed investments of time and resources in personalized translational epilepsy research. This Part II includes the experimental and translational approaches and a discussion of the future perspectives, while the diagnostic methods, EEG network analysis, biomarkers, and personalized treatment approaches were addressed in Part I [1]. Copyright © 2017

  9. ProLanGO: Protein Function Prediction Using Neural Machine Translation Based on a Recurrent Neural Network.

    Science.gov (United States)

    Cao, Renzhi; Freitas, Colton; Chan, Leong; Sun, Miao; Jiang, Haiqing; Chen, Zhangxin

    2017-10-17

    With the development of next generation sequencing techniques, it is fast and cheap to determine protein sequences but relatively slow and expensive to extract useful information from protein sequences because of limitations of traditional biological experimental techniques. Protein function prediction has been a long standing challenge to fill the gap between the huge amount of protein sequences and the known function. In this paper, we propose a novel method to convert the protein function problem into a language translation problem by the new proposed protein sequence language "ProLan" to the protein function language "GOLan", and build a neural machine translation model based on recurrent neural networks to translate "ProLan" language to "GOLan" language. We blindly tested our method by attending the latest third Critical Assessment of Function Annotation (CAFA 3) in 2016, and also evaluate the performance of our methods on selected proteins whose function was released after CAFA competition. The good performance on the training and testing datasets demonstrates that our new proposed method is a promising direction for protein function prediction. In summary, we first time propose a method which converts the protein function prediction problem to a language translation problem and applies a neural machine translation model for protein function prediction.

  10. A Comparative Study of "Google Translate" Translations: An Error Analysis of English-to-Persian and Persian-to-English Translations

    Science.gov (United States)

    Ghasemi, Hadis; Hashemian, Mahmood

    2016-01-01

    Both lack of time and the need to translate texts for numerous reasons brought about an increase in studying machine translation with a history spanning over 65 years. During the last decades, Google Translate, as a statistical machine translation (SMT), was in the center of attention for supporting 90 languages. Although there are many studies on…

  11. Our Policies, Their Text: German Language Students' Strategies with and Beliefs about Web-Based Machine Translation

    Science.gov (United States)

    White, Kelsey D.; Heidrich, Emily

    2013-01-01

    Most educators are aware that some students utilize web-based machine translators for foreign language assignments, however, little research has been done to determine how and why students utilize these programs, or what the implications are for language learning and teaching. In this mixed-methods study we utilized surveys, a translation task,…

  12. Designing Course An Initial Approach To Translation Teaching

    Directory of Open Access Journals (Sweden)

    Roswani Siregar

    2017-09-01

    Full Text Available Along with the human history translation is the sustainable communication tool among the cultures to preserve this knowledge from generation to generations. Undoubtedly both translation plays a very important role in an increasingly globalized world and translators have the prominent roles in the development of countries. Many translators really enjoy their work but hesitated to teach a course due to their lack of pedagogical knowledge and believe that the translation skill is gained by personal experiences and talents. Thus this paper attempt to promote the translation teaching in classroom by set the preliminary approach to teach translation. The sequences of teaching design are described by propose the brief definition to the nature of translation the importance translation teaching the translator competence and design of translation course. This paper is the preliminary approach to translation teaching for beginners in university setting.

  13. Integrated Features by Administering the Support Vector Machine (SVM of Translational Initiations Sites in Alternative Polymorphic Contex

    Directory of Open Access Journals (Sweden)

    Nurul Arneida Husin

    2012-04-01

    Full Text Available Many algorithms and methods have been proposed for classification problems in bioinformatics. In this study, the discriminative approach in particular support vector machines (SVM is employed to recognize the studied TIS patterns. The applied discriminative approach is used to learn about some discriminant functions of samples that have been labelled as positive or negative. After learning, the discriminant functions are employed to decide whether a new sample is true or false. In this study, support vector machines (SVM is employed to recognize the patterns for studied translational initiation sites in alternative weak context. The method has been optimized with the best parameters selected; c=100, E=10-6 and ex=2 for non linear kernel function. Results show that with top 5 features and non linear kernel, the best prediction accuracy achieved is 95.8%. J48 algorithm is applied to compare with SVM with top 15 features and the results show a good prediction accuracy of 95.8%. This indicates that the top 5 features selected by the IGR method and that are performed by SVM are sufficient to use in the prediction of TIS in weak contexts.

  14. An Open-Source Web-Based Tool for Resource-Agnostic Interactive Translation Prediction

    Directory of Open Access Journals (Sweden)

    Daniel Torregrosa

    2014-09-01

    Full Text Available We present a web-based open-source tool for interactive translation prediction (ITP and describe its underlying architecture. ITP systems assist human translators by making context-based computer-generated suggestions as they type. Most of the ITP systems in literature are strongly coupled with a statistical machine translation system that is conveniently adapted to provide the suggestions. Our system, however, follows a resource-agnostic approach and suggestions are obtained from any unmodified black-box bilingual resource. This paper reviews our ITP method and describes the architecture of Forecat, a web tool, partly based on the recent technology of web components, that eases the use of our ITP approach in any web application requiring this kind of translation assistance. We also evaluate the performance of our method when using an unmodified Moses-based statistical machine translation system as the bilingual resource.

  15. Data extraction from machine-translated versus original language randomized trial reports: a comparative study.

    Science.gov (United States)

    Balk, Ethan M; Chung, Mei; Chen, Minghua L; Chang, Lina Kong Win; Trikalinos, Thomas A

    2013-11-07

    Google Translate offers free Web-based translation, but it is unknown whether its translation accuracy is sufficient to use in systematic reviews to mitigate concerns about language bias. We compared data extraction from non-English language studies with extraction from translations by Google Translate of 10 studies in each of five languages (Chinese, French, German, Japanese and Spanish). Fluent speakers double-extracted original-language articles. Researchers who did not speak the given language double-extracted translated articles along with 10 additional English language trials. Using the original language extractions as a gold standard, we estimated the probability and odds ratio of correctly extracting items from translated articles compared with English, adjusting for reviewer and language. Translation required about 30 minutes per article and extraction of translated articles required additional extraction time. The likelihood of correct extractions was greater for study design and intervention domain items than for outcome descriptions and, particularly, study results. Translated Spanish articles yielded the highest percentage of items (93%) that were correctly extracted more than half the time (followed by German and Japanese 89%, French 85%, and Chinese 78%) but Chinese articles yielded the highest percentage of items (41%) that were correctly extracted >98% of the time (followed by Spanish 30%, French 26%, German 22%, and Japanese 19%). In general, extractors' confidence in translations was not associated with their accuracy. Translation by Google Translate generally required few resources. Based on our analysis of translations from five languages, using machine translation has the potential to reduce language bias in systematic reviews; however, pending additional empirical data, reviewers should be cautious about using translated data. There remains a trade-off between completeness of systematic reviews (including all available studies) and risk of

  16. Approaches to translational plant science

    DEFF Research Database (Denmark)

    Dresbøll, Dorte Bodin; Christensen, Brian; Thorup-Kristensen, Kristian

    2015-01-01

    is lessened. In our opinion, implementation of translational plant science is a necessity in order to solve the agricultural challenges of producing food and materials in the future. We suggest an approach to translational plant science forcing scientists to think beyond their own area and to consider higher......Translational science deals with the dilemma between basic research and the practical application of scientific results. In translational plant science, focus is on the relationship between agricultural crop production and basic science in various research fields, but primarily in the basic plant...... science. Scientific and technological developments have allowed great progress in our understanding of plant genetics and molecular physiology, with potentials for improving agricultural production. However, this development has led to a separation of the laboratory-based research from the crop production...

  17. Machine learning an artificial intelligence approach

    CERN Document Server

    Banerjee, R; Bradshaw, Gary; Carbonell, Jaime Guillermo; Mitchell, Tom Michael; Michalski, Ryszard Spencer

    1983-01-01

    Machine Learning: An Artificial Intelligence Approach contains tutorial overviews and research papers representative of trends in the area of machine learning as viewed from an artificial intelligence perspective. The book is organized into six parts. Part I provides an overview of machine learning and explains why machines should learn. Part II covers important issues affecting the design of learning programs-particularly programs that learn from examples. It also describes inductive learning systems. Part III deals with learning by analogy, by experimentation, and from experience. Parts IV a

  18. Statistical and machine learning approaches for network analysis

    CERN Document Server

    Dehmer, Matthias

    2012-01-01

    Explore the multidisciplinary nature of complex networks through machine learning techniques Statistical and Machine Learning Approaches for Network Analysis provides an accessible framework for structurally analyzing graphs by bringing together known and novel approaches on graph classes and graph measures for classification. By providing different approaches based on experimental data, the book uniquely sets itself apart from the current literature by exploring the application of machine learning techniques to various types of complex networks. Comprised of chapters written by internation

  19. Translation in language learning: a ‘what for’ approach

    Directory of Open Access Journals (Sweden)

    Paolo E. Balboni

    2017-12-01

    Full Text Available Literature about translation in language learning and teaching shows the prominence of the ‘for and against’ approach, while a ‘what for’ approach would be more profitable. In order to prevent the latter approach from becoming a random list of the potential benefits of the use of translation in language teaching, this essay suggests the use of a formal model of communicative competence, to see which of its components can profit of translation activities. The result is a map of the effects of translation in the wide range of competences and abilities which constitute language learning.

  20. Gene prediction in metagenomic fragments: A large scale machine learning approach

    Directory of Open Access Journals (Sweden)

    Morgenstern Burkhard

    2008-04-01

    Full Text Available Abstract Background Metagenomics is an approach to the characterization of microbial genomes via the direct isolation of genomic sequences from the environment without prior cultivation. The amount of metagenomic sequence data is growing fast while computational methods for metagenome analysis are still in their infancy. In contrast to genomic sequences of single species, which can usually be assembled and analyzed by many available methods, a large proportion of metagenome data remains as unassembled anonymous sequencing reads. One of the aims of all metagenomic sequencing projects is the identification of novel genes. Short length, for example, Sanger sequencing yields on average 700 bp fragments, and unknown phylogenetic origin of most fragments require approaches to gene prediction that are different from the currently available methods for genomes of single species. In particular, the large size of metagenomic samples requires fast and accurate methods with small numbers of false positive predictions. Results We introduce a novel gene prediction algorithm for metagenomic fragments based on a two-stage machine learning approach. In the first stage, we use linear discriminants for monocodon usage, dicodon usage and translation initiation sites to extract features from DNA sequences. In the second stage, an artificial neural network combines these features with open reading frame length and fragment GC-content to compute the probability that this open reading frame encodes a protein. This probability is used for the classification and scoring of gene candidates. With large scale training, our method provides fast single fragment predictions with good sensitivity and specificity on artificially fragmented genomic DNA. Additionally, this method is able to predict translation initiation sites accurately and distinguishes complete from incomplete genes with high reliability. Conclusion Large scale machine learning methods are well-suited for gene

  1. Predicting Post-Translational Modifications from Local Sequence Fragments Using Machine Learning Algorithms: Overview and Best Practices.

    Science.gov (United States)

    Tatjewski, Marcin; Kierczak, Marcin; Plewczynski, Dariusz

    2017-01-01

    Here, we present two perspectives on the task of predicting post translational modifications (PTMs) from local sequence fragments using machine learning algorithms. The first is the description of the fundamental steps required to construct a PTM predictor from the very beginning. These steps include data gathering, feature extraction, or machine-learning classifier selection. The second part of our work contains the detailed discussion of more advanced problems which are encountered in PTM prediction task. Probably the most challenging issues which we have covered here are: (1) how to address the training data class imbalance problem (we also present statistics describing the problem); (2) how to properly set up cross-validation folds with an approach which takes into account the homology of protein data records, to address this problem we present our folds-over-clusters algorithm; and (3) how to efficiently reach for new sources of learning features. Presented techniques and notes resulted from intense studies in the field, performed by our and other groups, and can be useful both for researchers beginning in the field of PTM prediction and for those who want to extend the repertoire of their research techniques.

  2. Thomas Mofolo's sentence design in Chaka approached in translation

    African Journals Online (AJOL)

    Thomas Mofolo's sentence design in Chaka approached in translation. ... by responding to several compelling questions, ranging from how five translators of the work approached it in their respective languages ... AJOL African Journals Online.

  3. Ausdruckskraft und Regelmaessigkeit: Was Esperanto fuer automatische Uebersetzung geeignet macht (Expressiveness and Formal Regularity: What Makes Esperanto Suitable for Machine Translation).

    Science.gov (United States)

    Schubert, Klaus

    1988-01-01

    Describes DLT, the multilingual machine translation system that uses Esperanto as an intermediate language in which substantial portions of the translation subprocesses are carried out. The criteria for choosing an intermediate language and the reasons for preferring Esperanto over other languages are explained. (Author/DJD)

  4. Let the Game Begin: Ergodic as an Approach for Video Game Translation

    OpenAIRE

    SF. Lukfianka Sanjaya Purnama; SF. Luthfie Arguby Purnomo; Dyah Nugrahani

    2016-01-01

    This paper attempts to propose ergodic as an approach for video game translation. The word approach here refers to an approach for translation products and to an approach for the translation process. The steps to formulate ergodic as an approach are first, Aarseth’sergodic literature is reviewed to elicit a basis for comprehension toward its relationship with video games and video game translation Secondly, taking the translation of Electronic Arts’Need for Speed: Own the City, Midway’s Morta...

  5. On Collocations and Their Interaction with Parsing and Translation

    Directory of Open Access Journals (Sweden)

    Violeta Seretan

    2013-10-01

    Full Text Available We address the problem of automatically processing collocations—a subclass of multi-word expressions characterized by a high degree of morphosyntactic flexibility—in the context of two major applications, namely, syntactic parsing and machine translation. We show that parsing and collocation identification are processes that are interrelated and that benefit from each other, inasmuch as syntactic information is crucial for acquiring collocations from corpora and, vice versa, collocational information can be used to improve parsing performance. Similarly, we focus on the interrelation between collocations and machine translation, highlighting the use of translation information for multilingual collocation identification, as well as the use of collocational knowledge for improving translation. We give a panorama of the existing relevant work, and we parallel the literature surveys with our own experiments involving a symbolic parser and a rule-based translation system. The results show a significant improvement over approaches in which the corresponding tasks are decoupled.

  6. Translator-computer interaction in action

    DEFF Research Database (Denmark)

    Bundgaard, Kristine; Christensen, Tina Paulsen; Schjoldager, Anne

    2016-01-01

    perspective, this paper investigates the relationship between machines and humans in the field of translation, analysing a CAT process in which machine-translation (MT) technology was integrated into a translation-memory (TM) suite. After a review of empirical research into the impact of CAT tools......Though we lack empirically-based knowledge of the impact of computer-aided translation (CAT) tools on translation processes, it is generally agreed that all professional translators are now involved in some kind of translator-computer interaction (TCI), using O’Brien’s (2012) term. Taking a TCI......, the study indicates that the tool helps the translator conform to project and customer requirements....

  7. A Taxonomy of Human Translation Styles

    DEFF Research Database (Denmark)

    Carl, Michael; Dragsted, Barbara; Lykke Jakobsen, Arnt

    2011-01-01

    on the translators' activity data, we develop a taxonomy of translation styles. The taxonomy could serve to inform the development of advanced translation assistance tools and provide a basis for a felicitous and grounded integration of human machine interaction in translation.......While the translation profession becomes increasingly technological, we are still far from understanding how humans actually translate and how they could be best supported by machines. In this paper we outline a method which helps to uncover characteristics of human translation processes. Based...

  8. Handbook of natural language processing and machine translation DARPA global autonomous language exploitation

    CERN Document Server

    Olive, Joseph P; McCary, John

    2011-01-01

    This comprehensive handbook, written by leading experts in the field, details the groundbreaking research conducted under the breakthrough GALE program - The Global Autonomous Language Exploitation within the Defense Advanced Research Projects Agency (DARPA), while placing it in the context of previous research in the fields of natural language and signal processing, artificial intelligence and machine translation. The most fundamental contrast between GALE and its predecessor programs was its holistic integration of previously separate or sequential processes. In earlier language research pro

  9. Let the Game Begin: Ergodic as an Approach for Video Game Translation

    Directory of Open Access Journals (Sweden)

    Sf. Lukfianka Sanjaya Purnama, Sf. Luthfie Arguby Purnomo, Dyah Nugrahani

    2017-01-01

    Full Text Available This paper attempts to propose ergodic as an approach for video game translation. The word approach here refers to an approach for translation products and to an approach for the translation process. The steps to formulate ergodic as an approach are first, Aarseth’sergodic literature is reviewed to elicit a basis for comprehension toward its relationship with video games and video game translation Secondly, taking the translation of Electronic Arts’Need for Speed: Own the City, Midway’s Mortal Kombat: Unchained, and Konami’s Metal Gear Solid, ergodic based approach for video game translation is formulated. The formulation signifies that ergodic, as an approach for video game translation, revolves around the treatment of video games as a cybertext from which scriptons, textons, and traversal functions as the configurative mechanism influence the selection of translation strategies and the transferability of variables and traversal function, game aesthetics, and ludus and narrative of the games. The challenges countered when treating video games as a cybertext are the necessities for the translators to convey anamorphosis, mechanical and narrative hidden meaning of the analyzed frame, to consider the textonomy of the games, and at the same time to concern on GILT (Globalization, Internationalization, Localization, and Translation.

  10. TRANSLATING AS A PURPOSEFUL ACTIVITY:A PROSPECTIVE APPROACH

    Directory of Open Access Journals (Sweden)

    Christiane Nord

    2006-01-01

    Full Text Available Taking a prospective approach to translation, translators choose their translation strategies according to the purpose or function the translated text is intended to fulfill for the target audience. Since communicative purposes need certain conditions in order to work, it is the translator's task to analyze the conditions of the target culture and to decide whether, and how, the source-text purposes can work for the target audience according to the specifications of the translation brief. If the target-culture conditions differ from those of the source culture, there are usually two basic options: either to transform the text in such a way that it can work under target-culture conditions (= instrumental translation, or to replace the source-text functions by their respective meta-functions (= documentary translation.

  11. Machine learning approaches in medical image analysis

    DEFF Research Database (Denmark)

    de Bruijne, Marleen

    2016-01-01

    Machine learning approaches are increasingly successful in image-based diagnosis, disease prognosis, and risk assessment. This paper highlights new research directions and discusses three main challenges related to machine learning in medical imaging: coping with variation in imaging protocols......, learning from weak labels, and interpretation and evaluation of results....

  12. Interdisciplinarity in translation teaching: competence-based education, translation task-based approach, context-based text typology

    Directory of Open Access Journals (Sweden)

    Edelweiss Vitol Gysel

    2017-05-01

    Full Text Available In the context of competence-based teaching, this paper draws upon the model of Translation Competence (TC put forward by the PACTE group (2003 to establish a dialogue between cognitive-constructivist paradigms for translation teaching and the model of the Context-based Text Typology (MATTHIESSEN et al., 2007. In this theoretical environment, it proposes a model for the design of a Teaching Unit (TU for the development of the bilingual competence in would-be-translators.To this end, it explores translation as a cognitive, communicative and textual activity (HURTADO ALBIR, 2011 and considers its teaching from the translation task-based approach (HURTADO ALBIR, 1999. This approach is illustrated through the practical example of the design of a TU elaborated for the subject ‘Introduction to Specialized Translation’,part of the curricular grid of the program ‘Secretariado Executivo’ at Universidade Federal de Santa Catarina. Aspects such as the establishment of learning objectives and their alignment with the translation tasks composing the TU are addressed for this specific pedagogical situation. We argue for the development of textual competences by means of the acquisition of strategies derived from the Context-based Text Typology to solve problems arising from the translation of different text types and contextual configurations.

  13. Morphological Analysis for Statistical Machine Translation

    National Research Council Canada - National Science Library

    Lee, Young-Suk

    2004-01-01

    .... The technique improves Arabic-to-English translation qualities significantly when applied to IBM Model 1 and Phrase Translation Models trained on the training corpus size ranging from 3,500 to 3.3 million sentence pairs.

  14. Understanding the organization of cognitive approaches to translation

    DEFF Research Database (Denmark)

    Serban, Maria

    2017-01-01

    Cognitive approaches to translation studies are driven by three interrelated aims: to understand the structure and organization of the capacities of cognitive agents involved in processes of translation, to build better theories and models of translation, and to develop more efficient methods...... theory, it is more descriptively adequate and more fruitful to understand it as a family of projects based on multiple theories that are relevant for studying different aspects of the translation process. This perspective allows us to extract the erotetic structure of these programs which are organized...

  15. Machine Learning Approaches in Cardiovascular Imaging.

    Science.gov (United States)

    Henglin, Mir; Stein, Gillian; Hushcha, Pavel V; Snoek, Jasper; Wiltschko, Alexander B; Cheng, Susan

    2017-10-01

    Cardiovascular imaging technologies continue to increase in their capacity to capture and store large quantities of data. Modern computational methods, developed in the field of machine learning, offer new approaches to leveraging the growing volume of imaging data available for analyses. Machine learning methods can now address data-related problems ranging from simple analytic queries of existing measurement data to the more complex challenges involved in analyzing raw images. To date, machine learning has been used in 2 broad and highly interconnected areas: automation of tasks that might otherwise be performed by a human and generation of clinically important new knowledge. Most cardiovascular imaging studies have focused on task-oriented problems, but more studies involving algorithms aimed at generating new clinical insights are emerging. Continued expansion in the size and dimensionality of cardiovascular imaging databases is driving strong interest in applying powerful deep learning methods, in particular, to analyze these data. Overall, the most effective approaches will require an investment in the resources needed to appropriately prepare such large data sets for analyses. Notwithstanding current technical and logistical challenges, machine learning and especially deep learning methods have much to offer and will substantially impact the future practice and science of cardiovascular imaging. © 2017 American Heart Association, Inc.

  16. The Temple Translator's Workstation Project

    National Research Council Canada - National Science Library

    Vanni, Michelle; Zajac, Remi

    1996-01-01

    .... The Temple Translator's Workstation is incorporated into a Tipster document management architecture and it allows both translator/analysts and monolingual analysts to use the machine- translation...

  17. Visible Machine Learning for Biomedicine.

    Science.gov (United States)

    Yu, Michael K; Ma, Jianzhu; Fisher, Jasmin; Kreisberg, Jason F; Raphael, Benjamin J; Ideker, Trey

    2018-06-14

    A major ambition of artificial intelligence lies in translating patient data to successful therapies. Machine learning models face particular challenges in biomedicine, however, including handling of extreme data heterogeneity and lack of mechanistic insight into predictions. Here, we argue for "visible" approaches that guide model structure with experimental biology. Copyright © 2018. Published by Elsevier Inc.

  18. Translational research-the need of a new bioethics approach.

    Science.gov (United States)

    Hostiuc, Sorin; Moldoveanu, Alin; Dascălu, Maria-Iuliana; Unnthorsson, Runar; Jóhannesson, Ómar I; Marcus, Ioan

    2016-01-15

    Translational research tries to apply findings from basic science to enhance human health and well-being. Many phases of the translational research may include non-medical tasks (information technology, engineering, nanotechnology, biochemistry, animal research, economy, sociology, psychology, politics, and so on). Using common bioethics principles to these areas might sometimes be not feasible, or even impossible. However, the whole process must respect some fundamental, moral principles. The purpose of this paper is to argument the need for a different approach to the morality in translational bioethics, and to suggest some directions that might be followed when constructing such a bioethics. We will show that a new approach is needed and present a few ethical issues that are specific to the translational research.

  19. Compositional translation

    NARCIS (Netherlands)

    Appelo, Lisette; Janssen, Theo; Jong, de F.M.G.; Landsbergen, S.P.J.

    1994-01-01

    This book provides an in-depth review of machine translation by discussing in detail a particular method, called compositional translation, and a particular system, Rosetta, which is based on this method. The Rosetta project is a unique combination of fundamental research and large-scale

  20. ASPECTS REGARDING THE METHOD OF REALIZING THE TECHNICAL EXPERTISE FOR REPAIRING THE TRANSLATION MECHANISM OF A M4A COAL-MINING MACHINE

    Directory of Open Access Journals (Sweden)

    Marius Liviu CÎRȚÎNĂ

    2018-05-01

    Full Text Available This paper presents the technical state of the mechanism of translation of the coalmining machine after the technical expertise. The rehabilitation to which the translation mechanism will be subjected will be carried out by performing the intervention works that will bring back into the normal operating parameters both the structural part and the functional part. The paper presents: the proposed solutions for repair after verification of the translation mechanism and the way of repairing the mechanism.

  1. VIRTUAL MODELING OF A NUMERICAL CONTROL MACHINE TOOL USED FOR COMPLEX MACHINING OPERATIONS

    Directory of Open Access Journals (Sweden)

    POPESCU Adrian

    2015-11-01

    Full Text Available This paper presents the 3D virtual model of the numerical control machine Modustar 100, in terms of machine elements. This is a CNC machine of modular construction, all components allowing the assembly in various configurations. The paper focused on the design of the subassemblies specific to the axes numerically controlled by means of CATIA v5, which contained different drive kinematic chains of different translation modules that ensures translation on X, Y and Z axis. Machine tool development for high speed and highly precise cutting demands employment of advanced simulation techniques witch it reflect on cost of total development of the machine.

  2. Domain Adaptation for Machine Translation with Instance Selection

    Directory of Open Access Journals (Sweden)

    Biçici Ergun

    2015-04-01

    Full Text Available Domain adaptation for machine translation (MT can be achieved by selecting training instances close to the test set from a larger set of instances. We consider 7 different domain adaptation strategies and answer 7 research questions, which give us a recipe for domain adaptation in MT. We perform English to German statistical MT (SMT experiments in a setting where test and training sentences can come from different corpora and one of our goals is to learn the parameters of the sampling process. Domain adaptation with training instance selection can obtain 22% increase in target 2-gram recall and can gain up to 3:55 BLEU points compared with random selection. Domain adaptation with feature decay algorithm (FDA not only achieves the highest target 2-gram recall and BLEU performance but also perfectly learns the test sample distribution parameter with correlation 0:99. Moses SMT systems built with FDA selected 10K training sentences is able to obtain F1 results as good as the baselines that use up to 2M sentences. Moses SMT systems built with FDA selected 50K training sentences is able to obtain F1 point better results than the baselines.

  3. Breaking the language barrier: machine assisted diagnosis using the medical speech translator.

    Science.gov (United States)

    Starlander, Marianne; Bouillon, Pierrette; Rayner, Manny; Chatzichrisafis, Nikos; Hockey, Beth Ann; Isahara, Hitoshi; Kanzaki, Kyoko; Nakao, Yukie; Santaholma, Marianne

    2005-01-01

    In this paper, we describe and evaluate an Open Source medical speech translation system (MedSLT) intended for safety-critical applications. The aim of this system is to eliminate the language barriers in emergency situation. It translates spoken questions from English into French, Japanese and Finnish in three medical subdomains (headache, chest pain and abdominal pain), using a vocabulary of about 250-400 words per sub-domain. The architecture is a compromise between fixed-phrase translation on one hand and complex linguistically-based systems on the other. Recognition is guided by a Context Free Grammar Language Model compiled from a general unification grammar, automatically specialised for the domain. We present an evaluation of this initial prototype that shows the advantages of this grammar-based approach for this particular translation task in term of both reliability and use.

  4. System approach to machine building enterprise innovative activity management

    Directory of Open Access Journals (Sweden)

    І.V. Levytska

    2016-12-01

    Full Text Available The company, which operates in a challenging competitive environment should focus on new products and provide innovative services that enhance their innovation to maintain the company’s market position. The article deals with the peculiarities of such an activity in the company. The authors analyze the various approaches used in the management, and supply the advantages and disadvantages of each. It is determine that the most optimal approach among them is a system approach. The definition of the consepts "a system" and "a systematic approach to innovative activity management" are suggested. The article works out the system of machine building enterprise innovative activity management, the organization of machine building enterprise innovative activity; the planning of machine building enterprise innovative activity; the control in the system of machine building enterprise innovative activity management; the elements of the control subsystem. The properties, typical for the system of innovative management, are supplied. The managers, engaged in enterprise innovative activity management, must perform a number of the suggested tasks, which affect the efficiency of the enterprise as a whole. These exact tasks are performed using the systematic approach, providing the enterprise competitive operation and quick adaptation to changes in the external environment.

  5. On the Systematicity of Human Translation Processes

    DEFF Research Database (Denmark)

    Carl, Michael; Dragsted, Barbara; Lykke Jakobsen, Arnt

    While translation careers and the translation profession become more globalised and more technological, we are still far from understanding how humans actually translate and how they could be best supported by machines. In this paper we attempt to outline a method which helps to uncover character......While translation careers and the translation profession become more globalised and more technological, we are still far from understanding how humans actually translate and how they could be best supported by machines. In this paper we attempt to outline a method which helps to uncover...... characteristic steps in human translation processes. Based on the translators' activity data, we develop a taxonomy of translation styles, which are characteristic for different kinds of translators. The taxonomy could serve to inform the development of advanced translation assistance tools and provide a basis...

  6. Chapter 16: text mining for translational bioinformatics.

    Science.gov (United States)

    Cohen, K Bretonnel; Hunter, Lawrence E

    2013-04-01

    Text mining for translational bioinformatics is a new field with tremendous research potential. It is a subfield of biomedical natural language processing that concerns itself directly with the problem of relating basic biomedical research to clinical practice, and vice versa. Applications of text mining fall both into the category of T1 translational research-translating basic science results into new interventions-and T2 translational research, or translational research for public health. Potential use cases include better phenotyping of research subjects, and pharmacogenomic research. A variety of methods for evaluating text mining applications exist, including corpora, structured test suites, and post hoc judging. Two basic principles of linguistic structure are relevant for building text mining applications. One is that linguistic structure consists of multiple levels. The other is that every level of linguistic structure is characterized by ambiguity. There are two basic approaches to text mining: rule-based, also known as knowledge-based; and machine-learning-based, also known as statistical. Many systems are hybrids of the two approaches. Shared tasks have had a strong effect on the direction of the field. Like all translational bioinformatics software, text mining software for translational bioinformatics can be considered health-critical and should be subject to the strictest standards of quality assurance and software testing.

  7. Quality assurance of a helical tomotherapy machine

    International Nuclear Information System (INIS)

    Fenwick, J D; Tome, W A; Jaradat, H A; Hui, S K; James, J A; Balog, J P; DeSouza, C N; Lucas, D B; Olivera, G H; Mackie, T R; Paliwal, B R

    2004-01-01

    Helical tomotherapy has been developed at the University of Wisconsin, and 'Hi-Art II' clinical machines are now commercially manufactured. At the core of each machine lies a ring-gantry-mounted short linear accelerator which generates x-rays that are collimated into a fan beam of intensity-modulated radiation by a binary multileaf, the modulation being variable with gantry angle. Patients are treated lying on a couch which is translated continuously through the bore of the machine as the gantry rotates. Highly conformal dose-distributions can be delivered using this technique, which is the therapy equivalent of spiral computed tomography. The approach requires synchrony of gantry rotation, couch translation, accelerator pulsing and the opening and closing of the leaves of the binary multileaf collimator used to modulate the radiation beam. In the course of clinically implementing helical tomotherapy, we have developed a quality assurance (QA) system for our machine. The system is analogous to that recommended for conventional clinical linear accelerator QA by AAPM Task Group 40 but contains some novel components, reflecting differences between the Hi-Art devices and conventional clinical accelerators. Here the design and dosimetric characteristics of Hi-Art machines are summarized and the QA system is set out along with experimental details of its implementation. Connections between this machine-based QA work, pre-treatment patient-specific delivery QA and fraction-by-fraction dose verification are discussed

  8. Translation Method and Computer Programme for Assisting the Same

    DEFF Research Database (Denmark)

    2013-01-01

    The present invention relates to a translation method comprising the steps of: a translator speaking a translation of a written source text in a target language, an automatic speech recognition system converting the spoken translation into a set of phone and word hypotheses in the target language......, a machine translation system translating the written source text into a set of translations hypotheses in the target language, and an integration module combining the set of spoken word hypotheses and the set of machine translation hypotheses obtaining a text in the target language. Thereby obtaining...

  9. Preliminary study of online machine translation use of nursing literature: quality evaluation and perceived usability

    Directory of Open Access Journals (Sweden)

    Anazawa Ryoko

    2012-11-01

    Full Text Available Abstract Background Japanese nurses are increasingly required to read published international research in clinical, educational, and research settings. Language barriers are a significant obstacle, and online machine translation (MT is a tool that can be used to address this issue. We examined the quality of Google Translate® (English to Japanese and Korean to Japanese, which is a representative online MT, using a previously verified evaluation method. We also examined the perceived usability and current use of online MT among Japanese nurses. Findings Randomly selected nursing abstracts were translated and then evaluated for intelligibility and usability by 28 participants, including assistants and research associates from nursing universities throughout Japan. They answered a questionnaire about their online MT use. From simple comparison of mean scores between two language pairs, translation quality was significantly better, with respect to both intelligibility and usability, for Korean-Japanese than for English-Japanese. Most respondents perceived a language barrier. Online MT had been used by 61% of the respondents and was perceived as not useful enough. Conclusion Nursing articles translated from Korean into Japanese by an online MT system could be read at an acceptable level of comprehension, but the same could not be said for English-Japanese translations. Respondents with experience using online MT used it largely to grasp the overall meanings of the original text. Enrichment in technical terms appeared to be the key to better usability. Users will be better able to use MT outputs if they improve their foreign language proficiency as much as possible. Further research is being conducted with a larger sample size and detailed analysis.

  10. Machine learning and computer vision approaches for phenotypic profiling.

    Science.gov (United States)

    Grys, Ben T; Lo, Dara S; Sahin, Nil; Kraus, Oren Z; Morris, Quaid; Boone, Charles; Andrews, Brenda J

    2017-01-02

    With recent advances in high-throughput, automated microscopy, there has been an increased demand for effective computational strategies to analyze large-scale, image-based data. To this end, computer vision approaches have been applied to cell segmentation and feature extraction, whereas machine-learning approaches have been developed to aid in phenotypic classification and clustering of data acquired from biological images. Here, we provide an overview of the commonly used computer vision and machine-learning methods for generating and categorizing phenotypic profiles, highlighting the general biological utility of each approach. © 2017 Grys et al.

  11. Implementing Professional Approach within a Translation

    Directory of Open Access Journals (Sweden)

    Nagwa ElShafei

    2014-03-01

    Full Text Available The recent and fast development in various spheres of information and communication technology, global trade, digital and social media have resulted in growth in excellent employment opportunities but also influenced the labor market. For instance, some jobs have become absolute, while others, related to information technology particularly, have become in higher demand. As such, there are many scenarios in which translators find themselves unable to communicate with their clients due to cultural and language barriers, especially in labor market environment. This clarifies the great need for translators to receive professional training which also takes into account the advancement in technology. Therefore, market demands should be taken into account when developing and planning university courses and curricula to meet the job market needs. Courses on translation and interpretation prepare professional translators as needed by the labor market. In other words, the role of academic professional and curriculum planners should be narrowing the gap between what the labor market needs from the modern translator and the courses offered by training institutions, universities and colleges. This research study introduces a Professional Approach to teacher to educate translators within the faculty of arts, in a manner that fits the requirements of the job market. As such, a unit was prepared and specified for the students, then taught by the researcher to the selected sample. The dependent t-test technique was employed to compare the means of the total scores of the experimental group on the proficiency pre-post administration of the tests. It was noted from the results that there is a notable difference between the mean scores of the two groups in favor of the experimental group.

  12. An introduction to quantum machine learning

    Science.gov (United States)

    Schuld, Maria; Sinayskiy, Ilya; Petruccione, Francesco

    2015-04-01

    Machine learning algorithms learn a desired input-output relation from examples in order to interpret new inputs. This is important for tasks such as image and speech recognition or strategy optimisation, with growing applications in the IT industry. In the last couple of years, researchers investigated if quantum computing can help to improve classical machine learning algorithms. Ideas range from running computationally costly algorithms or their subroutines efficiently on a quantum computer to the translation of stochastic methods into the language of quantum theory. This contribution gives a systematic overview of the emerging field of quantum machine learning. It presents the approaches as well as technical details in an accessible way, and discusses the potential of a future theory of quantum learning.

  13. The development of a classification schema for arts-based approaches to knowledge translation.

    Science.gov (United States)

    Archibald, Mandy M; Caine, Vera; Scott, Shannon D

    2014-10-01

    Arts-based approaches to knowledge translation are emerging as powerful interprofessional strategies with potential to facilitate evidence uptake, communication, knowledge, attitude, and behavior change across healthcare provider and consumer groups. These strategies are in the early stages of development. To date, no classification system for arts-based knowledge translation exists, which limits development and understandings of effectiveness in evidence syntheses. We developed a classification schema of arts-based knowledge translation strategies based on two mechanisms by which these approaches function: (a) the degree of precision in key message delivery, and (b) the degree of end-user participation. We demonstrate how this classification is necessary to explore how context, time, and location shape arts-based knowledge translation strategies. Classifying arts-based knowledge translation strategies according to their core attributes extends understandings of the appropriateness of these approaches for various healthcare settings and provider groups. The classification schema developed may enhance understanding of how, where, and for whom arts-based knowledge translation approaches are effective, and enable theorizing of essential knowledge translation constructs, such as the influence of context, time, and location on utilization strategies. The classification schema developed may encourage systematic inquiry into the effectiveness of these approaches in diverse interprofessional contexts. © 2014 Sigma Theta Tau International.

  14. Why Translation Is Difficult

    DEFF Research Database (Denmark)

    Carl, Michael; Schaeffer, Moritz Jonas

    2017-01-01

    The paper develops a definition of translation literality that is based on the syntactic and semantic similarity of the source and the target texts. We provide theoretical and empirical evidence that absolute literal translations are easy to produce. Based on a multilingual corpus of alternative...... translations we investigate the effects of cross-lingual syntactic and semantic distance on translation production times and find that non-literality makes from-scratch translation and post-editing difficult. We show that statistical machine translation systems encounter even more difficulties with non-literality....

  15. Free Online Translators: A Comparative Assessment in Terms of Idioms and Phrasal Verbs

    OpenAIRE

    Marziyeh Taleghani; Ehsan Pazouki

    2018-01-01

    Free online translators are in fact statistical machine translators that create translator models using parallel corpora. Although it’s not a new subject and many works are reported on that in recent years, it still suffers from lots of shortcomings and has a long way ahead. While the literature on machine translators is vast, there are only a few that evaluate free online machine translators in specific terms like idioms. The aim of this paper is to evaluate and compare four free...

  16. Computer-aided translation tools

    DEFF Research Database (Denmark)

    Christensen, Tina Paulsen; Schjoldager, Anne

    2016-01-01

    in Denmark is rather high in general, but limited in the case of machine translation (MT) tools: While most TSPs use translation-memory (TM) software, often in combination with a terminology management system (TMS), only very few have implemented MT, which is criticised for its low quality output, especially......The paper reports on a questionnaire survey from 2013 of the uptake and use of computer-aided translation (CAT) tools by Danish translation service providers (TSPs) and discusses how these tools appear to have impacted on the Danish translation industry. According to our results, the uptake...

  17. Translation Theory 'Translated'

    DEFF Research Database (Denmark)

    Wæraas, Arild; Nielsen, Jeppe

    2016-01-01

    Translation theory has proved to be a versatile analytical lens used by scholars working from different traditions. On the basis of a systematic literature review, this study adds to our understanding of the ‘translations’ of translation theory by identifying the distinguishing features of the most...... common theoretical approaches to translation within the organization and management discipline: actor-network theory, knowledge-based theory, and Scandinavian institutionalism. Although each of these approaches already has borne much fruit in research, the literature is diverse and somewhat fragmented......, but also overlapping. We discuss the ways in which the three versions of translation theory may be combined and enrich each other so as to inform future research, thereby offering a more complete understanding of translation in and across organizational settings....

  18. Machine learning: novel bioinformatics approaches for combating antimicrobial resistance.

    Science.gov (United States)

    Macesic, Nenad; Polubriaginof, Fernanda; Tatonetti, Nicholas P

    2017-12-01

    Antimicrobial resistance (AMR) is a threat to global health and new approaches to combating AMR are needed. Use of machine learning in addressing AMR is in its infancy but has made promising steps. We reviewed the current literature on the use of machine learning for studying bacterial AMR. The advent of large-scale data sets provided by next-generation sequencing and electronic health records make applying machine learning to the study and treatment of AMR possible. To date, it has been used for antimicrobial susceptibility genotype/phenotype prediction, development of AMR clinical decision rules, novel antimicrobial agent discovery and antimicrobial therapy optimization. Application of machine learning to studying AMR is feasible but remains limited. Implementation of machine learning in clinical settings faces barriers to uptake with concerns regarding model interpretability and data quality.Future applications of machine learning to AMR are likely to be laboratory-based, such as antimicrobial susceptibility phenotype prediction.

  19. Distinguishing Asthma Phenotypes Using Machine Learning Approaches.

    Science.gov (United States)

    Howard, Rebecca; Rattray, Magnus; Prosperi, Mattia; Custovic, Adnan

    2015-07-01

    Asthma is not a single disease, but an umbrella term for a number of distinct diseases, each of which are caused by a distinct underlying pathophysiological mechanism. These discrete disease entities are often labelled as 'asthma endotypes'. The discovery of different asthma subtypes has moved from subjective approaches in which putative phenotypes are assigned by experts to data-driven ones which incorporate machine learning. This review focuses on the methodological developments of one such machine learning technique-latent class analysis-and how it has contributed to distinguishing asthma and wheezing subtypes in childhood. It also gives a clinical perspective, presenting the findings of studies from the past 5 years that used this approach. The identification of true asthma endotypes may be a crucial step towards understanding their distinct pathophysiological mechanisms, which could ultimately lead to more precise prevention strategies, identification of novel therapeutic targets and the development of effective personalized therapies.

  20. An Approach for Implementing State Machines with Online Testability

    Directory of Open Access Journals (Sweden)

    P. K. Lala

    2010-01-01

    Full Text Available During the last two decades, significant amount of research has been performed to simplify the detection of transient or soft errors in VLSI-based digital systems. This paper proposes an approach for implementing state machines that uses 2-hot code for state encoding. State machines designed using this approach allow online detection of soft errors in registers and output logic. The 2-hot code considerably reduces the number of required flip-flops and leads to relatively straightforward implementation of next state and output logic. A new way of designing output logic for online fault detection has also been presented.

  1. Personalized translational epilepsy research - Novel approaches and future perspectives: Part I: Clinical and network analysis approaches.

    Science.gov (United States)

    Rosenow, Felix; van Alphen, Natascha; Becker, Albert; Chiocchetti, Andreas; Deichmann, Ralf; Deller, Thomas; Freiman, Thomas; Freitag, Christine M; Gehrig, Johannes; Hermsen, Anke M; Jedlicka, Peter; Kell, Christian; Klein, Karl Martin; Knake, Susanne; Kullmann, Dimitri M; Liebner, Stefan; Norwood, Braxton A; Omigie, Diana; Plate, Karlheinz; Reif, Andreas; Reif, Philipp S; Reiss, Yvonne; Roeper, Jochen; Ronellenfitsch, Michael W; Schorge, Stephanie; Schratt, Gerhard; Schwarzacher, Stephan W; Steinbach, Joachim P; Strzelczyk, Adam; Triesch, Jochen; Wagner, Marlies; Walker, Matthew C; von Wegner, Frederic; Bauer, Sebastian

    2017-11-01

    Despite the availability of more than 15 new "antiepileptic drugs", the proportion of patients with pharmacoresistant epilepsy has remained constant at about 20-30%. Furthermore, no disease-modifying treatments shown to prevent the development of epilepsy following an initial precipitating brain injury or to reverse established epilepsy have been identified to date. This is likely in part due to the polyetiologic nature of epilepsy, which in turn requires personalized medicine approaches. Recent advances in imaging, pathology, genetics and epigenetics have led to new pathophysiological concepts and the identification of monogenic causes of epilepsy. In the context of these advances, the First International Symposium on Personalized Translational Epilepsy Research (1st ISymPTER) was held in Frankfurt on September 8, 2016, to discuss novel approaches and future perspectives for personalized translational research. These included new developments and ideas in a range of experimental and clinical areas such as deep phenotyping, quantitative brain imaging, EEG/MEG-based analysis of network dysfunction, tissue-based translational studies, innate immunity mechanisms, microRNA as treatment targets, functional characterization of genetic variants in human cell models and rodent organotypic slice cultures, personalized treatment approaches for monogenic epilepsies, blood-brain barrier dysfunction, therapeutic focal tissue modification, computational modeling for target and biomarker identification, and cost analysis in (monogenic) disease and its treatment. This report on the meeting proceedings is aimed at stimulating much needed investments of time and resources in personalized translational epilepsy research. Part I includes the clinical phenotyping and diagnostic methods, EEG network-analysis, biomarkers, and personalized treatment approaches. In Part II, experimental and translational approaches will be discussed (Bauer et al., 2017) [1]. Copyright © 2017 Elsevier Inc

  2. Technology for Large-Scale Translation of Clinical Practice Guidelines: A Pilot Study of the Performance of a Hybrid Human and Computer-Assisted Approach.

    Science.gov (United States)

    Van de Velde, Stijn; Macken, Lieve; Vanneste, Koen; Goossens, Martine; Vanschoenbeek, Jan; Aertgeerts, Bert; Vanopstal, Klaar; Vander Stichele, Robert; Buysschaert, Joost

    2015-10-09

    The construction of EBMPracticeNet, a national electronic point-of-care information platform in Belgium, began in 2011 to optimize quality of care by promoting evidence-based decision making. The project involved, among other tasks, the translation of 940 EBM Guidelines of Duodecim Medical Publications from English into Dutch and French. Considering the scale of the translation process, it was decided to make use of computer-aided translation performed by certificated translators with limited expertise in medical translation. Our consortium used a hybrid approach, involving a human translator supported by a translation memory (using SDL Trados Studio), terminology recognition (using SDL MultiTerm terminology databases) from medical terminology databases, and support from online machine translation. This resulted in a validated translation memory, which is now in use for the translation of new and updated guidelines. The objective of this experiment was to evaluate the performance of the hybrid human and computer-assisted approach in comparison with translation unsupported by translation memory and terminology recognition. A comparison was also made with the translation efficiency of an expert medical translator. We conducted a pilot study in which two sets of 30 new and 30 updated guidelines were randomized to one of three groups. Comparable guidelines were translated (1) by certificated junior translators without medical specialization using the hybrid method, (2) by an experienced medical translator without this support, and (3) by the same junior translators without the support of the validated translation memory. A medical proofreader who was blinded for the translation procedure, evaluated the translated guidelines for acceptability and adequacy. Translation speed was measured by recording translation and post-editing time. The human translation edit rate was calculated as a metric to evaluate the quality of the translation. A further evaluation was made of

  3. National machine guarding program: Part 1. Machine safeguarding practices in small metal fabrication businesses

    OpenAIRE

    Parker, David L.; Yamin, Samuel C.; Brosseau, Lisa M.; Xi, Min; Gordon, Robert; Most, Ivan G.; Stanley, Rodney

    2015-01-01

    Background Metal fabrication workers experience high rates of traumatic occupational injuries. Machine operators in particular face high risks, often stemming from the absence or improper use of machine safeguarding or the failure to implement lockout procedures. Methods The National Machine Guarding Program (NMGP) was a translational research initiative implemented in conjunction with two workers' compensation insures. Insurance safety consultants trained in machine guarding used standardize...

  4. Application of Machine Learning Approaches for Protein-protein Interactions Prediction.

    Science.gov (United States)

    Zhang, Mengying; Su, Qiang; Lu, Yi; Zhao, Manman; Niu, Bing

    2017-01-01

    Proteomics endeavors to study the structures, functions and interactions of proteins. Information of the protein-protein interactions (PPIs) helps to improve our knowledge of the functions and the 3D structures of proteins. Thus determining the PPIs is essential for the study of the proteomics. In this review, in order to study the application of machine learning in predicting PPI, some machine learning approaches such as support vector machine (SVM), artificial neural networks (ANNs) and random forest (RF) were selected, and the examples of its applications in PPIs were listed. SVM and RF are two commonly used methods. Nowadays, more researchers predict PPIs by combining more than two methods. This review presents the application of machine learning approaches in predicting PPI. Many examples of success in identification and prediction in the area of PPI prediction have been discussed, and the PPIs research is still in progress. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  5. MULTIFUNCTION OF INTERNET IN TRANSLATION

    Directory of Open Access Journals (Sweden)

    Bayu Budiharjo

    2017-04-01

    Full Text Available Technology affects almost all areas, including translation. Many products of technology have made translational works easier, one of which is internet. Despite the wide use of internet, the potentials it has are sometimes unnoticed. While web-based dictionaries or thesaurus often serve as translators’ assistants and online Machine Translation issues become topics of many researches, other uses of internet related to translation may not be known by many. Internet can help disseminate newborn ideas, theories and findings worldwide to enhance translation theories. Besides, the contact between internet and translation generates new areas to examine. Internet also provides helping hand in the area of translation research. Researcher or anyone conducting research in the field of translation can find a range of research gaps as well as reference. Those who need group discussions to collect required data from informants, or researchers of the same interest coming from all over the world can meet and conduct Focus Group Discussion (FGD on virtual world. Furthermore, internet offers various forms of assistance for translation practitioners. The commonly used internet assistance consists of dictionaries, thesaurus and Machine Translations available on the internet. Other forms of aid provided by internet take form of parallel texts, images, and videos, which can be very helpful. Internet provides many things which can be utilized for the purpose of translation. Internet keeps on providing more as it develops from time to time in line with the development of technology. Internet awaits utilization of theorists, researchers, practitioners and those having concern on translation.

  6. Pattern recognition & machine learning

    CERN Document Server

    Anzai, Y

    1992-01-01

    This is the first text to provide a unified and self-contained introduction to visual pattern recognition and machine learning. It is useful as a general introduction to artifical intelligence and knowledge engineering, and no previous knowledge of pattern recognition or machine learning is necessary. Basic for various pattern recognition and machine learning methods. Translated from Japanese, the book also features chapter exercises, keywords, and summaries.

  7. Electric machines

    CERN Document Server

    Gross, Charles A

    2006-01-01

    BASIC ELECTROMAGNETIC CONCEPTSBasic Magnetic ConceptsMagnetically Linear Systems: Magnetic CircuitsVoltage, Current, and Magnetic Field InteractionsMagnetic Properties of MaterialsNonlinear Magnetic Circuit AnalysisPermanent MagnetsSuperconducting MagnetsThe Fundamental Translational EM MachineThe Fundamental Rotational EM MachineMultiwinding EM SystemsLeakage FluxThe Concept of Ratings in EM SystemsSummaryProblemsTRANSFORMERSThe Ideal n-Winding TransformerTransformer Ratings and Per-Unit ScalingThe Nonideal Three-Winding TransformerThe Nonideal Two-Winding TransformerTransformer Efficiency and Voltage RegulationPractical ConsiderationsThe AutotransformerOperation of Transformers in Three-Phase EnvironmentsSequence Circuit Models for Three-Phase Transformer AnalysisHarmonics in TransformersSummaryProblemsBASIC MECHANICAL CONSIDERATIONSSome General PerspectivesEfficiencyLoad Torque-Speed CharacteristicsMass Polar Moment of InertiaGearingOperating ModesTranslational SystemsA Comprehensive Example: The ElevatorP...

  8. A Comparison of Machine Learning Approaches for Corn Yield Estimation

    Science.gov (United States)

    Kim, N.; Lee, Y. W.

    2017-12-01

    Machine learning is an efficient empirical method for classification and prediction, and it is another approach to crop yield estimation. The objective of this study is to estimate corn yield in the Midwestern United States by employing the machine learning approaches such as the support vector machine (SVM), random forest (RF), and deep neural networks (DNN), and to perform the comprehensive comparison for their results. We constructed the database using satellite images from MODIS, the climate data of PRISM climate group, and GLDAS soil moisture data. In addition, to examine the seasonal sensitivities of corn yields, two period groups were set up: May to September (MJJAS) and July and August (JA). In overall, the DNN showed the highest accuracies in term of the correlation coefficient for the two period groups. The differences between our predictions and USDA yield statistics were about 10-11 %.

  9. A knowledge translation project on community-centred approaches in public health.

    Science.gov (United States)

    Stansfield, J; South, J

    2018-03-01

    This article examines the development and impact of a national knowledge translation project aimed at improving access to evidence and learning on community-centred approaches for health and wellbeing. Structural changes in the English health system meant that knowledge on community engagement was becoming lost and a fragmented evidence base was seen to impact negatively on policy and practice. A partnership started between Public Health England, NHS England and Leeds Beckett University in 2014 to address these issues. Following a literature review and stakeholder consultation, evidence was published in a national guide to community-centred approaches. This was followed by a programme of work to translate the evidence into national strategy and local practice.The article outlines the key features of the knowledge translation framework developed. Results include positive impacts on local practice and national policy, for example adoption within National Institute for Health and Care Evidence (NICE) guidance and Local Authority public health plans and utilization as a tool for local audit of practice and commissioning. The framework was successful in its non-linear approach to knowledge translation across a range of inter-connected activity, built on national leadership, knowledge brokerage, coalition building and a strong collaboration between research institute and government agency.

  10. Proposal and Evaluation of Sequencing Words in Chat Conversation between Japanese and Chinese using Machine Translation

    OpenAIRE

    李, 芬慧; 由井薗, 隆也

    2010-01-01

    日中翻訳チャットにおいて単語を並べた会話によるチャットコミュニケーションを提案する.比較評価のために,通常の文章チャットによる評価実験も行った.その結果,日中翻訳チャットにおいて,(1)単語チャットは会話速度や会話内容の理解において文章チャットと同等に使えること,(2)利用者は,単語チャットよりは文章チャットを好む傾向があること,(3)翻訳された会話の理解は日本人と中国人とで文化的違いがある可能性が得られた.今後は単語チャットの応用を検討する予定である. : We propose a chat conversation between Japanese and Chinese using machine translation by sequencing words. By comparison with a conventional chat using machine translation, it is showed that (1) sequencing words in the chat is as same speed and understanding as the...

  11. Machine learning approaches: from theory to application in schizophrenia.

    Science.gov (United States)

    Veronese, Elisa; Castellani, Umberto; Peruzzo, Denis; Bellani, Marcella; Brambilla, Paolo

    2013-01-01

    In recent years, machine learning approaches have been successfully applied for analysis of neuroimaging data, to help in the context of disease diagnosis. We provide, in this paper, an overview of recent support vector machine-based methods developed and applied in psychiatric neuroimaging for the investigation of schizophrenia. In particular, we focus on the algorithms implemented by our group, which have been applied to classify subjects affected by schizophrenia and healthy controls, comparing them in terms of accuracy results with other recently published studies. First we give a description of the basic terminology used in pattern recognition and machine learning. Then we separately summarize and explain each study, highlighting the main features that characterize each method. Finally, as an outcome of the comparison of the results obtained applying the described different techniques, conclusions are drawn in order to understand how much automatic classification approaches can be considered a useful tool in understanding the biological underpinnings of schizophrenia. We then conclude by discussing the main implications achievable by the application of these methods into clinical practice.

  12. Machine Learning Approaches: From Theory to Application in Schizophrenia

    Directory of Open Access Journals (Sweden)

    Elisa Veronese

    2013-01-01

    Full Text Available In recent years, machine learning approaches have been successfully applied for analysis of neuroimaging data, to help in the context of disease diagnosis. We provide, in this paper, an overview of recent support vector machine-based methods developed and applied in psychiatric neuroimaging for the investigation of schizophrenia. In particular, we focus on the algorithms implemented by our group, which have been applied to classify subjects affected by schizophrenia and healthy controls, comparing them in terms of accuracy results with other recently published studies. First we give a description of the basic terminology used in pattern recognition and machine learning. Then we separately summarize and explain each study, highlighting the main features that characterize each method. Finally, as an outcome of the comparison of the results obtained applying the described different techniques, conclusions are drawn in order to understand how much automatic classification approaches can be considered a useful tool in understanding the biological underpinnings of schizophrenia. We then conclude by discussing the main implications achievable by the application of these methods into clinical practice.

  13. A META-COMPOSITE SOFTWARE DEVELOPMENT APPROACH FOR TRANSLATIONAL RESEARCH

    Science.gov (United States)

    Sadasivam, Rajani S.; Tanik, Murat M.

    2013-01-01

    Translational researchers conduct research in a highly data-intensive and continuously changing environment and need to use multiple, disparate tools to achieve their goals. These researchers would greatly benefit from meta-composite software development or the ability to continuously compose and recompose tools together in response to their ever-changing needs. However, the available tools are largely disconnected, and current software approaches are inefficient and ineffective in their support for meta-composite software development. Building on the composite services development approach, the de facto standard for developing integrated software systems, we propose a concept-map and agent-based meta-composite software development approach. A crucial step in composite services development is the modeling of users’ needs as processes, which can then be specified in an executable format for system composition. We have two key innovations. First, our approach allows researchers (who understand their needs best) instead of technicians to take a leadership role in the development of process models, reducing inefficiencies and errors. A second innovation is that our approach also allows for modeling of complex user interactions as part of the process, overcoming the technical limitations of current tools. We demonstrate the feasibility of our approach using a real-world translational research use case. We also present results of usability studies evaluating our approach for future refinements. PMID:23504436

  14. A meta-composite software development approach for translational research.

    Science.gov (United States)

    Sadasivam, Rajani S; Tanik, Murat M

    2013-06-01

    Translational researchers conduct research in a highly data-intensive and continuously changing environment and need to use multiple, disparate tools to achieve their goals. These researchers would greatly benefit from meta-composite software development or the ability to continuously compose and recompose tools together in response to their ever-changing needs. However, the available tools are largely disconnected, and current software approaches are inefficient and ineffective in their support for meta-composite software development. Building on the composite services development approach, the de facto standard for developing integrated software systems, we propose a concept-map and agent-based meta-composite software development approach. A crucial step in composite services development is the modeling of users' needs as processes, which can then be specified in an executable format for system composition. We have two key innovations. First, our approach allows researchers (who understand their needs best) instead of technicians to take a leadership role in the development of process models, reducing inefficiencies and errors. A second innovation is that our approach also allows for modeling of complex user interactions as part of the process, overcoming the technical limitations of current tools. We demonstrate the feasibility of our approach using a real-world translational research use case. We also present results of usability studies evaluating our approach for future refinements.

  15. MODELS OF LIVE MIGRATION WITH ITERATIVE APPROACH AND MOVE OF VIRTUAL MACHINES

    Directory of Open Access Journals (Sweden)

    S. M. Aleksankov

    2015-11-01

    Full Text Available Subject of Research. The processes of live migration without shared storage with pre-copy approach and move migration are researched. Migration of virtual machines is an important opportunity of virtualization technology. It enables applications to move transparently with their runtime environments between physical machines. Live migration becomes noticeable technology for efficient load balancing and optimizing the deployment of virtual machines to physical hosts in data centres. Before the advent of live migration, only network migration (the so-called, «Move», has been used, that entails stopping the virtual machine execution while copying to another physical server, and, consequently, unavailability of the service. Method. Algorithms of live migration without shared storage with pre-copy approach and move migration of virtual machines are reviewed from the perspective of research of migration time and unavailability of services at migrating of virtual machines. Main Results. Analytical models are proposed predicting migration time of virtual machines and unavailability of services at migrating with such technologies as live migration with pre-copy approach without shared storage and move migration. In the latest works on the time assessment of unavailability of services and migration time using live migration without shared storage experimental results are described, that are applicable to draw general conclusions about the changes of time for unavailability of services and migration time, but not to predict their values. Practical Significance. The proposed models can be used for predicting the migration time and time of unavailability of services, for example, at implementation of preventive and emergency works on the physical nodes in data centres.

  16. English-to-Japanese Translation vs. Dictation vs. Post-editing

    DEFF Research Database (Denmark)

    Carl, Michael; Aizawa, Akiko; Yamada, Masaru

    2016-01-01

    of text production. This paper introduces and evaluates a corpus of more than 55 hours of English-to-Japanese user activity data that were collected within the ENJA15 project, in which translators were observed while writing and speaking translations (translation dictation) and during machine translation...

  17. Evolution of Replication Machines

    Science.gov (United States)

    Yao, Nina Y.; O'Donnell, Mike E.

    2016-01-01

    The machines that decode and regulate genetic information require the translation, transcription and replication pathways essential to all living cells. Thus, it might be expected that all cells share the same basic machinery for these pathways that were inherited from the primordial ancestor cell from which they evolved. A clear example of this is found in the translation machinery that converts RNA sequence to protein. The translation process requires numerous structural and catalytic RNAs and proteins, the central factors of which are homologous in all three domains of life, bacteria, archaea and eukarya. Likewise, the central actor in transcription, RNA polymerase, shows homology among the catalytic subunits in bacteria, archaea and eukarya. In contrast, while some “gears” of the genome replication machinery are homologous in all domains of life, most components of the replication machine appear to be unrelated between bacteria and those of archaea and eukarya. This review will compare and contrast the central proteins of the “replisome” machines that duplicate DNA in bacteria, archaea and eukarya, with an eye to understanding the issues surrounding the evolution of the DNA replication apparatus. PMID:27160337

  18. A rule-based approach to model checking of UML state machines

    Science.gov (United States)

    Grobelna, Iwona; Grobelny, Michał; Stefanowicz, Łukasz

    2016-12-01

    In the paper a new approach to formal verification of control process specification expressed by means of UML state machines in version 2.x is proposed. In contrast to other approaches from the literature, we use the abstract and universal rule-based logical model suitable both for model checking (using the nuXmv model checker), but also for logical synthesis in form of rapid prototyping. Hence, a prototype implementation in hardware description language VHDL can be obtained that fully reflects the primary, already formally verified specification in form of UML state machines. Presented approach allows to increase the assurance that implemented system meets the user-defined requirements.

  19. Animal to human translational paradigms relevant for approach avoidance conflict decision making.

    Science.gov (United States)

    Kirlic, Namik; Young, Jared; Aupperle, Robin L

    2017-09-01

    Avoidance behavior in clinical anxiety disorders is often a decision made in response to approach-avoidance conflict, resulting in a sacrifice of potential rewards to avoid potential negative affective consequences. Animal research has a long history of relying on paradigms related to approach-avoidance conflict to model anxiety-relevant behavior. This approach includes punishment-based conflict, exploratory, and social interaction tasks. There has been a recent surge of interest in the translation of paradigms from animal to human, in efforts to increase generalization of findings and support the development of more effective mental health treatments. This article briefly reviews animal tests related to approach-avoidance conflict and results from lesion and pharmacologic studies utilizing these tests. We then provide a description of translational human paradigms that have been developed to tap into related constructs, summarizing behavioral and neuroimaging findings. Similarities and differences in findings from analogous animal and human paradigms are discussed. Lastly, we highlight opportunities for future research and paradigm development that will support the clinical utility of this translational work. Copyright © 2017 Elsevier Ltd. All rights reserved.

  20. Aligning qualitative and quantitative approaches in professional translation quality assessment

    OpenAIRE

    Martínez Mateo, Roberto

    2016-01-01

    Translation Quality Assessment in professional translation is a long-debated issue that is still unsettled today, partly, due to the wide range of possible approaches. Given the elusive nature of the quality concept, first, it must be defined from a multifaceted and all-embracing viewpoint. Simultaneously and from a textual perspective, the quality notion must be defined as a notion of relative (and not absolute) adequacy with respect to a framework previously agreed by parties at...

  1. Report on Approaches to Database Translation. Final Report.

    Science.gov (United States)

    Gallagher, Leonard; Salazar, Sandra

    This report describes approaches to database translation (i.e., transferring data and data definitions from a source, either a database management system (DBMS) or a batch file, to a target DBMS), and recommends a method for representing the data structures of newly-proposed network and relational data models in a form suitable for database…

  2. Literal Translation using Google Translate in Translating the Text from French to English in Digital Tourism Brochure “Bienvenue À Paris”

    Directory of Open Access Journals (Sweden)

    Rila Hilma

    2011-05-01

    Full Text Available Translation is basically change of form. The form from which the translation is made will be called the source language and the form into which it is to be changed will be called the receptor language. Translation consists of transferring the meaning of the source language into the receptor language. Translating is not an easy job to do because many things to be considered to do this activity because translation means determining the meaning of a text, then reconstructing this same meaning using the appropriate structure and form in the receptor language. Translation is basically divided by two types of translation, one is literal and the other is idiomatic. Literal translation is really strict to the structure and form then often can not well express the true meaning of source language. Idiomatic translation makes every effort to communicate the meaning of the source language text in the natural forms of the receptor language. Then the most popular translation machine, Google Translate, in this study shows the results of translation which remain odd, unnatural, and nonsensical because the unsuccessful of message delivery, which is notably the typically error of literal translation.

  3. Free Online Translators: A Comparative Assessment in Terms of Idioms and Phrasal Verbs

    Directory of Open Access Journals (Sweden)

    Marziyeh Taleghani

    2018-03-01

    Full Text Available Free online translators are in fact statistical machine translators that create translator models using parallel corpora. Although it’s not a new subject and many works are reported on that in recent years, it still suffers from lots of shortcomings and has a long way ahead. While the literature on machine translators is vast, there are only a few that evaluate free online machine translators in specific terms like idioms. The aim of this paper is to evaluate and compare four free online translators in terms of translating English idioms (including idiomatic phrasal verbs into Persian. To that end, ten chosen texts from the book “oxford word Skills: idioms and phrasal verbs” were translated by four online translators, www.bing.com, www.translate.google.com , www.freetranslation.com and www.targoman.com , and the obtained results were compared in a subjectively method based on Aryanpur English to Persian dictionary. Comparison of the results shows that www.targoman.com has a better performance in translating idioms from English to Persian and as a result, it can be the best choice if the aim is to do so.

  4. Interactive Translation Prediction versus Conventional Post-editing in Practice

    DEFF Research Database (Denmark)

    Sanchis-Trilles, German; Alabau, Vicent; Buck, Christian

    2014-01-01

    We conducted a field trial in computer-assisted professional translation to compare Interactive Translation Prediction (ITP) against conventional post- editing (PE) of machine translation (MT) output. In contrast to the conventional PE set-up, where an MT system first produces a static translatio...

  5. Translation of Japanese Noun Compounds at Super-Function Based MT System

    Science.gov (United States)

    Zhao, Xin; Ren, Fuji; Kuroiwa, Shingo

    Noun compounds are frequently encountered construction in nature language processing (NLP), consisting of a sequence of two or more nouns which functions syntactically as one noun. The translation of noun compounds has become a major issue in Machine Translation (MT) due to their frequency of occurrence and high productivity. In our previous studies on Super-Function Based Machine Translation (SFBMT), we have found that noun compounds are very frequently used and difficult to be translated correctly, the overgeneration of noun compounds can be dangerous as it may introduce ambiguity in the translation. In this paper, we discuss the challenges in handling Japanese noun compounds in an SFBMT system, we present a shallow method for translating noun compounds by using a word level translation dictionary and target language monolingual corpus.

  6. Precise machine translation of computer science study

    CSIR Research Space (South Africa)

    Marais, L

    2015-07-01

    Full Text Available mobile (Android) application for translating discrete mathematics definitions between English and Afrikaans. The main component of the system is a Grammatical Framework (GF) application grammar which produces syntactically and semantically accurate...

  7. An Overall Perspective of Machine Translation with Its Shortcomings

    Science.gov (United States)

    Akbari, Alireza

    2014-01-01

    The petition for language translation has strikingly augmented recently due to cross-cultural communication and exchange of information. In order to communicate well, text should be translated correctly and completely in each field such as legal documents, technical texts, scientific texts, publicity leaflets, and instructional materials. In this…

  8. The Fortran-P Translator: Towards Automatic Translation of Fortran 77 Programs for Massively Parallel Processors

    Directory of Open Access Journals (Sweden)

    Matthew O'keefe

    1995-01-01

    Full Text Available Massively parallel processors (MPPs hold the promise of extremely high performance that, if realized, could be used to study problems of unprecedented size and complexity. One of the primary stumbling blocks to this promise has been the lack of tools to translate application codes to MPP form. In this article we show how applications codes written in a subset of Fortran 77, called Fortran-P, can be translated to achieve good performance on several massively parallel machines. This subset can express codes that are self-similar, where the algorithm applied to the global data domain is also applied to each subdomain. We have found many codes that match the Fortran-P programming style and have converted them using our tools. We believe a self-similar coding style will accomplish what a vectorizable style has accomplished for vector machines by allowing the construction of robust, user-friendly, automatic translation systems that increase programmer productivity and generate fast, efficient code for MPPs.

  9. An Event-Triggered Machine Learning Approach for Accelerometer-Based Fall Detection.

    Science.gov (United States)

    Putra, I Putu Edy Suardiyana; Brusey, James; Gaura, Elena; Vesilo, Rein

    2017-12-22

    The fixed-size non-overlapping sliding window (FNSW) and fixed-size overlapping sliding window (FOSW) approaches are the most commonly used data-segmentation techniques in machine learning-based fall detection using accelerometer sensors. However, these techniques do not segment by fall stages (pre-impact, impact, and post-impact) and thus useful information is lost, which may reduce the detection rate of the classifier. Aligning the segment with the fall stage is difficult, as the segment size varies. We propose an event-triggered machine learning (EvenT-ML) approach that aligns each fall stage so that the characteristic features of the fall stages are more easily recognized. To evaluate our approach, two publicly accessible datasets were used. Classification and regression tree (CART), k -nearest neighbor ( k -NN), logistic regression (LR), and the support vector machine (SVM) were used to train the classifiers. EvenT-ML gives classifier F-scores of 98% for a chest-worn sensor and 92% for a waist-worn sensor, and significantly reduces the computational cost compared with the FNSW- and FOSW-based approaches, with reductions of up to 8-fold and 78-fold, respectively. EvenT-ML achieves a significantly better F-score than existing fall detection approaches. These results indicate that aligning feature segments with fall stages significantly increases the detection rate and reduces the computational cost.

  10. Amp: A modular approach to machine learning in atomistic simulations

    Science.gov (United States)

    Khorshidi, Alireza; Peterson, Andrew A.

    2016-10-01

    Electronic structure calculations, such as those employing Kohn-Sham density functional theory or ab initio wavefunction theories, have allowed for atomistic-level understandings of a wide variety of phenomena and properties of matter at small scales. However, the computational cost of electronic structure methods drastically increases with length and time scales, which makes these methods difficult for long time-scale molecular dynamics simulations or large-sized systems. Machine-learning techniques can provide accurate potentials that can match the quality of electronic structure calculations, provided sufficient training data. These potentials can then be used to rapidly simulate large and long time-scale phenomena at similar quality to the parent electronic structure approach. Machine-learning potentials usually take a bias-free mathematical form and can be readily developed for a wide variety of systems. Electronic structure calculations have favorable properties-namely that they are noiseless and targeted training data can be produced on-demand-that make them particularly well-suited for machine learning. This paper discusses our modular approach to atomistic machine learning through the development of the open-source Atomistic Machine-learning Package (Amp), which allows for representations of both the total and atom-centered potential energy surface, in both periodic and non-periodic systems. Potentials developed through the atom-centered approach are simultaneously applicable for systems with various sizes. Interpolation can be enhanced by introducing custom descriptors of the local environment. We demonstrate this in the current work for Gaussian-type, bispectrum, and Zernike-type descriptors. Amp has an intuitive and modular structure with an interface through the python scripting language yet has parallelizable fortran components for demanding tasks; it is designed to integrate closely with the widely used Atomic Simulation Environment (ASE), which

  11. A control approach for plasma density in tokamak machines

    Energy Technology Data Exchange (ETDEWEB)

    Boncagni, Luca, E-mail: luca.boncagni@enea.it [EURATOM – ENEA Fusion Association, Frascati Research Center, Division of Fusion Physics, Rome, Frascati (Italy); Pucci, Daniele; Piesco, F.; Zarfati, Emanuele [Dipartimento di Ingegneria Informatica, Automatica e Gestionale ' ' Antonio Ruberti' ' , Sapienza Università di Roma (Italy); Mazzitelli, G. [EURATOM – ENEA Fusion Association, Frascati Research Center, Division of Fusion Physics, Rome, Frascati (Italy); Monaco, S. [Dipartimento di Ingegneria Informatica, Automatica e Gestionale ' ' Antonio Ruberti' ' , Sapienza Università di Roma (Italy)

    2013-10-15

    Highlights: •We show a control approach for line plasma density in tokamak. •We show a control approach for pressure in a tokamak chamber. •We show experimental results using one valve. -- Abstract: In tokamak machines, chamber pre-fill is crucial to attain plasma breakdown, while plasma density control is instrumental for several tasks such as machine protection and achievement of desired plasma performances. This paper sets the principles of a new control strategy for attaining both chamber pre-fill and plasma density regulation. Assuming that the actuation mean is a piezoelectric valve driven by a varying voltage, the proposed control laws ensure convergence to reference values of chamber pressure during pre-fill, and of plasma density during plasma discharge. Experimental results at FTU are presented to discuss weaknesses and strengths of the proposed control strategy. The whole system has been implemented by using the MARTe framework [1].

  12. National Machine Guarding Program: Part 1. Machine safeguarding practices in small metal fabrication businesses.

    Science.gov (United States)

    Parker, David L; Yamin, Samuel C; Brosseau, Lisa M; Xi, Min; Gordon, Robert; Most, Ivan G; Stanley, Rodney

    2015-11-01

    Metal fabrication workers experience high rates of traumatic occupational injuries. Machine operators in particular face high risks, often stemming from the absence or improper use of machine safeguarding or the failure to implement lockout procedures. The National Machine Guarding Program (NMGP) was a translational research initiative implemented in conjunction with two workers' compensation insures. Insurance safety consultants trained in machine guarding used standardized checklists to conduct a baseline inspection of machine-related hazards in 221 business. Safeguards at the point of operation were missing or inadequate on 33% of machines. Safeguards for other mechanical hazards were missing on 28% of machines. Older machines were both widely used and less likely than newer machines to be properly guarded. Lockout/tagout procedures were posted at only 9% of machine workstations. The NMGP demonstrates a need for improvement in many aspects of machine safety and lockout in small metal fabrication businesses. © 2015 The Authors. American Journal of Industrial Medicine published by Wiley Periodicals, Inc.

  13. A double-sided linear primary permanent magnet vernier machine.

    Science.gov (United States)

    Du, Yi; Zou, Chunhua; Liu, Xianxing

    2015-01-01

    The purpose of this paper is to present a new double-sided linear primary permanent magnet (PM) vernier (DSLPPMV) machine, which can offer high thrust force, low detent force, and improved power factor. Both PMs and windings of the proposed machine are on the short translator, while the long stator is designed as a double-sided simple iron core with salient teeth so that it is very robust to transmit high thrust force. The key of this new machine is the introduction of double stator and the elimination of translator yoke, so that the inductance and the volume of the machine can be reduced. Hence, the proposed machine offers improved power factor and thrust force density. The electromagnetic performances of the proposed machine are analyzed including flux, no-load EMF, thrust force density, and inductance. Based on using the finite element analysis, the characteristics and performances of the proposed machine are assessed.

  14. Review: Current Approaches to Business and Institutional Translation. Proceedings of the International Conference on Economic, Business, Financial and Institutional Translation

    Directory of Open Access Journals (Sweden)

    Miguel Tolosa Igualada

    2016-08-01

    Full Text Available Daniel Gallego-Hernández (ed.. Current Approaches to Business and Institutional Translation. Proceedings of the International Conference on Economic, Business, Financial and Institutional Translation / Enfoques actuales en traducción económica e institucional. Actas del Congreso Internacional de Traducción Económica, Comercial, Financiera e Institucional. Suíça: Peter Lang, 2015, 254 páginas. ISBN 978-3-0343-1656-9.

  15. Translational ethics: an analytical framework of translational movements between theory and practice and a sketch of a comprehensive approach.

    Science.gov (United States)

    Bærøe, Kristine

    2014-09-30

    , carefully designed, overall approaches combining justified, self-reflexive philosophical and practical efforts according to the suggested distinctions could be expected to realise - or at least improve a facilitation of - translation of ethics across the theory-practice gap.

  16. The translational study of apathy – an ecological approach

    Directory of Open Access Journals (Sweden)

    Flurin eCathomas

    2015-09-01

    Full Text Available Apathy, a quantitative reduction in goal-directed behavior, is a prevalent symptom dimension with a negative impact on functional outcome in various neuropsychiatric disorders including schizophrenia and depression. The aim of this review is to show that interview-based assessment of apathy in humans and observation of spontaneous rodent behavior in an ecological setting can serve as an important complementary approach to already existing task-based assessment, to study and understand the neurobiological bases of apathy. We first discuss the paucity of current translational approaches regarding animal equivalents of psychopathological assessment of apathy. We then present the existing evaluation scales for the assessment of apathy in humans and propose five sub-domains of apathy, namely self-care, social interaction, exploration, work/education and recreation. Each of the items in apathy evaluation scales can be assigned to one of these sub-domains. We then show that corresponding, well-validated behavioral readouts exist for rodents and that, indeed, three of the five human apathy sub-domains have a rodent equivalent. In conclusion, the translational ecological study of apathy in humans and mice is possible and will constitute an important approach to increase the understanding of the neurobiological bases of apathy and the development of novel treatments.

  17. Spiritualist Writing Machines: Telegraphy, Typtology, Typewriting

    Directory of Open Access Journals (Sweden)

    Anthony Enns

    2015-09-01

    Full Text Available This paper examines how religious concepts both reflected and informed the development of new technologies for encoding, transmitting, and printing written information. While many spiritualist writing machines were based on existing technologies that were repurposed for spirit communication, others prefigured or even inspired more advanced technological innovations. The history of spiritualist writing machines thus not only represents a response to the rise of new media technologies in the nineteenth century, but it also reflects a set of cultural demands that helped to shape the development of new technologies, such as the need to replace handwriting with discrete, uniform lettering, which accelerated the speed of composition; the need to translate written information into codes, which could be transmitted across vast distances; and the need to automate the process of transmitting, translating, and transcribing written information, which seemed to endow the machines themselves with a certain degree of autonomy or even intelligence. While spiritualists and inventors were often (but not always motivated by different goals, the development of spiritualist writing machines and the development of technological writing machines were nevertheless deeply interrelated and interdependent.

  18. Identity approach in translation : sociocultural implications

    Directory of Open Access Journals (Sweden)

    Alicja Żuchelkowska

    2012-01-01

    Full Text Available The objective of this text consists in presenting how it is necessary for contemporary translators and interpreters (both literary and specialised to acquire and develop the ability to recognize elements of identity discourse in translated texts. Nowadays, the need for inter-cultural exchange is inevitably connected with the necessity of establishing harmonious co-existence for numerous cultures and identities. Therefore, it is crucial to educate translators in a way that enables them to pay special attention to identity and cultural perturbations present in translated texts (culture and language hybridisation, multiple identity, cultural dislocation, presence in linguistic and political discourse of minority cultures, regardless of their genre or form. Such a strong emphasis on identity problems in the translation is especially relevant in the European context, where the attention of researchers and politicians directed at identity problems stemming from ethnical and cultural issues sets the framework for a new cultural paradigm that determines the future development of the Eu. Becoming acquainted with this paradigm which emphasises fl uency, identity unmarkedness and the new model of European collectivity is indispensable for a translator aspiring to become a true cultural mediator.

  19. Man-machine analysis of translation and work tasks of Skylab films

    Science.gov (United States)

    Hosler, W. W.; Boelter, J. G.; Morrow, J. R., Jr.; Jackson, J. T.

    1979-01-01

    An objective approach to determine the concurrent validity of computer-graphic models is real time film analysis. This technique was illustrated through the procedures and results obtained in an evaluation of translation of Skylab mission astronauts. The quantitative analysis was facilitated by the use of an electronic film analyzer, minicomputer, and specifically supportive software. The uses of this technique for human factors research are: (1) validation of theoretical operator models; (2) biokinetic analysis; (3) objective data evaluation; (4) dynamic anthropometry; (5) empirical time-line analysis; and (6) consideration of human variability. Computer assisted techniques for interface design and evaluation have the potential for improving the capability for human factors engineering.

  20. THE PROBLEM OF ―CULTURAL UNTRANSLATABILITY‖ FOUND IN THE ENGLISH TRANSLATION OF JOKOWI‘S INSTAGRAM POSTS

    Directory of Open Access Journals (Sweden)

    Bety Mawarni

    2017-12-01

    Full Text Available The massive feasibility of social media has been utilised by numerous organisations and public figures, particularly world leaders, as an interactive way to spread information and to engage people from various backgrounds. In response to the language challenges in the global community environment, social media sites are adopting automatic machine translation to stretch the vastness of information reception. This mini research aims to analyse the problems of cultural untranslatability found in the machine-generated translation of the Instagram posts shared by the President of the Republic of Indonesia, Joko Widodo. The first part of this paper explores the major factors of cultural untranslatability resulted from machine-generated translation in 17 Jokowi‘s Instagram posts during May 2017. Deploying Hofstede‘s theory of cultural dimension, the second part of this paper analyses how these factors affect the cross-cultural communication in the framework of global environment. The result of this mini research present cultural translatability problems generated from machine translation and how it affects cross-cultural communication in social media. It is expected that the results of this mini research contribute in the development of machine translation as a device to boost cross-cultural communication in social media.

  1. A New Approach to Spindle Radial Error Evaluation Using a Machine Vision System

    Directory of Open Access Journals (Sweden)

    Kavitha C.

    2017-03-01

    Full Text Available The spindle rotational accuracy is one of the important issues in a machine tool which affects the surface topography and dimensional accuracy of a workpiece. This paper presents a machine-vision-based approach to radial error measurement of a lathe spindle using a CMOS camera and a PC-based image processing system. In the present work, a precisely machined cylindrical master is mounted on the spindle as a datum surface and variations of its position are captured using the camera for evaluating runout of the spindle. The Circular Hough Transform (CHT is used to detect variations of the centre position of the master cylinder during spindle rotation at subpixel level from a sequence of images. Radial error values of the spindle are evaluated using the Fourier series analysis of the centre position of the master cylinder calculated with the least squares curve fitting technique. The experiments have been carried out on a lathe at different operating speeds and the spindle radial error estimation results are presented. The proposed method provides a simpler approach to on-machine estimation of the spindle radial error in machine tools.

  2. Advanced methods in NDE using machine learning approaches

    Science.gov (United States)

    Wunderlich, Christian; Tschöpe, Constanze; Duckhorn, Frank

    2018-04-01

    Machine learning (ML) methods and algorithms have been applied recently with great success in quality control and predictive maintenance. Its goal to build new and/or leverage existing algorithms to learn from training data and give accurate predictions, or to find patterns, particularly with new and unseen similar data, fits perfectly to Non-Destructive Evaluation. The advantages of ML in NDE are obvious in such tasks as pattern recognition in acoustic signals or automated processing of images from X-ray, Ultrasonics or optical methods. Fraunhofer IKTS is using machine learning algorithms in acoustic signal analysis. The approach had been applied to such a variety of tasks in quality assessment. The principal approach is based on acoustic signal processing with a primary and secondary analysis step followed by a cognitive system to create model data. Already in the second analysis steps unsupervised learning algorithms as principal component analysis are used to simplify data structures. In the cognitive part of the software further unsupervised and supervised learning algorithms will be trained. Later the sensor signals from unknown samples can be recognized and classified automatically by the algorithms trained before. Recently the IKTS team was able to transfer the software for signal processing and pattern recognition to a small printed circuit board (PCB). Still, algorithms will be trained on an ordinary PC; however, trained algorithms run on the Digital Signal Processor and the FPGA chip. The identical approach will be used for pattern recognition in image analysis of OCT pictures. Some key requirements have to be fulfilled, however. A sufficiently large set of training data, a high signal-to-noise ratio, and an optimized and exact fixation of components are required. The automated testing can be done subsequently by the machine. By integrating the test data of many components along the value chain further optimization including lifetime and durability

  3. Understanding and Writing G & M Code for CNC Machines

    Science.gov (United States)

    Loveland, Thomas

    2012-01-01

    In modern CAD and CAM manufacturing companies, engineers design parts for machines and consumable goods. Many of these parts are cut on CNC machines. Whether using a CNC lathe, milling machine, or router, the ideas and designs of engineers must be translated into a machine-readable form called G & M Code that can be used to cut parts to precise…

  4. PC-assisted translation of photogrammetric papers

    Science.gov (United States)

    Güthner, Karlheinz; Peipe, Jürgen

    A PC-based system for machine translation of photogrammetric papers from the English into the German language and vice versa is described. The computer-assisted translating process is not intended to create a perfect interpretation of a text but to produce a rough rendering of the content of a paper. Starting with the original text, a continuous data flow is effected into the translated version by means of hardware (scanner, personal computer, printer) and software (OCR, translation, word processing, DTP). An essential component of the system is a photogrammetric microdictionary which is being established at present. It is based on several sources, including e.g. the ISPRS Multilingual Dictionary.

  5. Statistical translation with scarce resources: a South African case study

    CSIR Research Space (South Africa)

    Ronald, K

    2006-11-01

    Full Text Available Statistical machine translation techniques offer great promise for the development of automatic translation systems. However, the realization of this potential requires the availability of significant amounts of parallel bilingual texts. This paper...

  6. A comparison of the stochastic and machine learning approaches in hydrologic time series forecasting

    Science.gov (United States)

    Kim, T.; Joo, K.; Seo, J.; Heo, J. H.

    2016-12-01

    Hydrologic time series forecasting is an essential task in water resources management and it becomes more difficult due to the complexity of runoff process. Traditional stochastic models such as ARIMA family has been used as a standard approach in time series modeling and forecasting of hydrological variables. Due to the nonlinearity in hydrologic time series data, machine learning approaches has been studied with the advantage of discovering relevant features in a nonlinear relation among variables. This study aims to compare the predictability between the traditional stochastic model and the machine learning approach. Seasonal ARIMA model was used as the traditional time series model, and Random Forest model which consists of decision tree and ensemble method using multiple predictor approach was applied as the machine learning approach. In the application, monthly inflow data from 1986 to 2015 of Chungju dam in South Korea were used for modeling and forecasting. In order to evaluate the performances of the used models, one step ahead and multi-step ahead forecasting was applied. Root mean squared error and mean absolute error of two models were compared.

  7. A Simple and General Approach to Determination of Self and Mutual Inductances for AC machines

    DEFF Research Database (Denmark)

    Lu, Kaiyuan; Rasmussen, Peter Omand; Ritchie, Ewen

    2011-01-01

    Modelling of AC electrical machines plays an important role in electrical engineering education related to electrical machine design and control. One of the fundamental requirements in AC machine modelling is to derive the self and mutual inductances, which could be position dependant. Theories...... developed so far for inductance determination are often associated with complicated machine magnetic field analysis, which exhibits a difficulty for most students. This paper describes a simple and general approach to the determination of self and mutual inductances of different types of AC machines. A new...... determination are given for a 3-phase, salient-pole synchronous machine, and an induction machine....

  8. National machine guarding program: Part 1. Machine safeguarding practices in small metal fabrication businesses

    Science.gov (United States)

    Yamin, Samuel C.; Brosseau, Lisa M.; Xi, Min; Gordon, Robert; Most, Ivan G.; Stanley, Rodney

    2015-01-01

    Background Metal fabrication workers experience high rates of traumatic occupational injuries. Machine operators in particular face high risks, often stemming from the absence or improper use of machine safeguarding or the failure to implement lockout procedures. Methods The National Machine Guarding Program (NMGP) was a translational research initiative implemented in conjunction with two workers' compensation insures. Insurance safety consultants trained in machine guarding used standardized checklists to conduct a baseline inspection of machine‐related hazards in 221 business. Results Safeguards at the point of operation were missing or inadequate on 33% of machines. Safeguards for other mechanical hazards were missing on 28% of machines. Older machines were both widely used and less likely than newer machines to be properly guarded. Lockout/tagout procedures were posted at only 9% of machine workstations. Conclusions The NMGP demonstrates a need for improvement in many aspects of machine safety and lockout in small metal fabrication businesses. Am. J. Ind. Med. 58:1174–1183, 2015. © 2015 The Authors. American Journal of Industrial Medicine published by Wiley Periodicals, Inc. PMID:26332060

  9. The cognitive approach to conscious machines

    CERN Document Server

    Haikonen, Pentti O

    2003-01-01

    Could a machine have an immaterial mind? The author argues that true conscious machines can be built, but rejects artificial intelligence and classical neural networks in favour of the emulation of the cognitive processes of the brain-the flow of inner speech, inner imagery and emotions. This results in a non-numeric meaning-processing machine with distributed information representation and system reactions. It is argued that this machine would be conscious; it would be aware of its own existence and its mental content and perceive this as immaterial. Novel views on consciousness and the mind-

  10. ILLC-UvA translation system for EMNLP-WMT 2011

    NARCIS (Netherlands)

    Khalilov, M.; Sima'an, K.

    2011-01-01

    In this paper we describe the Institute for Logic, Language and Computation (University of Amsterdam) phrase-based statistical machine translation system for Englishto- German translation proposed within the EMNLP-WMT 2011 shared task. The main novelty of the submitted system is a syntaxdriven

  11. A Machine Approach for Field Weakening of Permanent-Magnet Motors

    Energy Technology Data Exchange (ETDEWEB)

    Hsu, J.S.

    2000-04-02

    The commonly known technology of field weakening for permanent-magnet (PM) motors is achieved by controlling the direct-axis current component through an inverter, without using mechanical variation of the air gap, a new machine approach for field weakening of PM machines by direct control of air-gap fluxes is introduced. The demagnetization situation due to field weakening is not an issue with this new method. In fact, the PMs are strengthened at field weakening. The field-weakening ratio can reach 1O:1 or higher. This technology is particularly useful for the PM generators and electric vehicle drives.

  12. Technology: English Learners and Machine Translation, Part 2

    Science.gov (United States)

    Van Horn, Royal

    2004-01-01

    In this article, the author touches on the ways that technology can come to the aid of teachers with students who don't speak English. He discusses different word processors that successfully translate foreign text.

  13. Machine learning approach for the outcome prediction of temporal lobe epilepsy surgery.

    Directory of Open Access Journals (Sweden)

    Rubén Armañanzas

    Full Text Available Epilepsy surgery is effective in reducing both the number and frequency of seizures, particularly in temporal lobe epilepsy (TLE. Nevertheless, a significant proportion of these patients continue suffering seizures after surgery. Here we used a machine learning approach to predict the outcome of epilepsy surgery based on supervised classification data mining taking into account not only the common clinical variables, but also pathological and neuropsychological evaluations. We have generated models capable of predicting whether a patient with TLE secondary to hippocampal sclerosis will fully recover from epilepsy or not. The machine learning analysis revealed that outcome could be predicted with an estimated accuracy of almost 90% using some clinical and neuropsychological features. Importantly, not all the features were needed to perform the prediction; some of them proved to be irrelevant to the prognosis. Personality style was found to be one of the key features to predict the outcome. Although we examined relatively few cases, findings were verified across all data, showing that the machine learning approach described in the present study may be a powerful method. Since neuropsychological assessment of epileptic patients is a standard protocol in the pre-surgical evaluation, we propose to include these specific psychological tests and machine learning tools to improve the selection of candidates for epilepsy surgery.

  14. Modularity Design Approach for Preventive Machine Maintenance

    Science.gov (United States)

    Ernawati, D.; Pudji, E.; Ngatilah, Y.; Handoyo, R.

    2018-01-01

    In a company, machine maintenance system will be very influential in production process activity. The company should have a scheduled engine maintenance system that does not require high costs when repairing and replacing machine parts. Modularity Design method is able to provide solutions to the engine maintenance scheduling system and can prevent fatal damage to the engine components. It can minimize the cost of repair and replacement of these machine components.The paper provides a solution to machine maintenance problems. The paper is also completed with case study of milling machines. That case studies can give us a real description about impact implementation of modularity design to prevent fatal damage to components and minimize the cost of repair and replacement of components of the machine.

  15. Opinion Mining in Latvian Text Using Semantic Polarity Analysis and Machine Learning Approach

    Directory of Open Access Journals (Sweden)

    Gatis Špats

    2016-07-01

    Full Text Available In this paper we demonstrate approaches for opinion mining in Latvian text. Authors have applied, combined and extended results of several previous studies and public resources to perform opinion mining in Latvian text using two approaches, namely, semantic polarity analysis and machine learning. One of the most significant constraints that make application of opinion mining for written content classification in Latvian text challenging is the limited publicly available text corpora for classifier training. We have joined several sources and created a publically available extended lexicon. Our results are comparable to or outperform current achievements in opinion mining in Latvian. Experiments show that lexicon-based methods provide more accurate opinion mining than the application of Naive Bayes machine learning classifier on Latvian tweets. Methods used during this study could be further extended using human annotators, unsupervised machine learning and bootstrapping to create larger corpora of classified text.

  16. Ultrasonic fluid quantity measurement in dynamic vehicular applications a support vector machine approach

    CERN Document Server

    Terzic, Jenny; Nagarajah, Romesh; Alamgir, Muhammad

    2013-01-01

    Accurate fluid level measurement in dynamic environments can be assessed using a Support Vector Machine (SVM) approach. SVM is a supervised learning model that analyzes and recognizes patterns. It is a signal classification technique which has far greater accuracy than conventional signal averaging methods. Ultrasonic Fluid Quantity Measurement in Dynamic Vehicular Applications: A Support Vector Machine Approach describes the research and development of a fluid level measurement system for dynamic environments. The measurement system is based on a single ultrasonic sensor. A Support Vector Machines (SVM) based signal characterization and processing system has been developed to compensate for the effects of slosh and temperature variation in fluid level measurement systems used in dynamic environments including automotive applications. It has been demonstrated that a simple ν-SVM model with Radial Basis Function (RBF) Kernel with the inclusion of a Moving Median filter could be used to achieve the high levels...

  17. Elucidating Host-Pathogen Interactions Based on Post-Translational Modifications Using Proteomics Approaches

    DEFF Research Database (Denmark)

    Ravikumar, Vaishnavi; Jers, Carsten; Mijakovic, Ivan

    2015-01-01

    can be efficiently applied to gain an insight into the molecular mechanisms involved. The measurement of the proteome and post-translationally modified proteome dynamics using mass spectrometry, results in a wide array of information, such as significant changes in protein expression, protein...... display host specificity through a complex network of molecular interactions that aid their survival and propagation. Co-infection states further lead to complications by increasing the microbial burden and risk factors. Quantitative proteomics based approaches and post-translational modification analysis...... pathogen interactions....

  18. How can machine-learning methods assist in virtual screening for hyperuricemia? A healthcare machine-learning approach.

    Science.gov (United States)

    Ichikawa, Daisuke; Saito, Toki; Ujita, Waka; Oyama, Hiroshi

    2016-12-01

    Our purpose was to develop a new machine-learning approach (a virtual health check-up) toward identification of those at high risk of hyperuricemia. Applying the system to general health check-ups is expected to reduce medical costs compared with administering an additional test. Data were collected during annual health check-ups performed in Japan between 2011 and 2013 (inclusive). We prepared training and test datasets from the health check-up data to build prediction models; these were composed of 43,524 and 17,789 persons, respectively. Gradient-boosting decision tree (GBDT), random forest (RF), and logistic regression (LR) approaches were trained using the training dataset and were then used to predict hyperuricemia in the test dataset. Undersampling was applied to build the prediction models to deal with the imbalanced class dataset. The results showed that the RF and GBDT approaches afforded the best performances in terms of sensitivity and specificity, respectively. The area under the curve (AUC) values of the models, which reflected the total discriminative ability of the classification, were 0.796 [95% confidence interval (CI): 0.766-0.825] for the GBDT, 0.784 [95% CI: 0.752-0.815] for the RF, and 0.785 [95% CI: 0.752-0.819] for the LR approaches. No significant differences were observed between pairs of each approach. Small changes occurred in the AUCs after applying undersampling to build the models. We developed a virtual health check-up that predicted the development of hyperuricemia using machine-learning methods. The GBDT, RF, and LR methods had similar predictive capability. Undersampling did not remarkably improve predictive power. Copyright © 2016 Elsevier Inc. All rights reserved.

  19. A machine learning approach for predicting the relationship between energy resources and economic development

    Science.gov (United States)

    Cogoljević, Dušan; Alizamir, Meysam; Piljan, Ivan; Piljan, Tatjana; Prljić, Katarina; Zimonjić, Stefan

    2018-04-01

    The linkage between energy resources and economic development is a topic of great interest. Research in this area is also motivated by contemporary concerns about global climate change, carbon emissions fluctuating crude oil prices, and the security of energy supply. The purpose of this research is to develop and apply the machine learning approach to predict gross domestic product (GDP) based on the mix of energy resources. Our results indicate that GDP predictive accuracy can be improved slightly by applying a machine learning approach.

  20. An Image Processing Approach to Linguistic Translation

    Science.gov (United States)

    Kubatur, Shruthi; Sreehari, Suhas; Hegde, Rajeshwari

    2011-12-01

    The art of translation is as old as written literature. Developments since the Industrial Revolution have influenced the practice of translation, nurturing schools, professional associations, and standard. In this paper, we propose a method of translation of typed Kannada text (taken as an image) into its equivalent English text. The National Instruments (NI) Vision Assistant (version 8.5) has been used for Optical character Recognition (OCR). We developed a new way of transliteration (which we call NIV transliteration) to simplify the training of characters. Also, we build a special type of dictionary for the purpose of translation.

  1. Partnering with patients in translational oncology research: ethical approach.

    Science.gov (United States)

    Mamzer, Marie-France; Duchange, Nathalie; Darquy, Sylviane; Marvanne, Patrice; Rambaud, Claude; Marsico, Giovanna; Cerisey, Catherine; Scotté, Florian; Burgun, Anita; Badoual, Cécile; Laurent-Puig, Pierre; Hervé, Christian

    2017-04-08

    The research program CARPEM (cancer research and personalized medicine) brings together the expertise of researchers and hospital-based oncologists to develop translational research in the context of personalized or "precision" medicine for cancer. There is recognition that patient involvement can help to take into account their needs and priorities in the development of this emerging practice but there is currently no consensus about how this can be achieved. In this study, we developed an empirical ethical research action aiming to improve patient representatives' involvement in the development of the translational research program together with health professionals. The aim is to promote common understanding and sharing of knowledge between all parties and to establish a long-term partnership integrating patient's expectations. Two distinct committees were settled in CARPEM: an "Expert Committee", gathering healthcare and research professionals, and a "Patient Committee", gathering patients and patient representatives. A multidisciplinary team trained in medical ethics research ensured communication between the two committees as well as analysis of discussions, minutes and outputs from all stakeholders. The results highlight the efficiency of the transfer of knowledge between interested parties. Patient representatives and professionals were able to identify new ethical challenges and co-elaborate new procedures to gather information and consent forms for adapting to practices and recommendations developed during the process. Moreover, included patient representatives became full partners and participated in the transfer of knowledge to the public via conferences and publications. Empirical ethical research based on a patient-centered approach could help in establishing a fair model for coordination and support actions during cancer research, striking a balance between the regulatory framework, researcher needs and patient expectations. Our approach addresses

  2. A machine learning approach to the accurate prediction of monitor units for a compact proton machine.

    Science.gov (United States)

    Sun, Baozhou; Lam, Dao; Yang, Deshan; Grantham, Kevin; Zhang, Tiezhi; Mutic, Sasa; Zhao, Tianyu

    2018-05-01

    Clinical treatment planning systems for proton therapy currently do not calculate monitor units (MUs) in passive scatter proton therapy due to the complexity of the beam delivery systems. Physical phantom measurements are commonly employed to determine the field-specific output factors (OFs) but are often subject to limited machine time, measurement uncertainties and intensive labor. In this study, a machine learning-based approach was developed to predict output (cGy/MU) and derive MUs, incorporating the dependencies on gantry angle and field size for a single-room proton therapy system. The goal of this study was to develop a secondary check tool for OF measurements and eventually eliminate patient-specific OF measurements. The OFs of 1754 fields previously measured in a water phantom with calibrated ionization chambers and electrometers for patient-specific fields with various range and modulation width combinations for 23 options were included in this study. The training data sets for machine learning models in three different methods (Random Forest, XGBoost and Cubist) included 1431 (~81%) OFs. Ten-fold cross-validation was used to prevent "overfitting" and to validate each model. The remaining 323 (~19%) OFs were used to test the trained models. The difference between the measured and predicted values from machine learning models was analyzed. Model prediction accuracy was also compared with that of the semi-empirical model developed by Kooy (Phys. Med. Biol. 50, 2005). Additionally, gantry angle dependence of OFs was measured for three groups of options categorized on the selection of the second scatters. Field size dependence of OFs was investigated for the measurements with and without patient-specific apertures. All three machine learning methods showed higher accuracy than the semi-empirical model which shows considerably large discrepancy of up to 7.7% for the treatment fields with full range and full modulation width. The Cubist-based solution

  3. Neural Machine Translation with Recurrent Attention Modeling

    OpenAIRE

    Yang, Zichao; Hu, Zhiting; Deng, Yuntian; Dyer, Chris; Smola, Alex

    2016-01-01

    Knowing which words have been attended to in previous time steps while generating a translation is a rich source of information for predicting what words will be attended to in the future. We improve upon the attention model of Bahdanau et al. (2014) by explicitly modeling the relationship between previous and subsequent attention levels for each word using one recurrent network per input word. This architecture easily captures informative features, such as fertility and regularities in relat...

  4. A Machine Learning Approach to Automated Gait Analysis for the Noldus Catwalk System.

    Science.gov (United States)

    Frohlich, Holger; Claes, Kasper; De Wolf, Catherine; Van Damme, Xavier; Michel, Anne

    2018-05-01

    Gait analysis of animal disease models can provide valuable insights into in vivo compound effects and thus help in preclinical drug development. The purpose of this paper is to establish a computational gait analysis approach for the Noldus Catwalk system, in which footprints are automatically captured and stored. We present a - to our knowledge - first machine learning based approach for the Catwalk system, which comprises a step decomposition, definition and extraction of meaningful features, multivariate step sequence alignment, feature selection, and training of different classifiers (gradient boosting machine, random forest, and elastic net). Using animal-wise leave-one-out cross validation we demonstrate that with our method we can reliable separate movement patterns of a putative Parkinson's disease animal model and several control groups. Furthermore, we show that we can predict the time point after and the type of different brain lesions and can even forecast the brain region, where the intervention was applied. We provide an in-depth analysis of the features involved into our classifiers via statistical techniques for model interpretation. A machine learning method for automated analysis of data from the Noldus Catwalk system was established. Our works shows the ability of machine learning to discriminate pharmacologically relevant animal groups based on their walking behavior in a multivariate manner. Further interesting aspects of the approach include the ability to learn from past experiments, improve with more data arriving and to make predictions for single animals in future studies.

  5. Some Problems in German to English Machine Translation

    Science.gov (United States)

    1974-12-01

    fron Benanti^e is a slippery business, especially when I have just clalwsd to subscribe to the idea that the structure of an utterance is intinately...from the English translation on page 15, the example paragraph can be divided Into elm 134 sections. These diviaions can be characterized at

  6. Classification of follicular lymphoma images: a holistic approach with symbol-based machine learning methods.

    Science.gov (United States)

    Zorman, Milan; Sánchez de la Rosa, José Luis; Dinevski, Dejan

    2011-12-01

    It is not very often to see a symbol-based machine learning approach to be used for the purpose of image classification and recognition. In this paper we will present such an approach, which we first used on the follicular lymphoma images. Lymphoma is a broad term encompassing a variety of cancers of the lymphatic system. Lymphoma is differentiated by the type of cell that multiplies and how the cancer presents itself. It is very important to get an exact diagnosis regarding lymphoma and to determine the treatments that will be most effective for the patient's condition. Our work was focused on the identification of lymphomas by finding follicles in microscopy images provided by the Laboratory of Pathology in the University Hospital of Tenerife, Spain. We divided our work in two stages: in the first stage we did image pre-processing and feature extraction, and in the second stage we used different symbolic machine learning approaches for pixel classification. Symbolic machine learning approaches are often neglected when looking for image analysis tools. They are not only known for a very appropriate knowledge representation, but also claimed to lack computational power. The results we got are very promising and show that symbolic approaches can be successful in image analysis applications.

  7. An ensemble machine learning approach to predict survival in breast cancer.

    Science.gov (United States)

    Djebbari, Amira; Liu, Ziying; Phan, Sieu; Famili, Fazel

    2008-01-01

    Current breast cancer predictive signatures are not unique. Can we use this fact to our advantage to improve prediction? From the machine learning perspective, it is well known that combining multiple classifiers can improve classification performance. We propose an ensemble machine learning approach which consists of choosing feature subsets and learning predictive models from them. We then combine models based on certain model fusion criteria and we also introduce a tuning parameter to control sensitivity. Our method significantly improves classification performance with a particular emphasis on sensitivity which is critical to avoid misclassifying poor prognosis patients as good prognosis.

  8. Machine Learning and Radiology

    Science.gov (United States)

    Wang, Shijun; Summers, Ronald M.

    2012-01-01

    In this paper, we give a short introduction to machine learning and survey its applications in radiology. We focused on six categories of applications in radiology: medical image segmentation, registration, computer aided detection and diagnosis, brain function or activity analysis and neurological disease diagnosis from fMR images, content-based image retrieval systems for CT or MRI images, and text analysis of radiology reports using natural language processing (NLP) and natural language understanding (NLU). This survey shows that machine learning plays a key role in many radiology applications. Machine learning identifies complex patterns automatically and helps radiologists make intelligent decisions on radiology data such as conventional radiographs, CT, MRI, and PET images and radiology reports. In many applications, the performance of machine learning-based automatic detection and diagnosis systems has shown to be comparable to that of a well-trained and experienced radiologist. Technology development in machine learning and radiology will benefit from each other in the long run. Key contributions and common characteristics of machine learning techniques in radiology are discussed. We also discuss the problem of translating machine learning applications to the radiology clinical setting, including advantages and potential barriers. PMID:22465077

  9. Machine learning and complex-network for personalized and systems biomedicine

    KAUST Repository

    Cannistraci, Carlo Vittorio

    2016-01-27

    The talk will begin with an introduction on using machine learning to discover hidden information and unexpected patterns in large biomedical datasets. Then, recent results on the use of complex network theory in biomedicine and neuroscience will be discussed. In particular, metagenomics and metabolomics data, approaches for drug-target repositioning, functional/structural MR connectomes and gut-brain axis data will be presented. The conclusion will outline the novel and exciting perspectives offered by the translation of these methods from systems biology to systems medicine.

  10. Nanomedicine: tiny particles and machines give huge gains.

    Science.gov (United States)

    Tong, Sheng; Fine, Eli J; Lin, Yanni; Cradick, Thomas J; Bao, Gang

    2014-02-01

    Nanomedicine is an emerging field that integrates nanotechnology, biomolecular engineering, life sciences and medicine; it is expected to produce major breakthroughs in medical diagnostics and therapeutics. Nano-scale structures and devices are compatible in size with proteins and nucleic acids in living cells. Therefore, the design, characterization and application of nano-scale probes, carriers and machines may provide unprecedented opportunities for achieving a better control of biological processes, and drastic improvements in disease detection, therapy, and prevention. Recent advances in nanomedicine include the development of nanoparticle (NP)-based probes for molecular imaging, nano-carriers for drug/gene delivery, multifunctional NPs for theranostics, and molecular machines for biological and medical studies. This article provides an overview of the nanomedicine field, with an emphasis on NPs for imaging and therapy, as well as engineered nucleases for genome editing. The challenges in translating nanomedicine approaches to clinical applications are discussed.

  11. Comparative Analysis of Automatic Exudate Detection between Machine Learning and Traditional Approaches

    Science.gov (United States)

    Sopharak, Akara; Uyyanonvara, Bunyarit; Barman, Sarah; Williamson, Thomas

    To prevent blindness from diabetic retinopathy, periodic screening and early diagnosis are neccessary. Due to lack of expert ophthalmologists in rural area, automated early exudate (one of visible sign of diabetic retinopathy) detection could help to reduce the number of blindness in diabetic patients. Traditional automatic exudate detection methods are based on specific parameter configuration, while the machine learning approaches which seems more flexible may be computationally high cost. A comparative analysis of traditional and machine learning of exudates detection, namely, mathematical morphology, fuzzy c-means clustering, naive Bayesian classifier, Support Vector Machine and Nearest Neighbor classifier are presented. Detected exudates are validated with expert ophthalmologists' hand-drawn ground-truths. The sensitivity, specificity, precision, accuracy and time complexity of each method are also compared.

  12. Translational Creativity

    DEFF Research Database (Denmark)

    Nielsen, Sandro

    2010-01-01

    A long-established approach to legal translation focuses on terminological equivalence making translators strictly follow the words of source texts. Recent research suggests that there is room for some creativity allowing translators to deviate from the source texts. However, little attention...... is given to genre conventions in source texts and the ways in which they can best be translated. I propose that translators of statutes with an informative function in expert-to-expert communication may be allowed limited translational creativity when translating specific types of genre convention....... This creativity is a result of translators adopting either a source-language or a target-language oriented strategy and is limited by the pragmatic principle of co-operation. Examples of translation options are provided illustrating the different results in target texts. The use of a target-language oriented...

  13. Traduccion automatica mediante el ordenador (Automatic Translation Using a Computer).

    Science.gov (United States)

    Bueno, Julian L.

    This report on machine translation contains a brief history of the field; a description of the processes involved; a discussion of systems currently in use, including three software packages on the market (Teaching Assistant, Translate, and Globalink); reflections on implications for teaching; observations of results obtained when elements of…

  14. Machine learning approaches to analysing textual injury surveillance data: a systematic review.

    Science.gov (United States)

    Vallmuur, Kirsten

    2015-06-01

    To synthesise recent research on the use of machine learning approaches to mining textual injury surveillance data. Systematic review. The electronic databases which were searched included PubMed, Cinahl, Medline, Google Scholar, and Proquest. The bibliography of all relevant articles was examined and associated articles were identified using a snowballing technique. For inclusion, articles were required to meet the following criteria: (a) used a health-related database, (b) focused on injury-related cases, AND used machine learning approaches to analyse textual data. The papers identified through the search were screened resulting in 16 papers selected for review. Articles were reviewed to describe the databases and methodology used, the strength and limitations of different techniques, and quality assurance approaches used. Due to heterogeneity between studies meta-analysis was not performed. Occupational injuries were the focus of half of the machine learning studies and the most common methods described were Bayesian probability or Bayesian network based methods to either predict injury categories or extract common injury scenarios. Models were evaluated through either comparison with gold standard data or content expert evaluation or statistical measures of quality. Machine learning was found to provide high precision and accuracy when predicting a small number of categories, was valuable for visualisation of injury patterns and prediction of future outcomes. However, difficulties related to generalizability, source data quality, complexity of models and integration of content and technical knowledge were discussed. The use of narrative text for injury surveillance has grown in popularity, complexity and quality over recent years. With advances in data mining techniques, increased capacity for analysis of large databases, and involvement of computer scientists in the injury prevention field, along with more comprehensive use and description of quality

  15. Exploring prediction uncertainty of spatial data in geostatistical and machine learning Approaches

    Science.gov (United States)

    Klump, J. F.; Fouedjio, F.

    2017-12-01

    Geostatistical methods such as kriging with external drift as well as machine learning techniques such as quantile regression forest have been intensively used for modelling spatial data. In addition to providing predictions for target variables, both approaches are able to deliver a quantification of the uncertainty associated with the prediction at a target location. Geostatistical approaches are, by essence, adequate for providing such prediction uncertainties and their behaviour is well understood. However, they often require significant data pre-processing and rely on assumptions that are rarely met in practice. Machine learning algorithms such as random forest regression, on the other hand, require less data pre-processing and are non-parametric. This makes the application of machine learning algorithms to geostatistical problems an attractive proposition. The objective of this study is to compare kriging with external drift and quantile regression forest with respect to their ability to deliver reliable prediction uncertainties of spatial data. In our comparison we use both simulated and real world datasets. Apart from classical performance indicators, comparisons make use of accuracy plots, probability interval width plots, and the visual examinations of the uncertainty maps provided by the two approaches. By comparing random forest regression to kriging we found that both methods produced comparable maps of estimated values for our variables of interest. However, the measure of uncertainty provided by random forest seems to be quite different to the measure of uncertainty provided by kriging. In particular, the lack of spatial context can give misleading results in areas without ground truth data. These preliminary results raise questions about assessing the risks associated with decisions based on the predictions from geostatistical and machine learning algorithms in a spatial context, e.g. mineral exploration.

  16. Use of machine learning approaches for novel drug discovery.

    Science.gov (United States)

    Lima, Angélica Nakagawa; Philot, Eric Allison; Trossini, Gustavo Henrique Goulart; Scott, Luis Paulo Barbour; Maltarollo, Vinícius Gonçalves; Honorio, Kathia Maria

    2016-01-01

    The use of computational tools in the early stages of drug development has increased in recent decades. Machine learning (ML) approaches have been of special interest, since they can be applied in several steps of the drug discovery methodology, such as prediction of target structure, prediction of biological activity of new ligands through model construction, discovery or optimization of hits, and construction of models that predict the pharmacokinetic and toxicological (ADMET) profile of compounds. This article presents an overview on some applications of ML techniques in drug design. These techniques can be employed in ligand-based drug design (LBDD) and structure-based drug design (SBDD) studies, such as similarity searches, construction of classification and/or prediction models of biological activity, prediction of secondary structures and binding sites docking and virtual screening. Successful cases have been reported in the literature, demonstrating the efficiency of ML techniques combined with traditional approaches to study medicinal chemistry problems. Some ML techniques used in drug design are: support vector machine, random forest, decision trees and artificial neural networks. Currently, an important application of ML techniques is related to the calculation of scoring functions used in docking and virtual screening assays from a consensus, combining traditional and ML techniques in order to improve the prediction of binding sites and docking solutions.

  17. Predicting DPP-IV inhibitors with machine learning approaches

    Science.gov (United States)

    Cai, Jie; Li, Chanjuan; Liu, Zhihong; Du, Jiewen; Ye, Jiming; Gu, Qiong; Xu, Jun

    2017-04-01

    Dipeptidyl peptidase IV (DPP-IV) is a promising Type 2 diabetes mellitus (T2DM) drug target. DPP-IV inhibitors prolong the action of glucagon-like peptide-1 (GLP-1) and gastric inhibitory peptide (GIP), improve glucose homeostasis without weight gain, edema, and hypoglycemia. However, the marketed DPP-IV inhibitors have adverse effects such as nasopharyngitis, headache, nausea, hypersensitivity, skin reactions and pancreatitis. Therefore, it is still expected for novel DPP-IV inhibitors with minimal adverse effects. The scaffolds of existing DPP-IV inhibitors are structurally diversified. This makes it difficult to build virtual screening models based upon the known DPP-IV inhibitor libraries using conventional QSAR approaches. In this paper, we report a new strategy to predict DPP-IV inhibitors with machine learning approaches involving naïve Bayesian (NB) and recursive partitioning (RP) methods. We built 247 machine learning models based on 1307 known DPP-IV inhibitors with optimized molecular properties and topological fingerprints as descriptors. The overall predictive accuracies of the optimized models were greater than 80%. An external test set, composed of 65 recently reported compounds, was employed to validate the optimized models. The results demonstrated that both NB and RP models have a good predictive ability based on different combinations of descriptors. Twenty "good" and twenty "bad" structural fragments for DPP-IV inhibitors can also be derived from these models for inspiring the new DPP-IV inhibitor scaffold design.

  18. A General and Intuitive Approach to Understand and Compare the Torque Production Capability of AC Machines

    DEFF Research Database (Denmark)

    Wang, Dong; Lu, Kaiyuan; Rasmussen, Peter Omand

    2014-01-01

    Electromagnetic torque analysis is one of the key issues in the analysis of electric machines. It plays an important role in machine design and control. The common method described in most of the textbooks is to calculate the torque in the machine variables and then transform them to the dq......-frame, through complicated mathematical manipulations. This is a more mathematical approach rather than explaining the physics behind torque production, which even brings a lot of difficulties to specialist. This paper introduces a general and intuitive approach to obtain the dq-frame torque equation of various...... AC machines. In this method, torque equation can be obtained based on the intuitive physical understanding of the mechanism behind torque production. It is then approved to be applicable for general case, including rotor saliency and various types of magnetomotive force sources. As an application...

  19. Development of the EtsaTrans translation system prototype and its ...

    African Journals Online (AJOL)

    The issue of multilingualism at the University of the Free State (UFS) gained momentum with the development of the EtsaTrans translation system which is being developed according to the principles of example-based machine translation. In this article the development of the system prototype is described, and an ...

  20. Probabilistic and machine learning-based retrieval approaches for biomedical dataset retrieval

    Science.gov (United States)

    Karisani, Payam; Qin, Zhaohui S; Agichtein, Eugene

    2018-01-01

    Abstract The bioCADDIE dataset retrieval challenge brought together different approaches to retrieval of biomedical datasets relevant to a user’s query, expressed as a text description of a needed dataset. We describe experiments in applying a data-driven, machine learning-based approach to biomedical dataset retrieval as part of this challenge. We report on a series of experiments carried out to evaluate the performance of both probabilistic and machine learning-driven techniques from information retrieval, as applied to this challenge. Our experiments with probabilistic information retrieval methods, such as query term weight optimization, automatic query expansion and simulated user relevance feedback, demonstrate that automatically boosting the weights of important keywords in a verbose query is more effective than other methods. We also show that although there is a rich space of potential representations and features available in this domain, machine learning-based re-ranking models are not able to improve on probabilistic information retrieval techniques with the currently available training data. The models and algorithms presented in this paper can serve as a viable implementation of a search engine to provide access to biomedical datasets. The retrieval performance is expected to be further improved by using additional training data that is created by expert annotation, or gathered through usage logs, clicks and other processes during natural operation of the system. Database URL: https://github.com/emory-irlab/biocaddie

  1. Use of Online Machine Translation for Nursing Literature: A Questionnaire-Based Survey

    Science.gov (United States)

    Anazawa, Ryoko; Ishikawa, Hirono; Takahiro, Kiuchi

    2013-01-01

    Background: The language barrier is a significant obstacle for nurses who are not native English speakers to obtain information from international journals. Freely accessible online machine translation (MT) offers a possible solution to this problem. Aim: To explore how Japanese nursing professionals use online MT and perceive its usability in reading English articles and to discuss what should be considered for better utilisation of online MT lessening the language barrier. Method: In total, 250 randomly selected assistants and research associates at nursing colleges across Japan answered a questionnaire examining the current use of online MT and perceived usability among Japanese nurses, along with the number of articles read in English and the perceived language barrier. The items were rated on Likert scales, and t-test, ANOVA, chi-square test, and Spearman’s correlation were used for analyses. Results: Of the participants, 73.8% had used online MT. More than half of them felt it was usable. The language barrier was strongly felt, and academic degrees and English proficiency level were associated factors. The perceived language barrier was related to the frequency of online MT use. No associated factor was found for the perceived usability of online MT. Conclusion: Language proficiency is an important factor for optimum utilisation of MT. A need for education in the English language, reading scientific papers, and online MT training was indicated. Cooperation with developers and providers of MT for the improvement of their systems is required. PMID:23459140

  2. Translating Management Practices in Hierarchical Organizations

    DEFF Research Database (Denmark)

    Wæraas, Arild; Nielsen, Jeppe Agger

    structures affect translators’ approaches taken towards management ideas. This paper reports the findings from a longitudinal case study of the translation of Leadership Pipeline in a Danish fire department and how the translators’ approach changed over time from a modifying to a reproducing mode. The study......This study examines how translators in a hierarchical context approach the translation of management practices. Although current translation theory and research emphasize the importance of contextual factors in translation processes, little research has investigated how strongly hierarchical...... finds that translation does not necessarily imply transformation of the management idea, pointing instead to aspects of exact imitation and copying of an ”original” idea. It also highlights how translation is likely to involve multiple and successive translation modes and, furthermore, that strongly...

  3. Machine learning and radiology.

    Science.gov (United States)

    Wang, Shijun; Summers, Ronald M

    2012-07-01

    In this paper, we give a short introduction to machine learning and survey its applications in radiology. We focused on six categories of applications in radiology: medical image segmentation, registration, computer aided detection and diagnosis, brain function or activity analysis and neurological disease diagnosis from fMR images, content-based image retrieval systems for CT or MRI images, and text analysis of radiology reports using natural language processing (NLP) and natural language understanding (NLU). This survey shows that machine learning plays a key role in many radiology applications. Machine learning identifies complex patterns automatically and helps radiologists make intelligent decisions on radiology data such as conventional radiographs, CT, MRI, and PET images and radiology reports. In many applications, the performance of machine learning-based automatic detection and diagnosis systems has shown to be comparable to that of a well-trained and experienced radiologist. Technology development in machine learning and radiology will benefit from each other in the long run. Key contributions and common characteristics of machine learning techniques in radiology are discussed. We also discuss the problem of translating machine learning applications to the radiology clinical setting, including advantages and potential barriers. Copyright © 2012. Published by Elsevier B.V.

  4. Code-expanded radio access protocol for machine-to-machine communications

    DEFF Research Database (Denmark)

    Thomsen, Henning; Kiilerich Pratas, Nuno; Stefanovic, Cedomir

    2013-01-01

    The random access methods used for support of machine-to-machine, also referred to as Machine-Type Communications, in current cellular standards are derivatives of traditional framed slotted ALOHA and therefore do not support high user loads efficiently. We propose an approach that is motivated b...... subframes and orthogonal preambles, the amount of available contention resources is drastically increased, enabling the massive support of Machine-Type Communication users that is beyond the reach of current systems.......The random access methods used for support of machine-to-machine, also referred to as Machine-Type Communications, in current cellular standards are derivatives of traditional framed slotted ALOHA and therefore do not support high user loads efficiently. We propose an approach that is motivated...... by the random access method employed in LTE, which significantly increases the amount of contention resources without increasing the system resources, such as contention subframes and preambles. This is accomplished by a logical, rather than physical, extension of the access method in which the available system...

  5. Applications and modelling of bulk HTSs in brushless ac machines

    International Nuclear Information System (INIS)

    Barnes, G.J.

    2000-01-01

    The use of high temperature superconducting material in its bulk form for engineering applications is attractive due to the large power densities that can be achieved. In brushless electrical machines, there are essentially four properties that can be exploited; their hysteretic nature, their flux shielding properties, their ability to trap large flux densities and their ability to produce levitation. These properties translate to hysteresis machines, reluctance machines, trapped-field synchronous machines and linear motors respectively. Each one of these machines is addressed separately and computer simulations that reveal the current and field distributions within the machines are used to explain their operation. (author)

  6. Factored Translation with Unsupervised Word Clusters

    DEFF Research Database (Denmark)

    Rishøj, Christian; Søgaard, Anders

    2011-01-01

    Unsupervised word clustering algorithms — which form word clusters based on a measure of distributional similarity — have proven to be useful in providing beneficial features for various natural language processing tasks involving supervised learning. This work explores the utility of such word...... clusters as factors in statistical machine translation. Although some of the language pairs in this work clearly benefit from the factor augmentation, there is no consistent improvement in translation accuracy across the board. For all language pairs, the word clusters clearly improve translation for some...... proportion of the sentences in the test set, but has a weak or even detrimental effect on the rest. It is shown that if one could determine whether or not to use a factor when translating a given sentence, rather substantial improvements in precision could be achieved for all of the language pairs evaluated...

  7. Developing corpus-based translation methods between informal and formal mathematics : project description

    NARCIS (Netherlands)

    Kaliszyk, C.; Urban, J.; Vyskocil, J.; Geuvers, J.H.; Watt, S.M.; Davenport, J.H.; Sexton, A.P.; Sojka, P.; Urban, J.

    2014-01-01

    The goal of this project is to (i) accumulate annotated informal/formal mathematical corpora suitable for training semi-automated translation between informal and formal mathematics by statistical machine-translation methods, (ii) to develop such methods oriented at the formalization task, and in

  8. Syntactic discriminative language model rerankers for statistical machine translation

    NARCIS (Netherlands)

    Carter, S.; Monz, C.

    2011-01-01

    This article describes a method that successfully exploits syntactic features for n-best translation candidate reranking using perceptrons. We motivate the utility of syntax by demonstrating the superior performance of parsers over n-gram language models in differentiating between Statistical

  9. Efficient accurate syntactic direct translation models: one tree at a time

    NARCIS (Netherlands)

    Hassan, H.; Sima'an, K.; Way, A.

    2011-01-01

    A challenging aspect of Statistical Machine Translation from Arabic to English lies in bringing the Arabic source morpho-syntax to bear on the lexical as well as word-order choices of the English target string. In this article, we extend the feature-rich discriminative Direct Translation Model 2

  10. Predicting post-translational lysine acetylation using support vector machines

    DEFF Research Database (Denmark)

    Gnad, Florian; Ren, Shubin; Choudhary, Chunaram

    2010-01-01

    spectrometry to identify 3600 lysine acetylation sites on 1750 human proteins covering most of the previously annotated sites and providing the most comprehensive acetylome so far. This dataset should provide an excellent source to train support vector machines (SVMs) allowing the high accuracy in silico...

  11. Optimizing Distributed Machine Learning for Large Scale EEG Data Set

    Directory of Open Access Journals (Sweden)

    M Bilal Shaikh

    2017-06-01

    Full Text Available Distributed Machine Learning (DML has gained its importance more than ever in this era of Big Data. There are a lot of challenges to scale machine learning techniques on distributed platforms. When it comes to scalability, improving the processor technology for high level computation of data is at its limit, however increasing machine nodes and distributing data along with computation looks as a viable solution. Different frameworks   and platforms are available to solve DML problems. These platforms provide automated random data distribution of datasets which miss the power of user defined intelligent data partitioning based on domain knowledge. We have conducted an empirical study which uses an EEG Data Set collected through P300 Speller component of an ERP (Event Related Potential which is widely used in BCI problems; it helps in translating the intention of subject w h i l e performing any cognitive task. EEG data contains noise due to waves generated by other activities in the brain which contaminates true P300Speller. Use of Machine Learning techniques could help in detecting errors made by P300 Speller. We are solving this classification problem by partitioning data into different chunks and preparing distributed models using Elastic CV Classifier. To present a case of optimizing distributed machine learning, we propose an intelligent user defined data partitioning approach that could impact on the accuracy of distributed machine learners on average. Our results show better average AUC as compared to average AUC obtained after applying random data partitioning which gives no control to user over data partitioning. It improves the average accuracy of distributed learner due to the domain specific intelligent partitioning by the user. Our customized approach achieves 0.66 AUC on individual sessions and 0.75 AUC on mixed sessions, whereas random / uncontrolled data distribution records 0.63 AUC.

  12. A Wavelet Bicoherence-Based Quadratic Nonlinearity Feature for Translational Axis Condition Monitoring

    Directory of Open Access Journals (Sweden)

    Yong Li

    2014-01-01

    Full Text Available The translational axis is one of the most important subsystems in modern machine tools, as its degradation may result in the loss of the product qualification and lower the control precision. Condition-based maintenance (CBM has been considered as one of the advanced maintenance schemes to achieve effective, reliable and cost-effective operation of machine systems, however, current vibration-based maintenance schemes cannot be employed directly in the translational axis system, due to its complex structure and the inefficiency of commonly used condition monitoring features. In this paper, a wavelet bicoherence-based quadratic nonlinearity feature is proposed for translational axis condition monitoring by using the torque signature of the drive servomotor. Firstly, the quadratic nonlinearity of the servomotor torque signature is discussed, and then, a biphase randomization wavelet bicoherence is introduced for its quadratic nonlinear detection. On this basis, a quadratic nonlinearity feature is proposed for condition monitoring of the translational axis. The properties of the proposed quadratic nonlinearity feature are investigated by simulations. Subsequently, this feature is applied to the real-world servomotor torque data collected from the X-axis on a high precision vertical machining centre. All the results show that the performance of the proposed feature is much better than that of original condition monitoring features.

  13. Translational selection is ubiquitous in prokaryotes.

    Directory of Open Access Journals (Sweden)

    Fran Supek

    2010-06-01

    Full Text Available Codon usage bias in prokaryotic genomes is largely a consequence of background substitution patterns in DNA, but highly expressed genes may show a preference towards codons that enable more efficient and/or accurate translation. We introduce a novel approach based on supervised machine learning that detects effects of translational selection on genes, while controlling for local variation in nucleotide substitution patterns represented as sequence composition of intergenic DNA. A cornerstone of our method is a Random Forest classifier that outperformed previous distance measure-based approaches, such as the codon adaptation index, in the task of discerning the (highly expressed ribosomal protein genes by their codon frequencies. Unlike previous reports, we show evidence that translational selection in prokaryotes is practically universal: in 460 of 461 examined microbial genomes, we find that a subset of genes shows a higher codon usage similarity to the ribosomal proteins than would be expected from the local sequence composition. These genes constitute a substantial part of the genome--between 5% and 33%, depending on genome size--while also exhibiting higher experimentally measured mRNA abundances and tending toward codons that match tRNA anticodons by canonical base pairing. Certain gene functional categories are generally enriched with, or depleted of codon-optimized genes, the trends of enrichment/depletion being conserved between Archaea and Bacteria. Prominent exceptions from these trends might indicate genes with alternative physiological roles; we speculate on specific examples related to detoxication of oxygen radicals and ammonia and to possible misannotations of asparaginyl-tRNA synthetases. Since the presence of codon optimizations on genes is a valid proxy for expression levels in fully sequenced genomes, we provide an example of an "adaptome" by highlighting gene functions with expression levels elevated specifically in

  14. Process planning optimization on turning machine tool using a hybrid genetic algorithm with local search approach

    Directory of Open Access Journals (Sweden)

    Yuliang Su

    2015-04-01

    Full Text Available A turning machine tool is a kind of new type of machine tool that is equipped with more than one spindle and turret. The distinctive simultaneous and parallel processing abilities of turning machine tool increase the complexity of process planning. The operations would not only be sequenced and satisfy precedence constraints, but also should be scheduled with multiple objectives such as minimizing machining cost, maximizing utilization of turning machine tool, and so on. To solve this problem, a hybrid genetic algorithm was proposed to generate optimal process plans based on a mixed 0-1 integer programming model. An operation precedence graph is used to represent precedence constraints and help generate a feasible initial population of hybrid genetic algorithm. Encoding strategy based on data structure was developed to represent process plans digitally in order to form the solution space. In addition, a local search approach for optimizing the assignments of available turrets would be added to incorporate scheduling with process planning. A real-world case is used to prove that the proposed approach could avoid infeasible solutions and effectively generate a global optimal process plan.

  15. From machine learning to deep learning: progress in machine intelligence for rational drug discovery.

    Science.gov (United States)

    Zhang, Lu; Tan, Jianjun; Han, Dan; Zhu, Hao

    2017-11-01

    Machine intelligence, which is normally presented as artificial intelligence, refers to the intelligence exhibited by computers. In the history of rational drug discovery, various machine intelligence approaches have been applied to guide traditional experiments, which are expensive and time-consuming. Over the past several decades, machine-learning tools, such as quantitative structure-activity relationship (QSAR) modeling, were developed that can identify potential biological active molecules from millions of candidate compounds quickly and cheaply. However, when drug discovery moved into the era of 'big' data, machine learning approaches evolved into deep learning approaches, which are a more powerful and efficient way to deal with the massive amounts of data generated from modern drug discovery approaches. Here, we summarize the history of machine learning and provide insight into recently developed deep learning approaches and their applications in rational drug discovery. We suggest that this evolution of machine intelligence now provides a guide for early-stage drug design and discovery in the current big data era. Copyright © 2017 Elsevier Ltd. All rights reserved.

  16. Machine learning for adaptive many-core machines a practical approach

    CERN Document Server

    Lopes, Noel

    2015-01-01

    The overwhelming data produced everyday and the increasing performance and cost requirements of applications?are transversal to a wide range of activities in society, from science to industry. In particular, the magnitude and complexity of the tasks that Machine Learning (ML) algorithms have to solve are driving the need to devise adaptive many-core machines that scale well with the volume of data, or in other words, can handle Big Data.This book gives a concise view on how to extend the applicability of well-known ML algorithms in Graphics Processing Unit (GPU) with data scalability in mind.

  17. Prediction of In-hospital Mortality in Emergency Department Patients With Sepsis: A Local Big Data-Driven, Machine Learning Approach.

    Science.gov (United States)

    Taylor, R Andrew; Pare, Joseph R; Venkatesh, Arjun K; Mowafi, Hani; Melnick, Edward R; Fleischman, William; Hall, M Kennedy

    2016-03-01

    the 4,222 patients in the training group, 210 (5.0%) died during hospitalization, and of the 1,056 patients in the validation group, 50 (4.7%) died during hospitalization. The AUCs with 95% confidence intervals (CIs) for the different models were as follows: random forest model, 0.86 (95% CI = 0.82 to 0.90); CART model, 0.69 (95% CI = 0.62 to 0.77); logistic regression model, 0.76 (95% CI = 0.69 to 0.82); CURB-65, 0.73 (95% CI = 0.67 to 0.80); MEDS, 0.71 (95% CI = 0.63 to 0.77); and mREMS, 0.72 (95% CI = 0.65 to 0.79). The random forest model AUC was statistically different from all other models (p ≤ 0.003 for all comparisons). In this proof-of-concept study, a local big data-driven, machine learning approach outperformed existing CDRs as well as traditional analytic techniques for predicting in-hospital mortality of ED patients with sepsis. Future research should prospectively evaluate the effectiveness of this approach and whether it translates into improved clinical outcomes for high-risk sepsis patients. The methods developed serve as an example of a new model for predictive analytics in emergency care that can be automated, applied to other clinical outcomes of interest, and deployed in EHRs to enable locally relevant clinical predictions. © 2015 by the Society for Academic Emergency Medicine.

  18. DESIGN ANALYSIS OF ELECTRICAL MACHINES THROUGH INTEGRATED NUMERICAL APPROACH

    Directory of Open Access Journals (Sweden)

    ARAVIND C.V.

    2016-02-01

    Full Text Available An integrated design platform for the newer type of machines is presented in this work. The machine parameters are evaluated out using developed modelling tool. With the machine parameters, the machine is modelled using computer aided tool. The designed machine is brought to simulation tool to perform electromagnetic and electromechanical analysis. In the simulation, conditions setting are performed to setup the materials, meshes, rotational speed and the excitation circuit. Electromagnetic analysis is carried out to predict the behavior of the machine based on the movement of flux in the machines. Besides, electromechanical analysis is carried out to analyse the speed-torque characteristic, the current-torque characteristic and the phase angle-torque characteristic. After all the results are analysed, the designed machine is used to generate S block function that is compatible with MATLAB/SIMULINK tool for the dynamic operational characteristics. This allows the integration of existing drive system into the new machines designed in the modelling tool. An example of the machine design is presented to validate the usage of such a tool.

  19. Geminivirus data warehouse: a database enriched with machine learning approaches.

    Science.gov (United States)

    Silva, Jose Cleydson F; Carvalho, Thales F M; Basso, Marcos F; Deguchi, Michihito; Pereira, Welison A; Sobrinho, Roberto R; Vidigal, Pedro M P; Brustolini, Otávio J B; Silva, Fabyano F; Dal-Bianco, Maximiller; Fontes, Renildes L F; Santos, Anésia A; Zerbini, Francisco Murilo; Cerqueira, Fabio R; Fontes, Elizabeth P B

    2017-05-05

    The Geminiviridae family encompasses a group of single-stranded DNA viruses with twinned and quasi-isometric virions, which infect a wide range of dicotyledonous and monocotyledonous plants and are responsible for significant economic losses worldwide. Geminiviruses are divided into nine genera, according to their insect vector, host range, genome organization, and phylogeny reconstruction. Using rolling-circle amplification approaches along with high-throughput sequencing technologies, thousands of full-length geminivirus and satellite genome sequences were amplified and have become available in public databases. As a consequence, many important challenges have emerged, namely, how to classify, store, and analyze massive datasets as well as how to extract information or new knowledge. Data mining approaches, mainly supported by machine learning (ML) techniques, are a natural means for high-throughput data analysis in the context of genomics, transcriptomics, proteomics, and metabolomics. Here, we describe the development of a data warehouse enriched with ML approaches, designated geminivirus.org. We implemented search modules, bioinformatics tools, and ML methods to retrieve high precision information, demarcate species, and create classifiers for genera and open reading frames (ORFs) of geminivirus genomes. The use of data mining techniques such as ETL (Extract, Transform, Load) to feed our database, as well as algorithms based on machine learning for knowledge extraction, allowed us to obtain a database with quality data and suitable tools for bioinformatics analysis. The Geminivirus Data Warehouse (geminivirus.org) offers a simple and user-friendly environment for information retrieval and knowledge discovery related to geminiviruses.

  20. Discovery of Intermetallic Compounds from Traditional to Machine-Learning Approaches.

    Science.gov (United States)

    Oliynyk, Anton O; Mar, Arthur

    2018-01-16

    Intermetallic compounds are bestowed by diverse compositions, complex structures, and useful properties for many materials applications. How metallic elements react to form these compounds and what structures they adopt remain challenging questions that defy predictability. Traditional approaches offer some rational strategies to prepare specific classes of intermetallics, such as targeting members within a modular homologous series, manipulating building blocks to assemble new structures, and filling interstitial sites to create stuffed variants. Because these strategies rely on precedent, they cannot foresee surprising results, by definition. Exploratory synthesis, whether through systematic phase diagram investigations or serendipity, is still essential for expanding our knowledge base. Eventually, the relationships may become too complex for the pattern recognition skills to be reliably or practically performed by humans. Complementing these traditional approaches, new machine-learning approaches may be a viable alternative for materials discovery, not only among intermetallics but also more generally to other chemical compounds. In this Account, we survey our own efforts to discover new intermetallic compounds, encompassing gallides, germanides, phosphides, arsenides, and others. We apply various machine-learning methods (such as support vector machine and random forest algorithms) to confront two significant questions in solid state chemistry. First, what crystal structures are adopted by a compound given an arbitrary composition? Initial efforts have focused on binary equiatomic phases AB, ternary equiatomic phases ABC, and full Heusler phases AB 2 C. Our analysis emphasizes the use of real experimental data and places special value on confirming predictions through experiment. Chemical descriptors are carefully chosen through a rigorous procedure called cluster resolution feature selection. Predictions for crystal structures are quantified by evaluating

  1. National Heart, Lung, and Blood Institute and the translation of cardiovascular discoveries into therapeutic approaches.

    Science.gov (United States)

    Galis, Zorina S; Black, Jodi B; Skarlatos, Sonia I

    2013-04-26

    The molecular causes of ≈4000 medical conditions have been described, yet only 5% have associated therapies. For decades, the average time for drug development through approval has taken 10 to 20 years. In recent years, the serious challenges that confront the private sector have made it difficult to capitalize on new opportunities presented by advances in genomics and cellular therapies. Current trends are disturbing. Pharmaceutical companies are reducing their investments in research, and biotechnology companies are struggling to obtain venture funds. To support early-stage translation of the discoveries in basic science, the National Institutes of Health and the National Heart, Lung, and Blood Institute have developed new approaches to facilitating the translation of basic discoveries into clinical applications and will continue to develop a variety of programs that create teams of academic investigators and industry partners. The goal of these programs is to maximize the public benefit of investment of taxpayer dollars in biomedical research and to lessen the risk required for industry partners to make substantial investments. This article highlights several examples of National Heart, Lung, and Blood Institute-initiated translational programs and National Institutes of Health translational resources designed to catalyze and enable the earliest stages of the biomedical product development process. The translation of latest discoveries into therapeutic approaches depends on continued federal funding to enhance the early stages of the product development process and to stimulate and catalyze partnerships between academia, industry, and other sources of capital.

  2. Peak Detection Method Evaluation for Ion Mobility Spectrometry by Using Machine Learning Approaches

    DEFF Research Database (Denmark)

    Hauschild, Anne-Christin; Kopczynski, Dominik; D'Addario, Marianna

    2013-01-01

    machine learning methods exist, an inevitable preprocessing step is reliable and robust peak detection without manual intervention. In this work we evaluate four state-of-the-art approaches for automated IMS-based peak detection: local maxima search, watershed transformation with IPHEx, region......-merging with VisualNow, and peak model estimation (PME).We manually generated Metabolites 2013, 3 278 a gold standard with the aid of a domain expert (manual) and compare the performance of the four peak calling methods with respect to two distinct criteria. We first utilize established machine learning methods...

  3. Quantifying complexity in translational research: an integrated approach.

    Science.gov (United States)

    Munoz, David A; Nembhard, Harriet Black; Kraschnewski, Jennifer L

    2014-01-01

    The purpose of this paper is to quantify complexity in translational research. The impact of major operational steps and technical requirements is calculated with respect to their ability to accelerate moving new discoveries into clinical practice. A three-phase integrated quality function deployment (QFD) and analytic hierarchy process (AHP) method was used to quantify complexity in translational research. A case study in obesity was used to usability. Generally, the evidence generated was valuable for understanding various components in translational research. Particularly, the authors found that collaboration networks, multidisciplinary team capacity and community engagement are crucial for translating new discoveries into practice. As the method is mainly based on subjective opinion, some argue that the results may be biased. However, a consistency ratio is calculated and used as a guide to subjectivity. Alternatively, a larger sample may be incorporated to reduce bias. The integrated QFD-AHP framework provides evidence that could be helpful to generate agreement, develop guidelines, allocate resources wisely, identify benchmarks and enhance collaboration among similar projects. Current conceptual models in translational research provide little or no clue to assess complexity. The proposed method aimed to fill this gap. Additionally, the literature review includes various features that have not been explored in translational research.

  4. Measurements of translation, rotation and strain: new approaches to seismic processing and inversion

    NARCIS (Netherlands)

    Bernauer, M.; Fichtner, A.; Igel, H.

    2012-01-01

    We propose a novel approach to seismic tomography based on the joint processing of translation, strain and rotation measurements. Our concept is based on the apparent S and P velocities, defined as the ratios of displacement velocity and rotation amplitude, and displacement velocity and

  5. Machine Learning

    CERN Multimedia

    CERN. Geneva

    2017-01-01

    Machine learning, which builds on ideas in computer science, statistics, and optimization, focuses on developing algorithms to identify patterns and regularities in data, and using these learned patterns to make predictions on new observations. Boosted by its industrial and commercial applications, the field of machine learning is quickly evolving and expanding. Recent advances have seen great success in the realms of computer vision, natural language processing, and broadly in data science. Many of these techniques have already been applied in particle physics, for instance for particle identification, detector monitoring, and the optimization of computer resources. Modern machine learning approaches, such as deep learning, are only just beginning to be applied to the analysis of High Energy Physics data to approach more and more complex problems. These classes will review the framework behind machine learning and discuss recent developments in the field.

  6. On Literal Translation of English Idioms

    Science.gov (United States)

    Chen, Linli

    2009-01-01

    There are six translation tactics in translating English idioms into Chinese: literal translation, compensatory translation, free translation, explanational translation, borrowing, integrated approach. Each tactic should be reasonably employed in the process of translating, so as to keep the flavor of the original English idioms as well as to…

  7. A fuzzy regression with support vector machine approach to the estimation of horizontal global solar radiation

    International Nuclear Information System (INIS)

    Baser, Furkan; Demirhan, Haydar

    2017-01-01

    Accurate estimation of the amount of horizontal global solar radiation for a particular field is an important input for decision processes in solar radiation investments. In this article, we focus on the estimation of yearly mean daily horizontal global solar radiation by using an approach that utilizes fuzzy regression functions with support vector machine (FRF-SVM). This approach is not seriously affected by outlier observations and does not suffer from the over-fitting problem. To demonstrate the utility of the FRF-SVM approach in the estimation of horizontal global solar radiation, we conduct an empirical study over a dataset collected in Turkey and applied the FRF-SVM approach with several kernel functions. Then, we compare the estimation accuracy of the FRF-SVM approach to an adaptive neuro-fuzzy system and a coplot supported-genetic programming approach. We observe that the FRF-SVM approach with a Gaussian kernel function is not affected by both outliers and over-fitting problem and gives the most accurate estimates of horizontal global solar radiation among the applied approaches. Consequently, the use of hybrid fuzzy functions and support vector machine approaches is found beneficial in long-term forecasting of horizontal global solar radiation over a region with complex climatic and terrestrial characteristics. - Highlights: • A fuzzy regression functions with support vector machines approach is proposed. • The approach is robust against outlier observations and over-fitting problem. • Estimation accuracy of the model is superior to several existent alternatives. • A new solar radiation estimation model is proposed for the region of Turkey. • The model is useful under complex terrestrial and climatic conditions.

  8. Two Approaches for the Management of Virtual Machines on Grid Infrastructures

    International Nuclear Information System (INIS)

    Tapiador, D.; Rubio-Montero, A. J.; Juedo, E.; Montero, R. S.; Llorente, I. M.

    2007-01-01

    Virtual machines are a promising technology to overcome some of the problems found in current Grid infrastructures, like heterogeneity, performance partitioning or application isolation. This work shows a comparison between two strategies to manage virtual machines in Globus Grids. The first alternative is a straightforward deployment that does not require additional middle ware to be installed. It is only based on standard Grid services and is not bound to a given virtualization technology. Although this option is fully functional, it is only suitable for single process batch jobs. The second solution makes use of the Virtual Workspace Service which allows a remote client to securely negotiate and manage a virtual resource. This approach better exploits the potential benefits offered by the virtualization technology and provides a wider application range. (Author)

  9. Translational Epidemiology in Psychiatry

    Science.gov (United States)

    Weissman, Myrna M.; Brown, Alan S.; Talati, Ardesheer

    2012-01-01

    Translational research generally refers to the application of knowledge generated by advances in basic sciences research translated into new approaches for diagnosis, prevention, and treatment of disease. This direction is called bench-to-bedside. Psychiatry has similarly emphasized the basic sciences as the starting point of translational research. This article introduces the term translational epidemiology for psychiatry research as a bidirectional concept in which the knowledge generated from the bedside or the population can also be translated to the benches of laboratory science. Epidemiologic studies are primarily observational but can generate representative samples, novel designs, and hypotheses that can be translated into more tractable experimental approaches in the clinical and basic sciences. This bedside-to-bench concept has not been explicated in psychiatry, although there are an increasing number of examples in the research literature. This article describes selected epidemiologic designs, providing examples and opportunities for translational research from community surveys and prospective, birth cohort, and family-based designs. Rapid developments in informatics, emphases on large sample collection for genetic and biomarker studies, and interest in personalized medicine—which requires information on relative and absolute risk factors—make this topic timely. The approach described has implications for providing fresh metaphors to communicate complex issues in interdisciplinary collaborations and for training in epidemiology and other sciences in psychiatry. PMID:21646577

  10. Predicting Post-Editor Profiles from the Translation Process

    DEFF Research Database (Denmark)

    Singla, Karan; Orrego-Carmona, David; Gonzales, Ashleigh Rhea

    2014-01-01

    The purpose of the current investigation is to predict post-editor profiles based on user behaviour and demographics using machine learning techniques to gain a better understanding of post-editor styles. Our study extracts process unit features from the CasMaCat LS14 database from the CRITT...... of translation process features. The classification and clustering of participants resulting from our study suggest this type of exploration could be used as a tool to develop new translation tool features or customization possibilities....

  11. Two Machine Learning Approaches for Short-Term Wind Speed Time-Series Prediction.

    Science.gov (United States)

    Ak, Ronay; Fink, Olga; Zio, Enrico

    2016-08-01

    The increasing liberalization of European electricity markets, the growing proportion of intermittent renewable energy being fed into the energy grids, and also new challenges in the patterns of energy consumption (such as electric mobility) require flexible and intelligent power grids capable of providing efficient, reliable, economical, and sustainable energy production and distribution. From the supplier side, particularly, the integration of renewable energy sources (e.g., wind and solar) into the grid imposes an engineering and economic challenge because of the limited ability to control and dispatch these energy sources due to their intermittent characteristics. Time-series prediction of wind speed for wind power production is a particularly important and challenging task, wherein prediction intervals (PIs) are preferable results of the prediction, rather than point estimates, because they provide information on the confidence in the prediction. In this paper, two different machine learning approaches to assess PIs of time-series predictions are considered and compared: 1) multilayer perceptron neural networks trained with a multiobjective genetic algorithm and 2) extreme learning machines combined with the nearest neighbors approach. The proposed approaches are applied for short-term wind speed prediction from a real data set of hourly wind speed measurements for the region of Regina in Saskatchewan, Canada. Both approaches demonstrate good prediction precision and provide complementary advantages with respect to different evaluation criteria.

  12. Translating India

    CERN Document Server

    Kothari, Rita

    2014-01-01

    The cultural universe of urban, English-speaking middle class in India shows signs of growing inclusiveness as far as English is concerned. This phenomenon manifests itself in increasing forms of bilingualism (combination of English and one Indian language) in everyday forms of speech - advertisement jingles, bilingual movies, signboards, and of course conversations. It is also evident in the startling prominence of Indian Writing in English and somewhat less visibly, but steadily rising, activity of English translation from Indian languages. Since the eighties this has led to a frenetic activity around English translation in India's academic and literary circles. Kothari makes this very current phenomenon her chief concern in Translating India.   The study covers aspects such as the production, reception and marketability of English translation. Through an unusually multi-disciplinary approach, this study situates English translation in India amidst local and global debates on translation, representation an...

  13. A Double-Edged Sword: The Merits and the Policy Implications of Google Translate in Higher Education

    Science.gov (United States)

    Mundt, Klaus; Groves, Michael

    2016-01-01

    Machine translation, specifically Google Translate, is freely available, and is improving in its ability to provide grammatically accurate translations. This development has the potential to provoke a major transformation in the internationalization process at universities, since students may be, in the future, able to use technology to circumvent…

  14. Translation of Genotype to Phenotype by a Hierarchy of Cell Subsystems.

    Science.gov (United States)

    Yu, Michael Ku; Kramer, Michael; Dutkowski, Janusz; Srivas, Rohith; Licon, Katherine; Kreisberg, Jason; Ng, Cherie T; Krogan, Nevan; Sharan, Roded; Ideker, Trey

    2016-02-24

    Accurately translating genotype to phenotype requires accounting for the functional impact of genetic variation at many biological scales. Here we present a strategy for genotype-phenotype reasoning based on existing knowledge of cellular subsystems. These subsystems and their hierarchical organization are defined by the Gene Ontology or a complementary ontology inferred directly from previously published datasets. Guided by the ontology's hierarchical structure, we organize genotype data into an "ontotype," that is, a hierarchy of perturbations representing the effects of genetic variation at multiple cellular scales. The ontotype is then interpreted using logical rules generated by machine learning to predict phenotype. This approach substantially outperforms previous, non-hierarchical methods for translating yeast genotype to cell growth phenotype, and it accurately predicts the growth outcomes of two new screens of 2,503 double gene knockouts impacting DNA repair or nuclear lumen. Ontotypes also generalize to larger knockout combinations, setting the stage for interpreting the complex genetics of disease.

  15. Application of a 16-bit microprocessor to the digital control of machine tools

    International Nuclear Information System (INIS)

    Issaly, Alain

    1979-01-01

    After an overview of machine tools (various types, definition standardization, associated technologies for motors and position sensors), this research thesis describes the principles of computer-based digital control: classification of machine tool command systems, machining programming, programming languages, dialog function, interpolation function, servo-control function, tool compensation function. The author reports the application of a 16-bit microprocessor to the computer-based digital control of a machine tool: feasibility, selection of microprocessor, hardware presentation, software development and description, machining mode, translation-loading mode

  16. CULTURAL TRANSFER IN TRAVEL GUIDE TRANSLATION: DISCOURSE APPROACH

    Directory of Open Access Journals (Sweden)

    Novikova Elina Yuryevna

    2014-09-01

    Full Text Available Intercultural communication and dialogue between various social and political structures and their globalized conditions immediately lead to the development of tourism and services market in this area, including translation services. The study of linguocultural characteristics of a travel guide in terms of pragmatically adequate translation is an interesting aspect for the analysis of the development and functioning of logics of modern interaction planes because the mass tourism participants' communicative characteristics are determined, on the one hand, by the universal, global, economic, social and cultural programmes of mass tourism and, on the other hand, by the local and national peculiarities of tourism discourse in general. The choice of linguistic means in travel guides is determined by their communicative and pragmatic as well as ethno-cultural characteristics that form the main discourse oriented translation programme. The translation of the travel guide texts to German supposes significant differences at out- and in-text levels to achieve maximum compliance with the potential recipients' expectations. The analysis of the two translations of the Russian-language travel guide made to German by the native German speaker and the non-native German speaker let define the so-called sharp edges in the cultural transfer of the information important for the discourse. The travel guide is characterized by the specific features of the touristics discourse, on the one hand, and by the interesting experience of translating, on the other hand.

  17. Intelligent Machine Learning Approaches for Aerospace Applications

    Science.gov (United States)

    Sathyan, Anoop

    Machine Learning is a type of artificial intelligence that provides machines or networks the ability to learn from data without the need to explicitly program them. There are different kinds of machine learning techniques. This thesis discusses the applications of two of these approaches: Genetic Fuzzy Logic and Convolutional Neural Networks (CNN). Fuzzy Logic System (FLS) is a powerful tool that can be used for a wide variety of applications. FLS is a universal approximator that reduces the need for complex mathematics and replaces it with expert knowledge of the system to produce an input-output mapping using If-Then rules. The expert knowledge of a system can help in obtaining the parameters for small-scale FLSs, but for larger networks we will need to use sophisticated approaches that can automatically train the network to meet the design requirements. This is where Genetic Algorithms (GA) and EVE come into the picture. Both GA and EVE can tune the FLS parameters to minimize a cost function that is designed to meet the requirements of the specific problem. EVE is an artificial intelligence developed by Psibernetix that is trained to tune large scale FLSs. The parameters of an FLS can include the membership functions and rulebase of the inherent Fuzzy Inference Systems (FISs). The main issue with using the GFS is that the number of parameters in a FIS increase exponentially with the number of inputs thus making it increasingly harder to tune them. To reduce this issue, the FLSs discussed in this thesis consist of 2-input-1-output FISs in cascade (Chapter 4) or as a layer of parallel FISs (Chapter 7). We have obtained extremely good results using GFS for different applications at a reduced computational cost compared to other algorithms that are commonly used to solve the corresponding problems. In this thesis, GFSs have been designed for controlling an inverted double pendulum, a task allocation problem of clustering targets amongst a set of UAVs, a fire

  18. The Maximum Cross-Correlation approach to detecting translational motions from sequential remote-sensing images

    Science.gov (United States)

    Gao, J.; Lythe, M. B.

    1996-06-01

    This paper presents the principle of the Maximum Cross-Correlation (MCC) approach in detecting translational motions within dynamic fields from time-sequential remotely sensed images. A C program implementing the approach is presented and illustrated in a flowchart. The program is tested with a pair of sea-surface temperature images derived from Advanced Very High Resolution Radiometer (AVHRR) images near East Cape, New Zealand. Results show that the mean currents in the region have been detected satisfactorily with the approach.

  19. A practical approach for translating climate change adaptation principles into forest management actions

    Science.gov (United States)

    Maria K. Janowiak; Christopher W. Swanston; Linda M. Nagel; Leslie A. Brandt; Patricia R. Butler; Stephen D. Handler; P. Danielle Shannon; Louis R. Iverson; Stephen N. Matthews; Anantha Prasad; Matthew P. Peters

    2014-01-01

    There is an ever-growing body of literature on forest management strategies for climate change adaptation; however, few frameworks have been presented for integrating these strategies with the real-world challenges of forest management. We have developed a structured approach for translating broad adaptation concepts into specific management actions and silvicultural...

  20. Pol II promoter prediction using characteristic 4-mer motifs: a machine learning approach

    Directory of Open Access Journals (Sweden)

    Shoyaib Mohammad

    2008-10-01

    Full Text Available Abstract Background Eukaryotic promoter prediction using computational analysis techniques is one of the most difficult jobs in computational genomics that is essential for constructing and understanding genetic regulatory networks. The increased availability of sequence data for various eukaryotic organisms in recent years has necessitated for better tools and techniques for the prediction and analysis of promoters in eukaryotic sequences. Many promoter prediction methods and tools have been developed to date but they have yet to provide acceptable predictive performance. One obvious criteria to improve on current methods is to devise a better system for selecting appropriate features of promoters that distinguish them from non-promoters. Secondly improved performance can be achieved by enhancing the predictive ability of the machine learning algorithms used. Results In this paper, a novel approach is presented in which 128 4-mer motifs in conjunction with a non-linear machine-learning algorithm utilising a Support Vector Machine (SVM are used to distinguish between promoter and non-promoter DNA sequences. By applying this approach to plant, Drosophila, human, mouse and rat sequences, the classification model has showed 7-fold cross-validation percentage accuracies of 83.81%, 94.82%, 91.25%, 90.77% and 82.35% respectively. The high sensitivity and specificity value of 0.86 and 0.90 for plant; 0.96 and 0.92 for Drosophila; 0.88 and 0.92 for human; 0.78 and 0.84 for mouse and 0.82 and 0.80 for rat demonstrate that this technique is less prone to false positive results and exhibits better performance than many other tools. Moreover, this model successfully identifies location of promoter using TATA weight matrix. Conclusion The high sensitivity and specificity indicate that 4-mer frequencies in conjunction with supervised machine-learning methods can be beneficial in the identification of RNA pol II promoters comparative to other methods. This

  1. Identifying Green Infrastructure from Social Media and Crowdsourcing- An Image Based Machine-Learning Approach.

    Science.gov (United States)

    Rai, A.; Minsker, B. S.

    2016-12-01

    In this work we introduce a novel dataset GRID: GReen Infrastructure Detection Dataset and a framework for identifying urban green storm water infrastructure (GI) designs (wetlands/ponds, urban trees, and rain gardens/bioswales) from social media and satellite aerial images using computer vision and machine learning methods. Along with the hydrologic benefits of GI, such as reducing runoff volumes and urban heat islands, GI also provides important socio-economic benefits such as stress recovery and community cohesion. However, GI is installed by many different parties and cities typically do not know where GI is located, making study of its impacts or siting new GI difficult. We use object recognition learning methods (template matching, sliding window approach, and Random Hough Forest method) and supervised machine learning algorithms (e.g., support vector machines) as initial screening approaches to detect potential GI sites, which can then be investigated in more detail using on-site surveys. Training data were collected from GPS locations of Flickr and Instagram image postings and Amazon Mechanical Turk identification of each GI type. Sliding window method outperformed other methods and achieved an average F measure, which is combined metric for precision and recall performance measure of 0.78.

  2. Machine learning approaches for the prediction of signal peptides and otherprotein sorting signals

    DEFF Research Database (Denmark)

    Nielsen, Henrik; Brunak, Søren; von Heijne, Gunnar

    1999-01-01

    Prediction of protein sorting signals from the sequence of amino acids has great importance in the field of proteomics today. Recently,the growth of protein databases, combined with machine learning approaches, such as neural networks and hidden Markov models, havemade it possible to achieve...

  3. Machine Learning

    Energy Technology Data Exchange (ETDEWEB)

    Chikkagoudar, Satish; Chatterjee, Samrat; Thomas, Dennis G.; Carroll, Thomas E.; Muller, George

    2017-04-21

    The absence of a robust and unified theory of cyber dynamics presents challenges and opportunities for using machine learning based data-driven approaches to further the understanding of the behavior of such complex systems. Analysts can also use machine learning approaches to gain operational insights. In order to be operationally beneficial, cybersecurity machine learning based models need to have the ability to: (1) represent a real-world system, (2) infer system properties, and (3) learn and adapt based on expert knowledge and observations. Probabilistic models and Probabilistic graphical models provide these necessary properties and are further explored in this chapter. Bayesian Networks and Hidden Markov Models are introduced as an example of a widely used data driven classification/modeling strategy.

  4. Prediction of outcome in internet-delivered cognitive behaviour therapy for paediatric obsessive-compulsive disorder: A machine learning approach.

    Science.gov (United States)

    Lenhard, Fabian; Sauer, Sebastian; Andersson, Erik; Månsson, Kristoffer Nt; Mataix-Cols, David; Rück, Christian; Serlachius, Eva

    2018-03-01

    There are no consistent predictors of treatment outcome in paediatric obsessive-compulsive disorder (OCD). One reason for this might be the use of suboptimal statistical methodology. Machine learning is an approach to efficiently analyse complex data. Machine learning has been widely used within other fields, but has rarely been tested in the prediction of paediatric mental health treatment outcomes. To test four different machine learning methods in the prediction of treatment response in a sample of paediatric OCD patients who had received Internet-delivered cognitive behaviour therapy (ICBT). Participants were 61 adolescents (12-17 years) who enrolled in a randomized controlled trial and received ICBT. All clinical baseline variables were used to predict strictly defined treatment response status three months after ICBT. Four machine learning algorithms were implemented. For comparison, we also employed a traditional logistic regression approach. Multivariate logistic regression could not detect any significant predictors. In contrast, all four machine learning algorithms performed well in the prediction of treatment response, with 75 to 83% accuracy. The results suggest that machine learning algorithms can successfully be applied to predict paediatric OCD treatment outcome. Validation studies and studies in other disorders are warranted. Copyright © 2017 John Wiley & Sons, Ltd.

  5. A Cooperative Approach to Virtual Machine Based Fault Injection

    Energy Technology Data Exchange (ETDEWEB)

    Naughton III, Thomas J [ORNL; Engelmann, Christian [ORNL; Vallee, Geoffroy R [ORNL; Aderholdt, William Ferrol [ORNL; Scott, Stephen L [Tennessee Technological University (TTU)

    2017-01-01

    Resilience investigations often employ fault injection (FI) tools to study the effects of simulated errors on a target system. It is important to keep the target system under test (SUT) isolated from the controlling environment in order to maintain control of the experiement. Virtual machines (VMs) have been used to aid these investigations due to the strong isolation properties of system-level virtualization. A key challenge in fault injection tools is to gain proper insight and context about the SUT. In VM-based FI tools, this challenge of target con- text is increased due to the separation between host and guest (VM). We discuss an approach to VM-based FI that leverages virtual machine introspection (VMI) methods to gain insight into the target s context running within the VM. The key to this environment is the ability to provide basic information to the FI system that can be used to create a map of the target environment. We describe a proof- of-concept implementation and a demonstration of its use to introduce simulated soft errors into an iterative solver benchmark running in user-space of a guest VM.

  6. Sound Effects in Translation

    DEFF Research Database (Denmark)

    Mees, Inger M.; Dragsted, Barbara; Gorm Hansen, Inge

    2013-01-01

    On the basis of a pilot study using speech recognition (SR) software, this paper attempts to illustrate the benefits of adopting an interdisciplinary approach in translator training. It shows how the collaboration between phoneticians, translators and interpreters can (1) advance research, (2) have......), Translog was employed to measure task times. The quality of the products was assessed by three experienced translators, and the number and types of misrecognitions were identified by a phonetician. Results indicate that SR translation provides a potentially useful supplement to written translation...

  7. Translating Alcohol Research

    Science.gov (United States)

    Batman, Angela M.; Miles, Michael F.

    2015-01-01

    Alcohol use disorder (AUD) and its sequelae impose a major burden on the public health of the United States, and adequate long-term control of this disorder has not been achieved. Molecular and behavioral basic science research findings are providing the groundwork for understanding the mechanisms underlying AUD and have identified multiple candidate targets for ongoing clinical trials. However, the translation of basic research or clinical findings into improved therapeutic approaches for AUD must become more efficient. Translational research is a multistage process of streamlining the movement of basic biomedical research findings into clinical research and then to the clinical target populations. This process demands efficient bidirectional communication across basic, applied, and clinical science as well as with clinical practitioners. Ongoing work suggests rapid progress is being made with an evolving translational framework within the alcohol research field. This is helped by multiple interdisciplinary collaborative research structures that have been developed to advance translational work on AUD. Moreover, the integration of systems biology approaches with collaborative clinical studies may yield novel insights for future translational success. Finally, appreciation of genetic variation in pharmacological or behavioral treatment responses and optimal communication from bench to bedside and back may strengthen the success of translational research applications to AUD. PMID:26259085

  8. Synthesizing Marketing, Community Engagement, and Systems Science Approaches for Advancing Translational Research.

    Science.gov (United States)

    Kneipp, Shawn M; Leeman, Jennifer; McCall, Pamela; Hassmiller-Lich, Kristen; Bobashev, Georgiy; Schwartz, Todd A; Gilmore, Robert; Riggan, Scott; Gil, Benjamin

    2015-01-01

    The adoption and implementation of evidence-based interventions (EBIs) are the goals of translational research; however, potential end-users' perceptions of an EBI value have contributed to low rates of adoption. In this article, we describe our application of emerging dissemination and implementation science theoretical perspectives, community engagement, and systems science principles to develop a novel EBI dissemination approach. Using consumer-driven, graphics-rich simulation, the approach demonstrates predicted implementation effects on health and employment outcomes for socioeconomically disadvantaged women at the local level and is designed to increase adoption interest of county program managers accountable for improving these outcomes in their communities.

  9. Translation in ESL Classes

    Directory of Open Access Journals (Sweden)

    Nagy Imola Katalin

    2015-12-01

    Full Text Available The problem of translation in foreign language classes cannot be dealt with unless we attempt to make an overview of what translation meant for language teaching in different periods of language pedagogy. From the translation-oriented grammar-translation method through the complete ban on translation and mother tongue during the times of the audio-lingual approaches, we have come today to reconsider the role and status of translation in ESL classes. This article attempts to advocate for translation as a useful ESL class activity, which can completely fulfil the requirements of communicativeness. We also attempt to identify some activities and games, which rely on translation in some books published in the 1990s and the 2000s.

  10. Machine Learning Approaches for Detecting Diabetic Retinopathy from Clinical and Public Health Records.

    Science.gov (United States)

    Ogunyemi, Omolola; Kermah, Dulcie

    2015-01-01

    Annual eye examinations are recommended for diabetic patients in order to detect diabetic retinopathy and other eye conditions that arise from diabetes. Medically underserved urban communities in the US have annual screening rates that are much lower than the national average and could benefit from informatics approaches to identify unscreened patients most at risk of developing retinopathy. Using clinical data from urban safety net clinics as well as public health data from the CDC's National Health and Nutrition Examination Survey, we examined different machine learning approaches for predicting retinopathy from clinical or public health data. All datasets utilized exhibited a class imbalance. Classifiers learned on the clinical data were modestly predictive of retinopathy with the best model having an AUC of 0.72, sensitivity of 69.2% and specificity of 55.9%. Classifiers learned on public health data were not predictive of retinopathy. Successful approaches to detecting latent retinopathy using machine learning could help safety net and other clinics identify unscreened patients who are most at risk of developing retinopathy and the use of ensemble classifiers on clinical data shows promise for this purpose.

  11. Machine Learning Approaches to Increasing Value of Spaceflight Omics Databases

    Science.gov (United States)

    Gentry, Diana

    2017-01-01

    The number of spaceflight bioscience mission opportunities is too small to allow all relevant biological and environmental parameters to be experimentally identified. Simulated spaceflight experiments in ground-based facilities (GBFs), such as clinostats, are each suitable only for particular investigations -- a rotating-wall vessel may be 'simulated microgravity' for cell differentiation (hours), but not DNA repair (seconds) -- and introduce confounding stimuli, such as motor vibration and fluid shear effects. This uncertainty over which biological mechanisms respond to a given form of simulated space radiation or gravity, as well as its side effects, limits our ability to baseline spaceflight data and validate mission science. Machine learning techniques autonomously identify relevant and interdependent factors in a data set given the set of desired metrics to be evaluated: to automatically identify related studies, compare data from related studies, or determine linkages between types of data in the same study. System-of-systems (SoS) machine learning models have the ability to deal with both sparse and heterogeneous data, such as that provided by the small and diverse number of space biosciences flight missions; however, they require appropriate user-defined metrics for any given data set. Although machine learning in bioinformatics is rapidly expanding, the need to combine spaceflight/GBF mission parameters with omics data is unique. This work characterizes the basic requirements for implementing the SoS approach through the System Map (SM) technique, a composite of a dynamic Bayesian network and Gaussian mixture model, in real-world repositories such as the GeneLab Data System and Life Sciences Data Archive. The three primary steps are metadata management for experimental description using open-source ontologies, defining similarity and consistency metrics, and generating testing and validation data sets. Such approaches to spaceflight and GBF omics data may

  12. Prediction of skin sensitization potency using machine learning approaches.

    Science.gov (United States)

    Zang, Qingda; Paris, Michael; Lehmann, David M; Bell, Shannon; Kleinstreuer, Nicole; Allen, David; Matheson, Joanna; Jacobs, Abigail; Casey, Warren; Strickland, Judy

    2017-07-01

    The replacement of animal use in testing for regulatory classification of skin sensitizers is a priority for US federal agencies that use data from such testing. Machine learning models that classify substances as sensitizers or non-sensitizers without using animal data have been developed and evaluated. Because some regulatory agencies require that sensitizers be further classified into potency categories, we developed statistical models to predict skin sensitization potency for murine local lymph node assay (LLNA) and human outcomes. Input variables for our models included six physicochemical properties and data from three non-animal test methods: direct peptide reactivity assay; human cell line activation test; and KeratinoSens™ assay. Models were built to predict three potency categories using four machine learning approaches and were validated using external test sets and leave-one-out cross-validation. A one-tiered strategy modeled all three categories of response together while a two-tiered strategy modeled sensitizer/non-sensitizer responses and then classified the sensitizers as strong or weak sensitizers. The two-tiered model using the support vector machine with all assay and physicochemical data inputs provided the best performance, yielding accuracy of 88% for prediction of LLNA outcomes (120 substances) and 81% for prediction of human test outcomes (87 substances). The best one-tiered model predicted LLNA outcomes with 78% accuracy and human outcomes with 75% accuracy. By comparison, the LLNA predicts human potency categories with 69% accuracy (60 of 87 substances correctly categorized). These results suggest that computational models using non-animal methods may provide valuable information for assessing skin sensitization potency. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  13. Probability Machines: Consistent Probability Estimation Using Nonparametric Learning Machines

    Science.gov (United States)

    Malley, J. D.; Kruppa, J.; Dasgupta, A.; Malley, K. G.; Ziegler, A.

    2011-01-01

    Summary Background Most machine learning approaches only provide a classification for binary responses. However, probabilities are required for risk estimation using individual patient characteristics. It has been shown recently that every statistical learning machine known to be consistent for a nonparametric regression problem is a probability machine that is provably consistent for this estimation problem. Objectives The aim of this paper is to show how random forests and nearest neighbors can be used for consistent estimation of individual probabilities. Methods Two random forest algorithms and two nearest neighbor algorithms are described in detail for estimation of individual probabilities. We discuss the consistency of random forests, nearest neighbors and other learning machines in detail. We conduct a simulation study to illustrate the validity of the methods. We exemplify the algorithms by analyzing two well-known data sets on the diagnosis of appendicitis and the diagnosis of diabetes in Pima Indians. Results Simulations demonstrate the validity of the method. With the real data application, we show the accuracy and practicality of this approach. We provide sample code from R packages in which the probability estimation is already available. This means that all calculations can be performed using existing software. Conclusions Random forest algorithms as well as nearest neighbor approaches are valid machine learning methods for estimating individual probabilities for binary responses. Freely available implementations are available in R and may be used for applications. PMID:21915433

  14. Percussive drilling application of translational motion permanent magnet machine

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Shujun

    2012-07-01

    It is clear that percussive drills are very promising since they can increase the rate of penetration in hard rock formations. Any small improvements on the percussive drills can make a big contribution to lowering the drilling costs since drilling a well for the oil and gas industry is very costly. This thesis presents a percussive drilling system mainly driven by a tubular reciprocating translational motion permanent magnet synchronous motor (RTPMSM), which efficiently converts electric energy to kinetic energy for crushing the hard rock since there is no mechanical media. The thesis starts from state-of-the-art of percussive drilling techniques, reciprocating translational motion motors, and self-sensing control of electric motors and its implementation issues. The following chapters present modeling the hard rock, modeling the drill, the design issues of the drill, the RTPMSM and its control. A single-phase RTPMSM prototype is tested for the hard rock drilling. The presented variable voltage variable frequency control is also validated on it. The space vector control and self-sensing control are also explored on a three-phase RTPMSM prototype. The results show that the percussive drill can be implemented to the hard rock drilling applications. A detailed summarisation of contributions and future work is presented at the end of the thesis.(Author)

  15. The Translation and the Translator of the Peshitta of Hosea

    Science.gov (United States)

    Tully, Eric J.

    2012-01-01

    This comprehensive examination of the Syriac Peshitta of Hosea (P-Hosea) is the first study of the Peshitta conducted via insights and methods from the discipline of Translation Studies. It uses in particular Andrew Chesterman's Causal Model and Gideon Toury's descriptive approach. Every translator leaves residue of his or her…

  16. A cloud-based data network approach for translational cancer research.

    Science.gov (United States)

    Xing, Wei; Tsoumakos, Dimitrios; Ghanem, Moustafa

    2015-01-01

    We develop a new model and associated technology for constructing and managing self-organizing data to support translational cancer research studies. We employ a semantic content network approach to address the challenges of managing cancer research data. Such data is heterogeneous, large, decentralized, growing and continually being updated. Moreover, the data originates from different information sources that may be partially overlapping, creating redundancies as well as contradictions and inconsistencies. Building on the advantages of elasticity of cloud computing, we deploy the cancer data networks on top of the CELAR Cloud platform to enable more effective processing and analysis of Big cancer data.

  17. Machine-roomless elevator, SPACEL{sub TM}; Machine roomless elevator SPACEL{sub TM} `Supesuseru{sub TM}`

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1999-03-01

    A machine-roomless elevator, SPACEL{sub TM} requiring no machine room, which operates at a rated speed of 45 and 60 m/min, was put on sale in August 1998 with arrangement for passenger use, residential use and bed use. Another elevator operating at a rated speed of 90 and 105 m/min whose travel distance was extended to 75 m was added to the product series and put on sale in February 1999. The control equipment having been installed in a machine room conventionally was modified to a thickness of 100 mm by adopting an inverter device of thin design and densely mounted substrates. The control equipment was installed on the uppermost floor. The winch is a compact and thin type gearless winch incorporating a permanent magnet synchronizing motor, which was installed at the top of the hoistway. These arrangements have realized a machine-roomless elevator. Further system efficiency improvement has achieved energy conservation of about 10% as compared to the conventional rope type and about 80% as compared to the hydraulic type elevators. (translated by NEDO)

  18. Role of Shwachman-Bodian-Diamond syndrome protein in translation machinery and cell chemotaxis: a comparative genomics approach

    Directory of Open Access Journals (Sweden)

    Vasieva O

    2011-09-01

    Full Text Available Olga VasievaInstitute of Integrative Biology, University of Liverpool, Liverpool, United Kingdom; Fellowship for the Interpretation of Genomes, Burr Ridge, IL, USAAbstract: Shwachman-Bodian-Diamond syndrome (SBDS is linked to a mutation in a single gene. The SBDS proinvolved in RNA metabolism and ribosome-associated functions, but SBDS mutation is primarily linked to a defect in polymorphonuclear leukocytes unable to orient correctly in a spatial gradient of chemoattractants. Results of data mining and comparative genomic approaches undertaken in this study suggest that SBDS protein is also linked to tRNA metabolism and translation initiation. Analysis of crosstalk between translation machinery and cytoskeletal dynamics provides new insights into the cellular chemotactic defects caused by SBDS protein malfunction. The proposed functional interactions provide a new approach to exploit potential targets in the treatment and monitoring of this disease.Keywords: Shwachman-Bodian-Diamond syndrome, wybutosine, tRNA, chemotaxis, translation, genomics, gene proximity

  19. Mechatronic sensor system for robots and automated machines

    CSIR Research Space (South Africa)

    Shaik, AA

    2007-01-01

    Full Text Available machine makes a calculated estimate of where the tool-head should be. This is often achieved by monitoring sensors on axes that track linear translation and rotations of shafts or gears. For low precision applications this system is appropriate. However...

  20. Thin type inverter for machine-room-less elevator; Machine roomless elevator yo usugata inverter

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2000-01-10

    In the elevator industry, a machine-room-less elevator, which does not necessitate a machine room usually installed on the roof, has come into the spotlight in the domain of low and intermediate speed elevators. The lack of a machine room, however, will necessarily limit the space for the installation of the traction motor and control panel. Fuji Electric Co., Ltd., in order to properly cope with the situation, has developed in cooperation with Fujitec Co., Ltd., a very thin type inverter installable on an elevator hall floor. The inverter, based on Fuji Electric's high-performance vector control inverter FRENIC5000VG5, is as thin as 100mm, and is available in three series up to 11kW. For the embodiment of such a thin structure, a cooling structure of Fuji Electric's own is employed, and prudence is exercised as required at many locations so that maintainability will not be impaired throughout the very thin control panel design. (translated by NEDO)

  1. Evaluation of Machine Learning and Rules-Based Approaches for Predicting Antimicrobial Resistance Profiles in Gram-negative Bacilli from Whole Genome Sequence Data.

    Science.gov (United States)

    Pesesky, Mitchell W; Hussain, Tahir; Wallace, Meghan; Patel, Sanket; Andleeb, Saadia; Burnham, Carey-Ann D; Dantas, Gautam

    2016-01-01

    The time-to-result for culture-based microorganism recovery and phenotypic antimicrobial susceptibility testing necessitates initial use of empiric (frequently broad-spectrum) antimicrobial therapy. If the empiric therapy is not optimal, this can lead to adverse patient outcomes and contribute to increasing antibiotic resistance in pathogens. New, more rapid technologies are emerging to meet this need. Many of these are based on identifying resistance genes, rather than directly assaying resistance phenotypes, and thus require interpretation to translate the genotype into treatment recommendations. These interpretations, like other parts of clinical diagnostic workflows, are likely to be increasingly automated in the future. We set out to evaluate the two major approaches that could be amenable to automation pipelines: rules-based methods and machine learning methods. The rules-based algorithm makes predictions based upon current, curated knowledge of Enterobacteriaceae resistance genes. The machine-learning algorithm predicts resistance and susceptibility based on a model built from a training set of variably resistant isolates. As our test set, we used whole genome sequence data from 78 clinical Enterobacteriaceae isolates, previously identified to represent a variety of phenotypes, from fully-susceptible to pan-resistant strains for the antibiotics tested. We tested three antibiotic resistance determinant databases for their utility in identifying the complete resistome for each isolate. The predictions of the rules-based and machine learning algorithms for these isolates were compared to results of phenotype-based diagnostics. The rules based and machine-learning predictions achieved agreement with standard-of-care phenotypic diagnostics of 89.0 and 90.3%, respectively, across twelve antibiotic agents from six major antibiotic classes. Several sources of disagreement between the algorithms were identified. Novel variants of known resistance factors and

  2. Evaluation of Machine Learning and Rules-Based Approaches for Predicting Antimicrobial Resistance Profiles in Gram-negative Bacilli from Whole Genome Sequence Data

    Directory of Open Access Journals (Sweden)

    Mitchell Pesesky

    2016-11-01

    Full Text Available The time-to-result for culture-based microorganism recovery and phenotypic antimicrobial susceptibility testing necessitate initial use of empiric (frequently broad-spectrum antimicrobial therapy. If the empiric therapy is not optimal, this can lead to adverse patient outcomes and contribute to increasing antibiotic resistance in pathogens. New, more rapid technologies are emerging to meet this need. Many of these are based on identifying resistance genes, rather than directly assaying resistance phenotypes, and thus require interpretation to translate the genotype into treatment recommendations. These interpretations, like other parts of clinical diagnostic workflows, are likely to be increasingly automated in the future. We set out to evaluate the two major approaches that could be amenable to automation pipelines: rules-based methods and machine learning methods. The rules-based algorithm makes predictions based upon current, curated knowledge of Enterobacteriaceae resistance genes. The machine-learning algorithm predicts resistance and susceptibility based on a model built from a training set of variably resistant isolates. As our test set, we used whole genome sequence data from 78 clinical Enterobacteriaceae isolates, previously identified to represent a variety of phenotypes, from fully-susceptible to pan-resistant strains for the antibiotics tested. We tested three antibiotic resistance determinant databases for their utility in identifying the complete resistome for each isolate. The predictions of the rules-based and machine learning algorithms for these isolates were compared to results of phenotype-based diagnostics. The rules based and machine-learning predictions achieved agreement with standard-of-care phenotypic diagnostics of 89.0% and 90.3%, respectively, across twelve antibiotic agents from six major antibiotic classes. Several sources of disagreement between the algorithms were identified. Novel variants of known resistance

  3. Assembly processor program converts symbolic programming language to machine language

    Science.gov (United States)

    Pelto, E. V.

    1967-01-01

    Assembly processor program converts symbolic programming language to machine language. This program translates symbolic codes into computer understandable instructions, assigns locations in storage for successive instructions, and computer locations from symbolic addresses.

  4. A support vector machine approach for detection of microcalcifications.

    Science.gov (United States)

    El-Naqa, Issam; Yang, Yongyi; Wernick, Miles N; Galatsanos, Nikolas P; Nishikawa, Robert M

    2002-12-01

    In this paper, we investigate an approach based on support vector machines (SVMs) for detection of microcalcification (MC) clusters in digital mammograms, and propose a successive enhancement learning scheme for improved performance. SVM is a machine-learning method, based on the principle of structural risk minimization, which performs well when applied to data outside the training set. We formulate MC detection as a supervised-learning problem and apply SVM to develop the detection algorithm. We use the SVM to detect at each location in the image whether an MC is present or not. We tested the proposed method using a database of 76 clinical mammograms containing 1120 MCs. We use free-response receiver operating characteristic curves to evaluate detection performance, and compare the proposed algorithm with several existing methods. In our experiments, the proposed SVM framework outperformed all the other methods tested. In particular, a sensitivity as high as 94% was achieved by the SVM method at an error rate of one false-positive cluster per image. The ability of SVM to out perform several well-known methods developed for the widely studied problem of MC detection suggests that SVM is a promising technique for object detection in a medical imaging application.

  5. Bombsights and Adding Machines: Translating Wartime Technology into Peacetime Sales

    Science.gov (United States)

    Tremblay, Michael

    2010-01-01

    On 10 February 1947, A.C. Buehler, the president of the Victor Adding Machine Company presented Norden Bombsight #4120 to the Smithsonian Institute. This sight was in service on board the Enola Gay when it dropped the first atomic bomb on Hiroshima. Through this public presentation, Buehler forever linked his company to the Norden Bombsight, the…

  6. Machine medical ethics

    CERN Document Server

    Pontier, Matthijs

    2015-01-01

    The essays in this book, written by researchers from both humanities and sciences, describe various theoretical and experimental approaches to adding medical ethics to a machine in medical settings. Medical machines are in close proximity with human beings, and getting closer: with patients who are in vulnerable states of health, who have disabilities of various kinds, with the very young or very old, and with medical professionals. In such contexts, machines are undertaking important medical tasks that require emotional sensitivity, knowledge of medical codes, human dignity, and privacy. As machine technology advances, ethical concerns become more urgent: should medical machines be programmed to follow a code of medical ethics? What theory or theories should constrain medical machine conduct? What design features are required? Should machines share responsibility with humans for the ethical consequences of medical actions? How ought clinical relationships involving machines to be modeled? Is a capacity for e...

  7. Big Data Meets Quantum Chemistry Approximations: The Δ-Machine Learning Approach.

    Science.gov (United States)

    Ramakrishnan, Raghunathan; Dral, Pavlo O; Rupp, Matthias; von Lilienfeld, O Anatole

    2015-05-12

    Chemically accurate and comprehensive studies of the virtual space of all possible molecules are severely limited by the computational cost of quantum chemistry. We introduce a composite strategy that adds machine learning corrections to computationally inexpensive approximate legacy quantum methods. After training, highly accurate predictions of enthalpies, free energies, entropies, and electron correlation energies are possible, for significantly larger molecular sets than used for training. For thermochemical properties of up to 16k isomers of C7H10O2 we present numerical evidence that chemical accuracy can be reached. We also predict electron correlation energy in post Hartree-Fock methods, at the computational cost of Hartree-Fock, and we establish a qualitative relationship between molecular entropy and electron correlation. The transferability of our approach is demonstrated, using semiempirical quantum chemistry and machine learning models trained on 1 and 10% of 134k organic molecules, to reproduce enthalpies of all remaining molecules at density functional theory level of accuracy.

  8. Rotating electrical machines

    CERN Document Server

    Le Doeuff, René

    2013-01-01

    In this book a general matrix-based approach to modeling electrical machines is promulgated. The model uses instantaneous quantities for key variables and enables the user to easily take into account associations between rotating machines and static converters (such as in variable speed drives).   General equations of electromechanical energy conversion are established early in the treatment of the topic and then applied to synchronous, induction and DC machines. The primary characteristics of these machines are established for steady state behavior as well as for variable speed scenarios. I

  9. PRISMA database machine: A distributed, main-memory approach

    NARCIS (Netherlands)

    Schmidt, J.W.; Apers, Peter M.G.; Ceri, S.; Kersten, Martin L.; Oerlemans, Hans C.M.; Missikoff, M.

    1988-01-01

    The PRISMA project is a large-scale research effort in the design and implementation of a highly parallel machine for data and knowledge processing. The PRISMA database machine is a distributed, main-memory database management system implemented in an object-oriented language that runs on top of a

  10. Incorporating translation into sociolinguistic research: translation policy in an international non-governmental organisation

    OpenAIRE

    Tesseur, Wine

    2017-01-01

    This article explores aspects of translation, multilingualism and language policy in the field of transnational civil society. By focusing on translation policies at Amnesty International, an international non-governmental organisation that performs a key role in global governance, this article seeks to contribute to a globalisation-sensitive sociolinguistics. It argues that combining a sociolinguistic approach, more precisely linguistic ethnography, with translation studies leads to an incre...

  11. From scientific instrument to industrial machine coping with architectural stress in embedded systems

    CERN Document Server

    Doornbos, Richard

    2012-01-01

    Architectural stress is the inability of a system design to respond to new market demands. It is an important yet often concealed issue in high tech systems. In From scientific instrument to industrial machine, we look at the phenomenon of architectural stress in embedded systems in the context of a transmission electron microscope system built by FEI Company. Traditionally, transmission electron microscopes are manually operated scientific instruments, but they also have enormous potential for use in industrial applications. However, this new market has quite different characteristics. There are strong demands for cost-effective analysis, accurate and precise measurements, and ease-of-use. These demands can be translated into new system qualities, e.g. reliability, predictability and high throughput, as well as new functions, e.g. automation of electron microscopic analyses, automated focusing and positioning functions. From scientific instrument to industrial machine takes a pragmatic approach to the proble...

  12. Ex-vivo machine perfusion for kidney preservation.

    Science.gov (United States)

    Hamar, Matyas; Selzner, Markus

    2018-06-01

    Machine perfusion is a novel strategy to decrease preservation injury, improve graft assessment, and increase organ acceptance for transplantation. This review summarizes the current advances in ex-vivo machine-based kidney preservation technologies over the last year. Ex-vivo perfusion technologies, such as hypothermic and normothermic machine perfusion and controlled oxygenated rewarming, have gained high interest in the field of organ preservation. Keeping kidney grafts functionally and metabolically active during the preservation period offers a unique chance for viability assessment, reconditioning, and organ repair. Normothermic ex-vivo kidney perfusion has been recently translated into clinical practice. Preclinical results suggest that prolonged warm perfusion appears superior than a brief end-ischemic reconditioning in terms of renal function and injury. An established standardized protocol for continuous warm perfusion is still not available for human grafts. Ex-vivo machine perfusion represents a superior organ preservation method over static cold storage. There is still an urgent need for the optimization of the perfusion fluid and machine technology and to identify the optimal indication in kidney transplantation. Recent research is focusing on graft assessment and therapeutic strategies.

  13. Alternative strategy for steady growth towards high quality translation networks

    Energy Technology Data Exchange (ETDEWEB)

    Witkam, A P.M.

    1983-01-01

    This paper points out a rather new and largely unexplored direction. In machine translation (MT), but also in data-base enquiry, advanced word processing and natural language programming systems, the analysis of the source text is the crucial process, responsible for parsing and disambiguation. For this purpose, conventional MT systems initially relied on only grammar and dictionary, the grammar being limited to morphology and syntax. The author points to artificial intelligence as an alternative strategy, leading to knowledge based translation. 12 references.

  14. A new approach for translating strategic healthcare objectives into operational indicators

    DEFF Research Database (Denmark)

    Traberg, Andreas; Jacobsen, Peter

    2009-01-01

    The purpose of this paper is to propose a new performance measurement approach which enables healthcare managers to design a performance management system tailored for their individual settings. The model is based on the strategic goal of the individual health care facility. It has been developed...... level, a detailed and well-defined performance measurement structure is connected to the overall strategic plan The increasing complexity in modern healthcare requires new improved performance management systems for healthcare institutions (Landrum & Baker 2004). The process of translating strategic......). To be able to coordinate and manage these different requirements, a performance management system, encompassing performance indicators from all the three stakeholder groups is needed. Our approach was derived using the action research methodology (Coughlan & Coghlan 2002). The work is based on a two year...

  15. Making and Operating Molecular Machines: A Multidisciplinary Challenge.

    Science.gov (United States)

    Baroncini, Massimo; Casimiro, Lorenzo; de Vet, Christiaan; Groppi, Jessica; Silvi, Serena; Credi, Alberto

    2018-02-01

    Movement is one of the central attributes of life, and a key feature in many technological processes. While artificial motion is typically provided by macroscopic engines powered by internal combustion or electrical energy, movement in living organisms is produced by machines and motors of molecular size that typically exploit the energy of chemical fuels at ambient temperature to generate forces and ultimately execute functions. The progress in several areas of chemistry, together with an improved understanding of biomolecular machines, has led to the development of a large variety of wholly synthetic molecular machines. These systems have the potential to bring about radical innovations in several areas of technology and medicine. In this Minireview, we discuss, with the help of a few examples, the multidisciplinary aspects of research on artificial molecular machines and highlight its translational character.

  16. Support vector machine based fault detection approach for RFT-30 cyclotron

    Energy Technology Data Exchange (ETDEWEB)

    Kong, Young Bae, E-mail: ybkong@kaeri.re.kr; Lee, Eun Je; Hur, Min Goo; Park, Jeong Hoon; Park, Yong Dae; Yang, Seung Dae

    2016-10-21

    An RFT-30 is a 30 MeV cyclotron used for radioisotope applications and radiopharmaceutical researches. The RFT-30 cyclotron is highly complex and includes many signals for control and monitoring of the system. It is quite difficult to detect and monitor the system failure in real time. Moreover, continuous monitoring of the system is hard and time-consuming work for human operators. In this paper, we propose a support vector machine (SVM) based fault detection approach for the RFT-30 cyclotron. The proposed approach performs SVM learning with training samples to construct the classification model. To compensate the system complexity due to the large-scale accelerator, we utilize the principal component analysis (PCA) for transformation of the original data. After training procedure, the proposed approach detects the system faults in real time. We analyzed the performance of the proposed approach utilizing the experimental data of the RFT-30 cyclotron. The performance results show that the proposed SVM approach can provide an efficient way to control the cyclotron system.

  17. Translation and Creation

    Directory of Open Access Journals (Sweden)

    Paulo Bezerra

    2012-12-01

    Full Text Available The article begins with the differences betweenscientific and fictional translations, and focus on the second.The fictional translation works with meanings, opens itselfto the plurissignification in the purpose to create a similarity of the dissimilarity; in this process, the translator does nottranslate a language, but what a creative individuality makeswith a language. At last there is an approach to the knowledgeand skills necessaries to a translator of literature: theknowledge of the theories of the literature and of thetranslation, the capacity to preserve the national color ofthe original text and at the same time to respect the arrivallanguage, and the sensibility to his national languagevariations present in the daily and in the literary spheres.

  18. An artificial molecular machine that builds an asymmetric catalyst

    Science.gov (United States)

    De Bo, Guillaume; Gall, Malcolm A. Y.; Kuschel, Sonja; De Winter, Julien; Gerbaux, Pascal; Leigh, David A.

    2018-05-01

    Biomolecular machines perform types of complex molecular-level tasks that artificial molecular machines can aspire to. The ribosome, for example, translates information from the polymer track it traverses (messenger RNA) to the new polymer it constructs (a polypeptide)1. The sequence and number of codons read determines the sequence and number of building blocks incorporated into the biomachine-synthesized polymer. However, neither control of sequence2,3 nor the transfer of length information from one polymer to another (which to date has only been accomplished in man-made systems through template synthesis)4 is easily achieved in the synthesis of artificial macromolecules. Rotaxane-based molecular machines5-7 have been developed that successively add amino acids8-10 (including β-amino acids10) to a growing peptide chain by the action of a macrocycle moving along a mono-dispersed oligomeric track derivatized with amino-acid phenol esters. The threaded macrocycle picks up groups that block its path and links them through successive native chemical ligation reactions11 to form a peptide sequence corresponding to the order of the building blocks on the track. Here, we show that as an alternative to translating sequence information, a rotaxane molecular machine can transfer the narrow polydispersity of a leucine-ester-derivatized polystyrene chain synthesized by atom transfer radical polymerization12 to a molecular-machine-made homo-leucine oligomer. The resulting narrow-molecular-weight oligomer folds to an α-helical secondary structure13 that acts as an asymmetric catalyst for the Juliá-Colonna epoxidation14,15 of chalcones.

  19. Extracting meaning from audio signals - a machine learning approach

    DEFF Research Database (Denmark)

    Larsen, Jan

    2007-01-01

    * Machine learning framework for sound search * Genre classification * Music and audio separation * Wind noise suppression......* Machine learning framework for sound search * Genre classification * Music and audio separation * Wind noise suppression...

  20. Application of machine learning classification for structural brain MRI in mood disorders: Critical review from a clinical perspective.

    Science.gov (United States)

    Kim, Yong-Ku; Na, Kyoung-Sae

    2018-01-03

    Mood disorders are a highly prevalent group of mental disorders causing substantial socioeconomic burden. There are various methodological approaches for identifying the underlying mechanisms of the etiology, symptomatology, and therapeutics of mood disorders; however, neuroimaging studies have provided the most direct evidence for mood disorder neural substrates by visualizing the brains of living individuals. The prefrontal cortex, hippocampus, amygdala, thalamus, ventral striatum, and corpus callosum are associated with depression and bipolar disorder. Identifying the distinct and common contributions of these anatomical regions to depression and bipolar disorder have broadened and deepened our understanding of mood disorders. However, the extent to which neuroimaging research findings contribute to clinical practice in the real-world setting is unclear. As traditional or non-machine learning MRI studies have analyzed group-level differences, it is not possible to directly translate findings from research to clinical practice; the knowledge gained pertains to the disorder, but not to individuals. On the other hand, a machine learning approach makes it possible to provide individual-level classifications. For the past two decades, many studies have reported on the classification accuracy of machine learning-based neuroimaging studies from the perspective of diagnosis and treatment response. However, for the application of a machine learning-based brain MRI approach in real world clinical settings, several major issues should be considered. Secondary changes due to illness duration and medication, clinical subtypes and heterogeneity, comorbidities, and cost-effectiveness restrict the generalization of the current machine learning findings. Sophisticated classification of clinical and diagnostic subtypes is needed. Additionally, as the approach is inevitably limited by sample size, multi-site participation and data-sharing are needed in the future. Copyright

  1. Translation in Light of Bilingual Mental Lexicon: A Psycholinguistic Approach

    Directory of Open Access Journals (Sweden)

    Congmin Zhao

    2018-05-01

    Full Text Available This paper gives insight into the translating process of second language learners in language use in light of the mechanism of bilingual mental lexicon. Structure and development of second language mental lexicon explains the existence of first language items and translation equivalents. Conversely translation can promote the construction of second language mental lexicon and ultimately second language acquisition.

  2. Machine-roomless elevator, SPACEL[sub TM]. Machine roomless elevator SPACEL[sub TM] 'Supesuseru[sub TM]'

    Energy Technology Data Exchange (ETDEWEB)

    1999-03-01

    A machine-roomless elevator, SPACEL[sub TM] requiring no machine room, which operates at a rated speed of 45 and 60 m/min, was put on sale in August 1998 with arrangement for passenger use, residential use and bed use. Another elevator operating at a rated speed of 90 and 105 m/min whose travel distance was extended to 75 m was added to the product series and put on sale in February 1999. The control equipment having been installed in a machine room conventionally was modified to a thickness of 100 mm by adopting an inverter device of thin design and densely mounted substrates. The control equipment was installed on the uppermost floor. The winch is a compact and thin type gearless winch incorporating a permanent magnet synchronizing motor, which was installed at the top of the hoistway. These arrangements have realized a machine-roomless elevator. Further system efficiency improvement has achieved energy conservation of about 10% as compared to the conventional rope type and about 80% as compared to the hydraulic type elevators. (translated by NEDO)

  3. Application of Machine Learning Approaches for Classifying Sitting Posture Based on Force and Acceleration Sensors.

    Science.gov (United States)

    Zemp, Roland; Tanadini, Matteo; Plüss, Stefan; Schnüriger, Karin; Singh, Navrag B; Taylor, William R; Lorenzetti, Silvio

    2016-01-01

    Occupational musculoskeletal disorders, particularly chronic low back pain (LBP), are ubiquitous due to prolonged static sitting or nonergonomic sitting positions. Therefore, the aim of this study was to develop an instrumented chair with force and acceleration sensors to determine the accuracy of automatically identifying the user's sitting position by applying five different machine learning methods (Support Vector Machines, Multinomial Regression, Boosting, Neural Networks, and Random Forest). Forty-one subjects were requested to sit four times in seven different prescribed sitting positions (total 1148 samples). Sixteen force sensor values and the backrest angle were used as the explanatory variables (features) for the classification. The different classification methods were compared by means of a Leave-One-Out cross-validation approach. The best performance was achieved using the Random Forest classification algorithm, producing a mean classification accuracy of 90.9% for subjects with which the algorithm was not familiar. The classification accuracy varied between 81% and 98% for the seven different sitting positions. The present study showed the possibility of accurately classifying different sitting positions by means of the introduced instrumented office chair combined with machine learning analyses. The use of such novel approaches for the accurate assessment of chair usage could offer insights into the relationships between sitting position, sitting behaviour, and the occurrence of musculoskeletal disorders.

  4. The Utilization of Parallel Corpora for the Extension of Machine ...

    African Journals Online (AJOL)

    grammar rules for the identification of the grammatical category of each .... An example of the first type of corpus-based machine translation is a sub- ..... The MINISTER OF AGRICULTURE: Mr Chairman, while prayers were being read this.

  5. Omission and other sins: Tracking the quality of online machine ...

    African Journals Online (AJOL)

    Omission and other sins: Tracking the quality of online machine translation output over four years. ... Journal Home > Vol 46 (2016) > ... We believe users should be made aware of the risks they unknowingly take when using online MT.

  6. Translation as (Global) Writing

    Science.gov (United States)

    Horner, Bruce; Tetreault, Laura

    2016-01-01

    This article explores translation as a useful point of departure and framework for taking a translingual approach to writing engaging globalization. Globalization and the knowledge economy are putting renewed emphasis on translation as a key site of contest between a dominant language ideology of monolingualism aligned with fast capitalist…

  7. Amplification macroscopique de mouvements nanométriques induits par des machines moléculaires

    OpenAIRE

    Goujon , Antoine

    2016-01-01

    The last twenty years have seen tremendous progresses in the design and synthesis of complex molecular machines, often inspired by the beauty of the machinery found in biological systems. However, amplification of the molecular machines motion over several orders of magnitude above their typical length scale is still an ambitious challenge. This work describes how self-organization of molecular machines or motors allows for the synthesis of materials translating the motions of their component...

  8. COMPARISION OF FUZZY PERT APPROACHES IN MACHINE PRODUCTION PROCESS

    Directory of Open Access Journals (Sweden)

    İRFAN ERTUĞRUL

    2013-06-01

    Full Text Available In traditional PERT (Program Evaluation and Review Technique activity durations are represented as crisp numbers and assumed that they are drawn from beta distribution. However, in real life the duration of the activities are usually difficult to estimate precisely.  In order to overcome this difficulty, there are studies in the literature that combine fuzzy set theory and PERT method. In this study, two fuzzy PERT approaches proposed by different authors are employed to find the degrees of criticality of each path in the network and comparison of these two methods is also given. Furthermore, by the help of these methods the criticality of the activities in the marble machine production process of a company that manufactures machinery is determined and results are compared.

  9. Optimization of classification and regression analysis of four monoclonal antibodies from Raman spectra using collaborative machine learning approach.

    Science.gov (United States)

    Le, Laetitia Minh Maï; Kégl, Balázs; Gramfort, Alexandre; Marini, Camille; Nguyen, David; Cherti, Mehdi; Tfaili, Sana; Tfayli, Ali; Baillet-Guffroy, Arlette; Prognon, Patrice; Chaminade, Pierre; Caudron, Eric

    2018-07-01

    The use of monoclonal antibodies (mAbs) constitutes one of the most important strategies to treat patients suffering from cancers such as hematological malignancies and solid tumors. These antibodies are prescribed by the physician and prepared by hospital pharmacists. An analytical control enables the quality of the preparations to be ensured. The aim of this study was to explore the development of a rapid analytical method for quality control. The method used four mAbs (Infliximab, Bevacizumab, Rituximab and Ramucirumab) at various concentrations and was based on recording Raman data and coupling them to a traditional chemometric and machine learning approach for data analysis. Compared to conventional linear approach, prediction errors are reduced with a data-driven approach using statistical machine learning methods. In the latter, preprocessing and predictive models are jointly optimized. An additional original aspect of the work involved on submitting the problem to a collaborative data challenge platform called Rapid Analytics and Model Prototyping (RAMP). This allowed using solutions from about 300 data scientists in collaborative work. Using machine learning, the prediction of the four mAbs samples was considerably improved. The best predictive model showed a combined error of 2.4% versus 14.6% using linear approach. The concentration and classification errors were 5.8% and 0.7%, only three spectra were misclassified over the 429 spectra of the test set. This large improvement obtained with machine learning techniques was uniform for all molecules but maximal for Bevacizumab with an 88.3% reduction on combined errors (2.1% versus 17.9%). Copyright © 2018 Elsevier B.V. All rights reserved.

  10. Sadhana | Indian Academy of Sciences

    Indian Academy of Sciences (India)

    This paper proposes English to Tamil machine translation system, using the universal networking language (UNL) as the intermediate representation. The UNL approach is a hybrid approach of the rule and knowledge-based approaches to machine translation. UNL is a declarative formal language, specifically designed to ...

  11. Idioms and Back Translation

    Science.gov (United States)

    Griffin, Frank

    2004-01-01

    The challenges of intercultural communication are an integral part of many undergraduate business communication courses. Marketing gaffes clearly illustrate the pitfalls of translation and underscore the importance of a knowledge of the culture with which one is attempting to communicate. A good way to approach the topic of translation pitfalls in…

  12. Translation goes to the movies

    CERN Document Server

    Cronin, Michael

    2008-01-01

    This highly accessible introduction to translation theory, written by a leading author in the field, uses the genre of film to bring the main themes in translation to life. Through analyzing films as diverse as the Marx Brothers' A Night at the Opera, The Star Wars Trilogies and Lost in Translation, the reader is encouraged to think about both issues and problems of translation as they are played out on the screen and issues of filmic representation through examining the translation dimension of specific films. In highlighting how translation has featured in both mainstream commercial and arthouse films over the years, Cronin shows how translation has been a concern of filmmakers dealing with questions of culture, identity, conflict and representation. This book is a lively and accessible text for translation theory courses and offers a new and largely unexplored approach to topics of identity and representation on screen. Translation Goes to the Movies will be of interest to those on translation studies...

  13. Space Weather in the Machine Learning Era: A Multidisciplinary Approach

    Science.gov (United States)

    Camporeale, E.; Wing, S.; Johnson, J.; Jackman, C. M.; McGranaghan, R.

    2018-01-01

    The workshop entitled Space Weather: A Multidisciplinary Approach took place at the Lorentz Center, University of Leiden, Netherlands, on 25-29 September 2017. The aim of this workshop was to bring together members of the Space Weather, Mathematics, Statistics, and Computer Science communities to address the use of advanced techniques such as Machine Learning, Information Theory, and Deep Learning, to better understand the Sun-Earth system and to improve space weather forecasting. Although individual efforts have been made toward this goal, the community consensus is that establishing interdisciplinary collaborations is the most promising strategy for fully utilizing the potential of these advanced techniques in solving Space Weather-related problems.

  14. A machine learning approach for the classification of metallic glasses

    Science.gov (United States)

    Gossett, Eric; Perim, Eric; Toher, Cormac; Lee, Dongwoo; Zhang, Haitao; Liu, Jingbei; Zhao, Shaofan; Schroers, Jan; Vlassak, Joost; Curtarolo, Stefano

    Metallic glasses possess an extensive set of mechanical properties along with plastic-like processability. As a result, they are a promising material in many industrial applications. However, the successful synthesis of novel metallic glasses requires trial and error, costing both time and resources. Therefore, we propose a high-throughput approach that combines an extensive set of experimental measurements with advanced machine learning techniques. This allows us to classify metallic glasses and predict the full phase diagrams for a given alloy system. Thus this method provides a means to identify potential glass-formers and opens up the possibility for accelerating and reducing the cost of the design of new metallic glasses.

  15. MT-ComparEval: Graphical evaluation interface for Machine Translation development

    Directory of Open Access Journals (Sweden)

    Klejch Ondřej

    2015-10-01

    Full Text Available The tool described in this article has been designed to help MT developers by implementing a web-based graphical user interface that allows to systematically compare and evaluate various MT engines/experiments using comparative analysis via automatic measures and statistics. The evaluation panel provides graphs, tests for statistical significance and n-gram statistics. We also present a demo server http://wmt.ufal.cz with WMT14 and WMT15 translations.

  16. Prediction of breast cancer risk using a machine learning approach embedded with a locality preserving projection algorithm

    Science.gov (United States)

    Heidari, Morteza; Zargari Khuzani, Abolfazl; Hollingsworth, Alan B.; Danala, Gopichandh; Mirniaharikandehei, Seyedehnafiseh; Qiu, Yuchen; Liu, Hong; Zheng, Bin

    2018-02-01

    In order to automatically identify a set of effective mammographic image features and build an optimal breast cancer risk stratification model, this study aims to investigate advantages of applying a machine learning approach embedded with a locally preserving projection (LPP) based feature combination and regeneration algorithm to predict short-term breast cancer risk. A dataset involving negative mammograms acquired from 500 women was assembled. This dataset was divided into two age-matched classes of 250 high risk cases in which cancer was detected in the next subsequent mammography screening and 250 low risk cases, which remained negative. First, a computer-aided image processing scheme was applied to segment fibro-glandular tissue depicted on mammograms and initially compute 44 features related to the bilateral asymmetry of mammographic tissue density distribution between left and right breasts. Next, a multi-feature fusion based machine learning classifier was built to predict the risk of cancer detection in the next mammography screening. A leave-one-case-out (LOCO) cross-validation method was applied to train and test the machine learning classifier embedded with a LLP algorithm, which generated a new operational vector with 4 features using a maximal variance approach in each LOCO process. Results showed a 9.7% increase in risk prediction accuracy when using this LPP-embedded machine learning approach. An increased trend of adjusted odds ratios was also detected in which odds ratios increased from 1.0 to 11.2. This study demonstrated that applying the LPP algorithm effectively reduced feature dimensionality, and yielded higher and potentially more robust performance in predicting short-term breast cancer risk.

  17. Creating a Multi-axis Machining Postprocessor

    Directory of Open Access Journals (Sweden)

    Petr Vavruška

    2012-01-01

    Full Text Available This paper focuses on the postprocessor creation process. When using standard commercially available postprocessors it is often very difficult to modify its internal source code, and it is a very complex process, in many cases even impossible, to implement the newly-developed functions. It is therefore very important to have a method for creating a postprocessor for any CAM system, which allows CL data (Cutter Location data to be generated to a separate text file. The goal of our work is to verify the proposed method for creating a postprocessor. Postprocessor functions for multi-axis machiningare dealt with in this work. A file with CL data must be translated by the postprocessor into an NC program that has been customized for a specific production machine and its control system. The postprocessor is therefore verified by applications for machining free-form surfaces of complex parts, and by executing the NC programs that are generated on real machine tools. This is also presented here.

  18. Application of Machine Learning Approaches for Classifying Sitting Posture Based on Force and Acceleration Sensors

    Directory of Open Access Journals (Sweden)

    Roland Zemp

    2016-01-01

    Full Text Available Occupational musculoskeletal disorders, particularly chronic low back pain (LBP, are ubiquitous due to prolonged static sitting or nonergonomic sitting positions. Therefore, the aim of this study was to develop an instrumented chair with force and acceleration sensors to determine the accuracy of automatically identifying the user’s sitting position by applying five different machine learning methods (Support Vector Machines, Multinomial Regression, Boosting, Neural Networks, and Random Forest. Forty-one subjects were requested to sit four times in seven different prescribed sitting positions (total 1148 samples. Sixteen force sensor values and the backrest angle were used as the explanatory variables (features for the classification. The different classification methods were compared by means of a Leave-One-Out cross-validation approach. The best performance was achieved using the Random Forest classification algorithm, producing a mean classification accuracy of 90.9% for subjects with which the algorithm was not familiar. The classification accuracy varied between 81% and 98% for the seven different sitting positions. The present study showed the possibility of accurately classifying different sitting positions by means of the introduced instrumented office chair combined with machine learning analyses. The use of such novel approaches for the accurate assessment of chair usage could offer insights into the relationships between sitting position, sitting behaviour, and the occurrence of musculoskeletal disorders.

  19. Student Modeling and Machine Learning

    OpenAIRE

    Sison , Raymund; Shimura , Masamichi

    1998-01-01

    After identifying essential student modeling issues and machine learning approaches, this paper examines how machine learning techniques have been used to automate the construction of student models as well as the background knowledge necessary for student modeling. In the process, the paper sheds light on the difficulty, suitability and potential of using machine learning for student modeling processes, and, to a lesser extent, the potential of using student modeling techniques in machine le...

  20. Mamma Mia, A Singable Translation!

    Directory of Open Access Journals (Sweden)

    Andrej Stopar

    2016-06-01

    Full Text Available The article discusses and analyzes approaches to translating singable texts. It presents a linguistic (prosodic, lexical and structural analysis of the Slovenian translation of the musical Mamma Mia! The aim of the qualitative and quantitative study is to investigate the translation strategies used to produce a singable target text. The results of the analysis suggest that producing a prosodic match is a basic requirement, whereas the lexical, structural and/or poetic characteristics of the source text are subject to changes. Overall, the findings show that the function and the purpose of the translation play a crucial role in the prioritization of translation strategies.

  1. Assessing and evaluating multidisciplinary translational teams: a mixed methods approach.

    Science.gov (United States)

    Wooten, Kevin C; Rose, Robert M; Ostir, Glenn V; Calhoun, William J; Ameredes, Bill T; Brasier, Allan R

    2014-03-01

    A case report illustrates how multidisciplinary translational teams can be assessed using outcome, process, and developmental types of evaluation using a mixed-methods approach. Types of evaluation appropriate for teams are considered in relation to relevant research questions and assessment methods. Logic models are applied to scientific projects and team development to inform choices between methods within a mixed-methods design. Use of an expert panel is reviewed, culminating in consensus ratings of 11 multidisciplinary teams and a final evaluation within a team-type taxonomy. Based on team maturation and scientific progress, teams were designated as (a) early in development, (b) traditional, (c) process focused, or (d) exemplary. Lessons learned from data reduction, use of mixed methods, and use of expert panels are explored.

  2. Classification of Breast Cancer Resistant Protein (BCRP) Inhibitors and Non-Inhibitors Using Machine Learning Approaches.

    Science.gov (United States)

    Belekar, Vilas; Lingineni, Karthik; Garg, Prabha

    2015-01-01

    The breast cancer resistant protein (BCRP) is an important transporter and its inhibitors play an important role in cancer treatment by improving the oral bioavailability as well as blood brain barrier (BBB) permeability of anticancer drugs. In this work, a computational model was developed to predict the compounds as BCRP inhibitors or non-inhibitors. Various machine learning approaches like, support vector machine (SVM), k-nearest neighbor (k-NN) and artificial neural network (ANN) were used to develop the models. The Matthews correlation coefficients (MCC) of developed models using ANN, k-NN and SVM are 0.67, 0.71 and 0.77, and prediction accuracies are 85.2%, 88.3% and 90.8% respectively. The developed models were tested with a test set of 99 compounds and further validated with external set of 98 compounds. Distribution plot analysis and various machine learning models were also developed based on druglikeness descriptors. Applicability domain is used to check the prediction reliability of the new molecules.

  3. an overview of recent developments in translation studies

    African Journals Online (AJOL)

    adopt a descriptive approach towards the study of translated literature. .... During the 1990s the growing discipline of translation studies achieved ... new millennium, translation studies is an international network of scholar- ... In these terms, translation means communicating the foreign ..... the intercultural communication.

  4. Translational research: a concept analysis.

    Science.gov (United States)

    Wendler, M Cecilia; Kirkbride, Geri; Wade, Kristen; Ferrell, Lynne

    2013-01-01

    BACKGROUND/CONCEPTUAL FRAMEWORK: Little is known about which approaches facilitate adoption and sustainment of evidence-based practice change in the highly complex care environments that constitute clinical practice today. The purpose of this article was to complete a concept analysis of translational research using a modified Walker and Avant approach. DESIGN/DATA COLLECTION: Using a rigorous and thorough review of the recent health care literature generated by a deep electronic search from 2004-2011, 85 appropriate documents were retrieved. Close reading of the articles by three coresearchers yielded an analysis of the emerging concept of translational research. Using the iterative process described by Walker and Avant, a tentative definition of the concept of translational research, along with antecedents and consequences were identified. Implications for health care professionals in education, practice, and research are offered. Further research is needed to determine the adequacy of the definition, to identify empirical referents, and to guide theory development. The study resulted in a theoretical definition of the concept of translational research, along with identification of antecedents and consequences and a description of an ideal or model case to illustrate the definition. Implications for practice and education include the importance of focusing on translational research approaches that may reduce the research-practice gap in health care, thereby improving patient care delivery. Research is needed to determine the usefulness of the definition in health care clinical practice.

  5. Topical Review: Mind Your Language-Translation Matters (A Narrative Review of Translation Challenges).

    Science.gov (United States)

    Kiing, Jennifer S H; Rajgor, Dimple; Toh, Teck-Hock

    2016-11-01

    Translation of developmental-behavioral screening tools for use worldwide can be daunting. We summarize issues in translating these tools.  METHODS:  Instead of a theoretical framework of "equivalence" by Pena and International Test Commission guidelines, we decided upon a practical approach used by the American Association of Orthopedic Surgeons (AAOS). We derived vignettes from the Parents' Evaluation of Developmental Status manual and published literature and mapped them to AAOS.  RESULTS:  We found that a systematic approach to planning and translating developmental-behavioral screeners is essential to ensure "equivalence" and encourage wide consultation with experts.  CONCLUSION:  Our narrative highlights how translations can result in many challenges and needed revisions to achieve "equivalence" such that the items remain consistent, valid, and meaningful in the new language for use in different cultures. Information sharing across the community of researchers is encouraged. This narrative may be helpful to novice researchers. © The Author 2016. Published by Oxford University Press on behalf of the Society of Pediatric Psychology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  6. Classifying injury narratives of large administrative databases for surveillance-A practical approach combining machine learning ensembles and human review.

    Science.gov (United States)

    Marucci-Wellman, Helen R; Corns, Helen L; Lehto, Mark R

    2017-01-01

    Injury narratives are now available real time and include useful information for injury surveillance and prevention. However, manual classification of the cause or events leading to injury found in large batches of narratives, such as workers compensation claims databases, can be prohibitive. In this study we compare the utility of four machine learning algorithms (Naïve Bayes, Single word and Bi-gram models, Support Vector Machine and Logistic Regression) for classifying narratives into Bureau of Labor Statistics Occupational Injury and Illness event leading to injury classifications for a large workers compensation database. These algorithms are known to do well classifying narrative text and are fairly easy to implement with off-the-shelf software packages such as Python. We propose human-machine learning ensemble approaches which maximize the power and accuracy of the algorithms for machine-assigned codes and allow for strategic filtering of rare, emerging or ambiguous narratives for manual review. We compare human-machine approaches based on filtering on the prediction strength of the classifier vs. agreement between algorithms. Regularized Logistic Regression (LR) was the best performing algorithm alone. Using this algorithm and filtering out the bottom 30% of predictions for manual review resulted in high accuracy (overall sensitivity/positive predictive value of 0.89) of the final machine-human coded dataset. The best pairings of algorithms included Naïve Bayes with Support Vector Machine whereby the triple ensemble NB SW =NB BI-GRAM =SVM had very high performance (0.93 overall sensitivity/positive predictive value and high accuracy (i.e. high sensitivity and positive predictive values)) across both large and small categories leaving 41% of the narratives for manual review. Integrating LR into this ensemble mix improved performance only slightly. For large administrative datasets we propose incorporation of methods based on human-machine pairings such as

  7. Machine Learning in Computer-Aided Synthesis Planning.

    Science.gov (United States)

    Coley, Connor W; Green, William H; Jensen, Klavs F

    2018-05-15

    . While we introduce this task in the context of reaction validation, its utility extends to the prediction of side products and impurities, among other applications. We describe neural network-based approaches that we and others have developed for this forward prediction task that can be trained on previously published experimental data. Machine learning and artificial intelligence have revolutionized a number of disciplines, not limited to image recognition, dictation, translation, content recommendation, advertising, and autonomous driving. While there is a rich history of using machine learning for structure-activity models in chemistry, it is only now that it is being successfully applied more broadly to organic synthesis and synthesis design. As reported in this Account, machine learning is rapidly transforming CASP, but there are several remaining challenges and opportunities, many pertaining to the availability and standardization of both data and evaluation metrics, which must be addressed by the community at large.

  8. A comparative analysis of machine learning approaches for plant disease identification

    Directory of Open Access Journals (Sweden)

    Hidayat ur Rahman

    2017-08-01

    Full Text Available Background: The problems to leaf in plants are very severe and they usually shorten the lifespan of plants. Leaf diseases are mainly caused due to three types of attacks including viral, bacterial or fungal. Diseased leaves reduce the crop production and affect the agricultural economy. Since agriculture plays a vital role in the economy, thus effective mechanism is required to detect the problem in early stages. Methods: Traditional approaches used for the identification of diseased plants are based on field visits which is time consuming and tedious. In this paper a comparative analysis of machine learning approaches has been presented for the identification of healthy and non-healthy plant leaves. For experimental purpose three different types of plant leaves have been selected namely, cabbage, citrus and sorghum. In order to classify healthy and non-healthy plant leaves color based features such as pixels, statistical features such as mean, standard deviation, min, max and descriptors such as Histogram of Oriented Gradients (HOG have been used. Results: 382 images of cabbage, 539 images of citrus and 262 images of sorghum were used as the primary dataset. The 40% data was utilized for testing and 60% were used for training which consisted of both healthy and damaged leaves. The results showed that random forest classifier is the best machine method for classification of healthy and diseased plant leaves. Conclusion: From the extensive experimentation it is concluded that features such as color information, statistical distribution and histogram of gradients provides sufficient clue for the classification of healthy and non-healthy plants.

  9. Reading Strategies in a L2: A Study on Machine Translation

    Science.gov (United States)

    Karnal, Adriana Riess; Pereira, Vera Vanmacher

    2015-01-01

    This article aims at understanding cognitive strategies which are involved in reading academic texts in English as a L2/FL. Specifically, we focus on reading comprehension when a text is read either using Google translator or not. From this perspective we must consider the reading process in its complexity not only as a decoding process. We follow…

  10. A Cultural Approach to English Translating Strategies of Chinese Cuisine names

    Institute of Scientific and Technical Information of China (English)

    张昆鹏; 魏天婵

    2011-01-01

    Chinese food is not only characterized with its special cooking methods but its cultural implications.However,the status quo of English translation of Chinese dish names is not satisfying.For the purpose of spreading Chinese cuisine culture,4 translating principles and several translating methods are put forward in order to promote the exchanging between cultures.

  11. Learning by Translating: A Contrastive Methodology for ESP Learning and Translation

    Directory of Open Access Journals (Sweden)

    Sara Laviosa

    2015-11-01

    Full Text Available Over the last few years applied linguists have explored the possibility of integrating the insights of second language acquisition theories, contrastive analysis, foreign language teaching methodologies, and translation studies with a view to enhancing current communicative models and techniques for L2 teaching and translator training (see for example Sewell and Higgins 1996; Laviosa-Braithwaite 1997; Campbell 1998; Malmkjær 1998; Laviosa 2000; Colina 2002. We intend to make a contribution to this interdisciplinary orientation by putting forward a translation-based methodology for learning ESP vocabulary and grammar through real life mediating communicative activities. With particular reference to the translation task itself, we endeavour to provide teachers of English for special purposes and translator trainers with a methodology for guiding their students in producing, to the best of their abilities, a target text which meets the quality criteria of terminological accuracy and stylistic fluency, and is also effective in terms of the communicative situation it is intended for. After outlining the rationale and main theoretical approaches underpinning our work, we will illustrate our methodology for learning ESP vocabulary and translation skills from a contrastive perspective, as in our book Learning by Translating (Laviosa and Cleverton 2003.

  12. Dual Numbers Approach in Multiaxis Machines Error Modeling

    Directory of Open Access Journals (Sweden)

    Jaroslav Hrdina

    2014-01-01

    Full Text Available Multiaxis machines error modeling is set in the context of modern differential geometry and linear algebra. We apply special classes of matrices over dual numbers and propose a generalization of such concept by means of general Weil algebras. We show that the classification of the geometric errors follows directly from the algebraic properties of the matrices over dual numbers and thus the calculus over the dual numbers is the proper tool for the methodology of multiaxis machines error modeling.

  13. An object-oriented extension for debugging the virtual machine

    Energy Technology Data Exchange (ETDEWEB)

    Pizzi, Jr, Robert G. [Univ. of California, Davis, CA (United States)

    1994-12-01

    A computer is nothing more then a virtual machine programmed by source code to perform a task. The program`s source code expresses abstract constructs which are compiled into some lower level target language. When a virtual machine breaks, it can be very difficult to debug because typical debuggers provide only low-level target implementation information to the software engineer. We believe that the debugging task can be simplified by introducing aspects of the abstract design and data into the source code. We introduce OODIE, an object-oriented extension to programming languages that allows programmers to specify a virtual environment by describing the meaning of the design and data of a virtual machine. This specification is translated into symbolic information such that an augmented debugger can present engineers with a programmable debugging environment specifically tailored for the virtual machine that is to be debugged.

  14. Application of heuristic and machine-learning approach to engine model calibration

    Science.gov (United States)

    Cheng, Jie; Ryu, Kwang R.; Newman, C. E.; Davis, George C.

    1993-03-01

    Automation of engine model calibration procedures is a very challenging task because (1) the calibration process searches for a goal state in a huge, continuous state space, (2) calibration is often a lengthy and frustrating task because of complicated mutual interference among the target parameters, and (3) the calibration problem is heuristic by nature, and often heuristic knowledge for constraining a search cannot be easily acquired from domain experts. A combined heuristic and machine learning approach has, therefore, been adopted to improve the efficiency of model calibration. We developed an intelligent calibration program called ICALIB. It has been used on a daily basis for engine model applications, and has reduced the time required for model calibrations from many hours to a few minutes on average. In this paper, we describe the heuristic control strategies employed in ICALIB such as a hill-climbing search based on a state distance estimation function, incremental problem solution refinement by using a dynamic tolerance window, and calibration target parameter ordering for guiding the search. In addition, we present the application of a machine learning program called GID3* for automatic acquisition of heuristic rules for ordering target parameters.

  15. Geologic Carbon Sequestration Leakage Detection: A Physics-Guided Machine Learning Approach

    Science.gov (United States)

    Lin, Y.; Harp, D. R.; Chen, B.; Pawar, R.

    2017-12-01

    One of the risks of large-scale geologic carbon sequestration is the potential migration of fluids out of the storage formations. Accurate and fast detection of this fluids migration is not only important but also challenging, due to the large subsurface uncertainty and complex governing physics. Traditional leakage detection and monitoring techniques rely on geophysical observations including pressure. However, the resulting accuracy of these methods is limited because of indirect information they provide requiring expert interpretation, therefore yielding in-accurate estimates of leakage rates and locations. In this work, we develop a novel machine-learning technique based on support vector regression to effectively and efficiently predict the leakage locations and leakage rates based on limited number of pressure observations. Compared to the conventional data-driven approaches, which can be usually seem as a "black box" procedure, we develop a physics-guided machine learning method to incorporate the governing physics into the learning procedure. To validate the performance of our proposed leakage detection method, we employ our method to both 2D and 3D synthetic subsurface models. Our novel CO2 leakage detection method has shown high detection accuracy in the example problems.

  16. Translational research strategy: an essential approach to fight the spread of antimicrobial resistance.

    Science.gov (United States)

    Tacconelli, Evelina; Peschel, Andreas; Autenrieth, Ingo B

    2014-11-01

    Translation research strategy in infectious diseases, combining the results from basic research with patient-orientated research, aims to bridge the gap between laboratory findings and clinical infectious disease practice to improve disease management. In an era of increasing antimicrobial resistance, there are four main areas of clinical and scientific uncertainty that need to be urgently addressed by translational research: (i) early diagnosis of antibiotic-resistant infections and the appropriateness of empirical antibiotic therapy; (ii) the identification of reservoirs of antibiotic-resistant pathogens; (iii) the development of new antibiotics with lower propensities to evoke resistance; and (iv) the development of new non-antibiotic drugs to be used in the prevention of the spread of resistant bacterial strains. Strict European collaboration among major stakeholders is therefore essential. Appropriate educational tools to train a new generation of scientists with regard to a multifaceted approach to antimicrobial resistance research should be developed. Key areas include the support and implementation of European networks focused on translational research and related education activities, making potential therapeutics more attractive to investors and helping academic investigators to determine whether new molecules can be developed with clinical applicability. © The Author 2014. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  17. Theory of transformation groups I general properties of continuous transformation groups a contemporary approach and translation

    CERN Document Server

    2015-01-01

    This modern translation of Sophus Lie's and Friedrich Engel's “Theorie der Transformationsgruppen Band I” will allow readers to discover the striking conceptual clarity and remarkably systematic organizational thought of the original German text. Volume I presents a comprehensive introduction to the theory and is mainly directed towards the generalization of ideas drawn from the study of examples. The major part of the present volume offers an extremely clear translation of the lucid original. The first four chapters provide not only a translation, but also a contemporary approach, which will help present day readers to familiarize themselves with the concepts at the heart of the subject. The editor's main objective was to encourage a renewed interest in the detailed classification of Lie algebras in dimensions 1, 2 and 3, and to offer access to Sophus Lie's monumental Galois theory of continuous transformation groups, established at the end of the 19th Century. Lie groups are widespread in mathematics, p...

  18. Image Classification, Deep Learning and Convolutional Neural Networks : A Comparative Study of Machine Learning Frameworks

    OpenAIRE

    Airola, Rasmus; Hager, Kristoffer

    2017-01-01

    The use of machine learning and specifically neural networks is a growing trend in software development, and has grown immensely in the last couple of years in the light of an increasing need to handle big data and large information flows. Machine learning has a broad area of application, such as human-computer interaction, predicting stock prices, real-time translation, and self driving vehicles. Large companies such as Microsoft and Google have already implemented machine learning in some o...

  19. The quality of translated medical research questionnaires | Fourie ...

    African Journals Online (AJOL)

    The various steps researchers follow when translating their questionnaires or other texts are considered, ... The design, translation approach and quality of the original translations are explained, along with the ... AJOL African Journals Online.

  20. Incorporation of post-translational modified amino acids as an approach to increase both chemical and biological diversity of conotoxins and conopeptides.

    Science.gov (United States)

    Espiritu, Michael J; Cabalteja, Chino C; Sugai, Christopher K; Bingham, Jon-Paul

    2014-01-01

    Bioactive peptides from Conus venom contain a natural abundance of post-translational modifications that affect their chemical diversity, structural stability, and neuroactive properties. These modifications have continually presented hurdles in their identification and characterization. Early endeavors in their analysis relied on classical biochemical techniques that have led to the progressive development and use of novel proteomic-based approaches. The critical importance of these post-translationally modified amino acids and their specific assignment cannot be understated, having impact on their folding, pharmacological selectivity, and potency. Such modifications at an amino acid level may also provide additional insight into the advancement of conopeptide drugs in the quest for precise pharmacological targeting. To achieve this end, a concerted effort between the classical and novel approaches is needed to completely elucidate the role of post-translational modifications in conopeptide structure and dynamics. This paper provides a reflection in the advancements observed in dealing with numerous and multiple post-translationally modified amino acids within conotoxins and conopeptides and provides a summary of the current techniques used in their identification.

  1. Prediction of selective estrogen receptor beta agonist using open data and machine learning approach

    Directory of Open Access Journals (Sweden)

    Niu AQ

    2016-07-01

    Full Text Available Ai-qin Niu,1 Liang-jun Xie,2 Hui Wang,1 Bing Zhu,1 Sheng-qi Wang3 1Department of Gynecology, the First People’s Hospital of Shangqiu, Shangqiu, Henan, People’s Republic of China; 2Department of Image Diagnoses, the Third Hospital of Jinan, Jinan, Shandong, People’s Republic of China; 3Department of Mammary Disease, Guangdong Provincial Hospital of Chinese Medicine, the Second Clinical College of Guangzhou University of Chinese Medicine, Guangzhou, People’s Republic of China Background: Estrogen receptors (ERs are nuclear transcription factors that are involved in the regulation of many complex physiological processes in humans. ERs have been validated as important drug targets for the treatment of various diseases, including breast cancer, ovarian cancer, osteoporosis, and cardiovascular disease. ERs have two subtypes, ER-α and ER-β. Emerging data suggest that the development of subtype-selective ligands that specifically target ER-β could be a more optimal approach to elicit beneficial estrogen-like activities and reduce side effects. Methods: Herein, we focused on ER-β and developed its in silico quantitative structure-activity relationship models using machine learning (ML methods. Results: The chemical structures and ER-β bioactivity data were extracted from public chemogenomics databases. Four types of popular fingerprint generation methods including MACCS fingerprint, PubChem fingerprint, 2D atom pairs, and Chemistry Development Kit extended fingerprint were used as descriptors. Four ML methods including Naïve Bayesian classifier, k-nearest neighbor, random forest, and support vector machine were used to train the models. The range of classification accuracies was 77.10% to 88.34%, and the range of area under the ROC (receiver operating characteristic curve values was 0.8151 to 0.9475, evaluated by the 5-fold cross-validation. Comparison analysis suggests that both the random forest and the support vector machine are superior

  2. Vector control of induction machines

    CERN Document Server

    Robyns, Benoit

    2012-01-01

    After a brief introduction to the main law of physics and fundamental concepts inherent in electromechanical conversion, ""Vector Control of Induction Machines"" introduces the standard mathematical models for induction machines - whichever rotor technology is used - as well as several squirrel-cage induction machine vector-control strategies. The use of causal ordering graphs allows systematization of the design stage, as well as standardization of the structure of control devices. ""Vector Control of Induction Machines"" suggests a unique approach aimed at reducing parameter sensitivity for

  3. Machinability of Al 6061 Deposited with Cold Spray Additive Manufacturing

    Science.gov (United States)

    Aldwell, Barry; Kelly, Elaine; Wall, Ronan; Amaldi, Andrea; O'Donnell, Garret E.; Lupoi, Rocco

    2017-10-01

    Additive manufacturing techniques such as cold spray are translating from research laboratories into more mainstream high-end production systems. Similar to many additive processes, finishing still depends on removal processes. This research presents the results from investigations into aspects of the machinability of aluminum 6061 tubes manufactured with cold spray. Through the analysis of cutting forces and observations on chip formation and surface morphology, the effect of cutting speed, feed rate, and heat treatment was quantified, for both cold-sprayed and bulk aluminum 6061. High-speed video of chip formation shows changes in chip form for varying material and heat treatment, which is supported by the force data and quantitative imaging of the machined surface. The results shown in this paper demonstrate that parameters involved in cold spray directly impact on machinability and therefore have implications for machining parameters and strategy.

  4. Virtual Machine Language

    Science.gov (United States)

    Grasso, Christopher; Page, Dennis; O'Reilly, Taifun; Fteichert, Ralph; Lock, Patricia; Lin, Imin; Naviaux, Keith; Sisino, John

    2005-01-01

    Virtual Machine Language (VML) is a mission-independent, reusable software system for programming for spacecraft operations. Features of VML include a rich set of data types, named functions, parameters, IF and WHILE control structures, polymorphism, and on-the-fly creation of spacecraft commands from calculated values. Spacecraft functions can be abstracted into named blocks that reside in files aboard the spacecraft. These named blocks accept parameters and execute in a repeatable fashion. The sizes of uplink products are minimized by the ability to call blocks that implement most of the command steps. This block approach also enables some autonomous operations aboard the spacecraft, such as aerobraking, telemetry conditional monitoring, and anomaly response, without developing autonomous flight software. Operators on the ground write blocks and command sequences in a concise, high-level, human-readable programming language (also called VML ). A compiler translates the human-readable blocks and command sequences into binary files (the operations products). The flight portion of VML interprets the uplinked binary files. The ground subsystem of VML also includes an interactive sequence- execution tool hosted on workstations, which runs sequences at several thousand times real-time speed, affords debugging, and generates reports. This tool enables iterative development of blocks and sequences within times of the order of seconds.

  5. A new approach to the solution of the vacuum magnetic problem in fusion machines

    International Nuclear Information System (INIS)

    Zabeo, L.; Artaserse, G.; Cenedese, A.; Piccolo, F.; Sartori, F.

    2007-01-01

    The magnetic vacuum topology reconstruction using magnetic measurements is essential in controlling and understanding plasmas produced in magnetic confinement fusion devices. In a wide range of cases, the instruments used to approach the problem have been designed for a specific machine and to solve a specific plasma model. Recently, a new approach has been used for developing new magnetic software called FELIX. The adopted solution in the design allows the use of the software not only at JET but also at other machines. In order to reduce the analysis and debugging time the software has been designed with modularity and platform independence in mind. This results in a large portability and in particular it allows using the same code both offline and in real-time. One of the main aspects of the tool is its capability to solve different plasma models of current distribution. Thanks to this feature, in order to improve the plasma magnetic reconstruction in real-time, a set of different models has been run using FELIX. FELIX is presently running at JET in different real-time analysis and control systems that need vacuum magnetic topology

  6. Introduction to machine learning.

    Science.gov (United States)

    Baştanlar, Yalin; Ozuysal, Mustafa

    2014-01-01

    The machine learning field, which can be briefly defined as enabling computers make successful predictions using past experiences, has exhibited an impressive development recently with the help of the rapid increase in the storage capacity and processing power of computers. Together with many other disciplines, machine learning methods have been widely employed in bioinformatics. The difficulties and cost of biological analyses have led to the development of sophisticated machine learning approaches for this application area. In this chapter, we first review the fundamental concepts of machine learning such as feature assessment, unsupervised versus supervised learning and types of classification. Then, we point out the main issues of designing machine learning experiments and their performance evaluation. Finally, we introduce some supervised learning methods.

  7. Translational approach for gene therapy in epilepsy

    DEFF Research Database (Denmark)

    Ledri, Litsa Nikitidou; Melin, Esbjörn; Christiansen, Søren H.

    2016-01-01

    clinical trial for gene therapy of temporal lobe epilepsy was explored: We investigated (i) whether the post intrahippocampal kainate-induced status epilepticus (SE) model of chronic epilepsy in rats could be clinically relevant; and (ii) whether a translationally designed neuropeptide Y (NPY)/Y2 receptor...

  8. Machine Learning Based Classification of Microsatellite Variation: An Effective Approach for Phylogeographic Characterization of Olive Populations.

    Science.gov (United States)

    Torkzaban, Bahareh; Kayvanjoo, Amir Hossein; Ardalan, Arman; Mousavi, Soraya; Mariotti, Roberto; Baldoni, Luciana; Ebrahimie, Esmaeil; Ebrahimi, Mansour; Hosseini-Mazinani, Mehdi

    2015-01-01

    Finding efficient analytical techniques is overwhelmingly turning into a bottleneck for the effectiveness of large biological data. Machine learning offers a novel and powerful tool to advance classification and modeling solutions in molecular biology. However, these methods have been less frequently used with empirical population genetics data. In this study, we developed a new combined approach of data analysis using microsatellite marker data from our previous studies of olive populations using machine learning algorithms. Herein, 267 olive accessions of various origins including 21 reference cultivars, 132 local ecotypes, and 37 wild olive specimens from the Iranian plateau, together with 77 of the most represented Mediterranean varieties were investigated using a finely selected panel of 11 microsatellite markers. We organized data in two '4-targeted' and '16-targeted' experiments. A strategy of assaying different machine based analyses (i.e. data cleaning, feature selection, and machine learning classification) was devised to identify the most informative loci and the most diagnostic alleles to represent the population and the geography of each olive accession. These analyses revealed microsatellite markers with the highest differentiating capacity and proved efficiency for our method of clustering olive accessions to reflect upon their regions of origin. A distinguished highlight of this study was the discovery of the best combination of markers for better differentiating of populations via machine learning models, which can be exploited to distinguish among other biological populations.

  9. Towards a Participatory Approach to Bible Translation (PABT) 1

    African Journals Online (AJOL)

    It is generally acknowledged that the participation of the receptor community may enhance the community's ownership and acceptability of the translation. In spite of this acknowledgement, individuals and organisations engaged in mother tongue translations of the Bible often involve the members of the receptor community ...

  10. A new framework for Bible translation | Wilt | Acta Theologica

    African Journals Online (AJOL)

    ... as well as translators and choosing a particular translation approach in terms of mutually agreed upon goals. The Bible translation process may involve not just producing a text to represent the sacred text, but also supplementary texts to enhance understanding and appreciation of both the translation and the translated.

  11. The Circle of Meaning: From Translation to Paraphrasing and Back

    Science.gov (United States)

    Madnani, Nitin

    2010-01-01

    The preservation of meaning between inputs and outputs is perhaps the most ambitious and, often, the most elusive goal of systems that attempt to process natural language. Nowhere is this goal of more obvious importance than for the tasks of machine translation and paraphrase generation. Preserving meaning between the input and the output is…

  12. A machine-learning approach for computation of fractional flow reserve from coronary computed tomography.

    Science.gov (United States)

    Itu, Lucian; Rapaka, Saikiran; Passerini, Tiziano; Georgescu, Bogdan; Schwemmer, Chris; Schoebinger, Max; Flohr, Thomas; Sharma, Puneet; Comaniciu, Dorin

    2016-07-01

    Fractional flow reserve (FFR) is a functional index quantifying the severity of coronary artery lesions and is clinically obtained using an invasive, catheter-based measurement. Recently, physics-based models have shown great promise in being able to noninvasively estimate FFR from patient-specific anatomical information, e.g., obtained from computed tomography scans of the heart and the coronary arteries. However, these models have high computational demand, limiting their clinical adoption. In this paper, we present a machine-learning-based model for predicting FFR as an alternative to physics-based approaches. The model is trained on a large database of synthetically generated coronary anatomies, where the target values are computed using the physics-based model. The trained model predicts FFR at each point along the centerline of the coronary tree, and its performance was assessed by comparing the predictions against physics-based computations and against invasively measured FFR for 87 patients and 125 lesions in total. Correlation between machine-learning and physics-based predictions was excellent (0.9994, P machine-learning algorithm with a sensitivity of 81.6%, a specificity of 83.9%, and an accuracy of 83.2%. The correlation was 0.729 (P assessment of FFR. Average execution time went down from 196.3 ± 78.5 s for the CFD model to ∼2.4 ± 0.44 s for the machine-learning model on a workstation with 3.4-GHz Intel i7 8-core processor. Copyright © 2016 the American Physiological Society.

  13. Biomarkers of Eating Disorders Using Support Vector Machine Analysis of Structural Neuroimaging Data: Preliminary Results

    Directory of Open Access Journals (Sweden)

    Antonio Cerasa

    2015-01-01

    Full Text Available Presently, there are no valid biomarkers to identify individuals with eating disorders (ED. The aim of this work was to assess the feasibility of a machine learning method for extracting reliable neuroimaging features allowing individual categorization of patients with ED. Support Vector Machine (SVM technique, combined with a pattern recognition method, was employed utilizing structural magnetic resonance images. Seventeen females with ED (six with diagnosis of anorexia nervosa and 11 with bulimia nervosa were compared against 17 body mass index-matched healthy controls (HC. Machine learning allowed individual diagnosis of ED versus HC with an Accuracy ≥ 0.80. Voxel-based pattern recognition analysis demonstrated that voxels influencing the classification Accuracy involved the occipital cortex, the posterior cerebellar lobule, precuneus, sensorimotor/premotor cortices, and the medial prefrontal cortex, all critical regions known to be strongly involved in the pathophysiological mechanisms of ED. Although these findings should be considered preliminary given the small size investigated, SVM analysis highlights the role of well-known brain regions as possible biomarkers to distinguish ED from HC at an individual level, thus encouraging the translational implementation of this new multivariate approach in the clinical practice.

  14. Biomarkers of Eating Disorders Using Support Vector Machine Analysis of Structural Neuroimaging Data: Preliminary Results

    Science.gov (United States)

    Cerasa, Antonio; Castiglioni, Isabella; Salvatore, Christian; Funaro, Angela; Martino, Iolanda; Alfano, Stefania; Donzuso, Giulia; Perrotta, Paolo; Gioia, Maria Cecilia; Gilardi, Maria Carla; Quattrone, Aldo

    2015-01-01

    Presently, there are no valid biomarkers to identify individuals with eating disorders (ED). The aim of this work was to assess the feasibility of a machine learning method for extracting reliable neuroimaging features allowing individual categorization of patients with ED. Support Vector Machine (SVM) technique, combined with a pattern recognition method, was employed utilizing structural magnetic resonance images. Seventeen females with ED (six with diagnosis of anorexia nervosa and 11 with bulimia nervosa) were compared against 17 body mass index-matched healthy controls (HC). Machine learning allowed individual diagnosis of ED versus HC with an Accuracy ≥ 0.80. Voxel-based pattern recognition analysis demonstrated that voxels influencing the classification Accuracy involved the occipital cortex, the posterior cerebellar lobule, precuneus, sensorimotor/premotor cortices, and the medial prefrontal cortex, all critical regions known to be strongly involved in the pathophysiological mechanisms of ED. Although these findings should be considered preliminary given the small size investigated, SVM analysis highlights the role of well-known brain regions as possible biomarkers to distinguish ED from HC at an individual level, thus encouraging the translational implementation of this new multivariate approach in the clinical practice. PMID:26648660

  15. Nurturing and Testing Translation Competence for Text-Translating

    Science.gov (United States)

    Aubakirova, Karlygash Adilkhanovna

    2016-01-01

    The article analyzes the problems of contemporary professional education. As its instance, we examine the developmental scheme for training professional translators. Optimal ways of organizing the learning process are suggested from the point of view of the competence approach, which is widely recognized for training a modern specialist. The…

  16. The complexity of translationally invariant low-dimensional spin lattices in 3D

    Science.gov (United States)

    Bausch, Johannes; Piddock, Stephen

    2017-11-01

    In this theoretical paper, we consider spin systems in three spatial dimensions and consider the computational complexity of estimating the ground state energy, known as the local Hamiltonian problem, for translationally invariant Hamiltonians. We prove that the local Hamiltonian problem for 3D lattices with face-centered cubic unit cells and 4-local translationally invariant interactions between spin-3/2 particles and open boundary conditions is QMAEXP-complete, where QMAEXP is the class of problems which can be verified in exponential time on a quantum computer. We go beyond a mere embedding of past hard 1D history state constructions, for which the local spin dimension is enormous: even state-of-the-art constructions have local dimension 42. We avoid such a large local dimension by combining some different techniques in a novel way. For the verifier circuit which we embed into the ground space of the local Hamiltonian, we utilize a recently developed computational model, called a quantum ring machine, which is especially well suited for translationally invariant history state constructions. This is encoded with a new and particularly simple universal gate set, which consists of a single 2-qubit gate applied only to nearest-neighbour qubits. The Hamiltonian construction involves a classical Wang tiling problem as a binary counter which translates one cube side length into a binary description for the encoded verifier input and a carefully engineered history state construction that implements the ring machine on the cubic lattice faces. These novel techniques allow us to significantly lower the local spin dimension, surpassing the best translationally invariant result to date by two orders of magnitude (in the number of degrees of freedom per coupling). This brings our models on par with the best non-translationally invariant construction.

  17. Automated classification of tropical shrub species: a hybrid of leaf shape and machine learning approach.

    Science.gov (United States)

    Murat, Miraemiliana; Chang, Siow-Wee; Abu, Arpah; Yap, Hwa Jen; Yong, Kien-Thai

    2017-01-01

    Plants play a crucial role in foodstuff, medicine, industry, and environmental protection. The skill of recognising plants is very important in some applications, including conservation of endangered species and rehabilitation of lands after mining activities. However, it is a difficult task to identify plant species because it requires specialized knowledge. Developing an automated classification system for plant species is necessary and valuable since it can help specialists as well as the public in identifying plant species easily. Shape descriptors were applied on the myDAUN dataset that contains 45 tropical shrub species collected from the University of Malaya (UM), Malaysia. Based on literature review, this is the first study in the development of tropical shrub species image dataset and classification using a hybrid of leaf shape and machine learning approach. Four types of shape descriptors were used in this study namely morphological shape descriptors (MSD), Histogram of Oriented Gradients (HOG), Hu invariant moments (Hu) and Zernike moments (ZM). Single descriptor, as well as the combination of hybrid descriptors were tested and compared. The tropical shrub species are classified using six different classifiers, which are artificial neural network (ANN), random forest (RF), support vector machine (SVM), k-nearest neighbour (k-NN), linear discriminant analysis (LDA) and directed acyclic graph multiclass least squares twin support vector machine (DAG MLSTSVM). In addition, three types of feature selection methods were tested in the myDAUN dataset, Relief, Correlation-based feature selection (CFS) and Pearson's coefficient correlation (PCC). The well-known Flavia dataset and Swedish Leaf dataset were used as the validation dataset on the proposed methods. The results showed that the hybrid of all descriptors of ANN outperformed the other classifiers with an average classification accuracy of 98.23% for the myDAUN dataset, 95.25% for the Flavia dataset and 99

  18. Automated classification of tropical shrub species: a hybrid of leaf shape and machine learning approach

    Directory of Open Access Journals (Sweden)

    Miraemiliana Murat

    2017-09-01

    Full Text Available Plants play a crucial role in foodstuff, medicine, industry, and environmental protection. The skill of recognising plants is very important in some applications, including conservation of endangered species and rehabilitation of lands after mining activities. However, it is a difficult task to identify plant species because it requires specialized knowledge. Developing an automated classification system for plant species is necessary and valuable since it can help specialists as well as the public in identifying plant species easily. Shape descriptors were applied on the myDAUN dataset that contains 45 tropical shrub species collected from the University of Malaya (UM, Malaysia. Based on literature review, this is the first study in the development of tropical shrub species image dataset and classification using a hybrid of leaf shape and machine learning approach. Four types of shape descriptors were used in this study namely morphological shape descriptors (MSD, Histogram of Oriented Gradients (HOG, Hu invariant moments (Hu and Zernike moments (ZM. Single descriptor, as well as the combination of hybrid descriptors were tested and compared. The tropical shrub species are classified using six different classifiers, which are artificial neural network (ANN, random forest (RF, support vector machine (SVM, k-nearest neighbour (k-NN, linear discriminant analysis (LDA and directed acyclic graph multiclass least squares twin support vector machine (DAG MLSTSVM. In addition, three types of feature selection methods were tested in the myDAUN dataset, Relief, Correlation-based feature selection (CFS and Pearson’s coefficient correlation (PCC. The well-known Flavia dataset and Swedish Leaf dataset were used as the validation dataset on the proposed methods. The results showed that the hybrid of all descriptors of ANN outperformed the other classifiers with an average classification accuracy of 98.23% for the myDAUN dataset, 95.25% for the Flavia

  19. Machine learning with R

    CERN Document Server

    Lantz, Brett

    2013-01-01

    Written as a tutorial to explore and understand the power of R for machine learning. This practical guide that covers all of the need to know topics in a very systematic way. For each machine learning approach, each step in the process is detailed, from preparing the data for analysis to evaluating the results. These steps will build the knowledge you need to apply them to your own data science tasks.Intended for those who want to learn how to use R's machine learning capabilities and gain insight from your data. Perhaps you already know a bit about machine learning, but have never used R; or

  20. Tensor Voting A Perceptual Organization Approach to Computer Vision and Machine Learning

    CERN Document Server

    Mordohai, Philippos

    2006-01-01

    This lecture presents research on a general framework for perceptual organization that was conducted mainly at the Institute for Robotics and Intelligent Systems of the University of Southern California. It is not written as a historical recount of the work, since the sequence of the presentation is not in chronological order. It aims at presenting an approach to a wide range of problems in computer vision and machine learning that is data-driven, local and requires a minimal number of assumptions. The tensor voting framework combines these properties and provides a unified perceptual organiza

  1. Limitations Of The Current State Space Modelling Approach In Multistage Machining Processes Due To Operation Variations

    Science.gov (United States)

    Abellán-Nebot, J. V.; Liu, J.; Romero, F.

    2009-11-01

    The State Space modelling approach has been recently proposed as an engineering-driven technique for part quality prediction in Multistage Machining Processes (MMP). Current State Space models incorporate fixture and datum variations in the multi-stage variation propagation, without explicitly considering common operation variations such as machine-tool thermal distortions, cutting-tool wear, cutting-tool deflections, etc. This paper shows the limitations of the current State Space model through an experimental case study where the effect of the spindle thermal expansion, cutting-tool flank wear and locator errors are introduced. The paper also discusses the extension of the current State Space model to include operation variations and its potential benefits.

  2. A Hierarchical Approach Using Machine Learning Methods in Solar Photovoltaic Energy Production Forecasting

    OpenAIRE

    Zhaoxuan Li; SM Mahbobur Rahman; Rolando Vega; Bing Dong

    2016-01-01

    We evaluate and compare two common methods, artificial neural networks (ANN) and support vector regression (SVR), for predicting energy productions from a solar photovoltaic (PV) system in Florida 15 min, 1 h and 24 h ahead of time. A hierarchical approach is proposed based on the machine learning algorithms tested. The production data used in this work corresponds to 15 min averaged power measurements collected from 2014. The accuracy of the model is determined using computing error statisti...

  3. Term-creation strategies used by Ndebele translators in Zimbabwe ...

    African Journals Online (AJOL)

    Term-creation strategies used by Ndebele translators in Zimbabwe in the health sector: A corpus-based approach. ... strategies employed by Ndebele translators from a corpus-based approach using ParaConc, ... AJOL African Journals Online.

  4. Prediction of selective estrogen receptor beta agonist using open data and machine learning approach.

    Science.gov (United States)

    Niu, Ai-Qin; Xie, Liang-Jun; Wang, Hui; Zhu, Bing; Wang, Sheng-Qi

    2016-01-01

    Estrogen receptors (ERs) are nuclear transcription factors that are involved in the regulation of many complex physiological processes in humans. ERs have been validated as important drug targets for the treatment of various diseases, including breast cancer, ovarian cancer, osteoporosis, and cardiovascular disease. ERs have two subtypes, ER-α and ER-β. Emerging data suggest that the development of subtype-selective ligands that specifically target ER-β could be a more optimal approach to elicit beneficial estrogen-like activities and reduce side effects. Herein, we focused on ER-β and developed its in silico quantitative structure-activity relationship models using machine learning (ML) methods. The chemical structures and ER-β bioactivity data were extracted from public chemogenomics databases. Four types of popular fingerprint generation methods including MACCS fingerprint, PubChem fingerprint, 2D atom pairs, and Chemistry Development Kit extended fingerprint were used as descriptors. Four ML methods including Naïve Bayesian classifier, k-nearest neighbor, random forest, and support vector machine were used to train the models. The range of classification accuracies was 77.10% to 88.34%, and the range of area under the ROC (receiver operating characteristic) curve values was 0.8151 to 0.9475, evaluated by the 5-fold cross-validation. Comparison analysis suggests that both the random forest and the support vector machine are superior for the classification of selective ER-β agonists. Chemistry Development Kit extended fingerprints and MACCS fingerprint performed better in structural representation between active and inactive agonists. These results demonstrate that combining the fingerprint and ML approaches leads to robust ER-β agonist prediction models, which are potentially applicable to the identification of selective ER-β agonists.

  5. From translation to enactment: contributions of the Actor-Network Theory to the processual approach to organizations

    Directory of Open Access Journals (Sweden)

    Patricia Kinast De Camillis

    Full Text Available Abstract In the area of Administration, especially in the Organizational Studies (OS, the Actor-Network Theory (ANT has been regarded as part of a movement that aims to leave the functional emphasis of organization and pursue the study of process and practices of organizing - the processual approach to organizations. However, criticism to the ANT has led some authors to seek to overcome them through analytical twists concerning certain concepts. One of these "twists" involved the concept of translation and the inclusion of the concept of enactment . This article discusses both notions with the aid of two studies developed having these concepts as a basis, in order to indicate that the choice of enactment brings along a processual view different from that observed in translation. The concept of translation addresses the predominant and it emphasizes understanding how networks of relationships and objects become "stable"; in turn, enact works with multiplicity and fluidity, where the process takes precedence over things. Although the proposed term enactment does not seek to directly face all criticism, it contributes so that ANT does not take a neutral or mechanical view in its analyses and descriptions. Enactment has the view of organization as a result and product of continuous process and it allows understanding that this is not just working or not (success or failure, but it concerns the "production" of multiple realities when we conduct research in Administration having the processual approach to organizations as a basis.

  6. A hybrid Taguchi-artificial neural network approach to predict surface roughness during electric discharge machining of titanium alloys

    Energy Technology Data Exchange (ETDEWEB)

    Kumar, Sanjeev; Batish, Ajay [Thapar University, Patiala (India); Singh, Rupinder [GNDEC, Ludhiana (India); Singh, T. P. [Symbiosis Institute of Technology, Pune (India)

    2014-07-15

    In the present study, electric discharge machining process was used for machining of titanium alloys. Eight process parameters were varied during the process. Experimental results showed that current and pulse-on-time significantly affected the performance characteristics. Artificial neural network coupled with Taguchi approach was applied for optimization and prediction of surface roughness. The experimental results and the predicted results showed good agreement. SEM was used to investigate the surface integrity. Analysis for migration of different chemical elements and formation of compounds on the surface was performed using EDS and XRD pattern. The results showed that high discharge energy caused surface defects such as cracks, craters, thick recast layer, micro pores, pin holes, residual stresses and debris. Also, migration of chemical elements both from electrode and dielectric media were observed during EDS analysis. Presence of carbon was seen on the machined surface. XRD results showed formation of titanium carbide compound which precipitated on the machined surface.

  7. Game-powered machine learning.

    Science.gov (United States)

    Barrington, Luke; Turnbull, Douglas; Lanckriet, Gert

    2012-04-24

    Searching for relevant content in a massive amount of multimedia information is facilitated by accurately annotating each image, video, or song with a large number of relevant semantic keywords, or tags. We introduce game-powered machine learning, an integrated approach to annotating multimedia content that combines the effectiveness of human computation, through online games, with the scalability of machine learning. We investigate this framework for labeling music. First, a socially-oriented music annotation game called Herd It collects reliable music annotations based on the "wisdom of the crowds." Second, these annotated examples are used to train a supervised machine learning system. Third, the machine learning system actively directs the annotation games to collect new data that will most benefit future model iterations. Once trained, the system can automatically annotate a corpus of music much larger than what could be labeled using human computation alone. Automatically annotated songs can be retrieved based on their semantic relevance to text-based queries (e.g., "funky jazz with saxophone," "spooky electronica," etc.). Based on the results presented in this paper, we find that actively coupling annotation games with machine learning provides a reliable and scalable approach to making searchable massive amounts of multimedia data.

  8. Who translates the translation? (Retraduire les héros marginaux d'Alan Moore

    Directory of Open Access Journals (Sweden)

    Alice RAY

    2016-11-01

    Full Text Available The retranslation phenomenon is essential to the translation process. It is considered as the logical progression of this process which allows the translated literary work to regenerate in a restless cultural and language space. To a lesser extent, we can observe the same phenomenon in the translation of comics. However, this specific translation requires other competencies and a translating approach somehow different from the ones required to translate fiction literature, especially because of the presence of the visual system of drawings which is strongly bound to its own culture and the endless mutations it goes through. The comic book Watchmen (Les Gardiens, in the first French translation by Alan Moore and Dave Gibbons, is known in the whole world as the comic which had not only remodeled the vision we had of super-heroes, but had also given the comic books another voice. Watchmen was published between 1986 and 1987 in the United States and translated in French from 1987 to 1988. Fifteen years after this first translation by Jean-Patrick Manchette, Panini publishing decided to retranslate this famous comic in 2007. However, if the reviews of the first translation were laudatory, the retranslation did not enjoy a great reception from the readers or from the reviewers. This paper proposes a comparative analysis of both these translations and of their original version as well as an experiment on the readers, comic books readers or not, in order to establish why the first translation was a success and the retranslation a failure. Thus, we could withdraw the elements which allow us to understand the reception of comic translation.

  9. Combining macula clinical signs and patient characteristics for age-related macular degeneration diagnosis: a machine learning approach.

    Science.gov (United States)

    Fraccaro, Paolo; Nicolo, Massimo; Bonetto, Monica; Giacomini, Mauro; Weller, Peter; Traverso, Carlo Enrico; Prosperi, Mattia; OSullivan, Dympna

    2015-01-27

    To investigate machine learning methods, ranging from simpler interpretable techniques to complex (non-linear) "black-box" approaches, for automated diagnosis of Age-related Macular Degeneration (AMD). Data from healthy subjects and patients diagnosed with AMD or other retinal diseases were collected during routine visits via an Electronic Health Record (EHR) system. Patients' attributes included demographics and, for each eye, presence/absence of major AMD-related clinical signs (soft drusen, retinal pigment epitelium, defects/pigment mottling, depigmentation area, subretinal haemorrhage, subretinal fluid, macula thickness, macular scar, subretinal fibrosis). Interpretable techniques known as white box methods including logistic regression and decision trees as well as less interpreitable techniques known as black box methods, such as support vector machines (SVM), random forests and AdaBoost, were used to develop models (trained and validated on unseen data) to diagnose AMD. The gold standard was confirmed diagnosis of AMD by physicians. Sensitivity, specificity and area under the receiver operating characteristic (AUC) were used to assess performance. Study population included 487 patients (912 eyes). In terms of AUC, random forests, logistic regression and adaboost showed a mean performance of (0.92), followed by SVM and decision trees (0.90). All machine learning models identified soft drusen and age as the most discriminating variables in clinicians' decision pathways to diagnose AMD. Both black-box and white box methods performed well in identifying diagnoses of AMD and their decision pathways. Machine learning models developed through the proposed approach, relying on clinical signs identified by retinal specialists, could be embedded into EHR to provide physicians with real time (interpretable) support.

  10. Predicting sumoylation sites using support vector machines based on various sequence features, conformational flexibility and disorder.

    Science.gov (United States)

    Yavuz, Ahmet Sinan; Sezerman, Osman Ugur

    2014-01-01

    Sumoylation, which is a reversible and dynamic post-translational modification, is one of the vital processes in a cell. Before a protein matures to perform its function, sumoylation may alter its localization, interactions, and possibly structural conformation. Abberations in protein sumoylation has been linked with a variety of disorders and developmental anomalies. Experimental approaches to identification of sumoylation sites may not be effective due to the dynamic nature of sumoylation, laborsome experiments and their cost. Therefore, computational approaches may guide experimental identification of sumoylation sites and provide insights for further understanding sumoylation mechanism. In this paper, the effectiveness of using various sequence properties in predicting sumoylation sites was investigated with statistical analyses and machine learning approach employing support vector machines. These sequence properties were derived from windows of size 7 including position-specific amino acid composition, hydrophobicity, estimated sub-window volumes, predicted disorder, and conformational flexibility. 5-fold cross-validation results on experimentally identified sumoylation sites revealed that our method successfully predicts sumoylation sites with a Matthew's correlation coefficient, sensitivity, specificity, and accuracy equal to 0.66, 73%, 98%, and 97%, respectively. Additionally, we have showed that our method compares favorably to the existing prediction methods and basic regular expressions scanner. By using support vector machines, a new, robust method for sumoylation site prediction was introduced. Besides, the possible effects of predicted conformational flexibility and disorder on sumoylation site recognition were explored computationally for the first time to our knowledge as an additional parameter that could aid in sumoylation site prediction.

  11. Gregory Rabassa’s Views on Translation

    Directory of Open Access Journals (Sweden)

    Bolaños Cuéllar Sergio

    2011-06-01

    Full Text Available Gregory Rabassa is noted for his translations of famous Latin American authors (García Márquez, Vargas Llosa, Clarice Lispector, Jorge Amado, etc.. Less known are his views on translating. In this paper I aim at presenting and discussing his viewpoints as to the definition of translation (with a key discussion of the concept of equivalence, the role of the translator (a model speaker-listener of the target text, and some of the translation strategies he applies in his translational work (original's pre-eminence, problem solving, foreignizing, fictionalizing, and semantic networking. I argue that most of Rabassa's stances towards translating can be explained and are still valid within the framework of a modern translation approach. Examples from the English, French, German, Portuguese and Russian translations of García Márquez's Cien años de soledad are taken from a multilingual parallel corpus collected by the author of this paper.

  12. Improving Machining Accuracy of CNC Machines with Innovative Design Methods

    Science.gov (United States)

    Yemelyanov, N. V.; Yemelyanova, I. V.; Zubenko, V. L.

    2018-03-01

    The article considers achieving the machining accuracy of CNC machines by applying innovative methods in modelling and design of machining systems, drives and machine processes. The topological method of analysis involves visualizing the system as matrices of block graphs with a varying degree of detail between the upper and lower hierarchy levels. This approach combines the advantages of graph theory and the efficiency of decomposition methods, it also has visual clarity, which is inherent in both topological models and structural matrices, as well as the resiliency of linear algebra as part of the matrix-based research. The focus of the study is on the design of automated machine workstations, systems, machines and units, which can be broken into interrelated parts and presented as algebraic, topological and set-theoretical models. Every model can be transformed into a model of another type, and, as a result, can be interpreted as a system of linear and non-linear equations which solutions determine the system parameters. This paper analyses the dynamic parameters of the 1716PF4 machine at the stages of design and exploitation. Having researched the impact of the system dynamics on the component quality, the authors have developed a range of practical recommendations which have enabled one to reduce considerably the amplitude of relative motion, exclude some resonance zones within the spindle speed range of 0...6000 min-1 and improve machining accuracy.

  13. Using Machine Learning to Advance Personality Assessment and Theory.

    Science.gov (United States)

    Bleidorn, Wiebke; Hopwood, Christopher James

    2018-05-01

    Machine learning has led to important advances in society. One of the most exciting applications of machine learning in psychological science has been the development of assessment tools that can powerfully predict human behavior and personality traits. Thus far, machine learning approaches to personality assessment have focused on the associations between social media and other digital records with established personality measures. The goal of this article is to expand the potential of machine learning approaches to personality assessment by embedding it in a more comprehensive construct validation framework. We review recent applications of machine learning to personality assessment, place machine learning research in the broader context of fundamental principles of construct validation, and provide recommendations for how to use machine learning to advance our understanding of personality.

  14. BENCHMARKING MACHINE LEARNING TECHNIQUES FOR SOFTWARE DEFECT DETECTION

    OpenAIRE

    Saiqa Aleem; Luiz Fernando Capretz; Faheem Ahmed

    2015-01-01

    Machine Learning approaches are good in solving problems that have less information. In most cases, the software domain problems characterize as a process of learning that depend on the various circumstances and changes accordingly. A predictive model is constructed by using machine learning approaches and classified them into defective and non-defective modules. Machine learning techniques help developers to retrieve useful information after the classification and enable them to analyse data...

  15. Soft brain-machine interfaces for assistive robotics: A novel control approach.

    Science.gov (United States)

    Schiatti, Lucia; Tessadori, Jacopo; Barresi, Giacinto; Mattos, Leonardo S; Ajoudani, Arash

    2017-07-01

    Robotic systems offer the possibility of improving the life quality of people with severe motor disabilities, enhancing the individual's degree of independence and interaction with the external environment. In this direction, the operator's residual functions must be exploited for the control of the robot movements and the underlying dynamic interaction through intuitive and effective human-robot interfaces. Towards this end, this work aims at exploring the potential of a novel Soft Brain-Machine Interface (BMI), suitable for dynamic execution of remote manipulation tasks for a wide range of patients. The interface is composed of an eye-tracking system, for an intuitive and reliable control of a robotic arm system's trajectories, and a Brain-Computer Interface (BCI) unit, for the control of the robot Cartesian stiffness, which determines the interaction forces between the robot and environment. The latter control is achieved by estimating in real-time a unidimensional index from user's electroencephalographic (EEG) signals, which provides the probability of a neutral or active state. This estimated state is then translated into a stiffness value for the robotic arm, allowing a reliable modulation of the robot's impedance. A preliminary evaluation of this hybrid interface concept provided evidence on the effective execution of tasks with dynamic uncertainties, demonstrating the great potential of this control method in BMI applications for self-service and clinical care.

  16. Translating person-centered care into practice

    DEFF Research Database (Denmark)

    Zoffmann, Vibeke; Hörnsten, Åsa; Storbækken, Solveig

    2016-01-01

    OBJECTIVE: Person-centred care [PCC] can engage people in living well with a chronic condition. However, translating PCC into practice is challenging. We aimed to compare the translational potentials of three approaches: motivational interviewing [MI], illness integration support [IIS] and guided...... tools. CONCLUSION: Each approach has a primary application: MI, when ambivalence threatens positive change; IIS, when integrating newly diagnosed chronic conditions; and GSD, when problem solving is difficult, or deadlocked. PRACTICE IMPLICATIONS: Professionals must critically consider the context...

  17. Translating English Technical Texts The Role of the Translator and the Challenges of Technological Facilities

    Directory of Open Access Journals (Sweden)

    Dana Rus

    2009-12-01

    Full Text Available The paper approaches the specific case of the technical discourse in the context of a modern world which facilitates and promotes a more and more refined diversification of specialized texts. Created, imposed, promoted and sustained by economic reasons, the translation of technical texts finds new challenges as it is confronted with the opportunities offered by the cyberspace. While being quick, available and free, online instant translation services prove to be essentially inappropriate for the translation of technical texts, where accuracy is a prerogative.

  18. Translating Alcohol Research: Opportunities and Challenges.

    Science.gov (United States)

    Batman, Angela M; Miles, Michael F

    2015-01-01

    Alcohol use disorder (AUD) and its sequelae impose a major burden on the public health of the United States, and adequate long-term control of this disorder has not been achieved. Molecular and behavioral basic science research findings are providing the groundwork for understanding the mechanisms underlying AUD and have identified multiple candidate targets for ongoing clinical trials. However, the translation of basic research or clinical findings into improved therapeutic approaches for AUD must become more efficient. Translational research is a multistage process of stream-lining the movement of basic biomedical research findings into clinical research and then to the clinical target populations. This process demands efficient bidirectional communication across basic, applied, and clinical science as well as with clinical practitioners. Ongoing work suggests rapid progress is being made with an evolving translational framework within the alcohol research field. This is helped by multiple interdisciplinary collaborative research structures that have been developed to advance translational work on AUD. Moreover, the integration of systems biology approaches with collaborative clinical studies may yield novel insights for future translational success. Finally, appreciation of genetic variation in pharmacological or behavioral treatment responses and optimal communication from bench to bedside and back may strengthen the success of translational research applications to AUD.

  19. An effective secondary decomposition approach for wind power forecasting using extreme learning machine trained by crisscross optimization

    International Nuclear Information System (INIS)

    Yin, Hao; Dong, Zhen; Chen, Yunlong; Ge, Jiafei; Lai, Loi Lei; Vaccaro, Alfredo; Meng, Anbo

    2017-01-01

    Highlights: • A secondary decomposition approach is applied in the data pre-processing. • The empirical mode decomposition is used to decompose the original time series. • IMF1 continues to be decomposed by applying wavelet packet decomposition. • Crisscross optimization algorithm is applied to train extreme learning machine. • The proposed SHD-CSO-ELM outperforms other pervious methods in the literature. - Abstract: Large-scale integration of wind energy into electric grid is restricted by its inherent intermittence and volatility. So the increased utilization of wind power necessitates its accurate prediction. The contribution of this study is to develop a new hybrid forecasting model for the short-term wind power prediction by using a secondary hybrid decomposition approach. In the data pre-processing phase, the empirical mode decomposition is used to decompose the original time series into several intrinsic mode functions (IMFs). A unique feature is that the generated IMF1 continues to be decomposed into appropriate and detailed components by applying wavelet packet decomposition. In the training phase, all the transformed sub-series are forecasted with extreme learning machine trained by our recently developed crisscross optimization algorithm (CSO). The final predicted values are obtained from aggregation. The results show that: (a) The performance of empirical mode decomposition can be significantly improved with its IMF1 decomposed by wavelet packet decomposition. (b) The CSO algorithm has satisfactory performance in addressing the premature convergence problem when applied to optimize extreme learning machine. (c) The proposed approach has great advantage over other previous hybrid models in terms of prediction accuracy.

  20. Spoken language identification based on the enhanced self-adjusting extreme learning machine approach

    Science.gov (United States)

    Tiun, Sabrina; AL-Dhief, Fahad Taha; Sammour, Mahmoud A. M.

    2018-01-01

    Spoken Language Identification (LID) is the process of determining and classifying natural language from a given content and dataset. Typically, data must be processed to extract useful features to perform LID. The extracting features for LID, based on literature, is a mature process where the standard features for LID have already been developed using Mel-Frequency Cepstral Coefficients (MFCC), Shifted Delta Cepstral (SDC), the Gaussian Mixture Model (GMM) and ending with the i-vector based framework. However, the process of learning based on extract features remains to be improved (i.e. optimised) to capture all embedded knowledge on the extracted features. The Extreme Learning Machine (ELM) is an effective learning model used to perform classification and regression analysis and is extremely useful to train a single hidden layer neural network. Nevertheless, the learning process of this model is not entirely effective (i.e. optimised) due to the random selection of weights within the input hidden layer. In this study, the ELM is selected as a learning model for LID based on standard feature extraction. One of the optimisation approaches of ELM, the Self-Adjusting Extreme Learning Machine (SA-ELM) is selected as the benchmark and improved by altering the selection phase of the optimisation process. The selection process is performed incorporating both the Split-Ratio and K-Tournament methods, the improved SA-ELM is named Enhanced Self-Adjusting Extreme Learning Machine (ESA-ELM). The results are generated based on LID with the datasets created from eight different languages. The results of the study showed excellent superiority relating to the performance of the Enhanced Self-Adjusting Extreme Learning Machine LID (ESA-ELM LID) compared with the SA-ELM LID, with ESA-ELM LID achieving an accuracy of 96.25%, as compared to the accuracy of SA-ELM LID of only 95.00%. PMID:29672546

  1. Spoken language identification based on the enhanced self-adjusting extreme learning machine approach.

    Science.gov (United States)

    Albadr, Musatafa Abbas Abbood; Tiun, Sabrina; Al-Dhief, Fahad Taha; Sammour, Mahmoud A M

    2018-01-01

    Spoken Language Identification (LID) is the process of determining and classifying natural language from a given content and dataset. Typically, data must be processed to extract useful features to perform LID. The extracting features for LID, based on literature, is a mature process where the standard features for LID have already been developed using Mel-Frequency Cepstral Coefficients (MFCC), Shifted Delta Cepstral (SDC), the Gaussian Mixture Model (GMM) and ending with the i-vector based framework. However, the process of learning based on extract features remains to be improved (i.e. optimised) to capture all embedded knowledge on the extracted features. The Extreme Learning Machine (ELM) is an effective learning model used to perform classification and regression analysis and is extremely useful to train a single hidden layer neural network. Nevertheless, the learning process of this model is not entirely effective (i.e. optimised) due to the random selection of weights within the input hidden layer. In this study, the ELM is selected as a learning model for LID based on standard feature extraction. One of the optimisation approaches of ELM, the Self-Adjusting Extreme Learning Machine (SA-ELM) is selected as the benchmark and improved by altering the selection phase of the optimisation process. The selection process is performed incorporating both the Split-Ratio and K-Tournament methods, the improved SA-ELM is named Enhanced Self-Adjusting Extreme Learning Machine (ESA-ELM). The results are generated based on LID with the datasets created from eight different languages. The results of the study showed excellent superiority relating to the performance of the Enhanced Self-Adjusting Extreme Learning Machine LID (ESA-ELM LID) compared with the SA-ELM LID, with ESA-ELM LID achieving an accuracy of 96.25%, as compared to the accuracy of SA-ELM LID of only 95.00%.

  2. Machine learning approaches to the social determinants of health in the health and retirement study.

    Science.gov (United States)

    Seligman, Benjamin; Tuljapurkar, Shripad; Rehkopf, David

    2018-04-01

    Social and economic factors are important predictors of health and of recognized importance for health systems. However, machine learning, used elsewhere in the biomedical literature, has not been extensively applied to study relationships between society and health. We investigate how machine learning may add to our understanding of social determinants of health using data from the Health and Retirement Study. A linear regression of age and gender, and a parsimonious theory-based regression additionally incorporating income, wealth, and education, were used to predict systolic blood pressure, body mass index, waist circumference, and telomere length. Prediction, fit, and interpretability were compared across four machine learning methods: linear regression, penalized regressions, random forests, and neural networks. All models had poor out-of-sample prediction. Most machine learning models performed similarly to the simpler models. However, neural networks greatly outperformed the three other methods. Neural networks also had good fit to the data ( R 2 between 0.4-0.6, versus learning models, nine variables were frequently selected or highly weighted as predictors: dental visits, current smoking, self-rated health, serial-seven subtractions, probability of receiving an inheritance, probability of leaving an inheritance of at least $10,000, number of children ever born, African-American race, and gender. Some of the machine learning methods do not improve prediction or fit beyond simpler models, however, neural networks performed well. The predictors identified across models suggest underlying social factors that are important predictors of biological indicators of chronic disease, and that the non-linear and interactive relationships between variables fundamental to the neural network approach may be important to consider.

  3. Knowledge translation of research findings

    Directory of Open Access Journals (Sweden)

    Grimshaw Jeremy M

    2012-05-01

    translation strategy is informed by an assessment of the likely barriers and facilitators. Although our evidence on the likely effectiveness of different strategies to overcome specific barriers remains incomplete, there is a range of informative systematic reviews of interventions aimed at healthcare professionals and consumers (i.e., patients, family members, and informal carers and of factors important to research use by policy makers. Summary There is a substantial (if incomplete evidence base to guide choice of knowledge translation activities targeting healthcare professionals and consumers. The evidence base on the effects of different knowledge translation approaches targeting healthcare policy makers and senior managers is much weaker but there are a profusion of innovative approaches that warrant further evaluation.

  4. Knowledge translation of research findings.

    Science.gov (United States)

    Grimshaw, Jeremy M; Eccles, Martin P; Lavis, John N; Hill, Sophie J; Squires, Janet E

    2012-05-31

    likely barriers and facilitators. Although our evidence on the likely effectiveness of different strategies to overcome specific barriers remains incomplete, there is a range of informative systematic reviews of interventions aimed at healthcare professionals and consumers (i.e., patients, family members, and informal carers) and of factors important to research use by policy makers. There is a substantial (if incomplete) evidence base to guide choice of knowledge translation activities targeting healthcare professionals and consumers. The evidence base on the effects of different knowledge translation approaches targeting healthcare policy makers and senior managers is much weaker but there are a profusion of innovative approaches that warrant further evaluation.

  5. Six questions about translational due diligence.

    Science.gov (United States)

    Selinger, Evan

    2010-04-28

    To maintain stable respect and support, translational research must be guided by appropriate ethical, social, legal, and political concerns and carry out culturally competent practices. Considering six key questions concerning due diligence will enable the translational research community to examine critically how it approaches these endeavors.

  6. New Trends outside the Translation Classroom

    Directory of Open Access Journals (Sweden)

    Silvia Martínez Martínez

    2014-09-01

    Full Text Available This paper is based on the study of different elements at the University of Granada’s Faculty of Translation and Interpreting and seeks to elaborate a prototype for a multilingual and accessible audio guide (audio description, SDHH and Spanish sign language interpretation. We defend a new methodology, one that focuses on teaching the translation process from previous museum-based learning experiences in the translation classroom using QR codes. Our main goal is to innovate translation-related teaching based on the new approaches acquired through learning workshop perspectives. In this sense, we will offer an ideal framework in developing the new concept of translation learning. This concept involves systemising a new means of learning and organising the realities of translation itself, encompassing objectives, competences, methodology and evaluation.

  7. A SUPPORT VECTOR MACHINE APPROACH FOR DEVELOPING TELEMEDICINE SOLUTIONS: MEDICAL DIAGNOSIS

    Directory of Open Access Journals (Sweden)

    Mihaela GHEORGHE

    2015-06-01

    Full Text Available Support vector machine represents an important tool for artificial neural networks techniques including classification and prediction. It offers a solution for a wide range of different issues in which cases the traditional optimization algorithms and methods cannot be applied directly due to different constraints, including memory restrictions, hidden relationships between variables, very high volume of computations that needs to be handled. One of these issues relates to medical diagnosis, a subset of the medical field. In this paper, the SVM learning algorithm is tested on a diabetes dataset and the results obtained for training with different kernel functions are presented and analyzed in order to determine a good approach from a telemedicine perspective.

  8. Neuroimaging mechanisms of change in psychotherapy for addictive behaviors: emerging translational approaches that bridge biology and behavior.

    Science.gov (United States)

    Feldstein Ewing, Sarah W; Chung, Tammy

    2013-06-01

    Research on mechanisms of behavior change provides an innovative method to improve treatment for addictive behaviors. An important extension of mechanisms of change research involves the use of translational approaches, which examine how basic biological (i.e., brain-based mechanisms) and behavioral factors interact in initiating and sustaining positive behavior change as a result of psychotherapy. Articles in this special issue include integrative conceptual reviews and innovative empirical research on brain-based mechanisms that may underlie risk for addictive behaviors and response to psychotherapy from adolescence through adulthood. Review articles discuss hypothesized mechanisms of change for cognitive and behavioral therapies, mindfulness-based interventions, and neuroeconomic approaches. Empirical articles cover a range of addictive behaviors, including use of alcohol, cigarettes, marijuana, cocaine, and pathological gambling and represent a variety of imaging approaches including fMRI, magneto-encephalography, real-time fMRI, and diffusion tensor imaging. Additionally, a few empirical studies directly examine brain-based mechanisms of change, whereas others examine brain-based indicators as predictors of treatment outcome. Finally, two commentaries discuss craving as a core feature of addiction, and the importance of a developmental approach to examining mechanisms of change. Ultimately, translational research on mechanisms of behavior change holds promise for increasing understanding of how psychotherapy may modify brain structure and functioning and facilitate the initiation and maintenance of positive treatment outcomes for addictive behaviors. 2013 APA, all rights reserved

  9. Binary translation using peephole translation rules

    Science.gov (United States)

    Bansal, Sorav; Aiken, Alex

    2010-05-04

    An efficient binary translator uses peephole translation rules to directly translate executable code from one instruction set to another. In a preferred embodiment, the translation rules are generated using superoptimization techniques that enable the translator to automatically learn translation rules for translating code from the source to target instruction set architecture.

  10. Application of target costing in machining

    Science.gov (United States)

    Gopalakrishnan, Bhaskaran; Kokatnur, Ameet; Gupta, Deepak P.

    2004-11-01

    In today's intensely competitive and highly volatile business environment, consistent development of low cost and high quality products meeting the functionality requirements is a key to a company's survival. Companies continuously strive to reduce the costs while still producing quality products to stay ahead in the competition. Many companies have turned to target costing to achieve this objective. Target costing is a structured approach to determine the cost at which a proposed product, meeting the quality and functionality requirements, must be produced in order to generate the desired profits. It subtracts the desired profit margin from the company's selling price to establish the manufacturing cost of the product. Extensive literature review revealed that companies in automotive, electronic and process industries have reaped the benefits of target costing. However target costing approach has not been applied in the machining industry, but other techniques based on Geometric Programming, Goal Programming, and Lagrange Multiplier have been proposed for application in this industry. These models follow a forward approach, by first selecting a set of machining parameters, and then determining the machining cost. Hence in this study we have developed an algorithm to apply the concepts of target costing, which is a backward approach that selects the machining parameters based on the required machining costs, and is therefore more suitable for practical applications in process improvement and cost reduction. A target costing model was developed for turning operation and was successfully validated using practical data.

  11. Coil Optimization for HTS Machines

    DEFF Research Database (Denmark)

    Mijatovic, Nenad; Jensen, Bogi Bech; Abrahamsen, Asger Bech

    An optimization approach of HTS coils in HTS synchronous machines (SM) is presented. The optimization is aimed at high power SM suitable for direct driven wind turbines applications. The optimization process was applied to a general radial flux machine with a peak air gap flux density of ~3T...... is suitable for which coil segment is presented. Thus, the performed study gives valuable input for the coil design of HTS machines ensuring optimal usage of HTS tapes....

  12. vSphere virtual machine management

    CERN Document Server

    Fitzhugh, Rebecca

    2014-01-01

    This book follows a step-by-step tutorial approach with some real-world scenarios that vSphere businesses will be required to overcome every day. This book also discusses creating and configuring virtual machines and also covers monitoring virtual machine performance and resource allocation options. This book is for VMware administrators who want to build their knowledge of virtual machine administration and configuration. It's assumed that you have some experience with virtualization administration and vSphere.

  13. Research on the proficient machine system. Theoretical part; Jukutatsu machine system no chosa kenkyu. Rironhen

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1996-03-01

    The basic theory of the proficient machine system to be developed was studied. Important proficient techniques in manufacturing industries are becoming extinct because of insufficient succession to next generation. The proficient machine system was proposed to cope with such situation. This machine system includes the mechanism for progress and evolution of techniques and sensibilities to be adaptable to environmental changes by learning and recognizing various motions such as work and process. Consequently, the basic research fields are composed of thought, learning, perception and action. This machine requires not only deigned fixed functions but also introduction of the same proficient concept as human being to be adaptable to changes in situation, purpose, time and machine`s complexity. This report explains in detail the basic concept, system principle, approaching procedure and practical elemental technologies of the proficient machine system, and also describes the future prospect. 133 refs., 110 figs., 7 tabs.

  14. Serbian translation of the 20-item toronto alexithymia scale: Psychometric properties and the new methodological approach in translating scales

    Directory of Open Access Journals (Sweden)

    Trajanović Nikola N.

    2013-01-01

    Full Text Available Introduction. Since inception of the alexithymia construct in 1970’s, there has been a continuous effort to improve both its theoretical postulates and the clinical utility through development, standardization and validation of assessment scales. Objective. The aim of this study was to validate the Serbian translation of the 20-item Toronto Alexithymia Scale (TAS-20 and to propose a new method of translation of scales with a property of temporal stability. Methods. The scale was expertly translated by bilingual medical professionals and a linguist, and given to a sample of bilingual participants from the general population who completed both the English and the Serbian version of the scale one week apart. Results. The findings showed that the Serbian version of the TAS-20 had a good internal consistency reliability regarding total scale (α=0.86, and acceptable reliability of the three factors (α=0.71-0.79. Conclusion. The analysis confirmed the validity and consistency of the Serbian translation of the scale, with observed weakness of the factorial structure consistent with studies in other languages. The results also showed that the method of utilizing a self-control bilingual subject is a useful alternative to the back-translation method, particularly in cases of linguistically and structurally sensitive scales, or in cases where a larger sample is not available. This method, dubbed as ‘forth-translation’, could be used to translate psychometric scales measuring properties which have temporal stability over the period of at least several weeks.

  15. Rethermalization of a field-reversed configuration plasma in translation experiments

    International Nuclear Information System (INIS)

    Himura, H.; Okada, S.; Sugimoto, S.; Goto, S.

    1995-01-01

    A translation experiment of field-reversed configuration (FRC) plasma is performed on the FIX machine [Shiokawa and Goto, Phys. Fluids B 5, 534 (1993)]. The translated FRC bounces between magnetic mirror fields at both ends of a confinement region. The plasma loses some of its axial kinetic energy when it is reflected by the magnetic mirror field, and eventually settles down in the confinement region. In this reflection process, the plasma temperature rises significantly. Such plasma rethermalization has been observed in OCT-L1 experiments [Ito et al., Phys. Fluids 30, 168 (1987)], but rarely in FRX-C/T experiments [Rej et al., Phys. Fluids 29, 852 (1986)]. It is found that the rethermalization depends on the relation between the plasma temperature and the translation velocity. The rethermalization occurs only in the case where the translation velocity exceeds the sound velocity. This result implies the rethermalization is caused by a shock wave induced within the FRC when the plasma is reflected by the magnetic mirror field. copyright 1995 American Institute of Physics

  16. Considerations upon the Machine Learning Technologies

    OpenAIRE

    Alin Munteanu; Cristina Ofelia Sofran

    2006-01-01

    Artificial intelligence offers superior techniques and methods by which problems from diverse domains may find an optimal solution. The Machine Learning technologies refer to the domain of artificial intelligence aiming to develop the techniques allowing the computers to “learn”. Some systems based on Machine Learning technologies tend to eliminate the necessity of the human intelligence while the others adopt a man-machine collaborative approach.

  17. Engineering in translational medicine

    CERN Document Server

    2014-01-01

    This book covers a broad area of engineering research in translational medicine. Leaders in academic institutions around the world contributed focused chapters on a broad array of topics such as: cell and tissue engineering (6 chapters), genetic and protein engineering (10 chapters), nanoengineering (10 chapters), biomedical instrumentation (4 chapters), and theranostics and other novel approaches (4 chapters). Each chapter is a stand-alone review that summarizes the state-of-the-art of the specific research area. Engineering in Translational Medicine gives readers a comprehensive and in-depth overview of a broad array of related research areas, making this an excellent reference book for scientists and students both new to engineering/translational medicine and currently working in this area.

  18. Machine learning approach for single molecule localisation microscopy.

    Science.gov (United States)

    Colabrese, Silvia; Castello, Marco; Vicidomini, Giuseppe; Del Bue, Alessio

    2018-04-01

    Single molecule localisation (SML) microscopy is a fundamental tool for biological discoveries; it provides sub-diffraction spatial resolution images by detecting and localizing "all" the fluorescent molecules labeling the structure of interest. For this reason, the effective resolution of SML microscopy strictly depends on the algorithm used to detect and localize the single molecules from the series of microscopy frames. To adapt to the different imaging conditions that can occur in a SML experiment, all current localisation algorithms request, from the microscopy users, the choice of different parameters. This choice is not always easy and their wrong selection can lead to poor performance. Here we overcome this weakness with the use of machine learning. We propose a parameter-free pipeline for SML learning based on support vector machine (SVM). This strategy requires a short supervised training that consists in selecting by the user few fluorescent molecules (∼ 10-20) from the frames under analysis. The algorithm has been extensively tested on both synthetic and real acquisitions. Results are qualitatively and quantitatively consistent with the state of the art in SML microscopy and demonstrate that the introduction of machine learning can lead to a new class of algorithms competitive and conceived from the user point of view.

  19. Point card compatible automatic vending machine for canned drink; Point card taio kan jido hanbaiki

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2000-01-10

    A point card compatible automatic vending machine for canned drinks is developed, which provides drink manufacturers with a powerful tool to acquire selling sites and attract consumers. Since the machine is equipped with a device to handle point cards, regular customers have increased and sales have picked up. A point card issuing device is also installed, and the new machine issues a point card whenever a customer wants. The drink manufacturers are evaluating high of the vending machine because it will contribute to the diffusion of the point card system and because a sales promotion campaign may be conducted through the vending machine for instance by exchanging a fully marked card with a giveaway on the spot. In the future, a bill validator (paper money identifier) will be integrated even with small size machines for the diffusion of point card compatible machines. (translated by NEDO)

  20. Empirical Studies On Machine Learning Based Text Classification Algorithms

    OpenAIRE

    Shweta C. Dharmadhikari; Maya Ingle; Parag Kulkarni

    2011-01-01

    Automatic classification of text documents has become an important research issue now days. Properclassification of text documents requires information retrieval, machine learning and Natural languageprocessing (NLP) techniques. Our aim is to focus on important approaches to automatic textclassification based on machine learning techniques viz. supervised, unsupervised and semi supervised.In this paper we present a review of various text classification approaches under machine learningparadig...

  1. The stage of change approach for implementing ergonomics advice - Translating research into practice.

    Science.gov (United States)

    Rothmore, Paul; Aylward, Paul; Oakman, Jodi; Tappin, David; Gray, Jodi; Karnon, Jonathan

    2017-03-01

    The Stage of Change (SOC) approach has been proposed as a method to improve the implementation of ergonomics advice. However, despite evidence for its efficacy there is little evidence to suggest it has been adopted by ergonomics consultants. This paper investigates barriers and facilitators to the implementation, monitoring and effectiveness of ergonomics advice and the adoption of the SOC approach in a series of focus groups and a subsequent survey of members of the Human Factors Societies of Australia and New Zealand. A proposed SOC assessment tool developed for use by ergonomics practitioners is presented. Findings from this study suggest the limited application of a SOC based approach to work-related musculoskeletal injury prevention by ergonomics practitioners is due to the absence of a suitable tool in the ergonomists' repertoire, the need for training in this approach, and their limited access to relevant research findings. The final translation of the SOC assessment tool into professional ergonomics practice will require accessible demonstration of its real-world usability to practitioners and the training of ergonomics practitioners in its application. Copyright © 2016 Elsevier Ltd. All rights reserved.

  2. Reverse hypothesis machine learning a practitioner's perspective

    CERN Document Server

    Kulkarni, Parag

    2017-01-01

    This book introduces a paradigm of reverse hypothesis machines (RHM), focusing on knowledge innovation and machine learning. Knowledge- acquisition -based learning is constrained by large volumes of data and is time consuming. Hence Knowledge innovation based learning is the need of time. Since under-learning results in cognitive inabilities and over-learning compromises freedom, there is need for optimal machine learning. All existing learning techniques rely on mapping input and output and establishing mathematical relationships between them. Though methods change the paradigm remains the same—the forward hypothesis machine paradigm, which tries to minimize uncertainty. The RHM, on the other hand, makes use of uncertainty for creative learning. The approach uses limited data to help identify new and surprising solutions. It focuses on improving learnability, unlike traditional approaches, which focus on accuracy. The book is useful as a reference book for machine learning researchers and professionals as ...

  3. Employability and Related Context Prediction Framework for University Graduands: A Machine Learning Approach

    Directory of Open Access Journals (Sweden)

    Manushi P. Wijayapala

    2016-12-01

    Full Text Available In Sri Lanka (SL, graduands’ employability remains a national issue due to the increasing number of graduates produced by higher education institutions each year. Thus, predicting the employability of university graduands can mitigate this issue since graduands can identify what qualifications or skills they need to strengthen up in order to find a job of their desired field with a good salary, before they complete the degree. The main objective of the study is to discover the plausibility of applying machine learning approach efficiently and effectively towards predicting the employability and related context of university graduands in Sri Lanka by proposing an architectural framework which consists of four modules; employment status prediction, job salary prediction, job field prediction and job relevance prediction of graduands while also comparing performance of classification algorithms under each prediction module. Series of machine learning algorithms such as C4.5, Naïve Bayes and AODE have been experimented on the Graduand Employment Census - 2014 data. A pre-processing step is proposed to overcome challenges embedded in graduand employability data and a feature selection process is proposed in order to reduce computational complexity. Additionally, parameter tuning is also done to get the most optimized parameters. More importantly, this study utilizes several types of Sampling (Oversampling, Undersampling and Ensemble (Bagging, Boosting, RF techniques as well as a newly proposed hybrid approach to overcome the limitations caused by the class imbalance phenomena. For the validation purposes, a wide range of evaluation measures was used to analyze the effectiveness of applying classification algorithms and class imbalance mitigation techniques on the dataset. The experimented results indicated that RandomForest has recorded the highest classification performance for 3 modules, achieving the selected best predictive models under hybrid

  4. Machining of glass fiber reinforced polyamide

    Directory of Open Access Journals (Sweden)

    2007-12-01

    Full Text Available The machinability of a 30 wt% glass fiber reinforced polyamide (PA was investigated by means of drilling tests. A disk was cut from an extruded rod and drilled on the flat surface: thrust was acquired during drilling at different drilling speed, feed rate and drill diameter. Differential scanning calorimetry (DSC and indentation were used to characterize PA so as to evaluate the intrinsic lack of homogeneity of the extruded material. In conclusion, it was observed that the chip formation mechanism affects the thrust dependence on the machining parameters. A traditional modeling approach is able to predict thrust only in presence of a continuous chip. In some conditions, thrust increases as drilling speed increases and feed rate decreases; this evidence suggests not to consider the general scientific approach which deals the machining of plastics in analogy with metals. Moreover, the thrust can be significantly affected by the workpiece fabrication effect, as well as by the machining parameters; therefore, the fabrication effect is not negligible in the definition of an optimum for the machining process.

  5. Dynamism in a Semiconductor Industrial Machine Allocation Problem using a Hybrid of the Bio-inspired and Musical-Harmony Approach

    Science.gov (United States)

    Kalsom Yusof, Umi; Nor Akmal Khalid, Mohd

    2015-05-01

    Semiconductor industries need to constantly adjust to the rapid pace of change in the market. Most manufactured products usually have a very short life cycle. These scenarios imply the need to improve the efficiency of capacity planning, an important aspect of the machine allocation plan known for its complexity. Various studies have been performed to balance productivity and flexibility in the flexible manufacturing system (FMS). Many approaches have been developed by the researchers to determine the suitable balance between exploration (global improvement) and exploitation (local improvement). However, not much work has been focused on the domain of machine allocation problem that considers the effects of machine breakdowns. This paper develops a model to minimize the effect of machine breakdowns, thus increasing the productivity. The objectives are to minimize system unbalance and makespan as well as increase throughput while satisfying the technological constraints such as machine time availability. To examine the effectiveness of the proposed model, results for throughput, system unbalance and makespan on real industrial datasets were performed with applications of intelligence techniques, that is, a hybrid of genetic algorithm and harmony search. The result aims to obtain a feasible solution to the domain problem.

  6. An Integrated Approach of Fuzzy Linguistic Preference Based AHP and Fuzzy COPRAS for Machine Tool Evaluation.

    Directory of Open Access Journals (Sweden)

    Huu-Tho Nguyen

    Full Text Available Globalization of business and competitiveness in manufacturing has forced companies to improve their manufacturing facilities to respond to market requirements. Machine tool evaluation involves an essential decision using imprecise and vague information, and plays a major role to improve the productivity and flexibility in manufacturing. The aim of this study is to present an integrated approach for decision-making in machine tool selection. This paper is focused on the integration of a consistent fuzzy AHP (Analytic Hierarchy Process and a fuzzy COmplex PRoportional ASsessment (COPRAS for multi-attribute decision-making in selecting the most suitable machine tool. In this method, the fuzzy linguistic reference relation is integrated into AHP to handle the imprecise and vague information, and to simplify the data collection for the pair-wise comparison matrix of the AHP which determines the weights of attributes. The output of the fuzzy AHP is imported into the fuzzy COPRAS method for ranking alternatives through the closeness coefficient. Presentation of the proposed model application is provided by a numerical example based on the collection of data by questionnaire and from the literature. The results highlight the integration of the improved fuzzy AHP and the fuzzy COPRAS as a precise tool and provide effective multi-attribute decision-making for evaluating the machine tool in the uncertain environment.

  7. Machine Learning Approach to Deconvolution of Thermal Infrared (TIR) Spectrum of Mercury Supporting MERTIS Onboard ESA/JAXA BepiColombo

    Science.gov (United States)

    Varatharajan, I.; D'Amore, M.; Maturilli, A.; Helbert, J.; Hiesinger, H.

    2018-04-01

    Machine learning approach to spectral unmixing of emissivity spectra of Mercury is carried out using endmember spectral library measured at simulated daytime surface conditions of Mercury. Study supports MERTIS payload onboard ESA/JAXA BepiColombo.

  8. Passivity-Based Control of a Class of Blondel-Park Transformable Electric Machines

    Directory of Open Access Journals (Sweden)

    Per J. Nicklasson

    1997-10-01

    Full Text Available In this paper we study the viability of extending, to the general rotating electric machine's model, the passivity-based controller method that we have developed for induction motors. In this approach the passivity (energy dissipation properties of the motor are taken advantage of at two different levels. First, we prove that the motor model can be decomposed as the feedback interconnection of two passive subsystems, which can essentially be identified with the electrical and mechanical dynamics. Then, we design a torque tracking controller that preserves passivity for the electrical subsystem, and leave the mechanical part as a "passive disturbance". In position or speed control applications this procedure naturally leads to the well known cascaded controller structure which is typically analyzed invoking time-scale separation assumptions. A key feature of the new cascaded control paradigm is that the latter arguments are obviated in the stability analysis. Our objective in this paper is to characterize a class of machines for which such a passivity-based controller solves the output feedback torque tracking problem. Roughly speaking, the class consists of machines whose nonactuated dynamics are well damped and whose electrical and mechanical dynamics can be suitably decoupled via a coordinate transformation. The first condition translates into the requirement of approximate knowledge of the rotor resistances to avoid the need of injecting high gain into the loop. The latter condition is known in the electric machines literature as Blondel-Park transformability, and in practical terms it requires that the air-gap magnetomotive force must be suitably approximated by the first harmonic in its Fourier expansion. These conditions, stemming from the construction of the machine, have a clear physical interpretation in terms of the couplings between its electrical, magnetic and mechanical dynamics, and are satisfied by a large number of practical

  9. Considerations upon the Machine Learning Technologies

    Directory of Open Access Journals (Sweden)

    Alin Munteanu

    2006-01-01

    Full Text Available Artificial intelligence offers superior techniques and methods by which problems from diverse domains may find an optimal solution. The Machine Learning technologies refer to the domain of artificial intelligence aiming to develop the techniques allowing the computers to “learn”. Some systems based on Machine Learning technologies tend to eliminate the necessity of the human intelligence while the others adopt a man-machine collaborative approach.

  10. Machining of Complex Sculptured Surfaces

    CERN Document Server

    2012-01-01

    The machining of complex sculptured surfaces is a global technological topic in modern manufacturing with relevance in both industrialized and emerging in countries particularly within the moulds and dies sector whose applications include highly technological industries such as the automotive and aircraft industry. Machining of Complex Sculptured Surfaces considers new approaches to the manufacture of moulds and dies within these industries. The traditional technology employed in the manufacture of moulds and dies combined conventional milling and electro-discharge machining (EDM) but this has been replaced with  high-speed milling (HSM) which has been applied in roughing, semi-finishing and finishing of moulds and dies with great success. Machining of Complex Sculptured Surfaces provides recent information on machining of complex sculptured surfaces including modern CAM systems and process planning for three and five axis machining as well as explanations of the advantages of HSM over traditional methods ra...

  11. Translational physiology: from molecules to public health.

    Science.gov (United States)

    Seals, Douglas R

    2013-07-15

    The term 'translational research' was coined 20 years ago and has become a guiding influence in biomedical research. It refers to a process by which the findings of basic research are extended to the clinical research setting (bench to bedside) and then to clinical practice and eventually health policy (bedside to community). It is a dynamic, multidisciplinary research approach. The concept of translational physiology applies the translational research model to the physiological sciences. It differs from the traditional areas of integrative and clinical physiology by its broad investigative scope of basic research to community health. Translational physiology offers exciting opportunities, but presently is under-developed and -utilized. A key challenge will be to expand physiological research by extending investigations to communities of patients and healthy (or at risk) individuals. This will allow bidirectional physiological investigation throughout the translational continuum: basic research observations can be studied up to the population level, and mechanisms can be assessed by 'reverse translation' in clinical research settings and preclinical models based on initial observations made in populations. Examples of translational physiology questions, experimental approaches, roadblocks and strategies for promotion are discussed. Translational physiology provides a novel framework for physiology programs and an investigational platform for physiologists to study function from molecular events to public health. It holds promise for enhancing the completeness and societal impact of our work, while further solidifying the critical role of physiology in the biomedical research enterprise.

  12. Association Rule-based Predictive Model for Machine Failure in Industrial Internet of Things

    Science.gov (United States)

    Kwon, Jung-Hyok; Lee, Sol-Bee; Park, Jaehoon; Kim, Eui-Jik

    2017-09-01

    This paper proposes an association rule-based predictive model for machine failure in industrial Internet of things (IIoT), which can accurately predict the machine failure in real manufacturing environment by investigating the relationship between the cause and type of machine failure. To develop the predictive model, we consider three major steps: 1) binarization, 2) rule creation, 3) visualization. The binarization step translates item values in a dataset into one or zero, then the rule creation step creates association rules as IF-THEN structures using the Lattice model and Apriori algorithm. Finally, the created rules are visualized in various ways for users’ understanding. An experimental implementation was conducted using R Studio version 3.3.2. The results show that the proposed predictive model realistically predicts machine failure based on association rules.

  13. Functional Correspondence between Evaluators and Abstract Machines

    DEFF Research Database (Denmark)

    Ager, Mads Stig; Biernacki, Dariusz; Danvy, Olivier

    2003-01-01

    We bridge the gap between functional evaluators and abstract machines for the λ-calculus, using closure conversion, transformation into continuation-passing style, and defunctionalization.We illustrate this approach by deriving Krivine's abstract machine from an ordinary call-by-name evaluator...... and by deriving an ordinary call-by-value evaluator from Felleisen et al.'s CEK machine. The first derivation is strikingly simpler than what can be found in the literature. The second one is new. Together, they show that Krivine's abstract machine and the CEK machine correspond to the call-by-name and call...

  14. Decoding the non-stationary neuron spike trains by dual Monte Carlo point process estimation in motor Brain Machine Interfaces.

    Science.gov (United States)

    Liao, Yuxi; Li, Hongbao; Zhang, Qiaosheng; Fan, Gong; Wang, Yiwen; Zheng, Xiaoxiang

    2014-01-01

    Decoding algorithm in motor Brain Machine Interfaces translates the neural signals to movement parameters. They usually assume the connection between the neural firings and movements to be stationary, which is not true according to the recent studies that observe the time-varying neuron tuning property. This property results from the neural plasticity and motor learning etc., which leads to the degeneration of the decoding performance when the model is fixed. To track the non-stationary neuron tuning during decoding, we propose a dual model approach based on Monte Carlo point process filtering method that enables the estimation also on the dynamic tuning parameters. When applied on both simulated neural signal and in vivo BMI data, the proposed adaptive method performs better than the one with static tuning parameters, which raises a promising way to design a long-term-performing model for Brain Machine Interfaces decoder.

  15. Understanding factors associated with the translation of cardiovascular research: a multinational case study approach

    Science.gov (United States)

    2014-01-01

    Background Funders of health research increasingly seek to understand how best to allocate resources in order to achieve maximum value from their funding. We built an international consortium and developed a multinational case study approach to assess benefits arising from health research. We used that to facilitate analysis of factors in the production of research that might be associated with translating research findings into wider impacts, and the complexities involved. Methods We built on the Payback Framework and expanded its application through conducting co-ordinated case studies on the payback from cardiovascular and stroke research in Australia, Canada and the United Kingdom. We selected a stratified random sample of projects from leading medical research funders. We devised a series of innovative steps to: minimize the effect of researcher bias; rate the level of impacts identified in the case studies; and interrogate case study narratives to identify factors that correlated with achieving high or low levels of impact. Results Twenty-nine detailed case studies produced many and diverse impacts. Over the 15 to 20 years examined, basic biomedical research has a greater impact than clinical research in terms of academic impacts such as knowledge production and research capacity building. Clinical research has greater levels of wider impact on health policies, practice, and generating health gains. There was no correlation between knowledge production and wider impacts. We identified various factors associated with high impact. Interaction between researchers and practitioners and the public is associated with achieving high academic impact and translation into wider impacts, as is basic research conducted with a clinical focus. Strategic thinking by clinical researchers, in terms of thinking through pathways by which research could potentially be translated into practice, is associated with high wider impact. Finally, we identified the complexity of

  16. Computational prediction of multidisciplinary team decision-making for adjuvant breast cancer drug therapies: a machine learning approach.

    Science.gov (United States)

    Lin, Frank P Y; Pokorny, Adrian; Teng, Christina; Dear, Rachel; Epstein, Richard J

    2016-12-01

    Multidisciplinary team (MDT) meetings are used to optimise expert decision-making about treatment options, but such expertise is not digitally transferable between centres. To help standardise medical decision-making, we developed a machine learning model designed to predict MDT decisions about adjuvant breast cancer treatments. We analysed MDT decisions regarding adjuvant systemic therapy for 1065 breast cancer cases over eight years. Machine learning classifiers with and without bootstrap aggregation were correlated with MDT decisions (recommended, not recommended, or discussable) regarding adjuvant cytotoxic, endocrine and biologic/targeted therapies, then tested for predictability using stratified ten-fold cross-validations. The predictions so derived were duly compared with those based on published (ESMO and NCCN) cancer guidelines. Machine learning more accurately predicted adjuvant chemotherapy MDT decisions than did simple application of guidelines. No differences were found between MDT- vs. ESMO/NCCN- based decisions to prescribe either adjuvant endocrine (97%, p = 0.44/0.74) or biologic/targeted therapies (98%, p = 0.82/0.59). In contrast, significant discrepancies were evident between MDT- and guideline-based decisions to prescribe chemotherapy (87%, p machine learning models. A machine learning approach based on clinicopathologic characteristics can predict MDT decisions about adjuvant breast cancer drug therapies. The discrepancy between MDT- and guideline-based decisions regarding adjuvant chemotherapy implies that certain non-clincopathologic criteria, such as patient preference and resource availability, are factored into clinical decision-making by local experts but not captured by guidelines.

  17. Pattern Recognition by Humans and Machines

    International Nuclear Information System (INIS)

    Versino, C.; )

    2015-01-01

    Data visualization is centred on new ways of processing and displaying large data sets to support pattern recognition by humans rather than by machines. The motivation for approaches based on data visualization is to encourage data exploration and curiosity by analysts. They should help formulating the right question more than addressing specific predefined issues or expectations. Translated into IAEA's terms, they should help verify the completeness of information declared to the IAEA more than their correctness. Data visualization contrasts with traditional information retrieval where one needs first to formulate a query in order to get to a narrow slice of data. Using traditional information retrieval, no one knows what is missed out. The system may fail to recall relevant data due to the way the query was formulated, or the query itself may not be the most relevant one to be asked in the first place. Examples of data visualizations relevant to safeguards will be illustrated, including new approaches for the review of surveillance images and for trade analysis. Common to these examples is the attempt to enlarge the view of the analyst on a universe of data, where context or detailed data is presented on-demand and by levels of abstraction. The paper will make reference to ongoing research and to enabling information technologies. (author)

  18. Enter the machine

    Science.gov (United States)

    Palittapongarnpim, Pantita; Sanders, Barry C.

    2018-05-01

    Quantum tomography infers quantum states from measurement data, but it becomes infeasible for large systems. Machine learning enables tomography of highly entangled many-body states and suggests a new powerful approach to this problem.

  19. Predicting diabetes mellitus using SMOTE and ensemble machine learning approach: The Henry Ford ExercIse Testing (FIT) project.

    Science.gov (United States)

    Alghamdi, Manal; Al-Mallah, Mouaz; Keteyian, Steven; Brawner, Clinton; Ehrman, Jonathan; Sakr, Sherif

    2017-01-01

    Machine learning is becoming a popular and important approach in the field of medical research. In this study, we investigate the relative performance of various machine learning methods such as Decision Tree, Naïve Bayes, Logistic Regression, Logistic Model Tree and Random Forests for predicting incident diabetes using medical records of cardiorespiratory fitness. In addition, we apply different techniques to uncover potential predictors of diabetes. This FIT project study used data of 32,555 patients who are free of any known coronary artery disease or heart failure who underwent clinician-referred exercise treadmill stress testing at Henry Ford Health Systems between 1991 and 2009 and had a complete 5-year follow-up. At the completion of the fifth year, 5,099 of those patients have developed diabetes. The dataset contained 62 attributes classified into four categories: demographic characteristics, disease history, medication use history, and stress test vital signs. We developed an Ensembling-based predictive model using 13 attributes that were selected based on their clinical importance, Multiple Linear Regression, and Information Gain Ranking methods. The negative effect of the imbalance class of the constructed model was handled by Synthetic Minority Oversampling Technique (SMOTE). The overall performance of the predictive model classifier was improved by the Ensemble machine learning approach using the Vote method with three Decision Trees (Naïve Bayes Tree, Random Forest, and Logistic Model Tree) and achieved high accuracy of prediction (AUC = 0.92). The study shows the potential of ensembling and SMOTE approaches for predicting incident diabetes using cardiorespiratory fitness data.

  20. Predicting diabetes mellitus using SMOTE and ensemble machine learning approach: The Henry Ford ExercIse Testing (FIT project.

    Directory of Open Access Journals (Sweden)

    Manal Alghamdi

    Full Text Available Machine learning is becoming a popular and important approach in the field of medical research. In this study, we investigate the relative performance of various machine learning methods such as Decision Tree, Naïve Bayes, Logistic Regression, Logistic Model Tree and Random Forests for predicting incident diabetes using medical records of cardiorespiratory fitness. In addition, we apply different techniques to uncover potential predictors of diabetes. This FIT project study used data of 32,555 patients who are free of any known coronary artery disease or heart failure who underwent clinician-referred exercise treadmill stress testing at Henry Ford Health Systems between 1991 and 2009 and had a complete 5-year follow-up. At the completion of the fifth year, 5,099 of those patients have developed diabetes. The dataset contained 62 attributes classified into four categories: demographic characteristics, disease history, medication use history, and stress test vital signs. We developed an Ensembling-based predictive model using 13 attributes that were selected based on their clinical importance, Multiple Linear Regression, and Information Gain Ranking methods. The negative effect of the imbalance class of the constructed model was handled by Synthetic Minority Oversampling Technique (SMOTE. The overall performance of the predictive model classifier was improved by the Ensemble machine learning approach using the Vote method with three Decision Trees (Naïve Bayes Tree, Random Forest, and Logistic Model Tree and achieved high accuracy of prediction (AUC = 0.92. The study shows the potential of ensembling and SMOTE approaches for predicting incident diabetes using cardiorespiratory fitness data.

  1. On the Conditioning of Machine-Learning-Assisted Turbulence Modeling

    Science.gov (United States)

    Wu, Jinlong; Sun, Rui; Wang, Qiqi; Xiao, Heng

    2017-11-01

    Recently, several researchers have demonstrated that machine learning techniques can be used to improve the RANS modeled Reynolds stress by training on available database of high fidelity simulations. However, obtaining improved mean velocity field remains an unsolved challenge, restricting the predictive capability of current machine-learning-assisted turbulence modeling approaches. In this work we define a condition number to evaluate the model conditioning of data-driven turbulence modeling approaches, and propose a stability-oriented machine learning framework to model Reynolds stress. Two canonical flows, the flow in a square duct and the flow over periodic hills, are investigated to demonstrate the predictive capability of the proposed framework. The satisfactory prediction performance of mean velocity field for both flows demonstrates the predictive capability of the proposed framework for machine-learning-assisted turbulence modeling. With showing the capability of improving the prediction of mean flow field, the proposed stability-oriented machine learning framework bridges the gap between the existing machine-learning-assisted turbulence modeling approaches and the demand of predictive capability of turbulence models in real applications.

  2. Translational genomics

    Directory of Open Access Journals (Sweden)

    Martin Kussmann

    2014-09-01

    Full Text Available The term “Translational Genomics” reflects both title and mission of this new journal. “Translational” has traditionally been understood as “applied research” or “development”, different from or even opposed to “basic research”. Recent scientific and societal developments have triggered a re-assessment of the connotation that “translational” and “basic” are either/or activities: translational research nowadays aims at feeding the best science into applications and solutions for human society. We therefore argue here basic science to be challenged and leveraged for its relevance to human health and societal benefits. This more recent approach and attitude are catalyzed by four trends or developments: evidence-based solutions; large-scale, high dimensional data; consumer/patient empowerment; and systems-level understanding.

  3. A Cognitive Approach to the Compilation of Test Materials for the Evaluation of Translator's Skills

    Directory of Open Access Journals (Sweden)

    Elena Berg

    2016-12-01

    Full Text Available A Cognitive Approach to the Compilation of Test Materials for the Evaluation of Translator's Skills This paper discusses the importance of a cognitive approach to the evaluation of translator’s skills. The authors set forth their recommendations for the compilation of test materials for the evaluation of translators’ cognitive ability.   Kognitywne podejście do kompilowania tekstów służących ocenie umiejętności tłumacza Artykuł porusza wagę kognitywnego podejścia do ewaluacji umiejętności tłumacza. Autorzy przedstawiają swoje zalecenia co do kompilowania materiałów testowych do ewaluacji kognitywnych zdolności tłumacza.

  4. An Intensional Concurrent Faithful Encoding of Turing Machines

    Directory of Open Access Journals (Sweden)

    Thomas Given-Wilson

    2014-10-01

    Full Text Available The benchmark for computation is typically given as Turing computability; the ability for a computation to be performed by a Turing Machine. Many languages exploit (indirect encodings of Turing Machines to demonstrate their ability to support arbitrary computation. However, these encodings are usually by simulating the entire Turing Machine within the language, or by encoding a language that does an encoding or simulation itself. This second category is typical for process calculi that show an encoding of lambda-calculus (often with restrictions that in turn simulates a Turing Machine. Such approaches lead to indirect encodings of Turing Machines that are complex, unclear, and only weakly equivalent after computation. This paper presents an approach to encoding Turing Machines into intensional process calculi that is faithful, reduction preserving, and structurally equivalent. The encoding is demonstrated in a simple asymmetric concurrent pattern calculus before generalised to simplify infinite terms, and to show encodings into Concurrent Pattern Calculus and Psi Calculi.

  5. ERRORS AND DIFFICULTIES IN TRANSLATING LEGAL TEXTS

    Directory of Open Access Journals (Sweden)

    Camelia, CHIRILA

    2014-11-01

    Full Text Available Nowadays the accurate translation of legal texts has become highly important as the mistranslation of a passage in a contract, for example, could lead to lawsuits and loss of money. Consequently, the translation of legal texts to other languages faces many difficulties and only professional translators specialised in legal translation should deal with the translation of legal documents and scholarly writings. The purpose of this paper is to analyze translation from three perspectives: translation quality, errors and difficulties encountered in translating legal texts and consequences of such errors in professional translation. First of all, the paper points out the importance of performing a good and correct translation, which is one of the most important elements to be considered when discussing translation. Furthermore, the paper presents an overview of the errors and difficulties in translating texts and of the consequences of errors in professional translation, with applications to the field of law. The paper is also an approach to the differences between languages (English and Romanian that can hinder comprehension for those who have embarked upon the difficult task of translation. The research method that I have used to achieve the objectives of the paper was the content analysis of various Romanian and foreign authors' works.

  6. Identifying seizure onset zone from electrocorticographic recordings: A machine learning approach based on phase locking value.

    Science.gov (United States)

    Elahian, Bahareh; Yeasin, Mohammed; Mudigoudar, Basanagoud; Wheless, James W; Babajani-Feremi, Abbas

    2017-10-01

    Using a novel technique based on phase locking value (PLV), we investigated the potential for features extracted from electrocorticographic (ECoG) recordings to serve as biomarkers to identify the seizure onset zone (SOZ). We computed the PLV between the phase of the amplitude of high gamma activity (80-150Hz) and the phase of lower frequency rhythms (4-30Hz) from ECoG recordings obtained from 10 patients with epilepsy (21 seizures). We extracted five features from the PLV and used a machine learning approach based on logistic regression to build a model that classifies electrodes as SOZ or non-SOZ. More than 96% of electrodes identified as the SOZ by our algorithm were within the resected area in six seizure-free patients. In four non-seizure-free patients, more than 31% of the identified SOZ electrodes by our algorithm were outside the resected area. In addition, we observed that the seizure outcome in non-seizure-free patients correlated with the number of non-resected SOZ electrodes identified by our algorithm. This machine learning approach, based on features extracted from the PLV, effectively identified electrodes within the SOZ. The approach has the potential to assist clinicians in surgical decision-making when pre-surgical intracranial recordings are utilized. Copyright © 2017 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

  7. Protocol for a systematic review of the use of narrative storytelling and visual-arts-based approaches as knowledge translation tools in healthcare

    Science.gov (United States)

    2013-01-01

    Background The arts are powerful, accessible forms of communication that have the potential to impart knowledge by attracting interest and developing meaningful connections. Knowledge translation aims to reduce the ‘evidence-practice’ gap by developing, implementing and evaluating strategies designed to enhance awareness and promote behavior change congruent with research evidence. Increasingly, innovative approaches such as narrative storytelling and other arts-based interventions are being investigated to bridge the growing gap between practice and research. This study is the first to systematically identify and synthesize current research on narrative storytelling and visual art to translate and disseminate health research. Methods A health research librarian will develop and implement search strategies designed to identify relevant evidence. Studies will be included if they are primary research employing narrative storytelling and/or visual art as a knowledge translation strategy in healthcare. Two reviewers will independently perform study selection, quality assessment, and data extraction using standard forms. Disagreements will be resolved through discussion or third party adjudication. Data will be grouped and analyzed by research design, type of knowledge translation strategy (that is, a narrative or visual-arts-based approach), and target audience. An overall synthesis across all studies will be conducted. Discussion The findings from this research project will describe the ‘state of the science’ regarding the use of narrative storytelling and visual art as knowledge translation strategies. This systematic review will provide critical information for: (1) researchers conducting knowledge translation intervention studies; (2) nursing, medicine, and allied healthcare professionals; (3) healthcare consumers, including patients and families; and (4) decision makers and knowledge users who are charged to increase use of the latest research in

  8. Protocol for a systematic review of the use of narrative storytelling and visual-arts-based approaches as knowledge translation tools in healthcare.

    Science.gov (United States)

    Scott, Shannon D; Brett-MacLean, Pamela; Archibald, Mandy; Hartling, Lisa

    2013-03-20

    The arts are powerful, accessible forms of communication that have the potential to impart knowledge by attracting interest and developing meaningful connections. Knowledge translation aims to reduce the 'evidence-practice' gap by developing, implementing and evaluating strategies designed to enhance awareness and promote behavior change congruent with research evidence. Increasingly, innovative approaches such as narrative storytelling and other arts-based interventions are being investigated to bridge the growing gap between practice and research. This study is the first to systematically identify and synthesize current research on narrative storytelling and visual art to translate and disseminate health research. A health research librarian will develop and implement search strategies designed to identify relevant evidence. Studies will be included if they are primary research employing narrative storytelling and/or visual art as a knowledge translation strategy in healthcare. Two reviewers will independently perform study selection, quality assessment, and data extraction using standard forms. Disagreements will be resolved through discussion or third party adjudication. Data will be grouped and analyzed by research design, type of knowledge translation strategy (that is, a narrative or visual-arts-based approach), and target audience. An overall synthesis across all studies will be conducted. The findings from this research project will describe the 'state of the science' regarding the use of narrative storytelling and visual art as knowledge translation strategies. This systematic review will provide critical information for: (1) researchers conducting knowledge translation intervention studies; (2) nursing, medicine, and allied healthcare professionals; (3) healthcare consumers, including patients and families; and (4) decision makers and knowledge users who are charged to increase use of the latest research in healthcare settings.

  9. Translating the foundational model of anatomy into french using knowledge-based and lexical methods

    Directory of Open Access Journals (Sweden)

    Merabti Tayeb

    2011-10-01

    Full Text Available Abstract Background The Foundational Model of Anatomy (FMA is the reference ontology regarding human anatomy. FMA vocabulary was integrated into the Health Multi Terminological Portal (HMTP developed by CISMeF based on the CISMeF Information System which also includes 26 other terminologies and controlled vocabularies, mainly in French. However, FMA is primarily in English. In this context, the translation of FMA English terms into French could also be useful for searching and indexing French anatomy resources. Various studies have investigated automatic methods to assist the translation of medical terminologies or create multilingual medical vocabularies. The goal of this study was to facilitate the translation of FMA vocabulary into French. Methods We compare two types of approaches to translate the FMA terms into French. The first one is UMLS-based on the conceptual information of the UMLS metathesaurus. The second method is lexically-based on several Natural Language Processing (NLP tools. Results The UMLS-based approach produced a translation of 3,661 FMA terms into French whereas the lexical approach produced a translation of 3,129 FMA terms into French. A qualitative evaluation was made on 100 FMA terms translated by each method. For the UMLS-based approach, among the 100 translations, 52% were manually rated as "very good" and only 7% translations as "bad". For the lexical approach, among the 100 translations, 47% were rated as "very good" and 20% translations as "bad". Conclusions Overall, a low rate of translations were demonstrated by the two methods. The two approaches permitted us to semi-automatically translate 3,776 FMA terms from English into French, this was to added to the existing 10,844 French FMA terms in the HMTP (4,436 FMA French terms and 6,408 FMA terms manually translated.

  10. Addictions Neuroclinical Assessment: A reverse translational approach.

    Science.gov (United States)

    Kwako, Laura E; Momenan, Reza; Grodin, Erica N; Litten, Raye Z; Koob, George F; Goldman, David

    2017-08-01

    Incentive salience, negative emotionality, and executive function are functional domains that are etiologic in the initiation and progression of addictive disorders, having been implicated in humans with addictive disorders and in animal models of addictions. Measures of these three neuroscience-based functional domains can capture much of the effects of inheritance and early exposures that lead to trait vulnerability shared across different addictive disorders. For specific addictive disorders, these measures can be supplemented by agent specific measures such as those that access pharmacodynamic and pharmacokinetic variation attributable to agent-specific gatekeeper molecules including receptors and drug-metabolizing enzymes. Herein, we focus on the translation and reverse translation of knowledge derived from animal models of addiction to the human condition via measures of neurobiological processes that are orthologous in animals and humans, and that are shared in addictions to different agents. Based on preclinical data and human studies, measures of these domains in a general framework of an Addictions Neuroclinical Assessment (ANA) can transform the assessment and nosology of addictive disorders, and can be informative for staging disease progression. We consider next steps and challenges for implementation of ANA in clinical care and research. This article is part of the Special Issue entitled "Alcoholism". Published by Elsevier Ltd.

  11. Protocol: developing a conceptual framework of patient mediated knowledge translation, systematic review using a realist approach

    OpenAIRE

    Wiljer David; Webster Fiona; Brouwers Melissa C; Légaré France; Gagliardi Anna R; Badley Elizabeth; Straus Sharon

    2011-01-01

    Abstract Background Patient involvement in healthcare represents the means by which to achieve a healthcare system that is responsive to patient needs and values. Characterization and evaluation of strategies for involving patients in their healthcare may benefit from a knowledge translation (KT) approach. The purpose of this knowledge synthesis is to develop a conceptual framework for patient-mediated KT interventions. Methods A preliminary conceptual framework for patient-mediated KT interv...

  12. Mathematically modelling the power requirement for a vertical shaft mowing machine

    Directory of Open Access Journals (Sweden)

    Jorge Simón Pérez de Corcho Fuentes

    2008-09-01

    Full Text Available This work describes a mathematical model for determining the power demand for a vertical shaft mowing machine, particularly taking into account the influence of speed on cutting power, which is different from that of other models of mowers. The influence of the apparatus’ rotation and translation speeds was simulated in determining power demand. The results showed that no chan-ges in cutting power were produced by varying the knives’ angular speed (if translation speed was constant, while cutting power became increased if translation speed was increased. Variations in angular speed, however, influenced other parameters deter-mining total power demand. Determining this vertical shaft mower’s cutting pattern led to obtaining good crop stubble quality at the mower’s lower rotation speed, hence reducing total energy requirements.

  13. Decomposition of the compound Atwood machine

    Science.gov (United States)

    Lopes Coelho, R.

    2017-11-01

    Non-standard solving strategies for the compound Atwood machine problem have been proposed. The present strategy is based on a very simple idea. Taking an Atwood machine and replacing one of its bodies by another Atwood machine, we have a compound machine. As this operation can be repeated, we can construct any compound Atwood machine. This rule of construction is transferred to a mathematical model, whereby the equations of motion are obtained. The only difference between the machine and its model is that instead of pulleys and bodies, we have reference frames that move solidarily with these objects. This model provides us with the accelerations in the non-inertial frames of the bodies, which we will use to obtain the equations of motion. This approach to the problem will be justified by the Lagrange method and exemplified by machines with six and eight bodies.

  14. PCI: A PATRAN-NASTRAN model translator

    Science.gov (United States)

    Sheerer, T. J.

    1990-01-01

    The amount of programming required to develop a PATRAN-NASTRAN translator was surprisingly small. The approach taken produced a highly flexible translator comparable with the PATNAS translator and superior to the PATCOS translator. The coding required varied from around ten lines for a shell element to around thirty for a bar element, and the time required to add a feature to the program is typically less than an hour. The use of a lookup table for element names makes the translator also applicable to other versions of NASTRAN. The saving in time as a result of using PDA's Gateway utilities was considerable. During the writing of the program it became apparent that, with a somewhat more complex structure, it would be possible to extend the element data file to contain all data required to define the translation from PATRAN to NASTRAN by mapping of data between formats. Similar data files on property, material and grid formats would produce a completely universal translator from PATRAN to any FEA program, or indeed any CAE system.

  15. Designing “Theory of Machines and Mechanisms” course on Project Based Learning approach

    DEFF Research Database (Denmark)

    Shinde, Vikas

    2013-01-01

    by the industry and the learning outcomes specified by the National Board of Accreditation (NBA), India; this course is restructured on Project Based Learning approach. A mini project is designed to suit course objectives. An objective of this paper is to discuss the rationale of this course design......Theory of Machines and Mechanisms course is one of the essential courses of Mechanical Engineering undergraduate curriculum practiced at Indian Institute. Previously, this course was taught by traditional instruction based pedagogy. In order to achieve profession specific skills demanded...... and the process followed to design a project which meets diverse objectives....

  16. Developing Evidence for Public Health Policy and Practice: The Implementation of a Knowledge Translation Approach in a Staged, Multi-Methods Study in England, 2007-09

    Science.gov (United States)

    South, Jane; Cattan, Mima

    2014-01-01

    Effective knowledge translation processes are critical for the development of evidence-based public health policy and practice. This paper reports on the design and implementation of an innovative approach to knowledge translation within a mixed methods study on lay involvement in public health programme delivery. The study design drew on…

  17. Euphemism vs explicitness: A corpus-based analysis of translated ...

    African Journals Online (AJOL)

    This article examines the governing initial norms, namely explicitness and euphemism in English source texts and Ndebele translations, focusing on how these norms influenced the strategies chosen by the Ndebele translators in the translation of taboo terms. In the article, a corpus-based approach is used to identify head ...

  18. Machine learning methods without tears: a primer for ecologists.

    Science.gov (United States)

    Olden, Julian D; Lawler, Joshua J; Poff, N LeRoy

    2008-06-01

    Machine learning methods, a family of statistical techniques with origins in the field of artificial intelligence, are recognized as holding great promise for the advancement of understanding and prediction about ecological phenomena. These modeling techniques are flexible enough to handle complex problems with multiple interacting elements and typically outcompete traditional approaches (e.g., generalized linear models), making them ideal for modeling ecological systems. Despite their inherent advantages, a review of the literature reveals only a modest use of these approaches in ecology as compared to other disciplines. One potential explanation for this lack of interest is that machine learning techniques do not fall neatly into the class of statistical modeling approaches with which most ecologists are familiar. In this paper, we provide an introduction to three machine learning approaches that can be broadly used by ecologists: classification and regression trees, artificial neural networks, and evolutionary computation. For each approach, we provide a brief background to the methodology, give examples of its application in ecology, describe model development and implementation, discuss strengths and weaknesses, explore the availability of statistical software, and provide an illustrative example. Although the ecological application of machine learning approaches has increased, there remains considerable skepticism with respect to the role of these techniques in ecology. Our review encourages a greater understanding of machin learning approaches and promotes their future application and utilization, while also providing a basis from which ecologists can make informed decisions about whether to select or avoid these approaches in their future modeling endeavors.

  19. Community-based knowledge translation: unexplored opportunities

    Directory of Open Access Journals (Sweden)

    Armstrong Rebecca

    2011-06-01

    Full Text Available Abstract Background Knowledge translation is an interactive process of knowledge exchange between health researchers and knowledge users. Given that the health system is broad in scope, it is important to reflect on how definitions and applications of knowledge translation might differ by setting and focus. Community-based organizations and their practitioners share common characteristics related to their setting, the evidence used in this setting, and anticipated outcomes that are not, in our experience, satisfactorily reflected in current knowledge translation approaches, frameworks, or tools. Discussion Community-based organizations face a distinctive set of challenges and concerns related to engaging in the knowledge translation process, suggesting a unique perspective on knowledge translation in these settings. Specifically, community-based organizations tend to value the process of working in collaboration with multi-sector stakeholders in order to achieve an outcome. A feature of such community-based collaborations is the way in which 'evidence' is conceptualized or defined by these partners, which may in turn influence the degree to which generalizable research evidence in particular is relevant and useful when balanced against more contextually-informed knowledge, such as tacit knowledge. Related to the issues of evidence and context is the desire for local information. For knowledge translation researchers, developing processes to assist community-based organizations to adapt research findings to local circumstances may be the most helpful way to advance decision making in this area. A final characteristic shared by community-based organizations is involvement in advocacy activities, a function that has been virtually ignored in traditional knowledge translation approaches. Summary This commentary is intended to stimulate further discussion in the area of community-based knowledge translation. Knowledge translation, and exchange

  20. Machine-learning approach for local classification of crystalline structures in multiphase systems

    Science.gov (United States)

    Dietz, C.; Kretz, T.; Thoma, M. H.

    2017-07-01

    Machine learning is one of the most popular fields in computer science and has a vast number of applications. In this work we will propose a method that will use a neural network to locally identify crystal structures in a mixed phase Yukawa system consisting of fcc, hcp, and bcc clusters and disordered particles similar to plasma crystals. We compare our approach to already used methods and show that the quality of identification increases significantly. The technique works very well for highly disturbed lattices and shows a flexible and robust way to classify crystalline structures that can be used by only providing particle positions. This leads to insights into highly disturbed crystalline structures.

  1. Analysis and prediction of dimensions and cost of laser micro-machining internal channel fabrication process

    Directory of Open Access Journals (Sweden)

    Brabazon D.

    2010-06-01

    Full Text Available This paper presents the utilisation of Response Surface Methodology (RSM as the prediction tool for the laser micro-machining process. Laser internal microchannels machined using pulsed Nd:YVO4 laser in polycarbonate were investigated. The experiments were carried out according to 33 factorial Design of Experiment (DoE. In this work the three input process set as control parameters were laser power, P; pulse repetition frequency, PRF; and sample translation speed, U. Measured responses were the channel width and the micro-machining operating cost per metre of produced microchannels. The responses were sufficiently predicted within the set micro-machining parameters limits. Two factorial interaction (2FI and quadratic polynomial regression equations for both responses were constructed. It is proposed that the developed prediction equations can be used to find locally optimal micro-machining process parameters under experimental and operational conditions.

  2. Teaching Translation and Interpreting 2: Insights, Aims, Visions. [Selection of] Papers from the Second Language International Conference (Elsinore, Denmark, June 4-6, 1993).

    Science.gov (United States)

    Dollerup, Cay, Ed.; Lindegaard, Annette, Ed.

    This selection of papers starts with insights into multi- and plurilingual settings, then proceeds to discussions of aims for practical work with students, and ends with visions of future developments within translation for the mass media and the impact of machine translation. Papers are: "Interpreting at the European Commission";…

  3. Thomas Merton’s poetics of translation in his letters to writers

    Directory of Open Access Journals (Sweden)

    Marcela María Raggio

    2016-05-01

    Full Text Available This article explores Thomas Merton’s poetics of translation as reflected in his letters to writers. There, Merton expresses his ideas on poetic translation, the methods and the experience of approaching foreign literature through translation. Then, a translation analysis of a sample revises the connection between Merton’s poetics and practice of translation.

  4. Mapping Translation Technology Research in Translation Studies

    DEFF Research Database (Denmark)

    Schjoldager, Anne; Christensen, Tina Paulsen; Flanagan, Marian

    2017-01-01

    section aims to improve this situation by presenting new and innovative research papers that reflect on recent technological advances and their impact on the translation profession and translators from a diversity of perspectives and using a variety of methods. In Section 2, we present translation......Due to the growing uptake of translation technology in the language industry and its documented impact on the translation profession, translation students and scholars need in-depth and empirically founded knowledge of the nature and influences of translation technology (e.g. Christensen....../Schjoldager 2010, 2011; Christensen 2011). Unfortunately, the increasing professional use of translation technology has not been mirrored within translation studies (TS) by a similar increase in research projects on translation technology (Munday 2009: 15; O’Hagan 2013; Doherty 2016: 952). The current thematic...

  5. A hybrid training approach for leaf area index estimation via Cubist and random forests machine-learning

    KAUST Repository

    McCabe, Matthew

    2017-12-06

    With an increasing volume and dimensionality of Earth observation data, enhanced integration of machine-learning methodologies is needed to effectively analyze and utilize these information rich datasets. In machine-learning, a training dataset is required to establish explicit associations between a suite of explanatory ‘predictor’ variables and the target property. The specifics of this learning process can significantly influence model validity and portability, with a higher generalization level expected with an increasing number of observable conditions being reflected in the training dataset. Here we propose a hybrid training approach for leaf area index (LAI) estimation, which harnesses synergistic attributes of scattered in-situ measurements and systematically distributed physically based model inversion results to enhance the information content and spatial representativeness of the training data. To do this, a complimentary training dataset of independent LAI was derived from a regularized model inversion of RapidEye surface reflectances and subsequently used to guide the development of LAI regression models via Cubist and random forests (RF) decision tree methods. The application of the hybrid training approach to a broad set of Landsat 8 vegetation index (VI) predictor variables resulted in significantly improved LAI prediction accuracies and spatial consistencies, relative to results relying on in-situ measurements alone for model training. In comparing the prediction capacity and portability of the two machine-learning algorithms, a pair of relatively simple multi-variate regression models established by Cubist performed best, with an overall relative mean absolute deviation (rMAD) of ∼11%, determined based on a stringent scene-specific cross-validation approach. In comparison, the portability of RF regression models was less effective (i.e., an overall rMAD of ∼15%), which was attributed partly to model saturation at high LAI in association

  6. A hybrid training approach for leaf area index estimation via Cubist and random forests machine-learning

    Science.gov (United States)

    Houborg, Rasmus; McCabe, Matthew F.

    2018-01-01

    With an increasing volume and dimensionality of Earth observation data, enhanced integration of machine-learning methodologies is needed to effectively analyze and utilize these information rich datasets. In machine-learning, a training dataset is required to establish explicit associations between a suite of explanatory 'predictor' variables and the target property. The specifics of this learning process can significantly influence model validity and portability, with a higher generalization level expected with an increasing number of observable conditions being reflected in the training dataset. Here we propose a hybrid training approach for leaf area index (LAI) estimation, which harnesses synergistic attributes of scattered in-situ measurements and systematically distributed physically based model inversion results to enhance the information content and spatial representativeness of the training data. To do this, a complimentary training dataset of independent LAI was derived from a regularized model inversion of RapidEye surface reflectances and subsequently used to guide the development of LAI regression models via Cubist and random forests (RF) decision tree methods. The application of the hybrid training approach to a broad set of Landsat 8 vegetation index (VI) predictor variables resulted in significantly improved LAI prediction accuracies and spatial consistencies, relative to results relying on in-situ measurements alone for model training. In comparing the prediction capacity and portability of the two machine-learning algorithms, a pair of relatively simple multi-variate regression models established by Cubist performed best, with an overall relative mean absolute deviation (rMAD) of ∼11%, determined based on a stringent scene-specific cross-validation approach. In comparison, the portability of RF regression models was less effective (i.e., an overall rMAD of ∼15%), which was attributed partly to model saturation at high LAI in association with

  7. A hybrid training approach for leaf area index estimation via Cubist and random forests machine-learning

    KAUST Repository

    McCabe, Matthew; McCabe, Matthew

    2017-01-01

    With an increasing volume and dimensionality of Earth observation data, enhanced integration of machine-learning methodologies is needed to effectively analyze and utilize these information rich datasets. In machine-learning, a training dataset is required to establish explicit associations between a suite of explanatory ‘predictor’ variables and the target property. The specifics of this learning process can significantly influence model validity and portability, with a higher generalization level expected with an increasing number of observable conditions being reflected in the training dataset. Here we propose a hybrid training approach for leaf area index (LAI) estimation, which harnesses synergistic attributes of scattered in-situ measurements and systematically distributed physically based model inversion results to enhance the information content and spatial representativeness of the training data. To do this, a complimentary training dataset of independent LAI was derived from a regularized model inversion of RapidEye surface reflectances and subsequently used to guide the development of LAI regression models via Cubist and random forests (RF) decision tree methods. The application of the hybrid training approach to a broad set of Landsat 8 vegetation index (VI) predictor variables resulted in significantly improved LAI prediction accuracies and spatial consistencies, relative to results relying on in-situ measurements alone for model training. In comparing the prediction capacity and portability of the two machine-learning algorithms, a pair of relatively simple multi-variate regression models established by Cubist performed best, with an overall relative mean absolute deviation (rMAD) of ∼11%, determined based on a stringent scene-specific cross-validation approach. In comparison, the portability of RF regression models was less effective (i.e., an overall rMAD of ∼15%), which was attributed partly to model saturation at high LAI in association

  8. The role of soft computing in intelligent machines.

    Science.gov (United States)

    de Silva, Clarence W

    2003-08-15

    An intelligent machine relies on computational intelligence in generating its intelligent behaviour. This requires a knowledge system in which representation and processing of knowledge are central functions. Approximation is a 'soft' concept, and the capability to approximate for the purposes of comparison, pattern recognition, reasoning, and decision making is a manifestation of intelligence. This paper examines the use of soft computing in intelligent machines. Soft computing is an important branch of computational intelligence, where fuzzy logic, probability theory, neural networks, and genetic algorithms are synergistically used to mimic the reasoning and decision making of a human. This paper explores several important characteristics and capabilities of machines that exhibit intelligent behaviour. Approaches that are useful in the development of an intelligent machine are introduced. The paper presents a general structure for an intelligent machine, giving particular emphasis to its primary components, such as sensors, actuators, controllers, and the communication backbone, and their interaction. The role of soft computing within the overall system is discussed. Common techniques and approaches that will be useful in the development of an intelligent machine are introduced, and the main steps in the development of an intelligent machine for practical use are given. An industrial machine, which employs the concepts of soft computing in its operation, is presented, and one aspect of intelligent tuning, which is incorporated into the machine, is illustrated.

  9. On Interactive Teaching Model of Translation Course Based on Wechat

    Science.gov (United States)

    Lin, Wang

    2017-01-01

    Constructivism is a theory related to knowledge and learning, focusing on learners' subjective initiative, based on which the interactive approach has been proved to play a crucial role in language learning. Accordingly, the interactive approach can also be applied to translation teaching since translation itself is a bilingual transformational…

  10. A Review of Machine Learning and Data Mining Approaches for Business Applications in Social Networks

    OpenAIRE

    Evis Trandafili; Marenglen Biba

    2013-01-01

    Social networks have an outstanding marketing value and developing data mining methods for viral marketing is a hot topic in the research community. However, most social networks remain impossible to be fully analyzed and understood due to prohibiting sizes and the incapability of traditional machine learning and data mining approaches to deal with the new dimension in the learning process related to the large-scale environment where the data are produced. On one hand, the birth and evolution...

  11. The reflection of evolving bearing faults in the stator current's extended park vector approach for induction machines

    Science.gov (United States)

    Corne, Bram; Vervisch, Bram; Derammelaere, Stijn; Knockaert, Jos; Desmet, Jan

    2018-07-01

    Stator current analysis has the potential of becoming the most cost-effective condition monitoring technology regarding electric rotating machinery. Since both electrical and mechanical faults are detected by inexpensive and robust current-sensors, measuring current is advantageous on other techniques such as vibration, acoustic or temperature analysis. However, this technology is struggling to breach into the market of condition monitoring as the electrical interpretation of mechanical machine-problems is highly complicated. Recently, the authors built a test-rig which facilitates the emulation of several representative mechanical faults on an 11 kW induction machine with high accuracy and reproducibility. Operating this test-rig, the stator current of the induction machine under test can be analyzed while mechanical faults are emulated. Furthermore, while emulating, the fault-severity can be manipulated adaptively under controllable environmental conditions. This creates the opportunity of examining the relation between the magnitude of the well-known current fault components and the corresponding fault-severity. This paper presents the emulation of evolving bearing faults and their reflection in the Extended Park Vector Approach for the 11 kW induction machine under test. The results confirm the strong relation between the bearing faults and the stator current fault components in both identification and fault-severity. Conclusively, stator current analysis increases reliability in the application as a complete, robust, on-line condition monitoring technology.

  12. Translating Big Data into Smart Data for Veterinary Epidemiology.

    Science.gov (United States)

    VanderWaal, Kimberly; Morrison, Robert B; Neuhauser, Claudia; Vilalta, Carles; Perez, Andres M

    2017-01-01

    The increasing availability and complexity of data has led to new opportunities and challenges in veterinary epidemiology around how to translate abundant, diverse, and rapidly growing "big" data into meaningful insights for animal health. Big data analytics are used to understand health risks and minimize the impact of adverse animal health issues through identifying high-risk populations, combining data or processes acting at multiple scales through epidemiological modeling approaches, and harnessing high velocity data to monitor animal health trends and detect emerging health threats. The advent of big data requires the incorporation of new skills into veterinary epidemiology training, including, for example, machine learning and coding, to prepare a new generation of scientists and practitioners to engage with big data. Establishing pipelines to analyze big data in near real-time is the next step for progressing from simply having "big data" to create "smart data," with the objective of improving understanding of health risks, effectiveness of management and policy decisions, and ultimately preventing or at least minimizing the impact of adverse animal health issues.

  13. Translating Big Data into Smart Data for Veterinary Epidemiology

    Directory of Open Access Journals (Sweden)

    Kimberly VanderWaal

    2017-07-01

    Full Text Available The increasing availability and complexity of data has led to new opportunities and challenges in veterinary epidemiology around how to translate abundant, diverse, and rapidly growing “big” data into meaningful insights for animal health. Big data analytics are used to understand health risks and minimize the impact of adverse animal health issues through identifying high-risk populations, combining data or processes acting at multiple scales through epidemiological modeling approaches, and harnessing high velocity data to monitor animal health trends and detect emerging health threats. The advent of big data requires the incorporation of new skills into veterinary epidemiology training, including, for example, machine learning and coding, to prepare a new generation of scientists and practitioners to engage with big data. Establishing pipelines to analyze big data in near real-time is the next step for progressing from simply having “big data” to create “smart data,” with the objective of improving understanding of health risks, effectiveness of management and policy decisions, and ultimately preventing or at least minimizing the impact of adverse animal health issues.

  14. Introducing Machine Learning Concepts with WEKA.

    Science.gov (United States)

    Smith, Tony C; Frank, Eibe

    2016-01-01

    This chapter presents an introduction to data mining with machine learning. It gives an overview of various types of machine learning, along with some examples. It explains how to download, install, and run the WEKA data mining toolkit on a simple data set, then proceeds to explain how one might approach a bioinformatics problem. Finally, it includes a brief summary of machine learning algorithms for other types of data mining problems, and provides suggestions about where to find additional information.

  15. Human-machine interaction in nuclear power plants

    International Nuclear Information System (INIS)

    Yoshikawa, Hidekazu

    2005-01-01

    Advanced nuclear power plants are generally large complex systems automated by computers. Whenever a rate plant emergency occurs the plant operators must cope with the emergency under severe mental stress without committing any fatal errors. Furthermore, the operators must train to improve and maintain their ability to cope with every conceivable situation, though it is almost impossible to be fully prepared for an infinite variety of situations. In view of the limited capability of operators in emergency situations, there has been a new approach to preventing the human error caused by improper human-machine interaction. The new approach has been triggered by the introduction of advanced information systems that help operators recognize and counteract plant emergencies. In this paper, the adverse effect of automation in human-machine systems is explained. The discussion then focuses on how to configure a joint human-machine system for ideal human-machine interaction. Finally, there is a new proposal on how to organize technologies that recognize the different states of such a joint human-machine system

  16. Investigation of High-Speed Cryogenic Machining Based on Finite Element Approach

    Directory of Open Access Journals (Sweden)

    Pooyan Vahidi Pashaki

    Full Text Available Abstract The simulation of cryogenic machining process because of using a three-dimensional model and high process duration time in the finite element method, have been studied rarely. In this study, to overcome this limitation, a 2.5D finite element model using the commercial finite element software ABAQUS has been developed for the cryogenic machining process and by considering more realistic assumptions, the chip formation procedure investigated. In the proposed method, the liquid nitrogen has been used as a coolant. At the modeling of friction during the interaction of tools - chip, the Coulomb law has been used. In order to simulate the behavior of plasticity and failure criterion, Johnson-Cook model was used, and unlike previous investigations, thermal and mechanical properties of materials as a function of temperature were applied to the software. After examining accuracy of the model with present experimental data, the effect of parameters such as rake angle and the cutting speed as well as dry machining of aluminum alloy by the use of coupled dynamic temperature solution has been studied. Results indicated that at the cutting velocity of 10 m/s, cryogenic cooling has caused into decreasing 60 percent of tools temperature in comparison with the dry cooling. Furthermore, a chip which has been made by cryogenic machining were connected and without fracture in contrast to dry machining.

  17. Fingerprint-Based Machine Learning Approach to Identify Potent and Selective 5-HT2BR Ligands

    Directory of Open Access Journals (Sweden)

    Krzysztof Rataj

    2018-05-01

    Full Text Available The identification of subtype-selective GPCR (G-protein coupled receptor ligands is a challenging task. In this study, we developed a computational protocol to find compounds with 5-HT2BR versus 5-HT1BR selectivity. Our approach employs the hierarchical combination of machine learning methods, docking, and multiple scoring methods. First, we applied machine learning tools to filter a large database of druglike compounds by the new Neighbouring Substructures Fingerprint (NSFP. This two-dimensional fingerprint contains information on the connectivity of the substructural features of a compound. Preselected subsets of the database were then subjected to docking calculations. The main indicators of compounds’ selectivity were their different interactions with the secondary binding pockets of both target proteins, while binding modes within the orthosteric binding pocket were preserved. The combined methodology of ligand-based and structure-based methods was validated prospectively, resulting in the identification of hits with nanomolar affinity and ten-fold to ten thousand-fold selectivities.

  18. Taking the Time. Studying language effects in the translation class

    Directory of Open Access Journals (Sweden)

    Paola Brusasco

    2016-01-01

    Full Text Available Abstract – The current translation market places growing emphasis on technological tools that assist or even replace the translator in quickly producing adequate target texts. As a person involved in cultural processes that affect public discourse and society at large, both as a practising literary translator and as a teacher of translation, I feel that academia should not only pursue market-oriented translation skills, such as procedural knowledge of computer-assisted translation (CAT-tools and machine translation (MT, but also aim at strengthening would-be translators' processes of interpretation and making them autonomous language experts, aware of both the effects generated by language and their responsibility in using it. To support my position, I will draw on cognitive linguistics and critical discourse analysis (CDA. Adopting a constructivist approach, I will then refer to works by Kiraly (2000, Venuti (2013 and Laviosa (2014, and add some methodological proposals. Students will initially work individually and in groups, focusing on source texts, their translations and comparable texts in order to identify key language items and work toward meaning. By deploying CDA analytical tools, they will discuss the role played by individual items as well as the overall effect of both STs and TTs. New source texts will then be analysed in preparation for translation. The actual translation, effect analysis and final editing, carried out as team work, will complete a cycle aimed at 1 helping students to build knowledge through experience; 2 sensitising them to the complexity of the translation process and the paramount value of meaning-making within every single context.Riassunto – Il settore della traduzione attribuisce crescente importanza a strumenti tecnologici che aiutano o sostituiscono il traduttore nella rapida produzione di testi adeguati. In qualità di traduttrice letteraria e docente, coinvolta quindi in processi culturali che possono

  19. Style and ideology in translation

    CERN Document Server

    Munday, Jeremy

    2013-01-01

    Adopting an interdisciplinary approach, this book investigates the style, or 'voice,' of English language translations of twentieth-century Latin American writing, including fiction, political speeches, and film. Existing models of stylistic analysis, supported at times by computer-assisted analysis, are developed to examine a range of works and writers, selected for their literary, cultural, and ideological importance. The style of the different translators is subjected to a close linguistic investigation within their cultural and ideological framework.

  20. Translating Linguistic Jokes for Dubbing

    Directory of Open Access Journals (Sweden)

    Elena ALEKSANDROVA

    2012-01-01

    Full Text Available This study has attempted to establish the possible ways of translating linguistic jokes whendubbing. The study is also intended to identify the most problematic cases of screen translation andthe factors which cause these problems. In order to support such an approach a corpus of 7American and British films has been compiled, including as many as 16 as their various dubbingtranslations into Russian. In the films, almost 12 instances of original linguistic jokes have beenidentified.

  1. Revisiting interaction in knowledge translation

    Directory of Open Access Journals (Sweden)

    Zackheim Lisa

    2007-10-01

    Full Text Available Abstract Background Although the study of research utilization is not new, there has been increased emphasis on the topic over the recent past. Science push models that are researcher driven and controlled and demand pull models emphasizing users/decision-maker interests have largely been abandoned in favour of more interactive models that emphasize linkages between researchers and decisionmakers. However, despite these and other theoretical and empirical advances in the area of research utilization, there remains a fundamental gap between the generation of research findings and the application of those findings in practice. Methods Using a case approach, the current study looks at the impact of one particular interaction approach to research translation used by a Canadian funding agency. Results Results suggest there may be certain conditions under which different levels of decisionmaker involvement in research will be more or less effective. Four attributes are illuminated by the current case study: stakeholder diversity, addressability/actionability of results, finality of study design and methodology, and politicization of results. Future research could test whether these or other variables can be used to specify some of the conditions under which different approaches to interaction in knowledge translation are likely to facilitate research utilization. Conclusion This work suggests that the efficacy of interaction approaches to research translation may be more limited than current theory proposes and underscores the need for more completely specified models of research utilization that can help address the slow pace of change in this area.

  2. The importance of rat social behavior for translational research : An ethological approach

    NARCIS (Netherlands)

    Peters, S.M.

    2018-01-01

    At present, the preclinical research interest in rodent social behavior is focused on its use as readout parameter in animal models for neuropsychiatric disorders (‘translational research’). However, there are some major limitations that hamper progress. Pivotal is the limited translational value of

  3. Micro machining workstation for a diode pumped Nd:YAG high brightness laser system

    NARCIS (Netherlands)

    Kleijhorst, R.A.; Offerhaus, Herman L.; Bant, P.

    1998-01-01

    A Nd:YAG micro-machining workstation that allows cutting on a scale of a few microns has been developed and operated. The system incorporates a telescope viewing system that allows control during the work and a software interface to translate AutoCad files. Some examples of the performance are

  4. Translation as secondary communication. The relevance theory ...

    African Journals Online (AJOL)

    Ernst-August Gutt started one of the greatest translation debates of the past ten years when he suggested that relevance theory holds the key to providing a unified account of translation. The bulk of the debate has been between practitioners of functional equivalence and advocates of a relevance theoretic approach to ...

  5. Transductive and matched-pair machine learning for difficult target detection problems

    Science.gov (United States)

    Theiler, James

    2014-06-01

    This paper will describe the application of two non-traditional kinds of machine learning (transductive machine learning and the more recently proposed matched-pair machine learning) to the target detection problem. The approach combines explicit domain knowledge to model the target signal with a more agnostic machine-learning approach to characterize the background. The concept is illustrated with simulated data from an elliptically-contoured background distribution, on which a subpixel target of known spectral signature but unknown spatial extent has been implanted.

  6. Classifying smoking urges via machine learning.

    Science.gov (United States)

    Dumortier, Antoine; Beckjord, Ellen; Shiffman, Saul; Sejdić, Ervin

    2016-12-01

    Smoking is the largest preventable cause of death and diseases in the developed world, and advances in modern electronics and machine learning can help us deliver real-time intervention to smokers in novel ways. In this paper, we examine different machine learning approaches to use situational features associated with having or not having urges to smoke during a quit attempt in order to accurately classify high-urge states. To test our machine learning approaches, specifically, Bayes, discriminant analysis and decision tree learning methods, we used a dataset collected from over 300 participants who had initiated a quit attempt. The three classification approaches are evaluated observing sensitivity, specificity, accuracy and precision. The outcome of the analysis showed that algorithms based on feature selection make it possible to obtain high classification rates with only a few features selected from the entire dataset. The classification tree method outperformed the naive Bayes and discriminant analysis methods, with an accuracy of the classifications up to 86%. These numbers suggest that machine learning may be a suitable approach to deal with smoking cessation matters, and to predict smoking urges, outlining a potential use for mobile health applications. In conclusion, machine learning classifiers can help identify smoking situations, and the search for the best features and classifier parameters significantly improves the algorithms' performance. In addition, this study also supports the usefulness of new technologies in improving the effect of smoking cessation interventions, the management of time and patients by therapists, and thus the optimization of available health care resources. Future studies should focus on providing more adaptive and personalized support to people who really need it, in a minimum amount of time by developing novel expert systems capable of delivering real-time interventions. Copyright © 2016 Elsevier Ireland Ltd. All rights

  7. A Hybrid Supervised/Unsupervised Machine Learning Approach to Solar Flare Prediction

    Science.gov (United States)

    Benvenuto, Federico; Piana, Michele; Campi, Cristina; Massone, Anna Maria

    2018-01-01

    This paper introduces a novel method for flare forecasting, combining prediction accuracy with the ability to identify the most relevant predictive variables. This result is obtained by means of a two-step approach: first, a supervised regularization method for regression, namely, LASSO is applied, where a sparsity-enhancing penalty term allows the identification of the significance with which each data feature contributes to the prediction; then, an unsupervised fuzzy clustering technique for classification, namely, Fuzzy C-Means, is applied, where the regression outcome is partitioned through the minimization of a cost function and without focusing on the optimization of a specific skill score. This approach is therefore hybrid, since it combines supervised and unsupervised learning; realizes classification in an automatic, skill-score-independent way; and provides effective prediction performances even in the case of imbalanced data sets. Its prediction power is verified against NOAA Space Weather Prediction Center data, using as a test set, data in the range between 1996 August and 2010 December and as training set, data in the range between 1988 December and 1996 June. To validate the method, we computed several skill scores typically utilized in flare prediction and compared the values provided by the hybrid approach with the ones provided by several standard (non-hybrid) machine learning methods. The results showed that the hybrid approach performs classification better than all other supervised methods and with an effectiveness comparable to the one of clustering methods; but, in addition, it provides a reliable ranking of the weights with which the data properties contribute to the forecast.

  8. A Behavior-Preserving Translation From FBD Design to C Implementation for Reactor Protection System Software

    International Nuclear Information System (INIS)

    Yoo, Junbeom; Kim, Euisub; Lee, Jangsoo

    2013-01-01

    Software safety for nuclear reactor protection systems (RPSs) is the most important requirement for the obtainment of permission for operation and export from government authorities, which is why it should be managed with well-experienced software development processes. The RPS software is typically modeled with function block diagrams (FBDs) in the design phase, and then mechanically translated into C programs in the implementation phase, which is finally compiled into executable machine codes and loaded on RPS hardware - PLC (Programmable Logic Controller). Whereas C Compilers are fully-verified COTS (Commercial Off-The-Shelf) software, translators from FBDs to C programs are provided by PLC vendors. Long-term experience, experiments and simulations have validated their correctness and function safety. This paper proposes a behavior-preserving translation from FBD design to C implementation for RPS software. It includes two sets of translation algorithms and rules as well as a prototype translator. We used an example of RPS software in a Korean nuclear power plant to demonstrate the correctness and effectiveness of the proposed translation

  9. A Behavior-Preserving Translation From FBD Design to C Implementation for Reactor Protection System Software

    Energy Technology Data Exchange (ETDEWEB)

    Yoo, Junbeom; Kim, Euisub [Konkuk Univ., Seoul (Korea, Republic of); Lee, Jangsoo [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2013-08-15

    Software safety for nuclear reactor protection systems (RPSs) is the most important requirement for the obtainment of permission for operation and export from government authorities, which is why it should be managed with well-experienced software development processes. The RPS software is typically modeled with function block diagrams (FBDs) in the design phase, and then mechanically translated into C programs in the implementation phase, which is finally compiled into executable machine codes and loaded on RPS hardware - PLC (Programmable Logic Controller). Whereas C Compilers are fully-verified COTS (Commercial Off-The-Shelf) software, translators from FBDs to C programs are provided by PLC vendors. Long-term experience, experiments and simulations have validated their correctness and function safety. This paper proposes a behavior-preserving translation from FBD design to C implementation for RPS software. It includes two sets of translation algorithms and rules as well as a prototype translator. We used an example of RPS software in a Korean nuclear power plant to demonstrate the correctness and effectiveness of the proposed translation.

  10. A Systems Medicine Approach: Translating Emerging Science into Individualized Wellness

    Directory of Open Access Journals (Sweden)

    J. S. Bland

    2017-01-01

    Full Text Available In today’s aging society, more people are living with lifestyle-related noncommunicable diseases (NCDs such as cardiovascular disease, type 2 diabetes, obesity, and cancer. Numerous opinion-leader organizations recommend lifestyle medicine as the first-line approach in NCD prevention and treatment. However, there is a strong need for a personalized approach as “one-size-fits-all” public health recommendations have been insufficient in addressing the interindividual differences in the diverse populations. Advancement in systems biology and the “omics” technologies has allowed comprehensive analysis of how complex biological systems are impacted upon external perturbations (e.g., nutrition and exercise, and therefore is gradually pushing personalized lifestyle medicine toward reality. Clinicians and healthcare practitioners have a unique opportunity in advocating lifestyle medicine because patients see them as a reliable source of advice. However, there are still numerous technical and logistic challenges to overcome before personal “big data” can be translated into actionable and clinically relevant solutions. Clinicians are also facing various issues prior to bringing personalized lifestyle medicine to their practice. Nevertheless, emerging ground-breaking research projects have given us a glimpse of how systems thinking and computational methods may lead to personalized health advice. It is important that all stakeholders work together to create the needed paradigm shift in healthcare before the rising epidemic of NCDs overwhelm the society, the economy, and the dated health system.

  11. Linguistic Levels of Translation: A Generic Exploration of Translation Difficulties in Literary Textual Corpus

    Directory of Open Access Journals (Sweden)

    Magda Madkour

    2016-11-01

    Full Text Available This case study research was based on a generic exploration of the translation problems that graduate students face in literary translation. Literary translation is fundamental to translation programs at higher education due to the upsurge that has occurred in publishing classical and modern literary works from various cultures. However, literary texts have special characteristics that make the process of transferring them from one language into another a daunting task. Translating literary texts is difficult even for professional translators because misinterpreting the messages of the source texts can lead to distorting the aesthetic aspects of the literary work. Students need to learn various linguistic levels of literary translation as well as strategies and methods of translation. Learning the linguistics levels of translation necessitates providing adequate training that is based on enhancing students’ cognitive abilities. Cognitive-based translation training helps students learn the procedures of solving the problems of translating sound and literary devices. Cognitive approaches are relevant to the translation process since cognition implies mental activities that students can use to understand and synthesize the literary text, and reconstruct it creatively. Therefore, the current study aimed at examining the relationship between cognitive teaching methodologies and students’ performance in literary translation. To examine this relationship, qualitative and quantitative data was collected from graduate students at the College of Languages and Translation at Imam Mohammed bin Saud Islamic University (IMAMU University, Riyadh, Saudi Arabia. In addition, corpus data was gathered from authentic literary texts including, novels, short stories, and poetry, to investigate the effect of linguistic analysis and cognitive strategies on the quality of literary translation. Quantitative data was analyzed using the Statistical Package for the

  12. A machine learning approach to understand business processes

    NARCIS (Netherlands)

    Maruster, L.

    2003-01-01

    Business processes (industries, administration, hospitals, etc.) become nowadays more and more complex and it is difficult to have a complete understanding of them. The goal of the thesis is to show that machine learning techniques can be used successfully for understanding a process on the basis of

  13. Translating BPEL to FLOWer

    DEFF Research Database (Denmark)

    Lassen, Kristian Bisgaard

    FLOWer is a case handling tool made by Pallas-Athena for process management in the service industry. BPEL on the other hand is a language for web service orchestration, and has become a de facto standard, because of its popularity, for specifying workflow processes even though that was not its...... original purpose. This paper describe an approach translating BPLE to FLOWer, or more precisely form BPEL to CHIP. where CHIP is the interchange language that FLOWer import from and export to. The aim of the translation scheme that I give is to derive a CHIP specification that is behaviorally equivalent...

  14. Translation techniques for distributed-shared memory programming models

    Energy Technology Data Exchange (ETDEWEB)

    Fuller, Douglas James [Iowa State Univ., Ames, IA (United States)

    2005-01-01

    The high performance computing community has experienced an explosive improvement in distributed-shared memory hardware. Driven by increasing real-world problem complexity, this explosion has ushered in vast numbers of new systems. Each new system presents new challenges to programmers and application developers. Part of the challenge is adapting to new architectures with new performance characteristics. Different vendors release systems with widely varying architectures that perform differently in different situations. Furthermore, since vendors need only provide a single performance number (total MFLOPS, typically for a single benchmark), they only have strong incentive initially to optimize the API of their choice. Consequently, only a fraction of the available APIs are well optimized on most systems. This causes issues porting and writing maintainable software, let alone issues for programmers burdened with mastering each new API as it is released. Also, programmers wishing to use a certain machine must choose their API based on the underlying hardware instead of the application. This thesis argues that a flexible, extensible translator for distributed-shared memory APIs can help address some of these issues. For example, a translator might take as input code in one API and output an equivalent program in another. Such a translator could provide instant porting for applications to new systems that do not support the application's library or language natively. While open-source APIs are abundant, they do not perform optimally everywhere. A translator would also allow performance testing using a single base code translated to a number of different APIs. Most significantly, this type of translator frees programmers to select the most appropriate API for a given application based on the application (and developer) itself instead of the underlying hardware.

  15. Man-machine interactions 3

    CERN Document Server

    Czachórski, Tadeusz; Kozielski, Stanisław

    2014-01-01

    Man-Machine Interaction is an interdisciplinary field of research that covers many aspects of science focused on a human and machine in conjunction.  Basic goal of the study is to improve and invent new ways of communication between users and computers, and many different subjects are involved to reach the long-term research objective of an intuitive, natural and multimodal way of interaction with machines.  The rapid evolution of the methods by which humans interact with computers is observed nowadays and new approaches allow using computing technologies to support people on the daily basis, making computers more usable and receptive to the user's needs.   This monograph is the third edition in the series and presents important ideas, current trends and innovations in  the man-machine interactions area.  The aim of this book is to introduce not only hardware and software interfacing concepts, but also to give insights into the related theoretical background. Reader is provided with a compilation of high...

  16. Use of Machine-Learning Approaches to Predict Clinical Deterioration in Critically Ill Patients: A Systematic Review

    Directory of Open Access Journals (Sweden)

    Tadashi Kamio

    2017-06-01

    Full Text Available Introduction: Early identification of patients with unexpected clinical deterioration is a matter of serious concern. Previous studies have shown that early intervention on a patient whose health is deteriorating improves the patient outcome, and machine-learning-based approaches to predict clinical deterioration may contribute to precision improvement. To date, however, no systematic review in this area is available. Methods: We completed a search on PubMed on January 22, 2017 as well as a review of the articles identified by study authors involved in this area of research following the preferred reporting items for systematic reviews and meta-analyses (PRISMA guidelines for systematic reviews. Results: Twelve articles were selected for the current study from 273 articles initially obtained from the PubMed searches. Eleven of the 12 studies were retrospective studies, and no randomized controlled trials were performed. Although the artificial neural network techniques were the most frequently used and provided high precision and accuracy, we failed to identify articles that showed improvement in the patient outcome. Limitations were reported related to generalizability, complexity of models, and technical knowledge. Conclusions: This review shows that machine-learning approaches can improve prediction of clinical deterioration compared with traditional methods. However, these techniques will require further external validation before widespread clinical acceptance can be achieved.

  17. Maintaining Sentiment Polarity in Translation of User-Generated Content

    Directory of Open Access Journals (Sweden)

    Lohar Pintu

    2017-06-01

    Full Text Available The advent of social media has shaken the very foundations of how we share information, with Twitter, Facebook, and Linkedin among many well-known social networking platforms that facilitate information generation and distribution. However, the maximum 140-character restriction in Twitter encourages users to (sometimes deliberately write somewhat informally in most cases. As a result, machine translation (MT of user-generated content (UGC becomes much more difficult for such noisy texts. In addition to translation quality being affected, this phenomenon may also negatively impact sentiment preservation in the translation process. That is, a sentence with positive sentiment in the source language may be translated into a sentence with negative or neutral sentiment in the target language. In this paper, we analyse both sentiment preservation and MT quality per se in the context of UGC, focusing especially on whether sentiment classification helps improve sentiment preservation in MT of UGC. We build four different experimental setups for tweet translation (i using a single MT model trained on the whole Twitter parallel corpus, (ii using multiple MT models based on sentiment classification, (iii using MT models including additional out-of-domain data, and (iv adding MT models based on the phrase-table fill-up method to accompany the sentiment translation models with an aim of improving MT quality and at the same time maintaining sentiment polarity preservation. Our empirical evaluation shows that despite a slight deterioration in MT quality, our system significantly outperforms the Baseline MT system (without using sentiment classification in terms of sentiment preservation. We also demonstrate that using an MT engine that conveys a sentiment different from that of the UGC can even worsen both the translation quality and sentiment preservation.

  18. Thomas Mofolo's sentence design in Chaka approached in translation

    African Journals Online (AJOL)

    considered, his main focus had been on the leaking of the information about Nandi's impregnation by ..... Folgado, V. L. “Literary Translation as a Cognitive Activity.” Aspects of ... oSAC&printsec=frontcover=onepage&q&f=false>. Segoete, E.

  19. A machine learning approach to galaxy-LSS classification - I. Imprints on halo merger trees

    Science.gov (United States)

    Hui, Jianan; Aragon, Miguel; Cui, Xinping; Flegal, James M.

    2018-04-01

    The cosmic web plays a major role in the formation and evolution of galaxies and defines, to a large extent, their properties. However, the relation between galaxies and environment is still not well understood. Here, we present a machine learning approach to study imprints of environmental effects on the mass assembly of haloes. We present a galaxy-LSS machine learning classifier based on galaxy properties sensitive to the environment. We then use the classifier to assess the relevance of each property. Correlations between galaxy properties and their cosmic environment can be used to predict galaxy membership to void/wall or filament/cluster with an accuracy of 93 per cent. Our study unveils environmental information encoded in properties of haloes not normally considered directly dependent on the cosmic environment such as merger history and complexity. Understanding the physical mechanism by which the cosmic web is imprinted in a halo can lead to significant improvements in galaxy formation models. This is accomplished by extracting features from galaxy properties and merger trees, computing feature scores for each feature and then applying support vector machine (SVM) to different feature sets. To this end, we have discovered that the shape and depth of the merger tree, formation time, and density of the galaxy are strongly associated with the cosmic environment. We describe a significant improvement in the original classification algorithm by performing LU decomposition of the distance matrix computed by the feature vectors and then using the output of the decomposition as input vectors for SVM.

  20. Using human brain activity to guide machine learning.

    Science.gov (United States)

    Fong, Ruth C; Scheirer, Walter J; Cox, David D

    2018-03-29

    Machine learning is a field of computer science that builds algorithms that learn. In many cases, machine learning algorithms are used to recreate a human ability like adding a caption to a photo, driving a car, or playing a game. While the human brain has long served as a source of inspiration for machine learning, little effort has been made to directly use data collected from working brains as a guide for machine learning algorithms. Here we demonstrate a new paradigm of "neurally-weighted" machine learning, which takes fMRI measurements of human brain activity from subjects viewing images, and infuses these data into the training process of an object recognition learning algorithm to make it more consistent with the human brain. After training, these neurally-weighted classifiers are able to classify images without requiring any additional neural data. We show that our neural-weighting approach can lead to large performance gains when used with traditional machine vision features, as well as to significant improvements with already high-performing convolutional neural network features. The effectiveness of this approach points to a path forward for a new class of hybrid machine learning algorithms which take both inspiration and direct constraints from neuronal data.

  1. Thermo-energetic design of machine tools a systemic approach to solve the conflict between power efficiency, accuracy and productivity demonstrated at the example of machining production

    CERN Document Server

    2015-01-01

    The approach to the solution within the CRC/TR 96 financed by the German Research Foundation DFG aims at measures that will allow manufacturing accuracy to be maintained under thermally unstable conditions with increased productivity, without an additional demand for energy for tempering. The challenge of research in the CRC/TR 96 derives from the attempt to satisfy the conflicting goals of reducing energy consumption and increasing accuracy and productivity in machining. In the current research performed in 19 subprojects within the scope of the CRC/TR 96, correction and compensation solutions that influence the thermo-elastic machine tool behaviour efficiently and are oriented along the thermo-elastic functional chain are explored and implemented. As part of this general objective, the following issues must be researched and engineered in an interdisciplinary setting and brought together into useful overall solutions:   1.  Providing the modelling fundamentals to calculate the heat fluxes and the resulti...

  2. Health Informatics via Machine Learning for the Clinical Management of Patients.

    Science.gov (United States)

    Clifton, D A; Niehaus, K E; Charlton, P; Colopy, G W

    2015-08-13

    To review how health informatics systems based on machine learning methods have impacted the clinical management of patients, by affecting clinical practice. We reviewed literature from 2010-2015 from databases such as Pubmed, IEEE xplore, and INSPEC, in which methods based on machine learning are likely to be reported. We bring together a broad body of literature, aiming to identify those leading examples of health informatics that have advanced the methodology of machine learning. While individual methods may have further examples that might be added, we have chosen some of the most representative, informative exemplars in each case. Our survey highlights that, while much research is taking place in this high-profile field, examples of those that affect the clinical management of patients are seldom found. We show that substantial progress is being made in terms of methodology, often by data scientists working in close collaboration with clinical groups. Health informatics systems based on machine learning are in their infancy and the translation of such systems into clinical management has yet to be performed at scale.

  3. Predicting transmission of structure-borne sound power from machines by including terminal cross-coupling

    DEFF Research Database (Denmark)

    Ohlrich, Mogens

    2011-01-01

    of translational terminals in a global plane. This paired or bi-coupled power transmission represents the simplest case of cross-coupling. The procedure and quality of the predicted transmission using this improved technique is demonstrated experimentally for an electrical motor unit with an integrated radial fan......Structure-borne sound generated by audible vibration of machines in vehicles, equipment and house-hold appliances is often a major cause of noise. Such vibration of complex machines is mostly determined and quantified by measurements. It has been found that characterization of the vibratory source...

  4. Characterization of Adrenal Lesions on Unenhanced MRI Using Texture Analysis: A Machine-Learning Approach.

    Science.gov (United States)

    Romeo, Valeria; Maurea, Simone; Cuocolo, Renato; Petretta, Mario; Mainenti, Pier Paolo; Verde, Francesco; Coppola, Milena; Dell'Aversana, Serena; Brunetti, Arturo

    2018-01-17

    Adrenal adenomas (AA) are the most common benign adrenal lesions, often characterized based on intralesional fat content as either lipid-rich (LRA) or lipid-poor (LPA). The differentiation of AA, particularly LPA, from nonadenoma adrenal lesions (NAL) may be challenging. Texture analysis (TA) can extract quantitative parameters from MR images. Machine learning is a technique for recognizing patterns that can be applied to medical images by identifying the best combination of TA features to create a predictive model for the diagnosis of interest. To assess the diagnostic efficacy of TA-derived parameters extracted from MR images in characterizing LRA, LPA, and NAL using a machine-learning approach. Retrospective, observational study. Sixty MR examinations, including 20 LRA, 20 LPA, and 20 NAL. Unenhanced T 1 -weighted in-phase (IP) and out-of-phase (OP) as well as T 2 -weighted (T 2 -w) MR images acquired at 3T. Adrenal lesions were manually segmented, placing a spherical volume of interest on IP, OP, and T 2 -w images. Different selection methods were trained and tested using the J48 machine-learning classifiers. The feature selection method that obtained the highest diagnostic performance using the J48 classifier was identified; the diagnostic performance was also compared with that of a senior radiologist by means of McNemar's test. A total of 138 TA-derived features were extracted; among these, four features were selected, extracted from the IP (Short_Run_High_Gray_Level_Emphasis), OP (Mean_Intensity and Maximum_3D_Diameter), and T 2 -w (Standard_Deviation) images; the J48 classifier obtained a diagnostic accuracy of 80%. The expert radiologist obtained a diagnostic accuracy of 73%. McNemar's test did not show significant differences in terms of diagnostic performance between the J48 classifier and the expert radiologist. Machine learning conducted on MR TA-derived features is a potential tool to characterize adrenal lesions. 4 Technical Efficacy: Stage 2 J

  5. Designing System Reforms: Using a Systems Approach to Translate Incident Analyses into Prevention Strategies

    Science.gov (United States)

    Goode, Natassia; Read, Gemma J. M.; van Mulken, Michelle R. H.; Clacy, Amanda; Salmon, Paul M.

    2016-01-01

    Advocates of systems thinking approaches argue that accident prevention strategies should focus on reforming the system rather than on fixing the “broken components.” However, little guidance exists on how organizations can translate incident data into prevention strategies that address the systemic causes of accidents. This article describes and evaluates a series of systems thinking prevention strategies that were designed in response to the analysis of multiple incidents. The study was undertaken in the led outdoor activity (LOA) sector in Australia, which delivers supervised or instructed outdoor activities such as canyoning, sea kayaking, rock climbing and camping. The design process involved workshops with practitioners, and focussed on incident data analyzed using Rasmussen's AcciMap technique. A series of reflection points based on the systemic causes of accidents was used to guide the design process, and the AcciMap technique was used to represent the prevention strategies and the relationships between them, leading to the creation of PreventiMaps. An evaluation of the PreventiMaps revealed that all of them incorporated the core principles of the systems thinking approach and many proposed prevention strategies for improving vertical integration across the LOA system. However, the majority failed to address the migration of work practices and the erosion of risk controls. Overall, the findings suggest that the design process was partially successful in helping practitioners to translate incident data into prevention strategies that addressed the systemic causes of accidents; refinement of the design process is required to focus practitioners more on designing monitoring and feedback mechanisms to support decisions at the higher levels of the system. PMID:28066296

  6. Unlocking the potential of translation for FLT

    Directory of Open Access Journals (Sweden)

    Alenka Kocbek

    2014-12-01

    Full Text Available The paper proposes unlocking the potential of translation for foreign language teaching (FLT by seeking to create synergies with the related discipline of translation science (TS. This aim is in keeping with the guidelines for language teaching provided in the Common European Framework of Languages, which introduced a model of communicative competences including communicative language competences as those which enable a person to act by drawing on specific linguistic means. First, an overview of the changing status of translation in FLT is presented – from its being considered a fundamental teaching method and basic skill in the Grammar-Translation Method, to its being all but outlawed in more recent communicative and task-based approaches, to its final rehabilitation in recent decades. It is then shown that, in the development of FLT, the parallel evolution of TS somehow failed to be acknowledged and, consequently, the opportunity to create valuable synergies between the two disciplines was missed. Following the stance of authors who have advocated the use of translation in FLT, it is argued that translation can effectively supplement the development of the four traditional language skills and, moreover, that some of the insights developed by TS can effectively be integrated into FLT as strategies aimed at enhancing leaners’ cross-cultural communicative competences. To this purpose, selected insights from TS (e.g. the functional approach and the skopos theory, the cultureme model, the theory of memes are discussed and their potential for creating synergies with FLT are explored. Finally, the paper discusses the omnipresence of different forms of translation and interpreting in contemporary societies and shows that this naturally and logically calls for a systematic inclusion of translation in FLT.

  7. The Equivalence of Translated Songs Lyrics and their Effects - The Case of Translated Ecclesial Songs

    Directory of Open Access Journals (Sweden)

    S. Suharto

    2015-01-01

    Full Text Available This study aimed at describing the equivalence of eclessial song lyrics, which belong to the content word, the meaning of the sentences and their effect on church songs. The method used in this study is descriptive and qualitative by using music, language, and interdiciline approach. The data collection method used questionnaires technique, interview, documents and content analysis. The data used are 5 documents of songs chosen purposively as the primary data. Based on the data being analyzed, the results of this study were: 1 The translated content word located in the same bars and equivalent was around 27.07%, the translated content word located in the same bars, but not equivalent was 18.34%, the translated content word located in the different bars, but equivalent was 11.79%, the translated content word located in the different bars and not equivalent was 2.62%, and the untranslated words were 4.17%. 2 The translation of equivalence beautiful lyrics showed the beauty of the song was equivalent at 17.02%, the beauty of the song was less equivalent at 29.78%, the beauty of the song was not equivalent of 61.70%. 3. The differences of structure caused the incorrect dictions or choice of words and missing words in the translated lyrics.

  8. TRANSLATING ECONOMICS TEXTBOOKS: A CASE STUDY OF EPISTEMICIDE

    Directory of Open Access Journals (Sweden)

    KARNEDI

    2015-01-01

    Full Text Available As part of discourse in the social sciences, economics textbooks written in English in which knowledge has been transferred to other languages through translation have brought a certain impact on both the target language and the target culture. In terms of ideology, this article argues about the hegemonic status of the dominant language or culture that creates socalled epistemicide or the erosion of knowledge, partly due to translation strategies adopted by the translator. Investigation is done using the corpusbased approach, theories of translation strategies and the comparative model. The study reveals that the translator in the macro-level text adopts the ideology of foreignising strategy rather than domesticating strategy when translating an economics textbook from English into Indonesian. This is supported by the use of the number of the source language-orientated translation techniques leading to two translation methods (i.e. literal translation and faithful translation adopted in the micro-level text. This research strongly supports another relevant study pertaining to the globalisation of knowledge through translation and also the translation theories of equivalence (i.e. overt and covert translation. The research findings also have some pedagogical implications on teaching English for Specific Purposes in higher education.

  9. Adiabatic translation factors in slow ion-atom collisions

    International Nuclear Information System (INIS)

    Vaaben, J.; Taulbjerg, K.

    1981-01-01

    The general properties of translation factors in slow atomic collisions are discussed. It is emphasised that an acceptable form of translation factors must be conceptually consistent with the basic underlying assumption of the molecular model; i.e. translation factors must relax adiabatically at intermediate and small internuclear separations. A simple physical argument is applied to derive a general parameter-free expression for the translation factor pertinent to an electron in a two-centre Coulomb field. Within the present approach the adiabatic translation factor is considered to be a property of the two-centre field independently of the molecular state under consideration. The generalisation to many-electron systems is therefore readily made. (author)

  10. Understanding Translation

    DEFF Research Database (Denmark)

    Schjoldager, Anne Gram; Gottlieb, Henrik; Klitgård, Ida

    Understanding Translation is designed as a textbook for courses on the theory and practice of translation in general and of particular types of translation - such as interpreting, screen translation and literary translation. The aim of the book is to help you gain an in-depth understanding...... of the phenomenon of translation and to provide you with a conceptual framework for the analysis of various aspects of professional translation. Intended readers are students of translation and languages, but the book will also be relevant for others who are interested in the theory and practice of translation...... - translators, language teachers, translation users and literary, TV and film critics, for instance. Discussions focus on translation between Danish and English....

  11. Research on Error Modelling and Identification of 3 Axis NC Machine Tools Based on Cross Grid Encoder Measurement

    International Nuclear Information System (INIS)

    Du, Z C; Lv, C F; Hong, M S

    2006-01-01

    A new error modelling and identification method based on the cross grid encoder is proposed in this paper. Generally, there are 21 error components in the geometric error of the 3 axis NC machine tools. However according our theoretical analysis, the squareness error among different guide ways affects not only the translation error component, but also the rotational ones. Therefore, a revised synthetic error model is developed. And the mapping relationship between the error component and radial motion error of round workpiece manufactured on the NC machine tools are deduced. This mapping relationship shows that the radial error of circular motion is the comprehensive function result of all the error components of link, worktable, sliding table and main spindle block. Aiming to overcome the solution singularity shortcoming of traditional error component identification method, a new multi-step identification method of error component by using the Cross Grid Encoder measurement technology is proposed based on the kinematic error model of NC machine tool. Firstly, the 12 translational error components of the NC machine tool are measured and identified by using the least square method (LSM) when the NC machine tools go linear motion in the three orthogonal planes: XOY plane, XOZ plane and YOZ plane. Secondly, the circular error tracks are measured when the NC machine tools go circular motion in the same above orthogonal planes by using the cross grid encoder Heidenhain KGM 182. Therefore 9 rotational errors can be identified by using LSM. Finally the experimental validation of the above modelling theory and identification method is carried out in the 3 axis CNC vertical machining centre Cincinnati 750 Arrow. The entire 21 error components have been successfully measured out by the above method. Research shows the multi-step modelling and identification method is very suitable for 'on machine measurement'

  12. Gentzler, Edwin. Translation, hypertext, and creativity: Contemporary translation theories. Bristol: Multilingual Matters, 2001. 232 p.

    Directory of Open Access Journals (Sweden)

    Davi S. Gonçalves

    2018-01-01

    Full Text Available Contemporary translation theories (Gentzler,2001 provides readers with a thorough historical analysis of how the notion of creativity and autonomy in what regards reading has been transformed – as well as regarding its influence towards the idea of translation. The place occupied by the translator is a place between spaces; a fluid locale where any concreteness has melted. Meaning is thus not graspable or amenable to be tamed; on the contrary, literature is about opening up more space for the wilderness to be (rediscovered. A text is many texts, a hypertext, filled in with narratives that mutually supplement one another, deconstructing and reconstructing meanings; and, within such picture, translation emerges not as an opportunity to resurrect the body of an original text, but as a phantasm of both sameness and uniqueness. What does exist cannot be seen; it is always on the run; meanings surface from liquefied pages, pages that escape our attempt of defining them for good. This is why translation can be taken as metonym: as s/he recreates the original text within the target context, the translator choose to highlight those textual elements that s/he deems relevant – those fragments of the text that have touched and determined his/her reading. The experience of translation, that goes beyond dichotomist standards (e.g. foreign/domestic, equivalent/adapted, etc., is finally taken as a profitable realm for the literary discourse to validate its impalpability. Such shift in the approach towards translation is significant because, even though the process of recreation takes place in every textual practice, tradition has been pressuring translation scholars towards the designing of guidelines and norms that, I dare say, only obstruct the task of translating.

  13. Analysis of machining and machine tools

    CERN Document Server

    Liang, Steven Y

    2016-01-01

    This book delivers the fundamental science and mechanics of machining and machine tools by presenting systematic and quantitative knowledge in the form of process mechanics and physics. It gives readers a solid command of machining science and engineering, and familiarizes them with the geometry and functionality requirements of creating parts and components in today’s markets. The authors address traditional machining topics, such as: single and multiple point cutting processes grinding components accuracy and metrology shear stress in cutting cutting temperature and analysis chatter They also address non-traditional machining, such as: electrical discharge machining electrochemical machining laser and electron beam machining A chapter on biomedical machining is also included. This book is appropriate for advanced undergraduate and graduate mechani cal engineering students, manufacturing engineers, and researchers. Each chapter contains examples, exercises and their solutions, and homework problems that re...

  14. Evaluating Translational Research: A Process Marker Model

    Science.gov (United States)

    Trochim, William; Kane, Cathleen; Graham, Mark J.; Pincus, Harold A.

    2011-01-01

    Abstract Objective: We examine the concept of translational research from the perspective of evaluators charged with assessing translational efforts. One of the major tasks for evaluators involved in translational research is to help assess efforts that aim to reduce the time it takes to move research to practice and health impacts. Another is to assess efforts that are intended to increase the rate and volume of translation. Methods: We offer an alternative to the dominant contemporary tendency to define translational research in terms of a series of discrete “phases.”Results: We contend that this phased approach has been confusing and that it is insufficient as a basis for evaluation. Instead, we argue for the identification of key operational and measurable markers along a generalized process pathway from research to practice. Conclusions: This model provides a foundation for the evaluation of interventions designed to improve translational research and the integration of these findings into a field of translational studies. Clin Trans Sci 2011; Volume 4: 153–162 PMID:21707944

  15. Downscaling of MODIS One Kilometer Evapotranspiration Using Landsat-8 Data and Machine Learning Approaches

    Directory of Open Access Journals (Sweden)

    Yinghai Ke

    2016-03-01

    Full Text Available This study presented a MODIS 8-day 1 km evapotranspiration (ET downscaling method based on Landsat 8 data (30 m and machine learning approaches. Eleven indicators including albedo, land surface temperature (LST, and vegetation indices (VIs derived from Landsat 8 data were first upscaled to 1 km resolution. Machine learning algorithms including Support Vector Regression (SVR, Cubist, and Random Forest (RF were used to model the relationship between the Landsat indicators and MODIS 8-day 1 km ET. The models were then used to predict 30 m ET based on Landsat 8 indicators. A total of thirty-two pairs of Landsat 8 images/MODIS ET data were evaluated at four study sites including two in United States and two in South Korea. Among the three models, RF produced the lowest error, with relative Root Mean Square Error (rRMSE less than 20%. Vegetation greenness related indicators such as Normalized Difference Vegetation Index (NDVI, Enhanced Vegetation Index (EVI, Soil Adjusted Vegetation Index (SAVI, and vegetation moisture related indicators such as Normalized Difference Infrared Index—Landsat 8 OLI band 7 (NDIIb7 and Normalized Difference Water Index (NDWI were the five most important features used in RF model. Temperature-based indicators were less important than vegetation greenness and moisture-related indicators because LST could have considerable variation during each 8-day period. The predicted Landsat downscaled ET had good overall agreement with MODIS ET (average rRMSE = 22% and showed a similar temporal trend as MODIS ET. Compared to the MODIS ET product, the downscaled product demonstrated more spatial details, and had better agreement with in situ ET observations (R2 = 0.56. However, we found that the accuracy of MODIS ET was the main control factor of the accuracy of the downscaled product. Improved coarse-resolution ET estimation would result in better finer-resolution estimation. This study proved the potential of using machine learning

  16. A new approach to the solution of the vacuum magnetic problem in fusion machines

    International Nuclear Information System (INIS)

    Zabeo, L.; Piccolo, F.; Sartori, F.; Albanese, R.; Cenedese, A.

    2006-01-01

    The magnetic vacuum topology reconstruction using the magnetic measurements is essential in controlling and understanding plasmas produced by fusion machines. In a wide range of the cases, the instruments to approach the problem have been designed for a specific machine and to solve a specific plasma model. Recently a new approach has been used by developing new magnetic software called Felix. The adopted solution in the design allows the use of the software not only at JET but also at different machines by simply changing a configuration file. A database describing the tokamak in the magnetic point of view is used to provide different vacuum magnetic models (polynomial, moments, filamentary) that can be solved by Felix without any recompiling or testing. In order to reduce the analysis and debugging time the software has been designed with modularity and platform independence in mind. That results in a large portability and in particular it allows use of the same code both offline and in real-time. One of the main aspects of the tool is its capability to solve different plasma models of current distribution by changing its configuration file. In order to improve the plasma magnetic reconstruction in real time a set of models has been run using Felix. An improved polynomial based model compared with the one presently used and two models using current filaments have been tested and compared. The new system has also been improved the calculation of plasma magnetic parameters. Double null configurations smooth transitions, more accurate gap and strike-point calculations, detailed boundary reconstruction are now systematically available. Felix is presently running at JET in different real-time analysis and control systems that need vacuum magnetic topology such as control of the plasma shape, the wall protection system [F.Piccolo et al.'Upgrade of the protection system for the first wall at JET in the ITER Be and W tiles prespective' this conference], the magnetic

  17. QEFSM model and Markov Algorithm for translating Quran reciting rules into Braille code

    Directory of Open Access Journals (Sweden)

    Abdallah M. Abualkishik

    2015-07-01

    Full Text Available The Holy Quran is the central religious verbal text of Islam. Muslims are expected to read, understand, and apply the teachings of the Holy Quran. The Holy Quran was translated to Braille code as a normal Arabic text without having its reciting rules included. It is obvious that the users of this transliteration will not be able to recite the Quran the right way. Through this work, Quran Braille Translator (QBT presents a specific translator to translate Quran verses and their reciting rules into the Braille code. Quran Extended Finite State Machine (QEFSM model is proposed through this study as it is able to detect the Quran reciting rules (QRR from the Quran text. Basis path testing was used to evaluate the inner work for the model by checking all the test cases for the model. Markov Algorithm (MA was used for translating the detected QRR and Quran text into the matched Braille code. The data entries for QBT are Arabic letters and diacritics. The outputs of this study are seen in the double lines of Braille symbols; the first line is the proposed Quran reciting rules and the second line is for the Quran scripts.

  18. The art and science of rotating field machines design a practical approach

    CERN Document Server

    Ostović, Vlado

    2017-01-01

    This book highlights procedures utilized by the design departments of leading global manufacturers, offering readers essential insights into the electromagnetic and thermal design of rotating field (induction and synchronous) electric machines. Further, it details the physics of the key phenomena involved in the machines’ operation, conducts a thorough analysis and synthesis of polyphase windings, and presents the tools and methods used in the evaluation of winding performance. The book develops and solves the machines’ magnetic circuits, and determines their electromagnetic forces and torques. Special attention is paid to thermal problems in electrical machines, along with fluid flow computations. With a clear emphasis on the practical aspects of electric machine design and synthesis, the author applies his nearly 40 years of professional experience with electric machine manufacturers – both as an employee and consultant – to provide readers with the tools they need to determine fluid flow parameters...

  19. Models of evaluating efficiency and risks on integration of cloud-base IT-services of the machine-building enterprise: a system approach

    Science.gov (United States)

    Razumnikov, S.; Kurmanbay, A.

    2016-04-01

    The present paper suggests a system approach to evaluation of the effectiveness and risks resulted from the integration of cloud-based services in a machine-building enterprise. This approach makes it possible to estimate a set of enterprise IT applications and choose the applications to be migrated to the cloud with regard to specific business requirements, a technological strategy and willingness to risk.

  20. A geometric approach for fault detection and isolation of stator short circuit failure in a single asynchronous machine

    KAUST Repository

    Khelouat, Samir

    2012-06-01

    This paper deals with the problem of detection and isolation of stator short-circuit failure in a single asynchronous machine using a geometric approach. After recalling the basis of the geometric approach for fault detection and isolation in nonlinear systems, we will study some structural properties which are fault detectability and isolation fault filter existence. We will then design filters for residual generation. We will consider two approaches: a two-filters structure and a single filter structure, both aiming at generating residuals which are sensitive to one fault and insensitive to the other faults. Some numerical tests will be presented to illustrate the efficiency of the method.