WorldWideScience

Sample records for machine translation approach

  1. Machine Translation

    Institute of Scientific and Technical Information of China (English)

    张严心

    2015-01-01

    As a kind of ancillary translation tool, Machine Translation has been paid increasing attention to and received different kinds of study by a great deal of researchers and scholars for a long time. To know the definition of Machine Translation and to analyse its benefits and problems are significant for translators in order to make good use of Machine Translation, and helpful to develop and consummate Machine Translation Systems in the future.

  2. ARABIC-MALAY MACHINE TRANSLATION USING RULE-BASED APPROACH

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    Ahmed Jumaa Alsaket

    2014-01-01

    Full Text Available Arabic machine translation has been taking place in machine translation projects in recent years. This study concentrates on the translation of Arabic text to its equivalent in Malay language. The problem of this research is the syntactic and morphological differences between Arabic and Malay adjective sentences. The main aim of this study is to design and develop Arabic-Malay machine translation model. First, we analyze the adjective role in the Arabic and Malay languages. Based on this analysis, we identify the transfer bilingual rules form source language to target language so that the translation of source language to target language can be performed by computers successfully. Then, we build and implement a machine translation prototype called AMTS to translate from Arabic to Malay based on rule based approach. The system is evaluated on set of simple Arabic sentences. The techniques used to evaluate the correctness of the system translation are the BLEU metric algorithm and the human judgment. The results of the BLEU algorithm show that the AMTS system performs better than Google in the translation of Arabic sentences into Malay. In addition, the average accuracy given by human judges is 92.3% for our system and 75.3% for Google.

  3. 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.

  4. Urdu to Punjabi Machine Translation: An Incremental Training Approach

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    Umrinderpal Singh

    2016-04-01

    Full Text Available The statistical machine translation approach is highly popular in automatic translation research area and promising approach to yield good accuracy. Efforts have been made to develop Urdu to Punjabi statistical machine translation system. The system is based on an incremental training approach to train the statistical model. In place of the parallel sentences corpus has manually mapped phrases which were used to train the model. In preprocessing phase, various rules were used for tokenization and segmentation processes. Along with these rules, text classification system was implemented to classify input text to predefined classes and decoder translates given text according to selected domain by the text classifier. The system used Hidden Markov Model(HMM for the learning process and Viterbi algorithm has been used for decoding. Experiment and evaluation have shown that simple statistical model like HMM yields good accuracy for a closely related language pair like Urdu-Punjabi. The system has achieved 0.86 BLEU score and in manual testing and got more than 85% accuracy.

  5. On the Properties of Neural Machine Translation: Encoder-Decoder Approaches

    OpenAIRE

    Cho, Kyunghyun; van Merrienboer, Bart; Bahdanau, Dzmitry; Bengio, Yoshua

    2014-01-01

    Neural machine translation is a relatively new approach to statistical machine translation based purely on neural networks. The neural machine translation models often consist of an encoder and a decoder. The encoder extracts a fixed-length representation from a variable-length input sentence, and the decoder generates a correct translation from this representation. In this paper, we focus on analyzing the properties of the neural machine translation using two models; RNN Encoder--Decoder and...

  6. Topic-aware pivot language approach for statistical machine translation

    Institute of Scientific and Technical Information of China (English)

    Jin-song SU; Xiao-dong SHI; Yan-zhou HUANG; Yang LIU; Qing-qiang WU; Yi-dong CHEN; Huai-lin DONG

    2014-01-01

    The pivot language approach for statistical machine translation (SMT) is a good method to break the resource bottleneck for certain language pairs. However, in the implementation of conventional approaches, pivot-side context information is far from fully utilized, resulting in erroneous estimations of translation probabilities. In this study, we propose two topic-aware pivot language approaches to use different levels of pivot-side context. The fi rst method takes advantage of document-level context by assuming that the bridged phrase pairs should be similar in the document-level topic distributions. The second method focuses on the effect of local context. Central to this approach are that the phrase sense can be refl ected by local context in the form of probabilistic topics, and that bridged phrase pairs should be compatible in the latent sense distributions. Then, we build an interpolated model bringing the above methods together to further enhance the system performance. Experimental results on French-Spanish and French-German translations using English as the pivot language demonstrate the effectiveness of topic-based context in pivot-based SMT.

  7. Approaches to handle scarce resources for Bengali statistical machine translation

    OpenAIRE

    Roy, Maxim

    2010-01-01

    Machine translation (MT) is a hard problem because of the highly complex, irregular and diverse nature of natural language. MT refers to computerized systems that utilize software to translate text from one natural language into another with or without human assistance. It is impossible to accurately model all the linguistic rules and relationships that shape the translation process, and therefore MT has to make decisions based on incomplete data. In order to handle this incomplete data, a pr...

  8. A discourse based approach in text-based machine translation

    CERN Document Server

    Ullah, Sana; Kwak, Kyung Sup

    2009-01-01

    This paper presents a theoretical research based approach to ellipsis resolution in machine translation. Moreover, the formula of discourse is applied in order to resolve ellipses. The validity of the discourse formula is analyzed by applying it to the real world text i.e. newspaper fragments. The source text is converted into mono-sentential discourses where complex discourses require further dissection either directly into primitive discourses or first into compound discourses and later into primitive ones. The procedure of dissection needs further improvement i.e. discovering as many primitive discourse forms as possible [1]. This work is further improvement to the concepts presented by Khan (Khan, 1995). Likewise, an attempt has been made to investigate new primitive discourses i.e. patterns from the given text.

  9. Machine Translation Approaches and Survey for Indian Languages

    OpenAIRE

    Khan, Nadeem Jadoon; Anwar, Waqas; Durrani, Nadir

    2017-01-01

    In this study, we present an analysis regarding the performance of the state-of-art Phrase-based Statistical Machine Translation (SMT) on multiple Indian languages. We report baseline systems on several language pairs. The motivation of this study is to promote the development of SMT and linguistic resources for these language pairs, as the current state-of-the-art is quite bleak due to sparse data resources. The success of an SMT system is contingent on the availability of a large parallel c...

  10. A Lexical Conceptual Approach to Generation for Machine Translation

    Science.gov (United States)

    1988-01-01

    etc.). Once a verb has been selected to translate the predicate, the semantic arguments of the deep structure are filled with the instantiated...8217strid iii ts oft it, argumtents. Two examples are t he E nglish words shish and stil ilr: (4) (i) He slashed the woman * ’Dio cuchilladas a la mujer ...are simplified once rules and general inferencing are eliminated: LCS and $-role mappings obviate the need for complicated network searches and rule

  11. 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…

  12. A Novel Approach for English to South Dravidian Language Statistical Machine Translation System

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    Unnikrishnan P

    2010-11-01

    Full Text Available Development of a well fledged bilingual machine translation (MT system for any two natural languages with limited electronic resources and tools is a challenging and demanding task. This paper presents the development of a statistical machine translation (SMT system for English to South Dravidian languages like Malayalam and Kannada by incorporating syntactic and morphological information. SMT is a data oriented statistical framework for translating text from one natural language to another based on the knowledge extracted from bilingual corpus. Even though there are efforts towards building such an English to South Dravidian translation system ,unfortunately we do not have an efficient translation system till now. The first and most important step in SMT is creating a well aligned parallel corpus for training the system. Experimental research shows that the existing methodology for bilingual parallel corpus creation is not efficient for English to South Dravidian language in the SMT system. In order toincrease the performance of the translation system, we have introduced a new approach in creating parallel corpus. The mainideas which we have implemented and proven very effective forEnglish to south Dravidian languages SMT system are: (i reordering the English source sentence according to Dravidian syntax, (ii using the root suffix separation on both English and Dravidian words and iii use of morphological information which substantially reduce the corpus size required for training the system. Since the navailability of full fledged parsing and morphological tools for Malayalam and Kannada languages, sentence synthesis was done both manually and existing morph analyzer created by Amrita university. From the experiment we found that the performance of our systems are significantly well and achieves a very competitive accuracy for small sized bilingual corpora. The proposed ideas can be directly used for other south Dravidian languages like Tamil

  13. Evaluating Arabic to English Machine Translation

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    Laith S. Hadla

    2014-11-01

    Full Text Available Online text machine translation systems are widely used throughout the world freely. Most of these systems use statistical machine translation (SMT that is based on a corpus full with translation examples to learn from them how to translate correctly. Online text machine translation systems differ widely in their effectiveness, and therefore we have to fairly evaluate their effectiveness. Generally the manual (human evaluation of machine translation (MT systems is better than the automatic evaluation, but it is not feasible to be used. The distance or similarity of MT candidate output to a set of reference translations are used by many MT evaluation approaches. This study presents a comparison of effectiveness of two free online machine translation systems (Google Translate and Babylon machine translation system to translate Arabic to English. There are many automatic methods used to evaluate different machine translators, one of these methods; Bilingual Evaluation Understudy (BLEU method. BLEU is used to evaluate translation quality of two free online machine translation systems under consideration. A corpus consists of more than 1000 Arabic sentences with two reference English translations for each Arabic sentence is used in this study. This corpus of Arabic sentences and their English translations consists of 4169 Arabic words, where the number of unique Arabic words is 2539. This corpus is released online to be used by researchers. These Arabic sentences are distributed among four basic sentence functions (declarative, interrogative, exclamatory, and imperative. The experimental results show that Google machine translation system is better than Babylon machine translation system in terms of precision of translation from Arabic to English.

  14. Clinical utility of machine learning approaches in schizophrenia: Improving diagnostic confidence for translational neuroimaging

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    Sarina eIwabuchi

    2013-08-01

    Full Text Available Machine-learning approaches are becoming commonplace in the neuroimaging literature as potential diagnostic and prognostic tools for the study of clinical populations. However, very few studies provide clinically informative measures to aid in decision-making and resource allocation. Head-to-head comparison of neuroimaging-based multivariate classifiers is an essential first step to promote translation of these tools to clinical practice. We systematically evaluated the classifier performance using back-to-back structural MRI in two field strengths (3-Tesla and 7-Tesla to discriminate patients with schizophrenia (n=19 from healthy controls (n=20. Grey (GM and white matter (WM images were used as inputs into a support vector machine (SVM to classify patients and control subjects. 7T classifiers outperformed the 3T classifiers with accuracy reaching as high as 77% for the 7T GM classifier compared to 66.6% for the 3T GM classifier. Furthermore, diagnostic odds ratio (a measure that is not affected by variations in sample characteristics and number needed to predict (a measure based on Bayesian certainty of a test result indicated superior performance of the 7T classifiers, whereby for each correct diagnosis made, the number of patients that need to be examined using the 7T GM classifier was one less than the number that need to be examined if a different classifier was used. Using a hypothetical example, we highlight how these findings could have significant implications for clinical decision-making. We encourage the reporting of measures proposed here in future studies utilizing machine-learning approaches. This will not only promote the search for an optimum diagnostic tool but also aid in the translation of neuroimaging to clinical use.

  15. 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...... determines communication process largely, our data indicates communication relies more on a dynamic process where participants establish common ground than on reproducibility and grammatical accuracy.......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...

  16. 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 set...

  17. Discriminative syntactic reranking for statistical machine translation

    NARCIS (Netherlands)

    Carter, S.; Monz, C.

    2010-01-01

    This paper describes a method that successfully exploits simple syntactic features for n-best translation candidate reranking using perceptrons. Our approach uses discriminative language modelling to rerank the n-best translations generated by a statistical machine translation system. The performanc

  18. On Using Very Large Target Vocabulary for Neural Machine Translation

    OpenAIRE

    Jean, Sébastien; Cho, Kyunghyun; Memisevic, Roland; Bengio, Yoshua

    2014-01-01

    Neural machine translation, a recently proposed approach to machine translation based purely on neural networks, has shown promising results compared to the existing approaches such as phrase-based statistical machine translation. Despite its recent success, neural machine translation has its limitation in handling a larger vocabulary, as training complexity as well as decoding complexity increase proportionally to the number of target words. In this paper, we propose a method that allows us ...

  19. Offering a New Approach for Approximate Pattern Matching in Example-Based Machine Translation

    Directory of Open Access Journals (Sweden)

    Reza Akbari

    2015-01-01

    Full Text Available In this article, a new model is proposed in order to measure the degree of similarity between two sentences in machine translation based on example. The proposed model has applied genetic algorithm beside a new fitness function which is based on semantic load matching between the two sentences. Here, verbs are considered as the heart of a sentence because they are the main part of a sentence and carry the major part of the semantic load in the sentence; therefore more attention is paid to the verbs in the fitness function. It is noteworthy that the proposed model is largely dependent on the verbal part and the extracted synonyms from WordNet as well as the arrangement of words. The results are promising by precision and recall, indicating that the proposed method improves the quality of the retrieved matched sentences.

  20. 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,

  1. 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 set...... of post-editing effort, namely i) temporal (time), ii) cognitive (mental processes) and iii) technical (keyboard activity). For the purposes of this research, TER scores were correlated with two different indicators of post-editing effort as computed in the CRITT Translation Process Database (TPR......-DB) *. On the one hand, post-editing temporal effort was measured using FDur values (duration of segment production time excluding keystroke pauses >_ 200 seconds) and KDur values (duration of coherent keyboard activity excluding keystroke pauses >_ 5 seconds). On the other hand, post-editing technical effort...

  2. 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

  3. Unraveling the Contribution of Image Captioning and Neural Machine Translation for Multimodal Machine Translation

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    Lala Chiraag

    2017-06-01

    Full Text Available Recent work on multimodal machine translation has attempted to address the problem of producing target language image descriptions based on both the source language description and the corresponding image. However, existing work has not been conclusive on the contribution of visual information. This paper presents an in-depth study of the problem by examining the differences and complementarities of two related but distinct approaches to this task: textonly neural machine translation and image captioning. We analyse the scope for improvement and the effect of different data and settings to build models for these tasks. We also propose ways of combining these two approaches for improved translation quality.

  4. On automatic machine translation evaluation

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    Darinka Verdonik

    2013-05-01

    Full Text Available An important task of developing machine translation (MT is evaluating system performance. Automatic measures are most commonly used for this task, as manual evaluation is time-consuming and costly. However, to perform an objective evaluation is not a trivial task. Automatic measures, such as BLEU, TER, NIST, METEOR etc., have their own weaknesses, while manual evaluations are also problematic since they are always to some extent subjective. In this paper we test the influence of a test set on the results of automatic MT evaluation for the subtitling domain. Translating subtitles is a rather specific task for MT, since subtitles are a sort of summarization of spoken text rather than a direct translation of (written text. Additional problem when translating language pair that does not include English, in our example Slovene-Serbian, is that commonly the translations are done from English to Serbian and from English to Slovenian, and not directly, since most of the TV production is originally filmed in English. All this poses additional challenges to MT and consequently to MT evaluation. Automatic evaluation is based on a reference translation, which is usually taken from an existing parallel corpus and marked as a test set. In our experiments, we compare the evaluation results for the same MT system output using three types of test set. In the first round, the test set are 4000 subtitles from the parallel corpus of subtitles SUMAT. These subtitles are not direct translations from Serbian to Slovene or vice versa, but are based on an English original. In the second round, the test set are 1000 subtitles randomly extracted from the first test set and translated anew, from Serbian to Slovenian, based solely on the Serbian written subtitles. In the third round, the test set are the same 1000 subtitles, however this time the Slovene translations were obtained by manually correcting the Slovene MT outputs so that they are correct translations of the

  5. 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…

  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. Adding Statistical Machine Translation Adaptation to Computer-Assisted Translation

    Science.gov (United States)

    2013-09-01

    on Telecommunications. Tehran, 2012, 822–826. Bertoldi, N.; Federico, M. Domain Adaptation for Statistical Machine Translation with Monolingual ...for Interactive Machine Translation. ICMI’11. Alicante, Spain: ACM, 2011, 197–200. 14 Haffari, G.; Sarkar, A. Active Learning for Multilingual

  8. Syntactic Reordering for Arabic- English Phrase-Based Machine Translation

    Science.gov (United States)

    Hatem, Arwa; Omar, Nazlia

    Machine Translation (MT) refers to the use of a machine for performing translation task which converts text or speech in one Natural Language (Source Language (SL)) into another Natural Language (Target Language (TL)). The translation from Arabic to English is difficult task due to the Arabic languages are highly inflectional, rich morphology and relatively free word order. Word ordering plays an important part in the translation process. The paper proposes a transfer-based approach in Arabic to English MT to handle the word ordering problem. Preliminary tested indicate that our system, AE-TBMT is competitive when compared against other approaches from the literature.

  9. Machine Translation as a Complex System: The Role of Esperanto

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    Federic Gobbo

    2015-04-01

    Full Text Available 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 fact, there are multiple agents (both natural and artificial involved, interacting with one another and committed to achieve a common goal, i.e., the machine translation task. The main characteristics of language as a CAS are also shared in machine translation, especially if we consider the example-based, statistical approach, which is nowadays paradigmatic and unavoidable. In fact, control is distributed, there is no ideal representing agent (intrinsic diversity, there are perpetual dynamics in performance, adapted through amplification and competition of new examples from the crowd of users. On the other hand, Esperanto, being a living language, can be considered a CAS, but of a special kind, because its intrinsic regularity in structure simplifies the task of machine translation, at least up to a certain level. This paper reviews how Esperanto has enhanced the development of human-machine communication in general and within machine translation in particular, tracing some prospects for further development of machine translation, where Esperanto could play a key role.

  10. Machine Translation Based on Translation Corresponding Tree Structure

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    A representation schema called translation corresponding tree (TCT) has been applied to a Portuguese to Chinese example-based machine translation system. The translation examples are annotated by the representation of the TCT structure. Each TCT describes not only the syntactic structure of the source sentence (i.e., Portuguese in our system) but also the translation correspondences (i.e., Chinese translation). In addition, the TCT nodes describe the corresponding linguistic relationships between the source and target languages. The translation examples can be effectively represented with this annotation schema and organized in the bilingual knowledge database or example base. In the real machine translation process, the target language is synthesized with higher quality by referring to the TCT translation information.

  11. Quantum Neural Network Based Machine Translator for Hindi to English

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    Ravi Narayan

    2014-01-01

    Full Text Available 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.

  12. 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.

  13. Fundamentals of Machine Learning for Neural Machine Translation

    OpenAIRE

    Kelleher, John

    2016-01-01

    This paper presents a short introduction to neural networks and how they are used for machine translation and concludes with some discussion on the current research challenges being addressed by neural machine translation (NMT) research. The primary goal of this paper is to give a no-tears introduction to NMT to readers that do not have a computer science or mathematical background. The secondary goal is to provide the reader with a deep enough understanding of NMT that they can appreciate th...

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

    DEFF Research Database (Denmark)

    Flanagan, Marian

    Audiovisual Translation (AVT), and in particular subtitling, has been recognised as an area that could potentially benefit from the introduction of machine translation (followed by post-editing). In recent years the demands on subtitlers have increased, while the payment to subtitlers and time al...

  15. 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...

  16. English to Tamil machine translation system using universal networking language

    Indian Academy of Sciences (India)

    RAJESWARI SRIDHAR; PAVITHRA SETHURAMAN; KASHYAP KRISHNAKUMAR

    2016-06-01

    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 represent semantic data extracted from a natural language text. The input English sentence is converted to UNL (enconversion), which is then converted to a Tamil sentence (deconversion) by ensuring thatthe meaning of the input sentence is preserved. The representation of UNL was modified to suit the translation process. A new sentence formation algorithm was also proposed to rearrange the translated Tamil words to sentences. The translation system was evaluated using bilingual evaluation understudy (BLEU) score. A BLEU score of 0.581 was achieved, which is an indication that most of the information in the input sentence is retained in the translated sentence. The scores obtained using the UNL based approach were compared with existingapproaches to translation, and it can be concluded that the UNL is a more suited approach to machine translation.

  17. 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...

  18. Project-specific Machine Translation

    Science.gov (United States)

    2011-12-01

    Linguistic Data Consortium’s Reflex Pack for Less Commonly Taught Languages (LCTL) (7). The corpora labeled Sada -e-Azadi (SeA) (11) and Afghan Recovery...Linguistics, Philadelphia, PA, 2002, 311–318. 11. Sada -e Azadi. http://www.sada-e-azadi.net (accessed 2011). 12. Stolcke, A. SRILM - An Extensible...Translation Center QAMO Qamoosuna (dictionaries) RH Ranger Handbook SCFG Synchronous Context Free Grammar SeA Sada -e-Azadi SME subject matter expert SMT

  19. 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...

  20. Statistical Machine Translation Features with Multitask Tensor Networks

    OpenAIRE

    Setiawan, Hendra; Huang, Zhongqiang; Devlin, Jacob; Lamar, Thomas; Zbib, Rabih; Schwartz, Richard; Makhoul, John

    2015-01-01

    We present a three-pronged approach to improving Statistical Machine Translation (SMT), building on recent success in the application of neural networks to SMT. First, we propose new features based on neural networks to model various non-local translation phenomena. Second, we augment the architecture of the neural network with tensor layers that capture important higher-order interaction among the network units. Third, we apply multitask learning to estimate the neural network parameters joi...

  1. 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

  2. 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.

  3. Resolution of Unidentified Words in Machine Translation

    CERN Document Server

    Ullah, Sana; Kwak, Kyung Sup

    2009-01-01

    This paper presents a mechanism of resolving unidentified lexical units in text-based machine translation (TBMT). In machine translation system it is unlikely to have a complete MT lexicon and hence there is a need of a mechanism to handle the problem of unidentified words. These unknown words could be abbreviations, names, acronyms and newly introduced terms. We have proposed an algorithm for the resolution of the unidentified words. This algorithm takes discourse unit (primitive discourse) as a unit of analysis and provides real time updates to the lexicon. We have manually applied the algorithm to news paper fragments. Along with anaphora and cataphora1 resolution, many unknown words especially names and abbreviations were updated to the lexicon. Moreover flowchart of the proposed algorithm is also presented.

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

    Directory of Open Access Journals (Sweden)

    Haniyeh Sadeghi Azer

    2015-08-01

    Full Text Available 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 questionnaire was assigned to end-users to evaluate the outputs to examine and determine, if the machine-generated translations are intelligible and acceptable from their point of view and which one of the machine-generated translations produced by Padideh software and Google Translate is more acceptable and useful from the end-users point of view. The findings indicate that, the machine-generated translations are intelligible and acceptable in translating certain text-types, for end-users and Google Translate is more acceptable from end-users point of view. Keywords: Machine Translation, Machine Translation Evaluation, Translation Quality

  5. 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 sub

  6. 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 t

  7. An Efficient Machine Translation System for English to Indian Languages Using Hybrid Mechanism

    Directory of Open Access Journals (Sweden)

    J. Sangeetha

    2014-08-01

    Full Text Available Machine Translation is an essential approach for localization, and is especially appropriate in a linguistically diversenation like India. Automatic translation between languages which are morphologically rich and syntactically different is generally regarded as a complex task. A number of machine translation systems have been proposed in literature. But, conventional rule-based machine translation system is costly in terms of formulating rules. It introduces inconsistencies, and it is inflexible to be robust. Statistical MT is an approach that automatically attains knowledge from a vast amount of training data. This approach is characterized by the use of machine learning techniques. But, still there is scope for better performance of the system. In this paper, a Hybrid Machine Translation (HMT approach is proposed which is the combination of rule based and statistical technique for translating text from English to Indian languages such as Tamil, Malayalam and Hindi. The rule based machine translation technique, involves the formation of rules which helps to re-order the syntactic structures of the source language sentence along with its dependency information which brings close to the structure of the target sentence. The parser identifies the syntactical elements in English sentences and suggests its Indian languages translation taking into account various grammatical forms of those Indian languages. Context Free Grammars (CFG is used in generation of the language structures, and then the errors in the translated sentences are corrected by applying a statistical technique. Simplifying and segmenting an input language text becomes mandatory in order to improve the machine translation quality. The experimental results show that the proposed approach competes with the machine translation methods reported in the literature and it provides the best translated output in each language.

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

    DEFF Research Database (Denmark)

    Flanagan, Marian

    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...... 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...... more accessible for use within the AVT industry, and to put the system in a position where it could compete commercially with the SMT approach....

  9. Machine translation of TV subtitles for large scale production

    OpenAIRE

    Volk, Martin; Sennrich, Rico; Hardmeier, Christian; Tidström, Frida

    2010-01-01

    This paper describes our work on building and employing Statistical Machine Translation systems for TV subtitles in Scandinavia. We have built translation systems for Danish, English, Norwegian and Swedish. They are used in daily subtitle production and translate large volumes. As an example we report on our evaluation results for three TV genres. We discuss our lessons learned in the system development process which shed interesting light on the practical use of Machine Translation technology.

  10. Evaluation of Hindi to Punjabi Machine Translation System

    CERN Document Server

    Goyal, Vishal

    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 accuracy of about 92%. Both the systems i.e. system under question and developed system are between same closely related languages. Thus, this paper presents the evaluation results of Hindi to Punjabi machine translation system. It makes sense to use same evaluation criteria as that of Punjabi to Hindi Punjabi Machine Translation System. After evaluation, the accuracy of the system is found to be about 95%.

  11. 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

  12. Quantum Neural Network Based Machine Translator for Hindi to English

    OpenAIRE

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

    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 t...

  13. Quantum Neural Network Based Machine Translator for Hindi to English

    OpenAIRE

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

    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 t...

  14. LSTM Neural Reordering Feature for Statistical Machine Translation

    OpenAIRE

    Cui, Yiming; Wang, Shijin; Li, Jianfeng

    2015-01-01

    Artificial neural networks are powerful models, which have been widely applied into many aspects of machine translation, such as language modeling and translation modeling. Though notable improvements have been made in these areas, the reordering problem still remains a challenge in statistical machine translations. In this paper, we present a novel neural reordering model that directly models word pairs and alignment. By utilizing LSTM recurrent neural networks, much longer context could be ...

  15. Exact Decoding for Phrase-Based Statistical Machine Translation

    NARCIS (Netherlands)

    Aziz, W.; Dymetman, M.; Specia, L.

    2014-01-01

    The combinatorial space of translation derivations in phrase-based statistical machine translation is given by the intersection between a translation lattice and a target language model. We replace this intractable intersection by a tractable relaxation which incorporates a low-order upperbound on t

  16. Machine Translation in the German Classroom: Detection, Reaction, Prevention

    Science.gov (United States)

    Steding, Soren

    2009-01-01

    There are many websites today that offer free machine translations and although beginning students of German are not always proficient enough to judge the quality of these translations or to fully understand certain translation results, they use these services nonetheless for their assignments. The problem for the educator is to distinguish…

  17. Exploration and exploitation of multilingual data for statistical machine translation

    NARCIS (Netherlands)

    Carter, S.C.

    2012-01-01

    Shortly after the birth of computer science, researchers realised the importance of machine translation as a task worth of concentrated effort, but it is only recently that algorithms are able to provide automatic translations usable by the masses. Modern translation systems are dependent on bilingu

  18. 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....... To obtain a data set with spoken post-editing information, we use the French version of TED talks as the source texts submitted to MT, and the spoken English counterparts as their corrections, which are submitted to an ASR system. We experiment with various levels of artificial ASR noise and also...

  19. 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.

  20. Machine Translation of Noun Phrases from English to Igala using ...

    African Journals Online (AJOL)

    PROF. OLIVER OSUAGWA

    2014-06-01

    Jun 1, 2014 ... for easier processing of concepts This clearly shows that ... research organizations and government agencies to .... first hybrid machine translation in 2009. English and ... sentence structure in the target language. There is no ...

  1. 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…

  2. 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…

  3. Machine Translation-Assisted Language Learning: Writing for Beginners

    Science.gov (United States)

    Garcia, Ignacio; Pena, Maria Isabel

    2011-01-01

    The few studies that deal with machine translation (MT) as a language learning tool focus on its use by advanced learners, never by beginners. Yet, freely available MT engines (i.e. Google Translate) and MT-related web initiatives (i.e. Gabble-on.com) position themselves to cater precisely to the needs of learners with a limited command of a…

  4. Chunk Alignment for Corpus-Based Machine Translation

    Science.gov (United States)

    Kim, Jae Dong

    2011-01-01

    Since sub-sentential alignment is critically important to the translation quality of an Example-Based Machine Translation (EBMT) system, which operates by finding and combining phrase-level matches against the training examples, we developed a new alignment algorithm for the purpose of improving the EBMT system's performance. This new…

  5. Machine Translation with Many Manually Labeled Discourse Connectives

    OpenAIRE

    Meyer, Thomas; Polakova, Lucie

    2013-01-01

    The paper presents machine translation experiments from English to Czech with a large amount of manually annotated discourse connectives. The gold-standard discourse relation annotation leads to better translation performance in ranges of 4–60% for some ambiguous English connectives and helps to find correct syntactical constructs in Czech for less ambiguous connectives. Automatic scoring confirms the stability of the newly built discourse-aware translation systems. Error analysis and human t...

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

    DEFF Research Database (Denmark)

    Liyanapathirana, Jeevanthi

    than typing, making the translation process faster. The spoken translation is analyzed and combined with the machine translation output of the same sentence using different methods. We study a number of different translation models in the context of n-best list rescoring methods. As an alternative...... 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...... on the Danish – English language pair, with the use of a speech corpora and parallel text. The methods are investigated to check ways that the accuracy of the spoken translation of the translator can be increased with the use of machine translation outputs, which would be useful for potential computer...

  7. Linguistically motivated statistical machine translation models and algorithms

    CERN Document Server

    Xiong, Deyi

    2015-01-01

    This book provides a wide variety of algorithms and models to integrate linguistic knowledge into Statistical Machine Translation (SMT). It helps advance conventional SMT to linguistically motivated SMT by enhancing the following three essential components: translation, reordering and bracketing models. It also serves the purpose of promoting the in-depth study of the impacts of linguistic knowledge on machine translation. Finally it provides a systematic introduction of Bracketing Transduction Grammar (BTG) based SMT, one of the state-of-the-art SMT formalisms, as well as a case study of linguistically motivated SMT on a BTG-based platform.

  8. 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...

  9. Machine Translation in the Hands of Trainee Translators – an Empirical Study

    Directory of Open Access Journals (Sweden)

    Sycz-Opoń Joanna

    2017-03-01

    Full Text Available Automated translation (machine translation, MT is systematically gaining popularity among professional translators, who claim that editing MT output requires less time and effort than translating from scratch. MT technology is also offered in leading translator’s workstations, e.g., SDL Trados Studio, memoQ, Déjà Vu and Wordfast. Therefore, the dilemma arises: should MT be introduced into formal translation training? In order to answer this question, first, it is necessary to understand how trainee translators actually use MT.

  10. 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.

  11. 面向移动终端的统计机器翻译解码定点化方法%A Fixed Point Decoding Approach for Statistical Machine Translation on Mobile Terminals

    Institute of Scientific and Technical Information of China (English)

    李响; 徐金安; 姜文斌; 吕雅娟; 刘群

    2011-01-01

    面向移动终端的统计机器翻译需求越来越多,但无浮点运算单元的处理器限制了翻译速度.该文提出了一种对统计机器翻译解码运算的定点化运算方法,缓解了无浮点运算单元的处理器对翻译速度的影响.基于PC和移动终端的实验表明,在保证翻译质量的情况下,利用定点处理浮点运算的解码器的运算速度较编译器模拟的浮点运算速度提高135.6%.因此,该方法可以有效地提高浮点运算能力薄弱的移动终端统计机器翻译速度.%The demand for statistical machine translation (SMT) on mobile terminals is increasing, but the processor without floating point unit (FPU) restricts the translation speed. This paper proposes an approach to switch floating point operation to fixed point operation for decoder of SMT system on mobile terminals, and increase the translation speed on the processor without FPU. The experiments based on PC and mobile terminal show while this approach assures the quality of translation, the speed of our approach is 135.6% faster than the speed of floating point operation emulated by compiler. Therefore, this approach can efficiently increase the translation speed of SMT system on mobile terminals with weak ability in floating point operation.

  12. Approaches to translational plant science

    DEFF Research Database (Denmark)

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

    2015-01-01

    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...... 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...

  13. TRANSLATOR OF FINITE STATE MACHINE MODEL PARAMETERS FROM MATLAB ENVIRONMENT INTO HUMAN-MACHINE INTERFACE APPLICATION

    OpenAIRE

    2012-01-01

    Technology and means for automatic translation of FSM model parameters from Matlab application to human-machine interface application is proposed. The example of technology application to the electric apparatus model is described.

  14. 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.

  15. Good Applications for Crummy Machine Translation

    Science.gov (United States)

    1991-07-01

    multilingual 16 computational linguistics __.__n _____ODE 16. PRICE CODE 17. SECURITY CLASSIFICTION 18. SECURITY CLASSIFICATION 19. SECURITY...relatively few keystrokes. Peter Brown (personal communication) once remarked that such a super-fast typewriter ought to be possible in the monolingual case... Multilingual System under Development, Computational Linguistics, 11:2-3, pp. 155-169. [81 Kay, M. (1980) "The Proper Place of Men and Machines in Language

  16. Neural Networks Classifier for Data Selection in Statistical Machine Translation

    OpenAIRE

    Peris, Álvaro; Chinea-Rios, Mara; Casacuberta, Francisco

    2016-01-01

    We address the data selection problem in statistical machine translation (SMT) as a classification task. The new data selection method is based on a neural network classifier. We present a new method description and empirical results proving that our data selection method provides better translation quality, compared to a state-of-the-art method (i.e., Cross entropy). Moreover, the empirical results reported are coherent across different language pairs.

  17. Machine-Aided Translation: From Terminology Banks to Interactive Translation Systems.

    Science.gov (United States)

    Greenfield, Concetta C.; Serain, Daniel

    The rapid growth of the need for technical translations in recent years has led specialists to utilize computer technology to improve the efficiency and quality of translation. The two approaches considered were automatic translation and terminology banks. Since the results of fully automatic translation were considered unsatisfactory by various…

  18. Pre-editing and Recursive-Phrase Composites for a Better English-to-Arabic Machine Translation

    Directory of Open Access Journals (Sweden)

    Mansoor Al-A'ali

    2007-01-01

    Full Text Available This research presents an approach for an English-to-Arabic Machine Translation System based on Building correct grammar and phrase structures first and then automatically deriving Translation Rules for phrase translation. For every English phrase, the grammar is first analysed and then a corresponding Arabic translation is given which would be used by the machine learning system to produce a translation rule with the help of a dictionary and the user. These same derived rules can partially be used for other phrase sequences especially in the case of a phrase consisting of a number of smaller phrases and thus implemeting the idea of recusive phrase strucutres. The approach was implemented and tested on simple cases and the results are given which indicate that this approach is successful for small to medium phrases. Our approach is an enhancement on existing phrase translation techniques because it analyses the source language grammar first, then builds a syntactic structure before proceeding with the machine learning process of learning the translation rules. Our approach is enhancement on existing phrase based translations in two directions: the grammar editing before the translation rules and the derived translation rules can be complete for complete phrases or are rules for translating smaller phrases which are subsets of larger phrases. The approach has improved the speed and correctness of phrase translations.

  19. 互联网机器翻译%Web-based Machine Translation

    Institute of Scientific and Technical Information of China (English)

    王海峰; 吴华; 刘占一

    2011-01-01

    该文在回顾机器翻译发展的基础上,总结了主要的机器翻译方法,并主要阐述互联网机器翻译的特点及面临的挑战.面向互联网机器翻译的应用需求,并针对互联网资源具有海量、高噪声、时效性、稀疏的特点,提出了多策略混合翻译方法、资源挖掘和过滤以及分布式处理技术、领域自适应技术,针对数据稀疏论述枢轴语言技术和新语种快速部署技术;然后结合翻译与搜索技术,阐述翻译个性化特点和方案.最后,论述机器翻译技术和产品的应用.%This paper digs into the characteristics and challenges of web-based machine translation, and proposes possible solutions. First of all, we look back on the history of machine translation and summarize its methods. Next, we analyze the characteristics of internet bilingual corpora and monolingual corpora as: large scale, with lots of noise, real-time and sometimes sparse. Based on the features described above, we propose the hybrid machine translation method, corpus mining and filtering methods, and distributed computing methods. Furthermore, the pivot language approach is adopted to tackle the data sparseness problem, thus enabling the quick development of multilingual machine translation systems. We then discuss the approach to support the personalization of machine translation via the combination of translation technology and search technology. Finally the applications and products of machine translation technology are presented.

  20. Complex Networks Analysis of Manual and Machine Translations

    Science.gov (United States)

    Amancio, Diego R.; Antiqueira, Lucas; Pardo, Thiago A. S.; da F. Costa, Luciano; Oliveira, Osvaldo N.; Nunes, Maria G. V.

    Complex networks have been increasingly used in text analysis, including in connection with natural language processing tools, as important text features appear to be captured by the topology and dynamics of the networks. Following previous works that apply complex networks concepts to text quality measurement, summary evaluation, and author characterization, we now focus on machine translation (MT). In this paper we assess the possible representation of texts as complex networks to evaluate cross-linguistic issues inherent in manual and machine translation. We show that different quality translations generated by MT tools can be distinguished from their manual counterparts by means of metrics such as in- (ID) and out-degrees (OD), clustering coefficient (CC), and shortest paths (SP). For instance, we demonstrate that the average OD in networks of automatic translations consistently exceeds the values obtained for manual ones, and that the CC values of source texts are not preserved for manual translations, but are for good automatic translations. This probably reflects the text rearrangements humans perform during manual translation. We envisage that such findings could lead to better MT tools and automatic evaluation metrics.

  1. Foreign Developments in Information Processing and Machine Translation

    Science.gov (United States)

    2007-11-02

    on developments in the following fields of language data processing: Machine translation studies; questions on structural linguistics, phonological ...34katakana" or in phonetic syllables without the use of any "kanji" or Chinese characters, the "kun"- pronunciation of Chinese characters was adopted as

  2. Human in the Loop Machine Translation of Medical Terminology

    Science.gov (United States)

    2010-04-01

    March 30–31, 2009, http://www.aclweb.org/anthology/W/W09/W09-0x24. 3. Chiang, D.; Lopez, A.; Madnani, N.; Monz, C.; Resnik , P.; Subotin, M. The Hiero... Resnik , P. S. Machine Translation by Pattern Matching; University of Maryland at College Park, College Park, MD, 2008, ISBN: 978-0-549-57255-8

  3. The Database State Machine Approach

    OpenAIRE

    1999-01-01

    Database replication protocols have historically been built on top of distributed database systems, and have consequently been designed and implemented using distributed transactional mechanisms, such as atomic commitment. We present the Database State Machine approach, a new way to deal with database replication in a cluster of servers. This approach relies on a powerful atomic broadcast primitive to propagate transactions between database servers, and alleviates the need for atomic comm...

  4. UNITRAN: An Interlingual Machine Translation System.

    Science.gov (United States)

    1987-12-01

    modification in the interlingual approach as embodied by CETA and Sharp. ’Grenoble Universitv, France , 1961. 4 4 English Spanish French Japanese Parameter...comer: Yo como el pan. gustar: El libro me gusta a mi. eat: I eat the bread. like: I like the book. Figure 9: There is no thematic divergence between

  5. Self-Organizing Machine Translation Example-Driven Induction of Transfer Functions

    CERN Document Server

    Juola, P

    1994-01-01

    With the advent of faster computers, the notion of doing machine translation from a huge stored database of translation examples is no longer unreasonable. This paper describes an attempt to merge the Example-Based Machine Translation (EBMT) approach with psycholinguistic principles. A new formalism for context- free grammars, called *marker-normal form*, is demonstrated and used to describe language data in a way compatible with psycholinguistic theories. By embedding this formalism in a standard multivariate optimization framework, a system can be built that infers correct transfer functions for a set of bilingual sentence pairs and then uses those functions to translate novel sentences. The validity of this line of reasoning has been tested in the development of a system called METLA-1. This system has been used to infer English->French and English->Urdu transfer functions from small corpora. The results of those experiments are examined, both in engineering terms as well as in more linguistic terms. In ge...

  6. JTEC panel report on machine translation in Japan

    Science.gov (United States)

    Carbonell, Jaime; Rich, Elaine; Johnson, David; Tomita, Masaru; Vasconcellos, Muriel; Wilks, Yorick

    1992-01-01

    The goal of this report is to provide an overview of the state of the art of machine translation (MT) in Japan and to provide a comparison between Japanese and Western technology in this area. The term 'machine translation' as used here, includes both the science and technology required for automating the translation of text from one human language to another. Machine translation is viewed in Japan as an important strategic technology that is expected to play a key role in Japan's increasing participation in the world economy. MT is seen in Japan as important both for assimilating information into Japanese as well as for disseminating Japanese information throughout the world. Most of the MT systems now available in Japan are transfer-based systems. The majority of them exploit a case-frame representation of the source text as the basis of the transfer process. There is a gradual movement toward the use of deeper semantic representations, and some groups are beginning to look at interlingua-based systems.

  7. A Study on Automatic Scoring for Machine Translation Systems

    Institute of Scientific and Technical Information of China (English)

    Yao Jianmin(姚建民); Zhang Jing; Zhao Tiejun; Li Sheng

    2004-01-01

    String similarity measures of edit distance, cosine correlation and Dice coefficient are adopted to evaluate machine translation results. Experiment shows that the evaluation method distinguishes well between "good" and "bad" translations. Another experiment manifests a consistency between human and automatic scorings of 6 general-purpose MT systems. Equational analysis validates the experimental results. Although the data and graphs are very promising, correlation coefficient and significance tests at 0.01 level are made to ensure the reliability of the results. Linear regression is made to map the automatic scoring results to human scorings.

  8. 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.

  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. Building a Large-Scale Knowledge Base for Machine Translation

    CERN Document Server

    Knight, K; Knight, Kevin; Luk, Steve K.

    1994-01-01

    Knowledge-based machine translation (KBMT) systems have achieved excellent results in constrained domains, but have not yet scaled up to newspaper text. The reason is that knowledge resources (lexicons, grammar rules, world models) must be painstakingly handcrafted from scratch. One of the hypotheses being tested in the PANGLOSS machine translation project is whether or not these resources can be semi-automatically acquired on a very large scale. This paper focuses on the construction of a large ontology (or knowledge base, or world model) for supporting KBMT. It contains representations for some 70,000 commonly encountered objects, processes, qualities, and relations. The ontology was constructed by merging various online dictionaries, semantic networks, and bilingual resources, through semi-automatic methods. Some of these methods (e.g., conceptual matching of semantic taxonomies) are broadly applicable to problems of importing/exporting knowledge from one KB to another. Other methods (e.g., bilingual match...

  11. Countability and Number in Japanese-to-English Machine Translation

    CERN Document Server

    Bond, F; Ikehara, S; Bond, Francis; Ogura, Kentaro; Ikehara, Satoru

    1994-01-01

    This paper presents a heuristic method that uses information in the Japanese text along with knowledge of English countability and number stored in transfer dictionaries to determine the countability and number of English noun phrases. Incorporating this method into the machine translation system ALT-J/E, helped to raise the percentage of noun phrases generated with correct use of articles and number from 65% to 73%.

  12. 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...

  13. RM-structure alignment based statistical machine translation model

    Institute of Scientific and Technical Information of China (English)

    Sun Jiadong; Zhao Tiejun

    2008-01-01

    A novel model based on structure alignments is proposed for statistical machine translation in this paper.Meta-structure and sequence of meta-structure for a parse tree are defined.During the translation process, a parse tree is decomposed to deal with the structure divergence and the alignments can be constructed at different levels of recombination of meta-structure (RM).This method can perform the structure mapping across the sub-tree structure between languages.As a result, we get not only the translation for the target language, but sequence of meta-structure of its parse tree at the same time.Experiments show that the model in the framework of log-linear model has better generative ability and significantly outperforms Pharaoh, a phrase-based system.

  14. 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 which...... suggests that more literal translations are produced more easily, by humans and machine, and are also less error prone. Literal translations may not be appropriate or even possible for all languages, types of texts, and translation purposes. However, in this paper we show that an assessment...... of the literality of translations allows us to (1) evaluate human and machine translations in a similar fashion and (2) may be instrumental to predict machine translation quality scores,...

  15. Setup reduction approaches for machining

    Energy Technology Data Exchange (ETDEWEB)

    Gillespie, L.K.

    1997-04-01

    Rapid setup is a common improvement approach in press working operations such as blanking and shearing. It has paid major dividends in the sheet metal industry. It also has been a major improvement thrust for high-production machining operations. However, the literature does not well cover all the setup operations and constraints for job shop work. This review provides some insight into the issues involved. It highlights the floor problems and provides insights for further improvement. The report is designed to provide a quick understanding of the issues.

  16. Classifiers in Japanese-to-English Machine Translation

    CERN Document Server

    Bond, F; Ikehara, S; Bond, Francis; Ogura, Kentaro; Ikehara, Satoru

    1996-01-01

    This paper proposes an analysis of classifiers into four major types: UNIT, METRIC, GROUP and SPECIES, based on properties of both Japanese and English. The analysis makes possible a uniform and straightforward treatment of noun phrases headed by classifiers in Japanese-to-English machine translation, and has been implemented in the MT system ALT-J/E. Although the analysis is based on the characteristics of, and differences between, Japanese and English, it is shown to be also applicable to the unrelated language Thai.

  17. A Lexicalist Approach to the Translation of Colloquial Text

    CERN Document Server

    Popowich, F; Laurens, O; McFetridge, P; Nicholson, J D; McGivern, P; Peña, M C; Pidruchney, L; MacDonald, S; Popowich, Fred; Turcato, Davide; Laurens, Olivier; Fetridge, Paul Mc; Givern, Patrick Mc; Pena, Maricela Corzo; Pidruchney, Lisa; Donald, Scott Mac

    1997-01-01

    Colloquial English (CE) as found in television programs or typical conversations is different than text found in technical manuals, newspapers and books. Phrases tend to be shorter and less sophisticated. In this paper, we look at some of the theoretical and implementational issues involved in translating CE. We present a fully automatic large-scale multilingual natural language processing system for translation of CE input text, as found in the commercially transmitted closed-caption television signal, into simple target sentences. Our approach is based on the Whitelock's Shake and Bake machine translation paradigm, which relies heavily on lexical resources. The system currently translates from English to Spanish with the translation modules for Brazilian Portuguese under development.

  18. Functionalist Approaches to Advertisement Translation

    Institute of Scientific and Technical Information of China (English)

    王乐

    2009-01-01

    The 1970s saw a development of the Functionalism, with its three representative scholars Katharina Reiss, Hans. Vermeer and Justa Holz Manttari. Katharina Reiss proposed the text type theory; Vermeer brought up the skopostheory and Mantarri translational action theory. The Functional theories are very useful for the translators to adopt a fight translation strategy. In these years, various kinds of advertisement have appeared in people's daily life. They are becoming one important part in our culture. The companies need advertisements to sell their products and the consumers need the advertisement to decide which brand to buy after comparison. This paper will discuss how they are ap-plied to the advertisement translation.

  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. Advances in Fully-Automatic and Interactive Phrase-Based Statistical Machine Translation

    OpenAIRE

    Ortiz Martínez, Daniel

    2011-01-01

    This thesis presents different contributions in the fields of fully-automatic statistical machine translation and interactive statistical machine translation. In the field of statistical machine translation there are three problems that are to be addressed, namely, the modelling problem, the training problem and the search problem. In this thesis we present contributions regarding these three problems. Regarding the modelling problem, an alternative derivation of phrase-based s...

  1. ScaleMT: a free/open-source framework for building scalable machine translation web services

    OpenAIRE

    Sánchez-Cartagena, Víctor M.; Pérez-Ortiz, Juan Antonio

    2009-01-01

    Machine translation web services usage is growing amazingly mainly because of the translation quality and reliability of the service provided by the Google Ajax Language API. To allow the open-source machine ranslation projects to compete with Google’s one and gain visibility on the internet, we have developed ScaleMT: a free/open-source framework that exposes existing machine translation engines as public web services. This framework is highly scalable as it can run coordinately on many serv...

  2. Quantitative evaluation of English-Japanese machine translation of medical literature.

    Science.gov (United States)

    Kiuchi, T; Kaihara, S

    1991-08-01

    Although many machine-translation programs are currently available, few evaluation methods of such translation exist for any given application area. It is difficult to evaluate machine-translation systems objectively because the quality of a translation depends on the combination of three factors: the translation program, the dictionary, and the original document. In this study, we developed a quantitative evaluation method for assessing machine translation, which evaluates these three factors separately. We applied this method to the translation of English to Japanese for medical literature and the method proved to be a good indicator for further system improvement. Using this method we also discovered other important points for machine translation, such as the examination of target documents for the construction of a better application dictionary.

  3. A Probabilistic Approach to Knowledge Translation

    OpenAIRE

    Jiang, Shangpu; Lowd, Daniel; Dou, Dejing

    2015-01-01

    In this paper, we focus on a novel knowledge reuse scenario where the knowledge in the source schema needs to be translated to a semantically heterogeneous target schema. We refer to this task as "knowledge translation" (KT). Unlike data translation and transfer learning, KT does not require any data from the source or target schema. We adopt a probabilistic approach to KT by representing the knowledge in the source schema, the mapping between the source and target schemas, and the resulting ...

  4. Myanmar-English Bidirectional Machine Translation System with Numerical Particles Identification

    Directory of Open Access Journals (Sweden)

    Yin Yin Win

    2016-06-01

    Full Text Available This paper the development of MyanmarEnglish bidirectional machine translation system is implemented applying Rule based machine translation approach. Stanford and ML2KR parsers are used for preprocessing step. From this step, parsers generate corresponding parse tree structures. Used parsers generate corresponding CFG rules which are collected and created as synchronous context free grammar SCFG rules. Myanmar language can be written free order style, but it must be verb final structure. Therefore, CFG rules are required for reordering the structure of the two languages. After that tree to tree transformation is carried on the source tree structure which corresponds with used parser (Stanford parser or ML2KR‟s parser. When source parse tree is transformed as target parse tree, it is changed according to the SCFG rules. And then system carries out the morphological synthesis. In this stage, we need to solve only for English to Myanmar machine translation because Myanmar language is morphologically rich language. Therefore, particles for Myanmar language can be solved in this system by proposed algorithm. After finishing morphological synthesis, this system generates meaningful and appropriate smoothing sentences

  5. Translation: Towards a Critical-Functional Approach

    Science.gov (United States)

    Sadeghi, Sima; Ketabi, Saeed

    2010-01-01

    The controversy over the place of translation in the teaching of English as a Foreign Language (EFL) is a thriving field of inquiry. Many older language teaching methodologies such as the Direct Method, the Audio-lingual Method, and Natural and Communicative Approaches, tended to either neglect the role of translation, or prohibit it entirely as a…

  6. New approach to training support vector machine

    Institute of Scientific and Technical Information of China (English)

    Tang Faming; Chen Mianyun; Wang Zhongdong

    2006-01-01

    Support vector machine has become an increasingly popular tool for machine learning tasks involving classification, regression or novelty detection. Training a support vector machine requires the solution of a very large quadratic programming problem. Traditional optimization methods cannot be directly applied due to memory restrictions. Up to now, several approaches exist for circumventing the above shortcomings and work well. Another learning algorithm, particle swarm optimization, for training SVM is introduted. The method is tested on UCI datasets.

  7. 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 f

  8. Exploring the Further Integration of Machine Translation in English-Chinese Cross Language Information Access

    Science.gov (United States)

    Wu, Dan; He, Daqing

    2012-01-01

    Purpose: This paper seeks to examine the further integration of machine translation technologies with cross language information access in providing web users the capabilities of accessing information beyond language barriers. Machine translation and cross language information access are related technologies, and yet they have their own unique…

  9. Impact of Machine-Translated Text on Entity and Relationship Extraction

    Science.gov (United States)

    2014-12-01

    Impact of Machine-Translated Text on Entity and Relationship Extraction by Mark R Mittrick and John T Richardson ARL-TN-0649 December...2014 Impact of Machine-Translated Text on Entity and Relationship Extraction Mark R Mittrick and John T Richardson Computational and...

  10. 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 f

  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. 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

  13. Analysing Quality of English-Hindi Machine Translation Engine outputs using Baysian Classification

    OpenAIRE

    Rashmi Gupta; Nisheeth Joshi; Iti Mathur

    2013-01-01

    This paper considers the problem for estimating the quality of machine translation outputs which are independent of human intervention and are generally addressed using machine learning techniques.There are various measures through which a machine learns translations quality. Automatic Evaluation metrics produce good co-relation at corpus level but cannot produce the same results at the same segment or sentence level. In this paper 16 features are extracted from the input sentence...

  14. Hindi to English Transfer Based Machine Translation System

    Directory of Open Access Journals (Sweden)

    Shashi Pal Singh

    2015-06-01

    Full Text Available In large societies like India there is a huge demand to convert one human language into another. Lots of work has been done in this area. Many transfer based MTS have developed for English to other languages, as MANTRA CDAC Pune, MATRA CDAC Pune, SHAKTI IISc Bangalore and IIIT Hyderabad. Still there is a little work done for Hindi to other languages. Currently we are working on it. In this paper we focus on designing a system, that translate the document from Hindi to English by using transfer based approach. This system takes an input text check its structure through parsing. Reordering rules are used to generate the text in target language. It is better than Corpus Based MTS because Corpus Based MTS require large amount of word aligned data for translation that is not available for many languages while Transfer Based MTS requires only knowledge of both the languages (source language and target language to make transfer rules. We get correct translation for simple assertive sentences and almost correct for complex and compound sentences.

  15. 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.

  16. Can multilingual machine translation help make medical record content more comprehensible to patients?

    Science.gov (United States)

    Zeng-Treitler, Qing; Kim, Hyeoneui; Rosemblat, Graciela; Keselman, Alla

    2010-01-01

    With the development of electronic personal health records, more patients are gaining access to their own medical records. However, comprehension of medical record content remains difficult for many patients. Because each record is unique, it is also prohibitively costly to employ human translators to solve this problem. In this study, we investigated whether multilingual machine translation could help make medical record content more comprehensible to patients who lack proficiency in the language of the records. We used a popular general-purpose machine translation tool called Babel Fish to translate 213 medical record sentences from English into Spanish, Chinese, Russian and Korean. We evaluated the comprehensibility and accuracy of the translation. The text characteristics of the incorrectly translated sentences were also analyzed. In each language, the majority of the translations were incomprehensible (76% to 92%) and/or incorrect (77% to 89%). The main causes of the translation are vocabulary difficulty and syntactical complexity. A general-purpose machine translation tool like the Babel Fish is not adequate for the translation of medical records; however, a machine translation tool can potentially be improved significantly, if it is trained to target certain narrow domains in medicine.

  17. A Machine Learning Approach to Automated Negotiation

    Institute of Scientific and Technical Information of China (English)

    Zhang Huaxiang(张化祥); Zhang Liang; Huang Shangteng; Ma Fanyuan

    2004-01-01

    Automated negotiation between two competitive agents is analyzed, and a multi-issue negotiation model based on machine learning, time belief, offer belief and state-action pair expected Q value is developed. Unlike the widely used approaches such as game theory approach, heuristic approach and argumentation approach, This paper uses a machine learning method to compute agents' average Q values in each negotiation stage. The delayed reward is used to generate agents' offer and counteroffer of every issue. The effect of time and discount rate on negotiation outcome is analyzed. Theory analysis and experimental data show this negotiation model is practical.

  18. Quantifying the Efficiency of a Translator: The Effect of Syntactical and Literal Written Translations on Language Comprehension Using the Machine Translation System FALCon

    Science.gov (United States)

    McCulloh, Ian A.; Morton, Jillian; Jantzi, Jennifer K.; Rodriguez, Amy M.; Graham, John

    2008-01-01

    This study introduces a new method of evaluating human comprehension in the context of machine translation using a language translation program known as the FALCon (Forward Area Language Converter). The participants include 48 freshmen from the United States Military Academy enrolled in the General Psychology course, PL100. Results of this study…

  19. Quantifying the Efficiency of a Translator: The Effect of Syntactical and Literal Written Translations on Language Comprehension Using the Machine Translation System FALCon (Foreign Area Language Converter)

    Science.gov (United States)

    McCulloh, Ian A.; Morton, Jillian; Jantzi, Jennifer K.; Rodriguez, Amy M.; Graham, John

    2008-01-01

    The purpose of this study is to introduce a new method of evaluating human comprehension in the context of machine translation using a language translation program known as the FALCon (Forward Area Language Converter). The FALCon works by converting documents into digital images via scanner, and then converting those images to electronic text by…

  20. Integrated approach to advanced machining

    Energy Technology Data Exchange (ETDEWEB)

    LeSar, R.A.; Bourke, M.A.M.; Rangaswamy, P.; Day, R.D.; Hatch, D.J.

    1997-08-01

    The residual stress state induced by machining in a Ti alloy as function of cutting tool sharpness and depth of cut was predicted and measured. Residual stresses were greater for the dull tool than for the sharp tool. XRD was used to measure the residual stress state of the material; these measurements revealed that the hoop stress increased with depth of cut; however the radial stress decreased with depth of cut. An elastic-plastic model provided a possible explanation for this behavior in that, for small depths of cut, the tool makes multiple passes through the damage subsurface layer. This causes both residual stress components to increase, but the radial stress increases by a much greater amount than the hoop stress.

  1. Translation of Untranslatable Words — Integration of Lexical Approximation and Phrase-Table Extension Techniques into Statistical Machine Translation

    Science.gov (United States)

    Paul, Michael; Arora, Karunesh; Sumita, Eiichiro

    This paper proposes a method for handling out-of-vocabulary (OOV) words that cannot be translated using conventional phrase-based statistical machine translation (SMT) systems. For a given OOV word, lexical approximation techniques are utilized to identify spelling and inflectional word variants that occur in the training data. All OOV words in the source sentence are then replaced with appropriate word variants found in the training corpus, thus reducing the number of OOV words in the input. Moreover, in order to increase the coverage of such word translations, the SMT translation model is extended by adding new phrase translations for all source language words that do not have a single-word entry in the original phrase-table but only appear in the context of larger phrases. The effectiveness of the proposed methods is investigated for the translation of Hindi to English, Chinese, and Japanese.

  2. 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.

  3. 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.

  4. 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

  5. Advancement in Productivity of Arabic into English Machine Translation Systems from 2008 to 2013

    Science.gov (United States)

    Abu-Al-Sha'r, Awatif M.; AbuSeileek, Ali F.

    2013-01-01

    This paper attempts to compare between the advancements in the productivity of Arabic into English Machine Translation Systems between two years, 2008 and 2013. It also aims to evaluate the progress achieved by various systems of Arabic into English electronic translation between the two years. For tracing such advancement, a comparative analysis…

  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. 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 dire

  8. 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...

  9. Statistical Sign Language Machine Translation: from English written text to American Sign Language Gloss

    CERN Document Server

    Othman, Achraf

    2011-01-01

    This works aims to design a statistical machine translation from English text to American Sign Language (ASL). The system is based on Moses tool with some modifications and the results are synthesized through a 3D avatar for interpretation. First, we translate the input text to gloss, a written form of ASL. Second, we pass the output to the WebSign Plug-in to play the sign. Contributions of this work are the use of a new couple of language English/ASL and an improvement of statistical machine translation based on string matching thanks to Jaro-distance.

  10. Process analytical approach to translation and implications for translations teaching Process analytical approach to translation and implications for translations teaching

    Directory of Open Access Journals (Sweden)

    Wolfgang Lörscher

    2008-04-01

    Full Text Available The considerations which will be made in this paper can be located within the newly established field of translation process analysis (cf.Gerloff 1988; Jääskeläinen 1990; Krings 1986; Lörscher 1991; Séguinot 1989; Tirkkonen-Condit 1991. They are based on a research project which I have been carrying out since 1983. The aim of this project is to analyze psycholinguistically translation performance as contained in a corpus of orally produced translations from German into English and vice versa. This is done in order to reconstruct translation strategies. These underlie translation performance, operate within the translation process, and are thus not open to direct inspection. In the first stage of the project, translation processes of advanced foreign language learners were investigated. The considerations which will be made in this paper can be located within the newly established field of translation process analysis (cf.Gerloff 1988; Jääskeläinen 1990; Krings 1986; Lörscher 1991; Séguinot 1989; Tirkkonen-Condit 1991. They are based on a research project which I have been carrying out since 1983. The aim of this project is to analyze psycholinguistically translation performance as contained in a corpus of orally produced translations from German into English and vice versa. This is done in order to reconstruct translation strategies. These underlie translation performance, operate within the translation process, and are thus not open to direct inspection. In the first stage of the project, translation processes of advanced foreign language learners were investigated.

  11. 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

  12. 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...

  13. Evaluation of Machine Translation Errors in English and Iraqi Arabic

    Science.gov (United States)

    2010-05-01

    are made. Llitjós, Carbonell & Lavie (2005) created a hierarchical taxonomy of errors for use in refining rules of transfer-based MT systems...Translation. Proceedings of MT Summit XII. Llitjós, A., Carbonell , J., and Lavie, A. (2005). A framework for interactive and automatic refinement of

  14. Climbing the Tower of Babel: Perfecting Machine Translation

    Science.gov (United States)

    2011-02-16

    Peter Norvig , and Fernando Pereira, "The Unreasonable Effectiveness of Data," IEEE Intelligence Systems, (2009): 8. So, this [trillion-word] corpus...Alon Halevy, Peter Norvig , and Fernando Pereira, Google assisted translation? Some experts believe technology can develop MT capabilities with...recognition.htm (accessed 28 September 2010). Halevy, Alon, Peter Norvig , and Fernando Pereira. "The Unreasonable Effectiveness of Data." IEEE

  15. English-Lithuanian-English Machine Translation lexicon and engine: current state and future work

    CERN Document Server

    Barisevičius, G

    2011-01-01

    This article overviews the current state of the English-Lithuanian-English machine translation system. The first part of the article describes the problems that system poses today and what actions will be taken to solve them in the future. The second part of the article tackles the main issue of the translation process. Article briefly overviews the word sense disambiguation for MT technique using Google.

  16. An open-source highly scalable web service architecture for the Apertium machine translation engine

    OpenAIRE

    Sánchez-Cartagena, Víctor M.; Pérez-Ortiz, Juan Antonio

    2009-01-01

    Some machine translation services like Google Ajax Language API have become very popular as they make the collaboratively created contents of the web 2.0 available to speakers of many languages. One of the keys of its success is its clear and easy-to-use application programming interface (API) and a scalable and reliable service. This paper describes a highly scalable implementation of an Apertium-based translation web service, that aims to make contents available to speakers of lesser resour...

  17. ANALYTICAL MODEL OF CALCULUS FOR INFLUENCE THE TRANSLATION GUIDE WEAR OVER THE MACHINING ACCURACY ON THE MACHINE TOOL

    Directory of Open Access Journals (Sweden)

    Ivona PETRE

    2010-10-01

    Full Text Available The wear of machine tools guides influences favorably to vibrations. As a result of guides wear, the initial trajectory of cutting tools motion will be modified, the generating dimensional accuracy discrepancies and deviations of geometrical shape of the work pieces. As it has already been known, the wear of mobile and rigid guides is determined by many parameters (pressure, velocity, friction length, lubrication, material. The choice of one or another analytic model and/or the experimental model of the wear is depending by the working conditions, assuming that the coupling material is known.The present work’s goal is to establish an analytic model of calculus showing the influence of the translation guides wear over the machining accuracy on machine-tools.

  18. Translational approach for gene therapy in epilepsy

    DEFF Research Database (Denmark)

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

    2016-01-01

    Although novel treatment strategies based on the gene therapy approach for epilepsy has been encouraging, there is still a gap in demonstrating a proof-of-concept in a clinically relevant animal model and study design. In the present study, a conceptually novel framework reflecting a plausible...... 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......-based gene therapy approach targeting only the seizure-generating focus unilaterally can decrease seizure frequency in this chronic model of epilepsy.Our data suggest that the intrahippocampal kainate model resembles the disease development of human chronic mesial temporal lobe epilepsy (mTLE): (i...

  19. Toward an example-based machine translation from written text to ASL using virtual agent animation

    Directory of Open Access Journals (Sweden)

    Mehrez Boulares

    2012-01-01

    Full Text Available Modern computational linguistic software cannot produce important aspects of sign language translation. Using some researches we deduce that the majority of automatic sign language translation systems ignore many aspects when they generate animation; therefore the interpretation lost the truth information meaning. This problem is due to sign language consideration as a derivative language, but it is a complete language with its own unique grammar. This grammar is related to semantic-cognitive models of spatially, time, action and facial expression to represent complex information to make sign interpretation more efficiently, smooth, expressive and natural-looking human gestures. All this aspects give us useful insights into the design principles that have evolved in natural communication between people. In this work we are interested in American Sign Language, because it is the simplest and most standardized sign language. Our goals are: to translate written text from any language to ASL animation; to model maximum raw information using machine learning and computational techniques; and to produce a more adapted and expressive form to natural looking and understandable ASL animations. Our methods include linguistic annotation of initial text and semantic orientation to generate the facial expression. We use genetic algorithms coupled to learning/recognized systems to produce the most natural form. To detect emotion we based on fuzzy logic to produce the degree of interpolation between facial expressions. Roughly, we present a new expressive language Text Adapted Sign Modeling Language TASML that describes all maximum aspects related to a good sign language interpretation. This paper is organized as follow: the next section is devoted to present the comprehension effect of using Space/Time/SVO form in ASL animation based on experimentation. In section 3, we describe our technical considerations. We present the general approach we adopted to

  20. Web-Based Machine Translation as a Tool for Promoting Electronic Literacy and Language Awareness

    Science.gov (United States)

    Williams, Lawrence

    2006-01-01

    This article addresses a pervasive problem of concern to teachers of many foreign languages: the use of Web-Based Machine Translation (WBMT) by students who do not understand the complexities of this relatively new tool. Although networked technologies have greatly increased access to many language and communication tools, WBMT is still…

  1. Four Generations of Machine Translation Research and Prospects for the Future.

    Science.gov (United States)

    Wilks, Yorick

    This paper begins with a description of four generations of research in machine translation: the original efforts of 1957 to 1965 and three types of surviving and sometimes competing present projects. The three types of present projects include those relying on "brute force" methods involving larger and faster computers; those based on a…

  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. Development of Chinese-English Machine Translation System. Fnal Technical Report.

    Science.gov (United States)

    Wang, William S-Y; Chan, Stephen W.

    The report documents progress and results of a 2-1/3 year effort to further the prototype Chinese-English Machine Translation System. Additional rules were incorporated into the existing grammar for Chinese analysis and interlingual transfer, with emphasis on the latter. CHIDIC was updated and revised. Approximately 16,000 new entries were added…

  4. Improvement of Machine Translation Evaluation by Simple Linguistically Motivated Features

    Institute of Scientific and Technical Information of China (English)

    Mu-Yun Yang; Shu-Qi Sun; Jun-Guo Zhu; Sheng Li; Tie-Jun Zhao; Xiao-Ning Zhu

    2011-01-01

    Adopting the regression SVM framework, this paper proposes a linguistically motivated feature engineering strategy to develop an MT evaluation metric with a better correlation with human assessments. In contrast to current practices of "greedy" combination of all available features, six features are suggested according to the human intuition for translation quality. Then the contribution of linguistic features is examined and analyzed via a hill-climbing strategy. Experiments indicate that, compared to either the SVM-ranking model or the previous attempts on exhaustive linguistic features, the regression SVM model with six linguistic information based features generalizes across different datasets better, and augmenting these linguistic features with proper non-linguistic metrics can achieve additional improvements.

  5. 中日两国机器翻译研究进展及比较%Machine Translation Research in China and Japan: Advances and Comparison

    Institute of Scientific and Technical Information of China (English)

    张均胜; 何彦青; 李颖; 王惠临

    2011-01-01

    Machine translation investigates the use of computer software to translate text or speech from one natural language to another. Since the first computer was invented, people have been studying and exploring high quality and high efficiency of machine translation technology. Recently, rule-based machine translation, example-based machine translation and statistical translation are the main three translation patterns. There are some approaches ofsystem combination for better machine translation results. With the development of science, technology, economy and culture, machine translation has become more important in breaking the language barrier between Chinese and Japanese for promoting China-Japanese exchanges and cooperation. Machine translation researchers in China and Japan have carried out a large number of Chinese-Japanese/Japanese-Chinese machine translation of theoretical research and system development They have achieved a lot of effective results, however, it is still far from the practical translation application of large-scale and high quality. Therefore, it is necessary for researchers in China and Japan to cooperate in machine translation technology and system development for Ch inese-to-Japanese and Japanese-to-Chinese, especially in the parallel corpus, dictionary, terminology, syntactic analysis and so on. This paper presents an overview of the China-Japanese machine translation research and rampares machine translation research in China and Japan. We also discuss the prospects of China-Japanese cooperation in machine translation research.%机器翻译研究用计算机实现不同自然语言之间的翻译.自第一台计算机诞生开始,人们一直在研究和探索高质量高效率的机器翻译技术.近年来,基于规则的机器翻译、基于实例的机器翻译和基于统计的机器翻译这几种主要的翻译模式共同存在且相互补充,并有不断融合之势.随着中国和日本在科技、经济和文化交流的不

  6. 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.

  7. 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)

  8. An overview of the EtsaTrans machine translation system: compilation of an administrative domain

    Directory of Open Access Journals (Sweden)

    L. Ehlers

    2008-07-01

    Full Text Available The EtsaTrans machine translation system has been in development at the University of the Free State for the last four years and is currently the only machine translation system being developed in South Africa for specialised and nongeneral translation needs. The purpose of this exposition is to present the program through its phases of development, and to report on current levels of performance. We analyse the output, the size of the database, and then propose the future implementation of a part of speech tagger and word stemmer into the program to improve its linguistic performance. Our goal with the system is not to translate all types of document, but to work in a specialised domain that will allow the system to translate documents that are repetitive in nature. This will enable translators to spend more time on non-repetitive subject matter. By capturing the nature of the language of such repetitive documents in the database, we are able to create a standardised language usage for the specialised domain.

  9. On the application of AntConc in pre-translation of machine translation

    Institute of Scientific and Technical Information of China (English)

    王培; 赵茫茫

    2016-01-01

    This article introduces the application of a green software of corpus tool named AntConc. The article mainly focuses on its glossary function, analysis of frequency and concordance of lexical chunks, which makes the translation work more formal and standard.

  10. Iran’s Approach to Knowledge Translation

    OpenAIRE

    R Majdzadeh; S Nedjat; Fotouhi, A; H. Malekafzali

    2009-01-01

    "nKnowledge translation was created in response to the knowledge-do gap. With the growing number of research projects, utilization of research knowledge roused interest. One of its defects, which are seen more in developing countries, is the scarcity of recognized practical knowledge translation applications. The actions taken to strengthen knowledge translation can be classified into three categories of ‘push, pull and exchange'. In Iran, some of the interventions effecti...

  11. Modeling software with finite state machines a practical approach

    CERN Document Server

    Wagner, Ferdinand; Wagner, Thomas; Wolstenholme, Peter

    2006-01-01

    Modeling Software with Finite State Machines: A Practical Approach explains how to apply finite state machines to software development. It provides a critical analysis of using finite state machines as a foundation for executable specifications to reduce software development effort and improve quality. This book discusses the design of a state machine and of a system of state machines. It also presents a detailed analysis of development issues relating to behavior modeling with design examples and design rules for using finite state machines. This volume describes a coherent and well-tested fr

  12. 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.

  13. 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

  14. Rule Based Machine Translation of Noun Phrases from Punjabi to English

    Directory of Open Access Journals (Sweden)

    Kamaljeet Kaur Batra

    2010-09-01

    Full Text Available The paper presents automatic translation of noun phrases from Punjabi to English using transfer approach. The system has analysis, translation and synthesis component. The steps involved are pre processing, tagging, ambiguity resolution, translation and synthesis of words in target language. The accuracy is calculated for each step and the overall accuracy of the system is calculated to be about 85% for a particular type of noun phrases.

  15. TRANSLATE: New Strategic Approaches for English Learners

    Science.gov (United States)

    Goodwin, Amanda P.; Jiménez, Robert

    2016-01-01

    This teaching tip shares a research-based instructional model that uses translation to improve the English reading comprehension of English Learners. Within this instruction, English learners work collaboratively in small groups and use translation to facilitate understandings of their required English language arts curriculum. Students are taught…

  16. 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.

  17. 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.

  18. 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

  19. 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.

  20. 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-

  1. 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

  2. Toward an example-based machine translation from written text to ASL using virtual agent animation

    CERN Document Server

    Boulares, Mehrez

    2012-01-01

    Modern computational linguistic software cannot produce important aspects of sign language translation. Using some researches we deduce that the majority of automatic sign language translation systems ignore many aspects when they generate animation; therefore the interpretation lost the truth information meaning. Our goals are: to translate written text from any language to ASL animation; to model maximum raw information using machine learning and computational techniques; and to produce a more adapted and expressive form to natural looking and understandable ASL animations. Our methods include linguistic annotation of initial text and semantic orientation to generate the facial expression. We use the genetic algorithms coupled to learning/recognized systems to produce the most natural form. To detect emotion we are based on fuzzy logic to produce the degree of interpolation between facial expressions. Roughly, we present a new expressive language Text Adapted Sign Modeling Language TASML that describes all ...

  3. 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

  4. Approaches to Translation of Chinese Publicity Materials

    Science.gov (United States)

    Yin, Lu

    2009-01-01

    Chinese publicity materials are the windows for foreigners to know about China. There has been some problems in the translation for publicity materials both made by the enterprises and government departments. Especially for the growing international communication, the dispute between Chinese and its foreign counterpart is increasingly coming into…

  5. Domain adaptation of statistical machine translation with domain-focused web crawling.

    Science.gov (United States)

    Pecina, Pavel; Toral, Antonio; Papavassiliou, Vassilis; Prokopidis, Prokopis; Tamchyna, Aleš; Way, Andy; van Genabith, Josef

    In this paper, we tackle the problem of domain adaptation of statistical machine translation (SMT) by exploiting domain-specific data acquired by domain-focused crawling of text from the World Wide Web. We design and empirically evaluate a procedure for automatic acquisition of monolingual and parallel text and their exploitation for system training, tuning, and testing in a phrase-based SMT framework. We present a strategy for using such resources depending on their availability and quantity supported by results of a large-scale evaluation carried out for the domains of environment and labour legislation, two language pairs (English-French and English-Greek) and in both directions: into and from English. In general, machine translation systems trained and tuned on a general domain perform poorly on specific domains and we show that such systems can be adapted successfully by retuning model parameters using small amounts of parallel in-domain data, and may be further improved by using additional monolingual and parallel training data for adaptation of language and translation models. The average observed improvement in BLEU achieved is substantial at 15.30 points absolute.

  6. 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,…

  7. 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...... and programs for translator training. Meeting the goals of such a broad agenda requires the fusion of different theoretical and experimental tools, from fields such as cognitive psychology, linguistics, and artificial intelligence. From exploratory studies that aimed to carve out the problem space...

  8. Discriminative feature-rich models for syntax-based machine translation.

    Energy Technology Data Exchange (ETDEWEB)

    Dixon, Kevin R.

    2012-12-01

    This report describes the campus executive LDRD %E2%80%9CDiscriminative Feature-Rich Models for Syntax-Based Machine Translation,%E2%80%9D which was an effort to foster a better relationship between Sandia and Carnegie Mellon University (CMU). The primary purpose of the LDRD was to fund the research of a promising graduate student at CMU; in this case, Kevin Gimpel was selected from the pool of candidates. This report gives a brief overview of Kevin Gimpel's research.

  9. Improving a Japanese-Spanish Machine Translation System Using Wikipedia Medical Articles

    Directory of Open Access Journals (Sweden)

    Jessica C. Ramirez

    2015-02-01

    Full Text Available The quality, length and coverage of a parallel corp us are fundamental features in the performance of a Statistical Machine Translation Sy stem (SMT. For some pair of languages there is a considerable lack of resources suitable for Natural Language Processing tasks. This paper introduces a technique for extracting medical information from the Wikipedia page. Using a medical ontological dictionary and then we evaluate on a Japanese-Spanish SMT system. The study shows an increment in the BLEU sc ore.

  10. RuLearn: an Open-source Toolkit for the Automatic Inference of Shallow-transfer Rules for Machine Translation

    Directory of Open Access Journals (Sweden)

    Sánchez-Cartagena Víctor M.

    2016-10-01

    Full Text Available This paper presents ruLearn, an open-source toolkit for the automatic inference of rules for shallow-transfer machine translation from scarce parallel corpora and morphological dictionaries. ruLearn will make rule-based machine translation a very appealing alternative for under-resourced language pairs because it avoids the need for human experts to handcraft transfer rules and requires, in contrast to statistical machine translation, a small amount of parallel corpora (a few hundred parallel sentences proved to be sufficient. The inference algorithm implemented by ruLearn has been recently published by the same authors in Computer Speech & Language (volume 32. It is able to produce rules whose translation quality is similar to that obtained by using hand-crafted rules. ruLearn generates rules that are ready for their use in the Apertium platform, although they can be easily adapted to other platforms. When the rules produced by ruLearn are used together with a hybridisation strategy for integrating linguistic resources from shallow-transfer rule-based machine translation into phrase-based statistical machine translation (published by the same authors in Journal of Artificial Intelligence Research, volume 55, they help to mitigate data sparseness. This paper also shows how to use ruLearn and describes its implementation.

  11. 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.

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

    Science.gov (United States)

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

    2017-09-12

    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.

  13. 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.

  14. 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%.

  15. 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.

  16. 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.

  17. Reliability Approach for Machine Protection Design in Particle Accelerators

    CERN Document Server

    Apollonio, A; Mikulec, B; Puccio, B; Sanchez Alvarez, J L; Schmidt, R; Wagner, S

    2013-01-01

    Particle accelerators require Machine Protection Systems (MPS) to prevent beam-induced damage of equipment in case of failures. This becomes increasingly important for proton colliders with large energy stored in the beam such as LHC, for high power accelerators with a beam power of up to 10 MW, such as the European Spallation Source (ESS), and for linear colliders with high beam power and very small beam size. The reliability of Machine Protection Systems is crucial for safe machine operation; all possible sources of risk need to be taken into account in the early design stage. This paper presents a systematic approach to classify failures and to assess the associated risk, and discusses the impact of such considerations on the design of Machine Protection Systems. The application of this approach will be illustrated using the new design of the MPS for LINAC4, a linear accelerator under construction at CERN.

  18. Machine Learning Approaches for Modeling Spammer Behavior

    CERN Document Server

    Islam, Md Saiful; Islam, Md Rafiqul

    2010-01-01

    Spam is commonly known as unsolicited or unwanted email messages in the Internet causing potential threat to Internet Security. Users spend a valuable amount of time deleting spam emails. More importantly, ever increasing spam emails occupy server storage space and consume network bandwidth. Keyword-based spam email filtering strategies will eventually be less successful to model spammer behavior as the spammer constantly changes their tricks to circumvent these filters. The evasive tactics that the spammer uses are patterns and these patterns can be modeled to combat spam. This paper investigates the possibilities of modeling spammer behavioral patterns by well-known classification algorithms such as Na\\"ive Bayesian classifier (Na\\"ive Bayes), Decision Tree Induction (DTI) and Support Vector Machines (SVMs). Preliminary experimental results demonstrate a promising detection rate of around 92%, which is considerably an enhancement of performance compared to similar spammer behavior modeling research.

  19. Possessive Pronouns as Determiners in Japanese-to-English Machine Translation

    CERN Document Server

    Bond, F; Ikehara, S; Bond, Francis; Ogura, Kentaro; Ikehara, Satoru

    1996-01-01

    Possessive pronouns are used as determiners in English when no equivalent would be used in a Japanese sentence with the same meaning. This paper proposes a heuristic method of generating such possessive pronouns even when there is no equivalent in the Japanese. The method uses information about the use of possessive pronouns in English treated as a lexical property of nouns, in addition to contextual information about noun phrase referentiality and the subject and main verb of the sentence that the noun phrase appears in. The proposed method has been implemented in NTT Communication Science Laboratories' Japanese-to-English machine translation system ALT-J/E. In a test set of 6,200 sentences, the proposed method increased the number of noun phrases with appropriate possessive pronouns generated, by 263 to 609, at the cost of generating 83 noun phrases with inappropriate possessive pronouns.

  20. Remote leak localization approach for fusion machines

    Energy Technology Data Exchange (ETDEWEB)

    Durocher, Au., E-mail: aurelien.durocher@cea.fr [CEA-IRFM, F-13108 Saint Paul-Lez-Durance (France); Bruno, V.; Chantant, M.; Gargiulo, L. [CEA-IRFM, F-13108 Saint Paul-Lez-Durance (France); Gherman, T. [Floralis UJF Filiale, F-38610 Gières (France); Hatchressian, J.-C.; Houry, M.; Le, R.; Mouyon, D. [CEA-IRFM, F-13108 Saint Paul-Lez-Durance (France)

    2013-10-15

    Highlights: ► Description of leaks issue. ► Selection of leak localization concepts. ► Qualification of leak localization concepts. -- Abstract: Fusion machine operation requires high-vacuum conditions and does not tolerate water or gas leak in the vacuum vessels, even if they are micrometric. Tore Supra, as a fully actively cooled tokamak, has got a large leak management experience; 34 water leaks occurred since the beginning of its operation in 1988. To handle this issue, after preliminary machine protection phases, the current process for leak localization is based on water or helium pressurization network by network. It generally allows the identification of a set of components where the leakage element is located. However, the unique background of CEA-IRFM laboratory points needs of accuracy and promptness out in the leak localization process. Moreover, in-vessel interventions have to be performed trying to minimize time and risks for the persons. They are linked to access conditions, radioactivity, tracer gas high pressure and vessel conditioning. Remote operation will be one of the ways to improve these points on future fusion machines. In this case, leak sensors would have to be light weight devices in order to be integrated on a carrier or to be located outside with a sniffing process set up. A leak localization program is on-going at CEA-IRFM Laboratory with the first goal of identifying and characterizing relevant concepts to localize helium or water leaks on ITER. In the same time, CEA has developed robotic carrier for effective in-vessel intervention in a hostile environment. Three major tests campaigns with the goal to identify leak sensors have been achieved on several CEA test-beds since 2010. Very promising results have been obtained: relevant scenario of leak localization performed, concepts tested in a high volume test-bed called TITAN, and, in several conditions of pressure and temperature (ultrahigh vacuum to atmospheric pressure and 20

  1. Comparison of Parallel Kinematic Machines with Three Translational Degrees of Freedom and Linear Actuation

    Institute of Scientific and Technical Information of China (English)

    PRAUSE Isabel; CHARAF EDDINE Sami; CORVES Burkhard

    2015-01-01

    The development of new robot structures, in particular of parallel kinematic machines(PKM), is widely systematized by different structure synthesis methods. Recent research increasingly focuses on PKM with less than six degrees of freedom(DOF). However, an overall comparison and evaluation of these structures is missing. In order to compare symmetrical PKM with three translational DOF, different evaluation criteria are used. Workspace, maximum actuation forces and velocities, power, actuator stiffness, accuracy and transmission behavior are taken into account to investigate strengths and weaknesses of the PKMs. A selection scheme based on possible configurations of translational PKM including different frame configurations is presented. Moreover, an optimization method based on a genetic algorithm is described to determine the geometric parameters of the selected PKM for an exemplary load case and a prescribed workspace. The values of the mentioned criteria are determined for all considered PKM with respect to certain boundary conditions. The distribution and spreading of these values within the prescribed workspace is presented by using box plots for each criterion. Thereby, the performance characteristics of the different structures can be compared directly. The results show that there is no“best”PKM. Further inquiries such as dynamic or stiffness analysis are necessary to extend the comparison and to finally select a PKM.

  2. A Reordering Model Using a Source-Side Parse-Tree for Statistical Machine Translation

    Science.gov (United States)

    Hashimoto, Kei; Yamamoto, Hirofumi; Okuma, Hideo; Sumita, Eiichiro; Tokuda, Keiichi

    This paper presents a reordering model using a source-side parse-tree for phrase-based statistical machine translation. The proposed model is an extension of IST-ITG (imposing source tree on inversion transduction grammar) constraints. In the proposed method, the target-side word order is obtained by rotating nodes of the source-side parse-tree. We modeled the node rotation, monotone or swap, using word alignments based on a training parallel corpus and source-side parse-trees. The model efficiently suppresses erroneous target word orderings, especially global orderings. Furthermore, the proposed method conducts a probabilistic evaluation of target word reorderings. In English-to-Japanese and English-to-Chinese translation experiments, the proposed method resulted in a 0.49-point improvement (29.31 to 29.80) and a 0.33-point improvement (18.60 to 18.93) in word BLEU-4 compared with IST-ITG constraints, respectively. This indicates the validity of the proposed reordering model.

  3. OxLM: A Neural Language Modelling Framework for Machine Translation

    Directory of Open Access Journals (Sweden)

    Paul Baltescu

    2014-09-01

    Full Text Available This paper presents an open source implementation1 of a neural language model for machine translation. Neural language models deal with the problem of data sparsity by learning distributed representations for words in a continuous vector space. The language modelling probabilities are estimated by projecting a word's context in the same space as the word representations and by assigning probabilities proportional to the distance between the words and the context's projection. Neural language models are notoriously slow to train and test. Our framework is designed with scalability in mind and provides two optional techniques for reducing the computational cost: the so-called class decomposition trick and a training algorithm based on noise contrastive estimation. Our models may be extended to incorporate direct n-gram features to learn weights for every n-gram in the training data. Our framework comes with wrappers for the cdec and Moses translation toolkits, allowing our language models to be incorporated as normalized features in their decoders (inside the beam search.

  4. Quantifying complexity in translational research: an integrated approach

    Science.gov (United States)

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

    2014-01-01

    Purpose This article quantifies complexity in translational research. The impact of major operational steps and technical requirements (TR) is calculated with respect to their ability to accelerate moving new discoveries into clinical practice. Design/Methodology/Approach 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. Findings Generally, the evidence generated was valuable for understanding various components in translational research. Particularly, we found that collaboration networks, multidisciplinary team capacity and community engagement are crucial for translating new discoveries into practice. Research limitations/implications 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. Practical implications 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. Originality/value 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. PMID:25417380

  5. ABOUT COMPLEX APPROACH TO MODELLING OF TECHNOLOGICAL MACHINES FUNCTIONING

    Directory of Open Access Journals (Sweden)

    A. A. Honcharov

    2015-01-01

    Full Text Available Problems arise in the process of designing, production and investigation of a complicated technological machine. These problems concern not only properties of some types of equipment but they have respect to regularities of control object functioning as a whole. A technological machine is thought of as such technological complex where it is possible to lay emphasis on a control system (or controlling device and a controlled object. The paper analyzes a number of existing approaches to construction of models for controlling devices and their functioning. A complex model for a technological machine operation has been proposed in the paper; in other words it means functioning of a controlling device and a controlled object of the technological machine. In this case models of the controlling device and the controlled object of the technological machine can be represented as aggregate combination (elements of these models. The paper describes a conception on realization of a complex model for a technological machine as a model for interaction of units (elements in the controlling device and the controlled object. When a control activation is given to the controlling device of the technological machine its modelling is executed at an algorithmic or logic level and the obtained output signals are interpreted as events and information about them is transferred to executive mechanisms.The proposed scheme of aggregate integration considers element models as object classes and the integration scheme is presented as a combination of object property values (combination of a great many input and output contacts and combination of object interactions (in the form of an integration operator. Spawn of parent object descendants of the technological machine model and creation of their copies in various project parts is one of the most important means of the distributed technological machine modelling that makes it possible to develop complicated models of

  6. 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.

  7. A Comparative Study between Grammar-translation Approach and Communicative Approach

    Institute of Scientific and Technical Information of China (English)

    王卓; 李雅娟

    2009-01-01

    Grammar-translation Approach and Communicative Approach are both very important teaching method in the process of second language learning. This paper mainly discusses the connection between these two aproaches, and dis-cusses their distinct features.

  8. The Development of Meta-functional Approaches in Translation Studies

    Institute of Scientific and Technical Information of China (English)

    李菁菁

    2012-01-01

      Functional linguistics has exerted an increasing impact on modern linguistic studies. Functional approaches, especial⁃ly metafunctions have undergone a process of development and improvement. The affirmation of the metafunctions of lan⁃guage has aroused more and more scholars’concern on the“functional”facet of language, especially in Translation studies. The formation and improvement of functional approaches are introduced separately.

  9. On Grammar Translation Approach and Communicative Language Teaching

    Institute of Scientific and Technical Information of China (English)

    邓丽君

    2009-01-01

    Be driven by new knowledge abour the learner and the English language, foreign language teaching has developed into many different schools based on different theories. All them have their own advantages and disadvantages. Focusing on two of the most commonly used ones--the Grammar Translation Approach and Communicative Language Teaching this paper gives comments about these two different approaches and give advices that combine them together to promote guage teaching.

  10. Understanding bimolecular machines: Theoretical and experimental approaches

    Science.gov (United States)

    Goler, Adam Scott

    This dissertation concerns the study of two classes of molecular machines from a physical perspective: enzymes and membrane proteins. Though the functions of these classes of proteins are different, they each represent important test-beds from which new understanding can be developed by the application of different techniques. HIV1 Reverse Transcriptase is an enzyme that performs multiple functions, including reverse transcription of RNA into an RNA/DNA duplex, RNA degradation by the RNaseH domain, and synthesis of dsDNA. These functions allow for the incorporation of the retroviral genes into the host genome. Its catalytic cycle requires repeated large-scale conformational changes fundamental to its mechanism. Motivated by experimental work, these motions were studied theoretically by the application of normal mode analysis. It was observed that the lowest order modes correlate with largest amplitude (low-frequency) motion, which are most likely to be catalytically relevant. Comparisons between normal modes obtained via an elastic network model to those calculated from the essential dynamics of a series of all-atom molecular dynamics simulations show the self-consistency between these calculations. That similar conformational motions are seen between independent theoretical methods reinforces the importance of large-scale subdomain motion for the biochemical action of DNA polymerases in general. Moreover, it was observed that the major subunits of HIV1 Reverse Transcriptase interact quasi-harmonically. The 5HT3A Serotonin receptor and P2X1 receptor, by contrast, are trans-membrane proteins that function as ligand gated ion channels. Such proteins feature a central pore, which allows for the transit of ions necessary for cellular function across a membrane. The pore is opened by the ligation of binding sites on the extracellular portion of different protein subunits. In an attempt to resolve the individual subunits of these membrane proteins beyond the diffraction

  11. Quantitative systems pharmacology: a promising approach for translational pharmacology.

    Science.gov (United States)

    Gadkar, K; Kirouac, D; Parrott, N; Ramanujan, S

    Biopharmaceutical companies have increasingly been exploring Quantitative Systems Pharmacology (QSP) as a potential avenue to address current challenges in drug development. In this paper, we discuss the application of QSP modeling approaches to address challenges in the translational of preclinical findings to the clinic, a high risk area of drug development. Three cases have been highlighted with QSP models utilized to inform different questions in translational pharmacology. In the first, a mechanism based asthma model is used to evaluate efficacy and inform biomarker strategy for a novel bispecific antibody. In the second case study, a mitogen-activated protein kinase (MAPK) pathway signaling model is used to make translational predictions on clinical response and evaluate novel combination therapies. In the third case study, a physiologically based pharmacokinetic (PBPK) model it used to guide administration of oseltamivir in pediatric patients.

  12. Translational Approaches towards Cancer Gene Therapy: Hurdles and Hopes

    Directory of Open Access Journals (Sweden)

    Yadollah Omidi

    2012-09-01

    Full Text Available Introduction: Of the cancer gene therapy approaches, gene silencing, suicide/apoptosis inducing gene therapy, immunogene therapy and targeted gene therapy are deemed to sub­stantially control the biological consequences of genomic changes in cancerous cells. Thus, a large number of clinical trials have been conducted against various malignancies. In this review, we will discuss recent translational progresses of gene and cell therapy of cancer. Methods: Essential information on gene therapy of cancer were reviewed and discussed towards their clinical translations. Results: Gene transfer has been rigorously studied in vitro and in vivo, in which some of these gene therapy endeavours have been carried on towards translational investigations and clinical applications. About 65% of gene therapy trials are related to cancer therapy. Some of these trials have been combined with cell therapy to produce personalized medicines such as Sipuleucel-T (Provenge®, marketed by Dendreon, USA for the treatment of asymptomatic/minimally symptomatic metastatic hormone-refractory prostate cancer. Conclusion: Translational approach links two diverse boundaries of basic and clinical researches. For successful translation of geno­medicines into clinical applications, it is essential 1 to have the guidelines and standard operating procedures for development and application of the genomedicines specific to clinically relevant biomarker(s; 2 to conduct necessary animal experimental studies to show the “proof of concept” for the proposed genomedicines; 3 to perform an initial clinical investigation; and 4 to initiate extensive clinical trials to address all necessary requirements. In short, translational researches need to be refined to accelerate the geno­medicine development and clinical applications.

  13. A nonparametric Bayesian method of translating machine learning scores to probabilities in clinical decision support.

    Science.gov (United States)

    Connolly, Brian; Cohen, K Bretonnel; Santel, Daniel; Bayram, Ulya; Pestian, John

    2017-08-07

    Probabilistic assessments of clinical care are essential for quality care. Yet, machine learning, which supports this care process has been limited to categorical results. To maximize its usefulness, it is important to find novel approaches that calibrate the ML output with a likelihood scale. Current state-of-the-art calibration methods are generally accurate and applicable to many ML models, but improved granularity and accuracy of such methods would increase the information available for clinical decision making. This novel non-parametric Bayesian approach is demonstrated on a variety of data sets, including simulated classifier outputs, biomedical data sets from the University of California, Irvine (UCI) Machine Learning Repository, and a clinical data set built to determine suicide risk from the language of emergency department patients. The method is first demonstrated on support-vector machine (SVM) models, which generally produce well-behaved, well understood scores. The method produces calibrations that are comparable to the state-of-the-art Bayesian Binning in Quantiles (BBQ) method when the SVM models are able to effectively separate cases and controls. However, as the SVM models' ability to discriminate classes decreases, our approach yields more granular and dynamic calibrated probabilities comparing to the BBQ method. Improvements in granularity and range are even more dramatic when the discrimination between the classes is artificially degraded by replacing the SVM model with an ad hoc k-means classifier. The method allows both clinicians and patients to have a more nuanced view of the output of an ML model, allowing better decision making. The method is demonstrated on simulated data, various biomedical data sets and a clinical data set, to which diverse ML methods are applied. Trivially extending the method to (non-ML) clinical scores is also discussed.

  14. A GA-Based Approach for FMS Machine Loading Planing

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    The machine loading problem in flexible manufacturing system isaddressed in this paper. The problem is modelled as a mixed integer program. A Genetic Algorithm (GA) approach is developed to yield an optimal solution. In the genetic algorithm, chromosomes are encoded in term of operation routes. A point-to-point crossover search operator together with a Cyclic Shifting Mutation (CSM) operator is designed to adapt to the problem. At last computational experience with the model is presented, and the results show that our genetic algorithms are very powerful and suitable to machine loading problems.

  15. 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.

  16. Prediction of post-translational modification sites using multiple kernel support vector machine

    Directory of Open Access Journals (Sweden)

    BingHua Wang

    2017-04-01

    Full Text Available Protein post-translational modification (PTM is an important mechanism that is involved in the regulation of protein function. Considering the high-cost and labor-intensive of experimental identification, many computational prediction methods are currently available for the prediction of PTM sites by using protein local sequence information in the context of conserved motif. Here we proposed a novel computational method by using the combination of multiple kernel support vector machines (SVM for predicting PTM sites including phosphorylation, O-linked glycosylation, acetylation, sulfation and nitration. To largely make use of local sequence information and site-modification relationships, we developed a local sequence kernel and Gaussian interaction profile kernel, respectively. Multiple kernels were further combined to train SVM for efficiently leveraging kernel information to boost predictive performance. We compared the proposed method with existing PTM prediction methods. The experimental results revealed that the proposed method performed comparable or better performance than the existing prediction methods, suggesting the feasibility of the developed kernels and the usefulness of the proposed method in PTM sites prediction.

  17. Application of TRIZ approach to machine vibration condition monitoring problems

    Science.gov (United States)

    Cempel, Czesław

    2013-12-01

    Up to now machine condition monitoring has not been seriously approached by TRIZ1TRIZ= Russian acronym for Inventive Problem Solving System, created by G. Altshuller ca 50 years ago. users, and the knowledge of TRIZ methodology has not been applied there intensively. However, there are some introductory papers of present author posted on Diagnostic Congress in Cracow (Cempel, in press [11]), and Diagnostyka Journal as well. But it seems to be further need to make such approach from different sides in order to see, if some new knowledge and technology will emerge. In doing this we need at first to define the ideal final result (IFR) of our innovation problem. As a next we need a set of parameters to describe the problems of system condition monitoring (CM) in terms of TRIZ language and set of inventive principles possible to apply, on the way to IFR. This means we should present the machine CM problem by means of contradiction and contradiction matrix. When specifying the problem parameters and inventive principles, one should use analogy and metaphorical thinking, which by definition is not exact but fuzzy, and leads sometimes to unexpected results and outcomes. The paper undertakes this important problem again and brings some new insight into system and machine CM problems. This may mean for example the minimal dimensionality of TRIZ engineering parameter set for the description of machine CM problems, and the set of most useful inventive principles applied to given engineering parameter and contradictions of TRIZ.

  18. Practical approach to apply range image sensors in machine automation

    Science.gov (United States)

    Moring, Ilkka; Paakkari, Jussi

    1993-10-01

    In this paper we propose a practical approach to apply range imaging technology in machine automation. The applications we are especially interested in are industrial heavy-duty machines like paper roll manipulators in harbor terminals, harvesters in forests and drilling machines in mines. Characteristic of these applications is that the sensing system has to be fast, mid-ranging, compact, robust, and relatively cheap. On the other hand the sensing system is not required to be generic with respect to the complexity of scenes and objects or number of object classes. The key in our approach is that just a limited range data set or as we call it, a sparse range image is acquired and analyzed. This makes both the range image sensor and the range image analysis process more feasible and attractive. We believe that this is the way in which range imaging technology will enter the large industrial machine automation market. In the paper we analyze as a case example one of the applications mentioned and, based on that, we try to roughly specify the requirements for a range imaging based sensing system. The possibilities to implement the specified system are analyzed based on our own work on range image acquisition and interpretation.

  19. Quantum Machine and SR Approach: a Unified Model

    CERN Document Server

    Garola, C; Sozzo, S; Garola, Claudio; Pykacz, Jaroslav; Sozzo, Sandro

    2005-01-01

    The Geneva-Brussels approach to quantum mechanics (QM) and the semantic realism (SR) nonstandard interpretation of QM exhibit some common features and some deep conceptual differences. We discuss in this paper two elementary models provided in the two approaches as intuitive supports to general reasonings and as a proof of consistency of general assumptions, and show that Aerts' quantum machine can be embodied into a macroscopic version of the microscopic SR model, overcoming the seeming incompatibility between the two models. This result provides some hints for the construction of a unified perspective in which the two approaches can be properly placed.

  20. 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].

  1. Apertium goes SOA: an efficient and scalable service based on the Apertium rule-based machine translation platform

    OpenAIRE

    Minervini, Pasquale

    2009-01-01

    Service Oriented Architecture (SOA) is a paradigm for organising and using distributed services that may be under the control of different ownership domains and implemented using various technology stacks. In some contexts, an organisation using an IT infrastructure implementing the SOA paradigm can take a great benefit from the integration, in its business processes, of efficient machine translation (MT) services to overcome language barriers. This paper describes the architecture and the de...

  2. Evaluating machine learning classification for financial trading: An empirical approach

    OpenAIRE

    Gerlein, EA; McGinnity, M; Belatreche, A; Coleman, S.

    2016-01-01

    Technical and quantitative analysis in financial trading use mathematical and statistical tools to help investors decide on the optimum moment to initiate and close orders. While these traditional approaches have served their purpose to some extent, new techniques arising from the field of computational intelligence such as machine learning and data mining have emerged to analyse financial information. While the main financial engineering research has focused on complex computational models s...

  3. Transdisciplinary approaches enhance the production of translational knowledge.

    Science.gov (United States)

    Ciesielski, Timothy H; Aldrich, Melinda C; Marsit, Carmen J; Hiatt, Robert A; Williams, Scott M

    2017-04-01

    The primary goal of translational research is to generate and apply knowledge that can improve human health. Although research conducted within the confines of a single discipline has helped us to achieve this goal in many settings, this unidisciplinary approach may not be optimal when disease causation is complex and health decisions are pressing. To address these issues, we suggest that transdisciplinary approaches can facilitate the progress of translational research, and we review publications that demonstrate what these approaches can look like. These examples serve to (1) demonstrate why transdisciplinary research is useful, and (2) stimulate a conversation about how it can be further promoted. While we note that open-minded communication is a prerequisite for germinating any transdisciplinary work and that epidemiologists can play a key role in promoting it, we do not propose a rigid protocol for conducting transdisciplinary research, as one really does not exist. These achievements were developed in settings where typical disciplinary and institutional barriers were surmountable, but they were not accomplished with a single predetermined plan. The benefits of cross-disciplinary communication are hard to predict a priori and a detailed research protocol or process may impede the realization of novel and important insights. Overall, these examples demonstrate that enhanced cross-disciplinary information exchange can serve as a starting point that helps researchers frame better questions, integrate more relevant evidence, and advance translational knowledge more effectively. Specifically, we discuss examples where transdisciplinary approaches are helping us to better explore, assess, and intervene to improve human health. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

  4. 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.

  5. Comparison of Machine Learning Approaches on Arabic Twitter Sentiment Analysis

    Directory of Open Access Journals (Sweden)

    Merfat.M. Altawaier

    2016-12-01

    Full Text Available With the dramatic expansion of information over internet, users around the world express their opinion daily on the social network such as Facebook and Twitter. Large corporations nowadays invest on analyzing these opinions in order to assess their products or services by knowing the people feedback toward such business. The process of knowing users’ opinions toward particular product or services whether positive or negative is called sentiment analysis. Arabic is one of the common languages that have been addressed regarding sentiment analysis. In the literature, several approaches have been proposed for Arabic sentiment analysis and most of these approaches are using machine learning techniques. Machine learning techniques are various and have different performances. Therefore, in this study, we try to identifying a simple, but workable approach for Arabic sentiment analysis on Twitter. Hence, this study aims to investigate the machine learning technique in terms of Arabic sentiment analysis on Twitter. Three techniques have been used including Naïve Bayes, Decision Tree (DT and Support Vector Machine (SVM. In addition, two simple sub-tasks pre-processing have been also used; Term Frequency-Inverse Document Frequency (TF-IDF and Arabic stemming to get the heaviest weight term as the feature for tweet classification. TF-IDF aims to identify the most frequent words, whereas stemming aims to retrieve the stem of the word by removing the inflectional derivations. The dataset that has been used is Modern Arabic Corpus which consists of Arabic tweets. The performance of classification has been evaluated based on the information retrieval metrics precision, recall and f-measure. The experimental results have shown that DT has outperformed the other techniques by obtaining 78% of f-measure.

  6. A machine learning approach to extract spinal column centerline from three-dimensional CT data

    Science.gov (United States)

    Wang, Caihua; Li, Yuanzhong; Ito, Wataru; Shimura, Kazuo; Abe, Katsumi

    2009-02-01

    The spinal column is one of the most important anatomical structures in the human body and its centerline, that is, the centerline of vertebral bodies, is a very important feature used by many applications in medical image processing. In the past, some approaches have been proposed to extract the centerline of spinal column by using edge or region information of vertebral bodies. However, those approaches may suffer from difficulties in edge detection or region segmentation of vertebral bodies when there exist vertebral diseases such as osteoporosis, compression fracture. In this paper, we propose a novel approach based on machine learning to robustly extract the centerline of the spinal column from threedimensional CT data. Our approach first applies a machine learning algorithm, called AdaBoost, to detect vertebral cord regions, which have a S-shape similar to and close to, but can be detected more stably than, the spinal column. Then a centerline of detected vertebral cord regions is obtained by fitting a spline curve to their central points, using the associated AdaBoost scores as weights. Finally, the obtained centerline of vertebral cord is linearly deformed and translated in the sagittal direction to fit the top and bottom boundaries of the vertebral bodies and then a centerline of the spinal column is obtained. Experimental results on a large CT data set show the effectiveness of our approach.

  7. Devised Guidelines of Rapid Post-Editing in Machine Translation Out⁃put of Mark on Some Aspects

    Institute of Scientific and Technical Information of China (English)

    屈亚媛; 王庆怡

    2012-01-01

      One of uses of machine translation (MT), is helping readers to read for the gist of a foreign text through a draft translation produced by MT engines. Rapid post-editing, as Jeffrey Allen defines it as a“strictly minimal editing on texts in order to remove blatant and significant errors without considering stylistic issues”, can help present the reader with a roughly comprehensible translation as quickly as possible. The purpose of this article is on a proposed set of rapid post-editing guidelines for Biblical Chinese-English MT, with its application on editing the English MT version of Chapter one of Mark (马尔谷福音) of the Chinese Catholic Bible (天主教思高本圣经) as an example.

  8. 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.

  9. 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.

  10. TSMC: A Novel Approach for Live Virtual Machine Migration

    Directory of Open Access Journals (Sweden)

    Jiaxing Song

    2014-01-01

    Full Text Available Cloud computing attracted more and more attention in recent years, and virtualization technology is the key point for deploying infrastructure services in cloud environment. It allows application isolation and facilitates server consolidation, load balancing, fault management, and power saving. Live virtual machine migration can effectively relocate virtual resources and it has become an important management method in clusters and data centers. Existing precopy live migration approach has to iteratively copy redundant memory pages; another postcopy live migration approach would lead to a lot of page faults and application degradation. In this paper, we present a novel approach called TSMC (three-stage memory copy for live virtual machine migration. In TSMC, memory pages only need to be transmitted twice at most and page fault just occurred in small part of dirty pages. We implement it in Xen and compare it with Xen’s original precopy approach. The experimental results under various memory workloads show that TSMC approach can significantly reduce the cumulative migration time and total pages transferred and achieve better network IO performance in the same time.

  11. On Approaches to C-E Translation of Chinese Dish Names

    Institute of Scientific and Technical Information of China (English)

    ZHANG Zi-shun

    2015-01-01

    Literal translation and free translation are the most common methods of translation. It may be accepted that either the two methods or one, or neither on account of the different understandings of the two methods. The author tries to probe into some approaches to C-E translation of Chinese dish names according to the contrastive studies between Chinese and English dish names.

  12. 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.

  13. 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

  14. UNITRAN (UNIversal TRANslator): A Principle-Based Approach to Machine Translation.

    Science.gov (United States)

    1987-12-01

    external (agent animate)) (noun-form (muertc, f en) (subcat (patient animate))) (adj-torm ( muert /A) (subcat (cause)))" I’ muer /ER-IR-PRES "(root...bed))) inanimate" ’ * cart IN "(english ((letter))) inanimate" .. cas IN "(english ((house))) inanimate" cine /N "(english ((movie))) masc

  15. Novel statistical approaches to text classification, machine translation and computer-assisted translation

    OpenAIRE

    Civera Saiz, Jorge

    2008-01-01

    Esta tesis presenta diversas contribuciones en los campos de la clasificación automática de texto, traducción automática y traducción asistida por ordenador bajo el marco estadístico. En clasificación automática de texto, se propone una nueva aplicación llamada clasificación de texto bilingüe junto con una serie de modelos orientados a capturar dicha información bilingüe. Con tal fin se presentan dos aproximaciones a esta aplicación; la primera de ellas se ...

  16. An Efficient Audio Classification Approach Based on Support Vector Machines

    Directory of Open Access Journals (Sweden)

    Lhoucine Bahatti

    2016-05-01

    Full Text Available In order to achieve an audio classification aimed to identify the composer, the use of adequate and relevant features is important to improve performance especially when the classification algorithm is based on support vector machines. As opposed to conventional approaches that often use timbral features based on a time-frequency representation of the musical signal using constant window, this paper deals with a new audio classification method which improves the features extraction according the Constant Q Transform (CQT approach and includes original audio features related to the musical context in which the notes appear. The enhancement done by this work is also lay on the proposal of an optimal features selection procedure which combines filter and wrapper strategies. Experimental results show the accuracy and efficiency of the adopted approach in the binary classification as well as in the multi-class classification.

  17. 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.

  18. 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....

  19. Testing the committee approach to translating measures across cultures: Translating primary communication inventory from English to Japanese.

    Science.gov (United States)

    Furukawa, Ryoko; Driessnack, Martha

    2016-12-01

    This paper presents the initial translation process and follow-up psychometric evaluation of the Japanese version of the Primary Communication Inventory (J-PCI). The J-PCI was developed using the committee approach to translation and then used in a study exploring Japanese couples' communication satisfaction while separated during Satogaeri Bunben - a Japanese perinatal tradition. The committee approach attends to cultural nuance and context and is especially useful when languages have dissimilar linguistic roots and cultures, such as Japanese and English. The translation process and evaluation included five steps; (i) selection of the original PCI for research; (ii) selection of translators; (iii) development of the J-PCI using a committee approach; (iv) an initial small pilot study; and (v) a larger follow-up study. The J-PCI has good initial validity and reliability, although some nuances were observed in scoring.

  20. Conception d'une methodologie generale d'evaluation de la traduction automatique (Conception of a General Methodology for Evaluating Machine Translation).

    Science.gov (United States)

    van Slype, Georges

    1982-01-01

    It is proposed that assessment of human translation versus machine translation programs use methods and criteria that measure efficiency and cost effectiveness and are efficient and cost-effective in themselves. A variety of methods and criteria are evaluated and discussed. (MSE)

  1. Translational Systems Approaches to the Biology of Inflammation and Healing

    Science.gov (United States)

    Vodovotz, Yoram; Constantine, Gregory; Faeder, James; Mi, Qi; Rubin, Jonathan; Bartels, John; Sarkar, Joydeep; Squires, Robert H.; Okonkwo, David O.; Gerlach, Jörg; Zamora, Ruben; Luckhart, Shirley; Ermentrout, Bard; An, Gary

    2011-01-01

    Inflammation is a complex, non-linear process central to many of the diseases that affect both developed and emerging nations. A systems-based understanding of inflammation, coupled to translational applications, is therefore necessary for efficient development of drugs and devices, for streamlining analyses at the level of populations, and for the implementation of personalized medicine. We have carried out an iterative and ongoing program of literature analysis, generation of prospective data, data analysis, and computational modeling in various experimental and clinical inflammatory disease settings. These simulations have been used to gain basic insights into the inflammatory response under baseline, gene-knockout, and drug-treated experimental animals for in silico studies associated with the clinical settings of sepsis, trauma, acute liver failure, and wound healing to create patient-specific simulations in polytrauma, traumatic brain injury, and vocal fold inflammation; and to gain insight into host-pathogen interactions in malaria, necrotizing enterocolitis, and sepsis. These simulations have converged with other systems biology approaches (e.g., functional genomics) to aid in the design of new drugs or devices geared towards modulating inflammation. Since they include both circulating and tissue-level inflammatory mediators, these simulations transcend typical cytokine networks by associating inflammatory processes with tissue/organ impacts via tissue damage/dysfunction. This framework has now allowed us to suggest how to modulate acute inflammation in a rational, individually optimized fashion. This plethora of computational and intertwined experimental/engineering approaches is the cornerstone of Translational Systems Biology approaches for inflammatory diseases. PMID:20170421

  2. 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

  3. 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.

  4. 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

    2017-02-01

    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.

  5. Ideology and Translation: A Critical Discourse Analysis Approach towards the Representation of Political News in Translation

    Directory of Open Access Journals (Sweden)

    Mahdi Aslani

    2015-05-01

    Full Text Available Recently the impact of ideology of the powerful agents namely- Political Parties, News Agencies and even the translators- on the translation has been considered significantly among the translation scholars. This study investigates the role of ideology in translating news media. To this end, we utilize Norman Fairclough's assumptions in critical discourse analysis, claiming that "ideologies reside in texts" that "it is not possible to read off' ideologies from texts" and that "texts are open to diverse interpretations" (Fairclough, 1995a It also follows Lefevere’s (1992a, 1992b Patronage theory. In this paper, we will compare the news texts with their translations in order to reveal the role of ideology in the translation process. Keywords: Ideology, Critical Discourse Analysis, Patronage

  6. A machine learning approach to nonlinear modal analysis

    Science.gov (United States)

    Worden, K.; Green, P. L.

    2017-02-01

    Although linear modal analysis has proved itself to be the method of choice for the analysis of linear dynamic structures, its extension to nonlinear structures has proved to be a problem. A number of competing viewpoints on nonlinear modal analysis have emerged, each of which preserves a subset of the properties of the original linear theory. From the geometrical point of view, one can argue that the invariant manifold approach of Shaw and Pierre is the most natural generalisation. However, the Shaw-Pierre approach is rather demanding technically, depending as it does on the analytical construction of a mapping between spaces, which maps physical coordinates into invariant manifolds spanned by independent subsets of variables. The objective of the current paper is to demonstrate a data-based approach motivated by Shaw-Pierre method which exploits the idea of statistical independence to optimise a parametric form of the mapping. The approach can also be regarded as a generalisation of the Principal Orthogonal Decomposition (POD). A machine learning approach to inversion of the modal transformation is presented, based on the use of Gaussian processes, and this is equivalent to a nonlinear form of modal superposition. However, it is shown that issues can arise if the forward transformation is a polynomial and can thus have a multi-valued inverse. The overall approach is demonstrated using a number of case studies based on both simulated and experimental data.

  7. A new DFM approach to combine machining and additive manufacturing

    CERN Document Server

    Kerbrat, Olivier; Hascoët, Jean-Yves; 10.1016/j.compind.2011.04.003

    2011-01-01

    Design For Manufacturing (DFM) approaches aim to integrate manufacturability aspects during the design stage. Most of DFM approaches usually consider only one manufacturing process, but products competitiveness may be improved by designing hybrid modular products, in which products are seen as 3-D puzzles with modules realized aside by the best manufacturing process and further gathered. A new DFM system is created in order to give quantitative information during the product design stage of which modules will benefit in being machined and which ones will advantageously be realized by an additive process (such as Selective Laser Sintering or laser deposition). A methodology for a manufacturability evaluation in case of a subtractive or an additive manufacturing process is developed and implemented in a CAD software. Tests are carried out on industrial products from automotive industry.

  8. Support vector machine approach for protein subcellular localization prediction.

    Science.gov (United States)

    Hua, S; Sun, Z

    2001-08-01

    Subcellular localization is a key functional characteristic of proteins. A fully automatic and reliable prediction system for protein subcellular localization is needed, especially for the analysis of large-scale genome sequences. In this paper, Support Vector Machine has been introduced to predict the subcellular localization of proteins from their amino acid compositions. The total prediction accuracies reach 91.4% for three subcellular locations in prokaryotic organisms and 79.4% for four locations in eukaryotic organisms. Predictions by our approach are robust to errors in the protein N-terminal sequences. This new approach provides superior prediction performance compared with existing algorithms based on amino acid composition and can be a complementary method to other existing methods based on sorting signals. A web server implementing the prediction method is available at http://www.bioinfo.tsinghua.edu.cn/SubLoc/. Supplementary material is available at http://www.bioinfo.tsinghua.edu.cn/SubLoc/.

  9. 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.

  10. A survey of statistical machine translation using paraphrasing technology%引入复述技术的统计机器翻译研究综述

    Institute of Scientific and Technical Information of China (English)

    2013-01-01

      基于对引入复述技术的统计机器翻译研究现状的分析,提出具有研究价值的课题方向。首先归纳了复述的概念,总结了引入复述技术的统计机器翻译各类方法。然后对复述知识在统计机器翻译中的模型训练、参数调整、待译语句改写和机器翻译自动评测等方面应用的主流方法进行了概括、比较和分析,说明了复述与统计机器翻译是紧密相关的,强调了复述在统计机器翻译应用中的关键问题是复述的正确性和多样性。最后指出提高复述资源的精确度、建立复述与机器翻译的联合模型、采用新方法解决稀疏问题等是有待进一步研究的课题。%In this paper, the research team discussed possible new prospective research directions of paraphrasing technology in statistical machine translation (SMT), based on reviews of state-of-the-art technology.First the re-search team introduced the concept of paraphrases , and next a summarization of the latest progress utilizing para-phrasing technology in SMT was conducted.Finally, conclusions were drawn, data was compared and an analysis of the main issues of incorporating paraphrases into SMT , including translation model training, parameter tuning, in-put sentences rewriting and machine translation evaluation was performed .The results proved that there is an inher-ent connection between paraphrasing and SMT .The results also point out that the correctness and diversity of para-phrasing are the key issues to apply paraphrasing to SMT .It was highly noted that the improvement in the quality of paraphrasing resource, the establishment of a joint model of paraphrasing and machine translation and the new pro -posed approach to solve data sparseness are problems which need further study .

  11. 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.

  12. 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...

  13. 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...

  14. Supporting knowledge translation through collaborative translational research initiatives: 'bridging' versus 'blurring' boundary-spanning approaches in the UK CLAHRC initiative.

    Science.gov (United States)

    Evans, Sarah; Scarbrough, Harry

    2014-04-01

    Recent policy initiatives in the UK and internationally have sought to promote knowledge translation between the 'producers' and 'users' of research. Within this paper we explore how boundary-spanning interventions used within such initiatives can support knowledge translation between diverse groups. Using qualitative data from a 3-year research study conducted from January 2010 to December 2012 of two case-sites drawn from the CLAHRC initiative in the UK, we distinguish two different approaches to supporting knowledge translation; a 'bridging' approach that involves designated roles, discrete events and activities to span the boundaries between communities, and a 'blurring' approach that de-emphasises the boundaries between groups, enabling a more continuous process of knowledge translation as part of day-to-day work-practices. In this paper, we identify and differentiate these boundary-spanning approaches and describe how they emerged from the context defined by the wider CLAHRC networks. This highlights the need to develop a more contextualised analysis of the boundary-spanning that underpins knowledge translation processes, relating this to the distinctive features of a particular case.

  15. Translation

    OpenAIRE

    2005-01-01

    "Translation" is a life narrative about the ways in which cultural histories shape personal stories, and the capacity of the imagination to develop alternative narratives about oneself and the world. It can also be read a way of addressing the effects of what Ato Quayson calls the global process of postcolonializing. Quaysons critical perspective might be used as an interpretive lens for seeing some of the ways in which  this autobiographical narrative complicates the jargon of race, cl...

  16. Translation

    OpenAIRE

    2005-01-01

    "Translation" is a life narrative about the ways in which cultural histories shape personal stories, and the capacity of the imagination to develop alternative narratives about oneself and the world. It can also be read a way of addressing the effects of what Ato Quayson calls the global process of postcolonializing. Quaysons critical perspective might be used as an interpretive lens for seeing some of the ways in which  this autobiographical narrative complicates the jargon of race, class, ...

  17. Machine Learning Approaches for Predicting Protein Complex Similarity.

    Science.gov (United States)

    Farhoodi, Roshanak; Akbal-Delibas, Bahar; Haspel, Nurit

    2017-01-01

    Discriminating native-like structures from false positives with high accuracy is one of the biggest challenges in protein-protein docking. While there is an agreement on the existence of a relationship between various favorable intermolecular interactions (e.g., Van der Waals, electrostatic, and desolvation forces) and the similarity of a conformation to its native structure, the precise nature of this relationship is not known. Existing protein-protein docking methods typically formulate this relationship as a weighted sum of selected terms and calibrate their weights by using a training set to evaluate and rank candidate complexes. Despite improvements in the predictive power of recent docking methods, producing a large number of false positives by even state-of-the-art methods often leads to failure in predicting the correct binding of many complexes. With the aid of machine learning methods, we tested several approaches that not only rank candidate structures relative to each other but also predict how similar each candidate is to the native conformation. We trained a two-layer neural network, a multilayer neural network, and a network of Restricted Boltzmann Machines against extensive data sets of unbound complexes generated by RosettaDock and PyDock. We validated these methods with a set of refinement candidate structures. We were able to predict the root mean squared deviations (RMSDs) of protein complexes with a very small, often less than 1.5 Å, error margin when trained with structures that have RMSD values of up to 7 Å. In our most recent experiments with the protein samples having RMSD values up to 27 Å, the average prediction error was still relatively small, attesting to the potential of our approach in predicting the correct binding of protein-protein complexes.

  18. Improving Statistical Machine Translation Through N-best List Re-ranking and Optimization

    Science.gov (United States)

    2014-03-27

    Language Processing, 1352–1362. Association for Computational Linguistics, Edinburgh, Scotland , UK., July 2011. URL http://www.aclweb.org/anthology/D11-1125...Josef. “Minimum Error Rate Training in Statistical Machine Translation”. Erhard Hinrichs and Dan Roth (editors), Proceedings of the 41st Annual Meeting of

  19. 理性主义与经验主义相结合的机器翻译研究策略%Rationalism and Empiricism on the Combination in Machine Translation

    Institute of Scientific and Technical Information of China (English)

    徐金安

    2011-01-01

    主要介绍了基于规则、基于实例和基于统计等3种主流机器翻译方法,探讨了自然语言处理技术和机器翻译中基于规则的理性主义方法和基于统计的经验主义方法的优缺点,结合机器翻译研究的现状和发展方向,提出了规则和统计相结合的机器翻译方法的基本思路,阐述了词义消歧中的理性主义方法和经验主义方法相结合的发展方向,对机器翻译的发展趋势进行了探讨.%This paper firstly discussed the development of machine translation, secondly described the advantages and disadvantages of the rationalism and empiricism in natural language processing and machine translation, and thirdly introduced our basic ideas of combination of the rule-based approach and statistical approach.Furthermore, the paper deliberated the tendency of combination of the rationalism and empiricism in word sense disambiguation, finally summarized the developmental tendency of machine translation.

  20. 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…

  1. A Vectorial modeling for the pentaphase Permanent Magnet Synchronous Machine based on multimachine approach

    Directory of Open Access Journals (Sweden)

    Abdelkrim Sellam

    2012-12-01

    Full Text Available The polyphase [1] machines are developed mainly in the field of variable speed drives of high power because increasing the number of phases on the one hand allows to reduce the dimensions of the components in power modulators energy and secondly to improve the operating safety. By a vector approach (vector space, it is possible to find a set of single-phase machine and / or two-phase fictitious equivalent to polyphase synchronous machine.These fictitious machines are coupled electrically and mechanically but decoupled magnetically. This approach leads to introduce the concept of the equivalent machine (multimachine multiconverter system MMS which aims to analyze systems composed of multiple machines (or multiple converters in electric drives. A first classification multimachine multiconverter system follows naturally from MMS formalism. We present an example of a synchronous machine pent phase.

  2. Exeter at CLEF 2003: Experiments with machine translation for monolingual, bilingual and multilingual retrieval

    OpenAIRE

    Lam-Adesina, Adenike M.; Jones, Gareth J.F.

    2004-01-01

    The University of Exeter group participated in the monolingual, bilingual and multilingual-4 retrieval tasks this year. The main focus of our investigation this year was the small multilingual task comprising four languages, French, German, Spanish and English. We adopted a document translation strategy and tested four merging techniques to combine results from the separate document collections, as well as a merged collection strategy. For both the monolingual and bilingual tasks we explored ...

  3. 78 FR 12764 - Draft Office of Health Assessment and Translation Approach for Systematic Review and Evidence...

    Science.gov (United States)

    2013-02-25

    ... From the Federal Register Online via the Government Publishing Office DEPARTMENT OF HEALTH AND HUMAN SERVICES National Institutes of Health Draft Office of Health Assessment and Translation Approach... comments on the Draft Office of Health Assessment and Translation (OHAT) Approach for Systematic Review...

  4. A multidimensional approach to aligned sentences in translated text

    Directory of Open Access Journals (Sweden)

    Gard Buen Jenset

    2013-04-01

    Full Text Available Using unsupervised clustering techniques this study explores sentence alignment patterns in a parallel corpus of Norwegian source texts and Spanish translations, the NSPC (Hareide and Hofland 2012. The results show that three strategies with respect to sentence alignment dominate: one to one correspondence, merging two sentences into one, and removing sentences altogether (omission. The strategies are intricately correlated with the variables translator, author, and genre. However, we show how visualization techniques for cluster analyses offer a possibility for teasing apart these interactions as well as their relative importance. Our results indicate that non-fiction texts allow translators more freedom with respect to the treatment of sentences than do texts that are written by professional authors of fiction. The style of the author appears to play only a secondary role, but is especially important in fiction.   Keywords: corpus based translation, cluster analysis, parallel corpora, corpus alignment, unidirectional bilingual corpus

  5. 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...

  6. 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.

  7. 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 m

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

    NARCIS (Netherlands)

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

  9. Based on HNC Theory of Machine Translation Research ---English-Chinese Translation%基于HNC理论机助人译--英汉翻译对比研究

    Institute of Scientific and Technical Information of China (English)

    陆小鹿

    2014-01-01

    [Abstract]Machine Translation is indispensable to modern information era to overcome barriers of the language communication . HNC theory by using the method of primitives, hierarchical, network, formal, integrates the sentence structures with semantics, Based on the HNC theory, interprets the conversion of sentence category and patterns between English and Chinese and Contrast between English and Chinese.%机器翻译是现代信息时代克服语言交流障碍不可缺少的的手段。 HNC理论采用基元化、层次化、网络化、形式化的方法,通过句类精妙地把自然语言的表层结构和深层语义联系起来。通过机器翻译,对比研究英汉翻译中的句类句式转换的问题。

  10. Qualitative: Open Source Python Tool for Quality Estimation over Multiple Machine Translation Outputs

    Directory of Open Access Journals (Sweden)

    Eleftherios Avramidis

    2014-09-01

    Full Text Available “Qualitative” is a python toolkit for ranking and selection of sentence-level output by different MT systems using Quality Estimation. The toolkit implements a basic pipeline for annotating the given sentences with black-box features. Consequently, it applies a machine learning mechanism in order to rank data based on models pre-trained on human preferences. The preprocessing pipeline includes support for language models, PCFG parsing, language checking tools and various other pre-processors and feature generators. The code follows the principles of object-oriented programming to allow modularity and extensibility. The tool can operate by processing both batch-files and single sentences. An XML-RPC interface is provided for hooking up with web-services and a graphical animated web-based interface demonstrates its potential on-line use.

  11. South African sign language assistive translation

    CSIR Research Space (South Africa)

    Olivrin, GJ

    2008-04-01

    Full Text Available The authors describe a novel approach and practical solution to an interactive sign language machine translation system from English to South African Sign Language. They interface the system with the GNApp application, which is an augmentative...

  12. Determination of referential property and number of nouns in Japanese sentences for machine translation into English

    CERN Document Server

    Murata, M; Murata, Masaki; Nagao, Makoto

    1994-01-01

    When translating Japanese nouns into English, we face the problem of articles and numbers which the Japanese language does not have, but which are necessary for the English composition. To solve this difficult problem we classified the referential property and the number of nouns into three types respectively. This paper shows that the referential property and the number of nouns in a sentence can be estimated fairly reliably by the words in the sentence. Many rules for the estimation were written in forms similar to rewriting rules in expert systems. We obtained the correct recognition scores of 85.5\\% and 89.0\\% in the estimation of the referential property and the number respectively for the sentences which were used for the construction of our rules. We tested these rules for some other texts, and obtained the scores of 68.9\\% and 85.6\\% respectively.

  13. A support vector machine approach to the development of an ...

    African Journals Online (AJOL)

    PROMOTING ACCESS TO AFRICAN RESEARCH ... Abstract. This paper demonstrated the use of support vector machine (SVM) model to develop an ... system application and implementation was carried out with java programming language.

  14. 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.

  15. 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.

  16. On Structuralism and Equivalence-oriented Approaches in Translation Studies

    Institute of Scientific and Technical Information of China (English)

    Li; Xuemin; Yin; Xiaorong

    2014-01-01

    The present paper is intended to examine the concept of equivalence in translation studies by presenting typical advocates and their influential statement,meanwhile,how structuralism influences in the studies is also investigated.The advantages and disadvantages are figured out,and further tendencies are stated.

  17. Translation of Prophets’ Prayers in the Quran: A Pragmatic Approach

    Directory of Open Access Journals (Sweden)

    Hala Tawfik Sorour Maklad

    2015-05-01

    Full Text Available The paper attempts to develop a descriptive tool of translation products to reveal the aspects of approximation between source utterance acts and translated ones through the analysis of the illocutionary force components of speech acts in both source and target languages. The selected illocutionary act is the requestive prayers of prophets in the Qur'an (Source Text and two translations (Target Texts. The proposed pragmatic-based tool, referred to as Illocutionary Force Components Analysis (IFCA, works on the assumption that if the components that constitute the illocutionary force of the prayer illocutionary act in the target language approximate those in the source language, the illocutionary acts are similar in both languages. After analyzing the Qur'anic prayers of Zechariah, Moses, Jonah, Adam and Eve, Lot, Job, and Joseph using the IFCA, it is found that the translated prayer illocutionary acts are successful and approximate to the source acts as far as the illocutionary point and propositional content are concerned; however, non- approximation tends to occur in preparatory condition, sincerity condition and mode of achievement which produce defective acts.

  18. Translational Approaches in Tissue Engineering and Regenerative Medicine

    CERN Document Server

    Mao, Jeremy J

    2007-01-01

    This landmark book identifies the current and forthcoming roadblocks to scientific research and technological development in stem cell research, tissue engineering, wound healing, and in-vivo animal models. The book is the first to focus on the translational aspect of tissue engineering and regenerative medicine and bridges the gap between laboratory discovery and clinical applications.

  19. EQUIVALENT NORMAL CURVATURE APPROACH MILLING MODEL OF MACHINING FREEFORM SURFACES

    Institute of Scientific and Technical Information of China (English)

    YI Xianzhong; MA Weiguo; QI Haiying; YAN Zesheng; GAO Deli

    2008-01-01

    A new milling methodology with the equivalent normal curvature milling model machining freeform surfaces is proposed based on the normal curvature theorems on differential geometry. Moreover, a specialized whirlwind milling tool and a 5-axis CNC horizontal milling machine are introduced. This new milling model can efficiently enlarge the material removal volume at the tip of the whirlwind milling tool and improve the producing capacity. The machining strategy of this model is to regulate the orientation of the whirlwind milling tool relatively to the principal directions of the workpiece surface at the point of contact, so as to create a full match with collision avoidance between the workpiece surface and the symmetric rotational surface of the milling tool. The practical results show that this new milling model is an effective method in machining complex three- dimensional surfaces. This model has a good improvement on finishing machining time and scallop height in machining the freeform surfaces over other milling processes. Some actual examples for manufacturing the freeform surfaces with this new model are given.

  20. Crack identification for rotating machines based on a nonlinear approach

    Science.gov (United States)

    Cavalini, A. A., Jr.; Sanches, L.; Bachschmid, N.; Steffen, V., Jr.

    2016-10-01

    In a previous contribution, a crack identification methodology based on a nonlinear approach was proposed. The technique uses external applied diagnostic forces at certain frequencies attaining combinational resonances, together with a pseudo-random optimization code, known as Differential Evolution, in order to characterize the signatures of the crack in the spectral responses of the flexible rotor. The conditions under which combinational resonances appear were determined by using the method of multiple scales. In real conditions, the breathing phenomenon arises from the stress and strain distribution on the cross-sectional area of the crack. This mechanism behavior follows the static and dynamic loads acting on the rotor. Therefore, the breathing crack can be simulated according to the Mayes' model, in which the crack transition from fully opened to fully closed is described by a cosine function. However, many contributions try to represent the crack behavior by machining a small notch on the shaft instead of the fatigue process. In this paper, the open and breathing crack models are compared regarding their dynamic behavior and the efficiency of the proposed identification technique. The additional flexibility introduced by the crack is calculated by using the linear fracture mechanics theory (LFM). The open crack model is based on LFM and the breathing crack model corresponds to the Mayes' model, which combines LFM with a given breathing mechanism. For illustration purposes, a rotor composed by a horizontal flexible shaft, two rigid discs, and two self-aligning ball bearings is used to compose a finite element model of the system. Then, numerical simulation is performed to determine the dynamic behavior of the rotor. Finally, the results of the inverse problem conveyed show that the methodology is a reliable tool that is able to estimate satisfactorily the location and depth of the crack.

  1. The potential of translational bioinformatics approaches for pharmacology research.

    Science.gov (United States)

    Li, Lang

    2015-10-01

    The field of bioinformatics has allowed the interpretation of massive amounts of biological data, ushering in the era of 'omics' to biomedical research. Its potential impact on pharmacology research is enormous and it has shown some emerging successes. A full realization of this potential, however, requires standardized data annotation for large health record databases and molecular data resources. Improved standardization will further stimulate the development of system pharmacology models, using translational bioinformatics methods. This new translational bioinformatics paradigm is highly complementary to current pharmacological research fields, such as personalized medicine, pharmacoepidemiology and drug discovery. In this review, I illustrate the application of transformational bioinformatics to research in numerous pharmacology subdisciplines. © 2015 The British Pharmacological Society.

  2. Data Triage of Astronomical Transients: A Machine Learning Approach

    Science.gov (United States)

    Rebbapragada, U.

    This talk presents real-time machine learning systems for triage of big data streams generated by photometric and image-differencing pipelines. Our first system is a transient event detection system in development for the Palomar Transient Factory (PTF), a fully-automated synoptic sky survey that has demonstrated real-time discovery of optical transient events. The system is tasked with discriminating between real astronomical objects and bogus objects, which are usually artifacts of the image differencing pipeline. We performed a machine learning forensics investigation on PTF’s initial system that led to training data improvements that decreased both false positive and negative rates. The second machine learning system is a real-time classification engine of transients and variables in development for the Australian Square Kilometre Array Pathfinder (ASKAP), an upcoming wide-field radio survey with unprecedented ability to investigate the radio transient sky. The goal of our system is to classify light curves into known classes with as few observations as possible in order to trigger follow-up on costlier assets. We discuss the violation of standard machine learning assumptions incurred by this task, and propose the use of ensemble and hierarchical machine learning classifiers that make predictions most robustly.

  3. Machine learning approaches in medical image analysis: From detection to diagnosis

    NARCIS (Netherlands)

    M. de Bruijne (Marleen)

    2016-01-01

    textabstractMachine 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

  4. Machine learning approaches in medical image analysis: From detection to diagnosis.

    Science.gov (United States)

    de Bruijne, Marleen

    2016-10-01

    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.

  5. Machine Vision for Relative Spacecraft Navigation During Approach to Docking

    Science.gov (United States)

    Chien, Chiun-Hong; Baker, Kenneth

    2011-01-01

    This paper describes a machine vision system for relative spacecraft navigation during the terminal phase of approach to docking that: 1) matches high contrast image features of the target vehicle, as seen by a camera that is bore-sighted to the docking adapter on the chase vehicle, to the corresponding features in a 3d model of the docking adapter on the target vehicle and 2) is robust to on-orbit lighting. An implementation is provided for the case of the Space Shuttle Orbiter docking to the International Space Station (ISS) with quantitative test results using a full scale, medium fidelity mock-up of the ISS docking adapter mounted on a 6-DOF motion platform at the NASA Marshall Spaceflight Center Flight Robotics Laboratory and qualitative test results using recorded video from the Orbiter Docking System Camera (ODSC) during multiple orbiter to ISS docking missions. The Natural Feature Image Registration (NFIR) system consists of two modules: 1) Tracking which tracks the target object from image to image and estimates the position and orientation (pose) of the docking camera relative to the target object and 2) Acquisition which recognizes the target object if it is in the docking camera Field-of-View and provides an approximate pose that is used to initialize tracking. Detected image edges are matched to the 3d model edges whose predicted location, based on the pose estimate and its first time derivative from the previous frame, is closest to the detected edge1 . Mismatches are eliminated using a rigid motion constraint. The remaining 2d image to 3d model matches are used to make a least squares estimate of the change in relative pose from the previous image to the current image. The changes in position and in attitude are used as data for two Kalman filters whose outputs are smoothed estimate of position and velocity plus attitude and attitude rate that are then used to predict the location of the 3d model features in the next image.

  6. Extracting Information from Spoken User Input. A Machine Learning Approach

    NARCIS (Netherlands)

    Lendvai, P.K.

    2004-01-01

    We propose a module that performs automatic analysis of user input in spoken dialogue systems using machine learning algorithms. The input to the module is material received from the speech recogniser and the dialogue manager of the spoken dialogue system, the output is a four-level

  7. A New Approach For FEM Simulation of NC Machining Processes

    Science.gov (United States)

    Wang, Sheng Ping; Padmanaban, Shivakumar

    2004-06-01

    The paper describes a new method for a finite element based pseudo-simulation of Numerically Controlled (NC) machining (material removal) processes. Industrial machining of a component usually results in warping or distortion due to the re-establishment of equilibrium in the retained part along with the relief of the insitu residual stresses in the removed part. In many cases, these distortions can be so large that the part may no longer be able to serve its designated functionality. Considering that the machining process is fundamentally a material removal process, a new method based on an automated removal of finite elements in the cutting area has been developed in the finite element analysis (FEA) software MSC.Marc to conduct pseudo-simulation of the NC machining process., A number of key software enhancements have been made to facilitate the pseudo-simulation of the NC machining process. First, a seamless interface has been developed to import APT/CL data generated by CAD/CAM systems. Then, the cutting paths have been generated based on information in the APT/CL files and used for the automatic detection of the intersection between the cutter and the finite element mesh. With each incremental motion of the cutter, the FEA solver detects all the elements that are located within the cutting path. Such elements are then deactivated in a step-by-step manner that is consistent with the actual machining process. In order to improve the fidelity of the cut area, local adaptive mesh refinement in the vicinity of the cutting tool is undertaken. This enables relatively coarser meshes away from the cut area and provides more accurate representation of the actual volume that is removed. As demonstrated by an industrial example, the enhanced software features in MSC.Marc have made it possible to practically and efficiently analyze complex machining processes of 3D production parts and provide an elegant tool for predicting distortions in large structures due to the relief

  8. The unfolded protein response and translation attenuation: a modelling approach.

    Science.gov (United States)

    Trusina, A; Tang, C

    2010-10-01

    Unfolded protein response (UPR) is a stress response to increased levels of unfolded proteins in the endoplasmic reticulum (ER). To deal with this stress, all eukaryotic cells share a well-conserved strategy--the upregulation of chaperons and proteases to facilitate protein folding and to degrade the misfolded proteins. For metazoans, however, an additional and seemingly redundant strategy has been evolved--translation attenuation (TA) of proteins targeted to the ER via the protein kinase PERK pathway. PERK is essential in secretory cells, such as the pancreatic β-cells, but not in non-secretory cell types. We have recently developed a mathematical model of UPR, focusing on the interplay and synergy between the TA arm and the conserved Ire1 arm of the UPR. The model showed that the TA mechanism is beneficial in highly fluctuating environment, for example, in the case where the ER stress changes frequently. Under highly variable levels of ER stress, tight regulation of the ER load by TA avoids excess amount of chaperons and proteases being produced. The model also showed that TA is of greater importance when there is a large flux of proteins through the ER. In this study, we further expand our model to investigate different types of ER stress and different temporal profiles of the stress. We found that TA is more desirable in dealing with the translation stress, for example, prolonged stimulation of proinsulin biosynthesis, than the chemical stress.

  9. 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

  10. A Review on Approaches for Condition Based Maintenance in Applications with Induction Machines located Offshore

    Directory of Open Access Journals (Sweden)

    J. Cibulka

    2012-04-01

    Full Text Available This paper presents a review of different approaches for Condition Based Maintenance (CBM of induction machines and drive trains in offshore applications. The paper contains an overview of common failure modes, monitoring techniques, approaches for diagnostics, and an overview of typical maintenance actions. Although many papers have been written in this area before, this paper puts an emphasis on recent developments and limits the scope to induction machines and drive trains applied in applications located offshore.

  11. A Machine Learning Approach for the Identification of Bengali Noun-Noun Compound Multiword Expressions

    OpenAIRE

    Gayen, Vivekananda; Sarkar, Kamal

    2014-01-01

    This paper presents a machine learning approach for identification of Bengali multiword expressions (MWE) which are bigram nominal compounds. Our proposed approach has two steps: (1) candidate extraction using chunk information and various heuristic rules and (2) training the machine learning algorithm called Random Forest to classify the candidates into two groups: bigram nominal compound MWE or not bigram nominal compound MWE. A variety of association measures, syntactic and linguistic clue...

  12. Time-series prediction and applications a machine intelligence approach

    CERN Document Server

    Konar, Amit

    2017-01-01

    This book presents machine learning and type-2 fuzzy sets for the prediction of time-series with a particular focus on business forecasting applications. It also proposes new uncertainty management techniques in an economic time-series using type-2 fuzzy sets for prediction of the time-series at a given time point from its preceding value in fluctuating business environments. It employs machine learning to determine repetitively occurring similar structural patterns in the time-series and uses stochastic automaton to predict the most probabilistic structure at a given partition of the time-series. Such predictions help in determining probabilistic moves in a stock index time-series Primarily written for graduate students and researchers in computer science, the book is equally useful for researchers/professionals in business intelligence and stock index prediction. A background of undergraduate level mathematics is presumed, although not mandatory, for most of the sections. Exercises with tips are provided at...

  13. Machine Learning Approaches for analysis of League of Legends

    OpenAIRE

    Janežič, Simon

    2016-01-01

    Our goal is to use machine learning for predicting winners of League of Legends matches. League of Legends is a multiplayer game that combines elements from strategic and action games. Every year, multiple professional League of Legends competitions are being held acros the globe. We try to predict both professional and non-professional matches. Getting data for both types of matches is already a challenge. For non-professional matches official application programming interface is used, whil...

  14. Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting

    OpenAIRE

    Shi, Xingjian; Chen, Zhourong; Wang, Hao; Yeung, Dit-Yan; Wong, Wai-Kin; Woo, Wang-chun

    2015-01-01

    The goal of precipitation nowcasting is to predict the future rainfall intensity in a local region over a relatively short period of time. Very few previous studies have examined this crucial and challenging weather forecasting problem from the machine learning perspective. In this paper, we formulate precipitation nowcasting as a spatiotemporal sequence forecasting problem in which both the input and the prediction target are spatiotemporal sequences. By extending the fully connected LSTM (F...

  15. Sustainable malaria control: transdisciplinary approaches for translational applications

    Directory of Open Access Journals (Sweden)

    Birkholtz Lyn-Marie

    2012-12-01

    Full Text Available Abstract With the adoption of the Global Malaria Action Plan, several countries are moving from malaria control towards elimination and eradication. However, the sustainability of some of the approaches taken may be questionable. Here, an overview of malaria control and elimination strategies is provided and the sustainability of each in context of vector- and parasite control is assessed. From this, it can be concluded that transdisciplinary approaches are essential for sustained malaria control and elimination in malaria-endemic communities.

  16. Translational approaches: from fatty liver to non-alcoholic steatohepatitis.

    Science.gov (United States)

    Rosso, Natalia; Chavez-Tapia, Norberto C; Tiribelli, Claudio; Bellentani, Stefano

    2014-07-21

    Over the past few decades, non-alcoholic fatty liver disease (NAFLD) has become one, if not the most common, cause of chronic liver disease affecting both adults and children. The increasing number of cases at an early age is the most worrying aspect of this pathology, since it provides more time for its evolution. The spectrum of this disease ranges from liver steatosis to steatohepatitis, fibrosis and in some cases, hepatocellular carcinoma. NAFLD may not always be considered a benign disease and hepatologists must be cautious in the presence of fatty liver. This should prompt the use of the available experimental models to understand better the pathogenesis and to develop a rational treatment of a disease that is dangerously increasing. In spite of the growing efforts, the pathogenesis of NAFLD is still poorly understood. In the present article we review the most relevant hypotheses and evidence that account for the progression of NAFLD to non-alcoholic steatohepatitis (NASH) and fibrosis. The available in vitro and in vivo experimental models of NASH are discussed and revised in terms of their validity in translational studies. These studies must be aimed at the discovery of the still unknown triggers or mediators that induce the progression of hepatic inflammation, apoptosis and fibrosis.

  17. Oxytocin in General Anxiety and Social Fear: A Translational Approach.

    Science.gov (United States)

    Neumann, Inga D; Slattery, David A

    2016-02-01

    The neuropeptide oxytocin (OXT) has been revealed as a profound anxiolytic and antistress factor of the brain, besides its many prosocial and reproductive effects. Therefore, there is substantial scientific and medical interest in its potential therapeutic use for the treatment of psychopathologies associated with anxiety, fear, and social dysfunctions, such as generalized anxiety disorder, posttraumatic stress disorder, and social anxiety disorder, as well as autism and schizophrenia, among others. Focusing on preclinical studies, we review the existing evidence for the regulatory capacity of OXT to fine-tune general and social anxiety-related behaviors, as well as cued and social fear conditioning from a translational perspective. The available evidence from animal and human studies substantiates the hypothesis of an imbalance of the endogenous brain OXT system in the etiology of anxiety disorders, particularly those with a social component such as social anxiety disorder. In addition, such an imbalance of the OXT system is also likely to be the consequence of chronic OXT treatment resulting in a dose-dependent reduction in OXT receptor availability and increased anxiety.

  18. Compensation: An Approach towards Preserving Sociolinguistic Features in Translation

    Directory of Open Access Journals (Sweden)

    Nermeen Mohammed Yousry

    2012-10-01

    Full Text Available The research aims at bridging the cultural gaps arising due to sociolinguistic factors specific to the target culture by employing compensation as a problem-solving technique. In both written and spoken discourse, aspects like the speaker's attitude, social class, and profession are reflected through their usage of certain lexical items or means of expression. While some of these sociolinguistic features are easily rendered, they sometimes represent a problematic area in translation. If not dealt with efficiently, such sociolinguistic gaps can cause the target text some degree of loss in terms of accuracy and naturalness. The research is divided into six parts. The first part is an introduction and the second part specifies the aim of the research. In the third part, compensation is defined and its four types (compensation in kind, in place, by merging, and by splitting are explained. The fourth part is devoted to the elaboration of the sociolinguistic problematic areas subject of research (register, sociolect, dialects, and diglossia. In the fifth part, compensation is applied to deal with the sociolinguistic problematic areas included in various examples. The application proves compensation to be an effective problem-solving technique. The sixth part is the conclusion.

  19. A Machine Learning Approach to Test Data Generation

    DEFF Research Database (Denmark)

    Christiansen, Henning; Dahmcke, Christina Mackeprang

    2007-01-01

    been tested, and a more thorough statistical foundation is required. We propose to use logic-statistical modelling methods for machine-learning for analyzing existing and manually marked up data, integrated with the generation of new, artificial data. More specifically, we suggest to use the PRISM...... system developed by Sato and Kameya. Based on logic programming extended with random variables and parameter learning, PRISM appears as a powerful modelling environment, which subsumes HMMs and a wide range of other methods, all embedded in a declarative language. We illustrate these principles here...

  20. Improved Support Vector Machine Approach Based on Determining Thresholds Automatically

    Institute of Scientific and Technical Information of China (English)

    WANG Xiao-hua; YAN Xue-mei; WANG Xiao-guang

    2007-01-01

    To improve the training speed of support vector machine (SVM), a method called improved center distance ratio method (ICDRM) with determining thresholds automatically is presented here without reduce the identification rate. In this method border vectors are chosen from the given samples by comparing sample vectors with center distance ratio in advance. The number of training samples is reduced greatly and the training speed is improved. This method is used to the identification for license plate characters. Experimental results show that the improved SVM method-ICDRM does well at identification rate and training speed.

  1. Translating ICD-11 into French using lexical-based approach: a preliminary study.

    Science.gov (United States)

    Merabti, Tayeb; Grosjean, Julien; Rodrigues, Jean-Marie; Darmoni, Stefan Jacques

    2015-01-01

    To translate the 11th edition of the International Classification of Diseases (ICD-11) into French, we proposed a lexical approach using Natural Language Processing techniques. This method relies on the 56 biomedical terminologies and ontologies included in the Cross-lingual Health Multiple Terminologies and Ontologies Portal. From a sample of 336 ICD-11 terms, the algorithm translated 164 (49%) terms into at least one French term each.

  2. Filter Feeding Mechanism Simulated Machine Paradigms – A Theoretical Approach

    Directory of Open Access Journals (Sweden)

    Channaveerappa. H,

    2014-01-01

    Full Text Available Bionics is the emerging branch of bio engineering where in the structures and functions of organism are utilized to construct a gadget that resembles the structure and performs similar function. The functional principles are also used to construct special gadgets to perform functions in the form of simulated robots. Animal models have also been used in creation of many structures/machines, for example the organization and flight mechanism of birds, echolocation in bats, and internal ear of mammals have been taken as blue prints to design aero planes, radars and telegraphic systems respectively. Here we are using ciliary feeding mechanisms in animals to create a machine that can be used for a particular purpose. Cilia are minute finger like protoplasmic extensions serve different functions like movement, creation of water current propelling and filter feeding in animals. In many invertebrates and lower chordates rotor movements of cilia create whirl pool of water current to obtain food material. Animals those use cilia for feeding are referred to ciliary feeders or filter feeders. The filter feeders are highly diverse in their habit but share common requirements. The filter feeders may be sessile or free swimming forms but the principles of feeding remains the same. In lower chordates the pharngometry of pharynx plays a decisive role in filter feeding. The filter feeding mechanism is highly evolved in animals through well designed evolutionary paradigms.

  3. A Vectorial modeling for the pentaphase Permanent Magnet Synchronous Machine based on multimachine approach

    Directory of Open Access Journals (Sweden)

    Abdelkrim Sellam,Boubakeur Dehiba,Mohamed B. Benabdallah,Mohamed Abid,Nacéra Bachir Bouiadjra,Boubakeur Bensaid,Mustapha Djouhri

    2012-12-01

    Full Text Available The polyphase [1] machines are developed mainly inthe field of variable speed drives of high powerbecause increasing the number of phases on the onehand allows to reduce the dimensions of thecomponents in power modulators energy and secondlyto improve the operating safety. By a vector approach(vector space, it is possible to find a set of singlephasemachine and / or two-phase fictitious equivalentto polyphase synchronous machine.These fictitiousmachines are coupled electrically and mechanicallybut decoupled magnetically. This approach leads tointroduce the concept of the equivalent machine(multimachine multiconverter system MMS whichaims to analyze systems composed of mul tiplemachines (or multiple converters in electric drives. Afirst classification multimachine multiconvertersystem follows naturally from MMS formalism. Wepresent an example of a synchronous machine pent

  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. An Approach with Support Vector Machine using Variable Features Selection on Breast Cancer Prognosis

    Directory of Open Access Journals (Sweden)

    Sandeep Chaurasia

    2013-09-01

    Full Text Available Cancer diagnosis and clinical outcome prediction are among the most important emerging applications of machine learning. In this paper we have used an approach by using support vector machine classifier to construct a model that is useful for the breast cancer survivability prediction. We have used both 5 cross and 10 cross validation of variable selection on input feature vectors and the performance measurement through bio-learning class performance while measuring AUC, specificity and sensitivity. The performance of the SVM is much better than the other machine learning classifier.

  6. Machine-Learning Approach for Design of Nanomagnetic-Based Antennas

    Science.gov (United States)

    Gianfagna, Carmine; Yu, Huan; Swaminathan, Madhavan; Pulugurtha, Raj; Tummala, Rao; Antonini, Giulio

    2017-08-01

    We propose a machine-learning approach for design of planar inverted-F antennas with a magneto-dielectric nanocomposite substrate. It is shown that machine-learning techniques can be efficiently used to characterize nanomagnetic-based antennas by accurately mapping the particle radius and volume fraction of the nanomagnetic material to antenna parameters such as gain, bandwidth, radiation efficiency, and resonant frequency. A modified mixing rule model is also presented. In addition, the inverse problem is addressed through machine learning as well, where given the antenna parameters, the corresponding design space of possible material parameters is identified.

  7. A New Approach on the Design and Optimization of Brushless Doubly-Fed Reluctance Machines

    OpenAIRE

    Staudt, Tiago; Wurtz, Frédéric; Gerbaud, Laurent; Batistela, Nelson Jhoe; Kuo-Peng, Patrick

    2014-01-01

    International audience; The Brushless Doubly-Fed Reluctance Machine (BDFRM) is being considered as a viable generator alternative to be used in wind turbines. A literature review shows that there is still a lack of researches to define a design procedure to make this machine widely used in such application. This paper aims to address this issue by considering a new BDFRM design method using a reluctance network approach and the concepts of sizing and optimization models. It also presents a ca...

  8. Translating science into action: periodontal health through public health approaches.

    Science.gov (United States)

    Jürgensen, Nanna; Petersen, Poul E; Ogawa, Hiroshi; Matsumoto, Sayaka

    2012-10-01

    Clinical and public health research data have shown that a number of individual, professional and community health measures may be valuable in preventing the major oral diseases. The fundamental gap in knowledge, however, is not confined to 'what to do' but rather 'how' to translate the scientific findings into effective and sustainable programs for groups and populations. The advances in oral health science have not yet benefitted the poor and disadvantaged population groups around the world to the fullest extent possible and this has led to inequalities in periodontal health as well as in other chronic diseases. Research on the causative role of tobacco use in periodontal disease is strong because of the fact that tobacco-induced disease ultimately may lead to the loss of teeth. Studies also indicate that wound healing may be negatively affected by the use of tobacco. Likewise, research has shown that extreme use of alcohol, poor diet and nutrition, and psychological stress all have negative effects on periodontal health. Research on sociobehavioral risk factors has great implication to prevent periodontal disease. The case for tobacco is illustrated in this report. The global exposure to tobacco use in adults and adolescents is outlined. Because of the global Framework Convention for Tobacco Control (2003), the solid research on the harmful effect of tobacco is now being widely used for public health. The importance of tobacco prevention within the context of health-promoting schools is emphasized. Research on other population-directed strategies and their implications on public health would be instrumental to integrated prevention of chronic disease and periodontal disease. Community interventions and delivery of preventive oral care by oral health services may have positive outcomes for periodontal health but periodontal research needs to be further strengthened by the provision of sound evidence. It is somewhat remarkable that research on true population

  9. 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.

  10. Rule based systems for big data a machine learning approach

    CERN Document Server

    Liu, Han; Cocea, Mihaela

    2016-01-01

    The ideas introduced in this book explore the relationships among rule based systems, machine learning and big data. Rule based systems are seen as a special type of expert systems, which can be built by using expert knowledge or learning from real data. The book focuses on the development and evaluation of rule based systems in terms of accuracy, efficiency and interpretability. In particular, a unified framework for building rule based systems, which consists of the operations of rule generation, rule simplification and rule representation, is presented. Each of these operations is detailed using specific methods or techniques. In addition, this book also presents some ensemble learning frameworks for building ensemble rule based systems.

  11. A Machine Learning Approach to Test Data Generation

    DEFF Research Database (Denmark)

    Christiansen, Henning; Dahmcke, Christina Mackeprang

    2007-01-01

    Programs for gene prediction in computational biology are examples of systems for which the acquisition of authentic test data is difficult as these require years of extensive research. This has lead to test methods based on semiartificially produced test data, often produced by {\\em ad hoc......} techniques complemented by statistical models such as Hidden Markov Models (HMM). The quality of such a test method depends on how well the test data reflect the regularities in known data and how well they generalize these regularities. So far only very simplified and generalized, artificial data sets have...... been tested, and a more thorough statistical foundation is required. We propose to use logic-statistical modelling methods for machine-learning for analyzing existing and manually marked up data, integrated with the generation of new, artificial data. More specifically, we suggest to use the PRISM...

  12. Effective and efficient optics inspection approach using machine learning algorithms

    Energy Technology Data Exchange (ETDEWEB)

    Abdulla, G; Kegelmeyer, L; Liao, Z; Carr, W

    2010-11-02

    The Final Optics Damage Inspection (FODI) system automatically acquires and utilizes the Optics Inspection (OI) system to analyze images of the final optics at the National Ignition Facility (NIF). During each inspection cycle up to 1000 images acquired by FODI are examined by OI to identify and track damage sites on the optics. The process of tracking growing damage sites on the surface of an optic can be made more effective by identifying and removing signals associated with debris or reflections. The manual process to filter these false sites is daunting and time consuming. In this paper we discuss the use of machine learning tools and data mining techniques to help with this task. We describe the process to prepare a data set that can be used for training and identifying hardware reflections in the image data. In order to collect training data, the images are first automatically acquired and analyzed with existing software and then relevant features such as spatial, physical and luminosity measures are extracted for each site. A subset of these sites is 'truthed' or manually assigned a class to create training data. A supervised classification algorithm is used to test if the features can predict the class membership of new sites. A suite of self-configuring machine learning tools called 'Avatar Tools' is applied to classify all sites. To verify, we used 10-fold cross correlation and found the accuracy was above 99%. This substantially reduces the number of false alarms that would otherwise be sent for more extensive investigation.

  13. Metabolomics, a promising approach to translational research in cardiology

    Directory of Open Access Journals (Sweden)

    Martino Deidda

    2015-12-01

    In this article, we will provide a description of metabolomics in comparison with other, better known “omics” disciplines such as genomics and proteomics. In addition, we will review the current rationale for the implementation of metabolomics in cardiology, its basic methodology and the available data from human studies in this discipline. The topics covered will delineate the importance of being able to use the metabolomic information to understand the mechanisms of diseases from the perspective of systems biology, and as a non-invasive approach to the diagnosis, grading and treatment of cardiovascular diseases.

  14. Diagnostic classification of specific phobia subtypes using structural MRI data: a machine-learning approach.

    Science.gov (United States)

    Lueken, Ulrike; Hilbert, Kevin; Wittchen, Hans-Ulrich; Reif, Andreas; Hahn, Tim

    2015-01-01

    While neuroimaging research has advanced our knowledge about fear circuitry dysfunctions in anxiety disorders, findings based on diagnostic groups do not translate into diagnostic value for the individual patient. Machine-learning generates predictive information that can be used for single subject classification. We applied Gaussian process classifiers to a sample of patients with specific phobia as a model disorder for pathological forms of anxiety to test for classification based on structural MRI data. Gray (GM) and white matter (WM) volumetric data were analyzed in 33 snake phobics (SP; animal subtype), 26 dental phobics (DP; blood-injection-injury subtype) and 37 healthy controls (HC). Results showed good accuracy rates for GM and WM data in predicting phobia subtypes (GM: 62 % phobics vs. HC, 86 % DP vs. HC, 89 % SP vs. HC, 89 % DP vs. SP; WM: 88 % phobics vs. HC, 89 % DP vs. HC, 79 % SP vs. HC, 79 % DP vs. HC). Regarding GM, classification improved when considering the subtype compared to overall phobia status. The discriminatory brain pattern was not solely based on fear circuitry structures but included widespread cortico-subcortical networks. Results demonstrate that multivariate pattern recognition represents a promising approach for the development of neuroimaging-based diagnostic markers that could support clinical decisions. Regarding the increasing number of fMRI studies on anxiety disorders, researchers are encouraged to use functional and structural data not only for studying phenotype characteristics on a group level, but also to evaluate their incremental value for diagnostic or prognostic purposes.

  15. An Approach to the Classification of Cutting Vibration on Machine Tools

    Directory of Open Access Journals (Sweden)

    Jeng-Fung Chen

    2016-02-01

    Full Text Available Predictions of cutting vibrations are necessary for improving the operational efficiency, product quality, and safety in the machining process, since the vibration is the main factor for resulting in machine faults. “Cutting vibration” may be caused by setting incorrect parameters before machining is commenced and may affect the precision of the machined work piece. This raises the need to have an effective model that can be used to predict cutting vibrations. In this study, an artificial neural network (ANN model to forecast and classify the cutting vibration of the intelligent machine tool is presented. The factors that may cause cutting vibrations is firstly identified and a dataset for the research purpose is constructed. Then, the applicability of the model is illustrated. Based on the results in the comparative analysis, the artificial neural network approach performed better than the others. Because the vibration can be forecasted and classified, the product quality can be managed. This work may help new workers to avoid operating machine tools incorrectly, and hence can decrease manufacturing costs. It is expected that this study can enhance the performance of machine tools in metalworking sectors.

  16. Lost in translation: rethinking approaches to stroke recovery.

    Science.gov (United States)

    Corbett, Dale; Jeffers, Matthew; Nguemeni, Carine; Gomez-Smith, Mariana; Livingston-Thomas, Jessica

    2015-01-01

    Stroke is the second leading cause of death and the preeminent cause of neurological disability. Attempts to limit brain injury after ischemic stroke with clot-dissolving drugs have met with great success but their use remains limited due to a narrow therapeutic time window and concern over serious side effects. Unfortunately, the neuroprotective strategy failed in clinical trials. A more promising approach is to promote recovery of function in people affected by stroke. Following stroke, there is a heightened critical period of plasticity that appears to be receptive to exogenous interventions (e.g., delivery of growth factors) designed to enhance neuroplasticity processes important for recovery. An emerging concept is that combinational therapies appear much more effective than single interventions in improving stroke recovery. One of the most promising interventions, with clinical feasibility, is enriched rehabilitation, a combination of environmental enrichment and task-specific therapy. © 2015 Elsevier B.V. All rights reserved.

  17. A tabu search approach for a single-machine batching problem using an efficient method to calculate a best neighbour

    NARCIS (Netherlands)

    Hurink, Johann L.

    1998-01-01

    In this paper we present a tabu search approach for a single-machine batching problem. A set of jobs has to be scheduled on a batching machine. This machine is able to handle several jobs simultaneously. The time for processing a subset of jobs simultaneously is equal to the sum of the processing

  18. Faster and better: a machine learning approach to corner detection

    CERN Document Server

    Rosten, Edward; Drummond, Tom

    2008-01-01

    The repeatability and efficiency of a corner detector determines how likely it is to be useful in a real-world application. The repeatability is importand because the same scene viewed from different positions should yield features which correspond to the same real-world 3D locations [Schmid et al 2000]. The efficiency is important because this determines whether the detector combined with further processing can operate at frame rate. Three advances are described in this paper. First, we present a new heuristic for feature detection, and using machine learning we derive a feature detector from this which can fully process live PAL video using less than 5% of the available processing time. By comparison, most other detectors cannot even operate at frame rate (Harris detector 115%, SIFT 195%). Second, we generalize the detector, allowing it to be optimized for repeatability, with little loss of efficiency. Third, we carry out a rigorous comparison of corner detectors based on the above repeatability criterion a...

  19. A new DFM approach to combine machining and additive manufacturing

    OpenAIRE

    Kerbrat, Olivier; MOGNOL, Pascal; Hascoët, Jean-Yves

    2011-01-01

    International audience; Design For Manufacturing (DFM) approaches aim to integrate manufacturability aspects during the design stage. Most of DFM approaches usually consider only one manufacturing process, but products competitiveness may be improved by designing hybrid modular products, in which products are seen as 3-D puzzles with modules realized aside by the best manufacturing process and further gathered. A new DFM system is created in order to give quantitative information during the p...

  20. A new DFM approach to combine machining and additive manufacturing

    OpenAIRE

    Kerbrat, Olivier; Mognol, Pascal; Hascoët, Jean-Yves

    2011-01-01

    International audience; Design For Manufacturing (DFM) approaches aim to integrate manufacturability aspects during the design stage. Most of DFM approaches usually consider only one manufacturing process, but products competitiveness may be improved by designing hybrid modular products, in which products are seen as 3-D puzzles with modules realized aside by the best manufacturing process and further gathered. A new DFM system is created in order to give quantitative information during the p...

  1. 从机器翻译历程看自然语言处理研究的发展策略%The Development Strategy for Natural Language Processing Research Inspired from a Historical View on Machine Translation

    Institute of Scientific and Technical Information of China (English)

    孙茂松; 周建设

    2016-01-01

    Machine translation (MT) is one of the major research fi elds of natural language processing (NLP), and it always spearheads the research frontier in NLP. In this paper, after a systematic survey of the development history of MT from a macroscopic perspective, with particular emphasis on the main development path of underlying methodologies and core technologies in MT, we drew a general picture of the milestones that marked the key points of a long journey for both theoretical study and practical accomplishment for the past seven decades. The latest fruitful development achieved in the area of MT application shows that, the paradigm shift from the tradi-tional linguistic rule-based approaches to the so-called empirical approach, based on increasingly available amounts of “raw data” in the form of massive collections of texts and their translations, compounded by the phenomenal advancement of computer technology, will become the driving force that will potentially lead to the breakthrough in MT. Based on the above observation and analysis, some sug-gestions on the short-term development strategy for machine translation as well as natural language processing in China are proposed.%本文试图从超脱细节的宏观角度,对机器翻译的发展历程进行扼要的总结和深刻的评介,着重于刻画各个时期在基本方法和核心技术上的主要特征,从而勾勒出机器翻译的全过程演进脉络。在上述考察和分析的基础上,文章对国内机器翻译乃至自然语言处理研究的近期发展策略提出了若干建议。

  2. An interactive integrative approach to translating knowledge and building a "learning organization" in health services management.

    Science.gov (United States)

    Chunharas, Somsak

    2006-08-01

    This paper proposes a basic approach to ensuring that knowledge from research studies is translated for use in health services management with a view towards building a "learning organization". (A learning organization is one in which the environment is structured in such a way as to facilitate learning as well as the sharing of knowledge among members or employees.) This paper highlights various dimensions that determine the complexity of knowledge translation, using the problem-solving cycle as the backbone for gaining a better understanding of how different types of knowledge interact in health services management. It is essential to use an integrated and interactive approach to ensure that knowledge from research is translated in a way that allows a learning organization to be built and that knowledge is not used merely to influence a single decision in isolation from the overall services and management of an organization.

  3. 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 divergence a

  4. A Skopostheorie Approach to the Translation of Artistic Conception in Chinese Classic Poems

    Institute of Scientific and Technical Information of China (English)

    Huang Lu

    2015-01-01

    This paper is to examine the C-E translation of artistic conception of Chinese classic poems regarding feeling and setting from the angle of Skopostheorie. Artistic conception is an indispensable factor in Chinese classic poems. The approach of Skopostheorie can be ad⁃opted as a guide because of its rules of purpose, textual coherence and culture aspect.

  5. 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...

  6. Machine Learning Approaches for Predicting Human Skin Sensitization Hazard

    Science.gov (United States)

    One of ICCVAM’s top priorities is the development and evaluation of non-animal approaches to identify potential skin sensitizers. The complexity of biological events necessary for a substance to elicit a skin sensitization reaction suggests that no single in chemico, in vit...

  7. Machine Learning Approaches for Predicting Human Skin Sensitization Hazard

    Science.gov (United States)

    One of ICCVAM’s top priorities is the development and evaluation of non-animal approaches to identify potential skin sensitizers. The complexity of biological events necessary for a substance to elicit a skin sensitization reaction suggests that no single in chemico, in vit...

  8. 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...

  9. 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.

  10. Creating Situational Awareness in Spacecraft Operations with the Machine Learning Approach

    Science.gov (United States)

    Li, Z.

    2016-09-01

    This paper presents a machine learning approach for the situational awareness capability in spacecraft operations. There are two types of time dependent data patterns for spacecraft datasets: the absolute time pattern (ATP) and the relative time pattern (RTP). The machine learning captures the data patterns of the satellite datasets through the data training during the normal operations, which is represented by its time dependent trend. The data monitoring compares the values of the incoming data with the predictions of machine learning algorithm, which can detect any meaningful changes to a dataset above the noise level. If the difference between the value of incoming telemetry and the machine learning prediction are larger than the threshold defined by the standard deviation of datasets, it could indicate the potential anomaly that may need special attention. The application of the machine-learning approach to the Advanced Himawari Imager (AHI) on Japanese Himawari spacecraft series is presented, which has the same configuration as the Advanced Baseline Imager (ABI) on Geostationary Environment Operational Satellite (GOES) R series. The time dependent trends generated by the data-training algorithm are in excellent agreement with the datasets. The standard deviation in the time dependent trend provides a metric for measuring the data quality, which is particularly useful in evaluating the detector quality for both AHI and ABI with multiple detectors in each channel. The machine-learning approach creates the situational awareness capability, and enables engineers to handle the huge data volume that would have been impossible with the existing approach, and it leads to significant advances to more dynamic, proactive, and autonomous spacecraft operations.

  11. An optimal setup planning selection approach in a complex product machining process

    Science.gov (United States)

    Zhu, Fang

    2011-10-01

    Setup planning has very important influence on the product quality in a Complex Product Machining Process (CPMP). Part production in a CPMP involves multiple setup plans, which will lead into variation propagation and lead to extreme complexity in final product quality. Current approaches of setup planning in a CPMP are experience-based that lead to adopt higher machining process cost to ensure the final product quality, and most approaches are used for a single machining process. This work attempts to solve those challenging problems and aims to develop a method to obtain an optimal setup planning in a CPMP, which can satisfies the quality specifications and minimizes the expected value of the sum of machining costs. To this end, a machining process model is established to describe the variation propagation effect of setup plan throughout all stages in a CPMP firstly and then a quantitative setup plan evaluation methods driven by cost constraint is proposed to clarify what is optimality of setup plans. Based on the above procedures, an optimal setup planning is obtained through a dynamic programming solver. At last, a case study is provided to illustrate the validity and the significance of the proposed setup planning selective method.

  12. 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.

  13. 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...

  14. 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...

  15. 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...

  16. Meaning: lost, found or 'made' in translation? A hermeneutical approach to cross-language interview research

    Directory of Open Access Journals (Sweden)

    Barbara Fersch

    2013-08-01

    Full Text Available Qualitative research that includes interviews in languages foreign to the researcher(s has become increasingly common. However, there is surprisingly little reflection on the methodological implications of such research practices. Furthermore, strategies on how to analyse cross- and multi-language interview material are lacking. The aim of this article is to present possible ways of handling these challenges, focusing mainly on analysis. I propose a hermeneutical approach to the issue. First, I will discuss the epistemological/methodological foundations of the approach before proposing some 'tools' to help practically tackle the 'problem' of analysis using the chosen methodological perspective. Rather than ignoring or trying to circumvent the question of foreign language and/or translation, in the proposed approach linguistic questions and questions of translation are the central focus.

  17. An efficient fusion approach for combining human and machine decisions

    Science.gov (United States)

    Lee, Hyungtae; Kwon, Heesung; Robinson, Ryan M.; Nothwang, William D.; Marathe, Amar R.

    2016-05-01

    A novel approach for the fusion of heterogeneous object classification methods is proposed. In order to effectively integrate the outputs of multiple classifiers, the level of ambiguity in each individual classification score is estimated using the precision/recall relationship of the corresponding classifier. The main contribution of the proposed work is a novel fusion method, referred to as Dynamic Belief Fusion (DBF), which dynamically assigns probabilities to hypotheses (target, non-target, intermediate state (target or non-target) based on confidence levels in the classification results conditioned on the prior performance of individual classifiers. In DBF, a joint basic probability assignment, which is obtained from optimally fusing information from all classifiers, is determined by the Dempster's combination rule, and is easily reduced to a single fused classification score. Experiments on RSVP dataset demonstrates that the recognition accuracy of DBF is considerably greater than that of the conventional naive Bayesian fusion as well as individual classifiers used for the fusion.

  18. MACHINE LEARNING APPROACH FOR AUTOMATIC SEASONAL TOUR PACKAGE

    Directory of Open Access Journals (Sweden)

    Biswamayee M

    2015-10-01

    Full Text Available The online travel data imposes associate increasing difficult for tourists United Nations agency need to choose between sizable amount of accessible package for satisfying their customized desires. This TAST model will represent travel packages and tourists by totally different topics distribution, wherever the topics extraction is conditioned on each the tourists and also the intrinsic options like location , travel seasons of the landscapes. supported this subject model illustration we have a tendency to planned a cocktail approaches to come up with the list for customized travel package recommendation. we have a tendency to extend the TAST model to the tourist-relation-area-season topic (TRASTmodel for capturing the latent relationships among the tourists in every travel cluster.

  19. 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...

  20. 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.

  1. Nonlinear Modeling of a High Precision Servo Injection Molding Machine Including Novel Molding Approach

    Institute of Scientific and Technical Information of China (English)

    何雪松; 王旭永; 冯正进; 章志新; 杨钦廉

    2003-01-01

    A nonlinear mathematical model of the injection molding process for electrohydraulic servo injection molding machine (IMM) is developed.It was found necessary to consider the characteristics of asymmetric cylinder for electrohydraulic servo IMM.The model is based on the dynamics of the machine including servo valve,asymmetric cylinder and screw,and the non-Newtonian flow behavior of polymer melt in injection molding is also considered.The performance of the model was evaluated based on novel approach of molding - injection and compress molding,and the results of simulation and experimental data demonstrate the effectiveness of the model.

  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. Machine Learning Approaches for High-resolution Urban Land Cover Classification: A Comparative Study

    Energy Technology Data Exchange (ETDEWEB)

    Vatsavai, Raju [ORNL; Chandola, Varun [ORNL; Cheriyadat, Anil M [ORNL; Bright, Eddie A [ORNL; Bhaduri, Budhendra L [ORNL; Graesser, Jordan B [ORNL

    2011-01-01

    The proliferation of several machine learning approaches makes it difficult to identify a suitable classification technique for analyzing high-resolution remote sensing images. In this study, ten classification techniques were compared from five broad machine learning categories. Surprisingly, the performance of simple statistical classification schemes like maximum likelihood and Logistic regression over complex and recent techniques is very close. Given that these two classifiers require little input from the user, they should still be considered for most classification tasks. Multiple classifier systems is a good choice if the resources permit.

  4. A Multiple Model Approach to Modeling Based on Fuzzy Support Vector Machines

    Institute of Scientific and Technical Information of China (English)

    冯瑞; 张艳珠; 宋春林; 邵惠鹤

    2003-01-01

    A new multiple models(MM) approach was proposed to model complex industrial process by using Fuzzy Support Vector Machines (F SVMs). By applying the proposed approach to a pH neutralization titration experi-ment, F_SVMs MM not only provides satisfactory approximation and generalization property, but also achieves superior performance to USOCPN multiple modeling method and single modeling method based on standard SVMs.

  5. A network-theoretic approach for decompositional translation across Open Biological Ontologies.

    Science.gov (United States)

    Patel, Chintan O; Cimino, James J

    2010-08-01

    Biological ontologies are now being widely used for annotation, sharing and retrieval of the biological data. Many of these ontologies are hosted under the umbrella of the Open Biological Ontologies Foundry. In order to support interterminology mapping, composite terms in these ontologies need to be translated into atomic or primitive terms in other, orthogonal ontologies, for example, gluconeogenesis (biological process term) to glucose (chemical ontology term). Identifying such decompositional ontology translations is a challenging problem. In this paper, we propose a network-theoretic approach based on the structure of the integrated OBO relationship graph. We use a network-theoretic measure, called the clustering coefficient, to find relevant atomic terms in the neighborhood of a composite term. By eliminating the existing GO to ChEBI Ontology mappings from OBO, we evaluate whether the proposed approach can re-identify the corresponding relationships. The results indicate that the network structure provides strong cues for decompositional ontology translation and the existing relationships can be used to identify new translations.

  6. Detection of Dispersed Radio Pulses: A machine learning approach to candidate identification and classification

    CERN Document Server

    Devine, Thomas; McLaughlin, Maura

    2016-01-01

    Searching for extraterrestrial, transient signals in astronomical data sets is an active area of current research. However, machine learning techniques are lacking in the literature concerning single-pulse detection. This paper presents a new, two-stage approach for identifying and classifying dispersed pulse groups (DPGs) in single-pulse search output. The first stage identified DPGs and extracted features to characterize them using a new peak identification algorithm which tracks sloping tendencies around local maxima in plots of signal-to-noise ratio vs. dispersion measure. The second stage used supervised machine learning to classify DPGs. We created four benchmark data sets: one unbalanced and three balanced versions using three different imbalance treatments.We empirically evaluated 48 classifiers by training and testing binary and multiclass versions of six machine learning algorithms on each of the four benchmark versions. While each classifier had advantages and disadvantages, all classifiers with im...

  7. A new damage diagnosis approach for NC machine tools based on hybrid Stationary subspace analysis

    Science.gov (United States)

    Gao, Chen; Zhou, Yuqing; Ren, Yan

    2017-05-01

    This paper focused on the damage diagnosis for NC machine tools and put forward a damage diagnosis method based on hybrid Stationary subspace analysis (SSA), for improving the accuracy and visibility of damage identification. First, the observed single sensor signal was reconstructed to multi-dimensional signals by the phase space reconstruction technique, as the inputs of SSA. SSA method was introduced to separate the reconstructed data into stationary components and non-stationary components without the need for independency and prior information of the origin signals. Subsequently, the selected non-stationary components were analysed for training LS-SVM (Least Squares Support Vector Machine) classifier model, in which several statistic parameters in the time and frequency domains were exacted as the sample of LS-SVM. An empirical analysis in NC milling machine tools is developed, and the result shows high accuracy of the proposed approach.

  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. Supporting knowledge translation through collaborative translational research initiatives: ‘Bridging’ versus ‘blurring’ boundary-spanning approaches in the UK CLAHRC initiative

    Science.gov (United States)

    Evans, Sarah; Scarbrough, Harry

    2014-01-01

    Recent policy initiatives in the UK and internationally have sought to promote knowledge translation between the ‘producers’ and ‘users’ of research. Within this paper we explore how boundary-spanning interventions used within such initiatives can support knowledge translation between diverse groups. Using qualitative data from a 3-year research study conducted from January 2010 to December 2012 of two case-sites drawn from the CLAHRC initiative in the UK, we distinguish two different approaches to supporting knowledge translation; a ‘bridging’ approach that involves designated roles, discrete events and activities to span the boundaries between communities, and a ‘blurring’ approach that de-emphasises the boundaries between groups, enabling a more continuous process of knowledge translation as part of day-to-day work-practices. In this paper, we identify and differentiate these boundary-spanning approaches and describe how they emerged from the context defined by the wider CLAHRC networks. This highlights the need to develop a more contextualised analysis of the boundary-spanning that underpins knowledge translation processes, relating this to the distinctive features of a particular case. PMID:24561773

  10. FAULT DIAGNOSIS APPROACH BASED ON HIDDEN MARKOV MODEL AND SUPPORT VECTOR MACHINE

    Institute of Scientific and Technical Information of China (English)

    LIU Guanjun; LIU Xinmin; QIU Jing; HU Niaoqing

    2007-01-01

    Aiming at solving the problems of machine-learning in fault diagnosis, a diagnosis approach is proposed based on hidden Markov model (HMM) and support vector machine (SVM). HMM usually describes intra-class measure well and is good at dealing with continuous dynamic signals. SVM expresses inter-class difference effectively and has perfect classify ability. This approach is built on the merit of HMM and SVM. Then, the experiment is made in the transmission system of a helicopter. With the features extracted from vibration signals in gearbox, this HMM-SVM based diagnostic approach is trained and used to monitor and diagnose the gearbox's faults. The result shows that this method is better than HMM-based and SVM-based diagnosing methods in higher diagnostic accuracy with small training samples.

  11. 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.

  12. A collaborative approach to develop a multi-omics data analytics platform for translational research.

    Science.gov (United States)

    Schumacher, Axel; Rujan, Tamas; Hoefkens, Jens

    2014-12-01

    The integration and analysis of large datasets in translational research has become an increasingly challenging problem. We propose a collaborative approach to integrate established data management platforms with existing analytical systems to fill the hole in the value chain between data collection and data exploitation. Our proposal in particular ensures data security and provides support for widely distributed teams of researchers. As a successful example for such an approach, we describe the implementation of a unified single platform that combines capabilities of the knowledge management platform tranSMART and the data analysis system Genedata Analyst™. The combined end-to-end platform helps to quickly find, enter, integrate, analyze, extract, and share patient- and drug-related data in the context of translational R&D projects.

  13. Machine Learning Approach for the Outcome Prediction of Temporal Lobe Epilepsy Surgery

    Science.gov (United States)

    DeFelipe-Oroquieta, Jesús; Kastanauskaite, Asta; de Sola, Rafael G.; DeFelipe, Javier; Bielza, Concha; Larrañaga, Pedro

    2013-01-01

    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. PMID:23646148

  14. Machining Performance Study on Metal Matrix Composites-A Response Surface Methodology Approach

    Directory of Open Access Journals (Sweden)

    A. Srinivasan

    2012-01-01

    Full Text Available Problem statement: Metal Matrix Composites (MMC have become a leading material among composite materials and in particular, particle reinforced aluminum MMCs have received considerable attention due to their excellent engineering properties. These materials are known as the difficult-to-machine materials because of the hardness and abrasive nature of reinforcement element-like Alumina (Al2O3. Approach: In this study, an attempt has been made to model the machinability evaluation through the response surface methodology in machining of homogenized 10% micron Al2O3 LM25 Al MMC manufactured through stir casting method. Results: The combined effects of three machining parameters including cutting speed (s, feed rate (f and depth of cut (d on the basis of three performance characteristics of tool wear (VB, surface Roughness (Ra and cutting Force (Fz were investigated. The contour plots were generated to study the effect of process parameters as well as their interactions. Conclusion: The process parameters are optimized using desirability-based approach response surface methodology.

  15. A New Approach of Error Compensation on NC Machining Based on Memetic Computation

    Directory of Open Access Journals (Sweden)

    Huanglin Zeng

    2013-04-01

    Full Text Available This paper is a study of the application of Memetic computation integrating and coordinating intelligence algorithms to solve the problems of error compensation for a high-precision numeral control machining system. The primary focus is on development of integrated intelligent computation approach to set up an error compensation system of a numeral control machine tool based on a dynamic feedback neural network. Optimization of error measurement points of a numeral control machine tool is realized by way of application of error variable attribute reduction on rough set theory. A principal component analysis is used for data compression and feature extraction to reduce the input dimension of a dynamic feedback neural network. A dynamic feedback neural network is trained on ant colony algorithm so that network can converge to get a global optimum. Positioning error caused in thermal deformation compensation capabilities were tested using industry standard equipment and procedures. The results obtained shows that this approach can effectively improve compensation precision and real time of error compensation on machine tools.

  16. 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.

  17. Approach towards sensor placement, selection and fusion for real-time condition monitoring of precision machines

    Science.gov (United States)

    Er, Poi Voon; Teo, Chek Sing; Tan, Kok Kiong

    2016-02-01

    Moving mechanical parts in a machine will inevitably generate vibration profiles reflecting its operating conditions. Vibration profile analysis is a useful tool for real-time condition monitoring to avoid loss of performance and unwanted machine downtime. In this paper, we propose and validate an approach for sensor placement, selection and fusion for continuous machine condition monitoring. The main idea is to use a minimal series of sensors mounted at key locations of a machine to measure and infer the actual vibration spectrum at a critical point where it is not suitable to mount a sensor. The locations for sensors' mountings which are subsequently used for vibration inference are identified based on sensitivity calibration at these locations moderated with normalized Fisher Information (NFI) associated with the measurement quality of the sensor at that location. Each of the identified sensor placement location is associated with one or more sensitive frequencies for which it ranks top in terms of the moderated sensitivities calibrated. A set of Radial Basis Function (RBF), each of them associated with a range of sensitive frequencies, is used to infer the vibration at the critical point for that frequency. The overall vibration spectrum of the critical point is then fused from these components. A comprehensive set of experimental results for validation of the proposed approach is provided in the paper.

  18. 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.

  19. Machine-translatability and post-editing effort: an empirical study using translog and choice network analysis

    OpenAIRE

    O'Brien, Sharon

    2006-01-01

    Studies on Controlled Language (CL) suggest that by removing features that are known to be problematic for MT (termed here “negative translatability indicators”, or “NTIs”), the MT output can be improved. It is assumed that an improvement in the output will result in lower post-editing effort. This study tests that assumption by measuring the technical, temporal and cognitive post-editing effort (Krings 2001) for English sentences in a user manual that have been translated into German using a...

  20. 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 mo......, 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.......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...

  1. Translation Techniques

    Directory of Open Access Journals (Sweden)

    Marcia Pinheiro

    2015-05-01

    Full Text Available In this paper, we discuss three translation techniques: literal, cultural, and artistic. Literal translation is a well-known technique, which means that it is quite easy to find sources on the topic. Cultural and artistic translation may be new terms. Whilst cultural translation focuses on matching contexts, artistic translation focuses on matching reactions. Because literal translation matches only words, it is not hard to find situations in which we should not use this technique.  Because artistic translation focuses on reactions, judging the quality of an artistic translation work is one of the most difficult things one can do. We end up having a score of complexity and humanity for each one of the mentioned techniques: Literal translation would be the closest thing we have to the machines world and artistic translation would be the closest thing we have to the purely human world. By creating these classifications and studying the subtleties of each one of them, we are adding degrees of quality to our courses and to translation as a professional field. The main contribution of this paper is then the formalization of such a piece of knowledge. We, however, also lay the foundations for studies of this type.

  2. Lost in Translation

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    The intricacies of language still eludes even the most sophisticated technology IT is no surprise Jost Zetzsche,an English-to-German translator,raised the question of whether machine translation would ever replace the human variety in front of 700 interpreters and translators who gathered in San Francisco to discuss topical issues in the translation industry.

  3. Translators and Tools

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    Technology is not yet advanced enough to capture the nuances of language It is no surprise Jost Zetzsche,an English-to-German translator,raised the question of whether machine translation would ever replace the human variety in front of 700 interpreters and translators who gathered in San Francisco to discuss topical issues in the translation industry.

  4. Lost in Translation

    Institute of Scientific and Technical Information of China (English)

    Ding Zhitao; Chen Wen

    2011-01-01

    IT is no surprise Jost Zetzsche,an English-to-German translator,raised the question of whether machine translation would ever replace the human variety in front of 700 interpreters and translators who gathered in San Francisco to discuss topical issues in the translation industry.

  5. 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.

  6. A Novel Soft Sensor Modeling Approach Based on Least Squares Support Vector Machines

    Institute of Scientific and Technical Information of China (English)

    Feng Rui(冯瑞); Song Chunlin; Zhang Yanzhu; Shao Huihe

    2004-01-01

    Artificial Neural Networks (ANNs) such as radial basis function neural networks (RBFNNs) have been successfully used in soft sensor modeling. However, the generalization ability of conventional ANNs is not very well. For this reason, we present a novel soft sensor modeling approach based on Support Vector Machines (SVMs). Since standard SVMs have the limitation of speed and size in training large data set, we hereby propose Least Squares Support Vector Machines (LS_SVMs) and apply it to soft sensor modeling. Systematic analysis is performed and the result indicates that the proposed method provides satisfactory performance with excellent approximation and generalization property. Monte Carlo simulations show that our soft sensor modeling approach achieves performance superior to the conventional method based on RBFNNs.

  7. 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

  8. Drifting model approach to modeling based on weighted support vector machines

    Institute of Scientific and Technical Information of China (English)

    冯瑞; 宋春林; 邵惠鹤

    2004-01-01

    This paper proposes a novel drifting modeling (DM) method. Briefly, we first employ an improved SVMs algorithm named weighted support vector machines (W_SVMs), which is suitable for locally learning, and then the DM method using the algorithm is proposed. By applying the proposed modeling method to Fluidized Catalytic Cracking Unit (FCCU), the simulation results show that the property of this proposed approach is superior to global modeling method based on standard SVMs.

  9. Aspects of Production Ecologization of Machine-Building Enterprises as Part of the System Approach

    Science.gov (United States)

    Lazutina, T. V.; Tempel, Yu A.; Tempel, O. A.; Lazutin, N. К

    2017-05-01

    The paper considers the role of the machine-building industry in Russia and the impact of its activities on the ecological situation in the country. As part of the problem we identified areas of environmental pollution from different production industries, including foundry, power, metal working and welding. In addition, the paper presents a strategy for production ecologization, based on a system approach viewed as a set of measures aimed at reducing the danger of technological processes for the environment and people.

  10. Design Optimization And Thermal Analysis Of Multipurpose Refrigerant Gas Recovery Machine: An Innovative Approach

    Science.gov (United States)

    Jirapure, Sagar C.

    2010-10-01

    Today on the global scene, world will see a definite impact of global temperatures, coupled with burgeoning population, will make society more vulnerable to climatic disorder, drought, famines, and flood longer heat waves spreading to newer areas. Tropical islands and low-lying coastal areas will face the treat of being submerged. Hence, it is important to reduce refrigerant emission and the approaching and with approaching phase out date for CFC elimination. It is important to recover as much of refrigerant as possible. Likewise, HFCs should also be recovered as they have high GWP. For such recovery of refrigerant, a recovery & recycling machine is required. The machine is usually comprising a hermetic compressor, air-cooled condenser, distilator, Oil separator, filters and Electric motor. The refrigerant from the appliances is drown through the filters by compressor and then discharged into recovery cylinder. The recovery cylinder should just be used for recovered refrigerant. This is because oil will usually be covered with refrigerant and this will contaminate the cylinder. It is therefore very important to treat the recovery of refrigerant at most accuracy, which require close optimization of design and further analysis of gas behavior in the system. This project aims to provide optimum solution as regards to thermal analysis of gas recovery machine. For getting insight the parameters like Specific heat of vapor at constant pressure, Density of saturated vapor, Latent heat of vaporization at boiling point, Thermal conductivity of vapor, Surface tension, etc. will require critical approach. To impart the thermal analysis, ANSYS software is proposed. It in turn provides the details of temperatures through out the piping of machine, pressure and velocity of at various locations of different components as well as the thermal zones near to high pressure and temperatures in the machine, which gives better approach for design of future gas recovery machines. It is

  11. Word Translation Prediction for Morphologically Rich Languages with Bilingual Neural Networks

    NARCIS (Netherlands)

    Tran, K.; Bisazza, A.; Monz, C.

    2014-01-01

    Translating into morphologically rich languages is a particularly difficult problem in machine translation due to the high degree of inflectional ambiguity in the target language, often only poorly captured by existing word translation models. We present a general approach that exploits source-side

  12. English-Latvian SMT: the challenge of translating into a free word order language

    NARCIS (Netherlands)

    Khalilov, M.; Fonollosa, J.A.R.; Skadiņa, I.; Brālītis, E.; Pretkalniņa, L.

    2010-01-01

    This paper presents a comparative study of two approaches to statistical machine translation (SMT) and their application to a task of English-to-Latvian translation, which is still an open research line in the field of automatic translation. We consider a state-of-the-art phrase-based SMT and an alt

  13. An Integrated Approach of Fuzzy Linguistic Preference Based AHP and Fuzzy COPRAS for Machine Tool Evaluation.

    Science.gov (United States)

    Nguyen, Huu-Tho; Md Dawal, Siti Zawiah; Nukman, Yusoff; Aoyama, Hideki; Case, Keith

    2015-01-01

    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.

  14. 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 machine-learning model on a workstation with 3.4-GHz Intel i7 8-core processor. Copyright © 2016 the American Physiological Society.

  15. 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.

  16. 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...

  17. A long-term, strategic approach to evidence generation and knowledge translation in NSW, Australia

    Directory of Open Access Journals (Sweden)

    Sarah Thackway

    2017-02-01

    Full Text Available There is a growing body of literature about the barriers to, and enablers of, the use of research evidence in policy and practice. Research funders are in a unique position to influence activities aimed at promoting research use. During the past decade, NSW (New South Wales Health has systematically built and invested in an integrated population and health services research portfolio made up of different types of investment and policy focuses. Each of these investments has an explicit focus on translation. Ensuring a long-term, sustained, strategic approach to priority-driven research generation, true coproduction of evidence and effective knowledge translation will continue to deliver results for NSW. The NSW Population Health Research Strategy 2017–2021, currently in development, will have a strong emphasis on fostering environments and actions that promote the use of research in policy and practice.

  18. Towards a French/French Sign Language Machine-Translation System (TLF Vers un système de traduction automatique : français/langue des signes française (TLF

    Directory of Open Access Journals (Sweden)

    Gaspard Breton

    2009-04-01

    Full Text Available We present a work in the framewok of machine translation from French to French Sign Language (FSL with synthesis of gestures through a virtual agent. We first give some descriptive and theoretical elements about the FSL. Then we propose a formalization of the standard part of the FSL lexicon as well as propositions concerning some morpho-syntactic phenomena. Then we present the machine translation system based on interlingua representation system "TiLT" developed at France Telecom R&D and the adaptation of its generation module to FSL. We end with the avatar technology also developed at France Telecom R&D and its FSL treatment.

  19. Multilingual online machine translation research%多语言在线机器翻译研究

    Institute of Scientific and Technical Information of China (English)

    董兴华; 徐春; 王磊; 周喜

    2012-01-01

    This paper gives a description of implementing an online, high-powered multilingual translation engine, which consists of three language pairs, that is, Uyghur-Chinese, Kazakh-Chinese and Kyrgyz-Chinese, based on additional knowledge base and multithreading and task distributing technology. The translation engine is easy to be extended to other language pairs, which has an ability of translating words, phrases, sentences, files and webs in one language to those of another.%描述了通过使用外部知识库和基于短语的翻译模型,利用多线程、任务分发的技术实现了一个在线的、高性能的多语言翻译引擎,已初步实现了维汉、哈汉、柯汉三种语言间的翻译.翻译引擎很容易扩展到其他语言对,具有翻译词、短语、句子、文件和网页的功能.

  20. PREDICTION OF TOOL CONDITION DURING TURNING OF ALUMINIUM/ALUMINA/GRAPHITE HYBRID METAL MATRIX COMPOSITES USING MACHINE LEARNING APPROACH

    Directory of Open Access Journals (Sweden)

    N. RADHIKA

    2015-10-01

    Full Text Available Aluminium/alumina/graphite hybrid metal matrix composites manufactured using stir casting technique was subjected to machining studies to predict tool condition during machining. Fresh tool as well as tools with specific amount of wear deliberately created prior to machining experiments was used. Vibration signals were acquired using an accelerometer for each tool condition. These signals were then processed to extract statistical and histogram features to predict the tool condition during machining. Two classifiers namely, Random Forest and Classification and Regression Tree (CART were used to classify the tool condition. Results showed that histogram features with Random Forest classifier yielded maximum efficiency in predicting the tool condition. This machine learning approach enables the prediction of tool failure in advance, thereby minimizing the unexpected breakdown of tool and machine.

  1. 试论乔治·穆南的翻译观%On George Mounin's Approach to Translation

    Institute of Scientific and Technical Information of China (English)

    刘海云

    2001-01-01

    乔治·穆南是法国翻译语言学理论的创始人,他善于从语言学途径去研究翻译的有关语言层次问题,对翻译及翻译理论问题的探索超迈一般经验主义范围,其翻译观曾濡染影响法国整个翻译界。%George Mounin was the founder of linguistic theory to translation in France. He dared to study the linguistic hierarchical problems to translation by the way of linguistics,which surpassed the scope of empiricism concerning translation and translation theory. His approach to translation once immersed and influenced the whole world of translation in France.

  2. An intelligent approach to machine component health prognostics by utilizing only truncated histories

    Science.gov (United States)

    Lu, Chen; Tao, Laifa; Fan, Huanzhen

    2014-01-01

    Numerous techniques and methods have been proposed to reduce the production downtime, spare-part inventory, maintenance cost, and safety hazards of machineries and equipment. Prognostics are regarded as a significant and promising tool for achieving these benefits for machine maintenance. However, prognostic models, particularly probabilistic-based methods, require a large number of failure instances. In practice, engineering assets are rarely being permitted to run to failure. Many studies have reported valuable models and methods that engage in maximizing both truncated and failure data. However, limited studies have focused on cases where only truncated data are available, which is common in machine condition monitoring. Therefore, this study develops an intelligent machine component prognostics system by utilizing only truncated histories. First, the truncated Minimum Quantization Error (MQE) histories were obtained by Self-organizing Map network after feature extraction. The chaos-based parallel multilayer perceptron network and polynomial fitting for residual errors were adopted to generate the predicted MQEs and failure times following the truncation times. The feed-forward neural network (FFNN) was trained with inputs both from the truncated MQE histories and from the predicted MQEs. The target vectors of survival probabilities were estimated by intelligent product limit estimator using the truncation times and generated failure times. After validation, the FFNN was applied to predict the machine component health of individual units. To validate the proposed method, two cases were considered by using the degradation data generated by bearing testing rig. Results demonstrate that the proposed method is a promising intelligent prognostics approach for machine component health.

  3. 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.

  4. Analysis of machining characteristics in drilling of GFRP composite with application of fuzzy logic approach

    Directory of Open Access Journals (Sweden)

    B.C. Routar

    2013-10-01

    Full Text Available This paper discusses the application of the Taguchi method to optimize the machining parameters for machining of GFRP composite in drilling for individual responses such as thrust force and delamination factor. Moreover, a multi-response performance characteristic is used for optimization of process parameters with application of grey relational analysis. An orthogonal array (L9, grey relational generation, grey relational coefficient and grey – fuzzy grade obtained from the grey relational analysis applied as performance index to solve the optimization problem of drilling parameters for GFRP composite. Taguchi orthogonal array, the signal-to-noise ratio, and the analysis of variance are used to investigate the optimal levels of cutting parameters. The confirmation tests are conducted to verify the results and it is observed that grey-fuzzy approach is efficient in determining the optimal cutting parameters.

  5. 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.

  6. 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.

  7. Big Data meets Quantum Chemistry Approximations: The $\\Delta$-Machine Learning Approach

    CERN Document Server

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

    2015-01-01

    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 constitutional isomers of C$_7$H$_{10}$O$_2$ 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 semi-empirical quantum chemistry and machine learning models trained on 1 and 10\\% of 134k organ...

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2007-07-01

    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. A state machine approach in modelling the heating process of a building

    Energy Technology Data Exchange (ETDEWEB)

    Pakanen, Jouko [Helsinki University of Technology, P.O. Box 3300, FI-02015 TKK Espoo (Finland); Karjalainen, Sami [VTT, P.O. Box 1000, FI-02044 VTT Espoo (Finland)

    2009-05-15

    Process models and their applications have gradually become an integral part of the design, maintenance and automation of modern buildings. The following state machine model outlines a new approach in this area. The heating power described by the model is based on the recent inputs as well as on the past inputs and outputs of the process, thus also representing the states of the system. Identifying the model means collecting, assorting and storing observations, but also effectively utilizing their inherent relationships and nearest neighbours. The last aspect enables to create a uniform set of data, which forms the characteristic, dynamic behaviour of the HVAC process. The state machine model is non-parametric and needs no sophisticated algorithm for identification. It is therefore suitable for small microprocessor devices equipped with a larger memory capacity. The first test runs, performed in a simulated environment, were encouraging and showed good prediction capability. (author)

  10. A Machine Learning Approach for Business Intelligence Analysis using Commercial Shipping Transaction Data

    Energy Technology Data Exchange (ETDEWEB)

    Bramer, Lisa M.; Chatterjee, Samrat; Holmes, Aimee E.; Robinson, Sean M.; Bradley, Steven F.; Webb-Robertson, Bobbie-Jo M.

    2015-09-30

    Business intelligence problems are particularly challenging due to the use of large volume and high velocity data in attempts to model and explain complex underlying phenomena. Incremental machine learning based approaches for summarizing trends and identifying anomalous behavior are often desirable in such conditions to assist domain experts in characterizing their data. The overall goal of this research is to develop a machine learning algorithm that enables predictive analysis on streaming data, detects changes and anomalies in the data, and can evolve based on the dynamic behavior of the data. Commercial shipping transaction data for the U.S. is used to develop and test a Naïve Bayes model that classifies several companies into lines of businesses and demonstrates an ability to predict when the behavior of these companies changes by venturing into other lines of businesses.

  11. 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.

  12. Translational informatics approach for identifying the functional molecular communicators linking coronary artery disease, infection and inflammation.

    Science.gov (United States)

    Sharma, Ankit; Ghatge, Madankumar; Mundkur, Lakshmi; Vangala, Rajani Kanth

    2016-05-01

    Translational informatics approaches are required for the integration of diverse and accumulating data to enable the administration of effective translational medicine specifically in complex diseases such as coronary artery disease (CAD). In the current study, a novel approach for elucidating the association between infection, inflammation and CAD was used. Genes for CAD were collected from the CAD‑gene database and those for infection and inflammation were collected from the UniProt database. The cytomegalovirus (CMV)‑induced genes were identified from the literature and the CAD‑associated clinical phenotypes were obtained from the Unified Medical Language System. A total of 55 gene ontologies (GO) termed functional communicator ontologies were identified in the gene sets linking clinical phenotypes in the diseasome network. The network topology analysis suggested that important functions including viral entry, cell adhesion, apoptosis, inflammatory and immune responses networked with clinical phenotypes. Microarray data was extracted from the Gene Expression Omnibus (dataset: GSE48060) for highly networked disease myocardial infarction. Further analysis of differentially expressed genes and their GO terms suggested that CMV infection may trigger a xenobiotic response, oxidative stress, inflammation and immune modulation. Notably, the current study identified γ‑glutamyl transferase (GGT)‑5 as a potential biomarker with an odds ratio of 1.947, which increased to 2.561 following the addition of CMV and CMV‑neutralizing antibody (CMV‑NA) titers. The C‑statistics increased from 0.530 for conventional risk factors (CRFs) to 0.711 for GGT in combination with the above mentioned infections and CRFs. Therefore, the translational informatics approach used in the current study identified a potential molecular mechanism for CMV infection in CAD, and a potential biomarker for risk prediction.

  13. Moving Toward Paradigm-Shifting Research in Health Disparities Through Translational, Transformational, and Transdisciplinary Approaches

    Science.gov (United States)

    Rhee, Kyu B.; Stoff, David M.; Pohlhaus, Jennifer Reineke; Sy, Francisco S.; Stinson, Nathaniel; Ruffin, John

    2010-01-01

    Translational, transdisciplinary, and transformational research stands to become a paradigm-shifting mantra for research in health disparities. A windfall of research discoveries using these 3 approaches has increased our understanding of the health disparities in racial, ethnic, and low socioeconomic status groups. These distinct but related research spheres possess unique environments, which, when integrated, can lead to innovation in health disparities science. In this article, we review these approaches and propose integrating them to advance health disparities research through a change in philosophical position and an increased emphasis on community engagement. We argue that a balanced combination of these research approaches is needed to inform evidence-based practice, social action, and effective policy change to improve health in disparity communities. PMID:20147662

  14. 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.

  15. Korean to English Translation Using Synchronous TAGs

    CERN Document Server

    Egedi, D; Park, H S; Joshi, A K; Egedi, Dania; Palmer, Martha; Park, Hyun S.; Joshi, Aravind K.

    1994-01-01

    It is often argued that accurate machine translation requires reference to contextual knowledge for the correct treatment of linguistic phenomena such as dropped arguments and accurate lexical selection. One of the historical arguments in favor of the interlingua approach has been that, since it revolves around a deep semantic representation, it is better able to handle the types of linguistic phenomena that are seen as requiring a knowledge-based approach. In this paper we present an alternative approach, exemplified by a prototype system for machine translation of English and Korean which is implemented in Synchronous TAGs. This approach is essentially transfer based, and uses semantic feature unification for accurate lexical selection of polysemous verbs. The same semantic features, when combined with a discourse model which stores previously mentioned entities, can also be used for the recovery of topicalized arguments. In this paper we concentrate on the translation of Korean to English.

  16. Candidate gene prioritization by network analysis of differential expression using machine learning approaches

    Directory of Open Access Journals (Sweden)

    Nitsch Daniela

    2010-09-01

    Full Text Available Abstract Background Discovering novel disease genes is still challenging for diseases for which no prior knowledge - such as known disease genes or disease-related pathways - is available. Performing genetic studies frequently results in large lists of candidate genes of which only few can be followed up for further investigation. We have recently developed a computational method for constitutional genetic disorders that identifies the most promising candidate genes by replacing prior knowledge by experimental data of differential gene expression between affected and healthy individuals. To improve the performance of our prioritization strategy, we have extended our previous work by applying different machine learning approaches that identify promising candidate genes by determining whether a gene is surrounded by highly differentially expressed genes in a functional association or protein-protein interaction network. Results We have proposed three strategies scoring disease candidate genes relying on network-based machine learning approaches, such as kernel ridge regression, heat kernel, and Arnoldi kernel approximation. For comparison purposes, a local measure based on the expression of the direct neighbors is also computed. We have benchmarked these strategies on 40 publicly available knockout experiments in mice, and performance was assessed against results obtained using a standard procedure in genetics that ranks candidate genes based solely on their differential expression levels (Simple Expression Ranking. Our results showed that our four strategies could outperform this standard procedure and that the best results were obtained using the Heat Kernel Diffusion Ranking leading to an average ranking position of 8 out of 100 genes, an AUC value of 92.3% and an error reduction of 52.8% relative to the standard procedure approach which ranked the knockout gene on average at position 17 with an AUC value of 83.7%. Conclusion In this study we

  17. 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.

  18. A hybrid multi-objective evolutionary algorithm approach for handling sequence- and machine-dependent set-up times in unrelated parallel machine scheduling problem

    Indian Academy of Sciences (India)

    V K MANUPATI; G RAJYALAKSHMI; FELIX T S CHAN; J J THAKKAR

    2017-03-01

    This paper addresses a fuzzy mixed-integer non-linear programming (FMINLP) model by considering machine-dependent and job-sequence-dependent set-up times that minimize the total completion time,the number of tardy jobs, the total flow time and the machine load variation in the context of unrelated parallel machine scheduling (UPMS) problem. The above-mentioned multi-objectives were considered based on nonzero ready times, machine- and sequence-dependent set-up times and secondary resource constraints for jobs.The proposed approach considers unrelated parallel machines with inherent uncertainty in processing times and due dates. Since the problem is shown to be NP-hard in nature, it is a challenging task to find the optimal/nearoptimal solutions for conflicting objectives simultaneously in a reasonable time. Therefore, we introduced a new multi-objective-based evolutionary artificial immune non-dominated sorting genetic algorithm (AI-NSGA-II) to resolve the above-mentioned complex problem. The performance of the proposed multi-objective AI-NSGA-II algorithm has been compared to that of multi-objective particle swarm optimization (MOPSO) and conventionalnon-dominated sorting genetic algorithm (CNSGA-II), and it is found that the proposed multi-objective-based hybrid meta-heuristic produces high-quality solutions. Finally, the results obtained from benchmark instances and randomly generated instances as test problems evince the robust performance of the proposed multiobjective algorithm.

  19. Reliability Analysis of a 3-Machine Power Station Using State Space Approach

    Directory of Open Access Journals (Sweden)

    WasiuAkande Ahmed

    2014-07-01

    Full Text Available With the advent of high-integrity fault-tolerant systems, the ability to account for repairs of partially failed (but still operational systems become increasingly important. This paper presents a systemic method of determining the reliability of a 3-machine electric power station, taking into consideration the failure rates and repair rates of the individual component (machine that make up the system. A state-space transition process for a 3-machine with 23 states was developed and consequently, steady state equations were generated based on Markov mathematical modeling of the power station. Important reliability components were deduced from this analysis. This research simulation was achieved with codes written in Excel® -VBA programming environment. System reliability using state space approach proofs to be a viable and efficient technique of reliability prediction as it is able to predict the state of the system under consideration. For the purpose of neatness and easy entry of data, Graphic User Interface (GUI was designed.

  20. Biosimilarity Assessments of Model IgG1-Fc Glycoforms Using a Machine Learning Approach.

    Science.gov (United States)

    Kim, Jae Hyun; Joshi, Sangeeta B; Tolbert, Thomas J; Middaugh, C Russell; Volkin, David B; Smalter Hall, Aaron

    2016-02-01

    Biosimilarity assessments are performed to decide whether 2 preparations of complex biomolecules can be considered "highly similar." In this work, a machine learning approach is demonstrated as a mathematical tool for such assessments using a variety of analytical data sets. As proof-of-principle, physical stability data sets from 8 samples, 4 well-defined immunoglobulin G1-Fragment crystallizable glycoforms in 2 different formulations, were examined (see More et al., companion article in this issue). The data sets included triplicate measurements from 3 analytical methods across different pH and temperature conditions (2066 data features). Established machine learning techniques were used to determine whether the data sets contain sufficient discriminative power in this application. The support vector machine classifier identified the 8 distinct samples with high accuracy. For these data sets, there exists a minimum threshold in terms of information quality and volume to grant enough discriminative power. Generally, data from multiple analytical techniques, multiple pH conditions, and at least 200 representative features were required to achieve the highest discriminative accuracy. In addition to classification accuracy tests, various methods such as sample space visualization, similarity analysis based on Euclidean distance, and feature ranking by mutual information scores are demonstrated to display their effectiveness as modeling tools for biosimilarity assessments.

  1. Characterization of the Montane Huntington Wildlife Forest Ecosystem Using Machine Learning Approaches from Remote Sensing Data

    Science.gov (United States)

    Li, Manqi

    Montane forests are susceptible to various stressors such as land use and climate change. Consequently, research on characterizing montane forest ecosystems should be conducted on a continuous basis for sustainable forest management. In this research, forest type mapping and change analysis, and biomass/carbon stock quantification were performed over a mountainous forest located in the central Adirondack Park, NY, by employing machine learning techniques at the plot level. Multi-temporal Landsat TM data were used to classify forest type cover and to detect forest cover changes for the past 20 years. Forest biomass and carbon stock quantification was then performed using full waveform LiDAR data collected in September 2011. Accuracies from the two case studies were in support of the versatility of machine learning approaches for forest and ecological investigation. Topographic characteristics affected the classification accuracy as well as the forest type change for the past 20 years. LiDAR-derived metrics, especially height-based ones, proved useful for quantifying biomass/carbon stock. Keywords: Landsat TM, full waveform LiDAR, forest classification, forest change analysis, biomass, carbon stock, machine learning

  2. 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.

  3. A Decentralized Virtual Machine Migration Approach of Data Centers for Cloud Computing

    Directory of Open Access Journals (Sweden)

    Xiaoying Wang

    2013-01-01

    Full Text Available As cloud computing offers services to lots of users worldwide, pervasive applications from customers are hosted by large-scale data centers. Upon such platforms, virtualization technology is employed to multiplex the underlying physical resources. Since the incoming loads of different application vary significantly, it is important and critical to manage the placement and resource allocation schemes of the virtual machines (VMs in order to guarantee the quality of services. In this paper, we propose a decentralized virtual machine migration approach inside the data centers for cloud computing environments. The system models and power models are defined and described first. Then, we present the key steps of the decentralized mechanism, including the establishment of load vectors, load information collection, VM selection, and destination determination. A two-threshold decentralized migration algorithm is implemented to further save the energy consumption as well as keeping the quality of services. By examining the effect of our approach by performance evaluation experiments, the thresholds and other factors are analyzed and discussed. The results illustrate that the proposed approach can efficiently balance the loads across different physical nodes and also can lead to less power consumption of the entire system holistically.

  4. 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...

  5. 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

  6. 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.

  7. Automatic translation among spoken languages

    Science.gov (United States)

    Walter, Sharon M.; Costigan, Kelly

    1994-01-01

    The Machine Aided Voice Translation (MAVT) system was developed in response to the shortage of experienced military field interrogators with both foreign language proficiency and interrogation skills. Combining speech recognition, machine translation, and speech generation technologies, the MAVT accepts an interrogator's spoken English question and translates it into spoken Spanish. The spoken Spanish response of the potential informant can then be translated into spoken English. Potential military and civilian applications for automatic spoken language translation technology are discussed in this paper.

  8. 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

  9. A Cognitive Systems Engineering Approach to Developing Human Machine Interface Requirements for New Technologies

    Science.gov (United States)

    Fern, Lisa Carolynn

    This dissertation examines the challenges inherent in designing and regulating to support human-automation interaction for new technologies that will be deployed into complex systems. A key question for new technologies with increasingly capable automation, is how work will be accomplished by human and machine agents. This question has traditionally been framed as how functions should be allocated between humans and machines. Such framing misses the coordination and synchronization that is needed for the different human and machine roles in the system to accomplish their goals. Coordination and synchronization demands are driven by the underlying human-automation architecture of the new technology, which are typically not specified explicitly by designers. The human machine interface (HMI), which is intended to facilitate human-machine interaction and cooperation, typically is defined explicitly and therefore serves as a proxy for human-automation cooperation requirements with respect to technical standards for technologies. Unfortunately, mismatches between the HMI and the coordination and synchronization demands of the underlying human-automation architecture can lead to system breakdowns. A methodology is needed that both designers and regulators can utilize to evaluate the predicted performance of a new technology given potential human-automation architectures. Three experiments were conducted to inform the minimum HMI requirements for a detect and avoid (DAA) system for unmanned aircraft systems (UAS). The results of the experiments provided empirical input to specific minimum operational performance standards that UAS manufacturers will have to meet in order to operate UAS in the National Airspace System (NAS). These studies represent a success story for how to objectively and systematically evaluate prototype technologies as part of the process for developing regulatory requirements. They also provide an opportunity to reflect on the lessons learned in order

  10. English Translation Strategies of Lun Yu:A Post-colonial Approach

    Institute of Scientific and Technical Information of China (English)

    Zhang Xiaoman; Peng Zhen

    2016-01-01

    This paper discusses English translation strategies of Lun Yu from the perspec-tive of post-colonialism translation theory. Post-colonial translation theory makes research like cultural archaeology on translation practice, and influences translation practice through power difference of power discourse. It researches and interprets the translator’ s conscious and unconscious value orientations and choices of strategy. Under its guidance,a research is made concerning the English translation of Lun Yu,and four strategies,namely,domestication,for-eignization,hybridization and decolonization,are explicitly explained and analyzed.

  11. A Novel Approach to Automatic Road-Accident Detection using Machine Vision Techniques

    Directory of Open Access Journals (Sweden)

    Vaishnavi Ravindran

    2016-11-01

    Full Text Available In this paper, a novel approach for automatic road accident detection is proposed. The approach is based on detecting damaged vehicles from footage received from surveillance cameras installed in roads and highways which would indicate the occurrence of a road accident. Detection of damaged cars falls under the category of object detection in the field of machine vision and has not been achieved so far. In this paper, a new supervised learning method comprising of three different stages which are combined into a single framework in a serial manner which successfully detects damaged cars from static images is proposed. The three stages use five support vector machines trained with Histogram of gradients (HOG and Gray level co-occurrence matrix (GLCM features. Since damaged car detection has not been attempted, two datasets of damaged cars - Damaged Cars Dataset-1 (DCD-1 and Damaged Cars Dataset-2 (DCD-2 – was compiled for public release. Experiments were conducted on DCD-1 and DCD-2 which differ based on the distance at which the image is captured and the quality of the images. The accuracy of the system is 81.83% for DCD-1 captured at approximately 2 meters with good quality and 64.37% for DCD-2 captured at approximately 20 meters with poor quality.

  12. Development of Type 2 Diabetes Mellitus Phenotyping Framework Using Expert Knowledge and Machine Learning Approach.

    Science.gov (United States)

    Kagawa, Rina; Kawazoe, Yoshimasa; Ida, Yusuke; Shinohara, Emiko; Tanaka, Katsuya; Imai, Takeshi; Ohe, Kazuhiko

    2017-07-01

    Phenotyping is an automated technique that can be used to distinguish patients based on electronic health records. To improve the quality of medical care and advance type 2 diabetes mellitus (T2DM) research, the demand for T2DM phenotyping has been increasing. Some existing phenotyping algorithms are not sufficiently accurate for screening or identifying clinical research subjects. We propose a practical phenotyping framework using both expert knowledge and a machine learning approach to develop 2 phenotyping algorithms: one is for screening; the other is for identifying research subjects. We employ expert knowledge as rules to exclude obvious control patients and machine learning to increase accuracy for complicated patients. We developed phenotyping algorithms on the basis of our framework and performed binary classification to determine whether a patient has T2DM. To facilitate development of practical phenotyping algorithms, this study introduces new evaluation metrics: area under the precision-sensitivity curve (AUPS) with a high sensitivity and AUPS with a high positive predictive value. The proposed phenotyping algorithms based on our framework show higher performance than baseline algorithms. Our proposed framework can be used to develop 2 types of phenotyping algorithms depending on the tuning approach: one for screening, the other for identifying research subjects. We develop a novel phenotyping framework that can be easily implemented on the basis of proper evaluation metrics, which are in accordance with users' objectives. The phenotyping algorithms based on our framework are useful for extraction of T2DM patients in retrospective studies.

  13. 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.

  14. 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.

  15. A Machine Learning Approach to Recovery of Scene Geometry from Images

    CERN Document Server

    Trinh, Hoang

    2010-01-01

    Recovering the 3D structure of the scene from images yields useful information for tasks such as shape and scene recognition, object detection, or motion planning and object grasping in robotics. In this thesis, we introduce a general machine learning approach called unsupervised CRF learning based on maximizing the conditional likelihood. We apply our approach to computer vision systems that recover the 3-D scene geometry from images. We focus on recovering 3D geometry from single images, stereo pairs and video sequences. Building these systems requires algorithms for doing inference as well as learning the parameters of conditional Markov random fields (MRF). Our system is trained unsupervisedly without using ground-truth labeled data. We employ a slanted-plane stereo vision model in which we use a fixed over-segmentation to segment the left image into coherent regions called superpixels, then assign a disparity plane for each superpixel. Plane parameters are estimated by solving an MRF labelling problem, t...

  16. Fully nonlinear statistical and machine-learning approaches for hydrological frequency estimation at ungauged sites

    Science.gov (United States)

    Ouali, D.; Chebana, F.; Ouarda, T. B. M. J.

    2017-06-01

    The high complexity of hydrological systems has long been recognized. Despite the increasing number of statistical techniques that aim to estimate hydrological quantiles at ungauged sites, few approaches were designed to account for the possible nonlinear connections between hydrological variables and catchments characteristics. Recently, a number of nonlinear machine-learning tools have received attention in regional frequency analysis (RFA) applications especially for estimation purposes. In this paper, the aim is to study nonlinearity-related aspects in the RFA of hydrological variables using statistical and machine-learning approaches. To this end, a variety of combinations of linear and nonlinear approaches are considered in the main RFA steps (delineation and estimation). Artificial neural networks (ANNs) and generalized additive models (GAMs) are combined to a nonlinear ANN-based canonical correlation analysis (NLCCA) procedure to ensure an appropriate nonlinear modeling of the complex processes involved. A comparison is carried out between classical linear combinations (CCAs combined with linear regression (LR) model), semilinear combinations (e.g., NLCCA with LR) and fully nonlinear combinations (e.g., NLCCA with GAM). The considered models are applied to three different data sets located in North America. Results indicate that fully nonlinear models (in both RFA steps) are the most appropriate since they provide best performances and a more realistic description of the physical processes involved, even though they are relatively more complex than linear ones. On the other hand, semilinear models which consider nonlinearity either in the delineation or estimation steps showed little improvement over linear models. The linear approaches provided the lowest performances.

  17. Bi-directional memory-based dialog translation The KEMDT approach

    CERN Document Server

    Lee, G; Lee, J H; Lee, Geunbae; Jung, Hanmin; Lee, Jong-Hyeok

    1995-01-01

    A bi-directional Korean/English dialog translation system is designed and implemented using the memory-based translation technique. The system KEMDT (Korean/English Memory-based Dialog Translation system) can perform Korean to English, and English to Korean translation using unified memory network and extended marker passing algorithm. We resolve the word order variation and frequent word omission problems in Korean by classifying the concept sequence element in four different types and extending the marker- passing-based-translation algorithm. Unlike the previous memory-based translation systems, the KEMDT system develops the bilingual memory network and the unified bi-directional marker passing translation algorithm. For efficient language specific processing, we separate the morphological processors from the memory-based translator. The KEMDT technology provides a hierarchical memory network and an efficient marker-based control for the recent example-based MT paradigm.

  18. Culture of human limbal epithelial stem cells on tenon's fibroblast feeder-layers: a translational approach.

    Science.gov (United States)

    Scafetta, Gaia; Siciliano, Camilla; Frati, Giacomo; De Falco, Elena

    2015-01-01

    The coculture technique is the standard method to expand ex vivo limbal stem cells (LSCs) by using inactivated embryonic murine feeder layers (3T3). Although alternative techniques such as amniotic membranes or scaffolds have been proposed, feeder layers are still considered to be the best method, due to their ability to preserve some critical properties of LSCs such as cell growth and viability, stemness phenotype, and clonogenic potential. Furthermore, clinical applications of LSCs cultured on 3T3 have taken place. Nevertheless, for an improved Good Manufacturing Practice (GMP) compliance, the use of human feeder-layers as well as a fine standardization of the process is strictly encouraged. Here, we describe a translational approach in accordance with GMP regulations to culture LSCs onto human Tenon's fibroblasts (TFs). In this chapter, based on our experience we identify and analyze issues that often are encountered by researchers and discuss solutions to common problems.

  19. Stakeholder Meeting: Integrated Knowledge Translation Approach to Address the Caregiver Support Gap.

    Science.gov (United States)

    Holroyd-Leduc, Jayna M; McMillan, Jacqueline; Jette, Nathalie; Brémault-Phillips, Suzette C; Duggleby, Wendy; Hanson, Heather M; Parmar, Jasneet

    2017-03-01

    Family caregivers are an integral and increasingly overburdened part of the health care system. There is a gap between what research evidence shows is beneficial to caregivers and what is actually provided. Using an integrated knowledge translation approach, a stakeholder meeting was held among researchers, family caregivers, caregiver associations, clinicians, health care administrators, and policy makers. The objectives of the meeting were to review current research evidence and conduct multi-stakeholder dialogue on the potential gaps, facilitators, and barriers to the provision of caregiver supports. A two-day meeting was attended by 123 individuals. Three target populations of family caregivers were identified for discussion: caregivers of seniors with dementia, caregivers in end-of-life care, and caregivers of frail seniors with complex health needs. The results of this meeting can and are being used to inform the development of implementation research endeavours and policies targeted at providing evidence-informed caregiver supports.

  20. Translating cognitive neuroscience to the driver's operational environment: a neuroergonomic approach.

    Science.gov (United States)

    Lees, Monica N; Cosman, Joshua D; Lee, John D; Fricke, Nicola; Rizzo, Matthew

    2010-01-01

    Neuroergonomics provides a multidisciplinary translational approach that merges elements of neuroscience, human factors, cognitive psychology, and ergonomics to study brain structure and function in everyday environments. Driving safety, particularly that of older drivers with cognitive impairments, is a fruitful application domain for neuroergonomics. Driving makes demands on multiple cognitive processes that are often studied in isolation and so presents a useful challenge in generalizing findings from controlled laboratory tasks to predict safety outcomes. Neurology and the cognitive sciences help explain the mechanisms of cognitive breakdowns that undermine driving safety. Ergonomics complements this explanation with the tools for systematically exploring the various layers of complexity that define the activity of driving. A variety of tools, such as part task simulators, driving simulators, and instrumented vehicles, provide a window into cognition in the natural settings needed to assess the generalizability of laboratory findings and can provide an array of potential interventions to increase driving safety.

  1. Translating cognitive neuroscience to the driver’s operational environment: a neuroergonomics approach

    Science.gov (United States)

    Lees, Monica N.; Cosman, Joshua D.; Lee, John D.; Rizzo, Matthew; Fricke, Nicola

    2012-01-01

    Neuroergonomics provides a multidisciplinary translational approach that merges elements of neuroscience, human factors, cognitive psychology, and ergonomics to study brain structure and function in everyday environments. Driving safety, particularly that of older drivers with cognitive impairments, is a fruitful application domain for neuroergonomics. Driving makes demands on multiple cognitive processes that are often studied in isolation and so presents a useful challenge in generalizing findings from controlled laboratory tasks to predict safety outcomes. Neurology and the cognitive sciences help explain the mechanisms of cognitive breakdowns that undermine driving safety. Ergonomics complements this explanation with the tools for systematically exploring the various layers of complexity that define the activity of driving. A variety of tools, such as part task simulators, driving simulators, and instrumented vehicles provide a window into cognition in the natural settings needed to assess the generalizability of laboratory findings and can provide an array of potential interventions to increase safety. PMID:21291157

  2. 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.

  3. Enhancing Intercultural Communication and Understanding: Team Translation Project as a Student Engagement Learning Approach

    Science.gov (United States)

    Yang, Ping

    2015-01-01

    This paper reflects on a team translation project on Aboriginal culture designed to enhance university students' intercultural communication competence and understanding through engaging in an interactive team translation project funded by the Australia-China Council. A selected group of Chinese speaking translation students participated in the…

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

    Science.gov (United States)

    Kong, Young Bae; Lee, Eun Je; Hur, Min Goo; Park, Jeong Hoon; Park, Yong Dae; Yang, Seung Dae

    2016-10-01

    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.

  5. An integrated two-stage support vector machine approach to forecast inundation maps during typhoons

    Science.gov (United States)

    Jhong, Bing-Chen; Wang, Jhih-Huang; Lin, Gwo-Fong

    2017-04-01

    During typhoons, accurate forecasts of hourly inundation depths are essential for inundation warning and mitigation. Due to the lack of observed data of inundation maps, sufficient observed data are not available for developing inundation forecasting models. In this paper, the inundation depths, which are simulated and validated by a physically based two-dimensional model (FLO-2D), are used as a database for inundation forecasting. A two-stage inundation forecasting approach based on Support Vector Machine (SVM) is proposed to yield 1- to 6-h lead-time inundation maps during typhoons. In the first stage (point forecasting), the proposed approach not only considers the rainfall intensity and inundation depth as model input but also simultaneously considers cumulative rainfall and forecasted inundation depths. In the second stage (spatial expansion), the geographic information of inundation grids and the inundation forecasts of reference points are used to yield inundation maps. The results clearly indicate that the proposed approach effectively improves the forecasting performance and decreases the negative impact of increasing forecast lead time. Moreover, the proposed approach is capable of providing accurate inundation maps for 1- to 6-h lead times. In conclusion, the proposed two-stage forecasting approach is suitable and useful for improving the inundation forecasting during typhoons, especially for long lead times.

  6. Multi-targeted approach to cancer treatment: an international translational cancer research symposium.

    Science.gov (United States)

    Mehta, Kapil; Gandhi, Varsha; Pathak, Sen; Aggarwal, Bharat B; Grover, Rajesh K

    2014-11-01

    Whether it is chronic myeloid leukemia, ALK-expressing malignancies, or HER2-positive breast cancer, targeted-therapies for treatment of human cancers have shown great promise. However, as they hit a single molecule expressed in neoplastic cells, their use is frequently associated with development of resistance. In cancer cells many signaling pathways operate in parallel, hence the idea of multi-targeted therapy is prevailing. The Society of Translational Cancer Research held its biennial meeting in the capital city of India, Delhi from February 6th through 9th, 2014 to discuss 'Multi-targeted Approach to Treatment of Cancer'. Over 200 scientists, clinicians, trainees, and industry representatives from different countries gathered in Vigyan Bhavan, the hotspot of Delhi for four days to talk and discuss on a variety of topics related to multi-targeted therapeutic approaches. Talks were presented by leaders in the cancer research field from various countries. It became clear from this conference that coupling multiple targeted-agents or using an agent that hits an individual target in several independent locations in the disease-causing pathway(s) may be the best approach to treat different cancers.

  7. Mixed Integer Linear Programming based machine learning approach identifies regulators of telomerase in yeast.

    Science.gov (United States)

    Poos, Alexandra M; Maicher, André; Dieckmann, Anna K; Oswald, Marcus; Eils, Roland; Kupiec, Martin; Luke, Brian; König, Rainer

    2016-06-02

    Understanding telomere length maintenance mechanisms is central in cancer biology as their dysregulation is one of the hallmarks for immortalization of cancer cells. Important for this well-balanced control is the transcriptional regulation of the telomerase genes. We integrated Mixed Integer Linear Programming models into a comparative machine learning based approach to identify regulatory interactions that best explain the discrepancy of telomerase transcript levels in yeast mutants with deleted regulators showing aberrant telomere length, when compared to mutants with normal telomere length. We uncover novel regulators of telomerase expression, several of which affect histone levels or modifications. In particular, our results point to the transcription factors Sum1, Hst1 and Srb2 as being important for the regulation of EST1 transcription, and we validated the effect of Sum1 experimentally. We compiled our machine learning method leading to a user friendly package for R which can straightforwardly be applied to similar problems integrating gene regulator binding information and expression profiles of samples of e.g. different phenotypes, diseases or treatments.

  8. Mixed Integer Linear Programming based machine learning approach identifies regulators of telomerase in yeast

    Science.gov (United States)

    Poos, Alexandra M.; Maicher, André; Dieckmann, Anna K.; Oswald, Marcus; Eils, Roland; Kupiec, Martin; Luke, Brian; König, Rainer

    2016-01-01

    Understanding telomere length maintenance mechanisms is central in cancer biology as their dysregulation is one of the hallmarks for immortalization of cancer cells. Important for this well-balanced control is the transcriptional regulation of the telomerase genes. We integrated Mixed Integer Linear Programming models into a comparative machine learning based approach to identify regulatory interactions that best explain the discrepancy of telomerase transcript levels in yeast mutants with deleted regulators showing aberrant telomere length, when compared to mutants with normal telomere length. We uncover novel regulators of telomerase expression, several of which affect histone levels or modifications. In particular, our results point to the transcription factors Sum1, Hst1 and Srb2 as being important for the regulation of EST1 transcription, and we validated the effect of Sum1 experimentally. We compiled our machine learning method leading to a user friendly package for R which can straightforwardly be applied to similar problems integrating gene regulator binding information and expression profiles of samples of e.g. different phenotypes, diseases or treatments. PMID:26908654

  9. A Machine Learning Approach for Dynamical Mass Measurements of Galaxy Clusters

    CERN Document Server

    Ntampaka, Michelle; Sutherland, Dougal J; Battaglia, Nicholas; Poczos, Barnabas; Schneider, Jeff

    2014-01-01

    We present a modern machine learning approach for cluster dynamical mass measurements that is a factor of two improvement over using a conventional scaling relation. Different methods are tested against a mock cluster catalog constructed using halos with mass >= 10^14 Msolar/h from Multidark's publicly-available N-body MDPL halo catalog. In the conventional method, we use a standard M(sigma_v) power law scaling relation to infer cluster mass, M, from line-of-sight (LOS) galaxy velocity dispersion, sigma_v. The resulting fractional mass error distribution is broad, with width = 0.86 (68% scatter), and has extended high-error tails. The standard scaling relation can be simply enhanced by including higher-order moments of the LOS velocity distribution. Applying the kurtosis as a linear correction term to log(sigma_v) reduces the width of the error distribution to 0.74 (15% improvement). Machine learning can be used to take full advantage of all the information in the velocity distribution. We employ the Support ...

  10. Physics-informed machine learning approach for reconstructing Reynolds stress modeling discrepancies based on DNS data

    Science.gov (United States)

    Wang, Jian-Xun; Wu, Jin-Long; Xiao, Heng

    2017-03-01

    Turbulence modeling is a critical component in numerical simulations of industrial flows based on Reynolds-averaged Navier-Stokes (RANS) equations. However, after decades of efforts in the turbulence modeling community, universally applicable RANS models with predictive capabilities are still lacking. Large discrepancies in the RANS-modeled Reynolds stresses are the main source that limits the predictive accuracy of RANS models. Identifying these discrepancies is of significance to possibly improve the RANS modeling. In this work, we propose a data-driven, physics-informed machine learning approach for reconstructing discrepancies in RANS modeled Reynolds stresses. The discrepancies are formulated as functions of the mean flow features. By using a modern machine learning technique based on random forests, the discrepancy functions are trained by existing direct numerical simulation (DNS) databases and then used to predict Reynolds stress discrepancies in different flows where data are not available. The proposed method is evaluated by two classes of flows: (1) fully developed turbulent flows in a square duct at various Reynolds numbers and (2) flows with massive separations. In separated flows, two training flow scenarios of increasing difficulties are considered: (1) the flow in the same periodic hills geometry yet at a lower Reynolds number and (2) the flow in a different hill geometry with a similar recirculation zone. Excellent predictive performances were observed in both scenarios, demonstrating the merits of the proposed method.

  11. A Naive Bayes machine learning approach to risk prediction using censored, time-to-event data.

    Science.gov (United States)

    Wolfson, Julian; Bandyopadhyay, Sunayan; Elidrisi, Mohamed; Vazquez-Benitez, Gabriela; Vock, David M; Musgrove, Donald; Adomavicius, Gediminas; Johnson, Paul E; O'Connor, Patrick J

    2015-09-20

    Predicting an individual's risk of experiencing a future clinical outcome is a statistical task with important consequences for both practicing clinicians and public health experts. Modern observational databases such as electronic health records provide an alternative to the longitudinal cohort studies traditionally used to construct risk models, bringing with them both opportunities and challenges. Large sample sizes and detailed covariate histories enable the use of sophisticated machine learning techniques to uncover complex associations and interactions, but observational databases are often 'messy', with high levels of missing data and incomplete patient follow-up. In this paper, we propose an adaptation of the well-known Naive Bayes machine learning approach to time-to-event outcomes subject to censoring. We compare the predictive performance of our method with the Cox proportional hazards model which is commonly used for risk prediction in healthcare populations, and illustrate its application to prediction of cardiovascular risk using an electronic health record dataset from a large Midwest integrated healthcare system.

  12. A New Multivariate Approach for Prognostics Based on Extreme Learning Machine and Fuzzy Clustering.

    Science.gov (United States)

    Javed, Kamran; Gouriveau, Rafael; Zerhouni, Noureddine

    2015-12-01

    Prognostics is a core process of prognostics and health management (PHM) discipline, that estimates the remaining useful life (RUL) of a degrading machinery to optimize its service delivery potential. However, machinery operates in a dynamic environment and the acquired condition monitoring data are usually noisy and subject to a high level of uncertainty/unpredictability, which complicates prognostics. The complexity further increases, when there is absence of prior knowledge about ground truth (or failure definition). For such issues, data-driven prognostics can be a valuable solution without deep understanding of system physics. This paper contributes a new data-driven prognostics approach namely, an "enhanced multivariate degradation modeling," which enables modeling degrading states of machinery without assuming a homogeneous pattern. In brief, a predictability scheme is introduced to reduce the dimensionality of the data. Following that, the proposed prognostics model is achieved by integrating two new algorithms namely, the summation wavelet-extreme learning machine and subtractive-maximum entropy fuzzy clustering to show evolution of machine degradation by simultaneous predictions and discrete state estimation. The prognostics model is equipped with a dynamic failure threshold assignment procedure to estimate RUL in a realistic manner. To validate the proposition, a case study is performed on turbofan engines data from PHM challenge 2008 (NASA), and results are compared with recent publications.

  13. Global assessment of soil organic carbon stocks and spatial distribution of histosols: the Machine Learning approach

    Science.gov (United States)

    Hengl, Tomislav

    2016-04-01

    Preliminary results of predicting distribution of soil organic soils (Histosols) and soil organic carbon stock (in tonnes per ha) using global compilations of soil profiles (about 150,000 points) and covariates at 250 m spatial resolution (about 150 covariates; mainly MODIS seasonal land products, SRTM DEM derivatives, climatic images, lithological and land cover and landform maps) are presented. We focus on using a data-driven approach i.e. Machine Learning techniques that often require no knowledge about the distribution of the target variable or knowledge about the possible relationships. Other advantages of using machine learning are (DOI: 10.1371/journal.pone.0125814): All rules required to produce outputs are formalized. The whole procedure is documented (the statistical model and associated computer script), enabling reproducible research. Predicted surfaces can make use of various information sources and can be optimized relative to all available quantitative point and covariate data. There is more flexibility in terms of the spatial extent, resolution and support of requested maps. Automated mapping is also more cost-effective: once the system is operational, maintenance and production of updates are an order of magnitude faster and cheaper. Consequently, prediction maps can be updated and improved at shorter and shorter time intervals. Some disadvantages of automated soil mapping based on Machine Learning are: Models are data-driven and any serious blunders or artifacts in the input data can propagate to order-of-magnitude larger errors than in the case of expert-based systems. Fitting machine learning models is at the order of magnitude computationally more demanding. Computing effort can be even tens of thousands higher than if e.g. linear geostatistics is used. Many machine learning models are fairly complex often abstract and any interpretation of such models is not trivial and require special multidimensional / multivariable plotting and data mining

  14. A support vector machine approach to detect financial statement fraud in South Africa: A first look

    CSIR Research Space (South Africa)

    Moepya, SO

    2014-04-01

    Full Text Available Auditors face the difficult task of detecting companies that issue manipulated financial statements. In recent years, machine learning methods have provided a feasible solution to this task. This study develops support vector machine (SVM) models...

  15. 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...

  16. Research on joint Chinese-Japanese word segmentation for phrase-based statistical machine translation%面向短语统计机器翻译的汉日联合分词研究

    Institute of Scientific and Technical Information of China (English)

    吴培昊; 徐金安; 张玉洁

    2015-01-01

    Unknown words and word segmentation granularity are two main problems for Chinese-Japanese machine translation. Word segmentation is the first important step for Chinese and Japanese natural language processing. As Chi-nese and Japanese word segmentation is processed with different tagging system and semantic performance, the granularity of word segmentation results should be readjusted to improve the performance of Statistical Machine Translation(SMT). This paper proposes an approach to adjust the word segmentation granularity for improving the performance of SMT, which combines Hanzi-Kanji comparison table and Japanese-Chinese dictionary. Experimental results express that the pro-posed method could adjust the granularity between Chinese and Japanese effectively and improve the performance of SMT. This paper analyses the experimental results and discusses the effect of joint Chinese-Japanese word segmentation granularity for phrase-based SMT.%未登录词与分词粒度是汉日日汉机器翻译研究的两个主要问题。与英语等西方语言不同,汉语与日语词语间不存在空格,分词为汉日双语处理的重要工作。由于词性标注体系、文法及语义表现上的差异,分词结果的粒度需要进一步调整,以改善统计机器翻译系统的性能。提出了面向统计机器翻译的基于汉日汉字对照表及日汉词典信息的汉语与日语的分词粒度调整方法。实验结果表明,该方法能有效地调节源语言和目标语言端的分词粒度,提高统计机器翻译系统的性能。通过对比实验结果,分析探讨分词粒度对汉日双语统计系统性能的影响。

  17. 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

    2017-07-28

    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.

  18. An Approach to the Classification of Cutting Vibration on Machine Tools

    OpenAIRE

    Jeng-Fung Chen; Shih-Kuei Lo; Quang Hung Do

    2016-01-01

    Predictions of cutting vibrations are necessary for improving the operational efficiency, product quality, and safety in the machining process, since the vibration is the main factor for resulting in machine faults. “Cutting vibration” may be caused by setting incorrect parameters before machining is commenced and may affect the precision of the machined work piece. This raises the need to have an effective model that can be used to predict cutting vibrations. In this study, an artificial neu...

  19. 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.

  20. A hybrid least squares support vector machines and GMDH approach for river flow forecasting

    Science.gov (United States)

    Samsudin, R.; Saad, P.; Shabri, A.

    2010-06-01

    This paper proposes a novel hybrid forecasting model, which combines the group method of data handling (GMDH) and the least squares support vector machine (LSSVM), known as GLSSVM. The GMDH is used to determine the useful input variables for LSSVM model and the LSSVM model which works as time series forecasting. In this study the application of GLSSVM for monthly river flow forecasting of Selangor and Bernam River are investigated. The results of the proposed GLSSVM approach are compared with the conventional artificial neural network (ANN) models, Autoregressive Integrated Moving Average (ARIMA) model, GMDH and LSSVM models using the long term observations of monthly river flow discharge. The standard statistical, the root mean square error (RMSE) and coefficient of correlation (R) are employed to evaluate the performance of various models developed. Experiment result indicates that the hybrid model was powerful tools to model discharge time series and can be applied successfully in complex hydrological modeling.

  1. Exploring the spectroscopic diversity of type Ia supernovae with DRACULA: a machine learning approach

    CERN Document Server

    Sasdelli, Michele; Vilalta, R; Aguena, M; Busti, V C; Camacho, H; Trindade, A M M; Gieseke, F; de Souza, R S; Fantaye, Y T; Mazzali, P A

    2015-01-01

    The existence of multiple subclasses of type Ia supernovae (SNeIa) has been the subject of great debate in the last decade. One major challenge inevitably met when trying to infer the existence of one or more subclasses is the time consuming, and subjective, process of subclass definition. In this work, we show how machine learning tools facilitate the automatic discovery of sub-populations of SNIa; to that end we introduce the DRACULA Python package (Dimensionality Reduction And Clustering for Unsupervised Learning in Astronomy). Our approach is divided in three steps: (i) Transfer Learning, which takes advantage of all available spectra (even those without an epoch estimate) as an information source, (ii) dimensionality reduction through Deep Learning and (iii) unsupervised learning (clustering) using K-Means. Results match a previously suggested classification scheme, showing that the proposed method is able to grasp the main spectral features behind the definition of such subclasses. Moreover, our methodo...

  2. A MACHINE LEARNING APPROACH TO ANOMALY-BASED DETECTION ON ANDROID PLATFORMS

    Directory of Open Access Journals (Sweden)

    Joshua Abah

    2015-11-01

    Full Text Available The emergence of mobile platforms with increased storage and computing capabilities and the pervasive use of these platforms for sensitive applications such as online banking, e-commerce and the storage of sensitive information on these mobile devices have led to increasing danger associated with malware targeted at these devices. Detecting such malware presents inimitable challenges as signature-based detection techniques available today are becoming inefficient in detecting new and unknown malware. In this research, a machine learning approach for the detection of malware on Android platforms is presented. The detection system monitors and extracts features from the applications while in execution and uses them to perform in-device detection using a trained K-Nearest Neighbour classifier. Results shows high performance in the detection rate of the classifier with accuracy of 93.75%, low error rate of 6.25% and low false positive rate with ability of detecting real Android malware.

  3. Using a symbiotic man/machine approach to evaluating visual clinical research data.

    Science.gov (United States)

    Long, J M; Irani, E A; Hunter, D W; Slagle, J R; Matts, J P; Castaneda, W; Pearce, M; Bissett, J; Sawin, H; Edmiston, A

    1988-10-01

    Some candidate medical expert system applications have a significant visual component. Knowledge engineers usually dismiss such task domains as potential expert systems applications. Our success in developing ESCA, a system for evaluating serial coronary angiograms, shows that such task domains should not be dismissed so quickly. We used a symbiotic approach between man and machine, where technologists provide the visual skills with an expert system imitating the conceptual skills of the expert, to produce a partially automated system that is more consistent and cost effective than one that is fully manual. The agreement between the system's conclusions and that of a panel of experts is good. The expert system actually has a slightly higher agreement rate with the expert panel than the agreement rate between two expert panel teams evaluating the same film pair.

  4. Functional renormalization group approach to electronic structure calculations for systems without translational symmetry

    Science.gov (United States)

    Seiler, Christian; Evers, Ferdinand

    2016-10-01

    A formalism for electronic-structure calculations is presented that is based on the functional renormalization group (FRG). The traditional FRG has been formulated for systems that exhibit a translational symmetry with an associated Fermi surface, which can provide the organization principle for the renormalization group (RG) procedure. We here advance an alternative formulation, where the RG flow is organized in the energy-domain rather than in k space. This has the advantage that it can also be applied to inhomogeneous matter lacking a band structure, such as disordered metals or molecules. The energy-domain FRG (ɛ FRG) presented here accounts for Fermi-liquid corrections to quasiparticle energies and particle-hole excitations. It goes beyond the state of the art G W -BSE , because in ɛ FRG the Bethe-Salpeter equation (BSE) is solved in a self-consistent manner. An efficient implementation of the approach that has been tested against exact diagonalization calculations and calculations based on the density matrix renormalization group is presented. Similar to the conventional FRG, also the ɛ FRG is able to signalize the vicinity of an instability of the Fermi-liquid fixed point via runaway flow of the corresponding interaction vertex. Embarking upon this fact, in an application of ɛ FRG to the spinless disordered Hubbard model we calculate its phase boundary in the plane spanned by the interaction and disorder strength. Finally, an extension of the approach to finite temperatures and spin S =1 /2 is also given.

  5. 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.

  6. 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

  7. Separating depressive comorbidity from panic disorder: A combined functional magnetic resonance imaging and machine learning approach.

    Science.gov (United States)

    Lueken, Ulrike; Straube, Benjamin; Yang, Yunbo; Hahn, Tim; Beesdo-Baum, Katja; Wittchen, Hans-Ulrich; Konrad, Carsten; Ströhle, Andreas; Wittmann, André; Gerlach, Alexander L; Pfleiderer, Bettina; Arolt, Volker; Kircher, Tilo

    2015-09-15

    Depression is frequent in panic disorder (PD); yet, little is known about its influence on the neural substrates of PD. Difficulties in fear inhibition during safety signal processing have been reported as a pathophysiological feature of PD that is attenuated by depression. We investigated the impact of comorbid depression in PD with agoraphobia (AG) on the neural correlates of fear conditioning and the potential of machine learning to predict comorbidity status on the individual patient level based on neural characteristics. Fifty-nine PD/AG patients including 26 (44%) with a comorbid depressive disorder (PD/AG+DEP) underwent functional magnetic resonance imaging (fMRI). Comorbidity status was predicted using a random undersampling tree ensemble in a leave-one-out cross-validation framework. PD/AG-DEP patients showed altered neural activation during safety signal processing, while +DEP patients exhibited generally decreased dorsolateral prefrontal and insular activation. Comorbidity status was correctly predicted in 79% of patients (sensitivity: 73%; specificity: 85%) based on brain activation during fear conditioning (corrected for potential confounders: accuracy: 73%; sensitivity: 77%; specificity: 70%). No primary depressed patients were available; only medication-free patients were included. Major depression and dysthymia were collapsed (power considerations). Neurofunctional activation during safety signal processing differed between patients with or without comorbid depression, a finding which may explain heterogeneous results across previous studies. These findings demonstrate the relevance of comorbidity when investigating neurofunctional substrates of anxiety disorders. Predicting individual comorbidity status may translate neurofunctional data into clinically relevant information which might aid in planning individualized treatment. The study was registered with the ISRCTN80046034. Copyright © 2015 Elsevier B.V. All rights reserved.

  8. Study on Approach for Computer-Aided Design and Machining of General Cylindrical Cam Using Relative Velocity and Inverse Kinematics

    Institute of Scientific and Technical Information of China (English)

    Se-Hwan; Park; Byong-Kook; Gu; Joong-Ho; Shin; Geun-Jong; Yoo

    2002-01-01

    Cylindrical Cam Mechanism which is one of the best eq uipments to accomplish an accurate motion transmission is widely used in the fie lds of industries, such as machine tool exchangers, textile machinery and automa tic transfer equipments. This paper proposes a new approach for the shape design and manufacturing of the cylindrical cam. The design approach uses the relative velocity concept and the manufacturing approach uses the inverse kinematics concept. For the shape desig n, the contact points betw...

  9. System-based participatory research in health care: an approach for sustainable translational research and quality improvement.

    Science.gov (United States)

    Schmittdiel, Julie A; Grumbach, Kevin; Selby, Joe V

    2010-01-01

    Translational research seeks to improve health care by promoting action and change in real-world health care settings. Although translational research advocates a break from the traditional researcher-initiated approach to science, strategies to successfully engage clinicians and leaders of health care delivery organizations in research are still under development. We propose that applying the principles of community-based participatory research in a way that considers delivery systems-including their leaders, clinicians, and staff-as a focal community can enhance the ability of translational research to improve health care. Applying participatory research methods, such as engaging in collaborative partnerships, building on existing community strengths, investing in long-term relationships, and engaging in research as a cyclical, iterative process, can be a successful approach to sustainable quality improvement at the systems level.

  10. An Approach to Realizing Process Control for Underground Mining Operations of Mobile Machines.

    Directory of Open Access Journals (Sweden)

    Zhen Song

    Full Text Available The excavation and production in underground mines are complicated processes which consist of many different operations. The process of underground mining is considerably constrained by the geometry and geology of the mine. The various mining operations are normally performed in series at each working face. The delay of a single operation will lead to a domino effect, thus delay the starting time for the next process and the completion time of the entire process. This paper presents a new approach to the process control for underground mining operations, e.g. drilling, bolting, mucking. This approach can estimate the working time and its probability for each operation more efficiently and objectively by improving the existing PERT (Program Evaluation and Review Technique and CPM (Critical Path Method. If the delay of the critical operation (which is on a critical path inevitably affects the productivity of mined ore, the approach can rapidly assign mucking machines new jobs to increase this amount at a maximum level by using a new mucking algorithm under external constraints.

  11. A Novel Artificial Bee Colony Approach of Live Virtual Machine Migration Policy Using Bayes Theorem

    Directory of Open Access Journals (Sweden)

    Gaochao Xu

    2013-01-01

    Full Text Available Green cloud data center has become a research hotspot of virtualized cloud computing architecture. Since live virtual machine (VM migration technology is widely used and studied in cloud computing, we have focused on the VM placement selection of live migration for power saving. We present a novel heuristic approach which is called PS-ABC. Its algorithm includes two parts. One is that it combines the artificial bee colony (ABC idea with the uniform random initialization idea, the binary search idea, and Boltzmann selection policy to achieve an improved ABC-based approach with better global exploration’s ability and local exploitation’s ability. The other one is that it uses the Bayes theorem to further optimize the improved ABC-based process to faster get the final optimal solution. As a result, the whole approach achieves a longer-term efficient optimization for power saving. The experimental results demonstrate that PS-ABC evidently reduces the total incremental power consumption and better protects the performance of VM running and migrating compared with the existing research. It makes the result of live VM migration more high-effective and meaningful.

  12. German Functionalist Approaches to the Chinese-English Translation of Commentaries in Ningxia Museum

    Institute of Scientific and Technical Information of China (English)

    任宁

    2013-01-01

      Museum commentary emerges as the times demand. It falls into the category of publicity text. Not only does museum commentary play an important role in transferring information, but also in disseminating culture. Meanwhile, museum commentary translation is a prominent part of culture, carrying the task of cultural communication between China and foreign countries. Howev⁃er, scholars do not pay enough attention to museum commentary translation. Under the guidance of German functionalism, translators could pay much attention to the function of the museum commentary and adopt flexible translation strategies to fulfill it.

  13. A semi-analytical approach for stiffness modeling of PKM by considering compliance of machine frame with complex geometry

    Institute of Scientific and Technical Information of China (English)

    WANG YouYu; HUANG Tian; ZHAO XueMan; MEI JiangPing; Derek G CHETWYND

    2008-01-01

    Stiffness modeling is one of the most significant issues in the design of parallel kinematic machine (PKM).This paper presents a semi-analytical approach that enables the stiffness of PKM with complex machine frame geometry to be estimated effectively.This approach can be implemented by three steps:(i) decomposition of the entire system into two sub-systems associated with the parallel mechanism and the machine frame respectively;(ii) stiffness modeling of each sub-system using the analytical approach and the finite element analysis;and (iii) generation of the stiffness model of the entire system by means of linear superposition.In the modeling process of each sub-system,the virtual work princi-ple and overall deflection Jacobian are employed with special attention to the bending rigidity of the constrained passive limb and the interface stiffness of the machine frame.The stiffness distribution of a 5-DOF hybrid robot named TriVariant-B is investigated as an example to illustrate the effectivaness of this approach.The contributions of component rigidities to that of the system are evaluated using global indices.It shows that the results achieved by this approach have a good match to those obtained through finite element analysis and experiments.

  14. Developing a prevention synthesis and translation system to promote science-based approaches to teen pregnancy, HIV and STI prevention.

    Science.gov (United States)

    Lewis, Kelly M; Lesesne, Catherine A; Zahniser, S Christine; Wilson, Mary Martha; Desiderio, Gina; Wandersman, Abraham; Green, Diane C

    2012-12-01

    The Interactive Systems Framework for Dissemination and Implementation (ISF) is a multi-system framework that can guide research-to-practice efforts by building and supporting the work of three interacting systems: the Prevention Delivery, Support, and Synthesis and Translation Systems. The Synthesis and Translation system is vital to bridging science and practice, yet how to develop it and train support system partners to use it is under-researched. This article bridges this gap by offering a case example of the planning, development, and use of a synthesis and translation product called Promoting Science-based Approaches to Teen Pregnancy Prevention using Getting To Outcomes. The case presented documents the process used for developing the synthesis and translation product, reports on efforts to engage the Prevention Support system to use the product, and how we approached building interaction between the Synthesis and Translation System and the Support System partners. Practice-oriented evaluation data are also presented. Implications for practice, policy and research are discussed.

  15. Icing detection from Communication, Ocean and Meteorological Satellite and Himawari-8 data using machine learning approaches

    Science.gov (United States)

    Sim, S.; Park, H.; Im, J.; Park, S.

    2016-12-01

    Aircraft icing is a hazardous phenomenon which has potential to cause fatalities and socioeconomic losses. It is caused by super-cooled droplets (SCDs) colliding on the surface of aircraft frame when an aircraft flies through SCD rich clouds. When icing occurs, the aerodynamic balance of the aircraft is disturbed, resulting in a potential problem in aircraft operation. Thus, identification of potential icing clouds is crucial for aviation. Satellite remote sensing data such as Geostationary Operational Environmental Satellite (GOES) series have been widely used to detect potential icing clouds. An icing detection algorithm, operationally used in the US, consists of several thresholds of cloud optical depth, effective radius, and liquid water path based on the physical properties of icing. On the other hand, there is no operational icing detection algorithm in Asia, although there are several geostationary meteorological satellite sensors. In this study, we proposed machine learning-based models to detect icing over East Asia focusing on the Korean Peninsula using two geostationary satellite sensors—Meteorological Imager (MI) onboard Communication, Ocean and Meteorological Satellite (COMS) and Advanced Himawari Imager (AHI) onboard Himawari-8. While COMS MI provides data at 5 channels, Himawari-8 AHI has advanced capability of data collection, providing data at 16 channels. Instead of simple thresholding approaches used in the literature, we adopted two machine learning algorithms—decision trees (DT) and random forest (RF) to develop icing detection models based on Pilot REPorts (PIREPs) as reference data. Results show that the COMS icing detection model by RF produced a detection rate of 88.67% and a false alarm rate of 14.42%, which were improved when compared with the result of the direct application of the GOES algorithm to the COMS MI data (a detection rate of 20.83% and a false alarm rate of 25.44%). Although much higher accuracy (a detection rate > 95

  16. Machine Transliteration

    CERN Document Server

    Knight, K; Knight, Kevin; Graehl, Jonathan

    1997-01-01

    It is challenging to translate names and technical terms across languages with different alphabets and sound inventories. These items are commonly transliterated, i.e., replaced with approximate phonetic equivalents. For example, "computer" in English comes out as "konpyuutaa" in Japanese. Translating such items from Japanese back to English is even more challenging, and of practical interest, as transliterated items make up the bulk of text phrases not found in bilingual dictionaries. We describe and evaluate a method for performing backwards transliterations by machine. This method uses a generative model, incorporating several distinct stages in the transliteration process.

  17. Disrupted white matter connectivity underlying developmental dyslexia: A machine learning approach.

    Science.gov (United States)

    Cui, Zaixu; Xia, Zhichao; Su, Mengmeng; Shu, Hua; Gong, Gaolang

    2016-04-01

    Developmental dyslexia has been hypothesized to result from multiple causes and exhibit multiple manifestations, implying a distributed multidimensional effect on human brain. The disruption of specific white-matter (WM) tracts/regions has been observed in dyslexic children. However, it remains unknown if developmental dyslexia affects the human brain WM in a multidimensional manner. Being a natural tool for evaluating this hypothesis, the multivariate machine learning approach was applied in this study to compare 28 school-aged dyslexic children with 33 age-matched controls. Structural magnetic resonance imaging (MRI) and diffusion tensor imaging were acquired to extract five multitype WM features at a regional level: white matter volume, fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity. A linear support vector machine (LSVM) classifier achieved an accuracy of 83.61% using these MRI features to distinguish dyslexic children from controls. Notably, the most discriminative features that contributed to the classification were primarily associated with WM regions within the putative reading network/system (e.g., the superior longitudinal fasciculus, inferior fronto-occipital fasciculus, thalamocortical projections, and corpus callosum), the limbic system (e.g., the cingulum and fornix), and the motor system (e.g., the cerebellar peduncle, corona radiata, and corticospinal tract). These results were well replicated using a logistic regression classifier. These findings provided direct evidence supporting a multidimensional effect of developmental dyslexia on WM connectivity of human brain, and highlighted the involvement of WM tracts/regions beyond the well-recognized reading system in dyslexia. Finally, the discriminating results demonstrated a potential of WM neuroimaging features as imaging markers for identifying dyslexic individuals.

  18. Genome-scale identification of Legionella pneumophila effectors using a machine learning approach.

    Directory of Open Access Journals (Sweden)

    David Burstein

    2009-07-01

    Full Text Available A large number of highly pathogenic bacteria utilize secretion systems to translocate effector proteins into host cells. Using these effectors, the bacteria subvert host cell processes during infection. Legionella pneumophila translocates effectors via the Icm/Dot type-IV secretion system and to date, approximately 100 effectors have been identified by various experimental and computational techniques. Effector identification is a critical first step towards the understanding of the pathogenesis system in L. pneumophila as well as in other bacterial pathogens. Here, we formulate the task of effector identification as a classification problem: each L. pneumophila open reading frame (ORF was classified as either effector or not. We computationally defined a set of features that best distinguish effectors from non-effectors. These features cover a wide range of characteristics including taxonomical dispersion, regulatory data, genomic organization, similarity to eukaryotic proteomes and more. Machine learning algorithms utilizing these features were then applied to classify all the ORFs within the L. pneumophila genome. Using this approach we were able to predict and experimentally validate 40 new effectors, reaching a success rate of above 90%. Increasing the number of validated effectors to around 140, we were able to gain novel insights into their characteristics. Effectors were found to have low G+C content, supporting the hypothesis that a large number of effectors originate via horizontal gene transfer, probably from their protozoan host. In addition, effectors were found to cluster in specific genomic regions. Finally, we were able to provide a novel description of the C-terminal translocation signal required for effector translocation by the Icm/Dot secretion system. To conclude, we have discovered 40 novel L. pneumophila effectors, predicted over a hundred additional highly probable effectors, and shown the applicability of machine

  19. A Typological Approach to Translation of English and Chinese Motion Events

    Science.gov (United States)

    Deng, Yu; Chen, Huifang

    2012-01-01

    English and Chinese are satellite-framed languages in which Manner is usually incorporated with Motion in the verb and Path is denoted by the satellite. Based on Talmy's theory of motion event and typology, the research probes into translation of English and Chinese motion events and finds that: (1) Translation of motion events in English and…

  20. A community of practice for knowledge translation trainees: an innovative approach for learning and collaboration.

    Science.gov (United States)

    Urquhart, Robin; Cornelissen, Evelyn; Lal, Shalini; Colquhoun, Heather; Klein, Gail; Richmond, Sarah; Witteman, Holly O

    2013-01-01

    A growing number of researchers and trainees identify knowledge translation (KT) as their field of study or practice. Yet, KT educational and professional development opportunities and established KT networks remain relatively uncommon, making it challenging for trainees to develop the necessary skills, networks, and collaborations to optimally work in this area. The Knowledge Translation Trainee Collaborative is a trainee-initiated and trainee-led community of practice established by junior knowledge translation researchers and practitioners to: examine the diversity of knowledge translation research and practice, build networks with other knowledge translation trainees, and advance the field through knowledge generation activities. In this article, we describe how the collaborative serves as an innovative community of practice for continuing education and professional development in knowledge translation and present a logic model that provides a framework for designing an evaluation of its impact as a community of practice. The expectation is that formal and informal networking will lead to knowledge sharing and knowledge generation opportunities that improve individual members' competencies (eg, combination of skills, abilities, and knowledge) in knowledge translation research and practice and contribute to the development and advancement of the knowledge translation field.

  1. Audiovisual Translation and Assistive Technology: Towards a Universal Design Approach for Online Education

    Science.gov (United States)

    Patiniotaki, Emmanouela

    2016-01-01

    Audiovisual Translation (AVT) and Assistive Technology (AST) are two fields that share common grounds within accessibility-related research, yet they are rarely studied in combination. The reason most often lies in the fact that they have emerged from different disciplines, i.e. Translation Studies and Computer Science, making a possible combined…

  2. A functional renormalization group approach to electronic structure calculations for systems without translational symmetry

    CERN Document Server

    Seiler, Christian

    2016-01-01

    A formalism for electronic-structure calculations is presented that is based on the functional renormalization group (FRG). The traditional FRG has been formulated for systems that exhibit a translational symmetry with an associated Fermi surface, which can provide the organization principle for the renormalization group (RG) procedure. We here advance an alternative formulation, where the RG-flow is organized in the energy-domain rather than in k-space. This has the advantage that it can also be applied to inhomogeneous matter lacking a band-structure, such as disordered metals or molecules. The energy-domain FRG ({\\epsilon}FRG) presented here accounts for Fermi-liquid corrections to quasi-particle energies and particle-hole excitations. It goes beyond the state of the art GW-BSE, because in {\\epsilon}FRG the Bethe-Salpeter equation (BSE) is solved in a self-consistent manner. An efficient implementation of the approach that has been tested against exact diagonalization calculations and calculations based on...

  3. 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 NBSW=NBBI-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 we

  4. A novel approach to predict surface roughness in machining operations using fuzzy set theory

    Directory of Open Access Journals (Sweden)

    Tzu-Liang (Bill Tseng

    2016-01-01

    Full Text Available The increase of consumer needs for quality metal cutting related products with more precise tolerances and better product surface roughness has driven the metal cutting industry to continuously improve quality control of metal cutting processes. In this paper, two different approaches are discussed. First, design of experiments (DOE is used to determine the significant factors and then fuzzy logic approach is presented for the prediction of surface roughness. The data used for the training and checking the fuzzy logic performance is derived from the experiments conducted on a CNC milling machine. In order to obtain better surface roughness, the proper sets of cutting parameters are determined before the process takes place. The factors considered for DOE in the experiment were the depth of cut, feed rate per tooth, cutting speed, tool nose radius, the use of cutting fluid and the three components of the cutting force. Finally the significant factors were used as input factors for fuzzy logic mechanism and surface roughness is predicted with empirical formula developed. Test results show good agreement between the actual process output and the predicted surface roughness.

  5. The brain as a flexible task machine: implications for visual rehabilitation using noninvasive vs. invasive approaches.

    Science.gov (United States)

    Reich, Lior; Maidenbaum, Shachar; Amedi, Amir

    2012-02-01

    The exciting view of our brain as highly flexible task-based and not sensory-based raises the chances for visual rehabilitation, long considered unachievable, given adequate training in teaching the brain how to see. Recent advances in rehabilitation approaches, both noninvasive, like sensory substitution devices (SSDs) which present visual information using sound or touch, and invasive, like visual prosthesis, may potentially be used to achieve this goal, each alone, and most preferably together. Visual impairments and said solutions are being used as a model for answering fundamental questions ranging from basic cognitive neuroscience, showing that several key visual brain areas are actually highly flexible, modality-independent and, as was recently shown, even visual experience-independent task machines, to technological and behavioral developments, allowing blind persons to 'see' using SSDs and other approaches. SSDs can be potentially used as a research tool for assessing the brain's functional organization; as an aid for the blind in daily visual tasks; to visually train the brain prior to invasive procedures, by taking advantage of the 'visual' cortex's flexibility and task specialization even in the absence of vision; and to augment postsurgery functional vision using a unique SSD-prostheses hybrid. Taken together the reviewed results suggest a brighter future for visual neuro-rehabilitation.

  6. CoSpa: A Co-training Approach for Spam Review Identification with Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Wen Zhang

    2016-03-01

    Full Text Available Spam reviews are increasingly appearing on the Internet to promote sales or defame competitors by misleading consumers with deceptive opinions. This paper proposes a co-training approach called CoSpa (Co-training for Spam review identification to identify spam reviews by two views: one is the lexical terms derived from the textual content of the reviews and the other is the PCFG (Probabilistic Context-Free Grammars rules derived from a deep syntax analysis of the reviews. Using SVM (Support Vector Machine as the base classifier, we develop two strategies, CoSpa-C and CoSpa-U, embedded within the CoSpa approach. The CoSpa-C strategy selects unlabeled reviews classified with the largest confidence to augment the training dataset to retrain the classifier. The CoSpa-U strategy randomly selects unlabeled reviews with a uniform distribution of confidence. Experiments on the spam dataset and the deception dataset demonstrate that both the proposed CoSpa algorithms outperform the traditional SVM with lexical terms and PCFG rules in spam review identification. Moreover, the CoSpa-U strategy outperforms the CoSpa-C strategy when we use the absolute value of decision function of SVM as the confidence.

  7. Protocol: developing a conceptual framework of patient mediated knowledge translation, systematic review using a realist approach

    Directory of Open Access Journals (Sweden)

    Wiljer David

    2011-03-01

    Full Text Available 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 interventions was compiled to describe intended purpose, recipients, delivery context, intervention, and outcomes. A realist review will be conducted in consultation with stakeholders from the arthritis and cancer fields to explore how these interventions work, for whom, and in what contexts. To identify patient-mediated KT interventions in these fields, we will search MEDLINE, the Cochrane Library, and EMBASE from 1995 to 2010; scan references of all eligible studies; and examine five years of tables of contents for journals likely to publish quantitative or qualitative studies that focus on developing, implementing, or evaluating patient-mediated KT interventions. Screening and data collection will be performed independently by two individuals. Conclusions The conceptual framework of patient-mediated KT options and outcomes could be used by healthcare providers, managers, educationalists, patient advocates, and policy makers to guide program planning, service delivery, and quality improvement and by us and other researchers to evaluate existing interventions or develop new interventions. By raising awareness of options for involving patients in improving their own care, outcomes based on using a KT approach may lead to greater patient-centred care delivery and improved healthcare outcomes.

  8. 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.

  9. Learning Pulse: a machine learning approach for predicting performance in self-regulated learning using multimodal data

    NARCIS (Netherlands)

    Di Mitri, Daniele; Scheffel, Maren; Drachsler, Hendrik; Börner, Dirk; Ternier, Stefaan; Specht, Marcus

    2017-01-01

    Learning Pulse explores whether using a machine learning approach on multimodal data such as heart rate, step count, weather condition and learning activity can be used to predict learning performance in self-regulated learning settings. An experiment was carried out lasting eight weeks involving Ph

  10. Curriculum Assessment Using Artificial Neural Network and Support Vector Machine Modeling Approaches: A Case Study. IR Applications. Volume 29

    Science.gov (United States)

    Chen, Chau-Kuang

    2010-01-01

    Artificial Neural Network (ANN) and Support Vector Machine (SVM) approaches have been on the cutting edge of science and technology for pattern recognition and data classification. In the ANN model, classification accuracy can be achieved by using the feed-forward of inputs, back-propagation of errors, and the adjustment of connection weights. In…

  11. 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

  12. 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

  13. Statistical Machine Translation of Japanese

    Science.gov (United States)

    2007-03-01

    spoken, it may be phonologically displayed as /W AA T AA SH IY/, where each of the six elements between the slashes is a written representation of...phonemes. A chart showing the possible assignment of kana to phonemes is in Figure 3.1. The complete phonetic symbol set in Table 6.4 is the set of...sequences output by the recognizer. 6.6 Acoustic Model 66 The acoustic model, P(O|S) from Bayes’ rule, maps acoustic features to distinct phonetic

  14. Translation lexicon acquisition from bilingual dictionaries

    Science.gov (United States)

    Doermann, David S.; Ma, Huanfeng; Karagol-Ayan, Burcu; Oard, Douglas W.

    2001-12-01

    Bilingual dictionaries hold great potential as a source of lexical resources for training automated systems for optical character recognition, machine translation and cross-language information retrieval. In this work we describe a system for extracting term lexicons from printed copies of bilingual dictionaries. We describe our approach to page and definition segmentation and entry parsing. We have used the approach to parse a number of dictionaries and demonstrate the results for retrieval using a French-English Dictionary to generate a translation lexicon and a corpus of English queries applied to French documents to evaluation cross-language IR.

  15. Translator awareness Translator awareness

    Directory of Open Access Journals (Sweden)

    Wolfram Wilss

    2008-04-01

    Full Text Available If we want to encompass adequately the wide-ranging field of human translation, it is necessary to include in translation studies (TS the concept of translator awareness (or translator consciousness, for that matter. However, this is more easily said than done, because this concept does not easily lend itself to definition, let alone to measurement, e. g., by investigating translator behaviour. To put it bluntly: Translator awareness is a fuzzy concept. Like many obviously difficult-to-define concepts, with which dialogue in TS is burdened, translator awareness lacks an articulated theory within which different forms of translator behaviour can be convincingly related to, or distinguished from, one another. Hence, TS has so far not tackled, at least not systematically, the issue of translator awareness. If we want to encompass adequately the wide-ranging field of human translation, it is necessary to include in translation studies (TS the concept of translator awareness (or translator consciousness, for that matter. However, this is more easily said than done, because this concept does not easily lend itself to definition, let alone to measurement, e. g., by investigating translator behaviour. To put it bluntly: Translator awareness is a fuzzy concept. Like many obviously difficult-to-define concepts, with which dialogue in TS is burdened, translator awareness lacks an articulated theory within which different forms of translator behaviour can be convincingly related to, or distinguished from, one another. Hence, TS has so far not tackled, at least not systematically, the issue of translator awareness.

  16. Coastal water quality estimation from Geostationary Ocean Color Imager (GOCI) satellite data using machine learning approaches

    Science.gov (United States)

    Im, Jungho; Ha, Sunghyun; Kim, Yong Hoon; Ha, Hokyung; Choi, Jongkuk; Kim, Miae

    2014-05-01

    It is important to monitor coastal water quality using key parameters such as chlorophyll-a concentration and suspended sediment to better manage coastal areas as well as to better understand the nature of biophysical processes in coastal seawater. Remote sensing technology has been commonly used to monitor coastal water quality due to its ability of covering vast areas at high temporal resolution. While it is relatively straightforward to estimate water quality in open ocean (i.e., Case I water) using remote sensing, coastal water quality estimation is still challenging as many factors can influence water quality, including various materials coming from inland water systems and tidal circulation. There are continued efforts to accurately estimate water quality parameters in coastal seawater from remote sensing data in a timely manner. In this study, two major water quality indicators, chlorophyll-a concentration and the amount of suspended sediment, were estimated using Geostationary Ocean Color Imager (GOCI) satellite data. GOCI, launched in June 2010, is the first geostationary ocean color observation satellite in the world. GOCI collects data hourly for 8 hours a day at 6 visible and 2 near-infrared bands at a 500 m resolution with 2,500 x 2,500 km square around Korean peninsula. Along with conventional statistical methods (i.e., various linear and non-linear regression), three machine learning approaches such as random forest, Cubist, and support vector regression were evaluated for coastal water quality estimation. In situ measurements (63 samples; including location, two water quality parameters, and the spectra of surface water using a hand-held spectroradiometer) collected during four days between 2011 and 2012 were used as reference data. Due to the small sample size, leave-one-out cross validation was used to assess the performance of the water quality estimation models. Atmospherically corrected radiance data and selected band-ratioed images were used

  17. Machine learning approaches to supporting the identification of photoreceptor-enriched genes based on expression data

    Directory of Open Access Journals (Sweden)

    Simpson David

    2006-03-01

    Full Text Available Abstract Background Retinal photoreceptors are highly specialised cells, which detect light and are central to mammalian vision. Many retinal diseases occur as a result of inherited dysfunction of the rod and cone photoreceptor cells. Development and maintenance of photoreceptors requires appropriate regulation of the many genes specifically or highly expressed in these cells. Over the last decades, different experimental approaches have been developed to identify photoreceptor enriched genes. Recent progress in RNA analysis technology has generated large amounts of gene expression data relevant to retinal development. This paper assesses a machine learning methodology for supporting the identification of photoreceptor enriched genes based on expression data. Results Based on the analysis of publicly-available gene expression data from the developing mouse retina generated by serial analysis of gene expression (SAGE, this paper presents a predictive methodology comprising several in silico models for detecting key complex features and relationships encoded in the data, which may be useful to distinguish genes in terms of their functional roles. In order to understand temporal patterns of photoreceptor gene expression during retinal development, a two-way cluster analysis was firstly performed. By clustering SAGE libraries, a hierarchical tree reflecting relationships between developmental stages was obtained. By clustering SAGE tags, a more comprehensive expression profile for photoreceptor cells was revealed. To demonstrate the usefulness of machine learning-based models in predicting functional associations from the SAGE data, three supervised classification models were compared. The results indicated that a relatively simple instance-based model (KStar model performed significantly better than relatively more complex algorithms, e.g. neural networks. To deal with the problem of functional class imbalance occurring in the dataset, two data re

  18. TRII: A Probabilistic Scoring of Drosophila melanogaster Translation Initiation Sites

    Directory of Open Access Journals (Sweden)

    Rice Michael D

    2010-01-01

    Full Text Available Relative individual information is a measurement that scores the quality of DNA- and RNA-binding sites for biological machines. The development of analytical approaches to increase the power of this scoring method will improve its utility in evaluating the functions of motifs. In this study, the scoring method was applied to potential translation initiation sites in Drosophila to compute Translation Relative Individual Information (TRII scores. The weight matrix at the core of the scoring method was optimized based on high-confidence translation initiation sites identified by using a progressive partitioning approach. Comparing the distributions of TRII scores for sites of interest with those for high-confidence translation initiation sites and random sequences provides a new methodology for assessing the quality of translation initiation sites. The optimized weight matrices can also be used to describe the consensus at translation initiation sites, providing a quantitative measure of preferred and avoided nucleotides at each position.

  19. Self-commissioning of permanent magnet synchronous machine drives using hybrid approach

    DEFF Research Database (Denmark)

    Basar, M. Sertug; Bech, Michael Møller; Andersen, Torben Ole

    2014-01-01

    Self-commissioning of permanent-magnet (PM) synchronous machines (PMSMs) is of prime importance in an industrial drive system because control performance and system stability depend heavily on the accurate machine parameter information. This article focuses on a combination of offline and online ...

  20. Lost and Found in Translation: An Ecological Approach to Bilingual Research Methodology

    Directory of Open Access Journals (Sweden)

    Justin Jagosh PhD

    2009-06-01

    Full Text Available Translation issues emerged from a qualitative study, conducted in French and English, that gathered patient perspectives on a newly implemented undergraduate medical curriculum entitled Physicianship: The Physician as Professional and Healer. French-speaking participants were interviewed using a translated interview guide, originally developed in English. A major finding that francophone participants contested the idea of the physician-healer in a manner not witnessed among the anglophone participants. Consultation with multilingual health professionals was undertaken to explore whether the contestation was the result of poor translation of the word healer. This process confirmed that no appropriate French equivalent could be found. With hindsight, the authors emphasize the importance of pretesting translated research instrumentation. An ecological perspective on language equivalency is also emphasized, in which emergent linguistic discrepancies are viewed as opportunities for learning about the culture-language relationship.

  1. On Heuristic Approach for Solution of Scheduling Problem Involving Transportation Time and Break-down Times for Three Machines

    Directory of Open Access Journals (Sweden)

    A. Khodadadi

    2014-04-01

    Full Text Available In most manufacturing and distribution systems, semi-finished jobs are transferred from one processing facility to another by transporters such as automated guided vehicles and conveyors and finished jobs are delivered to customers or warehouses by vehicles such as trucks. Most machine scheduling models assume either that there are a finite number of transporters for delivering jobs or that jobs are delivered instantaneously from one location to another without transportation time involved. In this study we study a new simple heuristic algorithm for a ‘3-machine, n-job’ flow shop scheduling problem in which transportation time and break down times of machines are considered. A heuristic approach method to find optimal and near optimal sequence minimizing the total elapsed time.

  2. CPS Modeling of CNC Machine Tool Work Processes Using an Instruction-Domain Based Approach

    Directory of Open Access Journals (Sweden)

    Jihong Chen

    2015-06-01

    Full Text Available Building cyber-physical system (CPS models of machine tools is a key technology for intelligent manufacturing. The massive electronic data from a computer numerical control (CNC system during the work processes of a CNC machine tool is the main source of the big data on which a CPS model is established. In this work-process model, a method based on instruction domain is applied to analyze the electronic big data, and a quantitative description of the numerical control (NC processes is built according to the G code of the processes. Utilizing the instruction domain, a work-process CPS model is established on the basis of the accurate, real-time mapping of the manufacturing tasks, resources, and status of the CNC machine tool. Using such models, case studies are conducted on intelligent-machining applications, such as the optimization of NC processing parameters and the health assurance of CNC machine tools.

  3. Maximizing protein translation rate in the non-homogeneous ribosome flow model: a convex optimization approach.

    Science.gov (United States)

    Poker, Gilad; Zarai, Yoram; Margaliot, Michael; Tuller, Tamir

    2014-11-06

    Translation is an important stage in gene expression. During this stage, macro-molecules called ribosomes travel along the mRNA strand linking amino acids together in a specific order to create a functioning protein. An important question, related to many biomedical disciplines, is how to maximize protein production. Indeed, translation is known to be one of the most energy-consuming processes in the cell, and it is natural to assume that evolution shaped this process so that it maximizes the protein production rate. If this is indeed so then one can estimate various parameters of the translation machinery by solving an appropriate mathematical optimization problem. The same problem also arises in the context of synthetic biology, namely, re-engineer heterologous genes in order to maximize their translation rate in a host organism. We consider the problem of maximizing the protein production rate using a computational model for translation-elongation called the ribosome flow model (RFM). This model describes the flow of the ribosomes along an mRNA chain of length n using a set of n first-order nonlinear ordinary differential equations. It also includes n + 1 positive parameters: the ribosomal initiation rate into the mRNA chain, and n elongation rates along the chain sites. We show that the steady-state translation rate in the RFM is a strictly concave function of its parameters. This means that the problem of maximizing the translation rate under a suitable constraint always admits a unique solution, and that this solution can be determined using highly efficient algorithms for solving convex optimization problems even for large values of n. Furthermore, our analysis shows that the optimal translation rate can be computed based only on the optimal initiation rate and the elongation rate of the codons near the beginning of the ORF. We discuss some applications of the theoretical results to synthetic biology, molecular evolution, and functional genomics.

  4. A machine-learning approach for predicting palmitoylation sites from integrated sequence-based features.

    Science.gov (United States)

    Li, Liqi; Luo, Qifa; Xiao, Weidong; Li, Jinhui; Zhou, Shiwen; Li, Yongsheng; Zheng, Xiaoqi; Yang, Hua

    2017-02-01

    Palmitoylation is the covalent attachment of lipids to amino acid residues in proteins. As an important form of protein posttranslational modification, it increases the hydrophobicity of proteins, which contributes to the protein transportation, organelle localization, and functions, therefore plays an important role in a variety of cell biological processes. Identification of palmitoylation sites is necessary for understanding protein-protein interaction, protein stability, and activity. Since conventional experimental techniques to determine palmitoylation sites in proteins are both labor intensive and costly, a fast and accurate computational approach to predict palmitoylation sites from protein sequences is in urgent need. In this study, a support vector machine (SVM)-based method was proposed through integrating PSI-BLAST profile, physicochemical properties, [Formula: see text]-mer amino acid compositions (AACs), and [Formula: see text]-mer pseudo AACs into the principal feature vector. A recursive feature selection scheme was subsequently implemented to single out the most discriminative features. Finally, an SVM method was implemented to predict palmitoylation sites in proteins based on the optimal features. The proposed method achieved an accuracy of 99.41% and Matthews Correlation Coefficient of 0.9773 for a benchmark dataset. The result indicates the efficiency and accuracy of our method in prediction of palmitoylation sites based on protein sequences.

  5. An Artificial Intelligence Approach for Groutability Estimation Based on Autotuning Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Hong-Hai Tran

    2014-01-01

    Full Text Available Permeation grouting is a commonly used approach for soil improvement in construction engineering. Thus, predicting the results of grouting activities is a crucial task that needs to be carried out in the planning phase of any grouting project. In this research, a novel artificial intelligence approach—autotuning support vector machine—is proposed to forecast the result of grouting activities that employ microfine cement grouts. In the new model, the support vector machine (SVM algorithm is utilized to classify grouting activities into two classes: success and  failure. Meanwhile, the differential evolution (DE optimization algorithm is employed to identify the optimal tuning parameters of the SVM algorithm, namely, the penalty parameter and the kernel function parameter. The integration of the SVM and DE algorithms allows the newly established method to operate automatically without human prior knowledge or tedious processes for parameter setting. An experiment using a set of in situ data samples demonstrates that the newly established method can produce an outstanding prediction performance.

  6. Hybrid wavelet-support vector machine approach for modelling rainfall-runoff process.

    Science.gov (United States)

    Komasi, Mehdi; Sharghi, Soroush

    2016-01-01

    Because of the importance of water resources management, the need for accurate modeling of the rainfall-runoff process has rapidly grown in the past decades. Recently, the support vector machine (SVM) approach has been used by hydrologists for rainfall-runoff modeling and the other fields of hydrology. Similar to the other artificial intelligence models, such as artificial neural network (ANN) and adaptive neural fuzzy inference system, the SVM model is based on the autoregressive properties. In this paper, the wavelet analysis was linked to the SVM model concept for modeling the rainfall-runoff process of Aghchai and Eel River watersheds. In this way, the main time series of two variables, rainfall and runoff, were decomposed to multiple frequent time series by wavelet theory; then, these time series were imposed as input data on the SVM model in order to predict the runoff discharge one day ahead. The obtained results show that the wavelet SVM model can predict both short- and long-term runoff discharges by considering the seasonality effects. Also, the proposed hybrid model is relatively more appropriate than classical autoregressive ones such as ANN and SVM because it uses the multi-scale time series of rainfall and runoff data in the modeling process.

  7. Machine learning approach identifies new pathways associated with demyelination in a viral model of multiple sclerosis

    Science.gov (United States)

    Ulrich, Reiner; Kalkuhl, Arno; Deschl, Ulrich; Baumgärtner, Wolfgang

    2010-01-01

    Abstract Theiler’s murine encephalomyelitis is an experimentally virus-induced inflammatory demyelinating disease of the spinal cord, displaying clinical and pathological similarities to chronic progressive multiple sclerosis. The aim of this study was to identify pathways associated with chronic demyelination using an assumption-free combined microarray and immunohistology approach. Movement control as determined by rotarod assay significantly worsened in Theiler’s murine encephalomyelitis -virus-infected SJL/J mice from 42 to 196 days after infection (dpi). In the spinal cords, inflammatory changes were detected 14 to 196 dpi, and demyelination progressively increased from 42 to 196 dpi. Microarray analysis revealed 1001 differentially expressed genes over the study period. The dominating changes as revealed by k-means and functional annotation clustering included up-regulations related to intrathecal antibody production and antigen processing and presentation via major histocompatibility class II molecules. A random forest machine learning algorithm revealed that down-regulated lipid and cholesterol biosynthesis, differentially expressed neurite morphogenesis and up-regulated toll-like receptor-4-induced pathways were intimately associated with demyelination as measured by immunohistology. Conclusively, although transcriptional changes were dominated by the adaptive immune response, the main pathways associated with demyelination included up-regulation of toll-like receptor 4 and down-regulation of cholesterol biosynthesis. Cholesterol biosynthesis is a rate limiting step of myelination and its down-regulation is suggested to be involved in chronic demyelination by an inhibition of remyelination. PMID:19183246

  8. Intelligent Video Object Classification Scheme using Offline Feature Extraction and Machine Learning based Approach

    Directory of Open Access Journals (Sweden)

    Chandra Mani Sharma

    2012-01-01

    Full Text Available Classification of objects in video stream is important because of its application in many emerging areas such as visual surveillance, content based video retrieval and indexing etc. The task is far more challenging because the video data is of heavy and highly variable nature. The processing of video data is required to be in real-time. This paper presents a multiclass object classification technique using machine learning approach. Haar-like features are used for training the classifier. The feature calculation is performed using Integral Image representation and we train the classifier offline using a Stage-wise Additive Modeling using a Multiclass Exponential loss function (SAMME. The validity of the method has been verified from the implementation of a real-time human-car detector. Experimental results show that the proposed method can accurately classify objects, in video, into their respective classes. The proposed object classifier works well in outdoor environment in presence of moderate lighting conditions and variable scene background. The proposed technique is compared, with other object classification techniques, based on various performance parameters.

  9. A support vector machine approach to the automatic identification of fluorescence spectra emitted by biological agents

    Science.gov (United States)

    Gelfusa, M.; Murari, A.; Lungaroni, M.; Malizia, A.; Parracino, S.; Peluso, E.; Cenciarelli, O.; Carestia, M.; Pizzoferrato, R.; Vega, J.; Gaudio, P.

    2016-10-01

    Two of the major new concerns of modern societies are biosecurity and biosafety. Several biological agents (BAs) such as toxins, bacteria, viruses, fungi and parasites are able to cause damage to living systems either humans, animals or plants. Optical techniques, in particular LIght Detection And Ranging (LIDAR), based on the transmission of laser pulses and analysis of the return signals, can be successfully applied to monitoring the release of biological agents into the atmosphere. It is well known that most of biological agents tend to emit specific fluorescence spectra, which in principle allow their detection and identification, if excited by light of the appropriate wavelength. For these reasons, the detection of the UVLight Induced Fluorescence (UV-LIF) emitted by BAs is particularly promising. On the other hand, the stand-off detection of BAs poses a series of challenging issues; one of the most severe is the automatic discrimination between various agents which emit very similar fluorescence spectra. In this paper, a new data analysis method, based on a combination of advanced filtering techniques and Support Vector Machines, is described. The proposed approach covers all the aspects of the data analysis process, from filtering and denoising to automatic recognition of the agents. A systematic series of numerical tests has been performed to assess the potential and limits of the proposed methodology. The first investigations of experimental data have already given very encouraging results.

  10. A Machine-learning approach to classification of X-ray sources

    Science.gov (United States)

    Hare, Jeremy; Kargaltsev, Oleg; Rangelov, Blagoy; Pavlov, George; Posselt, Bettina; Volkov, Igor

    2017-08-01

    Chandra and XMM-Newton X-ray observatories have serendipitously detected a large number of Galactic sources. Although their properties are automatically extracted and stored in catalogs, most of these sources remain unexplored. Classifying these sources can enable population studies on much larger scales and may also reveal new types of X-ray sources. For most of these sources the X-ray data alone are not enough to identify their nature, and multiwavelength data must be used. We developed a multiwavelength classification pipeline (MUWCLASS), which relies on supervised machine learning and a rich training dataset. We describe the training dataset, the pipeline and its testing, and will show/discuss how the code performs in different example environments, such as unidentified gamma-ray sources, supernova remnants, dwarf galaxies, stellar clusters, and the inner Galactic plane. We also discuss the application of this approach to the data from upcoming new X-ray observatories (e.g., eROSITA, Athena).

  11. A machine learning approach for classification of anatomical coverage in CT

    Science.gov (United States)

    Wang, Xiaoyong; Lo, Pechin; Ramakrishna, Bharath; Goldin, Johnathan; Brown, Matthew

    2016-03-01

    Automatic classification of anatomical coverage of medical images is critical for big data mining and as a pre-processing step to automatically trigger specific computer aided diagnosis systems. The traditional way to identify scans through DICOM headers has various limitations due to manual entry of series descriptions and non-standardized naming conventions. In this study, we present a machine learning approach where multiple binary classifiers were used to classify different anatomical coverages of CT scans. A one-vs-rest strategy was applied. For a given training set, a template scan was selected from the positive samples and all other scans were registered to it. Each registered scan was then evenly split into k × k × k non-overlapping blocks and for each block the mean intensity was computed. This resulted in a 1 × k3 feature vector for each scan. The feature vectors were then used to train a SVM based classifier. In this feasibility study, four classifiers were built to identify anatomic coverages of brain, chest, abdomen-pelvis, and chest-abdomen-pelvis CT scans. Each classifier was trained and tested using a set of 300 scans from different subjects, composed of 150 positive samples and 150 negative samples. Area under the ROC curve (AUC) of the testing set was measured to evaluate the performance in a two-fold cross validation setting. Our results showed good classification performance with an average AUC of 0.96.

  12. A machine learning approach to automated structural network analysis: application to neonatal encephalopathy.

    Directory of Open Access Journals (Sweden)

    Etay Ziv

    Full Text Available Neonatal encephalopathy represents a heterogeneous group of conditions associated with life-long developmental disabilities and neurological deficits. Clinical measures and current anatomic brain imaging remain inadequate predictors of outcome in children with neonatal encephalopathy. Some studies have suggested that brain development and, therefore, brain connectivity may be altered in the subgroup of patients who subsequently go on to develop clinically significant neurological abnormalities. Large-scale structural brain connectivity networks constructed using diffusion tractography have been posited to reflect organizational differences in white matter architecture at the mesoscale, and thus offer a unique tool for characterizing brain development in patients with neonatal encephalopathy. In this manuscript we use diffusion tractography to construct structural networks for a cohort of patients with neonatal encephalopathy. We systematically map these networks to a high-dimensional space and then apply standard machine learning algorithms to predict neurological outcome in the cohort. Using nested cross-validation we demonstrate high prediction accuracy that is both statistically significant and robust over a broad range of thresholds. Our algorithm offers a novel tool to evaluate neonates at risk for developing neurological deficit. The described approach can be applied to any brain pathology that affects structural connectivity.

  13. Investigation of the influence of protein corona composition on gold nanoparticle bioactivity using machine learning approaches.

    Science.gov (United States)

    Papa, E; Doucet, J P; Sangion, A; Doucet-Panaye, A

    2016-07-01

    The understanding of the mechanisms and interactions that occur when nanomaterials enter biological systems is important to improve their future use. The adsorption of proteins from biological fluids in a physiological environment to form a corona on the surface of nanoparticles represents a key step that influences nanoparticle behaviour. In this study, the quantitative description of the composition of the protein corona was used to study the effect on cell association induced by 84 surface-modified gold nanoparticles of different sizes. Quantitative relationships between the protein corona and the activity of the gold nanoparticles were modelled by using several machine learning-based linear and non-linear approaches. Models based on a selection of only six serum proteins had robust and predictive results. The Projection Pursuit Regression method had the best performances (r(2) = 0.91; Q(2)loo = 0.81; r(2)ext = 0.79). The present study confirmed the utility of protein corona composition to predict the bioactivity of gold nanoparticles and identified the main proteins that act as promoters or inhibitors of cell association. In addition, the comparison of several techniques showed which strategies offer the best results in prediction and could be used to support new toxicological studies on gold-based nanomaterials.

  14. A microscopy approach for in situ inspection of micro-coordinate measurement machine styli for contamination

    Science.gov (United States)

    Feng, Xiaobing; Pascal, Jonathan; Lawes, Simon

    2017-09-01

    During the process of measurement using a micro-coordinate measurement machine (µCMM) contamination gradually builds up on the surface of the stylus tip and affects the dimensional accuracy of the measurement. Regular inspection of the stylus for contamination is essential to determine the appropriate cleaning interval and prevent the dimensional error from becoming significant. However, in situ inspection of a µCMM stylus is challenging due to the size, spherical shape, material and surface properties of a typical stylus. To address this challenge, this study evaluates several non-contact measurement technologies for in situ stylus inspection and, based on those findings, proposes a cost-effective microscopy approach. The operational principle is then demonstrated by an automated prototype, coordinated directly by the CMM software MCOSMOS, with an effective threshold of detection as low as 400 nm and a large field of view and depth of field. The level of contamination on the stylus has been found to increase steadily with the number of measurement contacts made. Once excessive contamination is detected on the stylus, measurement should be stopped and a stylus cleaning procedure should be performed to avoid affecting measurement accuracy.

  15. Alternating current multi-circuit electric machines a new approach to the steady-state parameter determination

    CERN Document Server

    Asanbayev, Valentin

    2015-01-01

    This book details an approach for realization of the field decomposition concept. The book presents the  methods as well as techniques and procedures for establishing electric machine circuit-loops and determining their parameters. The methods developed have been realized using the models of machines with laminated and solid rotor having classical structure. The use of such models are well recognized and simplifies practical implementation of the obtained results. This book also: ·         Includes methods for a construction of electric machine equivalent circuits that allows the replacement of the field models of the machine with simple circuit models ·         Demonstrates the practical implementation of the proposed techniques and procedures ·         Presents parameters of the circuit-loops in the form most convenient for practical implementation ·         Uses methods based on machine models widely used in practice

  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. A translation approach to metaphor teaching in the LSP classroom: sample exercises from a Business English syllabus

    Directory of Open Access Journals (Sweden)

    Marisol Velasco Sacristán

    2009-04-01

    Full Text Available Translation can provide a valuable contribution to the teaching of metaphor in the LSP classroom. Although all languages make use of metaphor, neither conceptual metaphors nor their linguistic renderings will necessarily always be the same across languages (Deignan et al., 1997. Thus the extent to which metaphor presents a hurdle for second language learners of professional discourse depends on the extent to which there is overlap between the metaphorical systems of the L1 and the L2. Hence it follows that a better understanding of the similarities and differences in metaphor use between language pairs can help L2 learners of different professional discourses overcome problems of transferring metaphors from one language and culture to another. In this paper I propose a translation approach to metaphor teaching in the LSP classroom, illustrating its use in a Business English syllabus in which some learner-centred cognitive translation activities have been used. The results of using this approach in that application, although still in need of further empirical research, seem to suggest that translation can constitute a valuable pedagogical and communicative means to teach metaphorical concepts and expressions to L2 learners of professional discourses.

  18. Optimizing machining parameters of wire-EDM process to cut Al7075/SiCp composites using an integrated statistical approach

    Institute of Scientific and Technical Information of China (English)

    Thella Babu Rao

    2016-01-01

    Metal matrix composites (MMCs) as advanced materials,while producing the components with high dimensional accuracy and intricate shapes,are more complex and cost effective for machining than conventional alloys.It is due to the presence of discontinuously distributed hard ceramic with the MMCs and involvement of a large number of machining control variables.However,determination of optimal machining conditions helps the process engineer to make the process efficient and effective.In the present investigation a novel hybrid multi-response optimization approach is proposed to derive the economic machining conditions for MMCs.This hybrid approach integrates the concepts of grey relational analysis (GRA),principal component analysis (PCA) and Taguchi method (TM) to derive the optimal machining conditions.The machining experiments are planned to machine A17075/SiCp MMCs using wire-electrical discharge machining (WEDM) process.SiC particulate size and its weight percentage are explicitly considered here as the process variables along with the WEDM input variables.The derived optimal process responses are confirmed by the experimental validation tests and the results show satisfactory.The practical possibility of the derived optimal machining conditions is also analyzed and presented using scanning electron microscope (SEM) examinations.According to the growing industrial need of making high performance,low cost components,this investigation provides a simple and sequential approach to enhance the WEDM performance while machining MMCs.

  19. Smart Cutting Tools and Smart Machining: Development Approaches, and Their Implementation and Application Perspectives

    Science.gov (United States)

    Cheng, Kai; Niu, Zhi-Chao; Wang, Robin C.; Rakowski, Richard; Bateman, Richard

    2017-09-01

    Smart machining has tremendous potential and is becoming one of new generation high value precision manufacturing technologies in line with the advance of Industry 4.0 concepts. This paper presents some innovative design concepts and, in particular, the development of four types of smart cutting tools, including a force-based smart cutting tool, a temperature-based internally-cooled cutting tool, a fast tool servo (FTS) and smart collets for ultraprecision and micro manufacturing purposes. Implementation and application perspectives of these smart cutting tools are explored and discussed particularly for smart machining against a number of industrial application requirements. They are contamination-free machining, machining of tool-wear-prone Si-based infra-red devices and medical applications, high speed micro milling and micro drilling, etc. Furthermore, implementation techniques are presented focusing on: (a) plug-and-produce design principle and the associated smart control algorithms, (b) piezoelectric film and surface acoustic wave transducers to measure cutting forces in process, (c) critical cutting temperature control in real-time machining, (d) in-process calibration through machining trials, (e) FE-based design and analysis of smart cutting tools, and (f) application exemplars on adaptive smart machining.

  20. Automatic de-identification of French clinical records: comparison of rule-based and machine-learning approaches.

    Science.gov (United States)

    Grouin, Cyril; Zweigenbaum, Pierre

    2013-01-01

    In this paper, we present a comparison of two approaches to automatically de-identify medical records written in French: a rule-based system and a machine-learning based system using a conditional random fields (CRF) formalism. Both systems have been designed to process nine identifiers in a corpus of medical records in cardiology. We performed two evaluations: first, on 62 documents in cardiology, and on 10 documents in foetopathology - produced by optical character recognition (OCR) - to evaluate the robustness of our systems. We achieved a 0.843 (rule-based) and 0.883 (machine-learning) exact match overall F-measure in cardiology. While the rule-based system allowed us to achieve good results on nominative (first and last names) and numerical data (dates, phone numbers, and zip codes), the machine-learning approach performed best on more complex categories (postal addresses, hospital names, medical devices, and towns). On the foetopathology corpus, although our systems have not been designed for this corpus and despite OCR character recognition errors, we obtained promising results: a 0.681 (rule-based) and 0.638 (machine-learning) exact-match overall F-measure. This demonstrates that existing tools can be applied to process new documents of lower quality.

  1. Identification of asteroids trapped inside three-body mean motion resonances: a machine-learning approach

    Science.gov (United States)

    Smirnov, Evgeny A.; Markov, Alexey B.

    2017-08-01

    In this paper, we apply the following machine learning methods that do not require numerical integration - namely, k-nearest neighbours, decision tree, gradient boosting and logistic regression - for identifying three-body resonant asteroids in the main belt. It is shown that the results of the identification by machine learning methods are accurate and take significantly less time than numerical integration (seconds versus days). We have identified 404 new asteroids subjected to the three-body resonance 4J-2S-1 using a machine learning methodology.

  2. Knowledge translation in health research: a novel approach to health sciences education.

    Science.gov (United States)

    Reitmanova, Sylvia

    2009-08-18

    The salient role of knowledge translation process, by which knowledge is put into practice, is increasingly recognized by various research stakeholders. However, medical schools are slow in providing medical students and health professionals engaged in research with the sufficient opportunities to examine more closely the facilitators and barriers to utilization of research evidence in policymaking and implementation, or the effectiveness of their research communication strategies. Memorial University of Newfoundland now offers a knowledge translation course that equips students of community health and applied health research with the knowledge and skills necessary for conducting research, that responds more closely to the needs of their communities, and for improving the utilization of their research by a variety of research consumers. This case study illustrates how the positive research outcomes resulted from implementing the knowledge translation strategies learned in the course. Knowledge translation can be useful also in attracting more funding and support from research agencies, industry, government agencies and the public. These reasons offer a compelling rationale for the standard inclusion of knowledge translation courses in health sciences education.

  3. A Community-Engaged Approach to Translating Research into Practice: A Physical Education Story.

    Science.gov (United States)

    Cutforth, Nick; Belansky, Elaine S

    2015-01-01

    The National Institutes of Health's Clinical and Translational Sciences Award program emphasizes the need to speed up the process of putting evidence-based practices into place. One strategy they promote is community engagement; however, few studies describe a process for meaningfully engaging communities in the translation process. This article describes steps taken by a university- community partnership to create a plan for implementing evidence-based physical education (PE) practices in rural schools. This partnership's efforts resulted in the acquisition of a $1.86 million grant to implement the plan. Qualitative data collected during the planning process were analyzed using content analysis. Key steps included undertaking a baseline assessment of community needs, reviewing and selecting evidence-based practices, developing a multilevel, community-driven action plan and establishing its feasibility with community stakeholders. These steps could be applied to other health topics across a variety of settings. Several strategies that made the process successful are described. Recommendations are made for expanding the roles of Clinical and Translational Science Awards (CTSAs) and local health foundations in supporting community-engaged translational research. University-community partnerships have the potential to create plans and obtain large-scale funding for translating evidence-based research into practice.

  4. Machine Learning

    CERN Document Server

    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.

  5. Novel approach of crater detection by crater candidate region selection and matrix-pattern-oriented least squares support vector machine

    Institute of Scientific and Technical Information of China (English)

    Ding Meng; Cao Yunfeng; Wu Qingxian

    2013-01-01

    Impacted craters are commonly found on the surface of planets,satellites,asteroids and other solar system bodies.In order to speed up the rate of constructing the database of craters,it is important to develop crater detection algorithms.This paper presents a novel approach to automatically detect craters on planetary surfaces.The approach contains two parts:crater candidate region selection and crater detection.In the first part,crater candidate region selection is achieved by Kanade-Lucas-Tomasi (KLT) detector.Matrix-pattern-oriented least squares support vector machine (MatLSSVM),as the matrixization version of least square support vector machine (SVM),inherits the advantages of least squares support vector machine (LSSVM),reduces storage space greatly and reserves spatial redundancies within each image matrix compared with general LSSVM.The second part of the approach employs MatLSSVM to design classifier for crater detection.Experimental results on the dataset which comprises 160 preprocessed image patches from Google Mars demonstrate that the accuracy rate of crater detection can be up to 88%.In addition,the outstanding feature of the approach introduced in this paper is that it takes resized crater candidate region as input pattern directly to finish crater detection.The results of the last experiment demonstrate that MatLSSVM-based classifier can detect crater regions effectively on the basis of KLT-based crater candidate region selection.

  6. Opinion word mining using translation and semantic approaches%基于翻译和语义方法的情感词挖掘研究

    Institute of Scientific and Technical Information of China (English)

    肖健; 徐建; 朱姝; 万缨; 许亮

    2011-01-01

    随着互联网的扩展,网络上出现了越来越多的含有观点信息的主观性评论文本.挖掘这些文本中的情感词语并进行极性判别具有重要的现实意义和商业价值.为此,提出一种基于翻译方法的情感词提取方法,使用汉英机器翻译系统翻译汉语种子情感词典生成候选英语词语,根据WordNet提取候选英语词语的上下位词、同义词或反义词并将这些词语翻译成汉语,进而提取汉语情感词语.另外,依据SentiWordNet判别候选英语词语极性,并将候选英语词语极性映射到目标汉语情感词语上,进而达到判别汉语情感词语极性的目的.实验结果表明上述方法可以有效提高情感词的识别效率以及极性判别的准确率.%With the rapid development of the Internet,more and more opinionated texts are surging on the web.It is of practical and commercial value to mine opinion words and classify their polarities in these texts.A translation approach is proposed to extract opinion words, using Chinese-English Machine Translation(MT) system to convert the Chinese seed opinion words into English words.The WordNet is employed to get hypernyms.hyponyms,synonyms of these English words and use English-Chinese MT system to translate them into corresponding Chinese words which are used as candidate opinion words. Additionally, the SentiWordNet is used to classify English opinionated word polarities, which are to be mapped to those of the Chinese opinion words.Experimental results show that the approaches taken in this paper improve the precision of mining opinionated words and classifying their polarities.

  7. Measuring Cognitive Translation Effort with Activity Units

    DEFF Research Database (Denmark)

    Schaeffer, Moritz; Carl, Michael; Lacruz, Isabel

    2016-01-01

    Despite the increased quality of Machine Translation output, human interaction will remain a crucial activity to guarantee the quality of the final translation products. Human-computer interaction in translation will likely be the more successful the more we understand the properties and compleme...... methods in empirical translation process research and suggests ngrams of Activity Units for measuring the translation process....

  8. 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.

  9. Polish, Greek and Cypriot Civil Procedure Terminology in Translation. A Parametric Approach

    Directory of Open Access Journals (Sweden)

    Gortych-Michalak Karolina

    2017-03-01

    Full Text Available The paper discusses the problem of translating selected Civil Procedure terminology from Greek into Polish and from Polish into Greek. The research material includes corpora of normative acts and more precisely those, which regulate Civil Procedure of Poland, Greece and the Republic of Cyprus. The research methodology is based on the concept of parameterisation, according to which the legal linguistic reality becomes axiomatic. Then the set of relevant dimensions and parameters is extracted. The set of parameters are a tool where certain information is given: yes/no/none and thus a clear result of comparison between legal system bond terminology can be drawn up. The results of this comparative analysis provide highly regulated and available translation equivalents, which are essential when legal translation is performed within the frame of legal reality. Selected examples of use of these equivalents are given when discussing the results.

  10. Parallel Machine Scheduling Models with Fuzzy Parameters and Precedence Constraints: A Credibility Approach

    Institute of Scientific and Technical Information of China (English)

    HOU Fu-jun; WU Qi-zong

    2007-01-01

    A method for modeling the parallel machine scheduling problems with fuzzy parameters and precedence constraints based on credibility measure is provided.For the given n jobs to be processed on m machines, it is assumed that the processing times and the due dates are nonnegative fuzzy numbers and all the weights are positive, crisp numbers.Based on credibility measure, three parallel machine scheduling problems and a goal-programming model are formulated.Feasible schedules are evaluated not only by their objective values but also by the credibility degree of satisfaction with their precedence constraints.The genetic algorithm is utilized to find the best solutions in a short period of time.An illustrative numerical example is also given.Simulation results show that the proposed models are effective, which can deal with the parallel machine scheduling problems with fuzzy parameters and precedence constraints based on credibility measure.

  11. Methods and Research for Multi-Component Cutting Force Sensing Devices and Approaches in Machining.

    Science.gov (United States)

    Liang, Qiaokang; Zhang, Dan; Wu, Wanneng; Zou, Kunlin

    2016-11-16

    Multi-component cutting force sensing systems in manufacturing processes applied to cutting tools are gradually becoming the most significant monitoring indicator. Their signals have been extensively applied to evaluate the machinability of workpiece materials, predict cutter breakage, estimate cutting tool wear, control machine tool chatter, determine stable machining parameters, and improve surface finish. Robust and effective sensing systems with capability of monitoring the cutting force in machine operations in real time are crucial for realizing the full potential of cutting capabilities of computer numerically controlled (CNC) tools. The main objective of this paper is to present a brief review of the existing achievements in the field of multi-component cutting force sensing systems in modern manufacturing.

  12. Methods and Research for Multi-Component Cutting Force Sensing Devices and Approaches in Machining

    Directory of Open Access Journals (Sweden)

    Qiaokang Liang

    2016-11-01

    Full Text Available Multi-component cutting force sensing systems in manufacturing processes applied to cutting tools are gradually becoming the most significant monitoring indicator. Their signals have been extensively applied to evaluate the machinability of workpiece materials, predict cutter breakage, estimate cutting tool wear, control machine tool chatter, determine stable machining parameters, and improve surface finish. Robust and effective sensing systems with capability of monitoring the cutting force in machine operations in real time are crucial for realizing the full potential of cutting capabilities of computer numerically controlled (CNC tools. The main objective of this paper is to present a brief review of the existing achievements in the field of multi-component cutting force sensing systems in modern manufacturing.

  13. An approach to error elimination for multi-axis CNC machining and robot manipulation

    Institute of Scientific and Technical Information of China (English)

    XIONG; CaiHua

    2007-01-01

    The geometrical accuracy of a machined feature on a workpiece during machining processes is mainly affected by the kinematic chain errors of multi-axis CNC machines and robots, locating precision of fixtures, and datum errors on the workpiece. It is necessary to find a way to minimize the feature errors on the workpiece. In this paper, the kinematic chain errors are transformed into the displacements of the workpiece. The relationship between the kinematic chain errors and the displacements of the position and orientation of the workpiece is developed. A mapping model between the displacements of workpieces and the datum errors, and adjustments of fixtures is established. The suitable sets of unit basis twists for each of the commonly encountered types of feature and the corresponding locating directions are analyzed, and an error elimination (EE) method of the machined feature is formulated. A case study is given to verify the EE method.

  14. 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...

  15. Processing outcomes of the AFM probe-based machining approach with different feed directions

    OpenAIRE

    2016-01-01

    We present experimental and theoretical results to describe and explain processing outcomes when producing nanochannels that are a few times wider than the atomic force microscope (AFM) probe using an AFM. This is achieved when AFM tip-based machining is performed with reciprocating motion of the tip of the AFM probe. In this case, different feed directions with respect to the orientation of the AFM probe can be used. The machining outputs of interest are the chip formation process, obtained ...

  16. A Multiobjective Optimization Approach to Solve a Parallel Machines Scheduling Problem

    OpenAIRE

    2010-01-01

    A multiobjective optimization problem which focuses on parallel machines scheduling is considered. This problem consists of scheduling independent jobs on identical parallel machines with release dates, due dates, and sequence-dependent setup times. The preemption of jobs is forbidden. The aim is to minimize two different objectives: makespan and total tardiness. The contribution of this paper is to propose first a new mathematical model for this specific p...

  17. Mortality risk prediction in burn injury: Comparison of logistic regression with machine learning approaches.

    Science.gov (United States)

    Stylianou, Neophytos; Akbarov, Artur; Kontopantelis, Evangelos; Buchan, Iain; Dunn, Ken W

    2015-08-01

    Predicting mortality from burn injury has traditionally employed logistic regression models. Alternative machine learning methods have been introduced in some areas of clinical prediction as the necessary software and computational facilities have become accessible. Here we compare logistic regression and machine learning predictions of mortality from burn. An established logistic mortality model was compared to machine learning methods (artificial neural network, support vector machine, random forests and naïve Bayes) using a population-based (England & Wales) case-cohort registry. Predictive evaluation used: area under the receiver operating characteristic curve; sensitivity; specificity; positive predictive value and Youden's index. All methods had comparable discriminatory abilities, similar sensitivities, specificities and positive predictive values. Although some machine learning methods performed marginally better than logistic regression the differences were seldom statistically significant and clinically insubstantial. Random forests were marginally better for high positive predictive value and reasonable sensitivity. Neural networks yielded slightly better prediction overall. Logistic regression gives an optimal mix of performance and interpretability. The established logistic regression model of burn mortality performs well against more complex alternatives. Clinical prediction with a small set of strong, stable, independent predictors is unlikely to gain much from machine learning outside specialist research contexts. Copyright © 2015 Elsevier Ltd and ISBI. All rights reserved.

  18. 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.

  19. A Machine Learning Approach to Discover Rules for Expressive Performance Actions in Jazz Guitar Music

    Science.gov (United States)

    Giraldo, Sergio I.; Ramirez, Rafael

    2016-01-01

    Expert musicians introduce expression in their performances by manipulating sound properties such as timing, energy, pitch, and timbre. Here, we present a data driven computational approach to induce expressive performance rule models for note duration, onset, energy, and ornamentation transformations in jazz guitar music. We extract high-level features from a set of 16 commercial audio recordings (and corresponding music scores) of jazz guitarist Grant Green in order to characterize the expression in the pieces. We apply machine learning techniques to the resulting features to learn expressive performance rule models. We (1) quantitatively evaluate the accuracy of the induced models, (2) analyse the relative importance of the considered musical features, (3) discuss some of the learnt expressive performance rules in the context of previous work, and (4) assess their generailty. The accuracies of the induced predictive models is significantly above base-line levels indicating that the audio performances and the musical features extracted contain sufficient information to automatically learn informative expressive performance patterns. Feature analysis shows that the most important musical features for predicting expressive transformations are note duration, pitch, metrical strength, phrase position, Narmour structure, and tempo and key of the piece. Similarities and differences between the induced expressive rules and the rules reported in the literature were found. Differences may be due to the fact that most previously studied performance data has consisted of classical music recordings. Finally, the rules' performer specificity/generality is assessed by applying the induced rules to performances of the same pieces performed by two other professional jazz guitar players. Results show a consistency in the ornamentation patterns between Grant Green and the other two musicians, which may be interpreted as a good indicator for generality of the ornamentation rules

  20. Designing Green Stormwater Infrastructure for Hydrologic and Human Benefits: An Image Based Machine Learning Approach

    Science.gov (United States)

    Rai, A.; Minsker, B. S.

    2014-12-01

    Urbanization over the last century has degraded our natural water resources by increasing storm-water runoff, reducing nutrient retention, and creating poor ecosystem health downstream. The loss of tree canopy and expansion of impervious area and storm sewer systems have significantly decreased infiltration and evapotranspiration, increased stream-flow velocities, and increased flood risk. These problems have brought increasing attention to catchment-wide implementation of green infrastructure (e.g., decentralized green storm water management practices such as bioswales, rain gardens, permeable pavements, tree box filters, cisterns, urban wetlands, urban forests, stream buffers, and green roofs) to replace or supplement conventional storm water management practices and create more sustainable urban water systems. Current green infrastructure (GI) practice aims at mitigating the negative effects of urbanization by restoring pre-development hydrology and ultimately addressing water quality issues at an urban catchment scale. The benefits of green infrastructure extend well beyond local storm water management, as urban green spaces are also major contributors to human health. Considerable research in the psychological sciences have shown significant human health benefits from appropriately designed green spaces, yet impacts on human wellbeing have not yet been formally considered in GI design frameworks. This research is developing a novel computational green infrastructure (GI) design framework that integrates hydrologic requirements with criteria for human wellbeing. A supervised machine learning model is created to identify specific patterns in urban green spaces that promote human wellbeing; the model is linked to RHESSYS model to evaluate GI designs in terms of both hydrologic and human health benefits. An application of the models to Dead Run Watershed in Baltimore showed that image mining methods were able to capture key elements of human preferences that could