WorldWideScience

Sample records for machine translation techniques

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

    Science.gov (United States)

    Peng, Hao

    2018-03-01

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

  2. 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…

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

    OpenAIRE

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

    2011-01-01

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

  4. Machine translation

    Energy Technology Data Exchange (ETDEWEB)

    Nagao, M

    1982-04-01

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

  5. 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…

  6. 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.

  7. 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.

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

    DEFF Research Database (Denmark)

    Carl, Michael; Schaeffer, Moritz

    2014-01-01

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

  9. 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....

  10. Machine Translation Effect on Communication

    DEFF Research Database (Denmark)

    Jensen, Mika Yasuoka; Bjørn, Pernille

    2011-01-01

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

  11. Machine Translation

    Indian Academy of Sciences (India)

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

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

    Directory of Open Access Journals (Sweden)

    Sutopo Anam

    2018-01-01

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

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

    Science.gov (United States)

    Sutopo, Anam

    2018-02-01

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

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

    NARCIS (Netherlands)

    Daiber, J.

    2018-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Eko Pujianto

    2017-04-01

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

  16. Automatic Evaluation of Machine Translation

    DEFF Research Database (Denmark)

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

    2015-01-01

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

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

    DEFF Research Database (Denmark)

    Liyanapathirana, Jeevanthi

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

  18. Machine Translation for Academic Purposes

    Science.gov (United States)

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

    2009-01-01

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

  19. 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.

  20. 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.

  1. 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…

  2. Evaluation of Hindi to Punjabi Machine Translation System

    OpenAIRE

    Goyal, Vishal; Lehal, Gurpreet Singh

    2009-01-01

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

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

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    Sadaoki Furui

    2009-01-01

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

  4. Telemedicine as a special case of machine translation.

    Science.gov (United States)

    Wołk, Krzysztof; Marasek, Krzysztof; Glinkowski, Wojciech

    2015-12-01

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

  5. Findings of the 2014 Workshop on Statistical Machine Translation

    NARCIS (Netherlands)

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

    2014-01-01

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

  6. Translation Techniques

    OpenAIRE

    Marcia Pinheiro

    2015-01-01

    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 a...

  7. Dictionary Based Machine Translation from Kannada to Telugu

    Science.gov (United States)

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

    2017-08-01

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

  8. 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

  9. 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.

  10. 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

  11. Machine Translation from Text

    Science.gov (United States)

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

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

  12. 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.

  13. 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.

  14. Treatment of Markup in Statistical Machine Translation

    OpenAIRE

    Müller, Mathias

    2017-01-01

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

  15. 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.

  16. 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...

  17. 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.

  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. 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,

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

    NARCIS (Netherlands)

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

    2017-01-01

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

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

    Science.gov (United States)

    Azer, Haniyeh Sadeghi; Aghayi, Mohammad Bagher

    2015-01-01

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

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

    Science.gov (United States)

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

    2013-01-01

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

  3. A translator and simulator for the Burroughs D machine

    Science.gov (United States)

    Roberts, J.

    1972-01-01

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

  4. 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.

  5. Machine Translation - A Gentle Introduction

    Indian Academy of Sciences (India)

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

  6. 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...

  7. Grammatical Metaphor, Controlled Languageand Machine Translation

    DEFF Research Database (Denmark)

    Møller, Margrethe

    2003-01-01

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

  8. 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

  9. 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

  10. 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.

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

    Science.gov (United States)

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

    2017-10-17

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

  12. MSD Recombination Method in Statistical Machine Translation

    Science.gov (United States)

    Gros, Jerneja Žganec

    2008-11-01

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

  13. A Survey of Statistical Machine Translation

    Science.gov (United States)

    2007-04-01

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

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

    Science.gov (United States)

    Tominaga, Isao; Sato, Masayuki

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

  15. Using Linguistic Knowledge in Statistical Machine Translation

    Science.gov (United States)

    2010-09-01

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

  16. Findings of the 2009 Workshop on Statistical Machine Translation

    NARCIS (Netherlands)

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

    2009-01-01

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

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

    Science.gov (United States)

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

    2018-02-22

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

  18. 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

  19. A MOOC on Approaches to Machine Translation

    Science.gov (United States)

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

    2015-01-01

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

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

    NARCIS (Netherlands)

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

    2017-01-01

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

  1. Morphological Analysis for Statistical Machine Translation

    National Research Council Canada - National Science Library

    Lee, Young-Suk

    2004-01-01

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

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

    Science.gov (United States)

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

    2013-01-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

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

    Science.gov (United States)

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

    2015-02-01

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

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

    Directory of Open Access Journals (Sweden)

    Raneem Khalid Al-Tuwayrish

    2016-02-01

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

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

    Science.gov (United States)

    Madkour, Magda

    2016-01-01

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

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

    DEFF Research Database (Denmark)

    Flanagan, Marian

    2009-01-01

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

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

    Science.gov (United States)

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

    2013-01-01

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

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

    Science.gov (United States)

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

    2017-12-01

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

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

    Directory of Open Access Journals (Sweden)

    Phuoc Tran

    2016-01-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

  12. Latent domain models for statistical machine translation

    NARCIS (Netherlands)

    Hoàng, C.

    2017-01-01

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

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

    DEFF Research Database (Denmark)

    Klyueva, Natalia; Liyanapathirana, Jeevanthi

    2015-01-01

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

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

    Directory of Open Access Journals (Sweden)

    POPESCU Adrian

    2015-11-01

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

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

    NARCIS (Netherlands)

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

    2013-01-01

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

  16. Convolutional over Recurrent Encoder for Neural Machine Translation

    Directory of Open Access Journals (Sweden)

    Dakwale Praveen

    2017-06-01

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

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

    OpenAIRE

    Doherty, Stephen; O'Brien, Sharon

    2012-01-01

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

  18. 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

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

    Science.gov (United States)

    Al-Tuwayrish, Raneem Khalid

    2016-01-01

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

  20. Machine learning techniques for optical communication system optimization

    DEFF Research Database (Denmark)

    Zibar, Darko; Wass, Jesper; Thrane, Jakob

    In this paper, machine learning techniques relevant to optical communication are presented and discussed. The focus is on applying machine learning tools to optical performance monitoring and performance prediction.......In this paper, machine learning techniques relevant to optical communication are presented and discussed. The focus is on applying machine learning tools to optical performance monitoring and performance prediction....

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

    Science.gov (United States)

    1960-09-29

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

  2. Prostate Cancer Probability Prediction By Machine Learning Technique.

    Science.gov (United States)

    Jović, Srđan; Miljković, Milica; Ivanović, Miljan; Šaranović, Milena; Arsić, Milena

    2017-11-26

    The main goal of the study was to explore possibility of prostate cancer prediction by machine learning techniques. In order to improve the survival probability of the prostate cancer patients it is essential to make suitable prediction models of the prostate cancer. If one make relevant prediction of the prostate cancer it is easy to create suitable treatment based on the prediction results. Machine learning techniques are the most common techniques for the creation of the predictive models. Therefore in this study several machine techniques were applied and compared. The obtained results were analyzed and discussed. It was concluded that the machine learning techniques could be used for the relevant prediction of prostate cancer.

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

    Directory of Open Access Journals (Sweden)

    Ferrández-Tordera Jorge

    2016-04-01

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

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

    NARCIS (Netherlands)

    Toral Ruiz, Antonio

    2017-01-01

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

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

    OpenAIRE

    Fellet, Anna

    2010-01-01

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

  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. Data Mining Practical Machine Learning Tools and Techniques

    CERN Document Server

    Witten, Ian H; Hall, Mark A

    2011-01-01

    Data Mining: Practical Machine Learning Tools and Techniques offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. This highly anticipated third edition of the most acclaimed work on data mining and machine learning will teach you everything you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining. Thorough updates reflect the technical changes and modernizations that have taken place

  8. 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%.

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

    Science.gov (United States)

    Tatjewski, Marcin; Kierczak, Marcin; Plewczynski, Dariusz

    2017-01-01

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

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

    CSIR Research Space (South Africa)

    Ronald, K

    2006-11-01

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

  12. AN ANALYSIS OF TRANSLATION TECHNIQUES IN THE ENGLISH VERSION OF ARRAHMAN SURAH

    Directory of Open Access Journals (Sweden)

    Farida Repelita Wati Kembaren

    2018-02-01

    Full Text Available The Holy Qur’an has been translated into many languages including English. However, different translator of the Holy Qur’an produces different English version of Al-Qur’an because every translator uses different translation techniques to translate Al-Qur’an. This study aims to compare the three English versions of Arrahman surah, and describe the most dominant translation techniques used by the three translators to translate the Holy Qur’an. Translation techniques proposed by Molina and Albir (2002, p.509-511 are used to analyze the data. The data for this study are words, phrases, and clauses in the 78 verses of Arrahman surah in Arabic and its three English versions translated by Maulawi Sher ‘Ali, Dr. Muhammad Taqi­ud­Din Al­Hilali and Dr. Muhammad Muhsin Khan, and Talal Itani. The result shows that there are four most dominant techniques used by the three translators in translating the Holy Qur’an; Adaptation, Amplification, Established Equivalent, and Literal Translation technique. The first and the second translator prefer to use Amplification to introduce details in brackets or footnotes, but the third translator prefers to use Established Equivalent to find a term or expression recognized (by dictionaries or language in use as an equivalent.

  13. 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…

  14. 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,…

  15. Application of Fuzzy TOPSIS for evaluating machining techniques using sustainability metrics

    Science.gov (United States)

    Digalwar, Abhijeet K.

    2018-04-01

    Sustainable processes and techniques are getting increased attention over the last few decades due to rising concerns over the environment, improved focus on productivity and stringency in environmental as well as occupational health and safety norms. The present work analyzes the research on sustainable machining techniques and identifies techniques and parameters on which sustainability of a process is evaluated. Based on the analysis these parameters are then adopted as criteria’s to evaluate different sustainable machining techniques such as Cryogenic Machining, Dry Machining, Minimum Quantity Lubrication (MQL) and High Pressure Jet Assisted Machining (HPJAM) using a fuzzy TOPSIS framework. In order to facilitate easy arithmetic, the linguistic variables represented by fuzzy numbers are transformed into crisp numbers based on graded mean representation. Cryogenic machining was found to be the best alternative sustainable technique as per the fuzzy TOPSIS framework adopted. The paper provides a method to deal with multi criteria decision making problems in a complex and linguistic environment.

  16. Machine learning techniques to examine large patient databases.

    Science.gov (United States)

    Meyfroidt, Geert; Güiza, Fabian; Ramon, Jan; Bruynooghe, Maurice

    2009-03-01

    Computerization in healthcare in general, and in the operating room (OR) and intensive care unit (ICU) in particular, is on the rise. This leads to large patient databases, with specific properties. Machine learning techniques are able to examine and to extract knowledge from large databases in an automatic way. Although the number of potential applications for these techniques in medicine is large, few medical doctors are familiar with their methodology, advantages and pitfalls. A general overview of machine learning techniques, with a more detailed discussion of some of these algorithms, is presented in this review.

  17. Comparative Performance Analysis of Machine Learning Techniques for Software Bug Detection

    OpenAIRE

    Saiqa Aleem; Luiz Fernando Capretz; Faheem Ahmed

    2015-01-01

    Machine learning techniques can be used to analyse data from different perspectives and enable developers to retrieve useful information. Machine learning techniques are proven to be useful in terms of software bug prediction. In this paper, a comparative performance analysis of different machine learning techniques is explored f or software bug prediction on public available data sets. Results showed most of the mac ...

  18. 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

  19. Machine learning techniques for persuasion dectection in conversation

    OpenAIRE

    Ortiz, Pedro.

    2010-01-01

    Approved for public release; distribution is unlimited We determined that it is possible to automatically detect persuasion in conversations using three traditional machine learning techniques, naive bayes, maximum entropy, and support vector machine. These results are the first of their kind and serve as a baseline for all future work in this field. The three techniques consistently outperformed the baseline F-score, but not at a level that would be useful for real world applications. The...

  20. BENCHMARKING MACHINE LEARNING TECHNIQUES FOR SOFTWARE DEFECT DETECTION

    OpenAIRE

    Saiqa Aleem; Luiz Fernando Capretz; Faheem Ahmed

    2015-01-01

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

  1. The application of machine learning techniques in the clinical drug therapy.

    Science.gov (United States)

    Meng, Huan-Yu; Jin, Wan-Lin; Yan, Cheng-Kai; Yang, Huan

    2018-05-25

    The development of a novel drug is an extremely complicated process that includes the target identification, design and manufacture, and proper therapy of the novel drug, as well as drug dose selection, drug efficacy evaluation, and adverse drug reaction control. Due to the limited resources, high costs, long duration, and low hit-to-lead ratio in the development of pharmacogenetics and computer technology, machine learning techniques have assisted novel drug development and have gradually received more attention by researchers. According to current research, machine learning techniques are widely applied in the process of the discovery of new drugs and novel drug targets, the decision surrounding proper therapy and drug dose, and the prediction of drug efficacy and adverse drug reactions. In this article, we discussed the history, workflow, and advantages and disadvantages of machine learning techniques in the processes mentioned above. Although the advantages of machine learning techniques are fairly obvious, the application of machine learning techniques is currently limited. With further research, the application of machine techniques in drug development could be much more widespread and could potentially be one of the major methods used in drug development. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  2. 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...

  3. 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...

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

    Science.gov (United States)

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

    2013-11-07

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

  5. 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)

  6. 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.

  7. 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.

  8. 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…

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

    Science.gov (United States)

    Schubert, Klaus

    1988-01-01

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

  10. 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.

  11. Translator-computer interaction in action

    DEFF Research Database (Denmark)

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

    2016-01-01

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

  12. 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....

  13. A Taxonomy of Human Translation Styles

    DEFF Research Database (Denmark)

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

    2011-01-01

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

  14. A Comparative Analysis of Machine Learning Techniques for Credit Scoring

    OpenAIRE

    Nwulu, Nnamdi; Oroja, Shola; İlkan, Mustafa

    2012-01-01

    Abstract Credit Scoring has become an oft researched topic in light of the increasing volatility of the global economy and the recent world financial crisis. Amidst the many methods used for credit scoring, machine learning techniques are becoming increasingly popular due to their efficient and accurate nature and relative simplicity. Furthermore machine learning techniques minimize the risk of human bias and error and maximize speed as they are able to perform computation...

  15. 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

  16. Novel Breast Imaging and Machine Learning: Predicting Breast Lesion Malignancy at Cone-Beam CT Using Machine Learning Techniques.

    Science.gov (United States)

    Uhlig, Johannes; Uhlig, Annemarie; Kunze, Meike; Beissbarth, Tim; Fischer, Uwe; Lotz, Joachim; Wienbeck, Susanne

    2018-05-24

    The purpose of this study is to evaluate the diagnostic performance of machine learning techniques for malignancy prediction at breast cone-beam CT (CBCT) and to compare them to human readers. Five machine learning techniques, including random forests, back propagation neural networks (BPN), extreme learning machines, support vector machines, and K-nearest neighbors, were used to train diagnostic models on a clinical breast CBCT dataset with internal validation by repeated 10-fold cross-validation. Two independent blinded human readers with profound experience in breast imaging and breast CBCT analyzed the same CBCT dataset. Diagnostic performance was compared using AUC, sensitivity, and specificity. The clinical dataset comprised 35 patients (American College of Radiology density type C and D breasts) with 81 suspicious breast lesions examined with contrast-enhanced breast CBCT. Forty-five lesions were histopathologically proven to be malignant. Among the machine learning techniques, BPNs provided the best diagnostic performance, with AUC of 0.91, sensitivity of 0.85, and specificity of 0.82. The diagnostic performance of the human readers was AUC of 0.84, sensitivity of 0.89, and specificity of 0.72 for reader 1 and AUC of 0.72, sensitivity of 0.71, and specificity of 0.67 for reader 2. AUC was significantly higher for BPN when compared with both reader 1 (p = 0.01) and reader 2 (p Machine learning techniques provide a high and robust diagnostic performance in the prediction of malignancy in breast lesions identified at CBCT. BPNs showed the best diagnostic performance, surpassing human readers in terms of AUC and specificity.

  17. IoT Security Techniques Based on Machine Learning

    OpenAIRE

    Xiao, Liang; Wan, Xiaoyue; Lu, Xiaozhen; Zhang, Yanyong; Wu, Di

    2018-01-01

    Internet of things (IoT) that integrate a variety of devices into networks to provide advanced and intelligent services have to protect user privacy and address attacks such as spoofing attacks, denial of service attacks, jamming and eavesdropping. In this article, we investigate the attack model for IoT systems, and review the IoT security solutions based on machine learning techniques including supervised learning, unsupervised learning and reinforcement learning. We focus on the machine le...

  18. Contemporary machine learning: techniques for practitioners in the physical sciences

    Science.gov (United States)

    Spears, Brian

    2017-10-01

    Machine learning is the science of using computers to find relationships in data without explicitly knowing or programming those relationships in advance. Often without realizing it, we employ machine learning every day as we use our phones or drive our cars. Over the last few years, machine learning has found increasingly broad application in the physical sciences. This most often involves building a model relationship between a dependent, measurable output and an associated set of controllable, but complicated, independent inputs. The methods are applicable both to experimental observations and to databases of simulated output from large, detailed numerical simulations. In this tutorial, we will present an overview of current tools and techniques in machine learning - a jumping-off point for researchers interested in using machine learning to advance their work. We will discuss supervised learning techniques for modeling complicated functions, beginning with familiar regression schemes, then advancing to more sophisticated decision trees, modern neural networks, and deep learning methods. Next, we will cover unsupervised learning and techniques for reducing the dimensionality of input spaces and for clustering data. We'll show example applications from both magnetic and inertial confinement fusion. Along the way, we will describe methods for practitioners to help ensure that their models generalize from their training data to as-yet-unseen test data. We will finally point out some limitations to modern machine learning and speculate on some ways that practitioners from the physical sciences may be particularly suited to help. This work was performed by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

  19. Prediction of drug synergy in cancer using ensemble-based machine learning techniques

    Science.gov (United States)

    Singh, Harpreet; Rana, Prashant Singh; Singh, Urvinder

    2018-04-01

    Drug synergy prediction plays a significant role in the medical field for inhibiting specific cancer agents. It can be developed as a pre-processing tool for therapeutic successes. Examination of different drug-drug interaction can be done by drug synergy score. It needs efficient regression-based machine learning approaches to minimize the prediction errors. Numerous machine learning techniques such as neural networks, support vector machines, random forests, LASSO, Elastic Nets, etc., have been used in the past to realize requirement as mentioned above. However, these techniques individually do not provide significant accuracy in drug synergy score. Therefore, the primary objective of this paper is to design a neuro-fuzzy-based ensembling approach. To achieve this, nine well-known machine learning techniques have been implemented by considering the drug synergy data. Based on the accuracy of each model, four techniques with high accuracy are selected to develop ensemble-based machine learning model. These models are Random forest, Fuzzy Rules Using Genetic Cooperative-Competitive Learning method (GFS.GCCL), Adaptive-Network-Based Fuzzy Inference System (ANFIS) and Dynamic Evolving Neural-Fuzzy Inference System method (DENFIS). Ensembling is achieved by evaluating the biased weighted aggregation (i.e. adding more weights to the model with a higher prediction score) of predicted data by selected models. The proposed and existing machine learning techniques have been evaluated on drug synergy score data. The comparative analysis reveals that the proposed method outperforms others in terms of accuracy, root mean square error and coefficient of correlation.

  20. Predicting Post-Editor Profiles from the Translation Process

    DEFF Research Database (Denmark)

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

    2014-01-01

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

  1. Techniques Of Translating English Figurative Expressions In ‘Colours’ Magazine By Garuda Indonesia Into Indonesian

    Directory of Open Access Journals (Sweden)

    Ni Luh Putu Unix Sumartini

    2016-04-01

    Full Text Available The article is aimed to find out the Techniques of Translating English Figurative Expression in ‘Colours’ Magazine by Garuda Indonesia into Indonesian. There are three problems are discussed in this study, namely (1 types of figurative expressions found in the English version of ‘Colours’ magazine and their translation’s equivalence into Indonesian and (2 kinds of translation techniques applied in translating the English figurative expression into Indonesian, This research belongs to qualitative research and the data used in this study were taken from the ‘Colours’ magazine by Garuda Indonesia. The main theory which is applied in this study is taken from the theory of Molina & Albir (2002 in their book entitled Translation Techniques Revisited; A Dynamic and Functionalist Approach. Another theory applied is taken from the theory of McArthur (1992 in his book entitled The Oxford Companion on The English Language. Other supporting theories which are used to support this study are the theory of Larson (1998 in her book entitled Meaning-Based Translation and some other books considered relevant to the topic. The result showed that there are eleven kinds of English figurative expressions found in the data. They are antithesis, euphemism, hyperbole, idioms, irony, metaphor, metonimy, personification, pleonasm, simile and synecdoche. In translating techniques, the translator applied ten translating techniques, they are; adaptation, borrowing, compensation, description, established equivalent, linguistic comprehension, literal technique, modulation, reduction and transposition. In translating a figurative expression from SL into TL, some of the results showed that an English figurative expression is translated into Indonesian figurative translation but some of them can not maintain its figurativeness in Indonesian, therefore the English figurative expression is translated into Indonesian non-figuratively.

  2. Comparison of Machine Learning Techniques in Inferring Phytoplankton Size Classes

    Directory of Open Access Journals (Sweden)

    Shuibo Hu

    2018-03-01

    Full Text Available The size of phytoplankton not only influences its physiology, metabolic rates and marine food web, but also serves as an indicator of phytoplankton functional roles in ecological and biogeochemical processes. Therefore, some algorithms have been developed to infer the synoptic distribution of phytoplankton cell size, denoted as phytoplankton size classes (PSCs, in surface ocean waters, by the means of remotely sensed variables. This study, using the NASA bio-Optical Marine Algorithm Data set (NOMAD high performance liquid chromatography (HPLC database, and satellite match-ups, aimed to compare the effectiveness of modeling techniques, including partial least square (PLS, artificial neural networks (ANN, support vector machine (SVM and random forests (RF, and feature selection techniques, including genetic algorithm (GA, successive projection algorithm (SPA and recursive feature elimination based on support vector machine (SVM-RFE, for inferring PSCs from remote sensing data. Results showed that: (1 SVM-RFE worked better in selecting sensitive features; (2 RF performed better than PLS, ANN and SVM in calibrating PSCs retrieval models; (3 machine learning techniques produced better performance than the chlorophyll-a based three-component method; (4 sea surface temperature, wind stress, and spectral curvature derived from the remote sensing reflectance at 490, 510, and 555 nm were among the most sensitive features to PSCs; and (5 the combination of SVM-RFE feature selection techniques and random forests regression was recommended for inferring PSCs. This study demonstrated the effectiveness of machine learning techniques in selecting sensitive features and calibrating models for PSCs estimations with remote sensing.

  3. The Temple Translator's Workstation Project

    National Research Council Canada - National Science Library

    Vanni, Michelle; Zajac, Remi

    1996-01-01

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

  4. 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

  5. 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 ...

  6. 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.

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

    International Nuclear Information System (INIS)

    Kim, Jae Yeob; Kim, Eui Sub; Yoo, Jun Beom

    2014-01-01

    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

  8. Compositional translation

    NARCIS (Netherlands)

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

    1994-01-01

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

  9. Shallow water bathymetry mapping using Support Vector Machine (SVM) technique and multispectral imagery

    NARCIS (Netherlands)

    Misra, Ankita; Vojinovic, Zoran; Ramakrishnan, Balaji; Luijendijk, Arjen; Ranasinghe, Roshanka

    2018-01-01

    Satellite imagery along with image processing techniques prove to be efficient tools for bathymetry retrieval as they provide time and cost-effective alternatives to traditional methods of water depth estimation. In this article, a nonlinear machine learning technique of Support Vector Machine (SVM)

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

    Directory of Open Access Journals (Sweden)

    Marius Liviu CÎRȚÎNĂ

    2018-05-01

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

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

    DEFF Research Database (Denmark)

    Flanagan, Marian

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

  12. Quality assurance of a helical tomotherapy machine

    International Nuclear Information System (INIS)

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

    2004-01-01

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

  13. 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.

  14. 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 ...

  15. Adapting Virtual Machine Techniques for Seamless Aspect Support

    NARCIS (Netherlands)

    Bockisch, Christoph; Arnold, Matthew; Dinkelaker, Tom; Mezini, Mira

    2006-01-01

    Current approaches to compiling aspect-oriented programs are inefficient. This inefficiency has negative effects on the productivity of the development process and is especially prohibitive for dynamic aspect deployment. In this work, we present how well-known virtual machine techniques can be used

  16. Machine Learning Techniques for Stellar Light Curve Classification

    Science.gov (United States)

    Hinners, Trisha A.; Tat, Kevin; Thorp, Rachel

    2018-07-01

    We apply machine learning techniques in an attempt to predict and classify stellar properties from noisy and sparse time-series data. We preprocessed over 94 GB of Kepler light curves from the Mikulski Archive for Space Telescopes (MAST) to classify according to 10 distinct physical properties using both representation learning and feature engineering approaches. Studies using machine learning in the field have been primarily done on simulated data, making our study one of the first to use real light-curve data for machine learning approaches. We tuned our data using previous work with simulated data as a template and achieved mixed results between the two approaches. Representation learning using a long short-term memory recurrent neural network produced no successful predictions, but our work with feature engineering was successful for both classification and regression. In particular, we were able to achieve values for stellar density, stellar radius, and effective temperature with low error (∼2%–4%) and good accuracy (∼75%) for classifying the number of transits for a given star. The results show promise for improvement for both approaches upon using larger data sets with a larger minority class. This work has the potential to provide a foundation for future tools and techniques to aid in the analysis of astrophysical data.

  17. Technique for Increasing Accuracy of Positioning System of Machine Tools

    Directory of Open Access Journals (Sweden)

    Sh. Ji

    2014-01-01

    Full Text Available The aim of research is to improve the accuracy of positioning and processing system using a technique for optimization of pressure diagrams of guides in machine tools. The machining quality is directly related to its accuracy, which characterizes an impact degree of various errors of machines. The accuracy of the positioning system is one of the most significant machining characteristics, which allow accuracy evaluation of processed parts.The literature describes that the working area of the machine layout is rather informative to characterize the effect of the positioning system on the macro-geometry of the part surfaces to be processed. To enhance the static accuracy of the studied machine, in principle, two groups of measures are possible. One of them points toward a decrease of the cutting force component, which overturns the slider moments. Another group of measures is related to the changing sizes of the guide facets, which may lead to their profile change.The study was based on mathematical modeling and optimization of the cutting zone coordinates. And we find the formula to determine the surface pressure of the guides. The selected parameters of optimization are vectors of the cutting force and values of slides and guides. Obtained results show that a technique for optimization of coordinates in the cutting zone was necessary to increase a processing accuracy.The research has established that to define the optimal coordinates of the cutting zone we have to change the sizes of slides, value and coordinates of applied forces, reaching the pressure equalization and improving the accuracy of positioning system of machine tools. In different points of the workspace a vector of forces is applied, pressure diagrams are found, which take into account the changes in the parameters of positioning system, and the pressure diagram equalization to provide the most accuracy of machine tools is achieved.

  18. Machine Learning Techniques for Modelling Short Term Land-Use Change

    Directory of Open Access Journals (Sweden)

    Mileva Samardžić-Petrović

    2017-11-01

    Full Text Available The representation of land use change (LUC is often achieved by using data-driven methods that include machine learning (ML techniques. The main objectives of this research study are to implement three ML techniques, Decision Trees (DT, Neural Networks (NN, and Support Vector Machines (SVM for LUC modeling, in order to compare these three ML techniques and to find the appropriate data representation. The ML techniques are applied on the case study of LUC in three municipalities of the City of Belgrade, the Republic of Serbia, using historical geospatial data sets and considering nine land use classes. The ML models were built and assessed using two different time intervals. The information gain ranking technique and the recursive attribute elimination procedure were implemented to find the most informative attributes that were related to LUC in the study area. The results indicate that all three ML techniques can be used effectively for short-term forecasting of LUC, but the SVM achieved the highest agreement of predicted changes.

  19. Machine learning and radiology.

    Science.gov (United States)

    Wang, Shijun; Summers, Ronald M

    2012-07-01

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

  20. On the Systematicity of Human Translation Processes

    DEFF Research Database (Denmark)

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

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

  1. An Effective Performance Analysis of Machine Learning Techniques for Cardiovascular Disease

    Directory of Open Access Journals (Sweden)

    Vinitha DOMINIC

    2015-03-01

    Full Text Available Machine learning techniques will help in deriving hidden knowledge from clinical data which can be of great benefit for society, such as reduce the number of clinical trials required for precise diagnosis of a disease of a person etc. Various areas of study are available in healthcare domain like cancer, diabetes, drugs etc. This paper focuses on heart disease dataset and how machine learning techniques can help in understanding the level of risk associated with heart diseases. Initially, data is preprocessed then analysis is done in two stages, in first stage feature selection techniques are applied on 13 commonly used attributes and in second stage feature selection techniques are applied on 75 attributes which are related to anatomic structure of the heart like blood vessels of the heart, arteries etc. Finally, validation of the reduced set of features using an exhaustive list of classifiers is done.In parallel study of the anatomy of the heart is done using the identified features and the characteristics of each class is understood. It is observed that these reduced set of features are anatomically relevant. Thus, it can be concluded that, applying machine learning techniques on clinical data is beneficial and necessary.

  2. Application of machine learning techniques to lepton energy reconstruction in water Cherenkov detectors

    Science.gov (United States)

    Drakopoulou, E.; Cowan, G. A.; Needham, M. D.; Playfer, S.; Taani, M.

    2018-04-01

    The application of machine learning techniques to the reconstruction of lepton energies in water Cherenkov detectors is discussed and illustrated for TITUS, a proposed intermediate detector for the Hyper-Kamiokande experiment. It is found that applying these techniques leads to an improvement of more than 50% in the energy resolution for all lepton energies compared to an approach based upon lookup tables. Machine learning techniques can be easily applied to different detector configurations and the results are comparable to likelihood-function based techniques that are currently used.

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

    Science.gov (United States)

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

    1979-01-01

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

  4. 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.

  5. 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...

  6. 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.

  7. Electric-Discharge Machining Techniques for Evaluating Tritium Effects on Materials

    International Nuclear Information System (INIS)

    Morgan, M.J.

    2003-01-01

    In this investigation, new ways to evaluate the long-term effects of tritium on the structural properties of components were developed. Electric-discharge machining (EDM) techniques for cutting tensile and fracture toughness samples from tritium exposed regions of returned reservoirs were demonstrated. An existing electric discharge machine was used to cut sub-size tensile and fracture toughness samples from the inside surfaces of reservoir mockups. Tensile properties from the EDM tensile samples were similar to those measured using full-size samples cut from similar stock. Although the existing equipment could not be used for machining tritium-exposed hardware, off-the shelf EDM units are available that could. With the right equipment and the required radiological controls in place, similar machining and testing techniques could be used to directly measure the effects of tritium on the properties of material cut from reservoir returns. Stress-strain properties from tritium-exposed reservoirs would improve finite element modeling of reservoir performance because the data would be representative of the true state of the reservoir material in the field. Tensile data from samples cut directly from reservoirs would also complement existing shelf storage and burst test data of the Life Storage Program and help answer questions about a specific reservoir's processing history and properties

  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

    network as well as the multi-variant linear regression. It is found that it is possible to estimate the longevity of flexibility with machine learning. The linear regression algorithm is, on average, able to estimate the longevity with a 15% error. However, there was a significant improvement with the ANN...... approach to investigating the longevity of aggregated response of a virtual power plant using historic bidding and aggregated behaviour with machine learning techniques. The two supervised machine learning techniques investigated and compared in this paper are, multivariate linear regression and single...... algorithm achieving, on average, a 5.3% error. This is lowered 2.4% when learning for the same virtual power plant. With this information it would be possible to accurately offer residential VPP flexibility for market operations to safely avoid causing further imbalances and financial penalties....

  9. 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

  10. Why Translation Is Difficult

    DEFF Research Database (Denmark)

    Carl, Michael; Schaeffer, Moritz Jonas

    2017-01-01

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

  11. Performance Evaluation of Eleven-Phase Induction Machine with Different PWM Techniques

    Directory of Open Access Journals (Sweden)

    M.I. Masoud

    2015-06-01

    Full Text Available Multiphase induction machines are used extensively in low and medium voltage (MV drives. In MV drives, power switches have a limitation associated with switching frequency. This paper is a comparative study of the eleven-phase induction machine’s performance when used as a prototype and fed sinusoidal pulse-width-modulation (SPWM with a low switching frequency, selective harmonic elimination (SHE, and single pulse modulation (SPM techniques. The comparison depends on voltage/frequency controls for the same phase of voltage applied on the machine terminals for all previous techniques. The comparative study covers torque ripple, stator and harmonic currents, and motor efficiency.

  12. 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.

  13. 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

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

    International Nuclear Information System (INIS)

    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

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

    OpenAIRE

    Marziyeh Taleghani; Ehsan Pazouki

    2018-01-01

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

  17. Computer-aided translation tools

    DEFF Research Database (Denmark)

    Christensen, Tina Paulsen; Schjoldager, Anne

    2016-01-01

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

  18. Machine safety: proper safeguarding techniques.

    Science.gov (United States)

    Martin, K J

    1992-06-01

    1. OSHA mandates certain safeguarding of machinery to prevent accidents and protect machine operators. OSHA specifies moving parts that must be guarded and sets criteria for the guards. 2. A 1989 OSHA standard for lockout/tagout requires locking the energy source during maintenance, periodically inspecting for power transmission, and training maintenance workers. 3. In an amputation emergency, first aid for cardiopulmonary resuscitation, shock, and bleeding are the first considerations. The amputated part should be wrapped in moist gauze, placed in a sealed plastic bag, and placed in a container of 50% water and 50% ice for transport. 4. The role of the occupational health nurse in machine safety is to conduct worksite analyses to identify proper safeguarding and to communicate deficiencies to appropriate personnel; to train workers in safe work practices and observe compliance in the use of machine guards; to provide care to workers injured by machines; and to reinforce safe work practices among machine operators.

  19. Percussive drilling application of translational motion permanent magnet machine

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Shujun

    2012-07-01

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

  20. A Comprehensive Review and meta-analysis on Applications of Machine Learning Techniques in Intrusion Detection

    Directory of Open Access Journals (Sweden)

    Manojit Chattopadhyay

    2018-05-01

    Full Text Available Securing a machine from various cyber-attacks has been of serious concern for researchers, statutory bodies such as governments, business organizations and users in both wired and wireless media. However, during the last decade, the amount of data handling by any device, particularly servers, has increased exponentially and hence the security of these devices has become a matter of utmost concern. This paper attempts to examine the challenges in the application of machine learning techniques to intrusion detection. We review different inherent issues in defining and applying the machine learning techniques to intrusion detection. We also attempt to identify the best technological solution for changing usage pattern by comparing different machine learning techniques on different datasets and summarizing their performance using various performance metrics. This paper highlights the research challenges and future trends of intrusion detection in dynamic scenarios of intrusion detection problems in diverse network technologies.

  1. Exploring machine-learning-based control plane intrusion detection techniques in software defined optical networks

    Science.gov (United States)

    Zhang, Huibin; Wang, Yuqiao; Chen, Haoran; Zhao, Yongli; Zhang, Jie

    2017-12-01

    In software defined optical networks (SDON), the centralized control plane may encounter numerous intrusion threatens which compromise the security level of provisioned services. In this paper, the issue of control plane security is studied and two machine-learning-based control plane intrusion detection techniques are proposed for SDON with properly selected features such as bandwidth, route length, etc. We validate the feasibility and efficiency of the proposed techniques by simulations. Results show an accuracy of 83% for intrusion detection can be achieved with the proposed machine-learning-based control plane intrusion detection techniques.

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

    OpenAIRE

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

    2015-01-01

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

  3. 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

    2017-09-01

    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.

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

    Science.gov (United States)

    Bausch, Johannes; Piddock, Stephen

    2017-11-01

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

  5. 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.

  6. Towards large-scale FAME-based bacterial species identification using machine learning techniques.

    Science.gov (United States)

    Slabbinck, Bram; De Baets, Bernard; Dawyndt, Peter; De Vos, Paul

    2009-05-01

    In the last decade, bacterial taxonomy witnessed a huge expansion. The swift pace of bacterial species (re-)definitions has a serious impact on the accuracy and completeness of first-line identification methods. Consequently, back-end identification libraries need to be synchronized with the List of Prokaryotic names with Standing in Nomenclature. In this study, we focus on bacterial fatty acid methyl ester (FAME) profiling as a broadly used first-line identification method. From the BAME@LMG database, we have selected FAME profiles of individual strains belonging to the genera Bacillus, Paenibacillus and Pseudomonas. Only those profiles resulting from standard growth conditions have been retained. The corresponding data set covers 74, 44 and 95 validly published bacterial species, respectively, represented by 961, 378 and 1673 standard FAME profiles. Through the application of machine learning techniques in a supervised strategy, different computational models have been built for genus and species identification. Three techniques have been considered: artificial neural networks, random forests and support vector machines. Nearly perfect identification has been achieved at genus level. Notwithstanding the known limited discriminative power of FAME analysis for species identification, the computational models have resulted in good species identification results for the three genera. For Bacillus, Paenibacillus and Pseudomonas, random forests have resulted in sensitivity values, respectively, 0.847, 0.901 and 0.708. The random forests models outperform those of the other machine learning techniques. Moreover, our machine learning approach also outperformed the Sherlock MIS (MIDI Inc., Newark, DE, USA). These results show that machine learning proves very useful for FAME-based bacterial species identification. Besides good bacterial identification at species level, speed and ease of taxonomic synchronization are major advantages of this computational species

  7. 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.

  8. Development of an evaluation technique for human-machine interface

    International Nuclear Information System (INIS)

    Min, Dae Hwan; Koo, Sang Hui; Ahn, Won Yeong; Ryu, Yeong Shin

    1997-07-01

    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

  9. MULTIFUNCTION OF INTERNET IN TRANSLATION

    Directory of Open Access Journals (Sweden)

    Bayu Budiharjo

    2017-04-01

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

  10. Sentiment Analysis in Geo Social Streams by using Machine Learning Techniques

    OpenAIRE

    Twanabasu, Bikesh

    2018-01-01

    Treball de Final de Màster Universitari Erasmus Mundus en Tecnologia Geoespacial (Pla de 2013). Codi: SIW013. Curs acadèmic 2017-2018 Massive amounts of sentiment rich data are generated on social media in the form of Tweets, status updates, blog post, reviews, etc. Different people and organizations are using these user generated content for decision making. Symbolic techniques or Knowledge base approaches and Machine learning techniques are two main techniques used for analysis sentiment...

  11. 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.

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

    Science.gov (United States)

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

    2017-10-01

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

  13. Electric machines

    CERN Document Server

    Gross, Charles A

    2006-01-01

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

  14. Classifying Structures in the ISM with Machine Learning Techniques

    Science.gov (United States)

    Beaumont, Christopher; Goodman, A. A.; Williams, J. P.

    2011-01-01

    The processes which govern molecular cloud evolution and star formation often sculpt structures in the ISM: filaments, pillars, shells, outflows, etc. Because of their morphological complexity, these objects are often identified manually. Manual classification has several disadvantages; the process is subjective, not easily reproducible, and does not scale well to handle increasingly large datasets. We have explored to what extent machine learning algorithms can be trained to autonomously identify specific morphological features in molecular cloud datasets. We show that the Support Vector Machine algorithm can successfully locate filaments and outflows blended with other emission structures. When the objects of interest are morphologically distinct from the surrounding emission, this autonomous classification achieves >90% accuracy. We have developed a set of IDL-based tools to apply this technique to other datasets.

  15. Driver drowsiness detection using behavioral measures and machine learning techniques: A review of state-of-art techniques

    CSIR Research Space (South Africa)

    Ngxande, Mkhuseli

    2017-11-01

    Full Text Available This paper presents a literature review of driver drowsiness detection based on behavioral measures using machine learning techniques. Faces contain information that can be used to interpret levels of drowsiness. There are many facial features...

  16. 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.

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

    OpenAIRE

    李, 芬慧; 由井薗, 隆也

    2010-01-01

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

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

    DEFF Research Database (Denmark)

    Carl, Michael; Aizawa, Akiko; Yamada, Masaru

    2016-01-01

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

  19. Evolution of Replication Machines

    Science.gov (United States)

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

    2016-01-01

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

  20. Using Machine Learning Techniques in the Analysis of Oceanographic Data

    Science.gov (United States)

    Falcinelli, K. E.; Abuomar, S.

    2017-12-01

    Acoustic Doppler Current Profilers (ADCPs) are oceanographic tools capable of collecting large amounts of current profile data. Using unsupervised machine learning techniques such as principal component analysis, fuzzy c-means clustering, and self-organizing maps, patterns and trends in an ADCP dataset are found. Cluster validity algorithms such as visual assessment of cluster tendency and clustering index are used to determine the optimal number of clusters in the ADCP dataset. These techniques prove to be useful in analysis of ADCP data and demonstrate potential for future use in other oceanographic applications.

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

    OpenAIRE

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

    2014-01-01

    Objectives 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.Methods 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...

  2. 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.

  3. Application of Machine Learning Techniques in Aquaculture

    OpenAIRE

    Rahman, Akhlaqur; Tasnim, Sumaira

    2014-01-01

    In this paper we present applications of different machine learning algorithms in aquaculture. Machine learning algorithms learn models from historical data. In aquaculture historical data are obtained from farm practices, yields, and environmental data sources. Associations between these different variables can be obtained by applying machine learning algorithms to historical data. In this paper we present applications of different machine learning algorithms in aquaculture applications.

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

    Directory of Open Access Journals (Sweden)

    Rila Hilma

    2011-05-01

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

  5. 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 windowing approach over historical values to generate a prediction for the current value. We evaluate a number of Machine Learning techniques as regressors including Support Vector Regression, Random Forests, Stochastic Gradient Decent Regression, Linear...

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

    Directory of Open Access Journals (Sweden)

    Marziyeh Taleghani

    2018-03-01

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

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

    DEFF Research Database (Denmark)

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

    2014-01-01

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

  8. Predicting transmission of structure-borne sound power from machines by including terminal cross-coupling

    DEFF Research Database (Denmark)

    Ohlrich, Mogens

    2011-01-01

    of translational terminals in a global plane. This paired or bi-coupled power transmission represents the simplest case of cross-coupling. The procedure and quality of the predicted transmission using this improved technique is demonstrated experimentally for an electrical motor unit with an integrated radial fan......Structure-borne sound generated by audible vibration of machines in vehicles, equipment and house-hold appliances is often a major cause of noise. Such vibration of complex machines is mostly determined and quantified by measurements. It has been found that characterization of the vibratory source...

  9. Taxi-Out Time Prediction for Departures at Charlotte Airport Using Machine Learning Techniques

    Science.gov (United States)

    Lee, Hanbong; Malik, Waqar; Jung, Yoon C.

    2016-01-01

    Predicting the taxi-out times of departures accurately is important for improving airport efficiency and takeoff time predictability. In this paper, we attempt to apply machine learning techniques to actual traffic data at Charlotte Douglas International Airport for taxi-out time prediction. To find the key factors affecting aircraft taxi times, surface surveillance data is first analyzed. From this data analysis, several variables, including terminal concourse, spot, runway, departure fix and weight class, are selected for taxi time prediction. Then, various machine learning methods such as linear regression, support vector machines, k-nearest neighbors, random forest, and neural networks model are applied to actual flight data. Different traffic flow and weather conditions at Charlotte airport are also taken into account for more accurate prediction. The taxi-out time prediction results show that linear regression and random forest techniques can provide the most accurate prediction in terms of root-mean-square errors. We also discuss the operational complexity and uncertainties that make it difficult to predict the taxi times accurately.

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

    Science.gov (United States)

    Zhao, Xin; Ren, Fuji; Kuroiwa, Shingo

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

  11. 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...

  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. 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

  14. An Overall Perspective of Machine Translation with Its Shortcomings

    Science.gov (United States)

    Akbari, Alireza

    2014-01-01

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

  15. Prediction of lung cancer patient survival via supervised machine learning classification techniques.

    Science.gov (United States)

    Lynch, Chip M; Abdollahi, Behnaz; Fuqua, Joshua D; de Carlo, Alexandra R; Bartholomai, James A; Balgemann, Rayeanne N; van Berkel, Victor H; Frieboes, Hermann B

    2017-12-01

    Outcomes for cancer patients have been previously estimated by applying various machine learning techniques to large datasets such as the Surveillance, Epidemiology, and End Results (SEER) program database. In particular for lung cancer, it is not well understood which types of techniques would yield more predictive information, and which data attributes should be used in order to determine this information. In this study, a number of supervised learning techniques is applied to the SEER database to classify lung cancer patients in terms of survival, including linear regression, Decision Trees, Gradient Boosting Machines (GBM), Support Vector Machines (SVM), and a custom ensemble. Key data attributes in applying these methods include tumor grade, tumor size, gender, age, stage, and number of primaries, with the goal to enable comparison of predictive power between the various methods The prediction is treated like a continuous target, rather than a classification into categories, as a first step towards improving survival prediction. The results show that the predicted values agree with actual values for low to moderate survival times, which constitute the majority of the data. The best performing technique was the custom ensemble with a Root Mean Square Error (RMSE) value of 15.05. The most influential model within the custom ensemble was GBM, while Decision Trees may be inapplicable as it had too few discrete outputs. The results further show that among the five individual models generated, the most accurate was GBM with an RMSE value of 15.32. Although SVM underperformed with an RMSE value of 15.82, statistical analysis singles the SVM as the only model that generated a distinctive output. The results of the models are consistent with a classical Cox proportional hazards model used as a reference technique. We conclude that application of these supervised learning techniques to lung cancer data in the SEER database may be of use to estimate patient survival time

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

    Directory of Open Access Journals (Sweden)

    Matthew O'keefe

    1995-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Wstawska Iwona

    2016-12-01

    Full Text Available 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.

  18. Machine-learning techniques applied to antibacterial drug discovery.

    Science.gov (United States)

    Durrant, Jacob D; Amaro, Rommie E

    2015-01-01

    The emergence of drug-resistant bacteria threatens to revert humanity back to the preantibiotic era. Even now, multidrug-resistant bacterial infections annually result in millions of hospital days, billions in healthcare costs, and, most importantly, tens of thousands of lives lost. As many pharmaceutical companies have abandoned antibiotic development in search of more lucrative therapeutics, academic researchers are uniquely positioned to fill the pipeline. Traditional high-throughput screens and lead-optimization efforts are expensive and labor intensive. Computer-aided drug-discovery techniques, which are cheaper and faster, can accelerate the identification of novel antibiotics, leading to improved hit rates and faster transitions to preclinical and clinical testing. The current review describes two machine-learning techniques, neural networks and decision trees, that have been used to identify experimentally validated antibiotics. We conclude by describing the future directions of this exciting field. © 2015 John Wiley & Sons A/S.

  19. Solar photovoltaic power forecasting using optimized modified extreme learning machine technique

    Directory of Open Access Journals (Sweden)

    Manoja Kumar Behera

    2018-06-01

    Full Text Available Prediction of photovoltaic power is a significant research area using different forecasting techniques mitigating the effects of the uncertainty of the photovoltaic generation. Increasingly high penetration level of photovoltaic (PV generation arises in smart grid and microgrid concept. Solar source is irregular in nature as a result PV power is intermittent and is highly dependent on irradiance, temperature level and other atmospheric parameters. Large scale photovoltaic generation and penetration to the conventional power system introduces the significant challenges to microgrid a smart grid energy management. It is very critical to do exact forecasting of solar power/irradiance in order to secure the economic operation of the microgrid and smart grid. In this paper an extreme learning machine (ELM technique is used for PV power forecasting of a real time model whose location is given in the Table 1. Here the model is associated with the incremental conductance (IC maximum power point tracking (MPPT technique that is based on proportional integral (PI controller which is simulated in MATLAB/SIMULINK software. To train single layer feed-forward network (SLFN, ELM algorithm is implemented whose weights are updated by different particle swarm optimization (PSO techniques and their performance are compared with existing models like back propagation (BP forecasting model. Keywords: PV array, Extreme learning machine, Maximum power point tracking, Particle swarm optimization, Craziness particle swarm optimization, Accelerate particle swarm optimization, Single layer feed-forward network

  20. 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...

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

    Science.gov (United States)

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

    2015-11-01

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

  2. A technique to identify some typical radio frequency interference using support vector machine

    Science.gov (United States)

    Wang, Yuanchao; Li, Mingtao; Li, Dawei; Zheng, Jianhua

    2017-07-01

    In this paper, we present a technique to automatically identify some typical radio frequency interference from pulsar surveys using support vector machine. The technique has been tested by candidates. In these experiments, to get features of SVM, we use principal component analysis for mosaic plots and its classification accuracy is 96.9%; while we use mathematical morphology operation for smog plots and horizontal stripes plots and its classification accuracy is 86%. The technique is simple, high accurate and useful.

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

    Science.gov (United States)

    Du, Yi; Zou, Chunhua; Liu, Xianxing

    2015-01-01

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

  4. An experimental result of estimating an application volume by machine learning techniques.

    Science.gov (United States)

    Hasegawa, Tatsuhito; Koshino, Makoto; Kimura, Haruhiko

    2015-01-01

    In this study, we improved the usability of smartphones by automating a user's operations. We developed an intelligent system using machine learning techniques that periodically detects a user's context on a smartphone. We selected the Android operating system because it has the largest market share and highest flexibility of its development environment. In this paper, we describe an application that automatically adjusts application volume. Adjusting the volume can be easily forgotten because users need to push the volume buttons to alter the volume depending on the given situation. Therefore, we developed an application that automatically adjusts the volume based on learned user settings. Application volume can be set differently from ringtone volume on Android devices, and these volume settings are associated with each specific application including games. Our application records a user's location, the volume setting, the foreground application name and other such attributes as learning data, thereby estimating whether the volume should be adjusted using machine learning techniques via Weka.

  5. 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.

  6. 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.

  7. New sensor and non-contact geometrical survey for the vibrating wire technique

    Energy Technology Data Exchange (ETDEWEB)

    Geraldes, Renan [Brazilian Synchrotron Light Laboratory (LNLS), Campinas, SP (Brazil); Junqueira Leão, Rodrigo, E-mail: rodrigo.leao@lnls.br [Brazilian Synchrotron Light Laboratory (LNLS), Campinas, SP (Brazil); Cernicchiaro, Geraldo [Brazilian Center for Research in Physics (CBPF), Rio de Janeiro, RJ (Brazil); Terenzi Neuenschwander, Regis; Citadini, James Francisco; Droher Rodrigues, Antônio Ricardo [Brazilian Synchrotron Light Laboratory (LNLS), Campinas, SP (Brazil)

    2016-03-01

    The tolerances for the alignment of the magnets in the girders of the next machine of the Brazilian Synchrotron Light Laboratory (LNLS), Sirius, are as small as 40 µm for translations and 0.2 mrad for rotations. Therefore, a novel approach to the well-known vibrating wire technique has been developed and tested for the precise fiducialization of magnets. The alignment bench consists of four commercial linear stages, a stretched wire, a commercial lock-in amplifier working with phase-locked loop (PLL), a coordinate measuring machine (CMM) and a vibration sensor for the wire. This novel sensor has been designed for a larger linear region of operation. For the mechanical metrology step of the fiducialization of quadrupoles an innovative technique, using the vision system of the CMM, is presented. While the work with pitch and yaw orientations is still ongoing with promising partial results, the system already presents an uncertainty level below 10 µm for translational alignment.

  8. On Collocations and Their Interaction with Parsing and Translation

    Directory of Open Access Journals (Sweden)

    Violeta Seretan

    2013-10-01

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

  9. Spiritualist Writing Machines: Telegraphy, Typtology, Typewriting

    Directory of Open Access Journals (Sweden)

    Anthony Enns

    2015-09-01

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

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

    Directory of Open Access Journals (Sweden)

    Bety Mawarni

    2017-12-01

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

  11. Wind Power Ramp Events Prediction with Hybrid Machine Learning Regression Techniques and Reanalysis Data

    Directory of Open Access Journals (Sweden)

    Laura Cornejo-Bueno

    2017-11-01

    Full Text Available Wind Power Ramp Events (WPREs are large fluctuations of wind power in a short time interval, which lead to strong, undesirable variations in the electric power produced by a wind farm. Its accurate prediction is important in the effort of efficiently integrating wind energy in the electric system, without affecting considerably its stability, robustness and resilience. In this paper, we tackle the problem of predicting WPREs by applying Machine Learning (ML regression techniques. Our approach consists of using variables from atmospheric reanalysis data as predictive inputs for the learning machine, which opens the possibility of hybridizing numerical-physical weather models with ML techniques for WPREs prediction in real systems. Specifically, we have explored the feasibility of a number of state-of-the-art ML regression techniques, such as support vector regression, artificial neural networks (multi-layer perceptrons and extreme learning machines and Gaussian processes to solve the problem. Furthermore, the ERA-Interim reanalysis from the European Center for Medium-Range Weather Forecasts is the one used in this paper because of its accuracy and high resolution (in both spatial and temporal domains. Aiming at validating the feasibility of our predicting approach, we have carried out an extensive experimental work using real data from three wind farms in Spain, discussing the performance of the different ML regression tested in this wind power ramp event prediction problem.

  12. Approximate multi-state reliability expressions using a new machine learning technique

    International Nuclear Information System (INIS)

    Rocco S, Claudio M.; Muselli, Marco

    2005-01-01

    The machine-learning-based methodology, previously proposed by the authors for approximating binary reliability expressions, is now extended to develop a new algorithm, based on the procedure of Hamming Clustering, which is capable to deal with multi-state systems and any success criterion. The proposed technique is presented in details and verified on literature cases: experiment results show that the new algorithm yields excellent predictions

  13. Clinical translation of autologous cell-based tissue engineering techniques as Class III therapeutics in China: Taking cartilage tissue engineering as an example

    Directory of Open Access Journals (Sweden)

    Wei Zhang

    2014-04-01

    Full Text Available Autologous cell-based tissue engineering (TE techniques have been clinically approved for approximately 4 years in China, since the first cartilage TE technique was approved for clinical use by the Zhejiang Health Bureau. TE techniques offer a promising alternative to traditional transplantation surgery, and are different from those for transplanted tissues (biologics or pharmaceutical, the clinical translational procedures are unique and multitasked, and the requirements may differ from those of the target tissues. Thus, the translational procedure is still unfamiliar to most researchers and needs further improvement. This perspectives paper describes the key guidelines and regulations involved in the current translational process, and shares our translational experiences in cartilage TE to provide an example of autologous cell-based TE translation in China. Finally, we discuss the scientific and social challenges and provide some suggestions for future improvements.

  14. 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.

  15. CRDM motion analysis using machine learning technique

    International Nuclear Information System (INIS)

    Nishimura, Takuya; Nakayama, Hiroyuki; Saitoh, Mayumi; Yaguchi, Seiji

    2017-01-01

    Magnetic jack type Control Rod Drive Mechanism (CRDM) for pressurized water reactor (PWR) plant operates control rods in response to electrical signals from a reactor control system. CRDM operability is evaluated by quantifying armature's response of closed/opened time which means interval time between coil energizing/de-energizing points and armature closed/opened points. MHI has already developed an automatic CRDM motion analysis and applied it to actual plants so far. However, CRDM operational data has wide variation depending on their characteristics such as plant condition, plant, etc. In the existing motion analysis, there is an issue of analysis accuracy for applying a single analysis technique to all plant conditions, plants, etc. In this study, MHI investigated motion analysis using machine learning (Random Forests) which is flexibly accommodated to CRDM operational data with wide variation, and is improved analysis accuracy. (author)

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

    Science.gov (United States)

    Loveland, Thomas

    2012-01-01

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

  17. 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.

  18. PC-assisted translation of photogrammetric papers

    Science.gov (United States)

    Güthner, Karlheinz; Peipe, Jürgen

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

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

    Science.gov (United States)

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

    2015-01-01

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

  20. Machine Learning or Information Retrieval Techniques for Bug Triaging: Which is better?

    Directory of Open Access Journals (Sweden)

    Anjali Goyal

    2017-07-01

    Full Text Available Bugs are the inevitable part of a software system. Nowadays, large software development projects even release beta versions of their products to gather bug reports from users. The collected bug reports are then worked upon by various developers in order to resolve the defects and make the final software product more reliable. The high frequency of incoming bugs makes the bug handling a difficult and time consuming task. Bug assignment is an integral part of bug triaging that aims at the process of assigning a suitable developer for the reported bug who corrects the source code in order to resolve the bug. There are various semi and fully automated techniques to ease the task of bug assignment. This paper presents the current state of the art of various techniques used for bug report assignment. Through exhaustive research, the authors have observed that machine learning and information retrieval based bug assignment approaches are most popular in literature. A deeper investigation has shown that the trend of techniques is taking a shift from machine learning based approaches towards information retrieval based approaches. Therefore, the focus of this work is to find the reason behind the observed drift and thus a comparative analysis is conducted on the bug reports of the Mozilla, Eclipse, Gnome and Open Office projects in the Bugzilla repository. The results of the study show that the information retrieval based technique yields better efficiency in recommending the developers for bug reports.

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

    NARCIS (Netherlands)

    Khalilov, M.; Sima'an, K.

    2011-01-01

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

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

    Science.gov (United States)

    Van Horn, Royal

    2004-01-01

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

  3. 3D CT cerebral angiography technique using a 320-detector machine with a time–density curve and low contrast medium volume: Comparison with fixed time delay technique

    International Nuclear Information System (INIS)

    Das, K.; Biswas, S.; Roughley, S.; Bhojak, M.; Niven, S.

    2014-01-01

    Aim: To describe a cerebral computed tomography angiography (CTA) technique using a 320-detector CT machine and a small contrast medium volume (35 ml, 15 ml for test bolus). Also, to compare the quality of these images with that of the images acquired using a larger contrast medium volume (90 or 120 ml) and a fixed time delay (FTD) of 18 s using a 16-detector CT machine. Materials and methods: Cerebral CTA images were acquired using a 320-detector machine by synchronizing the scanning time with the time of peak enhancement as determined from the time–density curve (TDC) using a test bolus dose. The quality of CTA images acquired using this technique was compared with that obtained using a FTD of 18 s (by 16-detector CT), retrospectively. Average densities in four different intracranial arteries, overall opacification of arteries, and the degree of venous contamination were graded and compared. Results: Thirty-eight patients were scanned using the TDC technique and 40 patients using the FTD technique. The arterial densities achieved by the TDC technique were higher (significant for supraclinoid and basilar arteries, p < 0.05). The proportion of images deemed as having “good” arterial opacification was 95% for TDC and 90% for FTD. The degree of venous contamination was significantly higher in images produced by the FTD technique (p < 0.001%). Conclusion: Good diagnostic quality CTA images with significant reduction of venous contamination can be achieved with a low contrast medium dose using a 320-detector machine by coupling the time of data acquisition with the time of peak enhancement

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

    OpenAIRE

    Akinyelu, Andronicus A.; Adewumi, Aderemi O.

    2013-01-01

    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 learnin...

  5. Big data - modelling of midges in Europa using machine learning techniques and satellite imagery

    DEFF Research Database (Denmark)

    Cuellar, Ana Carolina; Kjær, Lene Jung; Skovgaard, Henrik

    2017-01-01

    coordinates of each trap, start and end dates of trapping. We used 120 environmental predictor variables together with Random Forest machine learning algorithms to predict the overall species distribution (probability of occurrence) and monthly abundance in Europe. We generated maps for every month...... and the Obsoletus group, although abundance was generally higher for a longer period of time for C. imicula than for the Obsoletus group. Using machine learning techniques, we were able to model the spatial distribution in Europe for C. imicola and the Obsoletus group in terms of abundance and suitability...

  6. Using support vector machines in the multivariate state estimation technique

    International Nuclear Information System (INIS)

    Zavaljevski, N.; Gross, K.C.

    1999-01-01

    One approach to validate nuclear power plant (NPP) signals makes use of pattern recognition techniques. This approach often assumes that there is a set of signal prototypes that are continuously compared with the actual sensor signals. These signal prototypes are often computed based on empirical models with little or no knowledge about physical processes. A common problem of all data-based models is their limited ability to make predictions on the basis of available training data. Another problem is related to suboptimal training algorithms. Both of these potential shortcomings with conventional approaches to signal validation and sensor operability validation are successfully resolved by adopting a recently proposed learning paradigm called the support vector machine (SVM). The work presented here is a novel application of SVM for data-based modeling of system state variables in an NPP, integrated with a nonlinear, nonparametric technique called the multivariate state estimation technique (MSET), an algorithm developed at Argonne National Laboratory for a wide range of nuclear plant applications

  7. 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.

  8. A framework for detection of malicious software in Android handheld systems using machine learning techniques

    OpenAIRE

    Torregrosa García, Blas

    2015-01-01

    The present study aims at designing and developing new approaches to detect malicious applications in Android-based devices. More precisely, MaLDroide (Machine Learning-based Detector for Android malware), a framework for detection of Android malware based on machine learning techniques, is introduced here. It is devised to identify malicious applications. Este trabajo tiene como objetivo el diseño y el desarrollo de nuevas formas de detección de aplicaciones maliciosas en los dispositivos...

  9. Advanced Machine learning Algorithm Application for Rotating Machine Health Monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Kanemoto, Shigeru; Watanabe, Masaya [The University of Aizu, Aizuwakamatsu (Japan); Yusa, Noritaka [Tohoku University, Sendai (Japan)

    2014-08-15

    The present paper tries to evaluate the applicability of conventional sound analysis techniques and modern machine learning algorithms to rotating machine health monitoring. These techniques include support vector machine, deep leaning neural network, etc. The inner ring defect and misalignment anomaly sound data measured by a rotating machine mockup test facility are used to verify the above various kinds of algorithms. Although we cannot find remarkable difference of anomaly discrimination performance, some methods give us the very interesting eigen patterns corresponding to normal and abnormal states. These results will be useful for future more sensitive and robust anomaly monitoring technology.

  10. Advanced Machine learning Algorithm Application for Rotating Machine Health Monitoring

    International Nuclear Information System (INIS)

    Kanemoto, Shigeru; Watanabe, Masaya; Yusa, Noritaka

    2014-01-01

    The present paper tries to evaluate the applicability of conventional sound analysis techniques and modern machine learning algorithms to rotating machine health monitoring. These techniques include support vector machine, deep leaning neural network, etc. The inner ring defect and misalignment anomaly sound data measured by a rotating machine mockup test facility are used to verify the above various kinds of algorithms. Although we cannot find remarkable difference of anomaly discrimination performance, some methods give us the very interesting eigen patterns corresponding to normal and abnormal states. These results will be useful for future more sensitive and robust anomaly monitoring technology

  11. ROBUSTNESS OF A FACE-RECOGNITION TECHNIQUE BASED ON SUPPORT VECTOR MACHINES

    OpenAIRE

    Prashanth Harshangi; Koshy George

    2010-01-01

    The ever-increasing requirements of security concerns have placed a greater demand for face recognition surveillance systems. However, most current face recognition techniques are not quite robust with respect to factors such as variable illumination, facial expression and detail, and noise in images. In this paper, we demonstrate that face recognition using support vector machines are sufficiently robust to different kinds of noise, does not require image pre-processing, and can be used with...

  12. 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.

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

    Directory of Open Access Journals (Sweden)

    Daniel Torregrosa

    2014-09-01

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

  14. 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.

  15. Neural Machine Translation with Recurrent Attention Modeling

    OpenAIRE

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

    2016-01-01

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

  16. Some Problems in German to English Machine Translation

    Science.gov (United States)

    1974-12-01

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

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

    International Nuclear Information System (INIS)

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

    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 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

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

    Directory of Open Access Journals (Sweden)

    M Bilal Shaikh

    2017-06-01

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

  19. Comparison of machine learning techniques to predict all-cause mortality using fitness data: the Henry ford exercIse testing (FIT) project.

    Science.gov (United States)

    Sakr, Sherif; Elshawi, Radwa; Ahmed, Amjad M; Qureshi, Waqas T; Brawner, Clinton A; Keteyian, Steven J; Blaha, Michael J; Al-Mallah, Mouaz H

    2017-12-19

    Prior studies have demonstrated that cardiorespiratory fitness (CRF) is a strong marker of cardiovascular health. Machine learning (ML) can enhance the prediction of outcomes through classification techniques that classify the data into predetermined categories. The aim of this study is to present an evaluation and comparison of how machine learning techniques can be applied on medical records of cardiorespiratory fitness and how the various techniques differ in terms of capabilities of predicting medical outcomes (e.g. mortality). We use data of 34,212 patients free of known coronary artery disease or heart failure who underwent clinician-referred exercise treadmill stress testing at Henry Ford Health Systems Between 1991 and 2009 and had a complete 10-year follow-up. Seven machine learning classification techniques were evaluated: Decision Tree (DT), Support Vector Machine (SVM), Artificial Neural Networks (ANN), Naïve Bayesian Classifier (BC), Bayesian Network (BN), K-Nearest Neighbor (KNN) and Random Forest (RF). In order to handle the imbalanced dataset used, the Synthetic Minority Over-Sampling Technique (SMOTE) is used. Two set of experiments have been conducted with and without the SMOTE sampling technique. On average over different evaluation metrics, SVM Classifier has shown the lowest performance while other models like BN, BC and DT performed better. The RF classifier has shown the best performance (AUC = 0.97) among all models trained using the SMOTE sampling. The results show that various ML techniques can significantly vary in terms of its performance for the different evaluation metrics. It is also not necessarily that the more complex the ML model, the more prediction accuracy can be achieved. The prediction performance of all models trained with SMOTE is much better than the performance of models trained without SMOTE. The study shows the potential of machine learning methods for predicting all-cause mortality using cardiorespiratory fitness

  20. 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.

  1. LARA. Localization of an automatized refueling machine by acoustical sounding in breeder reactors - implementation of artificial intelligence techniques

    International Nuclear Information System (INIS)

    Lhuillier, C.; Malvache, P.

    1987-01-01

    The automatic control of the machine which handles the nuclear subassemblies in fast neutron reactors requires autonomous perception and decision tools. An acoustical device allows the machine to position in the work area. Artificial intelligence techniques are implemented to interpret the data: pattern recognition, scene analysis. The localization process is managed by an expert system. 6 refs.; 8 figs

  2. Optimization of Coolant Technique Conditions for Machining A319 Aluminium Alloy Using Response Surface Method (RSM)

    Science.gov (United States)

    Zainal Ariffin, S.; Razlan, A.; Ali, M. Mohd; Efendee, A. M.; Rahman, M. M.

    2018-03-01

    Background/Objectives: The paper discusses about the optimum cutting parameters with coolant techniques condition (1.0 mm nozzle orifice, wet and dry) to optimize surface roughness, temperature and tool wear in the machining process based on the selected setting parameters. The selected cutting parameters for this study were the cutting speed, feed rate, depth of cut and coolant techniques condition. Methods/Statistical Analysis Experiments were conducted and investigated based on Design of Experiment (DOE) with Response Surface Method. The research of the aggressive machining process on aluminum alloy (A319) for automotive applications is an effort to understand the machining concept, which widely used in a variety of manufacturing industries especially in the automotive industry. Findings: The results show that the dominant failure mode is the surface roughness, temperature and tool wear when using 1.0 mm nozzle orifice, increases during machining and also can be alternative minimize built up edge of the A319. The exploration for surface roughness, productivity and the optimization of cutting speed in the technical and commercial aspects of the manufacturing processes of A319 are discussed in automotive components industries for further work Applications/Improvements: The research result also beneficial in minimizing the costs incurred and improving productivity of manufacturing firms. According to the mathematical model and equations, generated by CCD based RSM, experiments were performed and cutting coolant condition technique using size nozzle can reduces tool wear, surface roughness and temperature was obtained. Results have been analyzed and optimization has been carried out for selecting cutting parameters, shows that the effectiveness and efficiency of the system can be identified and helps to solve potential problems.

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

    Science.gov (United States)

    Bueno, Julian L.

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

  4. Machine throughput improvement achieved using innovative control technique

    International Nuclear Information System (INIS)

    Sharma, V.; Acharya, S.; Mittal, K.C.

    2012-01-01

    In any type of fully or semi automatic machine the control systems plays an important role. The control system on the one hand has to consider the human psychology, intelligence requirement for an operator, and attention needed from him. On the other hand the complexity of the control has also to be understood well before designing a control system that can be handled comfortably and safely by the operator. As far as the user experience/comfort is concerned the design of control system GUI is vital. Considering these two aspects related to the user of the machine it is evident that the control system design is very important because it is has to accommodate the human behaviour and skill sets required/available as well as the capability of the machine under the control of the control system. An intelligently designed control system can enhance the productivity of the machine. (author)

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

    African Journals Online (AJOL)

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

  6. Event Streams Clustering Using Machine Learning Techniques

    Directory of Open Access Journals (Sweden)

    Hanen Bouali

    2015-10-01

    Full Text Available Data streams are usually of unbounded lengths which push users to consider only recent observations by focusing on a time window, and ignore past data. However, in many real world applications, past data must be taken in consideration to guarantee the efficiency, the performance of decision making and to handle data streams evolution over time. In order to build a selectively history to track the underlying event streams changes, we opt for the continuously data of the sliding window which increases the time window based on changes over historical data. In this paper, to have the ability to access to historical data without requiring any significant storage or multiple passes over the data. In this paper, we propose a new algorithm for clustering multiple data streams using incremental support vector machine and data representative points’ technique. The algorithm uses a sliding window model for the most recent clustering results and data representative points to model the old data clustering results. Our experimental results on electromyography signal show a better clustering than other present in the literature

  7. Classification of breast tumour using electrical impedance and machine learning techniques.

    Science.gov (United States)

    Al Amin, Abdullah; Parvin, Shahnaj; Kadir, M A; Tahmid, Tasmia; Alam, S Kaisar; Siddique-e Rabbani, K

    2014-06-01

    When a breast lump is detected through palpation, mammography or ultrasonography, the final test for characterization of the tumour, whether it is malignant or benign, is biopsy. This is invasive and carries hazards associated with any surgical procedures. The present work was undertaken to study the feasibility for such characterization using non-invasive electrical impedance measurements and machine learning techniques. Because of changes in cell morphology of malignant and benign tumours, changes are expected in impedance at a fixed frequency, and versus frequency of measurement. Tetrapolar impedance measurement (TPIM) using four electrodes at the corners of a square region of sides 4 cm was used for zone localization. Data of impedance in two orthogonal directions, measured at 5 and 200 kHz from 19 subjects, and their respective slopes with frequency were subjected to machine learning procedures through the use of feature plots. These patients had single or multiple tumours of various types in one or both breasts, and four of them had malignant tumours, as diagnosed by core biopsy. Although size and depth of the tumours are expected to affect the measurements, this preliminary work ignored these effects. Selecting 12 features from the above measurements, feature plots were drawn for the 19 patients, which displayed considerable overlap between malignant and benign cases. However, based on observed qualitative trend of the measured values, when all the feature values were divided by respective ages, the two types of tumours separated out reasonably well. Using K-NN classification method the results obtained are, positive prediction value: 60%, negative prediction value: 93%, sensitivity: 75%, specificity: 87% and efficacy: 84%, which are very good for such a test on a small sample size. Study on a larger sample is expected to give confidence in this technique, and further improvement of the technique may have the ability to replace biopsy.

  8. Classification of breast tumour using electrical impedance and machine learning techniques

    International Nuclear Information System (INIS)

    Amin, Abdullah Al; Parvin, Shahnaj; Kadir, M A; Tahmid, Tasmia; Alam, S Kaisar; Siddique-e Rabbani, K

    2014-01-01

    When a breast lump is detected through palpation, mammography or ultrasonography, the final test for characterization of the tumour, whether it is malignant or benign, is biopsy. This is invasive and carries hazards associated with any surgical procedures. The present work was undertaken to study the feasibility for such characterization using non-invasive electrical impedance measurements and machine learning techniques. Because of changes in cell morphology of malignant and benign tumours, changes are expected in impedance at a fixed frequency, and versus frequency of measurement. Tetrapolar impedance measurement (TPIM) using four electrodes at the corners of a square region of sides 4 cm was used for zone localization. Data of impedance in two orthogonal directions, measured at 5 and 200 kHz from 19 subjects, and their respective slopes with frequency were subjected to machine learning procedures through the use of feature plots. These patients had single or multiple tumours of various types in one or both breasts, and four of them had malignant tumours, as diagnosed by core biopsy. Although size and depth of the tumours are expected to affect the measurements, this preliminary work ignored these effects. Selecting 12 features from the above measurements, feature plots were drawn for the 19 patients, which displayed considerable overlap between malignant and benign cases. However, based on observed qualitative trend of the measured values, when all the feature values were divided by respective ages, the two types of tumours separated out reasonably well. Using K-NN classification method the results obtained are, positive prediction value: 60%, negative prediction value: 93%, sensitivity: 75%, specificity: 87% and efficacy: 84%, which are very good for such a test on a small sample size. Study on a larger sample is expected to give confidence in this technique, and further improvement of the technique may have the ability to replace biopsy. (paper)

  9. 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.

  10. Student Modeling and Machine Learning

    OpenAIRE

    Sison , Raymund; Shimura , Masamichi

    1998-01-01

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

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

    Science.gov (United States)

    Anazawa, Ryoko; Ishikawa, Hirono; Takahiro, Kiuchi

    2013-01-01

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

  12. 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...

  13. 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

    2016-01-01

    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. PMID:27046771

  14. 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.

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

    International Nuclear Information System (INIS)

    Barnes, G.J.

    2000-01-01

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

  16. Factored Translation with Unsupervised Word Clusters

    DEFF Research Database (Denmark)

    Rishøj, Christian; Søgaard, Anders

    2011-01-01

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

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

    NARCIS (Netherlands)

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

    2014-01-01

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

  18. Syntactic discriminative language model rerankers for statistical machine translation

    NARCIS (Netherlands)

    Carter, S.; Monz, C.

    2011-01-01

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

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

    NARCIS (Netherlands)

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

    2011-01-01

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

  20. 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.

  1. 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...

  2. Toward accelerating landslide mapping with interactive machine learning techniques

    Science.gov (United States)

    Stumpf, André; Lachiche, Nicolas; Malet, Jean-Philippe; Kerle, Norman; Puissant, Anne

    2013-04-01

    Despite important advances in the development of more automated methods for landslide mapping from optical remote sensing images, the elaboration of inventory maps after major triggering events still remains a tedious task. Image classification with expert defined rules typically still requires significant manual labour for the elaboration and adaption of rule sets for each particular case. Machine learning algorithm, on the contrary, have the ability to learn and identify complex image patterns from labelled examples but may require relatively large amounts of training data. In order to reduce the amount of required training data active learning has evolved as key concept to guide the sampling for applications such as document classification, genetics and remote sensing. The general underlying idea of most active learning approaches is to initialize a machine learning model with a small training set, and to subsequently exploit the model state and/or the data structure to iteratively select the most valuable samples that should be labelled by the user and added in the training set. With relatively few queries and labelled samples, an active learning strategy should ideally yield at least the same accuracy than an equivalent classifier trained with many randomly selected samples. Our study was dedicated to the development of an active learning approach for landslide mapping from VHR remote sensing images with special consideration of the spatial distribution of the samples. The developed approach is a region-based query heuristic that enables to guide the user attention towards few compact spatial batches rather than distributed points resulting in time savings of 50% and more compared to standard active learning techniques. The approach was tested with multi-temporal and multi-sensor satellite images capturing recent large scale triggering events in Brazil and China and demonstrated balanced user's and producer's accuracies between 74% and 80%. The assessment also

  3. Sensorless Speed/Torque Control of DC Machine Using Artificial Neural Network Technique

    Directory of Open Access Journals (Sweden)

    Rakan Kh. Antar

    2017-12-01

    Full Text Available In this paper, Artificial Neural Network (ANN technique is implemented to improve speed and torque control of a separately excited DC machine drive. The speed and torque sensorless scheme based on ANN is estimated adaptively. The proposed controller is designed to estimate rotor speed and mechanical load torque as a Model Reference Adaptive System (MRAS method for DC machine. The DC drive system consists of four quadrant DC/DC chopper with MOSFET transistors, ANN, logic gates and routing circuits. The DC drive circuit is designed, evaluated and modeled by Matlab/Simulink in the forward and reverse operation modes as a motor and generator, respectively. The DC drive system is simulated at different speed values (±1200 rpm and mechanical torque (±7 N.m in steady state and dynamic conditions. The simulation results illustratethe effectiveness of the proposed controller without speed or torque sensors.

  4. A Computer Program for Simplifying Incompletely Specified Sequential Machines Using the Paull and Unger Technique

    Science.gov (United States)

    Ebersole, M. M.; Lecoq, P. E.

    1968-01-01

    This report presents a description of a computer program mechanized to perform the Paull and Unger process of simplifying incompletely specified sequential machines. An understanding of the process, as given in Ref. 3, is a prerequisite to the use of the techniques presented in this report. This process has specific application in the design of asynchronous digital machines and was used in the design of operational support equipment for the Mariner 1966 central computer and sequencer. A typical sequential machine design problem is presented to show where the Paull and Unger process has application. A description of the Paull and Unger process together with a description of the computer algorithms used to develop the program mechanization are presented. Several examples are used to clarify the Paull and Unger process and the computer algorithms. Program flow diagrams, program listings, and a program user operating procedures are included as appendixes.

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

    Directory of Open Access Journals (Sweden)

    Yong Li

    2014-01-01

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

  6. Particle identification at LHCb: new calibration techniques and machine learning classification algorithms

    CERN Multimedia

    CERN. Geneva

    2018-01-01

    Particle identification (PID) plays a crucial role in LHCb analyses. Combining information from LHCb subdetectors allows one to distinguish between various species of long-lived charged and neutral particles. PID performance directly affects the sensitivity of most LHCb measurements. Advanced multivariate approaches are used at LHCb to obtain the best PID performance and control systematic uncertainties. This talk highlights recent developments in PID that use innovative machine learning techniques, as well as novel data-driven approaches which ensure that PID performance is well reproduced in simulation.

  7. Free focus radiography with miniaturized dental x-ray machines: a comparison of ''midline'' and ''lateral'' techniques

    International Nuclear Information System (INIS)

    Jensen, T.W.

    1983-01-01

    The use of free focus radiography (FFR) employing miniaturized dental x-ray machines with radiation probes has never been generally accepted in dentistry despite its recognized radiographic potential. The present investigation studied ways to improve imaging and lower radiation burdens in dental free focus radiography. Relatively high air exposures ranging from 42,050 mR per film for high-resolution images to 3,214 mR per film for lower-resolution images using a current midline radiographic technique for panoramic FFR were found. In a proposed lateral FFR panoramic technique, reduced exposures ranged from 420 mR per film for high-resolution images to 14 mR per film for lower-resolution images. In each technique the lower exposure was obtained with a rare earth imaging system. A proposed modification of the current midline FFR technique using a rare earth imaging system and heavy added copper filtration was found to produce exposures in the range normally used in dentistry (207 mr), and the resultant image was high in contrast with relatively low detail. A comparison of essential characteristics of midline and lateral FFR techniques failed to identify specific advantages for the midline technique in current use. Lateral exposure modes in dental FFR should receive increased attention in the interest of good imaging and radiation control. It was noted that existing miniaturized dental x-ray machines may have been designed specifically for use of the midline FFR exposure technique, and modification of this equipment to support reliable lateral exposure modes was recommended

  8. Machine Learning Techniques for Arterial Pressure Waveform Analysis

    Directory of Open Access Journals (Sweden)

    João Cardoso

    2013-05-01

    Full Text Available The Arterial Pressure Waveform (APW can provide essential information about arterial wall integrity and arterial stiffness. Most of APW analysis frameworks individually process each hemodynamic parameter and do not evaluate inter-dependencies in the overall pulse morphology. The key contribution of this work is the use of machine learning algorithms to deal with vectorized features extracted from APW. With this purpose, we follow a five-step evaluation methodology: (1 a custom-designed, non-invasive, electromechanical device was used in the data collection from 50 subjects; (2 the acquired position and amplitude of onset, Systolic Peak (SP, Point of Inflection (Pi and Dicrotic Wave (DW were used for the computation of some morphological attributes; (3 pre-processing work on the datasets was performed in order to reduce the number of input features and increase the model accuracy by selecting the most relevant ones; (4 classification of the dataset was carried out using four different machine learning algorithms: Random Forest, BayesNet (probabilistic, J48 (decision tree and RIPPER (rule-based induction; and (5 we evaluate the trained models, using the majority-voting system, comparatively to the respective calculated Augmentation Index (AIx. Classification algorithms have been proved to be efficient, in particular Random Forest has shown good accuracy (96.95% and high area under the curve (AUC of a Receiver Operating Characteristic (ROC curve (0.961. Finally, during validation tests, a correlation between high risk labels, retrieved from the multi-parametric approach, and positive AIx values was verified. This approach gives allowance for designing new hemodynamic morphology vectors and techniques for multiple APW analysis, thus improving the arterial pulse understanding, especially when compared to traditional single-parameter analysis, where the failure in one parameter measurement component, such as Pi, can jeopardize the whole evaluation.

  9. Fuzzy classification for strawberry diseases-infection using machine vision and soft-computing techniques

    Science.gov (United States)

    Altıparmak, Hamit; Al Shahadat, Mohamad; Kiani, Ehsan; Dimililer, Kamil

    2018-04-01

    Robotic agriculture requires smart and doable techniques to substitute the human intelligence with machine intelligence. Strawberry is one of the important Mediterranean product and its productivity enhancement requires modern and machine-based methods. Whereas a human identifies the disease infected leaves by his eye, the machine should also be capable of vision-based disease identification. The objective of this paper is to practically verify the applicability of a new computer-vision method for discrimination between the healthy and disease infected strawberry leaves which does not require neural network or time consuming trainings. The proposed method was tested under outdoor lighting condition using a regular DLSR camera without any particular lens. Since the type and infection degree of disease is approximated a human brain a fuzzy decision maker classifies the leaves over the images captured on-site having the same properties of human vision. Optimizing the fuzzy parameters for a typical strawberry production area at a summer mid-day in Cyprus produced 96% accuracy for segmented iron deficiency and 93% accuracy for segmented using a typical human instant classification approximation as the benchmark holding higher accuracy than a human eye identifier. The fuzzy-base classifier provides approximate result for decision making on the leaf status as if it is healthy or not.

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

    International Nuclear Information System (INIS)

    Lin Tong; Li Ruijiang; Tang Xiaoli; Jiang, Steve B; Dy, Jennifer G

    2009-01-01

    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.

  11. 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…

  12. HOW TO TRANSLATE SCIENTIFICALLY: A CASE IN THE JOURNAL OF “MEDICINA”

    Directory of Open Access Journals (Sweden)

    I Made Juliarta

    2016-05-01

    Full Text Available This reasearch aimed at analyzing and discussing the technique or procedure applied by translator in translating text found in the journal medicina. There are some procedures of translation techniques found and applied by translator. Some of the translation techniques applied by the translator consisting of borrowing, transposition, equivalence, structure shift, unti shift, literal, calque, addition and substraction. It was the borrowing technique used in applying the translation of terms which have been considered a part of respective TL. Unit shift is said as the change from word to group of word or in reverse. A different of modifierhead rule between SL and TL can occur in the structure shift. Equivalence and literal translation or words per word translation were found. It is important to apply the technique of calque which was reagarded as special kind of borrowing. There were the last two techniques which were also found as unavoidably which is applied by translator. Applying appropriate techniques in translating is needed in order the translation product can be reliable and acceptable for the reader.

  13. THE IMPACT OF TRANSLATION TECHNIQUES AND SUBTITLING RULES TO THE EQUIVALENCE OF MEANING OF CULINARY TERMS IN THE FRESH WITH ANNA OLSON SEASON 1 SUBTITLE

    Directory of Open Access Journals (Sweden)

    Hetty Hartati Novita

    2017-12-01

    Full Text Available The emergence of cable TV in Indonesia has made this author interested in focusing on the topic of culinary terms translation in the subtitle of Fresh with Anna Olson Season 1 program broadcasted on Asian Food Channel station. In this paper, this author analyzes the translation techniques suggested by Molina and Albir used by the translators to create the more accurate, natural, and communicative subtitle even though there are subtitling rules to follow. The result is, most of the translated terms have equivalence in meaning between the ST and the TT, while the ones which are not equivalent are due to the application of two particular techniques, Discursive Creation and Adaptation.

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

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1996-03-01

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

  15. 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.

  16. TRANSLATORS’ CENSORSHIP IN ENGLISH-INDONESIAN TRANSLATION OF DONALD DUCK COMICS

    Directory of Open Access Journals (Sweden)

    Issy Yuliasri

    2017-05-01

    Full Text Available Not all aspects of Western culture, reflected in the language used in Walt Disney’s Donald Duck comics, are acceptable in Indonesia. So, in translating the comics, the translators have to manipulate the text for it to be acceptable by the target readers and parents. This research aims at finding out censorship through the translation techniques used by the translators in translating the English humorous texts in the Walt Disney’s Donald Duck comics into Indonesian and the reasons underlying the translators’ choice of the translation techniques. It also aims at analysing whether or not the choice of the translation techniques affects the rendering of meaning, maintenance of humour, and acceptability of the translation. For these purposes a qualitative method was employed with content analysis technique and reader response analysis. Content analysis was used in comparing the source text (ST and target text (TT to find out the translation techniques used as a means of censorship and to find out the translators’ reasons for choosing the techniques. Reader-response analysis was done to find out the readers’ response to the rendering of meaning and maintenance of humour in the translation. The research findings discovered that the translators performed censorship through the dominant use of reduction and generalisation techniques so as to reduce sarcasm and insults. The interview with the publisher’s Senior Editor also revealed that “decency” was the first priority in the translation decision making, followed by clarity of meaning and maintenance of humour.  Further research to investigate other elements censored, and compared with other translated comics is recommended.

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

    Science.gov (United States)

    Mundt, Klaus; Groves, Michael

    2016-01-01

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

  18. 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.

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

    International Nuclear Information System (INIS)

    Issaly, Alain

    1979-01-01

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

  20. Considerations upon the Machine Learning Technologies

    OpenAIRE

    Alin Munteanu; Cristina Ofelia Sofran

    2006-01-01

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

  1. Visible Machine Learning for Biomedicine.

    Science.gov (United States)

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

    2018-06-14

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

  2. Machine performance assessment and enhancement for a hexapod machine

    Energy Technology Data Exchange (ETDEWEB)

    Mou, J.I. [Arizona State Univ., Tempe, AZ (United States); King, C. [Sandia National Labs., Livermore, CA (United States). Integrated Manufacturing Systems Center

    1998-03-19

    The focus of this study is to develop a sensor fused process modeling and control methodology to model, assess, and then enhance the performance of a hexapod machine for precision product realization. Deterministic modeling technique was used to derive models for machine performance assessment and enhancement. Sensor fusion methodology was adopted to identify the parameters of the derived models. Empirical models and computational algorithms were also derived and implemented to model, assess, and then enhance the machine performance. The developed sensor fusion algorithms can be implemented on a PC-based open architecture controller to receive information from various sensors, assess the status of the process, determine the proper action, and deliver the command to actuators for task execution. This will enhance a hexapod machine`s capability to produce workpieces within the imposed dimensional tolerances.

  3. Machine learning in healthcare informatics

    CERN Document Server

    Acharya, U; Dua, Prerna

    2014-01-01

    The book is a unique effort to represent a variety of techniques designed to represent, enhance, and empower multi-disciplinary and multi-institutional machine learning research in healthcare informatics. The book provides a unique compendium of current and emerging machine learning paradigms for healthcare informatics and reflects the diversity, complexity and the depth and breath of this multi-disciplinary area. The integrated, panoramic view of data and machine learning techniques can provide an opportunity for novel clinical insights and discoveries.

  4. Comparison of Machine Learning Techniques for the Prediction of Compressive Strength of Concrete

    Directory of Open Access Journals (Sweden)

    Palika Chopra

    2018-01-01

    Full Text Available A comparative analysis for the prediction of compressive strength of concrete at the ages of 28, 56, and 91 days has been carried out using machine learning techniques via “R” software environment. R is digging out a strong foothold in the statistical realm and is becoming an indispensable tool for researchers. The dataset has been generated under controlled laboratory conditions. Using R miner, the most widely used data mining techniques decision tree (DT model, random forest (RF model, and neural network (NN model have been used and compared with the help of coefficient of determination (R2 and root-mean-square error (RMSE, and it is inferred that the NN model predicts with high accuracy for compressive strength of concrete.

  5. An introduction to quantum machine learning

    Science.gov (United States)

    Schuld, Maria; Sinayskiy, Ilya; Petruccione, Francesco

    2015-04-01

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

  6. Discrimination of plant root zone water status in greenhouse production based on phenotyping and machine learning techniques.

    Science.gov (United States)

    Guo, Doudou; Juan, Jiaxiang; Chang, Liying; Zhang, Jingjin; Huang, Danfeng

    2017-08-15

    Plant-based sensing on water stress can provide sensitive and direct reference for precision irrigation system in greenhouse. However, plant information acquisition, interpretation, and systematical application remain insufficient. This study developed a discrimination method for plant root zone water status in greenhouse by integrating phenotyping and machine learning techniques. Pakchoi plants were used and treated by three root zone moisture levels, 40%, 60%, and 80% relative water content. Three classification models, Random Forest (RF), Neural Network (NN), and Support Vector Machine (SVM) were developed and validated in different scenarios with overall accuracy over 90% for all. SVM model had the highest value, but it required the longest training time. All models had accuracy over 85% in all scenarios, and more stable performance was observed in RF model. Simplified SVM model developed by the top five most contributing traits had the largest accuracy reduction as 29.5%, while simplified RF and NN model still maintained approximately 80%. For real case application, factors such as operation cost, precision requirement, and system reaction time should be synthetically considered in model selection. Our work shows it is promising to discriminate plant root zone water status by implementing phenotyping and machine learning techniques for precision irrigation management.

  7. Machining of uranium and uranium alloys

    International Nuclear Information System (INIS)

    Morris, T.O.

    1981-01-01

    Uranium and uranium alloys can be readily machined by conventional methods in the standard machine shop when proper safety and operating techniques are used. Material properties that affect machining processes and recommended machining parameters are discussed. Safety procedures and precautions necessary in machining uranium and uranium alloys are also covered. 30 figures

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

    International Nuclear Information System (INIS)

    Laranjeira, M.S.; Dias, A.G.; Santos, J.D.; Fernandes, M.H.

    2009-01-01

    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 μm. 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.

  9. Considerations upon the Machine Learning Technologies

    Directory of Open Access Journals (Sweden)

    Alin Munteanu

    2006-01-01

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

  10. 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.

  11. Chapter 16: text mining for translational bioinformatics.

    Science.gov (United States)

    Cohen, K Bretonnel; Hunter, Lawrence E

    2013-04-01

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

  12. Design of rotating electrical machines

    CERN Document Server

    Pyrhonen , Juha; Hrabovcova , Valeria

    2013-01-01

    In one complete volume, this essential reference presents an in-depth overview of the theoretical principles and techniques of electrical machine design. This timely new edition offers up-to-date theory and guidelines for the design of electrical machines, taking into account recent advances in permanent magnet machines as well as synchronous reluctance machines. New coverage includes: Brand new material on the ecological impact of the motors, covering the eco-design principles of rotating electrical machinesAn expanded section on the design of permanent magnet synchronous machines, now repo

  13. Survey of Analysis of Crime Detection Techniques Using Data Mining and Machine Learning

    Science.gov (United States)

    Prabakaran, S.; Mitra, Shilpa

    2018-04-01

    Data mining is the field containing procedures for finding designs or patterns in a huge dataset, it includes strategies at the convergence of machine learning and database framework. It can be applied to various fields like future healthcare, market basket analysis, education, manufacturing engineering, crime investigation etc. Among these, crime investigation is an interesting application to process crime characteristics to help the society for a better living. This paper survey various data mining techniques used in this domain. This study may be helpful in designing new strategies for crime prediction and analysis.

  14. Novel Machine Learning-Based Techniques for Efficient Resource Allocation in Next Generation Wireless Networks

    KAUST Repository

    AlQuerm, Ismail A.

    2018-02-21

    There is a large demand for applications of high data rates in wireless networks. These networks are becoming more complex and challenging to manage due to the heterogeneity of users and applications specifically in sophisticated networks such as the upcoming 5G. Energy efficiency in the future 5G network is one of the essential problems that needs consideration due to the interference and heterogeneity of the network topology. Smart resource allocation, environmental adaptivity, user-awareness and energy efficiency are essential features in the future networks. It is important to support these features at different networks topologies with various applications. Cognitive radio has been found to be the paradigm that is able to satisfy the above requirements. It is a very interdisciplinary topic that incorporates flexible system architectures, machine learning, context awareness and cooperative networking. Mitola’s vision about cognitive radio intended to build context-sensitive smart radios that are able to adapt to the wireless environment conditions while maintaining quality of service support for different applications. Artificial intelligence techniques including heuristics algorithms and machine learning are the shining tools that are employed to serve the new vision of cognitive radio. In addition, these techniques show a potential to be utilized in an efficient resource allocation for the upcoming 5G networks’ structures such as heterogeneous multi-tier 5G networks and heterogeneous cloud radio access networks due to their capability to allocate resources according to real-time data analytics. In this thesis, we study cognitive radio from a system point of view focusing closely on architectures, artificial intelligence techniques that can enable intelligent radio resource allocation and efficient radio parameters reconfiguration. We propose a modular cognitive resource management architecture, which facilitates a development of flexible control for

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

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1999-03-01

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

  16. Machine learning and statistical techniques : an application to the prediction of insolvency in Spanish non-life insurance companies

    OpenAIRE

    Díaz, Zuleyka; Segovia, María Jesús; Fernández, José

    2005-01-01

    Prediction of insurance companies insolvency has arisen as an important problem in the field of financial research. Most methods applied in the past to tackle this issue are traditional statistical techniques which use financial ratios as explicative variables. However, these variables often do not satisfy statistical assumptions, which complicates the application of the mentioned methods. In this paper, a comparative study of the performance of two non-parametric machine learning techniques ...

  17. A critical survey of live virtual machine migration techniques

    Directory of Open Access Journals (Sweden)

    Anita Choudhary

    2017-11-01

    Full Text Available Abstract Virtualization techniques effectively handle the growing demand for computing, storage, and communication resources in large-scale Cloud Data Centers (CDC. It helps to achieve different resource management objectives like load balancing, online system maintenance, proactive fault tolerance, power management, and resource sharing through Virtual Machine (VM migration. VM migration is a resource-intensive procedure as VM’s continuously demand appropriate CPU cycles, cache memory, memory capacity, and communication bandwidth. Therefore, this process degrades the performance of running applications and adversely affects efficiency of the data centers, particularly when Service Level Agreements (SLA and critical business objectives are to be met. Live VM migration is frequently used because it allows the availability of application service, while migration is performed. In this paper, we make an exhaustive survey of the literature on live VM migration and analyze the various proposed mechanisms. We first classify the types of Live VM migration (single, multiple and hybrid. Next, we categorize VM migration techniques based on duplication mechanisms (replication, de-duplication, redundancy, and compression and awareness of context (dependency, soft page, dirty page, and page fault and evaluate the various Live VM migration techniques. We discuss various performance metrics like application service downtime, total migration time and amount of data transferred. CPU, memory and storage data is transferred during the process of VM migration and we identify the category of data that needs to be transferred in each case. We present a brief discussion on security threats in live VM migration and categories them in three different classes (control plane, data plane, and migration module. We also explain the security requirements and existing solutions to mitigate possible attacks. Specific gaps are identified and the research challenges in improving

  18. 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....

  19. Mechatronic sensor system for robots and automated machines

    CSIR Research Space (South Africa)

    Shaik, AA

    2007-01-01

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

  20. Performance optimization in electro- discharge machining using a suitable multiresponse optimization technique

    Directory of Open Access Journals (Sweden)

    I. Nayak

    2017-06-01

    Full Text Available In the present research work, four different multi response optimization techniques, viz. multiple response signal-to-noise (MRSN ratio, weighted signal-to-noise (WSN ratio, Grey relational analysis (GRA and VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje in Serbian methods have been used to optimize the electro-discharge machining (EDM performance characteristics such as material removal rate (MRR, tool wear rate (TWR and surface roughness (SR simultaneously. Experiments have been planned on a D2 steel specimen based on L9 orthogonal array. Experimental results are analyzed using the standard procedure. The optimum level combinations of input process parameters such as voltage, current, pulse-on-time and pulse-off-time, and percentage contributions of each process parameter using ANOVA technique have been determined. Different correlations have been developed between the various input process parameters and output performance characteristics. Finally, the optimum performances of these four methods are compared and the results show that WSN ratio method is the best multiresponse optimization technique for this process. From the analysis, it is also found that the current has the maximum effect on the overall performance of EDM operation as compared to other process parameters.

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

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2000-01-10

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

  2. Development and Experimental Evaluation of Machine-Learning Techniques for an Intelligent Hairy Scalp Detection System

    Directory of Open Access Journals (Sweden)

    Wei-Chien Wang

    2018-05-01

    Full Text Available Deep learning has become the most popular research subject in the fields of artificial intelligence (AI and machine learning. In October 2013, MIT Technology Review commented that deep learning was a breakthrough technology. Deep learning has made progress in voice and image recognition, image classification, and natural language processing. Prior to deep learning, decision tree, linear discriminant analysis (LDA, support vector machines (SVM, k-nearest neighbors algorithm (K-NN, and ensemble learning were popular in solving classification problems. In this paper, we applied the previously mentioned and deep learning techniques to hairy scalp images. Hairy scalp problems are usually diagnosed by non-professionals in hair salons, and people with such problems may be advised by these non-professionals. Additionally, several common scalp problems are similar; therefore, non-experts may provide incorrect diagnoses. Hence, scalp problems have worsened. In this work, we implemented and compared the deep-learning method, the ImageNet-VGG-f model Bag of Words (BOW, with machine-learning classifiers, and histogram of oriented gradients (HOG/pyramid histogram of oriented gradients (PHOG with machine-learning classifiers. The tools from the classification learner apps were used for hairy scalp image classification. The results indicated that deep learning can achieve an accuracy of 89.77% when the learning rate is 1 × 10−4, and this accuracy is far higher than those achieved by BOW with SVM (80.50% and PHOG with SVM (53.0%.

  3. Machine learning in virtual screening.

    Science.gov (United States)

    Melville, James L; Burke, Edmund K; Hirst, Jonathan D

    2009-05-01

    In this review, we highlight recent applications of machine learning to virtual screening, focusing on the use of supervised techniques to train statistical learning algorithms to prioritize databases of molecules as active against a particular protein target. Both ligand-based similarity searching and structure-based docking have benefited from machine learning algorithms, including naïve Bayesian classifiers, support vector machines, neural networks, and decision trees, as well as more traditional regression techniques. Effective application of these methodologies requires an appreciation of data preparation, validation, optimization, and search methodologies, and we also survey developments in these areas.

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

    Science.gov (United States)

    Pelto, E. V.

    1967-01-01

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

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

    Science.gov (United States)

    Tremblay, Michael

    2010-01-01

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

  6. MLnet report: training in Europe on machine learning

    OpenAIRE

    Ellebrecht, Mario; Morik, Katharina

    1999-01-01

    Machine learning techniques offer opportunities for a variety of applications and the theory of machine learning investigates problems that are of interest for other fields of computer science (e.g., complexity theory, logic programming, pattern recognition). However, the impacts of machine learning can only be recognized by those who know the techniques and are able to apply them. Hence, teaching machine learning is necessary before this field can diversify computer science. In order ...

  7. 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.

  8. Machine Learning

    CERN Multimedia

    CERN. Geneva

    2017-01-01

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

  9. Machine Learning for Security

    CERN Multimedia

    CERN. Geneva

    2015-01-01

    Applied statistics, aka ‘Machine Learning’, offers a wealth of techniques for answering security questions. It’s a much hyped topic in the big data world, with many companies now providing machine learning as a service. This talk will demystify these techniques, explain the math, and demonstrate their application to security problems. The presentation will include how-to’s on classifying malware, looking into encrypted tunnels, and finding botnets in DNS data. About the speaker Josiah is a security researcher with HP TippingPoint DVLabs Research Group. He has over 15 years of professional software development experience. Josiah used to do AI, with work focused on graph theory, search, and deductive inference on large knowledge bases. As rules only get you so far, he moved from AI to using machine learning techniques identifying failure modes in email traffic. There followed digressions into clustered data storage and later integrated control systems. Current ...

  10. Broiler chickens can benefit from machine learning: support vector machine analysis of observational epidemiological data.

    Science.gov (United States)

    Hepworth, Philip J; Nefedov, Alexey V; Muchnik, Ilya B; Morgan, Kenton L

    2012-08-07

    Machine-learning algorithms pervade our daily lives. In epidemiology, supervised machine learning has the potential for classification, diagnosis and risk factor identification. Here, we report the use of support vector machine learning to identify the features associated with hock burn on commercial broiler farms, using routinely collected farm management data. These data lend themselves to analysis using machine-learning techniques. Hock burn, dermatitis of the skin over the hock, is an important indicator of broiler health and welfare. Remarkably, this classifier can predict the occurrence of high hock burn prevalence with accuracy of 0.78 on unseen data, as measured by the area under the receiver operating characteristic curve. We also compare the results with those obtained by standard multi-variable logistic regression and suggest that this technique provides new insights into the data. This novel application of a machine-learning algorithm, embedded in poultry management systems could offer significant improvements in broiler health and welfare worldwide.

  11. Ex-vivo machine perfusion for kidney preservation.

    Science.gov (United States)

    Hamar, Matyas; Selzner, Markus

    2018-06-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

    Witkam, A P.M.

    1983-01-01

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

  13. Machine Learning Approaches for Clinical Psychology and Psychiatry.

    Science.gov (United States)

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

    2018-05-07

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

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

    Science.gov (United States)

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

    2018-02-01

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

  15. Characterization of in vitro translation products

    International Nuclear Information System (INIS)

    Jagus, R.

    1987-01-01

    This chapter describes the characterization of in vitro translation products by the most commonly used techniques. The methods include SDS-polyacrylamide gel electrophoresis (SDS-PAGE), combined with immunoprecipitation and/or fluorography of [ 35 S]methionine-labeled translation products. The other frequently used characterization tool, translation of hybrid-selected mRNA or hybrid-arrested translation, is treated separately in this volume. Methods are also given for the recognition of mRNAs coding for secreted or membrane proteins

  16. An artificial molecular machine that builds an asymmetric catalyst

    Science.gov (United States)

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

    2018-05-01

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

  17. 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…

  18. High speed operation of permanent magnet machines

    Science.gov (United States)

    El-Refaie, Ayman M.

    This work proposes methods to extend the high-speed operating capabilities of both the interior PM (IPM) and surface PM (SPM) machines. For interior PM machines, this research has developed and presented the first thorough analysis of how a new bi-state magnetic material can be usefully applied to the design of IPM machines. Key elements of this contribution include identifying how the unique properties of the bi-state magnetic material can be applied most effectively in the rotor design of an IPM machine by "unmagnetizing" the magnet cavity center posts rather than the outer bridges. The importance of elevated rotor speed in making the best use of the bi-state magnetic material while recognizing its limitations has been identified. For surface PM machines, this research has provided, for the first time, a clear explanation of how fractional-slot concentrated windings can be applied to SPM machines in order to achieve the necessary conditions for optimal flux weakening. A closed-form analytical procedure for analyzing SPM machines designed with concentrated windings has been developed. Guidelines for designing SPM machines using concentrated windings in order to achieve optimum flux weakening are provided. Analytical and numerical finite element analysis (FEA) results have provided promising evidence of the scalability of the concentrated winding technique with respect to the number of poles, machine aspect ratio, and output power rating. Useful comparisons between the predicted performance characteristics of SPM machines equipped with concentrated windings and both SPM and IPM machines designed with distributed windings are included. Analytical techniques have been used to evaluate the impact of the high pole number on various converter performance metrics. Both analytical techniques and FEA have been used for evaluating the eddy-current losses in the surface magnets due to the stator winding subharmonics. Techniques for reducing these losses have been

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

    Energy Technology Data Exchange (ETDEWEB)

    1999-03-01

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

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

    African Journals Online (AJOL)

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

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

    African Journals Online (AJOL)

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

  2. 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

  3. Automatic Classification of Sub-Techniques in Classical Cross-Country Skiing Using a Machine Learning Algorithm on Micro-Sensor Data

    Directory of Open Access Journals (Sweden)

    Ole Marius Hoel Rindal

    2017-12-01

    Full Text Available The automatic classification of sub-techniques in classical cross-country skiing provides unique possibilities for analyzing the biomechanical aspects of outdoor skiing. This is currently possible due to the miniaturization and flexibility of wearable inertial measurement units (IMUs that allow researchers to bring the laboratory to the field. In this study, we aimed to optimize the accuracy of the automatic classification of classical cross-country skiing sub-techniques by using two IMUs attached to the skier’s arm and chest together with a machine learning algorithm. The novelty of our approach is the reliable detection of individual cycles using a gyroscope on the skier’s arm, while a neural network machine learning algorithm robustly classifies each cycle to a sub-technique using sensor data from an accelerometer on the chest. In this study, 24 datasets from 10 different participants were separated into the categories training-, validation- and test-data. Overall, we achieved a classification accuracy of 93.9% on the test-data. Furthermore, we illustrate how an accurate classification of sub-techniques can be combined with data from standard sports equipment including position, altitude, speed and heart rate measuring systems. Combining this information has the potential to provide novel insight into physiological and biomechanical aspects valuable to coaches, athletes and researchers.

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

    Directory of Open Access Journals (Sweden)

    Sara Laviosa

    2015-11-01

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

  5. Modelling risk of tick exposure in southern Scandinavia using machine learning techniques, satellite imagery, and human population density maps

    DEFF Research Database (Denmark)

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

    30 sites (forests and meadows) in each of Denmark, southern Norway and south-eastern Sweden. At each site we measured presence/absence of ticks, and used the data obtained along with environmental satellite images to run Boosted Regression Tree machine learning algorithms to predict overall spatial...... and Sweden), areas with high population densities tend to overlap with these zones.Machine learning techniques allow us to predict for larger areas without having to perform extensive sampling all over the region in question, and we were able to produce models and maps with high predictive value. The results...

  6. A Higher-Order Colon Translation

    DEFF Research Database (Denmark)

    Danvy, Olivier; Nielsen, Lasse Reichstein

    2001-01-01

    A lambda-encoding such as the CPS transformation gives rise to administrative redexes. In his seminal article ``Call-by-name, call-by-value and the lambda-calculus'', 25 years ago, Plotkin tackled administrative reductions using a so-called ``colon translation.'' 10 years ago, Danvy and Filinski...... integrated administrative reductions in the CPS transformation, making it operate in one pass. The technique applies to other lambda-encodings (e.g., variants of CPS), but we do not see it used in practice--instead, Plotkin's colon translation appears to be favored. Therefore, in an attempt to link both...... techniques, we recast Plotkin's proof of Indifference and Simulation to the higher-order specification of the one-pass CPS transformation. To this end, we extend his colon translation from first order to higher order...

  7. Energy Conversion Loops for Flux-Switching PM Machine Analysis

    Directory of Open Access Journals (Sweden)

    E. Ilhan

    2012-10-01

    Full Text Available Induction and synchronous machines have traditionally been the first choice of automotive manufacturers for electric/hybrid vehicles. However, these conventional machines are not able anymore to meet the increasing demands for a higher energy density due to space limitation in cars. Flux-switching PM (FSPM machines with their high energy density are very suitable to answer this demand. In this paper, the energy conversion loop technique is implemented on FSPM for the first time. The energy conversion technique is a powerful tool for the visualization of machine characteristics, both linear and nonlinear. Further, the technique provides insight into the torque production mechanism. A stepwise explanation is given on how to create these loops for FSPM along with the machine operation.

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

    OpenAIRE

    Goujon , Antoine

    2016-01-01

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

  9. JavaScript DNA translator: DNA-aligned protein translations.

    Science.gov (United States)

    Perry, William L

    2002-12-01

    There are many instances in molecular biology when it is necessary to identify ORFs in a DNA sequence. While programs exist for displaying protein translations in multiple ORFs in alignment with a DNA sequence, they are often expensive, exist as add-ons to software that must be purchased, or are only compatible with a particular operating system. JavaScript DNA Translator is a shareware application written in JavaScript, a scripting language interpreted by the Netscape Communicator and Internet Explorer Web browsers, which makes it compatible with several different operating systems. While the program uses a familiar Web page interface, it requires no connection to the Internet since calculations are performed on the user's own computer. The program analyzes one or multiple DNA sequences and generates translations in up to six reading frames aligned to a DNA sequence, in addition to displaying translations as separate sequences in FASTA format. ORFs within a reading frame can also be displayed as separate sequences. Flexible formatting options are provided, including the ability to hide ORFs below a minimum size specified by the user. The program is available free of charge at the BioTechniques Software Library (www.Biotechniques.com).

  10. Scoping Study of Machine Learning Techniques for Visualization and Analysis of Multi-source Data in Nuclear Safeguards

    Energy Technology Data Exchange (ETDEWEB)

    Cui, Yonggang

    2018-05-07

    In implementation of nuclear safeguards, many different techniques are being used to monitor operation of nuclear facilities and safeguard nuclear materials, ranging from radiation detectors, flow monitors, video surveillance, satellite imagers, digital seals to open source search and reports of onsite inspections/verifications. Each technique measures one or more unique properties related to nuclear materials or operation processes. Because these data sets have no or loose correlations, it could be beneficial to analyze the data sets together to improve the effectiveness and efficiency of safeguards processes. Advanced visualization techniques and machine-learning based multi-modality analysis could be effective tools in such integrated analysis. In this project, we will conduct a survey of existing visualization and analysis techniques for multi-source data and assess their potential values in nuclear safeguards.

  11. Translation of questionnaires into Arabic in cross-cultural research: techniques and equivalence issues.

    Science.gov (United States)

    Khalaila, Rabia

    2013-10-01

    To describe the translation process of nursing instruments into Arabic and discuss the equivalence issues arising from this process. Review of the literature. The Arabic language is essentially three different languages: Classical Arabic; Modern Standard Arabic (fuS-Ha or MSA); and colloquial Arabic (Lahja A'mmeya), which is itself divided into five different regional Arabic dialects. The Arabic fuS-Ha language is the dialect most widely used in the translation of instruments into Arabic. The literature reveals that only a few studies focused on the linguistic issues in the translation of instruments into Arabic. Brislin's back-translation emerged as the most common method widely used by researchers in studies with Arabic-speaking subjects, but not the perfect one. Linguistic issues in nursing research have not been sufficiently described and discussed in the context of Arabic language and culture. Although there is no standard guideline for instrument translation, the combined translation model is the most recommended procedure to use in cross-cultural research. Linguistic differences between the source culture and the target Arabic culture should be taken into account. Finally, we recommend the use of the fuS-Ha dialect and trilingual translators in the translation of nursing instruments into Arabic.

  12. A comparison of machine learning techniques for survival prediction in breast cancer.

    Science.gov (United States)

    Vanneschi, Leonardo; Farinaccio, Antonella; Mauri, Giancarlo; Antoniotti, Mauro; Provero, Paolo; Giacobini, Mario

    2011-05-11

    The ability to accurately classify cancer patients into risk classes, i.e. to predict the outcome of the pathology on an individual basis, is a key ingredient in making therapeutic decisions. In recent years gene expression data have been successfully used to complement the clinical and histological criteria traditionally used in such prediction. Many "gene expression signatures" have been developed, i.e. sets of genes whose expression values in a tumor can be used to predict the outcome of the pathology. Here we investigate the use of several machine learning techniques to classify breast cancer patients using one of such signatures, the well established 70-gene signature. We show that Genetic Programming performs significantly better than Support Vector Machines, Multilayered Perceptrons and Random Forests in classifying patients from the NKI breast cancer dataset, and comparably to the scoring-based method originally proposed by the authors of the 70-gene signature. Furthermore, Genetic Programming is able to perform an automatic feature selection. Since the performance of Genetic Programming is likely to be improvable compared to the out-of-the-box approach used here, and given the biological insight potentially provided by the Genetic Programming solutions, we conclude that Genetic Programming methods are worth further investigation as a tool for cancer patient classification based on gene expression data.

  13. A comparison of machine learning techniques for survival prediction in breast cancer

    Directory of Open Access Journals (Sweden)

    Vanneschi Leonardo

    2011-05-01

    Full Text Available Abstract Background The ability to accurately classify cancer patients into risk classes, i.e. to predict the outcome of the pathology on an individual basis, is a key ingredient in making therapeutic decisions. In recent years gene expression data have been successfully used to complement the clinical and histological criteria traditionally used in such prediction. Many "gene expression signatures" have been developed, i.e. sets of genes whose expression values in a tumor can be used to predict the outcome of the pathology. Here we investigate the use of several machine learning techniques to classify breast cancer patients using one of such signatures, the well established 70-gene signature. Results We show that Genetic Programming performs significantly better than Support Vector Machines, Multilayered Perceptrons and Random Forests in classifying patients from the NKI breast cancer dataset, and comparably to the scoring-based method originally proposed by the authors of the 70-gene signature. Furthermore, Genetic Programming is able to perform an automatic feature selection. Conclusions Since the performance of Genetic Programming is likely to be improvable compared to the out-of-the-box approach used here, and given the biological insight potentially provided by the Genetic Programming solutions, we conclude that Genetic Programming methods are worth further investigation as a tool for cancer patient classification based on gene expression data.

  14. 5-axes modular CNC machining center

    Directory of Open Access Journals (Sweden)

    Breaz Radu-Eugen

    2017-01-01

    Full Text Available The paper presents the development of a 5-axes CNC machining center. The main goal of the machine was to provide the students a practical layout for training in advanced CAM techniques. The mechanical structure of the machine was built in a modular way by a specialized company, which also implemented the CNC controller. The authors of this paper developed the geometric and kinematic model of the CNC machining center and the post-processor, in order to use the machine in a CAM environment.

  15. Machine learning models in breast cancer survival prediction.

    Science.gov (United States)

    Montazeri, Mitra; Montazeri, Mohadeseh; Montazeri, Mahdieh; Beigzadeh, Amin

    2016-01-01

    Breast cancer is one of the most common cancers with a high mortality rate among women. With the early diagnosis of breast cancer survival will increase from 56% to more than 86%. Therefore, an accurate and reliable system is necessary for the early diagnosis of this cancer. The proposed model is the combination of rules and different machine learning techniques. Machine learning models can help physicians to reduce the number of false decisions. They try to exploit patterns and relationships among a large number of cases and predict the outcome of a disease using historical cases stored in datasets. The objective of this study is to propose a rule-based classification method with machine learning techniques for the prediction of different types of Breast cancer survival. We use a dataset with eight attributes that include the records of 900 patients in which 876 patients (97.3%) and 24 (2.7%) patients were females and males respectively. Naive Bayes (NB), Trees Random Forest (TRF), 1-Nearest Neighbor (1NN), AdaBoost (AD), Support Vector Machine (SVM), RBF Network (RBFN), and Multilayer Perceptron (MLP) machine learning techniques with 10-cross fold technique were used with the proposed model for the prediction of breast cancer survival. The performance of machine learning techniques were evaluated with accuracy, precision, sensitivity, specificity, and area under ROC curve. Out of 900 patients, 803 patients and 97 patients were alive and dead, respectively. In this study, Trees Random Forest (TRF) technique showed better results in comparison to other techniques (NB, 1NN, AD, SVM and RBFN, MLP). The accuracy, sensitivity and the area under ROC curve of TRF are 96%, 96%, 93%, respectively. However, 1NN machine learning technique provided poor performance (accuracy 91%, sensitivity 91% and area under ROC curve 78%). This study demonstrates that Trees Random Forest model (TRF) which is a rule-based classification model was the best model with the highest level of

  16. Creativity in Machine Learning

    OpenAIRE

    Thoma, Martin

    2016-01-01

    Recent machine learning techniques can be modified to produce creative results. Those results did not exist before; it is not a trivial combination of the data which was fed into the machine learning system. The obtained results come in multiple forms: As images, as text and as audio. This paper gives a high level overview of how they are created and gives some examples. It is meant to be a summary of the current work and give people who are new to machine learning some starting points.

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

    Directory of Open Access Journals (Sweden)

    Antonio Cerasa

    2015-01-01

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

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

    Science.gov (United States)

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

    2015-01-01

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

  19. Component Pin Recognition Using Algorithms Based on Machine Learning

    Science.gov (United States)

    Xiao, Yang; Hu, Hong; Liu, Ze; Xu, Jiangchang

    2018-04-01

    The purpose of machine vision for a plug-in machine is to improve the machine’s stability and accuracy, and recognition of the component pin is an important part of the vision. This paper focuses on component pin recognition using three different techniques. The first technique involves traditional image processing using the core algorithm for binary large object (BLOB) analysis. The second technique uses the histogram of oriented gradients (HOG), to experimentally compare the effect of the support vector machine (SVM) and the adaptive boosting machine (AdaBoost) learning meta-algorithm classifiers. The third technique is the use of an in-depth learning method known as convolution neural network (CNN), which involves identifying the pin by comparing a sample to its training. The main purpose of the research presented in this paper is to increase the knowledge of learning methods used in the plug-in machine industry in order to achieve better results.

  20. Predicting breast screening attendance using machine learning techniques.

    Science.gov (United States)

    Baskaran, Vikraman; Guergachi, Aziz; Bali, Rajeev K; Naguib, Raouf N G

    2011-03-01

    Machine learning-based prediction has been effectively applied for many healthcare applications. Predicting breast screening attendance using machine learning (prior to the actual mammogram) is a new field. This paper presents new predictor attributes for such an algorithm. It describes a new hybrid algorithm that relies on back-propagation and radial basis function-based neural networks for prediction. The algorithm has been developed in an open source-based environment. The algorithm was tested on a 13-year dataset (1995-2008). This paper compares the algorithm and validates its accuracy and efficiency with different platforms. Nearly 80% accuracy and 88% positive predictive value and sensitivity were recorded for the algorithm. The results were encouraging; 40-50% of negative predictive value and specificity warrant further work. Preliminary results were promising and provided ample amount of reasons for testing the algorithm on a larger scale.

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

    Directory of Open Access Journals (Sweden)

    Klejch Ondřej

    2015-10-01

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

  2. Creating a Multi-axis Machining Postprocessor

    Directory of Open Access Journals (Sweden)

    Petr Vavruška

    2012-01-01

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

  3. Nano Mechanical Machining Using AFM Probe

    Science.gov (United States)

    Mostofa, Md. Golam

    Complex miniaturized components with high form accuracy will play key roles in the future development of many products, as they provide portability, disposability, lower material consumption in production, low power consumption during operation, lower sample requirements for testing, and higher heat transfer due to their very high surface-to-volume ratio. Given the high market demand for such micro and nano featured components, different manufacturing methods have been developed for their fabrication. Some of the common technologies in micro/nano fabrication are photolithography, electron beam lithography, X-ray lithography and other semiconductor processing techniques. Although these methods are capable of fabricating micro/nano structures with a resolution of less than a few nanometers, some of the shortcomings associated with these methods, such as high production costs for customized products, limited material choices, necessitate the development of other fabricating techniques. Micro/nano mechanical machining, such an atomic force microscope (AFM) probe based nano fabrication, has, therefore, been used to overcome some the major restrictions of the traditional processes. This technique removes material from the workpiece by engaging micro/nano size cutting tool (i.e. AFM probe) and is applicable on a wider range of materials compared to the photolithographic process. In spite of the unique benefits of nano mechanical machining, there are also some challenges with this technique, since the scale is reduced, such as size effects, burr formations, chip adhesions, fragility of tools and tool wear. Moreover, AFM based machining does not have any rotational movement, which makes fabrication of 3D features more difficult. Thus, vibration-assisted machining is introduced into AFM probe based nano mechanical machining to overcome the limitations associated with the conventional AFM probe based scratching method. Vibration-assisted machining reduced the cutting forces

  4. Machine learning with R cookbook

    CERN Document Server

    Chiu, Yu-Wei

    2015-01-01

    If you want to learn how to use R for machine learning and gain insights from your data, then this book is ideal for you. Regardless of your level of experience, this book covers the basics of applying R to machine learning through to advanced techniques. While it is helpful if you are familiar with basic programming or machine learning concepts, you do not require prior experience to benefit from this book.

  5. HTGR Metallic Reactor Internals Core Shell Cutting & Machining Antideformation Technique Study

    International Nuclear Information System (INIS)

    Xing Huiping; Xue Song

    2014-01-01

    The reactor shell assembly of HTGR nuclear power station demonstration project metallic reactor internals is key components of reactor, remains with high-precision large component with large-sized thin-walled straight cylinder-shaped structure, and is the first manufacture in China. As compared with other reactor shell, it has a larger ID (Φ5360mm), a longer length (19000mm), a smaller wall thickness (40mm) and a higher precision requirement. During the process of manufacture, the deformation due to cutting & machining will directly affect the final result of manufacture, the control of structural deformation and cutting deformation shall be throughout total manufacture process of such assembly. To realize the control of entire core shell assembly geometry, the key is to innovate and make breakthroughs on anti-deformation technique and then provide reliable technological foundations for the manufacture of HTGR metallic reactor internals. (author)

  6. A relevance vector machine technique for the automatic detection of clustered microcalcifications (Honorable Mention Poster Award)

    Science.gov (United States)

    Wei, Liyang; Yang, Yongyi; Nishikawa, Robert M.

    2005-04-01

    Microcalcification (MC) clusters in mammograms can be important early signs of breast cancer in women. Accurate detection of MC clusters is an important but challenging problem. In this paper, we propose the use of a recently developed machine learning technique -- relevance vector machine (RVM) -- for automatic detection of MCs in digitized mammograms. RVM is based on Bayesian estimation theory, and as a feature it can yield a decision function that depends on only a very small number of so-called relevance vectors. We formulate MC detection as a supervised-learning problem, and use RVM to classify if an MC object is present or not at each location in a mammogram image. MC clusters are then identified by grouping the detected MC objects. The proposed method is tested using a database of 141 clinical mammograms, and compared with a support vector machine (SVM) classifier which we developed previously. The detection performance is evaluated using the free-response receiver operating characteristic (FROC) curves. It is demonstrated that the RVM classifier matches closely with the SVM classifier in detection performance, and does so with a much sparser kernel representation than the SVM classifier. Consequently, the RVM classifier greatly reduces the computational complexity, making it more suitable for real-time processing of MC clusters in mammograms.

  7. Empirical Studies On Machine Learning Based Text Classification Algorithms

    OpenAIRE

    Shweta C. Dharmadhikari; Maya Ingle; Parag Kulkarni

    2011-01-01

    Automatic classification of text documents has become an important research issue now days. Properclassification of text documents requires information retrieval, machine learning and Natural languageprocessing (NLP) techniques. Our aim is to focus on important approaches to automatic textclassification based on machine learning techniques viz. supervised, unsupervised and semi supervised.In this paper we present a review of various text classification approaches under machine learningparadig...

  8. MACHINE LEARNING TECHNIQUES APPLIED TO LIGNOCELLULOSIC ETHANOL IN SIMULTANEOUS HYDROLYSIS AND FERMENTATION

    Directory of Open Access Journals (Sweden)

    J. Fischer

    Full Text Available Abstract This paper investigates the use of machine learning (ML techniques to study the effect of different process conditions on ethanol production from lignocellulosic sugarcane bagasse biomass using S. cerevisiae in a simultaneous hydrolysis and fermentation (SHF process. The effects of temperature, enzyme concentration, biomass load, inoculum size and time were investigated using artificial neural networks, a C5.0 classification tree and random forest algorithms. The optimization of ethanol production was also evaluated. The results clearly depict that ML techniques can be used to evaluate the SHF (R2 between actual and model predictions higher than 0.90, absolute average deviation lower than 8.1% and RMSE lower than 0.80 and predict optimized conditions which are in close agreement with those found experimentally. Optimal conditions were found to be a temperature of 35 ºC, an SHF time of 36 h, enzymatic load of 99.8%, inoculum size of 29.5 g/L and bagasse concentration of 24.9%. The ethanol concentration and volumetric productivity for these conditions were 12.1 g/L and 0.336 g/L.h, respectively.

  9. Estimating Global Seafloor Total Organic Carbon Using a Machine Learning Technique and Its Relevance to Methane Hydrates

    Science.gov (United States)

    Lee, T. R.; Wood, W. T.; Dale, J.

    2017-12-01

    Empirical and theoretical models of sub-seafloor organic matter transformation, degradation and methanogenesis require estimates of initial seafloor total organic carbon (TOC). This subsurface methane, under the appropriate geophysical and geochemical conditions may manifest as methane hydrate deposits. Despite the importance of seafloor TOC, actual observations of TOC in the world's oceans are sparse and large regions of the seafloor yet remain unmeasured. To provide an estimate in areas where observations are limited or non-existent, we have implemented interpolation techniques that rely on existing data sets. Recent geospatial analyses have provided accurate accounts of global geophysical and geochemical properties (e.g. crustal heat flow, seafloor biomass, porosity) through machine learning interpolation techniques. These techniques find correlations between the desired quantity (in this case TOC) and other quantities (predictors, e.g. bathymetry, distance from coast, etc.) that are more widely known. Predictions (with uncertainties) of seafloor TOC in regions lacking direct observations are made based on the correlations. Global distribution of seafloor TOC at 1 x 1 arc-degree resolution was estimated from a dataset of seafloor TOC compiled by Seiter et al. [2004] and a non-parametric (i.e. data-driven) machine learning algorithm, specifically k-nearest neighbors (KNN). Built-in predictor selection and a ten-fold validation technique generated statistically optimal estimates of seafloor TOC and uncertainties. In addition, inexperience was estimated. Inexperience is effectively the distance in parameter space to the single nearest neighbor, and it indicates geographic locations where future data collection would most benefit prediction accuracy. These improved geospatial estimates of TOC in data deficient areas will provide new constraints on methane production and subsequent methane hydrate accumulation.

  10. 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…

  11. Machine learning analysis of binaural rowing sounds

    DEFF Research Database (Denmark)

    Johard, Leonard; Ruffaldi, Emanuele; Hoffmann, Pablo F.

    2011-01-01

    Techniques for machine hearing are increasing their potentiality due to new application domains. In this work we are addressing the analysis of rowing sounds in natural context for the purpose of supporting a training system based on virtual environments. This paper presents the acquisition metho...... methodology and the evaluation of different machine learning techniques for classifying rowing-sound data. We see that a combination of principal component analysis and shallow networks perform equally well as deep architectures, while being much faster to train.......Techniques for machine hearing are increasing their potentiality due to new application domains. In this work we are addressing the analysis of rowing sounds in natural context for the purpose of supporting a training system based on virtual environments. This paper presents the acquisition...

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

    Energy Technology Data Exchange (ETDEWEB)

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

    1994-12-01

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

  13. Machines and Metaphors

    Directory of Open Access Journals (Sweden)

    Ángel Martínez García-Posada

    2016-10-01

    Full Text Available The edition La ley del reloj. Arquitectura, máquinas y cultura moderna (Cátedra, Madrid, 2016 registers the useful paradox of the analogy between architecture and technique. Its author, the architect Eduardo Prieto, also a philosopher, professor and writer, acknowledges the obvious distance from machines to buildings, so great that it can only be solved using strange comparisons, since architecture does not move nor are the machines habitable, however throughout the book, from the origin of the metaphor of the machine, with clarity in his essay and enlightening erudition, he points out with certainty some concomitances of high interest, drawing throughout history a beautiful cartography of the fruitful encounter between organics and mechanics.

  14. Discrimination of plant root zone water status in greenhouse production based on phenotyping and machine learning techniques

    OpenAIRE

    Guo, Doudou; Juan, Jiaxiang; Chang, Liying; Zhang, Jingjin; Huang, Danfeng

    2017-01-01

    Plant-based sensing on water stress can provide sensitive and direct reference for precision irrigation system in greenhouse. However, plant information acquisition, interpretation, and systematical application remain insufficient. This study developed a discrimination method for plant root zone water status in greenhouse by integrating phenotyping and machine learning techniques. Pakchoi plants were used and treated by three root zone moisture levels, 40%, 60%, and 80% relative water content...

  15. Effect of machining fluid on the process performance of wire electrical discharge machining of nanocomposite ceramic

    Directory of Open Access Journals (Sweden)

    Zhang Chengmao

    2015-01-01

    Full Text Available Wire electric discharge machining (WEDM promise to be effective and economical techniques for the production of tools and parts from conducting ceramic blanks. However, the manufacturing of nanocomposite ceramics blanks with these processes is a long and costly process. This paper presents a new process of machining nanocomposite ceramics using WEDM. WEDM uses water based emulsion, polyvinyl alcohol and distilled water as the machining fluid. Machining fluid is a primary factor that affects the material removal rate and surface quality of WEDM. The effects of emulsion concentration, polyvinyl alcohol concentration and distilled water of the machining fluid on the process performance have been investigated.

  16. Statistical and machine learning approaches for network analysis

    CERN Document Server

    Dehmer, Matthias

    2012-01-01

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

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

    OpenAIRE

    Airola, Rasmus; Hager, Kristoffer

    2017-01-01

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

  18. An Interactive Web-based Learning System for Assisting Machining Technology Education

    Directory of Open Access Journals (Sweden)

    Min Jou

    2008-05-01

    Full Text Available The key technique of manufacturing methods is machining. The degree of technique of machining directly affects the quality of the product. Therefore, the machining technique is of primary importance in promoting student practice ability during the training process. Currently, practical training is applied in shop floor to discipline student’s practice ability. Much time and cost are used to teach these techniques. Particularly, computerized machines are continuously increasing in use. The development of educating engineers on computerized machines becomes much more difficult than with traditional machines. This is because of the limitation of the extremely expensive cost of teaching. The quality and quantity of teaching cannot always be promoted in this respect. The traditional teaching methods can not respond well to the needs of the future. Therefore, this research aims to the following topics; (1.Propose the teaching strategies for the students to learning machining processing planning through web-based learning system. (2.Establish on-line teaching material for the computer-aided manufacturing courses including CNC coding method, CNC simulation. (3.Develop the virtual machining laboratory to bring the machining practical training to web-based learning system. (4.Integrate multi-media and virtual laboratory in the developed e-learning web-based system to enhance the effectiveness of machining education through web-based system.

  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. The Identification of Hunger Behaviour of Lates Calcarifer through the Integration of Image Processing Technique and Support Vector Machine

    Science.gov (United States)

    Taha, Z.; Razman, M. A. M.; Adnan, F. A.; Ghani, A. S. Abdul; Majeed, A. P. P. Abdul; Musa, R. M.; Sallehudin, M. F.; Mukai, Y.

    2018-03-01

    Fish Hunger behaviour is one of the important element in determining the fish feeding routine, especially for farmed fishes. Inaccurate feeding routines (under-feeding or over-feeding) lead the fishes to die and thus, reduces the total production of fishes. The excessive food which is not eaten by fish will be dissolved in the water and thus, reduce the water quality (oxygen quantity in the water will be reduced). The reduction of oxygen (water quality) leads the fish to die and in some cases, may lead to fish diseases. This study correlates Barramundi fish-school behaviour with hunger condition through the hybrid data integration of image processing technique. The behaviour is clustered with respect to the position of the centre of gravity of the school of fish prior feeding, during feeding and after feeding. The clustered fish behaviour is then classified by means of a machine learning technique namely Support vector machine (SVM). It has been shown from the study that the Fine Gaussian variation of SVM is able to provide a reasonably accurate classification of fish feeding behaviour with a classification accuracy of 79.7%. The proposed integration technique may increase the usefulness of the captured data and thus better differentiates the various behaviour of farmed fishes.

  1. 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.

  2. Stochastic subset selection for learning with kernel machines.

    Science.gov (United States)

    Rhinelander, Jason; Liu, Xiaoping P

    2012-06-01

    Kernel machines have gained much popularity in applications of machine learning. Support vector machines (SVMs) are a subset of kernel machines and generalize well for classification, regression, and anomaly detection tasks. The training procedure for traditional SVMs involves solving a quadratic programming (QP) problem. The QP problem scales super linearly in computational effort with the number of training samples and is often used for the offline batch processing of data. Kernel machines operate by retaining a subset of observed data during training. The data vectors contained within this subset are referred to as support vectors (SVs). The work presented in this paper introduces a subset selection method for the use of kernel machines in online, changing environments. Our algorithm works by using a stochastic indexing technique when selecting a subset of SVs when computing the kernel expansion. The work described here is novel because it separates the selection of kernel basis functions from the training algorithm used. The subset selection algorithm presented here can be used in conjunction with any online training technique. It is important for online kernel machines to be computationally efficient due to the real-time requirements of online environments. Our algorithm is an important contribution because it scales linearly with the number of training samples and is compatible with current training techniques. Our algorithm outperforms standard techniques in terms of computational efficiency and provides increased recognition accuracy in our experiments. We provide results from experiments using both simulated and real-world data sets to verify our algorithm.

  3. 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.

  4. Massively collaborative machine learning

    NARCIS (Netherlands)

    Rijn, van J.N.

    2016-01-01

    Many scientists are focussed on building models. We nearly process all information we perceive to a model. There are many techniques that enable computers to build models as well. The field of research that develops such techniques is called Machine Learning. Many research is devoted to develop

  5. Relevance vector machine technique for the inverse scattering problem

    International Nuclear Information System (INIS)

    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. (general)

  6. Inverse Problems in Geodynamics Using Machine Learning Algorithms

    Science.gov (United States)

    Shahnas, M. H.; Yuen, D. A.; Pysklywec, R. N.

    2018-01-01

    During the past few decades numerical studies have been widely employed to explore the style of circulation and mixing in the mantle of Earth and other planets. However, in geodynamical studies there are many properties from mineral physics, geochemistry, and petrology in these numerical models. Machine learning, as a computational statistic-related technique and a subfield of artificial intelligence, has rapidly emerged recently in many fields of sciences and engineering. We focus here on the application of supervised machine learning (SML) algorithms in predictions of mantle flow processes. Specifically, we emphasize on estimating mantle properties by employing machine learning techniques in solving an inverse problem. Using snapshots of numerical convection models as training samples, we enable machine learning models to determine the magnitude of the spin transition-induced density anomalies that can cause flow stagnation at midmantle depths. Employing support vector machine algorithms, we show that SML techniques can successfully predict the magnitude of mantle density anomalies and can also be used in characterizing mantle flow patterns. The technique can be extended to more complex geodynamic problems in mantle dynamics by employing deep learning algorithms for putting constraints on properties such as viscosity, elastic parameters, and the nature of thermal and chemical anomalies.

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

    Science.gov (United States)

    Madnani, Nitin

    2010-01-01

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

  8. Hierarchical State Machines as Modular Horn Clauses

    Directory of Open Access Journals (Sweden)

    Pierre-Loïc Garoche

    2016-07-01

    Full Text Available In model based development, embedded systems are modeled using a mix of dataflow formalism, that capture the flow of computation, and hierarchical state machines, that capture the modal behavior of the system. For safety analysis, existing approaches rely on a compilation scheme that transform the original model (dataflow and state machines into a pure dataflow formalism. Such compilation often result in loss of important structural information that capture the modal behaviour of the system. In previous work we have developed a compilation technique from a dataflow formalism into modular Horn clauses. In this paper, we present a novel technique that faithfully compile hierarchical state machines into modular Horn clauses. Our compilation technique preserves the structural and modal behavior of the system, making the safety analysis of such models more tractable.

  9. 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.

  10. Machine learning modelling for predicting soil liquefaction susceptibility

    Directory of Open Access Journals (Sweden)

    P. Samui

    2011-01-01

    Full Text Available This study describes two machine learning techniques applied to predict liquefaction susceptibility of soil based on the standard penetration test (SPT data from the 1999 Chi-Chi, Taiwan earthquake. The first machine learning technique which uses Artificial Neural Network (ANN based on multi-layer perceptions (MLP that are trained with Levenberg-Marquardt backpropagation algorithm. The second machine learning technique uses the Support Vector machine (SVM that is firmly based on the theory of statistical learning theory, uses classification technique. ANN and SVM have been developed to predict liquefaction susceptibility using corrected SPT [(N160] and cyclic stress ratio (CSR. Further, an attempt has been made to simplify the models, requiring only the two parameters [(N160 and peck ground acceleration (amax/g], for the prediction of liquefaction susceptibility. The developed ANN and SVM models have also been applied to different case histories available globally. The paper also highlights the capability of the SVM over the ANN models.

  11. Lost in Translation: Methodological Considerations in Cross-Cultural Research

    Science.gov (United States)

    Pena, Elizabeth D.

    2007-01-01

    In cross-cultural child development research there is often a need to translate instruments and instructions to languages other than English. Typically, the translation process focuses on ensuring linguistic equivalence. However, establishment of linguistic equivalence through translation techniques is often not sufficient to guard against…

  12. A strategy for man-machine system development in process industries

    International Nuclear Information System (INIS)

    Wirstad, J.

    1986-12-01

    A framework for Man-Machine System design in process industry projects is reported. It is based in the Guidelines for the Design of Man-Machine interfaces which have been generated in cooperation within the European Workshop for Industrial Computer Systems (EWICS). The application of EWICS Guidelines in industrial projects is demonstrated by six User Scenarios, which represent typical projects from different industries, e.g. electrical power generation and distribution, water control, pulp and paper production, oil and gas production. In all these projects Man-Machine System design has been conducted. It is recommended in the report that each Company develops its set of Man-Machine Systems Standard techniques/procedures. At present there are several techniques/procedures available which, for moderate costs, can be adapted to specific Company conditions. A menu of such Man-Machine System techniques/procedures is presented. Means of estimating the costs and benefits of Man-Machine System design are also described. (author)

  13. Application of Social Network Analysis Techniques to Machine Translated Documents

    Science.gov (United States)

    2010-04-01

    Mandela, por la nueva Asamblea nacional sudafricana. La Comisión electoral independiente , una gigantesca maquinaria administrativa con unos 300.000...seat perpetration 2 surpassed 1 ultramoderno 1 recount 3 party 1 sellar 1 posting 1 suspended 1 urns 1 regions 1 president 2 south_african 1

  14. Ability of the Tightrope® and percutaneous lateral fabellar suture techniques to control cranial tibial translation.

    Science.gov (United States)

    Biskup, Jeffery J; Griffon, Dominique J; Socie, Mike; Schaeffer, David J; Kurath, Peter

    2014-11-01

    To compare the ability of the Tightrope® (TR) cranial cruciate ligament (CCL) technique, percutaneous lateral fabella suture (pLFS) technique, and normal CCL to control cranial tibial translation (CTT). In vitro biomechanical study. Cadaveric canine pelvic limbs (n = 18 pairs). Six small animal surgical residents (1 pair each) and a Diplomate of the American College of Veterinary Surgeons (10 pairs) performed TR and pLFS techniques on paired limbs. Two intact limb pairs served as controls. Limbs were assessed by palpation, radiographs, and dissection before mechanical testing of resistance to CTT. Forces resisted during displacement were compared between groups with a mixed ANOVA and post hoc tests. With 5 mm of displacement, the pLFS resisted 72 ± 45 N and the TR resisted 66 ± 48 N of load. The intact CCL resisted 400 ± 35 N. The intact CCL resisted displacement significantly more than either surgical technique. TR and pLFS had similar ability to resist CTT but neither restored the biomechanical properties of an intact CCL. © Copyright 2014 by The American College of Veterinary Surgeons.

  15. A Review of Current Machine Learning Techniques Used in Manufacturing Diagnosis

    OpenAIRE

    Ademujimi , Toyosi ,; Brundage , Michael ,; Prabhu , Vittaldas ,

    2017-01-01

    Part 6: Intelligent Diagnostics and Maintenance Solutions; International audience; Artificial intelligence applications are increasing due to advances in data collection systems, algorithms, and affordability of computing power. Within the manufacturing industry, machine learning algorithms are often used for improving manufacturing system fault diagnosis. This study focuses on a review of recent fault diagnosis applications in manufacturing that are based on several prominent machine learnin...

  16. Throughput centered prioritization of machines in transfer lines

    Energy Technology Data Exchange (ETDEWEB)

    Pascual, R., E-mail: rpascual@ing.puc.cl [Physical Asset Management Lab, Centro de Mineria, Pontificia Universidad Catolica de Chile, Av. Vicuna Mackenna 4860, Santiago (Chile); Godoy, D. [Physical Asset Management Lab, Centro de Mineria, Pontificia Universidad Catolica de Chile, Av. Vicuna Mackenna 4860, Santiago (Chile); Louit, D.M. [Komatsu Chile S.A., Av. Americo Vespucio 0631, Quilicura, Santiago (Chile)

    2011-10-15

    In an environment of scarce resources and complex production systems, prioritizing is key to confront the challenge of managing physical assets. In the literature, there exist a number of techniques to prioritize maintenance decisions that consider safety, technical and business perspectives. However, the effect of risk mitigating elements-such as intermediate buffers in production lines-on prioritization has not yet been investigated in depth. In this line, the work proposes a user-friendly graphical technique called the system efficiency influence diagram (SEID). Asset managers may use SEID to identify machines that have a greater impact on the system throughput, and thus set prioritized maintenance policies and/or redesign of buffers capacities. The tool provides insight to the analyst as it decomposes the influence of a given machine on the system throughput as a product of two elements: (1) system influence efficiency factor and (2) machine unavailability factor. We illustrate its applicability using three case studies: a four-machine transfer line, a vehicle assembly line, and an open-pit mining conveyor system. The results confirm that the machines with greater unavailability factors are not necessarily the most important for the efficiency of the production line, as it is the case when no intermediate buffers exist. As a decision aid tool, SEID emphasizes the need to move from a maintenance vision focused on machine availability, to a systems engineering perspective. - Highlights: > We propose a graphical technique to prioritize machines in production lines. > The tool is called 'system efficiency influence diagram' (SEID). > It helps setting prioritized maintenance policies and/or redesign of buffers. > The SEID technique focuses on system efficiency and throughput. > We illustrate its applicability using three case studies.

  17. Philips high tension generator (x-ray machine) testing for baby ebm (electron beam machine) project

    International Nuclear Information System (INIS)

    Norman Awalludin; Leo Kwee Wah; Abu Bakar Mhd Ghazali

    2005-01-01

    This paper describes the test of the HT system (from X-ray machine) for usage of the mini EBM (Electron Beam Machine). It consists the procedures of the installation, the safety procedures when deals with HT, modification of the system for testing purpose and the technique/method for testing the HT system. As a result, the voltage for the HT system and the electron gun (filament) current can be measured. Based on the results, suitability of the machine for baby EBM could be confirmed. (Author)

  18. Nontraditional machining processes research advances

    CERN Document Server

    2013-01-01

    Nontraditional machining employs processes that remove material by various methods involving thermal, electrical, chemical and mechanical energy or even combinations of these. Nontraditional Machining Processes covers recent research and development in techniques and processes which focus on achieving high accuracies and good surface finishes, parts machined without burrs or residual stresses especially with materials that cannot be machined by conventional methods. With applications to the automotive, aircraft and mould and die industries, Nontraditional Machining Processes explores different aspects and processes through dedicated chapters. The seven chapters explore recent research into a range of topics including laser assisted manufacturing, abrasive water jet milling and hybrid processes. Students and researchers will find the practical examples and new processes useful for both reference and for developing further processes. Industry professionals and materials engineers will also find Nontraditional M...

  19. Possibilities of radiation technique application in machine-building industry of Bulgaria

    International Nuclear Information System (INIS)

    Petrov, A.; Avramov, D.; Kostov, St.

    1979-01-01

    In last ten years, in development of machine-building industry, tendency has been outlined for creation of machines and constructions having minimum weight and elevated reliability from one side due to improvement of design and technology of production and from the other side due to application of materials with improved parameters. Solution of these problems is closely connected with application of the radiation methods. State-of-art of the radiation technology application in the machine-building industry is analyzed and mainly for investigation of wear resistance of friction machineparts. Use of spatial radioactive labelling in investigation of materials and application of radiation methods for optimization of technological processes in metallurgy, foundry and so on is considered. Estimation is give of perspectives of further growth of introduction of radiation methods in Bulgaria [ru

  20. SPEECH ACT OF ILTIFAT AND ITS INDONESIAN TRANSLATION PROBLEMS

    Directory of Open Access Journals (Sweden)

    Zaka Al Farisi

    2015-01-01

    Full Text Available Abstract: Iltifat (shifting speech act is distinctive and considered unique style of Arabic. It has potential errors when it is translated into Indonesian. Therefore, translation of iltifat speech act into another language can be an important issue. The objective of the study is to know translation procedures/techniques and ideology required in dealing with iltifat speech act. This research is directed at translation as a cognitive product of a translator. The data used in the present study were the corpus of Koranic verses that contain iltifat speech act along with their translation. Data analysis typically used descriptive-evaluative method with content analysis model. The data source of this research consisted of the Koran and its translation. The purposive sampling technique was employed, with the sample of the iltifat speech act contained in the Koran. The results showed that more than 60% of iltifat speech act were translated by using literal procedure. The significant number of literal translation of the verses asserts that the Ministry of Religious Affairs tended to use literal method of translation. In other words, the Koran translation made by the Ministry of Religious Affairs tended to be oriented to the source language in dealing with iltifat speech act. The number of the literal procedure used shows a tendency of foreignization ideology. Transitional pronouns contained in the iltifat speech act can be clearly translated when thick translations were used in the form of description in parentheses. In this case, explanation can be a choice in translating iltifat speech act.

  1. Enhanced Quality Control in Pharmaceutical Applications by Combining Raman Spectroscopy and Machine Learning Techniques

    Science.gov (United States)

    Martinez, J. C.; Guzmán-Sepúlveda, J. R.; Bolañoz Evia, G. R.; Córdova, T.; Guzmán-Cabrera, R.

    2018-06-01

    In this work, we applied machine learning techniques to Raman spectra for the characterization and classification of manufactured pharmaceutical products. Our measurements were taken with commercial equipment, for accurate assessment of variations with respect to one calibrated control sample. Unlike the typical use of Raman spectroscopy in pharmaceutical applications, in our approach the principal components of the Raman spectrum are used concurrently as attributes in machine learning algorithms. This permits an efficient comparison and classification of the spectra measured from the samples under study. This also allows for accurate quality control as all relevant spectral components are considered simultaneously. We demonstrate our approach with respect to the specific case of acetaminophen, which is one of the most widely used analgesics in the market. In the experiments, commercial samples from thirteen different laboratories were analyzed and compared against a control sample. The raw data were analyzed based on an arithmetic difference between the nominal active substance and the measured values in each commercial sample. The principal component analysis was applied to the data for quantitative verification (i.e., without considering the actual concentration of the active substance) of the difference in the calibrated sample. Our results show that by following this approach adulterations in pharmaceutical compositions can be clearly identified and accurately quantified.

  2. 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.

  3. Accurate Identification of Cancerlectins through Hybrid Machine Learning Technology.

    Science.gov (United States)

    Zhang, Jieru; Ju, Ying; Lu, Huijuan; Xuan, Ping; Zou, Quan

    2016-01-01

    Cancerlectins are cancer-related proteins that function as lectins. They have been identified through computational identification techniques, but these techniques have sometimes failed to identify proteins because of sequence diversity among the cancerlectins. Advanced machine learning identification methods, such as support vector machine and basic sequence features (n-gram), have also been used to identify cancerlectins. In this study, various protein fingerprint features and advanced classifiers, including ensemble learning techniques, were utilized to identify this group of proteins. We improved the prediction accuracy of the original feature extraction methods and classification algorithms by more than 10% on average. Our work provides a basis for the computational identification of cancerlectins and reveals the power of hybrid machine learning techniques in computational proteomics.

  4. Study on ultra-fine w-EDM with on-machine measurement-assisted

    International Nuclear Information System (INIS)

    Chen Shuntong; Yang Hongye

    2011-01-01

    The purpose of this study was to develop the on-machine measurement techniques so as to precisely fabricate micro intricate part using ultra-fine w-EDM. The measurement-assisted approach which employs an automatic optical inspection (AOI) is incorporated to ultra-fine w-EDM process to on-machine detect the machining error for next re-machining. The AOI acquires the image through a high resolution CCD device from the contour of the workpiece after roughing in order to further process and recognize the image for determining the residual. This facilitates the on-machine error detection and compensation re-machining. The micro workpiece and electrode are not repositioned during machining. A fabrication for a micro probe of 30-μm diameter is rapidly machined and verified successfully. Based on the proposed technique, on-machine measurement with AOI has been realized satisfactorily.

  5. Hubble Tarantula Treasury Project - VI. Identification of Pre-Main-Sequence Stars using Machine Learning techniques

    Science.gov (United States)

    Ksoll, Victor F.; Gouliermis, Dimitrios A.; Klessen, Ralf S.; Grebel, Eva K.; Sabbi, Elena; Anderson, Jay; Lennon, Daniel J.; Cignoni, Michele; de Marchi, Guido; Smith, Linda J.; Tosi, Monica; van der Marel, Roeland P.

    2018-05-01

    The Hubble Tarantula Treasury Project (HTTP) has provided an unprecedented photometric coverage of the entire star-burst region of 30 Doradus down to the half Solar mass limit. We use the deep stellar catalogue of HTTP to identify all the pre-main-sequence (PMS) stars of the region, i.e., stars that have not started their lives on the main-sequence yet. The photometric distinction of these stars from the more evolved populations is not a trivial task due to several factors that alter their colour-magnitude diagram positions. The identification of PMS stars requires, thus, sophisticated statistical methods. We employ Machine Learning Classification techniques on the HTTP survey of more than 800,000 sources to identify the PMS stellar content of the observed field. Our methodology consists of 1) carefully selecting the most probable low-mass PMS stellar population of the star-forming cluster NGC2070, 2) using this sample to train classification algorithms to build a predictive model for PMS stars, and 3) applying this model in order to identify the most probable PMS content across the entire Tarantula Nebula. We employ Decision Tree, Random Forest and Support Vector Machine classifiers to categorise the stars as PMS and Non-PMS. The Random Forest and Support Vector Machine provided the most accurate models, predicting about 20,000 sources with a candidateship probability higher than 50 percent, and almost 10,000 PMS candidates with a probability higher than 95 percent. This is the richest and most accurate photometric catalogue of extragalactic PMS candidates across the extent of a whole star-forming complex.

  6. 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%.

  7. Electrical machines diagnosis

    CERN Document Server

    Trigeassou, Jean-Claude

    2013-01-01

    Monitoring and diagnosis of electrical machine faults is a scientific and economic issue which is motivated by objectives for reliability and serviceability in electrical drives.This book provides a survey of the techniques used to detect the faults occurring in electrical drives: electrical, thermal and mechanical faults of the electrical machine, faults of the static converter and faults of the energy storage unit.Diagnosis of faults occurring in electrical drives is an essential part of a global monitoring system used to improve reliability and serviceability. This diagnosis is perf

  8. Efficiency improvement of the maximum power point tracking for PV systems using support vector machine technique

    International Nuclear Information System (INIS)

    Kareim, Ameer A; Mansor, Muhamad Bin

    2013-01-01

    The aim of this paper is to improve efficiency of maximum power point tracking (MPPT) for PV systems. The Support Vector Machine (SVM) was proposed to achieve the MPPT controller. The theoretical, the perturbation and observation (P and O), and incremental conductance (IC) algorithms were used to compare with proposed SVM algorithm. MATLAB models for PV module, theoretical, SVM, P and O, and IC algorithms are implemented. The improved MPPT uses the SVM method to predict the optimum voltage of the PV system in order to extract the maximum power point (MPP). The SVM technique used two inputs which are solar radiation and ambient temperature of the modeled PV module. The results show that the proposed SVM technique has less Root Mean Square Error (RMSE) and higher efficiency than P and O and IC methods.

  9. Higgs Machine Learning Challenge 2014

    CERN Document Server

    Olivier, A-P; Bourdarios, C ; LAL / Orsay; Goldfarb, S ; University of Michigan

    2014-01-01

    High Energy Physics (HEP) has been using Machine Learning (ML) techniques such as boosted decision trees (paper) and neural nets since the 90s. These techniques are now routinely used for difficult tasks such as the Higgs boson search. Nevertheless, formal connections between the two research fields are rather scarce, with some exceptions such as the AppStat group at LAL, founded in 2006. In collaboration with INRIA, AppStat promotes interdisciplinary research on machine learning, computational statistics, and high-energy particle and astroparticle physics. We are now exploring new ways to improve the cross-fertilization of the two fields by setting up a data challenge, following the footsteps of, among others, the astrophysics community (dark matter and galaxy zoo challenges) and neurobiology (connectomics and decoding the human brain). The organization committee consists of ATLAS physicists and machine learning researchers. The Challenge will run from Monday 12th to September 2014.

  10. Proses dan Hasil Penerjemahan Mahasiswa (Studi Kasus Pada Mahasiswa Translation Theory and Practice Di STAIN Pamekasan

    Directory of Open Access Journals (Sweden)

    Mosleh Habibullah

    2015-05-01

    Full Text Available Research focus consists of: What method students use in process translating text from native language (BSu to target language (BSa and what process of mistake occasionally occurs in translating observed from the result of text translation BSu to BSa. This research employs qualitative approach by descriptive analysis paradigm. This data collecting procedure includes documentation, interview, and observation. Data validity by: data analysis through systematic arrangement and trace, interview transcript, field note, conclusion and verification, triangulation method. The result of research found: 1. Method which collage students use in translating process is placed in two categories, those are translation method pressed on BSu (NL: word by word translation, literal translation, faithful translation, and semantic translation, BSa (TL: press on: adaptation, free translation, idiomatic translation, and communicative translation. 2. Translation technique in this alternative step answers problem formulated on research problem, concerning translation procedure of religion text which is done by college students Translation Practice Semester VI from English to Indonesian, namely borrowing, loan translation (claque, literal translation, transposition, modulation, equivalence, and adaptation. 3 language mistake analyses in translation presented in this paper is study which analyze one paragraph from text 1 until text 4 above. Furthermore, comprehending about definition of translation error is language error. Language error can happen in every linguistic level because language produced by word, sentence and meaning, error which needs to analyze covered phonology, morphology, syntactic and semantic.Based on the result, it can be concluded that translating process done by college students is good wholly. Technique 1: using literal translation method. Technique 2: free translation method. Technique 3: adaptation method. Technique 4: unacceptable by the reader

  11. Machining of AISI D2 Tool Steel with Multiple Hole Electrodes by EDM Process

    Science.gov (United States)

    Prasad Prathipati, R.; Devuri, Venkateswarlu; Cheepu, Muralimohan; Gudimetla, Kondaiah; Uzwal Kiran, R.

    2018-03-01

    In recent years, with the increasing of technology the demand for machining processes is increasing for the newly developed materials. The conventional machining processes are not adequate to meet the accuracy of the machining of these materials. The non-conventional machining processes of electrical discharge machining is one of the most efficient machining processes is being widely used to machining of high accuracy products of various industries. The optimum selection of process parameters is very important in machining processes as that of an electrical discharge machining as they determine surface quality and dimensional precision of the obtained parts, even though time consumption rate is higher for machining of large dimension features. In this work, D2 high carbon and chromium tool steel has been machined using electrical discharge machining with the multiple hole electrode technique. The D2 steel has several applications such as forming dies, extrusion dies and thread rolling. But the machining of this tool steel is very hard because of it shard alloyed elements of V, Cr and Mo which enhance its strength and wear properties. However, the machining is possible by using electrical discharge machining process and the present study implemented a new technique to reduce the machining time using a multiple hole copper electrode. In this technique, while machining with multiple holes electrode, fin like projections are obtained, which can be removed easily by chipping. Then the finishing is done by using solid electrode. The machining time is reduced to around 50% while using multiple hole electrode technique for electrical discharge machining.

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

    KAUST Repository

    Harrou, Fouzi; Ramahaleomiarantsoa, Jacques F.; Nounou, Mohamed N.; Nounou, Hazem N.

    2016-01-01

    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

  13. Throughput centered prioritization of machines in transfer lines

    International Nuclear Information System (INIS)

    Pascual, R.; Godoy, D.; Louit, D.M.

    2011-01-01

    In an environment of scarce resources and complex production systems, prioritizing is key to confront the challenge of managing physical assets. In the literature, there exist a number of techniques to prioritize maintenance decisions that consider safety, technical and business perspectives. However, the effect of risk mitigating elements-such as intermediate buffers in production lines-on prioritization has not yet been investigated in depth. In this line, the work proposes a user-friendly graphical technique called the system efficiency influence diagram (SEID). Asset managers may use SEID to identify machines that have a greater impact on the system throughput, and thus set prioritized maintenance policies and/or redesign of buffers capacities. The tool provides insight to the analyst as it decomposes the influence of a given machine on the system throughput as a product of two elements: (1) system influence efficiency factor and (2) machine unavailability factor. We illustrate its applicability using three case studies: a four-machine transfer line, a vehicle assembly line, and an open-pit mining conveyor system. The results confirm that the machines with greater unavailability factors are not necessarily the most important for the efficiency of the production line, as it is the case when no intermediate buffers exist. As a decision aid tool, SEID emphasizes the need to move from a maintenance vision focused on machine availability, to a systems engineering perspective. - Highlights: → We propose a graphical technique to prioritize machines in production lines. → The tool is called 'system efficiency influence diagram' (SEID). → It helps setting prioritized maintenance policies and/or redesign of buffers. → The SEID technique focuses on system efficiency and throughput. → We illustrate its applicability using three case studies.

  14. Machining and characterization of self-reinforced polymers

    Science.gov (United States)

    Deepa, A.; Padmanabhan, K.; Kuppan, P.

    2017-11-01

    This Paper focuses on obtaining the mechanical properties and the effect of the different machining techniques on self-reinforced composites sample and to derive the best machining method with remarkable properties. Each sample was tested by the Tensile and Flexural tests, fabricated using hot compaction test and those loads were calculated. These composites are machined using conventional methods because of lack of advanced machinery in most of the industries. The advanced non-conventional methods like Abrasive water jet machining were used. These machining techniques are used to get the better output for the composite materials with good mechanical properties compared to conventional methods. But the use of non-conventional methods causes the changes in the work piece, tool properties and more economical compared to the conventional methods. Finding out the best method ideal for the designing of these Self Reinforced Composites with and without defects and the use of Scanning Electron Microscope (SEM) analysis for the comparing the microstructure of the PP and PE samples concludes our process.

  15. Exploration of machine learning techniques in predicting multiple sclerosis disease course

    OpenAIRE

    Zhao, Yijun; Healy, Brian C.; Rotstein, Dalia; Guttmann, Charles R. G.; Bakshi, Rohit; Weiner, Howard L.; Brodley, Carla E.; Chitnis, Tanuja

    2017-01-01

    Objective To explore the value of machine learning methods for predicting multiple sclerosis disease course. Methods 1693 CLIMB study patients were classified as increased EDSS?1.5 (worsening) or not (non-worsening) at up to five years after baseline visit. Support vector machines (SVM) were used to build the classifier, and compared to logistic regression (LR) using demographic, clinical and MRI data obtained at years one and two to predict EDSS at five years follow-up. Results Baseline data...

  16. Translation Theory 'Translated'

    DEFF Research Database (Denmark)

    Wæraas, Arild; Nielsen, Jeppe

    2016-01-01

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

  17. Dynamic Modal Analysis of Vertical Machining Centre Components

    OpenAIRE

    Anayet U. Patwari; Waleed F. Faris; A. K. M. Nurul Amin; S. K. Loh

    2009-01-01

    The paper presents a systematic procedure and details of the use of experimental and analytical modal analysis technique for structural dynamic evaluation processes of a vertical machining centre. The main results deal with assessment of the mode shape of the different components of the vertical machining centre. The simplified experimental modal analysis of different components of milling machine was carried out. This model of the different machine tool's structure is made by design software...

  18. Monitoring machining conditions by analyzing cutting force vibration

    Energy Technology Data Exchange (ETDEWEB)

    Piao, Chun Guang; Kim, Ju Wan; Kim, Jin Oh; Shin, Yoan [Soongsl University, Seoul (Korea, Republic of)

    2015-09-15

    This paper deals with an experimental technique for monitoring machining conditions by analyzing cutting-force vibration measured at a milling machine. This technique is based on the relationship of the cutting-force vibrations with the feed rate and cutting depth as reported earlier. The measurement system consists of dynamic force transducers and a signal amplifier. The analysis system includes an oscilloscope and a computer with a LabVIEW program. Experiments were carried out at various feed rates and cutting depths, while the rotating speed was kept constant. The magnitude of the cutting force vibration component corresponding to the number of cutting edges multiplied by the frequency of rotation was linearly correlated with the machining conditions. When one condition of machining is known, another condition can be identified by analyzing the cutting-force vibration.

  19. Monitoring machining conditions by analyzing cutting force vibration

    International Nuclear Information System (INIS)

    Piao, Chun Guang; Kim, Ju Wan; Kim, Jin Oh; Shin, Yoan

    2015-01-01

    This paper deals with an experimental technique for monitoring machining conditions by analyzing cutting-force vibration measured at a milling machine. This technique is based on the relationship of the cutting-force vibrations with the feed rate and cutting depth as reported earlier. The measurement system consists of dynamic force transducers and a signal amplifier. The analysis system includes an oscilloscope and a computer with a LabVIEW program. Experiments were carried out at various feed rates and cutting depths, while the rotating speed was kept constant. The magnitude of the cutting force vibration component corresponding to the number of cutting edges multiplied by the frequency of rotation was linearly correlated with the machining conditions. When one condition of machining is known, another condition can be identified by analyzing the cutting-force vibration

  20. Machine learning in heart failure: ready for prime time.

    Science.gov (United States)

    Awan, Saqib Ejaz; Sohel, Ferdous; Sanfilippo, Frank Mario; Bennamoun, Mohammed; Dwivedi, Girish

    2018-03-01

    The aim of this review is to present an up-to-date overview of the application of machine learning methods in heart failure including diagnosis, classification, readmissions and medication adherence. Recent studies have shown that the application of machine learning techniques may have the potential to improve heart failure outcomes and management, including cost savings by improving existing diagnostic and treatment support systems. Recently developed deep learning methods are expected to yield even better performance than traditional machine learning techniques in performing complex tasks by learning the intricate patterns hidden in big medical data. The review summarizes the recent developments in the application of machine and deep learning methods in heart failure management.

  1. Sequencing for Batch Production in a Group Flowline Machine Shop ...

    African Journals Online (AJOL)

    The purpose of the paper is to develop a useful technique for sequencing batches of components through machine shops arranged under the group flowline production system. The approach is to apply a modified version of Petrov's group flowline technique for machining components which follow a unidirectional route.

  2. Diamond turning on advanced machine tool prototypes

    International Nuclear Information System (INIS)

    Arnold, J.B.; Steger, P.J.

    1975-01-01

    Specular-quality metal mirrors are being machined for use in laser optical systems. The fabrication process incorporates special quality diamond tools and specially constructed turning machines. The machines are controlled by advanced control techniques and are housed in an environmentally controlled laboratory to insure ultimate machine stability and positional accuracy. The materials from which these mirrors are primarily produced are the softer face-center-cubic structure metals, such as gold, silver, copper, and aluminum. Mirror manufacturing by the single-point diamond machining process is in an early stage of development, but it is anticipated that this method will become the most economical way for producing high-quality metal mirrors. (U.S.)

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

    International Nuclear Information System (INIS)

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

    1995-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2000-01-10

    A point card compatible automatic vending machine for canned drinks is developed, which provides drink manufacturers with a powerful tool to acquire selling sites and attract consumers. Since the machine is equipped with a device to handle point cards, regular customers have increased and sales have picked up. A point card issuing device is also installed, and the new machine issues a point card whenever a customer wants. The drink manufacturers are evaluating high of the vending machine because it will contribute to the diffusion of the point card system and because a sales promotion campaign may be conducted through the vending machine for instance by exchanging a fully marked card with a giveaway on the spot. In the future, a bill validator (paper money identifier) will be integrated even with small size machines for the diffusion of point card compatible machines. (translated by NEDO)

  5. 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

  6. Computer vision and machine learning for archaeology

    NARCIS (Netherlands)

    van der Maaten, L.J.P.; Boon, P.; Lange, G.; Paijmans, J.J.; Postma, E.

    2006-01-01

    Until now, computer vision and machine learning techniques barely contributed to the archaeological domain. The use of these techniques can support archaeologists in their assessment and classification of archaeological finds. The paper illustrates the use of computer vision techniques for

  7. Proactive condition monitoring of low-speed machines

    CERN Document Server

    Stamboliska, Zhaklina; Moczko, Przemyslaw

    2015-01-01

    This book broadens readers’ understanding of proactive condition monitoring of low-speed machines in heavy industries. It focuses on why low-speed machines are different than others and how maintenance of these machines should be implemented with particular attention. The authors explain the best available monitoring techniques for various equipment and the principle of how to get proactive information from each technique. They further put forward possible strategies for application of FEM for detection of faults and technical assessment of machinery. Implementation phases are described and industrial case-studies of proactive condition monitoring are included. Proactive Condition Monitoring of Low-Speed Machines is an essential resource for engineers and technical managers across a range of industries as well as design engineers working in industrial product development. This book also: ·         Explains the practice of proactive condition monitoring and illustrates implementation phases ·   ...

  8. Using Machine Learning to Predict Student Performance

    OpenAIRE

    Pojon, Murat

    2017-01-01

    This thesis examines the application of machine learning algorithms to predict whether a student will be successful or not. The specific focus of the thesis is the comparison of machine learning methods and feature engineering techniques in terms of how much they improve the prediction performance. Three different machine learning methods were used in this thesis. They are linear regression, decision trees, and naïve Bayes classification. Feature engineering, the process of modification ...

  9. On-machine measurement of a slow slide servo diamond-machined 3D microstructure with a curved substrate

    International Nuclear Information System (INIS)

    Zhu, Wu-Le; Yang, Shunyao; Ju, Bing-Feng; Jiang, Jiacheng; Sun, Anyu

    2015-01-01

    A scanning tunneling microscope-based multi-axis measuring system is specially developed for the on-machine measurement of three-dimensional (3D) microstructures, to address the quality control difficulty with the traditional off-line measurement process. A typical 3D microstructure of the curved compound eye was diamond-machined by the slow slide servo technique, and then the whole surface was on-machine scanned three-dimensionally based on the tip-tracking strategy by utilizing a spindle, two linear motion stages, and an additional rotary stage. The machined surface profile and its shape deviation were accurately measured on-machine. The distortion of imaged ommatidia on the curved substrate was distinctively evaluated based on the characterized points extracted from the measured surface. Furthermore, the machining errors were investigated in connection with the on-machine measured surface and its characteristic parameters. Through experiments, the proposed measurement system is demonstrated to feature versatile on-machine measurement of 3D microstructures with a curved substrate, which is highly meaningful for quality control in the fabrication field. (paper)

  10. Materiality of a simulation: Scratch reading machine, 1931

    Directory of Open Access Journals (Sweden)

    Craig Saper

    2009-12-01

    Full Text Available Using Bob Brown's reading machine and the prepared texts for his machine, called readies, both designed in 1930, as an example of scratch turntablist techniques, suggests an alternative to narrow definitions of literacy and new ways to appreciate the history of scratch techniques. Brown's machine resembles the turntablist’s ability to rapidly shift reading (its direction, speed, and repetition rather than slowly flipping the pages of a book. Punctuation marks, in the readies, become visual analogies. For movement we see em-dashes (— that also, by definition, indicate that the sentence was interrupted or cut short. The old uses of punctuation, such as employment of periods to mark the end of a sentence, disappear. The result looks like a script for a turntablist’s performance, and dj Herc starts to sound like a reading teacher. An online simulation of Brown's machine, http://www.readies.org, reproduce, or approximate, the motion, scratch, jerking, flickering, and visual effects produced or illuminated with the machine. Those supplemental aspects of reading are always already part of reading. The supplement (movement, visuality, mechanicity to traditional notions of literacy usually remain part of an implicate process. The reading machine and scratch techniques are not simply a new conduit for the same supposedly natural process. The scratch reading highlights what Jacques Derrida calls the "virtual multimedia" (of reading print on paper. The increasing prevalence, even omnipresent and [to some critics] epidemic, use of text(ing machines, something outside or beside traditional literacy, the scratch-meaning becomes foregrounded. Brown's machine puts the natural process of reading under erasure or scratch (simply by adjusting the speed, direction, and layout. dj Herc did the same for music.

  11. Introducing Translation Studies:a Case Study of the Text of an Auto Company's Market Strategy%Introducing Translation Studies: a Case Study of the Text of an Auto Company's Market Strategy

    Institute of Scientific and Technical Information of China (English)

    盛洁; 谢玖兰

    2017-01-01

    This paper starts with the necessity of the translation from English to Chinese and the other way around in auto indus?try. Then, talks about the nature of translation and translating, translation standards, translation strategies and discusses the charac?teristics of the texts of the auto company's strategy, translation techniques and at last make the conclusion.

  12. Reliability analysis in intelligent machines

    Science.gov (United States)

    Mcinroy, John E.; Saridis, George N.

    1990-01-01

    Given an explicit task to be executed, an intelligent machine must be able to find the probability of success, or reliability, of alternative control and sensing strategies. By using concepts for information theory and reliability theory, new techniques for finding the reliability corresponding to alternative subsets of control and sensing strategies are proposed such that a desired set of specifications can be satisfied. The analysis is straightforward, provided that a set of Gaussian random state variables is available. An example problem illustrates the technique, and general reliability results are presented for visual servoing with a computed torque-control algorithm. Moreover, the example illustrates the principle of increasing precision with decreasing intelligence at the execution level of an intelligent machine.

  13. Working with corpora in the translation classroom

    Directory of Open Access Journals (Sweden)

    Ralph Krüger

    2012-10-01

    Full Text Available This article sets out to illustrate possible applications of electronic corpora in the translation classroom. Starting with a survey of corpus use within corpus-based translation studies, the didactic value of corpora in the translation classroom and their epistemic value in translation teaching and practice will be elaborated. A typology of translation practice-oriented corpora will be presented, and the use of corpora in translation will be positioned within two general models of translation competence. Special consideration will then be given to the design and application of so-called Do-it-yourself (DIY corpora, which are compiled ad hoc with the aim of completing a specific translation task. In this context, possible sources for retrieving corpus texts will be presented and evaluated and it will be argued that, owing to time and availability constraints in real-life translation, the Internet should be used as a major source of corpus data. After a brief discussion of possible Internet research techniques for targeted and quality-focused corpus compilation, the possible use of the Internet itself as a macro-corpus will be elaborated. The article concludes with a brief presentation of corpus use in translation teaching in the MA in Specialised Translation Programme offered at Cologne University of Applied Sciences, Germany.

  14. Association Rule-based Predictive Model for Machine Failure in Industrial Internet of Things

    Science.gov (United States)

    Kwon, Jung-Hyok; Lee, Sol-Bee; Park, Jaehoon; Kim, Eui-Jik

    2017-09-01

    This paper proposes an association rule-based predictive model for machine failure in industrial Internet of things (IIoT), which can accurately predict the machine failure in real manufacturing environment by investigating the relationship between the cause and type of machine failure. To develop the predictive model, we consider three major steps: 1) binarization, 2) rule creation, 3) visualization. The binarization step translates item values in a dataset into one or zero, then the rule creation step creates association rules as IF-THEN structures using the Lattice model and Apriori algorithm. Finally, the created rules are visualized in various ways for users’ understanding. An experimental implementation was conducted using R Studio version 3.3.2. The results show that the proposed predictive model realistically predicts machine failure based on association rules.

  15. Machine-learning techniques for family demography: an application of random forests to the analysis of divorce determinants in Germany

    OpenAIRE

    Arpino, Bruno; Le Moglie, Marco; Mencarini, Letizia

    2018-01-01

    Demographers often analyze the determinants of life-course events with parametric regression-type approaches. Here, we present a class of nonparametric approaches, broadly defined as machine learning (ML) techniques, and discuss advantages and disadvantages of a popular type known as random forest. We argue that random forests can be useful either as a substitute, or a complement, to more standard parametric regression modeling. Our discussion of random forests is intuitive and...

  16. An analysis of a digital variant of the Trail Making Test using machine learning techniques.

    Science.gov (United States)

    Dahmen, Jessamyn; Cook, Diane; Fellows, Robert; Schmitter-Edgecombe, Maureen

    2017-01-01

    The goal of this work is to develop a digital version of a standard cognitive assessment, the Trail Making Test (TMT), and assess its utility. This paper introduces a novel digital version of the TMT and introduces a machine learning based approach to assess its capabilities. Using digital Trail Making Test (dTMT) data collected from (N = 54) older adult participants as feature sets, we use machine learning techniques to analyze the utility of the dTMT and evaluate the insights provided by the digital features. Predicted TMT scores correlate well with clinical digital test scores (r = 0.98) and paper time to completion scores (r = 0.65). Predicted TICS exhibited a small correlation with clinically derived TICS scores (r = 0.12 Part A, r = 0.10 Part B). Predicted FAB scores exhibited a small correlation with clinically derived FAB scores (r = 0.13 Part A, r = 0.29 for Part B). Digitally derived features were also used to predict diagnosis (AUC of 0.65). Our findings indicate that the dTMT is capable of measuring the same aspects of cognition as the paper-based TMT. Furthermore, the dTMT's additional data may be able to help monitor other cognitive processes not captured by the paper-based TMT alone.

  17. Strategies for Translating Vocative Texts

    Directory of Open Access Journals (Sweden)

    Olga COJOCARU

    2014-12-01

    Full Text Available The paper deals with the linguistic and cultural elements of vocative texts and the techniques used in translating them by giving some examples of texts that are typically vocative (i.e. advertisements and instructions for use. Semantic and communicative strategies are popular in translation studies and each of them has its own advantages and disadvantages in translating vocative texts. The advantage of semantic translation is that it takes more account of the aesthetic value of the SL text, while communicative translation attempts to render the exact contextual meaning of the original text in such a way that both content and language are readily acceptable and comprehensible to the readership. Focus is laid on the strategies used in translating vocative texts, strategies that highlight and introduce a cultural context to the target audience, in order to achieve their overall purpose, that is to sell or persuade the reader to behave in a certain way. Thus, in order to do that, a number of advertisements from the field of cosmetics industry and electronic gadgets were selected for analysis. The aim is to gather insights into vocative text translation and to create new perspectives on this field of research, now considered a process of innovation and diversion, especially in areas as important as economy and marketing.

  18. Machine Learning of Musical Gestures

    OpenAIRE

    Caramiaux, Baptiste; Tanaka, Atau

    2013-01-01

    We present an overview of machine learning (ML) techniques and theirapplication in interactive music and new digital instruments design. We firstgive to the non-specialist reader an introduction to two ML tasks,classification and regression, that are particularly relevant for gesturalinteraction. We then present a review of the literature in current NIMEresearch that uses ML in musical gesture analysis and gestural sound control.We describe the ways in which machine learning is useful for cre...

  19. 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

  20. Translational Bioinformatics and Clinical Research (Biomedical) Informatics.

    Science.gov (United States)

    Sirintrapun, S Joseph; Zehir, Ahmet; Syed, Aijazuddin; Gao, JianJiong; Schultz, Nikolaus; Cheng, Donavan T

    2015-06-01

    Translational bioinformatics and clinical research (biomedical) informatics are the primary domains related to informatics activities that support translational research. Translational bioinformatics focuses on computational techniques in genetics, molecular biology, and systems biology. Clinical research (biomedical) informatics involves the use of informatics in discovery and management of new knowledge relating to health and disease. This article details 3 projects that are hybrid applications of translational bioinformatics and clinical research (biomedical) informatics: The Cancer Genome Atlas, the cBioPortal for Cancer Genomics, and the Memorial Sloan Kettering Cancer Center clinical variants and results database, all designed to facilitate insights into cancer biology and clinical/therapeutic correlations. Copyright © 2015 Elsevier Inc. All rights reserved.

  1. 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.

    2018-04-01

    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

  2. Machinability studies of infrared window materials and metals

    International Nuclear Information System (INIS)

    Arnold, J.B.; Morris, T.O.; Sladky, R.E.; Steger, P.J.

    1976-01-01

    Diamond machining of materials for optical applications is becoming an important fabrication process. Development work in material-removal technology to better understand the mechanics of the diamond-turning process, its limitations, and applications is described. The technique is presently limited to a select group of metals, most of which are of a face-center-cubic crystal structure. Machinability studies were done which were designed to better understand diamond compatibility and thus expand the range of applicable materials. Nonconventional methods such as ultrasonic tool stimulation were investigated. Work done to determine the machinability of infrared window materials indicates that this is a viable fabrication technique for many materials, although additional effort is needed to optimize the process for particular materials

  3. Finite Element Method in Machining Processes

    CERN Document Server

    Markopoulos, Angelos P

    2013-01-01

    Finite Element Method in Machining Processes provides a concise study on the way the Finite Element Method (FEM) is used in the case of manufacturing processes, primarily in machining. The basics of this kind of modeling are detailed to create a reference that will provide guidelines for those who start to study this method now, but also for scientists already involved in FEM and want to expand their research. A discussion on FEM, formulations and techniques currently in use is followed up by machining case studies. Orthogonal cutting, oblique cutting, 3D simulations for turning and milling, grinding, and state-of-the-art topics such as high speed machining and micromachining are explained with relevant examples. This is all supported by a literature review and a reference list for further study. As FEM is a key method for researchers in the manufacturing and especially in the machining sector, Finite Element Method in Machining Processes is a key reference for students studying manufacturing processes but al...

  4. Advanced Digitization Techniques in Retrieval of Mechanism and Machine Science Resources

    Science.gov (United States)

    Lovasz, E.-Ch.; Gruescu, C. M.; Ciupe, V.; Carabas, I.; Margineanu, D.; Maniu, I.; Dehelean, N.

    The European project thinkMOTION works on the purpose of retrieving all-times content regarding mechanisms and machine science by means of creating a digital library, accessible to a broad public through the portal Europeana. DMG-Lib is intended to display the development in the field, from its very beginning up to now days. There is a large range of significant objects available, physically very heterogeneous and needing all to be digitized. The paper presents the workflow, the equipments and specific techniques used in digitization of documents featuring very different characteristics (size, texture, color, degree of preservation, resolution and so on). Once the workflow established on very detailed steps, the development of the workstation is treated. Special equipments designed and assembled at Universitatea "Politehnica" Timisoara are presented. A large series of software applications, including original programs, work for digitization itself, processing of images, management of files, automatic optoelectronic control of capture, storage of information in different stages of processing. An illustrating example is explained, showing the steps followed in order to obtain a clear, high-resolution image from an old original document (very valuable as a historical proof but very poor in quality regarding clarity, contrast and resolution).

  5. Mathematically modelling the power requirement for a vertical shaft mowing machine

    Directory of Open Access Journals (Sweden)

    Jorge Simón Pérez de Corcho Fuentes

    2008-09-01

    Full Text Available This work describes a mathematical model for determining the power demand for a vertical shaft mowing machine, particularly taking into account the influence of speed on cutting power, which is different from that of other models of mowers. The influence of the apparatus’ rotation and translation speeds was simulated in determining power demand. The results showed that no chan-ges in cutting power were produced by varying the knives’ angular speed (if translation speed was constant, while cutting power became increased if translation speed was increased. Variations in angular speed, however, influenced other parameters deter-mining total power demand. Determining this vertical shaft mower’s cutting pattern led to obtaining good crop stubble quality at the mower’s lower rotation speed, hence reducing total energy requirements.

  6. The Equivalence of Translated Songs Lyrics and their Effects - The Case of Translated Ecclesial Songs

    Directory of Open Access Journals (Sweden)

    S. Suharto

    2015-01-01

    Full Text Available This study aimed at describing the equivalence of eclessial song lyrics, which belong to the content word, the meaning of the sentences and their effect on church songs. The method used in this study is descriptive and qualitative by using music, language, and interdiciline approach. The data collection method used questionnaires technique, interview, documents and content analysis. The data used are 5 documents of songs chosen purposively as the primary data. Based on the data being analyzed, the results of this study were: 1 The translated content word located in the same bars and equivalent was around 27.07%, the translated content word located in the same bars, but not equivalent was 18.34%, the translated content word located in the different bars, but equivalent was 11.79%, the translated content word located in the different bars and not equivalent was 2.62%, and the untranslated words were 4.17%. 2 The translation of equivalence beautiful lyrics showed the beauty of the song was equivalent at 17.02%, the beauty of the song was less equivalent at 29.78%, the beauty of the song was not equivalent of 61.70%. 3. The differences of structure caused the incorrect dictions or choice of words and missing words in the translated lyrics.

  7. TRANSLATING ECONOMICS TEXTBOOKS: A CASE STUDY OF EPISTEMICIDE

    Directory of Open Access Journals (Sweden)

    KARNEDI

    2015-01-01

    Full Text Available As part of discourse in the social sciences, economics textbooks written in English in which knowledge has been transferred to other languages through translation have brought a certain impact on both the target language and the target culture. In terms of ideology, this article argues about the hegemonic status of the dominant language or culture that creates socalled epistemicide or the erosion of knowledge, partly due to translation strategies adopted by the translator. Investigation is done using the corpusbased approach, theories of translation strategies and the comparative model. The study reveals that the translator in the macro-level text adopts the ideology of foreignising strategy rather than domesticating strategy when translating an economics textbook from English into Indonesian. This is supported by the use of the number of the source language-orientated translation techniques leading to two translation methods (i.e. literal translation and faithful translation adopted in the micro-level text. This research strongly supports another relevant study pertaining to the globalisation of knowledge through translation and also the translation theories of equivalence (i.e. overt and covert translation. The research findings also have some pedagogical implications on teaching English for Specific Purposes in higher education.

  8. Heart Failure: Diagnosis, Severity Estimation and Prediction of Adverse Events Through Machine Learning Techniques

    Directory of Open Access Journals (Sweden)

    Evanthia E. Tripoliti

    Full Text Available Heart failure is a serious condition with high prevalence (about 2% in the adult population in developed countries, and more than 8% in patients older than 75 years. About 3–5% of hospital admissions are linked with heart failure incidents. Heart failure is the first cause of admission by healthcare professionals in their clinical practice. The costs are very high, reaching up to 2% of the total health costs in the developed countries. Building an effective disease management strategy requires analysis of large amount of data, early detection of the disease, assessment of the severity and early prediction of adverse events. This will inhibit the progression of the disease, will improve the quality of life of the patients and will reduce the associated medical costs. Toward this direction machine learning techniques have been employed. The aim of this paper is to present the state-of-the-art of the machine learning methodologies applied for the assessment of heart failure. More specifically, models predicting the presence, estimating the subtype, assessing the severity of heart failure and predicting the presence of adverse events, such as destabilizations, re-hospitalizations, and mortality are presented. According to the authors' knowledge, it is the first time that such a comprehensive review, focusing on all aspects of the management of heart failure, is presented. Keywords: Heart failure, Diagnosis, Prediction, Severity estimation, Classification, Data mining

  9. GLOBAL PERCEPTION IN TRANSLATING THE CONTENT OF WEBSITES

    OpenAIRE

    Mariana Coancă

    2012-01-01

    Most of the time the visitors of a website are willing to purchase products if the content of the website is presented in their native language. Therefore, translators become the most import key, because they translate not only the words and sentences on the website, but also the general tone and the key messages, adapting each cultural reference. We focused on the translators’ task and we presented some techniques regarding the translation process. In order to exemplify this aspect, we selec...

  10. Machine learning applied to the prediction of citrus production

    OpenAIRE

    Díaz Rodríguez, Susana Irene; Mazza, Silvia M.; Fernández-Combarro Álvarez, Elías; Giménez, Laura I.; Gaiad, José E.

    2017-01-01

    An in-depth knowledge about variables affecting production is required in order to predict global production and take decisions in agriculture. Machine learning is a technique used in agricultural planning and precision agriculture. This work (i) studies the effectiveness of machine learning techniques for predicting orchards production; and (ii) variables affecting this production were also identified. Data from 964 orchards of lemon, mandarin, and orange in Corrientes, Argentina are analyse...

  11. Predicting genome-wide redundancy using machine learning

    Directory of Open Access Journals (Sweden)

    Shasha Dennis E

    2010-11-01

    Full Text Available Abstract Background Gene duplication can lead to genetic redundancy, which masks the function of mutated genes in genetic analyses. Methods to increase sensitivity in identifying genetic redundancy can improve the efficiency of reverse genetics and lend insights into the evolutionary outcomes of gene duplication. Machine learning techniques are well suited to classifying gene family members into redundant and non-redundant gene pairs in model species where sufficient genetic and genomic data is available, such as Arabidopsis thaliana, the test case used here. Results Machine learning techniques that combine multiple attributes led to a dramatic improvement in predicting genetic redundancy over single trait classifiers alone, such as BLAST E-values or expression correlation. In withholding analysis, one of the methods used here, Support Vector Machines, was two-fold more precise than single attribute classifiers, reaching a level where the majority of redundant calls were correctly labeled. Using this higher confidence in identifying redundancy, machine learning predicts that about half of all genes in Arabidopsis showed the signature of predicted redundancy with at least one but typically less than three other family members. Interestingly, a large proportion of predicted redundant gene pairs were relatively old duplications (e.g., Ks > 1, suggesting that redundancy is stable over long evolutionary periods. Conclusions Machine learning predicts that most genes will have a functionally redundant paralog but will exhibit redundancy with relatively few genes within a family. The predictions and gene pair attributes for Arabidopsis provide a new resource for research in genetics and genome evolution. These techniques can now be applied to other organisms.

  12. Analysis and prediction of dimensions and cost of laser micro-machining internal channel fabrication process

    Directory of Open Access Journals (Sweden)

    Brabazon D.

    2010-06-01

    Full Text Available This paper presents the utilisation of Response Surface Methodology (RSM as the prediction tool for the laser micro-machining process. Laser internal microchannels machined using pulsed Nd:YVO4 laser in polycarbonate were investigated. The experiments were carried out according to 33 factorial Design of Experiment (DoE. In this work the three input process set as control parameters were laser power, P; pulse repetition frequency, PRF; and sample translation speed, U. Measured responses were the channel width and the micro-machining operating cost per metre of produced microchannels. The responses were sufficiently predicted within the set micro-machining parameters limits. Two factorial interaction (2FI and quadratic polynomial regression equations for both responses were constructed. It is proposed that the developed prediction equations can be used to find locally optimal micro-machining process parameters under experimental and operational conditions.

  13. Chemically intuited, large-scale screening of MOFs by machine learning techniques

    Science.gov (United States)

    Borboudakis, Giorgos; Stergiannakos, Taxiarchis; Frysali, Maria; Klontzas, Emmanuel; Tsamardinos, Ioannis; Froudakis, George E.

    2017-10-01

    A novel computational methodology for large-scale screening of MOFs is applied to gas storage with the use of machine learning technologies. This approach is a promising trade-off between the accuracy of ab initio methods and the speed of classical approaches, strategically combined with chemical intuition. The results demonstrate that the chemical properties of MOFs are indeed predictable (stochastically, not deterministically) using machine learning methods and automated analysis protocols, with the accuracy of predictions increasing with sample size. Our initial results indicate that this methodology is promising to apply not only to gas storage in MOFs but in many other material science projects.

  14. 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.

  15. Applying Sight Translation as a Means to Enhance Reading Ability of Iranian EFL Students

    Science.gov (United States)

    Fatollahi, Moslem

    2016-01-01

    Sight translation is the oral translation of a written text and is a mixture of translation and interpreting. Sight translation is a widely-used activity in translation training programs. Yet, this mode of translation has rarely been applied as a reading instruction technique in Iranian EFL instruction context in spite of the growing interest in…

  16. Teaching Translation and Interpreting 2: Insights, Aims, Visions. [Selection of] Papers from the Second Language International Conference (Elsinore, Denmark, June 4-6, 1993).

    Science.gov (United States)

    Dollerup, Cay, Ed.; Lindegaard, Annette, Ed.

    This selection of papers starts with insights into multi- and plurilingual settings, then proceeds to discussions of aims for practical work with students, and ends with visions of future developments within translation for the mass media and the impact of machine translation. Papers are: "Interpreting at the European Commission";…

  17. Mapping Translation Technology Research in Translation Studies

    DEFF Research Database (Denmark)

    Schjoldager, Anne; Christensen, Tina Paulsen; Flanagan, Marian

    2017-01-01

    section aims to improve this situation by presenting new and innovative research papers that reflect on recent technological advances and their impact on the translation profession and translators from a diversity of perspectives and using a variety of methods. In Section 2, we present translation......Due to the growing uptake of translation technology in the language industry and its documented impact on the translation profession, translation students and scholars need in-depth and empirically founded knowledge of the nature and influences of translation technology (e.g. Christensen....../Schjoldager 2010, 2011; Christensen 2011). Unfortunately, the increasing professional use of translation technology has not been mirrored within translation studies (TS) by a similar increase in research projects on translation technology (Munday 2009: 15; O’Hagan 2013; Doherty 2016: 952). The current thematic...

  18. Translation of Onomatopoetic Component in Onomastics

    Directory of Open Access Journals (Sweden)

    Анна Владимировна Соколова

    2015-12-01

    Full Text Available This article covers the topic of the description of translation strategies of onomatopoetic component of proper names. The term of onomatopoetic proper names is introduced for the first time. The article is the fist work that gives a view of onomatopoetic component in proper names on the material of English proper names, product names, electronic resources, theatre plays and cartoon titles. Onomatopoeia in onomastics is seen form the viewpoint of sociolinguistics. Being an aspect of literary onomastics, onomatopoetic proper names are considered to be a functional and semantic word mark (meaning-creating and text-forming that serves as an individualizing and characteristic device. However examples of onomatopoeia in onomastics are seen not only in imaginative literature but also in advertisements and commercials. Onomatopoetic component is a unique device that allows to verbalize lingvocultural aspects of proper names. These names are pleasant to hear and easy to remember. They help to make up brand names. Translation strategies include two techniques: translator often resorts to borrowings, in other words transliterateration or transcription of the original onomatopoeia, or makes situational equivalents like occasionalisms or oral speech equivalents to render the expressive, stylistic and evaluative components of meaning of such proper names. This article will give an example of both these techniques and deduce the most affective strategies that can be applied to translation of onomatopoetic component of proper names.

  19. Translational profiling in childhood acute lymphoblastic leukemia: no evidence for glucocorticoid regulation of mRNA translation.

    Science.gov (United States)

    Aneichyk, Tatsiana; Bindreither, Daniel; Mantinger, Christine; Grazio, Daniela; Goetsch, Katrin; Kofler, Reinhard; Rainer, Johannes

    2013-12-01

    Glucocorticoids (GCs) are natural stress induced steroid hormones causing cell cycle arrest and cell death in lymphoid tissues. Therefore they are the central component in the treatment of lymphoid malignancies, in particular childhood acute lymphoblastic leukemia (chALL). GCs act mainly via regulating gene transcription, which has been intensively studied by us and others. GC control of mRNA translation has also been reported but has never been assessed systematically. In this study we investigate the effect of GCs on mRNA translation on a genome-wide scale. Childhood T- (CCRF-CEM) and precursor B-ALL (NALM6) cells were exposed to GCs and subjected to "translational profiling", a technique combining sucrose-gradient fractionation followed by Affymetrix Exon microarray analysis of mRNA from different fractions, to assess the translational efficiency of the expressed genes. Analysis of GC regulation in ribosome-bound fractions versus transcriptional regulation revealed no significant differences, i.e., GC did not entail a significant shift between ribosomal bound and unbound mRNAs. In the present study we analyzed for the first time possible effects of GC on the translational efficiency of expressed genes in two chALL model systems employing whole genome polysome profiling. Our results did not reveal significant differences in translational efficiency of expressed genes thereby arguing against a potential widespread regulatory effect of GCs on translation at least in the investigated in vitro systems.

  20. A portable virtual machine target for proof-carrying code

    DEFF Research Database (Denmark)

    Franz, Michael; Chandra, Deepak; Gal, Andreas

    2005-01-01

    Virtual Machines (VMs) and Proof-Carrying Code (PCC) are two techniques that have been used independently to provide safety for (mobile) code. Existing virtual machines, such as the Java VM, have several drawbacks: First, the effort required for safety verification is considerable. Second and mor...... simultaneously providing efficient justin-time compilation and target-machine independence. In particular, our approach reduces the complexity of the required proofs, resulting in fewer proof obligations that need to be discharged at the target machine....

  1. 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.

  2. Micro machining workstation for a diode pumped Nd:YAG high brightness laser system

    NARCIS (Netherlands)

    Kleijhorst, R.A.; Offerhaus, Herman L.; Bant, P.

    1998-01-01

    A Nd:YAG micro-machining workstation that allows cutting on a scale of a few microns has been developed and operated. The system incorporates a telescope viewing system that allows control during the work and a software interface to translate AutoCad files. Some examples of the performance are

  3. Translating Signs, Producing Subjects

    Directory of Open Access Journals (Sweden)

    Brett Neilson

    2009-08-01

    Full Text Available This paper moves between two streets: Liverpool Road in the Sydney suburb of Ashfield and Via Sarpi in the Italian city of Milan. What connects these streets is that both have become important sites for businesses in the Chinese diaspora. Moreover, both are streets on which locals have expressed desires for Chinese signs to be translated into the national lingua franca. The paper argues that the cultural politics inherent in this demand for translation cannot be fully understood in the context of national debates about diversity and integration. It is also necessary to consider the emergence of the official Chinese Putonghua as global language, which competes with English but also colonizes dialects and minority languages. In the case of these dual language signs, the space between languages can neither be reduced to a contact zone of minority and majority cultures nor celebrated as a ‘third space’ where the power relations implied by such differences are subverted. At stake is rather a space characterised by what Naoki Sakai calls the schema of co-figuration, which allows the representation of translation as the passage between two equivalents that resemble each other and thus makes possible their determination as conceptually different and comparable. Drawing on arguments about translation and citizenship, the paper critically interrogates the ethos of interchangeability implied by this regime of translation. A closing argument is made for a vision of the common that implies neither civilisational harmony nor the translation of all values into a general equivalent. Primary sources include government reports, internet texts and media stories. These are analyzed using techniques of discourse analysis and interpreted with the help of secondary literature concerning globalisation, language and migration. The disciplinary matrix cuts and mixes between cultural studies, translation studies, citizenship studies, globalization studies and

  4. Translating children's stories - reflections and practices

    Directory of Open Access Journals (Sweden)

    Muguras Constantinescu

    2015-08-01

    Full Text Available http://dx.doi.org/10.5007/2175-7968.2016v36n1p155 The present article is concerned with the specificity of translations for children with an emphasis on the cultural dimension to be preserved in the target text. Following a brief historical and theoretical overview on the issue of translating texts for children, we undertake a succint analysis on a corpus made up of tales which display an overtness to the other while treating the identity-alterity issue. Starting from our own translation practice, we will insist upon those strategies and techniques fit to render the cultural dimension of the source text in order to give young readers access to a foreign culture. Translational strategies are analysed along editorial and pedagogical strategies, with a special focus on the paratext which aims at satisfying the readers’ curiosity and contributing to the development of their encyclopedic competence.

  5. A Behavior-Preserving Translation From FBD Design to C Implementation for Reactor Protection System Software

    International Nuclear Information System (INIS)

    Yoo, Junbeom; Kim, Euisub; Lee, Jangsoo

    2013-01-01

    Software safety for nuclear reactor protection systems (RPSs) is the most important requirement for the obtainment of permission for operation and export from government authorities, which is why it should be managed with well-experienced software development processes. The RPS software is typically modeled with function block diagrams (FBDs) in the design phase, and then mechanically translated into C programs in the implementation phase, which is finally compiled into executable machine codes and loaded on RPS hardware - PLC (Programmable Logic Controller). Whereas C Compilers are fully-verified COTS (Commercial Off-The-Shelf) software, translators from FBDs to C programs are provided by PLC vendors. Long-term experience, experiments and simulations have validated their correctness and function safety. This paper proposes a behavior-preserving translation from FBD design to C implementation for RPS software. It includes two sets of translation algorithms and rules as well as a prototype translator. We used an example of RPS software in a Korean nuclear power plant to demonstrate the correctness and effectiveness of the proposed translation

  6. A Behavior-Preserving Translation From FBD Design to C Implementation for Reactor Protection System Software

    Energy Technology Data Exchange (ETDEWEB)

    Yoo, Junbeom; Kim, Euisub [Konkuk Univ., Seoul (Korea, Republic of); Lee, Jangsoo [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2013-08-15

    Software safety for nuclear reactor protection systems (RPSs) is the most important requirement for the obtainment of permission for operation and export from government authorities, which is why it should be managed with well-experienced software development processes. The RPS software is typically modeled with function block diagrams (FBDs) in the design phase, and then mechanically translated into C programs in the implementation phase, which is finally compiled into executable machine codes and loaded on RPS hardware - PLC (Programmable Logic Controller). Whereas C Compilers are fully-verified COTS (Commercial Off-The-Shelf) software, translators from FBDs to C programs are provided by PLC vendors. Long-term experience, experiments and simulations have validated their correctness and function safety. This paper proposes a behavior-preserving translation from FBD design to C implementation for RPS software. It includes two sets of translation algorithms and rules as well as a prototype translator. We used an example of RPS software in a Korean nuclear power plant to demonstrate the correctness and effectiveness of the proposed translation.

  7. 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.

  8. Machine Learning for Medical Imaging.

    Science.gov (United States)

    Erickson, Bradley J; Korfiatis, Panagiotis; Akkus, Zeynettin; Kline, Timothy L

    2017-01-01

    Machine learning is a technique for recognizing patterns that can be applied to medical images. Although it is a powerful tool that can help in rendering medical diagnoses, it can be misapplied. Machine learning typically begins with the machine learning algorithm system computing the image features that are believed to be of importance in making the prediction or diagnosis of interest. The machine learning algorithm system then identifies the best combination of these image features for classifying the image or computing some metric for the given image region. There are several methods that can be used, each with different strengths and weaknesses. There are open-source versions of most of these machine learning methods that make them easy to try and apply to images. Several metrics for measuring the performance of an algorithm exist; however, one must be aware of the possible associated pitfalls that can result in misleading metrics. More recently, deep learning has started to be used; this method has the benefit that it does not require image feature identification and calculation as a first step; rather, features are identified as part of the learning process. Machine learning has been used in medical imaging and will have a greater influence in the future. Those working in medical imaging must be aware of how machine learning works. © RSNA, 2017.

  9. Machine Learning and Inverse Problem in Geodynamics

    Science.gov (United States)

    Shahnas, M. H.; Yuen, D. A.; Pysklywec, R.

    2017-12-01

    During the past few decades numerical modeling and traditional HPC have been widely deployed in many diverse fields for problem solutions. However, in recent years the rapid emergence of machine learning (ML), a subfield of the artificial intelligence (AI), in many fields of sciences, engineering, and finance seems to mark a turning point in the replacement of traditional modeling procedures with artificial intelligence-based techniques. The study of the circulation in the interior of Earth relies on the study of high pressure mineral physics, geochemistry, and petrology where the number of the mantle parameters is large and the thermoelastic parameters are highly pressure- and temperature-dependent. More complexity arises from the fact that many of these parameters that are incorporated in the numerical models as input parameters are not yet well established. In such complex systems the application of machine learning algorithms can play a valuable role. Our focus in this study is the application of supervised machine learning (SML) algorithms in predicting mantle properties with the emphasis on SML techniques in solving the inverse problem. As a sample problem we focus on the spin transition in ferropericlase and perovskite that may cause slab and plume stagnation at mid-mantle depths. The degree of the stagnation depends on the degree of negative density anomaly at the spin transition zone. The training and testing samples for the machine learning models are produced by the numerical convection models with known magnitudes of density anomaly (as the class labels of the samples). The volume fractions of the stagnated slabs and plumes which can be considered as measures for the degree of stagnation are assigned as sample features. The machine learning models can determine the magnitude of the spin transition-induced density anomalies that can cause flow stagnation at mid-mantle depths. Employing support vector machine (SVM) algorithms we show that SML techniques

  10. Machine learning methods without tears: a primer for ecologists.

    Science.gov (United States)

    Olden, Julian D; Lawler, Joshua J; Poff, N LeRoy

    2008-06-01

    Machine learning methods, a family of statistical techniques with origins in the field of artificial intelligence, are recognized as holding great promise for the advancement of understanding and prediction about ecological phenomena. These modeling techniques are flexible enough to handle complex problems with multiple interacting elements and typically outcompete traditional approaches (e.g., generalized linear models), making them ideal for modeling ecological systems. Despite their inherent advantages, a review of the literature reveals only a modest use of these approaches in ecology as compared to other disciplines. One potential explanation for this lack of interest is that machine learning techniques do not fall neatly into the class of statistical modeling approaches with which most ecologists are familiar. In this paper, we provide an introduction to three machine learning approaches that can be broadly used by ecologists: classification and regression trees, artificial neural networks, and evolutionary computation. For each approach, we provide a brief background to the methodology, give examples of its application in ecology, describe model development and implementation, discuss strengths and weaknesses, explore the availability of statistical software, and provide an illustrative example. Although the ecological application of machine learning approaches has increased, there remains considerable skepticism with respect to the role of these techniques in ecology. Our review encourages a greater understanding of machin learning approaches and promotes their future application and utilization, while also providing a basis from which ecologists can make informed decisions about whether to select or avoid these approaches in their future modeling endeavors.

  11. Achieving precision in high density batch mode micro-electro-discharge machining

    International Nuclear Information System (INIS)

    Richardson, Mark T; Gianchandani, Yogesh B

    2008-01-01

    This paper reports a parametric study of batch mode micro-electro-discharge machining (µEDM) of high density features in stainless steel. Lithographically fabricated copper tools with single cross, parallel line and 8 × 8 circle/square array features of 5–100 µm width and 5–75 µm spacing were used to quantify trends in machining tolerance and the impact of debris accumulation. As the tool feature density is increased, debris accumulation effects begin to dominate, eventually degrading both tool and workpiece. Two independent techniques for mitigating this debris buildup are separately investigated. The first is a passivation coating which suppresses spurious discharges triggered from the sidewalls of the machining tool. By this method, the mean tool wear rate decreases from a typical of about 34% to 1.7% and machining non-uniformity reduces from 4.9 µm to 1.1 µm across the workpiece. The second technique involves a two-step machining process that enhances the hydrodynamic removal of machining debris compared to standard methods. This improves surface and edge finish, machining time and tool wear

  12. Injuries caused by firewood splitting machines.

    Science.gov (United States)

    Hellstrand, P H

    1989-01-01

    The aim of this paper is to present the types of injury caused by firewood splitting machines and also to elucidate the accident mechanism. The study is based on 15 cases. The machine has a rotating spiral cone, and usually the victims' gloved fingertips were caught by the point of the cone. This led to either amputations, usually of radial fingers and/or penetrating wounds through the middle of the hand. In most cases the accidents could not be blamed on bad working techniques. The study of the mechanisms of injury points to insufficient protective devices in a machine construction which has a potentially dangerous working principle.

  13. Translating children’s literature: some insights from corpus stylistics

    Directory of Open Access Journals (Sweden)

    Anna Čermáková

    2018-01-01

    Full Text Available In this paper I explore the potential of a corpus stylistic approach to the study of literary translation. The study focuses on translation of children’s literature with its specific constrains, and illustrates with two corpus linguistic techniques: keyword and cluster analysis — specific cases of repetition. So in a broader sense the paper discusses the phenomenon of repetition in different literary (stylistic traditions. These are illustrated by examples from two children’s classics aimed at two different age groups: the Harry Potter and the Winnie the Pooh books — and their translations into Czech. Various shifts in translation, especially in the translation of children’s literature, are often explained by the operation of so-called ‘translation universals’. Though ‘repetition’ as such does not belong to the commonly discussed set of translation universals, the stylistic norms opposing repetition seem to be a strong explanation for the translation shifts identified.

  14. Effect of electrical discharge machining on surface characteristics and machining damage of AISI D2 tool steel

    International Nuclear Information System (INIS)

    Guu, Y.H.; Hocheng, H.; Chou, C.Y.; Deng, C.S.

    2003-01-01

    In this work the electrical discharge machining (EDM) of AISI D2 tool steel was investigated. The surface characteristics and machining damage caused by EDM were studied in terms of machining parameters. Based on the experimental data, an empirical model of the tool steel was also proposed. A new damage variable was used to study the EDM damage. The workpiece surface and re-solidified layers were examined by a scanning electron microscopy. Surface roughness was determined with a surface profilometer. The residual stress acting on the EDM specimen was measured by the X-ray diffraction technique. Experimental results indicate that the thickness of the recast layer, and surface roughness are proportional to the power input. The EDM process introduces tensile residual stress on the machined surface. The EDM damage leads to strength degradation

  15. Machine learning a Bayesian and optimization perspective

    CERN Document Server

    Theodoridis, Sergios

    2015-01-01

    This tutorial text gives a unifying perspective on machine learning by covering both probabilistic and deterministic approaches, which rely on optimization techniques, as well as Bayesian inference, which is based on a hierarchy of probabilistic models. The book presents the major machine learning methods as they have been developed in different disciplines, such as statistics, statistical and adaptive signal processing and computer science. Focusing on the physical reasoning behind the mathematics, all the various methods and techniques are explained in depth, supported by examples and problems, giving an invaluable resource to the student and researcher for understanding and applying machine learning concepts. The book builds carefully from the basic classical methods to the most recent trends, with chapters written to be as self-contained as possible, making the text suitable for different courses: pattern recognition, statistical/adaptive signal processing, statistical/Bayesian learning, as well as shor...

  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. Evaluating automatically parallelized versions of the support vector machine

    NARCIS (Netherlands)

    Codreanu, Valeriu; Droge, Bob; Williams, David; Yasar, Burhan; Yang, Fo; Liu, Baoquan; Dong, Feng; Surinta, Olarik; Schomaker, Lambertus; Roerdink, Jos; Wiering, Marco

    2014-01-01

    The support vector machine (SVM) is a supervised learning algorithm used for recognizing patterns in data. It is a very popular technique in machine learning and has been successfully used in applications such as image classification, protein classification, and handwriting recognition. However, the

  18. Evaluating automatically parallelized versions of the support vector machine

    NARCIS (Netherlands)

    Codreanu, V.; Dröge, B.; Williams, D.; Yasar, B.; Yang, P.; Liu, B.; Dong, F.; Surinta, O.; Schomaker, L.R.B.; Roerdink, J.B.T.M.; Wiering, M.A.

    2016-01-01

    The support vector machine (SVM) is a supervised learning algorithm used for recognizing patterns in data. It is a very popular technique in machine learning and has been successfully used in applications such as image classification, protein classification, and handwriting recognition. However, the

  19. Maintaining Sentiment Polarity in Translation of User-Generated Content

    Directory of Open Access Journals (Sweden)

    Lohar Pintu

    2017-06-01

    Full Text Available The advent of social media has shaken the very foundations of how we share information, with Twitter, Facebook, and Linkedin among many well-known social networking platforms that facilitate information generation and distribution. However, the maximum 140-character restriction in Twitter encourages users to (sometimes deliberately write somewhat informally in most cases. As a result, machine translation (MT of user-generated content (UGC becomes much more difficult for such noisy texts. In addition to translation quality being affected, this phenomenon may also negatively impact sentiment preservation in the translation process. That is, a sentence with positive sentiment in the source language may be translated into a sentence with negative or neutral sentiment in the target language. In this paper, we analyse both sentiment preservation and MT quality per se in the context of UGC, focusing especially on whether sentiment classification helps improve sentiment preservation in MT of UGC. We build four different experimental setups for tweet translation (i using a single MT model trained on the whole Twitter parallel corpus, (ii using multiple MT models based on sentiment classification, (iii using MT models including additional out-of-domain data, and (iv adding MT models based on the phrase-table fill-up method to accompany the sentiment translation models with an aim of improving MT quality and at the same time maintaining sentiment polarity preservation. Our empirical evaluation shows that despite a slight deterioration in MT quality, our system significantly outperforms the Baseline MT system (without using sentiment classification in terms of sentiment preservation. We also demonstrate that using an MT engine that conveys a sentiment different from that of the UGC can even worsen both the translation quality and sentiment preservation.

  20. Large-Scale Machine Learning for Classification and Search

    Science.gov (United States)

    Liu, Wei

    2012-01-01

    With the rapid development of the Internet, nowadays tremendous amounts of data including images and videos, up to millions or billions, can be collected for training machine learning models. Inspired by this trend, this thesis is dedicated to developing large-scale machine learning techniques for the purpose of making classification and nearest…

  1. Survey of Machine Learning Methods for Database Security

    Science.gov (United States)

    Kamra, Ashish; Ber, Elisa

    Application of machine learning techniques to database security is an emerging area of research. In this chapter, we present a survey of various approaches that use machine learning/data mining techniques to enhance the traditional security mechanisms of databases. There are two key database security areas in which these techniques have found applications, namely, detection of SQL Injection attacks and anomaly detection for defending against insider threats. Apart from the research prototypes and tools, various third-party commercial products are also available that provide database activity monitoring solutions by profiling database users and applications. We present a survey of such products. We end the chapter with a primer on mechanisms for responding to database anomalies.

  2. Health Informatics via Machine Learning for the Clinical Management of Patients.

    Science.gov (United States)

    Clifton, D A; Niehaus, K E; Charlton, P; Colopy, G W

    2015-08-13

    To review how health informatics systems based on machine learning methods have impacted the clinical management of patients, by affecting clinical practice. We reviewed literature from 2010-2015 from databases such as Pubmed, IEEE xplore, and INSPEC, in which methods based on machine learning are likely to be reported. We bring together a broad body of literature, aiming to identify those leading examples of health informatics that have advanced the methodology of machine learning. While individual methods may have further examples that might be added, we have chosen some of the most representative, informative exemplars in each case. Our survey highlights that, while much research is taking place in this high-profile field, examples of those that affect the clinical management of patients are seldom found. We show that substantial progress is being made in terms of methodology, often by data scientists working in close collaboration with clinical groups. Health informatics systems based on machine learning are in their infancy and the translation of such systems into clinical management has yet to be performed at scale.

  3. Multimodal Translation System Using Texture-Mapped Lip-Sync Images for Video Mail and Automatic Dubbing Applications

    Science.gov (United States)

    Morishima, Shigeo; Nakamura, Satoshi

    2004-12-01

    We introduce a multimodal English-to-Japanese and Japanese-to-English translation system that also translates the speaker's speech motion by synchronizing it to the translated speech. This system also introduces both a face synthesis technique that can generate any viseme lip shape and a face tracking technique that can estimate the original position and rotation of a speaker's face in an image sequence. To retain the speaker's facial expression, we substitute only the speech organ's image with the synthesized one, which is made by a 3D wire-frame model that is adaptable to any speaker. Our approach provides translated image synthesis with an extremely small database. The tracking motion of the face from a video image is performed by template matching. In this system, the translation and rotation of the face are detected by using a 3D personal face model whose texture is captured from a video frame. We also propose a method to customize the personal face model by using our GUI tool. By combining these techniques and the translated voice synthesis technique, an automatic multimodal translation can be achieved that is suitable for video mail or automatic dubbing systems into other languages.

  4. Combining Formal Logic and Machine Learning for Sentiment Analysis

    DEFF Research Database (Denmark)

    Petersen, Niklas Christoffer; Villadsen, Jørgen

    2014-01-01

    This paper presents a formal logical method for deep structural analysis of the syntactical properties of texts using machine learning techniques for efficient syntactical tagging. To evaluate the method it is used for entity level sentiment analysis as an alternative to pure machine learning...

  5. Understanding Translation

    DEFF Research Database (Denmark)

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

    Understanding Translation is designed as a textbook for courses on the theory and practice of translation in general and of particular types of translation - such as interpreting, screen translation and literary translation. The aim of the book is to help you gain an in-depth understanding...... of the phenomenon of translation and to provide you with a conceptual framework for the analysis of various aspects of professional translation. Intended readers are students of translation and languages, but the book will also be relevant for others who are interested in the theory and practice of translation...... - translators, language teachers, translation users and literary, TV and film critics, for instance. Discussions focus on translation between Danish and English....

  6. Research on Error Modelling and Identification of 3 Axis NC Machine Tools Based on Cross Grid Encoder Measurement

    International Nuclear Information System (INIS)

    Du, Z C; Lv, C F; Hong, M S

    2006-01-01

    A new error modelling and identification method based on the cross grid encoder is proposed in this paper. Generally, there are 21 error components in the geometric error of the 3 axis NC machine tools. However according our theoretical analysis, the squareness error among different guide ways affects not only the translation error component, but also the rotational ones. Therefore, a revised synthetic error model is developed. And the mapping relationship between the error component and radial motion error of round workpiece manufactured on the NC machine tools are deduced. This mapping relationship shows that the radial error of circular motion is the comprehensive function result of all the error components of link, worktable, sliding table and main spindle block. Aiming to overcome the solution singularity shortcoming of traditional error component identification method, a new multi-step identification method of error component by using the Cross Grid Encoder measurement technology is proposed based on the kinematic error model of NC machine tool. Firstly, the 12 translational error components of the NC machine tool are measured and identified by using the least square method (LSM) when the NC machine tools go linear motion in the three orthogonal planes: XOY plane, XOZ plane and YOZ plane. Secondly, the circular error tracks are measured when the NC machine tools go circular motion in the same above orthogonal planes by using the cross grid encoder Heidenhain KGM 182. Therefore 9 rotational errors can be identified by using LSM. Finally the experimental validation of the above modelling theory and identification method is carried out in the 3 axis CNC vertical machining centre Cincinnati 750 Arrow. The entire 21 error components have been successfully measured out by the above method. Research shows the multi-step modelling and identification method is very suitable for 'on machine measurement'

  7. Analysis of machining and machine tools

    CERN Document Server

    Liang, Steven Y

    2016-01-01

    This book delivers the fundamental science and mechanics of machining and machine tools by presenting systematic and quantitative knowledge in the form of process mechanics and physics. It gives readers a solid command of machining science and engineering, and familiarizes them with the geometry and functionality requirements of creating parts and components in today’s markets. The authors address traditional machining topics, such as: single and multiple point cutting processes grinding components accuracy and metrology shear stress in cutting cutting temperature and analysis chatter They also address non-traditional machining, such as: electrical discharge machining electrochemical machining laser and electron beam machining A chapter on biomedical machining is also included. This book is appropriate for advanced undergraduate and graduate mechani cal engineering students, manufacturing engineers, and researchers. Each chapter contains examples, exercises and their solutions, and homework problems that re...

  8. Machine learning and evolutionary techniques in interplanetary trajectory design

    OpenAIRE

    Izzo, Dario; Sprague, Christopher; Tailor, Dharmesh

    2018-01-01

    After providing a brief historical overview on the synergies between artificial intelligence research, in the areas of evolutionary computations and machine learning, and the optimal design of interplanetary trajectories, we propose and study the use of deep artificial neural networks to represent, on-board, the optimal guidance profile of an interplanetary mission. The results, limited to the chosen test case of an Earth-Mars orbital transfer, extend the findings made previously for landing ...

  9. QEFSM model and Markov Algorithm for translating Quran reciting rules into Braille code

    Directory of Open Access Journals (Sweden)

    Abdallah M. Abualkishik

    2015-07-01

    Full Text Available The Holy Quran is the central religious verbal text of Islam. Muslims are expected to read, understand, and apply the teachings of the Holy Quran. The Holy Quran was translated to Braille code as a normal Arabic text without having its reciting rules included. It is obvious that the users of this transliteration will not be able to recite the Quran the right way. Through this work, Quran Braille Translator (QBT presents a specific translator to translate Quran verses and their reciting rules into the Braille code. Quran Extended Finite State Machine (QEFSM model is proposed through this study as it is able to detect the Quran reciting rules (QRR from the Quran text. Basis path testing was used to evaluate the inner work for the model by checking all the test cases for the model. Markov Algorithm (MA was used for translating the detected QRR and Quran text into the matched Braille code. The data entries for QBT are Arabic letters and diacritics. The outputs of this study are seen in the double lines of Braille symbols; the first line is the proposed Quran reciting rules and the second line is for the Quran scripts.

  10. A comparison of machine learning techniques for detection of drug target articles.

    Science.gov (United States)

    Danger, Roxana; Segura-Bedmar, Isabel; Martínez, Paloma; Rosso, Paolo

    2010-12-01

    Important progress in treating diseases has been possible thanks to the identification of drug targets. Drug targets are the molecular structures whose abnormal activity, associated to a disease, can be modified by drugs, improving the health of patients. Pharmaceutical industry needs to give priority to their identification and validation in order to reduce the long and costly drug development times. In the last two decades, our knowledge about drugs, their mechanisms of action and drug targets has rapidly increased. Nevertheless, most of this knowledge is hidden in millions of medical articles and textbooks. Extracting knowledge from this large amount of unstructured information is a laborious job, even for human experts. Drug target articles identification, a crucial first step toward the automatic extraction of information from texts, constitutes the aim of this paper. A comparison of several machine learning techniques has been performed in order to obtain a satisfactory classifier for detecting drug target articles using semantic information from biomedical resources such as the Unified Medical Language System. The best result has been achieved by a Fuzzy Lattice Reasoning classifier, which reaches 98% of ROC area measure. Copyright © 2010 Elsevier Inc. All rights reserved.

  11. Block-Module Electric Machines of Alternating Current

    Science.gov (United States)

    Zabora, I.

    2018-03-01

    The paper deals with electric machines having active zone based on uniform elements. It presents data on disk-type asynchronous electric motors with short-circuited rotors, where active elements are made by integrated technique that forms modular elements. Photolithography, spraying, stamping of windings, pressing of core and combined methods are utilized as the basic technological approaches of production. The constructions and features of operation for new electric machine - compatible electric machines-transformers are considered. Induction motors are intended for operation in hermetic plants with extreme conditions surrounding gas, steam-to-gas and liquid environment at a high temperature (to several hundred of degrees).

  12. BEBP: An Poisoning Method Against Machine Learning Based IDSs

    OpenAIRE

    Li, Pan; Liu, Qiang; Zhao, Wentao; Wang, Dongxu; Wang, Siqi

    2018-01-01

    In big data era, machine learning is one of fundamental techniques in intrusion detection systems (IDSs). However, practical IDSs generally update their decision module by feeding new data then retraining learning models in a periodical way. Hence, some attacks that comprise the data for training or testing classifiers significantly challenge the detecting capability of machine learning-based IDSs. Poisoning attack, which is one of the most recognized security threats towards machine learning...

  13. Elie Luzac and L’homme plus que machine (1748: The Dialogic Voice of an Enlightenment Printer

    Directory of Open Access Journals (Sweden)

    Lieve Jooken

    2018-01-01

    Full Text Available Early into his career as one of the most successful printerpublishers of the Dutch Republic, Elie Luzac (1721-1796 played a pivotal role in disseminating the materialist ideas of La Mettrie’s Homme machine (1747. This paper focuses on the dialogic voice (Bakhtine in a publication by Luzac himself, which oscillates between asserting and refuting La Mettrie’s views. Descended from Huguenot refugees, Luzac condemns what he publishes and publishes what he condemns. This discursive ambiguity emerges in Luzac’s L’homme plus que machine (1748, a work which cites La Mettrie’s theses in order to contest them. Building on the succès de scandale of the English version of L’homme machine (Man a Machine, 1749, the English translation of L’homme plus que machine, Man more than a Machine, appeared in 1752. The present contribution examines how the translator’s Voice, which is defined as an enarrative voice, effaces the concealed claims of the original text and replaces them with a discourse whose explicit anti-materialist tenor contrasts with the vehement rhetoric of Man a Machine.

  14. Advanced Machine Learning for Classification, Regression, and Generation in Jet Physics

    CERN Multimedia

    CERN. Geneva

    2017-01-01

    There is a deep connection between machine learning and jet physics - after all, jets are defined by unsupervised learning algorithms. Jet physics has been a driving force for studying modern machine learning in high energy physics. Domain specific challenges require new techniques to make full use of the algorithms. A key focus is on understanding how and what the algorithms learn. Modern machine learning techniques for jet physics are demonstrated for classification, regression, and generation. In addition to providing powerful baseline performance, we show how to train complex models directly on data and to generate sparse stacked images with non-uniform granularity.

  15. Reverse hypothesis machine learning a practitioner's perspective

    CERN Document Server

    Kulkarni, Parag

    2017-01-01

    This book introduces a paradigm of reverse hypothesis machines (RHM), focusing on knowledge innovation and machine learning. Knowledge- acquisition -based learning is constrained by large volumes of data and is time consuming. Hence Knowledge innovation based learning is the need of time. Since under-learning results in cognitive inabilities and over-learning compromises freedom, there is need for optimal machine learning. All existing learning techniques rely on mapping input and output and establishing mathematical relationships between them. Though methods change the paradigm remains the same—the forward hypothesis machine paradigm, which tries to minimize uncertainty. The RHM, on the other hand, makes use of uncertainty for creative learning. The approach uses limited data to help identify new and surprising solutions. It focuses on improving learnability, unlike traditional approaches, which focus on accuracy. The book is useful as a reference book for machine learning researchers and professionals as ...

  16. Precision machining and polishing of scintillating crystals for large calorimeters and hodoscopes

    International Nuclear Information System (INIS)

    Wuest, C.R.; Fuchs, B.A.; Holdener, F.R.; Heck, J.L. Jr.

    1994-04-01

    New machining and polishing techniques have been developed for large scintillating crystal arrays such as the Barium Fluoride Electromagnetic Calorimeter for the GEM Detector at SSCL, the Crystal Clear Collaboration's cerium fluoride or lead tungstenate calorimeter at the proposed LHC and CERN, the PHENIX Detector at RHIC (barium fluoride), and the cesium iodide Calorimeter for the BaBar Detector at PEP-2 B Factory at SLAC. The machining and polishing methods to be presented in this paper provide crystalline surfaces without sub-surface damage or deformation as verified by Rutherford Back-scattering (RBS) analysis. Surface roughness of about 10--20 angstroms and sub-micron mechanical tolerances have been demonstrated on large barium fluoride crystal samples. Mass production techniques have also been developed for machining the proper angled surfaces and polishing up to five 50 cm long crystals at one time. These techniques utilize kinematic mount technology developed at LLNL to allow precision machining and polishing of complex surfaces. They will present this technology along with detailed surface studies of barium fluoride and cerium fluoride crystals polished with this technique

  17. When Machines Think: Radiology's Next Frontier.

    Science.gov (United States)

    Dreyer, Keith J; Geis, J Raymond

    2017-12-01

    Artificial intelligence (AI), machine learning, and deep learning are terms now seen frequently, all of which refer to computer algorithms that change as they are exposed to more data. Many of these algorithms are surprisingly good at recognizing objects in images. The combination of large amounts of machine-consumable digital data, increased and cheaper computing power, and increasingly sophisticated statistical models combine to enable machines to find patterns in data in ways that are not only cost-effective but also potentially beyond humans' abilities. Building an AI algorithm can be surprisingly easy. Understanding the associated data structures and statistics, on the other hand, is often difficult and obscure. Converting the algorithm into a sophisticated product that works consistently in broad, general clinical use is complex and incompletely understood. To show how these AI products reduce costs and improve outcomes will require clinical translation and industrial-grade integration into routine workflow. Radiology has the chance to leverage AI to become a center of intelligently aggregated, quantitative, diagnostic information. Centaur radiologists, formed as a synergy of human plus computer, will provide interpretations using data extracted from images by humans and image-analysis computer algorithms, as well as the electronic health record, genomics, and other disparate sources. These interpretations will form the foundation of precision health care, or care customized to an individual patient. © RSNA, 2017.

  18. CLASSROOM SHARING EXPERIENCES: BUILDING STUDENTS’ AWARENESS FOR PROBLEM SOLVING IN TRANSLATING POETRY

    Directory of Open Access Journals (Sweden)

    Sri Handayani

    2015-12-01

    Abstract This research was aimed at describing the classroom sharing experiences to build students’ awareness dealing with the problem solving in translating poetry. The data were collected through questionnaire, interview and classroom observation involving 85 sixth semester students in two different classes and two lecturers of Translating Literary Works course at the English Language and Literature Studies in one state university in Bandung city.  The questionnaire was completed by 55 (out of 85 students invited to fill in the questionnaire. Interview was done to complete and cross check the information derived from the questionnaire.  Meanwhile, the observation was administered in the two parallel classes to observe the activities done by the two lecturers and students in the two classes.  The observation was focused on the course materials, teaching methods and techniques applied by the lecturers, problems faced and techniques used to solve the problems by the students in translating poetry. The data were then analyzed based on some relevant theories of translation.  The result of the research showed that the classroom sharing experiences gave some advantages to the students with several reasons: (1 motivating students to do their translation works more seriously since they had to present their translation works to the class; (2 developing the students’ self-confidence in translating the tasks since their translation works were given some feedbacks; (3 training the students to analyze the problems to find out the most appropriate techniques to solve the problems; (4 introducing the students to have more critical knowledge of both source and target languages; and (5 building the students’ awareness of how the problems appeared in a very complex translation process were solved. Keywords: awareness, problem solving, sharing experience

  19. Connection machine: a computer architecture based on cellular automata

    Energy Technology Data Exchange (ETDEWEB)

    Hillis, W D

    1984-01-01

    This paper describes the connection machine, a programmable computer based on cellular automata. The essential idea behind the connection machine is that a regular locally-connected cellular array can be made to behave as if the processing cells are connected into any desired topology. When the topology of the machine is chosen to match the topology of the application program, the result is a fast, powerful computing engine. The connection machine was originally designed to implement knowledge retrieval operations in artificial intelligence programs, but the hardware and the programming techniques are apparently applicable to a much larger class of problems. A machine with 100000 processing cells is currently being constructed. 27 references.

  20. Multimodal Translation System Using Texture-Mapped Lip-Sync Images for Video Mail and Automatic Dubbing Applications

    Directory of Open Access Journals (Sweden)

    Nakamura Satoshi

    2004-01-01

    Full Text Available We introduce a multimodal English-to-Japanese and Japanese-to-English translation system that also translates the speaker's speech motion by synchronizing it to the translated speech. This system also introduces both a face synthesis technique that can generate any viseme lip shape and a face tracking technique that can estimate the original position and rotation of a speaker's face in an image sequence. To retain the speaker's facial expression, we substitute only the speech organ's image with the synthesized one, which is made by a 3D wire-frame model that is adaptable to any speaker. Our approach provides translated image synthesis with an extremely small database. The tracking motion of the face from a video image is performed by template matching. In this system, the translation and rotation of the face are detected by using a 3D personal face model whose texture is captured from a video frame. We also propose a method to customize the personal face model by using our GUI tool. By combining these techniques and the translated voice synthesis technique, an automatic multimodal translation can be achieved that is suitable for video mail or automatic dubbing systems into other languages.

  1. Automatic Quality Inspection of Percussion Cap Mass Production by Means of 3D Machine Vision and Machine Learning Techniques

    Science.gov (United States)

    Tellaeche, A.; Arana, R.; Ibarguren, A.; Martínez-Otzeta, J. M.

    The exhaustive quality control is becoming very important in the world's globalized market. One of these examples where quality control becomes critical is the percussion cap mass production. These elements must achieve a minimum tolerance deviation in their fabrication. This paper outlines a machine vision development using a 3D camera for the inspection of the whole production of percussion caps. This system presents multiple problems, such as metallic reflections in the percussion caps, high speed movement of the system and mechanical errors and irregularities in percussion cap placement. Due to these problems, it is impossible to solve the problem by traditional image processing methods, and hence, machine learning algorithms have been tested to provide a feasible classification of the possible errors present in the percussion caps.

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

    Science.gov (United States)

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

    2014-02-01

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

  3. Implementing Machine Learning in Radiology Practice and Research.

    Science.gov (United States)

    Kohli, Marc; Prevedello, Luciano M; Filice, Ross W; Geis, J Raymond

    2017-04-01

    The purposes of this article are to describe concepts that radiologists should understand to evaluate machine learning projects, including common algorithms, supervised as opposed to unsupervised techniques, statistical pitfalls, and data considerations for training and evaluation, and to briefly describe ethical dilemmas and legal risk. Machine learning includes a broad class of computer programs that improve with experience. The complexity of creating, training, and monitoring machine learning indicates that the success of the algorithms will require radiologist involvement for years to come, leading to engagement rather than replacement.

  4. Mapping Translation Technology Research in Translation Studies

    DEFF Research Database (Denmark)

    Schjoldager, Anne; Christensen, Tina Paulsen; Flanagan, Marian

    2017-01-01

    /Schjoldager 2010, 2011; Christensen 2011). Unfortunately, the increasing professional use of translation technology has not been mirrored within translation studies (TS) by a similar increase in research projects on translation technology (Munday 2009: 15; O’Hagan 2013; Doherty 2016: 952). The current thematic...... section aims to improve this situation by presenting new and innovative research papers that reflect on recent technological advances and their impact on the translation profession and translators from a diversity of perspectives and using a variety of methods. In Section 2, we present translation...... technology research as a subdiscipline of TS, and we define and discuss some basic concepts and models of the field that we use in the rest of the paper. Based on a small-scale study of papers published in TS journals between 2006 and 2016, Section 3 attempts to map relevant developments of translation...

  5. Assessing thermally induced errors of machine tools by 3D length measurements

    NARCIS (Netherlands)

    Florussen, G.H.J.; Delbressine, F.L.M.; Schellekens, P.H.J.

    2003-01-01

    A new measurement technique is proposed for the assessment of thermally induced errors of machine tools. The basic idea is to measure changes of length by a telescopic double ball bar (TDEB) at multiple locations in the machine's workspace while the machine is thermally excited. In addition thermal

  6. 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.

  7. Machine learning and medicine: book review and commentary.

    Science.gov (United States)

    Koprowski, Robert; Foster, Kenneth R

    2018-02-01

    This article is a review of the book "Master machine learning algorithms, discover how they work and implement them from scratch" (ISBN: not available, 37 USD, 163 pages) edited by Jason Brownlee published by the Author, edition, v1.10 http://MachineLearningMastery.com . An accompanying commentary discusses some of the issues that are involved with use of machine learning and data mining techniques to develop predictive models for diagnosis or prognosis of disease, and to call attention to additional requirements for developing diagnostic and prognostic algorithms that are generally useful in medicine. Appendix provides examples that illustrate potential problems with machine learning that are not addressed in the reviewed book.

  8. 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...

  9. Efficient Translation of LTL Formulae into Buchi Automata

    Science.gov (United States)

    Giannakopoulou, Dimitra; Lerda, Flavio

    2001-01-01

    Model checking is a fully automated technique for checking that a system satisfies a set of required properties. With explicit-state model checkers, properties are typically defined in linear-time temporal logic (LTL), and are translated into B chi automata in order to be checked. This report presents how we have combined and improved existing techniques to obtain an efficient LTL to B chi automata translator. In particular, we optimize the core of existing tableau-based approaches to generate significantly smaller automata. Our approach has been implemented and is being released as part of the Java PathFinder software (JPF), an explicit state model checker under development at the NASA Ames Research Center.

  10. Gradient Boosting Machines, A Tutorial

    Directory of Open Access Journals (Sweden)

    Alexey eNatekin

    2013-12-01

    Full Text Available Gradient boosting machines are a family of powerful machine-learning techniques that have shown considerable success in a wide range of practical applications. They are highly customizable to the particular needs of the application, like being learned with respect to different loss functions. This article gives a tutorial introduction into the methodology of gradient boosting methods. A theoretical information is complemented with many descriptive examples and illustrations which cover all the stages of the gradient boosting model design. Considerations on handling the model complexity are discussed. A set of practical examples of gradient boosting applications are presented and comprehensively analyzed.

  11. Machine Learning in Computer-Aided Synthesis Planning.

    Science.gov (United States)

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

    2018-05-15

    Computer-aided synthesis planning (CASP) is focused on the goal of accelerating the process by which chemists decide how to synthesize small molecule compounds. The ideal CASP program would take a molecular structure as input and output a sorted list of detailed reaction schemes that each connect that target to purchasable starting materials via a series of chemically feasible reaction steps. Early work in this field relied on expert-crafted reaction rules and heuristics to describe possible retrosynthetic disconnections and selectivity rules but suffered from incompleteness, infeasible suggestions, and human bias. With the relatively recent availability of large reaction corpora (such as the United States Patent and Trademark Office (USPTO), Reaxys, and SciFinder databases), consisting of millions of tabulated reaction examples, it is now possible to construct and validate purely data-driven approaches to synthesis planning. As a result, synthesis planning has been opened to machine learning techniques, and the field is advancing rapidly. In this Account, we focus on two critical aspects of CASP and recent machine learning approaches to both challenges. First, we discuss the problem of retrosynthetic planning, which requires a recommender system to propose synthetic disconnections starting from a target molecule. We describe how the search strategy, necessary to overcome the exponential growth of the search space with increasing number of reaction steps, can be assisted through a learned synthetic complexity metric. We also describe how the recursive expansion can be performed by a straightforward nearest neighbor model that makes clever use of reaction data to generate high quality retrosynthetic disconnections. Second, we discuss the problem of anticipating the products of chemical reactions, which can be used to validate proposed reactions in a computer-generated synthesis plan (i.e., reduce false positives) to increase the likelihood of experimental success

  12. On the Use of Machine Learning for Identifying Botnet Network Traffic

    DEFF Research Database (Denmark)

    Stevanovic, Matija; Pedersen, Jens Myrup

    2016-01-01

    contemporary approaches use machine learning techniques for identifying malicious traffic. This paper presents a survey of contemporary botnet detection methods that rely on machine learning for identifying botnet network traffic. The paper provides a comprehensive overview on the existing scientific work thus...... contributing to the better understanding of capabilities, limitations and opportunities of using machine learning for identifying botnet traffic. Furthermore, the paper outlines possibilities for the future development of machine learning-based botnet detection systems....

  13. Mobile Vending - Benefit and limits of vending machines by using telemetry

    OpenAIRE

    Heinkele, Christian; Pousttchi, Key; Legler, Steffen

    2004-01-01

    The use of telemetry via wireless communication technique is able to support the process of operating vending machines. The advantages on appropriate kinds of vending machines can be achieved by using a demand-driven instead of a trigger-driven provisioning as well as a trouble-shooting in real time. The availability of reliable telemetrically collected real time data enhance the analysis and optimization of the supply in vending machines and the profitability of vending machine places, too. ...

  14. An automatic taxonomy of galaxy morphology using unsupervised machine learning

    Science.gov (United States)

    Hocking, Alex; Geach, James E.; Sun, Yi; Davey, Neil

    2018-01-01

    We present an unsupervised machine learning technique that automatically segments and labels galaxies in astronomical imaging surveys using only pixel data. Distinct from previous unsupervised machine learning approaches used in astronomy we use no pre-selection or pre-filtering of target galaxy type to identify galaxies that are similar. We demonstrate the technique on the Hubble Space Telescope (HST) Frontier Fields. By training the algorithm using galaxies from one field (Abell 2744) and applying the result to another (MACS 0416.1-2403), we show how the algorithm can cleanly separate early and late type galaxies without any form of pre-directed training for what an 'early' or 'late' type galaxy is. We then apply the technique to the HST Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey (CANDELS) fields, creating a catalogue of approximately 60 000 classifications. We show how the automatic classification groups galaxies of similar morphological (and photometric) type and make the classifications public via a catalogue, a visual catalogue and galaxy similarity search. We compare the CANDELS machine-based classifications to human-classifications from the Galaxy Zoo: CANDELS project. Although there is not a direct mapping between Galaxy Zoo and our hierarchical labelling, we demonstrate a good level of concordance between human and machine classifications. Finally, we show how the technique can be used to identify rarer objects and present lensed galaxy candidates from the CANDELS imaging.

  15. Tool path strategy and cutting process monitoring in intelligent machining

    Science.gov (United States)

    Chen, Ming; Wang, Chengdong; An, Qinglong; Ming, Weiwei

    2018-06-01

    Intelligent machining is a current focus in advanced manufacturing technology, and is characterized by high accuracy and efficiency. A central technology of intelligent machining—the cutting process online monitoring and optimization—is urgently needed for mass production. In this research, the cutting process online monitoring and optimization in jet engine impeller machining, cranio-maxillofacial surgery, and hydraulic servo valve deburring are introduced as examples of intelligent machining. Results show that intelligent tool path optimization and cutting process online monitoring are efficient techniques for improving the efficiency, quality, and reliability of machining.

  16. Machine-assisted verification of latent fingerprints: first results for nondestructive contact-less optical acquisition techniques with a CWL sensor

    Science.gov (United States)

    Hildebrandt, Mario; Kiltz, Stefan; Krapyvskyy, Dmytro; Dittmann, Jana; Vielhauer, Claus; Leich, Marcus

    2011-11-01

    A machine-assisted analysis of traces from crime scenes might be possible with the advent of new high-resolution non-destructive contact-less acquisition techniques for latent fingerprints. This requires reliable techniques for the automatic extraction of fingerprint features from latent and exemplar fingerprints for matching purposes using pattern recognition approaches. Therefore, we evaluate the NIST Biometric Image Software for the feature extraction and verification of contact-lessly acquired latent fingerprints to determine potential error rates. Our exemplary test setup includes 30 latent fingerprints from 5 people in two test sets that are acquired from different surfaces using a chromatic white light sensor. The first test set includes 20 fingerprints on two different surfaces. It is used to determine the feature extraction performance. The second test set includes one latent fingerprint on 10 different surfaces and an exemplar fingerprint to determine the verification performance. This utilized sensing technique does not require a physical or chemical visibility enhancement of the fingerprint residue, thus the original trace remains unaltered for further investigations. No particular feature extraction and verification techniques have been applied to such data, yet. Hence, we see the need for appropriate algorithms that are suitable to support forensic investigations.

  17. Novel jet observables from machine learning

    Science.gov (United States)

    Datta, Kaustuv; Larkoski, Andrew J.

    2018-03-01

    Previous studies have demonstrated the utility and applicability of machine learning techniques to jet physics. In this paper, we construct new observables for the discrimination of jets from different originating particles exclusively from information identified by the machine. The approach we propose is to first organize information in the jet by resolved phase space and determine the effective N -body phase space at which discrimination power saturates. This then allows for the construction of a discrimination observable from the N -body phase space coordinates. A general form of this observable can be expressed with numerous parameters that are chosen so that the observable maximizes the signal vs. background likelihood. Here, we illustrate this technique applied to discrimination of H\\to b\\overline{b} decays from massive g\\to b\\overline{b} splittings. We show that for a simple parametrization, we can construct an observable that has discrimination power comparable to, or better than, widely-used observables motivated from theory considerations. For the case of jets on which modified mass-drop tagger grooming is applied, the observable that the machine learns is essentially the angle of the dominant gluon emission off of the b\\overline{b} pair.

  18. Manufacturing tungsten monocrystal tubes by electro-spark machining and study of machined surface structure

    International Nuclear Information System (INIS)

    Abdukarimov, Eh.T.; Ismailov, L.R.; Krakhmalev, V.A.; Fershtat, L.N.

    1981-01-01

    A technique to manufacture tubes from tungsten monocrystals with low consumption of electrodes has been developed. Regimes of obtaining deep and through holes of different diameters with the productivity of 1 mm/min and with the minimum deviation from cylindrical shape are worked out using a specially designed electric pulse installation. X-ray and metallographical analyses have shown that as a result of electrospark machining a cold hardened layer is formed up to hundreds micrometers thick, pierced by the network of microcracks. Simultaneous use of electrospark and electrochemical machining permitted to manufacture tubes from tungsten monocrystals with non-distorted monocrystal surface and without a network of microcracks

  19. From Polarity to Plurality in Translation Scholarship

    Directory of Open Access Journals (Sweden)

    Abdolla Karimzadeh

    2012-09-01

    Full Text Available Review of the literature in translation studies shows that translation scholarship can be discussed in 3 Macro-levels including 1 Corpus-based studies, 2 Protocol-based studies, and 3 Systems- based studies. Researchers in the corpus-based studies test the hypothesis about the universals of translation. They also try to identify translation norms and regular linguistic patterns. This scholarship aims at showing that the language of translation is different from that of non-translation. The other purpose is to identify the techniques and strategies adopted by the translators. In protocol –based studies, the researchers study the mental activities and the individual behaviors of the translators while translating. They aim to describe the behavior of professional translators (versus translator trainees during the process of translation in a bid to identify how they chunk the source text (unit of translation and to describe how the translation trainees develop their translation competence. These studies are longitudinal for the reason that they aim to investigate the change of intended behaviors in the subjects of the study. Like corpus-based studies, they are experimental and data for analysis are collected by various methods including the translators’ verbal report, keystroke logging, eye tracking, and so on. Recently, in a method called “triangulation”, they combine the above-mentioned methods of data collection to test their hypotheses on a stronger experimental basis. To collect the data, they also employ the methods used in neurology (for example the technology of Electroencephalogram in order to obtain information on the physiological processes in the brains of the translators while translating. And finally in the systems-based studies, the researchers analyze more extended systems of production, distribution, and consumption of translations and their impacts on the target culture in a specific socio-cultural context. Differentiating

  20. The ATLAS Higgs Machine Learning Challenge

    CERN Document Server

    Cowan, Glen; The ATLAS collaboration; Bourdarios, Claire

    2015-01-01

    High Energy Physics has been using Machine Learning techniques (commonly known as Multivariate Analysis) since the 1990s with Artificial Neural Net and more recently with Boosted Decision Trees, Random Forest etc. Meanwhile, Machine Learning has become a full blown field of computer science. With the emergence of Big Data, data scientists are developing new Machine Learning algorithms to extract meaning from large heterogeneous data. HEP has exciting and difficult problems like the extraction of the Higgs boson signal, and at the same time data scientists have advanced algorithms: the goal of the HiggsML project was to bring the two together by a “challenge”: participants from all over the world and any scientific background could compete online to obtain the best Higgs to tau tau signal significance on a set of ATLAS fully simulated Monte Carlo signal and background. Instead of HEP physicists browsing through machine learning papers and trying to infer which new algorithms might be useful for HEP, then c...