WorldWideScience

Sample records for machine translation techniques

  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. 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.

  3. 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.

  4. Machine Translation and Other Translation Technologies.

    Science.gov (United States)

    Melby, Alan

    1996-01-01

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

  5. 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.

  6. 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…

  7. 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...

  8. 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...

  9. 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,

  10. 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...

  11. On automatic machine translation evaluation

    Directory of Open Access Journals (Sweden)

    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

  12. Evaluating Arabic to English Machine Translation

    Directory of Open Access Journals (Sweden)

    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.

  13. 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....

  14. 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

  15. 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.

  16. 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

  17. 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...

  18. 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...

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

    Directory of Open Access Journals (Sweden)

    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.

  20. 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

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

    DEFF Research Database (Denmark)

    Carl, Michael; Schaeffer, Moritz

    2014-01-01

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

  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. 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.

  4. 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

  5. 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 ...

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

    Directory of Open Access Journals (Sweden)

    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.

  7. 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.

  8. 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

  9. 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

  10. Machine learning techniques in dialogue act recognition

    Directory of Open Access Journals (Sweden)

    Mark Fišel

    2007-05-01

    Full Text Available This report addresses dialogue acts, their existing applications and techniques of automatically recognizing them, in Estonia as well as elsewhere. Three main applications are described: in dialogue systems to determine the intention of the speaker, in dialogue systems with machine translation to resolve ambiguities in the possible translation variants and in speech recognition to reduce word recognition error rate. Several recognition techniques are described on the surface level: how they work and how they are trained. A summary of the corresponding representation methods is provided for each technique. The paper also includes examples of applying the techniques to dialogue act recognition.The author comes to the conclusion that using the current evaluation metric it is impossible to compare dialogue act recognition techniques when these are applied to different dialogue act tag sets. Dialogue acts remain an open research area, with space and need for developing new recognition techniques and methods of evaluation.

  11. 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.

  12. 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

  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. 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.

  15. 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.

  16. 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%.

  17. 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

  18. 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...

  19. 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...

  20. 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 ...

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

    Directory of Open Access Journals (Sweden)

    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.

  2. 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

  3. 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…

  4. 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

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

    Directory of Open Access Journals (Sweden)

    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.

  6. 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.

  7. On Translatability of Metaphors and Relevant Translating Techniques

    Institute of Scientific and Technical Information of China (English)

    邱采真; 张文普

    2012-01-01

    Metaphor is one of the most poetic forms of language.It is widely used in daily life and good translation of it is of great significance.In spite of the cultural and lingual hindrance,to some extent,good translation of metaphors can be achieved because of the similarities between two cultures and the overlaps of two languages.This paper explores translatability of metaphores from cultural and linguistic perspectives as well as specific techniques in terms of metaphor translation.

  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 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 ...

  10. 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…

  11. 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…

  12. 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…

  13. 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…

  14. 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...

  15. 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...

  16. 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...

  17. 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.

  18. 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...

  19. 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.

  20. Machine Translation Using Constraint-Based Synchronous Grammar

    Institute of Scientific and Technical Information of China (English)

    WONG Fai; DONG Mingchui; HU Dongcheng

    2006-01-01

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

  1. English to Sanskrit Machine Translation Using Transfer Based approach

    Science.gov (United States)

    Pathak, Ganesh R.; Godse, Sachin P.

    2010-11-01

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

  2. 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.

  3. 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....

  4. 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.

  5. 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.

  6. 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

  7. 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...

  8. 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.

  9. 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...

  10. 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.

  11. 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.

  12. 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...

  13. 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.

  14. 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

  15. 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

  16. On the Techniques of Journalistic Text Translation

    Institute of Scientific and Technical Information of China (English)

    林燕

    2015-01-01

    With the development of economy globalization,the translation of journalistic text has become increasingly important to cultural exchanges or economy communication among different countries. This paper briefly introduces the characteristics of news text and provides some feasible techniques for translation from English to Chinese or Chinese to English based on the case study.

  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...... 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...

  18. 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.

  19. Machine learning techniques in optical communication

    DEFF Research Database (Denmark)

    Zibar, Darko; Piels, Molly; Jones, Rasmus Thomas

    2015-01-01

    Techniques from the machine learning community are reviewed and employed for laser characterization, signal detection in the presence of nonlinear phase noise, and nonlinearity mitigation. Bayesian filtering and expectation maximization are employed within nonlinear state-space framework...

  20. Machine learning techniques in optical communication

    DEFF Research Database (Denmark)

    Zibar, Darko; Piels, Molly; Jones, Rasmus Thomas

    2016-01-01

    Machine learning techniques relevant for nonlinearity mitigation, carrier recovery, and nanoscale device characterization are reviewed and employed. Markov Chain Monte Carlo in combination with Bayesian filtering is employed within the nonlinear state-space framework and demonstrated for parameter...

  1. Special techniques in ultra-precision machining

    Science.gov (United States)

    Li, Li; Min, Xu; Chen, Dong; Wang, JunHua

    2007-12-01

    As the development of ultra-precision machining, the SPDT (single point diamond turning) was applied for the manufacture of a variety of optical components for its high precision , versatility and lower manufacturing cost. Whereas, the improvement of ultra-precision machining is not only related to the most topnotch equipments in the world but also closely linked to the special techniques in the ultra-precision Machining. Therefore, the industrialization and marketization of the ultra-precision machining will not be realized without these special techniques. This paper introduces the principle, trait and application of some important special techniques which can match the SPDT efficaciously, they are FTS, STS, SSS, ACT, VQ, LADT and UADT techniques.

  2. 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.

  3. Machine Learning Techniques in Clinical Vision Sciences.

    Science.gov (United States)

    Caixinha, Miguel; Nunes, Sandrina

    2017-01-01

    This review presents and discusses the contribution of machine learning techniques for diagnosis and disease monitoring in the context of clinical vision science. Many ocular diseases leading to blindness can be halted or delayed when detected and treated at its earliest stages. With the recent developments in diagnostic devices, imaging and genomics, new sources of data for early disease detection and patients' management are now available. Machine learning techniques emerged in the biomedical sciences as clinical decision-support techniques to improve sensitivity and specificity of disease detection and monitoring, increasing objectively the clinical decision-making process. This manuscript presents a review in multimodal ocular disease diagnosis and monitoring based on machine learning approaches. In the first section, the technical issues related to the different machine learning approaches will be present. Machine learning techniques are used to automatically recognize complex patterns in a given dataset. These techniques allows creating homogeneous groups (unsupervised learning), or creating a classifier predicting group membership of new cases (supervised learning), when a group label is available for each case. To ensure a good performance of the machine learning techniques in a given dataset, all possible sources of bias should be removed or minimized. For that, the representativeness of the input dataset for the true population should be confirmed, the noise should be removed, the missing data should be treated and the data dimensionally (i.e., the number of parameters/features and the number of cases in the dataset) should be adjusted. The application of machine learning techniques in ocular disease diagnosis and monitoring will be presented and discussed in the second section of this manuscript. To show the clinical benefits of machine learning in clinical vision sciences, several examples will be presented in glaucoma, age-related macular degeneration

  4. 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...

  5. 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...

  6. 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%.

  7. 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...

  8. Nontraditional manufacturing technique-Nano machining technique based on SPM

    Institute of Scientific and Technical Information of China (English)

    DONG; Shen; YAN; Yongda; SUN; Tao; LIANG; Yingchun; CHENG

    2004-01-01

    Nano machining based on SPM is a novel, nontraditional advanced manufacturing technique. There are three main machining methods based on SPM, i.e.single atom manipulation, surface modification using physical or chemical actions and mechanical scratching. The current development of this technique is summarized. Based on the analysis of mechanical scratching mechanism, a 5 μm micro inflation hole is fabricated on the surface of inertial confinement fusion (ICF) target. The processing technique is optimized. The machining properties of brittle material, single crystal Ge, are investigated. A micro machining system combining SPM and a high accuracy stage is developed. Some 2D and 3D microstructures are fabricated using the system. This method has broad applications in the field of nano machining.

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

    Directory of Open Access Journals (Sweden)

    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.

  10. 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.

  11. 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.

  12. Principles and techniques for designing precision machines

    Energy Technology Data Exchange (ETDEWEB)

    Hale, L C

    1999-02-01

    This thesis is written to advance the reader's knowledge of precision-engineering principles and their application to designing machines that achieve both sufficient precision and minimum cost. It provides the concepts and tools necessary for the engineer to create new precision machine designs. Four case studies demonstrate the principles and showcase approaches and solutions to specific problems that generally have wider applications. These come from projects at the Lawrence Livermore National Laboratory in which the author participated: the Large Optics Diamond Turning Machine, Accuracy Enhancement of High- Productivity Machine Tools, the National Ignition Facility, and Extreme Ultraviolet Lithography. Although broad in scope, the topics go into sufficient depth to be useful to practicing precision engineers and often fulfill more academic ambitions. The thesis begins with a chapter that presents significant principles and fundamental knowledge from the Precision Engineering literature. Following this is a chapter that presents engineering design techniques that are general and not specific to precision machines. All subsequent chapters cover specific aspects of precision machine design. The first of these is Structural Design, guidelines and analysis techniques for achieving independently stiff machine structures. The next chapter addresses dynamic stiffness by presenting several techniques for Deterministic Damping, damping designs that can be analyzed and optimized with predictive results. Several chapters present a main thrust of the thesis, Exact-Constraint Design. A main contribution is a generalized modeling approach developed through the course of creating several unique designs. The final chapter is the primary case study of the thesis, the Conceptual Design of a Horizontal Machining Center.

  13. MACHINE LEARNING TECHNIQUES USED IN BIG DATA

    Directory of Open Access Journals (Sweden)

    STEFANIA LOREDANA NITA

    2016-07-01

    Full Text Available The classical tools used in data analysis are not enough in order to benefit of all advantages of big data. The amount of information is too large for a complete investigation, and the possible connections and relations between data could be missed, because it is difficult or even impossible to verify all assumption over the information. Machine learning is a great solution in order to find concealed correlations or relationships between data, because it runs at scale machine and works very well with large data sets. The more data we have, the more the machine learning algorithm is useful, because it “learns” from the existing data and applies the found rules on new entries. In this paper, we present some machine learning algorithms and techniques used in big data.

  14. 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.

  15. 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...

  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. The translating techniques analyzation of Oliver Twist

    Institute of Scientific and Technical Information of China (English)

    Ding Ran

    2014-01-01

    In order to deeply understanding the translation methods and further improving translation skil s, the article provides notions of Translation methods with examples form the translating version by Mr.Rong from shanghai.

  18. 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

  19. 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.

  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. Machine learning techniques and drug design.

    Science.gov (United States)

    Gertrudes, J C; Maltarollo, V G; Silva, R A; Oliveira, P R; Honório, K M; da Silva, A B F

    2012-01-01

    The interest in the application of machine learning techniques (MLT) as drug design tools is growing in the last decades. The reason for this is related to the fact that the drug design is very complex and requires the use of hybrid techniques. A brief review of some MLT such as self-organizing maps, multilayer perceptron, bayesian neural networks, counter-propagation neural network and support vector machines is described in this paper. A comparison between the performance of the described methods and some classical statistical methods (such as partial least squares and multiple linear regression) shows that MLT have significant advantages. Nowadays, the number of studies in medicinal chemistry that employ these techniques has considerably increased, in particular the use of support vector machines. The state of the art and the future trends of MLT applications encompass the use of these techniques to construct more reliable QSAR models. The models obtained from MLT can be used in virtual screening studies as well as filters to develop/discovery new chemicals. An important challenge in the drug design field is the prediction of pharmacokinetic and toxicity properties, which can avoid failures in the clinical phases. Therefore, this review provides a critical point of view on the main MLT and shows their potential ability as a valuable tool in drug design.

  3. 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.

  4. 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 ...

  5. 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.

  6. 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

  7. 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…

  8. 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...

  9. 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

  10. 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.

  11. Virtual Machine Monitor Indigenous Memory Reclamation Technique

    Directory of Open Access Journals (Sweden)

    Muhammad Shams Ul Haq

    2016-04-01

    Full Text Available Sandboxing is a mechanism to monitor and control the execution of malicious or untrusted program. Memory overhead incurred by sandbox solutions is one of bottleneck for sandboxing most of applications in a system. Memory reclamation techniques proposed for traditional full virtualization do not suit sandbox environment due to lack of full scale guest operating system in sandbox. In this paper, we propose memory reclamation technique for sandboxed applications. The proposed technique indigenously works in virtual machine monitor layer without installing any driver in VMX non root mode and without new communication channel with host kernel. Proposed Page reclamation algorithm is a simple modified form of Least recently used page reclamation and Working set page reclamation algorithms. For efficiently collecting working set of application, we use a hardware virtualization extension, page Modification logging introduced by Intel. We implemented proposed technique with one of open source sandboxes to show effectiveness of proposed memory reclamation method. Experimental results show that proposed technique successfully reclaim up to 11% memory from sandboxed applications with negligible CPU overheads

  12. 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.

  13. Optimization of machining techniques – A retrospective and literature review

    Indian Academy of Sciences (India)

    Aman Aggarwal; Hari Singh

    2005-12-01

    In this paper an attempt is made to review the literature on optimizing machining parameters in turning processes. Various conventional techniques employed for machining optimization include geometric programming, geometric plus linear programming, goal programming, sequential unconstrained minimizationtechnique, dynamic programming etc. The latest techniques for optimization include fuzzy logic, scatter search technique, genetic algorithm, Taguchi technique and response surface methodology.

  14. 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.

  15. 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…

  16. 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…

  17. 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...

  18. 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.

  19. 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

  20. 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…

  1. 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…

  2. 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

  3. 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...

  4. 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…

  5. The relevance vector machine technique for channel equalization application

    OpenAIRE

    Chen, S.; Gunn, S.R.; Harris, C J

    2001-01-01

    The recently introduced relevance vector machine (RVM) technique is applied to communication channel equalization. It is demonstrated that the RVM equalizer can closely match the optimal performance of the Bayesian equalizer, with a much sparser kernel representation than that is achievable by the state-of-art support vector machine (SVM) technique.

  6. 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.

  7. BENCHMARKING MACHINE LEARNING TECHNIQUES FOR SOFTWARE DEFECT DETECTION

    Directory of Open Access Journals (Sweden)

    Saiqa Aleem

    2015-06-01

    Full Text Available Machine Learning approaches are good in solving problems that have less information. In most cases, the software domain problems characterize as a process of learning that depend on the various circumstances and changes accordingly. A predictive model is constructed by using machine learning approaches and classified them into defective and non-defective modules. Machine learning techniques help developers to retrieve useful information after the classification and enable them to analyse data from different perspectives. Machine learning techniques are proven to be useful in terms of software bug prediction. This study used public available data sets of software modules and provides comparative performance analysis of different machine learning techniques for software bug prediction. Results showed most of the machine learning methods performed well on software bug datasets.

  8. Micro machining techniques commonly used in manufacturing field

    Directory of Open Access Journals (Sweden)

    Adem Çiçek

    2011-06-01

    Full Text Available Developing technology and the need for high-precision parts in manufacturing industry has revealed the micro-machining. Machine tools and work pieces are miniaturized through micro-machining, materials and power consumption reduced to a minimum level. High productiveness in the use of resources and time can be obtained through this rapidly growing industry around the world. In this paper, different micro-machining techniques have been classified revising the investigations recently performed in the field of micro-machining and discussed their contributions to manufacturing process.

  9. 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.

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

    DEFF Research Database (Denmark)

    Gnad, Florian; Ren, Shubin; Choudhary, Chunaram

    2010-01-01

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

  11. Machine learning approximation techniques using dual trees

    OpenAIRE

    Ergashbaev, Denis

    2015-01-01

    This master thesis explores a dual-tree framework as applied to a particular class of machine learning problems that are collectively referred to as generalized n-body problems. It builds a new algorithm on top of it and improves existing Boosted OGE classifier.

  12. 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

  13. 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.

  14. 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...

  15. 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

  16. 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

  17. 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.

  18. 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...

  19. Modelling tick abundance using machine learning techniques and satellite imagery

    DEFF Research Database (Denmark)

    Kjær, Lene Jung; Korslund, L.; Kjelland, V.

    satellite images to run Boosted Regression Tree machine learning algorithms to predict overall distribution (presence/absence of ticks) and relative tick abundance of nymphs and larvae in southern Scandinavia. For nymphs, the predicted abundance had a positive correlation with observed abundance...... the predicted distribution of larvae was mostly even throughout Denmark, it was primarily around the coastlines in Norway and Sweden. Abundance was fairly low overall except in some fragmented patches corresponding to forested habitats in the region. Machine learning techniques allow us to predict for larger...... the collected ticks for pathogens and using the same machine learning techniques to develop prevalence maps of the ScandTick region....

  20. Comparison of Machine Learning Techniques for Target Detection

    NARCIS (Netherlands)

    Vink, J.P.; Haan, G. de

    2013-01-01

    This paper focuses on machine learning techniques for real-time detection. Although many supervised learning techniques have been described in the literature, no technique always performs best. Several comparative studies are available, but have not always been performedcarefully, leading to invalid

  1. Comparison of Machine Learning Techniques for Target Detection

    NARCIS (Netherlands)

    Vink, J.P.; Haan, G. de

    2013-01-01

    This paper focuses on machine learning techniques for real-time detection. Although many supervised learning techniques have been described in the literature, no technique always performs best. Several comparative studies are available, but have not always been performedcarefully, leading to invalid

  2. 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.

  3. 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

  4. 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…

  5. 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…

  6. 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 ...

  7. 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…

  8. 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.

  9. 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.

  10. Translation techniques for distributed-shared memory programming models

    Energy Technology Data Exchange (ETDEWEB)

    Fuller, Douglas James [Iowa State Univ., Ames, IA (United States)

    2005-01-01

    The high performance computing community has experienced an explosive improvement in distributed-shared memory hardware. Driven by increasing real-world problem complexity, this explosion has ushered in vast numbers of new systems. Each new system presents new challenges to programmers and application developers. Part of the challenge is adapting to new architectures with new performance characteristics. Different vendors release systems with widely varying architectures that perform differently in different situations. Furthermore, since vendors need only provide a single performance number (total MFLOPS, typically for a single benchmark), they only have strong incentive initially to optimize the API of their choice. Consequently, only a fraction of the available APIs are well optimized on most systems. This causes issues porting and writing maintainable software, let alone issues for programmers burdened with mastering each new API as it is released. Also, programmers wishing to use a certain machine must choose their API based on the underlying hardware instead of the application. This thesis argues that a flexible, extensible translator for distributed-shared memory APIs can help address some of these issues. For example, a translator might take as input code in one API and output an equivalent program in another. Such a translator could provide instant porting for applications to new systems that do not support the application's library or language natively. While open-source APIs are abundant, they do not perform optimally everywhere. A translator would also allow performance testing using a single base code translated to a number of different APIs. Most significantly, this type of translator frees programmers to select the most appropriate API for a given application based on the application (and developer) itself instead of the underlying hardware.

  11. Translation techniques for distributed-shared memory programming models

    Energy Technology Data Exchange (ETDEWEB)

    Fuller, Douglas James

    2005-08-01

    The high performance computing community has experienced an explosive improvement in distributed-shared memory hardware. Driven by increasing real-world problem complexity, this explosion has ushered in vast numbers of new systems. Each new system presents new challenges to programmers and application developers. Part of the challenge is adapting to new architectures with new performance characteristics. Different vendors release systems with widely varying architectures that perform differently in different situations. Furthermore, since vendors need only provide a single performance number (total MFLOPS, typically for a single benchmark), they only have strong incentive initially to optimize the API of their choice. Consequently, only a fraction of the available APIs are well optimized on most systems. This causes issues porting and writing maintainable software, let alone issues for programmers burdened with mastering each new API as it is released. Also, programmers wishing to use a certain machine must choose their API based on the underlying hardware instead of the application. This thesis argues that a flexible, extensible translator for distributed-shared memory APIs can help address some of these issues. For example, a translator might take as input code in one API and output an equivalent program in another. Such a translator could provide instant porting for applications to new systems that do not support the application's library or language natively. While open-source APIs are abundant, they do not perform optimally everywhere. A translator would also allow performance testing using a single base code translated to a number of different APIs. Most significantly, this type of translator frees programmers to select the most appropriate API for a given application based on the application (and developer) itself instead of the underlying hardware.

  12. 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.

  13. 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.

  14. Analysing CMS transfers using Machine Learning techniques

    CERN Document Server

    Diotalevi, Tommaso

    2016-01-01

    LHC experiments transfer more than 10 PB/week between all grid sites using the FTS transfer service. In particular, CMS manages almost 5 PB/week of FTS transfers with PhEDEx (Physics Experiment Data Export). FTS sends metrics about each transfer (e.g. transfer rate, duration, size) to a central HDFS storage at CERN. The work done during these three months, here as a Summer Student, involved the usage of ML techniques, using a CMS framework called DCAFPilot, to process this new data and generate predictions of transfer latencies on all links between Grid sites. This analysis will provide, as a future service, the necessary information in order to proactively identify and maybe fix latency issued transfer over the WLCG.

  15. Machine Learning Techniques in Optimal Design

    Science.gov (United States)

    Cerbone, Giuseppe

    1992-01-01

    Many important applications can be formalized as constrained optimization tasks. For example, we are studying the engineering domain of two-dimensional (2-D) structural design. In this task, the goal is to design a structure of minimum weight that bears a set of loads. A solution to a design problem in which there is a single load (L) and two stationary support points (S1 and S2) consists of four members, E1, E2, E3, and E4 that connect the load to the support points is discussed. In principle, optimal solutions to problems of this kind can be found by numerical optimization techniques. However, in practice [Vanderplaats, 1984] these methods are slow and they can produce different local solutions whose quality (ratio to the global optimum) varies with the choice of starting points. Hence, their applicability to real-world problems is severely restricted. To overcome these limitations, we propose to augment numerical optimization by first performing a symbolic compilation stage to produce: (a) objective functions that are faster to evaluate and that depend less on the choice of the starting point and (b) selection rules that associate problem instances to a set of recommended solutions. These goals are accomplished by successive specializations of the problem class and of the associated objective functions. In the end, this process reduces the problem to a collection of independent functions that are fast to evaluate, that can be differentiated symbolically, and that represent smaller regions of the overall search space. However, the specialization process can produce a large number of sub-problems. This is overcome by deriving inductively selection rules which associate problems to small sets of specialized independent sub-problems. Each set of candidate solutions is chosen to minimize a cost function which expresses the tradeoff between the quality of the solution that can be obtained from the sub-problem and the time it takes to produce it. The overall solution

  16. 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

  17. Memory Based Machine Intelligence Techniques in VLSI hardware

    OpenAIRE

    James, Alex Pappachen

    2012-01-01

    We briefly introduce the memory based approaches to emulate machine intelligence in VLSI hardware, describing the challenges and advantages. Implementation of artificial intelligence techniques in VLSI hardware is a practical and difficult problem. Deep architectures, hierarchical temporal memories and memory networks are some of the contemporary approaches in this area of research. The techniques attempt to emulate low level intelligence tasks and aim at providing scalable solutions to high ...

  18. Memory Based Machine Intelligence Techniques in VLSI hardware

    CERN Document Server

    James, Alex Pappachen

    2012-01-01

    We briefly introduce the memory based approaches to emulate machine intelligence in VLSI hardware, describing the challenges and advantages. Implementation of artificial intelligence techniques in VLSI hardware is a practical and difficult problem. Deep architectures, hierarchical temporal memories and memory networks are some of the contemporary approaches in this area of research. The techniques attempt to emulate low level intelligence tasks and aim at providing scalable solutions to high level intelligence problems such as sparse coding and contextual processing.

  19. Using WSD Techniques for Lexical Selection in Statistical Machine Translation

    Science.gov (United States)

    2005-07-01

    Vih b...YKVml ¨ { hWY-p ` ] bd© jrYK\\ b ] ` YKR c_b ]_t�hfmxtj b ^_YITB\\ihT|hWYLml¥h ` Y7T Vih \\!hTh b \\ih b pKTR ª\\!ws\\ihWY-q«hfm � TVi^ XZY...YQ\\ihWThWY mleh ` Y¢T Vih b ]?\\ihWTh b \\ih b p�TR ­�Y¡ t_¡ ­Ŗp ` T]r^43eY-w z "" 6587msY ` ]?Y-h<TR¤¡ z "" 95 TVfp-jµT]_^ ¨

  20. 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

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

    Directory of Open Access Journals (Sweden)

    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

  2. Translating the research in insulin injection technique: implications for practice.

    Science.gov (United States)

    Saltiel-Berzin, Rita; Cypress, Marjorie; Gibney, Michael

    2012-01-01

    Glucose variability leading to suboptimal glycemic control is common among people using injection therapies. Advanced technology and new studies have identified important issues related to injection technique: needle length and gauge, body mass index, skin and subcutaneous tissue thickness, adequate resuspension of cloudy insulins, leakage, choice of injection site and rotation, pinching a skinfold, and lipohypertrophy. All these issues can affect pain and bruising, insulin absorption, and blood glucose levels. The purpose of this article is to review current and past research regarding insulin injection therapy and to provide practical, translational information regarding injection technique, teaching/learning techniques specific to insulin administration, and implications for diabetes self-management education and support. International injection recommendations for patients with diabetes have recently been published and have identified specific recommendations for health care professionals. This article provides an evidence-based translational and practical review of the research regarding injection technique and teaching/learning theory. Diabetes educators need to reevaluate how they provide instruction for the administration of insulin and other injectable medications. Research regarding skin and subcutaneous thickness reveals that shorter needles may be appropriate for the majority of patients regardless of body mass index. Periodic reassessment of injection technique, including suspension of cloudy insulins and inspection of injection sites for lipohypertrophy, is a critical aspect of the role of the diabetes educator. An injection checklist is provided as a guide for diabetes educators.

  3. 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.

  4. 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,…

  5. Data mining practical machine learning tools and techniques

    CERN Document Server

    Witten, Ian H

    2005-01-01

    As with any burgeoning technology that enjoys commercial attention, the use of data mining is surrounded by a great deal of hype. Exaggerated reports tell of secrets that can be uncovered by setting algorithms loose on oceans of data. But there is no magic in machine learning, no hidden power, no alchemy. Instead there is an identifiable body of practical techniques that can extract useful information from raw data. This book describes these techniques and shows how they work. The book is a major revision of the first edition that appeared in 1999. While the basic core remains the same

  6. 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.

  7. 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.

  8. 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.

  9. Decision Support System for Diabetes Mellitus through Machine Learning Techniques

    Directory of Open Access Journals (Sweden)

    Tarik A. Rashid

    2016-07-01

    Full Text Available recently, the diseases of diabetes mellitus have grown into extremely feared problems that can have damaging effects on the health condition of their sufferers globally. In this regard, several machine learning models have been used to predict and classify diabetes types. Nevertheless, most of these models attempted to solve two problems; categorizing patients in terms of diabetic types and forecasting blood surge rate of patients. This paper presents an automatic decision support system for diabetes mellitus through machine learning techniques by taking into account the above problems, plus, reflecting the skills of medical specialists who believe that there is a great relationship between patient’s symptoms with some chronic diseases and the blood sugar rate. Data sets are collected from Layla Qasim Clinical Center in Kurdistan Region, then, the data is cleaned and proposed using feature selection techniques such as Sequential Forward Selection and the Correlation Coefficient, finally, the refined data is fed into machine learning models for prediction, classification, and description purposes. This system enables physicians and doctors to provide diabetes mellitus (DM patients good health treatments and recommendations.

  10. 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.

  11. Analysis of Machine Learning Techniques for Heart Failure Readmissions.

    Science.gov (United States)

    Mortazavi, Bobak J; Downing, Nicholas S; Bucholz, Emily M; Dharmarajan, Kumar; Manhapra, Ajay; Li, Shu-Xia; Negahban, Sahand N; Krumholz, Harlan M

    2016-11-01

    The current ability to predict readmissions in patients with heart failure is modest at best. It is unclear whether machine learning techniques that address higher dimensional, nonlinear relationships among variables would enhance prediction. We sought to compare the effectiveness of several machine learning algorithms for predicting readmissions. Using data from the Telemonitoring to Improve Heart Failure Outcomes trial, we compared the effectiveness of random forests, boosting, random forests combined hierarchically with support vector machines or logistic regression (LR), and Poisson regression against traditional LR to predict 30- and 180-day all-cause readmissions and readmissions because of heart failure. We randomly selected 50% of patients for a derivation set, and a validation set comprised the remaining patients, validated using 100 bootstrapped iterations. We compared C statistics for discrimination and distributions of observed outcomes in risk deciles for predictive range. In 30-day all-cause readmission prediction, the best performing machine learning model, random forests, provided a 17.8% improvement over LR (mean C statistics, 0.628 and 0.533, respectively). For readmissions because of heart failure, boosting improved the C statistic by 24.9% over LR (mean C statistic 0.678 and 0.543, respectively). For 30-day all-cause readmission, the observed readmission rates in the lowest and highest deciles of predicted risk with random forests (7.8% and 26.2%, respectively) showed a much wider separation than LR (14.2% and 16.4%, respectively). Machine learning methods improved the prediction of readmission after hospitalization for heart failure compared with LR and provided the greatest predictive range in observed readmission rates. © 2016 American Heart Association, Inc.

  12. Dropout Prediction in E-Learning Courses through the Combination of Machine Learning Techniques

    Science.gov (United States)

    Lykourentzou, Ioanna; Giannoukos, Ioannis; Nikolopoulos, Vassilis; Mpardis, George; Loumos, Vassili

    2009-01-01

    In this paper, a dropout prediction method for e-learning courses, based on three popular machine learning techniques and detailed student data, is proposed. The machine learning techniques used are feed-forward neural networks, support vector machines and probabilistic ensemble simplified fuzzy ARTMAP. Since a single technique may fail to…

  13. Dropout Prediction in E-Learning Courses through the Combination of Machine Learning Techniques

    Science.gov (United States)

    Lykourentzou, Ioanna; Giannoukos, Ioannis; Nikolopoulos, Vassilis; Mpardis, George; Loumos, Vassili

    2009-01-01

    In this paper, a dropout prediction method for e-learning courses, based on three popular machine learning techniques and detailed student data, is proposed. The machine learning techniques used are feed-forward neural networks, support vector machines and probabilistic ensemble simplified fuzzy ARTMAP. Since a single technique may fail to…

  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. Development of an evaluation technique for human-machine interface

    Energy Technology Data Exchange (ETDEWEB)

    Min, Dae Hwan; Koo, Sang Hui; Ahn, Won Yeong; Ryu, Yeong Shin [Korea Univ., Seoul (Korea, Republic of)

    1997-07-15

    The purpose of this study is two-fold : firstly to establish an evaluation technique for HMI(Human Machine Interface) in NPPs(Nuclear Power Plants) and secondly to develop an architecture of a support system which can be used for the evaluation of HMI. In order to establish an evaluation technique, this study conducted literature review on basic theories of cognitive science studies and summarized the cognitive characteristics of humans. This study also surveyed evaluation techniques of HMI in general, and reviewed studies on the evaluation of HMI in NPPs. On the basis of this survey, the study established a procedure for the evaluation of HMI in NPPs in Korea and laid a foundation for empirical verification.

  16. Waveform interative techniques for device transient simulation on parallel machines

    Energy Technology Data Exchange (ETDEWEB)

    Lumsdaine, A. [Univ. of Notre Dame, IN (United States); Reichelt, M.W. [Massachusetts Institute of Technology, Cambridge, MA (United States)

    1993-12-31

    In this paper we describe our experiences with parallel implementations of several different waveform algorithms for performing transient simulation of semiconductor devices. Because of their inherent computation and communication structure, waveform methods are well suited to MIMD-type parallel machines having a high communication latency - such as a cluster of workstations. Experimental results using pWORDS, a parallel waveform-based device transient simulation program, in conjunction with PVM running on a cluster of eight workstations demonstrate that parallel waveform techniques are an efficient and faster alternative to standard simulation algorithms.

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

    Directory of Open Access Journals (Sweden)

    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.

  18. Resistance gene identification from Larimichthys crocea with machine learning techniques

    Science.gov (United States)

    Cai, Yinyin; Liao, Zhijun; Ju, Ying; Liu, Juan; Mao, Yong; Liu, Xiangrong

    2016-12-01

    The research on resistance genes (R-gene) plays a vital role in bioinformatics as it has the capability of coping with adverse changes in the external environment, which can form the corresponding resistance protein by transcription and translation. It is meaningful to identify and predict R-gene of Larimichthys crocea (L.Crocea). It is friendly for breeding and the marine environment as well. Large amounts of L.Crocea’s immune mechanisms have been explored by biological methods. However, much about them is still unclear. In order to break the limited understanding of the L.Crocea’s immune mechanisms and to detect new R-gene and R-gene-like genes, this paper came up with a more useful combination prediction method, which is to extract and classify the feature of available genomic data by machine learning. The effectiveness of feature extraction and classification methods to identify potential novel R-gene was evaluated, and different statistical analyzes were utilized to explore the reliability of prediction method, which can help us further understand the immune mechanisms of L.Crocea against pathogens. In this paper, a webserver called LCRG-Pred is available at http://server.malab.cn/rg_lc/.

  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. 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.

  1. 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 ...

  2. Modern machine learning techniques and their applications in cartoon animation research

    CERN Document Server

    Yu, Jun

    2013-01-01

    The integration of machine learning techniques and cartoon animation research is fast becoming a hot topic. This book helps readers learn the latest machine learning techniques, including patch alignment framework; spectral clustering, graph cuts, and convex relaxation; ensemble manifold learning; multiple kernel learning; multiview subspace learning; and multiview distance metric learning. It then presents the applications of these modern machine learning techniques in cartoon animation research. With these techniques, users can efficiently utilize the cartoon materials to generate animations

  3. Estimation of Alpine Skier Posture Using Machine Learning Techniques

    Directory of Open Access Journals (Sweden)

    Bojan Nemec

    2014-10-01

    Full Text Available High precision Global Navigation Satellite System (GNSS measurements are becoming more and more popular in alpine skiing due to the relatively undemanding setup and excellent performance. However, GNSS provides only single-point measurements that are defined with the antenna placed typically behind the skier’s neck. A key issue is how to estimate other more relevant parameters of the skier’s body, like the center of mass (COM and ski trajectories. Previously, these parameters were estimated by modeling the skier’s body with an inverted-pendulum model that oversimplified the skier’s body. In this study, we propose two machine learning methods that overcome this shortcoming and estimate COM and skis trajectories based on a more faithful approximation of the skier’s body with nine degrees-of-freedom. The first method utilizes a well-established approach of artificial neural networks, while the second method is based on a state-of-the-art statistical generalization method. Both methods were evaluated using the reference measurements obtained on a typical giant slalom course and compared with the inverted-pendulum method. Our results outperform the results of commonly used inverted-pendulum methods and demonstrate the applicability of machine learning techniques in biomechanical measurements of alpine skiing.

  4. Classification of Phishing Email Using Random Forest Machine Learning Technique

    Directory of Open Access Journals (Sweden)

    Andronicus A. Akinyelu

    2014-01-01

    Full Text Available Phishing is one of the major challenges faced by the world of e-commerce today. Thanks to phishing attacks, billions of dollars have been lost by many companies and individuals. In 2012, an online report put the loss due to phishing attack at about $1.5 billion. This global impact of phishing attacks will continue to be on the increase and thus requires more efficient phishing detection techniques to curb the menace. This paper investigates and reports the use of random forest machine learning algorithm in classification of phishing attacks, with the major objective of developing an improved phishing email classifier with better prediction accuracy and fewer numbers of features. From a dataset consisting of 2000 phishing and ham emails, a set of prominent phishing email features (identified from the literature were extracted and used by the machine learning algorithm with a resulting classification accuracy of 99.7% and low false negative (FN and false positive (FP rates.

  5. Improving Alzheimer's disease diagnosis with machine learning techniques.

    Science.gov (United States)

    Trambaiolli, Lucas R; Lorena, Ana C; Fraga, Francisco J; Kanda, Paulo A M; Anghinah, Renato; Nitrini, Ricardo

    2011-07-01

    There is not a specific test to diagnose Alzheimer's disease (AD). Its diagnosis should be based upon clinical history, neuropsychological and laboratory tests, neuroimaging and electroencephalography (EEG). Therefore, new approaches are necessary to enable earlier and more accurate diagnosis and to follow treatment results. In this study we used a Machine Learning (ML) technique, named Support Vector Machine (SVM), to search patterns in EEG epochs to differentiate AD patients from controls. As a result, we developed a quantitative EEG (qEEG) processing method for automatic differentiation of patients with AD from normal individuals, as a complement to the diagnosis of probable dementia. We studied EEGs from 19 normal subjects (14 females/5 males, mean age 71.6 years) and 16 probable mild to moderate symptoms AD patients (14 females/2 males, mean age 73.4 years. The results obtained from analysis of EEG epochs were accuracy 79.9% and sensitivity 83.2%. The analysis considering the diagnosis of each individual patient reached 87.0% accuracy and 91.7% sensitivity.

  6. Multilingual translation techniques in the analysis of narrative medical text.

    Science.gov (United States)

    Moore, G W; Polacsek, R A; Erozan, Y S; de la Monte, S M; Miller, R E; Hutchins, G M; Riede, U N

    1986-03-01

    The feasibility of computer translation of scientific and medical documents is controversial. This report describes a minicomputer-based translation system (TRANSOFT) that employs word order rearrangement followed by word-for-word translation and resolution of ambiguities based on context. This translation system was applied to an entire medical textbook written in German and to short medical texts written in French, Italian, Spanish and Turkish. Results suggest the versatility of TRANSOFT for narrowly defined translation problems. As foreign language medical documents and medical records become increasingly available in computer readable form through word processing, computerized typesetting and hospital information systems, computer translation methods may provide a rapid and inexpensive means of obtaining draft translations.

  7. 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.

  8. 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.

  9. Machine Learning Techniques in Diagnosis of Pulmonary Embolism

    Directory of Open Access Journals (Sweden)

    Goksu Berikol

    2016-04-01

    Full Text Available Aim: Pulmonary embolism (PE, is a high mortality disease which clinical suspicion and a variety of diagnostic laboratory and imagingresults have a high importance in diagnose. Anticoagulation and fybrinolytic treatments are hard to decide in some cases therefore early diagnose is important in emergency medicine.Material and Method: The study was designed retrospectively based on the records of the 201 patients who were presenting to Emergency Department with pulmonary complaints including dyspnea and chest pain between January 2010 and October 2013. Results: Machine learning techniques were used for calculating the success in diagnosing PE. The success rate of the classification tree method for detection of PE was 95%, which was higher than that of KNN classification (75% and Naive Bayes Classification (88.5%. Discussion: Classification tree and Bayesian method can be selected ones to diagnose or define possibility of pulmonary embolism in emergency centers with limited study tests and for the patients difficultly diagnosed.

  10. Short-term wind speed predictions with machine learning techniques

    Science.gov (United States)

    Ghorbani, M. A.; Khatibi, R.; FazeliFard, M. H.; Naghipour, L.; Makarynskyy, O.

    2016-02-01

    Hourly wind speed forecasting is presented by a modeling study with possible applications to practical problems including farming wind energy, aircraft safety and airport operations. Modeling techniques employed in this paper for such short-term predictions are based on the machine learning techniques of artificial neural networks (ANNs) and genetic expression programming (GEP). Recorded values of wind speed were used, which comprised 8 years of collected data at the Kersey site, Colorado, USA. The January data over the first 7 years (2005-2011) were used for model training; and the January data for 2012 were used for model testing. A number of model structures were investigated for the validation of the robustness of these two techniques. The prediction results were compared with those of a multiple linear regression (MLR) method and with the Persistence method developed for the data. The model performances were evaluated using the correlation coefficient, root mean square error, Nash-Sutcliffe efficiency coefficient and Akaike information criterion. The results indicate that forecasting wind speed is feasible using past records of wind speed alone, but the maximum lead time for the data was found to be 14 h. The results show that different techniques would lead to different results, where the choice between them is not easy. Thus, decision making has to be informed of these modeling results and decisions should be arrived at on the basis of an understanding of inherent uncertainties. The results show that both GEP and ANN are equally credible selections and even MLR should not be dismissed, as it has its uses.

  11. Translation Techniques of Reduplicated Words in Chinese Poems

    Institute of Scientific and Technical Information of China (English)

    张笑一

    2016-01-01

    Reduplicated words are used commonly as the rhetorical devices in ancient Chinese poems. Poets often use reduplicated words to add in the poetry works of rhythm and image in order to render the atmosphere and express feelings. Based on the analysis of common problems in the translation of reduplicated words in Chinese poems, the translation can be divided into two broad categories, the functional equivalence and semantic equivalence.

  12. Application of Krylov Reduction Technique for a Machine Tool Multibody Modelling

    Directory of Open Access Journals (Sweden)

    M. Sulitka

    2014-02-01

    Full Text Available Quick calculation of machine tool dynamic response represents one of the major requirements for machine tool virtual modelling and virtual machining, aiming at simulating the machining process performance, quality, and precision of a workpiece. Enhanced time effectiveness in machine tool dynamic simulations may be achieved by employing model order reduction (MOR techniques of the full finite element (FE models. The paper provides a case study aimed at comparison of Krylov subspace base and mode truncation technique. Application of both of the reduction techniques for creating a machine tool multibody model is evaluated. The Krylov subspace reduction technique shows high quality in terms of both dynamic properties of the reduced multibody model and very low time demands at the same time.

  13. Using machine learning techniques to differentiate acute coronary syndrome

    Directory of Open Access Journals (Sweden)

    Sougand Setareh

    2015-02-01

    Full Text Available Backgroud: Acute coronary syndrome (ACS is an unstable and dynamic process that includes unstable angina, ST elevation myocardial infarction, and non-ST elevation myocardial infarction. Despite recent technological advances in early diognosis of ACS, differentiating between different types of coronary diseases in the early hours of admission is controversial. The present study was aimed to accurately differentiate between various coronary events, using machine learning techniques. Such methods, as a subset of artificial intelligence, include algorithms that allow computers to learn and play a major role in treatment decisions. Methods: 1902 patients diagnosed with ACS and admitted to hospital were selected according to Euro Heart Survey on ACS. Patients were classified based on decision tree J48. Bagging aggregation algorithms was implemented to increase the efficiency of algorithm. Results: The performance of classifiers was estimated and compared based on their accuracy computed from confusion matrix. The accuracy rates of decision tree and bagging algorithm were calculated to be 91.74% and 92.53%, respectively. Conclusion: The proposed methods used in this study proved to have the ability to identify various ACS. In addition, using matrix of confusion, an acceptable number of subjects with acute coronary syndrome were identified in each class.

  14. DIAGNOSIS OF DIABETIC RETINOPATHY USING MACHINE LEARNING TECHNIQUES

    Directory of Open Access Journals (Sweden)

    R. Priya

    2013-07-01

    Full Text Available Diabetic retinopathy (DR is an eye disease caused by the complication of diabetes and we should detect it early for effective treatment. As diabetes progresses, the vision of a patient may start to deteriorate and lead to diabetic retinopathy. As a result, two groups were identified, namely non-proliferative diabetic retinopathy (NPDR and proliferative diabetic retinopathy (PDR. In this paper, to diagnose diabetic retinopathy, three models like Probabilistic Neural network (PNN, Bayesian Classification and Support vector machine (SVM are described and their performances are compared. The amount of the disease spread in the retina can be identified by extracting the features of the retina. The features like blood vessels, haemmoraghes of NPDR image and exudates of PDR image are extracted from the raw images using the image processing techniques and fed to the classifier for classification. A total of 350 fundus images were used, out of which 100 were used for training and 250 images were used for testing. Experimental results show that PNN has an accuracy of 89.6 % Bayes Classifier has an accuracy of 94.4% and SVM has an accuracy of 97.6%. This infers that the SVM model outperforms all other models. Also our system is also run on 130 images available from “DIARETDB0: Evaluation Database and Methodology for Diabetic Retinopathy” and the results show that PNN has an accuracy of 87.69% Bayes Classifier has an accuracy of 90.76% and SVM has an accuracy of 95.38%.

  15. Machine learning techniques for energy optimization in mobile embedded systems

    Science.gov (United States)

    Donohoo, Brad Kyoshi

    Mobile smartphones and other portable battery operated embedded systems (PDAs, tablets) are pervasive computing devices that have emerged in recent years as essential instruments for communication, business, and social interactions. While performance, capabilities, and design are all important considerations when purchasing a mobile device, a long battery lifetime is one of the most desirable attributes. Battery technology and capacity has improved over the years, but it still cannot keep pace with the power consumption demands of today's mobile devices. This key limiter has led to a strong research emphasis on extending battery lifetime by minimizing energy consumption, primarily using software optimizations. This thesis presents two strategies that attempt to optimize mobile device energy consumption with negligible impact on user perception and quality of service (QoS). The first strategy proposes an application and user interaction aware middleware framework that takes advantage of user idle time between interaction events of the foreground application to optimize CPU and screen backlight energy consumption. The framework dynamically classifies mobile device applications based on their received interaction patterns, then invokes a number of different power management algorithms to adjust processor frequency and screen backlight levels accordingly. The second strategy proposes the usage of machine learning techniques to learn a user's mobile device usage pattern pertaining to spatiotemporal and device contexts, and then predict energy-optimal data and location interface configurations. By learning where and when a mobile device user uses certain power-hungry interfaces (3G, WiFi, and GPS), the techniques, which include variants of linear discriminant analysis, linear logistic regression, non-linear logistic regression, and k-nearest neighbor, are able to dynamically turn off unnecessary interfaces at runtime in order to save energy.

  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. Development of techniques to enhance man/machine communication

    Science.gov (United States)

    Targ, R.; Cole, P.; Puthoff, H.

    1974-01-01

    A four-state random stimulus generator, considered to function as an ESP teaching machine was used to investigate an approach to facilitating interactions between man and machines. A subject tries to guess in which of four states the machine is. The machine offers the user feedback and reinforcement as to the correctness of his choice. Using this machine, 148 volunteer subjects were screened under various protocols. Several whose learning slope and/or mean score departed significantly from chance expectation were identified. Direct physiological evidence of perception of remote stimuli not presented to any known sense of the percipient using electroencephalographic (EEG) output when a light was flashed in a distant room was also studied.

  18. Wire electric-discharge machining and other fabrication techniques

    Science.gov (United States)

    Morgan, W. H.

    1983-01-01

    Wire electric discharge machining and extrude honing were used to fabricate a two dimensional wing for cryogenic wind tunnel testing. Electric-discharge cutting is done with a moving wire electrode. The cut track is controlled by means of a punched-tape program and the cutting feed is regulated according to the progress of the work. Electric-discharge machining involves no contact with the work piece, and no mechanical force is exerted. Extrude hone is a process for honing finish-machined surfaces by the extrusion of an abrasive material (silly putty), which is forced through a restrictive fixture. The fabrication steps are described and production times are given.

  19. SPAM CLASSIFICATION BASED ON SUPERVISED LEARNING USING MACHINE LEARNING TECHNIQUES

    Directory of Open Access Journals (Sweden)

    T. Hamsapriya

    2011-12-01

    Full Text Available E-mail is one of the most popular and frequently used ways of communication due to its worldwide accessibility, relatively fast message transfer, and low sending cost. The flaws in the e-mail protocols and the increasing amount of electronic business and financial transactions directly contribute to the increase in e-mail-based threats. Email spam is one of the major problems of the today’s Internet, bringing financial damage to companies and annoying individual users. Spam emails are invading users without their consent and filling their mail boxes. They consume more network capacity as well as time in checking and deleting spam mails. The vast majority of Internet users are outspoken in their disdain for spam, although enough of them respond to commercial offers that spam remains a viable source of income to spammers. While most of the users want to do right think to avoid and get rid of spam, they need clear and simple guidelines on how to behave. In spite of all the measures taken to eliminate spam, they are not yet eradicated. Also when the counter measures are over sensitive, even legitimate emails will be eliminated. Among the approaches developed to stop spam, filtering is the one of the most important technique. Many researches in spam filtering have been centered on the more sophisticated classifier-related issues. In recent days, Machine learning for spam classification is an important research issue. The effectiveness of the proposed work is explores and identifies the use of different learning algorithms for classifying spam messages from e-mail. A comparative analysis among the algorithms has also been presented.

  20. Cultural Dimensional Transformation Techniques of Hypotaxis and Parataxis in Tourist Publicity C-E Translation

    Institute of Scientific and Technical Information of China (English)

    肖付良

    2015-01-01

    In order to make foreign tourists familiar with China’s scenic spots, it is necessary that tourist publicity materials are properly translated. Cultural dimension, as one of the three key dimensions of eco-translatology, plays a very important role in translating. With its basis on cultural dimension of eco-translatology, this paper aims to present transformation techniques of parataxis and hypotaxis between Chinese and English. It is suggested that, with the cultural dimensional transformation tech-niques of parataxis and hypotaxis , translators should exert their subjectivity and creativity to achieve in maximizing the degree of holistic adaptation and selection for achieving successful translations.

  1. Application of Machine Vision Technique in Weed Identification

    Institute of Scientific and Technical Information of China (English)

    LIU Zhen-heng; ZHANG Chang-li; FANG Jun-long

    2004-01-01

    This paper mainly introduces some foreign research methods and fruits about weed identification by applying machine vision. This facet researches is lack in our country, this paper could be reference for domestic studies about weed identification.

  2. Machine learning techniques applied to system characterization and equalization

    DEFF Research Database (Denmark)

    Zibar, Darko; Thrane, Jakob; Wass, Jesper

    2016-01-01

    Linear signal processing algorithms are effective in combating linear fibre channel impairments. We demonstrate the ability of machine learning algorithms to combat nonlinear fibre channel impairments and perform parameter extraction from directly detected signals.......Linear signal processing algorithms are effective in combating linear fibre channel impairments. We demonstrate the ability of machine learning algorithms to combat nonlinear fibre channel impairments and perform parameter extraction from directly detected signals....

  3. 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...

  4. Survey of Mechatronic Techniques in Modern Machine Design

    Directory of Open Access Journals (Sweden)

    Devdas Shetty

    2012-01-01

    Full Text Available Increasing demands on the productivity of complex systems, such as manufacturing machines and their steadily growing technological importance will require the application of new methods in the product development process. A smart machine can make decisions about the process in real-time with plenty of adaptive controls. This paper shows the simulation based mechatronic model of a complex system with a better understanding of the dynamic behavior and interactions of the components. This offers improved possibilities of evaluating and optimizing the dynamic motion performance of the entire automated system in the early stages of the design process. Another effect is the growing influence of interactions between machine components on achievable machine dynamics and precision and quality of components. The examples cited in this paper, demonstrate the distinguishing feature of mechatronic systems through intensive integration. The case studies also show that it will no longer be sufficient to focus solely on the optimization of subsystems. Instead it will be necessary to strive for optimization of the complete system. The interactions between machine components, the influence of the control system and the machining process will have to be considered during the design process and the coordination of feed drives and frame structure components.

  5. The English Translation Strategies and Techniques of the Names of Tour-ist Attractions in Xi’an

    Institute of Scientific and Technical Information of China (English)

    TAO Pan

    2015-01-01

    In the translation of tourist materials, the translation of the names is the primary part. This paper aims to analyze the translation strategies and translation techniques of the names of tourist attractions. At the same time, it is aimed at awakening the cross-cultural awareness of translators and spread the distinctive culture of Xi ’an.

  6. 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.

  7. MUMAL: Multivariate analysis in shotgun proteomics using machine learning techniques

    Directory of Open Access Journals (Sweden)

    Cerqueira Fabio R

    2012-10-01

    Full Text Available Abstract Background The shotgun strategy (liquid chromatography coupled with tandem mass spectrometry is widely applied for identification of proteins in complex mixtures. This method gives rise to thousands of spectra in a single run, which are interpreted by computational tools. Such tools normally use a protein database from which peptide sequences are extracted for matching with experimentally derived mass spectral data. After the database search, the correctness of obtained peptide-spectrum matches (PSMs needs to be evaluated also by algorithms, as a manual curation of these huge datasets would be impractical. The target-decoy database strategy is largely used to perform spectrum evaluation. Nonetheless, this method has been applied without considering sensitivity, i.e., only error estimation is taken into account. A recently proposed method termed MUDE treats the target-decoy analysis as an optimization problem, where sensitivity is maximized. This method demonstrates a significant increase in the retrieved number of PSMs for a fixed error rate. However, the MUDE model is constructed in such a way that linear decision boundaries are established to separate correct from incorrect PSMs. Besides, the described heuristic for solving the optimization problem has to be executed many times to achieve a significant augmentation in sensitivity. Results Here, we propose a new method, termed MUMAL, for PSM assessment that is based on machine learning techniques. Our method can establish nonlinear decision boundaries, leading to a higher chance to retrieve more true positives. Furthermore, we need few iterations to achieve high sensitivities, strikingly shortening the running time of the whole process. Experiments show that our method achieves a considerably higher number of PSMs compared with standard tools such as MUDE, PeptideProphet, and typical target-decoy approaches. Conclusion Our approach not only enhances the computational performance, and

  8. Comments on the Co-Emergence of Machine Techniques, Paper-and-Pencil Techniques, and Theoretical Reflection

    Science.gov (United States)

    Monaghan, John; Ozmantar, Mehmet Fatih

    2006-01-01

    We comment on the paper "The co-emergence of machine techniques, paper-and-pencil techniques, and theoretical reflection: A study of CAS use in secondary school algebra" by Carolyn Kieran and Paul Drijvers. We look at aspects of Kieran and Drijvers' analysis with regard to "task-technique-theory" in the light of a model of abstraction in context…

  9. Comments on the Co-Emergence of Machine Techniques, Paper-and-Pencil Techniques, and Theoretical Reflection

    Science.gov (United States)

    Monaghan, John; Ozmantar, Mehmet Fatih

    2006-01-01

    We comment on the paper "The co-emergence of machine techniques, paper-and-pencil techniques, and theoretical reflection: A study of CAS use in secondary school algebra" by Carolyn Kieran and Paul Drijvers. We look at aspects of Kieran and Drijvers' analysis with regard to "task-technique-theory" in the light of a model of abstraction in context…

  10. Machine learning in Python essential techniques for predictive analysis

    CERN Document Server

    Bowles, Michael

    2015-01-01

    Learn a simpler and more effective way to analyze data and predict outcomes with Python Machine Learning in Python shows you how to successfully analyze data using only two core machine learning algorithms, and how to apply them using Python. By focusing on two algorithm families that effectively predict outcomes, this book is able to provide full descriptions of the mechanisms at work, and the examples that illustrate the machinery with specific, hackable code. The algorithms are explained in simple terms with no complex math and applied using Python, with guidance on algorithm selection, d

  11. Phishtest: Measuring the Impact of Email Headers on the Predictive Accuracy of Machine Learning Techniques

    Science.gov (United States)

    Tout, Hicham

    2013-01-01

    The majority of documented phishing attacks have been carried by email, yet few studies have measured the impact of email headers on the predictive accuracy of machine learning techniques in detecting email phishing attacks. Research has shown that the inclusion of a limited subset of email headers as features in training machine learning…

  12. Phishtest: Measuring the Impact of Email Headers on the Predictive Accuracy of Machine Learning Techniques

    Science.gov (United States)

    Tout, Hicham

    2013-01-01

    The majority of documented phishing attacks have been carried by email, yet few studies have measured the impact of email headers on the predictive accuracy of machine learning techniques in detecting email phishing attacks. Research has shown that the inclusion of a limited subset of email headers as features in training machine learning…

  13. 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.

  14. A comparison of machine learning techniques for predicting downstream acid mine drainage

    CSIR Research Space (South Africa)

    van Zyl, TL

    2014-07-01

    Full Text Available Canadian Symposium on Remote Sensing (IGARSS) 2014, Quebec, Canada, 13-18 July 2014 A comparison of machine learning techniques for predicting downstream acid mine drainage Terence L van Zyl EOSIT, Meraka Institute, CSIR, Pretoria, South Africa...

  15. Non-traditional Machining Techniques for Fabricating Metal Aerospace Filters

    Institute of Scientific and Technical Information of China (English)

    Wang Wei; Zhu Di; D.M.Allen; H.J.A.Almondb

    2008-01-01

    Thanks to recent advances in manufacturing technology, aerospace system designers have many more options to fabricate high-quality, low-weight, high-capacity, cost-effective filters. Aside from traditional methods such as stamping, drilling and milling,many new approaches have been widely used in filter-manufacturing practices on account of their increased processing abilities. However, the restrictions on costs, the need for studying under stricter conditions such as in aggressive fluids, the complicity in design, the workability of materials, and others have made it difficult to choose a satisfactory method from the newly developed processes, such as,photochemical machining (PCM), photo electroforming (PEF) and laser beam machining (LBM) to produce small, inexpensive, lightweight aerospace filters. This article appraises the technical and economical viability of PCM, PEF, and LBM to help engineers choose the fittest approach to turn out aerospace filters.

  16. Relevance vector machine technique for the inverse scattering problem

    Institute of Scientific and Technical Information of China (English)

    Wang Fang-Fang; Zhang Ye-Rong

    2012-01-01

    A novel method based on the relevance vector machine(RVM)for the inverse scattering problem is presented in this paper.The nonlinearity and the ill-posedness inherent in this problem are simultaneously considered.The nonlinearity is embodied in the relation between the scattered field and the target property,which can be obtained through the RVM training process.Besides,rather than utilizing regularization,the ill-posed nature of the inversion is naturally accounted for because the RVM can produce a probabilistic output.Simulation results reveal that the proposed RVM-based approach can provide comparative performances in terms of accuracy,convergence,robustness,generalization,and improved performance in terms of sparse property in comparison with the support vector machine(SVM)based approach.

  17. Forecasting daily and monthly exchange rates with machine learning techniques

    OpenAIRE

    Papadimitriou, Theophilos; Gogas, Periklis; Plakandaras, Vasilios

    2013-01-01

    We combine signal processing to machine learning methodologies by introducing a hybrid Ensemble Empirical Mode Decomposition (EEMD), Multivariate Adaptive Regression Splines (MARS) and Support Vector Regression (SVR) model in order to forecast the monthly and daily Euro (EUR)/United States Dollar (USD), USD/Japanese Yen (JPY), Australian Dollar (AUD)/Norwegian Krone (NOK), New Zealand Dollar (NZD)/Brazilian Real (BRL) and South African Rand (ZAR)/Philippine Peso (PHP) exchange rates. After th...

  18. 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)

  19. MODELING AND COMPENSATION TECHNIQUE FOR THE GEOMETRIC ERRORS OF FIVE-AXIS CNC MACHINE TOOLS

    Institute of Scientific and Technical Information of China (English)

    2003-01-01

    One of the important trends in precision machining is the development of real-time error compensation technique.The error compensation for multi-axis CNC machine tools is very difficult and attractive.The modeling for the geometric error of five-axis CNC machine tools based on multi-body systems is proposed.And the key technique of the compensation-identifying geometric error parameters-is developed.The simulation of cutting workpiece to verify the modeling based on the multi-body systems is also considered.

  20. Kernel-based machine learning techniques for infrasound signal classification

    Science.gov (United States)

    Tuma, Matthias; Igel, Christian; Mialle, Pierrick

    2014-05-01

    Infrasound monitoring is one of four remote sensing technologies continuously employed by the CTBTO Preparatory Commission. The CTBTO's infrasound network is designed to monitor the Earth for potential evidence of atmospheric or shallow underground nuclear explosions. Upon completion, it will comprise 60 infrasound array stations distributed around the globe, of which 47 were certified in January 2014. Three stages can be identified in CTBTO infrasound data processing: automated processing at the level of single array stations, automated processing at the level of the overall global network, and interactive review by human analysts. At station level, the cross correlation-based PMCC algorithm is used for initial detection of coherent wavefronts. It produces estimates for trace velocity and azimuth of incoming wavefronts, as well as other descriptive features characterizing a signal. Detected arrivals are then categorized into potentially treaty-relevant versus noise-type signals by a rule-based expert system. This corresponds to a binary classification task at the level of station processing. In addition, incoming signals may be grouped according to their travel path in the atmosphere. The present work investigates automatic classification of infrasound arrivals by kernel-based pattern recognition methods. It aims to explore the potential of state-of-the-art machine learning methods vis-a-vis the current rule-based and task-tailored expert system. To this purpose, we first address the compilation of a representative, labeled reference benchmark dataset as a prerequisite for both classifier training and evaluation. Data representation is based on features extracted by the CTBTO's PMCC algorithm. As classifiers, we employ support vector machines (SVMs) in a supervised learning setting. Different SVM kernel functions are used and adapted through different hyperparameter optimization routines. The resulting performance is compared to several baseline classifiers. All

  1. Analysis Of Machine Learning Techniques By Using Blogger Data

    Directory of Open Access Journals (Sweden)

    Gowsalya.R,

    2014-04-01

    Full Text Available Blogs are the recent fast progressing media which depends on information system and technological advancement. The mass media is not much developed for the developing countries are in government terms and their schemes are developed based on governmental concepts, so blogs are provided for knowledge and ideas sharing. This article has highlighted and performed simulations from obtained information, 100 instances of Bloggers by using Weka 3. 6 Tool, and by applying many machine learning algorithms and analyzed with the values of accuracy, precision, recall and F-measure for getting future tendency anticipation of users to blogging and using in strategical areas. Keywords -

  2. The impact of machine learning techniques in the study of bipolar disorder: A systematic review.

    Science.gov (United States)

    Librenza-Garcia, Diego; Kotzian, Bruno Jaskulski; Yang, Jessica; Mwangi, Benson; Cao, Bo; Pereira Lima, Luiza Nunes; Bermudez, Mariane Bagatin; Boeira, Manuela Vianna; Kapczinski, Flávio; Passos, Ives Cavalcante

    2017-07-18

    Machine learning techniques provide new methods to predict diagnosis and clinical outcomes at an individual level. We aim to review the existing literature on the use of machine learning techniques in the assessment of subjects with bipolar disorder. We systematically searched PubMed, Embase and Web of Science for articles published in any language up to January 2017. We found 757 abstracts and included 51 studies in our review. Most of the included studies used multiple levels of biological data to distinguish the diagnosis of bipolar disorder from other psychiatric disorders or healthy controls. We also found studies that assessed the prediction of clinical outcomes and studies using unsupervised machine learning to build more consistent clinical phenotypes of bipolar disorder. We concluded that given the clinical heterogeneity of samples of patients with BD, machine learning techniques may provide clinicians and researchers with important insights in fields such as diagnosis, personalized treatment and prognosis orientation. Copyright © 2017 Elsevier Ltd. All rights reserved.

  3. 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

  4. Ecological Footprint Model Using the Support Vector Machine Technique

    Science.gov (United States)

    Ma, Haibo; Chang, Wenjuan; Cui, Guangbai

    2012-01-01

    The per capita ecological footprint (EF) is one of the most widely recognized measures of environmental sustainability. It aims to quantify the Earth's biological resources required to support human activity. In this paper, we summarize relevant previous literature, and present five factors that influence per capita EF. These factors are: National gross domestic product (GDP), urbanization (independent of economic development), distribution of income (measured by the Gini coefficient), export dependence (measured by the percentage of exports to total GDP), and service intensity (measured by the percentage of service to total GDP). A new ecological footprint model based on a support vector machine (SVM), which is a machine-learning method based on the structural risk minimization principle from statistical learning theory was conducted to calculate the per capita EF of 24 nations using data from 123 nations. The calculation accuracy was measured by average absolute error and average relative error. They were 0.004883 and 0.351078% respectively. Our results demonstrate that the EF model based on SVM has good calculation performance. PMID:22291949

  5. Machine Learning Techniques for Prediction of Early Childhood Obesity.

    Science.gov (United States)

    Dugan, T M; Mukhopadhyay, S; Carroll, A; Downs, S

    2015-01-01

    This paper aims to predict childhood obesity after age two, using only data collected prior to the second birthday by a clinical decision support system called CHICA. Analyses of six different machine learning methods: RandomTree, RandomForest, J48, ID3, Naïve Bayes, and Bayes trained on CHICA data show that an accurate, sensitive model can be created. Of the methods analyzed, the ID3 model trained on the CHICA dataset proved the best overall performance with accuracy of 85% and sensitivity of 89%. Additionally, the ID3 model had a positive predictive value of 84% and a negative predictive value of 88%. The structure of the tree also gives insight into the strongest predictors of future obesity in children. Many of the strongest predictors seen in the ID3 modeling of the CHICA dataset have been independently validated in the literature as correlated with obesity, thereby supporting the validity of the model. This study demonstrated that data from a production clinical decision support system can be used to build an accurate machine learning model to predict obesity in children after age two.

  6. Machine learning techniques for gait biometric recognition using the ground reaction force

    CERN Document Server

    Mason, James Eric; Woungang, Isaac

    2016-01-01

    This book focuses on how machine learning techniques can be used to analyze and make use of one particular category of behavioral biometrics known as the gait biometric. A comprehensive Ground Reaction Force (GRF)-based Gait Biometrics Recognition framework is proposed and validated by experiments. In addition, an in-depth analysis of existing recognition techniques that are best suited for performing footstep GRF-based person recognition is also proposed, as well as a comparison of feature extractors, normalizers, and classifiers configurations that were never directly compared with one another in any previous GRF recognition research. Finally, a detailed theoretical overview of many existing machine learning techniques is presented, leading to a proposal of two novel data processing techniques developed specifically for the purpose of gait biometric recognition using GRF. This book · introduces novel machine-learning-based temporal normalization techniques · bridges research gaps concerning the effect of ...

  7. 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.

  8. Automatic Generation of English-Japanese Translation Pattern Utilizing Genetic Programming Technique

    Science.gov (United States)

    Matsumura, Koki; Tamekuni, Yuji; Kimura, Shuhei

    There are a lot of constructional differences in an English-Japanese phrase template, and that often makes the act of translation difficult. Moreover, there exist various and tremendous phrase templates and sentence to be refered to. It is not easy to prepare the corpus that covers the all. Therefore, it is very significant to generate the translation pattern of the sentence pattern automatically from a viewpoint of the translation success rate and the capacity of the pattern dictionary. Then, for the purpose of realizing the automatic generation of the translation pattern, this paper proposed the new method for the generation of the translation pattern by using the genetic programming technique (GP). The technique tries to generate the translation pattern of various sentences which are not registered in the phrase template dictionary automatically by giving the genetic operation to the parsing tree of a basic pattern. The tree consists of the pair of the English-Japanese sentence generated as the first stage population. The analysis tree data base with 50,100,150,200 pairs was prepared as the first stage population. And this system was applied and executed for an English input of 1,555 sentences. As a result, the analysis tree increases from 200 to 517, and the accuracy rate of the translation pattern has improved from 42.57% to 70.10%. And, 86.71% of the generated translations was successfully done, whose meanings are enough acceptable and understandable. It seemed that this proposal technique became a clue to raise the translation success rate, and to find the possibility of the reduction of the analysis tree data base.

  9. A Translator Verification Technique for FPGA Software Development in Nuclear Power Plants

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Jae Yeob; Kim, Eui Sub; Yoo, Jun Beom [Konkuk University, Seoul (Korea, Republic of)

    2014-10-15

    Although the FPGAs give a high performance than PLC (Programmable Logic Controller), the platform change from PLC to FPGA impose all PLC software engineers give up their experience, knowledge and practices accumulated over decades, and start a new FPGA-based hardware development from scratch. We have researched to fine the solution to this problem reducing the risk and preserving the experience and knowledge. One solution is to use the FBDtoVerilog translator, which translates the FBD programs into behavior-preserving Verilog programs. In general, the PLCs are usually designed with an FBD, while the FPGAs are described with a HDL (Hardware Description Language) such as Verilog or VHDL. Once PLC designer designed the FBD programs, the FBDtoVerilog translates the FBD into Verilog, mechanically. The designers, therefore, need not consider the rest of FPGA development process (e.g., Synthesis and Place and Routing) and can preserve the accumulated experience and knowledge. Even if we assure that the translation from FBD to Verilog is correct, it must be verified rigorously and thoroughly since it is used in nuclear power plants, which is one of the most safety critical systems. While the designer develops the FPGA software with the FBD program translated by the translator, there are other translation tools such as synthesis tool and place and routing tool. This paper also focuses to verify them rigorously and thoroughly. There are several verification techniques for correctness of translator, but they are hard to apply because of the outrageous cost and performance time. Instead, this paper tries to use an indirect verification technique for demonstrating the correctness of translator using the co-simulation technique. We intend to prove only against specific inputs which are under development for a target I and C system, not against all possible input cases.

  10. Improving Students’ Skills in Translation through Students-Teams Achievement Division (STAD Technique

    Directory of Open Access Journals (Sweden)

    Syarwan Ahmad

    2015-08-01

    Full Text Available This classroom action rresearch was aimed at improving students’ skills in translating at the English Department of the State Islamic University (UIN Ar-Rarniry Banda Aceh by using the Student-Teams Achievement Division (STAD Technique. Throughout the entire cycles, students worked in groups of 4-5 persons to plan and write their translations. The study showed that the average score of pre- test (66 increased dramatically to reach 86, and moved up a little higher (87 after the second cycle. It is recommended that STAD Cooperative Technique be implemented in teaching translation courses.  Key words: Teaching translation; STAD; UIN Aceh.Copyright © 2015 by Al-Ta'lim All right reserved

  11. Fabrication of titanium implant-retained restorations with nontraditional machining techniques.

    Science.gov (United States)

    Schmitt, S M; Chance, D A

    1995-01-01

    Traditional laboratory techniques are being supplemented by modern precision technologies to solve complex restorative problems. Electrical discharge machining combined with laser scanning and computer aided design-computer aided manufacturing can create very precise restorations without the lost wax method. A laser scanner is used to create a three-dimensional polyline data model that can then be converted into a stereolithography file format for output to a stereolithography apparatus or other rapid prototyping device. A stereolithography-generated model is used to create an electric discharge machining electrode via copper electroforming. This electrode is used to machine dental restorations from an ingot of titanium, bypassing the conventional lost wax casting process. Retaining screw access holes are machined using conventional drilling procedures, but could be accomplished with electric discharge machining if desired. Other rapid prototyping technologies are briefly discussed.

  12. Feasibility of Applying Controllable Lubrication Techniques to Reciprocating Machines

    DEFF Research Database (Denmark)

    Pulido, Edgar Estupinan

    modified hydrostatic lubrication. In this case, the hydrostatic lubrication is modified by injecting oil at controllable pressures, through orifices circumferentially located around the bearing surface. In order to study the performance of journal bearings of reciprocating machines, operating under...... conventional lubrication conditions, a mathematical model of a reciprocating mechanism connected to a rigid / flexible rotor via thin fluid films was developed. The mathematical model involves the use of multibody dynamics theory for the modelling of the reciprocating mechanism (rigid bodies), finite elements...... of the reciprocating engine, obtained with the help of multibody dynamics (rigid components) and finite elements method (flexible components), and the global system of equations is numerically solved. The analysis of the results was carried out with focus on the behaviour of the journal orbits, maximum fluid film...

  13. FRC Separatrix inference using machine-learning techniques

    Science.gov (United States)

    Romero, Jesus; Roche, Thomas; the TAE Team

    2016-10-01

    As Field Reversed Configuration (FRC) devices approach lifetimes exceeding the characteristic time of conductive structures external to the plasma, plasma stabilization cannot be achieved solely by the flux conserving effect of the external structures, and active control systems are then necessary. An essential component of such control systems is a reconstruction method for the plasma separatrix suitable for real time. We report on a method to infer the separatrix in an FRC using the information of magnetic probes located externally to the plasma. The method uses machine learning methods, namely Bayesian inference of Gaussian Processes, to obtain the most likely plasma current density distribution given the measurements of magnetic field external to the plasma. From the current sources, flux function and in particular separatrix are easily computed. The reconstruction method is non iterative and hence suitable for deterministic real time applications. Validation results with numerical simulations and application to separatrix inference of C-2U plasma discharges will be presented.

  14. Use of machine learning techniques for modeling of snow depth

    Directory of Open Access Journals (Sweden)

    G. V. Ayzel

    2017-01-01

    Full Text Available Snow exerts significant regulating effect on the land hydrological cycle since it controls intensity of heat and water exchange between the soil-vegetative cover and the atmosphere. Estimating of a spring flood runoff or a rain-flood on mountainous rivers requires understanding of the snow cover dynamics on a watershed. In our work, solving a problem of the snow cover depth modeling is based on both available databases of hydro-meteorological observations and easily accessible scientific software that allows complete reproduction of investigation results and further development of this theme by scientific community. In this research we used the daily observational data on the snow cover and surface meteorological parameters, obtained at three stations situated in different geographical regions: Col de Porte (France, Sodankyla (Finland, and Snoquamie Pass (USA.Statistical modeling of the snow cover depth is based on a complex of freely distributed the present-day machine learning models: Decision Trees, Adaptive Boosting, Gradient Boosting. It is demonstrated that use of combination of modern machine learning methods with available meteorological data provides the good accuracy of the snow cover modeling. The best results of snow cover depth modeling for every investigated site were obtained by the ensemble method of gradient boosting above decision trees – this model reproduces well both, the periods of snow cover accumulation and its melting. The purposeful character of learning process for models of the gradient boosting type, their ensemble character, and use of combined redundancy of a test sample in learning procedure makes this type of models a good and sustainable research tool. The results obtained can be used for estimating the snow cover characteristics for river basins where hydro-meteorological information is absent or insufficient.

  15. The applicability of Lean and Six Sigma techniques to clinical and translational research.

    Science.gov (United States)

    Schweikhart, Sharon A; Dembe, Allard E

    2009-10-01

    Lean and Six Sigma are business management strategies commonly used in production industries to improve process efficiency and quality. During the past decade, these process improvement techniques increasingly have been applied outside the manufacturing sector, for example, in health care and in software development. This article concerns the potential use of Lean and Six Sigma in improving the processes involved in clinical and translational research. Improving quality, avoiding delays and errors, and speeding up the time to implementation of biomedical discoveries are prime objectives of the National Institutes of Health (NIH) Roadmap for Medical Research and the NIH's Clinical and Translational Science Award program. This article presents a description of the main principles, practices, and methods used in Lean and Six Sigma. Available literature involving applications of Lean and Six Sigma to health care, laboratory science, and clinical and translational research is reviewed. Specific issues concerning the use of these techniques in different phases of translational research are identified. Examples of Lean and Six Sigma applications that are being planned at a current Clinical and Translational Science Award site are provided, which could potentially be replicated elsewhere. We describe how different process improvement approaches are best adapted for particular translational research phases. Lean and Six Sigma process improvement methods are well suited to help achieve NIH's goal of making clinical and translational research more efficient and cost-effective, enhancing the quality of the research, and facilitating the successful adoption of biomedical research findings into practice.

  16. Application of Artificial Intelligence Techniques for the Control of the Asynchronous Machine

    Directory of Open Access Journals (Sweden)

    F. Khammar

    2016-01-01

    Full Text Available The induction machine is experiencing a growing success for two decades by gradually replacing the DC machines and synchronous in many industrial applications. This paper is devoted to the study of advanced methods applied to the command of the asynchronous machine in order to obtain a system of control of high performance. While the criteria for response time, overtaking, and static error can be assured by the techniques of conventional control, the criterion of robustness remains a challenge for researchers. This criterion can be satisfied only by applying advanced techniques of command. After mathematical modeling of the asynchronous machine, it defines the control strategies based on the orientation of the rotor flux. The results of the different simulation tests highlight the properties of robustness of algorithms proposed and suggested to compare the different control strategies.

  17. 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...

  18. 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, ...

  19. Down syndrome detection from facial photographs using machine learning techniques

    Science.gov (United States)

    Zhao, Qian; Rosenbaum, Kenneth; Sze, Raymond; Zand, Dina; Summar, Marshall; Linguraru, Marius George

    2013-02-01

    Down syndrome is the most commonly occurring chromosomal condition; one in every 691 babies in United States is born with it. Patients with Down syndrome have an increased risk for heart defects, respiratory and hearing problems and the early detection of the syndrome is fundamental for managing the disease. Clinically, facial appearance is an important indicator in diagnosing Down syndrome and it paves the way for computer-aided diagnosis based on facial image analysis. In this study, we propose a novel method to detect Down syndrome using photography for computer-assisted image-based facial dysmorphology. Geometric features based on facial anatomical landmarks, local texture features based on the Contourlet transform and local binary pattern are investigated to represent facial characteristics. Then a support vector machine classifier is used to discriminate normal and abnormal cases; accuracy, precision and recall are used to evaluate the method. The comparison among the geometric, local texture and combined features was performed using the leave-one-out validation. Our method achieved 97.92% accuracy with high precision and recall for the combined features; the detection results were higher than using only geometric or texture features. The promising results indicate that our method has the potential for automated assessment for Down syndrome from simple, noninvasive imaging data.

  20. Twitter Sentiment Analysis of Movie Reviews using Machine Learning Techniques.

    Directory of Open Access Journals (Sweden)

    Akshay Amolik

    2015-12-01

    Full Text Available Sentiment analysis is basically concerned with analysis of emotions and opinions from text. We can refer sentiment analysis as opinion mining. Sentiment analysis finds and justifies the sentiment of the person with respect to a given source of content. Social media contain huge amount of the sentiment data in the form of tweets, blogs, and updates on the status, posts, etc. Sentiment analysis of this largely generated data is very useful to express the opinion of the mass. Twitter sentiment analysis is tricky as compared to broad sentiment analysis because of the slang words and misspellings and repeated characters. We know that the maximum length of each tweet in Twitter is 140 characters. So it is very important to identify correct sentiment of each word. In our project we are proposing a highly accurate model of sentiment analysis of tweets with respect to latest reviews of upcoming Bollywood or Hollywood movies. With the help of feature vector and classifiers such as Support vector machine and Naïve Bayes, we are correctly classifying these tweets as positive, negative and neutral to give sentiment of each tweet.

  1. 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

  2. The Applicability of Lean and Six Sigma Techniques to Clinical and Translational Research

    Science.gov (United States)

    Schweikhart, Sharon A.; Dembe, Allard E

    2010-01-01

    Background Lean and Six Sigma are business management strategies commonly used in production industries to improve process efficiency and quality. During the past decade, these process improvement techniques increasingly have been applied outside of the manufacturing sector, for example, in health care and in software development. This article concerns the potential use of Lean and Six Sigma to improve the processes involved in clinical and translational research. Improving quality, avoiding delays and errors, and speeding up the time to implementation of biomedical discoveries are prime objectives of the NIH Roadmap for Biomedical Research and the NIH Clinical and Translational Science Award (CTSA) program. Methods This article presents a description of the main principles, practices, and methodologies used in Lean and Six Sigma. Available literature involving applications of Lean and Six Sigma to health care, laboratory science, and clinical and translational research is reviewed. Specific issues concerning the use of these techniques in different phases of translational research are identified. Results Examples are provided of Lean and Six Sigma applications that are being planned at a current CTSA site, which could potentially be replicated elsewhere. We describe how different process improvement approaches are best adapted for particularly translational research phases. Conclusions Lean and Six Sigma process improvement methodologies are well suited to help achieve NIH’s goal of making clinical and translational research more efficient and cost-effective, enhancing the quality of the research, and facilitating the successful adoption of biomedical research findings into practice. PMID:19730130

  3. 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…

  4. Machinability of hypereutectic cast Al–Si alloys processed by SSM processing technique

    Indian Academy of Sciences (India)

    P K SOOD; RAKESH SEHGAL; D K DWIVEDI

    2017-03-01

    Experimental investigation carried out on the machinability studies to determine the influence of semi-solid metal processing and modification on hypereutectic Al–20Si–0.5Mg–1.2Fe-based alloy produced by conventional cast and semi-solid metal processing technique (mechanical stirring) and modified with iron correctors (Be and Cd) has been presented in this paper. The alloys under investigation were prepared bycontrolling melt using an induction melting furnace. Stirring of semi-solid metal takes place at constant cooling conditions from liquidus temperature at a constant stirring speed of 400 rpm. To determine the machining performance characteristics an orthogonal array, signal-to-noise ratio and statistical tool analysis of variance were jointly used during experimentation. A CNC lathe was used to conduct experiments in dry condition and coated carbide inserts were used as tool inserts. Machining variables like cutting velocity, approaching angle,feed rate and depth of cut, which can be considered as process parameters, are taken into account. The combined effect of modification and semi-solid metal processing has a significant effect on the machining characteristics,which was concluded from study. The modified alloy processed by semi-solid metal processing technique exhibits better machinability conditions when compared with the conventional cast. The feed rate has more effect on machining behaviour.

  5. Arabic Keyphrase Extraction using Linguistic knowledge and Machine Learning Techniques

    CERN Document Server

    El-shishtawy, Tarek

    2012-01-01

    In this paper, a supervised learning technique for extracting keyphrases of Arabic documents is presented. The extractor is supplied with linguistic knowledge to enhance its efficiency instead of relying only on statistical information such as term frequency and distance. During analysis, an annotated Arabic corpus is used to extract the required lexical features of the document words. The knowledge also includes syntactic rules based on part of speech tags and allowed word sequences to extract the candidate keyphrases. In this work, the abstract form of Arabic words is used instead of its stem form to represent the candidate terms. The Abstract form hides most of the inflections found in Arabic words. The paper introduces new features of keyphrases based on linguistic knowledge, to capture titles and subtitles of a document. A simple ANOVA test is used to evaluate the validity of selected features. Then, the learning model is built using the LDA - Linear Discriminant Analysis - and training documents. Althou...

  6. 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.

  7. An element search ant colony technique for solving virtual machine placement problem

    Science.gov (United States)

    Srija, J.; Rani John, Rose; Kanaga, Grace Mary, Dr.

    2017-09-01

    The data centres in the cloud environment play a key role in providing infrastructure for ubiquitous computing, pervasive computing, mobile computing etc. This computing technique tries to utilize the available resources in order to provide services. Hence maintaining the resource utilization without wastage of power consumption has become a challenging task for the researchers. In this paper we propose the direct guidance ant colony system for effective mapping of virtual machines to the physical machine with maximal resource utilization and minimal power consumption. The proposed algorithm has been compared with the existing ant colony approach which is involved in solving virtual machine placement problem and thus the proposed algorithm proves to provide better result than the existing technique.

  8. 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。

  9. 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.

  10. Reconstructing muscle activation during normal walking: a comparison of symbolic and connectionist machine learning techniques

    NARCIS (Netherlands)

    Heller, Ben W.; Veltink, Peter H.; Rijkhoff, Nico J.M.; Rutten, Wim L.C.; Andrews, Brian J.

    1993-01-01

    One symbolic (rule-based inductive learning) and one connectionist (neural network) machine learning technique were used to reconstruct muscle activation patterns from kinematic data measured during normal human walking at several speeds. The activation patterns (or desired outputs) consisted of sur

  11. A novel method to estimate model uncertainty using machine learning techniques

    NARCIS (Netherlands)

    Solomatine, D.P.; Lal Shrestha, D.

    2009-01-01

    A novel method is presented for model uncertainty estimation using machine learning techniques and its application in rainfall runoff modeling. In this method, first, the probability distribution of the model error is estimated separately for different hydrological situations and second, the

  12. Reconstructing muscle activation during normal walking: a comparison of symbolic and connectionist machine learning techniques

    NARCIS (Netherlands)

    Heller, Ben W.; Veltink, Petrus H.; Rijkhoff, N.J.M.; Rijkhoff, Nico J.M.; Rutten, Wim; Andrews, Brian J.

    1993-01-01

    One symbolic (rule-based inductive learning) and one connectionist (neural network) machine learning technique were used to reconstruct muscle activation patterns from kinematic data measured during normal human walking at several speeds. The activation patterns (or desired outputs) consisted of

  13. Exploring Machine Learning Techniques Using Patient Interactions in Online Health Forums to Classify Drug Safety

    Science.gov (United States)

    Chee, Brant Wah Kwong

    2011-01-01

    This dissertation explores the use of personal health messages collected from online message forums to predict drug safety using natural language processing and machine learning techniques. Drug safety is defined as any drug with an active safety alert from the US Food and Drug Administration (FDA). It is believed that this is the first…

  14. Exploring Machine Learning Techniques Using Patient Interactions in Online Health Forums to Classify Drug Safety

    Science.gov (United States)

    Chee, Brant Wah Kwong

    2011-01-01

    This dissertation explores the use of personal health messages collected from online message forums to predict drug safety using natural language processing and machine learning techniques. Drug safety is defined as any drug with an active safety alert from the US Food and Drug Administration (FDA). It is believed that this is the first…

  15. Locomotion training of legged robots using hybrid machine learning techniques

    Science.gov (United States)

    Simon, William E.; Doerschuk, Peggy I.; Zhang, Wen-Ran; Li, Andrew L.

    1995-01-01

    In this study artificial neural networks and fuzzy logic are used to control the jumping behavior of a three-link uniped robot. The biped locomotion control problem is an increment of the uniped locomotion control. Study of legged locomotion dynamics indicates that a hierarchical controller is required to control the behavior of a legged robot. A structured control strategy is suggested which includes navigator, motion planner, biped coordinator and uniped controllers. A three-link uniped robot simulation is developed to be used as the plant. Neurocontrollers were trained both online and offline. In the case of on-line training, a reinforcement learning technique was used to train the neurocontroller to make the robot jump to a specified height. After several hundred iterations of training, the plant output achieved an accuracy of 7.4%. However, when jump distance and body angular momentum were also included in the control objectives, training time became impractically long. In the case of off-line training, a three-layered backpropagation (BP) network was first used with three inputs, three outputs and 15 to 40 hidden nodes. Pre-generated data were presented to the network with a learning rate as low as 0.003 in order to reach convergence. The low learning rate required for convergence resulted in a very slow training process which took weeks to learn 460 examples. After training, performance of the neurocontroller was rather poor. Consequently, the BP network was replaced by a Cerebeller Model Articulation Controller (CMAC) network. Subsequent experiments described in this document show that the CMAC network is more suitable to the solution of uniped locomotion control problems in terms of both learning efficiency and performance. A new approach is introduced in this report, viz., a self-organizing multiagent cerebeller model for fuzzy-neural control of uniped locomotion is suggested to improve training efficiency. This is currently being evaluated for a possible

  16. Classification of the Regional Ionospheric Disturbance Based on Machine Learning Techniques

    Science.gov (United States)

    Terzi, Merve Begum; Arikan, Orhan; Karatay, Secil; Arikan, Feza; Gulyaeva, Tamara

    2016-08-01

    In this study, Total Electron Content (TEC) estimated from GPS receivers is used to model the regional and local variability that differs from global activity along with solar and geomagnetic indices. For the automated classification of regional disturbances, a classification technique based on a robust machine learning technique that have found wide spread use, Support Vector Machine (SVM) is proposed. Performance of developed classification technique is demonstrated for midlatitude ionosphere over Anatolia using TEC estimates generated from GPS data provided by Turkish National Permanent GPS Network (TNPGN-Active) for solar maximum year of 2011. As a result of implementing developed classification technique to Global Ionospheric Map (GIM) TEC data, which is provided by the NASA Jet Propulsion Laboratory (JPL), it is shown that SVM can be a suitable learning method to detect anomalies in TEC variations.

  17. Prediction of mortality after radical cystectomy for bladder cancer by machine learning techniques.

    Science.gov (United States)

    Wang, Guanjin; Lam, Kin-Man; Deng, Zhaohong; Choi, Kup-Sze

    2015-08-01

    Bladder cancer is a common cancer in genitourinary malignancy. For muscle invasive bladder cancer, surgical removal of the bladder, i.e. radical cystectomy, is in general the definitive treatment which, unfortunately, carries significant morbidities and mortalities. Accurate prediction of the mortality of radical cystectomy is therefore needed. Statistical methods have conventionally been used for this purpose, despite the complex interactions of high-dimensional medical data. Machine learning has emerged as a promising technique for handling high-dimensional data, with increasing application in clinical decision support, e.g. cancer prediction and prognosis. Its ability to reveal the hidden nonlinear interactions and interpretable rules between dependent and independent variables is favorable for constructing models of effective generalization performance. In this paper, seven machine learning methods are utilized to predict the 5-year mortality of radical cystectomy, including back-propagation neural network (BPN), radial basis function (RBFN), extreme learning machine (ELM), regularized ELM (RELM), support vector machine (SVM), naive Bayes (NB) classifier and k-nearest neighbour (KNN), on a clinicopathological dataset of 117 patients of the urology unit of a hospital in Hong Kong. The experimental results indicate that RELM achieved the highest average prediction accuracy of 0.8 at a fast learning speed. The research findings demonstrate the potential of applying machine learning techniques to support clinical decision making. Copyright © 2015 Elsevier Ltd. All rights reserved.

  18. State of the Art Review for Applying Computational Intelligence and Machine Learning Techniques to Portfolio Optimisation

    CERN Document Server

    Hurwitz, Evan

    2009-01-01

    Computational techniques have shown much promise in the field of Finance, owing to their ability to extract sense out of dauntingly complex systems. This paper reviews the most promising of these techniques, from traditional computational intelligence methods to their machine learning siblings, with particular view to their application in optimising the management of a portfolio of financial instruments. The current state of the art is assessed, and prospective further work is assessed and recommended

  19. Techniques and applications for binaural sound manipulation in human-machine interfaces

    Science.gov (United States)

    Begault, Durand R.; Wenzel, Elizabeth M.

    1992-01-01

    The implementation of binaural sound to speech and auditory sound cues (auditory icons) is addressed from both an applications and technical standpoint. Techniques overviewed include processing by means of filtering with head-related transfer functions. Application to advanced cockpit human interface systems is discussed, although the techniques are extendable to any human-machine interface. Research issues pertaining to three-dimensional sound displays under investigation at the Aerospace Human Factors Division at NASA Ames Research Center are described.

  20. 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.

  1. ISOLATED SPEECH RECOGNITION SYSTEM FOR TAMIL LANGUAGE USING STATISTICAL PATTERN MATCHING AND MACHINE LEARNING TECHNIQUES

    Directory of Open Access Journals (Sweden)

    VIMALA C.

    2015-05-01

    Full Text Available In recent years, speech technology has become a vital part of our daily lives. Various techniques have been proposed for developing Automatic Speech Recognition (ASR system and have achieved great success in many applications. Among them, Template Matching techniques like Dynamic Time Warping (DTW, Statistical Pattern Matching techniques such as Hidden Markov Model (HMM and Gaussian Mixture Models (GMM, Machine Learning techniques such as Neural Networks (NN, Support Vector Machine (SVM, and Decision Trees (DT are most popular. The main objective of this paper is to design and develop a speaker-independent isolated speech recognition system for Tamil language using the above speech recognition techniques. The background of ASR system, the steps involved in ASR, merits and demerits of the conventional and machine learning algorithms and the observations made based on the experiments are presented in this paper. For the above developed system, highest word recognition accuracy is achieved with HMM technique. It offered 100% accuracy during training process and 97.92% for testing process.

  2. Remotely sensed data assimilation technique to develop machine learning models for use in water management

    Science.gov (United States)

    Zaman, Bushra

    Increasing population and water conflicts are making water management one of the most important issues of the present world. It has become absolutely necessary to find ways to manage water more efficiently. Technological advancement has introduced various techniques for data acquisition and analysis, and these tools can be used to address some of the critical issues that challenge water resource management. This research used learning machine techniques and information acquired through remote sensing, to solve problems related to soil moisture estimation and crop identification on large spatial scales. In this dissertation, solutions were proposed in three problem areas that can be important in the decision making process related to water management in irrigated systems. A data assimilation technique was used to build a learning machine model that generated soil moisture estimates commensurate with the scale of the data. The research was taken further by developing a multivariate machine learning algorithm to predict root zone soil moisture both in space and time. Further, a model was developed for supervised classification of multi-spectral reflectance data using a multi-class machine learning algorithm. The procedure was designed for classifying crops but the model is data dependent and can be used with other datasets and hence can be applied to other landcover classification problems. The dissertation compared the performance of relevance vector and the support vector machines in estimating soil moisture. A multivariate relevance vector machine algorithm was tested in the spatio-temporal prediction of soil moisture, and the multi-class relevance vector machine model was used for classifying different crop types. It was concluded that the classification scheme may uncover important data patterns contributing greatly to knowledge bases, and to scientific and medical research. The results for the soil moisture models would give a rough idea to farmers

  3. 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.

  4. Machine learning and microsimulation techniques on the prognosis of dementia: A systematic literature review.

    Science.gov (United States)

    Dallora, Ana Luiza; Eivazzadeh, Shahryar; Mendes, Emilia; Berglund, Johan; Anderberg, Peter

    2017-01-01

    Dementia is a complex disorder characterized by poor outcomes for the patients and high costs of care. After decades of research little is known about its mechanisms. Having prognostic estimates about dementia can help researchers, patients and public entities in dealing with this disorder. Thus, health data, machine learning and microsimulation techniques could be employed in developing prognostic estimates for dementia. The goal of this paper is to present evidence on the state of the art of studies investigating and the prognosis of dementia using machine learning and microsimulation techniques. To achieve our goal we carried out a systematic literature review, in which three large databases-Pubmed, Socups and Web of Science were searched to select studies that employed machine learning or microsimulation techniques for the prognosis of dementia. A single backward snowballing was done to identify further studies. A quality checklist was also employed to assess the quality of the evidence presented by the selected studies, and low quality studies were removed. Finally, data from the final set of studies were extracted in summary tables. In total 37 papers were included. The data summary results showed that the current research is focused on the investigation of the patients with mild cognitive impairment that will evolve to Alzheimer's disease, using machine learning techniques. Microsimulation studies were concerned with cost estimation and had a populational focus. Neuroimaging was the most commonly used variable. Prediction of conversion from MCI to AD is the dominant theme in the selected studies. Most studies used ML techniques on Neuroimaging data. Only a few data sources have been recruited by most studies and the ADNI database is the one most commonly used. Only two studies have investigated the prediction of epidemiological aspects of Dementia using either ML or MS techniques. Finally, care should be taken when interpreting the reported accuracy of ML

  5. Process acceptance and adjustment techniques for Swiss automatic screw machine parts. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Robb, J.M.

    1976-01-01

    Product tolerance requirements for small, cylindrical, piece parts produced on swiss automatic screw machines have progressed to the reliability limits of inspection equipment. The miniature size, configuration, and tolerance requirements (plus or minus 0.0001 in.) (0.00254 mm) of these parts preclude the use of screening techniques to accept product or adjust processes during setup and production runs; therefore, existing means of product acceptance and process adjustment must be refined or new techniques must be developed. The purpose of this endeavor has been to determine benefits gained through the implementation of a process acceptance technique (PAT) to swiss automatic screw machine processes. PAT is a statistical approach developed for the purpose of accepting product and centering processes for parts produced by selected, controlled processes. Through this endeavor a determination has been made of the conditions under which PAT can benefit a controlled process and some specific types of screw machine processes upon which PAT could be applied. However, it was also determined that PAT, if used indiscriminately, may become a record keeping burden when applied to more than one dimension at a given machining operation. (auth)

  6. Machine and deep learning techniques in heavy-ion collisions with ALICE arXiv

    CERN Document Server

    INSPIRE-00382877

    Over the last years, machine learning tools have been successfully applied to a wealth of problems in high-energy physics. A typical example is the classification of physics objects. Supervised machine learning methods allow for significant improvements in classification problems by taking into account observable correlations and by learning the optimal selection from examples, e.g. from Monte Carlo simulations. Even more promising is the usage of deep learning techniques. Methods like deep convolutional networks might be able to catch features from low-level parameters that are not exploited by default cut-based methods. These ideas could be particularly beneficial for measurements in heavy-ion collisions, because of the very large multiplicities. Indeed, machine learning methods potentially perform much better in systems with a large number of degrees of freedom compared to cut-based methods. Moreover, many key heavy-ion observables are most interesting at low transverse momentum where the underlying event ...

  7. Impact of corpus domain for sentiment classification: An evaluation study using supervised machine learning techniques

    Science.gov (United States)

    Karsi, Redouane; Zaim, Mounia; El Alami, Jamila

    2017-07-01

    Thanks to the development of the internet, a large community now has the possibility to communicate and express its opinions and preferences through multiple media such as blogs, forums, social networks and e-commerce sites. Today, it becomes clearer that opinions published on the web are a very valuable source for decision-making, so a rapidly growing field of research called “sentiment analysis” is born to address the problem of automatically determining the polarity (Positive, negative, neutral,…) of textual opinions. People expressing themselves in a particular domain often use specific domain language expressions, thus, building a classifier, which performs well in different domains is a challenging problem. The purpose of this paper is to evaluate the impact of domain for sentiment classification when using machine learning techniques. In our study three popular machine learning techniques: Support Vector Machines (SVM), Naive Bayes and K nearest neighbors(KNN) were applied on datasets collected from different domains. Experimental results show that Support Vector Machines outperforms other classifiers in all domains, since it achieved at least 74.75% accuracy with a standard deviation of 4,08.

  8. Statistical and Machine-Learning Data Mining Techniques for Better Predictive Modeling and Analysis of Big Data

    CERN Document Server

    Ratner, Bruce

    2011-01-01

    The second edition of a bestseller, Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data is still the only book, to date, to distinguish between statistical data mining and machine-learning data mining. The first edition, titled Statistical Modeling and Analysis for Database Marketing: Effective Techniques for Mining Big Data, contained 17 chapters of innovative and practical statistical data mining techniques. In this second edition, renamed to reflect the increased coverage of machine-learning data mining techniques, the author has

  9. Retrieval of Similar Objects in Simulation Data Using Machine Learning Techniques

    Energy Technology Data Exchange (ETDEWEB)

    Cantu-Paz, E; Cheung, S-C; Kamath, C

    2003-06-19

    Comparing the output of a physics simulation with an experiment is often done by visually comparing the two outputs. In order to determine which simulation is a closer match to the experiment, more quantitative measures are needed. This paper describes our early experiences with this problem by considering the slightly simpler problem of finding objects in a image that are similar to a given query object. Focusing on a dataset from a fluid mixing problem, we report on our experiments using classification techniques from machine learning to retrieve the objects of interest in the simulation data. The early results reported in this paper suggest that machine learning techniques can retrieve more objects that are similar to the query than distance-based similarity methods.

  10. Hybrid Machine Learning Technique for Forecasting Dhaka Stock Market Timing Decisions

    OpenAIRE

    Shipra Banik; Khodadad Khan, A. F. M.; Mohammad Anwer

    2014-01-01

    Forecasting stock market has been a difficult job for applied researchers owing to nature of facts which is very noisy and time varying. However, this hypothesis has been featured by several empirical experiential studies and a number of researchers have efficiently applied machine learning techniques to forecast stock market. This paper studied stock prediction for the use of investors. It is always true that investors typically obtain loss because of uncertain investment purposes and unsigh...

  11. An Empirical Study of Machine Learning Techniques for Classifying Emotional States from EEG Data

    OpenAIRE

    2012-01-01

    With the great advancement in robot technology, smart human-robot interaction is considered to be the most wanted success by the researchers these days. If a robot can identify emotions and intentions of a human interacting with it, that would make robots more useful. Electroencephalography (EEG) is considered one effective way of recording emotions and motivations of a human using brain. Various machine learning techniques are used successfully to classify EEG data accurately. K-Nearest Neig...

  12. Auditory inspired machine learning techniques can improve speech intelligibility and quality for hearing-impaired listeners.

    Science.gov (United States)

    Monaghan, Jessica J M; Goehring, Tobias; Yang, Xin; Bolner, Federico; Wang, Shangqiguo; Wright, Matthew C M; Bleeck, Stefan

    2017-03-01

    Machine-learning based approaches to speech enhancement have recently shown great promise for improving speech intelligibility for hearing-impaired listeners. Here, the performance of three machine-learning algorithms and one classical algorithm, Wiener filtering, was compared. Two algorithms based on neural networks were examined, one using a previously reported feature set and one using a feature set derived from an auditory model. The third machine-learning approach was a dictionary-based sparse-coding algorithm. Speech intelligibility and quality scores were obtained for participants with mild-to-moderate hearing impairments listening to sentences in speech-shaped noise and multi-talker babble following processing with the algorithms. Intelligibility and quality scores were significantly improved by each of the three machine-learning approaches, but not by the classical approach. The largest improvements for both speech intelligibility and quality were found by implementing a neural network using the feature set based on auditory modeling. Furthermore, neural network based techniques appeared more promising than dictionary-based, sparse coding in terms of performance and ease of implementation.

  13. Decomposition of molecular motions into translational, rotational, and intramolecular parts by a projection operator technique

    DEFF Research Database (Denmark)

    Hansen, Flemming Yssing; Taub, H.

    2009-01-01

    The motion of the atoms in a molecule may be described as a superposition of translational motion of the molecular center-of-mass, rotational motion about the principal molecular axes, and an intramolecular motion that may be associated with vibrations and librations as well as molecular conforma......The motion of the atoms in a molecule may be described as a superposition of translational motion of the molecular center-of-mass, rotational motion about the principal molecular axes, and an intramolecular motion that may be associated with vibrations and librations as well as molecular...... conformational changes. We have constructed projection operators that use the atomic coordinates and velocities at any two times, t=0 and a later time t, to determine the molecular center-of-mass, rotational, and intramolecular motions in a molecular dynamics simulation. This model-independent technique...

  14. New Technique of High-Performance Torque Control Developed for Induction Machines

    Science.gov (United States)

    Kenny, Barbara H.

    2003-01-01

    Two forms of high-performance torque control for motor drives have been described in the literature: field orientation control and direct torque control. Field orientation control has been the method of choice for previous NASA electromechanical actuator research efforts with induction motors. Direct torque control has the potential to offer some advantages over field orientation, including ease of implementation and faster response. However, the most common form of direct torque control is not suitable for the highspeed, low-stator-flux linkage induction machines designed for electromechanical actuators with the presently available sample rates of digital control systems (higher sample rates are required). In addition, this form of direct torque control is not suitable for the addition of a high-frequency carrier signal necessary for the "self-sensing" (sensorless) position estimation technique. This technique enables low- and zero-speed position sensorless operation of the machine. Sensorless operation is desirable to reduce the number of necessary feedback signals and transducers, thus improving the reliability and reducing the mass and volume of the system. This research was directed at developing an alternative form of direct torque control known as a "deadbeat," or inverse model, solution. This form uses pulse-width modulation of the voltage applied to the machine, thus reducing the necessary sample and switching frequency for the high-speed NASA motor. In addition, the structure of the deadbeat form allows the addition of the high-frequency carrier signal so that low- and zero-speed sensorless operation is possible. The new deadbeat solution is based on using the stator and rotor flux as state variables. This choice of state variables leads to a simple graphical representation of the solution as the intersection of a constant torque line with a constant stator flux circle. Previous solutions have been expressed only in complex mathematical terms without a

  15. Classification of Cytochrome P450 1A2 Inhibitors and Non-Inhibitors by Machine Learning Techniques

    DEFF Research Database (Denmark)

    Vasanthanathan, Poongavanam; Taboureau, Olivier; Oostenbrink, Chris

    2009-01-01

    of CYP1A2 inhibitors and non-inhibitors. Training and test sets consisted of about 400 and 7000 compounds, respectively. Various machine learning techniques, like binary QSAR, support vector machine (SVM), random forest, kappa nearest neighbors (kNN), and decision tree methods were used to develop...

  16. Machine learning techniques for astrophysical modelling and photometric redshift estimation of quasars in optical sky surveys

    CERN Document Server

    Kumar, N Daniel

    2008-01-01

    Machine learning techniques are utilised in several areas of astrophysical research today. This dissertation addresses the application of ML techniques to two classes of problems in astrophysics, namely, the analysis of individual astronomical phenomena over time and the automated, simultaneous analysis of thousands of objects in large optical sky surveys. Specifically investigated are (1) techniques to approximate the precise orbits of the satellites of Jupiter and Saturn given Earth-based observations as well as (2) techniques to quickly estimate the distances of quasars observed in the Sloan Digital Sky Survey. Learning methods considered include genetic algorithms, particle swarm optimisation, artificial neural networks, and radial basis function networks. The first part of this dissertation demonstrates that GAs and PSOs can both be efficiently used to model functions that are highly non-linear in several dimensions. It is subsequently demonstrated in the second part that ANNs and RBFNs can be used as ef...

  17. Developing Fire Detection Algorithms by Geostationary Orbiting Platforms and Machine Learning Techniques

    Science.gov (United States)

    Salvador, Pablo; Sanz, Julia; Garcia, Miguel; Casanova, Jose Luis

    2016-08-01

    Fires in general and forest fires specific are a major concern in terms of economical and biological loses. Remote sensing technologies have been focusing on developing several algorithms, adapted to a large kind of sensors, platforms and regions in order to obtain hotspots as faster as possible. The aim of this study is to establish an automatic methodology to develop hotspots detection algorithms with Spinning Enhanced Visible and Infrared Imager (SEVIRI) sensor on board Meteosat Second Generation platform (MSG) based on machine learning techniques that can be exportable to others geostationary platforms and sensors and to any area of the Earth. The sensitivity (SE), specificity (SP) and accuracy (AC) parameters have been analyzed in order to develop the final machine learning algorithm taking into account the preferences and final use of the predicted data.

  18. GAPscreener: An automatic tool for screening human genetic association literature in PubMed using the support vector machine technique

    Directory of Open Access Journals (Sweden)

    Khoury Muin J

    2008-04-01

    Full Text Available Abstract Background Synthesis of data from published human genetic association studies is a critical step in the translation of human genome discoveries into health applications. Although genetic association studies account for a substantial proportion of the abstracts in PubMed, identifying them with standard queries is not always accurate or efficient. Further automating the literature-screening process can reduce the burden of a labor-intensive and time-consuming traditional literature search. The Support Vector Machine (SVM, a well-established machine learning technique, has been successful in classifying text, including biomedical literature. The GAPscreener, a free SVM-based software tool, can be used to assist in screening PubMed abstracts for human genetic association studies. Results The data source for this research was the HuGE Navigator, formerly known as the HuGE Pub Lit database. Weighted SVM feature selection based on a keyword list obtained by the two-way z score method demonstrated the best screening performance, achieving 97.5% recall, 98.3% specificity and 31.9% precision in performance testing. Compared with the traditional screening process based on a complex PubMed query, the SVM tool reduced by about 90% the number of abstracts requiring individual review by the database curator. The tool also ascertained 47 articles that were missed by the traditional literature screening process during the 4-week test period. We examined the literature on genetic associations with preterm birth as an example. Compared with the traditional, manual process, the GAPscreener both reduced effort and improved accuracy. Conclusion GAPscreener is the first free SVM-based application available for screening the human genetic association literature in PubMed with high recall and specificity. The user-friendly graphical user interface makes this a practical, stand-alone application. The software can be downloaded at no charge.

  19. Learning for Semantic Parsing and Natural Language Generation Using Statistical Machine Translation Techniques

    Science.gov (United States)

    2007-08-01

    XTAG grammar used by FERGUS is a bidirectional (or reversible) grammar that has been used for parsing as well ( Schabes and Joshi, 1988). The use of a...answer- ing (Wang et al., 2007), and syntactic parsing for resource-poor languages (Chiang et al., 2006). Shieber and Schabes (1990a,b) propose that... Schabes , 1990b; Bos, 2005; Zettlemoyer and Collins, 2007). In the future, we would like to devise learning algorithms similar to WASP that construct

  20. A Sociolinguistic Analysis of Polish and American Prison Slang within the Context of Selected Translation Techniques in Films with Subtitles

    Directory of Open Access Journals (Sweden)

    Katarzyna Sandra Nosek

    2016-11-01

    Full Text Available Cultural differences around the world may pose problems for translators who face issues connected with finding equivalents in source and target language occurred in the films. One of the most difficult styles is constantly changing, the hermetic and colloquial variety known as slang. Depending on the environment, it may vary, even in one language, of which an example is prison slang used by convicts to communicate with one another. Although very pejorative and full of negative connotations, it is a very curious subject matter to analyze, as well as, to investigate how it is translated, because more and more films about criminal environments are being produced. This study examines which translation techniques were used in the cases of the movies: Lockdown (2000, American Me (1992 and Animal Factory (2000. The research focuses on the issues connected with the most often used translation techniques, the reasons of using them, the other possible solutions, the untranslatable phrases and with translating taboo words.

  1. The influence of cooling techniques on cutting forces and surface roughness during cryogenic machining of titanium alloys

    Science.gov (United States)

    Wstawska, Iwona; Ślimak, Krzysztof

    2016-12-01

    Titanium alloys are one of the materials extensively used in the aerospace industry due to its excellent properties of high specific strength and corrosion resistance. On the other hand, they also present problems wherein titanium alloys are extremely difficult materials to machine. In addition, the cost associated with titanium machining is also high due to lower cutting velocities and shorter tool life. The main objective of this work is a comparison of different cooling techniques during cryogenic machining of titanium alloys. The analysis revealed that applied cooling technique has a significant influence on cutting force and surface roughness (Ra parameter) values. Furthermore, in all cases observed a positive influence of cryogenic machining on selected aspects after turning and milling of titanium alloys. This work can be also the starting point to the further research, related to the analysis of cutting forces and surface roughness during cryogenic machining of titanium alloys.

  2. Reservation Resource Technique for Virtual Machine Placement in Cloud Data Centre

    Directory of Open Access Journals (Sweden)

    Ajith Singh. N

    2014-04-01

    Full Text Available Migrations of Virtual Machine directly influence on energy consumption and QoS, to avoid migration of virtual machine when a host is overloaded a good placement technique need to be applied. Virtual Machine Placement is vital in cloud computing to utilize the resources in an efficient manner. Migration of a VM instance when a host is overloaded is familiar in cloud computing. VM selection policy finds a suitable VM to migrate from overloaded host and place to an under loaded host or turn on a new host. While migration there is small downtime of the service, even thou down time is small there is a huge change in energy consumption. Energy consumption in data centre has lead to emission of carbon dioxide to the environment. Frequent VM migration may cause the services to high latency in the network and may disturb the network environment. These works focus to reduce the VM migration, improve SLA and energy consumption. Therefore, a reservation method known as RTBBE (RTBBE (Reservation Technique Bin BECK Entropy proposed in the study that is by allocating and assigning double upper threshold with entropy method with new overload detection PR (Polynomial Regression and a VM selection policy MUR (Minimum Utilization Rank had proposed in this study. The result shows that the proposed technique reduces the energy consumption, SLA and VM migration. Experimental shows that the proposed method reduce the energy up to 21.30 kWh when the overload detection PR combines with MUR, SLA of 0.00029% with IQR with MUR and 775 VM were migrated with LRR and MC.

  3. Clustering technique-based least square support vector machine for EEG signal classification.

    Science.gov (United States)

    Siuly; Li, Yan; Wen, Peng Paul

    2011-12-01

    This paper presents a new approach called clustering technique-based least square support vector machine (CT-LS-SVM) for the classification of EEG signals. Decision making is performed in two stages. In the first stage, clustering technique (CT) has been used to extract representative features of EEG data. In the second stage, least square support vector machine (LS-SVM) is applied to the extracted features to classify two-class EEG signals. To demonstrate the effectiveness of the proposed method, several experiments have been conducted on three publicly available benchmark databases, one for epileptic EEG data, one for mental imagery tasks EEG data and another one for motor imagery EEG data. Our proposed approach achieves an average sensitivity, specificity and classification accuracy of 94.92%, 93.44% and 94.18%, respectively, for the epileptic EEG data; 83.98%, 84.37% and 84.17% respectively, for the motor imagery EEG data; and 64.61%, 58.77% and 61.69%, respectively, for the mental imagery tasks EEG data. The performance of the CT-LS-SVM algorithm is compared in terms of classification accuracy and execution (running) time with our previous study where simple random sampling with a least square support vector machine (SRS-LS-SVM) was employed for EEG signal classification. We also compare the proposed method with other existing methods in the literature for the three databases. The experimental results show that the proposed algorithm can produce a better classification rate than the previous reported methods and takes much less execution time compared to the SRS-LS-SVM technique. The research findings in this paper indicate that the proposed approach is very efficient for classification of two-class EEG signals.

  4. Technique for Calibration of Chassis components based on encoding marks and machine Vision metrology

    Institute of Scientific and Technical Information of China (English)

    SONG Li-mei; ZHANG Chun-bo; WEI Yi-ying; CHEN Hua-wei

    2011-01-01

    @@ A novel technique for calibrating crucial parameters of chassis components is proposed, which utilizes the machine vision metrology to measure 3D coordinates of the center of a component's hole for assembling in the 3D world coordinate system.In the measurement, encoding marks with special patterns will be assembled on the chassis component associated with cross drone and staff gauge located near the chassis.The geometry and coordinates of the cross drone consist of two planes orthogonal to each other and the staff gauge is in 3D space with high precision.A few images are taken by a highresolution camera in different orientations and perspectives.The 3D coordinates of 5 key points on the encoding marks will be calculated by the machine vision technique and those of the center of the holes to be calibrated will be calculated by the deduced algorithm in this paper.Experimental results show that the algorithm and the technique can satisfy the precision requirement when the components are assembled, and the average measurement precision provided by the algorithm is 0.0174 mm.

  5. OVERVIEW OF WORK PIECE TEMPERATURE MEASUREMENT TECHNIQUES FOR MACHINING OF Ti6Al4V#

    Directory of Open Access Journals (Sweden)

    P.J.T. Conradie

    2012-01-01

    Full Text Available

    ENGLISH ABSTRACT: Ti6Al4V is one of the most widely used titanium alloys in aerospace applications, but its machining remains a challenge. Comprehensive research has been done in the past, mainly investigating tool failure of various materials. Less research has been done to investigate the thermal effect of machining on work piece quality, including fatigue performance. Temperature measurement is considered to be a key enabling technology. This study presents an overview of current temperature measurement techniques for machined and tool surfaces. Two categories of methods were investigated: slower contact, and faster optical methods. Optical fibre two colour pyrometry experiments are reported that demonstrate the technique’s adequate response time. The infrared camera temperature measurement experiments synchronised temperature measurement with visual observation, aimed at mechanism analysis. The results corresponded with the literature.

    AFRIKAANSE OPSOMMING: Ti6Al4V is een van die mees gewilde lugvaart allooie, maar sy masjinering is ’n uitdaging. Bestaande navorsing dek beitelslytasie omvattend. Die termiese effek van masjinering op werkstuk integriteit, insluitend vermoeiingleeftyd, het egter veel minder dekking geniet. Temperatuurmeting wat in hierdie studie ondersoek word, word as ’n sleuteltegnologie beskou. Twee kategorië metodes is ondersoek, nl stadige kontakmetodes en optiese metodes met vinnige respons, wat die meting van oorgangsverskynsels moontlik maak. Eksperimentele werk wat beide optiese vesel tweekleurpirometrie en termiese kamera tegnieke insluit bewys die tegnieke as geskik vir die benodigde navorsing.

  6. Digital Mayhem 3D machine techniques where inspiration, techniques and digital art meet

    CERN Document Server

    Evans, Duncan

    2014-01-01

    From Icy Tundras to Desert savannahs, master the art of landscape and environment design for 2D and 3D digital content. Make it rain, shower your digital scene with a snow storm or develop a believable urban scene with a critical eye for modeling, lighting and composition. Move beyond the limitations of gallery style coffee table books with Digital Mayhem: 3D Landscapes-offering leading professional techniques, groundbreaking inspiration, and artistic mastery from some of the greatest digital artists. More than just a gallery book - each artist has written a breakdown overview, with supporting

  7. Detection of citrus canker and Huanglongbing using fluorescence imaging spectroscopy and support vector machine technique.

    Science.gov (United States)

    Wetterich, Caio Bruno; Felipe de Oliveira Neves, Ruan; Belasque, José; Marcassa, Luis Gustavo

    2016-01-10

    Citrus canker and Huanglongbing (HLB) are citrus diseases that represent a serious threat to the citrus production worldwide and may cause large economic losses. In this work, we combined fluorescence imaging spectroscopy (FIS) and a machine learning technique to discriminate between these diseases and other ordinary citrus conditions that may be present at citrus orchards, such as citrus scab and zinc deficiency. Our classification results are highly accurate when discriminating citrus canker from citrus scab (97.8%), and HLB from zinc deficiency (95%). These results show that it is possible to accurately identify citrus diseases that present similar symptoms.

  8. GPR Signal Characterization for Automated Landmine and UXO Detection Based on Machine Learning Techniques

    Directory of Open Access Journals (Sweden)

    Xavier Núñez-Nieto

    2014-10-01

    Full Text Available Landmine clearance is an ongoing problem that currently affects millions of people around the world. This study evaluates the effectiveness of ground penetrating radar (GPR in demining and unexploded ordnance detection using 2.3-GHz and 1-GHz high-frequency antennas. An automated detection tool based on machine learning techniques is also presented with the aim of automatically detecting underground explosive artifacts. A GPR survey was conducted on a designed scenario that included the most commonly buried items in historic battle fields, such as mines, projectiles and mortar grenades. The buried targets were identified using both frequencies, although the higher vertical resolution provided by the 2.3-GHz antenna allowed for better recognition of the reflection patterns. The targets were also detected automatically using machine learning techniques. Neural networks and logistic regression algorithms were shown to be able to discriminate between potential targets and clutter. The neural network had the most success, with accuracies ranging from 89% to 92% for the 1-GHz and 2.3-GHz antennas, respectively.

  9. A First Look at creating mock catalogs with machine learning techniques

    CERN Document Server

    Xu, Xiaoying; Trac, Hy; Schneider, Jeff; Poczos, Barnabas; Ntampaka, Michelle

    2013-01-01

    We investigate machine learning (ML) techniques for predicting the number of galaxies (N_gal) that occupy a halo, given the halo's properties. These types of mappings are crucial for constructing the mock galaxy catalogs necessary for analyses of large-scale structure. The ML techniques proposed here distinguish themselves from traditional halo occupation distribution (HOD) modeling as they do not assume a prescribed relationship between halo properties and N_gal. In addition, our ML approaches are only dependent on parent halo properties (like HOD methods), which are advantageous over subhalo-based approaches as identifying subhalos correctly is difficult. We test 2 algorithms: support vector machines (SVM) and k-nearest-neighbour (kNN) regression. We take galaxies and halos from the Millennium simulation and predict N_gal by training our algorithms on the following 6 halo properties: number of particles, M_200, \\sigma_v, v_max, half-mass radius and spin. For Millennium, our predicted N_gal values have a mea...

  10. Acronym Disambiguation in Spanish Electronic Health Narratives Using Machine Learning Techniques.

    Science.gov (United States)

    Rubio-López, Ignacio; Costumero, Roberto; Ambit, Héctor; Gonzalo-Martín, Consuelo; Menasalvas, Ernestina; Rodríguez González, Alejandro

    2017-01-01

    Electronic Health Records (EHRs) are now being massively used in hospitals what has motivated current developments of new methods to process clinical narratives (unstructured data) making it possible to perform context-based searches. Current approaches to process the unstructured texts in EHRs are based in applying text mining or natural language processing (NLP) techniques over the data. In particular Named Entity Recognition (NER) is of paramount importance to retrieve specific biomedical concepts from the text providing the semantic type of the concept retrieved. However, it is very common that clinical notes contain lots of acronyms that cannot be identified by NER processes and even if they are identified, an acronym may correspond to several meanings, so disambiguation of the found term is needed. In this work we provide an approach to perform acronym disambiguation in Spanish EHR using machine learning techniques.

  11. Advanced design technique of human-machine interfaces for PLC control of complex systems

    Directory of Open Access Journals (Sweden)

    Árpád-István Sütő

    2008-05-01

    Full Text Available Touchscreen operator panels proved to be a convenient succesor for clasical operator panels for implementing human-machine interfaces (HMIs in programmable logic controllers (PLC systems. The paper introduces a new technique for HMIs design in such systems, based on the idea of touchscreens replication. This redundancy allow actions which are not possible within the menus and sub-menus of a single touchscreen. Its strenght is revealed especially in complex systems, where operators can easily be overwhelmed by the huge amount of process information. The technique was applied on a mill tube rolling installation. The results also proved an increase of system security and zero downtime for HMI maintenance activities.

  12. Robot Guidance Using Machine Vision Techniques in Industrial Environments: A Comparative Review

    Directory of Open Access Journals (Sweden)

    Luis Pérez

    2016-03-01

    Full Text Available In the factory of the future, most of the operations will be done by autonomous robots that need visual feedback to move around the working space avoiding obstacles, to work collaboratively with humans, to identify and locate the working parts, to complete the information provided by other sensors to improve their positioning accuracy, etc. Different vision techniques, such as photogrammetry, stereo vision, structured light, time of flight and laser triangulation, among others, are widely used for inspection and quality control processes in the industry and now for robot guidance. Choosing which type of vision system to use is highly dependent on the parts that need to be located or measured. Thus, in this paper a comparative review of different machine vision techniques for robot guidance is presented. This work analyzes accuracy, range and weight of the sensors, safety, processing time and environmental influences. Researchers and developers can take it as a background information for their future works.

  13. Robot Guidance Using Machine Vision Techniques in Industrial Environments: A Comparative Review

    Science.gov (United States)

    Pérez, Luis; Rodríguez, Íñigo; Rodríguez, Nuria; Usamentiaga, Rubén; García, Daniel F.

    2016-01-01

    In the factory of the future, most of the operations will be done by autonomous robots that need visual feedback to move around the working space avoiding obstacles, to work collaboratively with humans, to identify and locate the working parts, to complete the information provided by other sensors to improve their positioning accuracy, etc. Different vision techniques, such as photogrammetry, stereo vision, structured light, time of flight and laser triangulation, among others, are widely used for inspection and quality control processes in the industry and now for robot guidance. Choosing which type of vision system to use is highly dependent on the parts that need to be located or measured. Thus, in this paper a comparative review of different machine vision techniques for robot guidance is presented. This work analyzes accuracy, range and weight of the sensors, safety, processing time and environmental influences. Researchers and developers can take it as a background information for their future works. PMID:26959030

  14. Binary translation using peephole translation rules

    Science.gov (United States)

    Bansal, Sorav; Aiken, Alex

    2010-05-04

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

  15. Optimization of process parameters on EN24 Tool steel using Taguchi technique in Electro-Discharge Machining (EDM)

    Science.gov (United States)

    Jeykrishnan, J.; Vijaya Ramnath, B.; Akilesh, S.; Pradeep Kumar, R. P.

    2016-09-01

    In the field of manufacturing sectors, electric discharge machining (EDM) is widely used because of its unique machining characteristics and high meticulousness which can't be done by other traditional machines. The purpose of this paper is to analyse the optimum machining parameter, to curtail the machining time with respect to high material removal rate (MRR) and low tool wear rate (TWR) by varying the parameters like current, pulse on time (Ton) and pulse off time (Toff). By conducting several dry runs using Taguchi technique of L9 orthogonal array (OA), optimized parameters were found using analysis of variance (ANOVA) and the error percentage can be validated and parameter contribution for MRR and TWR were found.

  16. Evaluating machine learning and statistical prediction techniques for landslide susceptibility modeling

    Science.gov (United States)

    Goetz, J. N.; Brenning, A.; Petschko, H.; Leopold, P.

    2015-08-01

    Statistical and now machine learning prediction methods have been gaining popularity in the field of landslide susceptibility modeling. Particularly, these data driven approaches show promise when tackling the challenge of mapping landslide prone areas for large regions, which may not have sufficient geotechnical data to conduct physically-based methods. Currently, there is no best method for empirical susceptibility modeling. Therefore, this study presents a comparison of traditional statistical and novel machine learning models applied for regional scale landslide susceptibility modeling. These methods were evaluated by spatial k-fold cross-validation estimation of the predictive performance, assessment of variable importance for gaining insights into model behavior and by the appearance of the prediction (i.e. susceptibility) map. The modeling techniques applied were logistic regression (GLM), generalized additive models (GAM), weights of evidence (WOE), the support vector machine (SVM), random forest classification (RF), and bootstrap aggregated classification trees (bundling) with penalized discriminant analysis (BPLDA). These modeling methods were tested for three areas in the province of Lower Austria, Austria. The areas are characterized by different geological and morphological settings. Random forest and bundling classification techniques had the overall best predictive performances. However, the performances of all modeling techniques were for the majority not significantly different from each other; depending on the areas of interest, the overall median estimated area under the receiver operating characteristic curve (AUROC) differences ranged from 2.9 to 8.9 percentage points. The overall median estimated true positive rate (TPR) measured at a 10% false positive rate (FPR) differences ranged from 11 to 15pp. The relative importance of each predictor was generally different between the modeling methods. However, slope angle, surface roughness and plan

  17. Coordinate space translation technique for simulation of electronic process in the ion-atom collision.

    Science.gov (United States)

    Wang, Feng; Hong, Xuhai; Wang, Jian; Kim, Kwang S

    2011-04-21

    Recently we developed a theoretical model of ion-atom collisions, which was made on the basis of a time-dependent density functional theory description of the electron dynamics and a classical treatment of the heavy particle motion. Taking advantage of the real-space grid method, we introduce a "coordinate space translation" technique to allow one to focus on a certain space of interest such as the region around the projectile or the target. Benchmark calculations are given for collisions between proton and oxygen over a wide range of impact energy. To extract the probability of charge transfer, the formulation of Lüdde and Dreizler [J. Phys. B 16, 3973 (1983)] has been generalized to ensemble-averaging application in the particular case of O((3)P). Charge transfer total cross sections are calculated, showing fairly good agreements between experimental data and present theoretical results.

  18. Teachers and Learners’ Perceptions of Applying Translation as a Method, Strategy, or Technique in an Iranian EFL Setting

    Directory of Open Access Journals (Sweden)

    Fatemeh Mollaei

    2017-04-01

    Full Text Available It has been found that translation is an efficient means to teach/learn grammar, syntax, and lexis of a foreign language. Meanwhile, translation is good for beginners who do not still enjoy the critical level of proficiency in their target language for expression.  This study was conducted to examine the teachers and learners’ perceptions of employing translation in the foreign language classroom; i.e., the effects, merits, demerits, limitations, as well as its use as a method, strategy or technique. Both quantitative and qualitative methods were used to collect and analyze the data from graduate and undergraduate learners (n=56 and teachers (n=44, male and female, who responded to two questionnaires. Additionally, only the teachers were interviewed to gain richer insight into their perceptions and attitudes. According to the results of independent samples t-test, there was no significant difference between teachers and learners’ attitude to applying translation as a method, strategy, or technique in learning a foreign language.  Based on the interview results, some teachers believed that employing translation in the foreign language context was helpful but not constantly. They claimed that translation was only effective in teaching vocabulary and grammar apart from leaners’ proficiency level as it can clarify meaning. But some other teachers noted that mother tongue would interfere with learning foreign language; they considered translation as a time-consuming activity through which students cannot capture the exact meaning.

  19. A FIRST LOOK AT CREATING MOCK CATALOGS WITH MACHINE LEARNING TECHNIQUES

    Energy Technology Data Exchange (ETDEWEB)

    Xu Xiaoying; Ho, Shirley; Trac, Hy; Schneider, Jeff; Ntampaka, Michelle [McWilliams Center for Cosmology, Department of Physics, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213 (United States); Poczos, Barnabas [School of Computer Science, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213 (United States)

    2013-08-01

    We investigate machine learning (ML) techniques for predicting the number of galaxies (N{sub gal}) that occupy a halo, given the halo's properties. These types of mappings are crucial for constructing the mock galaxy catalogs necessary for analyses of large-scale structure. The ML techniques proposed here distinguish themselves from traditional halo occupation distribution (HOD) modeling as they do not assume a prescribed relationship between halo properties and N{sub gal}. In addition, our ML approaches are only dependent on parent halo properties (like HOD methods), which are advantageous over subhalo-based approaches as identifying subhalos correctly is difficult. We test two algorithms: support vector machines (SVM) and k-nearest-neighbor (kNN) regression. We take galaxies and halos from the Millennium simulation and predict N{sub gal} by training our algorithms on the following six halo properties: number of particles, M{sub 200}, {sigma}{sub v}, v{sub max}, half-mass radius, and spin. For Millennium, our predicted N{sub gal} values have a mean-squared error (MSE) of {approx}0.16 for both SVM and kNN. Our predictions match the overall distribution of halos reasonably well and the galaxy correlation function at large scales to {approx}5%-10%. In addition, we demonstrate a feature selection algorithm to isolate the halo parameters that are most predictive, a useful technique for understanding the mapping between halo properties and N{sub gal}. Lastly, we investigate these ML-based approaches in making mock catalogs for different galaxy subpopulations (e.g., blue, red, high M{sub star}, low M{sub star}). Given its non-parametric nature as well as its powerful predictive and feature selection capabilities, ML offers an interesting alternative for creating mock catalogs.

  20. A First Look at Creating Mock Catalogs with Machine Learning Techniques

    Science.gov (United States)

    Xu, Xiaoying; Ho, Shirley; Trac, Hy; Schneider, Jeff; Poczos, Barnabas; Ntampaka, Michelle

    2013-08-01

    We investigate machine learning (ML) techniques for predicting the number of galaxies (N gal) that occupy a halo, given the halo's properties. These types of mappings are crucial for constructing the mock galaxy catalogs necessary for analyses of large-scale structure. The ML techniques proposed here distinguish themselves from traditional halo occupation distribution (HOD) modeling as they do not assume a prescribed relationship between halo properties and N gal. In addition, our ML approaches are only dependent on parent halo properties (like HOD methods), which are advantageous over subhalo-based approaches as identifying subhalos correctly is difficult. We test two algorithms: support vector machines (SVM) and k-nearest-neighbor (kNN) regression. We take galaxies and halos from the Millennium simulation and predict N gal by training our algorithms on the following six halo properties: number of particles, M 200, σ v , v max, half-mass radius, and spin. For Millennium, our predicted N gal values have a mean-squared error (MSE) of ~0.16 for both SVM and kNN. Our predictions match the overall distribution of halos reasonably well and the galaxy correlation function at large scales to ~5%-10%. In addition, we demonstrate a feature selection algorithm to isolate the halo parameters that are most predictive, a useful technique for understanding the mapping between halo properties and N gal. Lastly, we investigate these ML-based approaches in making mock catalogs for different galaxy subpopulations (e.g., blue, red, high M star, low M star). Given its non-parametric nature as well as its powerful predictive and feature selection capabilities, ML offers an interesting alternative for creating mock catalogs.

  1. Prediction of activity type in preschool children using machine learning techniques.

    Science.gov (United States)

    Hagenbuchner, Markus; Cliff, Dylan P; Trost, Stewart G; Van Tuc, Nguyen; Peoples, Gregory E

    2015-07-01

    Recent research has shown that machine learning techniques can accurately predict activity classes from accelerometer data in adolescents and adults. The purpose of this study is to develop and test machine learning models for predicting activity type in preschool-aged children. Participants completed 12 standardised activity trials (TV, reading, tablet game, quiet play, art, treasure hunt, cleaning up, active game, obstacle course, bicycle riding) over two laboratory visits. Eleven children aged 3-6 years (mean age=4.8±0.87; 55% girls) completed the activity trials while wearing an ActiGraph GT3X+ accelerometer on the right hip. Activities were categorised into five activity classes: sedentary activities, light activities, moderate to vigorous activities, walking, and running. A standard feed-forward Artificial Neural Network and a Deep Learning Ensemble Network were trained on features in the accelerometer data used in previous investigations (10th, 25th, 50th, 75th and 90th percentiles and the lag-one autocorrelation). Overall recognition accuracy for the standard feed forward Artificial Neural Network was 69.7%. Recognition accuracy for sedentary activities, light activities and games, moderate-to-vigorous activities, walking, and running was 82%, 79%, 64%, 36% and 46%, respectively. In comparison, overall recognition accuracy for the Deep Learning Ensemble Network was 82.6%. For sedentary activities, light activities and games, moderate-to-vigorous activities, walking, and running recognition accuracy was 84%, 91%, 79%, 73% and 73%, respectively. Ensemble machine learning approaches such as Deep Learning Ensemble Network can accurately predict activity type from accelerometer data in preschool children. Copyright © 2014 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

  2. Application of Machine Learning Techniques to High-Dimensional Clinical Data to Forecast Postoperative Complications.

    Directory of Open Access Journals (Sweden)

    Paul Thottakkara

    Full Text Available To compare performance of risk prediction models for forecasting postoperative sepsis and acute kidney injury.Retrospective single center cohort study of adult surgical patients admitted between 2000 and 2010.50,318 adult patients undergoing major surgery.We evaluated the performance of logistic regression, generalized additive models, naïve Bayes and support vector machines for forecasting postoperative sepsis and acute kidney injury. We assessed the impact of feature reduction techniques on predictive performance. Model performance was determined using the area under the receiver operating characteristic curve, accuracy, and positive predicted value. The results were reported based on a 70/30 cross validation procedure where the data were randomly split into 70% used for training the model and the 30% for validation.The areas under the receiver operating characteristic curve for different models ranged between 0.797 and 0.858 for acute kidney injury and between 0.757 and 0.909 for severe sepsis. Logistic regression, generalized additive model, and support vector machines had better performance compared to Naïve Bayes model. Generalized additive models additionally accounted for non-linearity of continuous clinical variables as depicted in their risk patterns plots. Reducing the input feature space with LASSO had minimal effect on prediction performance, while feature extraction using principal component analysis improved performance of the models.Generalized additive models and support vector machines had good performance as risk prediction model for postoperative sepsis and AKI. Feature extraction using principal component analysis improved the predictive performance of all models.

  3. A hybrid stock trading framework integrating technical analysis with machine learning techniques

    Directory of Open Access Journals (Sweden)

    Rajashree Dash

    2016-03-01

    Full Text Available In this paper, a novel decision support system using a computational efficient functional link artificial neural network (CEFLANN and a set of rules is proposed to generate the trading decisions more effectively. Here the problem of stock trading decision prediction is articulated as a classification problem with three class values representing the buy, hold and sell signals. The CEFLANN network used in the decision support system produces a set of continuous trading signals within the range 0–1 by analyzing the nonlinear relationship exists between few popular technical indicators. Further the output trading signals are used to track the trend and to produce the trading decision based on that trend using some trading rules. The novelty of the approach is to engender the profitable stock trading decision points through integration of the learning ability of CEFLANN neural network with the technical analysis rules. For assessing the potential use of the proposed method, the model performance is also compared with some other machine learning techniques such as Support Vector Machine (SVM, Naive Bayesian model, K nearest neighbor model (KNN and Decision Tree (DT model.

  4. Controlling the Adhesion of Superhydrophobic Surfaces Using Electrolyte Jet Machining Techniques

    Science.gov (United States)

    Yang, Xiaolong; Liu, Xin; Lu, Yao; Zhou, Shining; Gao, Mingqian; Song, Jinlong; Xu, Wenji

    2016-04-01

    Patterns with controllable adhesion on superhydrophobic areas have various biomedical and chemical applications. Electrolyte jet machining technique (EJM), an electrochemical machining method, was firstly exploited in constructing dimples with various profiles on the superhydrophobic Al alloy surface using different processing parameters. Sliding angles of water droplets on those dimples firstly increased and then stabilized at a certain value with the increase of the processing time or the applied voltages of the EJM, indicating that surfaces with different adhesion force could be obtained by regulating the processing parameters. The contact angle hysteresis and the adhesion force that restricts the droplet from sliding off were investigated through experiments. The results show that the adhesion force could be well described using the classical Furmidge equation. On account of this controllable adhesion force, water droplets could either be firmly pinned to the surface, forming various patterns or slide off at designed tilting angles at specified positions on a superhydrophobic surface. Such dimples on superhydrophopbic surfaces can be applied in water harvesting, biochemical analysis and lab-on-chip devices.

  5. Controlling the Adhesion of Superhydrophobic Surfaces Using Electrolyte Jet Machining Techniques.

    Science.gov (United States)

    Yang, Xiaolong; Liu, Xin; Lu, Yao; Zhou, Shining; Gao, Mingqian; Song, Jinlong; Xu, Wenji

    2016-04-05

    Patterns with controllable adhesion on superhydrophobic areas have various biomedical and chemical applications. Electrolyte jet machining technique (EJM), an electrochemical machining method, was firstly exploited in constructing dimples with various profiles on the superhydrophobic Al alloy surface using different processing parameters. Sliding angles of water droplets on those dimples firstly increased and then stabilized at a certain value with the increase of the processing time or the applied voltages of the EJM, indicating that surfaces with different adhesion force could be obtained by regulating the processing parameters. The contact angle hysteresis and the adhesion force that restricts the droplet from sliding off were investigated through experiments. The results show that the adhesion force could be well described using the classical Furmidge equation. On account of this controllable adhesion force, water droplets could either be firmly pinned to the surface, forming various patterns or slide off at designed tilting angles at specified positions on a superhydrophobic surface. Such dimples on superhydrophopbic surfaces can be applied in water harvesting, biochemical analysis and lab-on-chip devices.

  6. Influence of Heartwood on Wood Density and Pulp Properties Explained by Machine Learning Techniques

    Directory of Open Access Journals (Sweden)

    Carla Iglesias

    2017-01-01

    Full Text Available The aim of this work is to develop a tool to predict some pulp properties e.g., pulp yield, Kappa number, ISO brightness (ISO 2470:2008, fiber length and fiber width, using the sapwood and heartwood proportion in the raw-material. For this purpose, Acacia melanoxylon trees were collected from four sites in Portugal. Percentage of sapwood and heartwood, area and the stem eccentricity (in N-S and E-W directions were measured on transversal stem sections of A. melanoxylon R. Br. The relative position of the samples with respect to the total tree height was also considered as an input variable. Different configurations were tested until the maximum correlation coefficient was achieved. A classical mathematical technique (multiple linear regression and machine learning methods (classification and regression trees, multi-layer perceptron and support vector machines were tested. Classification and regression trees (CART was the most accurate model for the prediction of pulp ISO brightness (R = 0.85. The other parameters could be predicted with fair results (R = 0.64–0.75 by CART. Hence, the proportion of heartwood and sapwood is a relevant parameter for pulping and pulp properties, and should be taken as a quality trait when assessing a pulpwood resource.

  7. Acoustic Biometric System Based on Preprocessing Techniques and Linear Support Vector Machines.

    Science.gov (United States)

    del Val, Lara; Izquierdo-Fuente, Alberto; Villacorta, Juan J; Raboso, Mariano

    2015-06-17

    Drawing on the results of an acoustic biometric system based on a MSE classifier, a new biometric system has been implemented. This new system preprocesses acoustic images, extracts several parameters and finally classifies them, based on Support Vector Machine (SVM). The preprocessing techniques used are spatial filtering, segmentation-based on a Gaussian Mixture Model (GMM) to separate the person from the background, masking-to reduce the dimensions of images-and binarization-to reduce the size of each image. An analysis of classification error and a study of the sensitivity of the error versus the computational burden of each implemented algorithm are presented. This allows the selection of the most relevant algorithms, according to the benefits required by the system. A significant improvement of the biometric system has been achieved by reducing the classification error, the computational burden and the storage requirements.

  8. Acoustic Biometric System Based on Preprocessing Techniques and Linear Support Vector Machines

    Directory of Open Access Journals (Sweden)

    Lara del Val

    2015-06-01

    Full Text Available Drawing on the results of an acoustic biometric system based on a MSE classifier, a new biometric system has been implemented. This new system preprocesses acoustic images, extracts several parameters and finally classifies them, based on Support Vector Machine (SVM. The preprocessing techniques used are spatial filtering, segmentation—based on a Gaussian Mixture Model (GMM to separate the person from the background, masking—to reduce the dimensions of images—and binarization—to reduce the size of each image. An analysis of classification error and a study of the sensitivity of the error versus the computational burden of each implemented algorithm are presented. This allows the selection of the most relevant algorithms, according to the benefits required by the system. A significant improvement of the biometric system has been achieved by reducing the classification error, the computational burden and the storage requirements.

  9. Hybrid machine learning technique for forecasting Dhaka stock market timing decisions.

    Science.gov (United States)

    Banik, Shipra; Khodadad Khan, A F M; Anwer, Mohammad

    2014-01-01

    Forecasting stock market has been a difficult job for applied researchers owing to nature of facts which is very noisy and time varying. However, this hypothesis has been featured by several empirical experiential studies and a number of researchers have efficiently applied machine learning techniques to forecast stock market. This paper studied stock prediction for the use of investors. It is always true that investors typically obtain loss because of uncertain investment purposes and unsighted assets. This paper proposes a rough set model, a neural network model, and a hybrid neural network and rough set model to find optimal buy and sell of a share on Dhaka stock exchange. Investigational findings demonstrate that our proposed hybrid model has higher precision than the single rough set model and the neural network model. We believe this paper findings will help stock investors to decide about optimal buy and/or sell time on Dhaka stock exchange.

  10. Acoustic Biometric System Based on Preprocessing Techniques and Linear Support Vector Machines

    Science.gov (United States)

    del Val, Lara; Izquierdo-Fuente, Alberto; Villacorta, Juan J.; Raboso, Mariano

    2015-01-01

    Drawing on the results of an acoustic biometric system based on a MSE classifier, a new biometric system has been implemented. This new system preprocesses acoustic images, extracts several parameters and finally classifies them, based on Support Vector Machine (SVM). The preprocessing techniques used are spatial filtering, segmentation—based on a Gaussian Mixture Model (GMM) to separate the person from the background, masking—to reduce the dimensions of images—and binarization—to reduce the size of each image. An analysis of classification error and a study of the sensitivity of the error versus the computational burden of each implemented algorithm are presented. This allows the selection of the most relevant algorithms, according to the benefits required by the system. A significant improvement of the biometric system has been achieved by reducing the classification error, the computational burden and the storage requirements. PMID:26091392

  11. Discussion on "Techniques for Massive-Data Machine Learning in Astronomy" by A. Gray

    CERN Document Server

    Ball, Nicholas M

    2011-01-01

    Astronomy is increasingly encountering two fundamental truths: (1) The field is faced with the task of extracting useful information from extremely large, complex, and high dimensional datasets; (2) The techniques of astroinformatics and astrostatistics are the only way to make this tractable, and bring the required level of sophistication to the analysis. Thus, an approach which provides these tools in a way that scales to these datasets is not just desirable, it is vital. The expertise required spans not just astronomy, but also computer science, statistics, and informatics. As a computer scientist and expert in machine learning, Alex's contribution of expertise and a large number of fast algorithms designed to scale to large datasets, is extremely welcome. We focus in this discussion on the questions raised by the practical application of these algorithms to real astronomical datasets. That is, what is needed to maximally leverage their potential to improve the science return? This is not a trivial task. W...

  12. Fast supersymmetry phenomenology at the Large Hadron Collider using machine learning techniques

    CERN Document Server

    Buckley, A; White, M J

    2011-01-01

    A pressing problem for supersymmetry (SUSY) phenomenologists is how to incorporate Large Hadron Collider search results into parameter fits designed to measure or constrain the SUSY parameters. Owing to the computational expense of fully simulating lots of points in a generic SUSY space to aid the calculation of the likelihoods, the limits published by experimental collaborations are frequently interpreted in slices of reduced parameter spaces. For example, both ATLAS and CMS have presented results in the Constrained Minimal Supersymmetric Model (CMSSM) by fixing two of four parameters, and generating a coarse grid in the remaining two. We demonstrate that by generating a grid in the full space of the CMSSM, one can interpolate between the output of an LHC detector simulation using machine learning techniques, thus obtaining a superfast likelihood calculator for LHC-based SUSY parameter fits. We further investigate how much training data is required to obtain usable results, finding that approximately 2000 po...

  13. Modeling, Control and Analyze of Multi-Machine Drive Systems using Bond Graph Technique

    Directory of Open Access Journals (Sweden)

    J. Belhadj

    2006-03-01

    Full Text Available In this paper, a system viewpoint method has been investigated to study and analyze complex systems using Bond Graph technique. These systems are multimachine multi-inverter based on Induction Machine (IM, well used in industries like rolling mills, textile, and railway traction. These systems are multi-domains, multi-scales time and present very strong internal and external couplings, with non-linearity characterized by a high model order. The classical study with analytic model is difficult to manipulate and it is limited to some performances. In this study, a “systemic approach” is presented to design these kinds of systems, using an energetic representation based on Bond Graph formalism. Three types of multimachine are studied with their control strategies. The modeling is carried out by Bond Graph and results are discussed to show the performances of this methodology

  14. Quantum-state anomaly detection for arbitrary errors using a machine-learning technique

    Science.gov (United States)

    Hara, Satoshi; Ono, Takafumi; Okamoto, Ryo; Washio, Takashi; Takeuchi, Shigeki

    2016-10-01

    The accurate detection of small deviations in given density matrice is important for quantum information processing, which is a difficult task because of the intrinsic fluctuation in density matrices reconstructed using a limited number of experiments. We previously proposed a method for decoherence error detection using a machine-learning technique [S. Hara, T. Ono, R. Okamoto, T. Washio, and S. Takeuchi, Phys. Rev. A 89, 022104 (2014), 10.1103/PhysRevA.89.022104]. However, the previous method is not valid when the errors are just changes in phase. Here, we propose a method that is valid for arbitrary errors in density matrices. The performance of the proposed method is verified using both numerical simulation data and real experimental data.

  15. Development of Experimental Setup of Metal Rapid Prototyping Machine using Selective Laser Sintering Technique

    Science.gov (United States)

    Patil, S. N.; Mulay, A. V.; Ahuja, B. B.

    2016-08-01

    Unlike in the traditional manufacturing processes, additive manufacturing as rapid prototyping, allows designers to produce parts that were previously considered too complex to make economically. The shift is taking place from plastic prototype to fully functional metallic parts by direct deposition of metallic powders as produced parts can be directly used for desired purpose. This work is directed towards the development of experimental setup of metal rapid prototyping machine using selective laser sintering and studies the various parameters, which plays important role in the metal rapid prototyping using SLS technique. The machine structure in mainly divided into three main categories namely, (1) Z-movement of bed and table, (2) X-Y movement arrangement for LASER movements and (3) feeder mechanism. Z-movement of bed is controlled by using lead screw, bevel gear pair and stepper motor, which will maintain the accuracy of layer thickness. X-Y movements are controlled using timing belt and stepper motors for precise movements of LASER source. Feeder mechanism is then developed to control uniformity of layer thickness metal powder. Simultaneously, the study is carried out for selection of material. Various types of metal powders can be used for metal RP as Single metal powder, mixture of two metals powder, and combination of metal and polymer powder. Conclusion leads to use of mixture of two metals powder to minimize the problems such as, balling effect and porosity. Developed System can be validated by conducting various experiments on manufactured part to check mechanical and metallurgical properties. After studying the results of these experiments, various process parameters as LASER properties (as power, speed etc.), and material properties (as grain size and structure etc.) will be optimized. This work is mainly focused on the design and development of cost effective experimental setup of metal rapid prototyping using SLS technique which will gives the feel of

  16. Markerless gating for lung cancer radiotherapy based on machine learning techniques

    Energy Technology Data Exchange (ETDEWEB)

    Lin Tong; Li Ruijiang; Tang Xiaoli; Jiang, Steve B [Department of Radiation Oncology, University of California San Diego, La Jolla, CA 92093 (United States); Dy, Jennifer G [Department of Electrical and Computer Engineering, Northeastern University, Boston, MA 02115 (United States)], E-mail: sbjiang@ucsd.edu

    2009-03-21

    In lung cancer radiotherapy, radiation to a mobile target can be delivered by respiratory gating, for which we need to know whether the target is inside or outside a predefined gating window at any time point during the treatment. This can be achieved by tracking one or more fiducial markers implanted inside or near the target, either fluoroscopically or electromagnetically. However, the clinical implementation of marker tracking is limited for lung cancer radiotherapy mainly due to the risk of pneumothorax. Therefore, gating without implanted fiducial markers is a promising clinical direction. We have developed several template-matching methods for fluoroscopic marker-less gating. Recently, we have modeled the gating problem as a binary pattern classification problem, in which principal component analysis (PCA) and support vector machine (SVM) are combined to perform the classification task. Following the same framework, we investigated different combinations of dimensionality reduction techniques (PCA and four nonlinear manifold learning methods) and two machine learning classification methods (artificial neural networks-ANN and SVM). Performance was evaluated on ten fluoroscopic image sequences of nine lung cancer patients. We found that among all combinations of dimensionality reduction techniques and classification methods, PCA combined with either ANN or SVM achieved a better performance than the other nonlinear manifold learning methods. ANN when combined with PCA achieves a better performance than SVM in terms of classification accuracy and recall rate, although the target coverage is similar for the two classification methods. Furthermore, the running time for both ANN and SVM with PCA is within tolerance for real-time applications. Overall, ANN combined with PCA is a better candidate than other combinations we investigated in this work for real-time gated radiotherapy.

  17. Selection of machining datum and allocation of tolerance through tolerance charting technique

    Science.gov (United States)

    Thilak, Manoharan; Sivakumar, Karuppan; Jayaprakash, Govindharajalu

    2012-07-01

    Tolerance charting is an effective tool to determine the optimal allocation of working dimensions and working tolerances such that the blueprint dimensions and tolerances can be achieved to accomplish the cost objectives. The selection of machining datum and allocation of tolerances are critical in any machining process planning as they directly affect any setup methods/machine tools selection and machining time. This paper mainly focuses on the selection of optimum machining datums and machining tolerances simultaneously in process planning. A dynamic tolerance charting constraint scheme is developed and implemented in the optimization procedure. An optimization model is formulated for selecting machining datum and tolerances and implemented with an algorithm namely Elitist Non-Dominated Sorting Genetic Algorithm (NSGA-II).The computational results indicate that the proposed methodology is capable and robust in finding the optimal machining datum set and tolerances.

  18. Multivariate Time Series Forecasting of Crude Palm Oil Price Using Machine Learning Techniques

    Science.gov (United States)

    Kanchymalay, Kasturi; Salim, N.; Sukprasert, Anupong; Krishnan, Ramesh; Raba'ah Hashim, Ummi

    2017-08-01

    The aim of this paper was to study the correlation between crude palm oil (CPO) price, selected vegetable oil prices (such as soybean oil, coconut oil, and olive oil, rapeseed oil and sunflower oil), crude oil and the monthly exchange rate. Comparative analysis was then performed on CPO price forecasting results using the machine learning techniques. Monthly CPO prices, selected vegetable oil prices, crude oil prices and monthly exchange rate data from January 1987 to February 2017 were utilized. Preliminary analysis showed a positive and high correlation between the CPO price and soy bean oil price and also between CPO price and crude oil price. Experiments were conducted using multi-layer perception, support vector regression and Holt Winter exponential smoothing techniques. The results were assessed by using criteria of root mean square error (RMSE), means absolute error (MAE), means absolute percentage error (MAPE) and Direction of accuracy (DA). Among these three techniques, support vector regression(SVR) with Sequential minimal optimization (SMO) algorithm showed relatively better results compared to multi-layer perceptron and Holt Winters exponential smoothing method.

  19. Machine Learning Techniques for Optical Performance Monitoring from Directly Detected PDM-QAM Signals

    DEFF Research Database (Denmark)

    Thrane, Jakob; Wass, Jesper; Piels, Molly

    2017-01-01

    Linear signal processing algorithms are effective in dealing with linear transmission channel and linear signal detection, while the nonlinear signal processing algorithms, from the machine learning community, are effective in dealing with nonlinear transmission channel and nonlinear signal...... detection. In this paper, a brief overview of the various machine learning methods and their application in optical communication is presented and discussed. Moreover, supervised machine learning methods, such as neural networks and support vector machine, are experimentally demonstrated for in-band optical...

  20. 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 .

  1. Machine learning techniques in disease forecasting: a case study on rice blast prediction

    Directory of Open Access Journals (Sweden)

    Kapoor Amar S

    2006-11-01

    Full Text Available Abstract Background Diverse modeling approaches viz. neural networks and multiple regression have been followed to date for disease prediction in plant populations. However, due to their inability to predict value of unknown data points and longer training times, there is need for exploiting new prediction softwares for better understanding of plant-pathogen-environment relationships. Further, there is no online tool available which can help the plant researchers or farmers in timely application of control measures. This paper introduces a new prediction approach based on support vector machines for developing weather-based prediction models of plant diseases. Results Six significant weather variables were selected as predictor variables. Two series of models (cross-location and cross-year were developed and validated using a five-fold cross validation procedure. For cross-year models, the conventional multiple regression (REG approach achieved an average correlation coefficient (r of 0.50, which increased to 0.60 and percent mean absolute error (%MAE decreased from 65.42 to 52.24 when back-propagation neural network (BPNN was used. With generalized regression neural network (GRNN, the r increased to 0.70 and %MAE also improved to 46.30, which further increased to r = 0.77 and %MAE = 36.66 when support vector machine (SVM based method was used. Similarly, cross-location validation achieved r = 0.48, 0.56 and 0.66 using REG, BPNN and GRNN respectively, with their corresponding %MAE as 77.54, 66.11 and 58.26. The SVM-based method outperformed all the three approaches by further increasing r to 0.74 with improvement in %MAE to 44.12. Overall, this SVM-based prediction approach will open new vistas in the area of forecasting plant diseases of various crops. Conclusion Our case study demonstrated that SVM is better than existing machine learning techniques and conventional REG approaches in forecasting plant diseases. In this direction, we have also

  2. Closing the gap: accelerating the translational process in nanomedicine by proposing standardized characterization techniques.

    Science.gov (United States)

    Khorasani, Ali A; Weaver, James L; Salvador-Morales, Carolina

    2014-01-01

    On the cusp of widespread permeation of nanomedicine, academia, industry, and government have invested substantial financial resources in developing new ways to better treat diseases. Materials have unique physical and chemical properties at the nanoscale compared with their bulk or small-molecule analogs. These unique properties have been greatly advantageous in providing innovative solutions for medical treatments at the bench level. However, nanomedicine research has not yet fully permeated the clinical setting because of several limitations. Among these limitations are the lack of universal standards for characterizing nanomaterials and the limited knowledge that we possess regarding the interactions between nanomaterials and biological entities such as proteins. In this review, we report on recent developments in the characterization of nanomaterials as well as the newest information about the interactions between nanomaterials and proteins in the human body. We propose a standard set of techniques for universal characterization of nanomaterials. We also address relevant regulatory issues involved in the translational process for the development of drug molecules and drug delivery systems. Adherence and refinement of a universal standard in nanomaterial characterization as well as the acquisition of a deeper understanding of nanomaterials and proteins will likely accelerate the use of nanomedicine in common practice to a great extent.

  3. Closing the gap: accelerating the translational process in nanomedicine by proposing standardized characterization techniques

    Science.gov (United States)

    Khorasani, Ali A; Weaver, James L; Salvador-Morales, Carolina

    2014-01-01

    On the cusp of widespread permeation of nanomedicine, academia, industry, and government have invested substantial financial resources in developing new ways to better treat diseases. Materials have unique physical and chemical properties at the nanoscale compared with their bulk or small-molecule analogs. These unique properties have been greatly advantageous in providing innovative solutions for medical treatments at the bench level. However, nanomedicine research has not yet fully permeated the clinical setting because of several limitations. Among these limitations are the lack of universal standards for characterizing nanomaterials and the limited knowledge that we possess regarding the interactions between nanomaterials and biological entities such as proteins. In this review, we report on recent developments in the characterization of nanomaterials as well as the newest information about the interactions between nanomaterials and proteins in the human body. We propose a standard set of techniques for universal characterization of nanomaterials. We also address relevant regulatory issues involved in the translational process for the development of drug molecules and drug delivery systems. Adherence and refinement of a universal standard in nanomaterial characterization as well as the acquisition of a deeper understanding of nanomaterials and proteins will likely accelerate the use of nanomedicine in common practice to a great extent. PMID:25525356

  4. Issues and Techniques in Translating Scientific Terms from English to Khmer for a University-Level Text in Cambodia

    Science.gov (United States)

    Quigley, Cassie; Oliviera, Alandeom W.; Curry, Alastair; Buck, Gayle

    2011-01-01

    Teachers and students spend much time interacting with written resources such as textbooks, tests, or worksheets during classroom instruction. What if no text is available, however, in the language of the learners? This case study describes the processes and techniques adopted by two university lecturers in Cambodia, as they translated an L1…

  5. Machine Learning and Radiology

    Science.gov (United States)

    Wang, Shijun; Summers, Ronald M.

    2012-01-01

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

  6. 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...

  7. A methodology for automated CPA extraction using liver biopsy image analysis and machine learning techniques.

    Science.gov (United States)

    Tsipouras, Markos G; Giannakeas, Nikolaos; Tzallas, Alexandros T; Tsianou, Zoe E; Manousou, Pinelopi; Hall, Andrew; Tsoulos, Ioannis; Tsianos, Epameinondas

    2017-03-01

    Collagen proportional area (CPA) extraction in liver biopsy images provides the degree of fibrosis expansion in liver tissue, which is the most characteristic histological alteration in hepatitis C virus (HCV). Assessment of the fibrotic tissue is currently based on semiquantitative staging scores such as Ishak and Metavir. Since its introduction as a fibrotic tissue assessment technique, CPA calculation based on image analysis techniques has proven to be more accurate than semiquantitative scores. However, CPA has yet to reach everyday clinical practice, since the lack of standardized and robust methods for computerized image analysis for CPA assessment have proven to be a major limitation. The current work introduces a three-stage fully automated methodology for CPA extraction based on machine learning techniques. Specifically, clustering algorithms have been employed for background-tissue separation, as well as for fibrosis detection in liver tissue regions, in the first and the third stage of the methodology, respectively. Due to the existence of several types of tissue regions in the image (such as blood clots, muscle tissue, structural collagen, etc.), classification algorithms have been employed to identify liver tissue regions and exclude all other non-liver tissue regions from CPA computation. For the evaluation of the methodology, 79 liver biopsy images have been employed, obtaining 1.31% mean absolute CPA error, with 0.923 concordance correlation coefficient. The proposed methodology is designed to (i) avoid manual threshold-based and region selection processes, widely used in similar approaches presented in the literature, and (ii) minimize CPA calculation time. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  8. Analysed potential of big data and supervised machine learning techniques in effectively forecasting travel times from fused data

    Directory of Open Access Journals (Sweden)

    Ivana Šemanjski

    2015-12-01

    Full Text Available Travel time forecasting is an interesting topic for many ITS services. Increased availability of data collection sensors increases the availability of the predictor variables but also highlights the high processing issues related to this big data availability. In this paper we aimed to analyse the potential of big data and supervised machine learning techniques in effectively forecasting travel times. For this purpose we used fused data from three data sources (Global Positioning System vehicles tracks, road network infrastructure data and meteorological data and four machine learning techniques (k-nearest neighbours, support vector machines, boosting trees and random forest. To evaluate the forecasting results we compared them in-between different road classes in the context of absolute values, measured in minutes, and the mean squared percentage error. For the road classes with the high average speed and long road segments, machine learning techniques forecasted travel times with small relative error, while for the road classes with the small average speeds and segment lengths this was a more demanding task. All three data sources were proven itself to have a high impact on the travel time forecast accuracy and the best results (taking into account all road classes were achieved for the k-nearest neighbours and random forest techniques.

  9. 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.

  10. 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.

  11. 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.

  12. 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)

  13. Phase segmentation of X-ray computer tomography rock images using machine learning techniques: an accuracy and performance study

    Science.gov (United States)

    Chauhan, Swarup; Rühaak, Wolfram; Anbergen, Hauke; Kabdenov, Alen; Freise, Marcus; Wille, Thorsten; Sass, Ingo

    2016-07-01

    Performance and accuracy of machine learning techniques to segment rock grains, matrix and pore voxels from a 3-D volume of X-ray tomographic (XCT) grayscale rock images was evaluated. The segmentation and classification capability of unsupervised (k-means, fuzzy c-means, self-organized maps), supervised (artificial neural networks, least-squares support vector machines) and ensemble classifiers (bragging and boosting) were tested using XCT images of andesite volcanic rock, Berea sandstone, Rotliegend sandstone and a synthetic sample. The averaged porosity obtained for andesite (15.8 ± 2.5 %), Berea sandstone (16.3 ± 2.6 %), Rotliegend sandstone (13.4 ± 7.4 %) and the synthetic sample (48.3 ± 13.3 %) is in very good agreement with the respective laboratory measurement data and varies by a factor of 0.2. The k-means algorithm is the fastest of all machine learning algorithms, whereas a least-squares support vector machine is the most computationally expensive. Metrics entropy, purity, mean square root error, receiver operational characteristic curve and 10 K-fold cross-validation were used to determine the accuracy of unsupervised, supervised and ensemble classifier techniques. In general, the accuracy was found to be largely affected by the feature vector selection scheme. As it is always a trade-off between performance and accuracy, it is difficult to isolate one particular machine learning algorithm which is best suited for the complex phase segmentation problem. Therefore, our investigation provides parameters that can help in selecting the appropriate machine learning techniques for phase segmentation.

  14. Taxi Time Prediction at Charlotte Airport Using Fast-Time Simulation and Machine Learning Techniques

    Science.gov (United States)

    Lee, Hanbong

    2016-01-01

    Accurate taxi time prediction is required for enabling efficient runway scheduling that can increase runway throughput and reduce taxi times and fuel consumptions on the airport surface. Currently NASA and American Airlines are jointly developing a decision-support tool called Spot and Runway Departure Advisor (SARDA) that assists airport ramp controllers to make gate pushback decisions and improve the overall efficiency of airport surface traffic. In this presentation, we propose to use Linear Optimized Sequencing (LINOS), a discrete-event fast-time simulation tool, to predict taxi times and provide the estimates to the runway scheduler in real-time airport operations. To assess its prediction accuracy, we also introduce a data-driven analytical method using machine learning techniques. These two taxi time prediction methods are evaluated with actual taxi time data obtained from the SARDA human-in-the-loop (HITL) simulation for Charlotte Douglas International Airport (CLT) using various performance measurement metrics. Based on the taxi time prediction results, we also discuss how the prediction accuracy can be affected by the operational complexity at this airport and how we can improve the fast time simulation model before implementing it with an airport scheduling algorithm in a real-time environment.

  15. Evaluating machine-learning techniques for recruitment forecasting of seven North East Atlantic fish species

    KAUST Repository

    Fernandes, José Antonio

    2015-01-01

    The effect of different factors (spawning biomass, environmental conditions) on recruitment is a subject of great importance in the management of fisheries, recovery plans and scenario exploration. In this study, recently proposed supervised classification techniques, tested by the machine-learning community, are applied to forecast the recruitment of seven fish species of North East Atlantic (anchovy, sardine, mackerel, horse mackerel, hake, blue whiting and albacore), using spawning, environmental and climatic data. In addition, the use of the probabilistic flexible naive Bayes classifier (FNBC) is proposed as modelling approach in order to reduce uncertainty for fisheries management purposes. Those improvements aim is to improve probability estimations of each possible outcome (low, medium and high recruitment) based in kernel density estimation, which is crucial for informed management decision making with high uncertainty. Finally, a comparison between goodness-of-fit and generalization power is provided, in order to assess the reliability of the final forecasting models. It is found that in most cases the proposed methodology provides useful information for management whereas the case of horse mackerel is an example of the limitations of the approach. The proposed improvements allow for a better probabilistic estimation of the different scenarios, i.e. to reduce the uncertainty in the provided forecasts.

  16. Online laboratory evaluation of seeding-machine application by an acoustic technique

    Energy Technology Data Exchange (ETDEWEB)

    Karimi, H.; Navid, H.; Mahmoudi, A.

    2015-07-01

    Researchers and planter manufacturers have been working closely to develop an automated system for evaluating performance of seeding. In the present study, an innovative use of acoustic signal for laboratory evaluation of seeding-machine application is described. Seed detection technique of the proposed system was based on a rising voltage value that a microphone sensed in each impaction of seeds to a steel plate. Online determining of seed spacing was done with a script which was written in MATLAB software. To evaluate the acoustic system with desired seed spacing, a testing rig was designed. Seeds of wheat, corn and pelleted tomato were used as experimental material. Typical seed patterns were positioned manually on a belt stand with different spacing patterns. When the belt was running, the falling seeds from the end point of the belt impacted to the steel plate, and their acoustic signal was sensed by the microphone. In each impact, data was processed and spacing between the seeds was automatically obtained. Coefficient of determination of gathered data from the belt system and the corresponding seeds spacing measured with the acoustic system in all runs was about 0.98. This strong correlation indicates that the acoustic system worked well in determining the seeds spacing. (Author)

  17. Predicting Software Faults in Large Space Systems using Machine Learning Techniques

    Directory of Open Access Journals (Sweden)

    Bhekisipho Twala

    2011-07-01

    Full Text Available Recently, the use of machine learning (ML algorithms has proven to be of great practical value in solving a variety of engineering problems including the prediction of failure, fault, and defect-proneness as the space system software becomes complex. One of the most active areas of recent research in ML has been the use of ensemble classifiers. How ML techniques (or classifiers could be used to predict software faults in space systems, including many aerospace systems is shown, and further use ensemble individual classifiers by having them vote for the most popular class to improve system software fault-proneness prediction. Benchmarking results on four NASA public datasets show the Naive Bayes classifier as more robust software fault prediction while most ensembles with a decision tree classifier as one of its components achieve higher accuracy rates.Defence Science Journal, 2011, 61(4, pp.306-316, DOI:http://dx.doi.org/10.14429/dsj.61.1088

  18. Machine Learning Techniques Applied to Sensor Data Correction in Building Technologies

    Energy Technology Data Exchange (ETDEWEB)

    Smith, Matt K [ORNL; Castello, Charles C [ORNL; New, Joshua Ryan [ORNL

    2013-01-01

    Since commercial and residential buildings account for nearly half of the United States' energy consumption, making them more energy-efficient is a vital part of the nation's overall energy strategy. Sensors play an important role in this research by collecting data needed to analyze performance of components, systems, and whole-buildings. Given this reliance on sensors, ensuring that sensor data are valid is a crucial problem. Solutions being researched are machine learning techniques, namely: artificial neural networks and Bayesian Networks. Types of data investigated in this study are: (1) temperature; (2) humidity; (3) refrigerator energy consumption; (4) heat pump liquid pressure; and (5) water flow. These data are taken from Oak Ridge National Laboratory's (ORNL) ZEBRAlliance research project which is composed of four single-family homes in Oak Ridge, TN. Results show that for the temperature, humidity, pressure, and flow sensors, data can mostly be predicted with root-mean-square error (RMSE) of less than 10% of the respective sensor's mean value. Results for the energy sensor are not as good; RMSE are centered about 100% of the mean value and are often well above 200%. Bayesian networks have RSME of less than 5% of the respective sensor's mean value, but took substantially longer to train.

  19. Estimating gypsum equirement under no-till based on machine learning technique

    Directory of Open Access Journals (Sweden)

    Alaine Margarete Guimarães

    Full Text Available Chemical stratification occurs under no-till systems, including pH, considering that higher levels are formed from the soil surface towards the deeper layers. The subsoil acidity is a limiting factor of the yield. Gypsum has been suggested when subsoil acidity limits the crops root growth, i.e., when the calcium (Ca level is low and/or the aluminum (Al level is toxic in the subsoil layers. However, there are doubts about the more efficient methods to estimate the gypsum requirement. This study was carried out to develop numerical models to estimate the gypsum requirement in soils under no-till system by the use of Machine Learning techniques. Computational analyses of the dataset were made applying the M5'Rules algorithm, based on regression models. The dataset comprised of soil chemical properties collected from experiments under no-till that received gypsum rates on the soil surface, throughout eight years after the application, in Southern Brazil. The results showed that the numerical models generated by rule induction M5'Rules algorithm were positively useful contributing for estimate the gypsum requirements under no-till. The models showed that Ca saturation in the effective cation exchange capacity (ECEC was a more important attribute than Al saturation to estimate gypsum requirement in no-till soils.

  20. Modelling and analysing track cycling Omnium performances using statistical and machine learning techniques.

    Science.gov (United States)

    Ofoghi, Bahadorreza; Zeleznikow, John; Dwyer, Dan; Macmahon, Clare

    2013-01-01

    This article describes the utilisation of an unsupervised machine learning technique and statistical approaches (e.g., the Kolmogorov-Smirnov test) that assist cycling experts in the crucial decision-making processes for athlete selection, training, and strategic planning in the track cycling Omnium. The Omnium is a multi-event competition that will be included in the summer Olympic Games for the first time in 2012. Presently, selectors and cycling coaches make decisions based on experience and intuition. They rarely have access to objective data. We analysed both the old five-event (first raced internationally in 2007) and new six-event (first raced internationally in 2011) Omniums and found that the addition of the elimination race component to the Omnium has, contrary to expectations, not favoured track endurance riders. We analysed the Omnium data and also determined the inter-relationships between different individual events as well as between those events and the final standings of riders. In further analysis, we found that there is no maximum ranking (poorest performance) in each individual event that riders can afford whilst still winning a medal. We also found the required times for riders to finish the timed components that are necessary for medal winning. The results of this study consider the scoring system of the Omnium and inform decision-making toward successful participation in future major Omnium competitions.

  1. Current breathomics-a review on data pre-processing techniques and machine learning in metabolomics breath analysis

    DEFF Research Database (Denmark)

    Smolinska, A.; Hauschild, A. C.; Fijten, R. R. R.

    2014-01-01

    been extensively developed. Yet, the application of machine learning methods for fingerprinting VOC profiles in the breathomics is still in its infancy. Therefore, in this paper, we describe the current state of the art in data pre-processing and multivariate analysis of breathomics data. We start...... different conditions (e.g. disease stage, treatment). Independently of the utilized analytical method, the most important question, 'which VOCs are discriminatory?', remains the same. Answers can be given by several modern machine learning techniques (multivariate statistics) and, therefore, are the focus...

  2. Advancing Research in Second Language Writing through Computational Tools and Machine Learning Techniques: A Research Agenda

    Science.gov (United States)

    Crossley, Scott A.

    2013-01-01

    This paper provides an agenda for replication studies focusing on second language (L2) writing and the use of natural language processing (NLP) tools and machine learning algorithms. Specifically, it introduces a range of the available NLP tools and machine learning algorithms and demonstrates how these could be used to replicate seminal studies…

  3. Advancing Research in Second Language Writing through Computational Tools and Machine Learning Techniques: A Research Agenda

    Science.gov (United States)

    Crossley, Scott A.

    2013-01-01

    This paper provides an agenda for replication studies focusing on second language (L2) writing and the use of natural language processing (NLP) tools and machine learning algorithms. Specifically, it introduces a range of the available NLP tools and machine learning algorithms and demonstrates how these could be used to replicate seminal studies…

  4. 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.

  5. Technique of performing construction works by machines with hybrid: manual and remote control

    Directory of Open Access Journals (Sweden)

    Sevryugina Nadezhda

    2017-01-01

    Full Text Available The article discusses issues dealing with efficiency of construction work mechanization. It offers a mathematical model for assessment of mutual influence between the members of the ‘construction site-machine-operator’ system triad, that can give a quantitative assessment of how the efficiency of a technological task varies with more comprehensive use of operational capacities of the machine, while lower effect that limiting parameters of production environment and technical condition of the machine have on the operator. The article contains a constructive remote control solution for upgrade of the base machine. It describes the conditions for using the machines with hybrid: manual and remote control at construction sites. There is also an imitation model of operator’s scanning pattern and data experimental research that prove the efficiency of remotely controlled technological operations. The article proves that lower psychological load on the operator and better comfort contribute to positive economic effect and higher quality of the construction process.

  6. 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.

  7. Feature-Free Activity Classification of Inertial Sensor Data With Machine Vision Techniques: Method, Development, and Evaluation.

    Science.gov (United States)

    Dominguez Veiga, Jose Juan; O'Reilly, Martin; Whelan, Darragh; Caulfield, Brian; Ward, Tomas E

    2017-08-04

    Inertial sensors are one of the most commonly used sources of data for human activity recognition (HAR) and exercise detection (ED) tasks. The time series produced by these sensors are generally analyzed through numerical methods. Machine learning techniques such as random forests or support vector machines are popular in this field for classification efforts, but they need to be supported through the isolation of a potentially large number of additionally crafted features derived from the raw data. This feature preprocessing step can involve nontrivial digital signal processing (DSP) techniques. However, in many cases, the researchers interested in this type of activity recognition problems do not possess the necessary technical background for this feature-set development. The study aimed to present a novel application of established machine vision methods to provide interested researchers with an easier entry path into the HAR and ED fields. This can be achieved by removing the need for deep DSP skills through the use of transfer learning. This can be done by using a pretrained convolutional neural network (CNN) developed for machine vision purposes for exercise classification effort. The new method should simply require researchers to generate plots of the signals that they would like to build classifiers with, store them as images, and then place them in folders according to their training label before retraining the network. We applied a CNN, an established machine vision technique, to the task of ED. Tensorflow, a high-level framework for machine learning, was used to facilitate infrastructure needs. Simple time series plots generated directly from accelerometer and gyroscope signals are used to retrain an openly available neural network (Inception), originally developed for machine vision tasks. Data from 82 healthy volunteers, performing 5 different exercises while wearing a lumbar-worn inertial measurement unit (IMU), was collected. The ability of the

  8. [Influence of milking technique, milking hygiene and environmental hygiene parameters on the microbial contamination of milking machines].

    Science.gov (United States)

    Feldmann, M; Zimmermann, A; Hoedemaker, M

    2006-07-01

    It was the aim of this study to investigate the effect of various factors of the milking technique, milking hygiene and environment on microbial contamination of the milking machine. In 31 dairy herds, the degree of bacterial contamination was examined by taking swabs at four locations (teat cup liner, claw, short and long milk tube) before the milking procedure was started using a standardized protocol (DIN ISO 6887-1:1999). Furthermore, the total germ count was determined in the first milk entering the bulk tank as well as in the bulk tank milk following milking. For each farm, the quality of the milking process and the condition of the milking machine as well as of various environmental factors were recorded. A subjective evaluation of the status of the milking cluster or other parts of the milking machine ("good" or "moderate-poor") gave more information about bacterial contamination than the determination of age and type of material used. A temperature of the rinsing water of teat cleaning before milking or of postmilking teat disinfection did not affect the contamination of the milking machine and the bulk tank milk with environmental bacteria. Furthermore, type of bedding material affected bacterial contamination of milking clusters and bulk tank milk. In conclusion, our results suggest that the microbial contamination of the milking machine is not only influenced by the sanitation pro-

  9. Laser machining of advanced materials

    CERN Document Server

    Dahotre, Narendra B

    2011-01-01

    Advanced materialsIntroductionApplicationsStructural ceramicsBiomaterials CompositesIntermetallicsMachining of advanced materials IntroductionFabrication techniquesMechanical machiningChemical Machining (CM)Electrical machiningRadiation machining Hybrid machiningLaser machiningIntroductionAbsorption of laser energy and multiple reflectionsThermal effectsLaser machining of structural ceramicsIntrodu

  10. Machine Learning Techniques for the Detection of Shockable Rhythms in Automated External Defibrillators

    Science.gov (United States)

    Irusta, Unai; Morgado, Eduardo; Aramendi, Elisabete; Ayala, Unai; Wik, Lars; Kramer-Johansen, Jo; Eftestøl, Trygve; Alonso-Atienza, Felipe

    2016-01-01

    Early recognition of ventricular fibrillation (VF) and electrical therapy are key for the survival of out-of-hospital cardiac arrest (OHCA) patients treated with automated external defibrillators (AED). AED algorithms for VF-detection are customarily assessed using Holter recordings from public electrocardiogram (ECG) databases, which may be different from the ECG seen during OHCA events. This study evaluates VF-detection using data from both OHCA patients and public Holter recordings. ECG-segments of 4-s and 8-s duration were analyzed. For each segment 30 features were computed and fed to state of the art machine learning (ML) algorithms. ML-algorithms with built-in feature selection capabilities were used to determine the optimal feature subsets for both databases. Patient-wise bootstrap techniques were used to evaluate algorithm performance in terms of sensitivity (Se), specificity (Sp) and balanced error rate (BER). Performance was significantly better for public data with a mean Se of 96.6%, Sp of 98.8% and BER 2.2% compared to a mean Se of 94.7%, Sp of 96.5% and BER 4.4% for OHCA data. OHCA data required two times more features than the data from public databases for an accurate detection (6 vs 3). No significant differences in performance were found for different segment lengths, the BER differences were below 0.5-points in all cases. Our results show that VF-detection is more challenging for OHCA data than for data from public databases, and that accurate VF-detection is possible with segments as short as 4-s. PMID:27441719

  11. Translation, rotation, and scale invariant image registration technique using angular and radial difference functions

    Institute of Scientific and Technical Information of China (English)

    Li Li; Qingshuang Zeng; Fanfeng Meng

    2008-01-01

    An algorithm is proposed for registering images related by translation, rotation, and scale based on angular and radial difference fimctions. In frequency domain, the spatial translation parameters are computed via phase correlation method. The magnitudes of images are represented in log-polar grid, and the angular and radial difference functions are given and applied to measure shifts in both angular and radial dimensions for rotation and scale estimation. Experimental results show that this method achieves the same accurate level as classic fast Fourier transform (FFT) based method with invariance to illumination change and lower computation costs.

  12. Rotation, scaling, and translation invariant local watermarking technique with Krawtchouk moments

    Institute of Scientific and Technical Information of China (English)

    Li Zhang; Weiwei Xiao; Gongbin Qian; Zhen Ji

    2007-01-01

    A rotation, scaling, and translation invariant local watermarking is proposed with one or two Krawtchouk moment(s) of the original to estimate the geometric distortion parameters including rotation angle, scaling factor, and translation parameter. Krawtchouk moments can be used as private key of watermark extractor.Watermark is inserted into perceptually significant Krawtchouk moments of original, and watermark based on Krawtchouk moments is local. Independent component analysis (ICA) is utilized to extract watermark blindly. Experimental results show that this method has a good robustness against distortions preformed by watermark benchmark Stirmark.

  13. Results of error correction techniques applied on two high accuracy coordinate measuring machines

    Energy Technology Data Exchange (ETDEWEB)

    Pace, C.; Doiron, T.; Stieren, D.; Borchardt, B.; Veale, R. (Sandia National Labs., Albuquerque, NM (USA); National Inst. of Standards and Technology, Gaithersburg, MD (USA))

    1990-01-01

    The Primary Standards Laboratory at Sandia National Laboratories (SNL) and the Precision Engineering Division at the National Institute of Standards and Technology (NIST) are in the process of implementing software error correction on two nearly identical high-accuracy coordinate measuring machines (CMMs). Both machines are Moore Special Tool Company M-48 CMMs which are fitted with laser positioning transducers. Although both machines were manufactured to high tolerance levels, the overall volumetric accuracy was insufficient for calibrating standards to the levels both laboratories require. The error mapping procedure was developed at NIST in the mid 1970's on an earlier but similar model. The error mapping procedure was originally very complicated and did not make any assumptions about the rigidness of the machine as it moved, each of the possible error motions was measured at each point of the error map independently. A simpler mapping procedure was developed during the early 1980's which assumed rigid body motion of the machine. This method has been used to calibrate lower accuracy machines with a high degree of success and similar software correction schemes have been implemented by many CMM manufacturers. The rigid body model has not yet been used on highly repeatable CMMs such as the M48. In this report we present early mapping data for the two M48 CMMs. The SNL CMM was manufactured in 1985 and has been in service for approximately four years, whereas the NIST CMM was delivered in early 1989. 4 refs., 5 figs.

  14. In vitro biological characterization of macroporous 3D Bonelike structures prepared through a 3D machining technique

    Energy Technology Data Exchange (ETDEWEB)

    Laranjeira, M.S.; Dias, A.G. [INEB - Instituto de Engenharia Biomedica, Divisao de Biomateriais, Universidade do Porto, Rua do Campo Alegre, 823, 4150-180 Porto (Portugal); Santos, J.D. [INEB - Instituto de Engenharia Biomedica, Divisao de Biomateriais, Universidade do Porto, Rua do Campo Alegre, 823, 4150-180 Porto (Portugal); Universidade do Porto, Faculdade de Engenharia, Departamento de Engenharia Metalurgica e Materiais, Rua Dr. Roberto Frias, 4200-465 Porto - Portugal (Portugal); Fernandes, M.H., E-mail: mhrf@portugalmail.pt [Universidade do Porto, Faculdade de Medicina Dentaria, Laboratorio de Farmacologia e Biocompatibilidade Celular, Rua Dr. Manuel Pereira da Silva, 4200-392 Porto (Portugal)

    2009-04-30

    3D bioactive macroporous structures were prepared using a 3D machining technique. A virtual 3D structure model was created and a computer numerically controlled (CNC) milling device machined Bonelike samples. The resulting structures showed a reproducible macroporosity and interconnective structure. Macropores size after sintering was approximately 2000 {mu}m. In vitro testing using human bone marrow stroma showed that cells were able to adhere and proliferate on 3D structures surface and migrate into all macropore channels. In addition, these cells were able to differentiate, since mineralized globular structures associated with cell layer were identified. Results obtained showed that 3D structures of Bonelike successfully allow cell migration into all macropores, and allow human bone marrow stromal cells to proliferate and differentiate. This innovative technique may be considered as a step-forward preparation for 3D interconnective macroporous structures that allow bone ingrowth while maintaining mechanical integrity.

  15. Modelling and Calibration Technique of Laser Triangulation Sensors for Integration in Robot Arms and Articulated Arm Coordinate Measuring Machines

    Directory of Open Access Journals (Sweden)

    Juan J. Aguilar

    2009-09-01

    Full Text Available A technique for intrinsic and extrinsic calibration of a laser triangulation sensor (LTS integrated in an articulated arm coordinate measuring machine (AACMM is presented in this paper. After applying a novel approach to the AACMM kinematic parameter identification problem, by means of a single calibration gauge object, a one-step calibration method to obtain both intrinsic―laser plane, CCD sensor and camera geometry―and extrinsic parameters related to the AACMM main frame has been developed. This allows the integration of LTS and AACMM mathematical models without the need of additional optimization methods after the prior sensor calibration, usually done in a coordinate measuring machine (CMM before the assembly of the sensor in the arm. The experimental tests results for accuracy and repeatability show the suitable performance of this technique, resulting in a reliable, quick and friendly calibration method for the AACMM final user. The presented method is also valid for sensor integration in robot arms and CMMs.

  16. Modelling and calibration technique of laser triangulation sensors for integration in robot arms and articulated arm coordinate measuring machines.

    Science.gov (United States)

    Santolaria, Jorge; Guillomía, David; Cajal, Carlos; Albajez, José A; Aguilar, Juan J

    2009-01-01

    A technique for intrinsic and extrinsic calibration of a laser triangulation sensor (LTS) integrated in an articulated arm coordinate measuring machine (AACMM) is presented in this paper. After applying a novel approach to the AACMM kinematic parameter identification problem, by means of a single calibration gauge object, a one-step calibration method to obtain both intrinsic-laser plane, CCD sensor and camera geometry-and extrinsic parameters related to the AACMM main frame has been developed. This allows the integration of LTS and AACMM mathematical models without the need of additional optimization methods after the prior sensor calibration, usually done in a coordinate measuring machine (CMM) before the assembly of the sensor in the arm. The experimental tests results for accuracy and repeatability show the suitable performance of this technique, resulting in a reliable, quick and friendly calibration method for the AACMM final user. The presented method is also valid for sensor integration in robot arms and CMMs.

  17. GeckoFTL: Scalable Flash Translation Techniques For Very Large Flash Devices

    DEFF Research Database (Denmark)

    Dayan, Niv; Bonnet, Philippe; Idreos, Stratos

    2016-01-01

    The volume of metadata needed by a flash translation layer (FTL) is proportional to the storage capacity of a flash device. Ideally, this metadata should reside in the device's integrated RAM to enable fast access. However, as flash devices scale to terabytes, the necessary volume of metadata...

  18. Modelling and Calibration Technique of Laser Triangulation Sensors for Integration in Robot Arms and Articulated Arm Coordinate Measuring Machines

    OpenAIRE

    Aguilar, Juan J.; Albajez, José A.; Carlos Cajal; David Guillomía; Jorge Santolaria

    2009-01-01

    A technique for intrinsic and extrinsic calibration of a laser triangulation sensor (LTS) integrated in an articulated arm coordinate measuring machine (AACMM) is presented in this paper. After applying a novel approach to the AACMM kinematic parameter identification problem, by means of a single calibration gauge object, a one-step calibration method to obtain both intrinsic―laser plane, CCD sensor and camera geometry―and extrinsic parameters related to the AACMM main frame has been develope...

  19. The Smart Aerial Release Machine, a Universal System for Applying the Sterile Insect Technique

    Science.gov (United States)

    Mubarqui, Ruben Leal; Perez, Rene Cano; Kladt, Roberto Angulo; Lopez, Jose Luis Zavala; Parker, Andrew; Seck, Momar Talla; Sall, Baba; Bouyer, Jérémy

    2014-01-01

    Background Beyond insecticides, alternative methods to control insect pests for agriculture and vectors of diseases are needed. Management strategies involving the mass-release of living control agents have been developed, including genetic control with sterile insects and biological control with parasitoids, for which aerial release of insects is often required. Aerial release in genetic control programmes often involves the use of chilled sterile insects, which can improve dispersal, survival and competitiveness of sterile males. Currently available means of aerially releasing chilled fruit flies are however insufficiently precise to ensure homogeneous distribution at low release rates and no device is available for tsetse. Methodology/Principal Findings Here we present the smart aerial release machine, a new design by the Mubarqui Company, based on the use of vibrating conveyors. The machine is controlled through Bluetooth by a tablet with Android Operating System including a completely automatic guidance and navigation system (MaxNav software). The tablet is also connected to an online relational database facilitating the preparation of flight schedules and automatic storage of flight reports. The new machine was compared with a conveyor release machine in Mexico using two fruit flies species (Anastrepha ludens and Ceratitis capitata) and we obtained better dispersal homogeneity (% of positive traps, p<0.001) for both species and better recapture rates for Anastrepha ludens (p<0.001), especially at low release densities (<1500 per ha). We also demonstrated that the machine can replace paper boxes for aerial release of tsetse in Senegal. Conclusions/Significance This technology limits damages to insects and allows a large range of release rates from 10 flies/km2 for tsetse flies up to 600 000 flies/km2 for fruit flies. The potential of this machine to release other species like mosquitoes is discussed. Plans and operating of the machine are provided to allow its

  20. The smart aerial release machine, a universal system for applying the sterile insect technique.

    Directory of Open Access Journals (Sweden)

    Ruben Leal Mubarqui

    Full Text Available Beyond insecticides, alternative methods to control insect pests for agriculture and vectors of diseases are needed. Management strategies involving the mass-release of living control agents have been developed, including genetic control with sterile insects and biological control with parasitoids, for which aerial release of insects is often required. Aerial release in genetic control programmes often involves the use of chilled sterile insects, which can improve dispersal, survival and competitiveness of sterile males. Currently available means of aerially releasing chilled fruit flies are however insufficiently precise to ensure homogeneous distribution at low release rates and no device is available for tsetse.Here we present the smart aerial release machine, a new design by the Mubarqui Company, based on the use of vibrating conveyors. The machine is controlled through Bluetooth by a tablet with Android Operating System including a completely automatic guidance and navigation system (MaxNav software. The tablet is also connected to an online relational database facilitating the preparation of flight schedules and automatic storage of flight reports. The new machine was compared with a conveyor release machine in Mexico using two fruit flies species (Anastrepha ludens and Ceratitis capitata and we obtained better dispersal homogeneity (% of positive traps, p<0.001 for both species and better recapture rates for Anastrepha ludens (p<0.001, especially at low release densities (<1500 per ha. We also demonstrated that the machine can replace paper boxes for aerial release of tsetse in Senegal.This technology limits damages to insects and allows a large range of release rates from 10 flies/km2 for tsetse flies up to 600,000 flies/km2 for fruit flies. The potential of this machine to release other species like mosquitoes is discussed. Plans and operating of the machine are provided to allow its use worldwide.

  1. Moving beyond regression techniques in cardiovascular risk prediction: applying machine learning to address analytic challenges.

    Science.gov (United States)

    Goldstein, Benjamin A; Navar, Ann Marie; Carter, Rickey E

    2016-07-19

    Risk prediction plays an important role in clinical cardiology research. Traditionally, most risk models have been based on regression models. While useful and robust, these statistical methods are limited to using a small number of predictors which operate in the same way on everyone, and uniformly throughout their range. The purpose of this review is to illustrate the use of machine-learning methods for development of risk prediction models. Typically presented as black box approaches, most machine-learning methods are aimed at solving particular challenges that arise in data analysis that are not well addressed by typical regression approaches. To illustrate these challenges, as well as how different methods can address them, we consider trying to predicting mortality after diagnosis of acute myocardial infarction. We use data derived from our institution's electronic health record and abstract data on 13 regularly measured laboratory markers. We walk through different challenges that arise in modelling these data and then introduce different machine-learning approaches. Finally, we discuss general issues in the application of machine-learning methods including tuning parameters, loss functions, variable importance, and missing data. Overall, this review serves as an introduction for those working on risk modelling to approach the diffuse field of machine learning.

  2. 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.

  3. A High Performance Space Vector Modulation - Direct Torque Controlled Induction Machine Drive based on Stator Flux Orientation Technique

    Directory of Open Access Journals (Sweden)

    BELMADANI, B.

    2009-06-01

    Full Text Available This paper proposes the design and implementation of a novel direct torque controlled induction machine drive system. The control system enjoys the advantages of stator vector control and conventional direct torque control and avoids some of the implementation difficulties of either of the two control methods. The stator vector control principal is used to keep constant the amplitude of stator flux vector at rated value, and to develop the relationship between the machine torque and the rotating speed of the stator flux vector. Thus, the machine torque can be regulated to generate the stator angular speed, which becomes a command signal and permits to overcome the problem of its estimation. Furthermore, with the combined control methods, the reference stator voltage vector can be generated and proportional-integral controllers and space vector modulation technique can be used to obtain fixed switching frequency and low torque ripple. Simulation experiments results indicate that, with the proposed scheme, a precise control of the stator flux and machine torque can be achieved. Compared to conventional direct torque control, presented method is easily implemented, and the steady performances of ripples of both torque and flux are considerably improved.

  4. PSO-based support vector machine with cuckoo search technique for clinical disease diagnoses.

    Science.gov (United States)

    Liu, Xiaoyong; Fu, Hui

    2014-01-01

    Disease diagnosis is conducted with a machine learning method. We have proposed a novel machine learning method that hybridizes support vector machine (SVM), particle swarm optimization (PSO), and cuckoo search (CS). The new method consists of two stages: firstly, a CS based approach for parameter optimization of SVM is developed to find the better initial parameters of kernel function, and then PSO is applied to continue SVM training and find the best parameters of SVM. Experimental results indicate that the proposed CS-PSO-SVM model achieves better classification accuracy and F-measure than PSO-SVM and GA-SVM. Therefore, we can conclude that our proposed method is very efficient compared to the previously reported algorithms.

  5. PSO-Based Support Vector Machine with Cuckoo Search Technique for Clinical Disease Diagnoses

    Directory of Open Access Journals (Sweden)

    Xiaoyong Liu

    2014-01-01

    Full Text Available Disease diagnosis is conducted with a machine learning method. We have proposed a novel machine learning method that hybridizes support vector machine (SVM, particle swarm optimization (PSO, and cuckoo search (CS. The new method consists of two stages: firstly, a CS based approach for parameter optimization of SVM is developed to find the better initial parameters of kernel function, and then PSO is applied to continue SVM training and find the best parameters of SVM. Experimental results indicate that the proposed CS-PSO-SVM model achieves better classification accuracy and F-measure than PSO-SVM and GA-SVM. Therefore, we can conclude that our proposed method is very efficient compared to the previously reported algorithms.

  6. Accuracy comparison among different machine learning techniques for detecting malicious codes

    Science.gov (United States)

    Narang, Komal

    2016-03-01

    In this paper, a machine learning based model for malware detection is proposed. It can detect newly released malware i.e. zero day attack by analyzing operation codes on Android operating system. The accuracy of Naïve Bayes, Support Vector Machine (SVM) and Neural Network for detecting malicious code has been compared for the proposed model. In the experiment 400 benign files, 100 system files and 500 malicious files have been used to construct the model. The model yields the best accuracy 88.9% when neural network is used as classifier and achieved 95% and 82.8% accuracy for sensitivity and specificity respectively.

  7. On Figures of Speech in English News and the Translation Techniques

    Institute of Scientific and Technical Information of China (English)

    邵京京

    2014-01-01

    English Rhetoric is the essence of the English language, which often appears in various styles, including English news. Using all kinds of rhetoric has increased the artistic charm of the news language and attracts the attention of readers. This paper appreciates the most commonly used tropes in English news reports and analyses the respective rhetorical features. Based on this ,the author attempts to offer different approaches in translation, such as simile, metaphor, metonymy, synecdoche.

  8. On Figures of Speech in English News and the Translation Techniques

    Institute of Scientific and Technical Information of China (English)

    邵京京

    2014-01-01

    English Rhetoric is the essence of the English language, which often appears in various styles, including English news. Using all kinds of rhetoric has increased the artistic charm of the news language and attracts the attention of readers. This paper appreciates the most commonly used tropes in English news reports and analyses the respective rhetorical features.Based on this,the author attempts to offer different approaches in translation, such as simile, metaphor, metonymy, synecdoche.

  9. Engagement techniques and playing level impact the biomechanical demands on rugby forwards during machine-based scrummaging.

    Science.gov (United States)

    Preatoni, Ezio; Stokes, Keith A; England, Michael E; Trewartha, Grant

    2015-04-01

    This cross-sectional study investigated the factors that may influence the physical loading on rugby forwards performing a scrum by studying the biomechanics of machine-based scrummaging under different engagement techniques and playing levels. 34 forward packs from six playing levels performed repetitions of five different types of engagement techniques against an instrumented scrum machine under realistic training conditions. Applied forces and body movements were recorded in three orthogonal directions. The modification of the engagement technique altered the load acting on players. These changes were in a similar direction and of similar magnitude irrespective of the playing level. Reducing the dynamics of the initial engagement through a fold-in procedure decreased the peak compression force, the peak downward force and the engagement speed in excess of 30%. For example, peak compression (horizontal) forces in the professional teams changed from 16.5 (baseline technique) to 8.6 kN (fold-in procedure). The fold-in technique also reduced the occurrence of combined high forces and head-trunk misalignment during the absorption of the impact, which was used as a measure of potential hazard, by more than 30%. Reducing the initial impact did not decrease the ability of the teams to produce sustained compression forces. De-emphasising the initial impact against the scrum machine decreased the mechanical stresses acting on forward players and may benefit players' welfare by reducing the hazard factors that may induce chronic degeneration of the spine. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

  10. Applying machine learning and image feature extraction techniques to the problem of cerebral aneurysm rupture

    Directory of Open Access Journals (Sweden)

    Steren Chabert

    2017-01-01

    Full Text Available Cerebral aneurysm is a cerebrovascular disorder characterized by a bulging in a weak area in the wall of an artery that supplies blood to the brain. It is relevant to understand the mechanisms leading to the apparition of aneurysms, their growth and, more important, leading to their rupture. The purpose of this study is to study the impact on aneurysm rupture of the combination of different parameters, instead of focusing on only one factor at a time as is frequently found in the literature, using machine learning and feature extraction techniques. This discussion takes relevance in the context of the complex decision that the physicians have to take to decide which therapy to apply, as each intervention bares its own risks, and implies to use a complex ensemble of resources (human resources, OR, etc. in hospitals always under very high work load. This project has been raised in our actual working team, composed of interventional neuroradiologist, radiologic technologist, informatics engineers and biomedical engineers, from Valparaiso public Hospital, Hospital Carlos van Buren, and from Universidad de Valparaíso – Facultad de Ingeniería and Facultad de Medicina. This team has been working together in the last few years, and is now participating in the implementation of an “interdisciplinary platform for innovation in health”, as part of a bigger project leaded by Universidad de Valparaiso (PMI UVA1402. It is relevant to emphasize that this project is made feasible by the existence of this network between physicians and engineers, and by the existence of data already registered in an orderly manner, structured and recorded in digital format. The present proposal arises from the description in nowadays literature that the actual indicators, whether based on morphological description of the aneurysm, or based on characterization of biomechanical factor or others, these indicators were shown not to provide sufficient information in order

  11. Polynomial Transfer Lot Sizing Techniques for Batch Processing on Consecutive Machines

    Science.gov (United States)

    1989-09-01

    batch, while still specifying sizable batches? Goldratt , the developer of OPT (Optimized Production Technology) [7; 12, pp. 692-715; 101, answered this...and Jeffrey L Rummel, Batching to Minimize Flow Times on One Machine, Management Science, 33, #6, 1987, pp. 784-799. [71 Goldratt , Eliyahu and Robert

  12. Machining process influence on the chip form and surface roughness by neuro-fuzzy technique

    Science.gov (United States)

    Anicic, Obrad; Jović, Srđan; Aksić, Danilo; Skulić, Aleksandar; Nedić, Bogdan

    2017-04-01

    The main aim of the study was to analyze the influence of six machining parameters on the chip shape formation and surface roughness as well during turning of Steel 30CrNiMo8. Three components of cutting forces were used as inputs together with cutting speed, feed rate, and depth of cut. It is crucial for the engineers to use optimal machining parameters to get the best results or to high control of the machining process. Therefore, there is need to find the machining parameters for the optimal procedure of the machining process. Adaptive neuro-fuzzy inference system (ANFIS) was used to estimate the inputs influence on the chip shape formation and surface roughness. According to the results, the cutting force in direction of the depth of cut has the highest influence on the chip form. The testing error for the cutting force in direction of the depth of cut has testing error 0.2562. This cutting force determines the depth of cut. According to the results, the depth of cut has the highest influence on the surface roughness. Also the depth of cut has the highest influence on the surface roughness. The testing error for the cutting force in direction of the depth of cut has testing error 5.2753. Generally the depth of cut and the cutting force which provides the depth of cut are the most dominant factors for chip forms and surface roughness. Any small changes in depth of cut or in cutting force which provide the depth of cut could drastically affect the chip form or surface roughness of the working material.

  13. The application of machine learning techniques as an adjunct to clinical decision making in alcohol dependence treatment.

    Science.gov (United States)

    Connor, J P; Symons, M; Feeney, G F X; Young, R McD; Wiles, J

    2007-01-01

    With few exceptions, research in the addictive sciences has relied on linear statistics and methodologies. Addiction involves a complex array of nonlinear behaviors. This study applies two machine learning techniques, Bayesian and decision tree classifiers, in the assessment of outcome of an alcohol dependence treatment program. These nonlinear approaches are compared to a standard linear analysis. Seventy-three alcohol-dependent subjects undertaking a 12-week cognitive-behavioral therapy (CBT) program and 66 subjects undertaking an identical program but also prescribed the relapse prevention agent Acamprosate were employed in this study. Demographic, alcohol use, dependence severity, craving, health-related quality of life, and psychological measures at baseline were used to predict abstinence at 12 weeks. Decision trees had a 77% predictive accuracy across both data sets, Bayesian networks 73%, and discriminant analysis 42%. Combined with clinical experience, machine learning approaches offer promise in understanding the complex relationships that underlie treatment outcome for abstinence-based alcohol treatment programs.

  14. Operator functional state classification using least-square support vector machine based recursive feature elimination technique.

    Science.gov (United States)

    Yin, Zhong; Zhang, Jianhua

    2014-01-01

    This paper proposed two psychophysiological-data-driven classification frameworks for operator functional states (OFS) assessment in safety-critical human-machine systems with stable generalization ability. The recursive feature elimination (RFE) and least square support vector machine (LSSVM) are combined and used for binary and multiclass feature selection. Besides typical binary LSSVM classifiers for two-class OFS assessment, two multiclass classifiers based on multiclass LSSVM-RFE and decision directed acyclic graph (DDAG) scheme are developed, one used for recognizing the high mental workload and fatigued state while the other for differentiating overloaded and base-line states from the normal states. Feature selection results have revealed that different dimensions of OFS can be characterized by specific set of psychophysiological features. Performance comparison studies show that reasonable high and stable classification accuracy of both classification frameworks can be achieved if the RFE procedure is properly implemented and utilized.

  15. Applying a Machine Learning Technique to Classification of Japanese Pressure Patterns

    Directory of Open Access Journals (Sweden)

    H Kimura

    2009-04-01

    Full Text Available In climate research, pressure patterns are often very important. When a climatologists need to know the days of a specific pressure pattern, for example "low pressure in Western areas of Japan and high pressure in Eastern areas of Japan (Japanese winter-type weather," they have to visually check a huge number of surface weather charts. To overcome this problem, we propose an automatic classification system using a support vector machine (SVM, which is a machine-learning method. We attempted to classify pressure patterns into two classes: "winter type" and "non-winter type". For both training datasets and test datasets, we used the JRA-25 dataset from 1981 to 2000. An experimental evaluation showed that our method obtained a greater than 0.8 F-measure. We noted that variations in results were based on differences in training datasets.

  16. Forecasting the NOK/USD Exchange Rate with Machine Learning Techniques

    OpenAIRE

    Theophilos Papadimitriou; Periklis Gogas; Vasilios Plakandaras

    2013-01-01

    In this paper, we approximate the empirical findings of Papadamou and Markopoulos (2012) on the NOK/USD exchange rate under a Machine Learning (ML) framework. By applying Support Vector Regression (SVR) on a general monetary exchange rate model and a Dynamic Evolving Neuro-Fuzzy Inference System (DENFIS) to extract model structure, we test for the validity of popular monetary exchange rate models. We reach to mixed results since the coefficient sign of interest rate differential is in favor o...

  17. Application of Machine Learning Techniques for Amplitude and Phase Noise Characterization

    DEFF Research Database (Denmark)

    Zibar, Darko; de Carvalho, Luis Henrique Hecker; Piels, Molly

    2015-01-01

    In this paper, tools from machine learning community, such as Bayesian filtering and expectation maximization parameter estimation, are presented and employed for laser amplitude and phase noise characterization. We show that phase noise estimation based on Bayesian filtering outperforms...... conventional time-domain approach in the presence of moderate measurement noise. Additionally, carrier synchronization based on Bayesian filtering, in combination with expectation maximization, is demonstrated for the first time experimentally....

  18. Technique for optimal placement of transducers for fault detection in rotating machines

    OpenAIRE

    2013-01-01

    Online fault detection and diagnosis of rotating machinery requires a number of transducers that can be significantly expensive for industrial processes. The sensitivity of various transducers and their appropriate positioning are dependent on different types of fault conditions. It is critical to formulate a method to systematically determine the effectiveness of transducer locations for monitoring the condition of a machine. In this article, number of independent sources analysis is used as...

  19. Virtual Machine-level Software Transactional Memory: Principles, Techniques, and Implementation

    Science.gov (United States)

    2015-08-13

    VM-managed environment. ByteSTM is built by modifying Jikes RVM [3], a Java research virtual machine implemented in Java , using the optimizing...project have been publicly released as open-source software and research papers published at international conferences. In the following we summarize them... Research (AFOSR)/ RTC Arlington, Virginia 22203 Air Force Research Laboratory Air Force Materiel Command REPORT DOCUMENTATION PAGE Form Approved OMB No

  20. A New Technique: Research and industrial application of a novel compound permanent magnet synchronous machine

    Institute of Scientific and Technical Information of China (English)

    Cheng-zhi FAN; Ming-xing HUANG; Yun-yue YE

    2009-01-01

    We propose a novel kind of compound permanent magnet synchronous machine (CPMSM), which is applicable in low-speed and high-torque situations. We first explain the structure of the CPMSM. Based on theoretically deducing the calculation formulae of the CPMSM electromagnetic parameters, we analyze the operating characteristics of the CPMSM, and obtain the power-angle curves and working curves. The no-load magnetic field distribution and the cogging torque are analyzed by applying the finite element method of three-dimensional (3D) magnetic fields, to determine the no-load leakage coefficient and the wave0form of the cogging torque. Furthermore, the optimal parameters of the permanent magnet for reducing the cogging torque are determined. An important application target of the CPMSM is in direct-drive pumping units. We have installed and tested a directdrive pumping unit in an existing oil well. Test results show that the power consumption of the direct-drive pumping unit driven by CPMSM is 6 1. 1% of that of the beam-pumping unit, and that the floor space and weight are only 50% of those of a beam-pumping unit. The noise output does not exceed 58 dB in a range of 1 m around the machine when the machine is 1.5 m from the ground.

  1. A data-based technique for monitoring of wound rotor induction machines: A simulation study

    Directory of Open Access Journals (Sweden)

    Fouzi Harrou

    2016-09-01

    Full Text Available Detecting faults induction machines is crucial for a safe operation of these machines. The aim of this paper is to present a statistical fault detection methodology for the detection of faults in three-phase wound rotor induction machines (WRIM. The proposed fault detection approach is based on the use of principal components analysis (PCA. However, conventional PCA-based detection indices, such as the T2 and the Q statistics, are not well suited to detect small faults because these indices only use information from the most recent available samples. Detection of small faults is one of the most crucial and challenging tasks in the area of fault detection and diagnosis. In this paper, a new statistical system monitoring strategy is proposed for detecting changes resulting from small shifts in several variables associated with WRIM. The proposed approach combines modeling using PCA modeling with the exponentially weighted moving average (EWMA control scheme. In the proposed approach, EWMA control scheme is applied on the ignored principal components to detect the presence of faults. The performance of the proposed method is compared with those of the traditional PCA-based fault detection indices. The simulation results clearly show the effectiveness of the proposed method over the conventional ones, especially in the presence of faults with small magnitudes.

  2. A data-based technique for monitoring of wound rotor induction machines: A simulation study

    KAUST Repository

    Harrou, Fouzi

    2016-05-09

    Detecting faults induction machines is crucial for a safe operation of these machines. The aim of this paper is to present a statistical fault detection methodology for the detection of faults in three-phase wound rotor induction machines (WRIM). The proposed fault detection approach is based on the use of principal components analysis (PCA). However, conventional PCA-based detection indices, such as the T2T2 and the Q statistics, are not well suited to detect small faults because these indices only use information from the most recent available samples. Detection of small faults is one of the most crucial and challenging tasks in the area of fault detection and diagnosis. In this paper, a new statistical system monitoring strategy is proposed for detecting changes resulting from small shifts in several variables associated with WRIM. The proposed approach combines modeling using PCA modeling with the exponentially weighted moving average (EWMA) control scheme. In the proposed approach, EWMA control scheme is applied on the ignored principal components to detect the presence of faults. The performance of the proposed method is compared with those of the traditional PCA-based fault detection indices. The simulation results clearly show the effectiveness of the proposed method over the conventional ones, especially in the presence of faults with small magnitudes.

  3. Estimating Fractional Shrub Cover Using Simulated EnMAP Data: A Comparison of Three Machine Learning Regression Techniques

    Directory of Open Access Journals (Sweden)

    Marcel Schwieder

    2014-04-01

    Full Text Available Anthropogenic interventions in natural and semi-natural ecosystems often lead to substantial changes in their functioning and may ultimately threaten ecosystem service provision. It is, therefore, necessary to monitor these changes in order to understand their impacts and to support management decisions that help ensuring sustainability. Remote sensing has proven to be a valuable tool for these purposes, and especially hyperspectral sensors are expected to provide valuable data for quantitative characterization of land change processes. In this study, simulated EnMAP data were used for mapping shrub cover fractions along a gradient of shrub encroachment, in a study region in southern Portugal. We compared three machine learning regression techniques: Support Vector Regression (SVR; Random Forest Regression (RF; and Partial Least Squares Regression (PLSR. Additionally, we compared the influence of training sample size on the prediction performance. All techniques showed reasonably good results when trained with large samples, while SVR always outperformed the other algorithms. The best model was applied to produce a fractional shrub cover map for the whole study area. The predicted patterns revealed a gradient of shrub cover between regions affected by special agricultural management schemes for nature protection and areas without land use incentives. Our results highlight the value of EnMAP data in combination with machine learning regression techniques for monitoring gradual land change processes.

  4. From analog timers to the era of machine learning: The case of the transient hot-wire technique

    Science.gov (United States)

    Assael, Yannis M.; Antoniadis, Konstantinos D.; Assael, Marc J.

    2017-07-01

    In this work, we demonstrate how interdisciplinary knowledge can provide solutions to elusive challenges and advance science. As an example, we used the application of the THW in the measurement of the thermal conductivity of solids. To obtain a solution of the equations by FEM, about 10 h were required. By employing tools from the field of machine learning and computer science like a) automating the manual pipeline using a custom framework, b) using efficiently, Bayesian Optimisation to estimate the optimal thermal properties value, and c) applying further task specific optimisations, this time was reduced to 3 min, which is acceptable, and thus the technique can be easier used.

  5. Technique to reduce the shaft torque stress at an induction machine

    Directory of Open Access Journals (Sweden)

    Adrian Tulbure

    2005-10-01

    Full Text Available For the active attenuation at load stress in the drive shaft, the control system should receive as input signal the instantaneous shaft torque value. In this context an intelligent observer for shaft tongue of mains operatea induction machine, which is able to responding by variation of LIF (Load Input Function[1] must be developed. Extensive computer simulation prove the effectiveness of the proposed solution. In order to obtain a practical validation, the stimulated regulator has been designed and tested in the Institute of Electrical Engineering in Clausthal/Germany [2]. This paper contains following parts: Developing the mathematical model, Practical realisation, Simulations and measurements, Evaluating the control solutions and Conclusions.

  6. Research on Key Techniques of Condition Monitoring and Fault Diagnosing Systems of Machine Groups

    Institute of Scientific and Technical Information of China (English)

    WANG Yan-kai; LIAO Ming-fu; WANG Si-ji

    2005-01-01

    This paper describes the development of the condition monitoring and fault diagnosing system of a group of rotating machinery. The data management is performed by means of double redundant data bases stored simultaneously in both the analyzing server and monitoring client. In this way, high reliability of the storage of data is guaranteed. Condensation of trend data releases much space resource of the hard disk. Diagnosing strategies orientated to different typical faults of rotating machinery are developed and incorporated into the system. Experimental verification shows that the system is suitable and effective for condition monitoring and fault diagnosing for a rotating machine group.

  7. A Novel Diagnostic Technique to Study the Ageing of Rotating Machine Insulation: The

    OpenAIRE

    2000-01-01

    Rotating machine insulation ageing has been the subject of intensive research over the years. In this paper, model stator bars are investigated with the aid a Partial Discharge (PD) detector. The maximum PD magnitude is recorded as the applied voltage increases and as it decreases. The resulting “hysteresis curve” indicates whether the stator bar is in a “good” or “bad” condition, i.e. it indicates its “state of health”. The proposed method has certain advantages over other methods since it r...

  8. Beam Coupling Impedance Localization Technique Validation and Measurements in the CERN Machines

    CERN Document Server

    Biancacci, N; Argyropoulos, T; Bartosik, H; Calaga, R; Cornelis, K; Gilardoni, S; Métral, E; Mounet, N; Papaphilippou, Y; Persichelli, S; Rumolo, G; Salvant, B; Sterbini, G; Tomàs, R; Wasef, R; Migliorati, M; Palumbo, L

    2013-01-01

    The beam coupling impedance could lead to limitations in beam brightness and quality, and therefore it needs accurate quantification and continuous monitoring in order to detect and mitigate high impedance sources. In the CERN machines, for example, kickers and collimators are expected to be important contributors to the total imaginary part of the transverse impedance. In order to detect the other sources, a beam based measurement was developed: from the variation of betatron phase beating with intensity, it is possible to detect the locations of main impedance sources. In this work we present the application of the method with beam measurements in the CERN PS, SPS and LHC.

  9. Use of biogenic nanomaterials to improve the peritoneal dialysis technique: A Translational Research Perspective

    CERN Document Server

    Kumar, Dinesh

    2015-01-01

    Intraperitoneal and catheter exit site infections are the most common complications associated with prolonged peritoneal dialysis (PD) therapy used for treating the patients with end stage renal failure (ESRF). Recurrent and persistent infections often cause inflammation of the peritoneum, a condition known as infectious peritonitis and to resolve the condition, patients require antibiotic treatment. However, if the treatment is delayed or if it fails due to antibiotic resistance, the peritonitis may lead to permanent malfunctioning of peritoneal membrane causing technique failure and transferring the patients to haemodialysis. Severe and prolonged peritonitis is not only the major cause of technique failure, it is also the leading cause of mortality and morbidity in PD patients. Therefore, there is an urgent need to improve the existing PD technique so that the frequency of PD associated infections could be reduced and infectious peritonitis episodes thereof during prolonged peritoneal dialysis. In this pers...

  10. 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.

  11. Scheduling and sequencing in four machines robotic cell: Application of genetic algorithm and enumeration techniques

    Directory of Open Access Journals (Sweden)

    M.M.S. Abdulkader

    2013-09-01

    Full Text Available The introduction of robotic cells to manufacturing systems improved the efficiency, productivity and reliability of the system. The main objective of the scheduling problem of multi-item multi-machine robotic cells is the identification of the optimum robot cycle/s and jobs sequencing for certain processing conditions which yield the higher possible production rate. The objective of this work is to solve the scheduling problem in four-machine blocking robotic cells producing identical and different part types while minimizing the cycle time. A genetic algorithm is developed to find the parts sequence that minimizes the robot-moves cycle time for each robot cycle. The results showed that the developed genetic algorithm yields competitive results compared to the results of the full enumeration of all possible parts sequences. The results show also that the ratio between the average processing time of all parts and the robot travel time determines the cycle having the optimal robot-moves.

  12. An alternative hybrid evolutionary technique focused on allocating machines and sequencing operations

    Directory of Open Access Journals (Sweden)

    Mariano Frutos

    2016-09-01

    Full Text Available We present here a hybrid algorithm for the Flexible Job-Shop Scheduling Problem (FJSSP. This problem involves the optimal use of resources in a flexible production environment in which each operation can be carried out by more than a single machine. Our algorithm allocates, in a first step, the machines to operations and in a second stage it sequences them by integrating a Multi-Objective Evolutionary Algorithm (MOEA and a path-dependent search algorithm (Multi-Objective Simulated Annealing, which is enacted at the genetic phase of the procedure. The joint interaction of those two components yields a very efficient procedure for solving the FJSSP. An important step in the development of the algorithm was the selection of the right MOEA. Candidates were tested on problems of low, medium and high complexity. Further analyses showed the relevance of the search algorithm in the hybrid structure. Finally, comparisons with other algorithms in the literature indicate that the performance of our alternative is good.

  13. Automatic segmentation of airway tree based on local intensity filter and machine learning technique in 3D chest CT volume.

    Science.gov (United States)

    Meng, Qier; Kitasaka, Takayuki; Nimura, Yukitaka; Oda, Masahiro; Ueno, Junji; Mori, Kensaku

    2017-02-01

    Airway segmentation plays an important role in analyzing chest computed tomography (CT) volumes for computerized lung cancer detection, emphysema diagnosis and pre- and intra-operative bronchoscope navigation. However, obtaining a complete 3D airway tree structure from a CT volume is quite a challenging task. Several researchers have proposed automated airway segmentation algorithms basically based on region growing and machine learning techniques. However, these methods fail to detect the peripheral bronchial branches, which results in a large amount of leakage. This paper presents a novel approach for more accurate extraction of the complex airway tree. This proposed segmentation method is composed of three steps. First, Hessian analysis is utilized to enhance the tube-like structure in CT volumes; then, an adaptive multiscale cavity enhancement filter is employed to detect the cavity-like structure with different radii. In the second step, support vector machine learning will be utilized to remove the false positive (FP) regions from the result obtained in the previous step. Finally, the graph-cut algorithm is used to refine the candidate voxels to form an integrated airway tree. A test dataset including 50 standard-dose chest CT volumes was used for evaluating our proposed method. The average extraction rate was about 79.1 % with the significantly decreased FP rate. A new method of airway segmentation based on local intensity structure and machine learning technique was developed. The method was shown to be feasible for airway segmentation in a computer-aided diagnosis system for a lung and bronchoscope guidance system.

  14. 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.

  15. 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.

  16. Machine Learning Techniques for Single Nucleotide Polymorphism—Disease Classification Models in Schizophrenia

    Directory of Open Access Journals (Sweden)

    Cristian R. Munteanu

    2010-07-01

    Full Text Available Single nucleotide polymorphisms (SNPs can be used as inputs in disease computational studies such as pattern searching and classification models. Schizophrenia is an example of a complex disease with an important social impact. The multiple causes of this disease create the need of new genetic or proteomic patterns that can diagnose patients using biological information. This work presents a computational study of disease machine learning classification models using only single nucleotide polymorphisms at the HTR2A and DRD3 genes from Galician (Northwest Spain schizophrenic patients. These classification models establish for the first time, to the best knowledge of the authors, a relationship between the sequence of the nucleic acid molecule and schizophrenia (Quantitative Genotype – Disease Relationships that can automatically recognize schizophrenia DNA sequences and correctly classify between 78.3–93.8% of schizophrenia subjects when using datasets which include simulated negative subjects and a linear artificial neural network.

  17. A Capacitive Displacement Sensing Technique for Early Detection of Unbalanced Loads in a Washing Machine

    Directory of Open Access Journals (Sweden)

    Karthik Tiruthani

    2009-11-01

    Full Text Available Horizontal axis washing machines are water and energy efficient and becoming popular in the USA. Unlike a vertical axis washer, these do not have an agitator and depend solely on tumbling for the agitation of laundry during the wash cycle. However, due to the constant shifting of laundry during washing, the load distribution is often unbalanced during the high speed spin cycle. We present a displacement-based sensing method to detect unbalance early while the spin rate (rpm is well below the resonance frequency so that corrective actions may be taken prior to the high speed spin cycle. Experimental and analytical characterizations of the sensor configuration are presented. Results show that the displacement sensor is more appropriate than an accelerometer for this application and offer the potential for a simple, reliable, low cost detection of unbalance.

  18. Analysis and design of machine learning techniques evolutionary solutions for regression, prediction, and control problems

    CERN Document Server

    Stalph, Patrick

    2014-01-01

    Manipulating or grasping objects seems like a trivial task for humans, as these are motor skills of everyday life. Nevertheless, motor skills are not easy to learn for humans and this is also an active research topic in robotics. However, most solutions are optimized for industrial applications and, thus, few are plausible explanations for human learning. The fundamental challenge, that motivates Patrick Stalph, originates from the cognitive science: How do humans learn their motor skills? The author makes a connection between robotics and cognitive sciences by analyzing motor skill learning using implementations that could be found in the human brain – at least to some extent. Therefore three suitable machine learning algorithms are selected – algorithms that are plausible from a cognitive viewpoint and feasible for the roboticist. The power and scalability of those algorithms is evaluated in theoretical simulations and more realistic scenarios with the iCub humanoid robot. Convincing results confirm the...

  19. Correlation technique and least square support vector machine combine for frequency domain based ECG beat classification.

    Science.gov (United States)

    Dutta, Saibal; Chatterjee, Amitava; Munshi, Sugata

    2010-12-01

    The present work proposes the development of an automated medical diagnostic tool that can classify ECG beats. This is considered an important problem as accurate, timely detection of cardiac arrhythmia can help to provide proper medical attention to cure/reduce the ailment. The proposed scheme utilizes a cross-correlation based approach where the cross-spectral density information in frequency domain is used to extract suitable features. A least square support vector machine (LS-SVM) classifier is developed utilizing the features so that the ECG beats are classified into three categories: normal beats, PVC beats and other beats. This three-class classification scheme is developed utilizing a small training dataset and tested with an enormous testing dataset to show the generalization capability of the scheme. The scheme, when employed for 40 files in the MIT/BIH arrhythmia database, could produce high classification accuracy in the range 95.51-96.12% and could outperform several competing algorithms.

  20. Using machine vision and data mining techniques to identify cell properties via microfluidic flow analysis

    Science.gov (United States)

    Horowitz, Geoffrey; Bowie, Samuel; Liu, Anna; Stone, Nicholas; Sulchek, Todd; Alexeev, Alexander

    2016-11-01

    In order to quickly identify the wide range of mechanistic properties that are seen in cell populations, a coupled machine vision and data mining analysis is developed to examine high speed videos of cells flowing through a microfluidic device. The microfluidic device contains a microchannel decorated with a periodical array of diagonal ridges. The ridges compress flowing cells that results in complex cell trajectory and induces cell cross-channel drift, both depend on the cell intrinsic mechanical properties that can be used to characterize specific cell lines. Thus, the cell trajectory analysis can yield a parameter set that can serve as a unique identifier of a cell's membership to a specific cell population. By using the correlations between the cell populations and measured cell trajectories in the ridged microchannel, mechanical properties of individual cells and their specific populations can be identified via only information captured using video analysis. Financial support provided by National Science Foundation (NSF) Grant No. CMMI 1538161.

  1. Automation of printing machine

    OpenAIRE

    Sušil, David

    2016-01-01

    Bachelor thesis is focused on the automation of the printing machine and comparing the two types of printing machines. The first chapter deals with the history of printing, typesettings, printing techniques and various kinds of bookbinding. The second chapter describes the difference between sheet-fed printing machines and offset printing machines, the difference between two representatives of rotary machines, technological process of the products on these machines, the description of the mac...

  2. Language Techniques in Children's Literature Translation%儿童文学翻译的语言运用技巧

    Institute of Scientific and Technical Information of China (English)

    陈剑波; 严红美

    2012-01-01

    Though children's literature language is defined as "the art of plain language", children's literature translation is far more difficult than just utilizing plain language. Moreover, children's literature language has its own unique characteristics namely vividness, musicality, conciseness and fun. Therefore, certain language techniques such as utilizing onomatopoeic words, reduplicated words, curt sentences and children's language are needed to make the translation work "as faithful, expressive and close as the original text".%儿童文学语言虽是"浅语的艺术",但儿童文学翻译绝非只需浅显的语言那么简单,而必须使用儿童"听得懂、看得懂"的儿童文学语言。此外,儿童文学语言还有形象性、音乐性、简洁性及富有童趣等特点,因此翻译时须运用一定的语言技巧,才能使译文"信于内容,达如其分,切合风格"。

  3. 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

  4. Improving the Performance of Machine Learning Based Multi Attribute Face Recognition Algorithm Using Wavelet Based Image Decomposition Technique

    Directory of Open Access Journals (Sweden)

    S. Sakthivel

    2011-01-01

    Full Text Available Problem statement: Recognizing a face based attributes is an easy task for a human to perform; it is closely automated and requires little mental effort. A computer, on the other hand, has no innate ability to recognize a face or a facial feature and must be programmed with an algorithm to do so. Generally, to recognize a face, different kinds of the facial features were used separately or in a combined manner. In the previous work, we have developed a machine learning based multi attribute face recognition algorithm and evaluated it different set of weights to each input attribute and performance wise it is low compared to proposed wavelet decomposition technique. Approach: In this study, wavelet decomposition technique has been applied as a preprocessing technique to enhance the input face images in order to reduce the loss of classification performance due to changes in facial appearance. The Experiment was specifically designed to investigate the gain in robustness against illumination and facial expression changes. Results: In this study, a wavelet based image decomposition technique has been proposed to enhance the performance by 8.54 percent of the previously designed system. Conclusion: The proposed model has been tested on face images with difference in expression and illumination condition with a dataset obtained from face image databases from Olivetti Research Laboratory.

  5. 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.

  6. Translating Public Policy: Enhancing the Applicability of Social Impact Techniques for Grassroots Community Groups

    Directory of Open Access Journals (Sweden)

    Melissa Edwards

    2013-08-01

    Full Text Available This paper reports on an exploratory action research study designed to understand how grassroots community organisations engage in the measurement and reporting of social impact and how they demonstrate their social impact to local government funders. Our findings suggest that the relationships between small non-profit organisations, the communities they serve or represent and their funders are increasingly driven from the top down formalised practices. Volunteer-run grassroots organisations can be marginalized in this process. Members may lack awareness of funders’ strategic approaches or the formalized auditing and control requirements of funders mean grassroots organisations lose capacity to define their programs and projects. We conclude that, to help counter this trend, tools and techniques which open up possibilities for dialogue between those holding power and those seeking support are essential.

  7. Multivariate Cross-Classification: Applying machine learning techniques to characterize abstraction in neural representations

    Directory of Open Access Journals (Sweden)

    Jonas eKaplan

    2015-03-01

    Full Text Available Here we highlight an emerging trend in the use of machine learning classifiers to test for abstraction across patterns of neural activity. When a classifier algorithm is trained on data from one cognitive context, and tested on data from another, conclusions can be drawn about the role of a given brain region in representing information that abstracts across those cognitive contexts. We call this kind of analysis Multivariate Cross-Classification (MVCC, and review several domains where it has recently made an impact. MVCC has been important in establishing correspondences among neural patterns across cognitive domains, including motor-perception matching and cross-sensory matching. It has been used to test for similarity between neural patterns evoked by perception and those generated from memory. Other work has used MVCC to investigate the similarity of representations for semantic categories across different kinds of stimulus presentation, and in the presence of different cognitive demands. We use these examples to demonstrate the power of MVCC as a tool for investigating neural abstraction and discuss some important methodological issues related to its application.

  8. Hand Gesture recognition and classification by Discriminant and Principal Component Analysis using Machine Learning techniques

    Directory of Open Access Journals (Sweden)

    Sauvik Das Gupta

    2012-12-01

    Full Text Available This paper deals with the recognition of different hand gestures through machine learning approaches and principal component analysis. A Bio-Medical signal amplifier is built after doing a software simulation with the help of NI Multisim. At first a couple of surface electrodes are used to obtain the Electro-Myo-Gram (EMG signals from the hands. These signals from the surface electrodes have to be amplified with the help of the Bio-Medical Signal amplifier. The Bio-Medical Signal amplifier used is basically an Instrumentation amplifier made with the help of IC AD 620.The output from the Instrumentation amplifier is then filtered with the help of a suitable Band-Pass Filter. The output from the Band Pass filter is then fed to an Analog to Digital Converter (ADC which in this case is the NI USB 6008.The data from the ADC is then fed into a suitable algorithm which helps in recognition of the different hand gestures. The algorithm analysis is done in MATLAB. The results shown in this paper show a close to One-hundred per cent (100% classification result for three given hand gestures.

  9. submitter Studies of CMS data access patterns with machine learning techniques

    CERN Document Server

    De Luca, Silvia

    This thesis presents a study of the Grid data access patterns in distributed analysis in the CMS experiment at the LHC accelerator. This study ranges from the deep analysis of the historical patterns of access to the most relevant data types in CMS, to the exploitation of a supervised Machine Learning classification system to set-up a machinery able to eventually predict future data access patterns - i.e. the so-called dataset “popularity” of the CMS datasets on the Grid - with focus on specific data types. All the CMS workflows run on the Worldwide LHC Computing Grid (WCG) computing centers (Tiers), and in particular the distributed analysis systems sustains hundreds of users and applications submitted every day. These applications (or “jobs”) access different data types hosted on disk storage systems at a large set of WLCG Tiers. The detailed study of how this data is accessed, in terms of data types, hosting Tiers, and different time periods, allows to gain precious insight on storage occupancy ove...

  10. Feature extraction and classification for EEG signals using wavelet transform and machine learning techniques.

    Science.gov (United States)

    Amin, Hafeez Ullah; Malik, Aamir Saeed; Ahmad, Rana Fayyaz; Badruddin, Nasreen; Kamel, Nidal; Hussain, Muhammad; Chooi, Weng-Tink

    2015-03-01

    This paper describes a discrete wavelet transform-based feature extraction scheme for the classification of EEG signals. In this scheme, the discrete wavelet transform is applied on EEG signals and the relative wavelet energy is calculated in terms of detailed coefficients and the approximation coefficients of the last decomposition level. The extracted relative wavelet energy features are passed to classifiers for the classification purpose. The EEG dataset employed for the validation of the proposed method consisted of two classes: (1) the EEG signals recorded during the complex cognitive task--Raven's advance progressive metric test and (2) the EEG signals recorded in rest condition--eyes open. The performance of four different classifiers was evaluated with four performance measures, i.e., accuracy, sensitivity, specificity and precision values. The accuracy was achieved above 98 % by the support vector machine, multi-layer perceptron and the K-nearest neighbor classifiers with approximation (A4) and detailed coefficients (D4), which represent the frequency range of 0.53-3.06 and 3.06-6.12 Hz, respectively. The findings of this study demonstrated that the proposed feature extraction approach has the potential to classify the EEG signals recorded during a complex cognitive task by achieving a high accuracy rate.

  11. Prediction of Driver's Intention of Lane Change by Augmenting Sensor Information Using Machine Learning Techniques.

    Science.gov (United States)

    Kim, Il-Hwan; Bong, Jae-Hwan; Park, Jooyoung; Park, Shinsuk

    2017-06-10

    Driver assistance systems have become a major safety feature of modern passenger vehicles. The advanced driver assistance system (ADAS) is one of the active safety systems to improve the vehicle control performance and, thus, the safety of the driver and the passengers. To use the ADAS for lane change control, rapid and correct detection of the driver's intention is essential. This study proposes a novel preprocessing algorithm for the ADAS to improve the accuracy in classifying the driver's intention for lane change by augmenting basic measurements from conventional on-board sensors. The information on the vehicle states and the road surface condition is augmented by using an artificial neural network (ANN) models, and the augmented information is fed to a support vector machine (SVM) to detect the driver's intention with high accuracy. The feasibility of the developed algorithm was tested through driving simulator experiments. The results show that the classification accuracy for the driver's intention can be improved by providing an SVM model with sufficient driving information augmented by using ANN models of vehicle dynamics.

  12. Machine learning techniques in searches for tbar th in the h → bbar b decay channel

    Science.gov (United States)

    Santos, R.; Nguyen, M.; Webster, J.; Ryu, S.; Adelman, J.; Chekanov, S.; Zhou, J.

    2017-04-01

    Study of the production of pairs of top quarks in association with a Higgs boson is one of the primary goals of the Large Hadron Collider over the next decade, as measurements of this process may help us to understand whether the uniquely large mass of the top quark plays a special role in electroweak symmetry breaking. Higgs bosons decay predominantly to bbar b, yielding signatures for the signal that are similar to tbar t + jets with heavy flavor. Though particularly challenging to study due to the similar kinematics between signal and background events, such final states (tbar t bbar b) are an important channel for studying the top quark Yukawa coupling. This paper presents a systematic study of machine learning (ML) methods for detecting tbar th in the h → bbar b decay channel. Among the eight ML methods tested, we show that two models, extreme gradient boosted trees and neural network models, outperform alternative methods. We further study the effectiveness of ML algorithms by investigating the impact of feature set and data size, as well as the structure of the models. While extended feature set and larger training sets expectedly lead to improvement of performance, shallow models deliver comparable or better performance than their deeper counterparts. Our study suggests that ensembles of trees and neurons, not necessarily deep, work effectively for the problem of tbar th detection.

  13. Content-Based Image Retrieval Using Support Vector Machine in digital image processing techniques

    Directory of Open Access Journals (Sweden)

    G.V.Hari Prasad

    2012-04-01

    Full Text Available The rapid growth of computer technologies and the ad-vent of the World Wide Web have increased the amount and the complexity of multimedia information. A content-based image retrieval (CBIR system has been developed as an ef-ficient image retrieval tool, whereby the user can provide their query to the system to allow it to retrieve the user’s desired image from the image database. However, the tradi-tional relevance feedback of CBIR has some limitations that will decrease the performance of the CBIR system, such as the imbalance oftraining-set problem, classification prob-lem, limited information from user problem, and insuffi-cient trainingset problem. Therefore, in this study, we pro-posed an enhanced relevance-feedback method to support the user query based on the representative image selection and weight ranking of the images retrieved. The support vector machine (SVM has been used to support the learn-ing process to reduce the semantic gap between the user and the CBIR system. From these experiments, the proposed learning method has enabled users to improve their search results based on the performance of CBIR system. In addi-tion, the experiments also proved that by solving the imbal-ance training set issue, the performance of CBIR could be improved.

  14. Automated Classification of Heritage Buildings for As-Built Bim Using Machine Learning Techniques

    Science.gov (United States)

    Bassier, M.; Vergauwen, M.; Van Genechten, B.

    2017-08-01

    Semantically rich three dimensional models such as Building Information Models (BIMs) are increasingly used in digital heritage. They provide the required information to varying stakeholders during the different stages of the historic buildings life cyle which is crucial in the conservation process. The creation of as-built BIM models is based on point cloud data. However, manually interpreting this data is labour intensive and often leads to misinterpretations. By automatically classifying the point cloud, the information can be proccesed more effeciently. A key aspect in this automated scan-to-BIM process is the classification of building objects. In this research we look to automatically recognise elements in existing buildings to create compact semantic information models. Our algorithm efficiently extracts the main structural components such as floors, ceilings, roofs, walls and beams despite the presence of significant clutter and occlusions. More specifically, Support Vector Machines (SVM) are proposed for the classification. The algorithm is evaluated using real data of a variety of existing buildings. The results prove that the used classifier recognizes the objects with both high precision and recall. As a result, entire data sets are reliably labelled at once. The approach enables experts to better document and process heritage assets.

  15. Comparison of Feature Selection Techniques in Machine Learning for Anatomical Brain MRI in Dementia.

    Science.gov (United States)

    Tohka, Jussi; Moradi, Elaheh; Huttunen, Heikki

    2016-07-01

    We present a comparative split-half resampling analysis of various data driven feature selection and classification methods for the whole brain voxel-based classification analysis of anatomical magnetic resonance images. We compared support vector machines (SVMs), with or without filter based feature selection, several embedded feature selection methods and stability selection. While comparisons of the accuracy of various classification methods have been reported previously, the variability of the out-of-training sample classification accuracy and the set of selected features due to independent training and test sets have not been previously addressed in a brain imaging context. We studied two classification problems: 1) Alzheimer's disease (AD) vs. normal control (NC) and 2) mild cognitive impairment (MCI) vs. NC classification. In AD vs. NC classification, the variability in the test accuracy due to the subject sample did not vary between different methods and exceeded the variability due to different classifiers. In MCI vs. NC classification, particularly with a large training set, embedded feature selection methods outperformed SVM-based ones with the difference in the test accuracy exceeding the test accuracy variability due to the subject sample. The filter and embedded methods produced divergent feature patterns for MCI vs. NC classification that suggests the utility of the embedded feature selection for this problem when linked with the good generalization performance. The stability of the feature sets was strongly correlated with the number of features selected, weakly correlated with the stability of classification accuracy, and uncorrelated with the average classification accuracy.

  16. A Real-Time Interference Monitoring Technique for GNSS Based on a Twin Support Vector Machine Method.

    Science.gov (United States)

    Li, Wutao; Huang, Zhigang; Lang, Rongling; Qin, Honglei; Zhou, Kai; Cao, Yongbin

    2016-03-04

    Interferences can severely degrade the performance of Global Navigation Satellite System (GNSS) receivers. As the first step of GNSS any anti-interference measures, interference monitoring for GNSS is extremely essential and necessary. Since interference monitoring can be considered as a classification problem, a real-time interference monitoring technique based on Twin Support Vector Machine (TWSVM) is proposed in this paper. A TWSVM model is established, and TWSVM is solved by the Least Squares Twin Support Vector Machine (LSTWSVM) algorithm. The interference monitoring indicators are analyzed to extract features from the interfered GNSS signals. The experimental results show that the chosen observations can be used as the interference monitoring indicators. The interference monitoring performance of the proposed method is verified by using GPS L1 C/A code signal and being compared with that of standard SVM. The experimental results indicate that the TWSVM-based interference monitoring is much faster than the conventional SVM. Furthermore, the training time of TWSVM is on millisecond (ms) level and the monitoring time is on microsecond (μs) level, which make the proposed approach usable in practical interference monitoring applications.

  17. A Real-Time Interference Monitoring Technique for GNSS Based on a Twin Support Vector Machine Method

    Directory of Open Access Journals (Sweden)

    Wutao Li

    2016-03-01

    Full Text Available Interferences can severely degrade the performance of Global Navigation Satellite System (GNSS receivers. As the first step of GNSS any anti-interference measures, interference monitoring for GNSS is extremely essential and necessary. Since interference monitoring can be considered as a classification problem, a real-time interference monitoring technique based on Twin Support Vector Machine (TWSVM is proposed in this paper. A TWSVM model is established, and TWSVM is solved by the Least Squares Twin Support Vector Machine (LSTWSVM algorithm. The interference monitoring indicators are analyzed to extract features from the interfered GNSS signals. The experimental results show that the chosen observations can be used as the interference monitoring indicators. The interference monitoring performance of the proposed method is verified by using GPS L1 C/A code signal and being compared with that of standard SVM. The experimental results indicate that the TWSVM-based interference monitoring is much faster than the conventional SVM. Furthermore, the training time of TWSVM is on millisecond (ms level and the monitoring time is on microsecond (μs level, which make the proposed approach usable in practical interference monitoring applications.

  18. Uncertainty quantification and integration of machine learning techniques for predicting acid rock drainage chemistry: a probability bounds approach.

    Science.gov (United States)

    Betrie, Getnet D; Sadiq, Rehan; Morin, Kevin A; Tesfamariam, Solomon

    2014-08-15

    Acid rock drainage (ARD) is a major pollution problem globally that has adversely impacted the environment. Identification and quantification of uncertainties are integral parts of ARD assessment and risk mitigation, however previous studies on predicting ARD drainage chemistry have not fully addressed issues of uncertainties. In this study, artificial neural networks (ANN) and support vector machine (SVM) are used for the prediction of ARD drainage chemistry and their predictive uncertainties are quantified using probability bounds analysis. Furthermore, the predictions of ANN and SVM are integrated using four aggregation methods to improve their individual predictions. The results of this study showed that ANN performed better than SVM in enveloping the observed concentrations. In addition, integrating the prediction of ANN and SVM using the aggregation methods improved the predictions of individual techniques.

  19. High Classification Rates for Continuous Cow Activity Recognition using Low-cost GPS Positioning Sensors and Standard Machine Learning Techniques

    DEFF Research Database (Denmark)

    Godsk, Torben; Kjærgaard, Mikkel Baun

    2011-01-01

    In precision livestock farming, spotting cows in need of extra attention due to health or welfare issues are essential, since the time a farmer can devote to each animal is decreasing due to growing herd sizes and increasing efficiency demands. Often, the symptoms of health and welfare state...... activities. By preprocessing the raw cow position data, we obtain high classification rates using standard machine learning techniques to recognize cow activities. Our objectives were to (i) determine to what degree it is possible to robustly recognize cow activities from GPS positioning data, using low......-cost GPS receivers; and (ii) determine which types of activities can be classified, and what robustness to expect within the different classes. To provide data for this study low-cost GPS receivers were mounted on 14 dairy cows on grass for a day while they were observed from a distance...

  20. Reverse engineering smart card malware using side channel analysis with machine learning techniques

    CSIR Research Space (South Africa)

    Djonon Tsague, Hippolyte

    2016-12-01

    Full Text Available by evaluating its power consumption only. Besides well-studied methods from side channel analysis, we apply a combination of dimensionality reduction techniques in the form of PCA and LDA models to compress the large amount of data generated while preserving...

  1. Evolving techniques of diagnosis. Toward establishment of new paradigm for human machine cooperation

    Energy Technology Data Exchange (ETDEWEB)

    Kitamura, Masaharu; Takahashi, Makoto [Tohoku Univ., Sendai (Japan). Faculty of Engineering; Kanamoto, Shigeru; Saeki, Akira; Washio, Takashi; Ohga, Yukiharu; Furuta, Kazuo; Yoshikawa, Shinji

    1998-09-01

    By monitoring equipments of a plant and state of a process, the diagnostic technique to detect a sign of abnormality properly to identify its reason has often been advanced on a lot of researches in various industrial fields containing atomic force. Some fundamental studies expected for such diagnostic technique to play an important role to keep and improve operational safety of a nuclear plant have been conducted since early period of the nuclear reaction development, but their contents are evolved and changed rapidly, in recent. The technique on the diagnosis was related closely to a statistical analysis method on signal fluctuation component, so-called reactor noise analysis method in early 1980s, but technical innovation step of their recent advancement were remarkable by introduction of new techniques such as chaos theory, wavelet analysis, model base application of expert system, artificial intelligence, and so on at middle of 1980s. And, when diagnosing in the field of atomic force, owing to be required for much high ability, studies on a multi method integration system considered complementary application of a plurality of technical methods and a cooperative method between human and mechanical intelligences, are also forwarded actively faster than those in other industrial areas. In this paper, in each important item, its technical nature and present state of its application to diagnosis are described with their future technical view. (G.K.)

  2. Survey on Various Gesture Recognition Techniques for Interfacing Machines Based on Ambient Intelligence

    Directory of Open Access Journals (Sweden)

    Harshith.C

    2010-12-01

    Full Text Available Gesture recognition is mainly apprehensive on analyzing the functionality of human wits. The main goal of gesture recognition is to create a system which can recognize specific human gestures and use them to convey information or for device control. Hand gestures provide a separate complementary modality to speech for expressing ones ideas. Information associated with hand gestures in a conversation is degree, discourse structure, spatial and temporal structure. The approaches present can be mainly divided intoData-Glove Based and Vision Based approaches. An important face feature point is the nose tip. Since nose is the highest protruding point from the face. Besides that, it is not affected by facial expressions. Another important function of the nose is that it is able to indicate the head pose. Knowledge of the nose location will enable us to align an unknown 3D face with those in a face database. Eye detection is divided into eye position detection and eye contour detection. Existing works in eye detection can be classified into two major categories: traditional image-based passive approaches and the active IR based approaches. The former uses intensity and shape of eyes for detection and the latter works on the assumption that eyes have a reflection under near IR illumination and produce bright/dark pupileffect. The traditional methods can be broadly classified into three categories: template based methods, appearance based methods and feature based methods. The purpose of this paper is to compare various human Gesture recognition systems for interfacing machines directly to human wits without any corporeal media in an ambient environment.

  3. Classification and Ranking of Fermi LAT Gamma-ray Sources from the 3FGL Catalog using Machine Learning Techniques

    CERN Document Server

    Parkinson, P M Saz; Yu, P L H; Salvetti, D; Marelli, M; Falcone, A D

    2016-01-01

    We apply a number of statistical and machine learning techniques to classify and rank gamma-ray sources from the Third Fermi Large Area Telescope (LAT) Source Catalog (3FGL), according to their likelihood of falling into the two major classes of gamma-ray emitters: pulsars (PSR) or Active Galactic Nuclei (AGN). Using 1904 3FGL sources that have been identified/associated with AGN (1738) and PSR (166), we train (using 70% of our sample) and test (using 30%) our algorithms and find that the best overall accuracy (>96%) is obtained with the Random Forest (RF) technique, while using a logistic regression (LR) algorithm results in only marginally lower accuracy. We apply the same techniques on a sub-sample of 142 known gamma-ray pulsars to classify them into two major subcategories: young (YNG) and millisecond pulsars (MSP). Once more, the RF algorithm has the best overall accuracy (~90%), while a boosted LR analysis comes a close second. We apply our two best models (RF and LR) to the entire 3FGL catalog, providi...

  4. A new volumetric CT machine for dental imaging based on the cone-beam technique: preliminary results

    Energy Technology Data Exchange (ETDEWEB)

    Mozzo, P. [Dept. of Medical Physics, University Hospital, Verona (Italy); Procacci, C.; Tacconi, A.; Tinazzi Martini, P.; Bergamo Andreis, I.A. [Dept. of Radiology, University Hospital, Verona (Italy)

    1998-12-01

    The objective of this paper is to present a new type of volumetric CT which uses the cone-beam technique instead of traditional fan-beam technique. The machine is dedicated to the dento-maxillo-facial imaging, particularly for planning in the field of implantology. The main characteristics of the unit are presented with reference to the technical parameters as well as the software performance. Images obtained are reported as various 2D sections of a volume reconstruction. Also, measurements of the geometric accuracy and the radiation dose absorbed by the patient are obtained using specific phantoms. Absorbed dose is compared with that given off by spiral CT. Geometric accuracy, evaluated with reference to various reconstruction modalities and different spatial orientations, is 0.8-1 % for width measurements and 2.2 % for height measurements. Radiation dose absorbed during the scan shows different profiles in central and peripheral axes. As regards the maximum value of the central profile, dose from the new unit is approximately one sixth that of traditional spiral CT. The new system appears to be very promising in dento-maxillo-facial imaging and, due to the good ratio between performance and low cost, together with low radiation dose, very interesting in view of large-scale use of the CT technique in such diagnostic applications. (orig.) With 10 figs., 3 tabs., 15 refs.

  5. An isolated perfused pig heart model for the development, validation and translation of novel cardiovascular magnetic resonance techniques

    Directory of Open Access Journals (Sweden)

    Perera Divaka

    2010-09-01

    Full Text Available Abstract Background Novel cardiovascular magnetic resonance (CMR techniques and imaging biomarkers are often validated in small animal models or empirically in patients. Direct translation of small animal CMR protocols to humans is rarely possible, while validation in humans is often difficult, slow and occasionally not possible due to ethical considerations. The aim of this study is to overcome these limitations by introducing an MR-compatible, free beating, blood-perfused, isolated pig heart model for the development of novel CMR methodology. Methods 6 hearts were perfused outside of the MR environment to establish preparation stability. Coronary perfusion pressure (CPP, coronary blood flow (CBF, left ventricular pressure (LVP, arterial blood gas and electrolyte composition were monitored over 4 hours. Further hearts were perfused within 3T (n = 3 and 1.5T (n = 3 clinical MR scanners, and characterised using functional (CINE, perfusion and late gadolinium enhancement (LGE imaging. Perfusion imaging was performed globally and selectively for the right (RCA and left coronary artery (LCA. In one heart the RCA perfusion territory was determined and compared to infarct size after coronary occlusion. Results All physiological parameters measured remained stable and within normal ranges. The model proved amenable to CMR at both field strengths using typical clinical acquisitions. There was good agreement between the RCA perfusion territory measured by selective first pass perfusion and LGE after coronary occlusion (37% versus 36% of the LV respectively. Conclusions This flexible model allows imaging of cardiac function in a controllable, beating, human-sized heart using clinical MR systems. It should aid further development, validation and clinical translation of novel CMR methodologies, and imaging sequences.

  6. A New Profile Learning Model for Recommendation System based on Machine Learning Technique

    Directory of Open Access Journals (Sweden)

    Shereen H. Ali

    2016-03-01

    Full Text Available Recommender systems (RSs have been used to successfully address the information overload problem by providing personalized and targeted recommendations to the end users. RSs are software tools and techniques providing suggestions for items to be of use to a user, hence, they typically apply techniques and methodologies from Data Mining. The main contribution of this paper is to introduce a new user profile learning model to promote the recommendation accuracy of vertical recommendation systems. The proposed profile learning model employs the vertical classifier that has been used in multi classification module of the Intelligent Adaptive Vertical Recommendation (IAVR system to discover the user’s area of interest, and then build the user’s profile accordingly. Experimental results have proven the effectiveness of the proposed profile learning model, which accordingly will promote the recommendation accuracy.

  7. A Classical Fuzzy Approach for Software Effort Estimation on Machine Learning Technique

    OpenAIRE

    S.Malathi; Sridhar, S.

    2011-01-01

    Software Cost Estimation with resounding reliability, productivity and development effort is a challenging and onerous task. This has incited the software community to give much needed thrust and delve into extensive research in software effort estimation for evolving sophisticated methods. Estimation by analogy is one of the expedient techniques in software effort estimation field. However, the methodology utilized for the estimation of software effort by analogy is not able to handle the ca...

  8. Applying machine learning techniques for forecasting flexibility of virtual power plants

    DEFF Research Database (Denmark)

    MacDougall, Pamela; Kosek, Anna Magdalena; Bindner, Henrik W.

    2016-01-01

    hidden layer artificial neural network (ANN). Both techniques are used to model a relationship between the aggregator portfolio state and requested ramp power to the longevity of the delivered flexibility. Using validated individual household models, a smart controlled aggregated virtual power plant...... is simulated. A hierarchical market-based supply-demand matching control mechanism is used to steer the heating devices in the virtual power plant. For both the training and validation set of clusters, a random number of households, between 200 and 2000, is generated with day ahead profile scaled accordingly...

  9. Exploring Machine Learning Techniques For Dynamic Modeling on Future Exascale Systems

    Energy Technology Data Exchange (ETDEWEB)

    Song, Shuaiwen; Tallent, Nathan R.; Vishnu, Abhinav

    2013-09-23

    Future exascale systems must be optimized for both power and performance at scale in order to achieve DOE’s goal of a sustained petaflop within 20 Megawatts by 2022 [1]. Massive parallelism of the future systems combined with complex memory hierarchies will form a barrier to efficient application and architecture design. These challenges are exacerbated with emerging complex architectures such as GPGPUs and Intel Xeon Phi as parallelism increases orders of magnitude and system power consumption can easily triple or quadruple. Therefore, we need techniques that can reduce the search space for optimization, isolate power-performance bottlenecks, identify root causes for software/hardware inefficiency, and effectively direct runtime scheduling.

  10. Egg volume prediction using machine vision technique based on pappus theorem and artificial neural network.

    Science.gov (United States)

    Soltani, Mahmoud; Omid, Mahmoud; Alimardani, Reza

    2015-05-01

    Egg size is one of the important properties of egg that is judged by customers. Accordingly, in egg sorting and grading, the size of eggs must be considered. In this research, a new method of egg volume prediction was proposed without need to measure weight of egg. An accurate and efficient image processing algorithm was designed and implemented for computing major and minor diameters of eggs. Two methods of egg size modeling were developed. In the first method, a mathematical model was proposed based on Pappus theorem. In second method, Artificial Neural Network (ANN) technique was used to estimate egg volume. The determined egg volume by these methods was compared statistically with actual values. For mathematical modeling, the R(2), Mean absolute error and maximum absolute error values were obtained as 0.99, 0.59 cm(3) and 1.69 cm(3), respectively. To determine the best ANN, R(2) test and RMSEtest were used as selection criteria. The best ANN topology was 2-28-1 which had the R(2) test and RMSEtest of 0.992 and 0.66, respectively. After system calibration, the proposed models were evaluated. The results which indicated the mathematical modeling yielded more satisfying results. So this technique was selected for egg size determination.

  11. 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....

  12. Do Living Machines Exist? On the Relationship between Life and technique

    Directory of Open Access Journals (Sweden)

    Stascha Rohmer

    2016-12-01

    Full Text Available The industrial biotechnology calls the products of synthetic biology “living machines”. As I want to demonstrate in this article, the concept of “living machine” is misleading. The products of synthetic biology are rather modified organisms. Starting from the Kantian concept of an internal finality as the main characteristic of the living, Hegel showed that all living being is not only a being-for-itself, but also a being-for-others. As Plessner pointed out, this difference is the origin of technique, which is, according to his conception, an integral part of the process of life. We find this idea also in the organic philosophy of Whitehead. The possibility of mechanization of life originates from process of life itself.

  13. A Classical Fuzzy Approach for Software Effort Estimation on Machine Learning Technique

    CERN Document Server

    Malathi, S

    2011-01-01

    Software Cost Estimation with resounding reliability,productivity and development effort is a challenging and onerous task. This has incited the software community to give much needed thrust and delve into extensive research in software effort estimation for evolving sophisticated methods. Estimation by analogy is one of the expedient techniques in software effort estimation field. However, the methodology utilized for the estimation of software effort by analogy is not able to handle the categorical data in an explicit and precise manner. A new approach has been developed in this paper to estimate software effort for projects represented by categorical or numerical data using reasoning by analogy and fuzzy approach. The existing historical data sets, analyzed with fuzzy logic, produce accurate results in comparison to the data set analyzed with the earlier methodologies.

  14. A Classical Fuzzy Approach for Software Effort Estimation on Machine Learning Technique

    Directory of Open Access Journals (Sweden)

    S.Malathi

    2011-11-01

    Full Text Available Software Cost Estimation with resounding reliability, productivity and development effort is a challenging and onerous task. This has incited the software community to give much needed thrust and delve into extensive research in software effort estimation for evolving sophisticated methods. Estimation by analogy is one of the expedient techniques in software effort estimation field. However, the methodology utilized for the estimation of software effort by analogy is not able to handle the categorical data in an explicit and precise manner. A new approach has been developed in this paper to estimate software effort for projects represented by categorical or numerical data using reasoning by analogy and fuzzy approach. The existing historical datasets, analyzed with fuzzy logic, produce accurate results in comparison to the dataset analyzed with the earlier methodologies.

  15. Experimental and numerical analysis of the air inflow technique for dust removal from the vacuum vessel of a tokamak machine

    Energy Technology Data Exchange (ETDEWEB)

    Paci, S. [Pisa University, via Diotisalvi 2, I-56100 Pisa (Italy)], E-mail: sandro.paci@ing.unipi.it; Porfiri, M.T. [ENEA Nuclear Fusion Technologies, via E. Fermi 45, I-00044 Frascati, Rome (Italy)

    2008-01-15

    In fusion facilities, the dust production inside the plasma chamber is a concern from the viewpoint of both machine performance and safety. To the purpose of a correct handling of the experimental devices the problem of its removal must be properly solved. This work deals with the experiments carried out in the STARDUST facility by using as dust removal technique an air inflow into the volume representing the vacuum vessel. The goal was to evaluate the effectiveness of such an approach, less invasive as compared to all the others so far. These experiments, performed by using characterized carbon, tungsten and stainless steel dusts, show that the mobilization capability of the air inflow is between few percent and 100%, mainly depending on dust type of and deposit shape. The capture efficiency in a filter reached a maximum of about 7.5% in the STARDUST geometrical configuration. In conclusion, this simple and clean (from the radioactive point of view) removing technique needs particular care to be more effective and is not the perfect solution due to its low efficiency in the collection of removed powder in proper surfaces (i.e., filters). Nevertheless improvements are possible and worthwhile.

  16. Improving the vector auto regression technique for time-series link prediction by using support vector machine

    Directory of Open Access Journals (Sweden)

    Co Jan Miles

    2016-01-01

    Full Text Available Predicting links between the nodes of a graph has become an important Data Mining task because of its direct applications to biology, social networking, communication surveillance, and other domains. Recent literature in time-series link prediction has shown that the Vector Auto Regression (VAR technique is one of the most accurate for this problem. In this study, we apply Support Vector Machine (SVM to improve the VAR technique that uses an unweighted adjacency matrix along with 5 matrices: Common Neighbor (CN, Adamic-Adar (AA, Jaccard’s Coefficient (JC, Preferential Attachment (PA, and Research Allocation Index (RA. A DBLP dataset covering the years from 2003 until 2013 was collected and transformed into time-sliced graph representations. The appropriate matrices were computed from these graphs, mapped to the feature space, and then used to build baseline VAR models with lag of 2 and some corresponding SVM classifiers. Using the Area Under the Receiver Operating Characteristic Curve (AUC-ROC as the main fitness metric, the average result of 82.04% for the VAR was improved to 84.78% with SVM. Additional experiments to handle the highly imbalanced dataset by oversampling with SMOTE and undersampling with K-means clusters, however, did not improve the average AUC-ROC of the baseline SVM.

  17. Improvement of machining accuracy in precision micro-boring system by forecasting compensatory control technique

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    Presents the design of a micro-boring servo system. A piezoelectric actuator is employed to compensate the deflection errors of the cutter in the radial direction to reduce the force-induced errors in the workpiece. In order to bore small and deep holes, the boring bar is designed with a new structure consisting of two concentric bars, one being used for error measuring and the other for error compensation. As a result, the size of the micro-boring bar is not af fected even after the piezoelectric actuator and strain gauges have been incorporated. The outer diameter of the boring bar used is 16 mm and the length to diameter ratio is greater than 9. A Forecasting Compensatory Control (FCC) technique is adopted in this system for error prediction and error compensation. The off-line forecasting compensatory control simulation and on-line cutting results have verified that the roundness form errors in the workpiece can be re duced up to 60 percent with the developed micro-boring servo system.

  18. Wastewater quality monitoring system using sensor fusion and machine learning techniques.

    Science.gov (United States)

    Qin, Xusong; Gao, Furong; Chen, Guohua

    2012-03-15

    A multi-sensor water quality monitoring system incorporating an UV/Vis spectrometer and a turbidimeter was used to monitor the Chemical Oxygen Demand (COD), Total Suspended Solids (TSS) and Oil & Grease (O&G) concentrations of the effluents from the Chinese restaurant on campus and an electrocoagulation-electroflotation (EC-EF) pilot plant. In order to handle the noise and information unbalance in the fused UV/Vis spectra and turbidity measurements during the calibration model building, an improved boosting method, Boosting-Iterative Predictor Weighting-Partial Least Squares (Boosting-IPW-PLS), was developed in the present study. The Boosting-IPW-PLS method incorporates IPW into boosting scheme to suppress the quality-irrelevant variables by assigning small weights, and builds up the models for the wastewater quality predictions based on the weighted variables. The monitoring system was tested in the field with satisfactory results, underlying the potential of this technique for the online monitoring of water quality. Copyright © 2011 Elsevier Ltd. All rights reserved.

  19. HPC Usage Behavior Analysis and Performance Estimation with Machine Learning Techniques

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Hao [ORNL; You, Haihang [ORNL; Hadri, Bilel [ORNL; Fahey, Mark R [ORNL

    2012-01-01

    Most researchers with little high performance computing (HPC) experience have difficulties productively using the supercomputing resources. To address this issue, we investigated usage behaviors of the world s fastest academic Kraken supercomputer, and built a knowledge-based recommendation system to improve user productivity. Six clustering techniques, along with three cluster validation measures, were implemented to investigate the underlying patterns of usage behaviors. Besides manually defining a category for very large job submissions, six behavior categories were identified, which cleanly separated the data intensive jobs and computational intensive jobs. Then, job statistics of each behavior category were used to develop a knowledge-based recommendation system that can provide users with instructions about choosing appropriate software packages, setting job parameter values, and estimating job queuing time and runtime. Experiments were conducted to evaluate the performance of the proposed recommendation system, which included 127 job submissions by users from different research fields. Great feedback indicated the usefulness of the provided information. The average runtime estimation accuracy of 64.2%, with 28.9% job termination rate, was achieved in the experiments, which almost doubled the average accuracy in the Kraken dataset.

  20. Classifying depression patients and normal subjects using machine learning techniques and nonlinear features from EEG signal.

    Science.gov (United States)

    Hosseinifard, Behshad; Moradi, Mohammad Hassan; Rostami, Reza

    2013-03-01

    Diagnosing depression in the early curable stages is very important and may even save the life of a patient. In this paper, we study nonlinear analysis of EEG signal for discriminating depression patients and normal controls. Forty-five unmedicated depressed patients and 45 normal subjects were participated in this study. Power of four EEG bands and four nonlinear features including detrended fluctuation analysis (DFA), higuchi fractal, correlation dimension and lyapunov exponent were extracted from EEG signal. For discriminating the two groups, k-nearest neighbor, linear discriminant analysis and logistic regression as the classifiers are then used. Highest classification accuracy of 83.3% is obtained by correlation dimension and LR classifier among other nonlinear features. For further improvement, all nonlinear features are combined and applied to classifiers. A classification accuracy of 90% is achieved by all nonlinear features and LR classifier. In all experiments, genetic algorithm is employed to select the most important features. The proposed technique is compared and contrasted with the other reported methods and it is demonstrated that by combining nonlinear features, the performance is enhanced. This study shows that nonlinear analysis of EEG can be a useful method for discriminating depressed patients and normal subjects. It is suggested that this analysis may be a complementary tool to help psychiatrists for diagnosing depressed patients. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

  1. On the Use of Machine Vision Techniques to Detect Human Settlements in Satellite Images

    Energy Technology Data Exchange (ETDEWEB)

    Kamath, C; Sengupta, S K; Poland, D; Futterman, J A H

    2003-01-10

    The automated production of maps of human settlement from recent satellite images is essential to studies of urbanization, population movement, and the like. The spectral and spatial resolution of such imagery is often high enough to successfully apply computer vision techniques. However, vast amounts of data have to be processed quickly. In this paper, we propose an approach that processes the data in several different stages. At each stage, using features appropriate to that stage, we identify the portion of the data likely to contain information relevant to the identification of human settlements. This data is used as input to the next stage of processing. Since the size of the data has reduced, we can now use more complex features in this next stage. These features can be more representative of human settlements, and also more time consuming to extract from the image data. Such a hierarchical approach enables us to process large amounts of data in a reasonable time, while maintaining the accuracy of human settlement identification. We illustrate our multi-stage approach using IKONOS 4-band and panchromatic images, and compare it with the straight-forward processing of the entire image.

  2. Pattern recognition & machine learning

    CERN Document Server

    Anzai, Y

    1992-01-01

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

  3. 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.

  4. On Yao's method of translation

    NARCIS (Netherlands)

    Liu, X.; Hoede, C.

    2002-01-01

    Machine Translation, i.e., translating one kind of natural language to another kind of natural language by using a computer system, is a very important research branch in Artificial Intelligence. Yao developed a method of translation that he called ``Lexical-Semantic Driven". In his system he introd

  5. CLASSIFICATION AND RANKING OF FERMI LAT GAMMA-RAY SOURCES FROM THE 3FGL CATALOG USING MACHINE LEARNING TECHNIQUES

    Energy Technology Data Exchange (ETDEWEB)

    Saz Parkinson, P. M. [Department of Physics, The University of Hong Kong, Pokfulam Road, Hong Kong (China); Xu, H.; Yu, P. L. H. [Department of Statistics and Actuarial Science, The University of Hong Kong, Pokfulam Road, Hong Kong (China); Salvetti, D.; Marelli, M. [INAF—Istituto di Astrofisica Spaziale e Fisica Cosmica Milano, via E. Bassini 15, I-20133, Milano (Italy); Falcone, A. D. [Department of Astronomy and Astrophysics, The Pennsylvania State University, University Park, PA 16802 (United States)

    2016-03-20

    We apply a number of statistical and machine learning techniques to classify and rank gamma-ray sources from the Third Fermi Large Area Telescope Source Catalog (3FGL), according to their likelihood of falling into the two major classes of gamma-ray emitters: pulsars (PSR) or active galactic nuclei (AGNs). Using 1904 3FGL sources that have been identified/associated with AGNs (1738) and PSR (166), we train (using 70% of our sample) and test (using 30%) our algorithms and find that the best overall accuracy (>96%) is obtained with the Random Forest (RF) technique, while using a logistic regression (LR) algorithm results in only marginally lower accuracy. We apply the same techniques on a subsample of 142 known gamma-ray pulsars to classify them into two major subcategories: young (YNG) and millisecond pulsars (MSP). Once more, the RF algorithm has the best overall accuracy (∼90%), while a boosted LR analysis comes a close second. We apply our two best models (RF and LR) to the entire 3FGL catalog, providing predictions on the likely nature of unassociated sources, including the likely type of pulsar (YNG or MSP). We also use our predictions to shed light on the possible nature of some gamma-ray sources with known associations (e.g., binaries, supernova remnants/pulsar wind nebulae). Finally, we provide a list of plausible X-ray counterparts for some pulsar candidates, obtained using Swift, Chandra, and XMM. The results of our study will be of interest both for in-depth follow-up searches (e.g., pulsar) at various wavelengths and for broader population studies.

  6. Classification and Ranking of Fermi LAT Gamma-ray Sources from the 3FGL Catalog using Machine Learning Techniques

    Science.gov (United States)

    Saz Parkinson, P. M.; Xu, H.; Yu, P. L. H.; Salvetti, D.; Marelli, M.; Falcone, A. D.

    2016-03-01

    We apply a number of statistical and machine learning techniques to classify and rank gamma-ray sources from the Third Fermi Large Area Telescope Source Catalog (3FGL), according to their likelihood of falling into the two major classes of gamma-ray emitters: pulsars (PSR) or active galactic nuclei (AGNs). Using 1904 3FGL sources that have been identified/associated with AGNs (1738) and PSR (166), we train (using 70% of our sample) and test (using 30%) our algorithms and find that the best overall accuracy (>96%) is obtained with the Random Forest (RF) technique, while using a logistic regression (LR) algorithm results in only marginally lower accuracy. We apply the same techniques on a subsample of 142 known gamma-ray pulsars to classify them into two major subcategories: young (YNG) and millisecond pulsars (MSP). Once more, the RF algorithm has the best overall accuracy (∼90%), while a boosted LR analysis comes a close second. We apply our two best models (RF and LR) to the entire 3FGL catalog, providing predictions on the likely nature of unassociated sources, including the likely type of pulsar (YNG or MSP). We also use our predictions to shed light on the possible nature of some gamma-ray sources with known associations (e.g., binaries, supernova remnants/pulsar wind nebulae). Finally, we provide a list of plausible X-ray counterparts for some pulsar candidates, obtained using Swift, Chandra, and XMM. The results of our study will be of interest both for in-depth follow-up searches (e.g., pulsar) at various wavelengths and for broader population studies.

  7. Translations and Translators.

    Science.gov (United States)

    Nida, Eugene A.

    1979-01-01

    The necessity for stylistic appropriateness in translation as well as correct content is discussed. To acquire this skill, translators must be trained in stylistics through close examination of their own language and must have practice in translating for different audiences at different levels. (PMJ)

  8. Techniques Exploring on Machining External Thread of Hard Alloy by Electric Discharge Machine%硬质合金外螺纹的电火花成型机加工工艺探讨

    Institute of Scientific and Technical Information of China (English)

    何兴会; 杨国英

    2012-01-01

    结合硬质合金的材料特性,将电火花成型电极加工内外螺纹的工艺差异进行对比,分析硬质合金外螺纹电火花加工工艺难点,并提出合理的改进措施.再以电火花成型电极加工YG6硬质合金外螺纹为实例,运用改进方法成功加工出较高质量的外螺纹.结果表明:选取合适的峰值电流,改进加工电极结构是保证外螺纹加工质量的关键技术.最后对单电极电火花加工外螺纹的可行性工艺方案进行详细说明.%Considering the material attribute of hard alloy, the technique difference between external thread and inner thread machined by electric discharge machine is compared, and then the difficulties in machining external thread of hard alloy by electric discharge machine is analyzed and a better solution can be proposed. Take a machined work piece of YG6 for example to illustrate the high quality validity of the solutions. The results show that better quality is obtained by selecting suitable peak current and redesigning the electrode in machining external thread.

  9. Translating Words, Translating Cultures

    Directory of Open Access Journals (Sweden)

    Richard Whitaker

    2012-03-01

    Full Text Available What exactly does (or should translation from one language into another try to do? Attempt to convey to readers of the target language (the language into which one is translating something of the strangeness, difference and historicity of the original in the source language (the language from which one is translating? Or must translation try to bridge the gap between source and target language, by rendering the original in a thoroughly contemporary style and diction, as if this were a work being written now for the first time? And related to these the further questions: how closely should a translation render the genre, language, metre, style and content of the original? How far can a translation depart from the original without ceasing to be a translation – in other words, where is one to situate the border between “translation”, “version” and “adaptation”?

  10. Predicting the academic success of architecture students by pre-enrolment requirement: using machine-learning techniques

    Directory of Open Access Journals (Sweden)

    Ralph Olusola Aluko

    2016-12-01

    Full Text Available In recent years, there has been an increase in the number of applicants seeking admission into architecture programmes. As expected, prior academic performance (also referred to as pre-enrolment requirement is a major factor considered during the process of selecting applicants. In the present study, machine learning models were used to predict academic success of architecture students based on information provided in prior academic performance. Two modeling techniques, namely K-nearest neighbour (k-NN and linear discriminant analysis were applied in the study. It was found that K-nearest neighbour (k-NN outperforms the linear discriminant analysis model in terms of accuracy. In addition, grades obtained in mathematics (at ordinary level examinations had a significant impact on the academic success of undergraduate architecture students. This paper makes a modest contribution to the ongoing discussion on the relationship between prior academic performance and academic success of undergraduate students by evaluating this proposition. One of the issues that emerges from these findings is that prior academic performance can be used as a predictor of academic success in undergraduate architecture programmes. Overall, the developed k-NN model can serve as a valuable tool during the process of selecting new intakes into undergraduate architecture programmes in Nigeria.

  11. Recognition of Mould Colony on Unhulled Paddy Based on Computer Vision using Conventional Machine-learning and Deep Learning Techniques

    Science.gov (United States)

    Sun, Ke; Wang, Zhengjie; Tu, Kang; Wang, Shaojin; Pan, Leiqing

    2016-11-01

    To investigate the potential of conventional and deep learning techniques to recognize the species and distribution of mould in unhulled paddy, samples were inoculated and cultivated with five species of mould, and sample images were captured. The mould recognition methods were built using support vector machine (SVM), back-propagation neural network (BPNN), convolutional neural network (CNN), and deep belief network (DBN) models. An accuracy rate of 100% was achieved by using the DBN model to identify the mould species in the sample images based on selected colour-histogram parameters, followed by the SVM and BPNN models. A pitch segmentation recognition method combined with different classification models was developed to recognize the mould colony areas in the image. The accuracy rates of the SVM and CNN models for pitch classification were approximately 90% and were higher than those of the BPNN and DBN models. The CNN and DBN models showed quicker calculation speeds for recognizing all of the pitches segmented from a single sample image. Finally, an efficient uniform CNN pitch classification model for all five types of sample images was built. This work compares multiple classification models and provides feasible recognition methods for mouldy unhulled paddy recognition.

  12. CAD/CAM machining Vs pre-sintering in-lab fabrication techniques of Y-TZP ceramic specimens: Effects on their mechanical fatigue behavior.

    Science.gov (United States)

    Zucuni, C P; Guilardi, L F; Fraga, S; May, L G; Pereira, G K R; Valandro, L F

    2017-03-18

    This study evaluated the effects of different pre-sintering fabrication processing techniques of Y-TZP ceramic (CAD/CAM Vs. in-lab), considering surface characteristics and mechanical performance outcomes. Pre-sintered discs of Y-TZP ceramic (IPS e.max ZirCAD, Ivoclar Vivadent) were produced using different pre-sintering fabrication processing techniques: Machined- milling with a CAD/CAM system; Polished- fabrication using a cutting device followed by polishing (600 and 1200 SiC papers); Xfine- fabrication using a cutting machine followed by grinding with extra-fine diamond bur (grit size 30 μm); Fine- fabrication using a cutting machine followed by grinding with fine diamond bur (grit size 46 μm); SiC- fabrication using a cutting machine followed by grinding with 220 SiC paper. Afterwards, the discs were sintered and submitted to roughness (n=35), surface topography (n=2), phase transformation (n=2), biaxial flexural strength (n=20), and biaxial flexural fatigue strength (fatigue limit) (n=15) analyses. No monoclinic-phase content was observed in all processing techniques. It can be observed that obtaining a surface with similar characteristics to CAD/CAM milling is essential for the observation of similar mechanical performance. On this sense, grinding with fine diamond bur before sintering (Fine group) was the best mimic protocol in comparison to the CAD/CAM milling.

  13. To Weaken the Language Barriers for the Chinese Minorities by the Machine Translation Technology%利用机器翻译技术消弱少数民族语言障碍

    Institute of Scientific and Technical Information of China (English)

    吴凤娟

    2011-01-01

    As a multi-ethnic region, there are both advantages and disadvantages for China. The language barrier is always a great obstruction for the development of the minority nationalities. The machine translation specific to the languages of Chinese minorities contribute to advance the culture communication, to drive the economic growth and to build a harmonious society. By now some development has been made in this field. But if we want to get the actual applying effect, there is a long road before us. To advance the machine translation specific to the languages of Chinese minorities is of great significance.%我国多民族聚居的局面有利有弊,语言障碍一直是少数民族地区发展的巨大阻力.针对少数民族语言的机器翻译有助于推进文化交流、带动经济发展、建立和谐社会.目前该领域的研究已取得了一定进展,但要达到实际应用效果仍有较长的路要走.大力推进针对少数民族的机器翻译工作意义重大.

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

    Science.gov (United States)

    Ghasemi, Hadis; Hashemian, Mahmood

    2016-01-01

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

  15. Translation skills of Business English

    Institute of Scientific and Technical Information of China (English)

    Hu Lu; He Yan-ni

    2014-01-01

    With the deepening of economic globalization, business English plays an increasingly vital role. In order to better translate business English, the translator has to adopt some important translation techniques. Thus, emphasis is placed on business English translation skills, such as omission, supplement and word conversion, etc, which provides some practical advice to the translation of business English.

  16. Translation skills of Business English

    Institute of Scientific and Technical Information of China (English)

    Hu; Lu; He; Yan-ni

    2014-01-01

    With the deepening of economic globalization,business English plays an increasingly vital role.In order to better translate business English,the translator has to adopt some important translation techniques.Thus,emphasis is placed on business English translation skills,such as omission,supplement and word conversion,etc,which provides some practical advice to the translation of business English.

  17. 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.

  18. Completeness of Compositional Translation for Context-Free Grammars

    CERN Document Server

    Huijsen, W O

    1996-01-01

    A machine translation system is said to be *complete* if all expressions that are correct according to the source-language grammar can be translated into the target language. This paper addresses the completeness issue for compositional machine translation in general, and for compositional machine translation of context-free grammars in particular. Conditions that guarantee translation completeness of context-free grammars are presented.

  19. 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。

  20. A Taxonomy of Human Translation Styles

    DEFF Research Database (Denmark)

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

    2011-01-01

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

  1. Improving the Prediction of Survival in Cancer Patients by Using Machine Learning Techniques: Experience of Gene Expression Data: A Narrative Review.

    Science.gov (United States)

    Bashiri, Azadeh; Ghazisaeedi, Marjan; Safdari, Reza; Shahmoradi, Leila; Ehtesham, Hamide

    2017-02-01

    Today, despite the many advances in early detection of diseases, cancer patients have a poor prognosis and the survival rates in them are low. Recently, microarray technologies have been used for gathering thousands data about the gene expression level of cancer cells. These types of data are the main indicators in survival prediction of cancer. This study highlights the improvement of survival prediction based on gene expression data by using machine learning techniques in cancer patients. This review article was conducted by searching articles between 2000 to 2016 in scientific databases and e-Journals. We used keywords such as machine learning, gene expression data, survival and cancer. Studies have shown the high accuracy and effectiveness of gene expression data in comparison with clinical data in survival prediction. Because of bewildering and high volume of such data, studies have highlighted the importance of machine learning algorithms such as Artificial Neural Networks (ANN) to find out the distinctive signatures of gene expression in cancer patients. These algorithms improve the efficiency of probing and analyzing gene expression in cancer profiles for survival prediction of cancer. By attention to the capabilities of machine learning techniques in proteomics and genomics applications, developing clinical decision support systems based on these methods for analyzing gene expression data can prevent potential errors in survival estimation, provide appropriate and individualized treatments to patients and improve the prognosis of cancers.

  2. An investigation of penetrant techniques for detection of machining-induced surface-breaking cracks on monolithic ceramics

    Energy Technology Data Exchange (ETDEWEB)

    Forster, G.A.; Ellingson, W.A.

    1996-02-01

    The purpose of this effort was to evaluate penetrant methods for their ability to detect surface-breaking cracks in monolithic ceramic materials with an emphasis on detection of cracks generated by machining. There are two basic penetrant types, visible and fluorescent. The visible penetrant method is usually augmented by powder developers and cracks detected can be seen in visible light. Cracks detected by fluorescent penetrant are visible only under ultraviolet light used with or without a developer. The developer is basically a powder that wicks up penetrant from a crack to make it more observable. Although fluorescent penetrants were recommended in the literature survey conducted early in this effort, visible penetrants and two non-standard techniques, a capillary gaseous diffusion method under development at the institute of Chemical Physics in Moscow, and the {open_quotes}statiflux{close_quotes} method which involves use of electrically charged particles, were also investigated. SiAlON ring specimens (1 in. diameter, 3/4 in. wide) which had been subjected to different thermal-shock cycles were used for these tests. The capillary gaseous diffusion method is based on ammonia; the detector is a specially impregnated paper much like litmus paper. As expected, visible dye penetrants offered no detection sensitivity for tight, surface-breaking cracks in ceramics. Although the non-standard statiflux method showed promise on high-crack-density specimens, it was ineffective on limited-crack-density specimens. The fluorescent penetrant method was superior for surface-breaking crack detection, but successful application of this procedure depends greatly on the skill of the user. Two presently available high-sensitivity fluorescent penetrants were then evaluated for detection of microcracks on Si{sub 3}N{sub 4} and SiC from different suppliers. Although 50X optical magnification may be sufficient for many applications, 200X magnification provides excellent delectability.

  3. Computer aided prognosis for cell death categorization and prediction in vivo using quantitative ultrasound and machine learning techniques.

    Science.gov (United States)

    Gangeh, M J; Hashim, A; Giles, A; Sannachi, L; Czarnota, G J

    2016-12-01

    At present, a one-size-fits-all approach is typically used for cancer therapy in patients. This is mainly because there is no current imaging-based clinical standard for the early assessment and monitoring of cancer treatment response. Here, the authors have developed, for the first time, a complete computer-aided-prognosis (CAP) system based on multiparametric quantitative ultrasound (QUS) spectroscopy methods in association with texture descriptors and advanced machine learning techniques. This system was used to noninvasively categorize and predict cell death levels in fibrosarcoma mouse tumors treated using ultrasound-stimulated microbubbles as novel endothelial-cell radiosensitizers. Sarcoma xenograft tumor-bearing mice were treated using ultrasound-stimulated microbubbles, alone or in combination with x-ray radiation therapy, as a new antivascular treatment. Therapy effects were assessed at 2-3, 24, and 72 h after treatment using a high-frequency ultrasound. Two-dimensional spectral parametric maps were generated using the power spectra of the raw radiofrequency echo signal. Subsequently, the distances between "pretreatment" and "post-treatment" scans were computed as an indication of treatment efficacy, using a kernel-based metric on textural features extracted from 2D parametric maps. A supervised learning paradigm was used to either categorize cell death levels as low, medium, or high using a classifier, or to "continuously" predict the levels of cell death using a regressor. The developed CAP system performed at a high level for the classification of cell death levels. The area under curve of the receiver operating characteristic was 0.87 for the classification of cell death levels to both low/medium and medium/high levels. Moreover, the prediction of cell death levels using the proposed CAP system achieved a good correlation (r = 0.68,  p course of therapy to enable switching to more efficacious treatments.

  4. Historical and Epistemological Reflections on the Culture of Machines around the Renaissance: How Science and Technique Work?

    Directory of Open Access Journals (Sweden)

    Raffaele Pisano

    2014-10-01

    Full Text Available This paper is divided into two parts, this being the first one. The second is entitled ‘Historical and Epistemological Reflections on the Culture of Machines around Renaissance: Machines, Machineries and Perpetual Motion’ and will be published in Acta Baltica Historiae et Philosophiae Scientiarum in 2015. Based on our recent studies, we provide here a historical and epistemological feature on the role played by machines and machineries. Ours is an epistemological thesis based on a series of historical examples to show that the relations between theoretical science and the construction of machines cannot be taken for granted, a priori. Our analysis is mainly based on the culture of machines around 15th and 17th centuries, namely the epoch of Late Renaissance and Early Modern Age. For this is the period of scientific revolution and this age offers abundant interesting material for researches into the relations of theoretical science/construction of machines as well. However, to prove our epistemological thesis, we will also exploit examples of machines built in other historical periods. Particularly, a discussion concerning the relationship between science theory and the development of science art crafts produced by non-recognized scientists in a certain historical time is presented. The main questions are: when and why did the tension between science (physics, mathematics and geometry give rise to a new scientific approach to applied discipline such as studies on machines and machineries? What kind of science was used (if at all for projecting machines and machineries? Was science at the time a necessary precondition to build a machine? In the first part we will focus on the difference between Aristotelian-Euclidean and Archimedean approaches and we will outline the heritage of these two different approaches in late medieval and Renaissance science. In the second part, we will apply our reconstructions to some historical and epistemological

  5. Studies on the Material Removal Rate of Al-SiC Composites Machined by Powder- Mixed EDM Technique

    Directory of Open Access Journals (Sweden)

    G P Anuraag

    2016-04-01

    Full Text Available The metal-matrix composites are preferred due to their high hardness, light weight, flexibility, high strength, simplicity and ease of applicability which make them potentially valuable in every industrious area like motor vehicles industries, mechanical tools manufacturing industries, structural applications and aerospace industries. Electro-discharge machining is a non-conventional machining process which uses short electrical discharges to machine any material of any hardness and strength levels provided that they are electrically conductive. In this paper, an attempt was made to find the machinability of aluminium metal matrix composite using powder mixed electric discharge machining (PMEDM. The aluminium matrix was reinforced with different percentages of silicon carbide (3%, 9% & 15% to form the composites using stir casting process. The Characteristic Material removal rate (MRR was studied while varying the process parameters of discharge time (TON, peak current (I and concentration of SiC in work material (C according to the face cantered central composite design for a constant voltage of 40 volts. The Electric Discharge Machining of the composites was carried out using a copper electrode of Ø6mm and kerosene mixed with aluminium powder was used as dielectric fluid.

  6. NICT/ATR Chinese-Japanese-English Speech-to-Speech Translation System

    Institute of Scientific and Technical Information of China (English)

    Tohru Shimizu; Yutaka Ashikari; Eiichiro Sumita; ZHANG Jinsong; Satoshi Nakamura

    2008-01-01

    This paper describes the latest version of the Chinese-Japanese-English handheld speech-to-speech translation system developed by NICT/ATR,which is now ready to be deployed for travelers.With the entire speech-to-speech translation function being implemented into one terminal,it realizes real-time,location-free speech-to-speech translation.A new noise-suppression technique notably improves the speech recognition performance.Corpus-based approaches of speech recognition,machine translation,and speech synthesis enable coverage of a wide variety of topics and portability to other languages.Test results show that the character accuracy of speech recognition is 82%-94% for Chinese speech,with a bilingual evaluation understudy score of machine translation is 0.55-0.74 for Chinese-Japanese and Chinese-English.

  7. Methods and Techniques to Improve the Japanese-Chinese Translation Level%提高基础日汉互译的技巧

    Institute of Scientific and Technical Information of China (English)

    赵辉

    2012-01-01

    Translation is one of the essential ability for foreign language learners. To help students improve their translation a- bility, Japanese textbooks in China usually leave Japanese-Chinese translation exercises for them to practice. However, Japanese beginners can't translate accurately, sometimes even make some mistakes in the process of translation. There are two reasons. For one thing, students have some limitations in their study. For another, Japanese and Chinese are different from each other. Com- parativity analyzing the structure and ways of using of the two languages in the process of teaching, the author wrote this essay on improving the translation methods and techniques.%翻译是外语学习者必备能力之一。为培养学生的翻译能力,国内的日语教材,通常有日汉互译的题目供学生练习。而日语初学者在进行日汉互译过程中,存在很多翻译不够准确或者错误的现象。其原因一方面由于学生自身知识储备不够,另一方面由于汉日两种语言存在很多不同。笔者在教学过程中,对日汉两种语言的构造、表达习惯等进行对比分析,结合学生出错的原因,将提高翻译水平的方法和技≯虿加以总结归纳。

  8. Translation Method and Computer Programme for Assisting the Same

    DEFF Research Database (Denmark)

    2013-01-01

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

  9. MT In Business English Translation

    Institute of Scientific and Technical Information of China (English)

    张志新

    2009-01-01

    In this article the operational principles of MT in business English translation is briefly introduced with an aim to point out that to improve the MT quality machine study is a key factor to work on.

  10. Translating China

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    sidney Shapiro, an American-born translator famous for his translation of Chinese literary works, received the Lifetime Achievement Award in Translation by the Translators Association of China on December 2, 2010.

  11. 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...

  12. 汉语网络新词特征及英译技巧探析%Analysis of Characteristics of Chinese Internet Neologisms and Translation Techniques

    Institute of Scientific and Technical Information of China (English)

    宋媛

    2014-01-01

    近年来,汉语中涌现出相当数量的网络新词,在语义和构词上都有其自身特点,蕴含着丰富的文化内涵和现实意义。本文旨在分析汉语网络新词的上述特点,并结合英译常见手法如直译法,意译法,音译加注法,移译法等,探究可行的汉语网络新词的英译方法。%In recent years, a large amount of internet neologisms have sprung up in Chinese. These internet neologisms have their own characteristics in semantics and word formations and abundant cultural connotations and realistic significance. This paper aims to analyze the above characteristics of internet neologisms and combine with the common English translation techniques, such as literal translation, free translation, and transliteration with notes and so on, to explore the feasible translation methods of Chinese internet neologisms.

  13. Understanding Translation

    DEFF Research Database (Denmark)

    Schjoldager, Anne Gram; Gottlieb, Henrik; Klitgård, Ida

    Understanding Translation is designed as a textbook for courses on the theory and practice of translation in general and of particular types of translation - such as interpreting, screen translation and literary translation. The aim of the book is to help you gain an in-depth understanding...... - translators, language teachers, translation users and literary, TV and film critics, for instance. Discussions focus on translation between Danish and English....

  14. Understanding Translation

    DEFF Research Database (Denmark)

    Schjoldager, Anne Gram; Gottlieb, Henrik; Klitgård, Ida

    Understanding Translation is designed as a textbook for courses on the theory and practice of translation in general and of particular types of translation - such as interpreting, screen translation and literary translation. The aim of the book is to help you gain an in-depth understanding of the...... - translators, language teachers, translation users and literary, TV and film critics, for instance. Discussions focus on translation between Danish and English....

  15. Multidsciplinary Approaches to Coastal Adaptation - Aplying Machine Learning Techniques to assess coastal risk in Latin America and The Caribbean

    Science.gov (United States)

    Calil, J.

    2016-12-01

    The global population, currently at 7.3 billion, is increasing by nearly 230,000 people every day. As the world's population grows to an estimated 11.2 billion by 2100, the number of people living in low elevation areas, exposed to coastal hazards, is continuing to increase. In 2013, 22 million people were displaced by extreme weather events, with 37 events displacing at least 100,000 people each. Losses from natural disasters and disaster risk are determined by a complex interaction between physical hazards and the vulnerability of a society or social-ecological system, and its exposure to such hazards. Impacts from coastal hazards depend on the number of people, value of assets, and presence of critical resources in harm's way. Moreover, coastal risks are amplified by challenging socioeconomic dynamics, including ill-advised urban development, income inequality, and poverty level. Our results demonstrate that in Latin America and the Caribbean (LAC), more than half a million people live in areas where coastal hazards, exposure (of people, assets and ecosystems), and poverty converge, creating the ideal conditions for a perfect storm. In order to identify the population at greatest risk to coastal hazards in LAC, and in response to a growing demand for multidisciplinary coastal adaptation approaches, this study employs a combination of machine learning clustering techniques (K-Means and Self Organizing Maps), and a spatial index, to assess coastal risks on a comparative scale. Data for more than 13,000 coastal locations in LAC were collected and allocated into three categories: (1) Coastal Hazards (including storm surge, wave energy and El Niño); (2) Geographic Exposure (including population, agriculture, and ecosystems); and (3) Vulnerability (including income inequality, infant mortality rate and malnutrition). This study identified hotspots of coastal vulnerability, the key drivers of coastal risk at each geographic location. Our results provide important

  16. Transliteration in EST Translation

    Institute of Scientific and Technical Information of China (English)

    王新然

    2016-01-01

    Firstly, this paper presents the definition of transliteration and its important position in EST translation. Secondly, in terms of the previous practice and experience in EST translation, four main transliteration techniques are concluded and analyzed. But meanwhile, there are still some negative issues and phenomena. As a result, it is worthy to make good use of the existing transliteration techniques and create more proper ones to remove the obstructions and promote the development of EST translation.

  17. Techniques for translating English ship management documents%英语船舶管理文件的汉译技巧

    Institute of Scientific and Technical Information of China (English)

    朱晓玲

    2012-01-01

    针对英语船舶管理文件较多使用科技术语、名词化短语、被动语态及长句的语言特点,结合翻译实践,提出在汉译时应遵循准确性、规范性、一贯性原则,采用术语翻译“约定俗成”、名词化短语活译、被动语态转译和长句拆译等翻译技巧.这样不仅可以使译文忠实再现原文件内容,而且可以使译文通顺达意,确保文件精神得到有效贯彻和落实.%In light of frequent use of technical terms, nominalization phrases, passive voice and long sentences in English ship management documents, in combination with translation practices, the principles of exactness, nonnativeness and consistency are proposed, and such techniques as resorting to conventional terms, revising, conversion of the passive voice, and splitting are suggested for translating English ship management documents. These techniques ensure the faithfulness and expressiveness of translated texts and ensure effective implementation and enforcement of ship management documents.

  18. Synonymy and translation

    NARCIS (Netherlands)

    Jong, de Franciska; Appelo, Lisette

    1987-01-01

    This paper is meant to give some insight into the interaction between on the one hand theoretical concepts in the field of formal semantics, and on the other hand linguistic research directed towards an application, more specifically, the research in the machine translation project Rosetta. The cent

  19. Synonymy and Translation

    NARCIS (Netherlands)

    de Jong, Franciska M.G.; Appelo, Lisette

    1987-01-01

    This paper is meant to give some insight into the interaction between on the one hand theoretical concepts in the field of formal semantics, and on the other hand linguistic research directed towards an application, more specifically, the research in the machine translation project Rosetta. The

  20. Quantum machine learning.

    Science.gov (United States)

    Biamonte, Jacob; Wittek, Peter; Pancotti, Nicola; Rebentrost, Patrick; Wiebe, Nathan; Lloyd, Seth

    2017-09-13

    Fuelled by increasing computer power and algorithmic advances, machine learning techniques have become powerful tools for finding patterns in data. Quantum systems produce atypical patterns that classical systems are thought not to produce efficiently, so it is reasonable to postulate that quantum computers may outperform classical computers on machine learning tasks. The field of quantum machine learning explores how to devise and implement quantum software that could enable machine learning that is faster than that of classical computers. Recent work has produced quantum algorithms that could act as the building blocks of machine learning programs, but the hardware and software challenges are still considerable.

  1. Precision machine design

    CERN Document Server

    Slocum, Alexander H

    1992-01-01

    This book is a comprehensive engineering exploration of all the aspects of precision machine design - both component and system design considerations for precision machines. It addresses both theoretical analysis and practical implementation providing many real-world design case studies as well as numerous examples of existing components and their characteristics. Fast becoming a classic, this book includes examples of analysis techniques, along with the philosophy of the solution method. It explores the physics of errors in machines and how such knowledge can be used to build an error budget for a machine, how error budgets can be used to design more accurate machines.

  2. A new technique for imaging the temporomandibular joint with a panoramic x-ray machine. Part I. Description of the technique.

    Science.gov (United States)

    Chilvarquer, I; McDavid, W D; Langlais, R P; Chilvarquer, L W; Nummikoski, P V

    1988-05-01

    A new technique for imaging the temporomandibular joint with rotational panoramic radiography is explained and demonstrated with a tissue-equivalent phantom. In this technique the patient is displaced forward and laterally away from the side under examination. Radiographs made with the proposed technique show the temporomandibular joint with more sharpness and less distortion than do radiographs made with conventional panoramic techniques.

  3. The Changing Face of the of Former Soviet Cities: Elucidated by Remote Sensing and Machine Learning Techniques

    Science.gov (United States)

    Poghosyan, Armen

    2017-04-01

    Despite remote sensing of urbanization emerged as a powerful tool to acquire critical knowledge about urban growth and its effects on global environmental change, human-environment interface as well as environmentally sustainable urban development, there is lack of studies utilizing remote sensing techniques to investigate urbanization trends in the Post-Soviet states. The unique challenges accompanying the urbanization in the Post-Soviet republics combined with the expected robust urban growth in developing countries over the next several decades highlight the critical need for a quantitative assessment of the urban dynamics in the former Soviet states as they navigate towards a free market democracy. This study uses total of 32 Level-1 precision terrain corrected (L1T) Landsat scenes with 30-m resolution as well as further auxiliary population and economic data for ten cities distributed in nine former Soviet republics to quantify the urbanization patterns in the Post-Soviet region. Land cover in each urban center of this study was classified by using Support Vector Machine (SVM) learning algorithm with overall accuracies ranging from 87 % to 97 % for 29 classification maps over three time steps during the past twenty-five years in order to estimate quantities, trends and drivers of urban growth in the study area. The results demonstrated several spatial and temporal urbanization patterns observed across the Post-Soviet states and based on urban expansion rates the cities can be divided into two groups, fast growing and slow growing urban centers. The relatively fast-growing urban centers have an average urban expansion rate of about 2.8 % per year, whereas the slow growing cities have an average urban expansion rate of about 1.0 % per year. The total area of new land converted to urban environment ranged from as low as 26 km2 to as high as 780 km2 for the ten cities over the 1990 - 2015 period, while the overall urban land increase ranged from 11.3 % to 96

  4. [Application of infrared spectroscopy technique to protein content fast measurement in milk powder based on support vector machines].

    Science.gov (United States)

    Wu, Di; Cao, Fang; Feng, Shui-Juan; He, Yong

    2008-05-01

    In the present study, the JASCO Model FTIR-4 000 fourier transform infrared spectrometer (Japan) was used, with a valid range of 7 800-350 cm(-1). Seven brands of milk powder were bought in a local supermarket. Milk powder was compressed into a uniform tablet with a diameter of 5 mm and a thickness of 2 mm, and then scanned by the spectrometer. Each sample was scanned 40 times and the data were averaged. About 60 samples were measured for each brand, and data for 409 samples were obtained. NIRS analysis was based on the range of 4 000 to 6 666 cm(-1), while MIRS analysis was between 400 and 4 000 cm(-1). The protein content was determined by kjeldahl method and the factor 6.38 was used to convert the nitrogen values to protein. The protein content value is the weight of protein per 100 g of milk powder. The NIR data of the milk powder exhibited slight differences. Univariate analysis was not really appropriate for analyzing the data sets. From NIRS region, it could be observed that the trend of different curves is similar. The one around 4 312 cm(-1) embodies the vibration of protein. From MIRS region, it could be determined that there are many differences between transmission value curves. Two troughs around 1 545 and 1 656 cm(-1) stand for the vibration of amide I and II bands of protein. The smoothing way of Savitzky-Golay with 3 segments and zero polynomials and multiplicative scatter correction (MSC) were applied for denoising. First 8 important principle components (PCs), which were obtained from principle component analysis (PCA), were the optimal input feature subset. Least-squares support vector machines was applied to build the protein prediction model based on infrared spectral transmission value. The prediction result was better than that of traditional PLS regression model as the determination coefficient for prediction (R(p)2) is 0.951 7 and root mean square error for prediction (RMSEP) is 0.520 201. These indicate that LS-SVM is a powerful tool for

  5. Translating Means Translating Meaning

    Institute of Scientific and Technical Information of China (English)

    李海燕

    2000-01-01

    美国著名翻译理论家尤金·奈达说 :“翻译即译意 (Translating m eans translating m eaning)。”就实质而言 ,翻译即译意。就是把一种语言表达的意义用另一种语言表达出来。翻译分理解与表达两个步骤。理解是翻译的基础 ,表达直接决定译文的成败与优劣 ,两者缺一不可

  6. Learning Parse and Translation Decisions From Examples With Rich Context

    CERN Document Server

    Hermjakob, U; Hermjakob, Ulf; Mooney, Raymond J.

    1997-01-01

    We present a knowledge and context-based system for parsing and translating natural language and evaluate it on sentences from the Wall Street Journal. Applying machine learning techniques, the system uses parse action examples acquired under supervision to generate a deterministic shift-reduce parser in the form of a decision structure. It relies heavily on context, as encoded in features which describe the morphological, syntactic, semantic and other aspects of a given parse state.

  7. Human Translator and Translation Technology

    Institute of Scientific and Technical Information of China (English)

    李辰

    2016-01-01

    With the great development of technology, translation technology exerts great influence on human translators because during their translation process, they may use many computer-aided translation tools, such as TRADOS, Snowman, WordFisher and etc. However, they always misunderstand the concept of computer-aided translation, so this thesis managed to providedetails about some translation technology and human translators' strengths so as to help them improve the productivity and the quality of theirtranslation works effectively and efficiently.

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

    Science.gov (United States)

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

    2017-06-01

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

  9. When Machines Design Machines!

    DEFF Research Database (Denmark)

    2011-01-01

    Until recently we were the sole designers, alone in the driving seat making all the decisions. But, we have created a world of complexity way beyond human ability to understand, control, and govern. Machines now do more trades than humans on stock markets, they control our power, water, gas...... and food supplies, manage our elevators, microclimates, automobiles and transport systems, and manufacture almost everything. It should come as no surprise that machines are now designing machines. The chips that power our computers and mobile phones, the robots and commercial processing plants on which we...... depend, all are now largely designed by machines. So what of us - will be totally usurped, or are we looking at a new symbiosis with human and artificial intelligences combined to realise the best outcomes possible. In most respects we have no choice! Human abilities alone cannot solve any of the major...

  10. Rapid Spectrophotometric Technique for Quantifying Iron in Cells Labeled with Superparamagnetic Iron Oxide Nanoparticles: Potential Translation to the Clinic

    OpenAIRE

    Dadashzadeh, Esmaeel R.; Hobson, Matthew; Bryant, L. Henry; Dean, Dana D.; Joseph A Frank

    2013-01-01

    Labeling cells with superparamagnetic iron oxide (SPIO) nanoparticles provides the ability to track cells by Magnetic Resonance Imaging. Quantifying intracellular iron concentration in SPIO labeled cells would allow for the comparison of agents and techniques used to magnetically label cells. Here we describe a rapid spectrophotometric technique (ST) to quantify iron content of SPIO labeled cells, circumventing the previous requirement of an overnight acid digestion. Following lysis with 10% ...

  11. Machine learning in image steganalysis

    CERN Document Server

    Schaathun, Hans Georg

    2012-01-01

    "The only book to look at steganalysis from the perspective of machine learning theory, and to apply the common technique of machine learning to the particular field of steganalysis; ideal for people working in both disciplines"--

  12. Computer-aided Translation Technology and Its Applications

    Institute of Scientific and Technical Information of China (English)

    汪美侠; 何大顺

    2014-01-01

    This article begins with a brief analysis of the significance of translation technology in different spheres of modern life, followed by a distinction between machine translation (MT) and computer-aided translation (CAT). It then describes some trans-lation resources and tools and examines the negative and positive aspects of computer-aided translations. Finally it comes to a conclusion that it would be greatly efficient and productive for the translators to acquire the new skills in the translation work-place.

  13. On the Systematicity of Human Translation Processes

    DEFF Research Database (Denmark)

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

    While translation careers and the translation profession become more globalised and more technological, we are still far from understanding how humans actually translate and how they could be best supported by machines. In this paper we attempt to outline a method which helps to uncover character...

  14. 基于有限状态自动机的远程命令识别与解析%Recognition & Translation of Remote Commands Based on Finite State Machine

    Institute of Scientific and Technical Information of China (English)

    毛凤翔; 韩冰

    2013-01-01

    远程命令识别与解析是嵌入式环境中终端-控制台和上-下位机模式实现远程管控的基础和关键.文中分析水下探测智能终端的工作过程,提出了一种基于有限状态自动机的远程命令识别与解析方法,智能终端可以根据工作状态自动机模型对远程命令进行快速、准确地响应,避免了复杂的计算和繁琐的决策过程.实验发现,水下探测智能终端及时识别出控制台发送的管控指令,按要求转入相应的工作状态,该方法有效地提高了水下探测智能终端机的工作性能.%It is a fundamental and key problem of how to correctly recognize and translate remote commands for terminal-console and upper-low computer to conduct remote management and control in embedded systems.By carefully analyzing working procedure of underwater probe terminal in this paper,an effective method based on finite state machine model is put forward,which can quickly and accurately respond the remote instructions,and avoid complicated computation and decision.Applied practices show the underwater probe intelligent terminal can understand kinds of management-control instructions sent from console machine,and properly tune to corresponding working mode,which can greatly improve the performance of underwater probe intelligent terminal.

  15. 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。

  16. Geospatial and machine learning techniques for wicked social science problems: analysis of crash severity on a regional highway corridor

    Science.gov (United States)

    Effati, Meysam; Thill, Jean-Claude; Shabani, Shahin

    2015-04-01

    The contention of this paper is that many social science research problems are too "wicked" to be suitably studied using conventional statistical and regression-based methods of data analysis. This paper argues that an integrated geospatial approach based on methods of machine learning is well suited to this purpose. Recognizing the intrinsic wickedness of traffic safety issues, such approach is used to unravel the complexity of traffic crash severity on highway corridors as an example of such problems. The support vector machine (SVM) and coactive neuro-fuzzy inference system (CANFIS) algorithms are tested as inferential engines to predict crash severity and uncover spatial and non-spatial factors that systematically relate to crash severity, while a sensitivity analysis is conducted to determine the relative influence of crash severity factors. Different specifications of the two methods are implemented, trained, and evaluated against crash events recorded over a 4-year period on a regional highway corridor in Northern Iran. Overall, the SVM model outperforms CANFIS by a notable margin. The combined use of spatial analysis and artificial intelligence is effective at identifying leading factors of crash severity, while explicitly accounting for spatial dependence and spatial heterogeneity effects. Thanks to the demonstrated effectiveness of a sensitivity analysis, this approach produces comprehensive results that are consistent with existing traffic safety theories and supports the prioritization of effective safety measures that are geographically targeted and behaviorally sound on regional highway corridors.

  17. Translation-A Process of Transformation

    Institute of Scientific and Technical Information of China (English)

    Viola Zhu

    2008-01-01

    Translation is a process that involves transformation and reproduction. This essay discusses some useful techniques of trans-lating practice by introducing a simple model. A few examples of good translation are presented to support explaining the model cleady.

  18. Oscillation frequencies for 35 \\Kepler solar-type planet-hosting stars using Bayesian techniques and machine learning

    CERN Document Server

    Davies, G R; Bedding, T R; Handberg, R; Lund, M N; Chaplin, W J; Huber, D; White, T R; Benomar, O; Hekker, S; Basu, S; Campante, T L; Christensen-Dalsgaard, J; Elsworth, Y; Karoff, C; Kjeldsen, H; Lundkvist, M S; Metcalfe, T S; Stello, D

    2015-01-01

    \\Kepler has revolutionised our understanding of both exoplanets and their host stars. Asteroseismology is a valuable tool in the characterisation of stars and \\Kepler is an excellent observing facility to perform asteroseismology. Here we select a sample of 35 \\Kepler solar-type stars which host transiting exoplanets (or planet candidates) with detected solar-like oscillations. Using available \\Kepler short cadence data up to Quarter 16 we create power spectra optimised for asteroseismology of solar-type stars. We identify modes of oscillation and estimate mode frequencies by ``peak bagging'' using a Bayesian MCMC framework. In addition, we expand the methodology of quality assurance using a Bayesian unsupervised machine learning approach. We report the measured frequencies of the modes of oscillation for all 35 stars and frequency ratios commonly used in detailed asteroseismic modelling. Due to the high correlations associated with frequency ratios we report the covariance matrix of all frequencies measured ...

  19. Trans-Cultural Comparative Literature Method:Using Grammar Trans-lation Techniques and Communicative Language Teaching Effectively

    Institute of Scientific and Technical Information of China (English)

    李晓彤

    2014-01-01

    Trans-Cultural Comparative Literature Method originated from the discovery of common themes and viewpoints as comparing literary texts in different languages. This article explains how the method combine GT and CLT techniques in a lesson plan that engage students with activities that compare and contrast themes and cultural aspects found in two literary texts. It ex-plores worldviews using information and knowledge of literary structures that motivate Chinese students.

  20. 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...