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

ERIC Educational Resources Information Center

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…

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

ERIC Educational Resources Information Center

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,…

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

PubMed Central

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. PMID:27446207

Evolution of Replication Machines

PubMed Central

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

JTEC panel report on machine translation in Japan

NASA Technical Reports Server (NTRS)

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

1992-01-01

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

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

NASA Astrophysics Data System (ADS)

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.

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

ERIC Educational Resources Information Center

Williams, Lawrence

2006-01-01

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

Machine vs. human translation of SNOMED CT terms.

PubMed

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.

Retrosynthetic Reaction Prediction Using Neural Sequence-to-Sequence Models

PubMed Central

2017-01-01

We describe a fully data driven model that learns to perform a retrosynthetic reaction prediction task, which is treated as a sequence-to-sequence mapping problem. The end-to-end trained model has an encoder–decoder architecture that consists of two recurrent neural networks, which has previously shown great success in solving other sequence-to-sequence prediction tasks such as machine translation. The model is trained on 50,000 experimental reaction examples from the United States patent literature, which span 10 broad reaction types that are commonly used by medicinal chemists. We find that our model performs comparably with a rule-based expert system baseline model, and also overcomes certain limitations associated with rule-based expert systems and with any machine learning approach that contains a rule-based expert system component. Our model provides an important first step toward solving the challenging problem of computational retrosynthetic analysis. PMID:29104927

An artificial molecular machine that builds an asymmetric catalyst

NASA Astrophysics Data System (ADS)

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.

Learning Machine, Vietnamese Based Human-Computer Interface.

ERIC Educational Resources Information Center

Northwest Regional Educational Lab., Portland, OR.

The sixth session of IT@EDU98 consisted of seven papers on the topic of the learning machine--Vietnamese based human-computer interface, and was chaired by Phan Viet Hoang (Informatics College, Singapore). "Knowledge Based Approach for English Vietnamese Machine Translation" (Hoang Kiem, Dinh Dien) presents the knowledge base approach,…

A MOOC on Approaches to Machine Translation

ERIC Educational Resources Information Center

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…

Machine Translation in China--A Report.

ERIC Educational Resources Information Center

Yong-quan, Liu

1980-01-01

Reviews the history of machine translation (MT) research in China. Describes Chinese MT techniques as based on syntactic analysis, full use of fixed phrases, the key role of funtion words, and emphasis on formal analysis without neglecting meaning. (Available from ALLC, Dr. Rex Last, German Dept., Univ. of Hull, Hull HU57RX, England.) (Author/MES)

Machine Translation and Other Translation Technologies.

ERIC Educational Resources Information Center

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…

MultiMiTar: a novel multi objective optimization based miRNA-target prediction method.

PubMed

Mitra, Ramkrishna; Bandyopadhyay, Sanghamitra

2011-01-01

Machine learning based miRNA-target prediction algorithms often fail to obtain a balanced prediction accuracy in terms of both sensitivity and specificity due to lack of the gold standard of negative examples, miRNA-targeting site context specific relevant features and efficient feature selection process. Moreover, all the sequence, structure and machine learning based algorithms are unable to distribute the true positive predictions preferentially at the top of the ranked list; hence the algorithms become unreliable to the biologists. In addition, these algorithms fail to obtain considerable combination of precision and recall for the target transcripts that are translationally repressed at protein level. In the proposed article, we introduce an efficient miRNA-target prediction system MultiMiTar, a Support Vector Machine (SVM) based classifier integrated with a multiobjective metaheuristic based feature selection technique. The robust performance of the proposed method is mainly the result of using high quality negative examples and selection of biologically relevant miRNA-targeting site context specific features. The features are selected by using a novel feature selection technique AMOSA-SVM, that integrates the multi objective optimization technique Archived Multi-Objective Simulated Annealing (AMOSA) and SVM. MultiMiTar is found to achieve much higher Matthew's correlation coefficient (MCC) of 0.583 and average class-wise accuracy (ACA) of 0.8 compared to the others target prediction methods for a completely independent test data set. The obtained MCC and ACA values of these algorithms range from -0.269 to 0.155 and 0.321 to 0.582, respectively. Moreover, it shows a more balanced result in terms of precision and sensitivity (recall) for the translationally repressed data set as compared to all the other existing methods. An important aspect is that the true positive predictions are distributed preferentially at the top of the ranked list that makes MultiMiTar reliable for the biologists. MultiMiTar is now available as an online tool at www.isical.ac.in/~bioinfo_miu/multimitar.htm. MultiMiTar software can be downloaded from www.isical.ac.in/~bioinfo_miu/multimitar-download.htm.

Generalizing Word Lattice Translation

DTIC Science & Technology

2008-02-01

demonstrate substantial gains for Chinese-English and Arabic -English translation. Keywords: word lattice translation, phrase-based and hierarchical...introduce in reordering models. Our experiments evaluating the approach demonstrate substantial gains for Chinese-English and Arabic -English translation. 15...gains for Chinese-English and Arabic -English translation. 1 Introduction When Brown and colleagues introduced statistical machine translation in the

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

PubMed Central

Li, Yong; Wang, Xiufeng; Lin, Jing; Shi, Shengyu

2014-01-01

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. PMID:24473281

Application of statistical machine translation to public health information: a feasibility study.

PubMed

Kirchhoff, Katrin; Turner, Anne M; Axelrod, Amittai; Saavedra, Francisco

2011-01-01

Accurate, understandable public health information is important for ensuring the health of the nation. The large portion of the US population with Limited English Proficiency is best served by translations of public-health information into other languages. However, a large number of health departments and primary care clinics face significant barriers to fulfilling federal mandates to provide multilingual materials to Limited English Proficiency individuals. This article presents a pilot study on the feasibility of using freely available statistical machine translation technology to translate health promotion materials. The authors gathered health-promotion materials in English from local and national public-health websites. Spanish versions were created by translating the documents using a freely available machine-translation website. Translations were rated for adequacy and fluency, analyzed for errors, manually corrected by a human posteditor, and compared with exclusively manual translations. Machine translation plus postediting took 15-53 min per document, compared to the reported days or even weeks for the standard translation process. A blind comparison of machine-assisted and human translations of six documents revealed overall equivalency between machine-translated and manually translated materials. The analysis of translation errors indicated that the most important errors were word-sense errors. The results indicate that machine translation plus postediting may be an effective method of producing multilingual health materials with equivalent quality but lower cost compared to manual translations.

Application of statistical machine translation to public health information: a feasibility study

PubMed Central

Turner, Anne M; Axelrod, Amittai; Saavedra, Francisco

2011-01-01

Objective Accurate, understandable public health information is important for ensuring the health of the nation. The large portion of the US population with Limited English Proficiency is best served by translations of public-health information into other languages. However, a large number of health departments and primary care clinics face significant barriers to fulfilling federal mandates to provide multilingual materials to Limited English Proficiency individuals. This article presents a pilot study on the feasibility of using freely available statistical machine translation technology to translate health promotion materials. Design The authors gathered health-promotion materials in English from local and national public-health websites. Spanish versions were created by translating the documents using a freely available machine-translation website. Translations were rated for adequacy and fluency, analyzed for errors, manually corrected by a human posteditor, and compared with exclusively manual translations. Results Machine translation plus postediting took 15–53 min per document, compared to the reported days or even weeks for the standard translation process. A blind comparison of machine-assisted and human translations of six documents revealed overall equivalency between machine-translated and manually translated materials. The analysis of translation errors indicated that the most important errors were word-sense errors. Conclusion The results indicate that machine translation plus postediting may be an effective method of producing multilingual health materials with equivalent quality but lower cost compared to manual translations. PMID:21498805

An introduction to quantum machine learning

NASA Astrophysics Data System (ADS)

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.

Modeling workflow to design machine translation applications for public health practice

PubMed Central

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

2014-01-01

Objective 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). Materials and Methods 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. Results 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. Discussion 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. Counclusion 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. PMID:25445922

Research in Chinese-English Machine Translation. Final Report.

ERIC Educational Resources Information Center

Wang, William S-Y.; And Others

This report documents results of a two-year effort toward the study and investigation of the design of a prototype system for Chinese-English machine translation in the general area of physics. Previous work in Chinese-English machine translation is reviewed. Grammatical considerations in machine translation are discussed and detailed aspects of…

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dixon, Kevin R.

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

A Double-Sided Linear Primary Permanent Magnet Vernier Machine

PubMed Central

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. PMID:25874250

A double-sided linear primary permanent magnet vernier machine.

PubMed

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.

Gesture-Controlled Interfaces for Self-Service Machines

NASA Technical Reports Server (NTRS)

Cohen, Charles J.; Beach, Glenn

2006-01-01

Gesture-controlled interfaces are software- driven systems that facilitate device control by translating visual hand and body signals into commands. Such interfaces could be especially attractive for controlling self-service machines (SSMs) for example, public information kiosks, ticket dispensers, gasoline pumps, and automated teller machines (see figure). A gesture-controlled interface would include a vision subsystem comprising one or more charge-coupled-device video cameras (at least two would be needed to acquire three-dimensional images of gestures). The output of the vision system would be processed by a pure software gesture-recognition subsystem. Then a translator subsystem would convert a sequence of recognized gestures into commands for the SSM to be controlled; these could include, for example, a command to display requested information, change control settings, or actuate a ticket- or cash-dispensing mechanism. Depending on the design and operational requirements of the SSM to be controlled, the gesture-controlled interface could be designed to respond to specific static gestures, dynamic gestures, or both. Static and dynamic gestures can include stationary or moving hand signals, arm poses or motions, and/or whole-body postures or motions. Static gestures would be recognized on the basis of their shapes; dynamic gestures would be recognized on the basis of both their shapes and their motions. Because dynamic gestures include temporal as well as spatial content, this gesture- controlled interface can extract more information from dynamic than it can from static gestures.

Identifying the Machine Translation Error Types with the Greatest Impact on Post-editing Effort.

PubMed

Daems, Joke; Vandepitte, Sonia; Hartsuiker, Robert J; Macken, Lieve

2017-01-01

Translation Environment Tools make translators' work easier by providing them with term lists, translation memories and machine translation output. Ideally, such tools automatically predict whether it is more effortful to post-edit than to translate from scratch, and determine whether or not to provide translators with machine translation output. Current machine translation quality estimation systems heavily rely on automatic metrics, even though they do not accurately capture actual post-editing effort. In addition, these systems do not take translator experience into account, even though novices' translation processes are different from those of professional translators. In this paper, we report on the impact of machine translation errors on various types of post-editing effort indicators, for professional translators as well as student translators. We compare the impact of MT quality on a product effort indicator (HTER) with that on various process effort indicators. The translation and post-editing process of student translators and professional translators was logged with a combination of keystroke logging and eye-tracking, and the MT output was analyzed with a fine-grained translation quality assessment approach. We find that most post-editing effort indicators (product as well as process) are influenced by machine translation quality, but that different error types affect different post-editing effort indicators, confirming that a more fine-grained MT quality analysis is needed to correctly estimate actual post-editing effort. Coherence, meaning shifts, and structural issues are shown to be good indicators of post-editing effort. The additional impact of experience on these interactions between MT quality and post-editing effort is smaller than expected.

Identifying the Machine Translation Error Types with the Greatest Impact on Post-editing Effort

PubMed Central

Daems, Joke; Vandepitte, Sonia; Hartsuiker, Robert J.; Macken, Lieve

2017-01-01

Translation Environment Tools make translators’ work easier by providing them with term lists, translation memories and machine translation output. Ideally, such tools automatically predict whether it is more effortful to post-edit than to translate from scratch, and determine whether or not to provide translators with machine translation output. Current machine translation quality estimation systems heavily rely on automatic metrics, even though they do not accurately capture actual post-editing effort. In addition, these systems do not take translator experience into account, even though novices’ translation processes are different from those of professional translators. In this paper, we report on the impact of machine translation errors on various types of post-editing effort indicators, for professional translators as well as student translators. We compare the impact of MT quality on a product effort indicator (HTER) with that on various process effort indicators. The translation and post-editing process of student translators and professional translators was logged with a combination of keystroke logging and eye-tracking, and the MT output was analyzed with a fine-grained translation quality assessment approach. We find that most post-editing effort indicators (product as well as process) are influenced by machine translation quality, but that different error types affect different post-editing effort indicators, confirming that a more fine-grained MT quality analysis is needed to correctly estimate actual post-editing effort. Coherence, meaning shifts, and structural issues are shown to be good indicators of post-editing effort. The additional impact of experience on these interactions between MT quality and post-editing effort is smaller than expected. PMID:28824482

Machine Translation Project

NASA Technical Reports Server (NTRS)

Bajis, Katie

1993-01-01

The characteristics and capabilities of existing machine translation systems were examined and procurement recommendations were developed. Four systems, SYSTRAN, GLOBALINK, PC TRANSLATOR, and STYLUS, were determined to meet the NASA requirements for a machine translation system. Initially, four language pairs were selected for implementation. These are Russian-English, French-English, German-English, and Japanese-English.

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

ERIC Educational Resources Information Center

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,…

Thermally triggered polyrotaxane translational motion helps proton transfer.

PubMed

Ge, Xiaolin; He, Yubin; Liang, Xian; Wu, Liang; Zhu, Yuan; Yang, Zhengjin; Hu, Min; Xu, Tongwen

2018-06-12

Synthetic polyelectrolytes, capable of fast transporting protons, represent a challenging target for membrane engineering in so many fields, for example, fuel cells, redox flow batteries, etc. Inspired by the fast advance in molecular machines, here we report a rotaxane based polymer entity assembled via host-guest interaction and prove that by exploiting the thermally triggered translational motion (although not in a controlled manner) of mechanically bonded rotaxane, exceptionally fast proton transfer can be fulfilled at an external thermal input. The relative motion of the sulfonated axle to the ring in rotaxane happens at ~60 °C in our cases and because of that a proton conductivity (indicating proton transfer rate) of 260.2 mS cm -1 , which is much higher than that in the state-of-the-art Nafion, is obtained at a relatively low ion-exchange capacity (representing the amount of proton transfer groups) of 0.73 mmol g -1 .

A visual programming environment for the Navier-Stokes computer

NASA Technical Reports Server (NTRS)

Tomboulian, Sherryl; Crockett, Thomas W.; Middleton, David

1988-01-01

The Navier-Stokes computer is a high-performance, reconfigurable, pipelined machine designed to solve large computational fluid dynamics problems. Due to the complexity of the architecture, development of effective, high-level language compilers for the system appears to be a very difficult task. Consequently, a visual programming methodology has been developed which allows users to program the system at an architectural level by constructing diagrams of the pipeline configuration. These schematic program representations can then be checked for validity and automatically translated into machine code. The visual environment is illustrated by using a prototype graphical editor to program an example problem.

Statistical machine translation for biomedical text: are we there yet?

PubMed

Wu, Cuijun; Xia, Fei; Deleger, Louise; Solti, Imre

2011-01-01

In our paper we addressed the research question: "Has machine translation achieved sufficiently high quality to translate PubMed titles for patients?". We analyzed statistical machine translation output for six foreign language - English translation pairs (bi-directionally). We built a high performing in-house system and evaluated its output for each translation pair on large scale both with automated BLEU scores and human judgment. In addition to the in-house system, we also evaluated Google Translate's performance specifically within the biomedical domain. We report high performance for German, French and Spanish -- English bi-directional translation pairs for both Google Translate and our system.

Second Evaluation of the SYSTRAN Automatic Translation System. Final Report.

ERIC Educational Resources Information Center

Van Slype, Georges

The machine translation system SYSTRAN was assessed for translation quality and system productivity. The test was carried out on translations from English to French dealing with food science and technology. Machine translations were compared to manual translations of the same texts. SYSTRAN was found to be a useful system of information…

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

ERIC Educational Resources Information Center

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…

Translation: Aids, Robots, and Automation.

ERIC Educational Resources Information Center

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)

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

ERIC Educational Resources Information Center

Wu, Dan; He, Daqing

2012-01-01

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

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

ERIC Educational Resources Information Center

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…

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

NASA Astrophysics Data System (ADS)

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.

Domain-Adapted Convolutional Networks for Satellite Image Classification: A Large-Scale Interactive Learning Workflow

DOE PAGES

Lunga, Dalton D.; Yang, Hsiuhan Lexie; Reith, Andrew E.; ...

2018-02-06

Satellite imagery often exhibits large spatial extent areas that encompass object classes with considerable variability. This often limits large-scale model generalization with machine learning algorithms. Notably, acquisition conditions, including dates, sensor position, lighting condition, and sensor types, often translate into class distribution shifts introducing complex nonlinear factors and hamper the potential impact of machine learning classifiers. Here, this article investigates the challenge of exploiting satellite images using convolutional neural networks (CNN) for settlement classification where the class distribution shifts are significant. We present a large-scale human settlement mapping workflow based-off multiple modules to adapt a pretrained CNN to address themore » negative impact of distribution shift on classification performance. To extend a locally trained classifier onto large spatial extents areas we introduce several submodules: First, a human-in-the-loop element for relabeling of misclassified target domain samples to generate representative examples for model adaptation; second, an efficient hashing module to minimize redundancy and noisy samples from the mass-selected examples; and third, a novel relevance ranking module to minimize the dominance of source example on the target domain. The workflow presents a novel and practical approach to achieve large-scale domain adaptation with binary classifiers that are based-off CNN features. Experimental evaluations are conducted on areas of interest that encompass various image characteristics, including multisensors, multitemporal, and multiangular conditions. Domain adaptation is assessed on source–target pairs through the transfer loss and transfer ratio metrics to illustrate the utility of the workflow.« less

Domain-Adapted Convolutional Networks for Satellite Image Classification: A Large-Scale Interactive Learning Workflow

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lunga, Dalton D.; Yang, Hsiuhan Lexie; Reith, Andrew E.

Satellite imagery often exhibits large spatial extent areas that encompass object classes with considerable variability. This often limits large-scale model generalization with machine learning algorithms. Notably, acquisition conditions, including dates, sensor position, lighting condition, and sensor types, often translate into class distribution shifts introducing complex nonlinear factors and hamper the potential impact of machine learning classifiers. Here, this article investigates the challenge of exploiting satellite images using convolutional neural networks (CNN) for settlement classification where the class distribution shifts are significant. We present a large-scale human settlement mapping workflow based-off multiple modules to adapt a pretrained CNN to address themore » negative impact of distribution shift on classification performance. To extend a locally trained classifier onto large spatial extents areas we introduce several submodules: First, a human-in-the-loop element for relabeling of misclassified target domain samples to generate representative examples for model adaptation; second, an efficient hashing module to minimize redundancy and noisy samples from the mass-selected examples; and third, a novel relevance ranking module to minimize the dominance of source example on the target domain. The workflow presents a novel and practical approach to achieve large-scale domain adaptation with binary classifiers that are based-off CNN features. Experimental evaluations are conducted on areas of interest that encompass various image characteristics, including multisensors, multitemporal, and multiangular conditions. Domain adaptation is assessed on source–target pairs through the transfer loss and transfer ratio metrics to illustrate the utility of the workflow.« less

Feasibility Study on Fully Automatic High Quality Translation: Volume II. Final Technical Report.

ERIC Educational Resources Information Center

Lehmann, Winifred P.; Stachowitz, Rolf

This second volume of a two-volume report on a fully automatic high quality translation (FAHQT) contains relevant papers contributed by specialists on the topic of machine translation. The papers presented here cover such topics as syntactical analysis in transformational grammar and in machine translation, lexical features in translation and…

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

DTIC Science & Technology

1987-12-01

C*TENDONOSLA*) C*YENDO NOS LA *))) 0 %4 APPENDIX D. TRANSLATION SYSTEM PARAMETERS 222 0 1 :MERGES I ((A EL LADO DE ) (AL-.LADO- DE )) ((ACERCA DE ...not only permits a language to be de - ’Slocuim’s system ( 1994a) relies on a separate set of context-free language-specific rules for each source and...requirements as small subject domain, narrow linguistic coverage, and enormous lexical entries (as found in exclusively semantic-based systems). Thus

Information as Resoures ; A View toward the 2lst Century - Let's Construct Databases by Ourselves -

NASA Astrophysics Data System (ADS)

Ohmi, Akira

A highly-developed information-oriented society based on “Information Network Technology” will be realized in the 21st century. In enterprises, fundamental research will be regarded as important more and more, and the effective use of information as resources will be indispensable. From the viewpoint of international distribution of information there is a criticism that Japan has been offering the information on science and technology insufficiently to the overseas countries, but, for example, in the steel industry lots of house-organ technical journals in English version has been offered overseas. And recently several information firms have started translating Japanese information into English and providing overseas. However, there are some problems to be taken into consideration; 1. The information is not integrated, 2. there is not any co-ordination among the firms, 3. others. Then the author proposes communal use of machine translation system and construction of database for overseas that integrate such firms” work preserving each individuality.

Adding Statistical Machine Translation Adaptation to Computer-Assisted Translation

DTIC Science & Technology

2013-09-01

are automatically searched and used to suggest possible translations; (2) spell-checkers; (3) glossaries; (4) dictionaries ; (5) alignment and...matching against TMs to propose translations; spell-checking, glossary, and dictionary look-up; support for multiple file formats; regular expressions...on Telecommunications. Tehran, 2012, 822–826. Bertoldi, N.; Federico, M. Domain Adaptation for Statistical Machine Translation with Monolingual

Machine Translation for Academic Purposes

ERIC Educational Resources Information Center

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…

PC-assisted translation of photogrammetric papers

NASA Astrophysics Data System (ADS)

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.

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

PubMed

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.

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

ERIC Educational Resources Information Center

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…

Statistical Machine Translation of Japanese

DTIC Science & Technology

2007-03-01

hiragana and katakana) syllabaries…………………….. 20 3.2 Sample Japanese sentence showing kanji and kana……………………... 21 3.5 Japanese formality example...syllabary. 19 Figure 3.1. Japanese kana syllabaries, hiragana for native Japanese words, word endings, and particles, and katakana for foreign...Figure 3.2. Simple Japanese sentence showing the use of kanji, hiragana , and katakana. Kanji is used for nouns and verb, adjective, and

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

ERIC Educational Resources Information Center

Steding, Soren

2009-01-01

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

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

ERIC Educational Resources Information Center

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

2008-01-01

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

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

PubMed

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

2016-01-01

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

Soviet Patent Bulletin Processing: A Particular Application of Machine Translation.

ERIC Educational Resources Information Center

Bostad, Dale A.

1985-01-01

Describes some of the processes involved in the data structure manipulation and machine translation of a specific text form, namely, Soviet patent bulletins. The effort to modify this system in order to do specialized processing and translation is detailed. (Author/SED)

Automatic translation among spoken languages

NASA Technical Reports Server (NTRS)

Walter, Sharon M.; Costigan, Kelly

1994-01-01

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

A translator and simulator for the Burroughs D machine

NASA Technical Reports Server (NTRS)

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.

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

ERIC Educational Resources Information Center

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

2008-01-01

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

E-TIF: An Electronic Terminology Interchange Format.

ERIC Educational Resources Information Center

Melby, Alan

1995-01-01

Emphasizes the importance of terminology in an age of machine-based translation systems. Discusses differences between lexicography and terminology. Concludes with an argument for a new system based on the Text Encoding Initiative-based notions of elements and attributes. (CFR)

Impact and Estimation of Balance Coordinate System Rotations and Translations in Wind-Tunnel Testing

NASA Technical Reports Server (NTRS)

Toro, Kenneth G.; Parker, Peter A.

2017-01-01

Discrepancies between the model and balance coordinate systems lead to biases in the aerodynamic measurements during wind-tunnel testing. The reference coordinate system relative to the calibration coordinate system at which the forces and moments are resolved is crucial to the overall accuracy of force measurements. This paper discusses sources of discrepancies and estimates of coordinate system rotation and translation due to machining and assembly differences. A methodology for numerically estimating the coordinate system biases will be discussed and developed. Two case studies are presented using this methodology to estimate the model alignment. Examples span from angle measurement system shifts on the calibration system to discrepancies in actual wind-tunnel data. The results from these case-studies will help aerodynamic researchers and force balance engineers to better the understand and identify potential differences in calibration systems due to coordinate system rotation and translation.

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

NASA Astrophysics Data System (ADS)

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.

Machine translation project alternatives analysis

NASA Technical Reports Server (NTRS)

Bajis, Catherine J.; Bedford, Denise A. D.

1993-01-01

The Machine Translation Project consists of several components, two of which, the Project Plan and the Requirements Analysis, have already been delivered. The Project Plan details the overall rationale, objectives and time-table for the project as a whole. The Requirements Analysis compares a number of available machine translation systems, their capabilities, possible configurations, and costs. The Alternatives Analysis has resulted in a number of conclusions and recommendations to the NASA STI program concerning the acquisition of specific MT systems and related hardware and software.

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

NASA Astrophysics Data System (ADS)

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.

Interlingual Machine Translation: Prospects and Setbacks

ERIC Educational Resources Information Center

Acikgoz, Firat; Sert, Olcay

2006-01-01

This study, in an attempt to rise above the intricacy of "being informed on the verge of globalization," is founded on the premise that Machine Translation (MT) applications searching for an ideal key to find a universal foundation for all natural languages have a restricted say over the translation process at various discourse levels. Our paper…

Biosignature Discovery for Substance Use Disorders Using Statistical Learning.

PubMed

Baurley, James W; McMahan, Christopher S; Ervin, Carolyn M; Pardamean, Bens; Bergen, Andrew W

2018-02-01

There are limited biomarkers for substance use disorders (SUDs). Traditional statistical approaches are identifying simple biomarkers in large samples, but clinical use cases are still being established. High-throughput clinical, imaging, and 'omic' technologies are generating data from SUD studies and may lead to more sophisticated and clinically useful models. However, analytic strategies suited for high-dimensional data are not regularly used. We review strategies for identifying biomarkers and biosignatures from high-dimensional data types. Focusing on penalized regression and Bayesian approaches, we address how to leverage evidence from existing studies and knowledge bases, using nicotine metabolism as an example. We posit that big data and machine learning approaches will considerably advance SUD biomarker discovery. However, translation to clinical practice, will require integrated scientific efforts. Copyright © 2017 Elsevier Ltd. All rights reserved.

U.S. Army Research Laboratory (ARL) Corporate Dari Document Transcription and Translation Guidelines

DTIC Science & Technology

2012-10-01

text file format. 15. SUBJECT TERMS Transcription, Translation, guidelines, ground truth, Optical character recognition , OCR, Machine Translation, MT...foreign language into a target language in order to train, test, and evaluate optical character recognition (OCR) and machine translation (MT) embedded...graphic element and should not be transcribed. Elements that are not part of the primary text such as handwritten annotations or stamps should not be

The Linguistic Core Approach to StructuredTranslation and Analysis of Low Resource Languages

DTIC Science & Technology

2017-09-02

grammars from no training data and partial training data (as given by GFL). We are now anno - tating GFL for English, Portuguese, Chinese and...translation. In Proc. EMNLP, 2014. [20] F. Drewes, H.- J . Kreowski, and A. Habel. Hyperedge replacement graph grammars. Handbook of Graph Grammars, 1:95–162...tory, Jena, 2015. [41] B. Jones, J . Andreas, D. Bauer, K-M. Hermann, and K. Knight. Semantics- based machine translation with hyperedge replacement

Classifying publications from the clinical and translational science award program along the translational research spectrum: a machine learning approach.

PubMed

Surkis, Alisa; Hogle, Janice A; DiazGranados, Deborah; Hunt, Joe D; Mazmanian, Paul E; Connors, Emily; Westaby, Kate; Whipple, Elizabeth C; Adamus, Trisha; Mueller, Meridith; Aphinyanaphongs, Yindalon

2016-08-05

Translational research is a key area of focus of the National Institutes of Health (NIH), as demonstrated by the substantial investment in the Clinical and Translational Science Award (CTSA) program. The goal of the CTSA program is to accelerate the translation of discoveries from the bench to the bedside and into communities. Different classification systems have been used to capture the spectrum of basic to clinical to population health research, with substantial differences in the number of categories and their definitions. Evaluation of the effectiveness of the CTSA program and of translational research in general is hampered by the lack of rigor in these definitions and their application. This study adds rigor to the classification process by creating a checklist to evaluate publications across the translational spectrum and operationalizes these classifications by building machine learning-based text classifiers to categorize these publications. Based on collaboratively developed definitions, we created a detailed checklist for categories along the translational spectrum from T0 to T4. We applied the checklist to CTSA-linked publications to construct a set of coded publications for use in training machine learning-based text classifiers to classify publications within these categories. The training sets combined T1/T2 and T3/T4 categories due to low frequency of these publication types compared to the frequency of T0 publications. We then compared classifier performance across different algorithms and feature sets and applied the classifiers to all publications in PubMed indexed to CTSA grants. To validate the algorithm, we manually classified the articles with the top 100 scores from each classifier. The definitions and checklist facilitated classification and resulted in good inter-rater reliability for coding publications for the training set. Very good performance was achieved for the classifiers as represented by the area under the receiver operating curves (AUC), with an AUC of 0.94 for the T0 classifier, 0.84 for T1/T2, and 0.92 for T3/T4. The combination of definitions agreed upon by five CTSA hubs, a checklist that facilitates more uniform definition interpretation, and algorithms that perform well in classifying publications along the translational spectrum provide a basis for establishing and applying uniform definitions of translational research categories. The classification algorithms allow publication analyses that would not be feasible with manual classification, such as assessing the distribution and trends of publications across the CTSA network and comparing the categories of publications and their citations to assess knowledge transfer across the translational research spectrum.

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

PubMed

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 MT. Certain improvements are also obtained from German compound splitting on the source language side. Translation quality, however, does not appear to correlate with the IR performance - better translation does not necessarily yield better retrieval. We discuss in detail the contribution of the individual techniques and state-of-the-art features and provide future research directions. Copyright © 2014 Elsevier B.V. All rights reserved.

A Conjoint Analysis Framework for Evaluating User Preferences in Machine Translation

PubMed Central

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

2013-01-01

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. PMID:24683295

Machine Translation of Public Health Materials From English to Chinese: A Feasibility Study

PubMed Central

Desai, Loma

2015-01-01

Background Chinese is the second most common language spoken by limited English proficiency individuals in the United States, yet there are few public health materials available in Chinese. Previous studies have indicated that use of machine translation plus postediting by bilingual translators generated quality translations in a lower time and at a lower cost than human translations. Objective The purpose of this study was to investigate the feasibility of using machine translation (MT) tools (eg, Google Translate) followed by human postediting (PE) to produce quality Chinese translations of public health materials. Methods From state and national public health websites, we collected 60 health promotion documents that had been translated from English to Chinese through human translation. The English version of the documents were then translated to Chinese using Google Translate. The MTs were analyzed for translation errors. A subset of the MT documents was postedited by native Chinese speakers with health backgrounds. Postediting time was measured. Postedited versions were then blindly compared against human translations by bilingual native Chinese quality raters. Results The most common machine translation errors were errors of word sense (40%) and word order (22%). Posteditors corrected the MTs at a rate of approximately 41 characters per minute. Raters, blinded to the source of translation, consistently selected the human translation over the MT+PE. Initial investigation to determine the reasons for the lower quality of MT+PE indicate that poor MT quality, lack of posteditor expertise, and insufficient posteditor instructions can be barriers to producing quality Chinese translations. Conclusions Our results revealed problems with using MT tools plus human postediting for translating public health materials from English to Chinese. Additional work is needed to improve MT and to carefully design postediting processes before the MT+PE approach can be used routinely in public health practice for a variety of language pairs. PMID:27227135

Machine Translation-Assisted Language Learning: Writing for Beginners

ERIC Educational Resources Information Center

Garcia, Ignacio; Pena, Maria Isabel

2011-01-01

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

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

ERIC Educational Resources Information Center

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

2013-01-01

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

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

ERIC Educational Resources Information Center

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)

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

ERIC Educational Resources Information Center

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…

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

NASA Astrophysics Data System (ADS)

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.

Biologically-inspired robust and adaptive multi-sensor fusion and active control

NASA Astrophysics Data System (ADS)

Khosla, Deepak; Dow, Paul A.; Huber, David J.

2009-04-01

In this paper, we describe a method and system for robust and efficient goal-oriented active control of a machine (e.g., robot) based on processing, hierarchical spatial understanding, representation and memory of multimodal sensory inputs. This work assumes that a high-level plan or goal is known a priori or is provided by an operator interface, which translates into an overall perceptual processing strategy for the machine. Its analogy to the human brain is the download of plans and decisions from the pre-frontal cortex into various perceptual working memories as a perceptual plan that then guides the sensory data collection and processing. For example, a goal might be to look for specific colored objects in a scene while also looking for specific sound sources. This paper combines three key ideas and methods into a single closed-loop active control system. (1) Use high-level plan or goal to determine and prioritize spatial locations or waypoints (targets) in multimodal sensory space; (2) collect/store information about these spatial locations at the appropriate hierarchy and representation in a spatial working memory. This includes invariant learning of these spatial representations and how to convert between them; and (3) execute actions based on ordered retrieval of these spatial locations from hierarchical spatial working memory and using the "right" level of representation that can efficiently translate into motor actions. In its most specific form, the active control is described for a vision system (such as a pantilt- zoom camera system mounted on a robotic head and neck unit) which finds and then fixates on high saliency visual objects. We also describe the approach where the goal is to turn towards and sequentially foveate on salient multimodal cues that include both visual and auditory inputs.

NASA's online machine aided indexing system

NASA Technical Reports Server (NTRS)

Silvester, June P.; Genuardi, Michael T.; Klingbiel, Paul H.

1993-01-01

This report describes the NASA Lexical Dictionary, a machine aided indexing system used online at the National Aeronautics and Space Administration's Center for Aerospace Information (CASI). This system is comprised of a text processor that is based on the computational, non-syntactic analysis of input text, and an extensive 'knowledge base' that serves to recognize and translate text-extracted concepts. The structure and function of the various NLD system components are described in detail. Methods used for the development of the knowledge base are discussed. Particular attention is given to a statistically-based text analysis program that provides the knowledge base developer with a list of concept-specific phrases extracted from large textual corpora. Production and quality benefits resulting from the integration of machine aided indexing at CASI are discussed along with a number of secondary applications of NLD-derived systems including on-line spell checking and machine aided lexicography.

Translation Analysis on Civil Engineering Text Produced by Machine Translator

NASA Astrophysics Data System (ADS)

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.

Complex Networks Analysis of Manual and Machine Translations

NASA Astrophysics Data System (ADS)

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

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

Machine-aided indexing at NASA

NASA Technical Reports Server (NTRS)

Silvester, June P.; Genuardi, Michael T.; Klingbiel, Paul H.

1994-01-01

This report describes the NASA Lexical Dictionary (NLD), a machine-aided indexing system used online at the National Aeronautics and Space Administration's Center for AeroSpace Information (CASI). This system automatically suggests a set of candidate terms from NASA's controlled vocabulary for any designated natural language text input. The system is comprised of a text processor that is based on the computational, nonsyntactic analysis of input text and an extensive knowledge base that serves to recognize and translate text-extracted concepts. The functions of the various NLD system components are described in detail, and production and quality benefits resulting from the implementation of machine-aided indexing at CASI are discussed.

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

PubMed

Yu, Wei; Clyne, Melinda; Dolan, Siobhan M; Yesupriya, Ajay; Wulf, Anja; Liu, Tiebin; Khoury, Muin J; Gwinn, Marta

2008-04-22

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. 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. 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.

Experiments with Cross-Language Information Retrieval on a Health Portal for Psychology and Psychotherapy.

PubMed

Andrenucci, Andrea

2016-01-01

Few studies have been performed within cross-language information retrieval (CLIR) in the field of psychology and psychotherapy. The aim of this paper is to to analyze and assess the quality of available query translation methods for CLIR on a health portal for psychology. A test base of 100 user queries, 50 Multi Word Units (WUs) and 50 Single WUs, was used. Swedish was the source language and English the target language. Query translation methods based on machine translation (MT) and dictionary look-up were utilized in order to submit query translations to two search engines: Google Site Search and Quick Ask. Standard IR evaluation measures and a qualitative analysis were utilized to assess the results. The lexicon extracted with word alignment of the portal's parallel corpus provided better statistical results among dictionary look-ups. Google Translate provided more linguistically correct translations overall and also delivered better retrieval results in MT.

Evaluating the Use of Machine Translation Post-Editing in the Foreign Language Class

ERIC Educational Resources Information Center

Nino, Ana

2008-01-01

Generalised access to the Internet and globalisation has led to increased demand for translation services and a resurgence in the use of machine translation (MT) systems. MT post-editing or the correction of MT output to an acceptable standard is known to be one of the ways to face the huge demand on multilingual communication. Given that the use…

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

PubMed

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.

Quantum Support Vector Machine for Big Data Classification

NASA Astrophysics Data System (ADS)

Rebentrost, Patrick; Mohseni, Masoud; Lloyd, Seth

2014-09-01

Supervised machine learning is the classification of new data based on already classified training examples. In this work, we show that the support vector machine, an optimized binary classifier, can be implemented on a quantum computer, with complexity logarithmic in the size of the vectors and the number of training examples. In cases where classical sampling algorithms require polynomial time, an exponential speedup is obtained. At the core of this quantum big data algorithm is a nonsparse matrix exponentiation technique for efficiently performing a matrix inversion of the training data inner-product (kernel) matrix.

Machine Aids to Translation.

ERIC Educational Resources Information Center

Brinkmann, Karl-Heinz

1981-01-01

Describes the TEAM Program System of the Siemens Language Services Department, particularly the main features of its terminology data bank. Discusses criteria to which stored terminology must conform and methods of data bank utilization. Concludes by summarizing the consequences that machine-aided translation development has had for the…

Machine Translation: The Alternative for the 21st Century?

ERIC Educational Resources Information Center

Cribb, V. Michael

2000-01-01

Outlines a scenario for the future of Teaching English as a Second or Other Languages that has seldom, if ever been considered in academic discussion: that advances in and availability of quality machine translation could mitigate the need for English language learning. (Author/VWL)

A Survey of Statistical Machine Translation

DTIC Science & Technology

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

Collective helicity switching of a DNA-coat assembly

NASA Astrophysics Data System (ADS)

Kim, Yongju; Li, Huichang; He, Ying; Chen, Xi; Ma, Xiaoteng; Lee, Myongsoo

2017-07-01

Hierarchical assemblies of biomolecular subunits can carry out versatile tasks at the cellular level with remarkable spatial and temporal precision. As an example, the collective motion and mutual cooperation between complex protein machines mediate essential functions for life, such as replication, synthesis, degradation, repair and transport. Nucleic acid molecules are far less dynamic than proteins and need to bind to specific proteins to form hierarchical structures. The simplest example of these nucleic acid-based structures is provided by a rod-shaped tobacco mosaic virus, which consists of genetic material surrounded by coat proteins. Inspired by the complexity and hierarchical assembly of viruses, a great deal of effort has been devoted to design similarly constructed artificial viruses. However, such a wrapping approach makes nucleic acid dynamics insensitive to environmental changes. This limitation generally restricts, for example, the amplification of the conformational dynamics between the right-handed B form to the left-handed Z form of double-stranded deoxyribonucleic acid (DNA). Here we report a virus-like hierarchical assembly in which the native DNA and a synthetic coat undergo repeated collective helicity switching triggered by pH change under physiological conditions. We also show that this collective helicity inversion occurs during translocation of the DNA-coat assembly into intracellular compartments. Translating DNA conformational dynamics into a higher level of hierarchical dynamics may provide an approach to create DNA-based nanomachines.

Machine Learning and Radiology

PubMed Central

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

Support vector machine and mel frequency Cepstral coefficient based algorithm for hand gestures and bidirectional speech to text device

NASA Astrophysics Data System (ADS)

Balbin, Jessie R.; Padilla, Dionis A.; Fausto, Janette C.; Vergara, Ernesto M.; Garcia, Ramon G.; Delos Angeles, Bethsedea Joy S.; Dizon, Neil John A.; Mardo, Mark Kevin N.

2017-02-01

This research is about translating series of hand gesture to form a word and produce its equivalent sound on how it is read and said in Filipino accent using Support Vector Machine and Mel Frequency Cepstral Coefficient analysis. The concept is to detect Filipino speech input and translate the spoken words to their text form in Filipino. This study is trying to help the Filipino deaf community to impart their thoughts through the use of hand gestures and be able to communicate to people who do not know how to read hand gestures. This also helps literate deaf to simply read the spoken words relayed to them using the Filipino speech to text system.

Air-Bearing-Piston Suspension System

NASA Technical Reports Server (NTRS)

Mullen, Donald; Bishop, Stephen J.

1992-01-01

Suspension system based on air-bearing piston holds up steel ball against gravitation while allowing ball to translate vertically and rotate freely. System designed to simulate effect of microgravity on ball. Applicable to suppression of vibrations and delicate machining processes.

Rapid Prototyping in Technology Education.

ERIC Educational Resources Information Center

Flowers, Jim; Moniz, Matt

2002-01-01

Describes how technology education majors are using a high-tech model builder, called a fused deposition modeling machine, to develop their models directly from computer-based designs without any machining. Gives examples of applications in technology education. (JOW)

Translational Research from an Informatics Perspective

NASA Technical Reports Server (NTRS)

Bernstam, Elmer; Meric-Bernstam, Funda; Johnson-Throop, Kathy A.; Turley, James P.; Smith, Jack W.

2007-01-01

Clinical and translational research (CTR) is an essential part of a sustainable global health system. Informatics is now recognized as an important en-abler of CTR and informaticians are increasingly called upon to help CTR efforts. The US National Institutes of Health mandated biomedical informatics activity as part of its new national CTR grant initiative, the Clinical and Translational Science Award (CTSA). Traditionally, translational re-search was defined as the translation of laboratory discoveries to patient care (bench to bedside). We argue, however, that there are many other kinds of translational research. Indeed, translational re-search requires the translation of knowledge dis-covered in one domain to another domain and is therefore an information-based activity. In this panel, we will expand upon this view of translational research and present three different examples of translation to illustrate the point: 1) bench to bedside, 2) Earth to space and 3) academia to community. We will conclude with a discussion of our local translational research efforts that draw on each of the three examples.

Development of German-English Machine Translation System.

ERIC Educational Resources Information Center

Lehmann, Winifred P.; Stachowitz, Rolf

This report documents efforts over a five-month period toward completion of a pilot system for machine translation of German scientific and technical literature into English. The report is divided into three areas: grammar formalism, programming, and linguistics. Work on grammar formalism concentrated mainly on increasing the power of the…

MACHINE TRANSLATION RESEARCH DURING THE PAST TWO YEARS.

ERIC Educational Resources Information Center

LEHMANN, W.P.

THE AUTHOR RECOUNTS THE RISE IN IMPORTANCE OF MACHINE TRANSLATION, WHICH TOGETHER WITH LANGUAGE LEARNING AND TEACHING COMPRISE THE MAJOR FIELDS OF APPLIED LINGUISTICS. MUCH OF THE RECENT THEORETICAL WORK ON LANGUAGE DEALS WITH THE PROBLEM OF THE RELATIONSHIP BETWEEN THE SURFACE SYNTACTIC STRUCTURE OF LANGUAGE AND THE UNDERLYING STRUCTURE. THE…

Mean of the typical decoding rates: a new translation efficiency index based on the analysis of ribosome profiling data.

PubMed

Dana, Alexandra; Tuller, Tamir

2014-12-01

Gene translation modeling and prediction is a fundamental problem that has numerous biomedical implementations. In this work we present a novel, user-friendly tool/index for calculating the mean of the typical decoding rates that enables predicting translation elongation efficiency of protein coding genes for different tissue types, developmental stages, and experimental conditions. The suggested translation efficiency index is based on the analysis of the organism's ribosome profiling data. This index could be used for example to predict changes in translation elongation efficiency of lowly expressed genes that usually have relatively low and/or biased ribosomal densities and protein levels measurements, or can be used for example for predicting translation efficiency of new genetically engineered genes. We demonstrate the usability of this index via the analysis of six organisms in different tissues and developmental stages. Distributable cross platform application and guideline are available for download at: http://www.cs.tau.ac.il/~tamirtul/MTDR/MTDR_Install.html. Copyright © 2015 Dana and Tuller.

Advanced Cell Classifier: User-Friendly Machine-Learning-Based Software for Discovering Phenotypes in High-Content Imaging Data.

PubMed

Piccinini, Filippo; Balassa, Tamas; Szkalisity, Abel; Molnar, Csaba; Paavolainen, Lassi; Kujala, Kaisa; Buzas, Krisztina; Sarazova, Marie; Pietiainen, Vilja; Kutay, Ulrike; Smith, Kevin; Horvath, Peter

2017-06-28

High-content, imaging-based screens now routinely generate data on a scale that precludes manual verification and interrogation. Software applying machine learning has become an essential tool to automate analysis, but these methods require annotated examples to learn from. Efficiently exploring large datasets to find relevant examples remains a challenging bottleneck. Here, we present Advanced Cell Classifier (ACC), a graphical software package for phenotypic analysis that addresses these difficulties. ACC applies machine-learning and image-analysis methods to high-content data generated by large-scale, cell-based experiments. It features methods to mine microscopic image data, discover new phenotypes, and improve recognition performance. We demonstrate that these features substantially expedite the training process, successfully uncover rare phenotypes, and improve the accuracy of the analysis. ACC is extensively documented, designed to be user-friendly for researchers without machine-learning expertise, and distributed as a free open-source tool at www.cellclassifier.org. Copyright © 2017 Elsevier Inc. All rights reserved.

Machine Translation from Text

NASA Astrophysics Data System (ADS)

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.

Computational biology for cardiovascular biomarker discovery.

PubMed

Azuaje, Francisco; Devaux, Yvan; Wagner, Daniel

2009-07-01

Computational biology is essential in the process of translating biological knowledge into clinical practice, as well as in the understanding of biological phenomena based on the resources and technologies originating from the clinical environment. One such key contribution of computational biology is the discovery of biomarkers for predicting clinical outcomes using 'omic' information. This process involves the predictive modelling and integration of different types of data and knowledge for screening, diagnostic or prognostic purposes. Moreover, this requires the design and combination of different methodologies based on statistical analysis and machine learning. This article introduces key computational approaches and applications to biomarker discovery based on different types of 'omic' data. Although we emphasize applications in cardiovascular research, the computational requirements and advances discussed here are also relevant to other domains. We will start by introducing some of the contributions of computational biology to translational research, followed by an overview of methods and technologies used for the identification of biomarkers with predictive or classification value. The main types of 'omic' approaches to biomarker discovery will be presented with specific examples from cardiovascular research. This will include a review of computational methodologies for single-source and integrative data applications. Major computational methods for model evaluation will be described together with recommendations for reporting models and results. We will present recent advances in cardiovascular biomarker discovery based on the combination of gene expression and functional network analyses. The review will conclude with a discussion of key challenges for computational biology, including perspectives from the biosciences and clinical areas.

AMS 4.0: consensus prediction of post-translational modifications in protein sequences.

PubMed

Plewczynski, Dariusz; Basu, Subhadip; Saha, Indrajit

2012-08-01

We present here the 2011 update of the AutoMotif Service (AMS 4.0) that predicts the wide selection of 88 different types of the single amino acid post-translational modifications (PTM) in protein sequences. The selection of experimentally confirmed modifications is acquired from the latest UniProt and Phospho.ELM databases for training. The sequence vicinity of each modified residue is represented using amino acids physico-chemical features encoded using high quality indices (HQI) obtaining by automatic clustering of known indices extracted from AAindex database. For each type of the numerical representation, the method builds the ensemble of Multi-Layer Perceptron (MLP) pattern classifiers, each optimising different objectives during the training (for example the recall, precision or area under the ROC curve (AUC)). The consensus is built using brainstorming technology, which combines multi-objective instances of machine learning algorithm, and the data fusion of different training objects representations, in order to boost the overall prediction accuracy of conserved short sequence motifs. The performance of AMS 4.0 is compared with the accuracy of previous versions, which were constructed using single machine learning methods (artificial neural networks, support vector machine). Our software improves the average AUC score of the earlier version by close to 7 % as calculated on the test datasets of all 88 PTM types. Moreover, for the selected most-difficult sequence motifs types it is able to improve the prediction performance by almost 32 %, when compared with previously used single machine learning methods. Summarising, the brainstorming consensus meta-learning methodology on the average boosts the AUC score up to around 89 %, averaged over all 88 PTM types. Detailed results for single machine learning methods and the consensus methodology are also provided, together with the comparison to previously published methods and state-of-the-art software tools. The source code and precompiled binaries of brainstorming tool are available at http://code.google.com/p/automotifserver/ under Apache 2.0 licensing.

Parametric Instability of Static Shafts-Disk System Using Finite Element Method

NASA Astrophysics Data System (ADS)

Wahab, A. M.; Rasid, Z. A.; Abu, A.

2017-10-01

Parametric instability condition is an important consideration in design process as it can cause failure in machine elements. In this study, parametric instability behaviour was studied for a simple shaft and disk system that was subjected to axial load under pinned-pinned boundary condition. The shaft was modelled based on the Nelson’s beam model, which considered translational and rotary inertias, transverse shear deformation and torsional effect. The Floquet’s method was used to estimate the solution for Mathieu equation. Finite element codes were developed using MATLAB to establish the instability chart. The effect of additional disk mass on the stability chart was investigated for pinned-pinned boundary conditions. Numerical results and illustrative examples are given. It is found that the additional disk mass decreases the instability region during static condition. The location of the disk as well has significant effect on the instability region of the shaft.

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

ERIC Educational Resources Information Center

Greenfield, Concetta C.; Serain, Daniel

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

Chinese-English Machine Translation System.

ERIC Educational Resources Information Center

Wang, William S-Y; And Others

The report documents results of a two-year R&D effort directed at the completion of a prototype system for Chinese-English machine translation of S&T literature. The system, designated QUINCE, accepts Chinese input exactly as printed, with no pre-editing of any kind, and produces English output on experimental basis. Coding of Chinese text via…

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

ERIC Educational Resources Information Center

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

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

Exploring Local Public Health Workflow in the Context of Automated Translation Technologies

PubMed Central

Mandel, Hannah; Turner, Anne M.

2013-01-01

Despite the growing limited English proficiency (LEP) population in the US, and federal regulations requiring multilingual health information be available for LEP individuals, there is a lack of available high quality multilingual health promotion materials. The costs and personnel time associated with creating high quality translations serve as barriers to their creation, especially in resource limited public health settings. To explore the potential adoption of novel machine translation and document dissemination technologies for improving the creation and sharing of translated public health materials, we interviewed key health department personnel in Washington State. We analyzed translation workflow, elucidated key themes regarding public health translation work, and assessed attitudes towards electronic document exchange and machine translation. Public health personnel expressed the need for human quality assurance and oversight, but appreciated the potential of novel information technologies to assist in the production and dissemination of translated materials for public health practice. PMID:24551385

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

PubMed

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.

Local Health Department Translation Processes: Potential of Machine Translation Technologies to Help Meet Needs

PubMed Central

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. PMID:24551414

Analyzing Array Manipulating Programs by Program Transformation

NASA Technical Reports Server (NTRS)

Cornish, J. Robert M.; Gange, Graeme; Navas, Jorge A.; Schachte, Peter; Sondergaard, Harald; Stuckey, Peter J.

2014-01-01

We explore a transformational approach to the problem of verifying simple array-manipulating programs. Traditionally, verification of such programs requires intricate analysis machinery to reason with universally quantified statements about symbolic array segments, such as "every data item stored in the segment A[i] to A[j] is equal to the corresponding item stored in the segment B[i] to B[j]." We define a simple abstract machine which allows for set-valued variables and we show how to translate programs with array operations to array-free code for this machine. For the purpose of program analysis, the translated program remains faithful to the semantics of array manipulation. Based on our implementation in LLVM, we evaluate the approach with respect to its ability to extract useful invariants and the cost in terms of code size.

Machine learning and radiology.

PubMed

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.

Real English: A Translator to Enable Natural Language Man-Machine Conversation.

ERIC Educational Resources Information Center

Gautin, Harvey

This dissertation presents a pragmatic interpreter/translator called Real English to serve as a natural language man-machine communication interface in a multi-mode on-line information retrieval system. This multi-mode feature affords the user a library-like searching tool by giving him access to a dictionary, lexicon, thesaurus, synonym table,…

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

DTIC Science & Technology

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

CW-SSIM kernel based random forest for image classification

NASA Astrophysics Data System (ADS)

Fan, Guangzhe; Wang, Zhou; Wang, Jiheng

2010-07-01

Complex wavelet structural similarity (CW-SSIM) index has been proposed as a powerful image similarity metric that is robust to translation, scaling and rotation of images, but how to employ it in image classification applications has not been deeply investigated. In this paper, we incorporate CW-SSIM as a kernel function into a random forest learning algorithm. This leads to a novel image classification approach that does not require a feature extraction or dimension reduction stage at the front end. We use hand-written digit recognition as an example to demonstrate our algorithm. We compare the performance of the proposed approach with random forest learning based on other kernels, including the widely adopted Gaussian and the inner product kernels. Empirical evidences show that the proposed method is superior in its classification power. We also compared our proposed approach with the direct random forest method without kernel and the popular kernel-learning method support vector machine. Our test results based on both simulated and realworld data suggest that the proposed approach works superior to traditional methods without the feature selection procedure.

Chapter 16: text mining for translational bioinformatics.

PubMed

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.

CDISC SHARE, a Global, Cloud-based Resource of Machine-Readable CDISC Standards for Clinical and Translational Research

PubMed Central

Hume, Samuel; Chow, Anthony; Evans, Julie; Malfait, Frederik; Chason, Julie; Wold, J. Darcy; Kubick, Wayne; Becnel, Lauren B.

2018-01-01

The Clinical Data Interchange Standards Consortium (CDISC) is a global non-profit standards development organization that creates consensus-based standards for clinical and translational research. Several of these standards are now required by regulators for electronic submissions of regulated clinical trials’ data and by government funding agencies. These standards are free and open, available for download on the CDISC Website as PDFs. While these documents are human readable, they are not amenable to ready use by electronic systems. CDISC launched the CDISC Shared Health And Research Electronic library (SHARE) to provide the standards metadata in machine-readable formats to facilitate the automated management and implementation of the standards. This paper describes how CDISC SHARE’S standards can facilitate collecting, aggregating and analyzing standardized data from early design to end analysis; and its role as a central resource providing information systems with metadata that drives process automation including study setup and data pipelining. PMID:29888049

Development of a Machine-Vision System for Recording of Force Calibration Data

NASA Astrophysics Data System (ADS)

Heamawatanachai, Sumet; Chaemthet, Kittipong; Changpan, Tawat

This paper presents the development of a new system for recording of force calibration data using machine vision technology. Real time camera and computer system were used to capture images of the reading from the instruments during calibration. Then, the measurement images were transformed and translated to numerical data using optical character recognition (OCR) technique. These numerical data along with raw images were automatically saved to memories as the calibration database files. With this new system, the human error of recording would be eliminated. The verification experiments were done by using this system for recording the measurement results from an amplifier (DMP 40) with load cell (HBM-Z30-10kN). The NIMT's 100-kN deadweight force standard machine (DWM-100kN) was used to generate test forces. The experiments setup were done in 3 categories; 1) dynamics condition (record during load changing), 2) statics condition (record during fix load), and 3) full calibration experiments in accordance with ISO 376:2011. The captured images from dynamics condition experiment gave >94% without overlapping of number. The results from statics condition experiment were >98% images without overlapping. All measurement images without overlapping were translated to number by the developed program with 100% accuracy. The full calibration experiments also gave 100% accurate results. Moreover, in case of incorrect translation of any result, it is also possible to trace back to the raw calibration image to check and correct it. Therefore, this machine-vision-based system and program should be appropriate for recording of force calibration data.

Machine Learning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chikkagoudar, Satish; Chatterjee, Samrat; Thomas, Dennis G.

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

Energy Savings and Persistence from an Energy Services Performance Contract at an Army Base

DTIC Science & Technology

2011-10-01

control system upgrades, lighting retrofits, vending machine controls, and cooling tower variable frequency drivers (VFDs). To accomplish the...controls were installed in the vending machines , and for the 87018 thermal plant, cooling tower VFDs were implemented. To develop baseline models...identify the reasons of improved or deteriorated energy performance of the buildings. For example, periodic submetering of the vending machines

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

PubMed Central

Yu, Wei; Clyne, Melinda; Dolan, Siobhan M; Yesupriya, Ajay; Wulf, Anja; Liu, Tiebin; Khoury, Muin J; Gwinn, Marta

2008-01-01

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. PMID:18430222

Machine Translation-Supported Cross-Language Information Retrieval for a Consumer Health Resource

PubMed Central

Rosemblat, Graciela; Gemoets, Darren; Browne, Allen C.; Tse, Tony

2003-01-01

The U.S. National Institutes of Health, through its National Library of Medicine, developed ClinicalTrials.gov to provide the public with easy access to information on clinical trials on a wide range of conditions or diseases. Only English language information retrieval is currently supported. Given the growing number of Spanish speakers in the U.S. and their increasing use of the Web, we anticipate a significant increase in Spanish-speaking users. This study compares the effectiveness of two common cross-language information retrieval methods using machine translation, query translation versus document translation, using a subset of genuine user queries from ClinicalTrials.gov. Preliminary results conducted with the ClinicalTrials.gov search engine show that in our environment, query translation is statistically significantly better than document translation. We discuss possible reasons for this result and we conclude with suggestions for future work. PMID:14728236

Combining MEDLINE and publisher data to create parallel corpora for the automatic translation of biomedical text

PubMed Central

2013-01-01

Background Most of the institutional and research information in the biomedical domain is available in the form of English text. Even in countries where English is an official language, such as the United States, language can be a barrier for accessing biomedical information for non-native speakers. Recent progress in machine translation suggests that this technique could help make English texts accessible to speakers of other languages. However, the lack of adequate specialized corpora needed to train statistical models currently limits the quality of automatic translations in the biomedical domain. Results We show how a large-sized parallel corpus can automatically be obtained for the biomedical domain, using the MEDLINE database. The corpus generated in this work comprises article titles obtained from MEDLINE and abstract text automatically retrieved from journal websites, which substantially extends the corpora used in previous work. After assessing the quality of the corpus for two language pairs (English/French and English/Spanish) we use the Moses package to train a statistical machine translation model that outperforms previous models for automatic translation of biomedical text. Conclusions We have built translation data sets in the biomedical domain that can easily be extended to other languages available in MEDLINE. These sets can successfully be applied to train statistical machine translation models. While further progress should be made by incorporating out-of-domain corpora and domain-specific lexicons, we believe that this work improves the automatic translation of biomedical texts. PMID:23631733

Understanding and Writing G & M Code for CNC Machines

ERIC Educational Resources Information Center

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…

Agent-based models in translational systems biology

PubMed Central

An, Gary; Mi, Qi; Dutta-Moscato, Joyeeta; Vodovotz, Yoram

2013-01-01

Effective translational methodologies for knowledge representation are needed in order to make strides against the constellation of diseases that affect the world today. These diseases are defined by their mechanistic complexity, redundancy, and nonlinearity. Translational systems biology aims to harness the power of computational simulation to streamline drug/device design, simulate clinical trials, and eventually to predict the effects of drugs on individuals. The ability of agent-based modeling to encompass multiple scales of biological process as well as spatial considerations, coupled with an intuitive modeling paradigm, suggests that this modeling framework is well suited for translational systems biology. This review describes agent-based modeling and gives examples of its translational applications in the context of acute inflammation and wound healing. PMID:20835989

Claims-Based Authentication for a Web-Based Enterprise

DTIC Science & Technology

2013-07-01

authority must use known and registered (or in specific cases defined ) certificate revocation and currency-checking software . B. Translation of...Machines and services are issued software certificates that contain the public key with the private key generated and remaining in hardware...publicly available) information. A hardware token that contains the certificate is preferred to software -only certificates. For enterprise users

Enacting the Semantic Web: Ontological Orderings, Negotiated Standards, and Human-Machine Translations

ERIC Educational Resources Information Center

McCarthy, Matthew T.

2017-01-01

Artificial intelligence (AI) that is based upon semantic search has become one of the dominant means for accessing information in recent years. This is particularly the case in mobile contexts, as search-based AI are embedded in each of the major mobile operating systems. The implications are such that information is becoming less a matter of…

Climbing the Tower of Babel: Perfecting Machine Translation

DTIC Science & Technology

2011-02-16

Center) used MT tools to translate extraordinary numbers of Russian technical documents. 10 For the Air Force, the manpower and time savings were...recognition.htm. Granted, this number is tempered by the rules of a specific language that would disallow specific word orderings, or mandate particular word...sequences, (e.g., in English, prepositions can only be followed by articles, etc) but the overall numbers convey the complexity of the machine

Method and system for assembling miniaturized devices

DOEpatents

Montesanti, Richard C.; Klingmann, Jeffrey L.; Seugling, Richard M.

2013-03-12

An apparatus for assembling a miniaturized device includes a manipulator system including six manipulators operable to position and orient components of the miniaturized device with submicron precision and micron-level accuracy. The manipulator system includes a first plurality of motorized axes, a second plurality of manual axes, and force and torque and sensors. Each of the six manipulators includes at least one translation stage, at least one rotation stage, tooling attached to the at least one translation stage or the at least one rotation stage, and an attachment mechanism disposed at a distal end of the tooling and operable to attach at least a portion of the miniaturized device to the tooling. The apparatus also includes an optical coordinate-measuring machine (OCMM) including a machine-vision system, a laser-based distance-measuring probe, and a touch probe. The apparatus also includes an operator control system coupled to the manipulator system and the OCMM.

Methods, systems and apparatus for controlling third harmonic voltage when operating a multi-space machine in an overmodulation region

DOEpatents

Perisic, Milun; Kinoshita, Michael H; Ranson, Ray M; Gallegos-Lopez, Gabriel

2014-06-03

Methods, system and apparatus are provided for controlling third harmonic voltages when operating a multi-phase machine in an overmodulation region. The multi-phase machine can be, for example, a five-phase machine in a vector controlled motor drive system that includes a five-phase PWM controlled inverter module that drives the five-phase machine. Techniques for overmodulating a reference voltage vector are provided. For example, when the reference voltage vector is determined to be within the overmodulation region, an angle of the reference voltage vector can be modified to generate a reference voltage overmodulation control angle, and a magnitude of the reference voltage vector can be modified, based on the reference voltage overmodulation control angle, to generate a modified magnitude of the reference voltage vector. By modifying the reference voltage vector, voltage command signals that control a five-phase inverter module can be optimized to increase output voltages generated by the five-phase inverter module.

EXACT2: the semantics of biomedical protocols

PubMed Central

2014-01-01

Background The reliability and reproducibility of experimental procedures is a cornerstone of scientific practice. There is a pressing technological need for the better representation of biomedical protocols to enable other agents (human or machine) to better reproduce results. A framework that ensures that all information required for the replication of experimental protocols is essential to achieve reproducibility. Methods We have developed the ontology EXACT2 (EXperimental ACTions) that is designed to capture the full semantics of biomedical protocols required for their reproducibility. To construct EXACT2 we manually inspected hundreds of published and commercial biomedical protocols from several areas of biomedicine. After establishing a clear pattern for extracting the required information we utilized text-mining tools to translate the protocols into a machine amenable format. We have verified the utility of EXACT2 through the successful processing of previously 'unseen' (not used for the construction of EXACT2) protocols. Results The paper reports on a fundamentally new version EXACT2 that supports the semantically-defined representation of biomedical protocols. The ability of EXACT2 to capture the semantics of biomedical procedures was verified through a text mining use case. In this EXACT2 is used as a reference model for text mining tools to identify terms pertinent to experimental actions, and their properties, in biomedical protocols expressed in natural language. An EXACT2-based framework for the translation of biomedical protocols to a machine amenable format is proposed. Conclusions The EXACT2 ontology is sufficient to record, in a machine processable form, the essential information about biomedical protocols. EXACT2 defines explicit semantics of experimental actions, and can be used by various computer applications. It can serve as a reference model for for the translation of biomedical protocols in natural language into a semantically-defined format. PMID:25472549

Breaking the Language Barrier

NASA Technical Reports Server (NTRS)

1981-01-01

Preparation for the Apollo Soyuz mission entailed large-scale informational exchange that was accomplished by a computerized translation system. Based on this technology of commercial machine translation, a system known as SYSTRAN II was developed by LATSEC, Inc. and the World Translation Company of Canada. This system increases the output of a human translator by five to eight times, affording cost savings by allowing a large increase in document production without hiring additional people. Extra savings accrue from automatic production of camera-ready copy. Applications include translation of service manuals, proposals and tenders, planning studies, catalogs, list of parts and prices, textbooks, technical reports and education/training materials. System is operational for six language pairs. Systran users include Xerox Corporation, General Motors of Canada, Bell Northern Research of Canada, the U.S. Air Force and the European Commission. The company responsible for the production of SYSTRAN II has changed its name to SYSTRAN.

Acquiring Software Design Schemas: A Machine Learning Perspective

NASA Technical Reports Server (NTRS)

Harandi, Mehdi T.; Lee, Hing-Yan

1991-01-01

In this paper, we describe an approach based on machine learning that acquires software design schemas from design cases of existing applications. An overview of the technique, design representation, and acquisition system are presented. the paper also addresses issues associated with generalizing common features such as biases. The generalization process is illustrated using an example.

Anomaly detection for machine learning redshifts applied to SDSS galaxies

NASA Astrophysics Data System (ADS)

Hoyle, Ben; Rau, Markus Michael; Paech, Kerstin; Bonnett, Christopher; Seitz, Stella; Weller, Jochen

2015-10-01

We present an analysis of anomaly detection for machine learning redshift estimation. Anomaly detection allows the removal of poor training examples, which can adversely influence redshift estimates. Anomalous training examples may be photometric galaxies with incorrect spectroscopic redshifts, or galaxies with one or more poorly measured photometric quantity. We select 2.5 million `clean' SDSS DR12 galaxies with reliable spectroscopic redshifts, and 6730 `anomalous' galaxies with spectroscopic redshift measurements which are flagged as unreliable. We contaminate the clean base galaxy sample with galaxies with unreliable redshifts and attempt to recover the contaminating galaxies using the Elliptical Envelope technique. We then train four machine learning architectures for redshift analysis on both the contaminated sample and on the preprocessed `anomaly-removed' sample and measure redshift statistics on a clean validation sample generated without any preprocessing. We find an improvement on all measured statistics of up to 80 per cent when training on the anomaly removed sample as compared with training on the contaminated sample for each of the machine learning routines explored. We further describe a method to estimate the contamination fraction of a base data sample.

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

DTIC Science & Technology

2014-03-27

of Master of Science in Cyber Operations Jordan S. Keefer, B.S.C.S. Second Lieutenant, USAF March 2014 DISTRIBUTION STATEMENT A: APPROVED FOR PUBLIC...Atlantic Trade Organization NIST National Institute of Standards and Technology NL natural language NSF National Science Foundation ix Acronym Definition...the machine translation problem. In 1964 the Director of the National Science Foundation (NSF), 4 Dr. Leland Haworth, commissioned a research team to

A comparison of human and machine translation of health promotion materials for public health practice: time, costs, and quality.

PubMed

Turner, Anne M; Bergman, Margo; Brownstein, Megumu; Cole, Kate; Kirchhoff, Katrin

2014-01-01

Most local public health departments serve limited English proficiency groups but lack sufficient resources to translate the health promotion materials that they produce into different languages. Machine translation (MT) with human postediting could fill this gap and work toward decreasing health disparities among non-English speakers. (1) To identify the time and costs associated with human translation (HT) of public health documents, (2) determine the time necessary for human postediting of MT, and (3) compare the quality of postedited MT and HT. A quality comparison of 25 MT and HT documents was performed with public health translators. The public health professionals involved were queried about the workflow, costs, and time for HT of 11 English public health documents over a 20-month period. Three recently translated documents of similar size and topic were then machine translated, the time for human postediting was recorded, and a blind quality analysis was performed. Seattle/King County, Washington. Public health professionals. (1) Estimated times for various HT tasks; (2) observed postediting times for MT documents; (3) actual costs for HT; and (4) comparison of quality ratings for HT and MT. Human translation via local health department methods took 17 hours to 6 days. While HT postediting words per minute ranged from 1.58 to 5.88, MT plus human postediting words per minute ranged from 10 to 30. The cost of HT ranged from $130 to $1220; MT required no additional costs. A quality comparison by bilingual public health professionals showed that MT and HT were equivalently preferred. MT with human postediting can reduce the time and costs of translating public health materials while maintaining quality similar to HT. In conjunction with postediting, MT could greatly improve the availability of multilingual public health materials.

High performance cutting of aircraft and turbine components

NASA Astrophysics Data System (ADS)

Krämer, A.; Lung, D.; Klocke, F.

2012-04-01

Titanium and nickel-based alloys belong to the group of difficult-to-cut materials. The machining of these high-temperature alloys is characterized by low productivity and low process stability as a result of their physical and mechanical properties. Major problems during the machining of these materials are low applicable cutting speeds due to excessive tool wear, long machining times, and thus high manufacturing costs, as well as the formation of ribbon and snarled chips. Under these conditions automation of the production process is limited. This paper deals with strategies to improve machinability of titanium and nickel-based alloys. Using the example of the nickel-based alloy Inconel 718 high performance cutting with advanced cutting materials, such as PCBN and cutting ceramics, is presented. Afterwards the influence of different cooling strategies, like high-pressure lubricoolant supply and cryogenic cooling, during machining of TiAl6V4 is shown.

Argonne Braille Project

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grunwald, A.

1977-07-01

Development of a braille machine is summarized. It is noted that the machine has reached the stage where development of the system appears both possible and desirable. Sections are included containing papers on computer translation and auxiliary equipment, and on letters and awards in recognition of the braille machine development. (JRD)

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

ERIC Educational Resources Information Center

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…

A Morphological Analyzer for Vocalized or Not Vocalized Arabic Language

NASA Astrophysics Data System (ADS)

El Amine Abderrahim, Med; Breksi Reguig, Fethi

This research has been to show the realization of a morphological analyzer of the Arabic language (vocalized or not vocalized). This analyzer is based upon our object model for the Arabic Natural Language Processing (NLP) and can be exploited by NLP applications such as translation machine, orthographical correction and the search for information.

Translating Big Data into Smart Data for Veterinary Epidemiology.

PubMed

VanderWaal, Kimberly; Morrison, Robert B; Neuhauser, Claudia; Vilalta, Carles; Perez, Andres M

2017-01-01

The increasing availability and complexity of data has led to new opportunities and challenges in veterinary epidemiology around how to translate abundant, diverse, and rapidly growing "big" data into meaningful insights for animal health. Big data analytics are used to understand health risks and minimize the impact of adverse animal health issues through identifying high-risk populations, combining data or processes acting at multiple scales through epidemiological modeling approaches, and harnessing high velocity data to monitor animal health trends and detect emerging health threats. The advent of big data requires the incorporation of new skills into veterinary epidemiology training, including, for example, machine learning and coding, to prepare a new generation of scientists and practitioners to engage with big data. Establishing pipelines to analyze big data in near real-time is the next step for progressing from simply having "big data" to create "smart data," with the objective of improving understanding of health risks, effectiveness of management and policy decisions, and ultimately preventing or at least minimizing the impact of adverse animal health issues.

Biomolecular engineering of intracellular switches in eukaryotes

PubMed Central

Pastuszka, M.K.; Mackay, J.A.

2010-01-01

Tools to selectively and reversibly control gene expression are useful to study and model cellular functions. When optimized, these cellular switches can turn a protein's function “on” and “off” based on cues designated by the researcher. These cues include small molecules, drugs, hormones, and even temperature variations. Here we review three distinct areas in gene expression that are commonly targeted when designing cellular switches. Transcriptional switches target gene expression at the level of mRNA polymerization, with examples including the tetracycline gene induction system as well as nuclear receptors. Translational switches target the process of turning the mRNA signal into protein, with examples including riboswitches and RNA interference. Post-translational switches control how proteins interact with one another to attenuate or relay signals. Examples of post-translational modification include dimerization and intein splicing. In general, the delay times between switch and effect decreases from transcription to translation to post-translation; furthermore, the fastest switches may offer the most elegant opportunities to influence and study cell behavior. We discuss the pros and cons of these strategies, which directly influence their usefulness to study and implement drug targeting at the tissue and cellular level. PMID:21209849

On-Demand Associative Cross-Language Information Retrieval

NASA Astrophysics Data System (ADS)

Geraldo, André Pinto; Moreira, Viviane P.; Gonçalves, Marcos A.

This paper proposes the use of algorithms for mining association rules as an approach for Cross-Language Information Retrieval. These algorithms have been widely used to analyse market basket data. The idea is to map the problem of finding associations between sales items to the problem of finding term translations over a parallel corpus. The proposal was validated by means of experiments using queries in two distinct languages: Portuguese and Finnish to retrieve documents in English. The results show that the performance of our proposed approach is comparable to the performance of the monolingual baseline and to query translation via machine translation, even though these systems employ more complex Natural Language Processing techniques. The combination between machine translation and our approach yielded the best results, even outperforming the monolingual baseline.

Layout Design of Human-Machine Interaction Interface of Cabin Based on Cognitive Ergonomics and GA-ACA.

PubMed

Deng, Li; Wang, Guohua; Yu, Suihuai

2016-01-01

In order to consider the psychological cognitive characteristics affecting operating comfort and realize the automatic layout design, cognitive ergonomics and GA-ACA (genetic algorithm and ant colony algorithm) were introduced into the layout design of human-machine interaction interface. First, from the perspective of cognitive psychology, according to the information processing process, the cognitive model of human-machine interaction interface was established. Then, the human cognitive characteristics were analyzed, and the layout principles of human-machine interaction interface were summarized as the constraints in layout design. Again, the expression form of fitness function, pheromone, and heuristic information for the layout optimization of cabin was studied. The layout design model of human-machine interaction interface was established based on GA-ACA. At last, a layout design system was developed based on this model. For validation, the human-machine interaction interface layout design of drilling rig control room was taken as an example, and the optimization result showed the feasibility and effectiveness of the proposed method.

Layout Design of Human-Machine Interaction Interface of Cabin Based on Cognitive Ergonomics and GA-ACA

PubMed Central

Deng, Li; Wang, Guohua; Yu, Suihuai

2016-01-01

In order to consider the psychological cognitive characteristics affecting operating comfort and realize the automatic layout design, cognitive ergonomics and GA-ACA (genetic algorithm and ant colony algorithm) were introduced into the layout design of human-machine interaction interface. First, from the perspective of cognitive psychology, according to the information processing process, the cognitive model of human-machine interaction interface was established. Then, the human cognitive characteristics were analyzed, and the layout principles of human-machine interaction interface were summarized as the constraints in layout design. Again, the expression form of fitness function, pheromone, and heuristic information for the layout optimization of cabin was studied. The layout design model of human-machine interaction interface was established based on GA-ACA. At last, a layout design system was developed based on this model. For validation, the human-machine interaction interface layout design of drilling rig control room was taken as an example, and the optimization result showed the feasibility and effectiveness of the proposed method. PMID:26884745

Discovering Fine-grained Sentiment in Suicide Notes

PubMed Central

Wang, Wenbo; Chen, Lu; Tan, Ming; Wang, Shaojun; Sheth, Amit P.

2012-01-01

This paper presents our solution for the i2b2 sentiment classification challenge. Our hybrid system consists of machine learning and rule-based classifiers. For the machine learning classifier, we investigate a variety of lexical, syntactic and knowledge-based features, and show how much these features contribute to the performance of the classifier through experiments. For the rule-based classifier, we propose an algorithm to automatically extract effective syntactic and lexical patterns from training examples. The experimental results show that the rule-based classifier outperforms the baseline machine learning classifier using unigram features. By combining the machine learning classifier and the rule-based classifier, the hybrid system gains a better trade-off between precision and recall, and yields the highest micro-averaged F-measure (0.5038), which is better than the mean (0.4875) and median (0.5027) micro-average F-measures among all participating teams. PMID:22879770

In silico prediction of post-translational modifications.

PubMed

Liu, Chunmei; Li, Hui

2011-01-01

Methods for predicting protein post-translational modifications have been developed extensively. In this chapter, we review major post-translational modification prediction strategies, with a particular focus on statistical and machine learning approaches. We present the workflow of the methods and summarize the advantages and disadvantages of the methods.

Progress on big data publication and documentation for machine-to-machine discovery, access, and processing

NASA Astrophysics Data System (ADS)

Walker, J. I.; Blodgett, D. L.; Suftin, I.; Kunicki, T.

2013-12-01

High-resolution data for use in environmental modeling is increasingly becoming available at broad spatial and temporal scales. Downscaled climate projections, remotely sensed landscape parameters, and land-use/land-cover projections are examples of datasets that may exceed an individual investigation's data management and analysis capacity. To allow projects on limited budgets to work with many of these data sets, the burden of working with them must be reduced. The approach being pursued at the U.S. Geological Survey Center for Integrated Data Analytics uses standard self-describing web services that allow machine to machine data access and manipulation. These techniques have been implemented and deployed in production level server-based Web Processing Services that can be accessed from a web application or scripted workflow. Data publication techniques that allow machine-interpretation of large collections of data have also been implemented for numerous datasets at U.S. Geological Survey data centers as well as partner agencies and academic institutions. Discovery of data services is accomplished using a method in which a machine-generated metadata record holds content--derived from the data's source web service--that is intended for human interpretation as well as machine interpretation. A distributed search application has been developed that demonstrates the utility of a decentralized search of data-owner metadata catalogs from multiple agencies. The integrated but decentralized system of metadata, data, and server-based processing capabilities will be presented. The design, utility, and value of these solutions will be illustrated with applied science examples and success stories. Datasets such as the EPA's Integrated Climate and Land Use Scenarios, USGS/NASA MODIS derived land cover attributes, and downscaled climate projections from several sources are examples of data this system includes. These and other datasets, have been published as standard, self-describing, web services that provide the ability to inspect and subset the data. This presentation will demonstrate this file-to-web service concept and how it can be used from script-based workflows or web applications.

Functional language and data flow architectures

NASA Technical Reports Server (NTRS)

Ercegovac, M. D.; Patel, D. R.; Lang, T.

1983-01-01

This is a tutorial article about language and architecture approaches for highly concurrent computer systems based on the functional style of programming. The discussion concentrates on the basic aspects of functional languages, and sequencing models such as data-flow, demand-driven and reduction which are essential at the machine organization level. Several examples of highly concurrent machines are described.

Determination of real machine-tool settings and minimization of real surface deviation by computerized inspection

NASA Technical Reports Server (NTRS)

Litvin, Faydor L.; Kuan, Chihping; Zhang, YI

1991-01-01

A numerical method is developed for the minimization of deviations of real tooth surfaces from the theoretical ones. The deviations are caused by errors of manufacturing, errors of installment of machine-tool settings and distortion of surfaces by heat-treatment. The deviations are determined by coordinate measurements of gear tooth surfaces. The minimization of deviations is based on the proper correction of initially applied machine-tool settings. The contents of accomplished research project cover the following topics: (1) Descriptions of the principle of coordinate measurements of gear tooth surfaces; (2) Deviation of theoretical tooth surfaces (with examples of surfaces of hypoid gears and references for spiral bevel gears); (3) Determination of the reference point and the grid; (4) Determination of the deviations of real tooth surfaces at the points of the grid; and (5) Determination of required corrections of machine-tool settings for minimization of deviations. The procedure for minimization of deviations is based on numerical solution of an overdetermined system of n linear equations in m unknowns (m much less than n ), where n is the number of points of measurements and m is the number of parameters of applied machine-tool settings to be corrected. The developed approach is illustrated with numerical examples.

Automatic Extraction of Destinations, Origins and Route Parts from Human Generated Route Directions

NASA Astrophysics Data System (ADS)

Zhang, Xiao; Mitra, Prasenjit; Klippel, Alexander; Maceachren, Alan

Researchers from the cognitive and spatial sciences are studying text descriptions of movement patterns in order to examine how humans communicate and understand spatial information. In particular, route directions offer a rich source of information on how cognitive systems conceptualize movement patterns by segmenting them into meaningful parts. Route directions are composed using a plethora of cognitive spatial organization principles: changing levels of granularity, hierarchical organization, incorporation of cognitively and perceptually salient elements, and so forth. Identifying such information in text documents automatically is crucial for enabling machine-understanding of human spatial language. The benefits are: a) creating opportunities for large-scale studies of human linguistic behavior; b) extracting and georeferencing salient entities (landmarks) that are used by human route direction providers; c) developing methods to translate route directions to sketches and maps; and d) enabling queries on large corpora of crawled/analyzed movement data. In this paper, we introduce our approach and implementations that bring us closer to the goal of automatically processing linguistic route directions. We report on research directed at one part of the larger problem, that is, extracting the three most critical parts of route directions and movement patterns in general: origin, destination, and route parts. We use machine-learning based algorithms to extract these parts of routes, including, for example, destination names and types. We prove the effectiveness of our approach in several experiments using hand-tagged corpora.

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

ERIC Educational Resources Information Center

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…

An Overall Perspective of Machine Translation with Its Shortcomings

ERIC Educational Resources Information Center

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…

Extra high speed modified Lundell alternator parameters and open/short-circuit characteristics from global 3D-FE magnetic field solutions

NASA Astrophysics Data System (ADS)

Wang, R.; Demerdash, N. A.

1992-06-01

The combined magnetic vector potential - magnetic scalar potential method of computation of 3D magnetic fields by finite elements, introduced in a companion paper, is used for global 3D field analysis and machine performance computations under open-circuit and short-circuit conditions for an example 14.3 kVA modified Lundell alternator, whose magnetic field is of intrinsic 3D nature. The computed voltages and currents under these machine test conditions were verified and found to be in very good agreement with corresponding test data. Results of use of this modelling and computation method in the study of a design alteration example, in which the stator stack length of the example alternator is stretched in order to increase voltage and volt-ampere rating, are given here. These results demonstrate the inadequacy of conventional 2D-based design concepts and the imperative of use of this type of 3D magnetic field modelling in the design and investigation of such machines.

Extra high speed modified Lundell alternator parameters and open/short-circuit characteristics from global 3D-FE magnetic field solutions

NASA Technical Reports Server (NTRS)

Wang, R.; Demerdash, N. A.

1992-01-01

The combined magnetic vector potential - magnetic scalar potential method of computation of 3D magnetic fields by finite elements, introduced in a companion paper, is used for global 3D field analysis and machine performance computations under open-circuit and short-circuit conditions for an example 14.3 kVA modified Lundell alternator, whose magnetic field is of intrinsic 3D nature. The computed voltages and currents under these machine test conditions were verified and found to be in very good agreement with corresponding test data. Results of use of this modelling and computation method in the study of a design alteration example, in which the stator stack length of the example alternator is stretched in order to increase voltage and volt-ampere rating, are given here. These results demonstrate the inadequacy of conventional 2D-based design concepts and the imperative of use of this type of 3D magnetic field modelling in the design and investigation of such machines.

Machine learning-based methods for prediction of linear B-cell epitopes.

PubMed

Wang, Hsin-Wei; Pai, Tun-Wen

2014-01-01

B-cell epitope prediction facilitates immunologists in designing peptide-based vaccine, diagnostic test, disease prevention, treatment, and antibody production. In comparison with T-cell epitope prediction, the performance of variable length B-cell epitope prediction is still yet to be satisfied. Fortunately, due to increasingly available verified epitope databases, bioinformaticians could adopt machine learning-based algorithms on all curated data to design an improved prediction tool for biomedical researchers. Here, we have reviewed related epitope prediction papers, especially those for linear B-cell epitope prediction. It should be noticed that a combination of selected propensity scales and statistics of epitope residues with machine learning-based tools formulated a general way for constructing linear B-cell epitope prediction systems. It is also observed from most of the comparison results that the kernel method of support vector machine (SVM) classifier outperformed other machine learning-based approaches. Hence, in this chapter, except reviewing recently published papers, we have introduced the fundamentals of B-cell epitope and SVM techniques. In addition, an example of linear B-cell prediction system based on physicochemical features and amino acid combinations is illustrated in details.

Machine vision for digital microfluidics

NASA Astrophysics Data System (ADS)

Shin, Yong-Jun; Lee, Jeong-Bong

2010-01-01

Machine vision is widely used in an industrial environment today. It can perform various tasks, such as inspecting and controlling production processes, that may require humanlike intelligence. The importance of imaging technology for biological research or medical diagnosis is greater than ever. For example, fluorescent reporter imaging enables scientists to study the dynamics of gene networks with high spatial and temporal resolution. Such high-throughput imaging is increasingly demanding the use of machine vision for real-time analysis and control. Digital microfluidics is a relatively new technology with expectations of becoming a true lab-on-a-chip platform. Utilizing digital microfluidics, only small amounts of biological samples are required and the experimental procedures can be automatically controlled. There is a strong need for the development of a digital microfluidics system integrated with machine vision for innovative biological research today. In this paper, we show how machine vision can be applied to digital microfluidics by demonstrating two applications: machine vision-based measurement of the kinetics of biomolecular interactions and machine vision-based droplet motion control. It is expected that digital microfluidics-based machine vision system will add intelligence and automation to high-throughput biological imaging in the future.

Building translational ecology communities of practice: insights from the field

USGS Publications Warehouse

Lawson, Dawn M.; Hall, Kimberly R.; Yung, Laurie; Enquist, Carolyn A. F.

2017-01-01

Translational ecology (TE) prioritizes the understanding of social systems and decision contexts in order to address complex natural resource management issues. Although many practitioners in applied fields employ translational tactics, the body of literature addressing such approaches is limited. We present several case studies illustrating the principles of TE and the diversity of its applications. We anticipate that these examples will help others develop scientific products that decision makers can use “off the shelf” when solving critical ecological and social challenges. Our collective experience suggests that research of such immediate utility is rare. Long‐term commitment to working directly with partners to develop and reach shared goals is central to successful translation. The examples discussed here highlight the benefits of translational processes, including actionable scientific results, more informed policy making, increased investment in science‐driven solutions, and inspiration for partnerships. We aim to facilitate future TE‐based projects and build momentum for growing this community of practice.

NeuroRex: A Clinical Neural Interface Roadmap for EEG-based Brain Machine Interfaces to a Lower Body Robotic Exoskeleton*

PubMed Central

Contreras-Vidal, Jose L.; Grossman, Robert G.

2013-01-01

In this communication, a translational clinical brain-machine interface (BMI) roadmap for an EEG-based BMI to a robotic exoskeleton (NeuroRex) is presented. This multi-faceted project addresses important engineering and clinical challenges: It addresses the validation of an intelligent, self-balancing, robotic lower-body and trunk exoskeleton (Rex) augmented with EEG-based BMI capabilities to interpret user intent to assist a mobility-impaired person to walk independently. The goal is to improve the quality of life and health status of wheelchair-bounded persons by enabling standing and sitting, walking and backing, turning, ascending and descending stairs/curbs, and navigating sloping surfaces in a variety of conditions without the need for additional support or crutches. PMID:24110003

Ex-vivo machine perfusion for kidney preservation.

PubMed

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.

Applications of Support Vector Machines In Chemo And Bioinformatics

NASA Astrophysics Data System (ADS)

Jayaraman, V. K.; Sundararajan, V.

2010-10-01

Conventional linear & nonlinear tools for classification, regression & data driven modeling are being replaced on a rapid scale by newer techniques & tools based on artificial intelligence and machine learning. While the linear techniques are not applicable for inherently nonlinear problems, newer methods serve as attractive alternatives for solving real life problems. Support Vector Machine (SVM) classifiers are a set of universal feed-forward network based classification algorithms that have been formulated from statistical learning theory and structural risk minimization principle. SVM regression closely follows the classification methodology. In this work recent applications of SVM in Chemo & Bioinformatics will be described with suitable illustrative examples.

MetaKTSP: a meta-analytic top scoring pair method for robust cross-study validation of omics prediction analysis.

PubMed

Kim, SungHwan; Lin, Chien-Wei; Tseng, George C

2016-07-01

Supervised machine learning is widely applied to transcriptomic data to predict disease diagnosis, prognosis or survival. Robust and interpretable classifiers with high accuracy are usually favored for their clinical and translational potential. The top scoring pair (TSP) algorithm is an example that applies a simple rank-based algorithm to identify rank-altered gene pairs for classifier construction. Although many classification methods perform well in cross-validation of single expression profile, the performance usually greatly reduces in cross-study validation (i.e. the prediction model is established in the training study and applied to an independent test study) for all machine learning methods, including TSP. The failure of cross-study validation has largely diminished the potential translational and clinical values of the models. The purpose of this article is to develop a meta-analytic top scoring pair (MetaKTSP) framework that combines multiple transcriptomic studies and generates a robust prediction model applicable to independent test studies. We proposed two frameworks, by averaging TSP scores or by combining P-values from individual studies, to select the top gene pairs for model construction. We applied the proposed methods in simulated data sets and three large-scale real applications in breast cancer, idiopathic pulmonary fibrosis and pan-cancer methylation. The result showed superior performance of cross-study validation accuracy and biomarker selection for the new meta-analytic framework. In conclusion, combining multiple omics data sets in the public domain increases robustness and accuracy of the classification model that will ultimately improve disease understanding and clinical treatment decisions to benefit patients. An R package MetaKTSP is available online. (http://tsenglab.biostat.pitt.edu/software.htm). ctseng@pitt.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Searching to Translate and Translating to Search: When Information Retrieval Meets Machine Translation

ERIC Educational Resources Information Center

Ture, Ferhan

2013-01-01

With the adoption of web services in daily life, people have access to tremendous amounts of information, beyond any human's reading and comprehension capabilities. As a result, search technologies have become a fundamental tool for accessing information. Furthermore, the web contains information in multiple languages, introducing another barrier…

Development of German-English Machine Translation System. Final Technical Report.

ERIC Educational Resources Information Center

Lehmann, Winfred P.; Stachowitz, Rolf A.

This report describes work on a pilot system for a fully automatic, high-quality translation of German scientific and technical text into English and gives the results of an experiment designed to show the system's capability to produce quality mechanical translation. The areas considered were: (1) grammar formalism, mainly involving the addition…

ON THE QUANTITATIVE EVALUATION OF THE TERMINOLOGY OF A VOCABULARY.

ERIC Educational Resources Information Center

KRAVETS, L.G.

THE CREATION OF AN INDUSTRIAL SYSTEM OF MACHINE TRANSLATION WITH AUTOMATIC INDEXING OF THE TRANSLATED MATERIALS PRESUMES THE DEVELOPMENT OF DICTIONARIES WHICH PROVIDE FOR THE IDENTIFICATION OF KEY WORDS AND WORD COMBINATIONS, FOLLOWED BY THEIR TRANSLATION INTO THE DESCRIPTORS OF THE SEARCH LANGUAGE. THREE SIGNS WHICH SHOW THAT A GIVEN WORD IS A…

CART (Communication Access Realtime Translation). PEPNet Tipsheet

ERIC Educational Resources Information Center

Larson, Judy, Comp.

1999-01-01

Communication Access Realtime Translation--(CART)--is the instant translation of the spoken word into English text performed by a CART reporter using a stenotype machine, notebook computer and realtime software. The text is then displayed on a computer monitor or other display device for the student who is deaf or hard of hearing to read. This…

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

DOE PAGES

O'keefe, Matthew; Parr, Terence; Edgar, B. Kevin; ...

1995-01-01

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. Wemore » 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.« less

A Brain-Machine Interface Operating with a Real-Time Spiking Neural Network Control Algorithm.

PubMed

Dethier, Julie; Nuyujukian, Paul; Eliasmith, Chris; Stewart, Terry; Elassaad, Shauki A; Shenoy, Krishna V; Boahen, Kwabena

2011-01-01

Motor prostheses aim to restore function to disabled patients. Despite compelling proof of concept systems, barriers to clinical translation remain. One challenge is to develop a low-power, fully-implantable system that dissipates only minimal power so as not to damage tissue. To this end, we implemented a Kalman-filter based decoder via a spiking neural network (SNN) and tested it in brain-machine interface (BMI) experiments with a rhesus monkey. The Kalman filter was trained to predict the arm's velocity and mapped on to the SNN using the Neural Engineering Framework (NEF). A 2,000-neuron embedded Matlab SNN implementation runs in real-time and its closed-loop performance is quite comparable to that of the standard Kalman filter. The success of this closed-loop decoder holds promise for hardware SNN implementations of statistical signal processing algorithms on neuromorphic chips, which may offer power savings necessary to overcome a major obstacle to the successful clinical translation of neural motor prostheses.

Integrated machine learning, molecular docking and 3D-QSAR based approach for identification of potential inhibitors of trypanosomal N-myristoyltransferase.

PubMed

Singh, Nidhi; Shah, Priyanka; Dwivedi, Hemlata; Mishra, Shikha; Tripathi, Renu; Sahasrabuddhe, Amogh A; Siddiqi, Mohammad Imran

2016-11-15

N-Myristoyltransferase (NMT) catalyzes the transfer of myristate to the amino-terminal glycine of a subset of proteins, a co-translational modification involved in trafficking substrate proteins to membrane locations, stabilization and protein-protein interactions. It is a studied and validated pre-clinical drug target for fungal and parasitic infections. In the present study, a machine learning approach, docking studies and CoMFA analysis have been integrated with the objective of translation of knowledge into a pipelined workflow towards the identification of putative hits through the screening of large compound libraries. In the proposed pipeline, the reported parasitic NMT inhibitors have been used to develop predictive machine learning classification models. Simultaneously, a TbNMT complex model was generated to establish the relationship between the binding mode of the inhibitors for LmNMT and TbNMT through molecular dynamics simulation studies. A 3D-QSAR model was developed and used to predict the activity of the proposed hits in the subsequent step. The hits classified as active based on the machine learning model were assessed as the potential anti-trypanosomal NMT inhibitors through molecular docking studies, predicted activity using a QSAR model and visual inspection. In the final step, the proposed pipeline was validated through in vitro experiments. A total of seven hits have been proposed and tested in vitro for evaluation of dual inhibitory activity against Leishmania donovani and Trypanosoma brucei. Out of these five compounds showed significant inhibition against both of the organisms. The common topmost active compound SEW04173 belongs to a pyrazole carboxylate scaffold and is anticipated to enrich the chemical space with enhanced potency through optimization.

A Comparison of Human and Machine Translation of Health Promotion Materials for Public Health Practice: Time, Costs, and Quality

PubMed Central

Turner, Anne M.; Bergman, Margo; Brownstein, Megumu; Cole, Kate; Kirchhoff, Katrin

2017-01-01

Context Most local public health departments serve limited English proficiency groups but lack sufficient resources to translate the health promotion materials that they produce into different languages. Machine translation (MT) with human postediting could fill this gap and work toward decreasing health disparities among non–English speakers. Objectives (1) To identify the time and costs associated with human translation (HT) of public health documents, (2) determine the time necessary for human postediting of MT, and (3) compare the quality of postedited MT and HT. Design A quality comparison of 25 MT and HT documents was performed with public health translators. The public health professionals involved were queried about the workflow, costs, and time for HT of 11 English public health documents over a 20-month period. Three recently translated documents of similar size and topic were then machine translated, the time for human postediting was recorded, and a blind quality analysis was performed. Setting Seattle/King County, Washington. Participants Public health professionals. Main Outcome Measures (1) Estimated times for various HT tasks; (2) observed postediting times for MT documents; (3) actual costs for HT; and (4) comparison of quality ratings for HT and MT. Results Human translation via local health department methods took 17 hours to 6 days. While HT postediting words per minute ranged from 1.58 to 5.88, MT plus human postediting words per minute ranged from 10 to 30. The cost of HT ranged from $130 to $1220; MT required no additional costs. A quality comparison by bilingual public health professionals showed that MT and HT were equivalently preferred. Conclusions MT with human postediting can reduce the time and costs of translating public health materials while maintaining quality similar to HT. In conjunction with postediting, MT could greatly improve the availability of multilingual public health materials. PMID:24084391

UIVerify: A Web-Based Tool for Verification and Automatic Generation of User Interfaces

NASA Technical Reports Server (NTRS)

Shiffman, Smadar; Degani, Asaf; Heymann, Michael

2004-01-01

In this poster, we describe a web-based tool for verification and automatic generation of user interfaces. The verification component of the tool accepts as input a model of a machine and a model of its interface, and checks that the interface is adequate (correct). The generation component of the tool accepts a model of a given machine and the user's task, and then generates a correct and succinct interface. This write-up will demonstrate the usefulness of the tool by verifying the correctness of a user interface to a flight-control system. The poster will include two more examples of using the tool: verification of the interface to an espresso machine, and automatic generation of a succinct interface to a large hypothetical machine.

Translational Epidemiology in Psychiatry

PubMed Central

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

2012-01-01

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

A simulator study on information requirements for precision hovering

NASA Technical Reports Server (NTRS)

Lemons, J. L.; Dukes, T. A.

1975-01-01

A fixed base simulator study of an advanced helicopter instrument display utilizing translational acceleration, velocity and position information is reported. The simulation involved piloting a heavy helicopter using the Integrated Trajectory Error Display (ITED) in a precision hover task. The test series explored two basic areas. The effect on hover accuracy of adding acceleration information was of primary concern. Also of interest was the operators' ability to use degraded information derived from less sophisticated sources. The addition of translational acceleration to a display containing velocity and position information did not appear to improve the hover performance significantly. However, displayed acceleration information seemed to increase the damping of the man machine system. Finally, the pilots could use translational information synthesized from attitude and angular acceleration as effectively as perfect acceleration.

Contrastive Analysis and the Translation of Idioms: Some Remarks on Contrasting Idioms.

ERIC Educational Resources Information Center

Roos, Eckhard

Contrastive analysis can help solve certain problems in translation, for example, that of idioms. A contrastive analysis of source language (SL) and target language (TL) might have as its theoretical framework a contrastive lexical analysis based on generative semantics. In this approach both SL and TL idioms are broken down into their semantic…

Pathogens and Disease Play Havoc on the Host Epiproteome-The "First Line of Response" Role for Proteomic Changes Influenced by Disorder.

PubMed

Rikkerink, Erik H A

2018-03-08

Organisms face stress from multiple sources simultaneously and require mechanisms to respond to these scenarios if they are to survive in the long term. This overview focuses on a series of key points that illustrate how disorder and post-translational changes can combine to play a critical role in orchestrating the response of organisms to the stress of a changing environment. Increasingly, protein complexes are thought of as dynamic multi-component molecular machines able to adapt through compositional, conformational and/or post-translational modifications to control their largely metabolic outputs. These metabolites then feed into cellular physiological homeostasis or the production of secondary metabolites with novel anti-microbial properties. The control of adaptations to stress operates at multiple levels including the proteome and the dynamic nature of proteomic changes suggests a parallel with the equally dynamic epigenetic changes at the level of nucleic acids. Given their properties, I propose that some disordered protein platforms specifically enable organisms to sense and react rapidly as the first line of response to change. Using examples from the highly dynamic host-pathogen and host-stress response, I illustrate by example how disordered proteins are key to fulfilling the need for multiple levels of integration of response at different time scales to create robust control points.

Game-powered machine learning

PubMed Central

Barrington, Luke; Turnbull, Douglas; Lanckriet, Gert

2012-01-01

Searching for relevant content in a massive amount of multimedia information is facilitated by accurately annotating each image, video, or song with a large number of relevant semantic keywords, or tags. We introduce game-powered machine learning, an integrated approach to annotating multimedia content that combines the effectiveness of human computation, through online games, with the scalability of machine learning. We investigate this framework for labeling music. First, a socially-oriented music annotation game called Herd It collects reliable music annotations based on the “wisdom of the crowds.” Second, these annotated examples are used to train a supervised machine learning system. Third, the machine learning system actively directs the annotation games to collect new data that will most benefit future model iterations. Once trained, the system can automatically annotate a corpus of music much larger than what could be labeled using human computation alone. Automatically annotated songs can be retrieved based on their semantic relevance to text-based queries (e.g., “funky jazz with saxophone,” “spooky electronica,” etc.). Based on the results presented in this paper, we find that actively coupling annotation games with machine learning provides a reliable and scalable approach to making searchable massive amounts of multimedia data. PMID:22460786

Game-powered machine learning.

PubMed

Barrington, Luke; Turnbull, Douglas; Lanckriet, Gert

2012-04-24

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

A Java-based enterprise system architecture for implementing a continuously supported and entirely Web-based exercise solution.

PubMed

Wang, Zhihui; Kiryu, Tohru

2006-04-01

Since machine-based exercise still uses local facilities, it is affected by time and place. We designed a web-based system architecture based on the Java 2 Enterprise Edition that can accomplish continuously supported machine-based exercise. In this system, exercise programs and machines are loosely coupled and dynamically integrated on the site of exercise via the Internet. We then extended the conventional health promotion model, which contains three types of players (users, exercise trainers, and manufacturers), by adding a new player: exercise program creators. Moreover, we developed a self-describing strategy to accommodate a variety of exercise programs and provide ease of use to users on the web. We illustrate our novel design with examples taken from our feasibility study on a web-based cycle ergometer exercise system. A biosignal-based workload control approach was introduced to ensure that users performed appropriate exercise alone.

Computational data sciences for assessment and prediction of climate extremes

NASA Astrophysics Data System (ADS)

Ganguly, A. R.

2011-12-01

Climate extremes may be defined inclusively as severe weather events or large shifts in global or regional weather patterns which may be caused or exacerbated by natural climate variability or climate change. This area of research arguably represents one of the largest knowledge-gaps in climate science which is relevant for informing resource managers and policy makers. While physics-based climate models are essential in view of non-stationary and nonlinear dynamical processes, their current pace of uncertainty reduction may not be adequate for urgent stakeholder needs. The structure of the models may in some cases preclude reduction of uncertainty for critical processes at scales or for the extremes of interest. On the other hand, methods based on complex networks, extreme value statistics, machine learning, and space-time data mining, have demonstrated significant promise to improve scientific understanding and generate enhanced predictions. When combined with conceptual process understanding at multiple spatiotemporal scales and designed to handle massive data, interdisciplinary data science methods and algorithms may complement or supplement physics-based models. Specific examples from the prior literature and our ongoing work suggests how data-guided improvements may be possible, for example, in the context of ocean meteorology, climate oscillators, teleconnections, and atmospheric process understanding, which in turn can improve projections of regional climate, precipitation extremes and tropical cyclones in an useful and interpretable fashion. A community-wide effort is motivated to develop and adapt computational data science tools for translating climate model simulations to information relevant for adaptation and policy, as well as for improving our scientific understanding of climate extremes from both observed and model-simulated data.

Optimal Achievable Encoding for Brain Machine Interface

DTIC Science & Technology

2017-12-22

dictionary-based encoding approach to translate a visual image into sequential patterns of electrical stimulation in real time , in a manner that...including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and...networks, and by applying linear decoding to complete recorded populations of retinal ganglion cells for the first time . Third, we developed a greedy

Rule Extraction Based on Extreme Learning Machine and an Improved Ant-Miner Algorithm for Transient Stability Assessment.

PubMed

Li, Yang; Li, Guoqing; Wang, Zhenhao

2015-01-01

In order to overcome the problems of poor understandability of the pattern recognition-based transient stability assessment (PRTSA) methods, a new rule extraction method based on extreme learning machine (ELM) and an improved Ant-miner (IAM) algorithm is presented in this paper. First, the basic principles of ELM and Ant-miner algorithm are respectively introduced. Then, based on the selected optimal feature subset, an example sample set is generated by the trained ELM-based PRTSA model. And finally, a set of classification rules are obtained by IAM algorithm to replace the original ELM network. The novelty of this proposal is that transient stability rules are extracted from an example sample set generated by the trained ELM-based transient stability assessment model by using IAM algorithm. The effectiveness of the proposed method is shown by the application results on the New England 39-bus power system and a practical power system--the southern power system of Hebei province.

SignMT: An Alternative Language Learning Tool

ERIC Educational Resources Information Center

Ditcharoen, Nadh; Naruedomkul, Kanlaya; Cercone, Nick

2010-01-01

Learning a second language is very difficult, especially, for the disabled; the disability may be a barrier to learn and to utilize information written in text form. We present the SignMT, Thai sign to Thai machine translation system, which is able to translate from Thai sign language into Thai text. In the translation process, SignMT takes into…

MetaJC++: A flexible and automatic program transformation technique using meta framework

NASA Astrophysics Data System (ADS)

Beevi, Nadera S.; Reghu, M.; Chitraprasad, D.; Vinodchandra, S. S.

2014-09-01

Compiler is a tool to translate abstract code containing natural language terms to machine code. Meta compilers are available to compile more than one languages. We have developed a meta framework intends to combine two dissimilar programming languages, namely C++ and Java to provide a flexible object oriented programming platform for the user. Suitable constructs from both the languages have been combined, thereby forming a new and stronger Meta-Language. The framework is developed using the compiler writing tools, Flex and Yacc to design the front end of the compiler. The lexer and parser have been developed to accommodate the complete keyword set and syntax set of both the languages. Two intermediate representations have been used in between the translation of the source program to machine code. Abstract Syntax Tree has been used as a high level intermediate representation that preserves the hierarchical properties of the source program. A new machine-independent stack-based byte-code has also been devised to act as a low level intermediate representation. The byte-code is essentially organised into an output class file that can be used to produce an interpreted output. The results especially in the spheres of providing C++ concepts in Java have given an insight regarding the potential strong features of the resultant meta-language.

MBASIC batch processor architectural overview

NASA Technical Reports Server (NTRS)

Reynolds, S. M.

1978-01-01

The MBASIC (TM) batch processor, a language translator designed to operate in the MBASIC (TM) environment is described. Features include: (1) a CONVERT TO BATCH command, usable from the ready mode; and (2) translation of the users program in stages through several levels of intermediate language and optimization. The processor is to be designed and implemented in both machine-independent and machine-dependent sections. The architecture is planned so that optimization processes are transparent to the rest of the system and need not be included in the first design implementation cycle.

A Bag of Concepts Approach for Biomedical Document Classification Using Wikipedia Knowledge.

PubMed

Mouriño-García, Marcos A; Pérez-Rodríguez, Roberto; Anido-Rifón, Luis E

2017-01-01

The ability to efficiently review the existing literature is essential for the rapid progress of research. This paper describes a classifier of text documents, represented as vectors in spaces of Wikipedia concepts, and analyses its suitability for classification of Spanish biomedical documents when only English documents are available for training. We propose the cross-language concept matching (CLCM) technique, which relies on Wikipedia interlanguage links to convert concept vectors from the Spanish to the English space. The performance of the classifier is compared to several baselines: a classifier based on machine translation, a classifier that represents documents after performing Explicit Semantic Analysis (ESA), and a classifier that uses a domain-specific semantic an- notator (MetaMap). The corpus used for the experiments (Cross-Language UVigoMED) was purpose-built for this study, and it is composed of 12,832 English and 2,184 Spanish MEDLINE abstracts. The performance of our approach is superior to any other state-of-the art classifier in the benchmark, with performance increases up to: 124% over classical machine translation, 332% over MetaMap, and 60 times over the classifier based on ESA. The results have statistical significance, showing p-values < 0.0001. Using knowledge mined from Wikipedia to represent documents as vectors in a space of Wikipedia concepts and translating vectors between language-specific concept spaces, a cross-language classifier can be built, and it performs better than several state-of-the-art classifiers. Schattauer GmbH.

A Bag of Concepts Approach for Biomedical Document Classification Using Wikipedia Knowledge*. Spanish-English Cross-language Case Study.

PubMed

Mouriño-García, Marcos A; Pérez-Rodríguez, Roberto; Anido-Rifón, Luis E

2017-10-26

The ability to efficiently review the existing literature is essential for the rapid progress of research. This paper describes a classifier of text documents, represented as vectors in spaces of Wikipedia concepts, and analyses its suitability for classification of Spanish biomedical documents when only English documents are available for training. We propose the cross-language concept matching (CLCM) technique, which relies on Wikipedia interlanguage links to convert concept vectors from the Spanish to the English space. The performance of the classifier is compared to several baselines: a classifier based on machine translation, a classifier that represents documents after performing Explicit Semantic Analysis (ESA), and a classifier that uses a domain-specific semantic annotator (MetaMap). The corpus used for the experiments (Cross-Language UVigoMED) was purpose-built for this study, and it is composed of 12,832 English and 2,184 Spanish MEDLINE abstracts. The performance of our approach is superior to any other state-of-the art classifier in the benchmark, with performance increases up to: 124% over classical machine translation, 332% over MetaMap, and 60 times over the classifier based on ESA. The results have statistical significance, showing p-values < 0.0001. Using knowledge mined from Wikipedia to represent documents as vectors in a space of Wikipedia concepts and translating vectors between language-specific concept spaces, a cross-language classifier can be built, and it performs better than several state-of-the-art classifiers.

Approximation algorithms for scheduling unrelated parallel machines with release dates

NASA Astrophysics Data System (ADS)

Avdeenko, T. V.; Mesentsev, Y. A.; Estraykh, I. V.

2017-01-01

In this paper we propose approaches to optimal scheduling of unrelated parallel machines with release dates. One approach is based on the scheme of dynamic programming modified with adaptive narrowing of search domain ensuring its computational effectiveness. We discussed complexity of the exact schedules synthesis and compared it with approximate, close to optimal, solutions. Also we explain how the algorithm works for the example of two unrelated parallel machines and five jobs with release dates. Performance results that show the efficiency of the proposed approach have been given.

TU-FG-BRB-08: Challenges, Limitations and Future Outlook Towards Clinical Translation of Proton Acoustic Range Verification

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yousefi, S; Ahmad, M; Xiang, L

Purpose: To report our investigations of proton acoustic imaging, including computer simulations and preliminary experimental studies at clinical facilities. The ultimate achievable accuracy, sensitivity and clinical translation challenges are discussed. Methods: The acoustic pulse due to pressure rise was estimated using finite element model. Since the ionoacoustic pulse is highly dependent on the proton pulse width and energy, multiple pulse widths were studied. Based on the received signal spectrum at piezoelectric ultrasound transducer with consideration of random thermal noise, maximum spatial resolution of the proton-acoustic imaging modality was calculated. The simulation studies defined the design specifications of the system tomore » detect proton acoustic signal from Hitachi and Mevion clinical machines. A 500 KHz hydrophone with 100 dB amplification was set up in a water tank placed in front of the proton nozzle A 40 MHz data acquisition was synchronized by a trigger signal provided by the machine. Results: Given 30–800 mGy dose per pulse at the Bragg peak, the minimum number of protons detectable by the proton acoustic technique was on the order of 10×10^6 per pulse. The broader pulse widths produce signal with lower acoustic frequencies, with 10 µs pulses producing signals with frequency less than 100 kHz. As the proton beam pulse width increases, a higher dose rate is required to measure the acoustic signal. Conclusion: We have established the minimal detection limit for protonacoustic range validation for a variety of pulse parameters. Our study indicated practical proton-acoustic range verification can be feasible with a pulse shorter than 10 µs, 5×10^6 protons/pulse, 50 nA beam current and a highly sensitive ultrasonic transducer. The translational challenges into current clinical machines include proper magnetic shielding of the measurement equipment, providing a clean trigger signal from the proton machine, providing a shorter proton beam pulse and higher dose per pulse.« less

Transdisciplinary translational science and the case of preterm birth

PubMed Central

Stevenson, D K; Shaw, G M; Wise, P H; Norton, M E; Druzin, M L; Valantine, H A; McFarland, D A

2013-01-01

Medical researchers have called for new forms of translational science that can solve complex medical problems. Mainstream science has made complementary calls for heterogeneous teams of collaborators who conduct transdisciplinary research so as to solve complex social problems. Is transdisciplinary translational science what the medical community needs? What challenges must the medical community overcome to successfully implement this new form of translational science? This article makes several contributions. First, it clarifies the concept of transdisciplinary research and distinguishes it from other forms of collaboration. Second, it presents an example of a complex medical problem and a concrete effort to solve it through transdisciplinary collaboration: for example, the problem of preterm birth and the March of Dimes effort to form a transdisciplinary research center that synthesizes knowledge on it. The presentation of this example grounds discussion on new medical research models and reveals potential means by which they can be judged and evaluated. Third, this article identifies the challenges to forming transdisciplines and the practices that overcome them. Departments, universities and disciplines tend to form intellectual silos and adopt reductionist approaches. Forming a more integrated (or ‘constructionist'), problem-based science reflective of transdisciplinary research requires the adoption of novel practices to overcome these obstacles. PMID:23079774

Transdisciplinary translational science and the case of preterm birth.

PubMed

Stevenson, D K; Shaw, G M; Wise, P H; Norton, M E; Druzin, M L; Valantine, H A; McFarland, D A

2013-04-01

Medical researchers have called for new forms of translational science that can solve complex medical problems. Mainstream science has made complementary calls for heterogeneous teams of collaborators who conduct transdisciplinary research so as to solve complex social problems. Is transdisciplinary translational science what the medical community needs? What challenges must the medical community overcome to successfully implement this new form of translational science? This article makes several contributions. First, it clarifies the concept of transdisciplinary research and distinguishes it from other forms of collaboration. Second, it presents an example of a complex medical problem and a concrete effort to solve it through transdisciplinary collaboration: for example, the problem of preterm birth and the March of Dimes effort to form a transdisciplinary research center that synthesizes knowledge on it. The presentation of this example grounds discussion on new medical research models and reveals potential means by which they can be judged and evaluated. Third, this article identifies the challenges to forming transdisciplines and the practices that overcome them. Departments, universities and disciplines tend to form intellectual silos and adopt reductionist approaches. Forming a more integrated (or 'constructionist'), problem-based science reflective of transdisciplinary research requires the adoption of novel practices to overcome these obstacles.

HGML: a hypertext guideline markup language.

PubMed Central

Hagerty, C. G.; Pickens, D.; Kulikowski, C.; Sonnenberg, F.

2000-01-01

Existing text-based clinical practice guidelines can be difficult to put into practice. While a growing number of such documents have gained acceptance in the medical community and contain a wealth of valuable information, the time required to digest them is substantial. Yet the expressive power, subtlety and flexibility of natural language pose challenges when designing computer tools that will help in their application. At the same time, formal computer languages typically lack such expressiveness and the effort required to translate existing documents into these languages may be costly. We propose a method based on the mark-up concept for converting text-based clinical guidelines into a machine-operable form. This allows existing guidelines to be manipulated by machine, and viewed in different formats at various levels of detail according to the needs of the practitioner, while preserving their originally published form. PMID:11079898

Impact of Machine Virtualization on Timing Precision for Performance-critical Tasks

NASA Astrophysics Data System (ADS)

Karpov, Kirill; Fedotova, Irina; Siemens, Eduard

2017-07-01

In this paper we present a measurement study to characterize the impact of hardware virtualization on basic software timing, as well as on precise sleep operations of an operating system. We investigated how timer hardware is shared among heavily CPU-, I/O- and Network-bound tasks on a virtual machine as well as on the host machine. VMware ESXi and QEMU/KVM have been chosen as commonly used examples of hypervisor- and host-based models. Based on statistical parameters of retrieved distributions, our results provide a very good estimation of timing behavior. It is essential for real-time and performance-critical applications such as image processing or real-time control.

CLIR Experiments at Maryland for TREC-2002: Evidence Combination for Arabic-English Retrieval

DTIC Science & Technology

2002-01-01

translation resources of three types (machine translation lexicons, a printed bilingual dictionary that had been manually rekeyed, and translation...on both the term list and the collection). • The Salmone Arabic-to-English dictionary , which was made available for use in the TREC-CLIR track by...Tufts University. No translation preference information is provided in this dictionary , but it does include rich markup describing morphology and part

Using Ontologies to Formalize Services Specifications in Multi-Agent Systems

NASA Technical Reports Server (NTRS)

Breitman, Karin Koogan; Filho, Aluizio Haendchen; Haeusler, Edward Hermann

2004-01-01

One key issue in multi-agent systems (MAS) is their ability to interact and exchange information autonomously across applications. To secure agent interoperability, designers must rely on a communication protocol that allows software agents to exchange meaningful information. In this paper we propose using ontologies as such communication protocol. Ontologies capture the semantics of the operations and services provided by agents, allowing interoperability and information exchange in a MAS. Ontologies are a formal, machine processable, representation that allows to capture the semantics of a domain and, to derive meaningful information by way of logical inference. In our proposal we use a formal knowledge representation language (OWL) that translates into Description Logics (a subset of first order logic), thus eliminating ambiguities and providing a solid base for machine based inference. The main contribution of this approach is to make the requirements explicit, centralize the specification in a single document (the ontology itself), at the same that it provides a formal, unambiguous representation that can be processed by automated inference machines.

Sharing programming resources between Bio* projects through remote procedure call and native call stack strategies.

PubMed

Prins, Pjotr; Goto, Naohisa; Yates, Andrew; Gautier, Laurent; Willis, Scooter; Fields, Christopher; Katayama, Toshiaki

2012-01-01

Open-source software (OSS) encourages computer programmers to reuse software components written by others. In evolutionary bioinformatics, OSS comes in a broad range of programming languages, including C/C++, Perl, Python, Ruby, Java, and R. To avoid writing the same functionality multiple times for different languages, it is possible to share components by bridging computer languages and Bio* projects, such as BioPerl, Biopython, BioRuby, BioJava, and R/Bioconductor. In this chapter, we compare the two principal approaches for sharing software between different programming languages: either by remote procedure call (RPC) or by sharing a local call stack. RPC provides a language-independent protocol over a network interface; examples are RSOAP and Rserve. The local call stack provides a between-language mapping not over the network interface, but directly in computer memory; examples are R bindings, RPy, and languages sharing the Java Virtual Machine stack. This functionality provides strategies for sharing of software between Bio* projects, which can be exploited more often. Here, we present cross-language examples for sequence translation, and measure throughput of the different options. We compare calling into R through native R, RSOAP, Rserve, and RPy interfaces, with the performance of native BioPerl, Biopython, BioJava, and BioRuby implementations, and with call stack bindings to BioJava and the European Molecular Biology Open Software Suite. In general, call stack approaches outperform native Bio* implementations and these, in turn, outperform RPC-based approaches. To test and compare strategies, we provide a downloadable BioNode image with all examples, tools, and libraries included. The BioNode image can be run on VirtualBox-supported operating systems, including Windows, OSX, and Linux.

(M-CAT) Minor Caliber Weapons Trainer MK-19, 40mm Machine Gun

DTIC Science & Technology

1989-07-24

microprocessor chip with an Intel 387 math coprocessor. The Nova 620 is a digital time base corrector. It is used to time base correct the video data...the circuit. After filtering, the horizontal and vertical position signals are converted to digital values by the Data Translation (DTX-311) analog...from the computer. Each frame of the video disk is individually digitized as to target size, location, and range. The guns azimuth and elevation are

Role of ribosomal protein mutations in tumor development (Review)

PubMed Central

GOUDARZI, KAVEH M.; LINDSTRÖM, MIKAEL S.

2016-01-01

Ribosomes are cellular machines essential for protein synthesis. The biogenesis of ribosomes is a highly complex and energy consuming process that initiates in the nucleolus. Recently, a series of studies applying whole-exome or whole-genome sequencing techniques have led to the discovery of ribosomal protein gene mutations in different cancer types. Mutations in ribosomal protein genes have for example been found in endometrial cancer (RPL22), T-cell acute lymphoblastic leukemia (RPL10, RPL5 and RPL11), chronic lymphocytic leukemia (RPS15), colorectal cancer (RPS20), and glioma (RPL5). Moreover, patients suffering from Diamond-Blackfan anemia, a bone marrow failure syndrome caused by mutant ribosomal proteins are also at higher risk for developing leukemia, or solid tumors. Different experimental models indicate potential mechanisms whereby ribosomal proteins may initiate cancer development. In particular, deregulation of the p53 tumor suppressor network and altered mRNA translation are mechanisms likely to be involved. We envisage that changes in expression and the occurrence of ribosomal protein gene mutations play important roles in cancer development. Ribosome biology constitutes a re-emerging vital area of basic and translational cancer research. PMID:26892688

Translating Big Data into Smart Data for Veterinary Epidemiology

PubMed Central

VanderWaal, Kimberly; Morrison, Robert B.; Neuhauser, Claudia; Vilalta, Carles; Perez, Andres M.

2017-01-01

The increasing availability and complexity of data has led to new opportunities and challenges in veterinary epidemiology around how to translate abundant, diverse, and rapidly growing “big” data into meaningful insights for animal health. Big data analytics are used to understand health risks and minimize the impact of adverse animal health issues through identifying high-risk populations, combining data or processes acting at multiple scales through epidemiological modeling approaches, and harnessing high velocity data to monitor animal health trends and detect emerging health threats. The advent of big data requires the incorporation of new skills into veterinary epidemiology training, including, for example, machine learning and coding, to prepare a new generation of scientists and practitioners to engage with big data. Establishing pipelines to analyze big data in near real-time is the next step for progressing from simply having “big data” to create “smart data,” with the objective of improving understanding of health risks, effectiveness of management and policy decisions, and ultimately preventing or at least minimizing the impact of adverse animal health issues. PMID:28770216

Sampled-data controller implementation

NASA Astrophysics Data System (ADS)

Wang, Yu; Leduc, Ryan J.

2012-09-01

The setting of this article is the implementation of timed discrete-event systems (TDES) as sampled-data (SD) controllers. An SD controller is driven by a periodic clock and sees the system as a series of inputs and outputs. On each clock edge (tick event), it samples its inputs, changes states and updates its outputs. In this article, we establish a formal representation of an SD controller as a Moore synchronous finite state machine (FSM). We describe how to translate a TDES supervisor to an FSM, as well as necessary properties to be able to do so. We discuss how to construct a single centralised controller as well as a set of modular controllers, and show that they will produce equivalent output. We briefly discuss how the recently introduced SD controllability definition relates to our translation method. SD controllability is an extension of TDES controllability which captures several new properties that are useful in dealing with concurrency issues, as well as make it easier to translate a TDES supervisor into an SD controller. We next discuss the application of SD controllability to a small flexible manufacturing system (FMS) from the literature. The example demonstrates the successful application of the new SD properties. We describe the design of the system in detail to illustrate the new conditions and to provide designers with guidance on how to apply the properties. We also present some FSM translation issues encountered, as well as the FSM version of the system's supervisors.

The influence of negative training set size on machine learning-based virtual screening.

PubMed

Kurczab, Rafał; Smusz, Sabina; Bojarski, Andrzej J

2014-01-01

The paper presents a thorough analysis of the influence of the number of negative training examples on the performance of machine learning methods. The impact of this rather neglected aspect of machine learning methods application was examined for sets containing a fixed number of positive and a varying number of negative examples randomly selected from the ZINC database. An increase in the ratio of positive to negative training instances was found to greatly influence most of the investigated evaluating parameters of ML methods in simulated virtual screening experiments. In a majority of cases, substantial increases in precision and MCC were observed in conjunction with some decreases in hit recall. The analysis of dynamics of those variations let us recommend an optimal composition of training data. The study was performed on several protein targets, 5 machine learning algorithms (SMO, Naïve Bayes, Ibk, J48 and Random Forest) and 2 types of molecular fingerprints (MACCS and CDK FP). The most effective classification was provided by the combination of CDK FP with SMO or Random Forest algorithms. The Naïve Bayes models appeared to be hardly sensitive to changes in the number of negative instances in the training set. In conclusion, the ratio of positive to negative training instances should be taken into account during the preparation of machine learning experiments, as it might significantly influence the performance of particular classifier. What is more, the optimization of negative training set size can be applied as a boosting-like approach in machine learning-based virtual screening.

The influence of negative training set size on machine learning-based virtual screening

PubMed Central

2014-01-01

Background The paper presents a thorough analysis of the influence of the number of negative training examples on the performance of machine learning methods. Results The impact of this rather neglected aspect of machine learning methods application was examined for sets containing a fixed number of positive and a varying number of negative examples randomly selected from the ZINC database. An increase in the ratio of positive to negative training instances was found to greatly influence most of the investigated evaluating parameters of ML methods in simulated virtual screening experiments. In a majority of cases, substantial increases in precision and MCC were observed in conjunction with some decreases in hit recall. The analysis of dynamics of those variations let us recommend an optimal composition of training data. The study was performed on several protein targets, 5 machine learning algorithms (SMO, Naïve Bayes, Ibk, J48 and Random Forest) and 2 types of molecular fingerprints (MACCS and CDK FP). The most effective classification was provided by the combination of CDK FP with SMO or Random Forest algorithms. The Naïve Bayes models appeared to be hardly sensitive to changes in the number of negative instances in the training set. Conclusions In conclusion, the ratio of positive to negative training instances should be taken into account during the preparation of machine learning experiments, as it might significantly influence the performance of particular classifier. What is more, the optimization of negative training set size can be applied as a boosting-like approach in machine learning-based virtual screening. PMID:24976867

Agent Based Computing Machine

DTIC Science & Technology

2005-12-09

decision making logic that respond to the environment (concentration of operands - the state vector), and bias or "mood" as established by its history of...mentioned in the chart, there is no need for file management in a ABC Machine. Information is distributed, no history is maintained. The instruction set... Postgresql ) for collection of cluster samples/snapshots over intervals of time. An prototypical example of an XML file to configure and launch the ABC

Structural and Sequence Similarity Makes a Significant Impact on Machine-Learning-Based Scoring Functions for Protein-Ligand Interactions.

PubMed

Li, Yang; Yang, Jianyi

2017-04-24

The prediction of protein-ligand binding affinity has recently been improved remarkably by machine-learning-based scoring functions. For example, using a set of simple descriptors representing the atomic distance counts, the RF-Score improves the Pearson correlation coefficient to about 0.8 on the core set of the PDBbind 2007 database, which is significantly higher than the performance of any conventional scoring function on the same benchmark. A few studies have been made to discuss the performance of machine-learning-based methods, but the reason for this improvement remains unclear. In this study, by systemically controlling the structural and sequence similarity between the training and test proteins of the PDBbind benchmark, we demonstrate that protein structural and sequence similarity makes a significant impact on machine-learning-based methods. After removal of training proteins that are highly similar to the test proteins identified by structure alignment and sequence alignment, machine-learning-based methods trained on the new training sets do not outperform the conventional scoring functions any more. On the contrary, the performance of conventional functions like X-Score is relatively stable no matter what training data are used to fit the weights of its energy terms.

A proposal of an architecture for the coordination level of intelligent machines

NASA Technical Reports Server (NTRS)

Beard, Randall; Farah, Jeff; Lima, Pedro

1993-01-01

The issue of obtaining a practical, structured, and detailed description of an architecture for the Coordination Level of Center for Intelligent Robotic Systems for Sapce Exploration (CIRSSE) Testbed Intelligent Controller is addressed. Previous theoretical and implementation works were the departure point for the discussion. The document is organized as follows: after this introductory section, section 2 summarizes the overall view of the Intelligent Machine (IM) as a control system, proposing a performance measure on which to base its design. Section 3 addresses with some detail implementation issues. An hierarchic petri-net with feedback-based learning capabilities is proposed. Finally, section 4 is an attempt to address the feedback problem. Feedback is used for two functions: error recovery and reinforcement learning of the correct translations for the petri-net transitions.

Effectively identifying compound-protein interactions by learning from positive and unlabeled examples.

PubMed

Cheng, Zhanzhan; Zhou, Shuigeng; Wang, Yang; Liu, Hui; Guan, Jihong; Chen, Yi-Ping Phoebe

2016-05-18

Prediction of compound-protein interactions (CPIs) is to find new compound-protein pairs where a protein is targeted by at least a compound, which is a crucial step in new drug design. Currently, a number of machine learning based methods have been developed to predict new CPIs in the literature. However, as there is not yet any publicly available set of validated negative CPIs, most existing machine learning based approaches use the unknown interactions (not validated CPIs) selected randomly as the negative examples to train classifiers for predicting new CPIs. Obviously, this is not quite reasonable and unavoidably impacts the CPI prediction performance. In this paper, we simply take the unknown CPIs as unlabeled examples, and propose a new method called PUCPI (the abbreviation of PU learning for Compound-Protein Interaction identification) that employs biased-SVM (Support Vector Machine) to predict CPIs using only positive and unlabeled examples. PU learning is a class of learning methods that leans from positive and unlabeled (PU) samples. To the best of our knowledge, this is the first work that identifies CPIs using only positive and unlabeled examples. We first collect known CPIs as positive examples and then randomly select compound-protein pairs not in the positive set as unlabeled examples. For each CPI/compound-protein pair, we extract protein domains as protein features and compound substructures as chemical features, then take the tensor product of the corresponding compound features and protein features as the feature vector of the CPI/compound-protein pair. After that, biased-SVM is employed to train classifiers on different datasets of CPIs and compound-protein pairs. Experiments over various datasets show that our method outperforms six typical classifiers, including random forest, L1- and L2-regularized logistic regression, naive Bayes, SVM and k-nearest neighbor (kNN), and three types of existing CPI prediction models. Source code, datasets and related documents of PUCPI are available at: http://admis.fudan.edu.cn/projects/pucpi.html.

Translations on USSR Resources, Number 767.

DTIC Science & Technology

1978-01-19

photography and so on). The amount of data obtained as a result of additional surveys makes it possible to evaluate the intensity and configuration...machine tools , chemical products, refrigerators, as well as potatoes and products of livestock breeding. The Kazakh SSR made an enormous leap in its...of the fuel and water power resources of Georgia, Azerbaydzhan and Armenia. Petroleum, transport and electrical machine building, machine tool

Conquering Language Babel in the Classroom

ERIC Educational Resources Information Center

Minichino, Mario; Berson, Michael J.

2012-01-01

This article is an exploration of the available applications for speech to speech real-time translation software for use in the classroom. Three different types of machine language translation (MLT) software and devices are reviewed for their features and practical application in secondary education classrooms.

Bridging from Replication to Translation with a Thermal, Autonomous Replicator Made from Transfer RNA

NASA Astrophysics Data System (ADS)

Braun, Dieter; Möller, Friederike M.; Krammer, Hubert

2013-03-01

Central to the understanding of living systems is the interplay between DNA/RNA and proteins. Known as Eigen paradox, proteins require genetic information while proteins are needed for the replication of genes. RNA world scenarios focus on a base by base replication disconnected from translation. Here we used strategies from DNA machines to demonstrate a tight connection between a basic replication mechanism and translation. A pool of hairpin molecules replicate a two-letter code. The replication is thermally driven: the energy and negative entropy to drive replication is initially stored in metastable hairpins by kinetic cooling. Both are released by a highly specific and exponential replication reaction that is solely implemented by base hybridization. The duplication time is 30s. The reaction is monitored by fluorescence and described by a detailed kinetic model. The RNA hairpins usetransfer RNA sequences and the replication is driven by the simple disequilibrium setting of a thermal gradient The experiments propose a physical rather than a chemical scenario for the autonomous replication of protein encoding information. Supported by the NanoSystems Initiative Munich and ERC.

The Evaluation and Systems Analysis of the SYSTRAN Machine Translation System

DTIC Science & Technology

1977-01-01

DiFondi (IRDT) I. KIY *0*01 (Cu.wMu. .~ .‘~~.. lid. it a....Wp .11 id.iiSiIp Op e4.Sk s~~S.,) Machine Traca lation Evaluation scan Dictionary Update S...ntic Expression Dictionary Update *55? **Ct fCMi~ uw * lid. It -- p Sdsffl~~ Sr Sidsi ,~~~Siv) This report is the product of contractual effort to...translated end then corrected by a b ilingu.ai. exper t in each field. two types of corrections were considered iaplweatabi e, stan dictionary update and

Automatic Configuration of Programmable Logic Controller Emulators

DTIC Science & Technology

2015-03-01

25 11 Example tree generated using UPGMA [Edw13] . . . . . . . . . . . . . . . . . . . . 33 12 Example sequence alignment for two... UPGMA Unweighted Pair Group Method with Arithmetic Mean URL uniform resource locator VM virtual machine XML Extensible Markup Language xx List of...appearance in the ses- sion, and then they are clustered again using Unweighted Pair Group Method with Arithmetic Mean ( UPGMA ) with a distance matrix based

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

ERIC Educational Resources Information Center

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";…

Actes des Journees de linguistique (Proceedings of the Linguistics Conference) (6th, 1992).

ERIC Educational Resources Information Center

Brousseau, Martin, Ed.; And Others

Papers, all in French, presented at a conference on linguistics include: "Machine Translation: Historic Aspects" (Ghada Attieh); "Translation and Conditioning" (Stephanie Bedard); "Semantic or Pre-Semantic Structures? From Perception to Causation" (Denise Belanger); "Presentation of Poetry Sung in Maroc"…

Force reflecting hand controller

NASA Technical Reports Server (NTRS)

Mcaffee, Douglas A. (Inventor); Snow, Edward R. (Inventor); Townsend, William T. (Inventor)

1993-01-01

A universal input device for interfacing a human operator with a slave machine such as a robot or the like includes a plurality of serially connected mechanical links extending from a base. A handgrip is connected to the mechanical links distal from the base such that a human operator may grasp the handgrip and control the position thereof relative to the base through the mechanical links. A plurality of rotary joints is arranged to connect the mechanical links together to provide at least three translational degrees of freedom and at least three rotational degrees of freedom of motion of the handgrip relative to the base. A cable and pulley assembly for each joint is connected to a corresponding motor for transmitting forces from the slave machine to the handgrip to provide kinesthetic feedback to the operator and for producing control signals that may be transmitted from the handgrip to the slave machine. The device gives excellent kinesthetic feedback, high-fidelity force/torque feedback, a kinematically simple structure, mechanically decoupled motion in all six degrees of freedom, and zero backlash. The device also has a much larger work envelope, greater stiffness and responsiveness, smaller stowage volume, and better overlap of the human operator's range of motion than previous designs.

Decoding sORF translation - from small proteins to gene regulation.

PubMed

Cabrera-Quio, Luis Enrique; Herberg, Sarah; Pauli, Andrea

2016-11-01

Translation is best known as the fundamental mechanism by which the ribosome converts a sequence of nucleotides into a string of amino acids. Extensive research over many years has elucidated the key principles of translation, and the majority of translated regions were thought to be known. The recent discovery of wide-spread translation outside of annotated protein-coding open reading frames (ORFs) came therefore as a surprise, raising the intriguing possibility that these newly discovered translated regions might have unrecognized protein-coding or gene-regulatory functions. Here, we highlight recent findings that provide evidence that some of these newly discovered translated short ORFs (sORFs) encode functional, previously missed small proteins, while others have regulatory roles. Based on known examples we will also speculate about putative additional roles and the potentially much wider impact that these translated regions might have on cellular homeostasis and gene regulation.

Patient safety, quality of care, and knowledge translation in the intensive care unit.

PubMed

Needham, Dale M

2010-07-01

A large gap exists between the completion of clinical research demonstrating the benefit of new treatment interventions and improved patient outcomes resulting from implementation of these interventions as part of routine clinical practice. This gap clearly affects patient safety and quality of care. Knowledge translation is important for addressing this gap, but evaluation of the most appropriate and effective knowledge translation methods is still ongoing. Through describing one model for knowledge translation and an example of its implementation, insights can be gained into systematic methods for advancing the implementation of evidence-based interventions to improve safety, quality, and patient outcomes.

Optical-Fiber-Welding Machine

NASA Technical Reports Server (NTRS)

Goss, W. C.; Mann, W. A.; Goldstein, R.

1985-01-01

Technique yields joints with average transmissivity of 91.6 percent. Electric arc passed over butted fiber ends to melt them together. Maximum optical transmissivity of joint achieved with optimum choice of discharge current, translation speed, and axial compression of fibers. Practical welding machine enables delicate and tedious joining operation performed routinely.

Linguistic steganography on Twitter: hierarchical language modeling with manual interaction

NASA Astrophysics Data System (ADS)

Wilson, Alex; Blunsom, Phil; Ker, Andrew D.

2014-02-01

This work proposes a natural language stegosystem for Twitter, modifying tweets as they are written to hide 4 bits of payload per tweet, which is a greater payload than previous systems have achieved. The system, CoverTweet, includes novel components, as well as some already developed in the literature. We believe that the task of transforming covers during embedding is equivalent to unilingual machine translation (paraphrasing), and we use this equivalence to de ne a distortion measure based on statistical machine translation methods. The system incorporates this measure of distortion to rank possible tweet paraphrases, using a hierarchical language model; we use human interaction as a second distortion measure to pick the best. The hierarchical language model is designed to model the speci c language of the covers, which in this setting is the language of the Twitter user who is embedding. This is a change from previous work, where general-purpose language models have been used. We evaluate our system by testing the output against human judges, and show that humans are unable to distinguish stego tweets from cover tweets any better than random guessing.

Translations on North Korea No. 622

DTIC Science & Technology

1978-10-13

Pyongyang Power Station 5 July Electric Factory Hamhung Machine Tool Factory Kosan Plastic Pipe Factory Sog’wangea Plastic Pipe Factory 8...August Factory Double Chollima Hamhung Disabled Veterans’ Plastic Goods Factory Mangyongdae Machine Tool Factory Kangso Coal Mine Tongdaewon Garment...21 Jul 78 p 4) innovating in machine tool production (NC 21 Jul 78 p 2) in 40 days of the 蔴 days of combat" raised coal production 10 percent

Translations on Eastern Europe Political, Sociological, and Military Affairs No. 1482.

DTIC Science & Technology

1977-12-06

Soviet deliveries of complete industrial installations have become the basis of new sectors of Polish industry: machine - tool building, automotive...develop mutually advan- tageous cooperation. Poland has become an important supplier of industrial equipment and machines , and also of seagoing ships...to the USSR. Every fifth ship that sails under the Soviet flag has been built by Polish shipbuilders. We have supplied machines and equipment for

Creation of a Machine File and Subsequent Computer-Assisted Production of Publishing Outputs, Including a Translation Journal and an Index.

ERIC Educational Resources Information Center

Buckland, Lawrence F.; Weaver, Vance

Reported are the findings of the Uspekhi experiment in creating a labeled machine file, as well as sample products of this system - an article from a scientific journal and an index page. Production cost tables are presented for the machine file, primary journals, and journal indexes. Comparisons were made between the 1965 predicted costs and the…

A forestry application simulation of man-machine techniques for analyzing remotely sensed data

NASA Technical Reports Server (NTRS)

Berkebile, J.; Russell, J.; Lube, B.

1976-01-01

The typical steps in the analysis of remotely sensed data for a forestry applications example are simulated. The example uses numerically-oriented pattern recognition techniques and emphasizes man-machine interaction.

Translating research and into everyday clinical practice: Lessons learned from a USA national dental practice-based research network

PubMed Central

Gordan, Valeria V.

2012-01-01

Clinical studies are of paramount importance for testing and translation of the research findings to the community. Despite the existence of clinical studies, a significant delay exists between the generation of new knowledge and its application into the medical/dental community and their patients. One example is the repair of defective dental restorations. About 75% of practitioners in general dental practices do not consider the repair of dental restorations as a viable alternative to the replacement of defective restorations. Engaging and partnering with health practitioners in the field on studies addressing everyday clinical research questions may offer a solution to speed up the translation of the research findings. Practice-based research (PBR) offers a unique opportunity for practitioners to be involved in the research process, formulating clinical research questions. Additionally, PBR generates evidence-based knowledge with a broader spectrum that can be more readily generalized to the public. With PBR, clinicians are involved in the entire research process from its inception to its dissemination. Early practitioner interaction in the research process may result in ideas being more readily incorporated into practice. This paper discusses PBR as a mean to speed up the translation of research findings to clinical practice. It also reviews repair versus replacement of defective restorations as one example of the delay in the application of research findings to clinical practice. PMID:22889478

Decoding the non-stationary neuron spike trains by dual Monte Carlo point process estimation in motor Brain Machine Interfaces.

PubMed

Liao, Yuxi; Li, Hongbao; Zhang, Qiaosheng; Fan, Gong; Wang, Yiwen; Zheng, Xiaoxiang

2014-01-01

Decoding algorithm in motor Brain Machine Interfaces translates the neural signals to movement parameters. They usually assume the connection between the neural firings and movements to be stationary, which is not true according to the recent studies that observe the time-varying neuron tuning property. This property results from the neural plasticity and motor learning etc., which leads to the degeneration of the decoding performance when the model is fixed. To track the non-stationary neuron tuning during decoding, we propose a dual model approach based on Monte Carlo point process filtering method that enables the estimation also on the dynamic tuning parameters. When applied on both simulated neural signal and in vivo BMI data, the proposed adaptive method performs better than the one with static tuning parameters, which raises a promising way to design a long-term-performing model for Brain Machine Interfaces decoder.

Nanomedicine: Tiny Particles and Machines Give Huge Gains

PubMed Central

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

2014-01-01

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-based probes for molecular imaging, nano-carriers for drug/gene delivery, multi-functional nanoparticles for theranostics, and molecular machines for biological and medical studies. This article provides an overview of the nanomedicine field, with an emphasis on nanoparticles for imaging and therapy, as well as engineered nucleases for genome editing. The challenges in translating nanomedicine approaches to clinical applications are discussed. PMID:24297494

Annotation of rule-based models with formal semantics to enable creation, analysis, reuse and visualization.

PubMed

Misirli, Goksel; Cavaliere, Matteo; Waites, William; Pocock, Matthew; Madsen, Curtis; Gilfellon, Owen; Honorato-Zimmer, Ricardo; Zuliani, Paolo; Danos, Vincent; Wipat, Anil

2016-03-15

Biological systems are complex and challenging to model and therefore model reuse is highly desirable. To promote model reuse, models should include both information about the specifics of simulations and the underlying biology in the form of metadata. The availability of computationally tractable metadata is especially important for the effective automated interpretation and processing of models. Metadata are typically represented as machine-readable annotations which enhance programmatic access to information about models. Rule-based languages have emerged as a modelling framework to represent the complexity of biological systems. Annotation approaches have been widely used for reaction-based formalisms such as SBML. However, rule-based languages still lack a rich annotation framework to add semantic information, such as machine-readable descriptions, to the components of a model. We present an annotation framework and guidelines for annotating rule-based models, encoded in the commonly used Kappa and BioNetGen languages. We adapt widely adopted annotation approaches to rule-based models. We initially propose a syntax to store machine-readable annotations and describe a mapping between rule-based modelling entities, such as agents and rules, and their annotations. We then describe an ontology to both annotate these models and capture the information contained therein, and demonstrate annotating these models using examples. Finally, we present a proof of concept tool for extracting annotations from a model that can be queried and analyzed in a uniform way. The uniform representation of the annotations can be used to facilitate the creation, analysis, reuse and visualization of rule-based models. Although examples are given, using specific implementations the proposed techniques can be applied to rule-based models in general. The annotation ontology for rule-based models can be found at http://purl.org/rbm/rbmo The krdf tool and associated executable examples are available at http://purl.org/rbm/rbmo/krdf anil.wipat@newcastle.ac.uk or vdanos@inf.ed.ac.uk. © The Author 2015. Published by Oxford University Press.

HiVy automated translation of stateflow designs for model checking verification

NASA Technical Reports Server (NTRS)

Pingree, Paula

2003-01-01

tool set enables model checking of finite state machines designs. This is acheived by translating state-chart specifications into the input language of the Spin model checker. An abstract syntax of hierarchical sequential automata (HSA) is provided as an intermediate format tool set.

Measurement of aspheric mirror by nanoprofiler using normal vector tracing

NASA Astrophysics Data System (ADS)

Kitayama, Takao; Shiraji, Hiroki; Yamamura, Kazuya; Endo, Katsuyoshi

2016-09-01

Aspheric or free-form optics with high accuracy are necessary in many fields such as third-generation synchrotron radiation and extreme-ultraviolet lithography. Therefore the demand of measurement method for aspherical or free-form surface with nanometer accuracy increases. Purpose of our study is to develop a non-contact measurement technology for aspheric or free-form surfaces directly with high repeatability. To achieve this purpose we have developed threedimensional Nanoprofiler which detects normal vectors of sample surface. The measurement principle is based on the straightness of laser light and the accurate motion of rotational goniometers. This machine consists of four rotational stages, one translational stage and optical head which has the quadrant photodiode (QPD) and laser source. In this measurement method, we conform the incident light beam to reflect the beam by controlling five stages and determine the normal vectors and the coordinates of the surface from signal of goniometers, translational stage and QPD. We can obtain three-dimensional figure from the normal vectors and their coordinates by surface reconstruction algorithm. To evaluate performance of this machine we measure a concave aspheric mirror with diameter of 150 mm. As a result we achieve to measure large area of 150mm diameter. And we observe influence of systematic errors which the machine has. Then we simulated the influence and subtracted it from measurement result.

The Practical Value of Translation Theory.

ERIC Educational Resources Information Center

Komissarov, Vilen

1985-01-01

Discusses why translation theory has had an inadequate impact on translation practice and gives specific examples of ways in which translation theory can provide the translator with general principles and methods of translating idioms. (SED)

Machine Translation Based Data Augmentation for Cantonese Keyword Spotting (Author’s Manuscript)

DTIC Science & Technology

2016-05-19

for the key- word k at the specific threshold t is defined as ATWV (k, t) = 1− PFR(k, t)− C · PFA (k, t) (1) where C = 999.9 is a constant, PFR and... PFA are probabil- ities of miss and false accept, respectively. MTWV is com- puted as a maximal ATWV over all possible values of t. 4. RESULTS In this

Computer Generation of Natural Language from a Deep Conceptual Base

DTIC Science & Technology

1974-01-01

It would be useful to have machines which could read scientific documents, newspaper articles , novels, etc., and translate them into other...preparing abstracts :or articles and in headline writing (at least in those cases in which headlines are used as an indication of article content...above), a definite or indefinite article is attached to the noun phrase. The selection of color and size adjectives is made in .. fashion

Selecting, Adapting, and Implementing Evidence-based Interventions in Rural Settings: An Analysis of 70 Community Examples.

PubMed

Smith, Tina Anderson; Adimu, Tanisa Foxworth; Martinez, Amanda Phillips; Minyard, Karen

2016-01-01

This paper explores how communities translate evidence-based and promising health practices to rural contexts. A descriptive, qualitative analysis was conducted using data from 70 grantees funded by the Federal Office of Rural Health Policy to implement evidence-based health practices in rural settings. Findings were organized using The Interactive Systems Framework for Dissemination and Implementation. Grantees broadly interpreted evidence-based and promising practices, resulting in the implementation of a patchwork of health-related interventions that fell along a spectrum of evidentiary rigor. The cohort faced common challenges translating recognized practices into rural community settings and reported making deliberate modifications to original models as a result. Opportunities for building a more robust rural health evidence base include investments to incentivize evidence-based programming in rural settings; rural-specific research and theory-building; translation of existing evidence using a rural lens; technical assistance to support rural innovation; and prioritization of evaluation locally.

Initiation of translation in bacteria by a structured eukaryotic IRES RNA.

PubMed

Colussi, Timothy M; Costantino, David A; Zhu, Jianyu; Donohue, John Paul; Korostelev, Andrei A; Jaafar, Zane A; Plank, Terra-Dawn M; Noller, Harry F; Kieft, Jeffrey S

2015-03-05

The central dogma of gene expression (DNA to RNA to protein) is universal, but in different domains of life there are fundamental mechanistic differences within this pathway. For example, the canonical molecular signals used to initiate protein synthesis in bacteria and eukaryotes are mutually exclusive. However, the core structures and conformational dynamics of ribosomes that are responsible for the translation steps that take place after initiation are ancient and conserved across the domains of life. We wanted to explore whether an undiscovered RNA-based signal might be able to use these conserved features, bypassing mechanisms specific to each domain of life, and initiate protein synthesis in both bacteria and eukaryotes. Although structured internal ribosome entry site (IRES) RNAs can manipulate ribosomes to initiate translation in eukaryotic cells, an analogous RNA structure-based mechanism has not been observed in bacteria. Here we report our discovery that a eukaryotic viral IRES can initiate translation in live bacteria. We solved the crystal structure of this IRES bound to a bacterial ribosome to 3.8 Å resolution, revealing that despite differences between bacterial and eukaryotic ribosomes this IRES binds directly to both and occupies the space normally used by transfer RNAs. Initiation in both bacteria and eukaryotes depends on the structure of the IRES RNA, but in bacteria this RNA uses a different mechanism that includes a form of ribosome repositioning after initial recruitment. This IRES RNA bridges billions of years of evolutionary divergence and provides an example of an RNA structure-based translation initiation signal capable of operating in two domains of life.

Approaches to Machine Learning.

DTIC Science & Technology

1984-02-16

The field of machine learning strives to develop methods and techniques to automatic the acquisition of new information, new skills, and new ways of organizing existing information. In this article, we review the major approaches to machine learning in symbolic domains, covering the tasks of learning concepts from examples, learning search methods, conceptual clustering, and language acquisition. We illustrate each of the basic approaches with paradigmatic examples. (Author)

The Distribution of the Informative Intensity of the Text in Terms of its Structure (On Materials of the English Texts in the Mining Sphere)

NASA Astrophysics Data System (ADS)

Znikina, Ludmila; Rozhneva, Elena

2017-11-01

The article deals with the distribution of informative intensity of the English-language scientific text based on its structural features contributing to the process of formalization of the scientific text and the preservation of the adequacy of the text with derived semantic information in relation to the primary. Discourse analysis is built on specific compositional and meaningful examples of scientific texts taken from the mining field. It also analyzes the adequacy of the translation of foreign texts into another language, the relationships between elements of linguistic systems, the degree of a formal conformance, translation with the specific objectives and information needs of the recipient. Some key words and ideas are emphasized in the paragraphs of the English-language mining scientific texts. The article gives the characteristic features of the structure of paragraphs of technical text and examples of constructions in English scientific texts based on a mining theme with the aim to explain the possible ways of their adequate translation.

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

PubMed

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

2016-02-24

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

Research-to-policy translation for prevention of disordered weight and shape control behaviors: A case example targeting dietary supplements sold for weight loss and muscle building.

PubMed

Austin, S Bryn; Yu, Kimberly; Tran, Alvin; Mayer, Beth

2017-04-01

New approaches to universal eating disorders prevention and interventions targeting macro-environmental change are greatly needed, and research-to-policy translation efforts hold promise for advancing both of these goals. This paper describes as a policy-translation case example an academic-community-government partnership of the Strategic Training Initiative for the Prevention of Eating Disorders, Multi-Service Eating Disorders Association, and the office of Massachusetts Representative Kay Khan, all based in Massachusetts, USA. The partnership's research-to-policy translation project focused on dietary supplements sold for weight loss and muscle building, which have been linked with serious injury and death in consumers. Youth and people of all ages with eating disorders and body dysmorphic disorder may be especially vulnerable to use these products due to deceptive promises of fast and safe weight loss and muscle gain. The research-to-policy translation project was informed by a triggers-to-action framework to establish the evidentiary base of harm to consumers, operationalize policy solutions to mitigate harm through legislation, and generate political will to support action through legislation introduced in the Massachusetts legislature to restrict sales of weight-loss and muscle-building dietary supplements. The paper concludes with lessons learned from this unique policy translation effort for the prevention of disordered weight and shape control behaviors and offers recommendations for next steps for the field to advance research and practice for universal, macro-environmentally targeted prevention. Copyright © 2016 Elsevier Ltd. All rights reserved.

Aerospace Mechanisms Symposium (22nd) Held at Hampton, Virginia on 4-6 May 1988.

DTIC Science & Technology

1988-05-06

monitoring is accomplished by a pressure transducer located near the hole drilled through the vessel wall between seals. A lip is machined on the...are presented and a design example involving a machine tool metrology bench is given. Design goals included thousandfold strain attenuation in the...systems such as a metrology bench, etc. These bodies must be supported. Six degrees of freedom must be fixed, but if the base upon which they are

The media of sociology: tight or loose translations?

PubMed

Guggenheim, Michael

2015-06-01

Sociologists have increasingly come to recognize that the discipline has unduly privileged textual representations, but efforts to incorporate visual and other media are still only in their beginning. This paper develops an analysis of the ways objects of knowledge are translated into other media, in order to understand the visual practices of sociology and to point out unused possibilities. I argue that the discourse on visual sociology, by assuming that photographs are less objective than text, is based on an asymmetric media-determinism and on a misleading notion of objectivity. Instead, I suggest to analyse media with the concept of translations. I introduce several kinds of translations, most centrally the distinction between tight and loose ones. I show that many sciences, such as biology, focus on tight translations, using a variety of media and manipulating both research objects and representations. Sociology, in contrast, uses both tight and loose translations, but uses the latter only for texts. For visuals, sociology restricts itself to what I call 'the documentary': focusing on mechanical recording technologies without manipulating either the object of research or the representation. I conclude by discussing three rare examples of what is largely excluded in sociology: visual loose translations, visual tight translations based on non-mechanical recording technologies, and visual tight translations based on mechanical recording technologies that include the manipulation of both object and representation. © London School of Economics and Political Science 2015.

Automatic road sign detecion and classification based on support vector machines and HOG descriptos

NASA Astrophysics Data System (ADS)

Adam, A.; Ioannidis, C.

2014-05-01

This paper examines the detection and classification of road signs in color-images acquired by a low cost camera mounted on a moving vehicle. A new method for the detection and classification of road signs is proposed based on color based detection, in order to locate regions of interest. Then, a circular Hough transform is applied to complete detection taking advantage of the shape properties of the road signs. The regions of interest are finally represented using HOG descriptors and are fed into trained Support Vector Machines (SVMs) in order to be recognized. For the training procedure, a database with several training examples depicting Greek road sings has been developed. Many experiments have been conducted and are presented, to measure the efficiency of the proposed methodology especially under adverse weather conditions and poor illumination. For the experiments training datasets consisting of different number of examples were used and the results are presented, along with some possible extensions of this work.

Oligo kernels for datamining on biological sequences: a case study on prokaryotic translation initiation sites

PubMed Central

Meinicke, Peter; Tech, Maike; Morgenstern, Burkhard; Merkl, Rainer

2004-01-01

Background Kernel-based learning algorithms are among the most advanced machine learning methods and have been successfully applied to a variety of sequence classification tasks within the field of bioinformatics. Conventional kernels utilized so far do not provide an easy interpretation of the learnt representations in terms of positional and compositional variability of the underlying biological signals. Results We propose a kernel-based approach to datamining on biological sequences. With our method it is possible to model and analyze positional variability of oligomers of any length in a natural way. On one hand this is achieved by mapping the sequences to an intuitive but high-dimensional feature space, well-suited for interpretation of the learnt models. On the other hand, by means of the kernel trick we can provide a general learning algorithm for that high-dimensional representation because all required statistics can be computed without performing an explicit feature space mapping of the sequences. By introducing a kernel parameter that controls the degree of position-dependency, our feature space representation can be tailored to the characteristics of the biological problem at hand. A regularized learning scheme enables application even to biological problems for which only small sets of example sequences are available. Our approach includes a visualization method for transparent representation of characteristic sequence features. Thereby importance of features can be measured in terms of discriminative strength with respect to classification of the underlying sequences. To demonstrate and validate our concept on a biochemically well-defined case, we analyze E. coli translation initiation sites in order to show that we can find biologically relevant signals. For that case, our results clearly show that the Shine-Dalgarno sequence is the most important signal upstream a start codon. The variability in position and composition we found for that signal is in accordance with previous biological knowledge. We also find evidence for signals downstream of the start codon, previously introduced as transcriptional enhancers. These signals are mainly characterized by occurrences of adenine in a region of about 4 nucleotides next to the start codon. Conclusions We showed that the oligo kernel can provide a valuable tool for the analysis of relevant signals in biological sequences. In the case of translation initiation sites we could clearly deduce the most discriminative motifs and their positional variation from example sequences. Attractive features of our approach are its flexibility with respect to oligomer length and position conservation. By means of these two parameters oligo kernels can easily be adapted to different biological problems. PMID:15511290

Centre of mass determination based on an optical weighing machine using fiber Bragg gratings

NASA Astrophysics Data System (ADS)

Oliveira, Rui; Roriz, Paulo; Marques, Manuel B.; Frazão, Orlando

2015-09-01

The purpose of the present work was to construct a weighing machine based on fiber Bragg gratings (FBGs) for the location of the 2D coordinates of the center of gravity (COG) of objects with complex geometry and density distribution. The apparatus consisted of a rigid equilateral triangular platform mounted on three supports at its vertices, two of them having cantilevers instrumented with FBGs. As an example, two femur bone models, one with and one without a hip stem prosthesis, are used to discuss the changing of the COM caused by the implementation of the prosthesis.

Bidding-based autonomous process planning and scheduling

NASA Astrophysics Data System (ADS)

Gu, Peihua; Balasubramanian, Sivaram; Norrie, Douglas H.

1995-08-01

Improving productivity through computer integrated manufacturing systems (CIMS) and concurrent engineering requires that the islands of automation in an enterprise be completely integrated. The first step in this direction is to integrate design, process planning, and scheduling. This can be achieved through a bidding-based process planning approach. The product is represented in a STEP model with detailed design and administrative information including design specifications, batch size, and due dates. Upon arrival at the manufacturing facility, the product registered in the shop floor manager which is essentially a coordinating agent. The shop floor manager broadcasts the product's requirements to the machines. The shop contains autonomous machines that have knowledge about their functionality, capabilities, tooling, and schedule. Each machine has its own process planner and responds to the product's request in a different way that is consistent with its capabilities and capacities. When more than one machine offers certain process(es) for the same requirements, they enter into negotiation. Based on processing time, due date, and cost, one of the machines wins the contract. The successful machine updates its schedule and advises the product to request raw material for processing. The concept was implemented using a multi-agent system with the task decomposition and planning achieved through contract nets. The examples are included to illustrate the approach.

Sequence-invariant state machines

NASA Technical Reports Server (NTRS)

Whitaker, Sterling R.; Manjunath, Shamanna K.; Maki, Gary K.

1991-01-01

A synthesis method and an MOS VLSI architecture are presented to realize sequential circuits that have the ability to implement any state machine having N states and m inputs, regardless of the actual sequence specified in the flow table. The design method utilizes binary tree structured (BTS) logic to implement regular and dense circuits. The desired state sequence can be hardwired with power supply connections or can be dynamically reallocated if stored in a register. This allows programmable VLSI controllers to be designed with a compact size and performance approaching that of dedicated logic. Results of ICV implementations are reported and an example sequence-invariant state machine is contrasted with implementations based on traditional methods.

Simple Machines Curriculum. [Teachers' Manual.

ERIC Educational Resources Information Center

Anoka-Hennepin Independent School District No. 11, Coon Rapids, MN.

This manual provides suggestions for investigating simple machines and the teaching of certain basic concepts which pertain to them. Many of the lessons are designed to be used with the commercially available LEGO kits, in an effort to teach concepts in a way in which students must translate pictures shown in two dimension into three-dimensional…

Visible Machine Learning for Biomedicine.

PubMed

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.

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

PubMed

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.

Amplify scientific discovery with artificial intelligence

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gil, Yolanda; Greaves, Mark T.; Hendler, James

Computing innovations have fundamentally changed many aspects of scientific inquiry. For example, advances in robotics, high-end computing, networking, and databases now underlie much of what we do in science such as gene sequencing, general number crunching, sharing information between scientists, and analyzing large amounts of data. As computing has evolved at a rapid pace, so too has its impact in science, with the most recent computing innovations repeatedly being brought to bear to facilitate new forms of inquiry. Recently, advances in Artificial Intelligence (AI) have deeply penetrated many consumer sectors, including for example Apple’s Siri™ speech recognition system, real-time automatedmore » language translation services, and a new generation of self-driving cars and self-navigating drones. However, AI has yet to achieve comparable levels of penetration in scientific inquiry, despite its tremendous potential in aiding computers to help scientists tackle tasks that require scientific reasoning. We contend that advances in AI will transform the practice of science as we are increasingly able to effectively and jointly harness human and machine intelligence in the pursuit of major scientific challenges.« less

Translating knowledge: a framework for evidence-informed yoga programs in oncology.

PubMed

Wurz, Amanda J; Capozzi, Lauren C; Mackenzie, Michael J; Danhauer, Suzanne C; Culos-Reed, Nicole

2013-01-01

Empirical research suggests that yoga may positively influence the negative psychosocial and physical side effects associated with cancer and its treatment. The translation of these findings into sustainable, evidence-informed yoga programming for cancer survivors has lagged behind the research. This article provides (a) an overview of the yoga and cancer research, (b) a framework for successfully developing and delivering yoga to cancer populations, and (c) an example of a successful community-based program. The importance of continued research and knowledge translation efforts in the context of yoga and integrative oncology are highlighted.

Automatic selection of atomic fingerprints and reference configurations for machine-learning potentials

NASA Astrophysics Data System (ADS)

Imbalzano, Giulio; Anelli, Andrea; Giofré, Daniele; Klees, Sinja; Behler, Jörg; Ceriotti, Michele

2018-06-01

Machine learning of atomic-scale properties is revolutionizing molecular modeling, making it possible to evaluate inter-atomic potentials with first-principles accuracy, at a fraction of the costs. The accuracy, speed, and reliability of machine learning potentials, however, depend strongly on the way atomic configurations are represented, i.e., the choice of descriptors used as input for the machine learning method. The raw Cartesian coordinates are typically transformed in "fingerprints," or "symmetry functions," that are designed to encode, in addition to the structure, important properties of the potential energy surface like its invariances with respect to rotation, translation, and permutation of like atoms. Here we discuss automatic protocols to select a number of fingerprints out of a large pool of candidates, based on the correlations that are intrinsic to the training data. This procedure can greatly simplify the construction of neural network potentials that strike the best balance between accuracy and computational efficiency and has the potential to accelerate by orders of magnitude the evaluation of Gaussian approximation potentials based on the smooth overlap of atomic positions kernel. We present applications to the construction of neural network potentials for water and for an Al-Mg-Si alloy and to the prediction of the formation energies of small organic molecules using Gaussian process regression.

Retaining Critical Therapeutic Elements of Behavioral Interventions Translated For Delivery via the Internet: Recommendations and an Example Using Pain Coping Skills Training

PubMed Central

Porter, Laura S; Somers, Tamara J; McKee, Daphne C; Keefe, Francis J

2014-01-01

Evidence supporting the efficacy of behavioral interventions based on principles of cognitive behavioral therapies has spurred interest in translating these interventions for delivery via the Internet. However, the benefits of this dissemination method cannot be realized unless the translated interventions are as effective as possible. We describe a challenge that must be overcome to ensure this occurs—Internet interventions must retain therapeutic components and processes underlying the success of face-to-face interventions on which they are based. These components and processes vary in the ease with which they can be translated to the online environment. Moreover, some are subtle and may be overlooked, despite being recognized as essential to the success of face-to-face interventions. We provide preliminary guidance for retaining critical therapeutic components and processes in the translation process, using Pain Coping Skills Training for osteoarthritis pain to illustrate methods. Directions for future research are also discussed. PMID:25532216

Community-Based Participatory Research Contributions to Intervention Research: The Intersection of Science and Practice to Improve Health Equity

PubMed Central

Duran, Bonnie

2010-01-01

Community-based participatory research (CBPR) has emerged in the last decades as a transformative research paradigm that bridges the gap between science and practice through community engagement and social action to increase health equity. CBPR expands the potential for the translational sciences to develop, implement, and disseminate effective interventions across diverse communities through strategies to redress power imbalances; facilitate mutual benefit among community and academic partners; and promote reciprocal knowledge translation, incorporating community theories into the research. We identify the barriers and challenges within the intervention and implementation sciences, discuss how CBPR can address these challenges, provide an illustrative research example, and discuss next steps to advance the translational science of CBPR. PMID:20147663

Blind Cyclostationary Feature Detection Based Spectrum Sensing for Autonomous Self-Learning Cognitive Radios

DTIC Science & Technology

2012-06-01

communication policies. Given the importance of machine learning and reconfig- urable hardware in the design of the Radiobots [1], we propose, in this paper, a...liter- ature, including, for example, the model in [9] which uses support vector machines (SVM’s). In this paper, however, we employ non-parametric...Communication Technology (ICACT ’08), vol. 1, Gangwon-Do, South Korea, Feb. 2008, pp. 481 – 485. [9] M. Ramon, T. Atwood , S. Barbin, and C

Automatic vetting of planet candidates from ground based surveys: Machine learning with NGTS

NASA Astrophysics Data System (ADS)

Armstrong, David J.; Günther, Maximilian N.; McCormac, James; Smith, Alexis M. S.; Bayliss, Daniel; Bouchy, François; Burleigh, Matthew R.; Casewell, Sarah; Eigmüller, Philipp; Gillen, Edward; Goad, Michael R.; Hodgkin, Simon T.; Jenkins, James S.; Louden, Tom; Metrailler, Lionel; Pollacco, Don; Poppenhaeger, Katja; Queloz, Didier; Raynard, Liam; Rauer, Heike; Udry, Stéphane; Walker, Simon R.; Watson, Christopher A.; West, Richard G.; Wheatley, Peter J.

2018-05-01

State of the art exoplanet transit surveys are producing ever increasing quantities of data. To make the best use of this resource, in detecting interesting planetary systems or in determining accurate planetary population statistics, requires new automated methods. Here we describe a machine learning algorithm that forms an integral part of the pipeline for the NGTS transit survey, demonstrating the efficacy of machine learning in selecting planetary candidates from multi-night ground based survey data. Our method uses a combination of random forests and self-organising-maps to rank planetary candidates, achieving an AUC score of 97.6% in ranking 12368 injected planets against 27496 false positives in the NGTS data. We build on past examples by using injected transit signals to form a training set, a necessary development for applying similar methods to upcoming surveys. We also make the autovet code used to implement the algorithm publicly accessible. autovet is designed to perform machine learned vetting of planetary candidates, and can utilise a variety of methods. The apparent robustness of machine learning techniques, whether on space-based or the qualitatively different ground-based data, highlights their importance to future surveys such as TESS and PLATO and the need to better understand their advantages and pitfalls in an exoplanetary context.

Evaluating the translation process of an Internet-based self-help intervention for prevention of depression: a cost-effectiveness analysis.

PubMed

Lintvedt, Ove K; Griffiths, Kathleen M; Eisemann, Martin; Waterloo, Knut

2013-01-23

Depression is common and treatable with cognitive behavior therapy (CBT), for example. However, access to this therapy is limited. Internet-based interventions have been found to be effective in reducing symptoms of depression. The International Society for Research on Internet Interventions has highlighted the importance of translating effective Internet programs into multiple languages to enable worldwide dissemination. The aim of the current study was to determine if it would be cost effective to translate an existing English-language Internet-based intervention for use in a non-English-speaking country. This paper reports an evaluation of a trial in which a research group in Norway translated two English-language Internet-based interventions into Norwegian (MoodGYM and BluePages) that had previously been shown to reduce symptoms of depression. The translation process and estimates of the cost-effectiveness of such a translation process is described. Estimated health effect was found by using quality-adjusted life years (QALY). Conservative estimates indicate that for every 1000 persons treated, 16 QALYs are gained. The investment is returned 9 times and the cost-effectiveness ratio (CER) is 3432. The costs of the translation project totaled to approximately 27% of the estimated original English-language version development costs. The economic analysis shows that the cost-effectiveness of the translation project was substantial. Hopefully, these results will encourage others to do similar analyses and report cost-effectiveness data in their research reports.

Evaluating the Translation Process of an Internet-Based Self-Help Intervention for Prevention of Depression: A Cost-Effectiveness Analysis

PubMed Central

2013-01-01

Background Depression is common and treatable with cognitive behavior therapy (CBT), for example. However, access to this therapy is limited. Internet-based interventions have been found to be effective in reducing symptoms of depression. The International Society for Research on Internet Interventions has highlighted the importance of translating effective Internet programs into multiple languages to enable worldwide dissemination. Objective The aim of the current study was to determine if it would be cost effective to translate an existing English-language Internet-based intervention for use in a non-English-speaking country. Methods This paper reports an evaluation of a trial in which a research group in Norway translated two English-language Internet-based interventions into Norwegian (MoodGYM and BluePages) that had previously been shown to reduce symptoms of depression. The translation process and estimates of the cost-effectiveness of such a translation process is described. Estimated health effect was found by using quality-adjusted life years (QALY). Results Conservative estimates indicate that for every 1000 persons treated, 16 QALYs are gained. The investment is returned 9 times and the cost-effectiveness ratio (CER) is 3432. The costs of the translation project totaled to approximately 27% of the estimated original English-language version development costs. Conclusions The economic analysis shows that the cost-effectiveness of the translation project was substantial. Hopefully, these results will encourage others to do similar analyses and report cost-effectiveness data in their research reports. PMID:23343481

Applications of Machine Learning for Radiation Therapy.

PubMed

Arimura, Hidetaka; Nakamoto, Takahiro

2016-01-01

Radiation therapy has been highly advanced as image guided radiation therapy (IGRT) by making advantage of image engineering technologies. Recently, novel frameworks based on image engineering technologies as well as machine learning technologies have been studied for sophisticating the radiation therapy. In this review paper, the author introduces several researches of applications of machine learning for radiation therapy. For examples, a method to determine the threshold values for standardized uptake value (SUV) for estimation of gross tumor volume (GTV) in positron emission tomography (PET) images, an approach to estimate the multileaf collimator (MLC) position errors between treatment plans and radiation delivery time, and prediction frameworks for esophageal stenosis and radiation pneumonitis risk after radiation therapy are described. Finally, the author introduces seven issues that one should consider when applying machine learning models to radiation therapy.

TargetMiner: microRNA target prediction with systematic identification of tissue-specific negative examples.

PubMed

Bandyopadhyay, Sanghamitra; Mitra, Ramkrishna

2009-10-15

Prediction of microRNA (miRNA) target mRNAs using machine learning approaches is an important area of research. However, most of the methods suffer from either high false positive or false negative rates. One reason for this is the marked deficiency of negative examples or miRNA non-target pairs. Systematic identification of non-target mRNAs is still not addressed properly, and therefore, current machine learning approaches are compelled to rely on artificially generated negative examples for training. In this article, we have identified approximately 300 tissue-specific negative examples using a novel approach that involves expression profiling of both miRNAs and mRNAs, miRNA-mRNA structural interactions and seed-site conservation. The newly generated negative examples are validated with pSILAC dataset, which elucidate the fact that the identified non-targets are indeed non-targets.These high-throughput tissue-specific negative examples and a set of experimentally verified positive examples are then used to build a system called TargetMiner, a support vector machine (SVM)-based classifier. In addition to assessing the prediction accuracy on cross-validation experiments, TargetMiner has been validated with a completely independent experimental test dataset. Our method outperforms 10 existing target prediction algorithms and provides a good balance between sensitivity and specificity that is not reflected in the existing methods. We achieve a significantly higher sensitivity and specificity of 69% and 67.8% based on a pool of 90 feature set and 76.5% and 66.1% using a set of 30 selected feature set on the completely independent test dataset. In order to establish the effectiveness of the systematically generated negative examples, the SVM is trained using a different set of negative data generated using the method in Yousef et al. A significantly higher false positive rate (70.6%) is observed when tested on the independent set, while all other factors are kept the same. Again, when an existing method (NBmiRTar) is executed with the our proposed negative data, we observe an improvement in its performance. These clearly establish the effectiveness of the proposed approach of selecting the negative examples systematically. TargetMiner is now available as an online tool at www.isical.ac.in/ approximately bioinfo_miu

Inter-species pathway perturbation prediction via data-driven detection of functional homology.

PubMed

Hafemeister, Christoph; Romero, Roberto; Bilal, Erhan; Meyer, Pablo; Norel, Raquel; Rhrissorrakrai, Kahn; Bonneau, Richard; Tarca, Adi L

2015-02-15

Experiments in animal models are often conducted to infer how humans will respond to stimuli by assuming that the same biological pathways will be affected in both organisms. The limitations of this assumption were tested in the IMPROVER Species Translation Challenge, where 52 stimuli were applied to both human and rat cells and perturbed pathways were identified. In the Inter-species Pathway Perturbation Prediction sub-challenge, multiple teams proposed methods to use rat transcription data from 26 stimuli to predict human gene set and pathway activity under the same perturbations. Submissions were evaluated using three performance metrics on data from the remaining 26 stimuli. We present two approaches, ranked second in this challenge, that do not rely on sequence-based orthology between rat and human genes to translate pathway perturbation state but instead identify transcriptional response orthologs across a set of training conditions. The translation from rat to human accomplished by these so-called direct methods is not dependent on the particular analysis method used to identify perturbed gene sets. In contrast, machine learning-based methods require performing a pathway analysis initially and then mapping the pathway activity between organisms. Unlike most machine learning approaches, direct methods can be used to predict the activation of a human pathway for a new (test) stimuli, even when that pathway was never activated by a training stimuli. Gene expression data are available from ArrayExpress (accession E-MTAB-2091), while software implementations are available from http://bioinformaticsprb.med.wayne.edu?p=50 and http://goo.gl/hJny3h. christoph.hafemeister@nyu.edu or atarca@med.wayne.edu. Supplementary data are available at Bioinformatics online. Published by Oxford University Press 2014. This work is written by US Government employees and is in the public domain in the US.

Organic bioelectronics for electronic-to-chemical translation in modulation of neuronal signaling and machine-to-brain interfacing.

PubMed

Larsson, Karin C; Kjäll, Peter; Richter-Dahlfors, Agneta

2013-09-01

A major challenge when creating interfaces for the nervous system is to translate between the signal carriers of the nervous system (ions and neurotransmitters) and those of conventional electronics (electrons). Organic conjugated polymers represent a unique class of materials that utilizes both electrons and ions as charge carriers. Based on these materials, we have established a series of novel communication interfaces between electronic components and biological systems. The organic electronic ion pump (OEIP) presented in this review is made of the polymer-polyelectrolyte system poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS). The OEIP translates electronic signals into electrophoretic migration of ions and neurotransmitters. We demonstrate how spatio-temporally controlled delivery of ions and neurotransmitters can be used to modulate intracellular Ca(2+) signaling in neuronal cells in the absence of convective disturbances. The electronic control of delivery enables strict control of dynamic parameters, such as amplitude and frequency of Ca(2+) responses, and can be used to generate temporal patterns mimicking naturally occurring Ca(2+) oscillations. To enable further control of the ionic signals we developed the electrophoretic chemical transistor, an analog of the traditional transistor used to amplify and/or switch electronic signals. Finally, we demonstrate the use of the OEIP in a new "machine-to-brain" interface by modulating brainstem responses in vivo. This review highlights the potential of communication interfaces based on conjugated polymers in generating complex, high-resolution, signal patterns to control cell physiology. We foresee widespread applications for these devices in biomedical research and in future medical devices within multiple therapeutic areas. This article is part of a Special Issue entitled Organic Bioelectronics-Novel Applications in Biomedicine. Copyright © 2012 Elsevier B.V. All rights reserved.

Getting America Ready for Japanese Science and Technology Held at Washington, DC on 7-8 February 1985.

DTIC Science & Technology

1985-05-15

TRANSLATION: A LONG-TERM SOLUTION MACHINE TRANSLATIONS: DEVELOPMENTS AND PROSPECTS 96 Robert A. Russell, Assistant Professor, Department of Asian and...chairman of the board of WCC, Chicago. He is a member of the Japanese National Automatic Translation Telephone Development Committee. 1 ROBERT A. RUSSELL...redussol- Westerism through indexing enineiring student to trai- speaking M Ono"e langisage. 067 pubfiahang-some in services. said Robert W. Gib- law

PredPsych: A toolbox for predictive machine learning-based approach in experimental psychology research.

PubMed

Koul, Atesh; Becchio, Cristina; Cavallo, Andrea

2017-12-12

Recent years have seen an increased interest in machine learning-based predictive methods for analyzing quantitative behavioral data in experimental psychology. While these methods can achieve relatively greater sensitivity compared to conventional univariate techniques, they still lack an established and accessible implementation. The aim of current work was to build an open-source R toolbox - "PredPsych" - that could make these methods readily available to all psychologists. PredPsych is a user-friendly, R toolbox based on machine-learning predictive algorithms. In this paper, we present the framework of PredPsych via the analysis of a recently published multiple-subject motion capture dataset. In addition, we discuss examples of possible research questions that can be addressed with the machine-learning algorithms implemented in PredPsych and cannot be easily addressed with univariate statistical analysis. We anticipate that PredPsych will be of use to researchers with limited programming experience not only in the field of psychology, but also in that of clinical neuroscience, enabling computational assessment of putative bio-behavioral markers for both prognosis and diagnosis.

Bombsights and Adding Machines: Translating Wartime Technology into Peacetime Sales

ERIC Educational Resources Information Center

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…

AstroML: Python-powered Machine Learning for Astronomy

NASA Astrophysics Data System (ADS)

Vander Plas, Jake; Connolly, A. J.; Ivezic, Z.

2014-01-01

As astronomical data sets grow in size and complexity, automated machine learning and data mining methods are becoming an increasingly fundamental component of research in the field. The astroML project (http://astroML.org) provides a common repository for practical examples of the data mining and machine learning tools used and developed by astronomical researchers, written in Python. The astroML module contains a host of general-purpose data analysis and machine learning routines, loaders for openly-available astronomical datasets, and fast implementations of specific computational methods often used in astronomy and astrophysics. The associated website features hundreds of examples of these routines being used for analysis of real astronomical datasets, while the associated textbook provides a curriculum resource for graduate-level courses focusing on practical statistics, machine learning, and data mining approaches within Astronomical research. This poster will highlight several of the more powerful and unique examples of analysis performed with astroML, all of which can be reproduced in their entirety on any computer with the proper packages installed.

The measurement of an aspherical mirror by three-dimensional nanoprofiler

NASA Astrophysics Data System (ADS)

Tokuta, Yusuke; Okita, Kenya; Okuda, Kohei; Kitayama, Takao; Nakano, Motohiro; Nakatani, Shun; Kudo, Ryota; Yamamura, Kazuya; Endo, Katsuyoshi

2015-09-01

Aspherical optical elements with high accuracy are important in several fields such as third-generation synchrotron radiation and extreme-ultraviolet lithography. Then the demand of measurement method for aspherical or free-form surface with nanometer resolution is rising. Our purpose is to develop a non-contact profiler to measure free-form surfaces directly with repeatability of figure error of less than 1 nm PV. To achieve this purpose we have developed three-dimensional Nanoprofiler which traces normal vectors of sample surface. The measurement principle is based on the straightness of LASER light and the accuracy of a rotational goniometer. This machine consists of four rotational stages, one translational stage and optical head which has the quadrant photodiode (QPD) and LASER head at optically equal position. In this measurement method, we conform the incident light beam to reflect the beam by controlling five stages and determine the normal vectors and the coordinates of the surface from signal of goniometers, translational stage and QPD. We can obtain three-dimensional figure from the normal vectors and the coordinates by a reconstruction algorithm. To evaluate performance of this machine we measure a concave aspherical mirror ten times. From ten results we calculate measurement repeatability, and we evaluate measurement uncertainty to compare the result with that measured by an interferometer. In consequence, the repeatability of measurement was 2.90 nm (σ) and the difference between the two profiles was +/-20 nm. We conclude that the two profiles was correspondent considering systematic errors of each machine.

Sign Language Translator Application Using OpenCV

NASA Astrophysics Data System (ADS)

Triyono, L.; Pratisto, E. H.; Bawono, S. A. T.; Purnomo, F. A.; Yudhanto, Y.; Raharjo, B.

2018-03-01

This research focuses on the development of sign language translator application using OpenCV Android based, this application is based on the difference in color. The author also utilizes Support Machine Learning to predict the label. Results of the research showed that the coordinates of the fingertip search methods can be used to recognize a hand gesture to the conditions contained open arms while to figure gesture with the hand clenched using search methods Hu Moments value. Fingertip methods more resilient in gesture recognition with a higher success rate is 95% on the distance variation is 35 cm and 55 cm and variations of light intensity of approximately 90 lux and 100 lux and light green background plain condition compared with the Hu Moments method with the same parameters and the percentage of success of 40%. While the background of outdoor environment applications still can not be used with a success rate of only 6 managed and the rest failed.

Algorithm for real-time detection of signal patterns using phase synchrony: an application to an electrode array

NASA Astrophysics Data System (ADS)

Sadeghi, Saman; MacKay, William A.; van Dam, R. Michael; Thompson, Michael

2011-02-01

Real-time analysis of multi-channel spatio-temporal sensor data presents a considerable technical challenge for a number of applications. For example, in brain-computer interfaces, signal patterns originating on a time-dependent basis from an array of electrodes on the scalp (i.e. electroencephalography) must be analyzed in real time to recognize mental states and translate these to commands which control operations in a machine. In this paper we describe a new technique for recognition of spatio-temporal patterns based on performing online discrimination of time-resolved events through the use of correlation of phase dynamics between various channels in a multi-channel system. The algorithm extracts unique sensor signature patterns associated with each event during a training period and ranks importance of sensor pairs in order to distinguish between time-resolved stimuli to which the system may be exposed during real-time operation. We apply the algorithm to electroencephalographic signals obtained from subjects tested in the neurophysiology laboratories at the University of Toronto. The extension of this algorithm for rapid detection of patterns in other sensing applications, including chemical identification via chemical or bio-chemical sensor arrays, is also discussed.

Identifying translational science within the triangle of biomedicine.

PubMed

Weber, Griffin M

2013-05-24

The National Institutes of Health (NIH) Roadmap places special emphasis on "bench-to-bedside" research, or the "translation" of basic science research into practical clinical applications. The Clinical and Translational Science Awards (CTSA) Consortium is one example of the large investments being made to develop a national infrastructure to support translational science, which involves reducing regulatory burdens, launching new educational initiatives, and forming partnerships between academia and industry. However, while numerous definitions have been suggested for translational science, including the qualitative T1-T4 classification, a consensus has not yet been reached. This makes it challenging to tract the impact of these major policy changes. In this study, we use a bibliometric approach to map PubMed articles onto a graph, called the Triangle of Biomedicine. The corners of the triangle represent research related to animals, cells and molecules, and humans; and, the position of a publication on the graph is based on its topics, as determined by its Medical Subject Headings (MeSH). We define translation as movement of a collection of articles, or the articles that cite those articles, towards the human corner. The Triangle of Biomedicine provides a quantitative way of determining if an individual scientist, research organization, funding agency, or scientific field is producing results that are relevant to clinical medicine. We validate our technique using examples that have been previously described in the literature and by comparing it to prior methods of measuring translational science. The Triangle of Biomedicine is a novel way to identify translational science and track changes over time. This is important to policy makers in evaluating the impact of the large investments being made to accelerate translation. The Triangle of Biomedicine also provides a simple visual way of depicting this impact, which can be far more powerful than numbers alone.

Actes des Journees de Linguistique (Proceedings of the Linguistics Conference) (11th, Quebec, Canada, March 20-21, 1997).

ERIC Educational Resources Information Center

Caouette, Claudine, Ed.; Larrivee, Pierre, Ed.

English translations of articles in French in this issue include these: "Discourse Reported in the Print Media"; "Comparison of Register in Quebec and French Speakers"; "Method of Description of Specialized Verbs in View of Machine Translation Applications"; "Dialectal Areas in the Brazilian State of Rio Grande…

The Circle of Meaning: From Translation to Paraphrasing and Back

ERIC Educational Resources Information Center

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…

CPU Performance Counter-Based Problem Diagnosis for Software Systems

DTIC Science & Technology

2009-09-01

application servers and implementation techniques), this thesis only used the Enterprise Java Bean (EJB) SessionBean version of RUBiS. The PHP and Servlet ...collection statistics at the Java Virtual Machine (JVM) level can be reused for any Java application. Other examples of gray-box instrumentation include path...used gray-box approaches. For example, PinPoint [11, 14] and [29] use request tracing to diagnose Java exceptions, endless calls, and null calls in

Ultra-Compact Transputer-Based Controller for High-Level, Multi-Axis Coordination

NASA Technical Reports Server (NTRS)

Zenowich, Brian; Crowell, Adam; Townsend, William T.

2013-01-01

The design of machines that rely on arrays of servomotors such as robotic arms, orbital platforms, and combinations of both, imposes a heavy computational burden to coordinate their actions to perform coherent tasks. For example, the robotic equivalent of a person tracing a straight line in space requires enormously complex kinematics calculations, and complexity increases with the number of servo nodes. A new high-level architecture for coordinated servo-machine control enables a practical, distributed transputer alternative to conventional central processor electronics. The solution is inherently scalable, dramatically reduces bulkiness and number of conductor runs throughout the machine, requires only a fraction of the power, and is designed for cooling in a vacuum.

Translation of scales in cross-cultural research: issues and techniques.

PubMed

Cha, Eun-Seok; Kim, Kevin H; Erlen, Judith A

2007-05-01

This paper is a report of a study designed to: (i) describe issues and techniques of translation of standard measures for use in international research; (ii) identify a user-friendly and valid translation method when researchers have limited resources during translation procedure; and (iii) discuss translation issues using data from a pilot study as an example. The process of translation is an important part of cross-cultural studies. Cross-cultural researchers are often confronted by the need to translate scales from one language to another and to do this with limited resources. The lessons learned from our experience in a pilot study are presented to underline the importance of using appropriate translation procedures. The issues of the back-translation method are discussed to identify strategies to ensure success when translating measures. A combined technique is an appropriate method to maintain the content equivalences between the original and translated instruments in international research. There are several possible combinations of translation techniques. However, there is no gold standard of translation techniques because the research environment (e.g. accessibility and availability of bilingual people) and the research questions are different. It is important to use appropriate translation procedures and to employ a combined translation technique based on the research environment and questions.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vanchurin, Vitaly, E-mail: vvanchur@d.umn.edu

We initiate a formal study of logical inferences in context of the measure problem in cosmology or what we call cosmic logic. We describe a simple computational model of cosmic logic suitable for analysis of, for example, discretized cosmological systems. The construction is based on a particular model of computation, developed by Alan Turing, with cosmic observers (CO), cosmic measures (CM) and cosmic symmetries (CS) described by Turing machines. CO machines always start with a blank tape and CM machines take CO's Turing number (also known as description number or Gödel number) as input and output the corresponding probability. Similarly,more » CS machines take CO's Turing number as input, but output either one if the CO machines are in the same equivalence class or zero otherwise. We argue that CS machines are more fundamental than CM machines and, thus, should be used as building blocks in constructing CM machines. We prove the non-computability of a CS machine which discriminates between two classes of CO machines: mortal that halts in finite time and immortal that runs forever. In context of eternal inflation this result implies that it is impossible to construct CM machines to compute probabilities on the set of all CO machines using cut-off prescriptions. The cut-off measures can still be used if the set is reduced to include only machines which halt after a finite and predetermined number of steps.« less

Cosmic logic: a computational model

NASA Astrophysics Data System (ADS)

Vanchurin, Vitaly

2016-02-01

We initiate a formal study of logical inferences in context of the measure problem in cosmology or what we call cosmic logic. We describe a simple computational model of cosmic logic suitable for analysis of, for example, discretized cosmological systems. The construction is based on a particular model of computation, developed by Alan Turing, with cosmic observers (CO), cosmic measures (CM) and cosmic symmetries (CS) described by Turing machines. CO machines always start with a blank tape and CM machines take CO's Turing number (also known as description number or Gödel number) as input and output the corresponding probability. Similarly, CS machines take CO's Turing number as input, but output either one if the CO machines are in the same equivalence class or zero otherwise. We argue that CS machines are more fundamental than CM machines and, thus, should be used as building blocks in constructing CM machines. We prove the non-computability of a CS machine which discriminates between two classes of CO machines: mortal that halts in finite time and immortal that runs forever. In context of eternal inflation this result implies that it is impossible to construct CM machines to compute probabilities on the set of all CO machines using cut-off prescriptions. The cut-off measures can still be used if the set is reduced to include only machines which halt after a finite and predetermined number of steps.

Effect of Bayesian Student Modeling on Academic Achievement in Foreign Language Teaching (University Level English Preparatory School Example)

ERIC Educational Resources Information Center

Aslan, Burak Galip; Öztürk, Özlem; Inceoglu, Mustafa Murat

2014-01-01

Considering the increasing importance of adaptive approaches in CALL systems, this study implemented a machine learning based student modeling middleware with Bayesian networks. The profiling approach of the student modeling system is based on Felder and Silverman's Learning Styles Model and Felder and Soloman's Index of Learning Styles…

A Framework for Translating a High Level Security Policy into Low Level Security Mechanisms

NASA Astrophysics Data System (ADS)

Hassan, Ahmed A.; Bahgat, Waleed M.

2010-01-01

Security policies have different components; firewall, active directory, and IDS are some examples of these components. Enforcement of network security policies to low level security mechanisms faces some essential difficulties. Consistency, verification, and maintenance are the major ones of these difficulties. One approach to overcome these difficulties is to automate the process of translation of high level security policy into low level security mechanisms. This paper introduces a framework of an automation process that translates a high level security policy into low level security mechanisms. The framework is described in terms of three phases; in the first phase all network assets are categorized according to their roles in the network security and relations between them are identified to constitute the network security model. This proposed model is based on organization based access control (OrBAC). However, the proposed model extend the OrBAC model to include not only access control policy but also some other administrative security policies like auditing policy. Besides, the proposed model enables matching of each rule of the high level security policy with the corresponding ones of the low level security policy. Through the second phase of the proposed framework, the high level security policy is mapped into the network security model. The second phase could be considered as a translation of the high level security policy into an intermediate model level. Finally, the intermediate model level is translated automatically into low level security mechanism. The paper illustrates the applicability of proposed approach through an application example.

Translations from Kommunist, Number 13, September 1978

DTIC Science & Technology

1978-10-30

programmed machine tool here is merely a component of a more complex reprogrammable technological system. This includes the robot machine tools with...sufficient possibilities for changing technological operations and processes and automated technological lines. 52 The reprogrammable automated sets will...simulate the possibilities of such sets. A new technological level will be developed in industry related to reprogrammable automated sets, their design

Public-private partnerships in translational medicine: concepts and practical examples.

PubMed

Luijten, Peter R; van Dongen, Guus A M S; Moonen, Chrit T; Storm, Gert; Crommelin, Daan J A

2012-07-20

The way forward in multidisciplinary research according to former NIH's director Elias Zerhouni is to engage in predictive, personalized, preemptive and participatory medicine. For the creation of the optimal innovation climate that would allow for such a strategy, public-private partnerships have been widely proposed as an important instrument. Public-private partnerships have become an important instrument to expedite translational research in medicine. The Netherlands have initiated three large public-private partnerships in the life sciences and health area to facilitate the translation of valuable basic scientific concepts to new products and services in medicine. The focus of these partnerships has been on drug development, improved diagnosis and regenerative medicine. The Dutch model of public-private partnership forms the blueprint of a much larger European initiative called EATRIS. This paper will provide practical examples of public-private partnerships initiated to expedite the translation of new technology for drug development towards the clinic. Three specific technologies are in focus: companion diagnostics using nuclear medicine, the use of ultra high field MRI to generate sensitive surrogate endpoints based on endogenous contrast, and MRI guidance for High Intensity Focused Ultrasound mediated drug delivery. Copyright © 2012 Elsevier B.V. All rights reserved.

Werbung im Englischunterricht: Das Beispiel Einhorn - Onehorn - Unicorn (Advertising Material in English Teaching: The Example "Einhorn-Onehorn-Unicorn")

ERIC Educational Resources Information Center

Ruettgens, Hannelore

1976-01-01

Presents an advertisement from "Der Spiegel," composed in English that is saturated with Germanisms. Teaching procedures based on this are suggested: finding and classifying errors, composing alternative versions, translating into German, retranslating into English. Suggestions are given for further work based on the students' own…

Insights into the movements of landslides from combinations of field monitoring and novel direct shear testing

NASA Astrophysics Data System (ADS)

Petley, D. N.; Carey, J.; Massey, C. I.; Brain, M.

2015-12-01

The mechanisms of pre- and post-failure movement of translational landslides remain surprisingly poorly investigated. Previous approaches have focussed on field monitoring, for example through high resolution automated surveying and/or GPS measurements, or from modelling using dedicated codes. There has been some experimental work too, most notably using ring shear devices, although there are limitations as to the type of analyses that can be completed in these devices. In recent years the author has been involved in a series of studies that have sought to understand pre- and post-failure behaviour in translational landslides using both high precision monitoring and experimental investigation using novel apparatus. The latter approach has involved the use of the back pressured shear box, a direct shear machine that allows near-infinite variation of the normal and shear stress state, and measurement and control of the pore water pressure. More recently, a more advanced version of this machine has been developed that allows dynamic loading of both direct and normal shear stresses. This paper presents key lessons learnt about the behaviour of translational landslides from these approaches. The data highlight a number of key elements: The important differences in pre-failure behaviour for materials that show a brittle response compared with those that are ductile. In particular, some aspects of behaviour (e.g. the hyperbolic acceleration to failure) can only be replicated in materials that show brittle cracking processes; In the post-failure domain, all materials show a high level of sensitivity to small changes in pore water pressure when the Factor of Safety is close to unity; Rates of strain are not simply related to pore water pressure / stress state. In particular, some materials show a different deformation response during phases of increasing pore water pressure to that during periods of pore water pressure reduction. The reasons for this require further study; Dynamic behaviour is complex, with variations in behaviour between different materials types being greater than expected. These results show that the behaviour of materials in the post-failure domain is more complex than had been appreciated previously, suggesting that more work is needed to explain landslide behaviour in this regime.

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

PubMed Central

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

Cultural adaptation of patient and observational outcome measures: a methodological example using the COMFORT behavioral rating scale.

PubMed

Andersen, Randi Dovland; Jylli, Leena; Ambuel, Bruce

2014-06-01

There is little empirical evidence regarding the translation and cultural adaptation of self-report and observational outcome measures. Studies that evaluate and further develop existing practices are needed. This study explores the use of cognitive interviews in the translation and cultural adaptation of observational measures, using the COMFORT behavioral scale as an example, and demonstrates a structured approach to the analysis of data from cognitive interviews. The COMFORT behavioral scale is developed for assessment of distress and pain in a pediatric intensive care setting. Qualitative, descriptive methodological study. One general public hospital trust in southern Norway. N=12. Eight nurses, three physicians and one nurse assistant, from different wards and with experience caring for children. We translated the COMFORT behavior scale into Norwegian before conducting individual cognitive interviews. Participants first read and then used the translated version of the COMFORT behavioral scale to assess pain based on a 3-min film vignette depicting an infant in pain/distress. Two cognitive interview techniques were applied: Thinking Aloud (TA) during the assessment and Verbal Probing (VP) afterwards. In TA the participant verbalized his/her thought process while completing the COMFORT behavioral scale. During VP the participant responded to specific questions related to understanding of the measure, information recall and the decision process. We audio recorded, transcribed and analyzed interviews using a structured qualitative method (cross-case analysis based on predefined categories and development of a results matrix). Our analysis revealed two categories of problems: (1) Scale problems, warranting a change in the wording of the scale, including (a) translation errors, (b) content not understood as intended, and (c) differences between the original COMFORT scale and the revised COMFORT behavioral scale; and (2) Rater-context problems caused by (a) unfamiliarity with the scale, (b) lack of knowledge and experience, and (c) assessments based on a film vignette. Cognitive interviews revealed problems with both the translated and the original versions of the scale and suggested solutions that enhanced the validity of both versions. Cognitive interviews might be seen as a complement to current published best practices for translation and cultural adaptation. Copyright © 2013 Elsevier Ltd. All rights reserved.

26 CFR 1.48-2 - New section 38 property.

Code of Federal Regulations, 2012 CFR

2012-04-01

... of property, the adjusted basis of the reconstructed property as of the time such reconstruction is... machine acquired by the taxpayer will not be treated as being put to original use by the taxpayer. The... following examples: Example 1. If a machine with a total cost of $100,000 is completed after December 31...

26 CFR 1.48-2 - New section 38 property.

Code of Federal Regulations, 2013 CFR

2013-04-01

... of property, the adjusted basis of the reconstructed property as of the time such reconstruction is... machine acquired by the taxpayer will not be treated as being put to original use by the taxpayer. The... following examples: Example 1. If a machine with a total cost of $100,000 is completed after December 31...

26 CFR 1.48-2 - New section 38 property.

Code of Federal Regulations, 2011 CFR

2011-04-01

... of property, the adjusted basis of the reconstructed property as of the time such reconstruction is... machine acquired by the taxpayer will not be treated as being put to original use by the taxpayer. The... following examples: Example 1. If a machine with a total cost of $100,000 is completed after December 31...

26 CFR 1.48-2 - New section 38 property.

Code of Federal Regulations, 2014 CFR

2014-04-01

... of property, the adjusted basis of the reconstructed property as of the time such reconstruction is... machine acquired by the taxpayer will not be treated as being put to original use by the taxpayer. The... following examples: Example 1. If a machine with a total cost of $100,000 is completed after December 31...

Automated Verification of Specifications with Typestates and Access Permissions

NASA Technical Reports Server (NTRS)

Siminiceanu, Radu I.; Catano, Nestor

2011-01-01

We propose an approach to formally verify Plural specifications based on access permissions and typestates, by model-checking automatically generated abstract state-machines. Our exhaustive approach captures all the possible behaviors of abstract concurrent programs implementing the specification. We describe the formal methodology employed by our technique and provide an example as proof of concept for the state-machine construction rules. The implementation of a fully automated algorithm to generate and verify models, currently underway, provides model checking support for the Plural tool, which currently supports only program verification via data flow analysis (DFA).

Machine learning with naturally labeled data for identifying abbreviation definitions.

PubMed

Yeganova, Lana; Comeau, Donald C; Wilbur, W John

2011-06-09

The rapid growth of biomedical literature requires accurate text analysis and text processing tools. Detecting abbreviations and identifying their definitions is an important component of such tools. Most existing approaches for the abbreviation definition identification task employ rule-based methods. While achieving high precision, rule-based methods are limited to the rules defined and fail to capture many uncommon definition patterns. Supervised learning techniques, which offer more flexibility in detecting abbreviation definitions, have also been applied to the problem. However, they require manually labeled training data. In this work, we develop a machine learning algorithm for abbreviation definition identification in text which makes use of what we term naturally labeled data. Positive training examples are naturally occurring potential abbreviation-definition pairs in text. Negative training examples are generated by randomly mixing potential abbreviations with unrelated potential definitions. The machine learner is trained to distinguish between these two sets of examples. Then, the learned feature weights are used to identify the abbreviation full form. This approach does not require manually labeled training data. We evaluate the performance of our algorithm on the Ab3P, BIOADI and Medstract corpora. Our system demonstrated results that compare favourably to the existing Ab3P and BIOADI systems. We achieve an F-measure of 91.36% on Ab3P corpus, and an F-measure of 87.13% on BIOADI corpus which are superior to the results reported by Ab3P and BIOADI systems. Moreover, we outperform these systems in terms of recall, which is one of our goals.

Coordinating Council. Second Meeting: International Acquisitions

NASA Technical Reports Server (NTRS)

1990-01-01

The theme of this NASA Scientific and Technical Information Program Coordinating Council was International Acquisitions. Included are both visuals for presentations and reports on discussions related to the topics. Presentations were made on the following topics: Coordination council organization international plan, STI global network, International aerospace climate, Foreign exchange program, Foreign activities RMS & AIAA, NASA translation program, A.F. machine translation system, and CIRC cooperation.

Reading Strategies in a L2: A Study on Machine Translation

ERIC Educational Resources Information Center

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…

Recent advance in DNA-based traceability and authentication of livestock meat PDO and PGI products.

PubMed

Nicoloso, Letizia; Crepaldi, Paola; Mazza, Raffaele; Ajmone-Marsan, Paolo; Negrini, Riccardo

2013-04-01

This review updates the available molecular techniques and technologies and discusses how they can be used for traceability, food control and enforcement activities. The review also provides examples on how molecular techniques succeeded to trace back unknowns to their breeds of origin, to fingerprint single individuals and to generate evidence in court cases. The examples demonstrate the potential of the DNA based traceability techniques and explore possibilities for translating the next generation genomics tools into a food and feed control and enforcement framework.

Performance analysis of a new radial-axial flux machine with SMC cores and ferrite magnets

NASA Astrophysics Data System (ADS)

Liu, Chengcheng; Wang, Youhua; Lei, Gang; Guo, Youguang; Zhu, Jianguo

2017-05-01

Soft magnetic composite (SMC) is a popular material in designing of new 3D flux electrical machines nowadays for it has the merits of isotropic magnetic characteristic, low eddy current loss and high design flexibility over the electric steel. The axial flux machine (AFM) with the extended stator tooth tip both in the radial and circumferential direction is a good example, which has been investigated in the last years. Based on the 3D flux AFM and radial flux machine, this paper proposes a new radial-axial flux machine (RAFM) with SMC cores and ferrite magnets, which has very high torque density though the low cost low magnetic energy ferrite magnet is utilized. Moreover, the cost of RAFM is quite low since the manufacturing cost can be reduced by using the SMC cores and the material cost will be decreased due to the adoption of the ferrite magnets. The 3D finite element method (FEM) is used to calculate the magnetic flux density distribution and electromagnetic parameters. For the core loss calculation, the rotational core loss computation method is used based on the experiment results from previous 3D magnetic tester.

Research on criticality analysis method of CNC machine tools components under fault rate correlation

NASA Astrophysics Data System (ADS)

Gui-xiang, Shen; Xian-zhuo, Zhao; Zhang, Ying-zhi; Chen-yu, Han

2018-02-01

In order to determine the key components of CNC machine tools under fault rate correlation, a system component criticality analysis method is proposed. Based on the fault mechanism analysis, the component fault relation is determined, and the adjacency matrix is introduced to describe it. Then, the fault structure relation is hierarchical by using the interpretive structure model (ISM). Assuming that the impact of the fault obeys the Markov process, the fault association matrix is described and transformed, and the Pagerank algorithm is used to determine the relative influence values, combined component fault rate under time correlation can obtain comprehensive fault rate. Based on the fault mode frequency and fault influence, the criticality of the components under the fault rate correlation is determined, and the key components are determined to provide the correct basis for equationting the reliability assurance measures. Finally, taking machining centers as an example, the effectiveness of the method is verified.

Using Trained Pixel Classifiers to Select Images of Interest

NASA Technical Reports Server (NTRS)

Mazzoni, D.; Wagstaff, K.; Castano, R.

2004-01-01

We present a machine-learning-based approach to ranking images based on learned priorities. Unlike previous methods for image evaluation, which typically assess the value of each image based on the presence of predetermined specific features, this method involves using two levels of machine-learning classifiers: one level is used to classify each pixel as belonging to one of a group of rather generic classes, and another level is used to rank the images based on these pixel classifications, given some example rankings from a scientist as a guide. Initial results indicate that the technique works well, producing new rankings that match the scientist's rankings significantly better than would be expected by chance. The method is demonstrated for a set of images collected by a Mars field-test rover.

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

PubMed Central

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

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

PubMed

Kim, Yong-Ku; Na, Kyoung-Sae

2018-01-03

Mood disorders are a highly prevalent group of mental disorders causing substantial socioeconomic burden. There are various methodological approaches for identifying the underlying mechanisms of the etiology, symptomatology, and therapeutics of mood disorders; however, neuroimaging studies have provided the most direct evidence for mood disorder neural substrates by visualizing the brains of living individuals. The prefrontal cortex, hippocampus, amygdala, thalamus, ventral striatum, and corpus callosum are associated with depression and bipolar disorder. Identifying the distinct and common contributions of these anatomical regions to depression and bipolar disorder have broadened and deepened our understanding of mood disorders. However, the extent to which neuroimaging research findings contribute to clinical practice in the real-world setting is unclear. As traditional or non-machine learning MRI studies have analyzed group-level differences, it is not possible to directly translate findings from research to clinical practice; the knowledge gained pertains to the disorder, but not to individuals. On the other hand, a machine learning approach makes it possible to provide individual-level classifications. For the past two decades, many studies have reported on the classification accuracy of machine learning-based neuroimaging studies from the perspective of diagnosis and treatment response. However, for the application of a machine learning-based brain MRI approach in real world clinical settings, several major issues should be considered. Secondary changes due to illness duration and medication, clinical subtypes and heterogeneity, comorbidities, and cost-effectiveness restrict the generalization of the current machine learning findings. Sophisticated classification of clinical and diagnostic subtypes is needed. Additionally, as the approach is inevitably limited by sample size, multi-site participation and data-sharing are needed in the future. Copyright © 2017 Elsevier Inc. All rights reserved.

Big Data Toolsets to Pharmacometrics: Application of Machine Learning for Time-to-Event Analysis.

PubMed

Gong, Xiajing; Hu, Meng; Zhao, Liang

2018-05-01

Additional value can be potentially created by applying big data tools to address pharmacometric problems. The performances of machine learning (ML) methods and the Cox regression model were evaluated based on simulated time-to-event data synthesized under various preset scenarios, i.e., with linear vs. nonlinear and dependent vs. independent predictors in the proportional hazard function, or with high-dimensional data featured by a large number of predictor variables. Our results showed that ML-based methods outperformed the Cox model in prediction performance as assessed by concordance index and in identifying the preset influential variables for high-dimensional data. The prediction performances of ML-based methods are also less sensitive to data size and censoring rates than the Cox regression model. In conclusion, ML-based methods provide a powerful tool for time-to-event analysis, with a built-in capacity for high-dimensional data and better performance when the predictor variables assume nonlinear relationships in the hazard function. © 2018 The Authors. Clinical and Translational Science published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

Ultra-High Throughput Synthesis of Nanoparticles with Homogeneous Size Distribution Using a Coaxial Turbulent Jet Mixer

PubMed Central

2015-01-01

High-throughput production of nanoparticles (NPs) with controlled quality is critical for their clinical translation into effective nanomedicines for diagnostics and therapeutics. Here we report a simple and versatile coaxial turbulent jet mixer that can synthesize a variety of NPs at high throughput up to 3 kg/d, while maintaining the advantages of homogeneity, reproducibility, and tunability that are normally accessible only in specialized microscale mixing devices. The device fabrication does not require specialized machining and is easy to operate. As one example, we show reproducible, high-throughput formulation of siRNA-polyelectrolyte polyplex NPs that exhibit effective gene knockdown but exhibit significant dependence on batch size when formulated using conventional methods. The coaxial turbulent jet mixer can accelerate the development of nanomedicines by providing a robust and versatile platform for preparation of NPs at throughputs suitable for in vivo studies, clinical trials, and industrial-scale production. PMID:24824296

Kinematic support using elastic elements

NASA Technical Reports Server (NTRS)

Geirsson, Arni; Debra, Daniel B.

1988-01-01

The design of kinematic supports using elastic elements is reviewed. The two standard methods (cone, Vee and flat and three Vees) are presented and a design example involving a machine tool metrology bench is given. Design goals included thousandfold strain attenuation in the bench relative to the base when the base strains due to temperature variations and shifting loads. Space applications are also considered.

Flexible Endian Adjustment for Cross Architecture Binary Translation

NASA Astrophysics Data System (ADS)

Zhu, Tong; Liu, Bo; Guan, Haibing; Liang, Alei

Different architectures and/or ISA (Instruction Set Architecture) representations hold different data arranging formats in the memory. Therefore, the adjustment of byte packing order (endianness) is indispensable in cross- architecture binary translation if the source and target machines are of heterogeneous endianness, which may otherwise cause system failure. The issue is inconspicuous but may lead to significant performance bottleneck. This paper investigates the key aspects of endianness and finds several solutions to endian adjustment for cross-architecture binary translation. In particular, it considers the two principal methods of this field - byte swapping and address swizzling, and gives a comparison of them in our DBT (Dynamic Binary Translator) - CrossBit.

A Model-Free Machine Learning Method for Risk Classification and Survival Probability Prediction.

PubMed

Geng, Yuan; Lu, Wenbin; Zhang, Hao Helen

2014-01-01

Risk classification and survival probability prediction are two major goals in survival data analysis since they play an important role in patients' risk stratification, long-term diagnosis, and treatment selection. In this article, we propose a new model-free machine learning framework for risk classification and survival probability prediction based on weighted support vector machines. The new procedure does not require any specific parametric or semiparametric model assumption on data, and is therefore capable of capturing nonlinear covariate effects. We use numerous simulation examples to demonstrate finite sample performance of the proposed method under various settings. Applications to a glioma tumor data and a breast cancer gene expression survival data are shown to illustrate the new methodology in real data analysis.

Application of Quality Management Tools for Evaluating the Failure Frequency of Cutter-Loader and Plough Mining Systems

NASA Astrophysics Data System (ADS)

Biały, Witold

2017-06-01

Failure frequency in the mining process, with a focus on the mining machine, has been presented and illustrated by the example of two coal-mines. Two mining systems have been subjected to analysis: a cutter-loader and a plough system. In order to reduce costs generated by failures, maintenance teams should regularly make sure that the machines are used and operated in a rational and effective way. Such activities will allow downtimes to be reduced, and, in consequence, will increase the effectiveness of a mining plant. The evaluation of mining machines' failure frequency contained in this study has been based on one of the traditional quality management tools - the Pareto chart.

Research on rapid agile metrology for manufacturing based on real-time multitask operating system

NASA Astrophysics Data System (ADS)

Chen, Jihong; Song, Zhen; Yang, Daoshan; Zhou, Ji; Buckley, Shawn

1996-10-01

Rapid agile metrology for manufacturing (RAMM) using multiple non-contact sensors is likely to remain a growing trend in manufacturing. High speed inspecting systems for manufacturing is characterized by multitasks implemented in parallel and real-time events which occur simultaneously. In this paper, we introduce a real-time operating system into RAMM research. A general task model of a class-based object- oriented technology is proposed. A general multitask frame of a typical RAMM system using OPNet is discussed. Finally, an application example of a machine which inspects parts held on a carrier strip is described. With RTOS and OPNet, this machine can measure two dimensions of the contacts at 300 parts/second.

Coupled dynamics of translation and collapse of acoustically driven microbubbles.

PubMed

Reddy, Anil J; Szeri, Andrew J

2002-10-01

Pressure gradients drive the motion of microbubbles relative to liquids in which they are suspended. Examples include the hydrostatic pressure due to a gravitational field, and the pressure gradients in a sound field, useful for acoustic levitation. In this paper, the equations describing the coupled dynamics of radial oscillation and translation of a microbubble are given. The formulation is based on a recently derived expression for the hydrodynamic force on a bubble of changing size in an incompressible liquid [J. Magnaudet and D. Legendre, Phys. Fluids 10, 550-556 (1998)]. The complex interaction between radial and translation dynamics is best understood by examination of the added momentum associated with the liquid motion caused by the moving bubble. Translation is maximized when the bubble collapses violently. The new theory for coupled collapse and translation dynamics is compared to past experiments and to previous theories for decoupled translation dynamics. Special attention is paid to bubbles of relevance in biomedical applications.

Expert system for web based collaborative CAE

NASA Astrophysics Data System (ADS)

Hou, Liang; Lin, Zusheng

2006-11-01

An expert system for web based collaborative CAE was developed based on knowledge engineering, relational database and commercial FEA (Finite element analysis) software. The architecture of the system was illustrated. In this system, the experts' experiences, theories and typical examples and other related knowledge, which will be used in the stage of pre-process in FEA, were categorized into analysis process and object knowledge. Then, the integrated knowledge model based on object-oriented method and rule based method was described. The integrated reasoning process based on CBR (case based reasoning) and rule based reasoning was presented. Finally, the analysis process of this expert system in web based CAE application was illustrated, and an analysis example of a machine tool's column was illustrated to prove the validity of the system.

Computational Nanotechnology of Molecular Materials, Electronics, and Actuators with Carbon Nanotubes and Fullerenes

NASA Technical Reports Server (NTRS)

Srivastava, Deepak; Menon, Madhu; Cho, Kyeongjae; Biegel, Bryan (Technical Monitor)

2001-01-01

The role of computational nanotechnology in developing next generation of multifunctional materials, molecular scale electronic and computing devices, sensors, actuators, and machines is described through a brief review of enabling computational techniques and few recent examples derived from computer simulations of carbon nanotube based molecular nanotechnology.

The Bibliographical Control of Early Books.

ERIC Educational Resources Information Center

Cameron, William J.

Examples are given of the kinds of machine-readable data bases that should be developed in order to extend attempts at universal bibliographical control into neglected areas, the results of which can be used by researchers in the humanities, specifically those using books printed before 1801. The principles of bibliographical description,…

A general-purpose machine learning framework for predicting properties of inorganic materials

DOE PAGES

Ward, Logan; Agrawal, Ankit; Choudhary, Alok; ...

2016-08-26

A very active area of materials research is to devise methods that use machine learning to automatically extract predictive models from existing materials data. While prior examples have demonstrated successful models for some applications, many more applications exist where machine learning can make a strong impact. To enable faster development of machine-learning-based models for such applications, we have created a framework capable of being applied to a broad range of materials data. Our method works by using a chemically diverse list of attributes, which we demonstrate are suitable for describing a wide variety of properties, and a novel method formore » partitioning the data set into groups of similar materials to boost the predictive accuracy. In this manuscript, we demonstrate how this new method can be used to predict diverse properties of crystalline and amorphous materials, such as band gap energy and glass-forming ability.« less

A general-purpose machine learning framework for predicting properties of inorganic materials

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ward, Logan; Agrawal, Ankit; Choudhary, Alok

A very active area of materials research is to devise methods that use machine learning to automatically extract predictive models from existing materials data. While prior examples have demonstrated successful models for some applications, many more applications exist where machine learning can make a strong impact. To enable faster development of machine-learning-based models for such applications, we have created a framework capable of being applied to a broad range of materials data. Our method works by using a chemically diverse list of attributes, which we demonstrate are suitable for describing a wide variety of properties, and a novel method formore » partitioning the data set into groups of similar materials to boost the predictive accuracy. In this manuscript, we demonstrate how this new method can be used to predict diverse properties of crystalline and amorphous materials, such as band gap energy and glass-forming ability.« less

Computer-aided design/computer-aided manufacturing skull base drill.

PubMed

Couldwell, William T; MacDonald, Joel D; Thomas, Charles L; Hansen, Bradley C; Lapalikar, Aniruddha; Thakkar, Bharat; Balaji, Alagar K

2017-05-01

The authors have developed a simple device for computer-aided design/computer-aided manufacturing (CAD-CAM) that uses an image-guided system to define a cutting tool path that is shared with a surgical machining system for drilling bone. Information from 2D images (obtained via CT and MRI) is transmitted to a processor that produces a 3D image. The processor generates code defining an optimized cutting tool path, which is sent to a surgical machining system that can drill the desired portion of bone. This tool has applications for bone removal in both cranial and spine neurosurgical approaches. Such applications have the potential to reduce surgical time and associated complications such as infection or blood loss. The device enables rapid removal of bone within 1 mm of vital structures. The validity of such a machining tool is exemplified in the rapid (< 3 minutes machining time) and accurate removal of bone for transtemporal (for example, translabyrinthine) approaches.

The HEPiX Virtualisation Working Group: Towards a Grid of Clouds

NASA Astrophysics Data System (ADS)

Cass, Tony

2012-12-01

The use of virtual machine images, as for example with Cloud services such as Amazon's Elastic Compute Cloud, is attractive for users as they have a guaranteed execution environment, something that cannot today be provided across sites participating in computing grids such as the Worldwide LHC Computing Grid. However, Grid sites often operate within computer security frameworks which preclude the use of remotely generated images. The HEPiX Virtualisation Working Group was setup with the objective to enable use of remotely generated virtual machine images at Grid sites and, to this end, has introduced the idea of trusted virtual machine images which are guaranteed to be secure and configurable by sites such that security policy commitments can be met. This paper describes the requirements and details of these trusted virtual machine images and presents a model for their use to facilitate the integration of Grid- and Cloud-based computing environments for High Energy Physics.

Arbitrary norm support vector machines.

PubMed

Huang, Kaizhu; Zheng, Danian; King, Irwin; Lyu, Michael R

2009-02-01

Support vector machines (SVM) are state-of-the-art classifiers. Typically L2-norm or L1-norm is adopted as a regularization term in SVMs, while other norm-based SVMs, for example, the L0-norm SVM or even the L(infinity)-norm SVM, are rarely seen in the literature. The major reason is that L0-norm describes a discontinuous and nonconvex term, leading to a combinatorially NP-hard optimization problem. In this letter, motivated by Bayesian learning, we propose a novel framework that can implement arbitrary norm-based SVMs in polynomial time. One significant feature of this framework is that only a sequence of sequential minimal optimization problems needs to be solved, thus making it practical in many real applications. The proposed framework is important in the sense that Bayesian priors can be efficiently plugged into most learning methods without knowing the explicit form. Hence, this builds a connection between Bayesian learning and the kernel machines. We derive the theoretical framework, demonstrate how our approach works on the L0-norm SVM as a typical example, and perform a series of experiments to validate its advantages. Experimental results on nine benchmark data sets are very encouraging. The implemented L0-norm is competitive with or even better than the standard L2-norm SVM in terms of accuracy but with a reduced number of support vectors, -9.46% of the number on average. When compared with another sparse model, the relevance vector machine, our proposed algorithm also demonstrates better sparse properties with a training speed over seven times faster.

Creating the Future of Evidence-Based Nutrition Recommendations: Case Studies from Lipid Research123

PubMed Central

Dwyer, Johanna T; Rubin, Kristin H; Psota, Tricia L; Liska, DeAnn J; Montain, Scott J

2016-01-01

Strategic translational research is designed to address research gaps that answer specific guidance questions. It provides translational value with respect to nutrition guidance and regulatory and public policy. The relevance and the quality of evidence both matter in translational research. For example, design decisions regarding population, intervention, comparator, and outcome criteria affect whether or not high-quality studies are considered relevant to specific guidance questions and are therefore included as evidence within the context of systematic review frameworks used by authoritative food and health organizations. The process used in systematic reviews, developed by the USDA for its Nutrition Evidence Library, is described. An eating pattern and cardiovascular disease (CVD) evidence review is provided as an example, and factors that differentiated the studies considered relevant and included in that evidence base from those that were excluded are noted. Case studies on ω-3 (n–3) fatty acids (FAs) and industrial trans-FAs illustrate key factors vital to relevance and translational impact, including choice of a relevant population (e.g., healthy, at risk, or diseased subjects; general population or high-performance soldiers); dose and form of the intervention (e.g., food or supplement); use of relevant comparators (e.g., technically feasible and realistic); and measures for both exposure and outcomes (e.g., inflammatory markers or CVD endpoints). Specific recommendations are provided to help increase the impact of nutrition research on future dietary guidance, policy, and regulatory issues, particularly in the area of lipids. PMID:27422509

Translation lexicon acquisition from bilingual dictionaries

NASA Astrophysics Data System (ADS)

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

2001-12-01

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

SU-F-T-457: A Filmless Method for Measurement of Couch Translation Per Gantry Rotation and Couch Speed for Tomotherapy Using ArcCheck

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, B; Wong, R; Geng, H

Purpose: To develop a filmless methodology based on an ArcCheck for QA measurement of the couch translation per gantry rotation and couch speed of a Tomotherapy unit. Methods: Two test plans recommended by TG148 were chosen for this study. A helical plan with 1 cm field size opened the leaves for 180 degrees at the 2nd, 7th and 12th of total 13 rotations and was used to verify if the couch travelled the expected distance per gantry rotation. The other test plan was a static plan with the gantry at 0°, 1cm field width and constant couch movement speed ofmore » 0.5mm/s. It was used for couch speed measurement. The ArcCheck was isocentrically set up and recorded movie files which took a snapshot exposure every 50ms. Due to the spiral pattern of diodes distribution, when one of the diodes of the ArcCheck located at the beam center, the dose profile as measured by the row of diodes which surrounded the center diode should have a symmetrical pattern. We divided the profile into left half A and right half B. Then a shape parameter was defined as S=Σ|(A−B)|/Σ(A+B). By searching the local minimum of S parameter, the beam center at different time could be located. The machine trajectory log data were also collected and analyzed for comparison. Results: The mean value of measured couch translation and couch speed by ArcCheck had less than 0.05% deviation from the planned values. For couch speed measurement, our result showed a mean value of 0.5002 with an uncertainty ±0.0031, which agreed very well with both the plan setting of 0.5 mm/s and the machine log data of 0.5005 mm/s. Conclusion: Couch translation measured using ArcCheck is accurate and comparable to the film-based measurement. This filmless method also provides a convenient and independent way for measuring couch speed.« less

Semantic closure demonstrated by the evolution of a universal constructor architecture in an artificial chemistry.

PubMed

Clark, Edward B; Hickinbotham, Simon J; Stepney, Susan

2017-05-01

We present a novel stringmol-based artificial chemistry system modelled on the universal constructor architecture (UCA) first explored by von Neumann. In a UCA, machines interact with an abstract description of themselves to replicate by copying the abstract description and constructing the machines that the abstract description encodes. DNA-based replication follows this architecture, with DNA being the abstract description, the polymerase being the copier, and the ribosome being the principal machine in expressing what is encoded on the DNA. This architecture is semantically closed as the machine that defines what the abstract description means is itself encoded on that abstract description. We present a series of experiments with the stringmol UCA that show the evolution of the meaning of genomic material, allowing the concept of semantic closure and transitions between semantically closed states to be elucidated in the light of concrete examples. We present results where, for the first time in an in silico system, simultaneous evolution of the genomic material, copier and constructor of a UCA, giving rise to viable offspring. © 2017 The Author(s).

Maximizing the Impact of Systematic Reviews in Health Care Decision Making: A Systematic Scoping Review of Knowledge-Translation Resources

PubMed Central

Chambers, Duncan; Wilson, Paul M; Thompson, Carl A; Hanbury, Andria; Farley, Katherine; Light, Kate

2011-01-01

Context: Barriers to the use of systematic reviews by policymakers may be overcome by resources that adapt and present the findings in formats more directly tailored to their needs. We performed a systematic scoping review to identify such knowledge-translation resources and evaluations of them. Methods: Resources were eligible for inclusion in this study if they were based exclusively or primarily on systematic reviews and were aimed at health care policymakers at the national or local level. Resources were identified by screening the websites of health technology assessment agencies and systematic review producers, supplemented by an email survey. Electronic databases and proceedings of the Cochrane Colloquium and HTA International were searched as well for published and unpublished evaluations of knowledge-translation resources. Resources were classified as summaries, overviews, or policy briefs using a previously published classification. Findings: Twenty knowledge-translation resources were identified, of which eleven were classified as summaries, six as overviews, and three as policy briefs. Resources added value to systematic reviews by, for example, evaluating their methodological quality or assessing the reliability of their conclusions or their generalizability to particular settings. The literature search found four published evaluation studies of knowledge-translation resources, and the screening of abstracts and contact with authors found three more unpublished studies. The majority of studies reported on the perceived usefulness of the service, although there were some examples of review-based resources being used to assist actual decision making. Conclusions: Systematic review producers provide a variety of resources to help policymakers, of which focused summaries are the most common. More evaluations of these resources are required to ensure users’ needs are being met, to demonstrate their impact, and to justify their funding. PMID:21418315

The Trail Making test: a study of its ability to predict falls in the acute neurological in-patient population.

PubMed

Mateen, Bilal Akhter; Bussas, Matthias; Doogan, Catherine; Waller, Denise; Saverino, Alessia; Király, Franz J; Playford, E Diane

2018-05-01

To determine whether tests of cognitive function and patient-reported outcome measures of motor function can be used to create a machine learning-based predictive tool for falls. Prospective cohort study. Tertiary neurological and neurosurgical center. In all, 337 in-patients receiving neurosurgical, neurological, or neurorehabilitation-based care. Binary (Y/N) for falling during the in-patient episode, the Trail Making Test (a measure of attention and executive function) and the Walk-12 (a patient-reported measure of physical function). The principal outcome was a fall during the in-patient stay ( n = 54). The Trail test was identified as the best predictor of falls. Moreover, addition of other variables, did not improve the prediction (Wilcoxon signed-rank P < 0.001). Classical linear statistical modeling methods were then compared with more recent machine learning based strategies, for example, random forests, neural networks, support vector machines. The random forest was the best modeling strategy when utilizing just the Trail Making Test data (Wilcoxon signed-rank P < 0.001) with 68% (± 7.7) sensitivity, and 90% (± 2.3) specificity. This study identifies a simple yet powerful machine learning (Random Forest) based predictive model for an in-patient neurological population, utilizing a single neuropsychological test of cognitive function, the Trail Making test.

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

NASA Technical Reports Server (NTRS)

Morrow, J. R.; Boelter, J.

1978-01-01

Selected film segments were digitized. An efficiency of translation scale was developed, and each of 200 segments of film were rated with regard to the astronauts translation characteristics. Results indicated that in general the astronauts were able to acclimate themselves to the zero g environment quite well. Results also indicated that astronauts tended to translate in 1 g orientations when in the experimental compartment and the wardroom which were architecturally 1 g. However, when the astronauts were in the forward compartment, which was zero g oriented, they began to translate more frequently in a zero g manner. There appeared to be improvements in translation across time. These improvements appeared more so in the forward compartment than in the wardroom or the experimental compartment. Possible changes in the architecture of the wardroom and the experimental compartment were suggested in order to improve translation within these compartments.

ROOT.NET: Using ROOT from .NET languages like C# and F#

NASA Astrophysics Data System (ADS)

Watts, G.

2012-12-01

ROOT.NET provides an interface between Microsoft's Common Language Runtime (CLR) and .NET technology and the ubiquitous particle physics analysis tool, ROOT. ROOT.NET automatically generates a series of efficient wrappers around the ROOT API. Unlike pyROOT, these wrappers are statically typed and so are highly efficient as compared to the Python wrappers. The connection to .NET means that one gains access to the full series of languages developed for the CLR including functional languages like F# (based on OCaml). Many features that make ROOT objects work well in the .NET world are added (properties, IEnumerable interface, LINQ compatibility, etc.). Dynamic languages based on the CLR can be used as well, of course (Python, for example). Additionally it is now possible to access ROOT objects that are unknown to the translation tool. This poster will describe the techniques used to effect this translation, along with performance comparisons, and examples. All described source code is posted on the open source site CodePlex.

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

NASA Astrophysics Data System (ADS)

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.

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

PubMed Central

2012-01-01

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. PMID:23151362

Discovery of numerous novel small genes in the intergenic regions of the Escherichia coli O157:H7 Sakai genome

PubMed Central

Hücker, Sarah M.; Ardern, Zachary; Goldberg, Tatyana; Schafferhans, Andrea; Bernhofer, Michael; Vestergaard, Gisle; Nelson, Chase W.; Schloter, Michael; Rost, Burkhard; Scherer, Siegfried

2017-01-01

In the past, short protein-coding genes were often disregarded by genome annotation pipelines. Transcriptome sequencing (RNAseq) signals outside of annotated genes have usually been interpreted to indicate either ncRNA or pervasive transcription. Therefore, in addition to the transcriptome, the translatome (RIBOseq) of the enteric pathogen Escherichia coli O157:H7 strain Sakai was determined at two optimal growth conditions and a severe stress condition combining low temperature and high osmotic pressure. All intergenic open reading frames potentially encoding a protein of ≥ 30 amino acids were investigated with regard to coverage by transcription and translation signals and their translatability expressed by the ribosomal coverage value. This led to discovery of 465 unique, putative novel genes not yet annotated in this E. coli strain, which are evenly distributed over both DNA strands of the genome. For 255 of the novel genes, annotated homologs in other bacteria were found, and a machine-learning algorithm, trained on small protein-coding E. coli genes, predicted that 89% of these translated open reading frames represent bona fide genes. The remaining 210 putative novel genes without annotated homologs were compared to the 255 novel genes with homologs and to 250 short annotated genes of this E. coli strain. All three groups turned out to be similar with respect to their translatability distribution, fractions of differentially regulated genes, secondary structure composition, and the distribution of evolutionary constraint, suggesting that both novel groups represent legitimate genes. However, the machine-learning algorithm only recognized a small fraction of the 210 genes without annotated homologs. It is possible that these genes represent a novel group of genes, which have unusual features dissimilar to the genes of the machine-learning algorithm training set. PMID:28902868

Rosetta: Ensuring the Preservation and Usability of ASCII-based Data into the Future

NASA Astrophysics Data System (ADS)

Ramamurthy, M. K.; Arms, S. C.

2015-12-01

Field data obtained from dataloggers often take the form of comma separated value (CSV) ASCII text files. While ASCII based data formats have positive aspects, such as the ease of accessing the data from disk and the wide variety of tools available for data analysis, there are some drawbacks, especially when viewing the situation through the lens of data interoperability and stewardship. The Unidata data translation tool, Rosetta, is a web-based service that provides an easy, wizard-based interface for data collectors to transform their datalogger generated ASCII output into Climate and Forecast (CF) compliant netCDF files following the CF-1.6 discrete sampling geometries. These files are complete with metadata describing what data are contained in the file, the instruments used to collect the data, and other critical information that otherwise may be lost in one of many README files. The choice of the machine readable netCDF data format and data model, coupled with the CF conventions, ensures long-term preservation and interoperability, and that future users will have enough information to responsibly use the data. However, with the understanding that the observational community appreciates the ease of use of ASCII files, methods for transforming the netCDF back into a CSV or spreadsheet format are also built-in. One benefit of translating ASCII data into a machine readable format that follows open community-driven standards is that they are instantly able to take advantage of data services provided by the many open-source data server tools, such as the THREDDS Data Server (TDS). While Rosetta is currently a stand-alone service, this talk will also highlight efforts to couple Rosetta with the TDS, thus allowing self-publishing of thoroughly documented datasets by the data producers themselves.

Machine vision based teleoperation aid

NASA Technical Reports Server (NTRS)

Hoff, William A.; Gatrell, Lance B.; Spofford, John R.

1991-01-01

When teleoperating a robot using video from a remote camera, it is difficult for the operator to gauge depth and orientation from a single view. In addition, there are situations where a camera mounted for viewing by the teleoperator during a teleoperation task may not be able to see the tool tip, or the viewing angle may not be intuitive (requiring extensive training to reduce the risk of incorrect or dangerous moves by the teleoperator). A machine vision based teleoperator aid is presented which uses the operator's camera view to compute an object's pose (position and orientation), and then overlays onto the operator's screen information on the object's current and desired positions. The operator can choose to display orientation and translation information as graphics and/or text. This aid provides easily assimilated depth and relative orientation information to the teleoperator. The camera may be mounted at any known orientation relative to the tool tip. A preliminary experiment with human operators was conducted and showed that task accuracies were significantly greater with than without this aid.

Comparison Analysis of Recognition Algorithms of Forest-Cover Objects on Hyperspectral Air-Borne and Space-Borne Images

NASA Astrophysics Data System (ADS)

Kozoderov, V. V.; Kondranin, T. V.; Dmitriev, E. V.

2017-12-01

The basic model for the recognition of natural and anthropogenic objects using their spectral and textural features is described in the problem of hyperspectral air-borne and space-borne imagery processing. The model is based on improvements of the Bayesian classifier that is a computational procedure of statistical decision making in machine-learning methods of pattern recognition. The principal component method is implemented to decompose the hyperspectral measurements on the basis of empirical orthogonal functions. Application examples are shown of various modifications of the Bayesian classifier and Support Vector Machine method. Examples are provided of comparing these classifiers and a metrical classifier that operates on finding the minimal Euclidean distance between different points and sets in the multidimensional feature space. A comparison is also carried out with the " K-weighted neighbors" method that is close to the nonparametric Bayesian classifier.

Support vector machines and generalisation in HEP

NASA Astrophysics Data System (ADS)

Bevan, Adrian; Gamboa Goñi, Rodrigo; Hays, Jon; Stevenson, Tom

2017-10-01

We review the concept of Support Vector Machines (SVMs) and discuss examples of their use in a number of scenarios. Several SVM implementations have been used in HEP and we exemplify this algorithm using the Toolkit for Multivariate Analysis (TMVA) implementation. We discuss examples relevant to HEP including background suppression for H → τ + τ - at the LHC with several different kernel functions. Performance benchmarking leads to the issue of generalisation of hyper-parameter selection. The avoidance of fine tuning (over training or over fitting) in MVA hyper-parameter optimisation, i.e. the ability to ensure generalised performance of an MVA that is independent of the training, validation and test samples, is of utmost importance. We discuss this issue and compare and contrast performance of hold-out and k-fold cross-validation. We have extended the SVM functionality and introduced tools to facilitate cross validation in TMVA and present results based on these improvements.

Cyclotron accelerated beams applied in wear and corrosion studies

NASA Astrophysics Data System (ADS)

Racolta, P. M.; Popa-Simil, L.; Ivanov, E. A.; Alexandreanu, B.

1996-05-01

Wear and corrosion processes are characterized by a loss of material that is, for machine parts and components, usually in a micrometer's range. That is why, in the last two decades, many direct applications in machine construction, petrochemical and metallurgical industries based on the Thin Layer Activation (TLA) technique have been developed. In this paper general working patterns together with a few examples of TLA applications carried out using our laboratory's U-120 Cyclotron are presented. The relation between the counting rate of the radiation originating from the component's irradiated zone and the loss of the worn material can be determined mainly by two methods: the oil circulation method and the remnant radioactivity measuring method. The first method is illustrated with some typical examples such as the optimization of the running-in program of a diesel engine and anti-wear features certifying of lubricant oils. There is also presented an example where the second method mentioned above has been applied to corrosion rate determinations for different kinds of unoxidable steels used in inert gas generator construction.

Automated translating beam profiler for in situ laser beam spot-size and focal position measurements

NASA Astrophysics Data System (ADS)

Keaveney, James

2018-03-01

We present a simple and convenient, high-resolution solution for automated laser-beam profiling with axial translation. The device is based on a Raspberry Pi computer, Pi Noir CMOS camera, stepper motor, and commercial translation stage. We also provide software to run the device. The CMOS sensor is sensitive over a large wavelength range between 300 and 1100 nm and can be translated over 25 mm along the beam axis. The sensor head can be reversed without changing its axial position, allowing for a quantitative estimate of beam overlap with counter-propagating laser beams. Although not limited to this application, the intended use for this device is the automated measurement of the focal position and spot-size of a Gaussian laser beam. We present example data of one such measurement to illustrate device performance.

Automated translating beam profiler for in situ laser beam spot-size and focal position measurements.

PubMed

Keaveney, James

2018-03-01

We present a simple and convenient, high-resolution solution for automated laser-beam profiling with axial translation. The device is based on a Raspberry Pi computer, Pi Noir CMOS camera, stepper motor, and commercial translation stage. We also provide software to run the device. The CMOS sensor is sensitive over a large wavelength range between 300 and 1100 nm and can be translated over 25 mm along the beam axis. The sensor head can be reversed without changing its axial position, allowing for a quantitative estimate of beam overlap with counter-propagating laser beams. Although not limited to this application, the intended use for this device is the automated measurement of the focal position and spot-size of a Gaussian laser beam. We present example data of one such measurement to illustrate device performance.

Retrofit concept for small safety related stationary machines

NASA Astrophysics Data System (ADS)

Epple, S.; Jalba, C. K.; Muminovic, A.; Jung, R.

2017-05-01

More and more old machines have the problem that their control electronics’ lifecycle comes to its intended end of life, whilst the mechanics itself and process capability is still in very good condition. This article shows an example of a reactive ion etcher originally built in 1988, which was refitted with a new control concept. The original control unit was repaired several times based on manufacturer’s obsolescence management. At start of the retrofit project the integrated circuits were no longer available for further repair of the original control unit. Safety, repeatability and stability of the process were greatly improved.

Electrical machines and assemblies including a yokeless stator with modular lamination stacks

DOEpatents

Qu, Ronghai; Jansen, Patrick Lee; Bagepalli, Bharat Sampathkumar; Carl, Jr., Ralph James; Gadre, Aniruddha Dattatraya; Lopez, Fulton Jose

2010-04-06

An electrical machine includes a rotor with an inner rotor portion and an outer rotor portion, and a double-sided yokeless stator. The yokeless stator includes modular lamination stacks and is configured for radial magnetic flux flow. The double-sided yokeless stator is concentrically disposed between the inner rotor portion and the outer rotor portion of the electrical machine. Examples of particularly useful embodiments for the electrical machine include wind turbine generators, ship propulsion motors, switch reluctance machines and double-sided synchronous machines.

Machine Learning in Computer-Aided Synthesis Planning.

PubMed

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

An introduction to kernel-based learning algorithms.

PubMed

Müller, K R; Mika, S; Rätsch, G; Tsuda, K; Schölkopf, B

2001-01-01

This paper provides an introduction to support vector machines, kernel Fisher discriminant analysis, and kernel principal component analysis, as examples for successful kernel-based learning methods. We first give a short background about Vapnik-Chervonenkis theory and kernel feature spaces and then proceed to kernel based learning in supervised and unsupervised scenarios including practical and algorithmic considerations. We illustrate the usefulness of kernel algorithms by discussing applications such as optical character recognition and DNA analysis.

Classification of hadith into positive suggestion, negative suggestion, and information

NASA Astrophysics Data System (ADS)

Faraby, Said Al; Riviera Rachmawati Jasin, Eliza; Kusumaningrum, Andina; Adiwijaya

2018-03-01

As one of the Muslim life guidelines, based on the meaning of its sentence(s), a hadith can be viewed as a suggestion for doing something, or a suggestion for not doing something, or just information without any suggestion. In this paper, we tried to classify the Bahasa translation of hadith into the three categories using machine learning approach. We tried stemming and stopword removal in preprocessing, and TF-IDF of unigram, bigram, and trigram as the extracted features. As the classifier, we compared between SVM and Neural Network. Since the categories are new, so in order to compare the results of the previous pipelines, we created a baseline classifier using simple rule-based string matching technique. The rule-based algorithm conditions on the occurrence of words such as “janganlah, sholatlah, and so on” to determine the category. The baseline method achieved F1-Score of 0.69, while the best F1-Score from the machine learning approach was 0.88, and it was produced by SVM model with the linear kernel.

Machine-Assisted Translation in West Germany

DTIC Science & Technology

1977-03-04

the Ger- man, English , French or Russian languages are recorded, where it is known that they have been used in translation or teaching assignments...German literary language encompasses about 300,000 words, English about 600,000, and the vocabulary of a person of average education is about...Terminology Recording and Evaluation Method ) was developed in the language service of the Siemens company in Munich as an aid for in-house application

Extended robust support vector machine based on financial risk minimization.

PubMed

Takeda, Akiko; Fujiwara, Shuhei; Kanamori, Takafumi

2014-11-01

Financial risk measures have been used recently in machine learning. For example, ν-support vector machine ν-SVM) minimizes the conditional value at risk (CVaR) of margin distribution. The measure is popular in finance because of the subadditivity property, but it is very sensitive to a few outliers in the tail of the distribution. We propose a new classification method, extended robust SVM (ER-SVM), which minimizes an intermediate risk measure between the CVaR and value at risk (VaR) by expecting that the resulting model becomes less sensitive than ν-SVM to outliers. We can regard ER-SVM as an extension of robust SVM, which uses a truncated hinge loss. Numerical experiments imply the ER-SVM's possibility of achieving a better prediction performance with proper parameter setting.

Trust metrics in information fusion

NASA Astrophysics Data System (ADS)

Blasch, Erik

2014-05-01

Trust is an important concept for machine intelligence and is not consistent across many applications. In this paper, we seek to understand trust from a variety of factors: humans, sensors, communications, intelligence processing algorithms and human-machine displays of information. In modeling the various aspects of trust, we provide an example from machine intelligence that supports the various attributes of measuring trust such as sensor accuracy, communication timeliness, machine processing confidence, and display throughput to convey the various attributes that support user acceptance of machine intelligence results. The example used is fusing video and text whereby an analyst needs trust information in the identified imagery track. We use the proportional conflict redistribution rule as an information fusion technique that handles conflicting data from trusted and mistrusted sources. The discussion of the many forms of trust explored in the paper seeks to provide a systems-level design perspective for information fusion trust quantification.

From evidence based medicine to mechanism based medicine. Reviewing the role of pharmacogenetics.

PubMed

Wilffert, Bob; Swen, Jesse; Mulder, Hans; Touw, Daan; Maitland-Van der Zee, Anke-Hilse; Deneer, Vera

2013-06-01

The translation of evidence based medicine to a specific patient presents a considerable challenge. We present by means of the examples nortriptyline, tramadol, clopidogrel, coumarins, abacavir and antipsychotics the discrepancy between available pharmacogenetic information and its implementation in daily clinical practice. Literature review. A mechanism based approach may be helpful to personalize medicine for the individual patient to which pharmacogenetics may contribute significantly. The lack of consistency in what we accept in bioequivalence and in pharmacogenetics of drug metabolising enzymes is discussed and illustrated with the example of nortriptyline. The impact of pharmacogenetics on examples like tramadol, clopidogrel, coumarins and abacavir is described. Also the present status of the polymorphisms of 5-HT2A and C receptors in antipsychotic-induced weight gain is presented as a pharmacodynamic example with until now a greater distance to clinical implementation. The contribution of pharmacogenetics to tailor-made pharmacotherapy, which especially might be of value for patients deviating from the average, has not yet reached the position it seems to deserve.

Verifying Secrets and Relative Secrecy

DTIC Science & Technology

2000-01-01

Systems that authenticate a user based on a shared secret (such as a password or PIN) normally allow anyone to query whether the secret is a given...value. For example, an ATM machine allows one to ask whether a string is the secret PIN of a (lost or stolen) ATM card. Yet such queries are prohibited

Linguistic Problems in the Work of the Translator.

ERIC Educational Resources Information Center

Szymczak, M.

Noting that no clear and adequate basis for a theory of translation exists at this time, this article examines problems common to three fundamental elements of translation. Illustrative examples, taken from Slavic languages, relate to discussion of grammatical, semantic-lexical, and stylistic aspects of translation. Various contributions of…

The Development of using the digital projection method to measure the contact angle of ball screw

NASA Astrophysics Data System (ADS)

Chen, Chun-Jen; Jywe, Wenyuh; Liu, Yu-Chun; Jwo, Hsin-Hong

The ball screw frequently used to drive or translate the parts on the precision machine, such as machine tool and motorized stage. Therefore they were most frequently used on the precision machine, semiconductor equipment, medical instrument and aero industry. The main parts of ball screw are screw, ball and nut. The contact angle between the screw, ball and nut will affect the performance (include loading and noise) and lifecycle of a ball screw. If the actual contact angle and the designed contact angle are not the same, the friction between the ball, screw and nut will increase and it will result in the thermal increase and lifecycle decrease. This paper combines the traditional profile projector and commercial digital camera to build an imaging based and noncontact measurements system. It can implement the contact angle measurement quickly and accurately. Three different pitch angles of ball screws were completed tests in this paper. The angle resolution of this measurement system is about 0.001 degree and its accuracy is about 0.05 degree.

Translational bioinformatics in the era of real-time biomedical, health care and wellness data streams

PubMed Central

Miotto, Riccardo; Glicksberg, Benjamin S.; Morgan, Joseph W.; Dudley, Joel T.

2017-01-01

Monitoring and modeling biomedical, health care and wellness data from individuals and converging data on a population scale have tremendous potential to improve understanding of the transition to the healthy state of human physiology to disease setting. Wellness monitoring devices and companion software applications capable of generating alerts and sharing data with health care providers or social networks are now available. The accessibility and clinical utility of such data for disease or wellness research are currently limited. Designing methods for streaming data capture, real-time data aggregation, machine learning, predictive analytics and visualization solutions to integrate wellness or health monitoring data elements with the electronic medical records (EMRs) maintained by health care providers permits better utilization. Integration of population-scale biomedical, health care and wellness data would help to stratify patients for active health management and to understand clinically asymptomatic patients and underlying illness trajectories. In this article, we discuss various health-monitoring devices, their ability to capture the unique state of health represented in a patient and their application in individualized diagnostics, prognosis, clinical or wellness intervention. We also discuss examples of translational bioinformatics approaches to integrating patient-generated data with existing EMRs, personal health records, patient portals and clinical data repositories. Briefly, translational bioinformatics methods, tools and resources are at the center of these advances in implementing real-time biomedical and health care analytics in the clinical setting. Furthermore, these advances are poised to play a significant role in clinical decision-making and implementation of data-driven medicine and wellness care. PMID:26876889

ProDiGe: Prioritization Of Disease Genes with multitask machine learning from positive and unlabeled examples

PubMed Central

2011-01-01

Background Elucidating the genetic basis of human diseases is a central goal of genetics and molecular biology. While traditional linkage analysis and modern high-throughput techniques often provide long lists of tens or hundreds of disease gene candidates, the identification of disease genes among the candidates remains time-consuming and expensive. Efficient computational methods are therefore needed to prioritize genes within the list of candidates, by exploiting the wealth of information available about the genes in various databases. Results We propose ProDiGe, a novel algorithm for Prioritization of Disease Genes. ProDiGe implements a novel machine learning strategy based on learning from positive and unlabeled examples, which allows to integrate various sources of information about the genes, to share information about known disease genes across diseases, and to perform genome-wide searches for new disease genes. Experiments on real data show that ProDiGe outperforms state-of-the-art methods for the prioritization of genes in human diseases. Conclusions ProDiGe implements a new machine learning paradigm for gene prioritization, which could help the identification of new disease genes. It is freely available at http://cbio.ensmp.fr/prodige. PMID:21977986

Classification of highly unbalanced CYP450 data of drugs using cost sensitive machine learning techniques.

PubMed

Eitrich, T; Kless, A; Druska, C; Meyer, W; Grotendorst, J

2007-01-01

In this paper, we study the classifications of unbalanced data sets of drugs. As an example we chose a data set of 2D6 inhibitors of cytochrome P450. The human cytochrome P450 2D6 isoform plays a key role in the metabolism of many drugs in the preclinical drug discovery process. We have collected a data set from annotated public data and calculated physicochemical properties with chemoinformatics methods. On top of this data, we have built classifiers based on machine learning methods. Data sets with different class distributions lead to the effect that conventional machine learning methods are biased toward the larger class. To overcome this problem and to obtain sensitive but also accurate classifiers we combine machine learning and feature selection methods with techniques addressing the problem of unbalanced classification, such as oversampling and threshold moving. We have used our own implementation of a support vector machine algorithm as well as the maximum entropy method. Our feature selection is based on the unsupervised McCabe method. The classification results from our test set are compared structurally with compounds from the training set. We show that the applied algorithms enable the effective high throughput in silico classification of potential drug candidates.

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

PubMed

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

2015-01-01

Globalization of business and competitiveness in manufacturing has forced companies to improve their manufacturing facilities to respond to market requirements. Machine tool evaluation involves an essential decision using imprecise and vague information, and plays a major role to improve the productivity and flexibility in manufacturing. The aim of this study is to present an integrated approach for decision-making in machine tool selection. This paper is focused on the integration of a consistent fuzzy AHP (Analytic Hierarchy Process) and a fuzzy COmplex PRoportional ASsessment (COPRAS) for multi-attribute decision-making in selecting the most suitable machine tool. In this method, the fuzzy linguistic reference relation is integrated into AHP to handle the imprecise and vague information, and to simplify the data collection for the pair-wise comparison matrix of the AHP which determines the weights of attributes. The output of the fuzzy AHP is imported into the fuzzy COPRAS method for ranking alternatives through the closeness coefficient. Presentation of the proposed model application is provided by a numerical example based on the collection of data by questionnaire and from the literature. The results highlight the integration of the improved fuzzy AHP and the fuzzy COPRAS as a precise tool and provide effective multi-attribute decision-making for evaluating the machine tool in the uncertain environment.

A feasibility study of automatic lung nodule detection in chest digital tomosynthesis with machine learning based on support vector machine

NASA Astrophysics Data System (ADS)

Lee, Donghoon; Kim, Ye-seul; Choi, Sunghoon; Lee, Haenghwa; Jo, Byungdu; Choi, Seungyeon; Shin, Jungwook; Kim, Hee-Joung

2017-03-01

The chest digital tomosynthesis(CDT) is recently developed medical device that has several advantage for diagnosing lung disease. For example, CDT provides depth information with relatively low radiation dose compared to computed tomography (CT). However, a major problem with CDT is the image artifacts associated with data incompleteness resulting from limited angle data acquisition in CDT geometry. For this reason, the sensitivity of lung disease was not clear compared to CT. In this study, to improve sensitivity of lung disease detection in CDT, we developed computer aided diagnosis (CAD) systems based on machine learning. For design CAD systems, we used 100 cases of lung nodules cropped images and 100 cases of normal lesion cropped images acquired by lung man phantoms and proto type CDT. We used machine learning techniques based on support vector machine and Gabor filter. The Gabor filter was used for extracting characteristics of lung nodules and we compared performance of feature extraction of Gabor filter with various scale and orientation parameters. We used 3, 4, 5 scales and 4, 6, 8 orientations. After extracting features, support vector machine (SVM) was used for classifying feature of lesions. The linear, polynomial and Gaussian kernels of SVM were compared to decide the best SVM conditions for CDT reconstruction images. The results of CAD system with machine learning showed the capability of automatically lung lesion detection. Furthermore detection performance was the best when Gabor filter with 5 scale and 8 orientation and SVM with Gaussian kernel were used. In conclusion, our suggested CAD system showed improving sensitivity of lung lesion detection in CDT and decide Gabor filter and SVM conditions to achieve higher detection performance of our developed CAD system for CDT.

Online Vibration Monitoring of a Water Pump Machine to Detect Its Malfunction Components Based on Artificial Neural Network

NASA Astrophysics Data System (ADS)

Rahmawati, P.; Prajitno, P.

2018-04-01

Vibration monitoring is a measurement instrument used to identify, predict, and prevent failures in machine instruments[6]. This is very needed in the industrial applications, cause any problem with the equipment or plant translates into economical loss and they are mostly monitored component off-line[2]. In this research, a system has been developed to detect the malfunction of the components of Shimizu PS-128BT water pump machine, such as capacitor, bearing and impeller by online measurements. The malfunction components are detected by taking vibration data using a Micro-Electro-Mechanical System(MEMS)-based accelerometer that are acquired by using Raspberry Pi microcomputer and then the data are converted into the form of Relative Power Ratio(RPR). In this form the signal acquired from different components conditions have different patterns. The collected RPR used as the base of classification process for recognizing the damage components of the water pump that are conducted by Artificial Neural Network(ANN). Finally, the damage test result will be sent via text message using GSM module that are connected to Raspberry Pi microcomputer. The results, with several measurement readings, with each reading in 10 minutes duration for each different component conditions, all cases yield 100% of accuracies while in the case of defective capacitor yields 90% of accuracy.

Translation of etiology into evidence-based prevention: the life skills program IPSY.

PubMed

Weichold, Karina

2014-01-01

IPSY (Information + Psychosocial Competence = Protection) is a universal life skills program aiming at the promotion of generic intra- and interpersonal life skills, substance specific skills (for example, resistance skills), school bonding, knowledge, and the prevention of substance misuse with a focus on alcohol and tobacco in youth. This program is based on the WHO's life skills approach as well as on theories and empirical findings concerning the development of substance misuse during early adolescence. IPSY is implemented by teachers over three years of schooling (grades 5-7 in Germany). Guided by models of translational research dealing with conditions of a successful translation of etiological findings into evidence-based prevention programs, the chapter highlights the results of a more than ten-year research program focusing on the development and evaluation of the IPSY program. Findings on long-term general effects, mediators and moderators of program effectiveness, and cross-cultural transferability of the program to other European countries are summarized and discussed in light of dissemination issues. © WILEY PERIODICALS, INC.

Machinability of Al 6061 Deposited with Cold Spray Additive Manufacturing

NASA Astrophysics Data System (ADS)

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.

Machine Learning Approaches for Clinical Psychology and Psychiatry.

PubMed

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.

A functional language approach in high-speed digital simulation

NASA Technical Reports Server (NTRS)

Ercegovac, M. D.; Lu, S.-L.

1983-01-01

A functional programming approach for a multi-microprocessor architecture is presented. The language, based on Backus FP, its intermediate form and the translation process are discussed and illustrated with an example. The approach allows performance analysis to be performed at a high level as an aid in program partitioning.

Cultural Translation of Interventions: Diabetes Care in American Samoa

PubMed Central

Rosen, Rochelle K.; Batts-Turner, Marian; Bereolos, Nicole; House, Meaghan; Held, Rachel Forster; Nu'usolia, Ofeira; Tuitele, John; Goldstein, Michael G.; McGarvey, Stephen T.

2010-01-01

Translation of research advances into clinical practice for at-risk communities is important to eliminate disease disparities. Adult type 2 diabetes prevalence in the US territory of American Samoa is 21.5%, but little intervention research has been carried out there. We discuss our experience with cultural translation, drawing on an emerging implementation science, which aims to build a knowledge base on adapting interventions to real-world settings. We offer examples from our behavioral intervention study, Diabetes Care in American Samoa, which was adapted from Project Sugar 2, a nurse and community health worker intervention to support diabetes self-management among urban African Americans. The challenges we experienced and solutions we used may inform adaptations of interventions in other settings. PMID:20864729

Procedure and computer program to calculate machine contribution to sawmill recovery

Treesearch

Philip H. Steele; Hiram Hallock; Stanford Lunstrum

1981-01-01

The importance of considering individual machine contribution to total mill efficiency is discussed. A method for accurately calculating machine contribution is introduced, and an example is given using this method. A FORTRAN computer program to make the necessary complex calculations automatically is also presented with user instructions.

An assessment of the connection machine

NASA Technical Reports Server (NTRS)

Schreiber, Robert

1990-01-01

The CM-2 is an example of a connection machine. The strengths and problems of this implementation are considered as well as important issues in the architecture and programming environment of connection machines in general. These are contrasted to the same issues in Multiple Instruction/Multiple Data (MIMD) microprocessors and multicomputers.

Evaluating Kinase ATP Uptake and Tyrosine Phosphorylation using Multiplexed Quantification of Chemically Labeled and Post-Translationally Modified Peptides

PubMed Central

Fang, Bin; Hoffman, Melissa A.; Mirza, Abu-Sayeef; Mishall, Katie M.; Li, Jiannong; Peterman, Scott M.; Smalley, Keiran S. M.; Shain, Kenneth H.; Weinberger, Paul M.; Wu, Jie; Rix, Uwe; Haura, Eric B.; Koomen, John M.

2015-01-01

Cancer biologists and other healthcare researchers face an increasing challenge in addressing the molecular complexity of disease. Biomarker measurement tools and techniques now contribute to both basic science and translational research. In particular, liquid chromatography-multiple reaction monitoring mass spectrometry (LC-MRM) for multiplexed measurements of protein biomarkers has emerged as a versatile tool for systems biology. Assays can be developed for specific peptides that report on protein expression, mutation, or post-translational modification; discovery proteomics data rapidly translated into multiplexed quantitative approaches. Complementary advances in affinity purification enrich classes of enzymes or peptides representing post-translationally modified or chemically labeled substrates. Here, we illustrate the process for the relative quantification of hundreds of peptides in a single LC-MRM experiment. Desthiobiotinylated peptides produced by activity-based protein profiling (ABPP) using ATP probes and tyrosine-phosphorylated peptides are used as examples. These targeted quantification panels can be applied to further understand the biology of human disease. PMID:25782629

Natural Language Processing.

ERIC Educational Resources Information Center

Chowdhury, Gobinda G.

2003-01-01

Discusses issues related to natural language processing, including theoretical developments; natural language understanding; tools and techniques; natural language text processing systems; abstracting; information extraction; information retrieval; interfaces; software; Internet, Web, and digital library applications; machine translation for…

UNIVERSAL TRANSLATOR,

DTIC Science & Technology

all languages with the aid of electron machines is being derived to show how easy it would be to decode even ’dead’ languages, and languages of the foginess of Andromeda , if such a language ever existed. (Author)

Development and Evaluation of Heartbeat: A Machine Perfusion Heart Preservation System.

PubMed

Li, Yongnan; Zeng, Qingdong; Liu, Gang; Du, Junzhe; Gao, Bingren; Wang, Wei; Zheng, Zhe; Hu, Shengshou; Ji, Bingyang

2017-11-01

Static cold storage is accompanied with a partial safe ischemic interval for donor hearts. In this current study, a machine perfusion system was built to provide a better preservation for the donor heart and assessment for myocardial function. Chinese mini-swine (weight 30-35 kg, n = 16) were randomly divided into HTK, Celsior, and Heartbeat groups. All donor hearts were respectively preserved for 8 hours under static cold storage or machine perfusion. The perfusion solution is aimed to maintain its homeostasis based on monitoring the Heartbeat group. The ultrastructure of myocardium suggests better myocardial protection in the Heartbeat group compared with HTK or Celsior-preserved hearts. The myocardial and coronary artery structural and functional integrity was evaluated by immunofluorescence and Western blots in the Heartbeat. In the Heartbeat group, donor hearts maintained a high adenosine triphosphate level. Bcl-2 and Beclin-1 protein demonstrates high expression in the Celsior group. The Heartbeat system can be used to preserve donor hearts, and it could guarantee the myocardial and endothelial function of hearts during machine perfusion. Translating Heartbeat into clinical practice, it is such as to impact on donor heart preservation for cardiac transplantation. © 2017 International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

Mechatronics technology in predictive maintenance method

NASA Astrophysics Data System (ADS)

Majid, Nurul Afiqah A.; Muthalif, Asan G. A.

2017-11-01

This paper presents recent mechatronics technology that can help to implement predictive maintenance by combining intelligent and predictive maintenance instrument. Vibration Fault Simulation System (VFSS) is an example of mechatronics system. The focus of this study is the prediction on the use of critical machines to detect vibration. Vibration measurement is often used as the key indicator of the state of the machine. This paper shows the choice of the appropriate strategy in the vibration of diagnostic process of the mechanical system, especially rotating machines, in recognition of the failure during the working process. In this paper, the vibration signature analysis is implemented to detect faults in rotary machining that includes imbalance, mechanical looseness, bent shaft, misalignment, missing blade bearing fault, balancing mass and critical speed. In order to perform vibration signature analysis for rotating machinery faults, studies have been made on how mechatronics technology is used as predictive maintenance methods. Vibration Faults Simulation Rig (VFSR) is designed to simulate and understand faults signatures. These techniques are based on the processing of vibrational data in frequency-domain. The LabVIEW-based spectrum analyzer software is developed to acquire and extract frequency contents of faults signals. This system is successfully tested based on the unique vibration fault signatures that always occur in a rotating machinery.

Neural Networks for Computer Vision: A Framework for Specifications of a General Purpose Vision System

NASA Astrophysics Data System (ADS)

Skrzypek, Josef; Mesrobian, Edmond; Gungner, David J.

1989-03-01

The development of autonomous land vehicles (ALV) capable of operating in an unconstrained environment has proven to be a formidable research effort. The unpredictability of events in such an environment calls for the design of a robust perceptual system, an impossible task requiring the programming of a system bases on the expectation of future, unconstrained events. Hence, the need for a "general purpose" machine vision system that is capable of perceiving and understanding images in an unconstrained environment in real-time. The research undertaken at the UCLA Machine Perception Laboratory addresses this need by focusing on two specific issues: 1) the long term goals for machine vision research as a joint effort between the neurosciences and computer science; and 2) a framework for evaluating progress in machine vision. In the past, vision research has been carried out independently within different fields including neurosciences, psychology, computer science, and electrical engineering. Our interdisciplinary approach to vision research is based on the rigorous combination of computational neuroscience, as derived from neurophysiology and neuropsychology, with computer science and electrical engineering. The primary motivation behind our approach is that the human visual system is the only existing example of a "general purpose" vision system and using a neurally based computing substrate, it can complete all necessary visual tasks in real-time.

Joint optimization of maintenance, buffers and machines in manufacturing lines

NASA Astrophysics Data System (ADS)

Nahas, Nabil; Nourelfath, Mustapha

2018-01-01

This article considers a series manufacturing line composed of several machines separated by intermediate buffers of finite capacity. The goal is to find the optimal number of preventive maintenance actions performed on each machine, the optimal selection of machines and the optimal buffer allocation plan that minimize the total system cost, while providing the desired system throughput level. The mean times between failures of all machines are assumed to increase when applying periodic preventive maintenance. To estimate the production line throughput, a decomposition method is used. The decision variables in the formulated optimal design problem are buffer levels, types of machines and times between preventive maintenance actions. Three heuristic approaches are developed to solve the formulated combinatorial optimization problem. The first heuristic consists of a genetic algorithm, the second is based on the nonlinear threshold accepting metaheuristic and the third is an ant colony system. The proposed heuristics are compared and their efficiency is shown through several numerical examples. It is found that the nonlinear threshold accepting algorithm outperforms the genetic algorithm and ant colony system, while the genetic algorithm provides better results than the ant colony system for longer manufacturing lines.

A machine learning approach to computer-aided molecular design

NASA Astrophysics Data System (ADS)

Bolis, Giorgio; Di Pace, Luigi; Fabrocini, Filippo

1991-12-01

Preliminary results of a machine learning application concerning computer-aided molecular design applied to drug discovery are presented. The artificial intelligence techniques of machine learning use a sample of active and inactive compounds, which is viewed as a set of positive and negative examples, to allow the induction of a molecular model characterizing the interaction between the compounds and a target molecule. The algorithm is based on a twofold phase. In the first one — the specialization step — the program identifies a number of active/inactive pairs of compounds which appear to be the most useful in order to make the learning process as effective as possible and generates a dictionary of molecular fragments, deemed to be responsible for the activity of the compounds. In the second phase — the generalization step — the fragments thus generated are combined and generalized in order to select the most plausible hypothesis with respect to the sample of compounds. A knowledge base concerning physical and chemical properties is utilized during the inductive process.

Progress in development of coated indexable cemented carbide inserts for machining of iron based work piece materials

NASA Astrophysics Data System (ADS)

Czettl, C.; Pohler, M.

2016-03-01

Increasing demands on material properties of iron based work piece materials, e.g. for the turbine industry, complicate the machining process and reduce the lifetime of the cutting tools. Therefore, improved tool solutions, adapted to the requirements of the desired application have to be developed. Especially, the interplay of macro- and micro geometry, substrate material, coating and post treatment processes is crucial for the durability of modern high performance tool solutions. Improved and novel analytical methods allow a detailed understanding of material properties responsible for the wear behaviour of the tools. Those support the knowledge based development of tailored cutting materials for selected applications. One important factor for such a solution is the proper choice of coating material, which can be synthesized by physical or chemical vapor deposition techniques. Within this work an overview of state-of-the-art coated carbide grades is presented and application examples are shown to demonstrate their high efficiency. Machining processes for a material range from cast iron, low carbon steels to high alloyed steels are covered.

Identifying translational science within the triangle of biomedicine

PubMed Central

2013-01-01

Background The National Institutes of Health (NIH) Roadmap places special emphasis on “bench-to-bedside” research, or the “translation” of basic science research into practical clinical applications. The Clinical and Translational Science Awards (CTSA) Consortium is one example of the large investments being made to develop a national infrastructure to support translational science, which involves reducing regulatory burdens, launching new educational initiatives, and forming partnerships between academia and industry. However, while numerous definitions have been suggested for translational science, including the qualitative T1-T4 classification, a consensus has not yet been reached. This makes it challenging to tract the impact of these major policy changes. Methods In this study, we use a bibliometric approach to map PubMed articles onto a graph, called the Triangle of Biomedicine. The corners of the triangle represent research related to animals, cells and molecules, and humans; and, the position of a publication on the graph is based on its topics, as determined by its Medical Subject Headings (MeSH). We define translation as movement of a collection of articles, or the articles that cite those articles, towards the human corner. Results The Triangle of Biomedicine provides a quantitative way of determining if an individual scientist, research organization, funding agency, or scientific field is producing results that are relevant to clinical medicine. We validate our technique using examples that have been previously described in the literature and by comparing it to prior methods of measuring translational science. Conclusions The Triangle of Biomedicine is a novel way to identify translational science and track changes over time. This is important to policy makers in evaluating the impact of the large investments being made to accelerate translation. The Triangle of Biomedicine also provides a simple visual way of depicting this impact, which can be far more powerful than numbers alone. PMID:23705970

Integrating robotic action with biologic perception: A brain-machine symbiosis theory

NASA Astrophysics Data System (ADS)

Mahmoudi, Babak

In patients with motor disability the natural cyclic flow of information between the brain and external environment is disrupted by their limb impairment. Brain-Machine Interfaces (BMIs) aim to provide new communication channels between the brain and environment by direct translation of brain's internal states into actions. For enabling the user in a wide range of daily life activities, the challenge is designing neural decoders that autonomously adapt to different tasks, environments, and to changes in the pattern of neural activity. In this dissertation, a novel decoding framework for BMIs is developed in which a computational agent autonomously learns how to translate neural states into action based on maximization of a measure of shared goal between user and the agent. Since the agent and brain share the same goal, a symbiotic relationship between them will evolve therefore this decoding paradigm is called a Brain-Machine Symbiosis (BMS) framework. A decoding agent was implemented within the BMS framework based on the Actor-Critic method of Reinforcement Learning. The rule of the Actor as a neural decoder was to find mapping between the neural representation of motor states in the primary motor cortex (MI) and robot actions in order to solve reaching tasks. The Actor learned the optimal control policy using an evaluative feedback that was estimated by the Critic directly from the user's neural activity of the Nucleus Accumbens (NAcc). Through a series of computational neuroscience studies in a cohort of rats it was demonstrated that NAcc could provide a useful evaluative feedback by predicting the increase or decrease in the probability of earning reward based on the environmental conditions. Using a closed-loop BMI simulator it was demonstrated the Actor-Critic decoding architecture was able to adapt to different tasks as well as changes in the pattern of neural activity. The custom design of a dual micro-wire array enabled simultaneous implantation of MI and NAcc for the development of a full closed-loop system. The Actor-Critic decoding architecture was able to solve the brain-controlled reaching task using a robotic arm by capturing the interdependency between the simultaneous action representation in MI and reward expectation in NAcc.

A wearable computing platform for developing cloud-based machine learning models for health monitoring applications.

PubMed

Patel, Shyamal; McGinnis, Ryan S; Silva, Ikaro; DiCristofaro, Steve; Mahadevan, Nikhil; Jortberg, Elise; Franco, Jaime; Martin, Albert; Lust, Joseph; Raj, Milan; McGrane, Bryan; DePetrillo, Paolo; Aranyosi, A J; Ceruolo, Melissa; Pindado, Jesus; Ghaffari, Roozbeh

2016-08-01

Wearable sensors have the potential to enable clinical-grade ambulatory health monitoring outside the clinic. Technological advances have enabled development of devices that can measure vital signs with great precision and significant progress has been made towards extracting clinically meaningful information from these devices in research studies. However, translating measurement accuracies achieved in the controlled settings such as the lab and clinic to unconstrained environments such as the home remains a challenge. In this paper, we present a novel wearable computing platform for unobtrusive collection of labeled datasets and a new paradigm for continuous development, deployment and evaluation of machine learning models to ensure robust model performance as we transition from the lab to home. Using this system, we train activity classification models across two studies and track changes in model performance as we go from constrained to unconstrained settings.

A Prototype SSVEP Based Real Time BCI Gaming System

PubMed Central

Martišius, Ignas

2016-01-01

Although brain-computer interface technology is mainly designed with disabled people in mind, it can also be beneficial to healthy subjects, for example, in gaming or virtual reality systems. In this paper we discuss the typical architecture, paradigms, requirements, and limitations of electroencephalogram-based gaming systems. We have developed a prototype three-class brain-computer interface system, based on the steady state visually evoked potentials paradigm and the Emotiv EPOC headset. An online target shooting game, implemented in the OpenViBE environment, has been used for user feedback. The system utilizes wave atom transform for feature extraction, achieving an average accuracy of 78.2% using linear discriminant analysis classifier, 79.3% using support vector machine classifier with a linear kernel, and 80.5% using a support vector machine classifier with a radial basis function kernel. PMID:27051414

A Prototype SSVEP Based Real Time BCI Gaming System.

PubMed

Martišius, Ignas; Damaševičius, Robertas

2016-01-01

Although brain-computer interface technology is mainly designed with disabled people in mind, it can also be beneficial to healthy subjects, for example, in gaming or virtual reality systems. In this paper we discuss the typical architecture, paradigms, requirements, and limitations of electroencephalogram-based gaming systems. We have developed a prototype three-class brain-computer interface system, based on the steady state visually evoked potentials paradigm and the Emotiv EPOC headset. An online target shooting game, implemented in the OpenViBE environment, has been used for user feedback. The system utilizes wave atom transform for feature extraction, achieving an average accuracy of 78.2% using linear discriminant analysis classifier, 79.3% using support vector machine classifier with a linear kernel, and 80.5% using a support vector machine classifier with a radial basis function kernel.

78 FR 21891 - Rural Call Completion

Federal Register 2010, 2011, 2012, 2013, 2014

2013-04-12

... traffic may not be blocked, choked, reduced, or restricted, we have learned that carriers often do not... called party, including, for example, by voicemail, answering machine, or fax machine. We calculate a...

Design and Development of an Engineering Prototype Compact X-Ray Scanner (FMS 5000)

DTIC Science & Technology

1989-03-31

machined by "wire-EDM" (electro discharge machining ). Three different slice thicknesses can be selected from the scan menu. The set of slice thicknesses...circuit. This type of circuit is used whenever more than ten kilowatts of power are needed by a machine . For example, lathes and milling machines in a... machine shop usually use this type of input power. A three- phase circuit delivers power more efficiently than a single-phase circuit because three

Applications of General Systems Theory to the Development of an Adjustable Tutorial Software Machine.

ERIC Educational Resources Information Center

Vos, Hans J.

1994-01-01

Describes the construction of a model of computer-assisted instruction using a qualitative block diagram based on general systems theory (GST) as a framework. Subject matter representation is discussed, and appendices include system variables and system equations of the GST model, as well as an example of developing flexible courseware. (Contains…

Periodical capacity setting methods for make-to-order multi-machine production systems

PubMed Central

Altendorfer, Klaus; Hübl, Alexander; Jodlbauer, Herbert

2014-01-01

The paper presents different periodical capacity setting methods for make-to-order, multi-machine production systems with stochastic customer required lead times and stochastic processing times to improve service level and tardiness. These methods are developed as decision support when capacity flexibility exists, such as, a certain range of possible working hours a week for example. The methods differ in the amount of information used whereby all are based on the cumulated capacity demand at each machine. In a simulation study the methods’ impact on service level and tardiness is compared to a constant provided capacity for a single and a multi-machine setting. It is shown that the tested capacity setting methods can lead to an increase in service level and a decrease in average tardiness in comparison to a constant provided capacity. The methods using information on processing time and customer required lead time distribution perform best. The results found in this paper can help practitioners to make efficient use of their flexible capacity. PMID:27226649

Application of Elements of TPM Strategy for Operation Analysis of Mining Machine

NASA Astrophysics Data System (ADS)

Brodny, Jaroslaw; Tutak, Magdalena

2017-12-01

Total Productive Maintenance (TPM) strategy includes group of activities and actions in order to maintenance machines in failure-free state and without breakdowns thanks to tending limitation of failures, non-planned shutdowns, lacks and non-planned service of machines. These actions are ordered to increase effectiveness of utilization of possessed devices and machines in company. Very significant element of this strategy is connection of technical actions with changes in their perception by employees. Whereas fundamental aim of introduction this strategy is improvement of economic efficiency of enterprise. Increasing competition and necessity of reduction of production costs causes that also mining enterprises are forced to introduce this strategy. In the paper examples of use of OEE model for quantitative evaluation of selected mining devices were presented. OEE model is quantitative tool of TPM strategy and can be the base for further works connected with its introduction. OEE indicator is the product of three components which include availability and performance of the studied machine and the quality of the obtained product. The paper presents the results of the effectiveness analysis of the use of a set of mining machines included in the longwall system, which is the first and most important link in the technological line of coal production. The set of analyzed machines included the longwall shearer, armored face conveyor and cruscher. From a reliability point of view, the analyzed set of machines is a system that is characterized by the serial structure. The analysis was based on data recorded by the industrial automation system used in the mines. This method of data acquisition ensured their high credibility and a full time synchronization. Conclusions from the research and analyses should be used to reduce breakdowns, failures and unplanned downtime, increase performance and improve production quality.

The Riddle of the Smart Machines

ERIC Educational Resources Information Center

Howell, Dusti D.

2010-01-01

Hundreds of graduate students were introduced to the fields of instructional design and educational technology with the riddle of the smart machines, yet over the years no one has answered it correctly. After revealing the surprising answer to this riddle, both the negative and positive impacts of smart machines are analyzed. An example of this is…

The Role of Automata and Machine Theory in School and College Mathematics Syllabuses.

ERIC Educational Resources Information Center

Holcombe, M.

1981-01-01

The introduction of certain topics in the theory of machines and languages into school and college mathematics courses in place of the more usual discussion of groups and formal logic is proposed. Examples of machines and languages and their interconnections suitable for such courses are outlined. (MP)

Translating climate change effects on species into everyday language: an example of more driving and less fishing

USGS Publications Warehouse

Wagner, Tyler; Jefferson T. Deweber,

2015-01-01

Climate science is a complex issue, and we argue that when communicating potential responses of vegetation, fish, and wildlife to nonscientists, creative thinking with respect to the currency of communication will facilitate discussions between scientists, policy makers, and the public. We posit that with some additional thought and relatively simple summaries, the responses of fish and other species to climate change can be translated into everyday language that will facilitate climate science communication. Although such translations are rare, one example of this type of creativity is the translation from changes in habitat suitability for tree species to potential reductions in maple syrup production (West over 2012), which is arguably more interesting and understandable for the general public. Similar translations could be especially important for communicating climate change effects on game fish and other species that are socially and economically important to large groups of people. We demonstrate this translation by communicating the potential effects of climate change on the distribution of a coldwater fish species, the eastern Brook Trout Salvelinus fontinalis. Rather than communicating the potential forecasted contraction of the Brook Trout's distribution in terms of habitat loss, we report the predicted increases in the driving distance to streams likely offering Brook Trout angling opportunities under a climate change scenario. Travel costs based on distance have been widely used to value ecosystem services such as angling under climate change scenarios (e.g., Pendleton and Mendelsohn 1998; Mendelsohn and Markowski 1999; Ahn et al. 2000) but, to the best of our knowledge, have not been used for communicating potential changes to the public despite the intrinsic link to everyday life.

Towards a molecular logic machine

NASA Astrophysics Data System (ADS)

Remacle, F.; Levine, R. D.

2001-06-01

Finite state logic machines can be realized by pump-probe spectroscopic experiments on an isolated molecule. The most elaborate setup, a Turing machine, can be programmed to carry out a specific computation. We argue that a molecule can be similarly programmed, and provide examples using two photon spectroscopies. The states of the molecule serve as the possible states of the head of the Turing machine and the physics of the problem determines the possible instructions of the program. The tape is written in an alphabet that allows the listing of the different pump and probe signals that are applied in a given experiment. Different experiments using the same set of molecular levels correspond to different tapes that can be read and processed by the same head and program. The analogy to a Turing machine is not a mechanical one and is not completely molecular because the tape is not part of the molecular machine. We therefore also discuss molecular finite state machines, such as sequential devices, for which the tape is not part of the machine. Nonmolecular tapes allow for quite long input sequences with a rich alphabet (at the level of 7 bits) and laser pulse shaping experiments provide concrete examples. Single molecule spectroscopies show that a single molecule can be repeatedly cycled through a logical operation.

Isogeometric analysis and harmonic stator-rotor coupling for simulating electric machines

NASA Astrophysics Data System (ADS)

Bontinck, Zeger; Corno, Jacopo; Schöps, Sebastian; De Gersem, Herbert

2018-06-01

This work proposes Isogeometric Analysis as an alternative to classical finite elements for simulating electric machines. Through the spline-based Isogeometric discretization it is possible to parametrize the circular arcs exactly, thereby avoiding any geometrical error in the representation of the air gap where a high accuracy is mandatory. To increase the generality of the method, and to allow rotation, the rotor and the stator computational domains are constructed independently as multipatch entities. The two subdomains are then coupled using harmonic basis functions at the interface which gives rise to a saddle-point problem. The properties of Isogeometric Analysis combined with harmonic stator-rotor coupling are presented. The results and performance of the new approach are compared to the ones for a classical finite element method using a permanent magnet synchronous machine as an example.

Applying Process Improvement Methods to Clinical and Translational Research: Conceptual Framework and Case Examples.

PubMed

Daudelin, Denise H; Selker, Harry P; Leslie, Laurel K

2015-12-01

There is growing appreciation that process improvement holds promise for improving quality and efficiency across the translational research continuum but frameworks for such programs are not often described. The purpose of this paper is to present a framework and case examples of a Research Process Improvement Program implemented at Tufts CTSI. To promote research process improvement, we developed online training seminars, workshops, and in-person consultation models to describe core process improvement principles and methods, demonstrate the use of improvement tools, and illustrate the application of these methods in case examples. We implemented these methods, as well as relational coordination theory, with junior researchers, pilot funding awardees, our CTRC, and CTSI resource and service providers. The program focuses on capacity building to address common process problems and quality gaps that threaten the efficient, timely and successful completion of clinical and translational studies. © 2015 The Authors. Clinical and Translational Science published by Wiley Periodicals, Inc.

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

PubMed

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

2015-10-09

The construction of EBMPracticeNet, a national electronic point-of-care information platform in Belgium, began in 2011 to optimize quality of care by promoting evidence-based decision making. The project involved, among other tasks, the translation of 940 EBM Guidelines of Duodecim Medical Publications from English into Dutch and French. Considering the scale of the translation process, it was decided to make use of computer-aided translation performed by certificated translators with limited expertise in medical translation. Our consortium used a hybrid approach, involving a human translator supported by a translation memory (using SDL Trados Studio), terminology recognition (using SDL MultiTerm terminology databases) from medical terminology databases, and support from online machine translation. This resulted in a validated translation memory, which is now in use for the translation of new and updated guidelines. The objective of this experiment was to evaluate the performance of the hybrid human and computer-assisted approach in comparison with translation unsupported by translation memory and terminology recognition. A comparison was also made with the translation efficiency of an expert medical translator. We conducted a pilot study in which two sets of 30 new and 30 updated guidelines were randomized to one of three groups. Comparable guidelines were translated (1) by certificated junior translators without medical specialization using the hybrid method, (2) by an experienced medical translator without this support, and (3) by the same junior translators without the support of the validated translation memory. A medical proofreader who was blinded for the translation procedure, evaluated the translated guidelines for acceptability and adequacy. Translation speed was measured by recording translation and post-editing time. The human translation edit rate was calculated as a metric to evaluate the quality of the translation. A further evaluation was made of translation acceptability and adequacy. The average number of words per guideline was 1195 and the mean total translation time was 100.2 minutes/1000 words. No meaningful differences were found in the translation speed for new guidelines. The translation of updated guidelines was 59 minutes/1000 words faster (95% CI 2-115; P=.044) in the computer-aided group. Revisions due to terminology accounted for one third of the overall revisions by the medical proofreader. Use of the hybrid human and computer-aided translation by a non-expert translator makes the translation of updates of clinical practice guidelines faster and cheaper because of the benefits of translation memory. For the translation of new guidelines, there was no apparent benefit in comparison with the efficiency of translation unsupported by translation memory (whether by an expert or non-expert translator).

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

PubMed Central

2015-01-01

Background The construction of EBMPracticeNet, a national electronic point-of-care information platform in Belgium, began in 2011 to optimize quality of care by promoting evidence-based decision making. The project involved, among other tasks, the translation of 940 EBM Guidelines of Duodecim Medical Publications from English into Dutch and French. Considering the scale of the translation process, it was decided to make use of computer-aided translation performed by certificated translators with limited expertise in medical translation. Our consortium used a hybrid approach, involving a human translator supported by a translation memory (using SDL Trados Studio), terminology recognition (using SDL MultiTerm terminology databases) from medical terminology databases, and support from online machine translation. This resulted in a validated translation memory, which is now in use for the translation of new and updated guidelines. Objective The objective of this experiment was to evaluate the performance of the hybrid human and computer-assisted approach in comparison with translation unsupported by translation memory and terminology recognition. A comparison was also made with the translation efficiency of an expert medical translator. Methods We conducted a pilot study in which two sets of 30 new and 30 updated guidelines were randomized to one of three groups. Comparable guidelines were translated (1) by certificated junior translators without medical specialization using the hybrid method, (2) by an experienced medical translator without this support, and (3) by the same junior translators without the support of the validated translation memory. A medical proofreader who was blinded for the translation procedure, evaluated the translated guidelines for acceptability and adequacy. Translation speed was measured by recording translation and post-editing time. The human translation edit rate was calculated as a metric to evaluate the quality of the translation. A further evaluation was made of translation acceptability and adequacy. Results The average number of words per guideline was 1195 and the mean total translation time was 100.2 minutes/1000 words. No meaningful differences were found in the translation speed for new guidelines. The translation of updated guidelines was 59 minutes/1000 words faster (95% CI 2-115; P=.044) in the computer-aided group. Revisions due to terminology accounted for one third of the overall revisions by the medical proofreader. Conclusions Use of the hybrid human and computer-aided translation by a non-expert translator makes the translation of updates of clinical practice guidelines faster and cheaper because of the benefits of translation memory. For the translation of new guidelines, there was no apparent benefit in comparison with the efficiency of translation unsupported by translation memory (whether by an expert or non-expert translator). PMID:26453372

Experiments in balance with a 2D one-legged hopping machine

NASA Astrophysics Data System (ADS)

Raibert, M. H.; Brown, H. B., Jr.

1984-03-01

The ability to balance is important to the mobility obtained by legged creatures found in nature, and may someday lead to versatile legged vehicles. In order to study the role of balance in legged locomotion and to develop appropriate control strategies, a 2D hopping machine was constructed for experimentation. The machine has one leg on which it hops and runs, making balance a prime consideration. Control of the machine's locomotion was decomposed into three separate parts: a vertical height control part, a horizontal velocity part, and an angular attitude control part. Experiments showed that the three part control scheme, while very simple to implement, was powerful enough to permit the machine to hop in place, to run at a desired rate, to translate from place to place, and to leap over obstacles. Results from modeling and computer simulation of a similar one-legged device are described by Raibert (1983).

Non-stationary signal analysis based on general parameterized time-frequency transform and its application in the feature extraction of a rotary machine

NASA Astrophysics Data System (ADS)

Zhou, Peng; Peng, Zhike; Chen, Shiqian; Yang, Yang; Zhang, Wenming

2018-06-01

With the development of large rotary machines for faster and more integrated performance, the condition monitoring and fault diagnosis for them are becoming more challenging. Since the time-frequency (TF) pattern of the vibration signal from the rotary machine often contains condition information and fault feature, the methods based on TF analysis have been widely-used to solve these two problems in the industrial community. This article introduces an effective non-stationary signal analysis method based on the general parameterized time-frequency transform (GPTFT). The GPTFT is achieved by inserting a rotation operator and a shift operator in the short-time Fourier transform. This method can produce a high-concentrated TF pattern with a general kernel. A multi-component instantaneous frequency (IF) extraction method is proposed based on it. The estimation for the IF of every component is accomplished by defining a spectrum concentration index (SCI). Moreover, such an IF estimation process is iteratively operated until all the components are extracted. The tests on three simulation examples and a real vibration signal demonstrate the effectiveness and superiority of our method.

Development of a QFD-based expert system for CNC turning centre selection

NASA Astrophysics Data System (ADS)

Prasad, Kanika; Chakraborty, Shankar

2015-12-01

Computer numerical control (CNC) machine tools are automated devices capable of generating complicated and intricate product shapes in shorter time. Selection of the best CNC machine tool is a critical, complex and time-consuming task due to availability of a wide range of alternatives and conflicting nature of several evaluation criteria. Although, the past researchers had attempted to select the appropriate machining centres using different knowledge-based systems, mathematical models and multi-criteria decision-making methods, none of those approaches has given due importance to the voice of customers. The aforesaid limitation can be overcome using quality function deployment (QFD) technique, which is a systematic approach for integrating customers' needs and designing the product to meet those needs first time and every time. In this paper, the adopted QFD-based methodology helps in selecting CNC turning centres for a manufacturing organization, providing due importance to the voice of customers to meet their requirements. An expert system based on QFD technique is developed in Visual BASIC 6.0 to automate the CNC turning centre selection procedure for different production plans. Three illustrative examples are demonstrated to explain the real-time applicability of the developed expert system.

Model based PI power system stabilizer design for damping low frequency oscillations in power systems.

PubMed

Salgotra, Aprajita; Pan, Somnath

2018-05-01

This paper explores a two-level control strategy by blending local controller with centralized controller for the low frequency oscillations in a power system. The proposed control scheme provides stabilization of local modes using a local controller and minimizes the effect of inter-connection of sub-systems performance through a centralized control. For designing the local controllers in the form of proportional-integral power system stabilizer (PI-PSS), a simple and straight forward frequency domain direct synthesis method is considered that works on use of a suitable reference model which is based on the desired requirements. Several examples both on one machine infinite bus and multi-machine systems taken from the literature are illustrated to show the efficacy of the proposed PI-PSS. The effective damping of the systems is found to be increased remarkably which is reflected in the time-responses; even unstable operation has been stabilized with improved damping after applying the proposed controller. The proposed controllers give remarkable improvement in damping the oscillations in all the illustrations considered here and as for example, the value of damping factor has been increased from 0.0217 to 0.666 in Example 1. The simulation results obtained by the proposed control strategy are favourably compared with some controllers prevalent in the literature. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Translational Scholarship and a Palliative Approach: Enlisting the Knowledge-As-Action Framework.

PubMed

Reimer-Kirkham, Sheryl; Doane, Gweneth Hartrick; Antifeau, Elisabeth; Pesut, Barbara; Porterfield, Pat; Roberts, Della; Stajduhar, Kelli; Wikjord, Nicole

2015-01-01

Based on a retheorized epistemology for knowledge translation (KT) that problematizes the "know-do gap" and conceptualizes the knower, knowledge, and action as inseparable, this paper describes the application of the Knowledge-As-Action Framework. When applied as a heuristic device to support an inquiry process, the framework with the metaphor of a kite facilitates a responsiveness to the complexities that characterize KT. Examples from a KT demonstration project on the integration of a palliative approach at 3 clinical sites illustrate the interrelatedness of 6 dimensions-the local context, processes, people, knowledge, fluctuating realities, and values.

Automated benchmark generation based upon a specification language

NASA Technical Reports Server (NTRS)

Rajan, N.; Feteih, S. E.; Saito, J.

1984-01-01

The problem of validating and verifying digital flight control system (DFCS) software is addressed in this paper. A new specification language DIVERS is proposed, and is the keystone of the approach. This language consists of keywords where each keyword represents an element in the block diagram of a DFCS. DIVERS has a dictionary which contains all the keywords a DFCS designer might need. Translator programs convert the system specifications into an executable, high-level language program. The features of translators are discussed and are elucidated by examples. This language is used to describe a typical flight software module.

Strategies to promote practice nurse capacity to deliver evidence-based care: An example from sexual healthcare.

PubMed

Dadich, Ann; Abbott, Penny; Hosseinzadeh, Hassan

2015-01-01

Evidence-based practice is pivotal to effective patient care. However, its translation into practice remains limited. Given the central role of primary care in many healthcare systems, it is important to identify strategies that bolster clinician-capacity to promote evidence-based care. The purpose of this paper is to identify strategies to increase Practice Nurse capacity to promote evidence-based sexual healthcare within general practice. A survey of 217 Practice Nurses in an Australian state and ten respondent-interviews regarding two resources to promote evidence-based sexual healthcare - namely, a clinical aide and online training. The perceived impact of both resources was determined by views on relevance and design - particularly for the clinical aide. Resource-use was influenced by role and responsibilities within the workplace, accessibility, and support from patients and colleagues. This is the first Australian study to reveal strategies to promote evidence-based sexual healthcare among Practice Nurses. The findings provide a platform for future research on knowledge translation processes, particularly among clinicians who might be disengaged from sexual healthcare. Given the benefits of evidence-based practices, it is important that managers recognize their role, and the role of their services, in promoting these. Without explicit support for evidence-based care and recognition of the Practice Nurse role in such care, knowledge translation is likely to be limited. Knowledge translation among Practice Nurses can be facilitated by: resources-deemed informative, relevant, and user-friendly, as well as support from patients, colleagues, and their workplace.

Full-band error control and crack-free surface fabrication techniques for ultra-precision fly cutting of large-aperture KDP crystals

NASA Astrophysics Data System (ADS)

Zhang, F. H.; Wang, S. F.; An, C. H.; Wang, J.; Xu, Q.

2017-06-01

Large-aperture potassium dihydrogen phosphate (KDP) crystals are widely used in the laser path of inertial confinement fusion (ICF) systems. The most common method of manufacturing half-meter KDP crystals is ultra-precision fly cutting. When processing KDP crystals by ultra-precision fly cutting, the dynamic characteristics of the fly cutting machine and fluctuations in the fly cutting environment are translated into surface errors at different spatial frequency bands. These machining errors should be suppressed effectively to guarantee that KDP crystals meet the full-band machining accuracy specified in the evaluation index. In this study, the anisotropic machinability of KDP crystals and the causes of typical surface errors in ultra-precision fly cutting of the material are investigated. The structures of the fly cutting machine and existing processing parameters are optimized to improve the machined surface quality. The findings are theoretically and practically important in the development of high-energy laser systems in China.

Rewriting and Paraphrasing Source Texts in Second Language Writing

ERIC Educational Resources Information Center

Shi, Ling

2012-01-01

The present study is based on interviews with 48 students and 27 instructors in a North American university and explores whether students and professors across faculties share the same views on the use of paraphrased, summarized, and translated texts in four examples of L2 student writing. Participants' comments centered on whether the paraphrases…

Fine-Grained Linguistic Soft Constraints on Statistical Natural Language Processing Models

DTIC Science & Technology

2009-01-01

88 4 Monolingually -Derived Phrasal Paraphrase Generation for Statistical Ma- chine Translation 90 4.1...123 4.4 Spanish-English (S2E) results . . . . . . . . . . . . . . . . . . . . . . 125 4.5 Gains from using larger monolingual corpora for...96 4.2 Visual example of a phrasal distributional profile . . . . . . . . . . . . 103 4.3 Monolingual corpus-based distributional

Tasking and sharing sensing assets using controlled natural language

NASA Astrophysics Data System (ADS)

Preece, Alun; Pizzocaro, Diego; Braines, David; Mott, David

2012-06-01

We introduce an approach to representing intelligence, surveillance, and reconnaissance (ISR) tasks at a relatively high level in controlled natural language. We demonstrate that this facilitates both human interpretation and machine processing of tasks. More specically, it allows the automatic assignment of sensing assets to tasks, and the informed sharing of tasks between collaborating users in a coalition environment. To enable automatic matching of sensor types to tasks, we created a machine-processable knowledge representation based on the Military Missions and Means Framework (MMF), and implemented a semantic reasoner to match task types to sensor types. We combined this mechanism with a sensor-task assignment procedure based on a well-known distributed protocol for resource allocation. In this paper, we re-formulate the MMF ontology in Controlled English (CE), a type of controlled natural language designed to be readable by a native English speaker whilst representing information in a structured, unambiguous form to facilitate machine processing. We show how CE can be used to describe both ISR tasks (for example, detection, localization, or identication of particular kinds of object) and sensing assets (for example, acoustic, visual, or seismic sensors, mounted on motes or unmanned vehicles). We show how these representations enable an automatic sensor-task assignment process. Where a group of users are cooperating in a coalition, we show how CE task summaries give users in the eld a high-level picture of ISR coverage of an area of interest. This allows them to make ecient use of sensing resources by sharing tasks.

New algorithms for motion error detection of numerical control machine tool by laser tracking measurement on the basis of GPS principle.

PubMed

Wang, Jindong; Chen, Peng; Deng, Yufen; Guo, Junjie

2018-01-01

As a three-dimensional measuring instrument, the laser tracker is widely used in industrial measurement. To avoid the influence of angle measurement error on the overall measurement accuracy, the multi-station and time-sharing measurement with a laser tracker is introduced on the basis of the global positioning system (GPS) principle in this paper. For the proposed method, how to accurately determine the coordinates of each measuring point by using a large amount of measured data is a critical issue. Taking detecting motion error of a numerical control machine tool, for example, the corresponding measurement algorithms are investigated thoroughly. By establishing the mathematical model of detecting motion error of a machine tool with this method, the analytical algorithm concerning on base station calibration and measuring point determination is deduced without selecting the initial iterative value in calculation. However, when the motion area of the machine tool is in a 2D plane, the coefficient matrix of base station calibration is singular, which generates a distortion result. In order to overcome the limitation of the original algorithm, an improved analytical algorithm is also derived. Meanwhile, the calibration accuracy of the base station with the improved algorithm is compared with that with the original analytical algorithm and some iterative algorithms, such as the Gauss-Newton algorithm and Levenberg-Marquardt algorithm. The experiment further verifies the feasibility and effectiveness of the improved algorithm. In addition, the different motion areas of the machine tool have certain influence on the calibration accuracy of the base station, and the corresponding influence of measurement error on the calibration result of the base station depending on the condition number of coefficient matrix are analyzed.

New algorithms for motion error detection of numerical control machine tool by laser tracking measurement on the basis of GPS principle

NASA Astrophysics Data System (ADS)

Wang, Jindong; Chen, Peng; Deng, Yufen; Guo, Junjie

2018-01-01

As a three-dimensional measuring instrument, the laser tracker is widely used in industrial measurement. To avoid the influence of angle measurement error on the overall measurement accuracy, the multi-station and time-sharing measurement with a laser tracker is introduced on the basis of the global positioning system (GPS) principle in this paper. For the proposed method, how to accurately determine the coordinates of each measuring point by using a large amount of measured data is a critical issue. Taking detecting motion error of a numerical control machine tool, for example, the corresponding measurement algorithms are investigated thoroughly. By establishing the mathematical model of detecting motion error of a machine tool with this method, the analytical algorithm concerning on base station calibration and measuring point determination is deduced without selecting the initial iterative value in calculation. However, when the motion area of the machine tool is in a 2D plane, the coefficient matrix of base station calibration is singular, which generates a distortion result. In order to overcome the limitation of the original algorithm, an improved analytical algorithm is also derived. Meanwhile, the calibration accuracy of the base station with the improved algorithm is compared with that with the original analytical algorithm and some iterative algorithms, such as the Gauss-Newton algorithm and Levenberg-Marquardt algorithm. The experiment further verifies the feasibility and effectiveness of the improved algorithm. In addition, the different motion areas of the machine tool have certain influence on the calibration accuracy of the base station, and the corresponding influence of measurement error on the calibration result of the base station depending on the condition number of coefficient matrix are analyzed.

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

PubMed

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

2017-01-01

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

Knowledge-based machine indexing from natural language text: Knowledge base design, development, and maintenance

NASA Technical Reports Server (NTRS)

Genuardi, Michael T.

1993-01-01

One strategy for machine-aided indexing (MAI) is to provide a concept-level analysis of the textual elements of documents or document abstracts. In such systems, natural-language phrases are analyzed in order to identify and classify concepts related to a particular subject domain. The overall performance of these MAI systems is largely dependent on the quality and comprehensiveness of their knowledge bases. These knowledge bases function to (1) define the relations between a controlled indexing vocabulary and natural language expressions; (2) provide a simple mechanism for disambiguation and the determination of relevancy; and (3) allow the extension of concept-hierarchical structure to all elements of the knowledge file. After a brief description of the NASA Machine-Aided Indexing system, concerns related to the development and maintenance of MAI knowledge bases are discussed. Particular emphasis is given to statistically-based text analysis tools designed to aid the knowledge base developer. One such tool, the Knowledge Base Building (KBB) program, presents the domain expert with a well-filtered list of synonyms and conceptually-related phrases for each thesaurus concept. Another tool, the Knowledge Base Maintenance (KBM) program, functions to identify areas of the knowledge base affected by changes in the conceptual domain (for example, the addition of a new thesaurus term). An alternate use of the KBM as an aid in thesaurus construction is also discussed.

Machine-learning-assisted materials discovery using failed experiments

NASA Astrophysics Data System (ADS)

Raccuglia, Paul; Elbert, Katherine C.; Adler, Philip D. F.; Falk, Casey; Wenny, Malia B.; Mollo, Aurelio; Zeller, Matthias; Friedler, Sorelle A.; Schrier, Joshua; Norquist, Alexander J.

2016-05-01

Inorganic-organic hybrid materials such as organically templated metal oxides, metal-organic frameworks (MOFs) and organohalide perovskites have been studied for decades, and hydrothermal and (non-aqueous) solvothermal syntheses have produced thousands of new materials that collectively contain nearly all the metals in the periodic table. Nevertheless, the formation of these compounds is not fully understood, and development of new compounds relies primarily on exploratory syntheses. Simulation- and data-driven approaches (promoted by efforts such as the Materials Genome Initiative) provide an alternative to experimental trial-and-error. Three major strategies are: simulation-based predictions of physical properties (for example, charge mobility, photovoltaic properties, gas adsorption capacity or lithium-ion intercalation) to identify promising target candidates for synthetic efforts; determination of the structure-property relationship from large bodies of experimental data, enabled by integration with high-throughput synthesis and measurement tools; and clustering on the basis of similar crystallographic structure (for example, zeolite structure classification or gas adsorption properties). Here we demonstrate an alternative approach that uses machine-learning algorithms trained on reaction data to predict reaction outcomes for the crystallization of templated vanadium selenites. We used information on ‘dark’ reactions—failed or unsuccessful hydrothermal syntheses—collected from archived laboratory notebooks from our laboratory, and added physicochemical property descriptions to the raw notebook information using cheminformatics techniques. We used the resulting data to train a machine-learning model to predict reaction success. When carrying out hydrothermal synthesis experiments using previously untested, commercially available organic building blocks, our machine-learning model outperformed traditional human strategies, and successfully predicted conditions for new organically templated inorganic product formation with a success rate of 89 per cent. Inverting the machine-learning model reveals new hypotheses regarding the conditions for successful product formation.

Accelerating the Translation of Nanomaterials in Biomedicine

PubMed Central

Mitragotri, Samir; Anderson, Daniel G.; Chen, Xiaoyuan; Chow, Edward K.; Ho, Dean; Kabanov, Alexander V.; Karp, Jeffrey M.; Kataoka, Kazunori; Mirkin, Chad A.; Petrosko, Sarah Hurst; Shi, Jinjun; Stevens, Molly M.; Sun, Shouheng; Teoh, Sweehin; Venkatraman, Subbu S.; Xia, Younan; Wang, Shutao; Gu, Zhen; Xu, Chenjie

2017-01-01

Due to their size and tailorable physicochemical properties, nanomaterials are an emerging class of structures utilized in biomedical applications. There are now many prominent examples of nanomaterials being used to improve human health, in areas ranging from imaging and diagnostics to therapeutics and regenerative medicine. An overview of these examples reveals several common areas of synergy and future challenges. This Nano Focus discusses the current status and future potential of promising nanomaterials and their translation from the laboratory to the clinic, by highlighting a handful of successful examples. PMID:26115196

Abstract quantum computing machines and quantum computational logics

NASA Astrophysics Data System (ADS)

Chiara, Maria Luisa Dalla; Giuntini, Roberto; Sergioli, Giuseppe; Leporini, Roberto

2016-06-01

Classical and quantum parallelism are deeply different, although it is sometimes claimed that quantum Turing machines are nothing but special examples of classical probabilistic machines. We introduce the concepts of deterministic state machine, classical probabilistic state machine and quantum state machine. On this basis, we discuss the question: To what extent can quantum state machines be simulated by classical probabilistic state machines? Each state machine is devoted to a single task determined by its program. Real computers, however, behave differently, being able to solve different kinds of problems. This capacity can be modeled, in the quantum case, by the mathematical notion of abstract quantum computing machine, whose different programs determine different quantum state machines. The computations of abstract quantum computing machines can be linguistically described by the formulas of a particular form of quantum logic, termed quantum computational logic.

mRNA translation and protein synthesis: an analysis of different modelling methodologies and a new PBN based approach

PubMed Central

2014-01-01

Background mRNA translation involves simultaneous movement of multiple ribosomes on the mRNA and is also subject to regulatory mechanisms at different stages. Translation can be described by various codon-based models, including ODE, TASEP, and Petri net models. Although such models have been extensively used, the overlap and differences between these models and the implications of the assumptions of each model has not been systematically elucidated. The selection of the most appropriate modelling framework, and the most appropriate way to develop coarse-grained/fine-grained models in different contexts is not clear. Results We systematically analyze and compare how different modelling methodologies can be used to describe translation. We define various statistically equivalent codon-based simulation algorithms and analyze the importance of the update rule in determining the steady state, an aspect often neglected. Then a novel probabilistic Boolean network (PBN) model is proposed for modelling translation, which enjoys an exact numerical solution. This solution matches those of numerical simulation from other methods and acts as a complementary tool to analytical approximations and simulations. The advantages and limitations of various codon-based models are compared, and illustrated by examples with real biological complexities such as slow codons, premature termination and feedback regulation. Our studies reveal that while different models gives broadly similiar trends in many cases, important differences also arise and can be clearly seen, in the dependence of the translation rate on different parameters. Furthermore, the update rule affects the steady state solution. Conclusions The codon-based models are based on different levels of abstraction. Our analysis suggests that a multiple model approach to understanding translation allows one to ascertain which aspects of the conclusions are robust with respect to the choice of modelling methodology, and when (and why) important differences may arise. This approach also allows for an optimal use of analysis tools, which is especially important when additional complexities or regulatory mechanisms are included. This approach can provide a robust platform for dissecting translation, and results in an improved predictive framework for applications in systems and synthetic biology. PMID:24576337

Multi-functional dielectric elastomer artificial muscles for soft and smart machines

NASA Astrophysics Data System (ADS)

Anderson, Iain A.; Gisby, Todd A.; McKay, Thomas G.; O'Brien, Benjamin M.; Calius, Emilio P.

2012-08-01

Dielectric elastomer (DE) actuators are popularly referred to as artificial muscles because their impressive actuation strain and speed, low density, compliant nature, and silent operation capture many of the desirable physical properties of muscle. Unlike conventional robots and machines, whose mechanisms and drive systems rapidly become very complex as the number of degrees of freedom increases, groups of DE artificial muscles have the potential to generate rich motions combining many translational and rotational degrees of freedom. These artificial muscle systems can mimic the agonist-antagonist approach found in nature, so that active expansion of one artificial muscle is taken up by passive contraction in the other. They can also vary their stiffness. In addition, they have the ability to produce electricity from movement. But departing from the high stiffness paradigm of electromagnetic motors and gearboxes leads to new control challenges, and for soft machines to be truly dexterous like their biological analogues, they need precise control. Humans control their limbs using sensory feedback from strain sensitive cells embedded in muscle. In DE actuators, deformation is inextricably linked to changes in electrical parameters that include capacitance and resistance, so the state of strain can be inferred by sensing these changes, enabling the closed loop control that is critical for a soft machine. But the increased information processing required for a soft machine can impose a substantial burden on a central controller. The natural solution is to distribute control within the mechanism itself. The octopus arm is an example of a soft actuator with a virtually infinite number of degrees of freedom (DOF). The arm utilizes neural ganglia to process sensory data at the local "arm" level and perform complex tasks. Recent advances in soft electronics such as the piezoresistive dielectric elastomer switch (DES) have the potential to be fully integrated with actuators and sensors. With the DE switch, we can produce logic gates, oscillators, and a memory element, the building blocks for a soft computer, thus bringing us closer to emulating smart living structures like the octopus arm. The goal of future research is to develop fully soft machines that exploit smart actuation networks to gain capabilities formerly reserved to nature, and open new vistas in mechanical engineering.

Method and apparatus for characterizing and enhancing the dynamic performance of machine tools

DOEpatents

Barkman, William E; Babelay, Jr., Edwin F

2013-12-17

Disclosed are various systems and methods for assessing and improving the capability of a machine tool. The disclosure applies to machine tools having at least one slide configured to move along a motion axis. Various patterns of dynamic excitation commands are employed to drive the one or more slides, typically involving repetitive short distance displacements. A quantification of a measurable merit of machine tool response to the one or more patterns of dynamic excitation commands is typically derived for the machine tool. Examples of measurable merits of machine tool performance include dynamic one axis positional accuracy of the machine tool, dynamic cross-axis stability of the machine tool, and dynamic multi-axis positional accuracy of the machine tool.

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

PubMed Central

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

2015-01-01

Globalization of business and competitiveness in manufacturing has forced companies to improve their manufacturing facilities to respond to market requirements. Machine tool evaluation involves an essential decision using imprecise and vague information, and plays a major role to improve the productivity and flexibility in manufacturing. The aim of this study is to present an integrated approach for decision-making in machine tool selection. This paper is focused on the integration of a consistent fuzzy AHP (Analytic Hierarchy Process) and a fuzzy COmplex PRoportional ASsessment (COPRAS) for multi-attribute decision-making in selecting the most suitable machine tool. In this method, the fuzzy linguistic reference relation is integrated into AHP to handle the imprecise and vague information, and to simplify the data collection for the pair-wise comparison matrix of the AHP which determines the weights of attributes. The output of the fuzzy AHP is imported into the fuzzy COPRAS method for ranking alternatives through the closeness coefficient. Presentation of the proposed model application is provided by a numerical example based on the collection of data by questionnaire and from the literature. The results highlight the integration of the improved fuzzy AHP and the fuzzy COPRAS as a precise tool and provide effective multi-attribute decision-making for evaluating the machine tool in the uncertain environment. PMID:26368541

Insights and limits of translational research in critical care medicine.

PubMed

Pène, Frédéric; Ait-Oufella, Hafid; Taccone, Fabio Silvio; Monneret, Guillaume; Sharshar, Tarek; Tamion, Fabienne; Mira, Jean-Paul

2015-01-01

Experimental research has always been the cornerstone of pathophysiological and therapeutic advances in critical care medicine, where clinical observations and basic research mutually fed each other in a so-called translational approach. The objective of this review is to address the different aspects of translational research in the field of critical care medicine. We herein highlighted some demonstrative examples including the animal-to-human approach to study host-pathogen interactions, the human-to-animal approach for sepsis-induced immunosuppression, the still restrictive human approach to study critical illness-related neuromyopathy, and the technological developments to assess the microcirculatory changes in critically ill patients. These examples not only emphasize how translational research resulted in major improvements in the comprehension of the pathophysiology of severe clinical conditions and offered promising perspectives in critical care medicine but also point out the obstacles to translate such achievements into clinical practice.

Evaluating a Pivot-Based Approach for Bilingual Lexicon Extraction

PubMed Central

Kim, Jae-Hoon; Kwon, Hong-Seok; Seo, Hyeong-Won

2015-01-01

A pivot-based approach for bilingual lexicon extraction is based on the similarity of context vectors represented by words in a pivot language like English. In this paper, in order to show validity and usability of the pivot-based approach, we evaluate the approach in company with two different methods for estimating context vectors: one estimates them from two parallel corpora based on word association between source words (resp., target words) and pivot words and the other estimates them from two parallel corpora based on word alignment tools for statistical machine translation. Empirical results on two language pairs (e.g., Korean-Spanish and Korean-French) have shown that the pivot-based approach is very promising for resource-poor languages and this approach observes its validity and usability. Furthermore, for words with low frequency, our method is also well performed. PMID:25983745

Energy Landscapes: From Protein Folding to Molecular Assembly

Science.gov Websites

been used, for example, in DNA origami, in which artificial structures and machines are built in a mechanical processes and eventually to reproduce these in artificial machines. This conference will provide

Using Phun to Study "Perpetual Motion" Machines

ERIC Educational Resources Information Center

Kores, Jaroslav

2012-01-01

The concept of "perpetual motion" has a long history. The Indian astronomer and mathematician Bhaskara II (12th century) was the first person to describe a perpetual motion (PM) machine. An example of a 13th-century PM machine is shown in Fig. 1. Although the law of conservation of energy clearly implies the impossibility of PM construction, over…

Translating tuberculosis research into global policies: the example of an international collaboration on diagnostics.

PubMed

Ramsay, A; Steingart, K R; Cunningham, J; Pai, M

2011-10-01

Using the example of an international collaboration on tuberculosis (TB) diagnostics, we mapped the key stages and stakeholders involved in translating research into global policies. In our experience, the process begins with advocacy for high-quality, policy-relevant research and appropriate funding. Following the assessment of current policy and the identification of key study areas, policy-relevant research questions need to be formulated and prioritised. It is important that a framework for translating evidence into policy at the target policymaking level, in this case global, is available to researchers. This ensures that research questions, study designs and research standards are appropriate to the type and quality of evidence required. The framework may evolve during the period of research and, as evidence requirements may change, vigilance is required. Formal and informal multi-stakeholder partnerships, as well as information sharing through extensive networking, facilitate efficient building of a broad evidence base. Coordination of activities by an international, neutral body with strong convening powers is important, as is regular interaction with policy makers. It is recognised that studies on diagnostic accuracy provide weak evidence that a new diagnostic will improve patient care when implemented to scale in routine settings. This may be one reason why there has been poor uptake of new tools by national TB control programmes despite global policy recommendations. Stronger engagement with national policy makers and donors during the research-intopolicy process may be needed to ensure that their evidence requirements are met and that global policies translate into national policies. National policies are central to translating global policies into practice.

A review of translational medicine. The future paradigm: how can we connect the orthopedic dots better?

PubMed

Mediouni, Mohamed; R Schlatterer, Daniel; Madry, Henning; Cucchiarini, Magali; Rai, Balwant

2017-11-01

Patients with complex medical and surgical problems often travel great distances to prestigious university medical centers in search of solutions and in some cases for nothing more than a diagnosis of their condition. Translational medicine (TM) is an emerging method and process of facilitating medical advances efficiently from the scientist to the clinician. Most established clinicians and those in training know very little about this new discipline. The purpose of this article is to illustrate TM in varied scientific, medical and surgical fields. Anecdotal events in medicine and orthopaedics based upon a practicing orthopaedic surgeon's training and clinical experience are presented. TM is rapidly assuming a greater presence in the medical community. The National Institute of Health (NIH) recognizes this discipline and has funded TM projects. Numerous institutions in Europe and the USA offer advanced degrees in TM. Finally there is a European Society for Translational Medicine (EUTMS), an International Society for Translational Medicine, and an Academy of Translational Medical Professionals (ATMP). The examples of TM presented in this article support the argument for the formation of more TM networks on the local and regional levels. The need for increased participation of researchers and clinicians requires further study to identify the economic and social impact of TM. The examples of TM presented in this article support the argument for the formation of more TM networks on the local and regional levels. Financial constraints for TM can be overcome by pooling government, academic, private, and industry resources in an organized fashion with oversight by a lead TM researcher.

Electromagnetic variable degrees of freedom actuator systems and methods

DOEpatents

Montesanti, Richard C [Pleasanton, CA; Trumper, David L [Plaistow, NH; Kirtley, Jr., James L.

2009-02-17

The present invention provides a variable reluctance actuator system and method that can be adapted for simultaneous rotation and translation of a moving element by applying a normal-direction magnetic flux on the moving element. In a beneficial example arrangement, the moving element includes a swing arm that carries a cutting tool at a set radius from an axis of rotation so as to produce a rotary fast tool servo that provides a tool motion in a direction substantially parallel to the surface-normal of a workpiece at the point of contact between the cutting tool and workpiece. An actuator rotates a swing arm such that a cutting tool moves toward and away from a mounted rotating workpiece in a controlled manner in order to machine the workpiece. Position sensors provide rotation and displacement information for a swing arm to a control system. A control system commands and coordinates motion of the fast tool servo with the motion of a spindle, rotating table, cross-feed slide, and in feed slide of a precision lathe.

Kanerva's sparse distributed memory: An associative memory algorithm well-suited to the Connection Machine

NASA Technical Reports Server (NTRS)

Rogers, David

1988-01-01

The advent of the Connection Machine profoundly changes the world of supercomputers. The highly nontraditional architecture makes possible the exploration of algorithms that were impractical for standard Von Neumann architectures. Sparse distributed memory (SDM) is an example of such an algorithm. Sparse distributed memory is a particularly simple and elegant formulation for an associative memory. The foundations for sparse distributed memory are described, and some simple examples of using the memory are presented. The relationship of sparse distributed memory to three important computational systems is shown: random-access memory, neural networks, and the cerebellum of the brain. Finally, the implementation of the algorithm for sparse distributed memory on the Connection Machine is discussed.

Machine learning with quantum relative entropy

NASA Astrophysics Data System (ADS)

Tsuda, Koji

2009-12-01

Density matrices are a central tool in quantum physics, but it is also used in machine learning. A positive definite matrix called kernel matrix is used to represent the similarities between examples. Positive definiteness assures that the examples are embedded in an Euclidean space. When a positive definite matrix is learned from data, one has to design an update rule that maintains the positive definiteness. Our update rule, called matrix exponentiated gradient update, is motivated by the quantum relative entropy. Notably, the relative entropy is an instance of Bregman divergences, which are asymmetric distance measures specifying theoretical properties of machine learning algorithms. Using the calculus commonly used in quantum physics, we prove an upperbound of the generalization error of online learning.

Are we there yet?

PubMed

Cristianini, Nello

2010-05-01

Statistical approaches to Artificial Intelligence are behind most success stories of the field in the past decade. The idea of generating non-trivial behaviour by analysing vast amounts of data has enabled recommendation systems, search engines, spam filters, optical character recognition, machine translation and speech recognition, among other things. As we celebrate the spectacular achievements of this line of research, we need to assess its full potential and its limitations. What are the next steps to take towards machine intelligence? 2010 Elsevier Ltd. All rights reserved.

Controlled English to facilitate human/machine analytical processing

NASA Astrophysics Data System (ADS)

Braines, Dave; Mott, David; Laws, Simon; de Mel, Geeth; Pham, Tien

2013-06-01

Controlled English is a human-readable information representation format that is implemented using a restricted subset of the English language, but which is unambiguous and directly accessible by simple machine processes. We have been researching the capabilities of CE in a number of contexts, and exploring the degree to which a flexible and more human-friendly information representation format could aid the intelligence analyst in a multi-agent collaborative operational environment; especially in cases where the agents are a mixture of other human users and machine processes aimed at assisting the human users. CE itself is built upon a formal logic basis, but allows users to easily specify models for a domain of interest in a human-friendly language. In our research we have been developing an experimental component known as the "CE Store" in which CE information can be quickly and flexibly processed and shared between human and machine agents. The CE Store environment contains a number of specialized machine agents for common processing tasks and also supports execution of logical inference rules that can be defined in the same CE language. This paper outlines the basic architecture of this approach, discusses some of the example machine agents that have been developed, and provides some typical examples of the CE language and the way in which it has been used to support complex analytical tasks on synthetic data sources. We highlight the fusion of human and machine processing supported through the use of the CE language and CE Store environment, and show this environment with examples of highly dynamic extensions to the model(s) and integration between different user-defined models in a collaborative setting.

Feature Selection Has a Large Impact on One-Class Classification Accuracy for MicroRNAs in Plants.

PubMed

Yousef, Malik; Saçar Demirci, Müşerref Duygu; Khalifa, Waleed; Allmer, Jens

2016-01-01

MicroRNAs (miRNAs) are short RNA sequences involved in posttranscriptional gene regulation. Their experimental analysis is complicated and, therefore, needs to be supplemented with computational miRNA detection. Currently computational miRNA detection is mainly performed using machine learning and in particular two-class classification. For machine learning, the miRNAs need to be parametrized and more than 700 features have been described. Positive training examples for machine learning are readily available, but negative data is hard to come by. Therefore, it seems prerogative to use one-class classification instead of two-class classification. Previously, we were able to almost reach two-class classification accuracy using one-class classifiers. In this work, we employ feature selection procedures in conjunction with one-class classification and show that there is up to 36% difference in accuracy among these feature selection methods. The best feature set allowed the training of a one-class classifier which achieved an average accuracy of ~95.6% thereby outperforming previous two-class-based plant miRNA detection approaches by about 0.5%. We believe that this can be improved upon in the future by rigorous filtering of the positive training examples and by improving current feature clustering algorithms to better target pre-miRNA feature selection.

Analysis of precision and accuracy in a simple model of machine learning

NASA Astrophysics Data System (ADS)

Lee, Julian

2017-12-01

Machine learning is a procedure where a model for the world is constructed from a training set of examples. It is important that the model should capture relevant features of the training set, and at the same time make correct prediction for examples not included in the training set. I consider the polynomial regression, the simplest method of learning, and analyze the accuracy and precision for different levels of the model complexity.

Translational physiology: from molecules to public health.

PubMed

Seals, Douglas R

2013-07-15

The term 'translational research' was coined 20 years ago and has become a guiding influence in biomedical research. It refers to a process by which the findings of basic research are extended to the clinical research setting (bench to bedside) and then to clinical practice and eventually health policy (bedside to community). It is a dynamic, multidisciplinary research approach. The concept of translational physiology applies the translational research model to the physiological sciences. It differs from the traditional areas of integrative and clinical physiology by its broad investigative scope of basic research to community health. Translational physiology offers exciting opportunities, but presently is under-developed and -utilized. A key challenge will be to expand physiological research by extending investigations to communities of patients and healthy (or at risk) individuals. This will allow bidirectional physiological investigation throughout the translational continuum: basic research observations can be studied up to the population level, and mechanisms can be assessed by 'reverse translation' in clinical research settings and preclinical models based on initial observations made in populations. Examples of translational physiology questions, experimental approaches, roadblocks and strategies for promotion are discussed. Translational physiology provides a novel framework for physiology programs and an investigational platform for physiologists to study function from molecular events to public health. It holds promise for enhancing the completeness and societal impact of our work, while further solidifying the critical role of physiology in the biomedical research enterprise.

Tool path strategy and cutting process monitoring in intelligent machining

NASA Astrophysics Data System (ADS)

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.

Machine Learning for Education: Learning to Teach

DTIC Science & Technology

2016-12-01

such as commercial aviation, healthcare, and military operations. In the context of military applications, serious gaming – the training warfighters...problems. Playing these games not only allowed the warfighter to discover and learn new tactics, techniques, and procedures, but also allowed the...collecting information across relevant sample sizes have motivated a data-driven, game - based simulation approach. For example, industry and academia alike

Longest jobs first algorithm in solving job shop scheduling using adaptive genetic algorithm (GA)

NASA Astrophysics Data System (ADS)

Alizadeh Sahzabi, Vahid; Karimi, Iman; Alizadeh Sahzabi, Navid; Mamaani Barnaghi, Peiman

2012-01-01

In this paper, genetic algorithm was used to solve job shop scheduling problems. One example discussed in JSSP (Job Shop Scheduling Problem) and I described how we can solve such these problems by genetic algorithm. The goal in JSSP is to gain the shortest process time. Furthermore I proposed a method to obtain best performance on performing all jobs in shortest time. The method mainly, is according to Genetic algorithm (GA) and crossing over between parents always follows the rule which the longest process is at the first in the job queue. In the other word chromosomes is suggested to sorts based on the longest processes to shortest i.e. "longest job first" says firstly look which machine contains most processing time during its performing all its jobs and that is the bottleneck. Secondly, start sort those jobs which are belonging to that specific machine descending. Based on the achieved results," longest jobs first" is the optimized status in job shop scheduling problems. In our results the accuracy would grow up to 94.7% for total processing time and the method improved 4% the accuracy of performing all jobs in the presented example.

Designing a post-genomics knowledge ecosystem to translate pharmacogenomics into public health action.

PubMed

Dove, Edward S; Faraj, Samer A; Kolker, Eugene; Ozdemir, Vural

2012-01-01

Translation of pharmacogenomics to public health action is at the epicenter of the life sciences agenda. Post-genomics knowledge is simultaneously co-produced at multiple scales and locales by scientists, crowd-sourcing and biological citizens. The latter are entrepreneurial citizens who are autonomous, self-governing and increasingly conceptualizing themselves in biological terms, ostensibly taking responsibility for their own health, and engaging in patient advocacy and health activism. By studying these heterogeneous 'scientific cultures', we can locate innovative parameters of collective action to move pharmacogenomics to practice (personalized therapeutics). To this end, we reconceptualize knowledge-based innovation as a complex ecosystem comprising 'actors' and 'narrators'. For robust knowledge translation, we require a nested post-genomics technology governance system composed of first-order narrators (for example, social scientists, philosophers, bioethicists) situated at arm's length from innovation actors (for example, pharmacogenomics scientists). Yet, second-order narrators (for example, an independent and possibly crowd-funded think-tank of citizen scholars, marginalized groups and knowledge end-users) are crucial to prevent first-order narrators from gaining excessive power that can be misused in the course of steering innovations. To operate such 'self-calibrating' and nested innovation ecosystems, we introduce the concept of 'wiki-governance' to enable mutual and iterative learning among innovation actors and first- and second-order narrators. '[A] scientific expert is someone who knows more and more about less and less, until finally knowing (almost) everything about (almost) nothing.' [1] 'Ubuntu: I am because you are.' [2].

Designing a post-genomics knowledge ecosystem to translate pharmacogenomics into public health action

PubMed Central

2012-01-01

Translation of pharmacogenomics to public health action is at the epicenter of the life sciences agenda. Post-genomics knowledge is simultaneously co-produced at multiple scales and locales by scientists, crowd-sourcing and biological citizens. The latter are entrepreneurial citizens who are autonomous, self-governing and increasingly conceptualizing themselves in biological terms, ostensibly taking responsibility for their own health, and engaging in patient advocacy and health activism. By studying these heterogeneous 'scientific cultures', we can locate innovative parameters of collective action to move pharmacogenomics to practice (personalized therapeutics). To this end, we reconceptualize knowledge-based innovation as a complex ecosystem comprising 'actors' and 'narrators'. For robust knowledge translation, we require a nested post-genomics technology governance system composed of first-order narrators (for example, social scientists, philosophers, bioethicists) situated at arm's length from innovation actors (for example, pharmacogenomics scientists). Yet, second-order narrators (for example, an independent and possibly crowd-funded think-tank of citizen scholars, marginalized groups and knowledge end-users) are crucial to prevent first-order narrators from gaining excessive power that can be misused in the course of steering innovations. To operate such 'self-calibrating' and nested innovation ecosystems, we introduce the concept of 'wiki-governance' to enable mutual and iterative learning among innovation actors and first- and second-order narrators. '[A] scientific expert is someone who knows more and more about less and less, until finally knowing (almost) everything about (almost) nothing.' [1] 'Ubuntu: I am because you are.' [2] PMID:23194449

Best practice recommendations for the development, implementation, and evaluation of online knowledge translation resources in rehabilitation.

PubMed

Levac, Danielle; Glegg, Stephanie M N; Camden, Chantal; Rivard, Lisa M; Missiuna, Cheryl

2015-04-01

The knowledge-to-practice gap in rehabilitation has spurred knowledge translation (KT) initiatives aimed at promoting clinician behavior change and improving patient care. Online KT resources for physical therapists and other rehabilitation clinicians are appealing because of their potential to reach large numbers of individuals through self-paced, self-directed learning. This article proposes best practice recommendations for developing online KT resources that are designed to translate evidence into practice. Four recommendations are proposed with specific steps in the development, implementation, and evaluation process: (1) develop evidence-based, user-centered content; (2) tailor content to online format; (3) evaluate impact; and (4) share results and disseminate knowledge. Based on KT evidence and instructional design principles, concrete examples are provided along with insights gained from experiences in creating and evaluating online KT resources for physical therapists. In proposing these recommendations, the next steps for research are suggested, and others are invited to contribute to the discussion. © 2015 American Physical Therapy Association.

Support vector machines

NASA Technical Reports Server (NTRS)

Garay, Michael J.; Mazzoni, Dominic; Davies, Roger; Wagstaff, Kiri

2004-01-01

Support Vector Machines (SVMs) are a type of supervised learning algorith,, other examples of which are Artificial Neural Networks (ANNs), Decision Trees, and Naive Bayesian Classifiers. Supervised learning algorithms are used to classify objects labled by a 'supervisor' - typically a human 'expert.'.

Model-based and Model-free Machine Learning Techniques for Diagnostic Prediction and Classification of Clinical Outcomes in Parkinson's Disease.

PubMed

Gao, Chao; Sun, Hanbo; Wang, Tuo; Tang, Ming; Bohnen, Nicolaas I; Müller, Martijn L T M; Herman, Talia; Giladi, Nir; Kalinin, Alexandr; Spino, Cathie; Dauer, William; Hausdorff, Jeffrey M; Dinov, Ivo D

2018-05-08

In this study, we apply a multidisciplinary approach to investigate falls in PD patients using clinical, demographic and neuroimaging data from two independent initiatives (University of Michigan and Tel Aviv Sourasky Medical Center). Using machine learning techniques, we construct predictive models to discriminate fallers and non-fallers. Through controlled feature selection, we identified the most salient predictors of patient falls including gait speed, Hoehn and Yahr stage, postural instability and gait difficulty-related measurements. The model-based and model-free analytical methods we employed included logistic regression, random forests, support vector machines, and XGboost. The reliability of the forecasts was assessed by internal statistical (5-fold) cross validation as well as by external out-of-bag validation. Four specific challenges were addressed in the study: Challenge 1, develop a protocol for harmonizing and aggregating complex, multisource, and multi-site Parkinson's disease data; Challenge 2, identify salient predictive features associated with specific clinical traits, e.g., patient falls; Challenge 3, forecast patient falls and evaluate the classification performance; and Challenge 4, predict tremor dominance (TD) vs. posture instability and gait difficulty (PIGD). Our findings suggest that, compared to other approaches, model-free machine learning based techniques provide a more reliable clinical outcome forecasting of falls in Parkinson's patients, for example, with a classification accuracy of about 70-80%.

On the suitability of the connection machine for direct particle simulation

NASA Technical Reports Server (NTRS)

Dagum, Leonard

1990-01-01

The algorithmic structure was examined of the vectorizable Stanford particle simulation (SPS) method and the structure is reformulated in data parallel form. Some of the SPS algorithms can be directly translated to data parallel, but several of the vectorizable algorithms have no direct data parallel equivalent. This requires the development of new, strictly data parallel algorithms. In particular, a new sorting algorithm is developed to identify collision candidates in the simulation and a master/slave algorithm is developed to minimize communication cost in large table look up. Validation of the method is undertaken through test calculations for thermal relaxation of a gas, shock wave profiles, and shock reflection from a stationary wall. A qualitative measure is provided of the performance of the Connection Machine for direct particle simulation. The massively parallel architecture of the Connection Machine is found quite suitable for this type of calculation. However, there are difficulties in taking full advantage of this architecture because of lack of a broad based tradition of data parallel programming. An important outcome of this work has been new data parallel algorithms specifically of use for direct particle simulation but which also expand the data parallel diction.

DisGeNET-RDF: harnessing the innovative power of the Semantic Web to explore the genetic basis of diseases.

PubMed

Queralt-Rosinach, Núria; Piñero, Janet; Bravo, Àlex; Sanz, Ferran; Furlong, Laura I

2016-07-15

DisGeNET-RDF makes available knowledge on the genetic basis of human diseases in the Semantic Web. Gene-disease associations (GDAs) and their provenance metadata are published as human-readable and machine-processable web resources. The information on GDAs included in DisGeNET-RDF is interlinked to other biomedical databases to support the development of bioinformatics approaches for translational research through evidence-based exploitation of a rich and fully interconnected linked open data. http://rdf.disgenet.org/ support@disgenet.org. © The Author 2016. Published by Oxford University Press.

On the Safety of Machine Learning: Cyber-Physical Systems, Decision Sciences, and Data Products.

PubMed

Varshney, Kush R; Alemzadeh, Homa

2017-09-01

Machine learning algorithms increasingly influence our decisions and interact with us in all parts of our daily lives. Therefore, just as we consider the safety of power plants, highways, and a variety of other engineered socio-technical systems, we must also take into account the safety of systems involving machine learning. Heretofore, the definition of safety has not been formalized in a machine learning context. In this article, we do so by defining machine learning safety in terms of risk, epistemic uncertainty, and the harm incurred by unwanted outcomes. We then use this definition to examine safety in all sorts of applications in cyber-physical systems, decision sciences, and data products. We find that the foundational principle of modern statistical machine learning, empirical risk minimization, is not always a sufficient objective. We discuss how four different categories of strategies for achieving safety in engineering, including inherently safe design, safety reserves, safe fail, and procedural safeguards can be mapped to a machine learning context. We then discuss example techniques that can be adopted in each category, such as considering interpretability and causality of predictive models, objective functions beyond expected prediction accuracy, human involvement for labeling difficult or rare examples, and user experience design of software and open data.

Addressing the translational dilemma: dynamic knowledge representation of inflammation using agent-based modeling.

PubMed

An, Gary; Christley, Scott

2012-01-01

Given the panoply of system-level diseases that result from disordered inflammation, such as sepsis, atherosclerosis, cancer, and autoimmune disorders, understanding and characterizing the inflammatory response is a key target of biomedical research. Untangling the complex behavioral configurations associated with a process as ubiquitous as inflammation represents a prototype of the translational dilemma: the ability to translate mechanistic knowledge into effective therapeutics. A critical failure point in the current research environment is a throughput bottleneck at the level of evaluating hypotheses of mechanistic causality; these hypotheses represent the key step toward the application of knowledge for therapy development and design. Addressing the translational dilemma will require utilizing the ever-increasing power of computers and computational modeling to increase the efficiency of the scientific method in the identification and evaluation of hypotheses of mechanistic causality. More specifically, development needs to focus on facilitating the ability of non-computer trained biomedical researchers to utilize and instantiate their knowledge in dynamic computational models. This is termed "dynamic knowledge representation." Agent-based modeling is an object-oriented, discrete-event, rule-based simulation method that is well suited for biomedical dynamic knowledge representation. Agent-based modeling has been used in the study of inflammation at multiple scales. The ability of agent-based modeling to encompass multiple scales of biological process as well as spatial considerations, coupled with an intuitive modeling paradigm, suggest that this modeling framework is well suited for addressing the translational dilemma. This review describes agent-based modeling, gives examples of its applications in the study of inflammation, and introduces a proposed general expansion of the use of modeling and simulation to augment the generation and evaluation of knowledge by the biomedical research community at large.

High level language-based robotic control system

NASA Technical Reports Server (NTRS)

Rodriguez, Guillermo (Inventor); Kruetz, Kenneth K. (Inventor); Jain, Abhinandan (Inventor)

1994-01-01

This invention is a robot control system based on a high level language implementing a spatial operator algebra. There are two high level languages included within the system. At the highest level, applications programs can be written in a robot-oriented applications language including broad operators such as MOVE and GRASP. The robot-oriented applications language statements are translated into statements in the spatial operator algebra language. Programming can also take place using the spatial operator algebra language. The statements in the spatial operator algebra language from either source are then translated into machine language statements for execution by a digital control computer. The system also includes the capability of executing the control code sequences in a simulation mode before actual execution to assure proper action at execution time. The robot's environment is checked as part of the process and dynamic reconfiguration is also possible. The languages and system allow the programming and control of multiple arms and the use of inward/outward spatial recursions in which every computational step can be related to a transformation from one point in the mechanical robot to another point to name two major advantages.

High level language-based robotic control system

NASA Technical Reports Server (NTRS)

Rodriguez, Guillermo (Inventor); Kreutz, Kenneth K. (Inventor); Jain, Abhinandan (Inventor)

1996-01-01

This invention is a robot control system based on a high level language implementing a spatial operator algebra. There are two high level languages included within the system. At the highest level, applications programs can be written in a robot-oriented applications language including broad operators such as MOVE and GRASP. The robot-oriented applications language statements are translated into statements in the spatial operator algebra language. Programming can also take place using the spatial operator algebra language. The statements in the spatial operator algebra language from either source are then translated into machine language statements for execution by a digital control computer. The system also includes the capability of executing the control code sequences in a simulation mode before actual execution to assure proper action at execution time. The robot's environment is checked as part of the process and dynamic reconfiguration is also possible. The languages and system allow the programming and control of multiple arms and the use of inward/outward spatial recursions in which every computational step can be related to a transformation from one point in the mechanical robot to another point to name two major advantages.

Calibrating random forests for probability estimation.

PubMed

Dankowski, Theresa; Ziegler, Andreas

2016-09-30

Probabilities can be consistently estimated using random forests. It is, however, unclear how random forests should be updated to make predictions for other centers or at different time points. In this work, we present two approaches for updating random forests for probability estimation. The first method has been proposed by Elkan and may be used for updating any machine learning approach yielding consistent probabilities, so-called probability machines. The second approach is a new strategy specifically developed for random forests. Using the terminal nodes, which represent conditional probabilities, the random forest is first translated to logistic regression models. These are, in turn, used for re-calibration. The two updating strategies were compared in a simulation study and are illustrated with data from the German Stroke Study Collaboration. In most simulation scenarios, both methods led to similar improvements. In the simulation scenario in which the stricter assumptions of Elkan's method were not met, the logistic regression-based re-calibration approach for random forests outperformed Elkan's method. It also performed better on the stroke data than Elkan's method. The strength of Elkan's method is its general applicability to any probability machine. However, if the strict assumptions underlying this approach are not met, the logistic regression-based approach is preferable for updating random forests for probability estimation. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Fabrication of an infrared Shack-Hartmann sensor by combining high-speed single-point diamond milling and precision compression molding processes.

PubMed

Zhang, Lin; Zhou, Wenchen; Naples, Neil J; Yi, Allen Y

2018-05-01

A novel fabrication method by combining high-speed single-point diamond milling and precision compression molding processes for fabrication of discontinuous freeform microlens arrays was proposed. Compared with slow tool servo diamond broaching, high-speed single-point diamond milling was selected for its flexibility in the fabrication of true 3D optical surfaces with discontinuous features. The advantage of single-point diamond milling is that the surface features can be constructed sequentially by spacing the axes of a virtual spindle at arbitrary positions based on the combination of rotational and translational motions of both the high-speed spindle and linear slides. By employing this method, each micro-lenslet was regarded as a microstructure cell by passing the axis of the virtual spindle through the vertex of each cell. An optimization arithmetic based on minimum-area fabrication was introduced to the machining process to further increase the machining efficiency. After the mold insert was machined, it was employed to replicate the microlens array onto chalcogenide glass. In the ensuing optical measurement, the self-built Shack-Hartmann wavefront sensor was proven to be accurate in detecting an infrared wavefront by both experiments and numerical simulation. The combined results showed that precision compression molding of chalcogenide glasses could be an economic and precision optical fabrication technology for high-volume production of infrared optics.

Attention-Based Recurrent Temporal Restricted Boltzmann Machine for Radar High Resolution Range Profile Sequence Recognition.

PubMed

Zhang, Yifan; Gao, Xunzhang; Peng, Xuan; Ye, Jiaqi; Li, Xiang

2018-05-16

The High Resolution Range Profile (HRRP) recognition has attracted great concern in the field of Radar Automatic Target Recognition (RATR). However, traditional HRRP recognition methods failed to model high dimensional sequential data efficiently and have a poor anti-noise ability. To deal with these problems, a novel stochastic neural network model named Attention-based Recurrent Temporal Restricted Boltzmann Machine (ARTRBM) is proposed in this paper. RTRBM is utilized to extract discriminative features and the attention mechanism is adopted to select major features. RTRBM is efficient to model high dimensional HRRP sequences because it can extract the information of temporal and spatial correlation between adjacent HRRPs. The attention mechanism is used in sequential data recognition tasks including machine translation and relation classification, which makes the model pay more attention to the major features of recognition. Therefore, the combination of RTRBM and the attention mechanism makes our model effective for extracting more internal related features and choose the important parts of the extracted features. Additionally, the model performs well with the noise corrupted HRRP data. Experimental results on the Moving and Stationary Target Acquisition and Recognition (MSTAR) dataset show that our proposed model outperforms other traditional methods, which indicates that ARTRBM extracts, selects, and utilizes the correlation information between adjacent HRRPs effectively and is suitable for high dimensional data or noise corrupted data.

Generic decoding of seen and imagined objects using hierarchical visual features.

PubMed

Horikawa, Tomoyasu; Kamitani, Yukiyasu

2017-05-22

Object recognition is a key function in both human and machine vision. While brain decoding of seen and imagined objects has been achieved, the prediction is limited to training examples. We present a decoding approach for arbitrary objects using the machine vision principle that an object category is represented by a set of features rendered invariant through hierarchical processing. We show that visual features, including those derived from a deep convolutional neural network, can be predicted from fMRI patterns, and that greater accuracy is achieved for low-/high-level features with lower-/higher-level visual areas, respectively. Predicted features are used to identify seen/imagined object categories (extending beyond decoder training) from a set of computed features for numerous object images. Furthermore, decoding of imagined objects reveals progressive recruitment of higher-to-lower visual representations. Our results demonstrate a homology between human and machine vision and its utility for brain-based information retrieval.

Applying hospital evidence to paramedicine: issues of indirectness, validity and knowledge translation.

PubMed

Bigham, Blair; Welsford, Michelle

2015-05-01

The practice of emergency medicine (EM) has been intertwined with emergency medical services (EMS) for more than 40 years. In this commentary, we explore the practice of translating hospital based evidence into the prehospital setting. We will challenge both EMS and EM dogma-bringing hospital care to patients in the field is not always better. In providing examples of therapies championed in hospitals that have failed to translate into the field, we will discuss the unique prehospital environment, and why evidence from the hospital setting cannot necessarily be translated to the prehospital field. Paramedicine is maturing so that the capability now exists to conduct practice-specific research that can inform best practices. Before translation from the hospital environment is implemented, evidence must be evaluated by people with expertise in three domains: critical appraisal, EM, and EMS. Scientific evidence should be assessed for: quality and bias; directness, generalizability, and validity to the EMS population; effect size and anticipated benefit from prehospital application; feasibility (including economic evaluation, human resource availability in the mobile environment); and patient and provider safety.

Boundary Objects and Curriculum Change: The Case of Integrated versus Subject-Based Teaching

ERIC Educational Resources Information Center

Hultén, Magnus

2013-01-01

The article examines the stability and success of ideas within pedagogical discourses. Why do certain ideas attract actors and how does change come about? These general questions are dealt with through considering the example of the swift spread of an interdisciplinary idea, "arbetsområde" (translated to "spheres of work") in…

Choice as a Global Language in Local Practice: A Mixed Model of School Choice in Taiwan

ERIC Educational Resources Information Center

Mao, Chin-Ju

2015-01-01

This paper uses school choice policy as an example to demonstrate how local actors adopt, mediate, translate, and reformulate "choice" as neo-liberal rhetoric informing education reform. Complex processes exist between global policy about school choice and the local practice of school choice. Based on the theoretical sensibility of…

Online Localization of "Zooniverse" Citizen Science Projects--On the Use of Translation Platforms as Tools for Translator Education

ERIC Educational Resources Information Center

Michalak, Krzysztof

2015-01-01

This paper aims at describing the way in which online translation platforms can facilitate the process of training translators. "Zooniverse," a website hosting a variety of citizen science projects in which everyone can take part, was used as an example of such a concept. The first section of this paper is focused on the history, idea…

Implementing Value-Based Payment Reform: A Conceptual Framework and Case Examples.

PubMed

Conrad, Douglas A; Vaughn, Matthew; Grembowski, David; Marcus-Smith, Miriam

2016-08-01

This article develops a conceptual framework for implementation of value-based payment (VBP) reform and then draws on that framework to systematically examine six distinct multi-stakeholder coalition VBP initiatives in three different regions of the United States. The VBP initiatives deploy the following payment models: reference pricing, "shadow" primary care capitation, bundled payment, pay for performance, shared savings within accountable care organizations, and global payment. The conceptual framework synthesizes prior models of VBP implementation. It describes how context, project objectives, payment and care delivery strategies, and the barriers and facilitators to translating strategy into implementation affect VBP implementation and value for patients. We next apply the framework to six case examples of implementation, and conclude by discussing the implications of the case examples and the conceptual framework for future practice and research. © The Author(s) 2015.

Wire Detection Algorithms for Navigation

NASA Technical Reports Server (NTRS)

Kasturi, Rangachar; Camps, Octavia I.

2002-01-01

In this research we addressed the problem of obstacle detection for low altitude rotorcraft flight. In particular, the problem of detecting thin wires in the presence of image clutter and noise was studied. Wires present a serious hazard to rotorcrafts. Since they are very thin, their detection early enough so that the pilot has enough time to take evasive action is difficult, as their images can be less than one or two pixels wide. Two approaches were explored for this purpose. The first approach involved a technique for sub-pixel edge detection and subsequent post processing, in order to reduce the false alarms. After reviewing the line detection literature, an algorithm for sub-pixel edge detection proposed by Steger was identified as having good potential to solve the considered task. The algorithm was tested using a set of images synthetically generated by combining real outdoor images with computer generated wire images. The performance of the algorithm was evaluated both, at the pixel and the wire levels. It was observed that the algorithm performs well, provided that the wires are not too thin (or distant) and that some post processing is performed to remove false alarms due to clutter. The second approach involved the use of an example-based learning scheme namely, Support Vector Machines. The purpose of this approach was to explore the feasibility of an example-based learning based approach for the task of detecting wires from their images. Support Vector Machines (SVMs) have emerged as a promising pattern classification tool and have been used in various applications. It was found that this approach is not suitable for very thin wires and of course, not suitable at all for sub-pixel thick wires. High dimensionality of the data as such does not present a major problem for SVMs. However it is desirable to have a large number of training examples especially for high dimensional data. The main difficulty in using SVMs (or any other example-based learning method) is the need for a very good set of positive and negative examples since the performance depends on the quality of the training set.

Machine learning-based prediction of adverse drug effects: An example of seizure-inducing compounds.

PubMed

Gao, Mengxuan; Igata, Hideyoshi; Takeuchi, Aoi; Sato, Kaoru; Ikegaya, Yuji

2017-02-01

Various biological factors have been implicated in convulsive seizures, involving side effects of drugs. For the preclinical safety assessment of drug development, it is difficult to predict seizure-inducing side effects. Here, we introduced a machine learning-based in vitro system designed to detect seizure-inducing side effects. We recorded local field potentials from the CA1 alveus in acute mouse neocortico-hippocampal slices, while 14 drugs were bath-perfused at 5 different concentrations each. For each experimental condition, we collected seizure-like neuronal activity and merged their waveforms as one graphic image, which was further converted into a feature vector using Caffe, an open framework for deep learning. In the space of the first two principal components, the support vector machine completely separated the vectors (i.e., doses of individual drugs) that induced seizure-like events and identified diphenhydramine, enoxacin, strychnine and theophylline as "seizure-inducing" drugs, which indeed were reported to induce seizures in clinical situations. Thus, this artificial intelligence-based classification may provide a new platform to detect the seizure-inducing side effects of preclinical drugs. Copyright © 2017 The Authors. Production and hosting by Elsevier B.V. All rights reserved.

Method and apparatus for characterizing and enhancing the functional performance of machine tools

DOEpatents

Barkman, William E; Babelay, Jr., Edwin F; Smith, Kevin Scott; Assaid, Thomas S; McFarland, Justin T; Tursky, David A; Woody, Bethany; Adams, David

2013-04-30

Disclosed are various systems and methods for assessing and improving the capability of a machine tool. The disclosure applies to machine tools having at least one slide configured to move along a motion axis. Various patterns of dynamic excitation commands are employed to drive the one or more slides, typically involving repetitive short distance displacements. A quantification of a measurable merit of machine tool response to the one or more patterns of dynamic excitation commands is typically derived for the machine tool. Examples of measurable merits of machine tool performance include workpiece surface finish, and the ability to generate chips of the desired length.

Big Data Bioinformatics

PubMed Central

GREENE, CASEY S.; TAN, JIE; UNG, MATTHEW; MOORE, JASON H.; CHENG, CHAO

2017-01-01

Recent technological advances allow for high throughput profiling of biological systems in a cost-efficient manner. The low cost of data generation is leading us to the “big data” era. The availability of big data provides unprecedented opportunities but also raises new challenges for data mining and analysis. In this review, we introduce key concepts in the analysis of big data, including both “machine learning” algorithms as well as “unsupervised” and “supervised” examples of each. We note packages for the R programming language that are available to perform machine learning analyses. In addition to programming based solutions, we review webservers that allow users with limited or no programming background to perform these analyses on large data compendia. PMID:27908398

Big Data Bioinformatics

PubMed Central

GREENE, CASEY S.; TAN, JIE; UNG, MATTHEW; MOORE, JASON H.; CHENG, CHAO

2017-01-01

Recent technological advances allow for high throughput profiling of biological systems in a cost-efficient manner. The low cost of data generation is leading us to the “big data” era. The availability of big data provides unprecedented opportunities but also raises new challenges for data mining and analysis. In this review, we introduce key concepts in the analysis of big data, including both “machine learning” algorithms as well as “unsupervised” and “supervised” examples of each. We note packages for the R programming language that are available to perform machine learning analyses. In addition to programming based solutions, we review webservers that allow users with limited or no programming background to perform these analyses on large data compendia. PMID:24799088

Big data bioinformatics.

PubMed

Greene, Casey S; Tan, Jie; Ung, Matthew; Moore, Jason H; Cheng, Chao

2014-12-01

Recent technological advances allow for high throughput profiling of biological systems in a cost-efficient manner. The low cost of data generation is leading us to the "big data" era. The availability of big data provides unprecedented opportunities but also raises new challenges for data mining and analysis. In this review, we introduce key concepts in the analysis of big data, including both "machine learning" algorithms as well as "unsupervised" and "supervised" examples of each. We note packages for the R programming language that are available to perform machine learning analyses. In addition to programming based solutions, we review webservers that allow users with limited or no programming background to perform these analyses on large data compendia. © 2014 Wiley Periodicals, Inc.

Hierarchical representation and machine learning from faulty jet engine behavioral examples to detect real time abnormal conditions

NASA Technical Reports Server (NTRS)

Gupta, U. K.; Ali, M.

1988-01-01

The theoretical basis and operation of LEBEX, a machine-learning system for jet-engine performance monitoring, are described. The behavior of the engine is modeled in terms of four parameters (the rotational speeds of the high- and low-speed sections and the exhaust and combustion temperatures), and parameter variations indicating malfunction are transformed into structural representations involving instances and events. LEBEX extracts descriptors from a set of training data on normal and faulty engines, represents them hierarchically in a knowledge base, and uses them to diagnose and predict faults on a real-time basis. Diagrams of the system architecture and printouts of typical results are shown.

The translation and cultural adaptation of the Child Behavior Checklist for use in Israel (Hebrew), Korea, the US (Spanish), India (Malayalam and Kannada), and Spain

PubMed Central

Wild, Diane; Furtado, Tamzin; Angalakuditi, Mallik

2012-01-01

Background The Child Behavior Checklist (CBCL) is a caregiver rating scale for assessing the behavioral profile of children. It was developed in the US, and has been extensively translated and used in a large number of studies internationally. Objective The objective of this study was to translate the CBCL into six languages using a rigorous translation methodology, placing particular emphasis on cultural adaptation and ensuring that the measure has content validity with carers of children with epilepsy. Methods A rigorous translation and cultural adaptation methodology was used. This is a process which includes two forward translations, reconciliation, two back-translations, and cognitive debriefing interviews with five carers of children with epilepsy in each country. In addition, a series of open-ended questions were asked of the carers in order to provide evidence of content validity. Results A number of cultural adaptations were made during the translation process. This included adaptations to the examples of sports and hobbies. An addition of “milk delivery” was made to the job examples in the Malayalam translation. In addition, two sexual problem items were removed from the Hebrew translation for Israel. Conclusion An additional six translations of the CBCL are now available for use in multinational studies. These translations have evidence of content validity for use with parents of children with epilepsy and have been appropriately culturally adapted so that they are acceptable for use in the target countries. The study highlights the importance of a rigorous translation process and the process of cultural adaptation. PMID:22715318

Obtaining Global Picture From Single Point Observations by Combining Data Assimilation and Machine Learning Tools

NASA Astrophysics Data System (ADS)

Shprits, Y.; Zhelavskaya, I. S.; Kellerman, A. C.; Spasojevic, M.; Kondrashov, D. A.; Ghil, M.; Aseev, N.; Castillo Tibocha, A. M.; Cervantes Villa, J. S.; Kletzing, C.; Kurth, W. S.

2017-12-01

Increasing volume of satellite measurements requires deployment of new tools that can utilize such vast amount of data. Satellite measurements are usually limited to a single location in space, which complicates the data analysis geared towards reproducing the global state of the space environment. In this study we show how measurements can be combined by means of data assimilation and how machine learning can help analyze large amounts of data and can help develop global models that are trained on single point measurement. Data Assimilation: Manual analysis of the satellite measurements is a challenging task, while automated analysis is complicated by the fact that measurements are given at various locations in space, have different instrumental errors, and often vary by orders of magnitude. We show results of the long term reanalysis of radiation belt measurements along with fully operational real-time predictions using data assimilative VERB code. Machine Learning: We present application of the machine learning tools for the analysis of NASA Van Allen Probes upper-hybrid frequency measurements. Using the obtained data set we train a new global predictive neural network. The results for the Van Allen Probes based neural network are compared with historical IMAGE satellite observations. We also show examples of predictions of geomagnetic indices using neural networks. Combination of machine learning and data assimilation: We discuss how data assimilation tools and machine learning tools can be combine so that physics-based insight into the dynamics of the particular system can be combined with empirical knowledge of it's non-linear behavior.

Multilevel Analysis in Analyzing Speech Data

ERIC Educational Resources Information Center

Guddattu, Vasudeva; Krishna, Y.

2011-01-01

The speech produced by human vocal tract is a complex acoustic signal, with diverse applications in phonetics, speech synthesis, automatic speech recognition, speaker identification, communication aids, speech pathology, speech perception, machine translation, hearing research, rehabilitation and assessment of communication disorders and many…

Strategies, Language Transfer and the Simulation of the Second Language Learner's Mental Operations.

ERIC Educational Resources Information Center

Smith, Mike Sharwood

1979-01-01

An attempt is made to describe second language behavior and language transfer in cybernetic terms. This should make it possible to translate language into machine language and to clarify psycholinguistic explanations of second language performance. (PMJ)

Fostering Wisdom-Based Action through Web 2.0 Communities of Practice: An Example of the Early Childhood Family Support Community of Practice

ERIC Educational Resources Information Center

Turnbull, Ann P.; Summers, Jean Ann; Gotto, George; Stowe, Matt; Beauchamp, Donna; Klein, Samara; Kyzar, Kathleen; Turnbull, Rud; Zuna, Nina

2009-01-01

This article discusses a new approach to knowledge translation using Web 2.0 technologies in an online Community of Practice (CoP). The purpose of the CoP is to promote wisdom-based action, a process that encourages people to engage with knowledge, match it to their own values, vision, and contexts, make a well-informed decision, and act on that…

Relevance of Rodent Models of Depression in Clinical Practice: Can We Overcome the Obstacles in Translational Neuropsychiatry?

PubMed

Söderlund, Johan; Lindskog, Maria

2018-04-23

The diagnosis of a mental disorder generally depends on clinical observations and phenomenological symptoms reported by the patient. The definition of a given diagnosis is criteria based and relies on the ability to accurately interpret subjective symptoms and complex behavior. This type of diagnosis comprises a challenge to translate to reliable animal models, and these translational uncertainties hamper the development of new treatments. In this review, we will discuss how depressive-like behavior can be induced in rodents, and the relationship between these models and depression in humans. Specifically, we suggest similarities between triggers of depressive-like behavior in animal models and human conditions known to increase the risk of depression, for example exhaustion and bullying. Although we acknowledge the potential problems in comparing animal findings to human conditions, such comparisons are useful for understanding the complexity of depression, and we highlight the need to develop clinical diagnoses and animal models in parallel to overcome translational uncertainties.

Multidirectional Translation of Environmental Health Science in Community Settings: The Case of Oxidative Stress Pathways.

PubMed

Sampson, Natalie R; Tetteh, Myra M; Schulz, Amy J; Ramirez, Erminia; Wilkins, Donele; de Majo, Ricardo; Mentz, Graciela; Johnson-Lawrence, Vicki

2016-01-01

Translation of environmental health science in vulnerable communities is particularly important to promote public health and reduce health inequities. We describe a structured, multidirectional process used to develop a suite of health promotion tools (e.g., fact sheets, video, maps) documenting patterning of local air pollution sources and availability of antioxidant-rich foods in Detroit, Michigan as factors that jointly affect oxidative stress (OS). OS underlies many pathological processes associated with air pollution, including asthma, metabolic syndrome, cancer, diabetes, and obesity. This translational effort involved a 2-year dialogue among representatives from community-based and environmental organizations, health service providers, and academic researchers. This dialogue led to development of tools, as well as new opportunities to inform related policies and research. Through this example, we highlight how collaborative partnerships can enhance multidirectional dialogue to inform translation of environmental health science by promoting consideration of multilevel risk factors, local priorities and context, and diverse audiences.

Dynamics of pulsed expansion of polyatomic gas cloud: Internal-translational energy transfer contribution

NASA Astrophysics Data System (ADS)

Morozov, A. A.

2007-08-01

Polyatomic gas cloud expansion under pulsed laser evaporation is studied on the basis of one-dimensional direct Monte Carlo simulation. The effect of rotational-translational (RT) and vibrational-translational (VT) energy transfer on dynamics of the cloud expansion is considered. Efficiency of VT energy transfer dependence on the amount of evaporated matter is discussed. To analyze VT energy transfer impact, the number of collisions per molecule during the expansion is calculated. The data are generally in good agreement with available analytical and numerical predictions. Dependencies of the effective number of vibrational degrees of freedom on the number of vibrationally inelastic collisions are obtained and generalized. The importance of the consideration of energy transfer from the internal degrees of freedom to the translational ones is illustrated by an example of pulsed laser evaporation of polytetrafluoroethylene (PTFE). Based on the obtained regularities, analysis of experimental data on pulsed laser evaporation of aniline is performed. The calculated aniline vibrational temperature correlates well with the experimentally measured one.

Single molecule detection, thermal fluctuation and life

PubMed Central

YANAGIDA, Toshio; ISHII, Yoshiharu

2017-01-01

Single molecule detection has contributed to our understanding of the unique mechanisms of life. Unlike artificial man-made machines, biological molecular machines integrate thermal noises rather than avoid them. For example, single molecule detection has demonstrated that myosin motors undergo biased Brownian motion for stepwise movement and that single protein molecules spontaneously change their conformation, for switching to interactions with other proteins, in response to thermal fluctuation. Thus, molecular machines have flexibility and efficiency not seen in artificial machines. PMID:28190869

Citrate-Based Biomaterials and Their Applications in Regenerative Engineering

PubMed Central

Tran, Richard T.; Yang, Jian; Ameer, Guillermo A.

2015-01-01

Advances in biomaterials science and engineering are crucial to translating regenerative engineering, an emerging field that aims to recreate complex tissues, into clinical practice. In this regard, citrate-based biomaterials have become an important tool owing to their versatile material and biological characteristics including unique antioxidant, antimicrobial, adhesive, and fluorescent properties. This review discusses fundamental design considerations, strategies to incorporate unique functionality, and examples of how citrate-based biomaterials can be an enabling technology for regenerative engineering. PMID:27004046

Translational physiology: from molecules to public health

PubMed Central

Seals, Douglas R

2013-01-01

The term ‘translational research’ was coined 20 years ago and has become a guiding influence in biomedical research. It refers to a process by which the findings of basic research are extended to the clinical research setting (bench to bedside) and then to clinical practice and eventually health policy (bedside to community). It is a dynamic, multidisciplinary research approach. The concept of translational physiology applies the translational research model to the physiological sciences. It differs from the traditional areas of integrative and clinical physiology by its broad investigative scope of basic research to community health. Translational physiology offers exciting opportunities, but presently is under-developed and -utilized. A key challenge will be to expand physiological research by extending investigations to communities of patients and healthy (or at risk) individuals. This will allow bidirectional physiological investigation throughout the translational continuum: basic research observations can be studied up to the population level, and mechanisms can be assessed by ‘reverse translation’ in clinical research settings and preclinical models based on initial observations made in populations. Examples of translational physiology questions, experimental approaches, roadblocks and strategies for promotion are discussed. Translational physiology provides a novel framework for physiology programs and an investigational platform for physiologists to study function from molecular events to public health. It holds promise for enhancing the completeness and societal impact of our work, while further solidifying the critical role of physiology in the biomedical research enterprise. PMID:23732641

Policy Compliance of Queries for Private Information Retrieval

DTIC Science & Technology

2010-11-01

SPARQL, unfortunately, is not in RDF and so we had to develop tools to translate SPARQL queries into RDF to be used by our policy compliance prototype...policy-assurance/sparql2n3.py) that accepts SPARQL queries and returns the translated query in our simplified ontology. An example of a translated

Aspects of Sentence Retrieval

DTIC Science & Technology

2006-09-01

English-to-Arabic-to-English Lexicon . . . . . . . . . . . . . . . . . . . . . 89 6.2.4 A WordNet Probabilistic Dictionary ...19 4.1 Examples of “translations” of the terms “zebra” and “galileo” from a translation dictionary trained...106 6.13 Comparing the use of WordNet as a translation table, and as a dictionary during the training of a translation table

Applying Process Improvement Methods to Clinical and Translational Research: Conceptual Framework and Case Examples

PubMed Central

Selker, Harry P.; Leslie, Laurel K.

2015-01-01

Abstract There is growing appreciation that process improvement holds promise for improving quality and efficiency across the translational research continuum but frameworks for such programs are not often described. The purpose of this paper is to present a framework and case examples of a Research Process Improvement Program implemented at Tufts CTSI. To promote research process improvement, we developed online training seminars, workshops, and in‐person consultation models to describe core process improvement principles and methods, demonstrate the use of improvement tools, and illustrate the application of these methods in case examples. We implemented these methods, as well as relational coordination theory, with junior researchers, pilot funding awardees, our CTRC, and CTSI resource and service providers. The program focuses on capacity building to address common process problems and quality gaps that threaten the efficient, timely and successful completion of clinical and translational studies. PMID:26332869

L'Imparfait, le passe simple, et le passe compose francais et leur traduction en neerlandais (The French Imperfect, Past Definite, and Past Indefinite, and their Translation into Dutch)

ERIC Educational Resources Information Center

Ponette, Jean

1977-01-01

There are two tenses in Dutch to translate three French past tenses: the "imperfectum" and the "perfectum." When a one-for-one correspondence is impossible, the translator relies on other means, such as auxiliaries, to achieve desired clarity and nuances. Examples of translations and verb correspondences are given. (Text is in…

Atwood’s machine with a massive string

NASA Astrophysics Data System (ADS)

Lemos, Nivaldo A.

2017-11-01

The dynamics of Atwood’s machine with a string of significant mass are described by the Lagrangian formalism, providing an eloquent example of how the Lagrangian approach is a great deal simpler and so much more expedient than the Newtonian treatment.

Certification of highly complex safety-related systems.

PubMed

Reinert, D; Schaefer, M

1999-01-01

The BIA has now 15 years of experience with the certification of complex electronic systems for safety-related applications in the machinery sector. Using the example of machining centres this presentation will show the systematic procedure for verifying and validating control systems using Application Specific Integrated Circuits (ASICs) and microcomputers for safety functions. One section will describe the control structure of machining centres with control systems using "integrated safety." A diverse redundant architecture combined with crossmonitoring and forced dynamization is explained. In the main section the steps of the systematic certification procedure are explained showing some results of the certification of drilling machines. Specification reviews, design reviews with test case specification, statistical analysis, and walk-throughs are the analytical measures in the testing process. Systematic tests based on the test case specification, Electro Magnetic Interference (EMI), and environmental testing, and site acceptance tests on the machines are the testing measures for validation. A complex software driven system is always undergoing modification. Most of the changes are not safety-relevant but this has to be proven. A systematic procedure for certifying software modifications is presented in the last section of the paper.

Unsupervised quality estimation model for English to German translation and its application in extensive supervised evaluation.

PubMed

Han, Aaron L-F; Wong, Derek F; Chao, Lidia S; He, Liangye; Lu, Yi

2014-01-01

With the rapid development of machine translation (MT), the MT evaluation becomes very important to timely tell us whether the MT system makes any progress. The conventional MT evaluation methods tend to calculate the similarity between hypothesis translations offered by automatic translation systems and reference translations offered by professional translators. There are several weaknesses in existing evaluation metrics. Firstly, the designed incomprehensive factors result in language-bias problem, which means they perform well on some special language pairs but weak on other language pairs. Secondly, they tend to use no linguistic features or too many linguistic features, of which no usage of linguistic feature draws a lot of criticism from the linguists and too many linguistic features make the model weak in repeatability. Thirdly, the employed reference translations are very expensive and sometimes not available in the practice. In this paper, the authors propose an unsupervised MT evaluation metric using universal part-of-speech tagset without relying on reference translations. The authors also explore the performances of the designed metric on traditional supervised evaluation tasks. Both the supervised and unsupervised experiments show that the designed methods yield higher correlation scores with human judgments.

Computer Aided Process Planning of Machined Metal Parts

DTIC Science & Technology

1984-09-01

the manufac- turer to accentuate the positive to assist marketing . Machine usage costs and facility loadings are frequently critical. For example...Variant systems currently on the market include Multiplan (TM of OIR, Inc.), CY-Miplan (TM of Computervision), PICAPP (TM of PICAPP, Inc.) and CSD...Multiproduct, Multistage Manufacturing Systems, Journal of Engineering for Industry, ASME, August 1977. Hitomi, K. and I. Ham, Product Mix and Machine Loading

Towards Web 3.0: taxonomies and ontologies for medical education -- a systematic review.

PubMed

Blaum, Wolf E; Jarczweski, Anne; Balzer, Felix; Stötzner, Philip; Ahlers, Olaf

2013-01-01

Both for curricular development and mapping, as well as for orientation within the mounting supply of learning resources in medical education, the Semantic Web ("Web 3.0") poses a low-threshold, effective tool that enables identification of content related items across system boundaries. Replacement of the currently required manual with an automatically generated link, which is based on content and semantics, requires the use of a suitably structured vocabulary for a machine-readable description of object content. Aim of this study is to compile the existing taxonomies and ontologies used for the annotation of medical content and learning resources, to compare those using selected criteria, and to verify their suitability in the context described above. Based on a systematic literature search, existing taxonomies and ontologies for the description of medical learning resources were identified. Through web searches and/or direct contact with the respective editors, each of the structured vocabularies thus identified were examined in regards to topic, structure, language, scope, maintenance, and technology of the taxonomy/ontology. In addition, suitability for use in the Semantic Web was verified. Among 20 identified publications, 14 structured vocabularies were identified, which differed rather strongly in regards to language, scope, currency, and maintenance. None of the identified vocabularies fulfilled the necessary criteria for content description of medical curricula and learning resources in the German-speaking world. While moving towards Web 3.0, a significant problem lies in the selection and use of an appropriate German vocabulary for the machine-readable description of object content. Possible solutions include development, translation and/or combination of existing vocabularies, possibly including partial translations of English vocabularies.

Simulated Students and Classroom Use of Model-Based Intelligent Tutoring

NASA Technical Reports Server (NTRS)

Koedinger, Kenneth R.

2008-01-01

Two educational uses of models and simulations: 1) Students create models and use simulations ; and 2) Researchers create models of learners to guide development of reliably effective materials. Cognitive tutors simulate and support tutoring - data is crucial to create effective model. Pittsburgh Science of Learning Center: Resources for modeling, authoring, experimentation. Repository of data and theory. Examples of advanced modeling efforts: SimStudent learns rule-based model. Help-seeking model: Tutors metacognition. Scooter uses machine learning detectors of student engagement.

Use-related risk analysis for medical devices based on improved FMEA.

PubMed

Liu, Long; Shuai, Ma; Wang, Zhu; Li, Ping

2012-01-01

In order to effectively analyze and control use-related risk of medical devices, quantitative methodologies must be applied. Failure Mode and Effects Analysis (FMEA) is a proactive technique for error detection and risk reduction. In this article, an improved FMEA based on Fuzzy Mathematics and Grey Relational Theory is developed to better carry out user-related risk analysis for medical devices. As an example, the analysis process using this improved FMEA method for a certain medical device (C-arm X-ray machine) is described.

Walking robot: A design project for undergraduate students

NASA Technical Reports Server (NTRS)

1990-01-01

The design and construction of the University of Maryland walking machine was completed during the 1989 to 1990 academic year. It was required that the machine be capable of completing a number of tasks including walking a straight line, turning to change direction, and manuevering over an obstacle such as a set of stairs. The machine consists of two sets of four telescoping legs that alternately support the entire structure. A gear box and crank arm assembly is connected to the leg sets to provide the power required for the translational motion of the machine. By retracting all eight legs, the robot comes to rest on a central Bigfoot support. Turning is accomplished by rotating this machine about this support. The machine can be controlled by using either a user-operated remote tether or the onboard computer for the execution of control commands. Absolute encoders are attached to all motors to provide the control computer with information regarding the status of the motors. Long and short range infrared sensors provide the computer with feedback information regarding the machine's position relative to a series of stripes and reflectors. These infrared sensors simulate how the robot might sense and gain information about the environment of Mars.

Logic Learning Machine creates explicit and stable rules stratifying neuroblastoma patients

PubMed Central

2013-01-01

Background Neuroblastoma is the most common pediatric solid tumor. About fifty percent of high risk patients die despite treatment making the exploration of new and more effective strategies for improving stratification mandatory. Hypoxia is a condition of low oxygen tension occurring in poorly vascularized areas of the tumor associated with poor prognosis. We had previously defined a robust gene expression signature measuring the hypoxic component of neuroblastoma tumors (NB-hypo) which is a molecular risk factor. We wanted to develop a prognostic classifier of neuroblastoma patients' outcome blending existing knowledge on clinical and molecular risk factors with the prognostic NB-hypo signature. Furthermore, we were interested in classifiers outputting explicit rules that could be easily translated into the clinical setting. Results Shadow Clustering (SC) technique, which leads to final models called Logic Learning Machine (LLM), exhibits a good accuracy and promises to fulfill the aims of the work. We utilized this algorithm to classify NB-patients on the bases of the following risk factors: Age at diagnosis, INSS stage, MYCN amplification and NB-hypo. The algorithm generated explicit classification rules in good agreement with existing clinical knowledge. Through an iterative procedure we identified and removed from the dataset those examples which caused instability in the rules. This workflow generated a stable classifier very accurate in predicting good and poor outcome patients. The good performance of the classifier was validated in an independent dataset. NB-hypo was an important component of the rules with a strength similar to that of tumor staging. Conclusions The novelty of our work is to identify stability, explicit rules and blending of molecular and clinical risk factors as the key features to generate classification rules for NB patients to be conveyed to the clinic and to be used to design new therapies. We derived, through LLM, a set of four stable rules identifying a new class of poor outcome patients that could benefit from new therapies potentially targeting tumor hypoxia or its consequences. PMID:23815266

Logic Learning Machine creates explicit and stable rules stratifying neuroblastoma patients.

PubMed

Cangelosi, Davide; Blengio, Fabiola; Versteeg, Rogier; Eggert, Angelika; Garaventa, Alberto; Gambini, Claudio; Conte, Massimo; Eva, Alessandra; Muselli, Marco; Varesio, Luigi

2013-01-01

Neuroblastoma is the most common pediatric solid tumor. About fifty percent of high risk patients die despite treatment making the exploration of new and more effective strategies for improving stratification mandatory. Hypoxia is a condition of low oxygen tension occurring in poorly vascularized areas of the tumor associated with poor prognosis. We had previously defined a robust gene expression signature measuring the hypoxic component of neuroblastoma tumors (NB-hypo) which is a molecular risk factor. We wanted to develop a prognostic classifier of neuroblastoma patients' outcome blending existing knowledge on clinical and molecular risk factors with the prognostic NB-hypo signature. Furthermore, we were interested in classifiers outputting explicit rules that could be easily translated into the clinical setting. Shadow Clustering (SC) technique, which leads to final models called Logic Learning Machine (LLM), exhibits a good accuracy and promises to fulfill the aims of the work. We utilized this algorithm to classify NB-patients on the bases of the following risk factors: Age at diagnosis, INSS stage, MYCN amplification and NB-hypo. The algorithm generated explicit classification rules in good agreement with existing clinical knowledge. Through an iterative procedure we identified and removed from the dataset those examples which caused instability in the rules. This workflow generated a stable classifier very accurate in predicting good and poor outcome patients. The good performance of the classifier was validated in an independent dataset. NB-hypo was an important component of the rules with a strength similar to that of tumor staging. The novelty of our work is to identify stability, explicit rules and blending of molecular and clinical risk factors as the key features to generate classification rules for NB patients to be conveyed to the clinic and to be used to design new therapies. We derived, through LLM, a set of four stable rules identifying a new class of poor outcome patients that could benefit from new therapies potentially targeting tumor hypoxia or its consequences.

RPLP1 and RPLP2 Are Essential Flavivirus Host Factors That Promote Early Viral Protein Accumulation

PubMed Central

Campos, Rafael K.; Wong, Benjamin; Lu, Yi-Fan; Shi, Pei-Yong; Pompon, Julien

2016-01-01

ABSTRACT The Flavivirus genus contains several arthropod-borne viruses that pose global health threats, including dengue viruses (DENV), yellow fever virus (YFV), and Zika virus (ZIKV). In order to understand how these viruses replicate in human cells, we previously conducted genome-scale RNA interference screens to identify candidate host factors. In these screens, we identified ribosomal proteins RPLP1 and RPLP2 (RPLP1/2) to be among the most crucial putative host factors required for DENV and YFV infection. RPLP1/2 are phosphoproteins that bind the ribosome through interaction with another ribosomal protein, RPLP0, to form a structure termed the ribosomal stalk. RPLP1/2 were validated as essential host factors for DENV, YFV, and ZIKV infection in two human cell lines: A549 lung adenocarcinoma and HuH-7 hepatoma cells, and for productive DENV infection of Aedes aegypti mosquitoes. Depletion of RPLP1/2 caused moderate cell-line-specific effects on global protein synthesis, as determined by metabolic labeling. In A549 cells, global translation was increased, while in HuH-7 cells it was reduced, albeit both of these effects were modest. In contrast, RPLP1/2 knockdown strongly reduced early DENV protein accumulation, suggesting a requirement for RPLP1/2 in viral translation. Furthermore, knockdown of RPLP1/2 reduced levels of DENV structural proteins expressed from an exogenous transgene. We postulate that these ribosomal proteins are required for efficient translation elongation through the viral open reading frame. In summary, this work identifies RPLP1/2 as critical flaviviral host factors required for translation. IMPORTANCE Flaviviruses cause important diseases in humans. Examples of mosquito-transmitted flaviviruses include dengue, yellow fever and Zika viruses. Viruses require a plethora of cellular factors to infect cells, and the ribosome plays an essential role in all viral infections. The ribosome is a complex macromolecular machine composed of RNA and proteins and it is responsible for protein synthesis. We identified two specific ribosomal proteins that are strictly required for flavivirus infection of human cells and mosquitoes: RPLP1 and RPLP2 (RPLP1/2). These proteins are part of a structure known as the ribosomal stalk and help orchestrate the elongation phase of translation. We show that flaviviruses are particularly dependent on the function of RPLP1/2. Our findings suggest that ribosome composition is an important factor for virus translation and may represent a regulatory layer for translation of specific cellular mRNAs. PMID:27974556

Defense Logistics: Space-Available Travel Challenges May Be Exacerbated If Eligibility Expands

DTIC Science & Technology

2012-09-10

space-available travelers’ use of terminal facilities results in additional maintenance costs for waiting areas, restrooms, and vending machines ...additional required maintenance. For example, additional travelers’ use of waiting areas, restrooms, and vending machines in the terminals could require

Mechanically Compliant Electronic Materials for Wearable Photovoltaics and Human-Machine Interfaces

NASA Astrophysics Data System (ADS)

O'Connor, Timothy Francis, III

Applications of stretchable electronic materials for human-machine interfaces are described herein. Intrinsically stretchable organic conjugated polymers and stretchable electronic composites were used to develop stretchable organic photovoltaics (OPVs), mechanically robust wearable OPVs, and human-machine interfaces for gesture recognition, American Sign Language Translation, haptic control of robots, and touch emulation for virtual reality, augmented reality, and the transmission of touch. The stretchable and wearable OPVs comprise active layers of poly-3-alkylthiophene:phenyl-C61-butyric acid methyl ester (P3AT:PCBM) and transparent conductive electrodes of poly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate) (PEDOT:PSS) and devices could only be fabricated through a deep understanding of the connection between molecular structure and the co-engineering of electronic performance with mechanical resilience. The talk concludes with the use of composite piezoresistive sensors two smart glove prototypes. The first integrates stretchable strain sensors comprising a carbon-elastomer composite, a wearable microcontroller, low energy Bluetooth, and a 6-axis accelerometer/gyroscope to construct a fully functional gesture recognition glove capable of wirelessly translating American Sign Language to text on a cell phone screen. The second creates a system for the haptic control of a 3D printed robot arm, as well as the transmission of touch and temperature information.

Free-form machining for micro-imaging systems

NASA Astrophysics Data System (ADS)

Barkman, Michael L.; Dutterer, Brian S.; Davies, Matthew A.; Suleski, Thomas J.

2008-02-01

While mechanical ruling and single point diamond turning has been a mainstay of optical fabrication for many years, many types of micro-optical devices and structures are not conducive to simple diamond turning or ruling, such as, for example, microlens arrays, and optical surfaces with non-radial symmetry. More recent developments in machining technology have enabled significant expansion of fabrication capabilities. Modern machine tools can generate complex three-dimensional structures with optical quality surface finish, and fabricate structures across a dynamic range of dimensions not achievable with lithographic techniques. In particular, five-axis free-form micromachining offers a great deal of promise for realization of essentially arbitrary surface structures, including surfaces not realizable through binary or analog lithographic techniques. Furthermore, these machines can generate geometric features with optical finish on scales ranging from centimeters to micrometers with accuracies of 10s of nanometers. In this paper, we discuss techniques and applications of free-form surface machining of micro-optical elements. Aspects of diamond machine tool design to realize desired surface geometries in specific materials are discussed. Examples are presented, including fabrication of aspheric lens arrays in germanium for compact infrared imaging systems. Using special custom kinematic mounting equipment and the additional axes of the machine, the lenses were turned with surface finish better than 2 nm RMS and center to center positioning accuracy of +/-0.5 μm.

Frequency Response Function Expansion for Unmeasured Translation and Rotation Dofs for Impedance Modelling Applications

NASA Astrophysics Data System (ADS)

Avitabile, P.; O'Callahan, J.

2003-07-01

Inclusion of rotational effects is critical for the accuracy of the predicted system characteristics, in almost all system modelling studies. However, experimentally derived information for the description of one or more of the components for the system will generally not have any rotational effects included in the description of the component. The lack of rotational effects has long affected the results from any system model development whether using a modal-based approach or an impedance-based approach. Several new expansion processes are described herein for the development of FRFs needed for impedance-based system models. These techniques expand experimentally derived mode shapes, residual modes from the modal parameter estimation process and FRFs directly to allow for the inclusion of the necessary rotational dof. The FRFs involving translational to rotational dofs are developed as well as the rotational to rotational dof. Examples are provided to show the use of these techniques.

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

PubMed Central

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

Design and validation of a real-time spiking-neural-network decoder for brain-machine interfaces.

PubMed

Dethier, Julie; Nuyujukian, Paul; Ryu, Stephen I; Shenoy, Krishna V; Boahen, Kwabena

2013-06-01

Cortically-controlled motor prostheses aim to restore functions lost to neurological disease and injury. Several proof of concept demonstrations have shown encouraging results, but barriers to clinical translation still remain. In particular, intracortical prostheses must satisfy stringent power dissipation constraints so as not to damage cortex. One possible solution is to use ultra-low power neuromorphic chips to decode neural signals for these intracortical implants. The first step is to explore in simulation the feasibility of translating decoding algorithms for brain-machine interface (BMI) applications into spiking neural networks (SNNs). Here we demonstrate the validity of the approach by implementing an existing Kalman-filter-based decoder in a simulated SNN using the Neural Engineering Framework (NEF), a general method for mapping control algorithms onto SNNs. To measure this system's robustness and generalization, we tested it online in closed-loop BMI experiments with two rhesus monkeys. Across both monkeys, a Kalman filter implemented using a 2000-neuron SNN has comparable performance to that of a Kalman filter implemented using standard floating point techniques. These results demonstrate the tractability of SNN implementations of statistical signal processing algorithms on different monkeys and for several tasks, suggesting that a SNN decoder, implemented on a neuromorphic chip, may be a feasible computational platform for low-power fully-implanted prostheses. The validation of this closed-loop decoder system and the demonstration of its robustness and generalization hold promise for SNN implementations on an ultra-low power neuromorphic chip using the NEF.

Lysine acetylation sites prediction using an ensemble of support vector machine classifiers.

PubMed

Xu, Yan; Wang, Xiao-Bo; Ding, Jun; Wu, Ling-Yun; Deng, Nai-Yang

2010-05-07

Lysine acetylation is an essentially reversible and high regulated post-translational modification which regulates diverse protein properties. Experimental identification of acetylation sites is laborious and expensive. Hence, there is significant interest in the development of computational methods for reliable prediction of acetylation sites from amino acid sequences. In this paper we use an ensemble of support vector machine classifiers to perform this work. The experimentally determined acetylation lysine sites are extracted from Swiss-Prot database and scientific literatures. Experiment results show that an ensemble of support vector machine classifiers outperforms single support vector machine classifier and other computational methods such as PAIL and LysAcet on the problem of predicting acetylation lysine sites. The resulting method has been implemented in EnsemblePail, a web server for lysine acetylation sites prediction available at http://www.aporc.org/EnsemblePail/. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

The Cancer Prevention and Control Research Network: An Interactive Systems Approach to Advancing Cancer Control Implementation Research and Practice

PubMed Central

Fernández, María E.; Melvin, Cathy L.; Leeman, Jennifer; Ribisl, Kurt M.; Allen, Jennifer D.; Kegler, Michelle C.; Bastani, Roshan; Ory, Marcia G.; Risendal, Betsy C.; Hannon, Peggy A.; Kreuter, Matthew W.; Hebert, James R.

2018-01-01

Background Although cancer research has advanced at a rapid pace, a gap remains between what is known about how to improve cancer prevention and control (CPC) and what is implemented as best practices within health care systems and communities. The Cancer Prevention and Control Research Network (CPCRN), with more than 10 years of dissemination and implementation research experience, aims to accelerate the uptake and use of evidence-based CPC interventions. Methods The collective work of the CPCRN has facilitated the analysis and categorization of research and implementation efforts according to the Interactive Systems Framework for Dissemination and Implementation (ISF), providing a useful heuristic for bridging the gap between prevention research and practice. The ISF authors have called for examples of its application as input to help refine the model. Results We provide examples of how the collaborative activities supported by the CPCRN, using community-engaged processes, accelerated the synthesis and translation of evidence, built both general and innovation-specific capacity, and worked with delivery systems to advance cancer control research and practice. Conclusions The work of the CPCRN has provided real-world examples of the application of the ISF and demonstrated that synthesizing and translating evidence can increase the potential that evidence-based CPC programs will be used and that capacity building for both the support system and the delivery system is crucial for the successful implementation and maintenance of evidence-based cancer control. Impact Adoption and implementation of CPC can be enhanced by better understanding ISF systems and intervening to improve them. PMID:25155759